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Without numpy, ifft falls back to idft, which memoizes its multiplication factors. The first call accumulated its sum in a loop, while later calls used sum(), which since Python 3.12 uses compensated summation (and, since 3.14, for complex numbers too), so the same input gave results differing in the last bits, and test_dft_smoke failed. Compute both cases with the same loop (and the same division by (N+0j)), so the result no longer depends on whether the factors were already memoized. Add test_idft_memoized, which calls idft directly (so it also fails with numpy installed, without this change). See pjkundert#33.
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Fixes #33.
Without numpy,
ifftfalls back to the pure-Pythonidft, which memoizes its multiplication factors. The first call accumulated its sum in a loop, while later calls usedsum(), which since Python 3.12 uses compensated summation (and, since 3.14, for complex numbers too). So the same input gave results differing in the last bits, andtest_dft_smoke(which checks that memoizing doesn't change the result) failed on Python 3.14 without numpy.This computes both cases with the same loop (and the same division by
(N+0j)), so the result no longer depends on whether the factors were already memoized. The first call's numbers are unchanged.slip39/recovery/entropy.py(idft).test_idft_memoizedinslip39/recovery_test.py, which callsidftdirectly, so it also fails on currentmasterwhen numpy is installed, and passes with this change.pytest slip39/recovery_test.py: 20 passed (with numpy). Without numpy, the whole suite (minus the invoice/communications tests, which need optional packages) passed too: 47 passed, 4 skipped.