yzhao062 / pyod / 35066925458

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master: 93%

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github

Committed by web-flow

Commit Message

Iterate over rows in the unweighted branch of pearsonr_mat (#731)

`pearsonr_mat` builds an `(n_row, n_row)` matrix and fills it pairwise,
but the unweighted branch runs its outer loop over `n_col`:

    if w is not None:
        for cx in range(n_row):
            ...
    else:
        for cx in range(n_col):

The weighted branch directly above uses `n_row`, and the docstring
describes the result as "Row-wise pearson score matrix" of shape
(n_samples, n_samples).

When there are fewer columns than rows, every pair with `cx >= n_col` is
skipped and those cells keep the value the matrix was initialised with,
so the function reports a correlation of exactly 1.0 for pairs it never
looked at. On a (50, 4) matrix, 2070 of 2500 entries are wrong, with
errors up to 2.0.

Output is unchanged whenever `n_col >= n_row - 1`, and the weighted
branch is untouched. `n_col` has no remaining reader, so it goes too.

The existing test uses a (10, 20) matrix, which is in the unaffected
range, and only checks the shape; the added test compares every entry
against `scipy.stats.pearsonr` on an (8, 3) matrix.

Coverage Stats

10 of 10 new or added lines in 2 files covered. (100.0%)

1 existing line in 1 file now uncovered.

19258 of 20793 relevant lines covered (92.62%)

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