/**
* Copyright (C) 2012 - present by OpenGamma Inc. and the OpenGamma group of companies
*
* Please see distribution for license.
*/
package com.opengamma.analytics.financial.provider.curve.hullwhite;
import java.util.Set;
import com.opengamma.analytics.financial.interestrate.InstrumentDerivative;
import com.opengamma.analytics.financial.provider.description.interestrate.HullWhiteOneFactorProviderDiscount;
import com.opengamma.analytics.financial.provider.sensitivity.hullwhite.ParameterSensitivityHullWhiteMatrixAbstractCalculator;
import com.opengamma.analytics.math.function.Function1D;
import com.opengamma.analytics.math.matrix.DoubleMatrix1D;
import com.opengamma.analytics.math.matrix.DoubleMatrix2D;
/**
* Function computing the Jacobian of the error of valuation produce by a array representing the curve parameters.
*/
public class HullWhiteProviderDiscountFinderJacobian extends Function1D<DoubleMatrix1D, DoubleMatrix2D> {
/**
* The instrument parameter sensitivity calculator.
*/
private final ParameterSensitivityHullWhiteMatrixAbstractCalculator _parameterSensitivityCalculator;
/**
* The data required for curve building.
*/
private final HullWhiteProviderDiscountBuildingData _data;
/**
* Constructor.
* @param parameterSensitivityCalculator The instrument parameter sensitivity calculator.
* @param data The data required for curve building.
*/
public HullWhiteProviderDiscountFinderJacobian(final ParameterSensitivityHullWhiteMatrixAbstractCalculator parameterSensitivityCalculator, final HullWhiteProviderDiscountBuildingData data) {
_parameterSensitivityCalculator = parameterSensitivityCalculator;
_data = data;
}
@Override
public DoubleMatrix2D evaluate(DoubleMatrix1D x) {
final HullWhiteOneFactorProviderDiscount bundle = _data.getKnownData().copy();
HullWhiteOneFactorProviderDiscount newCurves = _data.getGeneratorMarket().evaluate(x);
bundle.setAll(newCurves);
Set<String> curvesSet = _data.getGeneratorMarket().getCurvesList();
final int nbParameters = _data.getNumberOfInstruments();
final double[][] res = new double[nbParameters][nbParameters];
for (int loopinstrument = 0; loopinstrument < _data.getNumberOfInstruments(); loopinstrument++) {
InstrumentDerivative deriv = _data.getInstrument(loopinstrument);
res[loopinstrument] = _parameterSensitivityCalculator.calculateSensitivity(deriv, bundle, curvesSet).getData();
}
return new DoubleMatrix2D(res);
}
}