This is documentation for an old release of NumPy (version 1.15.1). Read this page in the documentation of the latest stable release (version > 1.17).
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