`numpy:ascontiguousarray`

Signature

built-in ascontiguousarray ( a , dtype = None , * , like = None )

Return a contiguous array (ndim >= 1) in memory (C order).

a : array_like: Input array.
dtype : str or dtype object, optional: Data-type of returned array.
like : array_like, optional: Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.
versionadded 1.20.0

out : ndarray: Contiguous array of same shape and content as a, with type dtype if specified.

Starting with a Fortran-contiguous array:

import numpy as np
x = np.ones((2, 3), order='F')
x.flags['F_CONTIGUOUS']

✓

Calling ``ascontiguousarray`` makes a C-contiguous copy:

y = np.ascontiguousarray(x)
y.flags['C_CONTIGUOUS']
np.may_share_memory(x, y)

✓

Now, starting with a C-contiguous array:

x = np.ones((2, 3), order='C')
x.flags['C_CONTIGUOUS']

✓

Then, calling ``ascontiguousarray`` returns the same object:

y = np.ascontiguousarray(x)
x is y

✓

Note: This function returns an array with at least one-dimension (1-d) so it will not preserve 0-d arrays.