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source-git / ceres-solver

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Packit	ea1746	`<title>General Unconstrained Minimization — Ceres Solver</title>`
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Packit	ea1746	`<link rel="top" title="Ceres Solver" href="index.html"/>`
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Packit	ea1746	`<link rel="next" title="On Derivatives" href="derivatives.html"/>`
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Packit	ea1746	`Ceres Solver`
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Packit	ea1746	`1.13`
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Packit	ea1746	`Why?`
Packit	ea1746	`Installation`
Packit	ea1746	`Tutorial`
Packit	ea1746	`Non-linear Least Squares`
Packit	ea1746	`General Unconstrained Minimization`
Packit	ea1746	`Rosenbrock’s Function`
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Packit	ea1746	`On Derivatives`
Packit	ea1746	`Modeling Non-linear Least Squares`
Packit	ea1746	`Solving Non-linear Least Squares`
Packit	ea1746	`Covariance Estimation`
Packit	ea1746	`General Unconstrained Minimization`
Packit	ea1746	`FAQS, Tips & Tricks`
Packit	ea1746	`Users`
Packit	ea1746	`Contributing`
Packit	ea1746	`Version History`
Packit	ea1746	`Bibliography`
Packit	ea1746	`License`
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Packit	ea1746	`Ceres Solver`
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Packit	ea1746	`Docs »`
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Packit	ea1746	`Tutorial »`
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Packit	ea1746	`General Unconstrained Minimization`
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Packit	ea1746	`General Unconstrained Minimization¶`
Packit	ea1746	`While much of Ceres Solver is devoted to solving non-linear least`
Packit	ea1746	`squares problems, internally it contains a solver that can solve`
Packit	ea1746	`general unconstrained optimization problems using just their objective`
Packit	ea1746	`function value and gradients. The GradientProblem and`
Packit	ea1746	`GradientProblemSolver objects give the user access to this solver.`
Packit	ea1746	`So without much further ado, let us look at how one goes about using`
Packit	ea1746	`them.`
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Packit	ea1746	`Rosenbrock’s Function¶`
Packit	ea1746	`We consider the minimization of the famous Rosenbrock’s function [1].`
Packit	ea1746	`We begin by defining an instance of the FirstOrderFunction`
Packit	ea1746	`interface. This is the object that is responsible for computing the`
Packit	ea1746	`objective function value and the gradient (if required). This is the`
Packit	ea1746	`analog of the CostFunction when defining non-linear least`
Packit	ea1746	`squares problems in Ceres.`
Packit	ea1746	`class Rosenbrock : public ceres::FirstOrderFunction {`
Packit	ea1746	`public:`
Packit	ea1746	`virtual bool Evaluate(const double* parameters,`
Packit	ea1746	`double* cost,`
Packit	ea1746	`double* gradient) const {`
Packit	ea1746	`const double x = parameters[0];`
Packit	ea1746	`const double y = parameters[1];`
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Packit	ea1746	`cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x);`
Packit	ea1746	`if (gradient != NULL) {`
Packit	ea1746	`gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x;`
Packit	ea1746	`gradient[1] = 200.0 * (y - x * x);`
Packit	ea1746	`}`
Packit	ea1746	`return true;`
Packit	ea1746	`}`
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Packit	ea1746	`virtual int NumParameters() const { return 2; }`
Packit	ea1746	`};`

source-git / ceres-solver

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Blame docs/html/gradient_tutorial.html

General Unconstrained Minimization¶

Rosenbrock’s Function¶