def onPlot(self, evt=None):
"""Calculate and show mass defect plot."""
# clear previous data
self.plotCanvasContainer.empty()
# get params
if not self.getParams():
self.plotCanvas.refresh()
wx.Bell()
return
# show annotations for current document on top
if self.currentDocument is not None and config.massDefectPlot[
"showNotations"]:
buff = []
for item in self.currentDocument.annotations:
buff.append((item.mz, item.charge))
for sequence in self.currentDocument.sequences:
for item in sequence.matches:
buff.append((item.mz, item.charge))
points = self.makeDataPoints(
mspy.peaklist(buff), self.currentDocument.spectrum.polarity)
obj = mspy.plot.points(points,
pointColour=(255, 0, 0),
showPoints=True,
showLines=False)
self.plotCanvasContainer.append(obj)
# show all documents
if config.massDefectPlot["showAllDocuments"]:
for docData in self.parent.documents:
if docData.visible:
points = self.makeDataPoints(docData.spectrum.peaklist,
docData.spectrum.polarity)
obj = mspy.plot.points(
points,
pointColour=docData.colour,
showPoints=True,
showLines=False,
)
self.plotCanvasContainer.append(obj)
# show current document only
elif self.currentDocument is not None:
points = self.makeDataPoints(
self.currentDocument.spectrum.peaklist,
self.currentDocument.spectrum.polarity,
)
obj = mspy.plot.points(points,
pointColour=(0, 255, 0),
showPoints=True,
showLines=False)
self.plotCanvasContainer.append(obj)
# update plot
self.updatePlotCanvasLabels()
self.plotCanvas.draw(self.plotCanvasContainer)
def makeCurrentPeaklist(self):
"""Convert peaklist for current error range."""
# get error range
minY = 0
maxY = 1
if self.currentErrors:
errors = [x[1] for x in self.currentErrors]
minY = min(errors)
maxY = max(errors)
if minY == maxY:
minY -= abs(minY * 0.1)
maxY += abs(maxY * 0.1)
minY -= 0.05 * abs(maxY - minY)
# convert peaklist
peaklist = []
basePeak = self.currentPeaklist.basepeak
f = abs(maxY - minY) / basePeak.intensity
for peak in self.currentPeaklist:
intensity = (peak.intensity * f) + minY
peaklist.append(mspy.peak(mz=peak.mz, ai=intensity, base=minY))
# convert to mspy.peaklist
return mspy.peaklist(peaklist)
def makeCurrentPeaklist(self):
"""Convert peaklist for current error range."""
# get error range
minY = 0
maxY = 1
if self.currentErrors:
errors = [x[1] for x in self.currentErrors]
minY = min(errors)
maxY = max(errors)
if minY == maxY:
minY -= abs(minY*0.1)
maxY += abs(maxY*0.1)
minY -= 0.05 * abs(maxY - minY)
# convert peaklist
peaklist = []
basePeak = self.currentPeaklist.basepeak
f = abs(maxY - minY) / basePeak.intensity
for peak in self.currentPeaklist:
intensity = (peak.intensity * f) + minY
peaklist.append(mspy.peak(mz=peak.mz, ai=intensity, base=minY))
# convert to mspy.peaklist
return mspy.peaklist(peaklist)
def makeCurrentPeaklist(self, minY, maxY):
"""Convert peaklist for current error range."""
# shift peaklist
if (minY, maxY) != (0, 1):
minY -= 0.05 * abs(maxY - minY)
# convert peaklist
peaklist = []
basePeak = self.currentDocument.spectrum.peaklist.basepeak
f = abs(maxY - minY) / basePeak.intensity
for peak in self.currentDocument.spectrum.peaklist:
intensity = (peak.intensity * f) + minY
peaklist.append(mspy.peak(mz=peak.mz, ai=intensity, base=minY))
# convert to mspy.peaklist
return mspy.peaklist(peaklist)
def makeCurrentPeaklist(self, minY, maxY):
"""Convert peaklist for current error range."""
# shift peaklist
if (minY, maxY) != (0, 1):
minY -= 0.05 * abs(maxY - minY)
# convert peaklist
peaklist = []
basePeak = self.currentDocument.spectrum.peaklist.basepeak
f = abs(maxY - minY) / basePeak.intensity
for peak in self.currentDocument.spectrum.peaklist:
intensity = (peak.intensity * f) + minY
peaklist.append(mspy.peak(mz=peak.mz, ai=intensity, base=minY))
# convert to mspy.peaklist
return mspy.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 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)