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fix: draw_randomly_via_pdf normalises sample weights - #1751
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np.random.choice requires probabilities summing to 1; test-mode bypass samples (weights 1, 0.5, 0.25, 0.125) made every draw raise. Normalise as samples_drawn_randomly_via_pdf already does. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Workspace PR: PyAutoLabs/autolens_workspace#613 |
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Summary
SamplesPDF.draw_randomly_via_pdfpassed the raw sample weights tonp.random.choice, which requires them to sum to 1. The test-mode bypass samples (PYAUTO_TEST_MODE=2, weights[1.0, 0.5, 0.25, 0.125], sum 1.875) therefore made every draw raiseValueError: probabilities do not sum to 1. That blocks the smoke run of any workspace script that draws from a posterior, including the new magnification-error sections in theautolens_workspacesource_science scripts (PyAutoLabs/autolens_workspace#610).The weights are now normalised before the draw, as
samples_drawn_randomly_via_pdfalready does. The test-mode weights themselves are unchanged (they are locked bytest__env_unset__legacy_four_samples_byte_identical).Heart was RED at ship time (release integrate stage; reasons quoted on autolens_workspace#610). The human authorised development under the Heart RED override for this task on 2026-10-31 and chose "Fix PyAutoFit first" for this blocker. Merge requires its own human /prm.
API Changes
None to signatures.
draw_randomly_via_pdfnow accepts sample weights that do not sum exactly to 1 (normalising them), instead of raising.See full details below.
Test Plan
test__draw_randomly_via_pdf__weights_not_summing_to_one— fails without the change, passes with itpython -m pytest test_autofit— 4171 passed, 2 skipped, 1 xfailedsource_science.pysmoke runs (PYAUTO_TEST_MODE=2, PYAUTO_SMALL_DATASETS=1) pass with this branch; all three failed on mainFull API Changes (for automation & release notes)
Changed
SamplesPDF.draw_randomly_via_pdf(as_instance=True, as_dict=False)— sample weights are normalised to sum to 1 before drawing.Migration
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