def test_cov_nearest_factor_homog_sparse(self, dm):
# Check that dense and sparse inputs give the same result
d = 100
# Construct a test matrix with exact factor structure
X = np.zeros((d, dm), dtype=np.float64)
x = np.linspace(0, 2 * np.pi, d)
for j in range(dm):
X[:, j] = np.sin(x * (j + 1))
mat = np.dot(X, X.T)
np.fill_diagonal(mat, np.diag(mat) + 3.1)
# Fit to dense
rslt = cov_nearest_factor_homog(mat, dm)
mat1 = rslt.to_matrix()
# Fit to sparse
smat = sparse.csr_matrix(mat)
rslt = cov_nearest_factor_homog(smat, dm)
mat2 = rslt.to_matrix()
assert_allclose(mat1, mat2, rtol=0.25, atol=1e-3)
def test_cov_nearest_factor_homog_sparse(self, dm):
# Check that dense and sparse inputs give the same result
d = 100
# Construct a test matrix with exact factor structure
X = np.zeros((d, dm), dtype=np.float64)
x = np.linspace(0, 2*np.pi, d)
for j in range(dm):
X[:, j] = np.sin(x*(j+1))
mat = np.dot(X, X.T)
np.fill_diagonal(mat, np.diag(mat) + 3.1)
# Fit to dense
rslt = cov_nearest_factor_homog(mat, dm)
mat1 = rslt.to_matrix()
# Fit to sparse
smat = sparse.csr_matrix(mat)
rslt = cov_nearest_factor_homog(smat, dm)
mat2 = rslt.to_matrix()
assert_allclose(mat1, mat2, rtol=0.25, atol=1e-3)
def test_cov_nearest_factor_homog(self, dm):
d = 100
# Construct a test matrix with exact factor structure
X = np.zeros((d, dm), dtype=np.float64)
x = np.linspace(0, 2 * np.pi, d)
for j in range(dm):
X[:, j] = np.sin(x * (j + 1))
mat = np.dot(X, X.T)
np.fill_diagonal(mat, np.diag(mat) + 3.1)
# Try to recover the structure
rslt = cov_nearest_factor_homog(mat, dm)
mat1 = rslt.to_matrix()
assert_allclose(mat, mat1, rtol=0.25, atol=1e-3)
def test_cov_nearest_factor_homog(self, dm):
d = 100
# Construct a test matrix with exact factor structure
X = np.zeros((d, dm), dtype=np.float64)
x = np.linspace(0, 2*np.pi, d)
for j in range(dm):
X[:, j] = np.sin(x*(j+1))
mat = np.dot(X, X.T)
np.fill_diagonal(mat, np.diag(mat) + 3.1)
# Try to recover the structure
rslt = cov_nearest_factor_homog(mat, dm)
mat1 = rslt.to_matrix()
assert_allclose(mat, mat1, rtol=0.25, atol=1e-3)
def test_cov_nearest_factor_homog(self):
d = 100
for dm in 1,2:
# Construct a test matrix with exact factor structure
X = np.zeros((d,dm), dtype=np.float64)
x = np.linspace(0, 2*np.pi, d)
for j in range(dm):
X[:,j] = np.sin(x*(j+1))
mat = np.dot(X, X.T)
np.fill_diagonal(mat, np.diag(mat) + 3.1)
# Try to recover the structure
rslt = cov_nearest_factor_homog(mat, dm)
mat1 = rslt.to_matrix()
assert(np.abs(mat - mat1).max() < 1e-4)
