Classes
struct	Coords
	This namespace provides useful constants and utility functions. More...

class	Lattice
	This class contains the properties of a three-dimensional lattice and the functions needed to interact with it. More...

class	Morphology
	This class contains a lattice representation of a materials blend with the ability to simulate phase separation and perform a variety of structural analyses. More...

class	Parameters
	This class contains the parameters used by Ising_OPV and functions to import parameter files. More...

class	Version
	This class contains the current version information and version comparison operators. More...

Functions
std::vector< std::pair< double, double > >	calculateCumulativeHist (const std::vector< std::pair< double, double >> &data)
	Calculates the cumulative histogram from the input probability histogram data. More...

std::vector< std::pair< double, int > >	calculateHist (const std::vector< int > &data, int bin_size)
	Calculates the histogram for the input integer data vector using the input bin size. More...

std::vector< std::pair< double, double > >	calculateProbabilityHist (const std::vector< std::pair< double, int >> hist)
	Calculates the probability histogram for the input histogram data vector. The function outputs bin-centered x values and probability y values in a x-y pair vector. More...

std::vector< std::pair< double, double > >	calculateProbabilityHist (const std::vector< int > &data, int bin_size)
	Calculates the probability histogram for the input integer data vector using the input bin size. More...

std::vector< std::pair< double, double > >	calculateProbabilityHist (const std::vector< double > &data, int num_bins)
	Calculates the probability histogram for the input double data vector using the input number of bins. More...

std::vector< std::pair< double, double > >	calculateProbabilityHist (const std::vector< double > &data, double bin_size)
	Calculates the probability histogram for the input data vector using the input bin size. More...

std::vector< std::pair< double, double > >	calculateProbabilityHist (const std::vector< double > &data, const double bin_size, const int num_bins)
	Calculates the probability histogram for the input data vector using the input bin size and input number of bins. More...

std::vector< std::pair< double, double > >	calculateProbabilityHist (const std::vector< double > &data, const double bin_start, const double bin_size)
	Calculates the probability histogram for the input data vector using the input bin start value and bin size. More...

double	integrateData (const std::vector< std::pair< double, double >> &data)
	Numerically integrates a vector of x-y data using the trapezoid rule. More...

double	interpolateData (const std::vector< std::pair< double, double >> &data, const double x_val)
	Linearly interpolates an x-y data set to determine the interpolated y-value corresponding to an input x-value. More...

std::vector< std::pair< double, double > >	MPI_calculateProbHistAvg (const std::vector< std::pair< double, int >> &input_hist)
	Uses MPI to calculate the average probability histogram from separate histograms coming from different processors. More...

std::vector< double >	MPI_calculateVectorAvg (const std::vector< double > &input_vector)
	Uses MPI to calculate the element-wise average vector from separate vectors coming from different processors. More...

std::vector< double >	MPI_calculateVectorSum (const std::vector< double > &input_vector)
	Uses MPI to calculate the element-wise sum vector from separate equally sized vectors coming from different processors. More...

std::vector< int >	MPI_calculateVectorSum (const std::vector< int > &input_vector)
	Uses MPI to calculate the element-wise sum vector from separate vectors coming from different processors. More...

std::vector< int >	MPI_gatherValues (const int input_val)
	Uses MPI to gather integer values from separate processors to build one vector containing all of the data. More...

std::vector< double >	MPI_gatherValues (const double input_val)
	Uses MPI to gather double values from separate processors to build one vector containing all of the data. More...

std::vector< double >	MPI_gatherVectors (const std::vector< double > &input_vector)
	Uses MPI to gather vectors from separate processors to build one big vector containing all of the data. More...

std::vector< int >	MPI_gatherVectors (const std::vector< int > &input_vector)
	Uses MPI to gather vectors from separate processors to build one big vector containing all of the data. More...

std::string	removeWhitespace (const std::string &str)
	Removes all spaces and ta characters in a string. More...

int	round_int (const double num)
	Rounds the input double value to the nearest integer value. More...

bool	str2bool (const std::string &input)
	Extracts a boolean value from a string containing "true" or "false". Throws an invalid_argument exception if the input string is not "true" or "false". More...

template<typename T >
double	array_avg (const T data[], const int array_size)
	This template function calculates and returns the average value in double format when given an array of numerical datatypes. More...

template<typename T >
T	array_median (const T data[], const int array_size)
	This template function calculates and returns the median value when given an array of numerical datatypes. More...

template<typename T >
double	array_stdev (const T data[], const int array_size)
	This template function calculates and returns the standard deviation in double format when given an array of numerical datatypes. More...

template<typename T >
int	array_which_median (const T data[], const int array_size)
	This template function determines which element in the data array has the median value of the dataset. More...

template<typename T >
double	intpow (const T base, const int exponent)
	This template function calculates and returns the results of an integer power operation on a base numerical datatype. More...

template<typename T >
void	outputVectorToFile (std::vector< T > &vec, std::string filename)
	This template function outputs the input data vector to a file with the specified filename. More...

template<typename T >
void	outputVectorToFile (std::vector< std::pair< T, T >> &vec, std::string filename)
	This template function outputs the input data pair vector to a file with the specified filename. More...

template<typename T >
void	removeDuplicates (std::vector< T > &vec)
	This template function efficienctly removes the duplicate entries from an input vector. More...

template<typename T , typename A >
double	vector_avg (const std::vector< T, A > &data)
	This template function calculates and returns the average value in double format when given a vector of numerical datatypes. More...

template<typename T , typename A >
double	vector_median (std::vector< T, A > data)
	This template function calculates and returns the median value when given a vector of numerical datatypes. More...

template<typename T , typename A >
double	vector_stdev (const std::vector< T, A > &data)
	This template function calculates and returns the standard deviation in double format when given a vector of numerical datatypes. More...

template<typename T , typename A >
int	vector_which_median (const std::vector< T, A > &data)
	This template function determines which element in the data vector is closest to the median value of the dataset. More...

std::ostream &	operator<< (std::ostream &stream, const Version &input)

Variables
Version	Current_version ("4.0.2")

Function Documentation

◆ array_avg()

template<typename T >

double Ising_OPV::array_avg	(	const T	data[],
		const int	array_size
	)

This template function calculates and returns the average value in double format when given an array of numerical datatypes.

Parameters

data	is the array of numerical data.
array_size	is the size of the input data array.

Returns: The average of the data set in double format.

◆ array_median()

template<typename T >

T Ising_OPV::array_median	(	const T	data[],
		const int	array_size
	)

This template function calculates and returns the median value when given an array of numerical datatypes.

Parameters

data	is the array of numerical data.
array_size	is the size of the input data array.

Returns: The median value of the data set.

◆ array_stdev()

template<typename T >

double Ising_OPV::array_stdev	(	const T	data[],
		const int	array_size
	)

This template function calculates and returns the standard deviation in double format when given an array of numerical datatypes.

Parameters

data	is the input array of numerical data.
array_size	is the size of the input data array.

Returns: The standard deviation of the data set in double format.

◆ array_which_median()

template<typename T >

int Ising_OPV::array_which_median	(	const T	data[],
		const int	array_size
	)

This template function determines which element in the data array has the median value of the dataset.

Parameters

data	is the input array of numerical data.
array_size	is the size of the input data array.

Returns: the integer array index that indicates the median value.; -1 if the median cannot be determined.

◆ calculateCumulativeHist()

std::vector< std::pair< double, double > > Ising_OPV::calculateCumulativeHist ( const std::vector< std::pair< double, double >> & data )

Calculates the cumulative histogram from the input probability histogram data.

Parameters

data	is the input probability histogram which is a vector of x-y pairs consisting of bin-centered x values and probability y values.

Returns: A vector of x-y pairs consisting of bin-centered x values and cumulative probability y values.

◆ calculateHist()

std::vector< std::pair< double, int > > Ising_OPV::calculateHist	(	const std::vector< int > &	data,
		int	bin_size
	)

Calculates the histogram for the input integer data vector using the input bin size.

Linearly spaced bins are automatically created from the minimum value to the maximum value of the data set with the specified bin size. The function outputs bin-centered x values and counts y values in a x-y pair vector.

Parameters

data	is the input integer data vector.
bin_size	is the specified bin size

Returns: A vector of x-y pairs consisting of bin-centered x values and counts y values.

◆ calculateProbabilityHist() [1/6]

std::vector< std::pair< double, double > > Ising_OPV::calculateProbabilityHist ( const std::vector< std::pair< double, int >> hist )

Calculates the probability histogram for the input histogram data vector. The function outputs bin-centered x values and probability y values in a x-y pair vector.

Parameters

hist	is the input histogram data vector.

Returns: A vector of x-y pairs consisting of bin-centered x values and probability y values.

◆ calculateProbabilityHist() [2/6]

std::vector< std::pair< double, double > > Ising_OPV::calculateProbabilityHist	(	const std::vector< int > &	data,
		int	bin_size
	)

Calculates the probability histogram for the input integer data vector using the input bin size.

Linearly spaced bins are automatically created from the minimum value to the maximum value of the data set with the specified bin size. The function outputs bin-centered x values and probability y values in a x-y pair vector.

Parameters

data	is the input integer data vector.
bin_size	is the specified bin size

Returns: A vector of x-y pairs consisting of bin-centered x values and probability y values.

◆ calculateProbabilityHist() [3/6]

std::vector< std::pair< double, double > > Ising_OPV::calculateProbabilityHist	(	const std::vector< double > &	data,
		int	num_bins
	)

Calculates the probability histogram for the input double data vector using the input number of bins.

Linearly spaced bins are automatically created from the minimum value to the maximum value of the data set. The function outputs bin-centered x values and probability y values in a x-y pair vector.

Parameters

data	is the input data vector.
num_bins	is the desired number of bins.

Returns: A vector of x-y pairs consisting of bin-centered x values and probability y values.

◆ calculateProbabilityHist() [4/6]

std::vector< std::pair< double, double > > Ising_OPV::calculateProbabilityHist	(	const std::vector< double > &	data,
		double	bin_size
	)

Calculates the probability histogram for the input data vector using the input bin size.

Linearly spaced bins are automatically created from the minimum value to the maximum value of the data set. with the specified bin spacing. The function outputs bin-centered x values and probability y values in a x-y pair vector.

Parameters

data	is the input data vector.
bin_size	is the desired bin size.

Returns: A vector of x-y pairs consisting of bin-centered x values and probability y values.

◆ calculateProbabilityHist() [5/6]

std::vector< std::pair< double, double > > Ising_OPV::calculateProbabilityHist	(	const std::vector< double > &	data,
		const double	bin_size,
		const int	num_bins
	)

Calculates the probability histogram for the input data vector using the input bin size and input number of bins.

Linearly spaced bins are automatically created starting from the minimum value of the data set. The function outputs bin-centered x values and probability y values in a x-y pair vector.

Parameters

data	is the input data vector.
num_bins	is the number of bins that will be created.
bin_size	is the input bin size.

Returns: A vector of x-y pairs consisting of bin-centered x values and probability y values.

◆ calculateProbabilityHist() [6/6]

std::vector< std::pair< double, double > > Ising_OPV::calculateProbabilityHist	(	const std::vector< double > &	data,
		const double	bin_start,
		const double	bin_size
	)

Calculates the probability histogram for the input data vector using the input bin start value and bin size.

Linearly spaced bins are automatically created starting from the bin start value. The function outputs bin-centered x values and probability y values in a x-y pair vector.

Parameters

data	is the input data vector.
bin_start	is the starting value of the first bin.
bin_size	is the input bin size.

Returns: A vector of x-y pairs consisting of bin-centered x values and probability y values.

◆ integrateData()

double Ising_OPV::integrateData ( const std::vector< std::pair< double, double >> & data )

Numerically integrates a vector of x-y data using the trapezoid rule.

Warning: The function assumes that the data is sorted by the x values.

Parameters

data	is the data vector containing x-y data pairs.

Returns: the numerically calculated area.

◆ interpolateData()

double Ising_OPV::interpolateData	(	const std::vector< std::pair< double, double >> &	data,
		const double	x_val
	)

Linearly interpolates an x-y data set to determine the interpolated y-value corresponding to an input x-value.

Warning: The function assumes that the data is sorted by the x values.

Parameters

data	is the data vector containing x-y data pairs.
x_val	is the x-value that will be interpolated to.

Returns: the interpolated y-value when the input x-value lies within the range of the input data.

◆ intpow()

template<typename T >

double Ising_OPV::intpow	(	const T	base,
		const int	exponent
	)

This template function calculates and returns the results of an integer power operation on a base numerical datatype.

Parameters

base	is the base of the integer power operation and can be any numerical type.
exponent	is the integer exponent for the integer power operation.

Returns: The result of the integer power operation in double format.

◆ MPI_calculateProbHistAvg()

std::vector< std::pair< double, double > > Ising_OPV::MPI_calculateProbHistAvg ( const std::vector< std::pair< double, int >> & input_hist )

Uses MPI to calculate the average probability histogram from separate histograms coming from different processors.

Each processor calls this function and sends an input histogram. Each input histogram must have the same bin size.

Upon function return, processor 0 receives the average probabiliy histogram and all of the other processors receive an empty probability histogram.

Parameters

input_hist is the input histogram data from the processor calling the function.

Returns: A pair vector that is the average probability histogram of all input histograms from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_calculateVectorAvg()

std::vector< double > Ising_OPV::MPI_calculateVectorAvg ( const std::vector< double > & input_vector )

Uses MPI to calculate the element-wise average vector from separate vectors coming from different processors.

Each processor calls this function and sends an input vector. If vectors are different sizes, the function uses trailing zeroes to make all vectors the same size before averaging. Upon function return, processor 0 receives the average vector and all of the other processors receive an empty vector.

Parameters

input_vector is the input data from the processor calling the function.

Returns: A vector that is the element-wise average of all input vectors from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_calculateVectorSum() [1/2]

std::vector< double > Ising_OPV::MPI_calculateVectorSum ( const std::vector< double > & input_vector )

Uses MPI to calculate the element-wise sum vector from separate equally sized vectors coming from different processors.

Each processor calls this function and sends an input vector. Upon function return, processor 0 receives the sum vector and all of the other processors receive an empty vector.

Parameters

input_vector is the input data from the processor calling the function.

Returns: A vector that is the element-wise sum of all input vectors from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_calculateVectorSum() [2/2]

std::vector< int > Ising_OPV::MPI_calculateVectorSum ( const std::vector< int > & input_vector )

Uses MPI to calculate the element-wise sum vector from separate vectors coming from different processors.

Each processor calls this function and sends an input vector. Upon function return, processor 0 receives the sum vector and all of the other processors receive an empty vector.

Parameters

input_vector is the input data from the processor calling the function.

Returns: A vector that is the element-wise sum of all input vectors from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_gatherValues() [1/2]

std::vector< int > Ising_OPV::MPI_gatherValues ( const int input_val )

Uses MPI to gather integer values from separate processors to build one vector containing all of the data.

Each processor calls this function and sends an input value. Upon function return, processor 0 receives the data vector and all of the other processors receive an empty vector.

Parameters

input_val is the input integer data value from the processor calling the function.

Returns: A vector that is a collection of the values from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_gatherValues() [2/2]

std::vector< double > Ising_OPV::MPI_gatherValues ( const double input_val )

Uses MPI to gather double values from separate processors to build one vector containing all of the data.

Each processor calls this function and sends an input value. Upon function return, processor 0 receives the data vector and all of the other processors receive an empty vector.

Parameters

input_val is the input double data value from the processor calling the function.

Returns: A vector that is a collection of the values from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_gatherVectors() [1/2]

std::vector< double > Ising_OPV::MPI_gatherVectors ( const std::vector< double > & input_vector )

Uses MPI to gather vectors from separate processors to build one big vector containing all of the data.

Each processor calls this function and sends an input vector. Upon function return, processor 0 receives the large data vector and all of the other processors receive an empty vector.

Parameters

input_vector is the input data from the processor calling the function.

Returns: A vector that is a concatenation of all input vectors from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ MPI_gatherVectors() [2/2]

std::vector< int > Ising_OPV::MPI_gatherVectors ( const std::vector< int > & input_vector )

Uses MPI to gather vectors from separate processors to build one big vector containing all of the data.

Each processor calls this function and sends an input vector. Upon function return, processor 0 receives the large data vector and all of the other processors receive an empty vector.

Parameters

input_vector is the input data from the processor calling the function.

Returns: A vector that is a concatenation of all input vectors from each processor, when called on processor 0.; An empty vector when called on other processors.

◆ operator<<()

std::ostream& Ising_OPV::operator<<	(	std::ostream &	stream,
		const Version &	input
	)

◆ outputVectorToFile() [1/2]

template<typename T >

void Ising_OPV::outputVectorToFile	(	std::vector< T > &	vec,
		std::string	filename
	)

This template function outputs the input data vector to a file with the specified filename.

Warning: This function may overwrite existing files if not used carefully.

Parameters

vec	is the input data vector.
filename	is the input file name.

◆ outputVectorToFile() [2/2]

template<typename T >

void Ising_OPV::outputVectorToFile	(	std::vector< std::pair< T, T >> &	vec,
		std::string	filename
	)

This template function outputs the input data pair vector to a file with the specified filename.

Warning: This function may overwrite existing files if not used carefully.

Parameters

vec	is the input data pair vector.
filename	is the input file name.

◆ removeDuplicates()

template<typename T >

void Ising_OPV::removeDuplicates ( std::vector< T > & vec )

This template function efficienctly removes the duplicate entries from an input vector.

This algorithm allow efficient removal of duplicate vector objects when > or < comparison operators do not exist.

Parameters

vec	is the input vector to be operated on.

◆ removeWhitespace()

std::string Ising_OPV::removeWhitespace ( const std::string & str )

Removes all spaces and ta characters in a string.

Parameters

str	is the input string

Returns: a new string that will have the whitespace removed.

◆ round_int()

int Ising_OPV::round_int ( const double num )

Rounds the input double value to the nearest integer value.

Parameters

num	is the input double value.

Returns: an integer value that is the rounded value.

◆ str2bool()

bool Ising_OPV::str2bool ( const std::string & input )

Extracts a boolean value from a string containing "true" or "false". Throws an invalid_argument exception if the input string is not "true" or "false".

Parameters

input is the input string.

Returns: true if the input string is "true".; flase if the input string is "flase".

◆ vector_avg()

template<typename T , typename A >

double Ising_OPV::vector_avg ( const std::vector< T, A > & data )

This template function calculates and returns the average value in double format when given a vector of numerical datatypes.

Parameters

data	is the vector of numerical data.

Returns: The average of the data set in double format.

◆ vector_median()

template<typename T , typename A >

double Ising_OPV::vector_median ( std::vector< T, A > data )

This template function calculates and returns the median value when given a vector of numerical datatypes.

Parameters

data	is the vector of numerical data.

Returns: The median value in the data set.

◆ vector_stdev()

template<typename T , typename A >

double Ising_OPV::vector_stdev ( const std::vector< T, A > & data )

This template function calculates and returns the standard deviation in double format when given a vector of numerical datatypes.

Parameters

data	is the vector of numerical data.

Returns: The standard deviation of the data set in double format.

◆ vector_which_median()

template<typename T , typename A >

int Ising_OPV::vector_which_median ( const std::vector< T, A > & data )

This template function determines which element in the data vector is closest to the median value of the dataset.

if multiple values are equally close, the first one in the vector is selected.

Parameters

data	is the input vector of numerical data.

Returns: the integer vector index that indicates the median value.

Variable Documentation

◆ Current_version

Version Ising_OPV::Current_version

Classes

Functions

Variables

Function Documentation

◆ array_avg()

◆ array_median()

◆ array_stdev()

◆ array_which_median()

◆ calculateCumulativeHist()

◆ calculateHist()

◆ calculateProbabilityHist() [1/6]

◆ calculateProbabilityHist() [2/6]

◆ calculateProbabilityHist() [3/6]

◆ calculateProbabilityHist() [4/6]

◆ calculateProbabilityHist() [5/6]

◆ calculateProbabilityHist() [6/6]

◆ integrateData()

◆ interpolateData()

◆ intpow()

◆ MPI_calculateProbHistAvg()

◆ MPI_calculateVectorAvg()

◆ MPI_calculateVectorSum() [1/2]

◆ MPI_calculateVectorSum() [2/2]

◆ MPI_gatherValues() [1/2]

◆ MPI_gatherValues() [2/2]

◆ MPI_gatherVectors() [1/2]

◆ MPI_gatherVectors() [2/2]

◆ operator<<()

◆ outputVectorToFile() [1/2]

◆ outputVectorToFile() [2/2]

◆ removeDuplicates()

◆ removeWhitespace()

◆ round_int()

◆ str2bool()

◆ vector_avg()

◆ vector_median()

◆ vector_stdev()

◆ vector_which_median()

Variable Documentation

◆ Current_version