class TestGaussD2(object):
def setUp(self):
self.m = np.ones(2)
self.invSigma = np.eye(2)
self.distr = GaussDistr(m=self.m, L=self.invSigma)
def test_dimension(self):
assert self.distr.D == self.invSigma.shape[0]
def test_cholL(self):
chol = self.distr.cholL()
assert np.allclose(np.dot(chol, chol.T), self.distr.L)
def test_logdetL(self):
logdetL = self.distr.logdetL()
assert np.allclose( np.log(np.linalg.det(self.invSigma)), logdetL)
def test_dist_mahalanobis(self, N=10):
X = np.random.randn(N, self.distr.D)
Dist = self.distr.dist_mahalanobis(X)
invSigma = self.invSigma
MyDist = np.zeros(N)
for ii in range(N):
x = X[ii] - self.m
MyDist[ii] = np.dot(x.T, np.dot(invSigma, x))
#if error, we print it out
print MyDist[ii], Dist[ii]
assert np.allclose(MyDist, Dist)
def setUp(self):
PRNG = np.random.RandomState(867)
R = PRNG.rand(10,10)
self.m = np.ones(10)
self.invSigma = 1e-4*np.eye(10)
self.distr = GaussDistr(m=self.m, L=self.invSigma)
def setUp(self): self.m = np.ones(2) self.invSigma = np.eye(2) self.distr = GaussDistr(m=self.m, L=self.invSigma)
