Dateien nach "ILP/Kaffee" hochladen

ILP/Kaffee/caffeinesynthesis.py

@@ -21,13 +21,13 @@ HYPEREDGES = {
 VERTICES = ['Xanthine', '1-Methylxanthine', '3-Methylxanthine', '7-Methylxanthine', 'Theophylline', 'Paraxanthine', 'Theobromine',  'Caffeine']
 
 #Change to only have one likelihood, where with manual order association
-NMRLIKELYHOODS = [0.0, 0.52, 0.43, 0.62, 0.53, 0.56, 0.68, 0.0]
+NMRLIKELYHOODS = [0.0, 0.49, 0.43, 0.6, 0.5, 0.51, 0.67, 0.0]
-#Results for comparison with 7-Methylxanthine
+#Results for comparison with 7-Methylxanthine bei shift von 2.5
-NMRLIKELYHOODS1 = [0.54, 0.52, 0.43, 0.62, 0.52, 0.56, 0.48, 0.5]
+NMRLIKELYHOODS1 = [0.46, 0.49, 0.43, 0.6, 0.49, 0.6, 0.45, 0.51]
-#Results for comparison with 3,7-Methylxanthine
+#Results for comparison with 3,7-Methylxanthine bei shift von 2.5
-NMRLIKELYHOODS2 = [0.52, 0.52, 0.52, 0.61, 0.52, 0.56, 0.61, 0.59]
+NMRLIKELYHOODS2 = [0.45, 0.52, 0.52, 0.63, 0.52, 0.57, 0.59, 0.59]
-#Results for comparison with 3,7-Methylxanthine with Methyl C of spectrum 2 bei 
+#Results for comparison with 3,7-Methylxanthine with Methyl C of spectrum 2 bei shift von 2.5
-NMRLIKELYHOODS3 = [0.5, 0.53, 0.59, 0.59, 0.53, 0.56, 0.68, 0.62]
+NMRLIKELYHOODS3 = [0.48, 0.5, 0.51, 0.59, 0.5, 0.51, 0.67, 0.61]
 
 FIXED_FLOWS = {
     1: 1,

ILP/Kaffee/nmrSimilarityCaffeine.py

@@ -97,7 +97,7 @@ C17XANTHINE = {
     1: ([153.04], [1]),
     2: ([158.80], [1]),
     3: ([113.44], [1]),
-    4: ([1651.81], [1]),
+    4: ([151.81], [1]),
     5: ([142.72], [1]),
     6: ([36.80], [1]),
     7: ([28.59], [1]),
@@ -284,7 +284,7 @@ def correction(spectra, corretionppm):
     return newspectra
 
 def main():
-    spectrumref = CNMR3
+    spectrumref = CNMR2
     #1H-NMR Spectra ignoriert, da meiste H sauer, da an N gebunden
     #spectra = [HXANTHINE, H1XANTHINE, H3XANTHINE, H7XANTHINE, H1XANTHINE, H17XANTHINE, H37XANTHINE, H137XANTHINE]
     spectra = [CXANTHINE, C1XANTHINE, C3XANTHINE, C7XANTHINE, C1XANTHINE, C17XANTHINE, C37XANTHINE, C137XANTHINE]
@@ -293,7 +293,7 @@ def main():
     for spectrumtrue in spectra:
         similaritybycorrection = []
         #Paper Chemical reviews Carbons bound to Heavy atoms (TMS) to high -> this could be reason for too high values.
-        correctionvalues = [2.63] #np.arange(0, 1.51, 0.01) #for C tested np.arange(-0.37, 7.64, 0.1) 0, 2.63, 1 (for CNMR3), 1.5 (true for all ref, 8.37 + 1.5 for the precision), 1 (good for first, ok for second, third because only 7 better/equal but for first much higher) np.arange(-1.5, 1.49, 0.01) (only for first), for H 0 (not good), np.arange(-0.26, 0.34, 0.01), -0.06 for first, second never first either 17 or caf higher np.arange(-0.15, 0.16, 0.01) good measure
+        correctionvalues = [2.5] #np.arange(0, 1.51, 0.01) #for C tested np.arange(-0.37, 7.64, 0.1) 0, 2.63, 1 (for CNMR3), 1.5 (true for all ref, 8.37 + 1.5 for the precision), 1 (good for first, ok for second, third because only 7 better/equal but for first much higher) np.arange(-1.5, 1.49, 0.01) (only for first), for H 0 (not good), np.arange(-0.26, 0.34, 0.01), -0.06 for first, second never first either 17 or caf higher np.arange(-0.15, 0.16, 0.01) good measure
         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
             similaritylist = []