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Module « numpy.matlib »

Fonction ones_like - module numpy.matlib

Signature de la fonction ones_like

def ones_like(a, dtype=None, order='K', subok=True, shape=None, *, device=None) 

Description

help(numpy.matlib.ones_like)

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.
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.
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.
device : str, optional
    The device on which to place the created array. Default: None.
    For Array-API interoperability only, so must be ``"cpu"`` if passed.

    .. versionadded:: 2.0.0

Returns
-------
out : ndarray
    Array of ones with the same shape and type as `a`.

See Also
--------
empty_like : Return an empty array with shape and type of input.
zeros_like : Return an array of zeros with shape and type of input.
full_like : Return a new array with shape of input filled with value.
ones : Return a new array setting values to one.

Examples
--------
>>> import numpy as np
>>> 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=float)
>>> y
array([0., 1., 2.])
>>> np.ones_like(y)
array([1.,  1.,  1.])

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