OptimizePeakDeconvolution#

class pyopenms.OptimizePeakDeconvolution#

Bases: object

Cython implementation of _OptimizePeakDeconvolution

Original C++ documentation is available here: – Inherits from [‘DefaultParamHandler’]

__init__()#

Overload:

__init__(self) → None

Overload:

__init__(self, in_0: OptimizePeakDeconvolution) → None

Methods

`__init__`	Overload:
`getCharge`(self)	Returns the charge
`getDefaults`(self)	Returns the default parameters
`getName`(self)	Returns the name
`getNumberOfPeaks_`(self, charge, temp_shapes, ...)
`getParameters`(self)	Returns the parameters
`getPenalties`(self)	Returns the penalty parameter
`getSubsections`(self)
`optimize`(self, peaks, data)	Performs a nonlinear optimization of the peaks that belong to the current isotope pattern
`setCharge`(self, charge)	Sets the charge
`setName`(self, in_0)	Sets the name
`setParameters`(self, param)	Sets the parameters
`setPenalties`(self, penalties)	Sets the penalty parameter

getCharge(self) → int#: Returns the charge

getDefaults(self) → Param#: Returns the default parameters

getName(self) → bytes | str | String#: Returns the name

getNumberOfPeaks_(self, charge: int, temp_shapes: List[PeakShape], data: OptimizePeakDeconvolution_Data) → int#

getParameters(self) → Param#: Returns the parameters

getPenalties(self) → PenaltyFactorsIntensity#: Returns the penalty parameter

getSubsections(self) → List[bytes]#

optimize(self, peaks: List[PeakShape], data: OptimizePeakDeconvolution_Data) → bool#: Performs a nonlinear optimization of the peaks that belong to the current isotope pattern

setCharge(self, charge: int) → None#: Sets the charge

setName(self, in_0: bytes | str | String) → None#: Sets the name

setParameters(self, param: Param) → None#: Sets the parameters

setPenalties(self, penalties: PenaltyFactorsIntensity) → None#: Sets the penalty parameter