def testDivision(self):
product = Gaussian(0.2, 3.0 / sqrt(10))
standard_normal = Gaussian(0.0, 1.0)
product_divided_by_standard_normal = product / standard_normal
self.assertAlmostEqual(
2.0, product_divided_by_standard_normal.mean, None,
"testDivision mean expected %.15f, got %.15f" %
(2.0, product_divided_by_standard_normal.mean),
GaussianDistributionTest.ERROR_TOLERANCE)
self.assertAlmostEqual(
3.0, product_divided_by_standard_normal.stdev, None,
"testDivision stdev expected %.15f, got %.15f" %
(3.0, product_divided_by_standard_normal.stdev),
GaussianDistributionTest.ERROR_TOLERANCE)
product2 = Gaussian((4.0 * 7.0**2 + 6.0 * 5.0**2) / (5.0**2 + 7.0**2),
sqrt((5.0**2 * 7.0**2) / (5.0**2 + 7.0**2)))
m4s5 = Gaussian(4.0, 5.0)
product2divided_by_m4s5 = product2 / m4s5
self.assertAlmostEqual(
6.0, product2divided_by_m4s5.mean, None,
"testDivision mean2 expected %.15f, got %.15f" %
(6.0, product2divided_by_m4s5.mean),
GaussianDistributionTest.ERROR_TOLERANCE)
self.assertAlmostEqual(
7.0, product2divided_by_m4s5.stdev, None,
"testDivision stdev2 expected %.15f, got %.15f" %
(7.0, product2divided_by_m4s5.stdev),
GaussianDistributionTest.ERROR_TOLERANCE)
def testMultiplication(self):
standard_normal = Gaussian(0, 1)
shifted_gaussian = Gaussian(2, 3)
product = standard_normal * shifted_gaussian
self.assertAlmostEqual(
0.2, product.mean, None,
"testMultiplication mean expected %.15f, got %.15f" %
(0.2, product.mean), GaussianDistributionTest.ERROR_TOLERANCE)
self.assertAlmostEqual(
3.0 / sqrt(10), product.stdev, None,
"testMultiplication stdev expected %.15f, got %.15f" %
(0.2, product.mean), GaussianDistributionTest.ERROR_TOLERANCE)
m4s5 = Gaussian(4, 5)
m6s7 = Gaussian(6, 7)
product2 = m4s5 * m6s7
expectedMean = (4.0 * 7.0**2 + 6.0 * 5.0**2) / (5.0**2 + 7.0**2)
self.assertAlmostEqual(
expectedMean, product2.mean, None,
"testMultiplication mean2 expected %.15f, got %.15f" %
(expectedMean, product2.mean),
GaussianDistributionTest.ERROR_TOLERANCE)
expectedSigma = sqrt((5.0**2 * 7.0**2) / (5.0**2 + 7.0**2))
self.assertAlmostEqual(
expectedSigma, product2.stdev, None,
"testMultiplication stdev2 expected %.15f, got %.15f" %
(expectedSigma, product2.stdev),
GaussianDistributionTest.ERROR_TOLERANCE)
def testLogRatioNormalization(self):
m1s2 = Gaussian(1.0, 2.0)
m3s4 = Gaussian(3.0, 4.0)
lrn = Gaussian.log_ratio_normalization(m1s2, m3s4)
answer = 2.6157405972171204
self.assertAlmostEqual(
answer, lrn, None,
"testLogRatioNormalization lrn expected %.15f, got %.15f" %
(answer, lrn), GaussianDistributionTest.ERROR_TOLERANCE)
def partial_update(self, prior, full_posterior, update_percentage):
prior_gaussian = Gaussian(prior.mean, prior.stdev)
posterior_gaussian = Gaussian(full_posterior.mean, full_posterior.stdev)
partial_precision_diff = update_percentage * (posterior_gaussian.precision - prior_gaussian.precision)
partial_precision_mean_diff = update_percentage * (posterior_gaussian.precision_mean - prior_gaussian.precision_mean)
partial_posterior_gaussian = Gaussian.from_precision_mean(
prior_gaussian.precision_mean + partial_precision_mean_diff,
prior_gaussian.precision + partial_precision_diff)
return Rating(partial_posterior_gaussian.mean,
partial_posterior_gaussian.stdev)
def testSubtraction(self):
standard_normal = Gaussian(0.0, 1.0)
abs_diff = standard_normal - standard_normal
self.assertAlmostEqual(
0.0, abs_diff, None,
"testAbsoluteDifference abs_diff expected %.15f, got %.15f" %
(0.0, abs_diff), GaussianDistributionTest.ERROR_TOLERANCE)
m1s2 = Gaussian(1.0, 2.0)
m3s4 = Gaussian(3.0, 4.0)
abs_diff2 = m1s2 - m3s4
answer = 0.4330127018922193
self.assertAlmostEqual(
0.0, abs_diff, None,
"testAbsoluteDifference abs_diff2 expected %.15f, got %.15f" %
(answer, abs_diff2), GaussianDistributionTest.ERROR_TOLERANCE)
def __init__(self, mean, variance, variable):
GaussianFactor.__init__(self, "Prior value going to %s" % variable)
self.new_message = Gaussian(mean, sqrt(variance))
new_message = Message(Gaussian.from_precision_mean(0, 0),
"message from %s to %s" % (self, variable))
self.create_variable_to_message_binding_with_message(
variable, new_message)
def testLogProductNormalization(self):
standard_normal = Gaussian(0, 1)
lpn = Gaussian.log_product_normalization(standard_normal,
standard_normal)
answer = -1.2655121234846454
self.assertAlmostEqual(
answer, lpn, None,
"testLogProductNormalization lpn expected %.15f, got %.15f" %
(answer, lpn), GaussianDistributionTest.ERROR_TOLERANCE)
m1s2 = Gaussian(1.0, 2.0)
m3s4 = Gaussian(3.0, 4.0)
lpn2 = Gaussian.log_product_normalization(m1s2, m3s4)
answer = -2.5168046699816684
self.assertAlmostEqual(
answer, lpn2, None,
"testLogProductNormalization lpn2 expected %.15f, got %.15f" %
(answer, lpn2), GaussianDistributionTest.ERROR_TOLERANCE)
