nnp::Training Member List

This is the complete list of members for nnp::Training, including all inherited members.

addEnergyOffset(Structure &structure, bool ref=true)	nnp::Mode
addTrainingLogEntry(int proc, std::size_t il, double f, std::size_t isg, std::size_t is)	nnp::Training	private
addTrainingLogEntry(int proc, std::size_t il, double f, std::size_t isg, std::size_t is, std::size_t ia, std::size_t ic)	nnp::Training	private
addTrainingLogEntry(int proc, std::size_t il, double f, std::size_t isg, std::size_t is, std::size_t ia)	nnp::Training	private
advance() const	nnp::Training	private
allocateArrays(std::string const &property)	nnp::Training	private
calculateAtomicNeuralNetworks(Structure &structure, bool const derivatives, std::string id="")	nnp::Mode
calculateBufferSize(Structure const &structure) const	nnp::Dataset
calculateCharge(Structure &structure) const	nnp::Mode
calculateChargeErrorVec(Structure const &s, Eigen::VectorXd &cVec, double &cNorm)	nnp::Training
calculateEnergy(Structure &structure) const	nnp::Mode
calculateError(std::map< std::string, std::pair< std::string, std::string > > const fileNames)	nnp::Training
calculateErrorEpoch()	nnp::Training
calculateForces(Structure &structure) const	nnp::Mode
calculateNeighborLists()	nnp::Training
calculateSymmetryFunctionGroups(Structure &structure, bool const derivatives)	nnp::Mode
calculateSymmetryFunctions(Structure &structure, bool const derivatives)	nnp::Mode
calculateWeightDerivatives(Structure *structure)	nnp::Training
calculateWeightDerivatives(Structure *structure, std::size_t atom, std::size_t component)	nnp::Training
chargeEquilibration(Structure &structure, bool const derivativesElec)	nnp::Mode
checkExtrapolationWarnings	nnp::Mode	protected
checkSelectionMode()	nnp::Training
collectDGdxia(Atom const &atom, std::size_t indexAtom, std::size_t indexComponent)	nnp::Training	private
collectError(std::string const &property, std::map< std::string, double > &error, std::size_t &count) const	nnp::Dataset
collectSymmetryFunctionStatistics()	nnp::Dataset
combineFiles(std::string filePrefix) const	nnp::Dataset
comm	nnp::Dataset	protected
convCharge	nnp::Mode	protected
convEnergy	nnp::Mode	protected
convertToNormalizedUnits(Structure &structure) const	nnp::Mode
convertToPhysicalUnits(Structure &structure) const	nnp::Mode
convLength	nnp::Mode	protected
countUpdates	nnp::Training	private
cutoffAlpha	nnp::Mode	protected
cutoffs	nnp::Mode	protected
cutoffType	nnp::Mode	protected
Dataset()	nnp::Dataset
dataSetNormalization()	nnp::Training
dGdxia	nnp::Training	private
distributeStructures(bool randomize, bool excludeRank0=false, std::string const &fileName="input.data")	nnp::Dataset
dPdc(std::string property, Structure &structure, std::vector< std::vector< double > > &dEdc)	nnp::Training
dPdcN(std::string property, Structure &structure, std::vector< std::vector< double > > &dEdc, double delta=1.0E-4)	nnp::Training
elementMap	nnp::Mode
elements	nnp::Mode	protected
epoch	nnp::Training	private
epochSchedule	nnp::Training	private
erfcBuf	nnp::Mode	protected
evaluateNNP(Structure &structure, bool useForces=true, bool useDEdG=true)	nnp::Mode
ewaldSetup	nnp::Mode	protected
forceWeight	nnp::Training	private
fourPiEps	nnp::Mode	protected
freeMemory	nnp::Training	private
getConnectionOffsets(std::string id="short") const	nnp::Training
getConvCharge() const	nnp::Mode	inline
getConvEnergy() const	nnp::Mode	inline
getConvLength() const	nnp::Mode	inline
getEnergyOffset(Structure const &structure) const	nnp::Mode
getEnergyWithOffset(Structure const &structure, bool ref=true) const	nnp::Mode
getEwaldMaxCharge() const	nnp::Mode	inline
getEwaldMaxSigma() const	nnp::Mode	inline
getEwaldPrecision() const	nnp::Mode	inline
getEwaldTruncationMethod() const	nnp::Mode	inline
getMaxCutoffRadius() const	nnp::Mode	inline
getMeanEnergy() const	nnp::Mode	inline
getNnpType() const	nnp::Mode	inline
getNumConnections(std::string id="short") const	nnp::Training
getNumConnectionsPerElement(std::string id="short") const	nnp::Training
getNumElements() const	nnp::Mode	inline
getNumExtrapolationWarnings() const	nnp::Mode
getNumStructures(std::ifstream &dataFile)	nnp::Dataset
getNumSymmetryFunctions() const	nnp::Mode
getScreeningFunction() const	nnp::Mode
getSingleWeight(std::size_t element, std::size_t index)	nnp::Training
getWeights()	nnp::Training	private
hasStructures	nnp::Training	private
hasUpdaters	nnp::Training	private
initialize()	nnp::Mode
initializeWeights()	nnp::Training
initializeWeightsMemory(UpdateStrategy updateStrategy=US_COMBINED)	nnp::Training
JacobianMode enum name	nnp::Training
jacobianMode	nnp::Training	private
JM_FULL enum value	nnp::Training
JM_SUM enum value	nnp::Training
JM_TASK enum value	nnp::Training
kspaceGrid	nnp::Mode	protected
kspaceSolver() const	nnp::Mode	inline
loadSettingsFile(std::string const &fileName="input.nn")	nnp::Mode
log	nnp::Mode
logEwaldCutoffs()	nnp::Mode
loop()	nnp::Training
maxCutoffRadius	nnp::Mode	protected
meanEnergy	nnp::Mode	protected
minCutoffRadius	nnp::Mode	protected
minNeighbors	nnp::Mode	protected
Mode()	nnp::Mode
myName	nnp::Dataset	protected
myRank	nnp::Dataset	protected
nnId	nnp::Training	private
nnk	nnp::Mode	protected
NNPType enum name	nnp::Mode
nnpType	nnp::Mode	protected
nns	nnp::Mode	protected
normalize	nnp::Mode	protected
normalized(std::string const &property, double value) const	nnp::Mode
normalizedEnergy(Structure const &structure, bool ref=true) const	nnp::Mode
numElements	nnp::Mode	protected
numEpochs	nnp::Training	private
numProcs	nnp::Dataset	protected
numStructures	nnp::Dataset	protected
numUpdaters	nnp::Training	private
numWeights	nnp::Training	private
numWeightsPerUpdater	nnp::Training	private
p	nnp::Training	private
ParallelMode enum name	nnp::Training
parallelMode	nnp::Training	private
physical(std::string const &property, double value) const	nnp::Mode
physicalEnergy(Structure const &structure, bool ref=true) const	nnp::Mode
pk	nnp::Training	private
PM_TRAIN_ALL enum value	nnp::Training
PM_TRAIN_RK0 enum value	nnp::Training
prepareNumericForces(Structure &original, double delta)	nnp::Dataset
printEpoch()	nnp::Training
printHeader()	nnp::Training
pruneSymmetryFunctionsRange(double threshold)	nnp::Mode
pruneSymmetryFunctionsSensitivity(double threshold, std::vector< std::vector< double > > sensitivity)	nnp::Mode
randomizeNeuralNetworkWeights(std::string const &id)	nnp::Training	private
readNeuralNetworkWeights(std::string const &id, std::string const &fileName)	nnp::Mode	protected
recvStructure(Structure *structure, int src)	nnp::Dataset
removeEnergyOffset(Structure &structure, bool ref=true)	nnp::Mode
repeatedEnergyUpdates	nnp::Training	private
resetExtrapolationWarnings()	nnp::Mode
resetNeuronStatistics()	nnp::Training
rng	nnp::Dataset	protected
rngGlobal	nnp::Dataset	protected
rngGlobalNew	nnp::Training	private
rngNew	nnp::Training	private
scalingType	nnp::Mode	protected
screeningFunction	nnp::Mode	protected
SelectionMode enum name	nnp::Training
selectSets()	nnp::Training
sendStructure(Structure const &structure, int dest) const	nnp::Dataset
setEpochSchedule()	nnp::Training
setSingleWeight(std::size_t element, std::size_t index, double value)	nnp::Training
setStage(std::size_t stage)	nnp::Training
settings	nnp::Mode	protected
settingsGetValue(std::string const &keyword) const	nnp::Mode
settingsKeywordExists(std::string const &keyword) const	nnp::Mode
setTrainingLogFileName(std::string fileName)	nnp::Training
setupCutoff()	nnp::Mode
setupCutoffMatrix()	nnp::Mode
setupElectrostatics(bool initialHardness=false, std::string directoryPrefix="", std::string fileNameFormat="hardness.%03zu.data")	nnp::Mode	virtual
setupElementMap()	nnp::Mode	virtual
setupElements()	nnp::Mode	virtual
setupFileOutput(std::string const &type)	nnp::Training	private
setupGeneric(std::string const &nnpDir="", bool skipNormalize=false, bool initialHardness=false)	nnp::Mode
setupMPI()	nnp::Dataset
setupMPI(MPI_Comm *communicator)	nnp::Dataset
setupNeuralNetwork()	nnp::Mode	virtual
setupNeuralNetworkWeights(std::map< std::string, std::string > fileNameFormats=std::map< std::string, std::string >())	nnp::Mode	virtual
setupNeuralNetworkWeights(std::string directoryPrefix, std::map< std::string, std::string > fileNameFormats=std::map< std::string, std::string >())	nnp::Mode	virtual
setupNormalization(bool standalone=true)	nnp::Mode
setupNumericDerivCheck()	nnp::Training
setupRandomNumberGenerator()	nnp::Dataset
setupSelectionMode(std::string const &property)	nnp::Training	private
setupSymmetryFunctionCache(bool verbose=false)	nnp::Mode	virtual
setupSymmetryFunctionGroups()	nnp::Mode	virtual
setupSymmetryFunctionMemory(bool verbose=false)	nnp::Mode
setupSymmetryFunctions()	nnp::Mode	virtual
setupSymmetryFunctionScaling(std::string const &fileName="scaling.data")	nnp::Mode	virtual
setupSymmetryFunctionScalingNone()	nnp::Mode
setupSymmetryFunctionStatistics(bool collectStatistics, bool collectExtrapolationWarnings, bool writeExtrapolationWarnings, bool stopOnExtrapolationWarnings)	nnp::Mode
setupTraining()	nnp::Training
setupUpdatePlan(std::string const &property)	nnp::Training	private
setWeights()	nnp::Training	private
shuffleUpdateCandidates(std::string const &property)	nnp::Training
SM_RANDOM enum value	nnp::Training
SM_SORT enum value	nnp::Training
SM_THRESHOLD enum value	nnp::Training
sortNeighborLists()	nnp::Dataset
sortUpdateCandidates(std::string const &property)	nnp::Training
stage	nnp::Training	private
structures	nnp::Dataset
sw	nnp::Training	private
toNormalizedUnits()	nnp::Dataset
toPhysicalUnits()	nnp::Dataset
Training()	nnp::Training
trainingLog	nnp::Training	private
trainingLogFileName	nnp::Training	private
update(std::string const &property)	nnp::Training
updaters	nnp::Training	private
UpdaterType enum name	nnp::Training
updaterType	nnp::Training	private
UpdateStrategy enum name	nnp::Training
updateStrategy	nnp::Training	private
US_COMBINED enum value	nnp::Training
US_ELEMENT enum value	nnp::Training
useForces	nnp::Training	private
useNormalization() const	nnp::Mode	inline
UT_GD enum value	nnp::Training
UT_KF enum value	nnp::Training
UT_LM enum value	nnp::Training
weights	nnp::Training	private
weightsOffset	nnp::Training	private
writeAtomicEnvironmentFile(std::vector< std::vector< std::size_t > > neighCutoff, bool derivatives, std::string const &fileNamePrefix="atomic-env")	nnp::Dataset
writeHardness(std::string const &fileNameFormat) const	nnp::Training
writeHardnessEpoch() const	nnp::Training
writeLearningCurve(bool append, std::string const fileName="learning-curve.out") const	nnp::Training
writeNeighborHistogram(std::string const &fileNameHisto="neighbors.histo", std::string const &fileNameStructure="neighbors.out")	nnp::Dataset
writeNeighborLists(std::string const &fileName="neighbor-list.data")	nnp::Dataset
writeNeuronStatistics(std::string const &nnName, std::string const &fileName) const	nnp::Training
writeNeuronStatisticsAlways	nnp::Training	private
writeNeuronStatisticsEpoch() const	nnp::Training
writeNeuronStatisticsEvery	nnp::Training	private
writePrunedSettingsFile(std::vector< std::size_t > prune, std::string fileName="output.nn") const	nnp::Mode
writeSetsToFiles()	nnp::Training
writeSettingsFile(std::ofstream *const &file) const	nnp::Mode
writeSymmetryFunctionFile(std::string fileName="function.data")	nnp::Dataset
writeSymmetryFunctionHistograms(std::size_t numBins, std::string fileNameFormat="sf.%03zu.%04zu.histo")	nnp::Dataset
writeSymmetryFunctionScaling(std::string const &fileName="scaling.data")	nnp::Dataset
writeTimingData(bool append, std::string const fileName="timing.out")	nnp::Training	private
writeTrainingLog	nnp::Training	private
writeUpdaterStatus(bool append, std::string const fileNameFormat="updater.%03zu.out") const	nnp::Training
writeWeights(std::string const &nnName, std::string const &fileNameFormat) const	nnp::Training
writeWeightsAlways	nnp::Training	private
writeWeightsEpoch() const	nnp::Training
writeWeightsEvery	nnp::Training	private
~Dataset()	nnp::Dataset
~Training()	nnp::Training