minimize(method=’COBYLA’)#
- scipy.optimize.minimize(fun, x0, args=(), method='COBYLA', constraints=(), tol=None, callback=None, options={'rhobeg': 1.0, 'maxiter': 1000, 'disp': False, 'catol': 0.0002})
Minimize a scalar function of one or more variables using the Constrained Optimization BY Linear Approximation (COBYLA) algorithm.
See also
For documentation for the rest of the parameters, see
scipy.optimize.minimize
- Options
- ——-
- rhobegfloat
Reasonable initial changes to the variables.
- tolfloat
Final accuracy in the optimization (not precisely guaranteed). This is a lower bound on the size of the trust region.
- dispbool
Set to True to print convergence messages. If False, verbosity is ignored as set to 0.
- maxiterint
Maximum number of function evaluations.
- catolfloat
Tolerance (absolute) for constraint violations
- callbackcallable, optional
Called after each iteration, as
callback(x)
, wherex
is the current parameter vector.