numpy.ma.mask_rowcols(a, axis=None)
[source]
Mask rows and/or columns of a 2D array that contain masked values.
Mask whole rows and/or columns of a 2D array that contain masked values. The masking behavior is selected using the axis
parameter.
axis
is None, rows and columns are masked.axis
is 0, only rows are masked.axis
is 1 or -1, only columns are masked.Parameters: |
a : array_like, MaskedArray The array to mask. If not a MaskedArray instance (or if no array elements are masked). The result is a MaskedArray with axis : int, optional Axis along which to perform the operation. If None, applies to a flattened version of the array. |
---|---|
Returns: |
a : MaskedArray A modified version of the input array, masked depending on the value of the |
Raises: |
NotImplementedError If input array |
See also
mask_rows
mask_cols
masked_where
The input array’s mask is modified by this function.
>>> import numpy.ma as ma >>> a = np.zeros((3, 3), dtype=np.int) >>> a[1, 1] = 1 >>> a array([[0, 0, 0], [0, 1, 0], [0, 0, 0]]) >>> a = ma.masked_equal(a, 1) >>> a masked_array(data = [[0 0 0] [0 -- 0] [0 0 0]], mask = [[False False False] [False True False] [False False False]], fill_value=999999) >>> ma.mask_rowcols(a) masked_array(data = [[0 -- 0] [-- -- --] [0 -- 0]], mask = [[False True False] [ True True True] [False True False]], fill_value=999999)
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.ma.mask_rowcols.html