numpy.copy()

numpy.copy

numpy.copy(a, order='K') [source]

Return an array copy of the given object.

Parameters:

a : array_like

Input data.

order : {‘C’, ‘F’, ‘A’, ‘K’}, optional

Controls the memory layout of the copy. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if a is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of a as closely as possible. (Note that this function and ndarray.copy are very similar, but have different default values for their order= arguments.)

Returns:

arr : ndarray

Array interpretation of a.

Notes

This is equivalent to:

>>> np.array(a, copy=True)  

Examples

Create an array x, with a reference y and a copy z:

>>> x = np.array([1, 2, 3])
>>> y = x
>>> z = np.copy(x)

Note that, when we modify x, y changes, but not z:

>>> x[0] = 10
>>> x[0] == y[0]
True
>>> x[0] == z[0]
False

© 2008–2017 NumPy Developers
Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.copy.html

在线笔记
App下载
App下载

扫描二维码

下载编程狮App

公众号
微信公众号

编程狮公众号

意见反馈
返回顶部