FIAMSDataProcessor

class pyopenms.FIAMSDataProcessor

Bases: object

Cython implementation of _FIAMSDataProcessor

Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS_1_1FIAMSDataProcessor.html

– Inherits from [‘DefaultParamHandler’]

ADD PYTHON DOCUMENTATION HERE

__init__()
  • Cython signature: void FIAMSDataProcessor() Data processing for FIA-MS data

  • Cython signature: void FIAMSDataProcessor(FIAMSDataProcessor &)

Methods

__init__

  • Cython signature: void FIAMSDataProcessor()

convertToFeatureMap

Cython signature: FeatureMap convertToFeatureMap(MSSpectrum & input_)

extractPeaks

Cython signature: MSSpectrum extractPeaks(MSSpectrum & input_)

getDefaults

Cython signature: Param getDefaults() Returns the default parameters

getName

Cython signature: String getName() Returns the name

getParameters

Cython signature: Param getParameters() Returns the parameters

getSubsections

Cython signature: libcpp_vector[String] getSubsections()

run

Cython signature: bool run(MSExperiment & experiment, float & n_seconds, MzTab & output, bool load_cached_spectrum)

setName

Cython signature: void setName(const String &) Sets the name

setParameters

Cython signature: void setParameters(Param & param) Sets the parameters

trackNoise

Cython signature: MSSpectrum trackNoise(MSSpectrum & input_)

convertToFeatureMap()

Cython signature: FeatureMap convertToFeatureMap(MSSpectrum & input_)

Parameters

input – Input a picked spectrum

Returns

A feature map with the peaks converted to features and polarity from the parameters

Parameters

input – Input a picked spectrum

Returns

A spectrum object storing logSN information

extractPeaks()

Cython signature: MSSpectrum extractPeaks(MSSpectrum & input_)

Parameters

input – Input vector of spectra

Returns

A spectrum with picked peaks

Parameters

input – Input a picked spectrum

Returns

A feature map with the peaks converted to features and polarity from the parameters

Parameters

input – Input a picked spectrum

Returns

A spectrum object storing logSN information

getDefaults()

Cython signature: Param getDefaults() Returns the default parameters

getName()

Cython signature: String getName() Returns the name

getParameters()

Cython signature: Param getParameters() Returns the parameters

getSubsections()

Cython signature: libcpp_vector[String] getSubsections()

run()

Cython signature: bool run(MSExperiment & experiment, float & n_seconds, MzTab & output, bool load_cached_spectrum)

The workflow steps are: - the time axis of the experiment is cut to the interval from 0 to n_seconds - the spectra are summed into one along the time axis with the bin size determined by mz and instrument resolution - data is smoothed by applying the Savitzky-Golay filter - peaks are picked - the accurate mass search for all the picked peaks is performed

setName()

Cython signature: void setName(const String &) Sets the name

setParameters()

Cython signature: void setParameters(Param & param) Sets the parameters

trackNoise()

Cython signature: MSSpectrum trackNoise(MSSpectrum & input_)

Parameters

input – Input a picked spectrum

Returns

A spectrum object storing logSN information