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bundles / scipy 1.17.1 / scipy / optimize / _optimize / show_options

function

scipy.optimize._optimize:show_options

source: /scipy/optimize/_optimize.py :3948

Signature

def   show_options ( solver = None ,  method = None ,  disp = True )

Summary

Show documentation for additional options of optimization solvers.

Extended Summary

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 <optimize.minimize-neldermead>

  • Powell <optimize.minimize-powell>

  • CG <optimize.minimize-cg>

  • BFGS <optimize.minimize-bfgs>

  • Newton-CG <optimize.minimize-newtoncg>

  • L-BFGS-B <optimize.minimize-lbfgsb>

  • TNC <optimize.minimize-tnc>

  • COBYLA <optimize.minimize-cobyla>

  • COBYQA <optimize.minimize-cobyqa>

  • SLSQP <optimize.minimize-slsqp>

  • dogleg <optimize.minimize-dogleg>

  • trust-ncg <optimize.minimize-trustncg>

scipy.optimize.root

  • hybr <optimize.root-hybr>

  • lm <optimize.root-lm>

  • broyden1 <optimize.root-broyden1>

  • broyden2 <optimize.root-broyden2>

  • anderson <optimize.root-anderson>

  • linearmixing <optimize.root-linearmixing>

  • diagbroyden <optimize.root-diagbroyden>

  • excitingmixing <optimize.root-excitingmixing>

  • krylov <optimize.root-krylov>

  • df-sane <optimize.root-dfsane>

scipy.optimize.minimize_scalar

  • brent <optimize.minimize_scalar-brent>

  • golden <optimize.minimize_scalar-golden>

  • bounded <optimize.minimize_scalar-bounded>

scipy.optimize.root_scalar

  • bisect <optimize.root_scalar-bisect>

  • brentq <optimize.root_scalar-brentq>

  • brenth <optimize.root_scalar-brenth>

  • ridder <optimize.root_scalar-ridder>

  • toms748 <optimize.root_scalar-toms748>

  • newton <optimize.root_scalar-newton>

  • secant <optimize.root_scalar-secant>

  • halley <optimize.root_scalar-halley>

scipy.optimize.linprog

  • simplex <optimize.linprog-simplex>

  • interior-point <optimize.linprog-interior-point>

  • revised simplex <optimize.linprog-revised_simplex>

  • highs <optimize.linprog-highs>

  • highs-ds <optimize.linprog-highs-ds>

  • highs-ipm <optimize.linprog-highs-ipm>

scipy.optimize.quadratic_assignment

  • faq <optimize.qap-faq>

  • 2opt <optimize.qap-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)
✗

Aliases

  • scipy.optimize.show_options