numpy.asfortranarray(a, dtype=None, *, like=None)
Return an array (ndim >= 1) laid out in Fortran order in memory.
Parameters:aarray_likeInput array.
dtypestr or dtype object, optionalBy default, the data-type is inferred from the input data.
likearray_like, optionalReference 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.
Added in version 1.20.0.
Returns:outndarrayThe input a in Fortran, or column-major, order.
See also
Convert input to a contiguous (C order) array.
Convert input to an ndarray with either row or column-major memory order.
Return an ndarray that satisfies requirements.
Information about the memory layout of the array.
Examples
Starting with a C-contiguous array:
>>> importnumpyasnp>>> x=np.ones((2,3),order='C')>>> x.flags['C_CONTIGUOUS']TrueCalling asfortranarray makes a Fortran-contiguous copy:
>>> y=np.asfortranarray(x)>>> y.flags['F_CONTIGUOUS']True>>> np.may_share_memory(x,y)FalseNow, starting with a Fortran-contiguous array:
>>> x=np.ones((2,3),order='F')>>> x.flags['F_CONTIGUOUS']TrueThen, calling asfortranarray returns the same object:
>>> y=np.asfortranarray(x)>>> xisyTrueNote: This function returns an array with at least one-dimension (1-d) so it will not preserve 0-d arrays.