| #!/usr/bin/env python |
| import time |
| import random |
| |
| class Graph: |
| """ |
| Graph class provides implementations of graph algorithms. |
| The functions currently supported include: |
| - Comparing two graphs with specified attributes for vertices and edges |
| - Getting DFI (Depth First Index) and back edges during a DFS |
| - Chain decomposition of a graph |
| - Finding (non-)cut-edges and vertices |
| """ |
| |
| def __init__( self ): |
| # We use a dictionary to store all information about the graph |
| self.graphDict = {} |
| # Depth-first index of each vertex |
| self.DFI = {} |
| self.currentDFI = 0 |
| # Parent vertex (and edge to that vertex) of each vertex in depth-first search tree |
| self.parentVertexInDFS = {} |
| self.parentEdgeInDFS = {} |
| # Back edges of the graph generated during DFS |
| self.backEdges = {} |
| # All chains in chain decomposition algorithm |
| self.chains = [] |
| |
| def update( self, graphDict ): |
| """ |
| Update the graph data. The current graph dictionary will be replaced by the |
| new one. |
| graphDict is in a dictionary which maps each vertex to a list of attributes. |
| An example of graphDict: |
| { vertex1: { 'edges': ..., 'name': ..., 'protocol': ... }, |
| vertex2: { 'edges': ..., 'name': ..., 'protocol': ... } } |
| Each vertex should at least have an 'edges' attribute which describes the |
| adjacency information. The value of 'edges' attribute is also represented by |
| a dictionary, which maps each edge (identified by the neighbor vertex) to a |
| list of attributes. |
| An example of the edges dictionary: |
| 'edges': { vertex2: { 'port': ..., 'type': ... }, |
| vertex3: { 'port': ..., 'type': ... } } |
| """ |
| self.graphDict = graphDict |
| return main.TRUE |
| |
| def compareGraphs( self, graphDictA, graphDictB, vertexAttributes=['edges'], edgeAttributes=['port'] ): |
| """ |
| Compare two graphs. |
| By default only the adjacency relationship, i.e. 'port' attribute in |
| 'edges' attribute for each vertex, is compared, To get other attributes |
| included, attribute name needs to be specified in the args, e.g. |
| vertexAttributes=[ 'edges', 'protocol' ] or |
| edgeAttributes=[ 'port', 'type' ] |
| Return main.TRUE if two graphs are equal, otherwise main.FALSE |
| """ |
| try: |
| result = main.TRUE |
| for vertex in set( graphDictA ).difference( graphDictB ): |
| result = main.FALSE |
| main.log.warn( "Graph: graph B: vertex {} not found".format( vertex ) ) |
| for vertex in set( graphDictB ).difference( graphDictA ): |
| result = main.FALSE |
| main.log.warn( "Graph: graph A: vertex {} not found".format( vertex ) ) |
| for vertex in set( graphDictA ).intersection( graphDictB ): |
| for vertexAttribute in vertexAttributes: |
| attributeFound = True |
| if vertexAttribute not in graphDictA[ vertex ]: |
| main.log.warn( "Graph: graph A -> vertex {}: attribute {} not found".format( vertex, vertexAttribute ) ) |
| attributeFound = False |
| if vertexAttribute not in graphDictB[ vertex ]: |
| attributeFound = False |
| main.log.warn( "Graph: graph B -> vertex {}: attribute {} not found".format( vertex, vertexAttribute ) ) |
| if not attributeFound: |
| result = main.FALSE |
| continue |
| else: |
| # Compare two attributes |
| attributeValueA = graphDictA[ vertex ][ vertexAttribute ] |
| attributeValueB = graphDictB[ vertex ][ vertexAttribute ] |
| # FIXME: the comparison may not work for (sub)attribute values that are of list type |
| # For attributes except for 'edges', we just rely on '==' for comparison |
| if not vertexAttribute == 'edges': |
| if not attributeValueA == attributeValueB: |
| result = main.FALSE |
| main.log.warn( "Graph: vertex {}: {} does not match: {} and {}".format( vertex, |
| vertexAttribute, |
| attributeValueA, |
| attributeValueB ) ) |
| # The structure of 'edges' is similar to that of graphs, so we use the same method for comparison |
| else: |
| edgeDictA = attributeValueA |
| edgeDictB = attributeValueB |
| for neighbor in set( edgeDictA ).difference( edgeDictB ): |
| result = main.FALSE |
| main.log.warn( "Graph: graph B -> vertex {}: neighbor {} not found".format( vertex, neighbor ) ) |
| for neighbor in set( edgeDictB ).difference( edgeDictA ): |
| result = main.FALSE |
| main.log.warn( "Graph: graph A -> vertex {}: neighbor {} not found".format( vertex, neighbor ) ) |
| for neighbor in set( edgeDictA ).intersection( edgeDictB ): |
| for edgeAttribute in edgeAttributes: |
| attributeFound = True |
| if edgeAttribute not in edgeDictA[ neighbor ]: |
| attributeFound = False |
| main.log.warn( "Graph: graph A -> vertex {} -> neighbor {}: attribute {} not found".format( vertex, |
| neighbor, |
| edgeAttribute ) ) |
| if edgeAttribute not in edgeDictB[ neighbor ]: |
| attributeFound = False |
| main.log.warn( "Graph: graph B -> vertex {} -> neighbor {}: attribute {} not found".format( vertex, |
| neighbor, |
| edgeAttribute ) ) |
| if not attributeFound: |
| result = main.FALSE |
| continue |
| else: |
| # Compare two attributes |
| attributeValueA = edgeDictA[ neighbor ][ edgeAttribute ] |
| attributeValueB = edgeDictB[ neighbor ][ edgeAttribute ] |
| if not attributeValueA == attributeValueB: |
| result = main.FALSE |
| main.log.warn( "Graph: vertex {} -> neighbor {}: {} does not match: {} and {}".format( vertex, |
| neighbor, |
| edgeAttribute, |
| attributeValueA, |
| attributeValueB ) ) |
| if not result: |
| main.log.debug( "Graph: graphDictA: {}".format( graphDictA ) ) |
| main.log.debug( "Graph: graphDictB: {}".format( graphDictB ) ) |
| return result |
| except TypeError: |
| main.log.exception( "Graph: TypeError exception found" ) |
| return main.ERROR |
| except KeyError: |
| main.log.exception( "Graph: KeyError exception found" ) |
| return main.ERROR |
| except Exception: |
| main.log.exception( "Graph: Uncaught exception" ) |
| return main.ERROR |
| |
| def getNonCutEdges( self ): |
| """ |
| Get a list of non-cut-edges (non-bridges). |
| The definition of a cut-edge (bridge) is: the deletion of a cut-edge will |
| increase the number of connected component of a graph. |
| The function is realized by impelementing Schmidt's algorithm based on |
| chain decomposition. |
| Returns a list of edges, e.g. |
| [ [ vertex1, vertex2 ], [ vertex2, vertex3 ] ] |
| """ |
| try: |
| if not self.depthFirstSearch(): |
| return None |
| if not self.findChains(): |
| return None |
| nonCutEdges = [] |
| for chain in self.chains: |
| for edge in chain: |
| nonCutEdges.append( edge ) |
| main.log.debug( 'Non-cut-edges: {}'.format( nonCutEdges ) ) |
| return nonCutEdges |
| except Exception: |
| main.log.exception( "Graph: Uncaught exception" ) |
| return None |
| |
| def getNonCutVertices( self ): |
| """ |
| Get a list of non-cut-vertices. |
| The definition of a cut-vertex is: the deletion of a cut-vertex will |
| increase the number of connected component of a graph. |
| The function is realized by impelementing Schmidt's algorithm based on |
| chain decomposition. |
| Returns a list of vertices, e.g. [ vertex1, vertex2, vertex3 ] |
| """ |
| try: |
| nonCutEdges = self.getNonCutEdges() |
| # find all cycle chains |
| cycleChains = [] |
| for chain in self.chains: |
| # if the source vertex of the first chain equals to the destination vertex of the last |
| # chain, the chain is a cycle chain |
| if chain[ 0 ][ 0 ] == chain[ -1 ][ 1 ]: |
| cycleChains.append( chain ) |
| main.log.debug( 'Cycle chains: {}'.format( cycleChains ) ) |
| # Get a set of vertices which are the first vertices of a cycle chain (excluding the first |
| # cycle chain), and these vertices are a subset of all cut-vertices |
| subsetOfCutVertices = [] |
| if len( cycleChains ) > 1: |
| for cycleChain in cycleChains[ 1: ]: |
| subsetOfCutVertices.append( cycleChain[ 0 ][ 0 ] ) |
| main.log.debug( 'Subset of cut vertices: {}'.format( subsetOfCutVertices ) ) |
| nonCutVertices = [] |
| assert nonCutEdges != None |
| for vertex in self.graphDict.keys(): |
| if vertex in subsetOfCutVertices: |
| continue |
| vertexIsNonCut = True |
| for neighbor in self.graphDict[ vertex ][ 'edges' ].keys(): |
| edge = [ vertex, neighbor ] |
| backwardEdge = [ neighbor, vertex ] |
| if not edge in nonCutEdges and not backwardEdge in nonCutEdges: |
| vertexIsNonCut = False |
| break |
| if vertexIsNonCut: |
| nonCutVertices.append( vertex ) |
| main.log.debug( 'Non-cut-vertices: {}'.format( nonCutVertices ) ) |
| return nonCutVertices |
| except KeyError: |
| main.log.exception( "Graph: KeyError exception found" ) |
| return None |
| except AssertionError: |
| main.log.exception( "Graph: AssertionError exception found" ) |
| return None |
| except Exception: |
| main.log.exception( "Graph: Uncaught exception" ) |
| return None |
| |
| def depthFirstSearch( self ): |
| """ |
| This function runs a depth-first search and gets DFI of each vertex as well |
| as generates the back edges |
| """ |
| try: |
| assert self.graphDict != None and len( self.graphDict ) != 0 |
| for vertex in self.graphDict.keys(): |
| self.DFI[ vertex ] = -1 |
| self.parentVertexInDFS[ vertex ] = '' |
| self.parentEdgeInDFS[ vertex ] = None |
| firstVertex = self.graphDict.keys()[ 0 ] |
| self.currentDFI = 0 |
| self.backEdges = {} |
| if not self.depthFirstSearchRecursive( firstVertex ): |
| return main.ERROR |
| return main.TRUE |
| except KeyError: |
| main.log.exception( "Graph: KeyError exception found" ) |
| return main.ERROR |
| except AssertionError: |
| main.log.exception( "Graph: AssertionError exception found" ) |
| return main.ERROR |
| except Exception: |
| main.log.exception( "Graph: Uncaught exception" ) |
| return main.ERROR |
| |
| def depthFirstSearchRecursive( self, vertex ): |
| """ |
| Recursive function for depth-first search |
| """ |
| try: |
| self.DFI[ vertex ] = self.currentDFI |
| self.currentDFI += 1 |
| for neighbor in self.graphDict[ vertex ][ 'edges' ].keys(): |
| edge = [ vertex, neighbor ] |
| backwardEdge = [ neighbor, vertex ] |
| if neighbor == self.parentVertexInDFS[ vertex ]: |
| continue |
| elif self.DFI[ neighbor ] == -1: |
| self.parentVertexInDFS[ neighbor ] = vertex |
| self.parentEdgeInDFS[ neighbor ] = backwardEdge |
| if not self.depthFirstSearchRecursive( neighbor ): |
| return main.ERROR |
| else: |
| key = self.DFI[ neighbor ] |
| if key in self.backEdges.keys(): |
| if not edge in self.backEdges[ key ] and\ |
| not backwardEdge in self.backEdges[ key ]: |
| self.backEdges[ key ].append( backwardEdge ) |
| else: |
| tempKey = self.DFI[ vertex ] |
| if tempKey in self.backEdges.keys(): |
| if not edge in self.backEdges[ tempKey ] and\ |
| not backwardEdge in self.backEdges[ tempKey ]: |
| self.backEdges[ key ] = [ backwardEdge ] |
| else: |
| self.backEdges[ key ] = [ backwardEdge ] |
| return main.TRUE |
| except KeyError: |
| main.log.exception( "Graph: KeyError exception found" ) |
| return main.ERROR |
| except Exception: |
| main.log.exception( "Graph: Uncaught exception" ) |
| return main.ERROR |
| |
| def findChains( self ): |
| """ |
| This function finds all the chains in chain-decomposition algorithm |
| """ |
| keyList = self.backEdges.keys() |
| keyList.sort() |
| vertexIsVisited = {} |
| self.chains = [] |
| for vertex in self.graphDict.keys(): |
| vertexIsVisited[ vertex ] = False |
| try: |
| for key in keyList: |
| backEdgeList = self.backEdges[ key ] |
| for edge in backEdgeList: |
| chain = [] |
| currentEdge = edge |
| sourceVertex = edge[ 0 ] |
| while True: |
| currentVertex = currentEdge[ 0 ] |
| nextVertex = currentEdge[ 1 ] |
| vertexIsVisited[ currentVertex ] = True |
| chain.append( currentEdge ) |
| if nextVertex == sourceVertex or vertexIsVisited[ nextVertex ] == True: |
| break |
| currentEdge = self.parentEdgeInDFS[ nextVertex ] |
| self.chains.append( chain ) |
| return main.TRUE |
| except KeyError: |
| main.log.exception( "Graph: KeyError exception found" ) |
| return main.ERROR |
| except Exception: |
| main.log.exception( "Graph: Uncaught exception" ) |
| return main.ERROR |