331 lines
9.6 KiB
Python
331 lines
9.6 KiB
Python
config.ilp.solver="CPLEX"
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#import mod
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#from mod import *
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import networkx as nx
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# import Graph class from graph.py
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from graph import GraphObj
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# Search enough flows to include the known rare causal solution.
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MAX_SOLUTIONS = 10
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PRINT_FULL_PPP_OUTPUT = False
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# Important: the default analysis checks causal realisability from the
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# explicitly declared source molecules only. We do not add catalysts/seeds
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# to rescue an otherwise non-realisable flow.
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USE_CATALYSTS = False
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#ethylen = Graph.fromGMLString(
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"""graph [
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node [ id 0 label "H" ]
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node [ id 1 label "H" ]
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node [ id 2 label "C" ]
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node [ id 3 label "C" ]
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node [ id 4 label "H" ]
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node [ id 5 label "H" ]
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edge [ source 0 target 2 label "-" ]
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edge [ source 1 target 2 label "-" ]
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edge [ source 2 target 3 label "=" ]
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edge [ source 3 target 4 label "-" ]
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edge [ source 3 target 5 label "-" ]
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]"""
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#, name="Ethylen")
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butadien = Graph.fromGMLString(
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"""graph [
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node [ id 0 label "C" ]
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node [ id 1 label "C" ]
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node [ id 2 label "C" ]
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node [ id 3 label "C" ]
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node [ id 4 label "H" ]
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node [ id 5 label "H" ]
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node [ id 6 label "H" ]
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node [ id 7 label "H" ]
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node [ id 8 label "H" ]
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node [ id 9 label "H" ]
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edge [ source 0 target 1 label "=" ]
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edge [ source 1 target 2 label "-" ]
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edge [ source 2 target 3 label "=" ]
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edge [ source 0 target 4 label "-" ]
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edge [ source 0 target 5 label "-" ]
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edge [ source 1 target 6 label "-" ]
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edge [ source 2 target 7 label "-" ]
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edge [ source 3 target 8 label "-" ]
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edge [ source 3 target 9 label "-" ]
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]"""
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, name="Butadien")
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#benzene = Graph.fromSMILES('c1=cc=cc=c1')
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#benzene = Graph.fromGMLString(
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"""graph [
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node [ id 0 label "C" ]
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node [ id 1 label "H" ]
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node [ id 2 label "C" ]
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node [ id 3 label "H" ]
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node [ id 4 label "C" ]
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node [ id 5 label "H" ]
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node [ id 6 label "C" ]
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node [ id 7 label "H" ]
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node [ id 8 label "C" ]
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node [ id 9 label "H" ]
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node [ id 10 label "C" ]
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node [ id 11 label "H" ]
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edge [ source 0 target 1 label "-" ]
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edge [ source 0 target 2 label "=" ]
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edge [ source 2 target 3 label "-" ]
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edge [ source 2 target 4 label "-" ]
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edge [ source 4 target 5 label "-" ]
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edge [ source 4 target 6 label "=" ]
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edge [ source 6 target 7 label "-" ]
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edge [ source 6 target 8 label "-" ]
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edge [ source 8 target 9 label "-" ]
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edge [ source 8 target 10 label "=" ]
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edge [ source 10 target 11 label "-" ]
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edge [ source 10 target 0 label "-" ]
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]"""
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#, name="Benzene")
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#pentadien = Graph.fromGMLString(
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"""graph
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[
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node [ id 0 label "C" ]
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node [ id 1 label "C" ]
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node [ id 2 label "C" ]
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node [ id 3 label "C" ]
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node [ id 4 label "H" ]
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node [ id 5 label "H" ]
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node [ id 6 label "H" ]
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node [ id 7 label "H" ]
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node [ id 8 label "H" ]
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node [ id 9 label "C" ]
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node [ id 10 label "H" ]
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node [ id 11 label "H" ]
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node [ id 12 label "H" ]
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edge [ source 0 target 1 label "=" ]
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edge [ source 1 target 2 label "-" ]
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edge [ source 2 target 3 label "=" ]
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edge [ source 0 target 4 label "-" ]
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edge [ source 0 target 5 label "-" ]
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edge [ source 1 target 6 label "-" ]
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edge [ source 2 target 7 label "-" ]
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edge [ source 3 target 8 label "-" ]
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edge [ source 3 target 9 label "-" ]
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edge [ source 9 target 10 label "-" ]
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edge [ source 9 target 11 label "-" ]
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edge [ source 9 target 12 label "-" ]
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]
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"""
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#, name="Pentadien")
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restswap = Rule.fromGMLString(
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"""rule [
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left [
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edge [ source 1 target 2 label "=" ]
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edge [ source 3 target 4 label "=" ]
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]
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context [
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node [ id 1 label "C" ]
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node [ id 2 label "C"]
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node [ id 3 label "C"]
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node [ id 4 label "C"]
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]
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right [
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edge [ source 1 target 3 label "=" ]
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edge [ source 2 target 4 label "=" ]
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]
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]"""
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)
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dielsalder = Rule.fromGMLString(
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"""rule [
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left [
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edge [ source 1 target 2 label "=" ]
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edge [ source 2 target 3 label "-" ]
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edge [ source 3 target 4 label "=" ]
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edge [ source 5 target 6 label "=" ]
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]
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context [
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node [ id 1 label "C" ]
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node [ id 2 label "C"]
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node [ id 3 label "C"]
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node [ id 4 label "C"]
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node [ id 5 label "C"]
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node [ id 6 label "C"]
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]
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right [
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edge [ source 1 target 2 label "-" ]
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edge [ source 2 target 3 label "=" ]
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edge [ source 3 target 4 label "-" ]
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edge [ source 4 target 5 label "-" ]
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edge [ source 5 target 6 label "-" ]
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edge [ source 6 target 1 label "-" ]
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]
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]"""
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)
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def cyclesizes(g):
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nxGraph = GraphObj(g).nx_graph
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#Restriction to E/Z? Benzen can't be created or consumed by the reaction due to steric difficulties
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#Chain restrictions: (No steric reason)
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for nodestart in nxGraph.nodes:
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for nodeend in nxGraph.nodes:
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if nodeend != nodestart:
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paths = sorted(list(nx.all_shortest_paths(nxGraph, nodestart, nodeend)))
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for path in paths:
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if len(path) > 10: #First node included in length
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return True
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#Cycle restrictions:
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cycles = sorted(list(nx.chordless_cycles(nxGraph)))
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cycle_lengths = [len(x) for x in cycles]
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if cycles == []:
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return False
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#One Atom can't be in four different cycles
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for vertice in nxGraph.nodes:
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counter = 0
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for cycle in cycles:
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if vertice in cycle:
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counter += 1
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if counter >= 4:
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return True
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#One Cycle can't overlapp with another on over 2 Connection points
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for cycle in cycles:
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for cycleref in cycles:
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if cycle != cycleref and len(list(set(cycle) & set(cycleref))) >= 3:
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return True
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#Only cordless cycles of length 5,6 and 7 are acceptable
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if min(cycle_lengths) >= 6 and max(cycle_lengths) <=6:
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return False
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return True
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#Disallows Allenes (Two Doublebonds on same carbon)
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def doubledoublebond(g):
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for vertice in g.vertices:
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if (vertice.stringLabel == "C" and vertice.degree == 2): # and vertice.edges.label == ["=", "="]
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for edge in vertice.incidentEdges:
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print(type(edge.bondType))
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bonds = [type(edge.bondType) for edge in vertice.incidentEdges]
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if (bonds[0] == bonds[1] and len(bonds) == 2):
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return True
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return False
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def restriction(dg):
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for a in dg.right:
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if a.vLabelCount("C") > 10:
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return False
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if doubledoublebond(a):
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return False
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if cyclesizes(a):
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return False
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return True
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flowPrinter = FlowPrinter()
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flowPrinter.printUnfiltered = False
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ethylen = Graph.fromSMILES('C=C')
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goal = Graph.fromSMILES('C1C=CC=CC=1')
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dg = DG(graphDatabase=inputGraphs)
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dg.build().execute(
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addSubset(inputGraphs)
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>> rightPredicate[
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restriction
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](
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repeat(revive(inputRules)) #Revive not necessary
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)
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)
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# Deliberately no automatic DG/product printing here. Use
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# PRINT_FULL_PPP_OUTPUT below if the complete PPP-style report is wanted.
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flow = Flow(dg)
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flow.addSource(butadien)
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flow.addSink(ethylen)
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flow.addSink(goal)
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flow.addConstraint(inFlow[butadien] >= 2)
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flow.addConstraint(outFlow[goal] == 1)
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def printStuff(flowToPrint):
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# Same output structure as in the PPP example.
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post.summarySection("Loaded Graphs")
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for a in inputGraphs:
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a.print()
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post.summarySection("Loaded Rules")
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for a in inputRules:
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a.print()
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dg.print()
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post.summarySection("Product Graphs")
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for v in dg.vertices:
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v.graph.print()
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# Important: flowToPrint contains only the one selected causal solution.
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flowToPrint.solutions.print()
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def makeSingleSolutionFlow(solution):
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"""
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Copy the original hyperflow model and fix all core flow variables to the
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values of one already-computed solution. The copied model can then be
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printed with the normal PPP printStuff(), but contains only this solution.
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"""
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selectedFlow = hyperflow.Model(flow)
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# Fix every reaction/hyperedge multiplicity.
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for e in dg.edges:
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selectedFlow.addConstraint(
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edgeFlow[e] == solution.eval(edgeFlow[e])
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)
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# Also fix all external input/output multiplicities.
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for v in dg.vertices:
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selectedFlow.addConstraint(
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inFlow[v] == solution.eval(inFlow[v])
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)
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selectedFlow.addConstraint(
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outFlow[v] == solution.eval(outFlow[v])
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)
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selectedFlow.findSolutions(maxNumSolutions=1)
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return selectedFlow
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# Keep the test small.
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flow.findSolutions(maxNumSolutions=MAX_SOLUTIONS)
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numSolutions = 0
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numRealisable = 0
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for s in flow.solutions:
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numSolutions += 1
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# Exact PPP causality analysis / rendering.
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query = causality.RealisabilityQuery(flow.dg)
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printer = DGPrinter()
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printer.graphvizPrefix = 'layout = "dot";'
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def vertexVisible(v):
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return s.eval(vertexFlow[v]) != 0
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printer.pushVertexVisible(vertexVisible)
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dag = query.findDAG(s)
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if dag:
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numRealisable += 1
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data = dag.getPrintData(False)
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dg.print(printer=printer, data=data)
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print("\n=== causality summary ===")
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print(f"hyperflow solutions checked: {numSolutions}")
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print(f"causally realisable: {numRealisable}")
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print(f"not causally realisable: {numSolutions - numRealisable}")
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