def test_solve(self, reset_randomstate):
d = 30
dg = np.linspace(1, 2, d)
root = np.random.normal(size=(d, 2))
fac = FactoredPSDMatrix(dg, root)
rhs = np.random.normal(size=(d, 5))
sr1 = fac.solve(rhs)
mat = fac.to_matrix()
sr2 = np.linalg.solve(mat, rhs)
assert_almost_equal(sr1, sr2)
def test_solve(self):
d = 30
dg = np.linspace(1, 2, d)
root = np.random.normal(size=(d, 2))
fac = FactoredPSDMatrix(dg, root)
rhs = np.random.normal(size=(d, 5))
sr1 = fac.solve(rhs)
mat = fac.to_matrix()
sr2 = np.linalg.solve(mat, rhs)
assert_almost_equal(sr1, sr2)
def test_logdet(self, reset_randomstate):
d = 30
dg = np.linspace(1, 2, d)
root = np.random.normal(size=(d, 4))
fac = FactoredPSDMatrix(dg, root)
mat = fac.to_matrix()
_, ld = np.linalg.slogdet(mat)
ld2 = fac.logdet()
assert_almost_equal(ld, ld2)
def test_logdet(self):
d = 30
dg = np.linspace(1, 2, d)
root = np.random.normal(size=(d, 4))
fac = FactoredPSDMatrix(dg, root)
mat = fac.to_matrix()
_, ld = np.linalg.slogdet(mat)
ld2 = fac.logdet()
assert_almost_equal(ld, ld2)
def test_decorrelate(self, reset_randomstate):
d = 30
dg = np.linspace(1, 2, d)
root = np.random.normal(size=(d, 4))
fac = FactoredPSDMatrix(dg, root)
mat = fac.to_matrix()
rmat = np.linalg.cholesky(mat)
dcr = fac.decorrelate(rmat)
idm = np.dot(dcr, dcr.T)
assert_almost_equal(idm, np.eye(d))
rhs = np.random.normal(size=(d, 5))
mat2 = np.dot(rhs.T, np.linalg.solve(mat, rhs))
mat3 = fac.decorrelate(rhs)
mat3 = np.dot(mat3.T, mat3)
assert_almost_equal(mat2, mat3)
def test_decorrelate(self):
d = 30
dg = np.linspace(1, 2, d)
root = np.random.normal(size=(d, 4))
fac = FactoredPSDMatrix(dg, root)
mat = fac.to_matrix()
rmat = np.linalg.cholesky(mat)
dcr = fac.decorrelate(rmat)
idm = np.dot(dcr, dcr.T)
assert_almost_equal(idm, np.eye(d))
rhs = np.random.normal(size=(d, 5))
mat2 = np.dot(rhs.T, np.linalg.solve(mat, rhs))
mat3 = fac.decorrelate(rhs)
mat3 = np.dot(mat3.T, mat3)
assert_almost_equal(mat2, mat3)
