public override GradientMethod.Answer GetAnswer()
{
param = new TemporaryParams();
param.vectorX = input.vectorX0;
GradientMethod.Answer answer = new GradientMethod.Answer();
answer.iterCount = 0;
answer.funcCalcCount = 0;
double[] stepsArray = new double[input.vectorX0.Length];
for (int i = 0; i < stepsArray.Length; i++)
{
stepsArray[i] = input.epsilon * 100;
}
DichotomyMethod.Answer answerDM;
do
{
param.oldVectorX = Ext.cloneVector(param.vectorX);
for (int index = 0; index < param.vectorX.Length; index++)
{
param.currentVectorIndex = index;
double varWithNegativeStep = param.vectorX[index] - 3 * input.epsilon;
double varWithPositiveStep = param.vectorX[index] + 3 * input.epsilon;
double[] copyVector = Ext.cloneVector(param.vectorX);
copyVector[index] = varWithNegativeStep;
double f1 = input.mainFunc.calculate(copyVector);
copyVector[index] = varWithPositiveStep;
double f2 = input.mainFunc.calculate(copyVector);
param.direction = Math.Sign(f1 - f2);
answerDM = findStep(stepsArray[index]);
answer.iterCount += answerDM.iterCount;
stepsArray[index] = answerDM.approxMinX;
param.vectorX = takeAStep(stepsArray[index], param.vectorX, index, param.direction);
answer.funcCalcCount += answerDM.funcCalcCount * 2 + 2;
answer.approxMinFunc++;
}
} while (Ext.normOfVector(Ext.subtructOfVectors(param.vectorX, param.oldVectorX)) >= input.epsilon);
answer.approxMinFunc = input.mainFunc.calculate(param.vectorX);
answer.approxMinVectorX = param.vectorX;
return(answer);
}
private static void showAnswer(string methodName, GradientMethod.Answer answer)
{
Console.WriteLine($"Answer for {methodName}");
Console.WriteLine($" Approximate minimum of function: {answer.approxMinFunc}");
string dot = "";
for (int i = 0; i < answer.approxMinVectorX.Length - 1; i++)
{
dot += answer.approxMinVectorX[i] + ",";
}
dot += answer.approxMinVectorX[answer.approxMinVectorX.Length - 1];
Console.WriteLine($" Dot : x({dot})");
Console.WriteLine($" Functionc calculation count : {answer.funcCalcCount}");
Console.WriteLine($" Iteration count : {answer.iterCount}\n");
}
public override GradientMethod.Answer GetAnswer()
{
param = new TemporaryParams();
GradientMethod.Answer answer = new GradientMethod.Answer();
answer.iterCount = 0;
answer.funcCalcCount = 0;
param.vectorX = Ext.cloneVector(input.vectorX0);
param.firstOrderGradient = Ext.findFirstOrderGradient(input.firstOrderDerivatives, input.vectorX0);
double[,] secondOrderGradient = Ext.findSecondOrderGradient(input.secondOrderDerivatives, param.vectorX);
param.invertedSecondOrderGradient = Ext.findInversedMatrix(secondOrderGradient);;
answer.funcCalcCount += input.vectorX0.Length + Convert.ToInt32(Math.Pow(param.vectorX.Length, 2));
double step = 1000 * input.epsilon;
param.vectorX = Ext.cloneVector(input.vectorX0);
DichotomyMethod.Answer answerDM;
if (Ext.normOfVector(param.firstOrderGradient) > input.epsilon)
{
do
{
answerDM = findStep(step);
step = answerDM.approxMinX;
answer.iterCount += answerDM.iterCount;
param.vectorX = takeAStep(step, param.vectorX, param.invertedSecondOrderGradient, param.firstOrderGradient);
param.firstOrderGradient = Ext.findFirstOrderGradient(input.firstOrderDerivatives, param.vectorX);
answer.funcCalcCount += input.vectorX0.Length;
answer.iterCount++;
}while (Ext.normOfVector(param.firstOrderGradient) >= input.epsilon);
}
answer.approxMinVectorX = param.vectorX;
answer.approxMinFunc = input.mainFunc.calculate(param.vectorX);
answer.funcCalcCount++;
return(answer);
}
public override GradientMethod.Answer GetAnswer()
{
param = new TemporaryParams();
GradientMethod.Answer answer = new GradientMethod.Answer();
answer.iterCount = 0;
answer.funcCalcCount = 0;
double[] firstOrderGradient = Ext.findFirstOrderGradient(input.firstOrderDerivatives, input.vectorX0);
double[,] secondOrderGradient, invertedSecondOrderGradient;
answer.funcCalcCount += input.vectorX0.Length;
double[] sums = new double[input.vectorX0.Length];
param.vectorX = Ext.cloneVector(input.vectorX0);
if (Ext.normOfVector(firstOrderGradient) > input.epsilon)
{
do
{
secondOrderGradient = Ext.findSecondOrderGradient(input.secondOrderDerivatives, param.vectorX);
answer.funcCalcCount += Convert.ToInt32(Math.Pow(param.vectorX.Length, 2));
invertedSecondOrderGradient = Ext.findInversedMatrix(secondOrderGradient);
for (int i = 0; i < param.vectorX.Length; i++)
{
sums[i] = 0;
for (int j = 0; j < param.vectorX.Length; j++)
{
sums[i] += invertedSecondOrderGradient[i, j] * firstOrderGradient[j];
}
}
param.vectorX = Ext.subtructOfVectors(param.vectorX, sums);
firstOrderGradient = Ext.findFirstOrderGradient(input.firstOrderDerivatives, param.vectorX);
answer.funcCalcCount += input.vectorX0.Length;
answer.iterCount++;
}while (Ext.normOfVector(firstOrderGradient) >= input.epsilon);
}
answer.approxMinVectorX = param.vectorX;
answer.approxMinFunc = input.mainFunc.calculate(param.vectorX);
answer.funcCalcCount++;
return(answer);
}
public override GradientMethod.Answer GetAnswer()
{
param = new TemporaryParams();
GradientMethod.Answer answer = new GradientMethod.Answer();
answer.iterCount = 0;
answer.funcCalcCount = 0;
param.vectorX = Ext.cloneVector(input.vectorX0);
param.gradient = Ext.findFirstOrderGradient(input.firstOrderDerivatives, param.vectorX);
answer.funcCalcCount += input.vectorX0.Length;
if (Ext.normOfVector(param.gradient) > input.epsilon)
{
double step = 100 * input.epsilon;
DichotomyMethod.Answer answerDM;
do
{
answerDM = findStep(step);
step = answerDM.approxMinX;
answer.funcCalcCount += answerDM.funcCalcCount;
answer.iterCount += answerDM.iterCount;
param.oldVectorX = param.vectorX;
param.vectorX = takeAStep(step, param.vectorX, param.gradient);
param.gradient = Ext.findFirstOrderGradient(input.firstOrderDerivatives, param.vectorX);
answer.funcCalcCount += input.vectorX0.Length;
answer.iterCount++;
}while (Ext.normOfVector(Ext.subtructOfVectors(param.vectorX, param.oldVectorX)) >= input.epsilon &&
Ext.normOfVector(param.gradient) >= input.epsilon);
}
answer.approxMinVectorX = param.vectorX;
answer.approxMinFunc = input.mainFunc.calculate(param.vectorX);
answer.funcCalcCount++;
return(answer);
}