ElutionPeakDetection

class pyopenms.ElutionPeakDetection

Bases: object

Cython implementation of _ElutionPeakDetection

Original C++ documentation is available here

– Inherits from [‘ProgressLogger’, ‘DefaultParamHandler’]

__init__()

Overload:

__init__(self) → None

Overload:

__init__(self, in_0: ElutionPeakDetection) → None

Methods

__init__	Overload:
computeApexSNR(self, in_0)	Compute the signal to noise ratio at the apex (estimated by computeMassTraceNoise)
computeMassTraceNoise(self, in_0)	Compute noise level (as RMSE of the actual signal and the smoothed signal)
computeMassTraceSNR(self, in_0)	Compute the signal to noise ratio (estimated by computeMassTraceNoise)
detectPeaks	Overload:
endProgress(self)	Ends the progress display
filterByPeakWidth(self, in_, out)
findLocalExtrema(self, in_0, in_1, in_2, in_3)
getDefaults(self)	Returns the default parameters
getLogType(self)	Returns the type of progress log being used
getName(self)	Returns the name
getParameters(self)	Returns the parameters
getSubsections(self)
nextProgress(self)	Increment progress by 1 (according to range begin-end)
setLogType(self, in_0)	Sets the progress log that should be used.
setName(self, in_0)	Sets the name
setParameters(self, param)	Sets the parameters
setProgress(self, value)	Sets the current progress
smoothData(self, mt, win_size)
startProgress(self, begin, end, label)

computeApexSNR(self, in_0: Kernel_MassTrace) → float

Compute the signal to noise ratio at the apex (estimated by computeMassTraceNoise)

computeMassTraceNoise(self, in_0: Kernel_MassTrace) → float

Compute noise level (as RMSE of the actual signal and the smoothed signal)

computeMassTraceSNR(self, in_0: Kernel_MassTrace) → float

Compute the signal to noise ratio (estimated by computeMassTraceNoise)

detectPeaks()

Overload:

detectPeaks(self, in_: Kernel_MassTrace, out: List[Kernel_MassTrace]) → None

Overload:

detectPeaks(self, in_: List[Kernel_MassTrace], out: List[Kernel_MassTrace]) → None

endProgress(self) → None

Ends the progress display

filterByPeakWidth(self, in_: List[Kernel_MassTrace], out: List[Kernel_MassTrace]) → None

findLocalExtrema(self, in_0: Kernel_MassTrace, in_1: int, in_2: List[int], in_3: List[int]) → None

getDefaults(self) → Param

Returns the default parameters

getLogType(self) → int

Returns the type of progress log being used

getName(self) → Union[bytes, str, String]

Returns the name

getParameters(self) → Param

Returns the parameters

getSubsections(self) → List[bytes]

nextProgress(self) → None

Increment progress by 1 (according to range begin-end)

setLogType(self, in_0: int) → None

Sets the progress log that should be used. The default type is NONE!

setName(self, in_0: Union[bytes, str, String]) → None

Sets the name

setParameters(self, param: Param) → None

Sets the parameters

setProgress(self, value: int) → None

Sets the current progress

smoothData(self, mt: Kernel_MassTrace, win_size: int) → None

startProgress(self, begin: int, end: int, label: Union[bytes, str, String]) → None