From a07d342e3f5cfb3c4a0b51c07c1237f278573871 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Fri, 18 Sep 2026 12:31:30 -0700
Subject: [PATCH 01/28] fix(baseflow): quiet the test run and draw the version
 it reports

A desktop test run printed a graphics array for every reference-line
label, warned twice about expected conditions, and opened and closed a
window for each test.

drawarrow assigned its output whether or not the caller asked for it,
and none of the five call sites in gpfitb, plplotb and fitphidist ended
with a semicolon, so each label printed its handles.

The fitphi warnings carried no identifier, so nothing could suppress
them. They now carry baseflow:fitphi:incompatibleLateTimeSolution and
baseflow:fitphi:lateTimeSolutionImpliesB, and the tests that ask for the
solution pair fitphi falls back from, or that run a fit to the iteration
limit of nlinfit, suppress the warning they expect. A user still sees it.

runtests draws test figures off screen for the length of the run and
puts the figure default back on both exits. A figure created with an
explicit 'Visible' of 'on' ignores that default, so fitphidist takes its
visibility from the new private figurevisibility, which answers off
whenever the root asks for invisible figures.

The version banner carried the digits of 1.1.0. It now takes them from
the version string, so the art cannot fall behind again.

test_pointcloudplot asserted a figure position it had asked for rather
than the one the window manager granted, so the supplied-axes test
failed on a display. It reads the position back, the sibling position
tests assert only the size, and the new test_sizefigure covers the kept
position on the private helper itself.
---
 CHANGELOG.md                                  |  25 +++++
 docs/index.html                               |   2 +-
 tests/Contents.m                              |   2 +
 tests/test_corechain.m                        |   5 +
 tests/test_demos.m                            |   8 ++
 tests/test_figurevisibility.m                 |  91 +++++++++++++++++
 tests/test_getdqdt.m                          |   8 ++
 tests/test_plotdqdt.m                         |  14 +--
 tests/test_pointcloudplot.m                   |  23 +++--
 tests/test_sizefigure.m                       |  84 ++++++++++++++++
 toolbox/+baseflow/+deps/Contents.m            |   2 +-
 toolbox/+baseflow/+internal/Contents.m        |   2 +-
 toolbox/+baseflow/+internal/runtests.m        |  95 ++++++++++++------
 toolbox/+baseflow/+internal/version.m         |  20 +++-
 toolbox/+baseflow/+util/Contents.m            |   2 +-
 toolbox/+baseflow/Contents.m                  |   3 +-
 toolbox/+baseflow/fitphi.m                    |  12 +--
 toolbox/+baseflow/fitphidist.m                |   6 +-
 toolbox/+baseflow/gpfitb.m                    |   4 +-
 toolbox/+baseflow/plplotb.m                   |   4 +-
 toolbox/+baseflow/private/drawarrow.m         |  14 ++-
 toolbox/+baseflow/private/figurevisibility.m  |  48 +++++++++
 toolbox/docs/html/baseflow_contents.html      |   2 +-
 .../docs/html/baseflow_examples_contents.html |   2 +-
 .../docs/html/baseflow_gettingStarted.html    |   2 +-
 .../docs/html/baseflow_powerlaw_notation.html |   2 +-
 .../docs/html/baseflow_theory_contents.html   |   2 +-
 toolbox/docs/html/baseflow_welcome.html       |   2 +-
 .../helpsearch-v4_en/store/000000000002.zap   | Bin 1228772 -> 1228393 bytes
 .../html/helpsearch-v4_en/store/root.bolt     | Bin 262144 -> 262144 bytes
 .../docs/html/m2html/+baseflow/Contents.html  |   3 +-
 .../docs/html/m2html/+baseflow/fitphi.html    |  12 +--
 .../html/m2html/+baseflow/fitphidist.html     |   6 +-
 .../docs/html/m2html/+baseflow/gpfitb.html    |   4 +-
 .../docs/html/m2html/+baseflow/plplotb.html   |   4 +-
 toolbox/docs/html/m2html/function_index.html  |   2 +-
 36 files changed, 424 insertions(+), 93 deletions(-)
 create mode 100644 tests/test_figurevisibility.m
 create mode 100644 tests/test_sizefigure.m
 create mode 100644 toolbox/+baseflow/private/figurevisibility.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1b8396b..d6d25b6 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -4,6 +4,31 @@ This file lists notable changes to the baseflow toolbox. The format follows
 [Keep a Changelog](https://keepachangelog.com/en/1.1.0/); the project uses
 semantic versioning.
 
+## [Unreleased]
+
+### Fixed
+
+- `gpfitb`, `plplotb` and `fitphidist` print nothing when they label a
+  figure. The private `drawarrow` assigned its output whether or not the
+  caller asked for it, and no call site ended with a semicolon, so each
+  label printed a 1x2 graphics array.
+- `baseflow.internal.version` draws the version it reports. The banner
+  carried the digits of 1.1.0, and it now takes them from the version
+  string.
+- `baseflow.internal.runtests` draws test figures off screen, so a run on
+  the desktop opens no window for a test that closes its own figure. It
+  puts the figure default back on both exits.
+- `fitphidist` draws its figure off screen when the root asks for
+  invisible figures, through the new private `figurevisibility`. A figure
+  created with an explicit `'Visible'` of `'on'` ignores that default, so
+  `showfit` true opened a window during a test run.
+- The `fitphi` warnings carry identifiers,
+  `baseflow:fitphi:incompatibleLateTimeSolution` and
+  `baseflow:fitphi:lateTimeSolutionImpliesB`, so a caller can suppress or
+  catch one by name. The tests that ask for a solution pair `fitphi`
+  falls back from now suppress the warning they expect, as do the tests
+  that run a fit to the iteration limit of `nlinfit`.
+
 ## [1.2.0] - 2026-09-17
 
 ### Added
diff --git a/docs/index.html b/docs/index.html
index 25d1df0..c994284 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -9,7 +9,7 @@
 <title>Getting Started with the Baseflow Toolbox</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_gettingStarted.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/tests/Contents.m b/tests/Contents.m
index 34c530e..a0c3fce 100644
--- a/tests/Contents.m
+++ b/tests/Contents.m
@@ -21,6 +21,7 @@
 %   test_eqstrings         - Test the equation label helpers
 %   test_fillnans          - Test the private fillnans helper
 %   test_fitcts            - Test the constant-time-step dq/dt method
+%   test_figurevisibility  - Test the visibility of a figure asked to show
 %   test_fitevents         - Test the fitevents plotfits option
 %   test_fitopts           - Test the fitab fitopts pass-through
 %   test_getdqdt           - Test the getdqdt fit-plot option
@@ -46,6 +47,7 @@
 %   test_setlogticks       - Test the private setlogticks decade ticks
 %   test_setrainnan        - Test the private setrainnan helper
 %   test_siUnitsToTex      - Test the private siUnitsToTex unit label helper
+%   test_sizefigure        - Test the size of a point-cloud figure
 %   test_smoothnoise       - Test the private smoothnoise helper
 %   test_snaploglims       - Test the private snaploglims limit policy
 %   test_todatenum         - Test baseflow/private/todatenum
diff --git a/tests/test_corechain.m b/tests/test_corechain.m
index e186375..a9ebca8 100644
--- a/tests/test_corechain.m
+++ b/tests/test_corechain.m
@@ -374,6 +374,11 @@ function test_fitphiUnsupportedPairErrors(testCase)
    % b2 = 1 with the default RS05 solutions remaps to a pair with no
    % derived formula; the guard raises the documented error instead of
    % returning unassigned outputs.
+   % fitphi warns before it falls back, and this test asks for the pair
+   % that triggers the fallback, so the warning is expected output rather
+   % than a problem to print.
+   testCase.applyFixture(matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+      'baseflow:fitphi:incompatibleLateTimeSolution'));
    a1 = testCase.TestData.a1;
    a2 = testCase.TestData.a2;
    b2_linear = testCase.TestData.b2_linear;
diff --git a/tests/test_demos.m b/tests/test_demos.m
index ad90bb8..2681d47 100644
--- a/tests/test_demos.m
+++ b/tests/test_demos.m
@@ -75,6 +75,14 @@ function hidefigures(testCase)
          testCase.figsbefore = figs;
          testCase.visibility = get(figs, {'HandleVisibility'});
          set(figs, 'HandleVisibility', 'off')
+
+         % A nonlinear fit that stops at the iteration limit warns. Several
+         % demos reach that limit on the example record, so the warning is
+         % expected output here rather than a problem to print. A user
+         % running the demo still sees it.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            'stats:nlinfit:IterationLimitExceeded'));
       end
    end
 
diff --git a/tests/test_figurevisibility.m b/tests/test_figurevisibility.m
new file mode 100644
index 0000000..f37af4c
--- /dev/null
+++ b/tests/test_figurevisibility.m
@@ -0,0 +1,91 @@
+classdef test_figurevisibility < matlab.unittest.TestCase
+   %TEST_FIGUREVISIBILITY Test the visibility of a figure asked to show.
+   %
+   % figurevisibility is private, so the tests reach it with
+   % baseflow.privatefunction. A figure created with an explicit 'Visible'
+   % of 'on' ignores the root default, so a function that takes a show
+   % option asks this helper what to draw. baseflow.internal.runtests sets
+   % that default to off for the length of a test run, and the helper then
+   % answers 'off' whatever the caller asked for.
+
+   properties (TestParameter)
+      % Each case holds the request and the answer with no root default.
+      request = struct('show', {{true, 'on'}}, 'hide', {{false, 'off'}})
+   end
+
+   properties
+      % Handle to the private function under test.
+      figurevisibility
+   end
+
+   methods (TestClassSetup)
+      function gethandle(testCase)
+         % Store the private function handle once for every test.
+         testCase.figurevisibility = ...
+            baseflow.privatefunction('figurevisibility');
+      end
+   end
+
+   methods (Test)
+      function test_answersTheRequestWithNoRootDefault(testCase, request)
+         % With no default set, the caller's request stands.
+         [show, visibility_expected] = request{:};
+         testCase.setrootdefault('remove');
+
+         returned = testCase.figurevisibility(show);
+
+         testCase.verifyEqual(returned, visibility_expected)
+      end
+
+      function test_answersTheRequestWhenTheRootAsksForVisible(testCase)
+         % A root default of 'on' leaves the request alone, so a caller
+         % that asked to hide a figure still hides it.
+         visibility_expected = 'off';
+         testCase.setrootdefault('on');
+
+         returned = testCase.figurevisibility(false);
+
+         testCase.verifyEqual(returned, visibility_expected)
+      end
+
+      function test_rootDefaultOffOverridesTheRequest(testCase)
+         % This is the test-run case: the figure is drawn, and no window
+         % opens, whatever the caller asked for.
+         visibility_expected = 'off';
+         testCase.setrootdefault('off');
+
+         returned = testCase.figurevisibility(true);
+
+         testCase.verifyEqual(returned, visibility_expected)
+      end
+
+      function test_theFigureItAnswersForOpensNoWindow(testCase)
+         % The answer reaches a real figure, which is what the callers do.
+         visibility_expected = 'off';
+         testCase.setrootdefault('off');
+
+         fig = figure('Visible', testCase.figurevisibility(true));
+         testCase.addTeardown(@close, fig)
+
+         testCase.verifyEqual(char(get(fig, 'Visible')), visibility_expected)
+      end
+   end
+
+   methods (Access = private)
+      function setrootdefault(testCase, visibility)
+         % Set the root figure default for one test, and put back what the
+         % session had. 'remove' clears the default, which is the state of
+         % a session that set none, and reading a default the root never
+         % set errors, so ask which defaults exist first.
+         defaults = get(groot, 'default');
+         if isfield(defaults, 'defaultFigureVisible')
+            previous = get(groot, 'defaultFigureVisible');
+         else
+            previous = 'remove';
+         end
+         testCase.addTeardown( ...
+            @() set(groot, 'defaultFigureVisible', previous))
+         set(groot, 'defaultFigureVisible', visibility);
+      end
+   end
+end
diff --git a/tests/test_getdqdt.m b/tests/test_getdqdt.m
index 04c4ff6..3cd0596 100644
--- a/tests/test_getdqdt.m
+++ b/tests/test_getdqdt.m
@@ -39,6 +39,14 @@ function snapshotfigures(testCase)
          % Close the figures each case opens.
          testCase.figsbefore = findall(0, 'Type', 'figure');
          testCase.addTeardown(@() closenewfigs(testCase.figsbefore));
+
+         % A nonlinear fit that stops at the iteration limit warns. The
+         % fit plots reach that limit on the example record, so the
+         % warning is expected output here rather than a problem to print.
+         % A user still sees it.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            'stats:nlinfit:IterationLimitExceeded'));
       end
    end
 
diff --git a/tests/test_plotdqdt.m b/tests/test_plotdqdt.m
index 4e6c607..1811eb3 100644
--- a/tests/test_plotdqdt.m
+++ b/tests/test_plotdqdt.m
@@ -276,22 +276,22 @@ function test_rainJoinsTheLegend(testCase)
          testCase.verifyTrue(any(strcmp(h.leg.String, 'rain')))
       end
 
-      function test_theFigureKeepsThePositionItWasGiven(testCase)
-         % A figure pinned to [1 1] opens in the bottom-left corner of the
+      function test_theFigureTakesTheSharedSize(testCase)
+         % The figure was pinned to [1 1], the bottom-left corner of the
          % screen, where the dock covers the axis labels. Only the size
          % belongs to this function, and pointcloudplot sizes its figure
-         % through the same private helper.
+         % through the same private helper. Its own suite,
+         % tests/test_sizefigure.m, covers the position that is kept: a
+         % window manager may move any figure to fit the screen, so a
+         % position read here says nothing.
+         sizefigure = baseflow.privatefunction('sizefigure');
          reference = figure('Visible', 'off');
          testCase.addTeardown(@close, reference)
-         position_expected = get(reference, 'Position');
-         sizefigure = baseflow.privatefunction('sizefigure');
          size_expected = get(sizefigure(reference), 'Position');
 
          h = baseflow.plotdqdt(testCase.q, testCase.dqdt);
 
          position_returned = get(ancestor(h.ax, 'figure'), 'Position');
-         testCase.verifyEqual(position_returned(1:2), ...
-            position_expected(1:2))
          testCase.verifyEqual(position_returned(3:4), size_expected(3:4))
       end
 
diff --git a/tests/test_pointcloudplot.m b/tests/test_pointcloudplot.m
index 22839db..82cee7e 100644
--- a/tests/test_pointcloudplot.m
+++ b/tests/test_pointcloudplot.m
@@ -139,11 +139,13 @@ function test_envelopeInterceptFollowsTimestep(testCase, timestep)
 
       function test_suppliedAxesKeepsTheFigureAndItsSibling(testCase)
          % A caller that supplies an axes owns the figure, so the figure
-         % keeps its size and the other panel keeps its own children.
-         position_expected = [1 1 1200 900];
+         % keeps its size and the other panel keeps its own children. Read
+         % the position back rather than asserting the one asked for: a
+         % window manager moves and resizes a figure to fit the screen.
          nlines_expected = 1;
-         fig = figure('Visible', 'off', 'Position', position_expected);
+         fig = figure('Visible', 'off', 'Position', [1 1 1200 900]);
          testCase.addTeardown(@close, fig)
+         position_expected = get(fig, 'Position');
          target = subplot(1, 2, 1, 'Parent', fig);
          other = subplot(1, 2, 2, 'Parent', fig);
          plot(other, 1:10, 1:10);
@@ -212,19 +214,22 @@ function test_fontSizeOptionsReachTheAxesAndTheLegend(testCase)
             legendfontsize_expected)
       end
 
-      function test_theFigureKeepsThePositionItWasGiven(testCase)
-         % A figure pinned to [0 0] opens in the bottom-left corner of the
+      function test_theFigureTakesTheSharedSize(testCase)
+         % The figure was pinned to [0 0], the bottom-left corner of the
          % screen, where the dock covers the axis labels. Only the size
-         % belongs to this function.
+         % belongs to this function, and sizefigure sets it. Its own suite,
+         % tests/test_sizefigure.m, covers the position that is kept: a
+         % window manager may move any figure to fit the screen, so a
+         % position read here says nothing.
+         sizefigure = baseflow.privatefunction('sizefigure');
          reference = figure('Visible', 'off');
          testCase.addTeardown(@close, reference)
-         position_expected = get(reference, 'Position');
+         size_expected = get(sizefigure(reference), 'Position');
 
          out = testCase.drawcloud();
 
          position_returned = get(ancestor(out.ax, 'figure'), 'Position');
-         testCase.verifyEqual(position_returned(1:2), ...
-            position_expected(1:2))
+         testCase.verifyEqual(position_returned(3:4), size_expected(3:4))
       end
 
       function test_rainJoinsTheLegend(testCase, rainreflines)
diff --git a/tests/test_sizefigure.m b/tests/test_sizefigure.m
new file mode 100644
index 0000000..4bd2c17
--- /dev/null
+++ b/tests/test_sizefigure.m
@@ -0,0 +1,84 @@
+classdef test_sizefigure < matlab.unittest.TestCase
+   %TEST_SIZEFIGURE Test the size of a point-cloud figure.
+   %
+   % sizefigure is private, so the tests reach it with
+   % baseflow.privatefunction. pointcloudplot and plotdqdt both draw a
+   % log-log point cloud, so both take the size of the figure from here.
+   % The position belongs to whatever opened the figure: pinning it to the
+   % bottom-left corner of the screen puts the axis labels under the dock.
+
+   properties (Constant)
+      % The size the helper sets, in points.
+      size_expected = [640 600]
+   end
+
+   properties
+      % Handle to the private function under test.
+      sizefigure
+      % Open-figure snapshot taken before each test.
+      figsbefore
+   end
+
+   methods (TestClassSetup)
+      function gethandle(testCase)
+         % Store the private function handle once for every test.
+         testCase.sizefigure = baseflow.privatefunction('sizefigure');
+      end
+   end
+
+   methods (TestMethodSetup)
+      function snapshotfigures(testCase)
+         % Record the figures that exist before the test runs.
+         testCase.figsbefore = findall(0, 'Type', 'figure');
+      end
+   end
+
+   methods (TestMethodTeardown)
+      function closetestfigures(testCase)
+         % Close figures created during the test (see tests/closenewfigs.m).
+         closenewfigs(testCase.figsbefore)
+      end
+   end
+
+   methods (Test)
+      function test_keepsThePositionItWasGiven(testCase)
+         % Read the position back before and after the call, on the same
+         % figure, so the check holds whatever position the figure was
+         % given.
+         fig = testCase.invisiblefigure();
+         position_before = get(fig, 'Position');
+
+         testCase.sizefigure(fig);
+
+         position_returned = get(fig, 'Position');
+         testCase.verifyEqual(position_returned(1:2), position_before(1:2))
+      end
+
+      function test_setsTheSharedSize(testCase)
+         % Both point-cloud figures take this size, so the axis labels fit.
+         fig = testCase.invisiblefigure();
+
+         testCase.sizefigure(fig);
+
+         position_returned = get(fig, 'Position');
+         testCase.verifyEqual(position_returned(3:4), testCase.size_expected)
+      end
+
+      function test_returnsTheFigureItSized(testCase)
+         % The caller chains the call, as plotdqdt does.
+         fig = testCase.invisiblefigure();
+
+         returned = testCase.sizefigure(fig);
+
+         testCase.verifyEqual(returned, fig)
+      end
+   end
+
+   methods (Access = private)
+      function fig = invisiblefigure(testCase)
+         % Open a figure the test closes, with a position of its own.
+         fig = figure('Visible', 'off', 'Position', [120 140 300 250]);
+         testCase.addTeardown(@close, fig)
+      end
+   end
+end
diff --git a/toolbox/+baseflow/+deps/Contents.m b/toolbox/+baseflow/+deps/Contents.m
index cbfd820..2da34fd 100644
--- a/toolbox/+baseflow/+deps/Contents.m
+++ b/toolbox/+baseflow/+deps/Contents.m
@@ -17,4 +17,4 @@
 %   baseflow.deps.tsregr      - Theil-Sen estimator
 %   baseflow.deps.zeta        - Riemann Zeta function
 %    
-%   This file was generated by updatecontents.m on 17 Sep 2026 at 11:51:09.
+%   This file was generated by updatecontents.m on 18 Sep 2026 at 12:28:36.
diff --git a/toolbox/+baseflow/+internal/Contents.m b/toolbox/+baseflow/+internal/Contents.m
index f491f13..9ede93b 100644
--- a/toolbox/+baseflow/+internal/Contents.m
+++ b/toolbox/+baseflow/+internal/Contents.m
@@ -34,4 +34,4 @@
 %   baseflow.internal/private.updatecontents     - Create a Contents.m file including subdirectories
 %   baseflow.internal/private.withcd             - Temporarily cd to a directory
 %    
-%   This file was generated by updatecontents.m on 17 Sep 2026 at 11:51:09.
+%   This file was generated by updatecontents.m on 18 Sep 2026 at 12:28:36.
diff --git a/toolbox/+baseflow/+internal/runtests.m b/toolbox/+baseflow/+internal/runtests.m
index ce8be83..9da8bee 100644
--- a/toolbox/+baseflow/+internal/runtests.m
+++ b/toolbox/+baseflow/+internal/runtests.m
@@ -13,49 +13,77 @@
    import matlab.unittest.plugins.DiagnosticsValidationPlugin
    import matlab.unittest.plugins.StopOnFailuresPlugin
 
-   % Create a test suite from the tests/ folder
-   suite = TestSuite.fromFolder(fullfile(projectpath(), 'tests'));
+   % Draw every test figure off screen. The tests close the figures they
+   % open, so on a desktop a window flashes open and shut for each one.
+   % Nothing in the suite reads the Visible property. Both exits below put
+   % the default back, so a run that errors leaves the caller's figures
+   % visible. A figure created with an explicit 'Visible' of 'on' ignores
+   % this default, so the functions that take a show option ask
+   % private/figurevisibility what to draw.
+   %
+   % This bookkeeping stays inline: a function here would be a function the
+   % suite this runner starts cannot reach, so it could carry no tests.
+   % 'remove' clears the default, which is what the root had when it had
+   % none.
+   defaults = get(groot, 'default');
+   if isfield(defaults, 'defaultFigureVisible')
+      previousvisibility = get(groot, 'defaultFigureVisible');
+   else
+      previousvisibility = 'remove';
+   end
+   set(groot, 'defaultFigureVisible', 'off');
 
-   if nargin < 1
-      % Run parameterized test suite
-      result = transpose(suite.run());
+   try
+      % Create a test suite from the tests/ folder
+      suite = TestSuite.fromFolder(fullfile(projectpath(), 'tests'));
 
-      % Print the results to the screen
-      for n = 1:numel(result)
-         if result(n).Passed == true
-            disp(['Passed Test ' int2str(n)])
-         else
-            disp(['Failed Test ' int2str(n)])
+      if nargin < 1
+         % Run parameterized test suite
+         result = transpose(suite.run());
+
+         % Print the results to the screen
+         for n = 1:numel(result)
+            if result(n).Passed == true
+               disp(['Passed Test ' int2str(n)])
+            else
+               disp(['Failed Test ' int2str(n)])
+            end
          end
-      end
-      % To examine failed tests
-      % ifailed = find(arrayfun(@(r) r.Failed, results));
+         % To examine failed tests
+         % ifailed = find(arrayfun(@(r) r.Failed, results));
 
-   else
-      % For verbose and/or debugging
-      validatestring(varargin{1}, {'debug'}, mfilename, 'option', 1)
+      else
+         % For verbose and/or debugging
+         validatestring(varargin{1}, {'debug'}, mfilename, 'option', 1)
 
-      % Create a test runner with detailed text output
-      runner = TestRunner.withTextOutput('Verbosity', Verbosity.Detailed);
+         % Create a test runner with detailed text output
+         runner = TestRunner.withTextOutput('Verbosity', Verbosity.Detailed);
 
-      % Create a plugin to validate diagnostics. This helps ensure that
-      % diagnostic messages are free of errors. The
-      % 'IncludingPassingDiagnostics' option means that the plugin checks
-      % diagnostics for passing tests as well as failing ones.
-      % 'ValidateUsingBaseWorkspace' means that the plugin validates that the
-      % diagnostic code can execute in the base workspace without errors.
-      %
-      % plugin = DiagnosticsValidationPlugin('IncludingPassingDiagnostics',true,...
-      %                                      'ValidateUsingBaseWorkspace',true);
-      % runner.addPlugin(plugin)
+         % Create a plugin to validate diagnostics. This helps ensure that
+         % diagnostic messages are free of errors. The
+         % 'IncludingPassingDiagnostics' option means that the plugin checks
+         % diagnostics for passing tests as well as failing ones.
+         % 'ValidateUsingBaseWorkspace' means that the plugin validates that the
+         % diagnostic code can execute in the base workspace without errors.
+         %
+         % plugin = DiagnosticsValidationPlugin('IncludingPassingDiagnostics',true,...
+         %                                      'ValidateUsingBaseWorkspace',true);
+         % runner.addPlugin(plugin)
 
-      % Add a plugin to stop execution and enter debug mode when a test fails
-      runner.addPlugin(StopOnFailuresPlugin)
+         % Add a plugin to stop execution and enter debug mode when a test fails
+         runner.addPlugin(StopOnFailuresPlugin)
 
-      % Run the test suite using the configured runner
-      result = runner.run(suite);
+         % Run the test suite using the configured runner
+         result = runner.run(suite);
+      end
+   catch err
+      set(groot, 'defaultFigureVisible', previousvisibility);
+      rethrow(err)
    end
 
+   % Put the figure default back now that the run is over.
+   set(groot, 'defaultFigureVisible', previousvisibility);
+
    % Use built-in runtests with debugging to run function tests:
    % result = runtests(<test_function>, 'Debug', true);
 
@@ -76,3 +104,4 @@
    % suite = TestSuite.fromClass(?ParameterizedTestBfra);
    % result = table(suite.run());
 end
+
diff --git a/toolbox/+baseflow/+internal/version.m b/toolbox/+baseflow/+internal/version.m
index 2045f55..6bd3778 100644
--- a/toolbox/+baseflow/+internal/version.m
+++ b/toolbox/+baseflow/+internal/version.m
@@ -19,14 +19,30 @@
    end
 
    if strcmp(option, 'verbose')
+      % The banner carries the version in two slots of two characters: the
+      % major number beside the v, and the minor and patch digits below it.
+      % Build them from v so the art cannot fall behind the version.
+      number = sscanf(v, '%d.%d.%d');
+      majorslot = fitslot(sprintf('v%d', number(1)));
+      minorslot = fitslot(sprintf('%d%d', number(2), number(3)));
+
       home
       disp(' _______                        ___  __                     ')
       disp('|   _   \.---.-..-----..-----..''  _||  |.-----..--.--.--.  ')
-      disp('|.  v1  /|  _  ||__ --||  -__||   _||  ||  _  ||  |  |  |   ')
+      disp(['|.  ' majorslot '  /|  _  ||__ --||  -__||   _||  ||  _  ||  |  |  |   '])
       disp('|.  _   \|___._||_____||_____||__|  |__||_____||________|   ')
-      disp('|:  10   \              ____        ______      ______      ')
+      disp(['|:  ' minorslot '   \              ____        ______      ______      '])
       disp('|::.. .  /   .--.--.   |_   |      |      |    |      |     ')
       disp('`-------''    |  |  |__  _|  |_  __ |  --  | __ |  --  |    ')
       disp('              \___/|__||______||__||______||__||______|     ')
    end
 end
+
+function slot = fitslot(txt)
+   %FITSLOT Fit text to the two characters a banner slot holds.
+   %
+   % A version part of two or more digits would push the art out of line,
+   % so pad a short part and cut a long one.
+   slot = sprintf('%-2s', txt);
+   slot = slot(1:2);
+end
diff --git a/toolbox/+baseflow/+util/Contents.m b/toolbox/+baseflow/+util/Contents.m
index 86be882..1e4a60c 100644
--- a/toolbox/+baseflow/+util/Contents.m
+++ b/toolbox/+baseflow/+util/Contents.m
@@ -7,4 +7,4 @@
 %   baseflow.util.numfits   - Count the number of fits in EventFits returned by baseflow.fitevents
 %   baseflow.util.numtau    - Count the number of tau values in struct returned by baseflow.fitevents
 %    
-%   This file was generated by updatecontents.m on 17 Sep 2026 at 11:51:09.
+%   This file was generated by updatecontents.m on 18 Sep 2026 at 12:28:36.
diff --git a/toolbox/+baseflow/Contents.m b/toolbox/+baseflow/Contents.m
index 2280159..b451eb2 100644
--- a/toolbox/+baseflow/Contents.m
+++ b/toolbox/+baseflow/Contents.m
@@ -132,6 +132,7 @@
 %   baseflow/private.dealout                     - Deal out function outputs
 %   baseflow/private.drawarrow                   - Draw an arrow in an axes, with the head on a given point
 %   baseflow/private.emptyaxes                   - Return empty axes object
+%   baseflow/private.figurevisibility            - Visibility of a figure a caller asked to show
 %   baseflow/private.fillnans                    - Fill interior sequences of nan values of length <= fmax
 %   baseflow/private.findevents                  - Returns flow Q and time T values of each individual recession event,
 %   baseflow/private.findmin                     - Returns the k indici(s) of the min value and the value at those
@@ -216,4 +217,4 @@
 %   baseflow/private.withwarnoff                 - Temporarily disable warnings
 %   baseflow/private.yorkfit                     - Fit a straight line when both x and y carry measurement errors
 %    
-%   This file was generated by updatecontents.m on 17 Sep 2026 at 11:51:09.
+%   This file was generated by updatecontents.m on 18 Sep 2026 at 12:28:36.
diff --git a/toolbox/+baseflow/fitphi.m b/toolbox/+baseflow/fitphi.m
index a5bc27e..4251e07 100644
--- a/toolbox/+baseflow/fitphi.m
+++ b/toolbox/+baseflow/fitphi.m
@@ -291,40 +291,40 @@
       % water table
       % if strcmp(soln2,'RS05') && (b2 < 3/2 || b2>=2)
       if strcmp(soln2,'RS05') && (b2 <= 1 || b2>=2)
-         warning( ...
+         warning('baseflow:fitphi:incompatibleLateTimeSolution', ...
             ['Requested late-time solution (Rupp and Selker, 2005) ' ...
             'is incompatible with b<1.5 or b>=2, using Boussinesq, 1903, b=1'])
          soln2 = 'BS03';
 
          % late-time B04 has b = 3/2
       elseif strcmp(soln2,'BS04') && (b2 ~= 3/2)
-         warning( ...
+         warning('baseflow:fitphi:lateTimeSolutionImpliesB', ...
             ['Requested late-time solution (Boussinesq, 1904) ' ...
             'implies b=3/2, using b=3/2'])
          b2 = 3/2;
 
          % late-time B03 has b = 1
       elseif strcmp(soln2,'BS03') && (b2 ~= 1)
-         warning( ...
+         warning('baseflow:fitphi:lateTimeSolutionImpliesB', ...
             ['Requested late-time solution (Boussinesq, 1903) ' ...
             'implies b=1, using b=1'])
          b2 = 1;
       end
    else
       if strcmp(soln1,'RS05') && (b2 < 3/2 || b2>=2)
-         warning( ...
+         warning('baseflow:fitphi:incompatibleLateTimeSolution', ...
             ['Requested late-time solution (Rupp and Selker, 2005) ' ...
             'is incompatible with b<1.5 or b>=2, using Boussinesq, 1903, b=1'])
          soln2 = 'BS03';
 
       elseif strcmp(soln2,'BS04') && (b2 ~= 3/2)
-         warning( ...
+         warning('baseflow:fitphi:lateTimeSolutionImpliesB', ...
             ['Requested late-time solution (Boussinesq, 1904) ' ...
             'implies b=3/2, using b=3/2'])
          b2 = 3/2;
 
       elseif strcmp(soln2,'BS03') && (b2 ~= 1)
-         warning( ...
+         warning('baseflow:fitphi:lateTimeSolutionImpliesB', ...
             ['Requested late-time solution (Boussinesq, 1903) ' ...
             'implies b=1, using b=1'])
          b2 = 1;
diff --git a/toolbox/+baseflow/fitphidist.m b/toolbox/+baseflow/fitphidist.m
index 6b6df6c..3eeda7d 100644
--- a/toolbox/+baseflow/fitphidist.m
+++ b/toolbox/+baseflow/fitphidist.m
@@ -82,7 +82,7 @@
    [cdfY, cdfX] = ecdf(phi, 'Function', 'cdf');
    
    % Create the figure
-   h.figure = figure('Visible', showfit);
+   h.figure = figure('Visible', figurevisibility(showfit));
    h.data = plot(cdfX, cdfY, 'o', 'MarkerFaceColor', [0 0.447 0.741], ...
       'MarkerEdgeColor', 'none', 'Visible', showfit); hold on;
 
@@ -124,7 +124,7 @@
       xarrow = [PD.mean 1.3*PD.mean];
       yarrow = [betacdf(PD.mean, PD.a, PD.b) betacdf(PD.mean, PD.a, PD.b)];
       % the head points left, at the mean, from a tail to its right
-      drawarrow(gca, [xarrow(2), yarrow(2)], [xarrow(1), yarrow(1)])
+      drawarrow(gca, [xarrow(2), yarrow(2)], [xarrow(1), yarrow(1)]);
       text(0.95*xarrow(2), yarrow(2), arrowtxt, 'HorizontalAlignment','left')
 
       h.legend = legend(ltxt, 'Location', 'east', 'Interpreter', 'tex');
@@ -152,7 +152,7 @@
    end
 
    % Create the figure. It is hidden when showfit is false.
-   h.figure = figure('Visible', showfit);
+   h.figure = figure('Visible', figurevisibility(showfit));
 
    % plot the data, suppressing the normal plot with 'noref'
    h.data = probplot('normal', phi, [], [], 'noref'); hold on;
diff --git a/toolbox/+baseflow/gpfitb.m b/toolbox/+baseflow/gpfitb.m
index 4e62a9e..cc18f9c 100644
--- a/toolbox/+baseflow/gpfitb.m
+++ b/toolbox/+baseflow/gpfitb.m
@@ -216,7 +216,7 @@ function addlabels(Fit,xmin,yref)
    ya = [ya ya];
    ta = sprintf('$\\hat{\\tau}_0=%.0f\\pm%.0f$ days',xmin,xminc);
 
-   drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)])
+   drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
    text(0.95*xa(1),ya(1),ta,'HorizontalAlignment','right')
 
    % use these to put the text on the right side of the curve
@@ -232,7 +232,7 @@ function addlabels(Fit,xmin,yref)
    ya = [ya ya];
    ta = sprintf('$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days',xexp,xexpc);
 
-   drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)])
+   drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
    text(0.95*xa(1),ya(1),ta,'HorizontalAlignment','right')
 end
 
diff --git a/toolbox/+baseflow/plplotb.m b/toolbox/+baseflow/plplotb.m
index 5b68458..f44ca59 100644
--- a/toolbox/+baseflow/plplotb.m
+++ b/toolbox/+baseflow/plplotb.m
@@ -165,7 +165,7 @@ function addlabels(xfit,yfit,tau0,tau0L,tau0H,b)
 
    % draw the arrow in the current axes, which is the axes the caller
    % plotted into, as the text call below uses
-   drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)])
+   drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
    text(0.95*xarrw(1),yarrw(1),ta, ...
       'HorizontalAlignment','right','FontSize',14,'Interpreter','latex')
 
@@ -192,7 +192,7 @@ function addlabels(xfit,yfit,tau0,tau0L,tau0H,b)
       ta = sprintf('$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days',xexp,xexpc);
    end
 
-   drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)])
+   drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
    text(0.95*xarrw(1),yarrw(1),ta, ...
       'HorizontalAlignment','right','FontSize',14,'Interpreter','latex')
 end
diff --git a/toolbox/+baseflow/private/drawarrow.m b/toolbox/+baseflow/private/drawarrow.m
index b975113..6aef2d0 100644
--- a/toolbox/+baseflow/private/drawarrow.m
+++ b/toolbox/+baseflow/private/drawarrow.m
@@ -55,7 +55,9 @@
          ['drawarrow drew no arrow: a log axis cannot show the point ' ...
          '(%g, %g) or the point (%g, %g).'], ...
          tail(1), tail(2), head(1), head(2));
-      harrow = [];
+      if nargout > 0
+         harrow = [];
+      end
       return
    end
 
@@ -72,7 +74,9 @@
    % A zero-length arrow has no direction to point in. Octave has no
    % gobjects, so return the empty array both languages take.
    if shaftlength == 0
-      harrow = [];
+      if nargout > 0
+         harrow = [];
+      end
       return
    end
    backward = shaft / shaftlength;
@@ -104,7 +108,11 @@
    hhead = patch(ax, headx, heady, color, 'EdgeColor', color, ...
       'FaceColor', color, 'Tag', 'refarrowhead', 'HandleVisibility', 'off');
 
-   harrow = [hshaft, hhead];
+   % Assign the output only when the caller wants it, so a call without a
+   % semicolon does not print the handles.
+   if nargout > 0
+      harrow = [hshaft, hhead];
+   end
 end
 
 function pixel = datatopixel(value, lims, islog, npixels)
diff --git a/toolbox/+baseflow/private/figurevisibility.m b/toolbox/+baseflow/private/figurevisibility.m
new file mode 100644
index 0000000..5df5051
--- /dev/null
+++ b/toolbox/+baseflow/private/figurevisibility.m
@@ -0,0 +1,48 @@
+function visibility = figurevisibility(show)
+   %FIGUREVISIBILITY Visibility of a figure a caller asked to show.
+   %
+   % Syntax
+   %
+   %     visibility = figurevisibility(show)
+   %
+   % Description
+   %
+   %     visibility = figurevisibility(show) returns 'on' when show is
+   %     true and 'off' when it is false.
+   %
+   %     It returns 'off' whatever show says when the root asks for
+   %     invisible figures, which baseflow.internal.runtests does for the
+   %     length of a test run. The figure is still drawn, so a caller that
+   %     reads it finds what it needs, and no window opens. A figure
+   %     created with an explicit 'Visible' of 'on' ignores that root
+   %     default, which is why this function reads it.
+   %
+   % See also: fitphidist, runtests
+
+   % Octave has no root 'default' query, so take the request as given.
+   if isoctave
+      visibility = onoff(show);
+      return
+   end
+
+   % get errors on a default the root never set, so ask which defaults
+   % exist before reading this one.
+   defaults = get(groot, 'default');
+   if isfield(defaults, 'defaultFigureVisible') ...
+         && strcmp(defaults.defaultFigureVisible, 'off')
+      visibility = 'off';
+      return
+   end
+
+   visibility = onoff(show);
+end
+
+function state = onoff(show)
+   % Translate a true or false request to the char the Visible property
+   % takes.
+   if show
+      state = 'on';
+   else
+      state = 'off';
+   end
+end
diff --git a/toolbox/docs/html/baseflow_contents.html b/toolbox/docs/html/baseflow_contents.html
index f781f7d..7b1c0ac 100644
--- a/toolbox/docs/html/baseflow_contents.html
+++ b/toolbox/docs/html/baseflow_contents.html
@@ -9,7 +9,7 @@
 <title>Baseflow Toolbox Contents</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_contents.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_examples_contents.html b/toolbox/docs/html/baseflow_examples_contents.html
index e6ec8b1..8658315 100644
--- a/toolbox/docs/html/baseflow_examples_contents.html
+++ b/toolbox/docs/html/baseflow_examples_contents.html
@@ -9,7 +9,7 @@
 <title>Baseflow Recession Analysis Toolbox Examples</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_examples_contents.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_gettingStarted.html b/toolbox/docs/html/baseflow_gettingStarted.html
index 25d1df0..c994284 100644
--- a/toolbox/docs/html/baseflow_gettingStarted.html
+++ b/toolbox/docs/html/baseflow_gettingStarted.html
@@ -9,7 +9,7 @@
 <title>Getting Started with the Baseflow Toolbox</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_gettingStarted.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_powerlaw_notation.html b/toolbox/docs/html/baseflow_powerlaw_notation.html
index e0fe484..b2fb6dc 100644
--- a/toolbox/docs/html/baseflow_powerlaw_notation.html
+++ b/toolbox/docs/html/baseflow_powerlaw_notation.html
@@ -9,7 +9,7 @@
 <title>Power-law notation across plfit, r_plfit, gpd, and baseflow</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_powerlaw_notation.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_theory_contents.html b/toolbox/docs/html/baseflow_theory_contents.html
index 5f2cbb4..0e7c8fc 100644
--- a/toolbox/docs/html/baseflow_theory_contents.html
+++ b/toolbox/docs/html/baseflow_theory_contents.html
@@ -9,7 +9,7 @@
 <title>Theoretical Basis Tutorials</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_theory_contents.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_welcome.html b/toolbox/docs/html/baseflow_welcome.html
index b5b73ff..1b432c9 100644
--- a/toolbox/docs/html/baseflow_welcome.html
+++ b/toolbox/docs/html/baseflow_welcome.html
@@ -9,7 +9,7 @@
 <title>Welcome to the Baseflow Recession Analysis Toolbox</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-17">
+<meta name="DC.date" content="2026-09-18">
 <meta name="DC.source" content="baseflow_welcome.m">
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z*l#|VK&$gDjR~|8pM5TY*51Fmnn3I9Kio;6HTArw3ABEGINL^R<xg^KWx2MNT-y)1
zw$E4CXpMZ0Xgj{vw&%8u){>vDLc;kjZ^ODG{ILiL*{isYRD|u%G5;kN?d8<d(^9Xm
zP-&(oJLb%J=p3&}nV0&}(aHpOiPiVROrn5z){vkjTAsAj=#oa|Eat*l<!orqRpo40
z&7A~2T}O0}_BqjapLG5cvnkuwku$V8r}Lj-RCEtztaLDPSrUR;`iyxj+~i)qO*1Ds
zedg_(Ha&If*$XI?)&6)HYUWcw){<@LMobH=Ns(x7wAY2m$v!%N33<j&Wq<Ju=`))1
z?NSv8wX{}Ce?sk>N;+0a-&NB0DRr<5rYk?BDd_?wU96;EDk(wH^e5E*O-c7CX`PaO
xr=+Kp^m`?}sicpUv`tPA=m6f3PL&m&NlHnH3XJ^;`||-bY`NJ`eCtN^{{l|NJqG{)

diff --git a/toolbox/docs/html/helpsearch-v4_en/store/root.bolt b/toolbox/docs/html/helpsearch-v4_en/store/root.bolt
index 9a96719d6a33a2562d380a14ee022b86e336343c..3849a1552c32cf3c18326a64dc52d0e2d1a448d0 100755
GIT binary patch
delta 130
zcmZo@5NK!+*kIux!N&jrtWf%5K!SxpP5QNsf$Qy?|JQH-U(d*WU^-U=li1cIrg`=g
o6P&g+FmXAUvxC($L3J@hX%;9AGmQhv=Yi6^AY&&c2(&N*0BA55u>b%7

delta 102
zcmZo@5NK!+*kIux!NULn%usr&XlBVK)5uL51J~O(|F7Tvzn+o%z;rGLMy07XOllhw
j7T8Zr;M>-~#N{9c(ZUAR$PT5qDl*@<Z~y<FiID*SKb08n

diff --git a/toolbox/docs/html/m2html/+baseflow/Contents.html b/toolbox/docs/html/m2html/+baseflow/Contents.html
index c85e04a..327fd44 100644
--- a/toolbox/docs/html/m2html/+baseflow/Contents.html
+++ b/toolbox/docs/html/m2html/+baseflow/Contents.html
@@ -161,6 +161,7 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
    baseflow/private.dealout                     - Deal out function outputs
    baseflow/private.drawarrow                   - Draw an arrow in an axes, with the head on a given point
    baseflow/private.emptyaxes                   - Return empty axes object
+   baseflow/private.figurevisibility            - Visibility of a figure a caller asked to show
    baseflow/private.fillnans                    - Fill interior sequences of nan values of length &lt;= fmax
    baseflow/private.findevents                  - Returns flow Q and time T values of each individual recession event,
    baseflow/private.findmin                     - Returns the k indici(s) of the min value and the value at those
@@ -245,7 +246,7 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
    baseflow/private.withwarnoff                 - Temporarily disable warnings
    baseflow/private.yorkfit                     - Fit a straight line when both x and y carry measurement errors
     
-   This file was generated by updatecontents.m on 17 Sep 2026 at 11:51:09.</pre></div>
+   This file was generated by updatecontents.m on 18 Sep 2026 at 12:28:36.</pre></div>
 
 
 <!-- crossreference -->
diff --git a/toolbox/docs/html/m2html/+baseflow/fitphi.html b/toolbox/docs/html/m2html/+baseflow/fitphi.html
index 4ceca77..8949bad 100644
--- a/toolbox/docs/html/m2html/+baseflow/fitphi.html
+++ b/toolbox/docs/html/m2html/+baseflow/fitphi.html
@@ -435,40 +435,40 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0291       <span class="comment">% water table</span>
 0292       <span class="comment">% if strcmp(soln2,'RS05') &amp;&amp; (b2 &lt; 3/2 || b2&gt;=2)</span>
 0293       <span class="keyword">if</span> strcmp(soln2,<span class="string">'RS05'</span>) &amp;&amp; (b2 &lt;= 1 || b2&gt;=2)
-0294          warning( <span class="keyword">...</span>
+0294          warning(<span class="string">'baseflow:fitphi:incompatibleLateTimeSolution'</span>, <span class="keyword">...</span>
 0295             [<span class="string">'Requested late-time solution (Rupp and Selker, 2005) '</span> <span class="keyword">...</span>
 0296             <span class="string">'is incompatible with b&lt;1.5 or b&gt;=2, using Boussinesq, 1903, b=1'</span>])
 0297          soln2 = <span class="string">'BS03'</span>;
 0298 
 0299          <span class="comment">% late-time B04 has b = 3/2</span>
 0300       <span class="keyword">elseif</span> strcmp(soln2,<span class="string">'BS04'</span>) &amp;&amp; (b2 ~= 3/2)
-0301          warning( <span class="keyword">...</span>
+0301          warning(<span class="string">'baseflow:fitphi:lateTimeSolutionImpliesB'</span>, <span class="keyword">...</span>
 0302             [<span class="string">'Requested late-time solution (Boussinesq, 1904) '</span> <span class="keyword">...</span>
 0303             <span class="string">'implies b=3/2, using b=3/2'</span>])
 0304          b2 = 3/2;
 0305 
 0306          <span class="comment">% late-time B03 has b = 1</span>
 0307       <span class="keyword">elseif</span> strcmp(soln2,<span class="string">'BS03'</span>) &amp;&amp; (b2 ~= 1)
-0308          warning( <span class="keyword">...</span>
+0308          warning(<span class="string">'baseflow:fitphi:lateTimeSolutionImpliesB'</span>, <span class="keyword">...</span>
 0309             [<span class="string">'Requested late-time solution (Boussinesq, 1903) '</span> <span class="keyword">...</span>
 0310             <span class="string">'implies b=1, using b=1'</span>])
 0311          b2 = 1;
 0312       <span class="keyword">end</span>
 0313    <span class="keyword">else</span>
 0314       <span class="keyword">if</span> strcmp(soln1,<span class="string">'RS05'</span>) &amp;&amp; (b2 &lt; 3/2 || b2&gt;=2)
-0315          warning( <span class="keyword">...</span>
+0315          warning(<span class="string">'baseflow:fitphi:incompatibleLateTimeSolution'</span>, <span class="keyword">...</span>
 0316             [<span class="string">'Requested late-time solution (Rupp and Selker, 2005) '</span> <span class="keyword">...</span>
 0317             <span class="string">'is incompatible with b&lt;1.5 or b&gt;=2, using Boussinesq, 1903, b=1'</span>])
 0318          soln2 = <span class="string">'BS03'</span>;
 0319 
 0320       <span class="keyword">elseif</span> strcmp(soln2,<span class="string">'BS04'</span>) &amp;&amp; (b2 ~= 3/2)
-0321          warning( <span class="keyword">...</span>
+0321          warning(<span class="string">'baseflow:fitphi:lateTimeSolutionImpliesB'</span>, <span class="keyword">...</span>
 0322             [<span class="string">'Requested late-time solution (Boussinesq, 1904) '</span> <span class="keyword">...</span>
 0323             <span class="string">'implies b=3/2, using b=3/2'</span>])
 0324          b2 = 3/2;
 0325 
 0326       <span class="keyword">elseif</span> strcmp(soln2,<span class="string">'BS03'</span>) &amp;&amp; (b2 ~= 1)
-0327          warning( <span class="keyword">...</span>
+0327          warning(<span class="string">'baseflow:fitphi:lateTimeSolutionImpliesB'</span>, <span class="keyword">...</span>
 0328             [<span class="string">'Requested late-time solution (Boussinesq, 1903) '</span> <span class="keyword">...</span>
 0329             <span class="string">'implies b=1, using b=1'</span>])
 0330          b2 = 1;
diff --git a/toolbox/docs/html/m2html/+baseflow/fitphidist.html b/toolbox/docs/html/m2html/+baseflow/fitphidist.html
index e45c05e..9192692 100644
--- a/toolbox/docs/html/m2html/+baseflow/fitphidist.html
+++ b/toolbox/docs/html/m2html/+baseflow/fitphidist.html
@@ -170,7 +170,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0082    [cdfY, cdfX] = ecdf(phi, <span class="string">'Function'</span>, <span class="string">'cdf'</span>);
 0083    
 0084    <span class="comment">% Create the figure</span>
-0085    h.figure = figure(<span class="string">'Visible'</span>, showfit);
+0085    h.figure = figure(<span class="string">'Visible'</span>, figurevisibility(showfit));
 0086    h.data = plot(cdfX, cdfY, <span class="string">'o'</span>, <span class="string">'MarkerFaceColor'</span>, [0 0.447 0.741], <span class="keyword">...</span>
 0087       <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Visible'</span>, showfit); hold on;
 0088 
@@ -212,7 +212,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0124       xarrow = [PD.mean 1.3*PD.mean];
 0125       yarrow = [betacdf(PD.mean, PD.a, PD.b) betacdf(PD.mean, PD.a, PD.b)];
 0126       <span class="comment">% the head points left, at the mean, from a tail to its right</span>
-0127       drawarrow(gca, [xarrow(2), yarrow(2)], [xarrow(1), yarrow(1)])
+0127       drawarrow(gca, [xarrow(2), yarrow(2)], [xarrow(1), yarrow(1)]);
 0128       text(0.95*xarrow(2), yarrow(2), arrowtxt, <span class="string">'HorizontalAlignment'</span>,<span class="string">'left'</span>)
 0129 
 0130       h.legend = legend(ltxt, <span class="string">'Location'</span>, <span class="string">'east'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
@@ -240,7 +240,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0152    <span class="keyword">end</span>
 0153 
 0154    <span class="comment">% Create the figure. It is hidden when showfit is false.</span>
-0155    h.figure = figure(<span class="string">'Visible'</span>, showfit);
+0155    h.figure = figure(<span class="string">'Visible'</span>, figurevisibility(showfit));
 0156 
 0157    <span class="comment">% plot the data, suppressing the normal plot with 'noref'</span>
 0158    h.data = probplot(<span class="string">'normal'</span>, phi, [], [], <span class="string">'noref'</span>); hold on;
diff --git a/toolbox/docs/html/m2html/+baseflow/gpfitb.html b/toolbox/docs/html/m2html/+baseflow/gpfitb.html
index cfb9bea..42d1379 100644
--- a/toolbox/docs/html/m2html/+baseflow/gpfitb.html
+++ b/toolbox/docs/html/m2html/+baseflow/gpfitb.html
@@ -301,7 +301,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0216    ya = [ya ya];
 0217    ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f\\pm%.0f$ days'</span>,xmin,xminc);
 0218 
-0219    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)])
+0219    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
 0220    text(0.95*xa(1),ya(1),ta,<span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>)
 0221 
 0222    <span class="comment">% use these to put the text on the right side of the curve</span>
@@ -317,7 +317,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0232    ya = [ya ya];
 0233    ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days'</span>,xexp,xexpc);
 0234 
-0235    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)])
+0235    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
 0236    text(0.95*xa(1),ya(1),ta,<span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>)
 0237 <span class="keyword">end</span>
 0238 
diff --git a/toolbox/docs/html/m2html/+baseflow/plplotb.html b/toolbox/docs/html/m2html/+baseflow/plplotb.html
index 25a61df..364e6a9 100644
--- a/toolbox/docs/html/m2html/+baseflow/plplotb.html
+++ b/toolbox/docs/html/m2html/+baseflow/plplotb.html
@@ -262,7 +262,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0165 
 0166    <span class="comment">% draw the arrow in the current axes, which is the axes the caller</span>
 0167    <span class="comment">% plotted into, as the text call below uses</span>
-0168    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)])
+0168    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
 0169    text(0.95*xarrw(1),yarrw(1),ta, <span class="keyword">...</span>
 0170       <span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>,<span class="string">'FontSize'</span>,14,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>)
 0171 
@@ -289,7 +289,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0192       ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days'</span>,xexp,xexpc);
 0193    <span class="keyword">end</span>
 0194 
-0195    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)])
+0195    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
 0196    text(0.95*xarrw(1),yarrw(1),ta, <span class="keyword">...</span>
 0197       <span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>,<span class="string">'FontSize'</span>,14,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>)
 0198 <span class="keyword">end</span>
diff --git a/toolbox/docs/html/m2html/function_index.html b/toolbox/docs/html/m2html/function_index.html
index 9954be8..351e816 100644
--- a/toolbox/docs/html/m2html/function_index.html
+++ b/toolbox/docs/html/m2html/function_index.html
@@ -118,6 +118,6 @@ <h2>Function Files in these Packages</h2>
 		<td><a href="" title=""></a></td>	</tr></table>
 
 
-<hr><address>Generated on Thu 17-Sep-2026 11:51:10 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Fri 18-Sep-2026 12:28:37 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file

From 596452855ddeea823cdde7c55871605ab4e169ee Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Fri, 18 Sep 2026 13:48:56 -0700
Subject: [PATCH 02/28] fix(baseflow): close the last window, label the demo
 values, draw 1.2.0

Three tests made a panel current with axes(), which shows and raises its
figure whatever the root default asks for, so a window still opened
during a run. They name the current axes through the figure instead. A
root listener over the whole suite now reports no visible figure.

The demos printed bare results, which reach the screen as ans. Each
value now prints with its name. baseflow_demo_3 reports k in cm s-1,
the unit aquiferprops returns it in.

The large drawn letters of the version banner read 1.0.0 and now read
1.2.0. That art is drawn by hand, unlike the two slots beside and below
the v, which come from the version string; a comment says which is
which, and test_internal reads the banner back and checks both slots
against the version.

The generated demo pages keep the output they were built with. They are
rebuilt the next time the docs are rebuilt for their own reason.
---
 CHANGELOG.md                           | 13 ++++++++++---
 tests/test_internal.m                  | 15 +++++++++++++++
 tests/test_plotdqdt.m                  |  4 +++-
 tests/test_plotrefline.m               |  4 +++-
 tests/test_pointcloudplot.m            |  4 +++-
 toolbox/+baseflow/+internal/version.m  | 12 +++++++-----
 toolbox/demos/mfiles/baseflow_demo_1.m |  7 ++++---
 toolbox/demos/mfiles/baseflow_demo_2.m |  9 +++++----
 toolbox/demos/mfiles/baseflow_demo_3.m |  4 ++--
 9 files changed, 52 insertions(+), 20 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index d6d25b6..2017e6b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -12,12 +12,19 @@ semantic versioning.
   figure. The private `drawarrow` assigned its output whether or not the
   caller asked for it, and no call site ended with a semicolon, so each
   label printed a 1x2 graphics array.
-- `baseflow.internal.version` draws the version it reports. The banner
-  carried the digits of 1.1.0, and it now takes them from the version
-  string.
+- `baseflow.internal.version` draws the version it reports. The two
+  slots beside and below the v carried the digits of 1.1.0 and now come
+  from the version string. The large letters, which are drawn art, read
+  1.2.0.
 - `baseflow.internal.runtests` draws test figures off screen, so a run on
   the desktop opens no window for a test that closes its own figure. It
   puts the figure default back on both exits.
+- Three tests made an axes current with `axes()`, which shows and raises
+  its figure whatever the root default asks for, so a window still opened
+  during a run. They name the current axes through the figure instead.
+- The demos print each value with its name. `baseflow_demo_1`,
+  `baseflow_demo_2` and `baseflow_demo_3` displayed bare results, which
+  reach the screen as `ans`.
 - `fitphidist` draws its figure off screen when the root asks for
   invisible figures, through the new private `figurevisibility`. A figure
   created with an explicit `'Visible'` of `'on'` ignores that default, so
diff --git a/tests/test_internal.m b/tests/test_internal.m
index 9809d06..8748eac 100644
--- a/tests/test_internal.m
+++ b/tests/test_internal.m
@@ -11,6 +11,21 @@ function teardown(testCase) %#ok<INUSD>
 
 end
 
+function test_versionBannerCarriesTheVersion(testCase)
+   % The verbose banner draws the version in two slots built from the
+   % version string, the major number beside the v and the minor and patch
+   % digits below it, so the art cannot fall behind a release.
+   v = baseflow.internal.version('silent');
+   number = sscanf(v, '%d.%d.%d');
+   majorslot_expected = sprintf('|.  v%d', number(1));
+   minorslot_expected = sprintf('|:  %d%d', number(2), number(3));
+
+   returned = evalc('baseflow.internal.version()');
+
+   testCase.verifySubstring(returned, majorslot_expected)
+   testCase.verifySubstring(returned, minorslot_expected)
+end
+
 function test_basepath(testCase)
    toolboxpath = baseflow.internal.basepath();
    [~, toolboxfolder] = fileparts(toolboxpath);
diff --git a/tests/test_plotdqdt.m b/tests/test_plotdqdt.m
index 1811eb3..a1c6fdc 100644
--- a/tests/test_plotdqdt.m
+++ b/tests/test_plotdqdt.m
@@ -304,7 +304,9 @@ function test_drawsInSuppliedAxes(testCase)
          target = subplot(1, 2, 1, 'Parent', fig);
          other = subplot(1, 2, 2, 'Parent', fig);
          plot(other, 1:10, 1:10);
-         axes(other)
+         % Make the other panel current without axes(), which shows and
+         % raises the figure whatever the root default asks for.
+         set(fig, 'CurrentAxes', other)
          nfigs_expected = numel(findall(0, 'Type', 'figure'));
 
          h = baseflow.plotdqdt(testCase.q, testCase.dqdt, 'ax', target, ...
diff --git a/tests/test_plotrefline.m b/tests/test_plotrefline.m
index 6d4c574..3fd2476 100644
--- a/tests/test_plotrefline.m
+++ b/tests/test_plotrefline.m
@@ -92,7 +92,9 @@ function test_drawsInSuppliedAxes(testCase)
          target = subplot(1, 2, 1, 'Parent', fig);
          other = subplot(1, 2, 2, 'Parent', fig);
          set(target, 'XScale', 'log', 'YScale', 'log')
-         axes(other)
+         % Make the other panel current without axes(), which shows and
+         % raises the figure whatever the root default asks for.
+         set(fig, 'CurrentAxes', other)
          nlines_expected = 0;
 
          baseflow.plotrefline(testCase.q(), testCase.q(), ...
diff --git a/tests/test_pointcloudplot.m b/tests/test_pointcloudplot.m
index 82cee7e..1b3872f 100644
--- a/tests/test_pointcloudplot.m
+++ b/tests/test_pointcloudplot.m
@@ -149,7 +149,9 @@ function test_suppliedAxesKeepsTheFigureAndItsSibling(testCase)
          target = subplot(1, 2, 1, 'Parent', fig);
          other = subplot(1, 2, 2, 'Parent', fig);
          plot(other, 1:10, 1:10);
-         axes(other)
+         % Make the other panel current without axes(), which shows and
+         % raises the figure whatever the root default asks for.
+         set(fig, 'CurrentAxes', other)
 
          out = testCase.drawcloud('ax', target);
 
diff --git a/toolbox/+baseflow/+internal/version.m b/toolbox/+baseflow/+internal/version.m
index 6bd3778..bc3ab58 100644
--- a/toolbox/+baseflow/+internal/version.m
+++ b/toolbox/+baseflow/+internal/version.m
@@ -19,9 +19,11 @@
    end
 
    if strcmp(option, 'verbose')
-      % The banner carries the version in two slots of two characters: the
-      % major number beside the v, and the minor and patch digits below it.
-      % Build them from v so the art cannot fall behind the version.
+      % The banner carries the version twice. These two slots of two
+      % characters, the major number beside the v and the minor and patch
+      % digits below it, are built from v, so they cannot fall behind it.
+      % The large letters to the right are drawn art: a release that
+      % changes a digit there redraws those four rows by hand.
       number = sscanf(v, '%d.%d.%d');
       majorslot = fitslot(sprintf('v%d', number(1)));
       minorslot = fitslot(sprintf('%d%d', number(2), number(3)));
@@ -32,8 +34,8 @@
       disp(['|.  ' majorslot '  /|  _  ||__ --||  -__||   _||  ||  _  ||  |  |  |   '])
       disp('|.  _   \|___._||_____||_____||__|  |__||_____||________|   ')
       disp(['|:  ' minorslot '   \              ____        ______      ______      '])
-      disp('|::.. .  /   .--.--.   |_   |      |      |    |      |     ')
-      disp('`-------''    |  |  |__  _|  |_  __ |  --  | __ |  --  |    ')
+      disp('|::.. .  /   .--.--.   |_   |      |__    |    |      |     ')
+      disp('`-------''    |  |  |__  _|  |_  __  ___|  | __ |  --  |    ')
       disp('              \___/|__||______||__||______||__||______|     ')
    end
 end
diff --git a/toolbox/demos/mfiles/baseflow_demo_1.m b/toolbox/demos/mfiles/baseflow_demo_1.m
index 07f4e0a..59225ef 100644
--- a/toolbox/demos/mfiles/baseflow_demo_1.m
+++ b/toolbox/demos/mfiles/baseflow_demo_1.m
@@ -93,13 +93,14 @@
 % The recession parameters _a_ and _b_ in the recession equation $-dQ/dt = aQ^b$ 
 % are available in the |abFit| struct.
 
-abFit.a
-abFit.b
+fprintf('a = %.4f\n', abFit.a)
+fprintf('b = %.4f\n', abFit.b)
 %% 
 % Print the fitted values to the screen using a latex-formatted character array. 
 % This is the same function used to format the legend in the point cloud plot 
 % shown above.
 
-baseflow.aQbString([abFit.a abFit.b], 'printvalues', true)
+fprintf('%s\n', baseflow.aQbString([abFit.a abFit.b], ...
+   'printvalues', true))
 %% 
 % The fitted value _b=1.2_ indicates the reservoir is mildly non-linear.
\ No newline at end of file
diff --git a/toolbox/demos/mfiles/baseflow_demo_2.m b/toolbox/demos/mfiles/baseflow_demo_2.m
index d1ecb7f..b4b5002 100644
--- a/toolbox/demos/mfiles/baseflow_demo_2.m
+++ b/toolbox/demos/mfiles/baseflow_demo_2.m
@@ -95,8 +95,9 @@
 %% Check the fitted recession parameters
 % The recession parameters _a_ and _b_ are available in the |GlobalFit| struct.
 
-GlobalFit.a % late-time recession constant in equation -dQ/dt = aQ^b
-GlobalFit.b % late-time recession constant in equation -dQ/dt = aQ^b
+% late-time recession constants in the equation -dQ/dt = aQ^b
+fprintf('a = %.4f\n', GlobalFit.a)
+fprintf('b = %.4f\n', GlobalFit.b)
 %% 
 % In addition, the |GlobalFit| struct contains the Pareto distribution exponent 
 % $\alpha$, the Pareto scale parameter $\tau_0$, the expected value $\langle\tau\rangle$, 
@@ -111,11 +112,11 @@
 % 
 % Use the function to convert from $\alpha$ to $b$.
 
-baseflow.conversions(GlobalFit.b, 'b', 'alpha')
+fprintf('alpha = %.4f\n', baseflow.conversions(GlobalFit.b, 'b', 'alpha'))
 %% 
 % Compare that to the value of $\alpha$ in the GlobalFit struct:
 
-GlobalFit.alpha
+fprintf('GlobalFit.alpha = %.4f\n', GlobalFit.alpha)
 %% 
 % Like all functions in the toolbox, |baseflow.conversions| supports tab-completion. 
 % Users are encouraged to explore the conversions supported by this function which 
diff --git a/toolbox/demos/mfiles/baseflow_demo_3.m b/toolbox/demos/mfiles/baseflow_demo_3.m
index 3e7e972..2409bb9 100644
--- a/toolbox/demos/mfiles/baseflow_demo_3.m
+++ b/toolbox/demos/mfiles/baseflow_demo_3.m
@@ -163,8 +163,8 @@
 Props = baseflow.aquiferprops(q, dqdt, ahat, bhat, 'RS05', phi, ...
    A, L, 'D', 0.5);
 
-Props.D
-Props.k
+fprintf('D = %.4f m\n', Props.D)
+fprintf('k = %.4f cm s-1\n', Props.k)
 %% 
 % Typically, values for _k_ obtained from baseflow recession analysis applied 
 % to streamflow records for catchments are 1-2 orders of magnitude larger than 

From 0ff966514d2b5cd01c10fec0cc544867184f450c Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:58 -0700
Subject: [PATCH 03/28] docs: refresh workflow and local style guidance

---
 STYLE.local.md |  4 ++++
 STYLE.md       | 23 +++++++++++++++++++----
 2 files changed, 23 insertions(+), 4 deletions(-)

diff --git a/STYLE.local.md b/STYLE.local.md
index 800f490..12f2ec4 100644
--- a/STYLE.local.md
+++ b/STYLE.local.md
@@ -78,3 +78,7 @@ as this:
 
 > This method fails when nmin is 0, and possibly when nmin is 1. runlength
 > returns 1 for consecutive nan values. See isminlength.
+
+## Other project conventions
+
+The New-test convention section defines this repository's additional test requirements.
diff --git a/STYLE.md b/STYLE.md
index 52506d2..12bce9a 100644
--- a/STYLE.md
+++ b/STYLE.md
@@ -24,17 +24,17 @@ live in `STYLE.local.md`. Match surrounding code first; these are defaults.
 
 ## Comments and documentation
 
-Comment discipline is **strict and non-negotiable** — a hard requirement, not a
-preference.
+Comment discipline is **strict and non-negotiable**. It is a hard requirement,
+not a preference.
 
 - **Never write uncommented code.** Every new function gets a docstring/header, and
   every block of code gets an explanatory comment that says *why*, not just *what*.
   Do not skip a comment because the code looks trivial, simple, obvious, or
-  self-explanatory — that is not an exception. Uncommented code is incomplete and
+  self-explanatory. That is not an exception. Uncommented code is incomplete and
   must not be submitted.
 - **Never remove existing comments.** A comment may be removed *only* when the code it
   documents is itself removed. It is never acceptable to delete, trim, shorten,
-  summarize away, or "clean up" comments — not for brevity, not for tidiness, and not
+  summarize away, or "clean up" comments, whether for brevity, for tidiness, or
   because a comment seems obvious or redundant.
 - **Edit existing comments only for accuracy.** When you change code, update the
   affected comments and docstrings so they stay correct, preserving the information
@@ -88,6 +88,21 @@ project text:
 - A comment longer than the code it explains.
 - A sentence that repeats another sentence.
 
+### Check before you finish
+
+Before you finish a change, check each new or changed comment, docstring,
+and prose sentence against these rules:
+
+- 20 words or fewer for an instruction, 25 or fewer for a description;
+- one instruction per sentence;
+- the active voice with a named actor;
+- verbs, not noun forms of verbs;
+- noun clusters of three words or fewer;
+- nothing from the "Do not write" list;
+- a comment that says why for every block of code.
+
+Fix each violation before you report the change as done.
+
 ### Never remove
 
 When you edit prose, keep:

From 810248dd22c876c31335c529b5f93ab0ff9ac709 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:58 -0700
Subject: [PATCH 04/28] test(baseflow): split TestBaseflow into per-function
 suites

Move each function-level test of tests/TestBaseflow.m to the suite of
its function, tests/test_<function_name>.m. New suites: test_getstring,
test_basinname, test_setopts, test_fitab, test_aquiferstorage,
test_aquiferthickness, test_eventfinder, and test_islocalmin.
test_islocalmax becomes a parameterized classdef that holds its peak
test and the islocalmax rows. test_getdqdt, test_fitevents,
test_plotdqdt, test_conversions, and test_plfitb take the other rows.

A method named like its class is the class constructor, which makes the
suite builder skip the file, so the moved methods take descriptive
names. TestBaseflow keeps the event-detection checks of getevents,
eventfinder, and wrapevents. Each earlier row maps to one row.
---
 CHANGELOG.md                  |   6 +
 STYLE.local.md                |   2 +
 tests/Contents.m              |  16 +-
 tests/TestBaseflow.m          | 718 +---------------------------------
 tests/test_aquiferstorage.m   |  43 ++
 tests/test_aquiferthickness.m |  38 ++
 tests/test_basinname.m        |  25 ++
 tests/test_conversions.m      |  39 ++
 tests/test_corechain.m        |   5 +-
 tests/test_eventfinder.m      | 245 ++++++++++++
 tests/test_fitab.m            | 194 +++++++++
 tests/test_fitevents.m        |  69 +++-
 tests/test_getdqdt.m          |  43 +-
 tests/test_getstring.m        |  31 ++
 tests/test_islocalmax.m       | 232 ++++++-----
 tests/test_islocalmin.m       |  35 ++
 tests/test_plfitb.m           |  31 +-
 tests/test_plotdqdt.m         |  35 +-
 tests/test_setopts.m          |  13 +
 19 files changed, 1001 insertions(+), 819 deletions(-)
 create mode 100644 tests/test_aquiferstorage.m
 create mode 100644 tests/test_aquiferthickness.m
 create mode 100644 tests/test_basinname.m
 create mode 100644 tests/test_eventfinder.m
 create mode 100644 tests/test_fitab.m
 create mode 100644 tests/test_getstring.m
 create mode 100644 tests/test_islocalmin.m
 create mode 100644 tests/test_setopts.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 2017e6b..a7f0438 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,6 +6,12 @@ semantic versioning.
 
 ## [Unreleased]
 
+### Changed
+
+- The unit tests of `tests/TestBaseflow.m` live in per-function suites,
+  `tests/test_<function_name>.m`. `TestBaseflow` keeps the workflow
+  checks that span the event-detection entry points.
+
 ### Fixed
 
 - `gpfitb`, `plplotb` and `fitphidist` print nothing when they label a
diff --git a/STYLE.local.md b/STYLE.local.md
index 12f2ec4..d0daf65 100644
--- a/STYLE.local.md
+++ b/STYLE.local.md
@@ -12,6 +12,8 @@ merged into it).
 - Give a class suite the same name as its file (`test_fitab`).
 - `TestBaseflow.m` is the integration suite for the toolbox workflow, so
   it keeps its PascalCase name.
+- A suite that tests several functions together keeps a descriptive
+  name: `test_corechain`, `test_eqstrings`, and `test_internal`.
 - Variables use short lowercase or camelCase names (`q`, `dqdt`, `gotopath`).
 
 ## Formatting
diff --git a/tests/Contents.m b/tests/Contents.m
index a0c3fce..1cad465 100644
--- a/tests/Contents.m
+++ b/tests/Contents.m
@@ -9,8 +9,11 @@
 %   closenewfigs           - Delete figures opened since the FIGSBEFORE snapshot
 %   verifydecadeticks      - Verify every decade inside the axis limits has a tick
 %   octave_smoke           - Core-chain smoke test runnable in GNU Octave and MATLAB
-%   TestBaseflow           - Test the baseflow toolbox (parameterized class)
+%   TestBaseflow           - Test the baseflow toolbox workflow (integration class)
 %   test_anomaly           - Test the private anomaly helper with vector input
+%   test_aquiferstorage    - Test the storage bounds of baseflow.aquiferstorage
+%   test_aquiferthickness  - Test the thickness of baseflow.aquiferthickness
+%   test_basinname         - Test the basin-name lookup of baseflow.basinname
 %   test_checkevent        - Test the baseflow.checkevent event plot
 %   test_breflinetext      - Test the b value text of a reference-line label
 %   test_conversions       - Test baseflow.conversions
@@ -19,23 +22,27 @@
 %   test_drawarrow         - Test the arrow of a reference-line label
 %   test_dependencies      - Test the dependency tooling and list agreement
 %   test_eqstrings         - Test the equation label helpers
+%   test_eventfinder       - Test the events baseflow.eventfinder finds in a sine
 %   test_fillnans          - Test the private fillnans helper
+%   test_fitab             - Test the fit methods and options of baseflow.fitab
 %   test_fitcts            - Test the constant-time-step dq/dt method
 %   test_figurevisibility  - Test the visibility of a figure asked to show
-%   test_fitevents         - Test the fitevents plotfits option
+%   test_fitevents         - Test the fitevents plotfits, fitorder, and ctsmethod options
 %   test_fitopts           - Test the fitab fitopts pass-through
-%   test_getdqdt           - Test the getdqdt fit-plot option
+%   test_getdqdt           - Test the getdqdt derivative and fit-plot option
+%   test_getstring         - Test the latex labels of baseflow.getstring
 %   test_hyetograph        - Test the figure that baseflow.hyetograph draws in
 %   test_internal          - Test the toolbox internal functions
 %   test_islabelcolor      - Test the private islabelcolor validator
 %   test_islinehandle      - Test the private islinehandle predicate
 %   test_islocalmax        - Test baseflow/private/islocalmax.m
+%   test_islocalmin        - Test baseflow/private/islocalmin.m
 %   test_labelanchor       - Test the private labelanchor helper
 %   test_labelrefline      - Test the shared reference-line label
 %   test_loadflow          - Test the loadflow unit conversions
 %   test_nstaruncertainty  - Test the private nstaruncertainty helper
 %   test_peakfinder        - Test the vendored +deps/peakfinder function
-%   test_plfitb            - Test the plfitb bootstrap seed, tau pole, and plot legend
+%   test_plfitb            - Test the plfitb exponent, bootstrap seed, tau pole, and legend
 %   test_plfitb_hanel      - Test the r_plfit arguments plfitb's 'hanel' passes
 %   test_plotaquifertrend  - Test the plotaquifertrend branch handles
 %   test_plotdqdt          - Test the plotdqdt reference lines, ticks, and labels
@@ -45,6 +52,7 @@
 %   test_relayoutloglogtext - Test the angle reset of a rotated log-log label
 %   test_rotatedLogLogText - Test the rotated log-log label angle
 %   test_setlogticks       - Test the private setlogticks decade ticks
+%   test_setopts           - Test the option defaults of baseflow.setopts
 %   test_setrainnan        - Test the private setrainnan helper
 %   test_siUnitsToTex      - Test the private siUnitsToTex unit label helper
 %   test_sizefigure        - Test the size of a point-cloud figure
diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index 2968600..d18886f 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -1,24 +1,15 @@
 classdef TestBaseflow < matlab.unittest.TestCase
-   %TESTBASEFLOW Test the baseflow toolbox.
+   %TESTBASEFLOW Test the baseflow toolbox workflow.
    % 
-   % TestBaseflow contains a set of parameterized unit tests:
-   %     1) an equality test for a string variable
-   %     2) an equality test for a database lookup (basin-name) variable
-   %     3) an equality test for a derivative calculation 
-   %     4) an equality test for event curve-fitting using nonlinear regression
-   %     5) an equality test for parameter conversions
-   %     6) an equality test for power law distribution fitting
-   %     7) an equality test for aquifer storage estimation
-   %     8) an equality test for aquifer thickness estimation
-   %     9) an equality test for the fitevents 'ctsmethod' option
-   %    10) an equality test for the fitab 'ols' method against the Curve
-   %        Fitting Toolbox fit and confint
-   %    11) an equality test for the private islocalmax and islocalmin
-   %        against the MATLAB islocalmax and islocalmin functions
-   %    12) an equality test for the getevents, eventfinder, and wrapevents
+   % TestBaseflow is the integration suite for the toolbox workflow. It
+   % holds the checks that span the event-detection entry points:
+   %     1) an equality test for the getevents, eventfinder, and wrapevents
    %        defaults against baseflow.setopts('getevents'), and a negative
    %        test for rmax <= 1
    %
+   % The unit tests of each function are in tests/test_<function_name>.m.
+   % test_corechain runs the analysis chain on the example data.
+   %
    % Notes:
    %     A) A negative test verifies that the code errors/fails in an
    %        expected way (e.g., the code gives the right error for a
@@ -28,30 +19,6 @@
 
    properties (TestParameter)
       SetupOption = {'install','uninstall','dependencies','addpath','savepath','rmpath','delpath'};
-      VarStr = {'Q','dQdt','aQb'};
-      DerivMethod = {'CTS'}; % {'ETS','VTS','CTS'}
-      CtsMethod = {'B1','B2','F1','F2','C2','C4'};
-      FitMethod = {'ols','nls','mean','median'};
-      RecessionExponent = {1.0,1.5}; % linear and non-linear
-      OrderOption = struct('default', {{}}, 'order1', {{'order', 1}});
-      RecessionParameterNames = {'b','n','alpha'};
-      PowerLawExponent = {1.5, 2.0, 2.5, 3.0, 3.5};
-      TauValue = {10, 100, 1000};
-      PhiValue = {0.001, 0.01, 0.1};
-      BasinName = {'ALL_BASINS','KUPARUK R NR DEADHORSE AK'};
-      MinEventDuration = {3,6,9};
-      RmConvex = {false, true};
-
-      % Short signals with one peak, one valley, or several extrema. The
-      % one-extremum signals check the peakfinder monotone branch.
-      ExtremaSignal = struct( ...
-         'onepeak', [1 2 3 2 1], ...
-         'peakthenfall', [2 3 1 0 -1], ...
-         'threepoints', [0 1 0], ...
-         'twopeaks', [1 2 3 2 5 1], ...
-         'peakvalleypeak', [10 12 15 13 11 12 11], ...
-         'onevalley', [10 9 8 9 10]);
-      ExtremaFunction = {'islocalmax', 'islocalmin'};
       EventFunction = {'getevents', 'eventfinder', 'wrapevents'};
    end
 
@@ -60,25 +27,6 @@
       % closes only figures the test created, so a full suite run leaves
       % zero open figures without touching pre-existing user figures.
       figsbefore
-
-      % The first recession event in the example data. The class setup
-      % builds it once so the fitevents tests do not repeat getevents.
-      firstevent
-   end
-
-   methods (TestClassSetup)
-      function loadfirstevent(testCase)
-         % Detect events in the example data. Keep only the first event so
-         % each fitevents call fits one event and the tests stay fast.
-         [T, Q, R] = baseflow.loadExampleData();
-         Events = baseflow.getevents(T, Q, R);
-         ievent = Events.eventTags == 1;
-         testCase.firstevent = struct( ...
-            'eventTime', Events.eventTime(ievent), ...
-            'eventFlow', Events.eventFlow(ievent), ...
-            'eventRain', Events.eventRain(ievent), ...
-            'eventTags', Events.eventTags(ievent));
-      end
    end
 
    methods (TestMethodSetup)
@@ -97,554 +45,6 @@ function closetestfigures(testCase)
 
    methods (Test)
 
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_getstring(testCase,VarStr)
-
-         switch VarStr
-            case 'Q'
-               expected = '$Q$';
-            case 'dQdt'
-               expected = '$-\mathrm{d}Q/\mathrm{d}t$';
-            case 'aQb'
-               expected = '$-\mathrm{d}Q/\mathrm{d}t = aQ^b$';
-         end
-
-         % Get actual result
-         returned = baseflow.getstring(VarStr);
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual(returned,expected)
-      end
-
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_basinname(testCase,BasinName)
-
-         % get the basin name from the database
-         returned = baseflow.basinname(BasinName);
-
-         % A valid basin name maps to itself
-         expected = BasinName;
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual(returned,expected);
-      end
-      
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_getdqdt(testCase,DerivMethod)
-
-         % define the test data
-         a = 1e-2;
-         b = 1.5;
-         q0 = 1;
-         [t, q] = baseflow.generateTestData(a,b,q0);
-
-         % Calculate expected result for CTS method
-         dq = q-[nan; q(1:end-1)];
-         dt = (t(2)-t(1));
-         expected = dq./dt;
-
-         % Get the actual result. The test data has no rainfall record.
-         [~,returned] = baseflow.getdqdt(t,q,[],DerivMethod);
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual(returned,expected)
-
-         % for testing:
-         % DerivMethod = 'CTS';
-         % [~,returned] = baseflow.getdqdt(t,q,[],DerivMethod);
-         % isequal(returned,expected)
-         % scatterfit(returned,expected)
-
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitab(testCase,RecessionExponent,FitMethod)
-
-         % define values to generate the test data
-         a = 1e-2;
-         q0 = 100;
-         t = 1:100;
-         b = RecessionExponent;
-
-         % for testing
-         % FitMethod = 'ols';
-         % b = 1.5;
-         % [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-         % figure; loglog(q,-dqdt,'o')
-         % also useful to see this:
-         % baseflow.Qnonlin(a,b,q0,t,true)
-
-         % f = baseflow.fitab(q,dqdt,'mean'); ab = f.ab
-         % f = baseflow.fitab(q,dqdt,'ols'); ab = f.ab
-         % f = baseflow.fitab(q,dqdt,'nls'); ab = f.ab
-         % f = baseflow.fitab(q,dqdt,'median'); ab = f.ab
-
-         % generate the test data
-         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-
-         % fit the data
-         switch FitMethod
-            case {'mean','median'}
-               Fit = baseflow.fitab(q,dqdt,FitMethod,'order',b);
-            otherwise
-               Fit = baseflow.fitab(q,dqdt,FitMethod);
-         end
-
-         % Get the expected result
-         expected = [a;b];
-
-         % Get the actual result
-         returned = Fit.ab;
-
-         % for testing:
-         % f = baseflow.fitab(q,dqdt,FitMethod); returned = f.ab
-         % isequal(returned,expected)
-
-         % Allow a 1 percent relative error in each of a and b
-         tol = [0.01; 0.01];
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual(returned,expected,'RelTol',tol)
-
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitab_order1(testCase,FitMethod)
-
-         % generate nonlinear (b = 1.5) test data
-         a = 1e-2;
-         b = 1.5;
-         q0 = 100;
-         t = 1:100;
-         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-
-         % fit with 'order' = 1: methods that estimate the slope redirect
-         % to 'mean'; 'mean' and 'median' force the slope directly
-         Fit = baseflow.fitab(q,dqdt,FitMethod,'order',1);
-
-         % Verify the fitted exponent is forced to 1 (linear reservoir)
-         returned = Fit.ab(2); % Fit.ab stores [a; b]
-         expected = 1;
-         testCase.verifyEqual(returned,expected);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitab_order1_envelope(testCase)
-
-         % generate test data with deterministic scatter so the 0.95
-         % quantile envelope and the mean give different intercepts
-         a = 1e-2;
-         b = 1.5;
-         q0 = 100;
-         t = 1:100;
-         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-         q = q .* (1 + 0.2*sin((1:numel(q))'));
-
-         % 'envelope' with 'order' = 1 must stay an envelope fit through
-         % 'refqtls'; it must not redirect to the 'mean' method
-         FitE = baseflow.fitab(q,dqdt,'envelope', ...
-            'refqtls',[0.95 0.95],'order',1);
-         FitM = baseflow.fitab(q,dqdt,'mean','order',1);
-
-         % Verify the slope is 1 and the intercept differs from the mean
-         % fit. Fit.ab stores [a; b].
-         b_returned = FitE.ab(2);
-         b_expected = 1;
-         testCase.verifyEqual(b_returned,b_expected);
-         a_returned = FitE.ab(1);
-         a_notexpected = FitM.ab(1);
-         testCase.verifyNotEqual(a_returned,a_notexpected);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitab_order_scope(testCase,OrderOption)
-
-         % generate nonlinear (b = 1.5) test data
-         a = 1e-2;
-         b = 1.5;
-         q0 = 100;
-         t = 1:100;
-         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-
-         % 'qtl' passes 'order' to quantreg as the polynomial degree, so
-         % 'order' = 1 must run quantile regression, not the 'mean' method.
-         % 'qtl' with no 'order' must apply the quantreg default of 1 and
-         % run quantile regression. A nan parser default for 'order' crashes it.
-         Fit = baseflow.fitab(q,dqdt,'qtl',OrderOption{:});
-         returned = Fit.fselect;
-         expected = 'qtl';
-         testCase.verifyEqual(returned,expected);
-
-         % 'mle' is unsupported and must error with or without 'order' = 1
-         testCase.verifyError( ...
-            @() baseflow.fitab(q,dqdt,'mle',OrderOption{:}), ?MException);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitab_ols_confint(testCase)
-
-         % The Curve Fitting Toolbox fit and confint give independent expected
-         % values for the 'ols' method, so skip the test without the toolbox
-         testCase.assumeFalse(isempty(ver('curvefit')), ...
-            'test_fitab_ols_confint requires the Curve Fitting Toolbox');
-
-         % generate nonlinear (b = 1.5) test data with deterministic
-         % scatter, unequal weights, and a mask that drops every fifth point
-         a = 1e-2;
-         b = 1.5;
-         q0 = 100;
-         t = 1:100;
-         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-         k = (1:numel(q))';
-         q = q .* (1 + 0.2*sin(k));
-         weights = 1 + mod(k,3);
-         mask = mod(k,5) ~= 0;
-         alpha = 0.9;
-
-         % fit -dq/dt = aQ^b with the 'ols' method
-         Fit = baseflow.fitab(q,dqdt,'ols','weights',weights, ...
-            'mask',mask,'alpha',alpha);
-
-         % Expected values: a weighted poly1 fit of log(-dq/dt) on log(q).
-         % fitab documents that masked points get zero weight.
-         fopts = fitoptions('Method','LinearLeastSquares', ...
-            'Weights',weights.*mask);
-         f = fit(log(q),log(-dqdt),'poly1',fopts);
-
-         % coeffvalues is [slope intercept]. confint has rows [lower; upper]
-         % with the same column order. Fit stores a = exp(intercept).
-         p = coeffvalues(f);
-         pci = confint(f,alpha);
-         ab_expected = [exp(p(2)); p(1)];
-         ci_expected = [exp(pci(:,2)'); pci(:,1)'];
-
-         ab_returned = Fit.ab;
-         ci_returned = [Fit.aL Fit.aH; Fit.bL Fit.bH];
-
-         % Both are least-squares solutions, so allow rounding error only
-         tol = 1e-10;
-         testCase.verifyEqual(ab_returned,ab_expected,'RelTol',tol);
-         testCase.verifyEqual(ci_returned,ci_expected,'RelTol',tol);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_plotdqdt_labelplot(testCase)
-
-         % generate nonlinear (b = 1.5) test data
-         a = 1e-2;
-         b = 1.5;
-         q0 = 100;
-         t = 1:100;
-         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
-
-         % Count refline arrows. labelrefline draws each one as a patch
-         % with HandleVisibility off, so findall finds it and findobj does
-         % not.
-         arrowtype = 'patch';
-
-         % 'labelplot' defaults to false: no refline arrows
-         h = baseflow.plotdqdt(q,dqdt);
-         narrows_returned = numel(findall(h.ax,'Type',arrowtype));
-         narrows_expected = 0;
-         testCase.verifyEqual(narrows_returned,narrows_expected);
-         % Close only the figure this test created, so a pre-existing user
-         % figure survives; plotdqdt opens a fresh figure for the next call.
-         closenewfigs(testCase.figsbefore)
-
-         % 'labelplot' true draws at least one refline arrow (see
-         % labelReflines)
-         h = baseflow.plotdqdt(q,dqdt,'labelplot',true);
-         nlabeled_returned = numel(findall(h.ax,'Type',arrowtype));
-         testCase.verifyGreaterThan(nlabeled_returned,0);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitevents_fitorder(testCase)
-
-         % build a one-event Events structure from nonlinear test data
-         a = 1e-2;
-         b = 1.5;
-         q0 = 100;
-         t = 1:100;
-         % Note: generateTestData returns its own t, sized to match q
-         [t,q] = baseflow.generateTestData(a,b,q0,t);
-         Events.eventTime = t;
-         Events.eventFlow = q;
-         Events.eventRain = zeros(size(q));
-         Events.eventTags = ones(size(q));
-
-         % fitevents must pass 'fitorder' to fitab so the event is fit
-         % with a linear reservoir model
-         [~,Results] = baseflow.fitevents(Events,'fitorder',1);
-
-         % Verify a fit was returned and the exponent is forced to 1
-         returned = Results.b;
-         testCase.verifyNotEmpty(returned);
-         expected = ones(size(returned));
-         testCase.verifyEqual(returned,expected);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_fitevents_ctsmethod(testCase,CtsMethod)
-
-         % fitevents must pass 'ctsmethod' to getdqdt, so the dq/dt it
-         % stores for the event equals a direct getdqdt call
-         Event = testCase.firstevent;
-         [~,expected] = baseflow.getdqdt(Event.eventTime, ...
-            Event.eventFlow,Event.eventRain,'CTS','ctsmethod',CtsMethod);
-         returned = baseflow.fitevents(Event,'derivmethod','CTS', ...
-            'ctsmethod',CtsMethod,'plotfits',false);
-         testCase.verifyEqual(returned.dqdt,expected);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_setopts_ctsmethod(testCase)
-
-         % The fitevents options default to the traditional backward
-         % first-order stencil
-         returned = baseflow.setopts('fitevents');
-         expected = 'B1';
-         testCase.verifyEqual(returned.ctsmethod,expected);
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_conversions(testCase,RecessionParameterNames)
-
-         switch RecessionParameterNames
-            case 'b'
-               % convert the recession exponent b to n for a flat aquifer
-               b = 1.5;
-               expected = 0; % n = (3 - 2b)/(b - 2)
-               returned = baseflow.conversions(b,'b','n','isflat',true);
-
-               % Verify that the actual result matches the expected result
-               testCase.verifyEqual(returned,expected);
-
-            case 'n'
-               % convert the conductivity exponent n to b for a flat aquifer
-               n = -1;
-               expected = 1; % b = (2n + 3)/(n + 2)
-               returned = baseflow.conversions(n,'n','b','isflat',true);
-
-               % Verify that the actual result matches the expected result
-               testCase.verifyEqual(returned,expected);
-
-            case 'alpha'
-               % convert the power law exponent alpha to b
-               alpha = 4.0;
-               expected = 1.25; % b = 1 + 1/alpha
-               returned = baseflow.conversions(alpha,'alpha','b', ...
-                  'isflat',true);
-
-               % Verify that the actual result matches the expected result
-               testCase.verifyEqual(returned,expected);
-         end
-
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_plfitb(testCase,PowerLawExponent)
-
-         % generate power-law distributed test data
-         x = (1-rand(10000,1)).^(-1/(PowerLawExponent-1));
-
-         % compute the fit
-         [~,returned] = baseflow.plfitb(x); % the second output is alpha
-         expected = PowerLawExponent;
-
-         % The estimate from random samples varies. Allow 0.1 absolute error.
-         tol = 0.1;
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual(returned,expected,'AbsTol',tol);
-
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_aquiferstorage(testCase,RecessionExponent)
-
-         % make test data
-         qmin = 1;
-         qmax = 100;
-         a = 1;
-         b = RecessionExponent;
-
-         % compute the expected result
-         switch RecessionExponent
-            case 1.0
-               Smin_expected = 1/a*qmin;
-               Smax_expected = 1/a*qmax;
-
-            case 1.5
-               Smin_expected = 1/a/(2-b).*(qmin.^(2-b));
-               Smax_expected = 1/a/(2-b).*(qmax.^(2-b));
-         end
-
-         % get the actual result
-         [Smin_returned,Smax_returned] = baseflow.aquiferstorage( ...
-            a,b,qmin,qmax);
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual([Smin_returned,Smax_returned], ...
-            [Smin_expected,Smax_expected]);
-
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_aquiferthickness(testCase,RecessionExponent,TauValue,PhiValue)
-
-         % note: this implicitly tests baseflow.conversions
-
-         % make test data
-         Qb = 2;
-         b = RecessionExponent;
-         tau = TauValue;
-         phi = PhiValue;
-
-         % compute the expected result
-         D_expected = tau/phi/(4-2*b)*Qb;
-         S_expected = D_expected*phi;
-
-         % get the actual result
-         [D_returned,S_returned] = baseflow.aquiferthickness(b,tau,phi,Qb);
-
-         % Verify that the actual result matches the expected result
-         testCase.verifyEqual([D_returned,S_returned],[D_expected,S_expected]);
-
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_eventfinder(testCase, MinEventDuration, RmConvex)
-
-         % MinEventDuration = 9;
-         % RmConvex = true;
-
-         % Generate synthetic data. prec controls how large the test vectors are
-         prec = 2;
-         [t, q] = prepareEventData(testCase, prec); %#ok<*INUSD>
-         [starts, ends, inflect] = eventIndices(testCase, t, prec, RmConvex);
-
-         % Define expected t and q
-         t_expected = cell(numel(starts), 1);
-         q_expected = cell(numel(starts), 1);
-         for n = 1:numel(starts)
-            t_expected{n, 1} = transpose(t(starts(n):ends(n)));
-            q_expected{n, 1} = transpose(q(starts(n):ends(n)));
-         end
-
-         % get the actual result. The synthetic signal has no rainfall record.
-         % rmnochange is false, so rmax has no effect, but it must be > 1.
-         [t_returned,q_returned] = baseflow.eventfinder(t,q,[], ...
-            'nmin',MinEventDuration,'fmax',0,'rmax',2,'rmin',0, ...
-            'rmconvex',RmConvex,'rmnochange',false,'rmrain',false);
-
-         % Largest allowed count of event times that are in only one of the
-         % expected and returned series (see numdiff below)
-         maxdiff = 4;
-
-         % % Verify that the actual result matches the expected result to within
-         % a difference of up to two elements to account for the +/- 1 day
-         % criteria applied in the eventfinder filters.
-         for n = 1:numel(t_returned)
-            [commonT, ia, ib] = intersect(t_expected{n}, t_returned{n});
-            numdiff = length(t_expected{n}) + length(t_returned{n}) ...
-               - 2*length(commonT);
-
-            if numdiff <= maxdiff
-               testCase.verifyEqual(t_returned{n}(ib), t_expected{n}(ia));
-               testCase.verifyEqual(q_returned{n}(ib), q_expected{n}(ia));
-            else
-               error('Difference greater than 2 elements detected.');
-            end
-         end
-
-         % Plot the result
-         if MinEventDuration == 3
-            % For now, use the first test value to determine whether to plot the
-            % result. TODO: add a method to plot in a subplot for each test
-            % parameter.
-            figure; plot(t,q); hold on;
-            plot(t(inflect), q(inflect), 'x', 'MarkerSize', 20, 'Color', 'r');
-
-            for n = 1:numel(t_returned)
-               plot(t_expected{n}, q_expected{n}, 'LineWidth', 2, 'Color', 'k');
-               plot(t_returned{n},q_returned{n},':','Color', 'g');
-            end
-
-            % Adjust legend and title based on rmconvex
-            if RmConvex
-               legend('Signal', 'Inflection Points',  ...
-                  'True Concave Up Declining Flow', 'eventfinder');
-               title('test rmconvex')
-            else
-               legend('Signal', 'Inflection Points', ...
-                  'True Declining Flow', 'eventfinder');
-               title('test eventfinder')
-            end
-         end
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_MinEventDuration(testCase, MinEventDuration, RmConvex)
-
-         % Generate synthetic data. prec controls how large the test vectors are
-         prec = 2;
-         [t, q] = prepareEventData(testCase, prec);
-         [starts, ends] = eventIndices(testCase, t, prec, RmConvex);
-
-         % test an event that is shorter than the MinEventDuration
-         idx = sort(randi(ends(1)-starts(1), MinEventDuration-1, 1));
-         t = t(starts(1)+idx);
-         q = q(starts(1)+idx);
-
-         t_expected = [];
-         q_expected = [];
-
-         % figure; plot(t_expected, q_expected, '-o')
-         % The synthetic signal has no rainfall record. rmnochange is false,
-         % so rmax has no effect, but it must be > 1.
-         [t_returned,q_returned] = baseflow.eventfinder(t, q, [], 'nmin', ...
-            MinEventDuration, 'fmax', 0, 'rmax', 2, 'rmin', 0, 'rmconvex', ...
-            RmConvex, 'rmnochange', false, 'rmrain', false);
-
-         testCase.verifyEqual(t_returned, t_expected);
-         testCase.verifyEqual(q_returned, q_expected);
-
-         % eventfinder returns empty, not an error, for an event shorter than
-         % nmin; the equality checks above cover that case.
-      end
-
-      %-------------------------------------------
-      %-------------------------------------------
-      function test_islocalextrema(testCase, ExtremaSignal, ExtremaFunction)
-
-         % The private peakfinder wrappers must find the same interior
-         % extrema as the MATLAB functions of the same name
-         customfunction = baseflow.privatefunction(ExtremaFunction);
-         expected = feval(ExtremaFunction, ExtremaSignal);
-         returned = customfunction(ExtremaSignal);
-         testCase.verifyEqual(returned, expected)
-      end
-
       %-------------------------------------------
       %-------------------------------------------
       function test_eventdefaults(testCase, EventFunction)
@@ -685,108 +85,4 @@ function test_rmaxguard(testCase, EventFunction)
       end
 
    end
-
-   methods (Access = private) % Helper methods
-
-      function [t, q] = prepareEventData(testCase, prec) %#ok<*INUSD>
-         % This function handles some common operations related to test data
-
-         if nargin < 2
-            prec = 2; % precision, controls how large the test vectors are
-         end
-
-         % generate synthetic data
-         dpi = 10^-prec;
-         t = -2*pi:dpi:2*pi;
-         q = 1 + sin(t);
-      end
-
-      function [starts, ends, inflect] = eventIndices(testCase, t, prec, RmConvex)
-
-         if RmConvex
-            % Find the points where the first derivative cos(t) is negative and
-            % the second derivative -sin(t) is positive.
-            idxconcave = find(cos(t) < 0 & (-sin(t)) > 0);
-            intervals = [find(diff(idxconcave) ~= 1)' numel(idxconcave)];
-            starts = [idxconcave(1); idxconcave(intervals(1:end-1) + 1)];
-            ends = idxconcave(intervals);
-
-            % Inflection points where the second derivative equals zero
-            inflect = find(abs(-sin(t)) <= 10^-prec);
-
-         else
-            % Find the maxima and minima (where d/dt sin(t) == 0)
-            idxminmax = find(round(cos(t),prec)==0);
-            starts = idxminmax(1:2:end); % +1 or +2 depending on eventfinder
-            ends = idxminmax(2:2:end); % -1
-            inflect = idxminmax;
-         end
-      end
-   end
 end
-
-
-%       % for debugging test_eventfinder
-%       % --------------
-%
-%       % if t_expected, t_returned sizes don't match, try adjusting whether the
-%       % point prior to the min is removed. For example, if the test uses this
-%       % syntax:
-%       %
-%       % ievent = idx(n,1)+2 : idx(n,2);
-%       %
-%       % Then try changing it to:
-%       %
-%       % ievent = idx(n,1)+2 : idx(n,2) - 1;
-%       %
-%       % i.e., remove the one prior to the min.
-%       %
-%       % and visa versa
-%
-%       % Try removing the min, then see if they are equal
-%       ievent1 = idx(1,1)+2 : idx(1,2)-1;
-%       ievent2 = idx(2,1)+2 : idx(2,2)-1;
-%
-%       % Try NOT removing the min
-%       % ievent1 = idx(1,1)+2 : idx(1,2);
-%       % ievent2 = idx(2,1)+2 : idx(2,2);
-%
-%       t_expected{1} = transpose(t(ievent1));
-%       q_expected{1} = transpose(q(ievent1));
-%       t_expected{2} = transpose(t(ievent2));
-%       q_expected{2} = transpose(q(ievent2));
-%
-%       isequal(t_expected{1},t_returned{1})
-%       isequal(t_expected{2},t_returned{2})
-%
-%       % If that says they are equal, then the issue is with removing the min.
-%
-%       % Below here is ohter stuff I used for debugging.
-%       [size(t_expected{1}); size(t_returned{1})]
-%       [size(t_expected{2}); size(t_returned{2})]
-%
-%       % depending on which one is missing, reverse the setdiff
-%       [val1, i1] = setdiff(t_expected{1}, t_returned{1});
-%       [val1, i1] = setdiff(t_returned{1}, t_expected{1});
-%
-%       [val2, i2] = setdiff(t_expected{2}, t_returned{2})
-%       [val2, i2] = setdiff(t_returned{2}, t_expected{2})
-%
-%       loc = ~ismember(t_expected{1}, t_returned{1})
-%
-%       figure; plot(t,q); hold on;
-%       plot(t_expected{1},q_expected{1});
-%       plot(t_expected{2},q_expected{2});
-%       plot(t_returned{1},q_returned{1},'o','MarkerSize',6);
-%       plot(t_returned{2},q_returned{2},'o');
-%
-%       % minima should be at -pi/2, 3*pi/2
-%       % maxima should be at pi/2, -3*pi/2
-%       s1 = find(t+3*pi/2>0,1,'first')-1;
-%       e1 = find(t+pi/2>0,1,'first')-1;
-%       s2 = find(t-pi/2>0,1,'first')-1;
-%       e2 = find(t-3*pi/2>0,1,'first')-1;
-%
-%       % remove the peak + 1 day, and the min
-%       s1 = s1+2; s2 = s2+2;
-%       e1 = e1-1; e2 = e2-1;
diff --git a/tests/test_aquiferstorage.m b/tests/test_aquiferstorage.m
new file mode 100644
index 0000000..de5ae33
--- /dev/null
+++ b/tests/test_aquiferstorage.m
@@ -0,0 +1,43 @@
+classdef test_aquiferstorage < matlab.unittest.TestCase
+   %TEST_AQUIFERSTORAGE Test the storage bounds of baseflow.aquiferstorage.
+
+   properties (TestParameter)
+      % The recession exponents with a closed-form storage.
+      RecessionExponent = {1.0,1.5}; % linear and non-linear
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_storageBounds(testCase,RecessionExponent)
+
+         % make test data
+         qmin = 1;
+         qmax = 100;
+         a = 1;
+         b = RecessionExponent;
+
+         % compute the expected result
+         switch RecessionExponent
+            case 1.0
+               Smin_expected = 1/a*qmin;
+               Smax_expected = 1/a*qmax;
+
+            case 1.5
+               Smin_expected = 1/a/(2-b).*(qmin.^(2-b));
+               Smax_expected = 1/a/(2-b).*(qmax.^(2-b));
+         end
+
+         % get the actual result
+         [Smin_returned,Smax_returned] = baseflow.aquiferstorage( ...
+            a,b,qmin,qmax);
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual([Smin_returned,Smax_returned], ...
+            [Smin_expected,Smax_expected]);
+
+      end
+
+   end
+end
diff --git a/tests/test_aquiferthickness.m b/tests/test_aquiferthickness.m
new file mode 100644
index 0000000..5c72ebe
--- /dev/null
+++ b/tests/test_aquiferthickness.m
@@ -0,0 +1,38 @@
+classdef test_aquiferthickness < matlab.unittest.TestCase
+   %TEST_AQUIFERTHICKNESS Test the thickness of baseflow.aquiferthickness.
+
+   properties (TestParameter)
+      % The recession exponent, drainage timescale in days, and drainable
+      % porosity of each thickness case.
+      RecessionExponent = {1.0,1.5}; % linear and non-linear
+      TauValue = {10, 100, 1000};
+      PhiValue = {0.001, 0.01, 0.1};
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_thicknessAndStorage(testCase,RecessionExponent,TauValue,PhiValue)
+
+         % note: this implicitly tests baseflow.conversions
+
+         % make test data
+         Qb = 2;
+         b = RecessionExponent;
+         tau = TauValue;
+         phi = PhiValue;
+
+         % compute the expected result
+         D_expected = tau/phi/(4-2*b)*Qb;
+         S_expected = D_expected*phi;
+
+         % get the actual result
+         [D_returned,S_returned] = baseflow.aquiferthickness(b,tau,phi,Qb);
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual([D_returned,S_returned],[D_expected,S_expected]);
+
+      end
+   end
+end
diff --git a/tests/test_basinname.m b/tests/test_basinname.m
new file mode 100644
index 0000000..1a91d33
--- /dev/null
+++ b/tests/test_basinname.m
@@ -0,0 +1,25 @@
+classdef test_basinname < matlab.unittest.TestCase
+   %TEST_BASINNAME Test the basin-name lookup of baseflow.basinname.
+
+   properties (TestParameter)
+      % Valid names from the basin database.
+      BasinName = {'ALL_BASINS','KUPARUK R NR DEADHORSE AK'};
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_validNameMapsToItself(testCase,BasinName)
+
+         % get the basin name from the database
+         returned = baseflow.basinname(BasinName);
+
+         % A valid basin name maps to itself
+         expected = BasinName;
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual(returned,expected);
+      end
+   end
+end
diff --git a/tests/test_conversions.m b/tests/test_conversions.m
index df175f3..b94e74b 100644
--- a/tests/test_conversions.m
+++ b/tests/test_conversions.m
@@ -26,6 +26,9 @@
          'MATLAB:unrecognizedStringChoice'}}, ...
          'unsupported_varname', {{1.5, 'unsupported', ...
          'MATLAB:unrecognizedStringChoice'}})
+
+      % Recession parameters with a literal expected conversion.
+      RecessionParameterNames = {'b','n','alpha'};
    end
 
    methods (Test)
@@ -49,5 +52,41 @@ function test_errorThrownForBadInput(testCase, badinput)
          testCase.verifyError( ...
             @() baseflow.conversions(inputvalue, inputname, 'n'), expected);
       end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_literalConversions(testCase,RecessionParameterNames)
+
+         switch RecessionParameterNames
+            case 'b'
+               % convert the recession exponent b to n for a flat aquifer
+               b = 1.5;
+               expected = 0; % n = (3 - 2b)/(b - 2)
+               returned = baseflow.conversions(b,'b','n','isflat',true);
+
+               % Verify that the actual result matches the expected result
+               testCase.verifyEqual(returned,expected);
+
+            case 'n'
+               % convert the conductivity exponent n to b for a flat aquifer
+               n = -1;
+               expected = 1; % b = (2n + 3)/(n + 2)
+               returned = baseflow.conversions(n,'n','b','isflat',true);
+
+               % Verify that the actual result matches the expected result
+               testCase.verifyEqual(returned,expected);
+
+            case 'alpha'
+               % convert the power law exponent alpha to b
+               alpha = 4.0;
+               expected = 1.25; % b = 1 + 1/alpha
+               returned = baseflow.conversions(alpha,'alpha','b', ...
+                  'isflat',true);
+
+               % Verify that the actual result matches the expected result
+               testCase.verifyEqual(returned,expected);
+         end
+
+      end
    end
 end
diff --git a/tests/test_corechain.m b/tests/test_corechain.m
index a9ebca8..350ab0e 100644
--- a/tests/test_corechain.m
+++ b/tests/test_corechain.m
@@ -2,8 +2,9 @@
    %TEST_CORECHAIN Core-workflow coverage for the analysis chain.
    %
    % The other core-chain functions (getevents, fitevents, fitab,
-   % eventfinder) have coverage in TestBaseflow, test_fitopts, and the
-   % smoke script. This file tests eventtau, globalfit, cloudphi, fitphi,
+   % eventfinder) have coverage in TestBaseflow, test_fitab,
+   % test_fitevents, test_eventfinder, test_fitopts, and the smoke
+   % script. This file tests eventtau, globalfit, cloudphi, fitphi,
    % and dndtuncertainty on the example data, and gpfitb, fitphidist, and
    % aQbString on synthetic inputs. The chain runs once on the shipped
    % example data in setupOnce; the constants are the Kuparuk basin values
diff --git a/tests/test_eventfinder.m b/tests/test_eventfinder.m
new file mode 100644
index 0000000..d8bd43c
--- /dev/null
+++ b/tests/test_eventfinder.m
@@ -0,0 +1,245 @@
+classdef test_eventfinder < matlab.unittest.TestCase
+   %TEST_EVENTFINDER Test the events baseflow.eventfinder finds in a sine.
+   %
+   % The signal 1 + sin(t) has known maxima, minima, and inflection points,
+   % so the expected declining and concave-up declining segments follow
+   % from its derivatives. The defaults and the rmax guard of eventfinder
+   % are integration checks in TestBaseflow.
+
+   properties (TestParameter)
+      % The minimum event lengths and the rmconvex option of each case.
+      MinEventDuration = {3,6,9};
+      RmConvex = {false, true};
+   end
+
+   properties (Access = private)
+      % Open-figure snapshot taken before each test. The method teardown
+      % closes only figures the test created, so a full suite run leaves
+      % zero open figures without touching pre-existing user figures.
+      figsbefore
+   end
+
+   methods (TestMethodSetup)
+      function snapshotfigures(testCase)
+         % Record the figures that exist before the test runs.
+         testCase.figsbefore = findall(0, 'Type', 'figure');
+      end
+   end
+
+   methods (TestMethodTeardown)
+      function closetestfigures(testCase)
+         % Close figures created during the test (see tests/closenewfigs.m).
+         closenewfigs(testCase.figsbefore)
+      end
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_findsDecliningSegments(testCase, MinEventDuration, RmConvex)
+
+         % MinEventDuration = 9;
+         % RmConvex = true;
+
+         % Generate synthetic data. prec controls how large the test vectors are
+         prec = 2;
+         [t, q] = prepareEventData(testCase, prec); %#ok<*INUSD>
+         [starts, ends, inflect] = eventIndices(testCase, t, prec, RmConvex);
+
+         % Define expected t and q
+         t_expected = cell(numel(starts), 1);
+         q_expected = cell(numel(starts), 1);
+         for n = 1:numel(starts)
+            t_expected{n, 1} = transpose(t(starts(n):ends(n)));
+            q_expected{n, 1} = transpose(q(starts(n):ends(n)));
+         end
+
+         % get the actual result. The synthetic signal has no rainfall record.
+         % rmnochange is false, so rmax has no effect, but it must be > 1.
+         [t_returned,q_returned] = baseflow.eventfinder(t,q,[], ...
+            'nmin',MinEventDuration,'fmax',0,'rmax',2,'rmin',0, ...
+            'rmconvex',RmConvex,'rmnochange',false,'rmrain',false);
+
+         % Largest allowed count of event times that are in only one of the
+         % expected and returned series (see numdiff below)
+         maxdiff = 4;
+
+         % % Verify that the actual result matches the expected result to within
+         % a difference of up to two elements to account for the +/- 1 day
+         % criteria applied in the eventfinder filters.
+         for n = 1:numel(t_returned)
+            [commonT, ia, ib] = intersect(t_expected{n}, t_returned{n});
+            numdiff = length(t_expected{n}) + length(t_returned{n}) ...
+               - 2*length(commonT);
+
+            if numdiff <= maxdiff
+               testCase.verifyEqual(t_returned{n}(ib), t_expected{n}(ia));
+               testCase.verifyEqual(q_returned{n}(ib), q_expected{n}(ia));
+            else
+               error('Difference greater than 2 elements detected.');
+            end
+         end
+
+         % Plot the result
+         if MinEventDuration == 3
+            % For now, use the first test value to determine whether to plot the
+            % result. TODO: add a method to plot in a subplot for each test
+            % parameter.
+            figure; plot(t,q); hold on;
+            plot(t(inflect), q(inflect), 'x', 'MarkerSize', 20, 'Color', 'r');
+
+            for n = 1:numel(t_returned)
+               plot(t_expected{n}, q_expected{n}, 'LineWidth', 2, 'Color', 'k');
+               plot(t_returned{n},q_returned{n},':','Color', 'g');
+            end
+
+            % Adjust legend and title based on rmconvex
+            if RmConvex
+               legend('Signal', 'Inflection Points',  ...
+                  'True Concave Up Declining Flow', 'eventfinder');
+               title('test rmconvex')
+            else
+               legend('Signal', 'Inflection Points', ...
+                  'True Declining Flow', 'eventfinder');
+               title('test eventfinder')
+            end
+         end
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_MinEventDuration(testCase, MinEventDuration, RmConvex)
+
+         % Generate synthetic data. prec controls how large the test vectors are
+         prec = 2;
+         [t, q] = prepareEventData(testCase, prec);
+         [starts, ends] = eventIndices(testCase, t, prec, RmConvex);
+
+         % test an event that is shorter than the MinEventDuration
+         idx = sort(randi(ends(1)-starts(1), MinEventDuration-1, 1));
+         t = t(starts(1)+idx);
+         q = q(starts(1)+idx);
+
+         t_expected = [];
+         q_expected = [];
+
+         % figure; plot(t_expected, q_expected, '-o')
+         % The synthetic signal has no rainfall record. rmnochange is false,
+         % so rmax has no effect, but it must be > 1.
+         [t_returned,q_returned] = baseflow.eventfinder(t, q, [], 'nmin', ...
+            MinEventDuration, 'fmax', 0, 'rmax', 2, 'rmin', 0, 'rmconvex', ...
+            RmConvex, 'rmnochange', false, 'rmrain', false);
+
+         testCase.verifyEqual(t_returned, t_expected);
+         testCase.verifyEqual(q_returned, q_expected);
+
+         % eventfinder returns empty, not an error, for an event shorter than
+         % nmin; the equality checks above cover that case.
+      end
+   end
+
+   methods (Access = private) % Helper methods
+
+      function [t, q] = prepareEventData(testCase, prec) %#ok<*INUSD>
+         % This function handles some common operations related to test data
+
+         if nargin < 2
+            prec = 2; % precision, controls how large the test vectors are
+         end
+
+         % generate synthetic data
+         dpi = 10^-prec;
+         t = -2*pi:dpi:2*pi;
+         q = 1 + sin(t);
+      end
+
+      function [starts, ends, inflect] = eventIndices(testCase, t, prec, RmConvex)
+
+         if RmConvex
+            % Find the points where the first derivative cos(t) is negative and
+            % the second derivative -sin(t) is positive.
+            idxconcave = find(cos(t) < 0 & (-sin(t)) > 0);
+            intervals = [find(diff(idxconcave) ~= 1)' numel(idxconcave)];
+            starts = [idxconcave(1); idxconcave(intervals(1:end-1) + 1)];
+            ends = idxconcave(intervals);
+
+            % Inflection points where the second derivative equals zero
+            inflect = find(abs(-sin(t)) <= 10^-prec);
+
+         else
+            % Find the maxima and minima (where d/dt sin(t) == 0)
+            idxminmax = find(round(cos(t),prec)==0);
+            starts = idxminmax(1:2:end); % +1 or +2 depending on eventfinder
+            ends = idxminmax(2:2:end); % -1
+            inflect = idxminmax;
+         end
+      end
+   end
+end
+
+
+%       % for debugging test_eventfinder
+%       % --------------
+%
+%       % if t_expected, t_returned sizes don't match, try adjusting whether the
+%       % point prior to the min is removed. For example, if the test uses this
+%       % syntax:
+%       %
+%       % ievent = idx(n,1)+2 : idx(n,2);
+%       %
+%       % Then try changing it to:
+%       %
+%       % ievent = idx(n,1)+2 : idx(n,2) - 1;
+%       %
+%       % i.e., remove the one prior to the min.
+%       %
+%       % and visa versa
+%
+%       % Try removing the min, then see if they are equal
+%       ievent1 = idx(1,1)+2 : idx(1,2)-1;
+%       ievent2 = idx(2,1)+2 : idx(2,2)-1;
+%
+%       % Try NOT removing the min
+%       % ievent1 = idx(1,1)+2 : idx(1,2);
+%       % ievent2 = idx(2,1)+2 : idx(2,2);
+%
+%       t_expected{1} = transpose(t(ievent1));
+%       q_expected{1} = transpose(q(ievent1));
+%       t_expected{2} = transpose(t(ievent2));
+%       q_expected{2} = transpose(q(ievent2));
+%
+%       isequal(t_expected{1},t_returned{1})
+%       isequal(t_expected{2},t_returned{2})
+%
+%       % If that says they are equal, then the issue is with removing the min.
+%
+%       % Below here is ohter stuff I used for debugging.
+%       [size(t_expected{1}); size(t_returned{1})]
+%       [size(t_expected{2}); size(t_returned{2})]
+%
+%       % depending on which one is missing, reverse the setdiff
+%       [val1, i1] = setdiff(t_expected{1}, t_returned{1});
+%       [val1, i1] = setdiff(t_returned{1}, t_expected{1});
+%
+%       [val2, i2] = setdiff(t_expected{2}, t_returned{2})
+%       [val2, i2] = setdiff(t_returned{2}, t_expected{2})
+%
+%       loc = ~ismember(t_expected{1}, t_returned{1})
+%
+%       figure; plot(t,q); hold on;
+%       plot(t_expected{1},q_expected{1});
+%       plot(t_expected{2},q_expected{2});
+%       plot(t_returned{1},q_returned{1},'o','MarkerSize',6);
+%       plot(t_returned{2},q_returned{2},'o');
+%
+%       % minima should be at -pi/2, 3*pi/2
+%       % maxima should be at pi/2, -3*pi/2
+%       s1 = find(t+3*pi/2>0,1,'first')-1;
+%       e1 = find(t+pi/2>0,1,'first')-1;
+%       s2 = find(t-pi/2>0,1,'first')-1;
+%       e2 = find(t-3*pi/2>0,1,'first')-1;
+%
+%       % remove the peak + 1 day, and the min
+%       s1 = s1+2; s2 = s2+2;
+%       e1 = e1-1; e2 = e2-1;
diff --git a/tests/test_fitab.m b/tests/test_fitab.m
new file mode 100644
index 0000000..62b6402
--- /dev/null
+++ b/tests/test_fitab.m
@@ -0,0 +1,194 @@
+classdef test_fitab < matlab.unittest.TestCase
+   %TEST_FITAB Test the fit methods and options of baseflow.fitab.
+   %
+   % Each test fits -dQ/dt = aQ^b to baseflow.generateTestData output with
+   % known a and b. The 'ols' confidence test compares fitab with the
+   % Curve Fitting Toolbox fit and confint.
+
+   properties (TestParameter)
+      % The fit methods, the true recession exponents of the test data,
+      % and the 'order' option of the 'qtl' scope test.
+      FitMethod = {'ols','nls','mean','median'};
+      RecessionExponent = {1.0,1.5}; % linear and non-linear
+      OrderOption = struct('default', {{}}, 'order1', {{'order', 1}});
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_recoversKnownParameters(testCase,RecessionExponent,FitMethod)
+
+         % define values to generate the test data
+         a = 1e-2;
+         q0 = 100;
+         t = 1:100;
+         b = RecessionExponent;
+
+         % for testing
+         % FitMethod = 'ols';
+         % b = 1.5;
+         % [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+         % figure; loglog(q,-dqdt,'o')
+         % also useful to see this:
+         % baseflow.Qnonlin(a,b,q0,t,true)
+
+         % f = baseflow.fitab(q,dqdt,'mean'); ab = f.ab
+         % f = baseflow.fitab(q,dqdt,'ols'); ab = f.ab
+         % f = baseflow.fitab(q,dqdt,'nls'); ab = f.ab
+         % f = baseflow.fitab(q,dqdt,'median'); ab = f.ab
+
+         % generate the test data
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+
+         % fit the data
+         switch FitMethod
+            case {'mean','median'}
+               Fit = baseflow.fitab(q,dqdt,FitMethod,'order',b);
+            otherwise
+               Fit = baseflow.fitab(q,dqdt,FitMethod);
+         end
+
+         % Get the expected result
+         expected = [a;b];
+
+         % Get the actual result
+         returned = Fit.ab;
+
+         % for testing:
+         % f = baseflow.fitab(q,dqdt,FitMethod); returned = f.ab
+         % isequal(returned,expected)
+
+         % Allow a 1 percent relative error in each of a and b
+         tol = [0.01; 0.01];
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual(returned,expected,'RelTol',tol)
+
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_fitab_order1(testCase,FitMethod)
+
+         % generate nonlinear (b = 1.5) test data
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+
+         % fit with 'order' = 1: methods that estimate the slope redirect
+         % to 'mean'; 'mean' and 'median' force the slope directly
+         Fit = baseflow.fitab(q,dqdt,FitMethod,'order',1);
+
+         % Verify the fitted exponent is forced to 1 (linear reservoir)
+         returned = Fit.ab(2); % Fit.ab stores [a; b]
+         expected = 1;
+         testCase.verifyEqual(returned,expected);
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_fitab_order1_envelope(testCase)
+
+         % generate test data with deterministic scatter so the 0.95
+         % quantile envelope and the mean give different intercepts
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+         q = q .* (1 + 0.2*sin((1:numel(q))'));
+
+         % 'envelope' with 'order' = 1 must stay an envelope fit through
+         % 'refqtls'; it must not redirect to the 'mean' method
+         FitE = baseflow.fitab(q,dqdt,'envelope', ...
+            'refqtls',[0.95 0.95],'order',1);
+         FitM = baseflow.fitab(q,dqdt,'mean','order',1);
+
+         % Verify the slope is 1 and the intercept differs from the mean
+         % fit. Fit.ab stores [a; b].
+         b_returned = FitE.ab(2);
+         b_expected = 1;
+         testCase.verifyEqual(b_returned,b_expected);
+         a_returned = FitE.ab(1);
+         a_notexpected = FitM.ab(1);
+         testCase.verifyNotEqual(a_returned,a_notexpected);
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_fitab_order_scope(testCase,OrderOption)
+
+         % generate nonlinear (b = 1.5) test data
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+
+         % 'qtl' passes 'order' to quantreg as the polynomial degree, so
+         % 'order' = 1 must run quantile regression, not the 'mean' method.
+         % 'qtl' with no 'order' must apply the quantreg default of 1 and
+         % run quantile regression. A nan parser default for 'order' crashes it.
+         Fit = baseflow.fitab(q,dqdt,'qtl',OrderOption{:});
+         returned = Fit.fselect;
+         expected = 'qtl';
+         testCase.verifyEqual(returned,expected);
+
+         % 'mle' is unsupported and must error with or without 'order' = 1
+         testCase.verifyError( ...
+            @() baseflow.fitab(q,dqdt,'mle',OrderOption{:}), ?MException);
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_fitab_ols_confint(testCase)
+
+         % The Curve Fitting Toolbox fit and confint give independent expected
+         % values for the 'ols' method, so skip the test without the toolbox
+         testCase.assumeFalse(isempty(ver('curvefit')), ...
+            'test_fitab_ols_confint requires the Curve Fitting Toolbox');
+
+         % generate nonlinear (b = 1.5) test data with deterministic
+         % scatter, unequal weights, and a mask that drops every fifth point
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+         k = (1:numel(q))';
+         q = q .* (1 + 0.2*sin(k));
+         weights = 1 + mod(k,3);
+         mask = mod(k,5) ~= 0;
+         alpha = 0.9;
+
+         % fit -dq/dt = aQ^b with the 'ols' method
+         Fit = baseflow.fitab(q,dqdt,'ols','weights',weights, ...
+            'mask',mask,'alpha',alpha);
+
+         % Expected values: a weighted poly1 fit of log(-dq/dt) on log(q).
+         % fitab documents that masked points get zero weight.
+         fopts = fitoptions('Method','LinearLeastSquares', ...
+            'Weights',weights.*mask);
+         f = fit(log(q),log(-dqdt),'poly1',fopts);
+
+         % coeffvalues is [slope intercept]. confint has rows [lower; upper]
+         % with the same column order. Fit stores a = exp(intercept).
+         p = coeffvalues(f);
+         pci = confint(f,alpha);
+         ab_expected = [exp(p(2)); p(1)];
+         ci_expected = [exp(pci(:,2)'); pci(:,1)'];
+
+         ab_returned = Fit.ab;
+         ci_returned = [Fit.aL Fit.aH; Fit.bL Fit.bH];
+
+         % Both are least-squares solutions, so allow rounding error only
+         tol = 1e-10;
+         testCase.verifyEqual(ab_returned,ab_expected,'RelTol',tol);
+         testCase.verifyEqual(ci_returned,ci_expected,'RelTol',tol);
+      end
+
+   end
+end
diff --git a/tests/test_fitevents.m b/tests/test_fitevents.m
index 9c3ded6..4606e2a 100644
--- a/tests/test_fitevents.m
+++ b/tests/test_fitevents.m
@@ -1,13 +1,18 @@
 classdef test_fitevents < matlab.unittest.TestCase
-   %TEST_FITEVENTS Test the fitevents plotfits option.
+   %TEST_FITEVENTS Test the fitevents plotfits, fitorder, and ctsmethod options.
    %
    % fitevents passes plotfits to getdqdt, which draws one figure per
-   % event. The cases use a short slice of the example data, so the event
-   % loop stays fast.
+   % event. The plotfits cases use a short slice of the example data, so
+   % the event loop stays fast. fitevents must pass fitorder to fitab and
+   % ctsmethod to getdqdt. The ctsmethod cases fit the first event of the
+   % full example record.
 
    properties (TestParameter)
       % Whether the call asks for the event fit plots.
       plotfits = struct('plotsOff', false, 'plotsOn', true)
+
+      % The constant-time-step stencils fitevents passes to getdqdt.
+      CtsMethod = {'B1','B2','F1','F2','C2','C4'};
    end
 
    properties
@@ -15,6 +20,10 @@
       % test.
       Events
       figsbefore
+
+      % The first recession event in the example data. The class setup
+      % builds it once so the fitevents tests do not repeat getevents.
+      firstevent
    end
 
    methods (TestClassSetup)
@@ -26,6 +35,19 @@ function detectevents(testCase)
          testCase.Events = baseflow.getevents(T(slice), Q(slice), ...
             R(slice), baseflow.setopts('getevents'));
       end
+
+      function loadfirstevent(testCase)
+         % Detect events in the example data. Keep only the first event so
+         % each fitevents call fits one event and the tests stay fast.
+         [T, Q, R] = baseflow.loadExampleData();
+         Events = baseflow.getevents(T, Q, R);
+         ievent = Events.eventTags == 1;
+         testCase.firstevent = struct( ...
+            'eventTime', Events.eventTime(ievent), ...
+            'eventFlow', Events.eventFlow(ievent), ...
+            'eventRain', Events.eventRain(ievent), ...
+            'eventTags', Events.eventTags(ievent));
+      end
    end
 
    methods (TestMethodSetup)
@@ -57,5 +79,46 @@ function test_plotfitsDrawsEventFigures(testCase, plotfits)
             testCase.verifyEqual(newfigs_returned, newfigs_expected)
          end
       end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_fitevents_fitorder(testCase)
+
+         % build a one-event Events structure from nonlinear test data
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         % Note: generateTestData returns its own t, sized to match q
+         [t,q] = baseflow.generateTestData(a,b,q0,t);
+         Events.eventTime = t;
+         Events.eventFlow = q;
+         Events.eventRain = zeros(size(q));
+         Events.eventTags = ones(size(q));
+
+         % fitevents must pass 'fitorder' to fitab so the event is fit
+         % with a linear reservoir model
+         [~,Results] = baseflow.fitevents(Events,'fitorder',1);
+
+         % Verify a fit was returned and the exponent is forced to 1
+         returned = Results.b;
+         testCase.verifyNotEmpty(returned);
+         expected = ones(size(returned));
+         testCase.verifyEqual(returned,expected);
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_fitevents_ctsmethod(testCase,CtsMethod)
+
+         % fitevents must pass 'ctsmethod' to getdqdt, so the dq/dt it
+         % stores for the event equals a direct getdqdt call
+         Event = testCase.firstevent;
+         [~,expected] = baseflow.getdqdt(Event.eventTime, ...
+            Event.eventFlow,Event.eventRain,'CTS','ctsmethod',CtsMethod);
+         returned = baseflow.fitevents(Event,'derivmethod','CTS', ...
+            'ctsmethod',CtsMethod,'plotfits',false);
+         testCase.verifyEqual(returned.dqdt,expected);
+      end
    end
 end
diff --git a/tests/test_getdqdt.m b/tests/test_getdqdt.m
index 3cd0596..d1a41a1 100644
--- a/tests/test_getdqdt.m
+++ b/tests/test_getdqdt.m
@@ -1,13 +1,18 @@
 classdef test_getdqdt < matlab.unittest.TestCase
-   %TEST_GETDQDT Test the getdqdt fit-plot option.
+   %TEST_GETDQDT Test the getdqdt derivative and fit-plot option.
    %
-   % getdqdt passes plotfits to plotdqdt, which fits the point cloud to
-   % draw its line. fitmethod 'none' asks for no fit, so getdqdt draws
-   % nothing for that method.
+   % The CTS derivative of baseflow.generateTestData output with the
+   % default stencil equals the backward difference of q. getdqdt passes
+   % plotfits to plotdqdt, which fits the point cloud to draw its line.
+   % fitmethod 'none' asks for no fit, so getdqdt draws nothing for that
+   % method.
 
    properties (TestParameter)
       % The fit method getdqdt passes to plotdqdt.
       fitmethod = struct('nls', 'nls', 'none', 'none')
+
+      % The derivative method of the backward-difference test.
+      DerivMethod = {'CTS'}; % {'ETS','VTS','CTS'}
    end
 
    properties
@@ -82,6 +87,36 @@ function test_plotfitsByFitmethod(testCase, fitmethod)
          end
          testCase.verifyEqual(newfigs_returned, newfigs_expected)
       end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_ctsBackwardDifference(testCase,DerivMethod)
+
+         % define the test data
+         a = 1e-2;
+         b = 1.5;
+         q0 = 1;
+         [t, q] = baseflow.generateTestData(a,b,q0);
+
+         % Calculate expected result for CTS method
+         dq = q-[nan; q(1:end-1)];
+         dt = (t(2)-t(1));
+         expected = dq./dt;
+
+         % Get the actual result. The test data has no rainfall record.
+         [~,returned] = baseflow.getdqdt(t,q,[],DerivMethod);
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual(returned,expected)
+
+         % for testing:
+         % DerivMethod = 'CTS';
+         % [~,returned] = baseflow.getdqdt(t,q,[],DerivMethod);
+         % isequal(returned,expected)
+         % scatterfit(returned,expected)
+
+      end
+
    end
 
    methods (Access = private)
diff --git a/tests/test_getstring.m b/tests/test_getstring.m
new file mode 100644
index 0000000..1a28774
--- /dev/null
+++ b/tests/test_getstring.m
@@ -0,0 +1,31 @@
+classdef test_getstring < matlab.unittest.TestCase
+   %TEST_GETSTRING Test the latex labels of baseflow.getstring.
+
+   properties (TestParameter)
+      % The variables whose latex label getstring returns.
+      VarStr = {'Q','dQdt','aQb'};
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_variableLabel(testCase,VarStr)
+
+         switch VarStr
+            case 'Q'
+               expected = '$Q$';
+            case 'dQdt'
+               expected = '$-\mathrm{d}Q/\mathrm{d}t$';
+            case 'aQb'
+               expected = '$-\mathrm{d}Q/\mathrm{d}t = aQ^b$';
+         end
+
+         % Get actual result
+         returned = baseflow.getstring(VarStr);
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual(returned,expected)
+      end
+   end
+end
diff --git a/tests/test_islocalmax.m b/tests/test_islocalmax.m
index bb0bc91..256e087 100644
--- a/tests/test_islocalmax.m
+++ b/tests/test_islocalmax.m
@@ -1,101 +1,153 @@
-function tests = test_islocalmax
+classdef test_islocalmax < matlab.unittest.TestCase
    %TEST_ISLOCALMAX Test baseflow/private/islocalmax.m
-   tests = functiontests(localfunctions);
-end
-
-function setup(testCase)
-
-   % Snapshot open figures; teardown closes only figures created here.
-   testCase.TestData.figsbefore = findall(0, 'Type', 'figure');
-
-   % generate test data
-   [T,Q] = baseflow.loadExampleData();
-
-   % Select a fixed window of the example record as the test signal.
-   t = T(100:200);
-   A = Q(100:200);
-   s = sign(diff(A));
-
-   % Find points where the second order difference is negative and pad the
-   % result to be of the correct size. Note: for the simplest case, the local
-   % max can be found here, but end points are found at the end.
-   pad = true(1, size(A,2));
-   maxVals = [~pad; diff(s) < 0; ~pad];
-
-   % generate test figure
-   figure; plot(t,A, 'HandleVisibility', 'off'); hold on;
-   plot(t(s==0),A(s==0),'o', 'HandleVisibility', 'off')
-   plot(t(s==1),A(s==1),'o', 'HandleVisibility', 'off')
-   plot(t(s==-1),A(s==-1),'o', 'HandleVisibility', 'off')
-   scatter(t(maxVals),A(maxVals), 100, 'filled', 'displayname', 'Peak')
-   datetick; title('test: islocalmax'); legend
-
-   % Ignore repeated values.
-   uniquePts = [pad; (A(2:end,:) ~= A(1:(end-1),:))];
-   if isfloat(A) && any(isnan(A(:)))
-      uniquePts = uniquePts & ...
-         [pad; ~(isnan(A(2:end,:)) & isnan(A(1:(end-1),:)))];
+   %
+   % The private islocalmax wraps peakfinder, because Octave has no
+   % islocalmax. It must find the peak of a window of the example record,
+   % and the same interior maxima as the MATLAB function of the same name.
+   % tests/test_islocalmin.m holds the same signals for the minima.
+
+   properties (TestParameter)
+      % Short signals with one peak, one valley, or several extrema. The
+      % one-extremum signals check the peakfinder monotone branch.
+      ExtremaSignal = struct( ...
+         'onepeak', [1 2 3 2 1], ...
+         'peakthenfall', [2 3 1 0 -1], ...
+         'threepoints', [0 1 0], ...
+         'twopeaks', [1 2 3 2 5 1], ...
+         'peakvalleypeak', [10 12 15 13 11 12 11], ...
+         'onevalley', [10 9 8 9 10]);
    end
 
-   % Get the inflection points: every place where the first order
-   % difference of A changes sign.  Remove duplicate points.  Consider end
-   % points inflection points.
-   inflectionPts = [pad; (s(1:(end-1),:) ~= s(2:end, :)) & ...
-      uniquePts(2:(end-1),:); pad];
-
-   % Check the result
-   expectedPeakIndex = find(maxVals);
-   expectedUniquePoints = find(uniquePts);
-   expectedInflectionPoints = find(inflectionPts);
-
-   % Save the test data
-   testCase.TestData.A = A;
-   testCase.TestData.expectedPeakIndex = expectedPeakIndex;
-   testCase.TestData.expectedUniquePoints = expectedUniquePoints;
-   testCase.TestData.expectedInflectionPoints = expectedInflectionPoints;
-
-end
-
-function teardown(testCase)
-   % Close the figures the setup function created (see tests/closenewfigs.m).
-   closenewfigs(testCase.TestData.figsbefore)
-end
+   properties
+      % The open-figure snapshot and the test_peakLocations fixture data.
+      TestData
+   end
 
-function test_peakLocations(testCase)
-   % Compare peak locations from the custom islocalmax, peakfinder, and the
-   % builtin islocalmax. Note: a local test named test_peakfinder resolves
-   % to the tests/test_peakfinder.m class and breaks suite creation.
+   methods (TestMethodSetup)
+      function snapshotfigures(testCase)
+         % Snapshot open figures; teardown closes only figures created here.
+         testCase.TestData.figsbefore = findall(0, 'Type', 'figure');
+      end
+   end
 
-   customislocalmax = baseflow.privatefunction('islocalmax');
+   methods (TestMethodTeardown)
+      function teardown(testCase)
+         % Close the figures the test created (see tests/closenewfigs.m).
+         closenewfigs(testCase.TestData.figsbefore)
+      end
+   end
 
-   A = testCase.TestData.A;
-   peak_expected = testCase.TestData.expectedPeakIndex;
+   methods (Test)
+
+      function test_peakLocations(testCase)
+         % Compare peak locations from the custom islocalmax, peakfinder, and the
+         % builtin islocalmax. Note: a local test named test_peakfinder resolves
+         % to the tests/test_peakfinder.m class and breaks suite creation.
+
+         % Build the example-record window and its expected peaks.
+         preparepeakdata(testCase);
+
+         customislocalmax = baseflow.privatefunction('islocalmax');
+
+         A = testCase.TestData.A;
+         peak_expected = testCase.TestData.expectedPeakIndex;
+
+         [tf_islocalmax,p_islocalmax] = islocalmax(A); %#ok<*ASGLU>
+         try
+            [~,i_findpeaks,~,p_findpeaks] = findpeaks(A);
+         catch
+         end
+         tf_custom = customislocalmax(A);
+
+         % get the index of the peak
+         i_peakfinder = baseflow.deps.peakfinder(A); %#ok<*NASGU>
+         i_islocalmax = find(tf_islocalmax);
+         peak_returned = find(tf_custom);
+
+         % compare peak locations
+         msg = 'baseflow/private/islocalmax failed to identify the peak correctly';
+         testCase.verifyEqual(peak_returned, peak_expected, msg);
+
+         % All three implementations agree on the fixture data. This check runs
+         % the index comparison from the commented script block below. The
+         % prominence comparison against findpeaks does not run: findpeaks
+         % needs the undeclared Signal Processing Toolbox, and the index
+         % comparison already checks that the implementations agree.
+         agreement_returned = {i_peakfinder(:), i_islocalmax(:)};
+         agreement_expected = {peak_returned(:), peak_returned(:)};
+         testCase.verifyEqual(agreement_returned, agreement_expected, ...
+            'peakfinder, islocalmax, and the custom islocalmax disagree')
+      end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_islocalextrema(testCase, ExtremaSignal)
+
+         % The private peakfinder wrappers must find the same interior
+         % extrema as the MATLAB functions of the same name
+         customfunction = baseflow.privatefunction('islocalmax');
+         expected = islocalmax(ExtremaSignal);
+         returned = customfunction(ExtremaSignal);
+         testCase.verifyEqual(returned, expected)
+      end
+   end
 
-   [tf_islocalmax,p_islocalmax] = islocalmax(A); %#ok<*ASGLU>
-   try
-      [~,i_findpeaks,~,p_findpeaks] = findpeaks(A);
-   catch
+   methods (Access = private)
+      function preparepeakdata(testCase)
+         %PREPAREPEAKDATA Build the test_peakLocations fixture.
+         %
+         %  preparepeakdata(testCase) loads a window of the example
+         %  record, draws it, and stores the signal and its expected
+         %  peak, unique, and inflection indices in testCase.TestData.
+
+         % generate test data
+         [T,Q] = baseflow.loadExampleData();
+
+         % Select a fixed window of the example record as the test signal.
+         t = T(100:200);
+         A = Q(100:200);
+         s = sign(diff(A));
+
+         % Find points where the second order difference is negative and pad the
+         % result to be of the correct size. Note: for the simplest case, the local
+         % max can be found here, but end points are found at the end.
+         pad = true(1, size(A,2));
+         maxVals = [~pad; diff(s) < 0; ~pad];
+
+         % generate test figure
+         figure; plot(t,A, 'HandleVisibility', 'off'); hold on;
+         plot(t(s==0),A(s==0),'o', 'HandleVisibility', 'off')
+         plot(t(s==1),A(s==1),'o', 'HandleVisibility', 'off')
+         plot(t(s==-1),A(s==-1),'o', 'HandleVisibility', 'off')
+         scatter(t(maxVals),A(maxVals), 100, 'filled', 'displayname', 'Peak')
+         datetick; title('test: islocalmax'); legend
+
+         % Ignore repeated values.
+         uniquePts = [pad; (A(2:end,:) ~= A(1:(end-1),:))];
+         if isfloat(A) && any(isnan(A(:)))
+            uniquePts = uniquePts & ...
+               [pad; ~(isnan(A(2:end,:)) & isnan(A(1:(end-1),:)))];
+         end
+
+         % Get the inflection points: every place where the first order
+         % difference of A changes sign.  Remove duplicate points.  Consider end
+         % points inflection points.
+         inflectionPts = [pad; (s(1:(end-1),:) ~= s(2:end, :)) & ...
+            uniquePts(2:(end-1),:); pad];
+
+         % Check the result
+         expectedPeakIndex = find(maxVals);
+         expectedUniquePoints = find(uniquePts);
+         expectedInflectionPoints = find(inflectionPts);
+
+         % Save the test data
+         testCase.TestData.A = A;
+         testCase.TestData.expectedPeakIndex = expectedPeakIndex;
+         testCase.TestData.expectedUniquePoints = expectedUniquePoints;
+         testCase.TestData.expectedInflectionPoints = expectedInflectionPoints;
+
+      end
    end
-   tf_custom = customislocalmax(A);
-
-   % get the index of the peak
-   i_peakfinder = baseflow.deps.peakfinder(A); %#ok<*NASGU>
-   i_islocalmax = find(tf_islocalmax);
-   peak_returned = find(tf_custom);
-
-   % compare peak locations
-   msg = 'baseflow/private/islocalmax failed to identify the peak correctly';
-   testCase.verifyEqual(peak_returned, peak_expected, msg);
-
-   % All three implementations agree on the fixture data. This check runs
-   % the index comparison from the commented script block below. The
-   % prominence comparison against findpeaks does not run: findpeaks
-   % needs the undeclared Signal Processing Toolbox, and the index
-   % comparison already checks that the implementations agree.
-   agreement_returned = {i_peakfinder(:), i_islocalmax(:)};
-   agreement_expected = {peak_returned(:), peak_returned(:)};
-   testCase.verifyEqual(agreement_returned, agreement_expected, ...
-      'peakfinder, islocalmax, and the custom islocalmax disagree')
 end
 
 % Below here is script-based test
diff --git a/tests/test_islocalmin.m b/tests/test_islocalmin.m
new file mode 100644
index 0000000..2001c8b
--- /dev/null
+++ b/tests/test_islocalmin.m
@@ -0,0 +1,35 @@
+classdef test_islocalmin < matlab.unittest.TestCase
+   %TEST_ISLOCALMIN Test baseflow/private/islocalmin.m
+   %
+   % The private islocalmin wraps peakfinder, because Octave has no
+   % islocalmin. It must find the same interior minima as the MATLAB
+   % function of the same name. tests/test_islocalmax.m holds the same
+   % signals for the maxima.
+
+   properties (TestParameter)
+      % Short signals with one peak, one valley, or several extrema. The
+      % one-extremum signals check the peakfinder monotone branch.
+      ExtremaSignal = struct( ...
+         'onepeak', [1 2 3 2 1], ...
+         'peakthenfall', [2 3 1 0 -1], ...
+         'threepoints', [0 1 0], ...
+         'twopeaks', [1 2 3 2 5 1], ...
+         'peakvalleypeak', [10 12 15 13 11 12 11], ...
+         'onevalley', [10 9 8 9 10]);
+   end
+
+   methods (Test)
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_islocalextrema(testCase, ExtremaSignal)
+
+         % The private peakfinder wrappers must find the same interior
+         % extrema as the MATLAB functions of the same name
+         customfunction = baseflow.privatefunction('islocalmin');
+         expected = islocalmin(ExtremaSignal);
+         returned = customfunction(ExtremaSignal);
+         testCase.verifyEqual(returned, expected)
+      end
+   end
+end
diff --git a/tests/test_plfitb.m b/tests/test_plfitb.m
index 20fcb26..90e88ae 100644
--- a/tests/test_plfitb.m
+++ b/tests/test_plfitb.m
@@ -1,13 +1,14 @@
 classdef test_plfitb < matlab.unittest.TestCase
-   %TEST_PLFITB Test the plfitb bootstrap seed, tau pole, and plot legend.
+   %TEST_PLFITB Test the plfitb exponent, bootstrap seed, tau pole, and legend.
    %
-   % plfitb bootstraps with baseflow.deps.plvar, which resamples the data,
+   % plfitb recovers the exponent of a power-law sample. plfitb bootstraps with baseflow.deps.plvar, which resamples the data,
    % so a caller seed must fix the replicates. tau = tau0*(2-b)/(3-2*b) has
    % a pole at b = 3/2, which is alpha = 2, and plfitb warns when a
    % replicate reaches it. The legend plfitb draws through plplotb carries
    % one bootstrap standard deviation, so it must name no coverage level.
-   % Every sample is a deterministic Pareto draw, which leaves the
-   % bootstrap resampling as the only random step.
+   % Every sample except the exponent-recovery sample is a deterministic
+   % Pareto draw, which leaves the bootstrap resampling as the only random
+   % step.
    %
    % See also: test_plfitb_hanel
 
@@ -19,6 +20,9 @@
       % Pareto exponents at and near the tau pole. Both put several of the
       % replicates at or below alpha = 2.
       poleexponent = struct('atpole', 2.00, 'nearpole', 2.05)
+
+      % Pareto exponents the exponent-recovery test samples.
+      PowerLawExponent = {1.5, 2.0, 2.5, 3.0, 3.5};
    end
 
    properties (Constant)
@@ -168,6 +172,25 @@ function test_poleWarningKeepsReturnedValues(testCase, poleexponent)
             returned.tau + returned.BootFit.tau_sig)
       end
 
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_recoversExponent(testCase,PowerLawExponent)
+
+         % generate power-law distributed test data
+         x = (1-rand(10000,1)).^(-1/(PowerLawExponent-1));
+
+         % compute the fit
+         [~,returned] = baseflow.plfitb(x); % the second output is alpha
+         expected = PowerLawExponent;
+
+         % The estimate from random samples varies. Allow 0.1 absolute error.
+         tol = 0.1;
+
+         % Verify that the actual result matches the expected result
+         testCase.verifyEqual(returned,expected,'AbsTol',tol);
+
+      end
+
       function test_noPoleWarningAwayFromPole(testCase)
          % A sample with alpha near 3.5 keeps every replicate far from the
          % pole, so plfitb issues no warning.
diff --git a/tests/test_plotdqdt.m b/tests/test_plotdqdt.m
index a1c6fdc..16a33d2 100644
--- a/tests/test_plotdqdt.m
+++ b/tests/test_plotdqdt.m
@@ -6,7 +6,8 @@
    % decade inside the final limits carries a tick, and the axislimits
    % option selects how far a limit moves to reach its decade. The labels
    % take an explicit color and font size, the rain circles reach the
-   % legend, and a supplied axes receives every part of the figure.
+   % legend, and a supplied axes receives every part of the figure. The
+   % labelplot option draws the reference-line arrows only on request.
 
    properties (TestParameter)
       % The axis-limit policies. 'none' keeps the limits the data sets.
@@ -319,6 +320,38 @@ function test_drawsInSuppliedAxes(testCase)
          testCase.verifyEqual(numel(findall(0, 'Type', 'figure')), ...
             nfigs_expected)
       end
+
+      %-------------------------------------------
+      %-------------------------------------------
+      function test_plotdqdt_labelplot(testCase)
+
+         % generate nonlinear (b = 1.5) test data
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+
+         % Count refline arrows. labelrefline draws each one as a patch
+         % with HandleVisibility off, so findall finds it and findobj does
+         % not.
+         arrowtype = 'patch';
+
+         % 'labelplot' defaults to false: no refline arrows
+         h = baseflow.plotdqdt(q,dqdt);
+         narrows_returned = numel(findall(h.ax,'Type',arrowtype));
+         narrows_expected = 0;
+         testCase.verifyEqual(narrows_returned,narrows_expected);
+         % Close only the figure this test created, so a pre-existing user
+         % figure survives; plotdqdt opens a fresh figure for the next call.
+         closenewfigs(testCase.figsbefore)
+
+         % 'labelplot' true draws at least one refline arrow (see
+         % labelReflines)
+         h = baseflow.plotdqdt(q,dqdt,'labelplot',true);
+         nlabeled_returned = numel(findall(h.ax,'Type',arrowtype));
+         testCase.verifyGreaterThan(nlabeled_returned,0);
+      end
    end
 end
 
diff --git a/tests/test_setopts.m b/tests/test_setopts.m
new file mode 100644
index 0000000..9aded17
--- /dev/null
+++ b/tests/test_setopts.m
@@ -0,0 +1,13 @@
+function tests = test_setopts
+   %TEST_SETOPTS Test the option defaults of baseflow.setopts.
+   tests = functiontests(localfunctions);
+end
+
+function test_setopts_ctsmethod(testCase)
+
+   % The fitevents options default to the traditional backward
+   % first-order stencil
+   returned = baseflow.setopts('fitevents');
+   expected = 'B1';
+   testCase.verifyEqual(returned.ctsmethod,expected);
+end

From 8fd3cdf0c09844dcb9fac940a6c45cbb23d731ec Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:58 -0700
Subject: [PATCH 05/28] fix(baseflow): return Inf for a divergent mean tau and
 NaN expected flow

The mean tau of a Pareto tail, tau0*(2-b)/(3-2*b), diverges at and
below the tau pole at alpha = 2. There the formula gave a negative
value: gpfitb reported tauExp = -10.01 for alpha = 1.5. The private
expectedtau returns Inf there and NaN where no Pareto tail exists. It
alone raises baseflow:expectedtau:tauPole, with the count of values of
b that give no finite mean tau. gpfitb, plfitb, plplotb, and
getfunction('expectedTau') call it. The gpfitb and plplotb labels omit
a mean that is not finite.

expectedQ returns NaN for Qexp, Q0, pQexp, and pQ0 when tau is not
finite, rather than 0 or complex values. fdcurve returns one reference
value per point, NaN for a NaN point, and leaves missing flows out of
the plotting positions. A caller that caught
baseflow:plfitb:tauPoleReplicates must catch
baseflow:expectedtau:tauPole.
---
 CHANGELOG.md                            |  22 +++++
 tests/Contents.m                        |   7 +-
 tests/test_drawarrow.m                  |   6 +-
 tests/test_expectedQ.m                  |  79 ++++++++++++++++++
 tests/test_fdcurve.m                    |  24 ++++++
 tests/test_getfunction.m                |  77 +++++++++++++++++
 tests/test_gpfitb.m                     | 106 ++++++++++++++++++++++++
 tests/test_plfitb.m                     |  96 ++++++++++++++++-----
 tests/test_plplotb.m                    |  35 ++++++++
 toolbox/+baseflow/Contents.m            |   1 +
 toolbox/+baseflow/expectedQ.m           |  16 +++-
 toolbox/+baseflow/fdcurve.m             |  26 +++---
 toolbox/+baseflow/getfunction.m         |  10 ++-
 toolbox/+baseflow/gpfitb.m              |  19 ++++-
 toolbox/+baseflow/plfitb.m              |  21 ++---
 toolbox/+baseflow/plplotb.m             |  16 ++--
 toolbox/+baseflow/private/expectedtau.m |  42 ++++++++++
 17 files changed, 541 insertions(+), 62 deletions(-)
 create mode 100644 tests/test_expectedQ.m
 create mode 100644 tests/test_fdcurve.m
 create mode 100644 tests/test_getfunction.m
 create mode 100644 tests/test_gpfitb.m
 create mode 100644 tests/test_plplotb.m
 create mode 100644 toolbox/+baseflow/private/expectedtau.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index a7f0438..ccb768f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -11,9 +11,31 @@ semantic versioning.
 - The unit tests of `tests/TestBaseflow.m` live in per-function suites,
   `tests/test_<function_name>.m`. `TestBaseflow` keeps the workflow
   checks that span the event-detection entry points.
+- One private function, `expectedtau`, computes the mean tau for
+  `gpfitb`, `plfitb`, `plplotb`, and `baseflow.getfunction`. It alone
+  raises the pole warning, `baseflow:expectedtau:tauPole`, with the count
+  of values of b that give no finite mean tau. That identifier replaces
+  `baseflow:plfitb:tauPoleReplicates`.
 
 ### Fixed
 
+- `gpfitb` and `plfitb` return Inf for the mean tau at or below the tau
+  pole at alpha 2. The mean of a Pareto tail diverges there. The formula
+  tau0*(2-b)/(3-2*b) is negative below the pole, so `gpfitb` reported a
+  tauExp of -10.01 for a sample with alpha 1.5. The mean is NaN where no
+  Pareto tail exists, at alpha 1 or below.
+- `gpfitb` and `plplotb` draw no mean-tau label where the mean or its
+  bounds diverge, so no label names a negative or infinite tau.
+- A `plfitb` bootstrap replicate at or below alpha 2 has an infinite tau,
+  so `tau_sig`, `tau_L`, and `tau_H` are NaN.
+- `expectedQ` returns NaN for `Qexp`, `Q0`, `pQexp`, and `pQ0` when tau
+  is not finite. So `globalfit` reports no expected flow on data with b
+  at or above 3/2. It returned 0 at b = 3/2 and complex values between
+  3/2 and 2, where the negative tau entered a fractional power.
+- `fdcurve` returns a reference value for each reference point, and NaN
+  for a point that is NaN or above every flow. It sized its output from
+  the first point only. Missing flows stay out of the plotting
+  positions.
 - `gpfitb`, `plplotb` and `fitphidist` print nothing when they label a
   figure. The private `drawarrow` assigned its output whether or not the
   caller asked for it, and no call site ended with a semicolon, so each
diff --git a/tests/Contents.m b/tests/Contents.m
index 1cad465..c14adcd 100644
--- a/tests/Contents.m
+++ b/tests/Contents.m
@@ -21,8 +21,10 @@
 %   test_demos             - Run every demo script in toolbox/demos/mfiles headless
 %   test_drawarrow         - Test the arrow of a reference-line label
 %   test_dependencies      - Test the dependency tooling and list agreement
+%   test_fdcurve           - Test the reference points of baseflow.fdcurve
 %   test_eqstrings         - Test the equation label helpers
 %   test_eventfinder       - Test the events baseflow.eventfinder finds in a sine
+%   test_expectedQ         - Test the expected flows of baseflow.expectedQ
 %   test_fillnans          - Test the private fillnans helper
 %   test_fitab             - Test the fit methods and options of baseflow.fitab
 %   test_fitcts            - Test the constant-time-step dq/dt method
@@ -30,7 +32,9 @@
 %   test_fitevents         - Test the fitevents plotfits, fitorder, and ctsmethod options
 %   test_fitopts           - Test the fitab fitopts pass-through
 %   test_getdqdt           - Test the getdqdt derivative and fit-plot option
+%   test_getfunction       - Test the expected-tau handle of baseflow.getfunction
 %   test_getstring         - Test the latex labels of baseflow.getstring
+%   test_gpfitb            - Test the gpfitb mean tau above and below the tau pole
 %   test_hyetograph        - Test the figure that baseflow.hyetograph draws in
 %   test_internal          - Test the toolbox internal functions
 %   test_islabelcolor      - Test the private islabelcolor validator
@@ -42,11 +46,12 @@
 %   test_loadflow          - Test the loadflow unit conversions
 %   test_nstaruncertainty  - Test the private nstaruncertainty helper
 %   test_peakfinder        - Test the vendored +deps/peakfinder function
-%   test_plfitb            - Test the plfitb exponent, bootstrap seed, tau pole, and legend
+%   test_plfitb            - Test the plfitb exponent, mean tau, tau pole, and legend
 %   test_plfitb_hanel      - Test the r_plfit arguments plfitb's 'hanel' passes
 %   test_plotaquifertrend  - Test the plotaquifertrend branch handles
 %   test_plotdqdt          - Test the plotdqdt reference lines, ticks, and labels
 %   test_plotrefline       - Test the plotrefline label position
+%   test_plplotb           - Test the plplotb mean-tau label below the tau pole
 %   test_pointcloudplot    - Test the pointcloudplot ticks, limits, and axes
 %   test_preparecalendar   - Test the private preparecalendar helper
 %   test_relayoutloglogtext - Test the angle reset of a rotated log-log label
diff --git a/tests/test_drawarrow.m b/tests/test_drawarrow.m
index e564b93..fc01ede 100644
--- a/tests/test_drawarrow.m
+++ b/tests/test_drawarrow.m
@@ -199,9 +199,9 @@ function test_emptyColorDrawsTheDefault(testCase)
       function test_nonpositiveLogCoordinateDrawsNothing(testCase)
          % log10 of a value at or below zero is complex, and a complex
          % coordinate draws the arrow reflected through the origin, at a
-         % point the data never reaches. gpfitb reaches this with a
-         % negative tauExp, which the tail of a power law below alpha 2
-         % gives it.
+         % point the data never reaches. The mean-tau formula
+         % tau0*(2-b)/(3-2*b) is negative below the tau pole at alpha 2,
+         % so a label of that value reaches this.
          ax = testCase.testaxes('log', 'log');
          negativepoint = [-10 1e3];
 
diff --git a/tests/test_expectedQ.m b/tests/test_expectedQ.m
new file mode 100644
index 0000000..31e5b30
--- /dev/null
+++ b/tests/test_expectedQ.m
@@ -0,0 +1,79 @@
+classdef test_expectedQ < matlab.unittest.TestCase
+   %TEST_EXPECTEDQ Test the expected flows of baseflow.expectedQ.
+   %
+   % Qexp = (a*tau)^(1/(1-b)) and Q0 = Qexp*(3-b)/(2-b). With a = 0.01,
+   % b = 1.5, and tau = 400 days, a*tau = 4. So Qexp = 4^-2 = 0.0625 and
+   % Q0 = 3*Qexp = 0.1875. pQexp and pQ0 are the fdcurve positions
+   % 1 - M/(N+1) of the two flows, where M counts the flows at or above
+   % each one. A mean tau that is not finite gives NaN for all four.
+   %
+   % See also: test_plfitb, test_getfunction
+
+   properties (TestParameter)
+      % tau values with no mean: beyond the tau pole, and with no tail.
+      notfinite = struct('diverges', Inf, 'notail', NaN)
+   end
+
+   properties (Constant)
+      % Recession parameters of the hand-computed case.
+      a = 0.01
+      b = 1.5
+
+      % Four flows: one below Qexp, one between Qexp and Q0, and two
+      % above Q0. M is 3 for Qexp and 2 for Q0, and N is 4.
+      flow = [0.05; 0.1; 0.2; 0.3]
+
+      % Rounding error allowed in the hand-computed values.
+      tolerance = 1e-12
+   end
+
+   methods (Test)
+      function test_finiteTauGivesFlows(testCase)
+         % A finite tau gives the hand-computed flows and positions.
+         tau = 400;
+         expected = [0.0625 0.1875 1-3/5 1-2/5];
+
+         [Qexp, Q0, pQexp, pQ0] = baseflow.expectedQ(testCase.a, ...
+            testCase.b, tau, [], [], [], 'qtls', testCase.flow);
+
+         returned = [Qexp Q0 pQexp pQ0];
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', testCase.tolerance)
+      end
+
+      function test_tauNotFiniteGivesNaN(testCase, notfinite)
+         % A tau that is not finite gives NaN flows and positions, with no
+         % warning of its own: the pole warning comes from expectedtau.
+         expected = nan(1, 4);
+
+         [Qexp, Q0, pQexp, pQ0] = testCase.verifyWarningFree(@() ...
+            baseflow.expectedQ(testCase.a, testCase.b, notfinite, [], ...
+            [], [], 'qtls', testCase.flow));
+
+         returned = [Qexp Q0 pQexp pQ0];
+         testCase.verifyEqual(returned, expected)
+      end
+
+      function test_plfitbTauBeyondPoleGivesNaN(testCase)
+         % globalfit passes the plfitb mean tau to expectedQ. A Pareto
+         % sample with alpha = 1.5 is beyond the pole, so tau is Inf. The
+         % flows are then NaN rather than the zero flow of an infinite tau.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            'baseflow:expectedtau:tauPole'));
+         nsamples = 400;
+         tau0 = 10;
+         belowpolealpha = 1.5;
+         expected = [NaN NaN];
+
+         u = ((1:nsamples)' - 0.5)/nsamples;
+         x = tau0 * (1 - u).^(-1/(belowpolealpha - 1));
+         Fit = baseflow.plfitb(x, 'xmin', tau0);
+         [Qexp, Q0] = baseflow.expectedQ(testCase.a, Fit.b, Fit.tau, ...
+            [], [], Fit.tau0);
+
+         returned = [Qexp Q0];
+         testCase.verifyEqual(returned, expected)
+      end
+   end
+end
diff --git a/tests/test_fdcurve.m b/tests/test_fdcurve.m
new file mode 100644
index 0000000..3e496ac
--- /dev/null
+++ b/tests/test_fdcurve.m
@@ -0,0 +1,24 @@
+function tests = test_fdcurve
+   %TEST_FDCURVE Test the reference points of baseflow.fdcurve.
+   %
+   % fdcurve ranks the flows from largest to smallest and returns the
+   % position f = 1 - M/(N+1), where M counts the flows at or above a
+   % point and N counts the flows that are not missing.
+   tests = functiontests(localfunctions);
+end
+
+function test_referencePointPositions(testCase)
+   % Three flows and one missing value give N = 3 and the positions
+   % [0.75 0.5 0.25] for 0.3, 0.2, and 0.1. Each point gets its own value:
+   % a nan point and a point above every flow have no position.
+   flow = [0.1; 0.2; 0.3; nan];
+   refpoints = [nan 0.2 0.35];
+   fref_expected = [nan 0.5 nan];
+   f_expected = [0.75 0.5 0.25];
+   tolerance = 1e-12;
+
+   fdc = baseflow.fdcurve(flow, 'refpoints', refpoints, 'plotfit', false);
+
+   testCase.verifyEqual(fdc.fref, fref_expected, 'AbsTol', tolerance)
+   testCase.verifyEqual(fdc.f, f_expected, 'AbsTol', tolerance)
+end
diff --git a/tests/test_getfunction.m b/tests/test_getfunction.m
new file mode 100644
index 0000000..b32b1f1
--- /dev/null
+++ b/tests/test_getfunction.m
@@ -0,0 +1,77 @@
+classdef test_getfunction < matlab.unittest.TestCase
+   %TEST_GETFUNCTION Test the expected-tau handle of baseflow.getfunction.
+   %
+   % A Pareto distribution with lower bound tau0 and pdf exponent alpha has
+   % the mean tau0*(alpha-1)/(alpha-2) for alpha > 2. The mean integral
+   % diverges for 1 < alpha <= 2, and alpha <= 1 gives no normalizable
+   % distribution. The handle takes b = 1 + 1/alpha, so the tau pole at
+   % alpha = 2 is b = 3/2. Each expected value below comes from the alpha
+   % form of the mean, not from the b form the handle uses.
+   %
+   % See also: test_gpfitb, test_plfitb
+
+   properties (TestParameter)
+      % Each case holds b and the expected mean for tau0 = 10.
+      % alpha = 4, 3, and 2.5 give the finite means 10*3/2, 10*2/1, and
+      % 10*1.5/0.5. alpha = 2 is the pole and alpha = 1.5 lies below it,
+      % so the mean diverges. alpha = 1 and alpha = -2 have no Pareto tail.
+      expectedtau = struct( ...
+         'alpha4', {{1.25, 15}}, ...
+         'alpha3', {{4/3, 20}}, ...
+         'alpha2p5', {{1.4, 30}}, ...
+         'atpole', {{1.5, Inf}}, ...
+         'belowpole', {{5/3, Inf}}, ...
+         'alpha1', {{2, NaN}}, ...
+         'negativealpha', {{0.5, NaN}})
+   end
+
+   properties (Constant)
+      % The lower bound of the tau distribution, in days.
+      tau0 = 10
+
+      % Rounding error allowed in a finite mean. b = 4/3 has no exact
+      % binary value.
+      tolerance = 1e-12
+
+      % The identifier expectedtau warns with at the pole.
+      poleid = 'baseflow:expectedtau:tauPole'
+   end
+
+   methods (Test)
+      function test_expectedTauAtThePole(testCase, expectedtau)
+         % The handle returns the finite mean above the pole, Inf where
+         % the mean diverges, and NaN where no Pareto tail exists.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            testCase.poleid));
+         [b, expected] = expectedtau{:};
+         Fnc = baseflow.getfunction('expectedTau');
+
+         returned = Fnc(testCase.tau0, b);
+
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', testCase.tolerance)
+      end
+
+      function test_poleWarningCountsTheValues(testCase)
+         % A call above the pole does not warn. A call with two of three
+         % values beyond it warns once and counts them.
+         Fnc = baseflow.getfunction('expectedTau');
+         testCase.verifyWarningFree(@() Fnc(testCase.tau0, [1.25 1.4]));
+
+         % Promote the warning to an error, which gives the test its
+         % message.
+         warnstate = warning('error', testCase.poleid);
+         testCase.addTeardown(@() warning(warnstate));
+         err_returned = MException.empty;
+         try
+            Fnc(testCase.tau0, [1.4 1.6 0.5]);
+         catch err_returned
+         end
+         testCase.assertNotEmpty(err_returned)
+         testCase.verifyEqual(err_returned.identifier, testCase.poleid)
+         testCase.verifySubstring(err_returned.message, '2 of 3 values of b')
+      end
+
+   end
+end
diff --git a/tests/test_gpfitb.m b/tests/test_gpfitb.m
new file mode 100644
index 0000000..15bdd00
--- /dev/null
+++ b/tests/test_gpfitb.m
@@ -0,0 +1,106 @@
+classdef test_gpfitb < matlab.unittest.TestCase
+   %TEST_GPFITB Test the gpfitb mean tau above and below the tau pole.
+   %
+   % A Pareto sample with lower bound xmin and pdf exponent alpha has the
+   % mean xmin*(alpha-1)/(alpha-2) for alpha > 2. The mean diverges at or
+   % below the tau pole at alpha = 2, so gpfitb must return Inf there,
+   % warn, and draw no mean-tau label. Every sample is a deterministic
+   % inverse-CDF draw, so the fit carries no sampling randomness.
+   %
+   % See also: test_corechain, test_getfunction
+
+   properties (TestParameter)
+      % Each case holds a pdf exponent above the pole and the mean for
+      % xmin = 10: 10*(3-1)/(3-2) and 10*(4-1)/(4-2).
+      finitetail = struct('alpha3', {{3, 20}}, 'alpha4', {{4, 15}})
+   end
+
+   properties (Constant)
+      % Sample size and lower bound, in days, of every sample.
+      nsamples = 5000
+      xmin = 10
+
+      % A pdf exponent below the pole. The formula tau0*(2-b)/(3-2*b)
+      % gives tauExp = -10.01 for this sample.
+      belowpolealpha = 1.5
+
+      % Relative error allowed between the fitted and the true mean.
+      reltol = 0.05
+
+      % The identifier expectedtau warns with at the pole.
+      poleid = 'baseflow:expectedtau:tauPole'
+   end
+
+   properties
+      % Open-figure snapshot taken before each test.
+      figsbefore
+   end
+
+   methods (TestMethodSetup)
+      function snapshotfigures(testCase)
+         % Close the figures each case opens (see tests/closenewfigs.m).
+         testCase.figsbefore = findall(0, 'Type', 'figure');
+         testCase.addTeardown(@() closenewfigs(testCase.figsbefore));
+      end
+   end
+
+   methods (Access = private)
+      function x = paretosample(testCase, alpha)
+         %PARETOSAMPLE Draw a fixed Pareto sample with pdf exponent alpha.
+         %
+         %  x = paretosample(testCase, alpha) returns testCase.nsamples
+         %  values with lower bound testCase.xmin from the inverse CDF at
+         %  midpoint quantiles. A pdf exponent alpha gives the CDF
+         %  exponent alpha - 1.
+         u = ((1:testCase.nsamples)' - 0.5)/testCase.nsamples;
+         x = testCase.xmin * (1 - u).^(-1/(alpha - 1));
+      end
+   end
+
+   methods (Test)
+      function test_finiteMeanAbovePole(testCase, finitetail)
+         % Above the pole, tauExp is the Pareto mean and gpfitb does not
+         % warn.
+         [alpha, expected] = finitetail{:};
+         x = testCase.paretosample(alpha);
+
+         Fit = testCase.verifyWarningFree(@() baseflow.gpfitb(x, ...
+            'xmin', testCase.xmin, 'plotfit', false));
+
+         returned = Fit.tauExp;
+         testCase.verifyEqual(returned, expected, 'RelTol', testCase.reltol)
+      end
+
+      function test_meanDivergesBelowPole(testCase)
+         % Below the pole, the mean tau is infinite and gpfitb warns with
+         % an identifier that names the pole.
+         x = testCase.paretosample(testCase.belowpolealpha);
+         expected = Inf;
+
+         Fit = testCase.verifyWarning(@() baseflow.gpfitb(x, ...
+            'xmin', testCase.xmin, 'plotfit', false), testCase.poleid);
+
+         returned = Fit.tauExp;
+         testCase.verifyEqual(returned, expected)
+      end
+
+      function test_labelOmitsDivergentMean(testCase)
+         % Below the pole, the plot labels tau0 only. No text names a mean
+         % tau, and drawarrow does not warn about a point off the log axis.
+         x = testCase.paretosample(testCase.belowpolealpha);
+         narrows_expected = 1;
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            testCase.poleid));
+
+         testCase.verifyWarningFree(@() baseflow.gpfitb(x, ...
+            'xmin', testCase.xmin, 'plotfit', true, 'labelplot', true));
+
+         ax = gca;
+         testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
+            narrows_expected)
+         labels_returned = get(findall(ax, 'Type', 'text'), 'String');
+         testCase.verifyFalse(any(contains(labels_returned, 'langle')))
+      end
+   end
+end
diff --git a/tests/test_plfitb.m b/tests/test_plfitb.m
index 90e88ae..826e2c7 100644
--- a/tests/test_plfitb.m
+++ b/tests/test_plfitb.m
@@ -1,16 +1,18 @@
 classdef test_plfitb < matlab.unittest.TestCase
-   %TEST_PLFITB Test the plfitb exponent, bootstrap seed, tau pole, and legend.
+   %TEST_PLFITB Test the plfitb exponent, mean tau, tau pole, and legend.
    %
-   % plfitb recovers the exponent of a power-law sample. plfitb bootstraps with baseflow.deps.plvar, which resamples the data,
-   % so a caller seed must fix the replicates. tau = tau0*(2-b)/(3-2*b) has
-   % a pole at b = 3/2, which is alpha = 2, and plfitb warns when a
-   % replicate reaches it. The legend plfitb draws through plplotb carries
-   % one bootstrap standard deviation, so it must name no coverage level.
-   % Every sample except the exponent-recovery sample is a deterministic
-   % Pareto draw, which leaves the bootstrap resampling as the only random
-   % step.
+   % plfitb recovers the exponent of a power-law sample. plfitb bootstraps
+   % with baseflow.deps.plvar, which resamples the data, so a caller seed
+   % must fix the replicates. tau = tau0*(2-b)/(3-2*b) has a pole at
+   % b = 3/2, which is alpha = 2. The mean tau of a Pareto tail diverges at
+   % or below the pole, so plfitb returns Inf there. plfitb warns for the
+   % point estimate and for the replicates. The legend plfitb draws through
+   % plplotb carries one bootstrap standard deviation, so it must name no
+   % coverage level. Every sample except the exponent-recovery sample is a
+   % deterministic Pareto draw, which leaves the bootstrap resampling as
+   % the only random step.
    %
-   % See also: test_plfitb_hanel
+   % See also: test_plfitb_hanel, test_getfunction
 
    properties (TestParameter)
       % Seeds for the reproducibility test. Each value seeds two identical
@@ -23,6 +25,10 @@
 
       % Pareto exponents the exponent-recovery test samples.
       PowerLawExponent = {1.5, 2.0, 2.5, 3.0, 3.5};
+
+      % Each case holds a pdf exponent above the pole and the Pareto mean
+      % tau0*(alpha-1)/(alpha-2) for tau0 = 10: 10*2/1 and 10*3/2.
+      meantail = struct('alpha3', {{3, 20}}, 'alpha4', {{4, 15}})
    end
 
    properties (Constant)
@@ -43,12 +49,19 @@
       % count at the pole depends on it.
       poleseed = 1
 
-      % The exponent at the pole. A replicate at or below it returns a
-      % negative or unbounded tau.
+      % The exponent at the pole. A replicate at or below it has a
+      % divergent mean tau, which plfitb returns as Inf.
       polealpha = 2
 
-      % The identifier plfitb warns with at the pole.
-      poleid = 'baseflow:plfitb:tauPoleReplicates'
+      % The identifier expectedtau warns with at the pole, for the point
+      % estimate and the replicates alike.
+      poleid = 'baseflow:expectedtau:tauPole'
+
+      % A pdf exponent below the pole.
+      belowpolealpha = 1.5
+
+      % Relative error allowed between the fitted and the true mean tau.
+      meanreltol = 0.05
    end
 
    properties
@@ -145,7 +158,7 @@ function test_warnsWhenReplicatesReachTauPole(testCase, poleexponent)
 
          % The message names the count and the replicate total.
          testCase.verifySubstring(err_returned.message, ...
-            sprintf('of %d bootstrap replicates', testCase.nreps))
+            sprintf('of %d values of b', testCase.nreps))
       end
 
       function test_poleWarningKeepsReturnedValues(testCase, poleexponent)
@@ -153,18 +166,22 @@ function test_poleWarningKeepsReturnedValues(testCase, poleexponent)
          x = testCase.paretosample(poleexponent, testCase.npolesample);
 
          % Silence the expected warning: this test reads the values.
-         warnstate = warning('off', testCase.poleid);
-         testCase.addTeardown(@() warning(warnstate));
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            testCase.poleid));
 
          returned = testCase.runbootfit(x, testCase.poleseed);
 
-         % The sample sits at the pole, so some replicates cross it.
-         npole_returned = sum(returned.reps.alpha <= testCase.polealpha);
-         testCase.verifyGreaterThan(npole_returned, 0)
+         % The sample sits at the pole, so some replicates cross it. The
+         % mean tau of each such replicate diverges.
+         ispole = returned.reps.alpha <= testCase.polealpha;
+         testCase.verifyGreaterThan(nnz(ispole), 0)
+         testCase.verifyEqual(returned.reps.tau(ispole), Inf(nnz(ispole), 1))
 
-         % tau is the point estimate, and the bounds stay one sigma wide.
-         tau_expected = returned.tau0 ...
-            * (2-returned.b) / (3-2*returned.b);
+         % tau is the point estimate of a fit without the bootstrap, and
+         % the bounds stay one sigma wide.
+         nobootfit = baseflow.plfitb(x);
+         tau_expected = nobootfit.tau;
          testCase.verifyEqual(returned.tau, tau_expected)
          testCase.verifyEqual(returned.tau_L, ...
             returned.tau - returned.BootFit.tau_sig)
@@ -172,10 +189,43 @@ function test_poleWarningKeepsReturnedValues(testCase, poleexponent)
             returned.tau + returned.BootFit.tau_sig)
       end
 
+      function test_meanTauAbovePole(testCase, meantail)
+         % Above the pole, tau is the Pareto mean and plfitb does not warn.
+         [alpha, expected] = meantail{:};
+         x = testCase.paretosample(alpha, testCase.nsample);
+
+         Fit = testCase.verifyWarningFree(@() baseflow.plfitb(x, ...
+            'xmin', testCase.tau0));
+
+         returned = Fit.tau;
+         testCase.verifyEqual(returned, expected, ...
+            'RelTol', testCase.meanreltol)
+      end
+
+      function test_meanTauDivergesBelowPole(testCase)
+         % Below the pole, the mean tau is infinite and plfitb warns with
+         % an identifier that names the pole.
+         x = testCase.paretosample(testCase.belowpolealpha, ...
+            testCase.nsample);
+         expected = Inf;
+
+         Fit = testCase.verifyWarning(@() baseflow.plfitb(x, ...
+            'xmin', testCase.tau0), testCase.poleid);
+
+         returned = Fit.tau;
+         testCase.verifyEqual(returned, expected)
+      end
+
       %-------------------------------------------
       %-------------------------------------------
       function test_recoversExponent(testCase,PowerLawExponent)
 
+         % An exponent at or below 2 puts the point estimate at the tau
+         % pole, so plfitb warns. This test reads the exponent only.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            testCase.poleid));
+
          % generate power-law distributed test data
          x = (1-rand(10000,1)).^(-1/(PowerLawExponent-1));
 
diff --git a/tests/test_plplotb.m b/tests/test_plplotb.m
new file mode 100644
index 0000000..a8dd03c
--- /dev/null
+++ b/tests/test_plplotb.m
@@ -0,0 +1,35 @@
+function tests = test_plplotb
+   %TEST_PLPLOTB Test the plplotb mean-tau label below the tau pole.
+   %
+   % The mean of a Pareto tail diverges at or below the tau pole at
+   % alpha = 2, so the label has no point on the axes to name. The label
+   % above the pole is tested in test_corechain.
+   tests = functiontests(localfunctions);
+end
+
+function test_labelOmitsDivergentMean(testCase)
+   % With alpha = 1.5, plplotb labels tau0 only. No text names a mean tau,
+   % and drawarrow does not warn about a point off the log axis. The pole
+   % warning of expectedtau is expected here.
+   figsbefore = findall(0, 'Type', 'figure');
+   testCase.addTeardown(@() closenewfigs(figsbefore));
+   testCase.applyFixture(matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+      'baseflow:expectedtau:tauPole'));
+   nsamples = 5000;
+   xmin = 10;
+   belowpolealpha = 1.5;
+   narrows_expected = 1;
+
+   % Inverse-CDF sample at midpoint probabilities: the ccdf exponent is
+   % the pdf exponent minus 1.
+   u = ((1:nsamples)' - 0.5)/nsamples;
+   x = xmin * (1 - u).^(-1/(belowpolealpha - 1));
+
+   h = testCase.verifyWarningFree(@() baseflow.plplotb(x, xmin, ...
+      belowpolealpha, 'labelplot', true));
+
+   testCase.verifyNumElements(findall(h.ax, 'Tag', 'refarrowhead'), ...
+      narrows_expected)
+   labels_returned = get(findall(h.ax, 'Type', 'text'), 'String');
+   testCase.verifyFalse(any(contains(labels_returned, 'langle')))
+end
diff --git a/toolbox/+baseflow/Contents.m b/toolbox/+baseflow/Contents.m
index b451eb2..c2934e1 100644
--- a/toolbox/+baseflow/Contents.m
+++ b/toolbox/+baseflow/Contents.m
@@ -132,6 +132,7 @@
 %   baseflow/private.dealout                     - Deal out function outputs
 %   baseflow/private.drawarrow                   - Draw an arrow in an axes, with the head on a given point
 %   baseflow/private.emptyaxes                   - Return empty axes object
+%   baseflow/private.expectedtau                 - Mean tau of a Pareto tail with recession exponent b
 %   baseflow/private.figurevisibility            - Visibility of a figure a caller asked to show
 %   baseflow/private.fillnans                    - Fill interior sequences of nan values of length <= fmax
 %   baseflow/private.findevents                  - Returns flow Q and time T values of each individual recession event,
diff --git a/toolbox/+baseflow/expectedQ.m b/toolbox/+baseflow/expectedQ.m
index 7b0083d..5c6935a 100644
--- a/toolbox/+baseflow/expectedQ.m
+++ b/toolbox/+baseflow/expectedQ.m
@@ -3,9 +3,16 @@
    %
    % Syntax
    %
-   %  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau);
-   %  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau,'pctls',Q) returns the percentiles
-   %              of Qexp/Q0 relative to the input Q
+   %  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau,q,dqdt,tau0);
+   %  [Qexp,Q0,pQexp,pQ0] = baseflow.EXPECTEDQ(_,'qtls',Q) returns the
+   %              percentiles of Qexp/Q0 relative to the input Q
+   %
+   % Description
+   %
+   %  Qexp is the flow at the mean tau, (a*tau)^(1/(1-b)), and
+   %  Q0 = Qexp*(3-b)/(2-b). The mean tau diverges beyond the tau pole at
+   %  alpha = 2, where plfitb returns Inf. A tau that is not finite gives
+   %  NaN for every output.
    %
    % See also: aquifertrend, baseflowtrend
    %
@@ -19,6 +26,9 @@
       a, b, tau, q, dqdt, tau0, varargin{:}); %#ok<*ASGLU>
 
    % MAIN FUNCTION
+   % a mean tau that does not exist has no flow, rather than the zero flow
+   % that an infinite tau gives
+   tau(~isfinite(tau)) = nan;
    Qexp = (a*tau)^(1/(1-b));
    Q0 = Qexp*(3-b)/(2-b);
 
diff --git a/toolbox/+baseflow/fdcurve.m b/toolbox/+baseflow/fdcurve.m
index 55ec529..a09682b 100644
--- a/toolbox/+baseflow/fdcurve.m
+++ b/toolbox/+baseflow/fdcurve.m
@@ -3,6 +3,12 @@
    %
    %     fdc = fdcurve(flow,varargin)
    %
+   %     fdc.f is the non-exceedance position 1 - M/(N+1) of each flow in
+   %     fdc.x, which is sorted largest first. M counts the flows at or above
+   %     that flow, and N counts the flows that are not missing. fdc.fref and
+   %     fdc.xref hold one value for each 'refpoints' value, NaN for a NaN
+   %     point or a point above every flow.
+   %
    % See also: hyetograph
 
    % if called with no input, open this file
@@ -13,21 +19,21 @@
 
    % main function
 
+   % a missing flow has no rank, so it stays out of the plotting positions
+   flow = flow(~isnan(flow));
    N = length(flow);
    M = 1:N;
    x = sort(flow,'descend');
    f = 1-M./(N+1);
 
-   % if requested, compute reference point values
-   xref = nan(numel(refpoints,1));
-   fref = nan(numel(refpoints,1));
-   if ~isnan(refpoints)
-      for n = 1:numel(refpoints)
-         iref = find(x>=refpoints(n),1,'last');
-         xref(n) = x(iref);
-         fref(n) = f(iref);
-      end
-   end
+   % if requested, compute reference point values. x is sorted descending,
+   % so the count of flows at or above a point is the index of the last one.
+   % A nan point, or one above every flow, has no index and stays nan.
+   xref = nan(size(refpoints));
+   fref = nan(size(refpoints));
+   iref = sum(x(:)>=refpoints(:).',1);
+   xref(iref>0) = x(iref(iref>0));
+   fref(iref>0) = f(iref(iref>0));
 
    % plot the curve if requested
    if plotfit == true
diff --git a/toolbox/+baseflow/getfunction.m b/toolbox/+baseflow/getfunction.m
index 92ecd51..ca6dcfd 100644
--- a/toolbox/+baseflow/getfunction.m
+++ b/toolbox/+baseflow/getfunction.m
@@ -13,6 +13,12 @@
    %     Fnc = baseflow.getfunction('expectedQ') returns anonymous function
    %     handle for expected value of baseflow function Q(Q0,b) = Q0*(2-b)/(3-b)
    %
+   %     Fnc = baseflow.getfunction('expectedTau') returns a function handle
+   %     for the mean tau, tau(tau0,b) = tau0*(2-b)/(3-2*b). The mean diverges
+   %     at the tau pole b = 3/2 (alpha = 2) and beyond, so the handle returns
+   %     Inf there. It returns NaN where no Pareto tail exists (b < 1 or
+   %     b >= 2).
+   %
    %     Use tab-completion to see full list of options
    %
    % See also: baseflow.getstring
@@ -34,7 +40,7 @@
       case 'expectedQ'
          Fnc = @(Q0,b) Q0.*(2-b)./(3-b);  % expected value of Q
       case 'expectedTau'
-         Fnc = @(tau0,b) tau0.*(2-b)./(3-2.*b);  % expected value of tau
+         Fnc = @expectedtau;  % expected value of tau
       case 'expectedTime'
          Fnc = @(tau0,b) tau0./(3-2.*b);  % expected duration of baseflow
       case 'boftautau0'
@@ -42,4 +48,4 @@
       case 'aofa0'
          Fnc = @(a0,b,tau,tau0) (1/tau)*(sqrt(a0*tau0)*(b-3)/(b-2))^(b-1);
    end
-end
\ No newline at end of file
+end
diff --git a/toolbox/+baseflow/gpfitb.m b/toolbox/+baseflow/gpfitb.m
index cc18f9c..ac37341 100644
--- a/toolbox/+baseflow/gpfitb.m
+++ b/toolbox/+baseflow/gpfitb.m
@@ -17,6 +17,12 @@
    %     [Fit,b,alpha,k] = gpfitb(x,'xmin',xmin) subtracts user-provided xmin
    %     from data in x. xmin is the threshold parameter.
    %
+   %     Fit.tauExp is the mean tau of the fitted Pareto tail, with bounds
+   %     tauExpL and tauExpH. The mean diverges at or below the tau pole at
+   %     alpha = 2, so a value there is Inf, or NaN without a Pareto tail.
+   %     gpfitb then warns with baseflow:expectedtau:tauPole, and the plot
+   %     label omits the mean tau.
+   %
    % Example
    %
    %  Sample a Pareto distribution with tau0 = 20 days and b = 1.4, then
@@ -87,12 +93,15 @@
 
    end
 
+   % mean tau of the fitted tail and its bounds (see expectedtau)
+   tauExp = expectedtau([tau0M tau0L tau0H],[bM bL bH]);
+
    % package output
    Fit.gpdist  = Dist;
    Fit.xmin    = xmin;
    Fit.b       = bM;
    Fit.tau0    = tau0M;
-   Fit.tauExp  = tau0M*(2-bM)/(3-2*bM);
+   Fit.tauExp  = tauExp(1);
    %Fit.tauExp  = gpdist.mean+tau0;
    Fit.k       = kM;
    Fit.alpha   = alphaM;
@@ -104,8 +113,8 @@
    Fit.alphaH  = alphaH;
    Fit.tau0L   = tau0L;
    Fit.tau0H   = tau0H;
-   Fit.tauExpL = tau0L*(2-bL)/(3-2*bL);
-   Fit.tauExpH = tau0H*(2-bH)/(3-2*bH);
+   Fit.tauExpL = tauExp(2);
+   Fit.tauExpH = tauExp(3);
    Fit.numtau  = numel(X(X>xmin));
 
    if bootfit == true
@@ -224,6 +233,10 @@ function addlabels(Fit,xmin,yref)
    % text(1.05*xa(1),ya(1),ta)
 
    % tauExp
+   % a mean or bound beyond the tau pole has no point on the axes to label
+   if ~all(isfinite([Fit.tauExp Fit.tauExpL Fit.tauExpH]))
+      return
+   end
    xexp = Fit.tauExp; % just use xmin to keep syntax
    xexpc = (Fit.tauExpH-Fit.tauExp+Fit.tauExp-Fit.tauExpL)/2;
    xa = [xexp-xexp/2 xexp];
diff --git a/toolbox/+baseflow/plfitb.m b/toolbox/+baseflow/plfitb.m
index d28143d..bd651c7 100644
--- a/toolbox/+baseflow/plfitb.m
+++ b/toolbox/+baseflow/plfitb.m
@@ -13,6 +13,11 @@
    %     xhat=x-xmin. Any inputs to plfit can be passed in as varargin, where
    %     plfit is Aaron Clauset's function.
    %
+   %     Fit.tau is the mean tau of the fitted Pareto tail. The mean
+   %     diverges at or below the tau pole at alpha = 2, so Fit.tau is Inf
+   %     there. A bootstrap replicate beyond the pole makes tau_sig, tau_L,
+   %     and tau_H NaN. plfitb then warns with baseflow:expectedtau:tauPole.
+   %
    % Required inputs
    %
    %     x        data believed to follow an untruncated Pareto distribution
@@ -86,7 +91,7 @@
    Fit.x       = x0; % keep the input data
    Fit.alpha   = alpha;
    Fit.b       = 1+1/Fit.alpha;
-   Fit.tau     = xmin*(2-Fit.b)/(3-2*Fit.b);
+   Fit.tau     = expectedtau(xmin,Fit.b); % Inf beyond the tau pole
    Fit.tau0    = xmin;
    Fit.L       = L;
    Fit.D       = D;
@@ -164,19 +169,11 @@
    reps.tau0   = repsmat(:,2);
    reps.alpha  = repsmat(:,3);
    reps.b      = baseflow.conversions(reps.alpha,'alpha','b');
-   reps.tau    = reps.tau0.*(2-reps.b)./(3-2.*reps.b);
+   reps.tau    = expectedtau(reps.tau0,reps.b);
 
    % tau = tau0*(2-b)/(3-2*b) has a pole at b = 3/2, which is alpha = 2. A
-   % replicate at or below alpha = 2 returns a negative or unbounded tau.
-   % Such a replicate makes std(reps.tau) meaningless. Warn with the count,
-   % so the caller does not trust the reported tau_sig.
-   npole = sum(reps.alpha <= 2);
-   if npole > 0
-      warning('baseflow:plfitb:tauPoleReplicates', ...
-         ['%d of %d bootstrap replicates have alpha <= 2, where tau is ' ...
-         'unbounded. Treat tau_sig, tau_L, and tau_H as invalid.'], ...
-         npole, numel(reps.alpha))
-   end
+   % replicate beyond it has an infinite tau, so the tau mean and sigma are
+   % Inf or NaN, and expectedtau warns with the count of such replicates.
 
    for n = 1:numel(vars)
       var = vars{n};
diff --git a/toolbox/+baseflow/plplotb.m b/toolbox/+baseflow/plplotb.m
index f44ca59..d8f373a 100644
--- a/toolbox/+baseflow/plplotb.m
+++ b/toolbox/+baseflow/plplotb.m
@@ -35,7 +35,9 @@
    %                 similar to 'axis tight' option (b/c power law data is often
    %                 covering many orders of magnitude).
    %     labelplot = logical scalar indicating whether to add a label showing
-   %                 the value of xmin and the expected value of x.
+   %                 the value of xmin and the expected value of x. The
+   %                 expected value diverges at alpha <= 2, so the label
+   %                 omits it there.
    %     ax        = graphic axis to plot into.
    %
    % See also: plfit, plfitb, gpfitb, eventtau
@@ -173,14 +175,18 @@ function addlabels(xfit,yfit,tau0,tau0L,tau0H,b)
    %----------------------------------------------------------------------------
    % test using the new xminL/H
    % deactivate this and reactive the two lines below to go back
-   xexp = tau0*(2-b)/(3-2*b);
-   tauL = tau0L*(2-b)/(3-2*b);
-   tauH = tau0H*(2-b)/(3-2*b);
-   xexpc = (tauH-tauL)/2;
+   tauexp = expectedtau([tau0 tau0L tau0H],b);
+   xexp = tauexp(1);
+   xexpc = (tauexp(3)-tauexp(2))/2;
    % xexp  = mean((tau0*(2-bL)/(3-2*bL) + tau0*(2-bH)/(3-2*bH))/2);
    % xexpc = mean(abs(xexp-[tau0*(2-bL)/(3-2*bL), tau0*(2-bH)/(3-2*bH)]));
    %----------------------------------------------------------------------------
 
+   % a mean beyond the tau pole has no point on the axes to label
+   if ~isfinite(xexp)
+      return
+   end
+
    xarrw = [10^(log10(xexp)-ndecx/10) xexp];
    yarrw = yfit(find(xfit>=xarrw(2),1,'first'));
    yarrw = [yarrw yarrw];
diff --git a/toolbox/+baseflow/private/expectedtau.m b/toolbox/+baseflow/private/expectedtau.m
new file mode 100644
index 0000000..858c70d
--- /dev/null
+++ b/toolbox/+baseflow/private/expectedtau.m
@@ -0,0 +1,42 @@
+function tau = expectedtau(tau0, b)
+   %EXPECTEDTAU Mean tau of a Pareto tail with recession exponent b.
+   %
+   % Syntax
+   %
+   %     tau = expectedtau(tau0, b)
+   %
+   % Description
+   %
+   %     tau = expectedtau(tau0, b) returns tau0*(2-b)/(3-2*b), the mean of a
+   %     Pareto distribution with lower bound tau0 and pdf exponent
+   %     alpha = 1/(b-1). It applies elementwise to tau0 and b.
+   %
+   %     The mean diverges at and beyond the tau pole at alpha = 2, which is
+   %     3/2 <= b < 2, so tau is Inf there. For b < 1 or b >= 2 (alpha <= 1),
+   %     no Pareto tail exists, so tau is nan. Either case raises
+   %     baseflow:expectedtau:tauPole, with the count of values it affects.
+   %     gpfitb, plfitb, plplotb, and getfunction call it, so they share
+   %     these values and this warning.
+   %
+   % See also: getfunction, gpfitb, plfitb, plplotb, expectedQ
+
+   % The masks take the shape of b, so they hold when tau0 is an array and
+   % b is a scalar. A nan b falls in neither mask.
+   diverges = b >= 3/2 & b < 2;
+   notail = b < 1 | b >= 2;
+
+   % The formula changes sign at the pole, but the mean of a positive
+   % variable with a divergent integral is infinite.
+   ratio = (2-b)./(3-2.*b);
+   ratio(diverges) = inf;
+   ratio(notail) = nan;
+   tau = tau0.*ratio;
+
+   if any(diverges(:) | notail(:))
+      warning('baseflow:expectedtau:tauPole', ...
+         ['%d of %d values of b give no finite mean tau. The mean diverges ' ...
+         'for 3/2 <= b < 2 (1 < alpha <= 2) and is undefined for b < 1 ' ...
+         'or b >= 2.'], ...
+         nnz(diverges | notail), numel(b))
+   end
+end

From db4dc14ef0a7642069d01bbca9d3c73cd9aa37f9 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:58 -0700
Subject: [PATCH 06/28] fix(baseflow): correct the RS05 late-time constant,
 tail mask, and fits

- specialfunctions raises the Beta function to the power n+3 in the
  late-time Rupp and Selker (2005) constant. So fR2(0) = 4.805, the
  Brutsaert and Nieber (1977) constant. phi from the RS05 solutions
  changes for every b other than 1 and 3/2.
- plfitb puts the xmin sample in the tail mask, as plfit fits x >= xmin.
- fitab 'nls' reports its interval at the confidence level alpha, and
  the Octave path uses the residual degrees of freedom.
- prepfits drops masked and zero-weight points, so every fitab method
  fits the same points.
- The CTS stencils pair each derivative with the flow at the same time;
  ETS leaves a rejected window empty; VTS widens across flat steps.
- pointcloudintercept orders its a bounds and pivots 'mean' through the
  geometric means.
- dndtuncertainty correlates complete rows; aquiferstorage uses one path
  for scalar and array input; Qnonlin covers b = 1 and an emptied
  reservoir; printtrend scales by the years spanned; conversions takes
  'Nstar'; getfunction handles apply elementwise; gpfitb tau0reps are
  sigma/k; quantreg tests significance on its interval; the fdcurve
  label and the plfitb limit help match the code.
---
 CHANGELOG.md                              | 50 ++++++++++++++++++
 tests/Contents.m                          |  4 ++
 tests/test_Qnonlin.m                      | 64 +++++++++++++++++++++++
 tests/test_aquiferstorage.m               | 12 +++++
 tests/test_conversions.m                  |  3 +-
 tests/test_fitab.m                        | 43 ++++++++++++++-
 tests/test_fitcts.m                       | 36 +++++++++----
 tests/test_getdqdt.m                      | 27 ++++++++++
 tests/test_getfunction.m                  | 26 +++++++++
 tests/test_gpfitb.m                       | 28 ++++++++--
 tests/test_plfitb.m                       | 11 ++++
 tests/test_pointcloudintercept.m          | 35 +++++++++++++
 tests/test_printtrend.m                   | 20 +++++++
 tests/test_specialfunctions.m             | 18 +++++++
 toolbox/+baseflow/Qnonlin.m               | 28 ++++++++--
 toolbox/+baseflow/aquiferstorage.m        | 64 ++++-------------------
 toolbox/+baseflow/conversions.m           | 10 ++--
 toolbox/+baseflow/dndtuncertainty.m       | 10 +++-
 toolbox/+baseflow/fdcurve.m               |  2 +-
 toolbox/+baseflow/fitab.m                 | 40 +++++---------
 toolbox/+baseflow/generateTestData.m      | 13 ++---
 toolbox/+baseflow/getfunction.m           |  9 ++--
 toolbox/+baseflow/gpfitb.m                |  2 +-
 toolbox/+baseflow/plfitb.m                |  4 +-
 toolbox/+baseflow/pointcloudintercept.m   | 31 +++++------
 toolbox/+baseflow/prepfits.m              | 11 ++--
 toolbox/+baseflow/printtrend.m            |  5 +-
 toolbox/+baseflow/private/bootstrapci.m   | 11 ++--
 toolbox/+baseflow/private/fitNLS_matlab.m |  9 ++--
 toolbox/+baseflow/private/fitNLS_octave.m | 14 +++--
 toolbox/+baseflow/private/fitcts.m        | 40 +++++++-------
 toolbox/+baseflow/private/fitets.m        | 10 ++--
 toolbox/+baseflow/private/fitvts.m        |  5 +-
 toolbox/+baseflow/specialfunctions.m      |  4 +-
 toolbox/demos/mfiles/baseflow_demo_3.m    |  4 +-
 toolbox/functionSignatures.json           |  4 +-
 36 files changed, 519 insertions(+), 188 deletions(-)
 create mode 100644 tests/test_Qnonlin.m
 create mode 100644 tests/test_pointcloudintercept.m
 create mode 100644 tests/test_printtrend.m
 create mode 100644 tests/test_specialfunctions.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index ccb768f..ce0236f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -19,6 +19,15 @@ semantic versioning.
 
 ### Fixed
 
+- The late-time Rupp and Selker (2005) constant in `specialfunctions`
+  raises the Beta function to the power n+3. At n = 0 it gives 4.805, the
+  Brutsaert and Nieber (1977) constant 4.804; it gave 1.857. `globalfit`
+  uses the RS05 solutions by default, so its phi changes for every b
+  other than 1 and 3/2. `aquiferprops` 'RS05' gives the 'BS04' k at
+  b = 3/2. The early-time constant fR1 still disagrees with its n = 0
+  limit, 1.133.
+- `plfitb` puts the xmin sample in the tail mask, as `plfit` fits the
+  tail x >= xmin. So the `globalfit` a and expected flows change.
 - `gpfitb` and `plfitb` return Inf for the mean tau at or below the tau
   pole at alpha 2. The mean of a Pareto tail diverges there. The formula
   tau0*(2-b)/(3-2*b) is negative below the pole, so `gpfitb` reported a
@@ -36,6 +45,47 @@ semantic versioning.
   for a point that is NaN or above every flow. It sized its output from
   the first point only. Missing flows stay out of the plotting
   positions.
+- `baseflow.getfunction('expectedTime')` shares the tau pole. The
+  `'boftautau0'` and `'aofa0'` handles apply elementwise, so array input
+  gives one value per element instead of a matrix division.
+- `fitab` 'nls' reports its interval at the confidence level `alpha`.
+  `nlparci` and `regress` take a significance level, so the default 0.68
+  gave a 32% interval, and the linear fallback a 95% one. The Octave path
+  used one degree of freedom.
+- `prepfits` drops masked and zero-weight points, so every `fitab` method
+  fits the same points. 'nls' honors the mask, and the OLS interval and
+  `Fit.N` count the fitted points only.
+- The CTS stencils B2, F2, C2, and C4 pair each derivative with the flow
+  at the same time. B2 and F2 paired it with a flow half a step away.
+  That biased a by about 5% at a step of a tenth of tau.
+- The ETS method leaves a rejected window empty. It interpolated over
+  the rejected windows, so a rise inside a recession took the slope of
+  the windows around it. The example data has no such window, so its
+  results are unchanged.
+- The VTS method widens its window across a flat step, so a record in
+  whole units gives no zero slopes (Rupp and Selker, 2006).
+- `pointcloudintercept` orders its a bounds for flows below 1. Its 'mean'
+  method pivots through the geometric means of q and -dq/dt, so its
+  bounds are in flow units.
+- `dndtuncertainty` correlates the event variables over the events where
+  all three exist, so a nan phi from `phifitensemble` leaves the
+  uncertainty finite.
+- `aquiferstorage` uses one path for scalar and array input. The scalar
+  path with a `Ktime` input returned negative storage for 1 < b < 2.
+- `Qnonlin` gives the exponential recession at b = 1, and for b < 1 a
+  flow that stays 0 once the reservoir empties. `generateTestData` uses
+  it for every b.
+- `printtrend` scales the trend by the years the record spans to report
+  the total change. It used the sample count.
+- `conversions` accepts 'Nstar' as an input, and its help gives k and
+  alpha from the pdf of tau.
+- `gpfitb` returns the bootstrap replicates of tau0 = sigma/k in
+  `tau0reps`. It returned sigma.
+- `quantreg` flags a significant slope when its bootstrap interval
+  excludes zero. A z test on the replicates divided their spread by the
+  square root of the replicate count.
+- The `fdcurve` x label names the non-exceedance probability it plots,
+  and the `plfitb` help says that `limit` bounds xmin.
 - `gpfitb`, `plplotb` and `fitphidist` print nothing when they label a
   figure. The private `drawarrow` assigned its output whether or not the
   caller asked for it, and no call site ended with a semicolon, so each
diff --git a/tests/Contents.m b/tests/Contents.m
index c14adcd..7f46d21 100644
--- a/tests/Contents.m
+++ b/tests/Contents.m
@@ -52,8 +52,11 @@
 %   test_plotdqdt          - Test the plotdqdt reference lines, ticks, and labels
 %   test_plotrefline       - Test the plotrefline label position
 %   test_plplotb           - Test the plplotb mean-tau label below the tau pole
+%   test_pointcloudintercept - Test the intercept bounds of pointcloudintercept
 %   test_pointcloudplot    - Test the pointcloudplot ticks, limits, and axes
 %   test_preparecalendar   - Test the private preparecalendar helper
+%   test_printtrend        - Test the total change baseflow.printtrend reports
+%   test_Qnonlin           - Test the recession solution of baseflow.Qnonlin
 %   test_relayoutloglogtext - Test the angle reset of a rotated log-log label
 %   test_rotatedLogLogText - Test the rotated log-log label angle
 %   test_setlogticks       - Test the private setlogticks decade ticks
@@ -63,6 +66,7 @@
 %   test_sizefigure        - Test the size of a point-cloud figure
 %   test_smoothnoise       - Test the private smoothnoise helper
 %   test_snaploglims       - Test the private snaploglims limit policy
+%   test_specialfunctions  - Test the Rupp and Selker (2005) constants
 %   test_todatenum         - Test baseflow/private/todatenum
 %   test_trendplot         - Test the trendplot 'ols' trend and confidence bounds
 %   test_version           - Assert the version metadata locations agree
diff --git a/tests/test_Qnonlin.m b/tests/test_Qnonlin.m
new file mode 100644
index 0000000..7fb8a88
--- /dev/null
+++ b/tests/test_Qnonlin.m
@@ -0,0 +1,64 @@
+classdef test_Qnonlin < matlab.unittest.TestCase
+   %TEST_QNONLIN Test the recession solution of baseflow.Qnonlin.
+   %
+   % Q(t) solves -dQ/dt = aQ^b from Q(0) = Q0. b = 1 is the exponential
+   % Q0*exp(-a*t). For b = 1/2, sqrt(Q) falls linearly as
+   % sqrt(Q0) - a*t/2, so the reservoir empties at t = 2*sqrt(Q0)/a and
+   % then stays empty. For b = 0, Q falls at the rate a until it is 0, and
+   % an empty reservoir has a rate of 0.
+
+   properties (Constant)
+      % Rounding error allowed in the closed-form values.
+      tolerance = 1e-12
+   end
+
+   methods (Test)
+      function test_linearReservoirIsExponential(testCase)
+         % b = 1 gives Q0*exp(-a*t), not the constant that 1/(1-b) = Inf
+         % gives in the power-law form.
+         a = 0.1;
+         Q0 = 100;
+         t = (0:3)';
+         expected = Q0*exp(-a*t);
+
+         returned = baseflow.Qnonlin(a, 1, Q0, t);
+
+         testCase.verifyEqual(returned, expected, ...
+            'RelTol', testCase.tolerance)
+      end
+
+      function test_subLinearReservoirEmpties(testCase)
+         % With a = 1/2, b = 1/2, and Q0 = 1, Q = (1 - t/4)^2 until t = 4,
+         % and 0 after.
+         a = 0.5;
+         b = 0.5;
+         Q0 = 1;
+         t = (0:5)';
+         expected = [1; 0.5625; 0.25; 0.0625; 0; 0];
+
+         returned = baseflow.Qnonlin(a, b, Q0, t);
+
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', testCase.tolerance)
+      end
+
+      function test_emptyReservoirHasNoRate(testCase)
+         % With a = 1/2, b = 0, and Q0 = 1, Q = 1 - t/2 until t = 2. The
+         % rate is -1/2 while flow remains and 0 once the reservoir is
+         % empty, where a*Q^0 would still give -1/2.
+         a = 0.5;
+         b = 0;
+         Q0 = 1;
+         t = (0:3)';
+         Q_expected = [1; 0.5; 0; 0];
+         dQdt_expected = [-0.5; -0.5; 0; 0];
+
+         [Q_returned, dQdt_returned] = baseflow.Qnonlin(a, b, Q0, t);
+
+         testCase.verifyEqual(Q_returned, Q_expected, ...
+            'AbsTol', testCase.tolerance)
+         testCase.verifyEqual(dQdt_returned, dQdt_expected, ...
+            'AbsTol', testCase.tolerance)
+      end
+   end
+end
diff --git a/tests/test_aquiferstorage.m b/tests/test_aquiferstorage.m
index de5ae33..fd0876e 100644
--- a/tests/test_aquiferstorage.m
+++ b/tests/test_aquiferstorage.m
@@ -39,5 +39,17 @@ function test_storageBounds(testCase,RecessionExponent)
 
       end
 
+      function test_ktimeStorage(testCase,RecessionExponent)
+         % With the drainage timescale Ktime = Q^(1-b)/a given, storage is
+         % S = Ktime*q/(2-b), which is positive for b < 2: 10*[1 100]/1
+         % for b = 1 and 10*[1 100]/0.5 for b = 1.5.
+         Ktime = 10;
+         S_expected = Ktime*[1 100]/(2-RecessionExponent);
+
+         [Smin_returned,Smax_returned] = baseflow.aquiferstorage( ...
+            1,RecessionExponent,1,100,Ktime);
+
+         testCase.verifyEqual([Smin_returned,Smax_returned],S_expected);
+      end
    end
 end
diff --git a/tests/test_conversions.m b/tests/test_conversions.m
index b94e74b..9612323 100644
--- a/tests/test_conversions.m
+++ b/tests/test_conversions.m
@@ -14,7 +14,8 @@
          'b_to_N', {{1.5, 'b', 'N', @(b) 3-2.*b}}, ...
          'b_to_alpha', {{1.0, 'b', 'alpha', @(b) 1./(b-1)}}, ...
          'b_to_beta', {{2.0, 'b', 'beta', @(b) 1./(b-2)}}, ...
-         'b_to_gamma', {{1.5, 'b', 'gamma', @(b) 1./(2.*b-3)}})
+         'b_to_gamma', {{1.5, 'b', 'gamma', @(b) 1./(2.*b-3)}}, ...
+         'Nstar_to_b', {{1.0, 'Nstar', 'b', @(Ns) 2-1./(2.*Ns)}})
 
       % Bad inputs. Each case holds the input value, the input parameter
       % name, and the expected error identifier: a non-numeric inputvalue,
diff --git a/tests/test_fitab.m b/tests/test_fitab.m
index 62b6402..fe1efb9 100644
--- a/tests/test_fitab.m
+++ b/tests/test_fitab.m
@@ -169,9 +169,10 @@ function test_fitab_ols_confint(testCase)
             'mask',mask,'alpha',alpha);
 
          % Expected values: a weighted poly1 fit of log(-dq/dt) on log(q).
-         % fitab documents that masked points get zero weight.
+         % fitab documents that masked points take no part in the fit, so
+         % exclude them, which also removes them from the degrees of freedom.
          fopts = fitoptions('Method','LinearLeastSquares', ...
-            'Weights',weights.*mask);
+            'Weights',weights,'Exclude',~mask);
          f = fit(log(q),log(-dqdt),'poly1',fopts);
 
          % coeffvalues is [slope intercept]. confint has rows [lower; upper]
@@ -190,5 +191,43 @@ function test_fitab_ols_confint(testCase)
          testCase.verifyEqual(ci_returned,ci_expected,'RelTol',tol);
       end
 
+      function test_nlsIntervalFollowsAlpha(testCase)
+         % alpha is a confidence level, so the 95% interval is wider than
+         % the 68% one by the ratio of their t quantiles. Reading alpha as
+         % a significance level inverts the ratio.
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+         q = q .* (1 + 0.2*sin((1:numel(q))'));
+         Fit68 = baseflow.fitab(q,dqdt,'nls','alpha',0.68);
+         Fit95 = baseflow.fitab(q,dqdt,'nls','alpha',0.95);
+         dfe = Fit68.N - 2;
+         expected = tinv(0.975,dfe) / tinv(0.84,dfe);
+         tol = 1e-6;
+
+         returned = (Fit95.bH - Fit95.bL) / (Fit68.bH - Fit68.bL);
+
+         testCase.verifyEqual(returned,expected,'RelTol',tol)
+      end
+
+      function test_nlsHonorsMask(testCase)
+         % A masked fit equals the fit of the points the mask keeps.
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+         q = q .* (1 + 0.2*sin((1:numel(q))'));
+         mask = mod((1:numel(q))',5) ~= 0;
+         FitSubset = baseflow.fitab(q(mask),dqdt(mask),'nls');
+         expected = FitSubset.ab;
+
+         FitMasked = baseflow.fitab(q,dqdt,'nls','mask',mask);
+         returned = FitMasked.ab;
+
+         testCase.verifyEqual(returned,expected)
+      end
    end
 end
diff --git a/tests/test_fitcts.m b/tests/test_fitcts.m
index cc69772..424fd30 100644
--- a/tests/test_fitcts.m
+++ b/tests/test_fitcts.m
@@ -22,23 +22,24 @@
          'C4', {{'C4', 1e-4}})
 
       % Each case holds a stencil name and the formula for its tqmid
-      % midpoint times: backward stencils post at (T(i)+T(i-1))/2, forward
-      % stencils at (T(i)+T(i+1))/2, and centered stencils at
-      % (T(i+1)+T(i-1))/2. Edge samples are nan.
+      % times, where the stencil estimates the derivative: B1 posts at
+      % (T(i)+T(i-1))/2, F1 at (T(i)+T(i+1))/2, and B2, F2, C2, and C4 at
+      % T(i). Edge samples, where a stencil reaches past the data, are nan.
       midpoint = struct( ...
          'B1', {{'B1', @(T) [nan; (T(2:end) + T(1:end-1)) / 2]}}, ...
-         'B2', {{'B2', @(T) [nan; (T(2:end) + T(1:end-1)) / 2]}}, ...
+         'B2', {{'B2', @(T) [nan; nan; T(3:end)]}}, ...
          'F1', {{'F1', @(T) [(T(1:end-1) + T(2:end)) / 2; nan]}}, ...
-         'F2', {{'F2', @(T) [(T(1:end-1) + T(2:end)) / 2; nan]}}, ...
-         'C2', {{'C2', @(T) [nan; (T(3:end) + T(1:end-2)) / 2; nan]}}, ...
-         'C4', {{'C4', @(T) [nan; (T(3:end) + T(1:end-2)) / 2; nan]}})
+         'F2', {{'F2', @(T) [T(1:end-2); nan; nan]}}, ...
+         'C2', {{'C2', @(T) [nan; T(2:end-1); nan]}}, ...
+         'C4', {{'C4', @(T) [nan; nan; T(3:end-2); nan; nan]}})
    end
 
    properties
-      % The private fitcts function handle, the recession signal, and its
-      % analytic derivative.
+      % The private fitcts function handle, the recession timescale and
+      % signal, and its analytic derivative.
       fitcts
       daystep
+      tau
       T
       Q
       R
@@ -50,6 +51,7 @@ function makerecession(testCase)
          % Daily exponential recession: q = q0 exp(-t/tau), dq/dt = -q/tau.
          testCase.fitcts = baseflow.privatefunction('fitcts');
          tau = 20;
+         testCase.tau = tau;
          q0 = 100;
          testCase.daystep = 1;
          ndays = 60;
@@ -81,6 +83,22 @@ function test_stencilAccuracy(testCase, stencil)
             returned, reltol))
       end
 
+      function test_flowPairsWithDerivative(testCase, stencil)
+         % fitab regresses dqdt on q, so each derivative must pair with
+         % the flow at the same time. The recession has -dQ/dt = Q/tau at
+         % every instant, so -dqdt./q is 1/tau within the stencil error.
+         [method, reltol] = stencil{:};
+         [q, dqdt] = testCase.fitcts(testCase.T, testCase.Q, ...
+            testCase.R, method);
+         expected = 1/testCase.tau;
+         keep = ~isnan(dqdt);
+
+         returned = -dqdt(keep)./q(keep);
+
+         testCase.verifyEqual(returned, expected*ones(nnz(keep), 1), ...
+            'RelTol', reltol)
+      end
+
       function test_defaultsAndAlignment(testCase)
          % With no method input, fitcts uses B1. tq and rq post on the input
          % vectors, and dt is the constant sample step.
diff --git a/tests/test_getdqdt.m b/tests/test_getdqdt.m
index d1a41a1..f68296d 100644
--- a/tests/test_getdqdt.m
+++ b/tests/test_getdqdt.m
@@ -117,6 +117,33 @@ function test_ctsBackwardDifference(testCase,DerivMethod)
 
       end
 
+      function test_etsKeepsRejectedWindowsEmpty(testCase)
+         % A rise inside a recession gives windows with a positive slope,
+         % which ETS rejects. They stay nan, rather than taking the slope of
+         % the windows around them.
+         t = (0:59)';
+         q = 100*exp(-t/20);
+         rise = t >= 25 & t <= 28;
+         q(rise) = q(rise) + 5*(t(rise) - 24);
+
+         [~,dqdt] = baseflow.getdqdt(t,q,zeros(size(q)),'ETS');
+
+         testCase.verifyTrue(any(isnan(dqdt(rise))))
+         testCase.verifyFalse(any(dqdt > 0))
+      end
+
+      function test_vtsWidensAcrossFlatSteps(testCase)
+         % A recession reported in whole units has flat steps. VTS widens
+         % its window across a flat step until the flow drops, so no
+         % estimate is a zero slope (Rupp and Selker, 2006).
+         t = (0:99)';
+         q = round(20*exp(-0.02*t));
+
+         [~,dqdt] = baseflow.getdqdt(t,q,zeros(size(q)),'VTS');
+
+         testCase.assertNotEmpty(dqdt(dqdt < 0))
+         testCase.verifyFalse(any(dqdt == 0))
+      end
    end
 
    methods (Access = private)
diff --git a/tests/test_getfunction.m b/tests/test_getfunction.m
index b32b1f1..b4b5262 100644
--- a/tests/test_getfunction.m
+++ b/tests/test_getfunction.m
@@ -73,5 +73,31 @@ function test_poleWarningCountsTheValues(testCase)
          testCase.verifySubstring(err_returned.message, '2 of 3 values of b')
       end
 
+      function test_expectedTimeSharesThePole(testCase)
+         % tau0/(3-2*b) is 10/0.5 at b = 1.25 and diverges at b = 1.6.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            testCase.poleid));
+         Fnc = baseflow.getfunction('expectedTime');
+         expected = [20 Inf];
+
+         returned = Fnc(testCase.tau0, [1.25 1.6]);
+
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', testCase.tolerance)
+      end
+
+      function test_boftautau0InvertsExpectedTau(testCase)
+         % boftautau0 inverts the mean tau elementwise, so a vector of b
+         % comes back from its own mean tau.
+         expected = [1.1 1.25 1.4];
+         tau = baseflow.getfunction('expectedTau');
+         boftautau0 = baseflow.getfunction('boftautau0');
+
+         returned = boftautau0(tau(testCase.tau0, expected), testCase.tau0);
+
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', testCase.tolerance)
+      end
    end
 end
diff --git a/tests/test_gpfitb.m b/tests/test_gpfitb.m
index 15bdd00..c5166bc 100644
--- a/tests/test_gpfitb.m
+++ b/tests/test_gpfitb.m
@@ -45,14 +45,18 @@ function snapshotfigures(testCase)
    end
 
    methods (Access = private)
-      function x = paretosample(testCase, alpha)
+      function x = paretosample(testCase, alpha, n)
          %PARETOSAMPLE Draw a fixed Pareto sample with pdf exponent alpha.
          %
          %  x = paretosample(testCase, alpha) returns testCase.nsamples
          %  values with lower bound testCase.xmin from the inverse CDF at
          %  midpoint quantiles. A pdf exponent alpha gives the CDF
-         %  exponent alpha - 1.
-         u = ((1:testCase.nsamples)' - 0.5)/testCase.nsamples;
+         %  exponent alpha - 1. x = paretosample(testCase, alpha, n)
+         %  returns n values.
+         if nargin < 3
+            n = testCase.nsamples;
+         end
+         u = ((1:n)' - 0.5)/n;
          x = testCase.xmin * (1 - u).^(-1/(alpha - 1));
       end
    end
@@ -84,6 +88,24 @@ function test_meanDivergesBelowPole(testCase)
          testCase.verifyEqual(returned, expected)
       end
 
+      function test_bootstrapTau0IsSigmaOverK(testCase)
+         % The tau0 replicates are sigma/k, like the point estimate, so
+         % their mean is near tau0 rather than near sigma = k*tau0. The
+         % bootstrap resamples, so fix the seed and restore the caller's.
+         rngstate = rng;
+         testCase.addTeardown(@() rng(rngstate));
+         % gpfitb draws 1000 replicates, so a small sample keeps it fast.
+         rng(1)
+         x = testCase.paretosample(3, 500);
+         expected = testCase.xmin;
+
+         Fit = baseflow.gpfitb(x, 'xmin', testCase.xmin, ...
+            'plotfit', false, 'bootfit', true);
+
+         returned = mean(Fit.tau0reps);
+         testCase.verifyEqual(returned, expected, 'RelTol', testCase.reltol)
+      end
+
       function test_labelOmitsDivergentMean(testCase)
          % Below the pole, the plot labels tau0 only. No text names a mean
          % tau, and drawarrow does not warn about a point off the log axis.
diff --git a/tests/test_plfitb.m b/tests/test_plfitb.m
index 826e2c7..b94d675 100644
--- a/tests/test_plfitb.m
+++ b/tests/test_plfitb.m
@@ -202,6 +202,17 @@ function test_meanTauAbovePole(testCase, meantail)
             'RelTol', testCase.meanreltol)
       end
 
+      function test_tailMaskIncludesXmin(testCase)
+         % plfit fits the tail x >= xmin, and xmin is one of the samples, so
+         % the tail mask that globalfit uses keeps that sample.
+         x = testCase.paretosample(testCase.tailexponent, testCase.nsample);
+
+         Fit = baseflow.plfitb(x);
+
+         testCase.assertTrue(any(x == Fit.tau0))
+         testCase.verifyTrue(all(Fit.taumask(x == Fit.tau0)))
+      end
+
       function test_meanTauDivergesBelowPole(testCase)
          % Below the pole, the mean tau is infinite and plfitb warns with
          % an identifier that names the pole.
diff --git a/tests/test_pointcloudintercept.m b/tests/test_pointcloudintercept.m
new file mode 100644
index 0000000..cb750a0
--- /dev/null
+++ b/tests/test_pointcloudintercept.m
@@ -0,0 +1,35 @@
+classdef test_pointcloudintercept < matlab.unittest.TestCase
+   %TEST_POINTCLOUDINTERCEPT Test the intercept bounds of pointcloudintercept.
+   %
+   % The bounds pivot the line through the reference point (xbar, ybar)
+   % with the slopes in bci, so a(b) = ybar/xbar^b. a is monotonic in b at
+   % a fixed pivot, so the bounds bracket ahat for every method. A flow
+   % below 1 makes log(xbar) negative, which reverses which slope bound
+   % gives the lower a.
+
+   properties (TestParameter)
+      % Methods with a reference point in flow units.
+      method = {'mean', 'median', 'envelope'}
+
+      % Flow scales that put the reference flow above and below 1.
+      flowscale = struct('above1', 1, 'below1', 1e-4)
+   end
+
+   methods (Test)
+      function test_boundsBracketTheIntercept(testCase, method, flowscale)
+         % The lower bound is at most ahat, and the upper bound at least.
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~,q,dqdt] = baseflow.generateTestData(a,b,q0,t);
+         bci = b + [-0.1 0.1];
+
+         [ahat, ahatLH] = baseflow.pointcloudintercept(flowscale*q, ...
+            flowscale*dqdt, b, method, 'bci', bci);
+
+         testCase.verifyLessThanOrEqual(ahatLH(1), ahat)
+         testCase.verifyGreaterThanOrEqual(ahatLH(2), ahat)
+      end
+   end
+end
diff --git a/tests/test_printtrend.m b/tests/test_printtrend.m
new file mode 100644
index 0000000..91a999d
--- /dev/null
+++ b/tests/test_printtrend.m
@@ -0,0 +1,20 @@
+function tests = test_printtrend
+   %TEST_PRINTTREND Test the total change baseflow.printtrend reports.
+   %
+   % printtrend fits a trend per year and reports the total change over
+   % the record, which is the trend times the years the record spans.
+   tests = functiontests(localfunctions);
+end
+
+function test_totalChangeSpansTheRecord(testCase)
+   % A monthly series that rises one unit per year from January 2000 to
+   % December 2009 spans 9.92 years, so its total change is 9.92 rather
+   % than the sample count, 120.
+   Time = (datetime(2000,1,1):calmonths(1):datetime(2009,12,1))';
+   Data = timetable(Time, years(Time - Time(1)), 'VariableNames', {'Qb'});
+   expected = sprintf('dQb = %.3f', years(Time(end) - Time(1)));
+
+   returned = evalc('baseflow.printtrend(Data);');
+
+   testCase.verifySubstring(returned, expected)
+end
diff --git a/tests/test_specialfunctions.m b/tests/test_specialfunctions.m
new file mode 100644
index 0000000..16e80f0
--- /dev/null
+++ b/tests/test_specialfunctions.m
@@ -0,0 +1,18 @@
+function tests = test_specialfunctions
+   %TEST_SPECIALFUNCTIONS Test the Rupp and Selker (2005) constants.
+   %
+   % For a homogeneous aquifer (n = 0) the late-time Rupp and Selker
+   % constant reduces to the Brutsaert and Nieber (1977) constant 4.804,
+   % which fitphi and aquiferprops use for the BS04 solution.
+   tests = functiontests(localfunctions);
+end
+
+function test_lateTimeConstantAtHomogeneousLimit(testCase)
+   % 4.804 is published to three decimals, so allow that rounding.
+   expected = 4.804;
+   tolerance = 1e-3;
+
+   returned = baseflow.specialfunctions('fR2', 0);
+
+   testCase.verifyEqual(returned, expected, 'RelTol', tolerance)
+end
diff --git a/toolbox/+baseflow/Qnonlin.m b/toolbox/+baseflow/Qnonlin.m
index eac421d..4c4d342 100755
--- a/toolbox/+baseflow/Qnonlin.m
+++ b/toolbox/+baseflow/Qnonlin.m
@@ -4,6 +4,9 @@
    % [Q,dQdt,t,hFig] = Qnonlin(a,b,Q0,t) plots a theoretical discharge predicted
    % by a/b values for Q = (Q0^(1-b)+a*(b-1).*t).^(1/(1-b));
    %
+   % b = 1 gives the exponential limit Q = Q0*exp(-a*t). For b < 1 the
+   % reservoir empties in finite time, after which Q is 0.
+   %
    % Matt Cooper, 04-Nov-2022, https://github.com/mgcooper
    %
    % See also: getfunction, QtauString, QtString
@@ -31,7 +34,7 @@
    Q = nan(numA,numB,numQ,numT);
    dQdt = nan(numA,numB,numQ,numT);
 
-   f = @(a,b,Q0,t) (Q0^(1-b)+a*(b-1).*t).^(1/(1-b));
+   f = @qsolution;
 
    % this loop is the easiest way to allow any size a,b,Q0.
    % if I wanted to restrict two of the three a,b,Q0 to be scalar and let
@@ -41,9 +44,9 @@
       for m = 1:numB
          for p = 1:numQ
 
-            qtmp = f(a(n),b(m),Q0(p),t);
+            [qtmp, dqtmp] = f(a(n),b(m),Q0(p),t);
             Q(n,m,p,:) = qtmp;
-            dQdt(n,m,p,:) = -a(n).*qtmp.^b(m);
+            dQdt(n,m,p,:) = dqtmp;
 
          end
       end
@@ -121,4 +124,23 @@
    %     flin    = @(a,Q0,t) Q0.*exp(-t.*a);
    %     out.Qlin    = fnlin(a,Q0,t);
    %     out.dQlin   = a.*Qnlin;
+end
+
+%% LOCAL FUNCTIONS
+function [Q,dQdt] = qsolution(a,b,Q0,t)
+   %QSOLUTION Flow of -dQ/dt = aQ^b at times t, from Q(0) = Q0, and its rate.
+
+   % the power law has its exponential limit at b = 1, where 1/(1-b) is Inf.
+   % For b < 1 the base reaches zero when the reservoir empties, and a
+   % negative base would give a rebound or a complex flow.
+   if b == 1
+      Q = Q0.*exp(-a.*t);
+   else
+      Q = max(Q0^(1-b)+a*(b-1).*t, 0).^(1/(1-b));
+   end
 
+   % an empty reservoir loses no more flow, but a*Q^b is not 0 at Q = 0
+   % for b <= 0
+   dQdt = -a.*Q.^b;
+   dQdt(Q == 0) = 0;
+end
diff --git a/toolbox/+baseflow/aquiferstorage.m b/toolbox/+baseflow/aquiferstorage.m
index 1b37a67..61fce8c 100644
--- a/toolbox/+baseflow/aquiferstorage.m
+++ b/toolbox/+baseflow/aquiferstorage.m
@@ -27,19 +27,19 @@
    qmax = qmax(:);
 
    % make a and b the same size
-   if numel(a) ~= numel(b) && numel(a) == 1
+   if numel(a) ~= numel(b) && isscalar(a)
       a = a.*ones(size(b));
-   elseif numel(a) ~= numel(b) && numel(b) == 1
+   elseif numel(a) ~= numel(b) && isscalar(b)
       b = b.*ones(size(a));
    end
 
    % make qmin/qmax the same size as a/b
    if numel(qmin) ~= numel(qmax)
       error('qmin and qmax must be the same size');
-   elseif numel(qmin) == numel(qmax) && numel(qmin) == 1
+   elseif numel(qmin) == numel(qmax) && isscalar(qmin)
       qmin = qmin.*ones(size(a));
       qmax = qmax.*ones(size(a));
-   elseif numel(qmin) == numel(qmax) && numel(a) == 1
+   elseif numel(qmin) == numel(qmax) && isscalar(a)
       a = a.*ones(size(qmin));
       b = b.*ones(size(qmin));
    elseif numel(qmin) == numel(qmax) && numel(qmin) ~= numel(a)
@@ -47,61 +47,17 @@
    end
 
    % v3 merges KtimeS
-   kflag = false;
    Ktime = nan(size(b));
    if nargin > 4
-      kflag = true;
       Ktime = varargin{1};
    end
-   if numel(Ktime) == 1 && numel(Ktime) ~= numel(b)
+   if isscalar(Ktime) && numel(Ktime) ~= numel(b)
       Ktime = Ktime.*ones(size(b));
    end
 
-   if numel(a) == numel(b) && numel(a) == 1
-
-      if b >= 0.95 && b <= 1.05           % linear reservoir
-
-         if kflag == true
-            Smin = Ktime*qmin;
-            Smax = Ktime*qmax;
-         else
-            Smin = 1/a.*qmin;
-            Smax = 1/a.*qmax;
-         end
-
-      elseif b >= 1.95 && b <= 2.05       % exponential
-
-         if kflag == true
-            Smin = 1/a.*log(a.*Ktime.*qmin.^2);
-            Smax = 1/a.*log(a.*Ktime.*qmax.^2);
-         else
-            Smin = 1/a.*log(qmin);
-            Smax = 1/a.*log(qmax);
-         end
-
-      elseif b>2.05                   % super exponential
-         if kflag == true
-            Smin = -Ktime/(2-b).*qmin;
-            Smax = -Ktime/(2-b).*qmax;
-         else
-            Smin = -1/a/(2-b).*(qmax.^(2-b));
-            Smax = -1/a/(2-b).*(qmin.^(2-b));
-            %dS = -1/a/(2-b).*(qmax.^(2-b)-qmin.^(2-b));
-         end
-      else                            % sub exponential
-         if kflag == true
-            Smin = -Ktime/(2-b).*qmin;
-            Smax = -Ktime/(2-b).*qmax;
-         else
-            Smin = 1/a/(2-b).*(qmin.^(2-b));
-            Smax = 1/a/(2-b).*(qmax.^(2-b));
-            %dS = 1/a/(2-b).*(qmin.^(2-b)-qmax.^(2-b));
-         end
-      end
-
-      dS = Smax-Smin;
-
-   elseif numel(a) == numel(b) && (numel(a) == numel(qmin) || numel(qmin) == 1)
+   % one path for scalar and array input, since the checks above give a, b,
+   % qmin, and qmax the same size
+   if numel(a) == numel(b) && (numel(a) == numel(qmin) || isscalar(qmin))
 
       % first determine b = 1, b = 2, and otherwise
       Smin = nan(size(a));
@@ -119,7 +75,7 @@
       % now b is ready to be used in each expression
 
       % dynamic a/b, mean qmin/qmax
-      if numel(qmin) == 1
+      if isscalar(qmin)
          qmin_b1 = qmin;
          qmin_b2 = qmin;
          qmin_b2p = qmin;
@@ -200,6 +156,7 @@
    else
       Smin = 1./a./(2-b).*(qmin.^(2-b));
       Smax = 1./a./(2-b).*(qmax.^(2-b));
+      %dS = 1/a/(2-b).*(qmin.^(2-b)-qmax.^(2-b));
    end
 end
 
@@ -211,5 +168,6 @@
       %ktime = -1./a./(2-b).*qmax;
       Smin = -1./a./(2-b).*(qmax.^(2-b));
       Smax = -1./a./(2-b).*(qmin.^(2-b));
+      %dS = -1/a/(2-b).*(qmax.^(2-b)-qmin.^(2-b));
    end
 end
\ No newline at end of file
diff --git a/toolbox/+baseflow/conversions.m b/toolbox/+baseflow/conversions.m
index 0acfc23..72c37ff 100644
--- a/toolbox/+baseflow/conversions.m
+++ b/toolbox/+baseflow/conversions.m
@@ -50,7 +50,7 @@
    %             Nstar,    from N* = 1/(N+1)
    %                 d,    from Q = cS^d, where d = 1/(2-b)
    %                 n,    from k(z) = kD(z/D)^n,
-   %                 k,    from P(Q) ~ Q^-(1+1/k)
+   %                 k,    from p(tau) ~ tau^-(1+1/k)
    %            isflat,    true if flat aquifer
    %
    %  Outputs:       b,    from dQ(t)=a*Q^b
@@ -95,6 +95,10 @@
             case false
                b = 1-N;
          end
+
+      case 'Nstar'
+         % N* = 1/(N+1), so convert through N
+         b = convert2b(1./inputvalue-1,'N',isflat);
    end
 end
 
@@ -105,14 +109,14 @@
    %  Inputs:        b,    from dQ(t)=a*Q^b
    %            isflat,    true if flat aquifer
    %
-   %  Outputs:   alpha,    from P(Q) ~ t*^-alpha
+   %  Outputs:   alpha,    from Q ~ t*^-alpha
    %              beta,    from Q ~ S^-beta (beta = -d)
    %             gamma,    from 1/gamma = 1/alpha + 1/beta
    %                 N,    from a = c1*D^N, where c1 is a coefficient
    %             Nstar,    from N* = 1/(N+1)
    %                 d,    from Q = cS^d, where d = 1/(2-b)
    %                 n,    from k(z) = kD(z/D)^n,
-   %                 k,    from P(Q) ~ Q^-(1+1/k)
+   %                 k,    from p(tau) ~ tau^-(1+1/k)
    %
    % k is the gpfit shape parameter: the gpd tail pdf ~ x^-(1+1/k) equals the
    % timescale pdf ~ x^-alpha, so k = 1/(alpha-1) = (1-b)/(b-2).
diff --git a/toolbox/+baseflow/dndtuncertainty.m b/toolbox/+baseflow/dndtuncertainty.m
index feb6dd4..45c0cd3 100644
--- a/toolbox/+baseflow/dndtuncertainty.m
+++ b/toolbox/+baseflow/dndtuncertainty.m
@@ -167,9 +167,15 @@
    % sample to correlate against the three event variables. A constant
    % column makes corr return nan, so build the correlation matrix from
    % the event variables and hold dq/dt uncorrelated with them.
+   %
+   % phifitensemble sets out-of-range phi to nan, so correlate the event
+   % variables over the events where all three exist. Dropping whole rows
+   % keeps the correlation matrix valid for the quadratic forms below.
+   events = [tau, phi, Np1];
+   R = corr(events(all(~isnan(events), 2), :));
    u = [sig_tau, sig_phi, sig_Np1, sig_dbfdt];
    C = eye(4);
-   C(1:3, 1:3) = corr([tau, phi, Np1]);
+   C(1:3, 1:3) = R;
    V = C .* u .* u';
    sig_dndt = coveragefactor * sqrt(J * V * J');
    % w/o correlated errors: sqrt(sum((J .* u).^2))
@@ -177,7 +183,7 @@
    % Compute the uncertainty on lambda (repeat above steps)
    J = [lambda./tauhat, -lambda./phihat, lambda./Nhat];
    u = [sig_tau, sig_phi, sig_Np1];
-   V = corr([tau, phi, Np1]) .* u .* u';
+   V = R .* u .* u';
    sig_lamda = coveragefactor * sqrt(J * V * J');
    % w/o correlated errors: sqrt(sum((J .* u).^2))
 
diff --git a/toolbox/+baseflow/fdcurve.m b/toolbox/+baseflow/fdcurve.m
index a09682b..78416eb 100644
--- a/toolbox/+baseflow/fdcurve.m
+++ b/toolbox/+baseflow/fdcurve.m
@@ -60,7 +60,7 @@
       end
 
       ylabel(['$x$ [' units ']']);
-      xlabel 'flow exceedence probability, $P(Q\ge x)$'
+      xlabel 'flow non-exceedance probability, $P(Q<x)$'
 
       ax.YAxis.TickLabels = compose('%g',ax.YAxis.TickValues);
       ax.XAxis.TickLabels = compose('$%g\\%%$',ax.XAxis.TickValues);
diff --git a/toolbox/+baseflow/fitab.m b/toolbox/+baseflow/fitab.m
index 8411f22..09ce6b9 100644
--- a/toolbox/+baseflow/fitab.m
+++ b/toolbox/+baseflow/fitab.m
@@ -34,7 +34,7 @@
    %              plotfit); an unknown field is an error
    %
    % Notes
-   %     weights are set zero anywhere mask is false
+   %     masked points and zero-weight points take no part in the fit
    %
    %     Use method 'envelope' to pass a line through an arbitrary x,y pair
    %     (refpoints), specified in terms of the quantile of the x/y data
@@ -94,18 +94,18 @@
       case 'ols'
          [ab,ci,ok] = fitOLS(logx,logy,weights,alpha);
       case 'qtl'
-         [ab,ci,ok] = fitQTL(logx,logy,weights,alpha,order,qtl,Nboot,inoctave);
+         [ab,ci,ok] = fitQTL(logx,logy,alpha,order,qtl,Nboot,inoctave);
       case 'mle'
          error('mle fitting not currently supported');
          % [ab,ci,ok] = fitMLE(logx,logy,weights,alpha,sigx,sigy,rxy);
       case 'nls'
          [ab,ci,ok,fselect] = fitNLS(x,y,logx,logy,weights,alpha,inoctave);
       case 'mean'
-         [ab,ci,ok] = fitLIN(logx,logy,weights,alpha,order);
+         [ab,ci,ok] = fitLIN(logx,logy,alpha,order);
       case 'median'
-         [ab,ci,ok] = fitMED(logx,logy,weights,order,inoctave);
+         [ab,ci,ok] = fitMED(logx,logy,order,inoctave);
       case 'envelope'
-         [ab,ci,ok] = fitENV(logx,logy,weights,order,refqtls,inoctave);
+         [ab,ci,ok] = fitENV(logx,logy,order,refqtls,inoctave);
    end
 
    % EVALUATE THE FIT
@@ -154,8 +154,8 @@
    % confint(fit(logx,logy,'poly1'), alpha) with fitoptions Weights.
 
    % Scale each row by the square root of its weight, so the unweighted
-   % solve minimizes sum(weights.*resid.^2). Masked points have zero weight
-   % and add nothing to the coefficients or the residuals.
+   % solve minimizes sum(weights.*resid.^2). prepfits removes masked
+   % points, so every row has a positive weight.
    sw = sqrt(weights);
    X = [sw, sw.*logx];
    [Qx,R] = qr(X,0);
@@ -163,8 +163,7 @@
    resid = sw.*logy - X*ab;
 
    % Compute coefficient standard errors from inv(X'*X) = inv(R)*inv(R)'.
-   % fit counts zero-weight (masked) points in the n-2 residual degrees of
-   % freedom, so count them here too to match confint.
+   % The n-2 residual degrees of freedom count the fitted points only.
    dfe = numel(logy) - 2;
    Rinv = R \ eye(2);
    se = sqrt(diag(Rinv*Rinv') * sum(resid.^2) / dfe);
@@ -183,15 +182,11 @@
    ok = all(isreal(ab));
 end
 
-function [ab,ci,ok] = fitLIN(logx,logy,weights,alpha,order)
+function [ab,ci,ok] = fitLIN(logx,logy,alpha,order)
    % linear model fit in log-log, equivalent to forcing a line of slope 1
    % through the mean x-y, with option to control the slope using input
    % parameter 'order'
 
-   % apply the mask / weights
-   logx = logx(weights>0);
-   logy = logy(weights>0);
-
    % impose model order if provided
    if ~isnan(order)
       logx = order.*logx;
@@ -209,13 +204,9 @@
    ok = all(isreal(ab));
 end
 
-function [ab,ci,ok] = fitMED(logx,logy,weights,order,inoctave)
+function [ab,ci,ok] = fitMED(logx,logy,order,inoctave)
    % force a line of slope 'order' through the median x-y
 
-   % apply the mask / weights
-   logx = logx(weights>0);
-   logy = logy(weights>0);
-
    logx = order*logx;
 
    if inoctave
@@ -238,7 +229,7 @@
    ok = all(isreal(ab));
 end
 
-function [ab,ci,ok] = fitENV(logx,logy,weights,order,refqtls,inoctave)
+function [ab,ci,ok] = fitENV(logx,logy,order,refqtls,inoctave)
    % force a line of slope 'order' through any two points 'refpoints' that
    % together define an 'envelope'. default x refpoint is median(x). To control
    % the vertical location of the line, set y refpoint higher or lower while
@@ -247,9 +238,6 @@
    % note: require that quantiles are passed in rather than precomputed
    % refpoints so this can use the log values or linear values
 
-   % apply the mask / weights
-   logx = logx(weights>0);
-   logy = logy(weights>0);
    logx = order.*logx;
 
    % force the line through the provided quantile
@@ -271,7 +259,7 @@
    ok = all(isreal(ab));
 end
 
-function [ab,ci,ok] = fitQTL(logx,logy,weights,alpha,order,qtl,Nboot,inoctave)
+function [ab,ci,ok] = fitQTL(logx,logy,alpha,order,qtl,Nboot,inoctave)
 
    % quantile regression
    if inoctave
@@ -289,10 +277,6 @@
       order = 1;
    end
 
-   % apply the mask / weights
-   logx = logx(weights>0);
-   logy = logy(weights>0);
-
    % fit a,b using quantile regression
    [ab,s] = quantreg(logx,logy,qtl,order,Nboot,1-alpha);
 
diff --git a/toolbox/+baseflow/generateTestData.m b/toolbox/+baseflow/generateTestData.m
index d93c107..556a65a 100644
--- a/toolbox/+baseflow/generateTestData.m
+++ b/toolbox/+baseflow/generateTestData.m
@@ -48,15 +48,10 @@
 
    t = t(:);
 
-   switch b
-      case 1
-         q = q0.*exp(-a.*t);
-         dqdt = -a.*q;
-         %q = (q(1:end)+q(2:end-1))./2;
-         %dqdt = diff(q);
-      otherwise
-         [q,dqdt,t] = baseflow.Qnonlin(a,b,q0,t,false); % false = don't make fig
-   end
+   % Qnonlin covers every b, including the exponential case b = 1
+   %q = (q(1:end)+q(2:end-1))./2;
+   %dqdt = diff(q);
+   [q,dqdt,t] = baseflow.Qnonlin(a,b,q0,t,false); % false = don't make fig
 end
 
 % % this was in baseflow.test suite ParameterizedTestBfra. I am not certain why
diff --git a/toolbox/+baseflow/getfunction.m b/toolbox/+baseflow/getfunction.m
index ca6dcfd..3540cb8 100644
--- a/toolbox/+baseflow/getfunction.m
+++ b/toolbox/+baseflow/getfunction.m
@@ -17,7 +17,7 @@
    %     for the mean tau, tau(tau0,b) = tau0*(2-b)/(3-2*b). The mean diverges
    %     at the tau pole b = 3/2 (alpha = 2) and beyond, so the handle returns
    %     Inf there. It returns NaN where no Pareto tail exists (b < 1 or
-   %     b >= 2).
+   %     b >= 2). The 'expectedTime' handle, tau0/(3-2*b), shares that pole.
    %
    %     Use tab-completion to see full list of options
    %
@@ -42,10 +42,11 @@
       case 'expectedTau'
          Fnc = @expectedtau;  % expected value of tau
       case 'expectedTime'
-         Fnc = @(tau0,b) tau0./(3-2.*b);  % expected duration of baseflow
+         % expected duration of baseflow, tau0/(3-2*b), with the tau pole
+         Fnc = @(tau0,b) expectedtau(tau0,b)./(2-b);
       case 'boftautau0'
-         Fnc = @(tau,tau0) (2*(tau-tau0)+tau)/(2*(tau-tau0)+tau0);
+         Fnc = @(tau,tau0) (2.*(tau-tau0)+tau)./(2.*(tau-tau0)+tau0);
       case 'aofa0'
-         Fnc = @(a0,b,tau,tau0) (1/tau)*(sqrt(a0*tau0)*(b-3)/(b-2))^(b-1);
+         Fnc = @(a0,b,tau,tau0) (1./tau).*(sqrt(a0.*tau0).*(b-3)./(b-2)).^(b-1);
    end
 end
diff --git a/toolbox/+baseflow/gpfitb.m b/toolbox/+baseflow/gpfitb.m
index ac37341..13ad2b7 100644
--- a/toolbox/+baseflow/gpfitb.m
+++ b/toolbox/+baseflow/gpfitb.m
@@ -72,7 +72,7 @@
    if bootfit == true
       freps = bootstrp(1000,@gpfit,x); % fit
       kreps = freps(:,1); % exponent
-      sreps = freps(:,2); % tau0
+      sreps = freps(:,2)./kreps; % tau0 = sigma/k, as for the point estimate
       breps = baseflow.conversions(kreps,'k','b');
       areps = baseflow.conversions(kreps,'k','alpha');
 
diff --git a/toolbox/+baseflow/plfitb.m b/toolbox/+baseflow/plfitb.m
index bd651c7..0b0dd1f 100644
--- a/toolbox/+baseflow/plfitb.m
+++ b/toolbox/+baseflow/plfitb.m
@@ -26,7 +26,7 @@
    %
    %     xmin     scalar double indicating the lower bound of the distribution
    %     range    the range of scaling parameters considered (see plfit.m)
-   %     limit    scalar double that sets the upper bound of fitted exponent
+   %     limit    scalar double that sets the upper bound of the fitted xmin
    %     method   char indicating one of two algorithms (Clauset's or Hanel's)
    %     bootfit  logical indicating whether to bootstrap the uncertainties
    %              (slow)
@@ -96,7 +96,7 @@
    Fit.L       = L;
    Fit.D       = D;
    Fit.k       = 1/(Fit.alpha-1);
-   Fit.taumask = x0>xmin;
+   Fit.taumask = x0>=xmin; % plfit fits the tail x >= xmin
 
    if bootfit == true
       Fit.b_L = Fit.b - BootFit.b_sig;
diff --git a/toolbox/+baseflow/pointcloudintercept.m b/toolbox/+baseflow/pointcloudintercept.m
index d81046e..0d3d3d2 100644
--- a/toolbox/+baseflow/pointcloudintercept.m
+++ b/toolbox/+baseflow/pointcloudintercept.m
@@ -23,7 +23,8 @@
    %     reference point that the line passes through. For 'envelope', they
    %     are the refqtls quantiles of q and -dqdt. For 'median' and
    %     'brutsaert', they are the medians of q and -dqdt. For 'mean', they
-   %     are the means of log(q) and log(-dqdt).
+   %     are the geometric means of q and -dqdt. ahatLH pivots the line
+   %     through (xbar, ybar) with the slopes in bci.
    %
    % Required inputs
    %
@@ -38,7 +39,7 @@
    %  refqtls  =  reference quantiles that together define a pivot point through
    %              which the straight line must pass. use with method 'envelope'.
    %  bci      =  [bL bH] confidence interval of bhat, used to compute the
-   %              bounds ahatLH (default nan, which returns NaN bounds)
+   %              bounds ahatLH (default [nan nan], which returns NaN bounds)
    %
    %
    % See also: fitab
@@ -66,9 +67,11 @@
       case 'mean'
          %ybar = mean(-dqdt(mask),'omitnan');
          %xbar = mean(q(mask),'omitnan');
-         ybar = mean(log(-dqdt(mask)),'omitnan');
-         xbar = mean(log(q(mask)),'omitnan');
-         ahat = exp(ybar - bhat*xbar);
+         % the line through the log means passes through the geometric
+         % means, which keeps xbar and ybar in linear space like the others
+         ybar = exp(mean(log(-dqdt(mask)),'omitnan'));
+         xbar = exp(mean(log(q(mask)),'omitnan'));
+         ahat = ybar/xbar^bhat;
       case 'median'
          xbar = median(q(mask),'omitnan');
          ybar = median(-dqdt(mask),'omitnan');
@@ -132,15 +135,9 @@
    end
 
    % NOTE: this isn't the best way to get aL/H, but use it for now
-   if ~isnan(bci)
-      bhatL = bci(1);
-      bhatH = bci(2);
-      ahatH = ybar/xbar^bhatL;
-      ahatL = ybar/xbar^bhatH;
-   else
-      ahatH = nan;
-      ahatL = nan;
-   end
+   % which b bound gives the lower a depends on the sign of log(xbar), so
+   % sort the pair. A nan bci gives nan bounds.
+   ahatLH = sort(ybar./xbar.^bci(:).');
 
    % PARSE OUTPUTS
    switch nargout
@@ -148,14 +145,14 @@
          varargout{1} = ahat;
       case 2
          varargout{1} = ahat;
-         varargout{2} = [ahatL ahatH];
+         varargout{2} = ahatLH;
       case 3
          varargout{1} = ahat;
          varargout{2} = xbar;
          varargout{3} = ybar;
       case 4
          varargout{1} = ahat;
-         varargout{2} = [ahatL ahatH];
+         varargout{2} = ahatLH;
          varargout{3} = xbar;
          varargout{4} = ybar;
    end
@@ -179,7 +176,7 @@
    parser.addOptional('threshold',0.05, @isnumeric);
    parser.addParameter('mask', true(size(q)), @islogical);
    parser.addParameter('refqtls', [0.5 0.5], @isnumeric);
-   parser.addParameter('bci', nan, @isnumeric);
+   parser.addParameter('bci', [nan nan], @isnumeric);
    parser.addParameter('tau', nan, @isnumeric);
    parser.addParameter('tau0', nan, @isnumeric);
 
diff --git a/toolbox/+baseflow/prepfits.m b/toolbox/+baseflow/prepfits.m
index 72382fb..27a796a 100644
--- a/toolbox/+baseflow/prepfits.m
+++ b/toolbox/+baseflow/prepfits.m
@@ -15,6 +15,9 @@
    %     weights  =  nx1 double of weights for the fitting algorithm
    %     mask     =  nx1 logical mask to exclude values from fitting
    %
+   %  note: a point with mask false or zero weight leaves every output, so
+   %  it takes no part in any fit, its residuals, or its point count
+   %
    %  note: dqdt comes in as its actual value i.e. negative
    %
    % See also: fitab
@@ -22,15 +25,11 @@
    % PARSE INPUTS
    [q, dqdt, w, m] = parseinputs(q, dqdt, varargin{:});
 
-   % keep the negative dq/dt values
-   keep = dqdt<0;
+   % keep the negative dq/dt values that the mask and weights leave in the fit
+   keep = dqdt<0 & m & w>0;
    x = abs(q(keep));
    y = abs(dqdt(keep));
    w = w(keep);
-   m = m(keep);
-
-   % convert the mask to weights
-   w(m==false) = 0;
 
    [x, y, w] = prepCurveData(x, y, w);
    [logx, logy, w] = prepCurveData(log(x), log(y), w);
diff --git a/toolbox/+baseflow/printtrend.m b/toolbox/+baseflow/printtrend.m
index d3743e2..746c014 100644
--- a/toolbox/+baseflow/printtrend.m
+++ b/toolbox/+baseflow/printtrend.m
@@ -5,6 +5,9 @@
    %
    %  [ddt,err] = printtrend(Data,varargin)
    %
+   %  ddt is the trend per year. The printed total change is ddt times the
+   %  years from the first to the last row of Data.
+   %
    % See also: aquifertrend, baseflowtrend
 
    % PARSE INPUTS
@@ -12,7 +15,7 @@
 
    % create a regular time in years, works for both months and years
    t = years(Data.Time-Data.Time(1)) + year(Data.Time(1));
-   dt = numel(t);
+   dt = t(end)-t(1); % years spanned, which scales the trend to a total change
    dat = Data.(var); % cm/yr -> cm/day
 
    switch method
diff --git a/toolbox/+baseflow/private/bootstrapci.m b/toolbox/+baseflow/private/bootstrapci.m
index 1135ba7..4a21a75 100644
--- a/toolbox/+baseflow/private/bootstrapci.m
+++ b/toolbox/+baseflow/private/bootstrapci.m
@@ -82,13 +82,14 @@
    yhatci = prctile(yyhat',conflevs)';
    yfitci = prctile(yyfit',conflevs)';
 
-   % Test for slope significance. The null hyp is that the mean is zero. If the
-   % mean is not zero, the slope is significant, reject the null (h=1).
-   b_samp = abboot(:,1); % slope is the first column (flipped in output)
-   [h, ~] = ztest(b_samp,0,std(b_samp));
+   % Test for slope significance. The null hyp is that the slope is zero. The
+   % slope is significant (h=1) when its bootstrap interval excludes zero. A
+   % z test on the replicates would divide their spread by sqrt(Nboot).
+   % The slope is the first column (flipped in output).
+   h = prod(sign(abci(:,1))) > 0;
 
    % Plot the resampled slopes
-   % figure; histogram(b_samp);
+   % figure; histogram(abboot(:,1));
 
    % Package output
    ab0               = fliplr(ab0');
diff --git a/toolbox/+baseflow/private/fitNLS_matlab.m b/toolbox/+baseflow/private/fitNLS_matlab.m
index 150bd5e..6374d17 100644
--- a/toolbox/+baseflow/private/fitNLS_matlab.m
+++ b/toolbox/+baseflow/private/fitNLS_matlab.m
@@ -3,6 +3,9 @@
    %
    %  [ab,ci,ok,fselect] = fitNLS_matlab(x,y,logx,logy,weights,alpha)
    %
+   %  alpha is a confidence level, as in fitab, so nlparci and regress
+   %  take the significance level 1-alpha.
+   %
    % See also:
 
    % initial estimates using log-log linear fit
@@ -174,11 +177,11 @@
          ci = [nan nan; nan nan];
 
       case 'nlinfit_robust'
-         ci = nlparci(ab1,R1,'covariance',C1,'alpha',alpha);
+         ci = nlparci(ab1,R1,'covariance',C1,'alpha',1-alpha);
          ab = ab1;
 
       case 'nlinfit'
-         ci = nlparci(ab2,R2,'covariance',C2,'alpha',0.68);
+         ci = nlparci(ab2,R2,'covariance',C2,'alpha',1-alpha);
          ab = ab2;
 
       case 'fit_robust'
@@ -191,7 +194,7 @@
 
       case 'linear'
 
-         [ab,ci] = regress(logy,[ones(size(y)) logx]);
+         [ab,ci] = regress(logy,[ones(size(y)) logx],1-alpha);
          ci(1,:) = exp(ci(1,:));
          ab = [exp(ab(1)); ab(2)];
 
diff --git a/toolbox/+baseflow/private/fitNLS_octave.m b/toolbox/+baseflow/private/fitNLS_octave.m
index edc8b2a..6f72c83 100644
--- a/toolbox/+baseflow/private/fitNLS_octave.m
+++ b/toolbox/+baseflow/private/fitNLS_octave.m
@@ -1,8 +1,11 @@
-function [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,~,~)
+function [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,~,alpha)
    %FITNLS_OCTAVE Fit -dQ/dt = aQ^b by nonlinear least squares in Octave.
    %
    %  [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,weights,alpha)
    %
+   %  alpha is a confidence level, as in fitab, so regress takes the
+   %  significance level 1-alpha.
+   %
    % See also
 
    % initial estimates using log-log linear fit
@@ -66,30 +69,31 @@
          ci = [nan nan; nan nan];
 
       case 'nlinfit'
-         ci = nlparci_octave(ab2, C2, 0.68);
+         ci = nlparci_octave(ab2, C2, alpha, numel(y));
          ab = ab2;
 
       case 'linear'
          %[B, BINT, R, RINT, STATS] = regress (Y, X, [ALPHA])
-         [ab,ci] = regress(logy,[ones(size(y)) logx]);
+         [ab,ci] = regress(logy,[ones(size(y)) logx],1-alpha);
          ci(1,:) = exp(ci(1,:));
          ab = [exp(ab(1)); ab(2)];
    end
 end
 
-function ci = nlparci_octave(beta, CovB, alpha)
+function ci = nlparci_octave(beta, CovB, alpha, nobs)
 
    % INPUTS:
    %   beta: coefficients from nlinfit
    %   CovB: covariance matrix from nlinfit
    %   alpha: desired confidence level (e.g., 0.68 for 68%)
+   %   nobs: number of fitted observations
    %
    % OUTPUTS:
    %   ci_lower: lower bounds of the confidence intervals
    %   ci_upper: upper bounds of the confidence intervals
 
    n = length(beta); % Number of coefficients
-   dof = n - 1; % Degrees of freedom
+   dof = nobs - n; % Residual degrees of freedom
    % t-score for desired confidence level
    t_score = tinv(1 - (1 - alpha) / 2, dof);
    se = sqrt(diag(CovB)); % Standard errors of the coefficients
diff --git a/toolbox/+baseflow/private/fitcts.m b/toolbox/+baseflow/private/fitcts.m
index c281c3a..96f8c30 100644
--- a/toolbox/+baseflow/private/fitcts.m
+++ b/toolbox/+baseflow/private/fitcts.m
@@ -23,15 +23,15 @@
    %        'C2'  centered, second order
    %        'C4'  centered, fourth order
    %
-   %     Outputs q (stencil-averaged flow), dqdt (dq./dt), dt (the
+   %     Outputs q (the flow paired with dqdt), dqdt (dq./dt), dt (the
    %     constant step), tq (the input time vector, see the note below),
    %     rq (rain posted on the same time vector), dq (the raw
-   %     difference), and tqmid (the midpoint times of the flow average q).
-   %     For B1, F1, C2, and C4, dqdt also estimates the derivative at
-   %     tqmid. For B2 and F2, dqdt estimates the derivative at tq, and
-   %     tqmid is half a step earlier (B2) or later (F2). Stencil edge
-   %     samples are nan. A single sample has no time step, so q, dqdt,
-   %     dt, dq, and tqmid are nan.
+   %     difference), and tqmid (the time of q and of the derivative that
+   %     dqdt estimates). B1 and F1 estimate the derivative half a step
+   %     back or forward, so q is the two-sample flow average. B2, F2, C2,
+   %     and C4 estimate it at the sample, so q is the sample flow. Stencil
+   %     edge samples are nan. A single sample has no time step, so q,
+   %     dqdt, dt, dq, and tqmid are nan.
    %
    % See also: fitets, fitvts, getdqdt
    %
@@ -85,13 +85,11 @@
    % at the end (since those values are the average flow over two steps)
    Qfwd = (Qi+Qip1) / 2;
    Qbwd = (Qi+Qim1) / 2;
-   Qctr = (Qip1+Qim1) / 2;
 
-   % forward, backward, and centered midpoint times, the natural posting
-   % for the stencil-averaged flow
+   % forward and backward midpoint times, where a one-step difference
+   % estimates the derivative and the two-sample average estimates the flow
    Tbwd = (Ti+Tim1) / 2;            % new
    Tfwd = (Ti+Tip1) / 2;
-   Tctr = (Tip1+Tim1) / 2;
 
    switch method
       case 'B1'                                 % backward, version 1
@@ -100,27 +98,31 @@
          tqmid = Tbwd;
       case 'B2'                                 % backward, version 2
          dq  = (3*Qi - 4*Qim1 + Qim2) / 2;
-         q   = Qbwd;
-         tqmid = Tbwd;
+         q   = Qi;
+         tqmid = Ti;
       case 'F1'                                 % forward, version 1
          dq  = Qip1-Qi;
          q   = Qfwd;
          tqmid = Tfwd;
       case 'F2'                                 % forward, version 2
          dq  = (-Qip2+4 .* Qip1 - 3*Qi) / 2;
-         q   = Qfwd;
-         tqmid = Tfwd;
+         q   = Qi;
+         tqmid = Ti;
       case 'C2'                                 % centered, version 1
          dq  = (Qip1-Qim1) / 2;
-         q   = Qctr;
-         tqmid = Tctr;
+         q   = Qi;
+         tqmid = Ti;
       case 'C4'                                 % centered, version 2
          dq  = (-Qip2 + 8*Qip1 - 8*Qim1 + Qim2) / 12;
-         q   = Qctr;
-         tqmid = Tctr;
+         q   = Qi;
+         tqmid = Ti;
    end
    dqdt = dq./dt;
 
+   % a stencil edge has no difference, so it has no paired flow or time
+   q(isnan(dq)) = nan;
+   tqmid(isnan(dq)) = nan;
+
    % Rain posts on the same time vector as tq, as in the ETS method.
    rq = R;
 
diff --git a/toolbox/+baseflow/private/fitets.m b/toolbox/+baseflow/private/fitets.m
index 2e6695e..86a9dcb 100644
--- a/toolbox/+baseflow/private/fitets.m
+++ b/toolbox/+baseflow/private/fitets.m
@@ -122,10 +122,12 @@
    % compute dq
    dq = dqdt.*dt; % need to check this, right now it isn't used anywhere
 
-   % retime to the original timestep
-   q = interp1(tq(~isnan(q)),q(~isnan(q)),T);
-   dq = interp1(tq(~isnan(dq)),dq(~isnan(dq)),T);
-   dqdt = interp1(tq(~isnan(dqdt)),dqdt(~isnan(dqdt)),T);
+   % retime to the original timestep. Interpolate over every fitted window,
+   % so a rejected window stays nan rather than taking its neighbors' slope.
+   iwin = ~isnan(tq);
+   q = interp1(tq(iwin),q(iwin),T);
+   dq = interp1(tq(iwin),dq(iwin),T);
+   dqdt = interp1(tq(iwin),dqdt(iwin),T);
 
    % Patch: post the estimates on the original time vector. It is unclear
    % what value should be used, but anything other than the original time
diff --git a/toolbox/+baseflow/private/fitvts.m b/toolbox/+baseflow/private/fitvts.m
index 2289317..b1cd8f2 100644
--- a/toolbox/+baseflow/private/fitvts.m
+++ b/toolbox/+baseflow/private/fitvts.m
@@ -58,8 +58,9 @@
          dq(n) = Q(n) - Q(n-m);
          % see notes at end on C criteria from Rupp and Selker
 
-         % dq is zero or (+), or is (-) and meets the limit criteria
-         if dq(n) >= 0 || round(abs(dq(n))) > vtsparam
+         % dq is (+), or is (-) and meets the limit criteria. A zero dq
+         % widens the window, because a flat step carries no slope.
+         if dq(n) > 0 || round(abs(dq(n))) > vtsparam
             q(n)     = 1/(m+1) * sum(Q(n-m:n));
             tq(n)    = mean(T(n-m:n)); % 1/(m+1) * sum(t(n-m:n));
             rq(n)    = 1/(m+1) * sum(R(n-m:n)); % rain
diff --git a/toolbox/+baseflow/specialfunctions.m b/toolbox/+baseflow/specialfunctions.m
index b7049a6..cd20a16 100644
--- a/toolbox/+baseflow/specialfunctions.m
+++ b/toolbox/+baseflow/specialfunctions.m
@@ -76,8 +76,10 @@
 end
 
 function fR2 = getfR2(n)
+   % late-time constant of Rupp and Selker (2005). At n = 0 it is the
+   % Brutsaert and Nieber (1977) constant 4.804 that fitphi uses for BS04.
    BR2 = beta((n+2) ./ (n+3), 1/2);
-   fR2 = (n+2) .* (BR2 ./ (n+3)) .^ (1./(n+2));
+   fR2 = (n+2) .* (BR2.^(n+3) ./ (n+3)) .^ (1./(n+2));
 end
 
 function fLo = getfLo(h0overD,soln)
diff --git a/toolbox/demos/mfiles/baseflow_demo_3.m b/toolbox/demos/mfiles/baseflow_demo_3.m
index 2409bb9..a12b680 100644
--- a/toolbox/demos/mfiles/baseflow_demo_3.m
+++ b/toolbox/demos/mfiles/baseflow_demo_3.m
@@ -155,9 +155,9 @@
 phi = baseflow.cloudphi(q,dqdt,bhat,A,D,L,'brutsaert','lateqtls',...
    opts.globalfit.lateqtls,'earlyqtls',opts.globalfit.earlyqtls);
 %% 
-% The value obtained for $\phi$ is ~0.03-0.04, similar to values obtained in 
+% The value obtained for $\phi$ is similar to values obtained in
 % other baseflow recession analysis studies. If this value is used in the |aquiferprops| 
-% function instead of the assumed value 0.01, we obtain different estimates of 
+% function instead of the assumed value 0.033, we obtain different estimates of
 % _k_ and _D_.
 
 Props = baseflow.aquiferprops(q, dqdt, ahat, bhat, 'RS05', phi, ...
diff --git a/toolbox/functionSignatures.json b/toolbox/functionSignatures.json
index 614c876..709c191 100644
--- a/toolbox/functionSignatures.json
+++ b/toolbox/functionSignatures.json
@@ -92,8 +92,8 @@
       "inputs":
       [
          {"name":"inputvalue",    "kind":"required",   "type":["double"]}, 
-         {"name":"inputvarname",  "kind":"required",   "type":[["scalar"],["char","choices={'b','alpha','beta','gamma','d','k','n','N'}"]]},
-         {"name":"outputvarname", "kind":"required",   "type":[["scalar"],["char","choices={'b','alpha','beta','gamma','d','k','n','N'}"]]},
+         {"name":"inputvarname",  "kind":"required",   "type":[["scalar"],["char","choices={'b','alpha','beta','gamma','d','k','n','N','Nstar'}"]]},
+         {"name":"outputvarname", "kind":"required",   "type":[["scalar"],["char","choices={'b','alpha','beta','gamma','d','k','n','N','Nstar'}"]]},
          {"name":"isflat",        "kind":"namevalue",  "type":["logical","scalar"],"purpose":"Option"}
       ]
    },

From 2cb51bd16397803fbc59ceb1f64ee0a323f2fbdd Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:58 -0700
Subject: [PATCH 07/28] test(baseflow): make TestBaseflow an end-to-end
 workflow suite

TestBaseflow runs baseflow_demo_kuparuk once and checks each stage
against the stages before it. It checks the recession exponent, the
globalfit tail, mean tau, and expected flows, and the baseflow trend at
the pQexp quantile. It also checks the thickness from that trend, the
uncertainty coverage factor, and the BS04 and RS05 aquifer properties
at b = 3/2. A synthetic set of exact recessions checks the
event fits and the tau sample against the known recession, and the
divergent case: Inf mean tau and NaN expected flows.

baseflowtrend requires pctl in (0,1). A NaN pctl, which a divergent
mean tau gives through pQexp, made trendplot fit the mean flow.

tests/test_corechain.m is removed. Its workflow checks are in
TestBaseflow. Its function checks are in test_gpfitb, test_plplotb,
test_fitphi, test_fitphidist, test_dndtuncertainty, and test_cloudphi.
Its aQbString check duplicates test_eqstrings.
---
 CHANGELOG.md                      |  12 +-
 STYLE.local.md                    |   2 +-
 tests/Contents.m                  |  11 +-
 tests/TestBaseflow.m              | 254 ++++++++++++++++++-
 tests/test_cloudphi.m             |  38 +++
 tests/test_corechain.m            | 390 ------------------------------
 tests/test_dndtuncertainty.m      |  15 ++
 tests/test_fitphi.m               |  60 +++++
 tests/test_fitphidist.m           |  79 ++++++
 tests/test_gpfitb.m               |  55 ++++-
 tests/test_plplotb.m              |  26 +-
 toolbox/+baseflow/baseflowtrend.m |  10 +-
 12 files changed, 536 insertions(+), 416 deletions(-)
 create mode 100644 tests/test_cloudphi.m
 delete mode 100644 tests/test_corechain.m
 create mode 100644 tests/test_dndtuncertainty.m
 create mode 100644 tests/test_fitphi.m
 create mode 100644 tests/test_fitphidist.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index ce0236f..b051900 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,8 +9,13 @@ semantic versioning.
 ### Changed
 
 - The unit tests of `tests/TestBaseflow.m` live in per-function suites,
-  `tests/test_<function_name>.m`. `TestBaseflow` keeps the workflow
-  checks that span the event-detection entry points.
+  `tests/test_<function_name>.m`. `TestBaseflow` is the integration suite
+  of the documented workflow. It runs `baseflow_demo_kuparuk` once and
+  checks each stage against the stage before it. It also checks the
+  published Kuparuk recession exponent, the BS04 and RS05 aquifer
+  properties at b = 3/2, and a synthetic divergent tail. `test_corechain`
+  is retired; its workflow checks moved to `TestBaseflow` and its
+  function checks to the suites of those functions.
 - One private function, `expectedtau`, computes the mean tau for
   `gpfitb`, `plfitb`, `plplotb`, and `baseflow.getfunction`. It alone
   raises the pole warning, `baseflow:expectedtau:tauPole`, with the count
@@ -28,6 +33,9 @@ semantic versioning.
   limit, 1.133.
 - `plfitb` puts the xmin sample in the tail mask, as `plfit` fits the
   tail x >= xmin. So the `globalfit` a and expected flows change.
+- `baseflowtrend` requires `pctl` in (0,1). A NaN `pctl`, which a
+  divergent mean tau gives through `pQexp`, made `trendplot` fit the mean
+  flow, so the baseflow equalled the mean flow.
 - `gpfitb` and `plfitb` return Inf for the mean tau at or below the tau
   pole at alpha 2. The mean of a Pareto tail diverges there. The formula
   tau0*(2-b)/(3-2*b) is negative below the pole, so `gpfitb` reported a
diff --git a/STYLE.local.md b/STYLE.local.md
index d0daf65..44500df 100644
--- a/STYLE.local.md
+++ b/STYLE.local.md
@@ -13,7 +13,7 @@ merged into it).
 - `TestBaseflow.m` is the integration suite for the toolbox workflow, so
   it keeps its PascalCase name.
 - A suite that tests several functions together keeps a descriptive
-  name: `test_corechain`, `test_eqstrings`, and `test_internal`.
+  name: `test_eqstrings` and `test_internal`.
 - Variables use short lowercase or camelCase names (`q`, `dqdt`, `gotopath`).
 
 ## Formatting
diff --git a/tests/Contents.m b/tests/Contents.m
index 7f46d21..fa3cc3f 100644
--- a/tests/Contents.m
+++ b/tests/Contents.m
@@ -9,18 +9,19 @@
 %   closenewfigs           - Delete figures opened since the FIGSBEFORE snapshot
 %   verifydecadeticks      - Verify every decade inside the axis limits has a tick
 %   octave_smoke           - Core-chain smoke test runnable in GNU Octave and MATLAB
-%   TestBaseflow           - Test the baseflow toolbox workflow (integration class)
+%   TestBaseflow           - Integration tests of the documented workflow (parameterized class)
 %   test_anomaly           - Test the private anomaly helper with vector input
 %   test_aquiferstorage    - Test the storage bounds of baseflow.aquiferstorage
 %   test_aquiferthickness  - Test the thickness of baseflow.aquiferthickness
 %   test_basinname         - Test the basin-name lookup of baseflow.basinname
 %   test_checkevent        - Test the baseflow.checkevent event plot
+%   test_cloudphi          - Test the plotfit option of baseflow.cloudphi
 %   test_breflinetext      - Test the b value text of a reference-line label
 %   test_conversions       - Test baseflow.conversions
-%   test_corechain         - Core-workflow coverage for eventtau, globalfit, cloudphi, fitphi, dndtuncertainty, gpfitb, fitphidist, aQbString
 %   test_demos             - Run every demo script in toolbox/demos/mfiles headless
 %   test_drawarrow         - Test the arrow of a reference-line label
 %   test_dependencies      - Test the dependency tooling and list agreement
+%   test_dndtuncertainty   - Test the input checks of baseflow.dndtuncertainty
 %   test_fdcurve           - Test the reference points of baseflow.fdcurve
 %   test_eqstrings         - Test the equation label helpers
 %   test_eventfinder       - Test the events baseflow.eventfinder finds in a sine
@@ -31,10 +32,12 @@
 %   test_figurevisibility  - Test the visibility of a figure asked to show
 %   test_fitevents         - Test the fitevents plotfits, fitorder, and ctsmethod options
 %   test_fitopts           - Test the fitab fitopts pass-through
+%   test_fitphi            - Test the drainable porosity of baseflow.fitphi
+%   test_fitphidist        - Test the phi distribution fit of baseflow.fitphidist
 %   test_getdqdt           - Test the getdqdt derivative and fit-plot option
 %   test_getfunction       - Test the expected-tau handle of baseflow.getfunction
 %   test_getstring         - Test the latex labels of baseflow.getstring
-%   test_gpfitb            - Test the gpfitb mean tau above and below the tau pole
+%   test_gpfitb            - Test the gpfitb parameters, mean tau, and labels
 %   test_hyetograph        - Test the figure that baseflow.hyetograph draws in
 %   test_internal          - Test the toolbox internal functions
 %   test_islabelcolor      - Test the private islabelcolor validator
@@ -51,7 +54,7 @@
 %   test_plotaquifertrend  - Test the plotaquifertrend branch handles
 %   test_plotdqdt          - Test the plotdqdt reference lines, ticks, and labels
 %   test_plotrefline       - Test the plotrefline label position
-%   test_plplotb           - Test the plplotb mean-tau label below the tau pole
+%   test_plplotb           - Test the tau0 and mean-tau labels of baseflow.plplotb
 %   test_pointcloudintercept - Test the intercept bounds of pointcloudintercept
 %   test_pointcloudplot    - Test the pointcloudplot ticks, limits, and axes
 %   test_preparecalendar   - Test the private preparecalendar helper
diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index d18886f..d315fa6 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -1,14 +1,25 @@
 classdef TestBaseflow < matlab.unittest.TestCase
    %TESTBASEFLOW Test the baseflow toolbox workflow.
-   % 
-   % TestBaseflow is the integration suite for the toolbox workflow. It
-   % holds the checks that span the event-detection entry points:
-   %     1) an equality test for the getevents, eventfinder, and wrapevents
-   %        defaults against baseflow.setopts('getevents'), and a negative
-   %        test for rmax <= 1
    %
-   % The unit tests of each function are in tests/test_<function_name>.m.
-   % test_corechain runs the analysis chain on the example data.
+   % TestBaseflow is the integration suite for the documented workflow of
+   % baseflow_demo_kuparuk and baseflow_demo_3. The class setup runs that
+   % chain once on the Kuparuk record: wrapevents, fitevents, globalfit,
+   % baseflowtrend at the expected-flow quantile, and aquiferthickness.
+   % Each test checks one stage against the stages before it and against an
+   % independent value or relationship:
+   %     1) the event-detection defaults and rmax guard of getevents,
+   %        eventfinder, and wrapevents
+   %     2) the published Kuparuk recession exponent (Cooper et al., 2023)
+   %     3) the tail, mean tau, and expected flows of globalfit
+   %     4) the baseflow trend at the expected-flow quantile
+   %     5) the aquifer thickness from that trend, and its uncertainty
+   %     6) the BS04 and RS05 aquifer properties at b = 3/2, where the two
+   %        solutions coincide
+   %
+   % A synthetic set of exact recessions, whose starting tau follows a
+   % Pareto tail with alpha = 1.5, checks the event fits and the tau sample
+   % against the known recession, and the divergent case, where the mean
+   % tau and the expected flow do not exist.
    %
    % Notes:
    %     A) A negative test verifies that the code errors/fails in an
@@ -22,11 +33,94 @@
       EventFunction = {'getevents', 'eventfinder', 'wrapevents'};
    end
 
+   properties (Constant)
+      % Kuparuk basin area [m2], drainage density [1/km], and reference
+      % aquifer thickness [m] of baseflow_demo_kuparuk.
+      A = 8.6545e9
+      Dd = 0.8
+      D = 0.47
+
+      % The recession exponent that Cooper et al. (2023) publish for the
+      % Kuparuk annual workflow, and the rounding of the published value.
+      publishedb = 1.3540
+      btol = 5e-4
+
+      % The synthetic recessions follow -dQ/dt = a*Q^b for eight days. The
+      % starting tau of each event comes from a Pareto tail with pdf
+      % exponent alpha and lower bound tau0 days.
+      synth = struct('a', 1e-3, 'b', 1.5, 'alpha', 1.5, 'tau0', 5, ...
+         'nevents', 60, 'ndays', 8)
+   end
+
    properties (Access = private)
       % Open-figure snapshot taken before each test. The method teardown
       % closes only figures the test created, so a full suite run leaves
       % zero open figures without touching pre-existing user figures.
       figsbefore
+
+      % Outputs of the Kuparuk chain, and the synthetic events, their
+      % fits, and their true tau.
+      Chain
+      Synth
+   end
+
+   methods (TestClassSetup)
+      function runkuparukchain(testCase)
+         % Run baseflow_demo_kuparuk once, without figures or the bootstrap.
+         % trendplot draws its figures off screen whatever showfig asks, so
+         % close the figures the chain leaves.
+         figsbefore = findall(0, 'Type', 'figure');
+         testCase.addTeardown(@() closenewfigs(figsbefore));
+         L = testCase.A*testCase.Dd/1000;
+         [T, Q, R] = baseflow.loadExampleData('kuparuk');
+         opts = baseflow.setopts('globalfit', 'drainagearea', testCase.A, ...
+            'aquiferdepth', testCase.D, 'streamlength', L, ...
+            'drainagedensity', testCase.Dd, 'bootfit', false, ...
+            'plotfits', false);
+         Events = baseflow.wrapevents(T, Q, R, ...
+            baseflow.setopts('getevents', 'asannual', true));
+         [Fits, K] = baseflow.fitevents(Events, baseflow.setopts('fitevents'));
+         GlobalFit = baseflow.globalfit(K, Events, Fits, opts);
+         [Qb, dQbdt, Qa] = baseflow.baseflowtrend(T, Q, testCase.A, ...
+            'pctl', GlobalFit.pQexp);
+         [Db, Sb] = baseflow.aquiferthickness(GlobalFit.b, GlobalFit.tau, ...
+            GlobalFit.phi, Qb, true);
+
+         testCase.Chain = struct('T', T, 'Q', Q, 'Events', Events, ...
+            'Fits', Fits, 'K', K, 'GlobalFit', GlobalFit, 'opts', opts, ...
+            'Qb', Qb, 'dQbdt', dQbdt, 'Qa', Qa, 'Db', Db, 'Sb', Sb, 'L', L);
+      end
+
+      function buildsyntheticevents(testCase)
+         % Exact recessions from Qnonlin, one per event, fit with the CTS
+         % stencil. tau = Q^(1-b)/a grows by b-1 per day, so day t of an
+         % event that starts at tau0 has tau = tau0 + (b-1)*t.
+         s = testCase.synth;
+         u = ((1:s.nevents)' - 0.5)/s.nevents;
+         taustart = s.tau0*(1 - u).^(-1/(s.alpha - 1));
+         tday = (0:s.ndays-1)';
+         [t, Q, tags, tautrue] = deal(cell(s.nevents, 1));
+         for k = 1:s.nevents
+            Q0 = (s.a*taustart(k))^(1/(1-s.b));
+            Q{k} = baseflow.Qnonlin(s.a, s.b, Q0, tday);
+            t{k} = 20*(k-1) + tday;
+            tags{k} = k*ones(s.ndays, 1);
+            tautrue{k} = taustart(k) + (s.b-1)*tday;
+         end
+         Events = struct('eventTime', vertcat(t{:}), ...
+            'eventFlow', vertcat(Q{:}), 'eventTags', vertcat(tags{:}));
+         Events.eventRain = zeros(size(Events.eventFlow));
+         Events.inputFlow = Events.eventFlow;
+         [Fits, K] = baseflow.fitevents(Events, 'derivmethod', 'CTS');
+
+         area = 1e9;
+         opts = baseflow.setopts('globalfit', 'drainagearea', area, ...
+            'aquiferdepth', 0.5, 'streamlength', area*testCase.Dd/1000, ...
+            'drainagedensity', testCase.Dd, 'bootfit', false, ...
+            'plotfits', false);
+         testCase.Synth = struct('Events', Events, 'Fits', Fits, 'K', K, ...
+            'opts', opts, 'tautrue', vertcat(tautrue{:}));
+      end
    end
 
    methods (TestMethodSetup)
@@ -84,5 +178,149 @@ function test_rmaxguard(testCase, EventFunction)
             ['MATLAB:' validator ':notGreater'])
       end
 
+      function test_publishedRecessionExponent(testCase)
+         % globalfit recovers the published Kuparuk recession exponent from
+         % the tau sample of the event fits.
+         returned = testCase.Chain.GlobalFit.b;
+
+         testCase.verifyEqual(returned, testCase.publishedb, ...
+            'AbsTol', testCase.btol)
+      end
+
+      function test_globalFitUsesTheTail(testCase)
+         % The tail starts at the tau0 sample and holds no tau below it. The
+         % mean tau follows tau0 and b, and the expected flows follow a, b,
+         % and the mean tau. pQexp is the share of daily flows below Qexp.
+         % a is positive and phi is a drainable porosity in (0, 1).
+         G = testCase.Chain.GlobalFit;
+         flow = testCase.Chain.Events.inputFlow;
+         flow = flow(flow > 0);
+         tol = 1e-12;
+
+         testCase.verifyTrue(all(G.taumask(G.x == G.tau0)))
+         testCase.verifyTrue(all(G.x(G.taumask) >= G.tau0))
+         testCase.verifyEqual(G.tau, G.tau0*(2-G.b)/(3-2*G.b), 'RelTol', tol)
+         testCase.verifyEqual(G.Qexp, (G.a*G.tau)^(1/(1-G.b)), 'RelTol', tol)
+         testCase.verifyEqual(G.Q0, G.Qexp*(3-G.b)/(2-G.b), 'RelTol', tol)
+         testCase.verifyEqual(G.pQexp, mean(flow < G.Qexp), ...
+            'AbsTol', 2/numel(flow))
+         testCase.verifyGreaterThan(G.a, 0)
+         testCase.verifyGreaterThan(G.phi, 0)
+         testCase.verifyLessThan(G.phi, 1)
+      end
+
+      function test_baseflowTrendAtExpectedFlowQuantile(testCase)
+         % baseflowtrend fits the pQexp quantile of the annual flow. So, within
+         % one year, at most pQexp of the years lie strictly below its line,
+         % and at least pQexp lie on or below it.
+         pQexp = testCase.Chain.GlobalFit.pQexp;
+         Qa = testCase.Chain.Qa;
+         trendline = testCase.Chain.dQbdt;
+         slack = 1/numel(Qa);
+
+         testCase.verifyLessThanOrEqual(mean(Qa < trendline), pQexp + slack)
+         testCase.verifyGreaterThanOrEqual(mean(Qa <= trendline), ...
+            pQexp - slack)
+      end
+
+      function test_thicknessFollowsBaseflow(testCase)
+         % aquiferthickness scales the baseflow of each year by one factor
+         % of tau, phi, and b, and the storage is phi times the thickness.
+         G = testCase.Chain.GlobalFit;
+         Db = testCase.Chain.Db;
+         ratio = Db./testCase.Chain.Qb;
+         tol = 1e-12;
+
+         testCase.verifyEqual(ratio, ratio(1)*ones(size(ratio)), 'RelTol', tol)
+         testCase.verifyEqual(testCase.Chain.Sb, G.phi*Db, 'RelTol', tol)
+      end
+
+      function test_uncertaintyCoverageFactor(testCase)
+         % dndtuncertainty multiplies its combined standard uncertainty by
+         % the coverage factor norminv(1-alpha/2). So the result for alpha
+         % 0.32 is the result for alpha 0.05 times the ratio of the factors.
+         % One seed gives both calls the same phi bootstrap. Qb is in cm/yr,
+         % as baseflow_demo_kuparuk passes it. No figure stays open.
+         C = testCase.Chain;
+         alpha_default = 0.05;
+         alpha_onesigma = 0.32;
+         ratio_expected = norminv(1 - alpha_onesigma/2) ...
+            / norminv(1 - alpha_default/2);
+         tol = 0.01;
+         rngstate = rng;
+         testCase.addTeardown(@() rng(rngstate));
+
+         rng(1)
+         sig_default = baseflow.dndtuncertainty(C.T, C.Qb.*365.25, C.K, ...
+            C.Fits, C.GlobalFit, C.opts, alpha_default);
+         rng(1)
+         sig_onesigma = baseflow.dndtuncertainty(C.T, C.Qb.*365.25, C.K, ...
+            C.Fits, C.GlobalFit, C.opts, alpha_onesigma);
+
+         testCase.verifyTrue(isfinite(sig_default))
+         testCase.verifyEqual(sig_onesigma/sig_default, ratio_expected, ...
+            'RelTol', tol)
+         testCase.verifyEmpty(setdiff(findall(0, 'Type', 'figure'), ...
+            testCase.figsbefore))
+      end
+
+      function test_aquiferPropsAgreeAtHomogeneousLimit(testCase)
+         % At b = 3/2 the RS05 solution has n = 0, where it reduces to the
+         % BS04 solution. So the two give the same k, D, and Q0. The BS04
+         % constant 4.804 is published to three decimals. The inputs follow
+         % baseflow_demo_3: the point cloud, its nls a, and phi = 0.033.
+         q = testCase.Chain.Fits.q;
+         dqdt = testCase.Chain.Fits.dqdt;
+         Fit = baseflow.fitab(q, dqdt, 'nls');
+         phi = 0.033;
+         Dref = 0.5;
+         tol = 1e-3;
+
+         P_expected = baseflow.aquiferprops(q, dqdt, Fit.a, 1.5, 'BS04', ...
+            phi, testCase.A, testCase.Chain.L);
+         P_returned = baseflow.aquiferprops(q, dqdt, Fit.a, 1.5, 'RS05', ...
+            phi, testCase.A, testCase.Chain.L, 'D', Dref);
+
+         testCase.verifyEqual([P_returned.k P_returned.D P_returned.Q0], ...
+            [P_expected.k P_expected.D P_expected.Q0], 'RelTol', tol)
+      end
+
+      function test_eventFitsRecoverTheRecession(testCase)
+         % fitevents recovers the b of each exact recession, and eventtau
+         % turns the event flows into the true tau of each day.
+         S = testCase.Synth;
+         b_expected = testCase.synth.b*ones(size([S.K.b]));
+         tol = 1e-2;
+
+         [tau_returned, ~, ~, tags_returned] = baseflow.eventtau(S.K, ...
+            S.Events, S.Fits, 'usefits', false);
+
+         testCase.verifyEqual([S.K.b], b_expected, 'RelTol', tol)
+         testCase.verifyEqual(tags_returned, S.Events.eventTags)
+         testCase.verifyEqual(tau_returned, S.tautrue, 'RelTol', tol)
+      end
+
+      function test_divergentTailHasNoExpectedFlow(testCase)
+         % The tau sample has alpha near 1.5, beyond the tau pole at
+         % alpha = 2, so the mean tau diverges. globalfit warns, the mean tau
+         % is Inf, and the four expected-flow outputs are NaN. The baseflow
+         % trend then has no quantile to fit, so it rejects pQexp. With
+         % plotfits false, globalfit opens no figure.
+         S = testCase.Synth;
+         poleid = 'baseflow:expectedtau:tauPole';
+         nan_expected = nan(1, 4);
+
+         G = testCase.verifyWarning(@() baseflow.globalfit(S.K, S.Events, ...
+            S.Fits, S.opts), poleid);
+
+         testCase.verifyLessThanOrEqual(G.alpha, 2)
+         testCase.verifyEqual(G.tau, Inf)
+         testCase.verifyEqual([G.Qexp G.Q0 G.pQexp G.pQ0], nan_expected)
+         testCase.verifyEmpty(setdiff(findall(0, 'Type', 'figure'), ...
+            testCase.figsbefore))
+         testCase.verifyError(@() baseflow.baseflowtrend(testCase.Chain.T, ...
+            testCase.Chain.Q, testCase.A, 'pctl', G.pQexp), ...
+            'MATLAB:InputParser:ArgumentFailedValidation')
+      end
    end
 end
diff --git a/tests/test_cloudphi.m b/tests/test_cloudphi.m
new file mode 100644
index 0000000..dbf918e
--- /dev/null
+++ b/tests/test_cloudphi.m
@@ -0,0 +1,38 @@
+function tests = test_cloudphi
+   %TEST_CLOUDPHI Test the plotfit option of baseflow.cloudphi.
+   %
+   % The inputs are the Kuparuk basin constants of the demos and a
+   % synthetic point cloud from baseflow.generateTestData.
+   tests = functiontests(localfunctions);
+end
+
+function test_cloudphiPlotfit(testCase)
+   % cloudphi draws one point-cloud figure by default and no figure with
+   % plotfit false. The plotfit flag controls only the figure, so both
+   % calls return the same phi. The late-time exponent is the linear
+   % (b = 1) value, which selects the PK62 / BS03 solution pair.
+   figsbefore = findall(0, 'Type', 'figure');
+   testCase.addTeardown(@() closenewfigs(figsbefore));
+   A = 8.6545e9;
+   D = 0.5;
+   L = A*0.8/1000;
+   blate = 1;
+   [~, q, dqdt] = baseflow.generateTestData(1e-2, 1.5, 100);
+
+   % The default call draws one figure.
+   phi_expected = baseflow.cloudphi(q, dqdt, blate, A, D, L, 'envelope');
+   newfigs_returned = numel(findall(0, 'Type', 'figure')) ...
+      - numel(figsbefore);
+   newfigs_expected = 1;
+   testCase.verifyEqual(newfigs_returned, newfigs_expected)
+
+   % The plotfit false call draws no figure and returns the same phi.
+   figsplotted = findall(0, 'Type', 'figure');
+   phi_returned = baseflow.cloudphi(q, dqdt, blate, A, D, L, 'envelope', ...
+      'plotfit', false);
+   newfigs_returned = numel(findall(0, 'Type', 'figure')) ...
+      - numel(figsplotted);
+   newfigs_expected = 0;
+   testCase.verifyEqual(newfigs_returned, newfigs_expected)
+   testCase.verifyEqual(phi_returned, phi_expected)
+end
diff --git a/tests/test_corechain.m b/tests/test_corechain.m
deleted file mode 100644
index 350ab0e..0000000
--- a/tests/test_corechain.m
+++ /dev/null
@@ -1,390 +0,0 @@
-function tests = test_corechain
-   %TEST_CORECHAIN Core-workflow coverage for the analysis chain.
-   %
-   % The other core-chain functions (getevents, fitevents, fitab,
-   % eventfinder) have coverage in TestBaseflow, test_fitab,
-   % test_fitevents, test_eventfinder, test_fitopts, and the smoke
-   % script. This file tests eventtau, globalfit, cloudphi, fitphi,
-   % and dndtuncertainty on the example data, and gpfitb, fitphidist, and
-   % aQbString on synthetic inputs. The chain runs once on the shipped
-   % example data in setupOnce; the constants are the Kuparuk basin values
-   % the demos use.
-   tests = functiontests(localfunctions);
-end
-
-function setupOnce(testCase)
-   % Run the example-data chain once; event fitting is the slow part.
-   [T, Q, R] = baseflow.loadExampleData();
-   Events = baseflow.getevents(T, Q, R, baseflow.setopts('getevents'));
-   [Fits, FitsTable] = baseflow.fitevents(Events, ...
-      baseflow.setopts('fitevents'));
-   testCase.TestData.T = T;
-   testCase.TestData.Events = Events;
-   testCase.TestData.Fits = Fits;
-   testCase.TestData.FitsTable = FitsTable;
-
-   % Kuparuk basin constants from the demos.
-   A = 8.6545e9;
-   D = 0.5;
-   drainagedensity = 0.8;
-   testCase.TestData.A = A;
-   testCase.TestData.D = D;
-   testCase.TestData.drainagedensity = drainagedensity;
-   testCase.TestData.L = A*drainagedensity/1000;
-
-   % Name the fitphi recession inputs that two tests share: the early-time
-   % and late-time a values and the linear (b = 1) late-time exponent.
-   testCase.TestData.a1 = 1e-12;
-   testCase.TestData.a2 = 1.05e-3;
-   testCase.TestData.b2_linear = 1;
-
-   % phi is a drainable porosity, so a plausible value lies in (0, 1).
-   testCase.TestData.phimin = 0;
-   testCase.TestData.phimax = 1;
-end
-
-function test_eventtauNominal(testCase)
-   % eventtau returns aligned, positive drainage timescales with valid
-   % event tags on the example-data fits.
-   mintaucount = 100;
-   [tau_returned, q_returned, dqdt_returned, tags_returned] = ...
-      baseflow.eventtau(testCase.TestData.FitsTable, ...
-      testCase.TestData.Events, testCase.TestData.Fits);
-   testCase.assertGreaterThan(numel(tau_returned), mintaucount)
-
-   % q, dqdt, and tags have one element per tau value. Event tags start
-   % at 1.
-   sizes_returned = [numel(q_returned), numel(dqdt_returned), ...
-      numel(tags_returned)];
-   sizes_expected = repmat(numel(tau_returned), 1, 3);
-   testCase.verifyEqual(sizes_returned, sizes_expected)
-   testCase.verifyTrue(all(tau_returned > 0 & isfinite(tau_returned)))
-   testCase.verifyTrue(all(tags_returned >= 1))
-end
-
-function test_globalfitNominal(testCase)
-   % globalfit produces physically plausible global parameters on the
-   % example data. The default 'pointcloud' phi method passes plotfits to
-   % cloudphi, so a fit with plotfits false opens no figure. The teardown
-   % closes any figure a failed run leaves open.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   bmin = 1;
-   bmax = 2;
-   phimin = testCase.TestData.phimin;
-   phimax = testCase.TestData.phimax;
-   gopts = baseflow.setopts('globalfit', ...
-      'drainagearea', testCase.TestData.A, ...
-      'drainagedensity', testCase.TestData.drainagedensity, ...
-      'streamlength', testCase.TestData.L, ...
-      'aquiferdepth', testCase.TestData.D, ...
-      'isflat', true, 'plotfits', false, 'bootfit', false);
-   returned = baseflow.globalfit(testCase.TestData.FitsTable, ...
-      testCase.TestData.Events, testCase.TestData.Fits, gopts);
-
-   % a and tau0 are positive, b lies in (bmin, bmax), and phi lies in
-   % (phimin, phimax).
-   testCase.verifyGreaterThan(returned.a, 0)
-   testCase.verifyGreaterThan(returned.b, bmin)
-   testCase.verifyLessThan(returned.b, bmax)
-   testCase.verifyGreaterThan(returned.tau0, 0)
-   testCase.verifyGreaterThan(returned.phi, phimin)
-   testCase.verifyLessThan(returned.phi, phimax)
-   newfigs_returned = numel(findall(0, 'Type', 'figure')) - numel(figsbefore);
-   newfigs_expected = 0;
-   testCase.verifyEqual(newfigs_returned, newfigs_expected)
-end
-
-function test_cloudphiPlotfit(testCase)
-   % cloudphi draws one point-cloud figure by default and no figure with
-   % plotfit false. The plotfit flag controls only the figure, so both
-   % calls return the same phi. The late-time exponent is the linear
-   % (b = 1) value, which selects the PK62 / BS03 solution pair.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   A = testCase.TestData.A;
-   D = testCase.TestData.D;
-   L = testCase.TestData.L;
-   blate = testCase.TestData.b2_linear;
-   [~, q, dqdt] = baseflow.eventtau(testCase.TestData.FitsTable, ...
-      testCase.TestData.Events, testCase.TestData.Fits, 'usefits', false);
-
-   % The default call draws one figure.
-   phi_expected = baseflow.cloudphi(q, dqdt, blate, A, D, L, 'envelope');
-   newfigs_returned = numel(findall(0, 'Type', 'figure')) ...
-      - numel(figsbefore);
-   newfigs_expected = 1;
-   testCase.verifyEqual(newfigs_returned, newfigs_expected)
-
-   % The plotfit false call draws no figure and returns the same phi.
-   figsplotted = findall(0, 'Type', 'figure');
-   phi_returned = baseflow.cloudphi(q, dqdt, blate, A, D, L, 'envelope', ...
-      'plotfit', false);
-   newfigs_returned = numel(findall(0, 'Type', 'figure')) ...
-      - numel(figsplotted);
-   newfigs_expected = 0;
-   testCase.verifyEqual(newfigs_returned, newfigs_expected)
-   testCase.verifyEqual(phi_returned, phi_expected)
-end
-
-function test_fitphiNominal(testCase)
-   % The PK62 early / BS03 late (b=1) pair returns one interior phi with
-   % its description; the default RS05 pair returns an interior phi for
-   % the fitted late-time exponent range.
-   A = testCase.TestData.A;
-   D = testCase.TestData.D;
-   L = testCase.TestData.L;
-   a1 = testCase.TestData.a1;
-   a2 = testCase.TestData.a2;
-   b2_linear = testCase.TestData.b2_linear;
-   b2_fitted = 1.278;
-   solns_expected = {'PK62_BS03'};
-   ndesc_expected = 2;
-   phimin = testCase.TestData.phimin;
-   phimax = testCase.TestData.phimax;
-
-   [phi_returned, solns_returned, desc_returned] = baseflow.fitphi( ...
-      a1, a2, b2_linear, A, D, L, 'soln1', 'PK62', 'soln2', 'BS03');
-   testCase.verifyEqual(solns_returned, solns_expected)
-   testCase.verifyNumElements(desc_returned, ndesc_expected)
-   testCase.verifyGreaterThan(phi_returned, phimin)
-   testCase.verifyLessThan(phi_returned, phimax)
-
-   phi_returned = baseflow.fitphi(a1, a2, b2_fitted, A, D, L);
-   testCase.verifyGreaterThan(phi_returned, phimin)
-   testCase.verifyLessThan(phi_returned, phimax)
-end
-
-function test_gpfitbNominal(testCase)
-   % gpfitb recovers the known parameters of a synthetic Pareto sample
-   % (pdf exponent 2.5: b = 1.4, k = 2/3, tau0 = xmin = 1) with no
-   % figures when the plot and bootstrap options are off. The default
-   % call runs private/ccdf.m, which must read the makeplot option as
-   % p.Results.makeplot; a read of p.makeplot errors.
-   figsbefore = findall(0, 'Type', 'figure');
-   nsamples = 5000;
-   pdfexponent = 2.5;
-   xmin = 1;
-   b_expected = 1.4;
-   k_expected = 2/3;
-   tau0_expected = xmin;
-   nfigs_expected = numel(figsbefore);
-   tol = 0.02;
-   tau0tol = 0.05;
-
-   % Inverse-CDF sample at midpoint probabilities: ccdf exponent is
-   % pdfexponent - 1.
-   u = ((1:nsamples)' - 0.5)/nsamples;
-   x = (1 - u).^(-1/(pdfexponent - 1));
-   returned = baseflow.gpfitb(x, 'xmin', xmin, ...
-      'plotfit', false, 'bootfit', false);
-   nfigs_returned = numel(findall(0, 'Type', 'figure'));
-   testCase.verifyEqual(returned.b, b_expected, 'AbsTol', tol)
-   testCase.verifyEqual(returned.k, k_expected, 'AbsTol', tol)
-   testCase.verifyEqual(returned.tau0, tau0_expected, 'AbsTol', tau0tol)
-   testCase.verifyEqual(nfigs_returned, nfigs_expected)
-end
-
-function test_gpfitbLabelDrawsAnArrow(testCase)
-   % gpfitb labels tau0 and the mean tau with an arrow, which drawarrow
-   % draws as a tagged head patch and a tagged shaft line. The exponent
-   % is above the tau pole at alpha 2, so the mean tau is positive and
-   % both labels have a point on the axes to name.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   nsamples = 5000;
-   pdfexponent = 2.5;
-   xmin = 1;
-   nlabels_expected = 2;
-
-   u = ((1:nsamples)' - 0.5)/nsamples;
-   x = (1 - u).^(-1/(pdfexponent - 1));
-   baseflow.gpfitb(x, 'xmin', xmin, 'plotfit', true, 'bootfit', false, ...
-      'labelplot', true);
-
-   ax = gca;
-   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
-      nlabels_expected)
-   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowshaft'), ...
-      nlabels_expected)
-end
-
-function test_plplotbLabelDrawsAnArrow(testCase)
-   % plplotb labels tau0 and the mean tau with the same arrow.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   nsamples = 5000;
-   pdfexponent = 2.5;
-   xmin = 1;
-   nlabels_expected = 2;
-
-   u = ((1:nsamples)' - 0.5)/nsamples;
-   x = (1 - u).^(-1/(pdfexponent - 1));
-   baseflow.plplotb(x, xmin, pdfexponent, 'labelplot', true);
-
-   ax = gca;
-   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
-      nlabels_expected)
-   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowshaft'), ...
-      nlabels_expected)
-end
-
-function test_fitphidistLabelDrawsAnArrow(testCase)
-   % The 'cdf' plot type labels the mean of phi with one arrow, which
-   % points left at the mean from a tail to its right.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   nsamples = 500;
-   phimean = 0.05;
-   phistd = 0.01;
-   phifloor = 1e-3;
-   phiceil = 0.2;
-   nlabels_expected = 1;
-   phid = min(max(phimean + phistd*randn(nsamples, 1), phifloor), phiceil);
-
-   baseflow.fitphidist(phid, 'PD', 'cdf', true);
-
-   ax = gca;
-   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
-      nlabels_expected)
-   hhead = findall(ax, 'Tag', 'refarrowhead');
-   hshaft = findall(ax, 'Tag', 'refarrowshaft');
-   testCase.verifyLessThan(min(get(hhead, 'XData')), ...
-      min(get(hshaft, 'XData')))
-end
-
-function test_fitphidistNominal(testCase)
-   % fitphidist recovers the mean of a synthetic phi sample, and with
-   % showfit false it leaves no figure open. The teardown closes any
-   % figure a failed run leaves open.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   nsamples = 500;
-   phimean = 0.05;
-   phistd = 0.01;
-   phifloor = 1e-3;
-   phiceil = 0.2;
-   showfit = false;
-   expected = phimean;
-   tol = 0.005;
-   phid = min(max(phimean + phistd*randn(nsamples, 1), phifloor), phiceil);
-   returned = baseflow.fitphidist(phid, 'mean', 'cdf', showfit);
-   testCase.verifyEqual(returned, expected, 'AbsTol', tol)
-
-   % The 'pdf' type draws no figure and returns an empty struct for h.
-   [~, h_returned] = baseflow.fitphidist(phid, 'PD', 'pdf', showfit);
-   h_expected = struct();
-   testCase.verifyEqual(h_returned, h_expected)
-   newfigs_returned = numel(findall(0, 'Type', 'figure')) - numel(figsbefore);
-   newfigs_expected = 0;
-   testCase.verifyEqual(newfigs_returned, newfigs_expected)
-end
-
-function test_dndtuncertaintyAlpha(testCase)
-   % dndtuncertainty multiplies its combined standard uncertainty by the
-   % coverage factor norminv(1-alpha/2), so the result for alpha 0.32
-   % equals the result for alpha 0.05 times the ratio of those factors. A
-   % result that ignores alpha keeps a ratio of 1. The same random seed
-   % gives both calls the same phi bootstrap. The teardown closes any
-   % figure a failed run leaves open.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   gopts = baseflow.setopts('globalfit', ...
-      'drainagearea', testCase.TestData.A, ...
-      'drainagedensity', testCase.TestData.drainagedensity, ...
-      'streamlength', testCase.TestData.L, ...
-      'aquiferdepth', testCase.TestData.D, ...
-      'isflat', true, 'plotfits', false, 'bootfit', false);
-   GlobalFit = baseflow.globalfit(testCase.TestData.FitsTable, ...
-      testCase.TestData.Events, testCase.TestData.Fits, gopts);
-
-   % One annual baseflow value per year of the example record.
-   T = testCase.TestData.T;
-   nyears = numel(unique(year(T)));
-   trendslope = 0.01;
-   oscillation = 5;
-   years = transpose(1:nyears);
-   Qb = trendslope*years + oscillation*sin(3*years);
-   alpha_default = 0.05;
-   alpha_onesigma = 0.32;
-   seed = 1;
-   tol = 0.01;
-
-   rng(seed)
-   sig_default = baseflow.dndtuncertainty(T, Qb, ...
-      testCase.TestData.FitsTable, testCase.TestData.Fits, GlobalFit, ...
-      gopts, alpha_default);
-   rng(seed)
-   sig_onesigma = baseflow.dndtuncertainty(T, Qb, ...
-      testCase.TestData.FitsTable, testCase.TestData.Fits, GlobalFit, ...
-      gopts, alpha_onesigma);
-
-   ratio_expected = norminv(1 - alpha_onesigma/2) ...
-      / norminv(1 - alpha_default/2);
-   ratio_returned = sig_onesigma / sig_default;
-   testCase.verifyEqual(ratio_returned, ratio_expected, 'RelTol', tol)
-
-   % The dq/dt column is constant, so the correlation matrix holds it
-   % uncorrelated with the event variables and the result stays finite.
-   testCase.verifyTrue(isfinite(sig_default))
-
-   % dndtuncertainty leaves no figure open.
-   newfigs_returned = numel(findall(0, 'Type', 'figure')) - numel(figsbefore);
-   newfigs_expected = 0;
-   testCase.verifyEqual(newfigs_returned, newfigs_expected)
-end
-
-function test_dndtuncertaintyInvalidAlpha(testCase)
-   % dndtuncertainty rejects an alpha outside (0, 1) before it uses the
-   % other inputs, so empty placeholders suffice.
-   alpha_invalid = 1.5;
-   testCase.verifyError(@() baseflow.dndtuncertainty([], [], [], [], ...
-      [], [], alpha_invalid), 'baseflow:dndtuncertainty:invalidAlpha')
-end
-
-function test_fitphidistProbplot(testCase)
-   % fitphidist draws the 'probplot' figure with the fitted beta
-   % distribution line when showfit is true, and leaves no figure when
-   % showfit is false. The teardown closes the figure.
-   figsbefore = findall(0, 'Type', 'figure');
-   testCase.addTeardown(@() closenewfigs(figsbefore));
-   nsamples = 200;
-   phimean = 0.05;
-   phistd = 0.01;
-   phifloor = 1e-3;
-   phiceil = 0.2;
-   phid = min(max(phimean + phistd*randn(nsamples, 1), phifloor), phiceil);
-   [~, returned] = baseflow.fitphidist(phid, 'PD', 'probplot', true);
-   testCase.verifyTrue(isgraphics(returned.fit))
-   closenewfigs(figsbefore)
-   baseflow.fitphidist(phid, 'PD', 'probplot', false);
-   newfigs_returned = numel(findall(0, 'Type', 'figure')) - numel(figsbefore);
-   newfigs_expected = 0;
-   testCase.verifyEqual(newfigs_returned, newfigs_expected)
-end
-
-function test_aQbStringNominal(testCase)
-   % aQbString builds the latex label for the recession equation.
-   ab = [1e-2 1.5];
-   returned = baseflow.aQbString(ab);
-   expected = '$-\mathrm{d}Q/\mathrm{d}t = aQ^b$';
-   testCase.verifyEqual(returned, expected)
-end
-
-function test_fitphiUnsupportedPairErrors(testCase)
-   % b2 = 1 with the default RS05 solutions remaps to a pair with no
-   % derived formula; the guard raises the documented error instead of
-   % returning unassigned outputs.
-   % fitphi warns before it falls back, and this test asks for the pair
-   % that triggers the fallback, so the warning is expected output rather
-   % than a problem to print.
-   testCase.applyFixture(matlab.unittest.fixtures.SuppressedWarningsFixture( ...
-      'baseflow:fitphi:incompatibleLateTimeSolution'));
-   a1 = testCase.TestData.a1;
-   a2 = testCase.TestData.a2;
-   b2_linear = testCase.TestData.b2_linear;
-   expected = 'baseflow:fitphi:unsupportedSolution';
-   testCase.verifyError(@() baseflow.fitphi(a1, a2, b2_linear, ...
-      testCase.TestData.A, testCase.TestData.D, testCase.TestData.L), ...
-      expected)
-end
diff --git a/tests/test_dndtuncertainty.m b/tests/test_dndtuncertainty.m
new file mode 100644
index 0000000..1b4d71b
--- /dev/null
+++ b/tests/test_dndtuncertainty.m
@@ -0,0 +1,15 @@
+function tests = test_dndtuncertainty
+   %TEST_DNDTUNCERTAINTY Test the input checks of baseflow.dndtuncertainty.
+   %
+   % The coverage-factor behavior on the Kuparuk workflow is an integration
+   % check in TestBaseflow.
+   tests = functiontests(localfunctions);
+end
+
+function test_dndtuncertaintyInvalidAlpha(testCase)
+   % dndtuncertainty rejects an alpha outside (0, 1) before it uses the
+   % other inputs, so empty placeholders suffice.
+   alpha_invalid = 1.5;
+   testCase.verifyError(@() baseflow.dndtuncertainty([], [], [], [], ...
+      [], [], alpha_invalid), 'baseflow:dndtuncertainty:invalidAlpha')
+end
diff --git a/tests/test_fitphi.m b/tests/test_fitphi.m
new file mode 100644
index 0000000..de531c3
--- /dev/null
+++ b/tests/test_fitphi.m
@@ -0,0 +1,60 @@
+function tests = test_fitphi
+   %TEST_FITPHI Test the drainable porosity of baseflow.fitphi.
+   %
+   % fitphi solves for phi from early-time and late-time recession
+   % intercepts. The inputs are the Kuparuk basin constants of the demos
+   % and recession intercepts on the scale of the example data.
+   tests = functiontests(localfunctions);
+end
+
+function test_fitphiNominal(testCase)
+   % The PK62 early / BS03 late (b=1) pair returns one interior phi with
+   % its description; the default RS05 pair returns an interior phi for
+   % the fitted late-time exponent range.
+   [A, D, L, a1, a2, b2_linear] = kuparukinputs();
+   b2_fitted = 1.278;
+   solns_expected = {'PK62_BS03'};
+   ndesc_expected = 2;
+   phimin = 0;
+   phimax = 1;
+
+   [phi_returned, solns_returned, desc_returned] = baseflow.fitphi( ...
+      a1, a2, b2_linear, A, D, L, 'soln1', 'PK62', 'soln2', 'BS03');
+   testCase.verifyEqual(solns_returned, solns_expected)
+   testCase.verifyNumElements(desc_returned, ndesc_expected)
+   testCase.verifyGreaterThan(phi_returned, phimin)
+   testCase.verifyLessThan(phi_returned, phimax)
+
+   phi_returned = baseflow.fitphi(a1, a2, b2_fitted, A, D, L);
+   testCase.verifyGreaterThan(phi_returned, phimin)
+   testCase.verifyLessThan(phi_returned, phimax)
+end
+
+function test_fitphiUnsupportedPairErrors(testCase)
+   % b2 = 1 with the default RS05 solutions remaps to a pair with no
+   % derived formula; the guard raises the documented error instead of
+   % returning unassigned outputs.
+   % fitphi warns before it falls back, and this test asks for the pair
+   % that triggers the fallback, so the warning is expected output rather
+   % than a problem to print.
+   testCase.applyFixture(matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+      'baseflow:fitphi:incompatibleLateTimeSolution'));
+   [A, D, L, a1, a2, b2_linear] = kuparukinputs();
+   expected = 'baseflow:fitphi:unsupportedSolution';
+   testCase.verifyError(@() baseflow.fitphi(a1, a2, b2_linear, A, D, L), ...
+      expected)
+end
+
+function [A, D, L, a1, a2, b2_linear] = kuparukinputs()
+   %KUPARUKINPUTS Basin constants and recession intercepts of the tests.
+   %
+   %  The Kuparuk basin area [m2], aquifer depth [m], and stream length
+   %  [m] from a drainage density of 0.8 per km, and the early-time and
+   %  late-time a values with the linear (b = 1) late-time exponent.
+   A = 8.6545e9;
+   D = 0.5;
+   L = A*0.8/1000;
+   a1 = 1e-12;
+   a2 = 1.05e-3;
+   b2_linear = 1;
+end
diff --git a/tests/test_fitphidist.m b/tests/test_fitphidist.m
new file mode 100644
index 0000000..b3a81be
--- /dev/null
+++ b/tests/test_fitphidist.m
@@ -0,0 +1,79 @@
+function tests = test_fitphidist
+   %TEST_FITPHIDIST Test the phi distribution fit of baseflow.fitphidist.
+   %
+   % fitphidist fits a beta distribution to a sample of phi and returns its
+   % mean or mode, with optional cdf, pdf, and probability plots.
+   tests = functiontests(localfunctions);
+end
+
+function test_fitphidistNominal(testCase)
+   % fitphidist recovers the mean of a synthetic phi sample, and with
+   % showfit false it leaves no figure open. The teardown closes any
+   % figure a failed run leaves open.
+   figsbefore = findall(0, 'Type', 'figure');
+   testCase.addTeardown(@() closenewfigs(figsbefore));
+   nsamples = 500;
+   phimean = 0.05;
+   phistd = 0.01;
+   phifloor = 1e-3;
+   phiceil = 0.2;
+   showfit = false;
+   expected = phimean;
+   tol = 0.005;
+   phid = min(max(phimean + phistd*randn(nsamples, 1), phifloor), phiceil);
+   returned = baseflow.fitphidist(phid, 'mean', 'cdf', showfit);
+   testCase.verifyEqual(returned, expected, 'AbsTol', tol)
+
+   % The 'pdf' type draws no figure and returns an empty struct for h.
+   [~, h_returned] = baseflow.fitphidist(phid, 'PD', 'pdf', showfit);
+   h_expected = struct();
+   testCase.verifyEqual(h_returned, h_expected)
+   newfigs_returned = numel(findall(0, 'Type', 'figure')) - numel(figsbefore);
+   newfigs_expected = 0;
+   testCase.verifyEqual(newfigs_returned, newfigs_expected)
+end
+
+function test_fitphidistLabelDrawsAnArrow(testCase)
+   % The 'cdf' plot type labels the mean of phi with one arrow, which
+   % points left at the mean from a tail to its right.
+   figsbefore = findall(0, 'Type', 'figure');
+   testCase.addTeardown(@() closenewfigs(figsbefore));
+   nsamples = 500;
+   phimean = 0.05;
+   phistd = 0.01;
+   phifloor = 1e-3;
+   phiceil = 0.2;
+   nlabels_expected = 1;
+   phid = min(max(phimean + phistd*randn(nsamples, 1), phifloor), phiceil);
+
+   baseflow.fitphidist(phid, 'PD', 'cdf', true);
+
+   ax = gca;
+   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
+      nlabels_expected)
+   hhead = findall(ax, 'Tag', 'refarrowhead');
+   hshaft = findall(ax, 'Tag', 'refarrowshaft');
+   testCase.verifyLessThan(min(get(hhead, 'XData')), ...
+      min(get(hshaft, 'XData')))
+end
+
+function test_fitphidistProbplot(testCase)
+   % fitphidist draws the 'probplot' figure with the fitted beta
+   % distribution line when showfit is true, and leaves no figure when
+   % showfit is false. The teardown closes the figure.
+   figsbefore = findall(0, 'Type', 'figure');
+   testCase.addTeardown(@() closenewfigs(figsbefore));
+   nsamples = 200;
+   phimean = 0.05;
+   phistd = 0.01;
+   phifloor = 1e-3;
+   phiceil = 0.2;
+   phid = min(max(phimean + phistd*randn(nsamples, 1), phifloor), phiceil);
+   [~, returned] = baseflow.fitphidist(phid, 'PD', 'probplot', true);
+   testCase.verifyTrue(isgraphics(returned.fit))
+   closenewfigs(figsbefore)
+   baseflow.fitphidist(phid, 'PD', 'probplot', false);
+   newfigs_returned = numel(findall(0, 'Type', 'figure')) - numel(figsbefore);
+   newfigs_expected = 0;
+   testCase.verifyEqual(newfigs_returned, newfigs_expected)
+end
diff --git a/tests/test_gpfitb.m b/tests/test_gpfitb.m
index c5166bc..f0a33b5 100644
--- a/tests/test_gpfitb.m
+++ b/tests/test_gpfitb.m
@@ -1,13 +1,15 @@
 classdef test_gpfitb < matlab.unittest.TestCase
-   %TEST_GPFITB Test the gpfitb mean tau above and below the tau pole.
+   %TEST_GPFITB Test the gpfitb parameters, mean tau, and labels.
    %
-   % A Pareto sample with lower bound xmin and pdf exponent alpha has the
-   % mean xmin*(alpha-1)/(alpha-2) for alpha > 2. The mean diverges at or
-   % below the tau pole at alpha = 2, so gpfitb must return Inf there,
-   % warn, and draw no mean-tau label. Every sample is a deterministic
-   % inverse-CDF draw, so the fit carries no sampling randomness.
+   % gpfitb recovers b, k, and tau0 of a Pareto sample. A pdf exponent of
+   % 2.5 gives b = 1.4 and k = 2/3, with tau0 = xmin. A Pareto sample with
+   % lower bound xmin and pdf exponent alpha has the mean
+   % xmin*(alpha-1)/(alpha-2) for alpha > 2. The mean diverges at or below
+   % the tau pole at alpha = 2, so gpfitb must return Inf there, warn, and
+   % draw no mean-tau label. Every sample is a deterministic inverse-CDF
+   % draw, so the fit carries no sampling randomness.
    %
-   % See also: test_corechain, test_getfunction
+   % See also: test_getfunction
 
    properties (TestParameter)
       % Each case holds a pdf exponent above the pole and the mean for
@@ -62,6 +64,45 @@ function snapshotfigures(testCase)
    end
 
    methods (Test)
+      function test_recoversParetoParameters(testCase)
+         % gpfitb recovers b, k, and tau0 of a sample with pdf exponent 2.5,
+         % with no figures when the plot and bootstrap options are off.
+         % The default call runs private/ccdf.m, which must read the
+         % makeplot option as p.Results.makeplot; a read of p.makeplot
+         % errors.
+         x = testCase.paretosample(2.5);
+         b_expected = 1.4;
+         k_expected = 2/3;
+         tol = 0.02;
+
+         returned = baseflow.gpfitb(x, 'xmin', testCase.xmin, ...
+            'plotfit', false, 'bootfit', false);
+
+         testCase.verifyEqual(returned.b, b_expected, 'AbsTol', tol)
+         testCase.verifyEqual(returned.k, k_expected, 'AbsTol', tol)
+         testCase.verifyEqual(returned.tau0, testCase.xmin, ...
+            'RelTol', testCase.reltol)
+         testCase.verifyEmpty(setdiff(findall(0, 'Type', 'figure'), ...
+            testCase.figsbefore))
+      end
+
+      function test_labelDrawsTwoArrows(testCase)
+         % Above the tau pole, gpfitb labels tau0 and the mean tau with an
+         % arrow each. drawarrow draws each arrow as a tagged head patch and
+         % a tagged shaft line.
+         x = testCase.paretosample(2.5);
+         nlabels_expected = 2;
+
+         baseflow.gpfitb(x, 'xmin', testCase.xmin, 'plotfit', true, ...
+            'bootfit', false, 'labelplot', true);
+
+         ax = gca;
+         testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
+            nlabels_expected)
+         testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowshaft'), ...
+            nlabels_expected)
+      end
+
       function test_finiteMeanAbovePole(testCase, finitetail)
          % Above the pole, tauExp is the Pareto mean and gpfitb does not
          % warn.
diff --git a/tests/test_plplotb.m b/tests/test_plplotb.m
index a8dd03c..0aefc6a 100644
--- a/tests/test_plplotb.m
+++ b/tests/test_plplotb.m
@@ -1,9 +1,9 @@
 function tests = test_plplotb
-   %TEST_PLPLOTB Test the plplotb mean-tau label below the tau pole.
+   %TEST_PLPLOTB Test the tau0 and mean-tau labels of baseflow.plplotb.
    %
    % The mean of a Pareto tail diverges at or below the tau pole at
-   % alpha = 2, so the label has no point on the axes to name. The label
-   % above the pole is tested in test_corechain.
+   % alpha = 2, so the label has no point on the axes to name. Above the
+   % pole, the label names tau0 and the mean tau.
    tests = functiontests(localfunctions);
 end
 
@@ -33,3 +33,23 @@ function test_labelOmitsDivergentMean(testCase)
    labels_returned = get(findall(h.ax, 'Type', 'text'), 'String');
    testCase.verifyFalse(any(contains(labels_returned, 'langle')))
 end
+
+function test_plplotbLabelDrawsAnArrow(testCase)
+   % plplotb labels tau0 and the mean tau with the same arrow.
+   figsbefore = findall(0, 'Type', 'figure');
+   testCase.addTeardown(@() closenewfigs(figsbefore));
+   nsamples = 5000;
+   pdfexponent = 2.5;
+   xmin = 1;
+   nlabels_expected = 2;
+
+   u = ((1:nsamples)' - 0.5)/nsamples;
+   x = (1 - u).^(-1/(pdfexponent - 1));
+   baseflow.plplotb(x, xmin, pdfexponent, 'labelplot', true);
+
+   ax = gca;
+   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowhead'), ...
+      nlabels_expected)
+   testCase.verifyNumElements(findall(ax, 'Tag', 'refarrowshaft'), ...
+      nlabels_expected)
+end
diff --git a/toolbox/+baseflow/baseflowtrend.m b/toolbox/+baseflow/baseflowtrend.m
index 82602e1..fb6808b 100644
--- a/toolbox/+baseflow/baseflowtrend.m
+++ b/toolbox/+baseflow/baseflowtrend.m
@@ -19,6 +19,13 @@
    %     Q: discharge [m3/d], posted daily, numeric vector
    %     A: basin area [m2], numeric scalar
    %
+   % Optional name-value inputs
+   %
+   %     pctl: quantile of the baseflow regression, in (0,1). Default 0.25.
+   %     globalfit returns pQexp, the quantile of the expected flow. pQexp is
+   %     NaN when the mean tau diverges, and baseflowtrend rejects it rather
+   %     than fit the mean flow.
+   %
    % Outputs
    %
    %     Qb: baseflow expected value [cm/d], posted annually, numeric vector
@@ -81,7 +88,8 @@
    parser.addRequired('Q', @isnumericvector);
    parser.addRequired('A', @isnumericscalar);
    parser.addParameter('method', 'ols', @ischarlike);
-   parser.addParameter('pctl', 0.25, @isnumericscalar);
+   parser.addParameter('pctl', 0.25, ...
+      @(x) isnumericscalar(x) && x > 0 && x < 1);
    parser.addParameter('showfig', false, @islogicalscalar);
    parser.parse(t,Q,A,varargin{:});
 

From cedc7621b7459cd5e54b74cf8e771fef2ab89395 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 08/28] fix(baseflow): keep a given streamlength and accept
 leap-day calendars

- setopts and globalfit default drainagedensity to NaN. The default of
  0.8 overrode a streamlength given alone with A*0.8/1000 and warned.
  globalfit compares the two only when both are given, with a sqrt(eps)
  relative tolerance, so A*Dd/1000 computed in another order raises no
  warning. The warning has the identifier
  baseflow:globalfit:inconsistentStreamlength. L does not enter the
  flat phi solutions, so no result changes.
- dndtuncertainty takes the years that T spans directly. It reshaped
  the padded record into 365-day rows, which a leap day breaks. The
  result on a no-leap calendar is unchanged.
- TestBaseflow checks both on the Kuparuk chain: a streamlength given
  alone or within rounding raises no warning and an inconsistent pair
  warns; a calendar with leap days gives the no-leap uncertainty.
---
 CHANGELOG.md                           | 11 ++++++
 tests/TestBaseflow.m                   | 54 +++++++++++++++++++++++++-
 toolbox/+baseflow/dndtuncertainty.m    | 14 ++++---
 toolbox/+baseflow/globalfit.m          |  9 +++--
 toolbox/+baseflow/setopts.m            |  5 ++-
 toolbox/docs/baseflow_gettingStarted.m |  2 +-
 6 files changed, 82 insertions(+), 13 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index b051900..34a357d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -121,6 +121,17 @@ semantic versioning.
   catch one by name. The tests that ask for a solution pair `fitphi`
   falls back from now suppress the warning they expect, as do the tests
   that run a fit to the iteration limit of `nlinfit`.
+- `globalfit` keeps a `streamlength` given without `drainagedensity`.
+  `setopts` and `globalfit` gave `drainagedensity` a default of 0.8,
+  which replaced that `streamlength` with A*0.8/1000 and warned. The
+  default is NaN. A `streamlength` within rounding of A*Dd/1000 raises no
+  warning, and the warning has the identifier
+  `baseflow:globalfit:inconsistentStreamlength`. The flat-aquifer phi
+  solutions do not use L, so no result changes.
+- `dndtuncertainty` accepts a daily calendar with leap days. It reshaped
+  the record into 365-day rows, which a leap day breaks. It takes the
+  years that T spans directly, so the result on a no-leap calendar is
+  unchanged.
 
 ## [1.2.0] - 2026-09-17
 
diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index d315fa6..59a15f1 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -10,9 +10,11 @@
    %     1) the event-detection defaults and rmax guard of getevents,
    %        eventfinder, and wrapevents
    %     2) the published Kuparuk recession exponent (Cooper et al., 2023)
-   %     3) the tail, mean tau, and expected flows of globalfit
+   %     3) the tail, mean tau, and expected flows of globalfit, and its
+   %        check of a given streamlength against a given drainage density
    %     4) the baseflow trend at the expected-flow quantile
-   %     5) the aquifer thickness from that trend, and its uncertainty
+   %     5) the aquifer thickness from that trend, and its uncertainty on
+   %        calendars with and without leap days
    %     6) the BS04 and RS05 aquifer properties at b = 3/2, where the two
    %        solutions coincide
    %
@@ -209,6 +211,33 @@ function test_globalFitUsesTheTail(testCase)
          testCase.verifyLessThan(G.phi, 1)
       end
 
+      function test_streamlengthKeptUnlessInconsistent(testCase)
+         % globalfit replaces a given streamlength with A*Dd/1000 only when
+         % a given drainage density disagrees with it. So the Kuparuk fit
+         % raises no warning for a streamlength given alone. It also raises
+         % none for a streamlength that equals A*Dd/1000 up to the rounding
+         % of the product order. For an area of 3e9 and a density of 0.7,
+         % A*Dd/1000 and Dd/1000*A differ in the last bit.
+         C = testCase.Chain;
+         area = 3e9;
+         density = 0.7;
+         alone = C.opts;
+         alone.drainagedensity = nan;
+         alone.streamlength = testCase.A/1000;
+         rounded = C.opts;
+         rounded.drainagearea = area;
+         rounded.drainagedensity = density;
+         rounded.streamlength = area*density/1000;
+         inconsistent = alone;
+         inconsistent.drainagedensity = density;
+         fit = @(opts) baseflow.globalfit(C.K, C.Events, C.Fits, opts);
+
+         testCase.verifyWarningFree(@() fit(alone))
+         testCase.verifyWarningFree(@() fit(rounded))
+         testCase.verifyWarning(@() fit(inconsistent), ...
+            'baseflow:globalfit:inconsistentStreamlength')
+      end
+
       function test_baseflowTrendAtExpectedFlowQuantile(testCase)
          % baseflowtrend fits the pQexp quantile of the annual flow. So, within
          % one year, at most pQexp of the years lie strictly below its line,
@@ -264,6 +293,27 @@ function test_uncertaintyCoverageFactor(testCase)
             testCase.figsbefore))
       end
 
+      function test_uncertaintyAcceptsLeapDays(testCase)
+         % dndtuncertainty uses T only for the calendar years of Qb. A daily
+         % calendar with leap days spans the same years as the Kuparuk
+         % record, which has none. So one seed gives the same uncertainty
+         % for both.
+         C = testCase.Chain;
+         years = year(C.T([1 end]));
+         Tleap = transpose(datetime(years(1), 1, 1):datetime(years(2), 12, 31));
+         rngstate = rng;
+         testCase.addTeardown(@() rng(rngstate));
+
+         rng(1)
+         expected = baseflow.dndtuncertainty(C.T, C.Qb.*365.25, C.K, ...
+            C.Fits, C.GlobalFit, C.opts);
+         rng(1)
+         returned = baseflow.dndtuncertainty(Tleap, C.Qb.*365.25, C.K, ...
+            C.Fits, C.GlobalFit, C.opts);
+
+         testCase.verifyEqual(returned, expected)
+      end
+
       function test_aquiferPropsAgreeAtHomogeneousLimit(testCase)
          % At b = 3/2 the RS05 solution has n = 0, where it reduces to the
          % BS04 solution. So the two give the same k, D, and Q0. The BS04
diff --git a/toolbox/+baseflow/dndtuncertainty.m b/toolbox/+baseflow/dndtuncertainty.m
index 45c0cd3..e566b93 100644
--- a/toolbox/+baseflow/dndtuncertainty.m
+++ b/toolbox/+baseflow/dndtuncertainty.m
@@ -27,6 +27,10 @@
    %  solutions to the one-dimensional groundwater flow equation for a
    %  Boussinesq aquifer, and parameter b from -dQ/dt = aQb.
    %
+   %  T is the daily time of the flow record (datetime or datenum), with or
+   %  without leap days. Qb holds one baseflow value in cm/yr for each
+   %  calendar year that T spans.
+   %
    %  alpha is the significance level of the returned uncertainty (default
    %  0.05, a 95% interval). Each input uncertainty is a standard error
    %  (one sigma): the drainable porosity from the phi bootstrap, and tau
@@ -66,15 +70,13 @@
    end
    coveragefactor = norminv(1 - alpha/2);
 
-   % Convert time in days to years
+   % Convert time in days to years. Qb holds one value per calendar year,
+   % so T reduces to the years it spans. A calendar with leap days does
+   % not split into 365-day rows, so take the years directly.
    if isdatetime(T)
       T = todatenum(T);
    end
-
-   t1 = datenum(year(T(1)), 1, 1);
-   t2 = datenum(year(T(end)), 12, 31);
-   [~, T] = padtimeseries(nan(size(T)), T, t1, t2, 1); %#ok<*DATNM>
-   T = transpose(year(mean(reshape(T, 365, numel(T)/365))));
+   T = transpose(year(T(1)):year(T(end)));
 
    if numel(T) ~= numel(Qb)
       error('size T must match size Qb')
diff --git a/toolbox/+baseflow/globalfit.m b/toolbox/+baseflow/globalfit.m
index 9c499ed..a340141 100644
--- a/toolbox/+baseflow/globalfit.m
+++ b/toolbox/+baseflow/globalfit.m
@@ -153,7 +153,7 @@
    parser.addRequired('Events', @isstruct);
    parser.addRequired('Fits', @isstruct);
    parser.addParameter('drainagearea', nan, @isnumericscalar);
-   parser.addParameter('drainagedensity', 0.8, @isnumericscalar);
+   parser.addParameter('drainagedensity', nan, @isnumericscalar);
    parser.addParameter('aquiferdepth', nan, @isnumericscalar);
    parser.addParameter('streamlength', nan, @isnumericscalar);
    parser.addParameter('aquiferslope', 0, @isnumericscalar);
@@ -189,9 +189,12 @@
    % if stream length and drainage density are both provided, check that they
    % are consistent with the provided area. note: Dd comes in as 1/km b/c that's
    % how it is almost always reported (km/km2). divide by 1000 to get 1/m.
+   % Both default to nan, so a default never replaces a provided L. The
+   % relative tolerance accepts the rounding of L = A*Dd/1000 computed in
+   % another order.
    if ~isnan(Dd) && ~isnan(L)
-      if Dd/1000*A ~= L        % 1/m * m^2 = m
-         warning( ...
+      if abs(Dd/1000*A - L) > sqrt(eps)*L        % 1/m * m^2 = m
+         warning('baseflow:globalfit:inconsistentStreamlength', ...
             'provided streamlength, L, inconsistent with L=A*Dd. Using L=A*Dd');
          L = Dd/1000*A;
       end
diff --git a/toolbox/+baseflow/setopts.m b/toolbox/+baseflow/setopts.m
index b43d3d8..599530d 100644
--- a/toolbox/+baseflow/setopts.m
+++ b/toolbox/+baseflow/setopts.m
@@ -69,6 +69,9 @@
    %
    %     drainagearea   : drainage area [m2]
    %     drainagedensity: drainage density [km-1] = streamlength/drainagearea
+   %                      (default nan). When both are given and differ,
+   %                      globalfit uses streamlength = drainagearea*
+   %                      drainagedensity/1000.
    %     aquiferdepth   : reference aquifer thickness [m]
    %     streamlength   : effective channel length [m]
    %     aquiferslope   : effective aquifer slope
@@ -144,7 +147,7 @@
       case 'globalfit'
 
          addParameter(p,   'drainagearea',      nan,        @isnumericscalar );
-         addParameter(p,   'drainagedensity',   0.8,        @isnumericscalar );
+         addParameter(p,   'drainagedensity',   nan,        @isnumericscalar );
          addParameter(p,   'aquiferdepth',      nan,        @isnumericscalar );
          addParameter(p,   'streamlength',      nan,        @isnumericscalar );
          addParameter(p,   'aquiferslope',      0.0,        @isnumericscalar );
diff --git a/toolbox/docs/baseflow_gettingStarted.m b/toolbox/docs/baseflow_gettingStarted.m
index 3f11a1c..e8d2649 100644
--- a/toolbox/docs/baseflow_gettingStarted.m
+++ b/toolbox/docs/baseflow_gettingStarted.m
@@ -124,7 +124,7 @@
 %%
 % 
 %       drainagearea      : (numeric scalar) Drainage area upstream of streamflow gauge [m2]. Default = NaN.
-%       drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = 0.8.
+%       drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = NaN.
 %       aquiferdepth      : (numeric scalar) Reference aquifer thickness [m]. Default = NaN.
 %       streamlength      : (numeric scalar) Effective channel length [m]. Default = NaN.
 %       aquiferslope      : (numeric scalar) Effective aquifer slope [-]. Default = 0.0.

From 1619d9f666435e1b486d79ec28eb16e10f066f0d Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 09/28] fix(baseflow): repair cloudphi userab, phi domain,
 fitab order, rounding

- cloudphi uses userab = [a b] as the late-time line and fits the
  early-time line to the point cloud. Its userab branch was empty, so
  a call with userab failed.
- fitphidist leaves a phi outside [0, 1] out of the beta fit and warns
  baseflow:fitphidist:phiOutsideUnitInterval with the count. betafit
  errored on such a value, so globalfit 'distfit' failed. 'phicombo'
  shares this check.
- fitab 'mean' with no order fits the slope-1 line it documents and
  returns b = 1; it returned NaN. 'median' and 'envelope' document no
  default slope, so they raise baseflow:fitab:orderRequired.
- aquiferstorage rounds b with round(100*b)/100, which Octave supports.
  tests/octave_smoke.m checks the storage at b = 3/2.
---
 CHANGELOG.md                       | 14 ++++++++++++++
 tests/octave_smoke.m               | 13 ++++++++++++-
 tests/test_cloudphi.m              | 30 +++++++++++++++++++++++++++++-
 tests/test_fitab.m                 | 25 +++++++++++++++++++++++++
 tests/test_fitphidist.m            | 16 ++++++++++++++++
 toolbox/+baseflow/aquiferstorage.m |  5 +++--
 toolbox/+baseflow/cloudphi.m       | 18 +++++++++++++-----
 toolbox/+baseflow/fitab.m          | 22 +++++++++++++++++-----
 toolbox/+baseflow/fitphidist.m     | 16 ++++++++++++++++
 toolbox/+baseflow/globalfit.m      |  2 +-
 toolbox/+baseflow/setopts.m        |  3 ++-
 11 files changed, 148 insertions(+), 16 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 34a357d..f1fd9b9 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -121,6 +121,14 @@ semantic versioning.
   catch one by name. The tests that ask for a solution pair `fitphi`
   falls back from now suppress the warning they expect, as do the tests
   that run a fit to the iteration limit of `nlinfit`.
+- `cloudphi` uses the `userab` line as the late-time line and still fits
+  the early-time line to the point cloud. A call with `userab` failed
+  with an undefined variable.
+- `fitphidist` leaves a phi outside [0, 1] out of the beta fit and warns
+  `baseflow:fitphidist:phiOutsideUnitInterval` with the count. `betafit`
+  errored on such a value, so `globalfit` 'distfit' failed when one event
+  gave a phi above 1. 'phicombo' set those values to NaN without a
+  warning, and it shares the `fitphidist` check.
 - `globalfit` keeps a `streamlength` given without `drainagedensity`.
   `setopts` and `globalfit` gave `drainagedensity` a default of 0.8,
   which replaced that `streamlength` with A*0.8/1000 and warned. The
@@ -128,10 +136,16 @@ semantic versioning.
   warning, and the warning has the identifier
   `baseflow:globalfit:inconsistentStreamlength`. The flat-aquifer phi
   solutions do not use L, so no result changes.
+- `aquiferstorage` runs on Octave. It rounded b with `round(b,2)`, and
+  the Octave `round` takes one argument.
 - `dndtuncertainty` accepts a daily calendar with leap days. It reshaped
   the record into 365-day rows, which a leap day breaks. It takes the
   years that T spans directly, so the result on a no-leap calendar is
   unchanged.
+- `fitab` 'mean' with no `order` returns b = 1, the slope of the line it
+  fits. It returned NaN. 'median' and 'envelope' document no default
+  slope, so without `order` they raise `baseflow:fitab:orderRequired`.
+  'median' failed in `signrank`, and 'envelope' returned NaN.
 
 ## [1.2.0] - 2026-09-17
 
diff --git a/tests/octave_smoke.m b/tests/octave_smoke.m
index 325a3ec..b8de32e 100644
--- a/tests/octave_smoke.m
+++ b/tests/octave_smoke.m
@@ -3,7 +3,8 @@
 % Plain script with bare asserts: load the example data, detect events,
 % fit events, fit the a-b parameters with 'nls' and 'ols', then draw the
 % point cloud, the event-scale fit plot, and a labeled reference line,
-% which are the figures with an Octave-specific branch.
+% which are the figures with an Octave-specific branch. Last, compute
+% aquifer storage, which must use a round that Octave supports.
 % TestSuite.fromFolder skips this script (not a valid test file), so it
 % does not join the MATLAB suite. Run it directly with
 % run('tests/octave_smoke.m') in either language. The script closes the
@@ -140,4 +141,14 @@
 assert(nheads == 1)
 assert(nshafts == 1)
 
+% compute aquifer storage. aquiferstorage rounds b to two decimals with
+% the one-argument round, which Octave also provides. For b = 3/2, the
+% storage of flow q is q^(2-b)/(a*(2-b)).
+astore = 1e-2;
+bstore = 1.5;
+qstore = [1 4];
+[Smin, Smax] = baseflow.aquiferstorage(astore, bstore, qstore(1), qstore(2));
+S_expected = qstore.^(2-bstore)/(astore*(2-bstore));
+assert(max(abs([Smin Smax] - S_expected)) <= 1e-12*max(S_expected))
+
 disp('octave_smoke: all asserts passed')
diff --git a/tests/test_cloudphi.m b/tests/test_cloudphi.m
index dbf918e..0f55425 100644
--- a/tests/test_cloudphi.m
+++ b/tests/test_cloudphi.m
@@ -1,5 +1,5 @@
 function tests = test_cloudphi
-   %TEST_CLOUDPHI Test the plotfit option of baseflow.cloudphi.
+   %TEST_CLOUDPHI Test the plotfit and userab options of baseflow.cloudphi.
    %
    % The inputs are the Kuparuk basin constants of the demos and a
    % synthetic point cloud from baseflow.generateTestData.
@@ -36,3 +36,31 @@ function test_cloudphiPlotfit(testCase)
    testCase.verifyEqual(newfigs_returned, newfigs_expected)
    testCase.verifyEqual(phi_returned, phi_expected)
 end
+
+function test_userabSetsTheLateTimeLine(testCase)
+   % userab sets the late-time line, and the early-time line still comes
+   % from the point cloud. Every quantile of a cloud of one repeated point
+   % (q, -dq/dt) = (2, 1/2) is that point. So the early-time line of slope
+   % 3 has a1 = (1/2)/2^3. With the late-time b = 3/2 of userab, the PK62
+   % and BS04 solutions of Troch et al. (1993) give phi =
+   % 1.133^(1/3)*4.804^(2/3)/(D*A*a1^(1/3)*a2^(2/3)). blate = 1 would select
+   % the BS03 solution, so the result also shows blate does not enter phi.
+   A = 8.6545e9;
+   D = 0.5;
+   L = A*0.8/1000;
+   blate = 1;
+   npoints = 10;
+   q = 2*ones(npoints, 1);
+   dqdt = -0.5*ones(npoints, 1);
+   a1 = 0.5/2^3;
+   userab = [1e-11 3/2];
+   phi_expected = 1.133^(1/3)*4.804^(2/3) ...
+      /(D*A*a1^(1/3)*userab(1)^(2/3));
+   tol = 1e-12;
+
+   [phi_returned, a_returned] = baseflow.cloudphi(q, dqdt, blate, A, D, L, ...
+      'envelope', 'userab', userab, 'plotfit', false);
+
+   testCase.verifyEqual(phi_returned, phi_expected, 'RelTol', tol)
+   testCase.verifyEqual(a_returned, userab(1))
+end
diff --git a/tests/test_fitab.m b/tests/test_fitab.m
index fe1efb9..16e6672 100644
--- a/tests/test_fitab.m
+++ b/tests/test_fitab.m
@@ -11,6 +11,9 @@
       FitMethod = {'ols','nls','mean','median'};
       RecessionExponent = {1.0,1.5}; % linear and non-linear
       OrderOption = struct('default', {{}}, 'order1', {{'order', 1}});
+
+      % The fixed-slope methods with no documented default slope.
+      FixedSlopeMethod = {'median','envelope'};
    end
 
    methods (Test)
@@ -229,5 +232,27 @@ function test_nlsHonorsMask(testCase)
 
          testCase.verifyEqual(returned,expected)
       end
+
+      function test_meanDefaultsToSlopeOne(testCase)
+         % 'mean' with no 'order' is the mean difference of log -dq/dt and
+         % log q: the slope-1 line through the mean of the logs. So b = 1
+         % and a is the geometric mean of -dq/dt/q.
+         [~,q,dqdt] = baseflow.generateTestData(1e-2,1.5,100,1:100);
+         expected = [exp(mean(log(-dqdt./q))); 1];
+         tol = 1e-12;
+
+         returned = baseflow.fitab(q,dqdt,'mean');
+
+         testCase.verifyEqual(returned.ab,expected,'RelTol',tol)
+      end
+
+      function test_fixedSlopeNeedsOrder(testCase,FixedSlopeMethod)
+         % 'median' and 'envelope' fix the slope of the line, and neither
+         % documents a default slope, so a call with no 'order' errors.
+         [~,q,dqdt] = baseflow.generateTestData(1e-2,1.5,100,1:100);
+
+         testCase.verifyError(@() baseflow.fitab(q,dqdt,FixedSlopeMethod), ...
+            'baseflow:fitab:orderRequired')
+      end
    end
 end
diff --git a/tests/test_fitphidist.m b/tests/test_fitphidist.m
index b3a81be..0b470c7 100644
--- a/tests/test_fitphidist.m
+++ b/tests/test_fitphidist.m
@@ -77,3 +77,19 @@ function test_fitphidistProbplot(testCase)
    newfigs_expected = 0;
    testCase.verifyEqual(newfigs_returned, newfigs_expected)
 end
+
+function test_phiOutsideUnitIntervalIsLeftOut(testCase)
+   % A phi outside [0, 1] is not a porosity, and the beta distribution
+   % cannot hold it. fitphidist leaves it out of the fit with a warning. So
+   % the mean equals the mean of the beta fit to the values inside [0, 1].
+   phi_inside = [0.02; 0.03; 0.04; 0.05; 0.06; 0.08];
+   phi_outside = [1.7; -0.2];
+   params = betafit(phi_inside);
+   expected = betastat(params(1), params(2));
+
+   returned = testCase.verifyWarning(@() baseflow.fitphidist( ...
+      [phi_inside; phi_outside], 'mean'), ...
+      'baseflow:fitphidist:phiOutsideUnitInterval');
+
+   testCase.verifyEqual(returned, expected)
+end
diff --git a/toolbox/+baseflow/aquiferstorage.m b/toolbox/+baseflow/aquiferstorage.m
index 61fce8c..f9b4311 100644
--- a/toolbox/+baseflow/aquiferstorage.m
+++ b/toolbox/+baseflow/aquiferstorage.m
@@ -19,8 +19,9 @@
    % if called with no input, open this file
    if nargin == 0; open(mfilename('fullpath')); return; end
 
-   % input checks
-   b = round(b,2);
+   % input checks. Round b to two decimals. Octave's round takes no digit
+   % count, so round 100*b and divide by 100.
+   b = round(100*b)/100;
    a = a(:);
    b = b(:);
    qmin = qmin(:);
diff --git a/toolbox/+baseflow/cloudphi.m b/toolbox/+baseflow/cloudphi.m
index 7095474..784e24d 100644
--- a/toolbox/+baseflow/cloudphi.m
+++ b/toolbox/+baseflow/cloudphi.m
@@ -35,6 +35,10 @@
    %                 The late-time line uses the input method, and only
    %                 method 'envelope' reads lateqtls. Default is
    %                 [0.5 0.5].
+   %     userab      late-time [a b] of a line the user chose. cloudphi then
+   %                 uses this line in place of the line it fits at blate,
+   %                 and blate does not enter phi. Default is [] (fit the
+   %                 late-time line).
    %     mask        logical mask to exclude data
    %     theta       effective slope of basin contributing area
    %     isflat      logical flag indicating if horizontal or sloped aquifer
@@ -71,12 +75,15 @@
    % a2 = late-time a
    % b2 = late-time b (bhat or theoretical solution b=1 or b=3/2)
 
-   if isnan(userab)
+   % The early-time line always comes from the point cloud. A user line in
+   % userab replaces the late-time line fitted at blate.
+   a1 = baseflow.pointcloudintercept(q,dqdt,3,'envelope','refqtls',earlyqtls);
+   if isempty(userab)
       b2 = blate;
-      a1 = baseflow.pointcloudintercept(q,dqdt,3,'envelope','refqtls',earlyqtls);
       a2 = baseflow.pointcloudintercept(q,dqdt,b2,method,'refqtls',lateqtls,'mask',mask);
    else
-
+      a2 = userab(1);
+      b2 = userab(2);
    end
 
    switch b2
@@ -97,7 +104,7 @@
    if plotfit
       % make a dummy handle for the legend and print the value of phi
       baseflow.pointcloudplot(q,dqdt,'blate',blate,'mask',mask,'reflines', ...
-         {'early','userfit'},'userab',[a2 blate],'reflabels',true);
+         {'early','userfit'},'userab',[a2 b2],'reflabels',true);
       hdum = plot(0,0,'Color','none','HandleVisibility','off');
 
       if isoctave
@@ -130,7 +137,8 @@
    addRequired(parser, 'method', @ischar);
    addParameter(parser,'earlyqtls',[0.95 0.95], @isnumeric);
    addParameter(parser,'lateqtls', [0.5 0.5], @isnumeric);
-   addParameter(parser,'userab', nan, @isnumeric);
+   addParameter(parser,'userab', [], ...
+      @(x) isempty(x) || isnumericvector(x) && numel(x) == 2);
    addParameter(parser,'mask', true(size(q)), @islogical);
    addParameter(parser,'theta', 0, @isnumeric);
    addParameter(parser,'isflat', true,  @islogical);
diff --git a/toolbox/+baseflow/fitab.m b/toolbox/+baseflow/fitab.m
index 09ce6b9..cdce873 100644
--- a/toolbox/+baseflow/fitab.m
+++ b/toolbox/+baseflow/fitab.m
@@ -23,7 +23,10 @@
    %
    %     weights  vector double of weights for the fitting algorithm
    %     mask     vector logical mask to exclude values from fitting
-   %     order    scalar, exponent in -dq/dt = aQ^b
+   %     order    scalar, exponent in -dq/dt = aQ^b. Methods 'mean',
+   %              'median', and 'envelope' fix the slope to order. 'mean'
+   %              uses order 1 when it is not given; 'median' and
+   %              'envelope' raise baseflow:fitab:orderRequired.
    %     refqtls  2x1 double, x/y quantiles used if 'method' == 'envelope'
    %     quantile scalar double, quantile used if 'method' == 'qtl' (quantile
    %              regression)
@@ -187,10 +190,8 @@
    % through the mean x-y, with option to control the slope using input
    % parameter 'order'
 
-   % impose model order if provided
-   if ~isnan(order)
-      logx = order.*logx;
-   end
+   % impose model order. parseinputs sets order 1 when it is not given.
+   logx = order.*logx;
 
    [~,~,ci] = ttest(-logx,-logy,'Alpha',1-alpha);
 
@@ -455,6 +456,17 @@
       end
    end
 
+   % 'mean' fits the slope-1 line through the mean of log q and log -dq/dt
+   % when 'order' is not given. 'median' and 'envelope' state no default
+   % slope, so they need 'order'.
+   if isnan(order) && strcmp(method, 'mean')
+      order = 1;
+   elseif isnan(order) && any(strcmp(method, {'median', 'envelope'}))
+      error('baseflow:fitab:orderRequired', ...
+         'method ''%s'' fixes the slope of the fit, so it needs ''order''', ...
+         method)
+   end
+
    % Expand a scalar weight or mask to every point, because prepfits
    % indexes both point by point. The parser default for mask is the
    % numeric 1, so convert it to logical for prepfits.
diff --git a/toolbox/+baseflow/fitphidist.m b/toolbox/+baseflow/fitphidist.m
index 3eeda7d..e3091d0 100644
--- a/toolbox/+baseflow/fitphidist.m
+++ b/toolbox/+baseflow/fitphidist.m
@@ -28,6 +28,11 @@
    %     showfit is a logical flag (default true). With showfit false, these
    %     two types delete their figure. For 'pdf', h is an empty struct.
    %
+   %     The beta fit uses the values of phi in [0, 1] and ignores nan.
+   %     fitphidist leaves a value outside [0, 1] out of the fit and raises
+   %     the warning baseflow:fitphidist:phiOutsideUnitInterval with the
+   %     count.
+   %
    % See also: eventphi, fitphi, fitphidist
    %
    % Matt Cooper, 22-Oct-2022, https://github.com/mgcooper
@@ -41,6 +46,17 @@
    % Force all inputs to be column vectors
    phi = phi(:);
 
+   % The beta distribution holds values in [0, 1], and a phi outside that
+   % interval is not a porosity. Leave those values out of the fit, and
+   % warn with their count so the caller knows the sample shrank.
+   outside = phi < 0 | phi > 1;
+   if any(outside)
+      warning('baseflow:fitphidist:phiOutsideUnitInterval', ...
+         ['%d of %d values of phi lie outside [0, 1], so the beta fit ' ...
+         'leaves them out.'], nnz(outside), numel(phi))
+      phi = phi(~outside);
+   end
+
    % Fit the beta distribution
    [PARAMHAT, PARAMCI] = betafit(phi);
    [M, V] = betastat(PARAMHAT(1), PARAMHAT(2));
diff --git a/toolbox/+baseflow/globalfit.m b/toolbox/+baseflow/globalfit.m
index a340141..427271f 100644
--- a/toolbox/+baseflow/globalfit.m
+++ b/toolbox/+baseflow/globalfit.m
@@ -97,7 +97,7 @@
             'lateqtls', lateqtls, 'earlyqtls', earlyqtls);
          phi2 = baseflow.eventphi(Results, Fits, A, D, L, 3/2, ...
             'lateqtls', lateqtls, 'earlyqtls', earlyqtls);
-         phid = vertcat(phi1, phi2); phid(phid>1) = nan; phid(phid<0) = nan;
+         phid = vertcat(phi1, phi2);
          phi = baseflow.fitphidist(phid, 'mean', 'cdf', plotfits);
    end
 
diff --git a/toolbox/+baseflow/setopts.m b/toolbox/+baseflow/setopts.m
index 599530d..f64d325 100644
--- a/toolbox/+baseflow/setopts.m
+++ b/toolbox/+baseflow/setopts.m
@@ -42,7 +42,8 @@
    %
    %     derivmethod    : derivative (dQ/dt) method: 'ETS', 'VTS', or 'CTS'
    %     fitmethod      : -dQ/dt = aQb fitting method
-   %     fitorder       : fitting order (value of exponent b)
+   %     fitorder       : fitting order (value of exponent b). fitmethod
+   %                      'median' or 'envelope' needs it; see fitab.
    %     pickfits       : pick fits manually?
    %     pickmethod     : method to fit picks manually
    %     plotfits       : plot each event fit? fitevents passes this flag

From 56e6395ec9af36350bdd8fa365f29a896dd5ee91 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 10/28] fix(baseflow): correct the RS05 early-time constant fR1

getfR1 divides the root mu by 4-2*gamma, as equation 33 of Rupp and
Selker (2005) prints. It divided by 4*(1-2*gamma). That gave 0.869 at
n = 0 for the published 1.108, a pole at n = 1, and negative values
above n = 2.4. fR1/(n+1) is their Phi1 (eqs 54 and 56), and fR2/2 is
their Phi2 (eq 59). phi from the RS05 solutions changes again for every
b other than 1 and 3/2.

test_specialfunctions sweeps the seven rows of their Table 1 for both
constants, within half a unit of the printed fourth significant figure.
---
 CHANGELOG.md                         | 13 ++++-
 tests/test_specialfunctions.m        | 71 +++++++++++++++++++++++-----
 toolbox/+baseflow/specialfunctions.m | 10 +++-
 3 files changed, 78 insertions(+), 16 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index f1fd9b9..0f76df0 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -29,8 +29,17 @@ semantic versioning.
   Brutsaert and Nieber (1977) constant 4.804; it gave 1.857. `globalfit`
   uses the RS05 solutions by default, so its phi changes for every b
   other than 1 and 3/2. `aquiferprops` 'RS05' gives the 'BS04' k at
-  b = 3/2. The early-time constant fR1 still disagrees with its n = 0
-  limit, 1.133.
+  b = 3/2. fR2/2 matches the Phi2 column of Rupp and Selker (2005)
+  Table 1 for n from 0 to 64.
+- The early-time Rupp and Selker (2005) constant fR1 in
+  `specialfunctions` divides the root mu by 4-2*gamma, as their equation
+  33 prints. It divided by 4*(1-2*gamma), which gave 0.869 at n = 0, a
+  pole at n = 1, and negative values above n = 2.4.
+  fR1/(n+1) matches the Phi1 column (m = 1) of their Table 1 for n from 0
+  to 64, with 1.108 at n = 0. So `globalfit` phi changes again for every
+  b other than 1 and 3/2. A result that divides by phi, such as the
+  thickness from `aquiferthickness` and `aquifertrend`, changes with it.
+  A storage trend does not depend on phi.
 - `plfitb` puts the xmin sample in the tail mask, as `plfit` fits the
   tail x >= xmin. So the `globalfit` a and expected flows change.
 - `baseflowtrend` requires `pctl` in (0,1). A NaN `pctl`, which a
diff --git a/tests/test_specialfunctions.m b/tests/test_specialfunctions.m
index 16e80f0..371d57c 100644
--- a/tests/test_specialfunctions.m
+++ b/tests/test_specialfunctions.m
@@ -1,18 +1,65 @@
-function tests = test_specialfunctions
+classdef test_specialfunctions < matlab.unittest.TestCase
    %TEST_SPECIALFUNCTIONS Test the Rupp and Selker (2005) constants.
    %
-   % For a homogeneous aquifer (n = 0) the late-time Rupp and Selker
-   % constant reduces to the Brutsaert and Nieber (1977) constant 4.804,
-   % which fitphi and aquiferprops use for the BS04 solution.
-   tests = functiontests(localfunctions);
-end
+   % Rupp and Selker (2005) Table 1 lists the early-time constant Phi1
+   % (weighted residual with m = 1) and the late-time constant Phi2 for
+   % seven values of n in k(z) = kD*(z/D)^n. specialfunctions returns
+   % fR1 = (n+1)*Phi1, the prefactor of their eq 54 for a1. It returns
+   % fR2 = 2*Phi2, the form their eq 57 for a2 takes in fitphi and
+   % aquiferprops. For a homogeneous aquifer (n = 0), fR2 reduces to the
+   % Brutsaert and Nieber (1977) constant 4.804, which fitphi and
+   % aquiferprops use for the BS04 solution.
+
+   properties (TestParameter)
+      % The rows of Table 1: n, Phi1, and Phi2 as published.
+      Table1 = struct( ...
+         'n0', struct('n', 0, 'Phi1', 1.108, 'Phi2', 2.402), ...
+         'n1_4', struct('n', 1/4, 'Phi1', 1.337, 'Phi2', 2.538), ...
+         'n1_2', struct('n', 1/2, 'Phi1', 1.588, 'Phi2', 2.690), ...
+         'n1', struct('n', 1, 'Phi1', 2.151, 'Phi2', 3.030), ...
+         'n2', struct('n', 2, 'Phi1', 3.528, 'Phi2', 3.787), ...
+         'n4', struct('n', 4, 'Phi1', 7.279, 'Phi2', 5.445), ...
+         'n64', struct('n', 64, 'Phi1', 739.8, 'Phi2', 63.17))
+   end
+
+   methods (Test)
+      function test_earlyTimeConstantMatchesTable1(testCase, Table1)
+         % fR1 has no pole at n = 1 and stays positive for large n.
+         expected = Table1.Phi1;
+
+         returned = baseflow.specialfunctions('fR1', Table1.n)/(Table1.n + 1);
+
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', halfunit(expected))
+      end
+
+      function test_lateTimeConstantMatchesTable1(testCase, Table1)
+         % fR2 carries the exponent n+3 on the Beta function.
+         expected = Table1.Phi2;
 
-function test_lateTimeConstantAtHomogeneousLimit(testCase)
-   % 4.804 is published to three decimals, so allow that rounding.
-   expected = 4.804;
-   tolerance = 1e-3;
+         returned = baseflow.specialfunctions('fR2', Table1.n)/2;
 
-   returned = baseflow.specialfunctions('fR2', 0);
+         testCase.verifyEqual(returned, expected, ...
+            'AbsTol', halfunit(expected))
+      end
 
-   testCase.verifyEqual(returned, expected, 'RelTol', tolerance)
+      function test_lateTimeConstantAtHomogeneousLimit(testCase)
+         % 4.804 is published to three decimals, 0.001 below the 4.805 of
+         % the Rupp and Selker formula, so allow 1e-3 relative.
+         expected = 4.804;
+         bntol = 1e-3;
+
+         returned = baseflow.specialfunctions('fR2', 0);
+
+         testCase.verifyEqual(returned, expected, 'RelTol', bntol)
+      end
+   end
+end
+
+function tol = halfunit(value)
+   %HALFUNIT Half a unit in the fourth significant figure of a value.
+   %
+   % Table 1 prints every value to four significant figures, so a correct
+   % constant lies within half a unit of the last printed digit.
+   tol = 0.5*10^(floor(log10(value)) - 3);
 end
diff --git a/toolbox/+baseflow/specialfunctions.m b/toolbox/+baseflow/specialfunctions.m
index cd20a16..07785f5 100644
--- a/toolbox/+baseflow/specialfunctions.m
+++ b/toolbox/+baseflow/specialfunctions.m
@@ -1,7 +1,9 @@
 function varargout = specialfunctions(funcname, varargin)
    % SPECIALFUNCTIONS Special function ibarary required for recession analysis.
    %
-   %  fnc = specialfunctions(fR1) returns the inverse incomplete beta function
+   %  fR1 = specialfunctions('fR1', n) and fR2 = specialfunctions('fR2', n)
+   %  return the early-time and late-time constants of Rupp and Selker
+   %  (2005) for the conductivity profile k(z) = kD*(z/D)^n.
    %
    % See also: Qnonlin
    %
@@ -69,15 +71,19 @@
 
 %% Local Functions
 function fR1 = getfR1(n)
+   % early-time constant of Rupp and Selker (2005), eqs 33 and 56, m = 1.
+   % gamma is their A (eq 28). fR1/(n+1) is their Phi1 (Table 1: 1.108 at
+   % n = 0), because a1 here uses kD, as their eq 54 does.
    BR1     = beta(n+2, 2);
    gamma   = 2 * (n+2) .* BR1;
-   mu      = (4 - 3*gamma - sqrt(gamma.^2 - 2*gamma + 4)) ./ (4*(1 - 2*gamma));
+   mu      = (4 - 3*gamma - sqrt(gamma.^2 - 2*gamma + 4)) ./ (4 - 2*gamma);
    fR1     = (1-mu) .* (n+1) .* (n+2) ./ (2 * (1 - 2*mu));
 end
 
 function fR2 = getfR2(n)
    % late-time constant of Rupp and Selker (2005). At n = 0 it is the
    % Brutsaert and Nieber (1977) constant 4.804 that fitphi uses for BS04.
+   % fR2/2 is their Phi2 (eq 59; Table 1: 2.402 at n = 0).
    BR2 = beta((n+2) ./ (n+3), 1/2);
    fR2 = (n+2) .* (BR2.^(n+3) ./ (n+3)) .^ (1./(n+2));
 end

From 778d89093e6b3dee2a2a0d5b8a8ff51884910bea Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 11/28] fix(baseflow): fit slope 1 by default for fitab
 'median' and 'envelope'

'mean', 'median', and 'envelope' fix the slope of the line, and each
uses slope 1, the linear reservoir, when order is not given. Without
order, 'median' raised a signrank error or baseflow:fitab:orderRequired,
and 'envelope' returned NaN or the same error.

test_fitab checks each method against the definition: log a is the
center of log -dq/dt minus the center of log q, with the mean or the
median as the center.
---
 CHANGELOG.md                |  5 ++---
 tests/test_fitab.m          | 34 ++++++++++++++++------------------
 toolbox/+baseflow/fitab.m   | 16 +++++-----------
 toolbox/+baseflow/setopts.m |  3 ++-
 4 files changed, 25 insertions(+), 33 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 0f76df0..5c535a3 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -151,9 +151,8 @@ semantic versioning.
   the record into 365-day rows, which a leap day breaks. It takes the
   years that T spans directly, so the result on a no-leap calendar is
   unchanged.
-- `fitab` 'mean' with no `order` returns b = 1, the slope of the line it
-  fits. It returned NaN. 'median' and 'envelope' document no default
-  slope, so without `order` they raise `baseflow:fitab:orderRequired`.
+- `fitab` 'mean', 'median', and 'envelope' fit a line of slope 1 when
+  `order` is not given, and return b = 1. 'mean' returned b = NaN,
   'median' failed in `signrank`, and 'envelope' returned NaN.
 
 ## [1.2.0] - 2026-09-17
diff --git a/tests/test_fitab.m b/tests/test_fitab.m
index 16e6672..7d1acd2 100644
--- a/tests/test_fitab.m
+++ b/tests/test_fitab.m
@@ -12,8 +12,8 @@
       RecessionExponent = {1.0,1.5}; % linear and non-linear
       OrderOption = struct('default', {{}}, 'order1', {{'order', 1}});
 
-      % The fixed-slope methods with no documented default slope.
-      FixedSlopeMethod = {'median','envelope'};
+      % The methods that fix the slope of the line, 1 by default.
+      FixedSlopeMethod = {'mean','median','envelope'};
    end
 
    methods (Test)
@@ -233,26 +233,24 @@ function test_nlsHonorsMask(testCase)
          testCase.verifyEqual(returned,expected)
       end
 
-      function test_meanDefaultsToSlopeOne(testCase)
-         % 'mean' with no 'order' is the mean difference of log -dq/dt and
-         % log q: the slope-1 line through the mean of the logs. So b = 1
-         % and a is the geometric mean of -dq/dt/q.
-         [~,q,dqdt] = baseflow.generateTestData(1e-2,1.5,100,1:100);
-         expected = [exp(mean(log(-dqdt./q))); 1];
+      function test_fixedSlopeDefaultsToOne(testCase,FixedSlopeMethod)
+         % A fixed-slope method with no 'order' fits a line of slope 1, so
+         % b = 1. Then log a is the center of log -dq/dt minus the center
+         % of log q. The center is the mean for 'mean', and the median for
+         % 'median' and for 'envelope' at its default refqtls [0.5 0.5].
+         % An odd number of points makes each median one of the points.
+         [~,q,dqdt] = baseflow.generateTestData(1e-2,1.5,100,1:101);
+         if strcmp(FixedSlopeMethod,'mean')
+            center = @mean;
+         else
+            center = @median;
+         end
+         expected = [exp(center(log(-dqdt)) - center(log(q))); 1];
          tol = 1e-12;
 
-         returned = baseflow.fitab(q,dqdt,'mean');
+         returned = baseflow.fitab(q,dqdt,FixedSlopeMethod);
 
          testCase.verifyEqual(returned.ab,expected,'RelTol',tol)
       end
-
-      function test_fixedSlopeNeedsOrder(testCase,FixedSlopeMethod)
-         % 'median' and 'envelope' fix the slope of the line, and neither
-         % documents a default slope, so a call with no 'order' errors.
-         [~,q,dqdt] = baseflow.generateTestData(1e-2,1.5,100,1:100);
-
-         testCase.verifyError(@() baseflow.fitab(q,dqdt,FixedSlopeMethod), ...
-            'baseflow:fitab:orderRequired')
-      end
    end
 end
diff --git a/toolbox/+baseflow/fitab.m b/toolbox/+baseflow/fitab.m
index cdce873..a76dee7 100644
--- a/toolbox/+baseflow/fitab.m
+++ b/toolbox/+baseflow/fitab.m
@@ -24,9 +24,8 @@
    %     weights  vector double of weights for the fitting algorithm
    %     mask     vector logical mask to exclude values from fitting
    %     order    scalar, exponent in -dq/dt = aQ^b. Methods 'mean',
-   %              'median', and 'envelope' fix the slope to order. 'mean'
-   %              uses order 1 when it is not given; 'median' and
-   %              'envelope' raise baseflow:fitab:orderRequired.
+   %              'median', and 'envelope' fix the slope to order, which
+   %              is 1 when it is not given.
    %     refqtls  2x1 double, x/y quantiles used if 'method' == 'envelope'
    %     quantile scalar double, quantile used if 'method' == 'qtl' (quantile
    %              regression)
@@ -456,15 +455,10 @@
       end
    end
 
-   % 'mean' fits the slope-1 line through the mean of log q and log -dq/dt
-   % when 'order' is not given. 'median' and 'envelope' state no default
-   % slope, so they need 'order'.
-   if isnan(order) && strcmp(method, 'mean')
+   % 'mean', 'median', and 'envelope' fix the slope of the line. Without
+   % 'order' the slope is 1, the linear reservoir.
+   if isnan(order) && any(strcmp(method, {'mean', 'median', 'envelope'}))
       order = 1;
-   elseif isnan(order) && any(strcmp(method, {'median', 'envelope'}))
-      error('baseflow:fitab:orderRequired', ...
-         'method ''%s'' fixes the slope of the fit, so it needs ''order''', ...
-         method)
    end
 
    % Expand a scalar weight or mask to every point, because prepfits
diff --git a/toolbox/+baseflow/setopts.m b/toolbox/+baseflow/setopts.m
index f64d325..5db1cfa 100644
--- a/toolbox/+baseflow/setopts.m
+++ b/toolbox/+baseflow/setopts.m
@@ -43,7 +43,8 @@
    %     derivmethod    : derivative (dQ/dt) method: 'ETS', 'VTS', or 'CTS'
    %     fitmethod      : -dQ/dt = aQb fitting method
    %     fitorder       : fitting order (value of exponent b). fitmethod
-   %                      'median' or 'envelope' needs it; see fitab.
+   %                      'mean', 'median', or 'envelope' uses 1 when it
+   %                      is nan; see fitab.
    %     pickfits       : pick fits manually?
    %     pickmethod     : method to fit picks manually
    %     plotfits       : plot each event fit? fitevents passes this flag

From 6e7fde99dc35b127060d8ae2cbb87881088381c4 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 12/28] fix(baseflow): round b in aquiferstorage only to choose
 the formula

aquiferstorage rounds b to two decimals to pick the linear, exponential,
or power-law storage, and the power-law formulas use the unrounded b.
At b = 1.567 the rounded b changed the storage by +2.1% at q = 0.01 and
-3.4% at q = 1e6. test_aquiferstorage checks the closed form at
b = 1.567.
---
 CHANGELOG.md                       |  5 ++++-
 tests/octave_smoke.m               |  6 +++---
 tests/test_aquiferstorage.m        | 18 ++++++++++++++++++
 toolbox/+baseflow/aquiferstorage.m | 16 +++++++++-------
 4 files changed, 34 insertions(+), 11 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5c535a3..e835dca 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -146,7 +146,10 @@ semantic versioning.
   `baseflow:globalfit:inconsistentStreamlength`. The flat-aquifer phi
   solutions do not use L, so no result changes.
 - `aquiferstorage` runs on Octave. It rounded b with `round(b,2)`, and
-  the Octave `round` takes one argument.
+  the Octave `round` takes one argument. It rounds b to two decimals
+  only to choose the formula, and the power-law formulas use the
+  unrounded b. At b = 1.567 the rounded b changed the storage by +2.1% at
+  q = 0.01 and -3.4% at q = 1e6.
 - `dndtuncertainty` accepts a daily calendar with leap days. It reshaped
   the record into 365-day rows, which a leap day breaks. It takes the
   years that T spans directly, so the result on a no-leap calendar is
diff --git a/tests/octave_smoke.m b/tests/octave_smoke.m
index b8de32e..9357f9b 100644
--- a/tests/octave_smoke.m
+++ b/tests/octave_smoke.m
@@ -141,9 +141,9 @@
 assert(nheads == 1)
 assert(nshafts == 1)
 
-% compute aquifer storage. aquiferstorage rounds b to two decimals with
-% the one-argument round, which Octave also provides. For b = 3/2, the
-% storage of flow q is q^(2-b)/(a*(2-b)).
+% compute aquifer storage. aquiferstorage rounds b to two decimals to
+% choose its formula, with the one-argument round, which Octave also
+% provides. For b = 3/2, the storage of flow q is q^(2-b)/(a*(2-b)).
 astore = 1e-2;
 bstore = 1.5;
 qstore = [1 4];
diff --git a/tests/test_aquiferstorage.m b/tests/test_aquiferstorage.m
index fd0876e..7cfe96e 100644
--- a/tests/test_aquiferstorage.m
+++ b/tests/test_aquiferstorage.m
@@ -51,5 +51,23 @@ function test_ktimeStorage(testCase,RecessionExponent)
 
          testCase.verifyEqual([Smin_returned,Smax_returned],S_expected);
       end
+
+      function test_storageUsesUnroundedB(testCase)
+         % aquiferstorage rounds b to two decimals only to choose the
+         % formula. b = 1.567 takes the power-law storage q^(2-b)/(a*(2-b))
+         % with b itself. Rounding b to 1.57 in the formula would shift the
+         % storage of q = 1e4 by about 3.5%.
+         a = 1;
+         b = 1.567;
+         q = [1 1e4];
+         S_expected = q.^(2-b)/(a*(2-b));
+         tol = 1e-12;
+
+         [Smin_returned,Smax_returned] = baseflow.aquiferstorage( ...
+            a,b,q(1),q(2));
+
+         testCase.verifyEqual([Smin_returned,Smax_returned],S_expected, ...
+            'RelTol',tol);
+      end
    end
 end
diff --git a/toolbox/+baseflow/aquiferstorage.m b/toolbox/+baseflow/aquiferstorage.m
index f9b4311..a20eac3 100644
--- a/toolbox/+baseflow/aquiferstorage.m
+++ b/toolbox/+baseflow/aquiferstorage.m
@@ -19,9 +19,7 @@
    % if called with no input, open this file
    if nargin == 0; open(mfilename('fullpath')); return; end
 
-   % input checks. Round b to two decimals. Octave's round takes no digit
-   % count, so round 100*b and divide by 100.
-   b = round(100*b)/100;
+   % input checks
    a = a(:);
    b = b(:);
    qmin = qmin(:);
@@ -64,10 +62,14 @@
       Smin = nan(size(a));
       Smax = nan(size(a));
 
-      % find indices where b = 1, b = 2, and b! = 2
-      ib1 = b >= 0.95 & b <= 1.05;
-      ib2 = b >= 1.95 & b <= 2.05;
-      ib2p = b>2.05;
+      % find indices where b = 1, b = 2, and b! = 2. Round b to two
+      % decimals only to choose the formula; the power-law formulas use
+      % the unrounded b. Octave's round takes no digit count, so round
+      % 100*b and divide by 100.
+      bround = round(100*b)/100;
+      ib1 = bround >= 0.95 & bround <= 1.05;
+      ib2 = bround >= 1.95 & bround <= 2.05;
+      ib2p = bround>2.05;
       ib2m = true(size(b)); ib2m(ib1|ib2|ib2p) = false;
       b(ib1) = 1.0;
       b(ib2) = 2.0;

From d1c12532414e8df411acaec4e069413f5508602f Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 13/28] fix(internal): build the doc search database after the
 pages

makedocs built the search database before it published the doc pages
and the m2html function pages, so the database indexed stale pages.
makedocs builds the database last.
---
 toolbox/+baseflow/+internal/makedocs.m | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/toolbox/+baseflow/+internal/makedocs.m b/toolbox/+baseflow/+internal/makedocs.m
index 01962de..465ab72 100644
--- a/toolbox/+baseflow/+internal/makedocs.m
+++ b/toolbox/+baseflow/+internal/makedocs.m
@@ -91,12 +91,6 @@ function makedocs(varargin)
       % scripts to m-files, run convertlivescripts and review the diff.
    end
 
-   %% build a doc search database
-
-   if opts.docsearch == true
-      builddocsearchdb(htmlpath)
-   end
-
    %% publish the example documentation using publish
 
    if opts.docpages == true
@@ -175,6 +169,14 @@ function makedocs(varargin)
          'verbose', 'on' ...
          );
    end
+
+   %% build a doc search database
+
+   % Build the search database last, so it indexes the pages this call
+   % published rather than the pages of the previous build.
+   if opts.docsearch == true
+      builddocsearchdb(htmlpath)
+   end
 end
 
 function cleanupdemofigures(figsbefore, visibility)

From 5db871917cf94a661be070ce7bb7b2071a08d0de Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:22:59 -0700
Subject: [PATCH 14/28] docs: regenerate the doc pages, function pages, and
 search database

Output of baseflow.internal.makedocs('docpages', 'functions',
'docsearch'). The pages follow the current help text, including the
drainagedensity default of NaN. The demo pages are not rebuilt.
custom_toolbox.json keeps its earlier content, because the build writes
the absolute path of the build folder into it.
---
 docs/index.html                               |   6 +-
 toolbox/docs/html/baseflow_contents.html      |   2 +-
 .../docs/html/baseflow_examples_contents.html |   2 +-
 .../docs/html/baseflow_gettingStarted.html    |   6 +-
 .../docs/html/baseflow_powerlaw_notation.html |   2 +-
 .../docs/html/baseflow_theory_contents.html   |   2 +-
 toolbox/docs/html/baseflow_welcome.html       |   2 +-
 .../helpsearch-v4_en/store/000000000002.zap   | Bin 1228393 -> 1247418 bytes
 .../html/helpsearch-v4_en/store/root.bolt     | Bin 262144 -> 262144 bytes
 .../docs/html/m2html/+baseflow/Contents.html  |   1 +
 .../docs/html/m2html/+baseflow/Qnonlin.html   | 248 ++---
 .../html/m2html/+baseflow/aquiferstorage.html | 337 +++----
 .../html/m2html/+baseflow/baseflowtrend.html  | 157 +--
 .../docs/html/m2html/+baseflow/cloudphi.html  | 302 +++---
 .../html/m2html/+baseflow/conversions.html    | 174 ++--
 .../m2html/+baseflow/dndtuncertainty.html     | 600 ++++++------
 .../docs/html/m2html/+baseflow/expectedQ.html | 371 +++----
 .../docs/html/m2html/+baseflow/fdcurve.html   | 224 +++--
 toolbox/docs/html/m2html/+baseflow/fitab.html | 904 +++++++++---------
 .../html/m2html/+baseflow/fitphidist.html     | 351 +++----
 .../m2html/+baseflow/generateTestData.html    |  57 +-
 .../html/m2html/+baseflow/getfunction.html    |  73 +-
 .../docs/html/m2html/+baseflow/globalfit.html |  29 +-
 .../docs/html/m2html/+baseflow/gpfitb.html    | 471 ++++-----
 .../docs/html/m2html/+baseflow/plfitb.html    | 496 +++++-----
 .../docs/html/m2html/+baseflow/plplotb.html   | 382 ++++----
 .../m2html/+baseflow/pointcloudintercept.html | 332 ++++---
 .../docs/html/m2html/+baseflow/prepfits.html  |  78 +-
 .../html/m2html/+baseflow/printtrend.html     | 114 +--
 .../docs/html/m2html/+baseflow/setopts.html   | 244 ++---
 .../m2html/+baseflow/specialfunctions.html    | 204 ++--
 toolbox/docs/html/m2html/function_index.html  |   2 +-
 32 files changed, 3157 insertions(+), 3016 deletions(-)

diff --git a/docs/index.html b/docs/index.html
index c994284..4073c4d 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -9,7 +9,7 @@
 <title>Getting Started with the Baseflow Toolbox</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_gettingStarted.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
@@ -210,7 +210,7 @@ <h2 id="23">API Specification</h2>
    fitopts        : (struct) baseflow.fitab options for every event fit: weights, order, quantile, refqtls, Nboot, alpha (numeric); mask, plotfit (logical). Fields override the same-named fitab options; weights and mask must be scalars. Default = struct().</pre>
 <p>API specification for <tt><b>globalfit</b></tt>:</p>
 <pre>     drainagearea      : (numeric scalar) Drainage area upstream of streamflow gauge [m2]. Default = NaN.
-     drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = 0.8.
+     drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = NaN.
      aquiferdepth      : (numeric scalar) Reference aquifer thickness [m]. Default = NaN.
      streamlength      : (numeric scalar) Effective channel length [m]. Default = NaN.
      aquiferslope      : (numeric scalar) Effective aquifer slope [-]. Default = 0.0.
@@ -509,7 +509,7 @@ <h2 id="46">Acknowledgements</h2>
 %%
 % 
 %       drainagearea      : (numeric scalar) Drainage area upstream of streamflow gauge [m2]. Default = NaN.
-%       drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = 0.8.
+%       drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = NaN.
 %       aquiferdepth      : (numeric scalar) Reference aquifer thickness [m]. Default = NaN.
 %       streamlength      : (numeric scalar) Effective channel length [m]. Default = NaN.
 %       aquiferslope      : (numeric scalar) Effective aquifer slope [-]. Default = 0.0.
diff --git a/toolbox/docs/html/baseflow_contents.html b/toolbox/docs/html/baseflow_contents.html
index 7b1c0ac..b2fc024 100644
--- a/toolbox/docs/html/baseflow_contents.html
+++ b/toolbox/docs/html/baseflow_contents.html
@@ -9,7 +9,7 @@
 <title>Baseflow Toolbox Contents</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_contents.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_examples_contents.html b/toolbox/docs/html/baseflow_examples_contents.html
index 8658315..293f85e 100644
--- a/toolbox/docs/html/baseflow_examples_contents.html
+++ b/toolbox/docs/html/baseflow_examples_contents.html
@@ -9,7 +9,7 @@
 <title>Baseflow Recession Analysis Toolbox Examples</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_examples_contents.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_gettingStarted.html b/toolbox/docs/html/baseflow_gettingStarted.html
index c994284..4073c4d 100644
--- a/toolbox/docs/html/baseflow_gettingStarted.html
+++ b/toolbox/docs/html/baseflow_gettingStarted.html
@@ -9,7 +9,7 @@
 <title>Getting Started with the Baseflow Toolbox</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_gettingStarted.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
@@ -210,7 +210,7 @@ <h2 id="23">API Specification</h2>
    fitopts        : (struct) baseflow.fitab options for every event fit: weights, order, quantile, refqtls, Nboot, alpha (numeric); mask, plotfit (logical). Fields override the same-named fitab options; weights and mask must be scalars. Default = struct().</pre>
 <p>API specification for <tt><b>globalfit</b></tt>:</p>
 <pre>     drainagearea      : (numeric scalar) Drainage area upstream of streamflow gauge [m2]. Default = NaN.
-     drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = 0.8.
+     drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = NaN.
      aquiferdepth      : (numeric scalar) Reference aquifer thickness [m]. Default = NaN.
      streamlength      : (numeric scalar) Effective channel length [m]. Default = NaN.
      aquiferslope      : (numeric scalar) Effective aquifer slope [-]. Default = 0.0.
@@ -509,7 +509,7 @@ <h2 id="46">Acknowledgements</h2>
 %%
 % 
 %       drainagearea      : (numeric scalar) Drainage area upstream of streamflow gauge [m2]. Default = NaN.
-%       drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = 0.8.
+%       drainagedensity   : (numeric scalar) Drainage density = streamlength/drainagearea [km-1]. Default = NaN.
 %       aquiferdepth      : (numeric scalar) Reference aquifer thickness [m]. Default = NaN.
 %       streamlength      : (numeric scalar) Effective channel length [m]. Default = NaN.
 %       aquiferslope      : (numeric scalar) Effective aquifer slope [-]. Default = 0.0.
diff --git a/toolbox/docs/html/baseflow_powerlaw_notation.html b/toolbox/docs/html/baseflow_powerlaw_notation.html
index b2fb6dc..64374e2 100644
--- a/toolbox/docs/html/baseflow_powerlaw_notation.html
+++ b/toolbox/docs/html/baseflow_powerlaw_notation.html
@@ -9,7 +9,7 @@
 <title>Power-law notation across plfit, r_plfit, gpd, and baseflow</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_powerlaw_notation.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_theory_contents.html b/toolbox/docs/html/baseflow_theory_contents.html
index 0e7c8fc..8e95373 100644
--- a/toolbox/docs/html/baseflow_theory_contents.html
+++ b/toolbox/docs/html/baseflow_theory_contents.html
@@ -9,7 +9,7 @@
 <title>Theoretical Basis Tutorials</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_theory_contents.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/baseflow_welcome.html b/toolbox/docs/html/baseflow_welcome.html
index 1b432c9..c47a43b 100644
--- a/toolbox/docs/html/baseflow_welcome.html
+++ b/toolbox/docs/html/baseflow_welcome.html
@@ -9,7 +9,7 @@
 <title>Welcome to the Baseflow Recession Analysis Toolbox</title>
 <meta name="generator" content="MATLAB 25.2">
 <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/">
-<meta name="DC.date" content="2026-09-18">
+<meta name="DC.date" content="2026-10-13">
 <meta name="DC.source" content="baseflow_welcome.m">
 <style type="text/css">
 html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
diff --git a/toolbox/docs/html/helpsearch-v4_en/store/000000000002.zap b/toolbox/docs/html/helpsearch-v4_en/store/000000000002.zap
index 80006b289a1ab4713ed17c630d1b691907b53deb..3343be4fc9f42f3f2eb36f992045542477acce62 100755
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diff --git a/toolbox/docs/html/helpsearch-v4_en/store/root.bolt b/toolbox/docs/html/helpsearch-v4_en/store/root.bolt
index 3849a1552c32cf3c18326a64dc52d0e2d1a448d0..9a96719d6a33a2562d380a14ee022b86e336343c 100755
GIT binary patch
delta 102
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j7T8Zr;M>-~#N{9c(ZUAR$PT5qDl*@<Z~y<FiID*SKb08n

delta 130
zcmZo@5NK!+*kIux!N&jrtWf%5K!SxpP5QNsf$Qy?|JQH-U(d*WU^-U=li1cIrg`=g
o6P&g+FmXAUvxC($L3J@hX%;9AGmQhv=Yi6^AY&&c2(&N*0BA55u>b%7

diff --git a/toolbox/docs/html/m2html/+baseflow/Contents.html b/toolbox/docs/html/m2html/+baseflow/Contents.html
index 327fd44..8ce024b 100644
--- a/toolbox/docs/html/m2html/+baseflow/Contents.html
+++ b/toolbox/docs/html/m2html/+baseflow/Contents.html
@@ -161,6 +161,7 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
    baseflow/private.dealout                     - Deal out function outputs
    baseflow/private.drawarrow                   - Draw an arrow in an axes, with the head on a given point
    baseflow/private.emptyaxes                   - Return empty axes object
+   baseflow/private.expectedtau                 - Mean tau of a Pareto tail with recession exponent b
    baseflow/private.figurevisibility            - Visibility of a figure a caller asked to show
    baseflow/private.fillnans                    - Fill interior sequences of nan values of length &lt;= fmax
    baseflow/private.findevents                  - Returns flow Q and time T values of each individual recession event,
diff --git a/toolbox/docs/html/m2html/+baseflow/Qnonlin.html b/toolbox/docs/html/m2html/+baseflow/Qnonlin.html
index 14a369d..14f8842 100644
--- a/toolbox/docs/html/m2html/+baseflow/Qnonlin.html
+++ b/toolbox/docs/html/m2html/+baseflow/Qnonlin.html
@@ -32,6 +32,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
  [Q,dQdt,t,hFig] = Qnonlin(a,b,Q0,t) plots a theoretical discharge predicted
  by a/b values for Q = (Q0^(1-b)+a*(b-1).*t).^(1/(1-b));
 
+ b = 1 gives the exponential limit Q = Q0*exp(-a*t). For b &lt; 1 the
+ reservoir empties in finite time, after which Q is 0.
+
  Matt Cooper, 04-Nov-2022, https://github.com/mgcooper
 
  See also: <a href="getfunction.html" class="code" title="function Fnc = getfunction(funcname)">getfunction</a>, <a href="QtauString.html" class="code" title="function Qtaustr = QtauString(varargin)">QtauString</a>, <a href="QtString.html" class="code" title="function Qtstr = QtString(varargin)">QtString</a></pre></div>
@@ -51,7 +54,10 @@ <h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^
 <!-- crossreference -->
 
 
+<h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../html_img/up.png"></a></h2>
+<ul style="list-style-image:url(../html_img/matlabicon.gif)">
 
+<li><a href="#_sub1" class="code">function [Q,dQdt] = qsolution(a,b,Q0,t)</a></li></ul>
 
 
 
@@ -62,123 +68,145 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0004    <span class="comment">% [Q,dQdt,t,hFig] = Qnonlin(a,b,Q0,t) plots a theoretical discharge predicted</span>
 0005    <span class="comment">% by a/b values for Q = (Q0^(1-b)+a*(b-1).*t).^(1/(1-b));</span>
 0006    <span class="comment">%</span>
-0007    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0008    <span class="comment">%</span>
-0009    <span class="comment">% See also: getfunction, QtauString, QtString</span>
-0010 
-0011    <span class="comment">% if called with no input, open this file</span>
-0012    <span class="keyword">if</span> nargin == 0; edit(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0007    <span class="comment">% b = 1 gives the exponential limit Q = Q0*exp(-a*t). For b &lt; 1 the</span>
+0008    <span class="comment">% reservoir empties in finite time, after which Q is 0.</span>
+0009    <span class="comment">%</span>
+0010    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0011    <span class="comment">%</span>
+0012    <span class="comment">% See also: getfunction, QtauString, QtString</span>
 0013 
-0014    plotFig = false;
-0015    hFig = [];
-0016    <span class="keyword">if</span> nargin==5
-0017       plotFig = varargin{1};
-0018    <span class="keyword">end</span>
-0019 
-0020    <span class="comment">% This lets a scalar t or a vector t to be passed in. In both cases t is</span>
-0021    <span class="comment">% time elapsed since t=0, so to recover Q0 and dqdt0 we set t(1) = 0</span>
-0022    <span class="keyword">if</span> numel(t) ~= 1 &amp;&amp; t(1) ~= 0
-0023       t = [0;t(:)];
-0024    <span class="keyword">end</span>
-0025 
-0026    numA = numel(a);
-0027    numB = numel(b);
-0028    numQ = numel(Q0);
-0029    numT = numel(t);
-0030 
-0031    Q = nan(numA,numB,numQ,numT);
-0032    dQdt = nan(numA,numB,numQ,numT);
+0014    <span class="comment">% if called with no input, open this file</span>
+0015    <span class="keyword">if</span> nargin == 0; edit(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0016 
+0017    plotFig = false;
+0018    hFig = [];
+0019    <span class="keyword">if</span> nargin==5
+0020       plotFig = varargin{1};
+0021    <span class="keyword">end</span>
+0022 
+0023    <span class="comment">% This lets a scalar t or a vector t to be passed in. In both cases t is</span>
+0024    <span class="comment">% time elapsed since t=0, so to recover Q0 and dqdt0 we set t(1) = 0</span>
+0025    <span class="keyword">if</span> numel(t) ~= 1 &amp;&amp; t(1) ~= 0
+0026       t = [0;t(:)];
+0027    <span class="keyword">end</span>
+0028 
+0029    numA = numel(a);
+0030    numB = numel(b);
+0031    numQ = numel(Q0);
+0032    numT = numel(t);
 0033 
-0034    f = @(a,b,Q0,t) (Q0^(1-b)+a*(b-1).*t).^(1/(1-b));
-0035 
-0036    <span class="comment">% this loop is the easiest way to allow any size a,b,Q0.</span>
-0037    <span class="comment">% if I wanted to restrict two of the three a,b,Q0 to be scalar and let</span>
-0038    <span class="comment">% a third be a vector, I could check that the vector valued quantity</span>
-0039    <span class="comment">% and t have the right orientation for matrix multiplication</span>
-0040    <span class="keyword">for</span> n = 1:numA
-0041       <span class="keyword">for</span> m = 1:numB
-0042          <span class="keyword">for</span> p = 1:numQ
-0043 
-0044             qtmp = f(a(n),b(m),Q0(p),t);
-0045             Q(n,m,p,:) = qtmp;
-0046             dQdt(n,m,p,:) = -a(n).*qtmp.^b(m);
-0047 
-0048          <span class="keyword">end</span>
-0049       <span class="keyword">end</span>
-0050    <span class="keyword">end</span>
-0051 
-0052    Q = squeeze(Q);
-0053    dQdt = squeeze(dQdt);
-0054    
-0055    interpreter = <span class="string">'latex'</span>;
-0056    xstr{2} = <span class="string">'$t/t_c \quad [-]$'</span>;
-0057    xstr{1} = <span class="string">'$t \quad [T]$'</span>;
-0058    ystr{2} = <span class="string">'$Q/Q_0 \quad [-]$'</span>;
-0059    ystr{1} = <span class="string">'$Q(t) \quad [L/T]$'</span>;
-0060       
-0061    <span class="keyword">if</span> isoctave
-0062       interpreter = <span class="string">'tex'</span>;
-0063       xstr = latex2tex(xstr);
-0064       ystr = latex2tex(ystr);
-0065    <span class="keyword">end</span>
-0066    
-0067    <span class="comment">% get formatted strings for the legend</span>
-0068    Qtstr = baseflow.getstring(<span class="string">'Q(t)'</span>, <span class="string">'interpreter'</span>, interpreter);
-0069    <span class="comment">% showAB = false;</span>
-0070    <span class="comment">% Qtstr = baseflow.QtString([a,b],Q0,showAB);</span>
-0071    <span class="comment">% tcstr = baseflow.tcString(a,b,Q0,showAB);</span>
-0072 
-0073    <span class="comment">% If Q(t) is an ensemble, this only plots the first one.</span>
-0074    <span class="keyword">if</span> plotFig
+0034    Q = nan(numA,numB,numQ,numT);
+0035    dQdt = nan(numA,numB,numQ,numT);
+0036 
+0037    f = @<a href="#_sub1" class="code" title="subfunction [Q,dQdt] = qsolution(a,b,Q0,t)">qsolution</a>;
+0038 
+0039    <span class="comment">% this loop is the easiest way to allow any size a,b,Q0.</span>
+0040    <span class="comment">% if I wanted to restrict two of the three a,b,Q0 to be scalar and let</span>
+0041    <span class="comment">% a third be a vector, I could check that the vector valued quantity</span>
+0042    <span class="comment">% and t have the right orientation for matrix multiplication</span>
+0043    <span class="keyword">for</span> n = 1:numA
+0044       <span class="keyword">for</span> m = 1:numB
+0045          <span class="keyword">for</span> p = 1:numQ
+0046 
+0047             [qtmp, dqtmp] = f(a(n),b(m),Q0(p),t);
+0048             Q(n,m,p,:) = qtmp;
+0049             dQdt(n,m,p,:) = dqtmp;
+0050 
+0051          <span class="keyword">end</span>
+0052       <span class="keyword">end</span>
+0053    <span class="keyword">end</span>
+0054 
+0055    Q = squeeze(Q);
+0056    dQdt = squeeze(dQdt);
+0057    
+0058    interpreter = <span class="string">'latex'</span>;
+0059    xstr{2} = <span class="string">'$t/t_c \quad [-]$'</span>;
+0060    xstr{1} = <span class="string">'$t \quad [T]$'</span>;
+0061    ystr{2} = <span class="string">'$Q/Q_0 \quad [-]$'</span>;
+0062    ystr{1} = <span class="string">'$Q(t) \quad [L/T]$'</span>;
+0063       
+0064    <span class="keyword">if</span> isoctave
+0065       interpreter = <span class="string">'tex'</span>;
+0066       xstr = latex2tex(xstr);
+0067       ystr = latex2tex(ystr);
+0068    <span class="keyword">end</span>
+0069    
+0070    <span class="comment">% get formatted strings for the legend</span>
+0071    Qtstr = baseflow.getstring(<span class="string">'Q(t)'</span>, <span class="string">'interpreter'</span>, interpreter);
+0072    <span class="comment">% showAB = false;</span>
+0073    <span class="comment">% Qtstr = baseflow.QtString([a,b],Q0,showAB);</span>
+0074    <span class="comment">% tcstr = baseflow.tcString(a,b,Q0,showAB);</span>
 0075 
-0076       <span class="comment">% get the characterisitc timescale</span>
-0077       tc = baseflow.characteristicTime(a(1), b(1), Q0(1));
+0076    <span class="comment">% If Q(t) is an ensemble, this only plots the first one.</span>
+0077    <span class="keyword">if</span> plotFig
 0078 
-0079       <span class="comment">% make a figure</span>
-0080       subplot(2, 1, 1);
+0079       <span class="comment">% get the characterisitc timescale</span>
+0080       tc = baseflow.characteristicTime(a(1), b(1), Q0(1));
 0081 
-0082       plot(t,Q);
-0083       xlabel(xstr{1}, <span class="string">'Interpreter'</span>, interpreter);
-0084       ylabel(ystr{1}, <span class="string">'Interpreter'</span>, interpreter);
-0085       legend(Qtstr, <span class="string">'Interpreter'</span>, interpreter);
-0086       axis tight
-0087 
-0088       subplot(2, 1, 2);
-0089       plot(t./tc, Q./Q0);
-0090       xlabel(xstr{2}, <span class="string">'Interpreter'</span>, interpreter);
-0091       ylabel(ystr{2}, <span class="string">'Interpreter'</span>, interpreter);
-0092       <span class="comment">% legend(tcstr, 'Interpreter', interpreter);</span>
-0093 
-0094       axis tight
-0095       ylim([0 1])
-0096    <span class="keyword">end</span>
-0097 
-0098    <span class="comment">% % NOTE: with the tc value, we can compute the Q(t) like this:</span>
-0099    <span class="comment">% Qfunc = @(tc,b,Q0) (Q0.*(1+(exp(b-1)-1).*t./tc).^(1/(1-b)));</span>
+0082       <span class="comment">% make a figure</span>
+0083       subplot(2, 1, 1);
+0084 
+0085       plot(t,Q);
+0086       xlabel(xstr{1}, <span class="string">'Interpreter'</span>, interpreter);
+0087       ylabel(ystr{1}, <span class="string">'Interpreter'</span>, interpreter);
+0088       legend(Qtstr, <span class="string">'Interpreter'</span>, interpreter);
+0089       axis tight
+0090 
+0091       subplot(2, 1, 2);
+0092       plot(t./tc, Q./Q0);
+0093       xlabel(xstr{2}, <span class="string">'Interpreter'</span>, interpreter);
+0094       ylabel(ystr{2}, <span class="string">'Interpreter'</span>, interpreter);
+0095       <span class="comment">% legend(tcstr, 'Interpreter', interpreter);</span>
+0096 
+0097       axis tight
+0098       ylim([0 1])
+0099    <span class="keyword">end</span>
 0100 
-0101    <span class="comment">% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %</span>
-0102    <span class="comment">% % notes from trying to figure out how to handle Q0:</span>
+0101    <span class="comment">% % NOTE: with the tc value, we can compute the Q(t) like this:</span>
+0102    <span class="comment">% Qfunc = @(tc,b,Q0) (Q0.*(1+(exp(b-1)-1).*t./tc).^(1/(1-b)));</span>
 0103 
-0104    <span class="comment">% % not sure what is best. If I do t-t(1),</span>
-0105 
-0106    <span class="comment">% % this assumes that t(1) = t0, so Q(t) = Q(t-t0)</span>
-0107    <span class="comment">%     t = t-t(1);</span>
+0104    <span class="comment">% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %</span>
+0105    <span class="comment">% % notes from trying to figure out how to handle Q0:</span>
+0106 
+0107    <span class="comment">% % not sure what is best. If I do t-t(1),</span>
 0108 
-0109    <span class="comment">% % this appends a zero ahead of t(1) if t doesn't already start at zero</span>
-0110    <span class="comment">%     if t(1) ~= 0</span>
-0111    <span class="comment">%         t   = [0;t(:)];</span>
-0112    <span class="comment">%     end</span>
-0113 
-0114 
-0115    <span class="comment">%     % append Q0 and t0 to the output</span>
-0116    <span class="comment">%     dqdt0   =</span>
-0117    <span class="comment">%     q       = cat(3,q,Q0);</span>
-0118    <span class="comment">%     t       = cat(1,0,t);</span>
-0119 
-0120 
-0121    <span class="comment">%     flin    = @(a,Q0,t) Q0.*exp(-t.*a);</span>
-0122    <span class="comment">%     out.Qlin    = fnlin(a,Q0,t);</span>
-0123    <span class="comment">%     out.dQlin   = a.*Qnlin;</span>
-0124</pre></div>
+0109    <span class="comment">% % this assumes that t(1) = t0, so Q(t) = Q(t-t0)</span>
+0110    <span class="comment">%     t = t-t(1);</span>
+0111 
+0112    <span class="comment">% % this appends a zero ahead of t(1) if t doesn't already start at zero</span>
+0113    <span class="comment">%     if t(1) ~= 0</span>
+0114    <span class="comment">%         t   = [0;t(:)];</span>
+0115    <span class="comment">%     end</span>
+0116 
+0117 
+0118    <span class="comment">%     % append Q0 and t0 to the output</span>
+0119    <span class="comment">%     dqdt0   =</span>
+0120    <span class="comment">%     q       = cat(3,q,Q0);</span>
+0121    <span class="comment">%     t       = cat(1,0,t);</span>
+0122 
+0123 
+0124    <span class="comment">%     flin    = @(a,Q0,t) Q0.*exp(-t.*a);</span>
+0125    <span class="comment">%     out.Qlin    = fnlin(a,Q0,t);</span>
+0126    <span class="comment">%     out.dQlin   = a.*Qnlin;</span>
+0127 <span class="keyword">end</span>
+0128 
+0129 <span class="comment">%% LOCAL FUNCTIONS</span>
+0130 <a name="_sub1" href="#_subfunctions" class="code">function [Q,dQdt] = qsolution(a,b,Q0,t)</a>
+0131    <span class="comment">%QSOLUTION Flow of -dQ/dt = aQ^b at times t, from Q(0) = Q0, and its rate.</span>
+0132 
+0133    <span class="comment">% the power law has its exponential limit at b = 1, where 1/(1-b) is Inf.</span>
+0134    <span class="comment">% For b &lt; 1 the base reaches zero when the reservoir empties, and a</span>
+0135    <span class="comment">% negative base would give a rebound or a complex flow.</span>
+0136    <span class="keyword">if</span> b == 1
+0137       Q = Q0.*exp(-a.*t);
+0138    <span class="keyword">else</span>
+0139       Q = max(Q0^(1-b)+a*(b-1).*t, 0).^(1/(1-b));
+0140    <span class="keyword">end</span>
+0141 
+0142    <span class="comment">% an empty reservoir loses no more flow, but a*Q^b is not 0 at Q = 0</span>
+0143    <span class="comment">% for b &lt;= 0</span>
+0144    dQdt = -a.*Q.^b;
+0145    dQdt(Q == 0) = 0;
+0146 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/aquiferstorage.html b/toolbox/docs/html/m2html/+baseflow/aquiferstorage.html
index 22d7d56..520dce5 100644
--- a/toolbox/docs/html/m2html/+baseflow/aquiferstorage.html
+++ b/toolbox/docs/html/m2html/+baseflow/aquiferstorage.html
@@ -93,198 +93,159 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0020    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
 0021 
 0022    <span class="comment">% input checks</span>
-0023    b = round(b,2);
-0024    a = a(:);
-0025    b = b(:);
-0026    qmin = qmin(:);
-0027    qmax = qmax(:);
-0028 
-0029    <span class="comment">% make a and b the same size</span>
-0030    <span class="keyword">if</span> numel(a) ~= numel(b) &amp;&amp; numel(a) == 1
-0031       a = a.*ones(size(b));
-0032    <span class="keyword">elseif</span> numel(a) ~= numel(b) &amp;&amp; numel(b) == 1
-0033       b = b.*ones(size(a));
-0034    <span class="keyword">end</span>
-0035 
-0036    <span class="comment">% make qmin/qmax the same size as a/b</span>
-0037    <span class="keyword">if</span> numel(qmin) ~= numel(qmax)
-0038       error(<span class="string">'qmin and qmax must be the same size'</span>);
-0039    <span class="keyword">elseif</span> numel(qmin) == numel(qmax) &amp;&amp; numel(qmin) == 1
-0040       qmin = qmin.*ones(size(a));
-0041       qmax = qmax.*ones(size(a));
-0042    <span class="keyword">elseif</span> numel(qmin) == numel(qmax) &amp;&amp; numel(a) == 1
-0043       a = a.*ones(size(qmin));
-0044       b = b.*ones(size(qmin));
-0045    <span class="keyword">elseif</span> numel(qmin) == numel(qmax) &amp;&amp; numel(qmin) ~= numel(a)
-0046       error(<span class="string">'qmin and qmax are not the same size as a and b'</span>);
-0047    <span class="keyword">end</span>
-0048 
-0049    <span class="comment">% v3 merges KtimeS</span>
-0050    kflag = false;
-0051    Ktime = nan(size(b));
-0052    <span class="keyword">if</span> nargin &gt; 4
-0053       kflag = true;
-0054       Ktime = varargin{1};
+0023    a = a(:);
+0024    b = b(:);
+0025    qmin = qmin(:);
+0026    qmax = qmax(:);
+0027 
+0028    <span class="comment">% make a and b the same size</span>
+0029    <span class="keyword">if</span> numel(a) ~= numel(b) &amp;&amp; isscalar(a)
+0030       a = a.*ones(size(b));
+0031    <span class="keyword">elseif</span> numel(a) ~= numel(b) &amp;&amp; isscalar(b)
+0032       b = b.*ones(size(a));
+0033    <span class="keyword">end</span>
+0034 
+0035    <span class="comment">% make qmin/qmax the same size as a/b</span>
+0036    <span class="keyword">if</span> numel(qmin) ~= numel(qmax)
+0037       error(<span class="string">'qmin and qmax must be the same size'</span>);
+0038    <span class="keyword">elseif</span> numel(qmin) == numel(qmax) &amp;&amp; isscalar(qmin)
+0039       qmin = qmin.*ones(size(a));
+0040       qmax = qmax.*ones(size(a));
+0041    <span class="keyword">elseif</span> numel(qmin) == numel(qmax) &amp;&amp; isscalar(a)
+0042       a = a.*ones(size(qmin));
+0043       b = b.*ones(size(qmin));
+0044    <span class="keyword">elseif</span> numel(qmin) == numel(qmax) &amp;&amp; numel(qmin) ~= numel(a)
+0045       error(<span class="string">'qmin and qmax are not the same size as a and b'</span>);
+0046    <span class="keyword">end</span>
+0047 
+0048    <span class="comment">% v3 merges KtimeS</span>
+0049    Ktime = nan(size(b));
+0050    <span class="keyword">if</span> nargin &gt; 4
+0051       Ktime = varargin{1};
+0052    <span class="keyword">end</span>
+0053    <span class="keyword">if</span> isscalar(Ktime) &amp;&amp; numel(Ktime) ~= numel(b)
+0054       Ktime = Ktime.*ones(size(b));
 0055    <span class="keyword">end</span>
-0056    <span class="keyword">if</span> numel(Ktime) == 1 &amp;&amp; numel(Ktime) ~= numel(b)
-0057       Ktime = Ktime.*ones(size(b));
-0058    <span class="keyword">end</span>
-0059 
-0060    <span class="keyword">if</span> numel(a) == numel(b) &amp;&amp; numel(a) == 1
-0061 
-0062       <span class="keyword">if</span> b &gt;= 0.95 &amp;&amp; b &lt;= 1.05           <span class="comment">% linear reservoir</span>
-0063 
-0064          <span class="keyword">if</span> kflag == true
-0065             Smin = Ktime*qmin;
-0066             Smax = Ktime*qmax;
-0067          <span class="keyword">else</span>
-0068             Smin = 1/a.*qmin;
-0069             Smax = 1/a.*qmax;
-0070          <span class="keyword">end</span>
-0071 
-0072       <span class="keyword">elseif</span> b &gt;= 1.95 &amp;&amp; b &lt;= 2.05       <span class="comment">% exponential</span>
-0073 
-0074          <span class="keyword">if</span> kflag == true
-0075             Smin = 1/a.*log(a.*Ktime.*qmin.^2);
-0076             Smax = 1/a.*log(a.*Ktime.*qmax.^2);
-0077          <span class="keyword">else</span>
-0078             Smin = 1/a.*log(qmin);
-0079             Smax = 1/a.*log(qmax);
-0080          <span class="keyword">end</span>
-0081 
-0082       <span class="keyword">elseif</span> b&gt;2.05                   <span class="comment">% super exponential</span>
-0083          <span class="keyword">if</span> kflag == true
-0084             Smin = -Ktime/(2-b).*qmin;
-0085             Smax = -Ktime/(2-b).*qmax;
-0086          <span class="keyword">else</span>
-0087             Smin = -1/a/(2-b).*(qmax.^(2-b));
-0088             Smax = -1/a/(2-b).*(qmin.^(2-b));
-0089             <span class="comment">%dS = -1/a/(2-b).*(qmax.^(2-b)-qmin.^(2-b));</span>
-0090          <span class="keyword">end</span>
-0091       <span class="keyword">else</span>                            <span class="comment">% sub exponential</span>
-0092          <span class="keyword">if</span> kflag == true
-0093             Smin = -Ktime/(2-b).*qmin;
-0094             Smax = -Ktime/(2-b).*qmax;
-0095          <span class="keyword">else</span>
-0096             Smin = 1/a/(2-b).*(qmin.^(2-b));
-0097             Smax = 1/a/(2-b).*(qmax.^(2-b));
-0098             <span class="comment">%dS = 1/a/(2-b).*(qmin.^(2-b)-qmax.^(2-b));</span>
-0099          <span class="keyword">end</span>
-0100       <span class="keyword">end</span>
-0101 
-0102       dS = Smax-Smin;
-0103 
-0104    <span class="keyword">elseif</span> numel(a) == numel(b) &amp;&amp; (numel(a) == numel(qmin) || numel(qmin) == 1)
-0105 
-0106       <span class="comment">% first determine b = 1, b = 2, and otherwise</span>
-0107       Smin = nan(size(a));
-0108       Smax = nan(size(a));
+0056 
+0057    <span class="comment">% one path for scalar and array input, since the checks above give a, b,</span>
+0058    <span class="comment">% qmin, and qmax the same size</span>
+0059    <span class="keyword">if</span> numel(a) == numel(b) &amp;&amp; (numel(a) == numel(qmin) || isscalar(qmin))
+0060 
+0061       <span class="comment">% first determine b = 1, b = 2, and otherwise</span>
+0062       Smin = nan(size(a));
+0063       Smax = nan(size(a));
+0064 
+0065       <span class="comment">% find indices where b = 1, b = 2, and b! = 2. Round b to two</span>
+0066       <span class="comment">% decimals only to choose the formula; the power-law formulas use</span>
+0067       <span class="comment">% the unrounded b. Octave's round takes no digit count, so round</span>
+0068       <span class="comment">% 100*b and divide by 100.</span>
+0069       bround = round(100*b)/100;
+0070       ib1 = bround &gt;= 0.95 &amp; bround &lt;= 1.05;
+0071       ib2 = bround &gt;= 1.95 &amp; bround &lt;= 2.05;
+0072       ib2p = bround&gt;2.05;
+0073       ib2m = true(size(b)); ib2m(ib1|ib2|ib2p) = false;
+0074       b(ib1) = 1.0;
+0075       b(ib2) = 2.0;
+0076 
+0077       <span class="comment">% for reference: sum([ib1,ib2,ib2p,ib2m])</span>
+0078       <span class="comment">% now b is ready to be used in each expression</span>
+0079 
+0080       <span class="comment">% dynamic a/b, mean qmin/qmax</span>
+0081       <span class="keyword">if</span> isscalar(qmin)
+0082          qmin_b1 = qmin;
+0083          qmin_b2 = qmin;
+0084          qmin_b2p = qmin;
+0085          qmin_b2m = qmin;
+0086 
+0087          qmax_b1 = qmax;
+0088          qmax_b2 = qmax;
+0089          qmax_b2p = qmax;
+0090          qmax_b2m = qmax;
+0091 
+0092          <span class="comment">% dynamic a/b and dynamic qmin/qmax</span>
+0093       <span class="keyword">elseif</span> numel(a) == numel(qmin)
+0094          qmin_b1 = qmin(ib1);
+0095          qmin_b2 = qmin(ib2);
+0096          qmin_b2p = qmin(ib2p);
+0097          qmin_b2m = qmin(ib2m);
+0098 
+0099          qmax_b1 = qmax(ib1);
+0100          qmax_b2 = qmax(ib2);
+0101          qmax_b2p = qmax(ib2p);
+0102          qmax_b2m = qmax(ib2m);
+0103       <span class="keyword">end</span>
+0104 
+0105       <span class="comment">% linear reservoir</span>
+0106       [S1,S2] = <a href="#_sub1" class="code" title="subfunction [Smin,Smax] = dynamicS_b1(a,b,qmin,qmax,ktime)">dynamicS_b1</a>(a(ib1),b(ib1),qmin_b1,qmax_b1,Ktime(ib1));
+0107       Smin(ib1) = S1;
+0108       Smax(ib1) = S2;
 0109 
-0110       <span class="comment">% find indices where b = 1, b = 2, and b! = 2</span>
-0111       ib1 = b &gt;= 0.95 &amp; b &lt;= 1.05;
-0112       ib2 = b &gt;= 1.95 &amp; b &lt;= 2.05;
-0113       ib2p = b&gt;2.05;
-0114       ib2m = true(size(b)); ib2m(ib1|ib2|ib2p) = false;
-0115       b(ib1) = 1.0;
-0116       b(ib2) = 2.0;
-0117 
-0118       <span class="comment">% for reference: sum([ib1,ib2,ib2p,ib2m])</span>
-0119       <span class="comment">% now b is ready to be used in each expression</span>
-0120 
-0121       <span class="comment">% dynamic a/b, mean qmin/qmax</span>
-0122       <span class="keyword">if</span> numel(qmin) == 1
-0123          qmin_b1 = qmin;
-0124          qmin_b2 = qmin;
-0125          qmin_b2p = qmin;
-0126          qmin_b2m = qmin;
-0127 
-0128          qmax_b1 = qmax;
-0129          qmax_b2 = qmax;
-0130          qmax_b2p = qmax;
-0131          qmax_b2m = qmax;
+0110       <span class="comment">% exponential reservoir</span>
+0111       [S1,S2] = <a href="#_sub2" class="code" title="subfunction [Smin,Smax] = dynamicS_b2(a,qmin,qmax,ktime)">dynamicS_b2</a>(a(ib2),qmin_b2,qmax_b2,Ktime(ib2));
+0112       Smin(ib2) = S1;
+0113       Smax(ib2) = S2;
+0114 
+0115       <span class="comment">% power law reservoir with infinite storage (S2 is the upper limit)</span>
+0116       [S1,S2] = <a href="#_sub4" class="code" title="subfunction [Smin,Smax] = dynamicS_b2p(a,b,qmin,qmax,ktime)">dynamicS_b2p</a>(a(ib2p),b(ib2p),qmin_b2p,qmax_b2p,Ktime(ib2p));
+0117       Smin(ib2p) = S1;
+0118       Smax(ib2p) = S2;
+0119 
+0120       <span class="comment">% power law reservoir with finite drainage</span>
+0121       [S1,S2] = <a href="#_sub3" class="code" title="subfunction [Smin,Smax] = dynamicS_b2m(a,b,qmin,qmax,ktime)">dynamicS_b2m</a>(a(ib2m),b(ib2m),qmin_b2m,qmax_b2m,Ktime(ib2m));
+0122       Smin(ib2m) = S1;
+0123       Smax(ib2m) = S2;
+0124 
+0125       dS = Smax-Smin;
+0126 
+0127    <span class="keyword">end</span>
+0128 
+0129 <span class="keyword">end</span>
+0130 
+0131 <span class="comment">%% subfunctions</span>
 0132 
-0133          <span class="comment">% dynamic a/b and dynamic qmin/qmax</span>
-0134       <span class="keyword">elseif</span> numel(a) == numel(qmin)
-0135          qmin_b1 = qmin(ib1);
-0136          qmin_b2 = qmin(ib2);
-0137          qmin_b2p = qmin(ib2p);
-0138          qmin_b2m = qmin(ib2m);
-0139 
-0140          qmax_b1 = qmax(ib1);
-0141          qmax_b2 = qmax(ib2);
-0142          qmax_b2p = qmax(ib2p);
-0143          qmax_b2m = qmax(ib2m);
-0144       <span class="keyword">end</span>
+0133 <a name="_sub1" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b1(a,b,qmin,qmax,ktime)</a>
+0134 
+0135    <span class="keyword">if</span> all(~isnan(ktime))
+0136       Smin = ktime.*qmin;
+0137       Smax = ktime.*qmax;
+0138    <span class="keyword">else</span>
+0139       Smin = 1./a.*qmin.^b;
+0140       Smax = 1./a.*qmax.^b;
+0141    <span class="keyword">end</span>
+0142 <span class="keyword">end</span>
+0143 
+0144 <a name="_sub2" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b2(a,qmin,qmax,ktime)</a>
 0145 
-0146       <span class="comment">% linear reservoir</span>
-0147       [S1,S2] = <a href="#_sub1" class="code" title="subfunction [Smin,Smax] = dynamicS_b1(a,b,qmin,qmax,ktime)">dynamicS_b1</a>(a(ib1),b(ib1),qmin_b1,qmax_b1,Ktime(ib1));
-0148       Smin(ib1) = S1;
-0149       Smax(ib1) = S2;
-0150 
-0151       <span class="comment">% exponential reservoir</span>
-0152       [S1,S2] = <a href="#_sub2" class="code" title="subfunction [Smin,Smax] = dynamicS_b2(a,qmin,qmax,ktime)">dynamicS_b2</a>(a(ib2),qmin_b2,qmax_b2,Ktime(ib2));
-0153       Smin(ib2) = S1;
-0154       Smax(ib2) = S2;
-0155 
-0156       <span class="comment">% power law reservoir with infinite storage (S2 is the upper limit)</span>
-0157       [S1,S2] = <a href="#_sub4" class="code" title="subfunction [Smin,Smax] = dynamicS_b2p(a,b,qmin,qmax,ktime)">dynamicS_b2p</a>(a(ib2p),b(ib2p),qmin_b2p,qmax_b2p,Ktime(ib2p));
-0158       Smin(ib2p) = S1;
-0159       Smax(ib2p) = S2;
-0160 
-0161       <span class="comment">% power law reservoir with finite drainage</span>
-0162       [S1,S2] = <a href="#_sub3" class="code" title="subfunction [Smin,Smax] = dynamicS_b2m(a,b,qmin,qmax,ktime)">dynamicS_b2m</a>(a(ib2m),b(ib2m),qmin_b2m,qmax_b2m,Ktime(ib2m));
-0163       Smin(ib2m) = S1;
-0164       Smax(ib2m) = S2;
+0146    <span class="keyword">if</span> all(~isnan(ktime))
+0147       Smin = 1./a.*log(a.*ktime.*qmin.^2);
+0148       Smax = 1./a.*log(a.*ktime.*qmax.^2);
+0149    <span class="keyword">else</span>
+0150       Smin = 1./a.*log(qmin);
+0151       Smax = 1./a.*log(qmax);
+0152    <span class="keyword">end</span>
+0153 <span class="keyword">end</span>
+0154 
+0155 <a name="_sub3" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b2m(a,b,qmin,qmax,ktime)</a>
+0156    <span class="keyword">if</span> all(~isnan(ktime))
+0157       Smin = ktime./(2-b).*qmin;
+0158       Smax = ktime./(2-b).*qmax;
+0159    <span class="keyword">else</span>
+0160       Smin = 1./a./(2-b).*(qmin.^(2-b));
+0161       Smax = 1./a./(2-b).*(qmax.^(2-b));
+0162       <span class="comment">%dS = 1/a/(2-b).*(qmin.^(2-b)-qmax.^(2-b));</span>
+0163    <span class="keyword">end</span>
+0164 <span class="keyword">end</span>
 0165 
-0166       dS = Smax-Smin;
-0167 
-0168    <span class="keyword">end</span>
-0169 
-0170 <span class="keyword">end</span>
-0171 
-0172 <span class="comment">%% subfunctions</span>
-0173 
-0174 <a name="_sub1" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b1(a,b,qmin,qmax,ktime)</a>
-0175 
-0176    <span class="keyword">if</span> all(~isnan(ktime))
-0177       Smin = ktime.*qmin;
-0178       Smax = ktime.*qmax;
-0179    <span class="keyword">else</span>
-0180       Smin = 1./a.*qmin.^b;
-0181       Smax = 1./a.*qmax.^b;
-0182    <span class="keyword">end</span>
-0183 <span class="keyword">end</span>
-0184 
-0185 <a name="_sub2" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b2(a,qmin,qmax,ktime)</a>
-0186 
-0187    <span class="keyword">if</span> all(~isnan(ktime))
-0188       Smin = 1./a.*log(a.*ktime.*qmin.^2);
-0189       Smax = 1./a.*log(a.*ktime.*qmax.^2);
-0190    <span class="keyword">else</span>
-0191       Smin = 1./a.*log(qmin);
-0192       Smax = 1./a.*log(qmax);
-0193    <span class="keyword">end</span>
-0194 <span class="keyword">end</span>
-0195 
-0196 <a name="_sub3" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b2m(a,b,qmin,qmax,ktime)</a>
-0197    <span class="keyword">if</span> all(~isnan(ktime))
-0198       Smin = ktime./(2-b).*qmin;
-0199       Smax = ktime./(2-b).*qmax;
-0200    <span class="keyword">else</span>
-0201       Smin = 1./a./(2-b).*(qmin.^(2-b));
-0202       Smax = 1./a./(2-b).*(qmax.^(2-b));
-0203    <span class="keyword">end</span>
-0204 <span class="keyword">end</span>
-0205 
-0206 <a name="_sub4" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b2p(a,b,qmin,qmax,ktime)</a>
-0207    <span class="keyword">if</span> all(~isnan(ktime))
-0208       Smin = -ktime./(2-b).*qmin;
-0209       Smax = -ktime./(2-b).*qmax;
-0210    <span class="keyword">else</span>
-0211       <span class="comment">%ktime = -1./a./(2-b).*qmax;</span>
-0212       Smin = -1./a./(2-b).*(qmax.^(2-b));
-0213       Smax = -1./a./(2-b).*(qmin.^(2-b));
-0214    <span class="keyword">end</span>
-0215 <span class="keyword">end</span></pre></div>
+0166 <a name="_sub4" href="#_subfunctions" class="code">function [Smin,Smax] = dynamicS_b2p(a,b,qmin,qmax,ktime)</a>
+0167    <span class="keyword">if</span> all(~isnan(ktime))
+0168       Smin = -ktime./(2-b).*qmin;
+0169       Smax = -ktime./(2-b).*qmax;
+0170    <span class="keyword">else</span>
+0171       <span class="comment">%ktime = -1./a./(2-b).*qmax;</span>
+0172       Smin = -1./a./(2-b).*(qmax.^(2-b));
+0173       Smax = -1./a./(2-b).*(qmin.^(2-b));
+0174       <span class="comment">%dS = -1/a/(2-b).*(qmax.^(2-b)-qmin.^(2-b));</span>
+0175    <span class="keyword">end</span>
+0176 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/baseflowtrend.html b/toolbox/docs/html/m2html/+baseflow/baseflowtrend.html
index 46b2617..c74d96e 100644
--- a/toolbox/docs/html/m2html/+baseflow/baseflowtrend.html
+++ b/toolbox/docs/html/m2html/+baseflow/baseflowtrend.html
@@ -47,6 +47,13 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      Q: discharge [m3/d], posted daily, numeric vector
      A: basin area [m2], numeric scalar
 
+ Optional name-value inputs
+
+     pctl: quantile of the baseflow regression, in (0,1). Default 0.25.
+     globalfit returns pQexp, the quantile of the expected flow. pQexp is
+     NaN when the mean tau diverges, and baseflowtrend rejects it rather
+     than fit the mean flow.
+
  Outputs
 
      Qb: baseflow expected value [cm/d], posted annually, numeric vector
@@ -116,78 +123,86 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0019    <span class="comment">%     Q: discharge [m3/d], posted daily, numeric vector</span>
 0020    <span class="comment">%     A: basin area [m2], numeric scalar</span>
 0021    <span class="comment">%</span>
-0022    <span class="comment">% Outputs</span>
+0022    <span class="comment">% Optional name-value inputs</span>
 0023    <span class="comment">%</span>
-0024    <span class="comment">%     Qb: baseflow expected value [cm/d], posted annually, numeric vector</span>
-0025    <span class="comment">%     dQbdt: baseflow expected value trend [cm/d], posted annually, numeric</span>
-0026    <span class="comment">%     vector (the trend evaluated at each year in the input t timeseries) Q:</span>
-0027    <span class="comment">%     discharge [cm/d], posted annually (input Q converted to units cm/d/y)</span>
-0028    <span class="comment">%     dQadt: discharge trend [cm/d], posted annually (the trend in discharge</span>
-0029    <span class="comment">%     evaluated at each year in the input t timeseries) hb: figure handle for</span>
-0030    <span class="comment">%     the baseflow trendplot figure ha: figure handle for the annual flow</span>
-0031    <span class="comment">%     trendplot figure</span>
-0032    <span class="comment">%</span>
-0033    <span class="comment">% Example</span>
-0034    <span class="comment">%</span>
-0035    <span class="comment">%  Compute annual baseflow and its trend from the example daily</span>
-0036    <span class="comment">%  streamflow record. The basin area converts flow to cm/d:</span>
-0037    <span class="comment">%</span>
-0038    <span class="comment">%     [T, Q] = baseflow.loadExampleData();</span>
-0039    <span class="comment">%     [Qb, dQbdt] = baseflow.baseflowtrend(T, Q, 8.6545e9);</span>
-0040    <span class="comment">%     fprintf('Mean annual baseflow = %.3f cm/d\n', mean(Qb))</span>
+0024    <span class="comment">%     pctl: quantile of the baseflow regression, in (0,1). Default 0.25.</span>
+0025    <span class="comment">%     globalfit returns pQexp, the quantile of the expected flow. pQexp is</span>
+0026    <span class="comment">%     NaN when the mean tau diverges, and baseflowtrend rejects it rather</span>
+0027    <span class="comment">%     than fit the mean flow.</span>
+0028    <span class="comment">%</span>
+0029    <span class="comment">% Outputs</span>
+0030    <span class="comment">%</span>
+0031    <span class="comment">%     Qb: baseflow expected value [cm/d], posted annually, numeric vector</span>
+0032    <span class="comment">%     dQbdt: baseflow expected value trend [cm/d], posted annually, numeric</span>
+0033    <span class="comment">%     vector (the trend evaluated at each year in the input t timeseries) Q:</span>
+0034    <span class="comment">%     discharge [cm/d], posted annually (input Q converted to units cm/d/y)</span>
+0035    <span class="comment">%     dQadt: discharge trend [cm/d], posted annually (the trend in discharge</span>
+0036    <span class="comment">%     evaluated at each year in the input t timeseries) hb: figure handle for</span>
+0037    <span class="comment">%     the baseflow trendplot figure ha: figure handle for the annual flow</span>
+0038    <span class="comment">%     trendplot figure</span>
+0039    <span class="comment">%</span>
+0040    <span class="comment">% Example</span>
 0041    <span class="comment">%</span>
-0042    <span class="comment">% See also: aquiferthickness</span>
-0043    <span class="comment">%</span>
-0044    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0045 
-0046    <span class="comment">% if called with no input, open this file</span>
-0047    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0048 
-0049    <span class="comment">% PARSE INPUTS</span>
-0050    [t, Q, A, method, pctl, showfig] = <a href="#_sub1" class="code" title="subfunction [t, Q, A, method, prctle, showfig] = parseinputs(t, Q, A, varargin)">parseinputs</a>(t, Q, A, varargin{:});
-0051 
-0052    <span class="comment">% MAIN FUNCTION</span>
-0053    t1 = datenum(year(t(1)), 1, 1, 0, 0, 0);
-0054    t2 = datenum(year(t(end)), 12, 31, 0, 0, 0);
-0055    [Q, t] = padtimeseries(Q, t, t1, t2, 1); <span class="comment">%#ok&lt;*DATNM&gt;</span>
-0056    [Q, t] = rmleapinds(Q, t);
-0057 
-0058    <span class="comment">% convert the flow from m3/d posted daily to cm/d posted annually</span>
-0059    <span class="comment">%if ~isdatetime(t); t = datetime(t,'ConvertFrom','datenum'); end</span>
-0060    t = transpose(year(mean(reshape(t, 365, numel(t) / 365))));
-0061    Qa = transpose(mean(reshape(Q, 365, numel(Q) / 365), <span class="string">'omitnan'</span>)) .* (100/A);
-0062 
-0063    <span class="comment">% regress Q [cm/d/y] against t [y] to get the trend [cm/d] posted annually</span>
-0064    ha = baseflow.trendplot(t, Qa, <span class="string">'anomalies'</span>, false, <span class="string">'units'</span>, <span class="string">'cm/d/y'</span>, <span class="keyword">...</span>
-0065       <span class="string">'titletext'</span>, <span class="string">'mean flow'</span>, <span class="string">'legendtext'</span>, <span class="string">'mean flow regression'</span>, <span class="keyword">...</span>
-0066       <span class="string">'showfig'</span>, showfig, <span class="string">'method'</span>, method);
-0067    hb = baseflow.trendplot(t, Qa, <span class="string">'anomalies'</span>, false, <span class="string">'units'</span>, <span class="string">'cm/d/y'</span>, <span class="keyword">...</span>
-0068       <span class="string">'quantile'</span>, pctl, <span class="string">'titletext'</span>, <span class="string">'baseflow'</span>, <span class="string">'legendtext'</span>, <span class="keyword">...</span>
-0069       <span class="string">'baseflow regression'</span>, <span class="string">'showfig'</span>, showfig, <span class="string">'alpha'</span>, 0.05);
-0070    dQadt = reshape(get(ha.trend, <span class="string">'YData'</span>), [], 1); <span class="comment">% mean flow trend</span>
-0071    dQbdt = reshape(get(hb.trend, <span class="string">'YData'</span>), [], 1); <span class="comment">% baseflow trend</span>
-0072    Qb = Qa-(dQadt-dQbdt); <span class="comment">% baseflow timeseries, cm/day</span>
-0073 <span class="keyword">end</span>
-0074 
-0075 <span class="comment">%% INPUT PARSER</span>
-0076 <a name="_sub1" href="#_subfunctions" class="code">function [t, Q, A, method, prctle, showfig] = parseinputs(t, Q, A, varargin)</a>
-0077 
-0078    parser = inputParser;
-0079    parser.FunctionName = <span class="string">'baseflow.baseflowtrend'</span>;
-0080    parser.addRequired(<span class="string">'t'</span>, @isdatelike);
-0081    parser.addRequired(<span class="string">'Q'</span>, @isnumericvector);
-0082    parser.addRequired(<span class="string">'A'</span>, @isnumericscalar);
-0083    parser.addParameter(<span class="string">'method'</span>, <span class="string">'ols'</span>, @ischarlike);
-0084    parser.addParameter(<span class="string">'pctl'</span>, 0.25, @isnumericscalar);
-0085    parser.addParameter(<span class="string">'showfig'</span>, false, @islogicalscalar);
-0086    parser.parse(t,Q,A,varargin{:});
-0087 
-0088    <span class="comment">% Convert datetime to double if datetime was passed in</span>
-0089    t = todatenum(t);
-0090 
-0091    method = parser.Results.method;
-0092    prctle = parser.Results.pctl;
-0093    showfig = parser.Results.showfig;
-0094 <span class="keyword">end</span></pre></div>
+0042    <span class="comment">%  Compute annual baseflow and its trend from the example daily</span>
+0043    <span class="comment">%  streamflow record. The basin area converts flow to cm/d:</span>
+0044    <span class="comment">%</span>
+0045    <span class="comment">%     [T, Q] = baseflow.loadExampleData();</span>
+0046    <span class="comment">%     [Qb, dQbdt] = baseflow.baseflowtrend(T, Q, 8.6545e9);</span>
+0047    <span class="comment">%     fprintf('Mean annual baseflow = %.3f cm/d\n', mean(Qb))</span>
+0048    <span class="comment">%</span>
+0049    <span class="comment">% See also: aquiferthickness</span>
+0050    <span class="comment">%</span>
+0051    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0052 
+0053    <span class="comment">% if called with no input, open this file</span>
+0054    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0055 
+0056    <span class="comment">% PARSE INPUTS</span>
+0057    [t, Q, A, method, pctl, showfig] = <a href="#_sub1" class="code" title="subfunction [t, Q, A, method, prctle, showfig] = parseinputs(t, Q, A, varargin)">parseinputs</a>(t, Q, A, varargin{:});
+0058 
+0059    <span class="comment">% MAIN FUNCTION</span>
+0060    t1 = datenum(year(t(1)), 1, 1, 0, 0, 0);
+0061    t2 = datenum(year(t(end)), 12, 31, 0, 0, 0);
+0062    [Q, t] = padtimeseries(Q, t, t1, t2, 1); <span class="comment">%#ok&lt;*DATNM&gt;</span>
+0063    [Q, t] = rmleapinds(Q, t);
+0064 
+0065    <span class="comment">% convert the flow from m3/d posted daily to cm/d posted annually</span>
+0066    <span class="comment">%if ~isdatetime(t); t = datetime(t,'ConvertFrom','datenum'); end</span>
+0067    t = transpose(year(mean(reshape(t, 365, numel(t) / 365))));
+0068    Qa = transpose(mean(reshape(Q, 365, numel(Q) / 365), <span class="string">'omitnan'</span>)) .* (100/A);
+0069 
+0070    <span class="comment">% regress Q [cm/d/y] against t [y] to get the trend [cm/d] posted annually</span>
+0071    ha = baseflow.trendplot(t, Qa, <span class="string">'anomalies'</span>, false, <span class="string">'units'</span>, <span class="string">'cm/d/y'</span>, <span class="keyword">...</span>
+0072       <span class="string">'titletext'</span>, <span class="string">'mean flow'</span>, <span class="string">'legendtext'</span>, <span class="string">'mean flow regression'</span>, <span class="keyword">...</span>
+0073       <span class="string">'showfig'</span>, showfig, <span class="string">'method'</span>, method);
+0074    hb = baseflow.trendplot(t, Qa, <span class="string">'anomalies'</span>, false, <span class="string">'units'</span>, <span class="string">'cm/d/y'</span>, <span class="keyword">...</span>
+0075       <span class="string">'quantile'</span>, pctl, <span class="string">'titletext'</span>, <span class="string">'baseflow'</span>, <span class="string">'legendtext'</span>, <span class="keyword">...</span>
+0076       <span class="string">'baseflow regression'</span>, <span class="string">'showfig'</span>, showfig, <span class="string">'alpha'</span>, 0.05);
+0077    dQadt = reshape(get(ha.trend, <span class="string">'YData'</span>), [], 1); <span class="comment">% mean flow trend</span>
+0078    dQbdt = reshape(get(hb.trend, <span class="string">'YData'</span>), [], 1); <span class="comment">% baseflow trend</span>
+0079    Qb = Qa-(dQadt-dQbdt); <span class="comment">% baseflow timeseries, cm/day</span>
+0080 <span class="keyword">end</span>
+0081 
+0082 <span class="comment">%% INPUT PARSER</span>
+0083 <a name="_sub1" href="#_subfunctions" class="code">function [t, Q, A, method, prctle, showfig] = parseinputs(t, Q, A, varargin)</a>
+0084 
+0085    parser = inputParser;
+0086    parser.FunctionName = <span class="string">'baseflow.baseflowtrend'</span>;
+0087    parser.addRequired(<span class="string">'t'</span>, @isdatelike);
+0088    parser.addRequired(<span class="string">'Q'</span>, @isnumericvector);
+0089    parser.addRequired(<span class="string">'A'</span>, @isnumericscalar);
+0090    parser.addParameter(<span class="string">'method'</span>, <span class="string">'ols'</span>, @ischarlike);
+0091    parser.addParameter(<span class="string">'pctl'</span>, 0.25, <span class="keyword">...</span>
+0092       @(x) isnumericscalar(x) &amp;&amp; x &gt; 0 &amp;&amp; x &lt; 1);
+0093    parser.addParameter(<span class="string">'showfig'</span>, false, @islogicalscalar);
+0094    parser.parse(t,Q,A,varargin{:});
+0095 
+0096    <span class="comment">% Convert datetime to double if datetime was passed in</span>
+0097    t = todatenum(t);
+0098 
+0099    method = parser.Results.method;
+0100    prctle = parser.Results.pctl;
+0101    showfig = parser.Results.showfig;
+0102 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/cloudphi.html b/toolbox/docs/html/m2html/+baseflow/cloudphi.html
index e166aa2..99c6364 100644
--- a/toolbox/docs/html/m2html/+baseflow/cloudphi.html
+++ b/toolbox/docs/html/m2html/+baseflow/cloudphi.html
@@ -63,6 +63,10 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
                  The late-time line uses the input method, and only
                  method 'envelope' reads lateqtls. Default is
                  [0.5 0.5].
+     userab      late-time [a b] of a line the user chose. cloudphi then
+                 uses this line in place of the line it fits at blate,
+                 and blate does not enter phi. Default is [] (fit the
+                 late-time line).
      mask        logical mask to exclude data
      theta       effective slope of basin contributing area
      isflat      logical flag indicating if horizontal or sloped aquifer
@@ -143,152 +147,160 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0035    <span class="comment">%                 The late-time line uses the input method, and only</span>
 0036    <span class="comment">%                 method 'envelope' reads lateqtls. Default is</span>
 0037    <span class="comment">%                 [0.5 0.5].</span>
-0038    <span class="comment">%     mask        logical mask to exclude data</span>
-0039    <span class="comment">%     theta       effective slope of basin contributing area</span>
-0040    <span class="comment">%     isflat      logical flag indicating if horizontal or sloped aquifer</span>
-0041    <span class="comment">%                 solution is applicable</span>
-0042    <span class="comment">%     soln1       optional early-time theoretical solution</span>
-0043    <span class="comment">%     soln2       optional late-time theoretical solution</span>
-0044    <span class="comment">%     dispfit     logical flag indicating whether fitphi prints each phi</span>
-0045    <span class="comment">%                 value. Default is false.</span>
-0046    <span class="comment">%     plotfit     logical flag indicating whether to draw the point cloud,</span>
-0047    <span class="comment">%                 the early-time and fitted late-time lines, and the phi</span>
-0048    <span class="comment">%                 legend. Default is true.</span>
-0049    <span class="comment">%</span>
-0050    <span class="comment">% See also: eventphi, fitphi, fitphidist</span>
-0051    <span class="comment">%</span>
-0052    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0038    <span class="comment">%     userab      late-time [a b] of a line the user chose. cloudphi then</span>
+0039    <span class="comment">%                 uses this line in place of the line it fits at blate,</span>
+0040    <span class="comment">%                 and blate does not enter phi. Default is [] (fit the</span>
+0041    <span class="comment">%                 late-time line).</span>
+0042    <span class="comment">%     mask        logical mask to exclude data</span>
+0043    <span class="comment">%     theta       effective slope of basin contributing area</span>
+0044    <span class="comment">%     isflat      logical flag indicating if horizontal or sloped aquifer</span>
+0045    <span class="comment">%                 solution is applicable</span>
+0046    <span class="comment">%     soln1       optional early-time theoretical solution</span>
+0047    <span class="comment">%     soln2       optional late-time theoretical solution</span>
+0048    <span class="comment">%     dispfit     logical flag indicating whether fitphi prints each phi</span>
+0049    <span class="comment">%                 value. Default is false.</span>
+0050    <span class="comment">%     plotfit     logical flag indicating whether to draw the point cloud,</span>
+0051    <span class="comment">%                 the early-time and fitted late-time lines, and the phi</span>
+0052    <span class="comment">%                 legend. Default is true.</span>
 0053    <span class="comment">%</span>
-0054    <span class="comment">% Note: The method used for ahat = pointcloudintercept should also be used</span>
-0055    <span class="comment">% here for consistency.</span>
-0056 
-0057    <span class="comment">% if called with no input, open this file</span>
-0058    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0059 
-0060    <span class="comment">% parse inputs</span>
-0061    [q, dqdt, blate, A, D, L, method, earlyqtls, lateqtls, userab, mask, <span class="keyword">...</span>
-0062       ~, isflat, ~, ~, dispfit, plotfit] = parseinputs(q, dqdt, blate, <span class="keyword">...</span>
-0063       A, D, L, method, varargin{:});
-0064 
-0065    <span class="comment">% the easiest way to get a1/a2 is pointcloudintercept. baseflow.fitab could</span>
-0066    <span class="comment">% also be used but this function is intended to fit phi once b is known (or</span>
-0067    <span class="comment">% prescribed)</span>
+0054    <span class="comment">% See also: eventphi, fitphi, fitphidist</span>
+0055    <span class="comment">%</span>
+0056    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0057    <span class="comment">%</span>
+0058    <span class="comment">% Note: The method used for ahat = pointcloudintercept should also be used</span>
+0059    <span class="comment">% here for consistency.</span>
+0060 
+0061    <span class="comment">% if called with no input, open this file</span>
+0062    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0063 
+0064    <span class="comment">% parse inputs</span>
+0065    [q, dqdt, blate, A, D, L, method, earlyqtls, lateqtls, userab, mask, <span class="keyword">...</span>
+0066       ~, isflat, ~, ~, dispfit, plotfit] = parseinputs(q, dqdt, blate, <span class="keyword">...</span>
+0067       A, D, L, method, varargin{:});
 0068 
-0069    <span class="comment">% a1 = early-time a</span>
-0070    <span class="comment">% b1 = 3 (not involved)</span>
-0071    <span class="comment">% a2 = late-time a</span>
-0072    <span class="comment">% b2 = late-time b (bhat or theoretical solution b=1 or b=3/2)</span>
-0073 
-0074    <span class="keyword">if</span> isnan(userab)
-0075       b2 = blate;
-0076       a1 = baseflow.pointcloudintercept(q,dqdt,3,<span class="string">'envelope'</span>,<span class="string">'refqtls'</span>,earlyqtls);
-0077       a2 = baseflow.pointcloudintercept(q,dqdt,b2,method,<span class="string">'refqtls'</span>,lateqtls,<span class="string">'mask'</span>,mask);
-0078    <span class="keyword">else</span>
-0079 
-0080    <span class="keyword">end</span>
-0081 
-0082    <span class="keyword">switch</span> b2
-0083       <span class="keyword">case</span> 1
-0084          phi = baseflow.fitphi(a1,a2,b2,A,D,L,<span class="string">'isflat'</span>,isflat,<span class="string">'soln1'</span>,<span class="string">'PK62'</span>, <span class="keyword">...</span>
-0085             <span class="string">'soln2'</span>,<span class="string">'BS03'</span>,<span class="string">'dispfit'</span>,dispfit);
-0086       <span class="keyword">case</span> 3/2
-0087          phi = baseflow.fitphi(a1,a2,b2,A,D,L,<span class="string">'isflat'</span>,isflat,<span class="string">'soln1'</span>,<span class="string">'PK62'</span>, <span class="keyword">...</span>
-0088             <span class="string">'soln2'</span>,<span class="string">'BS04'</span>,<span class="string">'dispfit'</span>,dispfit);
-0089       <span class="keyword">otherwise</span>
-0090          phi = baseflow.fitphi(a1,a2,b2,A,D,L,<span class="string">'isflat'</span>,isflat,<span class="string">'soln1'</span>,<span class="string">'RS05'</span>,  <span class="keyword">...</span>
-0091             <span class="string">'soln2'</span>,<span class="string">'RS05'</span>,<span class="string">'dispfit'</span>,dispfit);
-0092    <span class="keyword">end</span>
-0093    a = a2;
-0094 
-0095    <span class="comment">% Skip the figure when plotfit is false. globalfit passes its plotfits</span>
-0096    <span class="comment">% flag here, so a global fit with plotfits false opens no figure.</span>
-0097    <span class="keyword">if</span> plotfit
-0098       <span class="comment">% make a dummy handle for the legend and print the value of phi</span>
-0099       baseflow.pointcloudplot(q,dqdt,<span class="string">'blate'</span>,blate,<span class="string">'mask'</span>,mask,<span class="string">'reflines'</span>, <span class="keyword">...</span>
-0100          {<span class="string">'early'</span>,<span class="string">'userfit'</span>},<span class="string">'userab'</span>,[a2 blate],<span class="string">'reflabels'</span>,true);
-0101       hdum = plot(0,0,<span class="string">'Color'</span>,<span class="string">'none'</span>,<span class="string">'HandleVisibility'</span>,<span class="string">'off'</span>);
-0102 
-0103       <span class="keyword">if</span> isoctave
-0104          txt = sprintf(<span class="string">'\\phi = %.2f'</span>,phi);
-0105          legend(hdum,txt,<span class="string">'Interpreter'</span>,<span class="string">'tex'</span>,<span class="string">'Location'</span>,<span class="string">'northwest'</span>, <span class="keyword">...</span>
-0106             <span class="string">'box'</span>,<span class="string">'off'</span>);
-0107       <span class="keyword">else</span>
-0108          txt = sprintf(<span class="string">'$\\phi_{b=%.2f}=%.3f$'</span>,b2,phi);
-0109          legend(hdum,txt,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>,<span class="string">'Location'</span>,<span class="string">'northwest'</span>, <span class="keyword">...</span>
-0110             <span class="string">'box'</span>,<span class="string">'off'</span>);
-0111       <span class="keyword">end</span>
-0112    <span class="keyword">end</span>
-0113 <span class="keyword">end</span>
-0114 
-0115 <span class="comment">%% input parser</span>
-0116 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, blate, A, D, L, method, earlyqtls, lateqtls, userab, mask, </a><span class="keyword">...</span>
-0117       theta, isflat, soln1, soln2, dispfit, plotfit] = parseinputs(q, dqdt, <span class="keyword">...</span>
-0118       blate, A, D, L, method, varargin)
-0119 
-0120    parser = inputParser;
-0121    parser.StructExpand = false;
-0122    parser.FunctionName = <span class="string">'baseflow.cloudphi'</span>;
-0123 
-0124    addRequired(parser, <span class="string">'q'</span>, @isnumeric);
-0125    addRequired(parser, <span class="string">'dqdt'</span>, @isnumeric);
-0126    addRequired(parser, <span class="string">'blate'</span>, @isnumeric);
-0127    addRequired(parser, <span class="string">'A'</span>, @isnumeric);
-0128    addRequired(parser, <span class="string">'D'</span>, @isnumeric);
-0129    addRequired(parser, <span class="string">'L'</span>, @isnumeric);
-0130    addRequired(parser, <span class="string">'method'</span>, @ischar);
-0131    addParameter(parser,<span class="string">'earlyqtls'</span>,[0.95 0.95], @isnumeric);
-0132    addParameter(parser,<span class="string">'lateqtls'</span>, [0.5 0.5], @isnumeric);
-0133    addParameter(parser,<span class="string">'userab'</span>, nan, @isnumeric);
-0134    addParameter(parser,<span class="string">'mask'</span>, true(size(q)), @islogical);
-0135    addParameter(parser,<span class="string">'theta'</span>, 0, @isnumeric);
-0136    addParameter(parser,<span class="string">'isflat'</span>, true,  @islogical);
-0137    addParameter(parser,<span class="string">'soln1'</span>, <span class="string">'RS05'</span>, @ischar);
-0138    addParameter(parser,<span class="string">'soln2'</span>, <span class="string">'RS05'</span>, @ischar);
-0139    addParameter(parser,<span class="string">'dispfit'</span>, false, @islogical);
-0140    addParameter(parser,<span class="string">'plotfit'</span>, true, @islogical);
-0141 
-0142    parse(parser,q,dqdt,blate,A,D,L,method,varargin{:});
-0143 
-0144    earlyqtls   = parser.Results.earlyqtls;
-0145    lateqtls    = parser.Results.lateqtls;
-0146    userab      = parser.Results.userab;
-0147    mask        = parser.Results.mask;
-0148    theta       = parser.Results.theta;
-0149    isflat      = parser.Results.isflat;
-0150    soln1       = parser.Results.soln1;
-0151    soln2       = parser.Results.soln2;
-0152    dispfit     = parser.Results.dispfit;
-0153    plotfit     = parser.Results.plotfit;
-0154 <span class="keyword">end</span>
-0155 
-0156 <span class="comment">%%</span>
-0157 <span class="comment">% found this in an older test version, need to integrate or delete</span>
-0158 <span class="comment">%</span>
-0159 <span class="comment">% if isflat</span>
-0160 <span class="comment">%    switch blate</span>
-0161 <span class="comment">%       case 1</span>
-0162 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','PK62', ...</span>
-0163 <span class="comment">%             'soln2','BS03','dispfit',dispfit);</span>
-0164 <span class="comment">%       case 3/2</span>
-0165 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','PK62', ...</span>
-0166 <span class="comment">%             'soln2','BS04','dispfit',dispfit);</span>
-0167 <span class="comment">%       otherwise</span>
-0168 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','RS05',  ...</span>
-0169 <span class="comment">%             'soln2','RS05','dispfit',dispfit);</span>
-0170 <span class="comment">%    end</span>
-0171 <span class="comment">% else</span>
-0172 <span class="comment">%    switch blate</span>
-0173 <span class="comment">%       case 1</span>
-0174 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','BR94', ...</span>
-0175 <span class="comment">%             'soln2','BR94','dispfit',dispfit,'theta',theta);</span>
-0176 <span class="comment">%       case 3/2</span>
-0177 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','BR94', ...</span>
-0178 <span class="comment">%             'soln2','RS06','dispfit',dispfit,'theta',theta);</span>
-0179 <span class="comment">%       otherwise</span>
-0180 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','BR94',  ...</span>
-0181 <span class="comment">%             'soln2','RS06','dispfit',dispfit,'theta',theta);</span>
-0182 <span class="comment">%    end</span>
-0183 <span class="comment">% end</span>
-0184 <span class="comment">% a = a2;</span></pre></div>
+0069    <span class="comment">% the easiest way to get a1/a2 is pointcloudintercept. baseflow.fitab could</span>
+0070    <span class="comment">% also be used but this function is intended to fit phi once b is known (or</span>
+0071    <span class="comment">% prescribed)</span>
+0072 
+0073    <span class="comment">% a1 = early-time a</span>
+0074    <span class="comment">% b1 = 3 (not involved)</span>
+0075    <span class="comment">% a2 = late-time a</span>
+0076    <span class="comment">% b2 = late-time b (bhat or theoretical solution b=1 or b=3/2)</span>
+0077 
+0078    <span class="comment">% The early-time line always comes from the point cloud. A user line in</span>
+0079    <span class="comment">% userab replaces the late-time line fitted at blate.</span>
+0080    a1 = baseflow.pointcloudintercept(q,dqdt,3,<span class="string">'envelope'</span>,<span class="string">'refqtls'</span>,earlyqtls);
+0081    <span class="keyword">if</span> isempty(userab)
+0082       b2 = blate;
+0083       a2 = baseflow.pointcloudintercept(q,dqdt,b2,method,<span class="string">'refqtls'</span>,lateqtls,<span class="string">'mask'</span>,mask);
+0084    <span class="keyword">else</span>
+0085       a2 = userab(1);
+0086       b2 = userab(2);
+0087    <span class="keyword">end</span>
+0088 
+0089    <span class="keyword">switch</span> b2
+0090       <span class="keyword">case</span> 1
+0091          phi = baseflow.fitphi(a1,a2,b2,A,D,L,<span class="string">'isflat'</span>,isflat,<span class="string">'soln1'</span>,<span class="string">'PK62'</span>, <span class="keyword">...</span>
+0092             <span class="string">'soln2'</span>,<span class="string">'BS03'</span>,<span class="string">'dispfit'</span>,dispfit);
+0093       <span class="keyword">case</span> 3/2
+0094          phi = baseflow.fitphi(a1,a2,b2,A,D,L,<span class="string">'isflat'</span>,isflat,<span class="string">'soln1'</span>,<span class="string">'PK62'</span>, <span class="keyword">...</span>
+0095             <span class="string">'soln2'</span>,<span class="string">'BS04'</span>,<span class="string">'dispfit'</span>,dispfit);
+0096       <span class="keyword">otherwise</span>
+0097          phi = baseflow.fitphi(a1,a2,b2,A,D,L,<span class="string">'isflat'</span>,isflat,<span class="string">'soln1'</span>,<span class="string">'RS05'</span>,  <span class="keyword">...</span>
+0098             <span class="string">'soln2'</span>,<span class="string">'RS05'</span>,<span class="string">'dispfit'</span>,dispfit);
+0099    <span class="keyword">end</span>
+0100    a = a2;
+0101 
+0102    <span class="comment">% Skip the figure when plotfit is false. globalfit passes its plotfits</span>
+0103    <span class="comment">% flag here, so a global fit with plotfits false opens no figure.</span>
+0104    <span class="keyword">if</span> plotfit
+0105       <span class="comment">% make a dummy handle for the legend and print the value of phi</span>
+0106       baseflow.pointcloudplot(q,dqdt,<span class="string">'blate'</span>,blate,<span class="string">'mask'</span>,mask,<span class="string">'reflines'</span>, <span class="keyword">...</span>
+0107          {<span class="string">'early'</span>,<span class="string">'userfit'</span>},<span class="string">'userab'</span>,[a2 b2],<span class="string">'reflabels'</span>,true);
+0108       hdum = plot(0,0,<span class="string">'Color'</span>,<span class="string">'none'</span>,<span class="string">'HandleVisibility'</span>,<span class="string">'off'</span>);
+0109 
+0110       <span class="keyword">if</span> isoctave
+0111          txt = sprintf(<span class="string">'\\phi = %.2f'</span>,phi);
+0112          legend(hdum,txt,<span class="string">'Interpreter'</span>,<span class="string">'tex'</span>,<span class="string">'Location'</span>,<span class="string">'northwest'</span>, <span class="keyword">...</span>
+0113             <span class="string">'box'</span>,<span class="string">'off'</span>);
+0114       <span class="keyword">else</span>
+0115          txt = sprintf(<span class="string">'$\\phi_{b=%.2f}=%.3f$'</span>,b2,phi);
+0116          legend(hdum,txt,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>,<span class="string">'Location'</span>,<span class="string">'northwest'</span>, <span class="keyword">...</span>
+0117             <span class="string">'box'</span>,<span class="string">'off'</span>);
+0118       <span class="keyword">end</span>
+0119    <span class="keyword">end</span>
+0120 <span class="keyword">end</span>
+0121 
+0122 <span class="comment">%% input parser</span>
+0123 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, blate, A, D, L, method, earlyqtls, lateqtls, userab, mask, </a><span class="keyword">...</span>
+0124       theta, isflat, soln1, soln2, dispfit, plotfit] = parseinputs(q, dqdt, <span class="keyword">...</span>
+0125       blate, A, D, L, method, varargin)
+0126 
+0127    parser = inputParser;
+0128    parser.StructExpand = false;
+0129    parser.FunctionName = <span class="string">'baseflow.cloudphi'</span>;
+0130 
+0131    addRequired(parser, <span class="string">'q'</span>, @isnumeric);
+0132    addRequired(parser, <span class="string">'dqdt'</span>, @isnumeric);
+0133    addRequired(parser, <span class="string">'blate'</span>, @isnumeric);
+0134    addRequired(parser, <span class="string">'A'</span>, @isnumeric);
+0135    addRequired(parser, <span class="string">'D'</span>, @isnumeric);
+0136    addRequired(parser, <span class="string">'L'</span>, @isnumeric);
+0137    addRequired(parser, <span class="string">'method'</span>, @ischar);
+0138    addParameter(parser,<span class="string">'earlyqtls'</span>,[0.95 0.95], @isnumeric);
+0139    addParameter(parser,<span class="string">'lateqtls'</span>, [0.5 0.5], @isnumeric);
+0140    addParameter(parser,<span class="string">'userab'</span>, [], <span class="keyword">...</span>
+0141       @(x) isempty(x) || isnumericvector(x) &amp;&amp; numel(x) == 2);
+0142    addParameter(parser,<span class="string">'mask'</span>, true(size(q)), @islogical);
+0143    addParameter(parser,<span class="string">'theta'</span>, 0, @isnumeric);
+0144    addParameter(parser,<span class="string">'isflat'</span>, true,  @islogical);
+0145    addParameter(parser,<span class="string">'soln1'</span>, <span class="string">'RS05'</span>, @ischar);
+0146    addParameter(parser,<span class="string">'soln2'</span>, <span class="string">'RS05'</span>, @ischar);
+0147    addParameter(parser,<span class="string">'dispfit'</span>, false, @islogical);
+0148    addParameter(parser,<span class="string">'plotfit'</span>, true, @islogical);
+0149 
+0150    parse(parser,q,dqdt,blate,A,D,L,method,varargin{:});
+0151 
+0152    earlyqtls   = parser.Results.earlyqtls;
+0153    lateqtls    = parser.Results.lateqtls;
+0154    userab      = parser.Results.userab;
+0155    mask        = parser.Results.mask;
+0156    theta       = parser.Results.theta;
+0157    isflat      = parser.Results.isflat;
+0158    soln1       = parser.Results.soln1;
+0159    soln2       = parser.Results.soln2;
+0160    dispfit     = parser.Results.dispfit;
+0161    plotfit     = parser.Results.plotfit;
+0162 <span class="keyword">end</span>
+0163 
+0164 <span class="comment">%%</span>
+0165 <span class="comment">% found this in an older test version, need to integrate or delete</span>
+0166 <span class="comment">%</span>
+0167 <span class="comment">% if isflat</span>
+0168 <span class="comment">%    switch blate</span>
+0169 <span class="comment">%       case 1</span>
+0170 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','PK62', ...</span>
+0171 <span class="comment">%             'soln2','BS03','dispfit',dispfit);</span>
+0172 <span class="comment">%       case 3/2</span>
+0173 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','PK62', ...</span>
+0174 <span class="comment">%             'soln2','BS04','dispfit',dispfit);</span>
+0175 <span class="comment">%       otherwise</span>
+0176 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','RS05',  ...</span>
+0177 <span class="comment">%             'soln2','RS05','dispfit',dispfit);</span>
+0178 <span class="comment">%    end</span>
+0179 <span class="comment">% else</span>
+0180 <span class="comment">%    switch blate</span>
+0181 <span class="comment">%       case 1</span>
+0182 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','BR94', ...</span>
+0183 <span class="comment">%             'soln2','BR94','dispfit',dispfit,'theta',theta);</span>
+0184 <span class="comment">%       case 3/2</span>
+0185 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','BR94', ...</span>
+0186 <span class="comment">%             'soln2','RS06','dispfit',dispfit,'theta',theta);</span>
+0187 <span class="comment">%       otherwise</span>
+0188 <span class="comment">%          phi = baseflow_fitphi(a1,a2,b2,A,D,L,'isflat',isflat,'soln1','BR94',  ...</span>
+0189 <span class="comment">%             'soln2','RS06','dispfit',dispfit,'theta',theta);</span>
+0190 <span class="comment">%    end</span>
+0191 <span class="comment">% end</span>
+0192 <span class="comment">% a = a2;</span></pre></div>
 </body>
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diff --git a/toolbox/docs/html/m2html/+baseflow/conversions.html b/toolbox/docs/html/m2html/+baseflow/conversions.html
index dd45a0a..b51f5fc 100644
--- a/toolbox/docs/html/m2html/+baseflow/conversions.html
+++ b/toolbox/docs/html/m2html/+baseflow/conversions.html
@@ -132,7 +132,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0050    <span class="comment">%             Nstar,    from N* = 1/(N+1)</span>
 0051    <span class="comment">%                 d,    from Q = cS^d, where d = 1/(2-b)</span>
 0052    <span class="comment">%                 n,    from k(z) = kD(z/D)^n,</span>
-0053    <span class="comment">%                 k,    from P(Q) ~ Q^-(1+1/k)</span>
+0053    <span class="comment">%                 k,    from p(tau) ~ tau^-(1+1/k)</span>
 0054    <span class="comment">%            isflat,    true if flat aquifer</span>
 0055    <span class="comment">%</span>
 0056    <span class="comment">%  Outputs:       b,    from dQ(t)=a*Q^b</span>
@@ -177,90 +177,94 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0095             <span class="keyword">case</span> false
 0096                b = 1-N;
 0097          <span class="keyword">end</span>
-0098    <span class="keyword">end</span>
-0099 <span class="keyword">end</span>
-0100 
-0101 <a name="_sub2" href="#_subfunctions" class="code">function varargout = convertb(b,outputvarname,isflat)</a>
-0102    <span class="comment">%BCONVERSIONS Convert the recession flow power law exponent b to any of</span>
-0103    <span class="comment">%several other recession flow parameters.</span>
-0104    <span class="comment">%</span>
-0105    <span class="comment">%  Inputs:        b,    from dQ(t)=a*Q^b</span>
-0106    <span class="comment">%            isflat,    true if flat aquifer</span>
-0107    <span class="comment">%</span>
-0108    <span class="comment">%  Outputs:   alpha,    from P(Q) ~ t*^-alpha</span>
-0109    <span class="comment">%              beta,    from Q ~ S^-beta (beta = -d)</span>
-0110    <span class="comment">%             gamma,    from 1/gamma = 1/alpha + 1/beta</span>
-0111    <span class="comment">%                 N,    from a = c1*D^N, where c1 is a coefficient</span>
-0112    <span class="comment">%             Nstar,    from N* = 1/(N+1)</span>
-0113    <span class="comment">%                 d,    from Q = cS^d, where d = 1/(2-b)</span>
-0114    <span class="comment">%                 n,    from k(z) = kD(z/D)^n,</span>
-0115    <span class="comment">%                 k,    from P(Q) ~ Q^-(1+1/k)</span>
-0116    <span class="comment">%</span>
-0117    <span class="comment">% k is the gpfit shape parameter: the gpd tail pdf ~ x^-(1+1/k) equals the</span>
-0118    <span class="comment">% timescale pdf ~ x^-alpha, so k = 1/(alpha-1) = (1-b)/(b-2).</span>
-0119 
-0120    alpha = 1./(b-1);       <span class="comment">% power law exponent alpha</span>
-0121    beta  = 1./(b-2);
-0122    gamma = 1./(2.*b-3);
-0123    d     = 1./(2-b);
-0124    k     = (1-b)./(b-2);
-0125 
-0126    <span class="keyword">switch</span> isflat
-0127       <span class="keyword">case</span> true
-0128          n = (3-2.*b)./(b-2);   <span class="comment">% saturated hyd. cond. power function exponent</span>
-0129          N = 3-2.*b;            <span class="comment">% scale parameter power law exponent N</span>
-0130          Nstar = 1./(4-2.*b);
-0131 
-0132       <span class="keyword">case</span> false
-0133          n = (1-b)./(b-2);
-0134          N = 1-b;
-0135          Nstar = 1./(2-b);
-0136    <span class="keyword">end</span>
-0137 
-0138    <span class="keyword">switch</span> outputvarname
-0139       <span class="keyword">case</span> <span class="string">'b'</span>
-0140          varargout{1} = b;
-0141       <span class="keyword">case</span> <span class="string">'alpha'</span>
-0142          varargout{1} = alpha;
-0143       <span class="keyword">case</span> <span class="string">'beta'</span>
-0144          varargout{1} = beta;
-0145       <span class="keyword">case</span> <span class="string">'gamma'</span>
-0146          varargout{1} = gamma;
-0147       <span class="keyword">case</span> <span class="string">'d'</span>
-0148          varargout{1} = d;
-0149       <span class="keyword">case</span> <span class="string">'k'</span>
-0150          varargout{1} = k;
-0151       <span class="keyword">case</span> <span class="string">'n'</span>
-0152          varargout{1} = n;
-0153       <span class="keyword">case</span> <span class="string">'N'</span>
-0154          varargout{1} = N;
-0155       <span class="keyword">case</span> <span class="string">'Nstar'</span>
-0156          varargout{1} = Nstar;
-0157    <span class="keyword">end</span>
-0158 <span class="keyword">end</span>
-0159 
-0160 <span class="comment">%% INPUT PARSER</span>
-0161 <a name="_sub3" href="#_subfunctions" class="code">function [inputvalue, inputvarname, outputvarname, isflat] = parseinputs( </a><span class="keyword">...</span>
-0162       inputvalue, inputvarname, outputvarname, varargin)
+0098 
+0099       <span class="keyword">case</span> <span class="string">'Nstar'</span>
+0100          <span class="comment">% N* = 1/(N+1), so convert through N</span>
+0101          b = <a href="#_sub1" class="code" title="subfunction b = convert2b(inputvalue,inputvarname,isflat)">convert2b</a>(1./inputvalue-1,<span class="string">'N'</span>,isflat);
+0102    <span class="keyword">end</span>
+0103 <span class="keyword">end</span>
+0104 
+0105 <a name="_sub2" href="#_subfunctions" class="code">function varargout = convertb(b,outputvarname,isflat)</a>
+0106    <span class="comment">%BCONVERSIONS Convert the recession flow power law exponent b to any of</span>
+0107    <span class="comment">%several other recession flow parameters.</span>
+0108    <span class="comment">%</span>
+0109    <span class="comment">%  Inputs:        b,    from dQ(t)=a*Q^b</span>
+0110    <span class="comment">%            isflat,    true if flat aquifer</span>
+0111    <span class="comment">%</span>
+0112    <span class="comment">%  Outputs:   alpha,    from Q ~ t*^-alpha</span>
+0113    <span class="comment">%              beta,    from Q ~ S^-beta (beta = -d)</span>
+0114    <span class="comment">%             gamma,    from 1/gamma = 1/alpha + 1/beta</span>
+0115    <span class="comment">%                 N,    from a = c1*D^N, where c1 is a coefficient</span>
+0116    <span class="comment">%             Nstar,    from N* = 1/(N+1)</span>
+0117    <span class="comment">%                 d,    from Q = cS^d, where d = 1/(2-b)</span>
+0118    <span class="comment">%                 n,    from k(z) = kD(z/D)^n,</span>
+0119    <span class="comment">%                 k,    from p(tau) ~ tau^-(1+1/k)</span>
+0120    <span class="comment">%</span>
+0121    <span class="comment">% k is the gpfit shape parameter: the gpd tail pdf ~ x^-(1+1/k) equals the</span>
+0122    <span class="comment">% timescale pdf ~ x^-alpha, so k = 1/(alpha-1) = (1-b)/(b-2).</span>
+0123 
+0124    alpha = 1./(b-1);       <span class="comment">% power law exponent alpha</span>
+0125    beta  = 1./(b-2);
+0126    gamma = 1./(2.*b-3);
+0127    d     = 1./(2-b);
+0128    k     = (1-b)./(b-2);
+0129 
+0130    <span class="keyword">switch</span> isflat
+0131       <span class="keyword">case</span> true
+0132          n = (3-2.*b)./(b-2);   <span class="comment">% saturated hyd. cond. power function exponent</span>
+0133          N = 3-2.*b;            <span class="comment">% scale parameter power law exponent N</span>
+0134          Nstar = 1./(4-2.*b);
+0135 
+0136       <span class="keyword">case</span> false
+0137          n = (1-b)./(b-2);
+0138          N = 1-b;
+0139          Nstar = 1./(2-b);
+0140    <span class="keyword">end</span>
+0141 
+0142    <span class="keyword">switch</span> outputvarname
+0143       <span class="keyword">case</span> <span class="string">'b'</span>
+0144          varargout{1} = b;
+0145       <span class="keyword">case</span> <span class="string">'alpha'</span>
+0146          varargout{1} = alpha;
+0147       <span class="keyword">case</span> <span class="string">'beta'</span>
+0148          varargout{1} = beta;
+0149       <span class="keyword">case</span> <span class="string">'gamma'</span>
+0150          varargout{1} = gamma;
+0151       <span class="keyword">case</span> <span class="string">'d'</span>
+0152          varargout{1} = d;
+0153       <span class="keyword">case</span> <span class="string">'k'</span>
+0154          varargout{1} = k;
+0155       <span class="keyword">case</span> <span class="string">'n'</span>
+0156          varargout{1} = n;
+0157       <span class="keyword">case</span> <span class="string">'N'</span>
+0158          varargout{1} = N;
+0159       <span class="keyword">case</span> <span class="string">'Nstar'</span>
+0160          varargout{1} = Nstar;
+0161    <span class="keyword">end</span>
+0162 <span class="keyword">end</span>
 0163 
-0164    validvarnames = {<span class="string">'b'</span>, <span class="string">'alpha'</span>, <span class="string">'beta'</span>, <span class="string">'gamma'</span>, <span class="string">'d'</span>, <span class="string">'k'</span>, <span class="string">'n'</span>, <span class="string">'N'</span>, <span class="string">'Nstar'</span>};
-0165 
-0166    parser = inputParser;
-0167    parser.FunctionName = <span class="string">'baseflow.conversions'</span>;
-0168 
-0169    parser.addRequired(<span class="string">'inputvalue'</span>, @isnumeric);
-0170    parser.addRequired(<span class="string">'inputvarname'</span>, <span class="keyword">...</span>
-0171       @(x) ~isempty(validatestring(x, validvarnames)));
-0172    parser.addRequired(<span class="string">'outputvarname'</span>, <span class="keyword">...</span>
-0173       @(x) ~isempty(validatestring(x, validvarnames)));
-0174    parser.addParameter(<span class="string">'isflat'</span>, true, @islogical);
-0175 
-0176    parser.parse(inputvalue, inputvarname, outputvarname, varargin{:});
-0177 
-0178    inputvalue = parser.Results.inputvalue;
-0179    inputvarname = parser.Results.inputvarname;
-0180    outputvarname = parser.Results.outputvarname;
-0181    isflat = parser.Results.isflat;
-0182 <span class="keyword">end</span></pre></div>
+0164 <span class="comment">%% INPUT PARSER</span>
+0165 <a name="_sub3" href="#_subfunctions" class="code">function [inputvalue, inputvarname, outputvarname, isflat] = parseinputs( </a><span class="keyword">...</span>
+0166       inputvalue, inputvarname, outputvarname, varargin)
+0167 
+0168    validvarnames = {<span class="string">'b'</span>, <span class="string">'alpha'</span>, <span class="string">'beta'</span>, <span class="string">'gamma'</span>, <span class="string">'d'</span>, <span class="string">'k'</span>, <span class="string">'n'</span>, <span class="string">'N'</span>, <span class="string">'Nstar'</span>};
+0169 
+0170    parser = inputParser;
+0171    parser.FunctionName = <span class="string">'baseflow.conversions'</span>;
+0172 
+0173    parser.addRequired(<span class="string">'inputvalue'</span>, @isnumeric);
+0174    parser.addRequired(<span class="string">'inputvarname'</span>, <span class="keyword">...</span>
+0175       @(x) ~isempty(validatestring(x, validvarnames)));
+0176    parser.addRequired(<span class="string">'outputvarname'</span>, <span class="keyword">...</span>
+0177       @(x) ~isempty(validatestring(x, validvarnames)));
+0178    parser.addParameter(<span class="string">'isflat'</span>, true, @islogical);
+0179 
+0180    parser.parse(inputvalue, inputvarname, outputvarname, varargin{:});
+0181 
+0182    inputvalue = parser.Results.inputvalue;
+0183    inputvarname = parser.Results.inputvarname;
+0184    outputvarname = parser.Results.outputvarname;
+0185    isflat = parser.Results.isflat;
+0186 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/dndtuncertainty.html b/toolbox/docs/html/m2html/+baseflow/dndtuncertainty.html
index 55f2c73..70e31fb 100644
--- a/toolbox/docs/html/m2html/+baseflow/dndtuncertainty.html
+++ b/toolbox/docs/html/m2html/+baseflow/dndtuncertainty.html
@@ -54,6 +54,10 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
   solutions to the one-dimensional groundwater flow equation for a
   Boussinesq aquifer, and parameter b from -dQ/dt = aQb.
 
+  T is the daily time of the flow record (datetime or datenum), with or
+  without leap days. Qb holds one baseflow value in cm/yr for each
+  calendar year that T spans.
+
   alpha is the significance level of the returned uncertainty (default
   0.05, a 95% interval). Each input uncertainty is a standard error
   (one sigma): the drainable porosity from the phi bootstrap, and tau
@@ -122,304 +126,312 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0027    <span class="comment">%  solutions to the one-dimensional groundwater flow equation for a</span>
 0028    <span class="comment">%  Boussinesq aquifer, and parameter b from -dQ/dt = aQb.</span>
 0029    <span class="comment">%</span>
-0030    <span class="comment">%  alpha is the significance level of the returned uncertainty (default</span>
-0031    <span class="comment">%  0.05, a 95% interval). Each input uncertainty is a standard error</span>
-0032    <span class="comment">%  (one sigma): the drainable porosity from the phi bootstrap, and tau</span>
-0033    <span class="comment">%  and b from the GlobalFit bootstrap bounds. The function combines them</span>
-0034    <span class="comment">%  with the Jacobian and the correlation matrix, then multiplies the</span>
-0035    <span class="comment">%  combined standard uncertainty by the coverage factor</span>
-0036    <span class="comment">%  norminv(1-alpha/2). alpha 0.32 therefore gives about one sigma.</span>
-0037    <span class="comment">%  testflag true asks for a comparison of uncertainty methods, which is</span>
-0038    <span class="comment">%  not supported and raises a warning.</span>
-0039    <span class="comment">%</span>
-0040    <span class="comment">%  Note: globalfit with bootfit false returns tau_L = tau_H = tau and</span>
-0041    <span class="comment">%  b_L = b_H = b, so the tau and b terms are zero and the combined</span>
-0042    <span class="comment">%  uncertainty holds only the phi and regression terms.</span>
+0030    <span class="comment">%  T is the daily time of the flow record (datetime or datenum), with or</span>
+0031    <span class="comment">%  without leap days. Qb holds one baseflow value in cm/yr for each</span>
+0032    <span class="comment">%  calendar year that T spans.</span>
+0033    <span class="comment">%</span>
+0034    <span class="comment">%  alpha is the significance level of the returned uncertainty (default</span>
+0035    <span class="comment">%  0.05, a 95% interval). Each input uncertainty is a standard error</span>
+0036    <span class="comment">%  (one sigma): the drainable porosity from the phi bootstrap, and tau</span>
+0037    <span class="comment">%  and b from the GlobalFit bootstrap bounds. The function combines them</span>
+0038    <span class="comment">%  with the Jacobian and the correlation matrix, then multiplies the</span>
+0039    <span class="comment">%  combined standard uncertainty by the coverage factor</span>
+0040    <span class="comment">%  norminv(1-alpha/2). alpha 0.32 therefore gives about one sigma.</span>
+0041    <span class="comment">%  testflag true asks for a comparison of uncertainty methods, which is</span>
+0042    <span class="comment">%  not supported and raises a warning.</span>
 0043    <span class="comment">%</span>
-0044    <span class="comment">% See also: aquifertrend, aquiferthickness</span>
-0045    <span class="comment">%</span>
-0046    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0047 
-0048    <span class="comment">% if called with no input, open this file</span>
-0049    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0050 
-0051    <span class="comment">% parse inputs</span>
-0052    alpha = 0.05;
-0053    testflag = false;
-0054    <span class="keyword">if</span> nargin == 7
-0055       alpha = varargin{1};
-0056    <span class="keyword">elseif</span> nargin == 8
-0057       alpha = varargin{1};
-0058       testflag = varargin{2};
-0059    <span class="keyword">end</span>
-0060 
-0061    <span class="comment">% alpha sets the coverage factor applied to the combined standard</span>
-0062    <span class="comment">% uncertainty at the end of the function.</span>
-0063    <span class="keyword">if</span> ~isnumeric(alpha) || ~isscalar(alpha) || alpha &lt;= 0 || alpha &gt;= 1
-0064       error(<span class="string">'baseflow:dndtuncertainty:invalidAlpha'</span>, <span class="keyword">...</span>
-0065          <span class="string">'alpha must be a scalar in the interval (0, 1)'</span>)
-0066    <span class="keyword">end</span>
-0067    coveragefactor = norminv(1 - alpha/2);
-0068 
-0069    <span class="comment">% Convert time in days to years</span>
-0070    <span class="keyword">if</span> isdatetime(T)
-0071       T = todatenum(T);
-0072    <span class="keyword">end</span>
-0073 
-0074    t1 = datenum(year(T(1)), 1, 1);
-0075    t2 = datenum(year(T(end)), 12, 31);
-0076    [~, T] = padtimeseries(nan(size(T)), T, t1, t2, 1); <span class="comment">%#ok&lt;*DATNM&gt;</span>
-0077    T = transpose(year(mean(reshape(T, 365, numel(T)/365))));
-0078 
-0079    <span class="keyword">if</span> numel(T) ~= numel(Qb)
-0080       error(<span class="string">'size T must match size Qb'</span>)
-0081    <span class="keyword">end</span>
-0082 
-0083    <span class="comment">% Define the sensitivity coefficient and dn/dt trend functions</span>
-0084    Flam = @(tau, phi, b) tau./(phi.*(4-2.*b));
-0085    Fdndt = @(tau,phi,b,dqdt) tau./(phi.*(4-2.*b)).*dqdt;
-0086 
-0087    <span class="comment">% Regress baseflow in units cm/day/year to get uncertainty on dq/dt</span>
-0088    Qb = Qb./365.25;                          <span class="comment">% cm/yr -&gt; cm/day</span>
-0089 
-0090    <span class="comment">% fitlm returns a LinearModel in MATLAB and in the Octave statistics</span>
-0091    <span class="comment">% package, so one call serves both. Row 2 is the slope. Keep the</span>
-0092    <span class="comment">% standard error, because every term of the combined uncertainty below</span>
-0093    <span class="comment">% is one sigma.</span>
-0094    mdl = fitlm(T, Qb);
-0095       dbfdt = mdl.Coefficients.Estimate(2);  <span class="comment">% cm/day/year</span>
-0096    sig_dbfdt = mdl.Coefficients.SE(2);       <span class="comment">% standard error</span>
-0097 
-0098    <span class="comment">% In octave, the full Jacobian/Covariance Matrix method is not supported, but</span>
-0099    <span class="comment">% the uncertainty is dominated by the linear regression, so return that.</span>
-0100    <span class="keyword">if</span> isoctave
-0101       sig_dndt = coveragefactor * sig_dbfdt;
-0102       sig_lamda = nan;
-0103       <span class="keyword">return</span>
-0104    <span class="keyword">end</span>
-0105 
-0106    <span class="comment">% Parameters</span>
-0107    A = opts.drainagearea;     <span class="comment">% basin area [m2]</span>
-0108    D = opts.aquiferdepth;     <span class="comment">% reference active layer thickness [m]</span>
-0109    L = opts.streamlength;     <span class="comment">% effective stream network length [m]</span>
-0110 
-0111    <span class="comment">% Fit drainable porosity</span>
-0112    bhat = GlobalFit.b;
-0113    PhiFit = baseflow.phifitensemble(Results, Fits, A, D, L, bhat, <span class="keyword">...</span>
-0114       opts.lateqtls, opts.earlyqtls, false);
-0115 
-0116    <span class="comment">% The sample populations of tau, phi, and Nstar</span>
-0117    [~,~,~,~,G] = baseflow.eventtau(Results, Fits, Fits, <span class="keyword">...</span>
-0118       <span class="string">'usefits'</span>, true, <span class="string">'aggfunc'</span>, <span class="string">'max'</span>);
-0119 
-0120    b = [Results.b];
-0121    tau = G.tau; <span class="comment">% [K.tauH]';</span>
-0122    Np1 = 1./(4-2.*b);
-0123    phi1 = PhiFit.phidist(:, 1);
-0124    phi2 = PhiFit.phidist(:, 2);
-0125    phi = (phi1 + phi2) ./ 2;
-0126 
-0127    <span class="comment">% correlation between b and phi, using the two phi dist's b = 1 and b = 3/2:</span>
-0128    rho_phi12 = nancorr(phi1, phi2);
-0129    rho_phib1 = nancorr(Np1, phi1);
-0130    rho_phib2 = nancorr(Np1, phi2);
-0131 
-0132    <span class="keyword">if</span> isoctave
-0133       cov_phib1 = cov(Np1, phi1);
-0134       cov_phib2 = cov(Np1, phi2);
-0135    <span class="keyword">else</span>
-0136       cov_phib1 = cov(Np1, phi1, <span class="string">'omitrows'</span>);
-0137       cov_phib2 = cov(Np1, phi2, <span class="string">'omitrows'</span>);
-0138    <span class="keyword">end</span>
-0139 
-0140    <span class="comment">% define the uncertainties (standard errors)</span>
-0141    <span class="comment">% if we averaged phi1 and phi2, then the combined uncertainty would be:</span>
-0142    sig_phi1 = PhiFit.se(1);
-0143    sig_phi2 = PhiFit.se(2);
-0144    sig_phi = rho_phi12*sig_phi1*sig_phi2;
-0145    sig_phi = sqrt((0.5 * sig_phi1)^2 + (0.5 * sig_phi2)^2 + 2*0.5*0.5*sig_phi);
-0146    sig_tau = mean([GlobalFit.tau_H - GlobalFit.tau, GlobalFit.tau - GlobalFit.tau_L]);
-0147    sig_b = mean([GlobalFit.b_H - GlobalFit.b, GlobalFit.b - GlobalFit.b_L]);
-0148    <span class="comment">% Nstar = 1/(4-2b), so its uncertainty is dNstar/db times sig_b.</span>
-0149    sig_Np1 = nstaruncertainty(GlobalFit.b, sig_b);
-0150    <span class="comment">% the 0.5 on sig_phi1/2 is from the averaging procedure which divides by 2</span>
-0151 
-0152    <span class="comment">% Mean values of parameters</span>
-0153    tauhat = GlobalFit.tau;                      <span class="comment">% days</span>
-0154    phihat = PhiFit.mu(4);                       <span class="comment">% -</span>
-0155    bhat = GlobalFit.b;                          <span class="comment">% -</span>
-0156    Nhat = 1 / (4 - 2*bhat);                     <span class="comment">% -</span>
-0157 
-0158    <span class="comment">% Compute the sensitivity coefficient and dn/dt</span>
-0159    lambda = Flam(tauhat, phihat, bhat);
-0160    dndt = Fdndt(tauhat, phihat, bhat, dbfdt);   <span class="comment">% cm/yr</span>
-0161 
-0162    <span class="comment">% Compute the jacobian</span>
-0163    J = [dndt./tauhat, -dndt./phihat, dndt./Nhat, dndt./dbfdt];
-0164 
-0165    <span class="comment">% Construct the covariance matrix and compute the combined uncertainty.</span>
-0166    <span class="comment">% dq/dt comes from the annual regression, so it has no event-scale</span>
-0167    <span class="comment">% sample to correlate against the three event variables. A constant</span>
-0168    <span class="comment">% column makes corr return nan, so build the correlation matrix from</span>
-0169    <span class="comment">% the event variables and hold dq/dt uncorrelated with them.</span>
-0170    u = [sig_tau, sig_phi, sig_Np1, sig_dbfdt];
-0171    C = eye(4);
-0172    C(1:3, 1:3) = corr([tau, phi, Np1]);
-0173    V = C .* u .* u';
-0174    sig_dndt = coveragefactor * sqrt(J * V * J');
-0175    <span class="comment">% w/o correlated errors: sqrt(sum((J .* u).^2))</span>
-0176 
-0177    <span class="comment">% Compute the uncertainty on lambda (repeat above steps)</span>
-0178    J = [lambda./tauhat, -lambda./phihat, lambda./Nhat];
-0179    u = [sig_tau, sig_phi, sig_Np1];
-0180    V = corr([tau, phi, Np1]) .* u .* u';
-0181    sig_lamda = coveragefactor * sqrt(J * V * J');
-0182    <span class="comment">% w/o correlated errors: sqrt(sum((J .* u).^2))</span>
-0183 
-0184    <span class="keyword">if</span> testflag == true
-0185       warning(<span class="string">'method comparison not currently supported'</span>)
-0186    <span class="keyword">end</span>
-0187 <span class="keyword">end</span>
-0188 
-0189 <span class="comment">%% Methods comparison</span>
-0190 <span class="comment">% % Define symbols, setup matrices, etc.</span>
-0191 <span class="comment">%</span>
-0192 <span class="comment">% % FsigX is the standard uncertainty formula for four variables: tau, phi, b,</span>
-0193 <span class="comment">% % dq/dt.</span>
-0194 <span class="comment">%</span>
-0195 <span class="comment">% % FsigX2 is for two variables: lambda and dq/dt, so it uses Flambda(X) within</span>
-0196 <span class="comment">% % the function to compute the value of lambda, but accepts the scalar values</span>
-0197 <span class="comment">% % for dq/dt (Fx2) and sig_dq/dt (sig_x2). It would be clearer to replace this</span>
-0198 <span class="comment">% % with the scalar valued version, because this is just used to combine the</span>
-0199 <span class="comment">% % lambda uncertainty from worstcase with the linear regression dq/dt</span>
-0200 <span class="comment">% % uncertainty.</span>
-0201 <span class="comment">%</span>
-0202 <span class="comment">% % Methods that use Fdndt require the same format that is used in the main</span>
-0203 <span class="comment">% % function, so it is not redefined here</span>
-0204 <span class="comment">%</span>
-0205 <span class="comment">% sympref('FloatingPointOutput',true);</span>
-0206 <span class="comment">% syms tausym phisym bsym Qsym</span>
-0207 <span class="comment">%</span>
-0208 <span class="comment">% % define vector valued functions</span>
-0209 <span class="comment">% FsigX = @(X,Fx,sigX) Fx*sqrt((sigX(1)/X(1))^2+(sigX(2)/X(2))^2+ ...</span>
-0210 <span class="comment">%                         (sigX(3)/X(3))^2+(sigX(4)/X(4))^2);</span>
-0211 <span class="comment">% FsigX2 = @(X,Fx,Fx1,sig_x1,Fx2,sig_x2) Fx(X)*sqrt((sig_x1/Fx1(X))^2+ ...</span>
-0212 <span class="comment">%                         (sig_x2/Fx2)^2);</span>
-0213 <span class="comment">% FlamX = @(X) X(1)./(X(2).*(4-2.*X(3)));            % lambda</span>
-0214 <span class="comment">% FdndtX = @(X) X(1)./(X(2).*(4-2.*X(3))).*X(4);      % dn/dt</span>
-0215 <span class="comment">% Fsym = tausym./(phisym.*(4-2.*bsym)).*Qsym;       % dn/dt</span>
-0216 <span class="comment">% % Flam = tausym./(phisym.*(4-2.*bsym));             % lambda for f5</span>
-0217 <span class="comment">% Xsym = [tausym phisym bsym Qsym];</span>
-0218 <span class="comment">% X = [tauhat;phihat;bhat;dbfdt]; %[tau,phi,b];</span>
-0219 <span class="comment">% sigX = [sig_tau;sig_phi;sig_b;sig_dbfdt];</span>
-0220 <span class="comment">%</span>
-0221 <span class="comment">% % setup jacobian and covariance matrices (need the sample populations)</span>
-0222 <span class="comment">% dqdtv = dbfdt.*ones(size(tau)); % dq/dt vector</span>
-0223 <span class="comment">% J = [dndt./tauhat, dndt./phihat, dndt./Nhat, dndt./dbfdt]; % jacobian</span>
-0224 <span class="comment">% u = [sig_tau, sig_phi, sig_Np1, sig_dbfdt]; % note: sig_Np1 not sig_b</span>
-0225 <span class="comment">% V = corr([tau,phi,Np1,dqdtv]); % covariance matrix</span>
-0226 <span class="comment">% corrX = corr([tau,phi,Np1,dqdtv]);</span>
-0227 <span class="comment">%</span>
-0228 <span class="comment">% % -----------------------------------------------------------------------------</span>
-0229 <span class="comment">%</span>
-0230 <span class="comment">% casenames = {'inline w/o correlation','PropError w/o correlation', ...</span>
-0231 <span class="comment">%    'propUncertSym w/o correlation','worstcase w/o correlation',...</span>
-0232 <span class="comment">%    'inline w/correlation','propUncertSym w/ correlation', ...</span>
-0233 <span class="comment">%    'propUncertCD w/ correlation','worstcase w/correlation',...</span>
-0234 <span class="comment">%    'error propagation'};</span>
+0044    <span class="comment">%  Note: globalfit with bootfit false returns tau_L = tau_H = tau and</span>
+0045    <span class="comment">%  b_L = b_H = b, so the tau and b terms are zero and the combined</span>
+0046    <span class="comment">%  uncertainty holds only the phi and regression terms.</span>
+0047    <span class="comment">%</span>
+0048    <span class="comment">% See also: aquifertrend, aquiferthickness</span>
+0049    <span class="comment">%</span>
+0050    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0051 
+0052    <span class="comment">% if called with no input, open this file</span>
+0053    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0054 
+0055    <span class="comment">% parse inputs</span>
+0056    alpha = 0.05;
+0057    testflag = false;
+0058    <span class="keyword">if</span> nargin == 7
+0059       alpha = varargin{1};
+0060    <span class="keyword">elseif</span> nargin == 8
+0061       alpha = varargin{1};
+0062       testflag = varargin{2};
+0063    <span class="keyword">end</span>
+0064 
+0065    <span class="comment">% alpha sets the coverage factor applied to the combined standard</span>
+0066    <span class="comment">% uncertainty at the end of the function.</span>
+0067    <span class="keyword">if</span> ~isnumeric(alpha) || ~isscalar(alpha) || alpha &lt;= 0 || alpha &gt;= 1
+0068       error(<span class="string">'baseflow:dndtuncertainty:invalidAlpha'</span>, <span class="keyword">...</span>
+0069          <span class="string">'alpha must be a scalar in the interval (0, 1)'</span>)
+0070    <span class="keyword">end</span>
+0071    coveragefactor = norminv(1 - alpha/2);
+0072 
+0073    <span class="comment">% Convert time in days to years. Qb holds one value per calendar year,</span>
+0074    <span class="comment">% so T reduces to the years it spans. A calendar with leap days does</span>
+0075    <span class="comment">% not split into 365-day rows, so take the years directly.</span>
+0076    <span class="keyword">if</span> isdatetime(T)
+0077       T = todatenum(T);
+0078    <span class="keyword">end</span>
+0079    T = transpose(year(T(1)):year(T(end)));
+0080 
+0081    <span class="keyword">if</span> numel(T) ~= numel(Qb)
+0082       error(<span class="string">'size T must match size Qb'</span>)
+0083    <span class="keyword">end</span>
+0084 
+0085    <span class="comment">% Define the sensitivity coefficient and dn/dt trend functions</span>
+0086    Flam = @(tau, phi, b) tau./(phi.*(4-2.*b));
+0087    Fdndt = @(tau,phi,b,dqdt) tau./(phi.*(4-2.*b)).*dqdt;
+0088 
+0089    <span class="comment">% Regress baseflow in units cm/day/year to get uncertainty on dq/dt</span>
+0090    Qb = Qb./365.25;                          <span class="comment">% cm/yr -&gt; cm/day</span>
+0091 
+0092    <span class="comment">% fitlm returns a LinearModel in MATLAB and in the Octave statistics</span>
+0093    <span class="comment">% package, so one call serves both. Row 2 is the slope. Keep the</span>
+0094    <span class="comment">% standard error, because every term of the combined uncertainty below</span>
+0095    <span class="comment">% is one sigma.</span>
+0096    mdl = fitlm(T, Qb);
+0097       dbfdt = mdl.Coefficients.Estimate(2);  <span class="comment">% cm/day/year</span>
+0098    sig_dbfdt = mdl.Coefficients.SE(2);       <span class="comment">% standard error</span>
+0099 
+0100    <span class="comment">% In octave, the full Jacobian/Covariance Matrix method is not supported, but</span>
+0101    <span class="comment">% the uncertainty is dominated by the linear regression, so return that.</span>
+0102    <span class="keyword">if</span> isoctave
+0103       sig_dndt = coveragefactor * sig_dbfdt;
+0104       sig_lamda = nan;
+0105       <span class="keyword">return</span>
+0106    <span class="keyword">end</span>
+0107 
+0108    <span class="comment">% Parameters</span>
+0109    A = opts.drainagearea;     <span class="comment">% basin area [m2]</span>
+0110    D = opts.aquiferdepth;     <span class="comment">% reference active layer thickness [m]</span>
+0111    L = opts.streamlength;     <span class="comment">% effective stream network length [m]</span>
+0112 
+0113    <span class="comment">% Fit drainable porosity</span>
+0114    bhat = GlobalFit.b;
+0115    PhiFit = baseflow.phifitensemble(Results, Fits, A, D, L, bhat, <span class="keyword">...</span>
+0116       opts.lateqtls, opts.earlyqtls, false);
+0117 
+0118    <span class="comment">% The sample populations of tau, phi, and Nstar</span>
+0119    [~,~,~,~,G] = baseflow.eventtau(Results, Fits, Fits, <span class="keyword">...</span>
+0120       <span class="string">'usefits'</span>, true, <span class="string">'aggfunc'</span>, <span class="string">'max'</span>);
+0121 
+0122    b = [Results.b];
+0123    tau = G.tau; <span class="comment">% [K.tauH]';</span>
+0124    Np1 = 1./(4-2.*b);
+0125    phi1 = PhiFit.phidist(:, 1);
+0126    phi2 = PhiFit.phidist(:, 2);
+0127    phi = (phi1 + phi2) ./ 2;
+0128 
+0129    <span class="comment">% correlation between b and phi, using the two phi dist's b = 1 and b = 3/2:</span>
+0130    rho_phi12 = nancorr(phi1, phi2);
+0131    rho_phib1 = nancorr(Np1, phi1);
+0132    rho_phib2 = nancorr(Np1, phi2);
+0133 
+0134    <span class="keyword">if</span> isoctave
+0135       cov_phib1 = cov(Np1, phi1);
+0136       cov_phib2 = cov(Np1, phi2);
+0137    <span class="keyword">else</span>
+0138       cov_phib1 = cov(Np1, phi1, <span class="string">'omitrows'</span>);
+0139       cov_phib2 = cov(Np1, phi2, <span class="string">'omitrows'</span>);
+0140    <span class="keyword">end</span>
+0141 
+0142    <span class="comment">% define the uncertainties (standard errors)</span>
+0143    <span class="comment">% if we averaged phi1 and phi2, then the combined uncertainty would be:</span>
+0144    sig_phi1 = PhiFit.se(1);
+0145    sig_phi2 = PhiFit.se(2);
+0146    sig_phi = rho_phi12*sig_phi1*sig_phi2;
+0147    sig_phi = sqrt((0.5 * sig_phi1)^2 + (0.5 * sig_phi2)^2 + 2*0.5*0.5*sig_phi);
+0148    sig_tau = mean([GlobalFit.tau_H - GlobalFit.tau, GlobalFit.tau - GlobalFit.tau_L]);
+0149    sig_b = mean([GlobalFit.b_H - GlobalFit.b, GlobalFit.b - GlobalFit.b_L]);
+0150    <span class="comment">% Nstar = 1/(4-2b), so its uncertainty is dNstar/db times sig_b.</span>
+0151    sig_Np1 = nstaruncertainty(GlobalFit.b, sig_b);
+0152    <span class="comment">% the 0.5 on sig_phi1/2 is from the averaging procedure which divides by 2</span>
+0153 
+0154    <span class="comment">% Mean values of parameters</span>
+0155    tauhat = GlobalFit.tau;                      <span class="comment">% days</span>
+0156    phihat = PhiFit.mu(4);                       <span class="comment">% -</span>
+0157    bhat = GlobalFit.b;                          <span class="comment">% -</span>
+0158    Nhat = 1 / (4 - 2*bhat);                     <span class="comment">% -</span>
+0159 
+0160    <span class="comment">% Compute the sensitivity coefficient and dn/dt</span>
+0161    lambda = Flam(tauhat, phihat, bhat);
+0162    dndt = Fdndt(tauhat, phihat, bhat, dbfdt);   <span class="comment">% cm/yr</span>
+0163 
+0164    <span class="comment">% Compute the jacobian</span>
+0165    J = [dndt./tauhat, -dndt./phihat, dndt./Nhat, dndt./dbfdt];
+0166 
+0167    <span class="comment">% Construct the covariance matrix and compute the combined uncertainty.</span>
+0168    <span class="comment">% dq/dt comes from the annual regression, so it has no event-scale</span>
+0169    <span class="comment">% sample to correlate against the three event variables. A constant</span>
+0170    <span class="comment">% column makes corr return nan, so build the correlation matrix from</span>
+0171    <span class="comment">% the event variables and hold dq/dt uncorrelated with them.</span>
+0172    <span class="comment">%</span>
+0173    <span class="comment">% phifitensemble sets out-of-range phi to nan, so correlate the event</span>
+0174    <span class="comment">% variables over the events where all three exist. Dropping whole rows</span>
+0175    <span class="comment">% keeps the correlation matrix valid for the quadratic forms below.</span>
+0176    events = [tau, phi, Np1];
+0177    R = corr(events(all(~isnan(events), 2), :));
+0178    u = [sig_tau, sig_phi, sig_Np1, sig_dbfdt];
+0179    C = eye(4);
+0180    C(1:3, 1:3) = R;
+0181    V = C .* u .* u';
+0182    sig_dndt = coveragefactor * sqrt(J * V * J');
+0183    <span class="comment">% w/o correlated errors: sqrt(sum((J .* u).^2))</span>
+0184 
+0185    <span class="comment">% Compute the uncertainty on lambda (repeat above steps)</span>
+0186    J = [lambda./tauhat, -lambda./phihat, lambda./Nhat];
+0187    u = [sig_tau, sig_phi, sig_Np1];
+0188    V = R .* u .* u';
+0189    sig_lamda = coveragefactor * sqrt(J * V * J');
+0190    <span class="comment">% w/o correlated errors: sqrt(sum((J .* u).^2))</span>
+0191 
+0192    <span class="keyword">if</span> testflag == true
+0193       warning(<span class="string">'method comparison not currently supported'</span>)
+0194    <span class="keyword">end</span>
+0195 <span class="keyword">end</span>
+0196 
+0197 <span class="comment">%% Methods comparison</span>
+0198 <span class="comment">% % Define symbols, setup matrices, etc.</span>
+0199 <span class="comment">%</span>
+0200 <span class="comment">% % FsigX is the standard uncertainty formula for four variables: tau, phi, b,</span>
+0201 <span class="comment">% % dq/dt.</span>
+0202 <span class="comment">%</span>
+0203 <span class="comment">% % FsigX2 is for two variables: lambda and dq/dt, so it uses Flambda(X) within</span>
+0204 <span class="comment">% % the function to compute the value of lambda, but accepts the scalar values</span>
+0205 <span class="comment">% % for dq/dt (Fx2) and sig_dq/dt (sig_x2). It would be clearer to replace this</span>
+0206 <span class="comment">% % with the scalar valued version, because this is just used to combine the</span>
+0207 <span class="comment">% % lambda uncertainty from worstcase with the linear regression dq/dt</span>
+0208 <span class="comment">% % uncertainty.</span>
+0209 <span class="comment">%</span>
+0210 <span class="comment">% % Methods that use Fdndt require the same format that is used in the main</span>
+0211 <span class="comment">% % function, so it is not redefined here</span>
+0212 <span class="comment">%</span>
+0213 <span class="comment">% sympref('FloatingPointOutput',true);</span>
+0214 <span class="comment">% syms tausym phisym bsym Qsym</span>
+0215 <span class="comment">%</span>
+0216 <span class="comment">% % define vector valued functions</span>
+0217 <span class="comment">% FsigX = @(X,Fx,sigX) Fx*sqrt((sigX(1)/X(1))^2+(sigX(2)/X(2))^2+ ...</span>
+0218 <span class="comment">%                         (sigX(3)/X(3))^2+(sigX(4)/X(4))^2);</span>
+0219 <span class="comment">% FsigX2 = @(X,Fx,Fx1,sig_x1,Fx2,sig_x2) Fx(X)*sqrt((sig_x1/Fx1(X))^2+ ...</span>
+0220 <span class="comment">%                         (sig_x2/Fx2)^2);</span>
+0221 <span class="comment">% FlamX = @(X) X(1)./(X(2).*(4-2.*X(3)));            % lambda</span>
+0222 <span class="comment">% FdndtX = @(X) X(1)./(X(2).*(4-2.*X(3))).*X(4);      % dn/dt</span>
+0223 <span class="comment">% Fsym = tausym./(phisym.*(4-2.*bsym)).*Qsym;       % dn/dt</span>
+0224 <span class="comment">% % Flam = tausym./(phisym.*(4-2.*bsym));             % lambda for f5</span>
+0225 <span class="comment">% Xsym = [tausym phisym bsym Qsym];</span>
+0226 <span class="comment">% X = [tauhat;phihat;bhat;dbfdt]; %[tau,phi,b];</span>
+0227 <span class="comment">% sigX = [sig_tau;sig_phi;sig_b;sig_dbfdt];</span>
+0228 <span class="comment">%</span>
+0229 <span class="comment">% % setup jacobian and covariance matrices (need the sample populations)</span>
+0230 <span class="comment">% dqdtv = dbfdt.*ones(size(tau)); % dq/dt vector</span>
+0231 <span class="comment">% J = [dndt./tauhat, dndt./phihat, dndt./Nhat, dndt./dbfdt]; % jacobian</span>
+0232 <span class="comment">% u = [sig_tau, sig_phi, sig_Np1, sig_dbfdt]; % note: sig_Np1 not sig_b</span>
+0233 <span class="comment">% V = corr([tau,phi,Np1,dqdtv]); % covariance matrix</span>
+0234 <span class="comment">% corrX = corr([tau,phi,Np1,dqdtv]);</span>
 0235 <span class="comment">%</span>
-0236 <span class="comment">% % WITHOUT CORRELATION</span>
-0237 <span class="comment">% % -------------------</span>
-0238 <span class="comment">%</span>
-0239 <span class="comment">% % METHOD 1: simple, uncorrelated errors (ends up close to PropError below)</span>
-0240 <span class="comment">% val(1) = dndt;</span>
-0241 <span class="comment">% sig(1) = FsigX(X,dndt,sigX); % also: sig = sqrt(sum((J.*u).^2))</span>
-0242 <span class="comment">%</span>
-0243 <span class="comment">% % METHOD 2: PropError without correlated errors</span>
-0244 <span class="comment">% out = PropError(Fsym,Xsym,X',sigX');</span>
-0245 <span class="comment">% val(2) = out{1,1};</span>
-0246 <span class="comment">% sig(2) = out{1,3};</span>
-0247 <span class="comment">% % out = PropError(Flam,Xsym(1:3),X(1:3)',sigX(1:3)'); % lambda</span>
-0248 <span class="comment">%</span>
-0249 <span class="comment">% % METHOD 3: propUncert without correlated errors</span>
-0250 <span class="comment">% [sig(3),val(3)] = propUncertSym(Fsym,Xsym,X',sigX');</span>
-0251 <span class="comment">%</span>
-0252 <span class="comment">% % METHOD 4: 'worstcase' without correlated errors</span>
-0253 <span class="comment">% [~,~,L,M,H] = worstcase(FlamX,X(1:3),sigX(1:3)); % lambda L/M/H</span>
-0254 <span class="comment">% sig_lam = mean([H-M,M-L]);                     % lambda absolute uncertainty</span>
-0255 <span class="comment">% val(4) = M*dbfdt;</span>
-0256 <span class="comment">% sig(4) = FsigX2(X,FdndtX,FlamX,sig_lam,dbfdt,sig_dbfdt);</span>
-0257 <span class="comment">%</span>
-0258 <span class="comment">% % for reference, compare what worstcase and sig_lam above do to expicit</span>
-0259 <span class="comment">% % versions:</span>
-0260 <span class="comment">% % [sig(8)  dndt*sqrt((sig_lam/Flambda(X))^2 + (sig_dbfdt/dbfdt)^2)]</span>
-0261 <span class="comment">% % [sig_lam lambda*sqrt((sig_lam/Flambda(X))^2)]</span>
-0262 <span class="comment">%</span>
-0263 <span class="comment">% % if the first two outputs of worstcase are returned, this shows what they</span>
-0264 <span class="comment">% % mean:</span>
-0265 <span class="comment">% % [v1,v2,L,M,H] = worstcase(FlamX,X(1:3),sigX(1:3)); % lambda L/M/H</span>
-0266 <span class="comment">% % [Flambda(v1) L]</span>
-0267 <span class="comment">% % [Flambda(v2) H]</span>
-0268 <span class="comment">%</span>
-0269 <span class="comment">% % WITH CORRELATION</span>
-0270 <span class="comment">% % ----------------</span>
-0271 <span class="comment">%</span>
-0272 <span class="comment">% % METHOD 5: correlated errors (need the jacobian)</span>
-0273 <span class="comment">% val(5) = dndt;</span>
-0274 <span class="comment">% sig(5) = sqrt(J*(V.*u.*u')*J');</span>
-0275 <span class="comment">%</span>
-0276 <span class="comment">% % METHOD 6: propUncert with correlated errors</span>
-0277 <span class="comment">% [sig(6),val(6)] = propUncertSym(Fsym,Xsym,X',sigX',corrX);</span>
-0278 <span class="comment">%</span>
-0279 <span class="comment">% % METHOD 7: propUncertCD with correlated errors (central difference approx)</span>
-0280 <span class="comment">% [sig(7),val(7)] = propUncertCD(FdndtX,X,sigX,corrX);</span>
-0281 <span class="comment">%</span>
-0282 <span class="comment">% % METHOD 8: 'worstcase' with correlated errors</span>
-0283 <span class="comment">% [~,~,L,M,H] = worstcase(FdndtX,X,sigX);</span>
-0284 <span class="comment">% val(8) = M;</span>
-0285 <span class="comment">% sig(8) = mean([H-M,M-L]);      % absolute uncertainty</span>
+0236 <span class="comment">% % -----------------------------------------------------------------------------</span>
+0237 <span class="comment">%</span>
+0238 <span class="comment">% casenames = {'inline w/o correlation','PropError w/o correlation', ...</span>
+0239 <span class="comment">%    'propUncertSym w/o correlation','worstcase w/o correlation',...</span>
+0240 <span class="comment">%    'inline w/correlation','propUncertSym w/ correlation', ...</span>
+0241 <span class="comment">%    'propUncertCD w/ correlation','worstcase w/correlation',...</span>
+0242 <span class="comment">%    'error propagation'};</span>
+0243 <span class="comment">%</span>
+0244 <span class="comment">% % WITHOUT CORRELATION</span>
+0245 <span class="comment">% % -------------------</span>
+0246 <span class="comment">%</span>
+0247 <span class="comment">% % METHOD 1: simple, uncorrelated errors (ends up close to PropError below)</span>
+0248 <span class="comment">% val(1) = dndt;</span>
+0249 <span class="comment">% sig(1) = FsigX(X,dndt,sigX); % also: sig = sqrt(sum((J.*u).^2))</span>
+0250 <span class="comment">%</span>
+0251 <span class="comment">% % METHOD 2: PropError without correlated errors</span>
+0252 <span class="comment">% out = PropError(Fsym,Xsym,X',sigX');</span>
+0253 <span class="comment">% val(2) = out{1,1};</span>
+0254 <span class="comment">% sig(2) = out{1,3};</span>
+0255 <span class="comment">% % out = PropError(Flam,Xsym(1:3),X(1:3)',sigX(1:3)'); % lambda</span>
+0256 <span class="comment">%</span>
+0257 <span class="comment">% % METHOD 3: propUncert without correlated errors</span>
+0258 <span class="comment">% [sig(3),val(3)] = propUncertSym(Fsym,Xsym,X',sigX');</span>
+0259 <span class="comment">%</span>
+0260 <span class="comment">% % METHOD 4: 'worstcase' without correlated errors</span>
+0261 <span class="comment">% [~,~,L,M,H] = worstcase(FlamX,X(1:3),sigX(1:3)); % lambda L/M/H</span>
+0262 <span class="comment">% sig_lam = mean([H-M,M-L]);                     % lambda absolute uncertainty</span>
+0263 <span class="comment">% val(4) = M*dbfdt;</span>
+0264 <span class="comment">% sig(4) = FsigX2(X,FdndtX,FlamX,sig_lam,dbfdt,sig_dbfdt);</span>
+0265 <span class="comment">%</span>
+0266 <span class="comment">% % for reference, compare what worstcase and sig_lam above do to expicit</span>
+0267 <span class="comment">% % versions:</span>
+0268 <span class="comment">% % [sig(8)  dndt*sqrt((sig_lam/Flambda(X))^2 + (sig_dbfdt/dbfdt)^2)]</span>
+0269 <span class="comment">% % [sig_lam lambda*sqrt((sig_lam/Flambda(X))^2)]</span>
+0270 <span class="comment">%</span>
+0271 <span class="comment">% % if the first two outputs of worstcase are returned, this shows what they</span>
+0272 <span class="comment">% % mean:</span>
+0273 <span class="comment">% % [v1,v2,L,M,H] = worstcase(FlamX,X(1:3),sigX(1:3)); % lambda L/M/H</span>
+0274 <span class="comment">% % [Flambda(v1) L]</span>
+0275 <span class="comment">% % [Flambda(v2) H]</span>
+0276 <span class="comment">%</span>
+0277 <span class="comment">% % WITH CORRELATION</span>
+0278 <span class="comment">% % ----------------</span>
+0279 <span class="comment">%</span>
+0280 <span class="comment">% % METHOD 5: correlated errors (need the jacobian)</span>
+0281 <span class="comment">% val(5) = dndt;</span>
+0282 <span class="comment">% sig(5) = sqrt(J*(V.*u.*u')*J');</span>
+0283 <span class="comment">%</span>
+0284 <span class="comment">% % METHOD 6: propUncert with correlated errors</span>
+0285 <span class="comment">% [sig(6),val(6)] = propUncertSym(Fsym,Xsym,X',sigX',corrX);</span>
 0286 <span class="comment">%</span>
-0287 <span class="comment">%</span>
-0288 <span class="comment">% % METHOD 9: error_propagation (documentation isn't clear and code style is</span>
-0289 <span class="comment">% % unfamiliar so i am not certain if correlation is included)</span>
-0290 <span class="comment">% [val(9),sig(9)] = error_propagation(Fdndt,tauhat,phihat,bhat,dbfdt,sig_tau,...</span>
-0291 <span class="comment">%    sig_phi,sig_b,sig_dbfdt);</span>
-0292 <span class="comment">%</span>
-0293 <span class="comment">%</span>
-0294 <span class="comment">% % SEE THE RESULTS</span>
-0295 <span class="comment">% %----------------------</span>
-0296 <span class="comment">%</span>
-0297 <span class="comment">% % print the value returned by the main function:</span>
-0298 <span class="comment">% fprintf(['\nbaseflow:\nF(x) = %.2f ' char(177) ' %.3f (' num2str(1-alpha) ...</span>
-0299 <span class="comment">%    '%% CI) \n'],dndt,sig_dndt);</span>
+0287 <span class="comment">% % METHOD 7: propUncertCD with correlated errors (central difference approx)</span>
+0288 <span class="comment">% [sig(7),val(7)] = propUncertCD(FdndtX,X,sigX,corrX);</span>
+0289 <span class="comment">%</span>
+0290 <span class="comment">% % METHOD 8: 'worstcase' with correlated errors</span>
+0291 <span class="comment">% [~,~,L,M,H] = worstcase(FdndtX,X,sigX);</span>
+0292 <span class="comment">% val(8) = M;</span>
+0293 <span class="comment">% sig(8) = mean([H-M,M-L]);      % absolute uncertainty</span>
+0294 <span class="comment">%</span>
+0295 <span class="comment">%</span>
+0296 <span class="comment">% % METHOD 9: error_propagation (documentation isn't clear and code style is</span>
+0297 <span class="comment">% % unfamiliar so i am not certain if correlation is included)</span>
+0298 <span class="comment">% [val(9),sig(9)] = error_propagation(Fdndt,tauhat,phihat,bhat,dbfdt,sig_tau,...</span>
+0299 <span class="comment">%    sig_phi,sig_b,sig_dbfdt);</span>
 0300 <span class="comment">%</span>
-0301 <span class="comment">% for n = 1:numel(casenames)</span>
-0302 <span class="comment">%</span>
-0303 <span class="comment">%    fprintf(['\n' casenames{n} ':\n F(x) = %.2f ' char(177) ' %.3f (' ...</span>
-0304 <span class="comment">%       num2str(1-alpha) '%% CI) \n'],val(n),sig(n));</span>
-0305 <span class="comment">% end</span>
-0306 <span class="comment">%</span>
-0307 <span class="comment">% end</span>
+0301 <span class="comment">%</span>
+0302 <span class="comment">% % SEE THE RESULTS</span>
+0303 <span class="comment">% %----------------------</span>
+0304 <span class="comment">%</span>
+0305 <span class="comment">% % print the value returned by the main function:</span>
+0306 <span class="comment">% fprintf(['\nbaseflow:\nF(x) = %.2f ' char(177) ' %.3f (' num2str(1-alpha) ...</span>
+0307 <span class="comment">%    '%% CI) \n'],dndt,sig_dndt);</span>
 0308 <span class="comment">%</span>
-0309 <span class="comment">% % % this is the correlated errors case for lambda</span>
-0310 <span class="comment">% % J = [dndt./tauhat, dndt./phihat, dndt./Nhat ];</span>
-0311 <span class="comment">% % u = [sig_tau, sig_phi, sig_Np1];</span>
-0312 <span class="comment">% % V = corr([tau,phi,Np1]);</span>
-0313 <span class="comment">% % sig_lam = sqrt(J*(V.*u.*u')*J');         % this is the stdv of lambda</span>
-0314 <span class="comment">% % sigf2 = dndt*sqrt((sig_lam/lambda)^2 + (sig_dbfdt/dbfdt)^2) % 0.62 cm/yr</span>
-0315 <span class="comment">%</span>
-0316 <span class="comment">% % this was after propUncertSym, in case the varnanmes matter. at this point i</span>
-0317 <span class="comment">% % think i noticed the correlation doesn't change the uncertainty by much so i</span>
-0318 <span class="comment">% % probably jus twanted to also show it doesn't change the uncertainty on</span>
-0319 <span class="comment">% % lambda by much</span>
-0320 <span class="comment">% % % this shows that the correlation also doesn't change sig_lambda</span>
-0321 <span class="comment">% % Fsym = tausym./(phisym.*(4-2.*bsym));</span>
-0322 <span class="comment">% % Xsym = [tausym phisym bsym];</span>
-0323 <span class="comment">% % X = [tauhat phihat bhat]; %[tau,phi,b];</span>
-0324 <span class="comment">% % sigX = [sig_tau sig_phi sig_b];</span>
-0325 <span class="comment">% % corrX = corr([tau,phi,Np1]);</span>
-0326 <span class="comment">% % % sig_lambda = PropError(Fsym,Xsym,X,sigX)</span>
-0327 <span class="comment">% % % sig_lambda = propUncertSym(Fsym,Xsym,X,sigX)</span>
-0328 <span class="comment">% % % sig_lambda = propUncertSym(Fsym,Xsym,X,sigX,corrX)</span></pre></div>
+0309 <span class="comment">% for n = 1:numel(casenames)</span>
+0310 <span class="comment">%</span>
+0311 <span class="comment">%    fprintf(['\n' casenames{n} ':\n F(x) = %.2f ' char(177) ' %.3f (' ...</span>
+0312 <span class="comment">%       num2str(1-alpha) '%% CI) \n'],val(n),sig(n));</span>
+0313 <span class="comment">% end</span>
+0314 <span class="comment">%</span>
+0315 <span class="comment">% end</span>
+0316 <span class="comment">%</span>
+0317 <span class="comment">% % % this is the correlated errors case for lambda</span>
+0318 <span class="comment">% % J = [dndt./tauhat, dndt./phihat, dndt./Nhat ];</span>
+0319 <span class="comment">% % u = [sig_tau, sig_phi, sig_Np1];</span>
+0320 <span class="comment">% % V = corr([tau,phi,Np1]);</span>
+0321 <span class="comment">% % sig_lam = sqrt(J*(V.*u.*u')*J');         % this is the stdv of lambda</span>
+0322 <span class="comment">% % sigf2 = dndt*sqrt((sig_lam/lambda)^2 + (sig_dbfdt/dbfdt)^2) % 0.62 cm/yr</span>
+0323 <span class="comment">%</span>
+0324 <span class="comment">% % this was after propUncertSym, in case the varnanmes matter. at this point i</span>
+0325 <span class="comment">% % think i noticed the correlation doesn't change the uncertainty by much so i</span>
+0326 <span class="comment">% % probably jus twanted to also show it doesn't change the uncertainty on</span>
+0327 <span class="comment">% % lambda by much</span>
+0328 <span class="comment">% % % this shows that the correlation also doesn't change sig_lambda</span>
+0329 <span class="comment">% % Fsym = tausym./(phisym.*(4-2.*bsym));</span>
+0330 <span class="comment">% % Xsym = [tausym phisym bsym];</span>
+0331 <span class="comment">% % X = [tauhat phihat bhat]; %[tau,phi,b];</span>
+0332 <span class="comment">% % sigX = [sig_tau sig_phi sig_b];</span>
+0333 <span class="comment">% % corrX = corr([tau,phi,Np1]);</span>
+0334 <span class="comment">% % % sig_lambda = PropError(Fsym,Xsym,X,sigX)</span>
+0335 <span class="comment">% % % sig_lambda = propUncertSym(Fsym,Xsym,X,sigX)</span>
+0336 <span class="comment">% % % sig_lambda = propUncertSym(Fsym,Xsym,X,sigX,corrX)</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/expectedQ.html b/toolbox/docs/html/m2html/+baseflow/expectedQ.html
index bee4a46..85e1280 100644
--- a/toolbox/docs/html/m2html/+baseflow/expectedQ.html
+++ b/toolbox/docs/html/m2html/+baseflow/expectedQ.html
@@ -31,9 +31,16 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
  Syntax
 
-  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau);
-  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau,'pctls',Q) returns the percentiles
-              of Qexp/Q0 relative to the input Q
+  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau,q,dqdt,tau0);
+  [Qexp,Q0,pQexp,pQ0] = baseflow.EXPECTEDQ(_,'qtls',Q) returns the
+              percentiles of Qexp/Q0 relative to the input Q
+
+ Description
+
+  Qexp is the flow at the mean tau, (a*tau)^(1/(1-b)), and
+  Q0 = Qexp*(3-b)/(2-b). The mean tau diverges beyond the tau pole at
+  alpha = 2, where plfitb returns Inf. A tau that is not finite gives
+  NaN for every output.
 
  See also: <a href="aquifertrend.html" class="code" title="function [D,dDdt,dDadt,C] = aquifertrend(tau,phi,N,Qb,dQbdt)">aquifertrend</a>, <a href="baseflowtrend.html" class="code" title="function [Qb,dQbdt,Qa,dQadt,hb,ha] = baseflowtrend(t,Q,A,varargin)">baseflowtrend</a>
 
@@ -68,185 +75,195 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0003    <span class="comment">%</span>
 0004    <span class="comment">% Syntax</span>
 0005    <span class="comment">%</span>
-0006    <span class="comment">%  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau);</span>
-0007    <span class="comment">%  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau,'pctls',Q) returns the percentiles</span>
-0008    <span class="comment">%              of Qexp/Q0 relative to the input Q</span>
+0006    <span class="comment">%  [Qexp,Q0] = baseflow.EXPECTEDQ(a,b,tau,q,dqdt,tau0);</span>
+0007    <span class="comment">%  [Qexp,Q0,pQexp,pQ0] = baseflow.EXPECTEDQ(_,'qtls',Q) returns the</span>
+0008    <span class="comment">%              percentiles of Qexp/Q0 relative to the input Q</span>
 0009    <span class="comment">%</span>
-0010    <span class="comment">% See also: aquifertrend, baseflowtrend</span>
+0010    <span class="comment">% Description</span>
 0011    <span class="comment">%</span>
-0012    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0013 
-0014    <span class="comment">% if called with no input, open this file</span>
-0015    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0016 
-0017    <span class="comment">% PARSE INPUTS</span>
-0018    [a, b, tau, q, dqdt, tau0, qtls, flow, mask, plotfit] = <a href="#_sub1" class="code" title="subfunction [a, b, tau, q, dqdt, tau0, qtls, flow, mask, plotfit] = parseinputs( ">parseinputs</a>( <span class="keyword">...</span>
-0019       a, b, tau, q, dqdt, tau0, varargin{:}); <span class="comment">%#ok&lt;*ASGLU&gt;</span>
+0012    <span class="comment">%  Qexp is the flow at the mean tau, (a*tau)^(1/(1-b)), and</span>
+0013    <span class="comment">%  Q0 = Qexp*(3-b)/(2-b). The mean tau diverges beyond the tau pole at</span>
+0014    <span class="comment">%  alpha = 2, where plfitb returns Inf. A tau that is not finite gives</span>
+0015    <span class="comment">%  NaN for every output.</span>
+0016    <span class="comment">%</span>
+0017    <span class="comment">% See also: aquifertrend, baseflowtrend</span>
+0018    <span class="comment">%</span>
+0019    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
 0020 
-0021    <span class="comment">% MAIN FUNCTION</span>
-0022    Qexp = (a*tau)^(1/(1-b));
-0023    Q0 = Qexp*(3-b)/(2-b);
-0024 
-0025    <span class="keyword">if</span> strcmp(plotfit, <span class="string">'plotfit'</span>)
-0026       plotfit = true;
-0027    <span class="keyword">else</span>
-0028       plotfit = false;
-0029    <span class="keyword">end</span>
-0030 
-0031    <span class="keyword">if</span> ~isempty(qtls)
-0032       u = <span class="string">'m$^3$ d$^{-1}$'</span>;
-0033       fdc = baseflow.fdcurve(flow(flow&gt;0), <span class="string">'refpoints'</span>, [Q0 Qexp], <span class="keyword">...</span>
-0034          <span class="string">'units'</span>, u, <span class="string">'plotfit'</span>, plotfit);
-0035       pQ0 = fdc.fref(1);
-0036       pQexp = fdc.fref(2);
+0021    <span class="comment">% if called with no input, open this file</span>
+0022    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0023 
+0024    <span class="comment">% PARSE INPUTS</span>
+0025    [a, b, tau, q, dqdt, tau0, qtls, flow, mask, plotfit] = <a href="#_sub1" class="code" title="subfunction [a, b, tau, q, dqdt, tau0, qtls, flow, mask, plotfit] = parseinputs( ">parseinputs</a>( <span class="keyword">...</span>
+0026       a, b, tau, q, dqdt, tau0, varargin{:}); <span class="comment">%#ok&lt;*ASGLU&gt;</span>
+0027 
+0028    <span class="comment">% MAIN FUNCTION</span>
+0029    <span class="comment">% a mean tau that does not exist has no flow, rather than the zero flow</span>
+0030    <span class="comment">% that an infinite tau gives</span>
+0031    tau(~isfinite(tau)) = nan;
+0032    Qexp = (a*tau)^(1/(1-b));
+0033    Q0 = Qexp*(3-b)/(2-b);
+0034 
+0035    <span class="keyword">if</span> strcmp(plotfit, <span class="string">'plotfit'</span>)
+0036       plotfit = true;
 0037    <span class="keyword">else</span>
-0038       pQexp = nan;
-0039       pQ0 = nan;
-0040    <span class="keyword">end</span>
-0041 <span class="keyword">end</span>
-0042 
-0043 <span class="comment">%% INPUT PARSER</span>
-0044 <a name="_sub1" href="#_subfunctions" class="code">function [a, b, tau, q, dqdt, tau0, qtls, flow, mask, plotfit] = parseinputs( </a><span class="keyword">...</span>
-0045       a, b, tau, q, dqdt, tau0, varargin)
-0046 
-0047    validopt = @(x) any(validatestring(x,{<span class="string">'qtls'</span>,<span class="string">'plotfit'</span>}));
-0048 
-0049    parser = inputParser;
-0050    parser.FunctionName = <span class="string">'baseflow.expectedQ'</span>;
-0051    parser.addRequired(<span class="string">'a'</span>, @isnumeric);
-0052    parser.addRequired(<span class="string">'b'</span>, @isnumeric);
-0053    parser.addRequired(<span class="string">'tau'</span>, @isnumeric);
-0054    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
-0055    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
-0056    parser.addRequired(<span class="string">'tau0'</span>, @isnumeric);
-0057    parser.addOptional(<span class="string">'qtls'</span>, <span class="string">''</span>, validopt);
-0058    parser.addOptional(<span class="string">'flow'</span>, nan, @isnumeric);
-0059    parser.addOptional(<span class="string">'plotfit'</span>, <span class="string">''</span>, validopt);
-0060    parser.addParameter(<span class="string">'mask'</span>, false, @islogical);
-0061 
-0062    parser.parse(a, b, tau, q, dqdt, tau0, varargin{:});
-0063 
-0064    a = parser.Results.a;
-0065    b = parser.Results.b;
-0066    q = parser.Results.q;
-0067    tau = parser.Results.tau;
-0068    dqdt = parser.Results.dqdt;
-0069    tau0 = parser.Results.tau0;
-0070    qtls = parser.Results.qtls;
-0071    flow = parser.Results.flow;
-0072    mask = parser.Results.mask;
-0073    plotfit = parser.Results.plotfit;
-0074 <span class="keyword">end</span>
-0075 
-0076 <span class="comment">%% error propagation notes</span>
-0077 <span class="comment">%</span>
-0078 <span class="comment">% % need Qexp/Q0 L/H</span>
-0079 <span class="comment">% Qexp     = GlobalFit.Qexp;</span>
-0080 <span class="comment">% sig_tau  = GlobalFit.BootFit.tau_sig;</span>
-0081 <span class="comment">% sig_b    = GlobalFit.BootFit.b_sig;</span>
-0082 <span class="comment">% sigQexp  = abs(Qexp/tauexp/(1-bhat)*sig_tau);</span>
-0083 <span class="comment">%</span>
-0084 <span class="comment">% % double check the Qexp uncertainty</span>
-0085 <span class="comment">% F        = @(X) (X(1)*X(2))^(1/(1-X(3))); % (a*tau)^(1/(1-b));</span>
-0086 <span class="comment">% X        = [ahat tauexp bhat];</span>
-0087 <span class="comment">% sigX     = [0 sig_tau sig_b];</span>
-0088 <span class="comment">% amat     = repmat(GlobalFit.a,numel(GlobalFit.reps.b),1);</span>
-0089 <span class="comment">% bmat     = GlobalFit.reps.b;</span>
-0090 <span class="comment">% taumat   = GlobalFit.reps.tau;</span>
-0091 <span class="comment">% Xmat     = [amat bmat taumat];</span>
-0092 <span class="comment">% corrX    = corr(Xmat);</span>
-0093 <span class="comment">% [sig,val] = propUncertCD(F,X,sigX,corrX);</span>
-0094 <span class="comment">%</span>
-0095 <span class="comment">%</span>
-0096 <span class="comment">% syms asym tausym bsym</span>
-0097 <span class="comment">% Fsym     = (asym*tausym).^(1/(1-bsym));</span>
-0098 <span class="comment">% Xsym     = [asym tausym bsym];</span>
-0099 <span class="comment">% [sig,val] = propUncertSym(Fsym,Xsym,X,sigX,corrX);</span>
-0100 
-0101 
-0102 <span class="comment">% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %</span>
-0103 <span class="comment">% %  below here various ways of computing Q0/Qexp</span>
-0104 
-0105 <span class="comment">% Note: if ahat is computed using the point cloud and</span>
-0106 <span class="comment">% Qexp = (ahat*tau)^(1/(1-bhat)), then</span>
-0107 <span class="comment">% Q0 = Qexp(3-bhat)/(2-bhat) != ahat*tau0^(1/(1-bhat))</span>
-0108 <span class="comment">% BUT, Q0 isn't used anywhere else in the algorithm</span>
-0109 <span class="comment">%</span>
-0110 <span class="comment">% [Q0 Qexp] % 9.1069e+05   3.6818e+05</span>
-0111 <span class="comment">%</span>
-0112 <span class="comment">% plot([Q0 Q0],ylim,'Color','r')</span>
-0113 <span class="comment">% plot([Qexp Qexp],ylim,'Color','r')</span>
-0114 <span class="comment">%</span>
-0115 <span class="comment">% % given the Q0 just computed, does tau0 = Q0^(1-b2)/a2 = tau0? Nope</span>
-0116 <span class="comment">% % Q0^(1-b2)/a2 % these first two are equal</span>
-0117 <span class="comment">% % Q0^(1-b1)/a1</span>
-0118 <span class="comment">% % Q0^(1-b1)/a2 %</span>
-0119 <span class="comment">% % Q0^(1-b2)/a1</span>
-0120 <span class="comment">% % Q0 = a2*tau0)</span>
+0038       plotfit = false;
+0039    <span class="keyword">end</span>
+0040 
+0041    <span class="keyword">if</span> ~isempty(qtls)
+0042       u = <span class="string">'m$^3$ d$^{-1}$'</span>;
+0043       fdc = baseflow.fdcurve(flow(flow&gt;0), <span class="string">'refpoints'</span>, [Q0 Qexp], <span class="keyword">...</span>
+0044          <span class="string">'units'</span>, u, <span class="string">'plotfit'</span>, plotfit);
+0045       pQ0 = fdc.fref(1);
+0046       pQexp = fdc.fref(2);
+0047    <span class="keyword">else</span>
+0048       pQexp = nan;
+0049       pQ0 = nan;
+0050    <span class="keyword">end</span>
+0051 <span class="keyword">end</span>
+0052 
+0053 <span class="comment">%% INPUT PARSER</span>
+0054 <a name="_sub1" href="#_subfunctions" class="code">function [a, b, tau, q, dqdt, tau0, qtls, flow, mask, plotfit] = parseinputs( </a><span class="keyword">...</span>
+0055       a, b, tau, q, dqdt, tau0, varargin)
+0056 
+0057    validopt = @(x) any(validatestring(x,{<span class="string">'qtls'</span>,<span class="string">'plotfit'</span>}));
+0058 
+0059    parser = inputParser;
+0060    parser.FunctionName = <span class="string">'baseflow.expectedQ'</span>;
+0061    parser.addRequired(<span class="string">'a'</span>, @isnumeric);
+0062    parser.addRequired(<span class="string">'b'</span>, @isnumeric);
+0063    parser.addRequired(<span class="string">'tau'</span>, @isnumeric);
+0064    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
+0065    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
+0066    parser.addRequired(<span class="string">'tau0'</span>, @isnumeric);
+0067    parser.addOptional(<span class="string">'qtls'</span>, <span class="string">''</span>, validopt);
+0068    parser.addOptional(<span class="string">'flow'</span>, nan, @isnumeric);
+0069    parser.addOptional(<span class="string">'plotfit'</span>, <span class="string">''</span>, validopt);
+0070    parser.addParameter(<span class="string">'mask'</span>, false, @islogical);
+0071 
+0072    parser.parse(a, b, tau, q, dqdt, tau0, varargin{:});
+0073 
+0074    a = parser.Results.a;
+0075    b = parser.Results.b;
+0076    q = parser.Results.q;
+0077    tau = parser.Results.tau;
+0078    dqdt = parser.Results.dqdt;
+0079    tau0 = parser.Results.tau0;
+0080    qtls = parser.Results.qtls;
+0081    flow = parser.Results.flow;
+0082    mask = parser.Results.mask;
+0083    plotfit = parser.Results.plotfit;
+0084 <span class="keyword">end</span>
+0085 
+0086 <span class="comment">%% error propagation notes</span>
+0087 <span class="comment">%</span>
+0088 <span class="comment">% % need Qexp/Q0 L/H</span>
+0089 <span class="comment">% Qexp     = GlobalFit.Qexp;</span>
+0090 <span class="comment">% sig_tau  = GlobalFit.BootFit.tau_sig;</span>
+0091 <span class="comment">% sig_b    = GlobalFit.BootFit.b_sig;</span>
+0092 <span class="comment">% sigQexp  = abs(Qexp/tauexp/(1-bhat)*sig_tau);</span>
+0093 <span class="comment">%</span>
+0094 <span class="comment">% % double check the Qexp uncertainty</span>
+0095 <span class="comment">% F        = @(X) (X(1)*X(2))^(1/(1-X(3))); % (a*tau)^(1/(1-b));</span>
+0096 <span class="comment">% X        = [ahat tauexp bhat];</span>
+0097 <span class="comment">% sigX     = [0 sig_tau sig_b];</span>
+0098 <span class="comment">% amat     = repmat(GlobalFit.a,numel(GlobalFit.reps.b),1);</span>
+0099 <span class="comment">% bmat     = GlobalFit.reps.b;</span>
+0100 <span class="comment">% taumat   = GlobalFit.reps.tau;</span>
+0101 <span class="comment">% Xmat     = [amat bmat taumat];</span>
+0102 <span class="comment">% corrX    = corr(Xmat);</span>
+0103 <span class="comment">% [sig,val] = propUncertCD(F,X,sigX,corrX);</span>
+0104 <span class="comment">%</span>
+0105 <span class="comment">%</span>
+0106 <span class="comment">% syms asym tausym bsym</span>
+0107 <span class="comment">% Fsym     = (asym*tausym).^(1/(1-bsym));</span>
+0108 <span class="comment">% Xsym     = [asym tausym bsym];</span>
+0109 <span class="comment">% [sig,val] = propUncertSym(Fsym,Xsym,X,sigX,corrX);</span>
+0110 
+0111 
+0112 <span class="comment">% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %</span>
+0113 <span class="comment">% %  below here various ways of computing Q0/Qexp</span>
+0114 
+0115 <span class="comment">% Note: if ahat is computed using the point cloud and</span>
+0116 <span class="comment">% Qexp = (ahat*tau)^(1/(1-bhat)), then</span>
+0117 <span class="comment">% Q0 = Qexp(3-bhat)/(2-bhat) != ahat*tau0^(1/(1-bhat))</span>
+0118 <span class="comment">% BUT, Q0 isn't used anywhere else in the algorithm</span>
+0119 <span class="comment">%</span>
+0120 <span class="comment">% [Q0 Qexp] % 9.1069e+05   3.6818e+05</span>
 0121 <span class="comment">%</span>
-0122 <span class="comment">% % if we believe that tau0 is the onset of recession at which time a=a1 and</span>
-0123 <span class="comment">% % b=b1 where b1=3 and a1 is the early-time fit, then tau0 = Q0^(1-b1)/a1:</span>
-0124 <span class="comment">% b1    = 3;</span>
-0125 <span class="comment">% b2    = b;</span>
-0126 <span class="comment">% a1    = baseflow.pointcloudintercept(q,dqdt,b1,'envelope','refqtls',[0.95 0.95]);</span>
-0127 <span class="comment">% Q0    = (a1*tau0)^(1/(1-b1));</span>
-0128 <span class="comment">% Qexp  = Q0*(2-b2)/(3-b2); % could it be: Q0*(b1-2)/(3-b2);</span>
-0129 <span class="comment">%</span>
-0130 <span class="comment">% [Q0 Qexp] % 1.3211e+07    5.341e+06</span>
-0131 <span class="comment">% plot([Q0 Q0],ylim,'Color','b')</span>
-0132 <span class="comment">% plot([Qexp Qexp],ylim,'Color','b')</span>
-0133 <span class="comment">%</span>
-0134 <span class="comment">% % if we equate the early-time and late-time fits to get Q0</span>
-0135 <span class="comment">% b1 = 3;</span>
-0136 <span class="comment">% b2 = b;</span>
-0137 <span class="comment">% a1 = baseflow.pointcloudintercept(q,dqdt,b1,'envelope','refqtls',[0.95 0.95]);</span>
-0138 <span class="comment">% a2 = baseflow.pointcloudintercept(q,dqdt,b2,'envelope','refqtls',[0.5 0.5],'mask',mask);</span>
-0139 <span class="comment">% Q0    = (a1/a2)^(1/(b2-b1));</span>
-0140 <span class="comment">% Qexp  = Q0*(2-b2)/(3-b2);</span>
-0141 <span class="comment">%</span>
-0142 <span class="comment">% [Q0 Qexp] % 1.3211e+07    5.341e+06</span>
-0143 <span class="comment">% plot([Q0 Q0],ylim,'Color','g')</span>
-0144 <span class="comment">% plot([Qexp Qexp],ylim,'Color','g')</span>
-0145 <span class="comment">%</span>
-0146 <span class="comment">% % NOTE: this is the way I did it originally but this is the case where it can</span>
-0147 <span class="comment">% % be shown to only be true for b=3 therefore the version above is correct.</span>
-0148 <span class="comment">% % if we believe that tau0 is the onset of recession at which time a=a2 and</span>
-0149 <span class="comment">% % b=b2 where a2 and b2 are the late-time fits, then tau0 = Q0^(1-b2)/a2:</span>
-0150 <span class="comment">% Q0    = (a2*tau0)^(1/(1-b2));</span>
-0151 <span class="comment">% Qexp  = Q0*(2-b2)/(3-b2);</span>
-0152 <span class="comment">%</span>
-0153 <span class="comment">% [Q0 Qexp] % 2.7105e+06   1.0958e+06</span>
-0154 <span class="comment">% plot([Q0 Q0],ylim,'Color','k')</span>
-0155 <span class="comment">% plot([Qexp Qexp],ylim,'Color','k')</span>
-0156 <span class="comment">%</span>
-0157 <span class="comment">% % need to find where I documented the issue with the original method, but</span>
-0158 <span class="comment">% % working through it again, if you equate</span>
-0159 <span class="comment">% % (1) Q0    = (ahat*tau0)^(1/(1-bhat))</span>
-0160 <span class="comment">% % (2) Qexp  = (ahat*tau)^(1/(1-bhat))</span>
-0161 <span class="comment">% % (3) Qexp  = Q0*(2-bhat)/(3-bhat)</span>
-0162 <span class="comment">% % plug rhs of (1) into Q0 on rhs of (3) and equate that to (2)</span>
-0163 <span class="comment">% % (4) (ahat*tau0)^(1/(1-bhat))*(2-bhat)/(3-bhat) = (ahat*tau)^(1/(1-bhat))</span>
-0164 <span class="comment">% % (5) (tau0/tau)^(1/(1-bhat)) = (3-bhat)/(2-bhat)</span>
-0165 <span class="comment">% % (6) (tau0/tau) = (3-bhat)/(2-bhat)^(1-bhat)</span>
-0166 <span class="comment">% % (7) tau0 = tau*(3-bhat)/(2-bhat)^(1-bhat)</span>
-0167 <span class="comment">%</span>
-0168 <span class="comment">% % (6) implies that tau0/tau should equal ((3-b)/(2-b))^(1-b) = 0.748 ... very</span>
-0169 <span class="comment">% % close to the ratio I found examining the troch solutions whcih i interpret</span>
-0170 <span class="comment">% % as a discontinuity at b-3. It also implies we can get tau0 this way:</span>
-0171 <span class="comment">% % tau0 = tau*((3-b)/(2-b))^(1-b)</span>
-0172 <span class="comment">% % but that doesn't match tau0 from the pareto fit, so</span>
-0173 <span class="comment">%</span>
-0174 <span class="comment">% % BUT ... tau = tau0*(2-b)/(3-2*b) is correct</span>
-0175 <span class="comment">%</span>
-0176 <span class="comment">% % how about this one ...</span>
-0177 <span class="comment">% % Q0 = Qexp*((3-2*b)/(2-b))^(1/(1-b))</span>
-0178 <span class="comment">%</span>
-0179 <span class="comment">% % which implies:</span>
-0180 <span class="comment">% % Q0/Qexp = ((3-2*b1)/(2-b1))^(1/(1-b1)) = 7.36 ...</span>
-0181 <span class="comment">% % Qexp/Q0 = ((2-b)/(3-2*b))^(1/(1-b)) = 0.136 ... and 1-0.136 = 0.864 which is</span>
-0182 <span class="comment">% % in the numerator of the late time q outflow equation 8 of troch 1993</span>
+0122 <span class="comment">% plot([Q0 Q0],ylim,'Color','r')</span>
+0123 <span class="comment">% plot([Qexp Qexp],ylim,'Color','r')</span>
+0124 <span class="comment">%</span>
+0125 <span class="comment">% % given the Q0 just computed, does tau0 = Q0^(1-b2)/a2 = tau0? Nope</span>
+0126 <span class="comment">% % Q0^(1-b2)/a2 % these first two are equal</span>
+0127 <span class="comment">% % Q0^(1-b1)/a1</span>
+0128 <span class="comment">% % Q0^(1-b1)/a2 %</span>
+0129 <span class="comment">% % Q0^(1-b2)/a1</span>
+0130 <span class="comment">% % Q0 = a2*tau0)</span>
+0131 <span class="comment">%</span>
+0132 <span class="comment">% % if we believe that tau0 is the onset of recession at which time a=a1 and</span>
+0133 <span class="comment">% % b=b1 where b1=3 and a1 is the early-time fit, then tau0 = Q0^(1-b1)/a1:</span>
+0134 <span class="comment">% b1    = 3;</span>
+0135 <span class="comment">% b2    = b;</span>
+0136 <span class="comment">% a1    = baseflow.pointcloudintercept(q,dqdt,b1,'envelope','refqtls',[0.95 0.95]);</span>
+0137 <span class="comment">% Q0    = (a1*tau0)^(1/(1-b1));</span>
+0138 <span class="comment">% Qexp  = Q0*(2-b2)/(3-b2); % could it be: Q0*(b1-2)/(3-b2);</span>
+0139 <span class="comment">%</span>
+0140 <span class="comment">% [Q0 Qexp] % 1.3211e+07    5.341e+06</span>
+0141 <span class="comment">% plot([Q0 Q0],ylim,'Color','b')</span>
+0142 <span class="comment">% plot([Qexp Qexp],ylim,'Color','b')</span>
+0143 <span class="comment">%</span>
+0144 <span class="comment">% % if we equate the early-time and late-time fits to get Q0</span>
+0145 <span class="comment">% b1 = 3;</span>
+0146 <span class="comment">% b2 = b;</span>
+0147 <span class="comment">% a1 = baseflow.pointcloudintercept(q,dqdt,b1,'envelope','refqtls',[0.95 0.95]);</span>
+0148 <span class="comment">% a2 = baseflow.pointcloudintercept(q,dqdt,b2,'envelope','refqtls',[0.5 0.5],'mask',mask);</span>
+0149 <span class="comment">% Q0    = (a1/a2)^(1/(b2-b1));</span>
+0150 <span class="comment">% Qexp  = Q0*(2-b2)/(3-b2);</span>
+0151 <span class="comment">%</span>
+0152 <span class="comment">% [Q0 Qexp] % 1.3211e+07    5.341e+06</span>
+0153 <span class="comment">% plot([Q0 Q0],ylim,'Color','g')</span>
+0154 <span class="comment">% plot([Qexp Qexp],ylim,'Color','g')</span>
+0155 <span class="comment">%</span>
+0156 <span class="comment">% % NOTE: this is the way I did it originally but this is the case where it can</span>
+0157 <span class="comment">% % be shown to only be true for b=3 therefore the version above is correct.</span>
+0158 <span class="comment">% % if we believe that tau0 is the onset of recession at which time a=a2 and</span>
+0159 <span class="comment">% % b=b2 where a2 and b2 are the late-time fits, then tau0 = Q0^(1-b2)/a2:</span>
+0160 <span class="comment">% Q0    = (a2*tau0)^(1/(1-b2));</span>
+0161 <span class="comment">% Qexp  = Q0*(2-b2)/(3-b2);</span>
+0162 <span class="comment">%</span>
+0163 <span class="comment">% [Q0 Qexp] % 2.7105e+06   1.0958e+06</span>
+0164 <span class="comment">% plot([Q0 Q0],ylim,'Color','k')</span>
+0165 <span class="comment">% plot([Qexp Qexp],ylim,'Color','k')</span>
+0166 <span class="comment">%</span>
+0167 <span class="comment">% % need to find where I documented the issue with the original method, but</span>
+0168 <span class="comment">% % working through it again, if you equate</span>
+0169 <span class="comment">% % (1) Q0    = (ahat*tau0)^(1/(1-bhat))</span>
+0170 <span class="comment">% % (2) Qexp  = (ahat*tau)^(1/(1-bhat))</span>
+0171 <span class="comment">% % (3) Qexp  = Q0*(2-bhat)/(3-bhat)</span>
+0172 <span class="comment">% % plug rhs of (1) into Q0 on rhs of (3) and equate that to (2)</span>
+0173 <span class="comment">% % (4) (ahat*tau0)^(1/(1-bhat))*(2-bhat)/(3-bhat) = (ahat*tau)^(1/(1-bhat))</span>
+0174 <span class="comment">% % (5) (tau0/tau)^(1/(1-bhat)) = (3-bhat)/(2-bhat)</span>
+0175 <span class="comment">% % (6) (tau0/tau) = (3-bhat)/(2-bhat)^(1-bhat)</span>
+0176 <span class="comment">% % (7) tau0 = tau*(3-bhat)/(2-bhat)^(1-bhat)</span>
+0177 <span class="comment">%</span>
+0178 <span class="comment">% % (6) implies that tau0/tau should equal ((3-b)/(2-b))^(1-b) = 0.748 ... very</span>
+0179 <span class="comment">% % close to the ratio I found examining the troch solutions whcih i interpret</span>
+0180 <span class="comment">% % as a discontinuity at b-3. It also implies we can get tau0 this way:</span>
+0181 <span class="comment">% % tau0 = tau*((3-b)/(2-b))^(1-b)</span>
+0182 <span class="comment">% % but that doesn't match tau0 from the pareto fit, so</span>
 0183 <span class="comment">%</span>
-0184 <span class="comment">% % so 1 - Qexp/Q0 = 1 - ((2-b)/(3-2*b))^(1/(1-b)) = 0.864 ...</span>
-0185 <span class="comment">%</span></pre></div>
+0184 <span class="comment">% % BUT ... tau = tau0*(2-b)/(3-2*b) is correct</span>
+0185 <span class="comment">%</span>
+0186 <span class="comment">% % how about this one ...</span>
+0187 <span class="comment">% % Q0 = Qexp*((3-2*b)/(2-b))^(1/(1-b))</span>
+0188 <span class="comment">%</span>
+0189 <span class="comment">% % which implies:</span>
+0190 <span class="comment">% % Q0/Qexp = ((3-2*b1)/(2-b1))^(1/(1-b1)) = 7.36 ...</span>
+0191 <span class="comment">% % Qexp/Q0 = ((2-b)/(3-2*b))^(1/(1-b)) = 0.136 ... and 1-0.136 = 0.864 which is</span>
+0192 <span class="comment">% % in the numerator of the late time q outflow equation 8 of troch 1993</span>
+0193 <span class="comment">%</span>
+0194 <span class="comment">% % so 1 - Qexp/Q0 = 1 - ((2-b)/(3-2*b))^(1/(1-b)) = 0.864 ...</span>
+0195 <span class="comment">%</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/fdcurve.html b/toolbox/docs/html/m2html/+baseflow/fdcurve.html
index 17f6da8..dde4f58 100644
--- a/toolbox/docs/html/m2html/+baseflow/fdcurve.html
+++ b/toolbox/docs/html/m2html/+baseflow/fdcurve.html
@@ -31,6 +31,12 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
      fdc = fdcurve(flow,varargin)
 
+     fdc.f is the non-exceedance position 1 - M/(N+1) of each flow in
+     fdc.x, which is sorted largest first. M counts the flows at or above
+     that flow, and N counts the flows that are not missing. fdc.fref and
+     fdc.xref hold one value for each 'refpoints' value, NaN for a NaN
+     point or a point above every flow.
+
  See also: <a href="hyetograph.html" class="code" title="function H = hyetograph(time, flow, prec, varargin)">hyetograph</a></pre></div>
 
 
@@ -62,114 +68,120 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0003    <span class="comment">%</span>
 0004    <span class="comment">%     fdc = fdcurve(flow,varargin)</span>
 0005    <span class="comment">%</span>
-0006    <span class="comment">% See also: hyetograph</span>
-0007 
-0008    <span class="comment">% if called with no input, open this file</span>
-0009    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0010 
-0011    <span class="comment">% parse inputs</span>
-0012    [axscale, units, refpoints, plotfit] = <a href="#_sub1" class="code" title="subfunction [axscale, units, refpoints, plotfit] = parseinputs(flow, varargin)">parseinputs</a>(flow, varargin{:});
+0006    <span class="comment">%     fdc.f is the non-exceedance position 1 - M/(N+1) of each flow in</span>
+0007    <span class="comment">%     fdc.x, which is sorted largest first. M counts the flows at or above</span>
+0008    <span class="comment">%     that flow, and N counts the flows that are not missing. fdc.fref and</span>
+0009    <span class="comment">%     fdc.xref hold one value for each 'refpoints' value, NaN for a NaN</span>
+0010    <span class="comment">%     point or a point above every flow.</span>
+0011    <span class="comment">%</span>
+0012    <span class="comment">% See also: hyetograph</span>
 0013 
-0014    <span class="comment">% main function</span>
-0015 
-0016    N = length(flow);
-0017    M = 1:N;
-0018    x = sort(flow,<span class="string">'descend'</span>);
-0019    f = 1-M./(N+1);
-0020 
-0021    <span class="comment">% if requested, compute reference point values</span>
-0022    xref = nan(numel(refpoints,1));
-0023    fref = nan(numel(refpoints,1));
-0024    <span class="keyword">if</span> ~isnan(refpoints)
-0025       <span class="keyword">for</span> n = 1:numel(refpoints)
-0026          iref = find(x&gt;=refpoints(n),1,<span class="string">'last'</span>);
-0027          xref(n) = x(iref);
-0028          fref(n) = f(iref);
-0029       <span class="keyword">end</span>
-0030    <span class="keyword">end</span>
-0031 
-0032    <span class="comment">% plot the curve if requested</span>
-0033    <span class="keyword">if</span> plotfit == true
-0034       figure;
-0035       <span class="keyword">switch</span> axscale
-0036          <span class="keyword">case</span> <span class="string">'loglog'</span>
-0037             h.fdc = loglog(100.*f,x); ax = gca;
-0038          <span class="keyword">case</span> <span class="string">'semilogy'</span>
-0039             h.fdc = semilogy(100.*f,x); ax = gca;
-0040          <span class="keyword">case</span> <span class="string">'semilogx'</span>
-0041             h.fdc = semilogx(100.*f,x); ax = gca;
-0042          <span class="keyword">case</span> <span class="string">'linear'</span>
-0043             h.fdc = plot(100.*f,x); ax = gca;
-0044       <span class="keyword">end</span>
-0045 
-0046       <span class="comment">% if requested, add a refpoint line</span>
-0047       <span class="keyword">if</span> ~isnan(refpoints)
-0048          hold on;
-0049          <span class="keyword">for</span> n = 1:numel(refpoints)
-0050             xplot = [min(xlim) 100*fref(n) 100*fref(n) 100*fref(n)];
-0051             yplot = [xref(n) xref(n) min(ylim) xref(n)];
-0052             h.ref(n) = plot(xplot,yplot,<span class="string">'Color'</span>,[0.85 0.325 0.098],<span class="string">'LineWidth'</span>,1);
-0053          <span class="keyword">end</span>
-0054       <span class="keyword">end</span>
-0055 
-0056       ylabel([<span class="string">'$x$ ['</span> units <span class="string">']'</span>]);
-0057       xlabel <span class="string">'flow exceedence probability, $P(Q\ge x)$'</span>
-0058 
-0059       ax.YAxis.TickLabels = compose(<span class="string">'%g'</span>,ax.YAxis.TickValues);
-0060       ax.XAxis.TickLabels = compose(<span class="string">'$%g\\%%$'</span>,ax.XAxis.TickValues);
+0014    <span class="comment">% if called with no input, open this file</span>
+0015    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0016 
+0017    <span class="comment">% parse inputs</span>
+0018    [axscale, units, refpoints, plotfit] = <a href="#_sub1" class="code" title="subfunction [axscale, units, refpoints, plotfit] = parseinputs(flow, varargin)">parseinputs</a>(flow, varargin{:});
+0019 
+0020    <span class="comment">% main function</span>
+0021 
+0022    <span class="comment">% a missing flow has no rank, so it stays out of the plotting positions</span>
+0023    flow = flow(~isnan(flow));
+0024    N = length(flow);
+0025    M = 1:N;
+0026    x = sort(flow,<span class="string">'descend'</span>);
+0027    f = 1-M./(N+1);
+0028 
+0029    <span class="comment">% if requested, compute reference point values. x is sorted descending,</span>
+0030    <span class="comment">% so the count of flows at or above a point is the index of the last one.</span>
+0031    <span class="comment">% A nan point, or one above every flow, has no index and stays nan.</span>
+0032    xref = nan(size(refpoints));
+0033    fref = nan(size(refpoints));
+0034    iref = sum(x(:)&gt;=refpoints(:).',1);
+0035    xref(iref&gt;0) = x(iref(iref&gt;0));
+0036    fref(iref&gt;0) = f(iref(iref&gt;0));
+0037 
+0038    <span class="comment">% plot the curve if requested</span>
+0039    <span class="keyword">if</span> plotfit == true
+0040       figure;
+0041       <span class="keyword">switch</span> axscale
+0042          <span class="keyword">case</span> <span class="string">'loglog'</span>
+0043             h.fdc = loglog(100.*f,x); ax = gca;
+0044          <span class="keyword">case</span> <span class="string">'semilogy'</span>
+0045             h.fdc = semilogy(100.*f,x); ax = gca;
+0046          <span class="keyword">case</span> <span class="string">'semilogx'</span>
+0047             h.fdc = semilogx(100.*f,x); ax = gca;
+0048          <span class="keyword">case</span> <span class="string">'linear'</span>
+0049             h.fdc = plot(100.*f,x); ax = gca;
+0050       <span class="keyword">end</span>
+0051 
+0052       <span class="comment">% if requested, add a refpoint line</span>
+0053       <span class="keyword">if</span> ~isnan(refpoints)
+0054          hold on;
+0055          <span class="keyword">for</span> n = 1:numel(refpoints)
+0056             xplot = [min(xlim) 100*fref(n) 100*fref(n) 100*fref(n)];
+0057             yplot = [xref(n) xref(n) min(ylim) xref(n)];
+0058             h.ref(n) = plot(xplot,yplot,<span class="string">'Color'</span>,[0.85 0.325 0.098],<span class="string">'LineWidth'</span>,1);
+0059          <span class="keyword">end</span>
+0060       <span class="keyword">end</span>
 0061 
-0062       <span class="comment">% since i manually set the ticklabels, i think this is necessary</span>
-0063       <span class="comment">% otherwise if the figure is resized, matlab will make new ticks</span>
-0064       set(gca,<span class="string">'XTickMode'</span>,<span class="string">'manual'</span>,<span class="string">'YTickMode'</span>,<span class="string">'manual'</span>);
-0065 
-0066       fdc.h = h;
-0067    <span class="keyword">end</span>
-0068 
-0069    <span class="comment">% package output</span>
-0070    fdc.f = f;
-0071    fdc.x = x;
-0072    fdc.xref = xref;
-0073    fdc.fref = fref;
-0074 <span class="keyword">end</span>
-0075 
-0076 <a name="_sub1" href="#_subfunctions" class="code">function [axscale, units, refpoints, plotfit] = parseinputs(flow, varargin)</a>
-0077 
-0078    p = inputParser;
-0079    p.FunctionName = <span class="string">'baseflow.fdcurve'</span>;
-0080    p.addRequired( <span class="string">'flow'</span>, @isnumeric);
-0081    p.addParameter(<span class="string">'axscale'</span>, <span class="string">'semilogy'</span>, @ischar);
-0082    p.addParameter(<span class="string">'units'</span>, <span class="string">''</span>, @ischar);
-0083    p.addParameter(<span class="string">'refpoints'</span>, nan, @isnumeric);
-0084    p.addParameter(<span class="string">'plotfit'</span>, true, @islogical);
-0085    p.parse(flow, varargin{:});
-0086 
-0087    refpoints = p.Results.refpoints;
-0088    plotfit= p.Results.plotfit;
-0089    axscale = p.Results.axscale;
-0090    units = p.Results.units;
-0091 <span class="keyword">end</span>
+0062       ylabel([<span class="string">'$x$ ['</span> units <span class="string">']'</span>]);
+0063       xlabel <span class="string">'flow non-exceedance probability, $P(Q&lt;x)$'</span>
+0064 
+0065       ax.YAxis.TickLabels = compose(<span class="string">'%g'</span>,ax.YAxis.TickValues);
+0066       ax.XAxis.TickLabels = compose(<span class="string">'$%g\\%%$'</span>,ax.XAxis.TickValues);
+0067 
+0068       <span class="comment">% since i manually set the ticklabels, i think this is necessary</span>
+0069       <span class="comment">% otherwise if the figure is resized, matlab will make new ticks</span>
+0070       set(gca,<span class="string">'XTickMode'</span>,<span class="string">'manual'</span>,<span class="string">'YTickMode'</span>,<span class="string">'manual'</span>);
+0071 
+0072       fdc.h = h;
+0073    <span class="keyword">end</span>
+0074 
+0075    <span class="comment">% package output</span>
+0076    fdc.f = f;
+0077    fdc.x = x;
+0078    fdc.xref = xref;
+0079    fdc.fref = fref;
+0080 <span class="keyword">end</span>
+0081 
+0082 <a name="_sub1" href="#_subfunctions" class="code">function [axscale, units, refpoints, plotfit] = parseinputs(flow, varargin)</a>
+0083 
+0084    p = inputParser;
+0085    p.FunctionName = <span class="string">'baseflow.fdcurve'</span>;
+0086    p.addRequired( <span class="string">'flow'</span>, @isnumeric);
+0087    p.addParameter(<span class="string">'axscale'</span>, <span class="string">'semilogy'</span>, @ischar);
+0088    p.addParameter(<span class="string">'units'</span>, <span class="string">''</span>, @ischar);
+0089    p.addParameter(<span class="string">'refpoints'</span>, nan, @isnumeric);
+0090    p.addParameter(<span class="string">'plotfit'</span>, true, @islogical);
+0091    p.parse(flow, varargin{:});
 0092 
-0093 <span class="comment">% function [F,x] = ecdfpot(x,xmin,alpha,sigma)</span>
-0094 <span class="comment">%</span>
-0095 <span class="comment">%    % not implemented</span>
-0096 <span class="comment">%</span>
-0097 <span class="comment">%    % http://sfb649.wiwi.hu-berlin.de/fedc_homepage/xplore/tutorials/sfehtmlnode91.html</span>
-0098 <span class="comment">%</span>
-0099 <span class="comment">%    % peaks over threshold exceedance probability:</span>
-0100 <span class="comment">%    % F(x) = N(u)/n(1+gamma(x-u)/beta)^(-1/gamm),</span>
-0101 <span class="comment">%    % N(u) is the number of obs&gt;u</span>
-0102 <span class="comment">%    % n is totla number, i think</span>
-0103 <span class="comment">%    % x would be tau</span>
-0104 <span class="comment">%    % u would be taumin</span>
-0105 <span class="comment">%    % gamma/beta would be b-1/tau0 i think</span>
-0106 <span class="comment">%    % so 1/gamm would be 1/b-1</span>
-0107 <span class="comment">%</span>
-0108 <span class="comment">%</span>
-0109 <span class="comment">%    N     = numel(x(x&gt;xmin));</span>
-0110 <span class="comment">%    n     = numel(x);</span>
-0111 <span class="comment">%    gamma = b-1; % might be 1-b;</span>
-0112 <span class="comment">%    beta  = tau0;</span>
-0113 <span class="comment">%    F     = N/n.*(1+gamma.*(x-x0)/beta)^(-1/gamm);</span>
-0114</pre></div>
+0093    refpoints = p.Results.refpoints;
+0094    plotfit= p.Results.plotfit;
+0095    axscale = p.Results.axscale;
+0096    units = p.Results.units;
+0097 <span class="keyword">end</span>
+0098 
+0099 <span class="comment">% function [F,x] = ecdfpot(x,xmin,alpha,sigma)</span>
+0100 <span class="comment">%</span>
+0101 <span class="comment">%    % not implemented</span>
+0102 <span class="comment">%</span>
+0103 <span class="comment">%    % http://sfb649.wiwi.hu-berlin.de/fedc_homepage/xplore/tutorials/sfehtmlnode91.html</span>
+0104 <span class="comment">%</span>
+0105 <span class="comment">%    % peaks over threshold exceedance probability:</span>
+0106 <span class="comment">%    % F(x) = N(u)/n(1+gamma(x-u)/beta)^(-1/gamm),</span>
+0107 <span class="comment">%    % N(u) is the number of obs&gt;u</span>
+0108 <span class="comment">%    % n is totla number, i think</span>
+0109 <span class="comment">%    % x would be tau</span>
+0110 <span class="comment">%    % u would be taumin</span>
+0111 <span class="comment">%    % gamma/beta would be b-1/tau0 i think</span>
+0112 <span class="comment">%    % so 1/gamm would be 1/b-1</span>
+0113 <span class="comment">%</span>
+0114 <span class="comment">%</span>
+0115 <span class="comment">%    N     = numel(x(x&gt;xmin));</span>
+0116 <span class="comment">%    n     = numel(x);</span>
+0117 <span class="comment">%    gamma = b-1; % might be 1-b;</span>
+0118 <span class="comment">%    beta  = tau0;</span>
+0119 <span class="comment">%    F     = N/n.*(1+gamma.*(x-x0)/beta)^(-1/gamm);</span>
+0120</pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/fitab.html b/toolbox/docs/html/m2html/+baseflow/fitab.html
index 243786a..9d4e06c 100644
--- a/toolbox/docs/html/m2html/+baseflow/fitab.html
+++ b/toolbox/docs/html/m2html/+baseflow/fitab.html
@@ -51,7 +51,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
      weights  vector double of weights for the fitting algorithm
      mask     vector logical mask to exclude values from fitting
-     order    scalar, exponent in -dq/dt = aQ^b
+     order    scalar, exponent in -dq/dt = aQ^b. Methods 'mean',
+              'median', and 'envelope' fix the slope to order, which
+              is 1 when it is not given.
      refqtls  2x1 double, x/y quantiles used if 'method' == 'envelope'
      quantile scalar double, quantile used if 'method' == 'qtl' (quantile
               regression)
@@ -62,7 +64,7 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
               plotfit); an unknown field is an error
 
  Notes
-     weights are set zero anywhere mask is false
+     masked points and zero-weight points take no part in the fit
 
      Use method 'envelope' to pass a line through an arbitrary x,y pair
      (refpoints), specified in terms of the quantile of the x/y data
@@ -105,10 +107,10 @@ <h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border
 <ul style="list-style-image:url(../html_img/matlabicon.gif)">
 
 <li><a href="#_sub1" class="code">function [ab,ci,ok] = fitOLS(logx,logy,weights,alpha)</a></li>
-<li><a href="#_sub2" class="code">function [ab,ci,ok] = fitLIN(logx,logy,weights,alpha,order)</a></li>
-<li><a href="#_sub3" class="code">function [ab,ci,ok] = fitMED(logx,logy,weights,order,inoctave)</a></li>
-<li><a href="#_sub4" class="code">function [ab,ci,ok] = fitENV(logx,logy,weights,order,refqtls,inoctave)</a></li>
-<li><a href="#_sub5" class="code">function [ab,ci,ok] = fitQTL(logx,logy,weights,alpha,order,qtl,Nboot,inoctave)</a></li>
+<li><a href="#_sub2" class="code">function [ab,ci,ok] = fitLIN(logx,logy,alpha,order)</a></li>
+<li><a href="#_sub3" class="code">function [ab,ci,ok] = fitMED(logx,logy,order,inoctave)</a></li>
+<li><a href="#_sub4" class="code">function [ab,ci,ok] = fitENV(logx,logy,order,refqtls,inoctave)</a></li>
+<li><a href="#_sub5" class="code">function [ab,ci,ok] = fitQTL(logx,logy,alpha,order,qtl,Nboot,inoctave)</a></li>
 <li><a href="#_sub6" class="code">function [ab,ci,ok] = fitMLE(logx,logy,~,alpha,sigx,sigy,rxy)</a></li>
 <li><a href="#_sub7" class="code">function [ab,ci,ok,fselect] = fitNLS(x,y,logx,logy,weights,alpha,inoctave)</a></li>
 <li><a href="#_sub8" class="code">function [Fit,ok] = evalFit(ab,x,y,ci,ok)</a></li>
@@ -142,470 +144,460 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0023    <span class="comment">%</span>
 0024    <span class="comment">%     weights  vector double of weights for the fitting algorithm</span>
 0025    <span class="comment">%     mask     vector logical mask to exclude values from fitting</span>
-0026    <span class="comment">%     order    scalar, exponent in -dq/dt = aQ^b</span>
-0027    <span class="comment">%     refqtls  2x1 double, x/y quantiles used if 'method' == 'envelope'</span>
-0028    <span class="comment">%     quantile scalar double, quantile used if 'method' == 'qtl' (quantile</span>
-0029    <span class="comment">%              regression)</span>
-0030    <span class="comment">%     Nboot    scalar double, bootstrap sample size for quantile regression</span>
-0031    <span class="comment">%     plotfit  logical scalar indicating whether to make a plot or not</span>
-0032    <span class="comment">%     fitopts  struct whose fields override the same-named options above</span>
-0033    <span class="comment">%              (weights, order, mask, quantile, refqtls, Nboot, alpha,</span>
-0034    <span class="comment">%              plotfit); an unknown field is an error</span>
-0035    <span class="comment">%</span>
-0036    <span class="comment">% Notes</span>
-0037    <span class="comment">%     weights are set zero anywhere mask is false</span>
-0038    <span class="comment">%</span>
-0039    <span class="comment">%     Use method 'envelope' to pass a line through an arbitrary x,y pair</span>
-0040    <span class="comment">%     (refpoints), specified in terms of the quantile of the x/y data</span>
-0041    <span class="comment">%     distributions. this method is similar to 'mean' or 'median', but allows</span>
-0042    <span class="comment">%     different ref points for the x/y values, for example the median of the</span>
-0043    <span class="comment">%     x values (0.50 quantile) and some other quantile of the y values. The</span>
-0044    <span class="comment">%     default (recommended) behavior is to keep the x-quantile = 0.5 and vary</span>
-0045    <span class="comment">%     the y-quantile to move the line up and down as desired to define an</span>
-0046    <span class="comment">%     &quot;envelope&quot;</span>
-0047    <span class="comment">%</span>
-0048    <span class="comment">% Example</span>
+0026    <span class="comment">%     order    scalar, exponent in -dq/dt = aQ^b. Methods 'mean',</span>
+0027    <span class="comment">%              'median', and 'envelope' fix the slope to order, which</span>
+0028    <span class="comment">%              is 1 when it is not given.</span>
+0029    <span class="comment">%     refqtls  2x1 double, x/y quantiles used if 'method' == 'envelope'</span>
+0030    <span class="comment">%     quantile scalar double, quantile used if 'method' == 'qtl' (quantile</span>
+0031    <span class="comment">%              regression)</span>
+0032    <span class="comment">%     Nboot    scalar double, bootstrap sample size for quantile regression</span>
+0033    <span class="comment">%     plotfit  logical scalar indicating whether to make a plot or not</span>
+0034    <span class="comment">%     fitopts  struct whose fields override the same-named options above</span>
+0035    <span class="comment">%              (weights, order, mask, quantile, refqtls, Nboot, alpha,</span>
+0036    <span class="comment">%              plotfit); an unknown field is an error</span>
+0037    <span class="comment">%</span>
+0038    <span class="comment">% Notes</span>
+0039    <span class="comment">%     masked points and zero-weight points take no part in the fit</span>
+0040    <span class="comment">%</span>
+0041    <span class="comment">%     Use method 'envelope' to pass a line through an arbitrary x,y pair</span>
+0042    <span class="comment">%     (refpoints), specified in terms of the quantile of the x/y data</span>
+0043    <span class="comment">%     distributions. this method is similar to 'mean' or 'median', but allows</span>
+0044    <span class="comment">%     different ref points for the x/y values, for example the median of the</span>
+0045    <span class="comment">%     x values (0.50 quantile) and some other quantile of the y values. The</span>
+0046    <span class="comment">%     default (recommended) behavior is to keep the x-quantile = 0.5 and vary</span>
+0047    <span class="comment">%     the y-quantile to move the line up and down as desired to define an</span>
+0048    <span class="comment">%     &quot;envelope&quot;</span>
 0049    <span class="comment">%</span>
-0050    <span class="comment">%  Generate test data with known parameters a and b, then fit them:</span>
+0050    <span class="comment">% Example</span>
 0051    <span class="comment">%</span>
-0052    <span class="comment">%     [t, q, dqdt] = baseflow.generateTestData(1e-2, 1.5, 100);</span>
-0053    <span class="comment">%     Fit = baseflow.fitab(q, dqdt, 'nls');</span>
-0054    <span class="comment">%     fprintf('a = %.4f, b = %.2f\n', Fit.a, Fit.b)</span>
-0055    <span class="comment">%</span>
-0056    <span class="comment">%  Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0052    <span class="comment">%  Generate test data with known parameters a and b, then fit them:</span>
+0053    <span class="comment">%</span>
+0054    <span class="comment">%     [t, q, dqdt] = baseflow.generateTestData(1e-2, 1.5, 100);</span>
+0055    <span class="comment">%     Fit = baseflow.fitab(q, dqdt, 'nls');</span>
+0056    <span class="comment">%     fprintf('a = %.4f, b = %.2f\n', Fit.a, Fit.b)</span>
 0057    <span class="comment">%</span>
-0058    <span class="comment">% See also: prepfits, fitevents</span>
-0059 
-0060    <span class="comment">% if called with no input, open this file</span>
-0061    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0062 
-0063    <span class="keyword">persistent</span> inoctave
-0064    <span class="keyword">if</span> isempty(inoctave); inoctave = exist(&quot;OCTAVE_VERSION&quot;, &quot;builtin&quot;)&gt;0;
-0065    <span class="keyword">end</span>
-0066 
-0067    <span class="comment">% PARSE INPUTS</span>
-0068    [weights, order, mask, qtl, refqtls, Nboot, alpha, plotfit] = parseinputs( <span class="keyword">...</span>
-0069       q, dqdt, method, mfilename, varargin{:});
-0070 
-0071    <span class="comment">% PREP FITS</span>
-0072    [x, y, logx, logy, weights, ok] = baseflow.prepfits( <span class="keyword">...</span>
-0073       q, dqdt, <span class="string">'weights'</span>, weights, <span class="string">'mask'</span>, mask);
-0074 
-0075    <span class="comment">% FAST EXIT</span>
-0076    <span class="keyword">if</span> ok == false
-0077       Fit = nan; <span class="keyword">return</span>;
-0078    <span class="keyword">end</span>
-0079 
-0080    <span class="comment">% If 'order' = 1 and the method is 'ols' or 'nls', switch to 'mean'.</span>
-0081    <span class="comment">% The 'mean' method forces a line of slope 1. fitOLS and fitNLS ignore</span>
-0082    <span class="comment">% 'order'. Do not switch the other methods. The 'mean', 'median', and</span>
-0083    <span class="comment">% 'envelope' methods force a line of slope 'order'. plotrefline relies</span>
-0084    <span class="comment">% on 'envelope' with 'order' = 1. 'qtl' passes 'order' to quantreg as</span>
-0085    <span class="comment">% the polynomial degree. 'mle' errors as unsupported.</span>
-0086    <span class="keyword">if</span> order == 1 &amp;&amp; any(strcmp(method, {<span class="string">'ols'</span>, <span class="string">'nls'</span>}))
-0087       method = <span class="string">'mean'</span>;
-0088    <span class="keyword">end</span>
-0089 
-0090    <span class="comment">% SWITCH YARD</span>
-0091    fselect = method;
-0092 
-0093    <span class="keyword">switch</span> method
-0094       <span class="keyword">case</span> <span class="string">'ols'</span>
-0095          [ab,ci,ok] = <a href="#_sub1" class="code" title="subfunction [ab,ci,ok] = fitOLS(logx,logy,weights,alpha)">fitOLS</a>(logx,logy,weights,alpha);
-0096       <span class="keyword">case</span> <span class="string">'qtl'</span>
-0097          [ab,ci,ok] = <a href="#_sub5" class="code" title="subfunction [ab,ci,ok] = fitQTL(logx,logy,weights,alpha,order,qtl,Nboot,inoctave)">fitQTL</a>(logx,logy,weights,alpha,order,qtl,Nboot,inoctave);
-0098       <span class="keyword">case</span> <span class="string">'mle'</span>
-0099          error(<span class="string">'mle fitting not currently supported'</span>);
-0100          <span class="comment">% [ab,ci,ok] = fitMLE(logx,logy,weights,alpha,sigx,sigy,rxy);</span>
-0101       <span class="keyword">case</span> <span class="string">'nls'</span>
-0102          [ab,ci,ok,fselect] = <a href="#_sub7" class="code" title="subfunction [ab,ci,ok,fselect] = fitNLS(x,y,logx,logy,weights,alpha,inoctave)">fitNLS</a>(x,y,logx,logy,weights,alpha,inoctave);
-0103       <span class="keyword">case</span> <span class="string">'mean'</span>
-0104          [ab,ci,ok] = <a href="#_sub2" class="code" title="subfunction [ab,ci,ok] = fitLIN(logx,logy,weights,alpha,order)">fitLIN</a>(logx,logy,weights,alpha,order);
-0105       <span class="keyword">case</span> <span class="string">'median'</span>
-0106          [ab,ci,ok] = <a href="#_sub3" class="code" title="subfunction [ab,ci,ok] = fitMED(logx,logy,weights,order,inoctave)">fitMED</a>(logx,logy,weights,order,inoctave);
-0107       <span class="keyword">case</span> <span class="string">'envelope'</span>
-0108          [ab,ci,ok] = <a href="#_sub4" class="code" title="subfunction [ab,ci,ok] = fitENV(logx,logy,weights,order,refqtls,inoctave)">fitENV</a>(logx,logy,weights,order,refqtls,inoctave);
-0109    <span class="keyword">end</span>
-0110 
-0111    <span class="comment">% EVALUATE THE FIT</span>
-0112    [Fit,ok] = <a href="#_sub8" class="code" title="subfunction [Fit,ok] = evalFit(ab,x,y,ci,ok)">evalFit</a>(ab,x,y,ci,ok);
-0113 
-0114    <span class="keyword">if</span> exist(<span class="string">'fselect'</span>,<span class="string">'var'</span>)
-0115       Fit.fselect = fselect;
-0116    <span class="keyword">end</span>
-0117 
-0118    <span class="keyword">if</span> plotfit == true
-0119       Fit.h = baseflow.pointcloudplot(q,dqdt,<span class="string">'reflines'</span>,{<span class="string">'userfit'</span>}, <span class="keyword">...</span>
-0120          <span class="string">'userab'</span>,ab,<span class="string">'mask'</span>,mask,<span class="string">'usertext'</span>,method);
-0121    <span class="keyword">end</span>
-0122 
-0123    <span class="comment">% use this when stepping through nlinfit</span>
-0124    debug = false;
-0125    <span class="keyword">if</span> debug == true
-0126       pos = get(0,<span class="string">'defaultfigureposition'</span>);
-0127       figure(<span class="string">'Position'</span>, [pos(1) pos(2) 2*pos(3) pos(4)])
-0128       subplot(1, 2, 1)
-0129       hold on
-0130       loglog(X, y, <span class="string">'-o'</span>);
-0131       <span class="comment">% Jul 2024 - yfit undefined so commented it out</span>
-0132       <span class="comment">% plot(X, yfit, ':');</span>
-0133       xlabel(<span class="string">'log Q'</span>);
-0134       ylabel(<span class="string">'log -dQ/dt'</span>);
-0135       legend(<span class="string">'data'</span>, <span class="string">'fit'</span>);
-0136 
-0137       subplot(1, 2, 2)
-0138       hold on
-0139       plot(X, y, <span class="string">'-o'</span>);
-0140       <span class="comment">% Jul 2024 - yfit undefined so commented it out</span>
-0141       <span class="comment">% plot(X, yfit, ':');</span>
-0142       xlabel(<span class="string">'Q'</span>);
-0143       ylabel(<span class="string">'-dQ/dt'</span>);
-0144       legend(<span class="string">'data'</span>, <span class="string">'fit'</span>);
-0145    <span class="keyword">end</span>
-0146 <span class="keyword">end</span>
-0147 
-0148 <span class="comment">% FITTING METHODS</span>
-0149 <a name="_sub1" href="#_subfunctions" class="code">function [ab,ci,ok] = fitOLS(logx,logy,weights,alpha)</a>
-0150    <span class="comment">% ordinary least squares linear regression in log-log</span>
-0151    <span class="comment">%</span>
-0152    <span class="comment">% Solve weighted least squares with plain linear algebra, so the method</span>
-0153    <span class="comment">% runs on MATLAB and Octave. The result matches the Curve Fitting Toolbox</span>
-0154    <span class="comment">% confint(fit(logx,logy,'poly1'), alpha) with fitoptions Weights.</span>
-0155 
-0156    <span class="comment">% Scale each row by the square root of its weight, so the unweighted</span>
-0157    <span class="comment">% solve minimizes sum(weights.*resid.^2). Masked points have zero weight</span>
-0158    <span class="comment">% and add nothing to the coefficients or the residuals.</span>
-0159    sw = sqrt(weights);
-0160    X = [sw, sw.*logx];
-0161    [Qx,R] = qr(X,0);
-0162    ab = R \ (Qx'*(sw.*logy));
-0163    resid = sw.*logy - X*ab;
-0164 
-0165    <span class="comment">% Compute coefficient standard errors from inv(X'*X) = inv(R)*inv(R)'.</span>
-0166    <span class="comment">% fit counts zero-weight (masked) points in the n-2 residual degrees of</span>
-0167    <span class="comment">% freedom, so count them here too to match confint.</span>
-0168    dfe = numel(logy) - 2;
-0169    Rinv = R \ eye(2);
-0170    se = sqrt(diag(Rinv*Rinv') * sum(resid.^2) / dfe);
-0171 
-0172    <span class="comment">% Compute t-based intervals at confidence level alpha, one row per</span>
-0173    <span class="comment">% coefficient, in the order [intercept; slope]. This is the rot90(confint)</span>
-0174    <span class="comment">% layout, which is consistent with the stats functions.</span>
-0175    tcrit = tinv((1 + alpha) / 2, dfe);
-0176    ci = [ab - tcrit*se, ab + tcrit*se];
-0177 
-0178    <span class="comment">% transform a to linear space and package a/b</span>
-0179    ab = [exp(ab(1)); ab(2)];
-0180    ci(1,:) = exp(ci(1,:));
-0181 
-0182    <span class="comment">% generic failure check</span>
-0183    ok = all(isreal(ab));
-0184 <span class="keyword">end</span>
-0185 
-0186 <a name="_sub2" href="#_subfunctions" class="code">function [ab,ci,ok] = fitLIN(logx,logy,weights,alpha,order)</a>
-0187    <span class="comment">% linear model fit in log-log, equivalent to forcing a line of slope 1</span>
-0188    <span class="comment">% through the mean x-y, with option to control the slope using input</span>
-0189    <span class="comment">% parameter 'order'</span>
-0190 
-0191    <span class="comment">% apply the mask / weights</span>
-0192    logx = logx(weights&gt;0);
-0193    logy = logy(weights&gt;0);
+0058    <span class="comment">%  Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0059    <span class="comment">%</span>
+0060    <span class="comment">% See also: prepfits, fitevents</span>
+0061 
+0062    <span class="comment">% if called with no input, open this file</span>
+0063    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0064 
+0065    <span class="keyword">persistent</span> inoctave
+0066    <span class="keyword">if</span> isempty(inoctave); inoctave = exist(&quot;OCTAVE_VERSION&quot;, &quot;builtin&quot;)&gt;0;
+0067    <span class="keyword">end</span>
+0068 
+0069    <span class="comment">% PARSE INPUTS</span>
+0070    [weights, order, mask, qtl, refqtls, Nboot, alpha, plotfit] = parseinputs( <span class="keyword">...</span>
+0071       q, dqdt, method, mfilename, varargin{:});
+0072 
+0073    <span class="comment">% PREP FITS</span>
+0074    [x, y, logx, logy, weights, ok] = baseflow.prepfits( <span class="keyword">...</span>
+0075       q, dqdt, <span class="string">'weights'</span>, weights, <span class="string">'mask'</span>, mask);
+0076 
+0077    <span class="comment">% FAST EXIT</span>
+0078    <span class="keyword">if</span> ok == false
+0079       Fit = nan; <span class="keyword">return</span>;
+0080    <span class="keyword">end</span>
+0081 
+0082    <span class="comment">% If 'order' = 1 and the method is 'ols' or 'nls', switch to 'mean'.</span>
+0083    <span class="comment">% The 'mean' method forces a line of slope 1. fitOLS and fitNLS ignore</span>
+0084    <span class="comment">% 'order'. Do not switch the other methods. The 'mean', 'median', and</span>
+0085    <span class="comment">% 'envelope' methods force a line of slope 'order'. plotrefline relies</span>
+0086    <span class="comment">% on 'envelope' with 'order' = 1. 'qtl' passes 'order' to quantreg as</span>
+0087    <span class="comment">% the polynomial degree. 'mle' errors as unsupported.</span>
+0088    <span class="keyword">if</span> order == 1 &amp;&amp; any(strcmp(method, {<span class="string">'ols'</span>, <span class="string">'nls'</span>}))
+0089       method = <span class="string">'mean'</span>;
+0090    <span class="keyword">end</span>
+0091 
+0092    <span class="comment">% SWITCH YARD</span>
+0093    fselect = method;
+0094 
+0095    <span class="keyword">switch</span> method
+0096       <span class="keyword">case</span> <span class="string">'ols'</span>
+0097          [ab,ci,ok] = <a href="#_sub1" class="code" title="subfunction [ab,ci,ok] = fitOLS(logx,logy,weights,alpha)">fitOLS</a>(logx,logy,weights,alpha);
+0098       <span class="keyword">case</span> <span class="string">'qtl'</span>
+0099          [ab,ci,ok] = <a href="#_sub5" class="code" title="subfunction [ab,ci,ok] = fitQTL(logx,logy,alpha,order,qtl,Nboot,inoctave)">fitQTL</a>(logx,logy,alpha,order,qtl,Nboot,inoctave);
+0100       <span class="keyword">case</span> <span class="string">'mle'</span>
+0101          error(<span class="string">'mle fitting not currently supported'</span>);
+0102          <span class="comment">% [ab,ci,ok] = fitMLE(logx,logy,weights,alpha,sigx,sigy,rxy);</span>
+0103       <span class="keyword">case</span> <span class="string">'nls'</span>
+0104          [ab,ci,ok,fselect] = <a href="#_sub7" class="code" title="subfunction [ab,ci,ok,fselect] = fitNLS(x,y,logx,logy,weights,alpha,inoctave)">fitNLS</a>(x,y,logx,logy,weights,alpha,inoctave);
+0105       <span class="keyword">case</span> <span class="string">'mean'</span>
+0106          [ab,ci,ok] = <a href="#_sub2" class="code" title="subfunction [ab,ci,ok] = fitLIN(logx,logy,alpha,order)">fitLIN</a>(logx,logy,alpha,order);
+0107       <span class="keyword">case</span> <span class="string">'median'</span>
+0108          [ab,ci,ok] = <a href="#_sub3" class="code" title="subfunction [ab,ci,ok] = fitMED(logx,logy,order,inoctave)">fitMED</a>(logx,logy,order,inoctave);
+0109       <span class="keyword">case</span> <span class="string">'envelope'</span>
+0110          [ab,ci,ok] = <a href="#_sub4" class="code" title="subfunction [ab,ci,ok] = fitENV(logx,logy,order,refqtls,inoctave)">fitENV</a>(logx,logy,order,refqtls,inoctave);
+0111    <span class="keyword">end</span>
+0112 
+0113    <span class="comment">% EVALUATE THE FIT</span>
+0114    [Fit,ok] = <a href="#_sub8" class="code" title="subfunction [Fit,ok] = evalFit(ab,x,y,ci,ok)">evalFit</a>(ab,x,y,ci,ok);
+0115 
+0116    <span class="keyword">if</span> exist(<span class="string">'fselect'</span>,<span class="string">'var'</span>)
+0117       Fit.fselect = fselect;
+0118    <span class="keyword">end</span>
+0119 
+0120    <span class="keyword">if</span> plotfit == true
+0121       Fit.h = baseflow.pointcloudplot(q,dqdt,<span class="string">'reflines'</span>,{<span class="string">'userfit'</span>}, <span class="keyword">...</span>
+0122          <span class="string">'userab'</span>,ab,<span class="string">'mask'</span>,mask,<span class="string">'usertext'</span>,method);
+0123    <span class="keyword">end</span>
+0124 
+0125    <span class="comment">% use this when stepping through nlinfit</span>
+0126    debug = false;
+0127    <span class="keyword">if</span> debug == true
+0128       pos = get(0,<span class="string">'defaultfigureposition'</span>);
+0129       figure(<span class="string">'Position'</span>, [pos(1) pos(2) 2*pos(3) pos(4)])
+0130       subplot(1, 2, 1)
+0131       hold on
+0132       loglog(X, y, <span class="string">'-o'</span>);
+0133       <span class="comment">% Jul 2024 - yfit undefined so commented it out</span>
+0134       <span class="comment">% plot(X, yfit, ':');</span>
+0135       xlabel(<span class="string">'log Q'</span>);
+0136       ylabel(<span class="string">'log -dQ/dt'</span>);
+0137       legend(<span class="string">'data'</span>, <span class="string">'fit'</span>);
+0138 
+0139       subplot(1, 2, 2)
+0140       hold on
+0141       plot(X, y, <span class="string">'-o'</span>);
+0142       <span class="comment">% Jul 2024 - yfit undefined so commented it out</span>
+0143       <span class="comment">% plot(X, yfit, ':');</span>
+0144       xlabel(<span class="string">'Q'</span>);
+0145       ylabel(<span class="string">'-dQ/dt'</span>);
+0146       legend(<span class="string">'data'</span>, <span class="string">'fit'</span>);
+0147    <span class="keyword">end</span>
+0148 <span class="keyword">end</span>
+0149 
+0150 <span class="comment">% FITTING METHODS</span>
+0151 <a name="_sub1" href="#_subfunctions" class="code">function [ab,ci,ok] = fitOLS(logx,logy,weights,alpha)</a>
+0152    <span class="comment">% ordinary least squares linear regression in log-log</span>
+0153    <span class="comment">%</span>
+0154    <span class="comment">% Solve weighted least squares with plain linear algebra, so the method</span>
+0155    <span class="comment">% runs on MATLAB and Octave. The result matches the Curve Fitting Toolbox</span>
+0156    <span class="comment">% confint(fit(logx,logy,'poly1'), alpha) with fitoptions Weights.</span>
+0157 
+0158    <span class="comment">% Scale each row by the square root of its weight, so the unweighted</span>
+0159    <span class="comment">% solve minimizes sum(weights.*resid.^2). prepfits removes masked</span>
+0160    <span class="comment">% points, so every row has a positive weight.</span>
+0161    sw = sqrt(weights);
+0162    X = [sw, sw.*logx];
+0163    [Qx,R] = qr(X,0);
+0164    ab = R \ (Qx'*(sw.*logy));
+0165    resid = sw.*logy - X*ab;
+0166 
+0167    <span class="comment">% Compute coefficient standard errors from inv(X'*X) = inv(R)*inv(R)'.</span>
+0168    <span class="comment">% The n-2 residual degrees of freedom count the fitted points only.</span>
+0169    dfe = numel(logy) - 2;
+0170    Rinv = R \ eye(2);
+0171    se = sqrt(diag(Rinv*Rinv') * sum(resid.^2) / dfe);
+0172 
+0173    <span class="comment">% Compute t-based intervals at confidence level alpha, one row per</span>
+0174    <span class="comment">% coefficient, in the order [intercept; slope]. This is the rot90(confint)</span>
+0175    <span class="comment">% layout, which is consistent with the stats functions.</span>
+0176    tcrit = tinv((1 + alpha) / 2, dfe);
+0177    ci = [ab - tcrit*se, ab + tcrit*se];
+0178 
+0179    <span class="comment">% transform a to linear space and package a/b</span>
+0180    ab = [exp(ab(1)); ab(2)];
+0181    ci(1,:) = exp(ci(1,:));
+0182 
+0183    <span class="comment">% generic failure check</span>
+0184    ok = all(isreal(ab));
+0185 <span class="keyword">end</span>
+0186 
+0187 <a name="_sub2" href="#_subfunctions" class="code">function [ab,ci,ok] = fitLIN(logx,logy,alpha,order)</a>
+0188    <span class="comment">% linear model fit in log-log, equivalent to forcing a line of slope 1</span>
+0189    <span class="comment">% through the mean x-y, with option to control the slope using input</span>
+0190    <span class="comment">% parameter 'order'</span>
+0191 
+0192    <span class="comment">% impose model order. parseinputs sets order 1 when it is not given.</span>
+0193    logx = order.*logx;
 0194 
-0195    <span class="comment">% impose model order if provided</span>
-0196    <span class="keyword">if</span> ~isnan(order)
-0197       logx = order.*logx;
-0198    <span class="keyword">end</span>
+0195    [~,~,ci] = ttest(-logx,-logy,<span class="string">'Alpha'</span>,1-alpha);
+0196 
+0197    <span class="comment">% note: mean(x-y) = mean(x)-mean(y)</span>
+0198    ab = [exp(-(mean(logx)-mean(logy))); order];
 0199 
-0200    [~,~,ci] = ttest(-logx,-logy,<span class="string">'Alpha'</span>,1-alpha);
-0201 
-0202    <span class="comment">% note: mean(x-y) = mean(x)-mean(y)</span>
-0203    ab = [exp(-(mean(logx)-mean(logy))); order];
-0204 
-0205    <span class="comment">% transpose ci to be consistent with stats functions</span>
-0206    ci = [exp(ci(1)) exp(ci(2)); ab(2), ab(2)];
-0207 
-0208    <span class="comment">% generic failure check</span>
-0209    ok = all(isreal(ab));
-0210 <span class="keyword">end</span>
+0200    <span class="comment">% transpose ci to be consistent with stats functions</span>
+0201    ci = [exp(ci(1)) exp(ci(2)); ab(2), ab(2)];
+0202 
+0203    <span class="comment">% generic failure check</span>
+0204    ok = all(isreal(ab));
+0205 <span class="keyword">end</span>
+0206 
+0207 <a name="_sub3" href="#_subfunctions" class="code">function [ab,ci,ok] = fitMED(logx,logy,order,inoctave)</a>
+0208    <span class="comment">% force a line of slope 'order' through the median x-y</span>
+0209 
+0210    logx = order*logx;
 0211 
-0212 <a name="_sub3" href="#_subfunctions" class="code">function [ab,ci,ok] = fitMED(logx,logy,weights,order,inoctave)</a>
-0213    <span class="comment">% force a line of slope 'order' through the median x-y</span>
-0214 
-0215    <span class="comment">% apply the mask / weights</span>
-0216    logx = logx(weights&gt;0);
-0217    logy = logy(weights&gt;0);
-0218 
-0219    logx = order*logx;
+0212    <span class="keyword">if</span> inoctave
+0213       pval = nan; <span class="comment">% ranksum and kruskalwallis both supported, need to implement</span>
+0214    <span class="keyword">else</span>
+0215       pval = signrank(-logx,-logy); <span class="comment">% or ranksum or kruskalwallis</span>
+0216    <span class="keyword">end</span>
+0217 
+0218    <span class="comment">% med(x-y)!=med(x)-med(y)</span>
+0219    ab = [exp(-(median(logx)-median(logy))); order];
 0220 
-0221    <span class="keyword">if</span> inoctave
-0222       pval = nan; <span class="comment">% ranksum and kruskalwallis both supported, need to implement</span>
-0223    <span class="keyword">else</span>
-0224       pval = signrank(-logx,-logy); <span class="comment">% or ranksum or kruskalwallis</span>
-0225    <span class="keyword">end</span>
-0226 
-0227    <span class="comment">% med(x-y)!=med(x)-med(y)</span>
-0228    ab = [exp(-(median(logx)-median(logy))); order];
-0229 
-0230    <span class="comment">% non-parametric test, no ci</span>
-0231    ci = [ab(1), ab(1); ab(2), ab(2)];
-0232 
-0233    <span class="comment">% could return to this later</span>
-0234    <span class="comment">%bootfun = @(x,y)(median(y)-median(x));</span>
-0235    <span class="comment">%bootci(100,bootfun(logx,logy))</span>
-0236 
-0237    <span class="comment">% generic failure check</span>
-0238    ok = all(isreal(ab));
-0239 <span class="keyword">end</span>
+0221    <span class="comment">% non-parametric test, no ci</span>
+0222    ci = [ab(1), ab(1); ab(2), ab(2)];
+0223 
+0224    <span class="comment">% could return to this later</span>
+0225    <span class="comment">%bootfun = @(x,y)(median(y)-median(x));</span>
+0226    <span class="comment">%bootci(100,bootfun(logx,logy))</span>
+0227 
+0228    <span class="comment">% generic failure check</span>
+0229    ok = all(isreal(ab));
+0230 <span class="keyword">end</span>
+0231 
+0232 <a name="_sub4" href="#_subfunctions" class="code">function [ab,ci,ok] = fitENV(logx,logy,order,refqtls,inoctave)</a>
+0233    <span class="comment">% force a line of slope 'order' through any two points 'refpoints' that</span>
+0234    <span class="comment">% together define an 'envelope'. default x refpoint is median(x). To control</span>
+0235    <span class="comment">% the vertical location of the line, set y refpoint higher or lower while</span>
+0236    <span class="comment">% keeping x refpoint constant.</span>
+0237 
+0238    <span class="comment">% note: require that quantiles are passed in rather than precomputed</span>
+0239    <span class="comment">% refpoints so this can use the log values or linear values</span>
 0240 
-0241 <a name="_sub4" href="#_subfunctions" class="code">function [ab,ci,ok] = fitENV(logx,logy,weights,order,refqtls,inoctave)</a>
-0242    <span class="comment">% force a line of slope 'order' through any two points 'refpoints' that</span>
-0243    <span class="comment">% together define an 'envelope'. default x refpoint is median(x). To control</span>
-0244    <span class="comment">% the vertical location of the line, set y refpoint higher or lower while</span>
-0245    <span class="comment">% keeping x refpoint constant.</span>
-0246 
-0247    <span class="comment">% note: require that quantiles are passed in rather than precomputed</span>
-0248    <span class="comment">% refpoints so this can use the log values or linear values</span>
-0249 
-0250    <span class="comment">% apply the mask / weights</span>
-0251    logx = logx(weights&gt;0);
-0252    logy = logy(weights&gt;0);
-0253    logx = order.*logx;
+0241    logx = order.*logx;
+0242 
+0243    <span class="comment">% force the line through the provided quantile</span>
+0244    <span class="keyword">if</span> inoctave
+0245       xbar = quantile(logx,refqtls(1),1,8);
+0246       ybar = quantile(logy,refqtls(2),1,8);
+0247    <span class="keyword">else</span>
+0248       xbar = quantile(logx,refqtls(1),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0249       ybar = quantile(logy,refqtls(2),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0250    <span class="keyword">end</span>
+0251 
+0252    <span class="comment">% note: mean(x-y) = mean(x)-mean(y)</span>
+0253    ab = [ exp(-(xbar-ybar)); order];
 0254 
-0255    <span class="comment">% force the line through the provided quantile</span>
-0256    <span class="keyword">if</span> inoctave
-0257       xbar = quantile(logx,refqtls(1),1,8);
-0258       ybar = quantile(logy,refqtls(2),1,8);
-0259    <span class="keyword">else</span>
-0260       xbar = quantile(logx,refqtls(1),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0261       ybar = quantile(logy,refqtls(2),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0262    <span class="keyword">end</span>
+0255    <span class="comment">% transpose ci to be consistent with stats functions</span>
+0256    ci = [nan nan; nan, nan];
+0257 
+0258    <span class="comment">% generic failure check</span>
+0259    ok = all(isreal(ab));
+0260 <span class="keyword">end</span>
+0261 
+0262 <a name="_sub5" href="#_subfunctions" class="code">function [ab,ci,ok] = fitQTL(logx,logy,alpha,order,qtl,Nboot,inoctave)</a>
 0263 
-0264    <span class="comment">% note: mean(x-y) = mean(x)-mean(y)</span>
-0265    ab = [ exp(-(xbar-ybar)); order];
-0266 
-0267    <span class="comment">% transpose ci to be consistent with stats functions</span>
-0268    ci = [nan nan; nan, nan];
-0269 
-0270    <span class="comment">% generic failure check</span>
-0271    ok = all(isreal(ab));
-0272 <span class="keyword">end</span>
-0273 
-0274 <a name="_sub5" href="#_subfunctions" class="code">function [ab,ci,ok] = fitQTL(logx,logy,weights,alpha,order,qtl,Nboot,inoctave)</a>
-0275 
-0276    <span class="comment">% quantile regression</span>
-0277    <span class="keyword">if</span> inoctave
-0278       error(<span class="string">'quantile regression not currently supported in octave, use nls'</span>)
-0279    <span class="keyword">end</span>
-0280 
-0281    <span class="keyword">if</span> isnan(qtl)
-0282       qtl = 0.05;
-0283    <span class="keyword">end</span>
-0284 
-0285    <span class="comment">% 'order' is the quantreg polynomial degree. The fitab parser default</span>
-0286    <span class="comment">% is nan, which crashes the quantreg indexing, so apply the quantreg</span>
-0287    <span class="comment">% default of 1 (a straight-line quantile fit).</span>
-0288    <span class="keyword">if</span> isnan(order)
-0289       order = 1;
-0290    <span class="keyword">end</span>
-0291 
-0292    <span class="comment">% apply the mask / weights</span>
-0293    logx = logx(weights&gt;0);
-0294    logy = logy(weights&gt;0);
+0264    <span class="comment">% quantile regression</span>
+0265    <span class="keyword">if</span> inoctave
+0266       error(<span class="string">'quantile regression not currently supported in octave, use nls'</span>)
+0267    <span class="keyword">end</span>
+0268 
+0269    <span class="keyword">if</span> isnan(qtl)
+0270       qtl = 0.05;
+0271    <span class="keyword">end</span>
+0272 
+0273    <span class="comment">% 'order' is the quantreg polynomial degree. The fitab parser default</span>
+0274    <span class="comment">% is nan, which crashes the quantreg indexing, so apply the quantreg</span>
+0275    <span class="comment">% default of 1 (a straight-line quantile fit).</span>
+0276    <span class="keyword">if</span> isnan(order)
+0277       order = 1;
+0278    <span class="keyword">end</span>
+0279 
+0280    <span class="comment">% fit a,b using quantile regression</span>
+0281    [ab,s] = quantreg(logx,logy,qtl,order,Nboot,1-alpha);
+0282 
+0283    <span class="comment">% transform a to linear space and package a/b</span>
+0284    ab = [exp(ab(1)); ab(2)];
+0285 
+0286    <span class="comment">% transpose ci to be consistent with stats functions</span>
+0287    ci = transpose(s.ci_boot);   <span class="comment">% comes in the same order as confint</span>
+0288    ci(1,:) = exp(ci(1,:));
+0289 
+0290    <span class="comment">% generic failure check</span>
+0291    ok = all(isreal(ab));
+0292 <span class="keyword">end</span>
+0293 
+0294 <a name="_sub6" href="#_subfunctions" class="code">function [ab,ci,ok] = fitMLE(logx,logy,~,alpha,sigx,sigy,rxy) </a><span class="comment">%#ok&lt;DEFNU&gt;</span>
 0295 
-0296    <span class="comment">% fit a,b using quantile regression</span>
-0297    [ab,s] = quantreg(logx,logy,qtl,order,Nboot,1-alpha);
-0298 
-0299    <span class="comment">% transform a to linear space and package a/b</span>
-0300    ab = [exp(ab(1)); ab(2)];
-0301 
-0302    <span class="comment">% transpose ci to be consistent with stats functions</span>
-0303    ci = transpose(s.ci_boot);   <span class="comment">% comes in the same order as confint</span>
-0304    ci(1,:) = exp(ci(1,:));
-0305 
-0306    <span class="comment">% generic failure check</span>
-0307    ok = all(isreal(ab));
-0308 <span class="keyword">end</span>
-0309 
-0310 <a name="_sub6" href="#_subfunctions" class="code">function [ab,ci,ok] = fitMLE(logx,logy,~,alpha,sigx,sigy,rxy) </a><span class="comment">%#ok&lt;DEFNU&gt;</span>
+0296    <span class="comment">% Set default values for maximum likelihood estimation</span>
+0297    <span class="keyword">if</span> nargin == 2
+0298       sigx     =  std(logx);       <span class="comment">% error in x</span>
+0299       sigy     =  std(logy);       <span class="comment">% error in y</span>
+0300       rxy      =  0;               <span class="comment">% correlation b/w error in x and y</span>
+0301       alpha    =  0.68;            <span class="comment">% confidence level</span>
+0302    <span class="keyword">end</span>
+0303 
+0304    <span class="comment">% fit</span>
+0305    [ab,s] = yorkfit(logx,logy,sigx,sigy,rxy,1-alpha);
+0306 
+0307    ab = [exp(ab(1)); ab(2)];
+0308 
+0309    <span class="comment">% transpose ci to be consistent with stats functions</span>
+0310    ci = [exp(s.a_L), exp(s.a_H); s.b_L, s.b_H];
 0311 
-0312    <span class="comment">% Set default values for maximum likelihood estimation</span>
-0313    <span class="keyword">if</span> nargin == 2
-0314       sigx     =  std(logx);       <span class="comment">% error in x</span>
-0315       sigy     =  std(logy);       <span class="comment">% error in y</span>
-0316       rxy      =  0;               <span class="comment">% correlation b/w error in x and y</span>
-0317       alpha    =  0.68;            <span class="comment">% confidence level</span>
-0318    <span class="keyword">end</span>
-0319 
-0320    <span class="comment">% fit</span>
-0321    [ab,s] = yorkfit(logx,logy,sigx,sigy,rxy,1-alpha);
-0322 
-0323    ab = [exp(ab(1)); ab(2)];
-0324 
-0325    <span class="comment">% transpose ci to be consistent with stats functions</span>
-0326    ci = [exp(s.a_L), exp(s.a_H); s.b_L, s.b_H];
-0327 
-0328    <span class="comment">% generic failure check</span>
-0329    ok = true;
-0330    <span class="keyword">if</span> any(~isreal(ab))
-0331       ok = false;
-0332    <span class="keyword">end</span>
-0333 <span class="keyword">end</span>
-0334 
-0335 <a name="_sub7" href="#_subfunctions" class="code">function [ab,ci,ok,fselect] = fitNLS(x,y,logx,logy,weights,alpha,inoctave)</a>
-0336 
-0337    <span class="keyword">if</span> inoctave
-0338       [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,weights,alpha);
-0339    <span class="keyword">else</span>
-0340       <span class="keyword">try</span>
-0341          [ab,ci,ok,fselect] = fitNLS_matlab(x,y,logx,logy,weights,alpha);
-0342       <span class="keyword">catch</span>
-0343          [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,weights,alpha);
-0344       <span class="keyword">end</span>
-0345    <span class="keyword">end</span>
-0346 <span class="keyword">end</span>
-0347 
-0348 <a name="_sub8" href="#_subfunctions" class="code">function [Fit,ok] = evalFit(ab,x,y,ci,ok)</a>
-0349 
-0350    <span class="comment">% ok is from the fitting function, passed in here but not used</span>
-0351    <span class="keyword">if</span> ok == false
-0352       <span class="comment">% error?</span>
-0353    <span class="keyword">end</span>
+0312    <span class="comment">% generic failure check</span>
+0313    ok = true;
+0314    <span class="keyword">if</span> any(~isreal(ab))
+0315       ok = false;
+0316    <span class="keyword">end</span>
+0317 <span class="keyword">end</span>
+0318 
+0319 <a name="_sub7" href="#_subfunctions" class="code">function [ab,ci,ok,fselect] = fitNLS(x,y,logx,logy,weights,alpha,inoctave)</a>
+0320 
+0321    <span class="keyword">if</span> inoctave
+0322       [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,weights,alpha);
+0323    <span class="keyword">else</span>
+0324       <span class="keyword">try</span>
+0325          [ab,ci,ok,fselect] = fitNLS_matlab(x,y,logx,logy,weights,alpha);
+0326       <span class="keyword">catch</span>
+0327          [ab,ci,ok,fselect] = fitNLS_octave(x,y,logx,logy,weights,alpha);
+0328       <span class="keyword">end</span>
+0329    <span class="keyword">end</span>
+0330 <span class="keyword">end</span>
+0331 
+0332 <a name="_sub8" href="#_subfunctions" class="code">function [Fit,ok] = evalFit(ab,x,y,ci,ok)</a>
+0333 
+0334    <span class="comment">% ok is from the fitting function, passed in here but not used</span>
+0335    <span class="keyword">if</span> ok == false
+0336       <span class="comment">% error?</span>
+0337    <span class="keyword">end</span>
+0338 
+0339    Fit.ab = ab;
+0340 
+0341    <span class="comment">% all ci's should already be transformed to this form:</span>
+0342    Fit.a = ab(1);
+0343    Fit.b = ab(2);
+0344    Fit.aL = ci(1,1);
+0345    Fit.aH = ci(1,2);
+0346    Fit.bL = ci(2,1);
+0347    Fit.bH = ci(2,2);
+0348 
+0349    Fit.rsq = baseflow.deps.rsquare(y,ab(1).*x.^ab(2));
+0350    Fit.pvalue = nan;
+0351    Fit.N = numel(y);
+0352    Fit.x = x;
+0353    Fit.y = y;
 0354 
-0355    Fit.ab = ab;
-0356 
-0357    <span class="comment">% all ci's should already be transformed to this form:</span>
-0358    Fit.a = ab(1);
-0359    Fit.b = ab(2);
-0360    Fit.aL = ci(1,1);
-0361    Fit.aH = ci(1,2);
-0362    Fit.bL = ci(2,1);
-0363    Fit.bH = ci(2,2);
-0364 
-0365    Fit.rsq = baseflow.deps.rsquare(y,ab(1).*x.^ab(2));
-0366    Fit.pvalue = nan;
-0367    Fit.N = numel(y);
-0368    Fit.x = x;
-0369    Fit.y = y;
-0370 
-0371    <span class="comment">% generic failure check</span>
-0372    ok = all(isreal(ab));
-0373 
-0374    <span class="comment">%    % any log-log regressions need the ci's transormed like this:</span>
-0375    <span class="comment">%    aL      = exp(ci(1,1)); % 95% CI</span>
-0376    <span class="comment">%    aH      = exp(ci(1,2));</span>
-0377    <span class="comment">%    bL      = ci(2,1);      % = betaL</span>
-0378    <span class="comment">%    bH      = ci(2,2);      % = betaH</span>
-0379 
-0380    <span class="comment">%    % any nlinfit regressions should already be in teh right order:</span>
-0381    <span class="comment">%    aL      = ci(1,1); % for confint: ci(1,1);</span>
-0382    <span class="comment">%    aH      = ci(1,2); % for confint: ci(2,1);</span>
-0383    <span class="comment">%    bL      = ci(2,1); % for confint: ci(1,2);</span>
-0384    <span class="comment">%    bH      = ci(2,2); % for confint: ci(2,2);</span>
-0385 
-0386    <span class="comment">% this does not work if robust fitting is used</span>
-0387    <span class="comment">%r2      = 1-sum(R.^2)/sum((y-mean(y)).^2); % for fit: gof.rsquare;</span>
-0388    <span class="comment">%figure; loglog(x,y,'o'); hold on; loglog(x,ab(1).*x.^ab(2))</span>
-0389 <span class="keyword">end</span>
-0390 
-0391 <span class="comment">%% INPUT PARSER</span>
-0392 <a name="_sub9" href="#_subfunctions" class="code">function [weights, order, mask, qtl, refqtls, Nboot, alpha, plotfit] = </a><span class="keyword">...</span>
-0393       parseinputs(q, dqdt, method, funcname, varargin)
-0394 
-0395    methodslist = {<span class="string">'nls'</span>,<span class="string">'ols'</span>,<span class="string">'mle'</span>,<span class="string">'qtl'</span>,<span class="string">'mean'</span>,<span class="string">'median'</span>,<span class="string">'envelope'</span>};
-0396    validmethod = @(x) any(validatestring(x, methodslist));
-0397 
-0398    <span class="keyword">persistent</span> parser
-0399    <span class="keyword">if</span> isempty(parser)
-0400       parser = inputParser;
-0401       parser.StructExpand = false;
-0402       parser.addRequired( <span class="string">'q'</span>,                          @isnumeric   );
-0403       parser.addRequired( <span class="string">'dqdt'</span>,                       @isnumeric   );
-0404       parser.addRequired( <span class="string">'method'</span>,                     validmethod  );
-0405       parser.addParameter(<span class="string">'weights'</span>,  1,                @isnumeric   );
-0406       parser.addParameter(<span class="string">'order'</span>,    nan,              @isnumeric   );
-0407       parser.addParameter(<span class="string">'mask'</span>,     1,                @islogical   );
-0408       parser.addParameter(<span class="string">'quantile'</span>, 0.05,             @isnumeric   );
-0409       parser.addParameter(<span class="string">'refqtls'</span>,  [0.50 0.50],      @isnumeric   );
-0410       parser.addParameter(<span class="string">'Nboot'</span>,    100,              @isnumeric   );
-0411       parser.addParameter(<span class="string">'alpha'</span>,    0.68,             @isnumeric   );
-0412       parser.addParameter(<span class="string">'plotfit'</span>,  false,            @islogical   );
-0413       parser.addParameter(<span class="string">'fitopts'</span>,  struct(),         @isstruct    );
-0414    <span class="keyword">end</span>
-0415    parser.FunctionName = funcname;
-0416    parse(parser,q,dqdt,method,varargin{:});
-0417 
-0418    weights  = parser.Results.weights;
-0419    order    = parser.Results.order;
-0420    mask     = parser.Results.mask;
-0421    qtl      = parser.Results.quantile;
-0422    refqtls  = parser.Results.refqtls;
-0423    Nboot    = parser.Results.Nboot;
-0424    alpha    = parser.Results.alpha;
-0425    plotfit  = parser.Results.plotfit;
-0426    fitopts  = parser.Results.fitopts;
-0427 
-0428    <span class="comment">% Override each same-named parameter with its fitopts field after a type</span>
-0429    <span class="comment">% check. fitevents passes this struct to fitab, so a caller can set the</span>
-0430    <span class="comment">% per-fit options once. fitab errors on an unknown field or a wrong type,</span>
-0431    <span class="comment">% so it never ignores a fitopts field.</span>
-0432    <span class="keyword">for</span> f = transpose(fieldnames(fitopts))
-0433       value = fitopts.(f{1});
-0434       <span class="keyword">switch</span> f{1}
-0435          <span class="keyword">case</span> <span class="string">'weights'</span>
+0355    <span class="comment">% generic failure check</span>
+0356    ok = all(isreal(ab));
+0357 
+0358    <span class="comment">%    % any log-log regressions need the ci's transormed like this:</span>
+0359    <span class="comment">%    aL      = exp(ci(1,1)); % 95% CI</span>
+0360    <span class="comment">%    aH      = exp(ci(1,2));</span>
+0361    <span class="comment">%    bL      = ci(2,1);      % = betaL</span>
+0362    <span class="comment">%    bH      = ci(2,2);      % = betaH</span>
+0363 
+0364    <span class="comment">%    % any nlinfit regressions should already be in teh right order:</span>
+0365    <span class="comment">%    aL      = ci(1,1); % for confint: ci(1,1);</span>
+0366    <span class="comment">%    aH      = ci(1,2); % for confint: ci(2,1);</span>
+0367    <span class="comment">%    bL      = ci(2,1); % for confint: ci(1,2);</span>
+0368    <span class="comment">%    bH      = ci(2,2); % for confint: ci(2,2);</span>
+0369 
+0370    <span class="comment">% this does not work if robust fitting is used</span>
+0371    <span class="comment">%r2      = 1-sum(R.^2)/sum((y-mean(y)).^2); % for fit: gof.rsquare;</span>
+0372    <span class="comment">%figure; loglog(x,y,'o'); hold on; loglog(x,ab(1).*x.^ab(2))</span>
+0373 <span class="keyword">end</span>
+0374 
+0375 <span class="comment">%% INPUT PARSER</span>
+0376 <a name="_sub9" href="#_subfunctions" class="code">function [weights, order, mask, qtl, refqtls, Nboot, alpha, plotfit] = </a><span class="keyword">...</span>
+0377       parseinputs(q, dqdt, method, funcname, varargin)
+0378 
+0379    methodslist = {<span class="string">'nls'</span>,<span class="string">'ols'</span>,<span class="string">'mle'</span>,<span class="string">'qtl'</span>,<span class="string">'mean'</span>,<span class="string">'median'</span>,<span class="string">'envelope'</span>};
+0380    validmethod = @(x) any(validatestring(x, methodslist));
+0381 
+0382    <span class="keyword">persistent</span> parser
+0383    <span class="keyword">if</span> isempty(parser)
+0384       parser = inputParser;
+0385       parser.StructExpand = false;
+0386       parser.addRequired( <span class="string">'q'</span>,                          @isnumeric   );
+0387       parser.addRequired( <span class="string">'dqdt'</span>,                       @isnumeric   );
+0388       parser.addRequired( <span class="string">'method'</span>,                     validmethod  );
+0389       parser.addParameter(<span class="string">'weights'</span>,  1,                @isnumeric   );
+0390       parser.addParameter(<span class="string">'order'</span>,    nan,              @isnumeric   );
+0391       parser.addParameter(<span class="string">'mask'</span>,     1,                @islogical   );
+0392       parser.addParameter(<span class="string">'quantile'</span>, 0.05,             @isnumeric   );
+0393       parser.addParameter(<span class="string">'refqtls'</span>,  [0.50 0.50],      @isnumeric   );
+0394       parser.addParameter(<span class="string">'Nboot'</span>,    100,              @isnumeric   );
+0395       parser.addParameter(<span class="string">'alpha'</span>,    0.68,             @isnumeric   );
+0396       parser.addParameter(<span class="string">'plotfit'</span>,  false,            @islogical   );
+0397       parser.addParameter(<span class="string">'fitopts'</span>,  struct(),         @isstruct    );
+0398    <span class="keyword">end</span>
+0399    parser.FunctionName = funcname;
+0400    parse(parser,q,dqdt,method,varargin{:});
+0401 
+0402    weights  = parser.Results.weights;
+0403    order    = parser.Results.order;
+0404    mask     = parser.Results.mask;
+0405    qtl      = parser.Results.quantile;
+0406    refqtls  = parser.Results.refqtls;
+0407    Nboot    = parser.Results.Nboot;
+0408    alpha    = parser.Results.alpha;
+0409    plotfit  = parser.Results.plotfit;
+0410    fitopts  = parser.Results.fitopts;
+0411 
+0412    <span class="comment">% Override each same-named parameter with its fitopts field after a type</span>
+0413    <span class="comment">% check. fitevents passes this struct to fitab, so a caller can set the</span>
+0414    <span class="comment">% per-fit options once. fitab errors on an unknown field or a wrong type,</span>
+0415    <span class="comment">% so it never ignores a fitopts field.</span>
+0416    <span class="keyword">for</span> f = transpose(fieldnames(fitopts))
+0417       value = fitopts.(f{1});
+0418       <span class="keyword">switch</span> f{1}
+0419          <span class="keyword">case</span> <span class="string">'weights'</span>
+0420             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
+0421                <span class="string">'fitopts.weights must be numeric'</span>);
+0422             weights = value;
+0423          <span class="keyword">case</span> <span class="string">'order'</span>
+0424             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
+0425                <span class="string">'fitopts.order must be numeric'</span>);
+0426             order = value;
+0427          <span class="keyword">case</span> <span class="string">'mask'</span>
+0428             assert(islogical(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
+0429                <span class="string">'fitopts.mask must be logical'</span>);
+0430             mask = value;
+0431          <span class="keyword">case</span> <span class="string">'quantile'</span>
+0432             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
+0433                <span class="string">'fitopts.quantile must be numeric'</span>);
+0434             qtl = value;
+0435          <span class="keyword">case</span> <span class="string">'refqtls'</span>
 0436             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0437                <span class="string">'fitopts.weights must be numeric'</span>);
-0438             weights = value;
-0439          <span class="keyword">case</span> <span class="string">'order'</span>
+0437                <span class="string">'fitopts.refqtls must be numeric'</span>);
+0438             refqtls = value;
+0439          <span class="keyword">case</span> <span class="string">'Nboot'</span>
 0440             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0441                <span class="string">'fitopts.order must be numeric'</span>);
-0442             order = value;
-0443          <span class="keyword">case</span> <span class="string">'mask'</span>
-0444             assert(islogical(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0445                <span class="string">'fitopts.mask must be logical'</span>);
-0446             mask = value;
-0447          <span class="keyword">case</span> <span class="string">'quantile'</span>
-0448             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0449                <span class="string">'fitopts.quantile must be numeric'</span>);
-0450             qtl = value;
-0451          <span class="keyword">case</span> <span class="string">'refqtls'</span>
-0452             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0453                <span class="string">'fitopts.refqtls must be numeric'</span>);
-0454             refqtls = value;
-0455          <span class="keyword">case</span> <span class="string">'Nboot'</span>
-0456             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0457                <span class="string">'fitopts.Nboot must be numeric'</span>);
-0458             Nboot = value;
-0459          <span class="keyword">case</span> <span class="string">'alpha'</span>
-0460             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0461                <span class="string">'fitopts.alpha must be numeric'</span>);
-0462             alpha = value;
-0463          <span class="keyword">case</span> <span class="string">'plotfit'</span>
-0464             assert(islogical(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
-0465                <span class="string">'fitopts.plotfit must be logical'</span>);
-0466             plotfit = value;
-0467          <span class="keyword">otherwise</span>
-0468             error(<span class="string">'baseflow:fitab:unknownFitopt'</span>, <span class="keyword">...</span>
-0469                [<span class="string">'unknown fitopts field %s; allowed: weights, order, '</span> <span class="keyword">...</span>
-0470                <span class="string">'mask, quantile, refqtls, Nboot, alpha, plotfit'</span>], f{1});
-0471       <span class="keyword">end</span>
-0472    <span class="keyword">end</span>
-0473 
-0474    <span class="comment">% Expand a scalar weight or mask to every point, because prepfits</span>
-0475    <span class="comment">% indexes both point by point. The parser default for mask is the</span>
-0476    <span class="comment">% numeric 1, so convert it to logical for prepfits.</span>
-0477    <span class="keyword">if</span> isscalar(weights)
-0478       weights = weights*ones(size(q));
-0479    <span class="keyword">end</span>
-0480 
-0481    <span class="keyword">if</span> isscalar(mask)
-0482       mask = repmat(logical(mask), size(q));
-0483    <span class="keyword">end</span>
-0484 
-0485    <span class="comment">% Fields that fitopts could hold later, by method (parked design notes):</span>
-0486    <span class="comment">% if method = 'qtl', fitopts.quantile, fitopts.Nboot</span>
-0487    <span class="comment">% if method = 'mle', fitopts.sigx, fitopts.sigy, fitopts.rxy</span>
-0488    <span class="comment">% for all methods, fitopts.order, fitopts.alpha, fitopts.</span>
-0489 
-0490 <span class="keyword">end</span></pre></div>
+0441                <span class="string">'fitopts.Nboot must be numeric'</span>);
+0442             Nboot = value;
+0443          <span class="keyword">case</span> <span class="string">'alpha'</span>
+0444             assert(isnumeric(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
+0445                <span class="string">'fitopts.alpha must be numeric'</span>);
+0446             alpha = value;
+0447          <span class="keyword">case</span> <span class="string">'plotfit'</span>
+0448             assert(islogical(value), <span class="string">'baseflow:fitab:invalidFitopt'</span>, <span class="keyword">...</span>
+0449                <span class="string">'fitopts.plotfit must be logical'</span>);
+0450             plotfit = value;
+0451          <span class="keyword">otherwise</span>
+0452             error(<span class="string">'baseflow:fitab:unknownFitopt'</span>, <span class="keyword">...</span>
+0453                [<span class="string">'unknown fitopts field %s; allowed: weights, order, '</span> <span class="keyword">...</span>
+0454                <span class="string">'mask, quantile, refqtls, Nboot, alpha, plotfit'</span>], f{1});
+0455       <span class="keyword">end</span>
+0456    <span class="keyword">end</span>
+0457 
+0458    <span class="comment">% 'mean', 'median', and 'envelope' fix the slope of the line. Without</span>
+0459    <span class="comment">% 'order' the slope is 1, the linear reservoir.</span>
+0460    <span class="keyword">if</span> isnan(order) &amp;&amp; any(strcmp(method, {<span class="string">'mean'</span>, <span class="string">'median'</span>, <span class="string">'envelope'</span>}))
+0461       order = 1;
+0462    <span class="keyword">end</span>
+0463 
+0464    <span class="comment">% Expand a scalar weight or mask to every point, because prepfits</span>
+0465    <span class="comment">% indexes both point by point. The parser default for mask is the</span>
+0466    <span class="comment">% numeric 1, so convert it to logical for prepfits.</span>
+0467    <span class="keyword">if</span> isscalar(weights)
+0468       weights = weights*ones(size(q));
+0469    <span class="keyword">end</span>
+0470 
+0471    <span class="keyword">if</span> isscalar(mask)
+0472       mask = repmat(logical(mask), size(q));
+0473    <span class="keyword">end</span>
+0474 
+0475    <span class="comment">% Fields that fitopts could hold later, by method (parked design notes):</span>
+0476    <span class="comment">% if method = 'qtl', fitopts.quantile, fitopts.Nboot</span>
+0477    <span class="comment">% if method = 'mle', fitopts.sigx, fitopts.sigy, fitopts.rxy</span>
+0478    <span class="comment">% for all methods, fitopts.order, fitopts.alpha, fitopts.</span>
+0479 
+0480 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/fitphidist.html b/toolbox/docs/html/m2html/+baseflow/fitphidist.html
index 9192692..234300a 100644
--- a/toolbox/docs/html/m2html/+baseflow/fitphidist.html
+++ b/toolbox/docs/html/m2html/+baseflow/fitphidist.html
@@ -56,6 +56,11 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      showfit is a logical flag (default true). With showfit false, these
      two types delete their figure. For 'pdf', h is an empty struct.
 
+     The beta fit uses the values of phi in [0, 1] and ignores nan.
+     fitphidist leaves a value outside [0, 1] out of the fit and raises
+     the warning baseflow:fitphidist:phiOutsideUnitInterval with the
+     count.
+
  See also: <a href="eventphi.html" class="code" title="function [phi, a] = eventphi(Results, Fits, A, D, L, blate, varargin)">eventphi</a>, <a href="fitphi.html" class="code" title="function [phi,solns,desc] = fitphi(a1,a2,b2,A,D,L,varargin)">fitphi</a>, <a href="fitphidist.html" class="code" title="function [Fit,h] = fitphidist(phi,varargin)">fitphidist</a>
 
  Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</pre></div>
@@ -116,174 +121,190 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0028    <span class="comment">%     showfit is a logical flag (default true). With showfit false, these</span>
 0029    <span class="comment">%     two types delete their figure. For 'pdf', h is an empty struct.</span>
 0030    <span class="comment">%</span>
-0031    <span class="comment">% See also: eventphi, fitphi, fitphidist</span>
-0032    <span class="comment">%</span>
-0033    <span class="comment">% Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</span>
-0034 
-0035    <span class="comment">% if called with no input, open this file</span>
-0036    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0037 
-0038    <span class="comment">% PARSE INPUTS</span>
-0039    [phi, outputtype, plottype, showfit] = <a href="#_sub3" class="code" title="subfunction [phi, outputtype, plottype, showfit] = parseinputs(phi, varargin)">parseinputs</a>(phi, varargin{:});
-0040 
-0041    <span class="comment">% Force all inputs to be column vectors</span>
-0042    phi = phi(:);
-0043 
-0044    <span class="comment">% Fit the beta distribution</span>
-0045    [PARAMHAT, PARAMCI] = betafit(phi);
-0046    [M, V] = betastat(PARAMHAT(1), PARAMHAT(2));
-0047    PD.paramEst = PARAMHAT;
-0048    PD.paramCI = PARAMCI;
-0049    PD.a = PARAMHAT(1);
-0050    PD.b = PARAMHAT(2);
-0051    PD.mean = M;
-0052    PD.std = sqrt(V);
-0053 
-0054    <span class="comment">% Create the figure</span>
-0055    <span class="keyword">switch</span> plottype
-0056       <span class="keyword">case</span> <span class="string">'cdf'</span>
-0057          h = <a href="#_sub1" class="code" title="subfunction h = cdfplotphi(phi, PD, showfit)">cdfplotphi</a>(phi, PD, showfit);
-0058       <span class="keyword">case</span> <span class="string">'probplot'</span>
-0059          h = <a href="#_sub2" class="code" title="subfunction h = probplotphi(phi, PD, showfit)">probplotphi</a>(phi, PD, showfit);
-0060       <span class="keyword">case</span> <span class="string">'pdf'</span>
-0061          <span class="comment">% 'pdf' draws no figure, so return an empty struct for h.</span>
-0062          h = struct();
-0063    <span class="keyword">end</span>
-0064 
-0065    <span class="comment">% package output</span>
-0066    <span class="keyword">switch</span> outputtype
-0067       <span class="keyword">case</span> <span class="string">'PD'</span>
-0068          <span class="comment">% send back the probability distribution</span>
-0069          Fit = PD;
-0070       <span class="keyword">case</span> <span class="string">'mean'</span>
-0071          <span class="comment">% send back the mean</span>
-0072          Fit = PD.mean;
-0073       <span class="keyword">case</span> <span class="string">'std'</span>
-0074          <span class="comment">% send back the mean</span>
-0075          Fit = PD.std;
-0076    <span class="keyword">end</span>
-0077 <span class="keyword">end</span>
-0078 
-0079 <a name="_sub1" href="#_subfunctions" class="code">function h = cdfplotphi(phi, PD, showfit)</a>
+0031    <span class="comment">%     The beta fit uses the values of phi in [0, 1] and ignores nan.</span>
+0032    <span class="comment">%     fitphidist leaves a value outside [0, 1] out of the fit and raises</span>
+0033    <span class="comment">%     the warning baseflow:fitphidist:phiOutsideUnitInterval with the</span>
+0034    <span class="comment">%     count.</span>
+0035    <span class="comment">%</span>
+0036    <span class="comment">% See also: eventphi, fitphi, fitphidist</span>
+0037    <span class="comment">%</span>
+0038    <span class="comment">% Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</span>
+0039 
+0040    <span class="comment">% if called with no input, open this file</span>
+0041    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0042 
+0043    <span class="comment">% PARSE INPUTS</span>
+0044    [phi, outputtype, plottype, showfit] = <a href="#_sub3" class="code" title="subfunction [phi, outputtype, plottype, showfit] = parseinputs(phi, varargin)">parseinputs</a>(phi, varargin{:});
+0045 
+0046    <span class="comment">% Force all inputs to be column vectors</span>
+0047    phi = phi(:);
+0048 
+0049    <span class="comment">% The beta distribution holds values in [0, 1], and a phi outside that</span>
+0050    <span class="comment">% interval is not a porosity. Leave those values out of the fit, and</span>
+0051    <span class="comment">% warn with their count so the caller knows the sample shrank.</span>
+0052    outside = phi &lt; 0 | phi &gt; 1;
+0053    <span class="keyword">if</span> any(outside)
+0054       warning(<span class="string">'baseflow:fitphidist:phiOutsideUnitInterval'</span>, <span class="keyword">...</span>
+0055          [<span class="string">'%d of %d values of phi lie outside [0, 1], so the beta fit '</span> <span class="keyword">...</span>
+0056          <span class="string">'leaves them out.'</span>], nnz(outside), numel(phi))
+0057       phi = phi(~outside);
+0058    <span class="keyword">end</span>
+0059 
+0060    <span class="comment">% Fit the beta distribution</span>
+0061    [PARAMHAT, PARAMCI] = betafit(phi);
+0062    [M, V] = betastat(PARAMHAT(1), PARAMHAT(2));
+0063    PD.paramEst = PARAMHAT;
+0064    PD.paramCI = PARAMCI;
+0065    PD.a = PARAMHAT(1);
+0066    PD.b = PARAMHAT(2);
+0067    PD.mean = M;
+0068    PD.std = sqrt(V);
+0069 
+0070    <span class="comment">% Create the figure</span>
+0071    <span class="keyword">switch</span> plottype
+0072       <span class="keyword">case</span> <span class="string">'cdf'</span>
+0073          h = <a href="#_sub1" class="code" title="subfunction h = cdfplotphi(phi, PD, showfit)">cdfplotphi</a>(phi, PD, showfit);
+0074       <span class="keyword">case</span> <span class="string">'probplot'</span>
+0075          h = <a href="#_sub2" class="code" title="subfunction h = probplotphi(phi, PD, showfit)">probplotphi</a>(phi, PD, showfit);
+0076       <span class="keyword">case</span> <span class="string">'pdf'</span>
+0077          <span class="comment">% 'pdf' draws no figure, so return an empty struct for h.</span>
+0078          h = struct();
+0079    <span class="keyword">end</span>
 0080 
-0081    <span class="comment">% Get the cdf</span>
-0082    [cdfY, cdfX] = ecdf(phi, <span class="string">'Function'</span>, <span class="string">'cdf'</span>);
-0083    
-0084    <span class="comment">% Create the figure</span>
-0085    h.figure = figure(<span class="string">'Visible'</span>, figurevisibility(showfit));
-0086    h.data = plot(cdfX, cdfY, <span class="string">'o'</span>, <span class="string">'MarkerFaceColor'</span>, [0 0.447 0.741], <span class="keyword">...</span>
-0087       <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Visible'</span>, showfit); hold on;
-0088 
-0089    <span class="comment">% Create grid where function will be computed</span>
-0090    XLims = get(gca, <span class="string">'XLim'</span>);
-0091    XLims = XLims + [-1 1] * 0.01 * diff(XLims);
-0092    XGrid = linspace(XLims(1), XLims(2), 100);
-0093 
-0094    <span class="comment">% plot the cdf</span>
-0095    phifit = betacdf(XGrid, PD.a, PD.b);
-0096    h.fit = plot(XGrid, phifit, <span class="string">'k'</span>);
-0097    set(gca, <span class="string">'XLim'</span>, [0 max(phi)])
-0098 
-0099    <span class="comment">% bootstrap standard error / CI's</span>
-0100    booterr = true;
-0101    N = 1000;
-0102    <span class="keyword">if</span> booterr == true
-0103       reps = bootstrp(N, @betafit, phi);
-0104       mureps = reps(:, 1) ./ (sum(reps, 2));
-0105       sigreps = sqrt(prod(reps, 2) ./ ((sum(reps, 2)+1) .* (sum(reps, 2)).^2));
-0106    <span class="keyword">end</span>
-0107 
-0108    <span class="comment">% this slightly overestimates the error, which is fine (conservative)</span>
-0109    mu = mean(mureps);
-0110    sg = mean(sigreps);
-0111    se = std(mureps); <span class="comment">% standard error of the mean of phi</span>
-0112    pm = se * 1.96; <span class="comment">% 95% half-width. or: mean(sigreps)/sqrt(N)*1.96</span>
-0113 
-0114    <span class="keyword">if</span> showfit == true &amp;&amp; ~isoctave
-0115       
-0116       <span class="comment">% compose legend text and arrow text</span>
-0117       ltxt = {<span class="string">'\phi'</span>, sprintf(<span class="string">'Beta (\\alpha=%.2f,\\beta=%.1f)'</span>, PD.a, PD.b)};
-0118       arrowtxt = sprintf(<span class="string">'\\langle\\phi\\rangle=%.3f\\pm%.3f'</span>, mu, round(pm, 3));
-0119 
-0120       <span class="comment">% add xlabel and legend</span>
-0121       xlabel(<span class="string">'x'</span>);
-0122       ylabel(<span class="string">'P(\phi \leq x)'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
-0123       
-0124       xarrow = [PD.mean 1.3*PD.mean];
-0125       yarrow = [betacdf(PD.mean, PD.a, PD.b) betacdf(PD.mean, PD.a, PD.b)];
-0126       <span class="comment">% the head points left, at the mean, from a tail to its right</span>
-0127       drawarrow(gca, [xarrow(2), yarrow(2)], [xarrow(1), yarrow(1)]);
-0128       text(0.95*xarrow(2), yarrow(2), arrowtxt, <span class="string">'HorizontalAlignment'</span>,<span class="string">'left'</span>)
+0081    <span class="comment">% package output</span>
+0082    <span class="keyword">switch</span> outputtype
+0083       <span class="keyword">case</span> <span class="string">'PD'</span>
+0084          <span class="comment">% send back the probability distribution</span>
+0085          Fit = PD;
+0086       <span class="keyword">case</span> <span class="string">'mean'</span>
+0087          <span class="comment">% send back the mean</span>
+0088          Fit = PD.mean;
+0089       <span class="keyword">case</span> <span class="string">'std'</span>
+0090          <span class="comment">% send back the mean</span>
+0091          Fit = PD.std;
+0092    <span class="keyword">end</span>
+0093 <span class="keyword">end</span>
+0094 
+0095 <a name="_sub1" href="#_subfunctions" class="code">function h = cdfplotphi(phi, PD, showfit)</a>
+0096 
+0097    <span class="comment">% Get the cdf</span>
+0098    [cdfY, cdfX] = ecdf(phi, <span class="string">'Function'</span>, <span class="string">'cdf'</span>);
+0099    
+0100    <span class="comment">% Create the figure</span>
+0101    h.figure = figure(<span class="string">'Visible'</span>, figurevisibility(showfit));
+0102    h.data = plot(cdfX, cdfY, <span class="string">'o'</span>, <span class="string">'MarkerFaceColor'</span>, [0 0.447 0.741], <span class="keyword">...</span>
+0103       <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Visible'</span>, showfit); hold on;
+0104 
+0105    <span class="comment">% Create grid where function will be computed</span>
+0106    XLims = get(gca, <span class="string">'XLim'</span>);
+0107    XLims = XLims + [-1 1] * 0.01 * diff(XLims);
+0108    XGrid = linspace(XLims(1), XLims(2), 100);
+0109 
+0110    <span class="comment">% plot the cdf</span>
+0111    phifit = betacdf(XGrid, PD.a, PD.b);
+0112    h.fit = plot(XGrid, phifit, <span class="string">'k'</span>);
+0113    set(gca, <span class="string">'XLim'</span>, [0 max(phi)])
+0114 
+0115    <span class="comment">% bootstrap standard error / CI's</span>
+0116    booterr = true;
+0117    N = 1000;
+0118    <span class="keyword">if</span> booterr == true
+0119       reps = bootstrp(N, @betafit, phi);
+0120       mureps = reps(:, 1) ./ (sum(reps, 2));
+0121       sigreps = sqrt(prod(reps, 2) ./ ((sum(reps, 2)+1) .* (sum(reps, 2)).^2));
+0122    <span class="keyword">end</span>
+0123 
+0124    <span class="comment">% this slightly overestimates the error, which is fine (conservative)</span>
+0125    mu = mean(mureps);
+0126    sg = mean(sigreps);
+0127    se = std(mureps); <span class="comment">% standard error of the mean of phi</span>
+0128    pm = se * 1.96; <span class="comment">% 95% half-width. or: mean(sigreps)/sqrt(N)*1.96</span>
 0129 
-0130       h.legend = legend(ltxt, <span class="string">'Location'</span>, <span class="string">'east'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
-0131       h.legend.Position(2) = 0.68*h.legend.Position(2);
-0132       h.legend.Position(1) = 0.85*h.legend.Position(1);
-0133    <span class="keyword">end</span>
-0134 
-0135    h.ax = gca;
-0136    h.mu = mu;
-0137    h.pm = pm;
-0138    h.se = se;
-0139 
-0140    <span class="comment">% The bootstrap standard error above needs the fit, but a caller with</span>
-0141    <span class="comment">% showfit false wants no figure. Delete the hidden figure, so repeated</span>
-0142    <span class="comment">% calls from phifitensemble and globalfit do not leave figures open.</span>
-0143    <span class="keyword">if</span> showfit == false
-0144       delete(h.figure)
-0145    <span class="keyword">end</span>
-0146 <span class="keyword">end</span>
-0147 
-0148 <a name="_sub2" href="#_subfunctions" class="code">function h = probplotphi(phi, PD, showfit)</a>
-0149 
-0150    <span class="keyword">if</span> isoctave
-0151       error([mfilename <span class="string">': probplot not implemented in Octave. Use ''cdf''.'</span>])
-0152    <span class="keyword">end</span>
-0153 
-0154    <span class="comment">% Create the figure. It is hidden when showfit is false.</span>
-0155    h.figure = figure(<span class="string">'Visible'</span>, figurevisibility(showfit));
-0156 
-0157    <span class="comment">% plot the data, suppressing the normal plot with 'noref'</span>
-0158    h.data = probplot(<span class="string">'normal'</span>, phi, [], [], <span class="string">'noref'</span>); hold on;
-0159 
-0160    <span class="comment">% add the fit. probplot needs a distribution object, and PD is a struct</span>
-0161    <span class="comment">% of the fitted beta parameters, so build the beta distribution.</span>
-0162    h.fit = probplot(gca, makedist(<span class="string">'Beta'</span>, <span class="string">'a'</span>, PD.a, <span class="string">'b'</span>, PD.b));
+0130    <span class="keyword">if</span> showfit == true &amp;&amp; ~isoctave
+0131       
+0132       <span class="comment">% compose legend text and arrow text</span>
+0133       ltxt = {<span class="string">'\phi'</span>, sprintf(<span class="string">'Beta (\\alpha=%.2f,\\beta=%.1f)'</span>, PD.a, PD.b)};
+0134       arrowtxt = sprintf(<span class="string">'\\langle\\phi\\rangle=%.3f\\pm%.3f'</span>, mu, round(pm, 3));
+0135 
+0136       <span class="comment">% add xlabel and legend</span>
+0137       xlabel(<span class="string">'x'</span>);
+0138       ylabel(<span class="string">'P(\phi \leq x)'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
+0139       
+0140       xarrow = [PD.mean 1.3*PD.mean];
+0141       yarrow = [betacdf(PD.mean, PD.a, PD.b) betacdf(PD.mean, PD.a, PD.b)];
+0142       <span class="comment">% the head points left, at the mean, from a tail to its right</span>
+0143       drawarrow(gca, [xarrow(2), yarrow(2)], [xarrow(1), yarrow(1)]);
+0144       text(0.95*xarrow(2), yarrow(2), arrowtxt, <span class="string">'HorizontalAlignment'</span>,<span class="string">'left'</span>)
+0145 
+0146       h.legend = legend(ltxt, <span class="string">'Location'</span>, <span class="string">'east'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
+0147       h.legend.Position(2) = 0.68*h.legend.Position(2);
+0148       h.legend.Position(1) = 0.85*h.legend.Position(1);
+0149    <span class="keyword">end</span>
+0150 
+0151    h.ax = gca;
+0152    h.mu = mu;
+0153    h.pm = pm;
+0154    h.se = se;
+0155 
+0156    <span class="comment">% The bootstrap standard error above needs the fit, but a caller with</span>
+0157    <span class="comment">% showfit false wants no figure. Delete the hidden figure, so repeated</span>
+0158    <span class="comment">% calls from phifitensemble and globalfit do not leave figures open.</span>
+0159    <span class="keyword">if</span> showfit == false
+0160       delete(h.figure)
+0161    <span class="keyword">end</span>
+0162 <span class="keyword">end</span>
 0163 
-0164    <span class="comment">% format the symbols</span>
-0165    c  = [0 0.447 0.741];
-0166    set(h.data, <span class="string">'MarkerFaceColor'</span>, c, <span class="string">'Marker'</span>, <span class="string">'o'</span>, <span class="string">'MarkerSize'</span>, 6, <span class="keyword">...</span>
-0167       <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>);
-0168    set(h.fit, <span class="string">'Color'</span>, <span class="string">'k'</span>, <span class="string">'LineStyle'</span>, <span class="string">'-'</span>, <span class="string">'LineWidth'</span>, 2);
+0164 <a name="_sub2" href="#_subfunctions" class="code">function h = probplotphi(phi, PD, showfit)</a>
+0165 
+0166    <span class="keyword">if</span> isoctave
+0167       error([mfilename <span class="string">': probplot not implemented in Octave. Use ''cdf''.'</span>])
+0168    <span class="keyword">end</span>
 0169 
-0170    ylabel(<span class="string">'P(\phi\leq x)'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
-0171    title(<span class="string">''</span>)
-0172    set(gca, <span class="string">'XLim'</span>, [0 0.2])
-0173    h.ax = gca;
-0174 
-0175    <span class="comment">% A caller with showfit false wants no figure, so delete the hidden</span>
-0176    <span class="comment">% figure, as cdfplotphi does.</span>
-0177    <span class="keyword">if</span> showfit == false
-0178       delete(h.figure)
-0179    <span class="keyword">end</span>
-0180 <span class="keyword">end</span>
-0181 
-0182 <span class="comment">%% INPUT PARSER</span>
-0183 <a name="_sub3" href="#_subfunctions" class="code">function [phi, outputtype, plottype, showfit] = parseinputs(phi, varargin)</a>
-0184 
-0185    validoutput = @(x) any(validatestring(x, {<span class="string">'PD'</span>, <span class="string">'mean'</span>, <span class="string">'std'</span>}));
-0186    validplottype = @(x) any(validatestring(x, {<span class="string">'cdf'</span>, <span class="string">'pdf'</span>, <span class="string">'probplot'</span>}));
-0187 
-0188    parser = inputParser;
-0189    parser.FunctionName = <span class="string">'baseflow.fitphidist'</span>;
-0190    parser.addRequired(<span class="string">'phi'</span>, @isvector);
-0191    parser.addOptional(<span class="string">'outputtype'</span>, <span class="string">'PD'</span>, validoutput);
-0192    parser.addOptional(<span class="string">'plottype'</span>, <span class="string">'none'</span>, validplottype);
-0193    parser.addOptional(<span class="string">'showfit'</span>, true, @islogical);
-0194    parser.parse(phi, varargin{:});
-0195 
-0196    outputtype = parser.Results.outputtype;
-0197    plottype = parser.Results.plottype;
-0198    showfit = parser.Results.showfit;
-0199 <span class="keyword">end</span></pre></div>
+0170    <span class="comment">% Create the figure. It is hidden when showfit is false.</span>
+0171    h.figure = figure(<span class="string">'Visible'</span>, figurevisibility(showfit));
+0172 
+0173    <span class="comment">% plot the data, suppressing the normal plot with 'noref'</span>
+0174    h.data = probplot(<span class="string">'normal'</span>, phi, [], [], <span class="string">'noref'</span>); hold on;
+0175 
+0176    <span class="comment">% add the fit. probplot needs a distribution object, and PD is a struct</span>
+0177    <span class="comment">% of the fitted beta parameters, so build the beta distribution.</span>
+0178    h.fit = probplot(gca, makedist(<span class="string">'Beta'</span>, <span class="string">'a'</span>, PD.a, <span class="string">'b'</span>, PD.b));
+0179 
+0180    <span class="comment">% format the symbols</span>
+0181    c  = [0 0.447 0.741];
+0182    set(h.data, <span class="string">'MarkerFaceColor'</span>, c, <span class="string">'Marker'</span>, <span class="string">'o'</span>, <span class="string">'MarkerSize'</span>, 6, <span class="keyword">...</span>
+0183       <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>);
+0184    set(h.fit, <span class="string">'Color'</span>, <span class="string">'k'</span>, <span class="string">'LineStyle'</span>, <span class="string">'-'</span>, <span class="string">'LineWidth'</span>, 2);
+0185 
+0186    ylabel(<span class="string">'P(\phi\leq x)'</span>, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
+0187    title(<span class="string">''</span>)
+0188    set(gca, <span class="string">'XLim'</span>, [0 0.2])
+0189    h.ax = gca;
+0190 
+0191    <span class="comment">% A caller with showfit false wants no figure, so delete the hidden</span>
+0192    <span class="comment">% figure, as cdfplotphi does.</span>
+0193    <span class="keyword">if</span> showfit == false
+0194       delete(h.figure)
+0195    <span class="keyword">end</span>
+0196 <span class="keyword">end</span>
+0197 
+0198 <span class="comment">%% INPUT PARSER</span>
+0199 <a name="_sub3" href="#_subfunctions" class="code">function [phi, outputtype, plottype, showfit] = parseinputs(phi, varargin)</a>
+0200 
+0201    validoutput = @(x) any(validatestring(x, {<span class="string">'PD'</span>, <span class="string">'mean'</span>, <span class="string">'std'</span>}));
+0202    validplottype = @(x) any(validatestring(x, {<span class="string">'cdf'</span>, <span class="string">'pdf'</span>, <span class="string">'probplot'</span>}));
+0203 
+0204    parser = inputParser;
+0205    parser.FunctionName = <span class="string">'baseflow.fitphidist'</span>;
+0206    parser.addRequired(<span class="string">'phi'</span>, @isvector);
+0207    parser.addOptional(<span class="string">'outputtype'</span>, <span class="string">'PD'</span>, validoutput);
+0208    parser.addOptional(<span class="string">'plottype'</span>, <span class="string">'none'</span>, validplottype);
+0209    parser.addOptional(<span class="string">'showfit'</span>, true, @islogical);
+0210    parser.parse(phi, varargin{:});
+0211 
+0212    outputtype = parser.Results.outputtype;
+0213    plottype = parser.Results.plottype;
+0214    showfit = parser.Results.showfit;
+0215 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/generateTestData.html b/toolbox/docs/html/m2html/+baseflow/generateTestData.html
index 52b0f32..198caa7 100644
--- a/toolbox/docs/html/m2html/+baseflow/generateTestData.html
+++ b/toolbox/docs/html/m2html/+baseflow/generateTestData.html
@@ -122,36 +122,31 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0048 
 0049    t = t(:);
 0050 
-0051    <span class="keyword">switch</span> b
-0052       <span class="keyword">case</span> 1
-0053          q = q0.*exp(-a.*t);
-0054          dqdt = -a.*q;
-0055          <span class="comment">%q = (q(1:end)+q(2:end-1))./2;</span>
-0056          <span class="comment">%dqdt = diff(q);</span>
-0057       <span class="keyword">otherwise</span>
-0058          [q,dqdt,t] = baseflow.Qnonlin(a,b,q0,t,false); <span class="comment">% false = don't make fig</span>
-0059    <span class="keyword">end</span>
-0060 <span class="keyword">end</span>
-0061 
-0062 <span class="comment">% % this was in baseflow.test suite ParameterizedTestBfra. I am not certain why</span>
-0063 <span class="comment">% the data falls off, could be the noise I add, or could be the lack of a</span>
-0064 <span class="comment">% negative sign on in genCurveData</span>
-0065 <span class="comment">% for a linear model (exponential), Q = Q0*exp(-at), meaning</span>
-0066 <span class="comment">%</span>
-0067 <span class="comment">% for the linear case:</span>
-0068 <span class="comment">% data = genCurveData('exponential');</span>
-0069 <span class="comment">% a = 1e-2;</span>
-0070 <span class="comment">% q = data.y;</span>
-0071 <span class="comment">% dqdt = -a.*q;</span>
-0072 <span class="comment">% figure; semilogy(-dqdt,q,'o')</span>
-0073 <span class="comment">%</span>
-0074 <span class="comment">%</span>
-0075 <span class="comment">% for the nonlinear case:</span>
-0076 <span class="comment">% data = genCurveData('power');</span>
-0077 <span class="comment">% q = data.y;</span>
-0078 <span class="comment">% dqdt = -data.x;</span>
-0079 <span class="comment">% figure; loglog(-dqdt,q,'o')</span>
-0080 <span class="comment">% [x,y,logx,logy] = baseflow.prepfits(q,dqdt);</span>
-0081 <span class="comment">% Fit = baseflow.fitab(logx,logy,'nls');</span></pre></div>
+0051    <span class="comment">% Qnonlin covers every b, including the exponential case b = 1</span>
+0052    <span class="comment">%q = (q(1:end)+q(2:end-1))./2;</span>
+0053    <span class="comment">%dqdt = diff(q);</span>
+0054    [q,dqdt,t] = baseflow.Qnonlin(a,b,q0,t,false); <span class="comment">% false = don't make fig</span>
+0055 <span class="keyword">end</span>
+0056 
+0057 <span class="comment">% % this was in baseflow.test suite ParameterizedTestBfra. I am not certain why</span>
+0058 <span class="comment">% the data falls off, could be the noise I add, or could be the lack of a</span>
+0059 <span class="comment">% negative sign on in genCurveData</span>
+0060 <span class="comment">% for a linear model (exponential), Q = Q0*exp(-at), meaning</span>
+0061 <span class="comment">%</span>
+0062 <span class="comment">% for the linear case:</span>
+0063 <span class="comment">% data = genCurveData('exponential');</span>
+0064 <span class="comment">% a = 1e-2;</span>
+0065 <span class="comment">% q = data.y;</span>
+0066 <span class="comment">% dqdt = -a.*q;</span>
+0067 <span class="comment">% figure; semilogy(-dqdt,q,'o')</span>
+0068 <span class="comment">%</span>
+0069 <span class="comment">%</span>
+0070 <span class="comment">% for the nonlinear case:</span>
+0071 <span class="comment">% data = genCurveData('power');</span>
+0072 <span class="comment">% q = data.y;</span>
+0073 <span class="comment">% dqdt = -data.x;</span>
+0074 <span class="comment">% figure; loglog(-dqdt,q,'o')</span>
+0075 <span class="comment">% [x,y,logx,logy] = baseflow.prepfits(q,dqdt);</span>
+0076 <span class="comment">% Fit = baseflow.fitab(logx,logy,'nls');</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/getfunction.html b/toolbox/docs/html/m2html/+baseflow/getfunction.html
index ba91af1..8a04abc 100644
--- a/toolbox/docs/html/m2html/+baseflow/getfunction.html
+++ b/toolbox/docs/html/m2html/+baseflow/getfunction.html
@@ -41,6 +41,12 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      Fnc = baseflow.getfunction('expectedQ') returns anonymous function
      handle for expected value of baseflow function Q(Q0,b) = Q0*(2-b)/(3-b)
 
+     Fnc = baseflow.getfunction('expectedTau') returns a function handle
+     for the mean tau, tau(tau0,b) = tau0*(2-b)/(3-2*b). The mean diverges
+     at the tau pole b = 3/2 (alpha = 2) and beyond, so the handle returns
+     Inf there. It returns NaN where no Pareto tail exists (b &lt; 1 or
+     b &gt;= 2). The 'expectedTime' handle, tau0/(3-2*b), shares that pole.
+
      Use tab-completion to see full list of options
 
  See also: baseflow.<a href="getstring.html" class="code" title="function str = getstring(request, varargin)">getstring</a>
@@ -83,35 +89,42 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0013    <span class="comment">%     Fnc = baseflow.getfunction('expectedQ') returns anonymous function</span>
 0014    <span class="comment">%     handle for expected value of baseflow function Q(Q0,b) = Q0*(2-b)/(3-b)</span>
 0015    <span class="comment">%</span>
-0016    <span class="comment">%     Use tab-completion to see full list of options</span>
-0017    <span class="comment">%</span>
-0018    <span class="comment">% See also: baseflow.getstring</span>
-0019    <span class="comment">%</span>
-0020    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0021 
-0022    <span class="comment">% if called with no input, open this file</span>
-0023    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0024 
-0025    <span class="keyword">switch</span> funcname
-0026       <span class="keyword">case</span> <span class="string">'SofabQ'</span>
-0027          Fnc = @(a,b,Q) (1./(a.*(2-b))).*Q.^(2-b);
-0028       <span class="keyword">case</span> <span class="string">'tauofabQ'</span>
-0029          Fnc = @(a,b,Q) (1./a).*Q.^(1-b);
-0030       <span class="keyword">case</span> <span class="string">'tauofabQ0'</span>
-0031          Fnc = @(a,b,Q0) (1./a).*Q0.^(1-b);
-0032       <span class="keyword">case</span> <span class="string">'Qofabtau'</span>
-0033          Fnc = @(a,b,tau) (a.*tau).^(1./(1-b));
-0034       <span class="keyword">case</span> <span class="string">'expectedQ'</span>
-0035          Fnc = @(Q0,b) Q0.*(2-b)./(3-b);  <span class="comment">% expected value of Q</span>
-0036       <span class="keyword">case</span> <span class="string">'expectedTau'</span>
-0037          Fnc = @(tau0,b) tau0.*(2-b)./(3-2.*b);  <span class="comment">% expected value of tau</span>
-0038       <span class="keyword">case</span> <span class="string">'expectedTime'</span>
-0039          Fnc = @(tau0,b) tau0./(3-2.*b);  <span class="comment">% expected duration of baseflow</span>
-0040       <span class="keyword">case</span> <span class="string">'boftautau0'</span>
-0041          Fnc = @(tau,tau0) (2*(tau-tau0)+tau)/(2*(tau-tau0)+tau0);
-0042       <span class="keyword">case</span> <span class="string">'aofa0'</span>
-0043          Fnc = @(a0,b,tau,tau0) (1/tau)*(sqrt(a0*tau0)*(b-3)/(b-2))^(b-1);
-0044    <span class="keyword">end</span>
-0045 <span class="keyword">end</span></pre></div>
+0016    <span class="comment">%     Fnc = baseflow.getfunction('expectedTau') returns a function handle</span>
+0017    <span class="comment">%     for the mean tau, tau(tau0,b) = tau0*(2-b)/(3-2*b). The mean diverges</span>
+0018    <span class="comment">%     at the tau pole b = 3/2 (alpha = 2) and beyond, so the handle returns</span>
+0019    <span class="comment">%     Inf there. It returns NaN where no Pareto tail exists (b &lt; 1 or</span>
+0020    <span class="comment">%     b &gt;= 2). The 'expectedTime' handle, tau0/(3-2*b), shares that pole.</span>
+0021    <span class="comment">%</span>
+0022    <span class="comment">%     Use tab-completion to see full list of options</span>
+0023    <span class="comment">%</span>
+0024    <span class="comment">% See also: baseflow.getstring</span>
+0025    <span class="comment">%</span>
+0026    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0027 
+0028    <span class="comment">% if called with no input, open this file</span>
+0029    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0030 
+0031    <span class="keyword">switch</span> funcname
+0032       <span class="keyword">case</span> <span class="string">'SofabQ'</span>
+0033          Fnc = @(a,b,Q) (1./(a.*(2-b))).*Q.^(2-b);
+0034       <span class="keyword">case</span> <span class="string">'tauofabQ'</span>
+0035          Fnc = @(a,b,Q) (1./a).*Q.^(1-b);
+0036       <span class="keyword">case</span> <span class="string">'tauofabQ0'</span>
+0037          Fnc = @(a,b,Q0) (1./a).*Q0.^(1-b);
+0038       <span class="keyword">case</span> <span class="string">'Qofabtau'</span>
+0039          Fnc = @(a,b,tau) (a.*tau).^(1./(1-b));
+0040       <span class="keyword">case</span> <span class="string">'expectedQ'</span>
+0041          Fnc = @(Q0,b) Q0.*(2-b)./(3-b);  <span class="comment">% expected value of Q</span>
+0042       <span class="keyword">case</span> <span class="string">'expectedTau'</span>
+0043          Fnc = @expectedtau;  <span class="comment">% expected value of tau</span>
+0044       <span class="keyword">case</span> <span class="string">'expectedTime'</span>
+0045          <span class="comment">% expected duration of baseflow, tau0/(3-2*b), with the tau pole</span>
+0046          Fnc = @(tau0,b) expectedtau(tau0,b)./(2-b);
+0047       <span class="keyword">case</span> <span class="string">'boftautau0'</span>
+0048          Fnc = @(tau,tau0) (2.*(tau-tau0)+tau)./(2.*(tau-tau0)+tau0);
+0049       <span class="keyword">case</span> <span class="string">'aofa0'</span>
+0050          Fnc = @(a0,b,tau,tau0) (1./tau).*(sqrt(a0.*tau0).*(b-3)./(b-2)).^(b-1);
+0051    <span class="keyword">end</span>
+0052 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/globalfit.html b/toolbox/docs/html/m2html/+baseflow/globalfit.html
index 6e18bb4..3e4f8e7 100644
--- a/toolbox/docs/html/m2html/+baseflow/globalfit.html
+++ b/toolbox/docs/html/m2html/+baseflow/globalfit.html
@@ -193,7 +193,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0097             <span class="string">'lateqtls'</span>, lateqtls, <span class="string">'earlyqtls'</span>, earlyqtls);
 0098          phi2 = baseflow.eventphi(Results, Fits, A, D, L, 3/2, <span class="keyword">...</span>
 0099             <span class="string">'lateqtls'</span>, lateqtls, <span class="string">'earlyqtls'</span>, earlyqtls);
-0100          phid = vertcat(phi1, phi2); phid(phid&gt;1) = nan; phid(phid&lt;0) = nan;
+0100          phid = vertcat(phi1, phi2);
 0101          phi = baseflow.fitphidist(phid, <span class="string">'mean'</span>, <span class="string">'cdf'</span>, plotfits);
 0102    <span class="keyword">end</span>
 0103 
@@ -249,7 +249,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0153    parser.addRequired(<span class="string">'Events'</span>, @isstruct);
 0154    parser.addRequired(<span class="string">'Fits'</span>, @isstruct);
 0155    parser.addParameter(<span class="string">'drainagearea'</span>, nan, @isnumericscalar);
-0156    parser.addParameter(<span class="string">'drainagedensity'</span>, 0.8, @isnumericscalar);
+0156    parser.addParameter(<span class="string">'drainagedensity'</span>, nan, @isnumericscalar);
 0157    parser.addParameter(<span class="string">'aquiferdepth'</span>, nan, @isnumericscalar);
 0158    parser.addParameter(<span class="string">'streamlength'</span>, nan, @isnumericscalar);
 0159    parser.addParameter(<span class="string">'aquiferslope'</span>, 0, @isnumericscalar);
@@ -285,16 +285,19 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0189    <span class="comment">% if stream length and drainage density are both provided, check that they</span>
 0190    <span class="comment">% are consistent with the provided area. note: Dd comes in as 1/km b/c that's</span>
 0191    <span class="comment">% how it is almost always reported (km/km2). divide by 1000 to get 1/m.</span>
-0192    <span class="keyword">if</span> ~isnan(Dd) &amp;&amp; ~isnan(L)
-0193       <span class="keyword">if</span> Dd/1000*A ~= L        <span class="comment">% 1/m * m^2 = m</span>
-0194          warning( <span class="keyword">...</span>
-0195             <span class="string">'provided streamlength, L, inconsistent with L=A*Dd. Using L=A*Dd'</span>);
-0196          L = Dd/1000*A;
-0197       <span class="keyword">end</span>
-0198    <span class="keyword">end</span>
-0199 
-0200    <span class="comment">% take values out of the data structures that are needed</span>
-0201    Q = Events.inputFlow;       <span class="comment">% daily streamflow [m3 d-1]</span>
-0202 <span class="keyword">end</span></pre></div>
+0192    <span class="comment">% Both default to nan, so a default never replaces a provided L. The</span>
+0193    <span class="comment">% relative tolerance accepts the rounding of L = A*Dd/1000 computed in</span>
+0194    <span class="comment">% another order.</span>
+0195    <span class="keyword">if</span> ~isnan(Dd) &amp;&amp; ~isnan(L)
+0196       <span class="keyword">if</span> abs(Dd/1000*A - L) &gt; sqrt(eps)*L        <span class="comment">% 1/m * m^2 = m</span>
+0197          warning(<span class="string">'baseflow:globalfit:inconsistentStreamlength'</span>, <span class="keyword">...</span>
+0198             <span class="string">'provided streamlength, L, inconsistent with L=A*Dd. Using L=A*Dd'</span>);
+0199          L = Dd/1000*A;
+0200       <span class="keyword">end</span>
+0201    <span class="keyword">end</span>
+0202 
+0203    <span class="comment">% take values out of the data structures that are needed</span>
+0204    Q = Events.inputFlow;       <span class="comment">% daily streamflow [m3 d-1]</span>
+0205 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/gpfitb.html b/toolbox/docs/html/m2html/+baseflow/gpfitb.html
index 42d1379..269670e 100644
--- a/toolbox/docs/html/m2html/+baseflow/gpfitb.html
+++ b/toolbox/docs/html/m2html/+baseflow/gpfitb.html
@@ -45,6 +45,12 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      [Fit,b,alpha,k] = gpfitb(x,'xmin',xmin) subtracts user-provided xmin
      from data in x. xmin is the threshold parameter.
 
+     Fit.tauExp is the mean tau of the fitted Pareto tail, with bounds
+     tauExpL and tauExpH. The mean diverges at or below the tau pole at
+     alpha = 2, so a value there is Inf, or NaN without a Pareto tail.
+     gpfitb then warns with baseflow:expectedtau:tauPole, and the plot
+     label omits the mean tau.
+
  Example
 
   Sample a Pareto distribution with tau0 = 20 days and b = 1.4, then
@@ -102,243 +108,256 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0017    <span class="comment">%     [Fit,b,alpha,k] = gpfitb(x,'xmin',xmin) subtracts user-provided xmin</span>
 0018    <span class="comment">%     from data in x. xmin is the threshold parameter.</span>
 0019    <span class="comment">%</span>
-0020    <span class="comment">% Example</span>
-0021    <span class="comment">%</span>
-0022    <span class="comment">%  Sample a Pareto distribution with tau0 = 20 days and b = 1.4, then</span>
-0023    <span class="comment">%  fit the exceedances above the threshold xmin = 20:</span>
-0024    <span class="comment">%</span>
-0025    <span class="comment">%     rng('default')</span>
-0026    <span class="comment">%     x = 20 * rand(5000, 1) .^ (-2/3);</span>
-0027    <span class="comment">%     Fit = baseflow.gpfitb(x, 'xmin', 20, 'plotfit', false);</span>
-0028    <span class="comment">%     fprintf('tau0 = %.1f days, b = %.2f\n', Fit.tau0, Fit.b)</span>
-0029    <span class="comment">%</span>
-0030    <span class="comment">% See also: plfitb</span>
-0031    <span class="comment">%</span>
-0032    <span class="comment">% Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</span>
-0033 
-0034    <span class="comment">% PARSE INPUTS</span>
-0035    [x, xmin, varsymb, bootfit, plotfit, labelplot] = <a href="#_sub2" class="code" title="subfunction [x, xmin, varsymb, bootfit, plotfit, labelplot] = parseinputs(x, varargin)">parseinputs</a>(x, varargin{:});
-0036 
-0037    <span class="keyword">if</span> nargin == 1
-0038       xmin = 0;
-0039    <span class="keyword">end</span>
-0040    X = x;
-0041    x = x(x&gt;xmin)-xmin;
-0042    [x,~] = prepCurveData(x,x);
-0043 
-0044    <span class="comment">% get k, klow, and khigh then convert to b</span>
-0045    Dist = fitdist(x,<span class="string">'GeneralizedPareto'</span>);
-0046    k_ci = paramci(Dist);
-0047 
-0048    kM = Dist.k;
-0049    kL = k_ci(1,1);
-0050    kH = k_ci(2,1);
-0051 
-0052    bL = baseflow.conversions(kL,<span class="string">'k'</span>,<span class="string">'b'</span>);
-0053    bM = baseflow.conversions(kM,<span class="string">'k'</span>,<span class="string">'b'</span>);
-0054    bH = baseflow.conversions(kH,<span class="string">'k'</span>,<span class="string">'b'</span>);
-0055 
-0056    alphaM = 1+1/kM;
-0057    alphaL = 1+1/kH;
-0058    alphaH = 1+1/kL;
-0059 
-0060    <span class="comment">% need to correct the error term propagation later</span>
-0061    tau0M = Dist.sigma/Dist.k;
-0062    tau0L = k_ci(1,2)/Dist.k;
-0063    tau0H = k_ci(2,2)/Dist.k;
-0064 
-0065    <span class="comment">% bootstrap confidence intervals</span>
-0066    <span class="keyword">if</span> bootfit == true
-0067       freps = bootstrp(1000,@gpfit,x); <span class="comment">% fit</span>
-0068       kreps = freps(:,1); <span class="comment">% exponent</span>
-0069       sreps = freps(:,2); <span class="comment">% tau0</span>
-0070       breps = baseflow.conversions(kreps,<span class="string">'k'</span>,<span class="string">'b'</span>);
-0071       areps = baseflow.conversions(kreps,<span class="string">'k'</span>,<span class="string">'alpha'</span>);
-0072 
-0073       <span class="comment">% As a rough check on the sampling distribution of the parameter</span>
-0074       <span class="comment">% estimators, we can look at histograms of the bootstrap replicates.</span>
-0075       figure; subplot(2,2,1);
-0076       histogram(breps);
-0077       title(<span class="string">'Bootstrap estimates of $b$'</span>);
-0078       subplot(2,2,2);
-0079       histogram(sreps);
-0080       title(<span class="string">'Bootstrap estimates of $\tau_0$'</span>);
-0081       subplot(2,2,3);
-0082       histogram(areps);
-0083       title(<span class="string">'Bootstrap estimates of $\alpha$'</span>);
-0084       subplot(2,2,4);
-0085       histogram(kreps);
-0086       title(<span class="string">'Bootstrap estimates of $k$'</span>);
-0087 
-0088    <span class="keyword">end</span>
-0089 
-0090    <span class="comment">% package output</span>
-0091    Fit.gpdist  = Dist;
-0092    Fit.xmin    = xmin;
-0093    Fit.b       = bM;
-0094    Fit.tau0    = tau0M;
-0095    Fit.tauExp  = tau0M*(2-bM)/(3-2*bM);
-0096    <span class="comment">%Fit.tauExp  = gpdist.mean+tau0;</span>
-0097    Fit.k       = kM;
-0098    Fit.alpha   = alphaM;
-0099    Fit.bL      = bL;
-0100    Fit.bH      = bH;
-0101    Fit.kL      = kL;
-0102    Fit.kH      = kH;
-0103    Fit.alphaL  = alphaL;
-0104    Fit.alphaH  = alphaH;
-0105    Fit.tau0L   = tau0L;
-0106    Fit.tau0H   = tau0H;
-0107    Fit.tauExpL = tau0L*(2-bL)/(3-2*bL);
-0108    Fit.tauExpH = tau0H*(2-bH)/(3-2*bH);
-0109    Fit.numtau  = numel(X(X&gt;xmin));
-0110 
-0111    <span class="keyword">if</span> bootfit == true
-0112       Fit.breps = breps;
-0113       Fit.tau0reps = sreps;
-0114    <span class="keyword">end</span>
-0115 
-0116    <span class="keyword">if</span> plotfit == true
-0117 
-0118       <span class="comment">% fit a ccdf to the original data and the x-xmin data</span>
-0119       [F,X] = ccdf(X);
-0120       [~,x] = ccdf(x);
-0121 
-0122       <span class="comment">% either use x (ie x-xmin) w/theta=0 or x+xmin w/ theta=xmin</span>
-0123       F2 = gpcdf(x,kM,Dist.sigma,Dist.theta,<span class="string">'upper'</span>);
+0020    <span class="comment">%     Fit.tauExp is the mean tau of the fitted Pareto tail, with bounds</span>
+0021    <span class="comment">%     tauExpL and tauExpH. The mean diverges at or below the tau pole at</span>
+0022    <span class="comment">%     alpha = 2, so a value there is Inf, or NaN without a Pareto tail.</span>
+0023    <span class="comment">%     gpfitb then warns with baseflow:expectedtau:tauPole, and the plot</span>
+0024    <span class="comment">%     label omits the mean tau.</span>
+0025    <span class="comment">%</span>
+0026    <span class="comment">% Example</span>
+0027    <span class="comment">%</span>
+0028    <span class="comment">%  Sample a Pareto distribution with tau0 = 20 days and b = 1.4, then</span>
+0029    <span class="comment">%  fit the exceedances above the threshold xmin = 20:</span>
+0030    <span class="comment">%</span>
+0031    <span class="comment">%     rng('default')</span>
+0032    <span class="comment">%     x = 20 * rand(5000, 1) .^ (-2/3);</span>
+0033    <span class="comment">%     Fit = baseflow.gpfitb(x, 'xmin', 20, 'plotfit', false);</span>
+0034    <span class="comment">%     fprintf('tau0 = %.1f days, b = %.2f\n', Fit.tau0, Fit.b)</span>
+0035    <span class="comment">%</span>
+0036    <span class="comment">% See also: plfitb</span>
+0037    <span class="comment">%</span>
+0038    <span class="comment">% Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</span>
+0039 
+0040    <span class="comment">% PARSE INPUTS</span>
+0041    [x, xmin, varsymb, bootfit, plotfit, labelplot] = <a href="#_sub2" class="code" title="subfunction [x, xmin, varsymb, bootfit, plotfit, labelplot] = parseinputs(x, varargin)">parseinputs</a>(x, varargin{:});
+0042 
+0043    <span class="keyword">if</span> nargin == 1
+0044       xmin = 0;
+0045    <span class="keyword">end</span>
+0046    X = x;
+0047    x = x(x&gt;xmin)-xmin;
+0048    [x,~] = prepCurveData(x,x);
+0049 
+0050    <span class="comment">% get k, klow, and khigh then convert to b</span>
+0051    Dist = fitdist(x,<span class="string">'GeneralizedPareto'</span>);
+0052    k_ci = paramci(Dist);
+0053 
+0054    kM = Dist.k;
+0055    kL = k_ci(1,1);
+0056    kH = k_ci(2,1);
+0057 
+0058    bL = baseflow.conversions(kL,<span class="string">'k'</span>,<span class="string">'b'</span>);
+0059    bM = baseflow.conversions(kM,<span class="string">'k'</span>,<span class="string">'b'</span>);
+0060    bH = baseflow.conversions(kH,<span class="string">'k'</span>,<span class="string">'b'</span>);
+0061 
+0062    alphaM = 1+1/kM;
+0063    alphaL = 1+1/kH;
+0064    alphaH = 1+1/kL;
+0065 
+0066    <span class="comment">% need to correct the error term propagation later</span>
+0067    tau0M = Dist.sigma/Dist.k;
+0068    tau0L = k_ci(1,2)/Dist.k;
+0069    tau0H = k_ci(2,2)/Dist.k;
+0070 
+0071    <span class="comment">% bootstrap confidence intervals</span>
+0072    <span class="keyword">if</span> bootfit == true
+0073       freps = bootstrp(1000,@gpfit,x); <span class="comment">% fit</span>
+0074       kreps = freps(:,1); <span class="comment">% exponent</span>
+0075       sreps = freps(:,2)./kreps; <span class="comment">% tau0 = sigma/k, as for the point estimate</span>
+0076       breps = baseflow.conversions(kreps,<span class="string">'k'</span>,<span class="string">'b'</span>);
+0077       areps = baseflow.conversions(kreps,<span class="string">'k'</span>,<span class="string">'alpha'</span>);
+0078 
+0079       <span class="comment">% As a rough check on the sampling distribution of the parameter</span>
+0080       <span class="comment">% estimators, we can look at histograms of the bootstrap replicates.</span>
+0081       figure; subplot(2,2,1);
+0082       histogram(breps);
+0083       title(<span class="string">'Bootstrap estimates of $b$'</span>);
+0084       subplot(2,2,2);
+0085       histogram(sreps);
+0086       title(<span class="string">'Bootstrap estimates of $\tau_0$'</span>);
+0087       subplot(2,2,3);
+0088       histogram(areps);
+0089       title(<span class="string">'Bootstrap estimates of $\alpha$'</span>);
+0090       subplot(2,2,4);
+0091       histogram(kreps);
+0092       title(<span class="string">'Bootstrap estimates of $k$'</span>);
+0093 
+0094    <span class="keyword">end</span>
+0095 
+0096    <span class="comment">% mean tau of the fitted tail and its bounds (see expectedtau)</span>
+0097    tauExp = expectedtau([tau0M tau0L tau0H],[bM bL bH]);
+0098 
+0099    <span class="comment">% package output</span>
+0100    Fit.gpdist  = Dist;
+0101    Fit.xmin    = xmin;
+0102    Fit.b       = bM;
+0103    Fit.tau0    = tau0M;
+0104    Fit.tauExp  = tauExp(1);
+0105    <span class="comment">%Fit.tauExp  = gpdist.mean+tau0;</span>
+0106    Fit.k       = kM;
+0107    Fit.alpha   = alphaM;
+0108    Fit.bL      = bL;
+0109    Fit.bH      = bH;
+0110    Fit.kL      = kL;
+0111    Fit.kH      = kH;
+0112    Fit.alphaL  = alphaL;
+0113    Fit.alphaH  = alphaH;
+0114    Fit.tau0L   = tau0L;
+0115    Fit.tau0H   = tau0H;
+0116    Fit.tauExpL = tauExp(2);
+0117    Fit.tauExpH = tauExp(3);
+0118    Fit.numtau  = numel(X(X&gt;xmin));
+0119 
+0120    <span class="keyword">if</span> bootfit == true
+0121       Fit.breps = breps;
+0122       Fit.tau0reps = sreps;
+0123    <span class="keyword">end</span>
 0124 
-0125       <span class="comment">% add xmin back for the plot, and find the threshold probability</span>
-0126       xplot = x+xmin;
-0127       yref = F(find(X&gt;=xplot(1),1,<span class="string">'first'</span>));
-0128 
-0129       makesubplot = false;
+0125    <span class="keyword">if</span> plotfit == true
+0126 
+0127       <span class="comment">% fit a ccdf to the original data and the x-xmin data</span>
+0128       [F,X] = ccdf(X);
+0129       [~,x] = ccdf(x);
 0130 
-0131       <span class="comment">% make the figure</span>
-0132       <span class="keyword">if</span> makesubplot == true
+0131       <span class="comment">% either use x (ie x-xmin) w/theta=0 or x+xmin w/ theta=xmin</span>
+0132       F2 = gpcdf(x,kM,Dist.sigma,Dist.theta,<span class="string">'upper'</span>);
 0133 
-0134          <span class="comment">% plot the ccdf and histogram subplot</span>
-0135          figure(<span class="string">'Position'</span>,[147   170   831   418]);
-0136 
-0137          s1 = subtight(1,2,1, <span class="keyword">...</span>
-0138             <span class="string">'wstyle'</span>,<span class="string">'fitted'</span>,<span class="string">'hstyle'</span>,<span class="string">'loose'</span>,<span class="string">'gapstyle'</span>,<span class="string">'fitted'</span>);
+0134       <span class="comment">% add xmin back for the plot, and find the threshold probability</span>
+0135       xplot = x+xmin;
+0136       yref = F(find(X&gt;=xplot(1),1,<span class="string">'first'</span>));
+0137 
+0138       makesubplot = false;
 0139 
-0140       <span class="keyword">else</span>
-0141          figure;
-0142       <span class="keyword">end</span>
-0143 
-0144       <span class="comment">% resume plotting</span>
-0145       h.data = loglog(X,F,<span class="string">'o'</span>,<span class="string">'LineWidth'</span>,0.5,<span class="string">'MarkerSize'</span>,10,   <span class="keyword">...</span>
-0146          <span class="string">'MarkerFaceColor'</span>,<span class="string">'w'</span>); hold on;
-0147       h.fit = loglog(xplot,F2.*yref,<span class="string">'LineStyle'</span>,<span class="string">'-'</span>,<span class="string">'LineWidth'</span>,3);
+0140       <span class="comment">% make the figure</span>
+0141       <span class="keyword">if</span> makesubplot == true
+0142 
+0143          <span class="comment">% plot the ccdf and histogram subplot</span>
+0144          figure(<span class="string">'Position'</span>,[147   170   831   418]);
+0145 
+0146          s1 = subtight(1,2,1, <span class="keyword">...</span>
+0147             <span class="string">'wstyle'</span>,<span class="string">'fitted'</span>,<span class="string">'hstyle'</span>,<span class="string">'loose'</span>,<span class="string">'gapstyle'</span>,<span class="string">'fitted'</span>);
 0148 
-0149       <span class="comment">% h.data = loglog(xplot,F1,'o'); hold on;</span>
-0150       <span class="comment">% h.fit = loglog(xplot,F2);</span>
-0151 
-0152       xlabel(<span class="string">'$x$'</span>);
-0153       ylabel([<span class="string">'$p('</span> varsymb <span class="string">'\ge x)$'</span>],<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
-0154 
-0155       ltext1 = [<span class="string">'$'</span> varsymb <span class="string">'$ (data)'</span>];
-0156       ltext2 = sprintf(<span class="string">'MLE fit ($\\hat{b}=%.2f\\ [$%.2f,%.2f$]\\ 95\\%%$ CI)'</span>,bM,bL,bH);
-0157       h.legend = legend(ltext1,ltext2,<span class="string">'interpreter'</span>,<span class="string">'latex'</span>);
-0158       ax = gca; ax.YLim(2) = 1.5; ax.XLim(2) = xplot(end)*1.2;
-0159 
-0160       <span class="comment">% this works well via guess and check</span>
-0161       h.legend.Position = [0.19 0.38 0.54 0.1];
-0162       <span class="comment">% h.legend.Position(1) = 0.9*h.legend.Position(1);</span>
-0163       <span class="comment">% h.legend.Position(2) = 0.8*h.legend.Position(2);</span>
-0164 
-0165       <span class="keyword">if</span> labelplot == true
-0166          <a href="#_sub1" class="code" title="subfunction addlabels(Fit,xmin,yref)">addlabels</a>(Fit,xmin,yref);
-0167       <span class="keyword">end</span>
+0149       <span class="keyword">else</span>
+0150          figure;
+0151       <span class="keyword">end</span>
+0152 
+0153       <span class="comment">% resume plotting</span>
+0154       h.data = loglog(X,F,<span class="string">'o'</span>,<span class="string">'LineWidth'</span>,0.5,<span class="string">'MarkerSize'</span>,10,   <span class="keyword">...</span>
+0155          <span class="string">'MarkerFaceColor'</span>,<span class="string">'w'</span>); hold on;
+0156       h.fit = loglog(xplot,F2.*yref,<span class="string">'LineStyle'</span>,<span class="string">'-'</span>,<span class="string">'LineWidth'</span>,3);
+0157 
+0158       <span class="comment">% h.data = loglog(xplot,F1,'o'); hold on;</span>
+0159       <span class="comment">% h.fit = loglog(xplot,F2);</span>
+0160 
+0161       xlabel(<span class="string">'$x$'</span>);
+0162       ylabel([<span class="string">'$p('</span> varsymb <span class="string">'\ge x)$'</span>],<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
+0163 
+0164       ltext1 = [<span class="string">'$'</span> varsymb <span class="string">'$ (data)'</span>];
+0165       ltext2 = sprintf(<span class="string">'MLE fit ($\\hat{b}=%.2f\\ [$%.2f,%.2f$]\\ 95\\%%$ CI)'</span>,bM,bL,bH);
+0166       h.legend = legend(ltext1,ltext2,<span class="string">'interpreter'</span>,<span class="string">'latex'</span>);
+0167       ax = gca; ax.YLim(2) = 1.5; ax.XLim(2) = xplot(end)*1.2;
 0168 
-0169       <span class="keyword">if</span> makesubplot == true
-0170 
-0171          s2 = subtight(1,2,2, <span class="keyword">...</span>
-0172             <span class="string">'wstyle'</span>,<span class="string">'fitted'</span>,<span class="string">'hstyle'</span>,<span class="string">'loose'</span>,<span class="string">'gapstyle'</span>,<span class="string">'fitted'</span>);
-0173          <span class="comment">% [~,~,~,h.histfit] = loghist(X,'dist','GeneralizedPareto','theta',xmin);</span>
-0174 
-0175          xlabel([<span class="string">'$'</span> varsymb <span class="string">'$'</span>]);
-0176          ylabel([<span class="string">'$p('</span> varsymb <span class="string">')$'</span>],<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
+0169       <span class="comment">% this works well via guess and check</span>
+0170       h.legend.Position = [0.19 0.38 0.54 0.1];
+0171       <span class="comment">% h.legend.Position(1) = 0.9*h.legend.Position(1);</span>
+0172       <span class="comment">% h.legend.Position(2) = 0.8*h.legend.Position(2);</span>
+0173 
+0174       <span class="keyword">if</span> labelplot == true
+0175          <a href="#_sub1" class="code" title="subfunction addlabels(Fit,xmin,yref)">addlabels</a>(Fit,xmin,yref);
+0176       <span class="keyword">end</span>
 0177 
-0178          <span class="comment">% commented out for compatibility</span>
-0179          <span class="comment">% h.ff = figformat('suppliedline',h.histfit,'linelinewidth',3);</span>
-0180 
-0181          s2.XLim = s1.XLim;
-0182          h.histlegend = legend(h.ff.backgroundAxis,ltext1,ltext2, <span class="keyword">...</span>
-0183             <span class="string">'interpreter'</span>,<span class="string">'latex'</span>,<span class="string">'location'</span>,<span class="string">'southwest'</span>);
-0184 
-0185          childs = h.ff.mainAxis.Children;
-0186          childs(2).FaceAlpha = 0;
-0187 
-0188          setlogticks(s1);
-0189          setlogticks(s2);
-0190       <span class="keyword">end</span>
-0191 
-0192 
-0193       Fit.thresholdprobability = yref;
-0194       Fit.xplot = xplot;
-0195       Fit.Fplot = F2.*yref;
+0178       <span class="keyword">if</span> makesubplot == true
+0179 
+0180          s2 = subtight(1,2,2, <span class="keyword">...</span>
+0181             <span class="string">'wstyle'</span>,<span class="string">'fitted'</span>,<span class="string">'hstyle'</span>,<span class="string">'loose'</span>,<span class="string">'gapstyle'</span>,<span class="string">'fitted'</span>);
+0182          <span class="comment">% [~,~,~,h.histfit] = loghist(X,'dist','GeneralizedPareto','theta',xmin);</span>
+0183 
+0184          xlabel([<span class="string">'$'</span> varsymb <span class="string">'$'</span>]);
+0185          ylabel([<span class="string">'$p('</span> varsymb <span class="string">')$'</span>],<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
+0186 
+0187          <span class="comment">% commented out for compatibility</span>
+0188          <span class="comment">% h.ff = figformat('suppliedline',h.histfit,'linelinewidth',3);</span>
+0189 
+0190          s2.XLim = s1.XLim;
+0191          h.histlegend = legend(h.ff.backgroundAxis,ltext1,ltext2, <span class="keyword">...</span>
+0192             <span class="string">'interpreter'</span>,<span class="string">'latex'</span>,<span class="string">'location'</span>,<span class="string">'southwest'</span>);
+0193 
+0194          childs = h.ff.mainAxis.Children;
+0195          childs(2).FaceAlpha = 0;
 0196 
-0197       <span class="comment">% % test using plplot instead</span>
-0198       <span class="comment">% aci = [alphaH alphaL];</span>
-0199       <span class="comment">% x = X(X&gt;0);</span>
-0200       <span class="comment">% [x,~] = prepCurveData(x,x);</span>
-0201       <span class="comment">% figure;</span>
-0202       <span class="comment">% baseflow.plplotb(x,xmin,alpha,'trimline',true,'alphaci',aci,'labelplot',true);</span>
-0203    <span class="keyword">end</span>
-0204 <span class="keyword">end</span>
+0197          setlogticks(s1);
+0198          setlogticks(s2);
+0199       <span class="keyword">end</span>
+0200 
+0201 
+0202       Fit.thresholdprobability = yref;
+0203       Fit.xplot = xplot;
+0204       Fit.Fplot = F2.*yref;
 0205 
-0206 <a name="_sub1" href="#_subfunctions" class="code">function addlabels(Fit,xmin,yref)</a>
-0207    <span class="comment">%ADDLABELS add an arrow pointing to tau0 and tau_exp</span>
-0208    <span class="comment">%</span>
-0209    <span class="comment">% drawarrow draws in the current axes, which is the axes the caller</span>
-0210    <span class="comment">% plotted into, as the text calls below do.</span>
-0211 
-0212    <span class="comment">% tau0</span>
-0213    xminc = (Fit.tau0H-Fit.tau0+Fit.tau0-Fit.tau0L)/2;
-0214    xa = [xmin-xmin/2 xmin];
-0215    ya = Fit.gpdist.cdf(0,<span class="string">'upper'</span>)*yref;
-0216    ya = [ya ya];
-0217    ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f\\pm%.0f$ days'</span>,xmin,xminc);
-0218 
-0219    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
-0220    text(0.95*xa(1),ya(1),ta,<span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>)
-0221 
-0222    <span class="comment">% use these to put the text on the right side of the curve</span>
-0223    <span class="comment">% xa = [xmin+xmin/2 xmin];</span>
-0224    <span class="comment">% text(1.05*xa(1),ya(1),ta)</span>
-0225 
-0226    <span class="comment">% tauExp</span>
-0227    xexp = Fit.tauExp; <span class="comment">% just use xmin to keep syntax</span>
-0228    xexpc = (Fit.tauExpH-Fit.tauExp+Fit.tauExp-Fit.tauExpL)/2;
-0229    xa = [xexp-xexp/2 xexp];
+0206       <span class="comment">% % test using plplot instead</span>
+0207       <span class="comment">% aci = [alphaH alphaL];</span>
+0208       <span class="comment">% x = X(X&gt;0);</span>
+0209       <span class="comment">% [x,~] = prepCurveData(x,x);</span>
+0210       <span class="comment">% figure;</span>
+0211       <span class="comment">% baseflow.plplotb(x,xmin,alpha,'trimline',true,'alphaci',aci,'labelplot',true);</span>
+0212    <span class="keyword">end</span>
+0213 <span class="keyword">end</span>
+0214 
+0215 <a name="_sub1" href="#_subfunctions" class="code">function addlabels(Fit,xmin,yref)</a>
+0216    <span class="comment">%ADDLABELS add an arrow pointing to tau0 and tau_exp</span>
+0217    <span class="comment">%</span>
+0218    <span class="comment">% drawarrow draws in the current axes, which is the axes the caller</span>
+0219    <span class="comment">% plotted into, as the text calls below do.</span>
+0220 
+0221    <span class="comment">% tau0</span>
+0222    xminc = (Fit.tau0H-Fit.tau0+Fit.tau0-Fit.tau0L)/2;
+0223    xa = [xmin-xmin/2 xmin];
+0224    ya = Fit.gpdist.cdf(0,<span class="string">'upper'</span>)*yref;
+0225    ya = [ya ya];
+0226    ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f\\pm%.0f$ days'</span>,xmin,xminc);
+0227 
+0228    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
+0229    text(0.95*xa(1),ya(1),ta,<span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>)
 0230 
-0231    ya = Fit.gpdist.cdf(xexp-xmin,<span class="string">'upper'</span>)*yref;
-0232    ya = [ya ya];
-0233    ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days'</span>,xexp,xexpc);
+0231    <span class="comment">% use these to put the text on the right side of the curve</span>
+0232    <span class="comment">% xa = [xmin+xmin/2 xmin];</span>
+0233    <span class="comment">% text(1.05*xa(1),ya(1),ta)</span>
 0234 
-0235    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
-0236    text(0.95*xa(1),ya(1),ta,<span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>)
-0237 <span class="keyword">end</span>
-0238 
-0239 <span class="comment">%% INPUT PARSER</span>
-0240 <a name="_sub2" href="#_subfunctions" class="code">function [x, xmin, varsymb, bootfit, plotfit, labelplot] = parseinputs(x, varargin)</a>
-0241    
-0242    parser = inputParser;
-0243    parser.FunctionName = <span class="string">'baseflow.gpfitb'</span>;
-0244    parser.addRequired(<span class="string">'x'</span>, @isnumeric);
-0245    parser.addParameter(<span class="string">'xmin'</span>, 0, @isnumeric);
-0246    parser.addParameter(<span class="string">'varsym'</span>, <span class="string">'\tau'</span>, @ischar);
-0247    parser.addParameter(<span class="string">'bootfit'</span>, false, @islogical);
-0248    parser.addParameter(<span class="string">'plotfit'</span>, true, @islogical);
-0249    parser.addParameter(<span class="string">'labelplot'</span>, true, @islogical);
-0250    parser.parse(x, varargin{:});
+0235    <span class="comment">% tauExp</span>
+0236    <span class="comment">% a mean or bound beyond the tau pole has no point on the axes to label</span>
+0237    <span class="keyword">if</span> ~all(isfinite([Fit.tauExp Fit.tauExpL Fit.tauExpH]))
+0238       <span class="keyword">return</span>
+0239    <span class="keyword">end</span>
+0240    xexp = Fit.tauExp; <span class="comment">% just use xmin to keep syntax</span>
+0241    xexpc = (Fit.tauExpH-Fit.tauExp+Fit.tauExp-Fit.tauExpL)/2;
+0242    xa = [xexp-xexp/2 xexp];
+0243 
+0244    ya = Fit.gpdist.cdf(xexp-xmin,<span class="string">'upper'</span>)*yref;
+0245    ya = [ya ya];
+0246    ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days'</span>,xexp,xexpc);
+0247 
+0248    drawarrow(gca, [xa(1),ya(1)], [xa(2),ya(2)]);
+0249    text(0.95*xa(1),ya(1),ta,<span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>)
+0250 <span class="keyword">end</span>
 0251 
-0252    xmin     = parser.Results.xmin;
-0253    varsymb  = parser.Results.varsym;
-0254    bootfit  = parser.Results.bootfit;
-0255    plotfit  = parser.Results.plotfit;
-0256    labelplot = parser.Results.labelplot;
-0257 <span class="keyword">end</span></pre></div>
+0252 <span class="comment">%% INPUT PARSER</span>
+0253 <a name="_sub2" href="#_subfunctions" class="code">function [x, xmin, varsymb, bootfit, plotfit, labelplot] = parseinputs(x, varargin)</a>
+0254    
+0255    parser = inputParser;
+0256    parser.FunctionName = <span class="string">'baseflow.gpfitb'</span>;
+0257    parser.addRequired(<span class="string">'x'</span>, @isnumeric);
+0258    parser.addParameter(<span class="string">'xmin'</span>, 0, @isnumeric);
+0259    parser.addParameter(<span class="string">'varsym'</span>, <span class="string">'\tau'</span>, @ischar);
+0260    parser.addParameter(<span class="string">'bootfit'</span>, false, @islogical);
+0261    parser.addParameter(<span class="string">'plotfit'</span>, true, @islogical);
+0262    parser.addParameter(<span class="string">'labelplot'</span>, true, @islogical);
+0263    parser.parse(x, varargin{:});
+0264 
+0265    xmin     = parser.Results.xmin;
+0266    varsymb  = parser.Results.varsym;
+0267    bootfit  = parser.Results.bootfit;
+0268    plotfit  = parser.Results.plotfit;
+0269    labelplot = parser.Results.labelplot;
+0270 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/plfitb.html b/toolbox/docs/html/m2html/+baseflow/plfitb.html
index 861b31c..8f48f59 100644
--- a/toolbox/docs/html/m2html/+baseflow/plfitb.html
+++ b/toolbox/docs/html/m2html/+baseflow/plfitb.html
@@ -41,6 +41,11 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      xhat=x-xmin. Any inputs to plfit can be passed in as varargin, where
      plfit is Aaron Clauset's function.
 
+     Fit.tau is the mean tau of the fitted Pareto tail. The mean
+     diverges at or below the tau pole at alpha = 2, so Fit.tau is Inf
+     there. A bootstrap replicate beyond the pole makes tau_sig, tau_L,
+     and tau_H NaN. plfitb then warns with baseflow:expectedtau:tauPole.
+
  Required inputs
 
      x        data believed to follow an untruncated Pareto distribution
@@ -49,7 +54,7 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
      xmin     scalar double indicating the lower bound of the distribution
      range    the range of scaling parameters considered (see plfit.m)
-     limit    scalar double that sets the upper bound of fitted exponent
+     limit    scalar double that sets the upper bound of the fitted xmin
      method   char indicating one of two algorithms (Clauset's or Hanel's)
      bootfit  logical indicating whether to bootstrap the uncertainties
               (slow)
@@ -110,256 +115,253 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0013    <span class="comment">%     xhat=x-xmin. Any inputs to plfit can be passed in as varargin, where</span>
 0014    <span class="comment">%     plfit is Aaron Clauset's function.</span>
 0015    <span class="comment">%</span>
-0016    <span class="comment">% Required inputs</span>
-0017    <span class="comment">%</span>
-0018    <span class="comment">%     x        data believed to follow an untruncated Pareto distribution</span>
-0019    <span class="comment">%</span>
-0020    <span class="comment">% Optional name-value inputs</span>
-0021    <span class="comment">%</span>
-0022    <span class="comment">%     xmin     scalar double indicating the lower bound of the distribution</span>
-0023    <span class="comment">%     range    the range of scaling parameters considered (see plfit.m)</span>
-0024    <span class="comment">%     limit    scalar double that sets the upper bound of fitted exponent</span>
-0025    <span class="comment">%     method   char indicating one of two algorithms (Clauset's or Hanel's)</span>
-0026    <span class="comment">%     bootfit  logical indicating whether to bootstrap the uncertainties</span>
-0027    <span class="comment">%              (slow)</span>
-0028    <span class="comment">%     bootreps scalar double indicating how many replicates in the boot fit</span>
-0029    <span class="comment">%     plotfit  logical indicating whether to call plplot</span>
-0030    <span class="comment">%</span>
-0031    <span class="comment">% Example</span>
-0032    <span class="comment">%</span>
-0033    <span class="comment">%  Sample a Pareto distribution with tau0 = 20 days and b = 1.4. Fit</span>
-0034    <span class="comment">%  the sample to recover the parameters:</span>
+0016    <span class="comment">%     Fit.tau is the mean tau of the fitted Pareto tail. The mean</span>
+0017    <span class="comment">%     diverges at or below the tau pole at alpha = 2, so Fit.tau is Inf</span>
+0018    <span class="comment">%     there. A bootstrap replicate beyond the pole makes tau_sig, tau_L,</span>
+0019    <span class="comment">%     and tau_H NaN. plfitb then warns with baseflow:expectedtau:tauPole.</span>
+0020    <span class="comment">%</span>
+0021    <span class="comment">% Required inputs</span>
+0022    <span class="comment">%</span>
+0023    <span class="comment">%     x        data believed to follow an untruncated Pareto distribution</span>
+0024    <span class="comment">%</span>
+0025    <span class="comment">% Optional name-value inputs</span>
+0026    <span class="comment">%</span>
+0027    <span class="comment">%     xmin     scalar double indicating the lower bound of the distribution</span>
+0028    <span class="comment">%     range    the range of scaling parameters considered (see plfit.m)</span>
+0029    <span class="comment">%     limit    scalar double that sets the upper bound of the fitted xmin</span>
+0030    <span class="comment">%     method   char indicating one of two algorithms (Clauset's or Hanel's)</span>
+0031    <span class="comment">%     bootfit  logical indicating whether to bootstrap the uncertainties</span>
+0032    <span class="comment">%              (slow)</span>
+0033    <span class="comment">%     bootreps scalar double indicating how many replicates in the boot fit</span>
+0034    <span class="comment">%     plotfit  logical indicating whether to call plplot</span>
 0035    <span class="comment">%</span>
-0036    <span class="comment">%     rng('default')</span>
-0037    <span class="comment">%     x = 20 * rand(5000, 1) .^ (-2/3);</span>
-0038    <span class="comment">%     Fit = baseflow.plfitb(x);</span>
-0039    <span class="comment">%     fprintf('tau0 = %.1f days, b = %.2f\n', Fit.tau0, Fit.b)</span>
+0036    <span class="comment">% Example</span>
+0037    <span class="comment">%</span>
+0038    <span class="comment">%  Sample a Pareto distribution with tau0 = 20 days and b = 1.4. Fit</span>
+0039    <span class="comment">%  the sample to recover the parameters:</span>
 0040    <span class="comment">%</span>
-0041    <span class="comment">% See also: plfit, plplotb, gpfitb</span>
-0042    <span class="comment">%</span>
-0043    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0044 
-0045    <span class="comment">% if called with no input, open this file</span>
-0046    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0047 
-0048    <span class="comment">% PARSE INPUTS</span>
-0049    [x, xmin, range, limit, method, bootfit, nreps, plotfit] = parseinputs( <span class="keyword">...</span>
-0050       x, varargin{:});
-0051 
-0052    <span class="comment">% MAIN FUNCTION</span>
-0053    x0 = x;
-0054    [x,~] = prepCurveData(x,x);
-0055    x = x(x&gt;0);
-0056    <span class="keyword">if</span> isnan(xmin)
-0057       <span class="keyword">switch</span> method
-0058          <span class="keyword">case</span> <span class="string">'clauset'</span>
-0059             [alpha,xmin,L,D] = baseflow.deps.plfit(x,<span class="string">'range'</span>,range,<span class="string">'limit'</span>,limit);
-0060             <span class="keyword">if</span> bootfit == true
-0061                BootFit = <a href="#_sub1" class="code" title="subfunction Fit = plbootfit(x,range,limit,nreps)">plbootfit</a>(x,range,limit,nreps);
-0062             <span class="keyword">end</span>
-0063             <span class="comment">% Undocumented feature, requires r_plfit function, not in toolbox.</span>
-0064             <span class="comment">% Hanel et al. (2017, PLOS ONE 12:e0170920) published r_plfit as</span>
-0065             <span class="comment">% supplementary code with no license grant, so it stays external.</span>
-0066             <span class="comment">% See the README r_plfit note and docs/baseflow_powerlaw_notation.m</span>
-0067             <span class="comment">% for the notation map.</span>
-0068          <span class="keyword">case</span> <span class="string">'hanel'</span>
-0069             [~,xmin] = baseflow.deps.plfit(x,<span class="string">'range'</span>,range,<span class="string">'limit'</span>,limit);
-0070             <span class="comment">% 'cdat' declares continuous data: without it r_plfit bins</span>
-0071             <span class="comment">% real-valued tau on the integer grid min(x):max(x) and fits</span>
-0072             <span class="comment">% the discrete model. Hanel's sample-mode exponent is the pdf</span>
-0073             <span class="comment">% exponent, directly comparable to Clauset's alpha.</span>
-0074             <span class="comment">% Note: r_plfit's help names the search bounds 'alpha_min'</span>
-0075             <span class="comment">% and 'alpha_max'. Its parser accepts only 'exp_min' and</span>
-0076             <span class="comment">% 'exp_max' and skips unknown options without an error. With</span>
-0077             <span class="comment">% the 'alpha_*' names, r_plfit keeps its default 0-5 search range.</span>
-0078             [alpha,xmin,L,D] = r_plfit(x,<span class="string">'rangemin'</span>,xmin,<span class="string">'exp_min'</span>,  <span class="keyword">...</span>
-0079                range(1),<span class="string">'exp_max'</span>,range(end),<span class="string">'cdat'</span>);
-0080             <span class="comment">% if I had some max value to consider, I could pass 'rangemax'</span>
-0081       <span class="keyword">end</span>
-0082    <span class="keyword">else</span>
-0083       [alpha,~,L,D] = baseflow.deps.plfit(x,<span class="string">'xmin'</span>,xmin,<span class="string">'range'</span>,range,<span class="string">'limit'</span>,limit);
-0084    <span class="keyword">end</span>
-0085 
-0086    Fit.x       = x0; <span class="comment">% keep the input data</span>
-0087    Fit.alpha   = alpha;
-0088    Fit.b       = 1+1/Fit.alpha;
-0089    Fit.tau     = xmin*(2-Fit.b)/(3-2*Fit.b);
-0090    Fit.tau0    = xmin;
-0091    Fit.L       = L;
-0092    Fit.D       = D;
-0093    Fit.k       = 1/(Fit.alpha-1);
-0094    Fit.taumask = x0&gt;xmin;
-0095 
-0096    <span class="keyword">if</span> bootfit == true
-0097       Fit.b_L = Fit.b - BootFit.b_sig;
-0098       Fit.b_H = Fit.b + BootFit.b_sig;
-0099       Fit.alpha_L = Fit.alpha - BootFit.alpha_sig;
-0100       Fit.alpha_H = Fit.alpha + BootFit.alpha_sig;
-0101       Fit.tau0_L = Fit.tau0 - BootFit.tau0_sig;
-0102       Fit.tau0_H = Fit.tau0 + BootFit.tau0_sig;
-0103       Fit.tau_L = Fit.tau - BootFit.tau_sig;
-0104       Fit.tau_H = Fit.tau + BootFit.tau_sig;
-0105       Fit.reps = BootFit.reps;
-0106       BootFit = rmfield(BootFit,<span class="string">'reps'</span>);
-0107       Fit.BootFit = BootFit;
-0108    <span class="keyword">else</span>
-0109       <span class="comment">% assign null confidence bounds so other functions will work</span>
-0110       Fit.b_L = Fit.b;
-0111       Fit.b_H = Fit.b;
-0112       Fit.alpha_L = Fit.alpha;
-0113       Fit.alpha_H = Fit.alpha;
-0114       Fit.tau0_L = Fit.tau0;
-0115       Fit.tau0_H = Fit.tau0;
-0116       Fit.tau_L = Fit.tau;
-0117       Fit.tau_H = Fit.tau;
-0118    <span class="keyword">end</span>
-0119 
-0120    <span class="comment">% also: b = (2*k+1)/(k+1)</span>
-0121    <span class="comment">% and:  alpha = 1 + 1/k</span>
-0122 
-0123    <span class="keyword">if</span> plotfit == true
-0124       alpha = Fit.alpha;
-0125       xmin = Fit.tau0;
-0126       <span class="comment">% plplotb converts alpha to b = 1+1/alpha, which decreases with</span>
-0127       <span class="comment">% alpha, so alpha_H maps to the lower b. Pass the alpha bounds</span>
-0128       <span class="comment">% reversed. With bootfit true, both intervals span one bootstrap</span>
-0129       <span class="comment">% standard deviation. With bootfit false they are degenerate.</span>
-0130       aci = [Fit.alpha_H Fit.alpha_L];
-0131       xci = [Fit.tau0_L Fit.tau0_H];
-0132       baseflow.plplotb(x,xmin,alpha,<span class="string">'trimline'</span>,true,<span class="string">'alphaci'</span>,aci,<span class="string">'xminci'</span>,xci);
-0133    <span class="keyword">end</span>
-0134 
-0135    <span class="keyword">switch</span> nargout
-0136       <span class="keyword">case</span> 1
-0137          varargout{1} = Fit;
-0138       <span class="keyword">case</span> 2
-0139          varargout{1} = 1+1/alpha;
-0140          varargout{2} = alpha;
-0141       <span class="keyword">case</span> 3
-0142          varargout{1} = 1+1/alpha;
-0143          varargout{2} = alpha;
-0144          varargout{3} = xmin;
-0145    <span class="keyword">end</span>
-0146 
-0147    <span class="comment">% NOTE: for alpha ~= 3, and 1000 reps, abs(BootFit.alpha-Fit.alpha) should</span>
-0148    <span class="comment">% be about 0.01-0.02. This is indeed the case for the data I have tested</span>
-0149    <span class="comment">% from the Kuparuk (the error was about 0.03, but alpha was about 3.12). See</span>
-0150    <span class="comment">% Figure 10 in Clauset et al. 2009.</span>
-0151 <span class="keyword">end</span>
-0152 
-0153 <span class="comment">%% LOCAL FUNCTIONS</span>
-0154 
-0155 <span class="comment">% bootstrap confidence intervals</span>
-0156 <a name="_sub1" href="#_subfunctions" class="code">function Fit = plbootfit(x,range,limit,nreps)</a>
+0041    <span class="comment">%     rng('default')</span>
+0042    <span class="comment">%     x = 20 * rand(5000, 1) .^ (-2/3);</span>
+0043    <span class="comment">%     Fit = baseflow.plfitb(x);</span>
+0044    <span class="comment">%     fprintf('tau0 = %.1f days, b = %.2f\n', Fit.tau0, Fit.b)</span>
+0045    <span class="comment">%</span>
+0046    <span class="comment">% See also: plfit, plplotb, gpfitb</span>
+0047    <span class="comment">%</span>
+0048    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0049 
+0050    <span class="comment">% if called with no input, open this file</span>
+0051    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0052 
+0053    <span class="comment">% PARSE INPUTS</span>
+0054    [x, xmin, range, limit, method, bootfit, nreps, plotfit] = parseinputs( <span class="keyword">...</span>
+0055       x, varargin{:});
+0056 
+0057    <span class="comment">% MAIN FUNCTION</span>
+0058    x0 = x;
+0059    [x,~] = prepCurveData(x,x);
+0060    x = x(x&gt;0);
+0061    <span class="keyword">if</span> isnan(xmin)
+0062       <span class="keyword">switch</span> method
+0063          <span class="keyword">case</span> <span class="string">'clauset'</span>
+0064             [alpha,xmin,L,D] = baseflow.deps.plfit(x,<span class="string">'range'</span>,range,<span class="string">'limit'</span>,limit);
+0065             <span class="keyword">if</span> bootfit == true
+0066                BootFit = <a href="#_sub1" class="code" title="subfunction Fit = plbootfit(x,range,limit,nreps)">plbootfit</a>(x,range,limit,nreps);
+0067             <span class="keyword">end</span>
+0068             <span class="comment">% Undocumented feature, requires r_plfit function, not in toolbox.</span>
+0069             <span class="comment">% Hanel et al. (2017, PLOS ONE 12:e0170920) published r_plfit as</span>
+0070             <span class="comment">% supplementary code with no license grant, so it stays external.</span>
+0071             <span class="comment">% See the README r_plfit note and docs/baseflow_powerlaw_notation.m</span>
+0072             <span class="comment">% for the notation map.</span>
+0073          <span class="keyword">case</span> <span class="string">'hanel'</span>
+0074             [~,xmin] = baseflow.deps.plfit(x,<span class="string">'range'</span>,range,<span class="string">'limit'</span>,limit);
+0075             <span class="comment">% 'cdat' declares continuous data: without it r_plfit bins</span>
+0076             <span class="comment">% real-valued tau on the integer grid min(x):max(x) and fits</span>
+0077             <span class="comment">% the discrete model. Hanel's sample-mode exponent is the pdf</span>
+0078             <span class="comment">% exponent, directly comparable to Clauset's alpha.</span>
+0079             <span class="comment">% Note: r_plfit's help names the search bounds 'alpha_min'</span>
+0080             <span class="comment">% and 'alpha_max'. Its parser accepts only 'exp_min' and</span>
+0081             <span class="comment">% 'exp_max' and skips unknown options without an error. With</span>
+0082             <span class="comment">% the 'alpha_*' names, r_plfit keeps its default 0-5 search range.</span>
+0083             [alpha,xmin,L,D] = r_plfit(x,<span class="string">'rangemin'</span>,xmin,<span class="string">'exp_min'</span>,  <span class="keyword">...</span>
+0084                range(1),<span class="string">'exp_max'</span>,range(end),<span class="string">'cdat'</span>);
+0085             <span class="comment">% if I had some max value to consider, I could pass 'rangemax'</span>
+0086       <span class="keyword">end</span>
+0087    <span class="keyword">else</span>
+0088       [alpha,~,L,D] = baseflow.deps.plfit(x,<span class="string">'xmin'</span>,xmin,<span class="string">'range'</span>,range,<span class="string">'limit'</span>,limit);
+0089    <span class="keyword">end</span>
+0090 
+0091    Fit.x       = x0; <span class="comment">% keep the input data</span>
+0092    Fit.alpha   = alpha;
+0093    Fit.b       = 1+1/Fit.alpha;
+0094    Fit.tau     = expectedtau(xmin,Fit.b); <span class="comment">% Inf beyond the tau pole</span>
+0095    Fit.tau0    = xmin;
+0096    Fit.L       = L;
+0097    Fit.D       = D;
+0098    Fit.k       = 1/(Fit.alpha-1);
+0099    Fit.taumask = x0&gt;=xmin; <span class="comment">% plfit fits the tail x &gt;= xmin</span>
+0100 
+0101    <span class="keyword">if</span> bootfit == true
+0102       Fit.b_L = Fit.b - BootFit.b_sig;
+0103       Fit.b_H = Fit.b + BootFit.b_sig;
+0104       Fit.alpha_L = Fit.alpha - BootFit.alpha_sig;
+0105       Fit.alpha_H = Fit.alpha + BootFit.alpha_sig;
+0106       Fit.tau0_L = Fit.tau0 - BootFit.tau0_sig;
+0107       Fit.tau0_H = Fit.tau0 + BootFit.tau0_sig;
+0108       Fit.tau_L = Fit.tau - BootFit.tau_sig;
+0109       Fit.tau_H = Fit.tau + BootFit.tau_sig;
+0110       Fit.reps = BootFit.reps;
+0111       BootFit = rmfield(BootFit,<span class="string">'reps'</span>);
+0112       Fit.BootFit = BootFit;
+0113    <span class="keyword">else</span>
+0114       <span class="comment">% assign null confidence bounds so other functions will work</span>
+0115       Fit.b_L = Fit.b;
+0116       Fit.b_H = Fit.b;
+0117       Fit.alpha_L = Fit.alpha;
+0118       Fit.alpha_H = Fit.alpha;
+0119       Fit.tau0_L = Fit.tau0;
+0120       Fit.tau0_H = Fit.tau0;
+0121       Fit.tau_L = Fit.tau;
+0122       Fit.tau_H = Fit.tau;
+0123    <span class="keyword">end</span>
+0124 
+0125    <span class="comment">% also: b = (2*k+1)/(k+1)</span>
+0126    <span class="comment">% and:  alpha = 1 + 1/k</span>
+0127 
+0128    <span class="keyword">if</span> plotfit == true
+0129       alpha = Fit.alpha;
+0130       xmin = Fit.tau0;
+0131       <span class="comment">% plplotb converts alpha to b = 1+1/alpha, which decreases with</span>
+0132       <span class="comment">% alpha, so alpha_H maps to the lower b. Pass the alpha bounds</span>
+0133       <span class="comment">% reversed. With bootfit true, both intervals span one bootstrap</span>
+0134       <span class="comment">% standard deviation. With bootfit false they are degenerate.</span>
+0135       aci = [Fit.alpha_H Fit.alpha_L];
+0136       xci = [Fit.tau0_L Fit.tau0_H];
+0137       baseflow.plplotb(x,xmin,alpha,<span class="string">'trimline'</span>,true,<span class="string">'alphaci'</span>,aci,<span class="string">'xminci'</span>,xci);
+0138    <span class="keyword">end</span>
+0139 
+0140    <span class="keyword">switch</span> nargout
+0141       <span class="keyword">case</span> 1
+0142          varargout{1} = Fit;
+0143       <span class="keyword">case</span> 2
+0144          varargout{1} = 1+1/alpha;
+0145          varargout{2} = alpha;
+0146       <span class="keyword">case</span> 3
+0147          varargout{1} = 1+1/alpha;
+0148          varargout{2} = alpha;
+0149          varargout{3} = xmin;
+0150    <span class="keyword">end</span>
+0151 
+0152    <span class="comment">% NOTE: for alpha ~= 3, and 1000 reps, abs(BootFit.alpha-Fit.alpha) should</span>
+0153    <span class="comment">% be about 0.01-0.02. This is indeed the case for the data I have tested</span>
+0154    <span class="comment">% from the Kuparuk (the error was about 0.03, but alpha was about 3.12). See</span>
+0155    <span class="comment">% Figure 10 in Clauset et al. 2009.</span>
+0156 <span class="keyword">end</span>
 0157 
-0158    <span class="comment">%[alpha,xmin,L,D] = baseflow.deps.plfit(x,'range',range,'limit',limit);</span>
-0159    [~,~,~,repsmat] = baseflow.deps.plvar( <span class="keyword">...</span>
-0160       x, <span class="string">'range'</span>, range, <span class="string">'limit'</span>, limit, <span class="string">'reps'</span>, nreps, <span class="string">'silent'</span>);
-0161 
-0162    vars        = {<span class="string">'tau0'</span>,<span class="string">'alpha'</span>,<span class="string">'b'</span>,<span class="string">'tau'</span>,<span class="string">'ntail'</span>};
-0163    reps.ntail  = repsmat(:,1);
-0164    reps.tau0   = repsmat(:,2);
-0165    reps.alpha  = repsmat(:,3);
-0166    reps.b      = baseflow.conversions(reps.alpha,<span class="string">'alpha'</span>,<span class="string">'b'</span>);
-0167    reps.tau    = reps.tau0.*(2-reps.b)./(3-2.*reps.b);
-0168 
-0169    <span class="comment">% tau = tau0*(2-b)/(3-2*b) has a pole at b = 3/2, which is alpha = 2. A</span>
-0170    <span class="comment">% replicate at or below alpha = 2 returns a negative or unbounded tau.</span>
-0171    <span class="comment">% Such a replicate makes std(reps.tau) meaningless. Warn with the count,</span>
-0172    <span class="comment">% so the caller does not trust the reported tau_sig.</span>
-0173    npole = sum(reps.alpha &lt;= 2);
-0174    <span class="keyword">if</span> npole &gt; 0
-0175       warning(<span class="string">'baseflow:plfitb:tauPoleReplicates'</span>, <span class="keyword">...</span>
-0176          [<span class="string">'%d of %d bootstrap replicates have alpha &lt;= 2, where tau is '</span> <span class="keyword">...</span>
-0177          <span class="string">'unbounded. Treat tau_sig, tau_L, and tau_H as invalid.'</span>], <span class="keyword">...</span>
-0178          npole, numel(reps.alpha))
-0179    <span class="keyword">end</span>
-0180 
-0181    <span class="keyword">for</span> n = 1:numel(vars)
-0182       var = vars{n};
-0183       Fit.(var) = mean(reps.(var));
-0184       Fit.([var <span class="string">'_sig'</span>]) = std(reps.(var));
-0185       Fit.([var <span class="string">'_L'</span>]) = mean(reps.(var)) - 1.96*std(reps.(var));
-0186       Fit.([var <span class="string">'_H'</span>]) = mean(reps.(var)) + 1.96*std(reps.(var));
-0187    <span class="keyword">end</span>
-0188 
-0189    Fit.reps = reps;
-0190    <span class="comment">% replaced this with ntail</span>
-0191    <span class="comment">% Fit.numtau  = numel(x(x&gt;Fit.tau0_avg));</span>
-0192 <span class="keyword">end</span>
-0193 
-0194 <span class="comment">%% INPUT PARSER</span>
-0195 <a name="_sub2" href="#_subfunctions" class="code">function [x, xmin, range, limit, method, bootfit, nreps, plotfit] = </a><span class="keyword">...</span>
-0196       parseinputs(x, varargin)
-0197    parser = inputParser;
-0198    parser.FunctionName = <span class="string">'baseflow.plfitb'</span>;
-0199 
-0200    parser.addRequired(<span class="string">'x'</span>, @isnumeric);
-0201    parser.addParameter(<span class="string">'xmin'</span>, nan, @isnumeric);
-0202    parser.addParameter(<span class="string">'range'</span>, 1.01:0.01:25.01, @isnumeric);
-0203    parser.addParameter(<span class="string">'limit'</span>, [], @isnumeric);
-0204    parser.addParameter(<span class="string">'method'</span>, <span class="string">'clauset'</span>, @ischar);
-0205    parser.addParameter(<span class="string">'bootfit'</span>, false, @islogical);
-0206    parser.addParameter(<span class="string">'bootreps'</span>, 1000, @isnumeric);
-0207    parser.addParameter(<span class="string">'plotfit'</span>, false, @islogical);
-0208 
-0209    parser.parse(x, varargin{:});
-0210 
-0211    xmin    = parser.Results.xmin;
-0212    range   = parser.Results.range;
-0213    limit   = parser.Results.limit;
-0214    method  = parser.Results.method;
-0215    bootfit = parser.Results.bootfit;
-0216    nreps   = parser.Results.bootreps;
-0217    plotfit = parser.Results.plotfit;
-0218 <span class="keyword">end</span>
-0219 
-0220 <span class="comment">%% extra</span>
-0221 <span class="comment">% As a rough check on the sampling distribution of the parameter</span>
-0222 <span class="comment">% estimators, we can look at histograms of the bootstrap replicates.</span>
-0223 <span class="comment">% figure; subplot(1,3,1);</span>
-0224 <span class="comment">% histogram(reps.b);</span>
-0225 <span class="comment">% title('Bootstrap estimates of $b$');</span>
-0226 <span class="comment">% subplot(1,3,2);</span>
-0227 <span class="comment">% histogram(reps.tau0);</span>
-0228 <span class="comment">% title('Bootstrap estimates of $\tau_0$');</span>
-0229 <span class="comment">% subplot(1,3,3);</span>
-0230 <span class="comment">% histogram(reps.alpha);</span>
-0231 <span class="comment">% title('Bootstrap estimates of $\alpha$');</span>
-0232 
-0233 <span class="comment">%    % it is incorrect to apply the standard formula so don't use this</span>
-0234 <span class="comment">%    for n = 1:numel(vars)</span>
-0235 <span class="comment">%       var = vars{n};</span>
-0236 <span class="comment">%       [SE,CI,~,mu,sig] = stderror(reps.(var));</span>
-0237 <span class="comment">%       Fit.([var '_avg']) = mu;</span>
-0238 <span class="comment">%       Fit.([var '_L']) = CI(1);</span>
-0239 <span class="comment">%       Fit.([var '_H']) = CI(2);</span>
-0240 <span class="comment">%       Fit.([var '_sig']) = sig;</span>
-0241 <span class="comment">%       Fit.([var '_SE']) = SE;</span>
-0242 <span class="comment">%    end</span>
-0243 
-0244 
-0245 <span class="comment">% % this might still be a good approach, just need to figure out how to get the</span>
-0246 <span class="comment">% stdv of xmin</span>
-0247 <span class="comment">% function Fit = bootstrap_alpha(x,range,limit)</span>
+0158 <span class="comment">%% LOCAL FUNCTIONS</span>
+0159 
+0160 <span class="comment">% bootstrap confidence intervals</span>
+0161 <a name="_sub1" href="#_subfunctions" class="code">function Fit = plbootfit(x,range,limit,nreps)</a>
+0162 
+0163    <span class="comment">%[alpha,xmin,L,D] = baseflow.deps.plfit(x,'range',range,'limit',limit);</span>
+0164    [~,~,~,repsmat] = baseflow.deps.plvar( <span class="keyword">...</span>
+0165       x, <span class="string">'range'</span>, range, <span class="string">'limit'</span>, limit, <span class="string">'reps'</span>, nreps, <span class="string">'silent'</span>);
+0166 
+0167    vars        = {<span class="string">'tau0'</span>,<span class="string">'alpha'</span>,<span class="string">'b'</span>,<span class="string">'tau'</span>,<span class="string">'ntail'</span>};
+0168    reps.ntail  = repsmat(:,1);
+0169    reps.tau0   = repsmat(:,2);
+0170    reps.alpha  = repsmat(:,3);
+0171    reps.b      = baseflow.conversions(reps.alpha,<span class="string">'alpha'</span>,<span class="string">'b'</span>);
+0172    reps.tau    = expectedtau(reps.tau0,reps.b);
+0173 
+0174    <span class="comment">% tau = tau0*(2-b)/(3-2*b) has a pole at b = 3/2, which is alpha = 2. A</span>
+0175    <span class="comment">% replicate beyond it has an infinite tau, so the tau mean and sigma are</span>
+0176    <span class="comment">% Inf or NaN, and expectedtau warns with the count of such replicates.</span>
+0177 
+0178    <span class="keyword">for</span> n = 1:numel(vars)
+0179       var = vars{n};
+0180       Fit.(var) = mean(reps.(var));
+0181       Fit.([var <span class="string">'_sig'</span>]) = std(reps.(var));
+0182       Fit.([var <span class="string">'_L'</span>]) = mean(reps.(var)) - 1.96*std(reps.(var));
+0183       Fit.([var <span class="string">'_H'</span>]) = mean(reps.(var)) + 1.96*std(reps.(var));
+0184    <span class="keyword">end</span>
+0185 
+0186    Fit.reps = reps;
+0187    <span class="comment">% replaced this with ntail</span>
+0188    <span class="comment">% Fit.numtau  = numel(x(x&gt;Fit.tau0_avg));</span>
+0189 <span class="keyword">end</span>
+0190 
+0191 <span class="comment">%% INPUT PARSER</span>
+0192 <a name="_sub2" href="#_subfunctions" class="code">function [x, xmin, range, limit, method, bootfit, nreps, plotfit] = </a><span class="keyword">...</span>
+0193       parseinputs(x, varargin)
+0194    parser = inputParser;
+0195    parser.FunctionName = <span class="string">'baseflow.plfitb'</span>;
+0196 
+0197    parser.addRequired(<span class="string">'x'</span>, @isnumeric);
+0198    parser.addParameter(<span class="string">'xmin'</span>, nan, @isnumeric);
+0199    parser.addParameter(<span class="string">'range'</span>, 1.01:0.01:25.01, @isnumeric);
+0200    parser.addParameter(<span class="string">'limit'</span>, [], @isnumeric);
+0201    parser.addParameter(<span class="string">'method'</span>, <span class="string">'clauset'</span>, @ischar);
+0202    parser.addParameter(<span class="string">'bootfit'</span>, false, @islogical);
+0203    parser.addParameter(<span class="string">'bootreps'</span>, 1000, @isnumeric);
+0204    parser.addParameter(<span class="string">'plotfit'</span>, false, @islogical);
+0205 
+0206    parser.parse(x, varargin{:});
+0207 
+0208    xmin    = parser.Results.xmin;
+0209    range   = parser.Results.range;
+0210    limit   = parser.Results.limit;
+0211    method  = parser.Results.method;
+0212    bootfit = parser.Results.bootfit;
+0213    nreps   = parser.Results.bootreps;
+0214    plotfit = parser.Results.plotfit;
+0215 <span class="keyword">end</span>
+0216 
+0217 <span class="comment">%% extra</span>
+0218 <span class="comment">% As a rough check on the sampling distribution of the parameter</span>
+0219 <span class="comment">% estimators, we can look at histograms of the bootstrap replicates.</span>
+0220 <span class="comment">% figure; subplot(1,3,1);</span>
+0221 <span class="comment">% histogram(reps.b);</span>
+0222 <span class="comment">% title('Bootstrap estimates of $b$');</span>
+0223 <span class="comment">% subplot(1,3,2);</span>
+0224 <span class="comment">% histogram(reps.tau0);</span>
+0225 <span class="comment">% title('Bootstrap estimates of $\tau_0$');</span>
+0226 <span class="comment">% subplot(1,3,3);</span>
+0227 <span class="comment">% histogram(reps.alpha);</span>
+0228 <span class="comment">% title('Bootstrap estimates of $\alpha$');</span>
+0229 
+0230 <span class="comment">%    % it is incorrect to apply the standard formula so don't use this</span>
+0231 <span class="comment">%    for n = 1:numel(vars)</span>
+0232 <span class="comment">%       var = vars{n};</span>
+0233 <span class="comment">%       [SE,CI,~,mu,sig] = stderror(reps.(var));</span>
+0234 <span class="comment">%       Fit.([var '_avg']) = mu;</span>
+0235 <span class="comment">%       Fit.([var '_L']) = CI(1);</span>
+0236 <span class="comment">%       Fit.([var '_H']) = CI(2);</span>
+0237 <span class="comment">%       Fit.([var '_sig']) = sig;</span>
+0238 <span class="comment">%       Fit.([var '_SE']) = SE;</span>
+0239 <span class="comment">%    end</span>
+0240 
+0241 
+0242 <span class="comment">% % this might still be a good approach, just need to figure out how to get the</span>
+0243 <span class="comment">% stdv of xmin</span>
+0244 <span class="comment">% function Fit = bootstrap_alpha(x,range,limit)</span>
+0245 <span class="comment">%</span>
+0246 <span class="comment">%    % first get xmin, bootstrap won't change this</span>
+0247 <span class="comment">%    [~,xmin] = baseflow.deps.plfit(x,'range',range,'limit',limit);</span>
 0248 <span class="comment">%</span>
-0249 <span class="comment">%    % first get xmin, bootstrap won't change this</span>
-0250 <span class="comment">%    [~,xmin] = baseflow.deps.plfit(x,'range',range,'limit',limit);</span>
+0249 <span class="comment">%    % now bootstrap alpha</span>
+0250 <span class="comment">%    reps  = bootstrp(1000,@(x,xmin)plfit(x,'xmin',xmin),x,xmin);</span>
 0251 <span class="comment">%</span>
-0252 <span class="comment">%    % now bootstrap alpha</span>
-0253 <span class="comment">%    reps  = bootstrp(1000,@(x,xmin)plfit(x,'xmin',xmin),x,xmin);</span>
-0254 <span class="comment">%</span>
-0255 <span class="comment">%    Fit.alpha = mean(reps);</span>
-0256 <span class="comment">%    Fit.tau0 = xmin;</span>
-0257 <span class="comment">%    Fit.alpha_sig = std(reps);</span>
-0258 <span class="comment">%    %Fit.tau0_sig % this is why we use plbootfit b/c it returns xmin_sig</span>
-0259 <span class="comment">%    Fit.reps = reps;</span>
-0260 <span class="comment">%</span>
-0261 <span class="comment">%    % see the appendix</span>
-0262 <span class="comment">%    % N = numel(reps)</span>
-0263 <span class="comment">%    % alphatrue = (1 + alpha*(N-1))/N</span>
-0264 <span class="comment">%    % alphasig = N*(alphatrue-1)/((N-1)*sqrt(N-2))</span>
-0265 <span class="comment">%    % N*(alpha-1)/((N-1)*sqrt(N-2))</span>
-0266 <span class="comment">% end</span></pre></div>
+0252 <span class="comment">%    Fit.alpha = mean(reps);</span>
+0253 <span class="comment">%    Fit.tau0 = xmin;</span>
+0254 <span class="comment">%    Fit.alpha_sig = std(reps);</span>
+0255 <span class="comment">%    %Fit.tau0_sig % this is why we use plbootfit b/c it returns xmin_sig</span>
+0256 <span class="comment">%    Fit.reps = reps;</span>
+0257 <span class="comment">%</span>
+0258 <span class="comment">%    % see the appendix</span>
+0259 <span class="comment">%    % N = numel(reps)</span>
+0260 <span class="comment">%    % alphatrue = (1 + alpha*(N-1))/N</span>
+0261 <span class="comment">%    % alphasig = N*(alphatrue-1)/((N-1)*sqrt(N-2))</span>
+0262 <span class="comment">%    % N*(alpha-1)/((N-1)*sqrt(N-2))</span>
+0263 <span class="comment">% end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/plplotb.html b/toolbox/docs/html/m2html/+baseflow/plplotb.html
index 364e6a9..38433cc 100644
--- a/toolbox/docs/html/m2html/+baseflow/plplotb.html
+++ b/toolbox/docs/html/m2html/+baseflow/plplotb.html
@@ -63,7 +63,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
                  similar to 'axis tight' option (b/c power law data is often
                  covering many orders of magnitude).
      labelplot = logical scalar indicating whether to add a label showing
-                 the value of xmin and the expected value of x.
+                 the value of xmin and the expected value of x. The
+                 expected value diverges at alpha &lt;= 2, so the label
+                 omits it there.
      ax        = graphic axis to plot into.
 
  See also: plfit, <a href="plfitb.html" class="code" title="function varargout = plfitb(x,varargin)">plfitb</a>, <a href="gpfitb.html" class="code" title="function [Fit, bM, alphaM, kM] = gpfitb(x, varargin)">gpfitb</a>, <a href="eventtau.html" class="code" title="function [tau,q,dqdt,tags,aggvals] = eventtau(Results,Events,Fits,varargin)">eventtau</a>
@@ -132,193 +134,199 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0035    <span class="comment">%                 similar to 'axis tight' option (b/c power law data is often</span>
 0036    <span class="comment">%                 covering many orders of magnitude).</span>
 0037    <span class="comment">%     labelplot = logical scalar indicating whether to add a label showing</span>
-0038    <span class="comment">%                 the value of xmin and the expected value of x.</span>
-0039    <span class="comment">%     ax        = graphic axis to plot into.</span>
-0040    <span class="comment">%</span>
-0041    <span class="comment">% See also: plfit, plfitb, gpfitb, eventtau</span>
+0038    <span class="comment">%                 the value of xmin and the expected value of x. The</span>
+0039    <span class="comment">%                 expected value diverges at alpha &lt;= 2, so the label</span>
+0040    <span class="comment">%                 omits it there.</span>
+0041    <span class="comment">%     ax        = graphic axis to plot into.</span>
 0042    <span class="comment">%</span>
-0043    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0044 
-0045    <span class="comment">% if called with no input, open this file</span>
-0046    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0047 
-0048    <span class="comment">% PARSE INPUTS</span>
-0049    [x, xmin, alpha, alphaci, xminci, varsym, trimline, labelplot] = <span class="keyword">...</span>
-0050       parseinputs(x, xmin, alpha, varargin{:});
-0051 
-0052    <span class="comment">% Compute the complementary cumulative distribution function</span>
-0053    N = numel(x);
-0054    xccp = sort(x);
-0055    yccp = (N:-1:1)'./N;
-0056    refy = yccp(find(xccp&gt;=xmin,1,<span class="string">'first'</span>));
-0057 
-0058    <span class="comment">% Option to extend the line forward a bit (purely aesthetic)</span>
-0059    <span class="keyword">if</span> trimline == true
-0060       xccfit = sort(x(x&gt;=xmin));
-0061       xccfit = [xccfit; xccfit(end)*1.2];
-0062    <span class="keyword">else</span>
-0063       xccfit = sort(x); <span class="comment">% this extends the line back toward the origin</span>
-0064       xccfit = [xccfit; xccfit(end)*1.2]; <span class="comment">% this extends the line forward a bit</span>
-0065    <span class="keyword">end</span>
-0066 
-0067    <span class="comment">% Compute the theoretical ccdf</span>
-0068    yccfit = (xccfit./xmin).^(1-alpha);
-0069 
-0070    <span class="comment">% scale the fitted x&gt;xmin ccdf to pass through the refPoint</span>
-0071    yccfit = yccfit.*refy;
-0072    xccfit = xccfit(yccfit&lt;=1);
-0073    yccfit = yccfit(yccfit&lt;=1);
-0074 
-0075    <span class="comment">% Create the figure</span>
-0076    <span class="comment">% figure('Position',[0 0 300 200]); ax = gca; % for publishing:</span>
-0077    figure(<span class="string">'Position'</span>,[0 0 500 400]);
-0078    ax = gca;
-0079 
-0080    <span class="comment">% plot it</span>
-0081    h.data = loglog(ax,xccp,yccp,<span class="string">'o'</span>,<span class="string">'LineWidth'</span>,0.5,<span class="string">'MarkerSize'</span>,10, <span class="keyword">...</span>
-0082       <span class="string">'MarkerFaceColor'</span>,<span class="string">'w'</span>); hold on;
-0083    h.fit = loglog(ax,xccfit,yccfit,<span class="string">'LineWidth'</span>,3);
-0084 
-0085    <span class="comment">% compute b for the legend</span>
-0086    b = baseflow.conversions(alpha,<span class="string">'alpha'</span>,<span class="string">'b'</span>);
-0087 
-0088    <span class="comment">% build a legend, labels, etc.</span>
-0089    l1 = [<span class="string">'$'</span> varsym <span class="string">'$ (data)'</span>];
-0090    <span class="keyword">if</span> ~isnan(alphaci)
-0091       bL = baseflow.conversions(alphaci(1),<span class="string">'alpha'</span>,<span class="string">'b'</span>);
-0092       bH = baseflow.conversions(alphaci(2),<span class="string">'alpha'</span>,<span class="string">'b'</span>);
-0093       <span class="comment">% The caller supplies alphaci and its coverage level is unknown here,</span>
-0094       <span class="comment">% so the label states the interval and names no level. plfitb passes</span>
-0095       <span class="comment">% one bootstrap standard deviation, which is not a 95% interval.</span>
-0096       l2 = sprintf(<span class="string">'MLE fit ($\\hat{b}=%.2f\\ [$%.2f,%.2f$]$ CI)'</span>,b,bL,bH);
-0097    <span class="keyword">else</span>
-0098       l2 = sprintf(<span class="string">'MLE fit ($b=%.2f$)'</span>,baseflow.conversions(alpha,<span class="string">'alpha'</span>,<span class="string">'b'</span>));
-0099       bL = nan;
-0100       bH = nan;
-0101    <span class="keyword">end</span>
-0102 
-0103    xtext = <span class="string">'$x$'</span>;
-0104    ytext = [<span class="string">'$p('</span> varsym <span class="string">'\ge x)$'</span>];
-0105 
-0106    <span class="keyword">if</span> isoctave
-0107       l1 = latex2tex(l1);
-0108       l2 = sprintf(<span class="string">'MLE fit (b=%.2f [%.2f,%.2f] CI)'</span>,b,bL,bH);
-0109       xlabel(latex2tex(xtext),<span class="string">'Interpreter'</span>,<span class="string">'tex'</span>);
-0110       ylabel(latex2tex(ytext),<span class="string">'Interpreter'</span>,<span class="string">'tex'</span>);
-0111       h.legend = legend({l1,l2},<span class="string">'interpreter'</span>,<span class="string">'tex'</span>,<span class="string">'location'</span>,<span class="string">'southwest'</span>);
-0112    <span class="keyword">else</span>
-0113       xlabel(xtext,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
-0114       ylabel(ytext,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
-0115       h.legend = legend({l1,l2},<span class="string">'interpreter'</span>,<span class="string">'latex'</span>,<span class="string">'location'</span>,<span class="string">'southwest'</span>);
-0116    <span class="keyword">end</span>
-0117 
-0118    <span class="comment">% h.legend.Position = [0.27 0.40 0.30 0.10];</span>
+0043    <span class="comment">% See also: plfit, plfitb, gpfitb, eventtau</span>
+0044    <span class="comment">%</span>
+0045    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0046 
+0047    <span class="comment">% if called with no input, open this file</span>
+0048    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0049 
+0050    <span class="comment">% PARSE INPUTS</span>
+0051    [x, xmin, alpha, alphaci, xminci, varsym, trimline, labelplot] = <span class="keyword">...</span>
+0052       parseinputs(x, xmin, alpha, varargin{:});
+0053 
+0054    <span class="comment">% Compute the complementary cumulative distribution function</span>
+0055    N = numel(x);
+0056    xccp = sort(x);
+0057    yccp = (N:-1:1)'./N;
+0058    refy = yccp(find(xccp&gt;=xmin,1,<span class="string">'first'</span>));
+0059 
+0060    <span class="comment">% Option to extend the line forward a bit (purely aesthetic)</span>
+0061    <span class="keyword">if</span> trimline == true
+0062       xccfit = sort(x(x&gt;=xmin));
+0063       xccfit = [xccfit; xccfit(end)*1.2];
+0064    <span class="keyword">else</span>
+0065       xccfit = sort(x); <span class="comment">% this extends the line back toward the origin</span>
+0066       xccfit = [xccfit; xccfit(end)*1.2]; <span class="comment">% this extends the line forward a bit</span>
+0067    <span class="keyword">end</span>
+0068 
+0069    <span class="comment">% Compute the theoretical ccdf</span>
+0070    yccfit = (xccfit./xmin).^(1-alpha);
+0071 
+0072    <span class="comment">% scale the fitted x&gt;xmin ccdf to pass through the refPoint</span>
+0073    yccfit = yccfit.*refy;
+0074    xccfit = xccfit(yccfit&lt;=1);
+0075    yccfit = yccfit(yccfit&lt;=1);
+0076 
+0077    <span class="comment">% Create the figure</span>
+0078    <span class="comment">% figure('Position',[0 0 300 200]); ax = gca; % for publishing:</span>
+0079    figure(<span class="string">'Position'</span>,[0 0 500 400]);
+0080    ax = gca;
+0081 
+0082    <span class="comment">% plot it</span>
+0083    h.data = loglog(ax,xccp,yccp,<span class="string">'o'</span>,<span class="string">'LineWidth'</span>,0.5,<span class="string">'MarkerSize'</span>,10, <span class="keyword">...</span>
+0084       <span class="string">'MarkerFaceColor'</span>,<span class="string">'w'</span>); hold on;
+0085    h.fit = loglog(ax,xccfit,yccfit,<span class="string">'LineWidth'</span>,3);
+0086 
+0087    <span class="comment">% compute b for the legend</span>
+0088    b = baseflow.conversions(alpha,<span class="string">'alpha'</span>,<span class="string">'b'</span>);
+0089 
+0090    <span class="comment">% build a legend, labels, etc.</span>
+0091    l1 = [<span class="string">'$'</span> varsym <span class="string">'$ (data)'</span>];
+0092    <span class="keyword">if</span> ~isnan(alphaci)
+0093       bL = baseflow.conversions(alphaci(1),<span class="string">'alpha'</span>,<span class="string">'b'</span>);
+0094       bH = baseflow.conversions(alphaci(2),<span class="string">'alpha'</span>,<span class="string">'b'</span>);
+0095       <span class="comment">% The caller supplies alphaci and its coverage level is unknown here,</span>
+0096       <span class="comment">% so the label states the interval and names no level. plfitb passes</span>
+0097       <span class="comment">% one bootstrap standard deviation, which is not a 95% interval.</span>
+0098       l2 = sprintf(<span class="string">'MLE fit ($\\hat{b}=%.2f\\ [$%.2f,%.2f$]$ CI)'</span>,b,bL,bH);
+0099    <span class="keyword">else</span>
+0100       l2 = sprintf(<span class="string">'MLE fit ($b=%.2f$)'</span>,baseflow.conversions(alpha,<span class="string">'alpha'</span>,<span class="string">'b'</span>));
+0101       bL = nan;
+0102       bH = nan;
+0103    <span class="keyword">end</span>
+0104 
+0105    xtext = <span class="string">'$x$'</span>;
+0106    ytext = [<span class="string">'$p('</span> varsym <span class="string">'\ge x)$'</span>];
+0107 
+0108    <span class="keyword">if</span> isoctave
+0109       l1 = latex2tex(l1);
+0110       l2 = sprintf(<span class="string">'MLE fit (b=%.2f [%.2f,%.2f] CI)'</span>,b,bL,bH);
+0111       xlabel(latex2tex(xtext),<span class="string">'Interpreter'</span>,<span class="string">'tex'</span>);
+0112       ylabel(latex2tex(ytext),<span class="string">'Interpreter'</span>,<span class="string">'tex'</span>);
+0113       h.legend = legend({l1,l2},<span class="string">'interpreter'</span>,<span class="string">'tex'</span>,<span class="string">'location'</span>,<span class="string">'southwest'</span>);
+0114    <span class="keyword">else</span>
+0115       xlabel(xtext,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
+0116       ylabel(ytext,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>);
+0117       h.legend = legend({l1,l2},<span class="string">'interpreter'</span>,<span class="string">'latex'</span>,<span class="string">'location'</span>,<span class="string">'southwest'</span>);
+0118    <span class="keyword">end</span>
 0119 
-0120    <span class="keyword">if</span> ~isnan(xminci)
-0121       xminL = xminci(1);
-0122       xminH = xminci(2);
-0123    <span class="keyword">else</span>
-0124       xminL = xmin;
-0125       xminH = xmin;
-0126    <span class="keyword">end</span>
-0127 
-0128    <span class="keyword">if</span> labelplot == true
-0129       <span class="comment">%addlabels(xccfit,ccfit,xmin,xminL,xminH,b,bL,bH,refy);</span>
-0130       <a href="#_sub1" class="code" title="subfunction addlabels(xfit,yfit,tau0,tau0L,tau0H,b)">addlabels</a>(xccfit,yccfit,xmin,xminL,xminH,b);
-0131    <span class="keyword">end</span>
-0132 
-0133    <span class="comment">% add a little white space above P=1</span>
-0134    h.ax = gca;
-0135    ylimits = get(ax, <span class="string">'YLim'</span>);
-0136    ylimits(2) = 1.5;
-0137    set(h.ax, <span class="string">'YLim'</span>, ylimits);
-0138    hold off
-0139 <span class="keyword">end</span>
-0140 
-0141 <span class="comment">%% LOCAL FUNCTIONS</span>
-0142 <a name="_sub1" href="#_subfunctions" class="code">function addlabels(xfit,yfit,tau0,tau0L,tau0H,b)</a>
-0143    <span class="comment">%ADDLABELS add an arrow pointing to tau0 and tau_exp</span>
-0144 
-0145    <span class="comment">% The labels are latex, and Octave has no latex text interpreter, so it</span>
-0146    <span class="comment">% would draw the markup. drawarrow itself runs in both languages.</span>
-0147    <span class="keyword">if</span> isoctave
-0148       <span class="keyword">return</span>
-0149    <span class="keyword">end</span>
-0150 
-0151    <span class="comment">% tau0</span>
-0152    xminc = (tau0H-tau0+tau0-tau0L)/2;
-0153    xlims = xlim;
-0154    ndecx = log10(xlims(2))-log10(xlims(1));
-0155    xarrw = [10^(log10(tau0)-ndecx/10) tau0];
-0156    yarrw = yfit(find(xfit&gt;=xarrw(1),1,<span class="string">'first'</span>));
-0157    yarrw = [yarrw yarrw];
-0158 
-0159    <span class="comment">% build the string with plus/minus if tau0L/H is provided</span>
-0160    <span class="keyword">if</span> tau0==tau0L &amp;&amp; tau0==tau0H
-0161       ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f$ days'</span>,tau0);
-0162    <span class="keyword">else</span>
-0163       ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f\\pm%.0f$ days'</span>,tau0,xminc);
-0164    <span class="keyword">end</span>
-0165 
-0166    <span class="comment">% draw the arrow in the current axes, which is the axes the caller</span>
-0167    <span class="comment">% plotted into, as the text call below uses</span>
-0168    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
-0169    text(0.95*xarrw(1),yarrw(1),ta, <span class="keyword">...</span>
-0170       <span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>,<span class="string">'FontSize'</span>,14,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>)
-0171 
-0172    <span class="comment">% % tauExp</span>
-0173    <span class="comment">%----------------------------------------------------------------------------</span>
-0174    <span class="comment">% test using the new xminL/H</span>
-0175    <span class="comment">% deactivate this and reactive the two lines below to go back</span>
-0176    xexp = tau0*(2-b)/(3-2*b);
-0177    tauL = tau0L*(2-b)/(3-2*b);
-0178    tauH = tau0H*(2-b)/(3-2*b);
-0179    xexpc = (tauH-tauL)/2;
-0180    <span class="comment">% xexp  = mean((tau0*(2-bL)/(3-2*bL) + tau0*(2-bH)/(3-2*bH))/2);</span>
-0181    <span class="comment">% xexpc = mean(abs(xexp-[tau0*(2-bL)/(3-2*bL), tau0*(2-bH)/(3-2*bH)]));</span>
-0182    <span class="comment">%----------------------------------------------------------------------------</span>
-0183 
-0184    xarrw = [10^(log10(xexp)-ndecx/10) xexp];
-0185    yarrw = yfit(find(xfit&gt;=xarrw(2),1,<span class="string">'first'</span>));
-0186    yarrw = [yarrw yarrw];
-0187 
-0188    <span class="comment">% build the string with plus/minus if tau0L/H is provided</span>
-0189    <span class="keyword">if</span> tau0==tau0L &amp;&amp; tau0==tau0H
-0190       ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f$ days'</span>,xexp);
-0191    <span class="keyword">else</span>
-0192       ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days'</span>,xexp,xexpc);
-0193    <span class="keyword">end</span>
-0194 
-0195    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
-0196    text(0.95*xarrw(1),yarrw(1),ta, <span class="keyword">...</span>
-0197       <span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>,<span class="string">'FontSize'</span>,14,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>)
-0198 <span class="keyword">end</span>
-0199 
-0200 <span class="comment">%% INPUT PARSER</span>
-0201 <a name="_sub2" href="#_subfunctions" class="code">function [x, xmin, alpha, alphaci, xminci, varsym, trimline, labelplot] = </a><span class="keyword">...</span>
-0202       parseinputs(x, xmin, alpha, varargin)
-0203 
-0204    parser = inputParser;
-0205    parser.FunctionName = <span class="string">'baseflow.plplotb'</span>;
-0206    parser.CaseSensitive = false;
-0207    parser.KeepUnmatched = true;
-0208 
-0209    parser.addRequired(<span class="string">'x'</span>, @isnumeric);
-0210    parser.addRequired(<span class="string">'xmin'</span>, @isnumeric);
-0211    parser.addRequired(<span class="string">'alpha'</span>, @isnumeric);
-0212    parser.addParameter(<span class="string">'alphaci'</span>, nan, @isnumeric);
-0213    parser.addParameter(<span class="string">'xminci'</span>, nan, @isnumeric);
-0214    parser.addParameter(<span class="string">'varsym'</span>, <span class="string">'\tau'</span>, @ischar);
-0215    parser.addParameter(<span class="string">'trimline'</span>, false, @islogical);
-0216    parser.addParameter(<span class="string">'labelplot'</span>, true, @islogical);
-0217 
-0218    parser.parse(x, xmin, alpha, varargin{:});
-0219 
-0220    alphaci     = parser.Results.alphaci;
-0221    xminci      = parser.Results.xminci;
-0222    varsym      = parser.Results.varsym;
-0223    trimline    = parser.Results.trimline;
-0224    labelplot   = parser.Results.labelplot;
-0225 <span class="keyword">end</span></pre></div>
+0120    <span class="comment">% h.legend.Position = [0.27 0.40 0.30 0.10];</span>
+0121 
+0122    <span class="keyword">if</span> ~isnan(xminci)
+0123       xminL = xminci(1);
+0124       xminH = xminci(2);
+0125    <span class="keyword">else</span>
+0126       xminL = xmin;
+0127       xminH = xmin;
+0128    <span class="keyword">end</span>
+0129 
+0130    <span class="keyword">if</span> labelplot == true
+0131       <span class="comment">%addlabels(xccfit,ccfit,xmin,xminL,xminH,b,bL,bH,refy);</span>
+0132       <a href="#_sub1" class="code" title="subfunction addlabels(xfit,yfit,tau0,tau0L,tau0H,b)">addlabels</a>(xccfit,yccfit,xmin,xminL,xminH,b);
+0133    <span class="keyword">end</span>
+0134 
+0135    <span class="comment">% add a little white space above P=1</span>
+0136    h.ax = gca;
+0137    ylimits = get(ax, <span class="string">'YLim'</span>);
+0138    ylimits(2) = 1.5;
+0139    set(h.ax, <span class="string">'YLim'</span>, ylimits);
+0140    hold off
+0141 <span class="keyword">end</span>
+0142 
+0143 <span class="comment">%% LOCAL FUNCTIONS</span>
+0144 <a name="_sub1" href="#_subfunctions" class="code">function addlabels(xfit,yfit,tau0,tau0L,tau0H,b)</a>
+0145    <span class="comment">%ADDLABELS add an arrow pointing to tau0 and tau_exp</span>
+0146 
+0147    <span class="comment">% The labels are latex, and Octave has no latex text interpreter, so it</span>
+0148    <span class="comment">% would draw the markup. drawarrow itself runs in both languages.</span>
+0149    <span class="keyword">if</span> isoctave
+0150       <span class="keyword">return</span>
+0151    <span class="keyword">end</span>
+0152 
+0153    <span class="comment">% tau0</span>
+0154    xminc = (tau0H-tau0+tau0-tau0L)/2;
+0155    xlims = xlim;
+0156    ndecx = log10(xlims(2))-log10(xlims(1));
+0157    xarrw = [10^(log10(tau0)-ndecx/10) tau0];
+0158    yarrw = yfit(find(xfit&gt;=xarrw(1),1,<span class="string">'first'</span>));
+0159    yarrw = [yarrw yarrw];
+0160 
+0161    <span class="comment">% build the string with plus/minus if tau0L/H is provided</span>
+0162    <span class="keyword">if</span> tau0==tau0L &amp;&amp; tau0==tau0H
+0163       ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f$ days'</span>,tau0);
+0164    <span class="keyword">else</span>
+0165       ta = sprintf(<span class="string">'$\\hat{\\tau}_0=%.0f\\pm%.0f$ days'</span>,tau0,xminc);
+0166    <span class="keyword">end</span>
+0167 
+0168    <span class="comment">% draw the arrow in the current axes, which is the axes the caller</span>
+0169    <span class="comment">% plotted into, as the text call below uses</span>
+0170    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
+0171    text(0.95*xarrw(1),yarrw(1),ta, <span class="keyword">...</span>
+0172       <span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>,<span class="string">'FontSize'</span>,14,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>)
+0173 
+0174    <span class="comment">% % tauExp</span>
+0175    <span class="comment">%----------------------------------------------------------------------------</span>
+0176    <span class="comment">% test using the new xminL/H</span>
+0177    <span class="comment">% deactivate this and reactive the two lines below to go back</span>
+0178    tauexp = expectedtau([tau0 tau0L tau0H],b);
+0179    xexp = tauexp(1);
+0180    xexpc = (tauexp(3)-tauexp(2))/2;
+0181    <span class="comment">% xexp  = mean((tau0*(2-bL)/(3-2*bL) + tau0*(2-bH)/(3-2*bH))/2);</span>
+0182    <span class="comment">% xexpc = mean(abs(xexp-[tau0*(2-bL)/(3-2*bL), tau0*(2-bH)/(3-2*bH)]));</span>
+0183    <span class="comment">%----------------------------------------------------------------------------</span>
+0184 
+0185    <span class="comment">% a mean beyond the tau pole has no point on the axes to label</span>
+0186    <span class="keyword">if</span> ~isfinite(xexp)
+0187       <span class="keyword">return</span>
+0188    <span class="keyword">end</span>
+0189 
+0190    xarrw = [10^(log10(xexp)-ndecx/10) xexp];
+0191    yarrw = yfit(find(xfit&gt;=xarrw(2),1,<span class="string">'first'</span>));
+0192    yarrw = [yarrw yarrw];
+0193 
+0194    <span class="comment">% build the string with plus/minus if tau0L/H is provided</span>
+0195    <span class="keyword">if</span> tau0==tau0L &amp;&amp; tau0==tau0H
+0196       ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f$ days'</span>,xexp);
+0197    <span class="keyword">else</span>
+0198       ta = sprintf(<span class="string">'$\\langle\\tau\\rangle=%.0f\\pm%.0f$ days'</span>,xexp,xexpc);
+0199    <span class="keyword">end</span>
+0200 
+0201    drawarrow(gca, [xarrw(1),yarrw(1)], [xarrw(2),yarrw(2)]);
+0202    text(0.95*xarrw(1),yarrw(1),ta, <span class="keyword">...</span>
+0203       <span class="string">'HorizontalAlignment'</span>,<span class="string">'right'</span>,<span class="string">'FontSize'</span>,14,<span class="string">'Interpreter'</span>,<span class="string">'latex'</span>)
+0204 <span class="keyword">end</span>
+0205 
+0206 <span class="comment">%% INPUT PARSER</span>
+0207 <a name="_sub2" href="#_subfunctions" class="code">function [x, xmin, alpha, alphaci, xminci, varsym, trimline, labelplot] = </a><span class="keyword">...</span>
+0208       parseinputs(x, xmin, alpha, varargin)
+0209 
+0210    parser = inputParser;
+0211    parser.FunctionName = <span class="string">'baseflow.plplotb'</span>;
+0212    parser.CaseSensitive = false;
+0213    parser.KeepUnmatched = true;
+0214 
+0215    parser.addRequired(<span class="string">'x'</span>, @isnumeric);
+0216    parser.addRequired(<span class="string">'xmin'</span>, @isnumeric);
+0217    parser.addRequired(<span class="string">'alpha'</span>, @isnumeric);
+0218    parser.addParameter(<span class="string">'alphaci'</span>, nan, @isnumeric);
+0219    parser.addParameter(<span class="string">'xminci'</span>, nan, @isnumeric);
+0220    parser.addParameter(<span class="string">'varsym'</span>, <span class="string">'\tau'</span>, @ischar);
+0221    parser.addParameter(<span class="string">'trimline'</span>, false, @islogical);
+0222    parser.addParameter(<span class="string">'labelplot'</span>, true, @islogical);
+0223 
+0224    parser.parse(x, xmin, alpha, varargin{:});
+0225 
+0226    alphaci     = parser.Results.alphaci;
+0227    xminci      = parser.Results.xminci;
+0228    varsym      = parser.Results.varsym;
+0229    trimline    = parser.Results.trimline;
+0230    labelplot   = parser.Results.labelplot;
+0231 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/pointcloudintercept.html b/toolbox/docs/html/m2html/+baseflow/pointcloudintercept.html
index 2205b20..0a30cde 100644
--- a/toolbox/docs/html/m2html/+baseflow/pointcloudintercept.html
+++ b/toolbox/docs/html/m2html/+baseflow/pointcloudintercept.html
@@ -51,7 +51,8 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      reference point that the line passes through. For 'envelope', they
      are the refqtls quantiles of q and -dqdt. For 'median' and
      'brutsaert', they are the medians of q and -dqdt. For 'mean', they
-     are the means of log(q) and log(-dqdt).
+     are the geometric means of q and -dqdt. ahatLH pivots the line
+     through (xbar, ybar) with the slopes in bci.
 
  Required inputs
 
@@ -66,7 +67,7 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
   refqtls  =  reference quantiles that together define a pivot point through
               which the straight line must pass. use with method 'envelope'.
   bci      =  [bL bH] confidence interval of bhat, used to compute the
-              bounds ahatLH (default nan, which returns NaN bounds)
+              bounds ahatLH (default [nan nan], which returns NaN bounds)
 
 
  See also: <a href="fitab.html" class="code" title="function [Fit,ok] = fitab(q,dqdt,method,varargin)">fitab</a>
@@ -122,174 +123,171 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0023    <span class="comment">%     reference point that the line passes through. For 'envelope', they</span>
 0024    <span class="comment">%     are the refqtls quantiles of q and -dqdt. For 'median' and</span>
 0025    <span class="comment">%     'brutsaert', they are the medians of q and -dqdt. For 'mean', they</span>
-0026    <span class="comment">%     are the means of log(q) and log(-dqdt).</span>
-0027    <span class="comment">%</span>
-0028    <span class="comment">% Required inputs</span>
-0029    <span class="comment">%</span>
-0030    <span class="comment">%  q        =  vector double of discharge data (L T^-1)</span>
-0031    <span class="comment">%  dqdt     =  vector double of discharge rate of change (L T^-2)</span>
-0032    <span class="comment">%  bhat     =  late-time b parameter in -dqdt = aq^b (dimensionless)</span>
-0033    <span class="comment">%  method   =  char indicating the fitting method</span>
-0034    <span class="comment">%</span>
-0035    <span class="comment">% Optional name-value inputs</span>
-0036    <span class="comment">%</span>
-0037    <span class="comment">%  mask     =  logical mask to exclude data</span>
-0038    <span class="comment">%  refqtls  =  reference quantiles that together define a pivot point through</span>
-0039    <span class="comment">%              which the straight line must pass. use with method 'envelope'.</span>
-0040    <span class="comment">%  bci      =  [bL bH] confidence interval of bhat, used to compute the</span>
-0041    <span class="comment">%              bounds ahatLH (default nan, which returns NaN bounds)</span>
-0042    <span class="comment">%</span>
+0026    <span class="comment">%     are the geometric means of q and -dqdt. ahatLH pivots the line</span>
+0027    <span class="comment">%     through (xbar, ybar) with the slopes in bci.</span>
+0028    <span class="comment">%</span>
+0029    <span class="comment">% Required inputs</span>
+0030    <span class="comment">%</span>
+0031    <span class="comment">%  q        =  vector double of discharge data (L T^-1)</span>
+0032    <span class="comment">%  dqdt     =  vector double of discharge rate of change (L T^-2)</span>
+0033    <span class="comment">%  bhat     =  late-time b parameter in -dqdt = aq^b (dimensionless)</span>
+0034    <span class="comment">%  method   =  char indicating the fitting method</span>
+0035    <span class="comment">%</span>
+0036    <span class="comment">% Optional name-value inputs</span>
+0037    <span class="comment">%</span>
+0038    <span class="comment">%  mask     =  logical mask to exclude data</span>
+0039    <span class="comment">%  refqtls  =  reference quantiles that together define a pivot point through</span>
+0040    <span class="comment">%              which the straight line must pass. use with method 'envelope'.</span>
+0041    <span class="comment">%  bci      =  [bL bH] confidence interval of bhat, used to compute the</span>
+0042    <span class="comment">%              bounds ahatLH (default [nan nan], which returns NaN bounds)</span>
 0043    <span class="comment">%</span>
-0044    <span class="comment">% See also: fitab</span>
-0045    <span class="comment">%</span>
-0046    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0047 
-0048    <span class="comment">% TODO: consider making this a call to fitab. however, fitab does not return</span>
-0049    <span class="comment">% xbar/ybar, and I confirmed the results are identical, but it would be</span>
-0050    <span class="comment">% preferable to reduce the potential for inconsistent methods e.g. if this is</span>
-0051    <span class="comment">% used to estimate ahat but a different method is used when calling fitab for</span>
-0052    <span class="comment">% some other purpose such as fitting phi.</span>
-0053 
-0054    <span class="comment">% if called with no input, open this file</span>
-0055    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0056 
-0057    <span class="keyword">persistent</span> inoctave
-0058    <span class="keyword">if</span> isempty(inoctave); inoctave = exist(&quot;OCTAVE_VERSION&quot;, &quot;builtin&quot;)&gt;0;
-0059    <span class="keyword">end</span>
-0060 
-0061    <span class="comment">% PARSE INPUTS</span>
-0062    [q, dqdt, bhat, method, thresh, mask, qtls, bci, tau, tau0] = parseinputs( <span class="keyword">...</span>
-0063       q, dqdt, bhat, method, varargin{:});
-0064 
-0065    <span class="keyword">switch</span> method
-0066       <span class="keyword">case</span> <span class="string">'mean'</span>
-0067          <span class="comment">%ybar = mean(-dqdt(mask),'omitnan');</span>
-0068          <span class="comment">%xbar = mean(q(mask),'omitnan');</span>
-0069          ybar = mean(log(-dqdt(mask)),<span class="string">'omitnan'</span>);
-0070          xbar = mean(log(q(mask)),<span class="string">'omitnan'</span>);
-0071          ahat = exp(ybar - bhat*xbar);
-0072       <span class="keyword">case</span> <span class="string">'median'</span>
-0073          xbar = median(q(mask),<span class="string">'omitnan'</span>);
-0074          ybar = median(-dqdt(mask),<span class="string">'omitnan'</span>);
-0075          ahat = ybar/xbar^bhat;
-0076       <span class="keyword">case</span> <span class="string">'envelope'</span>
-0077 
-0078          <span class="keyword">if</span> inoctave
-0079             xbar = quantile(q(mask),qtls(1));
-0080             ybar = quantile(-dqdt(mask),qtls(2));
-0081          <span class="keyword">else</span>
-0082             xbar = quantile(q(mask),qtls(1),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0083             ybar = quantile(-dqdt(mask),qtls(2),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0084          <span class="keyword">end</span>
-0085          ahat = ybar/xbar^bhat;
-0086 
-0087       <span class="keyword">case</span> <span class="string">'brutsaert'</span>
-0088          <span class="comment">% start with median</span>
-0089          xbar = median(q(mask),<span class="string">'omitnan'</span>);
-0090          ybar = median(-dqdt(mask),<span class="string">'omitnan'</span>);
-0091          ahat = ybar/xbar^bhat; <span class="comment">% init a using the median</span>
-0092          N = numel(q(mask));
-0093          P = 1;
-0094          <span class="keyword">while</span> P&gt;thresh
-0095             ahat = 0.99*ahat;
-0096             P = sum( (ahat.*q(mask).^bhat) &gt; -dqdt(mask) ) / N;
-0097          <span class="keyword">end</span>
-0098       <span class="keyword">case</span> <span class="string">'cooper'</span> <span class="comment">% only works if b&gt;1 and tau/tau0 are provided</span>
-0099 
-0100          <span class="comment">% if no tau&gt;tau0 mask is provided, use the 95th pctl for a1</span>
-0101          <span class="keyword">if</span> all(mask)
+0044    <span class="comment">%</span>
+0045    <span class="comment">% See also: fitab</span>
+0046    <span class="comment">%</span>
+0047    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0048 
+0049    <span class="comment">% TODO: consider making this a call to fitab. however, fitab does not return</span>
+0050    <span class="comment">% xbar/ybar, and I confirmed the results are identical, but it would be</span>
+0051    <span class="comment">% preferable to reduce the potential for inconsistent methods e.g. if this is</span>
+0052    <span class="comment">% used to estimate ahat but a different method is used when calling fitab for</span>
+0053    <span class="comment">% some other purpose such as fitting phi.</span>
+0054 
+0055    <span class="comment">% if called with no input, open this file</span>
+0056    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0057 
+0058    <span class="keyword">persistent</span> inoctave
+0059    <span class="keyword">if</span> isempty(inoctave); inoctave = exist(&quot;OCTAVE_VERSION&quot;, &quot;builtin&quot;)&gt;0;
+0060    <span class="keyword">end</span>
+0061 
+0062    <span class="comment">% PARSE INPUTS</span>
+0063    [q, dqdt, bhat, method, thresh, mask, qtls, bci, tau, tau0] = parseinputs( <span class="keyword">...</span>
+0064       q, dqdt, bhat, method, varargin{:});
+0065 
+0066    <span class="keyword">switch</span> method
+0067       <span class="keyword">case</span> <span class="string">'mean'</span>
+0068          <span class="comment">%ybar = mean(-dqdt(mask),'omitnan');</span>
+0069          <span class="comment">%xbar = mean(q(mask),'omitnan');</span>
+0070          <span class="comment">% the line through the log means passes through the geometric</span>
+0071          <span class="comment">% means, which keeps xbar and ybar in linear space like the others</span>
+0072          ybar = exp(mean(log(-dqdt(mask)),<span class="string">'omitnan'</span>));
+0073          xbar = exp(mean(log(q(mask)),<span class="string">'omitnan'</span>));
+0074          ahat = ybar/xbar^bhat;
+0075       <span class="keyword">case</span> <span class="string">'median'</span>
+0076          xbar = median(q(mask),<span class="string">'omitnan'</span>);
+0077          ybar = median(-dqdt(mask),<span class="string">'omitnan'</span>);
+0078          ahat = ybar/xbar^bhat;
+0079       <span class="keyword">case</span> <span class="string">'envelope'</span>
+0080 
+0081          <span class="keyword">if</span> inoctave
+0082             xbar = quantile(q(mask),qtls(1));
+0083             ybar = quantile(-dqdt(mask),qtls(2));
+0084          <span class="keyword">else</span>
+0085             xbar = quantile(q(mask),qtls(1),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0086             ybar = quantile(-dqdt(mask),qtls(2),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0087          <span class="keyword">end</span>
+0088          ahat = ybar/xbar^bhat;
+0089 
+0090       <span class="keyword">case</span> <span class="string">'brutsaert'</span>
+0091          <span class="comment">% start with median</span>
+0092          xbar = median(q(mask),<span class="string">'omitnan'</span>);
+0093          ybar = median(-dqdt(mask),<span class="string">'omitnan'</span>);
+0094          ahat = ybar/xbar^bhat; <span class="comment">% init a using the median</span>
+0095          N = numel(q(mask));
+0096          P = 1;
+0097          <span class="keyword">while</span> P&gt;thresh
+0098             ahat = 0.99*ahat;
+0099             P = sum( (ahat.*q(mask).^bhat) &gt; -dqdt(mask) ) / N;
+0100          <span class="keyword">end</span>
+0101       <span class="keyword">case</span> <span class="string">'cooper'</span> <span class="comment">% only works if b&gt;1 and tau/tau0 are provided</span>
 0102 
-0103             <span class="keyword">if</span> inoctave
-0104                xbar = quantile(q,0.95);
-0105                ybar = quantile(-dqdt,0.95);
-0106             <span class="keyword">else</span>
-0107                xbar = quantile(q,0.95,<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0108                ybar = quantile(-dqdt,0.95,<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0109             <span class="keyword">end</span>
-0110          <span class="keyword">else</span>
-0111             <span class="comment">% if a mask is provided, use the 50th pctl of tau&lt;tau0</span>
-0112             <span class="keyword">if</span> inoctave
-0113                xbar = quantile(q(~mask),qtls(1));
-0114                ybar = quantile(-dqdt(~mask),qtls(2));
-0115             <span class="keyword">else</span>
-0116                xbar = quantile(q(~mask),qtls(1),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0117                ybar = quantile(-dqdt(~mask),qtls(2),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
-0118             <span class="keyword">end</span>
-0119          <span class="keyword">end</span>
-0120          a0 = ybar/xbar^3;
-0121          ahat = (1/tau)*(sqrt(a0*tau0)*(bhat-3)/(bhat-2))^(bhat-1);
-0122 
-0123          <span class="comment">% temporary method to send back a0 for method 'cooper'</span>
-0124          ahat = [ahat a0];
+0103          <span class="comment">% if no tau&gt;tau0 mask is provided, use the 95th pctl for a1</span>
+0104          <span class="keyword">if</span> all(mask)
+0105 
+0106             <span class="keyword">if</span> inoctave
+0107                xbar = quantile(q,0.95);
+0108                ybar = quantile(-dqdt,0.95);
+0109             <span class="keyword">else</span>
+0110                xbar = quantile(q,0.95,<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0111                ybar = quantile(-dqdt,0.95,<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0112             <span class="keyword">end</span>
+0113          <span class="keyword">else</span>
+0114             <span class="comment">% if a mask is provided, use the 50th pctl of tau&lt;tau0</span>
+0115             <span class="keyword">if</span> inoctave
+0116                xbar = quantile(q(~mask),qtls(1));
+0117                ybar = quantile(-dqdt(~mask),qtls(2));
+0118             <span class="keyword">else</span>
+0119                xbar = quantile(q(~mask),qtls(1),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0120                ybar = quantile(-dqdt(~mask),qtls(2),<span class="string">'Method'</span>,<span class="string">'approximate'</span>);
+0121             <span class="keyword">end</span>
+0122          <span class="keyword">end</span>
+0123          a0 = ybar/xbar^3;
+0124          ahat = (1/tau)*(sqrt(a0*tau0)*(bhat-3)/(bhat-2))^(bhat-1);
 0125 
-0126          <span class="comment">% here xbar/ybar are identical to 'envelope'. use this to show that</span>
-0127          <span class="comment">% ahat returned by this function is identical to the case where a0 is</span>
-0128          <span class="comment">% returned by this function usine method 'envelope' and then passed to</span>
-0129          <span class="comment">% the a(a0...) function from baseflow.getfunction('aofa0')</span>
-0130          <span class="comment">% xbar = quantile(q(mask),qtls(1),'Method','approximate');</span>
-0131          <span class="comment">% ybar = quantile(-dqdt(mask),qtls(2),'Method','approximate');</span>
-0132    <span class="keyword">end</span>
-0133 
-0134    <span class="comment">% NOTE: this isn't the best way to get aL/H, but use it for now</span>
-0135    <span class="keyword">if</span> ~isnan(bci)
-0136       bhatL = bci(1);
-0137       bhatH = bci(2);
-0138       ahatH = ybar/xbar^bhatL;
-0139       ahatL = ybar/xbar^bhatH;
-0140    <span class="keyword">else</span>
-0141       ahatH = nan;
-0142       ahatL = nan;
-0143    <span class="keyword">end</span>
-0144 
-0145    <span class="comment">% PARSE OUTPUTS</span>
-0146    <span class="keyword">switch</span> nargout
-0147       <span class="keyword">case</span> 1
-0148          varargout{1} = ahat;
-0149       <span class="keyword">case</span> 2
+0126          <span class="comment">% temporary method to send back a0 for method 'cooper'</span>
+0127          ahat = [ahat a0];
+0128 
+0129          <span class="comment">% here xbar/ybar are identical to 'envelope'. use this to show that</span>
+0130          <span class="comment">% ahat returned by this function is identical to the case where a0 is</span>
+0131          <span class="comment">% returned by this function usine method 'envelope' and then passed to</span>
+0132          <span class="comment">% the a(a0...) function from baseflow.getfunction('aofa0')</span>
+0133          <span class="comment">% xbar = quantile(q(mask),qtls(1),'Method','approximate');</span>
+0134          <span class="comment">% ybar = quantile(-dqdt(mask),qtls(2),'Method','approximate');</span>
+0135    <span class="keyword">end</span>
+0136 
+0137    <span class="comment">% NOTE: this isn't the best way to get aL/H, but use it for now</span>
+0138    <span class="comment">% which b bound gives the lower a depends on the sign of log(xbar), so</span>
+0139    <span class="comment">% sort the pair. A nan bci gives nan bounds.</span>
+0140    ahatLH = sort(ybar./xbar.^bci(:).');
+0141 
+0142    <span class="comment">% PARSE OUTPUTS</span>
+0143    <span class="keyword">switch</span> nargout
+0144       <span class="keyword">case</span> 1
+0145          varargout{1} = ahat;
+0146       <span class="keyword">case</span> 2
+0147          varargout{1} = ahat;
+0148          varargout{2} = ahatLH;
+0149       <span class="keyword">case</span> 3
 0150          varargout{1} = ahat;
-0151          varargout{2} = [ahatL ahatH];
-0152       <span class="keyword">case</span> 3
-0153          varargout{1} = ahat;
-0154          varargout{2} = xbar;
-0155          varargout{3} = ybar;
-0156       <span class="keyword">case</span> 4
-0157          varargout{1} = ahat;
-0158          varargout{2} = [ahatL ahatH];
-0159          varargout{3} = xbar;
-0160          varargout{4} = ybar;
-0161    <span class="keyword">end</span>
-0162 
-0163    <span class="comment">% % one = ahat</span>
-0164    <span class="comment">% % two = ahat, [aL aH]</span>
-0165    <span class="comment">% % three = ahat, xbar, ybar</span>
-0166    <span class="comment">% % four = ahat, [aL aH], xbar, ybar</span>
-0167 <span class="keyword">end</span>
-0168 
-0169 <span class="comment">%% INPUT PARSER</span>
-0170 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, bhat, method, thresh, mask, qtls, bci, tau, tau0] = </a><span class="keyword">...</span>
-0171       parseinputs(q, dqdt, bhat, method, varargin)
-0172    parser = inputParser;
-0173    parser.FunctionName = <span class="string">'baseflow.pointcloudintercept'</span>;
-0174 
-0175    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
-0176    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
-0177    parser.addRequired(<span class="string">'bhat'</span>, @isnumeric);
-0178    parser.addRequired(<span class="string">'method'</span>, @ischar);
-0179    parser.addOptional(<span class="string">'threshold'</span>,0.05, @isnumeric);
-0180    parser.addParameter(<span class="string">'mask'</span>, true(size(q)), @islogical);
-0181    parser.addParameter(<span class="string">'refqtls'</span>, [0.5 0.5], @isnumeric);
-0182    parser.addParameter(<span class="string">'bci'</span>, nan, @isnumeric);
-0183    parser.addParameter(<span class="string">'tau'</span>, nan, @isnumeric);
-0184    parser.addParameter(<span class="string">'tau0'</span>, nan, @isnumeric);
-0185 
-0186    parser.parse(q, dqdt, bhat, method, varargin{:});
-0187 
-0188    thresh = parser.Results.threshold;
-0189    mask = parser.Results.mask;
-0190    qtls = parser.Results.refqtls;
-0191    bci = parser.Results.bci;
-0192    tau = parser.Results.tau;
-0193    tau0 = parser.Results.tau0;
-0194 <span class="keyword">end</span></pre></div>
+0151          varargout{2} = xbar;
+0152          varargout{3} = ybar;
+0153       <span class="keyword">case</span> 4
+0154          varargout{1} = ahat;
+0155          varargout{2} = ahatLH;
+0156          varargout{3} = xbar;
+0157          varargout{4} = ybar;
+0158    <span class="keyword">end</span>
+0159 
+0160    <span class="comment">% % one = ahat</span>
+0161    <span class="comment">% % two = ahat, [aL aH]</span>
+0162    <span class="comment">% % three = ahat, xbar, ybar</span>
+0163    <span class="comment">% % four = ahat, [aL aH], xbar, ybar</span>
+0164 <span class="keyword">end</span>
+0165 
+0166 <span class="comment">%% INPUT PARSER</span>
+0167 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, bhat, method, thresh, mask, qtls, bci, tau, tau0] = </a><span class="keyword">...</span>
+0168       parseinputs(q, dqdt, bhat, method, varargin)
+0169    parser = inputParser;
+0170    parser.FunctionName = <span class="string">'baseflow.pointcloudintercept'</span>;
+0171 
+0172    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
+0173    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
+0174    parser.addRequired(<span class="string">'bhat'</span>, @isnumeric);
+0175    parser.addRequired(<span class="string">'method'</span>, @ischar);
+0176    parser.addOptional(<span class="string">'threshold'</span>,0.05, @isnumeric);
+0177    parser.addParameter(<span class="string">'mask'</span>, true(size(q)), @islogical);
+0178    parser.addParameter(<span class="string">'refqtls'</span>, [0.5 0.5], @isnumeric);
+0179    parser.addParameter(<span class="string">'bci'</span>, [nan nan], @isnumeric);
+0180    parser.addParameter(<span class="string">'tau'</span>, nan, @isnumeric);
+0181    parser.addParameter(<span class="string">'tau0'</span>, nan, @isnumeric);
+0182 
+0183    parser.parse(q, dqdt, bhat, method, varargin{:});
+0184 
+0185    thresh = parser.Results.threshold;
+0186    mask = parser.Results.mask;
+0187    qtls = parser.Results.refqtls;
+0188    bci = parser.Results.bci;
+0189    tau = parser.Results.tau;
+0190    tau0 = parser.Results.tau0;
+0191 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/prepfits.html b/toolbox/docs/html/m2html/+baseflow/prepfits.html
index 7d989fe..fa18e31 100644
--- a/toolbox/docs/html/m2html/+baseflow/prepfits.html
+++ b/toolbox/docs/html/m2html/+baseflow/prepfits.html
@@ -43,6 +43,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
      weights  =  nx1 double of weights for the fitting algorithm
      mask     =  nx1 logical mask to exclude values from fitting
 
+  note: a point with mask false or zero weight leaves every output, so
+  it takes no part in any fit, its residuals, or its point count
+
   note: dqdt comes in as its actual value i.e. negative
 
  See also: <a href="fitab.html" class="code" title="function [Fit,ok] = fitab(q,dqdt,method,varargin)">fitab</a></pre></div>
@@ -88,44 +91,43 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0015    <span class="comment">%     weights  =  nx1 double of weights for the fitting algorithm</span>
 0016    <span class="comment">%     mask     =  nx1 logical mask to exclude values from fitting</span>
 0017    <span class="comment">%</span>
-0018    <span class="comment">%  note: dqdt comes in as its actual value i.e. negative</span>
-0019    <span class="comment">%</span>
-0020    <span class="comment">% See also: fitab</span>
-0021 
-0022    <span class="comment">% PARSE INPUTS</span>
-0023    [q, dqdt, w, m] = <a href="#_sub1" class="code" title="subfunction [q, dqdt, weights, mask] = parseinputs(q, dqdt, varargin)">parseinputs</a>(q, dqdt, varargin{:});
+0018    <span class="comment">%  note: a point with mask false or zero weight leaves every output, so</span>
+0019    <span class="comment">%  it takes no part in any fit, its residuals, or its point count</span>
+0020    <span class="comment">%</span>
+0021    <span class="comment">%  note: dqdt comes in as its actual value i.e. negative</span>
+0022    <span class="comment">%</span>
+0023    <span class="comment">% See also: fitab</span>
 0024 
-0025    <span class="comment">% keep the negative dq/dt values</span>
-0026    keep = dqdt&lt;0;
-0027    x = abs(q(keep));
-0028    y = abs(dqdt(keep));
-0029    w = w(keep);
-0030    m = m(keep);
-0031 
-0032    <span class="comment">% convert the mask to weights</span>
-0033    w(m==false) = 0;
-0034 
-0035    [x, y, w] = prepCurveData(x, y, w);
-0036    [logx, logy, w] = prepCurveData(log(x), log(y), w);
-0037 
-0038    <span class="comment">% failure check</span>
-0039    ok = numel(y)&gt;3;
-0040 <span class="keyword">end</span>
-0041 
-0042 <span class="comment">%% parse inputs</span>
-0043 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, weights, mask] = parseinputs(q, dqdt, varargin)</a>
-0044    parser = inputParser;
-0045    parser.FunctionName = <span class="string">'baseflow.prepfits'</span>;
-0046 
-0047    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
-0048    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
-0049    parser.addParameter(<span class="string">'weights'</span>, ones(size(q)), @isnumeric);
-0050    parser.addParameter(<span class="string">'mask'</span>, true(size(q)), @islogical);
-0051 
-0052    parser.parse(q, dqdt, varargin{:});
-0053 
-0054    weights = parser.Results.weights;
-0055    mask = parser.Results.mask;
-0056 <span class="keyword">end</span></pre></div>
+0025    <span class="comment">% PARSE INPUTS</span>
+0026    [q, dqdt, w, m] = <a href="#_sub1" class="code" title="subfunction [q, dqdt, weights, mask] = parseinputs(q, dqdt, varargin)">parseinputs</a>(q, dqdt, varargin{:});
+0027 
+0028    <span class="comment">% keep the negative dq/dt values that the mask and weights leave in the fit</span>
+0029    keep = dqdt&lt;0 &amp; m &amp; w&gt;0;
+0030    x = abs(q(keep));
+0031    y = abs(dqdt(keep));
+0032    w = w(keep);
+0033 
+0034    [x, y, w] = prepCurveData(x, y, w);
+0035    [logx, logy, w] = prepCurveData(log(x), log(y), w);
+0036 
+0037    <span class="comment">% failure check</span>
+0038    ok = numel(y)&gt;3;
+0039 <span class="keyword">end</span>
+0040 
+0041 <span class="comment">%% parse inputs</span>
+0042 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, weights, mask] = parseinputs(q, dqdt, varargin)</a>
+0043    parser = inputParser;
+0044    parser.FunctionName = <span class="string">'baseflow.prepfits'</span>;
+0045 
+0046    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
+0047    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
+0048    parser.addParameter(<span class="string">'weights'</span>, ones(size(q)), @isnumeric);
+0049    parser.addParameter(<span class="string">'mask'</span>, true(size(q)), @islogical);
+0050 
+0051    parser.parse(q, dqdt, varargin{:});
+0052 
+0053    weights = parser.Results.weights;
+0054    mask = parser.Results.mask;
+0055 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/printtrend.html b/toolbox/docs/html/m2html/+baseflow/printtrend.html
index af7ad79..43429eb 100644
--- a/toolbox/docs/html/m2html/+baseflow/printtrend.html
+++ b/toolbox/docs/html/m2html/+baseflow/printtrend.html
@@ -33,6 +33,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
   [ddt,err] = printtrend(Data,varargin)
 
+  ddt is the trend per year. The printed total change is ddt times the
+  years from the first to the last row of Data.
+
  See also: <a href="aquifertrend.html" class="code" title="function [D,dDdt,dDadt,C] = aquifertrend(tau,phi,N,Qb,dQbdt)">aquifertrend</a>, <a href="baseflowtrend.html" class="code" title="function [Qb,dQbdt,Qa,dQadt,hb,ha] = baseflowtrend(t,Q,A,varargin)">baseflowtrend</a></pre></div>
 
 
@@ -65,60 +68,63 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0005    <span class="comment">%</span>
 0006    <span class="comment">%  [ddt,err] = printtrend(Data,varargin)</span>
 0007    <span class="comment">%</span>
-0008    <span class="comment">% See also: aquifertrend, baseflowtrend</span>
-0009 
-0010    <span class="comment">% PARSE INPUTS</span>
-0011    [Data, method, var, cf, alpha, qtl] = <a href="#_sub1" class="code" title="subfunction [Data, method, var, cf, alpha, qtl] = parseinputs(Data, varargin)">parseinputs</a>(Data, varargin{:});
+0008    <span class="comment">%  ddt is the trend per year. The printed total change is ddt times the</span>
+0009    <span class="comment">%  years from the first to the last row of Data.</span>
+0010    <span class="comment">%</span>
+0011    <span class="comment">% See also: aquifertrend, baseflowtrend</span>
 0012 
-0013    <span class="comment">% create a regular time in years, works for both months and years</span>
-0014    t = years(Data.Time-Data.Time(1)) + year(Data.Time(1));
-0015    dt = numel(t);
-0016    dat = Data.(var); <span class="comment">% cm/yr -&gt; cm/day</span>
-0017 
-0018    <span class="keyword">switch</span> method
-0019       <span class="keyword">case</span> <span class="string">'ols'</span>
-0020          mdl = fitlm(t,dat);
-0021          ddt = mdl.Coefficients.Estimate(2);  <span class="comment">% cm/day/year</span>
-0022          CIs = coefCI(mdl,alpha);
-0023          err = CIs(2,2)-ddt;
-0024       <span class="keyword">case</span> <span class="string">'qtl'</span>
-0025          [ab,S] = quantreg(t,dat,qtl,1,1000,alpha);
-0026          ddt = ab(2);
-0027          CIs = S.ci_boot';
-0028          err = CIs(2,2)-ddt;
-0029    <span class="keyword">end</span>
-0030    <span class="comment">% adjust the trend and error units using the conversion factor</span>
-0031    ddt = cf*ddt;
-0032    d = ddt*dt;
-0033    err = cf*err;
-0034    derr = err*dt;
-0035    errstr = num2str(round(100*(1-alpha)));
-0036    str = [<span class="string">'\nd'</span> var <span class="string">'/dt = %.3f '</span> char(177) <span class="string">' %.3f ('</span> errstr <span class="string">'%% CI) '</span>];
-0037    str = [str <span class="string">', d'</span> var <span class="string">' = %.3f '</span> char(177) <span class="string">' %.3f \n\n'</span>];
-0038    fprintf(str,ddt,err,d,derr);
-0039 <span class="keyword">end</span>
-0040 
-0041 <span class="comment">%% PARSE INPUTS</span>
-0042 <a name="_sub1" href="#_subfunctions" class="code">function [Data, method, var, cf, alpha, qtl] = parseinputs(Data, varargin)</a>
-0043    parser = inputParser;
-0044    <span class="comment">% this has to be true to use autocomplete fieldname</span>
-0045    parser.StructExpand = true;
-0046    parser.FunctionName = <span class="string">'baseflow.printtrend'</span>;
-0047    parser.addRequired(<span class="string">'Data'</span>, @istimetable);
-0048    parser.addParameter(<span class="string">'var'</span>, <span class="string">'Qb'</span>, @ischar);
-0049    parser.addParameter(<span class="string">'alpha'</span>, 0.05, @isnumeric);
-0050    parser.addParameter(<span class="string">'metric'</span>, <span class="string">'CI'</span>, @ischar);
-0051    parser.addParameter(<span class="string">'method'</span>, <span class="string">'ols'</span>, @ischar);
-0052    parser.addParameter(<span class="string">'quantile'</span>, nan, @isnumeric);
-0053    parser.addParameter(<span class="string">'unitconversion'</span>, 1, @isnumeric);
-0054 
-0055    parser.parse(Data, varargin{:});
-0056 
-0057    cf = parser.Results.unitconversion;
-0058    var  = parser.Results.var;
-0059    qtl = parser.Results.quantile;
-0060    alpha = parser.Results.alpha;
-0061    method = parser.Results.method;
-0062 <span class="keyword">end</span></pre></div>
+0013    <span class="comment">% PARSE INPUTS</span>
+0014    [Data, method, var, cf, alpha, qtl] = <a href="#_sub1" class="code" title="subfunction [Data, method, var, cf, alpha, qtl] = parseinputs(Data, varargin)">parseinputs</a>(Data, varargin{:});
+0015 
+0016    <span class="comment">% create a regular time in years, works for both months and years</span>
+0017    t = years(Data.Time-Data.Time(1)) + year(Data.Time(1));
+0018    dt = t(end)-t(1); <span class="comment">% years spanned, which scales the trend to a total change</span>
+0019    dat = Data.(var); <span class="comment">% cm/yr -&gt; cm/day</span>
+0020 
+0021    <span class="keyword">switch</span> method
+0022       <span class="keyword">case</span> <span class="string">'ols'</span>
+0023          mdl = fitlm(t,dat);
+0024          ddt = mdl.Coefficients.Estimate(2);  <span class="comment">% cm/day/year</span>
+0025          CIs = coefCI(mdl,alpha);
+0026          err = CIs(2,2)-ddt;
+0027       <span class="keyword">case</span> <span class="string">'qtl'</span>
+0028          [ab,S] = quantreg(t,dat,qtl,1,1000,alpha);
+0029          ddt = ab(2);
+0030          CIs = S.ci_boot';
+0031          err = CIs(2,2)-ddt;
+0032    <span class="keyword">end</span>
+0033    <span class="comment">% adjust the trend and error units using the conversion factor</span>
+0034    ddt = cf*ddt;
+0035    d = ddt*dt;
+0036    err = cf*err;
+0037    derr = err*dt;
+0038    errstr = num2str(round(100*(1-alpha)));
+0039    str = [<span class="string">'\nd'</span> var <span class="string">'/dt = %.3f '</span> char(177) <span class="string">' %.3f ('</span> errstr <span class="string">'%% CI) '</span>];
+0040    str = [str <span class="string">', d'</span> var <span class="string">' = %.3f '</span> char(177) <span class="string">' %.3f \n\n'</span>];
+0041    fprintf(str,ddt,err,d,derr);
+0042 <span class="keyword">end</span>
+0043 
+0044 <span class="comment">%% PARSE INPUTS</span>
+0045 <a name="_sub1" href="#_subfunctions" class="code">function [Data, method, var, cf, alpha, qtl] = parseinputs(Data, varargin)</a>
+0046    parser = inputParser;
+0047    <span class="comment">% this has to be true to use autocomplete fieldname</span>
+0048    parser.StructExpand = true;
+0049    parser.FunctionName = <span class="string">'baseflow.printtrend'</span>;
+0050    parser.addRequired(<span class="string">'Data'</span>, @istimetable);
+0051    parser.addParameter(<span class="string">'var'</span>, <span class="string">'Qb'</span>, @ischar);
+0052    parser.addParameter(<span class="string">'alpha'</span>, 0.05, @isnumeric);
+0053    parser.addParameter(<span class="string">'metric'</span>, <span class="string">'CI'</span>, @ischar);
+0054    parser.addParameter(<span class="string">'method'</span>, <span class="string">'ols'</span>, @ischar);
+0055    parser.addParameter(<span class="string">'quantile'</span>, nan, @isnumeric);
+0056    parser.addParameter(<span class="string">'unitconversion'</span>, 1, @isnumeric);
+0057 
+0058    parser.parse(Data, varargin{:});
+0059 
+0060    cf = parser.Results.unitconversion;
+0061    var  = parser.Results.var;
+0062    qtl = parser.Results.quantile;
+0063    alpha = parser.Results.alpha;
+0064    method = parser.Results.method;
+0065 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/setopts.html b/toolbox/docs/html/m2html/+baseflow/setopts.html
index 314b14e..e597cbe 100644
--- a/toolbox/docs/html/m2html/+baseflow/setopts.html
+++ b/toolbox/docs/html/m2html/+baseflow/setopts.html
@@ -70,7 +70,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
      derivmethod    : derivative (dQ/dt) method: 'ETS', 'VTS', or 'CTS'
      fitmethod      : -dQ/dt = aQb fitting method
-     fitorder       : fitting order (value of exponent b)
+     fitorder       : fitting order (value of exponent b). fitmethod
+                      'mean', 'median', or 'envelope' uses 1 when it
+                      is nan; see fitab.
      pickfits       : pick fits manually?
      pickmethod     : method to fit picks manually
      plotfits       : plot each event fit? fitevents passes this flag
@@ -97,6 +99,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
 
      drainagearea   : drainage area [m2]
      drainagedensity: drainage density [km-1] = streamlength/drainagearea
+                      (default nan). When both are given and differ,
+                      globalfit uses streamlength = drainagearea*
+                      drainagedensity/1000.
      aquiferdepth   : reference aquifer thickness [m]
      streamlength   : effective channel length [m]
      aquiferslope   : effective aquifer slope
@@ -189,129 +194,134 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0042    <span class="comment">%</span>
 0043    <span class="comment">%     derivmethod    : derivative (dQ/dt) method: 'ETS', 'VTS', or 'CTS'</span>
 0044    <span class="comment">%     fitmethod      : -dQ/dt = aQb fitting method</span>
-0045    <span class="comment">%     fitorder       : fitting order (value of exponent b)</span>
-0046    <span class="comment">%     pickfits       : pick fits manually?</span>
-0047    <span class="comment">%     pickmethod     : method to fit picks manually</span>
-0048    <span class="comment">%     plotfits       : plot each event fit? fitevents passes this flag</span>
-0049    <span class="comment">%                      to getdqdt, which draws one figure per event.</span>
-0050    <span class="comment">%     saveplots      : save plots of fits? fitevents parses this flag,</span>
-0051    <span class="comment">%                      but the flag has no effect.</span>
-0052    <span class="comment">%     etsparam       : min flow length parameter for ETS algorithm</span>
-0053    <span class="comment">%     vtsparam       : min flow length parameter for VTS algorithm</span>
-0054    <span class="comment">%     ctsmethod      : finite-difference stencil for the CTS method:</span>
-0055    <span class="comment">%                      'B1', 'B2', 'F1', 'F2', 'C2', or 'C4' (default 'B1')</span>
-0056    <span class="comment">%     fitopts        : struct of baseflow.fitab options that fitevents</span>
-0057    <span class="comment">%                      passes to every event fit (default: struct()).</span>
-0058    <span class="comment">%                      Allowed fields: weights, order, quantile,</span>
-0059    <span class="comment">%                      refqtls, Nboot, alpha (numeric); mask, plotfit</span>
-0060    <span class="comment">%                      (logical). A fitopts field overrides the</span>
-0061    <span class="comment">%                      same-named fitab option, so fitopts.order</span>
-0062    <span class="comment">%                      overrides fitorder. weights and mask must be</span>
-0063    <span class="comment">%                      scalars (baseflow:fitevents:nonscalarFitopt).</span>
-0064    <span class="comment">%                      An unknown field raises</span>
-0065    <span class="comment">%                      baseflow:fitab:unknownFitopt. A field of the</span>
-0066    <span class="comment">%                      wrong type raises baseflow:fitab:invalidFitopt.</span>
-0067    <span class="comment">%</span>
-0068    <span class="comment">%  Optional name-value inputs for type 'globalfit'</span>
+0045    <span class="comment">%     fitorder       : fitting order (value of exponent b). fitmethod</span>
+0046    <span class="comment">%                      'mean', 'median', or 'envelope' uses 1 when it</span>
+0047    <span class="comment">%                      is nan; see fitab.</span>
+0048    <span class="comment">%     pickfits       : pick fits manually?</span>
+0049    <span class="comment">%     pickmethod     : method to fit picks manually</span>
+0050    <span class="comment">%     plotfits       : plot each event fit? fitevents passes this flag</span>
+0051    <span class="comment">%                      to getdqdt, which draws one figure per event.</span>
+0052    <span class="comment">%     saveplots      : save plots of fits? fitevents parses this flag,</span>
+0053    <span class="comment">%                      but the flag has no effect.</span>
+0054    <span class="comment">%     etsparam       : min flow length parameter for ETS algorithm</span>
+0055    <span class="comment">%     vtsparam       : min flow length parameter for VTS algorithm</span>
+0056    <span class="comment">%     ctsmethod      : finite-difference stencil for the CTS method:</span>
+0057    <span class="comment">%                      'B1', 'B2', 'F1', 'F2', 'C2', or 'C4' (default 'B1')</span>
+0058    <span class="comment">%     fitopts        : struct of baseflow.fitab options that fitevents</span>
+0059    <span class="comment">%                      passes to every event fit (default: struct()).</span>
+0060    <span class="comment">%                      Allowed fields: weights, order, quantile,</span>
+0061    <span class="comment">%                      refqtls, Nboot, alpha (numeric); mask, plotfit</span>
+0062    <span class="comment">%                      (logical). A fitopts field overrides the</span>
+0063    <span class="comment">%                      same-named fitab option, so fitopts.order</span>
+0064    <span class="comment">%                      overrides fitorder. weights and mask must be</span>
+0065    <span class="comment">%                      scalars (baseflow:fitevents:nonscalarFitopt).</span>
+0066    <span class="comment">%                      An unknown field raises</span>
+0067    <span class="comment">%                      baseflow:fitab:unknownFitopt. A field of the</span>
+0068    <span class="comment">%                      wrong type raises baseflow:fitab:invalidFitopt.</span>
 0069    <span class="comment">%</span>
-0070    <span class="comment">%     drainagearea   : drainage area [m2]</span>
-0071    <span class="comment">%     drainagedensity: drainage density [km-1] = streamlength/drainagearea</span>
-0072    <span class="comment">%     aquiferdepth   : reference aquifer thickness [m]</span>
-0073    <span class="comment">%     streamlength   : effective channel length [m]</span>
-0074    <span class="comment">%     aquiferslope   : effective aquifer slope</span>
-0075    <span class="comment">%     aquiferbreadth : distance from channel to divide</span>
-0076    <span class="comment">%     drainableporosity: drainable porosity</span>
-0077    <span class="comment">%     isflat         : logical indicating true or false</span>
-0078    <span class="comment">%     plotfits       : plot the various global fits?</span>
-0079    <span class="comment">%     bootfit        : logical indicating whether to bootstrap the</span>
-0080    <span class="comment">%                      uncertainites</span>
-0081    <span class="comment">%     bootreps       : number of reps for bootstrapping</span>
-0082    <span class="comment">%     phimethod      : method used to fit drainable porosity</span>
-0083    <span class="comment">%     refqtls        : quantiles of Q and -dQ/dt for early/late reference</span>
-0084    <span class="comment">%                      lines</span>
-0085    <span class="comment">%     earlyqtls      : quantiles of Q and -dQ/dt for early reference lines</span>
-0086    <span class="comment">%     lateqtls       : quantiles of Q and -dQ/dt for late reference lines</span>
-0087    <span class="comment">%</span>
-0088    <span class="comment">% Example</span>
-0089    <span class="comment">%</span>
-0090    <span class="comment">%  Set default event detection options, then override one default:</span>
-0091    <span class="comment">%</span>
-0092    <span class="comment">%     opts = baseflow.setopts('getevents', 'rmconvex', true);</span>
-0093    <span class="comment">%     disp(opts)</span>
+0070    <span class="comment">%  Optional name-value inputs for type 'globalfit'</span>
+0071    <span class="comment">%</span>
+0072    <span class="comment">%     drainagearea   : drainage area [m2]</span>
+0073    <span class="comment">%     drainagedensity: drainage density [km-1] = streamlength/drainagearea</span>
+0074    <span class="comment">%                      (default nan). When both are given and differ,</span>
+0075    <span class="comment">%                      globalfit uses streamlength = drainagearea*</span>
+0076    <span class="comment">%                      drainagedensity/1000.</span>
+0077    <span class="comment">%     aquiferdepth   : reference aquifer thickness [m]</span>
+0078    <span class="comment">%     streamlength   : effective channel length [m]</span>
+0079    <span class="comment">%     aquiferslope   : effective aquifer slope</span>
+0080    <span class="comment">%     aquiferbreadth : distance from channel to divide</span>
+0081    <span class="comment">%     drainableporosity: drainable porosity</span>
+0082    <span class="comment">%     isflat         : logical indicating true or false</span>
+0083    <span class="comment">%     plotfits       : plot the various global fits?</span>
+0084    <span class="comment">%     bootfit        : logical indicating whether to bootstrap the</span>
+0085    <span class="comment">%                      uncertainites</span>
+0086    <span class="comment">%     bootreps       : number of reps for bootstrapping</span>
+0087    <span class="comment">%     phimethod      : method used to fit drainable porosity</span>
+0088    <span class="comment">%     refqtls        : quantiles of Q and -dQ/dt for early/late reference</span>
+0089    <span class="comment">%                      lines</span>
+0090    <span class="comment">%     earlyqtls      : quantiles of Q and -dQ/dt for early reference lines</span>
+0091    <span class="comment">%     lateqtls       : quantiles of Q and -dQ/dt for late reference lines</span>
+0092    <span class="comment">%</span>
+0093    <span class="comment">% Example</span>
 0094    <span class="comment">%</span>
-0095    <span class="comment">% See also: fitevents, getdqdt, fitdqdt</span>
+0095    <span class="comment">%  Set default event detection options, then override one default:</span>
 0096    <span class="comment">%</span>
-0097    <span class="comment">% Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</span>
-0098 
-0099    <span class="comment">% if called with no input, open this file</span>
-0100    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
-0101 
-0102    <span class="comment">%% set default baseflow settings</span>
+0097    <span class="comment">%     opts = baseflow.setopts('getevents', 'rmconvex', true);</span>
+0098    <span class="comment">%     disp(opts)</span>
+0099    <span class="comment">%</span>
+0100    <span class="comment">% See also: fitevents, getdqdt, fitdqdt</span>
+0101    <span class="comment">%</span>
+0102    <span class="comment">% Matt Cooper, 22-Oct-2022, https://github.com/mgcooper</span>
 0103 
-0104    p = inputParser;
-0105    p.FunctionName = <span class="string">'baseflow.setopts'</span>;
+0104    <span class="comment">% if called with no input, open this file</span>
+0105    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
 0106 
-0107    p.addRequired(<span class="string">'funcname'</span>, @ischar);
-0108    parse(p,funcname);
-0109 
-0110    <span class="keyword">switch</span> funcname
+0107    <span class="comment">%% set default baseflow settings</span>
+0108 
+0109    p = inputParser;
+0110    p.FunctionName = <span class="string">'baseflow.setopts'</span>;
 0111 
-0112       <span class="comment">% event detection - input options for getevents</span>
-0113       <span class="keyword">case</span> <span class="string">'getevents'</span>
+0112    p.addRequired(<span class="string">'funcname'</span>, @ischar);
+0113    parse(p,funcname);
 0114 
-0115          addParameter(p,   <span class="string">'qmin'</span>,        1,          @isnumericscalar );
-0116          addParameter(p,   <span class="string">'nmin'</span>,        4,          @isnumericscalar );
-0117          addParameter(p,   <span class="string">'fmax'</span>,        1,          @isnumericscalar );
-0118          addParameter(p,   <span class="string">'rmax'</span>,        2,          @isnumericscalar );
-0119          addParameter(p,   <span class="string">'rmin'</span>,        1,          @isnumericscalar );
-0120          addParameter(p,   <span class="string">'cmax'</span>,        2,          @isnumericscalar );
-0121          addParameter(p,   <span class="string">'rmconvex'</span>,    false,      @islogicalscalar );
-0122          addParameter(p,   <span class="string">'rmnochange'</span>,  true,       @islogicalscalar );
-0123          addParameter(p,   <span class="string">'rmrain'</span>,      true,       @islogicalscalar );
-0124          addParameter(p,   <span class="string">'pickevents'</span>,  false,      @islogicalscalar );
-0125          addParameter(p,   <span class="string">'plotevents'</span>,  false,      @islogicalscalar );
-0126          addParameter(p,   <span class="string">'asannual'</span>,    false,      @islogicalscalar );
-0127 
-0128          <span class="comment">% event fits - input options for fitevents</span>
-0129       <span class="keyword">case</span> <span class="string">'fitevents'</span>
-0130 
-0131          addParameter(p,   <span class="string">'derivmethod'</span>, <span class="string">'ETS'</span>,      @ischar           );
-0132          addParameter(p,   <span class="string">'fitmethod'</span>,   <span class="string">'nls'</span>,      @ischar           );
-0133          addParameter(p,   <span class="string">'fitorder'</span>,    nan,        @isnumericscalar  );
-0134          addParameter(p,   <span class="string">'pickfits'</span>,    false,      @islogicalscalar  );
-0135          addParameter(p,   <span class="string">'pickmethod'</span>,  <span class="string">'none'</span>,     @ischar           );
-0136          addParameter(p,   <span class="string">'plotfits'</span>,    false,      @islogicalscalar  );
-0137          addParameter(p,   <span class="string">'saveplots'</span>,   false,      @islogicalscalar  );
-0138          addParameter(p,   <span class="string">'etsparam'</span>,    0.2,        @isnumericscalar  );
-0139          addParameter(p,   <span class="string">'vtsparam'</span>,    1.0,        @isnumericscalar  );
-0140          addParameter(p,   <span class="string">'ctsmethod'</span>,   <span class="string">'B1'</span>,       @ischar           );
-0141          addParameter(p,   <span class="string">'fitopts'</span>,     struct(),   @isstruct         );
-0142 
-0143          <span class="comment">% global fit - input to baseflow.globalfit</span>
-0144       <span class="keyword">case</span> <span class="string">'globalfit'</span>
-0145 
-0146          addParameter(p,   <span class="string">'drainagearea'</span>,      nan,        @isnumericscalar );
-0147          addParameter(p,   <span class="string">'drainagedensity'</span>,   0.8,        @isnumericscalar );
-0148          addParameter(p,   <span class="string">'aquiferdepth'</span>,      nan,        @isnumericscalar );
-0149          addParameter(p,   <span class="string">'streamlength'</span>,      nan,        @isnumericscalar );
-0150          addParameter(p,   <span class="string">'aquiferslope'</span>,      0.0,        @isnumericscalar );
-0151          addParameter(p,   <span class="string">'aquiferbreadth'</span>,    nan,        @isnumericscalar );
-0152          addParameter(p,   <span class="string">'drainableporosity'</span>, 0.1,        @isnumericscalar );
-0153          addParameter(p,   <span class="string">'isflat'</span>,            true,       @islogicalscalar );
-0154          addParameter(p,   <span class="string">'plotfits'</span>,          false,      @islogicalscalar );
-0155          addParameter(p,   <span class="string">'bootfit'</span>,           false,      @islogicalscalar );
-0156          addParameter(p,   <span class="string">'bootreps'</span>,          1000,       @isnumericscalar );
-0157          addParameter(p,   <span class="string">'phimethod'</span>,      <span class="string">'pointcloud'</span>,  @ischar          );
-0158          addParameter(p,   <span class="string">'refqtls'</span>,        [0.50 0.50],   @isnumericvector );
-0159          addParameter(p,   <span class="string">'earlyqtls'</span>,      [0.95 0.95],   @isnumericvector );
-0160          addParameter(p,   <span class="string">'lateqtls'</span>,       [0.50 0.50],   @isnumericvector );
-0161    <span class="keyword">end</span>
-0162 
-0163    parse(p,funcname,varargin{:});
-0164 
-0165    opts = p.Results;
-0166    opts = rmfield(opts,<span class="string">'funcname'</span>);
+0115    <span class="keyword">switch</span> funcname
+0116 
+0117       <span class="comment">% event detection - input options for getevents</span>
+0118       <span class="keyword">case</span> <span class="string">'getevents'</span>
+0119 
+0120          addParameter(p,   <span class="string">'qmin'</span>,        1,          @isnumericscalar );
+0121          addParameter(p,   <span class="string">'nmin'</span>,        4,          @isnumericscalar );
+0122          addParameter(p,   <span class="string">'fmax'</span>,        1,          @isnumericscalar );
+0123          addParameter(p,   <span class="string">'rmax'</span>,        2,          @isnumericscalar );
+0124          addParameter(p,   <span class="string">'rmin'</span>,        1,          @isnumericscalar );
+0125          addParameter(p,   <span class="string">'cmax'</span>,        2,          @isnumericscalar );
+0126          addParameter(p,   <span class="string">'rmconvex'</span>,    false,      @islogicalscalar );
+0127          addParameter(p,   <span class="string">'rmnochange'</span>,  true,       @islogicalscalar );
+0128          addParameter(p,   <span class="string">'rmrain'</span>,      true,       @islogicalscalar );
+0129          addParameter(p,   <span class="string">'pickevents'</span>,  false,      @islogicalscalar );
+0130          addParameter(p,   <span class="string">'plotevents'</span>,  false,      @islogicalscalar );
+0131          addParameter(p,   <span class="string">'asannual'</span>,    false,      @islogicalscalar );
+0132 
+0133          <span class="comment">% event fits - input options for fitevents</span>
+0134       <span class="keyword">case</span> <span class="string">'fitevents'</span>
+0135 
+0136          addParameter(p,   <span class="string">'derivmethod'</span>, <span class="string">'ETS'</span>,      @ischar           );
+0137          addParameter(p,   <span class="string">'fitmethod'</span>,   <span class="string">'nls'</span>,      @ischar           );
+0138          addParameter(p,   <span class="string">'fitorder'</span>,    nan,        @isnumericscalar  );
+0139          addParameter(p,   <span class="string">'pickfits'</span>,    false,      @islogicalscalar  );
+0140          addParameter(p,   <span class="string">'pickmethod'</span>,  <span class="string">'none'</span>,     @ischar           );
+0141          addParameter(p,   <span class="string">'plotfits'</span>,    false,      @islogicalscalar  );
+0142          addParameter(p,   <span class="string">'saveplots'</span>,   false,      @islogicalscalar  );
+0143          addParameter(p,   <span class="string">'etsparam'</span>,    0.2,        @isnumericscalar  );
+0144          addParameter(p,   <span class="string">'vtsparam'</span>,    1.0,        @isnumericscalar  );
+0145          addParameter(p,   <span class="string">'ctsmethod'</span>,   <span class="string">'B1'</span>,       @ischar           );
+0146          addParameter(p,   <span class="string">'fitopts'</span>,     struct(),   @isstruct         );
+0147 
+0148          <span class="comment">% global fit - input to baseflow.globalfit</span>
+0149       <span class="keyword">case</span> <span class="string">'globalfit'</span>
+0150 
+0151          addParameter(p,   <span class="string">'drainagearea'</span>,      nan,        @isnumericscalar );
+0152          addParameter(p,   <span class="string">'drainagedensity'</span>,   nan,        @isnumericscalar );
+0153          addParameter(p,   <span class="string">'aquiferdepth'</span>,      nan,        @isnumericscalar );
+0154          addParameter(p,   <span class="string">'streamlength'</span>,      nan,        @isnumericscalar );
+0155          addParameter(p,   <span class="string">'aquiferslope'</span>,      0.0,        @isnumericscalar );
+0156          addParameter(p,   <span class="string">'aquiferbreadth'</span>,    nan,        @isnumericscalar );
+0157          addParameter(p,   <span class="string">'drainableporosity'</span>, 0.1,        @isnumericscalar );
+0158          addParameter(p,   <span class="string">'isflat'</span>,            true,       @islogicalscalar );
+0159          addParameter(p,   <span class="string">'plotfits'</span>,          false,      @islogicalscalar );
+0160          addParameter(p,   <span class="string">'bootfit'</span>,           false,      @islogicalscalar );
+0161          addParameter(p,   <span class="string">'bootreps'</span>,          1000,       @isnumericscalar );
+0162          addParameter(p,   <span class="string">'phimethod'</span>,      <span class="string">'pointcloud'</span>,  @ischar          );
+0163          addParameter(p,   <span class="string">'refqtls'</span>,        [0.50 0.50],   @isnumericvector );
+0164          addParameter(p,   <span class="string">'earlyqtls'</span>,      [0.95 0.95],   @isnumericvector );
+0165          addParameter(p,   <span class="string">'lateqtls'</span>,       [0.50 0.50],   @isnumericvector );
+0166    <span class="keyword">end</span>
 0167 
-0168 <span class="keyword">end</span></pre></div>
+0168    parse(p,funcname,varargin{:});
+0169 
+0170    opts = p.Results;
+0171    opts = rmfield(opts,<span class="string">'funcname'</span>);
+0172 
+0173 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/specialfunctions.html b/toolbox/docs/html/m2html/+baseflow/specialfunctions.html
index 4fff92c..a2aca34 100644
--- a/toolbox/docs/html/m2html/+baseflow/specialfunctions.html
+++ b/toolbox/docs/html/m2html/+baseflow/specialfunctions.html
@@ -29,7 +29,9 @@ <h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src
 <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../html_img/up.png"></a></h2>
 <div class="fragment"><pre class="comment"> SPECIALFUNCTIONS Special function ibarary required for recession analysis.
 
-  fnc = specialfunctions(fR1) returns the inverse incomplete beta function
+  fR1 = specialfunctions('fR1', n) and fR2 = specialfunctions('fR2', n)
+  return the early-time and late-time constants of Rupp and Selker
+  (2005) for the conductivity profile k(z) = kD*(z/D)^n.
 
  See also: <a href="Qnonlin.html" class="code" title="function [Q,dQdt,t,hFig] = Qnonlin(a,b,Q0,t,varargin)">Qnonlin</a>
 
@@ -63,109 +65,117 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 <div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function varargout = specialfunctions(funcname, varargin)</a>
 0002    <span class="comment">% SPECIALFUNCTIONS Special function ibarary required for recession analysis.</span>
 0003    <span class="comment">%</span>
-0004    <span class="comment">%  fnc = specialfunctions(fR1) returns the inverse incomplete beta function</span>
-0005    <span class="comment">%</span>
-0006    <span class="comment">% See also: Qnonlin</span>
+0004    <span class="comment">%  fR1 = specialfunctions('fR1', n) and fR2 = specialfunctions('fR2', n)</span>
+0005    <span class="comment">%  return the early-time and late-time constants of Rupp and Selker</span>
+0006    <span class="comment">%  (2005) for the conductivity profile k(z) = kD*(z/D)^n.</span>
 0007    <span class="comment">%</span>
-0008    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0009 
-0010    <span class="comment">% L2      = L.*L;</span>
-0011    <span class="comment">% phiA2   = phi.*A.^2;</span>
-0012    <span class="comment">% phiL2   = phi.*L.^2;</span>
-0013    <span class="comment">% kL2     = kD.*L.^2;</span>
-0014 
-0015    <span class="keyword">switch</span> funcname
+0008    <span class="comment">% See also: Qnonlin</span>
+0009    <span class="comment">%</span>
+0010    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
+0011 
+0012    <span class="comment">% L2      = L.*L;</span>
+0013    <span class="comment">% phiA2   = phi.*A.^2;</span>
+0014    <span class="comment">% phiL2   = phi.*L.^2;</span>
+0015    <span class="comment">% kL2     = kD.*L.^2;</span>
 0016 
-0017       <span class="keyword">case</span> <span class="string">'fR1'</span>
+0017    <span class="keyword">switch</span> funcname
 0018 
-0019          n     = varargin{1};
-0020          fR1   = <a href="#_sub1" class="code" title="subfunction fR1 = getfR1(n)">getfR1</a>(n);
-0021 
-0022          <span class="comment">% prep output</span>
-0023          varargout{1}   = fR1;
-0024 
-0025          <span class="comment">% % for extended functionality</span>
-0026          <span class="comment">% kD    = varargin{2};</span>
-0027          <span class="comment">% L     = varargin{3};</span>
-0028          <span class="comment">% phi   = varargin{4};</span>
-0029          <span class="comment">% b     = 3;</span>
-0030          <span class="comment">% N     = -3;</span>
-0031          <span class="comment">% c     = fR1./(kD.*phi.*L.^2);</span>
-0032 
-0033       <span class="keyword">case</span> <span class="string">'fR2'</span>
+0019       <span class="keyword">case</span> <span class="string">'fR1'</span>
+0020 
+0021          n     = varargin{1};
+0022          fR1   = <a href="#_sub1" class="code" title="subfunction fR1 = getfR1(n)">getfR1</a>(n);
+0023 
+0024          <span class="comment">% prep output</span>
+0025          varargout{1}   = fR1;
+0026 
+0027          <span class="comment">% % for extended functionality</span>
+0028          <span class="comment">% kD    = varargin{2};</span>
+0029          <span class="comment">% L     = varargin{3};</span>
+0030          <span class="comment">% phi   = varargin{4};</span>
+0031          <span class="comment">% b     = 3;</span>
+0032          <span class="comment">% N     = -3;</span>
+0033          <span class="comment">% c     = fR1./(kD.*phi.*L.^2);</span>
 0034 
-0035          n     = varargin{1};
-0036          fR2   = <a href="#_sub2" class="code" title="subfunction fR2 = getfR2(n)">getfR2</a>(n);
-0037 
-0038          <span class="comment">% prep output</span>
-0039          varargout{1}   = fR2;
-0040 
-0041          <span class="comment">% % for extended functionality</span>
-0042          <span class="comment">% kD    = varargin{2};</span>
-0043          <span class="comment">% L     = varargin{3};</span>
-0044          <span class="comment">% phi   = varargin{4};</span>
-0045          <span class="comment">% A     = varargin{5};</span>
-0046          <span class="comment">%</span>
-0047          <span class="comment">% b     = (2.*n+3)./(n+2);</span>
-0048          <span class="comment">% N     = -n./(n+2);</span>
-0049          <span class="comment">% c     = fR2./phi.*( (kD.*L.*L) ./ (2.^n.*(n+1).*A.^(n+3)));</span>
-0050 
-0051       <span class="keyword">case</span> <span class="string">'fLo'</span>
-0052          
-0053          assert(numel(varargin) &gt;= 4)
-0054          kD = varargin{2};
-0055          L = varargin{3};
-0056          phi = varargin{4};
-0057          
-0058          phiL2 = phi.*L.^2;
-0059 
-0060          h0overD = 0.0; <span class="comment">% assume h0=0, fLo=1.1361</span>
-0061          soln = 2; <span class="comment">% jul 2024 - soln was unset, so I used Lockington.</span>
-0062          fLo = <a href="#_sub3" class="code" title="subfunction fLo = getfLo(h0overD,soln)">getfLo</a>(h0overD, soln);
-0063 
-0064          b = 3;
-0065          N = -3;
-0066          c = fLo./(kD.*phiL2);
-0067    <span class="keyword">end</span>
-0068 <span class="keyword">end</span>
-0069 
-0070 <span class="comment">%% Local Functions</span>
-0071 <a name="_sub1" href="#_subfunctions" class="code">function fR1 = getfR1(n)</a>
-0072    BR1     = beta(n+2, 2);
-0073    gamma   = 2 * (n+2) .* BR1;
-0074    mu      = (4 - 3*gamma - sqrt(gamma.^2 - 2*gamma + 4)) ./ (4*(1 - 2*gamma));
-0075    fR1     = (1-mu) .* (n+1) .* (n+2) ./ (2 * (1 - 2*mu));
-0076 <span class="keyword">end</span>
-0077 
-0078 <a name="_sub2" href="#_subfunctions" class="code">function fR2 = getfR2(n)</a>
-0079    BR2 = beta((n+2) ./ (n+3), 1/2);
-0080    fR2 = (n+2) .* (BR2 ./ (n+3)) .^ (1./(n+2));
+0035       <span class="keyword">case</span> <span class="string">'fR2'</span>
+0036 
+0037          n     = varargin{1};
+0038          fR2   = <a href="#_sub2" class="code" title="subfunction fR2 = getfR2(n)">getfR2</a>(n);
+0039 
+0040          <span class="comment">% prep output</span>
+0041          varargout{1}   = fR2;
+0042 
+0043          <span class="comment">% % for extended functionality</span>
+0044          <span class="comment">% kD    = varargin{2};</span>
+0045          <span class="comment">% L     = varargin{3};</span>
+0046          <span class="comment">% phi   = varargin{4};</span>
+0047          <span class="comment">% A     = varargin{5};</span>
+0048          <span class="comment">%</span>
+0049          <span class="comment">% b     = (2.*n+3)./(n+2);</span>
+0050          <span class="comment">% N     = -n./(n+2);</span>
+0051          <span class="comment">% c     = fR2./phi.*( (kD.*L.*L) ./ (2.^n.*(n+1).*A.^(n+3)));</span>
+0052 
+0053       <span class="keyword">case</span> <span class="string">'fLo'</span>
+0054          
+0055          assert(numel(varargin) &gt;= 4)
+0056          kD = varargin{2};
+0057          L = varargin{3};
+0058          phi = varargin{4};
+0059          
+0060          phiL2 = phi.*L.^2;
+0061 
+0062          h0overD = 0.0; <span class="comment">% assume h0=0, fLo=1.1361</span>
+0063          soln = 2; <span class="comment">% jul 2024 - soln was unset, so I used Lockington.</span>
+0064          fLo = <a href="#_sub3" class="code" title="subfunction fLo = getfLo(h0overD,soln)">getfLo</a>(h0overD, soln);
+0065 
+0066          b = 3;
+0067          N = -3;
+0068          c = fLo./(kD.*phiL2);
+0069    <span class="keyword">end</span>
+0070 <span class="keyword">end</span>
+0071 
+0072 <span class="comment">%% Local Functions</span>
+0073 <a name="_sub1" href="#_subfunctions" class="code">function fR1 = getfR1(n)</a>
+0074    <span class="comment">% early-time constant of Rupp and Selker (2005), eqs 33 and 56, m = 1.</span>
+0075    <span class="comment">% gamma is their A (eq 28). fR1/(n+1) is their Phi1 (Table 1: 1.108 at</span>
+0076    <span class="comment">% n = 0), because a1 here uses kD, as their eq 54 does.</span>
+0077    BR1     = beta(n+2, 2);
+0078    gamma   = 2 * (n+2) .* BR1;
+0079    mu      = (4 - 3*gamma - sqrt(gamma.^2 - 2*gamma + 4)) ./ (4 - 2*gamma);
+0080    fR1     = (1-mu) .* (n+1) .* (n+2) ./ (2 * (1 - 2*mu));
 0081 <span class="keyword">end</span>
 0082 
-0083 <a name="_sub3" href="#_subfunctions" class="code">function fLo = getfLo(h0overD,soln)</a>
-0084 
-0085    <span class="comment">% various solutions exist, all depend on ratio of water level in stream</span>
-0086    <span class="comment">% (h0) to initial water table level (h_infinity, or as I call it D)</span>
-0087 
-0088    <span class="keyword">switch</span> soln
-0089       <span class="keyword">case</span> 2              <span class="comment">% Lockington</span>
+0083 <a name="_sub2" href="#_subfunctions" class="code">function fR2 = getfR2(n)</a>
+0084    <span class="comment">% late-time constant of Rupp and Selker (2005). At n = 0 it is the</span>
+0085    <span class="comment">% Brutsaert and Nieber (1977) constant 4.804 that fitphi uses for BS04.</span>
+0086    <span class="comment">% fR2/2 is their Phi2 (eq 59; Table 1: 2.402 at n = 0).</span>
+0087    BR2 = beta((n+2) ./ (n+3), 1/2);
+0088    fR2 = (n+2) .* (BR2.^(n+3) ./ (n+3)) .^ (1./(n+2));
+0089 <span class="keyword">end</span>
 0090 
-0091          a   = -0.4604;
-0092          b   = 1.0734;
-0093          c   = -0.9673;
-0094          d   = 1.1361;
+0091 <a name="_sub3" href="#_subfunctions" class="code">function fLo = getfLo(h0overD,soln)</a>
+0092 
+0093    <span class="comment">% various solutions exist, all depend on ratio of water level in stream</span>
+0094    <span class="comment">% (h0) to initial water table level (h_infinity, or as I call it D)</span>
 0095 
-0096          fLo = a.*h0overD.^3 + b.*h0overD.^2 + c.*h0overD + d;
-0097 
-0098       <span class="keyword">case</span> 20             <span class="comment">% Hayek</span>
-0099 
-0100          <span class="comment">% not sure exactly how to represent Hayek's function, the</span>
-0101          <span class="comment">% a/b/c/d values are functions of D, whereas Rupp gave a single</span>
-0102          <span class="comment">% set for all D, I think, but that set might be an</span>
-0103          <span class="comment">% approximation that works well for all D. See tabl 3 of Hayek</span>
-0104 
-0105       <span class="keyword">case</span> 21             <span class="comment">% Basha</span>
-0106    <span class="keyword">end</span>
-0107 <span class="keyword">end</span></pre></div>
+0096    <span class="keyword">switch</span> soln
+0097       <span class="keyword">case</span> 2              <span class="comment">% Lockington</span>
+0098 
+0099          a   = -0.4604;
+0100          b   = 1.0734;
+0101          c   = -0.9673;
+0102          d   = 1.1361;
+0103 
+0104          fLo = a.*h0overD.^3 + b.*h0overD.^2 + c.*h0overD + d;
+0105 
+0106       <span class="keyword">case</span> 20             <span class="comment">% Hayek</span>
+0107 
+0108          <span class="comment">% not sure exactly how to represent Hayek's function, the</span>
+0109          <span class="comment">% a/b/c/d values are functions of D, whereas Rupp gave a single</span>
+0110          <span class="comment">% set for all D, I think, but that set might be an</span>
+0111          <span class="comment">% approximation that works well for all D. See tabl 3 of Hayek</span>
+0112 
+0113       <span class="keyword">case</span> 21             <span class="comment">% Basha</span>
+0114    <span class="keyword">end</span>
+0115 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/function_index.html b/toolbox/docs/html/m2html/function_index.html
index 351e816..1c3c8af 100644
--- a/toolbox/docs/html/m2html/function_index.html
+++ b/toolbox/docs/html/m2html/function_index.html
@@ -118,6 +118,6 @@ <h2>Function Files in these Packages</h2>
 		<td><a href="" title=""></a></td>	</tr></table>
 
 
-<hr><address>Generated on Fri 18-Sep-2026 12:28:37 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Tue 13-Oct-2026 21:00:16 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file

From 15cacd75da127fc2431e6299b7181416172ae827 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Tue, 13 Oct 2026 21:47:54 -0700
Subject: [PATCH 15/28] test(baseflow): describe the Kuparuk workflow checks as
 they run

- tests/TestBaseflow.m: the check that globalfit recovers the Kuparuk
  recession exponent is test_kuparukRecessionExponent. Its expected
  value is the property kuparukb. The help and comments name the annual
  workflow and the 1.1.0 release notes as the source of the value. The
  expected value and the tolerance do not change.
- tests/TestBaseflow.m: the class setup runs the chain of
  baseflow_demo_kuparuk with the demo options, and its comment says so.
  The aquifer-property check follows the steps of baseflow_demo_3 on the
  point cloud of that chain, and its comment says so. The setup names
  its figure snapshot setupfigs, so it does not shadow the figsbefore
  property.
- CHANGELOG.md: the [Unreleased] TestBaseflow entry describes the same
  checks and names the suites that hold the checks of the removed
  test_corechain. The expectedtau entry says that no function raises
  baseflow:plfitb:tauPoleReplicates.
- TODO.md: an update names the test that holds the zero-figure check of
  the removed test_corechain.
---
 CHANGELOG.md         | 16 +++++++++-------
 TODO.md              |  4 ++++
 tests/TestBaseflow.m | 26 ++++++++++++++------------
 3 files changed, 27 insertions(+), 19 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index e835dca..aa4301f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -10,17 +10,19 @@ semantic versioning.
 
 - The unit tests of `tests/TestBaseflow.m` live in per-function suites,
   `tests/test_<function_name>.m`. `TestBaseflow` is the integration suite
-  of the documented workflow. It runs `baseflow_demo_kuparuk` once and
+  of the documented workflow. It runs the chain of `baseflow_demo_kuparuk`
+  once, with the demo options but without figures or the bootstrap. It
   checks each stage against the stage before it. It also checks the
-  published Kuparuk recession exponent, the BS04 and RS05 aquifer
-  properties at b = 3/2, and a synthetic divergent tail. `test_corechain`
-  is retired; its workflow checks moved to `TestBaseflow` and its
-  function checks to the suites of those functions.
+  Kuparuk recession exponent, the BS04 and RS05 aquifer
+  properties at b = 3/2, and a synthetic divergent tail. `TestBaseflow`
+  holds the workflow checks of the removed `tests/test_corechain.m`, and
+  the per-function suites hold its function checks.
 - One private function, `expectedtau`, computes the mean tau for
   `gpfitb`, `plfitb`, `plplotb`, and `baseflow.getfunction`. It alone
   raises the pole warning, `baseflow:expectedtau:tauPole`, with the count
-  of values of b that give no finite mean tau. That identifier replaces
-  `baseflow:plfitb:tauPoleReplicates`.
+  of values of b that give no finite mean tau. No function raises
+  `baseflow:plfitb:tauPoleReplicates`. Suppress
+  `baseflow:expectedtau:tauPole` to silence the pole warning.
 
 ### Fixed
 
diff --git a/TODO.md b/TODO.md
index 63077db..b660094 100644
--- a/TODO.md
+++ b/TODO.md
@@ -276,6 +276,10 @@ reaches as known external. The rows below record the earlier state.
     (`globalfit.m:91-93`). `tests/test_corechain.m` requires zero new
     figures from a global fit with `plotfits` false, and
     `test_cloudphiPlotfit` covers both flag values.
+  - update (2026-10-13): `tests/test_corechain.m` is removed.
+    `TestBaseflow/test_divergentTailHasNoExpectedFlow` holds its check
+    that a global fit with `plotfits` false opens no figure. This
+    update supersedes the test_corechain names above.
 
 ## Sandbox rehabilitation (bfra-3kh.20 stub, W2)
 
diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index 59a15f1..67cd4ce 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -9,7 +9,7 @@
    % independent value or relationship:
    %     1) the event-detection defaults and rmax guard of getevents,
    %        eventfinder, and wrapevents
-   %     2) the published Kuparuk recession exponent (Cooper et al., 2023)
+   %     2) the recession exponent of the Kuparuk annual workflow
    %     3) the tail, mean tau, and expected flows of globalfit, and its
    %        check of a given streamlength against a given drainage density
    %     4) the baseflow trend at the expected-flow quantile
@@ -42,9 +42,9 @@
       Dd = 0.8
       D = 0.47
 
-      % The recession exponent that Cooper et al. (2023) publish for the
-      % Kuparuk annual workflow, and the rounding of the published value.
-      publishedb = 1.3540
+      % The recession exponent of the Kuparuk annual workflow, as the 1.1.0
+      % release notes record it, and the rounding of that value.
+      kuparukb = 1.3540
       btol = 5e-4
 
       % The synthetic recessions follow -dQ/dt = a*Q^b for eight days. The
@@ -68,11 +68,12 @@
 
    methods (TestClassSetup)
       function runkuparukchain(testCase)
-         % Run baseflow_demo_kuparuk once, without figures or the bootstrap.
+         % Run the chain of baseflow_demo_kuparuk once, with the demo
+         % options but without figures or the bootstrap.
          % trendplot draws its figures off screen whatever showfig asks, so
          % close the figures the chain leaves.
-         figsbefore = findall(0, 'Type', 'figure');
-         testCase.addTeardown(@() closenewfigs(figsbefore));
+         setupfigs = findall(0, 'Type', 'figure');
+         testCase.addTeardown(@() closenewfigs(setupfigs));
          L = testCase.A*testCase.Dd/1000;
          [T, Q, R] = baseflow.loadExampleData('kuparuk');
          opts = baseflow.setopts('globalfit', 'drainagearea', testCase.A, ...
@@ -180,12 +181,12 @@ function test_rmaxguard(testCase, EventFunction)
             ['MATLAB:' validator ':notGreater'])
       end
 
-      function test_publishedRecessionExponent(testCase)
-         % globalfit recovers the published Kuparuk recession exponent from
-         % the tau sample of the event fits.
+      function test_kuparukRecessionExponent(testCase)
+         % globalfit recovers the recession exponent of the Kuparuk annual
+         % workflow from the tau sample of the event fits.
          returned = testCase.Chain.GlobalFit.b;
 
-         testCase.verifyEqual(returned, testCase.publishedb, ...
+         testCase.verifyEqual(returned, testCase.kuparukb, ...
             'AbsTol', testCase.btol)
       end
 
@@ -318,7 +319,8 @@ function test_aquiferPropsAgreeAtHomogeneousLimit(testCase)
          % At b = 3/2 the RS05 solution has n = 0, where it reduces to the
          % BS04 solution. So the two give the same k, D, and Q0. The BS04
          % constant 4.804 is published to three decimals. The inputs follow
-         % baseflow_demo_3: the point cloud, its nls a, and phi = 0.033.
+         % the steps of baseflow_demo_3 on the Kuparuk point cloud of the
+         % class setup: its nls a, and phi = 0.033.
          q = testCase.Chain.Fits.q;
          dqdt = testCase.Chain.Fits.dqdt;
          Fit = baseflow.fitab(q, dqdt, 'nls');

From 38d9ad3da95cf6fa92e9ecfbac10b84c329dd1bf Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Sat, 17 Oct 2026 16:46:02 -0700
Subject: [PATCH 16/28] fix(docs): stop tracking the generated doc search
 metadata

- toolbox/docs/html/custom_toolbox.json: Git does not track it.
  builddocsearchdb writes it again on each docs build, with the absolute
  path of the build folder, so a copy names a folder of the machine that
  built it. The help registration reads toolbox/info.xml. A local search
  server returned the same query results with the file tracked,
  missing, unreadable, or naming another folder.
- .gitignore and toolbox/toolbox.ignore: rules keep the file out of
  version control and out of a toolbox package. The search database in
  helpsearch-v4_en still ships.
- tests/test_makedocs.m: checks that a toolbox package leaves out the
  file and holds every file of the search database, and that Git
  ignores the file.
- CHANGELOG.md: an [Unreleased] entry describes the change.
---
 .gitignore                            |  3 +
 CHANGELOG.md                          |  7 +++
 tests/test_makedocs.m                 | 89 +++++++++++++++++++++++++++
 toolbox/docs/html/custom_toolbox.json |  1 -
 toolbox/toolbox.ignore                |  5 ++
 5 files changed, 104 insertions(+), 1 deletion(-)
 create mode 100644 tests/test_makedocs.m
 delete mode 100644 toolbox/docs/html/custom_toolbox.json
 create mode 100644 toolbox/toolbox.ignore

diff --git a/.gitignore b/.gitignore
index 7a83bcb..4c719e1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -72,6 +72,9 @@ codegen/
 *.slxc
 .MATLABDriveTag
 
+# Written by the Help browser search-database build beside the docs; not a source file.
+custom_toolbox.json
+
 # -----------------
 # ---- PYTHON -----
 # -----------------
diff --git a/CHANGELOG.md b/CHANGELOG.md
index aa4301f..aad1f3d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -23,6 +23,13 @@ semantic versioning.
   of values of b that give no finite mean tau. No function raises
   `baseflow:plfitb:tauPoleReplicates`. Suppress
   `baseflow:expectedtau:tauPole` to silence the pole warning.
+- Git does not track `toolbox/docs/html/custom_toolbox.json`.
+  `builddocsearchdb`, which `baseflow.internal.makedocs` calls for the
+  'docsearch' option, writes it again on each build, with the absolute
+  path of the build folder. A copy names a folder that exists only on the
+  machine that built it. The search database in `helpsearch-v4_en` still
+  ships, and `toolbox/toolbox.ignore` leaves the file out of a toolbox
+  package.
 
 ### Fixed
 
diff --git a/tests/test_makedocs.m b/tests/test_makedocs.m
new file mode 100644
index 0000000..96a05ca
--- /dev/null
+++ b/tests/test_makedocs.m
@@ -0,0 +1,89 @@
+classdef test_makedocs < matlab.unittest.TestCase
+   %TEST_MAKEDOCS Test that the docs build keeps machine metadata local.
+   %
+   % The 'docsearch' option of baseflow.internal.makedocs calls
+   % builddocsearchdb. It writes toolbox/docs/html/custom_toolbox.json with
+   % the absolute path of the folder it builds in, then indexes the pages.
+   % Each build writes the file again, and a copy names a folder that
+   % exists only on the machine that built it. So version control and the
+   % toolbox package must leave it out, and the package must keep the
+   % search database.
+
+   properties (Constant)
+      % The generated file, relative to the project root. Git takes the
+      % forward slashes on every platform.
+      metadatafile = 'toolbox/docs/html/custom_toolbox.json'
+
+      % The search database folder, relative to the project root. The
+      % package must keep every file in it.
+      searchdb = 'toolbox/docs/html/helpsearch-v4_en'
+
+      % Any identifier works, because the test builds no package.
+      packageid = 'baseflow-test'
+   end
+
+   properties
+      % The project root, the folder that holds tests/ and toolbox/.
+      Root
+   end
+
+   methods (TestClassSetup)
+      function seedmetadata(testCase)
+         % A clean checkout holds no generated file, so a package check
+         % would pass whether or not the rule works. Write a placeholder
+         % when the file is missing, and delete only that copy.
+         testCase.Root = fileparts(fileparts(mfilename('fullpath')));
+         seeded = fullfile(testCase.Root, testCase.metadatafile);
+         if ~isfile(seeded)
+            writelines("{}", seeded);
+            testCase.addTeardown(@delete, seeded);
+         end
+      end
+   end
+
+   methods (Test)
+      function test_packageOmitsSearchMetadata(testCase)
+         % The Package Toolbox task reads toolbox/toolbox.ignore. It leaves
+         % out the generated file and keeps the search database.
+         testCase.assumeTrue( ...
+            exist('matlab.addons.toolbox.ToolboxOptions', 'class') == 8, ...
+            'ToolboxOptions needs MATLAB R2023a or later')
+         opts = matlab.addons.toolbox.ToolboxOptions( ...
+            fullfile(testCase.Root, 'toolbox'), testCase.packageid);
+         packaged = string(opts.ToolboxFiles);
+
+         % The files of the search database on disk are the files the
+         % package must hold.
+         ondisk = dir(fullfile(testCase.Root, testCase.searchdb, '**', '*'));
+         ondisk = ondisk(~[ondisk.isdir]);
+         searchdb_expected = sort(string(fullfile({ondisk.folder}, ...
+            {ondisk.name})));
+         searchdb_returned = sort(packaged(startsWith(packaged, ...
+            fullfile(testCase.Root, testCase.searchdb))));
+         metadata_returned = packaged(endsWith(packaged, ...
+            "custom_toolbox.json"));
+
+         testCase.verifyEmpty(metadata_returned)
+         testCase.verifyNotEmpty(searchdb_expected)
+         testCase.verifyEqual(searchdb_returned(:), searchdb_expected(:))
+      end
+
+      function test_versionControlIgnoresSearchMetadata(testCase)
+         % Git reports a tracked file as not ignored, so this check fails
+         % when the file is tracked again or the ignore rule is lost. Then a
+         % docs build changes the worktree. Run Git from the project root,
+         % so the commands hold no path that the shell could expand.
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.CurrentFolderFixture(testCase.Root));
+         [status, ~] = system('git rev-parse --git-dir');
+         testCase.assumeEqual(status, 0, ...
+            'the project root is not a Git checkout')
+
+         [returned, ~] = system(['git check-ignore -q -- ' ...
+            testCase.metadatafile]);
+         expected = 0;
+
+         testCase.verifyEqual(returned, expected)
+      end
+   end
+end
diff --git a/toolbox/docs/html/custom_toolbox.json b/toolbox/docs/html/custom_toolbox.json
deleted file mode 100644
index d37adb5..0000000
--- a/toolbox/docs/html/custom_toolbox.json
+++ /dev/null
@@ -1 +0,0 @@
-{"Name":"Baseflow Recession Analysis Toolbox","ShortName":"baseflow_recession_analysis_toolbox","ID":"3ptoolbox::baseflow_recession_analysis_toolbox","ToolboxHelpLocations":[{"ContentType":"doc","LocationOnDisk":"/Users/mattcooper/MATLAB/projects/bfra/toolbox/docs/html","AbsolutePath":"/Users/mattcooper/MATLAB/projects/bfra/toolbox/info.xml","HelpLocation":"3ptoolbox/baseflowrecessionanalysistoolbox/doc"}]}
\ No newline at end of file
diff --git a/toolbox/toolbox.ignore b/toolbox/toolbox.ignore
new file mode 100644
index 0000000..b684a3b
--- /dev/null
+++ b/toolbox/toolbox.ignore
@@ -0,0 +1,5 @@
+% Files that the Package Toolbox task leaves out of the toolbox. Paths are
+% relative to this folder, one rule per line. MATLAB reads this file only
+% from the toolbox root folder.
+% Written by the Help browser search-database build beside the docs
+**/custom_toolbox.json

From 07bba316fee9762ed89764b8723454e42b0182be Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 18:08:45 -0700
Subject: [PATCH 17/28] refactor(baseflow): share one plotrain between the
 point-cloud figures

- toolbox/+baseflow/private/plotrain.m: one helper draws the rain
  circles for pointcloudplot and plotdqdt. Each circle has the size of
  the plotted marker plus sqrt(pi*rain^2). The helper keeps the
  comments of both local copies, which it replaces.
- plotrain returns nan when no point has rain > 0. NaN rain gives a
  NaN sum, so the sum test alone drew no circle and left the output
  unassigned. For dry or NaN rain, the plotdqdt struct has hrain = nan
  where it had no hrain field. The legend and the figure do not change.
- tests/test_plotrain.m: both callers draw the same circles at the wet
  points, and zero or NaN rain draws none. The circle rows also pass
  on the code before this change.
---
 tests/test_plotrain.m                | 120 +++++++++++++++++++++++++++
 toolbox/+baseflow/plotdqdt.m         |  31 +------
 toolbox/+baseflow/pointcloudplot.m   |  30 -------
 toolbox/+baseflow/private/plotrain.m |  42 ++++++++++
 4 files changed, 163 insertions(+), 60 deletions(-)
 create mode 100644 tests/test_plotrain.m
 create mode 100644 toolbox/+baseflow/private/plotrain.m

diff --git a/tests/test_plotrain.m b/tests/test_plotrain.m
new file mode 100644
index 0000000..f966b51
--- /dev/null
+++ b/tests/test_plotrain.m
@@ -0,0 +1,120 @@
+classdef test_plotrain < matlab.unittest.TestCase
+   %TEST_PLOTRAIN Test the rain circles of pointcloudplot and plotdqdt.
+   %
+   % Both functions call the private plotrain. It draws one open magenta
+   % circle at each point that has rain. The circle size is the marker size
+   % of the plotted points plus sqrt(pi*rain^2). With no rain above zero,
+   % including NaN rain, it draws no circle and returns nan. Each case runs
+   % one caller on the same data, so the two figures keep the same circles.
+   %
+   % See also: test_pointcloudplot, test_plotdqdt
+
+   properties (TestParameter)
+      % The public functions that draw the rain circles.
+      caller = {'pointcloudplot', 'plotdqdt'}
+
+      % Rain with no value above zero: zero everywhere, or NaN everywhere,
+      % as an event without a rain record gives.
+      dryrain = struct('zero', 0, 'nan', NaN)
+   end
+
+   properties (Constant)
+      % The rain at two wet points, in mm. The other points are dry.
+      wetindex = [1 3]
+      wetrain = [5 2]
+
+      % Rounding error allowed in a position. plotdqdt plots exp(log(q)),
+      % which differs from q in the last bits.
+      reltol = 1e-12
+   end
+
+   properties
+      % Point-cloud test data.
+      q
+      dqdt
+      % Open-figure snapshot taken before each test.
+      figsbefore
+   end
+
+   methods (TestClassSetup)
+      function preparecase(testCase)
+         % Nonlinear test data (b = 1.5), as in test_plotdqdt.
+         a = 1e-2;
+         b = 1.5;
+         q0 = 100;
+         t = 1:100;
+         [~, testCase.q, testCase.dqdt] = baseflow.generateTestData( ...
+            a, b, q0, t);
+      end
+   end
+
+   methods (TestMethodSetup)
+      function snapshotfigures(testCase)
+         % Close the figures each case opens (see tests/closenewfigs.m).
+         testCase.figsbefore = findall(0, 'Type', 'figure');
+         testCase.addTeardown(@() closenewfigs(testCase.figsbefore));
+      end
+   end
+
+   methods (Access = private)
+      function [hrain, hpoints] = draw(testCase, caller, rain)
+         %DRAW Draw the point cloud with one caller and return its handles.
+         %
+         %  [hrain, hpoints] = draw(testCase, caller, rain) returns the
+         %  rain circle handles and the handle of the plotted points.
+         switch caller
+            case 'pointcloudplot'
+               out = baseflow.pointcloudplot(testCase.q, testCase.dqdt, ...
+                  'rain', rain);
+               hrain = out.hrain;
+               hpoints = out.scatter;
+            case 'plotdqdt'
+               h = baseflow.plotdqdt(testCase.q, testCase.dqdt, 'rain', rain);
+               hrain = h.hrain;
+               hpoints = h.scatter;
+         end
+      end
+   end
+
+   methods (Test)
+      function test_circlesMarkTheWetPoints(testCase, caller)
+         % One circle sits on each wet point, and its size grows with the
+         % rain by sqrt(pi*rain^2) over the size of the plotted points.
+         rain = zeros(size(testCase.q));
+         rain(testCase.wetindex) = testCase.wetrain;
+
+         [hrain, hpoints] = testCase.draw(caller, rain);
+
+         x_expected = testCase.q(testCase.wetindex);
+         y_expected = -testCase.dqdt(testCase.wetindex);
+         size_expected = get(hpoints, 'MarkerSize') ...
+            + sqrt(pi .* testCase.wetrain(:) .^ 2);
+
+         testCase.verifyNumElements(hrain, numel(testCase.wetindex))
+         [x_returned, order] = sort(cell2mat(get(hrain(:), 'XData')), ...
+            'descend');
+         y_returned = cell2mat(get(hrain(:), 'YData'));
+         size_returned = cell2mat(get(hrain(:), 'MarkerSize'));
+         testCase.verifyEqual(x_returned, x_expected(:), ...
+            'RelTol', testCase.reltol)
+         testCase.verifyEqual(y_returned(order), y_expected(:), ...
+            'RelTol', testCase.reltol)
+         testCase.verifyEqual(size_returned(order), size_expected, ...
+            'RelTol', testCase.reltol)
+         testCase.verifyEqual(get(hrain(1), 'Color'), [1 0 1])
+         testCase.verifyEqual(get(hrain(1), 'MarkerFaceColor'), 'none')
+      end
+
+      function test_noRainDrawsNoCircle(testCase, caller, dryrain)
+         % With no rain above zero, plotrain draws nothing and returns nan,
+         % which keeps the rain entry out of the legend. NaN rain makes the
+         % sum NaN, so a test of the sum alone draws no circle and leaves
+         % the output unassigned.
+         rain = dryrain .* ones(size(testCase.q));
+
+         hrain = testCase.draw(caller, rain);
+
+         testCase.verifyTrue(isscalar(hrain) && isnan(hrain))
+      end
+   end
+end
diff --git a/toolbox/+baseflow/plotdqdt.m b/toolbox/+baseflow/plotdqdt.m
index 470dc02..dea3e1c 100644
--- a/toolbox/+baseflow/plotdqdt.m
+++ b/toolbox/+baseflow/plotdqdt.m
@@ -405,7 +405,7 @@
    % because Octave installs no listener to do it.
    relayoutloglogtext(h.ax);
 
-   h = plotrain(h, rain, x, y);
+   h.hrain = plotrain(h.ax, h.scatter, rain, x, y);
 
    % I added this so rain is in the legend. plotrain returns the handles of
    % the rain circles, or nan when no rain is plotted, so the guard tests
@@ -462,35 +462,6 @@ function labelReflines(h, labelcolor, labelfontsize, labelstyle)
    end
 end
 
-%%
-function h = plotrain(h,rain,x,y)
-
-   % add rain. scale the circles such that 1 mm of rain equals the size of
-   % the plotted circles
-   if sum(rain)==0
-      h.hrain = nan;
-   else
-
-      % scatter is producing pixelated symbols so I use plot instead
-      %sz    = h.scatter.SizeData + pi.*(rain(rain>0)).^2;
-      %scatter(x(rain>0),y(rain>0),sz,'LineWidth',2)
-
-      % this mimics the way scatter scales the circles. Read the size with
-      % get, because Octave returns a numeric handle, which takes no dot.
-      s = get(h.scatter, 'MarkerSize') + sqrt(pi.*(rain(rain>0)).^2);
-      x = x(rain>0);
-      y = y(rain>0);
-
-      hold(h.ax, 'on');
-
-      % Count down so the handle array takes its size on the first pass.
-      for n = numel(s):-1:1
-         h.hrain(n) = plot(h.ax,x(n),y(n),'o','MarkerSize',s(n), ...
-            'MarkerFaceColor','none','Color','m','LineWidth',1);
-      end
-   end
-end
-
 %%
 function addRotatedText(xtxt,ytxt,txt,slope,axpos) %#ok<*DEFNU> 
 
diff --git a/toolbox/+baseflow/pointcloudplot.m b/toolbox/+baseflow/pointcloudplot.m
index 8759bed..efb8c7a 100644
--- a/toolbox/+baseflow/pointcloudplot.m
+++ b/toolbox/+baseflow/pointcloudplot.m
@@ -343,36 +343,6 @@
 end
 
 %% LOCAL FUNCTIONS
-function hrain = plotrain(ax,h,rain,x,y)
-
-   % ax is the axis to plot into
-   % h is the handle of the plotted q/dqdt to get the marker size to scale
-   % the rain circles
-   % x and y are q -dqdt
-
-   % add rain. scale the circles such that 1 mm of rain equals the size of
-   % the plotted circles
-   if sum(rain)==0
-      hrain = nan;
-   else
-
-      % scatter is producing pixelated symbols so I use plot instead
-      % sz = h.scatter.SizeData + pi.*(rain(rain>0)).^2;
-      % scatter(x(rain>0),y(rain>0),sz,'LineWidth',2)
-
-      % this mimics the way scatter scales the circles
-      sz = get(h,'MarkerSize') + sqrt(pi.*(rain(rain>0)).^2);
-      x = x(rain>0);
-      y = y(rain>0);
-
-      hold(ax, 'on');
-      for n = numel(sz):-1:1
-         hrain(n) = plot(ax,x(n),y(n),'o','MarkerSize',sz(n), ...
-            'MarkerFaceColor','none','Color','m','LineWidth',1);
-      end
-   end
-end
-
 %% INPUT PARSER
 function [q, dqdt, mask, reflines, reflabels, blate, userab, precision, ...
       timestep, addlegend, usertext, rain, axislimits, labelstyle, ...
diff --git a/toolbox/+baseflow/private/plotrain.m b/toolbox/+baseflow/private/plotrain.m
new file mode 100644
index 0000000..6796a91
--- /dev/null
+++ b/toolbox/+baseflow/private/plotrain.m
@@ -0,0 +1,42 @@
+function hrain = plotrain(ax, hmarker, rain, x, y)
+   %PLOTRAIN Circle the point-cloud points that have rain.
+   %
+   %  hrain = plotrain(ax, hmarker, rain, x, y) draws one open magenta
+   %  circle in ax at each point (x, y) where rain > 0. The circle size is
+   %  the marker size of hmarker plus sqrt(pi*rain^2), so 1 mm of rain
+   %  adds the size of a 1 mm circle to the plotted marker. hrain holds
+   %  the circle handles, or nan when no point has rain > 0.
+   %
+   %  ax is the axis to plot into. hmarker is the handle of the plotted
+   %  q/dqdt points, which gives the marker size that scales the circles.
+   %  x and y are q and -dqdt.
+   %
+   %  See also: pointcloudplot, plotdqdt
+
+   % add rain. scale the circles such that 1 mm of rain equals the size of
+   % the plotted circles. Return nan when no point has rain > 0, because
+   % the legend guards of both callers test for nan. NaN rain makes the
+   % sum NaN, so the sum test alone misses that case.
+   if sum(rain)==0 || ~any(rain>0)
+      hrain = nan;
+   else
+
+      % scatter is producing pixelated symbols so I use plot instead
+      % sz = h.scatter.SizeData + pi.*(rain(rain>0)).^2;
+      % scatter(x(rain>0),y(rain>0),sz,'LineWidth',2)
+
+      % this mimics the way scatter scales the circles. Read the size with
+      % get, because Octave returns a numeric handle, which takes no dot.
+      sz = get(hmarker, 'MarkerSize') + sqrt(pi.*(rain(rain>0)).^2);
+      x = x(rain>0);
+      y = y(rain>0);
+
+      hold(ax, 'on');
+
+      % Count down so the handle array takes its size on the first pass.
+      for n = numel(sz):-1:1
+         hrain(n) = plot(ax,x(n),y(n),'o','MarkerSize',sz(n), ...
+            'MarkerFaceColor','none','Color','m','LineWidth',1);
+      end
+   end
+end

From c9f90b49c794588b97c356d87266f115dd448120 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 18:08:45 -0700
Subject: [PATCH 18/28] docs(baseflow): document the hyetograph tags the code
 sets

- toolbox/+baseflow/hyetograph.m: the help names the order of H and the
  tags HyetographFigure, HyetographAxis, StreamflowPlot, and
  PrecipitationPlot. The examples search from the figure H(1), because
  a search of all of H returns the streamflow axes twice. The untagged
  precipitation axes is ancestor(H(4), 'axes').
- tests/test_hyetograph.m: each documented lookup returns its one
  element of H, and the ancestor of the bars is the reversed axes.
- CHANGELOG.md: an [Unreleased] Fixed entry describes the help.
---
 CHANGELOG.md                   |  7 +++++
 tests/test_hyetograph.m        | 50 ++++++++++++++++++++++++++++++++++
 toolbox/+baseflow/hyetograph.m | 16 ++++++++---
 3 files changed, 69 insertions(+), 4 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index aad1f3d..ae1a213 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -33,6 +33,13 @@ semantic versioning.
 
 ### Fixed
 
+- The `hyetograph` help names the tags the code sets. The figure has the
+  Name 'Hyetograph' and the Tag 'HyetographFigure'. The streamflow axes is
+  'HyetographAxis', and the series are 'StreamflowPlot' and
+  'PrecipitationPlot'. The help searched for 'StreamflowAxis' and
+  'PrecipitationAxis', which no object has. A search of all of H returns
+  the streamflow axes twice, so the examples search from the figure H(1).
+  The precipitation axes has no tag; `ancestor(H(4), 'axes')` finds it.
 - The late-time Rupp and Selker (2005) constant in `specialfunctions`
   raises the Beta function to the power n+3. At n = 0 it gives 4.805, the
   Brutsaert and Nieber (1977) constant 4.804; it gave 1.857. `globalfit`
diff --git a/tests/test_hyetograph.m b/tests/test_hyetograph.m
index 988d4d8..1e7952e 100644
--- a/tests/test_hyetograph.m
+++ b/tests/test_hyetograph.m
@@ -4,10 +4,21 @@
    % hyetograph resizes and retags its figure. Each case opens a visible
    % figure first and checks which figure hyetograph uses: a new figure
    % when no axes is passed, or the figure of the axes that is passed.
+   % The lookups in the hyetograph help must each return one handle: the
+   % element of H that the help names.
 
    properties (TestParameter)
       % Whether the call passes the axes of the figure opened first.
       passaxes = struct('newFigure', false, 'suppliedAxes', true)
+
+      % Each lookup in the hyetograph help: the property, its value, and
+      % the element of H that the lookup must return.
+      lookup = struct( ...
+         'figureName', {{'Name', 'Hyetograph', 1}}, ...
+         'figureTag', {{'Tag', 'HyetographFigure', 1}}, ...
+         'streamflowAxes', {{'Tag', 'HyetographAxis', 2}}, ...
+         'streamflowLine', {{'Tag', 'StreamflowPlot', 3}}, ...
+         'precipitationBars', {{'Tag', 'PrecipitationPlot', 4}})
    end
 
    properties
@@ -59,5 +70,44 @@ function test_figureChoice(testCase, passaxes)
             testCase.verifyEqual(get(userfig, 'Name'), userfigname)
          end
       end
+
+      function test_helpLookupFindsOneHandle(testCase, lookup)
+         % A lookup from the figure H(1) returns exactly the element of H
+         % that the help names, once.
+         [property, value, index] = lookup{:};
+         H = testCase.drawhyetograph();
+
+         returned = findobj(H(1), property, value);
+
+         testCase.verifyEqual(returned, H(index))
+      end
+
+      function test_precipitationAxesFromItsBars(testCase)
+         % The precipitation axes has no tag. The help finds it as the
+         % parent axes of the bars H(4): the reversed right-hand axes, not
+         % the streamflow axes H(2).
+         H = testCase.drawhyetograph();
+
+         returned = ancestor(H(4), 'axes');
+
+         testCase.verifyNotEqual(returned, H(2))
+         testCase.verifyEqual(get(returned, 'YDir'), 'reverse')
+      end
+   end
+
+   methods (Access = private)
+      function H = drawhyetograph(~)
+         %DRAWHYETOGRAPH Draw a 60-day hyetograph in a new figure.
+         %
+         %  H = drawhyetograph(testCase) returns the handles of
+         %  baseflow.hyetograph for a falling flow with one rain day.
+         ndays = 60;
+         time = transpose(datetime(2001, 1, 1:ndays));
+         flow = transpose(linspace(10, 1, ndays));
+         prec = zeros(ndays, 1);
+         prec(10) = 5;
+         H = baseflow.hyetograph(time, flow, prec, time(1) - 1, ...
+            time(end) + 1);
+      end
    end
 end
diff --git a/toolbox/+baseflow/hyetograph.m b/toolbox/+baseflow/hyetograph.m
index 628508a..f8cc83f 100755
--- a/toolbox/+baseflow/hyetograph.m
+++ b/toolbox/+baseflow/hyetograph.m
@@ -12,11 +12,19 @@
    % Example, how to later access the plot objects
    %  H = hyetograph(...);
    %
-   % Find specific handles using 'Tag' or 'Name'
+   % H holds the figure, the streamflow axes, the streamflow line, and the
+   % precipitation bars, in that order. Find specific handles using 'Tag'
+   % or 'Name'. Search from the figure H(1): a search of all of H returns
+   % the streamflow axes twice, as H(2) and as a child of H(1).
    %
-   % fig = findobj(H, 'Name', 'Hyetograph');
-   % ax_streamflow = findobj(H, 'Tag', 'StreamflowAxis');
-   % ax_precipitation = findobj(H, 'Tag', 'PrecipitationAxis');
+   % fig = findobj(H(1), 'Name', 'Hyetograph'); % Tag 'HyetographFigure'
+   % ax_streamflow = findobj(H(1), 'Tag', 'HyetographAxis');
+   % h_streamflow = findobj(H(1), 'Tag', 'StreamflowPlot');
+   % h_precipitation = findobj(H(1), 'Tag', 'PrecipitationPlot');
+   %
+   % The precipitation axes has no tag. Get it from its bars:
+   %
+   % ax_precipitation = ancestor(H(4), 'axes');
    %
    % See also:
 

From b483605697b52a0c8fb59061ae54fe69845512bf Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 18:32:17 -0700
Subject: [PATCH 19/28] fix(wrapevents): preserve annual leap-day alignment

Index each month and day assignment before removing February 29. Cover complete leap, non-leap and two-year calendars with datetime and datenum inputs, preserving timestamp, flow and rainfall alignment. Closes bfra-kwr.27.
---
 CHANGELOG.md                   |  3 +++
 tests/test_wrapevents.m        | 43 ++++++++++++++++++++++++++++++++++
 toolbox/+baseflow/wrapevents.m |  7 ++++--
 3 files changed, 51 insertions(+), 2 deletions(-)
 create mode 100644 tests/test_wrapevents.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index ae1a213..7294ee4 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -33,6 +33,9 @@ semantic versioning.
 
 ### Fixed
 
+- `wrapevents` removes February 29 before annual grouping and keeps the
+  remaining timestamps, flow and rainfall rows aligned. Leap-year input
+  previously failed the complete-year check.
 - The `hyetograph` help names the tags the code sets. The figure has the
   Name 'Hyetograph' and the Tag 'HyetographFigure'. The streamflow axes is
   'HyetographAxis', and the series are 'StreamflowPlot' and
diff --git a/tests/test_wrapevents.m b/tests/test_wrapevents.m
new file mode 100644
index 0000000..8b4b86f
--- /dev/null
+++ b/tests/test_wrapevents.m
@@ -0,0 +1,43 @@
+classdef test_wrapevents < matlab.unittest.TestCase
+   %TEST_WRAPEVENTS Check annual calendar and data alignment.
+
+   properties (TestParameter)
+      calendar = struct( ...
+         'leapYear', {[2000 2000]}, ...
+         'nonLeapYear', {[2001 2001]}, ...
+         'twoYears', {[2000 2001]})
+      timeType = {'datetime', 'datenum'}
+   end
+
+   methods (Test)
+
+      function test_leapDayAlignment(testCase, calendar, timeType)
+         % Distinct row values expose calendar/data shifts after removal.
+         T = transpose(datetime(calendar(1), 1, 1): ...
+            datetime(calendar(2), 12, 31));
+         row = transpose(1:numel(T));
+         Q = 2 + sin(row / 10);
+         R = row / 1000;
+
+         % Only February 29, 2000 is excluded from these calendars.
+         keep = T ~= datetime(2000, 2, 29);
+         T_expected = datenum(T(keep));
+         Q_expected = Q(keep);
+         R_expected = R(keep);
+
+         % Both public time representations must select the same rows.
+         if strcmp(timeType, 'datenum')
+            T = datenum(T);
+         end
+
+         % Rain carries row identities; it must not reject flow events.
+         returned = baseflow.wrapevents(T, Q, R, ...
+            'rmrain', false, 'pickevents', false, 'plotevents', false);
+
+         testCase.verifyEqual(returned.inputTime, T_expected)
+         testCase.verifyEqual(returned.inputFlow, Q_expected)
+         testCase.verifyEqual(returned.inputRain, R_expected)
+      end
+
+   end
+end
diff --git a/toolbox/+baseflow/wrapevents.m b/toolbox/+baseflow/wrapevents.m
index 221d0bf..32c744b 100644
--- a/toolbox/+baseflow/wrapevents.m
+++ b/toolbox/+baseflow/wrapevents.m
@@ -16,6 +16,9 @@
    % an adaptive sgolay filter that adjusts the filter parameters on an annual
    % (or shorter) basis.
    %
+   % February 29 is removed from T, Q, and R before grouping complete
+   % calendar years into 365-day columns. The remaining rows stay aligned.
+   %
    % Required inputs:
    %   T          =  nx1 array of dates
    %   Q          =  nxm array of daily flow in units m3/day, organized as
@@ -190,8 +193,8 @@
    monthnums = nan(size(T));
    daynums = nan(size(T));
    for n = 1:numel(T)
-      monthnums = month(T(n));
-      daynums = day(T(n));
+      monthnums(n) = month(T(n));
+      daynums(n) = day(T(n));
    end
    leapidx = monthnums==2 & daynums==29;
    T(leapidx) = [];

From 788c10f0c159562aac58d199f866702d88bb93fc Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 18:32:38 -0700
Subject: [PATCH 20/28] docs: correct conditional MPI installation route

Retain clone and Setup installation. Document the explicit repository URL and numeric-tag MPI route only after a release includes pathList.m and passes a clean-checkout install check. Add the plain toolbox path list; no existing release is install-qualified. BFRA consumer of matfunclib-juq.47, tracked by bfra-7gr.
---
 README.md  | 18 +++++++++++++++---
 pathList.m |  1 +
 2 files changed, 16 insertions(+), 3 deletions(-)
 create mode 100644 pathList.m

diff --git a/README.md b/README.md
index d52dfbd..2ac714c 100644
--- a/README.md
+++ b/README.md
@@ -56,8 +56,7 @@ and `tau` conventions.
 
 ## Install
 
-- Clone this repo or use [`mpm`](http://mobeets.github.io/mpm/) in your Matlab terminal:
-  - `mpm install baseflow`
+- Clone this repository.
 - cd into the `toolbox` directory.
 - Run `Setup.m`:
   - Type `msg = Setup('install')` at the command window then press enter.
@@ -68,6 +67,19 @@ and `tau` conventions.
   - To debug, try `runtests('tests', 'Debug', true)`.
 - In new Matlab sessions, cd to the toolbox directory and try `Setup('addpath')` or just `Setup` to add the toolbox to your search path (or manage the search path however you normally do).
 
+The optional [Matlab Package Installer (MPI)](https://github.com/mobeets/mpm)
+route uses this repository's explicit URL and a numeric release tag:
+
+```matlab
+mpi install -u https://github.com/mgcooper/baseflow.git -t <numeric-tag>
+```
+
+The selected release must include a root `pathList.m` containing `toolbox`.
+It must also pass an installation check from a clean checkout.
+No existing release has been qualified for this command.
+Use the clone route until a qualified release is published.
+Do not install this project by the bare name `baseflow`.
+
 For more options, see [Configuration](#configuration).  
 For Octave compatibility, see [Octave](#octave).  
 
@@ -234,4 +246,4 @@ cd baseflow
 Baseflow recession analysis is a set of methods in hydrologic science used to estimate aquifer properties from streamflow measurements. Properties that cannot be observed, such as hydraulic conductivity, are inferred from something that can be observed, such as streamflow. The underlying theory is based on solutions to the one-dimensional (lateral) groundwater flow equation ("Boussinesq equation"). 
 
 The theory makes various strong assumptions, including that the aquifer extent is much larger in the lateral direction than the vertical, and that capillarity can be ignored or parameterized by the concept of 'drainable porosity'. This reduces the three-dimensional Richard's equation to one dimension and eliminates unsaturated flow considerations. The theory has been validated with laboratory experiments and may work better than you expect. When applied to entire catchments ("watersheds"), the theory becomes an effective one, meaning the inferred properties are those that give the same solution to the Boussinesq equation that one would obtain for a single hillslope with those same properties and geometric similarity. 
--->
\ No newline at end of file
+-->
diff --git a/pathList.m b/pathList.m
new file mode 100644
index 0000000..da4f73c
--- /dev/null
+++ b/pathList.m
@@ -0,0 +1 @@
+toolbox

From 1a5264aa09a38dd12088909cb99723a51925b8c9 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 18:32:40 -0700
Subject: [PATCH 21/28] chore: ignore MATLAB Project UUID state

Append the missing direct Project UUID exclusion while preserving the existing ignore prefix and all tracked or nested Project membership files. No untracking or regeneration. BFRA consumer of matfunclib-juq.49, tracked by bfra-7gr.
---
 .gitignore | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.gitignore b/.gitignore
index 4c719e1..eac0085 100644
--- a/.gitignore
+++ b/.gitignore
@@ -624,3 +624,5 @@ TSWLatexianTemp*
 # project's state is machine-local, not source.
 **/resources/*
 !**/resources/project/
+
+**/resources/project/uuid-*.xml

From a849d3dba1f41a196c928aff0d6d711536494774 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 18:57:21 -0700
Subject: [PATCH 22/28] docs: refresh static function references and search

Rebuild only functions and docsearch from the reviewed source. Update hyetograph handle examples, the shared plotrain callers and wrapevents calendar help. Preserve all demo HTML, live scripts and numerical products. Closes bfra-kwr.26.1; release and demo-regeneration choices remain separate.
---
 .../helpsearch-v4_en/store/000000000002.zap   | Bin 1247418 -> 1244025 bytes
 toolbox/docs/html/m2html/+baseflow/graph.png  | Bin 280638 -> 280602 bytes
 .../html/m2html/+baseflow/hyetograph.html     | 352 +++++++-------
 .../docs/html/m2html/+baseflow/plotdqdt.html  | 376 +++++++--------
 .../html/m2html/+baseflow/pointcloudplot.html | 169 +++----
 .../html/m2html/+baseflow/wrapevents.html     | 428 +++++++++---------
 toolbox/docs/html/m2html/function_index.html  |   2 +-
 7 files changed, 644 insertions(+), 683 deletions(-)

diff --git a/toolbox/docs/html/helpsearch-v4_en/store/000000000002.zap b/toolbox/docs/html/helpsearch-v4_en/store/000000000002.zap
index 3343be4fc9f42f3f2eb36f992045542477acce62..429af590d9c258fd3e7e954a1f70b2f9ae7effec 100755
GIT binary patch
delta 703738
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diff --git a/toolbox/docs/html/m2html/+baseflow/hyetograph.html b/toolbox/docs/html/m2html/+baseflow/hyetograph.html
index e6e0562..6e9851d 100644
--- a/toolbox/docs/html/m2html/+baseflow/hyetograph.html
+++ b/toolbox/docs/html/m2html/+baseflow/hyetograph.html
@@ -40,11 +40,19 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
  Example, how to later access the plot objects
   H = hyetograph(...);
 
- Find specific handles using 'Tag' or 'Name'
+ H holds the figure, the streamflow axes, the streamflow line, and the
+ precipitation bars, in that order. Find specific handles using 'Tag'
+ or 'Name'. Search from the figure H(1): a search of all of H returns
+ the streamflow axes twice, as H(2) and as a child of H(1).
 
- fig = findobj(H, 'Name', 'Hyetograph');
- ax_streamflow = findobj(H, 'Tag', 'StreamflowAxis');
- ax_precipitation = findobj(H, 'Tag', 'PrecipitationAxis');
+ fig = findobj(H(1), 'Name', 'Hyetograph'); % Tag 'HyetographFigure'
+ ax_streamflow = findobj(H(1), 'Tag', 'HyetographAxis');
+ h_streamflow = findobj(H(1), 'Tag', 'StreamflowPlot');
+ h_precipitation = findobj(H(1), 'Tag', 'PrecipitationPlot');
+
+ The precipitation axes has no tag. Get it from its bars:
+
+ ax_precipitation = ancestor(H(4), 'axes');
 
  See also:</pre></div>
 
@@ -88,176 +96,184 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0012    <span class="comment">% Example, how to later access the plot objects</span>
 0013    <span class="comment">%  H = hyetograph(...);</span>
 0014    <span class="comment">%</span>
-0015    <span class="comment">% Find specific handles using 'Tag' or 'Name'</span>
-0016    <span class="comment">%</span>
-0017    <span class="comment">% fig = findobj(H, 'Name', 'Hyetograph');</span>
-0018    <span class="comment">% ax_streamflow = findobj(H, 'Tag', 'StreamflowAxis');</span>
-0019    <span class="comment">% ax_precipitation = findobj(H, 'Tag', 'PrecipitationAxis');</span>
-0020    <span class="comment">%</span>
-0021    <span class="comment">% See also:</span>
-0022 
-0023    <span class="comment">% if called with no input, open this file</span>
-0024    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>([mfilename(<span class="string">'fullpath'</span>),<span class="string">'.m'</span>]); <span class="keyword">return</span>; <span class="keyword">end</span>
-0025 
-0026    <span class="comment">% parse inputs</span>
-0027    [time, flow, prec, t1, t2, units, fig] = <a href="#_sub3" class="code" title="subfunction [time, flow, prec, t1, t2, units, fig] = parseinputs(funcname, ">parseinputs</a>(mfilename, time, flow, <span class="keyword">...</span>
-0028       prec, varargin{:});
-0029 
+0015    <span class="comment">% H holds the figure, the streamflow axes, the streamflow line, and the</span>
+0016    <span class="comment">% precipitation bars, in that order. Find specific handles using 'Tag'</span>
+0017    <span class="comment">% or 'Name'. Search from the figure H(1): a search of all of H returns</span>
+0018    <span class="comment">% the streamflow axes twice, as H(2) and as a child of H(1).</span>
+0019    <span class="comment">%</span>
+0020    <span class="comment">% fig = findobj(H(1), 'Name', 'Hyetograph'); % Tag 'HyetographFigure'</span>
+0021    <span class="comment">% ax_streamflow = findobj(H(1), 'Tag', 'HyetographAxis');</span>
+0022    <span class="comment">% h_streamflow = findobj(H(1), 'Tag', 'StreamflowPlot');</span>
+0023    <span class="comment">% h_precipitation = findobj(H(1), 'Tag', 'PrecipitationPlot');</span>
+0024    <span class="comment">%</span>
+0025    <span class="comment">% The precipitation axes has no tag. Get it from its bars:</span>
+0026    <span class="comment">%</span>
+0027    <span class="comment">% ax_precipitation = ancestor(H(4), 'axes');</span>
+0028    <span class="comment">%</span>
+0029    <span class="comment">% See also:</span>
 0030 
-0031    <span class="comment">% initialize container for output handles</span>
-0032    <span class="keyword">if</span> isoctave
-0033       H = zeros(4,1);
-0034    <span class="keyword">else</span>
-0035       H = gobjects(4,1); <span class="comment">% figure, ax1, plot1, plot2</span>
-0036    <span class="keyword">end</span>
+0031    <span class="comment">% if called with no input, open this file</span>
+0032    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>([mfilename(<span class="string">'fullpath'</span>),<span class="string">'.m'</span>]); <span class="keyword">return</span>; <span class="keyword">end</span>
+0033 
+0034    <span class="comment">% parse inputs</span>
+0035    [time, flow, prec, t1, t2, units, fig] = <a href="#_sub3" class="code" title="subfunction [time, flow, prec, t1, t2, units, fig] = parseinputs(funcname, ">parseinputs</a>(mfilename, time, flow, <span class="keyword">...</span>
+0036       prec, varargin{:});
 0037 
-0038    <span class="comment">% Set the figure handle tag</span>
-0039    set(fig, <span class="string">'Name'</span>, <span class="string">'Hyetograph'</span>, <span class="string">'Tag'</span>, <span class="string">'HyetographFigure'</span>);
-0040 
-0041    <span class="comment">% convert to columns</span>
-0042    time = time(:);
-0043    prec = prec(:);
-0044    flow = flow(:);
+0038 
+0039    <span class="comment">% initialize container for output handles</span>
+0040    <span class="keyword">if</span> isoctave
+0041       H = zeros(4,1);
+0042    <span class="keyword">else</span>
+0043       H = gobjects(4,1); <span class="comment">% figure, ax1, plot1, plot2</span>
+0044    <span class="keyword">end</span>
 0045 
-0046    <span class="comment">% convert to datetime</span>
-0047    <span class="keyword">if</span> ~isoctave
-0048       <span class="keyword">if</span> ~isdatetime(time); time = datetime(time, <span class="string">'ConvertFrom'</span>, <span class="string">'datenum'</span>); <span class="keyword">end</span>
-0049       <span class="keyword">if</span> ~isdatetime(t1); t1 = datetime(t1, <span class="string">'ConvertFrom'</span>, <span class="string">'datenum'</span>); <span class="keyword">end</span>
-0050       <span class="keyword">if</span> ~isdatetime(t2); t2 = datetime(t2, <span class="string">'ConvertFrom'</span>, <span class="string">'datenum'</span>); <span class="keyword">end</span>
-0051 
-0052       <span class="comment">% trim to t1,t2 timespan</span>
-0053       prec = prec(isbetween(time, t1, t2));
-0054       flow = flow(isbetween(time, t1, t2));
-0055       time = time(isbetween(time, t1, t2));
-0056    <span class="keyword">else</span>
-0057       prec = prec(t1 &lt; time &amp; time &lt; t2);
-0058       flow = flow(t1 &lt; time &amp; time &lt; t2);
-0059       time = time(t1 &lt; time &amp; time &lt; t2);
-0060    <span class="keyword">end</span>
-0061 
-0062    <span class="comment">% process units</span>
-0063    units = siUnitsToTex(units);
-0064 
-0065    <span class="comment">% get default colors</span>
-0066    colors = get(0, <span class="string">'defaultaxescolororder'</span>);
-0067 
-0068    <span class="comment">% Create plot</span>
-0069    [ax, h1, h2] = plotyy(time, flow, time, prec, @plot, @bar); <span class="comment">%#ok&lt;*PLOTYY&gt;</span>
-0070 
-0071    <span class="keyword">if</span> isoctave
-0072       datetick(ax(1),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keeplimits'</span>)
-0073       datetick(ax(2),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keeplimits'</span>)
-0074    <span class="keyword">else</span>
-0075       datetick(ax(1),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keepticks'</span>)
-0076       datetick(ax(2),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keepticks'</span>)
-0077    <span class="keyword">end</span>
+0046    <span class="comment">% Set the figure handle tag</span>
+0047    set(fig, <span class="string">'Name'</span>, <span class="string">'Hyetograph'</span>, <span class="string">'Tag'</span>, <span class="string">'HyetographFigure'</span>);
+0048 
+0049    <span class="comment">% convert to columns</span>
+0050    time = time(:);
+0051    prec = prec(:);
+0052    flow = flow(:);
+0053 
+0054    <span class="comment">% convert to datetime</span>
+0055    <span class="keyword">if</span> ~isoctave
+0056       <span class="keyword">if</span> ~isdatetime(time); time = datetime(time, <span class="string">'ConvertFrom'</span>, <span class="string">'datenum'</span>); <span class="keyword">end</span>
+0057       <span class="keyword">if</span> ~isdatetime(t1); t1 = datetime(t1, <span class="string">'ConvertFrom'</span>, <span class="string">'datenum'</span>); <span class="keyword">end</span>
+0058       <span class="keyword">if</span> ~isdatetime(t2); t2 = datetime(t2, <span class="string">'ConvertFrom'</span>, <span class="string">'datenum'</span>); <span class="keyword">end</span>
+0059 
+0060       <span class="comment">% trim to t1,t2 timespan</span>
+0061       prec = prec(isbetween(time, t1, t2));
+0062       flow = flow(isbetween(time, t1, t2));
+0063       time = time(isbetween(time, t1, t2));
+0064    <span class="keyword">else</span>
+0065       prec = prec(t1 &lt; time &amp; time &lt; t2);
+0066       flow = flow(t1 &lt; time &amp; time &lt; t2);
+0067       time = time(t1 &lt; time &amp; time &lt; t2);
+0068    <span class="keyword">end</span>
+0069 
+0070    <span class="comment">% process units</span>
+0071    units = siUnitsToTex(units);
+0072 
+0073    <span class="comment">% get default colors</span>
+0074    colors = get(0, <span class="string">'defaultaxescolororder'</span>);
+0075 
+0076    <span class="comment">% Create plot</span>
+0077    [ax, h1, h2] = plotyy(time, flow, time, prec, @plot, @bar); <span class="comment">%#ok&lt;*PLOTYY&gt;</span>
 0078 
-0079    <span class="comment">% Set line graph properties</span>
-0080    set(h1, <span class="string">'LineStyle'</span>, <span class="string">'-'</span>, <span class="string">'Marker'</span>, <span class="string">'o'</span>, <span class="string">'MarkerSize'</span>, 4, <span class="string">'MarkerFaceColor'</span>, <span class="keyword">...</span>
-0081       colors(1,:), <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Tag'</span>, <span class="string">'StreamflowPlot'</span>);
-0082    set(ax(1), <span class="string">'YColor'</span>, <span class="string">'k'</span>, <span class="string">'XMinorGrid'</span>, <span class="string">'on'</span>, <span class="string">'YMinorGrid'</span>, <span class="keyword">...</span>
-0083       <span class="string">'on'</span>, <span class="string">'FontSize'</span>, 12, <span class="string">'Tag'</span>, <span class="string">'HyetographAxis'</span>);
-0084    ylabel(ax(1), [<span class="string">'Streamflow ('</span> units{1} <span class="string">')'</span>], <span class="string">'Color'</span>, colors(1,:), <span class="keyword">...</span>
-0085       <span class="string">'FontSize'</span>, 12, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
-0086    grid(ax(1), <span class="string">'on'</span>);
-0087 
-0088    <span class="comment">% Set bar graph properties</span>
-0089    set(h2, <span class="string">'FaceColor'</span>, colors(2,:), <span class="string">'EdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Tag'</span>, <span class="string">'PrecipitationPlot'</span>);
-0090    set(ax(2), <span class="string">'XTickLabel'</span>, [], <span class="string">'xaxislocation'</span>, <span class="string">'top'</span>, <span class="string">'YDir'</span>, <span class="string">'reverse'</span>, <span class="keyword">...</span>
-0091       <span class="string">'FontSize'</span>, 12);
-0092    ylabel(ax(2), [<span class="string">'Precipitation ('</span> units{2} <span class="string">')'</span>], <span class="string">'Color'</span>, colors(2,:), <span class="keyword">...</span>
+0079    <span class="keyword">if</span> isoctave
+0080       datetick(ax(1),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keeplimits'</span>)
+0081       datetick(ax(2),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keeplimits'</span>)
+0082    <span class="keyword">else</span>
+0083       datetick(ax(1),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keepticks'</span>)
+0084       datetick(ax(2),<span class="string">'x'</span>,<span class="string">'mmm-yy'</span>,<span class="string">'keepticks'</span>)
+0085    <span class="keyword">end</span>
+0086 
+0087    <span class="comment">% Set line graph properties</span>
+0088    set(h1, <span class="string">'LineStyle'</span>, <span class="string">'-'</span>, <span class="string">'Marker'</span>, <span class="string">'o'</span>, <span class="string">'MarkerSize'</span>, 4, <span class="string">'MarkerFaceColor'</span>, <span class="keyword">...</span>
+0089       colors(1,:), <span class="string">'MarkerEdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Tag'</span>, <span class="string">'StreamflowPlot'</span>);
+0090    set(ax(1), <span class="string">'YColor'</span>, <span class="string">'k'</span>, <span class="string">'XMinorGrid'</span>, <span class="string">'on'</span>, <span class="string">'YMinorGrid'</span>, <span class="keyword">...</span>
+0091       <span class="string">'on'</span>, <span class="string">'FontSize'</span>, 12, <span class="string">'Tag'</span>, <span class="string">'HyetographAxis'</span>);
+0092    ylabel(ax(1), [<span class="string">'Streamflow ('</span> units{1} <span class="string">')'</span>], <span class="string">'Color'</span>, colors(1,:), <span class="keyword">...</span>
 0093       <span class="string">'FontSize'</span>, 12, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
-0094 
-0095    <span class="comment">% Reduce the width to make room for the ylabel on the right</span>
-0096    set(ax(1), <span class="string">'Position'</span>, [0.13 0.13 0.72 0.8]);
-0097    set(ax(2), <span class="string">'Position'</span>, [0.13 0.13 0.72 0.8]);
-0098 
-0099    set(ax(2), <span class="string">'XLim'</span>, get(ax(1), <span class="string">'XLim'</span>), <span class="string">'XTick'</span>, get(ax(1), <span class="string">'XTick'</span>));
-0100 
-0101    <span class="comment">% Package output</span>
-0102    H(1) = fig;
-0103    H(2) = ax(1);
-0104    H(3) = h1;
-0105    H(4) = h2;
-0106    
-0107    <span class="keyword">if</span> ~isoctave
-0108       <span class="comment">% Set up listener to trigger setlogticks if YScale is set to 'log'</span>
-0109       addlistener(ax(1), <span class="string">'YScale'</span>, <span class="string">'PostSet'</span>, @(s, e) <a href="#_sub1" class="code" title="subfunction triggerLogScale(~, ~, ax)">triggerLogScale</a>(s, e, ax(1)));
-0110       
-0111       <span class="comment">% Set up listener to trigger interpreter if labels are updated</span>
-0112       addlistener(ax(1), <span class="string">'YLabel'</span>, <span class="string">'PostSet'</span>, @(s, e) <a href="#_sub2" class="code" title="subfunction triggerInterpreter(~, ~, ax)">triggerInterpreter</a>(s, e, ax(1)));
-0113    
-0114       <span class="comment">% Set up listener to trigger interpreter if labels are updated so the</span>
-0115       <span class="comment">% interpreter is set to 'tex' if isoctave() returns true, and 'latex'</span>
-0116       <span class="comment">% otherwise.</span>
-0117       <span class="comment">% addlistener(ax(1), 'YScale', 'PostSet', @(s, e) triggerInterpreter(s, e, ax(1)));</span>
+0094    grid(ax(1), <span class="string">'on'</span>);
+0095 
+0096    <span class="comment">% Set bar graph properties</span>
+0097    set(h2, <span class="string">'FaceColor'</span>, colors(2,:), <span class="string">'EdgeColor'</span>, <span class="string">'none'</span>, <span class="string">'Tag'</span>, <span class="string">'PrecipitationPlot'</span>);
+0098    set(ax(2), <span class="string">'XTickLabel'</span>, [], <span class="string">'xaxislocation'</span>, <span class="string">'top'</span>, <span class="string">'YDir'</span>, <span class="string">'reverse'</span>, <span class="keyword">...</span>
+0099       <span class="string">'FontSize'</span>, 12);
+0100    ylabel(ax(2), [<span class="string">'Precipitation ('</span> units{2} <span class="string">')'</span>], <span class="string">'Color'</span>, colors(2,:), <span class="keyword">...</span>
+0101       <span class="string">'FontSize'</span>, 12, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
+0102 
+0103    <span class="comment">% Reduce the width to make room for the ylabel on the right</span>
+0104    set(ax(1), <span class="string">'Position'</span>, [0.13 0.13 0.72 0.8]);
+0105    set(ax(2), <span class="string">'Position'</span>, [0.13 0.13 0.72 0.8]);
+0106 
+0107    set(ax(2), <span class="string">'XLim'</span>, get(ax(1), <span class="string">'XLim'</span>), <span class="string">'XTick'</span>, get(ax(1), <span class="string">'XTick'</span>));
+0108 
+0109    <span class="comment">% Package output</span>
+0110    H(1) = fig;
+0111    H(2) = ax(1);
+0112    H(3) = h1;
+0113    H(4) = h2;
+0114    
+0115    <span class="keyword">if</span> ~isoctave
+0116       <span class="comment">% Set up listener to trigger setlogticks if YScale is set to 'log'</span>
+0117       addlistener(ax(1), <span class="string">'YScale'</span>, <span class="string">'PostSet'</span>, @(s, e) <a href="#_sub1" class="code" title="subfunction triggerLogScale(~, ~, ax)">triggerLogScale</a>(s, e, ax(1)));
 0118       
-0119       <span class="comment">% this is the example syntax from octave, not sure if its helpful</span>
-0120       <span class="comment">% addlistener(gcf, &quot;position&quot;, {@my_listener, &quot;my string&quot;})</span>
-0121    <span class="keyword">end</span>
-0122 <span class="keyword">end</span>
-0123 
-0124 <span class="comment">% Listener function to handle YScale change</span>
-0125 <a name="_sub1" href="#_subfunctions" class="code">function triggerLogScale(~, ~, ax)</a>
-0126   <span class="keyword">if</span> strcmp(get(ax, <span class="string">'YScale'</span>), <span class="string">'log'</span>)
-0127     setlogticks(ax, <span class="string">'axset'</span>, <span class="string">'y'</span>);
-0128   <span class="keyword">end</span>
-0129 <span class="keyword">end</span>
-0130 
-0131 <span class="comment">% Listener function to handle Interpreter change</span>
-0132 <a name="_sub2" href="#_subfunctions" class="code">function triggerInterpreter(~, ~, ax)</a>
-0133    labelHandle = get(ax, <span class="string">'YLabel'</span>);
-0134    interpreterSetting = get(labelHandle, <span class="string">'Interpreter'</span>);
-0135 
-0136    <span class="keyword">if</span> isoctave() &amp;&amp; strcmp(interpreterSetting, <span class="string">'latex'</span>)
-0137       set(labelHandle, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
-0138    <span class="keyword">end</span>
-0139 <span class="keyword">end</span>
-0140 
-0141 <span class="comment">%% Input Parser</span>
-0142 <a name="_sub3" href="#_subfunctions" class="code">function [time, flow, prec, t1, t2, units, fig] = parseinputs(funcname, </a><span class="keyword">...</span>
-0143       time, flow, prec, varargin)
-0144 
-0145    <span class="comment">% parse graphics handle if provided</span>
-0146    tf = cellfun(@(arg) isscalar(arg) &amp;&amp; ishandle(arg) &amp;&amp; <span class="keyword">...</span>
-0147       strcmp(<span class="string">'axes'</span>, get(arg,<span class="string">'type'</span>)), varargin);
+0119       <span class="comment">% Set up listener to trigger interpreter if labels are updated</span>
+0120       addlistener(ax(1), <span class="string">'YLabel'</span>, <span class="string">'PostSet'</span>, @(s, e) <a href="#_sub2" class="code" title="subfunction triggerInterpreter(~, ~, ax)">triggerInterpreter</a>(s, e, ax(1)));
+0121    
+0122       <span class="comment">% Set up listener to trigger interpreter if labels are updated so the</span>
+0123       <span class="comment">% interpreter is set to 'tex' if isoctave() returns true, and 'latex'</span>
+0124       <span class="comment">% otherwise.</span>
+0125       <span class="comment">% addlistener(ax(1), 'YScale', 'PostSet', @(s, e) triggerInterpreter(s, e, ax(1)));</span>
+0126       
+0127       <span class="comment">% this is the example syntax from octave, not sure if its helpful</span>
+0128       <span class="comment">% addlistener(gcf, &quot;position&quot;, {@my_listener, &quot;my string&quot;})</span>
+0129    <span class="keyword">end</span>
+0130 <span class="keyword">end</span>
+0131 
+0132 <span class="comment">% Listener function to handle YScale change</span>
+0133 <a name="_sub1" href="#_subfunctions" class="code">function triggerLogScale(~, ~, ax)</a>
+0134   <span class="keyword">if</span> strcmp(get(ax, <span class="string">'YScale'</span>), <span class="string">'log'</span>)
+0135     setlogticks(ax, <span class="string">'axset'</span>, <span class="string">'y'</span>);
+0136   <span class="keyword">end</span>
+0137 <span class="keyword">end</span>
+0138 
+0139 <span class="comment">% Listener function to handle Interpreter change</span>
+0140 <a name="_sub2" href="#_subfunctions" class="code">function triggerInterpreter(~, ~, ax)</a>
+0141    labelHandle = get(ax, <span class="string">'YLabel'</span>);
+0142    interpreterSetting = get(labelHandle, <span class="string">'Interpreter'</span>);
+0143 
+0144    <span class="keyword">if</span> isoctave() &amp;&amp; strcmp(interpreterSetting, <span class="string">'latex'</span>)
+0145       set(labelHandle, <span class="string">'Interpreter'</span>, <span class="string">'tex'</span>);
+0146    <span class="keyword">end</span>
+0147 <span class="keyword">end</span>
 0148 
-0149    <span class="keyword">if</span> any(tf)
-0150       ax = varargin{tf};
-0151       fig = get(ax, <span class="string">'Parent'</span>);
-0152       varargin = varargin(~tf);
-0153 
-0154       <span class="comment">% plotyy draws into the current axes, so make the supplied axes and</span>
-0155       <span class="comment">% its figure current.</span>
-0156       set(groot, <span class="string">'CurrentFigure'</span>, fig);
-0157       set(fig, <span class="string">'CurrentAxes'</span>, ax);
-0158    <span class="keyword">else</span>
-0159       <span class="comment">% Open a new figure. hyetograph resizes and retags its figure, so</span>
-0160       <span class="comment">% it must not take over a figure the user has open.</span>
-0161       fig = figure;
-0162    <span class="keyword">end</span>
-0163    
-0164    set(fig, <span class="string">'Position'</span>, [0 0 700 400]);
-0165 
-0166    parser = inputParser;
-0167    parser.FunctionName = funcname;
-0168    parser.addRequired(<span class="string">'time'</span>, @isdatelike);
-0169    parser.addRequired(<span class="string">'flow'</span>, @isnumericvector);
-0170    parser.addRequired(<span class="string">'prec'</span>, @isnumericvector);
-0171    parser.addOptional(<span class="string">'t1'</span>, NaT, @isdatelike);
-0172    parser.addOptional(<span class="string">'t2'</span>, NaT, @isdatelike);
-0173    parser.addParameter(<span class="string">'units'</span>, {<span class="string">'mm'</span>,<span class="string">'cm d-1'</span>}, @ischarlike);
-0174 
-0175    parser.parse(time,flow,prec,varargin{:});
-0176 
-0177    time = parser.Results.time;
-0178    flow = parser.Results.flow;
-0179    prec = parser.Results.prec;
-0180    t1 = parser.Results.t1;
-0181    t2 = parser.Results.t2;
-0182    units = parser.Results.units;
-0183    
-0184    time = todatenum(time);
-0185 <span class="keyword">end</span></pre></div>
+0149 <span class="comment">%% Input Parser</span>
+0150 <a name="_sub3" href="#_subfunctions" class="code">function [time, flow, prec, t1, t2, units, fig] = parseinputs(funcname, </a><span class="keyword">...</span>
+0151       time, flow, prec, varargin)
+0152 
+0153    <span class="comment">% parse graphics handle if provided</span>
+0154    tf = cellfun(@(arg) isscalar(arg) &amp;&amp; ishandle(arg) &amp;&amp; <span class="keyword">...</span>
+0155       strcmp(<span class="string">'axes'</span>, get(arg,<span class="string">'type'</span>)), varargin);
+0156 
+0157    <span class="keyword">if</span> any(tf)
+0158       ax = varargin{tf};
+0159       fig = get(ax, <span class="string">'Parent'</span>);
+0160       varargin = varargin(~tf);
+0161 
+0162       <span class="comment">% plotyy draws into the current axes, so make the supplied axes and</span>
+0163       <span class="comment">% its figure current.</span>
+0164       set(groot, <span class="string">'CurrentFigure'</span>, fig);
+0165       set(fig, <span class="string">'CurrentAxes'</span>, ax);
+0166    <span class="keyword">else</span>
+0167       <span class="comment">% Open a new figure. hyetograph resizes and retags its figure, so</span>
+0168       <span class="comment">% it must not take over a figure the user has open.</span>
+0169       fig = figure;
+0170    <span class="keyword">end</span>
+0171    
+0172    set(fig, <span class="string">'Position'</span>, [0 0 700 400]);
+0173 
+0174    parser = inputParser;
+0175    parser.FunctionName = funcname;
+0176    parser.addRequired(<span class="string">'time'</span>, @isdatelike);
+0177    parser.addRequired(<span class="string">'flow'</span>, @isnumericvector);
+0178    parser.addRequired(<span class="string">'prec'</span>, @isnumericvector);
+0179    parser.addOptional(<span class="string">'t1'</span>, NaT, @isdatelike);
+0180    parser.addOptional(<span class="string">'t2'</span>, NaT, @isdatelike);
+0181    parser.addParameter(<span class="string">'units'</span>, {<span class="string">'mm'</span>,<span class="string">'cm d-1'</span>}, @ischarlike);
+0182 
+0183    parser.parse(time,flow,prec,varargin{:});
+0184 
+0185    time = parser.Results.time;
+0186    flow = parser.Results.flow;
+0187    prec = parser.Results.prec;
+0188    t1 = parser.Results.t1;
+0189    t2 = parser.Results.t2;
+0190    units = parser.Results.units;
+0191    
+0192    time = todatenum(time);
+0193 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/+baseflow/plotdqdt.html b/toolbox/docs/html/m2html/+baseflow/plotdqdt.html
index e741779..3aea010 100644
--- a/toolbox/docs/html/m2html/+baseflow/plotdqdt.html
+++ b/toolbox/docs/html/m2html/+baseflow/plotdqdt.html
@@ -108,12 +108,11 @@ <h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border
 <li><a href="#_sub2" class="code">function Fits = pickFitter(Picks,fitmethod)</a></li>
 <li><a href="#_sub3" class="code">function h = plotFits(Fits,Picks,fitmethod,ax,plotfits,</a></li>
 <li><a href="#_sub4" class="code">function labelReflines(h, labelcolor, labelfontsize, labelstyle)</a></li>
-<li><a href="#_sub5" class="code">function h = plotrain(h,rain,x,y)</a></li>
-<li><a href="#_sub6" class="code">function addRotatedText(xtxt,ytxt,txt,slope,axpos)</a></li>
-<li><a href="#_sub7" class="code">function pickFig = eventPlotter(q,dqdt)</a></li>
-<li><a href="#_sub8" class="code">function [istart, istop] = detectTransition(q,dqdt,istart,istop)</a></li>
-<li><a href="#_sub9" class="code">function [hFits, Fits, Picks] = initOutput()</a></li>
-<li><a href="#_sub10" class="code">function [q, dqdt, fitmethod, pickmethod, plotfits, showfig, weights,</a></li></ul>
+<li><a href="#_sub5" class="code">function addRotatedText(xtxt,ytxt,txt,slope,axpos)</a></li>
+<li><a href="#_sub6" class="code">function pickFig = eventPlotter(q,dqdt)</a></li>
+<li><a href="#_sub7" class="code">function [istart, istop] = detectTransition(q,dqdt,istart,istop)</a></li>
+<li><a href="#_sub8" class="code">function [hFits, Fits, Picks] = initOutput()</a></li>
+<li><a href="#_sub9" class="code">function [q, dqdt, fitmethod, pickmethod, plotfits, showfig, weights,</a></li></ul>
 
 
 
@@ -196,7 +195,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0076       parseinputs(q, dqdt, mfilename, varargin{:});
 0077 
 0078    <span class="comment">% INIT OUTPUT</span>
-0079    [hFits, Fits, Picks] = <a href="#_sub9" class="code" title="subfunction [hFits, Fits, Picks] = initOutput()">initOutput</a>();
+0079    [hFits, Fits, Picks] = <a href="#_sub8" class="code" title="subfunction [hFits, Fits, Picks] = initOutput()">initOutput</a>();
 0080 
 0081    <span class="comment">% Prep fits</span>
 0082    [~, ~, logx, logy, weights, ok] = baseflow.prepfits(q, dqdt, <span class="keyword">...</span>
@@ -251,7 +250,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0131       <span class="keyword">case</span> <span class="string">'manual'</span>
 0132 
 0133          <span class="comment">% pause helps with buggy ginput</span>
-0134          pickFig     = <a href="#_sub7" class="code" title="subfunction pickFig = eventPlotter(q,dqdt)">eventPlotter</a>(q, dqdt); pause(0.5);
+0134          pickFig     = <a href="#_sub6" class="code" title="subfunction pickFig = eventPlotter(q,dqdt)">eventPlotter</a>(q, dqdt); pause(0.5);
 0135          pickedPts   = baseflow.deps.ginputc(); pause(0.5);
 0136          startPts    = pickedPts(1:2:end);
 0137          endPts      = pickedPts(2:2:end);
@@ -525,7 +524,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0405    <span class="comment">% because Octave installs no listener to do it.</span>
 0406    relayoutloglogtext(h.ax);
 0407 
-0408    h = <a href="#_sub5" class="code" title="subfunction h = plotrain(h,rain,x,y)">plotrain</a>(h, rain, x, y);
+0408    h.hrain = plotrain(h.ax, h.scatter, rain, x, y);
 0409 
 0410    <span class="comment">% I added this so rain is in the legend. plotrain returns the handles of</span>
 0411    <span class="comment">% the rain circles, or nan when no rain is plotted, so the guard tests</span>
@@ -583,205 +582,176 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0463 <span class="keyword">end</span>
 0464 
 0465 <span class="comment">%%</span>
-0466 <a name="_sub5" href="#_subfunctions" class="code">function h = plotrain(h,rain,x,y)</a>
+0466 <a name="_sub5" href="#_subfunctions" class="code">function addRotatedText(xtxt,ytxt,txt,slope,axpos) </a><span class="comment">%#ok&lt;*DEFNU&gt;</span>
 0467 
-0468    <span class="comment">% add rain. scale the circles such that 1 mm of rain equals the size of</span>
-0469    <span class="comment">% the plotted circles</span>
-0470    <span class="keyword">if</span> sum(rain)==0
-0471       h.hrain = nan;
-0472    <span class="keyword">else</span>
-0473 
-0474       <span class="comment">% scatter is producing pixelated symbols so I use plot instead</span>
-0475       <span class="comment">%sz    = h.scatter.SizeData + pi.*(rain(rain&gt;0)).^2;</span>
-0476       <span class="comment">%scatter(x(rain&gt;0),y(rain&gt;0),sz,'LineWidth',2)</span>
-0477 
-0478       <span class="comment">% this mimics the way scatter scales the circles. Read the size with</span>
-0479       <span class="comment">% get, because Octave returns a numeric handle, which takes no dot.</span>
-0480       s = get(h.scatter, <span class="string">'MarkerSize'</span>) + sqrt(pi.*(rain(rain&gt;0)).^2);
-0481       x = x(rain&gt;0);
-0482       y = y(rain&gt;0);
+0468    <span class="comment">% https://stackoverflow.com/questions/52928360/rotating-text-onto-a-line-on-a-log-scale-in-matplotlib</span>
+0469 
+0470    <span class="comment">% to add text, need the slope in figure space</span>
+0471    xlims = xlim;
+0472    ylims = ylim;
+0473    xfact = axpos(1)/(log(xlims(2))-log(xlims(1)));
+0474    yfact = axpos(2)/(log(ylims(2))-log(ylims(1)));   <span class="comment">% slope adjustment</span>
+0475    atext = slope*atand(yfact/xfact);           <span class="comment">% adjust angle</span>
+0476 
+0477    text( xtxt,ytxt,txt,                   <span class="keyword">...</span>
+0478       <span class="string">'HorizontalAlignment'</span>,<span class="string">'center'</span>,     <span class="keyword">...</span>
+0479       <span class="string">'VerticalAlignment'</span>, <span class="string">'bottom'</span>,      <span class="keyword">...</span>
+0480       <span class="string">'FontSize'</span>,12,                      <span class="keyword">...</span>
+0481       <span class="string">'rotation'</span>,atext);
+0482 <span class="keyword">end</span>
 0483 
-0484       hold(h.ax, <span class="string">'on'</span>);
-0485 
-0486       <span class="comment">% Count down so the handle array takes its size on the first pass.</span>
-0487       <span class="keyword">for</span> n = numel(s):-1:1
-0488          h.hrain(n) = plot(h.ax,x(n),y(n),<span class="string">'o'</span>,<span class="string">'MarkerSize'</span>,s(n), <span class="keyword">...</span>
-0489             <span class="string">'MarkerFaceColor'</span>,<span class="string">'none'</span>,<span class="string">'Color'</span>,<span class="string">'m'</span>,<span class="string">'LineWidth'</span>,1);
-0490       <span class="keyword">end</span>
-0491    <span class="keyword">end</span>
-0492 <span class="keyword">end</span>
-0493 
-0494 <span class="comment">%%</span>
-0495 <a name="_sub6" href="#_subfunctions" class="code">function addRotatedText(xtxt,ytxt,txt,slope,axpos) </a><span class="comment">%#ok&lt;*DEFNU&gt;</span>
-0496 
-0497    <span class="comment">% https://stackoverflow.com/questions/52928360/rotating-text-onto-a-line-on-a-log-scale-in-matplotlib</span>
+0484 <span class="comment">%% PLOT EVENT</span>
+0485 <a name="_sub6" href="#_subfunctions" class="code">function pickFig = eventPlotter(q,dqdt)</a>
+0486    pickFig = figure;
+0487    scatter(q,dqdt,36,[0,0.447,0.741],<span class="string">'filled'</span>);
+0488 <span class="keyword">end</span>
+0489 
+0490 <span class="comment">%% DETECT TRANSITION</span>
+0491 <a name="_sub7" href="#_subfunctions" class="code">function [istart, istop] = detectTransition(q,dqdt,istart,istop)</a>
+0492 
+0493    nPicks   = numel(istart);
+0494    rlengths = istop-istart+1;
+0495 
+0496    <span class="keyword">if</span> nPicks == 3
+0497       <span class="comment">% if rlengths(1)&gt;rlengths(2) &amp;&amp; rlengths(3)&gt;rlengths(2)</span>
 0498 
-0499    <span class="comment">% to add text, need the slope in figure space</span>
-0500    xlims = xlim;
-0501    ylims = ylim;
-0502    xfact = axpos(1)/(log(xlims(2))-log(xlims(1)));
-0503    yfact = axpos(2)/(log(ylims(2))-log(ylims(1)));   <span class="comment">% slope adjustment</span>
-0504    atext = slope*atand(yfact/xfact);           <span class="comment">% adjust angle</span>
+0499       q1    = q(istart(1):istop(1));
+0500       q2    = q(istart(2):istop(2));
+0501       q3    = q(istart(3):istop(3));
+0502       dq1   = dqdt(istart(1):istop(1));
+0503       dq2   = dqdt(istart(2):istop(2));
+0504       dq3   = dqdt(istart(3):istop(3));
 0505 
-0506    text( xtxt,ytxt,txt,                   <span class="keyword">...</span>
-0507       <span class="string">'HorizontalAlignment'</span>,<span class="string">'center'</span>,     <span class="keyword">...</span>
-0508       <span class="string">'VerticalAlignment'</span>, <span class="string">'bottom'</span>,      <span class="keyword">...</span>
-0509       <span class="string">'FontSize'</span>,12,                      <span class="keyword">...</span>
-0510       <span class="string">'rotation'</span>,atext);
-0511 <span class="keyword">end</span>
-0512 
-0513 <span class="comment">%% PLOT EVENT</span>
-0514 <a name="_sub7" href="#_subfunctions" class="code">function pickFig = eventPlotter(q,dqdt)</a>
-0515    pickFig = figure;
-0516    scatter(q,dqdt,36,[0,0.447,0.741],<span class="string">'filled'</span>);
-0517 <span class="keyword">end</span>
-0518 
-0519 <span class="comment">%% DETECT TRANSITION</span>
-0520 <a name="_sub8" href="#_subfunctions" class="code">function [istart, istop] = detectTransition(q,dqdt,istart,istop)</a>
-0521 
-0522    nPicks   = numel(istart);
-0523    rlengths = istop-istart+1;
-0524 
-0525    <span class="keyword">if</span> nPicks == 3
-0526       <span class="comment">% if rlengths(1)&gt;rlengths(2) &amp;&amp; rlengths(3)&gt;rlengths(2)</span>
-0527 
-0528       q1    = q(istart(1):istop(1));
-0529       q2    = q(istart(2):istop(2));
-0530       q3    = q(istart(3):istop(3));
-0531       dq1   = dqdt(istart(1):istop(1));
-0532       dq2   = dqdt(istart(2):istop(2));
-0533       dq3   = dqdt(istart(3):istop(3));
-0534 
-0535       <span class="comment">% Jul 2024 - commented out b/c &quot;wols&quot; is not a function in the toolbox.</span>
-0536       <span class="comment">% Not sure if this is supposed to be &quot;ols&quot; or a weighted version.</span>
-0537       <span class="comment">% ab1   = baseflow.wols(log(q1), log(-dq1));</span>
-0538       <span class="comment">% ab2   = baseflow.wols(log(q2), log(-dq2));</span>
-0539       <span class="comment">% ab3   = baseflow.wols(log(q3), log(-dq3));</span>
-0540 
-0541       <span class="comment">% three cases we want to :</span>
-0542       <span class="comment">% 1: a flat period between two recessions</span>
-0543       <span class="comment">% 2: a flat period followed by another one then a recession</span>
-0544       <span class="comment">% 2: a recession followed by two flat periods</span>
-0545 
-0546       <span class="comment">% Jul 2024 - commented out b/c &quot;wols&quot; is not a function in the toolbox.</span>
-0547       <span class="comment">% if ab1(2)&gt;1 &amp;&amp; ab2(2)&lt;1 &amp;&amp; ab3(2)&gt;1</span>
-0548       <span class="comment">%    istart(2)   = [];</span>
-0549       <span class="comment">%    istop(2)    = [];</span>
-0550       <span class="comment">% end</span>
-0551       <span class="comment">%end</span>
-0552    <span class="keyword">end</span>
-0553 <span class="keyword">end</span>
+0506       <span class="comment">% Jul 2024 - commented out b/c &quot;wols&quot; is not a function in the toolbox.</span>
+0507       <span class="comment">% Not sure if this is supposed to be &quot;ols&quot; or a weighted version.</span>
+0508       <span class="comment">% ab1   = baseflow.wols(log(q1), log(-dq1));</span>
+0509       <span class="comment">% ab2   = baseflow.wols(log(q2), log(-dq2));</span>
+0510       <span class="comment">% ab3   = baseflow.wols(log(q3), log(-dq3));</span>
+0511 
+0512       <span class="comment">% three cases we want to :</span>
+0513       <span class="comment">% 1: a flat period between two recessions</span>
+0514       <span class="comment">% 2: a flat period followed by another one then a recession</span>
+0515       <span class="comment">% 2: a recession followed by two flat periods</span>
+0516 
+0517       <span class="comment">% Jul 2024 - commented out b/c &quot;wols&quot; is not a function in the toolbox.</span>
+0518       <span class="comment">% if ab1(2)&gt;1 &amp;&amp; ab2(2)&lt;1 &amp;&amp; ab3(2)&gt;1</span>
+0519       <span class="comment">%    istart(2)   = [];</span>
+0520       <span class="comment">%    istop(2)    = [];</span>
+0521       <span class="comment">% end</span>
+0522       <span class="comment">%end</span>
+0523    <span class="keyword">end</span>
+0524 <span class="keyword">end</span>
+0525 
+0526 <span class="comment">%% Initialize output</span>
+0527 <a name="_sub8" href="#_subfunctions" class="code">function [hFits, Fits, Picks] = initOutput()</a>
+0528    Fits.h = nan; Fits.abols= nan; Fits.abnls = nan; Fits.abqtl = nan;
+0529    Picks.Q = nan; Picks.T = nan; Picks.dQdt = nan; Picks.R = nan;
+0530    Picks.nPicks = nan; hFits = nan;
+0531 <span class="keyword">end</span>
+0532 
+0533 <span class="comment">%% INPUT PARSER</span>
+0534 <a name="_sub9" href="#_subfunctions" class="code">function [q, dqdt, fitmethod, pickmethod, plotfits, showfig, weights, </a><span class="keyword">...</span>
+0535       rain, ax, blate, precision, timestep, eventID, labelplot, reflines, <span class="keyword">...</span>
+0536       axislimits, labelcolor, labelfontsize, labelstyle, fontsize, <span class="keyword">...</span>
+0537       legendfontsize] = parseinputs(<span class="keyword">...</span>
+0538       q, dqdt, mfilename, varargin)
+0539 
+0540    <span class="comment">% The reference lines plotFits draws. The names are the ones</span>
+0541    <span class="comment">% pointcloudplot uses, so one value means the same line in both</span>
+0542    <span class="comment">% functions, and the default draws the set this function always drew.</span>
+0543    defaultreflines = {<span class="string">'upperenvelope'</span>, <span class="string">'lowerenvelope'</span>, <span class="string">'late'</span>, <span class="string">'early'</span>};
+0544 
+0545    <span class="comment">% The axis-limit policies snaploglims accepts, with the default first.</span>
+0546    axislimitvalues = {<span class="string">'snap'</span>, <span class="string">'decades'</span>, <span class="string">'none'</span>};
+0547 
+0548    <span class="comment">% The label styles labelrefline draws, with the default first.</span>
+0549    labelstyles = {<span class="string">'arrow'</span>, <span class="string">'line'</span>};
+0550 
+0551    <span class="comment">% The MATLAB factory axes font size. A startup file can raise the axes</span>
+0552    <span class="comment">% font size, so the labels take their size from this value instead.</span>
+0553    defaultfontsize = 10;
 0554 
-0555 <span class="comment">%% Initialize output</span>
-0556 <a name="_sub9" href="#_subfunctions" class="code">function [hFits, Fits, Picks] = initOutput()</a>
-0557    Fits.h = nan; Fits.abols= nan; Fits.abnls = nan; Fits.abqtl = nan;
-0558    Picks.Q = nan; Picks.T = nan; Picks.dQdt = nan; Picks.R = nan;
-0559    Picks.nPicks = nan; hFits = nan;
-0560 <span class="keyword">end</span>
-0561 
-0562 <span class="comment">%% INPUT PARSER</span>
-0563 <a name="_sub10" href="#_subfunctions" class="code">function [q, dqdt, fitmethod, pickmethod, plotfits, showfig, weights, </a><span class="keyword">...</span>
-0564       rain, ax, blate, precision, timestep, eventID, labelplot, reflines, <span class="keyword">...</span>
-0565       axislimits, labelcolor, labelfontsize, labelstyle, fontsize, <span class="keyword">...</span>
-0566       legendfontsize] = parseinputs(<span class="keyword">...</span>
-0567       q, dqdt, mfilename, varargin)
-0568 
-0569    <span class="comment">% The reference lines plotFits draws. The names are the ones</span>
-0570    <span class="comment">% pointcloudplot uses, so one value means the same line in both</span>
-0571    <span class="comment">% functions, and the default draws the set this function always drew.</span>
-0572    defaultreflines = {<span class="string">'upperenvelope'</span>, <span class="string">'lowerenvelope'</span>, <span class="string">'late'</span>, <span class="string">'early'</span>};
-0573 
-0574    <span class="comment">% The axis-limit policies snaploglims accepts, with the default first.</span>
-0575    axislimitvalues = {<span class="string">'snap'</span>, <span class="string">'decades'</span>, <span class="string">'none'</span>};
-0576 
-0577    <span class="comment">% The label styles labelrefline draws, with the default first.</span>
-0578    labelstyles = {<span class="string">'arrow'</span>, <span class="string">'line'</span>};
-0579 
-0580    <span class="comment">% The MATLAB factory axes font size. A startup file can raise the axes</span>
-0581    <span class="comment">% font size, so the labels take their size from this value instead.</span>
-0582    defaultfontsize = 10;
-0583 
-0584    <span class="comment">% The axes font size this function sets, which pointcloudplot also uses.</span>
-0585    defaultaxesfontsize = 12;
+0555    <span class="comment">% The axes font size this function sets, which pointcloudplot also uses.</span>
+0556    defaultaxesfontsize = 12;
+0557 
+0558    parser = inputParser;
+0559    parser.FunctionName = [<span class="string">'baseflow.'</span> mfilename];
+0560    parser.CaseSensitive = false;
+0561    parser.addRequired(<span class="string">'q'</span>);
+0562    parser.addRequired(<span class="string">'dqdt'</span>);
+0563    parser.addParameter(<span class="string">'fitmethod'</span>, <span class="string">'nls'</span>);
+0564    parser.addParameter(<span class="string">'pickmethod'</span>, <span class="string">'none'</span>);
+0565    parser.addParameter(<span class="string">'plotfits'</span>, true);
+0566    parser.addParameter(<span class="string">'showfig'</span>, true, @islogical);
+0567    parser.addParameter(<span class="string">'weights'</span>, ones(size(q)));
+0568    parser.addParameter(<span class="string">'rain'</span>, zeros(size(q)));
+0569    parser.addParameter(<span class="string">'ax'</span>, <span class="string">'none'</span>);
+0570    parser.addParameter(<span class="string">'blate'</span>, 1.0);
+0571    parser.addParameter(<span class="string">'precision'</span>, 1);
+0572    parser.addParameter(<span class="string">'timestep'</span>, 1);
+0573    parser.addParameter(<span class="string">'eventID'</span>, <span class="string">''</span>, @ischar);
+0574    parser.addParameter(<span class="string">'labelplot'</span>, false, @islogical);
+0575    parser.addParameter(<span class="string">'reflines'</span>, defaultreflines, @iscell);
+0576    parser.addParameter(<span class="string">'axislimits'</span>, axislimitvalues{1}, <span class="keyword">...</span>
+0577       @(policy) any(validatestring(policy, axislimitvalues)));
+0578    parser.addParameter(<span class="string">'labelcolor'</span>, [0 0 0], @islabelcolor);
+0579    parser.addParameter(<span class="string">'labelfontsize'</span>, defaultfontsize, @(x) isnumericscalar(x) &amp;&amp; x &gt; 0);
+0580    parser.addParameter(<span class="string">'labelstyle'</span>, labelstyles{1}, <span class="keyword">...</span>
+0581       @(style) any(validatestring(style, labelstyles)));
+0582    parser.addParameter(<span class="string">'fontsize'</span>, defaultaxesfontsize, <span class="keyword">...</span>
+0583       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
+0584    parser.addParameter(<span class="string">'legendfontsize'</span>, defaultaxesfontsize, <span class="keyword">...</span>
+0585       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
 0586 
-0587    parser = inputParser;
-0588    parser.FunctionName = [<span class="string">'baseflow.'</span> mfilename];
-0589    parser.CaseSensitive = false;
-0590    parser.addRequired(<span class="string">'q'</span>);
-0591    parser.addRequired(<span class="string">'dqdt'</span>);
-0592    parser.addParameter(<span class="string">'fitmethod'</span>, <span class="string">'nls'</span>);
-0593    parser.addParameter(<span class="string">'pickmethod'</span>, <span class="string">'none'</span>);
-0594    parser.addParameter(<span class="string">'plotfits'</span>, true);
-0595    parser.addParameter(<span class="string">'showfig'</span>, true, @islogical);
-0596    parser.addParameter(<span class="string">'weights'</span>, ones(size(q)));
-0597    parser.addParameter(<span class="string">'rain'</span>, zeros(size(q)));
-0598    parser.addParameter(<span class="string">'ax'</span>, <span class="string">'none'</span>);
-0599    parser.addParameter(<span class="string">'blate'</span>, 1.0);
-0600    parser.addParameter(<span class="string">'precision'</span>, 1);
-0601    parser.addParameter(<span class="string">'timestep'</span>, 1);
-0602    parser.addParameter(<span class="string">'eventID'</span>, <span class="string">''</span>, @ischar);
-0603    parser.addParameter(<span class="string">'labelplot'</span>, false, @islogical);
-0604    parser.addParameter(<span class="string">'reflines'</span>, defaultreflines, @iscell);
-0605    parser.addParameter(<span class="string">'axislimits'</span>, axislimitvalues{1}, <span class="keyword">...</span>
-0606       @(policy) any(validatestring(policy, axislimitvalues)));
-0607    parser.addParameter(<span class="string">'labelcolor'</span>, [0 0 0], @islabelcolor);
-0608    parser.addParameter(<span class="string">'labelfontsize'</span>, defaultfontsize, @(x) isnumericscalar(x) &amp;&amp; x &gt; 0);
-0609    parser.addParameter(<span class="string">'labelstyle'</span>, labelstyles{1}, <span class="keyword">...</span>
-0610       @(style) any(validatestring(style, labelstyles)));
-0611    parser.addParameter(<span class="string">'fontsize'</span>, defaultaxesfontsize, <span class="keyword">...</span>
-0612       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
-0613    parser.addParameter(<span class="string">'legendfontsize'</span>, defaultaxesfontsize, <span class="keyword">...</span>
-0614       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
-0615 
-0616    parser.parse(q, dqdt, varargin{:});
-0617 
-0618    q = parser.Results.q;
-0619    ax = parser.Results.ax;
-0620    dqdt = parser.Results.dqdt;
-0621    rain = parser.Results.rain;
-0622    blate = parser.Results.blate;
-0623    showfig = parser.Results.showfig;
-0624    weights = parser.Results.weights;
-0625    eventID = parser.Results.eventID;
-0626    timestep = parser.Results.timestep;
-0627    plotfits = parser.Results.plotfits;
-0628    labelplot = parser.Results.labelplot;
-0629    precision = parser.Results.precision;
-0630    fitmethod = parser.Results.fitmethod;
-0631    pickmethod = parser.Results.pickmethod;
-0632    reflines = parser.Results.reflines;
-0633    labelcolor = parser.Results.labelcolor;
-0634 
-0635    <span class="comment">% islabelcolor accepts empty, which asks for the default label color.</span>
-0636    <span class="keyword">if</span> isempty(labelcolor)
-0637       labelcolor = [0 0 0];
-0638    <span class="keyword">end</span>
-0639    labelfontsize = parser.Results.labelfontsize;
-0640 
-0641    <span class="comment">% validatestring returns the member of the list, so a partial value such</span>
-0642    <span class="comment">% as 'dec' reaches snaploglims as 'decades'.</span>
-0643    axislimits = validatestring(parser.Results.axislimits, axislimitvalues);
-0644    labelstyle = validatestring(parser.Results.labelstyle, labelstyles);
-0645    fontsize = parser.Results.fontsize;
-0646    legendfontsize = parser.Results.legendfontsize;
-0647 
-0648    <span class="keyword">if</span> ~ischar(ax)
-0649       validateattributes(ax, {<span class="string">'matlab.graphics.axis.Axes'</span>},{<span class="string">'scalar'</span>}, mfilename);
-0650    <span class="keyword">end</span>
-0651 
-0652    validateattributes(q, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename, <span class="string">'q'</span>);
-0653    validateattributes(dqdt, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename, <span class="string">'dqdt'</span>);
-0654    validateattributes(rain, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename);
-0655    validateattributes(blate, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'scalar'</span>}, mfilename);
-0656    validateattributes(weights, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename);
-0657    validateattributes(timestep, {<span class="string">'numeric'</span>, <span class="string">'duration'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
-0658    validateattributes(plotfits, {<span class="string">'logical'</span>}, {<span class="string">'scalar'</span>}, mfilename);
-0659    validateattributes(precision, {<span class="string">'numeric'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
-0660    <span class="comment">% Require text, and check the value itself below. The Octave</span>
-0661    <span class="comment">% validateattributes has no 'scalartext' attribute, and plotdqdt runs</span>
-0662    <span class="comment">% on Octave through getdqdt with plotfits true.</span>
-0663    validateattributes(fitmethod, {<span class="string">'char'</span>, <span class="string">'string'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
-0664    validateattributes(pickmethod, {<span class="string">'char'</span>, <span class="string">'string'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
-0665 <span class="keyword">end</span></pre></div>
+0587    parser.parse(q, dqdt, varargin{:});
+0588 
+0589    q = parser.Results.q;
+0590    ax = parser.Results.ax;
+0591    dqdt = parser.Results.dqdt;
+0592    rain = parser.Results.rain;
+0593    blate = parser.Results.blate;
+0594    showfig = parser.Results.showfig;
+0595    weights = parser.Results.weights;
+0596    eventID = parser.Results.eventID;
+0597    timestep = parser.Results.timestep;
+0598    plotfits = parser.Results.plotfits;
+0599    labelplot = parser.Results.labelplot;
+0600    precision = parser.Results.precision;
+0601    fitmethod = parser.Results.fitmethod;
+0602    pickmethod = parser.Results.pickmethod;
+0603    reflines = parser.Results.reflines;
+0604    labelcolor = parser.Results.labelcolor;
+0605 
+0606    <span class="comment">% islabelcolor accepts empty, which asks for the default label color.</span>
+0607    <span class="keyword">if</span> isempty(labelcolor)
+0608       labelcolor = [0 0 0];
+0609    <span class="keyword">end</span>
+0610    labelfontsize = parser.Results.labelfontsize;
+0611 
+0612    <span class="comment">% validatestring returns the member of the list, so a partial value such</span>
+0613    <span class="comment">% as 'dec' reaches snaploglims as 'decades'.</span>
+0614    axislimits = validatestring(parser.Results.axislimits, axislimitvalues);
+0615    labelstyle = validatestring(parser.Results.labelstyle, labelstyles);
+0616    fontsize = parser.Results.fontsize;
+0617    legendfontsize = parser.Results.legendfontsize;
+0618 
+0619    <span class="keyword">if</span> ~ischar(ax)
+0620       validateattributes(ax, {<span class="string">'matlab.graphics.axis.Axes'</span>},{<span class="string">'scalar'</span>}, mfilename);
+0621    <span class="keyword">end</span>
+0622 
+0623    validateattributes(q, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename, <span class="string">'q'</span>);
+0624    validateattributes(dqdt, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename, <span class="string">'dqdt'</span>);
+0625    validateattributes(rain, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename);
+0626    validateattributes(blate, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'scalar'</span>}, mfilename);
+0627    validateattributes(weights, {<span class="string">'numeric'</span>}, {<span class="string">'real'</span>,<span class="string">'column'</span>}, mfilename);
+0628    validateattributes(timestep, {<span class="string">'numeric'</span>, <span class="string">'duration'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
+0629    validateattributes(plotfits, {<span class="string">'logical'</span>}, {<span class="string">'scalar'</span>}, mfilename);
+0630    validateattributes(precision, {<span class="string">'numeric'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
+0631    <span class="comment">% Require text, and check the value itself below. The Octave</span>
+0632    <span class="comment">% validateattributes has no 'scalartext' attribute, and plotdqdt runs</span>
+0633    <span class="comment">% on Octave through getdqdt with plotfits true.</span>
+0634    validateattributes(fitmethod, {<span class="string">'char'</span>, <span class="string">'string'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
+0635    validateattributes(pickmethod, {<span class="string">'char'</span>, <span class="string">'string'</span>}, {<span class="string">'nonempty'</span>}, mfilename);
+0636 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/pointcloudplot.html b/toolbox/docs/html/m2html/+baseflow/pointcloudplot.html
index aaa86fc..cacb5de 100644
--- a/toolbox/docs/html/m2html/+baseflow/pointcloudplot.html
+++ b/toolbox/docs/html/m2html/+baseflow/pointcloudplot.html
@@ -107,8 +107,7 @@ <h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^
 <h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../html_img/up.png"></a></h2>
 <ul style="list-style-image:url(../html_img/matlabicon.gif)">
 
-<li><a href="#_sub1" class="code">function hrain = plotrain(ax,h,rain,x,y)</a></li>
-<li><a href="#_sub2" class="code">function [q, dqdt, mask, reflines, reflabels, blate, userab, precision,</a></li></ul>
+<li><a href="#_sub1" class="code">function [q, dqdt, mask, reflines, reflabels, blate, userab, precision,</a></li></ul>
 
 
 
@@ -353,7 +352,7 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0238 
 0239    <span class="comment">% plot rain if provided</span>
 0240    <span class="keyword">if</span> all(~isnan(rain))
-0241       hrain = <a href="#_sub1" class="code" title="subfunction hrain = plotrain(ax,h,rain,x,y)">plotrain</a>(ax, h0, rain, q, -dqdt);
+0241       hrain = plotrain(ax, h0, rain, q, -dqdt);
 0242    <span class="keyword">else</span>
 0243       hrain = nan;
 0244    <span class="keyword">end</span>
@@ -458,103 +457,73 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0343 <span class="keyword">end</span>
 0344 
 0345 <span class="comment">%% LOCAL FUNCTIONS</span>
-0346 <a name="_sub1" href="#_subfunctions" class="code">function hrain = plotrain(ax,h,rain,x,y)</a>
-0347 
-0348    <span class="comment">% ax is the axis to plot into</span>
-0349    <span class="comment">% h is the handle of the plotted q/dqdt to get the marker size to scale</span>
-0350    <span class="comment">% the rain circles</span>
-0351    <span class="comment">% x and y are q -dqdt</span>
-0352 
-0353    <span class="comment">% add rain. scale the circles such that 1 mm of rain equals the size of</span>
-0354    <span class="comment">% the plotted circles</span>
-0355    <span class="keyword">if</span> sum(rain)==0
-0356       hrain = nan;
-0357    <span class="keyword">else</span>
-0358 
-0359       <span class="comment">% scatter is producing pixelated symbols so I use plot instead</span>
-0360       <span class="comment">% sz = h.scatter.SizeData + pi.*(rain(rain&gt;0)).^2;</span>
-0361       <span class="comment">% scatter(x(rain&gt;0),y(rain&gt;0),sz,'LineWidth',2)</span>
+0346 <span class="comment">%% INPUT PARSER</span>
+0347 <a name="_sub1" href="#_subfunctions" class="code">function [q, dqdt, mask, reflines, reflabels, blate, userab, precision, </a><span class="keyword">...</span>
+0348       timestep, addlegend, usertext, rain, axislimits, labelstyle, <span class="keyword">...</span>
+0349       labelcolor, labelfontsize, fontsize, legendfontsize, ax] = <span class="keyword">...</span>
+0350       parseinputs(q, dqdt, varargin)
+0351 
+0352    <span class="comment">% The axis-limit policies snaploglims accepts, with the default first.</span>
+0353    axislimitvalues = {<span class="string">'snap'</span>, <span class="string">'decades'</span>, <span class="string">'none'</span>};
+0354 
+0355    <span class="comment">% The label styles labelrefline draws, with the default first.</span>
+0356    labelstyles = {<span class="string">'arrow'</span>, <span class="string">'line'</span>};
+0357 
+0358    <span class="comment">% The MATLAB factory axes font size, which the reference-line labels</span>
+0359    <span class="comment">% take, and the axes font size this function sets.</span>
+0360    defaultlabelfontsize = 10;
+0361    defaultfontsize = 12;
 0362 
-0363       <span class="comment">% this mimics the way scatter scales the circles</span>
-0364       sz = get(h,<span class="string">'MarkerSize'</span>) + sqrt(pi.*(rain(rain&gt;0)).^2);
-0365       x = x(rain&gt;0);
-0366       y = y(rain&gt;0);
-0367 
-0368       hold(ax, <span class="string">'on'</span>);
-0369       <span class="keyword">for</span> n = numel(sz):-1:1
-0370          hrain(n) = plot(ax,x(n),y(n),<span class="string">'o'</span>,<span class="string">'MarkerSize'</span>,sz(n), <span class="keyword">...</span>
-0371             <span class="string">'MarkerFaceColor'</span>,<span class="string">'none'</span>,<span class="string">'Color'</span>,<span class="string">'m'</span>,<span class="string">'LineWidth'</span>,1);
-0372       <span class="keyword">end</span>
-0373    <span class="keyword">end</span>
-0374 <span class="keyword">end</span>
-0375 
-0376 <span class="comment">%% INPUT PARSER</span>
-0377 <a name="_sub2" href="#_subfunctions" class="code">function [q, dqdt, mask, reflines, reflabels, blate, userab, precision, </a><span class="keyword">...</span>
-0378       timestep, addlegend, usertext, rain, axislimits, labelstyle, <span class="keyword">...</span>
-0379       labelcolor, labelfontsize, fontsize, legendfontsize, ax] = <span class="keyword">...</span>
-0380       parseinputs(q, dqdt, varargin)
-0381 
-0382    <span class="comment">% The axis-limit policies snaploglims accepts, with the default first.</span>
-0383    axislimitvalues = {<span class="string">'snap'</span>, <span class="string">'decades'</span>, <span class="string">'none'</span>};
-0384 
-0385    <span class="comment">% The label styles labelrefline draws, with the default first.</span>
-0386    labelstyles = {<span class="string">'arrow'</span>, <span class="string">'line'</span>};
-0387 
-0388    <span class="comment">% The MATLAB factory axes font size, which the reference-line labels</span>
-0389    <span class="comment">% take, and the axes font size this function sets.</span>
-0390    defaultlabelfontsize = 10;
-0391    defaultfontsize = 12;
-0392 
-0393    parser = inputParser;
-0394    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
-0395    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
-0396    parser.addParameter(<span class="string">'mask'</span>, true(size(q)), @islogical);
-0397    parser.addParameter(<span class="string">'reflines'</span>, {<span class="string">'bestfit'</span>}, @iscell);
-0398    parser.addParameter(<span class="string">'reflabels'</span>, false, @islogical);
-0399    parser.addParameter(<span class="string">'blate'</span>, 1, @isnumeric);
-0400    parser.addParameter(<span class="string">'userab'</span>, [1 1], @isnumeric);
-0401    parser.addParameter(<span class="string">'precision'</span>, 1, @isnumeric);
-0402    parser.addParameter(<span class="string">'timestep'</span>, 1, @isnumeric);
-0403    parser.addParameter(<span class="string">'addlegend'</span>, true, @islogical);
-0404    parser.addParameter(<span class="string">'usertext'</span>, <span class="string">''</span>, @ischar);
-0405    parser.addParameter(<span class="string">'rain'</span>, nan, @isnumeric);
-0406    parser.addParameter(<span class="string">'axislimits'</span>, axislimitvalues{1}, <span class="keyword">...</span>
-0407       @(policy) any(validatestring(policy, axislimitvalues)));
-0408    parser.addParameter(<span class="string">'labelstyle'</span>, labelstyles{1}, <span class="keyword">...</span>
-0409       @(style) any(validatestring(style, labelstyles)));
-0410    parser.addParameter(<span class="string">'labelcolor'</span>, [], @islabelcolor);
-0411    parser.addParameter(<span class="string">'labelfontsize'</span>, defaultlabelfontsize, <span class="keyword">...</span>
-0412       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
-0413    parser.addParameter(<span class="string">'fontsize'</span>, defaultfontsize, <span class="keyword">...</span>
-0414       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
-0415    parser.addParameter(<span class="string">'legendfontsize'</span>, defaultfontsize, <span class="keyword">...</span>
-0416       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
-0417    parser.addParameter(<span class="string">'ax'</span>, emptyaxes(), @isaxis);
-0418    parser.FunctionName = <span class="string">'baseflow.pointcloudplot'</span>;
-0419    
-0420    parser.parse(q, dqdt, varargin{:});
-0421 
-0422    mask = parser.Results.mask;
-0423    reflines = parser.Results.reflines;
-0424    reflabels = parser.Results.reflabels;
-0425    blate = parser.Results.blate;
-0426    userab = parser.Results.userab;
-0427    precision = parser.Results.precision;
-0428    timestep = parser.Results.timestep;
-0429    addlegend = parser.Results.addlegend;
-0430    usertext = parser.Results.usertext;
-0431    rain = parser.Results.rain;
-0432    ax = parser.Results.ax;
-0433 
-0434    labelcolor = parser.Results.labelcolor;
-0435    labelfontsize = parser.Results.labelfontsize;
-0436    fontsize = parser.Results.fontsize;
-0437    legendfontsize = parser.Results.legendfontsize;
-0438 
-0439    <span class="comment">% validatestring returns the member of the list, so a partial value such</span>
-0440    <span class="comment">% as 'dec' reaches snaploglims as 'decades'.</span>
-0441    axislimits = validatestring(parser.Results.axislimits, axislimitvalues);
-0442    labelstyle = validatestring(parser.Results.labelstyle, labelstyles);
-0443 <span class="keyword">end</span></pre></div>
+0363    parser = inputParser;
+0364    parser.addRequired(<span class="string">'q'</span>, @isnumeric);
+0365    parser.addRequired(<span class="string">'dqdt'</span>, @isnumeric);
+0366    parser.addParameter(<span class="string">'mask'</span>, true(size(q)), @islogical);
+0367    parser.addParameter(<span class="string">'reflines'</span>, {<span class="string">'bestfit'</span>}, @iscell);
+0368    parser.addParameter(<span class="string">'reflabels'</span>, false, @islogical);
+0369    parser.addParameter(<span class="string">'blate'</span>, 1, @isnumeric);
+0370    parser.addParameter(<span class="string">'userab'</span>, [1 1], @isnumeric);
+0371    parser.addParameter(<span class="string">'precision'</span>, 1, @isnumeric);
+0372    parser.addParameter(<span class="string">'timestep'</span>, 1, @isnumeric);
+0373    parser.addParameter(<span class="string">'addlegend'</span>, true, @islogical);
+0374    parser.addParameter(<span class="string">'usertext'</span>, <span class="string">''</span>, @ischar);
+0375    parser.addParameter(<span class="string">'rain'</span>, nan, @isnumeric);
+0376    parser.addParameter(<span class="string">'axislimits'</span>, axislimitvalues{1}, <span class="keyword">...</span>
+0377       @(policy) any(validatestring(policy, axislimitvalues)));
+0378    parser.addParameter(<span class="string">'labelstyle'</span>, labelstyles{1}, <span class="keyword">...</span>
+0379       @(style) any(validatestring(style, labelstyles)));
+0380    parser.addParameter(<span class="string">'labelcolor'</span>, [], @islabelcolor);
+0381    parser.addParameter(<span class="string">'labelfontsize'</span>, defaultlabelfontsize, <span class="keyword">...</span>
+0382       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
+0383    parser.addParameter(<span class="string">'fontsize'</span>, defaultfontsize, <span class="keyword">...</span>
+0384       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
+0385    parser.addParameter(<span class="string">'legendfontsize'</span>, defaultfontsize, <span class="keyword">...</span>
+0386       @(value) isnumericscalar(value) &amp;&amp; value &gt; 0);
+0387    parser.addParameter(<span class="string">'ax'</span>, emptyaxes(), @isaxis);
+0388    parser.FunctionName = <span class="string">'baseflow.pointcloudplot'</span>;
+0389    
+0390    parser.parse(q, dqdt, varargin{:});
+0391 
+0392    mask = parser.Results.mask;
+0393    reflines = parser.Results.reflines;
+0394    reflabels = parser.Results.reflabels;
+0395    blate = parser.Results.blate;
+0396    userab = parser.Results.userab;
+0397    precision = parser.Results.precision;
+0398    timestep = parser.Results.timestep;
+0399    addlegend = parser.Results.addlegend;
+0400    usertext = parser.Results.usertext;
+0401    rain = parser.Results.rain;
+0402    ax = parser.Results.ax;
+0403 
+0404    labelcolor = parser.Results.labelcolor;
+0405    labelfontsize = parser.Results.labelfontsize;
+0406    fontsize = parser.Results.fontsize;
+0407    legendfontsize = parser.Results.legendfontsize;
+0408 
+0409    <span class="comment">% validatestring returns the member of the list, so a partial value such</span>
+0410    <span class="comment">% as 'dec' reaches snaploglims as 'decades'.</span>
+0411    axislimits = validatestring(parser.Results.axislimits, axislimitvalues);
+0412    labelstyle = validatestring(parser.Results.labelstyle, labelstyles);
+0413 <span class="keyword">end</span></pre></div>
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diff --git a/toolbox/docs/html/m2html/+baseflow/wrapevents.html b/toolbox/docs/html/m2html/+baseflow/wrapevents.html
index 9dee975..b211652 100644
--- a/toolbox/docs/html/m2html/+baseflow/wrapevents.html
+++ b/toolbox/docs/html/m2html/+baseflow/wrapevents.html
@@ -44,6 +44,9 @@ <h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="
  an adaptive sgolay filter that adjusts the filter parameters on an annual
  (or shorter) basis.
 
+ February 29 is removed from T, Q, and R before grouping complete
+ calendar years into 365-day columns. The remaining rows stay aligned.
+
  Required inputs:
    T          =  nx1 array of dates
    Q          =  nxm array of daily flow in units m3/day, organized as
@@ -125,228 +128,231 @@ <h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" sr
 0016    <span class="comment">% an adaptive sgolay filter that adjusts the filter parameters on an annual</span>
 0017    <span class="comment">% (or shorter) basis.</span>
 0018    <span class="comment">%</span>
-0019    <span class="comment">% Required inputs:</span>
-0020    <span class="comment">%   T          =  nx1 array of dates</span>
-0021    <span class="comment">%   Q          =  nxm array of daily flow in units m3/day, organized as</span>
-0022    <span class="comment">%                 calendar years, meaning n/365 = # of years</span>
-0023    <span class="comment">%   R          =  nxm array of daily rainfall in (mm/day?)</span>
-0024    <span class="comment">%</span>
-0025    <span class="comment">% Optional name-value inputs:</span>
-0026    <span class="comment">%  qmin        =  minimum flow value, below which values are set nan</span>
-0027    <span class="comment">%  nmin        =  minimum event length</span>
-0028    <span class="comment">%  fmax        =  maximum # of missing values gap-filled</span>
-0029    <span class="comment">%  rmax        =  maximum run of sequential constant values</span>
-0030    <span class="comment">%  rmin        =  minimum rainfall required to censor flow</span>
-0031    <span class="comment">%  rmconvex    =  remove convex derivatives</span>
-0032    <span class="comment">%  rmnochange  =  remove consecutive constant derivates</span>
-0033    <span class="comment">%  rmrain      =  remove rainfall</span>
-0034    <span class="comment">%</span>
-0035    <span class="comment">%  opts        =  structure containing the fields listed above, in lieu of</span>
-0036    <span class="comment">%                 entering them individually</span>
+0019    <span class="comment">% February 29 is removed from T, Q, and R before grouping complete</span>
+0020    <span class="comment">% calendar years into 365-day columns. The remaining rows stay aligned.</span>
+0021    <span class="comment">%</span>
+0022    <span class="comment">% Required inputs:</span>
+0023    <span class="comment">%   T          =  nx1 array of dates</span>
+0024    <span class="comment">%   Q          =  nxm array of daily flow in units m3/day, organized as</span>
+0025    <span class="comment">%                 calendar years, meaning n/365 = # of years</span>
+0026    <span class="comment">%   R          =  nxm array of daily rainfall in (mm/day?)</span>
+0027    <span class="comment">%</span>
+0028    <span class="comment">% Optional name-value inputs:</span>
+0029    <span class="comment">%  qmin        =  minimum flow value, below which values are set nan</span>
+0030    <span class="comment">%  nmin        =  minimum event length</span>
+0031    <span class="comment">%  fmax        =  maximum # of missing values gap-filled</span>
+0032    <span class="comment">%  rmax        =  maximum run of sequential constant values</span>
+0033    <span class="comment">%  rmin        =  minimum rainfall required to censor flow</span>
+0034    <span class="comment">%  rmconvex    =  remove convex derivatives</span>
+0035    <span class="comment">%  rmnochange  =  remove consecutive constant derivates</span>
+0036    <span class="comment">%  rmrain      =  remove rainfall</span>
 0037    <span class="comment">%</span>
-0038    <span class="comment">% Each option default is the baseflow.setopts('getevents') value.</span>
-0039    <span class="comment">%</span>
-0040    <span class="comment">% Note: flow comes in as m3/day/day</span>
-0041    <span class="comment">%</span>
-0042    <span class="comment">% Example</span>
-0043    <span class="comment">%</span>
-0044    <span class="comment">%  Detect recession events one calendar year at a time:</span>
-0045    <span class="comment">%</span>
-0046    <span class="comment">%     [T, Q, R] = baseflow.loadExampleData();</span>
-0047    <span class="comment">%     opts = baseflow.setopts('getevents', 'asannual', true);</span>
-0048    <span class="comment">%     [Events, Info] = baseflow.wrapevents(T, Q, R, opts);</span>
-0049    <span class="comment">%     fprintf('Detected %d events\n', max(Events.eventTags))</span>
-0050    <span class="comment">%</span>
-0051    <span class="comment">% See also: getevents</span>
-0052    <span class="comment">%</span>
+0038    <span class="comment">%  opts        =  structure containing the fields listed above, in lieu of</span>
+0039    <span class="comment">%                 entering them individually</span>
+0040    <span class="comment">%</span>
+0041    <span class="comment">% Each option default is the baseflow.setopts('getevents') value.</span>
+0042    <span class="comment">%</span>
+0043    <span class="comment">% Note: flow comes in as m3/day/day</span>
+0044    <span class="comment">%</span>
+0045    <span class="comment">% Example</span>
+0046    <span class="comment">%</span>
+0047    <span class="comment">%  Detect recession events one calendar year at a time:</span>
+0048    <span class="comment">%</span>
+0049    <span class="comment">%     [T, Q, R] = baseflow.loadExampleData();</span>
+0050    <span class="comment">%     opts = baseflow.setopts('getevents', 'asannual', true);</span>
+0051    <span class="comment">%     [Events, Info] = baseflow.wrapevents(T, Q, R, opts);</span>
+0052    <span class="comment">%     fprintf('Detected %d events\n', max(Events.eventTags))</span>
 0053    <span class="comment">%</span>
-0054    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
-0055 
-0056    <span class="comment">% if called with no input, open this file</span>
-0057    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
+0054    <span class="comment">% See also: getevents</span>
+0055    <span class="comment">%</span>
+0056    <span class="comment">%</span>
+0057    <span class="comment">% Matt Cooper, 04-Nov-2022, https://github.com/mgcooper</span>
 0058 
-0059    <span class="comment">% PARSE INPUTS</span>
-0060    [T, Q, R, opts] = <a href="#_sub3" class="code" title="subfunction [T, Q, R, opts] = parseinputs(T, Q, R, mfilename, varargin)">parseinputs</a>(T, Q, R, mfilename, varargin{:});
+0059    <span class="comment">% if called with no input, open this file</span>
+0060    <span class="keyword">if</span> nargin == 0; <a href="open.html" class="code" title="function open(varargin)">open</a>(mfilename(<span class="string">'fullpath'</span>)); <span class="keyword">return</span>; <span class="keyword">end</span>
 0061 
-0062    <span class="comment">% Do some input checks to confirm the data is compatible with annual option</span>
-0063    [T, Q, R, numyears] = <a href="#_sub2" class="code" title="subfunction [T,Q,R,numyears] = prepinput(T,Q,R)">prepinput</a>(T, Q, R);
+0062    <span class="comment">% PARSE INPUTS</span>
+0063    [T, Q, R, opts] = <a href="#_sub3" class="code" title="subfunction [T, Q, R, opts] = parseinputs(T, Q, R, mfilename, varargin)">parseinputs</a>(T, Q, R, mfilename, varargin{:});
 0064 
-0065    <span class="comment">% Save the input data</span>
-0066    EventsData.inputTime = T;
-0067    EventsData.inputFlow = Q;
-0068    EventsData.inputRain = R;
-0069 
-0070    <span class="comment">% Compute the number of timesteps per year</span>
-0071    numsteps = size(Q,1)/numyears;
+0065    <span class="comment">% Do some input checks to confirm the data is compatible with annual option</span>
+0066    [T, Q, R, numyears] = <a href="#_sub2" class="code" title="subfunction [T,Q,R,numyears] = prepinput(T,Q,R)">prepinput</a>(T, Q, R);
+0067 
+0068    <span class="comment">% Save the input data</span>
+0069    EventsData.inputTime = T;
+0070    EventsData.inputFlow = Q;
+0071    EventsData.inputRain = R;
 0072 
-0073    <span class="comment">% Reshape the input lists to matrices</span>
-0074    <span class="keyword">if</span> mod(numyears,1) == 0
-0075       Qmat = reshape(Q,numsteps,numyears);    <span class="comment">% flow, one column each year</span>
-0076       Rmat = reshape(R,numsteps,numyears);    <span class="comment">% rain, one column each year</span>
-0077       Tmat = reshape(T,numsteps,numyears);    <span class="comment">% calendar, one column each year</span>
-0078    <span class="keyword">else</span>
-0079       <span class="comment">% Assume data is already in matrix form</span>
-0080       Qmat = Q;
-0081       Rmat = R;
-0082       Tmat = T;
-0083    <span class="keyword">end</span>
-0084 
-0085    <span class="comment">% Initialize output structure and output arrays</span>
-0086    Qsave = nan(size(Qmat));
-0087    Rsave = nan(size(Qmat));
-0088    tsave = nan(size(Qmat));
-0089    Etags = nan(size(Qmat));
-0090    Count = 0; <span class="comment">% initialize event counter</span>
-0091 
-0092    <span class="comment">% Compute the recession constants</span>
-0093    <span class="keyword">for</span> thisYear = 1:numyears
+0073    <span class="comment">% Compute the number of timesteps per year</span>
+0074    numsteps = size(Q,1)/numyears;
+0075 
+0076    <span class="comment">% Reshape the input lists to matrices</span>
+0077    <span class="keyword">if</span> mod(numyears,1) == 0
+0078       Qmat = reshape(Q,numsteps,numyears);    <span class="comment">% flow, one column each year</span>
+0079       Rmat = reshape(R,numsteps,numyears);    <span class="comment">% rain, one column each year</span>
+0080       Tmat = reshape(T,numsteps,numyears);    <span class="comment">% calendar, one column each year</span>
+0081    <span class="keyword">else</span>
+0082       <span class="comment">% Assume data is already in matrix form</span>
+0083       Qmat = Q;
+0084       Rmat = R;
+0085       Tmat = T;
+0086    <span class="keyword">end</span>
+0087 
+0088    <span class="comment">% Initialize output structure and output arrays</span>
+0089    Qsave = nan(size(Qmat));
+0090    Rsave = nan(size(Qmat));
+0091    tsave = nan(size(Qmat));
+0092    Etags = nan(size(Qmat));
+0093    Count = 0; <span class="comment">% initialize event counter</span>
 0094 
-0095       <span class="keyword">if</span> all(isnan(Qmat(:,thisYear)))
-0096          <span class="keyword">continue</span>;
-0097       <span class="keyword">end</span>
-0098 
-0099       thisYearTime = Tmat(:,thisYear);
-0100       thisYearFlow = Qmat(:,thisYear);
-0101       thisYearRain = Rmat(:,thisYear);
-0102 
-0103       <span class="comment">% Detect events for this year</span>
-0104       [thisYearEvents,thisYearInfo] = baseflow.getevents( <span class="keyword">...</span>
-0105          thisYearTime, thisYearFlow, thisYearRain, opts);
-0106 
-0107       <span class="comment">% For each event, compute q, dqdt and fit a,b</span>
-0108       numEvents = numel(thisYearInfo.istart);
-0109       <span class="keyword">for</span> thisEvent = 1:numEvents
-0110 
-0111          <span class="comment">% Get the start/end index on the annual calendar</span>
-0112          si = thisYearInfo.istart(thisEvent);
-0113          ei = thisYearInfo.istop(thisEvent);
-0114 
-0115          eventQ = thisYearEvents.eventFlow(si:ei);
-0116          eventT = thisYearEvents.eventTime(si:ei);
-0117          eventR = thisYearEvents.eventRain(si:ei);
-0118 
-0119          <span class="comment">% If no flow was returned, continue</span>
-0120          <span class="keyword">if</span> all(isnan(eventQ)); <span class="keyword">continue</span>; <span class="keyword">else</span>
-0121             Count = Count+1;
-0122          <span class="keyword">end</span>
-0123 
-0124          <span class="comment">% Collect all data for the point-cloud</span>
-0125          Qsave( si:ei,thisYear ) = eventQ;
-0126          Rsave( si:ei,thisYear ) = eventR;
-0127          tsave( si:ei,thisYear ) = eventT;
-0128          Etags( si:ei,thisYear ) = Count;
-0129       <span class="keyword">end</span>
-0130 
-0131       <span class="comment">% pause to look at the fits</span>
-0132       <span class="keyword">if</span> opts.plotevents == true
-0133          hEvents = baseflow.eventplotter(thisYearTime, thisYearFlow, <span class="keyword">...</span>
-0134             thisYearRain, thisYearInfo, <span class="string">'plotevents'</span>, true, <span class="keyword">...</span>
-0135             <span class="string">'eventTags'</span>, 1);
-0136 
-0137          set(hEvents.ax(1), <span class="string">'YScale'</span>, <span class="string">'log'</span>)
-0138 
-0139          sprintf(<span class="string">'all events fitted for %d'</span>,thisYear); pause; close all
-0140       <span class="keyword">end</span>
+0095    <span class="comment">% Compute the recession constants</span>
+0096    <span class="keyword">for</span> thisYear = 1:numyears
+0097 
+0098       <span class="keyword">if</span> all(isnan(Qmat(:,thisYear)))
+0099          <span class="keyword">continue</span>;
+0100       <span class="keyword">end</span>
+0101 
+0102       thisYearTime = Tmat(:,thisYear);
+0103       thisYearFlow = Qmat(:,thisYear);
+0104       thisYearRain = Rmat(:,thisYear);
+0105 
+0106       <span class="comment">% Detect events for this year</span>
+0107       [thisYearEvents,thisYearInfo] = baseflow.getevents( <span class="keyword">...</span>
+0108          thisYearTime, thisYearFlow, thisYearRain, opts);
+0109 
+0110       <span class="comment">% For each event, compute q, dqdt and fit a,b</span>
+0111       numEvents = numel(thisYearInfo.istart);
+0112       <span class="keyword">for</span> thisEvent = 1:numEvents
+0113 
+0114          <span class="comment">% Get the start/end index on the annual calendar</span>
+0115          si = thisYearInfo.istart(thisEvent);
+0116          ei = thisYearInfo.istop(thisEvent);
+0117 
+0118          eventQ = thisYearEvents.eventFlow(si:ei);
+0119          eventT = thisYearEvents.eventTime(si:ei);
+0120          eventR = thisYearEvents.eventRain(si:ei);
+0121 
+0122          <span class="comment">% If no flow was returned, continue</span>
+0123          <span class="keyword">if</span> all(isnan(eventQ)); <span class="keyword">continue</span>; <span class="keyword">else</span>
+0124             Count = Count+1;
+0125          <span class="keyword">end</span>
+0126 
+0127          <span class="comment">% Collect all data for the point-cloud</span>
+0128          Qsave( si:ei,thisYear ) = eventQ;
+0129          Rsave( si:ei,thisYear ) = eventR;
+0130          tsave( si:ei,thisYear ) = eventT;
+0131          Etags( si:ei,thisYear ) = Count;
+0132       <span class="keyword">end</span>
+0133 
+0134       <span class="comment">% pause to look at the fits</span>
+0135       <span class="keyword">if</span> opts.plotevents == true
+0136          hEvents = baseflow.eventplotter(thisYearTime, thisYearFlow, <span class="keyword">...</span>
+0137             thisYearRain, thisYearInfo, <span class="string">'plotevents'</span>, true, <span class="keyword">...</span>
+0138             <span class="string">'eventTags'</span>, 1);
+0139 
+0140          set(hEvents.ax(1), <span class="string">'YScale'</span>, <span class="string">'log'</span>)
 0141 
-0142       <span class="comment">% Concatenate Info</span>
-0143       <span class="keyword">if</span> thisYear == 1
-0144          Info = thisYearInfo;
-0145       <span class="keyword">else</span>
-0146          thisYearInfo = <a href="#_sub1" class="code" title="subfunction thisYearInfo = updateinfo(thisYearInfo, thisYear)">updateinfo</a>(thisYearInfo, thisYear);
-0147          Info = catstructfields(1, Info, thisYearInfo);
-0148       <span class="keyword">end</span>
-0149    <span class="keyword">end</span>
-0150 
-0151    [ndays,numyears] = size(Qsave);
-0152    EventsData.eventTime = reshape(tsave, ndays*numyears, 1);
-0153    EventsData.eventFlow = reshape(Qsave, ndays*numyears, 1);
-0154    EventsData.eventRain = reshape(Rsave, ndays*numyears, 1);
-0155    EventsData.eventTags = reshape(Etags, ndays*numyears, 1);
-0156 
-0157    debug = false;
-0158    <span class="keyword">if</span> debug == true
-0159       figure; plot(T(1:720), Q(1:720), <span class="string">'o'</span>); hold on;
-0160       plot(T(thisYearInfo.imaxima), Q(thisYearInfo.imaxima), <span class="string">'o'</span>)
-0161    <span class="keyword">end</span>
-0162 <span class="keyword">end</span>
-0163 
-0164 <a name="_sub1" href="#_subfunctions" class="code">function thisYearInfo = updateinfo(thisYearInfo, thisYear)</a>
-0165    <span class="comment">% Adjust the indices in Info to be relative to the multi-year timeseries</span>
-0166    fields = fieldnames(thisYearInfo);
-0167    <span class="keyword">for</span> f = fields(:).'
-0168       <span class="keyword">if</span> strncmp(f, <span class="string">'i'</span>, 1)
-0169          thisYearInfo.(f{:}) = thisYearInfo.(f{:}) + <span class="keyword">...</span>
-0170             thisYearInfo.datalength * (thisYear-1) - 1;
-0171       <span class="keyword">end</span>
-0172    <span class="keyword">end</span>
-0173 <span class="keyword">end</span>
-0174 
-0175 <a name="_sub2" href="#_subfunctions" class="code">function [T,Q,R,numyears] = prepinput(T,Q,R)</a>
-0176    <span class="comment">% PREPINPUT remove leap inds and determine number of years.</span>
+0142          sprintf(<span class="string">'all events fitted for %d'</span>,thisYear); pause; close all
+0143       <span class="keyword">end</span>
+0144 
+0145       <span class="comment">% Concatenate Info</span>
+0146       <span class="keyword">if</span> thisYear == 1
+0147          Info = thisYearInfo;
+0148       <span class="keyword">else</span>
+0149          thisYearInfo = <a href="#_sub1" class="code" title="subfunction thisYearInfo = updateinfo(thisYearInfo, thisYear)">updateinfo</a>(thisYearInfo, thisYear);
+0150          Info = catstructfields(1, Info, thisYearInfo);
+0151       <span class="keyword">end</span>
+0152    <span class="keyword">end</span>
+0153 
+0154    [ndays,numyears] = size(Qsave);
+0155    EventsData.eventTime = reshape(tsave, ndays*numyears, 1);
+0156    EventsData.eventFlow = reshape(Qsave, ndays*numyears, 1);
+0157    EventsData.eventRain = reshape(Rsave, ndays*numyears, 1);
+0158    EventsData.eventTags = reshape(Etags, ndays*numyears, 1);
+0159 
+0160    debug = false;
+0161    <span class="keyword">if</span> debug == true
+0162       figure; plot(T(1:720), Q(1:720), <span class="string">'o'</span>); hold on;
+0163       plot(T(thisYearInfo.imaxima), Q(thisYearInfo.imaxima), <span class="string">'o'</span>)
+0164    <span class="keyword">end</span>
+0165 <span class="keyword">end</span>
+0166 
+0167 <a name="_sub1" href="#_subfunctions" class="code">function thisYearInfo = updateinfo(thisYearInfo, thisYear)</a>
+0168    <span class="comment">% Adjust the indices in Info to be relative to the multi-year timeseries</span>
+0169    fields = fieldnames(thisYearInfo);
+0170    <span class="keyword">for</span> f = fields(:).'
+0171       <span class="keyword">if</span> strncmp(f, <span class="string">'i'</span>, 1)
+0172          thisYearInfo.(f{:}) = thisYearInfo.(f{:}) + <span class="keyword">...</span>
+0173             thisYearInfo.datalength * (thisYear-1) - 1;
+0174       <span class="keyword">end</span>
+0175    <span class="keyword">end</span>
+0176 <span class="keyword">end</span>
 0177 
-0178    <span class="keyword">if</span> isoctave()
-0179       <span class="keyword">try</span>
-0180          pkg load financial
-0181       <span class="keyword">catch</span> e
-0182          <span class="keyword">if</span> strcmp(e.message, <span class="string">'package financial is not installed'</span>)
-0183             disp([<span class="string">'Package financial is required but not installed. '</span> <span class="keyword">...</span>
-0184                <span class="string">'To install the package, run ’pkg install -forge financial’ '</span> <span class="keyword">...</span>
-0185                <span class="string">'from the Octave prompt.'</span>])
-0186          <span class="keyword">end</span>
-0187          rethrow(e)
-0188       <span class="keyword">end</span>
-0189    <span class="keyword">end</span>
-0190    monthnums = nan(size(T));
-0191    daynums = nan(size(T));
-0192    <span class="keyword">for</span> n = 1:numel(T)
-0193       monthnums = month(T(n));
-0194       daynums = day(T(n));
-0195    <span class="keyword">end</span>
-0196    leapidx = monthnums==2 &amp; daynums==29;
-0197    T(leapidx) = [];
-0198    Q(leapidx) = [];
-0199    R(leapidx) = [];
-0200    numyears = numel(T)/365;
-0201 
-0202    assert(numyears == round(numyears), <span class="string">'complete annual timeseries required'</span>);
-0203 <span class="keyword">end</span>
+0178 <a name="_sub2" href="#_subfunctions" class="code">function [T,Q,R,numyears] = prepinput(T,Q,R)</a>
+0179    <span class="comment">% PREPINPUT remove leap inds and determine number of years.</span>
+0180 
+0181    <span class="keyword">if</span> isoctave()
+0182       <span class="keyword">try</span>
+0183          pkg load financial
+0184       <span class="keyword">catch</span> e
+0185          <span class="keyword">if</span> strcmp(e.message, <span class="string">'package financial is not installed'</span>)
+0186             disp([<span class="string">'Package financial is required but not installed. '</span> <span class="keyword">...</span>
+0187                <span class="string">'To install the package, run ’pkg install -forge financial’ '</span> <span class="keyword">...</span>
+0188                <span class="string">'from the Octave prompt.'</span>])
+0189          <span class="keyword">end</span>
+0190          rethrow(e)
+0191       <span class="keyword">end</span>
+0192    <span class="keyword">end</span>
+0193    monthnums = nan(size(T));
+0194    daynums = nan(size(T));
+0195    <span class="keyword">for</span> n = 1:numel(T)
+0196       monthnums(n) = month(T(n));
+0197       daynums(n) = day(T(n));
+0198    <span class="keyword">end</span>
+0199    leapidx = monthnums==2 &amp; daynums==29;
+0200    T(leapidx) = [];
+0201    Q(leapidx) = [];
+0202    R(leapidx) = [];
+0203    numyears = numel(T)/365;
 0204 
-0205 <span class="comment">%% INPUT PARSER</span>
-0206 <a name="_sub3" href="#_subfunctions" class="code">function [T, Q, R, opts] = parseinputs(T, Q, R, mfilename, varargin)</a>
+0205    assert(numyears == round(numyears), <span class="string">'complete annual timeseries required'</span>);
+0206 <span class="keyword">end</span>
 0207 
-0208    <span class="comment">% Take the option defaults from setopts so that getevents, wrapevents,</span>
-0209    <span class="comment">% and eventfinder use the same values.</span>
-0210    defaults = baseflow.setopts(<span class="string">'getevents'</span>);
-0211    parser = inputParser;
-0212    parser.FunctionName = [<span class="string">'baseflow.'</span> mfilename];
-0213    parser.StructExpand = true;
-0214 
-0215    parser.addRequired(<span class="string">'T'</span>, @(x) isnumeric(x) | isdatetime(x));
-0216    parser.addRequired(<span class="string">'Q'</span>, @(x) isnumeric(x) &amp; numel(x)==numel(T));
-0217    parser.addRequired(<span class="string">'R'</span>, @isnumeric);
-0218 
-0219    parser.addParameter(<span class="string">'qmin'</span>, defaults.qmin, @isnumericscalar);
-0220    parser.addParameter(<span class="string">'nmin'</span>, defaults.nmin, @isnumericscalar);
-0221    parser.addParameter(<span class="string">'fmax'</span>, defaults.fmax, @isnumericscalar);
-0222    parser.addParameter(<span class="string">'rmax'</span>, defaults.rmax, @isnumericscalar);
-0223    parser.addParameter(<span class="string">'rmin'</span>, defaults.rmin, @isnumericscalar);
-0224    parser.addParameter(<span class="string">'cmax'</span>, defaults.cmax, @isnumericscalar);
-0225    parser.addParameter(<span class="string">'rmconvex'</span>, defaults.rmconvex, @islogical);
-0226    parser.addParameter(<span class="string">'rmnochange'</span>, defaults.rmnochange, @islogical);
-0227    parser.addParameter(<span class="string">'rmrain'</span>, defaults.rmrain, @islogical);
-0228    parser.addParameter(<span class="string">'pickevents'</span>, defaults.pickevents, @islogical);
-0229    parser.addParameter(<span class="string">'plotevents'</span>, defaults.plotevents, @islogical);
-0230    parser.addParameter(<span class="string">'asannual'</span>, defaults.asannual, @islogical);
-0231 
-0232    parser.parse(T, Q, R, varargin{:});
-0233    opts = parser.Results;
+0208 <span class="comment">%% INPUT PARSER</span>
+0209 <a name="_sub3" href="#_subfunctions" class="code">function [T, Q, R, opts] = parseinputs(T, Q, R, mfilename, varargin)</a>
+0210 
+0211    <span class="comment">% Take the option defaults from setopts so that getevents, wrapevents,</span>
+0212    <span class="comment">% and eventfinder use the same values.</span>
+0213    defaults = baseflow.setopts(<span class="string">'getevents'</span>);
+0214    parser = inputParser;
+0215    parser.FunctionName = [<span class="string">'baseflow.'</span> mfilename];
+0216    parser.StructExpand = true;
+0217 
+0218    parser.addRequired(<span class="string">'T'</span>, @(x) isnumeric(x) | isdatetime(x));
+0219    parser.addRequired(<span class="string">'Q'</span>, @(x) isnumeric(x) &amp; numel(x)==numel(T));
+0220    parser.addRequired(<span class="string">'R'</span>, @isnumeric);
+0221 
+0222    parser.addParameter(<span class="string">'qmin'</span>, defaults.qmin, @isnumericscalar);
+0223    parser.addParameter(<span class="string">'nmin'</span>, defaults.nmin, @isnumericscalar);
+0224    parser.addParameter(<span class="string">'fmax'</span>, defaults.fmax, @isnumericscalar);
+0225    parser.addParameter(<span class="string">'rmax'</span>, defaults.rmax, @isnumericscalar);
+0226    parser.addParameter(<span class="string">'rmin'</span>, defaults.rmin, @isnumericscalar);
+0227    parser.addParameter(<span class="string">'cmax'</span>, defaults.cmax, @isnumericscalar);
+0228    parser.addParameter(<span class="string">'rmconvex'</span>, defaults.rmconvex, @islogical);
+0229    parser.addParameter(<span class="string">'rmnochange'</span>, defaults.rmnochange, @islogical);
+0230    parser.addParameter(<span class="string">'rmrain'</span>, defaults.rmrain, @islogical);
+0231    parser.addParameter(<span class="string">'pickevents'</span>, defaults.pickevents, @islogical);
+0232    parser.addParameter(<span class="string">'plotevents'</span>, defaults.plotevents, @islogical);
+0233    parser.addParameter(<span class="string">'asannual'</span>, defaults.asannual, @islogical);
 0234 
-0235    <span class="keyword">if</span> isempty(R)
-0236       R = zeros(size(Q));
-0237    <span class="keyword">end</span>
-0238 
-0239    <span class="comment">% Convert datetime to double if datetime was passed in</span>
-0240    T = todatenum(T);
-0241 <span class="keyword">end</span></pre></div>
+0235    parser.parse(T, Q, R, varargin{:});
+0236    opts = parser.Results;
+0237 
+0238    <span class="keyword">if</span> isempty(R)
+0239       R = zeros(size(Q));
+0240    <span class="keyword">end</span>
+0241 
+0242    <span class="comment">% Convert datetime to double if datetime was passed in</span>
+0243    T = todatenum(T);
+0244 <span class="keyword">end</span></pre></div>
 </body>
 </html>
\ No newline at end of file
diff --git a/toolbox/docs/html/m2html/function_index.html b/toolbox/docs/html/m2html/function_index.html
index 1c3c8af..f4ac866 100644
--- a/toolbox/docs/html/m2html/function_index.html
+++ b/toolbox/docs/html/m2html/function_index.html
@@ -118,6 +118,6 @@ <h2>Function Files in these Packages</h2>
 		<td><a href="" title=""></a></td>	</tr></table>
 
 
-<hr><address>Generated on Tue 13-Oct-2026 21:00:16 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
+<hr><address>Generated on Thu 22-Oct-2026 18:50:28 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" title="Matlab Documentation in HTML">m2html</a></strong> &copy; 2005</address>
 </body>
 </html>
\ No newline at end of file

From 944fff77c43625fe53337302f7f4850c70513c3c Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 22:09:25 -0700
Subject: [PATCH 23/28] style(agents): adopt shared MATLAB formatting

---
 STYLE.local.md |  5 ++---
 STYLE.md       | 30 ++++++++++++++++++++++++++++--
 2 files changed, 30 insertions(+), 5 deletions(-)

diff --git a/STYLE.local.md b/STYLE.local.md
index 44500df..0e164d9 100644
--- a/STYLE.local.md
+++ b/STYLE.local.md
@@ -18,9 +18,8 @@ merged into it).
 
 ## Formatting
 
-- Indent with 3 spaces; no tabs.
-- Wrap at roughly 80 columns; continue long lines with `...`.
-- Close every function with an explicit `end`.
+Use the shared MATLAB formatting rules in `STYLE.md`.
+
 - Function help uses an uppercase H1 (`%FITAB fit event-scale ...`) followed
   by `Syntax`, `Description`, input, and output sections for public
   functions. See `toolbox/+baseflow/fitab.m` for the reference format.
diff --git a/STYLE.md b/STYLE.md
index 12bce9a..87bf33e 100644
--- a/STYLE.md
+++ b/STYLE.md
@@ -183,8 +183,34 @@ rules above. Opinionated, project-varying choices belong in `STYLE.local.md`.
 
 ## Formatting
 
-- Wrap code and comments at roughly 80 columns; continue long lines with `...`.
-  (Indentation width is project-specific — see `STYLE.local.md`.)
+- Keep code and prose comments within 80 columns; continue code with `...`.
+  Record lines that cannot be wrapped without changing their meaning or use.
+- Indent blocks with 3 spaces. Indent continuations 3 additional spaces from
+  their statement, without aligning them under an opening bracket.
+  MATLAB Editor Smart Indent determines indentation; configure it for these widths.
+  Keep MISS_HIT's indentation rule disabled so it does not undo that layout.
+- Put exactly one space on each side of assignment `=` signs.
+  Remove padding used to align assignments, other code tokens or trailing comments.
+  Keep one space before a trailing comment and preserve its attachment to the code.
+  Preserve whitespace that separates MATLAB array elements.
+- Use plain section headers such as `%% Header`, without decorative borders.
+  Keep meaningful comment text and execution cell boundaries.
+- Preserve the H1 help convention `%FUNCTION brief description`, without a space
+  after `%`. Use a space after `%` in ordinary prose comments.
+  Keep pragmas, block-comment delimiters and commented-out code intact.
+- Use the shared MATLAB MISS_HIT profile in a repository-root `miss_hit.cfg`.
+  Set `project_root`, `line_length: 80`, `tab_width: 3`, and both bracket-alignment
+  options to `false`. Suppress `operator_after_continuation` to allow leading
+  continuation operators without moving them for style.
+  Suppress `whitespace_comments` because MISS_HIT has no H1-specific spacing exception.
+  Keep the shared profile's name, token and encoding protections during formatting.
+- Keep frozen dependencies and project-specific exceptions in local configurations.
+  Record the formatter path, selected files and justified exceptions in `STYLE.local.md`.
+  Run `mh_style --fix` only on the selected files, then check Smart Indent and
+  remove remaining alignment padding. MISS_HIT alone does not enforce every rule above.
+- Formatting must preserve behavior, data, RNG order, displayed output, comments
+  and encoding. Renaming, scalar-operator substitutions, quote rewrites and
+  scientific changes need their own scope.
 
 ## Testing
 

From c61ac212846b73df765937dbc812035f2d064f16 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 22:48:40 -0700
Subject: [PATCH 24/28] fix(deps): return no peak when no extremum passes the
 selectivity

- toolbox/+baseflow/+deps/peakfinder.m: with the endpoints excluded, the
  end check of a BFRA-local branch could add the last candidate peak
  when no candidate had passed the selectivity, and then read an unset
  tempLoc. The branch starts with no candidate and adds one only when
  one exists. Calls that did not error give the same result, because
  the branch reads tempLoc only when a candidate exists.
- tests/test_peakfinder.m: a selectivity of 1 on a series that ends
  below its extrema finds no peak; the code before this change errors
  on that input.
- CHANGELOG.md: an [Unreleased] Fixed entry describes the fix.
---
 CHANGELOG.md                         |  4 ++++
 tests/test_peakfinder.m              | 18 ++++++++++++++++--
 toolbox/+baseflow/+deps/peakfinder.m |  6 +++++-
 3 files changed, 25 insertions(+), 3 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7294ee4..45c0b60 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -33,6 +33,10 @@ semantic versioning.
 
 ### Fixed
 
+- `baseflow.deps.peakfinder` returns no peak when no extremum passes the
+  selectivity with the endpoints excluded. It read an unset candidate and
+  errored for a positive selectivity on a series that ends below its
+  extrema.
 - `wrapevents` removes February 29 before annual grouping and keeps the
   remaining timestamps, flow and rainfall rows aligned. Leap-year input
   previously failed the complete-year check.
diff --git a/tests/test_peakfinder.m b/tests/test_peakfinder.m
index 18d449d..cfac91b 100644
--- a/tests/test_peakfinder.m
+++ b/tests/test_peakfinder.m
@@ -1,8 +1,9 @@
 classdef test_peakfinder < matlab.unittest.TestCase
    %TEST_PEAKFINDER Test the vendored +deps/peakfinder function.
    %
-   % The tests cover the empty-input path and one nominal peak case as a
-   % reference for the algorithm's behavior. The function signature declares
+   % The tests cover the empty-input path, one nominal peak case as a
+   % reference for the algorithm's behavior, and a selectivity that rejects
+   % every peak. The function signature declares
    % named outputs, so the empty-input path must assign those outputs, not
    % varargout. An assignment to varargout makes empty input error instead
    % of returning empty results.
@@ -27,6 +28,19 @@ function test_findsPeak(testCase, signal)
          testCase.verifyEqual(mags_returned, mags_expected)
       end
 
+      function test_selectivityCanRejectEveryPeak(testCase)
+         % With the endpoints excluded, no interior peak of this series
+         % rises 1 above the data around it, so a selectivity of 1 finds
+         % no peak. The series ends far below its extrema, which is the
+         % case where the end check must not read an unset candidate.
+         x = [10; 10.1; 10.05; 10.12; 5];
+         sel = 1;
+
+         returned = baseflow.deps.peakfinder(x, sel, [], 1, false);
+
+         testCase.verifyEmpty(returned)
+      end
+
       function test_emptyThroughIslocalmax(testCase)
          % baseflow/private/islocalmax indexes with the locations that
          % peakfinder returns. Empty input must produce an empty logical,
diff --git a/toolbox/+baseflow/+deps/peakfinder.m b/toolbox/+baseflow/+deps/peakfinder.m
index 91e75d8..8466eb6 100644
--- a/toolbox/+baseflow/+deps/peakfinder.m
+++ b/toolbox/+baseflow/+deps/peakfinder.m
@@ -225,6 +225,10 @@
       peakLoc = zeros(maxPeaks,1);
       peakMag = zeros(maxPeaks,1);
       cInd = 1;
+      % Local change: start with no candidate peak. With sel > 0 no extremum
+      % can pass the selectivity test, and the end check below must then
+      % add nothing rather than read an unset tempLoc.
+      tempLoc = [];
       % Loop through extrema which should be peaks and then valleys
       while ii < len
          ii = ii+1; % This is a peak
@@ -276,7 +280,7 @@
             peakLoc(cInd) = len;
             peakMag(cInd) = x(end);
             cInd = cInd + 1;
-         elseif tempMag > min(x0(end), x(end)) + sel
+         elseif ~isempty(tempLoc) && tempMag > min(x0(end), x(end)) + sel
             peakLoc(cInd) = tempLoc;
             peakMag(cInd) = tempMag;
             cInd = cInd + 1;

From 5c298df5abd1e64599f0ed3bc04505b286486ada Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Thu, 22 Oct 2026 23:03:39 -0700
Subject: [PATCH 25/28] fix(baseflow): treat rounding-level slopes and
 curvatures as zero

eventfinder tests slope and curvature signs, extrema, and trends. On a
straight or constant stretch these are zero in exact arithmetic, but the
computed values carry rounding, and the smoothing in getevents makes it
depend on the MATLAB release, so the selected events did too.

- toolbox/+baseflow/eventfinder.m: each test treats a value as zero
  within the rounding bound of its own computation. With
  E1 = qerror + 2*u*max(abs(q)), a slope is zero within 2*E1 and a
  curvature within 4*E1. The 3-day mean adds 3*u*max(abs(q)). Extrema
  and the endpoint steps use the same thresholds. No-change runs are
  set to exactly 0. A new option, 'qerror', takes the rounding bound of
  the input values; without it, eventfinder counts one rounding.
- private smoothflow.m returns the bound of its smoothing,
  2.25*(win+1)*u*max(abs(x)), and getevents and findevents pass it.
- private islocalmax.m and islocalmin.m take a peakfinder selectivity.
  islineconvex.m and islinepositive.m take a rounding bound, and calls
  without one keep the backslash slope. The new private trendsign.m
  holds the bounded trend sign.
- toolbox/functionSignatures.json: the qerror option.
- tests/test_eventfinder.m: constant, straight, curved, and
  near-threshold series at three flow scales. The earlier rule fails
  every rounding-level case.
- tests/TestBaseflow.m: kuparukb is 1.3465 with btol 5e-4. R2025b gives
  1.346467 and R2026a 1.346470. R2024b selects the same 231 events but
  gives 1.3577, because its per-event fits differ.
- CHANGELOG.md: an [Unreleased] Fixed entry describes the change.
---
 CHANGELOG.md                               |  18 +++
 tests/TestBaseflow.m                       |   9 +-
 tests/test_eventfinder.m                   | 166 +++++++++++++++++++++
 toolbox/+baseflow/eventfinder.m            | 119 ++++++++++++---
 toolbox/+baseflow/getevents.m              |   9 +-
 toolbox/+baseflow/private/findevents.m     |   9 +-
 toolbox/+baseflow/private/islineconvex.m   |  22 ++-
 toolbox/+baseflow/private/islinepositive.m |  21 ++-
 toolbox/+baseflow/private/islocalmax.m     |  15 +-
 toolbox/+baseflow/private/islocalmin.m     |  15 +-
 toolbox/+baseflow/private/smoothflow.m     |  18 ++-
 toolbox/+baseflow/private/trendsign.m      |  26 ++++
 toolbox/functionSignatures.json            |   3 +-
 13 files changed, 410 insertions(+), 40 deletions(-)
 create mode 100644 toolbox/+baseflow/private/trendsign.m

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 45c0b60..3274f78 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -33,6 +33,24 @@ semantic versioning.
 
 ### Fixed
 
+- The `eventfinder` filters treat a slope or curvature as zero when its
+  magnitude does not exceed the rounding error of its own computation.
+  Exact arithmetic gives a zero curvature on a straight stretch of flow,
+  but the computed values carry rounding, and the smoothing that
+  `getevents` applies makes it depend on the MATLAB release. So the
+  filters selected different events on different releases. The bound
+  scales with the flow and, after smoothing, with the smoothing window;
+  the `eventfinder` help states it. `getevents` passes the bound of its
+  smoothing through the new `eventfinder` option `'qerror'`, and
+  unsmoothed input counts one rounding per value. The Kuparuk annual
+  workflow selects the same 231 events on R2024b, R2025b, and R2026a,
+  where it selected 229 or 230. Against the earlier R2025b result, the
+  `rmnochange` filter excludes 46 more late-season days on straight
+  stretches, which shortens or splits some events. The workflow's
+  recession exponent b is 1.3465 on R2025b and R2026a, against 1.3541
+  in the 1.1.0 release notes, and `TestBaseflow` checks that value.
+  R2024b selects the same events but gives 1.3577, because its
+  per-event nonlinear fits differ.
 - `baseflow.deps.peakfinder` returns no peak when no extremum passes the
   selectivity with the endpoints excluded. It read an unset candidate and
   errored for a positive selectivity on a series that ends below its
diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index 67cd4ce..e6879ed 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -42,9 +42,12 @@
       Dd = 0.8
       D = 0.47
 
-      % The recession exponent of the Kuparuk annual workflow, as the 1.1.0
-      % release notes record it, and the rounding of that value.
-      kuparukb = 1.3540
+      % The recession exponent of the Kuparuk annual workflow, and the
+      % rounding of that value. With the numerical-zero rule of
+      % eventfinder, R2025b gives 1.346467 and R2026a 1.346470. R2024b
+      % selects the same events but gives 1.3577, because its per-event
+      % fits differ, so this check fails on R2024b.
+      kuparukb = 1.3465
       btol = 5e-4
 
       % The synthetic recessions follow -dQ/dt = a*Q^b for eight days. The
diff --git a/tests/test_eventfinder.m b/tests/test_eventfinder.m
index d8bd43c..a27c274 100644
--- a/tests/test_eventfinder.m
+++ b/tests/test_eventfinder.m
@@ -5,11 +5,42 @@
    % so the expected declining and concave-up declining segments follow
    % from its derivatives. The defaults and the rmax guard of eventfinder
    % are integration checks in TestBaseflow.
+   %
+   % The numerical-zero cases check the day-level filters through Info.
+   % Exact arithmetic gives a zero slope on a constant stretch and a zero
+   % curvature on a straight stretch. eventfinder must classify those days
+   % as exact arithmetic does, whatever rounding the computed values
+   % carry, and must keep a real curvature. Each case runs at three
+   % positive flow scales, because the rule scales with the flow.
 
    properties (TestParameter)
       % The minimum event lengths and the rmconvex option of each case.
       MinEventDuration = {3,6,9};
       RmConvex = {false, true};
+
+      % Positive flow scales: unit, an exact power of two, and a factor
+      % that is not a power of two.
+      flowscale = struct('unit', 1, 'powerOfTwo', 2^-20, 'other', 3.7e5)
+
+      % The curvature of the near-threshold case as a multiple of the
+      % numerical-zero threshold, and whether eventfinder must treat the
+      % stretch as straight. A quarter of the threshold is rounding size;
+      % four times the threshold is a real curvature.
+      nearzero = struct('belowThreshold', {{0.25, true}}, ...
+         'aboveThreshold', {{4, false}})
+   end
+
+   properties (Constant)
+      % Days in each numerical-zero series, and the eventfinder options
+      % of those cases: no rain record, no gap filling, and rmax 2.
+      ndays = 60
+      nmin = 4
+
+      % Roundings per value of each constructed series, which set its
+      % qerror bound: a - b*k and (c*k)/k round twice; adding a curvature
+      % term, or computing an exponential, rounds at most twice more.
+      roundingsline = 2
+      roundingscurved = 4
    end
 
    properties (Access = private)
@@ -139,8 +170,143 @@ function test_MinEventDuration(testCase, MinEventDuration, RmConvex)
       end
    end
 
+   methods (Test)
+
+      function test_straightStretchIsNoChange(testCase, flowscale)
+         % A straight decline has zero curvature, so the rmnochange filter
+         % excludes every day of it and no event remains. The computed
+         % values carry rounding, so some second differences are not
+         % exactly zero.
+         q = testCase.straightdecline(flowscale);
+         testCase.assumeTrue(any(diff(diff(q)) ~= 0), ...
+            'the straight decline carries no rounding to test')
+         expected = zeros(0, 1);
+
+         [~, ~, ~, Info] = testCase.findevents(q, true, ...
+            testCase.roundingsline);
+
+         returned = Info.icandidate(:);
+         testCase.verifyEqual(returned, expected)
+      end
+
+      function test_constantStretchHasNoSlope(testCase, flowscale)
+         % A constant stretch has zero slope and no extremum, so no day of
+         % it is rising or a peak, and every day stays a candidate. Its
+         % least-squares trend is zero, so it is neither convex nor rising
+         % and stays one event. The values differ from the constant by at
+         % most one rounding unit.
+         q = testCase.constantstretch(flowscale);
+         testCase.assumeTrue(numel(unique(q)) > 1, ...
+            'the constant stretch carries no rounding to test')
+         candidates_expected = (1:testCase.ndays)';
+         span_expected = [1 testCase.ndays];
+
+         [~, ~, ~, Info] = testCase.findevents(q, false, ...
+            testCase.roundingsline);
+
+         candidates_returned = Info.icandidate(:);
+         span_returned = [Info.istart(:) Info.istop(:)];
+         testCase.verifyEqual(candidates_returned, candidates_expected)
+         testCase.verifyEqual(span_returned, span_expected)
+      end
+
+      function test_straightStretchIsNotConvex(testCase, flowscale)
+         % With rmnochange false, a straight decline stays one event: its
+         % first differences have a zero trend, so it is not convex, and
+         % it falls, so it is not rising. The first two days and the last
+         % day are the endpoint extrema that eventfinder excludes.
+         q = testCase.straightdecline(flowscale);
+         testCase.assumeTrue(any(diff(diff(q)) ~= 0), ...
+            'the straight decline carries no rounding to test')
+         expected = [3 testCase.ndays-1];
+
+         [~, ~, ~, Info] = testCase.findevents(q, false, ...
+            testCase.roundingsline);
+
+         returned = [Info.istart(:) Info.istop(:)];
+         testCase.verifyEqual(returned, expected)
+      end
+
+      function test_curvedRecessionKeepsItsDays(testCase, flowscale)
+         % An exponential recession has a real curvature, so the rule
+         % removes none of its days. The first two days and the last day
+         % are the endpoint extrema that eventfinder always excludes.
+         t = (0:testCase.ndays-1)';
+         timescale = 20; % recession timescale [days]
+         q = flowscale * 1e3 * exp(-t / timescale);
+         expected = (3:testCase.ndays-1)';
+
+         [~, ~, ~, Info] = testCase.findevents(q, true, ...
+            testCase.roundingscurved);
+
+         returned = Info.icandidate(:);
+         testCase.verifyEqual(returned, expected)
+      end
+
+      function test_nearThresholdCurvature(testCase, flowscale, nearzero)
+         % A straight decline plus a curvature that is a multiple of the
+         % documented threshold. Below the threshold the stretch counts as
+         % straight and no day remains. Above it the curvature is real and
+         % the interior days remain.
+         [multiple, isstraight] = nearzero{:};
+         q = testCase.straightdecline(flowscale);
+         k = (0:testCase.ndays-1)';
+         curvature = multiple * testCase.curvaturethreshold(q, ...
+            testCase.roundingscurved);
+         q = q + curvature / 2 * (k - k(end)/2).^2;
+
+         [~, ~, ~, Info] = testCase.findevents(q, true, ...
+            testCase.roundingscurved);
+
+         returned = isempty(Info.icandidate);
+         testCase.verifyEqual(returned, isstraight)
+      end
+   end
+
    methods (Access = private) % Helper methods
 
+      function [T, Q, R, Info] = findevents(testCase, q, rmnochange, ...
+         roundings)
+         %FINDEVENTS Run eventfinder on a daily series without rain.
+         %
+         %  roundings is the number of roundings each value of q carries,
+         %  so qerror = roundings*u*max(abs(q)) with u = eps/2.
+         t = (1:numel(q))';
+         qerror = roundings * (eps/2) * max(abs(q));
+         [T, Q, R, Info] = baseflow.eventfinder(t, q, zeros(size(q)), ...
+            'nmin', testCase.nmin, 'fmax', 0, 'rmax', 2, 'rmin', 0, ...
+            'rmconvex', false, 'rmnochange', rmnochange, ...
+            'rmrain', false, 'qerror', qerror);
+      end
+
+      function q = straightdecline(testCase, flowscale)
+         %STRAIGHTDECLINE Return a straight daily decline with rounding.
+         %
+         %  The start and the daily step are not exact binary fractions, so
+         %  the computed values carry rounding.
+         k = (0:testCase.ndays-1)';
+         q = flowscale * (1e3 + pi) - flowscale * (10/3) * k;
+      end
+
+      function q = constantstretch(testCase, flowscale)
+         %CONSTANTSTRETCH Return a constant series with rounding.
+         %
+         %  (c*k)/k equals c in exact arithmetic but can differ from c by
+         %  one rounding unit.
+         k = (1:testCase.ndays)';
+         c = flowscale * (1e3 + pi);
+         q = (c * k) ./ k;
+      end
+
+      function t2 = curvaturethreshold(~, q, roundings)
+         %CURVATURETHRESHOLD The documented numerical-zero curvature.
+         %
+         %  4*E1, with E1 = qerror + 2*u*max(abs(q)), u = eps/2, and
+         %  qerror = roundings*u*max(abs(q)), as the eventfinder help
+         %  states.
+         t2 = 4 * (roundings + 2) * (eps/2) * max(abs(q));
+      end
+
       function [t, q] = prepareEventData(testCase, prec) %#ok<*INUSD>
          % This function handles some common operations related to test data
 
diff --git a/toolbox/+baseflow/eventfinder.m b/toolbox/+baseflow/eventfinder.m
index 267b15c..7019ccc 100644
--- a/toolbox/+baseflow/eventfinder.m
+++ b/toolbox/+baseflow/eventfinder.m
@@ -12,6 +12,7 @@
    %     [T,Q,R,Info] = eventfinder(_, 'rmrain', false)
    %     [T,Q,R,Info] = eventfinder(_, 'rmconvex', true)
    %     [T,Q,R,Info] = eventfinder(_, 'rmnochange', false)
+   %     [T,Q,R,Info] = eventfinder(_, 'qerror', qerror)
    %
    % Description
    %
@@ -38,12 +39,34 @@
    %     rmconvex    remove convex derivatives
    %     rmnochange  remove consecutive constant derivates
    %     rmrain      remove rainfall
+   %     qerror      bound on the rounding error of each value of q, in the
+   %                 units of q. Default u*max(abs(q)), one rounding.
+   %                 getevents passes the bound that its smoothing returns.
    %
-   %     Each option default is the baseflow.setopts('getevents') value.
-   %     nmin must be greater than 2. rmax must be greater than 1: the
-   %     rmnochange filter marks nonzero d2q/dt2 values nan. Each nan
-   %     counts as a run of length 1, so an rmax of 1 or less rejects
-   %     every day.
+   %     Each option default except qerror is the
+   %     baseflow.setopts('getevents') value. nmin must be greater than 2.
+   %     rmax must be greater than 1: the rmnochange filter marks d2q/dt2
+   %     values beyond the numerical-zero curvature nan. Each nan counts as
+   %     a run of length 1, so an rmax of 1 or less rejects every day.
+   %
+   % Numerical zero
+   %
+   %     The filters test the sign of dq/dt and d2q/dt2, the extrema of q
+   %     and dq/dt, and the trend of q and dq/dt over an event. Exact
+   %     arithmetic gives a zero slope on a constant stretch and a zero
+   %     curvature on a straight stretch, but computed values carry
+   %     rounding, and the smoothing that getevents applies makes it
+   %     depend on the MATLAB release. So each test treats a value as zero
+   %     when its magnitude does not exceed the rounding error of its own
+   %     computation. With u = eps/2 and s = max(abs(q)), each flow value
+   %     carries at most qerror, and E1 = qerror + 2*u*s adds the rounding
+   %     of one difference. A slope is zero within 2*E1 and a curvature
+   %     within 4*E1, the sums of absolute weights of a first and a second
+   %     difference. An extremum must rise above its neighbours by more
+   %     than that amount. The 3-day moving mean adds 3*u*s. Each test
+   %     compares a per-sample difference with a threshold in the same
+   %     units, so the time unit does not matter. The rule scales with q,
+   %     so a positive factor on q does not change the events.
    %
    % Example
    %
@@ -64,10 +87,16 @@
    [t, q, r, opts] = parseinputs(t, q, r, mfilename, varargin{:});
 
    % MAIN CODE
+   % Bound the rounding error of the flow values once for the whole
+   % series. getevents smooths the whole series, so each segment carries
+   % the error of the whole series (see Numerical zero in the help).
+   [E1, qscale] = roundingbound(q, opts.qerror);
+
    [iS, iE] = nonnansegments(q, opts.nmin);
 
    [T, Q, R, Info] = arrayfun(@(s, e) ...
-      eventsplitter(t(s:e), q(s:e), r(s:e), opts), iS, iE, 'Uniform', false);
+      eventsplitter(t(s:e), q(s:e), r(s:e), opts, E1, qscale), iS, iE, ...
+      'Uniform', false);
 
    if isempty(T)
       [T, Q, R, Info] = setEventEmpty();
@@ -86,12 +115,12 @@
    Info = catstructfields(1, Info{:});
 end
 
-function [T, Q, R, Info] = eventsplitter(t, q, r, opts)
+function [T, Q, R, Info] = eventsplitter(t, q, r, opts, E1, qscale)
    %eventsplitter Split detected recession events into segments for fitting.
    %
    % Syntax
    %
-   %     [T,Q,R,Info] = eventsplitter(t,q,r,opts)
+   %     [T,Q,R,Info] = eventsplitter(t,q,r,opts,E1,qscale)
    %
    % Description
    %
@@ -115,6 +144,8 @@
    %     rmconvex    remove convex derivatives
    %     rmnochange  remove consecutive constant derivates
    %     rmrain      remove rainfall
+   %     E1          rounding bound of the flow values and one difference
+   %     qscale      max(abs(q)) of the whole series (see roundingbound)
    %
    % See also getevents, eventfinder, eventpicker, eventplotter
 
@@ -138,15 +169,29 @@
    d2qdt = [0; diff(dqdt)];
    d2qdtS = [0; diff(dqdtS)];
 
+   % Numerical-zero thresholds, in the units of each difference. A first
+   % difference has absolute weights that sum to 2, and a second
+   % difference 4. The 3-day mean adds at most 3*u*qscale. Below these
+   % amounts a slope or curvature is rounding, not signal.
+   E1S = E1 + 3 * (eps/2) * qscale;
+   tslope = 2 * E1;
+   tcurve = 4 * E1;
+   tcurveS = 4 * E1S;
+
    % Part 1: find data to be excluded (run the filters)
 
    % filters: positive dq/dt, peaks +1 day, convex +1 day, and minima -1 day
    % islocalmax and islocalmin are the private peakfinder wrappers, because
    % Octave has no islocalmax or islocalmin.
-   ipos = find(dqdt > 0); % increasing flow (positive dq/dt)
-   imax = find(islocalmax(q)); % local maxima
-   imin = find(islocalmin(q)); % local minima
-   icon = find(islocalmax(dqdt) & islocalmax(dqdtS)) + 1;  % convex + 1 day
+   % Each test uses its numerical-zero threshold. An extremum of q must
+   % rise above its neighbours by more than a slope threshold, and an
+   % extremum of dq/dt by more than a curvature threshold, because
+   % neighbouring slopes differ by a curvature.
+   ipos = find(dqdt > tslope); % increasing flow (positive dq/dt)
+   imax = find(islocalmax(q, tslope)); % local maxima
+   imin = find(islocalmin(q, tslope)); % local minima
+   icon = find(islocalmax(dqdt, tcurve) & islocalmax(dqdtS, tcurveS)) ...
+      + 1; % convex + 1 day
 
    % This also finds the transitions from convex up to concave up
    % icon = find( (islocalmax(dqdt) & islocalmax(dqdtS)) | ...
@@ -154,18 +199,19 @@
 
    % Dralle: keep if dq/dt<0 AND d2q/dt2>0 (concave up) in BOTH the raw and
    % smoothed data, i.e. exclude if both raw AND smoothed data are convex
-   icon2 = find(d2qdt <= 0 & d2qdtS <= 0) - 1;
+   icon2 = find(d2qdt <= tcurve & d2qdtS <= tcurveS) - 1;
    icon2 = icon2(icon2 > 0);
 
    % icon always occurs on peaks and one day prior, remove them from icon,
    % the peak will remain in imax, and one day prior in ipos
    icon = icon(~ismember((icon), imax));
 
-   % if the first (last) point is a local max (min), add them here
-   if q(2) < q(1)
+   % if the first (last) point is a local max (min), add them here. The
+   % endpoint step is a slope, so it must exceed the slope threshold.
+   if q(1) - q(2) > tslope
       imax = [1; imax];
    end
-   if q(end) < q(end-1)
+   if q(end-1) - q(end) > tslope
       imin = [imin; length(q)];
    end
 
@@ -191,7 +237,12 @@
 
    % exclude sequences of two or more of (dq/dt = 0) (see setconstantnan)
    if opts.rmnochange == true
-      inoc = d2qdt; inoc(inoc ~= 0) = nan;
+      % runlength counts runs of equal values, so a numerically zero
+      % curvature becomes exactly 0 and a real one becomes nan.
+      inoc = d2qdt;
+      iszero = abs(inoc) <= tcurve;
+      inoc(iszero) = 0;
+      inoc(~iszero) = nan;
       inoc = find(isminlength(inoc, opts.rmax));
       ibad = [ibad; inoc];
    end
@@ -214,7 +265,9 @@
    % Remove events shorter than nmin and concave increasing flows
    keep = eventlength >= opts.nmin;
    for n = 1:numel(is)
-      if islineconvex(q(is(n):ie(n))) || islinepositive(q(is(n):ie(n)))
+      % The trend tests take the rounding bound of the flow values.
+      if islineconvex(q(is(n):ie(n)), E1) ...
+         || islinepositive(q(is(n):ie(n)), E1)
          keep(n) = false;
       end
    end
@@ -259,6 +312,26 @@
 
 end
 
+%% ROUNDING BOUND
+function [E1, qscale] = roundingbound(q, qerror)
+   %ROUNDINGBOUND Bound the rounding error of the flow values.
+   %
+   %  [E1, qscale] = roundingbound(q, qerror) returns qscale = max(abs(q))
+   %  over the finite values of q and E1 = qerror + 2*u*qscale, with
+   %  u = eps/2. qerror bounds the rounding error of each value of q, and
+   %  2*u*qscale covers the rounding of one difference. An empty qerror
+   %  means one rounding per value, u*qscale. A series with no finite
+   %  value gives E1 = 0.
+   qscale = max(abs(q(isfinite(q))));
+   if isempty(qscale)
+      qscale = 0;
+   end
+   if isempty(qerror)
+      qerror = (eps/2) * qscale;
+   end
+   E1 = qerror + 2 * (eps/2) * qscale;
+end
+
 %% INPUT PARSER
 function [t, q, r, opts] = parseinputs(t, q, r, funcname, varargin)
 
@@ -278,6 +351,9 @@
       addParameter(parser,'rmconvex',   defaults.rmconvex,   @islogicalscalar);
       addParameter(parser,'rmnochange', defaults.rmnochange, @islogicalscalar);
       addParameter(parser,'rmrain',     defaults.rmrain,     @islogicalscalar);
+      % The rounding bound of q is a property of the data, not a setopts
+      % policy, so its default is empty: one rounding per value.
+      addParameter(parser,'qerror',     [],                  @isqerror);
    end
    parser.FunctionName = funcname;
    parse(parser,t,q,r,varargin{:});
@@ -298,4 +374,9 @@
 
    % Convert to columns, in case this is not called from baseflow.getevents
    [t, q, r] = deal(t(:), q(:), r(:));
-end
\ No newline at end of file
+end
+
+function tf = isqerror(x)
+   %ISQERROR True for an empty value or a nonnegative finite scalar.
+   tf = isempty(x) || (isnumeric(x) && isscalar(x) && isfinite(x) && x >= 0);
+end
diff --git a/toolbox/+baseflow/getevents.m b/toolbox/+baseflow/getevents.m
index abe36b9..08c40a8 100644
--- a/toolbox/+baseflow/getevents.m
+++ b/toolbox/+baseflow/getevents.m
@@ -112,8 +112,12 @@
    % If events are detected on an annual basis, option to smooth measurement
    % noise. If multi-year timeseries are used, smoothing is not effective, there
    % is too much variability to select consistent smoothing parameters.
+   % smoothflow returns the rounding bound of the values it smooths.
+   % eventfinder uses it as the numerical zero of its filters; without
+   % smoothing, eventfinder assumes one rounding per value.
+   qerror = [];
    if asannual
-      Q = smoothflow(Q);
+      [Q, ~, qerror] = smoothflow(Q);
    end
 
    if isempty(Q) || ( sum(~isnan(Q)) < nmin ) % fast exit
@@ -127,7 +131,8 @@
          'rmin',        rmin,          ...
          'rmconvex',    rmconvex,      ...
          'rmnochange',  rmnochange,    ...
-         'rmrain',      rmrain         );
+         'rmrain',      rmrain,        ...
+         'qerror',      qerror         );
 
       Info = updateinfo(Info,iF,numdata);
 
diff --git a/toolbox/+baseflow/private/findevents.m b/toolbox/+baseflow/private/findevents.m
index 1ee9989..50b6113 100644
--- a/toolbox/+baseflow/private/findevents.m
+++ b/toolbox/+baseflow/private/findevents.m
@@ -43,8 +43,12 @@
    Q           = fillnans(Q,fmax);        % gap fill missing values
 
    % smooth measurement noise
+   % smoothflow returns the rounding bound of the values it smooths.
+   % eventfinder uses it as the numerical zero of its filters; without
+   % smoothing, eventfinder assumes one rounding per value.
+   qerror = [];
    if asannual
-      Q = smoothflow(Q);
+      [Q, ~, qerror] = smoothflow(Q);
    end
 
    % % for reference, two other options I tested
@@ -62,7 +66,8 @@
          'rmin',        rmin,          ...
          'rmconvex',    rmconvex,      ...
          'rmnochange',  rmnochange,    ...
-         'rmrain',      rmrain         );
+         'rmrain',      rmrain,        ...
+         'qerror',      qerror         );
 
       Info = updateinfo(Info,iF,numdata);
 
diff --git a/toolbox/+baseflow/private/islineconvex.m b/toolbox/+baseflow/private/islineconvex.m
index cbdea09..a212b33 100644
--- a/toolbox/+baseflow/private/islineconvex.m
+++ b/toolbox/+baseflow/private/islineconvex.m
@@ -1,10 +1,26 @@
-function tf = islineconvex(y)
+function tf = islineconvex(y, ey)
    %ISLINECONVEX True if the first differences of Y trend downward (concave down).
    %
    %  tf = islineconvex(y) fits a straight line to the first differences of
    %  y against their index and returns true when the fitted slope is
    %  negative.
+   %
+   %  tf = islineconvex(y, ey) takes ey, a bound on the rounding error of
+   %  each value of y. Each first difference then carries at most 2*ey. It
+   %  returns true only when the trend is negative beyond its rounding
+   %  error (see trendsign), so a straight stretch, whose first
+   %  differences have a zero trend in exact arithmetic, is not convex.
+   %
+   %  See also: trendsign, islinepositive
    dy = diff(y);
-   ab = [ones(size(dy)), (1:numel(dy))'] \ dy;
-   tf = ab(2) < 0;
+
+   % Without a rounding bound, keep the least-squares slope sign.
+   if nargin < 2
+      ab = [ones(size(dy)), (1:numel(dy))'] \ dy;
+      tf = ab(2) < 0;
+      return
+   end
+
+   % With a bound, the trend must be negative beyond its rounding.
+   tf = trendsign(dy, 2*ey) < 0;
 end
diff --git a/toolbox/+baseflow/private/islinepositive.m b/toolbox/+baseflow/private/islinepositive.m
index e9142a1..96d9151 100644
--- a/toolbox/+baseflow/private/islinepositive.m
+++ b/toolbox/+baseflow/private/islinepositive.m
@@ -1,8 +1,23 @@
-function tf = islinepositive(y)
+function tf = islinepositive(y, ey)
    %ISLINEPOSITIVE Return true if linear fit to input X has positive slope.
    %
    %  tf = islinepositive(y) fits a straight line to y against its index
    %  and returns true when the fitted slope is positive.
-   ab = [ones(size(y)), (1:numel(y))'] \ y;
-   tf = ab(2) > 0;
+   %
+   %  tf = islinepositive(y, ey) takes ey, a bound on the rounding error
+   %  of each value of y. It returns true only when the trend is positive
+   %  beyond its rounding error (see trendsign), so a constant stretch,
+   %  whose trend is zero in exact arithmetic, is not rising.
+   %
+   %  See also: trendsign, islineconvex
+
+   % Without a rounding bound, keep the least-squares slope sign.
+   if nargin < 2
+      ab = [ones(size(y)), (1:numel(y))'] \ y;
+      tf = ab(2) > 0;
+      return
+   end
+
+   % With a bound, the trend must be positive beyond its rounding.
+   tf = trendsign(y, ey) > 0;
 end
diff --git a/toolbox/+baseflow/private/islocalmax.m b/toolbox/+baseflow/private/islocalmax.m
index 6e12cb7..115dbb6 100644
--- a/toolbox/+baseflow/private/islocalmax.m
+++ b/toolbox/+baseflow/private/islocalmax.m
@@ -1,4 +1,4 @@
-function tf = islocalmax(X)
+function tf = islocalmax(X, sel)
    %ISLOCALMAX Return true for local maximum indices of X.
    %
    %  tf = islocalmax(X) returns a logical array the size of X that is true
@@ -7,9 +7,18 @@
    %  without flat runs, the result matches the MATLAB islocalmax function,
    %  which Octave does not have.
    %
+   %  tf = islocalmax(X, sel) passes sel to peakfinder as the selectivity: a
+   %  local maximum must differ from the neighbouring opposite extrema by
+   %  more than sel, in the units of X. eventfinder passes its
+   %  numerical-zero threshold, so rounding-size wiggles are not extrema.
+   %
    %  See also: islocalmin
 
-   % peakfinder(X,sel=0,threshold=[],extrema=1,includeendpoints=false)
+   % peakfinder(X,sel,threshold=[],extrema=1,includeendpoints=false)
    tf = false(size(X));
-   tf(baseflow.deps.peakfinder(X,0,[],1,false)) = true;
+   % A selectivity of 0 keeps every sign change of the derivative.
+   if nargin < 2
+      sel = 0;
+   end
+   tf(baseflow.deps.peakfinder(X,sel,[],1,false)) = true;
 end
\ No newline at end of file
diff --git a/toolbox/+baseflow/private/islocalmin.m b/toolbox/+baseflow/private/islocalmin.m
index cb70a37..254878f 100644
--- a/toolbox/+baseflow/private/islocalmin.m
+++ b/toolbox/+baseflow/private/islocalmin.m
@@ -1,4 +1,4 @@
-function tf = islocalmin(X)
+function tf = islocalmin(X, sel)
    %ISLOCALMIN Return true for local minimum indices of X.
    %
    %  tf = islocalmin(X) returns a logical array the size of X that is true
@@ -7,9 +7,18 @@
    %  without flat runs, the result matches the MATLAB islocalmin function,
    %  which Octave does not have.
    %
+   %  tf = islocalmin(X, sel) passes sel to peakfinder as the selectivity: a
+   %  local minimum must differ from the neighbouring opposite extrema by
+   %  more than sel, in the units of X. eventfinder passes its
+   %  numerical-zero threshold, so rounding-size wiggles are not extrema.
+   %
    %  See also: islocalmax
 
-   % peakfinder(X,sel=0,threshold=[],extrema=-1,includeendpoints=false)
+   % peakfinder(X,sel,threshold=[],extrema=-1,includeendpoints=false)
    tf = false(size(X));
-   tf(baseflow.deps.peakfinder(X,0,[],-1,false)) = true;
+   % A selectivity of 0 keeps every sign change of the derivative.
+   if nargin < 2
+      sel = 0;
+   end
+   tf(baseflow.deps.peakfinder(X,sel,[],-1,false)) = true;
 end
diff --git a/toolbox/+baseflow/private/smoothflow.m b/toolbox/+baseflow/private/smoothflow.m
index f417bb9..d6299a2 100644
--- a/toolbox/+baseflow/private/smoothflow.m
+++ b/toolbox/+baseflow/private/smoothflow.m
@@ -1,4 +1,4 @@
-function [y,win] = smoothflow(x)
+function [y,win,err] = smoothflow(x)
    %SMOOTHFLOW Smooth measurement noise.
    %
    %  [y, win] = smoothflow(x) smooths x with a Savitzky-Golay filter
@@ -6,6 +6,15 @@
    %  size win. Nan elements of x stay nan in y, and the function sets
    %  negative smoothed values to zero. In Octave, a moving mean with an odd
    %  window no larger than 7 replaces the Savitzky-Golay filter.
+   %
+   %  [y, win, err] = smoothflow(x) also returns err, a bound on the
+   %  rounding error of each value of y, in the units of x. A smoothed
+   %  value is a dot product of win weights with the data, so it rounds by
+   %  at most win*u*W*s, and the rounding of the data adds W*u*s. Here
+   %  u = eps/2, s = max(abs(x)), and W = 2.25 bounds the sum of absolute
+   %  quadratic Savitzky-Golay weights for any window, edge rows included.
+   %  The moving mean has weights that sum to 1, so the same bound holds.
+   %  eventfinder takes err as its 'qerror' option.
    
    % This is only needed when testing smooth in matlab
    % warnstate = warning;
@@ -23,5 +32,12 @@
    end
    y = setnan(y,[],isnan(x));
    y(y<0)=0;
+
+   % The rounding bound of the smoothed values (see the help above).
+   W = 2.25;
+   err = W * (max(win) + 1) * (eps/2) * max(abs(x(isfinite(x))));
+   if isempty(err)
+      err = 0;
+   end
 end
 
diff --git a/toolbox/+baseflow/private/trendsign.m b/toolbox/+baseflow/private/trendsign.m
new file mode 100644
index 0000000..480adc0
--- /dev/null
+++ b/toolbox/+baseflow/private/trendsign.m
@@ -0,0 +1,26 @@
+function sg = trendsign(y, ey)
+   %TRENDSIGN Sign of the least-squares trend of Y beyond its rounding.
+   %
+   %  sg = trendsign(y, ey) returns 1 or -1 when the least-squares slope of
+   %  y against its index is positive or negative by more than its
+   %  rounding error, and 0 otherwise. ey bounds the rounding error of each
+   %  value of y.
+   %
+   %  The slope has the sign of its numerator N = sum((k - kbar).*y),
+   %  because its denominator is positive. k - kbar is exact for the index
+   %  k. N carries at most sum(abs(k - kbar))*ey from the values of y, and
+   %  the sum rounds by at most L*u*sum(abs(k - kbar))*max(abs(y)), with
+   %  L = numel(y) and u = eps/2.
+   %
+   %  See also: islineconvex, islinepositive
+
+   % The centred index makes the numerator carry the slope sign.
+   y = y(:);
+   L = numel(y);
+   k = (1:L)' - (L + 1)/2;
+   N = sum(k .* y);
+
+   % A trend counts only beyond the rounding bound of its numerator.
+   tol = sum(abs(k)) * (ey + L * (eps/2) * max(abs(y)));
+   sg = (N > tol) - (N < -tol);
+end
diff --git a/toolbox/functionSignatures.json b/toolbox/functionSignatures.json
index 709c191..22740b2 100644
--- a/toolbox/functionSignatures.json
+++ b/toolbox/functionSignatures.json
@@ -110,7 +110,8 @@
          {"name":"rmin",         "kind":"namevalue",  "type":["double","scalar"]},
          {"name":"rmconvex",     "kind":"namevalue",  "type":["logical","scalar"],"purpose":"Option"},
          {"name":"rmnochange",   "kind":"namevalue",  "type":["logical","scalar"],"purpose":"Option"},
-         {"name":"rmrain",       "kind":"namevalue",  "type":["logical","scalar"],"purpose":"Option"}
+         {"name":"rmrain",       "kind":"namevalue",  "type":["logical","scalar"],"purpose":"Option"},
+         {"name":"qerror",       "kind":"namevalue",  "type":["double","scalar",">=0"]}
       ]
    },
    "baseflow.eventpicker":

From 62febf8b66b5ac03c0b7974b81af0f9c3bb98449 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Sat, 24 Oct 2026 14:11:18 -0700
Subject: [PATCH 26/28] fix(baseflow): reject unsupported sloped porosity
 requests

---
 tests/TestBaseflow.m                    |  21 +++++
 tests/test_flatcontract.m               | 117 ++++++++++++++++++++++++
 toolbox/+baseflow/cloudphi.m            |  10 +-
 toolbox/+baseflow/eventphi.m            |   5 +
 toolbox/+baseflow/fitphi.m              |  18 +++-
 toolbox/+baseflow/globalfit.m           |   5 +
 toolbox/+baseflow/private/requireflat.m |  14 +++
 toolbox/functionSignatures.json         |  21 ++---
 8 files changed, 193 insertions(+), 18 deletions(-)
 create mode 100644 tests/test_flatcontract.m
 create mode 100644 toolbox/+baseflow/private/requireflat.m

diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index e6879ed..0811fc6 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -193,6 +193,27 @@ function test_kuparukRecessionExponent(testCase)
             'AbsTol', testCase.btol)
       end
 
+      function test_globalFitRejectsSlopedBeforeBootstrap(testCase)
+         % Invalid geometry must stop before bootstrap and figure work.
+         C = testCase.Chain;
+         opts = C.opts;
+         opts.isflat = false;
+         opts.bootfit = true;
+         opts.plotfits = true;
+         state = rng;
+         testCase.addTeardown(@() rng(state));
+         figures = findall(groot,'Type','figure');
+         phiMethods = {'pointcloud','distfit','phicombo'};
+         for k = 1:numel(phiMethods)
+            opts.phimethod = phiMethods{k};
+            testCase.verifyError(@() baseflow.globalfit( ...
+               C.K,C.Events,C.Fits,opts), ...
+               'baseflow:unsupportedSlopedAquifer');
+         end
+         testCase.verifyEqual(rng,state);
+         testCase.verifyEqual(findall(groot,'Type','figure'),figures);
+      end
+
       function test_globalFitUsesTheTail(testCase)
          % The tail starts at the tau0 sample and holds no tau below it. The
          % mean tau follows tau0 and b, and the expected flows follow a, b,
diff --git a/tests/test_flatcontract.m b/tests/test_flatcontract.m
new file mode 100644
index 0000000..92311ed
--- /dev/null
+++ b/tests/test_flatcontract.m
@@ -0,0 +1,117 @@
+classdef test_flatcontract < matlab.unittest.TestCase
+   %TEST_FLATCONTRACT Flat porosity values and early unsupported-call errors.
+   properties (TestParameter)
+      rejected = {'directFalse','cloudFalse','globalFalse','eventShort', ...
+         'eventLong','cloudShort','cloudLong','directShort','directLong', ...
+         'allPairs','directEmpty','cloudEmpty','directVector'}
+      flatPair = {'linear','nonlinear'}
+   end
+   methods (TestMethodSetup)
+      function preserveState(testCase)
+         %PRESERVESTATE Restore random state and close test-created figures.
+         rng_original = rng;
+         testCase.addTeardown(@() rng(rng_original));
+         figures_original = findall(groot,'Type','figure');
+         testCase.addTeardown(@() closenewfigs(figures_original));
+      end
+   end
+   methods (Test)
+      function rejectsBeforeWork(testCase,rejected)
+         %REJECTSBEFOREWORK Reject before RNG or figure changes.
+         q = 2*ones(10,1); dqdt = -0.5*ones(10,1);
+         rng(109); rng_expected = rng;
+         figures_expected = findall(groot,'Type','figure');
+         error_expected = 'baseflow:unsupportedSlopedAquifer';
+         switch rejected
+            case 'directFalse'
+               call = @() baseflow.fitphi(1,1,1,100,2,10, ...
+                  'isflat',false,'soln1','PK62','soln2','BS03');
+            case 'directEmpty'
+               call = @() baseflow.fitphi(1,1,1,100,2,10, ...
+                  'isflat',logical([]),'soln1','PK62','soln2','BS03');
+            case 'directVector'
+               call = @() baseflow.fitphi(1,1,1,100,2,10, ...
+                  'isflat',[true,true],'soln1','PK62','soln2','BS03');
+            case 'cloudEmpty'
+               call = @() baseflow.cloudphi(q,dqdt,1,100,2,10, ...
+                  'envelope','isflat',logical([]),'plotfit',true);
+            case 'cloudFalse'
+               call = @() baseflow.cloudphi(q,dqdt,1,100,2,10, ...
+                  'envelope','isflat',false,'plotfit',true);
+            case 'globalFalse'
+               % These parser-valid structs cannot reach eventtau safely.
+               call = @() baseflow.globalfit(struct(), ...
+                  struct('inputFlow',[]),struct(),'isflat',false, ...
+                  'bootfit',true,'plotfits',true);
+            case 'eventShort'
+               call = @() baseflow.eventphi(struct(),struct(),100,2,10,1, ...
+                  'soln1','BR94','soln2','BR94');
+            case 'eventLong'
+               call = @() baseflow.eventphi(struct(),struct(),100,2,10,1, ...
+                  'soln1','Brutsaert, 1994', ...
+                  'soln2','Rupp and Selker, 2006 b=1');
+            case 'cloudShort'
+               call = @() baseflow.cloudphi(q,dqdt,1,100,2,10, ...
+                  'envelope','soln2','RS06b1','plotfit',true);
+            case 'cloudLong'
+               call = @() baseflow.cloudphi(q,dqdt,1,100,2,10, ...
+                  'envelope','soln1','Brutsaert, 1994','plotfit',true);
+            case 'directShort'
+               call = @() baseflow.fitphi(1,1,1.5,100,2,10, ...
+                  'soln1','BR94','soln2','RS06');
+            case 'directLong'
+               call = @() baseflow.fitphi(1,1,1.5,100,2,10, ...
+                  'soln1','Brutsaert, 1994', ...
+                  'soln2','Rupp and Selker, 2006 b=f(n)');
+            case 'allPairs'
+               call = @() baseflow.fitphi(1,1,1.5,100,2,10, ...
+                  'soln1','all','soln2','all');
+         end
+         testCase.verifyError(call,error_expected);
+         rng_returned = rng;
+         figures_returned = findall(groot,'Type','figure');
+         testCase.verifyEqual(rng_returned,rng_expected);
+         testCase.verifyEqual(figures_returned,figures_expected);
+      end
+      function literalFlatSolutions(testCase,flatPair)
+         %LITERALFLATSOLUTIONS Check flat values from forward coefficients.
+         % Forward PK62/Boussinesq coefficients for k=1 and phi=0.1.
+         phi_expected = 0.1;
+         descriptionCount_expected = 2;
+         tolerance = 2e-14;
+         if strcmp(flatPair,'linear')
+            a2 = 0.6579736267392905; b2 = 1; late = 'BS03';
+         else
+            a2 = 0.4804; b2 = 1.5; late = 'BS04';
+         end
+         [phi_returned,names_returned,description_returned] = ...
+            baseflow.fitphi(0.0141625,a2,b2,100,2,10, ...
+            'soln1','PK62','soln2',late);
+         names_expected = {['PK62_' late]};
+         testCase.verifyEqual(phi_returned,phi_expected,'AbsTol',tolerance);
+         testCase.verifyEqual(names_returned,names_expected);
+         testCase.verifyNumElements( ...
+            description_returned,descriptionCount_expected);
+      end
+      function literalPublicRouting(testCase,flatPair)
+         %LITERALPUBLICROUTING Check flat solutions through public callers.
+         % Repeated points make every early/late quantile the same point.
+         tolerance = 2e-14;
+         if strcmp(flatPair,'linear')
+            b2 = 1; phi_expected = 0.077226115743088686;
+         else
+            b2 = 1.5; phi_expected = 0.11872402921012785;
+         end
+         q = 2*ones(10,1); dqdt = -0.5*ones(10,1);
+         cloud_returned = baseflow.cloudphi(q,dqdt,b2,100,2,10,'envelope', ...
+            'plotfit',false);
+         fits = struct('q',q,'dqdt',dqdt,'eventTags',ones(10,1));
+         event_returned = baseflow.eventphi( ...
+            struct('eventTag',1),fits,100,2,10,b2);
+         testCase.verifyEqual(cloud_returned,phi_expected, ...
+            'AbsTol',tolerance);
+         testCase.verifyEqual(event_returned,phi_expected, ...
+            'AbsTol',tolerance);
+      end
+   end
+end
diff --git a/toolbox/+baseflow/cloudphi.m b/toolbox/+baseflow/cloudphi.m
index 784e24d..6651f9e 100644
--- a/toolbox/+baseflow/cloudphi.m
+++ b/toolbox/+baseflow/cloudphi.m
@@ -51,6 +51,11 @@
    %                 the early-time and fitted late-time lines, and the phi
    %                 legend. Default is true.
    %
+   % Only flat fits are supported. isflat=false and sloped solution names
+   % raise baseflow:unsupportedSlopedAquifer before fitting or plotting.
+   % The function selects flat pairs from blate (or userab). soln1, soln2
+   % and theta are retained compatibility options, not a sloped workflow.
+   %
    % See also: eventphi, fitphi, fitphidist
    %
    % Matt Cooper, 04-Nov-2022, https://github.com/mgcooper
@@ -63,8 +68,11 @@
 
    % parse inputs
    [q, dqdt, blate, A, D, L, method, earlyqtls, lateqtls, userab, mask, ...
-      ~, isflat, ~, ~, dispfit, plotfit] = parseinputs(q, dqdt, blate, ...
+      ~, isflat, soln1, soln2, dispfit, plotfit] = parseinputs( ...
+      q, dqdt, blate, ...
       A, D, L, method, varargin{:});
+   % Reject unsupported geometry before fitting or drawing samples.
+   requireflat(isflat,soln1,soln2);
 
    % the easiest way to get a1/a2 is pointcloudintercept. baseflow.fitab could
    % also be used but this function is intended to fit phi once b is known (or
diff --git a/toolbox/+baseflow/eventphi.m b/toolbox/+baseflow/eventphi.m
index 54583a4..35573bc 100644
--- a/toolbox/+baseflow/eventphi.m
+++ b/toolbox/+baseflow/eventphi.m
@@ -36,6 +36,9 @@
    %     soln1       String indicating early-time theoretical solution.
    %     soln2       String indicating late-time theoretical solution.
    %
+   % Sloped solution names raise baseflow:unsupportedSlopedAquifer before
+   % reading event data or fitting. This function has no isflat/theta option.
+   %
    % See also: cloudphi, fitphi, fitphidist
    %
    % Matt Cooper, 04-Nov-2022, https://github.com/mgcooper
@@ -46,6 +49,8 @@
    % PARSE INPUTS
    [Results, Fits, A, D, L, b2, earlyqtls, lateqtls, soln1, soln2] = ...
       parseinputs(Results, Fits, A, D, L, blate, varargin{:});
+   % Reject unsupported geometry before fitting or drawing samples.
+   requireflat(true,soln1,soln2);
 
    % warning off % commented out for octave, need msgid
 
diff --git a/toolbox/+baseflow/fitphi.m b/toolbox/+baseflow/fitphi.m
index 4251e07..dad7446 100644
--- a/toolbox/+baseflow/fitphi.m
+++ b/toolbox/+baseflow/fitphi.m
@@ -24,11 +24,16 @@
    % Optional inputs
    %
    %     theta    effective slope of basin contributing area
-   %     isflat   logical flag indicating horizontal or sloped aquifer solution
+   %     isflat   true only; false raises an unsupported-workflow error
    %     soln1    optional early-time theoretical solution
    %     soln2    optional late-time theoretical solution
    %     dispfit  logical flag indicating whether to print each phi value
    %
+   % Theta remains a compatibility input and is unused for flat solutions.
+   % Sloped pairs and all-pair requests raise
+   % baseflow:unsupportedSlopedAquifer. The raw sloped formulas and catalog
+   % below are retained for research; they are not qualified callable results.
+   %
    % Example
    %
    %  Estimate drainable porosity from typical early-time (a1) and late-time
@@ -94,6 +99,8 @@
    % PARSE INPUTS
    [a1, a2, b2, A, D, L, theta, isflat, dispfit, soln1, soln2] = ...
       parseinputs(a1, a2, b2, A, D, L, varargin{:});
+   % Reject unsupported geometry before fitting or drawing samples.
+   requireflat(isflat,soln1,soln2);
 
    % MAIN FUNCTION
 
@@ -212,12 +219,13 @@
 
             % phi = c1c2/a1a2;
 
+            % These diagnostic relations do not contribute to returned phi.
             % multiply by *100/86400 to go from m/d to cm/s
-            k1 = 1.133/(D^3*L^2*a1*c1c2/a1a2);   % early
-            k2 = ((a2*A^(3/2)*c1c2/a1a2)/(4.804*L))^2;
+            % k1 = 1.133/(D^3*L^2*a1*c1c2/a1a2);   % early
+            % k2 = ((a2*A^(3/2)*c1c2/a1a2)/(4.804*L))^2;
 
             % compute Q0
-            Q0 = 3.448*k1*D^2*L^2/A; % or: 3.448*k1*D^2*Dd*L if Dd is used
+            % Q0 = 3.448*k1*D^2*L^2/A; % or: 3.448*k1*D^2*Dd*L if Dd is used
 
             % once phi and k are known, we can check D
 
@@ -311,7 +319,7 @@
          b2 = 1;
       end
    else
-      if strcmp(soln1,'RS05') && (b2 < 3/2 || b2>=2)
+      if strcmp(soln2,'RS05') && (b2 < 3/2 || b2>=2)
          warning('baseflow:fitphi:incompatibleLateTimeSolution', ...
             ['Requested late-time solution (Rupp and Selker, 2005) ' ...
             'is incompatible with b<1.5 or b>=2, using Boussinesq, 1903, b=1'])
diff --git a/toolbox/+baseflow/globalfit.m b/toolbox/+baseflow/globalfit.m
index 427271f..b14ab05 100644
--- a/toolbox/+baseflow/globalfit.m
+++ b/toolbox/+baseflow/globalfit.m
@@ -38,6 +38,9 @@
    %     fprintf('b = %.2f, tau = %.0f days, phi = %.3f\n', ...
    %        GlobalFit.b, GlobalFit.tau, GlobalFit.phi)
    %
+   % Only flat aquifer fits are supported. isflat=false raises
+   % baseflow:unsupportedSlopedAquifer before fitting or plotting.
+   %
    % See also: setopts, getevents, fitevents, fitphi, eventphi, eventtau
    %
    % Matt Cooper, 22-Oct-2022, https://github.com/mgcooper
@@ -185,6 +188,8 @@
    earlyqtls   = parser.Results.earlyqtls;
    lateqtls    = parser.Results.lateqtls;
    isflat      = parser.Results.isflat;
+   % Reject unsupported geometry before fitting or drawing samples.
+   requireflat(isflat,'','');
 
    % if stream length and drainage density are both provided, check that they
    % are consistent with the provided area. note: Dd comes in as 1/km b/c that's
diff --git a/toolbox/+baseflow/private/requireflat.m b/toolbox/+baseflow/private/requireflat.m
new file mode 100644
index 0000000..8329aa8
--- /dev/null
+++ b/toolbox/+baseflow/private/requireflat.m
@@ -0,0 +1,14 @@
+function requireflat(isflat,soln1,soln2)
+   %REQUIREFLAT Reject unsupported sloped porosity requests before fitting.
+   % Raw sloped formulas remain in fitphi for research, not callable results.
+   sloped = {'BR94','RS06','RS06b1','Brutsaert, 1994', ...
+      'Rupp and Selker, 2006 b=1','Rupp and Selker, 2006 b=f(n)','all'};
+   % Empty logical inputs must not pass through an unsupported geometry path.
+   if ~isscalar(isflat) || ~isflat || any(strcmpi(soln1,sloped)) || ...
+         any(strcmpi(soln2,sloped))
+      error('baseflow:unsupportedSlopedAquifer', ...
+         ['Sloped porosity workflows and all-pair requests ' ...
+         'are unsupported. ' ...
+         'Use isflat=true and a supported flat solution pair.']);
+   end
+end
diff --git a/toolbox/functionSignatures.json b/toolbox/functionSignatures.json
index 22740b2..636da52 100644
--- a/toolbox/functionSignatures.json
+++ b/toolbox/functionSignatures.json
@@ -81,8 +81,8 @@
          {"name":"mask",      "kind": "namevalue", "type": ["vector","logical"]},
          {"name":"theta",     "kind": "namevalue", "type": ["scalar","double"]},
          {"name":"isflat",    "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"},
-         {"name":"soln1",     "kind": "namevalue", "type": ["char", "choices={'Polubarinova-Kochina, 1962','Rupp and Selker, 2005','Brutsaert, 1994','PK62','RS05','BR94'}"],"default":"'Rupp and Selker, 2005'","purpose":"Option"},
-         {"name":"soln2",     "kind": "namevalue", "type": ["char", "choices={'Boussinesq, 1904 b=3/2','Rupp and Selker, 2005 b=f(n)','Boussinesq, 1903 b=1','Brutsaert, 1994','Rupp and Selker, 2006 b=1','Rupp and Selker, 2006 b=f(n)','BS04','BS03','BR94','RS06b1','RS06','RS05'}"],"default":"'RS05bn'","purpose":"Option"},
+         {"name":"soln1",     "kind": "namevalue", "type": ["char", "choices={'Polubarinova-Kochina, 1962','Rupp and Selker, 2005','PK62','RS05'}"],"default":"'Rupp and Selker, 2005'","purpose":"Option"},
+         {"name":"soln2",     "kind": "namevalue", "type": ["char", "choices={'Boussinesq, 1904 b=3/2','Rupp and Selker, 2005 b=f(n)','Boussinesq, 1903 b=1','BS04','BS03','RS05'}"],"default":"'RS05'","purpose":"Option"},
          {"name":"dispfit",   "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"},
          {"name":"plotfit",   "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"}
       ]
@@ -144,19 +144,16 @@
    {
       "inputs":
       [
-         {"name":"Results",   "kind": "required",  "type": ["table"]},
+         {"name":"Results",   "kind": "required",  "type": ["struct"]},
          {"name":"Fits",      "kind": "required",  "type": ["struct"]},
          {"name":"A",         "kind": "required",  "type": ["scalar","double"]},
          {"name":"D",         "kind": "required",  "type": ["scalar","double"]},
          {"name":"L",         "kind": "required",  "type": ["scalar","double"]},
          {"name":"blate",     "kind": "required",  "type": ["scalar","double"]},
-         {"name":"method",    "kind": "required",  "type": ["char", "choices={'mean','median','envelope'}"],"default":"'median'","purpose":"Option"},
-         {"name":"refqtls",   "kind": "namevalue", "type": ["vector","double"]},
-         {"name":"theta",     "kind": "namevalue", "type": ["scalar","double"]},
-         {"name":"isflat",    "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"},
-         {"name":"soln1",     "kind": "namevalue", "type": ["char", "choices={'Polubarinova-Kochina, 1962','Rupp and Selker, 2005','Brutsaert, 1994','PK62','RS05','BR94'}"],"default":"'Rupp and Selker, 2005'","purpose":"Option"},
-         {"name":"soln2",     "kind": "namevalue", "type": ["char", "choices={'Boussinesq, 1904 b=3/2','Rupp and Selker, 2005 b=f(n)','Boussinesq, 1903 b=1','Brutsaert, 1994','Rupp and Selker, 2006 b=1','Rupp and Selker, 2006 b=f(n)','BS04','BS03','BR94','RS06b1','RS06','RS05'}"],"default":"'RS05bn'","purpose":"Option"},
-         {"name":"dispfit",   "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"}
+         {"name":"earlyqtls", "kind": "namevalue", "type": ["vector","double"]},
+         {"name":"lateqtls",  "kind": "namevalue", "type": ["vector","double"]},
+         {"name":"soln1",     "kind": "namevalue", "type": ["char", "choices={'Polubarinova-Kochina, 1962','Rupp and Selker, 2005','PK62','RS05'}"],"default":"''","purpose":"Option"},
+         {"name":"soln2",     "kind": "namevalue", "type": ["char", "choices={'Boussinesq, 1904 b=3/2','Rupp and Selker, 2005 b=f(n)','Boussinesq, 1903 b=1','BS04','BS03','RS05'}"],"default":"''","purpose":"Option"}
       ]
    },
    "baseflow.eventtau":
@@ -247,8 +244,8 @@
          {"name":"theta",     "kind": "namevalue", "type": ["scalar","double"]},
          {"name":"isflat",    "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"},
          {"name":"dispfit",   "kind": "namevalue", "type": ["logical","scalar"],"purpose":"Option"},
-         {"name":"soln1",     "kind": "namevalue", "type": ["char", "choices={'Polubarinova-Kochina, 1962','Rupp and Selker, 2005','Brutsaert, 1994','PK62','RS05','BR94'}"],"default":"'Rupp and Selker, 2005'","purpose":"Option"},
-         {"name":"soln2",     "kind": "namevalue", "type": ["char", "choices={'Boussinesq, 1904 b=3/2','Rupp and Selker, 2005 b=f(n)','Boussinesq, 1903 b=1','Brutsaert, 1994','Rupp and Selker, 2006 b=1','Rupp and Selker, 2006 b=f(n)','BS04','BS03','BR94','RS06b1','RS06','RS05'}"],"default":"'RS05bn'","purpose":"Option"}
+         {"name":"soln1",     "kind": "namevalue", "type": ["char", "choices={'Polubarinova-Kochina, 1962','Rupp and Selker, 2005','PK62','RS05'}"],"default":"'Rupp and Selker, 2005'","purpose":"Option"},
+         {"name":"soln2",     "kind": "namevalue", "type": ["char", "choices={'Boussinesq, 1904 b=3/2','Rupp and Selker, 2005 b=f(n)','Boussinesq, 1903 b=1','BS04','BS03','RS05'}"],"default":"'RS05'","purpose":"Option"}
       ]
    },
    "baseflow.fitphidist":

From bda74bc379db32587fc19c7e34498f0863f4ff8f Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Sat, 24 Oct 2026 14:11:18 -0700
Subject: [PATCH 27/28] feat(baseflow): add descriptive bootstrap percentile
 summaries

---
 tests/test_bootstrappercentiles.m             | 131 ++++++++++++++++++
 .../+internal/bootstrappercentiles.m          |  41 ++++++
 toolbox/+baseflow/plfitb.m                    |  13 ++
 3 files changed, 185 insertions(+)
 create mode 100644 tests/test_bootstrappercentiles.m
 create mode 100644 toolbox/+baseflow/+internal/bootstrappercentiles.m

diff --git a/tests/test_bootstrappercentiles.m b/tests/test_bootstrappercentiles.m
new file mode 100644
index 0000000..6814b94
--- /dev/null
+++ b/tests/test_bootstrappercentiles.m
@@ -0,0 +1,131 @@
+classdef test_bootstrappercentiles < matlab.unittest.TestCase
+   %TEST_BOOTSTRAPPERCENTILES Literal quantiles and real public bootstrap use.
+   properties (TestParameter)
+      invalid = {NaN,Inf,-Inf}
+   end
+   methods (TestMethodSetup)
+      function preserveState(testCase)
+         %PRESERVESTATE Restore the random state after each test.
+         rng_original = rng;
+         testCase.addTeardown(@() rng(rng_original));
+      end
+   end
+   methods (Test)
+      function literalSkewedQuantiles(testCase)
+         %LITERALSKEWEDQUANTILES Verify fixed endpoints for a skewed sample.
+         probabilities_expected = [0.025,0.975];
+         method_expected = 'midpoint';
+         bounds_expected = [1.5,519.5];
+         sampleCount_expected = 40;
+         reps = struct('b',[1:39,1000]');
+         returned = baseflow.internal.bootstrappercentiles(reps);
+         testCase.verifyEqual( ...
+            returned.probabilities,probabilities_expected);
+         testCase.verifyEqual(returned.method,method_expected);
+         testCase.verifyEqual(returned.b.bounds,bounds_expected);
+         testCase.verifyTrue(returned.b.available);
+         testCase.verifyEqual(returned.b.sampleCount,sampleCount_expected);
+         testCase.verifyEqual(returned.b.invalidCount,0);
+      end
+      function constantQuantiles(testCase)
+         %CONSTANTQUANTILES Keep both endpoints at the constant value.
+         bounds_expected = [7,7];
+         returned = baseflow.internal.bootstrappercentiles( ...
+            struct('b',7*ones(40,1)));
+         testCase.verifyEqual(returned.b.bounds,bounds_expected);
+      end
+      function neverDiscardsInvalidSamples(testCase,invalid)
+         %NEVERDISCARDSINVALIDSAMPLES Mark nonfinite replicates unavailable.
+         reason_expected = 'nonfiniteReplicates';
+         sampleCount_expected = 40;
+         returned = baseflow.internal.bootstrappercentiles( ...
+            struct('b',[1:39,invalid]'));
+         testCase.verifyFalse(returned.b.available);
+         testCase.verifyTrue(all(isnan(returned.b.bounds)));
+         testCase.verifyEqual(returned.b.reason,reason_expected);
+         testCase.verifyEqual(returned.b.sampleCount,sampleCount_expected);
+         testCase.verifyEqual(returned.b.invalidCount,1);
+      end
+      function emptyReplicatesHaveNoBounds(testCase)
+         %EMPTYREPLICATESHAVENOBOUNDS Report an empty sample explicitly.
+         reason_expected = 'emptyReplicates';
+         returned = baseflow.internal.bootstrappercentiles(struct('b',[]));
+         testCase.verifyEqual(returned.b.reason,reason_expected);
+         testCase.verifyFalse(returned.b.available);
+         testCase.verifyEqual(returned.b.sampleCount,0);
+      end
+      function publicBootstrapUsesLiteralOrderWeights(testCase)
+         %PUBLICBOOTSTRAPUSESLITERALORDERWEIGHTS Check public output bounds.
+         sampleCount_expected = 50;
+         relativeTolerance = 2e-14;
+         bTolerance = 2e-16;
+         tauTolerance = 2e-14;
+         u = ((1:200)'-0.5)/200;
+         x = 10*(1-u).^(-1/2.5);
+         rng(71);
+         fit_returned = baseflow.plfitb(x,'bootfit',true,'bootreps',50);
+         names = {'alpha','b','tau0','tau','ntail'};
+         for k = 1:numel(names)
+            name = names{k}; values = sort(fit_returned.reps.(name));
+            % For n=50, midpoint knots give these fixed endpoint weights.
+            expected = [0.25*values(1)+0.75*values(2), ...
+               0.75*values(49)+0.25*values(50)];
+            summary_returned = fit_returned.Percentiles.(name);
+            testCase.verifyTrue(summary_returned.available);
+            testCase.verifyEqual(summary_returned.bounds,expected, ...
+               'RelTol',relativeTolerance);
+            testCase.verifyEqual( ...
+               summary_returned.sampleCount,sampleCount_expected);
+         end
+         % Propagation fields remain one-sigma quantities.
+         bSigma_returned = fit_returned.b_H-fit_returned.b;
+         bSigma_expected = fit_returned.BootFit.b_sig;
+         tauSigma_returned = fit_returned.tau_H-fit_returned.tau;
+         tauSigma_expected = fit_returned.BootFit.tau_sig;
+         testCase.verifyEqual(bSigma_returned,bSigma_expected, ...
+            'AbsTol',bTolerance);
+         testCase.verifyEqual(tauSigma_returned,tauSigma_expected, ...
+            'AbsTol',tauTolerance);
+      end
+      function publicPoleKeepsFiniteParameterSummaries(testCase)
+         %PUBLICPOLEKEEPSFINITEPARAMETERSUMMARIES Limit pole effects to tau.
+         reason_expected = 'tauPole';
+         sampleCount_expected = 50;
+         testCase.applyFixture( ...
+            matlab.unittest.fixtures.SuppressedWarningsFixture( ...
+            'baseflow:expectedtau:tauPole'));
+         u = ((1:200)'-0.5)/200; x = 10*(1-u).^(-1/1.05);
+         rng(1);
+         fit_returned = baseflow.plfitb(x,'bootfit',true,'bootreps',50);
+         poleCount_expected = nnz(fit_returned.reps.alpha<=2);
+         testCase.verifyGreaterThan(poleCount_expected,0);
+         testCase.verifyFalse(fit_returned.Percentiles.tau.available);
+         testCase.verifyEqual( ...
+            fit_returned.Percentiles.tau.reason,reason_expected);
+         testCase.verifyEqual( ...
+            fit_returned.Percentiles.tau.poleCount,poleCount_expected);
+         testCase.verifyEqual( ...
+            fit_returned.Percentiles.tau.invalidCount,poleCount_expected);
+         testCase.verifyNumElements( ...
+            fit_returned.reps.tau,sampleCount_expected);
+         testCase.verifyTrue(fit_returned.Percentiles.b.available);
+         testCase.verifyTrue(fit_returned.Percentiles.alpha.available);
+      end
+      function noBootstrapDoesNotInventEvidence(testCase)
+         %NOBOOTSTRAPDOESNOTINVENTEVIDENCE Keep unavailable bounds explicit.
+         reason_expected = 'notBootstrapped';
+         u = ((1:200)'-0.5)/200; x = 10*(1-u).^(-1/2.5);
+         fit_returned = baseflow.plfitb(x);
+         testCase.verifyFalse(fit_returned.Percentiles.b.available);
+         testCase.verifyEqual( ...
+            fit_returned.Percentiles.b.reason,reason_expected);
+         testCase.verifyEqual(fit_returned.Percentiles.b.sampleCount,0);
+         testCase.verifyEqual(fit_returned.b_L,fit_returned.b);
+         testCase.verifyEqual(fit_returned.b_H,fit_returned.b);
+         [b_returned,alpha_returned,tau0_returned] = baseflow.plfitb(x);
+         returned = [b_returned,alpha_returned,tau0_returned];
+         expected = [fit_returned.b,fit_returned.alpha,fit_returned.tau0];
+         testCase.verifyEqual(returned,expected);
+      end
+   end
+end
diff --git a/toolbox/+baseflow/+internal/bootstrappercentiles.m b/toolbox/+baseflow/+internal/bootstrappercentiles.m
new file mode 100644
index 0000000..9584ced
--- /dev/null
+++ b/toolbox/+baseflow/+internal/bootstrappercentiles.m
@@ -0,0 +1,41 @@
+function summary = bootstrappercentiles(reps)
+   %BOOTSTRAPPERCENTILES Summarize retained bootstrap samples without omission.
+   % The midpoint convention linearly interpolates sorted samples at
+   % probabilities (k-0.5)/n and clamps values beyond the endpoint knots.
+   % Missing fields mean no bootstrap was requested. Nonfinite samples make
+   % that parameter unavailable; no sample is removed or replaced.
+   if nargin == 0
+      reps = struct();
+   end
+   summary.probabilities = [0.025,0.975];
+   summary.method = 'midpoint';
+   names = {'alpha','b','tau0','tau','ntail'};
+   for k = 1:numel(names)
+      name = names{k};
+      item = struct('bounds',[NaN,NaN],'available',false, ...
+         'sampleCount',0,'invalidCount',0,'poleCount',0, ...
+         'reason','notBootstrapped');
+      if isfield(reps,name)
+         values = reps.(name);
+         item.sampleCount = numel(values);
+         item.invalidCount = nnz(~isfinite(values));
+         if strcmp(name,'tau') && isfield(reps,'alpha')
+            item.poleCount = nnz(reps.alpha<=2);
+         end
+         if isempty(values)
+            item.reason = 'emptyReplicates';
+         elseif item.poleCount>0
+            item.reason = 'tauPole';
+         elseif item.invalidCount>0
+            item.reason = 'nonfiniteReplicates';
+         else
+            % MATLAB exact and Octave method 5 use midpoint interpolation.
+            item.bounds = reshape(quantile(values(:), ...
+               summary.probabilities),1,[]);
+            item.available = true;
+            item.reason = '';
+         end
+      end
+      summary.(name) = item;
+   end
+end
diff --git a/toolbox/+baseflow/plfitb.m b/toolbox/+baseflow/plfitb.m
index 0b0dd1f..58a4c00 100644
--- a/toolbox/+baseflow/plfitb.m
+++ b/toolbox/+baseflow/plfitb.m
@@ -18,6 +18,16 @@
    %     there. A bootstrap replicate beyond the pole makes tau_sig, tau_L,
    %     and tau_H NaN. plfitb then warns with baseflow:expectedtau:tauPole.
    %
+   % Fit.Percentiles summarizes retained alpha, b, tau0, tau and ntail
+   % bootstrap samples at probabilities [0.025,0.975]. Each parameter has
+   % bounds, available, sampleCount, invalidCount, poleCount and reason.
+   % The midpoint method linearly interpolates sorted values at (k-0.5)/n
+   % and clamps beyond endpoint knots. These descriptive percentiles do not
+   % establish coverage. The one-sigma and BootFit fields remain separate.
+   % A nonfinite sample makes that parameter unavailable; samples are never
+   % discarded or redrawn. Tau poles are counted separately. No bootstrap
+   % gives unavailable bounds with reason notBootstrapped.
+   %
    % Required inputs
    %
    %     x        data believed to follow an untruncated Pareto distribution
@@ -110,6 +120,8 @@
       Fit.reps = BootFit.reps;
       BootFit = rmfield(BootFit,'reps');
       Fit.BootFit = BootFit;
+      % Describe the retained draws without changing uncertainty propagation.
+      Fit.Percentiles = baseflow.internal.bootstrappercentiles(Fit.reps);
    else
       % assign null confidence bounds so other functions will work
       Fit.b_L = Fit.b;
@@ -120,6 +132,7 @@
       Fit.tau0_H = Fit.tau0;
       Fit.tau_L = Fit.tau;
       Fit.tau_H = Fit.tau;
+      Fit.Percentiles = baseflow.internal.bootstrappercentiles();
    end
 
    % also: b = (2*k+1)/(k+1)

From ba668ee430ef9f1324b6a530032d3f297e8ba5a0 Mon Sep 17 00:00:00 2001
From: mgcooper <mguycooper@gmail.com>
Date: Wed, 28 Oct 2026 15:52:00 -0700
Subject: [PATCH 28/28] fix: stabilize event-scale nonlinear power-law fits

Scale event inputs before nonlinear fitting and restore coefficients and
confidence bounds to their original units. Reject nonconverged curve fits
while preserving the solver order and power-law model.

Add ten public-entry conditioning regressions and adopt the owner-approved
Kuparuk software reference 1.3650 with the existing 0.0005 tolerance.

Validation: 613/613 native R2025b tests; R2025b Mac/Linux and R2026a Mac
Kuparuk captures agree. Configured review accepted the four-file candidate.
---
 tests/TestBaseflow.m                      |  11 +-
 tests/test_fitab_conditioning.m           | 247 ++++++++++++++++++++++
 toolbox/+baseflow/fitab.m                 |   5 +
 toolbox/+baseflow/private/fitNLS_matlab.m |  96 ++++-----
 4 files changed, 303 insertions(+), 56 deletions(-)
 create mode 100644 tests/test_fitab_conditioning.m

diff --git a/tests/TestBaseflow.m b/tests/TestBaseflow.m
index 0811fc6..5e86682 100644
--- a/tests/TestBaseflow.m
+++ b/tests/TestBaseflow.m
@@ -42,12 +42,11 @@
       Dd = 0.8
       D = 0.47
 
-      % The recession exponent of the Kuparuk annual workflow, and the
-      % rounding of that value. With the numerical-zero rule of
-      % eventfinder, R2025b gives 1.346467 and R2026a 1.346470. R2024b
-      % selects the same events but gives 1.3577, because its per-event
-      % fits differ, so this check fails on R2024b.
-      kuparukb = 1.3465
+      % The Kuparuk annual workflow gives 1.3650481543 with event-scale
+      % NLS conditioning on R2025b (Mac and Linux) and R2026a (Mac).
+      % The rounded software reference keeps the same absolute tolerance.
+      % R2024b has not been qualified with this conditioning repair.
+      kuparukb = 1.3650
       btol = 5e-4
 
       % The synthetic recessions follow -dQ/dt = a*Q^b for eight days. The
diff --git a/tests/test_fitab_conditioning.m b/tests/test_fitab_conditioning.m
new file mode 100644
index 0000000..73058ef
--- /dev/null
+++ b/tests/test_fitab_conditioning.m
@@ -0,0 +1,247 @@
+classdef test_fitab_conditioning < matlab.unittest.TestCase
+   % Public NLS fitting must not depend on discharge units or roundoff.
+   % The saved vectors derive from the public Kuparuk fixture. Events 77,
+   % 62 and 38 are checksum-bound in the October 28 repair evidence.
+
+   properties (TestParameter)
+      Event = {77, 62, 38}
+   end
+
+   properties (Constant, Access=private)
+      % Roundoff must remain much smaller than the scientific btol=5e-4.
+      exponentTolerance = 1e-6
+      intervalTolerance = 2e-5
+      coefficientTolerance = 1e-4
+   end
+
+   methods (Test)
+      function savedInputPerturbations(testCase,Event)
+         [q1,d1,q2,d2] = testCase.vectors(Event);
+         [expected,ok1] = baseflow.fitab(q1,d1,'nls');
+         [returned,ok2] = baseflow.fitab(q2,d2,'nls');
+         testCase.verifyTrue(ok1 && ok2);
+         testCase.verifyEqual(returned.b,expected.b, ...
+            'AbsTol',testCase.exponentTolerance);
+         testCase.verifyEqual([returned.bL returned.bH], ...
+            [expected.bL expected.bH],'AbsTol',testCase.intervalTolerance);
+      end
+
+      function physicalUnitInvariance(testCase,Event)
+         [q,dqdt] = testCase.vectors(Event);
+         unitScale = 1e6;
+         expected = baseflow.fitab(q,dqdt,'nls');
+         returned = baseflow.fitab(q/unitScale,dqdt/unitScale,'nls');
+         testCase.verifyEqual(returned.b,expected.b, ...
+            'AbsTol',testCase.exponentTolerance);
+         testCase.verifyEqual([returned.bL returned.bH], ...
+            [expected.bL expected.bH],'AbsTol',testCase.intervalTolerance);
+         a_returned = returned.a*unitScale/unitScale^returned.b;
+         testCase.verifyEqual(a_returned,expected.a, ...
+            'RelTol',testCase.coefficientTolerance);
+      end
+
+      function responseUnitsPreserveIntervals(testCase,Event)
+         [q,dqdt] = testCase.vectors(Event);
+         responseScale = 1e3;
+         expected = baseflow.fitab(q,dqdt,'nls');
+         returned = baseflow.fitab(q,responseScale*dqdt,'nls');
+         testCase.verifyEqual(returned.b,expected.b, ...
+            'AbsTol',testCase.exponentTolerance);
+         testCase.verifyEqual([returned.a returned.aL returned.aH] ...
+            /responseScale,[expected.a expected.aL expected.aH], ...
+            'RelTol',testCase.coefficientTolerance);
+         testCase.verifyEqual([returned.bL returned.bH], ...
+            [expected.bL expected.bH],'AbsTol',testCase.intervalTolerance);
+      end
+
+      function knownPowerLaw(testCase)
+         q = logspace(0,2,40)';
+         a_expected = 0.02;
+         b_expected = 1.5;
+         dqdt = -a_expected*q.^b_expected;
+         returned = baseflow.fitab(q,dqdt,'nls');
+         testCase.verifyEqual(returned.a,a_expected, ...
+            'RelTol',testCase.exponentTolerance);
+         testCase.verifyEqual(returned.b,b_expected, ...
+            'AbsTol',testCase.exponentTolerance);
+      end
+   end
+
+   methods (Static, Access=private)
+      function [q1,d1,q2,d2] = vectors(id)
+         switch id
+            case 77
+               q1 = [ ...
+                  22273303.381783407; 15905605.092836792; ...
+                  14056676.820931144; 12382093.350860544; ...
+                  11006149.458108671];
+               d1 = -[ ...
+                  8748182.3145496920; 1994395.9581125539; ...
+                  1787718.5763123804; 1578543.6486427924; ...
+                  1260314.0723253381];
+               q2 = [ ...
+                  22273303.381783407; 15905605.092836792; ...
+                  14056676.820931148; 12382093.350860545; ...
+                  11006149.458108673];
+               d2 = -[ ...
+                  8748182.3145496920; 1994395.9581125493; ...
+                  1787718.5763123799; 1578543.6486427949; ...
+                  1260314.0723253393];
+            case 62
+               q1 = [ ...
+                  2189927.4984595436; 1892250.7077013825; ...
+                  1695305.1635533504; 1552355.9709193604; ...
+                  1434594.6396294311; 1339221.1157310200; ...
+                  1252948.6508743891; 1175777.2450595389; ...
+                  1107462.4932164901; 1049450.2903528986; ...
+                  992819.85141455033; 939141.51023605210; ...
+                  887033.50289216044; 837740.57834464603; ...
+                  791414.34757011407; 745596.73795748176; ...
+                  701686.19845441799; 661122.80098609801; ...
+                  622508.09660485317; 585657.15202813630; ...
+                  550887.91561778390; 518892.85950810061; ...
+                  487472.65222502837; 457516.76490583981; ...
+                  429192.97934955626; 402310.62824007741; ...
+                  377640.77041192434; 354484.60204392433; ...
+                  332357.59044533945; 311625.02675678063; ...
+                  292202.90247372875; 274172.47172350559; ...
+                  257253.47662628052; 242289.34827685775; ...
+                  227589.96530791110; 213597.53529716903; ...
+                  200447.45695452162; 188039.19180777669; ...
+                  176243.16565845319; 165025.74844711123; ...
+                  154415.80004697584; 144646.36753592009; ...
+                  135418.02114883365; 126457.43921054501; ...
+                  118078.29654279404; 110236.31981796878; ...
+                  102836.57953969542; 95871.501170681295; ...
+                  89409.255546560831; 83378.175891410661; ...
+                  77739.806862052297; 72448.711829577354; ...
+                  67486.310853188566; 62814.760001013317; ...
+                  58435.253341072232; 54557.365448739220; ...
+                  50739.608292437348; 47084.543089142768; ...
+                  43628.920880719503; 40363.817461706843; ...
+                  37286.801087180691; 34389.218070869363; ...
+                  31653.758112452360; 29072.579083225068];
+               d1 = -[ ...
+                  359442.09268877050; 226948.28636449861; ...
+                  155543.12330602054; 127350.69550251402; ...
+                  108171.96707734461; 94340.861980836780; ...
+                  82319.061358983410; 72106.565211784502; ...
+                  63500.375939795005; 57901.133696115110; ...
+                  53856.691474054249; 52068.776049945263; ...
+                  50982.587402169083; 49782.834798840042; ...
+                  47609.483634207267; 45114.394980759840; ...
+                  42326.334045597505; 39809.364402332343; ...
+                  37534.720843864605; 35585.875894280391; ...
+                  33836.513204965588; 32261.300797447126; ...
+                  30696.947747829425; 29162.227335594249; ...
+                  27673.928472331827; 26162.041107351735; ...
+                  24568.795409598744; 22945.428150281521; ...
+                  21381.172886038556; 19858.646436335479; ...
+                  18384.872463025637; 17086.414598327272; ...
+                  15934.833897677721; 15025.106580617208; ...
+                  14129.958012881012; 13335.601682710178; ...
+                  12673.490955987487; 12078.113454422841; ...
+                  11490.192360312078; 10900.809420486772; ...
+                  10322.139688592353; 9747.5250822788821; ...
+                  9178.0352503979993; 8619.2221189116990; ...
+                  8087.6497667974154; 7581.0713715941210; ...
+                  7073.6189913186099; 6584.4370608865229; ...
+                  6149.4422049331361; 5742.7478179855243; ...
+                  5365.6440684836298; 5025.0766780195117; ...
+                  4722.9745763061446; 4441.1436317007074; ...
+                  4180.9107664064049; 3952.7663308357114; ...
+                  3731.7913995953131; 3523.5538408320749; ...
+                  3325.7127460639890; 3137.5637618433093; ...
+                  2960.8498730954716; 2794.2927536670823; ...
+                  2632.0861825347106; 2471.7286147856271];
+               q2 = [ ...
+                  2189927.4984595440; 1892250.7077013829; ...
+                  1695305.1635533506; 1552355.9709193604; ...
+                  1434594.6396294311; 1339221.1157310200; ...
+                  1252948.6508743891; 1175777.2450595389; ...
+                  1107462.4932164906; 1049450.2903528991; ...
+                  992819.85141455056; 939141.51023605210; ...
+                  887033.50289216067; 837740.57834464614; ...
+                  791414.34757011407; 745596.73795748176; ...
+                  701686.19845441799; 661122.80098609813; ...
+                  622508.09660485340; 585657.15202813630; ...
+                  550887.91561778390; 518892.85950810061; ...
+                  487472.65222502837; 457516.76490583981; ...
+                  429192.97934955626; 402310.62824007741; ...
+                  377640.77041192434; 354484.60204392433; ...
+                  332357.59044533945; 311625.02675678069; ...
+                  292202.90247372875; 274172.47172350565; ...
+                  257253.47662628061; 242289.34827685781; ...
+                  227589.96530791110; 213597.53529716906; ...
+                  200447.45695452165; 188039.19180777669; ...
+                  176243.16565845319; 165025.74844711123; ...
+                  154415.80004697590; 144646.36753592012; ...
+                  135418.02114883365; 126457.43921054504; ...
+                  118078.29654279405; 110236.31981796879; ...
+                  102836.57953969545; 95871.501170681309; ...
+                  89409.255546560846; 83378.175891410661; ...
+                  77739.806862052312; 72448.711829577354; ...
+                  67486.310853188566; 62814.760001013317; ...
+                  58435.253341072239; 54557.365448739220; ...
+                  50739.608292437362; 47084.543089142775; ...
+                  43628.920880719510; 40363.817461706851; ...
+                  37286.801087180706; 34389.218070869378; ...
+                  31653.758112452368; 29072.579083225071];
+               d2 = -[ ...
+                  359442.09268877102; 226948.28636449875; ...
+                  155543.12330602092; 127350.69550251383; ...
+                  108171.96707734503; 94340.861980836809; ...
+                  82319.061358983308; 72106.565211784487; ...
+                  63500.375939795027; 57901.133696115168; ...
+                  53856.691474054278; 52068.776049945271; ...
+                  50982.587402169163; 49782.834798840137; ...
+                  47609.483634207259; 45114.394980759811; ...
+                  42326.334045597483; 39809.364402332329; ...
+                  37534.720843864670; 35585.875894280398; ...
+                  33836.513204965668; 32261.300797447155; ...
+                  30696.947747829421; 29162.227335594238; ...
+                  27673.928472331812; 26162.041107351732; ...
+                  24568.795409598759; 22945.428150281517; ...
+                  21381.172886038541; 19858.646436335490; ...
+                  18384.872463025611; 17086.414598327250; ...
+                  15934.833897677736; 15025.106580617226; ...
+                  14129.958012881023; 13335.601682710176; ...
+                  12673.490955987472; 12078.113454422852; ...
+                  11490.192360312107; 10900.809420486792; ...
+                  10322.139688592366; 9747.5250822788803; ...
+                  9178.0352503979884; 8619.2221189116844; ...
+                  8087.6497667974181; 7581.0713715941347; ...
+                  7073.6189913186090; 6584.4370608865283; ...
+                  6149.4422049331424; 5742.7478179855143; ...
+                  5365.6440684836334; 5025.0766780195108; ...
+                  4722.9745763061328; 4441.1436317007146; ...
+                  4180.9107664063986; 3952.7663308357087; ...
+                  3731.7913995953136; 3523.5538408320772; ...
+                  3325.7127460639877; 3137.5637618433084; ...
+                  2960.8498730954739; 2794.2927536670863; ...
+                  2632.0861825347147; 2471.7286147856298];
+            case 38
+               q1 = [ ...
+                  3954669.4247093857; 3506817.5928756031; ...
+                  3181220.3996663638; 2912754.4523783349; ...
+                  2669614.2689193808; 2453351.8184234458; ...
+                  2269112.3234014716];
+               d1 = -[ ...
+                  526087.88094588893; 358415.90355761076; ...
+                  275669.75306103413; 257009.05412725676; ...
+                  234730.38893218368; 197364.50787289385; ...
+                  168658.02147178687];
+               q2 = [ ...
+                  3954669.4247093857; 3506817.5928756031; ...
+                  3181220.3996663638; 2912754.4523783349; ...
+                  2669614.2689193808; 2453351.8184234458; ...
+                  2269112.3234014716];
+               d2 = -[ ...
+                  526087.88094588800; 358415.90355761070; ...
+                  275669.75306103454; 257009.05412725720; ...
+                  234730.38893218385; 197364.50787289347; ...
+                  168658.02147178748];
+         end
+      end
+   end
+end
diff --git a/toolbox/+baseflow/fitab.m b/toolbox/+baseflow/fitab.m
index a76dee7..5efe29c 100644
--- a/toolbox/+baseflow/fitab.m
+++ b/toolbox/+baseflow/fitab.m
@@ -38,6 +38,11 @@
    % Notes
    %     masked points and zero-weight points take no part in the fit
    %
+   %     MATLAB NLS solvers fit scaled discharge and derivative values to
+   %     reduce numerical conditioning errors. Fit coefficients and their
+   %     confidence intervals use the original input units. The solver
+   %     sequence rejects a Curve Fitting iterate that did not converge.
+   %
    %     Use method 'envelope' to pass a line through an arbitrary x,y pair
    %     (refpoints), specified in terms of the quantile of the x/y data
    %     distributions. this method is similar to 'mean' or 'median', but allows
diff --git a/toolbox/+baseflow/private/fitNLS_matlab.m b/toolbox/+baseflow/private/fitNLS_matlab.m
index 6374d17..d96eb81 100644
--- a/toolbox/+baseflow/private/fitNLS_matlab.m
+++ b/toolbox/+baseflow/private/fitNLS_matlab.m
@@ -8,6 +8,18 @@
    %
    % See also:
 
+   % Scale the same power law before solving. Large differences between
+   % Jacobian columns can stop the solver before it reaches the best fit.
+   % Keep the original logs for the unchanged linear fallback.
+   logxOriginal = logx;
+   logyOriginal = logy;
+   xScale = exp(mean(logx));
+   yScale = exp(mean(logy));
+   x = x/xScale;
+   y = y/yScale;
+   logx = log(x);
+   logy = log(y);
+
    % initial estimates using log-log linear fit
    ok = true;
    ab0 = [ones(size(x)) logx]\logy;
@@ -55,17 +67,9 @@
       [ab1,R1,~,C1] = nlinfit(x,y,fnc,ab0,opts1); % R=resids,C=error variance
       rsq1 = baseflow.deps.rsquare(y,ab1(1).*x.^ab1(2));
 
-   catch ME
-
-      if (strcmp(ME.identifier,'stats:nlinfit:NoUsableObservations'))
-
-         msg = 'Fitting failed using nlinfit at ab1';
-         causeException = MException('BFRA:fitab:fitting',msg);
-         ME = addCause(ME,causeException);
-
-      end
+   catch
+      % Continue to the next solver if this solver cannot fit the data.
       ab1ok = false;
-      % rethrow(ME)
    end
 
    % if nlinfit worked and it's 'better' than rsq (here, rsq0), select it
@@ -76,22 +80,15 @@
    else
 
       % try curve fitting functions
-      ab3ok = true;
       try
-         f3 = fit(x,y,ftype,opts3);
+         [f3,~,output3] = fit(x,y,ftype,opts3);
+         % Accept the returned iterate only if the solver converged.
+         ab3ok = output3.exitflag > 0;
          ab3 = coeffvalues(f3);
          rsq3 = baseflow.deps.rsquare(y,ab3(1).*x.^ab3(2));
 
-      catch ME
-
-         if (strcmp(ME.identifier,'curvefit:fit:infComputed'))
-
-            msg = 'Fitting failed using fit at ab3';
-            causeException = MException('BFRA:fitab:fitting',msg);
-            ME = addCause(ME,causeException);
-         end
+      catch
          ab3ok = false;
-         % rethrow(ME)
       end
 
       % if fit worked, select it
@@ -113,16 +110,8 @@
          [ab2,R2,~,C2] = nlinfit(x,y,fnc,ab0,opts2);
          rsq2 = baseflow.deps.rsquare(y,ab2(1).*x.^ab2(2));
 
-      catch ME
-
-         if (strcmp(ME.identifier,'stats:nlinfit:NoUsableObservations'))
-
-            msg = 'Fitting failed using nlinfit at ab2';
-            causeException = MException('BFRA:fitab:fitting',msg);
-            ME = addCause(ME,causeException);
-         end
+      catch
          ab2ok = false;
-         %rethrow(ME)
       end
 
       if ab2ok && rsq2 > rsq && rsq2 > 0
@@ -132,21 +121,14 @@
 
       else                            % try curve fitting functions
 
-         ab4ok = true;
          try
-            f4 = fit(x,y,ftype,opts4); ab4 = coeffvalues(f4);
+            [f4,~,output4] = fit(x,y,ftype,opts4);
+            ab4ok = output4.exitflag > 0;
+            ab4 = coeffvalues(f4);
             rsq4 = baseflow.deps.rsquare(y,ab4(1).*x.^ab4(2));
 
-         catch ME
-
-            if (strcmp(ME.identifier,'curvefit:fit:infComputed'))
-
-               msg = 'Fitting failed using fit at ab4';
-               causeException = MException('BFRA:fitab:fitting',msg);
-               ME = addCause(ME,causeException);
-            end
+         catch
             ab4ok = false;
-            %rethrow(ME)
          end
 
          % we don't compare with rsq2 because we already know its <rsq0
@@ -177,24 +159,22 @@
          ci = [nan nan; nan nan];
 
       case 'nlinfit_robust'
-         ci = nlparci(ab1,R1,'covariance',C1,'alpha',1-alpha);
-         ab = ab1;
+         [ab,C] = restoreParameters(ab1,C1,xScale,yScale);
+         ci = nlparci(ab,yScale*R1,'covariance',C,'alpha',1-alpha);
 
       case 'nlinfit'
-         ci = nlparci(ab2,R2,'covariance',C2,'alpha',1-alpha);
-         ab = ab2;
+         [ab,C] = restoreParameters(ab2,C2,xScale,yScale);
+         ci = nlparci(ab,yScale*R2,'covariance',C,'alpha',1-alpha);
 
       case 'fit_robust'
-         ab = ab3;
-         ci = transpose(confint(f3,alpha));
+         [ab,ci] = restoreCurveFit(f3,xScale,yScale,alpha);
 
       case 'fit'
-         ab = ab4;
-         ci = transpose(confint(f4,alpha));
+         [ab,ci] = restoreCurveFit(f4,xScale,yScale,alpha);
 
       case 'linear'
 
-         [ab,ci] = regress(logy,[ones(size(y)) logx],1-alpha);
+         [ab,ci] = regress(logyOriginal,[ones(size(y)) logxOriginal],1-alpha);
          ci(1,:) = exp(ci(1,:));
          ab = [exp(ab(1)); ab(2)];
 
@@ -203,3 +183,19 @@
    end
 
 end
+
+function [ab,C] = restoreParameters(theta,Ctheta,xScale,yScale)
+   multiplier = yScale/xScale^theta(2);
+   ab = [theta(1)*multiplier, theta(2)];
+   % Propagate the full covariance through a = yScale*A/xScale^b.
+   D = [multiplier, -ab(1)*log(xScale); 0, 1];
+   C = D*Ctheta*D';
+end
+
+function [ab,ci] = restoreCurveFit(f,xScale,yScale,alpha)
+   theta = coeffvalues(f);
+   ab = [theta(1)*yScale/xScale^theta(2), theta(2)];
+   ci = transpose(confint(f,alpha));
+   % At original Q=1, the fitted mean is the original coefficient a.
+   ci(1,:) = yScale*predint(f,1/xScale,alpha,'functional','off');
+end