numpy.copy()

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

Return an array copy of the given object.

Parameters:

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 :meth:ndarray.copy are very similar, but have different default values for their order= arguments.)
Returns:	arr : ndarray Array interpretation of `a`.

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 :meth: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

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.copy.html

doc_NumPy

2017-01-10 18:13:07

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