def test_goodness_of_fit(self):
mx = 5
trial = 100
vals = [random.randint(0, mx).get() for _ in range(trial)]
counts = numpy.histogram(vals, bins=numpy.arange(mx + 1))[0]
expected = numpy.array([float(trial) / mx] * mx)
self.assertTrue(hypothesis.chi_square_test(counts, expected))
def test_goodness_of_fit_2(self):
mx = 5
# vals = random.randint(mx, size=(5, 20)).get()
# counts = numpy.histogram(vals, bins=numpy.arange(mx + 1))[0]
vals = random.randint(mx, size=(5, 20)).reshape(5 * 20)
counts = numpy.histogram(numpy.asarray(vals), bins=numpy.arange(mx + 1))[0]
expected = numpy.array([float(vals.size) / mx] * mx)
self.assertTrue(hypothesis.chi_square_test(counts, expected))