Python Graph Algorithm instance analysis and python algorithm instance analysis

Python Graph Algorithm instance analysis and python algorithm instance analysis

This example describes the Python graph algorithm. We will share this with you for your reference. The details are as follows:

#encoding=utf-8import networkx,heapq,sysfrom matplotlib import pyplotfrom collections import defaultdict,OrderedDictfrom numpy import array# Data in graphdata.txt:# a b  4# a h  8# b c  8# b h  11# h i  7# h g  1# g i  6# g f  2# c f  4# c i  2# c d  7# d f  14# d e  9# f e  10def Edge(): return defaultdict(Edge)class Graph:  def __init__(self):    self.Link = Edge()    self.FileName = ''    self.Separator = ''  def MakeLink(self,filename,separator):    self.FileName = filename    self.Separator = separator    graphfile = open(filename,'r')    for line in graphfile:      items = line.split(separator)      self.Link[items[0]][items[1]] = int(items[2])      self.Link[items[1]][items[0]] = int(items[2])    graphfile.close()  def LocalClusteringCoefficient(self,node):    neighbors = self.Link[node]    if len(neighbors) <= 1: return 0    links = 0    for j in neighbors:      for k in neighbors:        if j in self.Link[k]:          links += 0.5    return 2.0*links/(len(neighbors)*(len(neighbors)-1))  def AverageClusteringCoefficient(self):    total = 0.0    for node in self.Link.keys():      total += self.LocalClusteringCoefficient(node)    return total/len(self.Link.keys())  def DeepFirstSearch(self,start):    visitedNodes = []    todoList = [start]    while todoList:      visit = todoList.pop(0)      if visit not in visitedNodes:        visitedNodes.append(visit)        todoList = self.Link[visit].keys() + todoList    return visitedNodes  def BreadthFirstSearch(self,start):    visitedNodes = []    todoList = [start]    while todoList:      visit = todoList.pop(0)      if visit not in visitedNodes:        visitedNodes.append(visit)        todoList = todoList + self.Link[visit].keys()    return visitedNodes  def ListAllComponent(self):    allComponent = []    visited = {}    for node in self.Link.iterkeys():      if node not in visited:        oneComponent = self.MakeComponent(node,visited)        allComponent.append(oneComponent)    return allComponent  def CheckConnection(self,node1,node2):    return True if node2 in self.MakeComponent(node1,{}) else False  def MakeComponent(self,node,visited):    visited[node] = True    component = [node]    for neighbor in self.Link[node]:      if neighbor not in visited:        component += self.MakeComponent(neighbor,visited)    return component  def MinimumSpanningTree_Kruskal(self,start):    graphEdges = [line.strip('\n').split(self.Separator) for line in open(self.FileName,'r')]    nodeSet = {}    for idx,node in enumerate(self.MakeComponent(start,{})):      nodeSet[node] = idx    edgeNumber = 0; totalEdgeNumber = len(nodeSet)-1    for oneEdge in sorted(graphEdges,key=lambda x:int(x[2]),reverse=False):      if edgeNumber == totalEdgeNumber: break      nodeA,nodeB,cost = oneEdge      if nodeA in nodeSet and nodeSet[nodeA] != nodeSet[nodeB]:        nodeBSet = nodeSet[nodeB]        for node in nodeSet.keys():          if nodeSet[node] == nodeBSet:            nodeSet[node] = nodeSet[nodeA]        print nodeA,nodeB,cost        edgeNumber += 1  def MinimumSpanningTree_Prim(self,start):    expandNode = set(self.MakeComponent(start,{}))    distFromTreeSoFar = {}.fromkeys(expandNode,sys.maxint); distFromTreeSoFar[start] = 0    linkToNode = {}.fromkeys(expandNode,'');linkToNode[start] = start    while expandNode:      # Find the closest dist node      closestNode = ''; shortestdistance = sys.maxint;      for node,dist in distFromTreeSoFar.iteritems():        if node in expandNode and dist < shortestdistance:          closestNode,shortestdistance = node,dist      expandNode.remove(closestNode)      print linkToNode[closestNode],closestNode,shortestdistance      for neighbor in self.Link[closestNode].iterkeys():        recomputedist = self.Link[closestNode][neighbor]        if recomputedist < distFromTreeSoFar[neighbor]:          distFromTreeSoFar[neighbor] = recomputedist          linkToNode[neighbor] = closestNode  def ShortestPathOne2One(self,start,end):    pathFromStart = {}    pathFromStart[start] = [start]    todoList = [start]    while todoList:      current = todoList.pop(0)      for neighbor in self.Link[current]:        if neighbor not in pathFromStart:          pathFromStart[neighbor] = pathFromStart[current] + [neighbor]          if neighbor == end:            return pathFromStart[end]          todoList.append(neighbor)    return []  def Centrality(self,node):    path2All = self.ShortestPathOne2All(node)    # The average of the distances of all the reachable nodes    return float(sum([len(path)-1 for path in path2All.itervalues()]))/len(path2All)  def SingleSourceShortestPath_Dijkstra(self,start):    expandNode = set(self.MakeComponent(start,{}))    distFromSourceSoFar = {}.fromkeys(expandNode,sys.maxint); distFromSourceSoFar[start] = 0    while expandNode:      # Find the closest dist node      closestNode = ''; shortestdistance = sys.maxint;      for node,dist in distFromSourceSoFar.iteritems():        if node in expandNode and dist < shortestdistance:          closestNode,shortestdistance = node,dist      expandNode.remove(closestNode)      for neighbor in self.Link[closestNode].iterkeys():        recomputedist = distFromSourceSoFar[closestNode] + self.Link[closestNode][neighbor]        if recomputedist < distFromSourceSoFar[neighbor]:          distFromSourceSoFar[neighbor] = recomputedist    for node in distFromSourceSoFar:      print start,node,distFromSourceSoFar[node]  def AllpairsShortestPaths_MatrixMultiplication(self,start):    nodeIdx = {}; idxNode = {};     for idx,node in enumerate(self.MakeComponent(start,{})):      nodeIdx[node] = idx; idxNode[idx] = node    matrixSize = len(nodeIdx)    MaxInt = 1000    nodeMatrix = array([[MaxInt]*matrixSize]*matrixSize)    for node in nodeIdx.iterkeys():      nodeMatrix[nodeIdx[node]][nodeIdx[node]] = 0    for line in open(self.FileName,'r'):      nodeA,nodeB,cost = line.strip('\n').split(self.Separator)      if nodeA in nodeIdx:        nodeMatrix[nodeIdx[nodeA]][nodeIdx[nodeB]] = int(cost)        nodeMatrix[nodeIdx[nodeB]][nodeIdx[nodeA]] = int(cost)    result = array([[0]*matrixSize]*matrixSize)    for i in xrange(matrixSize):      for j in xrange(matrixSize):        result[i][j] = nodeMatrix[i][j]    for itertime in xrange(2,matrixSize):      for i in xrange(matrixSize):        for j in xrange(matrixSize):          if i==j:            result[i][j] = 0            continue          result[i][j] = MaxInt          for k in xrange(matrixSize):            result[i][j] = min(result[i][j],result[i][k]+nodeMatrix[k][j])    for i in xrange(matrixSize):      for j in xrange(matrixSize):        if result[i][j] != MaxInt:          print idxNode[i],idxNode[j],result[i][j]  def ShortestPathOne2All(self,start):    pathFromStart = {}    pathFromStart[start] = [start]    todoList = [start]    while todoList:      current = todoList.pop(0)      for neighbor in self.Link[current]:        if neighbor not in pathFromStart:          pathFromStart[neighbor] = pathFromStart[current] + [neighbor]          todoList.append(neighbor)    return pathFromStart  def NDegreeNode(self,start,n):    pathFromStart = {}    pathFromStart[start] = [start]    pathLenFromStart = {}    pathLenFromStart[start] = 0    todoList = [start]    while todoList:      current = todoList.pop(0)      for neighbor in self.Link[current]:        if neighbor not in pathFromStart:          pathFromStart[neighbor] = pathFromStart[current] + [neighbor]          pathLenFromStart[neighbor] = pathLenFromStart[current] + 1          if pathLenFromStart[neighbor] <= n+1:            todoList.append(neighbor)    for node in pathFromStart.keys():      if len(pathFromStart[node]) != n+1:        del pathFromStart[node]    return pathFromStart  def Draw(self):    G = networkx.Graph()    nodes = self.Link.keys()    edges = [(node,neighbor) for node in nodes for neighbor in self.Link[node]]    G.add_edges_from(edges)    networkx.draw(G)    pyplot.show()if __name__=='__main__':  separator = '\t'  filename = 'C:\\Users\\Administrator\\Desktop\\graphdata.txt'  resultfilename = 'C:\\Users\\Administrator\\Desktop\\result.txt'  myGraph = Graph()  myGraph.MakeLink(filename,separator)  print 'LocalClusteringCoefficient',myGraph.LocalClusteringCoefficient('a')  print 'AverageClusteringCoefficient',myGraph.AverageClusteringCoefficient()  print 'DeepFirstSearch',myGraph.DeepFirstSearch('a')  print 'BreadthFirstSearch',myGraph.BreadthFirstSearch('a')  print 'ShortestPathOne2One',myGraph.ShortestPathOne2One('a','d')  print 'ShortestPathOne2All',myGraph.ShortestPathOne2All('a')  print 'NDegreeNode',myGraph.NDegreeNode('a',3).keys()  print 'ListAllComponent',myGraph.ListAllComponent()  print 'CheckConnection',myGraph.CheckConnection('a','f')  print 'Centrality',myGraph.Centrality('c')  myGraph.MinimumSpanningTree_Kruskal('a')  myGraph.AllpairsShortestPaths_MatrixMultiplication('a')  myGraph.MinimumSpanningTree_Prim('a')  myGraph.SingleSourceShortestPath_Dijkstra('a')  # myGraph.Draw()