OptimizePick

class pyopenms.OptimizePick

Bases: object

Cython implementation of _OptimizePick

Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS_1_1OptimizePick.html

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__()

  • Cython signature: void OptimizePick()

  • Cython signature: void OptimizePick(OptimizePick &)

  • Cython signature: void OptimizePick(OptimizationFunctions_PenaltyFactors penalties_, int max_iteration_)

Methods

__init__

  • Cython signature: void OptimizePick()

getNumberIterations

Cython signature: unsigned int getNumberIterations() Returns the number of iterations

getPenalties

Cython signature: OptimizationFunctions_PenaltyFactors getPenalties() Returns the penalty factors

setNumberIterations

Cython signature: void setNumberIterations(int max_iteration) Sets the number of iterations

setPenalties

Cython signature: void setPenalties(OptimizationFunctions_PenaltyFactors penalties) Sets the penalty factors
getNumberIterations()

Cython signature: unsigned int getNumberIterations() Returns the number of iterations

getPenalties()

Cython signature: OptimizationFunctions_PenaltyFactors getPenalties() Returns the penalty factors

setNumberIterations()

Cython signature: void setNumberIterations(int max_iteration) Sets the number of iterations

setPenalties()

Cython signature: void setPenalties(OptimizationFunctions_PenaltyFactors penalties) Sets the penalty factors