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bundles / numpy 2.4.4 / numpy / outer

_ArrayFunctionDispatcher

numpy:outer

source: /numpy/_core/numeric.py:909

Signature

def outer(a, b, out = None)

Summary

Compute the outer product of two vectors.

Extended Summary

Given two vectors a and b of length M and N, respectively, the outer product [1] is 

[[a_0*b_0  a_0*b_1 ... a_0*b_{N-1} ]
 [a_1*b_0    .
 [ ...          .
 [a_{M-1}*b_0            a_{M-1}*b_{N-1} ]]

Parameters

a : (M,) array_like

First input vector. Input is flattened if not already 1-dimensional.

b : (N,) array_like

Second input vector. Input is flattened if not already 1-dimensional.

out : (M, N) ndarray, optional

A location where the result is stored

Returns

out : (M, N) ndarray

out[i, j] = a[i] * b[j]

Examples

Make a (*very* coarse) grid for computing a Mandelbrot set: 
import numpy as np
rl = np.outer(np.ones((5,)), np.linspace(-2, 2, 5))
rl
im = np.outer(1j*np.linspace(2, -2, 5), np.ones((5,)))
im
grid = rl + im
grid
✓
array([[-2.+2.j, -1.+2.j,  0.+2.j,  1.+2.j,  2.+2.j],
       [-2.+1.j, -1.+1.j,  0.+1.j,  1.+1.j,  2.+1.j],
       [-2.+0.j, -1.+0.j,  0.+0.j,  1.+0.j,  2.+0.j],
       [-2.-1.j, -1.-1.j,  0.-1.j,  1.-1.j,  2.-1.j],
       [-2.-2.j, -1.-2.j,  0.-2.j,  1.-2.j,  2.-2.j]])
An example using a "vector" of letters: 
x = np.array(['a', 'b', 'c'], dtype=object)
np.outer(x, [1, 2, 3])
✓
array([['a', 'aa', 'aaa'],
       ['b', 'bb', 'bbb'],
       ['c', 'cc', 'ccc']], dtype=object)

See also

einsum

einsum('i,j->ij', a.ravel(), b.ravel()) is the equivalent.

inner
linalg.outer

An Array API compatible variation of np.outer, which accepts 1-dimensional inputs only.

tensordot

np.tensordot(a.ravel(), b.ravel(), axes=((), ())) is the equivalent.

ufunc.outer

A generalization to dimensions other than 1D and other operations. np.multiply.outer(a.ravel(), b.ravel()) is the equivalent.

Aliases

  • numpy.outer