def grouped_shortest_pair(g, shortest_path, shortest_path_2):
'''Find shortest pair of paths of two interlacing original paths.
Last step of the optimal edge-disjoint and vertex-disjoint shortest-pair
algorithms.
@param g: original NetworkX Graph or DiGraph
@param shortest_path: list of path nodes
@param shortest_path_2: list of path nodes
@return path1: first non-interlacing shortest path
@return path2: second non-interlacing shortest path
'''
#shortest_path = int(shortest_path)
#shortest_path2 = int(shortest_path2)
src = shortest_path[0]
dst = shortest_path[-1]
assert src == shortest_path_2[0]
assert dst == shortest_path_2[-1]
g3 = nx.Graph()
g3.add_path(shortest_path)
g3.add_path(shortest_path_2)
# copy edges on path:
for a, b in edges_on_path(shortest_path):
g3[a][b]['weight'] = g[a][b]['weight']
g3.add_path(shortest_path_2)
for a, b in edges_on_path(shortest_path_2):
g3[a][b]['weight'] = g[a][b]['weight']
for a, b in interlacing_edges(shortest_path, shortest_path_2):
g3.remove_edge(a, b)
# Find a path through graph and remove edges used.
path1 = BFS(g3, src, dst)
for a, b in edges_on_path(path1):
g3.remove_edge(a, b)
path2 = BFS(g3, src, dst)
for a, b in edges_on_path(path2):
g3.remove_edge(a, b)
assert g3.number_of_edges() == 0
return path1, path2
def grouped_shortest_pair(g, shortest_path, shortest_path_2):
'''Find shortest pair of paths of two interlacing original paths.
Last step of the optimal edge-disjoint and vertex-disjoint shortest-pair
algorithms.
@param g: original NetworkX Graph or DiGraph
@param shortest_path: list of path nodes
@param shortest_path_2: list of path nodes
@return path1: first non-interlacing shortest path
@return path2: second non-interlacing shortest path
'''
#shortest_path = int(shortest_path)
#shortest_path2 = int(shortest_path2)
src = shortest_path[0]
dst = shortest_path[-1]
assert src == shortest_path_2[0]
assert dst == shortest_path_2[-1]
g3 = nx.Graph()
g3.add_path(shortest_path)
g3.add_path(shortest_path_2)
# copy edges on path:
for a, b in edges_on_path(shortest_path):
g3[a][b]['weight'] = g[a][b]['weight']
g3.add_path(shortest_path_2)
for a, b in edges_on_path(shortest_path_2):
g3[a][b]['weight'] = g[a][b]['weight']
for a, b in interlacing_edges(shortest_path, shortest_path_2):
g3.remove_edge(a, b)
# Find a path through graph and remove edges used.
path1 = BFS(g3, src, dst)
for a, b in edges_on_path(path1):
g3.remove_edge(a, b)
path2 = BFS(g3, src, dst)
for a, b in edges_on_path(path2):
g3.remove_edge(a, b)
assert g3.number_of_edges() == 0
return path1, path2
('G', 'H', 8),
('H', 'Z', 4),
('I', 'Z', 5)
])
# Figure 3.16a, pg 74
# Unfortunately, this graph is pictured without weights. Presumably the
# author intended for the central path to have unit weights and the other
# paths to have much larger weights.
graph_fig_3_16_a = nx.Graph()
graph_fig_3_16_a.add_path([i for i in 'AJKLMZIHGPNABCDEFZ'])
edges_to_add = ['JC', 'KD', 'LE', 'LF', 'GD', 'EH', 'IF']
for e in edges_to_add:
graph_fig_3_16_a.add_edge(e[0], e[1])
set_weights(graph_fig_3_16_a, 5.0)
for src, dst in edges_on_path([i for i in 'ABCDEFZ']):
graph_fig_3_16_a[src][dst]['weight'] = 1.0
# Figure 3.13a mod 1, pg 78
graph_fig_3_13_a_mod_1 = graph_fig_3_13_a.copy()
graph_fig_3_13_a_mod_1['G']['H']['weight'] = 3.0
# Figure 3.13a mod 2, pg 78
graph_fig_3_13_a_mod_2 = graph_fig_3_13_a.copy()
graph_fig_3_13_a_mod_2['G']['C']['weight'] = 3.0
graph_fig_3_13_a_mod_2['G']['D']['weight'] = 3.0
graph_fig_3_13_a_mod_2['H']['Z']['weight'] = 1.0
def compare_path_lists(test, one, two, g = None, total = None):
'''Compare two path lists.
('E', 'F', 1), ('E', 'H', 2),
('E', 'I', 3), ('F', 'Z', 1),
('F', 'I', 3), ('G', 'H', 8),
('H', 'Z', 4), ('I', 'Z', 5)])
# Figure 3.16a, pg 74
# Unfortunately, this graph is pictured without weights. Presumably the
# author intended for the central path to have unit weights and the other
# paths to have much larger weights.
graph_fig_3_16_a = nx.Graph()
graph_fig_3_16_a.add_path([i for i in 'AJKLMZIHGPNABCDEFZ'])
edges_to_add = ['JC', 'KD', 'LE', 'LF', 'GD', 'EH', 'IF']
for e in edges_to_add:
graph_fig_3_16_a.add_edge(e[0], e[1])
set_weights(graph_fig_3_16_a, 5.0)
for src, dst in edges_on_path([i for i in 'ABCDEFZ']):
graph_fig_3_16_a[src][dst]['weight'] = 1.0
# Figure 3.13a mod 1, pg 78
graph_fig_3_13_a_mod_1 = graph_fig_3_13_a.copy()
graph_fig_3_13_a_mod_1['G']['H']['weight'] = 3.0
# Figure 3.13a mod 2, pg 78
graph_fig_3_13_a_mod_2 = graph_fig_3_13_a.copy()
graph_fig_3_13_a_mod_2['G']['C']['weight'] = 3.0
graph_fig_3_13_a_mod_2['G']['D']['weight'] = 3.0
graph_fig_3_13_a_mod_2['H']['Z']['weight'] = 1.0
def compare_path_lists(test, one, two, g=None, total=None):
'''Compare two path lists.
