scikit-hep / iminuit / 33647519024

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Commit Message

fix: masked BinnedNLL gradient (#1137)

:robot: _AI text below_ :robot:

The masked renormalization correction in `BinnedNLL._grad` summed the
model gradient over both axes, which gave one scalar for all parameters.
It must give one correction per parameter. Any masked `BinnedNLL` fit
that used the analytic gradient got silently wrong results.

The mask selects along the first axis only, so for a multi-dimensional
histogram the correction must also sum over the remaining bin axes, then
reshape to broadcast over the prediction.

The existing `test_BinnedNLL_mask` uses a one-parameter 1D model, for
which the sums agree, so the bug was not seen. The new tests compare
against a numerical gradient with two parameters in 1D and with a masked
2D histogram.

Reported in #1132.

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2 of 2 new or added lines in 1 file covered. (100.0%)

8 existing lines in 1 file now uncovered.

3924 of 3939 relevant lines covered (99.62%)

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