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CApproxJointDiagonalizer Class Reference

Detailed Description

Class ApproxJointDiagonalizer defines an Approximate Joint Diagonalizer (AJD) interface.

AJD finds the matrix V that best diagonalizes a set \({C^1 ... C^k}\) of real valued symmetric \(NxN\) matrices - \(V*C*V^T\)

Definition at line 36 of file ApproxJointDiagonalizer.h.

Inheritance diagram for CApproxJointDiagonalizer:
Inheritance graph

Public Member Functions

 CApproxJointDiagonalizer ()
virtual ~CApproxJointDiagonalizer ()
virtual SGMatrix< float64_tcompute (SGNDArray< float64_t > C, SGMatrix< float64_t > V0=SGMatrix< float64_t >(NULL, 0, 0, false), double eps=CMath::MACHINE_EPSILON, int itermax=200)=0
SGMatrix< float64_tget_V ()
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 bool update_parameter_hash ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0)
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)

Protected Attributes

SGMatrix< float64_tm_V

Constructor & Destructor Documentation


Definition at line 41 of file ApproxJointDiagonalizer.h.

virtual ~CApproxJointDiagonalizer ( )


Definition at line 46 of file ApproxJointDiagonalizer.h.

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 1196 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 1313 of file SGObject.cpp.

virtual SGMatrix<float64_t> compute ( SGNDArray< float64_t C,
SGMatrix< float64_t V0 = SGMatrixfloat64_t >(NULL, 0, 0, false),
double  eps = CMath::MACHINE_EPSILON,
int  itermax = 200 
pure virtual

Computes the matrix V that best diagonalizes C

Cthe set of matrices to be diagonalized
V0an estimate of the matrix V
epsmachine epsilon or desired epsilon
itermaxmaximum number of iterations
V the matrix that best diagonalizes C

Implemented in CFFDiag, CJADiag, CJADiagOrth, CJediDiag, CQDiag, and CUWedge.

virtual CSGObject* deep_copy ( ) const

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

Definition at line 160 of file SGObject.h.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0 

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)
true if all parameters were equal, false if not

Definition at line 1217 of file SGObject.cpp.

SGIO * get_global_io ( )

get the io object

io object

Definition at line 214 of file SGObject.cpp.

Parallel * get_global_parallel ( )

get the parallel object

parallel object

Definition at line 249 of file SGObject.cpp.

Version * get_global_version ( )

get the version object

version object

Definition at line 262 of file SGObject.cpp.

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

Definition at line 1100 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 1124 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 1137 of file SGObject.cpp.

virtual const char* get_name ( ) const
pure virtualinherited

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

name of the SGSerializable

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

SGMatrix<float64_t> get_V ( )

return the matrix V that best diagonalizes C

Definition at line 63 of file ApproxJointDiagonalizer.h.

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 268 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 673 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 514 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 345 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 occurres.

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

Definition at line 1029 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 occurres.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicArray< uint64_t >, and CDynamicObjectArray.

Definition at line 1024 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 711 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 918 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 858 of file SGObject.cpp.

void print_modsel_params ( )

prints all parameter registered for model selection and their type

Definition at line 1076 of file SGObject.cpp.

void print_serializable ( const char *  prefix = "")

prints registered parameters out

prefixprefix for members

Definition at line 280 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 286 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 occurres.

Reimplemented in CKernel.

Definition at line 1039 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 occurres.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicArray< uint64_t >, and CDynamicObjectArray.

Definition at line 1034 of file SGObject.cpp.

void set_generic< complex128_t > ( )

set generic type to T

Definition at line 41 of file SGObject.cpp.

void set_global_io ( SGIO io)

set the io object

ioio object to use

Definition at line 207 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)

set the parallel object

parallelparallel object to use

Definition at line 220 of file SGObject.cpp.

void set_global_version ( Version version)

set the version object

versionversion object to use

Definition at line 255 of file SGObject.cpp.

virtual 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 151 of file SGObject.h.

void unset_generic ( )

unset generic type

this has to be called in classes specializing a template class

Definition at line 275 of file SGObject.cpp.

bool update_parameter_hash ( )

Updates the hash of current parameter combination.

bool if parameter combination has changed since last update.

Definition at line 227 of file SGObject.cpp.

Member Data Documentation

SGIO* io


Definition at line 514 of file SGObject.h.

Parameter* m_gradient_parameters

parameters wrt which we can compute gradients

Definition at line 529 of file SGObject.h.

uint32_t m_hash

Hash of parameter values

Definition at line 535 of file SGObject.h.

Parameter* m_model_selection_parameters

model selection parameters

Definition at line 526 of file SGObject.h.

ParameterMap* m_parameter_map

map for different parameter versions

Definition at line 532 of file SGObject.h.

Parameter* m_parameters


Definition at line 523 of file SGObject.h.

SGMatrix<float64_t> m_V

the matrix V that best diagonalizes C

Definition at line 71 of file ApproxJointDiagonalizer.h.

Parallel* parallel


Definition at line 517 of file SGObject.h.

Version* version


Definition at line 520 of file SGObject.h.

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

SHOGUN Machine Learning Toolbox - Documentation