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#!/usr/bin/env python
"""
Example for retrieving monoisotopic peaks from the processed spectrum.
The python-matplotlib has to be installed for plotting. Otherwise a list of
monoisotopic peaks will be returned.
Example:
>>> import pymzml, get_example_file
>>> example_file = get_example_file.open_example('deconvolution.mzML.gz')
>>> run = pymzml.MSRun(example_file, MS1_Precision = 5e-6, MSn_Precision = 20e-6)
>>> for spectrum in run:
... if spectrum.lvl == 2:
... l = spectrum.get_deisotopedMZ_for_chargeDeconvolution()
... if len(l) > 0:
... print(l)
"""
from __future__ import print_function
import sys
import os
import pymzml
import get_example_file
def deconvolution():
example_file = get_example_file.open_example('deconvolution.mzML.gz')
run = pymzml.run.Reader(example_file, MS1_Precision = 5e-6, MSn_Precision = 20e-6)
for spec in run:
charge_dict = dict()
for mz, i, charge, n in spec._get_deisotopedMZ_for_chargeDeconvolution():
charge_dict[mz] = charge
p = pymzml.plot.Factory()
tmp = spec.deRef()
tmp.reduce((590, 615))
p.newPlot(header = 'centroided I', mzRange = [590, 615])
p.add(spec.centroidedPeaks, color=(200,00,00), style='sticks')
for mz, i in tmp.centroidedPeaks:
try:
p.add([ (mz,'mz = {0}, z = {1}'.format(mz, charge_dict[mz]) ) ], color=(000,200,00), style='label' )
except KeyError:
p.add([ (mz,'mz = {0}'.format(mz) ) ], color=(000,200,00), style='label' )
tmp = spec.deRef()
tmp.reduce((1190, 1215))
p.newPlot(header = 'centroided II', mzRange = [1190, 1215])
p.add(spec.centroidedPeaks, color=(200,00,00), style='sticks')
for mz, i in tmp.centroidedPeaks:
try:
p.add([ (mz,'mz = {0}, z = {1}'.format(mz, charge_dict[mz]) ) ], color=(000,200,00), style='label' )
except KeyError:
p.add([ (mz,'mz = {0}'.format(mz) ) ], color=(000,200,00), style='label' )
p.newPlot(header = 'deconvoluted', mzRange = [1190, 1215])
p.add(spec.deconvolutedPeaks, color=(200,00,00), style='sticks')
tmp = spec.deRef()
tmp.reduce((1190, 1215))
for mass, i in tmp.deconvolutedPeaks:
p.add([ (mass,'mass = {0}'.format(mass) ) ], color=(000,200,00), style='label' )
p.save(filename = "output/deconvolution.xhtml",)
if __name__ == '__main__':
deconvolution()
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