nlcpy.add = <ufunc 'nlcpy_add'>

Computes the element-wise addition of the inputs.

x1, x2array_like

The arrays to be added. If x1.shape != x2.shape, they must be broadcastable to a common shape (which becomes the shape of the output).

outndarray or None, optional

A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

wherearray_like, optional

This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None, locations within it where the condition is False will remain uninitialized.


For other keyword-only arguments, see the section Optional Keyword Arguments.


The sum of x1 and x2, element-wise. If x1 and x2 are both scalars, this function returns the result as a 0-dimension ndarray.


Equivalent to x1 + x2 in terms of array broadcasting.


>>> import nlcpy as vp
>>> vp.add(1.0, 4.0)
>>> x1 = vp.arange(9.0).reshape((3, 3))
>>> x2 = vp.arange(3.0)
>>> vp.add(x1,x2)
array([[ 0.,  2.,  4.],
       [ 3.,  5.,  7.],
       [ 6.,  8., 10.]])