Dateien nach "ILP" hochladen

ILP/nmrSimilarity.py

@@ -213,14 +213,14 @@ CNMR1= {
 
 
 #Experimental Theobromine nmr
-HNMR2= {
+HNMR2 = {
     1: ([11.10], [1]),
     2: ([3.33], [3]),
     3: ([3.84], [3]),
     4: ([7.97], [1]),
 }
 
-CNMR2= {
+CNMR2 = {
     1: ([154.9], [1]),
     2: ([149.8], [1]),
     3: ([107.1], [1]),
@@ -230,6 +230,17 @@ CNMR2= {
     7: ([33.9], [1]),
 }
 
+#Combination of methyl group and base purine rings from two papers
+CNMR3 = {
+    1: ([153.1], [1]),
+    2: ([150.0], [1]),
+    3: ([108.1], [1]),
+    4: ([154.9], [1]),
+    5: ([142.6], [1]),
+    6: ([29.3], [1]),
+    7: ([33.9], [1]),
+}
+
 def overlap(listref, listnew):
     twoleft = np.sum(np.multiply(np.concatenate((listref, [0, 0])),  np.concatenate(([0, 0], listnew))))
     oneleft = np.sum(np.multiply(np.concatenate((listref, [0])),  np.concatenate(([0], listnew))))
@@ -283,13 +294,13 @@ def correction(spectra, corretionppm):
     return newspectra
 
 def main():
-    spectrumref = CNMR1
+    spectrumref = CNMR3
     spectrafalse = [CXANTHINE, C1XANTHINE, C3XANTHINE, C7XANTHINE, C1XANTHINE, C17XANTHINE, C37XANTHINE, C137XANTHINE]
     likelihood = []
     for spectrumtrue in spectrafalse:
         #errorlist = {}
         errorlist = []
-        for correctionvalue in range(8, 16):
+        for correctionvalue in range(8, 12): #also tested 8.4, 8.37, 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
             error = 0
             total = 0
@@ -313,6 +324,7 @@ def main():
                 error += negative
             #errorlist[correctionvalue] = error
             errorlist.append(error)
+            #print(min(range(len(errorlist)), key=errorlist.__getitem__))
         likelihood.append(round((total - min(errorlist))/total, 2))
     print(likelihood)
     '''for i in np.arange(0.01, 0.07, 0.01):