# scipy.optimize.show_options

scipy.optimize.show_options(solver=None, method=None, disp=True)

  Show documentation for additional options of optimization solvers.

  These are method-specific options that can be supplied through the `options` dict.

  Parameters
    solver str

      Type of optimization solver. One of ‘minimize’, ‘minimize_scalar’, ‘root’, ‘root_scalar’, ‘linprog’, or ‘quadratic_assignment’.

    method str, optional

      If not given, shows all methods of the specified solver. Otherwise, show only the options for the specified method. Valid values corresponds to methods’ names of respective solver (e.g., ‘BFGS’ for ‘minimize’).

    disp bool, optional

      Whether to print the result rather than returning it.

  Returns
    text

      Either None (for disp=True) or the text string (disp=False)

  Notes

  The solver-specific methods are:

  `scipy.optimize.minimize`

  - Nelder-Mead

  - Powell

  - CG

  - BFGS

  - Newton-CG

  - L-BFGS-B

  - TNC

  - COBYLA

  - SLSQP

  - dogleg

  - trust-ncg

  `scipy.optimize.root`

  - hybr

  - lm

  - broyden1

  - broyden2

  - anderson

  - linearmixing

  - diagbroyden

  - excitingmixing

  - krylov

  - df-sane

  `scipy.optimize.minimize_scalar`

  - brent

  - golden

  - bounded

  `scipy.optimize.root_scalar`

  - bisect

  - brentq

  - brenth

  - ridder

  - toms748

  - newton

  - secant

  - halley

  `scipy.optimize.linprog`

  - simplex

  - interior-point

  - revised simplex

  - highs

  - highs-ds

  - highs-ipm

  `scipy.optimize.quadratic_assignment`

  - faq

  - 2opt

  Examples

  We can print documentations of a solver in stdout:

      >>> from scipy.optimize import show_options
      >>> show_options(solver="minimize")
      ...

  Specifying a method is possible:

      >>> show_options(solver="minimize", method="Nelder-Mead")
      ...

  We can also get the documentations as a string:

      >>> show_options(solver="minimize", method="Nelder-Mead", disp=False)
      Minimization of scalar function of one or more variables using the ...

Optimization and root finding (`scipy.optimize`) scipy.optimize.OptimizeResult