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.