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test: re-pin two knife-edge positions_threshold pins after the exact grid transform (PyAutoArray#519) #722

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Merged
Jammy2211 merged 1 commit into from
Sep 3, 2026
Merged

test: re-pin two knife-edge positions_threshold pins after the exact grid transform (PyAutoArray#519) #722

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16 changes: 13 additions & 3 deletions test_autolens/analysis/test_result.py
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Original file line number Diff line number Diff line change
Expand Up @@ -211,9 +211,14 @@ def test__positions_threshold_from(analysis_imaging_7x7):

result = res.Result(samples_summary=samples_summary, analysis=analysis_imaging_7x7)

assert result.positions_threshold_from() == pytest.approx(0.0019501455, 1.0e-4)
# Knife-edge pin: the fixture is exactly mirror-symmetric (lens centre and source on
# x = 0), so the point solver's branch is decided by sub-ULP tie-breaking; PyAutoArray#519's
# exact identity transform at angle 0 selected the other branch (positions_threshold
# 0.0019501455 -> 0.0019534291, positions[1].x sign flip, magnitude bit-identical). Values
# are the exact-transform branch; a 1e-15 centre nudge flips them. See PyAutoLens#721.
assert result.positions_threshold_from() == pytest.approx(0.0019534291, 1.0e-4)
assert result.positions_threshold_from(factor=5.0) == pytest.approx(
0.0097507278035, 1.0e-4
0.0097671455155, 1.0e-4
)
assert result.positions_threshold_from(minimum_threshold=10.0) == pytest.approx(
10.0, 1.0e-4
Expand Down Expand Up @@ -337,11 +342,16 @@ def test__positions_likelihood_from__mass_centre_radial_distance_min(

assert isinstance(positions_likelihood, al.PositionsLH)
assert len(positions_likelihood.positions) == 2
# Knife-edge pin: the fixture is exactly mirror-symmetric (lens centre and source on
# x = 0), so the point solver's branch is decided by sub-ULP tie-breaking; PyAutoArray#519's
# exact identity transform at angle 0 selected the other branch (positions_threshold
# 0.0019501455 -> 0.0019534291, positions[1].x sign flip, magnitude bit-identical). Values
# are the exact-transform branch; a 1e-15 centre nudge flips them. See PyAutoLens#721.
assert positions_likelihood.positions[0] == pytest.approx(
(-1.00097656e00, 5.63818622e-04), 1.0e-4
)
assert positions_likelihood.positions[1] == pytest.approx(
(1.00097656e00, -5.63818622e-04), 1.0e-4
(1.00097656e00, 5.63818622e-04), 1.0e-4
)


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