def test_fixedpoint_cm_5(self):
"""test with 3 classes of cardinality 1
and no zero degrees
"""
A = np.array([
[0, 0, 1],
[0, 0, 1],
[1, 1, 0],
])
g = sample.UndirectedGraph(A)
g._solve_problem(
model="cm-new",
method="quasinewton",
initial_guess="random",
max_steps=100,
verbose=False,
linsearch=True,
)
g.solution_error()
# print('degseq = ', np.concatenate((g.dseq_out, g.dseq_in)))
# print('expected degseq = ',g.expected_dseq)
# debug
# print(g.r_dseq_out)
# print(g.r_dseq_in)
# print(g.rnz_dseq_out)
# print(g.rnz_dseq_in)
# print('\ntest 5: error = {}'.format(g.error))
# test result
self.assertTrue(g.error < 1e-1)
def test_fixedpoint_cm_9(self):
"""classes with cardinality more than 1 and zero degrees"""
# test Matrix 1
n, seed = (100, 22)
A = mg.random_binary_matrix_generator_dense(n, sym=True, seed=seed)
g = sample.UndirectedGraph(A)
g._solve_problem(
model="cm-new",
method="quasinewton",
initial_guess="random",
max_steps=300,
verbose=False,
linsearch="True",
)
g.solution_error()
# print('degseq = ', np.concatenate((g.dseq_out, g.dseq_in)))
# print('expected degseq = ',g.expected_dseq)
# debug
# print(g.r_dseq_out)
# print(g.r_dseq_in)
# print(g.rnz_dseq_out)
# print(g.rnz_dseq_in)
# print('\ntest 9: error = {}'.format(g.error))
# test result
self.assertTrue(g.error < 1e-1)
def test_CReAMa_original_quasinewton_random_dense_20_undir(self):
network = mg.random_weighted_matrix_generator_dense(n=20,
sup_ext=10,
sym=False,
seed=None)
network_bin = (network > 0).astype(int)
g = sample_und.UndirectedGraph(adjacency=network)
g.solve_tool(
model="CReAMa",
method="newton",
initial_guess="random",
adjacency=network_bin,
max_steps=1000,
verbose=False,
)
g.solution_error()
# test result
self.assertTrue(g.relative_error_strength < 1e-1)
self.assertTrue(g.relative_error_strength < 1e-2)
def test_cm_uniform(self):
n, seed = (4, 22)
A = mg.random_binary_matrix_generator_dense(n, sym=True, seed=seed)
g = sample_u.UndirectedGraph(A)
g.initial_guess = 'uniform'
g.last_model = "cm"
g._set_initial_guess('cm')
self.assertTrue(g.x0.all() == np.array([0.5, 0.5]).all())
def test_cm(self):
n, seed = (4, 22)
A = mg.random_binary_matrix_generator_dense(n, sym=True, seed=seed)
x0 = np.random.rand(n)
g = sample_u.UndirectedGraph(A)
g.initial_guess = x0
g._set_initial_guess_cm()
g.full_return = False
g.last_model = "cm"
g._set_solved_problem_cm(g.x0)
self.assertTrue(g.x.all() == x0.all())
def test_ecm(self):
n, seed = (4, 22)
A = mg.random_weighted_matrix_generator_dense(n,
sym=False,
seed=seed,
sup_ext=100,
intweights=True)
x0 = np.random.rand(n)
g = sample_u.UndirectedGraph(A)
g.initial_guess = x0
g._set_initial_guess_CReAMa()
self.assertTrue(g.x0.all() == x0.all())
def test_CREAMA_uniform(self):
n, seed = (4, 22)
A = mg.random_weighted_matrix_generator_dense(n,
sym=False,
seed=seed,
sup_ext=100,
intweights=True)
g = sample_u.UndirectedGraph(A)
g.initial_guess = 'strengths_minor'
g._set_initial_guess('CReAMa')
x = (g.strength_sequence > 0).astype(float) / (g.strength_sequence + 1)
self.assertTrue(g.x0.all() == x.all())
def test_CREAMA(self):
n, seed = (4, 22)
A = mg.random_weighted_matrix_generator_dense(n,
sym=False,
seed=seed,
sup_ext=100,
intweights=True)
x0 = np.random.rand(n)
g = sample_u.UndirectedGraph(A)
g.initial_guess = x0
g._set_initial_guess_CReAMa()
g.full_return = False
g._set_solved_problem_CReAMa(g.x0)
self.assertTrue(g.beta.all() == x0.all())
def test_ECM_Dianati_random_dense_20_undir(self):
network = mg.random_weighted_matrix_generator_dense(n=20,
sup_ext=10,
sym=True,
seed=None,
intweights=True)
network_bin = (network > 0).astype(int)
g = sample_und.UndirectedGraph(adjacency=network)
g.solve_tool(
model="ecm",
method="quasinewton",
max_steps=1000,
verbose=False,
initial_guess="random",
)
g.solution_error()
# test result
self.assertTrue(g.error < 1e-1)