# `optimize`¶

### Optimization¶

#### Local Optimization¶

 `minimize` `minimize_scalar` `OptimizeResult` `OptimizeWarning`

The minimize function supports the following methods:

The minimize_scalar function supports the following methods:

The specific optimization method interfaces below in this subsection are not recommended for use in new scripts; all of these methods are accessible via a newer, more consistent interface provided by the functions above.

General-purpose multivariate methods:

 `fmin` `fmin_powell` `fmin_cg` `fmin_bfgs` `fmin_ncg`

Constrained multivariate methods:

 `fmin_l_bfgs_b` `fmin_tnc` `fmin_cobyla` `fmin_slsqp` `differential_evolution`

Univariate (scalar) minimization methods:

 `fminbound` `brent` `golden`

#### Equation (Local) Minimizers¶

 `leastsq` `least_squares` `nnls` `lsq_linear`

#### Global Optimization¶

 `basinhopping` `brute` `differential_evolution`

#### Rosenbrock function¶

 `rosen` `rosen_der` `rosen_hess` `rosen_hess_prod`

### Fitting¶

 `curve_fit`

### Root finding¶

#### Scalar functions¶

 `brentq` `brenth` `ridder` `bisect` Bisection algorithms. `newton`

Fixed point finding:

 `fixed_point`

#### Multidimensional¶

General nonlinear solvers:

 `root` `fsolve` `broyden1` `broyden2`

The root function supports the following methods:

Large-scale nonlinear solvers:

 `newton_krylov` `anderson`

Simple iterations:

 `excitingmixing` `linearmixing` `diagbroyden`

`Additional information on the nonlinear solvers`

### Linear Programming¶

General linear programming solver:

 `linprog`

The linprog function supports the following methods:

The simplex method supports callback functions, such as:

 `linprog_verbose_callback`

Assignment problems:

 `linear_sum_assignment`

### Utilities¶

 `approx_fprime` `bracket` `check_grad` `line_search` `show_options` `LbfgsInvHessProduct`