fix: guard against ZeroDivisionError in Comparitor._calc_stats#566
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haoyu-haoyu wants to merge 3 commits intoMIT-LCP:mainfrom
Open
fix: guard against ZeroDivisionError in Comparitor._calc_stats#566haoyu-haoyu wants to merge 3 commits intoMIT-LCP:mainfrom
haoyu-haoyu wants to merge 3 commits intoMIT-LCP:mainfrom
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When there are no reference annotations (tp + fn == 0) or no test annotations (n_test == 0), computing sensitivity and positive predictivity raises ZeroDivisionError. Return NaN instead, matching the convention used by sklearn.metrics for undefined ratios. Fixes MIT-LCP#278
Cover three boundary scenarios that previously raised ZeroDivisionError: - Empty reference, non-empty test → sensitivity=NaN, PPV=0.0 - Non-empty reference, empty test → sensitivity=0.0, PPV=NaN - Both empty → both NaN
The existing test_qrs class uses lowercase naming which pytest's default collection does not pick up. Move the new empty-annotation tests to module level so they are actually discovered and run in CI.
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Summary
Guard against
ZeroDivisionErrorwhen comparing annotations with empty reference or test arrays.Bug
Comparitor._calc_stats()dividestpby(tp + fn)for sensitivity and byn_testfor positive predictivity without checking for zero denominators. When either annotation array is empty, this raisesZeroDivisionError.Fix
Return
float("nan")when the denominator is zero, matching the convention used bysklearn.metricsfor undefined ratios.Tests
Three module-level test functions covering all edge cases:
Fixes #278