diff --git a/.github/dependabot.yml b/.github/dependabot.yml index aa8cacb16b..448cf4b98b 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -42,6 +42,7 @@ updates: - "orthax" - "quadax" - "jax-finufft" + - "adv-jax-math" - package-ecosystem: "github-actions" directory: "/" schedule: diff --git a/CHANGELOG.md b/CHANGELOG.md index 7e8a890414..b60bfc4b83 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,9 +4,16 @@ Changelog Performance Improvements - Improves memory management to reduce the base memory used during optimization while using `lsq-exact`, `lsq-auglag` and `fmin-auglag` optimizers. +- Sparse reverse-mode differentiation was introduced to yield significant performance improvements [#2170](https://github.com/PlasmaControl/DESC/pull/2170). Plumbing to use this method was added that will be progressively taken advantage of in the future. - Speeds up ``field_line_integrate`` and ``trace_particles`` for filamentary coils (``Coil``, ``CoilSet``, ``MixedCoilSet``) by precomputing the constant source information, so that the ODE right hand side only evaluates a single fused Biot-Savart kernel instead of recomputing the coil geometry at every solver step. - Improves the non-singular Biot-Savart kernel which should give a speed/memory improvement to objectives that compute magnetic field from coils such as ``QuadraticFlux``. +Breaking Changes and Deprecations + +- The parameter ``num_transit`` in ``EffectiveRipple``, ``Gamma_c``, ``Bounce2D`` and related functions has been changed to ``field_period_transits``. This should make using a consistent resolution across different equilibria easier. The now-deprecated ``num_transit`` may still be used but note the equivalence ``field_period_transits = num_transit * grid.NFP``. +- The parameter ``Y_B`` in ``EffectiveRipple``, ``Gamma_c``, ``Bounce2D`` is now the resolution over a single field period rather than a full toroidal transit. This should make using a consistent resolution across different equilibria easier. +- Objectives using ``Bounce2D`` now do not support fwd mode differentiation for JAX versions <0.11.0. + Bug Fixes - Fixes bug in ``auglag`` optimizers which prevented them from accepting solver hyperparameters. @@ -16,6 +23,7 @@ Bug Fixes ``fmin-auglag`` with the default ``tr_method="exact"``, and in ``lsq-exact``/``lsq-auglag`` with ``tr_method="cho"``. + v0.17.3 ------- @@ -44,11 +52,11 @@ Bug Fixes - Updates ``"reactor_QA"`` in ``desc.examples`` to fix this. Note that if using ``"reactor_QA"`` example from ``v0.16.0`` until this fix, the current profile in that example has this issue. - Fixes bug in `CoilSet.from_symmetry` that ignored the passed in `check_intersection` value. This caused redundant checks in various other functions such as `plot_coils`. - Breaking Changes - Name change in `_CoilObjective` replacing `coilset_mask` with `objective_mask`. Custom subclasses with `_broadcast_input="node"` that previously used `coilset_mask` should switch to `objective_mask`. + v0.17.2 ------- @@ -58,7 +66,6 @@ New Features - Sub-objectives of an `ObjectiveFunction` can now have different `use_jit` values than the `ObjectiveFunction`. These objectives have to be built before building the `ObjectiveFunction`. - Adds ``num_neighbors`` parameter to ``CoilSetMinDistance`` that limits the pairwise distance computation to the nearest neighbors per coil, reducing memory useage for large coilsets. - Method to plot frequency spectrum of inverse stream map in field line coordinates ``Bounce2D.plot_angle_spectrum``. -- Method to compute bounce integrals in batches is now added to the public API ``Bounce2D.batch``. - Initiated deprecation of ``Bounce2D.compute_fieldline_length`` in favor of ``eq.compute("V_psi")``. - The quadrature resolution in ``Bounce2D.compute_fieldline_length`` now corresponds to the resolution over a single field period instead of the resolution over a toroidal transit. - Adds an optional attribute `ion_density` to the `Equilibrium` class, to allow the ion density profile to be set independently of the electron density and effective atomic number. Also adds compute functions for ``"ni_rr"`` and ``"Zeff_rr"``. @@ -68,6 +75,7 @@ New Features Bug Fixes - Fixes SyntaxError thrown when loading hdf5 data from file-like objects. +- Fixes ``pitch_batch_size`` argument getting ignored in compute functions. - Fixes a bug in `OmnigenousField.change_resolution` when changing `L_B`. - Scaling a `ScaledProfile` or taking power of a `PowerProfile` now only updates the `scale`/`power` attributes instead of nesting the `ScaledProfile`/`PowerProfile`s. - `jax.Array`s in `_static_attrs` will be automatically converted to `np.ndarray` to prevent stalling code. In general, jax arrays should be omitted in `_static_attrs`. @@ -79,7 +87,6 @@ Performance Improvements - Now, `desc.compute._build_data_index` uses depth-first search algorithm to construct the dependency tree. - Some of the default value computations at import time are removed (i.e. `desc.integrals.bounce_integral.default_quad`) - [Significantly improves convergence of inverse stream maps](https://github.com/PlasmaControl/DESC/pull/1919). -- Check-pointing to bounce integrals to improve speed and reduce memory of reverse mode differentiation. - Resolves a JAX memory regression in bounce integrals by avoiding materialization of a large tensor in memory. Previously, we had closed the issue by adding nuffts as a workaround. This update actually solves the issue for the case when a user specifies to not use nuffts as well. - ``ObjectiveFunction.print_value`` can now use the previously computed ``compute_scaled_error`` values to print. For bounded objectives, we fall back to computing ``compute_unscaled``. Additionally, ``compute_scaled_error`` and array splitting are used in other parts of the code to prevent recompilation for one-time tasks, which makes initialization faster. diff --git a/desc/batching.py b/desc/batching.py index eec6bedb51..f6f6e3b023 100644 --- a/desc/batching.py +++ b/desc/batching.py @@ -2,6 +2,7 @@ from functools import partial +from adv_jax_math import batch_map # noqa: F401 from jax._src.api import ( _check_input_dtype_jacfwd, _check_input_dtype_jacrev, @@ -197,6 +198,21 @@ def vmap_chunked( - https://github.com/jax-ml/jax/issues/26689 - https://github.com/jax-ml/jax/issues/27591 - https://github.com/jax-ml/jax/issues/31919 + - Due to an actively worked on issue in JAX, + https://docs.jax.dev/en/latest/jep/ + 2026-custom-derivatives.html#main-problem-descriptions, + this function can simply ignore custom derivative rules + of the function in wraps if ``chunk_size`` is not ``None``, + and therefore can damp the effeciency gains of ``sparse_pullback``. + Use ``batch_map`` instead to avoid this, + or try to make a hack with jax.custom_transforms to bypass this. + - Only out axes = 0 is supported. + + See Also + -------- + batch_map + If the function supports native vectorization, use ``batch_map`` instead + for the reasons discussed the docstring. Parameters ---------- @@ -230,49 +246,6 @@ def vmap_chunked( ) -def batch_map( - fun, fun_input, /, batch_size=None, *, reduction=None, chunk_reduction=identity -): - """Compute ``chunk_reduction(fun(fun_input))`` in batches. - - This utility is like ``vmap_chunked`` except that ``fun`` is assumed to be - vectorized natively. No JAX vectorization such as ``vmap`` is applied to the - supplied function. This makes compilation faster and avoids the weaknesses of - applying JAX vectorization, such as executing all branches of code conditioned on - dynamic values. For example, this function would be useful for GitHub issue #1303. - - Parameters - ---------- - fun : callable - Natively vectorized function. - fun_input : pytree - Data to split into batches to feed to ``fun``. - batch_size : int or None - Size of batches. If no batching should be done or the batch size is the - full input then supply ``None``. - reduction : callable or None - Binary reduction operation. - Should take two arguments and return one output, e.g. ``jnp.add``. - chunk_reduction : callable - Chunk-wise reduction operation. - Should typically apply ``reduction`` along the mapped axis, - e.g. ``jnp.add.reduce``. - - Returns - ------- - fun_output - Returns ``chunk_reduction(fun(fun_input))``. - - """ - return ( - chunk_reduction(fun(fun_input)) - if batch_size is None - else _evaluate_in_chunks( - fun, batch_size, (0,), reduction, chunk_reduction, fun_input - ) - ) - - def batched_vectorize(pyfunc, *, excluded=frozenset(), signature=None, chunk_size=None): """Define a vectorized function with broadcasting and batching. diff --git a/desc/compute/_fast_ion.py b/desc/compute/_fast_ion.py index 71dd974d5b..969500518b 100644 --- a/desc/compute/_fast_ion.py +++ b/desc/compute/_fast_ion.py @@ -5,9 +5,8 @@ from desc.backend import jit, jnp from ..batching import batch_map -from ..integrals.bounce_integral import Bounce2D -from ..utils import cross, dot, safediv -from ._neoclassical import _bounce_doc, _bounce_static_argnames +from ..integrals.bounce_integral import Bounce2D, BounceOptions +from ..utils import cross, dot, parse_argname_change, safediv from .data_index import register_compute_fun # We rewrite equivalents of Nemov et al.'s expressions (21, 22) to resolve @@ -26,13 +25,30 @@ # (|∇ρ| ‖e_α|ρ,ϕ‖)ᵢ ∫ dℓ [ (1 − λ|B|/2)/√(1 − λ|B|) ∂|B|/∂ρ + √(1 − λ|B|) K ] / |B| +def _gamma_c_data(data): + # The grid has to be dense enough to avoid aliasing error on |B| anyway, + # so we might as well interplate anything smoother than |B| with one + # Fourier series rather than transforming each term. Last term in K + # behaves as ∂log(|B|²/(R₀B₀B^ϕ))/∂ρ |B| where R₀B₀ is a constant with + # units Tesla meters. Smoothness is determined by positive lower bound of + # log argument, and hence behaves as ∂log(|B|/B₀)/∂ρ |B| = ∂|B|/∂ρ. + return { + "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], + "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], + "|B|_r|v,p": data["|B|_r|v,p"], + "K": data["iota_r"] + * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) + - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), + } + + def _v_tau(data, B, pitch): # Note v τ = 4λ⁻²B₀⁻¹ ∂I/∂((λB₀)⁻¹) where v is the particle velocity, # τ is the bounce time, and I is defined in Nemov et al. eq. 36. return safediv(2.0, jnp.sqrt(jnp.abs(1 - pitch * B))) -def _drift1(data, B, pitch): +def _radial_drift_1(data, B, pitch): return ( safediv(1 - 0.5 * pitch * B, jnp.sqrt(jnp.abs(1 - pitch * B))) * data["|grad(psi)|*kappa_g"] @@ -40,7 +56,7 @@ def _drift1(data, B, pitch): ) -def _drift2(data, B, pitch): +def _poloidal_drift_periodic(data, B, pitch): return ( safediv(1 - 0.5 * pitch * B, jnp.sqrt(jnp.abs(1 - pitch * B))) * data["|B|_r|v,p"] @@ -48,6 +64,22 @@ def _drift2(data, B, pitch): ) / B +def _radial_drift_2(data, B, pitch): + return safediv( + data["cvdrift0"] * (1 - 0.5 * pitch * B), + jnp.sqrt(jnp.abs(1 - pitch * B)), + ) + + +def _poloidal_drift_secular(data, B, pitch): + # TODO (#465), multiply by (omega + zeta) instead of zeta + return safediv( + (data["gbdrift (periodic)"] + data["gbdrift (secular)/phi"] * data["zeta"]) + * (1 - 0.5 * pitch * B), + jnp.sqrt(jnp.abs(1 - pitch * B)), + ) + + @register_compute_fun( name="Gamma_c", label=( @@ -82,9 +114,9 @@ def _drift2(data, B, pitch): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **BounceOptions._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=BounceOptions._static_argnames) def _Gamma_c(params, transforms, profiles, data, **kwargs): """Fast ion confinement proxy as defined by Nemov et al. @@ -114,115 +146,60 @@ def _Gamma_c(params, transforms, profiles, data, **kwargs): have high energy with collisionless orbits, so it is assumed to be zero. """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(-2, grid, **kwargs) + opts = BounceOptions.guess(-2, grid, **kwargs) def Gamma_c(data): - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, - ) + bounce = Bounce2D(grid, data, data["angle"], **opts) def fun(pitch_inv): - points = bounce.points(pitch_inv, num_well) - v_tau, drift1, drift2 = bounce.integrate( - [_v_tau, _drift1, _drift2], + points = bounce.points(pitch_inv, opts.num_well) + v_tau, radial_drift, poloidal_drift = bounce.integrate( + [_v_tau, _radial_drift_1, _poloidal_drift_periodic], pitch_inv, data, ["|grad(psi)|*kappa_g", "|B|_r|v,p", "K"], points, - nufft_eps=nufft_eps, - is_fourier=True, ) - # This is γ_c π/2. - gamma_c = jnp.arctan( + gamma_c_pi_over_2 = jnp.arctan( safediv( - drift1, - drift2 + radial_drift, + poloidal_drift * bounce.interp_to_argmin( - data["|grad(rho)|*|e_alpha|r,p|"], - points, - nufft_eps=nufft_eps, - is_fourier=True, + data["|grad(rho)|*|e_alpha|r,p|"], points ), ) ) - return (v_tau * gamma_c**2).sum(-1).mean(-2) + return (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) + pitch_inv, weight = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) return jnp.sum( - batch_map(fun, data["pitch_inv"], pitch_batch_size) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + batch_map(fun, pitch_inv, opts.pitch_batch_size) * weight / pitch_inv**2, axis=-1, ) - # It is assumed the grid is sufficiently dense to reconstruct |B|, - # so anything smoother than |B| may be captured accurately as a single - # Fourier series rather than transforming each component. Last term in K - # behaves as ∂log(|B|²/(R₀B₀B^ϕ))/∂ρ |B| where R₀B₀ is a constant with - # units Tesla meters. Smoothness is determined by positive lower bound of - # log argument, and hence behaves as ∂log(|B|/B₀)/∂ρ |B| = ∂|B|/∂ρ. - fun_data = { - "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], - "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], - "|B|_r|v,p": data["|B|_r|v,p"], - "K": data["iota_r"] - * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) - - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), - } + out = Bounce2D.batch( + Gamma_c, + _gamma_c_data(data), + data, + angle, + grid, + surf_batch_size=opts.surf_batch_size, + ) + assert out.ndim == 1 data["Gamma_c"] = ( - Bounce2D.batch( - Gamma_c, - fun_data, - data, - angle, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) + grid.expand(out) / data["V_psi"] - / (num_transit * 2**0.5) + / (opts.field_period_transits / grid.NFP * 2**0.5) ) return data -def _radial_drift(data, B, pitch): - return safediv( - data["cvdrift0"] * (1 - 0.5 * pitch * B), jnp.sqrt(jnp.abs(1 - pitch * B)) - ) - - -def _poloidal_drift(data, B, pitch): - return safediv( - (data["gbdrift (periodic)"] + data["gbdrift (secular)/phi"] * data["zeta"]) - * (1 - 0.5 * pitch * B), - jnp.sqrt(jnp.abs(1 - pitch * B)), - ) - - @register_compute_fun( name="gamma_c", label="\\sum_{w} \\gamma_c(\\rho, \\alpha, \\lambda, w)", @@ -252,9 +229,9 @@ def _poloidal_drift(data, B, pitch): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **BounceOptions._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=BounceOptions._static_argnames) def _little_gamma_c_Nemov(params, transforms, profiles, data, **kwargs): """Fast ion confinement proxy as defined by Nemov et al. @@ -265,71 +242,42 @@ def _little_gamma_c_Nemov(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - _, - _, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(-2, grid, **kwargs) + opts = BounceOptions.guess(-2, grid, loop=True, **kwargs) def gamma_c0(data): - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, + pitch_inv, _ = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad ) - - points = bounce.points(data["pitch_inv"], num_well) - drift1, drift2 = bounce.integrate( - [_drift1, _drift2], - data["pitch_inv"], + bounce = Bounce2D(grid, data, data["angle"], **opts) + points = bounce.points(pitch_inv, opts.num_well) + radial_drift, poloidal_drift = bounce.integrate( + [_radial_drift_1, _poloidal_drift_periodic], + pitch_inv, data, ["|grad(psi)|*kappa_g", "|B|_r|v,p", "K"], points, - nufft_eps=nufft_eps, - is_fourier=True, - low_ram=True, + loop=opts.loop, ) return (2 / jnp.pi) * jnp.arctan( safediv( - drift1, - drift2 - * bounce.interp_to_argmin( - data["|grad(rho)|*|e_alpha|r,p|"], - points, - nufft_eps=nufft_eps, - is_fourier=True, - ), + radial_drift, + poloidal_drift + * bounce.interp_to_argmin(data["|grad(rho)|*|e_alpha|r,p|"], points), ) ).sum(-1) - fun_data = { - "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], - "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], - "|B|_r|v,p": data["|B|_r|v,p"], - "K": data["iota_r"] - * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) - - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), - } data["gamma_c"] = Bounce2D.batch( - gamma_c0, fun_data, data, angle, grid, num_pitch, 1 + gamma_c0, + _gamma_c_data(data), + data, + angle, + grid, + surf_batch_size=1, + sparse=False, # don't know of any applications that differentiate anyway ) return data @@ -361,9 +309,9 @@ def gamma_c0(data): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **BounceOptions._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=BounceOptions._static_argnames) def _Gamma_c_Velasco(params, transforms, profiles, data, **kwargs): """Fast ion confinement proxy as defined by Velasco et al. @@ -382,74 +330,50 @@ def _Gamma_c_Velasco(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(-1, grid, **kwargs) + opts = BounceOptions.guess(-1, grid, **kwargs) def Gamma_c(data): - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, - ) + bounce = Bounce2D(grid, data, data["angle"], **opts) def fun(pitch_inv): v_tau, radial_drift, poloidal_drift = bounce.integrate( - [_v_tau, _radial_drift, _poloidal_drift], + [_v_tau, _radial_drift_2, _poloidal_drift_secular], pitch_inv, data, ["cvdrift0", "gbdrift (periodic)", "gbdrift (secular)/phi"], - num_well=num_well, - nufft_eps=nufft_eps, - is_fourier=True, + num_well=opts.num_well, ) - # This is γ_c π/2. - gamma_c = jnp.arctan(safediv(radial_drift, poloidal_drift)) - return (v_tau * gamma_c**2).sum(-1).mean(-2) + gamma_c_pi_over_2 = jnp.arctan(safediv(radial_drift, poloidal_drift)) + return (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) + pitch_inv, weight = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) return jnp.sum( - batch_map(fun, data["pitch_inv"], pitch_batch_size) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + batch_map(fun, pitch_inv, opts.pitch_batch_size) * weight / pitch_inv**2, axis=-1, ) + out = Bounce2D.batch( + Gamma_c, + { + "cvdrift0": data["cvdrift0"], + "gbdrift (periodic)": data["gbdrift (periodic)"], + "gbdrift (secular)/phi": data["gbdrift (secular)/phi"], + }, + data, + angle, + grid, + surf_batch_size=opts.surf_batch_size, + ) + assert out.ndim == 1 data["Gamma_c Velasco"] = ( - Bounce2D.batch( - Gamma_c, - { - "cvdrift0": data["cvdrift0"], - "gbdrift (periodic)": data["gbdrift (periodic)"], - "gbdrift (secular)/phi": data["gbdrift (secular)/phi"], - }, - data, - angle, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) + grid.expand(out) / data["V_psi"] - / (num_transit * 2**0.5) + / (opts.field_period_transits / grid.NFP * 2**0.5) ) return data diff --git a/desc/compute/_neoclassical.py b/desc/compute/_neoclassical.py index 6f21c4b9ca..c348baa673 100644 --- a/desc/compute/_neoclassical.py +++ b/desc/compute/_neoclassical.py @@ -5,109 +5,11 @@ from desc.backend import jit, jnp from ..batching import batch_map -from ..integrals.bounce_integral import Bounce2D +from ..integrals.bounce_integral import Bounce2D, BounceOptions from ..integrals.surface_integral import surface_integrals -from ..utils import safediv +from ..utils import parse_argname_change, safediv from .data_index import register_compute_fun -_bounce_doc = { - "angle": """jnp.ndarray : - Shape (num rho, X, Y). - Angle returned by ``Bounce2D.angle``. - """, - "Y_B": """int : - Desired resolution for algorithm to compute bounce points. - If the option ``spline`` is ``True``, the bounce points are found with - 8th order accuracy in this parameter. If the option ``spline`` is ``False``, - then the bounce points are found with spectral accuracy in this parameter. - A reference value for the ``spline=True`` option is - ``grid.NFP*(grid.num_theta+grid.num_zeta)//2``. - A reference value for the ``spline=False`` option is - ``(grid.num_theta+grid.num_zeta)//2``. - - An error of ε in a bounce point manifests - 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and - 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. - """, - "alpha": """jnp.ndarray : - Shape (num alpha, ). - Starting field line poloidal labels. - Default is single field line. To compute a surface average - on a rational surface, it is necessary to average over multiple - field lines until the surface is covered sufficiently. - """, - "num_transit": """int : - Number of toroidal transits to follow field line. - In an axisymmetric device, field line integration over a single poloidal - transit is sufficient to capture a surface average. For a 3D - configuration, more transits will approximate surface averages on an - irrational magnetic surface better, with diminishing returns. - """, - "num_well": """int : - Maximum number of wells to detect for each pitch and field line. - Giving ``-1`` will detect all wells but due to current limitations in - JAX this will have worse performance. - Specifying a number that tightly upper bounds the number of wells will - increase performance. In general, an upper bound on the number of wells - per toroidal transit is ``Aι+C`` where ``A``, ``C`` are the poloidal and - toroidal Fourier resolution of B, respectively, in straight-field line - PEST coordinates, and ι is the rotational transform normalized by 2π. - A tighter upper bound than ``num_well=(Aι+C)*num_transit`` is preferable. - The ``check_points`` or ``plot`` methods in ``desc.integrals.Bounce2D`` - are useful to select a reasonable value. - - This is the most important parameter to specify for performance. - """, - "num_quad": """int : - Resolution for quadrature of bounce integrals. - Default is 32. This parameter is ignored if given ``quad``. - """, - "num_pitch": """int : - Resolution for quadrature over velocity coordinate. - """, - "pitch_batch_size": """int : - Number of pitch values with which to compute simultaneously. - If given ``None``, then ``pitch_batch_size`` is ``num_pitch``. - Default is ``num_pitch``. - """, - "surf_batch_size": """int : - Number of flux surfaces with which to compute simultaneously. - If given ``None``, then ``surf_batch_size`` is ``grid.num_rho``. - Default is ``1``. Only consider increasing if ``pitch_batch_size`` is ``None``. - """, - "nufft_eps": """float : - Precision requested for interpolation with non-uniform fast Fourier - transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - """, - "spline": """bool : - Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. Default is ``True``. - """, - "quad": """tuple[jnp.ndarray] : - Used to compute bounce integrals. - Quadrature points xₖ and weights wₖ for the - approximate evaluation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). - """, - "_vander": """dict[str,jnp.ndarray] : - Precomputed transform matrix "dct spline". - This private parameter is intended to be used only by - developers for objectives. - """, - "theta": "", -} - -_bounce_static_argnames = ( - "Y_B", - "num_transit", - "num_well", - "num_quad", - "num_pitch", - "pitch_batch_size", - "surf_batch_size", - "nufft_eps", - "spline", -) - @register_compute_fun( name="V_psi", @@ -150,13 +52,7 @@ def _dI_2(data, B, pitch): @register_compute_fun( name="effective ripple 3/2", - label=( - # ε¹ᐧ⁵ = π/(8√2) R₀²〈|∇ψ|〉⁻² B₀⁻¹ ∫ dλ λ⁻² 〈 ∑ⱼ Hⱼ²/Iⱼ 〉 - "\\epsilon_{\\mathrm{eff}}^{3/2} = \\frac{\\pi}{8 \\sqrt{2}} " - "R_0^2 \\langle \\vert\\nabla \\psi\\vert \\rangle^{-2} " - "B_0^{-1} \\int d\\lambda \\lambda^{-2} " - "\\langle \\sum_j H_j^2 / I_j \\rangle" - ), + label="\\epsilon_{\\mathrm{eff}}^{3/2}", units="~", units_long="None", description="Effective ripple modulation amplitude to 3/2 power", @@ -177,9 +73,9 @@ def _dI_2(data, B, pitch): + Bounce2D.required_names, resolution_requirement="tz", grid_requirement={"can_fft2": True}, - **_bounce_doc, + **BounceOptions._doc, ) -@partial(jit, static_argnames=_bounce_static_argnames) +@partial(jit, static_argnames=BounceOptions._static_argnames) def _epsilon_32(params, transforms, profiles, data, **kwargs): """Effective ripple modulation amplitude to 3/2 power. @@ -199,40 +95,15 @@ def _epsilon_32(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency + angle = parse_argname_change( + kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" + ) + # TODO: in future don't close over grid so that sharding works grid = transforms["grid"] - ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) = Bounce2D._defaults(1, grid, **kwargs) + opts = BounceOptions.guess(1, grid, **kwargs) def eps_32(data): - """(∂ψ/∂ρ)⁻² B₀⁻³ ∫ dλ λ⁻² ∑ⱼ Hⱼ²/Iⱼ.""" - # B₀ has units of λ⁻¹. - # Nemov's ∑ⱼ Hⱼ²/Iⱼ = (∂ψ/∂ρ)² (λB₀)³ (I₁²/I₂).sum(-1). - # (λB₀)³ d(λB₀)⁻¹ = B₀² λ³ d(λ⁻¹) = -B₀² λ dλ. - bounce = Bounce2D( - grid, - data, - data["angle"], - Y_B, - alpha, - num_transit, - quad, - nufft_eps=nufft_eps, - is_fourier=True, - spline=spline, - vander=vander, - ) + bounce = Bounce2D(grid, data, data["angle"], **opts) def fun(pitch_inv): I_1, I_2 = bounce.integrate( @@ -240,35 +111,35 @@ def fun(pitch_inv): pitch_inv, data, ["|grad(rho)|*kappa_g"], - num_well=num_well, - nufft_eps=nufft_eps, - is_fourier=True, + num_well=opts.num_well, ) return safediv(I_1**2, I_2).sum(-1).mean(-2) + # B₀ has units of λ⁻¹. + # (λB₀)³ d(λB₀)⁻¹ = B₀² λ³ d(λ⁻¹) = -B₀² λ dλ. + pitch_inv, weight = Bounce2D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) return jnp.sum( - batch_map(fun, data["pitch_inv"], pitch_batch_size) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 3, + batch_map(fun, pitch_inv, opts.pitch_batch_size) * weight / pitch_inv**3, axis=-1, ) B0 = data["max_tz |B|"] - scalar = (jnp.pi * data["R0"]) ** 2 / (num_transit * 4 * 2**0.5) - + scalar = (jnp.pi * data["R0"]) ** 2 / ( + opts.field_period_transits / grid.NFP * 4 * 2**0.5 + ) + out = Bounce2D.batch( + eps_32, + {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, + data, + angle, + grid, + surf_batch_size=opts.surf_batch_size, + ) + assert out.ndim == 1 data["effective ripple 3/2"] = scalar * ( - (B0 / data["<|grad(rho)|>"]) ** 2 - * Bounce2D.batch( - eps_32, - {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, - data, - angle, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["V_psi"] + (B0 / data["<|grad(rho)|>"]) ** 2 * grid.expand(out) / data["V_psi"] ) return data diff --git a/desc/compute/_old.py b/desc/compute/_old.py index 17b4bc6181..032bcc6a27 100644 --- a/desc/compute/_old.py +++ b/desc/compute/_old.py @@ -1,44 +1,37 @@ """Old compute functions. These do not appear in the public documentation under the list of variables. +They are kept for verification and correctness testing. """ from functools import partial -from orthax.legendre import leggauss - from desc.backend import jit, jnp -from ..integrals.bounce_integral import Bounce1D -from ..integrals.quad_utils import ( - automorphism_sin, - chebgauss2, - get_quadrature, - grad_automorphism_sin, +from ..integrals.bounce_integral import Bounce1D, BounceOptions +from ..utils import safediv +from ._fast_ion import ( + _gamma_c_data, + _poloidal_drift_periodic, + _radial_drift_1, + _radial_drift_2, + _v_tau, ) -from ..utils import cross, dot, safediv -from ._fast_ion import _drift1, _drift2, _radial_drift, _v_tau -from ._neoclassical import _bounce_doc, _dI_1, _dI_2 +from ._neoclassical import _dI_1, _dI_2 from .data_index import register_compute_fun _bounce1D_doc = { - "num_well": _bounce_doc["num_well"], - "num_quad": _bounce_doc["num_quad"], - "num_pitch": _bounce_doc["num_pitch"], - "surf_batch_size": _bounce_doc["surf_batch_size"], - "quad": _bounce_doc["quad"], + "num_well": BounceOptions._doc["num_well"], + "num_quad": BounceOptions._doc["num_quad"], + "num_pitch": BounceOptions._doc["num_pitch"], + "surf_batch_size": BounceOptions._doc["surf_batch_size"], + "quad": BounceOptions._doc["quad"], } @register_compute_fun( name="old effective ripple 3/2", - label=( - # ε¹ᐧ⁵ = π/(8√2) R₀²〈|∇ψ|〉⁻² B₀⁻¹ ∫ dλ λ⁻² 〈 ∑ⱼ Hⱼ²/Iⱼ 〉 - "\\epsilon_{\\mathrm{eff}}^{3/2} = \\frac{\\pi}{8 \\sqrt{2}} " - "R_0^2 \\langle \\vert\\nabla \\psi\\vert \\rangle^{-2} " - "B_0^{-1} \\int d\\lambda \\lambda^{-2} " - "\\langle \\sum_j H_j^2 / I_j \\rangle" - ), + label="\\epsilon_{\\mathrm{eff}}^{3/2}", units="~", units_long="None", description="Effective ripple modulation amplitude to 3/2 power", @@ -73,48 +66,35 @@ def _epsilon_32_1D(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency grid = transforms["grid"].source_grid - num_well = kwargs.get("num_well", None) - num_pitch = kwargs.get("num_pitch", 51) - surf_batch_size = kwargs.get("surf_batch_size", 1) - quad = ( - kwargs["quad"] if "quad" in kwargs else chebgauss2(kwargs.get("num_quad", 32)) - ) + opts = BounceOptions.guess(eta=1, grid=grid, Y_B=grid.num_zeta, **kwargs) + num_well = kwargs.get("num_well", -1) def eps_32(data): - """(∂ψ/∂ρ)⁻² B₀⁻³ ∫ dλ λ⁻² ∑ⱼ Hⱼ²/Iⱼ.""" - # B₀ has units of λ⁻¹. - # Nemov's ∑ⱼ Hⱼ²/Iⱼ = (∂ψ/∂ρ)² (λB₀)³ (I₁²/I₂).sum(-1). - # (λB₀)³ d(λB₀)⁻¹ = B₀² λ³ d(λ⁻¹) = -B₀² λ dλ. - bounce = Bounce1D(grid, data, quad, is_reshaped=True) - I_1, I_2 = bounce.integrate( - [_dI_1, _dI_2], - data["pitch_inv"], - data, - ["|grad(rho)|*kappa_g"], - num_well=num_well, + pitch_inv, weight = Bounce1D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) + I_1, I_2 = Bounce1D(grid, data, opts.quad).integrate( + [_dI_1, _dI_2], pitch_inv, data, ["|grad(rho)|*kappa_g"], num_well=num_well ) return jnp.sum( - safediv(I_1**2, I_2).sum(-1).mean(-2) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 3, + safediv(I_1**2, I_2).sum(-1).mean(-2) * weight / pitch_inv**3, axis=-1, ) B0 = data["max_tz |B|"] scalar = jnp.pi / (8 * 2**0.5) * data["R0"] ** 2 - + out = Bounce1D.batch( + eps_32, + {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, + data, + grid, + surf_batch_size=opts.surf_batch_size, + ) + assert out.ndim == 1 data["old effective ripple 3/2"] = ( (B0 / data["<|grad(rho)|>"]) ** 2 * scalar - * Bounce1D.batch( - eps_32, - {"|grad(rho)|*kappa_g": data["|grad(rho)|"] * data["kappa_g"]}, - data, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) + * grid.expand(out) / data["fieldline length"] ) return data @@ -206,73 +186,44 @@ def _Gamma_c_1D(params, transforms, profiles, data, **kwargs): """ # noqa: unused dependency grid = transforms["grid"].source_grid - num_pitch = kwargs.get("num_pitch", 65) - num_well = kwargs.get("num_well", None) - surf_batch_size = kwargs.get("surf_batch_size", 1) - quad = ( - kwargs["quad"] - if "quad" in kwargs - else get_quadrature( - leggauss(kwargs.get("num_quad", 32)), - (automorphism_sin, grad_automorphism_sin), - ) - ) + opts = BounceOptions.guess(eta=-2, grid=grid, Y_B=grid.num_zeta, **kwargs) + num_well = kwargs.get("num_well", -1) def Gamma_c(data): - bounce = Bounce1D(grid, data, quad, is_reshaped=True) - points = bounce.points(data["pitch_inv"], num_well) - v_tau, drift1, drift2 = bounce.integrate( - [_v_tau, _drift1, _drift2], - data["pitch_inv"], + pitch_inv, weight = Bounce1D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) + bounce = Bounce1D(grid, data, opts.quad) + points = bounce.points(pitch_inv, num_well) + v_tau, radial_drift, poloidal_drift = bounce.integrate( + [_v_tau, _radial_drift_1, _poloidal_drift_periodic], + pitch_inv, data, ["|grad(psi)|*kappa_g", "|B|_r|v,p", "K"], points, ) - # This is γ_c π/2. - gamma_c = jnp.arctan( + gamma_c_pi_over_2 = jnp.arctan( safediv( - drift1, - drift2 + radial_drift, + poloidal_drift * bounce.interp_to_argmin(data["|grad(rho)|*|e_alpha|r,p|"], points), ) ) return jnp.sum( - (v_tau * gamma_c**2).sum(-1).mean(-2) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) * weight / pitch_inv**2, axis=-1, ) - fun_data = { - "|grad(psi)|*kappa_g": data["|grad(psi)|"] * data["kappa_g"], - "|grad(rho)|*|e_alpha|r,p|": data["|grad(rho)|"] * data["|e_alpha|r,p|"], - "|B|_r|v,p": data["|B|_r|v,p"], - "K": data["iota_r"] - * dot(cross(data["grad(psi)"], data["b"]), data["grad(phi)"]) - - (2 * data["|B|_r|v,p"] - data["|B|"] * data["B^phi_r|v,p"] / data["B^phi"]), - } + out = Bounce1D.batch( + Gamma_c, _gamma_c_data(data), data, grid, surf_batch_size=opts.surf_batch_size + ) + assert out.ndim == 1 data["old Gamma_c"] = ( - Bounce1D.batch( - Gamma_c, - fun_data, - data, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["fieldline length"] - / (2**1.5 * jnp.pi) + grid.expand(out) / data["fieldline length"] / (2**1.5 * jnp.pi) ) return data -def _poloidal_drift(data, B, pitch): - return safediv( - data["gbdrift"] * (1 - 0.5 * pitch * B), jnp.sqrt(jnp.abs(1 - pitch * B)) - ) - - @register_compute_fun( name="old Gamma_c Velasco", label=( @@ -304,56 +255,44 @@ def _Gamma_c_Velasco_1D(params, transforms, profiles, data, **kwargs): J.L. Velasco et al. 2021 Nucl. Fusion 61 116059. https://doi.org/10.1088/1741-4326/ac2994. - This expression has a secular term that drives the result to zero as the number - of toroidal transits increases if the secular term is not averaged out from the - singular integrals. It is observed that this implementation does not average - out the secular term. Currently, an optimization using this metric may need - to be evaluated by measuring decrease in Γ_c at a fixed number of toroidal - transits. """ # noqa: unused dependency grid = transforms["grid"].source_grid - num_well = kwargs.get("num_well", None) - num_pitch = kwargs.get("num_pitch", 65) - surf_batch_size = kwargs.get("surf_batch_size", 1) - quad = ( - kwargs["quad"] - if "quad" in kwargs - else get_quadrature( - leggauss(kwargs.get("num_quad", 32)), - (automorphism_sin, grad_automorphism_sin), + opts = BounceOptions.guess(eta=-1, grid=grid, Y_B=grid.num_zeta, **kwargs) + num_well = kwargs.get("num_well", -1) + + def _poloidal_drift_secular(data, B, pitch): + return safediv( + data["gbdrift"] * (1 - 0.5 * pitch * B), + jnp.sqrt(jnp.abs(1 - pitch * B)), ) - ) def Gamma_c(data): - bounce = Bounce1D(grid, data, quad, is_reshaped=True) - v_tau, radial_drift, poloidal_drift = bounce.integrate( - [_v_tau, _radial_drift, _poloidal_drift], - data["pitch_inv"], + pitch_inv, weight = Bounce1D.pitch_quad( + data["min_tz |B|"], data["max_tz |B|"], opts.pitch_quad + ) + v_tau, radial_drift, poloidal_drift = Bounce1D(grid, data, opts.quad).integrate( + [_v_tau, _radial_drift_2, _poloidal_drift_secular], + pitch_inv, data, ["cvdrift0", "gbdrift"], num_well=num_well, ) - # This is γ_c π/2. - gamma_c = jnp.arctan(safediv(radial_drift, poloidal_drift)) + gamma_c_pi_over_2 = jnp.arctan(safediv(radial_drift, poloidal_drift)) return jnp.sum( - (v_tau * gamma_c**2).sum(-1).mean(-2) - * data["pitch_inv weight"] - / data["pitch_inv"] ** 2, + (v_tau * gamma_c_pi_over_2**2).sum(-1).mean(-2) * weight / pitch_inv**2, axis=-1, ) + out = Bounce1D.batch( + Gamma_c, + {"cvdrift0": data["cvdrift0"], "gbdrift": data["gbdrift"]}, + data, + grid, + surf_batch_size=opts.surf_batch_size, + ) + assert out.ndim == 1 data["old Gamma_c Velasco"] = ( - Bounce1D.batch( - Gamma_c, - {"cvdrift0": data["cvdrift0"], "gbdrift": data["gbdrift"]}, - data, - grid, - num_pitch, - surf_batch_size, - expand_out=True, - ) - / data["fieldline length"] - / (2**1.5 * jnp.pi) + grid.expand(out) / data["fieldline length"] / (2**1.5 * jnp.pi) ) return data diff --git a/desc/compute/utils.py b/desc/compute/utils.py index 1d82010658..21c176bb77 100644 --- a/desc/compute/utils.py +++ b/desc/compute/utils.py @@ -88,7 +88,7 @@ def compute( # noqa: C901 "instead.", DeprecationWarning, ) - bad_kwargs = kwargs.keys() - allowed_kwargs + bad_kwargs = kwargs.keys() - allowed_kwargs - {"num_transit"} if len(bad_kwargs) > 0: raise ValueError(f"Unrecognized argument(s): {bad_kwargs}") diff --git a/desc/grid.py b/desc/grid.py index 43d6963387..0d9090b8d3 100644 --- a/desc/grid.py +++ b/desc/grid.py @@ -584,7 +584,10 @@ def expand(self, x, surface_label="rho"): """ surface_label = self.get_label(surface_label) - errorif(len(x) != getattr(self, f"num_{surface_label}")) + errorif( + len(x) != getattr(self, f"num_{surface_label}"), + msg=f"Got unexpected len(x) of {len(x)}.", + ) return x[getattr(self, f"inverse_{surface_label}_idx")] def copy_data_from_other(self, x, other_grid, surface_label="rho", tol=1e-14): diff --git a/desc/integrals/_bounce_utils.py b/desc/integrals/_bounce_utils.py index fee1609022..fa21dc42a7 100644 --- a/desc/integrals/_bounce_utils.py +++ b/desc/integrals/_bounce_utils.py @@ -22,7 +22,6 @@ ) from interpax_fft._series import _add2legend, _plot_intersect from matplotlib import pyplot as plt -from orthax.chebyshev import chebvander from desc.backend import dct, ifft, jax, jnp from desc.integrals._interp_utils import ( @@ -37,10 +36,10 @@ from desc.integrals.quad_utils import bijection_from_disc from desc.utils import atleast_nd, flatten_mat, setdefault -_sentinel = -1e5 - -def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): +def _bounce_points( + pitch_inv, knots, B, num_well=-1, *, sentinel=-1.0, return_mask=False +): """Compute the bounce points given 1D spline of B and pitch λ. Parameters @@ -56,7 +55,7 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): Polynomial coefficients of the spline of B in local power basis. Last axis enumerates the coefficients of power series. Second to last axis enumerates the polynomials that compose a particular spline. - num_well : int or None + num_well : int Specify to return the first ``num_well`` pairs of bounce points for each pitch and field line. Choosing ``-1`` will detect all wells, but due to current limitations in JAX this will have worse performance. @@ -69,6 +68,10 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): If there were fewer wells detected along a field line than the size of the last axis of the returned arrays, then that axis is padded with zero. + sentinel : float + Sentinel value which should be less than ζ coordinate of all bounce points, + which can be guaranteed by choosing branch cut for α appropriately. + Default is -1. return_mask : bool Whether to return the mask ``z1 B.shape[-2]: + # The number of interior minima for C¹ continuous cubic spline must be < N, + # and every minima must be a simple root. + num_well = B.shape[-2] + B = B[..., None, :, :] intersect = polyroot_vec( c=B, @@ -106,11 +114,11 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): # Transform out of local power basis expansion. intersect = flatten_mat(intersect + knots[:-1, None]) - z1 = take_mask(intersect, z1, size=num_well, fill_value=_sentinel) - z2 = take_mask(intersect, z2, size=num_well, fill_value=_sentinel) + z1 = take_mask(intersect, z1, size=num_well, fill_value=sentinel) + z2 = take_mask(intersect, z2, size=num_well, fill_value=sentinel) del intersect - mask = (z1 > _sentinel) & (z2 > _sentinel) + mask = (z1 > sentinel) & (z2 > sentinel) # Set to zero so integration is over set of measure zero # and basis functions are faster to evaluate in downstream routines. z1 = jnp.where(mask, z1, 0.0) @@ -118,12 +126,13 @@ def bounce_points(pitch_inv, knots, B, num_well=-1, return_mask=False): return (z1, z2, mask) if return_mask else (z1, z2) -def _newton(o, pitch_inv, z1, z2, mask, nufft_eps): - """Newton step using maps used in the quadrature. +def _halley(o, pitch_inv, z, mask, nufft_eps, diagnostic=0): + """Solve for the bounce points using the maps used in quadrature. - An error of ε in a bounce point manifests - * 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹. - * 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. + Halley (Schröder second kind) irrational step. + + The bounce parameters Y_B and Y should be high enough that + initial guess is in basin of attraction for Halley step. Parameters ---------- @@ -131,77 +140,153 @@ def _newton(o, pitch_inv, z1, z2, mask, nufft_eps): Object instance. pitch_inv : jnp.ndarray Shape broadcasts with (num ρ, num α, num pitch). - z1, z2 : tuple[jnp.ndarray] - Shape (num ρ, num α, num pitch, num well). + z: jnp.ndarray + Shape (2, num ρ ?, num α, num pitch, num well). + Bounce points. mask : jnp.ndarray - Shape (num ρ, num α, num pitch, num well). + Shape (num ρ ?, num α, num pitch, num well). Subset of points to refine. nufft_eps : float - Desired error ε of the returned bounce points. + Precision requested for interpolation with non-uniform fast Fourier transform + (NUFFT). If less than ``1e-14`` then NUFFT will not be used. Should satisfy ε < εᵢₙ² where εᵢₙ is the error of the input points. + diagnostic : int + Positive integer denoting iteration step to print. Returns ------- - z1, z2 : tuple[jnp.ndarray] - Shape (num ρ, num α, num pitch, num well). + z : jnp.ndarray + Shape (2, num ρ ?, num α, num pitch, num well). """ - shape = (*z1.shape[:-2], 2, *z1.shape[-2:]) + t, B = _halley_coefficients(o) + + # calling this method with shapes (1, b=2, ρ?,α, λ, w) + # (3, 1, ρ?,α, 1, X, Y). + t, dt, dt2 = o._theta.eval1d(z[None], t[:, None, ..., None, :, :]) + # shapes match z, i.e. (b, ρ ?, α, λ, w) + + if no_nufft(nufft_eps): + # Halley step is free compared to recomputing the basis. + z_eff = z if o._num_z > 1 else jnp.zeros((1,) * z.ndim) + dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2 = jnp.einsum( + "...czt, b...apwz, b...apwt -> cb...apw", + B, + jnp.exp(1j * o._modes_z * z_eff[..., None]), + jnp.exp(1j * o._modes_t * t[..., None]), + optimize=[(0, 1), (0, 1)], + ).real + else: + dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2 = _acrobatics( + z, t, B, o._NFP, nufft_eps, mask + ) - z = flatten_mat(jnp.stack((z1, z2), axis=-3), 3) - t, dt_dz = o._theta.eval1d( - z[None], - jnp.stack( - [ - o._theta.cheb, - chebder(o._theta.cheb, scl=o._NFP / jnp.pi, axis=-1, keepdims=True), - ] - ), - ) - dt_dz = dt_dz.reshape(shape) - t = flatten_mat(t) - z = flatten_mat(z) - - B = nufft2d2r( - z, - t, - jnp.concatenate( - [ - o._c["|B|"], - o._c["|B|"] * (1j * o._modes_z)[:, None], - o._c["|B|"] * (1j * o._modes_t), - ], - -3, - ), - (0, 2 * jnp.pi / o._NFP), - vec=True, - eps=nufft_eps, - mask=( - None - if _JF_BUG - else flatten_mat(jnp.broadcast_to(mask[..., None, :, :], shape), 4) - ), - ) - B, dB_dz, dB_dt = ( - B.reshape(3, *shape) - if B.ndim == 2 - # reshape before swap to avoid memory copy - else B.reshape(shape[0], 3, *shape[1:]).swapaxes(0, 1) + f = B - pitch_inv[..., None] + df = dB_dz + dB_dt * dt + df2 = dB_dz2 + 2 * dB_dzdt * dt + dB_dt2 * dt**2 + dB_dt * dt2 + df2 = df**2 - 2 * f * df2 + update = 2 * f / (df + jnp.sign(df) * jnp.sqrt(jnp.where(df2 > 0, df2, df**2))) + + del f, df, df2, dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2, t, dt, dt2 + + if diagnostic: + jax.debug.print( + "After {iteration:1d} iteration(s) | " + "ζ₁₂(w) error mean = {:5.0e} | std. dev. = {:5.0e} | max = {:5.0e}", + jnp.abs(update).mean(where=mask), + jnp.abs(update).std(where=mask), + jnp.abs(update).max(where=mask, initial=-jnp.inf), + iteration=diagnostic - 1, + ordered=True, + ) + + return _safe_update(mask, z, update, FENCE=2 * jnp.pi / o._NFP) + + +def _safe_update(mask, old, update, FENCE): + """Returns old - update where intervals are preserved and update < FENCE.""" + new = old - update + return jnp.where( + mask & (new[0] < new[1]) & (jnp.abs(update) < FENCE), + new, + old, ) - z = z.reshape(shape) - dz = (B - pitch_inv[..., None, :, None]) / (dB_dz + dB_dt * dt_dz) - Z = z - dz - mask = mask & (Z[..., 0, :, :] < Z[..., 1, :, :]) # Deny interval inversion. - mask = mask[..., None, :, :] & (jnp.abs(dz) < 1e-1) # Deny large updates. - z = jnp.where(mask, Z, z) - return z[..., 0, :, :], z[..., 1, :, :] +def _halley_coefficients(o, jvp=False): + """Returns coefficient arrays for the nonlinear solve. + + Parameters + ---------- + o : Bounce2D + Object instance. + jvp : bool + Whether to return only the coefficients needed for the jvp. + + Returns + ------- + t, B : tuple[jnp.ndarray] + Coefficient arrays. + t, dt, dt2 + dB_dz, dB_dt, B, dB_dz2, dB_dzdt, dB_dt2 + + """ + t = [ + o._theta.cheb, + chebder(o._theta.cheb, scl=o._NFP / jnp.pi, axis=-1, keepdims=True), + ] + B = [ + o._c["|B|"] * (1j * o._modes_z)[:, None], + o._c["|B|"] * (1j * o._modes_t), + ] + + if not jvp: + B += [ + o._c["|B|"], + o._c["|B|"] * (-o._modes_z**2)[:, None], + o._c["|B|"] * (-o._modes_z[:, None] * o._modes_t), + o._c["|B|"] * (-o._modes_t**2), + ] + t.append(chebder(t[1], scl=o._NFP / jnp.pi, axis=-1, keepdims=True)) + + # shape is (# of funs e.g. 2 or 3, ρ ?, α, X, Y) + t = jnp.stack(t) + # shape is (ρ ?, # of funs, z modes, t modes) + B = jnp.concatenate(B, -3) + return t, B + + +def _acrobatics(z, t, c, NFP, eps, mask): + # Some reshape acrobatics required due to frankenstein vectorization of jax-finufft. + t = t.swapaxes(0, -4) + swapped_shape = t.shape + t = flatten_mat(t, 4) # shape is (ρ, points per ρ surface) + # or just ( points per ρ surface) + return ( + nufft2d2r( + flatten_mat(z.swapaxes(0, -4), 4), + t, + c, + (0, 2 * jnp.pi / NFP), + vec=True, + eps=eps, + mask=( + None + if _JF_BUG + else flatten_mat( + jnp.broadcast_to(mask[None], (2,) + mask.shape).swapaxes(0, -4), 4 + ) + ), + ) + .swapaxes(0, -2) # so that first axis splits into e.g. dB_dz, dB_dt, B + .reshape((-1,) + swapped_shape) # then shape is (-1, ρ ?, b, α, λ, w) + .swapaxes(1, -4) # recover shape (-1, b, ρ ?, α, λ, w) + ) @partial(jax.custom_jvp, nondiff_argnums=(2,)) -def regular_points(o, pitch_inv, num_well): - """Bounce points then Newton, with regularized jvp. +def bounce_points(o, pitch_inv, num_well): + """Bounce points then iterative solve, with regularized ift jvp. Parameters ---------- @@ -213,16 +298,17 @@ def regular_points(o, pitch_inv, num_well): The usual suspect. """ - return _newton( - o, - pitch_inv, - *bounce_points(pitch_inv, o._c["knots"], o._c["B(z)"], num_well, True), - min(o._nufft_eps, 1e-10), + *z, mask = _bounce_points( + pitch_inv, o._c["knots"], o._B, num_well, return_mask=True + ) + z = jnp.stack(z) + return _halley( + o, pitch_inv, z, mask, nufft_eps=min(o._nufft_eps, 1e-10), diagnostic=0 ) -@regular_points.defjvp -def regular_points_jvp(num_well, primals, tangents): +@bounce_points.defjvp +def bounce_points_jvp(num_well, primals, tangents): """Implicit function theorem with regularization. Regularization used to smooth the discretized system so that it recognizes @@ -231,7 +317,7 @@ def regular_points_jvp(num_well, primals, tangents): References ---------- - See supplementary information in DESC/publications/unalmis2025. + See supplementary information in publications/unalmis2025. """ # Cannot mix primals and tangents; see https://github.com/jax-ml/jax/issues/36319. @@ -239,55 +325,45 @@ def regular_points_jvp(num_well, primals, tangents): o, p = primals do, dp = tangents - z1, z2 = regular_points(o, p, num_well) - - shape = (*z1.shape[:-2], 2, *z1.shape[-2:]) - - z = flatten_mat(jnp.stack((z1, z2), axis=-3), 3) - t, dt_dz = o._theta.eval1d( - z[None], - jnp.stack( - [ - o._theta.cheb, - chebder(o._theta.cheb, scl=o._NFP / jnp.pi, axis=-1, keepdims=True), - ] - ), - ) - dt_do = o._theta.eval1d(z, do._theta.cheb).reshape(shape) - dt_dz = dt_dz.reshape(shape) - t = flatten_mat(t) - z = flatten_mat(z) - - mask = (z1 < z2)[..., None, :, :] + z = bounce_points(o, p, num_well) + mask = z[0] < z[1] nufft_eps = min(o._nufft_eps, 1e-10) - dB_dz = nufft2d2r( - z, - t, - jnp.concatenate( - [o._c["|B|"] * (1j * o._modes_z)[:, None], o._c["|B|"] * (1j * o._modes_t)], - -3, - ), - (0, 2 * jnp.pi / o._NFP), - vec=True, - eps=nufft_eps, - mask=None if _JF_BUG else flatten_mat(jnp.broadcast_to(mask, shape), 4), - ) - dB_do = nufft2d2r( - z, - t, - do._c["|B|"].squeeze(-3), - (0, 2 * jnp.pi / o._NFP), - eps=nufft_eps, - mask=None if _JF_BUG else flatten_mat(jnp.broadcast_to(mask, shape), 4), - ).reshape(shape) - - dB_dz, dB_dt = ( - dB_dz.reshape(2, *shape) - if dB_dz.ndim == 2 - # reshape before swap to avoid memory copy - else dB_dz.reshape(shape[0], 2, *shape[1:]).swapaxes(0, 1) - ) + t, dB_dz = _halley_coefficients(o, jvp=True) + + # calling this method with shapes (1, b=2, ρ?,α, λ, w) + # (2, 1, ρ?,α, 1, X, Y). + t, dt_dz = o._theta.eval1d(z[None], t[:, None, ..., None, :, :]) + dt_do = o._theta.eval1d(z, do._theta.cheb[None, ..., None, :, :]) + # shapes match z, i.e. (b, ρ ?, α, λ, w) + + if no_nufft(nufft_eps): + z_eff = jnp.exp( + 1j + * o._modes_z + * (z if o._num_z > 1 else jnp.zeros((1,) * z.ndim))[..., None] + ) + t = jnp.exp(1j * o._modes_t * t[..., None]) + + dB_dz, dB_dt = jnp.einsum( + "...czt, b...apwz, b...apwt -> cb...apw", + dB_dz, + z_eff, + t, + optimize=[(0, 1), (0, 1)], + ).real + dB_do = jnp.einsum( + "...zt, b...apwz, b...apwt -> b...apw", + do._c["|B|"].squeeze(-3), + z_eff, + t, + optimize=[(0, 1), (0, 1)], + ).real + + del z_eff, t + else: + dB_dz, dB_dt = _acrobatics(z, t, dB_dz, o._NFP, nufft_eps, mask) + (dB_do,) = _acrobatics(z, t, do._c["|B|"], o._NFP, nufft_eps, mask) # chain rule to move from (∂/∂ζ)|ρ,θ to (∂/∂ζ)|ρ,a dB_dz += dB_dt * dt_dz @@ -298,9 +374,9 @@ def regular_points_jvp(num_well, primals, tangents): dB_dz, dB_dz + jnp.copysign(_eps, dB_dz.real), ) - dz12 = jnp.where(mask, (dp[..., None, :, None] - dB_do) / dB_dz, 0.0) + dz = jnp.where(mask, (dp[..., None] - dB_do) / dB_dz, 0.0) - return (z1, z2), (dz12[..., 0, :, :], dz12[..., 1, :, :]) + return z, dz def set_default_plot_kwargs(kwargs, l=None, m=None): @@ -335,7 +411,6 @@ def check_bounce_points(z1, z2, pitch_inv, knots, B, plot=True, **kwargs): "Second to last axis does not enumerate polynomials of spline. " f"Spline shape {B.shape}. Knots shape {knots.shape}." ) - assert knots[0] > _sentinel, "Reduce sentinel in desc/integrals/_bounce_utils.py." z1 = atleast_nd(4, z1) z2 = atleast_nd(4, z2) @@ -589,7 +664,7 @@ def plot_ppoly( def get_mins(knots, B, num_mins=-1, fill_value=0.0): - """Return minima of (z*, B(z*)) within open interval defined by knots. + """Return minima of (z*, B(z*)) within interval defined by knots. Parameters ---------- @@ -601,7 +676,7 @@ def get_mins(knots, B, num_mins=-1, fill_value=0.0): Polynomial coefficients of the spline of B in local power basis. Last axis enumerates the coefficients of power series. Second to last axis enumerates the polynomials that compose a particular spline. - num_mins : jnp.ndarray + num_mins : int Number of minima to return. Otherwise returns maximum possible. fill_value : float If there were less than ``num_mins`` minima detected, then the result @@ -643,7 +718,11 @@ def get_mins(knots, B, num_mins=-1, fill_value=0.0): def argmin(z1, z2, f, mins, B_mins): - """Let E = {ζ ∣ ζ₁ < ζ < ζ₂} and A ∈ argmin_E B(ζ). Returns f(A). + """Returns f at argmin of B between ``z1`` and ``z2``. + + Let E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Given the minima of B and f interpolated to those minima, + returns {f ∘ A(w)}. Parameters ---------- @@ -654,12 +733,18 @@ def argmin(z1, z2, f, mins, B_mins): f : jnp.ndarray Function interpolated to ``mins``. Shape (..., num mins). + mins : jnp.ndarray + Minima of B. + Shape ``f.shape``. + B_mins : jnp.ndarray + B interpolated to ``mins``. + Shape ``f.shape``. Returns ------- f : jnp.ndarray Shape (..., num pitch, num well). - ``f`` at the minimum of ``B`` between ``z1`` and ``z2``. + Returns f at argmin of B between ``z1`` and ``z2``. """ assert z1.ndim > 1 and z2.ndim > 1 @@ -681,7 +766,7 @@ def argmin(z1, z2, f, mins, B_mins): return jnp.take_along_axis(f[..., None, None, :], where, axis=-1).squeeze(-1) -def get_alphas(alpha, iota, num_transit, NFP): +def get_alphas(alpha, iota, field_period_transits, NFP): """Get set of field line poloidal coordinates {Aᵢ | Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎)}. Parameters @@ -692,24 +777,24 @@ def get_alphas(alpha, iota, num_transit, NFP): iota : jnp.ndarray Shape (num ρ, ). Rotational transform normalized by 2π. - num_transit : int - Number of toroidal transits to follow field line. + field_period_transits : int + Number of field periods to follow field line. NFP: int - Number of field periods. + Number of field periods per toroidal transit. Returns ------- alphas : jnp.ndarray - Shape (num α, num ρ, num transit * NFP). + Shape (num α, num ρ, num field periods). Set of field line poloidal coordinates {Aᵢ | Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎)}. """ alpha = alpha[:, None, None] iota = iota[:, None] - return alpha + iota * (2 * jnp.pi / NFP) * jnp.arange(num_transit * NFP) + return alpha + iota * (2 * jnp.pi / NFP) * jnp.arange(field_period_transits) -def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): +def theta_on_fieldlines(angle, iota, alpha, field_period_transits, NFP, *, X_min=24): """Parameterize θ on field lines α. Parameters @@ -723,10 +808,10 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): alpha : jnp.ndarray Shape (num α, ). Starting field line poloidal labels {αᵢ₀}. - num_transit : int - Number of toroidal transits to follow field line. + field_period_transits : int + Number of field periods to follow field line. NFP : int - Number of field periods. + Number of field periods per toroidal transit. X_min : int See notes section. This parameter should never be changed. It is included in the function signature for code optics only. @@ -743,8 +828,8 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): Set of 1D Chebyshev spectral coefficients of θ on field lines. {θ_αᵢⱼ : ζ ↦ θ(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line ``α[i]``. Each Chebyshev series approximates - θ over one toroidal transit. ``theta.cheb`` broadcasts with - shape (num ρ, num α, num transit * NFP, max(1,7Y//8)). + θ over one field period. ``theta.cheb`` broadcasts with + shape (num ρ, num α, num field periods, max(1,7Y//8)). Notes ----- @@ -781,7 +866,7 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): domain = (0, 2 * jnp.pi / NFP) # peeling off field lines - alpha = get_alphas(alpha, iota, num_transit, NFP) + alpha = get_alphas(alpha, iota, field_period_transits, NFP) if angle.ndim == 2: alpha = alpha.squeeze(1) @@ -796,7 +881,7 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): ) alpha = alpha.swapaxes(0, -2) delta = delta.at[..., 0].add(alpha) # This is now θ = α + δ. - assert delta.shape == (*angle.shape[:-2], num_alpha, num_transit * NFP, Y) + assert delta.shape == (*angle.shape[:-2], num_alpha, field_period_transits, Y) if X < X_min: # This is needed as our algorithm assumes continuity of |B| along field @@ -806,7 +891,7 @@ def theta_on_fieldlines(angle, iota, alpha, num_transit, NFP, *, X_min=24): return PiecewiseChebyshevSeries(delta, domain) -def fast_chebyshev(theta, f, Y, num_t, modes_t, modes_z, *, vander=None): +def fast_chebyshev(theta, f, Y, modes_t, modes_z, *, vander=None): """Compute Chebyshev approximation of ``f`` on field lines using fast transforms. Parameters @@ -815,16 +900,14 @@ def fast_chebyshev(theta, f, Y, num_t, modes_t, modes_z, *, vander=None): Set of 1D Chebyshev spectral coefficients of θ on field lines. {θ_αᵢⱼ : ζ ↦ θ(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line αᵢ. Each Chebyshev series approximates - θ over one toroidal transit. ``theta.cheb`` should broadcast with - shape (num ρ, num α, num transit * NFP, theta.Y). + θ over one field period. ``theta.cheb`` should broadcast with + shape (num ρ, num α, num field periods, theta.Y). f : jnp.ndarray Shape broadcasts with (num ρ, 1, modes_z.size, modes_t.size). Fourier transform of f(θ, ζ) as returned by ``Bounce2D.fourier``. Y : int Chebyshev spectral resolution for ``f`` over a field period. Preferably power of 2. - num_t : int - Fourier resolution in poloidal direction. modes_t : jnp.ndarray Real FFT Fourier modes in poloidal direction. modes_z : jnp.ndarray @@ -838,25 +921,33 @@ def fast_chebyshev(theta, f, Y, num_t, modes_t, modes_z, *, vander=None): Set of 1D Chebyshev spectral coefficients of ``f`` on field lines. {f_αᵢⱼ : ζ ↦ f(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line αᵢ. Each Chebyshev series approximates - ``f`` over one toroidal transit. ``f.cheb`` broadcasts with - shape (num ρ, num α, num transit * NFP, Y). + ``f`` over one field period. ``f.cheb`` broadcasts with + shape (num ρ, num α, num field periods, Y). """ + if f.shape[-2] == 1: # axisymmetric + vander = None + z_eff = jnp.zeros((1, 1)) + elif vander is None: + z_eff = cheb_pts(Y, theta.domain)[:, None] + else: + z_eff = None + # Let m, n denote the poloidal and toroidal Fourier resolution. We need to - # compute a set of 2D Fourier series each on non-uniform tensor product grids - # of size |𝛉|×|𝛇| where |𝛉| = num α × num transit × NFP and |𝛇| = Y. - # Partial summation is more efficient than direct evaluation when - # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| or equivalently n|𝛉| > n + |𝛉|. + # compute a set of 2D Fourier series on non-uniform tensor product grids of size + # |𝛉|×|𝛇| where |𝛉| = num α × num field periods × Y/z_eff and |𝛇| = z_eff. + # Partial summation is more efficient than direct evaluation since + # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| i.e. when n|𝛉| > n + |𝛉|. f = ifft_mmt( - cheb_pts(Y, theta.domain)[:, None] if vander is None else None, + z_eff, f, theta.domain, axis=-2, modes=modes_z, vander=vander, )[..., None, None, :, :] - f = irfft_mmt_pos(theta.evaluate(Y), f, num_t, modes=modes_t) + f = irfft_mmt_pos(theta.evaluate(Y), f, n=jnp.nan, modes=modes_t) f = cheb_from_dct(dct(f, type=2, axis=-1) / Y) f = PiecewiseChebyshevSeries(f, theta.domain) assert f.cheb.shape == (*theta.cheb.shape[:-1], Y) @@ -867,10 +958,8 @@ def fast_cubic_spline( theta, f, Y, - num_t, modes_t, modes_z, - NFP=1, nufft_eps=1e-6, *, vander_t=None, @@ -885,25 +974,20 @@ def fast_cubic_spline( Set of 1D Chebyshev spectral coefficients of θ on field lines. {θ_αᵢⱼ : ζ ↦ θ(αᵢⱼ, ζ) | αᵢⱼ ∈ Aᵢ} where Aᵢ = (αᵢ₀, αᵢ₁, ..., αᵢ₍ₘ₋₁₎) enumerates field line αᵢ. Each Chebyshev series approximates - θ over one toroidal transit. ``theta.cheb`` should broadcast with - shape (num ρ, num α, num transit * NFP, theta.Y). + θ over one field period. ``theta.cheb`` should broadcast with + shape (num ρ, num α, num field periods, theta.Y). f : jnp.ndarray Shape broadcasts with (num ρ, 1, modes_z.size, modes_t.size). Fourier transform of f(θ, ζ) as returned by ``Bounce2D.fourier``. Y : int - Number of knots per toroidal transit to interpolate ``f``. - This number will be rounded up to an integer multiple of ``NFP``. - num_t : int - Fourier resolution in poloidal direction. + Number of knots per field period to interpolate ``f``. modes_t : jnp.ndarray Real FFT Fourier modes in poloidal direction. modes_z : jnp.ndarray FFT Fourier modes in toroidal direction. - NFP : int - Number of field periods. nufft_eps : float - Precision requested for interpolation with non-uniform fast Fourier - transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. + Precision requested for interpolation with non-uniform fast Fourier transform + (NUFFT). If less than ``1e-14`` then NUFFT will not be used. vander_t : jnp.ndarray Precomputed transform matrix. vander_z : jnp.ndarray @@ -914,37 +998,32 @@ def fast_cubic_spline( Returns ------- f : jnp.ndarray - Shape broadcasts with (num ρ, num α, num transit * Y - 1, 4). + Shape broadcasts with (num ρ, num α, num field periods * Y - 1, 4). Polynomial coefficients of the spline of f in local power basis. Last axis enumerates the coefficients of power series. For a polynomial given by ∑ᵢⁿ cᵢ xⁱ, coefficient cᵢ is stored at ``f[...,n-i]``. Second to last axis enumerates the polynomials that compose a particular spline. knots : jnp.ndarray - Shape (num transit * Y). + Shape (num field periods * Y). Knots of spline ``f``. """ - assert theta.domain == (0, 2 * jnp.pi / NFP) - - lines = theta.cheb.shape[:-2] - num_transit = theta.X // NFP - - axisymmetric = f.shape[-2] == 1 - Y, num_z = round_up_rule(Y, NFP, axisymmetric) - x = jnp.linspace(-1, 1, (Y // NFP) if axisymmetric else num_z, endpoint=False) + x = jnp.linspace(-1, 1, Y, endpoint=False) z = bijection_from_disc(x, *theta.domain) + axisymmetric = f.shape[-2] == 1 + z_eff = 1 if axisymmetric else Y # Let m, n denote the poloidal and toroidal Fourier resolution. We need to - # compute a set of 2D Fourier series each on uniform (non-uniform) in ζ (θ) + # compute a set of 2D Fourier series on uniform (non-uniform) in ζ (θ) # tensor product grids of size - # |𝛉|×|𝛇| where |𝛉| = num α × num transit × NFP and |𝛇| = Y/NFP. - # Partial summation via FFT is more efficient than direct evaluation when - # mn|𝛉||𝛇| > m log(|𝛇|) |𝛇| + m|𝛉||𝛇| or equivalently n|𝛉| > log|𝛇| + |𝛉|. + # |𝛉|×|𝛇| where |𝛉| = num α × num field periods × Y/z_eff and |𝛇| = z_eff. + # Partial summation via FFT is more efficient than direct evaluation since + # mn|𝛉||𝛇| > m log(|𝛇|) |𝛇| + m|𝛉||𝛇| i.e. when n|𝛉| > log|𝛇| + |𝛉|. - if num_z >= f.shape[-2]: + if z_eff >= f.shape[-2]: f = f.squeeze(-3) - p = num_z - f.shape[-2] + p = z_eff - f.shape[-2] p = (p // 2, p - p // 2) pad = [(0, 0)] * f.ndim pad[-2] = p if (f.shape[-2] % 2 == 0) else p[::-1] @@ -959,34 +1038,39 @@ def fast_cubic_spline( modes=modes_z, vander=vander_z, ) + # f shape is (..., z_eff, modes_t.size) + + lines = theta.cheb.shape[:-2] # (..., num α) + field_period_transits = theta.X # θ at uniform ζ on field lines - t = idct_mmt( - x, - theta.cheb.reshape(*lines, num_transit, NFP, 1, theta.Y), - vander=vander_t, - ) - if axisymmetric: - t = t.reshape(*lines, num_transit, -1, 1) + t = idct_mmt(x, theta.cheb[..., None, :], vander=vander_t) + assert t.shape == (*lines, field_period_transits, Y) - if nufft_eps < 1e-14 or f.shape[-1] < 14: - # second condition for GPU - f = f[..., None, None, None, :, :] - f = irfft_mmt_pos(t, f, num_t, modes=modes_t) + if no_nufft(nufft_eps) or f.shape[-1] <= 16: + f = f[..., None, None, :, :] + f = irfft_mmt_pos(t, f, n=jnp.nan, modes=modes_t) + assert f.shape == t.shape else: - if len(lines) > 1: - t = t.transpose(0, 4, 1, 2, 3).reshape(lines[0], num_z, -1) + if axisymmetric: + t = t.reshape(*lines, -1, z_eff) + if len(lines) > 1: # then lines is (num ρ, num α) + t = t.transpose(0, 3, 1, 2).reshape(lines[0], z_eff, -1) else: - t = t.transpose(3, 0, 1, 2).reshape(num_z, -1) + t = t.transpose(2, 0, 1).reshape(z_eff, -1) + # t shape is (..., z_eff, num α × num field periods × Y/z_eff) f = nufft1d2r(t, f, eps=nufft_eps).mT + # f shape is (..., num α × num field periods × Y/z_eff, z_eff) f = f.reshape(*lines, -1) z = jnp.ravel( - z + (theta.domain[1] - theta.domain[0]) * jnp.arange(theta.X)[:, None] + z + + (theta.domain[1] - theta.domain[0]) + * jnp.arange(field_period_transits)[:, None] ) f = CubicSpline(x=z, y=f, axis=-1, check=check).c f = jnp.moveaxis(f, (0, 1), (-1, -2)) - assert f.shape == (*lines, num_transit * Y - 1, 4) + assert f.shape == (*lines, field_period_transits * Y - 1, 4) return f, z @@ -1066,70 +1150,6 @@ def truncate_rule(Y): return max(1, 7 * Y // 8) -def round_up_rule(Y, NFP, axisymmetric): - """Round Y up to NFP multiple. - - Returns - ------- - Y : int - Number of points per toroidal transit. - num_z : int - Number of points per field period. - axisymmetric : bool - Whether there toroidal smmetry. - - """ - if axisymmetric: - assert Y % NFP == 0, "Should set NFP = 1." - NFP = Y - num_z = (Y + NFP - 1) // NFP - return num_z * NFP, num_z - - -def Y_B_rule(grid, spline): - """Guess Y_B from grid resolution. - - Parameters - ---------- - grid : Grid - Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes - (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). - spline : bool - Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. - - Returns - ------- - Y_B : int - Desired resolution for algorithm to compute bounce points. - - """ - Y_B = (grid.num_theta + grid.num_zeta) // 2 - # Due to backwards compatibility reasons Y_B is expected to indicate - # resolution over full transit (a single field period) when spline is - # true (false). - return (Y_B * grid.NFP) if spline else Y_B - - -def num_well_rule(num_transit, NFP, mins_per_transit=None): - """Guess upper bound for number of wells based on spectrum. - - This should be loose enough that it is equivalent to ``num_well=None``, - but more performant. - """ - num_well = num_transit * (20 + NFP) - return ( - num_well - if mins_per_transit is None - else min(num_well, num_transit * mins_per_transit) - ) - - -def get_vander_spline(grid, Y, Y_B, NFP): - """Builds Vandermonde matrices for objectives.""" - Y_trunc = truncate_rule(Y) - Y_B, num_z = round_up_rule(Y_B, NFP, grid.num_zeta == 1) - x = jnp.linspace( - -1, 1, (Y_B // NFP) if (grid.num_zeta == 1) else num_z, endpoint=False - ) - return {"dct spline": chebvander(x, Y_trunc - 1)} +def no_nufft(nufft_eps): + """True if nuffts should not be used.""" + return nufft_eps < 1e-14 diff --git a/desc/integrals/_interp_utils.py b/desc/integrals/_interp_utils.py index b77a32e7ea..4699618eed 100644 --- a/desc/integrals/_interp_utils.py +++ b/desc/integrals/_interp_utils.py @@ -81,7 +81,7 @@ def nufft1d2r(x, f, domain=(0, 2 * jnp.pi), vec=False, eps=1e-6): Real function value at query points. """ - # This is optimized away under JIT if the operation is an idenity. + # This is optimized away under JIT if the operation is an identity. s = 2 * jnp.pi / (domain[1] - domain[0]) x = (x - domain[0]) * s @@ -157,7 +157,7 @@ def nufft2d2r( Real function value at query points. """ - # This is optimized away under JIT if the operation is an idenity. + # This is optimized away under JIT if the operation is an identity. s0 = 2 * jnp.pi / (domain0[1] - domain0[0]) s1 = 2 * jnp.pi / (domain1[1] - domain1[0]) x0 = (x0 - domain0[0]) * s0 @@ -328,7 +328,8 @@ def polyroot_vec( if ( num_coef in func and get_only_real_roots - and not (jnp.iscomplexobj(c) or jnp.iscomplexobj(k)) + and jnp.isrealobj(c) + and jnp.isrealobj(k) ): # Compute from analytic formula to avoid the issue of complex roots with small # imaginary parts. Also consumes less memory. diff --git a/desc/integrals/bounce_integral.py b/desc/integrals/bounce_integral.py index 3f8fa1326f..b45bb91cb1 100644 --- a/desc/integrals/bounce_integral.py +++ b/desc/integrals/bounce_integral.py @@ -2,8 +2,10 @@ import warnings from abc import ABC, abstractmethod +from typing import NamedTuple import equinox as eqx +from adv_jax_math import batch_map, sparse_pullback from interpax import CubicHermiteSpline, PPoly from interpax_fft import ( FourierChebyshevSeries, @@ -20,14 +22,14 @@ from matplotlib import pyplot as plt from matplotlib.colors import LogNorm from matplotlib.ticker import MaxNLocator +from orthax.chebyshev import chebvander from orthax.legendre import leggauss from desc.backend import jax, jnp, rfft2 -from desc.batching import batch_map from desc.grid import LinearGrid from desc.integrals._bounce_utils import ( - Y_B_rule, - _sentinel, + _bounce_points, + _halley, argmin, bounce_points, broadcast_for_bounce, @@ -36,14 +38,13 @@ fast_chebyshev, fast_cubic_spline, get_mins, - get_vander_spline, mmt_for_bounce, move, - num_well_rule, + no_nufft, plot_ppoly, - regular_points, set_default_plot_kwargs, theta_on_fieldlines, + truncate_rule, ) from desc.integrals._interp_utils import ( _JF_BUG, @@ -74,11 +75,11 @@ ) -class Bounce(eqx.Module, ABC): +class _Bounce(eqx.Module, ABC): """Abstract class for bounce integrals.""" @staticmethod - def get_pitch_inv_quad(min_B, max_B, num_pitch, simp=True): + def get_pitch_inv_quad(min_B, max_B, num_pitch, **kwargs): """Return 1/λ values and weights for quadrature between ``min_B`` and ``max_B``. Parameters @@ -87,38 +88,45 @@ def get_pitch_inv_quad(min_B, max_B, num_pitch, simp=True): Minimum B value. max_B : jnp.ndarray Maximum B value. - num_pitch : int - Number of values. - simp : bool - If ``True``, then the pitch angles are chosen so that the quadrature - over the velocity coordinate of 1/λ is done with Simpson’s 1/3 in the - interior completed by an open midpoint scheme near the boundary such - that an accuracy of fourth order is preserved. - If ``False``, then an open midpoint scheme is returned, which - is only recommended for plotting purposes. + num_pitch : int or tuple[jnp.ndarray] + If given an integer, this is interpreted as the resolution for + a quadrature using Simpson’s 1/3 in the interior completed by an + open midpoint scheme near the boundary. + If given a tuple, then this is interpreted as the quadrature + points xₖ and weights wₖ for the approximation of the integral + ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). Then this method simply rescales + the quadrature for integration between ``min_B`` and ``max_B``. Returns ------- - x, w : tuple[jnp.ndarray] - Shape (min_B.shape, num pitch). - 1/λ values and weights. + pitch_inv, weight : tuple[jnp.ndarray] + Shape (min_B.shape, num pitch). 1/λ values and weights. """ - errorif( - num_pitch > 1e5, - msg="Floating point error impedes detection of bounce points " - f"near global extrema. Choose {num_pitch} < 1e5.", - ) - # Samples should be uniformly spaced in |B| and not λ. - # Important to do an open quadrature since the bounce integrals at the - # global maxima of |B| are not computable even ignoring precision issues. - x, w = simpson2(num_pitch) if simp else uniform(num_pitch) - x = bijection_from_disc(x, min_B[..., None], max_B[..., None]) - w = w * grad_bijection_from_disc(min_B, max_B)[..., None] + if isinstance(num_pitch, int): + errorif( + num_pitch > 1e5, + msg="Floating point error impedes detection of bounce points " + f"near global extrema. Choose {num_pitch} < 1e5.", + ) + # by default, get pitch angles with Simpson's 1/3 rule + simp = kwargs.get("simp", True) + num_pitch = simpson2(num_pitch) if simp else uniform(num_pitch) + + if jnp.ndim(min_B): + min_B = min_B[..., None] + max_B = max_B[..., None] + + x, w = num_pitch + x = bijection_from_disc(x, min_B, max_B) + w = w * grad_bijection_from_disc(min_B, max_B) return x, w + # aliased for convenience + pitch_quad = get_pitch_inv_quad + @abstractmethod - def points(self, pitch_inv, num_well=None): + def points(self, pitch_inv, num_well=-1): """Compute bounce points.""" @abstractmethod @@ -134,21 +142,27 @@ def integrate( names=None, points=None, *, - num_well=None, + num_well=-1, quad=None, ): """Bounce integrate ∫ f(ρ,α,λ,ℓ) dℓ.""" @abstractmethod def interp_to_argmin(self, f, points): - """Interpolate ``f`` to the deepest point pⱼ in magnetic well j.""" + """Interpolate ``f`` to the deepest point in magnetic well w. + + Interpolate f to the argmin of the magnetic field + between each pair in ``points``. Explicitly, let + E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Returns {f ∘ A(w)}. + """ @abstractmethod def plot(self, l, m, pitch_inv=None, **kwargs): """Plot B and bounce points on the specified field line.""" -class Bounce2D(Bounce): +class Bounce2D(_Bounce): """Computes bounce integrals using pseudo-spectral methods. The bounce integral is defined as ∫ f(ρ,α,λ,ℓ) dℓ where @@ -171,8 +185,8 @@ class Bounce2D(Bounce): A much more performant version is available at https://github.com/unalmis/DESC. The reference 2 below refers to that implementation. - Refrences - --------- + References + ---------- Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications. Kaya Unalmis et al. Journal of Plasma Physics. @@ -190,8 +204,9 @@ class Bounce2D(Bounce): Some comments comparing ``Bounce1D`` to ``Bounce2D`` are given below. ``Bounce1D`` uses lower order accurate, one-dimensional splines. ``Bounce2D`` is superior for optimization objectives in DESC as it solves the - moving grid interpolation problem and avoids recomputing 3D Fourier-Zernike - series on a time-dependent grid. + moving grid interpolation problem, avoids recomputing 3D Fourier-Zernike + series on a time-dependent grid, and is able to compute the derivative + matrix relevant to optimization with a compact sparse pullback. Parameters ---------- @@ -200,41 +215,42 @@ class Bounce2D(Bounce): (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). Number of poloidal and toroidal nodes preferably rounded down to powers of two. Determines the flux surfaces to compute on and resolution of FFTs. - The ζ coordinates (the unique values prior to taking the tensor-product) - must be strictly increasing. data : dict[str, jnp.ndarray] Data evaluated on ``grid``. Must include names in ``Bounce2D.required_names``. + If the input is not a real-valued array, then it + is assumed that the Fourier transform as returned by ``Bounce2D.fourier`` + was given instead. angle : jnp.ndarray Shape (num ρ, X, Y). Angle returned by ``Bounce2D.angle``. Y_B : int Desired resolution for algorithm to compute bounce points. + A reference value is ``(grid.num_theta+grid.num_zeta)//2``. + If the option ``spline`` is ``True``, the bounce points are found with - 8th order accuracy in this parameter. If the option ``spline`` is ``False``, - then the bounce points are found with spectral accuracy in this parameter. - A reference value for the ``spline=True`` option is - ``grid.NFP*(grid.num_theta+grid.num_zeta)//2``. - A reference value for the ``spline=False`` option is - ``(grid.num_theta+grid.num_zeta)//2``. - - An error of ε in a bounce point manifests - 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and - 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. + 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order + 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and + 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹. + + If the option ``spline`` is ``False``, the bounce points are found such + that the bounce integrals have exponential accuracy in this parameter. alpha : jnp.ndarray Shape (num α, ). Starting field line poloidal labels. - Default is single field line. To compute a surface average - on a rational surface, it is necessary to average over multiple - field lines until the surface is covered sufficiently. - num_transit : int - Number of toroidal transits to follow field line. - In an axisymmetric device, field line integration over a single poloidal - transit is sufficient to capture a surface average. For a 3D - configuration, more transits will approximate surface averages on an - irrational magnetic surface better, with diminishing returns. + Default is single field line. + On irrational magnetic surfaces, it is sufficient to integrate along a + single field line. On a rational or near-rational surface in + non-axisymmetric configurations, it is necessary to integrate along + multiple field lines until the surface is covered sufficiently. + field_period_transits : int + Number of field periods to follow field line. + In axisymmetric configurations, integration along the field line for a + single poloidal transit between two global maxima of B is sufficient for + convergence. For a 3D configuration, the magnetic surface should be covered + sufficiently. quad : tuple[jnp.ndarray] - Quadrature points xₖ and weights wₖ for the approximate evaluation of an + Quadrature points xₖ and weights wₖ for the approximation of an integral ∫₋₁¹ g(x) dx = ∑ₖ wₖ g(xₖ). Default is 32 points. automorphism : tuple[Callable] or None The first callable should be an automorphism of the real interval [-1, 1]. @@ -242,27 +258,13 @@ class Bounce2D(Bounce): a change of variable for the bounce integral. The choice made for the automorphism will affect the performance of the quadrature. nufft_eps : float - Precision requested for interpolation with non-uniform fast Fourier - transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - is_reshaped : bool - Whether the arrays in ``data`` are already reshaped to the expected form of - shape (..., num ζ, num θ) or (num ρ, num ζ, num θ). - This option can be used to iteratively compute bounce integrals one flux - surface at a time, reducing memory usage. - To do so, set to ``True`` and provide only those chunks of the reshaped data. - If set to ``True``, then it is assumed that ``data["iota"]`` has shape - ``(grid.num_rho,)`` or is a scalar. - is_fourier : bool - If true, then it is assumed that ``data`` holds Fourier transforms - as returned by ``Bounce2D.fourier`` and ``data["iota"]`` has shape - ``(grid.num_rho,)`` or is a scalar. Default is false. - Bref : float - Optional. Reference magnetic field strength for normalization. - Lref : float - Optional. Reference length scale for normalization. + Precision requested for interpolation with non-uniform fast Fourier transform + (NUFFT). If less than ``1e-14`` then NUFFT will not be used. spline : bool Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. Default is ``True``. + instead of Chebyshev series. Default is ``True``. It can be preferable + to set to ``False`` on equilibria with high ``NFP``, (such cases make + smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast. check : bool Flag for debugging. Must be false for JAX transformations. @@ -278,6 +280,7 @@ class Bounce2D(Bounce): _modes_t: jax.Array _c: dict[str, jax.Array] _theta: PiecewiseChebyshevSeries + _B: jax.Array or PiecewiseChebyshevSeries _nufft_eps: float = eqx.field(static=True) def __init__( @@ -286,16 +289,12 @@ def __init__( data, angle, Y_B=None, - alpha=jnp.array([0.0]), - num_transit=20, + alpha=None, + field_period_transits=20, quad=None, *, automorphism=None, nufft_eps=1e-6, - is_reshaped=False, - is_fourier=False, - Bref=1.0, - Lref=1.0, spline=True, check=False, vander=None, @@ -303,16 +302,21 @@ def __init__( ): """Returns an object to compute bounce integrals.""" assert grid.can_fft2 - is_reshaped = is_reshaped or is_fourier - vander = setdefault(vander, {}) + if "num_transit" in kwargs: + warnif( + True, + FutureWarning, + "Argument num_transit has been deprecated in favor of" + " field_period_transits, converting to" + " field_period_transits = num_transit*eq.NFP.", + ) + field_period_transits = kwargs.pop("num_transit") * grid.NFP if quad is None: - quad = get_quadrature( - leggauss(32), (automorphism_sin, grad_automorphism_sin) - ) + quad = BounceOptions._quad(eta=-2, num_quad=32) else: quad = get_quadrature(quad, automorphism) - self._quad = jax.lax.stop_gradient(quad) + self._quad = quad self._NFP = grid.NFP self._num_t = grid.num_theta @@ -320,34 +324,47 @@ def __init__( grid.num_zeta, grid.num_theta, (0, 2 * jnp.pi / grid.NFP) ) - self._c = {"|B|": data["|B|"] / Bref, "B^zeta": data["B^zeta"] * Lref / Bref} + # Figure out if input is split into batches or needs a Fourier transform. + is_real = jnp.isrealobj(data["|B|"]) + s = data["|B|"].shape + is_reshaped = ( + len(s) > 1 + and s[-2] == grid.num_zeta + and s[-1] == (grid.num_theta if is_real else (grid.num_theta // 2 + 1)) + ) + errorif( + is_reshaped and jnp.size(data["iota"]) != (s[0] if (len(s) > 2) else 1), + msg="You forgot to call grid.compress(data['iota'])", + ) + + self._c = {"|B|": data["|B|"], "B^zeta": data["B^zeta"]} if not is_reshaped: self._c["|B|"] = Bounce2D.reshape(grid, self._c["|B|"]) self._c["B^zeta"] = Bounce2D.reshape(grid, self._c["B^zeta"]) - if not is_fourier: + if is_real: self._c["|B|"] = Bounce2D.fourier(self._c["|B|"]) self._c["B^zeta"] = Bounce2D.fourier(self._c["B^zeta"]) angle = parse_argname_change(angle, kwargs, "theta", "angle") iota = data["iota"] if is_reshaped else grid.compress(data["iota"]) - iota, alpha = jnp.atleast_1d(iota, alpha) - self._theta = theta_on_fieldlines(angle, iota, alpha, num_transit, grid.NFP) + iota, alpha = jnp.atleast_1d(iota, jnp.zeros(1) if alpha is None else alpha) + self._theta = theta_on_fieldlines( + angle, iota, alpha, field_period_transits, grid.NFP + ) self._nufft_eps = float(nufft_eps) if Y_B is None: - Y_B = Y_B_rule(grid, spline) + Y_B = BounceOptions._guess_Y_B(grid) if spline: - self._c["B(z)"], self._c["knots"] = fast_cubic_spline( + self._B, self._c["knots"] = fast_cubic_spline( self._theta, self._c["|B|"], Y_B, - self._num_t, self._modes_t, self._modes_z, - self._NFP, self._nufft_eps, - vander_t=vander.get("dct spline", None), + vander_t=None if vander is None else vander.get("dct spline", None), check=check, ) else: @@ -355,182 +372,14 @@ def __init__( Y_B > grid.num_theta + grid.num_zeta, msg="Unnecessarily high resolution for Y_B with spline=False.", ) - self._c["B(z)"] = fast_chebyshev( + self._B = fast_chebyshev( self._theta, self._c["|B|"], Y_B, - self._num_t, self._modes_t, self._modes_z, ) - @staticmethod - def _build(obj, names, eta): - """Builds the objective, selecting default values if they were not specified. - - Examples - -------- - * ``desc/objectives/_fast_ion.py::GammaC`` - * ``desc/objectives/_neoclassical.py::EffectiveRipple`` - - Parameters - ---------- - obj : _Objective - The objective instance. - names : str - Builds profiles and transforms for the compute quantities registered - with these names. - eta : int - The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the - behavior of the integrand near the bounce points. If η ∉ {-1, 1}, - then a quadrature that works for all η ∈ {−1, 0, 1} will be used. - - """ - from desc.compute import get_profiles, get_transforms - from desc.objectives.utils import _parse_callable_target_bounds - - eq = obj.things[0] - if obj._grid is None: - obj._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - assert obj._grid.can_fft2 - - X = obj._hyperparam.pop("X") - Y = obj._hyperparam.pop("Y") - obj._constants["x"] = fourier_pts(X) - obj._constants["y"] = cheb_pts(Y, (0, 2 * jnp.pi / eq.NFP))[::-1] - - Y_B = obj._hyperparam["Y_B"] - if Y_B is None: - Y_B = Y_B_rule(obj._grid, obj._hyperparam["spline"]) - obj._hyperparam["Y_B"] = Y_B - if obj._hyperparam["num_well"] is None: - obj._hyperparam["num_well"] = num_well_rule( - obj._hyperparam["num_transit"], - eq.NFP, - # Due to legacy reasons Y_B is resolution over full transit - # if spline is true. - Y_B if obj._hyperparam["spline"] else (Y_B * eq.NFP), - ) - - obj._constants["_vander"] = ( - get_vander_spline(obj._grid, Y, Y_B, eq.NFP) - if obj._hyperparam["spline"] - else {} - ) - - num_quad = obj._hyperparam.pop("num_quad") - if eta == 1: - obj._constants["quad"] = chebgauss2(num_quad) - elif eta == -1: - obj._constants["quad"] = chebgauss1(num_quad) - else: - obj._constants["quad"] = get_quadrature( - leggauss(num_quad), (automorphism_sin, grad_automorphism_sin) - ) - - rho = obj._grid.compress(obj._grid.nodes[:, 0]) - obj._constants["lambda"] = get_transforms( - "lambda", - eq, - grid=LinearGrid( - rho=rho, M=eq.L_basis.M, zeta=obj._constants["y"], NFP=eq.NFP - ), - )["L"] - - obj._constants["profiles"] = get_profiles(names, eq, grid=obj._grid) - obj._constants["transforms"] = get_transforms(names, eq, grid=obj._grid) - obj._dim_f = obj._grid.num_rho - obj._target, obj._bounds = _parse_callable_target_bounds( - obj._target, obj._bounds, rho - ) - - @staticmethod - def _defaults(eta, grid, **kwargs): - """Defaults for the registered compute functions. - - Parameters - ---------- - eta : int - The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the - behavior of the integrand near the bounce points. If η ∉ {-1, 1}, - then a quadrature that works for all η ∈ {−1, 0, 1} will be used. - grid : Grid - Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes - (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). - - Returns - ------- - angle, Y_B, alpha, num_transit, num_well, num_pitch - pitch_batch_size, surf_batch_size, - quad, nufft_eps, spline, vander - - """ - if eta == 1: - quad = ( - kwargs["quad"] - if "quad" in kwargs - else chebgauss2(kwargs.get("num_quad", 32)) - ) - num_pitch = kwargs.get("num_pitch", 51) - nufft_eps = kwargs.get("nufft_eps", 1e-6) - elif eta == -1: - quad = ( - kwargs["quad"] - if "quad" in kwargs - else chebgauss1(kwargs.get("num_quad", 32)) - ) - num_pitch = kwargs.get("num_pitch", 65) - nufft_eps = kwargs.get("nufft_eps", 1e-7) - else: - quad = ( - kwargs["quad"] - if "quad" in kwargs - else get_quadrature( - leggauss(kwargs.get("num_quad", 32)), - (automorphism_sin, grad_automorphism_sin), - ) - ) - num_pitch = kwargs.get("num_pitch", 65) - nufft_eps = kwargs.get("nufft_eps", 1e-7) - - pitch_batch_size = kwargs.get("pitch_batch_size", None) - surf_batch_size = kwargs.get("surf_batch_size", 1) - assert ( - surf_batch_size == 1 or pitch_batch_size is None - ), f"Expected pitch_batch_size to be None, got {pitch_batch_size}." - - spline = kwargs.get("spline", True) - vander = kwargs.get("_vander", None) - - angle = parse_argname_change( - kwargs.get("angle", kwargs.get("theta", None)), kwargs, "theta", "angle" - ) - alpha = kwargs.get("alpha", jnp.array([0.0])) - num_transit = kwargs.get("num_transit", 20) - - Y_B = kwargs.get("Y_B", Y_B_rule(grid, spline)) - num_well = kwargs.get( - "num_well", - # Due to legacy reasons Y_B is resolution over full transit - # if spline is true. - num_well_rule(num_transit, grid.NFP, Y_B if spline else (Y_B * grid.NFP)), - ) - - return ( - angle, - Y_B, - alpha, - num_transit, - num_well, - num_pitch, - pitch_batch_size, - surf_batch_size, - nufft_eps, - spline, - quad, - vander, - ) - @staticmethod def batch( fun, @@ -538,10 +387,10 @@ def batch( desc_data, angle, grid, - num_pitch, + *, surf_batch_size=1, - simp=True, - expand_out=False, + sparse=True, + **kwargs, ): """Compute function ``fun`` over phase space in batches. @@ -557,10 +406,9 @@ def batch( Parameters ---------- fun : callable - A function which takes a single argument ``fun_data`` and computes + A function which takes a single argument ``fun_data`` and computes bounce integrals assuming ``fun_data`` holds all required quantities - to construct a ``Bounce2D`` operator as well as call its methods with - the flag ``is_fourier=True``. + to construct a ``Bounce2D`` operator as well as call its methods. fun_data : dict[str, jnp.ndarray] Data to reshape, interpolate, and pass to ``fun``. The structure of the data should match the structure @@ -574,40 +422,47 @@ def batch( Angle returned by ``Bounce2D.angle``. grid : Grid Grid on which ``fun_data`` and ``desc_data`` were computed. - num_pitch : int - Number of pitch angles to add to ``fun_data`` for use in the computation. surf_batch_size : int Number of flux surfaces with which to compute simultaneously. Default is ``1``. - simp : bool - Whether the pitch angles should be chosen for use with open Simpson rule - instead of uniform weights for quadrature over velocity coordinate. - Default is True. - expand_out : bool - Whether to expand output to full grid so that the first dimension - has size ``grid.num_nodes`` instead of ``grid.num_rho``. - Default is False. + sparse : bool + Whether to differentiate with sparsity preserving pullbacks. + Default is ``True``, which makes the most sense if the output has + shape (num_rho, ). Otherwise, if the output shape is larger, and + the final objective of interest is a lower dimensional quantity + than the output, it may be preferable to delay the vjp + by setting to ``False``. Returns ------- The output ``fun(fun_data)``. """ + warnif( + "num_pitch" in kwargs, + FutureWarning, + "Argument num_pitch has been deprecated and is no longer used.", + ) + warnif( + "expand_out" in kwargs, + FutureWarning, + "Argument expand_out has been deprecated and is no longer used.", + ) + for name in Bounce2D.required_names: fun_data[name] = desc_data[name] fun_data.pop("iota", None) for name in fun_data: fun_data[name] = Bounce2D.fourier(Bounce2D.reshape(grid, fun_data[name])) fun_data["iota"] = grid.compress(desc_data["iota"]) + fun_data["min_tz |B|"] = grid.compress(desc_data["min_tz |B|"]) + fun_data["max_tz |B|"] = grid.compress(desc_data["max_tz |B|"]) fun_data["angle"] = angle - fun_data["pitch_inv"], fun_data["pitch_inv weight"] = Bounce.get_pitch_inv_quad( - grid.compress(desc_data["min_tz |B|"]), - grid.compress(desc_data["max_tz |B|"]), - num_pitch, - simp=simp, - ) - out = batch_map(fun, fun_data, surf_batch_size) - return grid.expand(out) if expand_out else out + + if sparse: + return sparse_pullback(fun, fun_data, surf_batch_size, strip_dim0=True) + + return batch_map(fun, fun_data, surf_batch_size, strip_dim0=True) @staticmethod def reshape(grid, f): @@ -617,6 +472,8 @@ def reshape(grid, f): ---------- grid : Grid Tensor-product grid in (ρ, θ, ζ). + The ζ coordinates (the unique values prior to taking the tensor-product) + must be strictly increasing. f : jnp.ndarray Data evaluated on grid. @@ -738,14 +595,18 @@ def angle( in_name = "vartheta" zeta = fourier_pts(Y, (0, 2 * jnp.pi / eq.NFP)) - grid = LinearGrid(rho=rho, M=eq.L_basis.M, zeta=zeta.size, NFP=eq.NFP) + grid = LinearGrid( + rho=rho, M=eq.L_basis.M, zeta=Y if eq.N > 0 else 1, NFP=eq.NFP + ) if iota is None: iota = 0.0 elif name == "delta": in_name = "alpha" zeta = cheb_pts(Y, (0, 2 * jnp.pi / eq.NFP))[::-1] - grid = LinearGrid(rho=rho, M=eq.L_basis.M, zeta=zeta, NFP=eq.NFP) + grid = LinearGrid( + rho=rho, M=eq.L_basis.M, zeta=zeta if eq.N > 0 else 1, NFP=eq.NFP + ) if iota is None: iota = eq._compute_iota_under_jit(rho, params, profiles, **kwargs) @@ -766,7 +627,7 @@ def angle( def _num_z(self): return self._modes_z.size - def _swap_pitch(self, pitch_inv): + def _swap_axes(self, pitch_inv): """Transpose to simplify broadcasting. Parameters @@ -824,23 +685,41 @@ def points(self, pitch_inv, num_well=None): """ if num_well is None: - num_well = num_well_rule(self._theta.X // self._NFP, self._NFP) + num_well = BounceOptions._guess_num_well( + field_period_transits=self._theta.X, + NFP=self._NFP, + mins_per_field_period=getattr(self._B, "Y", jnp.inf) // 2, + ) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - # Skip Newton update since these points are exponentially accurate. - z1, z2 = self._c["B(z)"].intersect1d( - self._swap_pitch(pitch_inv), num_intersect=num_well, eps=_eps + if isinstance(self._B, PiecewiseChebyshevSeries): + # We skip Halley stepping since we use this Chebyshev series of |B| + # to compute v_∥ rather than the original Fourier series. We do this + # because we found the points exactly for the Chebyshev series. + # Since the Chebyshev series is exponentially accurate, we retain + # exponential accuracy in the bounce integrals when we compute v_∥ with it; + # in particular, this holds even if our choice of resolution for the + # Chebyshev series does not fully reconstruct the true function. + # If we instead computed v_∥ from the original Fourier series, we would + # need to make sure that the roots of the Chebyshev series match the + # Fourier series', which is akin to a stiffness condition between Y_B + # and the grid resolution for the FFTs in (θ, ζ). + # Accurate roots needed to also increase the correlation in the + # discretization error in a neighborhood of any given point in the + # optimization landscape. See supplement in publications/unalmis2025. + # Experimentally, we find that the difference between the automatic + # derivative and a 4 point finite difference stencil at the optimal step + # size of 10⁻⁸ is reduced from 10³ to 10⁻⁶ for Γ_c + # (which has the singular weight 1/v_∥). + z1, z2 = self._B.intersect1d( + self._swap_axes(pitch_inv), num_intersect=num_well, eps=_eps ) z1 = move(z1) z2 = move(z2) return z1, z2 - pitch_inv = broadcast_for_bounce(pitch_inv) - if self._nufft_eps < 1e-14: - # FIXME: Newton update has only been implemented for nuffts; contributions - # welcome : copy logic in desc/equilibrium/coords._map_poloidal_coordinates. - return bounce_points(pitch_inv, self._c["knots"], self._c["B(z)"], num_well) - return regular_points(self, pitch_inv, num_well) + # We use the original Fourier series |B| to compute v_∥, so a Halley step + # is done using the roots of the spline as the initial guess. + return bounce_points(self, broadcast_for_bounce(pitch_inv), num_well) def check_points(self, points, pitch_inv, *, plot=True, **kwargs): """Check that bounce points are computed correctly. @@ -871,20 +750,31 @@ def check_points(self, points, pitch_inv, *, plot=True, **kwargs): """ kwargs = set_default_plot_kwargs(kwargs) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - z1, z2 = points - return self._c["B(z)"].check_intersect1d( - move(z1, False), - move(z2, False), - self._swap_pitch(pitch_inv), + if isinstance(self._B, PiecewiseChebyshevSeries): + return self._B.check_intersect1d( + move(points[0], False), + move(points[1], False), + self._swap_axes(pitch_inv), plot=plot, **kwargs, ) + + pitch_inv = broadcast_for_bounce(pitch_inv) + + print("Error statistics for the given bounce points:") + _halley( + self, + pitch_inv, + points, + mask=points[0] < points[1], + nufft_eps=0.0, + diagnostic=2, + ) return check_bounce_points( *points, pitch_inv, self._c["knots"], - self._c["B(z)"], + self._B, plot=plot, **kwargs, ) @@ -898,12 +788,12 @@ def integrate( points=None, *, num_well=None, - nufft_eps=1e-6, - is_fourier=False, - low_ram=False, + nufft_eps=-1.0, + loop=False, quad=None, check=False, plot=False, + **kwargs, ): """Bounce integrate ∫ f(ρ,α,λ,ℓ) dℓ. @@ -931,7 +821,9 @@ def integrate( Real scalar-valued periodic functions in (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP) evaluated on the ``grid`` supplied to construct this object. Use the method ``Bounce2D.reshape`` to reshape the data into the - expected shape. + expected shape. If the input is not a real-valued array, then it + is assumed that the Fourier transform as returned by ``Bounce2D.fourier`` + was given instead. names : str or list[str] Names in ``data`` to interpolate. Default is all keys in ``data``. points : tuple[jnp.ndarray] @@ -945,12 +837,9 @@ def integrate( nufft_eps : float Precision requested for interpolation with non-uniform fast Fourier transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - is_fourier : bool - If true, then it is assumed that ``data`` holds Fourier transforms - as returned by ``Bounce2D.fourier``. Default is false. - low_ram : bool - Whether to use a more memory efficient algorithm. - However, this is slower to differentiate with JAX. + loop : bool + Whether to use loops to compute sums where a loop option is implemented. + This is slower to differentiate with JAX. For best performance, one should only use this option if batching is already being done via ``Bounce2D.batch`` with ``surf_batch_size=1``. quad : tuple[jnp.ndarray] @@ -970,16 +859,19 @@ def integrate( and pitch value. """ + if nufft_eps < 0: + nufft_eps = self._nufft_eps x, w = setdefault(quad, self._quad) + if not isinstance(integrand, (list, tuple)): integrand = [integrand] - exclude = ("|B|", "B^zeta", "|e_zeta|r,a|", "zeta", "theta") - data = setdefault(data, {}) - if is_fourier: - data = apply(data, subset=names, exclude=exclude) - else: - data = apply(data, Bounce2D.fourier, names, exclude) + data = apply( + data, + _fourier_if_real, + subset=names, + exclude=("|B|", "B^zeta", "|e_zeta|r,a|", "zeta", "theta"), + ) if points is None: points = self.points(pitch_inv, num_well) @@ -991,10 +883,10 @@ def integrate( elif jnp.ndim(pitch) > 1: pitch = pitch[:, None, :, None, None] - if nufft_eps < 1e-14: - data = self._nummt(x, *points, data, low_ram) + if no_nufft(nufft_eps): + data = self._nummt(x, *points, data, loop) else: - data = self._nufft(x, *points, data, low_ram, nufft_eps, pitch_inv) + data = self._nufft(x, *points, data, loop, nufft_eps, pitch_inv) data["|e_zeta|r,a|"] = data["|B|"] / jnp.abs(data["B^zeta"]) # Strictly increasing ζ knots enforces dζ > 0. @@ -1019,77 +911,74 @@ def integrate( return result[0] if len(result) == 1 else result - def _nufft(self, x, z1, z2, data, low_ram, eps, pitch_inv): - shape = (*z1.shape, x.size) + def _nufft(self, x, z1, z2, data, loop, eps, pitch_inv): + shape = z1.shape + (x.size,) + + keys = list(data.keys()) + keys.append("B^zeta") + c = list(data.values()) + c.append(self._c["B^zeta"]) + if not (is_chebyshev := isinstance(self._B, PiecewiseChebyshevSeries)): + c.append(self._c["|B|"]) + keys.append("|B|") z = flatten_mat(bijection_from_disc(x, z1[..., None], z2[..., None]), 3) - t = flatten_mat(self._theta.eval1d(z, loop=low_ram)) + t = self._theta.eval1d(z, loop=loop) + if is_chebyshev: + B = self._B.eval1d(z, loop=loop).reshape(shape) + t = flatten_mat(t) z = flatten_mat(z) # t and z have shape (num rho surfaces, num points on each surface) # or just ( num points on each surface). - if _JF_BUG: mask = fill_value = None else: mask = flatten_mat(jnp.broadcast_to((z1 < z2)[..., None], shape), 4) fill_value = 0.5 * jnp.min(pitch_inv) - c = nufft2d2r( z, t, - jnp.concatenate([*data.values(), self._c["B^zeta"], self._c["|B|"]], -3), + jnp.concatenate(c, -3), (0, 2 * jnp.pi / self._NFP), vec=True, eps=eps, mask=mask, fill_value=fill_value, ) - c = ( - c.reshape(len(data) + 2, *shape) - if c.ndim == 2 - # reshape before swap to avoid memory copy - else c.reshape(shape[0], len(data) + 2, *shape[1:]).swapaxes(0, 1) - ) + c = c.swapaxes(0, -2).reshape((-1,) + shape) - data = dict(zip([*data.keys(), "B^zeta", "|B|"], c)) + data = dict(zip(keys, c)) + if is_chebyshev: + data["|B|"] = B data["zeta"] = z.reshape(shape) return data - def _nummt(self, x, z1, z2, data, low_ram): - shape = (*z1.shape, x.size) + def _nummt(self, x, z1, z2, data, loop): + shape = z1.shape + (x.size,) zeta = bijection_from_disc(x, z1[..., None], z2[..., None]) z = flatten_mat(zeta, 3) - t = self._theta.eval1d(z, loop=low_ram).reshape(*shape, 1) - - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - # Using the same |B| that gave bounce points increases correlation - # in discretization error in an open neighboorhood around the - # current point in the optimization landscape, and hence removes - # noise from optimization derivatives. For example, the difference - # between the auto derivative and a 4 point finite difference - # stencil at the optimal step size is reduced from 10³ to 10⁻⁶ for - # Γ_c (which has the singular weight 1/v_∥). - # Also uses less memory due to the dimension reduction. - B = self._c["B(z)"].eval1d(z, loop=low_ram).reshape(shape) - - z = zeta[..., None] + t = self._theta.eval1d(z, loop=loop).reshape(*shape, 1) + if is_chebyshev := isinstance(self._B, PiecewiseChebyshevSeries): + B = self._B.eval1d(z, loop=loop).reshape(shape) + + z = zeta[..., None] if self._num_z > 1 else jnp.zeros((1,) * (zeta.ndim + 1)) z = jnp.exp(1j * self._modes_z * z) t = jnp.exp(1j * self._modes_t * t) + data = {name: mmt_for_bounce(z, t, c) for name, c in data.items()} data["B^zeta"] = mmt_for_bounce(z, t, self._c["B^zeta"]) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries): - data["|B|"] = B - else: - data["|B|"] = mmt_for_bounce(z, t, self._c["|B|"]) + data["|B|"] = B if is_chebyshev else mmt_for_bounce(z, t, self._c["|B|"]) data["zeta"] = zeta - return data - def interp_to_argmin( - self, f, points, *, nufft_eps=1e-6, is_fourier=False, **kwargs - ): - """Interpolate ``f`` to the deepest point pⱼ in magnetic well j. + def interp_to_argmin(self, f, points, *, nufft_eps=-1.0, **kwargs): + """Interpolate ``f`` to the deepest point in magnetic well w. + + Interpolate f to the argmin of the magnetic field + between each pair in ``points``. Explicitly, let + E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Returns {f ∘ A(w)}. Parameters ---------- @@ -1098,7 +987,9 @@ def interp_to_argmin( Real scalar-valued periodic function in (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP) evaluated on the ``grid`` supplied to construct this object. Use the method ``Bounce2D.reshape`` to reshape the data into the - expected shape. + expected shape. If the input is not a real-valued array, then it + is assumed that the Fourier transform as returned by ``Bounce2D.fourier`` + was given instead. points : tuple[jnp.ndarray] Shape (num ρ, num α, num pitch, num well). Optional, output of method ``self.points``. @@ -1108,9 +999,6 @@ def interp_to_argmin( nufft_eps : float Precision requested for interpolation with non-uniform fast Fourier transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. - is_fourier : bool - If true, then it is assumed that ``f`` is the Fourier transforms - as returned by ``Bounce2D.fourier``. Default is false. Returns ------- @@ -1119,23 +1007,26 @@ def interp_to_argmin( ``f`` interpolated to the deepest point between ``points``. """ - if not is_fourier: - f = Bounce2D.fourier(f) + if nufft_eps < 0: + nufft_eps = self._nufft_eps + f = _fourier_if_real(f) + + num_mins = kwargs.get("num_mins", -1) + if isinstance(self._B, PiecewiseChebyshevSeries): + bound = self._B.X * (self._B.Y // 2) + num_mins = bound if (num_mins < 0) else min(num_mins, bound) - num_transit = self._theta.X // self._NFP - K_z = max(self._num_z // 2 * self._NFP, self._num_t // 2, 5) # liberal - num_mins = kwargs.get("num_mins", num_transit * K_z) # We set fill value to 0 since we chose our coordinates # such that all bounce points are at ζ >= 0; and therefore, # junk values in B_mins cannot be selected in argmin. mins, B_mins = ( - self._c["B(z)"].extrema1d(1, num_mins, fill_value=0.0, eps=_eps) - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries) - else get_mins(self._c["knots"], self._c["B(z)"], num_mins, fill_value=0.0) + self._B.extrema1d(1, num_mins, fill_value=0.0, eps=_eps) + if isinstance(self._B, PiecewiseChebyshevSeries) + else get_mins(self._c["knots"], self._B, num_mins, fill_value=0.0) ) t = self._theta.eval1d(mins) - if nufft_eps < 1e-14: + if no_nufft(nufft_eps): f = irfft2_mmt_pos( mins, t, @@ -1164,7 +1055,7 @@ def compute_fieldline_length(self, quad=None): ---------- quad : tuple[jnp.ndarray] Quadrature points xₖ and weights wₖ for the - approximate evaluation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). + approximation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). Default is Gauss-Legendre quadrature on each field period along the field line. @@ -1176,48 +1067,37 @@ def compute_fieldline_length(self, quad=None): """ warnings.warn( "This result will converge to " - "(num transit / 2π) * ∬_Ω abs(𝐁⋅∇ζ)⁻¹ dα dζ where (α,ζ) ∈ Ω = [0, 2π)². " + "(num field periods / 2π) * ∬_Ω abs(𝐁⋅∇ζ)⁻¹ dα dζ, " + "where (α,ζ) ∈ Ω = [0, 2π) × [0, 2π/NFP).\n" "This can be computed more efficiently as " - '(num transit / 2π) * eq.compute("V_psi").', + '(num field periods / 2π) * eq.compute("V_psi") / eq.NFP.\n', DeprecationWarning, ) if quad is None: - deg = max( - ( - self._c["B(z)"].Y - if isinstance(self._c["B(z)"], PiecewiseChebyshevSeries) - else self._theta.Y - ), - 8, - ) - quad = leggauss(deg) + quad = leggauss(getattr(self._B, "Y", self._theta.Y)) x, w = quad - shape = ( - *self._theta.cheb.shape[:-2], - self._theta.X // self._NFP, - self._NFP, - 1, - self._theta.Y, - ) - # Let m, n denote the poloidal and toroidal Fourier resolution. We need to - # compute a set of 2D Fourier series each on non-uniform tensor product grids - # of size |𝛉|×|𝛇| where |𝛉| = num α × num transit × NFP and |𝛇| = x.size. - # Partial summation is more efficient than direct evaluation when - # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| or equivalently n|𝛉| > n + |𝛉|. + # compute a set of 2D Fourier series on non-uniform tensor product grids of size + # |𝛉|×|𝛇| where |𝛉| = num α × num field periods × deg/z_eff and |𝛇| = z_eff. + # Partial summation is more efficient than direct evaluation since + # mn|𝛉||𝛇| > mn|𝛇| + m|𝛉||𝛇| i.e. when n|𝛉| > n + |𝛉|. + + if self._num_z > 1: + z_eff = bijection_from_disc(x, *self._theta.domain)[:, None] + else: + z_eff = jnp.zeros((1, 1)) B_sup_z = ifft_mmt( - bijection_from_disc(x, *self._theta.domain)[:, None], + z_eff, self._c["B^zeta"], (0, 2 * jnp.pi / self._NFP), axis=-2, modes=self._modes_z, - ) - B_sup_z = B_sup_z[..., None, None, None, :, :] + )[..., None, None, :, :] B_sup_z = irfft_mmt_pos( - idct_mmt(x, self._theta.cheb.reshape(shape)), + idct_mmt(x, self._theta.cheb[..., None, :]), B_sup_z, self._num_t, modes=self._modes_t, @@ -1227,7 +1107,7 @@ def compute_fieldline_length(self, quad=None): # Simple mean over α because when ζ extends beyond one transit we need # to weight all field lines uniformly regardless of their area wrt α. dz_dx = jnp.pi / self._NFP - return jnp.abs(jnp.reciprocal(B_sup_z).dot(w).sum((-1, -2)).mean(-1)) * dz_dx + return jnp.abs(jnp.reciprocal(B_sup_z).dot(w).sum(-1).mean(-1)) * dz_dx def plot(self, l, m, pitch_inv=None, **kwargs): """Plot B and bounce points on the specified field line. @@ -1258,7 +1138,7 @@ def plot(self, l, m, pitch_inv=None, **kwargs): ) kwargs = set_default_plot_kwargs(kwargs, l, m) - B = self._c["B(z)"] + B = self._B if isinstance(B, PiecewiseChebyshevSeries): domain = B.domain B = B.cheb @@ -1277,7 +1157,7 @@ def plot(self, l, m, pitch_inv=None, **kwargs): if B.ndim == 3: B = B[m] if pitch_inv is not None: - kwargs["z1"], kwargs["z2"] = bounce_points(pitch_inv, self._c["knots"], B) + kwargs["z1"], kwargs["z2"] = _bounce_points(pitch_inv, self._c["knots"], B) kwargs["k"] = pitch_inv return plot_ppoly(PPoly(B.T, self._c["knots"]), **kwargs) @@ -1320,13 +1200,13 @@ def plot_angle_spectrum( angle, l, *, - truncate=0, norm=LogNorm(1e-7), h_ax_numticks=None, v_ax_numticks=None, + truncate=0, **kwargs, ): - """Plot frequency spectrum of the given stream map. + """Plot frequency spectrum of the given inverse stream map. Parameters ---------- @@ -1335,11 +1215,6 @@ def plot_angle_spectrum( Angle returned by ``Bounce2D.angle``. l : int Index into first axis of ``angle``. - truncate : int - Index at which to truncate any Chebyshev series. - This will remove aliasing error at the shortest wavelengths where the signal - to noise ratio is lowest. The default value is zero which is interpreted as - no truncation. norm : str The normalization method used for the color scale. See https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html. @@ -1348,6 +1223,10 @@ def plot_angle_spectrum( If given, labels at most ``h_ax_numticks`` marks on the horizontal axis. v_ax_numticks : int If given, labels at most ``v_ax_numticks`` marks on the vertical axis. + truncate : int + Index at which to truncate any Chebyshev series. This will remove aliasing + error at the shortest wavelengths where the signal to noise ratio is lowest. + The default value is zero which is interpreted as no truncation. kwargs Keyword arguments to pass to ``matplotlib``. @@ -1413,8 +1292,12 @@ def plot_angle_spectrum( return fig -class Bounce1D(Bounce): - """Computes bounce integrals using one-dimensional local spline methods. +def _fourier_if_real(thing): + return Bounce2D.fourier(thing) if jnp.isrealobj(thing) else thing + + +class Bounce1D(_Bounce): + """Computes bounce integrals using one-dimensional spline methods. The bounce integral is defined as ∫ f(ρ,α,λ,ℓ) dℓ where @@ -1434,6 +1317,8 @@ class Bounce1D(Bounce): Examples -------- * ``tests/test_integrals.py::TestBounce::test_bounce1d_checks`` + * ``desc/compute/_old.py::_epsilon_32_1D`` + * ``desc/compute/_old.py::_Gamma_c_1D`` See Also -------- @@ -1444,44 +1329,32 @@ class Bounce1D(Bounce): The domain is projected to ℝ, where information sampled about the function at infinity cannot support reconstruction of the function near the origin. As the functions of interest do not vanish at infinity, pseudo-spectral - techniques are not used. Instead, function approximation is done with local - splines. This is useful if one can efficiently obtain data along field lines + techniques are not used. Instead, function approximation is done with splines. + This is useful if one can efficiently obtain data along field lines and the number of toroidal transits to follow a field line is not large. Parameters ---------- grid : Grid Tensor-product grid in (ρ, α, ζ) Clebsch coordinates. - The ζ coordinates (the unique values prior to taking the tensor-product) - must be strictly increasing and preferably uniformly spaced. These are used - as knots to construct splines. A reference knot density is 100 knots per - toroidal transit. Also, the minimum value of the zeta coordinate must be - greater than the sentinel value of ``-1e5``. If this requirement is limiting - make a GitHub issue requesting to lower this value. + The ζ coordinates are preferably uniformly spaced as they are the + knots for the spline interpolation. data : dict[str, jnp.ndarray] Data evaluated on ``grid``. Must include names in ``Bounce1D.required_names``. quad : tuple[jnp.ndarray] - Quadrature points xₖ and weights wₖ for the approximate evaluation of an + Quadrature points xₖ and weights wₖ for the approximation of an integral ∫₋₁¹ g(x) dx = ∑ₖ wₖ g(xₖ). Default is 32 points. automorphism : tuple[Callable] or None The first callable should be an automorphism of the real interval [-1, 1]. The second callable should be the derivative of the first. This map defines a change of variable for the bounce integral. The choice made for the automorphism will affect the performance of the quadrature. - Bref : float - Optional. Reference magnetic field strength for normalization. - Lref : float - Optional. Reference length scale for normalization. - is_reshaped : bool - Whether the arrays in ``data`` are already reshaped to the expected form of - shape (..., num ζ) or (..., num α, num ζ) or - (num ρ, num α, num ζ). This option can be used to iteratively - compute bounce integrals one flux surface or one field line at a time, - respectively, reducing memory usage. - To do so, set to ``True`` and provide only those chunks of the reshaped data. check : bool Flag for debugging. Must be false for JAX transformations. + sentinel : float + A number which is less than all ζ coordinates in the grid. + Default is ``-1e5``. """ @@ -1490,8 +1363,9 @@ class Bounce1D(Bounce): _quad: tuple[jax.Array] _data: dict[str, jax.Array] - _zeta: jax.Array + _knots: jax.Array _B: jax.Array + _sentinel: float = eqx.field(static=True) def __init__( self, @@ -1500,38 +1374,44 @@ def __init__( quad=None, *, automorphism=None, - Bref=1.0, - Lref=1.0, - is_reshaped=False, check=False, + sentinel=-1e5, + **kwargs, ): """Returns an object to compute bounce integrals.""" assert grid.is_meshgrid + if quad is None: - quad = get_quadrature( - leggauss(32), (automorphism_sin, grad_automorphism_sin) - ) + quad = BounceOptions._quad(eta=-2, num_quad=32) else: quad = get_quadrature(quad, automorphism) - self._quad = jax.lax.stop_gradient(quad) + self._quad = quad + self._data = { - "|b^zeta|": jnp.abs(data["B^zeta"]) * Lref / data["|B|"], - "|B|": data["|B|"] / Bref, - "|B|_z|r,a": data["|B|_z|r,a"] / Bref, + "|b^zeta|": jnp.abs(data["B^zeta"]) / data["|B|"], + "|B|": data["|B|"], + "|B|_z|r,a": data["|B|_z|r,a"], } self._data["|b^zeta|_z|r,a"] = ( - data["B^zeta_z|r,a"] * jnp.sign(data["B^zeta"]) * Lref + data["B^zeta_z|r,a"] * jnp.sign(data["B^zeta"]) - self._data["|b^zeta|"] * data["|B|_z|r,a"] ) / data["|B|"] + # Figure out if input is split into batches. + s = data["|B|"].shape + is_reshaped = len(s) > 1 and s[-2] == grid.num_alpha and s[-1] == grid.num_zeta if not is_reshaped: for name in self._data: self._data[name] = Bounce1D.reshape(grid, self._data[name]) - self._zeta = jnp.asarray(grid.compress(grid.nodes[:, 2], surface_label="zeta")) + self._knots = jnp.asarray(grid.compress(grid.nodes[:, 2], surface_label="zeta")) + self._sentinel = sentinel + if check: + assert self._knots.min() > sentinel + self._B = jnp.moveaxis( CubicHermiteSpline( - x=self._zeta, + x=self._knots, y=self._data["|B|"], dydx=self._data["|B|_z|r,a"], axis=-1, @@ -1543,14 +1423,7 @@ def __init__( @staticmethod def batch( - fun, - fun_data, - desc_data, - grid, - num_pitch, - surf_batch_size=1, - simp=True, - expand_out=False, + fun, fun_data, desc_data, grid, *, surf_batch_size=1, sparse=True, **kwargs ): """Compute function ``fun`` over phase space in batches. @@ -1560,16 +1433,15 @@ def batch( Examples -------- - * ``desc/compute/_old.py::_epsilon_32_1D`` - * ``desc/compute/_old.py::_Gamma_c_1D`` + * ``desc/compute/_old.py::_epsilon_32_1D`` + * ``desc/compute/_old.py::_Gamma_c_1D`` Parameters ---------- fun : callable - A function which takes a single argument ``fun_data`` and computes + A function which takes a single argument ``fun_data`` and computes bounce integrals assuming ``fun_data`` holds all required quantities - to construct a ``Bounce1D`` operator with the flag ``is_reshaped=True`` - as well as call its methods. + to construct a ``Bounce1D`` operator as well as call its methods. fun_data : dict[str, jnp.ndarray] Data to reshape, interpolate, and pass to ``fun``. The structure of the data should match the structure @@ -1580,37 +1452,44 @@ def batch( functions in ``desc.compute``. grid : Grid Grid on which ``fun_data`` and ``desc_data`` were computed. - num_pitch : int - Number of pitch angles to add to ``fun_data`` for use in the computation. surf_batch_size : int Number of flux surfaces with which to compute simultaneously. Default is ``1``. - simp : bool - Whether the pitch angles should be chosen for use with open Simpson rule - instead of uniform weights for quadrature over velocity coordinate. - Default is True. - expand_out : bool - Whether to expand output to full grid so that the first dimension - has size ``grid.num_nodes`` instead of ``grid.num_rho``. - Default is False. + sparse : bool + Whether to differentiate with sparsity preserving pullbacks. + Default is ``True``, which makes the most sense if the output has + shape (num_rho, ). Otherwise, if the output shape is larger, and + the final objective of interest is a lower dimensional quantity + than the output, it may be preferable to delay the vjp + by setting to ``False``. Returns ------- The output ``fun(fun_data)``. """ + warnif( + "num_pitch" in kwargs, + FutureWarning, + "Argument num_pitch has been deprecated and is no longer used.", + ) + warnif( + "expand_out" in kwargs, + FutureWarning, + "Argument expand_out has been deprecated and is no longer used.", + ) + for name in Bounce1D.required_names: fun_data[name] = desc_data[name] for name in fun_data: fun_data[name] = Bounce1D.reshape(grid, fun_data[name]) - fun_data["pitch_inv"], fun_data["pitch_inv weight"] = Bounce.get_pitch_inv_quad( - grid.compress(desc_data["min_tz |B|"]), - grid.compress(desc_data["max_tz |B|"]), - num_pitch, - simp=simp, - ) - out = batch_map(fun, fun_data, surf_batch_size) - return grid.expand(out) if expand_out else out + fun_data["min_tz |B|"] = grid.compress(desc_data["min_tz |B|"]) + fun_data["max_tz |B|"] = grid.compress(desc_data["max_tz |B|"]) + + if sparse: + return sparse_pullback(fun, fun_data, surf_batch_size, strip_dim0=True) + + return batch_map(fun, fun_data, surf_batch_size, strip_dim0=True) @staticmethod def reshape(grid, f): @@ -1620,6 +1499,8 @@ def reshape(grid, f): ---------- grid : Grid Tensor-product grid in (ρ, α, ζ) Clebsch coordinates. + The ζ coordinates (the unique values prior to taking the tensor-product) + must be strictly increasing. f : jnp.ndarray Data evaluated on grid. @@ -1632,7 +1513,7 @@ def reshape(grid, f): """ return grid.meshgrid_reshape(f, "raz") - def points(self, pitch_inv, num_well=None): + def points(self, pitch_inv, num_well=-1): """Compute bounce points. Parameters @@ -1671,8 +1552,12 @@ def points(self, pitch_inv, num_well=None): line and pitch, is padded with zero. """ - return bounce_points( - broadcast_for_bounce(pitch_inv), self._zeta, self._B, num_well + return _bounce_points( + broadcast_for_bounce(pitch_inv), + self._knots, + self._B, + num_well, + sentinel=self._sentinel, ) def check_points(self, points, pitch_inv, *, plot=True, **kwargs): @@ -1703,7 +1588,13 @@ def check_points(self, points, pitch_inv, *, plot=True, **kwargs): """ return check_bounce_points( - *points, pitch_inv, self._zeta, self._B, plot=plot, **kwargs + *points, + pitch_inv, + self._knots, + self._B, + plot=plot, + sentinel=self._sentinel, + **kwargs, ) def integrate( @@ -1714,7 +1605,7 @@ def integrate( names=None, points=None, *, - num_well=None, + num_well=-1, method="cubic", quad=None, check=False, @@ -1755,7 +1646,7 @@ def integrate( Tuple of length two (z1, z2) that stores ζ coordinates of bounce points. The points are ordered and grouped such that the straight line path between ``z1`` and ``z2`` resides in the epigraph of B. - num_well : int or None + num_well : int See ``self.points`` for the description of this parameter. method : str Method of interpolation. @@ -1779,10 +1670,11 @@ def integrate( """ x, w = setdefault(quad, self._quad) + if not isinstance(integrand, (list, tuple)): integrand = [integrand] - data = apply(setdefault(data, {}), subset=names, exclude=("|B|",)) + data = apply(data, subset=names, exclude=("|B|",)) if points is None: points = self.points(pitch_inv, num_well) @@ -1790,24 +1682,24 @@ def integrate( pitch = broadcast_for_bounce(1 / pitch_inv)[..., None, None] - shape = (*z1.shape, x.size) # (..., num pitch, num well, num quad) + shape = z1.shape + (x.size,) # (..., num pitch, num well, num quad) z = flatten_mat(bijection_from_disc(x, z1[..., None], z2[..., None]), 3) b_sup_z = interp1d_Hermite_vec( z, - self._zeta, + self._knots, self._data["|b^zeta|"], self._data["|b^zeta|_z|r,a"], ).reshape(shape) B = interp1d_Hermite_vec( z, - self._zeta, + self._knots, self._data["|B|"], self._data["|B|_z|r,a"], ).reshape(shape) data = { - k: interp1d_vec(z, self._zeta, v, method=method).reshape(shape) + k: interp1d_vec(z, self._knots, v, method=method).reshape(shape) for k, v in data.items() } @@ -1831,7 +1723,12 @@ def integrate( return result[0] if len(result) == 1 else result def interp_to_argmin(self, f, points, *, method="cubic"): - """Interpolate ``f`` to the deepest point pⱼ in magnetic well j. + """Interpolate ``f`` to the deepest point in magnetic well w. + + Interpolate f to the argmin of the magnetic field + between each pair in ``points``. Explicitly, let + E(w) = {ζ ∣ ζ₁(w) < ζ < ζ₂(w)} and A(w) ∈ argmin_E(w) B. + Returns {f ∘ A(w)}. Parameters ---------- @@ -1861,9 +1758,9 @@ def interp_to_argmin(self, f, points, *, method="cubic"): # We set fill value to sentinel since all bounce points are at # ζ > sentinel (as documented in Bounce1D docstring); and # therefore, junk values in B_mins cannot be selected in argmin. - mins, B_mins = get_mins(self._zeta, self._B, fill_value=_sentinel) + mins, B_mins = get_mins(self._knots, self._B, fill_value=self._sentinel) return argmin( - *points, interp1d_vec(mins, self._zeta, f, method=method), mins, B_mins + *points, interp1d_vec(mins, self._knots, f, method=method), mins, B_mins ) def plot(self, l, m, pitch_inv=None, **kwargs): @@ -1887,6 +1784,8 @@ def plot(self, l, m, pitch_inv=None, **kwargs): Matplotlib (fig, ax) tuple. """ + kwargs = set_default_plot_kwargs(kwargs, l, m) + B = self._B if B.ndim == 4: B = B[l] @@ -1897,9 +1796,338 @@ def plot(self, l, m, pitch_inv=None, **kwargs): jnp.ndim(pitch_inv) > 1, msg=f"Got pitch_inv.ndim={jnp.ndim(pitch_inv)}, but expected 1.", ) - kwargs["z1"], kwargs["z2"] = bounce_points(pitch_inv, self._zeta, B) + kwargs["z1"], kwargs["z2"] = _bounce_points( + pitch_inv, self._knots, B, sentinel=self._sentinel + ) kwargs["k"] = pitch_inv - fig, ax = plot_ppoly( - PPoly(B.T, self._zeta), **set_default_plot_kwargs(kwargs, l, m) + return plot_ppoly(PPoly(B.T, self._knots), **kwargs) + + +class BounceOptions(NamedTuple): + """Parameter container for Bounce2D.""" + + # TODO(#2152): Consider instead of having users pass in 10 kwargs + # have them pass in this object, e.g. eq.compute(bounce_opts=opts). + # Reasons: 1) eq.compute kwarg namespace is polluted; + # e.g. some other compute function can't use the kwarg spline. + # 2) Long kwarg descriptions aren't readable in the public list + # of variables docs. + _doc = { + "angle": """jnp.ndarray : + Shape (num rho, X, Y). + Angle returned by ``Bounce2D.angle``. + """, + "Y_B": """int : + Desired resolution for algorithm to compute bounce points. + A reference value is ``(grid.num_theta+grid.num_zeta)//2``. + + If the option ``spline`` is ``True``, the bounce points are found with + 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order + 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and + 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹. + + If the option ``spline`` is ``False``, the bounce points are found such + that the bounce integrals have exponential accuracy in this parameter. + """, + "alpha": """jnp.ndarray : + Shape (num alpha, ). + Starting field line poloidal labels. + Default is single field line. + On irrational magnetic surfaces, it is sufficient to integrate along a + single field line. On a rational or near-rational surface in + non-axisymmetric configurations, it is necessary to integrate along + multiple field lines until the surface is covered sufficiently. + """, + "field_period_transits": """int : + Number of field periods to follow field line. + In axisymmetric configurations, integration along the field line for a + single poloidal transit between two global maxima of B is sufficient for + convergence. For a 3D configuration, the magnetic surface should be covered + sufficiently. + """, + "num_well": """int : + Maximum number of wells to detect for each pitch and field line. + Giving ``-1`` will detect all wells but due to current limitations in + JAX this will have worse performance. + Specifying a number that tightly upper bounds the number of wells will + increase performance. In general, an upper bound on the number of wells + per toroidal transit is ``Aι+C`` where ``A``, ``C`` are the poloidal and + toroidal Fourier resolution of B, respectively, in straight-field line + PEST coordinates, and ι is the rotational transform normalized by 2π. + A tighter upper bound than ``num_well=(Aι+C)*num_transit`` is preferable. + The ``check_points`` or ``plot`` methods in ``desc.integrals.Bounce2D`` + are useful to select a reasonable value. + + This is the most important parameter to specify for performance. + """, + "num_quad": """int : + Resolution for quadrature of bounce integrals. + Default is 32. This parameter is ignored if given ``quad``. + """, + "num_pitch": """int : + Resolution for quadrature over velocity coordinate. + """, + "pitch_batch_size": """int : + Number of pitch values with which to compute simultaneously. + If given ``None``, then ``pitch_batch_size`` is ``num_pitch``. + Default is ``num_pitch``. + """, + "surf_batch_size": """int : + Number of flux surfaces with which to compute simultaneously. + If given ``None``, then ``surf_batch_size`` is ``grid.num_rho``. + Default is ``1``. + Only consider increasing if ``pitch_batch_size`` is ``None``. + """, + "nufft_eps": """float : + Precision requested for interpolation with non-uniform fast Fourier + transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. + """, + "spline": """bool : + Whether to use cubic splines to compute initial guess for bounce points + instead of Chebyshev series. Default is ``True``. It can be preferable + to set to ``False`` on equilibria with high ``NFP``, (such cases make + smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast. + """, + "quad": """tuple[jnp.ndarray] : + Used to compute bounce integrals. + Quadrature points xₖ and weights wₖ for the + approximation of the integral ∫₋₁¹ f(x) dx ≈ ∑ₖ wₖ f(xₖ). + """, + "_vander": """dict[str,jnp.ndarray] : + Precomputed transform matrix "dct spline". + This private parameter is intended to be used only by + developers for objectives. + """, + "theta": "", + } + + _static_argnames = ( + "nufft_eps", + "field_period_transits", + "num_pitch", + "num_quad", + "num_well", + "pitch_batch_size", + "spline", + "surf_batch_size", + "Y_B", + ) + + alpha: jnp.ndarray + loop: bool + nufft_eps: float + field_period_transits: int + num_well: int + pitch_batch_size: int + pitch_quad: tuple[jnp.ndarray] + quad: tuple[jnp.ndarray] + spline: bool + surf_batch_size: int + vander: tuple[jnp.ndarray] + Y_B: int + + @classmethod + def guess( + cls, + eta, + grid, + *, + alpha=None, + loop=False, + nufft_eps=-1.0, + field_period_transits=20, + num_pitch=None, + num_quad=32, + num_well=None, + pitch_batch_size=None, + quad=None, + spline=True, + surf_batch_size=1, + Y_B=None, + **kwargs, + ): + """Guess parameters based on eta and grid. + + Parameters + ---------- + eta : int + The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the + behavior of the integrand near the bounce points. If η ∉ {-1, 1}, + then a quadrature that works for all η ∈ {−1, 0, 1} will be used. + grid : Grid + Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes + (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). + + """ + errorif( + (surf_batch_size > 1) and (pitch_batch_size is not None), + msg=f"Expected pitch_batch_size to be None, got {pitch_batch_size}.", + ) + + if eta == 1: + nufft_eps = 1e-6 if (nufft_eps < 0) else nufft_eps + num_pitch = setdefault(num_pitch, 51) + else: + nufft_eps = 1e-7 if (nufft_eps < 0) else nufft_eps + num_pitch = setdefault(num_pitch, 65) + nufft_eps = float(nufft_eps) + + if Y_B is None: + Y_B = BounceOptions._guess_Y_B(grid) + + if num_well is None: + num_well = BounceOptions._guess_num_well( + field_period_transits=field_period_transits, + NFP=grid.NFP, + mins_per_field_period=Y_B if spline else (Y_B // 2), + ) + + return cls( + alpha=jnp.zeros(1) if alpha is None else alpha, + loop=loop, + nufft_eps=nufft_eps, + field_period_transits=field_period_transits, + num_well=num_well, + pitch_batch_size=pitch_batch_size, + pitch_quad=jax.lax.stop_gradient(simpson2(num_pitch)), + quad=BounceOptions._quad(eta, num_quad) if quad is None else quad, + spline=spline, + surf_batch_size=surf_batch_size, + vander=kwargs.get("_vander", None), + Y_B=Y_B, ) - return fig, ax + + def keys(self): + """Names of elements in tuple.""" + return self._fields + + def __getitem__(self, key): + """Lookup by string or index.""" + return getattr(self, key) if isinstance(key, str) else tuple.__getitem__(key) + + @staticmethod + def _quad(eta, num_quad): + if eta == 1: + quad = chebgauss2(num_quad) + elif eta == -1: + quad = chebgauss1(num_quad) + else: + quad = get_quadrature( + leggauss(num_quad), (automorphism_sin, grad_automorphism_sin) + ) + quad = jax.lax.stop_gradient(quad) + return quad + + @staticmethod + def _guess_num_well(*, field_period_transits, NFP, mins_per_field_period=jnp.inf): + """Guess upper bound for number of wells based on spectrum. + + Parameters + ---------- + field_period_transits : int + Number of field periods to follow field line. + NFP : int + Number of field periods per toroidal transit. + mins_per_field_period : int + An upper bound for the number of minima of B, (and hence number of wells), + per field period. For splines this is the number of knots per field period. + For Chebyshev series, this is the max degree floor division by 2. + + Returns + ------- + num_well : int + A guess for the max number of wells that exist for any pitch angle + or field line after following it for the specified length. + The guess will ideally be more conservative than + ``field_period_transits*mins_per_field_period`` to enhance performance, + yet still remain loose enough that all wells are always detected. + + """ + # e.g. heliotron with nfp 19 needs num field periods * 2 + num_well = round(field_period_transits * (1 + 20 / NFP)) + return min(num_well, field_period_transits * mins_per_field_period) + + @staticmethod + def _guess_Y_B(grid): + """Guess Y_B from grid resolution. + + Parameters + ---------- + grid : Grid + Tensor-product grid in (ρ, θ, ζ) with uniformly spaced nodes + (θ, ζ) ∈ [0, 2π) × [0, 2π/NFP). + + """ + return (grid.num_theta + grid.num_zeta) // 2 + + @staticmethod + def _build_objective(o, names, eta): + """Builds the objective, selecting default values if they were not specified. + + Examples + -------- + * ``desc/objectives/_fast_ion.py::GammaC`` + * ``desc/objectives/_neoclassical.py::EffectiveRipple`` + + Parameters + ---------- + o : _Objective + The objective instance. + names : str + Builds profiles and transforms for the compute quantities registered + with these names. + eta : int + The number η ∈ {−1, 1} denoting which factor (v_∥)^η matches the + behavior of the integrand near the bounce points. If η ∉ {-1, 1}, + then a quadrature that works for all η ∈ {−1, 0, 1} will be used. + + """ + from desc.compute import get_profiles, get_transforms + from desc.objectives.utils import _parse_callable_target_bounds + + eq = o.things[0] + if o._grid is None: + o._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) + assert o._grid.can_fft2 + + X = o._hyperparam.pop("X") + Y = o._hyperparam.pop("Y") + o._constants["x"] = fourier_pts(X) + o._constants["y"] = cheb_pts(Y, (0, 2 * jnp.pi / eq.NFP))[::-1] + + Y_B = o._hyperparam["Y_B"] + if Y_B is None: + o._hyperparam["Y_B"] = Y_B = BounceOptions._guess_Y_B(o._grid) + if o._hyperparam["num_well"] is None: + o._hyperparam["num_well"] = BounceOptions._guess_num_well( + field_period_transits=o._hyperparam["field_period_transits"], + NFP=eq.NFP, + mins_per_field_period=Y_B if o._hyperparam["spline"] else (Y_B // 2), + ) + + o._constants["_vander"] = ( + { + "dct spline": chebvander( + jnp.linspace(-1, 1, Y_B, endpoint=False), truncate_rule(Y) - 1 + ) + } + if o._hyperparam["spline"] + else {} + ) + o._constants["quad"] = BounceOptions._quad(eta, o._hyperparam.pop("num_quad")) + + rho = o._grid.compress(o._grid.nodes[:, 0]) + o._constants["lambda"] = get_transforms( + "lambda", + eq, + grid=LinearGrid( + rho=rho, + M=eq.L_basis.M, # assuming this doesn't change in optimization + zeta=o._constants["y"] if (o._grid.num_zeta > 1) else 1, + NFP=eq.NFP, + ), + )["L"] + o._constants["profiles"] = get_profiles(names, eq, grid=o._grid) + o._constants["transforms"] = get_transforms(names, eq, grid=o._grid) + o._dim_f = o._grid.num_rho + o._target, o._bounds = _parse_callable_target_bounds(o._target, o._bounds, rho) diff --git a/desc/objectives/_fast_ion.py b/desc/objectives/_fast_ion.py index a1b169c110..61aab2650b 100644 --- a/desc/objectives/_fast_ion.py +++ b/desc/objectives/_fast_ion.py @@ -1,22 +1,14 @@ """Objectives for fast ion confinement.""" -from orthax.legendre import leggauss +import jax +from packaging import version from desc.backend import jnp -from desc.compute import get_profiles, get_transforms from desc.compute.utils import _compute as compute_fun -from desc.grid import LinearGrid -from desc.integrals._bounce_utils import Y_B_rule, num_well_rule -from desc.integrals.bounce_integral import Bounce2D -from desc.utils import setdefault, warnif +from desc.integrals.bounce_integral import BounceOptions +from desc.utils import errorif, warnif -from ..integrals.quad_utils import ( - automorphism_sin, - get_quadrature, - grad_automorphism_sin, -) from .objective_funs import _Objective, collect_docs, doc_bounce -from .utils import _parse_callable_target_bounds class GammaC(_Objective): @@ -65,12 +57,10 @@ class GammaC(_Objective): Default is Nemov. Set to ``False`` to use Velasco's. Nemov's Γ_c converges to a finite nonzero value in the infinity limit - of the number of toroidal transits. Velasco's expression has a secular - term that drives the result to zero as the number of toroidal transits - increases if the secular term is not averaged out from the singular - integrals. At finite resolution, an optimization using Velasco's metric - may need to be evaluated by measuring decrease in Γ_c at a fixed number - of toroidal transits. + of the number of toroidal transits. Velasco et al.'s expression has a + secular part that drives the result to zero. Therefore, an optimization + using Velasco et al.'s metric should be evaluated by measuring + improvement over a fixed number of field period transits. """.rstrip() + collect_docs( target_default="``target=0``.", @@ -80,12 +70,7 @@ class GammaC(_Objective): ) ) - _static_attrs = _Objective._static_attrs + [ - "_hyperparam", - "_key", - "_keys_1dr", - "_use_bounce1d", - ] + _static_attrs = _Objective._static_attrs + ["_hyperparam", "_key"] _coordinates = "r" _units = "~" @@ -101,15 +86,15 @@ def __init__( normalize=True, normalize_target=True, loss_function=None, - deriv_mode="auto", + deriv_mode="rev", # TODO: change to deriv_mode="auto" once jax>0.11.0 jac_chunk_size=None, name="Gamma_c", grid=None, X=32, Y=32, Y_B=None, - alpha=jnp.array([0.0]), - num_transit=20, + alpha=None, + field_period_transits=20, num_well=None, num_quad=32, num_pitch=65, @@ -117,32 +102,53 @@ def __init__( surf_batch_size=1, nufft_eps=1e-7, spline=True, - use_bounce1d=False, Nemov=True, **kwargs, ): + errorif( + deriv_mode == "fwd" + and (version.parse(jax.__version__) < version.parse("0.11.0")), + ValueError, + "JAX version >= 0.11.0 required for fwd deriv mode for objective: GammaC.", + ) try: import jax_finufft # noqa: F401 - except: # noqa: E722 + except Exception: warnif( nufft_eps >= 1e-14, msg="\njax-finufft is not installed properly.\n" "Setting parameter nufft_eps to zero.\n" - "Performance will deteriorate significantly.\n", + "Performance may be somewhat slower.\n", ) nufft_eps = 0.0 + nufft_eps = float(nufft_eps) + + warnif( + "use_bounce1d" in kwargs, + FutureWarning, + "Argument use_bounce1d has been deprecated and is no longer used.", + ) + if "num_transit" in kwargs: + warnif( + True, + FutureWarning, + "Argument num_transit has been deprecated in favor of " + "field_period_transits, converting to" + " field_period_transits = num_transit*eq.NFP", + ) + field_period_transits = kwargs.pop("num_transit") * eq.NFP if target is None and bounds is None: target = 0.0 - - self._use_bounce1d = use_bounce1d self._grid = grid + if alpha is None: + alpha = jnp.zeros(1) self._constants = {"quad_weights": 1.0, "alpha": alpha} self._hyperparam = { "X": X, "Y": Y, "Y_B": Y_B, - "num_transit": num_transit, + "field_period_transits": field_period_transits, "num_well": num_well, "num_quad": num_quad, "num_pitch": num_pitch, @@ -151,13 +157,6 @@ def __init__( "nufft_eps": nufft_eps, "spline": spline, } - if use_bounce1d: - self._hyperparam.pop("X") - self._hyperparam.pop("Y") - self._hyperparam.pop("pitch_batch_size") - self._hyperparam.pop("nufft_eps") - self._hyperparam.pop("spline") - self._key = "Gamma_c" if Nemov else "Gamma_c Velasco" super().__init__( @@ -169,8 +168,8 @@ def __init__( normalize_target=normalize_target, loss_function=loss_function, deriv_mode=deriv_mode, - name=name, jac_chunk_size=jac_chunk_size, + name=name, ) def build(self, use_jit=True, verbose=1): @@ -184,11 +183,8 @@ def build(self, use_jit=True, verbose=1): Level of output. """ - if self._use_bounce1d: - return self._build_bounce1d(use_jit, verbose) - - Bounce2D._build( - self, names=self._key, eta={"Gamma_c": -2, "Gamma_c Velasco": -1}[self._key] + BounceOptions._build_objective( + self, self._key, eta={"Gamma_c": -2, "Gamma_c Velasco": -1}[self._key] ) super().build(use_jit=use_jit, verbose=verbose) @@ -210,9 +206,6 @@ def compute(self, params, constants=None): Γ_c as a function of the flux surface label. """ - if self._use_bounce1d: - return self._compute_bounce1d(params, constants) - constants = self._get_deprecated_constants(constants) eq = self.things[0] @@ -244,79 +237,3 @@ def compute(self, params, constants=None): **self._hyperparam, ) return constants["transforms"]["grid"].compress(data[self._key]) - - def _build_bounce1d(self, use_jit=True, verbose=1): - eq = self.things[0] - if self._grid is None: - self._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym) - assert self._grid.is_meshgrid and eq.sym == self._grid.sym - - Y_B = self._hyperparam.pop("Y_B") - Y_B = setdefault(Y_B, Y_B_rule(self._grid, spline=True)) - - num_transit = self._hyperparam.pop("num_transit") - - if self._hyperparam["num_well"] is None: - self._hyperparam["num_well"] = num_well_rule(num_transit, eq.NFP, Y_B) - - num_quad = self._hyperparam.pop("num_quad") - - self._constants["zeta"] = jnp.linspace( - 0, 2 * jnp.pi * num_transit, Y_B * num_transit - ) - - self._keys_1dr = ["iota", "iota_r", "min_tz |B|", "max_tz |B|"] - self._key = "old " + self._key - - rho = self._grid.compress(self._grid.nodes[:, 0]) - self._constants["rho"] = rho - self._constants["quad"] = get_quadrature( - leggauss(num_quad), (automorphism_sin, grad_automorphism_sin) - ) - self._constants["profiles"] = get_profiles( - self._keys_1dr + [self._key], eq, self._grid - ) - self._constants["transforms_1dr"] = get_transforms( - self._keys_1dr, eq, self._grid - ) - - self._dim_f = self._grid.num_rho - self._target, self._bounds = _parse_callable_target_bounds( - self._target, self._bounds, rho - ) - super().build(use_jit=use_jit, verbose=verbose) - - def _compute_bounce1d(self, params, constants=None): - constants = self._get_deprecated_constants(constants) - eq = self.things[0] - - data = compute_fun( - eq, - self._keys_1dr, - params, - constants["transforms_1dr"], - constants["profiles"], - ) - grid = eq._get_rtz_grid( - constants["rho"], - constants["alpha"], - constants["zeta"], - coordinates="raz", - iota=self._grid.compress(data["iota"]), - params=params, - ) - data = { - key: grid.copy_data_from_other(data[key], self._grid) - for key in self._keys_1dr - } - data = compute_fun( - eq, - self._key, - params, - transforms=get_transforms(self._key, eq, grid, jitable=True), - profiles=constants["profiles"], - data=data, - quad=constants["quad"], - **self._hyperparam, - ) - return grid.compress(data[self._key]) diff --git a/desc/objectives/_neoclassical.py b/desc/objectives/_neoclassical.py index d2d926b3a5..e805291bd8 100644 --- a/desc/objectives/_neoclassical.py +++ b/desc/objectives/_neoclassical.py @@ -1,16 +1,14 @@ """Objectives for neoclassical transport.""" +import jax +from packaging import version + from desc.backend import jnp -from desc.compute import get_profiles, get_transforms from desc.compute.utils import _compute as compute_fun -from desc.grid import LinearGrid -from desc.integrals._bounce_utils import Y_B_rule, num_well_rule -from desc.integrals.bounce_integral import Bounce2D -from desc.utils import setdefault, warnif +from desc.integrals.bounce_integral import BounceOptions +from desc.utils import errorif, warnif -from ..integrals.quad_utils import chebgauss2 from .objective_funs import _Objective, collect_docs, doc_bounce -from .utils import _parse_callable_target_bounds class EffectiveRipple(_Objective): @@ -21,7 +19,7 @@ class EffectiveRipple(_Objective): transport from ripple wells can become the dominant transport channel. The effective ripple (ε) proxy estimates the neoclassical transport coefficients in the banana regime. To ensure low neoclassical transport, - a stellarator is typically optimized so that ε < 0.02. + a stellarator is typically optimized so that ε < 10⁻². Notes ----- @@ -51,11 +49,7 @@ class EffectiveRipple(_Objective): ) ) - _static_attrs = _Objective._static_attrs + [ - "_hyperparam", - "_keys_1dr", - "_use_bounce1d", - ] + _static_attrs = _Objective._static_attrs + ["_hyperparam"] _coordinates = "r" _units = "~" @@ -71,15 +65,15 @@ def __init__( normalize=True, normalize_target=True, loss_function=None, - deriv_mode="auto", + deriv_mode="rev", # TODO: change to deriv_mode="auto" once jax>0.11.0 jac_chunk_size=None, name="Effective ripple", grid=None, X=32, Y=32, Y_B=None, - alpha=jnp.array([0.0]), - num_transit=20, + alpha=None, + field_period_transits=20, num_well=None, num_quad=32, num_pitch=51, @@ -87,31 +81,53 @@ def __init__( surf_batch_size=1, nufft_eps=1e-6, spline=True, - use_bounce1d=False, **kwargs, ): + errorif( + deriv_mode == "fwd" + and (version.parse(jax.__version__) < version.parse("0.11.0")), + ValueError, + "JAX version >= 0.11.0 required for fwd deriv mode for objective: " + "EffectiveRipple.", + ) try: import jax_finufft # noqa: F401 - except: # noqa: E722 + except Exception: warnif( nufft_eps >= 1e-14, msg="\njax-finufft is not installed properly.\n" "Setting parameter nufft_eps to zero.\n" - "Performance will deteriorate significantly.\n", + "Performance may be somewhat slower.\n", ) nufft_eps = 0.0 + nufft_eps = float(nufft_eps) + + warnif( + "use_bounce1d" in kwargs, + FutureWarning, + "Argument use_bounce1d has been deprecated and is no longer used.", + ) + if "num_transit" in kwargs: + warnif( + True, + FutureWarning, + "Argument num_transit has been deprecated in favor of " + "field_period_transits, converting to" + " field_period_transits = num_transit*eq.NFP", + ) + field_period_transits = kwargs.pop("num_transit") * eq.NFP if target is None and bounds is None: target = 0.0 - - self._use_bounce1d = use_bounce1d self._grid = grid + if alpha is None: + alpha = jnp.zeros(1) self._constants = {"quad_weights": 1.0, "alpha": alpha} self._hyperparam = { "X": X, "Y": Y, "Y_B": Y_B, - "num_transit": num_transit, + "field_period_transits": field_period_transits, "num_well": num_well, "num_quad": num_quad, "num_pitch": num_pitch, @@ -120,12 +136,6 @@ def __init__( "nufft_eps": nufft_eps, "spline": spline, } - if use_bounce1d: - self._hyperparam.pop("X") - self._hyperparam.pop("Y") - self._hyperparam.pop("pitch_batch_size") - self._hyperparam.pop("nufft_eps") - self._hyperparam.pop("spline") super().__init__( things=eq, @@ -136,8 +146,8 @@ def __init__( normalize_target=normalize_target, loss_function=loss_function, deriv_mode=deriv_mode, - name=name, jac_chunk_size=jac_chunk_size, + name=name, ) def build(self, use_jit=True, verbose=1): @@ -151,10 +161,7 @@ def build(self, use_jit=True, verbose=1): Level of output. """ - if self._use_bounce1d: - return self._build_bounce1d(use_jit, verbose) - - Bounce2D._build(self, names="effective ripple", eta=1) + BounceOptions._build_objective(self, "effective ripple", eta=1) super().build(use_jit=use_jit, verbose=verbose) def compute(self, params, constants=None): @@ -175,9 +182,6 @@ def compute(self, params, constants=None): Effective ripple as a function of the flux surface label. """ - if self._use_bounce1d: - return self._compute_bounce1d(params, constants) - constants = self._get_deprecated_constants(constants) eq = self.things[0] @@ -209,87 +213,3 @@ def compute(self, params, constants=None): **self._hyperparam, ) return constants["transforms"]["grid"].compress(data["effective ripple"]) - - def _build_bounce1d(self, use_jit=True, verbose=1): - eq = self.things[0] - if self._grid is None: - self._grid = LinearGrid(M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym) - assert self._grid.is_meshgrid and eq.sym == self._grid.sym - - Y_B = self._hyperparam.pop("Y_B") - Y_B = setdefault(Y_B, Y_B_rule(self._grid, spline=True)) - - num_transit = self._hyperparam.pop("num_transit") - - if self._hyperparam["num_well"] is None: - self._hyperparam["num_well"] = num_well_rule(num_transit, eq.NFP, Y_B) - - num_quad = self._hyperparam.pop("num_quad") - - self._constants["zeta"] = jnp.linspace( - 0, 2 * jnp.pi * num_transit, Y_B * num_transit - ) - - self._keys_1dr = [ - "iota", - "iota_r", - "<|grad(rho)|>", - "min_tz |B|", - "max_tz |B|", - "R0", - ] - - rho = self._grid.compress(self._grid.nodes[:, 0]) - self._constants["rho"] = rho - self._constants["quad"] = chebgauss2(num_quad) - self._constants["profiles"] = get_profiles( - self._keys_1dr + ["old effective ripple"], eq, self._grid - ) - self._constants["transforms_1dr"] = get_transforms( - self._keys_1dr, eq, self._grid - ) - - self._dim_f = self._grid.num_rho - self._target, self._bounds = _parse_callable_target_bounds( - self._target, self._bounds, rho - ) - super().build(use_jit=use_jit, verbose=verbose) - - def _compute_bounce1d(self, params, constants=None): - constants = self._get_deprecated_constants(constants) - eq = self.things[0] - - data = compute_fun( - eq, - self._keys_1dr, - params, - constants["transforms_1dr"], - constants["profiles"], - ) - grid = eq._get_rtz_grid( - constants["rho"], - constants["alpha"], - constants["zeta"], - coordinates="raz", - iota=self._grid.compress(data["iota"]), - params=params, - ) - data = { - key: ( - grid.copy_data_from_other(data[key], self._grid) - if key != "R0" - else data[key] - ) - for key in self._keys_1dr - } - data = compute_fun( - eq, - "old effective ripple", - params, - transforms=get_transforms("old effective ripple", eq, grid, jitable=True), - profiles=constants["profiles"], - data=data, - quad=constants["quad"], - **self._hyperparam, - ) - return grid.compress(data["old effective ripple"]) diff --git a/desc/objectives/objective_funs.py b/desc/objectives/objective_funs.py index 9ec99d6808..f66f0a7c26 100644 --- a/desc/objectives/objective_funs.py +++ b/desc/objectives/objective_funs.py @@ -134,13 +134,10 @@ doc_bounce = """ Notes ----- - Consider using an optimizer that uses a scalar output loss function - to improve performance before reducing ``jac_chunk_size``. - Developer notes: Performance will improve significantly by resolving GitHub issues: * ``1206`` Upsample data above midplane to full grid assuming stellarator symmetry * ``1034`` Optimizers/objectives with auxiliary output - * ``2168`` Sparse cotangent pullbacks + * ``2171`` Single cotangent pullback through compute pipeline. Parameters ---------- @@ -163,29 +160,29 @@ Default is 32. Y_B : int Desired resolution for algorithm to compute bounce points. + A reference value is ``(grid.num_theta+grid.num_zeta)//2``. + If the option ``spline`` is ``True``, the bounce points are found with - 8th order accuracy in this parameter. If the option ``spline`` is ``False``, - then the bounce points are found with spectral accuracy in this parameter. - A reference value for the ``spline=True`` option is - ``grid.NFP*(grid.num_theta+grid.num_zeta)//2``. - A reference value for the ``spline=False`` option is - ``(grid.num_theta+grid.num_zeta)//2``. - - An error of ε in a bounce point manifests - 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and - 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹. + 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order + 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and + 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹. + + If the option ``spline`` is ``False``, the bounce points are found such + that the bounce integrals have exponential accuracy in this parameter. alpha : jnp.ndarray Shape (num alpha, ). Starting field line poloidal labels. - Default is single field line. To compute a surface average - on a rational surface, it is necessary to average over multiple - field lines until the surface is covered sufficiently. - num_transit : int - Number of toroidal transits to follow field line. - In an axisymmetric device, field line integration over a single poloidal - transit is sufficient to capture a surface average. For a 3D - configuration, more transits will approximate surface averages on an - irrational magnetic surface better, with diminishing returns. + Default is single field line. + On irrational magnetic surfaces, it is sufficient to integrate along a + single field line. On a rational or near-rational surface in + non-axisymmetric configurations, it is necessary to integrate along + multiple field lines until the surface is covered sufficiently. + field_period_transits : int + Number of field periods to follow field line. + In axisymmetric configurations, integration along the field line for a + single poloidal transit between two global maxima of B is sufficient for + convergence. For a 3D configuration, the magnetic surface should be covered + sufficiently. num_well : int Maximum number of wells to detect for each pitch and field line. Giving ``-1`` will detect all wells but due to current limitations in @@ -213,11 +210,13 @@ If given ``None``, then ``surf_batch_size`` is ``grid.num_rho``. Default is ``1``. Only consider increasing if ``pitch_batch_size`` is ``None``. nufft_eps : float - Precision requested for interpolation with non-uniform fast Fourier - transform (NUFFT). If less than ``1e-14`` then NUFFT will not be used. + Precision requested for interpolation with non-uniform fast Fourier transform + (NUFFT). If less than ``1e-14`` then NUFFT will not be used. spline : bool Whether to use cubic splines to compute initial guess for bounce points - instead of Chebyshev series. Default is ``True``. + instead of Chebyshev series. Default is ``True``. It can be preferable + to set to ``False`` on equilibria with high ``NFP``, (such cases make + smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast. """.rstrip() diff --git a/desc/plotting.py b/desc/plotting.py index 59bff4df5c..ffcc6e0998 100644 --- a/desc/plotting.py +++ b/desc/plotting.py @@ -24,7 +24,6 @@ from desc.equilibrium.coords import map_coordinates from desc.grid import Grid, LinearGrid from desc.integrals import surface_averages_map -from desc.integrals._bounce_utils import Y_B_rule, num_well_rule from desc.magnetic_fields import field_line_integrate from desc.particles import trace_particles from desc.utils import ( @@ -4699,7 +4698,7 @@ def plot_gammac( matplotlib) * ``cmap``: str, matplotlib colormap scheme to use, passed to ax.contourf * ``X``, ``Y``, ``Y_B``, ``num_quad``, ``num_well``: int - * ``num_transit``: int + * ``field_period_transits``: int hyperparameters for bounce integration. See ``Bounce2D`` @@ -4733,14 +4732,9 @@ def plot_gammac( # TODO(#1352) grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - kwargs.pop("pitch_batch_size", None) - kwargs.pop("surf_batch_size", None) X = kwargs.pop("X", 32) Y = kwargs.pop("Y", 32) - Y_B = kwargs.pop("Y_B", Y_B_rule(grid, spline=True)) - num_quad = kwargs.pop("num_quad", 32) - num_transit = kwargs.pop("num_transit", 2) - num_well = kwargs.pop("num_well", num_well_rule(num_transit, eq.NFP, Y_B)) + field_period_transits = kwargs.pop("field_period_transits", 5) figsize = kwargs.pop("figsize", (6, 5)) cmap = kwargs.pop("cmap", "plasma") @@ -4755,18 +4749,16 @@ def plot_gammac( "gamma_c", grid=grid, angle=Bounce2D.angle(eq, X, Y, rho), - Y_B=Y_B, - num_transit=num_transit, - num_quad=num_quad, + field_period_transits=field_period_transits, num_pitch=num_pitch, - num_well=num_well, alpha=alphas, + **kwargs, ) # Extract pitch angle range minB = data0["min_tz |B|"][0] maxB = data0["max_tz |B|"][0] - inv_pitch, _ = Bounce2D.get_pitch_inv_quad(minB, maxB, num_pitch) + inv_pitch, _ = Bounce2D.pitch_quad(minB, maxB, num_pitch) # Create figure and prepare colormap fig, ax = _format_ax(ax, figsize=figsize) diff --git a/desc/utils.py b/desc/utils.py index 34088ebb01..77f8627dfc 100644 --- a/desc/utils.py +++ b/desc/utils.py @@ -1155,6 +1155,8 @@ def apply(d, fun=identity, subset=None, exclude=None): and keys not in ``exclude``. """ + if d is None: + return {} if subset is None: subset = d.keys() elif isinstance(subset, str): diff --git a/docs/installation.rst b/docs/installation.rst index 9a0aab96c7..67c678cd82 100644 --- a/docs/installation.rst +++ b/docs/installation.rst @@ -291,7 +291,7 @@ On Most Linux Computing Clusters .. code-block:: sh pip install -r devtools/dev-requirements.txt - + Run a test by replacing path_to_DESC with your path .. code-block:: sh @@ -350,7 +350,7 @@ To verify your installation works, try the following. from desc.examples import get from desc.objectives import ObjectiveFunction, GammaC - obj = ObjectiveFunction(GammaC(get("W7-X"), num_transit=1, num_pitch=1)) + obj = ObjectiveFunction(GammaC(get("W7-X"), field_period_transits=1, num_pitch=1)) obj.build() x = obj.x() obj.compute_scaled_error(x).block_until_ready() diff --git a/docs/notebooks/tutorials/EffectiveRipple.ipynb b/docs/notebooks/tutorials/EffectiveRipple.ipynb index 36130b0983..8257e5eb7e 100644 --- a/docs/notebooks/tutorials/EffectiveRipple.ipynb +++ b/docs/notebooks/tutorials/EffectiveRipple.ipynb @@ -11,15 +11,13 @@ "So we will also breifly show how to visualize the ripples and accordingly pick resolution parameters.\n", "The same tutorial can be used to optimize for fast ion confinement with Γ_c. To do so, replace the objective ``EffectiveRipple`` with ``GammaC``.\n", "\n", - "- Note that there is still work in progress to improve the performance in DESC by an order of magnitude. See the GitHub issues linked in the objective docstring if you would like to contribute.\n", - "\n", "## Neoclassical transport in banana regime\n", "A 3D stellarator magnetic field admits ripple wells that lead to enhanced\n", "radial drift of trapped particles. In the banana regime, neoclassical (thermal)\n", "transport from ripple wells can become the dominant transport channel.\n", "The effective ripple (ε) proxy estimates the neoclassical transport\n", "coefficients in the banana regime. To ensure low neoclassical transport,\n", - "a stellarator is typically optimized so that ε < 0.02.\n", + "a stellarator is typically optimized so that ε < $10^{-2}$.\n", "\n", "## Fast ion confinement\n", "The energetic particle confinement\n", @@ -39,7 +37,7 @@ "https://doi.org/10.1063/1.2912456)\n", "V. V. Nemov, S. V. Kasilov, W. Kernbichler, G. O. Leitold.\n", "Phys. Plasmas 1 May 2008; 15 (5): 052501.\n", - "- Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications. Kaya Unalmis et al. Journal of Plasma Physics." + "- [Spectrally accurate, reverse-mode differentiable bounce-averaging algorithm and its applications.](https://arxiv.org/abs/2412.01724) Kaya Unalmis et al. Journal of Plasma Physics." ] }, { @@ -106,15 +104,7 @@ "execution_count": 4, "id": "2ca9de52-32a6-4552-86f0-ca648cf6616f", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n" - ] - } - ], + "outputs": [], "source": [ "import numpy as np\n", "from matplotlib import pyplot as plt\n", @@ -143,12 +133,11 @@ "metadata": {}, "source": [ "## Documentation\n", - "Please read the full documentation of the methods to understand what the input parameters do. In Jupyter Lab, you can click on the code and press ``Shift+Tab`` to pull up the documentation. Breifly,\n", + "Please read the full documentation of the methods to understand what the input parameters do. In Jupyter Lab, you can click on the code and press ``Shift+Tab`` to pull up the documentation. Briefly,\n", "\n", "- The equilibrium resolution determines the spectral resolution of the FourierZernike series fit to the boundary.\n", "- The grid determines the flux surfaces to compute on and the resolution of FFTs.\n", - "- The parameters ``X`` and ``Y`` determine the spectral resolution of the map between coordinates that parameterize the boundary and field line coordinates.\n", - "- The parameter ``Y_B`` determines the resolution for the bounce point finding algorithm. Feel free to reduce this until the plots of $\\vert B\\vert$ along field lines do not change. If $\\vert B\\vert$ is high frequency, then a larger value will be needed (larger than ``Y``)." + "- The parameters ``X`` and ``Y`` determine the spectral resolution of the map between coordinates that parameterize the boundary and field line coordinates." ] }, { @@ -173,7 +162,7 @@ "outputs": [ { "data": { - "image/png": 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zp8ftwIEDqlevntfrh5YtW6aoqCi/bgX3KZXO3JXXsRPsvgpq166dunbtqtzcXM2bN8/rNUo5OTn65JNPtH37dtWtW7fQ8/HkyZOqVq1akfspid9++02HDh0K6nqwoqxfv142m8293d69eyszM1PLli2Tw+HQ5s2bC7392bhxY0VHR6tq1aqqWrWq+5qp09vr16+vu+66y/01Kv4+j06ePKkFCxZ4XA8mnbrO7sSJEx4X6m/cuFGSfL7ulfS5ECxTxLWFbdu21fTp0/X666/r/PPPL/QVHL7mtrRt3rxZnTt3LrXtzZw5U8nJyYqJiVFiYqIGDx5c4b9zsiwF+7oUzOtgXl6ePv30U1133XWFjrns7GzZbDbFxsZKOnVtaHR0tPvDQME4ePCgrrrqKsXExKhp06ZatGhRwNsI+pqwDh06uD8dWZSoqKhgd+HBdY3K3/72Nw0ePNhrn1atWrmf9Fbz9enK8q5v586dOnbsWKHrXw4ePChJGjlypN/b+vHHH2WM8es6sILGjBmjv/zlLz7Xv/fee3rllVc0ePDgQtcCuT6pV/C6r4yMDH311Ve65ZZbvG6zWbNmfr//f/pF4S6lOXeBsPLYef3117Vp0yZNnDhRgwcP1tq1awu9mO3cuVPHjx/X5MmT1alTJ6/bKY3rpnwpyfVg0qnrVvPy8nTs2DGPsLhhwwadc8457sDdqVMn1a5dWx999JHi4+N14sQJr4/riy++cH/oyFv7tm3b1LVrVzVr1kwjRozw+3n09ddfKzMzU1deeaVH+6ZNmyR5Bi7XnPgKYSV9LgTryJEjio6O9vp7YPPmzRo/fry6d++uESNGeJ0PX3NbGvLy8hQWFtyvQF9jH3nkEc2YMUOvvPKKLrvsMjkcDr355pv68ssvfb5OwbtgXgfXrl2rY8eOqXXr1oXWrVu3TikpKe5PRG/atKnEJ2tGjhypuLg4HTx4UAsXLtTAgQO1bds21axZ0+9tlNqF+f6oU6eOoqOjvf5P66efflJISIgSEhJ8jq1WrZocDkeRX0XgdDoVGxvrfqEqir+f6CtJ3YEoi/24AoPrAm6XtLQ0r+1FcYWhYD4JmZyc7POLXOfNm6fXXntNN954o1599dVCF+m6flFmZWV5tL/22mvKzc3ViBEjvG43Li7O54cB/FEac1cWP1Nf818a++ratau6du2qAwcO6OGHH9bOnTt17rnnevRxfRL1ggsusORrQVxnfbyFsMOHD6tu3brKzMxUdHS0pFOfbP33v/+tpUuXSjoVSKRT/xM+fRsbNmzQxRdf7F4OCQlRamqqPvroI3fYDCb4NWnSRJdccok2b94syf/n0SeffKLmzZsXush+06ZNCgkJ0QUXXOBu27hxo/uspDclfS4Ea9euXR51nu6LL77QiRMn9MorrwT8RdObN2/W7bffro0bN+rcc8/VM8884/7Z2Ww2paenu79Ut1u3bvr73/+uv/3tb7LZbHr22Wf1xBNPqGHDhvrqq6/UuHFjvfHGG+rSpYv27NmjESNGaOXKlapbt66eeuop9+uWt7GnO3r0qKZMmaK5c+d6BOeCn+j+6KOPNG3aNB07dkz33HOPJkyY4F5X1P6lU6+Vjz/+uHJzc3XPPfdo7NixmjJlirZu3erxxbmXXnqpbrvtNl1//fUaPXq05s6dq7y8PDVp0kSfffaZ+7UrmFoeeeQR7dixwyPUd+/eXcOGDfP6dTHl9ftTkvuvxhT8D/tvv/2mr7/+Wg888IC7raQhLCsrSx9++KF27typ6OhoXX311UpOTtb8+fPd7875o1w/khIaGqrLL79c8+fP9zg9u3//fs2dO1ddunRxnyr0NrZ///56//33vQYs1y/MkJAQXXPNNfroo4/c3yV0utNTtOsHVdw3j5ek7kCUxX7sdrskeczZ3LlztWzZMknSiRMn/N6W65fBBx98EFANxZkzZ477Kwu8fUqqVatWCgkJ8fjzNb/88osmT56sm2++udS+MqCg0pi7sviZ+jpuS3NfrrcCvD03GjduLJvNpvfff7/Qury8vGLfNi2pDRs2KDQ0VM2bNy+0rmbNmkpISHCfGcrLy9PEiRM1ZcoUdx/XW0+nvz7s27dPBw4cKHSmq3fv3tq5c6feeustScGd4duyZYu++uor9//O/X0effrpp4XeipROHY+uP9vl8tNPP1n+PWLerF271v1dfgVlZmZKUsC/gHNzc9WnTx8NGDBABw8e1Lhx49SnTx+/j7sFCxZo/fr1+uKLLzzanU6n+vTpo169emn//v169dVXddNNN3n8JRhfYyVpxYoVys3NVe/evYvc/5dffqmNGzdqyZIlevjhh93fLODP/j/++GNt2rRJS5Ys0ZNPPqlFixbpxhtv1Pz5892vR7/88ou+//579e3bV1988YWWL1+unTt36vfff9eLL77o8d14wdQyaNAgzZ8/XydPnpR06rmzatUq9e3b1+vjLa/fn9KfZ4Rd/+GSTr0GjBgxQna73f0n0yTvIax3796qXr2619tjjz3m0Xfbtm2qWrWqx1/QSE5Odv9ny2+BXkTmumjd2ycPT+e6uO7gwYMe7Zs2bTIxMTGmQYMG5tFHHzVTp04155xzjomIiDArV670ui/XBcj79u0zjRo1MtHR0eauu+4yL774oklLSzMDBgwwNWrUcI/75ZdfTFxcnImOjjajR482L774onnooYdMixYtzJEjR9z9Vq1aZSSZK6+80rz++uvmrbfeMllZWV4/Helv3b4et7dteuPvfvy9MN/hcJikpCQTHh5uJk6caB566CETGRlpBg4caCSZIUOGmA0bNniMkWQuvfRSr9vr1auXkWSuvfZa8/zzz5vPPvvM5OTkFFnDtm3bTGZmps/1J06cKPYTK/369TNVqlQxEydONE888YRJSEgwKSkpxV6kWRLBzJ03pX3s+DpuA9lXcYp7nv/1r381ksxVV11lnnvuOfP000+bO+64wzRo0MB89dVXfu8nGCkpKaZp06Y+11933XXm3//+tzHGmJkzZ3r9hvuWLVt6fHL7888/N5LMBx984NHv6NGjpkqVKsZms5n4+PhC22nUqJGpWrWqsdvtxm63m7vvvrtQe1JSkrnvvvuMw+FwjyvuebRz504jySxZsqTQPps1a2auvvpqj7b4+HjTpUsXj9e3svDss8+ayZMnmxEjRhhJpl+/fmby5Mlm8uTJ5ujRox59XR9gWbhwoddtuY53X3zNreuDI6fr1KmTmTt3rjGm8AXnl156qZkzZ457XcGL8Bs1amS++uors2LFCtOkSROPdf3793d/+MDb2NPNmTPH1KtXz+d61zZWr17tXm7fvr2ZN2+eMcb4tf/Fixe71/3jH/8ww4cPN8YYc8kll7g/kfyvf/3LfWwvXLjQnH/++ebbb78tdKF6SWq58MILzccff2yMOXVMXHvttUU+7kBel0ryO7Rr166mefPmJiIiwowfP95Mnz7ddOrUyYSGhrofm0tycrL55ptviqy7KN6Ow/vvv9/9iW9/lXsIM8aYtWvXml69epmqVaua6Oho0717d68Ht7dJ379/vxk5cqRJSEgwVapUMXFxcaZHjx7mpZde8hj7888/m5tvvtnUqVPHREREmHPOOceMHDmyUGCYPHmyadCggQkJCXHvy9cP25+6SxrC/N1PIJ+O/P77702nTp1MRESEqVGjhvnHP/5hnE6nueWWW0xYWJiZPXu2u++xY8eMJHP99dd73daxY8fMvffea84991wTHh5uJJX6n3Hx5vDhw6Zfv34mJibG1KtXz9xxxx1FBrvSEsjcFaW0jx1vx20g+yrO66+/biT5DFQnTpwwU6ZMMc2bNzdRUVGmVq1apn379mbSpEll+im3kydPmvDwcI+vjijoscceM8OHDzcnTpwwiYmJZs2aNYX6PPnkk6Zq1arur36YNm2akWS2b99eqG/37t2NJHPFFVcUWuf6Be5vu0txz6PnnnvO2O32Qv85ycnJMWFhYeb+++/3aB82bJiJiIgw/fr187nP0tCoUSOfXxNT8LVt/PjxJjEx0eenLceNG2dCQ0OL3Je3OXz77bdNly5dPNoGDRpk/vWvfxljig9he/bs8bqfd955x4SFhblDn91uNzExMWbKlClex77xxhsmJibGxMTEmNtuu818+umnJjQ0tMj/UBZVmz/7P/34fOGFF0zv3r2NMca8+OKL5rrrrjPGnPoU7+l/buzJJ580KSkppl69euaee+5xf9q3JLVMnTrV3HTTTcYYY7p06WLefvttn4/Zxd/XpZL8Dq1Ro4Z54IEHzEsvvWQSEhJMRESE6dy5s1m0aJFHv5MnT5qIiIgS/Sd+7dq1Hid/jDFm1KhR5p577gloOwGHsPL08ssvl9vHaHHKJ598Ymw2m19neIwx5r777jOSzOHDh8u4MpSnRYsWGUnm1ltvNbt377bs6wOCsXDhQtOuXTvz1FNPmf79+3vtc/ToUVOzZk2P7y0LRrAhrKCCz6PU1NQig2ZFd+LECRMXF2emT59eaN3vv/9uNmzYYFq1amUSExN9bsPXHHo7A9G5c2f3mbDo6GizdetW97pmzZp5hLCCv09c+/n666+L/NqQ4n4XHTlyxERGRpoPP/zQ722cHnz82b+vM2GHDx821atXN6tXrza1atVyB63T7dmzx7Rs2dLjzFqwtezatcvY7XazY8cOU7VqVfeZeCu5vqbFdRwUZfPmzSYhIaFQ+xVXXOEO1gVvjz76qEffY8eOmSpVqnh8z123bt0C+g5NY0rwFRXl4bfffpPNZgvokwYomcWLF+v666/3++P/derUUVRUlMf1Kaj8LrnkEl188cV66aWX1Lhx40JfH1CRtW3bVps3b9bUqVM9vmn+dHa7XePGjdPjjz/u/uS1lQo+j7p166a7777b4qqCN2vWLFWpUkW33357oXVt2rRRq1attHnzZvef4AqE69vVn3vuOeXl5endd9/Vjz/+6L6APSUlRW+//bYcDodef/11bd++3e/tOp1OPf/888rNzVVubq6++uor7dmzx6/x1atX1z/+8Q/93//9nz7//HPl5OTo+PHjevXVV73+ab1g9j916lRlZmZqy5YtevXVVzVw4EBJp76+oXv37ho8eLAGDBjg/nNuq1ev1nfffae8vDxVq1ZNVapU8evvIhdXS+PGjXXBBRdo+PDhuvLKK8v0L5b4y/WBHX+ujfR1Uf5nn32mrKwsr7f777/fo2/VqlXVt29fTZo0SX/88Yc+/vhjbdiwwee1cT4FFNnKyb59+8xzzz1nGjRoYC666CKry4EPzzzzjKlWrVrA74Gj8ti2bZtZsmSJz2/Or6jOPfdc99slZak0zoSdbc+jb775xixfvrzYs+dFzeH69evNRRddZGJjY82FF15oli1b5l63cuVK07RpUxMbG2vuvPNO07VrV7/OhBljzO7du03fvn1N7dq1Ta1atUyvXr3cb395G+vNiy++aFq2bGmioqJMw4YNzc0332x2797tdRunn33yZ//PPPOMSUhIMHXr1jVpaWke+33//feNJI+5WLhwoWnZsqWJiYkxdevWNaNGjXL/xYeS1GLMn3/x4L333it2TspDWlqaCQ0NNSdOnCi274MPPujxZcfBOnDggElNTTVRUVGmSZMmZsGCBQFvw2ZMBflirdO4/ihwhw4dNHPmzCL/hhys0759e7Vt21ZPPvkkZ8JQYWRlZalJkyb65ptvdM4551hdTrF4HqE0rF69Wv3799fu3buD+hqhyu7GG2/U6tWrS/XLhstDhQxhABCsu+++Ww6HQ88884zVpQDlwuFw6JZbblFSUpIeeughq8tBACr0NWEA4K9169bJbrdrw4YNHt8LBpzJDh8+LLvdrh9++EGjR4+2uhwEiDNhAAAAFuBMGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQdpoZM2aocePGioyMVMeOHbVq1SqrS6qwHnroIdlsNo9bs2bNrC6rwli2bJn69Omj+Ph42Ww2ffjhhx7rjTGaOHGi6tevr6ioKPXs2VPbtm2zptgKoLj5GjJkSKHj7YorrrCm2AogLS1N7du3V7Vq1VS3bl1dc8012rJli0efEydOaOTIkapVq5aqVq2q/v37a//+/RZVbC1/5qtbt26FjrHbb7/dooqt9fzzz6tVq1aKjY1VbGysOnfurM8++8y9nmOr9BDC8r3zzjsaM2aMJk2apLVr1yolJUW9evXSgQMHrC6twmrRooV+++039+3rr7+2uqQKIzs7WykpKZoxY4bX9dOmTdMzzzyjF154Qd9++61iYmLUq1cvnThxopwrrRiKmy9JuuKKKzyOt7feeqscK6xYli5dqpEjR2rlypVasGCBTp48qcsvv1zZ2dnuPnfffbc++ugjvfvuu1q6dKn27t2rfv36WVi1dfyZL0kaPny4xzE2bdo0iyq2VsOGDfXYY49pzZo1Wr16tS677DL17dtXmzdvlsSxVaoMjDHGdOjQwYwcOdK97HA4THx8vElLS7Owqopr0qRJJiUlxeoyKgVJZt68ee5lp9Np4uLizOOPP+5uO3r0qImIiDBvvfWWBRVWLAXnyxhjBg8ebPr27WtJPZXBgQMHjCSzdOlSY8yp46lKlSrm3Xffdff58ccfjSSzYsUKq8qsMArOlzHGXHrppeauu+6yrqgKrkaNGubll1/m2CplnAmTlJubqzVr1qhnz57utpCQEPXs2VMrVqywsLKKbdu2bYqPj9c555yjG2+8UXv27LG6pEph165d2rdvn8fxZrfb1bFjR463IixZskR169ZV06ZNNWLECP3+++9Wl1RhZGRkSJJq1qwpSVqzZo1OnjzpcYw1a9ZMiYmJHGMqPF8ub775pmrXrq2WLVtqwoQJOn78uBXlVSgOh0Nvv/22srOz1blzZ46tUhZmdQEVwaFDh+RwOFSvXj2P9nr16umnn36yqKqKrWPHjpo9e7aaNm2q3377TQ8//LAuueQSbdq0SdWqVbO6vApt3759kuT1eHOtg6crrrhC/fr1U1JSknbs2KH7779fqampWrFihUJDQ60uz1JOp1OjR4/WxRdfrJYtW0o6dYyFh4erevXqHn05xrzPlyT99a9/VaNGjRQfH68NGzZo/Pjx2rJliz744AMLq7XOxo0b1blzZ504cUJVq1bVvHnz1Lx5c61bt45jqxQRwhCU1NRU979btWqljh07qlGjRvrPf/6jYcOGWVgZzkTXX3+9+9/Jyclq1aqVzj33XC1ZskQ9evSwsDLrjRw5Ups2beKaTD/5mq9bb73V/e/k5GTVr19fPXr00I4dO3TuueeWd5mWa9q0qdatW6eMjAy99957Gjx4sJYuXWp1WWcc3o6UVLt2bYWGhhb6dMf+/fsVFxdnUVWVS/Xq1XX++edr+/btVpdS4bmOKY634J1zzjmqXbv2WX+8jRo1Sh9//LEWL16shg0butvj4uKUm5uro0ePevQ/248xX/PlTceOHSXprD3GwsPDdd5556lt27ZKS0tTSkqKnn76aY6tUkYI06mDrW3btlq0aJG7zel0atGiRercubOFlVUeWVlZ2rFjh+rXr291KRVeUlKS4uLiPI63zMxMffvttxxvfvrll1/0+++/n7XHmzFGo0aN0rx58/Tll18qKSnJY33btm1VpUoVj2Nsy5Yt2rNnz1l5jBU3X96sW7dOks7aY6wgp9OpnJwcjq1SxtuR+caMGaPBgwerXbt26tChg6ZPn67s7GwNHTrU6tIqpHvvvVd9+vRRo0aNtHfvXk2aNEmhoaG64YYbrC6tQsjKyvL4H/SuXbu0bt061axZU4mJiRo9erQeeeQRNWnSRElJSXrwwQcVHx+va665xrqiLVTUfNWsWVMPP/yw+vfvr7i4OO3YsUPjxo3Teeedp169ellYtXVGjhypuXPnav78+apWrZr7Why73a6oqCjZ7XYNGzZMY8aMUc2aNRUbG6s77rhDnTt3VqdOnSyuvvwVN187duzQ3LlzdeWVV6pWrVrasGGD7r77bnXt2lWtWrWyuPryN2HCBKWmpioxMVHHjh3T3LlztWTJEv3vf//j2CptVn88syJ59tlnTWJiogkPDzcdOnQwK1eutLqkCmvQoEGmfv36Jjw83DRo0MAMGjTIbN++3eqyKozFixcbSYVugwcPNsac+pqKBx980NSrV89ERESYHj16mC1btlhbtIWKmq/jx4+byy+/3NSpU8dUqVLFNGrUyAwfPtzs27fP6rIt422uJJlZs2a5+/zxxx/m//7v/0yNGjVMdHS0ufbaa81vv/1mXdEWKm6+9uzZY7p27Wpq1qxpIiIizHnnnWfGjh1rMjIyrC3cIrfccotp1KiRCQ8PN3Xq1DE9evQwX3zxhXs9x1bpsRljTHmGPgAAAHBNGAAAgCUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQVkJOTo4ceekg5OTlWl1IpMF+BYb4Cw3wFhvkKDPMVGOar9PE9YQVkZmbKbrcrIyNDsbGxVpdT4TFfgWG+AsN8BYb5CgzzFRjmq/RxJgwAAMAChDAAAAALnHV/wNvpdGrv3r2qVq2abDZbofWZmZke9yga8xUY5iswzFdgmK/AMF+BKcv5Msbo2LFjio+PV0jI2XN+6Ky7JuyXX35RQkKC1WUAAIAC0tPT1bBhQ6vLKDdn3ZmwatWqSZLuCpUivJwJK46jBJH1i9gOwQ+W9Hby+qDHXr8xJeixS+84GPTYS5+tE/RYSVp235Ggx3Z9rEbQY9/6Mi/osTdcVrKn1XNrcoMeO6pteNBjH9hyMuixjzStEvRYSeq7q3bQY+cnHQp6bLddjYIeuyTp56DHSlKHnc2CHrvqnJ+CHlvnp55Bjz3YbGHQYyXpyKo7gx5bo8MzQY89/MHzQY+t2W9E0GMlKXbi/4Iem/nPXkGPrd3rqaDHHvrf3UGPlaQqMYGHKIfzpNbv/a/7d/TZ4qwLYa63ICNstuBCWAn2HWor2XRXCwu83tLYd2xk8KeGS/qYY6NCLdl3SV4HSvqYq1YL/igryb6jY52W7FeSImODD3El2XdEbPChtaSPOdyifYfFRlqyX0kKqRZtyb5Dqla1ZL+SFBYV/KcIS/RzDrfuMYeGBP989naZ0Jns7HnjFQAAoAKptCFsxowZaty4sSIjI9WxY0etWrXK6pIAAAD8VilD2DvvvKMxY8Zo0qRJWrt2rVJSUtSrVy8dOHDA6tIAAAD8UilD2JNPPqnhw4dr6NChat68uV544QVFR0fr1VdfLdQ3JydHmZmZHjcAAACrVboQlpubqzVr1qhnzz8/4RMSEqKePXtqxYoVhfqnpaXJbre7b3w9BQAAqAgqXQg7dOiQHA6H6tWr59Fer1497du3r1D/CRMmKCMjw31LT08vr1IBAAB8OuO/oiIiIkIRERFWlwEAAOCh0p0Jq127tkJDQ7V//36P9v379ysuLs6iqgAAAAJT6UJYeHi42rZtq0WLFrnbnE6nFi1apM6dO1tYGQAAgP8q5duRY8aM0eDBg9WuXTt16NBB06dPV3Z2toYOHWp1aQAAAH6plCFs0KBBOnjwoCZOnKh9+/apdevW+vzzzwtdrA8AAFBR2YwxJfiT1JVPZmam7Ha7/nLgPlUJ4m+ovb3ui6D3ve3c4P8wsyQdiwj+RxUd/N9m1qc1Ggc99gLH3uB3LOnFk1cHPdYeGvx3wv2S2yDosXv2tg16rCQ1iFsX9NgjG68MemxO481Bj626pWSPOcQZ/JURVY8E/4c+Ix97IuixUYPGBz1WkvIWzgt6rHEG/4Q++v2MoMdWazIw6LGSlHtoU9BjI+M7Bj0286e5QY+NqNE86LGSdOLQ9yUaf7ZwmDxtPPKtMjIyFBsb/N/brGwq3TVhAAAAZwJCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAVsxhhjdRHlKTMzU3a7Xd0eOaKwyNiAxx9pnBP0vqseigx6rCRl1vsj6LHVf4kKemyVI7lBj3X+sDHosZIUUr1O0GNzNi8MemxobP2gxx5eMSXosSUVHd816LHH9y4Lemxk7QuDHitJJw59X6LxACo3h8nTxiPfKiMjQ7Gxgf9urqw4EwYAAGABQhgAAIAFCGEAAAAWIIQBAABYoNKFsLS0NLVv317VqlVT3bp1dc0112jLli1WlwUAABCQShfCli5dqpEjR2rlypVasGCBTp48qcsvv1zZ2dlWlwYAAOC3MKsLCNTnn3/usTx79mzVrVtXa9asUdeuwX88HwAAoDxVuhBWUEZGhiSpZs2aXtfn5OQoJ+fP7/bKzMwsl7oAAACKUunejjyd0+nU6NGjdfHFF6tly5Ze+6Slpclut7tvCQkJ5VwlAABAYZU6hI0cOVKbNm3S22+/7bPPhAkTlJGR4b6lp6eXY4UAAADeVdq3I0eNGqWPP/5Yy5YtU8OGDX32i4iIUERERDlWBgAAULxKF8KMMbrjjjs0b948LVmyRElJSVaXBAAAELBKF8JGjhypuXPnav78+apWrZr27dsnSbLb7YqKCv6PVAMAAJSnSndN2PPPP6+MjAx169ZN9evXd9/eeecdq0sDAADwW6U7E2aMsboEAACAEqt0Iay0/P7EFQq1le/DzyjXvXk6YuG+UX6O711myX5PHPrekv0CQGVW6d6OBAAAOBMQwgAAACxACAMAALAAIQwAAMAChDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMAChDAAAAALEMIAAAAsQAgDAACwQKUPYY899phsNptGjx5tdSkAAAB+q9Qh7LvvvtOLL76oVq1aWV0KAABAQCptCMvKytKNN96omTNnqkaNGj775eTkKDMz0+MGAABgtUobwkaOHKmrrrpKPXv2LLJfWlqa7Ha7+5aQkFBOFQIAAPhWKUPY22+/rbVr1yotLa3YvhMmTFBGRob7lp6eXg4VAgAAFC3M6gIClZ6errvuuksLFixQZGRksf0jIiIUERFRDpUBAAD4r9KFsDVr1ujAgQNq06aNu83hcGjZsmV67rnnlJOTo9DQUAsrBAAAKF6lC2E9evTQxo0bPdqGDh2qZs2aafz48QQwAABQKVS6EFatWjW1bNnSoy0mJka1atUq1A4AAFBRVcoL8wEAACq7SncmzJslS5ZYXQIAAEBAOBMGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABaolCHs119/1d/+9jfVqlVLUVFRSk5O1urVq60uCwAAwG9hVhcQqCNHjujiiy9W9+7d9dlnn6lOnTratm2batSoYXVpAAAAfqt0IWzq1KlKSEjQrFmz3G1JSUkWVgQAABC4Svd25H//+1+1a9dOAwYMUN26dXXhhRdq5syZPvvn5OQoMzPT4wYAAGC1ShfCdu7cqeeff15NmjTR//73P40YMUJ33nmnXnvtNa/909LSZLfb3beEhIRyrhgAAKAwmzHGWF1EIMLDw9WuXTstX77c3XbnnXfqu+++04oVKwr1z8nJUU5Ojns5MzNTCQkJSq7RUaG2SvduLAAAZxyHydPGI98qIyNDsbGxVpdTbirdmbD69eurefPmHm0XXHCB9uzZ47V/RESEYmNjPW4AAABWq3Qh7OKLL9aWLVs82rZu3apGjRpZVBEAAEDgKl0Iu/vuu7Vy5UpNmTJF27dv19y5c/XSSy9p5MiRVpcGAADgt0oXwtq3b6958+bprbfeUsuWLTV58mRNnz5dN954o9WlAQAA+K3SXZhfUpmZmbLb7VyYDwBABcGF+QAAACg3hDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMAChDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsECJQ9ixY8dKow6/ORwOPfjgg0pKSlJUVJTOPfdcTZ48WcaYcq0DAACgJMJKuoFLLrlEn3/+ueLi4kqjnmJNnTpVzz//vF577TW1aNFCq1ev1tChQ2W323XnnXeWSw0AAAAlVeIzYRdeeKE6duyon376yaN93bp1uvLKK0u6+UKWL1+uvn376qqrrlLjxo113XXX6fLLL9eqVau89s/JyVFmZqbHDQAAwGolDmGzZs3SkCFD1KVLF3399dfaunWrBg4cqLZt2yo0NLQ0avRw0UUXadGiRdq6daskaf369fr666+VmprqtX9aWprsdrv7lpCQUOo1AQAABKrEb0dK0sMPP6yIiAj95S9/kcPhUI8ePbRixQp16NChNDbv4b777lNmZqaaNWum0NBQORwOPfroo7rxxhu99p8wYYLGjBnjXs7MzCSIAQAAy5U4hO3fv19TpkzRzJkz1bx5c/30008aMmRImQQwSfrPf/6jN998U3PnzlWLFi20bt06jR49WvHx8Ro8eHCh/hEREYqIiCiTWgAAAIJV4hCWlJSkpk2b6t1339VVV12lzz//XIMGDdKePXs0duzY0qjRw9ixY3Xffffp+uuvlyQlJyfr559/VlpamtcQBgAAUBGVOIS9+uqr7kAkSVdccYUWL16s3r17a/fu3ZoxY0ZJd+Hh+PHjCgnxvJQtNDRUTqezVPcDAABQlkocwk4PYC5t2rTR8uXLfV4sXxJ9+vTRo48+qsTERLVo0ULff/+9nnzySd1yyy2lvi8AAICyYjNl+C2nR44cUY0aNUp1m8eOHdODDz6oefPm6cCBA4qPj9cNN9ygiRMnKjw8vNjxmZmZstvtSq7RUaG2UvlcAgAAKAGHydPGI98qIyNDsbGxVpdTbso0hFVEhDAAACqWszWE8bcjAQAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMAChDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMACFS6ELVu2TH369FF8fLxsNps+/PBDj/XGGE2cOFH169dXVFSUevbsqW3btllTLAAAQJAqXAjLzs5WSkqKZsyY4XX9tGnT9Mwzz+iFF17Qt99+q5iYGPXq1UsnTpwo50oBAACCF2Z1AQWlpqYqNTXV6zpjjKZPn64HHnhAffv2lSS9/vrrqlevnj788ENdf/315VkqAABA0CrcmbCi7Nq1S/v27VPPnj3dbXa7XR07dtSKFSu8jsnJyVFmZqbHDQAAwGqVKoTt27dPklSvXj2P9nr16rnXFZSWlia73e6+JSQklHmdAAAAxalUISwYEyZMUEZGhvuWnp5udUkAAACVK4TFxcVJkvbv3+/Rvn//fve6giIiIhQbG+txAwAAsFqlCmFJSUmKi4vTokWL3G2ZmZn69ttv1blzZwsrAwAACEyF+3RkVlaWtm/f7l7etWuX1q1bp5o1ayoxMVGjR4/WI488oiZNmigpKUkPPvig4uPjdc0111hXNAAAQIAqXAhbvXq1unfv7l4eM2aMJGnw4MGaPXu2xo0bp+zsbN166606evSounTpos8//1yRkZFWlQwAABAwmzHGWF1EecrMzJTdbldyjY4KtVW4DAoAwFnHYfK08ci3ysjIOKuu3a5U14QBAACcKQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFigwoWwZcuWqU+fPoqPj5fNZtOHH37oXnfy5EmNHz9eycnJiomJUXx8vG6++Wbt3bvXuoIBAACCUOFCWHZ2tlJSUjRjxoxC644fP661a9fqwQcf1Nq1a/XBBx9oy5Ytuvrqqy2oFAAAIHhhVhdQUGpqqlJTU72us9vtWrBggUfbc889pw4dOmjPnj1KTEwsjxIBAABKrMKFsEBlZGTIZrOpevXqXtfn5OQoJyfHvZyZmVlOlQEAAPhW4d6ODMSJEyc0fvx43XDDDYqNjfXaJy0tTXa73X1LSEgo5yoBAAAKq7Qh7OTJkxo4cKCMMXr++ed99pswYYIyMjLct/T09HKsEgAAwLtK+XakK4D9/PPP+vLLL32eBZOkiIgIRURElGN1AAAAxat0IcwVwLZt26bFixerVq1aVpcEAAAQsAoXwrKysrR9+3b38q5du7Ru3TrVrFlT9evX13XXXae1a9fq448/lsPh0L59+yRJNWvWVHh4uFVlAwAABMRmjDFWF3G6JUuWqHv37oXaBw8erIceekhJSUlexy1evFjdunUrdvuZmZmy2+1KrtFRobYKl0EBADjrOEyeNh75VhkZGUVeYnSmqXAppFu3bioqF1awzAgAABCUSvvpSAAAgMqMEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFqhwIWzZsmXq06eP4uPjZbPZ9OGHH/rse/vtt8tms2n69OnlVh8AAEBpqHAhLDs7WykpKZoxY0aR/ebNm6eVK1cqPj6+nCoDAAAoPWFWF1BQamqqUlNTi+zz66+/6o477tD//vc/XXXVVUX2zcnJUU5Ojns5MzOzVOoEAAAoiQp3Jqw4TqdTN910k8aOHasWLVoU2z8tLU12u919S0hIKIcqAQAAilbpQtjUqVMVFhamO++806/+EyZMUEZGhvuWnp5exhUCAAAUr8K9HVmUNWvW6Omnn9batWtls9n8GhMREaGIiIgyrgwAACAwlepM2FdffaUDBw4oMTFRYWFhCgsL088//6x77rlHjRs3tro8AAAAv1WqM2E33XSTevbs6dHWq1cv3XTTTRo6dKhFVQEAAASuwoWwrKwsbd++3b28a9curVu3TjVr1lRiYqJq1arl0b9KlSqKi4tT06ZNy7tUAACAoFW4ELZ69Wp1797dvTxmzBhJ0uDBgzV79myLqgIAAChdFS6EdevWTcYYv/vv3r277IoBAAAoI5XqwnwAAIAzBSEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMAChDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAtUqBC2bNky9enTR/Hx8bLZbPrwww8L9fnxxx919dVXy263KyYmRu3bt9eePXvKv1gAAIASqFAhLDs7WykpKZoxY4bX9Tt27FCXLl3UrFkzLVmyRBs2bNCDDz6oyMjIcq4UAACgZGzGGGN1Ed7YbDbNmzdP11xzjbvt+uuvV5UqVTRnzpygt5uZmSm73a7kGh0VagsrhUoBAEBJOEyeNh75VhkZGYqNjbW6nHJToc6EFcXpdOqTTz7R+eefr169eqlu3brq2LGj17csT5eTk6PMzEyPGwAAgNUqTQg7cOCAsrKy9Nhjj+mKK67QF198oWuvvVb9+vXT0qVLfY5LS0uT3W533xISEsqxagAAAO8qTQhzOp2SpL59++ruu+9W69atdd9996l379564YUXfI6bMGGCMjIy3Lf09PTyKhkAAMCnSnNRVO3atRUWFqbmzZt7tF9wwQX6+uuvfY6LiIhQREREWZcHAAAQkEpzJiw8PFzt27fXli1bPNq3bt2qRo0aWVQVAABAcCrUmbCsrCxt377dvbxr1y6tW7dONWvWVGJiosaOHatBgwapa9eu6t69uz7//HN99NFHWrJkiXVFAwAABKFCfUXFkiVL1L1790LtgwcP1uzZsyVJr776qtLS0vTLL7+oadOmevjhh9W3b1+/98FXVAAAULGcrV9RUaFCWHnIyMhQ9erV1bx6W0IYAAAVgMPk6Yeja3T06FHZ7Xaryyk3Z10KOXbsmCTph6NrLK4EAACc7tixY2dVCDvrzoQ5nU7t3btX1apVk81mK7Q+MzNTCQkJSk9PP6tOiQaL+QoM8xUY5iswzFdgmK/AlOV8GWN07NgxxcfHKySk0nxmsMTOujNhISEhatiwYbH9YmNjeVIGgPkKDPMVGOYrMMxXYJivwJTVfJ1NZ8Bczp64CQAAUIEQwgAAACxACCsgIiJCkyZN4lv2/cR8BYb5CgzzFRjmKzDMV2CYr9J31l2YDwAAUBFwJgwAAMAChDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIA1CpNGzYUP/+97892pYvX67o6Gj9/PPPFlUFAIEjhAGoVDp27KjvvvvOvWyM0ejRo3X33XerUaNGFlYGAIEhhAGoVDp16uQRwubMmaP09HRNmDDBwqoAIHCEMACVSqdOnfTjjz8qKytL2dnZuv/++/XII4+oatWqVpcGAAEJs7oAAAhE27ZtFRISorVr12rhwoWqU6eOhg4danVZABAwQhiASiU6OlrJycl6//33NXPmTH366acKCeGkPoDKh1cuAJVOp06d9Oyzz6pXr17q1q2b1eUAQFAIYQAqnZSUFFWpUkWPP/641aUAQNBsxhhjdREAEIju3burTZs2euKJJ6wuBQCCxjVhACoFp9OpgwcP6pVXXtG2bds0f/58q0sCgBIhhAGoFJYtW6bLLrtMzZo10/vvv6/Y2FirSwKAEuHtSAAAAAtwYT4AAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABQhhAAAAFiCEAQAAWIAQBgAAYAFCGAAAgAUIYQAAABYghAEAAFiAEAYAAGABQhgAAIAFCGEAAAAWIIQBAABYgBAGAABgAUIYAACABcKsLqA8nDhxQrm5uVaXAQAAAhAeHq7IyEiryygzZ3wIO3HihGpHRSnb6kIAAEBA4uLitGvXrjM2iJ3xISw3N1fZkkaFhijGZiRJIbZT68Ly70Ntp26n/m3cbZIUGiLP5YL3+etd7+u62kN8jXP1d/ezuf9dcN2fyzav7bYQz3bXPkNc7SE+2k/bt63gtgr0Ldj+5z5d6/P7h3r2t7knwua53nVvO+3f7vuQAssFt+m5Xj7Gq2ANoYWXC/Yt9IMqONmF2j2Xjc9l5S+fupfNJuPq41rn7uOjPf/eaSuw7KOfCTEe6/+8N+5tOAv2sXn2/XOfp/o5Cm6rYLsKrj917zhtu+5/u9fZPPedv+yrn0M2z375k+taduYvOwqsdyhEebbQ/D6n1uW514XmL4d6tDtdy8az3dXPPc6EeY4v0N9hwtxtjvyXW3cfE+LR7jCe23AYz/5OE+LR7nD3c613LYe4l50FxhrXsjM0fzm/rzPEY9l1ABj3DzTUo/3P5fz7/B+WLb/dZkLdB4O7zXHqPsTdnn+fv80QVz9Xu4/+IY4Qj/bC622nrcuvy+HaZv7rkbF5Lrv7yeuyzem6N57LDpP/+M2fy/n/liO/k9Pz3uZaLri+0PKpnRtnfhGue4ejQL+8U/0cDsmZl7/utLbTlv/sezL/vkB/58n8fp7rjTO3QPtJj3bjOCnjyC3Qllugb07+NnIKrM8pcJ+b//BOyGEc+mHfauXm5hLCKrsISRH5L86u34/eQ1jhdcHc+xvCQv0JYQXCk692v0PYacuFwpW/Icy9Pr+/jxBm8xXCQmz+hzAf632GsEKhq/C4gn39DmE++hUfwv5cH3QI83u5iBB22r891vkMZ36GMFdgKkEIcxQKYTbPdh8hzBFACHO4w1TRIczVHpofMkLlee/qH5IfiELcy6Eey3km7FQgkRSS/3LrWnbfF2iXe32Yx7LDvd6zXQW25152hp7WxzOEqUAIk7PAen9DmPu+QODyK4R5hq6CISzEZwjzbHeFsqJCWEjBEOYOWQGGMEcJQpijuBBWMFzlhzCHrxDmWvYSwlxtIZ4hSyGu9pMe93+GtvxlW/56173r52wLy2/PP37y59UoVCb/uWPyn39GBe9PzYsxBe+dXu/dx/8ZLsTqAgAAAM5GhDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMAChDAAAAALEMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAJhVhdQXnIkhRkj6c/k6Xrwofm3U/827jZJCjXyXC54n78+xNXPJo99uJbd9/ntIaf1C/Gxzr1sCrTnL9sKtIcYP++d+fchki2/UNd9SIH7gu3uZVuBZafnss3pKr7Aete9zciWPyl/3qvAcv59iPf18jFeIbYC/UyhcbbQgpNa4L7gZBdq91w2PpeVvyzXA5dx9XGtc/fx0Z5/77QVWPbRz+T/oJ0F+jlDjHsbzoJ9bJ59/9znqX6Ogtsq2K6C60/dO07brvvf7nU2z33nL/vq55DNs1/+5LqWnfnLjgLrHQpRXn69zvxt5LnXOfOXnR7tTteycbU78u9D88eFFljvWg713L5xuNscrm24+hhXDWH5fT234TBhHstOV3/j2d/hXu9aDnEvOwuMNa5lZ2j+cn5fZ4jHsusAMO4faKhH+5/L+ff5PyxbfrvNhLoPBnebw9XX1Z5/X2CbrnaT398U6G8cnrUVXm87bV3+sZE/xpZ/cIUYm+eyq/5TP6JCy+7XLafxXHbkvz642h3G/W858js5Pe9truWC6wstO/IfQ34RrnuHo0C/vPzH7ZCcefnrTms7bfnPvifz7wv0d57M7+e53jhzC7Sf9Gg3jpMyjtwCbble+8q13nnSx/2pfTpNnhwmv/4z2BkfwsLDwxUXF6fn9u2zuhQfTCn1AQDgzFK1alUZc+b+DrSZM/nR5Ttx4oQOHTqkhIQEpaenKzY2Vu3bt9d3333n7hPocnHtxa0LpE9J+hcnMzPTY14K7sOfeQh0bspiXoIdU5SCcxPMMRLIfPn7GKw+ZqSi56Ysjpni1vmzvrTGFIVjxrdAjhlvbWfLa3BlPWaCHVMU19xkZGS4fz+dac74M2GSFBkZ6f4BxsbGKjY2VqGhoR4/1ECXi2svbl0gfUrS31+ueSm4D3/mIdC5KYt5CXaMP4I9ZgJp82ddIH1K0j8Q3uamLI6Z4tb5s760xviDY8Y3f44Zb21ny2twZT1mgh1ztjtrL8wfOXJkiZaLay9uXSB9StI/GKfvw595CHRuymJegh1Tku0HOzccM2XzfOKY8b+O0u4fjKKOGW9tZ8trcGU9ZoIdc7Y7K96OlE6d1rTb7Wf0ac1gMC++MTe+MTfeMS++MTfeMS++nQ1zc9acCYuIiNCkSZMUERFhdSkVCvPiG3PjG3PjHfPiG3PjHfPi29kwN2fNmTAAAICK5Kw5EwYAAFCREMIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCJH388cdq2rSpmjRpopdfftnqciq0a6+9VjVq1NB1111ndSkVRnp6urp166bmzZurVatWevfdd60uqcI4evSo2rVrp9atW6tly5aaOXOm1SVVKMePH1ejRo107733Wl1KhdK4cWO1atVKrVu3Vvfu3a0up0LZtWuXunfvrubNmys5OVnZ2dlWl2S5LVu2qHXr1u5bVFSUPvzwQ6vL8stZ/xUVeXl5at68uRYvXiy73a62bdtq+fLlqlWrltWlVUhLlizRsWPH9Nprr+m9996zupwK4bffftP+/fvVunVr7du3T23bttXWrVsVExNjdWmWczgcysnJUXR0tLKzs9WyZUutXr2a51e+f/zjH9q+fbsSEhL0r3/9y+pyKozGjRtr06ZNqlq1qtWlVDiXXnqpHnnkEV1yySU6fPiwYmNjFRZ2VvwFQr9kZWWpcePG+vnnnyvFa/BZfyZs1apVatGihRo0aKCqVasqNTVVX3zxhdVlVVjdunVTtWrVrC6jQqlfv75at24tSYqLi1Pt2rV1+PBha4uqIEJDQxUdHS1JysnJkTFGZ/n/+9y2bdumn376SampqVaXgkpi8+bNqlKlii655BJJUs2aNQlgBfz3v/9Vjx49KkUAk86AELZs2TL16dNH8fHxstlsXk9BzpgxQ40bN1ZkZKQ6duyoVatWudft3btXDRo0cC83aNBAv/76a3mUXupKOhdnqvKclzVr1sjhcCghIaGEVZeP8pibo0ePKiUlRQ0bNtTYsWNVu3btUqq+7JTHvNx7771KS0srpYrLT3nMjc1m06WXXqr27dvrzTffLKXKy15Zz822bdtUtWpV9enTR23atNGUKVNKsfqyU56vwf/5z380aNCgElZcfip9CMvOzlZKSopmzJjhdf0777yjMWPGaNKkSVq7dq1SUlLUq1cvHThwoJwrLXulMReua3cK3vbu3VteD6PUlde8HD58WDfffLNeeumlMn9MpaU85qZ69epav369du3apblz52r//v3l8thKoqznZf78+Tr//PN1/vnnl9dDKjXlccx8/fXXWrNmjf773/9qypQp2rBhQ7k8tpIq67nJy8vTV199pX//+99asWKFFixYoAULFpTXwwtaeb0GZ2Zmavny5bryyivL/DGVGnMGkWTmzZvn0dahQwczcuRI97LD4TDx8fEmLS3NGGPMN998Y6655hr3+rvuusu8+eab5VJvWQpmLvy1ePFi079//9Ios9yV1bycOHHCXHLJJeb1118vrVLLXVkeMy4jRoww7777bknKLHdlMS/33XefadiwoWnUqJGpVauWiY2NNQ8//HBpll0uyuOYuffee82sWbNKUKU1ymJuli9fbi6//HL38rRp08y0adNKpd7yUpbHzOuvv25uvPHG0iiz3FT6M2FFyc3N1Zo1a9SzZ093W0hIiHr27KkVK1ZIkjp06KBNmzbp119/VVZWlj777DP16tXLqpLLjD9zcTYqjXkxxmjIkCG67LLLdNNNN5VVqeWuNOZm//79OnbsmCQpIyNDy5YtU9OmTcuk3vJSGvOSlpam9PR07d69W//61780fPhwTZw4saxKLjelMTfZ2dnuYyYrK0tffvmlWrRoUSb1lqfSmJv27dvrwIEDOnLkiJxOp5YtW6YLLrigrEouF6X5u6myvRUpSWf0FX2HDh2Sw+FQvXr1PNrr1aunn376SZIUFhamJ554Qt27d5fT6dS4cePOyE9u+TMX/ujZs6fWr1+v7OxsNWzYUO+++646d+5c2uWWm9KYl2+++UbvvPOOWrVq5b7WYc6cOUpOTi7tcstVaczNzz//rFtvvdV9Qf4dd9zBvJzBSmNu9u/fr2uvvVbSqU/XDh8+XO3bty/1WstbacxNWFiYpkyZoq5du8oYo8svv1y9e/cui3LLTWk9nzIyMrRq1Sq9//77pV1imTqjQ5i/rr76al199dVWl1EpLFy40OoSKpwuXbrI6XRaXUaF1KFDB61bt87qMiq0IUOGWF1ChXLOOedo/fr1VpdRYaWmpvKJWi/sdnuluN60oDP67cjatWsrNDS00A9m//79iouLs6gqazAX3jEvvjE33jEvvjE3vjE33p3t83JGh7Dw8HC1bdtWixYtcrc5nU4tWrSoUr+FFgzmwjvmxTfmxjvmxTfmxjfmxruzfV4q/duRWVlZ2r59u3t5165dWrdunWrWrKnExESNGTNGgwcPVrt27dShQwdNnz5d2dnZGjp0qIVVlw3mwjvmxTfmxjvmxTfmxjfmxjvmpQjWfjiz5BYvXmwkFboNHjzY3efZZ581iYmJJjw83HTo0MGsXLnSuoLLEHPhHfPiG3PjHfPiG3PjG3PjHfPi21n/tyMBAACscEZfEwYAAFBREcIAAAAsQAgDAACwACEMAADAAoQwAAAACxDCAAAALEAIAwAAsAAhDAAAwAKEMAAAAAsQwgAAACxACAMAALAAIQwAAMAC/w90vKtv0P//1QAAAABJRU5ErkJggg==", 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", 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Kh+co5eXl4fvvv8fRo0dRu3btYs/H69evIyQkpMRxPHH27FlcvHhR1flgJdm7dy80Go2y3T59+sBsNiM1NRUWiwUHDx4s9vFn/fr1ERgYiODgYAQHByvnTN3cXqdOHTz99NPKZVRcfR5dv34da9assTsfDLhxnl1ubq7difr79+8HAKeve54+F9QSJZxbGB8fj3nz5mHJkiVo1KhRsUtwOJtbbzt48CA6duzote0tWLAAsbGxCAoKQlRUFJKSkir8NSfLktrXJTWvgwUFBfjhhx/wwAMPFNvncnJyoNFoYDAYANw4NzQwMFD5MpAa7777Llq3bg1fX1/V11JUfU5Yu3btlG9HliQgIEDtEHZs56g88sgjSEpKctinZcuWypNeNmffrizv/I4fP46srKxi579cuHABAJCcnOzytn7//XcIIVw6D6yoCRMm4B//+IfT9V999RU++ugjJCUlFTsXyPZNvaLnfZlMJmzatAmPP/64w202adLE5c//bz4p3Mabc+cOmfvOkiVLcODAAUybNg1JSUnYvXt3sRez48eP49q1a5g5cyY6dOjgcDveOG/KGU/OBwNunLdaUFCArKwsu2Jx3759aNCggVJwd+jQATVr1sS3336LiIgI5ObmOnxcP/30k/KlI0ftR44cQZcuXdCkSROMGTPG5efR5s2bYTabcc8999i1HzhwAIB9wWWbE2dFmKfPBbWuXLmCwMBAh+8DBw8exOTJk5GQkIAxY8Y4nA9nc+sNBQUF8PFR9xboLPall17C/Pnz8dFHH+Huu++GxWLBp59+ip9//tnp6xQ5puZ1cPfu3cjKykKrVq2KrduzZw/i4uKUb0QfOHDA44M1derUwYwZM7Bs2TLV2/DaifmuqFWrFgIDAx3+T+uPP/6AVqtFZGSk09iQkBBYLJYSL0VgtVphMBiUF6qSuPqNPk/ydkdZjGMrGGwncNukpKQ4bC+JrRhS803I2NhYpxdyXbFiBT7++GMMHToUCxcuLHaSru2NMjs72679448/Rn5+PsaMGeNwu+Hh4U6/DOAKb8xdWfxNnc2/N8bq0qULunTpgvPnz+PFF1/E8ePHcdttt9n1sX0TtWnTplIuC2I76uOoCLt8+TJq164Ns9mMwMBAADe+2fqf//wHGzduBHCjIAFu/E/45m3s27cPd911l7Ks1WqRmJiIb7/9Vik21RR+DRs2ROfOnXHw4EEArj+Pvv/+ezRr1qzYSfYHDhyAVqtF06ZNlbb9+/crRyUd8fS5oFZ6erpdnjf76aefkJubi48++sjtC00fPHgQTzzxBPbv34/bbrsNb731lvK302g0yMjIUC6q261bN/zf//0fHnnkEWg0Grz99tt4/fXXUa9ePWzatAn169fHJ598gk6dOuHkyZMYM2YMtm3bhtq1a+ONN95QXrccxd7s6tWrmDVrFpYtW2ZXOBf9Rve3336LOXPmICsrC8888wymTJmirCtpfODGa+Wrr76K/Px8PPPMM5g4cSJmzZqFw4cP2104t2vXrhg9ejQefPBBjBs3DsuWLUNBQQEaNmyIH3/8UXntUpPLSy+9hGPHjtkV9QkJCRgxYoTDy8WU1/snAOVXY4r+h/3s2bPYvHkzXnjhBaXNG0VY//79Ady4jIxa5fqVFJ1Oh549e2LVqlV2h2czMzOxbNkydOrUSTlU6Ch24MCB+Prrrx0WWLY3TK1Wi/79++Pbb79VriV0s5uraNsfqrQrj3uStzvKYhyj0QgAdnO2bNkypKamAgByc3Nd3pbtzeCbb75xK4fSLF26VLlkgaNvSbVs2RJardbu52tOnTqFmTNn4rHHHvPaJQOK8sbclcXf1Nl+682xbB8FOHpu1K9fHxqNBl9//XWxdQUFBaV+bOqpffv2QafToVmzZsXWhYaGIjIyUjkyVFBQgGnTpmHWrFlKH9tHTze/Ppw7dw7nz58vdqSrT58+OH78OD777DMA6o7wHTp0CJs2bVL+d+7q8+iHH34o9lEkcGN/tP1sl80ff/wh/TpijuzevVu5ll9RZrMZANx+A87Pz0ffvn0xaNAgXLhwAZMmTULfvn1d3u/WrFmDvXv34qeffrJrt1qt6Nu3L3r16oXMzEwsXLgQjz76qN0vwTiLBYCtW7ciPz8fffr0KXH8n3/+Gfv378eGDRvw4osvKlcWcGX87777DgcOHMCGDRswd+5crFu3DkOHDsWqVauU16NTp07h119/Rb9+/fDTTz9hy5YtOH78OC5duoT333/f7tp4anIZMmQIVq1ahevXrwO48dzZsWMH+vXr5/Dxltf7J/D3EWHbf7iAG68BY8aMgdFoVH4yDXBchPXp0wfVqlVzeHvllVe8kmMx7p5EZjtp3dE3D29mO7nuwoULdu0HDhwQQUFBom7duuLll18Ws2fPFg0aNBB6vV5s27bN4Vi2E5DPnTsnoqOjRWBgoHj66afF+++/L1JSUsSgQYNE9erVlbhTp06J8PBwERgYKMaNGyfef/99MWPGDNG8eXNx5coVpd+OHTsEAHHPPfeIJUuWiM8++0xkZ2c7/Hakq3k7e9yOtumIq+O4emK+xWIRMTExws/PT0ybNk3MmDFD+Pv7i8GDBwsAYtiwYWLfvn12MQBE165dHW6vV69eAoC4//77xbvvvit+/PFHkZeXV2IOR44cEWaz2en63NzcUr+xMmDAAOHr6yumTZsmXn/9dREZGSni4uJKPUnTE2rmzhFv7zvO9lt3xipNac/zhx9+WAAQ9957r3jnnXfEm2++KZ588klRt25dsWnTJpfHUSMuLk40btzY6foHHnhA/Oc//xFCCLFgwQKHV7hv0aKF3Te3V69eLQCIb775xq7f1atXha+vr9BoNCIiIqLYdqKjo0VwcLAwGo3CaDSK8ePHF2uPiYkRzz33nLBYLEpcac+j48ePCwBiw4YNxcZs0qSJuO++++zaIiIiRKdOnexe38rC22+/LWbOnCnGjBkjAIgBAwaImTNnipkzZ4qrV6/a9bV9gWXt2rUOt2Xb351xNre2L47crEOHDmLZsmVCiOInnHft2lUsXbpUWVf0JPzo6GixadMmsXXrVtGwYUO7dQMHDlS+fOAo9mZLly4VYWFhTtfbtpGWlqYst23bVqxYsUIIIVwaf/369cq6f/3rX2LkyJFCCCE6d+6sfCP5tddeU/bttWvXikaNGont27cXO1Hdk1zuuOMO8d133wkhbuwT999/f4mP253XJU/eQ7t06SKaNWsm9Hq9mDx5spg3b57o0KGD0Ol0ymOziY2NFb/88kuJebtq9OjRYvr06apiy70IE0KI3bt3i169eong4GARGBgoEhISHO7cjiY9MzNTJCcni8jISOHr6yvCw8NF9+7dxQcffGAX++eff4rHHntM1KpVS+j1etGgQQORnJxcrGCYOXOmqFu3rtBqtcpYzv7YruTtaRHm6jjufDvy119/FR06dBB6vV5Ur15d/Otf/xJWq1U8/vjjwsfHRyxevFjpm5WVJQCIBx980OG2srKyxLPPPituu+024efnJwB4/WdcHLl8+bIYMGCACAoKEmFhYeLJJ58ssbDzFnfmriTe3ncc7bfujFWaJUuWCABOC6rc3Fwxa9Ys0axZMxEQECBq1Kgh2rZtK6ZPn16m33K7fv268PPzs7t0RFGvvPKKGDlypMjNzRVRUVFi165dxfrMnTtXBAcHK5d+mDNnjgAgjh49WqxvQkKCACB69+5dbJ3tDdzVdpvSnkfvvPOOMBqNxf5zkpeXJ3x8fMTzzz9v1z5ixAih1+vFgAEDnI7pDdHR0U4vE1P0tW3y5MkiKirK6bctJ02aJHQ6XYljOZrDzz//XHTq1MmubciQIeK1114TQpRehJ08edLhOF988YXw8fFRij6j0SiCgoLErFmzHMZ+8sknIigoSAQFBYnRo0eLH374Qeh0uhL/Q1lSbq6Mf/P++d5774k+ffoIIYR4//33xQMPPCCEuPEt3pt/bmzu3LkiLi5OhIWFiWeeeUb5tq8nucyePVs8+uijQgghOnXqJD7//HOnj9nG1dclT95Dq1evLl544QXxwQcfiMjISKHX60XHjh3FunXr7Ppdv35d6PV6r/0nvlyLsPL04YcfltvXaOmG77//Xmg0GpeO8AghxHPPPScAiMuXL5dxZlSe1q1bJwCIUaNGiRMnTki7fIAaa9euFW3atBFvvPGGGDhwoMM+V69eFaGhoXbXLVNDbRFWVNHnUWJiYomFZkWXm5srwsPDxbx584qtu3Tpkti3b59o2bKliIqKcroNZ3Po6EhYx44dlSNhgYGB4vDhw8q6Jk2a2BVhRd9PbONs3ry5xMuGlPZedOXKFeHv7y9Wrlzp8jZuLnxcGd/ZkbDLly+LatWqibS0NFGjRg2l0LrZyZMnRYsWLeyOrKnNJT09XRiNRnHs2DERHBysHImXyXaZFtt+UJKDBw+KyMjIYu29e/dWCuuit5dfftnp9jwpwir0ZYrPnj0LjUaD0NBQ2alUGevXr8eDDz7o8tf/a9WqhYCAALvzU6jy69y5M+666y588MEHqF+/frHLB1Rk8fHxOHjwIGbPnm13pfmbGY1GTJo0Ca+++qryzWuZij6PunXrhvHjx0vOSr1FixbB19cXTzzxRLF1rVu3RsuWLXHw4EHlJ7jcYbu6+jvvvIOCggIsX74cv//+u3ICe1xcHD7//HNYLBYsWbIER48edXm7VqsV7777LvLz85Gfn49Nmzbh5MmTLsVXq1YN//rXv/DPf/4Tq1evRl5eHq5du4aFCxc6/Gk9NePPnj0bZrMZhw4dwsKFCzF48GAANy7fkJCQgKSkJAwaNEj5Obe0tDTs3LkTBQUFCAkJga+vr0u/i1xaLvXr10fTpk0xcuRI3HPPPWX6iyWusn1hx5VzI52dlP/jjz8iOzvb4e35558v1r+goAC5ubmwWCx2/3aLqtKtjJ07d0688847om7duuLOO++UnQ458dZbb4mQkBDlqud06zly5IjYsGGD0yvnV1S33Xab8nFJWfLGkbCq9jz65ZdfxJYtW0o9el7SHO7du1fceeedwmAwiDvuuEOkpqYq67Zt2yYaN24sDAaDeOqpp0SXLl1cOhImhBAnTpwQ/fr1EzVr1hQ1atQQvXr1Uj7+chTryPvvvy9atGghAgICRL169cRjjz0mTpw44XAbNx99cmX8t956S0RGRoratWuLlJQUu3G//vprAcBuLtauXStatGghgoKCRO3atcXYsWOVX3zwJBch/v7Fg6+++qrUOSkPKSkpQqfTidzc3FL7Tp061e5ix2rZPjq9+VbaBYyL0ghRQS6sdRPbjwK3a9cOCxYsKPE35Eietm3bIj4+HnPnzuWRMKowsrOz0bBhQ/zyyy9o0KCB7HRKxecReUNaWhoGDhyIEydOqLqMUGU3dOhQpKWlefViw+WhQhZhRERqjR8/HhaLBW+99ZbsVIjKhcViweOPP46YmBjVV24nOSr0OWFERK7as2cPjEYj9u3bZ3ddMKJb2eXLl2E0GvHbb79h3LhxstMhN/FIGBEREZEEPBJGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREErAIIyIiIpKARRgRERGRBCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswm4yf/581K9fH/7+/mjfvj127NghO6UKa8aMGdBoNHa3Jk2ayE6rwkhNTUXfvn0REREBjUaDlStX2q0XQmDatGmoU6cOAgIC0KNHDxw5ckROshVAafM1bNiwYvtb79695SQrWUpKCtq2bYuQkBDUrl0b/fv3x6FDh+z65ObmIjk5GTVq1EBwcDAGDhyIzMxMSRnL58qcdevWrdg+9sQTT0jKWK53330XLVu2hMFggMFgQMeOHfHjjz8q67l/eQ+LsEJffPEFJkyYgOnTp2P37t2Ii4tDr169cP78edmpVVjNmzfH2bNnldvmzZtlp1Rh5OTkIC4uDvPnz3e4fs6cOXjrrbfw3nvvYfv27QgKCkKvXr2Qm5tbzplWDKXNFwD07t3bbn/77LPPyjHDimPjxo1ITk7Gtm3bsGbNGly/fh09e/ZETk6O0mf8+PH49ttvsXz5cmzcuBFnzpzBgAEDJGYtlytzBgAjR46028fmzJkjKWO56tWrh1deeQW7du1CWloa7r77bvTr1w8HDx4EwP3LqwQJIYRo166dSE5OVpYtFouIiIgQKSkpErOquKZPny7i4uJkp1EpABArVqxQlq1WqwgPDxevvvqq0nb16lWh1+vFZ599JiHDiqXofAkhRFJSkujXr5+UfCq68+fPCwBi48aNQogb+5Kvr69Yvny50uf3338XAMTWrVtlpVmhFJ0zIYTo2rWrePrpp+UlVcFVr15dfPjhh9y/vIxHwgDk5+dj165d6NGjh9Km1WrRo0cPbN26VWJmFduRI0cQERGBBg0aYOjQoTh58qTslCqF9PR0nDt3zm5/MxqNaN++Pfe3EmzYsAG1a9dG48aNMWbMGFy6dEl2ShWCyWQCAISGhgIAdu3ahevXr9vtX02aNEFUVBT3r0JF58zm008/Rc2aNdGiRQtMmTIF165dk5FehWKxWPD5558jJycHHTt25P7lZT6yE6gILl68CIvFgrCwMLv2sLAw/PHHH5Kyqtjat2+PxYsXo3Hjxjh79ixefPFFdO7cGQcOHEBISIjs9Cq0c+fOAYDD/c22juz17t0bAwYMQExMDI4dO4bnn38eiYmJ2Lp1K3Q6nez0pLFarRg3bhzuuusutGjRAsCN/cvPzw/VqlWz68v96wZHcwYADz/8MKKjoxEREYF9+/Zh8uTJOHToEL755huJ2cqzf/9+dOzYEbm5uQgODsaKFSvQrFkz7Nmzh/uXF7EII1USExOVf7ds2RLt27dHdHQ0vvzyS4wYMUJiZnQrevDBB5V/x8bGomXLlrjtttuwYcMGdO/eXWJmciUnJ+PAgQM8H9MNzuZs1KhRyr9jY2NRp04ddO/eHceOHcNtt91W3mlK17hxY+zZswcmkwlfffUVkpKSsHHjRtlp3XL4cSSAmjVrQqfTFft2R2ZmJsLDwyVlVblUq1YNjRo1wtGjR2WnUuHZ9inub+o1aNAANWvWrNL729ixY/Hdd99h/fr1qFevntIeHh6O/Px8XL161a4/9y/nc+ZI+/btAaDK7mN+fn64/fbbER8fj5SUFMTFxeHNN9/k/uVlLMJwY2eLj4/HunXrlDar1Yp169ahY8eOEjOrPLKzs3Hs2DHUqVNHdioVXkxMDMLDw+32N7PZjO3bt3N/c9GpU6dw6dKlKrm/CSEwduxYrFixAj///DNiYmLs1sfHx8PX19du/zp06BBOnjxZZfev0ubMkT179gBAldzHHLFarcjLy+P+5WX8OLLQhAkTkJSUhDZt2qBdu3aYN28ecnJyMHz4cNmpVUjPPvss+vbti+joaJw5cwbTp0+HTqfDQw89JDu1CiE7O9vuf9Dp6enYs2cPQkNDERUVhXHjxuGll15Cw4YNERMTg6lTpyIiIgL9+/eXl7REJc1XaGgoXnzxRQwcOBDh4eE4duwYJk2ahNtvvx29evWSmLUcycnJWLZsGVatWoWQkBDlPByj0YiAgAAYjUaMGDECEyZMQGhoKAwGA5588kl07NgRHTp0kJy9HKXN2bFjx7Bs2TLcc889qFGjBvbt24fx48ejS5cuaNmypeTsy9+UKVOQmJiIqKgoZGVlYdmyZdiwYQP+97//cf/yNtlfz6xI3n77bREVFSX8/PxEu3btxLZt22SnVGENGTJE1KlTR/j5+Ym6deuKIUOGiKNHj8pOq8JYv369AFDslpSUJIS4cZmKqVOnirCwMKHX60X37t3FoUOH5CYtUUnzde3aNdGzZ09Rq1Yt4evrK6Kjo8XIkSPFuXPnZKcthaN5AiAWLVqk9Pnrr7/EP//5T1G9enURGBgo7r//fnH27Fl5SUtW2pydPHlSdOnSRYSGhgq9Xi9uv/12MXHiRGEymeQmLsnjjz8uoqOjhZ+fn6hVq5bo3r27+Omnn5T13L+8RyOEEOVZ9BERERERzwkjIiIikoJFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIqyIvLw8zJgxA3l5ebJTqRQ4X+7hfLmH8+Uezpd7OF/u4Xx5H68TVoTZbIbRaITJZILBYJCdToXH+XIP58s9nC/3cL7cw/lyD+fL+3gkjIiIiEgCFmFEREREElS5H/C2Wq04c+YMQkJCoNFoiq03m81291Qyzpd7OF/u4Xy5h/PlHs6Xe8pyvoQQyMrKQkREBLTaqnN8qMqdE3bq1ClERkbKToOIiIiKyMjIQL169WSnUW6q3JGwkJAQAMDTOkDv4EhYaSwelKw/GdqpDwbwVfx+1bEP7IpVHZv6zCXVsV1er6E6FgBSZ19TP/bkQNWxr+xX/+2f52L1qmMB4PlDBapjZzVW/5QenG5UHftljEl1LAA0PtpGdeyh29NUx9Y93EV17OlGqapjASDw4H2qY681/6/qWNPOZNWxxrbzVccCwPkfXlMdW/ueZ1XH6t5cpTrW8nQ/1bEAUOvxr1XHXlg4UHWssflw1bGmg4tUx6plEQX47eou5T26qqhyRZjtI0i9RqOuCPNgbJ3Gs+kO8XU/X2+MbfDXSRkXAAwBcsYOMqgvhDx9zIEG9ZW+J2P7G3yljAsAvgb1hasnY8saFwB8DP5SxtaGqP/PiaePWRscLGVsXaAH3+Tz9O+sVz+2J4/ZxydAyriecnSa0K2s6nzwSkRERFSBVNoibP78+ahfvz78/f3Rvn177NixQ3ZKRERERC6rlEXYF198gQkTJmD69OnYvXs34uLi0KtXL5w/f152akREREQuqZRF2Ny5czFy5EgMHz4czZo1w3vvvYfAwEAsXLiwWN+8vDyYzWa7GxEREZFsla4Iy8/Px65du9CjRw+lTavVokePHti6dWux/ikpKTAajcqNl6cgIiKiiqDSFWEXL16ExWJBWFiYXXtYWBjOnTtXrP+UKVNgMpmUW0ZGRnmlSkREROTULX+JCr1eD73es+s2EREREXlbpTsSVrNmTeh0OmRmZtq1Z2ZmIjw8XFJWRERERO6pdEWYn58f4uPjsW7dOqXNarVi3bp16Nixo8TMiIiIiFxXKT+OnDBhApKSktCmTRu0a9cO8+bNQ05ODoYPV/8zDURERETlqVIWYUOGDMGFCxcwbdo0nDt3Dq1atcLq1auLnaxPREREVFFphBAe/CR15WM2m2E0GvFzeisEG9z/XUKfbntVj12/ufrfTQMAjVbOb2ppxjdVHRv43zMejX30iVqqYxscUv9/jMwoq+rYywZPfmEUqJat/iyBrZHqH3PEX+p/tHxnsGfnYxZ4cGbEcWtd1bFbs9qqjr1W4Nnz+dq16qpjqx2+Q3XslZjfVcdq8tT/7iQA6PLV/16m719BqmNDLoeqjg3IVp8zABj/VP/7t5pr+apjC9LWq4711OWts9yOsYgC7L+yHSaTCQaDB7/1WclUunPCiIiIiG4FLMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCH9kJyBK7xweGIPcfvu/4ZqrHtNTyVx0LALrT11THFkQHqY7Nu646FEefqKU+GEBAnkZ17KrO6seNzipQHfu+oaP6gQEc/Pl11bHjIhNUx34U0El1bA/rbtWxALAwr6/q2I4Bv6qODfbNlhILACbdX6pjL9/mqzpWo7Wqjg05FaE6FgA0Fp3q2NonaqqODTir/vmsuZanOhYAcjd8ojpWZ1A/31d2vKo6lsoPj4QRERERScAijIiIiEgCFmFEREREErAIIyIiIpKg0hVhKSkpaNu2LUJCQlC7dm30798fhw4dkp0WERERkVsqXRG2ceNGJCcnY9u2bVizZg2uX7+Onj17IicnR3ZqRERERC6rdJeoWL16td3y4sWLUbt2bezatQtdunSRlBURERGReypdEVaUyWQCAISGhjpcn5eXh7y8v6/zYjabyyUvIiIiopJUuo8jb2a1WjFu3DjcddddaNGihcM+KSkpMBqNyi0yMrKcsyQiIiIqrlIXYcnJyThw4AA+//xzp32mTJkCk8mk3DIyMsoxQyIiIiLHKu3HkWPHjsV3332H1NRU1KtXz2k/vV4PvV5fjpkRERERla7SFWFCCDz55JNYsWIFNmzYgJiYGNkpEREREbmt0hVhycnJWLZsGVatWoWQkBCcO3cOAGA0GhEQECA5OyIiIiLXVLpzwt59912YTCZ069YNderUUW5ffPGF7NSIiIiIXFbpjoQJIWSnQEREROQxjahiVY3ZbIbRaMQnF+IRaHC/Bo02W1SPrS/QqI4FgD9qqD9wGZqnPu96V9SPe7SWZ7uXxYMpO+lnVB2bgVqqY+sjU3UsAGy3NlMdu+nqnapjfbX5qmM9FaD7S3XsmVNt1Q+staoOjdnZWv24AEJ2nlcde7mz4+siuqJ6uvr/e18P8ezDE59r6l8PNLkF6mOvq3/9Q7aHv8biwa+5iKzLqmMLzh9THWvJuaA6FgCuXznqdkyBJQ87D8+HyWSCwWDwaPzKpNJ9HElERER0K2ARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREEvjITkCWDyx94GPxdzvukdAfVY+5xtpGdSwAnMkPVx3bOShNdey6FctUx/Z6ZIjqWE/5wKI6dl3OXapjq/tcUR0LAGdyI1THZmeHqY71D1Cfd97521THAkDorljVsX5NT6iOjToQozr2L2Oe6lgAyN21UnVsaNDDHgycqzr06uyB6scFENrxedWxFvNZ1bF/ndqkOjYw+m7VsQBgzc9RHVtgzlAdq9H5qY7NyVirOhYA9NWbuR1jteZ7NGZlxSNhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkqNRF2CuvvAKNRoNx48bJToWIiIjILZW2CNu5cyfef/99tGzZUnYqRERERG6rlEVYdnY2hg4digULFqB69eol9s3Ly4PZbLa7EREREclWKYuw5ORk3HvvvejRo0epfVNSUmA0GpVbZGRkOWRIREREVLJKV4R9/vnn2L17N1JSUlzqP2XKFJhMJuWWkaH+4ndERERE3lKprpifkZGBp59+GmvWrIG/v2tXu9fr9dDr9WWcGREREZF7KlURtmvXLpw/fx6tW7dW2iwWC1JTU/HOO+8gLy8POp1OYoZERERErqlURVj37t2xf/9+u7bhw4ejSZMmmDx5MgswIiIiqjQqVREWEhKCFi1a2LUFBQWhRo0axdqJiIiIKrJKd2I+ERER0a1AI4QQspMoT2azGUajES1OvgmdIcDt+JyCYNVjh64dqDoWALKrZ6uOvVwvXXVs4/o/q45Nz2qoOhYAhJDz/4SgA3eqjs1pscWjsets7K06Nmjxj6pjLQPvUx2b3uqo6lgAaLDrdtWxZxteUB1b+7klqmN9H3tGdSwA+J6/pj44S/1rgbh8XnWsJtCgOhYAzn85VHVsjQTXvhHvyKX1U1TH+te8Q3UsAORe/NWj+KrCIgqw/8p2mEwmGAye7WeVCY+EEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREErAIIyIiIpKARRgRERGRBCzCiIiIiCTwkZ2ALDWXPAYff4PbcZcSDqse0+JjUR0LAHUOVlMdeyVCpzo2b+V41bGNfz6uOhYAjozwUx0bmOX+39cm/I/qqmN91ieojgWAY70vqI41JvRRHWuunqs6tkav4apjAUA/fKXq2OhNp1XHmi4eUB2bPb2z6lhPhXZ8XnVs9m9fqo4NiR2qOtZTeemb5Ix75Tcp41LVwCNhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkqJRF2OnTp/HII4+gRo0aCAgIQGxsLNLS0mSnRUREROSySvftyCtXruCuu+5CQkICfvzxR9SqVQtHjhxB9erqv81GREREVN4qXRE2e/ZsREZGYtGiRUpbTEyMxIyIiIiI3FfpPo7873//izZt2mDQoEGoXbs27rjjDixYsMBp/7y8PJjNZrsbERERkWyVrgg7fvw43n33XTRs2BD/+9//MGbMGDz11FP4+OOPHfZPSUmB0WhUbpGRkeWcMREREVFxla4Is1qtaN26NWbNmoU77rgDo0aNwsiRI/Hee+857D9lyhSYTCbllpGRUc4ZExERERVX6YqwOnXqoFmzZnZtTZs2xcmTJx321+v1MBgMdjciIiIi2SpdEXbXXXfh0KFDdm2HDx9GdHS0pIyIiIiI3FfpirDx48dj27ZtmDVrFo4ePYply5bhgw8+QHJysuzUiIiIiFxW6Yqwtm3bYsWKFfjss8/QokULzJw5E/PmzcPQoUNlp0ZERETkskp3nTAA6NOnD/r06SM7DSIiIiLVNEIIITuJ8mQ2m2E0GpEw/RJ8/N0/SV9zWf11xs5/dJ/qWACodZ/z66GVRlwzqY7VRjdSHYuQIPWxAHDhsurQ/KbhqmP9LuarjhW+OtWxAHDh1W6qY2v2eE11rLBcVx2r0fmqjgWAi2ufVR0bENZedaw1P0t1bN6V31THAkBgRBfVsX9lblcdKyx5qmOJyopFFGD/le0wmUxV6gt0le7jSCIiIqJbAYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSQCOEELKTKE9msxlGoxHx0Q9Bp/VzOz7fdFT12DV7zlMdCwAa/yDVsZdWP6s61ppvUh3rqVr3LVAda7mQrjr28tZZqmNDOz6vOhYANL4BqmMvpU71aGy1guvf41F8QfZZ1bG5F3/1aGwiks8iCrD/ynaYTCYYDAbZ6ZQbHgkjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCSBx0VYVlaWN/JwmcViwdSpUxETE4OAgADcdtttmDlzJqrY9wuIiIiokvPxdAOdO3fG6tWrER4e7o18SjV79my8++67+Pjjj9G8eXOkpaVh+PDhMBqNeOqpp8olByIiIiJPeXwk7I477kD79u3xxx9/2LXv2bMH99zj2dfWHdmyZQv69euHe++9F/Xr18cDDzyAnj17YseOHQ775+XlwWw2292IiIiIZPO4CFu0aBGGDRuGTp06YfPmzTh8+DAGDx6M+Ph46HQ6b+Ro584778S6detw+PBhAMDevXuxefNmJCYmOuyfkpICo9Go3CIjI72eExEREZG7PP44EgBefPFF6PV6/OMf/4DFYkH37t2xdetWtGvXzhubt/Pcc8/BbDajSZMm0Ol0sFgsePnllzF06FCH/adMmYIJEyYoy2azmYUYERERSedxEZaZmYlZs2ZhwYIFaNasGf744w8MGzasTAowAPjyyy/x6aefYtmyZWjevDn27NmDcePGISIiAklJScX66/V66PX6MsmFiIiISC2Pi7CYmBg0btwYy5cvx7333ovVq1djyJAhOHnyJCZOnOiNHO1MnDgRzz33HB588EEAQGxsLP7880+kpKQ4LMKIiIiIKiKPi7CFCxcqBREA9O7dG+vXr0efPn1w4sQJzJ8/39Mh7Fy7dg1arf2pbDqdDlar1avjEBEREZUlj4uwmwswm9atW2PLli1OT5b3RN++ffHyyy8jKioKzZs3x6+//oq5c+fi8ccf9/pYRERERGXFKyfmO1K/fn1s2bLF69t9++23MXXqVPzzn//E+fPnERERgdGjR2PatGleH4uIiIiorGhEFbvUvNlshtFoRGz19tBpyqwGdci/5h0exede/FV1rG+w+m+EanTqv9iQbzqqOlYmrZ9Rdaw13+TFTNzjZ7xddez17AzVscKSpzqWiMgiCrD/ynaYTCYYDAbZ6ZQb/nYkERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREErAIIyIiIpKARRgRERGRBCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJwCKMiIiISAIf2QlUJbkXf5U29vXsDGljV0bWfJPsFFTJNx2VnQIREbmIR8KIiIiIJGARRkRERCQBizAiIiIiCViEEREREUlQoYqw1NRU9O3bFxEREdBoNFi5cqXdeiEEpk2bhjp16iAgIAA9evTAkSNH5CRLRERE5IEKVYTl5OQgLi4O8+fPd7h+zpw5eOutt/Dee+9h+/btCAoKQq9evZCbm1vOmRIRERF5pkJdoiIxMRGJiYkO1wkhMG/ePLzwwgvo168fAGDJkiUICwvDypUr8eCDD5ZnqkREREQeqVBHwkqSnp6Oc+fOoUePHkqb0WhE+/btsXXrVqdxeXl5MJvNdjciIiIi2SpNEXbu3DkAQFhYmF17WFiYss6RlJQUGI1G5RYZGVmmeRIRERG5otIUYWpNmTIFJpNJuWVk8MrxREREJF+lKcLCw8MBAJmZmXbtmZmZyjpH9Ho9DAaD3Y2IiIhItkpThMXExCA8PBzr1q1T2sxmM7Zv346OHTtKzIyIiIjIfRXq25HZ2dk4evTvHyBOT0/Hnj17EBoaiqioKIwbNw4vvfQSGjZsiJiYGEydOhURERHo37+/vKSJiIiIVKhQRVhaWhoSEhKU5QkTJgAAkpKSsHjxYkyaNAk5OTkYNWoUrl69ik6dOmH16tXw9/eXlTIRERGRKhohhJCdRHkym80wGo2Ird4eOk2FqkGJiIiqJIsowP4r22EymarUuduV5pwwIiIiolsJizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREErAIIyIiIpKARRgRERGRBCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJUKGKsNTUVPTt2xcRERHQaDRYuXKlsu769euYPHkyYmNjERQUhIiICDz22GM4c+aMvISJiIiIVKpQRVhOTg7i4uIwf/78YuuuXbuG3bt3Y+rUqdi9eze++eYbHDp0CPfdd5+ETImIiIg84yM7gZslJiYiMTHR4Tqj0Yg1a9bYtb3zzjto164dTp48iaioqPJIkYiIiMgrKlQR5i6TyQSNRoNq1ao57ZOXl4e8vDxl2Ww2l0NmRERERCWrUB9HuiM3NxeTJ0/GQw89BIPB4LRfSkoKjEajcouMjCzHLImIiIgcq5RF2PXr1zF48GAIIfDuu++W2HfKlCkwmUzKLSMjo5yyJCIiInKu0n0caSvA/vzzT/z8888lHgUDAL1eD71eX07ZEREREbmmUhVhtgLsyJEjWL9+PWrUqCE7JSIiIiJVKlQRlp2djaNHjyrL6enp2LNnD0JDQ1GnTh088MAD2L17N7777jtYLBacO3cOABAaGgo/Pz9ZaRMRERG5TSOEELKTsNmwYQMSEhKKtSclJWHGjBmIiYlxGLd+/Xp069bNpTHMZjOMRiNiq7eHTlOhalAiIqIqySIKsP/KdphMplJPM7qVVKgqpFu3biipJqxA9SIRERGRRyrltyOJiIiIKjsWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREErAIIyIiIpKARRgRERGRBBWqCEtNTUXfvn0REREBjUaDlStXOu37xBNPQKPRYN68eeWWHxEREZG3VKgiLCcnB3FxcZg/f36J/VasWIFt27YhIiKinDIjIiIi8i4f2QncLDExEYmJiSX2OX36NJ588kn873//w7333lvqNvPy8pCXl6csm81mj/MkIiIi8lSFOhJWGqvVikcffRQTJ05E8+bNXYpJSUmB0WhUbpGRkWWcJREREVHpKlURNnv2bPj4+OCpp55yOWbKlCkwmUzKLSMjowwzJCIiInJNhfo4siS7du3Cm2++id27d0Oj0bgcp9frodfryzAzIiIiIvdVmiNhmzZtwvnz5xEVFQUfHx/4+Pjgzz//xDPPPIP69evLTo+IiIjILZXmSNijjz6KHj162LX16tULjz76KIYPHy4pKyIiIiJ1KlQRlp2djaNHjyrL6enp2LNnD0JDQxEVFYUaNWrY9ff19UV4eDgaN25c3qkSEREReaRCFWFpaWlISEhQlidMmAAASEpKwuLFiyVlRUREROR9FaoI69atG4QQLvc/ceJE2SVDREREVIYqzYn5RERERLcSFmFEREREErAIIyIiIpKARRgRERGRBCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSoEIVYampqejbty8iIiKg0WiwcuXKYn1+//133HfffTAajQgKCkLbtm1x8uTJ8k+WiIiIyAMVqgjLyclBXFwc5s+f73D9sWPH0KlTJzRp0gQbNmzAvn37MHXqVPj7+5dzpkRERESe0QghhOwkHNFoNFixYgX69++vtD344IPw9fXF0qVLVW/XbDbDaDQitnp76DQ+XsiUiIiIPGERBdh/ZTtMJhMMBoPsdMpNhToSVhKr1Yrvv/8ejRo1Qq9evVC7dm20b9/e4UeWN8vLy4PZbLa7EREREclWaYqw8+fPIzs7G6+88gp69+6Nn376Cffffz8GDBiAjRs3Oo1LSUmB0WhUbpGRkeWYNREREZFjlaYIs1qtAIB+/fph/PjxaNWqFZ577jn06dMH7733ntO4KVOmwGQyKbeMjIzySpmIiIjIqUpzUlTNmjXh4+ODZs2a2bU3bdoUmzdvdhqn1+uh1+vLOj0iIiIit1SaI2F+fn5o27YtDh06ZNd++PBhREdHS8qKiIiISJ0KdSQsOzsbR48eVZbT09OxZ88ehIaGIioqChMnTsSQIUPQpUsXJCQkYPXq1fj222+xYcMGeUkTERERqVChLlGxYcMGJCQkFGtPSkrC4sWLAQALFy5ESkoKTp06hcaNG+PFF19Ev379XB6Dl6ggIiKqWKrqJSoqVBFWHkwmE6pVq4Zm1eJZhBEREVUAFlGA367uwtWrV2E0GmWnU26qXBWSlZUFAPjt6i7JmRAREdHNsrKyqlQRVuWOhFmtVpw5cwYhISHQaDTF1pvNZkRGRiIjI6NKHRJVi/PlHs6Xezhf7uF8uYfz5Z6ynC8hBLKyshAREQGtttJ8Z9BjVe5ImFarRb169UrtZzAY+KR0A+fLPZwv93C+3MP5cg/nyz1lNV9V6QiYTdUpN4mIiIgqEBZhRERERBKwCCtCr9dj+vTpvMq+izhf7uF8uYfz5R7Ol3s4X+7hfHlflTsxn4iIiKgi4JEwIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkSVSr169fCf//zHrm3Lli0IDAzEn3/+KSkrIiL3sQgjokqlffv22Llzp7IshMC4ceMwfvx4REdHS8yMiMg9LMKIqFLp0KGDXRG2dOlSZGRkYMqUKRKzIiJyH4swIqpUOnTogN9//x3Z2dnIycnB888/j5deegnBwcGyUyMicouP7ASIiNwRHx8PrVaL3bt3Y+3atahVqxaGDx8uOy0iIrexCCOiSiUwMBCxsbH4+uuvsWDBAvzwww/QanlQn4gqH75yEVGl06FDB7z99tvo1asXunXrJjsdIiJVWIQRUaUTFxcHX19fvPrqq7JTISJSTSOEELKTICJyR0JCAlq3bo3XX39ddipERKrxnDAiqhSsVisuXLiAjz76CEeOHMGqVatkp0RE5BEWYURUKaSmpuLuu+9GkyZN8PXXX8NgMMhOiYjII/w4koiIiEgCnphPREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREErAIIyIiIpKARRgRERGRBCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJWIQRERERScAijIiIiEgCFmFEREREEvjITqA85ObmIj8/X3YaRERE5AY/Pz/4+/vLTqPM3PJFWG5uLmoGBCBHdiJERETklvDwcKSnp9+yhdgtX4Tl5+cjB8BYnRZBGgEA0GoAH82N9bpi98J+Weusn/162+e6tnatszjtjfFv9NEo+dhtq9iy436aIvG2MZXtaou3Fx1bU3Rb2qLr7dv/HtM+Xquz769RJkKjrLe1FYb+vazcax23ax2vh5N4FM3hprHhpG+xP1TRyS7Wbr8snC4DQgfc/MCFrU/hppV7nZP2wnurpsiyk35CK5T1VqWvsNuG9aY+9u1Fx7zRz1JkzGLtKLoesBTZprKssS1r7McuXHbWzwKNfb/CZ51t2Vq4bNFolHW2+wKNrrDPjb4Fynpd4bLOrt1qWxb27bZ+SpzwsY8Xur+3bVsnbDH2ywVCa9duEfZjFo23CvvtWpR+tvU6WAr7WG9quzlW2JatusLlwv5Wrd2ybQcQyh9UZ9f+93LhvVUDTWGbRmkrfL7a2i037rVKe+F94Ta1tn62dif9tRatXbvWqr1pnabIusLnu8W2zcL1QmO/rPSDw2WN1XYv7JctArC1WUTh4y68txR2strfa2zLRdcXW74xuLAWJmG7t1j+7mcpuNFHaSuwuy/WrvS/XnhfpL/1emE/+/XCml+k/brS9ve28u36Ksu29da8wm3kFVmfV+Q+v/Dh5cIiLPjtXBry8/NZhFV2egD6whdrXYlF2I370taXdu9KEaZztQhz1k9NEeakj9tFWJEizlkRpnFUhBXtU1oR5mS90yKsSDt0WudFmNM/oJMizEm/kouwIuvUFmEuL5dQhDlbdlqcuViE2QomD4owS7EiTGPf7qQIs7hRhCnLpRRhtnZdYUGhg/29rb+2sCDSKss65d+2As1WlGhhv6zcF2mHst7HbtmirLdvx83bs/27aJFUpAhDkSIM1iLrXS3ClHutiiLMvugqWoRpnRZh9u1aS+lFmLZoEaYUWW4WYRYPijBLaUWYxeHy34VU0SLM4rwIs7Vr7YssaG3t1+3u/y7aCpc1hett97a/s8ansF0HUTinonB/F4XPHWH7zyaK3t+YFyGK3lsd3iv7/y1OKzsBIiIioqqIRRgRERGRBCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCViEEREREUnAIoyIiIhIAhZhRERERBKwCCMiIiKSgEUYERERkQQswoiIiIgkYBFGREREJAGLMCIiIiIJfGQnUF7yAPgIAeBG5Wl74Lpi98J+WTjrZ79ea+ungTLGzcvKPQBtkT7am9Y5XBZF2guXNUXataL0e6218N+Fg2uK3Gu1jtcXW9YUWbYW2Z7Vlvzf621tmsLENYWT8vc9HLdrHa+Hk3hoNUX6CQcxRSe1yH3RyS7Wbr8snC4DwpaXpnCdrU/h3Cj3OifthfdWTZFlJ/1E4R/cqv27j9XWpimyXGTbRbdpLfxbWYqMWawdRdcDliLbVJY1tmWN/diFy876WaCx71e4c9mWrYXLFo1GWWe7LyjM11q4jQJlvbVw2WrXbrUtC1u7pfBeVxinK7Letqz7e9vCorTdiLFfLhC2HHwK++vs+wsfu2Wrrb+w729R1utgKexjvant5lhhW7bqCpcL+1u1dsu2HUAof1CdXfvfy4X3Vg00hW0ape1GX6XdUrS98L7INm3torC/KNJfWOxzE1btTes0RdYV7huFMZrC9VqhsV+22pbhcFl57bIK+2WLAGxtlsLXisJlWAo7We3vNbblouuLLVsKH0NhErZ7i+XvfpaCwsdtayuwuy/WrvS/XnhfpL/1emE/+/XCml+k/brS9ve28u36Ksu29bZt2NZbrzu5vzGmVRQoz6Fb2S1fhPn5+SE8PBzvnDsnOxUHhJf7ERER3TqCg4MhxK37HqgRt/KjK5Sbm4uLFy8iMjISGRkZMBgMaNu2LXbu3Kn0cXe5tPbS1rnTx5P+pTGbzR7Niztt7jwGNY+zos1NVdlnio6hdp9R0+5uH2/ElORWeT55e16AkuemLPaZ0ta5st5bMSXhPuOcbW5MJpPyWnOrueWPhAGAv7+/8gc0GAwwGAzQ6XR2f1R3l0trL22dO3086e8qtfPiTpsr69zp440YV3Cfccw2L0XHULvPqGl3t483YlxR2Z9PZTUvgOO5KYt9prR1rqz3VowruM9UTVX2xPzk5GSPlktrL22dO3086e8uNfPgapsr69zp440YT7bPfcbxGGr3GTXt7vbxRown268sz6dbYZ8pbZ0r670V48n2uc/c2qrEx5HAjcOaRqPxlj6sqQbnxTnOjWOcF+c4N85xbhzjvDhXFeamyhwJ0+v1mD59OvR6vexUKhTOi3OcG8c4L85xbpzj3DjGeXGuKsxNlTkSRkRERFSRVJkjYUREREQVCYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgD8N1336Fx48Zo2LAhPvzwQ9npVGj3338/qlevjgceeEB2KhVGRkYGunXrhmbNmqFly5ZYvny57JQqjKtXr6JNmzZo1aoVWrRogQULFshOqUK5du0aoqOj8eyzz8pOpUKpX78+WrZsiVatWiEhIUF2OhVGeno6EhIS0KxZM8TGxiInJ0d2ShXCoUOH0KpVK+UWEBCAlStXyk7LJVX+EhUFBQVo1qwZ1q9fD6PRiPj4eGzZsgU1atSQnVqFtGHDBmRlZeHjjz/GV199JTudCuHs2bPIzMxEq1atcO7cOcTHx+Pw4cMICgqSnZp0FosFeXl5CAwMRE5ODlq0aIG0tDQ+vwr961//wtGjRxEZGYnXXntNdjoVRv369XHgwAEEBwfLTqVC6dq1K1566SV07twZly9fhsFggI9Plfj1QZdlZ2ejfv36+PPPPyvFa3CVPxK2Y8cONG/eHHXr1kVwcDASExPx008/yU6rwurWrRtCQkJkp1Gh1KlTB61atQIAhIeHo2bNmrh8+bLcpCoInU6HwMBAAEBeXh6EEKji/+9THDlyBH/88QcSExNlp0KVwMGDB+Hr64vOnTsDAEJDQ1mAOfDf//4X3bt3rxQFGHALFGGpqano27cvIiIioNFoHB6CnD9/PurXrw9/f3+0b98eO3bsUNadOXMGdevWVZbr1q2L06dPl0fqXufpXNyqynNedu3aBYvFgsjISA+zLh/lMTdXr15FXFwc6tWrh4kTJ6JmzZpeyr7slMe8PPvss0hJSfFSxuWnPOZGo9Gga9euaNu2LT799FMvZV62ynpejhw5guDgYPTt2xetW7fGrFmzvJh92SrP1+Avv/wSQ4YM8TDj8lPpi7CcnBzExcVh/vz5Dtd/8cUXmDBhAqZPn47du3cjLi4OvXr1wvnz58s507LnjbmwnbtT9HbmzJnyehheV17zcvnyZTz22GP44IMPyvwxeUt5zE21atWwd+9epKenY9myZcjMzCyXx+aJsp6XVatWoVGjRmjUqFF5PSSvKY99ZvPmzdi1axf++9//YtasWdi3b1+5PDZPlPW8FBQUYNOmTfjPf/6DrVu3Ys2aNVizZk15PTyPlNdrsNlsxpYtW3DPPfeU+WPyGnELASBWrFhh19auXTuRnJysLFssFhERESFSUlKEEEL88ssvon///sr6p59+Wnz66aflkm9ZUjMXrlq/fr0YOHCgN9Isd2U1L7m5uaJz585iyZIl3kq13JXlPmMzZswYsXz5ck/SLHdlMS/PPfecqFevnoiOjhY1atQQBoNBvPjii95Mu1yUxz7z7LPPikWLFnmQZfkri3nZsmWL6Nmzp7I8Z84cMWfOHK/kW57Kcp9ZsmSJGDp0qDfSLDeV/khYSfLz87Fr1y706NFDadNqtejRowe2bt0KAGjXrh0OHDiA06dPIzs7Gz/++CN69eolK+Uy48pcVEXemBchBIYNG4a7774bjz76aFmlWu68MTeZmZnIysoCAJhMJqSmpqJx48Zlkm958ca8pKSkICMjAydOnMBrr72GkSNHYtq0aWWVcrnxxtzk5OQo+0x2djZ+/vlnNG/evEzyLS/emJe2bdvi/PnzuHLlCqxWK1JTU9G0adOySrncePO9qbJ9FAkAt/RZfRcvXoTFYkFYWJhde1hYGP744w8AgI+PD15//XUkJCTAarVi0qRJt+Q3t1yZC1f06NEDe/fuRU5ODurVq4fly5ejY8eO3k633HhjXn755Rd88cUXaNmypXKuw9KlSxEbG+vtdMuVN+bmzz//xKhRo5QT8p988knOyy3MG3OTmZmJ+++/H8CNb9eOHDkSbdu29Xqu5ckb8+Lj44NZs2ahS5cuEEKgZ8+e6NOnT1mkW6689XwymUzYsWMHvv76a2+nWKZu6SLMVffddx/uu+8+2WlUCmvXrpWdQoXTqVMnWK1W2WlUSO3atcOePXtkp1GhDRs2THYKFUqDBg2wd+9e2WlUSImJifw2rRNGo7FSnG9a1C39cWTNmjWh0+mK/WEyMzMRHh4uKSs5OBeOcV6c49w4xnlxjnPjGOfFuao+N7d0Eebn54f4+HisW7dOabNarVi3bl2l/ghNDc6FY5wX5zg3jnFenOPcOMZ5ca6qz02l/zgyOzsbR48eVZbT09OxZ88ehIaGIioqChMmTEBSUhLatGmDdu3aYd68ecjJycHw4cMlZl02OBeOcV6c49w4xnlxjnPjGOfFOc5NCeR+OdNz69evFwCK3ZKSkpQ+b7/9toiKihJ+fn6iXbt2Ytu2bfISLkOcC8c4L85xbhzjvDjHuXGM8+Ic58a5Kv/bkUREREQy3NLnhBERERFVVCzCiIiIiCRgEUZEREQkAYswIiIiIglYhBERERFJwCKMiIiISAIWYUREREQSsAgjIiIikoBFGBEREZEELMKIiIiIJGARRkRERCQBizAiIiIiCf4fmgazJWL2ZTUAAAAASUVORK5CYII=", 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", 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", 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" ] @@ -204,7 +183,7 @@ ], "source": [ "eq = get(\"precise_QH\")\n", - "rho = np.linspace(0.01, 1, 3)\n", + "rho = np.linspace(0.01, 1, 2)\n", "angle = Bounce2D.angle(eq, X=32, Y=32, rho=rho)\n", "for l in range(rho.size):\n", " fig = Bounce2D.plot_angle_spectrum(angle, l)" @@ -215,7 +194,7 @@ "id": "2287362f-1570-4e71-9cfb-7068c76feb19", "metadata": {}, "source": [ - "- Flux surface averaged bounce integrals seem to be well-conditioned to discretization error in this map. If the spectrum is green at the high frequency edges, then ``X`` and ``Y`` are large enough." + "- If you need higher resolution, you should make sure the maximum error allowed by the Newton solve with the ``tol`` argument to ``.angle()`` is consistent." ] }, { @@ -226,13 +205,13 @@ "## Plotting ripple wells\n", "\n", "- Here we plot $\\vert B\\vert$ along field lines to see the structure of the ripple wells. This is beneficial to choose the resolution for the optimization.\n", - "- Due to limitations in JAX, it is recommended to plot the field lines and pick a reasonable, yet preferably tight, upper bound on the number of ripple wells. From the plots, we see that ``num_well=W * num_transit`` with ``W=10`` is a reasonable upper bound. By making this extra effort, the optimization will be ``Y_B/W`` times more performant. If one were to select something much less than ``10``, as shown in the next example, then it should be clear from the plot that some ripple wells are ignored, which is not desirable.\n", + "- Due to limitations in JAX, it is recommended to plot the field lines and pick a reasonable, yet preferably tight, upper bound on the number of ripple wells. From the plots, we see that ``num_well=W * num_field_periods`` with ``W=3`` is a reasonable upper bound. By making this extra effort, the optimization will be more performant. If one were to select something much smaller, as shown in the next example, then it should be clear from the plot that some ripple wells are ignored, which is not desirable.\n", "- Making a good choice for ``num_well`` is important for performance in optimization." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "6eb81b56-6b1b-45ba-903e-741c21047c7e", "metadata": {}, "outputs": [], @@ -241,14 +220,18 @@ " eq,\n", " grid,\n", " angle,\n", + " *,\n", " Y_B=None,\n", - " num_transit=3,\n", - " num_well=None,\n", + " spline=True,\n", " num_pitch=10,\n", - " **kwargs,\n", + " alpha=None,\n", + " field_period_transits=3,\n", + " num_well=None,\n", "):\n", " \"\"\"Plotting tool to help user set tighter upper bound on ``num_well``.\n", "\n", + " Also prints error statistics for the bounce points.\n", + "\n", " Parameters\n", " ----------\n", " eq : Equilibrium\n", @@ -263,20 +246,36 @@ " Angle returned by ``Bounce2D.angle``.\n", " Y_B : int\n", " Desired resolution for algorithm to compute bounce points.\n", + " A reference value is ``(grid.num_theta+grid.num_zeta)//2``.\n", + "\n", " If the option ``spline`` is ``True``, the bounce points are found with\n", - " 8th order accuracy in this parameter. If the option ``spline`` is ``False``,\n", - " then the bounce points are found with spectral accuracy in this parameter.\n", - " A reference value for the ``spline`` option is 100.\n", + " 𝒪(Y_B⁻¹²) error. In this case, the final error will be of order\n", + " 𝒪(Y_B⁻¹⁸) in bounce integrals with (v_∥)¹ and\n", + " 𝒪(Y_B⁻⁶) in bounce integrals with (v_∥)⁻¹.\n", "\n", - " An error of ε in a bounce point manifests\n", - " 𝒪(ε¹ᐧ⁵) error in bounce integrals with (v_∥)¹ and\n", - " 𝒪(ε⁰ᐧ⁵) error in bounce integrals with (v_∥)⁻¹.\n", - " num_transit : int\n", - " Number of toroidal transits to follow field line.\n", - " In an axisymmetric device, field line integration over a single poloidal\n", - " transit is sufficient to capture a surface average. For a 3D\n", - " configuration, more transits will approximate surface averages on an\n", - " irrational magnetic surface better, with diminishing returns.\n", + " If the option ``spline`` is ``False``, the bounce points are found such\n", + " that the bounce integrals have exponential accuracy in this parameter.\n", + " spline : bool\n", + " Whether to use cubic splines to compute initial guess for bounce points\n", + " instead of Chebyshev series. Default is ``True``. It can be preferable\n", + " to set to ``False`` on equilibria with high ``NFP``, (such cases make\n", + " smaller ``Y_B`` feasible), or on GPUs where eigenvalue solves are fast.\n", + " num_pitch: int\n", + " Number of pitch angles.\n", + " alpha : jnp.ndarray\n", + " Shape (num α, ).\n", + " Starting field line poloidal labels.\n", + " Default is single field line.\n", + " On irrational magnetic surfaces, it is sufficient to integrate along a\n", + " single field line. On a rational or near-rational surface in\n", + " non-axisymmetric configurations, it is necessary to integrate along\n", + " multiple field lines until the surface is covered sufficiently.\n", + " field_period_transits : int\n", + " Number of field periods to follow field line.\n", + " In axisymmetric configurations, integration along the field line for a\n", + " single poloidal transit between two global maxima of B is sufficient for\n", + " convergence. For a 3D configuration, the magnetic surface should be covered\n", + " sufficiently.\n", " num_well : int\n", " Maximum number of wells to detect for each pitch and field line.\n", " Giving ``-1`` will detect all wells but due to current limitations in\n", @@ -289,8 +288,6 @@ " A tighter upper bound than ``num_well=(Aι+C)*num_transit`` is preferable.\n", " The ``check_points`` or ``plot`` methods in ``desc.integrals.Bounce2D``\n", " are useful to select a reasonable value.\n", - " num_pitch: int\n", - " Number of pitch angles.\n", "\n", " Returns\n", " -------\n", @@ -299,8 +296,17 @@ "\n", " \"\"\"\n", " data = eq.compute(Bounce2D.required_names + [\"min_tz |B|\", \"max_tz |B|\"], grid=grid)\n", - " bounce = Bounce2D(grid, data, angle, Y_B, num_transit=num_transit, **kwargs)\n", - " pitch_inv, _ = Bounce2D.get_pitch_inv_quad(\n", + " bounce = Bounce2D(\n", + " grid=grid,\n", + " data=data,\n", + " angle=angle,\n", + " Y_B=Y_B,\n", + " spline=spline,\n", + " alpha=alpha,\n", + " field_period_transits=field_period_transits,\n", + " quad=(np.zeros(0), np.zeros(0)),\n", + " )\n", + " pitch_inv, _ = Bounce2D.pitch_quad(\n", " grid.compress(data[\"min_tz |B|\"]),\n", " grid.compress(data[\"max_tz |B|\"]),\n", " num_pitch,\n", @@ -315,30 +321,28 @@ "id": "a65d955f", "metadata": {}, "source": [ - "We plot the magnetic field norm over 3 toroidal transits (12 field periods) to educate our guess for the ``num_well`` parameter." + "We plot the magnetic field norm over 12 field periods to educate our guess for the ``num_well`` parameter." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "728efd05-7f52-4ece-af52-c031c6f61441", "metadata": { "scrolled": true }, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "Error statistics for the given bounce points:\n", + "After 1 iteration(s) | ζ₁₂(w) error mean = 1e-08 | std. dev. = 3e-08 | max = 3e-07\n" + ] }, { "data": { - "image/png": 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", + "image/png": 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", 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", 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", 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" ] @@ -360,16 +364,14 @@ "source": [ "grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False)\n", "angle = Bounce2D.angle(eq, X=16, Y=16, rho=rho)\n", - "num_transit = 3\n", - "Y_B = 32\n", + "field_period_transits = 12\n", "\n", "plot_wells(\n", " eq,\n", " grid,\n", " angle,\n", - " Y_B,\n", - " num_transit,\n", - " num_well=10 * num_transit,\n", + " field_period_transits=field_period_transits,\n", + " num_well=3 * field_period_transits,\n", ");" ] }, @@ -385,25 +387,23 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "92403ae4-d958-49ad-9e2c-911822473409", "metadata": { "scrolled": true }, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "Error statistics for the given bounce points:\n", + "After 1 iteration(s) | ζ₁₂(w) error mean = 2e-08 | std. dev. = 3e-08 | max = 3e-07\n" + ] }, { "data": { - "image/png": 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", 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", 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", 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", 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" ] @@ -427,9 +427,8 @@ " eq,\n", " grid,\n", " angle,\n", - " Y_B,\n", - " num_transit,\n", - " num_well=1 * num_transit,\n", + " field_period_transits=field_period_transits,\n", + " num_well=field_period_transits // 3,\n", ");" ] }, @@ -446,21 +445,20 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "066b90da-9212-4834-bb81-0488d69a5c3d", "metadata": {}, "outputs": [], "source": [ "rho = np.linspace(0.01, 1, 10)\n", "grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False)\n", - "num_transit = 10\n", + "field_period_transits = 32\n", "data = eq.compute(\n", " \"effective ripple\",\n", " grid,\n", " angle=Bounce2D.angle(eq, X=16, Y=16, rho=rho),\n", - " Y_B=Y_B,\n", - " num_transit=num_transit,\n", - " num_well=15 * num_transit,\n", + " field_period_transits=field_period_transits,\n", + " num_well=3 * field_period_transits,\n", " num_quad=16,\n", " num_pitch=15,\n", ")\n", @@ -475,7 +473,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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", 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" + } + ], + "source": [ + "rho = np.linspace(0.01, 1, 2)\n", + "eq0 = get(\"HELIOTRON\")\n", + "angle = Bounce2D.angle(eq0, X=40, Y=20, rho=rho)\n", + "for l in range(rho.size):\n", + " fig = Bounce2D.plot_angle_spectrum(angle, l)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b876cb44-9052-4dcf-af2d-29196d91722f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Error statistics for the given bounce points:\n", + "After 1 iteration(s) | ζ₁₂(w) error mean = 5e-11 | std. dev. = 7e-11 | max = 7e-10\n" + ] }, { "data": { - "image/png": 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3b1/179/f57Z3714lJCT4PX9oxYoVqlGjRlC3on1K5TN2lbXvlLavos4991z17t1b+fn5euedd/yeo5SXl6cPP/xQW7duVf369Ys9H48dO6aaNWuetJ+y2LNnj/bv31+q88FOZv369XI4HN71Dho0SJmZmVqxYoVcLpc2bdpU7OPPpk2bKioqSjExMYqJifGeM3Vie4MGDXTbbbd5f0Yl2OfRsWPH9Nlnn/mcDyYdP88uNzfX50T9H374QZICvu6V9blQWuYk5xZ27txZs2fP1sKFC9WyZctiP8ERaGzL26ZNm9SjR49yW99zzz2ndu3aKTo6Wo0bN9bw4cOr/G9OVqTSvi6V5nWwoKBAH330kf785z8X2+dycnLkcDgUGxsr6fi5oVFRUd4vA1mVl5enm266SY0bN1ZsbKy6d++uVatWWV5Pqc8J69q1q/fbkSdTo0aN0nbhw3OOyl/+8hcNHz7cb0z79u29T3q7Bfp2ZWXnt337dmVlZRU7/2Xfvn2SpDFjxgS9rp9++knGmKDOAytq/Pjx+tOf/hRw/ltvvaUXXnhBw4cPL3YukOebekXP+zpy5Ii++OIL3XTTTX7X2bp166A//z/xpHCP8hw7K+zcdxYuXKiNGzdq0qRJGj58uNauXVvsxWz79u06evSopk6dqu7du/tdT3mcNxVIWc4Hk46ft1pQUKCsrCyfYnHDhg1q3ry5t+Du3r276tatq/fff19JSUnKzc31u12ffvqp90tH/tq3bNmi3r17q3Xr1ho9enTQz6Mvv/xSmZmZuvjii33aN27cKMm34PKMSaAirKzPhdI6dOiQoqKi/L4PbNq0SRMnTlS/fv00evRov+MRaGzLQ0FBgUJDS/cWGGjZBx98UHPnztULL7ygCy64QC6XSy+//LI+//zzgK9T8K80r4Nr165VVlaWOnbsWGzeunXr1KFDB+83ojdu3FimgzUFBQVq2rSpvvzySzVq1EhvvPGGBg8erB07dvj9pz2QcjsxPxj16tVTVFSU3/+0fv75ZzmdTiUnJwdctmbNmnK5XCf9KQK3263Y2FjvC9XJBPuNvrLkbUVF9OMpGDwncHtMnz7db/vJeIqh0nwTsl27dgF/yPWdd97Riy++qOuuu07z5s0rdpKu540yOzvbp/3FF19Ufn6+Ro8e7Xe9iYmJAb8MEIzyGLuKeEwDjX959NW7d2/17t1be/fu1f3336/t27frjDPO8InxfBP1rLPOsuVnQTxHffwVYQcPHlT9+vWVmZmpqKgoSce/2frkk09q+fLlko4XJNLx/4RPXMeGDRt0/vnne6edTqdSUlL0/vvve4vN0hR+LVq0UK9evbRp0yZJwT+PPvzwQ7Vp06bYSfYbN26U0+nUWWed5W374YcfvEcl/Snrc6G0UlNTffI80aeffqrc3Fy98MILln9oetOmTfrb3/6mH374QWeccYYef/xx72PncDiUlpbm/VHdvn376q9//av+8pe/yOFwaM6cOXr00UfVqFEjffHFF2ratKleeukl9ezZUzt37tTo0aP19ddfq379+nrssce8r1v+lj3R4cOHNW3aNL3yyis+hXPRb3S///77mjlzprKysnTHHXfonnvu8c47Wf/S8dfKhx9+WPn5+brjjjt01113adq0afrll198fji3T58+uuWWW3T11Vdr3LhxeuWVV1RQUKAWLVro448/9r52lSaXBx98UNu2bfMp6vv166eRI0f6/bmYynr/lOS9akzRf9j37NmjL7/8Uvfee6+3raxFWHR0tCZNmuSdvvrqqzV+/Hht3rzZ+8PLwajUr6SEhITooosu0nvvvedzeDYjI0OvvPKKevbs6T1U6G/ZIUOG6O233/ZbYHneMJ1Opy6//HK9//773t8SOtGJVbTngSrpl8fLkrcVFdFPXFycJPmM2SuvvKIVK1ZIknJzc4Nel+fN4D//+Y+lHEqyaNEi708W+PuWVPv27eV0On0uX7Nr1y5NnTpVN9xwQ7n9ZEBR5TF2FfGYBtpvy7Mvz0cB/p4bTZs2lcPh0Ntvv11sXkFBQYkfm5bVhg0bFBISojZt2hSbFx8fr+TkZO+RoYKCAk2aNEnTpk3zxng+ejrx9SE9PV179+4tdqRr0KBB2r59u1599VVJpTvCt3nzZn3xxRfe/86DfR599NFHxT6KlI7vj57Ldnn8/PPPtv+OmD9r1671/pZfUZmZmZJk+Q04Pz9fgwcP1tChQ7Vv3z5NmDBBgwcPDnq/++yzz7R+/Xp9+umnPu1ut1uDBw/WgAEDlJGRoXnz5un666/3uRJMoGUladWqVcrPz9egQYNO2v/nn3+uH374QcuWLdP999/v/WWBYPr/4IMPtHHjRi1btkyzZs3SkiVLdN111+m9997zvh7t2rVL33//vS677DJ9+umnWrlypbZv364DBw7omWee8fltvNLkMmzYML333ns6duyYpOPPnW+//VaXXXaZ3+2trPdP6Y8jwp5/uKTjrwGjR49WXFyc95Jpkv8ibNCgQapVq5bf27/+9a+T9r1lyxYdPHhQZ555prWkrZ5E5jlp3d83D0/kOblu3759Pu0bN2400dHRpmHDhuahhx4yM2bMMM2bNzcRERHm66+/9tuX5wTk9PR006RJExMVFWVuu+0288wzz5jp06eboUOHmtq1a3uX27Vrl0lMTDRRUVFm3Lhx5plnnjFTpkwxbdu2NYcOHfLGffvtt0aSufjii83ChQvNq6++arKzs/1+OzLYvANtt791+hNsP8GemO9yuUyzZs1MeHi4mTRpkpkyZYqJjIw0V111lZFkRowYYTZs2OCzjCTTp08fv+sbMGCAkWSuuOIK89RTT5mPP/7Y5OXlnTSHLVu2mMzMzIDzc3NzS/zGypVXXmnCwsLMpEmTzKOPPmqSk5NNhw4dSjxJsyxKM3b+lPe+E2i/tdJXSUp6nl977bVGkrnkkkvME088Yf7973+bW2+91TRs2NB88cUXQfdTGh06dDCtWrUKOP/Pf/6zefLJJ40xxjz33HN+f+H+7LPP9vnm9ieffGIkmf/85z8+cYcPHzZhYWHG4XCYpKSkYutp0qSJiYmJMXFxcSYuLs7cfvvtxdqbNWtm7r77buNyubzLlfQ82r59u5Fkli1bVqzP1q1bm0svvdSnLSkpyfTs2dPn9a0izJkzx0ydOtWMHj3aSDJXXnmlmTp1qpk6dao5fPiwT6znCyyLFy/2uy7P/h5IoLH1fHHkRN27dzevvPKKMab4Ced9+vQxixYt8s4rehJ+kyZNzBdffGFWrVplWrRo4TNvyJAh3i8f+Fv2RIsWLTIJCQkB53vWsXr1au90ly5dzDvvvGOMMUH1v3TpUu+8f/7zn2bUqFHGGGN69erl/UbyI4884t23Fy9ebFq2bGm++eabYieqlyWXc845x3zwwQfGmOP7xBVXXHHS7bbyulSW99DevXubNm3amIiICDNx4kQze/Zs0717dxMSEuLdNo927dqZr7766qR5B+vo0aOma9euZsqUKZaXrfQizBhj1q5dawYMGGBiYmJMVFSU6devn9+d29+gZ2RkmDFjxpjk5GQTFhZmEhMTzYUXXmieffZZn2V//fVXc8MNN5h69eqZiIgI07x5czNmzJhiBcPUqVNNw4YNjdPp9PYV6MEOJu+yFmHB9mPl25Hff/+96d69u4mIiDC1a9c2//znP43b7TY33XSTCQ0NNQsWLPDGZmVlGUnm6quv9ruurKwsc+edd5ozzjjDhIeHG0nlfhkXfw4ePGiuvPJKEx0dbRISEsytt9560sKuvFgZu5Mp733H335rpa+SLFy40EgKWFDl5uaaadOmmTZt2pgaNWqYOnXqmC5dupjJkydX6Lfcjh07ZsLDw31+OqKof/3rX2bUqFEmNzfXNG7c2KxZs6ZYzKxZs0xMTIz3px9mzpxpJJmtW7cWi+3Xr5+RZAYOHFhsnucNPNh2j5KeR0888YSJi4sr9s9JXl6eCQ0NNf/4xz982keOHGkiIiLMlVdeGbDP8tCkSZOAPxNT9LVt4sSJpnHjxgG/bTlhwgQTEhJy0r78jeFrr71mevbs6dM2bNgw88gjjxhjSi7Cdu7c6bef119/3YSGhnqLvri4OBMdHW2mTZvmd9mXXnrJREdHm+joaHPLLbeYjz76yISEhJz0H8qT5RZM/yfun08//bQZNGiQMcaYZ555xvz5z382xhz/Fu+JlxubNWuW6dChg0lISDB33HGH99u+ZcllxowZ5vrrrzfGGNOzZ0/z2muvBdxmj2Bfl8ryHlq7dm1z7733mmeffdYkJyebiIgI06NHD7NkyRKfuGPHjpmIiIhy+Sc+Pz/fXHLJJebaa68t1aUOLRdhlen555+vtK/R4rgPP/zQOByOoI7wGGPM3XffbSSZgwcPVnBmqExLliwxkszNN99sduzYYdvPB5TG4sWLzbnnnmsee+wxM2TIEL8xhw8fNvHx8T6/W1YapS3Ciir6PEpJSTlpoVnV5ebmmsTERDN79uxi8w4cOGA2bNhg2rdvbxo3bhxwHYHG0N+RsB49eniPhEVFRZlffvnFO69169Y+RVjR9xNPP19++eVJfzakpPeiQ4cOmcjISPPuu+8GvY4TC59g+g90JOzgwYOmVq1aZvXq1aZOnTreQutEO3fuNGeffbbPkbXS5pKammri4uLMtm3bTExMjPdIvJ08P9Pi2Q9OZtOmTSY5OblY+8CBA72FddHbQw89VCze5XKZYcOGmUGDBpX698eq9M8U79mzRw6HQ/Hx8XanctpYunSprr766qC//l+vXj3VqFHD5/wUnPp69eql888/X88++6yaNm1a7OcDqrLOnTtr06ZNmjFjhs8vzZ8oLi5OEyZM0MMPP+z95rWdij6P+vbtq9tvv93mrEpv/vz5CgsL09/+9rdi8zp16qT27dtr06ZN3ktwWeH5dfUnnnhCBQUFevPNN/XTTz95T2Dv0KGDXnvtNblcLi1cuFBbt24Ner1ut1tPPfWU8vPzlZ+fry+++EI7d+4MavlatWrpn//8p/7v//5Pn3zyifLy8nT06FHNmzfP76X1StP/jBkzlJmZqc2bN2vevHm66qqrJB3/+YZ+/fpp+PDhGjp0qPdybqtXr9Z3332ngoIC1axZU2FhYUFdF7mkXJo2baqzzjpLo0aN0sUXX1yhVywJlucLO8GcGxnopPyPP/5Y2dnZfm//+Mc/isXfcsst2rNnj958881Sf9O2Sh4JS09PN0888YRp2LChOe+88+xOBwE8/vjjpmbNmt5fPUf1s2XLFrNs2bKAv5xfVZ1xxhnej0sqUnkcCTvdnkdfffWVWblyZYlHz082huvXrzfnnXeeiY2NNeecc45ZsWKFd97XX39tWrVqZWJjY83f//5307t376COhBljzI4dO8xll11m6tata+rUqWMGDBjg/fjL37L+PPPMM+bss882NWrUMI0aNTI33HCD2bFjh991nHj0KZj+H3/8cZOcnGzq169vpk+f7tPv22+/bST5jMXixYvN2WefbaKjo039+vXN2LFjvVd8KEsuxvxxxYO33nqrxDGpDNOnTzchISEmNze3xNj77rvP58eOS2PHjh3eH+0+8YjZieMfDIcxVeSHtU7guShw165d9dxzz530GnKwT5cuXdS5c2fNmjWLI2GoMrKzs9WiRQt99dVXat68ud3plIjnEcrD6tWrNWTIEO3YsaNUPyN0qrvuuuu0evXqcv2x4cpQJYswACit22+/XS6XS48//rjdqQCVwuVy6aabblKzZs00ZcoUu9OBBVX6nDAACNa6desUFxenDRs2+PwuGFCdHTx4UHFxcfrxxx81btw4u9OBRRwJAwAAsAFHwgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGE4Lc+fOVdOmTRUZGalu3brp22+/tTulCjVlyhQ5HA6fW+vWre1Oq9ytWLFCgwcPVlJSkhwOh959912f+cYYTZo0SQ0aNFCNGjXUv39/bdmyxZ5ky0lJ2zxixIhij/3AgQPtSRbASVGEodp7/fXXNX78eE2ePFlr165Vhw4dNGDAAO3du9fu1CpU27ZttWfPHu/tyy+/tDulcpeTk6MOHTpo7ty5fufPnDlTjz/+uJ5++ml98803io6O1oABA5Sbm1vJmZafkrZZkgYOHOjz2L/66quVmCGAYIXanQBQ0WbNmqVRo0bpxhtvlCQ9/fTT+vDDDzVv3jzdfffdNmdXcUJDQ5WYmGh3GhUqJSVFKSkpfucZYzR79mzde++9uuyyyyRJCxcuVEJCgt59911dffXVlZlquTnZNntERERU+8ceqA44EoZqLT8/X2vWrFH//v29bU6nU/3799eqVatszKzibdmyRUlJSWrevLmuu+467dy50+6UKlVqaqrS09N9Hvu4uDh169at2j/2y5YtU/369dWqVSuNHj1aBw4csDslAH5QhKFa279/v1wulxISEnzaExISlJ6eblNWFa9bt25asGCBPvnkEz311FNKTU1Vr169lJWVZXdqlcbz+J5uj/3AgQO1cOFCLVmyRDNmzNDy5cuVkpIil8tld2oAiuDjSKAaOvHjqvbt26tbt25q0qSJ3njjDY0cOdLGzFDRTvyYtV27dmrfvr3OOOMMLVu2TBdeeKGNmQEoiiNhqNbq1q2rkJAQZWRk+LRnZGScVufM1KpVSy1bttTWrVvtTqXSeB7f0/2xb968uerWrXtaPfbAqYIiDNVaeHi4OnfurCVLlnjb3G63lixZoh49etiYWeXKzs7Wtm3b1KBBA7tTqTTNmjVTYmKiz2OfmZmpb7755rR67Hft2qUDBw6cVo89cKrg40hUe+PHj9fw4cN17rnnqmvXrpo9e7ZycnK835asju68804NHjxYTZo00e7duzV58mSFhITommuusTu1cpWdne1zhCc1NVXr1q1TfHy8GjdurHHjxunBBx9UixYt1KxZM913331KSkrS5Zdfbl/SZXSybY6Pj9f999+vIUOGKDExUdu2bdOECRN05plnasCAATZmDcAvA5wG5syZYxo3bmzCw8NN165dzddff213ShVq2LBhpkGDBiY8PNw0bNjQDBs2zGzdutXutMrd0qVLjaRit+HDhxtjjHG73ea+++4zCQkJJiIiwlx44YVm8+bN9iZdRifb5qNHj5qLLrrI1KtXz4SFhZkmTZqYUaNGmfT0dLvTBuCHwxhj7CoAAQAATlecEwYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGE4beXl5mjJlivLy8uxOpdKcjtssnZ7bfTpuM3Cq43fCcNrIzMxUXFycjhw5otjYWLvTqRSn4zZLp+d2n47bDJzqOBIGAABgA4owAAAAG3ABb1Qrbrdbu3fvVs2aNeVwOHzmZWZm+tyfDk7HbZZOz+2u7ttsjFFWVpaSkpLkdHL8ANUD54ShWtm1a5eSk5PtTgNABUlLS1OjRo3sTgMoFxwJQ7VSs2ZNSdKTtaUaFfjP8ix3N0vxT67OtxT/f+eGW4qXpIGpSZbiP2m221J8xiczLMVLUsLAiZbi6930tqX4ffOGWIqXpIj4Dpbi8w6ut9wHyp/LFOjHw2u8z3GgOqAIQ5U0d+5cPfzww0pPT1eHDh00Z84cde3atcTlPB9B1nBKUU5HCdGlF2KsPXViarqsrd9h/akZERtWoX04Y2IsxZemj9AIa9/qK804hYZYK3ALStEHKk7R0wyAUxkfrKPKef311zV+/HhNnjxZa9euVYcOHTRgwADt3bvX7tQAACg3FGGocmbNmqVRo0bpxhtvVJs2bfT0008rKipK8+bNszs1AADKDUUYqpT8/HytWbNG/fv397Y5nU71799fq1atKhafl5enzMxMnxsAAKcCijBUKfv375fL5VJCQoJPe0JCgtLT04vFT58+XXFxcd4b34wEAJwqKMJwSrvnnnt05MgR7y0tLc3ulAAACApf+0GVUrduXYWEhCgjI8OnPSMjQ4mJicXiIyIiFBERUVnpAQBQbjgShiolPDxcnTt31pIlS7xtbrdbS5YsUY8ePWzMDACA8sWRMFQ548eP1/Dhw3Xuueeqa9eumj17tnJycnTjjTfanRoAAOWGIgxVzrBhw7Rv3z5NmjRJ6enp6tixoz755JNiJ+ufTGSoFBnkcd4m9UMs57jinM2W4iPnWPuh07UzrP8qeN4Kt6X4v6wvsBT/TYPbLcVL0su/DbQU/9PG4l++OJlW22dbipckZ616luJjDu6x3EfWGms/p5J36EfLfQA49VGEoUoaO3asxo4da3caAABUGM4JAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGzAtSNRLZ3TtoZqhjqCio2MC7O8fle+y1L8oXUHLMXXSMu2FC9JNdLjLMWfeTjeUnzN1scsxUtSfNP/Wor/7zm/WYr/4OHLLcVLUtOl51iKj3xlneU+uCA3gGBwJAwAAMAGFGEAAAA2oAgDAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAdeORLVUv2cDxUYG9z+G60i+5fWHtaltKb5g82FL8c4Y69ezdCTHWIrPSbTWR1r9PEvxkvSf0B6W4pcf6mUp3ukssBQvSXvOTLMU36JOY8t91B9p7ZqZyrU2tq60n62tX9LRzR9Yiv894xvLfQCwhiNhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA24diSqpaN96io0OrjdO3r775bXf9uwcyzFP/rpJkvxxm0pXJJ0LNra/1RHa1rrJKLAYSlekgaaNdYWsHZJTn376VRrC0jK6bzEUvzPj1i/jmd+1lFL8THpTS3FJ27vbSlekmr+cq6l+Mi1n1uKP/Ttw5biAXAkDAAAwBYUYQAAADagCAMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQAAADagCAMAALABRRgAAIANuIA3qqUv2rkUFRtcbO+wSMvrv/7wekvxW9tb+3+nZo71/49+j3RZij8cbS3+SIT1C3hHuqz18aeQtZbizxtwhaV4SdrvqGkpfru7oeU+foltbik+NXaftfi4MyzFS1KDmDMtxdcJu8hSfHyI9QudH1w1zfIyQHXCkTAAAAAbUIQBAADYgCIMVcqUKVPkcDh8bq1bt7Y7LQAAyh3nhKHKadu2rRYvXuydDg1lNwUAVD+8u6HKCQ0NVWJiYlCxeXl5ysvL805nZmZWVFoAAJQrPo5ElbNlyxYlJSWpefPmuu6667Rz586AsdOnT1dcXJz3lpycXImZAgBQehRhqFK6deumBQsW6JNPPtFTTz2l1NRU9erVS1lZWX7j77nnHh05csR7S0tLq+SMAQAoHT6ORJWSkpLi/bt9+/bq1q2bmjRpojfeeEMjR44sFh8REaGIiIjKTBEAgHLBkTBUabVq1VLLli21detWu1MBAKBcUYShSsvOzta2bdvUoEEDu1MBAKBcUYShSrnzzju1fPly7dixQytXrtQVV1yhkJAQXXPNNXanBgBAueKcMFQpu3bt0jXXXKMDBw6oXr166tmzp77++mvVq1fP0noeyr1BIeE1goqd2fpZy3nmhoRYir9t8+uW4h/s+hdL8ZIUfyzf4hLW/gfLdVr/n+1AaHCPgcePamIp/pMj/SzFS1KtD6yNbWoXa9ezlKSQ3ChL8dEHre3f9XfUtRQvSVE/HrQUn7P4CWvxaYtLDgLggyIMVcprr71mdwoAAFQKPo4EAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAUUYAACADRzGGGN3EkB5yczMVFxcnHqnT1ZobGRQy2z9Yajlfjp0XGAtPuwXS/G/uetbipekWo4sS/GdzVbLfVi111nTUvzbR/9kKT7U4bIUL0mNw3+zFJ9rIiz3caCgtqX4335vZCn+SHaCpXhJCt2fbCm+9p4kS/F1U6091pIUdij4650W5Gbq82n1deTIEcXGxlruC6iKOBIGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQAAADagCAMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAahdicAVIT6YfsVFhbchZePtv3Q8vpdxtpTZ2XuOZbiu0ZusBQvSW8dHGwpPiI++IsnS1KSDliKl6RMRVuKt3pB7gP5dSzFS8f3jYoW6iiwFB/mtPZYlEZoXnAXtPdI+DnGUvzvi+63FC9JodfeF3SssficA04FHAkDAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAUUYAACADSjCAAAAbMDFuFAtZbujFOYO7tqRuY3fsLz+6PTzLcX/uHa4pfiGXdItxUtSy5hfLMV/mtXbUvz5Md9ZipekAoVYis8zwT1mHvv2tbIUL0kxYdmW4kNk7TqQkpRdUNNSfGZevKV4kxdlKV6S3CHWrsuZ0draONUeO9lSvCS5s0zwsS6H5fUDVR1HwgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbcO1IVEt7chsoJLxGULHZv4yxvP7d+XssxYe2XGUpfnXWOZbiJSk+/ICl+LqPXG8pfu3Eo5biJSkuNMtSfPaxGEvxHeY0txQvSZvuPmwpPiw013IfxwoiLcUXZNexFF/jQKKleEmqvzPJUnx4jrW3h8htmZbiJSn3jNigYwtCuXYkqh+OhAEAANiAIgwAAMAGFGEAAAA2oAhDibKyrJ3XczIrVqzQ4MGDlZSUJIfDoXfffddnvjFGkyZNUoMGDVSjRg31799fW7ZsKbf+AQCoKijCUKJevXopPT29XNaVk5OjDh06aO7cuX7nz5w5U48//riefvppffPNN4qOjtaAAQOUm2v95GgAAKoyijCU6JxzzlG3bt30888/+7SvW7dOF198saV1paSk6MEHH9QVV1xRbJ4xRrNnz9a9996ryy67TO3bt9fChQu1e/fuYkfMPPLy8pSZmelzAwDgVEARhhLNnz9fI0aMUM+ePfXll1/ql19+0VVXXaXOnTsrJCSk3PpJTU1Venq6+vfv722Li4tTt27dtGqV/594mD59uuLi4ry35OTkcssHAICKxO+EISj333+/IiIi9Kc//Ukul0sXXnihVq1apa5du5ZbH56PPBMSEnzaExISAn4ces8992j8+PHe6czMTAoxAMApgSIMJcrIyNC0adP03HPPqU2bNvr55581YsSIci3ASisiIkIRERF2pwEAgGV8HIkSNWvWTCtWrNCbb76pNWvW6O2339bNN9+shx9+uFz7SUw8/ivgGRkZPu0ZGRneeQAAVBcUYSjRvHnz9P333+uSSy6RJA0cOFBLly7VY489pjFjrF/yJ5BmzZopMTFRS5Ys8bZlZmbqm2++UY8ePcqtHwAAqgI+jkSJrr766mJtnTp10sqVK5WSkmJpXdnZ2dq6dat3OjU1VevWrVN8fLwaN26scePG6cEHH1SLFi3UrFkz3XfffUpKStLll19e1s0AAKBKcRhjjN1J4NR16NAh1a5dO+j4ZcuWqV+/fsXahw8frgULFsgYo8mTJ+vZZ5/V4cOH1bNnTz355JNq2bJlUOvPzMxUXFyc6q3/QM6a0UEtUytuV9D5e2T9bu2Cy+Fh1i5+XfO7P1mKl6Qj535uKf7YvqaW4k3Ng5biJSmu5m5L8b9bvIC3fm1nLV5SWJ61i2tnJ6RZ7sPhtvat4bDsWpbiY/fVsxQvSfV2xFmKD132jaX4/YvvtBQvSfVS5gQdW3AsW0vf6K0jR44oNjb4C38DVRlHwlAmVgowSerbt69OVvc7HA498MADeuCBB8qaGgAAVRrnhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGXLYI1VKj77sqJCq468vtOX+x5fUnfNfHUvzudmssxUeFFViKlyST1tZSvNUnf4vPO1hcQvqx/1pL8SYs11J8uNNtKV6Smq9KtBS/v6W1S3NJUnbtI5aXsSL0mPWX7mNR1sYq+6uZluJrnTPGUrwkFXTvGHzs75nSG5a7AKo0joQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANuDakaiWam11KDTSEVTsb2c1tLz+uD01LMXnR7Sz3IdVLaZssRSfOfxCS/EFUZbCJUlt/3eOpfjf2h20FH8sIs9SvCSlt82xFN/g40zLfUR3SrIUn1X3qKV4p9v6/8+uMGMpPv6SRyz3YVWBhctZOqylD5wSOBIGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQAAADagCAMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAZcwBvVkqtmmByRYUHFJm1uZXn9BRHWriYc9pdBluLr3LvCUrwk6cKBlsIL/tbbUnzo5C8sxZdG43dzLcUf7FPPch95UdYu+p3TpYHlPsJf/o+l+JjrrrAUfyzSZSlekhyu4C5o75WQYC3+sPULnYdkHQs61uQGHwucKjgSBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAa0eiWgo9lKvQiPCgYuPXbLW8fkejppbia9y1zFoH6zZZi5fkOLOlpfh6E5dbii/4+L+W4iXJfemlluKdDepbio//2do1PCXpcMtIS/HuUvyrGta+r6X40D3WtuP3+pXw0h1msY8Q6wPlyP49+Ni84GOBUwVHwgAAAGxAEQYAAGADijBUqhUrVmjw4MFKSkqSw+HQu+++6zN/xIgRcjgcPreBAwfakywAABWIIgyVKicnRx06dNDcuXMDxgwcOFB79uzx3l599dVKzBAAgMrBifmoVCkpKUpJSTlpTEREhBITEyspIwAA7MGRMFQ5y5YtU/369dWqVSuNHj1aBw4cCBibl5enzMxMnxsAAKcCijBUKQMHDtTChQu1ZMkSzZgxQ8uXL1dKSopcLpff+OnTpysuLs57S05OruSMAQAoHT6ORJVy9dVXe/9u166d2rdvrzPOOEPLli3ThRdeWCz+nnvu0fjx473TmZmZFGIAgFMCR8JQpTVv3lx169bV1q3+f1A1IiJCsbGxPjcAAE4FFGGo0nbt2qUDBw6oQYMGdqcCAEC54uNIVKrs7Gyfo1qpqalat26d4uPjFR8fr/vvv19DhgxRYmKitm3bpgkTJujMM8/UgAEDbMwaAIDyRxGGSrV69Wr169fPO+05n2v48OF66qmntGHDBr344os6fPiwkpKSdNFFF2nq1KmKiIiw1I/rh+/kCIsOLthdYGndknTo07stxdcd9YaleNOylaV4Sfr9/actxUdeOcZSfFiLrpbiJUkZuZbCXXHWHuesOTdZipekmHHzLcUXRFnuQoqraSncrF9nKT68R2dL8ZJkrH7u4XJbiw8JsdiBpKys4GPzs62vH6jiKMJQqfr27StjAl+s+H//+18lZgMAgH04JwwAAMAGFGEAAAA2oAgDAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAdeORLV0cOWDCnEEt3vXOsfahawlqc7ARyzFu35cayk+pIP1i2VHNDvPUrzjkMULIteMsRYv6djKDy3Fh/a51FJ8rQH3W4qXJKXutRTubFTPeh8WL359+ItpluLjWyyyFC9JJibS2gJHf7fch1Um61DwsVzAG9UQR8IAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQAAADagCAMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG3DtSFRL4bHNFeIMDyr28PdzLa+/XsOnLMUfWHqPpfj6yW9bipckZ2y8pfiCH76yFB/aprul+NJw7A/+WoKSpLDgHuMT/b7qdUvxNfoNt9yHXC5L4XHdb7cUb3b/ZilekhwJDawtcOSwtfioaGvxklwH0oKPPXbU8vqBqo4jYQAAADagCAMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQAAADagCAMAALABRRgAAIANuHYkqqWC3/fLOMOCiq2R0M3y+q1c806SYltfZ2392zdYipckZ826luLzdn1rKT6kTrKleEkKbdjWUrzV7Q5JPMNSvCTl799oKT5y907Lfchp7aXVGV3LUnzeT0ssxUtSZNTlluJd6dssxYc0b28pXpJyf/0y6NgCV57l9QNVHUfCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAIgwAAMAGFGEAAAA2oAgDAACwAUUYAACADSjCAAAAbEARBgAAYAOKMAAAABtQhAEAANiAC3ijWnIfy5TDEdzu/XvGN5bXfywz1fIyVhT8/LLlZaKSeluKd+dnWYo/tGSypXhJqtnmWmt9rJltKb5253GW4iUp79CPluJz1r5quQ+rYxuZfJ6l+MxS7B8hsUmW4g+vedxSfLzzXkvxknR094qgY12mwPL6gaqOI2EAAAA2oAgDAACwAUUYKs306dPVpUsX1axZU/Xr19fll1+uzZs3+8Tk5uZqzJgxqlOnjmJiYjRkyBBlZGTYlDEAABWHIgyVZvny5RozZoy+/vprffbZZzp27Jguuugi5eTkeGNuv/12vf/++3rzzTe1fPly7d69W1deeaWNWQMAUDE4MR+V5pNPPvGZXrBggerXr681a9aod+/eOnLkiF544QW98soruuCCCyRJ8+fP11lnnaWvv/5a3bt3L7bOvLw85eXleaczMzMrdiMAACgnHAmDbY4cOSJJio+PlyStWbNGx44dU//+/b0xrVu3VuPGjbVq1Sq/65g+fbri4uK8t+Tk5IpPHACAckARBlu43W6NGzdO559/vs4++2xJUnp6usLDw1WrVi2f2ISEBKWnp/tdzz333KMjR454b2lpaRWdOgAA5YKPI2GLMWPGaOPGjfryyy/LtJ6IiAhFRESUU1YAAFQejoSh0o0dO1YffPCBli5dqkaNGnnbExMTlZ+fr8OHD/vEZ2RkKDExsZKzBACgYlGEodIYYzR27Fi98847+vzzz9WsWTOf+Z07d1ZYWJiWLFnibdu8ebN27typHj16VHa6AABUKD6ORKUZM2aMXnnlFb333nuqWbOm9zyvuLg41ahRQ3FxcRo5cqTGjx+v+Ph4xcbG6tZbb1WPHj38fjPSH2OMpIq/xInDfaxC11+a/AtceSUHncDtyrcU7yrFNhcUHLXWh8Xttrr+UvVhcVwl62Nb0eNUqj7cFsfpWE7JQUX7sLAdnljPcxyoDhyGPRqVxOFw+G2fP3++RowYIen4j7XecccdevXVV5WXl6cBAwboySefDPrjyF27dvENSaAaS0tL8zmNATiVUYShWnG73dq9e7dq1qxZrOjLzMxUcnKy0tLSFBsba1OGlet03Gbp9Nzu6r7NxhhlZWUpKSlJTidn0qB64ONIVCtOp7PE/5JjY2Or5ZvUyZyO2yydnttdnbc5Li7O7hSAcsW/EwAAADagCAMAALABRRhOGxEREZo8efJp9eOup+M2S6fndp+O2wyc6jgxHwAAwAYcCQMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQBOKY0aNdKTTz7p07Zy5UpFRUXp119/tSkrALCOIgzAKaVbt2767rvvvNPGGI0bN0633367mjRpYmNmAGANRRiAU0r37t19irBFixYpLS1N99xzj41ZAYB1FGEATindu3fXTz/9pOzsbOXk5Ogf//iHHnzwQcXExNidGgBYEmp3AgBgRefOneV0OrV27VotXrxY9erV04033mh3WgBgGUUYgFNKVFSU2rVrp7ffflvPPfecPvroIzmdHNQHcOrhlQvAKad79+6aM2eOBgwYoL59+9qdDgCUCkUYgFNOhw4dFBYWpocfftjuVACg1BzGGGN3EgBgRb9+/dSpUyc9+uijdqcCAKXGOWEATglut1v79u3TCy+8oC1btui9996zOyUAKBOKMACnhBUrVuiCCy5Q69at9fbbbys2NtbulACgTPg4EgAAwAacmA8AAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANgi1O4HKkJubq/z8fLvTAAAAFoSHhysyMtLuNCpMtS/CcnNzVbdGDeXYnQgAALAkMTFRqamp1bYQq/ZFWH5+vnIkjQ1xKtph5HQcbw8tvA8pdm98p52B4nznez7X9bQ7/SznjfXGOHymi87/Y9p/nKPI8p4+vet1/tFetC/PtKPoupxF5/u2/9Gn7/LOEN94h3cgHH/M89wXznIUbS/csGLtTv/zFWB5nZhDkRgFiC32wBYd7GLtvtPG33ThoiZEOnHDjSfGM98bF6C98N7tKDIdIM44jXfeH/fGZx3e6SLrLrpOd+HzwVV0fUXb9cd8z7pcRdbpnfbOd/j2XTgdKM4lh29c4QB7pt1ynhDr9LkvcIQUxhyfX+CdH1I4HeLT7vZMG992T5x3ORPqbS8a6/LMM55lfKcLjNOn3WV8+yy6vNv4rtfljQuR2/t3Yf7eZXyXNZ5pd0jhdGG82+kz7dkBjPcBD/Fp/2M6xPtAOQrbHJ4dvnBZb7vr+L3T2154X7hOpyfO0x4g3ulyetuLz3P4LOP05ObyrLNwvnH4Tnvj5Hfa4fbcG++0w2UKt7Owrci0XIULuX3vHZ7povOLTR/v3LgLk/Dcu1wnxBQcj3F5Ygp87ou1e+OPFd4XiXcfK4zznW/c+d5277KFbX+sK79Ie5H57rzCdeQVmZ9X5D6/cBhy5TIu/Zi+Wvn5+RRhp7oISREOh/e9M3ARFtz8ku6DKcJCgi3CAsWVpggLEGO5CCtSxAUqwhz+irCiMSUVYQHmByzCTmwPuEwJ1XWgIixA3MmLsCLzSluEBT19kiIs0HTA4izIIsxTMJWhCHMVK8Icvu0BijCXhSLMO11CEeZpDyksKELke++JdxYWRE6FyFkY6yxSoDm87b7T3vsi7fLOD/WZdnnn+7bLhBRf1h1SJMa3CFORIkzuIvODLcLcIcWLraCLMN+iq2gR5gxYhP3R7inISirCnEWLMG+RZbEIc5WhCHOVVIS5/E7/UUidWIR5/i6h2HL6FllyetqP+dz/UbQVTjsK53vuPY+3I1Sm8LlkCsfUFO7vpvC5Yzz/bKro/fFxMabovdvvvXf/r+acdicAAABwOqIIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGADijAAAAAbUIQBAADYgCIMAADABhRhAAAANqAIAwAAsAFFGAAAgA0owgAAAGxAEQYAAGCDULsTqCx5kkKN8Vadng0PKXZvfKdNoDjf+U5PnKNwWr7TIY4/lnEWifFMF53vnTZF2gunHUXanSbwvfdvd+F9YeeOIvdOp//5xaYdRabdRdbn9iR/wjzPfWHijsLB+eNe/tud/ucrwPJyntAeYgIsU3RQi9wXHexi7b7Txt904VgYT16OwnmeGM98b1yA9sJ7t6PIdIA44zTeeX/cG591eKeLrLvoOt2Fj5Wr6PqKtuuP+Z51uYqs0zvtne/w7btwOlCcSw7fuMIB9ky75Twh1ulzX1CYr7twHQXe+e7CabdPu9szbTztrsL7kMLlQorMD1FB4QPtXbcpXMZ4lvGdLjCeHEIL40N8402oz7TbE298410mRG7v34X5e5fxXdZ4pt0hhdOF8W6nz7RnBzDeBzzEp/2P6RDvA+UobHN4dvjCZb3trqLthfdF1ulpN4Xxpki8cf2RW/F5Dp9lTGFu7sJlHIXzncbhO+3ZhuMPUbFp72uX23inHa7C1wZPW5FpuQoXcvveOzzTRecXm3YVbkNhEp57l+uEmILC7fbEFPjcF2v3xh8rvC8S7z5WGOc737jzve3eZQvb/lhXfpH2IvM96/DMdx8LcH+8T7cp8D6HqrNqX4SFh4crMTFRT6Sn252KH6ac4wAAqD5iYmJkTPV9D3SY6rx1hXJzc7V//34lJycrLS1NsbGx6tKli7777jtJ8vnbo2ibv5iTtZc0z0pMWeJLkpmZGXBc/PUXzFiVlGdFjEtplzmZso7N6bLPFO2jtPtMadqtxpTHMidTXZ5P1WGfKWleMPPLa5mTYZ8JzDM2R44c8e431U21PxImSZGRkd4HMDY2VrGxsQoJCfG2nfi3R9E2fzEnay9pnpWYssQHy9+4+OsvmLEqKc+KGJfSLhOM0o7N6bLPFO2jtPtMadqtxpTHMsE41Z9P1WGfKWleMPPLa5lgsM+cnk7bE/PHjBnj9+9Abf5iTtZe0jwrMWWJt6qk7Q5mrAK1BTPPSkx5LFOW9ZdmrE7WXtI8KzFliS+Nkz2frOwfpRkzKzHlsUxZ1n+qPJ+qwz5T0rxg5pfXMmVZP/tM9XZafBwpHT+sGRcXV60Pa5YG4xIYY+Mf4xIYY+Mf4xIYYxPY6TA2p82RsIiICE2ePFkRERF2p1KlMC6BMTb+MS6BMTb+MS6BMTaBnQ5jc9ocCQMAAKhKTpsjYQAAAFUJRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CESfrggw/UqlUrtWjRQs8//7zd6VRpV1xxhWrXrq0///nPdqdSZaSlpalv375q06aN2rdvrzfffNPulKqMw4cP69xzz1XHjh119tln67nnnrM7pSrl6NGjatKkie688067U6lSmjZtqvbt26tjx47q16+f3elUGampqerXr5/atGmjdu3aKScnx+6UqoTNmzerY8eO3luNGjX07rvv2p1WUE77n6goKChQmzZttHTpUsXFxalz585auXKl6tSpY3dqVdKyZcuUlZWlF198UW+99Zbd6VQJe/bsUUZGhjp27Kj09HR17txZv/zyi6Kjo+1OzXYul0t5eXmKiopSTk6Ozj77bK1evZrnV6F//vOf2rp1q5KTk/XII4/YnU6V0bRpU23cuFExMTF2p1Kl9OnTRw8++KB69eqlgwcPKjY2VqGhp8XVB4OWnZ2tpk2b6tdffz0lXoNP+yNh3377rdq2bauGDRsqJiZGKSkp+vTTT+1Oq8rq27evatasaXcaVUqDBg3UsWNHSVJiYqLq1q2rgwcP2ptUFRESEqKoqChJUl5enowxOs3/7/PasmWLfv75Z6WkpNidCk4BmzZtUlhYmHr16iVJio+PpwDz47///a8uvPDCU6IAk6pBEbZixQoNHjxYSUlJcjgcfg9Bzp07V02bNlVkZKS6deumb7/91jtv9+7datiwoXe6YcOG+u233yoj9XJX1rGoripzXNasWSOXy6Xk5OQyZl05KmNsDh8+rA4dOqhRo0a66667VLdu3XLKvuJUxrjceeedmj59ejllXHkqY2wcDof69OmjLl266OWXXy6nzCtWRY/Lli1bFBMTo8GDB6tTp06aNm1aOWZfsSrzNfiNN97QsGHDyphx5Tnli7CcnBx16NBBc+fO9Tv/9ddf1/jx4zV58mStXbtWHTp00IABA7R3795KzrTilcdYeM7dKXrbvXt3ZW1GuauscTl48KBuuOEGPfvssxW+TeWlMsamVq1aWr9+vVJTU/XKK68oIyOjUratLCp6XN577z21bNlSLVu2rKxNKjeVsc98+eWXWrNmjf773/9q2rRp2rBhQ6VsW1lU9LgUFBToiy++0JNPPqlVq1bps88+02effVZZm1cmlfUanJmZqZUrV+riiy+u8G0qN6YakWTeeecdn7auXbuaMWPGeKddLpdJSkoy06dPN8YY89VXX5nLL7/cO/+2224zL7/8cqXkW5FKMxbBWrp0qRkyZEh5pFnpKmpccnNzTa9evczChQvLK9VKV5H7jMfo0aPNm2++WZY0K11FjMvdd99tGjVqZJo0aWLq1KljYmNjzf3331+eaVeKythn7rzzTjN//vwyZFn5KmJcVq5caS666CLv9MyZM83MmTPLJd/KVJH7zMKFC811111XHmlWmlP+SNjJ5Ofna82aNerfv7+3zel0qn///lq1apUkqWvXrtq4caN+++03ZWdn6+OPP9aAAQPsSrnCBDMWp6PyGBdjjEaMGKELLrhA119/fUWlWunKY2wyMjKUlZUlSTpy5IhWrFihVq1aVUi+laU8xmX69OlKS0vTjh079Mgjj2jUqFGaNGlSRaVcacpjbHJycrz7THZ2tj7//HO1bdu2QvKtLOUxLl26dNHevXt16NAhud1urVixQmeddVZFpVxpyvO96VT7KFKSqvVZffv375fL5VJCQoJPe0JCgn7++WdJUmhoqB599FH169dPbrdbEyZMqJbf3ApmLILRv39/rV+/Xjk5OWrUqJHefPNN9ejRo7zTrTTlMS5fffWVXn/9dbVv3957rsOiRYvUrl278k63UpXH2Pz666+6+eabvSfk33rrrYxLNVYeY5ORkaErrrhC0vFv144aNUpdunQp91wrU3mMS2hoqKZNm6bevXvLGKOLLrpIgwYNqoh0K1V5PZ+OHDmib7/9Vm+//XZ5p1ihqnURFqxLL71Ul156qd1pnBIWL15sdwpVTs+ePeV2u+1Oo0rq2rWr1q1bZ3caVdqIESPsTqFKad68udavX293GlVSSkoK36YNIC4u7pQ437Soav1xZN26dRUSElLsgcnIyFBiYqJNWdmDsfCPcQmMsfGPcQmMsfGPcQnsdB+bal2EhYeHq3PnzlqyZIm3ze12a8mSJaf0R2ilwVj4x7gExtj4x7gExtj4x7gEdrqPzSn/cWR2dra2bt3qnU5NTdW6desUHx+vxo0ba/z48Ro+fLjOPfdcde3aVbNnz1ZOTo5uvPFGG7OuGIyFf4xLYIyNf4xLYIyNf4xLYIzNSdj75cyyW7p0qZFU7DZ8+HBvzJw5c0zjxo1NeHi46dq1q/n666/tS7gCMRb+MS6BMTb+MS6BMTb+MS6BMTaBnfbXjgQAALBDtT4nDAAAoKqiCAMAALABRRgAAIANKMIAAABsQBEGAABgA4owAAAAG1CEAQAA2IAiDAAAwAYUYQAAADagCAMAALABRRgAAIANKMIAAABs8P9IIxaA8T0iMwAAAABJRU5ErkJggg==", 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", 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", + "text/plain": [ + "
" ] }, "metadata": {}, @@ -540,16 +571,18 @@ } ], "source": [ - "rho = np.linspace(0.01, 1, 3)\n", - "eq0 = get(\"HELIOTRON\")\n", - "angle = Bounce2D.angle(eq0, X=40, Y=20, rho=rho)\n", - "for l in range(rho.size):\n", - " fig = Bounce2D.plot_angle_spectrum(angle, l)" + "plot_wells(\n", + " eq0,\n", + " LinearGrid(rho=rho, M=eq0.M_grid, N=eq0.N_grid, NFP=eq0.NFP, sym=False),\n", + " angle,\n", + " field_period_transits=15,\n", + " num_well=2 * 15,\n", + ");" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "36934653-6515-4c86-854e-062adbee9dec", "metadata": { "scrolled": true @@ -559,17 +592,15 @@ "rho = np.linspace(0.01, 1, 10)\n", "angle = Bounce2D.angle(eq0, X=32, Y=20, rho=rho)\n", "grid = LinearGrid(rho=rho, M=eq0.M_grid, N=eq0.N_grid, NFP=eq0.NFP, sym=False)\n", - "Y_B = 133\n", - "num_transit = 20\n", - "num_well = 25 * num_transit\n", + "field_period_transits = 398\n", + "num_well = 2 * field_period_transits\n", "num_quad = 48\n", "num_pitch = 45\n", "data = eq0.compute(\n", " \"effective ripple\",\n", " grid,\n", " angle=angle,\n", - " Y_B=Y_B,\n", - " num_transit=num_transit,\n", + " field_period_transits=field_period_transits,\n", " num_well=num_well,\n", " num_quad=num_quad,\n", " num_pitch=num_pitch,\n", @@ -579,13 +610,13 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "dcccf61f-7309-4d54-8be9-0604c275a09b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -612,16 +643,22 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "b0075707-d70c-4629-b9aa-b02fe56dda04", "metadata": {}, "outputs": [], "source": [ + "# This cell will consume significant memory.\n", + "knots_per_field_period = (grid.num_zeta + grid.num_theta) // 2\n", "low_order_eps_grid = Grid.create_meshgrid(\n", " [\n", " rho,\n", " np.array([0]),\n", - " np.linspace(0, num_transit * 2 * np.pi, num_transit * 200),\n", + " np.linspace(\n", + " 0,\n", + " field_period_transits * 2 * np.pi / eq0.NFP,\n", + " field_period_transits * knots_per_field_period,\n", + " ),\n", " ],\n", " coordinates=\"raz\",\n", ")\n", @@ -632,12 +669,14 @@ " num_quad=num_quad,\n", " num_pitch=num_pitch,\n", ")[\"old effective ripple\"]\n", - "low_order_eps = low_order_eps_grid.compress(low_order_eps)" + "low_order_eps = low_order_eps_grid.compress(low_order_eps)\n", + "del low_order_eps_grid\n", + "del knots_per_field_period" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "id": "cd1bbdc5-592f-4abf-98af-298d194725dc", "metadata": { "scrolled": true @@ -645,7 +684,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -678,7 +717,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "5e65af04-7b46-4f30-b265-6467254eb2cb", "metadata": {}, "outputs": [ @@ -693,26 +732,26 @@ "Building objective: Effective ripple\n", "Building objective: aspect ratio\n", "Precomputing transforms\n", - "Timer: Precomputing transforms = 101 ms\n", + "Timer: Precomputing transforms = 33.4 ms\n", "Building objective: Generic\n", - "Timer: Objective build = 4.11 sec\n", + "Timer: Objective build = 2.09 sec\n", "Building objective: force\n", "Precomputing transforms\n", - "Timer: Precomputing transforms = 148 ms\n", - "Timer: Objective build = 1.05 sec\n", - "Timer: Objective build = 3.37 ms\n", - "Timer: Eq Update LinearConstraintProjection build = 6.71 sec\n", - "Timer: Proximal projection build = 46.7 sec\n", + "Timer: Precomputing transforms = 38.9 ms\n", + "Timer: Objective build = 496 ms\n", + "Timer: Objective build = 812 us\n", + "Timer: Eq Update LinearConstraintProjection build = 1.99 sec\n", + "Timer: Proximal projection build = 12.8 sec\n", "Building objective: lcfs R\n", "Building objective: lcfs Z\n", "Building objective: fixed pressure\n", "Building objective: fixed iota\n", "Building objective: fixed Psi\n", - "Timer: Objective build = 1.44 sec\n", - "Timer: LinearConstraintProjection build = 1.95 sec\n", + "Timer: Objective build = 667 ms\n", + "Timer: LinearConstraintProjection build = 704 ms\n", "Number of parameters: 8\n", "Number of objectives: 253\n", - "Timer: Initializing the optimization = 50.2 sec\n", + "Timer: Initializing the optimization = 14.2 sec\n", "\n", "Starting optimization\n", "Using method: proximal-lsq-exact\n", @@ -722,7 +761,7 @@ "Maximum Allowed Total Δx Norm : inf\n", "Scaled Termination : True\n", "Trust Region Method : qr\n", - "Initial Trust Radius : 1.681e-02\n", + "Initial Trust Radius : 1.677e-02\n", "Maximum Trust Radius : inf\n", "Minimum Trust Radius : 2.220e-16\n", "Trust Radius Increase Ratio : 2.000e+00\n", @@ -732,44 +771,44 @@ "------------------------------------------------------------ \n", "\n", " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", - " 0 1 4.110e-01 8.444e-01 \n", - " 1 2 3.967e-01 1.431e-02 4.772e-03 7.723e-01 \n", - " 2 3 3.632e-01 3.346e-02 4.144e-03 7.002e-01 \n", - " 3 4 3.211e-01 4.206e-02 8.471e-03 6.110e-01 \n", - " 4 5 2.726e-01 4.855e-02 1.540e-02 5.204e-01 \n", - " 5 6 2.266e-01 4.599e-02 2.000e-02 3.346e-01 \n", - " 6 7 1.641e-01 6.245e-02 1.915e-02 2.900e-01 \n", - " 7 9 1.429e-01 2.121e-02 1.660e-02 2.203e-01 \n", + " 0 1 4.105e-01 8.483e-01 \n", + " 1 2 3.847e-01 2.579e-02 4.576e-03 7.533e-01 \n", + " 2 3 3.434e-01 4.136e-02 8.062e-03 6.567e-01 \n", + " 3 4 2.743e-01 6.902e-02 1.538e-02 5.024e-01 \n", + " 4 5 1.881e-01 8.630e-02 2.817e-02 3.293e-01 \n", + " 5 7 1.608e-01 2.721e-02 2.136e-02 2.597e-01 \n", + " 6 9 1.483e-01 1.250e-02 7.956e-03 2.419e-01 \n", + " 7 10 1.257e-01 2.265e-02 1.889e-02 1.754e-01 \n", "Warning: Maximum number of iterations has been exceeded.\n", - " Current function value: 1.429e-01\n", - " Total delta_x: 6.451e-02\n", + " Current function value: 1.257e-01\n", + " Total delta_x: 8.343e-02\n", " Iterations: 7\n", - " Function evaluations: 9\n", + " Function evaluations: 10\n", " Jacobian evaluations: 8\n", - "Timer: Solution time = 10.8 min\n", - "Timer: Avg time per step = 1.35 min\n", + "Timer: Solution time = 2.78 min\n", + "Timer: Avg time per step = 20.8 sec\n", "==============================================================================================================\n", " Start --> End\n", - "Total (sum of squares): 4.107e-01 --> 1.429e-01, \n", - "Maximum absolute Effective ripple ε: 4.492e-01 --> 3.178e-01 ~\n", - "Minimum absolute Effective ripple ε: 2.524e-01 --> 1.517e-01 ~\n", - "Average absolute Effective ripple ε: 3.985e-01 --> 2.317e-01 ~\n", - "Maximum absolute Effective ripple ε: 4.492e-01 --> 3.178e-01 (normalized)\n", - "Minimum absolute Effective ripple ε: 2.524e-01 --> 1.517e-01 (normalized)\n", - "Average absolute Effective ripple ε: 3.985e-01 --> 2.317e-01 (normalized)\n", - "Aspect ratio: 1.048e+01 --> 1.083e+01 (dimensionless)\n", - "Maximum Generic objective value: -6.864e-01 --> -6.981e-01 (m^{-1})\n", - "Minimum Generic objective value: -5.858e+00 --> -6.293e+00 (m^{-1})\n", - "Average Generic objective value: -1.566e+00 --> -1.601e+00 (m^{-1})\n", - "Maximum Generic objective value: -6.864e-01 --> -6.981e-01 (normalized)\n", - "Minimum Generic objective value: -5.858e+00 --> -6.293e+00 (normalized)\n", - "Average Generic objective value: -1.566e+00 --> -1.601e+00 (normalized)\n", - "Maximum absolute Force error: 5.503e+03 --> 6.578e+03 (N)\n", - "Minimum absolute Force error: 1.430e-02 --> 8.531e-04 (N)\n", - "Average absolute Force error: 7.043e+01 --> 5.048e+01 (N)\n", - "Maximum absolute Force error: 4.426e-04 --> 5.291e-04 (normalized)\n", - "Minimum absolute Force error: 1.150e-09 --> 6.861e-11 (normalized)\n", - "Average absolute Force error: 5.664e-06 --> 4.060e-06 (normalized)\n", + "Total (sum of squares): 4.105e-01 --> 1.257e-01, \n", + "Maximum absolute Effective ripple ε: 4.496e-01 --> 2.994e-01 ~\n", + "Minimum absolute Effective ripple ε: 2.495e-01 --> 1.268e-01 ~\n", + "Average absolute Effective ripple ε: 3.982e-01 --> 2.158e-01 ~\n", + "Maximum absolute Effective ripple ε: 4.496e-01 --> 2.994e-01 (normalized)\n", + "Minimum absolute Effective ripple ε: 2.495e-01 --> 1.268e-01 (normalized)\n", + "Average absolute Effective ripple ε: 3.982e-01 --> 2.158e-01 (normalized)\n", + "Aspect ratio: 1.048e+01 --> 1.100e+01 (dimensionless)\n", + "Maximum Generic objective value: -6.864e-01 --> -6.858e-01 (m^{-1})\n", + "Minimum Generic objective value: -5.858e+00 --> -6.339e+00 (m^{-1})\n", + "Average Generic objective value: -1.566e+00 --> -1.628e+00 (m^{-1})\n", + "Maximum Generic objective value: -6.864e-01 --> -6.858e-01 (normalized)\n", + "Minimum Generic objective value: -5.858e+00 --> -6.339e+00 (normalized)\n", + "Average Generic objective value: -1.566e+00 --> -1.628e+00 (normalized)\n", + "Maximum absolute Force error: 5.503e+03 --> 6.476e+03 (N)\n", + "Minimum absolute Force error: 1.430e-02 --> 5.463e-03 (N)\n", + "Average absolute Force error: 7.043e+01 --> 4.982e+01 (N)\n", + "Maximum absolute Force error: 4.426e-04 --> 5.208e-04 (normalized)\n", + "Minimum absolute Force error: 1.150e-09 --> 4.394e-10 (normalized)\n", + "Average absolute Force error: 5.664e-06 --> 4.006e-06 (normalized)\n", "R boundary error: 0.000e+00 --> 0.000e+00 (m)\n", "Z boundary error: 0.000e+00 --> 0.000e+00 (m)\n", "Fixed pressure profile error: 0.000e+00 --> 0.000e+00 (Pa)\n", @@ -816,9 +855,8 @@ " grid=ripple_grid,\n", " X=32,\n", " Y=20,\n", - " Y_B=133,\n", - " num_transit=10,\n", - " num_well=24 * 10,\n", + " field_period_transits=190,\n", + " num_well=250,\n", " num_quad=32,\n", " num_pitch=45,\n", " ),\n", @@ -832,6 +870,7 @@ " ),\n", " )\n", ")\n", + "# does an expensive qr/svd solve at each step\n", "optimizer = Optimizer(\"proximal-lsq-exact\")\n", "(eq1,), _ = optimizer.optimize(\n", " eq1,\n", @@ -849,7 +888,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "ceced2bb-a5ef-45b7-8864-e874d78239fd", "metadata": { "scrolled": true @@ -860,8 +899,7 @@ " \"effective ripple\",\n", " grid,\n", " angle=Bounce2D.angle(eq1, X=40, Y=20, rho=rho),\n", - " Y_B=Y_B,\n", - " num_transit=num_transit,\n", + " field_period_transits=field_period_transits,\n", " num_well=num_well,\n", " num_quad=num_quad,\n", " num_pitch=num_pitch,\n", @@ -871,7 +909,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "id": "7289f3dc-857a-49d6-9a21-1835d55ef6c0", "metadata": { "scrolled": true @@ -879,7 +917,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -898,15 +936,15 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "a0d2154f", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -922,7 +960,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "desc-env", "language": "python", "name": "python3" }, @@ -936,7 +974,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.14.3" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/publications/unalmis2025/effective_ripple_profile.py b/publications/unalmis2025/effective_ripple_profile.py index e53ff37a50..2e4dda4b13 100644 --- a/publications/unalmis2025/effective_ripple_profile.py +++ b/publications/unalmis2025/effective_ripple_profile.py @@ -14,6 +14,7 @@ Profiling requires python < 3.14. - pip install xprof tensorboard tensorboard_plugin_profile + - pip install 'setuptools < 82' - cd DESC/publications/unalmis2025 - python effective_ripple_profile.py - tensorboard --logdir=/tmp/profile-data @@ -31,7 +32,7 @@ rho = np.linspace(0.1, 1, 10) grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) -num_transit = 15 +field_period_transits = 75 obj = ObjectiveFunction( [ EffectiveRipple( @@ -39,9 +40,8 @@ grid=grid, X=32, Y=32, - Y_B=100, - num_transit=num_transit, - num_well=16 * num_transit, + field_period_transits=field_period_transits, + num_well=3 * field_period_transits, num_quad=32, num_pitch=101, ) diff --git a/publications/unalmis2025/plots.py b/publications/unalmis2025/plots.py deleted file mode 100644 index b235558c5d..0000000000 --- a/publications/unalmis2025/plots.py +++ /dev/null @@ -1,1069 +0,0 @@ -"""Scripts to generate plots for the article. - -May need to run - - tar -xf utils.tar.xz - -""" - -import pickle -import warnings -from fractions import Fraction -from itertools import product - -import matplotlib.pyplot as plt -import matplotlib.ticker as mticker -import numpy as np -import pytest -from matplotlib.ticker import AutoMinorLocator -from mpl_toolkits.axes_grid1.inset_locator import mark_inset - -from desc.backend import jnp -from desc.compat import flip_theta -from desc.compute import data_index -from desc.equilibrium import Equilibrium -from desc.examples import get -from desc.external.neo import NeoIO -from desc.grid import Grid, LinearGrid -from desc.integrals import Bounce2D -from desc.integrals._bounce_utils import truncate_rule -from desc.plotting import plot_boozer_surface - - -def pi_formatter(ax, NFP=1): - - def pi_form(x, pos): - multiple = np.round(NFP * x / np.pi) - if multiple == 0: - return "0" - elif multiple == 1: - return r"$\pi$" - elif multiple == -1: - return r"$-\pi$" - else: - return rf"${int(multiple)}\pi$" - - ax.set_major_locator(mticker.MultipleLocator(base=np.pi / NFP)) - ax.set_major_formatter(mticker.FuncFormatter(pi_form)) - return ax - - -def pi_half_formatter(ax, NFP=1): - - def pi_half_form(x, pos): - multiple = np.round(NFP * x / (np.pi / 2)) - if multiple == 0: - return "0" - - frac = Fraction(int(multiple), 2).limit_denominator() - num, den = frac.numerator, frac.denominator - - if num == 1: - num_str = r"\pi" - elif num == -1: - num_str = r"-\pi" - else: - num_str = rf"{num}\pi" - - return rf"${num_str}$" if (den == 1) else rf"${num_str}/{den}$" - - ax.set_major_locator(mticker.MultipleLocator(base=np.pi / 2 / NFP)) - ax.set_major_formatter(mticker.FuncFormatter(pi_half_form)) - return ax - - -def dual_pi_formatter(ax_axis, iota_NFP, NFP=1): - def major_pi_form(x, pos): - if np.isclose(x, np.pi / 2): - return "" # too close to iota tick for NFP - - multiple = np.round(NFP * x / (np.pi / 2)) - if multiple == 0: - return "0" - - frac = Fraction(int(multiple), 2 * NFP).limit_denominator() - num, den = frac.numerator, frac.denominator - - num_str = r"\pi" if num == 1 else (r"-\pi" if num == -1 else rf"{num}\pi") - return rf"${num_str}$" if (den == 1) else rf"${num_str}/{den}$" - - def minor_iota_form(x, pos): - iota_step = iota_NFP * (2 * np.pi) - multiple_iota = np.round(x / iota_step, 5) - - if np.isclose(x, 0): - return "" - - if multiple_iota % 1 == 0: - return rf"$({int(multiple_iota * 2)} \pi / N_{{\text{{FP}}}}) \iota$" - return "" - - def get_locs(base): - vmin, vmax = ax_axis.get_view_interval() - return np.arange( - np.floor(vmin / base) * base, np.ceil(vmax / base) * base + base, base - ) - - ax_axis.set_major_locator(mticker.FixedLocator(get_locs(np.pi / 2))) - ax_axis.set_major_formatter(mticker.FuncFormatter(major_pi_form)) - - ax_axis.set_minor_locator(mticker.FixedLocator(get_locs(iota_NFP * (2 * np.pi)))) - ax_axis.set_minor_formatter(mticker.FuncFormatter(minor_iota_form)) - - ax = ax_axis.axes - - ax.tick_params(axis="y", which="minor", length=3, labelsize="small") - ax.tick_params(axis="y", which="major") - - return ax_axis - - -def test_plot_bounce_point(name="W7-X", X=64, Y=64, Y_B=500, num_pitch=20): - """High resolution plot for the paper.""" - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams["font.size"] = 14 - plt.rcParams["axes.labelsize"] = 14 - plt.rcParams["xtick.labelsize"] = 13 - plt.rcParams["ytick.labelsize"] = 12 - - eq = get(name) - rho = 1.0 - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP) - data = eq.compute(Bounce2D.required_names + ["min_tz |B|", "max_tz |B|"], grid=grid) - angle = Bounce2D.angle(eq, X, Y, rho=rho) - bounce = Bounce2D(grid, data, angle, Y_B, num_transit=2) - pitch_inv, _ = Bounce2D.get_pitch_inv_quad( - grid.compress(data["min_tz |B|"]), - grid.compress(data["max_tz |B|"]), - num_pitch, - simp=False, - ) - fig, ax, legend = bounce.plot( - 0, - 0, - pitch_inv[0], - klabel=r"$\varrho$", - k_transparency=0.25, - show=False, - include_legend=False, - return_legend=True, - figsize=(8.5, 4), - title="", - markersize=plt.rcParams["lines.markersize"] * 1.5, - ) - fig.tight_layout() - ax.xaxis = pi_half_formatter(ax.xaxis) - fig.subplots_adjust(right=0.75) - - ax.spines["top"].set_visible(True) - ax.spines["right"].set_visible(True) - for spine in ax.spines.values(): - spine.set_linewidth(1.75) - - left, bottom, width, height = [0.775, 0.6, 0.1625, 0.35] - axins = fig.add_axes([left, bottom, width, height]) - line = ax.lines[0] - x_data = line.get_xdata() - y_data = line.get_ydata() - axins.plot(x_data, y_data) - - for collection in ax.collections: - offsets = collection.get_offsets() - x_scatter, y_scatter = offsets[:, 0], offsets[:, 1] - color = collection.get_facecolor() - marker = collection.get_paths()[0] - size = collection.get_sizes()[0] - axins.scatter(x_scatter, y_scatter, c=color, marker=marker, s=size) - - x1, x2 = 6, 7.2 - y1, y2 = 2.6, 2.8 - axins.set_xlim(x1, x2) - axins.set_ylim(y1, y2) - axins.spines["top"].set_visible(True) - axins.spines["right"].set_visible(True) - axins.spines["left"].set_visible(True) - axins.spines["bottom"].set_visible(True) - for spine in axins.spines.values(): - spine.set_linewidth(1.75) - - axins.tick_params( - left=False, right=True, labelleft=False, labelright=True, labelsize=11 - ) - mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5", lw=1.5, linestyle=":") - fig.legend( - legend.values(), - legend.keys(), - loc="lower right", - bbox_to_anchor=(0.925, 0.175), - labelspacing=0.1, - frameon=False, - ) - plt.savefig("bounce_point_w7x.pdf") - - -def test_plot2d_alphas(name="NCSX"): - """Plot alpha 2d plots.""" - # plotting file in utils.tar.xz - from plotting import plot_2d - - plt.rcParams["figure.constrained_layout.use"] = True - fig, axs = plt.subplots(1, 2, figsize=(7, 3), sharex=True) - - eq = get(name) - M = max(eq.M_grid, 50) - N = max(eq.N_grid, 50) - grid = LinearGrid(rho=1, M=M, N=N, NFP=eq.NFP) - iota = eq.compute("iota", grid=grid)["iota"].mean() - - kwargs = dict( - cbar_format="%.2f", - cbar_ax_tick_label_size=10, - ax_tick_params_label_size=12, - title_fontsize=14, - xlabel_fontsize=13, - ylabel_fontsize=13, - ) - with warnings.catch_warnings(): - warnings.filterwarnings("ignore", "Unequal number of field periods") - warnings.filterwarnings( - "ignore", - "Poloidal grid resolution is higher than necessary for coordinate", - ) - _, ax = plot_2d( - eq, - "|B|", - grid=grid, - ax=axs[1], - cmap="viridis", - label=r"$\vert B \vert$", - **kwargs, - ) - ax.yaxis = pi_half_formatter(ax.yaxis) - ax.xaxis = pi_half_formatter(ax.xaxis, NFP=eq.NFP) - ax.set_xlabel(r"$N_{\text{FP}} \zeta$") - ax.set_ylabel(r"$\theta$", labelpad=-5) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - custom_name = "alpha, zeta to theta - alpha" - fig, ax, t_dat = plot_2d( - eq, - custom_name, - grid=grid, - ax=axs[0], - cmap="twilight", - label=r"$\theta - \alpha$", - **kwargs, - return_data=True, - ) - ax.yaxis = dual_pi_formatter(ax.yaxis, np.abs(iota) / eq.NFP) - ax.set_xlabel(r"$N_{\text{FP}} \zeta$") - alphs = t_dat[r"$\alpha$".strip("$").strip("\\")] - theta = t_dat["alpha, zeta to theta - alpha"] + alphs - zets = t_dat[r"$\zeta$".strip("$").strip("\\")] - - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - - print(alphs.shape, theta.shape) - mid = alphs.shape[0] // 2 - tmid = (theta[mid, :] + theta[mid + 1, :]) / 2 - axs[1].plot(zets[mid], tmid, color="white", linewidth=2.5) - - plt.savefig(f"plot_2d_alphas_{name}.pdf") - - -def test_plot_theta_mod(X=64, Y=64, tol=1e-7): - """θ mod (2π).""" - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 15}) - plt.rcParams["axes.labelsize"] = 16 - plt.rcParams["xtick.labelsize"] = 15 - plt.rcParams["ytick.labelsize"] = 15 - - eq = get("NCSX") - rho = 1.0 - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP) - data = eq.compute(Bounce2D.required_names, grid=grid) - angle = Bounce2D.angle(eq, X, Y, rho, tol=tol) - bounce = Bounce2D(grid, data, angle, 1, np.array([0.0, np.pi / 2, np.pi]), 4) - - lw = 1.5 - kwargs = dict(title="", show=False, include_legend=False, lw=lw) - fig, ax = bounce.plot_theta(0, 0, **kwargs) - fig2, ax2 = bounce.plot_theta(0, 1, **kwargs) - fig3, ax3 = bounce.plot_theta(0, 2, **kwargs) - for line in ax2.lines: - x_data = line.get_xdata() - y_data = line.get_ydata() - label = line.get_label() - ax.plot(x_data, y_data, label=label, lw=lw) - for line in ax3.lines: - x_data = line.get_xdata() - y_data = line.get_ydata() - label = line.get_label() - ax.plot(x_data, y_data, label=label, lw=lw) - plt.close(fig2) - plt.close(fig3) - - ax.lines[0].set_label(r"$\alpha = 0$") - ax.lines[1].set_label(r"$\alpha = \pi/2$") - ax.lines[2].set_label(r"$\alpha = \pi$") - - for line in ax.lines: - y_data = line.get_ydata() - diffs = np.diff(y_data) - jump_indices = np.where(np.abs(diffs) > 1.9 * np.pi)[0] - y_new = y_data.copy() - y_new[jump_indices] = np.nan - line.set_ydata(y_new) - - ax.yaxis = pi_half_formatter(ax.yaxis) - ax.xaxis = pi_formatter(ax.xaxis) - ax.grid(axis="y", linestyle="--", color="gray", alpha=0.3) - ax.legend(labelspacing=0.001, framealpha=1, borderpad=0.25, fontsize=12) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.5) - - plt.savefig("theta_plot_ncsx.pdf") - - -@pytest.mark.parametrize("name, X, Y", [("NCSX", 82, 59), ("HELIOTRON", 50, 30)]) -def test_plot_angle_spectrum(name, X, Y, tol=1e-7): - """Magnitude of the spectral coefficients of α, ζ → θ − α.""" - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 16}) - plt.rcParams["axes.labelsize"] = 19 - plt.rcParams["xtick.labelsize"] = 16 - plt.rcParams["ytick.labelsize"] = 16 - - angle = Bounce2D.angle(get(name), X, Y, rho=1.0, tol=tol) - fig = Bounce2D.plot_angle_spectrum(angle, 0, title="", truncate=truncate_rule(Y)) - fig.savefig(f"angle_spectrum_{name}.pdf") - - -def test_plot_resolution_scan(name="W7-X", mode=1, top=0.0011): - """Mode 0 for compute, 1 for plot.""" - assert mode == 0 or mode == 1 - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 20}) - plt.rcParams["axes.labelsize"] = 24 - plt.rcParams["xtick.labelsize"] = 20 - plt.rcParams["ytick.labelsize"] = 20 - plt.figure(figsize=(7, 5)) - - res_table = [ - [16, 24, 12, 25], - [16, 24, 16, 50], - [24, 32, 32, 100], - # very high resolution... let's assume this one is truth to machine precision - [64, 64, 64, 200], - ] - colors = plt.rcParams["axes.prop_cycle"].by_key()["color"][: len(res_table)] - colors[3] = "purple" - linestyles = ["-", "--", ":", "-."] - - if mode == 0: - eq = get(name) - rho = jnp.linspace(0, 1, 40) - alpha = jnp.linspace(0, 2 * jnp.pi, 5, endpoint=False) - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - num_transit = 20 - pick_data = {"rho": rho, "eps_32": []} - else: - with open(f"res_scan_{name}.pkl", "rb") as file: - pick_data = pickle.load(file) - - for i, res in enumerate(res_table): - if mode == 0: - data = eq.compute( - "effective ripple 3/2", - grid=grid, - angle=Bounce2D.angle(eq, X=res[0], Y=res[1], rho=rho), - alpha=alpha, - Y_B=200, - num_transit=num_transit, - num_well=20 * num_transit, - num_quad=res[2], - num_pitch=res[3], - ) - eps_32 = grid.compress(data["effective ripple 3/2"]) - pick_data["eps_32"].append(eps_32) - continue - - plt.plot( - pick_data["rho"], - pick_data["eps_32"][i], - linewidth=2, - label=rf"${res[0], res[1], res[3], res[2]}$", - linestyle=linestyles[i % len(linestyles)], - color=colors[i], - ) - - if mode == 0: - with open(f"res_scan_{name}.pkl", "wb") as file: - pickle.dump(pick_data, file) - return - - plt.ylim(top=top) - plt.xlabel(r"$\rho$", fontsize=24) - plt.ylabel(r"$\epsilon_{\text{eff}}^{3/2}$", fontsize=24) - plt.gca().yaxis.set_minor_locator(AutoMinorLocator()) - plt.legend(fontsize=23) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2.5) - - plt.savefig(f"res_scan_{name}.pdf") - - -def test_plot_neo_compare( - pick_filename="res_scan_W7-X.pkl", - neo_filename="../../tests/inputs/neo_out.W7-X", - top=0.0011, -): - """Plot comparison to NEO.""" - with open(pick_filename, "rb") as file: - data = pickle.load(file) - - neo_rho, neo_eps_32 = NeoIO.read(neo_filename) - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 20}) - plt.rcParams["axes.labelsize"] = 24 - plt.rcParams["xtick.labelsize"] = 20 - plt.rcParams["ytick.labelsize"] = 20 - plt.figure(figsize=(7, 5)) - - plt.plot(neo_rho, neo_eps_32, "--", linewidth=3, label="NEO", color="tab:blue") - plt.plot( - data["rho"], data["eps_32"][-1], "-", linewidth=3, label="DESC", color="purple" - ) - plt.ylim(top=top) - plt.xlabel(r"$\rho$", fontsize=24) - plt.ylabel(r"$\epsilon_{\text{eff}}^{3/2}$", fontsize=24) - plt.gca().yaxis.set_minor_locator(AutoMinorLocator()) - plt.legend(fontsize=20) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2.5) - - plt.savefig("NEO_vs_DESC.pdf") - - -def test_plot_optimized_ripple(mode=1): - """Mode 0 for compute, 1 for plot.""" - assert mode == 0 or mode == 1 - - def compute(eq): - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - num_transit = 20 - data = eq.compute( - "effective ripple 3/2", - grid=grid, - angle=Bounce2D.angle(eq, X=32, Y=32, rho=rho), - alpha=jnp.linspace(0, 2 * jnp.pi, 3, endpoint=False), - Y_B=200, - num_transit=num_transit, - num_well=20 * num_transit, - num_quad=32, - num_pitch=100, - ) - return grid.compress(data["effective ripple 3/2"]) - - if mode == 0: - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - rho = jnp.linspace(0, 1, 20) - data = {"rho": rho, "eps_32_init": compute(eq0), "eps_32_opt": compute(eq1)} - with open("data_opt.pkl", "wb") as file: - pickle.dump(data, file) - return - - with open("data_opt.pkl", "rb") as file: - data = pickle.load(file) - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 22}) - plt.rcParams["axes.labelsize"] = 29 - plt.rcParams["xtick.labelsize"] = 24 - plt.rcParams["ytick.labelsize"] = 23 - plt.figure(figsize=(7, 6)) - - plt.plot( - data["rho"], - data["eps_32_init"], - "-", - linewidth=4, - label="initial", - color="tab:red", - ) - plt.plot( - data["rho"], - data["eps_32_opt"], - "-", - linewidth=4, - label="optimized", - color="tab:blue", - ) - plt.gca().xaxis.set_minor_locator(AutoMinorLocator()) - plt.gca().yaxis.set_minor_locator(AutoMinorLocator()) - plt.xlabel(r"$\rho$") - plt.ylabel(r"$\epsilon_{\text{eff}}^{3/2}$") - plt.legend(fontsize=26) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2.5) - - plt.savefig("ripple_comparison.pdf") - - -def test_plot_optimized_boozer(): - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - eq1 = flip_theta(eq1) - assert eq0.NFP == eq1.NFP - - plt.rcParams["figure.constrained_layout.use"] = True - - rho0 = 1.0 - fig, ax, Boozer_data0 = plot_boozer_surface(eq0, rho=rho0, return_data=True) - plt.close() - - fig, ax, Boozer_data1 = plot_boozer_surface(eq1, rho=rho0, return_data=True) - plt.close() - - for i, Boozer_data in enumerate([Boozer_data0, Boozer_data1]): - theta_B0 = Boozer_data["theta_B"] - zeta_B0 = Boozer_data["zeta_B"] - B0 = Boozer_data["|B|"] - - fig, ax = plt.subplots(figsize=(6, 5)) - contour = ax.contour( - zeta_B0, - theta_B0, - B0, - levels=np.linspace(np.min(B0), np.max(B0), 30), - cmap="turbo", - ) - - cbar = fig.colorbar(contour, ax=ax, orientation="vertical", format="%.2f") - cbar.ax.tick_params(labelsize=18) - ax.xaxis = pi_half_formatter(ax.xaxis, NFP=eq1.NFP) - ax.yaxis = pi_half_formatter(ax.yaxis) - ax.set_xlabel(r"$N_{\text{FP}} \zeta_{\mathrm{Boozer}}$", fontsize=24) - ax.set_ylabel(r"$\theta_{\mathrm{Boozer}}$", fontsize=24) - ax.tick_params(axis="both", which="major", labelsize=20) - - ax = plt.gca() - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2) - - plt.savefig(f"Boozer_contour_plot_{i}.pdf") - plt.close() - - -def plot_bavg_drift( - eq, rho=1.0, alphas=None, num_pitch=None, ax=None, mode=1, **kwargs -): - vmin = kwargs.pop("vmin", None) - vmax = kwargs.pop("vmax", None) - levels = kwargs.pop("levels", 30) - - plt.rcParams["figure.constrained_layout.use"] = True - nufft_eps = kwargs.pop("nufft_eps", 1e-9) - X = kwargs.pop("X", 32) - Y = kwargs.pop("Y", 32) - Y_B = kwargs.pop("Y_B", 64) - num_quad = kwargs.pop("num_quad", 32) - num_transit = kwargs.pop("num_transit", 1 if (eq.NFP > 1) else 2) - - from desc.integrals.bounce_integral import Bounce2D - - figsize = kwargs.pop("figsize", (3.5, 3)) - cmap = kwargs.pop("cmap", "turbo") - cbar_format = kwargs.pop("cbar_format", "%.2f") - cbar_ax_tick_label_size = kwargs.pop("cbar_ax_tick_label_size", 11) - ax_tick_params_label_size = kwargs.pop("ax_tick_params_label_size", 12) - xlabel_fontsize = kwargs.pop("xlabel_fontsize", 13) - ylabel_fontsize = kwargs.pop("ylabel_fontsize", 13) - - if alphas is None: - alphas = np.linspace(0, 2 * np.pi, 50) - if num_pitch is None: - num_pitch = 50 - - grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - data0 = eq.compute( - "gamma_c", - grid=grid, - angle=Bounce2D.angle(eq, X, Y, rho, tol=1e-9), - Y_B=Y_B, - num_transit=num_transit, - num_quad=num_quad, - num_pitch=num_pitch, - alpha=alphas, - nufft_eps=nufft_eps, - ) - - gamma_c = data0["gamma_c"][0].T - if mode == 0: - return gamma_c.min(), gamma_c.max() - - minB = data0["min_tz |B|"][0] - maxB = data0["max_tz |B|"][0] - pitch, _ = Bounce2D.get_pitch_inv_quad(minB, maxB, num_pitch) - - if ax is None: - fig, ax = plt.subplots(figsize=figsize) - else: - fig = ax.get_figure() - - xx, yy = np.meshgrid(alphas, pitch) - - im = ax.contourf(xx, yy, gamma_c, levels=levels, cmap=cmap, vmin=vmin, vmax=vmax) - cbar = fig.colorbar(im, format=cbar_format) - cbar.ax.tick_params(labelsize=cbar_ax_tick_label_size) - cbar.update_ticks() - - ax.xaxis = pi_half_formatter(ax.xaxis) - ax.set_xlabel(r"$\alpha$", fontsize=xlabel_fontsize) - ax.set_ylabel(r"$\varrho$", fontsize=ylabel_fontsize) - ax.tick_params(labelsize=ax_tick_params_label_size) - - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - - return fig, ax - - -def test_plot_bavg_drift(): - # use desc/compute/_fast_ion.py file in utils.tar.xz - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - eq1 = flip_theta(eq1) - assert eq0.NFP == eq1.NFP - - rho0 = 1.0 - alphas = np.linspace(0, 2 * np.pi, 100) - num_pitch = 150 - - ming, maxg = plot_bavg_drift( - eq0, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - mode=0, - ) - ming1, maxg1 = plot_bavg_drift( - eq1, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - mode=0, - ) - - vmin = min(ming, ming1) - vmax = max(maxg, maxg1) - levels = np.linspace(vmin, vmax, 30) - - fig, ax = plot_bavg_drift( - eq0, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - mode=1, - vmin=vmin, - vmax=vmax, - levels=levels, - ) - plt.savefig("raddrift_contour_plot_1.pdf") - plt.close() - - fig, ax = plot_bavg_drift( - eq1, - rho=rho0, - alphas=alphas, - num_pitch=num_pitch, - X=80, - Y=80, - Y_B=400, - num_quad=150, - vmin=vmin, - mode=1, - vmax=vmax, - levels=levels, - ) - plt.savefig("raddrift_contour_plot_2.pdf") - plt.close() - - -def test_plot_X_section(): - """Plots cross-sections of initial and optimized equilibrium.""" - # plotting file in utils.tar.xz - from plotting import plot_comparison - - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 24}) - - fig, ax = plot_comparison( - [eq0, eq1], - lw=np.array([2, 1.5]), - phi=4, - xlabel_fontsize=22, - ylabel_fontsize=22, - title_fontsize=22, - color=["tab:red", "tab:blue"], - labels=["initial", "optimized"], - rows=1, - figw=12, - legend_kw=dict(loc="lower right"), - ) - plt.savefig("Xsection_comparison.pdf") - - -def test_plot_3d(): - """Plot initial and optimized boundary in 3D.""" - # plotting file in utils.tar.xz - import os - - from plotting import plot_3d - - eq0 = Equilibrium.load("eq_initial.h5") - eq1 = Equilibrium.load("eq_optimized.h5") - plt.rcParams["figure.constrained_layout.use"] = True - - legend_list = ["initial", "optimized"] - eq_list = [eq0, eq1] - scale_list = [2, 4] - - for eq, legend, scale in zip(eq_list, legend_list, scale_list): - plt.figure() - theta_grid = np.linspace(0, 2 * np.pi, 300) - zeta_grid = np.linspace(0, 2 * np.pi, 300) - grid = LinearGrid(rho=1.0, theta=theta_grid, zeta=zeta_grid) - # May want to turn off title in source code. - fig = plot_3d( - eq, - name="|B|", - grid=grid, - showgrid=False, - zeroline=False, - showticklabels=False, - showaxislabels=False, - update_traces=dict(colorbar=dict(tickfont=dict(size=75))), - ) - - config = { - "toImageButtonOptions": { - "filename": f"modB_3d_{legend}", - "format": "svg", - "scale": scale, - } - } - save_path_html = os.getcwd() + f"/modB_3d_{legend}.html" - fig.write_html( - save_path_html, config=config, include_plotlyjs=True, full_html=True - ) - plt.close() - - -def test_plot_binormal_drift(): - """Get binormal drift plots.""" - import os - import sys - - sys.path.insert( - 0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")) - ) - from tests.test_integrals import TestBounce, TestBounce2D - - os.chdir(os.path.abspath(os.path.join(os.path.dirname(__file__), "../.."))) - - data, things = TestBounce.get_drift_analytical_data() - drift_analytical, _, _, pitch_inv = TestBounce.drift_analytical(data) - - eq = things["eq"] - grid = LinearGrid(rho=data["rho"], M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) - names = ["cvdrift (periodic)", "gbdrift (periodic)", "gbdrift (secular)/phi"] - grid_data = eq.compute(names=Bounce2D.required_names + names, grid=grid) - for name in names: - grid_data[name] = grid_data[name] * data["normalization"] - - bounce = Bounce2D( - grid, - grid_data, - Bounce2D.angle(eq, X=32, Y=32, rho=data["rho"], iota=data["iota"], tol=1e-10), - 32, - data["alpha"] - 2.5 * np.pi * data["iota"], - num_transit=3, - Bref=data["Bref"], - Lref=data["a"], - nufft_eps=0, - spline=False, - ) - points = bounce.points(pitch_inv, num_well=1) - - data = {name: Bounce2D.reshape(grid, grid_data[name]) for name in names} - drift_numerical_num, drift_numerical_den = bounce.integrate( - [TestBounce2D.drift_num_integrand, TestBounce.drift_den_integrand], - pitch_inv, - data, - points=points, - nufft_eps=0, - ) - drift_numerical = np.squeeze(drift_numerical_num / drift_numerical_den) - assert np.isfinite(drift_numerical).all() - msg = "There should be one bounce integral per pitch in this example." - assert drift_numerical.size == drift_analytical.size, msg - - plt.rcParams["figure.constrained_layout.use"] = True - plt.rcParams.update({"font.size": 17}) - plt.rcParams["axes.labelsize"] = 20 - plt.rcParams["xtick.labelsize"] = 17 - plt.rcParams["ytick.labelsize"] = 17 - fig = bounce.check_points( - (points[0][..., 5::10, :], points[1][..., 5::10, :]), - pitch_inv[5::10], - plot=True, - klabel=r"$1/(\lambda B_0)$", - k_transparency=0.25, - show=False, - vlabel=r"$\vert B \vert / B_0$", - legend_kwargs=dict( - loc="lower right", labelspacing=0.1, framealpha=1, borderpad=0.3 - ), - markersize=(plt.rcParams["lines.markersize"] ** 2) * 1.5, - title="", - linewidth=2.5, - ) - ax = plt.gca() - ax.xaxis = pi_formatter(ax.xaxis) - ax.set_yticks(np.linspace(0.95, 1.025, 4)) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2) - - plt.savefig("bavg_drift_field.pdf") - plt.close() - - fig, ax = plt.subplots() - ax.plot( - pitch_inv, - drift_analytical, - label="model", - color="black", - lw=4, - ) - - ax.plot( - pitch_inv, - drift_numerical, - label="computation", - color="tab:orange", - lw=2, - linestyle="--", - ) - ax.set_xlabel(r"$1/(\lambda B_0)$") - ax.set_ylabel(r"1/seconds") - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(2) - plt.legend() - plt.savefig("bavg_drift.pdf") - plt.close() - - -keys = [ - "kappa_g", - "|grad(rho)|", - "|e_alpha|r,p|", - "|B|", - "|B|_r|v,p", - "B^phi_r|v,p", - "gbdrift", -] - - -def _err_PEST(data_PEST, data): - return {k: np.abs(data[k] - data_PEST[k]).max() for k in keys} - - -def _err_append(err_PEST_1, err_PEST_2): - if err_PEST_1 is None: - return err_PEST_2 - return {k: np.append(err_PEST_1[k], err_PEST_2[k]) for k in keys} - - -@pytest.mark.parametrize( - "name, upscale, tol", - product(["W7-X", "NCSX"], np.array([1, 2, 3, 4]), [1e-10, 5e-7]), -) -def test_PEST_convergence_run(name, upscale, tol, maxiter=30): - """Generate data for PEST basis convergence.""" - eq = get(name) - eq_PEST = eq.to_sfl( - L=eq.L * upscale, - M=eq.M * upscale, - N=eq.N * upscale, - copy=True, - tol=tol, - maxiter=maxiter, - ) - eq.change_resolution( - L_grid=eq_PEST.L_grid, M_grid=eq_PEST.M_grid, N_grid=eq_PEST.N_grid - ) - - grid_PEST = LinearGrid( - rho=np.linspace(0.1, 1, 20), M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym - ) - grid_DESC = Grid( - eq.map_coordinates( - grid_PEST.nodes, ("rho", "theta_PEST", "zeta"), tol=tol, maxiter=maxiter - ) - ) - data_PEST = eq_PEST.compute(keys, grid_PEST) - data = eq.compute(keys, grid_DESC) - err = _err_PEST(data_PEST, data) - - grid_PEST = LinearGrid(rho=0, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=eq.sym) - grid_DESC = Grid( - eq.map_coordinates( - grid_PEST.nodes, ("rho", "theta_PEST", "zeta"), tol=tol, maxiter=maxiter - ) - ) - data_PEST = eq_PEST.compute(keys, grid_PEST) - data = eq.compute(keys, grid_DESC) - axis_err = _err_PEST(data_PEST, data) - - with open(f"{name}_{upscale}_{tol}.pkl", "wb") as file: - pickle.dump( - {"eq": eq, "eq_PEST": eq_PEST, "err": err, "axis_err": axis_err}, - file, - ) - - -def _plot_PEST_convergence(plot_data, keys, data_index, filename): - fig, axs = plt.subplots(1, 2, figsize=(8, 3.5), sharey=True) - lines, labels = [], [] - - for i, ax in enumerate(axs): - data = plot_data[i] - err = data["err"] - - for k in keys: - label_text = data_index["desc.equilibrium.equilibrium.Equilibrium"][k][ - "label" - ] - x_vals = np.arange(1, err[k].size + 1) ** 3 - line = ax.semilogy(x_vals, err[k], "--", marker="D")[0] - ax.set_xticks(x_vals) - - if i == 0: - lines.append(line) - labels.append(rf"${label_text}$") - - ax.set_title(data["title"]) - for spine in ax.spines.values(): - spine.set_visible(True) - spine.set_linewidth(1.75) - - fig.supxlabel( - "Spectral resolution ratio " - r"$(L M N)_{\vartheta, \phi} / (L M N)_{\theta, \zeta}$" - r" of $(R, Z, \Lambda, \omega)$." - ) - fig.supylabel("Absolute error") - fig.legend(handles=lines, labels=labels, loc="center right", frameon=False) - - fig.tight_layout(rect=[0, -0.05, 0.8, 1]) - plt.savefig(filename) - plt.close(fig) - - -@pytest.mark.parametrize("tol", [1e-10, 5e-7]) -def test_plot_PEST_convergence(tol, plot_axis=False): - """Saves PEST basis conversion plots for W7-X and NCSX.""" - plt.rcParams.update( - { - "axes.labelsize": 16, - "axes.titlesize": 14, - "xtick.labelsize": 12, - "ytick.labelsize": 11, - "legend.fontsize": 14, - "lines.linewidth": 2, - "lines.markersize": 5, - "axes.grid": False, - } - ) - p = "desc.equilibrium.equilibrium.Equilibrium" - data_index[p]["gbdrift"]["label"] = "(\\nabla \\vert B \\vert)_{\\mathrm{drift}}" - - configs = ["W7-X", "NCSX"] - all_data = {} - - for name in configs: - err, axis_err = None, None - for i in range(1, 5): - with open(f"{name}_{i}_{tol}.pkl", "rb") as file: - pick = pickle.load(file) - err = _err_append(err, pick["err"]) - axis_err = _err_append(axis_err, pick["axis_err"]) - all_data[name] = {"err": err, "axis_err": axis_err, "eq": get(name)} - - weq = all_data["W7-X"]["eq"] - neq = all_data["NCSX"]["eq"] - - a1 = { - "err": all_data["W7-X"]["err"], - "eq": weq, - "title": rf"W7-X $(L M N)_{{\theta, \zeta}} = ({weq.L},{weq.M},{weq.N})$", - } - a2 = { - "err": all_data["NCSX"]["err"], - "eq": neq, - "title": rf"NCSX $(L M N)_{{\theta, \zeta}} = ({neq.L},{neq.M},{neq.N})$", - } - _plot_PEST_convergence( - [a1, a2], keys, data_index, f"plot_PEST_convergence_{tol}.pdf" - ) - - if plot_axis: - a1 = { - "err": all_data["W7-X"]["axis_err"], - "eq": weq, - "title": rf"W7-X $(L,M,N)_{{\theta, \zeta}} = ({weq.L},{weq.M},{weq.N})$", - } - a2 = { - "err": all_data["NCSX"]["axis_err"], - "eq": neq, - "title": rf"NCSX $(L,M,N)_{{\theta, \zeta}} = ({neq.L},{neq.M},{neq.N})$", - } - _plot_PEST_convergence( - [a1, a2], keys, data_index, f"plot_PEST_convergence_{tol}_axis.pdf" - ) diff --git a/publications/unalmis2025/utils.tar.xz b/publications/unalmis2025/plots.tar.xz similarity index 99% rename from publications/unalmis2025/utils.tar.xz rename to publications/unalmis2025/plots.tar.xz index 72c2906503..d3eb59b4d3 100644 Binary files a/publications/unalmis2025/utils.tar.xz and b/publications/unalmis2025/plots.tar.xz differ diff --git a/publications/unalmis2025/plots_quad.py b/publications/unalmis2025/plots_quad.py deleted file mode 100644 index 81682ff1a4..0000000000 --- a/publications/unalmis2025/plots_quad.py +++ /dev/null @@ -1,419 +0,0 @@ -"""Quadrature benchmarking.""" - -import pickle - -import numpy as np -from matplotlib import pyplot as plt -from numpy.polynomial.legendre import leggauss -from scipy import integrate -from scipy.special import ellipe, ellipk - -from desc.integrals.quad_utils import ( # automorphism_arcsin,; grad_automorphism_arcsin, - automorphism_sin, - bijection_from_disc, - chebgauss1, - chebgauss2, - get_quadrature, - grad_automorphism_sin, - grad_bijection_from_disc, - leggauss_lob, - simpson2, - tanh_sinh, - uniform, -) -from desc.utils import safediv - -apprx_err = 0 -noise_level = 0 - -n = np.arange(7, 202, 2) -n[-1] = 200 -try: - with open("legs_quad.pkl", "rb") as file: - leg_gaus, leg_lobs = pickle.load(file) -except FileNotFoundError: - leg_gaus = {k: leggauss(k) for k in n} - # I enabled the tridiagonal solver in backend. - leg_lobs = {k: leggauss_lob(k, interior_only=True) for k in n} - with open("legs_quad.pkl", "wb") as file: - pickle.dump((leg_gaus, leg_lobs), file) - - -def leggauss_sin(m): - if m in leg_gaus: - m = leg_gaus[m] - else: - m = leggauss(m) - return get_quadrature(m, (automorphism_sin, grad_automorphism_sin)) - - -def leggauss_lob_sin(m): - if m in leg_lobs: - m = leg_lobs[m] - else: - m = leggauss_lob(m, interior_only=True) - return get_quadrature(m, (automorphism_sin, grad_automorphism_sin)) - - -def get_quadratures_to_test(is_F): - if is_F: - cheb = chebgauss1 - cheb_name = r"GC$_{1}$" - legs = leggauss_sin - legs_name = r"GL$_{1}$ & $\sin$" - else: - cheb = chebgauss2 - cheb_name = r"GC$_{2}$" - legs = leggauss_lob_sin - legs_name = r"GL$_{2}$ & $\sin$" - - # def cheb_arcsin(n): - # # Kosloff and Tal-Ezer almost-equispaced grid where γ = 1−β = cos(0.5). - # # Spectrally convergent with almost uniformly spaced nodes. - # return get_quadrature(cheb(n), (automorphism_arcsin, grad_automorphism_arcsin)) - - # cheb_arcsin_name = cheb_name + r" & $\arcsin$" - - quad_funs = [ - uniform, - simpson2, - tanh_sinh, - cheb, - # cheb_arcsin, - legs, - ] - names = [ - "Midpoint", - "Simpson", - "DE", - cheb_name, - # cheb_arcsin_name, - legs_name, - ] - - return quad_funs, names - - -def plot_quadratures( - truth, - fun, - n, - quad_funs, - names, - interval, - filename, - include_legend=True, - include_mach_eps=True, - simpson_lw=None, -): - eps_label = "Mach. prec.\n" + r"$5 \times 10^{-16}$" - # Free to increase eps as we please for plots so long as eps <= 1e^{-precision}. - eps = np.finfo(np.array(1.0).dtype).eps - eps = max(eps, 5e-16) - print("eps =", eps) - print("precision =", np.finfo(np.array(1.0).dtype).precision) - - fig, ax = plt.subplots(figsize=(10 if include_legend else 6.75, 6)) - - for j, quad_fun in enumerate(quad_funs): - abs_error = np.zeros(n.size) - for i, n_i in enumerate(n): - x, w = quad_fun(n_i) - x = bijection_from_disc(x, *interval) - result = fun(x).dot(w) * grad_bijection_from_disc(*interval) - abs_error[i] = np.abs(result - truth) - - linewidth = 6 - markersize = 12 - if names[j] == "Simpson": - markersize = 0 - if simpson_lw is not None: - linewidth = simpson_lw - if names[j] == "Midpoint": - markersize = 0 - - ax.semilogy( - n, - abs_error, - label=names[j], - marker="o", - linestyle="-", - markevery=slice(0, 10, 2), - markersize=markersize, - linewidth=linewidth, - ) - - if include_mach_eps: - ax.axhline(y=eps, color="black", linestyle="--", lw=5, label=eps_label) - - ax.set_xlabel(r"$N_q$", fontsize=28) - ax.set_ylabel("Abs. error", fontsize=28, labelpad=-3) - ax.set_xticks([7, 25, 50, 100, 150, 200]) - ax.tick_params(which="both", labelsize=26) - ax.grid(True, linestyle="--", linewidth=0.5, alpha=1) - ax.xaxis.get_major_ticks()[-1].gridline.set_visible(False) - - for spine in ax.spines.values(): - spine.set_linewidth(3) - - if include_legend: - fig.tight_layout(rect=[0.3, 0, 1, 1]) - fig.legend(loc="center left", frameon=False, fontsize=24) - - fig.savefig(f"{filename}_quad_compare.pdf") - return fig - - -def plot_B_and_fun(B, fun, fun_latex="", filename="example"): - fig, ax1 = plt.subplots(figsize=(10, 6)) - ax1.set_xlabel(r"$\zeta$", fontsize=28) - ax1.set_ylabel(r"$\vert B \vert$", fontsize=28) - color1, color2 = "tab:blue", "k" - ax1.tick_params(axis="x", labelsize=26) - ax1.tick_params(axis="y", labelcolor=color1, labelsize=26) - for spine in ax1.spines.values(): - spine.set_linewidth(3) - - ax2 = ax1.twinx() - ax2.set_ylabel(fun_latex, fontsize=28) - ax2.tick_params(axis="y", labelcolor=color2, labelsize=26) - - x = np.linspace(-1, 1, 1000)[1:-1] - ax1.plot(x, B(x), color=color1, label=r"$\vert B \vert$", linewidth=5) - ax2.plot(x, fun(x), "--", color=color2, label=r"$f$", linewidth=5) - - fig.tight_layout(rect=[0, 0, 0.8, 1]) - fig.legend(loc="center right", frameon=False, fontsize=26) - fig.savefig(f"{filename}.pdf") - return fig - - -class EllipticIntegral: - """Elliptic integral quadrature plotter.""" - - @staticmethod - def integrand_F(z, k): - return np.reciprocal(np.sqrt(k**2 - np.sin(z) ** 2)) - - @staticmethod - def integrand_E(z, k): - return np.sqrt(k**2 - np.sin(z) ** 2) - - @staticmethod - def analytic_F(k): - """Incomplete elliptic F(arcsin k, 1/k) / k.""" - # ellipkm1 only useful when k close to 1 s.t. 1-k is wrong - return ellipk(k**2) - - @staticmethod - def analytic_E(k): - """Incomplete elliptic E(arcsin k, 1/k) k.""" - return ellipe(k**2) + (k**2 - 1) * ellipk(k**2) - - @staticmethod - def fixed(fun, k, quad_fun, resolution): - k = np.atleast_1d(k) - b = np.arcsin(k) - a = -b - x, w = quad_fun(resolution) - z = bijection_from_disc(x, a[..., np.newaxis], b[..., np.newaxis]) - k = k[..., np.newaxis] - result = fun(z, k).dot(w) * grad_bijection_from_disc(a, b) - return result / 2 - - @staticmethod - def plot_vs_k(is_F, k, resolution, quad_fun, quad_fun_name, color=None): - fig, ax = plt.subplots(figsize=(6, 6)) - - if is_F: - fun = EllipticIntegral.integrand_F - filename = "Incomplete_elliptic_F_k" - else: - fun = EllipticIntegral.integrand_E - filename = "Incomplete_elliptic_kE" - - ax.plot( - k, - EllipticIntegral.fixed(fun, k, quad_fun, resolution), - label=quad_fun_name + rf" $(N_q = {resolution})$", - color="tab:orange" if color is None else color, - linewidth=7.5, - ) - - if is_F: - ax.plot( - k, - EllipticIntegral.analytic_F(k), - label=r"$k^{-1} F(\arcsin k, k^{-1})$", - color="black", - linewidth=5, - linestyle="--", - ) - else: - ax.plot( - k, - EllipticIntegral.analytic_E(k), - label=r"$k E(\arcsin k, k^{-1})$", - color="black", - linestyle="--", - linewidth=5, - ) - - ax.set_xlabel(r"$k$", fontsize=30) - ax.set_xticks([0, 0.2, 0.4, 0.6, 0.8, 1]) - ax.tick_params(which="both", labelsize=26) - for spine in ax.spines.values(): - spine.set_linewidth(3) - - handles, labels = ax.get_legend_handles_labels() - ax.legend( - [handles[1], handles[0]], - [labels[1], labels[0]], - fontsize=28, - loc="upper left", - frameon=False, - ) - - fig.savefig(filename + f"_vs_{quad_fun_name[:2]}_plot_vs_k.pdf") - return fig - - @staticmethod - def plot_vs_quad(is_F, k, include_legend=True): - if is_F: - fun = EllipticIntegral.integrand_F - filename = f"Incomplete_elliptic_F_k_k={k}" - truth = 2 * EllipticIntegral.analytic_F(k) - else: - fun = EllipticIntegral.integrand_E - filename = f"Incomplete_elliptic_kE_k={k}" - truth = 2 * EllipticIntegral.analytic_E(k) - - z2 = np.arcsin(k) - z1 = -z2 - - quad_funs, names = get_quadratures_to_test(is_F) - plot_quadratures( - truth=truth, - fun=lambda z: fun(z, k), - n=n, - quad_funs=quad_funs, - names=names, - interval=(z1 + apprx_err, z2 - apprx_err), - filename=filename, - include_legend=include_legend, - ) - - -class BumpyWell: - """Bounce integral on W shaped well.""" - - def bump(x, h): - """Well with bump of height h in [0, 1 - epsilon small] in middle""" - if noise_level > 0: - x = x + noise_level * np.random.randn(*np.atleast_1d(x).shape) - return h * (1 - x**2) ** 2 + x**2 + 1 - - def plot(weak, B, fun_latex, filename, h): - """Compare quadratures in W-shaped wells.""" - - def fun(x): - w = np.sqrt(np.abs(2 - B(x))) - if weak: - return safediv(1, w) - return w - - quad_funs, names = get_quadratures_to_test(weak) - m = h / (h - 1) - if weak: - true_anal = 2 / np.sqrt(1 - h) * ellipk(m) - else: - true_anal = (2 / (3 * h)) * ((2 * h - 1) * ellipe(h) + (1 - h) * ellipk(h)) - - true1, err1 = integrate.quad( - fun, - -1, - 0, - points=(-1, 0), - epsabs=1e-14, - epsrel=1e-13, - ) - true2, err2 = integrate.quad( - fun, - 0, - 1, - points=(0, 1), - epsabs=1e-14, - epsrel=1e-13, - ) - err = err1 + err2 - assert err < 1e-12 - np.testing.assert_allclose( - true1 + true2, true_anal, err_msg="Analytic result wrong." - ) - - plot_B_and_fun(B, fun, fun_latex, filename=f"{filename}_B") - plot_quadratures( - truth=true_anal, - fun=fun, - n=n, - quad_funs=quad_funs, - names=names, - interval=(-1 + apprx_err, 1 - apprx_err), - filename=filename, - include_mach_eps="0p999" not in filename, - simpson_lw=3.5 if ("0p999" in filename) else None, - ) - - @staticmethod - def run_W_well(): - """W shaped well with different quadratures.""" - hs = [0.85, 0.999, 0.85, 0.999] - examples = [ - ( - False, - lambda x: BumpyWell.bump(x, hs[0]), - r"$f = (2 - \vert B \vert)^{1/2}$", - "W_shaped_0p85", - ), - ( - False, - lambda x: BumpyWell.bump(x, hs[1]), - r"$f = (2 - \vert B \vert)^{1/2}$", - "W_shaped_0p999", - ), - ( - True, - lambda x: BumpyWell.bump(x, hs[2]), - r"$f = (2 - \vert B \vert)^{-1/2}$", - "W_shaped_0p85_weak", - ), - ( - True, - lambda x: BumpyWell.bump(x, hs[3]), - r"$f = (2 - \vert B \vert)^{-1/2}$", - "W_shaped_0p999_weak", - ), - ] - for i, example in enumerate(examples): - BumpyWell.plot(*example, h=hs[i]) - - -if __name__ == "__main__": - plt.rcParams["figure.constrained_layout.use"] = True - - k1 = np.array([0.25, 0.999]) - k2 = np.linspace(1e-3, 1, 1000, endpoint=False) - resolution = n[0] - - EllipticIntegral.plot_vs_k( - False, k2, resolution, chebgauss2, r"GC$_2$", color="tab:red" - ) - EllipticIntegral.plot_vs_k( - True, k2, resolution, leggauss_sin, r"GL$_{1}$ & $\sin$", color="tab:purple" - ) - - for is_F in (True, False): - EllipticIntegral.plot_vs_quad(is_F, k1[0], include_legend=True) - EllipticIntegral.plot_vs_quad(is_F, k1[1], include_legend=False) - - BumpyWell.run_W_well() diff --git a/publications/unalmis2025/spectral_reverse_bounce.pdf b/publications/unalmis2025/spectral_reverse_bounce.pdf index 5b95e28136..55bb034fc9 100644 Binary files a/publications/unalmis2025/spectral_reverse_bounce.pdf and b/publications/unalmis2025/spectral_reverse_bounce.pdf differ diff --git a/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf b/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf index c37eed3250..f82b0492e8 100644 Binary files a/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf and b/publications/unalmis2025/spectral_reverse_bounce_supplement.pdf differ diff --git a/requirements.txt b/requirements.txt index 5cac817f6b..53192f4be6 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,10 +1,11 @@ jax >= 0.6.2, != 0.7.1, < 0.10.0 +adv-jax-math >= 1.2, <= 1.2 colorama <= 0.4.6 diffrax >= 0.6.0, <= 0.7.2 equinox >=0.11.10, <=0.13.8 h5py >= 3.0.0, <= 3.16.0 interpax >= 0.3.3, < 0.4 -interpax_fft >= 0.0.6, <= 0.1.0 +interpax_fft >= 0.1.0, <= 0.1.0 jax-finufft >= 1.1.0, <= 1.3.1 matplotlib >= 3.7.3, <= 3.11.1 mpmath >= 1.0.0, <= 1.4.1 diff --git a/tests/baseline/test_plot_gammac.png b/tests/baseline/test_plot_gammac.png index 80234cb422..b7a1b8d147 100644 Binary files a/tests/baseline/test_plot_gammac.png and b/tests/baseline/test_plot_gammac.png differ diff --git a/tests/benchmarks/benchmark_cpu_small.py b/tests/benchmarks/benchmark_cpu_small.py index 10835235a9..9d82b6ae11 100644 --- a/tests/benchmarks/benchmark_cpu_small.py +++ b/tests/benchmarks/benchmark_cpu_small.py @@ -501,44 +501,29 @@ def run(obj, con): @pytest.mark.benchmark def test_objective_compute_ripple(benchmark): """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, False, "compute_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_compute_ripple_bounce1d(benchmark): - """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, True, "compute_scaled_error") + _test_objective_ripple(benchmark, "compute_scaled_error") @pytest.mark.slow @pytest.mark.benchmark def test_objective_grad_ripple(benchmark): """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, False, "jac_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_grad_ripple_bounce1d(benchmark): - """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, True, "jac_scaled_error") + _test_objective_ripple(benchmark, "jac_scaled_error") -def _test_objective_ripple(benchmark, use_bounce1d, method): +def _test_objective_ripple(benchmark, method): eq = desc.examples.get("W7-X") with pytest.warns(UserWarning, match="Reducing radial"): eq.change_resolution(L=eq.L // 2, M=eq.M // 2, N=eq.N // 2) - num_transit = 20 + field_period_transits = 100 objective = ObjectiveFunction( [ EffectiveRipple( eq, - num_transit=num_transit, - num_well=10 * num_transit, + field_period_transits=field_period_transits, + num_well=2 * field_period_transits, num_quad=16, - Y_B=64, - use_bounce1d=use_bounce1d, + Y_B=13, ) ] ) diff --git a/tests/benchmarks/benchmark_gpu_small.py b/tests/benchmarks/benchmark_gpu_small.py index 13a29b39b4..eec8f786d1 100644 --- a/tests/benchmarks/benchmark_gpu_small.py +++ b/tests/benchmarks/benchmark_gpu_small.py @@ -515,44 +515,29 @@ def run(obj, con): @pytest.mark.benchmark def test_objective_compute_ripple(benchmark): """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, False, "compute_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_compute_ripple_bounce1d(benchmark): - """Benchmark computing objective for effective ripple.""" - _test_objective_ripple(benchmark, True, "compute_scaled_error") + _test_objective_ripple(benchmark, "compute_scaled_error") @pytest.mark.slow @pytest.mark.benchmark def test_objective_grad_ripple(benchmark): """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, False, "jac_scaled_error") - - -@pytest.mark.slow -@pytest.mark.benchmark -def test_objective_grad_ripple_bounce1d(benchmark): - """Benchmark computing objective gradient for effective ripple.""" - _test_objective_ripple(benchmark, True, "jac_scaled_error") + _test_objective_ripple(benchmark, "jac_scaled_error") -def _test_objective_ripple(benchmark, use_bounce1d, method): +def _test_objective_ripple(benchmark, method): eq = desc.examples.get("W7-X") with pytest.warns(UserWarning, match="Reducing radial"): eq.change_resolution(L=eq.L // 2, M=eq.M // 2, N=eq.N // 2) - num_transit = 20 + field_period_transits = 100 objective = ObjectiveFunction( [ EffectiveRipple( eq, - num_transit=num_transit, - num_well=10 * num_transit, + field_period_transits=field_period_transits, + num_well=2 * field_period_transits, num_quad=16, - Y_B=64, - use_bounce1d=use_bounce1d, + Y_B=13, ) ] ) diff --git a/tests/benchmarks/memory_funcs.py b/tests/benchmarks/memory_funcs.py index 0f1250bd1e..497b8363a6 100644 --- a/tests/benchmarks/memory_funcs.py +++ b/tests/benchmarks/memory_funcs.py @@ -177,17 +177,11 @@ def test_proximal_freeb_jac_blocked(): @pytest.mark.memory def test_proximal_jac_ripple(): """Benchmark computing objective jacobian for effective ripple.""" - _test_proximal_ripple(False, "jac_scaled_error") + _test_proximal_ripple("jac_scaled_error") @pytest.mark.memory -def test_proximal_jac_ripple_bounce1d(): - """Benchmark computing objective jacobian for effective ripple.""" - _test_proximal_ripple(True, "jac_scaled_error") - - -@pytest.mark.memory -def _test_proximal_ripple(use_bounce1d, method): +def _test_proximal_ripple(method): jax.clear_caches() gc.collect() eq = desc.examples.get("HELIOTRON") @@ -195,16 +189,15 @@ def _test_proximal_ripple(use_bounce1d, method): with warnings.catch_warnings(): warnings.simplefilter("ignore") eq.change_resolution(res, res, res, 2 * res, 2 * res, 2 * res) - num_transit = 20 + field_period_transits = 100 objective = ObjectiveFunction( [ EffectiveRipple( eq, - num_transit=num_transit, - num_well=10 * num_transit, + field_period_transits=field_period_transits, + num_well=2 * field_period_transits, num_quad=16, - Y_B=64, - use_bounce1d=use_bounce1d, + Y_B=13, ) ] ) @@ -264,8 +257,6 @@ def test_objective_quadratic_flux_jac(): test_proximal_freeb_jac_blocked() elif func == "test_proximal_jac_ripple": test_proximal_jac_ripple() - elif func == "test_proximal_jac_ripple_bounce1d": - test_proximal_jac_ripple_bounce1d() elif func == "test_eq_solve": test_eq_solve() elif func == "test_objective_quadratic_flux_jac": diff --git a/tests/inputs/master_compute_data_rpz.pkl b/tests/inputs/master_compute_data_rpz.pkl index a4ac2ba3aa..6c945045a6 100644 Binary files a/tests/inputs/master_compute_data_rpz.pkl and b/tests/inputs/master_compute_data_rpz.pkl differ diff --git a/tests/inputs/neo_out.W7-X b/tests/inputs/neo_out.W7-X deleted file mode 100644 index cc716cd93c..0000000000 --- a/tests/inputs/neo_out.W7-X +++ /dev/null @@ -1,255 +0,0 @@ - 2 0.5432659069E-03 -0.2772731753E-01 0.8561233823E+00 0.2834012523E+01 0.5623110897E+01 0.5432659069E-03 0.0000000000E+00 0.8426598155E-01 0.1951917472E+00 0.8760206147E-02 0.4700376663E-01 0.1618994194E-04 - 3 0.5467057430E-03 -0.5973370290E-01 0.8562776927E+00 0.2845099983E+01 0.5623110897E+01 0.5467057430E-03 0.0000000000E+00 0.1382358383E+00 0.2045320718E+00 0.2357496515E-01 0.5160984961E-01 0.1248551365E-04 - 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angle=Bounce2D.angle(eq, X=32, Y=32, rho=rho, tol=1e-10), - Y_B=grid.num_zeta * grid.NFP, - num_transit=5, - num_well=20 * 5, - nufft_eps=1e-10, + angle=Bounce2D.angle(eq, X=32, Y=48, rho=rho, tol=1e-10), + Y_B=grid.num_zeta, + field_period_transits=25, + num_well=100, ) - data = eq.compute(fft_names, grid, **kwargs) + data = eq.compute(fft_names, grid, nufft_eps=nufft_eps, **kwargs) # check vectorization too d = data.copy() del d["Gamma_c"] - d = eq.compute("Gamma_c", grid, data=d, surf_batch_size=2, **kwargs) + d = eq.compute( + "Gamma_c", grid, data=d, surf_batch_size=2, nufft_eps=nufft_eps, **kwargs + ) np.testing.assert_allclose( d["Gamma_c"], data["Gamma_c"], @@ -346,19 +348,17 @@ def fft_grid_data(p): ) # check no nufft del d["Gamma_c"] - kwargs["nufft_eps"] = 0.0 - d = eq.compute("Gamma_c", grid, data=d, **kwargs) + data["Gamma_c no nufft"] = eq.compute( + "Gamma_c", grid, data=d, nufft_eps=0.0, **kwargs + )["Gamma_c"] np.testing.assert_allclose( - d["Gamma_c"], data["Gamma_c"], - # This is large since no nuffts + spline for bounce points - # are innaccurate due to lack of Newton step after finding bounce point - # approximation with splines. - rtol=0.2, + data["Gamma_c no nufft"], + rtol=5e-5, err_msg="Gamma_c no nufft", ) - data = apply(data, grid.compress, fft_names) + data = apply(data, grid.compress, fft_names + ["Gamma_c no nufft"]) return data @@ -372,10 +372,10 @@ def raz_grid_data(p): eq = get("W7-X") num_transit = 2 - Y_B = eq.N_grid * 2 * eq.NFP + Y_B = eq.N_grid * 2 rho = np.linspace(1e-2, 1, 10) alpha = np.array([0]) - zeta = np.linspace(0, num_transit * 2 * np.pi, num_transit * Y_B) + zeta = np.linspace(0, num_transit * 2 * np.pi, num_transit * Y_B * eq.NFP) grid = Grid.create_meshgrid([rho, alpha, zeta], coordinates="raz") data = eq.compute(raz_names, grid, num_well=20 * num_transit, tol=1e-10) diff --git a/tests/test_integrals.py b/tests/test_integrals.py index d26761ec19..65ebe45f64 100644 --- a/tests/test_integrals.py +++ b/tests/test_integrals.py @@ -34,12 +34,7 @@ surface_variance, virtual_casing_biot_savart, ) -from desc.integrals._bounce_utils import ( - _newton, - bounce_points, - check_bounce_points, - get_mins, -) +from desc.integrals._bounce_utils import _bounce_points, check_bounce_points, get_mins from desc.integrals.quad_utils import ( automorphism_sin, bijection_from_disc, @@ -732,7 +727,7 @@ def test_z1_first(self): B = CubicHermiteSpline(k, np.cos(k), -np.sin(k)) pitch_inv = 0.5 intersect = B.solve(pitch_inv, extrapolate=False) - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -748,7 +743,7 @@ def test_z2_first(self): B = CubicHermiteSpline(k, np.cos(k), -np.sin(k)) pitch_inv = 0.5 intersect = B.solve(pitch_inv, extrapolate=False) - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -767,7 +762,7 @@ def test_z1_before_extrema(self): k, np.cos(k) + 2 * np.sin(-2 * k), -np.sin(k) - 4 * np.cos(-2 * k) ) pitch_inv = B(B.derivative().roots(extrapolate=False))[3] - 1e-13 - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -792,7 +787,7 @@ def test_z2_before_extrema(self): -np.sin(k) - 4 * np.cos(-2 * k) + 1 / 4, ) pitch_inv = B(B.derivative().roots(extrapolate=False))[2] - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -813,7 +808,7 @@ def test_extrema_first_and_before_z1(self): -np.sin(k) - 4 * np.cos(-2 * k) + 1 / 20, ) pitch_inv = B(B.derivative().roots(extrapolate=False))[2] + 1e-13 - z1, z2 = bounce_points(pitch_inv, k[2:], B.c[:, 2:].T) + z1, z2 = _bounce_points(pitch_inv, k[2:], B.c[:, 2:].T, sentinel=start) check_bounce_points( z1, z2, @@ -845,7 +840,7 @@ def test_extrema_first_and_before_z2(self): -np.sin(k) - 4 * np.cos(-2 * k) + 1 / 10, ) pitch_inv = B(B.derivative().roots(extrapolate=False))[1] - 1e-13 - z1, z2 = bounce_points(pitch_inv, k, B.c.T) + z1, z2 = _bounce_points(pitch_inv, k, B.c.T, sentinel=start) check_bounce_points(z1, z2, pitch_inv, k, B.c.T, plot=True, include_knots=True) z1, z2 = TestBouncePoints.filter(z1, z2) assert z1.size and z2.size @@ -890,10 +885,7 @@ class TestBounceQuadrature: "is_strong, quad, automorphism", [ (True, tanh_sinh(30), None), - (False, tanh_sinh(20), None), (True, leggauss(25), auto_sin), - # chebgauss1 without c.o.v. is sensitive to approximation error - (True, chebgauss1(25), auto_sin), (False, leggauss_lob(8, interior_only=True), auto_sin), (False, chebgauss2(21), None), ], @@ -1099,7 +1091,7 @@ def test_bounce1d_checks(self): Bounce1D.required_names + ["min_tz |B|", "max_tz |B|", "g_zz"], grid=grid ) bounce = Bounce1D(grid, data, check=True) - pitch_inv, _ = bounce.get_pitch_inv_quad( + pitch_inv, _ = bounce.pitch_quad( min_B=grid.compress(data["min_tz |B|"]), max_B=grid.compress(data["max_tz |B|"]), num_pitch=10, @@ -1280,26 +1272,24 @@ def drift_analytical(data): + np.cos(data["theta_PEST"]) - gds21_analytic / data["shear"] * np.sin(data["theta_PEST"]) ) - gbdrift_analytic_low_order = fudge_1 * ( + gbdrift_analytical_low_order = fudge_1 * ( -data["shear"] + np.cos(data["theta_PEST"]) - gds21_analytic_low_order / data["shear"] * np.sin(data["theta_PEST"]) ) fudge_2 = 0.07 cvdrift_analytical = gbdrift_analytical + fudge_2 * alpha_MHD / B**2 - cvdrift_analytic_low_order = ( - gbdrift_analytic_low_order + fudge_2 * alpha_MHD / B0**2 + cvdrift_analytical_low_order = ( + gbdrift_analytical_low_order + fudge_2 * alpha_MHD / B0**2 ) np.testing.assert_allclose(gbdrift, gbdrift_analytical, atol=1e-2) np.testing.assert_allclose(cvdrift, cvdrift_analytical, atol=2e-2) - np.testing.assert_allclose(gbdrift, gbdrift_analytic_low_order, atol=1e-2) - np.testing.assert_allclose(cvdrift, cvdrift_analytic_low_order, atol=2e-2) + np.testing.assert_allclose(gbdrift, gbdrift_analytical_low_order, atol=1e-2) + np.testing.assert_allclose(cvdrift, cvdrift_analytical_low_order, atol=2e-2) # Exclude singularity not captured by analytic approximation for pitch near # the maximum |B|. (This is captured by the numerical integration). - pitch_inv = Bounce1D.get_pitch_inv_quad(np.min(B), np.max(B), 100, simp=False)[ - 0 - ][:-1] + pitch_inv = Bounce1D.pitch_quad(np.min(B), np.max(B), 100, simp=False)[0][:-1] k2 = 0.5 * ((1 - B0 / pitch_inv) / (epsilon * B0 / pitch_inv) + 1) I_0, I_1, I_2, I_3, I_4, I_5, I_6, I_7 = ( TestBounceQuadrature.elliptic_incomplete(k2) @@ -1342,13 +1332,18 @@ def drift_den_integrand(data, B, pitch): def test_binormal_drift_bounce1d(self): """Test bounce-averaged drift with analytical expressions.""" data, things = TestBounce.get_drift_analytical_data() - drift_analytic, cvdrift, gbdrift, pitch_inv = TestBounce.drift_analytical(data) + drift_analytical, cvdrift, gbdrift, pitch_inv = TestBounce.drift_analytical( + data + ) + + data["|B|"] /= data["Bref"] + data["|B|_z|r,a"] /= data["Bref"] + data["B^zeta"] *= data["a"] / data["Bref"] + data["B^zeta_z|r,a"] *= data["a"] / data["Bref"] bounce = Bounce1D( things["grid"].source_grid, data, - Bref=data["Bref"], - Lref=data["a"], check=True, ) points = bounce.points(pitch_inv, num_well=1) @@ -1367,16 +1362,16 @@ def test_binormal_drift_bounce1d(self): drift_numerical = np.squeeze(drift_numerical_num / drift_numerical_den) assert np.isfinite(drift_numerical).all() msg = "There should be one bounce integral per pitch in this example." - assert drift_numerical.size == drift_analytic.size, msg + assert drift_numerical.size == drift_analytical.size, msg np.testing.assert_allclose( - drift_numerical, drift_analytic, atol=5e-3, rtol=5e-2 + drift_numerical, drift_analytical, atol=5e-3, rtol=5e-2 ) TestBounce._test_bounce_autodiff(bounce, TestBounce.drift_num_integrand, data) fig, ax = plt.subplots() - ax.plot(pitch_inv, drift_analytic) + ax.plot(pitch_inv, drift_analytical) ax.plot(pitch_inv, drift_numerical) return fig @@ -1478,7 +1473,7 @@ def g(z): # dummy value; h depends on ζ alone, so doesn't matter what θ(α, ζ) is angle=Bounce2D.reshape(grid, grid.nodes[:, 1]), Y_B=2 * nyquist, - num_transit=1, + field_period_transits=1, nufft_eps=nufft_eps, ) points = np.array(0, ndmin=2), np.array(2 * np.pi, ndmin=2) @@ -1514,12 +1509,12 @@ def test_bounce2d_checks(self): data, angle, alpha=alpha, - num_transit=2, + field_period_transits=38, check=True, spline=False, quad=chebgauss1(16), # this is our own custom chebgauss1 ) - pitch_inv, _ = bounce.get_pitch_inv_quad( + pitch_inv, _ = bounce.pitch_quad( min_B=grid.compress(data["min_tz |B|"]), max_B=grid.compress(data["max_tz |B|"]), num_pitch=10, @@ -1595,7 +1590,7 @@ def _not_part_of_tutorial_test( points=points, nufft_eps=1e-7, check=True, - low_ram=True, + loop=True, ) near_zero_nufft = np.isclose(num_nufft, 0, rtol=0, atol=1e-6) near_zero = np.isclose(num, 0, rtol=0, atol=1e-6) @@ -1605,13 +1600,10 @@ def _not_part_of_tutorial_test( num_nufft[~near_zero_nufft], num[~near_zero], rtol=3e-2 ) - bounce = Bounce2D(grid, data, angle, alpha=alpha, num_transit=2, check=True) - points = bounce.points(pitch_inv) - z1, z2 = _newton( - bounce, pitch_inv[:, None], *points, points[0] < points[1], 1e-10 + bounce = Bounce2D( + grid, data, angle, alpha=alpha, field_period_transits=38, check=True ) - np.testing.assert_allclose(points[0], z1, rtol=5e-6) - np.testing.assert_allclose(points[1], z2, rtol=5e-6) + points = bounce.points(pitch_inv) bounce.check_points(points, pitch_inv, plot=False) l, m = 1, 0 @@ -1648,6 +1640,8 @@ def test_binormal_drift_bounce2d(self, nufft_eps, spline, Y_B): grid_data = eq.compute(names=Bounce2D.required_names + names, grid=grid) for name in names: grid_data[name] = grid_data[name] * data["normalization"] + grid_data["|B|"] /= data["Bref"] + grid_data["B^zeta"] *= data["a"] / data["Bref"] bounce = Bounce2D( grid, @@ -1655,9 +1649,7 @@ def test_binormal_drift_bounce2d(self, nufft_eps, spline, Y_B): Bounce2D.angle(eq, X=8, Y=8, rho=data["rho"], iota=data["iota"]), Y_B, data["alpha"] - 2.5 * np.pi * data["iota"], - num_transit=3, - Bref=data["Bref"], - Lref=data["a"], + field_period_transits=3, nufft_eps=nufft_eps, spline=spline, check=True, diff --git a/tests/test_objective_funs.py b/tests/test_objective_funs.py index f97bc93a27..e101dbd25d 100644 --- a/tests/test_objective_funs.py +++ b/tests/test_objective_funs.py @@ -2112,59 +2112,33 @@ def test(field, grid, regularization): test(field, grid, "sqrt(Phi)") @pytest.mark.unit - @pytest.mark.parametrize("use_bounce1d", [False, True]) - def test_objective_against_compute_bounce(self, use_bounce1d): + def test_objective_against_compute_bounce(self): """Test objectives are built properly.""" eq = get("W7-X") rho = np.linspace(0.1, 1, 3) - obj_grid = LinearGrid( - rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=use_bounce1d and eq.sym - ) + obj_grid = LinearGrid(rho=rho, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP, sym=False) X = 16 Y = 32 - num_transit = 4 + field_period_transits = 20 opts = dict( - Y_B=64, - num_transit=num_transit, - num_well=15 * num_transit, + Y_B=13, + field_period_transits=field_period_transits, + num_well=3 * field_period_transits, num_quad=16, num_pitch=10, ) names = ["effective ripple", "Gamma_c"] - if use_bounce1d: - names = ["old " + n for n in names] - angle = None - alpha = np.array([0.0]) - zeta = np.linspace(0, num_transit * 2 * np.pi, num_transit * opts["Y_B"]) - grid = Grid.create_meshgrid([rho, alpha, zeta], coordinates="raz") - else: - angle = Bounce2D.angle(eq, X, Y, rho) - grid = obj_grid + angle = Bounce2D.angle(eq, X, Y, rho) + grid = obj_grid data = eq.compute(names, grid, angle=angle, **opts) - obj = EffectiveRipple( - eq, - grid=obj_grid, - nufft_eps=1e-6, - use_bounce1d=use_bounce1d, - X=X, - Y=Y, - **opts, - ) + obj = EffectiveRipple(eq, grid=obj_grid, nufft_eps=1e-6, X=X, Y=Y, **opts) obj.build() assert obj._hyperparam["num_well"] == opts["num_well"] np.testing.assert_allclose( obj.compute(eq.params_dict), grid.compress(data[names[0]]) ) - obj = GammaC( - eq, - grid=obj_grid, - nufft_eps=1e-7, - use_bounce1d=use_bounce1d, - X=X, - Y=Y, - **opts, - ) + obj = GammaC(eq, grid=obj_grid, nufft_eps=1e-7, X=X, Y=Y, **opts) obj.build() assert obj._hyperparam["num_well"] == opts["num_well"] np.testing.assert_allclose( @@ -3310,8 +3284,8 @@ def _reduced_resolution_objective(eq, objective, **kwargs): if objective in {EffectiveRipple, GammaC}: kwargs["X"] = 16 kwargs["Y"] = 24 - kwargs["num_transit"] = 4 - kwargs["num_well"] = 15 * kwargs["num_transit"] + kwargs["field_period_transits"] = 10 + kwargs["num_well"] = 15 * kwargs["field_period_transits"] // eq.NFP kwargs["num_pitch"] = 24 kwargs["num_quad"] = 16 return objective(eq=eq, **kwargs) @@ -4231,22 +4205,7 @@ def test_objective_no_nangrad_effective_ripple(self): obj.build(verbose=0) g = obj.grad(obj.x()) assert not np.any(np.isnan(g)) - # This test needs high tolerance because the no nuffts + spline - # method for bounce points doesn't do a Newton step. Recall - # an O(ε) error in the spline approximation of bounce point - # yields O(ε¹ᐧ⁵) error in integrals with v_||. For the - # gradient it is probably O(ε) in general, but you'd need to work this out - # from the supplementary information. - # TODO: Reduce tolerance after someone implements the Newton step. - # (When we used to do the Newton step the atol could be 1e-6). - np.testing.assert_allclose(g, g_0, atol=0.0025) - - obj = ObjectiveFunction( - _reduced_resolution_objective(eq, EffectiveRipple, use_bounce1d=True) - ) - obj.build(verbose=0) - g = obj.grad(obj.x()) - assert not np.any(np.isnan(g)) + np.testing.assert_allclose(g, g_0, atol=1e-6) @pytest.mark.unit def test_objective_no_nangrad_Gamma_c(self): @@ -4265,22 +4224,7 @@ def test_objective_no_nangrad_Gamma_c(self): obj.build(verbose=0) g = obj.grad(obj.x()) assert not np.any(np.isnan(g)) - # This test needs high tolerance because the no nuffts + spline - # method for bounce points doesn't do a Newton step. Recall - # an O(ε) error in the spline approximation of bounce point - # yields O(ε⁰ᐧ⁵) error in integrals with 1/v_||. For the gradient - # it is probably O(ε⁰ᐧ³³) in general, but you'd need to work this out - # from the supplementary information. - # TODO: Reduce tolerance after someone implements the Newton step. - # (When we used to do the Newton step the atol could be 1e-6). - np.testing.assert_allclose(g, g_0, atol=0.042) - - obj = ObjectiveFunction( - _reduced_resolution_objective(eq, GammaC, use_bounce1d=True) - ) - obj.build(verbose=0) - g = obj.grad(obj.x()) - assert not np.any(np.isnan(g)) + np.testing.assert_allclose(g, g_0, atol=2e-5) @pytest.mark.unit def test_objective_no_nangrad_ballooning(self):