nnp Namespace Reference

Namespaces
namespace	settings

Classes
struct	Atom
	Storage for a single atom. More...
class	CompactFunction
	A general function with compact support. More...
class	CoreFunction
class	CutoffFunction
class	Dataset
	Collect and process large data sets. More...
class	Element
	Contains element-specific data. More...
class	ElementCabana
	Derived Cabana class for element-specific data. More...
class	ElementMap
	Contains element map. More...
struct	ErfcBuf
	Helper class to store previously calculated values of erfc() that are needed during the charge equilibration. More...
struct	EwaldGlobalSettings
struct	EwaldParameters
class	EwaldSetup
	Setup data for Ewald summation. More...
class	EwaldStructureData
class	EwaldTruncJackson
class	EwaldTruncKolafaFixR
class	EwaldTruncKolafaOptEta
class	GradientDescent
	Weight updates based on simple gradient descent methods. More...
class	IEwaldTrunc
class	InterfaceLammps
class	KalmanFilter
	Implementation of the Kalman filter method. More...
class	KspaceGrid
class	Kvector
class	Log
	Logging class for library output. More...
class	Mode
	Base class for all NNP applications. More...
class	ModeCabana
	Derived Cabana main NNP class. More...
class	NeuralNetwork
	This class implements a feed-forward neural network. More...
class	Prediction
class	ScreeningFunction
	A screening functions for use with electrostatics. More...
class	SetupAnalysis
class	Stopwatch
	Implements a simple stopwatch on different platforms. More...
struct	Structure
	Storage for one atomic configuration. More...
class	SymFnc
	Symmetry function base class. More...
class	SymFncBaseComp
	Symmetry function base class for SFs with compact support. More...
class	SymFncBaseCompAng
	Intermediate symmetry function class for angular SFs with compact support. More...
class	SymFncBaseCompAngWeighted
	Intermediate symmetry function class for weighted angular compact SFs. More...
class	SymFncBaseCutoff
	Intermediate class for SFs based on cutoff functions. More...
class	SymFncBaseExpAng
	Intermediate class for angular SFs based on cutoffs and exponentials. More...
class	SymFncCompAngn
	Narrow angular symmetry function with compact support (type 21) More...
class	SymFncCompAngnWeighted
	Weighted narrow angular symmetry function with compact support (type 24) More...
class	SymFncCompAngw
	Wide angular symmetry function with compact support (type 22) More...
class	SymFncCompAngwWeighted
	Weighted wide angular symmetry function with compact support (type 25) More...
class	SymFncCompRad
	Radial symmetry function with compact support (type 20) More...
class	SymFncCompRadWeighted
	Weighted radial symmetry function with compact support (type 23) More...
class	SymFncExpAngn
	Angular symmetry function (type 3) More...
class	SymFncExpAngnWeighted
	Weighted angular symmetry function (type 13) More...
class	SymFncExpAngw
	Angular symmetry function (type 9) More...
class	SymFncExpRad
	Radial symmetry function (type 2) More...
class	SymFncExpRadWeighted
	Weighted radial symmetry function (type 12) More...
class	SymFncStatistics
class	SymGrp
class	SymGrpBaseComp
class	SymGrpBaseCompAng
class	SymGrpBaseCompAngWeighted
class	SymGrpBaseCutoff
class	SymGrpBaseExpAng
class	SymGrpCompAngn
	Narrow angular symmetry function with compact support (type 21) More...
class	SymGrpCompAngnWeighted
	Weighted narrow angular symmetry function with compact support (type 24) More...
class	SymGrpCompAngw
	Wide angular symmetry function with compact support (type 22) More...
class	SymGrpCompAngwWeighted
	Weighted wide angular symmetry function with compact support (type 25) More...
class	SymGrpCompRad
	Radial symmetry function with compact support (type 20) More...
class	SymGrpCompRadWeighted
	Weighted radial symmetry function with compact support (type 23) More...
class	SymGrpExpAngn
	Angular symmetry function group (type 3) More...
class	SymGrpExpAngnWeighted
	Weighted angular symmetry function group (type 13) More...
class	SymGrpExpAngw
	Angular symmetry function group (type 3) More...
class	SymGrpExpRad
	Radial symmetry function group (type 2) More...
class	SymGrpExpRadWeighted
	Weighted radial symmetry function group (type 12) More...
class	Training
	Training methods. More...
class	Updater
	Base class for different weight update methods. More...
struct	Vec3D
	Vector in 3 dimensional real space. More...

Enumerations
enum class	EWALDTruncMethod { JACKSON_CATLOW , KOLAFA_PERRAM }

Functions
NeuralNetwork::ActivationFunction	activationFromString (std::string c)
	Convert string to activation function. More...
vector< string >	split (std::string const &input, char delimiter=' ')
	Split string at each delimiter. More...
string	trim (std::string const &line, std::string const &whitespace=" \t")
	Remove leading and trailing whitespaces from string. More...
string	reduce (std::string const &line, std::string const &whitespace=" \t", std::string const &fill=" ")
	Replace multiple whitespaces with fill. More...
string	pad (string const &input, size_t num, char fill, bool right)
string	strpr (const char *format,...)
	String version of printf function. More...
string	cap (std::string word)
	Capitalize first letter of word. More...
vector< string >	createFileHeader (vector< string > const &title, vector< size_t > const &colSize, vector< string > const &colName, vector< string > const &colInfo, char const &commentChar)
void	appendLinesToFile (std::ofstream &file, std::vector< std::string > const lines)
	Append multiple lines of strings to open file stream. More...
void	appendLinesToFile (FILE *const &file, std::vector< std::string > const lines)
	Append multiple lines of strings to open file pointer. More...
map< size_t, vector< double > >	readColumnsFromFile (string fileName, vector< size_t > columns, char comment)
double	pow_int (double x, int n)
	Integer version of power function, "fast exponentiation algorithm". More...
std::string	pad (std::string const &input, std::size_t num, char fill=' ', bool right=true)
	Pad string to given length with fill character. More...
std::vector< std::string >	createFileHeader (std::vector< std::string > const &title, std::vector< std::size_t > const &colLength, std::vector< std::string > const &colName, std::vector< std::string > const &colInfo, char const &commentChar='#')
	Generate output file header with info section and column labels. More...
std::map< std::size_t, std::vector< double > >	readColumnsFromFile (std::string fileName, std::vector< std::size_t > columns, char comment='#')
	Read multiple columns of data from file. More...
template<typename K , typename V >
V const &	safeFind (std::map< K, V > const &stdMap, typename std::map< K, V >::key_type const &key)
	Safely access map entry. More...
template<typename T >
bool	vectorContains (std::vector< T > const &stdVec, T value)
	Test if vector contains specified value. More...
template<typename T , typename U >
bool	unorderedMapContainsKey (std::unordered_map< T, U > const &stdMap, T key)
	Test if unordered map contains specified key. More...
template<typename T >
bool	comparePointerTargets (T *lhs, T *rhs)
	Compare pointer targets. More...
Vec3D	operator+ (Vec3D lhs, Vec3D const &rhs)
	Overload + operator to implement vector addition. More...
Vec3D	operator- (Vec3D lhs, Vec3D const &rhs)
	Overload - operator to implement vector subtraction. More...
Vec3D	operator- (Vec3D v)
	Overload - operator to implement vector sign change. More...
Vec3D	operator* (Vec3D v, double const a)
	Overload * operator to implement multiplication with scalar. More...
Vec3D	operator* (Vec3D const (&A)[3], Vec3D v)
	Overload * operator to implement (left) multiplication with a matrix. More...
Vec3D	operator/ (Vec3D v, double const a)
	Overload / operator to implement division by scalar. More...
Vec3D	operator* (double const a, Vec3D v)
	Overload * operator to implement multiplication with scalar (scalar first). More...

Variables
double constexpr	TrOverTk = 3.676

Enumeration Type Documentation

EWALDTruncMethod

enum class nnp::EWALDTruncMethod

strong

Enumerator
JACKSON_CATLOW	Method 0: Used by RuNNer (DOI: 10.1080/08927028808080944).
KOLAFA_PERRAM	Method 1: Optimized in n2p2 (DOI: 10.1080/08927029208049126).

Definition at line 29 of file EwaldSetup.h.

                            {
    JACKSON_CATLOW,
    KOLAFA_PERRAM
};

Function Documentation

activationFromString()

NeuralNetwork::ActivationFunction nnp::activationFromString

(

std::string

c

)

Convert string to activation function.

Parameters

[in]

letter

String representing activation function.

Returns

Activation corresponding to string.

Definition at line 1078 of file NeuralNetwork.cpp.

{
    NeuralNetwork::ActivationFunction a;
 
    if      (c == "l") a = NeuralNetwork::AF_IDENTITY;
    else if (c == "t") a = NeuralNetwork::AF_TANH;
    else if (c == "s") a = NeuralNetwork::AF_LOGISTIC;
    else if (c == "p") a = NeuralNetwork::AF_SOFTPLUS;
    else if (c == "r") a = NeuralNetwork::AF_RELU;
    else if (c == "g") a = NeuralNetwork::AF_GAUSSIAN;
    else if (c == "c") a = NeuralNetwork::AF_COS;
    else if (c == "S") a = NeuralNetwork::AF_REVLOGISTIC;
    else if (c == "e") a = NeuralNetwork::AF_EXP;
    else if (c == "h") a = NeuralNetwork::AF_HARMONIC;
    else
    {
        throw runtime_error("ERROR: Unknown activation function.\n");
    }
 
    return a;
}

References nnp::NeuralNetwork::AF_COS, nnp::NeuralNetwork::AF_EXP, nnp::NeuralNetwork::AF_GAUSSIAN, nnp::NeuralNetwork::AF_HARMONIC, nnp::NeuralNetwork::AF_IDENTITY, nnp::NeuralNetwork::AF_LOGISTIC, nnp::NeuralNetwork::AF_RELU, nnp::NeuralNetwork::AF_REVLOGISTIC, nnp::NeuralNetwork::AF_SOFTPLUS, and nnp::NeuralNetwork::AF_TANH.

Referenced by nnp::Mode::setupNeuralNetwork().

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split()

std::vector< std::string > nnp::split	(	std::string const &	input,
		char	delimiter = ' '
	)

Split string at each delimiter.

Parameters

[in]	input	Input string.
[in]	delimiter	Delimiter character (default ' ').

Returns

Vector containing the string parts.

Definition at line 33 of file utility.cpp.

{
    vector<string> parts;
    stringstream ss;
 
    ss.str(input);
    string item;
    while (getline(ss, item, delimiter)) {
        parts.push_back(item);
    }
 
    return parts;
}

Referenced by nnp::SymFnc::addCacheIndex(), nnp::Element::addSymmetryFunction(), nnp::ElementCabana::addSymmetryFunction(), nnp::Training::dataSetNormalization(), nnp::Dataset::getNumStructures(), nnp::InterfaceLammps::initialize(), main(), readColumnsFromFile(), nnp::Structure::readFromFile(), nnp::Structure::readFromLines(), nnp::ElementMap::registerElements(), nnp::SymFncBaseCompAng::setParameters(), nnp::SymFncBaseCompAngWeighted::setParameters(), nnp::SymFncBaseExpAng::setParameters(), nnp::SymFncCompRad::setParameters(), nnp::SymFncCompRadWeighted::setParameters(), nnp::SymFncExpAngnWeighted::setParameters(), nnp::SymFncExpRad::setParameters(), nnp::SymFncExpRadWeighted::setParameters(), nnp::SymFnc::setScalingType(), nnp::ElementCabana::setScalingType(), nnp::Mode::setupCutoff(), nnp::Mode::setupElectrostatics(), nnp::ModeCabana< t_device >::setupElementMap(), nnp::Mode::setupElements(), nnp::ModeCabana< t_device >::setupElements(), nnp::Training::setupFileOutput(), nnp::Mode::setupNeuralNetwork(), nnp::ModeCabana< t_device >::setupNeuralNetwork(), nnp::ModeCabana< t_device >::setupNeuralNetworkWeights(), nnp::Training::setupSelectionMode(), nnp::Mode::setupSymmetryFunctionCache(), nnp::Mode::setupSymmetryFunctions(), nnp::ModeCabana< t_device >::setupSymmetryFunctions(), and nnp::Structure::writeToFilePoscar().

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trim()

std::string nnp::trim	(	std::string const &	line,
		std::string const &	whitespace = " \t"
	)

Remove leading and trailing whitespaces from string.

Parameters

[in]	line	Input string.
[in]	whitespace	All characters identified as whitespace (default: " \t").

Returns

String without leading and trailing whitespaces.

Definition at line 47 of file utility.cpp.

{
    size_t const begin = line.find_first_not_of(whitespace);
    if (begin == string::npos)
    {
        return "";
    }
    size_t const end = line.find_last_not_of(whitespace);
    size_t const range = end - begin + 1;
 
    return line.substr(begin, range);
}

Referenced by nnp::InterfaceLammps::initialize(), and reduce().

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reduce()

std::string nnp::reduce	(	std::string const &	line,
		std::string const &	whitespace = " \t",
		std::string const &	fill = " "
	)

Replace multiple whitespaces with fill.

Parameters

[in]	line	Input string.
[in]	whitespace	All characters identified as whitespace (default: " \t").
[in]	fill	Replacement character (default: " ").

Returns

String with fill replacements.

Calls trim() at the beginning.

Definition at line 60 of file utility.cpp.

{
    string result = trim(line, whitespace);
 
    size_t begin = result.find_first_of(whitespace);
    while (begin != string::npos)
    {
        size_t const end = result.find_first_not_of(whitespace, begin);
        size_t const range = end - begin;
        result.replace(begin, range, fill);
        size_t const newBegin = begin + fill.length();
        begin = result.find_first_of(whitespace, newBegin);
    }
 
    return result;
}

References trim().

Referenced by nnp::Element::addSymmetryFunction(), nnp::ElementCabana::addSymmetryFunction(), nnp::Dataset::getNumStructures(), nnp::InterfaceLammps::initialize(), main(), nnp::settings::Settings::parseLines(), readColumnsFromFile(), nnp::Structure::readFromFile(), nnp::Structure::readFromLines(), nnp::ElementMap::registerElements(), nnp::SymFncBaseCompAng::setParameters(), nnp::SymFncBaseCompAngWeighted::setParameters(), nnp::SymFncBaseExpAng::setParameters(), nnp::SymFncCompRad::setParameters(), nnp::SymFncCompRadWeighted::setParameters(), nnp::SymFncExpAngnWeighted::setParameters(), nnp::SymFncExpRad::setParameters(), nnp::SymFncExpRadWeighted::setParameters(), nnp::SymFnc::setScalingType(), nnp::ElementCabana::setScalingType(), nnp::Mode::setupElectrostatics(), nnp::ModeCabana< t_device >::setupElementMap(), nnp::Mode::setupElements(), nnp::ModeCabana< t_device >::setupElements(), nnp::Training::setupFileOutput(), nnp::Mode::setupNeuralNetwork(), nnp::ModeCabana< t_device >::setupNeuralNetwork(), nnp::ModeCabana< t_device >::setupNeuralNetworkWeights(), nnp::Mode::setupSymmetryFunctions(), and nnp::ModeCabana< t_device >::setupSymmetryFunctions().

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pad() [1/2]

string nnp::pad	(	string const &	input,
		size_t	num,
		char	fill,
		bool	right
	)

Definition at line 79 of file utility.cpp.

{
    string result = input;
 
    if (input.size() >= num) return result;
 
    string pad(num - input.size(), fill);
    if (right) return result + pad;
    else return pad + result;
}

References pad().

Referenced by pad(), nnp::SymFnc::parameterInfo(), nnp::SymFncBaseComp::parameterInfo(), nnp::SymFncBaseCompAng::parameterInfo(), nnp::SymFncBaseCompAngWeighted::parameterInfo(), nnp::SymFncBaseCutoff::parameterInfo(), nnp::SymFncBaseExpAng::parameterInfo(), nnp::SymFncCompRad::parameterInfo(), nnp::SymFncExpAngnWeighted::parameterInfo(), nnp::SymFncExpRad::parameterInfo(), and nnp::SymFncExpRadWeighted::parameterInfo().

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strpr()

std::string nnp::strpr	(	const char *	format,
			...
	)

String version of printf function.

Definition at line 90 of file utility.cpp.

{
    char buffer[STRPR_MAXBUF];
 
    va_list args;
    va_start(args, format);
    vsprintf(buffer, format, args);
    va_end(args);
 
    string s(buffer);
 
    return s;
}

References STRPR_MAXBUF.

Referenced by nnp::SymFnc::addCacheIndex(), nnp::Training::addTrainingLogEntry(), nnp::Training::allocateArrays(), nnp::Training::calculateError(), nnp::Training::calculateErrorEpoch(), nnp::Training::calculateNeighborLists(), nnp::Mode::calculateSymmetryFunctionGroups(), nnp::Mode::calculateSymmetryFunctions(), nnp::Training::checkSelectionMode(), nnp::Dataset::collectSymmetryFunctionStatistics(), nnp::Dataset::combineFiles(), nnp::Training::dataSetNormalization(), nnp::Dataset::distributeStructures(), nnp::SymFncBaseCompAng::getCacheIdentifiers(), nnp::SymFncBaseCompAngWeighted::getCacheIdentifiers(), nnp::SymFncBaseExpAng::getCacheIdentifiers(), nnp::SymFncCompRad::getCacheIdentifiers(), nnp::SymFncCompRadWeighted::getCacheIdentifiers(), nnp::SymFncExpAngnWeighted::getCacheIdentifiers(), nnp::SymFncExpRad::getCacheIdentifiers(), nnp::SymFncExpRadWeighted::getCacheIdentifiers(), nnp::Atom::getChargeLine(), nnp::ElementMap::getElementsString(), nnp::Structure::getEnergyLine(), nnp::SymFncStatistics::getExtrapolationWarningLines(), nnp::Atom::getForcesLines(), nnp::SymFncBaseCompAng::getSettingsLine(), nnp::SymFncBaseCompAngWeighted::getSettingsLine(), nnp::SymFncBaseExpAng::getSettingsLine(), nnp::SymFncCompRad::getSettingsLine(), nnp::SymFncCompRadWeighted::getSettingsLine(), nnp::SymFncExpAngnWeighted::getSettingsLine(), nnp::SymFncExpRad::getSettingsLine(), nnp::SymFncExpRadWeighted::getSettingsLine(), nnp::Atom::Neighbor::info(), nnp::Atom::info(), nnp::CoreFunction::info(), nnp::ElementMap::info(), nnp::NeuralNetwork::info(), nnp::ScreeningFunction::info(), nnp::Structure::info(), nnp::GradientDescent::info(), nnp::KalmanFilter::info(), nnp::InterfaceLammps::initialize(), nnp::Training::initializeWeightsMemory(), nnp::Mode::loadSettingsFile(), nnp::EwaldSetup::logEwaldCutoffs(), nnp::Training::loop(), main(), nnp::SymFnc::parameterInfo(), nnp::SymFncBaseComp::parameterInfo(), nnp::SymFncBaseCompAng::parameterInfo(), nnp::SymFncBaseCompAngWeighted::parameterInfo(), nnp::SymFncBaseCutoff::parameterInfo(), nnp::SymFncBaseExpAng::parameterInfo(), nnp::SymFncCompRad::parameterInfo(), nnp::SymFncExpAngnWeighted::parameterInfo(), nnp::SymFncExpRad::parameterInfo(), nnp::SymFncExpRadWeighted::parameterInfo(), nnp::SymFncBaseCompAng::parameterLine(), nnp::SymFncBaseCompAngWeighted::parameterLine(), nnp::SymFncBaseExpAng::parameterLine(), nnp::SymFncCompRad::parameterLine(), nnp::SymFncCompRadWeighted::parameterLine(), nnp::SymFncExpAngnWeighted::parameterLine(), nnp::SymFncExpRad::parameterLine(), nnp::SymFncExpRadWeighted::parameterLine(), nnp::SymGrpBaseCompAng::parameterLines(), nnp::SymGrpBaseCompAngWeighted::parameterLines(), nnp::SymGrpBaseExpAng::parameterLines(), nnp::SymGrpCompRad::parameterLines(), nnp::SymGrpCompRadWeighted::parameterLines(), nnp::SymGrpExpAngnWeighted::parameterLines(), nnp::SymGrpExpRad::parameterLines(), nnp::SymGrpExpRadWeighted::parameterLines(), nnp::settings::Settings::parseLines(), nnp::Dataset::prepareNumericForces(), nnp::Training::printEpoch(), nnp::Training::printHeader(), nnp::Training::randomizeNeuralNetworkWeights(), nnp::settings::Settings::readFile(), nnp::Mode::readNeuralNetworkWeights(), runTest(), nnp::settings::Settings::sanityCheck(), nnp::SymFnc::scalingLine(), nnp::ElementCabana::scalingLine(), nnp::Training::selectSets(), nnp::SymFncBaseComp::setCompactFunction(), nnp::SymFncBaseCutoff::setCutoffFunction(), nnp::Element::setScalingNone(), nnp::Training::setStage(), nnp::Mode::setupCutoff(), nnp::Mode::setupElectrostatics(), nnp::Mode::setupElementMap(), nnp::ModeCabana< t_device >::setupElementMap(), nnp::Mode::setupElements(), nnp::ModeCabana< t_device >::setupElements(), nnp::Training::setupFileOutput(), nnp::Dataset::setupMPI(), nnp::Mode::setupNeuralNetwork(), nnp::ModeCabana< t_device >::setupNeuralNetwork(), nnp::ModeCabana< t_device >::setupNeuralNetworkWeights(), nnp::Mode::setupNeuralNetworkWeights(), nnp::Mode::setupNormalization(), nnp::Dataset::setupRandomNumberGenerator(), nnp::Training::setupSelectionMode(), nnp::Mode::setupSymmetryFunctionCache(), nnp::Mode::setupSymmetryFunctionGroups(), nnp::ModeCabana< t_device >::setupSymmetryFunctionGroups(), nnp::Mode::setupSymmetryFunctionMemory(), nnp::Mode::setupSymmetryFunctions(), nnp::ModeCabana< t_device >::setupSymmetryFunctions(), nnp::Mode::setupSymmetryFunctionScaling(), nnp::ModeCabana< t_device >::setupSymmetryFunctionScaling(), nnp::Mode::setupSymmetryFunctionStatistics(), nnp::Training::setupTraining(), nnp::Training::setupUpdatePlan(), nnp::GradientDescent::status(), nnp::KalmanFilter::status(), nnp::ElementMap::symbolFromAtomicNumber(), nnp::Element::updateSymmetryFunctionStatistics(), nnp::Dataset::writeAtomicEnvironmentFile(), nnp::NeuralNetwork::writeConnections(), nnp::Training::writeHardness(), nnp::Training::writeHardnessEpoch(), nnp::Training::writeLearningCurve(), nnp::Dataset::writeNeighborHistogram(), nnp::Dataset::writeNeighborLists(), nnp::Training::writeNeuronStatistics(), nnp::Training::writeNeuronStatisticsEpoch(), nnp::Training::writeSetsToFiles(), nnp::Dataset::writeSymmetryFunctionFile(), nnp::Dataset::writeSymmetryFunctionHistograms(), nnp::Dataset::writeSymmetryFunctionScaling(), nnp::SetupAnalysis::writeSymmetryFunctionShape(), nnp::Training::writeTimingData(), nnp::Structure::writeToFile(), nnp::Structure::writeToFilePoscar(), nnp::Structure::writeToFileXyz(), nnp::Training::writeUpdaterStatus(), nnp::Training::writeWeights(), and nnp::Training::writeWeightsEpoch().

cap()

std::string nnp::cap

(

std::string

word

)

Capitalize first letter of word.

Parameters

[in]

word

String to capitalize.

Returns

Input string with first letter in capital letters.

Definition at line 104 of file utility.cpp.

{
    word[0] = toupper(word[0]);
 
    return word;
}

Referenced by nnp::Mode::setupNeuralNetworkWeights().

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createFileHeader() [1/2]

vector< string > nnp::createFileHeader	(	vector< string > const &	title,
		vector< size_t > const &	colSize,
		vector< string > const &	colName,
		vector< string > const &	colInfo,
		char const &	commentChar
	)

Definition at line 111 of file utility.cpp.

{
    size_t const stdWidth = 80;
    vector<string> h;
    if (!(colSize.size() == colName.size() &&
          colName.size() == colInfo.size()))
    {
        throw runtime_error("ERROR: Could not create file header, column sizes"
                            " are not equal.\n");
    }
    size_t numCols = colSize.size();
 
    // Separator line definition.
    string sepLine(stdWidth, commentChar);
    sepLine += '\n';
    // Start string.
    string startStr(1, commentChar);
 
    // Add title lines.
    h.push_back(sepLine);
    for (vector<string>::const_iterator it = title.begin();
         it != title.end(); ++it)
    {
        h.push_back(startStr + ' ' + (*it) + '\n');
    }
    h.push_back(sepLine);
 
    // Determine maximum width of names.
    size_t widthNames = 0;
    for (vector<string>::const_iterator it = colName.begin();
         it != colName.end(); ++it)
    {
        widthNames = max(widthNames, it->size());
    }
 
    // Column description section.
    stringstream s;
    s << startStr << ' '
      << left << setw(4) << "Col" << ' '
      << left << setw(widthNames) << "Name" << ' '
      << left << "Description\n";
    h.push_back(s.str());
    h.push_back(sepLine);
    for (size_t i = 0; i < numCols; ++i)
    {
        s.clear();
        s.str(string());
        s << startStr << ' '
          << left << setw(4) << i + 1 << ' '
          << left << setw(widthNames) << colName.at(i) << ' '
          << colInfo.at(i) << '\n';
        h.push_back(s.str());
    }
 
    // Determine total data width.
    size_t widthData = 0;
    for (vector<size_t>::const_iterator it = colSize.begin();
         it != colSize.end(); ++it)
    {
        widthData += (*it) + 1;
    }
    widthData -= 1;
 
    if (widthData > stdWidth)
    {
        // Long separator line.
        h.push_back(string(widthData, commentChar) + "\n");
    }
    else
    {
        h.push_back(sepLine);
    }
 
    // Write column number.
    s.clear();
    s.str(string());
    s << startStr;
    for (size_t i = 0; i < numCols; ++i)
    {
        size_t n = colSize.at(i);
        if (i == 0) n -= 2;
        s << ' ' << right << setw(n) << i + 1;
    }
    s << '\n';
    h.push_back(s.str());
 
    // Write column name.
    s.clear();
    s.str(string());
    s << startStr;
    for (size_t i = 0; i < numCols; ++i)
    {
        size_t n = colSize.at(i);
        if (i == 0) n -= 2;
        string name = colName.at(i);
        if (name.size() > n)
        {
            name.erase(n, string::npos);
        }
        s << ' ' << right << setw(n) << name;
    }
    s << '\n';
    h.push_back(s.str());
 
    // Long separator line.
    h.push_back(string(widthData, commentChar) + "\n");
 
    return h;
}

Referenced by nnp::Training::calculateError(), nnp::Training::dataSetNormalization(), main(), nnp::Training::setupTraining(), nnp::GradientDescent::statusHeader(), nnp::KalmanFilter::statusHeader(), nnp::NeuralNetwork::writeConnections(), nnp::Training::writeLearningCurve(), nnp::Dataset::writeNeighborHistogram(), nnp::Training::writeNeuronStatistics(), nnp::Dataset::writeSymmetryFunctionHistograms(), nnp::Dataset::writeSymmetryFunctionScaling(), nnp::SetupAnalysis::writeSymmetryFunctionShape(), and nnp::Training::writeTimingData().

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appendLinesToFile() [1/2]

void nnp::appendLinesToFile	(	std::ofstream &	file,
		std::vector< std::string > const	lines
	)

Append multiple lines of strings to open file stream.

Parameters

[in,out]	file	File stream to append lines to.
[in]	lines	Vector of strings with line content.

Definition at line 225 of file utility.cpp.

{
    for (vector<string>::const_iterator it = lines.begin();
         it != lines.end(); ++it)
    {
        file << (*it);
    }
 
    return;
}

Referenced by nnp::Training::calculateError(), nnp::Training::dataSetNormalization(), main(), nnp::Training::setupTraining(), nnp::NeuralNetwork::writeConnections(), nnp::Training::writeLearningCurve(), nnp::Dataset::writeNeighborHistogram(), nnp::Training::writeNeuronStatistics(), nnp::Dataset::writeSymmetryFunctionHistograms(), nnp::Dataset::writeSymmetryFunctionScaling(), nnp::SetupAnalysis::writeSymmetryFunctionShape(), nnp::Training::writeTimingData(), and nnp::Training::writeUpdaterStatus().

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appendLinesToFile() [2/2]

void nnp::appendLinesToFile	(	FILE *const &	file,
		std::vector< std::string > const	lines
	)

Append multiple lines of strings to open file pointer.

Parameters

[in,out]	file	File pointer.
[in]	lines	Vector of strings with line content.

Definition at line 236 of file utility.cpp.

{
    for (vector<string>::const_iterator it = lines.begin();
         it != lines.end(); ++it)
    {
        fprintf(file, "%s", it->c_str());
    }
 
    return;
}

readColumnsFromFile() [1/2]

map< size_t, vector< double > > nnp::readColumnsFromFile	(	string	fileName,
		vector< size_t >	columns,
		char	comment
	)

Definition at line 247 of file utility.cpp.

{
    map<size_t, vector<double>> result;
 
    sort(columns.begin(), columns.end());
    for (auto col : columns)
    {
        result[col] = vector<double>();
    }
 
    ifstream file;
    file.open(fileName.c_str());
    if (!file.is_open())
    {
        throw runtime_error("ERROR: Could not open file: \"" + fileName
                            + "\".\n");
    }
    string line;
    while (getline(file, line))
    {
        if (line.size() == 0) continue;
        if (line.at(0) != comment)
        {
            vector<string> splitLine = split(reduce(line));
            for (auto col : columns)
            {
                if (col >= splitLine.size())
                {
                    result[col].push_back(
                        std::numeric_limits<double>::quiet_NaN());
                }
                else
                {
                    result[col].push_back(atof(splitLine.at(col).c_str()));
                }
            }
        }
    }
    file.close();
 
    return result;
}

References reduce(), and split().

Referenced by nnp::Mode::readNeuralNetworkWeights(), and nnp::Mode::setupElectrostatics().

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pow_int()

double nnp::pow_int	(	double	x,
		int	n
	)

Integer version of power function, "fast exponentiation algorithm".

Parameters

[in]	x	Base number.
[in]	n	Integer exponent.

Returns

x^n

Definition at line 292 of file utility.cpp.

{
    // Need an unsigned integer for bit-shift divison.
    unsigned int m;
 
    // If negative exponent, take the inverse of x and change sign of n.
    if (n < 0)
    {
        x = 1.0 / x;
        m = -n;
    }
    else m = n;
 
    // Exponentiation by squaring, "fast exponentiation algorithm"
    double result = 1.0;
    do
    {
        if (m & 1) result *= x;
        // Division by 2.
        m >>= 1;
        x *= x;
    }
    while (m);
 
    return result;
}

Referenced by nnp::SymFncExpAngn::calculate(), nnp::SymFncExpAngnWeighted::calculate(), nnp::SymFncExpAngw::calculate(), nnp::SymGrpExpAngn::calculate(), nnp::SymGrpExpAngnWeighted::calculate(), and nnp::SymGrpExpAngw::calculate().

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pad() [2/2]

std::string nnp::pad	(	std::string const &	input,
		std::size_t	num,
		char	fill = ' ',
		bool	right = true
	)

Pad string to given length with fill character.

Parameters

[in]	input	Input string.
[in]	num	Desired width of padded string.
[in]	fill	Padding character.
[in]	right	If true, pad right. Pad left otherwise.

Returns

String padded to desired length or original string if length of old string is not shorter than desired length.

createFileHeader() [2/2]

std::vector< std::string > nnp::createFileHeader	(	std::vector< std::string > const &	title,
		std::vector< std::size_t > const &	colLength,
		std::vector< std::string > const &	colName,
		std::vector< std::string > const &	colInfo,
		char const &	commentChar = '#'
	)

Generate output file header with info section and column labels.

Parameters

[in]	title	Multiple lines of title text.
[in]	colLength	Length of the individual columns.
[in]	colName	Names of the individual columns.
[in]	colInfo	Description of the individual columns.
[in]	commentChar	Character used for starting each line and to create separator lines.

Returns

Vector of strings, one entry per line.

readColumnsFromFile() [2/2]

std::map< std::size_t, std::vector< double > > nnp::readColumnsFromFile	(	std::string	fileName,
		std::vector< std::size_t >	columns,
		char	comment = '#'
	)

Read multiple columns of data from file.

Parameters

[in]	fileName	Name of data file.
[in]	columns	Vector with column indices of interest (starting with 0).
[in]	comment	Lines starting with comment sign are ignored.

Returns

Map from column index to vector of data.

safeFind()

template<typename K , typename V >

V const & nnp::safeFind	(	std::map< K, V > const &	stdMap,
		typename std::map< K, V >::key_type const &	key
	)

Safely access map entry.

Parameters

[in]	stdMap	Map to search in.
[in]	key	Key requested.

The .at() member function of maps is available only for C++11.

Definition at line 144 of file utility.h.

{
    if (stdMap.find(key) == stdMap.end())
    {
        std::stringstream message;
        message << "ERROR: No map entry found for key \"";
        message << key;
        message << "\".\n";
        throw std::range_error(message.str());
    }
    return stdMap.find(key)->second;
}

Referenced by nnp::SymFnc::getPrintFormat(), nnp::SymGrp::getPrintFormatCommon(), nnp::SymGrp::getPrintFormatMember(), nnp::ElementMap::index(), nnp::ElementMap::symbol(), and nnp::Dataset::writeSymmetryFunctionHistograms().

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vectorContains()

template<typename T >

bool nnp::vectorContains	(	std::vector< T > const &	stdVec,
		T	value
	)

Test if vector contains specified value.

Parameters

[in]	stdVec	Vector to search in.
[in]	value	Value to search for.

Returns

True if value is located in vector.

Definition at line 166 of file utility.h.

{
    return (std::find(stdVec.begin(), stdVec.end(), value) != stdVec.end());
}

Referenced by nnp::Element::getCutoffRadii(), nnp::Mode::setupCutoffMatrix(), and nnp::Structure::setupNeighborCutoffMap().

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unorderedMapContainsKey()

template<typename T , typename U >

bool nnp::unorderedMapContainsKey	(	std::unordered_map< T, U > const &	stdMap,
		T	key
	)

Test if unordered map contains specified key.

Parameters

[in]	stdMap	Map to search in.
[in]	key	Key to search for.

Returns

True if key is located in map.

Definition at line 179 of file utility.h.

{
    return ( stdMap.find(key) != stdMap.end() );
}

Referenced by nnp::Atom::calculateNumNeighbors(), and nnp::Atom::getStoredMinNumNeighbors().

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comparePointerTargets()

template<typename T >

bool nnp::comparePointerTargets	(	T *	lhs,
		T *	rhs
	)

Compare pointer targets.

Parameters

[in]	lhs	Pointer to left side of comparison.
[in]	rhs	Pointer to right side of comparison.

Returns

True if dereferenced lhs < dereferenced rhs, False otherwise.

Definition at line 194 of file utility.h.

{
    return ((*lhs) < (*rhs));
}

operator+()

Vec3D nnp::operator+ ( Vec3D  lhs, Vec3D const &  rhs  )

inline

Overload + operator to implement vector addition.

Returns

Sum of two vectors.

Definition at line 330 of file Vec3D.h.

{
    return lhs += rhs;
}

operator-() [1/2]

Vec3D nnp::operator- ( Vec3D  lhs, Vec3D const &  rhs  )

inline

Overload - operator to implement vector subtraction.

Returns

Difference between two vectors.

Definition at line 335 of file Vec3D.h.

{
    return lhs -= rhs;
}

operator-() [2/2]

Vec3D nnp::operator- ( Vec3D  v )

inline

Overload - operator to implement vector sign change.

Returns

Negative vector.

Definition at line 340 of file Vec3D.h.

{
    v *= -1.0;
    return v;
}

operator*() [1/3]

Vec3D nnp::operator* ( Vec3D  v, double const  a  )

inline

Overload * operator to implement multiplication with scalar.

Returns

Vector multiplied with scalar.

Definition at line 346 of file Vec3D.h.

{
    return v *= a;
}

operator*() [2/3]

Vec3D nnp::operator* ( Vec3D const (&)  A[3], Vec3D  v  )

inline

Overload * operator to implement (left) multiplication with a matrix.

Returns

Vector multiplied with a matrix.

Definition at line 361 of file Vec3D.h.

{
    return v *= A;
}

operator/()

Vec3D nnp::operator/ ( Vec3D  v, double const  a  )

inline

Overload / operator to implement division by scalar.

Returns

Vector divided by scalar.

Definition at line 351 of file Vec3D.h.

{
    return v /= a;
}

operator*() [3/3]

Vec3D nnp::operator* ( double const  a, Vec3D  v  )

inline

Overload * operator to implement multiplication with scalar (scalar first).

Returns

Vector multiplied with scalar.

Definition at line 356 of file Vec3D.h.

{
    return v *= a;
}

Variable Documentation

TrOverTk

double constexpr nnp::TrOverTk = 3.676

constexpr

Definition at line 14 of file EwaldTruncKolafaOptEta.cpp.

Referenced by nnp::EwaldTruncKolafaOptEta::calculateEta().