NeurApp 1.1
NeurApp - software for exploring approximation by artificial neural networks on functions of one or two variables.

IG::Neural::TestFunctions Class Reference

List of all members.

Static Public Member Functions

static void GenerateFunctionTrainingSamples (double lowerInputLimit, double upperInputLimit, double step, IRealFunction function, ref SampledDataSet trainingData)
static IRealFunction CreateFunction (string equation)
 Creates a function loader and uses it for dynamic definition of functions.
static int CalculateNumSteps (double lowLimit, double highLimit, double steps)
static IVector[][] GenerateInputParameters2D (double step, double xMin, int xNumSteps, double yMin, int yNumSteps)
static IVector[][] CalculateFunction2D (IVector[][] inputPArameters)
static IVector[][] TrainingPoints2D (IVector[][] functionCoordinates, int numTrainingPoints, bool random)
 Calculate desired number of training poits from data set in random or regullary order.
static IVector[][] TrainingPoints2D (IVector[][] functionCoordinates, int numXTrainingPoints, int numYTrainingPoints, bool random)
 Calculate desired number of training poits from data set in random or regullary order.

Static Private Member Functions

static void GenerateInputParameters (double lowerInputLimit, double step, int numSteps, ref IVector[] inputParameters)

Member Function Documentation

static void IG::Neural::TestFunctions::GenerateFunctionTrainingSamples ( double  lowerInputLimit,
double  upperInputLimit,
double  step,
IRealFunction  function,
ref SampledDataSet  trainingData 
) [inline, static]
static IRealFunction IG::Neural::TestFunctions::CreateFunction ( string  equation) [inline, static]

Creates a function loader and uses it for dynamic definition of functions.

static void IG::Neural::TestFunctions::GenerateInputParameters ( double  lowerInputLimit,
double  step,
int  numSteps,
ref IVector[]  inputParameters 
) [inline, static, private]
static int IG::Neural::TestFunctions::CalculateNumSteps ( double  lowLimit,
double  highLimit,
double  steps 
) [inline, static]
static IVector [][] IG::Neural::TestFunctions::GenerateInputParameters2D ( double  step,
double  xMin,
int  xNumSteps,
double  yMin,
int  yNumSteps 
) [inline, static]
Parameters:
stepStep for x and y axes.
xMinMinimum on x axes.
xNumStepsNumber of steps on x axes.
yMinMinimum on y axes.
yNumStepsNumber of steps on y axes.
Returns:
Returns points InputParameters2D[y][x]
static IVector [][] IG::Neural::TestFunctions::CalculateFunction2D ( IVector  inputPArameters[][]) [inline, static]
static IVector [][] IG::Neural::TestFunctions::TrainingPoints2D ( IVector  functionCoordinates[][],
int  numTrainingPoints,
bool  random 
) [inline, static]

Calculate desired number of training poits from data set in random or regullary order.

Parameters:
functionCoordinatesData set.
numTrainingPointsNumber of training points for x and y axses.
Returns:
Training points.
static IVector [][] IG::Neural::TestFunctions::TrainingPoints2D ( IVector  functionCoordinates[][],
int  numXTrainingPoints,
int  numYTrainingPoints,
bool  random 
) [inline, static]

Calculate desired number of training poits from data set in random or regullary order.

Parameters:
functionCoordinatesData set.
numXTrainingPointsNumber of training points for x axses.
numYTrainingPointsNumber of training points for y axses.
Returns:
Training points.

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