#include <MergeTreeNeuralNetwork.h>

Inheritance diagram for ttk::MergeTreeNeuralNetwork:

Public Member Functions
	MergeTreeNeuralNetwork ()

void	execute (std::vector< ftm::MergeTree< float > > &trees, std::vector< ftm::MergeTree< float > > &trees2)

Public Member Functions inherited from ttk::Debug
	Debug ()

	~Debug () override

virtual int	setDebugLevel (const int &debugLevel)

int	setWrapper (const Wrapper *wrapper) override

int	printMsg (const std::string &msg, const debug::Priority &priority=debug::Priority::INFO, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cout) const

int	printMsg (const std::vector< std::string > &msgs, const debug::Priority &priority=debug::Priority::INFO, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cout) const

int	printErr (const std::string &msg, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cerr) const

int	printWrn (const std::string &msg, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cerr) const

int	printMsg (const std::string &msg, const double &progress, const double &time, const int &threads, const double &memory, const debug::LineMode &lineMode=debug::LineMode::NEW, const debug::Priority &priority=debug::Priority::PERFORMANCE, std::ostream &stream=std::cout) const

int	printMsg (const std::string &msg, const double &progress, const double &time, const debug::LineMode &lineMode=debug::LineMode::NEW, const debug::Priority &priority=debug::Priority::PERFORMANCE, std::ostream &stream=std::cout) const

int	printMsg (const std::string &msg, const double &progress, const double &time, const int &threads, const debug::LineMode &lineMode=debug::LineMode::NEW, const debug::Priority &priority=debug::Priority::PERFORMANCE, std::ostream &stream=std::cout) const

int	printMsg (const std::string &msg, const double &progress, const debug::LineMode &lineMode=debug::LineMode::NEW, const debug::Priority &priority=debug::Priority::PERFORMANCE, std::ostream &stream=std::cout) const

int	printMsg (const std::string &msg, const double &progress, const debug::Priority &priority, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cout) const

int	printMsg (const std::vector< std::vector< std::string > > &rows, const debug::Priority &priority=debug::Priority::INFO, const bool hasHeader=true, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cout) const

int	printMsg (const debug::Separator &separator, const debug::LineMode &lineMode=debug::LineMode::NEW, const debug::Priority &priority=debug::Priority::INFO, std::ostream &stream=std::cout) const

int	printMsg (const debug::Separator &separator, const debug::Priority &priority, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cout) const

int	printMsg (const std::string &msg, const debug::Separator &separator, const debug::LineMode &lineMode=debug::LineMode::NEW, const debug::Priority &priority=debug::Priority::INFO, std::ostream &stream=std::cout) const

void	setDebugMsgPrefix (const std::string &prefix)

Public Member Functions inherited from ttk::BaseClass
	BaseClass ()

virtual	~BaseClass ()=default

int	getThreadNumber () const

virtual int	setThreadNumber (const int threadNumber)

Public Member Functions inherited from ttk::MergeTreeNeuralBase
	MergeTreeNeuralBase ()

Public Member Functions inherited from ttk::MergeTreeAxesAlgorithmBase
	MergeTreeAxesAlgorithmBase ()

void	setDeterministic (const bool deterministic)

void	setNumberOfProjectionSteps (const unsigned int k)

void	setBarycenterSizeLimitPercent (const double barycenterSizeLimitPercent)

void	setProbabilisticVectorsInit (const bool probabilisticVectorsInit)

template<class dataType>
void	computeOneDistance (const ftm::MergeTree< dataType > &tree1, const ftm::MergeTree< dataType > &tree2, std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > &matching, dataType &distance, bool isCalled=false, bool useDoubleInput=false, bool isFirstInput=true)

template<class dataType>
void	computeOneDistance (const ftm::MergeTree< dataType > &tree1, const ftm::MergeTree< dataType > &tree2, dataType &distance, bool isCalled=false, bool useDoubleInput=false, bool isFirstInput=true)

template<class dataType>
void	initVectorFromMatching (ftm::MergeTree< dataType > &barycenter, ftm::MergeTree< dataType > &tree, std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > &matching, std::vector< std::vector< double > > &v)

template<class dataType>
void	initRandomVector (ftm::MergeTree< dataType > &barycenter, std::vector< std::vector< double > > &v, std::vector< std::vector< std::vector< double > > > &vS, std::vector< std::vector< std::vector< double > > > &v2s)

template<class dataType, typename F>
int	initVectors (int axeNumber, ftm::MergeTree< dataType > &barycenter, std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &barycenter2, std::vector< ftm::MergeTree< dataType > > &trees2, std::vector< std::vector< double > > &v1, std::vector< std::vector< double > > &v2, std::vector< std::vector< double > > &trees2V1, std::vector< std::vector< double > > &trees2V2, int newVectorOffset, std::vector< double > &inputToOriginDistances, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &baryMatchings, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &baryMatchings2, std::vector< std::vector< double > > &inputToAxesDistances, std::vector< std::vector< std::vector< double > > > &vS, std::vector< std::vector< std::vector< double > > > &v2s, std::vector< std::vector< std::vector< double > > > &trees2Vs, std::vector< std::vector< std::vector< double > > > &trees2V2s, bool projectInitializedVectors, F initializedVectorsProjection)

template<class dataType>
void	computeOneBarycenter (std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &baryMergeTree, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &matchings, std::vector< double > &finalDistances, double barycenterSizeLimitPercent, unsigned int barycenterMaximumNumberOfPairs, int barycenterInitIndex, bool oneIter, bool useDoubleInput=false, bool isFirstInput=true)

template<class dataType>
void	computeOneBarycenter (std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &baryMergeTree, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &matchings, std::vector< double > &finalDistances, double barycenterSizeLimitPercent, unsigned int barycenterMaximumNumberOfPairs, bool useDoubleInput=false, bool isFirstInput=true)

template<class dataType>
void	computeOneBarycenter (std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &baryMergeTree, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &matchings, std::vector< double > &finalDistances, double barycenterSizeLimitPercent, bool useDoubleInput=false, bool isFirstInput=true)

template<class dataType>
void	computeOneBarycenter (std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &baryMergeTree, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &matchings, std::vector< double > &finalDistances, bool useDoubleInput=false, bool isFirstInput=true)

template<class dataType>
void	computeOneBarycenter (std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &baryMergeTree, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &matchings)

template<class dataType>
void	computeOneBarycenter (std::vector< ftm::MergeTree< dataType > > &trees, ftm::MergeTree< dataType > &baryMergeTree)

template<class dataType>
void	preprocessingTrees (std::vector< ftm::MergeTree< dataType > > &trees, std::vector< std::vector< int > > &nodeCorr, bool useMinMaxPairT=true)

template<class dataType>
void	preprocessingTrees (std::vector< ftm::MergeTree< dataType > > &trees, bool useMinMaxPairT=true)

template<class dataType>
std::tuple< dataType, dataType >	getParametrizedBirthDeath (ftm::FTMTree_MT *tree, ftm::idNode node)

template<class dataType>
void	computeBranchesCorrelationMatrix (const ftm::MergeTree< dataType > &barycenter, std::vector< ftm::MergeTree< dataType > > &trees, std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > &baryMatchings, std::vector< std::vector< double > > &allTs, std::vector< std::vector< double > > &branchesCorrelationMatrix, std::vector< std::vector< double > > &persCorrelationMatrix)

Public Member Functions inherited from ttk::MergeTreeBase
	MergeTreeBase ()

void	setAssignmentSolver (int assignmentSolver)

void	setEpsilon1UseFarthestSaddle (bool b)

void	setEpsilonTree1 (double epsilon)

void	setEpsilonTree2 (double epsilon)

void	setEpsilon2Tree1 (double epsilon)

void	setEpsilon2Tree2 (double epsilon)

void	setEpsilon3Tree1 (double epsilon)

void	setEpsilon3Tree2 (double epsilon)

void	setPersistenceThreshold (double pt)

void	setParallelize (bool para)

void	setNodePerTask (int npt)

void	setBranchDecomposition (bool useBD)

void	setNormalizedWasserstein (bool normalizedWasserstein)

void	setKeepSubtree (bool keepSubtree)

void	setNonMatchingWeight (double weight)

void	setBarycenterMergeTree (bool imt)

void	setDistanceSquaredRoot (bool distanceSquaredRoot)

void	setUseMinMaxPair (bool useMinMaxPair)

void	setDeleteMultiPersPairs (bool deleteMultiPersPairsT)

void	setCleanTree (bool clean)

void	setIsPersistenceDiagram (bool isPD)

void	setJoinSplitMixtureCoefficient (const double mixtureCoefficient)

void	setUseDoubleInput (const bool useDoubleInput)

std::vector< std::vector< int > >	getTreesNodeCorr ()

double	mixDistancesMinMaxPairWeight (bool isFirstInput)

double	mixDistancesWeight (bool isFirstInput)

template<class dataType>
double	mixDistances (dataType distance1, dataType distance2)

template<class dataType>
void	mixDistancesMatrix (std::vector< std::vector< dataType > > &distanceMatrix, std::vector< std::vector< dataType > > &distanceMatrix2)

template<class dataType>
void	mergeSaddle (ftm::FTMTree_MT *tree, double epsilon, std::vector< std::vector< ftm::idNode > > &treeNodeMerged, bool mergeByPersistence=false)

template<class dataType>
void	persistenceMerging (ftm::FTMTree_MT *tree, double epsilon2, double epsilon3=100)

void	deletePersistenceDiagramsPairs (ftm::FTMTree_MT *tree, std::vector< ftm::idNode > &nodes)

template<class dataType>
void	keepMostImportantPairs (ftm::FTMTree_MT *tree, int n, bool useBD)

template<class dataType>
void	persistenceThresholding (ftm::FTMTree_MT *tree, double persistenceThresholdT, std::vector< ftm::idNode > &deletedNodes)

template<class dataType>
void	persistenceThresholding (ftm::FTMTree_MT *tree, std::vector< ftm::idNode > &deletedNodes)

template<class dataType>
void	persistenceThresholding (ftm::FTMTree_MT *tree, double persistenceThresholdT)

template<class dataType>
void	persistenceThresholding (ftm::FTMTree_MT *tree)

template<class dataType>
void	verifyOrigins (ftm::FTMTree_MT *tree)

template<class dataType>
void	preprocessTree (ftm::FTMTree_MT *tree, bool deleteInconsistentNodes=true)

template<class dataType>
ftm::FTMTree_MT *	computeBranchDecomposition (ftm::FTMTree_MT *tree, std::vector< std::vector< ftm::idNode > > &treeNodeMerged)

template<class dataType>
void	dontUseMinMaxPair (ftm::FTMTree_MT *tree)

void	verifyPairsTree (ftm::FTMTree_MT *tree)

template<class dataType>
void	deleteMultiPersPairs (ftm::FTMTree_MT *tree, bool useBD)

template<class dataType>
void	preprocessingPipeline (ftm::MergeTree< dataType > &mTree, double epsilonTree, double epsilon2Tree, double epsilon3Tree, bool branchDecompositionT, bool useMinMaxPairT, bool cleanTreeT, double persistenceThreshold, std::vector< int > &nodeCorr, bool deleteInconsistentNodes=true)

template<class dataType>
void	preprocessingPipeline (ftm::MergeTree< dataType > &mTree, double epsilonTree, double epsilon2Tree, double epsilon3Tree, bool branchDecompositionT, bool useMinMaxPairT, bool cleanTreeT, std::vector< int > &nodeCorr, bool deleteInconsistentNodes=true)

void	reverseNodeCorr (ftm::FTMTree_MT *tree, std::vector< int > &nodeCorr)

template<class dataType>
void	mtFlattening (ftm::MergeTree< dataType > &mt)

template<class dataType>
void	mtsFlattening (std::vector< ftm::MergeTree< dataType > > &mts)

double	getSizeLimitMetric (std::vector< ftm::FTMTree_MT * > &trees)

template<class dataType>
void	copyMinMaxPair (ftm::MergeTree< dataType > &mTree1, ftm::MergeTree< dataType > &mTree2, bool setOrigins=false)

template<class dataType>
std::tuple< int, dataType >	fixMergedRootOrigin (ftm::FTMTree_MT *tree)

template<class dataType>
void	branchDecompositionToTree (ftm::FTMTree_MT *tree)

template<class dataType>
void	putBackMergedNodes (ftm::FTMTree_MT *tree)

template<class dataType>
void	postprocessingPipeline (ftm::FTMTree_MT *tree)

template<class dataType>
void	convertBranchDecompositionMatching (ftm::FTMTree_MT tree1, ftm::FTMTree_MT tree2, std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > &outputMatching)

template<class dataType>
void	convertBranchDecompositionMatching (ftm::FTMTree_MT tree1, ftm::FTMTree_MT tree2, std::vector< std::tuple< ftm::idNode, ftm::idNode > > &outputMatching)

template<class dataType>
void	identifyRealMatching (ftm::FTMTree_MT tree1, ftm::FTMTree_MT tree2, std::vector< std::tuple< ftm::idNode, ftm::idNode > > &outputMatching, std::vector< std::tuple< ftm::idNode, ftm::idNode, bool > > &realMatching)

template<class dataType>
dataType	computeDistance (dataType x1, dataType x2, dataType y1, dataType y2, double power=2)

template<class dataType>
dataType	deleteCost (const ftm::FTMTree_MT *tree, ftm::idNode nodeId)

template<class dataType>
dataType	insertCost (const ftm::FTMTree_MT *tree, ftm::idNode nodeId)

template<class dataType>
dataType	relabelCostOnly (const ftm::FTMTree_MT tree1, ftm::idNode nodeId1, const ftm::FTMTree_MT tree2, ftm::idNode nodeId2)

template<class dataType>
dataType	relabelCost (const ftm::FTMTree_MT tree1, ftm::idNode nodeId1, const ftm::FTMTree_MT tree2, ftm::idNode nodeId2)

void	getParamNames (std::vector< std::string > &paramNames)

double	getParamValueFromName (std::string &paramName)

void	setParamValueFromName (std::string &paramName, double value)

void	getTreesStats (std::vector< ftm::FTMTree_MT * > &trees, std::array< double, 3 > &stats)

void	printTreesStats (std::vector< ftm::FTMTree_MT * > &trees)

template<class dataType>
void	printTreesStats (std::vector< ftm::MergeTree< dataType > > &trees)

template<class dataType>
void	printTableVector (std::vector< std::vector< dataType > > &table)

template<class dataType>
void	printTable (dataType *table, int nRows, int nCols)

void	printMatching (std::vector< MatchingType > &matchings)

void	printMatching (std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > &matchings)

void	printMatching (std::vector< std::tuple< ftm::idNode, ftm::idNode > > &matchings)

template<class dataType>
void	printPairs (std::vector< std::tuple< SimplexId, SimplexId, dataType > > &treePairs)

template<class dataType>
void	printOutputMatching (std::vector< std::tuple< ftm::idNode, ftm::idNode > > &outputMatching, ftm::FTMTree_MT tree1, ftm::FTMTree_MT tree2, bool computeCosts=true)

Protected Attributes
unsigned int	minIteration_ = 0

unsigned int	maxIteration_ = 0

unsigned int	iterationGap_ = 100

double	batchSize_ = 1

int	optimizer_ = 0

double	gradientStepSize_ = 0.1

double	beta1_ = 0.9

double	beta2_ = 0.999

unsigned int	noInit_ = 4

bool	activateOutputInit_ = false

double	originPrimeSizePercent_ = 15

double	trainTestSplit_ = 1.0

bool	shuffleBeforeSplit_ = true

bool	createOutput_ = true

std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > >	originsMatchings_

std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > >	reconstMatchings_

std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > >	customMatchings_

std::vector< std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > > >	dataMatchings_

unsigned	noLayers_

float	bestLoss_

std::vector< unsigned int >	clusterAsgn_

std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > >	baryMatchings_L0_

std::vector< std::vector< std::tuple< ftm::idNode, ftm::idNode, double > > >	baryMatchings2_L0_

std::vector< double >	inputToBaryDistances_L0_

std::vector< std::vector< double > >	branchesCorrelationMatrix_

std::vector< std::vector< double > >	persCorrelationMatrix_

double	t_allVectorCopy_time_ = 0.0

std::vector< unsigned int >	originsNoZeroGrad_

std::vector< unsigned int >	originsPrimeNoZeroGrad_

std::vector< unsigned int >	vSNoZeroGrad_

std::vector< unsigned int >	vSPrimeNoZeroGrad_

std::vector< unsigned int >	origins2NoZeroGrad_

std::vector< unsigned int >	origins2PrimeNoZeroGrad_

std::vector< unsigned int >	vS2NoZeroGrad_

std::vector< unsigned int >	vS2PrimeNoZeroGrad_

Protected Attributes inherited from ttk::Debug
int	debugLevel_

std::string	debugMsgPrefix_

std::string	debugMsgNamePrefix_

Protected Attributes inherited from ttk::BaseClass
bool	lastObject_

int	threadNumber_

Wrapper *	wrapper_

Protected Attributes inherited from ttk::MergeTreeNeuralBase
double	dropout_ = 0.0

bool	euclideanVectorsInit_ = false

bool	randomAxesInit_ = false

bool	initBarycenterRandom_ = false

bool	initBarycenterOneIter_ = false

bool	initOriginPrimeStructByCopy_ = true

bool	initOriginPrimeValuesByCopy_ = true

double	initOriginPrimeValuesByCopyRandomness_ = 0.0

bool	activate_ = true

unsigned int	activationFunction_ = 1

bool	useGpu_ = false

float	bigValuesThreshold_ = 0

Protected Attributes inherited from ttk::MergeTreeAxesAlgorithmBase
bool	deterministic_ = true

unsigned int	numberOfAxes_ = 2

unsigned int	k_ = 16

double	barycenterSizeLimitPercent_ = 20.0

bool	probabilisticVectorsInit_ = false

std::vector< std::vector< int > >	trees2NodeCorr_

Protected Attributes inherited from ttk::MergeTreeBase
int	assignmentSolverID_ = 0

bool	epsilon1UseFarthestSaddle_ = false

double	epsilonTree1_ = 0

double	epsilonTree2_ = 0

double	epsilon2Tree1_ = 100

double	epsilon2Tree2_ = 100

double	epsilon3Tree1_ = 100

double	epsilon3Tree2_ = 100

double	persistenceThreshold_ = 0

bool	barycenterMergeTree_ = false

bool	useMinMaxPair_ = true

bool	deleteMultiPersPairs_ = false

bool	branchDecomposition_ = true

int	wassersteinPower_ = 2

bool	normalizedWasserstein_ = true

bool	keepSubtree_ = false

double	nonMatchingWeight_ = 1.0

bool	distanceSquaredRoot_ = true

bool	useFullMerge_ = false

bool	isPersistenceDiagram_ = false

bool	convertToDiagram_ = false

double	mixtureCoefficient_ = 0.5

bool	useDoubleInput_ = false

bool	parallelize_ = true

int	nodePerTask_ = 32

bool	cleanTree_ = true

std::vector< std::vector< int > >	treesNodeCorr_

Additional Inherited Members
Protected Member Functions inherited from ttk::Debug
int	printMsgInternal (const std::string &msg, const std::string &right, const std::string &filler, const debug::Priority &priority=debug::Priority::INFO, const debug::LineMode &lineMode=debug::LineMode::NEW, std::ostream &stream=std::cout) const

int	printMsgInternal (const std::string &msg, const debug::Priority &priority, const debug::LineMode &lineMode, std::ostream &stream=std::cout) const

int	welcomeMsg (std::ostream &stream)

Static Protected Attributes inherited from ttk::Debug
static COMMON_EXPORTS debug::LineMode	lastLineMode = ttk::debug::LineMode::NEW

Detailed Description

The MergeTreeNeuralNetwork class provides methods to define a neural network able to process merge trees or persistence diagrams.

Author: Mathieu Pont mathi.nosp@m.eu.p.nosp@m.ont@l.nosp@m.ip6..nosp@m.fr

Date: 2023.

This module defines the MergeTreeNeuralNetwork class providing functions to define a neural network able to process merge trees or persistence diagrams.

This is an abstract class, to implement a derived class you need to define the following functions:

"initParameters" : initializes the network, like the different layers. A strategy to initialize a sequence of layers consist in initializing a first layer with the input topological representations, then pass them through this layer to initialize the second one and so on. A simple loop (whose number of iterations corresponds to the number of layers) can do this using the "initInputBasis" and the "initOutputBasis" function, then the "initGetReconstructed" function to pass the representations to the layer that just have been initialized.
"initResetOutputBasis" : please refer to the documentation of this function.
"customInit" : called just before the "initStep" function (that call the "initParameters" function), is is intended to do custom operations depending on the architecture and the optimization you want to define (such as computing the distance matrix for the metric loss in the autoencoder case). This function can be empty.
"backwardStep" : optimizes the parameters of the network. A loss using differentiable torch operations should be computed using the output of some layers of the network (usually the output of the last layer but it can also be any other layers). You can either use the torch coordinates of the representations in a layer or their torch tensors to compute the loss. Then use the torch::Tensor "backward" function to compute the gradients, then the torch::optim::Optimizer "step" function to update the model parameters, after this, the torch::optim::Optimizer "zero_grad" function should be called to reset the gradient. If you have correctly created the MergeTreeNeuralLayer objects (refer to the corresponding class documentation), basically by calling the "requires_grad" function (with true as parameter) for each layer after initializing its parameters, then everything would be automatically handled to backpropagate the gradient of the loss through the layers.
"addCustomParameters" : adds custom parameters to the parameter list that will be given to the optimizer, depending on the architecture and the optimization you want to define (such as the centroids for the cluster loss in the autoencoder case). This function can be empty.
"computeOneLoss" : computes the loss for one input topological representation, the loss computed here does not need to be differentiable because it will only be used to print it in the console and to check convergence of the method (i.e. it is not called in the "backwardStep" function).
"computeCustomLosses" : computes custom losses for all input topological representations depending on the architecture and the optimization you want to define (such as the clustering and the metric loss in the autoendoer case). Like "computeOneLoss", the losses do not need to be differentiable because they will only be used to print them in the console and to check convergence of the method. This function can be empty.
"computeIterationTotalLoss"
"printCustomLosses" : prints the custom loss depending on the architecture and the optimization you want to define (such as the clustering and the metric loss in the autoendoer case). This function can be empty.
"printGapLoss" : prints the "gap" loss, the aggregated loss over iterationGap_ iterations.
"copyCustomParams" : copy the custom parameters (for instance to save them when a better loss is reached during the optimization) depending on the architecture and the optimization you want to define (such as the centroids for the cluster loss in the autoencoder case). This function can be empty.
"executeEndFunction" : does specific operations at the end of the optimization, such as calling the "computeTrackingInformation" and the "computeCorrelationMatrix" functions.

Related publication:
"Wasserstein Auto-Encoders of Merge Trees (and Persistence Diagrams)"
Mathieu Pont, Julien Tierny.
IEEE Transactions on Visualization and Computer Graphics, 2023

Definition at line 106 of file MergeTreeNeuralNetwork.h.

Constructor & Destructor Documentation

◆ MergeTreeNeuralNetwork()

ttk::MergeTreeNeuralNetwork::MergeTreeNeuralNetwork ( )

Definition at line 8 of file MergeTreeNeuralNetwork.cpp.

Member Function Documentation

◆ execute()

void ttk::MergeTreeNeuralNetwork::execute	(	std::vector< ftm::MergeTree< float > > &	trees,
		std::vector< ftm::MergeTree< float > > &	trees2 )

Definition at line 1210 of file MergeTreeNeuralNetwork.cpp.

Member Data Documentation

◆ activateOutputInit_

bool ttk::MergeTreeNeuralNetwork::activateOutputInit_ = false

protected

Definition at line 131 of file MergeTreeNeuralNetwork.h.

◆ baryMatchings2_L0_

std::vector<std::vector<std::tuple<ftm::idNode, ftm::idNode, double> > > ttk::MergeTreeNeuralNetwork::baryMatchings2_L0_

protected

Definition at line 166 of file MergeTreeNeuralNetwork.h.

◆ baryMatchings_L0_

std::vector<std::vector<std::tuple<ftm::idNode, ftm::idNode, double> > > ttk::MergeTreeNeuralNetwork::baryMatchings_L0_

protected

Definition at line 166 of file MergeTreeNeuralNetwork.h.

◆ batchSize_

double ttk::MergeTreeNeuralNetwork::batchSize_ = 1

protected

Definition at line 117 of file MergeTreeNeuralNetwork.h.

◆ bestLoss_

float ttk::MergeTreeNeuralNetwork::bestLoss_

protected

Definition at line 163 of file MergeTreeNeuralNetwork.h.

◆ beta1_

double ttk::MergeTreeNeuralNetwork::beta1_ = 0.9

protected

Definition at line 126 of file MergeTreeNeuralNetwork.h.

◆ beta2_

double ttk::MergeTreeNeuralNetwork::beta2_ = 0.999

protected

Definition at line 127 of file MergeTreeNeuralNetwork.h.

◆ branchesCorrelationMatrix_

std::vector<std::vector<double> > ttk::MergeTreeNeuralNetwork::branchesCorrelationMatrix_

protected

Definition at line 168 of file MergeTreeNeuralNetwork.h.

◆ clusterAsgn_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::clusterAsgn_

protected

Definition at line 164 of file MergeTreeNeuralNetwork.h.

◆ createOutput_

bool ttk::MergeTreeNeuralNetwork::createOutput_ = true

protected

Definition at line 140 of file MergeTreeNeuralNetwork.h.

◆ customMatchings_

std::vector<std::vector<std::tuple<ftm::idNode, ftm::idNode, double> > > ttk::MergeTreeNeuralNetwork::customMatchings_

protected

Definition at line 156 of file MergeTreeNeuralNetwork.h.

◆ dataMatchings_

std::vector< std::vector<std::vector<std::tuple<ftm::idNode, ftm::idNode, double> > > > ttk::MergeTreeNeuralNetwork::dataMatchings_

protected

Definition at line 159 of file MergeTreeNeuralNetwork.h.

◆ gradientStepSize_

double ttk::MergeTreeNeuralNetwork::gradientStepSize_ = 0.1

protected

Definition at line 124 of file MergeTreeNeuralNetwork.h.

◆ inputToBaryDistances_L0_

std::vector<double> ttk::MergeTreeNeuralNetwork::inputToBaryDistances_L0_

protected

Definition at line 167 of file MergeTreeNeuralNetwork.h.

◆ iterationGap_

unsigned int ttk::MergeTreeNeuralNetwork::iterationGap_ = 100

protected

Definition at line 115 of file MergeTreeNeuralNetwork.h.

◆ maxIteration_

unsigned int ttk::MergeTreeNeuralNetwork::maxIteration_ = 0

protected

Definition at line 113 of file MergeTreeNeuralNetwork.h.

◆ minIteration_

unsigned int ttk::MergeTreeNeuralNetwork::minIteration_ = 0

protected

Definition at line 111 of file MergeTreeNeuralNetwork.h.

◆ noInit_

unsigned int ttk::MergeTreeNeuralNetwork::noInit_ = 4

protected

Definition at line 129 of file MergeTreeNeuralNetwork.h.

◆ noLayers_

unsigned ttk::MergeTreeNeuralNetwork::noLayers_

protected

Definition at line 162 of file MergeTreeNeuralNetwork.h.

◆ optimizer_

int ttk::MergeTreeNeuralNetwork::optimizer_ = 0

protected

Definition at line 122 of file MergeTreeNeuralNetwork.h.

◆ originPrimeSizePercent_

double ttk::MergeTreeNeuralNetwork::originPrimeSizePercent_ = 15

protected

Definition at line 134 of file MergeTreeNeuralNetwork.h.

◆ origins2NoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::origins2NoZeroGrad_

protected

Definition at line 174 of file MergeTreeNeuralNetwork.h.

◆ origins2PrimeNoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::origins2PrimeNoZeroGrad_

protected

Definition at line 175 of file MergeTreeNeuralNetwork.h.

◆ originsMatchings_

std::vector<std::vector<std::tuple<ftm::idNode, ftm::idNode, double> > > ttk::MergeTreeNeuralNetwork::originsMatchings_

protected

Definition at line 156 of file MergeTreeNeuralNetwork.h.

◆ originsNoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::originsNoZeroGrad_

protected

Definition at line 173 of file MergeTreeNeuralNetwork.h.

◆ originsPrimeNoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::originsPrimeNoZeroGrad_

protected

Definition at line 173 of file MergeTreeNeuralNetwork.h.

◆ persCorrelationMatrix_

std::vector<std::vector<double> > ttk::MergeTreeNeuralNetwork::persCorrelationMatrix_

protected

Definition at line 169 of file MergeTreeNeuralNetwork.h.

◆ reconstMatchings_

std::vector<std::vector<std::tuple<ftm::idNode, ftm::idNode, double> > > ttk::MergeTreeNeuralNetwork::reconstMatchings_

protected

Definition at line 156 of file MergeTreeNeuralNetwork.h.

◆ shuffleBeforeSplit_

bool ttk::MergeTreeNeuralNetwork::shuffleBeforeSplit_ = true

protected

Definition at line 138 of file MergeTreeNeuralNetwork.h.

◆ t_allVectorCopy_time_

double ttk::MergeTreeNeuralNetwork::t_allVectorCopy_time_ = 0.0

protected

Definition at line 172 of file MergeTreeNeuralNetwork.h.

◆ trainTestSplit_

double ttk::MergeTreeNeuralNetwork::trainTestSplit_ = 1.0

protected

Definition at line 136 of file MergeTreeNeuralNetwork.h.

◆ vS2NoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::vS2NoZeroGrad_

protected

Definition at line 175 of file MergeTreeNeuralNetwork.h.

◆ vS2PrimeNoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::vS2PrimeNoZeroGrad_

protected

Definition at line 175 of file MergeTreeNeuralNetwork.h.

◆ vSNoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::vSNoZeroGrad_

protected

Definition at line 174 of file MergeTreeNeuralNetwork.h.

◆ vSPrimeNoZeroGrad_

std::vector<unsigned int> ttk::MergeTreeNeuralNetwork::vSPrimeNoZeroGrad_

protected

Definition at line 174 of file MergeTreeNeuralNetwork.h.

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

/home/julien/Pro/git/github/thomas/ttk-dani/core/base/mergeTreeNeuralNetwork/MergeTreeNeuralNetwork.h
/home/julien/Pro/git/github/thomas/ttk-dani/core/base/mergeTreeNeuralNetwork/MergeTreeNeuralNetwork.cpp

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ MergeTreeNeuralNetwork()

Member Function Documentation

◆ execute()

Member Data Documentation

◆ activateOutputInit_

◆ baryMatchings2_L0_

◆ baryMatchings_L0_

◆ batchSize_

◆ bestLoss_

◆ beta1_

◆ beta2_

◆ branchesCorrelationMatrix_

◆ clusterAsgn_

◆ createOutput_

◆ customMatchings_

◆ dataMatchings_

◆ gradientStepSize_

◆ inputToBaryDistances_L0_

◆ iterationGap_

◆ maxIteration_

◆ minIteration_

◆ noInit_

◆ noLayers_

◆ optimizer_

◆ originPrimeSizePercent_

◆ origins2NoZeroGrad_

◆ origins2PrimeNoZeroGrad_

◆ originsMatchings_

◆ originsNoZeroGrad_

◆ originsPrimeNoZeroGrad_

◆ persCorrelationMatrix_

◆ reconstMatchings_

◆ shuffleBeforeSplit_

◆ t_allVectorCopy_time_

◆ trainTestSplit_

◆ vS2NoZeroGrad_

◆ vS2PrimeNoZeroGrad_

◆ vSNoZeroGrad_

◆ vSPrimeNoZeroGrad_