scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
xtol
ftol
[float] Relative error in xopt acceptable for convergence.
[number] Relative error in func(xopt) acceptable for convergence.
maxiter
[int] Maximum number of iterations to perform.
maxfun
[number] Maximum number of function evaluations to make.
full_output
[bool] Set to True if fval and warnflag outputs are desired.
disp
[bool] Set to True to print convergence messages.
retall
[bool] Set to True to return list of solutions at each iteration.
Notes
Uses a Nelder-Mead simplex algorithm to find the minimum of function of one or more variables.
Check OpenOpt - a tool which offers a unified syntax to call this and other solvers with
possibility of automatic differentiation.
fmin_powell(func, x0, args=(), xtol=0.0001, ftol=0.0001, maxiter=None, maxfun=None, full_output=0, disp=1,
retall=0, callback=None, direc=None)
Minimize a function using modified Powell’s method.
Parameters
func
[callable f(x,*args)] Objective function to be minimized.
x0
[ndarray] Initial guess.
args
[tuple] Eextra arguments passed to func.
callback
[callable] An optional user-supplied function, called after each iteration. Called as
callback(xk), where xk is the current parameter vector.
direc
[ndarray] Initial direction set.
Returns
(xopt, {fopt, xi, direc, iter, funcalls, warnflag}, {allvecs})
xopt
[ndarray] Parameter which minimizes func.
fopt
[number] Value of function at minimum: fopt = func(xopt).
direc
[ndarray] Current direction set.
iter
[int] Number of iterations.
298 Chapter 3. Reference