Package com.opengamma.analytics.math.matrix

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

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    }

    final DoubleMatrix2D[] resMatrix = this._solver.solveWithSensitivity(xValues, yValues);
    final int len = resMatrix.length;
    for (int k = 0; k < len; k++) {
      DoubleMatrix2D m = resMatrix[k];
      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[len - 1];
    System.arraycopy(resMatrix, 1, coefSenseMatrix, 0, len - 1);
    final int nCoefs = coefMatrix.getNumberOfColumns();

    return new PiecewisePolynomialResultsWithSensitivity(this._solver.getKnotsMat1D(xValues), coefMatrix, nCoefs, 1, coefSenseMatrix);
  }
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    for (int i = 0; i < n - 1; i++) {
      deltaX[i] = x[i + 1] - x[i];
      oneOverDeltaX[i] = 1.0 / deltaX[i];
      deltaYOverDeltaX[i] = (y[i + 1] - y[i]) * oneOverDeltaX[i];
    }
    final DoubleMatrix2D inverseTriDiag = getInverseTridiagonalMatrix(deltaX);
    final DoubleMatrix1D rhsVector = getRHSVector(deltaYOverDeltaX);
    return ((DoubleMatrix1D) OG_ALGEBRA.multiply(inverseTriDiag, rhsVector)).getData();
  }
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        deltaX[i] = x[i + 1] - x[i];
        oneOverDeltaX[i] = 1.0 / deltaX[i];
        deltaYOverDeltaX[i] = (y[i + 1] - y[i]) * oneOverDeltaX[i];
      }

      final DoubleMatrix2D inverseTriDiag = getInverseTridiagonalMatrix(deltaX);
      final DoubleMatrix2D rhsMatrix = getRHSMatrix(oneOverDeltaX);
      _secondDerivativesSensitivities = ((DoubleMatrix2D) OG_ALGEBRA.multiply(inverseTriDiag, rhsMatrix)).getData();
    }
    return _secondDerivativesSensitivities;
  }
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    if (!_rightNatural) {
      res[n - 1][n - 1] = -oneOverDeltaX[n - 2];
      res[n - 2][n - 2] = oneOverDeltaX[n - 2];
    }
    return new DoubleMatrix2D(res);
  }
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      final InstrumentDerivativeVisitor<MulticurveProviderInterface, MulticurveSensitivity> sensitivityCalculator) {
    final GeneratorMulticurveProviderDiscount generator = new GeneratorMulticurveProviderDiscount(knownData, discountingMap, forwardIborMap, forwardONMap, generatorsMap);
    final MulticurveDiscountBuildingData data = new MulticurveDiscountBuildingData(instruments, generator);
    final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new MulticurveDiscountFinderJacobian(new ParameterSensitivityMulticurveUnderlyingMatrixCalculator(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;
  }
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              for (i = 0; i < m; i++) {
                res[i][j] = (up.getEntry(i) - y.getEntry(i)) / _eps;
              }
              xData[j] = oldValue;
            }
            return new DoubleMatrix2D(res);
          }
        };
      case CENTRAL:
        return new Function1D<DoubleMatrix1D, DoubleMatrix2D>() {

          @SuppressWarnings("synthetic-access")
          @Override
          public DoubleMatrix2D evaluate(final DoubleMatrix1D x) {
            Validate.notNull(x, "x");
            final DoubleMatrix1D y = function.evaluate(x); // need this unused evaluation to get size of y
            final int n = x.getNumberOfElements();
            final int m = y.getNumberOfElements();
            final double[] xData = x.getData();
            double oldValue;
            final double[][] res = new double[m][n];
            int i, j;
            DoubleMatrix1D up, down;
            for (j = 0; j < n; j++) {
              oldValue = xData[j];
              xData[j] += _eps;
              up = function.evaluate(x);
              xData[j] -= _twoEps;
              down = function.evaluate(x);
              for (i = 0; i < m; i++) {
                res[i][j] = (up.getEntry(i) - down.getEntry(i)) / _twoEps;
              }
              xData[j] = oldValue;
            }
            return new DoubleMatrix2D(res);
          }
        };
      case BACKWARD:
        return new Function1D<DoubleMatrix1D, DoubleMatrix2D>() {

          @SuppressWarnings("synthetic-access")
          @Override
          public DoubleMatrix2D evaluate(final DoubleMatrix1D x) {
            Validate.notNull(x, "x");
            final DoubleMatrix1D y = function.evaluate(x);
            final int n = x.getNumberOfElements();
            final int m = y.getNumberOfElements();
            final double[] xData = x.getData();
            double oldValue;
            final double[][] res = new double[m][n];
            int i, j;
            DoubleMatrix1D down;
            for (j = 0; j < n; j++) {
              oldValue = xData[j];
              xData[j] -= _eps;
              down = function.evaluate(x);
              for (i = 0; i < m; i++) {
                res[i][j] = (y.getEntry(i) - down.getEntry(i)) / _eps;
              }
              xData[j] = oldValue;
            }
            return new DoubleMatrix2D(res);
          }
        };
      default:
        throw new IllegalArgumentException("Can only handle forward, backward and central differencing");
    }
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            }
            res[i][j] = sum / _twoEps;
          }
          xData[j] = oldValue;
        }
        return new DoubleMatrix2D(res);
      }
    };

  }
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    _jac = new Function1D<DoubleMatrix1D, DoubleMatrix2D>() {
      @SuppressWarnings("synthetic-access")
      @Override
      public DoubleMatrix2D evaluate(final DoubleMatrix1D yStar) {
        final DoubleMatrix1D y = _transform.inverseTransform(yStar);
        final DoubleMatrix2D h = jac.evaluate(y);
        final DoubleMatrix2D invJ = _transform.inverseJacobian(yStar);
        return (DoubleMatrix2D) MA.multiply(h, invJ);
      }
    };

  }
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    ArgumentChecker.isTrue(gamma[0].getNumberOfColumns() == m, "tenor wrong size. Seond index is {}, should be {}", gamma[0].getNumberOfColumns(), m);
    DoubleMatrix2D[] res = new DoubleMatrix2D[n];
    for (int i = 0; i < n; i++) {
      double[][] temp = new double[m][m];
      for (int j = 0; j < m; j++) {
        DoubleMatrix2D gammaJ = gamma[j];
        for (int k = j; k < m; k++) {
          temp[j][k] = gammaJ.getEntry(i, k);
        }
      }
      for (int j = 0; j < m; j++) {
        for (int k = 0; k < j; k++) {
          temp[j][k] = temp[k][j];
        }
      }
      res[i] = new DoubleMatrix2D(temp);
    }
    return res;
  }
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          for (j = 0; j < n; j++) {
            for (k = 0; k < j; k++) {
              res[i][j][k] = res[i][k][j];
            }
          }
          mres[i] = new DoubleMatrix2D(res[i]);
        }
        return mres;
      }
    };
  }
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