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graph.py
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graph.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2014 Martin Raspaud
# Author(s):
# Martin Raspaud <martin.raspaud@smhi.se>
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
"""Graph manipulation.
"""
import numpy as np
class Graph(object):
def __init__(self, n_vertices=None, adj_matrix=None):
if n_vertices is not None:
self.order = n_vertices
self.vertices = np.arange(self.order)
self.adj_matrix = np.zeros((self.order, self.order), np.bool)
self.weight_matrix = np.zeros((self.order, self.order), np.float)
elif adj_matrix is not None:
self.order = adj_matrix.shape[0]
self.vertices = np.arange(self.order)
self.adj_matrix = adj_matrix
self.weight_matrix = np.zeros_like(adj_matrix)
def weight(self, u, v):
"""weight of the *u*-*v* edge.
"""
return self.weight_matrix[u, v]
def neighbours(self, v):
return self.vertices[self.adj_matrix[v, :] != 0]
def add_edge(self, v1, v2, weight=1):
self.weight_matrix[v1, v2] = weight
self.weight_matrix[v2, v1] = weight
self.adj_matrix[v1, v2] = True
self.adj_matrix[v2, v1] = True
def add_arc(self, v1, v2, weight=1):
self.adj_matrix[v1, v2] = True
self.weight_matrix[v1, v2] = weight
def bron_kerbosch(self, r, p, x):
"""Get the maximal cliques.
"""
if len(p) == 0 and len(x) == 0:
yield r
for v in p:
for res in self.bron_kerbosch(r | set((v, )),
p & set(self.neighbours(v)),
x & set(self.neighbours(v))):
yield res
p = p - set((v, ))
x = x | set((v, ))
def dag_longest_path(self, v1, v2=None):
"""Give the longest path from *v1* to all other vertices or *v2* if
specified. Assumes the vertices are sorted topologically and that the
graph is directed and acyclic (DAG).
"""
self.weight_matrix = -self.weight_matrix
dist, path = self.dag_shortest_path(v1, v2)
self.weight_matrix = -self.weight_matrix
return dist, path
def dag_shortest_path(self, v1, v2=None):
"""Give the sortest path from *v1* to all other vertices or *v2* if
specified. Assumes the vertices are sorted topologically and that the
graph is directed and acyclic (DAG). *v1* and *v2* are the indices of
the vertices in the vertice list.
"""
# Dijkstra for DAGs.
dists = [np.inf] * self.order
paths = [list() for _ in range(self.order)]
dists[v1] = 0
for u in self.vertices:
# could be interrupted when we reach v2 ?
for v in self.neighbours(u):
if (dists[v] > dists[u] + self.weight(u, v)):
dists[v] = dists[u] + self.weight(u, v)
paths[v] = u
if v2 is None:
return dists, paths
else:
end = v2
path = [end]
while end != v1:
path.append(paths[end])
end = paths[end]
return dists[v2], path
def save(self, filename):
np.savez_compressed(filename,
adj=self.adj_matrix,
weights=self.weight_matrix)
def load(self, filename):
stuff = np.load(filename)
self.adj_matrix = stuff["adj"]
self.weight_matrix = stuff["weights"]
self.order = self.adj_matrix.shape[0]
self.vertices = np.arange(self.order)
def export(self, filename="./sched.gv", labels=None):
"""dot sched.gv -Tpdf -otruc.pdf
"""
with open(filename, "w") as fd_:
fd_.write("digraph schedule { \n size=\"80, 10\";\n center=\"1\";\n")
for v1 in range(1, self.order - 1):
for v2 in range(1, self.order - 1):
if self.adj_matrix[v1, v2]:
fd_.write('"' + str(labels[v1 - 1]) + '"' + " -> " +
'"' + str(labels[v2 - 1]) + '"' +
' [ label = "' + str(self.weight_matrix[v1, v2]) + '" ];\n')
fd_.write("}\n")