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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/venv/lib/python3.9/site-packages/networkx/algorithms/reciprocity.py

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"""Algorithms to calculate reciprocity in a directed graph."""
from networkx import NetworkXError
from ..utils import not_implemented_for
__all__ = ["reciprocity", "overall_reciprocity"]
@not_implemented_for("undirected", "multigraph")
def reciprocity(G, nodes=None):
r"""Compute the reciprocity in a directed graph.
The reciprocity of a directed graph is defined as the ratio
of the number of edges pointing in both directions to the total
number of edges in the graph.
Formally, $r = |{(u,v) \in G|(v,u) \in G}| / |{(u,v) \in G}|$.
The reciprocity of a single node u is defined similarly,
it is the ratio of the number of edges in both directions to
the total number of edges attached to node u.
Parameters
----------
G : graph
A networkx directed graph
nodes : container of nodes, optional (default=whole graph)
Compute reciprocity for nodes in this container.
Returns
-------
out : dictionary
Reciprocity keyed by node label.
Notes
-----
The reciprocity is not defined for isolated nodes.
In such cases this function will return None.
"""
# If `nodes` is not specified, calculate the reciprocity of the graph.
if nodes is None:
return overall_reciprocity(G)
# If `nodes` represents a single node in the graph, return only its
# reciprocity.
if nodes in G:
reciprocity = next(_reciprocity_iter(G, nodes))[1]
if reciprocity is None:
raise NetworkXError("Not defined for isolated nodes.")
else:
return reciprocity
# Otherwise, `nodes` represents an iterable of nodes, so return a
# dictionary mapping node to its reciprocity.
return dict(_reciprocity_iter(G, nodes))
def _reciprocity_iter(G, nodes):
""" Return an iterator of (node, reciprocity).
"""
n = G.nbunch_iter(nodes)
for node in n:
pred = set(G.predecessors(node))
succ = set(G.successors(node))
overlap = pred & succ
n_total = len(pred) + len(succ)
# Reciprocity is not defined for isolated nodes.
# Return None.
if n_total == 0:
yield (node, None)
else:
reciprocity = 2.0 * float(len(overlap)) / float(n_total)
yield (node, reciprocity)
@not_implemented_for("undirected", "multigraph")
def overall_reciprocity(G):
"""Compute the reciprocity for the whole graph.
See the doc of reciprocity for the definition.
Parameters
----------
G : graph
A networkx graph
"""
n_all_edge = G.number_of_edges()
n_overlap_edge = (n_all_edge - G.to_undirected().number_of_edges()) * 2
if n_all_edge == 0:
raise NetworkXError("Not defined for empty graphs")
return float(n_overlap_edge) / float(n_all_edge)