def test_wrp_metric_params():
def metric(x, y, **kwargs):
return np.linalg.norm(x - y)
metric_params = {"parameter": 0.}
wrp = WeightedRipsPersistence(metric=metric, metric_params=metric_params)
wrp.fit_transform(X_pc)
def test_wrp_same_as_vrp_when_zero_weights(X, metric, weight_params,
collapse_edges, max_edge_weight,
infinity_values):
wrp = WeightedRipsPersistence(weights=lambda x: np.zeros(x.shape[0]),
weight_params=weight_params,
metric=metric,
collapse_edges=collapse_edges,
max_edge_weight=max_edge_weight,
infinity_values=infinity_values)
# This is not generally true, it is only a way to obtain the res array
# in this specific case
X_exp = X_vrp_exp.copy()
X_exp[:, :, :2][X_exp[:, :, :2] >= max_edge_weight] = infinity_values
assert_almost_equal(wrp.fit_transform(X), X_exp)
def test_wrp_infinity_error():
with pytest.raises(ValueError, match="Input contains"):
wrp = WeightedRipsPersistence(metric='precomputed')
wrp.fit_transform(X_dist_disconnected)
def test_wrp_transform(X, metric, weight_params, collapse_edges):
wrp = WeightedRipsPersistence(weight_params=weight_params,
metric=metric,
collapse_edges=collapse_edges)
assert_almost_equal(wrp.fit_transform(X), X_wrp_exp[weight_params['p']])
def test_wrp_params():
metric = 'not_defined'
wrp = WeightedRipsPersistence(metric=metric)
with pytest.raises(ValueError):
wrp.fit_transform(X_pc)