/**
* Copyright (C) 2012 - present by OpenGamma Inc. and the OpenGamma group of companies
*
* Please see distribution for license.
*/
package com.opengamma.analytics.financial.curve.interestrate.building;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.LinkedHashMap;
import java.util.List;
import org.apache.commons.lang.ArrayUtils;
import com.opengamma.analytics.financial.curve.interestrate.generator.GeneratorYDCurve;
import com.opengamma.analytics.financial.curve.interestrate.sensitivity.ParameterUnderlyingSensitivityCalculator;
import com.opengamma.analytics.financial.interestrate.InstrumentDerivative;
import com.opengamma.analytics.financial.interestrate.InstrumentDerivativeVisitor;
import com.opengamma.analytics.financial.interestrate.InterestRateCurveSensitivity;
import com.opengamma.analytics.financial.interestrate.YieldCurveBundle;
import com.opengamma.analytics.financial.provider.curve.CurveBuildingBlock;
import com.opengamma.analytics.financial.provider.curve.CurveBuildingBlockBundle;
import com.opengamma.analytics.financial.provider.curve.multicurve.MulticurveDiscountBuildingRepository;
import com.opengamma.analytics.math.function.Function1D;
import com.opengamma.analytics.math.linearalgebra.DecompositionFactory;
import com.opengamma.analytics.math.matrix.CommonsMatrixAlgebra;
import com.opengamma.analytics.math.matrix.DoubleMatrix1D;
import com.opengamma.analytics.math.matrix.DoubleMatrix2D;
import com.opengamma.analytics.math.matrix.MatrixAlgebra;
import com.opengamma.analytics.math.rootfinding.newton.BroydenVectorRootFinder;
import com.opengamma.util.tuple.ObjectsPair;
import com.opengamma.util.tuple.Pair;
/**
* Functions to build curves.
* @deprecated Curve builders that use and populate {@link YieldCurveBundle}s are deprecated. Use classes such as
* {@link MulticurveDiscountBuildingRepository}.
*/
@Deprecated
public class CurveBuildingFunction {
/**
* The absolute tolerance for the root finder.
*/
private final double _toleranceAbs;
/**
* The relative tolerance for the root finder.
*/
private final double _toleranceRel;
/**
* The relative tolerance for the root finder.
*/
private final int _stepMaximum;
/**
* The root finder used for curve calibration.
*/
private final BroydenVectorRootFinder _rootFinder;
/**
* The matrix algebra used for matrix inversion.
*/
private static final MatrixAlgebra MATRIX_ALGEBRA = new CommonsMatrixAlgebra();
/**
* Constructor.
* @param toleranceAbs The absolute tolerance for the root finder.
* @param toleranceRel The relative tolerance for the root finder.
* @param stepMaximum The maximum number of step for the root finder.
*/
public CurveBuildingFunction(final double toleranceAbs, final double toleranceRel, final int stepMaximum) {
_toleranceAbs = toleranceAbs;
_toleranceRel = toleranceRel;
_stepMaximum = stepMaximum;
_rootFinder = new BroydenVectorRootFinder(_toleranceAbs, _toleranceRel, _stepMaximum, DecompositionFactory.getDecomposition(DecompositionFactory.SV_COLT_NAME));
// TODO: make the root finder flexible.
}
/**
* Build a unit of curves.
* @param instruments The instruments used for the unit calibration.
* @param initGuess The initial parameters guess.
* @param curveGenerators The map of curve names to curve generators used to build the unit.
* @param knownData The known data (fx rates, other curves, model parameters, ...)
* @param calculator The calculator of the value on which the calibration is done (usually ParSpreadMarketQuoteCalculator (recommended) or converted present value).
* @param sensitivityCalculator The parameter sensitivity calculator.
* @return The new curves and the calibrated parameters.
*/
public Pair<YieldCurveBundle, Double[]> makeUnit(final InstrumentDerivative[] instruments, final double[] initGuess, final LinkedHashMap<String, GeneratorYDCurve> curveGenerators,
final YieldCurveBundle knownData,
final InstrumentDerivativeVisitor<YieldCurveBundle, Double> calculator, final InstrumentDerivativeVisitor<YieldCurveBundle, InterestRateCurveSensitivity> sensitivityCalculator) {
final MultipleYieldCurveFinderGeneratorDataBundle data = new MultipleYieldCurveFinderGeneratorDataBundle(instruments, knownData, curveGenerators);
final Function1D<DoubleMatrix1D, DoubleMatrix1D> curveCalculator = new MultipleYieldCurveFinderGeneratorFunction(calculator, data);
final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new MultipleYieldCurveFinderGeneratorJacobian(new ParameterUnderlyingSensitivityCalculator(sensitivityCalculator), data);
final double[] parameters = _rootFinder.getRoot(curveCalculator, jacobianCalculator, new DoubleMatrix1D(initGuess)).getData();
final YieldCurveBundle newCurves = data.getBuildingFunction().evaluate(new DoubleMatrix1D(parameters));
return new ObjectsPair<>(newCurves, ArrayUtils.toObject(parameters));
}
/**
* Build the Jacobian matrixes associated to a unit of curves.
* @param instruments The instruments used for the block calibration.
* @param curveGenerators The map of curve names to curve generators used to build the block.
* @param startBlock The index of the first parameter of the unit in the block.
* @param nbParameters The number of parameters for each curve in the unit.
* @param parameters The parameters used to build each curve in the block.
* @param knownData The known data (FX rates, other curves, model parameters, ...) for the block calibration.
* @param sensitivityCalculator The parameter sensitivity calculator for the value on which the calibration is done (usually ParSpreadMarketQuoteCalculator (recommended) or converted present value).
* @return The part of the inverse Jacobian matrix associated to each curve.
* The Jacobian matrix is the transition matrix between the curve parameters and the par spread.
* TODO: Currently only for the ParSpreadMarketQuoteCalculator.
*/
public DoubleMatrix2D[] makeCurveMatrix(final InstrumentDerivative[] instruments, final LinkedHashMap<String, GeneratorYDCurve> curveGenerators, final int startBlock, final int[] nbParameters,
final Double[] parameters,
final YieldCurveBundle knownData, final InstrumentDerivativeVisitor<YieldCurveBundle, InterestRateCurveSensitivity> sensitivityCalculator) {
final MultipleYieldCurveFinderGeneratorDataBundle data = new MultipleYieldCurveFinderGeneratorDataBundle(instruments, knownData, curveGenerators);
final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new MultipleYieldCurveFinderGeneratorJacobian(new ParameterUnderlyingSensitivityCalculator(sensitivityCalculator), data);
final DoubleMatrix2D jacobian = jacobianCalculator.evaluate(new DoubleMatrix1D(parameters));
final DoubleMatrix2D inverseJacobian = MATRIX_ALGEBRA.getInverse(jacobian);
final double[][] matrixTotal = inverseJacobian.getData();
final DoubleMatrix2D[] result = new DoubleMatrix2D[nbParameters.length];
int startCurve = 0;
for (int loopmat = 0; loopmat < nbParameters.length; loopmat++) {
final double[][] matrixCurve = new double[nbParameters[loopmat]][matrixTotal.length];
for (int loopparam = 0; loopparam < nbParameters[loopmat]; loopparam++) {
matrixCurve[loopparam] = matrixTotal[startBlock + startCurve + loopparam].clone();
}
result[loopmat] = new DoubleMatrix2D(matrixCurve);
startCurve += nbParameters[loopmat];
}
return result;
}
/**
* Build a block of curves.
* @param instruments The instruments used for the block calibration.
* @param curveGenerators The curve generators (final version). As an array of arrays, representing the units and the curves within the units.
* @param curveNames The names of the different curves. As an array of arrays, representing the units and the curves within the units.
* @param parametersGuess The initial guess for the parameters. As an array of arrays, representing the units and the parameters for one unit (all the curves of the unit concatenated).
* @param knownData The known data (fx rates, other curves, model parameters, ...)
* @param calculator The calculator of the value on which the calibration is done (usually ParSpreadMarketQuoteCalculator (recommended) or converted present value).
* @param sensitivityCalculator The parameter sensitivity calculator.
* @return A pair with the calibrated yield curve bundle (including the known data) and the CurveBuildingBlckBundle with the relevant inverse Jacobian Matrix.
*/
public Pair<YieldCurveBundle, CurveBuildingBlockBundle> makeCurvesFromDerivatives(final InstrumentDerivative[][][] instruments, final GeneratorYDCurve[][] curveGenerators,
final String[][] curveNames,
final double[][] parametersGuess, final YieldCurveBundle knownData, final InstrumentDerivativeVisitor<YieldCurveBundle, Double> calculator,
final InstrumentDerivativeVisitor<YieldCurveBundle, InterestRateCurveSensitivity> sensitivityCalculator) {
final int nbUnits = curveGenerators.length;
final YieldCurveBundle knownSoFarData = knownData.copy();
final List<InstrumentDerivative> instrumentsSoFar = new ArrayList<>();
final LinkedHashMap<String, GeneratorYDCurve> generatorsSoFar = new LinkedHashMap<>();
final LinkedHashMap<String, Pair<CurveBuildingBlock, DoubleMatrix2D>> unitBundleSoFar = new LinkedHashMap<>();
final List<Double> parametersSoFar = new ArrayList<>();
final LinkedHashMap<String, Pair<Integer, Integer>> unitMap = new LinkedHashMap<>();
int startUnit = 0;
for (int loopunit = 0; loopunit < nbUnits; loopunit++) {
final int nbCurve = curveGenerators[loopunit].length;
final int[] startCurve = new int[nbCurve]; // First parameter index of the curve in the unit.
final LinkedHashMap<String, GeneratorYDCurve> gen = new LinkedHashMap<>();
final int[] nbIns = new int[curveGenerators[loopunit].length];
int nbInsUnit = 0; // Number of instruments in the unit.
for (int loopcurve = 0; loopcurve < nbCurve; loopcurve++) {
startCurve[loopcurve] = nbInsUnit;
nbIns[loopcurve] = instruments[loopunit][loopcurve].length;
nbInsUnit += nbIns[loopcurve];
instrumentsSoFar.addAll(Arrays.asList(instruments[loopunit][loopcurve]));
}
final InstrumentDerivative[] instrumentsUnit = new InstrumentDerivative[nbInsUnit];
final InstrumentDerivative[] instrumentsSoFarArray = instrumentsSoFar.toArray(new InstrumentDerivative[instrumentsSoFar.size()]);
for (int loopcurve = 0; loopcurve < nbCurve; loopcurve++) {
System.arraycopy(instruments[loopunit][loopcurve], 0, instrumentsUnit, startCurve[loopcurve], nbIns[loopcurve]);
}
for (int loopcurve = 0; loopcurve < nbCurve; loopcurve++) {
final GeneratorYDCurve tmp = curveGenerators[loopunit][loopcurve].finalGenerator(instruments[loopunit][loopcurve]);
gen.put(curveNames[loopunit][loopcurve], tmp);
generatorsSoFar.put(curveNames[loopunit][loopcurve], tmp);
unitMap.put(curveNames[loopunit][loopcurve], new ObjectsPair<>(startUnit + startCurve[loopcurve], nbIns[loopcurve]));
}
final Pair<YieldCurveBundle, Double[]> unitCal = makeUnit(instrumentsUnit, parametersGuess[loopunit], gen, knownSoFarData, calculator, sensitivityCalculator);
parametersSoFar.addAll(Arrays.asList(unitCal.getSecond()));
final DoubleMatrix2D[] mat = makeCurveMatrix(instrumentsSoFarArray, generatorsSoFar, startUnit, nbIns, parametersSoFar.toArray(new Double[parametersSoFar.size()]),
knownData, sensitivityCalculator);
for (int loopcurve = 0; loopcurve < curveGenerators[loopunit].length; loopcurve++) {
unitBundleSoFar.put(curveNames[loopunit][loopcurve], new ObjectsPair<>(new CurveBuildingBlock(unitMap), mat[loopcurve]));
}
knownSoFarData.addAll(unitCal.getFirst());
startUnit = startUnit + nbInsUnit;
}
return new ObjectsPair<>(knownSoFarData, new CurveBuildingBlockBundle(unitBundleSoFar));
}
}