public void Run()
{
var function = new F4();
// Generate simplex with offset from 1 to 20 and in point [0.5, 0.5]
Console.WriteLine("Case 1: Generate simplex with offset from 1 to 20 and in point [0.5, 0.5].");
for (int i = 1; i <= 20; i++)
{
var opt = new NelderMeadMinimizer();
opt.IsOutputEnabled = false;
opt.IsOutputPerIterationEnabled = false;
double[] min = opt.Minimize(function, new double[] { 0.5, 0.5 }, i);
Console.WriteLine($"offset={i}, evals={function.Evaluations}, x_min={min.Format(16)}, f(x_min)={function.Value(min).ToString("F16")}");
function.Clear();
}
Console.WriteLine();
// Generate simplex with offset from 1 to 20 and in point [20, 20]
Console.WriteLine("Case 2: Generate simplex with offset from 1 to 20 and in point [20, 20].");
for (int i = 1; i <= 20; i++)
{
var opt = new NelderMeadMinimizer();
opt.IsOutputEnabled = false;
opt.IsOutputPerIterationEnabled = false;
double[] min = opt.Minimize(function, new double[] { 20, 20 }, i);
Console.WriteLine($"offset={i}, evals={function.Evaluations}, x_min={min.Format(16)}, f(x_min)={function.Value(min).ToString("F16")}");
function.Clear();
}
}
public void Run()
{
var function = new F3();
// var function = new DelegateFunction(x => Math.Pow(x[0] - 3, 2));
for (int i = 10; i <= 15; i++)
{
// Coordinate descent method
var opt1 = new CoordinateDescentMinimizer();
opt1.IsOutputPerIterationEnabled = false;
opt1.Minimize(function, new double[] { i });
// Golden section search
var opt2 = new GoldenSectionMinimizer();
opt2.IsOutputPerIterationEnabled = false;
opt2.Minimize(function, i);
// Nelder-Mead search
var opt3 = new NelderMeadMinimizer();
opt3.IsOutputPerIterationEnabled = false;
opt3.Minimize(function, new double[] { i });
// Hooke-Jeeves pattern search
var opt4 = new HookeJeevesMinimizer();
opt4.IsOutputPerIterationEnabled = false;
opt4.Minimize(function, new double[] { i });
}
}
public void Run()
{
var result = new List <Tuple <string, string, string, string> >();
var functions = new List <Tuple <Function, double[]> >()
{
new Tuple <Function, double[]>(new F1(), new double[] { -1.9, 2.0 }),
new Tuple <Function, double[]>(new F2(), new double[] { 0.1, 0.3 }),
new Tuple <Function, double[]>(new F3(), new double[] { 0, 0, 0, 0, 0 }),
new Tuple <Function, double[]>(new F4(), new double[] { 5.1, 1.1 })
};
for (int i = 0; i < functions.Count; i++)
{
var item = functions[i];
var opt1 = new NelderMeadMinimizer();
opt1.IsOutputEnabled = false;
var min1 = opt1.Minimize(item.Item1, item.Item2.Copy());
var opt1Evals = item.Item1.Evaluations;
var opt2 = new HookeJeevesMinimizer();
opt2.IsOutputEnabled = false;
var min2 = opt2.Minimize(item.Item1, item.Item2.Copy());
var opt2Evals = item.Item1.Evaluations;
var opt3 = new CoordinateDescentMinimizer();
opt3.IsOutputEnabled = false;
var min3 = opt3.Minimize(item.Item1, item.Item2.Copy());
var opt3Evals = item.Item1.Evaluations;
int outputPrecision = 6;
result.Add(new Tuple <string, string, string, string>((i + 1).ToString(),
"min: " + min1.Format(outputPrecision),
"min: " + min2.Format(outputPrecision),
"min: " + min3.Format(outputPrecision)));
result.Add(new Tuple <string, string, string, string>(string.Empty,
"f(min): " + item.Item1.Value(min1).ToString("F" + outputPrecision),
"f(min): " + item.Item1.Value(min2).ToString("F" + outputPrecision),
"f(min): " + item.Item1.Value(min3).ToString("F" + outputPrecision)));
result.Add(new Tuple <string, string, string, string>(string.Empty,
"evals: " + opt1Evals.ToString(),
"evals: " + opt2Evals.ToString(),
"evals: " + opt3Evals.ToString()));
}
Console.WriteLine(result.ToStringTable(
new[] { "Function", "Nelder and Mead", "Hooke-Jeeves", "Coordinate Descent" },
a => a.Item1, a => a.Item2, a => a.Item3, a => a.Item4));
Console.WriteLine();
// Hooke-Jeeves will stuck at function F4 because of the nature of exploration which explores a better point only
// in one axis, not all at once, and because at point [3.1 3.1] only [2.975 2.975] is fitter, the algorithm
// can't determine that there is a better point in the environment
}
public void Run()
{
var function = new F4();
// Nelder-Mead search
var opt1 = new NelderMeadMinimizer();
opt1.IsOutputPerIterationEnabled = false;
opt1.Minimize(function, new double[] { 5, 5 });
// Hooke-Jeeves pattern search
var opt2 = new HookeJeevesMinimizer();
opt2.IsOutputPerIterationEnabled = false;
opt2.Minimize(function, new double[] { 5, 5 });
}
public void TestNelderMead()
{
LinearFunction function = new LinearFunction();
List <Point> data = new List <Point>();
data.Add(new Point(0, 1));
data.Add(new Point(1, 3));
SquaredResidualsSumDistance distance = new SquaredResidualsSumDistance(data.ToArray());
var minimizer = new NelderMeadMinimizer();
var res = minimizer.Minimize(function, distance, 0.01, 100);
function.SetParametersValues(res);
Assert.AreEqual(res[0], 2, 1e-8);
Assert.AreEqual(res[1], 1, 1e-8);
}
public void Run()
{
var random = new Random();
var function = new F6();
int foundCounter = 0;
for (int i = 0; i < 10000; i++)
{
var opt = new NelderMeadMinimizer();
opt.IsOutputEnabled = false;
opt.IsOutputPerIterationEnabled = false;
var final = opt.Minimize(function, new double[] { random.Next(-50, 51) });
if (function.Value(final) < 10e-4)
{
foundCounter++;
}
}
Console.WriteLine("Probability: " + (foundCounter / (double)10000) + "%");
Console.WriteLine();
}