public void TestOptimizationProblemContext()
{
var in1 = new ContinuousDimension("in_1", 0, 10);
var in2 = new DiscreteDimension("in_2", 1, 20);
var inputHypergrid = new Hypergrid("input", in1, in2);
var out1 = new ContinuousDimension("out_1", -5, 7);
var objectiveHypergrid = new Hypergrid("output", out1);
var context1 = new DiscreteDimension("ctx_1", -100, -0);
var contextHypergrid = new Hypergrid("context", context1);
var objectives = new OptimizationObjective[]
{
new OptimizationObjective("out_1", true),
new OptimizationObjective("nonExistent", false),
};
var optimizationProblem = new OptimizationProblem(inputHypergrid, contextHypergrid, objectiveHypergrid, objectives);
var serialized = OptimizerServiceEncoder.EncodeOptimizationProblem(optimizationProblem);
var deserialized = OptimizerServiceDecoder.DecodeOptimizationProblem(serialized);
Assert.Equal(optimizationProblem.ParameterSpace.Name, deserialized.ParameterSpace.Name);
Assert.Equal(optimizationProblem.ObjectiveSpace.Name, deserialized.ObjectiveSpace.Name);
Assert.Equal(optimizationProblem.ContextSpace.Name, deserialized.ContextSpace.Name);
Assert.Equal(optimizationProblem.Objectives[0].Name, objectives[0].Name);
Assert.Equal(optimizationProblem.Objectives[0].Minimize, objectives[0].Minimize);
Assert.Equal(optimizationProblem.Objectives[1].Name, objectives[1].Name);
Assert.Equal(optimizationProblem.Objectives[1].Minimize, objectives[1].Minimize);
// This is not a rigorous test but it should be sufficient given the other tests in this set.
Assert.Equal(optimizationProblem.ParameterSpace.Dimensions[0].Name, deserialized.ParameterSpace.Dimensions[0].Name);
Assert.Equal(optimizationProblem.ParameterSpace.Dimensions[1].Name, deserialized.ParameterSpace.Dimensions[1].Name);
Assert.Equal(optimizationProblem.ObjectiveSpace.Dimensions[0].Name, deserialized.ObjectiveSpace.Dimensions[0].Name);
Assert.Equal(optimizationProblem.ContextSpace.Dimensions[0].Name, deserialized.ContextSpace.Dimensions[0].Name);
}
public static OptimizerService.DiscreteDimension EncodeDiscreteDimension(DiscreteDimension dimension)
{
return(new OptimizerService.DiscreteDimension
{
Name = dimension.Name,
Min = dimension.Min,
Max = dimension.Max,
});
}
public void TestDiscreteDimension()
{
var dimension = new DiscreteDimension("_%% \n \t \\//", long.MinValue, long.MaxValue);
var serialized = OptimizerServiceEncoder.EncodeDiscreteDimension(dimension);
var deserialized = OptimizerServiceDecoder.DecodeDiscreteDimension(serialized);
Assert.Equal(deserialized.Name, dimension.Name);
Assert.Equal(deserialized.Min, dimension.Min);
Assert.Equal(deserialized.Max, dimension.Max);
}
private void Awake()
{
m_Car = GetComponent <CarController>();
inputSpeed = new ContinuousDimension("", "", "", -100, 180);
backwardSpeed = new RightQuadraticSet(inputSpeed, "", -100, -10, 0);
zeroSpeed = new BellSet(inputSpeed, "", 0, 5, 10);
lowSpeed = new QuadraticSet(inputSpeed, "", 10, 40, 0, 50, 5, 45);
//private FuzzySet medSpeed;
highSpeed = new LeftQuadraticSet(inputSpeed, "", 40, 45, 50);
inputSideBoundDistance = new ContinuousDimension("", "", "", -10, 10);
dangerousRight = new LeftQuadraticSet(inputSideBoundDistance, "", 0, 9, 10);
dangerousLeft = new RightQuadraticSet(inputSideBoundDistance, "", -10, -9, 0);
safe = new TrapezoidalSet(inputSideBoundDistance, "", -5, 5, -7, 7);
inputFrontBoundDistance = new ContinuousDimension("", "", "", 0, 150);
far = new LeftLinearSet(inputFrontBoundDistance, "", 20, 40);
close = new TrapezoidalSet(inputFrontBoundDistance, "", 15, 20, 10, 25);
dangerousClose = new RightLinearSet(inputFrontBoundDistance, "", 10, 15);
outputGas = new ContinuousDimension("", "", "", -100, 100);
pedalToMetal = new LeftQuadraticSet(outputGas, "", 0, 80, 100);
clutch = new SingletonSet(outputGas, "", 0);
brake = new RightLinearSet(outputGas, "", -100, 0);
outputBrakes = new ContinuousDimension("", "", "", 0, 1);
outputAction = new DiscreteDimension("", "");
outputSteeringWheel = new ContinuousDimension("", "", "", -100, 100);
turnLeft = new RightLinearSet(outputSteeringWheel, "", -100, 0);
turnRight = new LeftLinearSet(outputSteeringWheel, "", 0, 100);
forward = new TriangularSet(outputSteeringWheel, "", 0, -10, 10);
simpleSteeringRules =
(dangerousLeft & turnRight) |
(dangerousRight & turnLeft) |
(safe & forward);
simpleGasRules =
(far & pedalToMetal) |
((close & lowSpeed) & clutch) |
((close & highSpeed) & brake) |
((close & zeroSpeed) & brake) |
(dangerousClose & brake);
}
public TestSerializingAndDeserializing()
{
/* FIXME: This needs better cross-plat support and error handling.
* - We should include C:\Python37 as another PYTHONHOME location to look for by default
* - Currently this doesn't handle Linux very well
* - On Ubuntu Python 3.7 needs to be installed from a separate
* repo, which installs as libpython3.7m.so which fails tobe
* found due to the trailing "m".
*/
string pathToVirtualEnv = Environment.GetEnvironmentVariable("PYTHONHOME");
if (string.IsNullOrEmpty(pathToVirtualEnv))
{
pathToVirtualEnv = @"c:\ProgramData\Anaconda3";
}
else
{
Environment.SetEnvironmentVariable("PYTHONHOME", pathToVirtualEnv, EnvironmentVariableTarget.Process);
}
string pathToPythonPkg = $"{pathToVirtualEnv}\\pkgs\\python-3.7.4-h5263a28_0";
Environment.SetEnvironmentVariable("PATH", $"{pathToVirtualEnv};{pathToPythonPkg}", EnvironmentVariableTarget.Process);
Environment.SetEnvironmentVariable("PYTHONPATH", $"{pathToVirtualEnv}\\Lib\\site-packages;{pathToVirtualEnv}\\Lib", EnvironmentVariableTarget.Process);
continuous = new ContinuousDimension(name: "continuous", min: 1, max: 10);
discrete = new DiscreteDimension(name: "discrete", min: 1, max: 10);
ordinal = new OrdinalDimension(name: "ordinal", orderedValues: new List <object>()
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
}, ascending: true);
categorical = new CategoricalDimension(name: "categorical", values: new List <object>()
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
});
allKindsOfDimensions = new Hypergrid(
name: "all_kinds_of_dimensions",
dimensions: new IDimension[]
{
continuous,
discrete,
ordinal,
categorical,
});
}
public void TestOptimizationProblemNoContext()
{
var in1 = new ContinuousDimension("in_1", 0, 10);
var in2 = new DiscreteDimension("in_2", 1, 20);
var inputHypergrid = new Hypergrid("input", in1, in2);
var out1 = new ContinuousDimension("out_1", -5, 7);
var objectiveHypergrid = new Hypergrid("output", out1);
var objectives = new OptimizationObjective[]
{
new OptimizationObjective("out_1", true),
new OptimizationObjective("nonExistent", false),
};
var optimizationProblem = new OptimizationProblem(inputHypergrid, objectiveHypergrid, objectives);
var serialized = OptimizerServiceEncoder.EncodeOptimizationProblem(optimizationProblem);
var deserialized = OptimizerServiceDecoder.DecodeOptimizationProblem(serialized);
Assert.Null(deserialized.ContextSpace);
}
public TestSerializingAndDeserializing()
{
string pathToVirtualEnv = Environment.GetEnvironmentVariable("PYTHONHOME");
if (string.IsNullOrEmpty(pathToVirtualEnv))
{
pathToVirtualEnv = @"c:\ProgramData\Anaconda3";
}
else
{
Environment.SetEnvironmentVariable("PYTHONHOME", pathToVirtualEnv, EnvironmentVariableTarget.Process);
}
string pathToPythonPkg = $"{pathToVirtualEnv}\\pkgs\\python-3.7.4-h5263a28_0";
Environment.SetEnvironmentVariable("PATH", $"{pathToVirtualEnv};{pathToPythonPkg}", EnvironmentVariableTarget.Process);
Environment.SetEnvironmentVariable("PYTHONPATH", $"{pathToVirtualEnv}\\Lib\\site-packages;{pathToVirtualEnv}\\Lib", EnvironmentVariableTarget.Process);
continuous = new ContinuousDimension(name: "continuous", min: 1, max: 10);
discrete = new DiscreteDimension(name: "discrete", min: 1, max: 10);
ordinal = new OrdinalDimension(name: "ordinal", orderedValues: new List <object>()
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
}, ascending: true);
categorical = new CategoricalDimension(name: "categorical", values: new List <object>()
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
});
allKindsOfDimensions = new SimpleHypergrid(
name: "all_kinds_of_dimensions",
dimensions: new List <IDimension>()
{
continuous,
discrete,
ordinal,
categorical,
});
}
