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# numpy.ma.notmasked_contiguous

`numpy.ma.``notmasked_contiguous`(a, axis=None)

  Find contiguous unmasked data in a masked array along the given axis.

  Parameters: | a : array_like The input array. axis : int, optional Axis along which to perform the operation. If None (default), applies to a flattened version of the array.
  Returns: | endpoints : list A list of slices (start and end indexes) of unmasked indexes in the array.

  See also

  `flatnotmasked_edges`, `flatnotmasked_contiguous`, `notmasked_edges`, `clump_masked`, `clump_unmasked`

  Notes

  Only accepts 2-D arrays at most.

  Examples

      >>> a = np.arange(9).reshape((3, 3))
      >>> mask = np.zeros_like(a)
      >>> mask[1:, 1:] = 1

      >>> ma = np.ma.array(a, mask=mask)
      >>> np.array(ma[~ma.mask])
      array([0, 1, 2, 3, 6])

      >>> np.ma.notmasked_contiguous(ma)
      [slice(0, 4, None), slice(6, 7, None)]