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
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