numpy.zeros_like(a, dtype=None, order='K', subok=True)
[source]
Return an array of zeros with the same shape and type as a given array.
Parameters: |
a : array_like The shape and data-type of dtype : data-type, optional Overrides the data type of the result. New in version 1.6.0. order : {‘C’, ‘F’, ‘A’, or ‘K’}, optional Overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if New in version 1.6.0. subok : bool, optional. If True, then the newly created array will use the sub-class type of ‘a’, otherwise it will be a base-class array. Defaults to True. |
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Returns: |
out : ndarray Array of zeros with the same shape and type as |
See also
ones_like
empty_like
zeros
ones
empty
>>> x = np.arange(6) >>> x = x.reshape((2, 3)) >>> x array([[0, 1, 2], [3, 4, 5]]) >>> np.zeros_like(x) array([[0, 0, 0], [0, 0, 0]])
>>> y = np.arange(3, dtype=float) >>> y array([ 0., 1., 2.]) >>> np.zeros_like(y) array([ 0., 0., 0.])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.zeros_like.html