#include <kedf_ml.h>

Collaboration diagram for KEDF_ML:

Public Member Functions
	KEDF_ML ()

	~KEDF_ML ()

void	set_para (const int nx, const double dV, const double nelec, const double tf_weight, const double vw_weight, const double chi_p, const double chi_q, const std::vector< double > &chi_xi, const std::vector< double > &chi_pnl, const std::vector< double > &chi_qnl, const int &nkernel, const std::vector< int > &kernel_type, const std::vector< double > &kernel_scaling, const std::vector< double > &yukawa_alpha, const std::vector< std::string > &kernel_file, const bool &of_ml_gamma, const bool &of_ml_p, const bool &of_ml_q, const bool &of_ml_tanhp, const bool &of_ml_tanhq, const std::vector< int > &of_ml_gammanl, const std::vector< int > &of_ml_pnl, const std::vector< int > &of_ml_qnl, const std::vector< int > &of_ml_xi, const std::vector< int > &of_ml_tanhxi, const std::vector< int > &of_ml_tanhxi_nl, const std::vector< int > &of_ml_tanh_pnl, const std::vector< int > &of_ml_tanh_qnl, const std::vector< int > &of_ml_tanhp_nl, const std::vector< int > &of_ml_tanhq_nl, const std::string device_inpt, ModulePW::PW_Basis *pw_rho)

void	set_device (std::string device_inpt)
	Set the device for ML KEDF.

double	get_energy (const double const prho, ModulePW::PW_Basis *pw_rho)
	Get the energy of ML KEDF.

void	ml_potential (const double const prho, ModulePW::PW_Basis *pw_rho, ModuleBase::matrix &rpotential)
	Get the potential of ML KEDF, and add it into rpotential.

void	generateTrainData (const double const prho, ModulePW::PW_Basis pw_rho, const double veff)
	Generate training data for ML KEDF.

void	localTest (const double const prho, ModulePW::PW_Basis *pw_rho)
	For test.

void	NN_forward (const double const prho, ModulePW::PW_Basis *pw_rho, bool cal_grad)
	Interface to Neural Network forward.

void	get_potential_ (const double const prho, ModulePW::PW_Basis *pw_rho, ModuleBase::matrix &rpotential)
	Calculate the Pauli potential of ML KEDF.

double	potGammaTerm (int ir)

double	potPTerm1 (int ir)

double	potQTerm1 (int ir)

double	potXiTerm1 (int ir)

double	potTanhxiTerm1 (int ir)

double	potTanhpTerm1 (int ir)

double	potTanhqTerm1 (int ir)

void	potGammanlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rGammanlTerm)

void	potXinlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rXinlTerm)

void	potTanhxinlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rTanhxinlTerm)

void	potTanhxi_nlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rTanhxi_nlTerm)

void	potPPnlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rPPnlTerm)

void	potQQnlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rQQnlTerm)

void	potTanhpTanh_pnlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rTanhpTanh_pnlTerm)

void	potTanhqTanh_qnlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rTanhqTanh_qnlTerm)

void	potTanhpTanhp_nlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rTanhpTanhp_nlTerm)

void	potTanhqTanhq_nlTerm (const double const prho, ModulePW::PW_Basis *pw_rho, std::vector< double > &rTanhqTanhq_nlTerm)

void	loadVector (std::string filename, std::vector< double > &data)

void	dumpVector (std::string filename, const std::vector< double > &data)

void	dumpTensor (std::string filename, const torch::Tensor &data)
	Dump the torch::Tensor into .npy file.

void	dumpMatrix (std::string filename, const ModuleBase::matrix &data)
	Dump the matrix into .npy file.

void	updateInput (const double const prho, ModulePW::PW_Basis *pw_rho)
	Update the desciptors for ML KEDF.

void	init_data (const int &nkernel, const bool &of_ml_gamma, const bool &of_ml_p, const bool &of_ml_q, const bool &of_ml_tanhp, const bool &of_ml_tanhq, const std::vector< int > &of_ml_gammanl_, const std::vector< int > &of_ml_pnl, const std::vector< int > &of_ml_qnl, const std::vector< int > &of_ml_xi, const std::vector< int > &of_ml_tanhxi, const std::vector< int > &of_ml_tanhxi_nl, const std::vector< int > &of_ml_tanh_pnl, const std::vector< int > &of_ml_tanh_qnl, const std::vector< int > &of_ml_tanhp_nl, const std::vector< int > &of_ml_tanhq_nl)
	Initialize the data for ML KEDF, and generate the mapping between descriptor and kernel.

torch::Tensor	get_data (std::string parameter, const int ikernel)
	Return the descriptors for ML KEDF.

Public Attributes
ModuleIO::Cal_MLKEDF_Descriptors *	cal_tool = nullptr

int	nx = 0

int	nx_tot = 0

double	dV = 0.

const double	cTF = 3.0/10.0 * std::pow(3std::pow(M_PI, 2.0), 2.0/3.0) 2

const double	pqcoef = 1.0 / (4.0 * std::pow(3*std::pow(M_PI, 2.0), 2.0/3.0))

double	ml_energy = 0.

double	feg_net_F = 0.

double	feg3_correct = 0.541324854612918

int	ninput = 0

std::vector< double >	gamma = {}

std::vector< double >	p = {}

std::vector< double >	q = {}

std::vector< std::vector< double > >	gammanl = {}

std::vector< std::vector< double > >	pnl = {}

std::vector< std::vector< double > >	qnl = {}

std::vector< std::vector< double > >	nablaRho = {}

std::vector< double >	chi_xi = {1.0}

double	chi_p = 1.

double	chi_q = 1.

std::vector< std::vector< double > >	xi = {}

std::vector< std::vector< double > >	tanhxi = {}

std::vector< std::vector< double > >	tanhxi_nl = {}

std::vector< double >	tanhp = {}

std::vector< double >	tanhq = {}

std::vector< double >	chi_pnl = {1.0}

std::vector< double >	chi_qnl = {1.0}

std::vector< std::vector< double > >	tanh_pnl = {}

std::vector< std::vector< double > >	tanh_qnl = {}

std::vector< std::vector< double > >	tanhp_nl = {}

std::vector< std::vector< double > >	tanhq_nl = {}

torch::DeviceType	device_type = torch::kCPU

torch::Device	device = torch::Device(torch::kCPU)

torch::Device	device_CPU = torch::Device(torch::kCPU)

std::shared_ptr< NN_OFImpl >	nn

double *	enhancement_cpu_ptr = nullptr

double *	gradient_cpu_ptr = nullptr

int	nkernel = 1

bool	ml_gamma = false

bool	ml_p = false

bool	ml_q = false

bool	ml_tanhp = false

bool	ml_tanhq = false

bool	ml_gammanl = false

bool	ml_pnl = false

bool	ml_qnl = false

bool	ml_xi = false

bool	ml_tanhxi = false

bool	ml_tanhxi_nl = false

bool	ml_tanh_pnl = false

bool	ml_tanh_qnl = false

bool	ml_tanhp_nl = false

bool	ml_tanhq_nl = false

std::vector< std::string >	descriptor_type = {}

std::vector< int >	kernel_index = {}

std::map< std::string, std::vector< int > >	descriptor2kernel = {}

std::map< std::string, std::vector< int > >	descriptor2index = {}

std::map< std::string, std::vector< bool > >	gene_data_label = {}

Constructor & Destructor Documentation

◆ KEDF_ML()

KEDF_ML::KEDF_ML ( )

inline

◆ ~KEDF_ML()

KEDF_ML::~KEDF_ML ( )

inline

Member Function Documentation

◆ dumpMatrix()

void KEDF_ML::dumpMatrix	(	std::string	filename,
		const ModuleBase::matrix &	data
	)

Dump the matrix into .npy file.

Parameters

data	matrix
filename	file name

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◆ dumpTensor()

void KEDF_ML::dumpTensor	(	std::string	filename,
		const torch::Tensor &	data
	)

Dump the torch::Tensor into .npy file.

Parameters

data	torch::Tensor
filename	file name

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◆ dumpVector()

void KEDF_ML::dumpVector	(	std::string	filename,
		const std::vector< double > &	data
	)

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◆ generateTrainData()

void KEDF_ML::generateTrainData	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		const double *	veff
	)

Generate training data for ML KEDF.

Parameters

prho	charge density
wt	KEDF_WT
tf	KEDF_TF
pw_rho	PW_Basis
veff	effective potential

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◆ get_data()

torch::Tensor KEDF_ML::get_data	(	std::string	parameter,
		const int	ikernel
	)

Return the descriptors for ML KEDF.

Parameters

parameter	"gamma", "p", "q", "tanhp", "tanhq", "gammanl", "pnl", "qnl", "xi", "tanhxi", "tanhxi_nl", "tanh_pnl", "tanh_qnl", "tanhp_nl", "tanhq_nl"
ikernel	kernel index

◆ get_energy()

double KEDF_ML::get_energy	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho
	)

Get the energy of ML KEDF.

$E_{ML} = c_{TF} * \int{F(\rho) \rho^{5/3} dr}$

Parameters

prho	charge density
pw_rho	PW_Basis

Returns: the energy of ML KEDF

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◆ get_potential_()

void KEDF_ML::get_potential_	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		ModuleBase::matrix &	rpotential
	)

Calculate the Pauli potential of ML KEDF.

Parameters

prho	charge density
pw_rho	PW_Basis
rpotential	rpotential => rpotential + V_{ML}

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◆ init_data()

void KEDF_ML::init_data	(	const int &	nkernel,
		const bool &	of_ml_gamma,
		const bool &	of_ml_p,
		const bool &	of_ml_q,
		const bool &	of_ml_tanhp,
		const bool &	of_ml_tanhq,
		const std::vector< int > &	of_ml_gammanl,
		const std::vector< int > &	of_ml_pnl,
		const std::vector< int > &	of_ml_qnl,
		const std::vector< int > &	of_ml_xi,
		const std::vector< int > &	of_ml_tanhxi,
		const std::vector< int > &	of_ml_tanhxi_nl,
		const std::vector< int > &	of_ml_tanh_pnl,
		const std::vector< int > &	of_ml_tanh_qnl,
		const std::vector< int > &	of_ml_tanhp_nl,
		const std::vector< int > &	of_ml_tanhq_nl
	)

Initialize the data for ML KEDF, and generate the mapping between descriptor and kernel.

Parameters

nkernel	number of kernels
of_ml_gamma	whether to use gamma descriptor
of_ml_p	whether to use p descriptor
of_ml_q	whether to use q descriptor
of_ml_tanhp	whether to use tanhp descriptor
of_ml_tanhq	whether to use tanhq descriptor
of_ml_gammanl	whether to use gammanl descriptor
of_ml_pnl	whether to use pnl descriptor
of_ml_qnl	whether to use qnl descriptor
of_ml_xi	whether to use xi descriptor
of_ml_tanhxi	whether to use tanhxi descriptor
of_ml_tanhxi_nl	whether to use tanhxi_nl descriptor
of_ml_tanh_pnl	whether to use tanh_pnl descriptor
of_ml_tanh_qnl	whether to use tanh_qnl descriptor
of_ml_tanhp_nl	whether to use tanhp_nl descriptor
of_ml_tanhq_nl	whether to use tanhq_nl descriptor

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◆ loadVector()

void KEDF_ML::loadVector	(	std::string	filename,
		std::vector< double > &	data
	)

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◆ localTest()

void KEDF_ML::localTest	(	const double const	pprho,
		ModulePW::PW_Basis *	pw_rho
	)

For test.

Parameters

prho	charge density
pw_rho	PW_Basis

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◆ ml_potential()

void KEDF_ML::ml_potential	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		ModuleBase::matrix &	rpotential
	)

Get the potential of ML KEDF, and add it into rpotential.

Parameters

prho	charge density
pw_rho	PW_Basis
rpotential	rpotential => rpotential + V_{ML}

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◆ NN_forward()

void KEDF_ML::NN_forward	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		bool	cal_grad
	)

Interface to Neural Network forward.

Parameters

prho	charge density
pw_rho	PW_Basis
cal_grad	whether to calculate the gradient

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◆ potGammanlTerm()

void KEDF_ML::potGammanlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rGammanlTerm
	)

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◆ potGammaTerm()

double KEDF_ML::potGammaTerm ( int ir )

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◆ potPPnlTerm()

void KEDF_ML::potPPnlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rPPnlTerm
	)

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◆ potPTerm1()

double KEDF_ML::potPTerm1 ( int ir )

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◆ potQQnlTerm()

void KEDF_ML::potQQnlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rQQnlTerm
	)

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◆ potQTerm1()

double KEDF_ML::potQTerm1 ( int ir )

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◆ potTanhpTanh_pnlTerm()

void KEDF_ML::potTanhpTanh_pnlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rTanhpTanh_pnlTerm
	)

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◆ potTanhpTanhp_nlTerm()

void KEDF_ML::potTanhpTanhp_nlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rTanhpTanhp_nlTerm
	)

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◆ potTanhpTerm1()

double KEDF_ML::potTanhpTerm1 ( int ir )

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◆ potTanhqTanh_qnlTerm()

void KEDF_ML::potTanhqTanh_qnlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rTanhqTanh_qnlTerm
	)

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◆ potTanhqTanhq_nlTerm()

void KEDF_ML::potTanhqTanhq_nlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rTanhqTanhq_nlTerm
	)

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◆ potTanhqTerm1()

double KEDF_ML::potTanhqTerm1 ( int ir )

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◆ potTanhxi_nlTerm()

void KEDF_ML::potTanhxi_nlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rTanhxi_nlTerm
	)

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◆ potTanhxinlTerm()

void KEDF_ML::potTanhxinlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rTanhxinlTerm
	)

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◆ potTanhxiTerm1()

double KEDF_ML::potTanhxiTerm1 ( int ir )

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◆ potXinlTerm()

void KEDF_ML::potXinlTerm	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho,
		std::vector< double > &	rXinlTerm
	)

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◆ potXiTerm1()

double KEDF_ML::potXiTerm1 ( int ir )

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◆ set_device()

void KEDF_ML::set_device ( std::string device_inpt )

Set the device for ML KEDF.

Parameters

device_inpt "cpu" or "gpu"

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◆ set_para()

void KEDF_ML::set_para	(	const int	nx,
		const double	dV,
		const double	nelec,
		const double	tf_weight,
		const double	vw_weight,
		const double	chi_p,
		const double	chi_q,
		const std::vector< double > &	chi_xi,
		const std::vector< double > &	chi_pnl,
		const std::vector< double > &	chi_qnl,
		const int &	nkernel,
		const std::vector< int > &	kernel_type,
		const std::vector< double > &	kernel_scaling,
		const std::vector< double > &	yukawa_alpha,
		const std::vector< std::string > &	kernel_file,
		const bool &	of_ml_gamma,
		const bool &	of_ml_p,
		const bool &	of_ml_q,
		const bool &	of_ml_tanhp,
		const bool &	of_ml_tanhq,
		const std::vector< int > &	of_ml_gammanl,
		const std::vector< int > &	of_ml_pnl,
		const std::vector< int > &	of_ml_qnl,
		const std::vector< int > &	of_ml_xi,
		const std::vector< int > &	of_ml_tanhxi,
		const std::vector< int > &	of_ml_tanhxi_nl,
		const std::vector< int > &	of_ml_tanh_pnl,
		const std::vector< int > &	of_ml_tanh_qnl,
		const std::vector< int > &	of_ml_tanhp_nl,
		const std::vector< int > &	of_ml_tanhq_nl,
		const std::string	device_inpt,
		ModulePW::PW_Basis *	pw_rho
	)

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◆ updateInput()

void KEDF_ML::updateInput	(	const double const	prho,
		ModulePW::PW_Basis *	pw_rho
	)

Update the desciptors for ML KEDF.

Parameters

prho	charge density
pw_rho	PW_Basis

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Member Data Documentation

◆ cal_tool

ModuleIO::Cal_MLKEDF_Descriptors* KEDF_ML::cal_tool = nullptr

◆ chi_p

double KEDF_ML::chi_p = 1.

◆ chi_pnl

std::vector<double> KEDF_ML::chi_pnl = {1.0}

◆ chi_q

double KEDF_ML::chi_q = 1.

◆ chi_qnl

std::vector<double> KEDF_ML::chi_qnl = {1.0}

◆ chi_xi

std::vector<double> KEDF_ML::chi_xi = {1.0}

◆ cTF

const double KEDF_ML::cTF = 3.0/10.0 * std::pow(3*std::pow(M_PI, 2.0), 2.0/3.0) * 2

◆ descriptor2index

std::map<std::string, std::vector<int> > KEDF_ML::descriptor2index = {}

◆ descriptor2kernel

std::map<std::string, std::vector<int> > KEDF_ML::descriptor2kernel = {}

◆ descriptor_type

std::vector<std::string> KEDF_ML::descriptor_type = {}

◆ device

torch::Device KEDF_ML::device = torch::Device(torch::kCPU)

◆ device_CPU

torch::Device KEDF_ML::device_CPU = torch::Device(torch::kCPU)

◆ device_type

torch::DeviceType KEDF_ML::device_type = torch::kCPU

◆ dV

double KEDF_ML::dV = 0.

◆ enhancement_cpu_ptr

double* KEDF_ML::enhancement_cpu_ptr = nullptr

◆ feg3_correct

double KEDF_ML::feg3_correct = 0.541324854612918

◆ feg_net_F

double KEDF_ML::feg_net_F = 0.

◆ gamma

std::vector<double> KEDF_ML::gamma = {}

◆ gammanl

std::vector<std::vector<double> > KEDF_ML::gammanl = {}

◆ gene_data_label

std::map<std::string, std::vector<bool> > KEDF_ML::gene_data_label = {}

◆ gradient_cpu_ptr

double* KEDF_ML::gradient_cpu_ptr = nullptr

◆ kernel_index

std::vector<int> KEDF_ML::kernel_index = {}

◆ ml_energy

double KEDF_ML::ml_energy = 0.

◆ ml_gamma

bool KEDF_ML::ml_gamma = false

◆ ml_gammanl

bool KEDF_ML::ml_gammanl = false

◆ ml_p

bool KEDF_ML::ml_p = false

◆ ml_pnl

bool KEDF_ML::ml_pnl = false

◆ ml_q

bool KEDF_ML::ml_q = false

◆ ml_qnl

bool KEDF_ML::ml_qnl = false

◆ ml_tanh_pnl

bool KEDF_ML::ml_tanh_pnl = false

◆ ml_tanh_qnl

bool KEDF_ML::ml_tanh_qnl = false

◆ ml_tanhp

bool KEDF_ML::ml_tanhp = false

◆ ml_tanhp_nl

bool KEDF_ML::ml_tanhp_nl = false

◆ ml_tanhq

bool KEDF_ML::ml_tanhq = false

◆ ml_tanhq_nl

bool KEDF_ML::ml_tanhq_nl = false

◆ ml_tanhxi

bool KEDF_ML::ml_tanhxi = false

◆ ml_tanhxi_nl

bool KEDF_ML::ml_tanhxi_nl = false

◆ ml_xi

bool KEDF_ML::ml_xi = false

◆ nablaRho

std::vector<std::vector<double> > KEDF_ML::nablaRho = {}

◆ ninput

int KEDF_ML::ninput = 0

◆ nkernel

int KEDF_ML::nkernel = 1

◆ nn

std::shared_ptr<NN_OFImpl> KEDF_ML::nn

◆ nx

int KEDF_ML::nx = 0

◆ nx_tot

int KEDF_ML::nx_tot = 0

◆ p

std::vector<double> KEDF_ML::p = {}

◆ pnl

std::vector<std::vector<double> > KEDF_ML::pnl = {}

◆ pqcoef

const double KEDF_ML::pqcoef = 1.0 / (4.0 * std::pow(3*std::pow(M_PI, 2.0), 2.0/3.0))

◆ q

std::vector<double> KEDF_ML::q = {}

◆ qnl

std::vector<std::vector<double> > KEDF_ML::qnl = {}

◆ tanh_pnl

std::vector<std::vector<double> > KEDF_ML::tanh_pnl = {}

◆ tanh_qnl

std::vector<std::vector<double> > KEDF_ML::tanh_qnl = {}

◆ tanhp

std::vector<double> KEDF_ML::tanhp = {}

◆ tanhp_nl

std::vector<std::vector<double> > KEDF_ML::tanhp_nl = {}

◆ tanhq

std::vector<double> KEDF_ML::tanhq = {}

◆ tanhq_nl

std::vector<std::vector<double> > KEDF_ML::tanhq_nl = {}

◆ tanhxi

std::vector<std::vector<double> > KEDF_ML::tanhxi = {}

◆ tanhxi_nl

std::vector<std::vector<double> > KEDF_ML::tanhxi_nl = {}

◆ xi

std::vector<std::vector<double> > KEDF_ML::xi = {}

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

/home/runner/work/abacus-develop/abacus-develop/source/source_pw/module_ofdft/kedf_ml.h
/home/runner/work/abacus-develop/abacus-develop/source/source_pw/module_ofdft/kedf_ml.cpp
/home/runner/work/abacus-develop/abacus-develop/source/source_pw/module_ofdft/kedf_ml_label.cpp
/home/runner/work/abacus-develop/abacus-develop/source/source_pw/module_ofdft/kedf_ml_pot.cpp

Public Member Functions

Public Attributes

Constructor & Destructor Documentation

◆ KEDF_ML()

◆ ~KEDF_ML()

Member Function Documentation

◆ dumpMatrix()

◆ dumpTensor()

◆ dumpVector()

◆ generateTrainData()

◆ get_data()

◆ get_energy()

◆ get_potential_()

◆ init_data()

◆ loadVector()

◆ localTest()

◆ ml_potential()

◆ NN_forward()

◆ potGammanlTerm()

◆ potGammaTerm()

◆ potPPnlTerm()

◆ potPTerm1()

◆ potQQnlTerm()

◆ potQTerm1()

◆ potTanhpTanh_pnlTerm()

◆ potTanhpTanhp_nlTerm()

◆ potTanhpTerm1()

◆ potTanhqTanh_qnlTerm()

◆ potTanhqTanhq_nlTerm()

◆ potTanhqTerm1()

◆ potTanhxi_nlTerm()

◆ potTanhxinlTerm()

◆ potTanhxiTerm1()

◆ potXinlTerm()

◆ potXiTerm1()

◆ set_device()

◆ set_para()

◆ updateInput()

Member Data Documentation

◆ cal_tool

◆ chi_p

◆ chi_pnl

◆ chi_q

◆ chi_qnl

◆ chi_xi

◆ cTF

◆ descriptor2index

◆ descriptor2kernel

◆ descriptor_type

◆ device

◆ device_CPU

◆ device_type

◆ dV

◆ enhancement_cpu_ptr

◆ feg3_correct

◆ feg_net_F

◆ gamma

◆ gammanl

◆ gene_data_label

◆ gradient_cpu_ptr

◆ kernel_index

◆ ml_energy

◆ ml_gamma

◆ ml_gammanl

◆ ml_p

◆ ml_pnl

◆ ml_q

◆ ml_qnl

◆ ml_tanh_pnl

◆ ml_tanh_qnl

◆ ml_tanhp

◆ ml_tanhp_nl

◆ ml_tanhq

◆ ml_tanhq_nl

◆ ml_tanhxi

◆ ml_tanhxi_nl

◆ ml_xi

◆ nablaRho

◆ ninput

◆ nkernel