Trait opencv::core::MinProblemSolver

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pub trait MinProblemSolver: AlgorithmTrait + MinProblemSolverConst {
    // Required method
    fn as_raw_mut_MinProblemSolver(&mut self) -> *mut c_void;

    // Provided methods
    fn set_function(
        &mut self,
        f: &Ptr<dyn MinProblemSolver_Function>
    ) -> Result<()> { ... }
    fn set_term_criteria(&mut self, termcrit: TermCriteria) -> Result<()> { ... }
    fn minimize(&mut self, x: &mut dyn ToInputOutputArray) -> Result<f64> { ... }
}
Expand description

Basic interface for all solvers

Required Methods§

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fn as_raw_mut_MinProblemSolver(&mut self) -> *mut c_void

Provided Methods§

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fn set_function(&mut self, f: &Ptr<dyn MinProblemSolver_Function>) -> Result<()>

Setter for the optimized function.

It should be called at least once before the call to minimize(), as default value is not usable.

Parameters
  • f: The new function to optimize.
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fn set_term_criteria(&mut self, termcrit: TermCriteria) -> Result<()>

Set terminal criteria for solver.

This method is not necessary to be called before the first call to minimize(), as the default value is sensible.

Algorithm stops when the number of function evaluations done exceeds termcrit.maxCount, when the function values at the vertices of simplex are within termcrit.epsilon range or simplex becomes so small that it can enclosed in a box with termcrit.epsilon sides, whatever comes first.

Parameters
  • termcrit: Terminal criteria to be used, represented as cv::TermCriteria structure.
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fn minimize(&mut self, x: &mut dyn ToInputOutputArray) -> Result<f64>

actually runs the algorithm and performs the minimization.

The sole input parameter determines the centroid of the starting simplex (roughly, it tells where to start), all the others (terminal criteria, initial step, function to be minimized) are supposed to be set via the setters before the call to this method or the default values (not always sensible) will be used.

Parameters
  • x: The initial point, that will become a centroid of an initial simplex. After the algorithm will terminate, it will be set to the point where the algorithm stops, the point of possible minimum.
Returns

The value of a function at the point found.

Implementors§