外部产品使用numpy/scipy [英] Outer product using numpy/scipy

问题描述

我正在使用Python 2.7，NumPy 1.6.2和SciPy 0.16.0来计算以下内容.

I am using Python 2.7, NumPy 1.6.2 and SciPy 0.16.0 to calculate the following.

我创建了一个Hadamard矩阵.我想从中获取一个向量，然后计算出它的外部乘积.这是我的代码.

I have created a Hadamard matrix. I would like to take a vector from it and compute its outer product with itself. Here is my code.

from scipy import linalg
import numpy
from numpy import linalg as np

def test():
    hadamard_matrix = linalg.hadamard(8)
    outer_product_0 = numpy.multiply(hadamard_matrix[0], hadamard_matrix[0].transpose())
    outer_product_1 = numpy.multiply(hadamard_matrix[0].transpose(), hadamard_matrix[0])

    print str(outer_product_0)
    print str(outer_product_1)

输出:

Python 2.7 (r27:82525, Jul  4 2010, 09:01:59) [MSC v.1500 32 bit (Intel)] on win32
>>> import scipytest
>>> scipytest.test()
[1 1 1 1 1 1 1 1]
[1 1 1 1 1 1 1 1]

您可以看到，我得到的不是向量，而是2X2矩阵.我在做错什么吗?

You can see that instead of getting a 2X2 matrix I am getting a vector. Am I doing something wrong?

推荐答案

有一个外部产品，它完全按照指定.

因此，大小为n的向量本身是外部乘积，将生成nxn矩阵.

So vector of size n which is outer-producted with itself would result in nxn matrix.

a = [1, 2, 3]
np.outer(a, a)

会给你

array([[1, 2, 3],
       [2, 4, 6],
       [3, 6, 9]])

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