--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/planemo/lib/python3.7/site-packages/networkx/algorithms/euler.py	Fri Jul 31 00:32:28 2020 -0400
@@ -0,0 +1,379 @@
+# -*- coding: utf-8 -*-
+#
+#    Copyright (C) 2010 by
+#    Aric Hagberg <hagberg@lanl.gov>
+#    Dan Schult <dschult@colgate.edu>
+#    Pieter Swart <swart@lanl.gov>
+#    All rights reserved.
+#    BSD license.
+#
+# Authors:
+#   Nima Mohammadi <nima.irt@gmail.com>
+#   Aric Hagberg <hagberg@lanl.gov>
+#   Mike Trenfield <william.trenfield@utsouthwestern.edu>
+"""
+Eulerian circuits and graphs.
+"""
+from itertools import combinations
+
+import networkx as nx
+from ..utils import arbitrary_element, not_implemented_for
+
+__all__ = ['is_eulerian', 'eulerian_circuit', 'eulerize',
+           'is_semieulerian', 'has_eulerian_path', 'eulerian_path',
+           ]
+
+
+def is_eulerian(G):
+    """Returns True if and only if `G` is Eulerian.
+
+    A graph is *Eulerian* if it has an Eulerian circuit. An *Eulerian
+    circuit* is a closed walk that includes each edge of a graph exactly
+    once.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+       A graph, either directed or undirected.
+
+    Examples
+    --------
+    >>> nx.is_eulerian(nx.DiGraph({0: [3], 1: [2], 2: [3], 3: [0, 1]}))
+    True
+    >>> nx.is_eulerian(nx.complete_graph(5))
+    True
+    >>> nx.is_eulerian(nx.petersen_graph())
+    False
+
+    Notes
+    -----
+    If the graph is not connected (or not strongly connected, for
+    directed graphs), this function returns False.
+
+    """
+    if G.is_directed():
+        # Every node must have equal in degree and out degree and the
+        # graph must be strongly connected
+        return (all(G.in_degree(n) == G.out_degree(n) for n in G) and
+                nx.is_strongly_connected(G))
+    # An undirected Eulerian graph has no vertices of odd degree and
+    # must be connected.
+    return all(d % 2 == 0 for v, d in G.degree()) and nx.is_connected(G)
+
+
+def is_semieulerian(G):
+    """Return True iff `G` is semi-Eulerian.
+
+    G is semi-Eulerian if it has an Eulerian path but no Eulerian circuit.
+    """
+    return has_eulerian_path(G) and not is_eulerian(G)
+
+
+def _find_path_start(G):
+    """Return a suitable starting vertex for an Eulerian path.
+
+    If no path exists, return None.
+    """
+    if not has_eulerian_path(G):
+        return None
+
+    if is_eulerian(G):
+        return arbitrary_element(G)
+
+    if G.is_directed():
+        v1, v2 = [v for v in G if G.in_degree(v) != G.out_degree(v)]
+        # Determines which is the 'start' node (as opposed to the 'end')
+        if G.out_degree(v1) > G.in_degree(v1):
+            return v1
+        else:
+            return v2
+
+    else:
+        # In an undirected graph randomly choose one of the possibilities
+        start = [v for v in G if G.degree(v) % 2 != 0][0]
+        return start
+
+
+def _simplegraph_eulerian_circuit(G, source):
+    if G.is_directed():
+        degree = G.out_degree
+        edges = G.out_edges
+    else:
+        degree = G.degree
+        edges = G.edges
+    vertex_stack = [source]
+    last_vertex = None
+    while vertex_stack:
+        current_vertex = vertex_stack[-1]
+        if degree(current_vertex) == 0:
+            if last_vertex is not None:
+                yield (last_vertex, current_vertex)
+            last_vertex = current_vertex
+            vertex_stack.pop()
+        else:
+            _, next_vertex = arbitrary_element(edges(current_vertex))
+            vertex_stack.append(next_vertex)
+            G.remove_edge(current_vertex, next_vertex)
+
+
+def _multigraph_eulerian_circuit(G, source):
+    if G.is_directed():
+        degree = G.out_degree
+        edges = G.out_edges
+    else:
+        degree = G.degree
+        edges = G.edges
+    vertex_stack = [(source, None)]
+    last_vertex = None
+    last_key = None
+    while vertex_stack:
+        current_vertex, current_key = vertex_stack[-1]
+        if degree(current_vertex) == 0:
+            if last_vertex is not None:
+                yield (last_vertex, current_vertex, last_key)
+            last_vertex, last_key = current_vertex, current_key
+            vertex_stack.pop()
+        else:
+            triple = arbitrary_element(edges(current_vertex, keys=True))
+            _, next_vertex, next_key = triple
+            vertex_stack.append((next_vertex, next_key))
+            G.remove_edge(current_vertex, next_vertex, next_key)
+
+
+def eulerian_circuit(G, source=None, keys=False):
+    """Returns an iterator over the edges of an Eulerian circuit in `G`.
+
+    An *Eulerian circuit* is a closed walk that includes each edge of a
+    graph exactly once.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+       A graph, either directed or undirected.
+
+    source : node, optional
+       Starting node for circuit.
+
+    keys : bool
+       If False, edges generated by this function will be of the form
+       ``(u, v)``. Otherwise, edges will be of the form ``(u, v, k)``.
+       This option is ignored unless `G` is a multigraph.
+
+    Returns
+    -------
+    edges : iterator
+       An iterator over edges in the Eulerian circuit.
+
+    Raises
+    ------
+    NetworkXError
+       If the graph is not Eulerian.
+
+    See Also
+    --------
+    is_eulerian
+
+    Notes
+    -----
+    This is a linear time implementation of an algorithm adapted from [1]_.
+
+    For general information about Euler tours, see [2]_.
+
+    References
+    ----------
+    .. [1] J. Edmonds, E. L. Johnson.
+       Matching, Euler tours and the Chinese postman.
+       Mathematical programming, Volume 5, Issue 1 (1973), 111-114.
+    .. [2] https://en.wikipedia.org/wiki/Eulerian_path
+
+    Examples
+    --------
+    To get an Eulerian circuit in an undirected graph::
+
+        >>> G = nx.complete_graph(3)
+        >>> list(nx.eulerian_circuit(G))
+        [(0, 2), (2, 1), (1, 0)]
+        >>> list(nx.eulerian_circuit(G, source=1))
+        [(1, 2), (2, 0), (0, 1)]
+
+    To get the sequence of vertices in an Eulerian circuit::
+
+        >>> [u for u, v in nx.eulerian_circuit(G)]
+        [0, 2, 1]
+
+    """
+    if not is_eulerian(G):
+        raise nx.NetworkXError("G is not Eulerian.")
+    if G.is_directed():
+        G = G.reverse()
+    else:
+        G = G.copy()
+    if source is None:
+        source = arbitrary_element(G)
+    if G.is_multigraph():
+        for u, v, k in _multigraph_eulerian_circuit(G, source):
+            if keys:
+                yield u, v, k
+            else:
+                yield u, v
+    else:
+        for u, v in _simplegraph_eulerian_circuit(G, source):
+            yield u, v
+
+
+def has_eulerian_path(G):
+    """Return True iff `G` has an Eulerian path.
+
+    An Eulerian path is a path in a graph which uses each edge of a graph
+    exactly once.
+
+    A directed graph has an Eulerian path iff:
+        - at most one vertex has out_degree - in_degree = 1,
+        - at most one vertex has in_degree - out_degree = 1,
+        - every other vertex has equal in_degree and out_degree,
+        - and all of its vertices with nonzero degree belong to a
+        - single connected component of the underlying undirected graph.
+
+    An undirected graph has an Eulerian path iff:
+        - exactly zero or two vertices have odd degree,
+        - and all of its vertices with nonzero degree belong to a
+        - single connected component.
+
+    Parameters
+    ----------
+    G : NetworkX Graph
+        The graph to find an euler path in.
+
+    Returns
+    -------
+    Bool : True if G has an eulerian path.
+
+    See Also
+    --------
+    is_eulerian
+    eulerian_path
+    """
+    if G.is_directed():
+        ins = G.in_degree
+        outs = G.out_degree
+        semibalanced_ins = sum(ins(v) - outs(v) == 1 for v in G)
+        semibalanced_outs = sum(outs(v) - ins(v) == 1 for v in G)
+        return (semibalanced_ins <= 1 and
+                semibalanced_outs <= 1 and
+                sum(G.in_degree(v) != G.out_degree(v) for v in G) <= 2 and
+                nx.is_weakly_connected(G))
+    else:
+        return (sum(d % 2 == 1 for v, d in G.degree()) in (0, 2)
+                and nx.is_connected(G))
+
+
+def eulerian_path(G, source=None, keys=False):
+    """Return an iterator over the edges of an Eulerian path in `G`.
+
+    Parameters
+    ----------
+    G : NetworkX Graph
+        The graph in which to look for an eulerian path.
+    source : node or None (default: None)
+        The node at which to start the search. None means search over all
+        starting nodes.
+    keys : Bool (default: False)
+        Indicates whether to yield edge 3-tuples (u, v, edge_key).
+        The default yields edge 2-tuples
+
+    Yields
+    ------
+    Edge tuples along the eulerian path.
+
+    Warning: If `source` provided is not the start node of an Euler path
+    will raise error even if an Euler Path exists.
+    """
+    if not has_eulerian_path(G):
+        raise nx.NetworkXError("Graph has no Eulerian paths.")
+    if G.is_directed():
+        G = G.reverse()
+    else:
+        G = G.copy()
+    if source is None:
+        source = _find_path_start(G)
+    if G.is_multigraph():
+        for u, v, k in _multigraph_eulerian_circuit(G, source):
+            if keys:
+                yield u, v, k
+            else:
+                yield u, v
+    else:
+        for u, v in _simplegraph_eulerian_circuit(G, source):
+            yield u, v
+
+
+@not_implemented_for('directed')
+def eulerize(G):
+    """Transforms a graph into an Eulerian graph
+
+    Parameters
+    ----------
+    G : NetworkX graph
+       An undirected graph
+
+    Returns
+    -------
+    G : NetworkX multigraph
+
+    Raises
+    ------
+    NetworkXError
+       If the graph is not connected.
+
+    See Also
+    --------
+    is_eulerian
+    eulerian_circuit
+
+    References
+    ----------
+    .. [1] J. Edmonds, E. L. Johnson.
+       Matching, Euler tours and the Chinese postman.
+       Mathematical programming, Volume 5, Issue 1 (1973), 111-114.
+       [2] https://en.wikipedia.org/wiki/Eulerian_path
+    .. [3] http://web.math.princeton.edu/math_alive/5/Notes1.pdf
+
+    Examples
+    --------
+        >>> G = nx.complete_graph(10)
+        >>> H = nx.eulerize(G)
+        >>> nx.is_eulerian(H)
+        True
+
+    """
+    if G.order() == 0:
+        raise nx.NetworkXPointlessConcept("Cannot Eulerize null graph")
+    if not nx.is_connected(G):
+        raise nx.NetworkXError("G is not connected")
+    odd_degree_nodes = [n for n, d in G.degree() if d % 2 == 1]
+    G = nx.MultiGraph(G)
+    if len(odd_degree_nodes) == 0:
+        return G
+
+    # get all shortest paths between vertices of odd degree
+    odd_deg_pairs_paths = [(m,
+                            {n: nx.shortest_path(G, source=m, target=n)}
+                            )
+                           for m, n in combinations(odd_degree_nodes, 2)]
+
+    # use inverse path lengths as edge-weights in a new graph
+    # store the paths in the graph for easy indexing later
+    Gp = nx.Graph()
+    for n, Ps in odd_deg_pairs_paths:
+        for m, P in Ps.items():
+            if n != m:
+                Gp.add_edge(m, n, weight=1/len(P), path=P)
+
+    # find the minimum weight matching of edges in the weighted graph
+    best_matching = nx.Graph(list(nx.max_weight_matching(Gp)))
+
+    # duplicate each edge along each path in the set of paths in Gp
+    for m, n in best_matching.edges():
+        path = Gp[m][n]["path"]
+        G.add_edges_from(nx.utils.pairwise(path))
+    return G