def runSpectrumGenerator(self):
"""Generate spectrum."""
self.currentProfile = None
self.currentPeaks = None
# run task
try:
# make profile spectrum
self.currentProfile = mspy.profile(
peaklist=self.currentDocument.spectrum.peaklist,
fwhm=config.spectrumGenerator["fwhm"],
points=config.spectrumGenerator["points"],
noise=config.spectrumGenerator["noise"],
forceFwhm=config.spectrumGenerator["forceFwhm"],
model=config.spectrumGenerator["peakShape"],
)
# make peak spectra
self.currentPeaks = []
for peak in self.currentDocument.spectrum.peaklist:
# get fwhm
fwhm = config.spectrumGenerator["fwhm"]
if peak.fwhm and not config.spectrumGenerator["forceFwhm"]:
fwhm = peak.fwhm
# gaussian shape
if config.spectrumGenerator["peakShape"] == "gaussian":
points = mspy.gaussian(
x=peak.mz, minY=peak.base, maxY=peak.ai, fwhm=fwhm
)
# lorentzian shape
elif config.spectrumGenerator["peakShape"] == "lorentzian":
points = mspy.lorentzian(
x=peak.mz, minY=peak.base, maxY=peak.ai, fwhm=fwhm
)
# gauss-lorentzian shape
elif config.spectrumGenerator["peakShape"] == "gausslorentzian":
points = mspy.gausslorentzian(
x=peak.mz, minY=peak.base, maxY=peak.ai, fwhm=fwhm
)
self.currentPeaks.append(points)
# task canceled
except mspy.ForceQuit:
self.currentProfile = None
self.currentPeaks = None
def makeProfile(self):
"""Generate pattern profile."""
self.currentPatternProfile = None
self.currentPatternPeaks = None
self.currentPatternScan = None
# check pattern
if self.currentPattern == None:
return
# get selected charge
charge = 0
if self.currentIon != None:
charge = self.currentIon[3]
# make profile
self.currentPatternProfile = mspy.profile(
peaklist = self.currentPattern,
fwhm = config.massCalculator['patternFwhm'],
points = 20,
model = config.massCalculator['patternPeakShape'],
)
# get scale and shift for specified intensity and baseline
basepeak = mspy.basepeak(self.currentPatternProfile)
scale = (config.massCalculator['patternIntensity'] - config.massCalculator['patternBaseline']) / self.currentPatternProfile[basepeak][1]
shift = config.massCalculator['patternBaseline']
# rescale profile
self.currentPatternProfile = mspy.multiply(self.currentPatternProfile, y=scale)
self.currentPatternProfile = mspy.offset(self.currentPatternProfile, y=shift)
# make real peaklist from profile
peaklist = []
for isotope in mspy.maxima(self.currentPatternProfile):
mz = isotope[0]
centroid = mspy.centroid(self.currentPatternProfile, isotope[0], isotope[1]*0.99)
if abs(mz-centroid) < config.massCalculator['patternFwhm']/20:
mz = centroid
peak = mspy.peak(
mz = mz,
ai = isotope[1],
base = shift,
charge = charge
)
peaklist.append(peak)
peaklist = mspy.peaklist(peaklist)
# make individual peak shapes
self.currentPatternPeaks = []
if config.massCalculator['patternShowPeaks']:
# gaussian shape
if config.massCalculator['patternPeakShape'] == 'gaussian':
for isotope in self.currentPattern:
peak = mspy.gaussian(
x = isotope[0],
minY = shift,
maxY = isotope[1]*scale+shift,
fwhm = config.massCalculator['patternFwhm']
)
self.currentPatternPeaks.append(peak)
# lorentzian shape
elif config.massCalculator['patternPeakShape'] == 'lorentzian':
for isotope in self.currentPattern:
peak = mspy.lorentzian(
x = isotope[0],
minY = shift,
maxY = isotope[1]*scale+shift,
fwhm = config.massCalculator['patternFwhm']
)
self.currentPatternPeaks.append(peak)
# gauss-lorentzian shape
elif config.massCalculator['patternPeakShape'] == 'gausslorentzian':
for isotope in self.currentPattern:
peak = mspy.gausslorentzian(
x = isotope[0],
minY = shift,
maxY = isotope[1]*scale+shift,
fwhm = config.massCalculator['patternFwhm']
)
self.currentPatternPeaks.append(peak)
# make scan object
self.currentPatternScan = mspy.scan(profile=self.currentPatternProfile, peaklist=peaklist)
def makeProfile(self):
"""Generate pattern profile."""
self.currentPatternProfile = None
self.currentPatternPeaks = None
self.currentPatternScan = None
# check pattern
if self.currentPattern == None:
return
# get selected charge
charge = 0
if self.currentIon != None:
charge = self.currentIon[3]
# make profile
self.currentPatternProfile = mspy.profile(
peaklist=self.currentPattern,
fwhm=config.massCalculator['patternFwhm'],
points=20,
model=config.massCalculator['patternPeakShape'],
)
# get scale and shift for specified intensity and baseline
basepeak = mspy.basepeak(self.currentPatternProfile)
scale = (config.massCalculator['patternIntensity'] -
config.massCalculator['patternBaseline']
) / self.currentPatternProfile[basepeak][1]
shift = config.massCalculator['patternBaseline']
# rescale profile
self.currentPatternProfile = mspy.multiply(self.currentPatternProfile,
y=scale)
self.currentPatternProfile = mspy.offset(self.currentPatternProfile,
y=shift)
# make real peaklist from profile
peaklist = []
for isotope in mspy.maxima(self.currentPatternProfile):
mz = isotope[0]
centroid = mspy.centroid(self.currentPatternProfile, isotope[0],
isotope[1] * 0.99)
if abs(mz - centroid) < config.massCalculator['patternFwhm'] / 20:
mz = centroid
peak = mspy.peak(mz=mz, ai=isotope[1], base=shift, charge=charge)
peaklist.append(peak)
peaklist = mspy.peaklist(peaklist)
# make individual peak shapes
self.currentPatternPeaks = []
if config.massCalculator['patternShowPeaks']:
# gaussian shape
if config.massCalculator['patternPeakShape'] == 'gaussian':
for isotope in self.currentPattern:
peak = mspy.gaussian(
x=isotope[0],
minY=shift,
maxY=isotope[1] * scale + shift,
fwhm=config.massCalculator['patternFwhm'])
self.currentPatternPeaks.append(peak)
# lorentzian shape
elif config.massCalculator['patternPeakShape'] == 'lorentzian':
for isotope in self.currentPattern:
peak = mspy.lorentzian(
x=isotope[0],
minY=shift,
maxY=isotope[1] * scale + shift,
fwhm=config.massCalculator['patternFwhm'])
self.currentPatternPeaks.append(peak)
# gauss-lorentzian shape
elif config.massCalculator[
'patternPeakShape'] == 'gausslorentzian':
for isotope in self.currentPattern:
peak = mspy.gausslorentzian(
x=isotope[0],
minY=shift,
maxY=isotope[1] * scale + shift,
fwhm=config.massCalculator['patternFwhm'])
self.currentPatternPeaks.append(peak)
# make scan object
self.currentPatternScan = mspy.scan(profile=self.currentPatternProfile,
peaklist=peaklist)
def runSpectrumGenerator(self):
"""Generate spectrum."""
self.currentProfile = None
self.currentPeaks = None
# run task
try:
# make profile spectrum
self.currentProfile = mspy.profile(
peaklist = self.currentDocument.spectrum.peaklist,
fwhm = config.spectrumGenerator['fwhm'],
points = config.spectrumGenerator['points'],
noise = config.spectrumGenerator['noise'],
forceFwhm = config.spectrumGenerator['forceFwhm'],
model = config.spectrumGenerator['peakShape'],
)
# make peak spectra
self.currentPeaks = []
for peak in self.currentDocument.spectrum.peaklist:
# get fwhm
fwhm = config.spectrumGenerator['fwhm']
if peak.fwhm and not config.spectrumGenerator['forceFwhm']:
fwhm = peak.fwhm
# gaussian shape
if config.spectrumGenerator['peakShape'] == 'gaussian':
points = mspy.gaussian(
x = peak.mz,
minY = peak.base,
maxY = peak.ai,
fwhm = fwhm
)
# lorentzian shape
elif config.spectrumGenerator['peakShape'] == 'lorentzian':
points = mspy.lorentzian(
x = peak.mz,
minY = peak.base,
maxY = peak.ai,
fwhm = fwhm
)
# gauss-lorentzian shape
elif config.spectrumGenerator['peakShape'] == 'gausslorentzian':
points = mspy.gausslorentzian(
x = peak.mz,
minY = peak.base,
maxY = peak.ai,
fwhm = fwhm
)
self.currentPeaks.append(points)
# task canceled
except mspy.ForceQuit:
self.currentProfile = None
self.currentPeaks = None
