public void SplineSlopeConditionsTest()
{
ClString name = "SplineSlopeConditionsTest";
BeginTest(name);
// Testing data: CallGeomBrownian; Linear, Parabolic, Exponential Data; PayoffButterfly, PayoffCallOption.
ApproximationTestsHelper test = new ApproximationTestsHelper(Log, Context, name, ConsoleOutput);
foreach (ClString testName in test.GetInputFileNames(GetType().FullName, "Slope"))
{
test.StartTest(testName);
// Read input data.
ClString fileName = testName + ".csv";
ClPoint[] data, reference;
test.ReadCSVInputData(fileName, out data, out reference);
// Read slope.
double slopeLeft = 0;
double slopeRight = 0;
var n = reference.Length;
try
{
fileName = testName + "Slope.csv";
var matrix = new ClCsvMatrix(Context.AsFileContext.LoadText(fileName));
slopeLeft = matrix[0, 0].ToDouble();
slopeRight = matrix[0, 1].ToDouble();
}
catch (Exception)
{
// if slopes are not set, calculates slopes by first and last two points of reference points.
slopeLeft = (reference[1].Value - reference[0].Value) / (reference[1].X[0] - reference[0].X[0]);
slopeRight = (reference[n - 1].Value - reference[n - 2].Value) / (reference[n - 1].X[0] - reference[n - 2].X[0]);
}
// Initialise spline and calculate spline coefficients.
var spline = new ClSplineCubicSmoothSlope1D(new Spline1DBuilder())
{
Params =
{
SlopeLeft = slopeLeft,
SlopeRight = slopeRight
}
};
spline.LoadData(data);
test.CalculationTime.Restart();
spline.Calculate();
test.CalculationTime.Stop();
// Store results and complete test.
test.Print(String.Format("Optimal lambda: {0}", spline.Params.SmoothParam));
if (PlotResults)
{
test.StoreSpline1D(spline, reference);
}
test.Print("Completed " + name + " for " + testName);
}
test.FinishTest(PrintPerformance);
}
public void SplineEndValueTest()
{
ClString name = "SplineEndValueTest";
BeginTest(name);
// Testing data: Call, Put, Risk Reversal, Straddle, Strangle, Bull, Bear, Butterfly and Barrier (Down-and-in call, Down-and-out call, Up-and-in call, Up-and-out call ) Options.
ApproximationTestsHelper test = new ApproximationTestsHelper(Log, Context, name, ConsoleOutput);
foreach (ClString testName in test.GetInputFileNames(GetType().FullName, "Value"))
{
test.StartTest(testName);
// Read input data.
ClString fileName = testName + ".csv";
ClPoint[] data, reference;
test.ReadCSVInputData(fileName, out data, out reference);
// Read end values.
double valueLeft = 0;
double valueRight = 0;
var n = reference.Length;
try
{
fileName = testName + "Value.csv";
var matrix = new ClCsvMatrix(Context.AsFileContext.LoadText(fileName));
valueLeft = matrix[0, 0].ToDouble();
valueRight = matrix[0, 1].ToDouble();
}
catch (Exception)
{
// set reference values at end points if end values are not set.
valueLeft = reference[0].Value;
valueRight = reference[n - 1].Value;
}
// Initialise spline and calculate spline coefficients.
Spline1DBuilder builder = new Spline1DBuilder();
builder.ValueLeft = valueLeft;
builder.ValueRight = valueRight;
var spline = new ClSplineCubicSmoothEndValue1D(builder);
spline.LoadData(data);
test.CalculationTime.Restart();
spline.Calculate();
test.CalculationTime.Stop();
// Store results and complete test.
test.Print(String.Format("Optimal lambda: {0}", spline.Params.SmoothParam));
if (PlotResults)
{
test.StoreSpline1D(spline, reference);
}
test.Print("Completed " + name + " for " + testName);
}
test.FinishTest(PrintPerformance);
}
/// <summary>Returns spline values on the grid with a specified step.</summary>
public ClCsvMatrix ValueOnGrid(double nodeStep)
{
ClInt n = Convert.ToInt32(Math.Ceiling((Points[PointsNumber - 1] - Points[0]) / nodeStep));
ClCsvMatrix matrix = new ClCsvMatrix(n, 2);
for (ClInt i = 0; i < n; i++)
{
ClDouble x = Points[0] + i * nodeStep;
matrix[i, 0] = x.ToVariant();
matrix[i, 1] = ValueAt(x);
}
return(matrix);
}
/// <summary> Return ClCsvMatrix with all spline coefficients. </summary>
public ClCsvMatrix GetCoefficients()
{
ClCsvMatrix matrix = new ClCsvMatrix(splineSections_.Length - 1, 6);
for (int i = 0; i < splineSections_.Length - 1; i++)
{
matrix[i, 0] = new ClDouble(splineSections_[i].X).ToVariant();
matrix[i, 1] = new ClDouble(splineSections_[i + 1].X).ToVariant();
matrix[i, 2] = new ClDouble(splineSections_[i].A).ToVariant();
matrix[i, 3] = new ClDouble(splineSections_[i].B).ToVariant();
matrix[i, 4] = new ClDouble(splineSections_[i].C).ToVariant();
matrix[i, 5] = new ClDouble(splineSections_[i].D).ToVariant();
}
return(matrix);
}
/// <summary>Return ClCsvMatrix with input data.</summary>
public ClCsvMatrix GetInputData()
{
if (!IsInitialized)
{
throw new ClEx("Spline is not initialised.");
}
// Build matrix with input data.
var matrix = new ClCsvMatrix(PointsNumber, 2);
for (ClInt i = 0; i < PointsNumber; i++)
{
matrix[i, 0] = new ClDouble(Points[i]).ToVariant();
matrix[i, 1] = new ClDouble(Values[i]).ToVariant();
}
return(matrix);
}
/// <summary>Return ClCsvMatrix with fitted data.</summary>
public ClCsvMatrix GetFittedData()
{
if (!IsCalculated)
{
throw new ClEx("Spline is not calculated.");
}
// Build matrix with fitted data.
var matrix = new ClCsvMatrix(splineMath_.DataNumber, 2);
for (ClInt i = 0; i < splineMath_.DataNumber; i++)
{
var x = Points[i];
matrix[i, 0] = new ClDouble(x).ToVariant();
matrix[i, 1] = new ClDouble(ValueAt(x)).ToVariant();
}
return(matrix);
}
public void KernelRegressionTest()
{
ClString name = "KernelRegressionTest";
BeginTest(name);
// Testing data: CallGeomBrownian; Linear, Parabolic, Exponential Data; PayoffButterfly, PayoffCallOption.
NadarayaWatsonKernelRegressionTest test = new NadarayaWatsonKernelRegressionTest(Log, Context, name, ConsoleOutput);
foreach (ClString testName in test.GetInputFileNames(GetType().FullName))
{
test.StartTest(testName);
// Read input data.
ClString fileName = testName + ".csv";
ClPoint[] data, reference;
test.ReadCSVInputData(fileName, out data, out reference);
test.TotalPointsNumber += data.Length;
// Initialise spline and calculate spline coefficients.
test.CalculationTime.Restart();
ClNadarayaWatsonKernelRegression spline = new ClNadarayaWatsonKernelRegression(new ClKernelRegressionParams());
//spline.OptimSteer.StartSeed = startSeed;
//// TODO Switch to CvGoldenSection, CvScan, NcpScan or NcpGoldenSection optimization.
//spline.OptimSteer.Method = ClSplineCubicOptimalSmooth1D.OptimizationSteering.UseMethod.CvGoldenSection;
spline.LoadData(data);
//spline.Calculate();
test.CalculationTime.Stop();
Array.Sort(data, new ClPointComparerX());
ClCsvMatrix gridData = test.ValueOnGrid(spline, data[0].X[0], data[data.Length - 1].X[0], 0.01);
// Store results and complete test.
if (PlotResults)
{
test.StoreNadarayaWatson1D(spline, data, reference, gridData);
}
test.Print("Completed " + name + " for " + testName);
}
test.FinishTest(PrintPerformance);
}
public void SplineBoundTest()
{
ClString name = "SplineBoundTest";
BeginTest(name);
// Testing data: CallGeomBrownian, PayoffButterfly, PayoffCallOption.
var test = new ApproximationTestsHelper(Log, Context, name, ConsoleOutput);
foreach (ClString testName in test.GetInputFileNames(GetType().FullName, "Bounds"))
{
test.StartTest(testName);
// Read input data.
ClString fileName = testName + ".csv";
ClPoint[] data, reference;
test.ReadCSVInputData(fileName, out data, out reference);
// Read bounds.
ClDouble boundMin;
ClDouble boundMax;
const bool fromFile = false;
// TODO Switch to true to load bounds from file
if (fromFile)
{
fileName = testName + "Bounds.csv";
ClCsvMatrix matrix = new ClCsvMatrix(Context.AsFileContext.LoadText(fileName));
boundMin = matrix[0, 0].ToDouble();
boundMax = matrix[0, 1].ToDouble();
}
else
{
var refer = new double[reference.Length];
for (var i = 0; i < refer.Length; i++)
{
refer[i] = reference[i].Value;
}
boundMin = refer.Min();
boundMax = refer.Max();
}
// Initialise spline and calculate spline coefficients.
var splineParams = new Spline1DBuilder {
Min = boundMin, Max = boundMax
};
var spline = new ClSplineCubicSmooth1D(splineParams);
spline.LoadData(data);
test.CalculationTime.Restart();
spline.Calculate();
test.CalculationTime.Stop();
// Store results and complete test.
if (PlotResults)
{
test.StoreSpline1D(spline, reference);
}
test.Print("Completed " + name + " for " + testName);
}
test.FinishTest(PrintPerformance);
}
