用numpy执行外部加法 [英] performing outer addition with numpy

问题描述

很抱歉，如果这是一个愚蠢的问题，但是我刚开始使用python/numpy，我真的不确定最有效的处理方法.我正在为一些学生准备一个演示N体模拟器，但是现在，我正在通过循环这些粒子的位置来计算粒子之间的力，这可以想象与糖蜜一样慢.基本上，给定向量x[i]，我想计算:

Sorry if this is a silly question but I am just getting started with python/numpy and I'm really not sure of the most efficient ways to go about things. I'm putting together a demo N-body simulator for some students, but for now, I am computing the force between particles by looping over the positions of those particles which is predictably as slow as molasses. Basically, given a vector x[i], I would like to compute:

n[i] = sum from j = 0 to n-1, j != i of (x[i]-x[j])^-2,

使用numpy函数而不是循环.如果可以执行外部加法/乘法:

using numpy functions rather than looping. If there is a way to perform outer addition/multiplication:

m[i,j] = x[i]-x[j],

m[i,j] = x[i]*x[j],

我可以用它来进行计算.

I could use that to do the computation.

推荐答案

所有带有两个输入参数的通用函数都具有属性outer:

All universal functions that take two input arguments have an attribute outer:

x = np.array([1, 2, 3])
np.subtract.outer(x, x)

给予:

array([[ 0, -1, -2],
       [ 1,  0, -1],
       [ 2,  1,  0]])

和

np.multiply.outer(x, x)

导致:

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

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