numpy.ma.dot(a, b, strict=False, out=None)
[source]
Return the dot product of two arrays.
This function is the equivalent of numpy.dot
that takes masked values into account. Note that strict
and out
are in different position than in the method version. In order to maintain compatibility with the corresponding method, it is recommended that the optional arguments be treated as keyword only. At some point that may be mandatory.
Note
Works only with 2-D arrays at the moment.
Parameters: |
a, b : masked_array_like Inputs arrays. strict : bool, optional Whether masked data are propagated (True) or set to 0 (False) for the computation. Default is False. Propagating the mask means that if a masked value appears in a row or column, the whole row or column is considered masked. out : masked_array, optional Output argument. This must have the exact kind that would be returned if it was not used. In particular, it must have the right type, must be C-contiguous, and its dtype must be the dtype that would be returned for New in version 1.10.2. |
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See also
numpy.dot
>>> a = ma.array([[1, 2, 3], [4, 5, 6]], mask=[[1, 0, 0], [0, 0, 0]]) >>> b = ma.array([[1, 2], [3, 4], [5, 6]], mask=[[1, 0], [0, 0], [0, 0]]) >>> np.ma.dot(a, b) masked_array(data = [[21 26] [45 64]], mask = [[False False] [False False]], fill_value = 999999) >>> np.ma.dot(a, b, strict=True) masked_array(data = [[-- --] [-- 64]], mask = [[ True True] [ True False]], fill_value = 999999)
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.ma.dot.html