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
Inherits no_assignment_operator.
- Returns
- a reference to the diagonal of the jacobian
- Returns
- the norm of current vector function
- Returns
- a reference to the current vector function
- Returns
- the norm of the gradient of the error
ComputationInfo info |
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const |
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inline |
- Returns
- the number of iterations performed
JacobianType& jacobian |
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inline |
- Returns
- a reference to the matrix where the current Jacobian matrix is stored
RealScalar lm_param |
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void |
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inline |
JacobianType& matrixR |
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inline |
- Returns
- a reference to the triangular matrix R from the QR of the jacobian matrix.
- See also
- jacobian()
- Returns
- the number of functions evaluation
- Returns
- the number of jacobian evaluation
PermutationType permutation |
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inline |
the permutation used in the QR factorization
Sets the default parameters
void setEpsilon |
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RealScalar |
epsfcn | ) |
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inline |
void setExternalScaling |
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bool |
value | ) |
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inline |
Use an external Scaling. If set to true, pass a nonzero diagonal to diag()
void setFactor |
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RealScalar |
factor | ) |
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inline |
Sets the step bound for the diagonal shift
void setFtol |
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RealScalar |
ftol | ) |
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inline |
void setGtol |
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RealScalar |
gtol | ) |
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inline |
Sets the tolerance for the norm of the gradient of the error vector
void setMaxfev |
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Index |
maxfev | ) |
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inline |
void setXtol |
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RealScalar |
xtol | ) |
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inline |
The documentation for this class was generated from the following files: