From c5b9d50963f0e33ff5a861e89c394224533a90bd Mon Sep 17 00:00:00 2001 From: kilian Date: Wed, 9 Sep 2026 12:45:34 +0200 Subject: [PATCH] Dateien nach "ILP/butadien" hochladen --- ILP/butadien/butadiensynthesis.py | 35 +++++++++++-------------------- 1 file changed, 12 insertions(+), 23 deletions(-) diff --git a/ILP/butadien/butadiensynthesis.py b/ILP/butadien/butadiensynthesis.py index ce29599..c2244c4 100644 --- a/ILP/butadien/butadiensynthesis.py +++ b/ILP/butadien/butadiensynthesis.py @@ -91,15 +91,15 @@ VERTICES = ['Butadien', 'p_{0,0}', 'p_{0,1}', 'p_{0,2}', 'p_{0,3}', 'p_{0,4}', ' #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] #Normalisiert -#NMR1 = [0.11, 0.18, 0.31, 0.0, 0.04, 0.21, 0.02, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.06, 0.0, 0.03] +NMR1 = [0.11, 0.18, 0.31, 0.0, 0.04, 0.21, 0.02, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.06, 0.0, 0.03] #Vergleich mit dem NMR von Ethylen und Octrien NMR2 = [0.33, 0.43, 0.6, 0.0, 0.13, 0.9, 0.07, 0.01, 0.0, 0.0, 0.01, 0.0, 0.0, 0.01, 0.1, 0.0, 0.0, 0.22, 0.0, 0.13] #Normalisiert -#NMR2 = [0.11, 0.15, 0.21, 0.0, 0.04, 0.31, 0.02, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.07, 0.0, 0.04] +NMR2 = [0.11, 0.15, 0.21, 0.0, 0.04, 0.31, 0.02, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.07, 0.0, 0.04] #Vergleich mit dem NMR von Ethylen und Benzol 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, 0.17, 0.0, 0.0, 0.0, 0.0, 0.0, 0.05] #Normalisiert -#NMR3 = [0.0, 0.17, 0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.01, 0.0, 0.16, 0.51, 0.09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03] +NMR3 = [0.0, 0.17, 0.0, 0.0, 0.0, 0.0, 0.03, 0.0, 0.0, 0.01, 0.0, 0.16, 0.51, 0.09, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03] 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)] @@ -128,7 +128,7 @@ EDGEMAX = {} modes = ["Product", "Average"] mode = modes[0] -#print(round(np.prod([1, 0.9]))) +#Ist es besser, die Edukte mit zu berücksichtigen? Dann hin rück gleich wahrscheinlich, aber nur 1 kann gewählt werden #Ordnet die Kantenwahrscheinlichkeit basierend auf dem Mittel oder Produkt der Wahrscheinlichkeiten der Produkte for edge, (tails, heads) in HYPERGRAPH.items(): if heads == [] or tails == []: @@ -136,7 +136,6 @@ for edge, (tails, heads) in HYPERGRAPH.items(): EDGE2[edge] = 0.0 EDGE3[edge] = 0.0 elif mode == "Product": - #Produkt klappt nur, wenn normalisierte Likelihoods #print([VERTICE1[head] for head in heads]) EDGE1[edge] = round(np.prod([VERTICE1[head] for head in heads]),2) EDGE2[edge] = round(np.prod([VERTICE2[head] for head in heads]),2) @@ -147,10 +146,10 @@ for edge, (tails, heads) in HYPERGRAPH.items(): EDGE3[edge] = round(sum(VERTICE3[head] for head in heads)/len(heads),2) EDGEMAX[edge] = max([EDGE1[edge], EDGE2[edge], EDGE3[edge]]) - print(EDGEMAX[edge], HYPERGRAPH[edge]) -print(EDGEMAX[4]) -print(EDGEMAX[23]) -print(EDGEMAX[42]) + #print(EDGEMAX[edge], HYPERGRAPH[edge]) +#print(EDGEMAX[4]) +#print(EDGEMAX[23]) +#print(EDGEMAX[42]) FIXED_FLOWS = { @@ -162,22 +161,12 @@ FIXED_FLOWS = { #42: 1, } -def build_model(name, hyperedges, edgelikelihoodsmax, edgelikelihoods1, edgelikelihoods2, edgelikelihoods3, excluded_support=None): +def build_model(name, hyperedges, elmax, el1, el2, el3, excluded_support=None): model = Model(name) 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} - enmax = model.addVars(hyperedges, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmrmax") - en1 = model.addVars(hyperedges, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmr1") - en2 = model.addVars(hyperedges, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmr2") - en3 = model.addVars(hyperedges, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "edgenmr3") - - for edge, elmax, el1, el2, el3 in zip(hyperedges, edgelikelihoodsmax, edgelikelihoods1, edgelikelihoods2, edgelikelihoods3): - enmax[edge] = elmax - en1[edge] = el1 - en2[edge] = el2 - en3[edge] = el3 vertices = set(v for tails, heads in hyperedges.values() for v in tails + heads) @@ -218,9 +207,9 @@ def build_model(name, hyperedges, edgelikelihoodsmax, edgelikelihoods1, edgelike #Multiply edgelikelihood with the edge use boolean #Adapt to have model.setObjectiveN( - quicksum(enmax[e_id] * b[e_id] for e_id in hyperedges), + quicksum(elmax[e_id] * b[e_id] for e_id in hyperedges), index = 0, - priority = 2000, + priority = 2, name = "maximize_nmr_similarity", ) #Minimize the overall flow @@ -244,7 +233,7 @@ def build_model(name, hyperedges, edgelikelihoodsmax, edgelikelihoods1, edgelike model.addConstr(quicksum(b[e_id] for e_id, (tails, heads) in hyperedges.items() if tails == [] and heads == startmolecule)== 1) #model.addConstr(b[213] == 1) - + #model.addConstr(b[41] == 1)