diff --git a/ILP/butadien/butadiensynthesis.py b/ILP/butadien/butadiensynthesis.py index 698df50..1363847 100644 --- a/ILP/butadien/butadiensynthesis.py +++ b/ILP/butadien/butadiensynthesis.py @@ -1,3 +1,4 @@ +import math import gurobipy as gp from gurobipy import GRB, Model, quicksum @@ -65,6 +66,27 @@ HYPERGRAPH = { 211: (['Butadien', 'p_{0,11}'], ['p_{0,18}']), 213: ([], ['Butadien']), } + +HYPERGRAPH2 = { + 2: (['p_{0,0}'], []), + 3: (['p_{0,1}'], []), + 4: (['Butadien', 'Butadien'], ['p_{0,0}', 'p_{0,1}']), + 6: (['p_{0,2}'], []), + 7: (['Butadien', 'Butadien'], ['p_{0,2}']), + 17: (['p_{0,4}'], []), + 23: (['Butadien', 'p_{0,1}'], ['p_{0,0}', 'p_{0,4}']), + 41: (['p_{0,11}'], []), + 42: (['p_{0,4}'], ['p_{0,0}', 'p_{0,11}']), + 213: ([], ['Butadien']), +} + +HYPERGRAPH3 = { + 0: (['Butadien'], []), + 213: ([], ['Butadien']), + 4: (['Butadien', 'Butadien'], ['p_{0,0}', 'Butadien']), + 2: (['p_{0,0}'], []), +} + VERTICES = ['Butadien', 'p_{0,0}', 'p_{0,1}', 'p_{0,2}', 'p_{0,3}', 'p_{0,4}', 'p_{0,5}', 'p_{0,6}', 'p_{0,7}', 'p_{0,8}', 'p_{0,9}', 'p_{0,10}', 'p_{0,11}', 'p_{0,12}', 'p_{0,13}', 'p_{0,14}', 'p_{0,15}', 'p_{0,16}', 'p_{0,17}', 'p_{0,18}'] #Vergleich mit dem NMR von Ethylen und Hexatrien NMR1 = [0.32, 0.5, 0.87, 0.0, 0.11, 0.58, 0.06, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.09, 0.0, 0.0, 0.17, 0.0, 0.09] @@ -75,8 +97,11 @@ NMR3 = [0.0, 0.32, 0.0, 0.0, 0.0, 0.0, 0.05, 0.0, 0.0, 0.02, 0.0, 0.29, 0.95, 0. VERTICESSMILES = ['C=CC=C', 'C=C', 'C=CC=CC=C', 'C1CCC(C=C)CC=1', 'C(CCC(C=C)CC=C)=C', 'C=CC=CC=CC=C', 'C1CCC(C=CC=C)CC=1', 'C=CC1C=CCCC1', 'C1CCCCC=1', 'C=CC1CC=CCC1C=C', 'C1CCC(C=C)C(C=C)C=1', 'C(C1CC(C=C)C=CC1)=C', 'C1C=CC=CC=1', 'C(CCC1C=CC=CC1)=C', 'C1C(C=CC=C)CCCC=1', 'C=CC(C=C)CCCC=C', 'C=CCCCCC=C', 'C=CC1C=CC(C=C)CC1', 'C1CC2CCCCC2CC=1', 'C1CC2C=CC=CC2CC=1'] NMRMAX = [max(n1,n2,n3) for n1,n2,n3 in zip(NMR1,NMR2,NMR3)] +#Implement Edgelikelihood before Model + + FIXED_FLOWS = { - 213: 3, + #213: 3, #2: 3, #4: 1, #23: 1, @@ -89,6 +114,7 @@ def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, x = {e_id: model.addVar(vtype=GRB.INTEGER, lb = 0, name = f"x_{e_id}") for e_id in hyperedges} b = {e_id: model.addVar(vtype=GRB.BINARY, name = f"b_{e_id}") for e_id in hyperedges} + count = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, name = "count") nmax = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmrmax") n1 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr1") n2 = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr2") @@ -104,10 +130,16 @@ def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, n1[v] = nmr1 n2[v] = nmr2 n3[v] = nmr3 + count[v] = 0 #Assigns the edges a likelihood based on the products for e, (tails, heads) in hyperedges.items(): - if heads != [] and tails != []: + en1[e] = math.prod(n1[head] for head in heads) + en2[e] = math.prod(n2[head] for head in heads) + en3[e] = math.prod(n3[head] for head in heads) + enmax[e] = max([en1[e], en2[e], en3[e]]) + ''' + if heads != [] and tails != []: #Multiplication better? enmax[e] = quicksum(nmax[head] for head in heads)/len(heads) en1[e] = quicksum(n1[head] for head in heads)/len(heads) en2[e] = quicksum(n2[head] for head in heads)/len(heads) @@ -117,15 +149,15 @@ def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, en1[e] = 0.0 en2[e] = 0.0 en3[e] = 0.0 - - print(enmax[123]) - print(enmax[42]) + ''' + #print(enmax[123]) + #print(enmax[42]) vertices = set(v for tails, heads in hyperedges.values() for v in tails + heads) for v in vertices: - inflow = quicksum(x[e_id] for e_id, (_, heads) in hyperedges.items() if v in heads) - outflow = quicksum(x[e_id] for e_id, (tails, _) in hyperedges.items() if v in tails) + inflow = quicksum(x[e_id] * heads.count(v) for e_id, (_, heads) in hyperedges.items() if v in heads) + outflow = quicksum(x[e_id] * tails.count(v) for e_id, (tails, _) in hyperedges.items() if v in tails) model.addConstr(inflow == outflow, name = f"flow_conservation_{v}") for e_id, value in FIXED_FLOWS.items(): @@ -144,33 +176,40 @@ def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, #Multiplizier den node Wert mit infow + outflow model.ModelSense = GRB.MAXIMIZE - #Multiply node value with infow or outflow + #Multiply edgelikelihood with the edge use boolean model.setObjectiveN( - quicksum(enmax[e_id] * x[e_id] for e_id, (_, _) in hyperedges.items()), + quicksum(enmax[e_id] * b[e_id] for e_id, (_, _) in hyperedges.items()), index = 0, priority = 2, name = "maximize_nmr_similarity", ) - + #Minimize the overall flow model.setObjectiveN( - quicksum(x[e_id] for e_id in hyperedges), + quicksum(-1 * x[e_id] for e_id in hyperedges), index=1, - priority= - 1, + priority= 1, name="minimize_used_hyperedges", ) - + #Excluding creation and destruction only three reactions for three nmr model.addConstr(quicksum(b[e_id] for e_id, (heads, tails) in hyperedges.items() if tails != [] and heads != []) == 3) #Restrict number of used edges to prevent using all available - #model.addConstr(quicksum(x[e_id] for e_id in hyperedges) <= 10) + #model.addConstr(quicksum(x[e_id] for e_id in hyperedges) <= 16) - #2 Butadien create first different molecule: + #2 Butadien create first different molecule and it has to be created first: model.addConstr(b[4] + b[7] == 1) + model.addConstr(b[213] == 1) + #model.addConstr(b[41] == 1) #Every item created has to be consumed: - + for mol in vertices: + for edge, (heads, tails) in hyperedges.items(): + count[mol] += x[edge] * (heads.count(mol) - tails.count(mol)) + #model.addConstr(count[mol] == 0) + #No cyclic reaction pairs: + for e_id1, (heads1, tails1) in hyperedges.items(): for e_id2, (heads2, tails2) in hyperedges.items(): if (heads1, tails1) == (tails2, heads2):