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
Example #2
0
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()

#--------------
Example #3
0
"""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)