Package com.opengamma.analytics.math.matrix

Examples of com.opengamma.analytics.math.matrix.DoubleMatrix2D

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      pvcsCalCal[loopcal] = pvcsCalCal[loopcal].cleaned();
      pvcsCalDiff[loopcal] = pvcsCalBase[loopcal].plus(pvcsCalCal[loopcal].multipliedBy(-1));
      pvcsCalDiff[loopcal] = pvcsCalDiff[loopcal].cleaned();
    }
    final CommonsMatrixAlgebra matrix = new CommonsMatrixAlgebra();
    final DoubleMatrix2D dPvCaldLambdaMatrix = new DoubleMatrix2D(dPvCaldLambda);
    final DoubleMatrix2D dPvCaldLambdaMatrixInverse = matrix.getInverse(dPvCaldLambdaMatrix);
    // Curve sensitivity
    final InterestRateCurveSensitivity[] dLambdadC = new InterestRateCurveSensitivity[nbCal];
    for (int loopcal1 = 0; loopcal1 < nbCal; loopcal1++) {
      dLambdadC[loopcal1] = new InterestRateCurveSensitivity();
      for (int loopcal2 = 0; loopcal2 <= loopcal1; loopcal2++) {
        dLambdadC[loopcal1] = dLambdadC[loopcal1].plus(pvcsCalDiff[loopcal2].multipliedBy(dPvCaldLambdaMatrixInverse.getEntry(loopcal1, loopcal2)));
      }
    }
    InterestRateCurveSensitivity pvcsAdjust = new InterestRateCurveSensitivity();
    for (int loopcal = 0; loopcal < nbCal; loopcal++) {
      pvcsAdjust = pvcsAdjust.plus(dLambdadC[loopcal].multipliedBy(dPvAmdLambda[loopcal]));
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      pvcsCalCal[loopcal] = pvcsCalCal[loopcal].cleaned();
      pvcsCalDiff[loopcal] = pvcsCalBase[loopcal].plus(pvcsCalCal[loopcal].multipliedBy(-1));
      pvcsCalDiff[loopcal] = pvcsCalDiff[loopcal].cleaned();
    }
    final CommonsMatrixAlgebra matrix = new CommonsMatrixAlgebra();
    final DoubleMatrix2D dPvCaldLambdaMatrix = new DoubleMatrix2D(dPvCaldLambda);
    final DoubleMatrix2D dPvCaldLambdaMatrixInverse = matrix.getInverse(dPvCaldLambdaMatrix);
    // SABR sensitivity
    final double[][] dPvCaldAlpha = new double[nbCal][nbCal];
    final double[][] dPvCaldRho = new double[nbCal][nbCal];
    final double[][] dPvCaldNu = new double[nbCal][nbCal];
    for (int loopcal = 0; loopcal < nbCal; loopcal++) {
      dPvCaldSABR[loopcal] = METHOD_SWAPTION_SABR.presentValueSABRSensitivity(swaptionCalibration[loopcal], curves);
      final Set<DoublesPair> keySet = dPvCaldSABR[loopcal].getAlpha().getMap().keySet();
      final DoublesPair[] keys = keySet.toArray(new DoublesPair[keySet.size()]);
      dPvCaldAlpha[loopcal][loopcal] = dPvCaldSABR[loopcal].getAlpha().getMap().get(keys[0]);
      dPvCaldRho[loopcal][loopcal] = dPvCaldSABR[loopcal].getRho().getMap().get(keys[0]);
      dPvCaldNu[loopcal][loopcal] = dPvCaldSABR[loopcal].getNu().getMap().get(keys[0]);
    }
    final DoubleMatrix1D dPvAmdLambdaMatrix = new DoubleMatrix1D(dPvAmdLambda);
    final DoubleMatrix2D dPvCaldAlphaMatrix = new DoubleMatrix2D(dPvCaldAlpha);
    final DoubleMatrix2D dLambdadAlphaMatrix = (DoubleMatrix2D) matrix.multiply(dPvCaldLambdaMatrixInverse, dPvCaldAlphaMatrix);
    final DoubleMatrix2D dPvAmdAlphaMatrix = (DoubleMatrix2D) matrix.multiply(matrix.getTranspose(dLambdadAlphaMatrix), dPvAmdLambdaMatrix);
    final DoubleMatrix2D dPvCaldRhoMatrix = new DoubleMatrix2D(dPvCaldRho);
    final DoubleMatrix2D dLambdadRhoMatrix = (DoubleMatrix2D) matrix.multiply(dPvCaldLambdaMatrixInverse, dPvCaldRhoMatrix);
    final DoubleMatrix2D dPvAmdRhoMatrix = (DoubleMatrix2D) matrix.multiply(matrix.getTranspose(dLambdadRhoMatrix), dPvAmdLambdaMatrix);
    final DoubleMatrix2D dPvCaldNuMatrix = new DoubleMatrix2D(dPvCaldNu);
    final DoubleMatrix2D dLambdadNuMatrix = (DoubleMatrix2D) matrix.multiply(dPvCaldLambdaMatrixInverse, dPvCaldNuMatrix);
    final DoubleMatrix2D dPvAmdNuMatrix = (DoubleMatrix2D) matrix.multiply(matrix.getTranspose(dLambdadNuMatrix), dPvAmdLambdaMatrix);
    final double[] dPvAmdAlpha = matrix.getTranspose(dPvAmdAlphaMatrix).getData()[0];
    final double[] dPvAmdRho = matrix.getTranspose(dPvAmdRhoMatrix).getData()[0];
    final double[] dPvAmdNu = matrix.getTranspose(dPvAmdNuMatrix).getData()[0];
    // Storage in PresentValueSABRSensitivityDataBundle
    final PresentValueSABRSensitivityDataBundle pvss = new PresentValueSABRSensitivityDataBundle();
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   * @param x A Commons matrix, not null
   * @return An OG 2-D matrix of doubles
   */
  public static DoubleMatrix2D unwrap(final RealMatrix x) {
    Validate.notNull(x);
    return new DoubleMatrix2D(x.getData());
  }
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   * @param x A Colt 2D matrix of doubles, not null
   * @return An OG 2D matrix
   */
  public static DoubleMatrix2D wrap(final cern.colt.matrix.DoubleMatrix2D x) {
    Validate.notNull(x, "x");
    return new DoubleMatrix2D(x.toArray());
  }
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    final double[] scale = new double[nCaps];
    for (int i = 0; i < nCaps; i++) {
      scale[i] = 1.0 / (Math.max(minPrice, capPrices[i]));
    }
    final DoubleMatrix2D mScale = DoubleMatrixUtils.getTwoDimensionalDiagonalMatrix(scale);

    final Function1D<DoubleMatrix1D, DoubleMatrix1D> weightedPriceFunc = new Function1D<DoubleMatrix1D, DoubleMatrix1D>() {

      @SuppressWarnings("synthetic-access")
      @Override
      public DoubleMatrix1D evaluate(final DoubleMatrix1D x) {

        final VolatilityTermStructure vol = _volModel.evaluate(x);
        final double[] modelPrices = pricer.price(vol);

        final double[] res = new double[nCaps];
        for (int i = 0; i < nCaps; i++) {
          res[i] = (modelPrices[i] - capPrices[i]) * scale[i];
        }
        return new DoubleMatrix1D(res);
      }
    };

    final Function1D<DoubleMatrix1D, DoubleMatrix2D> priceJac = new Function1D<DoubleMatrix1D, DoubleMatrix2D>() {

      @SuppressWarnings("synthetic-access")
      @Override
      public DoubleMatrix2D evaluate(final DoubleMatrix1D x) {

        final Interpolator1DDataBundle db = _interpolator.getDataBundle(_knots, x.getData());

        final double[] capletVols = new double[nCaplets];
        final double[][] sense = new double[nCaplets][];
        for (int i = 0; i < nCaplets; i++) {
          capletVols[i] = _interpolator.interpolate(db, capletExp[i]);
          sense[i] = _interpolator.getNodeSensitivitiesForValue(db, capletExp[i]);
        }
        final DoubleMatrix2D curveSensitivity = new DoubleMatrix2D(sense);
        final DoubleMatrix2D vega = pricer.vegaFromCapletVols(capletVols);
        final DoubleMatrix2D jac = (DoubleMatrix2D) MA.multiply(vega, curveSensitivity);
        // must now scale
        return (DoubleMatrix2D) MA.multiply(mScale, jac);
      }
    };

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    final ParametricVaRDataBundle secondOrderData = data.get(2);
    double deltaStd = 0;
    double gammaStd = 0;
    if (firstOrderData != null) {
      final DoubleMatrix1D delta = (DoubleMatrix1D) firstOrderData.getSensitivities();
      final DoubleMatrix2D deltaCovariance = firstOrderData.getCovarianceMatrix();
      deltaStd = _algebra.getInnerProduct(delta, _algebra.multiply(deltaCovariance, delta));
    }
    if (secondOrderData != null) {
      final Matrix<?> gamma = secondOrderData.getSensitivities();
      final DoubleMatrix2D gammaCovariance = secondOrderData.getCovarianceMatrix();
      gammaStd = 0.5 * _algebra.getTrace(_algebra.getPower(_algebra.multiply(gamma, gammaCovariance), 2));
    }
    return Math.sqrt(deltaStd + gammaStd);
  }
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        ArgumentChecker.isFalse(Double.isInfinite(res[i][j]), "Too large input");
        ArgumentChecker.isFalse(Double.isNaN(res[i][j]), "Too large input");
      }
    }

    return new DoubleMatrix2D(res);

  }
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    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);
  }
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              paramOffset += nSense;
            }
          }
          optionOffset += l;
        }
        return new DoubleMatrix2D(res);
      }
    };
  }
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      }
      final double bound = Math.max(Math.abs(ref) + Math.abs(yValuesSrt[i + 1]), 1.e-1);
      ArgumentChecker.isTrue(Math.abs(ref - yValuesSrt[i + 1]) < ERROR * bound, "Input is too large/small or data points are too close");
    }

    return new PiecewisePolynomialResult(new DoubleMatrix1D(xValuesSrt), new DoubleMatrix2D(coefs), 4, 1);
  }
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