public void RandomSearchOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(10.0, 37.5, Transform.Linear)
};
var sut = maxDegreeOfParallelism.HasValue ?
new RandomSearchOptimizer(parameters, 2, 42, true, maxDegreeOfParallelism.Value) :
new RandomSearchOptimizer(parameters, 2);
var actual = sut.Optimize(MinimizeWeightFromHeight);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 13.8749507052707 }, 23438.2157641635),
new OptimizerResult(new double[] { 28.3729278125674 }, 3690.81119818742),
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void GridSearchOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new GridParameterSpec[]
{
new GridParameterSpec(10.0, 37.5)
};
var sut = maxDegreeOfParallelism.HasValue ?
new GridSearchOptimizer(parameters, true, maxDegreeOfParallelism.Value) :
new GridSearchOptimizer(parameters);
var actual = sut.Optimize(Minimize);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.5 }, 111.20889999999987),
new OptimizerResult(new double[] { 10 }, 31638.9579)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void GlobalizedBoundedNelderMeadOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = maxDegreeOfParallelism.HasValue ?
new GlobalizedBoundedNelderMeadOptimizer(parameters, 5, 1e-5, 10,
maxDegreeOfParallelism: maxDegreeOfParallelism.Value) :
new GlobalizedBoundedNelderMeadOptimizer(parameters, 5, 1e-5, 10);
var results = sut.Optimize(MinimizeWeightFromHeight);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.71314535727786 }, 109.34381396310141),
new OptimizerResult(new double[] { 37.7131485180996 }, 109.34381396350526)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void SmacOptimizer_Optimize()
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = new SmacOptimizer(parameters,
iterations: 80,
randomStartingPointCount: 20,
functionEvaluationsPerIterationCount: 1,
localSearchPointCount: 10,
randomSearchPointCount: 1000,
epsilon: 0.00001,
seed: 42);
var actual = sut.Optimize(MinimizeWeightFromHeight);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 90.513222660177 }, 114559.431919558),
new OptimizerResult(new double[] { 41.8333740634068 }, 806.274612132759),
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), Delta);
}
public void BayesianOptimizer_Optimize()
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = new BayesianOptimizer(parameters,
iterations: 120,
randomStartingPointCount: 5,
functionEvaluationsPerIterationCount: 1,
randomSearchPointCount: 1000,
seed: 42,
runParallel: false); // Note, since the returned results are not ordered on error,
// running with parallel computations will not return reproducible order of results,
// so runParallel must be false for this test.
var results = sut.Optimize(MinimizeWeightFromHeight);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 43.216748276360683 }, 1352.8306605984087),
new OptimizerResult(new double[] { 38.201425707992833 }, 119.1316225267316)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), Delta);
}
public void ParticleSwarmOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = maxDegreeOfParallelism.HasValue ?
new ParticleSwarmOptimizer(parameters, 100, maxDegreeOfParallelism: maxDegreeOfParallelism.Value) :
new ParticleSwarmOptimizer(parameters, 100);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 38.1151505704492 }, 115.978346548015),
new OptimizerResult(new double[] { 37.2514904205637 }, 118.093289672808),
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void RandomSearchOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(10.0, 37.5, Transform.Linear)
};
var sut = maxDegreeOfParallelism.HasValue ?
new RandomSearchOptimizer(parameters, 100, 42, true, maxDegreeOfParallelism.Value) :
new RandomSearchOptimizer(parameters, 100);
var actual = sut.Optimize(MinimizeWeightFromHeight);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 28.3729278125674 }, 3690.81119818742),
new OptimizerResult(new double[] { 19.1529422843144 }, 14251.396910816733),
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void ParticleSwarmOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = CreateSut(maxDegreeOfParallelism, parameters);
var results = sut.Optimize(MinimizeWeightFromHeight);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 38.1151505704492 }, 115.978346548015),
new OptimizerResult(new double[] { 37.2514904205637 }, 118.093289672808),
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void GridSearchOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new GridParameterSpec[]
{
new GridParameterSpec(10.0, 20.0, 30.0, 35.0, 37.5, 40.0, 50.0, 60.0)
};
var sut = maxDegreeOfParallelism.HasValue ?
new GridSearchOptimizer(parameters, true, maxDegreeOfParallelism.Value) :
new GridSearchOptimizer(parameters);
var actual = sut.Optimize(MinimizeWeightFromHeight);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 10 }, 31638.9579),
new OptimizerResult(new double[] { 60 }, 20500.6279)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void GlobalizedBoundedNelderMeadOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = CreateSut(maxDegreeOfParallelism, parameters);
var results = sut.Optimize(MinimizeWeightFromHeight);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.71314634450421 }, 109.3438139631394),
new OptimizerResult(new double[] { 37.713142445047254 }, 109.34381396345546)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void BayesianOptimizer_OptimizeNonDeterministicInParallel()
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0, 1, Transform.Linear, ParameterType.Discrete)
};
var sut = new BayesianOptimizer(parameters, iterations: 240, randomStartingPointCount: 5, functionEvaluationsPerIteration: 5,
seed: Seed, maxDegreeOfParallelism: -1, allowMultipleEvaluations: true);
var results = sut.Optimize(p => MinimizeNonDeterministic(p, Random));
var actual = new OptimizerResult[] { results.First(), results.Last() }.OrderByDescending(o => o.Error);
Assert.AreEqual(1, actual.First().Error);
Assert.AreEqual(1, (int)actual.First().ParameterSet[0]);
}
public void GridSearchOptimizer_Optimize()
{
var parameters = new double[][] { new double[] { 10.0, 37.5 } };
var sut = new GridSearchOptimizer(parameters);
var actual = sut.Optimize(Minimize);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.5 }, 111.20889999999987),
new OptimizerResult(new double[] { 10 }, 31638.9579)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void RandomSearchOptimizer_Optimize()
{
var parameters = new double[][] { new double[] { 10.0, 37.5 } };
var sut = new RandomSearchOptimizer(parameters, 2);
var actual = sut.Optimize(Minimize);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 28.372927812567415 }, 3690.8111981874217),
new OptimizerResult(new double[] { 13.874950705270725 }, 23438.215764163542)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void SequentialModelBasedOptimizer_Optimize()
{
var parameters = new double[][] { new double[] { 0.0, 100.0 } };
var sut = new SequentialModelBasedOptimizer(parameters, 20, 5);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.712345696964071 }, 109.34384021647092),
new OptimizerResult(new double[] { 66.810646591154239 }, 34867.634010511123)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void ParticleSwarmOptimizer_Optimize()
{
var parameters = new double[][] { new double[] { 0.0, 100.0 } };
var sut = new ParticleSwarmOptimizer(parameters, 100);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.635959742891046 }, 109.58839344747747),
new OptimizerResult(new double[] { 38.891904333594624 }, 166.38611320480345)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void GlobalizedBoundedNelderMeadOptimizer_Optimize()
{
var parameters = new double[][] { new double[] { 0.0, 100.0 } };
var sut = new GlobalizedBoundedNelderMeadOptimizer(parameters, 5, 1e-5, 10);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.71314535727786 }, 109.34381396310141),
new OptimizerResult(new double[] { 37.7131485180996 }, 109.34381396350526)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void BayesianOptimizer_Optimize()
{
var parameters = new double[][] { new double[] { 0.0, 100.0 } };
var sut = new BayesianOptimizer(parameters, 120, 5, 1);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.710969353891429 }, 109.34400835405613),
new OptimizerResult(new double[] { 99.646240426062718 }, 157577.44222424511)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void BayesianOptimizer_Optimize()
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = new BayesianOptimizer(parameters, 120, 5, 1);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 90.513222660177 }, 114559.431919558),
new OptimizerResult(new double[] { 24.204380402436 }, 7601.008090362)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, m_delta);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), m_delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, m_delta);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), m_delta);
}
public void ParticleSwarmOptimizer_Optimize()
{
var parameters = new ParameterBounds[]
{
new ParameterBounds(0.0, 100.0, Transform.Linear)
};
var sut = new ParticleSwarmOptimizer(parameters, 100);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.660092259635064 }, 109.45936368750877),
new OptimizerResult(new double[] { 39.038272502859328 }, 181.43166846962754)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void ParticleSwarmOptimizer_Optimize()
{
var parameters = new ParameterBounds[]
{
new ParameterBounds(0.0, 100.0, Transform.Linear)
};
var sut = new ParticleSwarmOptimizer(parameters, 100);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 37.804275358363732 }, 109.68474734728727),
new OptimizerResult(new double[] { 35.942821697748165 }, 238.00642904844648)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, 0.0001);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), 0.0001);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, 0.0001);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), 0.0001);
}
public void BayesianOptimizer_Optimize()
{
var parameters = new ParameterBounds[]
{
new ParameterBounds(0.0, 100.0, Transform.Linear)
};
var sut = new BayesianOptimizer(parameters, 120, 5, 1);
var results = sut.Optimize(Minimize2);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 42.323589763754789 }, 981.97873691815118),
new OptimizerResult(new double[] { 99.110398813667885 }, 154864.41962974239)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, m_delta);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), m_delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, m_delta);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), m_delta);
}
public void SmacOptimizer_Optimize()
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = CreateSut(parameters);
var actual = sut.Optimize(MinimizeWeightFromHeight);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 90.513222660177 }, 114559.431919558),
new OptimizerResult(new double[] { 41.8333740634068 }, 806.274612132759),
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), Delta);
}
public void BayesianOptimizer_Optimize()
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = new BayesianOptimizer(parameters, 120, 5, 1, maxDegreeOfParallelism: 1);
var results = sut.Optimize(MinimizeWeightFromHeight);
var actual = new OptimizerResult[] { results.First(), results.Last() }.OrderByDescending(o => o.Error);
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 90.513222660177 }, 114559.431919558),
new OptimizerResult(new double[] { 24.2043804024367 }, 7601.00809036235)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(),
actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(),
actual.Last().ParameterSet.First(), Delta);
}
public void BayesianOptimizer_Optimize(int?maxDegreeOfParallelism)
{
var parameters = new MinMaxParameterSpec[]
{
new MinMaxParameterSpec(0.0, 100.0, Transform.Linear)
};
var sut = CreateSut(maxDegreeOfParallelism, parameters);
var results = sut.Optimize(MinimizeWeightFromHeight);
var actual = new OptimizerResult[] { results.First(), results.Last() };
var expected = new OptimizerResult[]
{
new OptimizerResult(new double[] { 90.513222660177036 }, 114559.43191955783),
new OptimizerResult(new double[] { 41.752538896050559 }, 779.196560786838)
};
Assert.AreEqual(expected.First().Error, actual.First().Error, Delta);
Assert.AreEqual(expected.First().ParameterSet.First(), actual.First().ParameterSet.First(), Delta);
Assert.AreEqual(expected.Last().Error, actual.Last().Error, Delta);
Assert.AreEqual(expected.Last().ParameterSet.First(), actual.Last().ParameterSet.First(), Delta);
}
