Hi Oliver,
If you’re looking for the current state at each iteration, you want to check
res.trace.states.
One way to field out this kind of information is to use the names function:
julia> names(res)
15-element Array{Symbol,1}:
:method
:initial_x
:minimum
:f_minimum
:iterations
:iteration_converged
:x_converged
:xtol
:f_converged
:ftol
:gr_converged
:grtol
:trace
:f_calls
:g_calls
julia> names(res.trace)
1-element Array{Symbol,1}:
:states
Of course, you still need to figure out what the fields mean, but we’ve tried
to use sensible names for the fields in Optim.
— John
On Jan 4, 2014, at 11:14 AM, Oliver Lylloff <[email protected]> wrote:
> Hi John,
> Thanks for the fast answer.
>
> I still don't think I get the output I want. The res.minimum only return the
> converged solution (one vector), however I would like to get the minimum for
> all 1 to N iterations (N vectors). Setting store_trace=true gets me closer,
> since res.trace prints the information I'm seeking but not as an field
> (res.trace.x).
>
> Hope it makes sense.
> Best,
> Oliver
>
> Den lørdag den 4. januar 2014 16.56.03 UTC+1 skrev John Myles White:
> Hi Oliver,
>
> The result of optimize is an object with a field called minimum that has the
> solution.
>
> Try something like the following:
>
> julia> res = optimize(x -> (10.0 - x[1])^2, [0.0], method =
> :gradient_descent)
> Results of Optimization Algorithm
> * Algorithm: Gradient Descent
> * Starting Point: 0
>
> * Minimum: 10.000000000118629
>
> * Value of Function at Minimum: 0.000000
> * Iterations: 1
> * Convergence: true
> * |x - x'| < 1.0e-32: false
> * |f(x) - f(x')| / |f(x)| < 1.0e-08: false
> * |g(x)| < 1.0e-08: true
> * Exceeded Maximum Number of Iterations: false
> * Objective Function Calls: 4
> * Gradient Call: 4
>
> julia> res.minimum
> 1-element Array{Float64,1}:
> 10.0
>
> — John
>
> On Jan 4, 2014, at 10:52 AM, Oliver Lylloff <[email protected]> wrote:
>
> > Hello all,
> >
> > I'm trying to get acquainted with the Optim package - so far I think
> > everything looks very interesting.
> > I would like to get the solution vector of each iteration as an output
> > (e.g. for plotting) - how do I do that?
> >
> > Trying the Rosenbrock example from https://github.com/JuliaOpt/Optim.jl
> > with extended_trace option
> >
> > optimize(f,g!,[0.0,0.0],method=:gradient_descent,extended_trace=true)
> >
> > prints the solution vector x at each iteration but I can't seem to access
> > it and store it. Any ideas?
> >
> >
> > Best,
> > Oliver
> >
> >
>
