def test_get_density(self):
"""Test FStudentT.get_density"""
n = 10
for i in range(10):
m, s, v = uniform(-10, 10), uniform(1, 10), uniform(1, 60)
x = np.random.uniform(-100, 100, n)
jx = np.ones_like(x)
f = FStudentT(x, jx, m, s, v, "test")
exp_dens = np.exp(-evaluate_studentt(x, m, s, v))
self.assertAlmostEqual(f.get_density(), exp_dens, delta=1e-6)
def test_evaluate_Dnu(self):
"""Test FStudentT.evaluate_derivative_nu"""
n = 10
for i in range(10):
m, s, v = uniform(-10, 10), uniform(1, 10), uniform(1, 60)
x = np.random.uniform(-100, 100, n)
jx = np.ones_like(x)
f = FStudentT(x, jx, m, s, v, "test")
f.update_cached_values()
exp_derv = evaluate_derivative_v(x, m, s, v)
self.assertAlmostEqual(f.evaluate_derivative_nu(), exp_derv,
delta=1e-6)
def test_update_sufficient_statistics(self):
"""Test sufficient statistics correctly updated."""
n = 10
for i in range(10):
x = np.random.uniform(-100, 100, n)
jx = 2 * np.ones_like(x)
sumx = x.sum()
sumx2 = (x**2).sum()
logJX = np.log(jx).sum()
f = FStudentT(x, jx, 1., 10., 10., "test")
stats = f.get_sufficient_statistics()
self.assertAlmostEqual(stats[0], sumx, delta=1e-4)
self.assertAlmostEqual(stats[1], sumx2, delta=1e-2)
self.assertAlmostEqual(stats[2], n, delta=1e-6)
self.assertAlmostEqual(f.get_LogJX(), logJX, delta=1e-6)
x = np.random.uniform(-100, 100, n)
jx = 3 * np.ones_like(x)
sumx = x.sum()
sumx2 = (x**2).sum()
logJX = np.log(jx).sum()
f.update_sufficient_statistics(x, jx)
stats = f.get_sufficient_statistics()
self.assertAlmostEqual(stats[0], sumx, delta=1e-4)
self.assertAlmostEqual(stats[1], sumx2, delta=1e-2)
self.assertAlmostEqual(stats[2], n, delta=1e-6)
self.assertAlmostEqual(f.get_LogJX(), logJX, delta=1e-6)
def test_create_from_sufficient_statistics(self):
"""Test constructor with sufficient stats."""
n = 10
for i in range(10):
x = np.random.uniform(-100, 100, n)
jx = 2 * np.ones_like(x)
sumx = x.sum()
sumx2 = (x**2).sum()
logJX = np.log(jx).sum()
f = FStudentT(sumx, sumx2, n, logJX, 1., 10., 10., "test")
stats = f.get_sufficient_statistics()
self.assertAlmostEqual(stats[0], sumx, delta=1e-4)
self.assertAlmostEqual(stats[1], sumx2, delta=1e-2)
self.assertAlmostEqual(stats[2], n, delta=1e-6)
self.assertAlmostEqual(f.get_LogJX(), logJX, delta=1e-6)
def test_evaluate_DFX(self):
"""Test FStudentT.evaluate_derivative_FX"""
n = 10
for i in range(10):
m, s, v = uniform(-10, 10), uniform(1, 10), uniform(1, 60)
x = np.random.uniform(-100, 100, n)
jx = np.ones_like(x)
f = FStudentT(x, jx, m, s, v, "test")
f.update_cached_values()
exp_dervs = evaluate_derivative_fx(x, m, s, v)
batch_dervs = f.evaluate_derivative_FX(x)
for i in range(n):
single_derv = f.evaluate_derivative_Fx(x[i])
self.assertAlmostEqual(single_derv, exp_dervs[i],
delta=1e-6)
self.assertAlmostEqual(batch_dervs[i], exp_dervs[i],
delta=1e-6)
def test_evaluate(self):
"""Test FStudentT.evaluate"""
n = 10
for i in range(10):
# Test Student-t
m, s, v = uniform(-10, 10), uniform(1, 10), uniform(1, 60)
x = np.random.uniform(-100, 100, n)
jx = np.ones_like(x)
f = FStudentT(x, jx, m, s, v, "test")
exp_score = evaluate_studentt(x, m, s, v)
self.assertAlmostEqual(f.evaluate(), exp_score, delta=1e-6)
# Test Log-Student-t
m, s, v = uniform(.1, 10), uniform(1, 10), uniform(1, 60)
x = np.random.uniform(.1, 100, n)
jx = 1. / x
logx = np.log(x)
logm = np.log(m)
f = FStudentT(logx, jx, logm, s, v, "test")
exp_score = evaluate_logstudentt(logx, logm, s, v)
self.assertAlmostEqual(f.evaluate(), exp_score, delta=1e-6)
def test_setters_getters(self):
f = FStudentT(*get_random_attributes())
for i in range(10):
vs = get_random_attributes()
f.set_sumFX(vs[0])
f.set_sumFX2(vs[1])
f.set_N(vs[2])
f.set_LogJX(vs[3])
f.set_FM(vs[4])
f.set_sigma(vs[5])
f.set_nu(vs[6])
self.assertAlmostEqual(f.get_sumFX(), vs[0], delta=1e-6)
self.assertAlmostEqual(f.get_sumFX2(), vs[1], delta=1e-6)
self.assertAlmostEqual(f.get_N(), vs[2], delta=1e-6)
self.assertAlmostEqual(f.get_LogJX(), vs[3], delta=1e-6)
self.assertAlmostEqual(f.get_FM(), vs[4], delta=1e-6)
self.assertAlmostEqual(f.get_sigma(), vs[5], delta=1e-6)
self.assertAlmostEqual(f.get_nu(), vs[6], delta=1e-6)