I am trying to generate symmetric matrices in numpy. Specifically, these matrices are to have random places entries, and in each entry the contents can be random. Along the main diagonal we are not concerned with what entries are in there, so I have randomized those as well.

The approach I have taken is to first generate a nxn all zero matrix and simply loop over the indices of the matrices. How can I do this more efficiently using numpy?

import numpy as np
import random

def empty(x, y):
    return x*0

b = np.fromfunction(empty, (n, n), dtype = int)

for i in range(0, n):
    for j in range(0, n):
        if i == j:
            b[i][j] = random.randrange(-2000, 2000)
        else:
            switch = random.random()
            random.seed()
            if switch > random.random():
                a = random.randrange(-2000, 2000)
                b[i][j] = a
                b[j][i] = a
            else:
                b[i][j] = 0
                b[j][i] = 0

You could just do something like:

import numpy as np

N = 100
b = np.random.random_integers(-2000,2000,size=(N,N))
b_symm = (b + b.T)/2

Where you can choose from whatever distribution you want in the np.random or equivalent scipy module.

Update: If you are trying to build graph-like structures, definitely check out the networkx package:

http://networkx.lanl.gov

which has a number of built-in routines to build graphs:

http://networkx.lanl.gov/reference/generators.html

Also if you want to add some number of randomly placed zeros, you can always generate a random set of indices and replace the values with zero.