def compare_hypergraph_with_cliques(number_of_nodes,
cardinality, fraction, t_max,
plot_representations=False):
"""Create hypergraph and clique, run diffusion and compare"""
HG = uniform_hypergraph(
n=number_of_nodes,
k=cardinality,
number_of_edges=int(
number_of_nodes *
fraction))
nodes = HG.nodes()
hyperedges = HG.hyper_edges()
all_nodes = []
for hyperedge in hyperedges:
all_nodes += hyperedge
if plot_representations:
utils.plot_different_representations(nodes, hyperedges)
markov_matrix = create_markov_matrix(hyperedges)
print(markov_matrix)
engine = DiffusionEngine(markov_matrix)
most_common, states = engine.simulate(t_max)
plt.figure(figsize=(12, 10))
utils.plot_hyperedges_frequencies(most_common, hyperedges,
'Occurrences of hyperedges'
' in a hypergraph')
most_common_nodes = count_nodes(nodes, hyperedges, most_common)
plt.figure(figsize=(12, 10))
utils.plot_nodes_frequencies(most_common_nodes, 'Nodes in a hypergraph')
clique_graph = converters.convert_to_clique_graph(nodes, hyperedges)
clique_markov_matrix = create_markov_matrix(clique_graph.edges())
print("clique markov matrix")
print(clique_markov_matrix)
engine = DiffusionEngine(markov_matrix)
most_common, states = engine.simulate(t_max)
plt.figure(figsize=(12, 10))
utils.plot_hyperedges_frequencies(most_common, clique_graph.edges(),
'Occurrences of edges in a graph')
most_common_nodes = count_nodes(clique_graph.nodes(), clique_graph.edges(),
most_common)
plt.figure(figsize=(12, 10))
utils.plot_nodes_frequencies(most_common_nodes, 'Nodes in a graph')
def plot_diffusion_results(most_common, most_common_nodes, edges, name):
"""Plot results of diffusion.
Parameters:
most_common: indexes of hyperedges and their frequences
most_common_nodes: indexes of nodes and their frequences
edges: names of edge
name: name of object on which diffusion was simulated, used
plot title
Returns:
probabilities of being in a node
"""
plt.figure(figsize=(8, 4))
utils.plot_hyperedges_frequencies(most_common,
edges, ('Occurrences of hyperedges in'
' a {}').format(name),
normed=True)
plt.figure(figsize=(8, 4))
return utils.plot_nodes_frequencies(most_common_nodes,
'Nodes in a {}'.format(name),
normed=True)
def plot_diffusion_results(most_common, most_common_nodes, edges, name):
"""Plot results of diffusion.
Parameters:
most_common: indexes of hyperedges and their frequences
most_common_nodes: indexes of nodes and their frequences
edges: names of edge
name: name of object on which diffusion was simulated, used
plot title
Returns:
probabilities of being in a node
"""
plt.figure(figsize=(8, 4))
utils.plot_hyperedges_frequencies(most_common, edges,
('Occurrences of hyperedges in'
' a {}').format(name),
normed=True)
plt.figure(figsize=(8, 4))
return utils.plot_nodes_frequencies(most_common_nodes,
'Nodes in a {}'.format(name),
normed=True)