public IHyperCube <double> GenerateRandomWithinHypercube(IHyperCube <double>[] points)
{
if (points.Length == 0)
{
return(this.GenerateRandom(points[0]));
}
else
{
IHyperCube <double> p = points[0].Clone() as IHyperCube <double>;
string[] varNames = p.GetVariableNames();
for (int i = 0; i < varNames.Length; i++)
{
string v = varNames[i];
double minimum;
double maximum;
GetSmallestIntervalForValues(points, v, out minimum, out maximum);
minimum = Math.Max(minimum, p.GetMinValue(v));
maximum = Math.Min(maximum, p.GetMaxValue(v));
checkFeasibleInterval(minimum, maximum, v);
p.SetValue(varNames[i], GetRandomisedValue(minimum, maximum));
}
return(p);
}
}
public static bool CheckInBounds <T>(IHyperCube <T> point) where T : IComparable
{
foreach (var varName in point.GetVariableNames())
{
var min = point.GetMinValue(varName);
var max = point.GetMaxValue(varName);
var val = point.GetValue(varName);
if (!MetaheuristicsHelper.CheckInBounds(val, min, max, throwIfFalse: false))
{
return(false);
}
}
return(true);
}
public IHyperCube <double> GenerateRandom(IHyperCube <double> point)
{
string[] varNames = point.GetVariableNames( );
IHyperCube <double> result = point.Clone( ) as IHyperCube <double>;
for (int i = 0; i < varNames.Length; i++)
{
string v = varNames[i];
// We take the bounds of the result point, to cater for cascading parameter constraints.
double min = result.GetMinValue(v);
double max = result.GetMaxValue(v);
checkFeasibleInterval(min, max, v);
result.SetValue(varNames[i], GetRandomisedValue(min, max));
}
return(result);
}
public static HyperCubeInterop ToDataFrame(IHyperCube <double> paramSet)
{
var names = paramSet.GetVariableNames();
var r = new HyperCubeInterop(names.Length);
for (int i = 0; i < names.Length; i++)
{
var name = names[i];
r.Name[i] = name;
r.Description[i] = "";
r.Value[i] = paramSet.GetValue(name);
r.Min[i] = paramSet.GetMinValue(name);
r.Max[i] = paramSet.GetMaxValue(name);
}
return(r);
}
private bool tryAdd(string varName, IHyperCube <U> sysConfig, double realStepSize)
{
var min = sysConfig.GetMinValue(varName).ToDouble(null);
var max = sysConfig.GetMaxValue(varName).ToDouble(null);
var val = sysConfig.GetValue(varName).ToDouble(null);
var newval = val + realStepSize;
bool result = true;
if (newval < min)
{
newval = min; result = false;
}
else if (newval > max)
{
newval = max; result = false;
}
sysConfig.SetValue(varName, (U)((IConvertible)newval).ToType(typeof(U), CultureInfo.InvariantCulture));
return(result);
}
/// <summary>
/// populates the internal array of parameters with the relavant pest values. In the
/// current version, it considers all parameters to be of the same group (not sure
/// if this functionality is required for TIME models)
/// </summary>
/// <param name="parameters">starting point and range of input parameters </param>
public void AddParameterSet(IHyperCube <double> parameters)
{
List <PESTParameterData> parameterList = new List <PESTParameterData>();
foreach (String paramName in parameters.GetVariableNames())
{
PESTParameterData tmpParameter = new PESTParameterData();
tmpParameter.Scale = 1.0;
tmpParameter.MaxValue = parameters.GetMaxValue(paramName);
tmpParameter.MinValue = parameters.GetMinValue(paramName);
tmpParameter.InitialValue = parameters.GetValue(paramName);
tmpParameter.ParameterName = paramName;
tmpParameter.TransformType = PestConstants.ParameterDataConstants.ParameterTransformationType.noneType;
tmpParameter.ChangeLimitedType = PestConstants.ParameterDataConstants.ParameterChangeLimitedType.relativeChange;
tmpParameter.ParameterGroup = "param";
parameterList.Add(tmpParameter);
}
this.Parameters = parameterList.ToArray();
}
public static HyperCubeInterop ToDataFrame(IHyperCube<double> paramSet)
{
var names = paramSet.GetVariableNames();
var r = new HyperCubeInterop(names.Length);
for (int i = 0; i < names.Length; i++)
{
var name = names[i];
r.Name[i] = name;
r.Description[i] = "";
r.Value[i] = paramSet.GetValue(name);
r.Min[i] = paramSet.GetMinValue(name);
r.Max[i] = paramSet.GetMaxValue(name);
}
return r;
}