import numpy as np

Max-Min Composition given by Zadeh

def maxMin(x, y):
z = []
for x1 in x:
for y1 in y.T:
z.append(max(np.minimum(x1, y1)))
return np.array(z).reshape((x.shape[0], y.shape[1]))

Max-Product Composition given by Rosenfeld

def maxProduct(x, y):
z = []
for x1 in x:
for y1 in y.T:
z.append(max(np.multiply(x1, y1)))
return np.array(z).reshape((x.shape[0], y.shape[1]))

3 arrays for the example

r1 = np.array([[1, 0, .7], [.3, .2, 0], [0, .5, 1]])
r2 = np.array([[.6, .6, 0], [0, .6, .1], [0, .1, 0]])
r3 = np.array([[1, 0, .7], [0, 1, 0], [.7, 0, 1]])

print "R1oR2 => Max-Min :\n" + str(maxMin(r1, r2)) + "\n"
print "R1oR2 => Max-Product :\n" + str(maxProduct(r1, r2)) + "\n\n"

print "R1oR3 => Max-Min :\n" + str(maxMin(r1, r3)) + "\n"
print "R1oR3 => Max-Product :\n" + str(maxProduct(r1, r3)) + "\n\n"

print "R1oR2oR3 => Max-Min :\n" + str(maxMin(r1, maxMin(r2, r3))) + "\n"
print "R1oR2oR3 => Max-Product :\n" + str(maxProduct(r1, maxProduct(r2, r3))) + "\n\n"