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LevenbergMarquardt< _FunctorType > Class Template Reference
[Non linear optimization module]

Performs non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm. More...

Inherits internal::no_assignment_operator.

List of all members.

Public Member Functions

FVectorType & diag ()
RealScalar fnorm ()
FVectorType & fvec ()
RealScalar gnorm ()
ComputationInfo info () const
 Reports whether the minimization was successful.
Index iterations ()
JacobianType & jacobian ()
RealScalar lm_param (void)
JacobianType & matrixR ()
Index nfev ()
Index njev ()
PermutationType permutation ()
void resetParameters ()
void setEpsilon (RealScalar epsfcn)
void setExternalScaling (bool value)
void setFactor (RealScalar factor)
void setFtol (RealScalar ftol)
void setGtol (RealScalar gtol)
void setMaxfev (Index maxfev)
void setXtol (RealScalar xtol)

Detailed Description

template<typename _FunctorType>
class Eigen::LevenbergMarquardt< _FunctorType >

Performs non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm.

Check wikipedia for more information. http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm


Member Function Documentation

FVectorType& diag (  )  [inline]
Returns:
a reference to the diagonal of the jacobian
RealScalar fnorm (  )  [inline]
Returns:
the norm of current vector function
FVectorType& fvec (  )  [inline]
Returns:
a reference to the current vector function
RealScalar gnorm (  )  [inline]
Returns:
the norm of the gradient of the error
ComputationInfo info (  )  const [inline]

Reports whether the minimization was successful.

Returns:
Success if the minimization was succesful, NumericalIssue if a numerical problem arises during the minimization process, for exemple during the QR factorization NoConvergence if the minimization did not converge after the maximum number of function evaluation allowed InvalidInput if the input matrix is invalid
Index iterations (  )  [inline]
Returns:
the number of iterations performed
JacobianType& jacobian (  )  [inline]
Returns:
a reference to the matrix where the current Jacobian matrix is stored
RealScalar lm_param ( void   )  [inline]
Returns:
the LevenbergMarquardt parameter
JacobianType& matrixR (  )  [inline]
Returns:
a reference to the triangular matrix R from the QR of the jacobian matrix.
See also:
jacobian()
Index nfev (  )  [inline]
Returns:
the number of functions evaluation
Index njev (  )  [inline]
Returns:
the number of jacobian evaluation
PermutationType permutation (  )  [inline]

the permutation used in the QR factorization

void resetParameters (  )  [inline]

Sets the default parameters

void setEpsilon ( RealScalar  epsfcn  )  [inline]

Sets the error precision

void setExternalScaling ( bool  value  )  [inline]

Use an external Scaling. If set to true, pass a nonzero diagonal to diag()

void setFactor ( RealScalar  factor  )  [inline]

Sets the step bound for the diagonal shift

void setFtol ( RealScalar  ftol  )  [inline]

Sets the tolerance for the norm of the vector function

void setGtol ( RealScalar  gtol  )  [inline]

Sets the tolerance for the norm of the gradient of the error vector

void setMaxfev ( Index  maxfev  )  [inline]

Sets the maximum number of function evaluation

void setXtol ( RealScalar  xtol  )  [inline]

Sets the tolerance for the norm of the solution vector


The documentation for this class was generated from the following files: