safe_mask#

sklearn.utils.safe_mask(X, mask)[source]#

Return a mask which is safe to use on X.

Parameters:

X{array-like, sparse matrix}: Data on which to apply mask.
maskarray-like: Mask to be used on X.

Returns:

maskndarray: Array that is safe to use on X.

Examples

>>> from sklearn.utils import safe_mask
>>> from scipy.sparse import csr_matrix
>>> data = csr_matrix([[1], [2], [3], [4], [5]])
>>> condition = [False, True, True, False, True]
>>> mask = safe_mask(data, condition)
>>> data[mask].toarray()
array([[2],
       [3],
       [5]])