standard deviation on power vs. frequency graph
3 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
nines
le 18 Jan 2020
Réponse apportée : Star Strider
le 18 Jan 2020
Hello all!
I am trying to put a shaded standard deviation on a power vs. frequency graph.
I've tried:
%errorbar
plot(f, mean(allspectrums_cortex_young)); hold on;
errorbar(f, std(allspectrums_cortex_young)/sqrt(13)); hold on;
fill(f, std(allspectrums_cortex_young)/sqrt(13),[1 0 0],'LineStyle','none');
title('Young Power - Cortex')
ylim([0 2000])
xlim([0 .15])
xlabel('Frequency (in hertz)');
ylabel('Power (n=13)'
%fill
plot(f, mean(allspectrums_cortex_young)); hold on;
fill(f, std(allspectrums_cortex_young)/sqrt(13),[1 0 0],'LineStyle','none');
title('Young Power - Cortex')
ylim([0 2000])
xlim([0 .15])
xlabel('Frequency (in hertz)');
ylabel('Power (n=13)'
and I get this:
when I am looking for something more like:
does anyone have any ideas? thanks so so much!
0 commentaires
Réponse acceptée
Star Strider
le 18 Jan 2020
It would help to have your data, however I created some to illustrate the approach:
f = linspace(0, 0.5, 25); % Frequency Vector
allspectrums_cortex_young = 1E+3*rand(5, 25) + 1600*exp(-10*f); % Synthetic Spectrum
mn_allspectrums_cortex_young = mean(allspectrums_cortex_young);
sd_allspectrums_cortex_young = std(allspectrums_cortex_young);
figure
plot(f, mn_allspectrums_cortex_young)
hold on
patch([f fliplr(f)], [(mn_allspectrums_cortex_young+sd_allspectrums_cortex_young) fliplr(mn_allspectrums_cortex_young-sd_allspectrums_cortex_young)], 'r', 'FaceAlpha',0.5, 'EdgeColor','none')
hold off
The approach (using the patch function) is to create a closed curve that patch then fills. That is done here by adding and then subtracting the std from the mean, after plotting the mean.
Example —
0 commentaires
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Teaching Resources dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!