def test_pdfloglikconsistency(self):
print "Testing consistency of pdf and loglik ... "
sys.stdout.flush()
p = Distributions.MixtureOfLogNormals({'K': 5})
dat = p.sample(100)
tol = 1e-6
ll = p.loglik(dat)
pdf = np.log(p.pdf(dat))
prot = {}
prot[
'message'] = 'Difference in log(p(x)) and loglik(x) MixtureOfLogNormals greater than ' + str(
tol)
prot['max diff'] = np.max(np.abs(pdf - ll))
prot['mean diff'] = np.mean(np.abs(pdf - ll))
self.assertFalse(
np.max(np.abs(ll - pdf)) > tol, Auxiliary.prettyPrintDict(prot))
def test_derivatives(self):
print "Testing derivatives w.r.t. data ... "
sys.stdout.flush()
p = Distributions.MixtureOfLogNormals({'K': 5})
dat = p.sample(100)
h = 1e-8
tol = 1e-4
y = np.array(dat.X) + h
df = p.dldx(dat)
df2 = (p.loglik(Data(y)) - p.loglik(dat)) / h
prot = {}
prot[
'message'] = 'Difference in derivative of log-likelihood for MixtureOfLogNormals greater than ' + str(
tol)
prot['max diff'] = np.max(np.abs(df - df2))
prot['mean diff'] = np.mean(np.abs(df - df2))
self.assertFalse(
np.mean(np.abs(df - df2)) > tol, Auxiliary.prettyPrintDict(prot))
