def main( file = None ):
mzMLFile = 'profile-mass-spectrum.mzml'
get_example_file.open_example(mzMLFile)
run = pymzml.run.Reader("mzML_example_files/"+mzMLFile, MSn_Precision = 25e-6)
p = pymzml.plot.Factory()
for spec in run:
p.newPlot()
p.add(spec.peaks, color=(200,0,0), style='squares')
p.add(spec.centroidedPeaks, color=(0,0,0), style='sticks')
p.add(spec.reprofiledPeaks, color=(25,0,200), style='circles')
p.save( filename="output/plotAspect.xhtml" , mzRange = [744.7,747] )
def main(file=None):
mzMLFile = 'profile-mass-spectrum.mzml'
get_example_file.open_example(mzMLFile)
run = pymzml.run.Reader("mzML_example_files/" + mzMLFile,
MSn_Precision=25e-6)
p = pymzml.plot.Factory()
for spec in run:
p.newPlot()
p.add(spec.peaks, color=(200, 0, 0), style='squares')
p.add(spec.centroidedPeaks, color=(0, 0, 0), style='sticks')
p.add(spec.reprofiledPeaks, color=(25, 0, 200), style='circles')
p.save(filename="output/plotAspect.xhtml", mzRange=[744.7, 747])
def main():
ref = set([(801.266, 1), (419.115, 1), (460.227, 1), (723.888, 1),
(948.349, 1), (406.261, 1), (919.143, 1), (536.459, 1),
(1082.504, 1), (474.342, 1)])
example_file = get_example_file.open_example('dta_example.mzML')
run = pymzml.run.Reader(example_file,
MS1_Precision=5e-6,
MSn_Precision=20e-6)
precursor_count_dict = ddict(int)
for spectrum in run:
if spectrum["ms level"] == 2:
if "precursors" in spectrum.keys():
precursor_count_dict[round(
float(spectrum["precursors"][0]["mz"]), 3)] += 1
precursor_set = set()
for precursor, frequency in sorted(precursor_count_dict.items(),
key=itemgetter(1)):
precursor_set.add((precursor, frequency))
if precursor_set == ref:
return True
else:
return False
def main(verbose = False):
file_n = 0
successful = dict()
for example_file in get_example_file.SHA256_DICT.keys():
file_n += 1
n = 1
if verbose:
print("{0}\t{1}\t{2}".format(file_n, n, example_file),file = sys.stderr)
try:
for spec in pymzml.run.Reader(get_example_file.open_example(example_file)):
n += 1
spec.peaks
spec.centroidedPeaks
spec.removeNoise('median')
spec.hasPeak(100)
spec.deRef()
spec.extremeValues('mz')
spec.extremeValues('i')
successful[example_file] = True
except:
if verbose:
raise
successful[example_file] = False
return False
if verbose:
for file in successful:
print('{0}\t{1}'.format(file, successful[file]))
return True
def main(verbose=False):
examplemzML = get_example_file.open_example('BSA1.mzML')
if verbose:
print("""
comparing specs
""")
run = pymzml.run.Reader(examplemzML)
tmp = []
for spec in run:
if spec['ms level'] == 1:
if verbose:
print("Parsing spec lvl 1 has id {0}".format(spec['id']))
tmp.append(spec.deRef())
if len(tmp) >= 3:
break
if verbose:
print("Print total number of specs collected {0}".format(len(tmp)))
print("cosine between spec 1 & 2 is ", tmp[0].similarityTo(tmp[1]))
print("cosine score between spec 1 & 3 is ",
tmp[0].similarityTo(tmp[2]))
print("cosine score between spec 2 & 3 is ",
tmp[1].similarityTo(tmp[2]))
print("cosine score between first spec against itself ",
tmp[0].similarityTo(tmp[0]))
if tmp[0].similarityTo(tmp[0]) == 1:
return True
else:
return False
def main(verbose = False):
file_n = 0
successful = dict()
for example_file in get_example_file.SHA256_DICT.keys():
file_n += 1
n = 1
if verbose:
print("{0}\t{1}\t{2}".format(file_n, n, example_file),file = sys.stderr)
try:
for spec in pymzml.run.Reader(get_example_file.open_example(example_file)):
n += 1
spec.peaks
spec.centroidedPeaks
spec.removeNoise('median')
spec.hasPeak(100)
spec.deRef()
spec.extremeValues('mz')
spec.extremeValues('i')
successful[example_file] = True
except:
if verbose:
raise
successful[example_file] = False
return False
if verbose:
for file in successful:
print('{0}\t{1}'.format(file, successful[file]))
return True
def main(verbose = False):
examplemzML = get_example_file.open_example('BSA1.mzML')
if verbose:
print("""
comparing specs
""")
run = pymzml.run.Reader(examplemzML)
tmp = []
for spec in run:
if spec['ms level'] == 1:
if verbose:
print("Parsing spec lvl 1 has id {0}".format(spec['id']))
tmp.append(spec.deRef())
if len(tmp) >= 3:
break
if verbose:
print("Print total number of specs collected {0}".format(len(tmp) ) )
print("cosine between spec 1 & 2 is ",tmp[0].similarityTo(tmp[1]))
print("cosine score between spec 1 & 3 is ",tmp[0].similarityTo(tmp[2]))
print("cosine score between spec 2 & 3 is ",tmp[1].similarityTo(tmp[2]))
print("cosine score between first spec against itself ",tmp[0].similarityTo(tmp[0]))
if tmp[0].similarityTo(tmp[0]) == 1:
return True
else:
return False
def main():
answer = False
pymzmlRun = pymzml.run.Reader(get_example_file.open_example('small.pwiz.1.1.mzML'))
if pymzmlRun['TIC'].profile == [(0.004935, 15245068.0), (0.007896666666666666, 12901166.0), (0.011218333333333334, 586279.0), (0.022838333333333332, 441570.15625), (0.034925, 114331.703125), (0.04862, 130427.3046875), (0.06192333333333334, 580561.0625), (0.075015, 15148302.0), (0.07778833333333333, 10349958.0), (0.08120333333333334, 848427.3125), (0.09290333333333332, 456143.4375), (0.10480333333333333, 124170.3828125), (0.11721500000000001, 104264.796875), (0.13002166666666667, 147409.234375), (0.14345166666666667, 18257344.0), (0.14640833333333333, 11037852.0), (0.149755, 1102582.125), (0.16144166666666668, 360250.96875), (0.17337, 125874.828125), (0.18665833333333332, 142243.390625), (0.200695, 147414.578125), (0.2136733333333333, 17613074.0), (0.21674666666666667, 1597410.5), (0.22007333333333332, 990298.5), (0.23292333333333332, 447647.96875), (0.244745, 71677.03125), (0.2591716666666667, 119999.7421875), (0.2726633333333333, 152281.25), (0.28548333333333337, 22136832.0), (0.2888983333333333, 12434530.0), (0.3037033333333333, 379009.78125), (0.31565, 120473.4296875), (0.32852666666666663, 113763.3515625), (0.342915, 73607.4921875), (0.35855833333333337, 16495375.0), (0.36142833333333335, 6548706.5), (0.364755, 1041573.75), (0.37657833333333335, 626711.3125), (0.3886733333333333, 109042.7265625), (0.40196166666666666, 156294.984375), (0.4151316666666667, 79339.078125), (0.4284833333333333, 12015003.0), (0.4332216666666666, 13332331.0), (0.4365666666666667, 925073.25), (0.44832, 419351.46875), (0.46056499999999995, 88901.921875), (0.47310333333333326, 100616.1953125), (0.48723666666666665, 77939.0078125)]:
answer = True
return answer
def main(verbose=False):
ref_intensities = set([
9258.819334518503, 19141.735187697403, 20922.463809964283,
10594.642802391083, 9193.546071711491
])
example_file = get_example_file.open_example('deconvolution.mzML.gz')
run = pymzml.run.Reader(example_file,
MS1_Precision=5e-6,
MSn_Precision=20e-6)
highest_i_list = list()
for spectrum in run:
if spectrum["ms level"] == 2:
if spectrum["id"] == 1770:
for mz, i in spectrum.highestPeaks(5):
highest_i_list.append(i)
if set(highest_i_list) == set(ref_intensities):
if verbose:
print("Function .highestPeaks worked properly")
return True
else:
return False
def main():
"""
Accessing positive or negative polarity of scan using obo 1.1.0
usage:
./polarity.py
"""
example_file = get_example_file.open_example("small.pwiz.1.1.mzML")
run = pymzml.run.Reader(example_file, obo_version="1.1.0")
for spec in run:
negative_polarity = spec["negative scan"]
if negative_polarity is None:
negative_polarity = False
if negative_polarity == "":
negative_polarity = True
positive_polarity = spec["positive scan"]
if positive_polarity is None:
positive_polarity = False
if positive_polarity == "":
positive_polarity = True
else:
positive_polarity = False
print("Polarity negative {0} - Polarity positive {1}".format(
negative_polarity, positive_polarity))
exit(1)
return
def setUp(self):
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:
# there is only one spectrum, so just read this
self.spec = spec
break
def main():
"""
Accessing positive or negative polarity of scan using obo 1.1.0
usage:
./polarity.py
"""
example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
run = pymzml.run.Reader(
example_file,
obo_version='1.1.0',
)
for spec in run:
negative_polarity = spec['negative scan']
if negative_polarity is None:
negative_polarity = False
if negative_polarity == '':
negative_polarity = True
positive_polarity = spec['positive scan']
if positive_polarity is None:
positive_polarity = False
if positive_polarity == '':
positive_polarity = True
else:
positive_polarity = False
print('Polarity negative {0} - Polarity positive {1}'.format(
negative_polarity, positive_polarity))
exit(1)
return
def main(verbose = False):
example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
run = pymzml.run.Reader(
example_file,
MSn_Precision = 250e-6,
obo_version = '1.1.0',
extraAccessions = [
('MS:1000129',['value']),
('MS:1000130',['value'])
]
)
for spec in run:
negative_polarity = spec.get('MS:1000129', False)
if negative_polarity == '':
negative_polarity = True
positive_polarity = spec.get('MS:1000130', False)
if positive_polarity == '':
positive_polarity = True
print(
'Polarity negative {0} - Polarity positive {1}'.format(
negative_polarity,
positive_polarity
)
)
exit(1)
return True
def setUp(self):
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:
# there is only one spectrum, so just read this
self.spec = spec
break
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", )
def main(verbose = False):
example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
run = pymzml.run.Reader(example_file, MS1_Precision = 20e-6, MSn_Precision = 20e-6)
timeDependentIntensities = []
for spectrum in run:
if spectrum['ms level'] == 1:
matchList = spectrum.hasPeak(MASS_2_FOLLOW)
if matchList != []:
for mz,I in matchList:
timeDependentIntensities.append( [ spectrum['scan time'], I , mz ])
print('RT \ti \tmz')
for rt, i, mz in timeDependentIntensities:
print('{0:5.3f}\t{1:13.4f}\t{2:10}'.format( rt, i, mz ))
return
def main(verbose=False):
example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
run = pymzml.run.Reader(example_file, MSn_Precision=250e-6)
spectrum = run[1]
if verbose:
print(spectrum['id'], spectrum['ms level'])
for element in spectrum.xmlTree:
if verbose:
print('-' * 40)
print(element)
print(element.get('accession'))
print(element.tag)
print(element.items())
return True
def main(verbose = False):
example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
run = pymzml.run.Reader(example_file, MSn_Precision = 250e-6)
spectrum = run[1]
if verbose:
print(spectrum['id'], spectrum['ms level'])
for element in spectrum.xmlTree:
if verbose:
print('-'*40)
print(element)
print(element.get('accession') )
print(element.tag)
print(element.items())
return True
def main():
mzMLFile = "profile-mass-spectrum.mzml"
example_file = get_example_file.open_example(mzMLFile)
run = pymzml.run.Reader(example_file, MSn_Precision=250e-6)
p = pymzml.plot.Factory()
for spec in run:
p.newPlot()
p.add(spec.peaks, color=(200, 00, 00), style="circles")
p.add(spec.centroidedPeaks, color=(00, 00, 00), style="sticks")
p.add(spec.reprofiledPeaks, color=(00, 255, 00), style="circles")
p.save(filename="output/plotAspect.xhtml", mzRange=[744.7, 747])
break
return
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",)
def main():
ref = set([(801.266,1),(419.115,1),(460.227,1),(723.888,1),(948.349,1),(406.261,1),(919.143,1),(536.459, 1),(1082.504,1),(474.342, 1)])
example_file = get_example_file.open_example('dta_example.mzML')
run = pymzml.run.Reader(example_file, MS1_Precision = 5e-6, MSn_Precision = 20e-6)
precursor_count_dict = ddict(int)
for spectrum in run:
if spectrum["ms level"] == 2:
if "precursors" in spectrum.keys():
precursor_count_dict[round(float(spectrum["precursors"][0]["mz"]),3)] += 1
precursor_set = set()
for precursor, frequency in sorted(precursor_count_dict.items(), key = itemgetter(1)):
precursor_set.add((precursor, frequency))
if precursor_set == ref:
return True
else:
return False
def main( file = None):
if file == None:
mzMLFile = 'profile-mass-spectrum.mzml'
example_file = get_example_file.open_example(mzMLFile)
else:
example_file = file
run = pymzml.run.Reader(example_file, MSn_Precision = 250e-6)
p = pymzml.plot.Factory()
from collections import defaultdict as ddict
checks = ddict(int)
for spec in run:
if spec['id'] <= 1000:
continue
if sum(checks.values()) > 55:
break
if checks[1] > 30:
continue
if checks[2] > 30:
continue
p.newPlot(header = '{ms level}'.format(**spec))
# p.add(spec.peaks, color=(200,00,00), style='circles')
p.add(spec.reprofiledPeaks, color=(100,100,100), style='triangle')
p.add(spec.centroidedPeaks, color=(00,00,00), style='sticks')
checks[ int(spec['ms level']) ] += 1
p.save( filename="output/plotAspect_all.xhtml" )
exit(1)
specs = [ 4927,4930,4934,4936,4938,4942,4946,4948,4950,4954,4955,4957,4959,4962,4965,4967,4971,4976,4979,4982,4985,4990,4991,4995,4999,5004]
for specID in specs:
spec = run[ specID ]
p.newPlot()
# p.add(spec.peaks, color=(200,00,00), style='circles')
p.add(spec.reprofiledPeaks, color=(100,100,100), style='triangle')
p.add(spec.centroidedPeaks, color=(00,00,00), style='sticks')
# break
p.save( filename="output/plotAspect.xhtml" , mzRange = [840.,853.] )
return
def main(verbose = False):
ref_intensities = set([9258.819334518503, 19141.735187697403, 20922.463809964283, 10594.642802391083, 9193.546071711491])
example_file = get_example_file.open_example('deconvolution.mzML.gz')
run = pymzml.run.Reader(example_file, MS1_Precision = 5e-6, MSn_Precision = 20e-6)
highest_i_list = list()
for spectrum in run:
if spectrum["ms level"] == 2:
if spectrum["id"] == 1770:
for mz,i in spectrum.highestPeaks(5):
highest_i_list.append(i)
if set(highest_i_list) == set(ref_intensities):
if verbose:
print("Function .highestPeaks worked properly")
return True
else:
return False
def main( file = None):
if file == None:
mzMLFile = 'profile-mass-spectrum.mzml'
example_file = get_example_file.open_example(mzMLFile)
else:
example_file = file
run = pymzml.run.Reader(example_file, MSn_Precision = 250e-6)
p = pymzml.plot.Factory()
specs = [ 4927,4930,4934,4936,4938,4942,4946,4948,4950,4954,4955,4957,4959,4962,4965,4967,4971,4976,4979,4982,4985,4990,4991,4995,4999,5004]
for specID in specs:
spec = run[ specID ]
p.newPlot()
# p.add(spec.peaks, color=(200,00,00), style='circles')
p.add(spec.reprofiledPeaks, color=(100,100,100), style='triangle')
p.add(spec.centroidedPeaks, color=(00,00,00), style='sticks')
# break
p.save( filename="output/plotAspect.xhtml" , mzRange = [840.,853.] )
return
def main(verbose=False):
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 spectrum in run:
if verbose:
print("Processing spectrum #{0}".format(spectrum['id']), end="\r")
print('')
if spectrum['ms level'] == 2:
test1 = spectrum.hasDeconvolutedPeak(1044.559675129575)
test2 = spectrum.hasDeconvolutedPeak(1044.5804)
test3 = spectrum.hasDeconvolutedPeak(1044.5806)
test4 = spectrum.hasDeconvolutedPeak(1044.5800)
test5 = spectrum.hasDeconvolutedPeak(6000)
test6 = spectrum.hasPeak(1016.5402567492666)
test7 = spectrum.hasPeak(6000)
tests = [False, False, False, False, False, False, False]
if test1 == [(1044.559675129575, 3809.4356300564586)]:
tests[0] = True
if test2 == [(1044.559675129575, 3809.4356300564586)]:
tests[1] = True
if test3 == []:
tests[2] = True
if test4 == [(1044.559675129575, 3809.4356300564586)]:
tests[3] = True
if test5 == []:
tests[4] = True
if test6 == [(1016.5402567492666, 19141.735187697403)]:
tests[5] = True
if test7 == []:
tests[6] = True
all = True
for i in range(len(tests)):
if not tests[i]:
all = False
if all:
if verbose:
print('All tests were successful.')
else:
print(tests)
if verbose:
print('deconvoluted peaks list:')
print('')
print('centroided peaks list:')
print(spectrum.centroidedPeaks)
print('')
print('deconvolutedPeaks list:')
print(spectrum.deconvolutedPeaks)
print('')
print(
"1044.559675129575 in deconvoluted spectrum? (should be)",
test1)
print(
"1044.559675129575 + 20 ppm = 1044.5804 in deconvoluted spectrum? (should be)",
test2)
print(
"1044.559675129575 + >20 ppm = 1044.5806 in deconvoluted spectrum? (shouldn't)",
test3)
print("1044.5800 in deconvoluted spectrum? (should be)", test4)
print("6000 in deconvoluted spectrum (shouldn't)?", test5)
print("1016.5402567492666 in centroided peaks (True)", test6)
print("6000 in centroided peaks (None)", test7)
if all:
return True
Example:
>>> example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
>>> run = pymzml.run.Reader(example_file, MS1_Precision = 5e-6)
>>> run2 = pymzml.run.Writer(filename = 'write_test.mzML', run= run , overwrite = True)
>>> specOfIntrest = run[2]
>>> run2.addSpec(spec)
>>> run2.save()
"""
from __future__ import print_function
import pymzml
import get_example_file
if __name__ == '__main__':
example_file = get_example_file.open_example('small.pwiz.1.1.mzML')
run = pymzml.run.Reader(
example_file,
MS1_Precision = 5e-6
)
run2 = pymzml.run.Writer(
filename = 'write_test.mzML',
run= run,
overwrite = True
)
spec = run[1]
run2.addSpec(spec)
run2.save()
def main(verbose = False):
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 spectrum in run:
if verbose:
print("Processing spectrum #{0}".format(spectrum['id']), end="\r")
print('')
if spectrum['ms level'] == 2:
test1 = spectrum.hasDeconvolutedPeak(1044.559675129575)
test2 = spectrum.hasDeconvolutedPeak(1044.5804)
test3 = spectrum.hasDeconvolutedPeak(1044.5806)
test4 = spectrum.hasDeconvolutedPeak(1044.5800)
test5 = spectrum.hasDeconvolutedPeak(6000)
test6 = spectrum.hasPeak(1016.5402567492666)
test7 = spectrum.hasPeak(6000)
tests = [False, False, False, False, False, False, False]
if test1 == [(1044.559675129575, 3809.4356300564586)]:
tests[0] = True
if test2 == [(1044.559675129575, 3809.4356300564586)]:
tests[1] = True
if test3 == []:
tests[2] = True
if test4 == [(1044.559675129575, 3809.4356300564586)]:
tests[3] = True
if test5 == []:
tests[4] = True
if test6 == [(1016.5402567492666, 19141.735187697403)]:
tests[5] = True
if test7 == []:
tests[6] = True
all = True
for i in range(len(tests)):
if not tests[i]:
all = False
if all:
if verbose:
print('All tests were successful.')
else:
print(tests)
if verbose:
print('deconvoluted peaks list:')
print('')
print('centroided peaks list:')
print(spectrum.centroidedPeaks)
print('')
print('deconvolutedPeaks list:')
print(spectrum.deconvolutedPeaks)
print('')
print("1044.559675129575 in deconvoluted spectrum? (should be)", test1)
print("1044.559675129575 + 20 ppm = 1044.5804 in deconvoluted spectrum? (should be)", test2)
print("1044.559675129575 + >20 ppm = 1044.5806 in deconvoluted spectrum? (shouldn't)", test3)
print("1044.5800 in deconvoluted spectrum? (should be)", test4)
print("6000 in deconvoluted spectrum (shouldn't)?", test5)
print("1016.5402567492666 in centroided peaks (True)", test6)
print("6000 in centroided peaks (None)", test7)
if all:
return True
