OptimizePick

class pyopenms.OptimizePick

Bases: object

Cython implementation of _OptimizePick

Original C++ documentation is available here

This class provides the non-linear optimization of the peak parameters

Given a vector of peak shapes, this class optimizes all peak shapes parameters using a non-linear optimization For the non-linear optimization we use the Levenberg-Marquardt algorithm provided by the Eigen

__init__()

Overload:

__init__(self) → None

Overload:

__init__(self, in_0: OptimizePick) → None

Overload:

__init__(self, penalties_: OptimizationFunctions_PenaltyFactors, max_iteration_: int) → None

Methods

__init__	Overload:
getNumberIterations(self)	Returns the number of iterations
getPenalties(self)	Returns the penalty factors
setNumberIterations(self, max_iteration)	Sets the number of iterations
setPenalties(self, penalties)	Sets the penalty factors

getNumberIterations(self) → int

Returns the number of iterations

getPenalties(self) → OptimizationFunctions_PenaltyFactors

Returns the penalty factors

setNumberIterations(self, max_iteration: int) → None

Sets the number of iterations

setPenalties(self, penalties: OptimizationFunctions_PenaltyFactors) → None

Sets the penalty factors