Examples of com.opengamma.analytics.math.differentiation.VectorFieldFirstOrderDifferentiator

Package com.opengamma.analytics.math.differentiation

Examples of com.opengamma.analytics.math.differentiation.VectorFieldFirstOrderDifferentiator

com.opengamma.analytics.math.differentiation.VectorFieldFirstOrderDifferentiator
Differentiates a vector field (i.e. there is a vector value for every point in some vector space) with respect to the vector space using finite difference.
For a function $\mathbf{y} = f(\mathbf{x})$ where $\mathbf{x}$ is a n-dimensional vector and $\mathbf{y}$ is a m-dimensional vector, this class produces the Jacobian function $\mathbf{J}(\mathbf{x})$, i.e. a function that returns the Jacobian for each point $\mathbf{x}$, where $\mathbf{J}$ is the $m \times n$ matrix $\frac{dy_i}{dx_j}$

   * @param penalty Penalty matrix 
   * @return value of the fitted parameters
   */
  public LeastSquareResults solve(final DoubleMatrix1D observedValues, final Function1D<DoubleMatrix1D, DoubleMatrix1D> func, final DoubleMatrix1D startPos, final DoubleMatrix2D penalty) {
    final int n = observedValues.getNumberOfElements();
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return solve(observedValues, new DoubleMatrix1D(n, 1.0), func, jac.differentiate(func), startPos, penalty);
  }

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    * @param penalty Penalty matrix 
   * @return value of the fitted parameters
   */
  public LeastSquareResults solve(final DoubleMatrix1D observedValues, final DoubleMatrix1D sigma, final Function1D<DoubleMatrix1D, DoubleMatrix1D> func, final DoubleMatrix1D startPos,
      final DoubleMatrix2D penalty) {
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return solve(observedValues, sigma, func, jac.differentiate(func), startPos, penalty);
  }

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  * without resorting to a non-linear parameter transform. In some circumstances this approach will lead to slow convergence.
   * @return value of the fitted parameters
   */
  public LeastSquareResults solve(final DoubleMatrix1D observedValues, final DoubleMatrix1D sigma, final Function1D<DoubleMatrix1D, DoubleMatrix1D> func, final DoubleMatrix1D startPos,
      final DoubleMatrix2D penalty, final Function1D<DoubleMatrix1D, Boolean> allowedValue) {
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return solve(observedValues, sigma, func, jac.differentiate(func), startPos, penalty, allowedValue);
  }

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   * @param startPos  Initial value of the parameters
   * @return value of the fitted parameters
   */
  public LeastSquareResults solve(final DoubleMatrix1D observedValues, final Function1D<DoubleMatrix1D, DoubleMatrix1D> func, final DoubleMatrix1D startPos) {
    final int n = observedValues.getNumberOfElements();
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return solve(observedValues, new DoubleMatrix1D(n, 1.0), func, jac.differentiate(func), startPos, null);
  }

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   * @param startPos  Initial value of the parameters
   * @return value of the fitted parameters
   */
  public LeastSquareResults solve(final DoubleMatrix1D observedValues, final DoubleMatrix1D sigma, final Function1D<DoubleMatrix1D, DoubleMatrix1D> func,
      final DoubleMatrix1D startPos) {
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return solve(observedValues, sigma, func, jac.differentiate(func), startPos, null);
  }

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   * on the step size is applied.
   * @return value of the fitted parameters
   */
  public LeastSquareResults solve(final DoubleMatrix1D observedValues, final DoubleMatrix1D sigma, final Function1D<DoubleMatrix1D, DoubleMatrix1D> func,
      final DoubleMatrix1D startPos, final DoubleMatrix1D maxJumps) {
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return solve(observedValues, sigma, func, jac.differentiate(func), startPos, maxJumps);
  }

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    final int n = x.getNumberOfElements();


    final Function1D<DoubleMatrix1D, DoubleMatrix1D> func = _fitter.getModelValueFunction();
    final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacFunc = _fitter.getModelJacobianFunction();


    final VectorFieldFirstOrderDifferentiator differ = new VectorFieldFirstOrderDifferentiator();
    final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacFuncFD = differ.differentiate(func);


    final DoubleMatrix2D jac = jacFunc.evaluate(x);
    final DoubleMatrix2D jacFD = jacFuncFD.evaluate(x);
    final int rows = jacFD.getNumberOfRows();
    final int cols = jacFD.getNumberOfColumns();

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  }


  @Test
  public void testJacobian() {


    final VectorFieldFirstOrderDifferentiator jacFDCal = new VectorFieldFirstOrderDifferentiator();
    final Function1D<DoubleMatrix1D, DoubleMatrix1D> func = new CapletStrippingFunction(CAPS, YIELD_CURVES, VOL_MODEL_PROVIDER);
    final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacFDFunc = jacFDCal.differentiate(func);
    final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacAnalFunc = new CapletStrippingJacobian(CAPS, YIELD_CURVES, CURVE_NODES, INTERPOLATORS, TRANSFORMS, null);


    final DoubleMatrix2D jacFD = jacFDFunc.evaluate(END);
    final DoubleMatrix2D jacAnal = jacAnalFunc.evaluate(END);
    final int rows = jacFD.getNumberOfRows();

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    UncoupledParameterTransforms transforms = new UncoupledParameterTransforms(start, TRANSFORMS, fixed);
    NonLinearTransformFunction transFunc = new NonLinearTransformFunction(FUNCTION, JACOBIAN, transforms);
    Function1D<DoubleMatrix1D, DoubleMatrix1D> func = transFunc.getFittingFunction();
    Function1D<DoubleMatrix1D, DoubleMatrix2D> jacFunc = transFunc.getFittingJacobian();


    VectorFieldFirstOrderDifferentiator diff = new VectorFieldFirstOrderDifferentiator();
    Function1D<DoubleMatrix1D, DoubleMatrix2D> jacFuncFD = diff.differentiate(func);


    DoubleMatrix1D testPoint = new DoubleMatrix1D(new double[] {4.5, -2.1 });
    DoubleMatrix2D jac = jacFunc.evaluate(testPoint);
    DoubleMatrix2D jacFD = jacFuncFD.evaluate(testPoint);
    assertEquals(3, jac.getNumberOfRows());

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    _updateFunction = updateFunction;
  }


  @Override
  public DoubleMatrix1D getRoot(final Function1D<DoubleMatrix1D, DoubleMatrix1D> function, final DoubleMatrix1D startPosition) {
    final VectorFieldFirstOrderDifferentiator jac = new VectorFieldFirstOrderDifferentiator();
    return getRoot(function, jac.differentiate(function), startPosition);
  }

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