[Scilab-users] ?==?utf-8?q? Scilab 6.1 too slow to list large vectors

[Clément David]

Hello Pierre,

FYI your reported issue is probably not related at all to the matrix printing in the console. The Xcos simulation engine is kind of a gateway from the Scilab interpreter point of view (like optim() for instance), let's keep them separate issues.

Thanks,

--
Clément 

> -----Original Message-----
> From: users <users-bounces at lists.scilab.org> On Behalf Of Perrichon
> Sent: Tuesday, March 31, 2020 12:05 PM
> To: 'Users mailing list for Scilab' <users at lists.scilab.org>
> Subject: Re: [Scilab-users] ?==?utf-8?q? Scilab 6.1 too slow to list large vectors
> 
> Hello,
> 
> On another way, see bugzilla #16359 in Xcos
> 
> I've provided the program to ESI
> 
> Results :
> Xcos Scilab 5.5.2 :
> Durée de la simulation : 258.3 s
> 
> Xcos Sciab 6.1.0 :
> Durée de la simulation : 4353.4 s
> 
> Stack? Mallloc ?
> 
> Regards
> 
> 
> 
> Before printing, think about ENVIRONMENTAL responsabity
> 
> 
> -----Message d'origine-----
> De : users <users-bounces at lists.scilab.org> De la part de Antoine Monmayrant
> Envoyé : mardi 31 mars 2020 11:55 À : Users mailing list for Scilab
> <users at lists.scilab.org> Objet : Re: [Scilab-users] ?==?utf-8?q? Scilab 6.1 too
> slow to list large vectors
> 
> Hello,
> 
> I also ran some tests and it seems that the regression is clearly line-based: ie the
> regression is worse for vector than for matrix because there more lines to print
> to display a vector than a matrix of similar length.
> See my test code below.
> 
> 
> n1=300;
> n2=100;
> mat=rand(n1,n2);
> tn=[];
> 
> /* Ctrl+E the code below several times*/
> 
> tic
> mat // matrix
> //mat(:) // vector
> t=toc()
> tn=[tn,t];
> 
> disp('---------')
> disp('N_run = '+string(length(tn)))
> disp('T='+string(mean(tn))+'+/-'+string(stdev(tn)));
> 
> 
> /*
> 6.0.2 matrix
> N_run = 20
> T=0.6392742+/-0.056698
> 1.6x slower  but plotting 4 values per line ie 4x less lines to plot than for the
> matrix version
> 
> 6.1.0 matrix
> N_run = 10
> T=1.0335109+/-0.0317414
> 
> 6.0.2 vector mat(:)
> N_run = 20
> T=0.4943449+/-0.0662727
> 
> 6.1.0 vector mat(:)
> N_run = 10
> T=3.800698+/-0.1121251
> 7.7x slower ie same slow down per line than for the vector version as we plot 4
> values per line so 4x more lines
> 
> */
> 
> 
> 
> Le Mardi, Mars 31, 2020 11:36 CEST, Federico Miyara
> <fmiyara at fceia.unr.edu.ar> a écrit:
> 
> >
> > Stéphane,
> >
> > I simplified and diversified the test:
> >
> > tic
> > u = rand(100,1000)
> > toc
> >
> > takes
> > 16 s in 6.1
> > 10 s in 6.0.2
> >
> > tic
> > u = u(:)'
> > toc
> >
> > takes
> > 66 s in 6.1
> > 1.29 s in 6.0.2
> >
> > tic
> > u = u(:)
> > toc
> >
> > takes
> > 107 s in 6.1
> > 1.52 s in 6.0.2
> >
> > tic
> > u = matrix(u,1000,100)
> > toc
> >
> > takes
> > 16 s in 6.1
> > 10 s in 6.0.2
> >
> > tic
> > u = matrix(u,100, 100, 10)
> > toc
> >
> > takes
> > 0.5 s in 6.1
> > 0.5 s in 6.0.2
> >
> > Seems as if vertical (many line feeds) print took more time than
> > horizontal print.
> >
> > Regards,
> >
> > Federico Miyara
> >
> >
> >
> > On 31/03/2020 05:23, Stéphane Mottelet wrote:
> > >
> > > Hi Frederico,
> > >
> > > Thanks for reporting. Can you test if the regression also holds for
> > > matrices ?
> > >
> > > S.
> > >
> > > Le 30/03/2020 à 11:56, Federico Miyara a écrit :
> > >>
> > >> Fs  =  44100
> > >> T  =  2.5
> > >> t  =  [0:T*Fs]/Fs;
> > >> ximp  =  exp(-t/0.3).*rand(t,"normal")  +  0.004*rand(t,"normal");
> > >>
> > >> tic
> > >> ximp  =  ximp(:)
> > >> toc
> > > --
> > > Stéphane Mottelet
> > > Ingénieur de recherche
> > > EA 4297 Transformations Intégrées de la Matière Renouvelable
> > > Département Génie des Procédés Industriels Sorbonne Universités -
> > > Université de Technologie de Compiègne CS 60319, 60203 Compiègne
> > > cedex Tel : +33(0)344234688 http://www.utc.fr/~mottelet
> > >
> > > _______________________________________________
> > > users mailing list
> > > users at lists.scilab.org
> > > http://lists.scilab.org/mailman/listinfo/users
> >
> 
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