numpy.ones_like¶
- numpy.ones_like(a, dtype=None, order='K', subok=True)[source]¶
Return an array of ones 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.
Returns: out : ndarray
Array of ones with the same shape and type as a.
See also
- zeros_like
- Return an array of zeros with shape and type of input.
- empty_like
- Return an empty array with shape and type of input.
- zeros
- Return a new array setting values to zero.
- ones
- Return a new array setting values to one.
- empty
- Return a new uninitialized array.
Examples
>>> x = np.arange(6) >>> x = x.reshape((2, 3)) >>> x array([[0, 1, 2], [3, 4, 5]]) >>> np.ones_like(x) array([[1, 1, 1], [1, 1, 1]])
>>> y = np.arange(3, dtype=np.float) >>> y array([ 0., 1., 2.]) >>> np.ones_like(y) array([ 1., 1., 1.])