[Scilab-users] Scilab 6.1 too slow to list large vectors

[Heinz Nabielek]

On my  iMac macOS Catalina 10.15.3
 Processor Name:	Quad-Core Intel Core i7
  Processor Speed:	3.1 GHz
Darwin Kernel Version 19.3.0: Thu Jan  9 20:58:23 PST 2020; root:xnu-6153.81.5~1/RELEASE_X86_64 x86_64
Should anybody be interested....
Heinz


   2.107417
   0.564745

tic
u = u(:)
toc
   0.557869

tic 
u = matrix(u,1000,100)
toc
   2.194178


tic
u = matrix(u,100, 100, 10)
toc
   0.069732


> On 31.03.2020, at 11:36, Federico Miyara <fmiyara at fceia.unr.edu.ar> wrote:
> 
> 
> 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
>>> 
>>>