public GPDApproximation(IList <double> data, FittingMethod method = FittingMethod.Pickands_SupNorm, Random rand = null)
{
if (data.Count < 30)
{
throw new ArgumentException("Insufficient data count for Pickands Balkema De Haan theorem.");
}
sortedData = new List <double>(data);
sortedData.Sort();
int m; // Transition index
switch (method)
{
case FittingMethod.BFGS_MSE:
ApproximateExcessDistributionParametersBFGS(sortedData, out a, out c, out transitionAbscissa);
// Compute the index of the closest element that is at or before u in the data
int transitionIndex = sortedData.BinarySearch(transitionAbscissa);
if (transitionIndex < 0)
{
transitionIndex = ~transitionIndex;
}
transitionProportion = transitionIndex * 1.0 / sortedData.Count; // Shouldn't this be + 1 here?
break;
case FittingMethod.Moments_MSE:
ApproximateExcessDistributionParametersMoments(sortedData, out a, out c, out m);
transitionProportion = (sortedData.Count - m + 1.0) / sortedData.Count;
transitionAbscissa = sortedData[sortedData.Count - m]; // Convert from m to the actual transitionIndex; m is guaranteed to be > 0
break;
case FittingMethod.V4:
ApproximateExcessDistributionParametersV4(sortedData, out a, out c, out transitionAbscissa);
int transitionIdx = sortedData.BinarySearch(transitionAbscissa);
if (transitionIdx < 0)
{
transitionIdx = ~transitionIdx; // Now the index of the next-largest element
if (transitionIdx == 0)
{
transitionProportion = 0; break;
}
transitionProportion = Interpolation.Lerp(
sortedData[transitionIdx - 1], transitionIdx * 1.0 / sortedData.Count,
sortedData[transitionIdx], (transitionIdx + 1) * 1.0 / sortedData.Count,
transitionAbscissa);
break;
}
transitionProportion = (transitionIdx + 1) * 1.0 / sortedData.Count;
break;
default:
ApproximateExcessDistributionParametersPickands(sortedData, out a, out c, out m); // Write m to transitionIndex
transitionProportion = (sortedData.Count - 4 * m + 1.0) / sortedData.Count;
transitionAbscissa = sortedData[sortedData.Count - 4 * m]; // Convert from m to the actual transitionIndex; m is guaranteed to be > 0
break;
}
this.rand = rand ?? Program.rand;
}
public FittingMethod fitResults()
{
FittingMethod ret = new FittingMethod(NQuantLibcPINVOKE.FittedBondDiscountCurve_fitResults(swigCPtr), false);
if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
{
throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
return(ret);
}
//! curve reference date fixed for life of curve
public FittedBondDiscountCurve(Date referenceDate,
List <BondHelper> bondHelpers,
DayCounter dayCounter,
FittingMethod fittingMethod,
double accuracy = 1.0e-10,
int maxEvaluations = 10000,
Vector guess = null,
double simplexLambda = 1.0,
int maxStationaryStateIterations = 100)
: base(referenceDate, new Calendar(), dayCounter)
{
accuracy_ = accuracy;
maxEvaluations_ = maxEvaluations;
simplexLambda_ = simplexLambda;
maxStationaryStateIterations_ = maxStationaryStateIterations;
guessSolution_ = guess;
bondHelpers_ = bondHelpers;
fittingMethod_ = fittingMethod;
fittingMethod_.curve_ = this;
setup();
}
public FittingMethod fitResults() {
FittingMethod ret = new FittingMethod(NQuantLibcPINVOKE.FittedBondDiscountCurve_fitResults(swigCPtr), false);
if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public FittedBondDiscountCurve(Date referenceDate, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_9(Date.getCPtr(referenceDate), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod)), true) {
if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
public FittedBondDiscountCurve(Date referenceDate, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod, double accuracy, uint maxEvaluations, QlArray guess) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_6(Date.getCPtr(referenceDate), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod), accuracy, maxEvaluations, QlArray.getCPtr(guess)), true) {
if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
public FittedBondDiscountCurve(uint settlementDays, Calendar calendar, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_4(settlementDays, Calendar.getCPtr(calendar), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod)), true) {
if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
public FittedBondDiscountCurve(uint settlementDays, Calendar calendar, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod, double accuracy, uint maxEvaluations, QlArray guess, double simplexLambda) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_0(settlementDays, Calendar.getCPtr(calendar), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod), accuracy, maxEvaluations, QlArray.getCPtr(guess), simplexLambda), true) {
if (NQuantLibcPINVOKE.SWIGPendingException.Pending) throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
public FittedBondDiscountCurve(Date referenceDate, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod, double accuracy, uint maxEvaluations, QlArray guess) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_6(Date.getCPtr(referenceDate), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod), accuracy, maxEvaluations, QlArray.getCPtr(guess)), true)
{
if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
{
throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
}
public FittedBondDiscountCurve(uint settlementDays, Calendar calendar, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_4(settlementDays, Calendar.getCPtr(calendar), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod)), true)
{
if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
{
throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
}
public FittedBondDiscountCurve(uint settlementDays, Calendar calendar, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod, double accuracy, uint maxEvaluations, QlArray guess, double simplexLambda) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_0(settlementDays, Calendar.getCPtr(calendar), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod), accuracy, maxEvaluations, QlArray.getCPtr(guess), simplexLambda), true)
{
if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
{
throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
}
public FittedBondDiscountCurve(Date referenceDate, RateHelperVector helpers, DayCounter dayCounter, FittingMethod fittingMethod) : this(NQuantLibcPINVOKE.new_FittedBondDiscountCurve__SWIG_9(Date.getCPtr(referenceDate), RateHelperVector.getCPtr(helpers), DayCounter.getCPtr(dayCounter), FittingMethod.getCPtr(fittingMethod)), true)
{
if (NQuantLibcPINVOKE.SWIGPendingException.Pending)
{
throw NQuantLibcPINVOKE.SWIGPendingException.Retrieve();
}
}
internal static global::System.Runtime.InteropServices.HandleRef getCPtr(FittingMethod obj)
{
return((obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.swigCPtr);
}
internal static global::System.Runtime.InteropServices.HandleRef getCPtr(FittingMethod obj) {
return (obj == null) ? new global::System.Runtime.InteropServices.HandleRef(null, global::System.IntPtr.Zero) : obj.swigCPtr;
}
private static Tuple <Solution, double> Optimize(PackingShape bin, IList <PackingItem> items, SortingMethod sorting, FittingMethod fitting, double delta, bool stackingConstraints, IEvaluator evaluator, CancellationToken token)
{
Permutation sorted = null;
switch (sorting)
{
case SortingMethod.Given:
sorted = new Permutation(PermutationTypes.Absolute, Enumerable.Range(0, items.Count).ToArray());
break;
case SortingMethod.VolumeHeight:
sorted = new Permutation(PermutationTypes.Absolute,
items.Select((v, i) => new { Index = i, Item = v })
.OrderByDescending(x => x.Item.Depth * x.Item.Width * x.Item.Height)
.ThenByDescending(x => x.Item.Height)
.Select(x => x.Index).ToArray());
break;
case SortingMethod.HeightVolume:
sorted = new Permutation(PermutationTypes.Absolute,
items.Select((v, i) => new { Index = i, Item = v })
.OrderByDescending(x => x.Item.Height)
.ThenByDescending(x => x.Item.Depth * x.Item.Width * x.Item.Height)
.Select(x => x.Index).ToArray());
break;
case SortingMethod.AreaHeight:
sorted = new Permutation(PermutationTypes.Absolute,
items.Select((v, i) => new { Index = i, Item = v })
.OrderByDescending(x => x.Item.Depth * x.Item.Width)
.ThenByDescending(x => x.Item.Height)
.Select(x => x.Index).ToArray());
break;
case SortingMethod.HeightArea:
sorted = new Permutation(PermutationTypes.Absolute,
items.Select((v, i) => new { Index = i, Item = v })
.OrderByDescending(x => x.Item.Height)
.ThenByDescending(x => x.Item.Depth * x.Item.Width)
.Select(x => x.Index).ToArray());
break;
case SortingMethod.ClusteredAreaHeight:
double clusterRange = bin.Width * bin.Depth * delta;
sorted = new Permutation(PermutationTypes.Absolute,
items.Select((v, i) => new { Index = i, Item = v, ClusterId = (int)(Math.Ceiling(v.Width * v.Depth / clusterRange)) })
.GroupBy(x => x.ClusterId)
.Select(x => new { Cluster = x.Key, Items = x.OrderByDescending(y => y.Item.Height).ToList() })
.OrderByDescending(x => x.Cluster)
.SelectMany(x => x.Items)
.Select(x => x.Index).ToArray());
break;
case SortingMethod.ClusteredHeightArea:
double clusterRange2 = bin.Height * delta;
sorted = new Permutation(PermutationTypes.Absolute,
items.Select((v, i) => new { Index = i, Item = v, ClusterId = (int)(Math.Ceiling(v.Height / clusterRange2)) })
.GroupBy(x => x.ClusterId)
.Select(x => new { Cluster = x.Key, Items = x.OrderByDescending(y => y.Item.Depth * y.Item.Width).ToList() })
.OrderByDescending(x => x.Cluster)
.SelectMany(x => x.Items)
.Select(x => x.Index).ToArray());
break;
default: throw new ArgumentException("Unknown sorting method: " + sorting);
}
ExtremePointPermutationDecoderBase decoder = null;
switch (fitting)
{
case FittingMethod.FirstFit:
decoder = new ExtremePointPermutationDecoder();
break;
case FittingMethod.FreeVolumeBestFit:
decoder = new FreeVolumeBestFitExtremePointPermutationDecoder();
break;
case FittingMethod.ResidualSpaceBestFit:
decoder = new ResidualSpaceBestFitExtremePointPermutationDecoder();
break;
default: throw new ArgumentException("Unknown fitting method: " + fitting);
}
var sol = decoder.Decode(sorted, bin, items, stackingConstraints);
var fit = evaluator.Evaluate(sol);
return(Tuple.Create(sol, fit));
}
