numpy.ascontiguousarray#

numpy.ascontiguousarray(a,dtype=None,*,like=None)#

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

Parameters:

aarray_like

Input array.

dtypestr or dtype object, optional

Data-type of returned array.

likearray_like, optional

Reference object to allow the creation of arrays which are notNumPy arrays. If an array-like passed in aslike supportsthe__array_function__ protocol, the result will be definedby it. In this case, it ensures the creation of an array objectcompatible with that passed in via this argument.

New in version 1.20.0.

Returns:

outndarray

Contiguous array of same shape and content asa, with typedtypeif specified.

See also

asfortranarray

Convert input to an ndarray with column-major memory order.

require

Return an ndarray that satisfies requirements.

ndarray.flags

Information about the memory layout of the array.

Examples

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Starting with a Fortran-contiguous array:

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

Callingascontiguousarray makes a C-contiguous copy:

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

Now, starting with a C-contiguous array:

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

Then, callingascontiguousarray returns the same object:

>>>y=np.ascontiguousarray(x)>>>xisyTrue

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

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