`numpy:copy`

source: /numpy/lib/_function_base_impl.py :924

Signature

def copy ( a , order = K , subok = False )

Summary

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.)
subok : bool, optional: If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (defaults to False).

Returns

arr : ndarray: Array interpretation of a.

Notes

This is equivalent to:

>>> np.array(a, copy=True)  #doctest: +SKIP

The copy made of the data is shallow, i.e., for arrays with object dtype, the new array will point to the same objects. See Examples from ndarray.copy.

Examples

import numpy as np

✓

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]
x[0] == z[0]

✗

Note that, np.copy clears previously set WRITEABLE=False flag.

a = np.array([1, 2, 3])
a.flags["WRITEABLE"] = False
b = np.copy(a)
b.flags["WRITEABLE"]
b[0] = 3
b

✓

Aliases

numpy.copy

Referenced by

This package

Other packages

astropy astropy.io.fits.fitsrec:FITS_rec.copy