This is documentation for an old release of NumPy (version 1.13). Read this page Search for this page in the documentation of the latest stable release (version 2.2).

numpy.copy

numpy.copy(a, order='K')

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