def calibrationFigure(self,fig,calibrationObj,spToDisplay=0,autoAxesLimits=1,colourList=0,**kwargs):
# TODO(gns) - This can probably be removed only used in:
# 121207_test_SpecialFigureCalibration.py, 121209_test_SpecialFigureCalibration2.py
if not spToDisplay:
spToDisplay = calibrationObj.calibrants.keys()[0]
if not colourList:
colourList = utils.colourList
sps = calibrationObj.calibrants.keys()
bandColour = colourList[sps.index(spToDisplay)]
calibrant = calibrationObj.calibrants[spToDisplay]
ax = fig.add_subplot(311) # mass spectrum
calibrant.plotMsAndExtractionLimits(ax,bandColour,**kwargs)
if autoAxesLimits:
mzs = [utils.get_mz(calibrant.approxMass, z) for z in calibrant.charges]
plt.xlim([min(mzs)*0.5,max(mzs)*2])
ax = fig.add_subplot(312) # atds
calibrant.plotChargeStateAtds(ax,colourList=colourList)
calibrant.plotCalibrantTdPeaks(ax,colourList=colourList)
if autoAxesLimits:
tdPrimes = [calibrant.tdsDoublePrime[z] for z in calibrant.charges]
plt.xlim([min(tdPrimes)*0.5,max(tdPrimes)*2.0])
ax = fig.add_subplot(313) # fit
calibrationObj.plotCalibrationCurve(ax,colourList,**kwargs)
def plotTheoreticalMzs(self,ax,xvals,yvals,absolute=0,mass=0,**kwargs):
"""Used to draw the positions of calculated charge state peaks.
If a value for absolute is given, it is used as the y axis position for charge
state labels.
All matplotlib.pyplot.plot() arguments are allowed in **kwargs.
"""
if not mass:
mass = self.mass
oneDone = False
for i,z in enumerate(np.arange(100)+1):
mz = utils.get_mz(mass, z)
if xvals[0] < mz < xvals[-1]:
# the line
if not oneDone: ax.axvline(mz, label="%s - %.1f Da +/- %.1f" %(self.name,self.mass,self.calcMassError), **kwargs)
else: ax.axvline(mz, **kwargs)
oneDone = True
# annotation
if z/2 == float(z)/2: lift = .1 * yvals.max()
else: lift = .2 * yvals.max()
if not 'color' in kwargs:
color = 'blue'
else:
color = kwargs['color']
if not absolute:
ax.text(mz,lift,'+%d' %z, color=color)
else:
ax.text(mz,absolute,'+%d' %z, color=color)
def _getMzLimits(self, species, charge):
"""Get the m/z value upper and lower limits for extracting arrival
time data.
:parameter species: Name of molecular species (species)
:parameter charge: Charge state (int)
"""
mz = utils.get_mz(self.atrOb.simulatedSpecies[species].mass, charge)
fwhm = self.atrOb.simulatedSpecies[species].peakFwhm
left = (self.widthL * fwhm) / 2.
right = (self.widthR * fwhm) / 2.
return [mz - left, mz + right]
def _getMzLimits(self,species,charge):
"""Get the m/z value upper and lower limits for extracting arrival
time data.
:parameter species: Name of molecular species (species)
:parameter charge: Charge state (int)
"""
mz = utils.get_mz(self.atrOb.simulatedSpecies[species].mass,charge)
fwhm = self.atrOb.simulatedSpecies[species].peakFwhm
left = (self.widthL*fwhm)/2.
right = (self.widthR*fwhm)/2.
return [mz-left,mz+right]
def getTotalIntensity(self, xvals, yvals):
"""Using the supplied data, sum the intensity of the highest
point of the data at the m/z value for each charge state in
self.charges using self.mass as the mass.
"""
'''Gets experimental intensity'''
intensity = 0
for charge in self.charges:
mz = utils.get_mz(self.mass, charge)
i = utils.closest(mz, xvals)
intensity += yvals[i]
return intensity
def getTotalIntensity(self,xvals,yvals):
"""Using the supplied data, sum the intensity of the highest
point of the data at the m/z value for each charge state in
self.charges using self.mass as the mass.
"""
'''Gets experimental intensity'''
intensity = 0
for charge in self.charges:
mz = utils.get_mz(self.mass, charge)
i = utils.closest(mz, xvals)
intensity += yvals[i]
return intensity
def eventAddCalibrant(
self,
event,
autoAxesLimits=1): # wxGlade: CalibrationGui.<event_handler>
"""Add a calibrant to the calibration. Opens calibrant using path textbox,
processes it and recalculates the calibration curve.
"""
# please wait dialog
bi = wx.BusyInfo("Working, please wait", self)
wx.Yield()
if self.textCtrlPath.GetValue() != "":
self.settings.setCalPath(self.textCtrlPath.GetValue())
calibrantName = self.settings.getCalNameCurrent()
# Mass Spectrum panel
calibrant = Calibrant(calibrantName, self.settings.calPath)
calibrant.plotMsAndExtractionLimits(self.getAxMS())
if autoAxesLimits:
mzs = [
utils.get_mz(calibrant.approxMass, z)
for z in calibrant.charges
]
self.settings.xlimsMs[calibrantName] = [
min(mzs) * 0.5, max(mzs) * 2
]
self.figure.axMs.set_xlim(self.settings.xlimsMs[calibrantName])
self.settings.ylimsMs[calibrantName] = self.figure.axMs.get_ylim()
self.figure.axMs.set_xlim(self.settings.xlimsMs[calibrantName])
self.figure.axMs.set_yticks([])
# Tds panel
calibrant.plotChargeStateAtds(self.getAxTds())
calibrant.plotCalibrantTdPeaks(self.getAxTds(clear=0))
if autoAxesLimits:
tds = [calibrant.tds[z] for z in calibrant.charges][:]
self.settings.xlimsTds[calibrantName] = [
min(tds) * 0.5, max(tds) * 2.0
]
self.settings.ylimsTds[calibrantName] = self.figure.axTds.get_ylim(
)
self.figure.axTds.set_xlim(self.settings.xlimsTds[calibrantName])
# Fill in the grid
self.panelCalibrantListCtrl.setData(calibrant)
self.calibrants[calibrantName] = calibrant
self.calibrantCharges[calibrantName] = calibrant.charges[:]
self.createCalibration()
self.draw()
bi.Destroy()
def __init__(self, mass, charge, speciesAllCharges):
# self.mass = None
# self.charge = None
# self.species = None
self.mass = mass
self.charge = charge
self.speciesAllCharges = sorted(speciesAllCharges, reverse=True)
self.mz = utils.get_mz(self.mass, self.charge)
self.limits = [None, None]
def simulateSpecies(self,xvals,peakShape='hybrid'):
"""Simulates a mass spectrum using the object's attributes
Valid peak shapes are: 'hybrid', 'gaussian' & 'lorentzian
if one_fwhh is to be used be sure to set self.peakFwhm before
calling this function.
"""
combined = np.zeros(len(xvals),dtype='float')
for z in self.charges:
centre = utils.get_mz(self.mass, z)
amplitude = self.zGauss.calculateAmplitude(centre)
combined += utils.draw_peaks[peakShape](xvals,amplitude,centre,self.peakFwhm)
return combined
def simulateSpecies(self, xvals, peakShape='hybrid'):
"""Simulates a mass spectrum using the object's attributes
Valid peak shapes are: 'hybrid', 'gaussian' & 'lorentzian
if one_fwhh is to be used be sure to set self.peakFwhm before
calling this function.
"""
combined = np.zeros(len(xvals), dtype='float')
for z in self.charges:
centre = utils.get_mz(self.mass, z)
amplitude = self.zGauss.calculateAmplitude(centre)
combined += utils.draw_peaks[peakShape](xvals, amplitude, centre,
self.peakFwhm)
return combined
def plotAtroposSelectionAutoWidth(self,ax,limitsD):
"""Uses limits generated by: getAutoPeakLimits() instead of relative to
atropos generated fwhm values.
:parameter ax: Matplotlib Axes object to use
:parameter limitsD: Set to True to use automatic maximum width size
for extraction
"""
ylims = ax.get_ylim()
for sp,d in limitsD.items():
mass = self.settings.imOb.species[sp].mass
for z,limits in d.items():
mz = utils.get_mz(mass,z)
ax.fill_betweenx(ylims,limits[0],
limits[1],color='red',alpha=0.1)
def generateCorrectedTdsAndCcss(self,waveVelocity,gas='Nitrogen'):
"""Calculate td prime and CCS prime, using the calibration equations
including the reduced mass equation.
:parameter waveVelocity: Velocity in m/s
:parameter gas: Mobililty gas used (default: 'Nitrogen')
"""
for i,charge in enumerate(self.charges):
mz = utils.get_mz(self.approxMass, charge)
# td
tdPrime = utils._calculateTdPrime(self.tds[charge], waveVelocity)
self.tdsDoublePrime[charge] = utils._calculateTdDoublePrime(tdPrime, mz)
#CCS
reducedMass = utils._calculateReducedMass(mz, charge, gas)
self.CcssPrime[charge] = utils._calculateOmegaPrime(self.publishedCcss[charge], charge, reducedMass)
def setSpeciesGivenMass(self, mass, xvals, yvals, peakFwhm, zs):
"""Similar to Species.setSpecies(). Except that instead of using
gPeaks, the Species() object is setup automatically when given
values for mass and the charges to be analysed.
"""
self.mass = mass
self.charges = zs
pseudogPeaks = {}
for z in zs:
xval = utils.get_mz(self.mass, z)
i = utils.closest(xval, xvals)
yval = yvals[i]
pseudogPeaks[z] = [xval, yval]
self.setSpecies(pseudogPeaks, peakFwhm)
def setSpeciesGivenMass(self,mass,xvals,yvals,peakFwhm,zs):
"""Similar to Species.setSpecies(). Except that instead of using
gPeaks, the Species() object is setup automatically when given
values for mass and the charges to be analysed.
"""
self.mass = mass
self.charges = zs
pseudogPeaks = {}
for z in zs:
xval = utils.get_mz(self.mass, z)
i = utils.closest(xval, xvals)
yval = yvals[i]
pseudogPeaks[z] = [xval,yval]
self.setSpecies(pseudogPeaks, peakFwhm)
def getPeakWidthLimits(self,name,charge,leftMultiplier=1,rightMultiplier=1):
"""Calculate the lower and upper m/z limits for a particular peak in relation
to the multiplier values. (only use after calculating the mass spectrum fit).
:parameter name: Species name
:parameter charge: Charge to display
:parameter leftMultiplier: Value to multiply the peak fwhm below the mean
:parameter rightMultiplier: Value to multiply the peak fwhm above the mean
:returns: m/z limits when using multiplier as [lowerLimit,upperLimit]
"""
mass = self.species[name].mass
fwhm = self.species[name].peakFwhm
mz = utils.get_mz(mass,charge)
leftLim = mz - (fwhm/2 * leftMultiplier)
rightLim = mz + (fwhm/2 * rightMultiplier)
return [leftLim,rightLim]
def plotAtroposSelectionAutoWidth(self, ax, limitsD):
"""Uses limits generated by: getAutoPeakLimits() instead of relative to
atropos generated fwhm values.
:parameter ax: Matplotlib Axes object to use
:parameter limitsD: Set to True to use automatic maximum width size
for extraction
"""
ylims = ax.get_ylim()
for sp, d in limitsD.items():
mass = self.settings.imOb.species[sp].mass
for z, limits in d.items():
mz = utils.get_mz(mass, z)
ax.fill_betweenx(ylims,
limits[0],
limits[1],
color='red',
alpha=0.1)
def _estimateCharges(self,limit=1):
"""Estimate charges to be simulated by fitting the charge state
Gaussian distribution.
Used as a subfunction for self.setSpecies()
Limit is given as a percentage of the total height of the Gaussian
and is used as the cutoff point for whether a charge state is to
be included or discarded.
"""
# TODO(gns) - perhaps lower the limit for atropos at least
# probably the default value as well.
zs = np.arange(1,151)
charges = []
for z in zs:
xval = utils.get_mz(self.mass, z)
height = self.zGauss.calculateAmplitude(xval)
if height > self.zGauss.amplitude*(float(limit)/100):
charges.append(z)
return charges
def _estimateCharges(self, limit=1):
"""Estimate charges to be simulated by fitting the charge state
Gaussian distribution.
Used as a subfunction for self.setSpecies()
Limit is given as a percentage of the total height of the Gaussian
and is used as the cutoff point for whether a charge state is to
be included or discarded.
"""
# TODO(gns) - perhaps lower the limit for atropos at least
# probably the default value as well.
zs = np.arange(1, 151)
charges = []
for z in zs:
xval = utils.get_mz(self.mass, z)
height = self.zGauss.calculateAmplitude(xval)
if height > self.zGauss.amplitude * (float(limit) / 100):
charges.append(z)
return charges
def eventAddCalibrant(self, event,autoAxesLimits=1): # wxGlade: CalibrationGui.<event_handler>
"""Add a calibrant to the calibration. Opens calibrant using path textbox,
processes it and recalculates the calibration curve.
"""
# please wait dialog
bi = wx.BusyInfo("Working, please wait", self)
wx.Yield()
if self.textCtrlPath.GetValue() != "":
self.settings.setCalPath(self.textCtrlPath.GetValue())
calibrantName = self.settings.getCalNameCurrent()
# Mass Spectrum panel
calibrant = Calibrant(calibrantName,self.settings.calPath)
calibrant.plotMsAndExtractionLimits(self.getAxMS())
if autoAxesLimits:
mzs = [utils.get_mz(calibrant.approxMass, z) for z in calibrant.charges]
self.settings.xlimsMs[calibrantName] = [min(mzs)*0.5,max(mzs)*2]
self.figure.axMs.set_xlim(self.settings.xlimsMs[calibrantName])
self.settings.ylimsMs[calibrantName] = self.figure.axMs.get_ylim()
self.figure.axMs.set_xlim(self.settings.xlimsMs[calibrantName])
self.figure.axMs.set_yticks([])
# Tds panel
calibrant.plotChargeStateAtds(self.getAxTds())
calibrant.plotCalibrantTdPeaks(self.getAxTds(clear=0))
if autoAxesLimits:
tds = [calibrant.tds[z] for z in calibrant.charges][:]
self.settings.xlimsTds[calibrantName] = [min(tds)*0.5,max(tds)*2.0]
self.settings.ylimsTds[calibrantName] = self.figure.axTds.get_ylim()
self.figure.axTds.set_xlim(self.settings.xlimsTds[calibrantName])
# Fill in the grid
self.panelCalibrantListCtrl.setData(calibrant)
self.calibrants[calibrantName] = calibrant
self.calibrantCharges[calibrantName] = calibrant.charges[:]
self.createCalibration()
self.draw()
bi.Destroy()
def forLeastSquaresOptimisation(self,p0,xvals,zs,oneFwhm):
"""Creates the simulated mass spectrum for MassSpectrum.leastSquaresOptimisation().
p0 - parameters to be used in simulation
zs - charges to be simulated
oneFwhm - if True use same FWHM for each species.
"""
ps = self._splitPs(p0)
combined = np.zeros(len(xvals))
zGauss = Gaussian()
for i,p in enumerate(ps):
zGauss.setParameters(p[1], p[2], p[3])
for j,z in enumerate(zs[i]):
centre = utils.get_mz(p[0], z)
amplitude = zGauss.calculateAmplitude(centre)
if oneFwhm:
combined += utils.draw_peaks['hybrid'](xvals,amplitude,centre,p0[4])
else:
combined += utils.draw_peaks['hybrid'](xvals,amplitude,centre,p[4])
return combined
def _updateSpecies(self,speciesObj=0,peakFwhm=0,leftMultiplier=0,rightMultiplier=0,updateApex=1):
"""Update the settings of the species object.
:parameter speciesObj: msClasses.Species() object (or 0 to use self.speciesObj)
:parameter peakFwhm: m/z width to use when extracting arrival time data
:parameter leftMultiplier: Multiply by the peak width lower than the mean
:parameter rightMultiplier: Multiply by the peak width above the mean
:parameter updateApex: If True, recalculate the td apex
"""
if peakFwhm:
self.peakFwhm = peakFwhm
if leftMultiplier:
self.leftMultiplier = leftMultiplier
if rightMultiplier:
self.rightMultiplier = rightMultiplier
if not speciesObj:
speciesObj = self.speciesObj
# check charges are within the mass spectrum limits
zs = []
left = self.peakFwhm * self.leftMultiplier
right = self.peakFwhm * self.rightMultiplier
for z in self.charges:
mz = utils.get_mz(self.approxMass,z)
if self.imObj.xaxis.min()+left < mz < self.imObj.xaxis.max()-right:
zs.append(z)
else:
print 'charge outside m/z range'
self.charges = zs
self.speciesObj.charges = self.charges
self.imObj.setSpecies(self.speciesObj)
self.imObj.generateSpeciesSlicesFwhm(self.name, self.leftMultiplier, self.rightMultiplier)
if updateApex:
self.tds = collections.OrderedDict()
for z in self.charges:
self.imObj.dataSlices[self.name][z].atd.smoothingSG(window_len=3, smoothes=1, poly_order=1)
td = self.imObj.dataSlices[self.name][z].getAtdApex()
self.tds[z] = td
def getPeakWidthLimits(self,
name,
charge,
leftMultiplier=1,
rightMultiplier=1):
"""Calculate the lower and upper m/z limits for a particular peak in relation
to the multiplier values. (only use after calculating the mass spectrum fit).
:parameter name: Species name
:parameter charge: Charge to display
:parameter leftMultiplier: Value to multiply the peak fwhm below the mean
:parameter rightMultiplier: Value to multiply the peak fwhm above the mean
:returns: m/z limits when using multiplier as [lowerLimit,upperLimit]
"""
mass = self.species[name].mass
fwhm = self.species[name].peakFwhm
mz = utils.get_mz(mass, charge)
leftLim = mz - (fwhm / 2 * leftMultiplier)
rightLim = mz + (fwhm / 2 * rightMultiplier)
return [leftLim, rightLim]
def getAutoPeakLimits(self):
# Get all the mzs of the various species charge states
zsD,massD = self.settings.getChargeAndMassDictionaries()
mzsD = OrderedDict()
chargeStatePeakObs = []
allMzs = []
for sp, zs in zsD.items():
mzsD[sp] = []
for z in zs:
mz = utils.get_mz(massD[sp],z)
mzsD[sp].append(mz)
allMzs.append(mz)
# See if they overlap
limitsD = OrderedDict()
for sp,zs in zsD.items():
limitsD[sp] = OrderedDict()
for z in zs:
csOb = ChargeStatePeak.ChargeStatePeak(massD[sp],z,zs)
limits = csOb.getLimits(allMzs)
limitsD[sp][z] = limits
return limitsD
def getAutoPeakLimits(self):
# Get all the mzs of the various species charge states
zsD, massD = self.settings.getChargeAndMassDictionaries()
mzsD = OrderedDict()
chargeStatePeakObs = []
allMzs = []
for sp, zs in zsD.items():
mzsD[sp] = []
for z in zs:
mz = utils.get_mz(massD[sp], z)
mzsD[sp].append(mz)
allMzs.append(mz)
# See if they overlap
limitsD = OrderedDict()
for sp, zs in zsD.items():
limitsD[sp] = OrderedDict()
for z in zs:
csOb = ChargeStatePeak.ChargeStatePeak(massD[sp], z, zs)
limits = csOb.getLimits(allMzs)
limitsD[sp][z] = limits
return limitsD
def forLeastSquaresOptimisation(self, p0, xvals, zs, oneFwhm):
"""Creates the simulated mass spectrum for MassSpectrum.leastSquaresOptimisation().
p0 - parameters to be used in simulation
zs - charges to be simulated
oneFwhm - if True use same FWHM for each species.
"""
ps = self._splitPs(p0)
combined = np.zeros(len(xvals))
zGauss = Gaussian()
for i, p in enumerate(ps):
zGauss.setParameters(p[1], p[2], p[3])
for j, z in enumerate(zs[i]):
centre = utils.get_mz(p[0], z)
amplitude = zGauss.calculateAmplitude(centre)
if oneFwhm:
combined += utils.draw_peaks['hybrid'](xvals, amplitude,
centre, p0[4])
else:
combined += utils.draw_peaks['hybrid'](xvals, amplitude,
centre, p[4])
return combined
def plotTheoreticalMzs(self,
ax,
xvals,
yvals,
absolute=0,
mass=0,
**kwargs):
"""Used to draw the positions of calculated charge state peaks.
If a value for absolute is given, it is used as the y axis position for charge
state labels.
All matplotlib.pyplot.plot() arguments are allowed in **kwargs.
"""
if not mass:
mass = self.mass
oneDone = False
for i, z in enumerate(np.arange(100) + 1):
mz = utils.get_mz(mass, z)
if xvals[0] < mz < xvals[-1]:
# the line
if not oneDone:
ax.axvline(mz,
label="%s - %.1f Da +/- %.1f" %
(self.name, self.mass, self.calcMassError),
**kwargs)
else:
ax.axvline(mz, **kwargs)
oneDone = True
# annotation
if z / 2 == float(z) / 2: lift = .1 * yvals.max()
else: lift = .2 * yvals.max()
if not 'color' in kwargs:
color = 'blue'
else:
color = kwargs['color']
if not absolute:
ax.text(mz, lift, '+%d' % z, color=color)
else:
ax.text(mz, absolute, '+%d' % z, color=color)
def calibrationFigure(self,
fig,
calibrationObj,
spToDisplay=0,
autoAxesLimits=1,
colourList=0,
**kwargs):
# TODO(gns) - This can probably be removed only used in:
# 121207_test_SpecialFigureCalibration.py, 121209_test_SpecialFigureCalibration2.py
if not spToDisplay:
spToDisplay = calibrationObj.calibrants.keys()[0]
if not colourList:
colourList = utils.colourList
sps = calibrationObj.calibrants.keys()
bandColour = colourList[sps.index(spToDisplay)]
calibrant = calibrationObj.calibrants[spToDisplay]
ax = fig.add_subplot(311) # mass spectrum
calibrant.plotMsAndExtractionLimits(ax, bandColour, **kwargs)
if autoAxesLimits:
mzs = [
utils.get_mz(calibrant.approxMass, z)
for z in calibrant.charges
]
plt.xlim([min(mzs) * 0.5, max(mzs) * 2])
ax = fig.add_subplot(312) # atds
calibrant.plotChargeStateAtds(ax, colourList=colourList)
calibrant.plotCalibrantTdPeaks(ax, colourList=colourList)
if autoAxesLimits:
tdPrimes = [calibrant.tdsDoublePrime[z] for z in calibrant.charges]
plt.xlim([min(tdPrimes) * 0.5, max(tdPrimes) * 2.0])
ax = fig.add_subplot(313) # fit
calibrationObj.plotCalibrationCurve(ax, colourList, **kwargs)
def getMz(self,z):
"""Calculate the m/z value for a given charge state using the mass
from self.mass
"""
return utils.get_mz(self.mass, z)
def getMz(self, z):
"""Calculate the m/z value for a given charge state using the mass
from self.mass
"""
return utils.get_mz(self.mass, z)
