Graph
- graph_tiger.graphs.as_733()
Returns the ‘as19971108’ graph from: http://snap.stanford.edu/data/as-733.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.barabasi_albert(n, m=3, seed=None)
Returns a Barabasi Albert NetworkX graph
- Parameters
n – number of nodes
m – number of edges to attach from a new node to existing nodes
seed – fixes the graph generation process
- Returns
a NetworkX graph
- graph_tiger.graphs.c4_graph()
Returns a 4 node cycle graph
- Returns
undirected NetworkX graph
- graph_tiger.graphs.ca_astro_ph()
Returns the graph from: https://snap.stanford.edu/data/ca-AstroPh.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.ca_grqc()
Returns the graph from: https://snap.stanford.edu/data/ca-GrQc.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.ca_hep_th()
Returns the graph from: https://snap.stanford.edu/data/cit-HepTh.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.cit_hep_th()
Returns the graph from: https://snap.stanford.edu/data/cit-HepTh.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.clustered_scale_free(n, m=3, p=0.3, seed=None)
Returns a Clustered Scale-Free NetworkX graph
- Parameters
n – number of nodes
m – the number of random edges to add for each new node
p – probability of adding a triangle after adding a random edge
seed – fixes the graph generation process
- Returns
a NetworkX graph
- graph_tiger.graphs.dblp()
Returns the graph from: https://snap.stanford.edu/data/com-DBLP.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.download_dataset(dataset)
Reading the dataset from the web.
- Parameters
dataset – a string representing the dataset to download
- graph_tiger.graphs.electrical()
Returns the graph from: http://konect.cc/networks/opsahl-powergrid/, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.email_eu_all()
Returns the graph from: https://snap.stanford.edu/data/email-EuAll.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.enron_email()
Returns the graph from: https://snap.stanford.edu/data/email-Enron.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.erdos_reyni(n, p=None, seed=None)
Returns a Erdos Reyni NetworkX graph
- Parameters
n – number of nodes
p – probability for edge creation
seed – fixes the graph generation process
- Returns
a NetworkX graph
- graph_tiger.graphs.get_graph_options()
Returns a formatted string containing all of the generators, datasets and custom graphs implemented in TIGER
- Returns
formatted string
- graph_tiger.graphs.get_graph_urls()
Returns a dictionary of the datasets used in TIGER and the original link to download them
- Returns
dictionary containing links to each dataset
- graph_tiger.graphs.graph_loader(graph_type, **kwargs)
Loads any of the available graph models, supported user-downloaded datasets and toy graphs. In order to get a list of available graph options run ‘get_graph_options()’.
- Parameters
graph_type – a string representing the graph you want to load. For example, ‘ER’, ‘WS’, ‘BA’, ‘oregon_1’ (must first download), ‘electrical’ (must first download)
kwargs – allows user to specify specific graph model properties
- Returns
an undirected NetworkX graph
- graph_tiger.graphs.k4_1_graph()
Returns a 4 node diamond graph (1 diagonal edge)
- Returns
undirected NetworkX graph
- graph_tiger.graphs.k4_2_graph()
Returns a 4 node diamond graph (2 diagonal edges), a.k.a. complete graph
- Returns
undirected NetworkX graph
- graph_tiger.graphs.karate()
Returns the graph from: https://networkx.org/documentation/stable/reference/generated/networkx.generators.social.karate_club_graph.html,
- Returns
undirected NetworkX graph
- graph_tiger.graphs.o4_graph()
Returns a 4 node disconnected graph
- Returns
undirected NetworkX graph
- graph_tiger.graphs.oregeon_1()
Returns the graph from: https://snap.stanford.edu/data/oregon1_010331.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.p2p_gnuetella08()
Returns the graph from: https://snap.stanford.edu/data/p2p-Gnutella08.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.p4_graph()
Returns a 4 node path graph
- Returns
undirected NetworkX graph
- graph_tiger.graphs.s4_graph()
Returns a 4 node star graph
- Returns
undirected NetworkX graph
- graph_tiger.graphs.two_c4_0_bridge()
Returns two disconnected 4 node cycle graphs
- Returns
undirected NetworkX graph
- graph_tiger.graphs.two_c4_1_bridge()
Returns two 4 node cycle graphs connected by 1 edge
- Returns
undirected NetworkX graph
- graph_tiger.graphs.two_c4_2_bridge()
Returns two 4 node cycle graphs connected by 2 edges
- Returns
undirected NetworkX graph
- graph_tiger.graphs.two_c4_3_bridge()
Returns two 4 node cycle graphs connected by 3 edges
- Returns
undirected NetworkX graph
- graph_tiger.graphs.watts_strogatz(n, m=4, p=0.05, seed=None)
Returns a Watts Strogatz NetworkX graph
- Parameters
n – number of nodes
m – each node is joined with its k nearest neighbors in a ring topology
p – probability of rewiring each edge
seed – fixes the graph generation process
- Returns
a NetworkX graph
- graph_tiger.graphs.wdn_ky2()
Returns the graph from: https://uknowledge.uky.edu/wdst/4/, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph
- graph_tiger.graphs.wiki_vote()
Returns the graph from: https://snap.stanford.edu/data/wiki-Vote.html, where we preprocess it to only keep the largest connected component
- Returns
undirected NetworkX graph