https://github.com/swharden/swarmfit

A .NET package for fitting curves to data using particle swarm optimization
https://github.com/swharden/swarmfit

curve curve-fitting math mathmatics particle-swarm-optimization

Last synced: about 2 months ago
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A .NET package for fitting curves to data using particle swarm optimization

• Host: GitHub
• URL: https://github.com/swharden/swarmfit
• Owner: swharden
• License: mit
• Created: 2024-08-14T16:20:10.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-09-25T02:04:19.000Z (3 months ago)
• Last Synced: 2024-11-04T15:06:27.041Z (about 2 months ago)
• Topics: curve, curve-fitting, math, mathmatics, particle-swarm-optimization
• Language: C#
• Homepage: https://www.nuget.org/packages/SwarmFit/
• Size: 730 KB
• Stars: 13
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# SwarmFit

[![CI](https://github.com/swharden/SwarmFit/actions/workflows/ci.yaml/badge.svg)](https://github.com/swharden/SwarmFit/actions/workflows/ci.yaml)

**SwarmFit is a .NET package for fitting curves to X/Y data** points using [particle swarm optimization](https://en.wikipedia.org/wiki/Particle_swarm_optimization). Unlike other gradient decent strategies, finding the derivative of the error function is not required. SwarmFit can be used to calculate best fit curves for arbitrary equations that use any number of parameters.

![](dev/fit2.gif)

## Quickstart

```cs

// data points to fit

double[] xs = [1, 2, 3, 4, 5];

double[] ys = [304, 229, 174, 134, 111];

// a custom function to fit to the data using any number of parameters

static double MyFitFunc(double x, double[] parameters)

{

	double a = parameters[0];

	double b = parameters[1];

	double c = parameters[2];

	return a + b * Math.Exp(x * c);

}

// the minimum and maximum value for each parameter

double[] minVars = [-100, -5000, -10];

double[] maxVars = [100, 5000, 10];

// perform the fit with general purpose settings

double[] solution = QuickFit.Solve(xs, ys, MyFitFunc, minVars, maxVars);

// display the solution

double a = solution[0];

double b = solution[1];

double c = solution[2];

Console.WriteLine($"Y = {a} + {b} * e^(x * {c})");

```

## Graphical Demo

A sample application is included with this repository which generates random data and fits it using common curve functions. This application demonstrates advanced features such as fitter fine-tuning, iterative error logging, charting, etc.

![](dev/example3.png)