On 10/04/2021 23:58, Heinz Nabielek wrote:
On 10.04.2021, at 08:10, Antoine Monmayrant <antoine.monmayr...@laas.fr> wrote:
On 09/04/2021 23:55, Heinz Nabielek wrote:
xfpoly does generally a good job for me, sometimes I would wish that the
filling colour could be made transparent.
This is a much needed improvement of the scilab graphical stack that currently
does not provide any transparency.
I think this is not an easy improvement.
At the moment, my workaround is to plot everything I need, export as svg and
than add the transparency I need in the svg using inkscape or directly editing
the svg file with a text editor...
Heinz
PS 1: Is there a new version of the 2011 BetweenCurves around?
Er, no, it was just a dirty hack I needed for my own publications and I think
2011 is the most recent one.
I can try to see how to improve it if this can improve scilab...
I had initiated by log vs lin plot with
plot2d([0 80],[1 100], style=0,logflag = "nl");
but BetweenCurves starts with its own plot and here I would not know, what to
do...
Hello,
There are two options:
(1) If you already have a handle "h0" to a plot and want BetweenCurves
to use it, you can do:
[h,epoly,ey1,ey2]=BetweenCurves(x,y1,y2,handle, h0)
(2) you can also do:
[h,epoly,ey1,ey2]=BetweenCurves(x,y1,y2,handle, h0)
and then use
h.children(1).log_flags='nln'
to change from linear to log y axis.
Is this what you have in mind?
Antoine
Heinz
BTW, how do the French infection rates look like?
I must admit it is not a metric I track.
For the trend in France I go here
https://coronavirus.politologue.com/coronavirus-france.FR and for a more
global view there: https://coronavirus.politologue.com/100k-habitants/
PS 2: Any suggestion to make my clumsy coding more elegent, is highly welcome
PS 2: BTW, since the recent lockdown, infection rates are coming down in
Austria.....
A=[12.628 13.942 17.077 17.054 15.594 14.976 14.796 11.875
13.448 16.504 17.717 19.447 16.099 13.302 13.762 16.032
19.492 22.098 20.425 21.087 20.649 14.268 19.402 22.525
26.862 23.514 27.603 23.851 15.830 21.570 28.682 26.109
29.974 28.727 24.705 21.458 27.087 28.401 33.670 35.119
33.962 28.120 21.301 27.244 37.467 37.715 39.490 37.569
30.480 27.098 38.366 36.951 35.097 43.759 39.299]';
d=(1:length(A))';
up=10^(d/53);
M=[ones(up) up];
aa=M\A;
B=inv(M'*M);
DD=(1:110)';
U=10^(DD/53);
MM=[ones(U) U];
yh = M*aa; //Fitted values yh to approximate measured y's
e=A-yh; //Errors or residuals
SSE=e'*e; //Sum of squared errors
ybar=mean(A); R2=1-SSE/sum((A-ybar)^2);
[m n]=size(M);
MSE = SSE/(m-n-1); //Mean square error
C=MSE*B // covariance matrix
sig=sqrt(MSE);
seb=sqrt(diag(C));
[aa seb]
[n pp]=size(M);
CONF=.95; alpha=1-CONF;
ta2 = cdft('T',n-pp,1-alpha/2,alpha/2); //t-value for alpha/2
yhh= MM*aa;
p=sig*sqrt(diag(1+MM*B*MM'));
N=[yhh+ta2*p yhh-ta2*p];
polyX = [DD;flipdim(DD,1)];
polyY = [N(:,1);flipdim(N(:,2),1)];
plot2d([0 80],[1 100], style=0,logflag = "nl");
xgrid;
xfpoly(polyX, polyY,6);
plot(DD,MM*aa,'g.-');
plot(d,A,'b.') ;
title('AUSTRIA daily infection rates per 100,000','fontsize',5);
xlabel('days since 1 Feb 2021','fontsize',3);
ylabel('number of infections per day per 100,000','fontsize',3);
legend('data from Johns Hopkins GitHub','95% confidence range','model
prediction','AUSTRIA recorded',4);
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