On 07/28/2014 03:59 PM, chloe.kykam wrote:
Thanks Antoine, it does work after I restart Scilab.

However, my actual code consists of more than 1 data set, and I would have
to normalise them according the their respective areas under the curve. The
code only works without the normalisation part (replacing ri with r), but
error 21 arises when the part is included.

funcprot(0)
workbook = readxls('C:\Users\Kying\Desktop\Stray_light\Data.xls')
sheet = workbook(1) //old

k=6.63e-34*3e8/1.38e-23
x=sheet(:,2)
ri=sheet(:,3)
gi=sheet(:,4)
bi=sheet(:,5)
uvi=sheet(:,6)

//normalization
norm=max([inttrap(x,ri),inttrap(x,gi),inttrap(x,bi),inttrap(x,uvi)])
r=norm/inttrap(x,ri)*ri
g=norm/inttrap(x,gi)*gi
b=norm/inttrap(x,bi)*bi
uv=norm/inttrap(x,uvi)*uvi
//end of normalization

dims=1
ur=min(find(r>0.71*max(r))) //uppler limit
lr=max(find(find(r<10)<find(r==max(r)))) //lower limit
wr=matrix((cat(dims,zeros(lr-1,1),ones(ur-lr+1,1),zeros(1024-ur,1))),1024,1)
//weighting

//exponential function
function y=yth(x,a)
      y=a(1)*exp(-k./x/a(2))
endfunction

//initial parameters
a0=[1.0;300]

function e=myfun(a,x,r,wr)
      e=wr.*(yth(x,a)-r)
endfunction

//call leastsq
[f,xopt,gopt]=leastsq(list(myfun,x,r,wr),a0)

scf();
plot2d(x,r,logflag=&quot;nl&quot;,style=[color(&quot;red&quot;)])
//plot2d(x,yth(x,xopt))
plot2d(x,g,logflag=&quot;nl&quot;,style=[color(&quot;green&quot;)])
plot2d(x,b,logflag=&quot;nl&quot;,style=[color(&quot;blue&quot;)])
plot2d(x,uv,logflag=&quot;nl&quot;,style=[color(&quot;purple&quot;)])

Error message:
-->exec('C:\Users\Kying\Desktop\Stray_light\testing2.sce', -1)
  !--error 21
Invalid index.
at line     118 of function numderivative called by :
at line       2 of function Dfun called by :
at line       2 of function %opt called by :
at line      92 of function leastsq called by :
[f,xopt,gopt]=leastsq(list(myfun,x,r,wr),a0)
at line      38 of exec file called by :
exec('C:\Users\Kying\Desktop\Stray_light\testing2.sce', -1)

Do you have any idea why that is?

Check the length and dimension (ie is it 1xn or nx1) of the vectors you are using with and without the normalization.
Are there any difference before and after the normalization?
leastsq is particularly picky: x and y need to be column vectors, not row vectors. Moreover, when x and y have not the right length or dimensions, it tends to output cryptic error messages.

Cheers,

Antoine


Thanks




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