SciPy, dtype=None, order='K', subok=True) = < instance at 0x7f075dd9e9e0>

Return a new array with the same shape and type as a given array.


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.


out : ndarray

Array of uninitialized (arbitrary) data with the same shape and type as a.

See also

Return an array of ones with shape and type of input.
Return an array of zeros with shape and type of input.
Return a new uninitialized array.
Return a new array setting values to one.
Return a new array setting values to zero.


This function does not initialize the returned array; to do that use zeros_like or ones_like instead. It may be marginally faster than the functions that do set the array values.


>>> a = ([1,2,3], [4,5,6])                         # a is array-like
>>> np.empty_like(a)
array([[-1073741821, -1073741821,           3],    #random
       [          0,           0, -1073741821]])
>>> a = np.array([[1., 2., 3.],[4.,5.,6.]])
>>> np.empty_like(a)
array([[ -2.00000715e+000,   1.48219694e-323,  -2.00000572e+000],#random
       [  4.38791518e-305,  -2.00000715e+000,   4.17269252e-309]])

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