This is a pre-release version (latest).Go to latest (1.18.0)
{ } Raw JSON

bundles / scipy latest / scipy / optimize / _cobyla_py / _minimize_cobyla

function

scipy.optimize._cobyla_py:_minimize_cobyla

source: build-install/usr/lib/python3.14/site-packages/scipy/optimize/_cobyla_py.py:186

Signature

def _minimize_cobyla(fun, x0, args = (), constraints = (), rhobeg = 1.0, tol = 0.0001, maxiter = 1000, disp = 0, catol = None, f_target = -inf, callback = None, bounds = None, **unknown_options)

Summary

Minimize a scalar function of one or more variables using the Constrained Optimization BY Linear Approximation (COBYLA) algorithm. This method uses the pure-python implementation of the algorithm from PRIMA.

Parameters

rhobeg : float

Reasonable initial changes to the variables.

tol : float

Final accuracy in the optimization (not precisely guaranteed). This is a lower bound on the size of the trust region.

disp : int

Controls the frequency of output:

  • (default) There will be no printing

  • A message will be printed to the screen at the end of iteration, showing the best vector of variables found and its objective function value

  • in addition to 1, each new value of RHO is printed to the screen, with the best vector of variables so far and its objective function value.

  • in addition to 2, each function evaluation with its variables will be printed to the screen.

maxiter : int

Maximum number of function evaluations.

catol : float

Tolerance (absolute) for constraint violations

f_target : float

Stop if the objective function is less than f_target.

Aliases

  • scipy.optimize._cobyla_py._minimize_cobyla