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Carbon_plotting.py
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Carbon_plotting.py
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from matplotlib import pyplot as plt
import matplotlib
matplotlib.use('Agg')
import numpy as np
import os
from pathlib import Path
def PlotCarbon(NMRData,Isomers,settings):
xdata = NMRData.carbondata["xdata"]
ydata = NMRData.carbondata["ydata"]
exppeaks = NMRData.carbondata["exppeaks"]
simulated_ydata = NMRData.carbondata["simulated_ydata"]
removed = NMRData.carbondata["removed"]
if settings.OutputFolder == '':
gdir = Path.cwd() / "Graphs" / settings.InputFiles[0]
else:
gdir = settings.OutputFolder / "Graphs" / settings.InputFiles[0]
for isomerindex,isomer in enumerate(Isomers):
assigned_peaks = []
assigned_shifts = []
assigned_labels = []
for i,peak in enumerate(isomer.Cexp):
if peak != '':
assigned_peaks.append(peak)
assigned_shifts.append(isomer.Cshifts[i])
assigned_labels.append(isomer.Clabels[i])
plt.close()
fig1 = plt.figure(1)
fig1.set_size_inches(30, 17)
ax1 = fig1.add_subplot(111)
exppeaks_ppm = xdata[exppeaks].tolist()
shiftlist = assigned_shifts
totallist = exppeaks_ppm + shiftlist
plt.xlim([max(totallist) + 10, min(totallist) - 10])
plt.plot(xdata, ydata, color='grey', linewidth=0.75, label='experimental spectrum')
plt.plot(xdata, simulated_ydata, label='simulated spectrum')
plt.xlabel('PPM') # axis labels
# plt.yticks([], [])
plt.title(str(settings.InputFiles[0]) +
"\nCarbon NMR of Isomer " + str(isomerindex + 1) + "\n Number of Peaks Found = " + str(len(exppeaks)))
# plot assignments
for ind1, peak in enumerate(assigned_peaks):
wh = np.argmin(abs(xdata - peak))
plt.plot([peak, assigned_shifts[ind1]],
[ydata[wh], 1.1], linewidth=0.5, color='cyan')
prev = round(exppeaks_ppm[0], 2)
count = 0
# annotate peak locations
for x, txt in enumerate([round(i, 2) for i in exppeaks_ppm]):
if abs(prev - txt) < 5:
count += 1
else:
count = 0
prev = txt
if exppeaks_ppm[x] in assigned_peaks:
color = 'C1'
else:
color = 'grey'
ax1.annotate(txt, (exppeaks_ppm[x], -0.06 - 0.025 * count), color=color, size=10)
plt.plot(exppeaks_ppm[x], ydata[exppeaks[x]], 'o', color=color)
if len(removed) > 0:
plt.plot(xdata[removed],
simulated_ydata[removed], "ro")
# annotate shift positions
count = 0
####some quick sorting
sortshifts = isomer.Cshifts[::-1]
slabels = isomer.Clabels[::-1]
prev = sortshifts[0]
for x, txt in enumerate(slabels):
if abs(prev - sortshifts[x]) < 4:
count += 1
else:
count = 0
prev = sortshifts[x]
ax1.annotate(txt, (sortshifts[x], + 2.05 + 0.05 * count), size=18)
simulated_calc_ydata = simulate_calc_data(xdata, isomer.Cshifts, simulated_ydata)
plt.plot(xdata, simulated_calc_ydata + 1.1, label='calculated spectrum')
plt.legend()
f_name = "Carbon_" + str(isomerindex + 1 ) + ".svg"
plt.savefig(gdir / f_name,format = "svg", bbox_inches='tight')
plt.close()
def simulate_calc_data(spectral_xdata_ppm, calculated_locations, simulated_ydata):
###simulate calcutated data
simulated_calc_ydata = np.zeros(len(spectral_xdata_ppm))
for peak in calculated_locations:
y = np.exp(-0.5 * ((spectral_xdata_ppm - peak) / 0.002) ** 2)
simulated_calc_ydata += y
scaling_factor = np.amax(simulated_ydata) / np.amax(simulated_calc_ydata)
simulated_calc_ydata = simulated_calc_ydata * scaling_factor
return simulated_calc_ydata