MathGroup Archive 2005

[Date Index] [Thread Index] [Author Index]

Search the Archive

Re: Optimization doing more function evaluations than claimed?

  • To: mathgroup at smc.vnet.net
  • Subject: [mg57242] Re: Optimization doing more function evaluations than claimed?
  • From: Gareth Russell <gjr2008 at columbia.edu>
  • Date: Sat, 21 May 2005 02:41:11 -0400 (EDT)
  • Organization: Columbia University
  • References: <d6k9kl$12g$1@smc.vnet.net>
  • Sender: owner-wri-mathgroup at wolfram.com

Hello again,

Daniel Lichtblau sent me a suggestion (thanks Daniel), which led 
tangentially to the following observation: the double evaluation I 
described goes away if I remove the large secondary arguments (vectors 
and matrices that are the datasets) from the function by making them 
global variables. So the new function is

lDistExp[b1_?NumericQ] := Module[{distQ,pMaps, logList, logLike},
    distQ = mapExponential2[distMaps, b1];
    pMaps = Map[toProbs[#] &, distQ];
    logList = Log[MapThread[#1[[#2]] &, {pMaps, e}]];
    loglike=Apply[Plus, logList];
    Print[{b1,logLike}];
    logLike
    ]

and distMaps and e are global.

My practical problem is now solved, but can anyone explain why the 
passing of large numerical expressions as arguments might cause a 
double evaluation when the function is within a FindMinimum statement? 
Just wondering, really...

Gareth

On 2005-05-20 05:11:49 -0400, Gareth Russell <gjr2008 at columbia.edu> said:

> Hi All,
> 
> I have been using FindMaximize without symbolic derivatives to maximize 
> a likelihood function that operates on a large dataset. Because the 
> process is slow, I want to track progress as it happens, so I include a 
> Print[{parameter1, parameter2, ..., likelihood}] step in the function 
> being evaluated. In doing so, I have noticed that the function appears 
> to be evaluated twice for each trial of the parameter values. When I 
> look at diagnostics after the fit is complete, such as the output of 
> the EvaluationMonitor option, it shows each trial only once. For 
> example, if Mathematica claims 20 steps after the fact, the number of 
> printed outputs is always 40, in identical pairs. The 40 outputs appear 
> evenly spaced in time, and the total timing of the fitting process, 
> compared to the timing of one evaluation of the function, confirms that 
> indeed, it was evaluated 40 times.
> 
> Does anyone know why (i.e., under what conditions) FindMinimum might do 
> this? You won't be able to evaluate my function, as it calls the 
> datasets, but here it is anyway, with some info:
> 
> lDistExp[distMaps_, e_, b1_?NumericQ] := Module[{distQ,     pMaps, 
> logList, logLike},
>     distQ = mapExponential2[distMaps, b1];
>     pMaps = Map[toProbs[#] &, distQ];
>     logList = Log[MapThread[#1[[#2]] &, {pMaps, e}]];
>     loglike=Apply[Plus, logList];
>     Print[{b1,logLike}];
>     logLike
>     ]
>    distMaps is a (large) matrix of reals, e is a vector of integers, 
> and b1 is a real.
> 
> The functions mapExponential2[] and toProbs[] are compiled functions 
> (for speed).
> 
> The function is maximized with respect to b1.
> 
> As a side note that may be relevant, if I load the 
> Optimization`UnconstrainedProblems` package and use the FindMinimumPlot 
> function, the target function is be evaluated THREE times per step, 
> even though the output again says just 20 steps.
> 
> Because the fitting procedure is necessarily slow because of dataset 
> size, I don't want to be doing more function evaluations than are 
> necessary!
> 
> Thanks,
> 
> Gareth Russell
> Columbia University



  • Prev by Date: Re: runs test for evaluation of model fit
  • Next by Date: Re: Nestwhile
  • Previous by thread: Optimization doing more function evaluations than claimed?
  • Next by thread: How to Clear y'[0]