numpy.full_like(a, fill_value, dtype=None, order='K', subok=True)
[source]
Return a full array with the same shape and type as a given array.
Parameters: |
a : array_like The shape and data-type of fill_value : scalar Fill value. dtype : data-type, optional Overrides the data type of the result. 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 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 |
See also
zeros_like
ones_like
empty_like
zeros
ones
empty
full
>>> x = np.arange(6, dtype=int) >>> np.full_like(x, 1) array([1, 1, 1, 1, 1, 1]) >>> np.full_like(x, 0.1) array([0, 0, 0, 0, 0, 0]) >>> np.full_like(x, 0.1, dtype=np.double) array([ 0.1, 0.1, 0.1, 0.1, 0.1, 0.1]) >>> np.full_like(x, np.nan, dtype=np.double) array([ nan, nan, nan, nan, nan, nan])
>>> y = np.arange(6, dtype=np.double) >>> np.full_like(y, 0.1) array([ 0.1, 0.1, 0.1, 0.1, 0.1, 0.1])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.full_like.html