numpy.ma.mask_cols
-
numpy.ma.mask_cols(a, axis=None)
[source] -
Mask columns of a 2D array that contain masked values.
This function is a shortcut to
mask_rowcols
withaxis
equal to 1.See also
-
mask_rowcols
- Mask rows and/or columns of a 2D array.
-
masked_where
- Mask where a condition is met.
Examples
>>> 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_cols(a) masked_array(data = [[0 -- 0] [0 -- 0] [0 -- 0]], mask = [[False True False] [False True False] [False True False]], fill_value=999999)
-
© 2008–2017 NumPy Developers
Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.ma.mask_cols.html