pkg
mathias.brandewinder/Quipuv1.1.0-beta1
.NET 6.0
Nelder-Mead function minimization solver.
Get Started
$ dotnet add package QuipuReadme
Quipu
Quipu is a dotnet implementation of the Nelder–Mead method. It is a numerical solver used to find the minimum or maximum of a function. It is particularly useful for nonlinear optimization problems for which derivatives may not be known.
Example usage
The solver can be used from F# and C#, with similar APIs.
Let's use Quipu to find the minimum of f(x,y) = (x-1)^2 + (y-2)^2 + 42.
This function has a unique global minimum, for x=1,y=2.
Basic usage, F# pipeline
#r "nuget: Quipu, 1.0.0"
open Quipu
let f (x, y) = pown (x - 1.0) 2 + pown (y - 2.0) 2 + 42.0
let solverResult =
NelderMead.objective f
|> NelderMead.minimize
if solverResult.HasSolution
then
let solution = solverResult.Solution
printfn $"Solution: {solution.Status}"
let candidate = solution.Candidate
let args = candidate.Arguments
let value = candidate.Value
printfn $"f(%.3f{args[0]}, %.3f{args[1]}) = %.3f{value}"
Solution: Optimal
f(1.000, 2.000) = 42.000
Basic usage, C# fluent interface
#r "nuget: Quipu, 1.0.0"
using Quipu.CSharp;
using System;
Func<Double,Double,Double> f =
(x, y) => Math.Pow(x - 1.0, 2) + Math.Pow(y - 2.0, 2) + 42.0;
var solverResult =
NelderMead
.Objective(f)
.Minimize();
if (solverResult.HasSolution)
{
var solution = solverResult.Solution;
Console.WriteLine($"Solution: {solution.Status}");
var candidate = solution.Candidate;
var args = candidate.Arguments;
var value = candidate.Value;
Console.WriteLine($"f({args[0]:N3}, {args[1]:N3}) = {value:N3}");
}
Solution: Optimal
f(1.000, 2.000) = 42.000
Advanced usage
The solver provides more fine grained control if needed, see the test suite for more examples: