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PLearn::Object Class Reference

The Object class. More...

#include <Object.h>

Inheritance diagram for PLearn::Object:

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List of all members.

Public Types

typedef Object inherited

Public Member Functions

virtual string classname () const
virtual OptionList & getOptionList () const
virtual Object * deepCopy (CopiesMap &copies) const
 Object ()
 SUBCLASS WRITING Note: all subclasses should define a default constructor (one that can be called without arguments), whose main role is to give a reasonable default value to all build options (see declareOptions).

virtual void build ()
 Should call simply inherited::build(), then this class's build_().

virtual void makeDeepCopyFromShallowCopy (CopiesMap &copies)
virtual string info () const
 returns a bit more informative string about object (default returns classname())

virtual void print (ostream &out) const
void readOptionVal (PStream &in, const string &optionname)
 Reads and sets the value for the specified option from the specified stream.

void writeOptionVal (PStream &out, const string &optionname) const
 Writes the value of the specified option to the specified stream.

virtual string getOptionsToSave () const
 returns a string of the names of all options to save (optionnames are to be separated by a space, and must be supported by writeOptionVal)

void newwrite (PStream &out) const
 Serializes this object in the new format Classname(optionname=optionval; optionname=optionval; ...).

void newread (PStream &in)
 reads and builds an object in the new format Classname(optionname=optionval; optionname=optionval; ...)

void setOption (const string &optionname, const string &value)
string getOption (const string &optionname) const
virtual void changeOptions (const map< string, string > &name_value)
void changeOption (const string &optionname, const string &value)
 Non-virtual method calls virtual changeOptions.

virtual void write (ostream &out) const
virtual void read (istream &in)
virtual void call (const string &methodname, int nargs, PStream &in_parameters, PStream &out_results)
 The call method is the standard way to allow for remote method invocation on instances of your class.

virtual void run ()
 Overload this for runnable objects (default method issues a runtime error) Runnable objects are objects that can be used as *THE* object of a .plearn script.

virtual void oldread (istream &in)
 DEPRECATED For backward compatibility with old saved object.

virtual void save (const string &filename) const
 This method is deprecated.

virtual void load (const string &filename)
 This method is deprecated.

virtual ~Object ()

Static Public Member Functions

string _classname_ ()
OptionList & _getOptionList_ ()
Object * _new_instance_for_typemap_ ()
bool _isa_ (Object *o)
void _static_initialize_ ()

Static Public Attributes

StaticInitializer _static_initializer_

Protected Member Functions

void prepareToSendResults (PStream &out, int nres)

Static Protected Member Functions

void declareOptions (OptionList &ol)
 redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down)


Private Member Functions

void build_ ()

Detailed Description

The Object class.

Definition at line 349 of file Object.h.

Member Typedef Documentation

typedef Object PLearn::Object::inherited
 

Reimplemented in PLearn::RealMapping, PLearn::SetOption, PLearn::SDBVMatrix, PLearn::UCISpecification, PLearn::AdditiveNormalizationKernel, PLearn::ClassDistanceProportionCostFunction, PLearn::ClassErrorCostFunction, PLearn::ClassMarginCostFunction, PLearn::CompactVMatrixGaussianKernel, PLearn::CompactVMatrixPolynomialKernel, PLearn::ConvexBasisKernel, PLearn::DifferenceKernel, PLearn::DirectNegativeCostFunction, PLearn::DistanceKernel, PLearn::DivisiveNormalizationKernel, PLearn::DotProductKernel, PLearn::GaussianDensityKernel, PLearn::GaussianKernel, PLearn::GeneralizedDistanceRBFKernel, PLearn::GeodesicDistanceKernel, PLearn::Kernel, PLearn::LaplacianKernel, PLearn::LiftBinaryCostFunction, PLearn::LLEKernel, PLearn::LogOfGaussianDensityKernel, PLearn::MulticlassErrorCostFunction, PLearn::NegKernel, PLearn::NegLogProbCostFunction, PLearn::NegOutputCostFunction, PLearn::NormalizedDotProductKernel, PLearn::PolynomialKernel, PLearn::PowDistanceKernel, PLearn::PrecomputedKernel, PLearn::PricingTransactionPairProfitFunction, PLearn::QuadraticUtilityCostFunction, PLearn::ReconstructionWeightsKernel, PLearn::ScaledGaussianKernel, PLearn::ScaledGeneralizedDistanceRBFKernel, PLearn::ScaledLaplacianKernel, PLearn::SelectedOutputCostFunction, PLearn::SigmoidalKernel, PLearn::SigmoidPrimitiveKernel, PLearn::SourceKernel, PLearn::SquaredErrorCostFunction, PLearn::WeightedCostFunction, PLearn::Binner, PLearn::ConditionalCDFSmoother, PLearn::ConditionalStatsCollector, PLearn::LiftStatsCollector, PLearn::LimitedGaussianSmoother, PLearn::ManualBinner, PLearn::ScaledConditionalCDFSmoother, PLearn::Smoother, PLearn::StatsCollector, PLearn::StatsCollector, PLearn::StatsIterator, PLearn::MeanStatsIterator, PLearn::ExpMeanStatsIterator, PLearn::StddevStatsIterator, PLearn::StderrStatsIterator, PLearn::SharpeRatioStatsIterator, PLearn::MinStatsIterator, PLearn::MaxStatsIterator, PLearn::LiftStatsIterator, PLearn::QuantilesStatsIterator, PLearn::VecStatsCollector, PLearn::NearestNeighborPredictionCost, PLearn::ObjectGenerator, PLearn::RunObject, PLearn::ShellScript, PLearn::AdaptGradientOptimizer, PLearn::ConjGradientOptimizer, PLearn::GradientOptimizer, PLearn::HyperOptimizer, PLearn::HSetVal, PLearn::HTryAll, PLearn::HCoordinateDescent, PLearn::HTryCombinations, PLearn::Optimizer, PLearn::AbsVariable, PLearn::AffineTransformVariable, PLearn::AffineTransformWeightPenalty, PLearn::ArgmaxVariable, PLearn::ArgminVariable, PLearn::BinaryClassificationLossVariable, PLearn::BinaryVariable, PLearn::ClassificationLossVariable, PLearn::ColumnIndexVariable, PLearn::ColumnSumVariable, PLearn::ConcatColumnsVariable, PLearn::ConcatOfVariable, PLearn::ConcatRowsVariable, PLearn::ConvolveVariable, PLearn::CrossEntropyVariable, PLearn::CutAboveThresholdVariable, PLearn::CutBelowThresholdVariable, PLearn::DeterminantVariable, PLearn::DiagonalizedFactorsProductVariable, PLearn::DilogarithmVariable, PLearn::DivVariable, PLearn::DotProductVariable, PLearn::DuplicateColumnVariable, PLearn::DuplicateRowVariable, PLearn::DuplicateScalarVariable, PLearn::ElementAtPositionVariable, PLearn::EqualConstantVariable, PLearn::EqualScalarVariable, PLearn::EqualVariable, PLearn::ErfVariable, PLearn::ExpVariable, PLearn::ExtendedVariable, PLearn::Function, PLearn::HardSlopeVariable, PLearn::IfThenElseVariable, PLearn::IndexAtPositionVariable, PLearn::InterValuesVariable, PLearn::InvertElementsVariable, PLearn::IsAboveThresholdVariable, PLearn::IsLargerVariable, PLearn::IsMissingVariable, PLearn::IsSmallerVariable, PLearn::LeftPseudoInverseVariable, PLearn::LiftOutputVariable, PLearn::LogAddVariable, PLearn::LogSoftmaxVariable, PLearn::LogSumVariable, PLearn::LogVariable, PLearn::MarginPerceptronCostVariable, PLearn::MatrixAffineTransformFeedbackVariable, PLearn::MatrixAffineTransformVariable, PLearn::MatrixElementsVariable, PLearn::MatrixInverseVariable, PLearn::MatrixOneHotSquaredLoss, PLearn::MatrixSoftmaxLossVariable, PLearn::MatrixSoftmaxVariable, PLearn::MatrixSumOfVariable, PLearn::MatRowVariable, PLearn::Max2Variable, PLearn::MaxVariable, PLearn::MiniBatchClassificationLossVariable, PLearn::MinusColumnVariable, PLearn::MinusRowVariable, PLearn::MinusScalarVariable, PLearn::MinusTransposedColumnVariable, PLearn::MinusVariable, PLearn::MinVariable, PLearn::MulticlassLossVariable, PLearn::NaryVariable, PLearn::NegateElementsVariable, PLearn::NegCrossEntropySigmoidVariable, PLearn::NllSemisphericalGaussianVariable, PLearn::OneHotSquaredLoss, PLearn::OneHotVariable, PLearn::PDistributionVariable, PLearn::PLogPVariable, PLearn::PlusColumnVariable, PLearn::PlusConstantVariable, PLearn::PlusRowVariable, PLearn::PlusScalarVariable, PLearn::PlusVariable, PLearn::PowVariable, PLearn::PowVariableVariable, PLearn::ProductTransposeVariable, PLearn::ProductVariable, PLearn::ProjectionErrorVariable, PLearn::ReshapeVariable, PLearn::RightPseudoInverseVariable, PLearn::RowAtPositionVariable, PLearn::RowSumVariable, PLearn::SemiSupervisedProbClassCostVariable, PLearn::SigmoidVariable, PLearn::SignVariable, PLearn::SoftmaxLossVariable, PLearn::SoftmaxVariable, PLearn::SoftplusVariable, PLearn::SoftSlopeIntegralVariable, PLearn::SoftSlopeVariable, PLearn::SourceVariable, PLearn::SquareRootVariable, PLearn::SquareVariable, PLearn::SubMatTransposeVariable, PLearn::SubMatVariable, PLearn::SubsampleVariable, PLearn::SumAbsVariable, PLearn::SumOfVariable, PLearn::SumOverBagsVariable, PLearn::SumSquareVariable, PLearn::SumVariable, PLearn::TanhVariable, PLearn::TimesColumnVariable, PLearn::TimesConstantVariable, PLearn::TimesRowVariable, PLearn::TimesScalarVariable, PLearn::TimesVariable, PLearn::TransposeProductVariable, PLearn::UnaryHardSlopeVariable, PLearn::UnaryVariable, PLearn::UnequalConstantVariable, PLearn::UnfoldedFuncVariable, PLearn::UnfoldedSumOfVariable, PLearn::VarArrayElementVariable, PLearn::VarColumnsVariable, PLearn::VarElementVariable, PLearn::Variable, PLearn::VarRowsVariable, PLearn::VarRowVariable, PLearn::VecElementVariable, PLearn::WeightedSumSquareVariable, PLearn::AsciiVMatrix, PLearn::AutoVMatrix, PLearn::BatchVMatrix, PLearn::BootstrapSplitter, PLearn::BootstrapVMatrix, PLearn::ByteMemoryVMatrix, PLearn::CenteredVMatrix, PLearn::CompactVMatrix, PLearn::CompressedVMatrix, PLearn::ConcatColumnsVMatrix, PLearn::ConcatRowsSubVMatrix, PLearn::ConcatRowsVMatrix, PLearn::CrossReferenceVMatrix, PLearn::CumVMatrix, PLearn::DatedJoinVMatrix, PLearn::DatedVMatrix, PLearn::DBSplitter, PLearn::DiskVMatrix, PLearn::ExplicitSplitter, PLearn::ExtendedVMatrix, PLearn::FileVMatrix, PLearn::FilteredVMatrix, PLearn::FilterSplitter, PLearn::FinancePreprocVMatrix, PLearn::ForwardVMatrix, PLearn::FractionSplitter, PLearn::GeneralizedOneHotVMatrix, PLearn::GetInputVMatrix, PLearn::GramVMatrix, PLearn::IndexedVMatrix, PLearn::InterleaveVMatrix, PLearn::JoinVMatrix, PLearn::JulianizeVMatrix, PLearn::KernelVMatrix, PLearn::KFoldSplitter, PLearn::KNNVMatrix, PLearn::LearnerProcessedVMatrix, PLearn::LocalNeighborsDifferencesVMatrix, PLearn::MemoryVMatrix, PLearn::MovingAverageVMatrix, PLearn::MultiInstanceVMatrix, PLearn::OneHotVMatrix, PLearn::PairsVMatrix, PLearn::PLearnerOutputVMatrix, PLearn::PrecomputedVMatrix, PLearn::ProcessingVMatrix, PLearn::RangeVMatrix, PLearn::RegularGridVMatrix, PLearn::RemapLastColumnVMatrix, PLearn::RemoveDuplicateVMatrix, PLearn::RemoveRowsVMatrix, PLearn::RepeatSplitter, PLearn::RowBufferedVMatrix, PLearn::RowsSubVMatrix, PLearn::SelectColumnsVMatrix, PLearn::SelectRowsFileIndexVMatrix, PLearn::SelectRowsVMatrix, PLearn::SequentialSplitter, PLearn::ShiftAndRescaleVMatrix, PLearn::SortRowsVMatrix, PLearn::SourceVMatrix, PLearn::SourceVMatrixSplitter, PLearn::SparseVMatrix, PLearn::Splitter, PLearn::StrTableVMatrix, PLearn::SubInputVMatrix, PLearn::SubVMatrix, PLearn::TemporalHorizonVMatrix, PLearn::TestInTrainSplitter, PLearn::ThresholdVMatrix, PLearn::ToBagSplitter, PLearn::TrainTestBagsSplitter, PLearn::TrainTestSplitter, PLearn::TrainValidTestSplitter, PLearn::TransposeVMatrix, PLearn::UniformizeVMatrix, PLearn::UniformVMatrix, PLearn::UpsideDownVMatrix, PLearn::VecExtendedVMatrix, PLearn::VMatLanguage, PLearn::PreprocessingVMatrix, PLearn::VMatrix, PLearn::VMatrixFromDistribution, PLearn::VVec, PLearn::VVMatrix, PLearn::YMDDatedVMatrix, PLearn::AdaBoost, PLearn::ClassifierFromDensity, PLearn::MultiInstanceNNet, PLearn::ConditionalDensityNet, PLearn::ConditionalDistribution, PLearn::ConditionalGaussianDistribution, PLearn::Distribution, PLearn::EmpiricalDistribution, PLearn::GaussianDistribution, PLearn::GaussianProcessRegressor, PLearn::GaussMix, PLearn::HistogramDistribution, PLearn::LocallyWeightedDistribution, PLearn::ManifoldParzen2, PLearn::PConditionalDistribution, PLearn::PDistribution, PLearn::SpiralDistribution, PLearn::UnconditionalDistribution, PLearn::UniformDistribution, PLearn::AddCostToLearner, PLearn::EmbeddedLearner, PLearn::Learner, PLearn::NeighborhoodSmoothnessNNet, PLearn::NeuralNet, PLearn::NNet, PLearn::PLearner, PLearn::SelectInputSubsetLearner, PLearn::StackedLearner, PLearn::StatefulLearner, PLearn::TestingLearner, PLearn::GraphicalBiText, PLearn::Dictionary, PLearn::TextSenseSequenceVMatrix, PLearn::Experiment, PLearn::GenerateDecisionPlot, PLearn::Grapher, PLearn::PTester, PLearn::ConstantRegressor, PLearn::LinearRegressor, PLearn::PLS, PLearn::MovingAverage, PLearn::SequentialLearner, PLearn::SequentialModelSelector, PLearn::SequentialValidation, PLearn::PTester, PLearn::TestMethod, PLearn::Train, PLearn::EntropyContrast, PLearn::GaussianContinuum, PLearn::Isomap, PLearn::IsomapTangentLearner, PLearn::KernelPCA, PLearn::KernelProjection, PLearn::KPCATangentLearner, PLearn::LLE, PLearn::PCA, PLearn::SpectralClustering, and PLearn::TangentLearner.

Definition at line 374 of file Object.h.

Constructor & Destructor Documentation

PLearn::Object::Object (   ) 
 

SUBCLASS WRITING Note: all subclasses should define a default constructor (one that can be called without arguments), whose main role is to give a reasonable default value to all build options (see declareOptions).

Completing the actual building of the object is left to the build_() and build() methods (see below).

Definition at line 56 of file Object.cc.

PLearn::Object::~Object (   )  [virtual]
 

Definition at line 336 of file Object.cc.

Member Function Documentation

string PLearn::Object::_classname_ (   )  [static]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

OptionList & PLearn::Object::_getOptionList_ (   )  [static]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

bool PLearn::Object::_isa_ (  Object *  o  )  [static]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

Object * PLearn::Object::_new_instance_for_typemap_ (   )  [static]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

void PLearn::Object::_static_initialize_ (   )  [static]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

void PLearn::Object::build (   )  [virtual]
 

Should call simply inherited::build(), then this class's build_().

This method should be callable again at later times, after modifying some option fields to change the "architecture" of the object.

Reimplemented in PLearn::SetOption, PLearn::UCISpecification, PLearn::AdditiveNormalizationKernel, PLearn::DivisiveNormalizationKernel, PLearn::GaussianKernel, PLearn::GeodesicDistanceKernel, PLearn::Kernel, PLearn::LLEKernel, PLearn::PrecomputedKernel, PLearn::ReconstructionWeightsKernel, PLearn::SourceKernel, PLearn::Binner, PLearn::ConditionalCDFSmoother, PLearn::ConditionalStatsCollector, PLearn::LiftStatsCollector, PLearn::LimitedGaussianSmoother, PLearn::ManualBinner, PLearn::ScaledConditionalCDFSmoother, PLearn::Smoother, PLearn::StatsCollector, PLearn::StatsIterator, PLearn::VecStatsCollector, PLearn::NearestNeighborPredictionCost, PLearn::ObjectGenerator, PLearn::RunObject, PLearn::ShellScript, PLearn::AdaptGradientOptimizer, PLearn::ConjGradientOptimizer, PLearn::GradientOptimizer, PLearn::HTryCombinations, PLearn::Optimizer, PLearn::AffineTransformVariable, PLearn::BinaryClassificationLossVariable, PLearn::ClassificationLossVariable, PLearn::ColumnIndexVariable, PLearn::ConcatColumnsVariable, PLearn::ConcatOfVariable, PLearn::ConcatRowsVariable, PLearn::CrossEntropyVariable, PLearn::DeterminantVariable, PLearn::DiagonalizedFactorsProductVariable, PLearn::DivVariable, PLearn::DotProductVariable, PLearn::DuplicateColumnVariable, PLearn::DuplicateRowVariable, PLearn::DuplicateScalarVariable, PLearn::ElementAtPositionVariable, PLearn::EqualScalarVariable, PLearn::EqualVariable, PLearn::ExtendedVariable, PLearn::Function, PLearn::IfThenElseVariable, PLearn::IndexAtPositionVariable, PLearn::InterValuesVariable, PLearn::IsLargerVariable, PLearn::IsSmallerVariable, PLearn::LeftPseudoInverseVariable, PLearn::LiftOutputVariable, PLearn::LogAddVariable, PLearn::MarginPerceptronCostVariable, PLearn::MatrixElementsVariable, PLearn::MatrixOneHotSquaredLoss, PLearn::MatrixSoftmaxLossVariable, PLearn::MatrixSumOfVariable, PLearn::MatRowVariable, PLearn::Max2Variable, PLearn::MiniBatchClassificationLossVariable, PLearn::MinusColumnVariable, PLearn::MinusRowVariable, PLearn::MinusScalarVariable, PLearn::MinusTransposedColumnVariable, PLearn::MinusVariable, PLearn::MulticlassLossVariable, PLearn::NegCrossEntropySigmoidVariable, PLearn::NllSemisphericalGaussianVariable, PLearn::OneHotSquaredLoss, PLearn::OneHotVariable, PLearn::PDistributionVariable, PLearn::PlusColumnVariable, PLearn::PlusRowVariable, PLearn::PlusScalarVariable, PLearn::PlusVariable, PLearn::PowVariableVariable, PLearn::ProductTransposeVariable, PLearn::ProductVariable, PLearn::ProjectionErrorVariable, PLearn::ReshapeVariable, PLearn::RightPseudoInverseVariable, PLearn::RowAtPositionVariable, PLearn::SemiSupervisedProbClassCostVariable, PLearn::SoftmaxLossVariable, PLearn::SubMatTransposeVariable, PLearn::SubMatVariable, PLearn::SubsampleVariable, PLearn::SumOfVariable, PLearn::SumOverBagsVariable, PLearn::TimesColumnVariable, PLearn::TimesRowVariable, PLearn::TimesScalarVariable, PLearn::TimesVariable, PLearn::TransposeProductVariable, PLearn::UnaryHardSlopeVariable, PLearn::UnfoldedFuncVariable, PLearn::UnfoldedSumOfVariable, PLearn::VarArrayElementVariable, PLearn::VarElementVariable, PLearn::Variable, PLearn::VarRowsVariable, PLearn::VarRowVariable, PLearn::VecElementVariable, PLearn::WeightedSumSquareVariable, PLearn::AsciiVMatrix, PLearn::AutoVMatrix, PLearn::BatchVMatrix, PLearn::BootstrapSplitter, PLearn::BootstrapVMatrix, PLearn::CenteredVMatrix, PLearn::CompactVMatrix, PLearn::ConcatColumnsVMatrix, PLearn::ConcatRowsSubVMatrix, PLearn::ConcatRowsVMatrix, PLearn::CrossReferenceVMatrix, PLearn::CumVMatrix, PLearn::DatedJoinVMatrix, PLearn::DatedVMatrix, PLearn::DBSplitter, PLearn::DiskVMatrix, PLearn::ExplicitSplitter, PLearn::ExtendedVMatrix, PLearn::FileVMatrix, PLearn::FilteredVMatrix, PLearn::FilterSplitter, PLearn::FinancePreprocVMatrix, PLearn::ForwardVMatrix, PLearn::FractionSplitter, PLearn::GeneralizedOneHotVMatrix, PLearn::GetInputVMatrix, PLearn::GramVMatrix, PLearn::IndexedVMatrix, PLearn::InterleaveVMatrix, PLearn::JoinVMatrix, PLearn::JulianizeVMatrix, PLearn::KernelVMatrix, PLearn::KFoldSplitter, PLearn::KNNVMatrix, PLearn::LearnerProcessedVMatrix, PLearn::LocalNeighborsDifferencesVMatrix, PLearn::MemoryVMatrix, PLearn::MovingAverageVMatrix, PLearn::MultiInstanceVMatrix, PLearn::OneHotVMatrix, PLearn::PairsVMatrix, PLearn::PLearnerOutputVMatrix, PLearn::PrecomputedVMatrix, PLearn::ProcessingVMatrix, PLearn::RangeVMatrix, PLearn::RegularGridVMatrix, PLearn::RemapLastColumnVMatrix, PLearn::RemoveDuplicateVMatrix, PLearn::RemoveRowsVMatrix, PLearn::RepeatSplitter, PLearn::RowsSubVMatrix, PLearn::SelectColumnsVMatrix, PLearn::SelectRowsFileIndexVMatrix, PLearn::SelectRowsVMatrix, PLearn::SequentialSplitter, PLearn::ShiftAndRescaleVMatrix, PLearn::SortRowsVMatrix, PLearn::SourceVMatrix, PLearn::SourceVMatrixSplitter, PLearn::SparseVMatrix, PLearn::SubInputVMatrix, PLearn::SubVMatrix, PLearn::TemporalHorizonVMatrix, PLearn::TestInTrainSplitter, PLearn::ToBagSplitter, PLearn::TrainTestBagsSplitter, PLearn::TrainTestSplitter, PLearn::TrainValidTestSplitter, PLearn::TransposeVMatrix, PLearn::UniformizeVMatrix, PLearn::UniformVMatrix, PLearn::UpsideDownVMatrix, PLearn::VecExtendedVMatrix, PLearn::VMatLanguage, PLearn::PreprocessingVMatrix, PLearn::VMatrix, PLearn::VMatrixFromDistribution, PLearn::VVec, PLearn::VVMatrix, PLearn::YMDDatedVMatrix, PLearn::AdaBoost, PLearn::ClassifierFromDensity, PLearn::MultiInstanceNNet, PLearn::ConditionalDensityNet, PLearn::ConditionalGaussianDistribution, PLearn::Distribution, PLearn::GaussianProcessRegressor, PLearn::GaussMix, PLearn::HistogramDistribution, PLearn::LocallyWeightedDistribution, PLearn::ManifoldParzen2, PLearn::PConditionalDistribution, PLearn::PDistribution, PLearn::SpiralDistribution, PLearn::UnconditionalDistribution, PLearn::UniformDistribution, PLearn::AddCostToLearner, PLearn::EmbeddedLearner, PLearn::Learner, PLearn::NeighborhoodSmoothnessNNet, PLearn::NeuralNet, PLearn::NNet, PLearn::PLearner, PLearn::SelectInputSubsetLearner, PLearn::StackedLearner, PLearn::StatefulLearner, PLearn::TestingLearner, PLearn::GraphicalBiText, PLearn::Dictionary, PLearn::TextSenseSequenceVMatrix, PLearn::Experiment, PLearn::GenerateDecisionPlot, PLearn::Grapher, PLearn::PTester, PLearn::ConstantRegressor, PLearn::LinearRegressor, PLearn::PLS, PLearn::EmbeddedSequentialLearner, PLearn::MovingAverage, PLearn::SequentialLearner, PLearn::SequentialModelSelector, PLearn::SequentialValidation, PLearn::PTester, PLearn::TestMethod, PLearn::Train, PLearn::EntropyContrast, PLearn::GaussianContinuum, PLearn::Isomap, PLearn::IsomapTangentLearner, PLearn::KernelPCA, PLearn::KernelProjection, PLearn::KPCATangentLearner, PLearn::LLE, PLearn::PCA, PLearn::SpectralClustering, and PLearn::TangentLearner.

Definition at line 105 of file Object.cc.

Referenced by PLearn::loadObject(), PLearn::macroLoadObject(), and newread().

void PLearn::Object::build_ (   )  [private]
 

This method should be redefined in subclasses and do the actual building of the object according to previously set option fields. Constructors can just set option fields, and then call build_. This method is NOT virtual, and will typically be called only from three places: a constructor, the public virtual build() method, and possibly the public virtual read method (which calls its parent's read). build_() can assume that it's parent's build_ has already been called.

Reimplemented in PLearn::SetOption, PLearn::UCISpecification, PLearn::AdditiveNormalizationKernel, PLearn::DivisiveNormalizationKernel, PLearn::GaussianKernel, PLearn::GeodesicDistanceKernel, PLearn::Kernel, PLearn::LLEKernel, PLearn::PrecomputedKernel, PLearn::ReconstructionWeightsKernel, PLearn::SourceKernel, PLearn::Binner, PLearn::ConditionalCDFSmoother, PLearn::ConditionalStatsCollector, PLearn::LiftStatsCollector, PLearn::LimitedGaussianSmoother, PLearn::ManualBinner, PLearn::ScaledConditionalCDFSmoother, PLearn::Smoother, PLearn::StatsCollector, PLearn::VecStatsCollector, PLearn::NearestNeighborPredictionCost, PLearn::ObjectGenerator, PLearn::RunObject, PLearn::ShellScript, PLearn::AdaptGradientOptimizer, PLearn::ConjGradientOptimizer, PLearn::GradientOptimizer, PLearn::Optimizer, PLearn::AffineTransformVariable, PLearn::BinaryClassificationLossVariable, PLearn::ClassificationLossVariable, PLearn::ColumnIndexVariable, PLearn::ConcatColumnsVariable, PLearn::ConcatOfVariable, PLearn::ConcatRowsVariable, PLearn::CrossEntropyVariable, PLearn::DeterminantVariable, PLearn::DiagonalizedFactorsProductVariable, PLearn::DivVariable, PLearn::DotProductVariable, PLearn::DuplicateColumnVariable, PLearn::DuplicateRowVariable, PLearn::DuplicateScalarVariable, PLearn::ElementAtPositionVariable, PLearn::EqualScalarVariable, PLearn::EqualVariable, PLearn::ExtendedVariable, PLearn::Function, PLearn::IfThenElseVariable, PLearn::IndexAtPositionVariable, PLearn::InterValuesVariable, PLearn::IsLargerVariable, PLearn::IsSmallerVariable, PLearn::LeftPseudoInverseVariable, PLearn::LiftOutputVariable, PLearn::LogAddVariable, PLearn::MarginPerceptronCostVariable, PLearn::MatrixElementsVariable, PLearn::MatrixOneHotSquaredLoss, PLearn::MatrixSoftmaxLossVariable, PLearn::MatrixSumOfVariable, PLearn::MatRowVariable, PLearn::Max2Variable, PLearn::MiniBatchClassificationLossVariable, PLearn::MinusColumnVariable, PLearn::MinusRowVariable, PLearn::MinusScalarVariable, PLearn::MinusTransposedColumnVariable, PLearn::MinusVariable, PLearn::MulticlassLossVariable, PLearn::NegCrossEntropySigmoidVariable, PLearn::NllSemisphericalGaussianVariable, PLearn::OneHotSquaredLoss, PLearn::OneHotVariable, PLearn::PDistributionVariable, PLearn::PlusColumnVariable, PLearn::PlusRowVariable, PLearn::PlusScalarVariable, PLearn::PlusVariable, PLearn::PowVariableVariable, PLearn::ProductTransposeVariable, PLearn::ProductVariable, PLearn::ProjectionErrorVariable, PLearn::ReshapeVariable, PLearn::RightPseudoInverseVariable, PLearn::RowAtPositionVariable, PLearn::SemiSupervisedProbClassCostVariable, PLearn::SoftmaxLossVariable, PLearn::SubMatTransposeVariable, PLearn::SubMatVariable, PLearn::SubsampleVariable, PLearn::SumOfVariable, PLearn::SumOverBagsVariable, PLearn::TimesColumnVariable, PLearn::TimesRowVariable, PLearn::TimesScalarVariable, PLearn::TimesVariable, PLearn::TransposeProductVariable, PLearn::UnaryHardSlopeVariable, PLearn::UnfoldedFuncVariable, PLearn::UnfoldedSumOfVariable, PLearn::VarArrayElementVariable, PLearn::VarElementVariable, PLearn::Variable, PLearn::VarRowsVariable, PLearn::VarRowVariable, PLearn::VecElementVariable, PLearn::WeightedSumSquareVariable, PLearn::AsciiVMatrix, PLearn::AutoVMatrix, PLearn::BatchVMatrix, PLearn::BootstrapSplitter, PLearn::BootstrapVMatrix, PLearn::CenteredVMatrix, PLearn::ConcatColumnsVMatrix, PLearn::ConcatRowsSubVMatrix, PLearn::ConcatRowsVMatrix, PLearn::CrossReferenceVMatrix, PLearn::CumVMatrix, PLearn::DatedJoinVMatrix, PLearn::DatedVMatrix, PLearn::DBSplitter, PLearn::DiskVMatrix, PLearn::ExplicitSplitter, PLearn::ExtendedVMatrix, PLearn::FileVMatrix, PLearn::FilteredVMatrix, PLearn::FilterSplitter, PLearn::FinancePreprocVMatrix, PLearn::ForwardVMatrix, PLearn::FractionSplitter, PLearn::GeneralizedOneHotVMatrix, PLearn::GetInputVMatrix, PLearn::GramVMatrix, PLearn::IndexedVMatrix, PLearn::InterleaveVMatrix, PLearn::JoinVMatrix, PLearn::JulianizeVMatrix, PLearn::KernelVMatrix, PLearn::KFoldSplitter, PLearn::KNNVMatrix, PLearn::LearnerProcessedVMatrix, PLearn::LocalNeighborsDifferencesVMatrix, PLearn::MemoryVMatrix, PLearn::MovingAverageVMatrix, PLearn::MultiInstanceVMatrix, PLearn::OneHotVMatrix, PLearn::PairsVMatrix, PLearn::PLearnerOutputVMatrix, PLearn::PrecomputedVMatrix, PLearn::ProcessingVMatrix, PLearn::RangeVMatrix, PLearn::RegularGridVMatrix, PLearn::RemapLastColumnVMatrix, PLearn::RemoveDuplicateVMatrix, PLearn::RemoveRowsVMatrix, PLearn::RepeatSplitter, PLearn::RowsSubVMatrix, PLearn::SelectColumnsVMatrix, PLearn::SelectRowsFileIndexVMatrix, PLearn::SelectRowsVMatrix, PLearn::SequentialSplitter, PLearn::ShiftAndRescaleVMatrix, PLearn::SortRowsVMatrix, PLearn::SourceVMatrix, PLearn::SourceVMatrixSplitter, PLearn::SparseVMatrix, PLearn::SubInputVMatrix, PLearn::SubVMatrix, PLearn::TemporalHorizonVMatrix, PLearn::TestInTrainSplitter, PLearn::ToBagSplitter, PLearn::TrainTestBagsSplitter, PLearn::TrainTestSplitter, PLearn::TrainValidTestSplitter, PLearn::TransposeVMatrix, PLearn::UniformizeVMatrix, PLearn::UniformVMatrix, PLearn::UpsideDownVMatrix, PLearn::VecExtendedVMatrix, PLearn::VMatLanguage, PLearn::PreprocessingVMatrix, PLearn::VMatrix, PLearn::VMatrixFromDistribution, PLearn::VVec, PLearn::VVMatrix, PLearn::YMDDatedVMatrix, PLearn::AdaBoost, PLearn::ClassifierFromDensity, PLearn::MultiInstanceNNet, PLearn::ConditionalDensityNet, PLearn::Distribution, PLearn::GaussianProcessRegressor, PLearn::GaussMix, PLearn::HistogramDistribution, PLearn::LocallyWeightedDistribution, PLearn::ManifoldParzen2, PLearn::PConditionalDistribution, PLearn::PDistribution, PLearn::SpiralDistribution, PLearn::UnconditionalDistribution, PLearn::UniformDistribution, PLearn::AddCostToLearner, PLearn::EmbeddedLearner, PLearn::Learner, PLearn::NeighborhoodSmoothnessNNet, PLearn::NeuralNet, PLearn::NNet, PLearn::PLearner, PLearn::SelectInputSubsetLearner, PLearn::StackedLearner, PLearn::StatefulLearner, PLearn::TestingLearner, PLearn::GraphicalBiText, PLearn::Dictionary, PLearn::TextSenseSequenceVMatrix, PLearn::Experiment, PLearn::GenerateDecisionPlot, PLearn::Grapher, PLearn::PTester, PLearn::ConstantRegressor, PLearn::LinearRegressor, PLearn::PLS, PLearn::EmbeddedSequentialLearner, PLearn::MovingAverage, PLearn::SequentialLearner, PLearn::SequentialModelSelector, PLearn::SequentialValidation, PLearn::PTester, PLearn::TestMethod, PLearn::Train, PLearn::EntropyContrast, PLearn::GaussianContinuum, PLearn::Isomap, PLearn::IsomapTangentLearner, PLearn::KernelPCA, PLearn::KernelProjection, PLearn::KPCATangentLearner, PLearn::LLE, PLearn::PCA, PLearn::SpectralClustering, and PLearn::TangentLearner.

Definition at line 102 of file Object.cc.

void PLearn::Object::call (  const string &  methodname,
int  nargs,
PStream &  in_parameters,
PStream &  out_results
)  [virtual]
 

The call method is the standard way to allow for remote method invocation on instances of your class.

This should result in reading nargs input parameters from in_parameters, call the appropriate method, and send results to out_results. A "Remote-callable method" is typically associated with an actual methods of your class, but it will usually differ in its "calling" conventions: its "name", number or input arguments, and number and nature of output results may differ.

Here is what such a method should do: 1) Determine from the methodname what actual method to call. If the given methodname is none of those supported by your call method, call the parent's "call" Ex: inherited::call(methodname, nargs, in_parameters, out_results) 2) The number of arguments nargs may also influence what version of the method you want to call 3) read the narg arguments from in_parameters Ex: in_parameters >> age >> length >> n; 4) call the actual associated method 5) call prepareToSendResults(out_results, nres) where nres is the number of result parameters. 6) send the nres result parameters to out_results Ex: out_results << res1 << res2 <<res3; 7) call out_results.flush()

If anything goes wrong during the process (bad arguments, etc...) simply call PLERROR with a meaningful message.

Definition at line 319 of file Object.cc.

References PLERROR.

void PLearn::Object::changeOption (  const string &  optionname,
const string &  value
) 
 

Non-virtual method calls virtual changeOptions.

Definition at line 95 of file Object.cc.

References changeOptions().

void PLearn::Object::changeOptions (  const map< string, string > &  name_value  )  [virtual]
 

This method should be used, rather than setOption, when modifying some options of an already built object. Default version simply calls setOption, but subclasses should override it to execute any code required to put the object in a consistent state. If the set of options would put the object in an inconsistent state, a runtime error should be issued.

Definition at line 84 of file Object.cc.

References setOption().

Referenced by changeOption().

string PLearn::Object::classname (   )  const [virtual]
 

Reimplemented in PLearn::RealMapping, PLearn::SetOption, PLearn::SourceSampleVariable, PLearn::UnarySampleVariable, PLearn::BinarySampleVariable, PLearn::UniformSampleVariable, PLearn::MultinomialSampleVariable, and PLearn::DiagonalNormalSampleVariable.

Definition at line 59 of file Object.cc.

Referenced by PLearn::Kernel::apply(), PLearn::Learner::basename(), PLearn::Variable::bbprop(), PLearn::Kernel::computeGramMatrix(), PLearn::VMatrix::deleteStringMapping(), PLearn::VMatrix::get(), info(), PLearn::VMatrix::loadAllStringMappings(), newread(), newwrite(), PLearn::NaryVariable::printInfo(), readOptionVal(), PLearn::Variable::rfprop(), PLearn::Variable::setParents(), and PLearn::Variable::symbolicBprop().

void PLearn::Object::declareOptions (  OptionList &  ol  )  [inline, static, protected]
 

redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down)

ex: static void declareOptions(OptionList& ol) { declareOption(ol, "inputsize", &MyObject::inputsize_, OptionBase::buildoption, "the size of the input\n it must be provided"); declareOption(ol, "weights", &MyObject::weights, OptionBase::learntoption, "the learnt model weights"); inherited::declareOptions(ol); }

Reimplemented in PLearn::RealMapping, PLearn::SetOption, PLearn::UCISpecification, PLearn::AdditiveNormalizationKernel, PLearn::ClassErrorCostFunction, PLearn::ClassMarginCostFunction, PLearn::CompactVMatrixGaussianKernel, PLearn::CompactVMatrixPolynomialKernel, PLearn::ConvexBasisKernel, PLearn::DistanceKernel, PLearn::DivisiveNormalizationKernel, PLearn::GaussianDensityKernel, PLearn::GaussianKernel, PLearn::GeneralizedDistanceRBFKernel, PLearn::GeodesicDistanceKernel, PLearn::Kernel, PLearn::LaplacianKernel, PLearn::LiftBinaryCostFunction, PLearn::LLEKernel, PLearn::LogOfGaussianDensityKernel, PLearn::NegKernel, PLearn::NegLogProbCostFunction, PLearn::NormalizedDotProductKernel, PLearn::PolynomialKernel, PLearn::PowDistanceKernel, PLearn::PrecomputedKernel, PLearn::PricingTransactionPairProfitFunction, PLearn::QuadraticUtilityCostFunction, PLearn::ReconstructionWeightsKernel, PLearn::ScaledGaussianKernel, PLearn::ScaledGeneralizedDistanceRBFKernel, PLearn::SelectedOutputCostFunction, PLearn::SigmoidalKernel, PLearn::SigmoidPrimitiveKernel, PLearn::SourceKernel, PLearn::SquaredErrorCostFunction, PLearn::WeightedCostFunction, PLearn::Binner, PLearn::ConditionalCDFSmoother, PLearn::ConditionalStatsCollector, PLearn::LiftStatsCollector, PLearn::LimitedGaussianSmoother, PLearn::ManualBinner, PLearn::ScaledConditionalCDFSmoother, PLearn::Smoother, PLearn::StatsCollector, PLearn::StatsIterator, PLearn::MeanStatsIterator, PLearn::ExpMeanStatsIterator, PLearn::StddevStatsIterator, PLearn::StderrStatsIterator, PLearn::SharpeRatioStatsIterator, PLearn::MinStatsIterator, PLearn::MaxStatsIterator, PLearn::LiftStatsIterator, PLearn::QuantilesStatsIterator, PLearn::VecStatsCollector, PLearn::NearestNeighborPredictionCost, PLearn::ObjectGenerator, PLearn::RunObject, PLearn::ShellScript, PLearn::AdaptGradientOptimizer, PLearn::ConjGradientOptimizer, PLearn::GradientOptimizer, PLearn::HyperOptimizer, PLearn::HSetVal, PLearn::HTryAll, PLearn::HCoordinateDescent, PLearn::HTryCombinations, PLearn::Optimizer, PLearn::AffineTransformWeightPenalty, PLearn::BinaryVariable, PLearn::ConcatOfVariable, PLearn::CutAboveThresholdVariable, PLearn::CutBelowThresholdVariable, PLearn::DuplicateColumnVariable, PLearn::DuplicateRowVariable, PLearn::DuplicateScalarVariable, PLearn::ElementAtPositionVariable, PLearn::EqualConstantVariable, PLearn::ExtendedVariable, PLearn::Function, PLearn::IndexAtPositionVariable, PLearn::IsAboveThresholdVariable, PLearn::IsMissingVariable, PLearn::MarginPerceptronCostVariable, PLearn::MatrixElementsVariable, PLearn::MatrixOneHotSquaredLoss, PLearn::MatrixSumOfVariable, PLearn::MatRowVariable, PLearn::NaryVariable, PLearn::OneHotSquaredLoss, PLearn::OneHotVariable, PLearn::PDistributionVariable, PLearn::PlusConstantVariable, PLearn::PowVariable, PLearn::ReshapeVariable, PLearn::RowAtPositionVariable, PLearn::SemiSupervisedProbClassCostVariable, PLearn::SoftSlopeIntegralVariable, PLearn::SoftSlopeVariable, PLearn::SubMatTransposeVariable, PLearn::SubMatVariable, PLearn::SubsampleVariable, PLearn::SumOfVariable, PLearn::SumOverBagsVariable, PLearn::UnaryHardSlopeVariable, PLearn::UnaryVariable, PLearn::UnequalConstantVariable, PLearn::UnfoldedFuncVariable, PLearn::UnfoldedSumOfVariable, PLearn::Variable, PLearn::VecElementVariable, PLearn::AsciiVMatrix, PLearn::AutoVMatrix, PLearn::BatchVMatrix, PLearn::BootstrapSplitter, PLearn::BootstrapVMatrix, PLearn::CenteredVMatrix, PLearn::ConcatColumnsVMatrix, PLearn::ConcatRowsSubVMatrix, PLearn::ConcatRowsVMatrix, PLearn::CrossReferenceVMatrix, PLearn::CumVMatrix, PLearn::DatedJoinVMatrix, PLearn::DatedVMatrix, PLearn::DBSplitter, PLearn::DiskVMatrix, PLearn::ExplicitSplitter, PLearn::ExtendedVMatrix, PLearn::FileVMatrix, PLearn::FilteredVMatrix, PLearn::FilterSplitter, PLearn::FinancePreprocVMatrix, PLearn::ForwardVMatrix, PLearn::FractionSplitter, PLearn::GeneralizedOneHotVMatrix, PLearn::GetInputVMatrix, PLearn::GramVMatrix, PLearn::IndexedVMatrix, PLearn::InterleaveVMatrix, PLearn::JoinVMatrix, PLearn::JulianizeVMatrix, PLearn::KernelVMatrix, PLearn::KFoldSplitter, PLearn::KNNVMatrix, PLearn::LearnerProcessedVMatrix, PLearn::LocalNeighborsDifferencesVMatrix, PLearn::MemoryVMatrix, PLearn::MovingAverageVMatrix, PLearn::MultiInstanceVMatrix, PLearn::OneHotVMatrix, PLearn::PairsVMatrix, PLearn::PLearnerOutputVMatrix, PLearn::PrecomputedVMatrix, PLearn::ProcessingVMatrix, PLearn::RangeVMatrix, PLearn::RegularGridVMatrix, PLearn::RemapLastColumnVMatrix, PLearn::RemoveDuplicateVMatrix, PLearn::RemoveRowsVMatrix, PLearn::RepeatSplitter, PLearn::RowsSubVMatrix, PLearn::SelectColumnsVMatrix, PLearn::SelectRowsFileIndexVMatrix, PLearn::SelectRowsVMatrix, PLearn::SequentialSplitter, PLearn::ShiftAndRescaleVMatrix, PLearn::SortRowsVMatrix, PLearn::SourceVMatrix, PLearn::SourceVMatrixSplitter, PLearn::SparseVMatrix, PLearn::SubInputVMatrix, PLearn::SubVMatrix, PLearn::TemporalHorizonVMatrix, PLearn::TestInTrainSplitter, PLearn::ToBagSplitter, PLearn::TrainTestBagsSplitter, PLearn::TrainTestSplitter, PLearn::TrainValidTestSplitter, PLearn::TransposeVMatrix, PLearn::UniformizeVMatrix, PLearn::UniformVMatrix, PLearn::UpsideDownVMatrix, PLearn::VecExtendedVMatrix, PLearn::VMatLanguage, PLearn::PreprocessingVMatrix, PLearn::VMatrix, PLearn::VMatrixFromDistribution, PLearn::VVec, PLearn::VVMatrix, PLearn::YMDDatedVMatrix, PLearn::AdaBoost, PLearn::ClassifierFromDensity, PLearn::MultiInstanceNNet, PLearn::ConditionalDensityNet, PLearn::ConditionalGaussianDistribution, PLearn::Distribution, PLearn::EmpiricalDistribution, PLearn::GaussianDistribution, PLearn::GaussianProcessRegressor, PLearn::GaussMix, PLearn::HistogramDistribution, PLearn::LocallyWeightedDistribution, PLearn::PConditionalDistribution, PLearn::PDistribution, PLearn::SpiralDistribution, PLearn::UnconditionalDistribution, PLearn::UniformDistribution, PLearn::AddCostToLearner, PLearn::EmbeddedLearner, PLearn::Learner, PLearn::NeighborhoodSmoothnessNNet, PLearn::NeuralNet, PLearn::NNet, PLearn::PLearner, PLearn::SelectInputSubsetLearner, PLearn::StackedLearner, PLearn::StatefulLearner, PLearn::TestingLearner, PLearn::GraphicalBiText, PLearn::Dictionary, PLearn::TextSenseSequenceVMatrix, PLearn::Experiment, PLearn::GenerateDecisionPlot, PLearn::Grapher, PLearn::PTester, PLearn::ConstantRegressor, PLearn::LinearRegressor, PLearn::PLS, PLearn::EmbeddedSequentialLearner, PLearn::MovingAverage, PLearn::SequentialLearner, PLearn::SequentialModelSelector, PLearn::SequentialValidation, PLearn::PTester, PLearn::TestMethod, PLearn::Train, PLearn::EntropyContrast, PLearn::GaussianContinuum, PLearn::Isomap, PLearn::IsomapTangentLearner, PLearn::KernelPCA, PLearn::KernelProjection, PLearn::KPCATangentLearner, PLearn::LLE, PLearn::PCA, PLearn::SpectralClustering, and PLearn::TangentLearner.

Definition at line 365 of file Object.h.

References declareOptions().

Referenced by declareOptions().

Object * PLearn::Object::deepCopy (  CopiesMap &  copies  )  const [virtual]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

string PLearn::Object::getOption (  const string &  optionname  )  const
 

This is a generic method to be able to retrieve the value of an option supported by the object (and its derivatives). The option value is returned as a string and MUST be converted to the correct type before use.

Definition at line 72 of file Object.cc.

References PLearn::removeblanks(), and writeOptionVal().

OptionList & PLearn::Object::getOptionList (   )  const [virtual]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

Definition at line 59 of file Object.cc.

Referenced by getOptionsToSave(), newread(), readOptionVal(), and writeOptionVal().

string PLearn::Object::getOptionsToSave (   )  const [virtual]
 

returns a string of the names of all options to save (optionnames are to be separated by a space, and must be supported by writeOptionVal)

Definition at line 226 of file Object.cc.

References PLearn::OptionBase::flag_t, and getOptionList().

Referenced by newwrite().

string PLearn::Object::info (   )  const [virtual]
 

returns a bit more informative string about object (default returns classname())

Reimplemented in PLearn::ClassErrorCostFunction, PLearn::ClassMarginCostFunction, PLearn::DirectNegativeCostFunction, PLearn::DistanceKernel, PLearn::LiftBinaryCostFunction, PLearn::MulticlassErrorCostFunction, PLearn::NegLogProbCostFunction, PLearn::PowDistanceKernel, PLearn::PricingTransactionPairProfitFunction, PLearn::QuadraticUtilityCostFunction, PLearn::SelectedOutputCostFunction, PLearn::SquaredErrorCostFunction, PLearn::WeightedCostFunction, PLearn::MeanStatsIterator, PLearn::ExpMeanStatsIterator, PLearn::StddevStatsIterator, PLearn::StderrStatsIterator, PLearn::SharpeRatioStatsIterator, PLearn::MinStatsIterator, PLearn::MaxStatsIterator, PLearn::LiftStatsIterator, PLearn::QuantilesStatsIterator, PLearn::EqualConstantVariable, PLearn::IsMissingVariable, PLearn::PlusConstantVariable, PLearn::TimesConstantVariable, and PLearn::UnequalConstantVariable.

Definition at line 108 of file Object.cc.

References classname().

Referenced by PLearn::Learner::costNames(), PLearn::Variable::print(), PLearn::UnfoldedSumOfVariable::printInfo(), PLearn::UnfoldedFuncVariable::printInfo(), PLearn::SumOverBagsVariable::printInfo(), PLearn::SumOfVariable::printInfo(), and PLearn::MatrixSumOfVariable::printInfo().

void PLearn::Object::load (  const string &  filename  )  [virtual]
 

This method is deprecated.

It simply calls the generic PLearn load function (that can load any PLearn object): PLearn::load(filename, *this) So you should call PLearn::load directly (it's defined in pl_io.h).

Reimplemented in PLearn::Learner.

Definition at line 333 of file Object.cc.

References PLearn::load().

virtual void PLearn::Object::makeDeepCopyFromShallowCopy (  CopiesMap &  copies  )  [virtual]
 

Does the necessary operations to transform a shallow copy (this) into a deep copy by deep-copying all the members that need to be. Typical implementation:

void CLASS_OF_THIS::makeDeepCopyFromShallowCopy(CopiesMap& copies) { SUPERCLASS_OF_THIS::makeDeepCopyFromShallowCopy(copies); member_ptr = member_ptr->deepCopy(copies); member_smartptr = member_smartptr->deepCopy(copies); member_mat.makeDeepCopyFromShallowCopy(copies); member_vec.makeDeepCopyFromShallowCopy(copies); ... }

Reimplemented in PLearn::Kernel, PLearn::AdaptGradientOptimizer, PLearn::ConjGradientOptimizer, PLearn::GradientOptimizer, PLearn::MultiInstanceNNet, PLearn::EmpiricalDistribution, PLearn::GaussianDistribution, PLearn::Learner, PLearn::NeighborhoodSmoothnessNNet, PLearn::NeuralNet, PLearn::NNet, PLearn::PLearner, PLearn::EmbeddedSequentialLearner, PLearn::SequentialLearner, and PLearn::SequentialModelSelector.

Referenced by PLearn::deepCopyField().

void PLearn::Object::newread (  PStream &  in  ) 
 

reads and builds an object in the new format Classname(optionname=optionval; optionname=optionval; ...)

Definition at line 241 of file Object.cc.

References build(), c_str(), classname(), PLearn::PStream::get(), PLearn::PStream::getline(), getOptionList(), PLearn::PStream::peek(), PLERROR, readOptionVal(), PLearn::removeblanks(), PLearn::PStream::skipBlanksAndComments(), PLearn::PStream::skipBlanksAndCommentsAndSeparators(), and PLearn::PStream::unget().

Referenced by PLearn::operator>>(), read(), and PLearn::readObject().

void PLearn::Object::newwrite (  PStream &  out  )  const
 

Serializes this object in the new format Classname(optionname=optionval; optionname=optionval; ...).

Definition at line 283 of file Object.cc.

References classname(), getOptionsToSave(), PLearn::split(), PLearn::PStream::write(), and writeOptionVal().

Referenced by PLearn::operator<<(), and write().

void PLearn::Object::oldread (  istream &  in  )  [virtual]
 

DEPRECATED For backward compatibility with old saved object.

Reimplemented in PLearn::StatsCollector, PLearn::StatsIterator, PLearn::MeanStatsIterator, PLearn::ExpMeanStatsIterator, PLearn::StddevStatsIterator, PLearn::StderrStatsIterator, PLearn::SharpeRatioStatsIterator, PLearn::MinStatsIterator, PLearn::MaxStatsIterator, PLearn::LiftStatsIterator, PLearn::QuantilesStatsIterator, PLearn::Optimizer, PLearn::Variable, PLearn::ForwardVMatrix, PLearn::VMatrix, and PLearn::Learner.

Definition at line 327 of file Object.cc.

References PLERROR.

Referenced by read().

void PLearn::Object::prepareToSendResults (  PStream &  out,
int  nres
)  [inline, protected]
 

Definition at line 368 of file Object.h.

References prepareToSendResults().

Referenced by prepareToSendResults().

void PLearn::Object::print (  ostream &  out  )  const [virtual]
 

Prints a human-readable, short (not necessarily complete) description of this object instance (default prints info()). This is what is called by operator<< on Object

Reimplemented in PLearn::RealMapping, PLearn::StatsCollector, PLearn::Variable, PLearn::VMatrix, and PLearn::VVec.

Definition at line 110 of file Object.cc.

References PLearn::endl().

Referenced by PLearn::operator<<().

void PLearn::Object::read (  istream &  in  )  [virtual]
 

DEPRECATED (use the declareOption / build_ mecanism instead, that provides automatic serialization) The read method is the counterpart of the write method. It should be able to reconstruct an object that has been previously written with the write method. The current implementation automatically decides whether to call newread() (which is based on the new declareOptions/build mechanism) or oldread() for backward compatibility (if the header is of the form <classname>).

Reimplemented in PLearn::RealMapping.

Definition at line 306 of file Object.cc.

References newread(), oldread(), PLearn::PStream::peek(), and PLearn::ws().

Referenced by PLearn::readObject().

void PLearn::Object::readOptionVal (  PStream &  in,
const string &  optionname
) 
 

Reads and sets the value for the specified option from the specified stream.

Definition at line 118 of file Object.cc.

References classname(), getOptionList(), PLearn::OptionList, PLERROR, and PLearn::toint().

Referenced by newread(), and setOption().

void PLearn::Object::run (   )  [virtual]
 

Overload this for runnable objects (default method issues a runtime error) Runnable objects are objects that can be used as *THE* object of a .plearn script.

The run() method specifies what they should do when executed.

Reimplemented in PLearn::NearestNeighborPredictionCost, PLearn::RunObject, PLearn::ShellScript, PLearn::Experiment, PLearn::GenerateDecisionPlot, PLearn::Grapher, PLearn::PTester, PLearn::SequentialValidation, PLearn::PTester, and PLearn::Train.

Definition at line 324 of file Object.cc.

References PLERROR.

Referenced by PLearn::VMatLanguage::run().

void PLearn::Object::save (  const string &  filename  )  const [virtual]
 

This method is deprecated.

It simply calls the generic PLearn save function (that can save any PLearn object): PLearn::save(filename, *this) So you should call PLearn::save directly (it's defined in pl_io.h).

Reimplemented in PLearn::ForwardVMatrix, PLearn::VMatrix, and PLearn::Learner.

Definition at line 330 of file Object.cc.

References PLearn::save().

void PLearn::Object::setOption (  const string &  optionname,
const string &  value
) 
 

This is a generic method to be able to set an option in an object in the most generic manner value is a string representation of the value to be set. It should only be called for initial construction or reloading of an object, prior to calling build(); To modify the options of an already built object, call changeOptions or changeOption instead. If no option with that name exists, it causes an "Unknown option" runtime error.

Definition at line 65 of file Object.cc.

References readOptionVal().

Referenced by changeOptions().

void PLearn::Object::write (  ostream &  out  )  const [virtual]
 

DEPRECATED (use the declareOption / build_ mecanism instead, that provides automatic serialization) The write method should write a complete description of the object to the given stream, that should be enough to later reconstruct it. (a somewhat human-readable ascii format is usually preferred). The new default version simply calls newwrite(...) which simply writes all the "options" declared in declareOptions, so there is no need to overload write in subclasses. Old classes that still overload write should progressively be moved to the new declareOptions/build mechanism.

Reimplemented in PLearn::RealMapping, and PLearn::Variable.

Definition at line 300 of file Object.cc.

References newwrite().

void PLearn::Object::writeOptionVal (  PStream &  out,
const string &  optionname
)  const
 

Writes the value of the specified option to the specified stream.

Definition at line 181 of file Object.cc.

References getOptionList(), PLERROR, and PLearn::toint().

Referenced by getOption(), and newwrite().

Member Data Documentation

StaticInitializer PLearn::Object::_static_initializer_ [static]
 

Reimplemented in PLearn::RealMapping, and PLearn::SetOption.

The documentation for this class was generated from the following files:
Generated on Tue Aug 17 16:22:34 2004 for PLearn by doxygen 1.3.7