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Dateien nach "ILP" hochladen

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kilian 2026-06-10 12:48:12 +02:00
parent cfac69b7af
commit 3b7d785b24
1 changed files with 92 additions and 20 deletions
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86
ILP/nmrSimilarity.py
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@ -1,3 +1,6 @@
#Binning mostly for broader peaks?
#
import math
import numpy as np
@ -98,6 +101,17 @@ C17XANTHINE= {
7: ([36.96], [1]),
}
CPARAXANTHINE = {
1: ([26.7], [1]),
2: ([32.9], [1]),
3: ([151.1], [1]),
4: ([106.5], [1]),
5: ([147.4], [1]),
6: ([155.3], [1]),
7: ([143.0], [1]),
}
#Theobromine
H37XANTHINE = {
1: ([4.49], [3]),
@ -116,13 +130,13 @@ C37XANTHINE= {
}
#Caffeine
H37XANTHINE= {
H137XANTHINE = {
1: ([7.73], [1]),
2: ([4.15], [3]),
3: ([4.52], [3]),
4: ([4.01], [3]),
}
C37XANTHINE= {
C137XANTHINE = {
1: ([163.66], [1]),
2: ([166.66], [1]),
3: ([122.03], [1]),
@ -133,7 +147,29 @@ C37XANTHINE= {
8: ([37.17], [1]),
}
#Neue Quelle für 13CNMR für beide
CCAFFEINE = {
1: ([155.7], [1]),
2: ([148.8], [1]),
3: ([107.7], [1]),
4: ([152.2], [1]),
5: ([143.0], [1]),
6: ([27.2], [1]),
7: ([29.1], [1]),
8: ([32.9], [1]),
}
CCAFFEINE2 = {
1: ([27.7], [1]),
2: ([29.3], [1]),
3: ([33.1], [1]),
4: ([151.0], [1]),
5: ([148.1], [1]),
6: ([106.6], [1]),
7: ([154.5], [1]),
8: ([142.8], [1]),
}
#Experimental 7-Methylxanthine nmr
HNMR1= {
1: ([10.85], [1]),
@ -142,6 +178,15 @@ HNMR1= {
4: ([7.88], [1]),
}
CNMR1= {
1: ([155.85], [1]),
2: ([151.35], [1]),
3: ([149.30], [1]),
4: ([143.01], [1]),
5: ([106.90], [1]),
6: ([33.03], [1]),
}
#Experimental Theobromine nmr
@ -181,12 +226,23 @@ def bin_array(spectra, highest_ppm, lowest_ppm, bin_width):
normalizedbin = np.divide(bin, np.sum(bin))
return normalizedbin
def similarity_nmr(spectraref, spectranew, bin_width, highest_ppm, lowest_ppm):
def define_border_values(spectraref, spectranew):
shifts = []
for _,(shift,_) in spectraref.items():
shifts.append(shift[0])
for _,(shift,_) in spectranew.items():
shifts.append(shift[0])
highest_ppm = math.ceil(max(shifts))
lowest_ppm = math.floor(min(shifts))
return (lowest_ppm, highest_ppm)
def similarity_nmr(spectraref, spectranew, bin_width):
#Maximize likelihood or minimize Deviation
#Values for two spectra and optimize largest for both different?
#Spectra in Nodes to allow maximize overlapp with both spectra or one spectra.
#5.4.2 Eliminating X–H signals from 1H NMR spectra
lowest_ppm, highest_ppm = define_border_values(spectraref, spectranew)
binref = bin_array(spectraref, highest_ppm, lowest_ppm, bin_width)
binnew = bin_array(spectranew, highest_ppm, lowest_ppm, bin_width)
crosscorr = overlap(binref, binnew)
@ -196,9 +252,25 @@ def similarity_nmr(spectraref, spectranew, bin_width, highest_ppm, lowest_ppm):
return(simidx)
def main():
print(similarity_nmr(H1XANTHINE, HNMR1, 0.4, 13, 3))
print(similarity_nmr(H3XANTHINE, HNMR1, 0.4, 13, 3))
print(similarity_nmr(H7XANTHINE, HNMR1, 0.4, 13, 3))
positive = 0
negative = 0
bad_binwidth = []
'''for i in [0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0, 2.5, 3.0, 3.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 25.0, 30.0, 35.0]:
print(similarity_nmr(CNMR1, CNMR2, i), i)
if(similarity_nmr(CCAFFEINE2, CCAFFEINE, i) - similarity_nmr(CPARAXANTHINE, CCAFFEINE, i) < 0):
negative += 1
bad_binwidth.append(i)
else:
positive += 1
print(f'Wrong similarity result: {negative} and Right similarity result: {positive}')
print(bad_binwidth)'''
for i in np.arange(0.01, 0.07, 0.01):
print(f'Increment i: {i}')
print(similarity_nmr(HNMR1, HNMR2, i))
print(similarity_nmr(H1XANTHINE, HNMR1, i))
print(similarity_nmr(H3XANTHINE, HNMR1, i))
print(similarity_nmr(H7XANTHINE, HNMR1, i))
if __name__ == "__main__":
main()