nums.numpy.copy

nums.numpy.copy(a, order='K', subok=False)[source]

Return an array copy of the given object.

This docstring was copied from numpy.copy.

Some inconsistencies with the NumS version may exist.

Parameters

a (BlockArray) – 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.)
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 – Array interpretation of a.

Return type

BlockArray

See also

Notes

This is equivalent to:

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

Only default args supported.

Examples

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

nums.numpy.transpose

nums.numpy.min