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
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)
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 #
- getLogType(self) int #
Returns the type of progress log being used
- 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!
- setProgress(self, value: int) None #
Sets the current progress
- smoothData(self, mt: Kernel_MassTrace, win_size: int) None #