def testRandom2Choice(self):
n = 1000
V = numpy.array([[0.3, 0.7], [0.5, 0.5]])
J = Util.random2Choice(V, n)
self.assertAlmostEquals(numpy.sum(J[0, :]==0)/float(n), V[0, 0], places=1)
self.assertAlmostEquals(numpy.sum(J[0, :]==1)/float(n), V[0, 1], places=1)
self.assertAlmostEquals(numpy.sum(J[1, :]==0)/float(n), V[1, 0], places=1)
self.assertAlmostEquals(numpy.sum(J[1, :]==1)/float(n), V[1, 1], places=1)
#Now use a vector of probabilities
v = numpy.array([0.3, 0.7])
j = Util.random2Choice(v, n)
self.assertAlmostEquals(numpy.sum(j==0)/float(n), v[0], places=1)
self.assertAlmostEquals(numpy.sum(j==1)/float(n), v[1], places=1)
def testRandom2Choice(self):
n = 1000
V = numpy.array([[0.3, 0.7], [0.5, 0.5]])
J = Util.random2Choice(V, n)
self.assertAlmostEquals(numpy.sum(J[0, :] == 0) / float(n),
V[0, 0],
places=1)
self.assertAlmostEquals(numpy.sum(J[0, :] == 1) / float(n),
V[0, 1],
places=1)
self.assertAlmostEquals(numpy.sum(J[1, :] == 0) / float(n),
V[1, 0],
places=1)
self.assertAlmostEquals(numpy.sum(J[1, :] == 1) / float(n),
V[1, 1],
places=1)
#Now use a vector of probabilities
v = numpy.array([0.3, 0.7])
j = Util.random2Choice(v, n)
self.assertAlmostEquals(numpy.sum(j == 0) / float(n), v[0], places=1)
self.assertAlmostEquals(numpy.sum(j == 1) / float(n), v[1], places=1)
