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scipy.optimize.fmin_cobyla

scipy.optimize.fmin_cobyla(func, x0, cons, args=(), consargs=None, rhobeg=1.0, rhoend=0.0001, iprint=1, maxfun=1000)

Minimize a function using the Constrained Optimization BY Linear Approximation (COBYLA) method.

Parameters :

func : callable f(x, *args)

Function to minimize.

x0 : ndarray

Initial guess.

cons : sequence

Constraint functions; must all be >=0 (a single function if only 1 constraint).

args : tuple

Extra arguments to pass to function.

consargs : tuple

Extra arguments to pass to constraint functions (default of None means use same extra arguments as those passed to func). Use () for no extra arguments.

rhobeg : :

Reasonable initial changes to the variables.

rhoend : :

Final accuracy in the optimization (not precisely guaranteed).

iprint : {0, 1, 2, 3}

Controls the frequency of output; 0 implies no output.

maxfun : int

Maximum number of function evaluations.

Returns :

x : ndarray

The argument that minimises f.