def test_kmr_matrix():
"""Test with KMR matrices"""
print(__name__ + '.' + test_kmr_matrix.__name__)
matrices = Matrices()
for matrix_dict in matrices.kmr_matrix_dicts:
x = gth_solve(matrix_dict['A'])
yield StationaryDistSumOne(), x
yield StationaryDistNonnegative(), x
yield StationaryDistLeftEigenVec(), matrix_dict['A'], x
def test_stoch_matrix():
"""Test with stochastic matrices"""
print(__name__ + '.' + test_stoch_matrix.__name__)
matrices = Matrices()
for matrix_dict in matrices.stoch_matrix_dicts:
x = gth_solve(matrix_dict['A'])
yield StationaryDistSumOne(), x
yield StationaryDistNonnegative(), x
yield StationaryDistEqualToKnown(), matrix_dict['stationary_dist'], x
def test_stoch_matrix():
"""Test with stochastic matrices"""
print(__name__ + '.' + test_stoch_matrix.__name__)
matrices = Matrices()
for matrix_dict in matrices.stoch_matrix_dicts:
x = gth_solve(matrix_dict['A'])
yield StationaryDistSumOne(), x
yield StationaryDistNonnegative(), x
yield StationaryDistEqualToKnown(), matrix_dict['stationary_dist'], x
def test_kmr_matrix():
"""Test with KMR matrices"""
print(__name__ + '.' + test_kmr_matrix.__name__)
matrices = Matrices()
for matrix_dict in matrices.kmr_matrix_dicts:
x = gth_solve(matrix_dict['A'])
yield StationaryDistSumOne(), x
yield StationaryDistNonnegative(), x
yield StationaryDistLeftEigenVec(), matrix_dict['A'], x
def test_matrices_with_C_F_orders():
"""
Test matrices with C- and F-contiguous orders
See the issue and fix on Numba:
github.com/numba/numba/issues/1103
github.com/numba/numba/issues/1104
Fix in gth_solve(A):
added `order='C'` when `A1` copies the input `A`
"""
P_C = np.array([[0.5, 0.5], [0, 1]], order='C')
P_F = np.array([[0.5, 0.5], [0, 1]], order='F')
stationary_dist = [0., 1.]
computed_C_and_F = gth_solve(np.array([[1]]))
assert_array_equal(computed_C_and_F, [1])
computed_C = gth_solve(P_C)
computed_F = gth_solve(P_F)
assert_array_equal(computed_C, stationary_dist)
assert_array_equal(computed_F, stationary_dist)
def test_matrices_with_C_F_orders():
"""
Test matrices with C- and F-contiguous orders
See the issue and fix on Numba:
github.com/numba/numba/issues/1103
github.com/numba/numba/issues/1104
Fix in gth_solve(A):
added `order='C'` when `A1` copies the input `A`
"""
P_C = np.array([[0.5, 0.5], [0, 1]], order='C')
P_F = np.array([[0.5, 0.5], [0, 1]], order='F')
stationary_dist = [0., 1.]
computed_C_and_F = gth_solve(np.array([[1]]))
assert_array_equal(computed_C_and_F, [1])
computed_C = gth_solve(P_C)
computed_F = gth_solve(P_F)
assert_array_equal(computed_C, stationary_dist)
assert_array_equal(computed_F, stationary_dist)
def test_gen_matrix_1():
"""Test with generator matrices"""
matrices = Matrices()
for matrix_dict in matrices.gen_matrix_dicts:
x = gth_solve(matrix_dict['A'])
StationaryDistEqualToKnown()(matrix_dict['stationary_dist'], x)
def test_gen_matrix(test_class):
"""Test with generator matrices"""
matrices = Matrices()
for matrix_dict in matrices.gen_matrix_dicts:
x = gth_solve(matrix_dict['A'])
test_class()(x)
def test_kmr_matrix_1():
"""Test with KMR matrices"""
matrices = Matrices()
for matrix_dict in matrices.kmr_matrix_dicts:
x = gth_solve(matrix_dict['A'])
StationaryDistLeftEigenVec()(matrix_dict['A'], x)
def test_kmr_matrix(test_class):
"""Test with KMR matrices"""
matrices = Matrices()
for matrix_dict in matrices.kmr_matrix_dicts:
x = gth_solve(matrix_dict['A'])
test_class()(x)
def test_stoch_matrix_1():
"""Test with stochastic matrices"""
matrices = Matrices()
for matrix_dict in matrices.stoch_matrix_dicts:
x = gth_solve(matrix_dict['A'])
StationaryDistEqualToKnown()(matrix_dict['stationary_dist'], x)
def test_stoch_matrix(test_class):
"""Test with stochastic matrices"""
matrices = Matrices()
for matrix_dict in matrices.stoch_matrix_dicts:
x = gth_solve(matrix_dict['A'])
test_class()(x)
def test_raises_value_error_non_square():
"""Test with non square input"""
gth_solve(np.array([[0.4, 0.6]]))
def test_raises_value_error_non_2dim():
"""Test with non 2dim input"""
gth_solve(np.array([0.4, 0.6]))
def test_raises_value_error_non_square():
"""Test with non square input"""
gth_solve(np.array([[0.4, 0.6]]))
def test_raises_value_error_non_2dim():
"""Test with non 2dim input"""
gth_solve(np.array([0.4, 0.6]))
