`numpy:asfortranarray`

Signature

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

Return an array (ndim >= 1) laid out in Fortran order in memory.

a : array_like: Input array.
dtype : str or dtype object, optional: By default, the data-type is inferred from the input data.
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

Starting with a C-contiguous array:

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

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Calling ``asfortranarray`` makes a Fortran-contiguous copy:

y = np.asfortranarray(x)
y.flags['F_CONTIGUOUS']
np.may_share_memory(x, y)

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Now, starting with a Fortran-contiguous array:

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

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

y = np.asfortranarray(x)
x is y

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