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Dateien nach "ILP/Vanilla" hochladen

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kilian
2026-09-18 12:42:06 +02:00
parent cc702732e7
commit dced90a8cb
2 changed files with 14 additions and 9 deletions
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ILP/Vanilla/nmrSimilarityVanillien.py
+7 -7
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@@ -280,17 +280,17 @@ def main():
for correctionvalue in correctionvalues: for correctionvalue in correctionvalues:
spectrumrefcorrected = correction(spectrumref, correctionvalue) #CCAFFEINE 11 (klappt hier sehr gut) CCAFFEINE2 12 CPARAXANTHINE 10 CNMR1 9, 10 o 11 (sehr gut) CNMR2 10 o 11 spectrumrefcorrected = correction(spectrumref, correctionvalue) #CCAFFEINE 11 (klappt hier sehr gut) CCAFFEINE2 12 CPARAXANTHINE 10 CNMR1 9, 10 o 11 (sehr gut) CNMR2 10 o 11
similaritylist = [] similaritylist = []
binwidthlist = np.arange(0.1, 3.9, 0.1) binwidthlist = np.arange(0.1, 1.1, 0.1)
for i in binwidthlist: for i in binwidthlist:
similaritylist.append(similarity_nmr(spectrumtrue, spectrumrefcorrected, i)) similaritylist.append(similarity_nmr(spectrumtrue, spectrumrefcorrected, i))
similaritymean = sum(similaritylist) / len(similaritylist) similaritymean = sum(similaritylist) / len(similaritylist)
similaritybycorrection.append(similaritymean) similaritybycorrection.append(similaritymean)
likelihoods.append(sum(similaritybycorrection)/len(similaritybycorrection)) likelihoods.append(sum(similaritybycorrection)/len(similaritybycorrection))
if normalize: if normalize:
normalizedlikelihood = [round(likelihood/np.sum(likelihoods), 2) for likelihood in likelihoods] normalizedlikelihood = [round(likelihood/np.sum(likelihoods), 2) for likelihood in likelihoods]
print(normalizedlikelihood) print(normalizedlikelihood)
if not normalize: if not normalize:
notnormalizedlikelihood = [round(likelihood, 2) for likelihood in likelihoods] notnormalizedlikelihood = [round(likelihood, 2) for likelihood in likelihoods]
print(notnormalizedlikelihood) print(notnormalizedlikelihood)
if __name__ == "__main__": if __name__ == "__main__":
main() main()
ILP/Vanilla/vanillasynthesis.py
+7 -2
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@@ -76,10 +76,15 @@ def print_solution(title, flow_solution, binary_solution, hyperedges):
def main(): def main():
VERTICES = ['Cinnamicacid', 'p-Coumaricacid', 'm-Coumaricacid', 'Benzaldehyd', 'Caffeicacid', '3-Hydroxybenzaldehyd', '4-Hydroxybenzaldehyd', '34Dihydroxybenzaldehyd'] VERTICES = ['Cinnamicacid', 'p-Coumaricacid', 'm-Coumaricacid', 'Benzaldehyd', 'Caffeicacid', '3-Hydroxybenzaldehyd', '4-Hydroxybenzaldehyd', '34Dihydroxybenzaldehyd']
#Results for comparison with p-Coumaricacid bei shift von 2.5 #Results for comparison with p-Coumaricacid bei shift von 2.5 mit binwidth 0.1 bis 3.9
NMR1 = [0.37, 0.65, 0.38, 0.25, 0.55, 0.2, 0.47, 0.44] NMR1 = [0.37, 0.65, 0.38, 0.25, 0.55, 0.2, 0.47, 0.44]
#Results for comparison with 4-Hydroxybenzaldehyd bei shift von 2.5 #Results for comparison with p-Coumaricacid bei shift von 2.5 mit binwidth 0.1 bis 1.1
NMR1 = [0.09, 0.38, 0.12, 0.09, 0.34, 0.02, 0.34, 0.17]
#Results for comparison with 4-Hydroxybenzaldehyd bei shift von 2.5 mit binwidth 0.1 bis 3.9
NMR2 = [0.54, 0.71, 0.4, 0.5, 0.37, 0.24, 0.62, 0.51] NMR2 = [0.54, 0.71, 0.4, 0.5, 0.37, 0.24, 0.62, 0.51]
#Results for comparison with 4-Hydroxybenzaldehyd bei shift von 2.5 mit binwidth 0.1 bis 1.1
NMR2 = [0.17, 0.44, 0.12, 0.18, 0.15, 0.03, 0.26, 0.17]
#Chosable parameters #Chosable parameters
modes = ["Product", "Average"] modes = ["Product", "Average"]