From 6a4454bdc2ef31a77d6339bbcc667fe1ca8b0d16 Mon Sep 17 00:00:00 2001 From: kilian Date: Fri, 4 Sep 2026 11:23:16 +0200 Subject: [PATCH] Dateien nach "ILP/butadien" hochladen Adapted for Likelihood multiplication --- ILP/butadien/butadiensynthesis.py | 159 ++++++++++++++------------ ILP/butadien/nmrSimilarityButadien.py | 9 +- 2 files changed, 93 insertions(+), 75 deletions(-) diff --git a/ILP/butadien/butadiensynthesis.py b/ILP/butadien/butadiensynthesis.py index f1440eb..54e658c 100644 --- a/ILP/butadien/butadiensynthesis.py +++ b/ILP/butadien/butadiensynthesis.py @@ -3,68 +3,68 @@ import gurobipy as gp from gurobipy import GRB, Model, quicksum HYPERGRAPH = { - 0: (['Butadien'], []), - 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}']), - 10: (['p_{0,0}', 'p_{0,1}'], ['Butadien', 'Butadien']), - 12: (['p_{0,3}'], []), - 13: (['p_{0,0}', 'p_{0,2}'], ['p_{0,3}']), - 17: (['p_{0,4}'], []), - 18: (['p_{0,1}', 'p_{0,1}'], ['Butadien', 'p_{0,4}']), - 19: (['p_{0,5}'], []), - 20: (['p_{0,1}', 'p_{0,2}'], ['Butadien', 'p_{0,5}']), - 23: (['Butadien', 'p_{0,1}'], ['p_{0,0}', 'p_{0,4}']), - 26: (['Butadien', 'p_{0,2}'], ['p_{0,0}', 'p_{0,5}']), - 27: (['p_{0,6}'], []), - 28: (['p_{0,0}', 'p_{0,1}'], ['p_{0,6}']), - 29: (['p_{0,7}'], []), - 30: (['Butadien', 'p_{0,0}'], ['p_{0,7}']), - 31: (['p_{0,8}'], []), - 32: (['Butadien', 'p_{0,1}'], ['p_{0,8}']), - 33: (['Butadien', 'p_{0,1}'], ['p_{0,5}']), - 34: (['p_{0,9}'], []), - 35: (['Butadien', 'p_{0,1}'], ['p_{0,9}']), - 36: (['p_{0,10}'], []), - 37: (['Butadien', 'p_{0,1}'], ['p_{0,10}']), - 38: (['p_{0,3}'], ['p_{0,0}', 'p_{0,2}']), - 41: (['p_{0,11}'], []), - 42: (['p_{0,4}'], ['p_{0,0}', 'p_{0,11}']), - 43: (['p_{0,12}'], []), - 44: (['p_{0,5}'], ['p_{0,12}']), - 63: (['p_{0,13}'], []), - 64: (['p_{0,4}', 'p_{0,6}'], ['p_{0,1}', 'p_{0,13}']), - 65: (['p_{0,2}', 'p_{0,4}'], ['p_{0,1}', 'p_{0,5}']), - 66: (['p_{0,0}', 'p_{0,4}'], ['Butadien', 'p_{0,1}']), - 67: (['Butadien', 'p_{0,4}'], ['p_{0,1}', 'p_{0,1}']), - 77: (['p_{0,5}', 'p_{0,6}'], ['p_{0,2}', 'p_{0,13}']), - 79: (['p_{0,0}', 'p_{0,5}'], ['Butadien', 'p_{0,2}']), - 80: (['Butadien', 'p_{0,5}'], ['p_{0,1}', 'p_{0,2}']), - 83: (['p_{0,1}', 'p_{0,5}'], ['p_{0,2}', 'p_{0,4}']), - 96: (['Butadien', 'p_{0,6}'], ['p_{0,0}', 'p_{0,13}']), - 97: (['p_{0,1}', 'p_{0,6}'], ['Butadien', 'p_{0,13}']), - 99: (['p_{0,14}'], []), - 100: (['p_{0,0}', 'p_{0,6}'], ['p_{0,14}']), - 101: (['p_{0,15}'], []), - 102: (['p_{0,0}', 'p_{0,7}'], ['p_{0,15}']), - 121: (['p_{0,0}', 'p_{0,4}'], ['p_{0,13}']), - 122: (['p_{0,16}'], []), - 123: (['p_{0,0}', 'p_{0,4}'], ['p_{0,16}']), - 124: (['p_{0,17}'], []), - 125: (['Butadien', 'p_{0,7}'], ['p_{0,17}']), - 127: (['p_{0,12}'], ['p_{0,5}']), - 130: (['p_{0,14}'], ['p_{0,0}', 'p_{0,6}']), - 132: (['p_{0,15}'], ['p_{0,0}', 'p_{0,7}']), - 135: (['p_{0,0}', 'p_{0,11}'], ['p_{0,4}']), - 153: (['Butadien', 'p_{0,13}'], ['p_{0,1}', 'p_{0,6}']), - 155: (['p_{0,0}', 'p_{0,13}'], ['Butadien', 'p_{0,6}']), - 157: (['p_{0,1}', 'p_{0,13}'], ['p_{0,4}', 'p_{0,6}']), - 158: (['p_{0,2}', 'p_{0,13}'], ['p_{0,5}', 'p_{0,6}']), - 210: (['p_{0,18}'], []), - 211: (['Butadien', 'p_{0,11}'], ['p_{0,18}']), - 213: ([], ['Butadien']), + 0: (['Butadien'], []), + 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}']), + 10: (['p_{0,0}', 'p_{0,1}'], ['Butadien', 'Butadien']), + 12: (['p_{0,3}'], []), + 13: (['p_{0,0}', 'p_{0,2}'], ['p_{0,3}']), + 17: (['p_{0,4}'], []), + 18: (['p_{0,1}', 'p_{0,1}'], ['Butadien', 'p_{0,4}']), + 19: (['p_{0,5}'], []), + 20: (['p_{0,1}', 'p_{0,2}'], ['Butadien', 'p_{0,5}']), + 23: (['Butadien', 'p_{0,1}'], ['p_{0,0}', 'p_{0,4}']), + 26: (['Butadien', 'p_{0,2}'], ['p_{0,0}', 'p_{0,5}']), + 27: (['p_{0,6}'], []), + 28: (['p_{0,0}', 'p_{0,1}'], ['p_{0,6}']), + 29: (['p_{0,7}'], []), + 30: (['Butadien', 'p_{0,0}'], ['p_{0,7}']), + 31: (['p_{0,8}'], []), + 32: (['Butadien', 'p_{0,1}'], ['p_{0,8}']), + 33: (['Butadien', 'p_{0,1}'], ['p_{0,5}']), + 34: (['p_{0,9}'], []), + 35: (['Butadien', 'p_{0,1}'], ['p_{0,9}']), + 36: (['p_{0,10}'], []), + 37: (['Butadien', 'p_{0,1}'], ['p_{0,10}']), + 38: (['p_{0,3}'], ['p_{0,0}', 'p_{0,2}']), + 41: (['p_{0,11}'], []), + 42: (['p_{0,4}'], ['p_{0,0}', 'p_{0,11}']), + 43: (['p_{0,12}'], []), + 44: (['p_{0,5}'], ['p_{0,12}']), + 63: (['p_{0,13}'], []), + 64: (['p_{0,4}', 'p_{0,6}'], ['p_{0,1}', 'p_{0,13}']), + 65: (['p_{0,2}', 'p_{0,4}'], ['p_{0,1}', 'p_{0,5}']), + 66: (['p_{0,0}', 'p_{0,4}'], ['Butadien', 'p_{0,1}']), + 67: (['Butadien', 'p_{0,4}'], ['p_{0,1}', 'p_{0,1}']), + 77: (['p_{0,5}', 'p_{0,6}'], ['p_{0,2}', 'p_{0,13}']), + 79: (['p_{0,0}', 'p_{0,5}'], ['Butadien', 'p_{0,2}']), + 80: (['Butadien', 'p_{0,5}'], ['p_{0,1}', 'p_{0,2}']), + 83: (['p_{0,1}', 'p_{0,5}'], ['p_{0,2}', 'p_{0,4}']), + 96: (['Butadien', 'p_{0,6}'], ['p_{0,0}', 'p_{0,13}']), + 97: (['p_{0,1}', 'p_{0,6}'], ['Butadien', 'p_{0,13}']), + 99: (['p_{0,14}'], []), + 100: (['p_{0,0}', 'p_{0,6}'], ['p_{0,14}']), + 101: (['p_{0,15}'], []), + 102: (['p_{0,0}', 'p_{0,7}'], ['p_{0,15}']), + 121: (['p_{0,0}', 'p_{0,4}'], ['p_{0,13}']), + 122: (['p_{0,16}'], []), + 123: (['p_{0,0}', 'p_{0,4}'], ['p_{0,16}']), + 124: (['p_{0,17}'], []), + 125: (['Butadien', 'p_{0,7}'], ['p_{0,17}']), + 127: (['p_{0,12}'], ['p_{0,5}']), + 130: (['p_{0,14}'], ['p_{0,0}', 'p_{0,6}']), + 132: (['p_{0,15}'], ['p_{0,0}', 'p_{0,7}']), + 135: (['p_{0,0}', 'p_{0,11}'], ['p_{0,4}']), + 153: (['Butadien', 'p_{0,13}'], ['p_{0,1}', 'p_{0,6}']), + 155: (['p_{0,0}', 'p_{0,13}'], ['Butadien', 'p_{0,6}']), + 157: (['p_{0,1}', 'p_{0,13}'], ['p_{0,4}', 'p_{0,6}']), + 158: (['p_{0,2}', 'p_{0,13}'], ['p_{0,5}', 'p_{0,6}']), + 210: (['p_{0,18}'], []), + 211: (['Butadien', 'p_{0,11}'], ['p_{0,18}']), + 213: ([], ['Butadien']), } HYPERGRAPH2 = { @@ -90,10 +90,16 @@ HYPERGRAPH3 = { 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] +#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] #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] #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] 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)] @@ -134,13 +140,19 @@ def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, #Assigns the edges a likelihood based on the products for e, (tails, heads) in hyperedges.items(): - ''' - 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? + #Produkt klappt nur, wenn normalisierte Likelihoods + 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]]) + else: + enmax[e] = 0.0 + en1[e] = 0.0 + en2[e] = 0.0 + en3[e] = 0.0 + ''' + if heads != [] and tails != []: 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) @@ -149,10 +161,15 @@ def build_model(name, hyperedges, vertices, nmrlikelihoodsmax, nmrlikelihoods1, enmax[e] = 0.0 en1[e] = 0.0 en2[e] = 0.0 - en3[e] = 0.0 + en3[e] = 0.0 + ''' + + - #print(enmax[123]) - #print(enmax[42]) + print(enmax[2]) + print(enmax[3]) + print(enmax[17]) + print(enmax[41]) vertices = set(v for tails, heads in hyperedges.values() for v in tails + heads) diff --git a/ILP/butadien/nmrSimilarityButadien.py b/ILP/butadien/nmrSimilarityButadien.py index 5e201f7..00d57c4 100644 --- a/ILP/butadien/nmrSimilarityButadien.py +++ b/ILP/butadien/nmrSimilarityButadien.py @@ -268,14 +268,15 @@ def main(): spectra = [CBUTADIEN, CP0, CP1, CP2, CP3, CP4, CP5, CP6, CP7, CP8, CP9, CP10, CP11, CP12, CP13, CP14, CP15, CP16, CP17, CP18] spectranames = ['C=CC=C or Butadien', 'C=C or Ethyen or CP0', 'C=CC=CC=C or Hexatrien or CP1', 'C1CCC(C=C)CC=1 or CP2', 'C(CCC(C=C)CC=C)=C or CP3', 'C=CC=CC=CC=C or Octatetraen or CP4', 'C1CCC(C=CC=C)CC=1 or CP5', 'C=CC1C=CCCC1 or CP6', 'C1CCCCC=1 or Cyclohexen or CP7', 'C=CC1CC=CCC1C=C or CP8', 'C1CCC(C=C)C(C=C)C=1 or CP9', 'C(C1CC(C=C)C=CC1)=C or CP10', 'C1C=CC=CC=1 or CP11', 'C(CCC1C=CC=CC1)=C or CP12', 'C1C(C=CC=C)CCCC=1 or CP13', 'C=CC(C=C)CCCC=C or CP14', 'C=CCCCCC=C or CP15', 'C=CC1C=CC(C=C)CC1 or CP16', 'C1CC2CCCCC2CC=1 or CP17', 'C1CC2C=CC=CC2CC=1 or CP18'] for spectrumref in spectrumrefs: - likelihood = [] + likelihoods = [] for spectrumtrue in spectra: similaritylist = [] binwidthlist = np.arange(0.1, 1.1, 0.1) for i in binwidthlist: similaritylist.append(similarity_nmr(spectrumtrue, spectrumref, i)) - similaritymean = round(sum(similaritylist) / len(similaritylist), 2) - likelihood.append(similaritymean) - print(likelihood) + similaritymean = sum(similaritylist) / len(similaritylist) + likelihoods.append(similaritymean) + normalizedlikelihood = [round(likelihood/np.sum(likelihoods), 2) for likelihood in likelihoods] + print(normalizedlikelihood) if __name__ == "__main__": main() \ No newline at end of file