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# numpy.ma.dot

`numpy.ma.``dot`(a, b, strict=False)

  Return the dot product of two arrays.

  Note

  Works only with 2-D arrays at the moment.

  This function is the equivalent of `numpy.dot` that takes masked values into account, see `numpy.dot` for details.

  Parameters : | a, b : ndarray 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.

  See also

  `numpy.dot`
    Equivalent function for ndarrays.

  Examples

      >>> 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)