Square Matrix in Python with values -1 or 0 or 1-CodePudding

I'm trying to generate a square matrix that only contains the values -1 or 0 or 1 but no other values. The matrix is used as a relationship matrix for a genetic algorithm project that I am working on. The diagonal has to be all zeros.

So far I have tried this:

import numpy as np

n = 5

M = []
for i in range(n):
   disc = random.random()
      if disc <= 0.33:
           M.append(-1)
      elif disc > 0.33 and disc <= 0.66:
           M.append(0)
      else:
           M.append(1)
                    
                    
RelMat = np.array(M).reshape(int(sqrt(n)),-1)
np.fill_diagonal(RelMat, 0)

This will yield me a matrix with all three values but it won't allow me to make it symmetrical. I have tried to multiply it with its transpose but then the values are not correct anymore.

I have also tried to get it to work with:

import numpy as np

N = 5
b = np.random.random_integers(-1,2,size=(N,N))
b_symm = (b   b.T)/2

but this will give me 0.5 as values in the matrix which pose a problem.

My main issues is the symmetry of the matrix and the condition that the matrix has to contain all three numbers. Any help is appreciated.

CodePudding user response：

numpy.triu returns the upper triangular portion of the matrix (it sets elements below the k-th diagonal to 0). You could also zero the main diagonal too in that same call (to avoid calling fill_diagonal).

After that b b.T should give you a symmetric matrix with the desired values.