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updated with nice outputs for review

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This commit is contained in:
Luca Lombardo
2023-02-09 16:21:01 +01:00
parent 3236e18d36
commit 1cfa9c6ed0
2 changed files with 15791 additions and 73 deletions
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main.ipynb
+15785 -64
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File diff suppressed because one or more lines are too long
src/utils.py
+6 -9
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@@ -502,8 +502,8 @@ def create_random_graphs(G: nx.Graph, model = None, save = True) -> nx.Graph:
if model == "erdos_renyi":
G_random = nx.erdos_renyi_graph(G.number_of_nodes(), nx.density(G))
print("Creating a random graph with the Erdos-Renyi model {}" .format(G.name))
print("Number of edges in the original graph: {}" .format(G.number_of_edges()))
print("Number of edges in the random graph: {}" .format(G_random.number_of_edges()))
# print("Number of edges in the original graph: {}" .format(G.number_of_edges()))
# print("Number of edges in the random graph: {}" .format(G_random.number_of_edges()))
G_random.name = G.name + " Erdos-Renyi"
if save:
@@ -520,8 +520,8 @@ def create_random_graphs(G: nx.Graph, model = None, save = True) -> nx.Graph:
p = G.number_of_edges() / (G.number_of_nodes())
avg_degree = int(np.mean([d for n, d in G.degree()]))
G_random = nx.watts_strogatz_graph(G.number_of_nodes(), avg_degree, p)
print("Number of edges in the original graph: {}" .format(G.number_of_edges()))
print("Number of edges in the random graph: {}" .format(G_random.number_of_edges()))
# print("Number of edges in the original graph: {}" .format(G.number_of_edges()))
# print("Number of edges in the random graph: {}" .format(G_random.number_of_edges()))
G_random.name = G.name + " Watts-Strogatz"
if save:
@@ -635,7 +635,7 @@ def random_sample(graph: nx.Graph, k: float) -> nx.Graph:
The graph to sample
`k`: float
The percentage of nodes to sample from the graph.
The percentage of nodes to remove from the graph
Returns
-------
@@ -644,8 +644,7 @@ def random_sample(graph: nx.Graph, k: float) -> nx.Graph:
"""
nodes = list(graph.nodes())
n = int(k*len(nodes))
nodes_sample = random.sample(nodes, n)
nodes_sample = np.random.choice(nodes, size=int((1-k)*len(nodes)), replace=False)
G = graph.subgraph(nodes_sample)
@@ -654,8 +653,6 @@ def random_sample(graph: nx.Graph, k: float) -> nx.Graph:
connected = max(nx.connected_components(G), key=len)
G_connected = graph.subgraph(connected)
print(nx.is_connected(G_connected))
print("Number of nodes in the sampled graph: ", G.number_of_nodes())
print("Number of edges in the sampled graph: ", G.number_of_edges())