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diff --git a/lib/python2.7/site-packages/setoolsgui/networkx/algorithms/components/attracting.py b/lib/python2.7/site-packages/setoolsgui/networkx/algorithms/components/attracting.py
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+# -*- coding: utf-8 -*-
+"""
+Attracting components.
+"""
+#    Copyright (C) 2004-2011 by 
+#    Aric Hagberg <hagberg@lanl.gov>
+#    Dan Schult <dschult@colgate.edu>
+#    Pieter Swart <swart@lanl.gov>
+#    All rights reserved.
+#    BSD license.
+import networkx as nx
+__authors__ = "\n".join(['Christopher Ellison'])
+__all__ = ['number_attracting_components', 
+           'attracting_components',
+           'is_attracting_component', 
+           'attracting_component_subgraphs',
+           ]
+
+def attracting_components(G):
+    """Returns a list of attracting components in `G`.
+
+    An attracting component in a directed graph `G` is a strongly connected
+    component with the property that a random walker on the graph will never
+    leave the component, once it enters the component.
+
+    The nodes in attracting components can also be thought of as recurrent
+    nodes.  If a random walker enters the attractor containing the node, then
+    the node will be visited infinitely often.
+
+    Parameters
+    ----------
+    G : DiGraph, MultiDiGraph
+        The graph to be analyzed.
+
+    Returns
+    -------
+    attractors : list
+        The list of attracting components, sorted from largest attracting
+        component to smallest attracting component.
+
+    See Also
+    --------
+    number_attracting_components
+    is_attracting_component 
+    attracting_component_subgraphs
+
+    """
+    scc = nx.strongly_connected_components(G)
+    cG = nx.condensation(G, scc)
+    attractors = [scc[n] for n in cG if cG.out_degree(n) == 0]
+    attractors.sort(key=len,reverse=True)
+    return attractors
+
+
+def number_attracting_components(G):
+    """Returns the number of attracting components in `G`.
+
+    Parameters
+    ----------
+    G : DiGraph, MultiDiGraph
+        The graph to be analyzed.
+
+    Returns
+    -------
+    n : int
+        The number of attracting components in G.
+
+    See Also
+    --------
+    attracting_components
+    is_attracting_component
+    attracting_component_subgraphs
+
+    """
+    n = len(attracting_components(G))
+    return n
+
+
+def is_attracting_component(G):
+    """Returns True if `G` consists of a single attracting component.
+
+    Parameters
+    ----------
+    G : DiGraph, MultiDiGraph
+        The graph to be analyzed.
+
+    Returns
+    -------
+    attracting : bool
+        True if `G` has a single attracting component. Otherwise, False.
+
+    See Also
+    --------
+    attracting_components
+    number_attracting_components
+    attracting_component_subgraphs
+
+    """
+    ac = attracting_components(G)
+    if len(ac[0]) == len(G):
+        attracting = True
+    else:
+        attracting = False
+    return attracting
+
+
+def attracting_component_subgraphs(G):
+    """Returns a list of attracting component subgraphs from `G`.
+
+    Parameters
+    ----------
+    G : DiGraph, MultiDiGraph
+        The graph to be analyzed.
+
+    Returns
+    -------
+    subgraphs : list
+        A list of node-induced subgraphs of the attracting components of `G`.
+    
+    Notes
+    -----
+    Graph, node, and edge attributes are copied to the subgraphs.
+
+    See Also
+    --------
+    attracting_components
+    number_attracting_components
+    is_attracting_component
+
+    """
+    subgraphs = [G.subgraph(ac).copy() for ac in attracting_components(G)]
+    return subgraphs
+