OfflinePrecursorIonSelection

class pyopenms.OfflinePrecursorIonSelection

Bases: object

Cython implementation of _OfflinePrecursorIonSelection

Original C++ documentation is available here

– Inherits from [‘DefaultParamHandler’]

__init__()

Overload:

__init__(self) → None

Overload:

__init__(self, in_0: OfflinePrecursorIonSelection) → None

Methods

__init__	Overload:
createProteinSequenceBasedLPInclusionList(...)
getDefaults(self)	Returns the default parameters
getLPSolver(self)
getName(self)	Returns the name
getParameters(self)	Returns the parameters
getSubsections(self)
makePrecursorSelectionForKnownLCMSMap(self, ...)	Makes the precursor selection for a given feature map, either feature or scan based
setLPSolver(self, solver)
setName(self, in_0)	Sets the name
setParameters(self, param)	Sets the parameters

createProteinSequenceBasedLPInclusionList(self, include_: bytes | str | String, rt_model_file: bytes | str | String, pt_model_file: bytes | str | String, precursors: FeatureMap) → None

getDefaults(self) → Param

Returns the default parameters

getLPSolver(self) → int

getName(self) → bytes | str | String

Returns the name

getParameters(self) → Param

Returns the parameters

getSubsections(self) → List[bytes]

makePrecursorSelectionForKnownLCMSMap(self, features: FeatureMap, experiment: MSExperiment, ms2: MSExperiment, charges_set: Set[int], feature_based: bool) → None

Makes the precursor selection for a given feature map, either feature or scan based

Parameters:

• features – Input feature map

• experiment – Input raw data

• ms2 – Precursors are added as empty MS2 spectra to this MSExperiment

• charges_set – Allowed charge states

• feature_based – If true the selection is feature based, if false it is scan based and the highest signals in each spectrum are chosen

setLPSolver(self, solver: int) → None

setName(self, in_0: bytes | str | String) → None

Sets the name

setParameters(self, param: Param) → None

Sets the parameters