public void Given_min_max_precision_When_creating_range_Then_should_return_all_members()
{
var actual = RangeWithPrecision.Range(1, 2, 1).ToArray();
var expected = new double[] { 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0 };
expected.ShouldDeepEqual(actual);
}
public void Given_uneven_min_max_And_high_precision_When_creating_range_Then_should_return_all_members()
{
const double min = 0.056;
const double max = 0.967;
const int precision = 6;
var actual = RangeWithPrecision.Range(min, max, precision).ToArray();
Assert.Equal(CalculateLength(min, max, precision), actual.Length);
Assert.Equal(min, actual[0]);
Assert.Equal(0.056001, actual[1]);
Assert.Equal(0.966999, actual.TakeLast(2).ElementAt(0));
Assert.Equal(max, actual.Last());
}
public async Task <IterationResult> Start(IOptimizerConfiguration config, CancellationToken cancellationToken)
{
CancellationToken = cancellationToken;
var parameters = config.Genes.Select(s =>
new MinMaxParameterSpec(min: s.Min ?? s.Actual.Value, max: s.Max ?? s.Actual.Value,
transform: Transform.Linear, parameterType: s.Precision > 0 ? ParameterType.Continuous : ParameterType.Discrete)
).ToArray();
Keys = config.Genes.Where(g => g.Key != "id").Select(s => s.Key);
IOptimizer optimizerMethod = null;
if (config.Fitness != null)
{
if (config.Fitness.OptimizerTypeName == Enums.OptimizerTypeOptions.RandomSearch.ToString())
{
optimizerMethod = new RandomSearchOptimizer(parameters, iterations: config.Generations, seed: 42, runParallel: false);
}
else if (config.Fitness.OptimizerTypeName == Enums.OptimizerTypeOptions.ParticleSwarm.ToString())
{
optimizerMethod = new ParticleSwarmOptimizer(parameters, maxIterations: config.Generations, numberOfParticles: config.PopulationSize,
seed: 42, maxDegreeOfParallelism: 1);
}
else if (config.Fitness.OptimizerTypeName == Enums.OptimizerTypeOptions.Bayesian.ToString())
{
optimizerMethod = new BayesianOptimizer(parameters: parameters, iterations: config.Generations, randomStartingPointCount: config.PopulationSize,
functionEvaluationsPerIterationCount: config.PopulationSize, seed: 42, runParallel: false);
}
else if (config.Fitness.OptimizerTypeName == Enums.OptimizerTypeOptions.GlobalizedBoundedNelderMead.ToString())
{
optimizerMethod = new GlobalizedBoundedNelderMeadOptimizer(parameters, maxRestarts: config.Generations,
maxIterationsPrRestart: config.PopulationSize, seed: 42, maxDegreeOfParallelism: 1);
}
else if (config.Fitness.OptimizerTypeName == Enums.OptimizerTypeOptions.GridSearch.ToString())
{
optimizerMethod = new GridSearchOptimizer(config.Genes.Select(s => new GridParameterSpec(RangeWithPrecision.Range(s.Min.Value, s.Max.Value, s.Precision.Value).ToArray())).ToArray(), runParallel: false);
}
}
else
{
throw new ArgumentException("No optimizer was configured.");
}
var result = await optimizerMethod.OptimizeBest(Minimize);
return(new IterationResult {
ParameterSet = result.ParameterSet, Cost = IsMaximizing ? result.Error * -1 : result.Error
});
}
