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[ENH] statistics: Speed up countnans for sparse matrices #2965

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Mar 23, 2018
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[ENH] statistics: Speed up countnans for sparse matrices #2965

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9 changes: 6 additions & 3 deletions Orange/statistics/util.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,10 +25,13 @@ def _count_nans_per_row_sparse(X, weights, dtype=None):

w = sp.coo_matrix((data_weights, (nan_rows, nan_cols)), shape=X.shape)
w = w.tocsr()
return np.asarray(w.sum(axis=1), dtype=dtype).ravel()

return np.fromiter((np.sum(row.data) for row in w), dtype=dtype)

return np.fromiter((np.isnan(row.data).sum() for row in X), dtype=dtype)
if isinstance(X, (sp.csr_matrix, sp.csc_matrix)):
X = type(X)((np.isnan(X.data), X.indices, X.indptr), X.shape)
return np.asarray(X.sum(axis=1), dtype=dtype).ravel()
else: # pragma: no cover
raise TypeError("unsupported type '{}'".format(type(X).__name__))


def sparse_count_implicit_zeros(x):
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