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Re: NMinimize

  • To: mathgroup at smc.vnet.net
  • Subject: [mg81775] Re: [mg81740] NMinimize
  • From: DrMajorBob <drmajorbob at bigfoot.com>
  • Date: Wed, 3 Oct 2007 02:33:30 -0400 (EDT)
  • References: <28656799.1191337430978.JavaMail.root@m35>
  • Reply-to: drmajorbob at bigfoot.com

It all depends on what the meaning of "do this" is. Without data, it's  
hard to say.

Offhand, calculating Select again for every value of Di, De, and i -- when  
it depends only on i -- can't be a good idea. For that, you can define

tiSelected[i_] :=
  tiSelected[i] = Select[ti, i - 2880 <= #[[2]] <= i - 1 &]

or

tiSelected[i_] :=
  tiSelected[i] = Pick[ti, ti[[All, 2]], x_ /; i - 2880 <= x <= i - 1]

and use tiSelected[i] in the NMinimize statement.

You can do even better, since this ALSO depends only on i:

Plus @@ ((func[15.2, Di, De, i, First@#, Last@#] &) /@
    Select[ti, i - floor <= #[[2]] <= i - 1 &])

if Di and De are left in symbolic form for now. One way to do this is

Clear[di, de, func]
plus[i_] :=
  plus[i] = func[15.2, di, de, i, First@#, Last@#] & /@ tiSelected[i]

(You can experiment with defining func before or after this. If before, 
then don't Clear it. Evaluate plus[20001] and see what you get, each way.)

Another optimization comes from realizing that Plus@@Table is the same as  
Sum and, so that

f[di_, de_] = Sum[data[[i - 20000]] - plus[i], {i, 22881, 25000}];

or -- better yet --

f[di_, de_] = Total@data[[881 ;; 3000]] - Sum[plus[i], {i, 22881, 25000}]

(double-check those limits) allows the final result to be

NMinimize[{f[di, de], 10^-8 <= di <= 10^-1,
   10^-8 <= de <= 10^-1}, {di, de}]

f[di,de] will be a very large expression, so that level of optimization 
may not work out... but "tiSelected" and "plus" should still be  
worthwhile. In that case, defining func BEFORE plus may be best. (Or not.  
Try it out.)

The functions change when ti and "data" change, of course, but not within  
NMinimize. Without data I can't fully test it, but these are the kind of 
"tricks" you'll need.

Bobby

On Tue, 02 Oct 2007 04:47:30 -0500, Raj <rajanikanth at gmail.com> wrote:

> hi!
> Could somebody tell me if there is a better way to do this in
> Mathematica:
>
> data = Flatten@Import["moistureAtDepth1.dat"];
> data = data[[20000 ;; 30000]];
> ti = Import["times.dat"];
> func[x_, Di_, De_, t_, t1_, t2_] :=
>    (Erfc[x/Sqrt[2400 Di (t - t1)]] -
>    Erfc[x/Sqrt[2400 Di (t - t2)]] +
>    Erf[x/Sqrt[2400 De (t - t2) ]])
> parameters = {Di,De};
> NMinimize[ {Plus@@Table[ (data[[i-20000]] -
>       Plus @@ ((func[15.2, Di, De, i, First@#, Last@#] &) /@
>          Select[ti, i - 2880 <= #[[2]] <= i-1 &]))^2,{i,22881,25000}],
> 10^-8<=Di<=10^-1,10^-8<=De<=10^-1},parameters]
>
> I am interested in Optimizing  the NMinimize line.
>
> Thanks,
>
> Raj
>
>
>



-- 
DrMajorBob at bigfoot.com


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