def test_tadw(): """ Testing the TADW node embedding. """ graph = nx.newman_watts_strogatz_graph(250, 10, 0.2) features = np.random.uniform(0, 1, (250, 128)) model = TADW() model.fit(graph, features) embedding = model.get_embedding() assert embedding.shape[0] == graph.number_of_nodes() assert embedding.shape[1] == 2 * model.dimensions assert type(embedding) == np.ndarray graph = nx.newman_watts_strogatz_graph(150, 10, 0.2) features = np.random.uniform(0, 1, (150, 128)) model = TADW(dimensions=8) model.fit(graph, features) embedding = model.get_embedding() assert embedding.shape[0] == graph.number_of_nodes() assert embedding.shape[1] == 2 * model.dimensions assert type(embedding) == np.ndarray
x = np.random.uniform(0, 1, (200, 200)) model = FSCNMF() model.fit(g, x) #--------------- # TADW example #--------------- g = nx.newman_watts_strogatz_graph(200, 20, 0.05) x = np.random.uniform(0, 1, (200, 200)) model = TADW() model.fit(g, x) #----------------- # GL2Vec example #----------------- graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(100)] model = GL2Vec() model.fit(graphs) model.get_embedding() #--------------
"""TADW example.""" import numpy as np import networkx as nx from karateclub.node_embedding.attributed import TADW g = nx.newman_watts_strogatz_graph(200, 20, 0.05) x = np.random.uniform(0, 1, (200, 200)) model = TADW() model.fit(g, x)