def test_DCER_inputs(self):
with pytest.raises(TypeError):
DCEREstimator(directed="hey")
with pytest.raises(TypeError):
DCEREstimator(loops=6)
graph = er_np(100, 0.5)
dcere = DCEREstimator()
with pytest.raises(ValueError):
dcere.fit(graph[:, :99])
with pytest.raises(ValueError):
dcere.fit(graph[..., np.newaxis])
def test_DCER_sample(self):
np.random.seed(8888)
estimator = DCEREstimator(directed=True, loops=False)
g = self.graph
p_mat = self.p_mat
with pytest.raises(NotFittedError):
estimator.sample()
estimator.fit(g)
with pytest.raises(ValueError):
estimator.sample(n_samples=-1)
with pytest.raises(TypeError):
estimator.sample(n_samples="nope")
B = 0.5
dc = np.random.uniform(0.25, 0.75, size=100)
p_mat = np.outer(dc, dc) * B
p_mat -= np.diag(np.diag(p_mat))
g = sample_edges(p_mat, directed=True)
estimator.fit(g)
estimator.p_mat_ = p_mat
_test_sample(estimator, p_mat, n_samples=1000, atol=0.2)
def test_DCER_nparams(self):
n_verts = 1000
graph = self.graph
e = DCEREstimator(directed=True)
e.fit(graph)
assert e._n_parameters() == (n_verts + 1)