Store retirement_age as int16 to shrink the parameters object - #1230
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Addresses the data-type part of PSLmodels#1080. retirement_age is a whole number of years, bounded well under the int16 range, but it was stored as a float64 array of length T+S. Casting it to int16 (rounding first, which keeps behavior identical to how it is already consumed in the retire calculation) cuts that array from 8 to 2 bytes per element. A baseline SS still solves to r = 0.0628 with pension outlays unchanged, and tests/test_parameters.py passes. This is the safe, self-contained piece of PSLmodels#1080; the broader float32/float16 downcasting of other arrays would change numerical results and is left out.
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What this does
Addresses the data-type part of #1080.
retirement_ageis a whole number of years, bounded well under the int16 range, but it was stored as a float64 array of length T+S. Casting it to int16 (rounding first, which keeps behavior identical to how it is already consumed in theretirecalculation) cuts that array from 8 to 2 bytes per element.Behavior and testing
A baseline SS still solves to r = 0.0628 with pension outlays unchanged,
retireis byte-for-byte the same (44 in the default calibration), andtests/test_parameters.pypasses (16 passed).ruff check/formatclean.Scope
This is the safe, self-contained piece of #1080. The broader float32/float16 downcasting of other arrays suggested in the issue would change numerical results, and the T-dimension array truncation is a larger refactor; both are left for separate work and a maintainer decision on the accuracy/memory tradeoff.