Package com.opengamma.analytics.math.matrix

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

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    }

    final DoubleMatrix2D dfdThetaMat = new DoubleMatrix2D(dfdTheta);
    final DoubleMatrix2D dfdPhiMat = new DoubleMatrix2D(dfdPhi);
    final DoubleMatrix2D dPhidThetaMat = (DoubleMatrix2D) ALGEBRA.scale(ALGEBRA.multiply(ALGEBRA.getInverse(dfdPhiMat), dfdThetaMat), -1.0);
    final DoubleMatrix1D dPvdPhiMat = new DoubleMatrix1D(dPvdPhi);
    final DoubleMatrix2D dPvdThetaMat = ALGEBRA.getTranspose(ALGEBRA.multiply(ALGEBRA.getTranspose(dPhidThetaMat), dPvdPhiMat));
    final double[] dPvdTheta = dPvdThetaMat.getData()[0];

    // Storage in PresentValueSABRSensitivityDataBundle
    final PresentValueSABRSensitivityDataBundle sensi = new PresentValueSABRSensitivityDataBundle();
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    final DoubleMatrix2D dfdThetaMat = new DoubleMatrix2D(dfdTheta);
    final DoubleMatrix2D dfdPhiMat = new DoubleMatrix2D(dfdPhi);
    final DoubleMatrix2D dfdPhiInvMat = ALGEBRA.getInverse(dfdPhiMat);
    final DoubleMatrix2D dPhidThetaMat = (DoubleMatrix2D) ALGEBRA.scale(ALGEBRA.multiply(dfdPhiInvMat, dfdThetaMat), -1.0);
    final DoubleMatrix1D dPvdPhiMat = new DoubleMatrix1D(dPvdPhi);
    final DoubleMatrix2D dPvdThetaMat = ALGEBRA.getTranspose(ALGEBRA.multiply(ALGEBRA.getTranspose(dPhidThetaMat), dPvdPhiMat));
    final double[] dPvdTheta = dPvdThetaMat.getData()[0];

    // Storage in PresentValueSABRSensitivityDataBundle
    final PresentValueSABRSensitivityDataBundle sensiSABR = new PresentValueSABRSensitivityDataBundle();
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      }
      b[i] = sum;

    }

    final DoubleMatrix1D mb = new DoubleMatrix1D(b);
    DoubleMatrix2D ma = getAMatrix(f, invSigmaSqr);

    if (lambda > 0.0) {
      final DoubleMatrix2D d = getDiffMatrix(m, differenceOrder);
      ma = (DoubleMatrix2D) _algebra.add(ma, _algebra.scale(d, lambda));
    }

    final DecompositionResult decmp = _decomposition.evaluate(ma);
    final DoubleMatrix1D w = decmp.solve(mb);
    final DoubleMatrix2D covar = decmp.solve(DoubleMatrixUtils.getIdentityMatrix2D(m));

    double chiSq = 0;
    for (i = 0; i < n; i++) {
      double temp = 0;
      for (k = 0; k < m; k++) {
        temp += w.getEntry(k) * f[k][i];
      }
      chiSq += FunctionUtils.square(y.get(i) - temp) * invSigmaSqr[i];
    }

    return new GeneralizedLeastSquareResults<>(basisFunctions, chiSq, w, covar);
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      }
      b[i] = sum;

    }

    final DoubleMatrix1D mb = new DoubleMatrix1D(b);
    DoubleMatrix2D ma = getAMatrix(f, invSigmaSqr);

    for (i = 0; i < dim; i++) {
      if (lambda[i] > 0.0) {
        final DoubleMatrix2D d = getDiffMatrix(sizes, differenceOrder[i], i);
        ma = (DoubleMatrix2D) _algebra.add(ma, _algebra.scale(d, lambda[i]));
      }
    }

    final DecompositionResult decmp = _decomposition.evaluate(ma);
    final DoubleMatrix1D w = decmp.solve(mb);
    final DoubleMatrix2D covar = decmp.solve(DoubleMatrixUtils.getIdentityMatrix2D(m));

    double chiSq = 0;
    for (i = 0; i < n; i++) {
      double temp = 0;
      for (k = 0; k < m; k++) {
        temp += w.getEntry(k) * f[k][i];
      }
      chiSq += FunctionUtils.square(y.get(i) - temp) * invSigmaSqr[i];
    }

    return new GeneralizedLeastSquareResults<>(basisFunctions, chiSq, w, covar);
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      getCalibrationObjective().setInstruments(instruments);
      getCalibrationObjective().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, getCalibrationObjective(), 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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    }

    final DoubleMatrix2D dfdThetaMat = new DoubleMatrix2D(dfdTheta);
    final DoubleMatrix2D dfdPhiMat = new DoubleMatrix2D(dfdPhi);
    final DoubleMatrix2D dPhidThetaMat = (DoubleMatrix2D) ALGEBRA.scale(ALGEBRA.multiply(ALGEBRA.getInverse(dfdPhiMat), dfdThetaMat), -1.0);
    final DoubleMatrix1D dPvdPhiMat = new DoubleMatrix1D(dPvdPhi);
    final DoubleMatrix2D dPvdThetaMat = ALGEBRA.getTranspose(ALGEBRA.multiply(ALGEBRA.getTranspose(dPhidThetaMat), dPvdPhiMat));
    final double[] dPvdTheta = dPvdThetaMat.getData()[0];

    // Storage in PresentValueSABRSensitivityDataBundle
    final PresentValueSABRSensitivityDataBundle sensi = new PresentValueSABRSensitivityDataBundle();
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    final DoubleMatrix2D dfdThetaMat = new DoubleMatrix2D(dfdTheta);
    final DoubleMatrix2D dfdPhiMat = new DoubleMatrix2D(dfdPhi);
    final DoubleMatrix2D dfdPhiInvMat = ALGEBRA.getInverse(dfdPhiMat);
    final DoubleMatrix2D dPhidThetaMat = (DoubleMatrix2D) ALGEBRA.scale(ALGEBRA.multiply(dfdPhiInvMat, dfdThetaMat), -1.0);
    final DoubleMatrix1D dPvdPhiMat = new DoubleMatrix1D(dPvdPhi);
    final DoubleMatrix2D dPvdThetaMat = ALGEBRA.getTranspose(ALGEBRA.multiply(ALGEBRA.getTranspose(dPhidThetaMat), dPvdPhiMat));
    final double[] dPvdTheta = dPvdThetaMat.getData()[0];

    // Storage in PresentValueSABRSensitivityDataBundle
    final PresentValueSABRSensitivityDataBundle sensiSABR = new PresentValueSABRSensitivityDataBundle();
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        final YieldAndDiscountCurve curve = bundle.getCurve(curveName);
        final List<Double> oneCurveSensitivity = pointToParameterSensitivity(sensitivity.getSensitivities().get(curveName), curve);
        result.addAll(oneCurveSensitivity);
      }
    }
    return new DoubleMatrix1D(result.toArray(new Double[result.size()]));
  }
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    for (final Currency ccy : sensitivity.getCurrencies()) {
      for (final String curveName : sensitivity.getSensitivity(ccy).getSensitivities().keySet()) {
        if (!fixedCurves.contains(curveName)) {
          final YieldAndDiscountCurve curve = bundle.getCurve(curveName);
          final Double[] oneCurveSensitivity = pointToParameterSensitivity(sensitivity.getSensitivity(ccy).getSensitivities().get(curveName), curve);
          result.put(new ObjectsPair<>(curveName, ccy), new DoubleMatrix1D(oneCurveSensitivity));
        }
      }
    }
    return new MultipleCurrencyParameterSensitivity(result);
  }
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      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);
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