import graphFunctions
import searchTree
import searchTreeNode as nd
import time
# E-mail stuff
import smtplib
for i in range(6):
# Name of the file containing edges for the graph
FILENAME = "sampleGraphs/links2010.edges-" + str(i) + ".anonGraph"
content = FILENAME + "\n"
graph = graphFunctions.read_edges_from_file(FILENAME, " ")
for j in range(graph.number_of_nodes()/8, graph.number_of_nodes()/2):
for k in range(1, len(graph.edges())/12):
tree = searchTree.SearchTree()
print "Working on a graph with", graph.number_of_nodes(), "vertices"
msg = "Working on a graph with " + str(graph.number_of_nodes()) + " vertices\n"
tree.set_root(nd.Node(graph.edges(),0))
print "Looking for at most", k, "edges to delete, so as to"
print "separate the graph into components of size at most", j, "nodes"
msg = msg + "Looking for at most " + k + " edges to delete, so as to\n"
msg = msg + "separate the graph into components of size at most " + j + " nodes\n"
# Code to track execution time
print "Starting search..."
start_time = time.time()
# Change search method HERE --v
minEdges = tree.breadth_first_search(15,3)
import graphFunctions
import searchTree
import searchTreeNode as nd
import time
# E-mail stuff
import smtplib
for i in range(6):
# Name of the file containing edges for the graph
FILENAME = "sampleGraphs/links2010.edges-" + str(i) + ".anonGraph"
content = FILENAME + "\n"
graph = graphFunctions.read_edges_from_file(FILENAME, " ")
for j in range(graph.number_of_nodes() / 8, graph.number_of_nodes() / 2):
for k in range(1, len(graph.edges()) / 12):
tree = searchTree.SearchTree()
print "Working on a graph with", graph.number_of_nodes(
), "vertices"
msg = "Working on a graph with " + str(
graph.number_of_nodes()) + " vertices\n"
tree.set_root(nd.Node(graph.edges(), 0))
print "Looking for at most", k, "edges to delete, so as to"
print "separate the graph into components of size at most", j, "nodes"
msg = msg + "Looking for at most " + k + " edges to delete, so as to\n"
msg = msg + "separate the graph into components of size at most " + j + " nodes\n"
# Code to track execution time
print "Starting search..."
start_time = time.time()
baseFiles.append(line.strip())
startString = "TreeDecomp"
endString = ".dgf.txt"
for baseFile in baseFiles:
decompName = startString + baseFile + endString
tree = jd.readDot(decompName)
root = tree.nodes()[0]
neighbours = tree.neighbors(root)
td.make_it_nice(tree, root, neighbours)
graph = gf.read_edges_from_file(baseFile, " ")
root = tree.nodes()[0]
tree = td.get_nice_tree_decomp(tree, root)
orderOfComputation = list(nx.dfs_postorder_nodes(tree,root))
delValuesTable = {}
for guy in orderOfComputation:
print str(guy) +" has kind " + tree.node[guy ]["kind"] + " and bag " + tree.node[guy ]["label"] + " and neighbours " + str(tree.neighbors(guy))
maxK = len(graph.edges())
maxH = 6
hSolved = False
start1 = time.time()
for h in range(5, maxH):
baseFiles = []
for line in open(fileOfFiles):
baseFiles.append(line.strip())
startString = "TreeDecomp"
endString = ".dgf.txt"
for baseFile in baseFiles:
decompName = startString + baseFile + endString
tree = jd.readDot(decompName)
root = tree.nodes()[0]
neighbours = tree.neighbors(root)
td.make_it_nice(tree, root, neighbours)
graph = gf.read_edges_from_file(baseFile, " ")
root = tree.nodes()[0]
tree = td.get_nice_tree_decomp(tree, root)
orderOfComputation = list(nx.dfs_postorder_nodes(tree, root))
delValuesTable = {}
for guy in orderOfComputation:
print str(guy) + " has kind " + tree.node[guy][
"kind"] + " and bag " + tree.node[guy][
"label"] + " and neighbours " + str(tree.neighbors(guy))
maxK = len(graph.edges())
maxH = 6
hSolved = False
start1 = time.time()
import treeDecomposition as td
import time
# E-mail stuff
import smtplib
INFINITY = 999999999
for i in range(6):
# Name of the file containing edges for the graph
GRAPHNAME = "sampleGraphs/links2012.edges-"+ str(i) +".anonGraph"
TREENAME = "TreeDecomplinks2012.edges-" + str(i) + ".anonGraph.dgf.txt"
#content = GRAPHNAME + "\n" + TREENAME + "\n\n"
print "GraphName =", GRAPHNAME
print "DecompName =", TREENAME
treeDecomp = nx.read_dot(TREENAME)
graph = gf.read_edges_from_file(GRAPHNAME, " ")
root = treeDecomp.nodes()[0]
niceTreeDecomp = td.get_nice_tree_decomp(treeDecomp, root)
for j in range(graph.number_of_nodes()/8, graph.number_of_nodes()/2):
for k in range(1, len(graph.edges())):
print "Working on a graph with", graph.number_of_nodes(), "vertices"
#msg = "Working on a graph with " + str(graph.number_of_nodes()) + " vertices\n"
print "Looking for at most", k, "edges to delete, so as to"
print "separate the graph into components of size at most", j, "nodes"
#msg = msg + "Looking for at most " + str(k) + " edges to delete, so as to\n"
#msg = msg + "separate the graph into components of size at most " + str(j) + " nodes\n"
# Code to track execution time
print "Starting search..."
print "Calling td.apply_algorithm(graph, treeDecomp, ",j,",",k,")"