https://docs.scipy.org/doc/scipy/reference/optimize.html#local-optimization
- minimize(method=’Nelder-Mead’)
- minimize(method=’Powell’)
- minimize(method=’CG’)
- minimize(method=’BFGS’)
- minimize(method=’Newton-CG’)
- minimize(method=’L-BFGS-B’)
- minimize(method=’TNC’)
- minimize(method=’COBYLA’)
- minimize(method=’SLSQP’)
- minimize(method=’dogleg’)
- minimize(method=’trust-ncg’)
General-purpose multivariate methods:
- fmin(func, x0[, args, xtol, ftol, maxiter, ...]) Minimize a function using the downhill simplex algorithm.
- fmin_powell(func, x0[, args, xtol, ftol, ...]) Minimize a function using modified Powell’s method.
- fmin_cg(f, x0[, fprime, args, gtol, norm, ...]) Minimize a function using a nonlinear conjugate gradient algorithm.
- fmin_bfgs(f, x0[, fprime, args, gtol, norm, ...]) Minimize a function using the BFGS algorithm.
- fmin_ncg(f, x0, fprime[, fhess_p, fhess, ...]) Unconstrained minimization of a function using the Newton-CG method.
Constrained multivariate methods: => A mettre dans un autre notebook "..._constrained_localoptimization..." !
- fmin_l_bfgs_b(func, x0[, fprime, args, ...]) Minimize a function func using the L-BFGS-B algorithm.
- fmin_tnc(func, x0[, fprime, args, ...]) Minimize a function with variables subject to bounds, using gradient information in a truncated Newton algorithm.
- fmin_cobyla(func, x0, cons[, args, ...]) Minimize a function using the Constrained Optimization BY Linear Approximation (COBYLA) method.
- fmin_slsqp(func, x0[, eqcons, f_eqcons, ...]) Minimize a function using Sequential Least SQuares Programming
- differential_evolution(func, bounds[, args, ...]) Finds the global minimum of a multivariate function.
Univariate (scalar) minimization methods:
- fminbound(func, x1, x2[, args, xtol, ...]) Bounded minimization for scalar functions.
- brent(func[, args, brack, tol, full_output, ...]) Given a function of one-variable and a possible bracketing interval, return the minimum of the function isolated to a fractional precision of tol.
- golden(func[, args, brack, tol, ...]) Return the minimum of a function of one variable.