PyMacroPTPlugin.MacroPTExperiment

class MacroPTExperiment

Inheritance diagram of PyMacroPTPlugin.MacroPTExperiment

Synopsis

Methods

Note

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Detailed Description

A Macro Assignment Experiment. It holds variables that affects the internal models. They can be changed to calibrated a model.

A Macro Experiment is part of one, and only one, Scenario ( MacroScenario ).

__init__()
execute(taskId)
Parameters:

taskId – str

Return type:

bool

getAlgorithm()
Return type:

str

Algorithm internal name

getCreateParameters()
Return type:

MacroPTExperimentParams

Returns the experiment parameters previously created it they exist. If the current parameters are NULL it initializes new parameters and returns it.

getEngine()
Return type:

str

Engine internal name

getNbThreads()
Return type:

int

Returns the number of threads to be use.

getOutputData()
Return type:

PTExperimentOutputData

getParameters()
Return type:

MacroPTExperimentParams

Returns the experiment parameters previously created or NULL if no parameters have been defined.

getSimulating()
Return type:

bool

getTotalCost()
Return type:

float

iterationsInfo()
Return type:

.list of MacroIterationInfo

setAlgorithm(name)
Parameters:

name – str

Algorithm internal name

setEngine(name)
Parameters:

name – str

Engine internal name

setForest(iForest)
Parameters:

iForestPTForest

setIterationsInfo(iterationsInfo)
Parameters:

iterationsInfo – .list of MacroIterationInfo

setNbThreads(value)
Parameters:

value – int

Sets the number of threads to be use.

setParameters(iParams)
Parameters:

iParamsMacroPTExperimentParams

Sets the experiment parameters

setSimulating(_simulating)
Parameters:

_simulating – bool