nums.numpy.copy

nums.numpy.copy(a: nums.core.array.blockarray.BlockArray, order='K', subok=False)

Return an array copy of the given object.

This docstring was copied from numpy.copy.

Some inconsistencies with the NumS version may exist.

aBlockArray

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 BlockArray.copy() are very similar, but have different default values for their order= arguments.)

subokbool, 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).

arrBlockArray

Array interpretation of a.

copy : Preferred method for creating an array copy

This is equivalent to:

>>> nps.array(a, copy=True).get()  

Only default args supported.

The doctests shown below are copied from NumPy. They won’t show the correct result until you operate get().

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

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

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

>>> x[0] = 10  
>>> (x[0] == y[0]).get()  
array(True)
>>> (x[0] == z[0]).get()  
False