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Basic Integration QuickStart Sample (C#)
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Basic Integration QuickStart Sample (C#)
Illustrates the basic numerical integration (quadrature) classes
(Extreme.Mathematics.Calculus namespace) in C#.
VB.NET code F# code
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using System;
namespace Extreme.Mathematics.QuickStart.CSharp
{
// The numerical integration classes reside in the
// Extreme.Mathematics.Calculus namespace.
using Extreme.Mathematics.Calculus;
// Function delegates reside in the Extreme.Mathematics
// namespace.
using Extreme.Mathematics;
/// <summary>
/// Illustrates the basic use of the numerical integration
/// classes in the Extreme.Mathematics.Calculus namespace.
/// </summary>
class BasicIntegration
{
/// <summary>
/// The main entry point for the application.
/// </summary>
[STAThread]
static void Main(string[] args)
{
// Numerical integration algorithms fall into two
// main categories: adaptive and non-adaptive.
// This QuickStart Sample illustrates the use of
// the non-adaptive numerical integrators.
//
// All numerical integration classes derive from
// NumericalIntegrator. This abstract base class
// defines properties and methods that are shared
// by all numerical integration classes.
//
// The integrand
//
// The function we are integrating must be
// provided as a RealFunction. For more
// information about this delegate, see the
// FunctionDelegates QuickStart sample.
RealFunction f =
new RealFunction(Math.Sin);
// Variable to hold the result:
double result;
//
// SimpsonIntegrator
//
// The simplest numerical integration algorithm
// is Simpson's rule.
SimpsonIntegrator simpson = new SimpsonIntegrator();
// You can set the relative or absolute tolerance
// to which to evaluate the integral.
simpson.RelativeTolerance = 1e-5;
// You can select the type of tolerance using the
// ConvergenceCriterion property:
simpson.ConvergenceCriterion =
ConvergenceCriterion.WithinRelativeTolerance;
// The Integrate method performs the actual
// integration:
result = simpson.Integrate(f, 0, 2);
Console.WriteLine("sin(x) on [0,2]");
Console.WriteLine("Simpson integrator:");
// The result is also available in the Result
// property:
Console.WriteLine(" Value: {0}", simpson.Result);
// To see whether the algorithm ended normally,
// inspect the Status property:
Console.WriteLine(" Status: {0}",
simpson.Status);
// You can find out the estimated error of the result
// through the EstimatedError property:
Console.WriteLine(" Estimated error: {0}",
simpson.EstimatedError);
// The number of iterations to achieve the result
// is available through the IterationsNeeded property.
Console.WriteLine(" Iterations: {0}",
simpson.IterationsNeeded);
// The number of function evaluations is available
// through the FunctionEvaluationsNeeded property.
Console.WriteLine(" Function evaluations: {0}",
simpson.FunctionEvaluationsNeeded);
//
// Gauss-Kronrod Integration
//
// Gauss-Kronrod integrators also use a fixed point
// scheme, but with certain optimizations in the
// choice of points where the integrand is evaluated.
//
// The Extreme.Mathematics.Calculus namespace contains a series
// of Gauss-Kronrod integrators that are mainly used
// as an integration rule for the adaptive
// integrator. No iteration is used.
// Here's the 21-point rule:
GaussKronrodIntegrator21 gk21 = new GaussKronrodIntegrator21();
gk21.Integrate(f, 0, 2);
Console.WriteLine("21 point Gauss-Kronrod rule:");
Console.WriteLine(" Value: {0}", gk21.Result);
Console.WriteLine(" Status: {0}",
gk21.Status);
Console.WriteLine(" Estimated error: {0}",
gk21.EstimatedError);
Console.WriteLine(" Iterations: {0}",
gk21.IterationsNeeded);
Console.WriteLine(" Function evaluations: {0}",
gk21.FunctionEvaluationsNeeded);
// The NonAdaptiveGaussKronrodIntegrator uses a
// succession of 10, 21, 43, and 87 point rules
// to approximate the integral.
NonAdaptiveGaussKronrodIntegrator nagk =
new NonAdaptiveGaussKronrodIntegrator();
nagk.Integrate(f, 0, 2);
Console.WriteLine("Non-adaptive Gauss-Kronrod rule:");
Console.WriteLine(" Value: {0}", nagk.Result);
Console.WriteLine(" Status: {0}",
nagk.Status);
Console.WriteLine(" Estimated error: {0}",
nagk.EstimatedError);
Console.WriteLine(" Iterations: {0}",
nagk.IterationsNeeded);
Console.WriteLine(" Function evaluations: {0}",
nagk.FunctionEvaluationsNeeded);
//
// Romberg Integration
//
// Romberg integration combines Simpson's Rule
// with a scheme to accelerate convergence.
// This algorithm is useful for smooth integrands.
RombergIntegrator romberg = new RombergIntegrator();
result = romberg.Integrate(f, 0, 2);
Console.WriteLine("Romberg integration:");
Console.WriteLine(" Value: {0}", romberg.Result);
Console.WriteLine(" Status: {0}",
romberg.Status);
Console.WriteLine(" Estimated error: {0}",
romberg.EstimatedError);
Console.WriteLine(" Iterations: {0}",
romberg.IterationsNeeded);
Console.WriteLine(" Function evaluations: {0}",
romberg.FunctionEvaluationsNeeded);
// However, it breaks down if the integration
// algorithm contains singularities or
// discontinuities.
f = new RealFunction(HardIntegrand);
result = romberg.Integrate(f, 0, 1);
Console.WriteLine("Romberg on hard integrand:");
Console.WriteLine(" Value: {0}", romberg.Result);
Console.WriteLine(" Actual value: 100");
Console.WriteLine(" Status: {0}",
romberg.Status);
Console.WriteLine(" Estimated error: {0}",
romberg.EstimatedError);
Console.WriteLine(" Iterations: {0}",
romberg.IterationsNeeded);
Console.WriteLine(" Function evaluations: {0}",
romberg.FunctionEvaluationsNeeded);
Console.Write("Press Enter key to exit...");
Console.ReadLine();
}
/// <summary>
/// Function that will cause difficulties to the
/// simplistic integration algorithms.
/// </summary>
private static double HardIntegrand(double x)
{
// This is put in because some integration rules
// evaluate the function at x=0.
if (x <= 0)
return 0;
return Math.Pow(x,-0.9) * Math.Log(1/x);
}
}
}
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