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[FIX] stats: Fix statistics for primitive variables #3722

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Apr 5, 2019
Merged

[FIX] stats: Fix statistics for primitive variables #3722

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4 changes: 3 additions & 1 deletion Orange/statistics/util.py
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Original file line number Diff line number Diff line change
Expand Up @@ -361,7 +361,9 @@ def weighted_mean():
X.shape[0] - non_zero,
non_zero))
else:
nans = (~X.astype(bool)).sum(axis=0) if X.size else np.zeros(X.shape[1])
X_str = X.astype(str)
nans = ((X_str == "nan") | (X_str == "")).sum(axis=0) \
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I have my doubts about a literal 'nan' being treated as missing.

if X.size else np.zeros(X.shape[1])
return np.column_stack((
np.tile(np.inf, X.shape[1]),
np.tile(-np.inf, X.shape[1]),
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9 changes: 5 additions & 4 deletions Orange/tests/test_statistics.py
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Expand Up @@ -118,13 +118,14 @@ def test_stats_weights_sparse(self):

def test_stats_non_numeric(self):
X = np.array([
['', 'a', 'b'],
['a', '', 'b'],
['a', 'b', ''],
["", "a", np.nan, 0],
["a", "", np.nan, 1],
["a", "b", 0, 0],
], dtype=object)
np.testing.assert_equal(stats(X), [[np.inf, -np.inf, 0, 0, 1, 2],
[np.inf, -np.inf, 0, 0, 1, 2],
[np.inf, -np.inf, 0, 0, 1, 2]])
[np.inf, -np.inf, 0, 0, 2, 1],
[np.inf, -np.inf, 0, 0, 0, 3]])

def test_nanmin_nanmax(self):
warnings.filterwarnings("ignore", r".*All-NaN slice encountered.*")
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