#config.ilp.solver="CPLEX" #import mod #from mod import * import networkx as nx # import Graph class from graph.py from graph import GraphObj butadien = Graph.fromGMLString( """graph [ node [ id 0 label "C" ] node [ id 1 label "C" ] node [ id 2 label "C" ] node [ id 3 label "C" ] node [ id 4 label "H" ] node [ id 5 label "H" ] node [ id 6 label "H" ] node [ id 7 label "H" ] node [ id 8 label "H" ] node [ id 9 label "H" ] edge [ source 0 target 1 label "=" ] edge [ source 1 target 2 label "-" ] edge [ source 2 target 3 label "=" ] edge [ source 0 target 4 label "-" ] edge [ source 0 target 5 label "-" ] edge [ source 1 target 6 label "-" ] edge [ source 2 target 7 label "-" ] edge [ source 3 target 8 label "-" ] edge [ source 3 target 9 label "-" ] ]""" , name="Butadien") #pentadien = Graph.fromGMLString( """graph [ node [ id 0 label "C" ] node [ id 1 label "C" ] node [ id 2 label "C" ] node [ id 3 label "C" ] node [ id 4 label "H" ] node [ id 5 label "H" ] node [ id 6 label "H" ] node [ id 7 label "H" ] node [ id 8 label "H" ] node [ id 9 label "C" ] node [ id 10 label "H" ] node [ id 11 label "H" ] node [ id 12 label "H" ] edge [ source 0 target 1 label "=" ] edge [ source 1 target 2 label "-" ] edge [ source 2 target 3 label "=" ] edge [ source 0 target 4 label "-" ] edge [ source 0 target 5 label "-" ] edge [ source 1 target 6 label "-" ] edge [ source 2 target 7 label "-" ] edge [ source 3 target 8 label "-" ] edge [ source 3 target 9 label "-" ] edge [ source 9 target 10 label "-" ] edge [ source 9 target 11 label "-" ] edge [ source 9 target 12 label "-" ] ] """ #, name="Pentadien") restswap = Rule.fromGMLString( """rule [ left [ edge [ source 1 target 2 label "=" ] edge [ source 3 target 4 label "=" ] ] context [ node [ id 1 label "C" ] node [ id 2 label "C"] node [ id 3 label "C"] node [ id 4 label "C"] ] right [ edge [ source 1 target 3 label "=" ] edge [ source 2 target 4 label "=" ] ] ]""" ) dielsalder = Rule.fromGMLString( """rule [ left [ edge [ source 1 target 2 label "=" ] edge [ source 2 target 3 label "-" ] edge [ source 3 target 4 label "=" ] edge [ source 5 target 6 label "=" ] ] context [ node [ id 1 label "C" ] node [ id 2 label "C"] node [ id 3 label "C"] node [ id 4 label "C"] node [ id 5 label "C"] node [ id 6 label "C"] ] right [ edge [ source 1 target 2 label "-" ] edge [ source 2 target 3 label "=" ] edge [ source 3 target 4 label "-" ] edge [ source 4 target 5 label "-" ] edge [ source 5 target 6 label "-" ] edge [ source 6 target 1 label "-" ] ] ]""" ) def cyclesizes(g): nxGraph = GraphObj(g).nx_graph #Chein restrictions: (No steric reason) paths = sorted(list(nx.all_simple_paths(nxGraph))) if max(paths > 12): return True #Cycle restrictions: cycles = sorted(list(nx.chordless_cycles(nxGraph))) cycle_lengths = [len(x) for x in cycles] if cycles == []: return False #One Atom can't be in four different cycles for vertice in nxGraph.nodes: counter = 0 for cycle in cycles: if vertice in cycle: counter += 1 if counter >= 4: return True #One Cycle can't overlapp with another on over 2 Connection points for cycle in cycles: for cycleref in cycles: if cycle != cycleref and len(list(set(cycle) & set(cycleref))) >= 3: return True #Only cordless cycles of length 5,6 and 7 are acceptable if min(cycle_lengths) >= 5 and max(cycle_lengths) <=7: return False return True #Disallows Allenes (Two Doublebonds on same carbon) def doubledoublebond(g): for vertice in g.vertices: if (vertice.stringLabel == "C" and vertice.degree == 2): # and vertice.edges.label == ["=", "="] for edge in vertice.incidentEdges: print(type(edge.bondType)) bonds = [type(edge.bondType) for edge in vertice.incidentEdges] if (bonds[0] == bonds[1] and len(bonds) == 2): return True return False def restriction(dg): #Only rings 5 to 7 #No neighbouring double bonds. Is this already in MOD? Can this even happen? #No Carbon in 3 rings? Better 4? for a in dg.right: if a.vLabelCount("C") > 10: return False if doubledoublebond(a): return False if cyclesizes(a): return False return True flowPrinter = FlowPrinter() flowPrinter.printUnfiltered = False postSection("Loaded Graphs") for a in inputGraphs: a.print() postSection("Loaded Rules") for a in inputRules: a.print() dg = DG(graphDatabase=inputGraphs) dg.build().execute( addSubset(inputGraphs) >> rightPredicate[ restriction ]( repeat(revive(inputRules)) #Revive not necessary ) ) dg.print() postSection("Product Graphs") for a in dg.vertices: a.graph.print() #flow = Flow(dg) #flow.addSource(butadien) #flow.findSolutions() #flow.solutions.list() #flow.solutions.print(flowPrinter) sys.exit(0) rc = rcEvaluator(inputRules) for dRef in dg.derivations: der = dRef.derivation educt = rcId(der.left[0]) for i in range(1, len(der.left)): educt = educt *rcParallel* rcId(der.left[i]) product = rcId(der.right[0]) for i in range(1, len(der.right)): product = product *rcParallel* rcId(der.right[i]) rcExp = educt *rcSuper(allowPartial=False)* der.rule *rcSuper(allowPartial=False)* product res = rc.eval(rcExp) dRef.print() for a in res: a.print() a.printGML()