Effacer les filtres
Effacer les filtres

Two bar graphs - two data sets - different bin width

13 vues (au cours des 30 derniers jours)
Flo
Flo le 4 Juil 2016
Hi everyone,
I am kinda new to matlab and may not have been asking the right question to google. Anyway, here is my problem: I've got two data sets called one and two:
none = length(one)
ntwo = length(two)
%h = nan(max(none,ntwo),2)
h(1:none,1)=one
h(1:ntwo,2)=two
From there I extract the best bin width and the theoretical best amount of bin for each data set ( following the The Freedman-Diaconis rule):
%one -------
minNumberOne = round(min(h(1:none,1)))
maxNumberOne = ceil(max(h(1:none,1)))
iqrVarOne = iqr(h(1:none,1))
hOne = ceil(2 * iqrVarOne * none^(-1/3))
binsOne = ceil((maxNumberOne - minNumberOne)/hOne)
%two -------
minNumberTwo = round(min(h(1:ntwo,2)))
maxNumberTwo = ceil(max(h(1:ntwo,2)))
iqrVarTwo = iqr(h(1:ntwo,2))
hTwo = ceil(2 * iqrVarTwo * ntwo^(-1/3))
binsTwo = ceil((maxNumberTwo - minNumberTwo)/hTwo)
From now I am a bit lost. I'd like to apply for each bar graph the number of bin and the bin width, AND displaying those graph on the same figure, like that:
My code:
figure(1)
data = [h(:,1) h(:,2)]
[y, x] = hist(data)
bar(x,y, 'group')
this code doesn't take into account the bins calculated before of course. Do you have any ideas on how to integrate that to my code?
Cheers everyone. I hope I have been clear enough...
Flo

Réponses (2)

José-Luis
José-Luis le 4 Juil 2016
one = rand(100,1);
two = rand(100,1);
nOne = 10;
nTwo = 15;
figure
histogram(one,nOne);
hold on;
histogram(two,nTwo);
%clearer
figure
ksdensity(one);
hold on;
ksdensity(two)
  9 commentaires
José-Luis
José-Luis le 5 Juil 2016
Such a plot might be a mess depending on how you bins intersect though...
Flo
Flo le 5 Juil 2016
By looking on google I've found a way apparently. It may interest some person. Let me know what you think about it:
figure(1);
[dummy, t] = hist([one;two], numBin);
nx = hist(one, t); % Sort x into bins.
nx = transpose(nx/sum(nx));
ny = hist(two, t); % Sort y into bins.
ny = transpose(ny/sum(ny));
bar(t, [nx, ny]);

Connectez-vous pour commenter.


Duncan Po
Duncan Po le 5 Juil 2016
histogram/histcounts have builtin support for Freedman-Diaconis rule:
histogram(x, 'BinMethod', 'fd')
or
[n, binedges] = histcounts(x, 'BinMethod', 'fd')

Catégories

En savoir plus sur Environment and Settings 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!

Translated by