numpy.zeros_like
(a, dtype=None, order='K', subok=True, shape=None)[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 a define these same attributes of the returned array.
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 a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible.
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.
shape:int or sequence of ints, optional.
Overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied.
New in version 1.17.0.
Returns:
out:ndarray
Array of zeros with the same shape and type as a.
See also
Return an empty array with shape and type of input.
Return an array of ones with shape and type of input.
Return a new array with shape of input filled with value.
Return a new array setting values to zero.
Examples
>>> 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.])