xorbits.numpy.ascontiguousarray#

xorbits.numpy.ascontiguousarray(a, dtype=None, *, like=None)[源代码]#

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

参数
  • 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.

    1.20.0(numpy) 新版功能.

返回

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

返回类型

ndarray

参见

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.

实际案例

Starting with a Fortran-contiguous array:

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

Calling ascontiguousarray 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, calling ascontiguousarray returns the same object:

>>> y = np.ascontiguousarray(x)  
>>> x is y  
True

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

This docstring was copied from numpy.