SHOGUN  3.2.1
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CSGObject Class Reference

Detailed Description

Class SGObject is the base class of all shogun objects.

Apart from dealing with reference counting that is used to manage shogung objects in memory (erase unused object, avoid cleaning objects when they are still in use), it provides interfaces for:

  1. parallel - to determine the number of used CPUs for a method (cf. Parallel)
  2. io - to output messages and general i/o (cf. IO)
  3. version - to provide version information of the shogun version used (cf. Version)

All objects can be cloned and compared (deep copy, recursively)

Definition at line 98 of file SGObject.h.

Inherits SGRefObject.

Inherited by CCache< char >, CCache< float64_t >, CCache< KERNELCACHE_ELEM >, CCache< SGSparseVectorEntry< float64_t > >, CCache< SGSparseVectorEntry< ST > >, CCache< SGSparseVectorEntry< T > >, CCache< ST >, CCache< uint16_t >, CCache< uint32_t >, CCache< uint8_t >, CDynamicArray< bool >, CDynamicArray< char >, CDynamicArray< float32_t >, CDynamicArray< float64_t >, CDynamicArray< int32_t >, CEMBase< MixModelData >, CLinearOperator< SGVector< complex128_t >, SGVector< complex128_t > >, CLinearOperator< SGVector< float64_t >, SGVector< float64_t > >, CLinearOperator< SGVector< T >, SGVector< T > >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< float64_t, float64_t >, CLinearSolver< T, T >, CMap< TParameter *, CSGObject * >, CMap< TParameter *, SGVector< float64_t > >, CMemoryMappedFile< ST >, COperatorFunction< float64_t >, CTreeMachineNode< C45TreeNodeData >, CTreeMachineNode< CARTreeNodeData >, CTreeMachineNode< CHAIDTreeNodeData >, CTreeMachineNode< ConditionalProbabilityTreeNodeData >, CTreeMachineNode< id3TreeNodeData >, CTreeMachineNode< NbodyTreeNodeData >, CTreeMachineNode< RelaxedTreeNodeData >, CTreeMachineNode< VwConditionalProbabilityTreeNodeData >, CTrie< DNATrie >, CTrie< POIMTrie >, CAlphabet, CApproxJointDiagonalizer, CBinaryStream< T >, CBitString, CCache< T >, CCircularBuffer, CCombinationRule, CCompressor, CConverter, CCplex, CCrossValidationOutput, CData, CDataGenerator, CDeepBeliefNetwork, CDifferentiableFunction, CDisjointSet, CDistance, CDistribution, CDynamicArray< T >, CDynamicObjectArray, CDynProg, CECOCDecoder, CECOCEncoder, CEigenSolver, CEMBase< T >, CEvaluation, CEvaluationResult, CFactor, CFactorDataSource, CFactorGraph, CFactorType, CFeatures, CFile, CFunction, CGCArray< T >, CGMNPLib, CGNPPLib, CGUIClassifier, CGUIConverter, CGUIDistance, CGUIFeatures, CGUIHMM, CGUIKernel, CGUILabels, CGUIMath, CGUIPluginEstimate, CGUIPreprocessor, CGUIStructure, CGUITime, CHash, CHypothesisTest, CIndependentComputationEngine, CIndependentJob, CIndexBlock, CIndexBlockRelation, CIntegration, CIntronList, CIOBuffer, CJacobiEllipticFunctions, CJobResult, CJobResultAggregator, CKernel, CKernelMeanMatching, CKernelNormalizer, CKernelSelection, CLabels, CLabelsFactory, CLatentModel, CLikelihoodModel, CLinearOperator< RetType, OperandType >, CLinearSolver< T, ST >, CLineReader, CList, CListElement, CLMNN, CLMNNStatistics, CLogDetEstimator, CLossFunction, CMachine, CMachineEvaluation, CMap< K, T >, CMAPInference, CMAPInferImpl, CMath, CMeanFunction, CMemoryMappedFile< T >, CModelSelection, CModelSelectionParameters, CMulticlassStrategy, CNeuralLayer, CNeuralLayers, CNode, COperatorFunction< T >, CParameterCombination, CParser, CPlifBase, CPlifMatrix, CPreprocessor, CProbabilityDistribution, CQPBSVMLib, CRandom, CRBM, CRejectionStrategy, CResultSet, CSegmentLoss, CSerializableFile, CSerializableFile::TSerializableReader, CSet< T >, CSignal, CSimpleFile< T >, CSOSVMHelper, CSparseInverseCovariance, CSplittingStrategy, CStateModel, CStatistics, CStreamingFile, CStructuredData, CStructuredModel, CSubset, CSubsetStack, CTask, CTaskRelation, CTaxonomy, CTime, CTokenizer, CTraceSampler, CTreeMachineNode< T >, CTrie< Trie >, CVwCacheReader, CVwCacheWriter, CVwEnvironment, CVwLearner, CVwParser, CVwRegressor, and MKLMulticlassOptimizationBase.

Public Member Functions

 CSGObject ()
 CSGObject (const CSGObject &orig)
virtual ~CSGObject ()
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual const char * get_name () const =0
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGStringList< char > get_modelsel_names ()
void print_modsel_params ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
virtual void update_parameter_hash ()
virtual bool parameter_hash_changed ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
virtual CSGObjectclone ()

Public Attributes

uint32_t m_hash

Protected Member Functions

virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
virtual void load_serializable_pre () throw (ShogunException)
virtual void load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)

Constructor & Destructor Documentation

CSGObject ( )

default constructor

Definition at line 117 of file SGObject.cpp.

CSGObject ( const CSGObject orig)

copy constructor

Definition at line 124 of file SGObject.cpp.

~CSGObject ( )


Definition at line 131 of file SGObject.cpp.

Member Function Documentation

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > *  dict)

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

dictdictionary of parameters to be built.

Definition at line 1189 of file SGObject.cpp.

CSGObject * clone ( )

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Definition at line 1306 of file SGObject.cpp.

CSGObject * deep_copy ( ) const

A deep copy. All the instance variables will also be copied.

Definition at line 146 of file SGObject.cpp.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
true if all parameters were equal, false if not

Definition at line 1210 of file SGObject.cpp.

SGIO * get_global_io ( )

get the io object

io object

Definition at line 183 of file SGObject.cpp.

Parallel * get_global_parallel ( )

get the parallel object

parallel object

Definition at line 224 of file SGObject.cpp.

Version * get_global_version ( )

get the version object

version object

Definition at line 237 of file SGObject.cpp.

SGStringList< char > get_modelsel_names ( )
vector of names of all parameters which are registered for model selection

Definition at line 1081 of file SGObject.cpp.

char * get_modsel_param_descr ( const char *  param_name)

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

param_namename of the parameter
description of the parameter

Definition at line 1105 of file SGObject.cpp.

index_t get_modsel_param_index ( const char *  param_name)

Returns index of model selection parameter with provided index

param_namename of model selection parameter
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1118 of file SGObject.cpp.

virtual const char* get_name ( ) const
pure virtual

Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

name of the SGSerializable

Implements SGRefObject.

Implemented in CMath, CHMM, CStringFeatures< ST >, CStringFeatures< T >, CStringFeatures< uint8_t >, CStringFeatures< char >, CStringFeatures< uint16_t >, CSVMLight, CTrie< Trie >, CTrie< DNATrie >, CTrie< POIMTrie >, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CMultitaskKernelTreeNormalizer, CList, CDynProg, CLibSVMFile, CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, CFile, CStatistics, CSparseFeatures< ST >, CSparseFeatures< float64_t >, CSparseFeatures< T >, CSpecificityMeasure, CPrecisionMeasure, CPlif, CRecallMeasure, CUAIFile, CDynamicObjectArray, CCrossCorrelationMeasure, CCSVFile, CF1Measure, CLaRank, CBinaryFile, CWRACCMeasure, CProtobufFile, CRBM, CTaxonomy, CBALMeasure, CBitString, CStreamingVwFeatures, CStreamingSparseFeatures< T >, CMultitaskKernelPlifNormalizer, CErrorRateMeasure, CWDSVMOcas, CMachine, CNeuralLayer, CAccuracyMeasure, CStreamingFile, CQuadraticTimeMMD, CRandom, CStreamingMMD, CMultitaskKernelMaskNormalizer, CMemoryMappedFile< T >, CMemoryMappedFile< ST >, CAlphabet, CMKL, CStreamingDenseFeatures< T >, CLMNNStatistics, CStructuredModel, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CCombinedDotFeatures, CFeatureSelection< ST >, CFeatureSelection< float64_t >, CGUIStructure, CCache< T >, CCache< SGSparseVectorEntry< ST > >, CCache< uint32_t >, CCache< ST >, CCache< SGSparseVectorEntry< float64_t > >, CCache< float64_t >, CCache< uint8_t >, CCache< KERNELCACHE_ELEM >, CCache< char >, CCache< uint16_t >, CCache< SGSparseVectorEntry< T > >, CMultitaskKernelMaskPairNormalizer, CSVM, CMultitaskKernelNormalizer, CNeuralNetwork, CGUIClassifier, CGaussian, CGUIFeatures, CGMM, CBinaryStream< T >, CHashedWDFeaturesTransposed, CLinearHMM, CSimpleFile< T >, CParameterCombination, CDeepBeliefNetwork, CStreamingStringFeatures< T >, CNeuralLinearLayer, CMulticlassSVM, CStateModel, CRandomKitchenSinksDotFeatures, COnlineLinearMachine, CVwParser, CPluginEstimate, CVowpalWabbit, CBinnedDotFeatures, CSVMOcas, CNeuralConvolutionalLayer, CSVRLight, CHashedWDFeatures, CPlifMatrix, CCrossValidation, CImplicitWeightedSpecFeatures, CCombinedFeatures, CSparseMatrixOperator< T >, CSNPFeatures, CWDFeatures, CKMeans, CCrossValidationMulticlassStorage, CHashedDenseFeatures< ST >, CIOBuffer, CLossFunction, CTwoStateModel, CPCA, CHMSVMModel, CDeepAutoencoder, CLeastAngleRegression, CGUIKernel, CKNN, CRandomFourierGaussPreproc, CMKLMulticlass, CHashedSparseFeatures< ST >, CAutoencoder, CHypothesisTest, CExplicitSpecFeatures, CModelSelectionParameters, CLibLinearMTL, CNOCCO, CPositionalPWM, CHashedDocDotFeatures, CGUIHMM, COnlineSVMSGD, CIntegration, CJacobiEllipticFunctions, CLibLinear, CLDA, CZeroMeanCenterKernelNormalizer, CSparsePolyFeatures, CHashedMultilabelModel, CSqrtDiagKernelNormalizer, CHuberLoss, CScatterKernelNormalizer, CCplex, CFisherLDA, CHSIC, CRationalApproximation, CStochasticProximityEmbedding, CLatentModel, CGMNPLib, CMulticlassMachine, CDixonQTestRejectionStrategy, CTableFactorType, CSVMSGD, CVwCacheReader, CLBPPyrDotFeatures, CRidgeKernelNormalizer, CDependenceMaximization, CLinearMachine, CGraphCut, CMulticlassSOLabels, CSerializableAsciiFile, CSGDQN, CSNPStringKernel, CTime, CMatrixFeatures< ST >, CWeightedCommWordStringKernel, CHingeLoss, CTwoSampleTest, CSquaredLoss, CAbsoluteDeviationLoss, CExponentialLoss, CQPBSVMLib, CCustomKernel, CMulticlassLabels, CHash, CLinearTimeMMD, CFactor, CPlifArray, CStreamingVwFile, CStreamingHashedDocDotFeatures, CKernelIndependenceTest, CCustomDistance, CWeightedDegreeStringKernel, CKernelRidgeRegression, CBaggingMachine, CQDA, CNeuralLayers, CNeuralLogisticLayer, CNeuralRectifiedLinearLayer, CTOPFeatures, CDiceKernelNormalizer, CHierarchicalMultilabelModel, CMultitaskKernelMklNormalizer, CTask, CGaussianProcessClassification, CVwEnvironment, CBinaryLabels, CMultilabelModel, CDomainAdaptationSVMLinear, CMultilabelSOLabels, CCHAIDTree, CKernelTwoSampleTest, CWeightedDegreePositionStringKernel, CMAPInferImpl, CBesselKernel, CTanimotoKernelNormalizer, CCircularBuffer, CMCLDA, CGaussianDistribution, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CAvgDiagKernelNormalizer, CVarianceKernelNormalizer, CMulticlassModel, COnlineLibLinear, CIndexFeatures, CCARTree, CHierarchical, CIndependenceTest, CFKFeatures, CSpectrumMismatchRBFKernel, COperatorFunction< T >, CMultilabelCLRModel, COperatorFunction< float64_t >, CStreamingAsciiFile, CCombinedKernel, CSparseSpatialSampleStringKernel, CVwRegressor, CHashedDocConverter, CFactorGraphLabels, CKLInferenceMethod, CSubsequenceStringKernel, CDotKernel, CGaussianKernel, CCommWordStringKernel, CSet< T >, CDataGenerator, CNeuralInputLayer, CSequenceLabels, CNode, CContingencyTableEvaluation, CPolyFeatures, CDenseMatrixOperator< T >, CLibSVR, CDenseMatrixOperator< float64_t >, CChi2Kernel, CPyramidChi2, CSignal, CSalzbergWordStringKernel, CStructuredLabels, CSquaredHingeLoss, CLPBoost, CNewtonSVM, CKLApproxDiagonalInferenceMethod, CVwLearner, CKLCholeskyInferenceMethod, CKLCovarianceInferenceMethod, CIterativeLinearSolver< T, ST >, CIterativeLinearSolver< float64_t, float64_t >, CIterativeLinearSolver< complex128_t, float64_t >, CIterativeLinearSolver< T, T >, CCommUlongStringKernel, CCompressor, CHomogeneousKernelMap, CSVMLin, CHistogram, CGaussianShiftKernel, CGCArray< T >, CIndexBlockTree, CMultiLaplacianInferenceMethod, CNeuralSoftmaxLayer, CLocallyLinearEmbedding, CMahalanobisDistance, CAttributeFeatures, CRandomFourierDotFeatures, CFirstElementKernelNormalizer, CMap< K, T >, CLogLoss, CLogLossMargin, CSmoothHingeLoss, CScatterSVM, CMap< TParameter *, CSGObject * >, CMap< TParameter *, SGVector< float64_t > >, CGNPPLib, CVwNativeCacheReader, CDistanceKernel, CLatentLabels, CMultilabelLabels, CKLLowerTriangularInferenceMethod, CSingleLaplacianInferenceMethodWithLBFGS, CSoftMaxLikelihood, CMMDKernelSelection, CSpectrumRBFKernel, CLogDetEstimator, CSegmentLoss, CKernelDistance, CStreamingFileFromFeatures, CLinearRidgeRegression, CDomainAdaptationSVM, CPolyMatchStringKernel, CSimpleLocalityImprovedStringKernel, CKernelSelection, CStreamingVwCacheFile, COligoStringKernel, CKLDualInferenceMethod, CEigenSolver, CLPM, CCircularKernel, CConstKernel, CDiagKernel, CSphericalKernel, CLogitDVGLikelihood, CC45ClassifierTree, CMultitaskClusteredLogisticRegression, CEmbeddingConverter, CEuclideanDistance, CWeightedMajorityVote, CMulticlassOVREvaluation, CPolyKernel, CPolyMatchWordStringKernel, CLanczosEigenSolver, CID3ClassifierTree, CNearestCentroid, CMultidimensionalScaling, CStreamingFileFromDenseFeatures< T >, CStreamingFileFromSparseFeatures< T >, CStreamingFileFromStringFeatures< T >, CANOVAKernel, CProductKernel, CSparseKernel< ST >, CGaussianMatchStringKernel, CKernelPCA, CFixedDegreeStringKernel, CStringKernel< ST >, CTensorProductPairKernel, CRandomForest, CTraceSampler, CGaussianNaiveBayes, CMulticlassOneVsRestStrategy, CStringKernel< uint16_t >, CStringKernel< char >, CStringKernel< uint64_t >, CKernelDensity, CParser, CTStudentKernel, CWaveletKernel, CGaussianProcessRegression, MKLMulticlassGradient, CDiffusionMaps, CMinkowskiMetric, CExponentialKernel, CLaplacianEigenmaps, CAttenuatedEuclideanDistance, CCauchyKernel, CLogKernel, CPowerKernel, CRationalQuadraticKernel, CDistantSegmentsKernel, CWaveKernel, CLaplacianInferenceBase, CKernelMachine, CBAHSIC, CLocalityImprovedStringKernel, CMatchWordStringKernel, CRegulatoryModulesStringKernel, CDistanceMachine, CStructuredOutputMachine, CKernelDependenceMaximization, CAUCKernel, CHistogramIntersectionKernel, CSigmoidKernel, CGaussianProcessMachine, CInverseMultiQuadricKernel, CFFDiag, CJADiag, CJADiagOrth, CLibLinearRegression, CMMDKernelSelectionCombOpt, CLocalAlignmentStringKernel, CLabelsFactory, CJediDiag, CQDiag, CUWedge, CTreeMachineNode< T >, CTreeMachineNode< ConditionalProbabilityTreeNodeData >, CTreeMachineNode< RelaxedTreeNodeData >, CTreeMachineNode< id3TreeNodeData >, CTreeMachineNode< VwConditionalProbabilityTreeNodeData >, CTreeMachineNode< CARTreeNodeData >, CTreeMachineNode< C45TreeNodeData >, CTreeMachineNode< CHAIDTreeNodeData >, CTreeMachineNode< NbodyTreeNodeData >, CMulticlassAccuracy, CGaussianARDKernel, CGaussianShortRealKernel, CMultiquadricKernel, CExactInferenceMethod, CPerceptron, CICAConverter, CSplineKernel, CDelimiterTokenizer, CDualVariationalGaussianLikelihood, CLogitVGPiecewiseBoundLikelihood, CLogRationalApproximationIndividual, CDimensionReductionPreprocessor, CGHMM, CHistogramWordStringKernel, CMatrixOperator< T >, CTaskTree, CMatrixOperator< float64_t >, CProbabilityDistribution, CConstMean, CStochasticGBMachine, CLinearOperator< RetType, OperandType >, CCGMShiftedFamilySolver, CIterativeShiftedLinearFamilySolver< T, ST >, CLogRationalApproximationCGM, CTreeMachine< T >, CMMDKernelSelectionCombMaxL2, CMultitaskL12LogisticRegression, CMultitaskROCEvaluation, CLinearOperator< SGVector< complex128_t >, SGVector< complex128_t > >, CLinearOperator< SGVector< T >, SGVector< T > >, CLinearOperator< SGVector< float64_t >, SGVector< float64_t > >, CIterativeShiftedLinearFamilySolver< float64_t, complex128_t >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CCanberraMetric, CCosineDistance, CManhattanMetric, CLineReader, CJensenShannonKernel, CLinearKernel, CNumericalVGLikelihood, CLinearStructuredOutputMachine, CDualLibQPBMSOSVM, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CIdentityKernelNormalizer, CLinearStringKernel, CFITCInferenceMethod, CDecompressString< ST >, CGUIConverter, CNGramTokenizer, CStudentsTVGLikelihood, CMMDKernelSelectionMedian, MKLMulticlassGLPK, CChiSquareDistance, CHammingWordDistance, CLogitVGLikelihood, CProbitVGLikelihood, CRandomSearchModelSelection, CGUILabels, CAveragedPerceptron, CSOBI, CKernelLocallyLinearEmbedding, CSparseDistance< ST >, CCrossValidationResult, CLatentFeatures, CBinaryTreeMachineNode< T >, CMMDKernelSelectionOpt, CSparseDistance< float64_t >, CFFSep, CBrayCurtisDistance, CChebyshewMetric, CFactorGraphFeatures, CRegressionLabels, CJobResultAggregator, CMulticlassOneVsOneStrategy, CNbodyTree, CSparsePreprocessor< ST >, CLeastSquaresRegression, MKLMulticlassOptimizationBase, CVwNativeCacheWriter, CJediSep, CUWedgeSep, CSparseEuclideanDistance, CRealFileFeatures, CLinearARDKernel, CSingleLaplacianInferenceMethod, CDenseMatrixExactLog, CPNorm, CSparseMultilabel, CGUIPluginEstimate, CVwAdaptiveLearner, CStringDistance< ST >, CStructuredAccuracy, CLinearLatentMachine, CMulticlassStrategy, CRescaleFeatures, CStringDistance< uint16_t >, CVwNonAdaptiveLearner, CWeightedDegreeRBFKernel, CIndependentJob, CECOCRandomSparseEncoder, CLogPlusOne, CGradientCriterion, CLatentSVM, CEPInferenceMethod, CGMNPSVM, CNormOne, CMixtureModel, CFactorGraphObservation, CScalarResult< T >, CDirectLinearSolverComplex, CIndividualJobResultAggregator, CMAPInference, CMultitaskTraceLogisticRegression, CLibSVM, CStringFileFeatures< ST >, CLinearMulticlassMachine, CRationalApproximationCGMJob, CBallTree, CKDTree, CStringPreprocessor< ST >, CSumOne, CMultitaskLogisticRegression, CStringPreprocessor< uint16_t >, CStringPreprocessor< uint64_t >, CFastICA, CCanberraWordDistance, CManhattanWordDistance, CCrossValidationOutput, CRationalApproximationIndividualJob, CECOCDiscriminantEncoder, CRandomCARTree, CSortWordString, CResultSet, CTaskGroup, CGUIDistance, CStoreVectorAggregator< T >, CConjugateOrthogonalCGSolver, CPruneVarSubMean, CCCSOSVM, CIntronList, CRealNumber, CStoreVectorAggregator< complex128_t >, CJade, CIndexBlock, CIndexBlockGroup, CGradientModelSelection, CSortUlongString, CSequence, CGUIPreprocessor, CFeatureBlockLogisticRegression, CMeanSquaredError, CMeanSquaredLogError, CLatentSOSVM, CStudentsTLikelihood, CDenseExactLogJob, CMulticlassLibLinear, CMeanAbsoluteError, CDummyFeatures, CListElement, CIsomap, CDenseDistance< ST >, CRealDistance, CIndependentComputationEngine, CVectorResult< T >, CKernelStructuredOutputMachine, CLMNN, CThresholdRejectionStrategy, CMMDKernelSelectionMax, CDenseDistance< float64_t >, CSVMLightOneClass, CLinearLocalTangentSpaceAlignment, CNeighborhoodPreservingEmbedding, CEMBase< T >, CEMMixtureModel, CClusteringAccuracy, CClusteringMutualInformation, CMultilabelAccuracy, CMeanShiftDataGenerator, CVwConditionalProbabilityTree, CEMBase< MixModelData >, CHessianLocallyLinearEmbedding, CCustomMahalanobisDistance, CCombinationRule, CStoreScalarAggregator< T >, CConjugateGradientSolver, CMMDKernelSelectionComb, CFactorGraphModel, CMultitaskLeastSquaresRegression, CLocalTangentSpaceAlignment, CSubsetStack, CGaussianLikelihood, CGridSearchModelSelection, CStochasticSOSVM, CMultitaskLinearMachine, CMajorityVote, CMeanRule, CDirectEigenSolver, CLinearSolver< T, ST >, CLinearSolver< float64_t, float64_t >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< T, T >, CLocalityPreservingProjections, CGradientEvaluation, CSerialComputationEngine, CECOCEncoder, CMulticlassLibSVM, CMKLRegression, CFactorDataSource, CFactorGraph, CTaskRelation, CGaussianBlobsDataGenerator, CIndexBlockRelation, CKernelMeanMatching, CLibSVMOneClass, CROCEvaluation, CKernelMulticlassMachine, CNormalSampler, CBalancedConditionalProbabilityTree, CFactorType, CSOSVMHelper, CDomainAdaptationMulticlassLibLinear, CMKLOneClass, CGPBTSVM, CMPDSVM, CGradientResult, CECOCIHDDecoder, CMulticlassTreeGuidedLogisticRegression, CConditionalProbabilityTree, CRelaxedTree, CFWSOSVM, CMKLClassification, CSubset, CDirectSparseLinearSolver, CECOCRandomDenseEncoder, CMulticlassLogisticRegression, CMulticlassOCAS, CShareBoost, CGNPPSVM, CStratifiedCrossValidationSplitting, CPRCEvaluation, CProbitLikelihood, CSparseInverseCovariance, CCrossValidationSplitting, CDisjointSet, CDenseSubsetFeatures< ST >, CECOCForestEncoder, CGUIMath, CGUITime, CLogitLikelihood, CTDistributedStochasticNeighborEmbedding, CCrossValidationPrintOutput, CJobResult, CECOCDecoder, CFactorAnalysis, CManifoldSculpting, CCrossValidationMKLStorage, SerializableAsciiReader00, CNativeMulticlassMachine, CFunction, CECOCAEDDecoder, CECOCEDDecoder, CECOCStrategy, CData, CZeroMean, CConverter, CLOOCrossValidationSplitting, CBaseMulticlassMachine, CECOCSimpleDecoder, CECOCLLBDecoder, CStructuredData, CECOCHDDecoder, CECOCOVOEncoder, CECOCOVREncoder, CRandomConditionalProbabilityTree, and CRejectionStrategy.

bool is_generic ( EPrimitiveType *  generic) const

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

genericset to the type of the generic if returning TRUE
TRUE if a class template.

Definition at line 243 of file SGObject.cpp.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
(sorted) array of created TParameter instances with file data

Definition at line 650 of file SGObject.cpp.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
new array with TParameter instances with the attached data

Definition at line 491 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
TRUE if done, otherwise FALSE

Definition at line 320 of file SGObject.cpp.

void load_serializable_post ( ) throw (ShogunException)

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 1008 of file SGObject.cpp.

void load_serializable_pre ( ) throw (ShogunException)

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 1003 of file SGObject.cpp.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

param_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

Definition at line 688 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

Definition at line 895 of file SGObject.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

Definition at line 835 of file SGObject.cpp.

bool parameter_hash_changed ( )
whether parameter combination has changed since last update

Definition at line 209 of file SGObject.cpp.

void print_modsel_params ( )

prints all parameter registered for model selection and their type

Definition at line 1057 of file SGObject.cpp.

void print_serializable ( const char *  prefix = "")

prints registered parameters out

prefixprefix for members

Definition at line 255 of file SGObject.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 

Save this object to file.

filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
TRUE if done, otherwise FALSE

Definition at line 261 of file SGObject.cpp.

void save_serializable_post ( ) throw (ShogunException)

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 1018 of file SGObject.cpp.

void save_serializable_pre ( ) throw (ShogunException)

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 1013 of file SGObject.cpp.

void set_generic< complex128_t > ( )

set generic type to T

Definition at line 38 of file SGObject.cpp.

void set_global_io ( SGIO io)

set the io object

ioio object to use

Definition at line 176 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)

set the parallel object

parallelparallel object to use

Definition at line 189 of file SGObject.cpp.

void set_global_version ( Version version)

set the version object

versionversion object to use

Definition at line 230 of file SGObject.cpp.

CSGObject * shallow_copy ( ) const

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 140 of file SGObject.cpp.

void unset_generic ( )

unset generic type

this has to be called in classes specializing a template class

Definition at line 250 of file SGObject.cpp.

void update_parameter_hash ( )

Updates the hash of current parameter combination

Definition at line 196 of file SGObject.cpp.

Member Data Documentation

SGIO* io


Definition at line 457 of file SGObject.h.

Parameter* m_gradient_parameters

parameters wrt which we can compute gradients

Definition at line 472 of file SGObject.h.

uint32_t m_hash

Hash of parameter values

Definition at line 478 of file SGObject.h.

Parameter* m_model_selection_parameters

model selection parameters

Definition at line 469 of file SGObject.h.

ParameterMap* m_parameter_map

map for different parameter versions

Definition at line 475 of file SGObject.h.

Parameter* m_parameters


Definition at line 466 of file SGObject.h.

Parallel* parallel


Definition at line 460 of file SGObject.h.

Version* version


Definition at line 463 of file SGObject.h.

The documentation for this class was generated from the following files:

SHOGUN Machine Learning Toolbox - Documentation