using System;
using System.Collections.Generic;
namespace Algorithms.Numeric;
///
/// In numerical analysis, the Runge–Kutta methods are a family of implicit and explicit iterative methods,
/// used in temporal discretization for the approximate solutions of simultaneous nonlinear equations.
/// The most widely known member of the Runge–Kutta family is generally referred to as
/// "RK4", the "classic Runge–Kutta method" or simply as "the Runge–Kutta method".
///
public static class RungeKuttaMethod
{
///
/// Loops through all the steps until xEnd is reached, adds a point for each step and then
/// returns all the points.
///
/// Initial conditions x-value.
/// Last x-value.
/// Step-size on the x-axis.
/// Initial conditions y-value.
/// The right hand side of the differential equation.
/// The solution of the Cauchy problem.
public static List ClassicRungeKuttaMethod(
double xStart,
double xEnd,
double stepSize,
double yStart,
Func function)
{
if (xStart >= xEnd)
{
throw new ArgumentOutOfRangeException(
nameof(xEnd),
$"{nameof(xEnd)} should be greater than {nameof(xStart)}");
}
if (stepSize <= 0)
{
throw new ArgumentOutOfRangeException(
nameof(stepSize),
$"{nameof(stepSize)} should be greater than zero");
}
List points = new();
double[] firstPoint = { xStart, yStart };
points.Add(firstPoint);
var yCurrent = yStart;
var xCurrent = xStart;
while (xCurrent < xEnd)
{
var k1 = function(xCurrent, yCurrent);
var k2 = function(xCurrent + 0.5 * stepSize, yCurrent + 0.5 * stepSize * k1);
var k3 = function(xCurrent + 0.5 * stepSize, yCurrent + 0.5 * stepSize * k2);
var k4 = function(xCurrent + stepSize, yCurrent + stepSize * k3);
yCurrent += (1.0 / 6.0) * stepSize * (k1 + 2 * k2 + 2 * k3 + k4);
xCurrent += stepSize;
double[] newPoint = { xCurrent, yCurrent };
points.Add(newPoint);
}
return points;
}
}