def get_average_mass_spectrum_by_scanlist(
self,
scans_list: List[int],
auto_process: bool = True,
ppm_tolerance: float = 5.0) -> MassSpecProfile:
'''
Averages selected scans mass spectra using Thermo's AverageScans method
scans_list: list[int]
auto_process: bool
If true performs peak picking, and noise threshold calculation after creation of mass spectrum object
Returns:
MassSpecProfile
'''
"""
Averages selected scans mass spectra using Thermo's AverageScans method
scans_list: list[int]
auto_process: bool
If true performs peak picking, and noise threshold calculation after creation of mass spectrum object
Returns:
MassSpecProfile
"""
d_params = self.set_metadata(scans_list=scans_list)
# assumes scans is full scan or reduced profile scan
scans = List[int]()
for scan in scans_list:
scans.Add(scan)
# Create the mass options object that will be used when averaging the scans
options = MassOptions()
options.ToleranceUnits = ToleranceUnits.ppm
options.Tolerance = ppm_tolerance
# Get the scan filter for the first scan. This scan filter will be used to located
# scans within the given scan range of the same type
averageScan = Extensions.AverageScans(self.iRawDataPlus, scans,
options)
len_data = averageScan.SegmentedScan.Positions.Length
mz_list = list(averageScan.SegmentedScan.Positions)
abund_list = list(averageScan.SegmentedScan.Intensities)
data_dict = {
Labels.mz: mz_list,
Labels.abundance: abund_list,
}
mass_spec = MassSpecProfile(data_dict,
d_params,
auto_process=auto_process)
return mass_spec
def GetAverageSpectrum(rawFile, firstScanNumber: int, lastScanNumber: int,
outputData: bool):
# Create the mass options object that will be used when averaging the scans
options = MassOptions()
options.ToleranceUnits = ToleranceUnits.ppm
options.Tolerance = 5.0
# Get the scan filter for the first scan. This scan filter will be used to located
# scans within the given scan range of the same type
scanFilter = rawFile.GetFilterForScanNumber(firstScanNumber)
print(scanFilter.ScanMode)
# Get the average mass spectrum for the provided scan range. In addition to getting the
# average scan using a scan range, the library also provides a similar method that takes
# a time range.
averageScan = Extensions.AverageScansInScanRange(rawFile, firstScanNumber,
lastScanNumber,
scanFilter, options)
#average= ScanAveragerFactory.GetScanAverager(rawFile)
#averageScan = rawFile.AverageScansInScanRange(firstScanNumber, lastScanNumber, scanFilter, options)
if averageScan.HasCentroidStream:
print("Average spectrum ({0} points)".format(
averageScan.CentroidScan.Length))
# Print the spectral data (mass, intensity values)
#if outputData:
# for i in range(averageScan.CentroidScan.Length):
# print(" {}\t{}".format(averageScan.CentroidScan.Masses[i], averageScan.CentroidScan.Intensities[i]))
# This example uses a different method to get the same average spectrum that was calculated in the
# previous portion of this method. Instead of passing the start and end scan, a list of scans will
# be passed to the GetAveragedMassSpectrum function.
scans = List[int]()
for scan in (1, 6, 7, 9, 11, 12, 14):
scans.Add(scan)
averageScan = Extensions.AverageScans(rawFile, scans, options)
len_data = averageScan.SegmentedScan.Positions.Length
mz_list = list(averageScan.SegmentedScan.Positions)
abund_list = list(averageScan.SegmentedScan.Intensities)
#for i in range(len_data):
# mz_list.append(averageScan.SegmentedScan.Positions[i])
# abund_list.append(averageScan.SegmentedScan.Intensities[i])
pyplot.plot(mz_list, abund_list)
#pyplot.show()
centroid_mz_list = []
abundance_mz_list = []
if averageScan.HasCentroidStream:
print("Average spectrum ({0} points)".format(
averageScan.CentroidScan.Length))
# Print the spectral data (mass, intensity values)
if outputData:
for i in range(averageScan.CentroidScan.Length):
centroid_mz_list.append(averageScan.CentroidScan.Masses[i])
averageScan.CentroidScan.Resolutions
abundance_mz_list.append(
averageScan.CentroidScan.Intensities[i])
#print(" {}\t{}".format(averageScan.CentroidScan.Masses[i], averageScan.CentroidScan.Intensities[i]) )
pyplot.plot(centroid_mz_list, abundance_mz_list, linewidth=0, marker='o')
pyplot.show()
print()