Package com.opengamma.analytics.math.matrix

Examples of com.opengamma.analytics.math.matrix.DoubleMatrix1D

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  @Override
  public DoubleMatrix1D getKnotsMat1D(final double[] xValues) {
    final int nData = xValues.length;
    if (nData == 2) {
      return new DoubleMatrix1D(new double[] {xValues[0], xValues[nData - 1] });
    }
    if (nData == 3) {
      return new DoubleMatrix1D(new double[] {xValues[0], xValues[nData - 1] });
    }
    return new DoubleMatrix1D(xValues);
  }
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    ArgumentChecker.notNull(ccy1, "currency 1");
    ArgumentChecker.notNull(ccy2, "currency 2");
    ArgumentChecker.isTrue(numberExpiry >= 0, "number of expiries must be greater than or equal to zero");
    ArgumentChecker.isTrue(numberDelta >= 0, "number of deltas must be greater than or equal to zero");
    _currencyPair = ObjectsPair.of(ccy1, ccy2);
    _expiries = new DoubleMatrix1D(new double[numberExpiry]);
    _delta = new DoubleMatrix1D(new double[numberDelta]);
    _vega = new DoubleMatrix2D(numberExpiry, numberDelta);
  }
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      _calibrationObjective.setInstruments(instruments);
      _calibrationObjective.setPrice(prices);
      objective.setStartIndex(_instrumentIndex.get(loopblock * _nbInstrumentsBlock));
      objective.setEndIndex(_instrumentIndex.get((loopblock + 1) * _nbInstrumentsBlock) - 1);
      // Implementation note: the index start is from the first instrument of the block and the index end is from the last instrument of the block.
      final DoubleMatrix1D observedValues = new DoubleMatrix1D(_nbInstrumentsBlock, 0.0);
      @SuppressWarnings("unused")
      final
      LeastSquareResults result = ls.solve(observedValues, _calibrationObjective, new DoubleMatrix1D(1.0, 0.0));
      // Implementation note: the start value is a multiplicative factor of one and an additive term of 0 (parameters unchanged).
      //   The observed values are 0 as the function returns the difference between the calculated prices and the targets.
    }
  }
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          sensitivity[loopccypv][loopnode] = pvDiff.getAmount(ccyList.get(loopccypv)) / _shift;
        }
      }
      final String name = multicurve.getName(index);
      for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
        result = result.plus(new ObjectsPair<>(name, ccyList.get(loopccypv)), new DoubleMatrix1D(sensitivity[loopccypv]));
      }
    }

    // Discounting
    final Set<Currency> ccyDiscounting = multicurve.getCurrencies();
    for (final Currency ccy : ccyDiscounting) {
      final YieldAndDiscountCurve curve = multicurve.getCurve(ccy);
      ArgumentChecker.isTrue(curve instanceof YieldCurve, "Curve should be a YieldCurve");
      final YieldCurve curveYield = (YieldCurve) curve;
      ArgumentChecker.isTrue(curveYield.getCurve() instanceof InterpolatedDoublesCurve, "Yield curve should be based on InterpolatedDoublesCurve");
      final InterpolatedDoublesCurve curveInt = (InterpolatedDoublesCurve) curveYield.getCurve();
      final int nbNodePoint = curveInt.getXDataAsPrimitive().length;
      final double[][] sensitivity = new double[nbCcy][nbNodePoint];
      for (int loopnode = 0; loopnode < nbNodePoint; loopnode++) {
        final double[] yieldBumped = curveInt.getYDataAsPrimitive().clone();
        yieldBumped[loopnode] += _shift;
        final YieldAndDiscountCurve dscBumped = new YieldCurve(curveInt.getName(), new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumped, curveInt.getInterpolator(), true));
        final InflationProviderDiscount marketDscBumped = multicurve.withDiscountFactor(ccy, dscBumped);
        final MultipleCurrencyAmount pvBumped = instrument.accept(_valueCalculator, marketDscBumped);
        final MultipleCurrencyAmount pvDiff = pvBumped.plus(pvInitMinus);
        for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
          sensitivity[loopccypv][loopnode] = pvDiff.getAmount(ccyList.get(loopccypv)) / _shift;
        }
      }
      final String name = multicurve.getName(ccy);
      for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
        result = result.plus(new ObjectsPair<>(name, ccyList.get(loopccypv)), new DoubleMatrix1D(sensitivity[loopccypv]));
      }
    }
    // Forward ON
    final Set<IndexON> indexON = multicurve.getIndexesON();
    for (final IndexON index : indexON) {
      final YieldAndDiscountCurve curve = multicurve.getCurve(index);
      ArgumentChecker.isTrue(curve instanceof YieldCurve, "Curve should be a YieldCurve");
      final YieldCurve curveYield = (YieldCurve) curve;
      ArgumentChecker.isTrue(curveYield.getCurve() instanceof InterpolatedDoublesCurve, "Yield curve should be based on InterpolatedDoublesCurve");
      final InterpolatedDoublesCurve curveInt = (InterpolatedDoublesCurve) curveYield.getCurve();
      final int nbNodePoint = curveInt.getXDataAsPrimitive().length;
      final double[][] sensitivity = new double[nbCcy][nbNodePoint];
      for (int loopnode = 0; loopnode < nbNodePoint; loopnode++) {
        final double[] yieldBumped = curveInt.getYDataAsPrimitive().clone();
        yieldBumped[loopnode] += _shift;
        final YieldAndDiscountCurve fwdBumped = new YieldCurve(curveInt.getName(), new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumped, curveInt.getInterpolator(), true));
        final InflationProviderDiscount marketFwdBumped = multicurve.withForward(index, fwdBumped);
        final MultipleCurrencyAmount pvBumped = instrument.accept(_valueCalculator, marketFwdBumped);
        final MultipleCurrencyAmount pvDiff = pvBumped.plus(pvInitMinus);
        for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
          sensitivity[loopccypv][loopnode] = pvDiff.getAmount(ccyList.get(loopccypv)) / _shift;
        }
      }
      final String name = multicurve.getName(index);
      for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
        result = result.plus(new ObjectsPair<>(name, ccyList.get(loopccypv)), new DoubleMatrix1D(sensitivity[loopccypv]));
      }
    }
    // Forward Ibor
    final Set<IborIndex> indexForward = multicurve.getIndexesIbor();
    for (final IborIndex index : indexForward) {
      final YieldAndDiscountCurve curve = multicurve.getCurve(index);
      ArgumentChecker.isTrue(curve instanceof YieldCurve, "Curve should be a YieldCurve");
      final YieldCurve curveYield = (YieldCurve) curve;
      ArgumentChecker.isTrue(curveYield.getCurve() instanceof InterpolatedDoublesCurve, "Yield curve should be based on InterpolatedDoublesCurve");
      final InterpolatedDoublesCurve curveInt = (InterpolatedDoublesCurve) curveYield.getCurve();
      final int nbNodePoint = curveInt.getXDataAsPrimitive().length;
      final double[][] sensitivity = new double[nbCcy][nbNodePoint];
      for (int loopnode = 0; loopnode < nbNodePoint; loopnode++) {
        final double[] yieldBumped = curveInt.getYDataAsPrimitive().clone();
        yieldBumped[loopnode] += _shift;
        final YieldAndDiscountCurve fwdBumped = new YieldCurve(curveInt.getName(), new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumped, curveInt.getInterpolator(), true));
        final InflationProviderDiscount marketFwdBumped = multicurve.withForward(index, fwdBumped);
        final MultipleCurrencyAmount pvBumped = instrument.accept(_valueCalculator, marketFwdBumped);
        final MultipleCurrencyAmount pvDiff = pvBumped.plus(pvInitMinus);
        for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
          sensitivity[loopccypv][loopnode] = pvDiff.getAmount(ccyList.get(loopccypv)) / _shift;
        }
      }
      final String name = multicurve.getName(index);
      for (int loopccypv = 0; loopccypv < nbCcy; loopccypv++) {
        result = result.plus(new ObjectsPair<>(name, ccyList.get(loopccypv)), new DoubleMatrix1D(sensitivity[loopccypv]));
      }
    }
    return result;
  }
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        ArgumentChecker.isFalse(Double.isNaN(coefs[i][j]), "Too large input");
        ArgumentChecker.isFalse(Double.isInfinite(coefs[i][j]), "Too large input");
      }
    }

    return new PiecewisePolynomialResult(new DoubleMatrix1D(xValuesSrt), new DoubleMatrix2D(coefs), 6, 1);
  }
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      }
      for (int loops = 0; loops < nbNewParamSensiCurve[loopcurve]; loops++) {
        sensiClean[startCleanParameter[loopcurve] + loops] += sensiDirty[startDirtyParameter[loopcurve][indexOtherSensiCurve[loopcurve].length] + loops];
      }
    }
    return new DoubleMatrix1D(sensiClean);
  }
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        ArgumentChecker.isFalse(Double.isNaN(resMatrix[i][j]), "Too large input");
        ArgumentChecker.isFalse(Double.isInfinite(resMatrix[i][j]), "Too large input");
      }
    }

    return new PiecewisePolynomialResult(new DoubleMatrix1D(xValuesSrt), new DoubleMatrix2D(resMatrix), nCoefs, dim);
  }
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      bValues = bValuesCalculator(slopes, first);
      intervalsA = getIntervalsA(intervals, slopes, first, bValues);
      intervalsB = getIntervalsB(intervals, slopes, first, aValues);
    }
    final double[] second = secondDerivativeCalculator(initialSecond, intervalsA, intervalsB);
    firstWithSensitivity[0] = new DoubleMatrix1D(first);
    secondWithSensitivity[0] = new DoubleMatrix1D(second);

    /*
     * Centered finite difference method is used for computing node sensitivity
     */
    int nExtra = (nDataPts == yValuesLen) ? 0 : 1;
    final double[] yValuesUp = Arrays.copyOf(yValues, nDataPts + 2 * nExtra);
    final double[] yValuesDw = Arrays.copyOf(yValues, nDataPts + 2 * nExtra);
    final double[][] tmpFirst = new double[nDataPts][nDataPts];
    final double[][] tmpSecond = new double[nDataPts][nDataPts];
    for (int l = nExtra; l < nDataPts + nExtra; ++l) {
      final double den = Math.abs(yValues[l]) < SMALL ? EPS : yValues[l] * EPS;
      yValuesUp[l] = Math.abs(yValues[l]) < SMALL ? EPS : yValues[l] * (1. + EPS);
      yValuesDw[l] = Math.abs(yValues[l]) < SMALL ? -EPS : yValues[l] * (1. - EPS);
      final double[] yValuesSrtUp = Arrays.copyOfRange(yValuesUp, nExtra, nDataPts + nExtra);
      final double[] yValuesSrtDw = Arrays.copyOfRange(yValuesDw, nExtra, nDataPts + nExtra);

      final DoubleMatrix1D[] yValuesUpDw = new DoubleMatrix1D[] {new DoubleMatrix1D(yValuesUp), new DoubleMatrix1D(yValuesDw) };
      final DoubleMatrix1D[] yValuesSrtUpDw = new DoubleMatrix1D[] {new DoubleMatrix1D(yValuesSrtUp), new DoubleMatrix1D(yValuesSrtDw) };
      final DoubleMatrix1D[] firstSecondUpDw = new DoubleMatrix1D[4];
      for (int ii = 0; ii < 2; ++ii) {
        final double[] slopesUpDw = _solver.slopesCalculator(yValuesSrtUpDw[ii].getData(), intervals);
        final PiecewisePolynomialResult resultUpDw = _method.interpolate(xValues, yValuesUpDw[ii].getData());
        final double[] initialFirstUpDw = _function.differentiate(resultUpDw, xValues).getData()[0];
        final double[] initialSecondUpDw = _function.differentiateTwice(resultUpDw, xValues).getData()[0];
        double[] firstUpDw = firstDerivativeCalculator(yValuesSrtUpDw[ii].getData(), intervals, slopesUpDw, initialFirstUpDw);
        boolean modFirstUpDw = false;
        double[] aValuesUpDw = aValuesCalculator(slopesUpDw, firstUpDw);
        double[] bValuesUpDw = bValuesCalculator(slopesUpDw, firstUpDw);
        double[][] intervalsAUpDw = getIntervalsA(intervals, slopesUpDw, firstUpDw, bValuesUpDw);
        double[][] intervalsBUpDw = getIntervalsB(intervals, slopesUpDw, firstUpDw, aValuesUpDw);
        while (modFirstUpDw == false) {
          k = 0;
          for (int i = 0; i < nDataPts - 2; ++i) {
            if (firstUpDw[i + 1] > 0.) {
              if (intervalsAUpDw[i + 1][1] + Math.abs(intervalsAUpDw[i + 1][1]) * ERROR < intervalsBUpDw[i][0] - Math.abs(intervalsBUpDw[i][0]) * ERROR |
                  intervalsAUpDw[i + 1][0] - Math.abs(intervalsAUpDw[i + 1][0]) * ERROR > intervalsBUpDw[i][1] + Math.abs(intervalsBUpDw[i][1]) * ERROR) {
                ++k;
                firstUpDw[i + 1] = firstDerivativesRecalculator(intervals, slopesUpDw, aValuesUpDw, bValuesUpDw, i + 1);
              }
            }
          }
          if (k == 0) {
            modFirstUpDw = true;
          }
          aValuesUpDw = aValuesCalculator(slopesUpDw, firstUpDw);
          bValuesUpDw = bValuesCalculator(slopesUpDw, firstUpDw);
          intervalsAUpDw = getIntervalsA(intervals, slopesUpDw, firstUpDw, bValuesUpDw);
          intervalsBUpDw = getIntervalsB(intervals, slopesUpDw, firstUpDw, aValuesUpDw);
        }
        final double[] secondUpDw = secondDerivativeCalculator(initialSecondUpDw, intervalsAUpDw, intervalsBUpDw);
        firstSecondUpDw[ii] = new DoubleMatrix1D(firstUpDw);
        firstSecondUpDw[2 + ii] = new DoubleMatrix1D(secondUpDw);
      }
      for (int j = 0; j < nDataPts; ++j) {
        tmpFirst[j][l - nExtra] = 0.5 * (firstSecondUpDw[0].getData()[j] - firstSecondUpDw[1].getData()[j]) / den;
        tmpSecond[j][l - nExtra] = 0.5 * (firstSecondUpDw[2].getData()[j] - firstSecondUpDw[3].getData()[j]) / den;
      }
      yValuesUp[l] = yValues[l];
      yValuesDw[l] = yValues[l];
    }
    for (int i = 0; i < nDataPts; ++i) {
      firstWithSensitivity[i + 1] = new DoubleMatrix1D(tmpFirst[i]);
      secondWithSensitivity[i + 1] = new DoubleMatrix1D(tmpSecond[i]);
    }

    final DoubleMatrix2D[] resMatrix = _solver.solveWithSensitivity(yValuesSrt, intervals, slopes, slopesSensitivity, firstWithSensitivity, secondWithSensitivity);

    for (int l = 0; l < nDataPts; ++l) {
      DoubleMatrix2D m = resMatrix[l];
      final int rows = m.getNumberOfRows();
      final int cols = m.getNumberOfColumns();
      for (int i = 0; i < rows; ++i) {
        for (int j = 0; j < cols; ++j) {
          ArgumentChecker.isTrue(Doubles.isFinite(m.getEntry(i, j)), "Matrix contains a NaN or infinite");
        }
      }
    }

    final DoubleMatrix2D coefMatrix = resMatrix[0];
    final DoubleMatrix2D[] coefSenseMatrix = new DoubleMatrix2D[nDataPts - 1];
    System.arraycopy(resMatrix, 1, coefSenseMatrix, 0, nDataPts - 1);
    final int nCoefs = coefMatrix.getNumberOfColumns();

    return new PiecewisePolynomialResultsWithSensitivity(new DoubleMatrix1D(xValues), coefMatrix, nCoefs, 1, coefSenseMatrix);
  }
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    SimpleParameterSensitivity ps = new SimpleParameterSensitivity();

    final Map<String, List<DoublesPair>> sensitivityPriceCurve = sensitivity.getPriceCurveSensitivities();
    for (final Map.Entry<String, List<DoublesPair>> entry : sensitivityPriceCurve.entrySet()) {
      if (curvesSet.contains(entry.getKey())) {
        ps = ps.plus(entry.getKey(), new DoubleMatrix1D(inflation.parameterInflationSensitivity(entry.getKey(), entry.getValue())));
      }
    }

    // YieldAndDiscount
    final Map<String, List<DoublesPair>> sensitivityDsc = sensitivity.getYieldDiscountingSensitivities();
    for (final Map.Entry<String, List<DoublesPair>> entry : sensitivityDsc.entrySet()) {
      if (curvesSet.contains(entry.getKey())) {
        ps = ps.plus(entry.getKey(), new DoubleMatrix1D(inflation.getMulticurveProvider().parameterSensitivity(entry.getKey(), entry.getValue())));
      }
    }
    // Forward
    final Map<String, List<ForwardSensitivity>> sensitivityFwd = sensitivity.getForwardSensitivities();
    for (final Map.Entry<String, List<ForwardSensitivity>> entry : sensitivityFwd.entrySet()) {
      if (curvesSet.contains(entry.getKey())) {
        ps = ps.plus(entry.getKey(), new DoubleMatrix1D(inflation.getMulticurveProvider().parameterForwardSensitivity(entry.getKey(), entry.getValue())));
      }
    }

    // By curve name in the curves set (to have the right order)
    double[] result = new double[0];
    for (final String name : curvesSet) {
      final DoubleMatrix1D sensi = ps.getSensitivity(name);
      if (sensi != null) {
        result = ArrayUtils.addAll(result, sensi.getData());
      } else {
        result = ArrayUtils.addAll(result, new double[inflation.getNumberOfParameters(name)]);
      }
    }
    return new DoubleMatrix1D(result);
  }
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            g2curves.getG2ppParameters(), g2curves.getG2ppCurrency());
        final double valueBumpedMinus = instrument.accept(_valueCalculator, marketDscBumpedMinus);
        sensitivity[loopnode] = (valueBumpedPlus - valueBumpedMinus) / (2 * _shift);
      }
      final String name = g2curves.getMulticurveProvider().getName(ccy);
      result = result.plus(name, new DoubleMatrix1D(sensitivity));
    }
    // Forward ON
    final Set<IndexON> indexON = g2curves.getMulticurveProvider().getIndexesON();
    for (final IndexON index : indexON) {
      final YieldAndDiscountCurve curve = g2curves.getMulticurveProvider().getCurve(index);
      ArgumentChecker.isTrue(curve instanceof YieldCurve, "Curve should be a YieldCurve");
      final YieldCurve curveYield = (YieldCurve) curve;
      ArgumentChecker.isTrue(curveYield.getCurve() instanceof InterpolatedDoublesCurve, "Yield curve should be based on InterpolatedDoublesCurve");
      final InterpolatedDoublesCurve curveInt = (InterpolatedDoublesCurve) curveYield.getCurve();
      final int nbNodePoint = curveInt.getXDataAsPrimitive().length;
      final double[] sensitivity = new double[nbNodePoint];
      for (int loopnode = 0; loopnode < nbNodePoint; loopnode++) {
        final double[] yieldBumpedPlus = curveInt.getYDataAsPrimitive().clone();
        yieldBumpedPlus[loopnode] += _shift;
        final YieldAndDiscountCurve dscBumpedPlus = new YieldCurve(curveInt.getName(), new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumpedPlus, curveInt.getInterpolator(), true));
        final G2ppProviderDiscount marketFwdBumpedPlus = new G2ppProviderDiscount(g2curves.getMulticurveProvider().withForward(index, dscBumpedPlus),
            g2curves.getG2ppParameters(), g2curves.getG2ppCurrency());
        final double valueBumpedPlus = instrument.accept(_valueCalculator, marketFwdBumpedPlus);
        final double[] yieldBumpedMinus = curveInt.getYDataAsPrimitive().clone();
        yieldBumpedMinus[loopnode] -= _shift;
        final YieldAndDiscountCurve dscBumpedMinus = new YieldCurve(curveInt.getName(),
            new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumpedMinus, curveInt.getInterpolator(), true));
        final G2ppProviderDiscount marketFwdBumpedMinus = new G2ppProviderDiscount(g2curves.getMulticurveProvider().withForward(index, dscBumpedMinus),
            g2curves.getG2ppParameters(), g2curves.getG2ppCurrency());
        final double valueBumpedMinus = instrument.accept(_valueCalculator, marketFwdBumpedMinus);
        sensitivity[loopnode] = (valueBumpedPlus - valueBumpedMinus) / (2 * _shift);
      }
      final String name = g2curves.getMulticurveProvider().getName(index);
      result = result.plus(name, new DoubleMatrix1D(sensitivity));
    }
    // Forward Ibor - symmetrical
    final Set<IborIndex> indexForward = g2curves.getMulticurveProvider().getIndexesIbor();
    for (final IborIndex index : indexForward) {
      final YieldAndDiscountCurve curve = g2curves.getMulticurveProvider().getCurve(index);
      ArgumentChecker.isTrue(curve instanceof YieldCurve, "Curve should be a YieldCurve");
      final YieldCurve curveYield = (YieldCurve) curve;
      ArgumentChecker.isTrue(curveYield.getCurve() instanceof InterpolatedDoublesCurve, "Yield curve should be based on InterpolatedDoublesCurve");
      final InterpolatedDoublesCurve curveInt = (InterpolatedDoublesCurve) curveYield.getCurve();
      final int nbNodePoint = curveInt.getXDataAsPrimitive().length;
      final double[] sensitivity = new double[nbNodePoint];
      for (int loopnode = 0; loopnode < nbNodePoint; loopnode++) {
        final double[] yieldBumpedPlus = curveInt.getYDataAsPrimitive().clone();
        yieldBumpedPlus[loopnode] += _shift;
        final YieldAndDiscountCurve dscBumpedPlus = new YieldCurve(curveInt.getName(), new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumpedPlus, curveInt.getInterpolator(), true));
        final G2ppProviderDiscount marketFwdBumpedPlus = new G2ppProviderDiscount(g2curves.getMulticurveProvider().withForward(index, dscBumpedPlus),
            g2curves.getG2ppParameters(), g2curves.getG2ppCurrency());
        final double valueBumpedPlus = instrument.accept(_valueCalculator, marketFwdBumpedPlus);
        final double[] yieldBumpedMinus = curveInt.getYDataAsPrimitive().clone();
        yieldBumpedMinus[loopnode] -= _shift;
        final YieldAndDiscountCurve dscBumpedMinus = new YieldCurve(curveInt.getName(),
            new InterpolatedDoublesCurve(curveInt.getXDataAsPrimitive(), yieldBumpedMinus, curveInt.getInterpolator(), true));
        final G2ppProviderDiscount marketFwdBumpedMinus = new G2ppProviderDiscount(g2curves.getMulticurveProvider().withForward(index, dscBumpedMinus),
            g2curves.getG2ppParameters(), g2curves.getG2ppCurrency());
        final double valueBumpedMinus = instrument.accept(_valueCalculator, marketFwdBumpedMinus);
        sensitivity[loopnode] = (valueBumpedPlus - valueBumpedMinus) / (2 * _shift);
      }
      final String name = g2curves.getMulticurveProvider().getName(index);
      result = result.plus(name, new DoubleMatrix1D(sensitivity));
    }
    return result;
  }
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