//! Calibrate to a set of market instruments (caps/swaptions)
/*! An additional constraint can be passed which must be
* satisfied in addition to the constraints of the model.
*/
//public void calibrate(List<CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
// Constraint constraint = new Constraint(), List<double> weights = new List<double>()) {
public void calibrate(List <CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
Constraint additionalConstraint, List <double> weights)
{
if (!(weights.Count == 0 || weights.Count == instruments.Count))
{
throw new ApplicationException("mismatch between number of instruments and weights");
}
Constraint c;
if (additionalConstraint.empty())
{
c = constraint_;
}
else
{
c = new CompositeConstraint(constraint_, additionalConstraint);
}
List <double> w = weights.Count == 0 ? new InitializedList <double>(instruments.Count, 1.0): weights;
CalibrationFunction f = new CalibrationFunction(this, instruments, w);
Problem prob = new Problem(f, c, parameters());
shortRateEndCriteria_ = method.minimize(prob, endCriteria);
Vector result = new Vector(prob.currentValue());
setParams(result);
// recheck
Vector shortRateProblemValues_ = prob.values(result);
notifyObservers();
}
public double value(Vector p, List <CalibrationHelper> instruments)
{
List <double> w = new InitializedList <double>(instruments.Count, 1.0);
CalibrationFunction f = new CalibrationFunction(this, instruments, w);
return(f.value(p));
}
public ProcessData()
{
InitializeComponent();
this.cbMacro.Items.Add("Default");
this.cbMacro.SelectedIndex = 0;
this.cbCalFunctions.Items.Add("None");
this.cbCalFunctions.Items.Add("S. cerevisiae");
this.cbCalFunctions.Items.Add("S. pombe");
this.cbCalFunctions.Items.Add("C. albicans");
this.cbCalFunctions.Items.Add("P. pastoris");
this.cbCalFunctions.Items.Add("E. coli");
this.cbCalFunctions.Items.Add("Custom");
this.cbCalFunctions.SelectedIndex = 1;
this.txBlank.Text = "0";
BlankValue = 0;
txtCoeffA.Text = "1";
txtCoeffB.Text = "0";
txtCoeffC.Text = "0.8324057";
TrueODCalibarationFunction = new CalibrationFunction();
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, (float)0.8324057);
}
public double value(Vector parameters, List <CalibrationHelper> instruments)
{
List <double> w = new InitializedList <double>(instruments.Count, 1.0);
Projection p = new Projection(parameters);
CalibrationFunction f = new CalibrationFunction(this, instruments, w, p);
return(f.value(parameters));
}
//! Calibrate to a set of market instruments (caps/swaptions)
/*! An additional constraint can be passed which must be
* satisfied in addition to the constraints of the model.
*/
//public void calibrate(List<CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
// Constraint constraint = new Constraint(), List<double> weights = new List<double>()) {
public void calibrate(List <CalibrationHelper> instruments,
OptimizationMethod method,
EndCriteria endCriteria,
Constraint additionalConstraint = null,
List <double> weights = null,
List <bool> fixParameters = null)
{
if (weights == null)
{
weights = new List <double>();
}
if (additionalConstraint == null)
{
additionalConstraint = new Constraint();
}
Utils.QL_REQUIRE(weights.empty() || weights.Count == instruments.Count, () =>
"mismatch between number of instruments (" +
instruments.Count + ") and weights(" +
weights.Count + ")");
Constraint c;
if (additionalConstraint.empty())
{
c = constraint_;
}
else
{
c = new CompositeConstraint(constraint_, additionalConstraint);
}
List <double> w = weights.Count == 0 ? new InitializedList <double>(instruments.Count, 1.0): weights;
Vector prms = parameters();
List <bool> all = new InitializedList <bool>(prms.size(), false);
Projection proj = new Projection(prms, fixParameters ?? all);
CalibrationFunction f = new CalibrationFunction(this, instruments, w, proj);
ProjectedConstraint pc = new ProjectedConstraint(c, proj);
Problem prob = new Problem(f, pc, proj.project(prms));
shortRateEndCriteria_ = method.minimize(prob, endCriteria);
Vector result = new Vector(prob.currentValue());
setParams(proj.include(result));
Vector shortRateProblemValues_ = prob.values(result);
notifyObservers();
//CalibrationFunction f = new CalibrationFunction(this, instruments, w);
//Problem prob = new Problem(f, c, parameters());
//shortRateEndCriteria_ = method.minimize(prob, endCriteria);
//Vector result = new Vector(prob.currentValue());
//setParams(result);
//// recheck
//Vector shortRateProblemValues_ = prob.values(result);
//notifyObservers();
}
private static CalibrationFunction SetCalibrationFunction(float calibrationCoefA, float calibrationCoefB, float calibrationCoefC)
{
var trueODCalibartionFunction = new CalibrationFunction();
trueODCalibartionFunction.AddTerm(0, calibrationCoefA);
trueODCalibartionFunction.AddTerm(1, calibrationCoefB);
trueODCalibartionFunction.AddTerm(2, calibrationCoefC);
return(trueODCalibartionFunction);
}
public double value(Vector p, List<CalibrationHelper> instruments)
{
List<double> w = new InitializedList<double>(instruments.Count, 1.0);
CalibrationFunction f = new CalibrationFunction(this, instruments, w);
return f.value(p);
}
//! Calibrate to a set of market instruments (caps/swaptions)
/*! An additional constraint can be passed which must be
satisfied in addition to the constraints of the model.
*/
//public void calibrate(List<CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
// Constraint constraint = new Constraint(), List<double> weights = new List<double>()) {
public void calibrate(List<CalibrationHelper> instruments, OptimizationMethod method, EndCriteria endCriteria,
Constraint additionalConstraint, List<double> weights)
{
if (!(weights.Count == 0 || weights.Count == instruments.Count))
throw new ApplicationException("mismatch between number of instruments and weights");
Constraint c;
if (additionalConstraint.empty())
c = constraint_;
else
c = new CompositeConstraint(constraint_,additionalConstraint);
List<double> w = weights.Count == 0 ? new InitializedList<double>(instruments.Count, 1.0): weights;
CalibrationFunction f = new CalibrationFunction(this, instruments, w);
Problem prob = new Problem(f, c, parameters());
shortRateEndCriteria_ = method.minimize(prob, endCriteria);
Vector result = new Vector(prob.currentValue());
setParams(result);
// recheck
Vector shortRateProblemValues_ = prob.values(result);
notifyObservers();
}
private void SetCalibrationFunction()
{
Single coeffA;
Single coeffB;
Single coeffC;
if (cbCalFunctions.SelectedIndex != 6)
{
TrueODCalibarationFunction = new CalibrationFunction();
var x = cbCalFunctions.SelectedIndex;
switch (x)
{
case 0:
//None
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, 0);
break;
case 1:
//S. cerevisiae
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, (float)0.8324057);
break;
case 2:
//S. pombe
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, (float)0.64672463774234579);
break;
case 3:
//C. albicans
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, (float)0.5790256635480614);
break;
case 4:
//P. pastoris
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, (float)0.5653284345804932);
break;
case 5:
//E.coli
TrueODCalibarationFunction.AddTerm(0, 1);
TrueODCalibarationFunction.AddTerm(1, 0);
TrueODCalibarationFunction.AddTerm(2, (float)0.75389848795692815);
break;
}
}
else
{
var isCoeefAValid = ValidateTextBoxEntry(txtCoeffA, out coeffA);
var isCoeefBValid = ValidateTextBoxEntry(txtCoeffB, out coeffB);
var isCoeefCValid = ValidateTextBoxEntry(txtCoeffC, out coeffC);
if (!isCoeefAValid || !isCoeefBValid || !isCoeefCValid)
{
return;
}
TrueODCalibarationFunction = new CalibrationFunction();
TrueODCalibarationFunction.AddTerm(0, coeffA);
TrueODCalibarationFunction.AddTerm(1, coeffB);
TrueODCalibarationFunction.AddTerm(2, coeffC);
}
}
public CalibrationFunctionOption(CalibrationFunction func)
{
TF = func;
}
private static void SetThinRawData(bool apply, ref Culture culture, float blankValue, CalibrationFunction trueODCalibartionFunction, int pointsToSkip = 0)
{
if (!apply)
{
return;
}
AddRawThinned(ref culture, pointsToSkip, false, trueODCalibartionFunction);
var thinRaw = culture.GrowthMeasurements.GetMeasurements(DataType.RawThinned);
var processesThinned = Modules.ProccessedDatapoints(thinRaw, blankValue, trueODCalibartionFunction);
culture.GrowthMeasurements.SetMeasurements(processesThinned, DataType.ProcessedThinned);
}
private static List <GrowthMeasurement> NNSmoothProcessedData(bool apply, List <GrowthMeasurement> raw, List <GrowthMeasurement> smooth, float blankValue, CalibrationFunction trueODCalibartionFunction, int count, float maxPeak)
{
if (!apply)
{
return(smooth);
}
var neuroD = new Neural();
var fittedRaw = neuroD.GetFittedData(raw);
return(Modules.ProccessedDatapoints(fittedRaw, blankValue, trueODCalibartionFunction, out count, out maxPeak, true));
}
private static void ProcessData(Culture culture, float blankValue, bool doFit, CalibrationFunction trueODCalibartionFunction, bool skipMonotonicFilter = false)
{
var raw = culture.GrowthMeasurements.GetMeasurements(DataType.Raw);
var count = 0;
float maxPeak = 0;
var treated = Modules.ProccessedDatapoints(raw, blankValue, trueODCalibartionFunction, out count, out maxPeak, false, false, skipMonotonicFilter);
treated = NNSmoothProcessedData(false, raw, treated, blankValue, trueODCalibartionFunction, count, maxPeak);
SetRawFilteredData(false, raw, ref culture);
SetRawUnFilteredData(false, raw, ref culture, blankValue);
var uncalibrated = Modules.ProccessedDatapoints(raw, blankValue, trueODCalibartionFunction, out count, out maxPeak, false, true);
culture.GrowthMeasurements.SetMeasurements(uncalibrated, DataType.ProcessedUncalibrated);
if (count > 0)
{
SessionVariables.Peaks.Add(new Peak {
Well = culture.Container, MaxPeak = maxPeak, Number = count
});
}
culture.GrowthMeasurements.SetMeasurements(treated, DataType.Processed);
var firstDeriv = Modules.CalculateFirstDerivative(treated, FirstDerivWindow);
culture.GrowthMeasurements.SetMeasurements(firstDeriv, DataType.FirstDerivative);
SetNNSmoothFirstDeriv(false, firstDeriv, ref culture);
culture.GrowthMeasurements.SetMeasurements(Modules.ConvertBioScreenTimeToHrs(raw), DataType.Raw);
if (doFit)
{
SetNNSmoothProcessed(culture, treated);
}
}
public static void AddRawThinned(ref Culture culture, int skip = 0, bool isFirstDeriv = false, CalibrationFunction calibrationFunction = null)
{
var raw = culture.GrowthMeasurements.GetMeasurements(DataType.Raw);
var thinRaw = new List <GrowthMeasurement>();
for (int i = 0; i < raw.Count; i += skip + 1)
{
var measurement = raw[i];
thinRaw.Add(measurement);
}
culture.GrowthMeasurements.SetMeasurements(thinRaw, DataType.RawThinned);
var processesThinned = Modules.ReProccessedDatapoints(thinRaw, BlankValue, calibrationFunction);
if (isFirstDeriv)
{
var firstDeriv = Modules.CalculateFirstDerivative(processesThinned, FirstDerivWindow);
culture.GrowthMeasurements.SetMeasurements(firstDeriv, DataType.FirstDerivative);
}
culture.GrowthMeasurements.SetMeasurements(processesThinned, DataType.ProcessedThinned);
if (Modules.NoGrowth(processesThinned))
{
return;
}
var metaDataThinned = new GrowthVariableMetaData();
var macroLagData = Modules.GetLag(processesThinned);
metaDataThinned.Lag = macroLagData.InterceptStretchs;
var macroYieldData = Modules.GetYield(processesThinned);
metaDataThinned.Yield = macroYieldData.YieldAnchors;
var macroRateData = Modules.GetGT(processesThinned);
metaDataThinned.Rate = macroRateData.RateSlopeAnchors;
culture.GrowthMeasurements.SetMetaData(DataType.ProcessedThinned, metaDataThinned);
}
