LapjvCSharp 1.0.2

lap: Linear Assignment Problem solver

Original package https://github.com/gatagat/lap, made for Python and translated to C# by RainBowDash.

Params

• cost - type double[,]
• extendCost - type bool default : false
• costLimit - type double default : double.PositiveInfinity

Use

It can be used as an instance or as dependency injection.

    private static void Main(string[] args)
    {
        LapjvCSharp.Lapjv lap = new LapjvCSharp.Lapjv();

        var Matriz8x8 = new double[,]
        {
            {1000, 2, 11, 10, 8, 7, 6, 5},
            { 6, 1000, 1, 8, 8, 4, 6, 7},
            { 5, 12, 1000, 11, 8, 12, 3, 11},
            { 11, 9, 10, 1000, 1, 9, 8, 10},
            { 11, 11, 9, 4, 1000, 2, 10, 9},
            { 12, 8, 5, 2, 11, 1000, 11, 9},
            { 10, 11, 12, 10, 9, 12, 1000, 3},
            { 10, 10, 10, 10, 6, 3, 1, 1000}
        };

        var result = lap.lapjvCsharp(Matriz8x8, true, 4.99);
    }

If a cost_limit is not required for your calculation, use:

    private static void Main(string[] args)
    {
        LapjvCSharp.Lapjv lap = new LapjvCSharp.Lapjv();

        var Matriz8x8 = new double[,]
        {
            {1000, 2, 11, 10, 8, 7, 6, 5},
            { 6, 1000, 1, 8, 8, 4, 6, 7},
            { 5, 12, 1000, 11, 8, 12, 3, 11},
            { 11, 9, 10, 1000, 1, 9, 8, 10},
            { 11, 11, 9, 4, 1000, 2, 10, 9},
            { 12, 8, 5, 2, 11, 1000, 11, 9},
            { 10, 11, 12, 10, 9, 12, 1000, 3},
            { 10, 10, 10, 10, 6, 3, 1, 1000}
        };

        var result = lap.lapjvCsharp(Matriz8x8);
    }

Benchmark Performance

The following benchmarks compare the performance of methods using float and double for solving matrices of varying sizes.

System Specifications:

• Processor: Intel Core i7-8700 CPU @ 3.20GHz (Coffee Lake)
• Cores: 6 physical, 12 logical
• OS: Windows 10 (22H2/2022 Update)
• .NET Version: .NET 8.0.7
• Benchmark Framework: BenchmarkDotNet v0.14.0

Benchmark Results:

Changelog

• Version 1.0.0: Initial release of the project.
• Version 1.0.1: Bugfix by jmurphyct to handle 1x2 matrices correctly.
• Version 1.0.2: Added support for matrices using float instead of double. Methods for double were duplicated to avoid potential performance issues due to type transformations.