def test_retrieve_adjacency_matrix():
# No connections.
cgpms = build_cgpm_no_connection()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_matrix(cgpms, vtc)
assert np.allclose(adj, np.asarray([
[0, 0, 0],
[0, 0, 0],
[0, 0, 0],
]))
# V structure.
cgpms = build_cgpms_v_structure()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_matrix(cgpms, vtc)
assert np.allclose(adj, np.asarray([
[0, 0, 1],
[0, 0, 1],
[0, 0, 0],
]))
# Markov chain.
cgpms = build_cgpms_markov_chain()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_matrix(cgpms, vtc)
assert np.allclose(adj, np.asarray([
[0, 0, 1],
[0, 0, 0],
[0, 1, 0],
]))
# Complex.
cgpms = build_cgpms_complex()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_matrix(cgpms, vtc)
assert np.allclose(
adj,
np.asarray([
[0, 0, 0, 0],
[0, 0, 0, 0],
[1, 0, 0, 1],
[1, 1, 0, 0],
]))
# Fork.
cgpms = build_cgpms_fork()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_matrix(cgpms, vtc)
assert np.allclose(adj, np.asarray([
[0, 0, 0],
[1, 0, 0],
[1, 0, 0],
]))
def test_retrieve_variable_to_cgpm():
cgpms = [
CGpm(outputs=[0, 1, 5], inputs=[2]),
CGpm(outputs=[2], inputs=[]),
CGpm(outputs=[-1], inputs=[7]),
]
for order in itertools.permutations(cgpms):
variable_to_cgpm = helpers.retrieve_variable_to_cgpm(order)
for v, c in variable_to_cgpm.iteritems():
assert v in order[c].outputs
def __init__(self, cgpms, accuracy=None, rng=None):
if accuracy is None:
accuracy = 1
self.rng = rng if rng else gu.gen_rng(1)
self.cgpms = hu.validate_cgpms(cgpms)
self.accuracy = accuracy
self.v_to_c = hu.retrieve_variable_to_cgpm(self.cgpms)
self.adjacency = hu.retrieve_adjacency_list(self.cgpms, self.v_to_c)
self.extraneous = hu.retrieve_extraneous_inputs(
self.cgpms, self.v_to_c)
self.topo = hu.topological_sort(self.adjacency)
def __init__(self, cgpms, accuracy=None, rng=None):
# Validate inputs.
cgpms_valid = validate_cgpms(cgpms)
# From constructor
self.cgpms = flatten_cgpms(cgpms_valid, Chain)
self.accuracy = accuracy or 1
self.rng = rng if rng else get_prng(1)
# Derived attributes.
self.outputs = lchain(*[cgpm.outputs for cgpm in self.cgpms])
self.inputs = lchain(*[cgpm.inputs for cgpm in self.cgpms])
self.v_to_c = retrieve_variable_to_cgpm(self.cgpms)
self.adjacency = retrieve_adjacency_list(self.cgpms, self.v_to_c)
self.extraneous = retrieve_extraneous_inputs(self.cgpms, self.v_to_c)
self.topo = topological_sort(self.adjacency)
def test_retrieve_extraneous_inputs():
# No connections.
cgpms = build_cgpm_no_connection()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
ext = helpers.retrieve_extraneous_inputs(cgpms, vtc)
assert [] == ext
# V structure.
cgpms = build_cgpms_v_structure()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
ext = helpers.retrieve_extraneous_inputs(cgpms, vtc)
assert [] == ext
# Markov chain.
cgpms = build_cgpms_markov_chain()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
ext = helpers.retrieve_extraneous_inputs(cgpms, vtc)
assert [5] == ext
# Complex.
cgpms = build_cgpms_complex()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
ext = helpers.retrieve_extraneous_inputs(cgpms, vtc)
assert set([0, -8, -9, -10, -11, -12]) == set(ext)
def test_retrieve_adjacency_list():
# No connections.
cgpms = build_cgpm_no_connection()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_list(cgpms, vtc)
assert {0: [], 1: [], 2: []} == adj
# V structure.
cgpms = build_cgpms_v_structure()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_list(cgpms, vtc)
assert {0: [], 1: [], 2: [0, 1]} == adj
# Markov chain.
cgpms = build_cgpms_markov_chain()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_list(cgpms, vtc)
assert {0: [], 1: [2], 2: [0]} == adj
# Complex.
cgpms = build_cgpms_complex()
vtc = helpers.retrieve_variable_to_cgpm(cgpms)
adj = helpers.retrieve_adjacency_list(cgpms, vtc)
assert {0: [2, 3], 1: [3], 2: [], 3: [2]} == adj