"{}/../datasets/Example_pairwise_targets.csv".format(
os.path.dirname(
os.path.realpath(__file__)))).iloc[:, :50].set_index("SampleID")
data_pairwise = read_causal_pairs(
"{}/../datasets/Example_pairwise_pairs.csv".format(
os.path.dirname(os.path.realpath(__file__)))).iloc[:5, :50]
data_graph = pd.read_csv('{}/../datasets/Example_graph_numdata.csv'.format(
os.path.dirname(os.path.realpath(__file__)))).iloc[:100, :5]
train_data = pd.concat([train_data] * 5, ignore_index=True)
train_target = pd.concat([train_target] * 5, ignore_index=True)
train_target.iloc[10:, :] = 0
# print(train_target)
graph_skeleton = Glasso().predict(data_graph)
def test_pairwise():
for method in [Jarfo]: # Jarfo
# print(method)
m = method()
if hasattr(m, "fit"):
# print(train_data)
m.fit(train_data, train_target)
r = m.predict(data_pairwise)
assert r is not None
print(r)
return 0
def test_indirect_link_removal():
data = init()
umg = Glasso().predict(data)
for method in ["nd", "clr", "aracne"]:
assert isinstance(remove_indirect_links(umg, alg=method), nx.Graph)
return 0