How to plot a smooth curve for Empirical probability density ?

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Andi
Andi 2022 年 3 月 29 日
コメント済み: Mathieu NOE 2022 年 4 月 1 日
Hi everyone,
I require to plot an empirical probability density curve of a data set (184 rows, 59 columns). Initially, I pick one column to plot the results but, the EPD curve looks so wired. May someone suggest to me how can I get desired result (Attached). Data is also attached for reference.
clear all
clc
X = load('R_0.01T.csv'); % input data
SzX = size(X) % matrix size
r=[X(1,:)]; % first row of the data set
ra = r(~isnan(r)); % remove all nan enteries
[f,x,flo,fhi] = ecdf(ra);
WinLen = 5
dfdxs = smoothdata(gradient(f)./gradient(x), 'movmedian',WinLen); % ... Then, Smooth Them Again ...
aaa = smooth(dfdxs);
plot(x, aaa)
This is what i get
Here is the expected results.
  2 件のコメント
VBBV
VBBV 2022 年 3 月 29 日
Change the line
WinLen = 35%
Modify this value and you can observe the difference
Andi
Andi 2022 年 3 月 29 日
Still not expected, I have tried with different values but no significant change.

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Mathieu NOE
Mathieu NOE 2022 年 3 月 29 日
hello
tried a few options , smoothdata and spline fit. In fact, I was thinking you wanted something super smooth so I first opted for the spline fit. But I saw that the expected plot was supposed to have some waviness , so I changed to smoothdata
NB as I don't have the toolbox for ecdf , I found an alternative on FEX for it https://fr.mathworks.com/matlabcentral/fileexchange/32831-homemade-ecdf
but I had to correct a bug (the corrected function is attaced fyi)
hope the code below can help you
clear all
clc
X = load('R_0.01T.csv'); % input data
SzX = size(X); % matrix size
r=X(1,:); % first row of the data set
ra = r(~isnan(r)); % remove all nan enteries
% [f,x,flo,fhi] = ecdf(ra);
[f,x] = homemade_ecdf(ra); % FEX : https://fr.mathworks.com/matlabcentral/fileexchange/32831-homemade-ecdf
% remove duplicates
[x,ia,ic] = unique(x);
f = f(ia);
% resample the data (interpolation) on linearly spaced points
xx = linspace(min(x),max(x),100);
ff = interp1(x,f,xx);
% smoothing
ffs = smoothdata(ff, 'loess',40);
% or spline fit ?
% Breaks interpolated from data (log x scale to get more points in the
% lower x range and less in the upper x range)
breaks = logspace(log10(min(x)),log10(max(x)),5); %
p = splinefit(xx,ff,breaks); %
ff2 = ppval(p,xx);
figure(1),
plot(x,f,'*',xx,ffs,'-',xx,ff2,'-')
legend('raw','smoothed','spline fit');
% compute gradient from spline fitted data (my choice)
dx = mean(diff(xx));
dfdxs = gradient(ffs)./dx;
figure(2),plot(xx, dfdxs)
  14 件のコメント
Andi
Andi 2022 年 3 月 31 日
編集済み: Andi 2022 年 3 月 31 日
Thank a lot. I think now i very near to the expected results. I have modified your script a bit to actual condition and plot the results. But woundering, why i unable to set color bar as jet, secondly the tick bar are not required only few ont power termed be fine.
clear all
clc
X = load('PDS_case.csv'); % input data
C_sort = sortrows(X,5);
Tri = C_sort(1:86,:);
data1 = sortrows(Tri,7);
PDS=(data1(:,7))';
data2=data1(:,8:66);
data4=data2';
Y=data4(:,1:86);
X=Y';
UU=[2e-8, 4e-8, 6e-8, 8e-8, 1e-7, 3e-7]; % these values linked with each color bar, should be make a color bar
r{1}=[X(1:60,:)];
r{2}=[X(61:68,:)];
r{3}=[X(69:76,:)];
r{4}=[X(77:79,:)];
r{5}=[X(80:81,:)];
r{6}=[X(82:85,:)];
figure
cm = colormap(jet(numel(r)));
cc = colorbar('vert');
set(cc,'Ticks',((1:numel(UU))/numel(UU))');
set(cc,'TickLabels',num2str(UU'));
ylabel(cc,'PDS')
hold on
for k = 1:numel(r) % ... Then, Remove The 'NaN' Elements ...
ra = r{k};
ra = ra(~isnan(ra));
[f ,x ] = ecdf(ra);
[x ,ia ,ic ] = unique(x);
f = f(ia );
xx = linspace(min(x ),max(x ),100);
ff = interp1(x ,f ,xx );
ffs = smoothdata(ff , 'loess',10);
dx = mean(diff(xx ));
dfdxs = gradient(ffs )./dx ;
plot(xx , dfdxs , '-', 'linewidth', 1, 'Color',cm(k,:))
ylim([0, 8])
end
hold off
grid
Here is what i get
and the expected one should be like
Mathieu NOE
Mathieu NOE 2022 年 4 月 1 日
hello again
1/ seems the expected curves are smoother compare to what we have now. You can probably increase the smoothing (driven by the value in smoothdata parameter)
ffs = smoothdata(ff , 'loess',10); % increase 10 =>20
2/ scale of the colorbar (ticks) : I don't know what are the values you specify in UU coming from ?

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