Plot data and keep the maximum values
3 views (last 30 days)
Show older comments
Hello I have a set of data in a matrix, that have, two columns, the first is a distance, and the second is a shear stress. The plot that comes out when i plot these is this:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1402974/image.png)
Is there a way that I can keep a simple curve of that plot that looks something like this:
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1402979/image.png)
I am also attaching the set of data. Thank you.
0 Comments
Accepted Answer
More Answers (3)
Pramil
on 5 Jun 2023
Edited: Pramil
on 5 Jun 2023
you can try and fit a regression line to the scatter plot of your data to obtain a simple curve that approximates the trend in your data. https://www.mathworks.com/help/matlab/ref/polyfit.html
0 Comments
Nathan Hardenberg
on 5 Jun 2023
Maybe using the islocalmax-function is appropriate. But looking at your desired line this might get to many points:
x = 1:30;
y = rand([1,30]);
maxPoints = islocalmax(y);
figure(1);clf; hold on;
plot(x,y)
plot(x(maxPoints),y(maxPoints))
0 Comments
Mathieu NOE
on 5 Jun 2023
hello
several approaches are possible to draw an envelope of your data - like those examples
you will notice that none of those codes does really match the shape of your expected envelop at the rising portion of your data (at the end)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1403039/image.png)
this will require a liitle bit more work if you really want this shape
so far my suggestions :
data = readmatrix('data.txt');
t = data(:,1);
x = data(:,2);
% remove duplicates
[t,ia,ic] = unique(t);
x = x(ia);
% obtain the envelope data
%--------------------------------------------
[up1,down1] = envelope(x,17,'peak'); % option 1 with regular (TMW) envelope function
[up2,down2] = envelope2(t,x,'linear'); % option 2 with envelope2 (see function provided below)
[env] = env_secant(t, x, 10, 'top'); % option 3 with env_secant (see function attached)
tf = islocalmax(x,'MinProminence',1e-4,'MinSeparation',5); % option 3 with islocalmax (you can also try with find peaks)
tt = t(tf);
xt = x(tf);
plot(t,x,t,up1,t,up2,tt,xt,t,env)
legend('signal','envelope','envelope2','islocalmax','env secant');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [up,down] = envelope2(x,y,interpMethod)
%ENVELOPE gets the data of upper and down envelope of the known input (x,y).
%
% Input parameters:
% x the abscissa of the given data
% y the ordinate of the given data
% interpMethod the interpolation method
%
% Output parameters:
% up the upper envelope, which has the same length as x.
% down the down envelope, which has the same length as x.
%
% See also DIFF INTERP1
% Designed by: Lei Wang, <WangLeiBox@hotmail.com>, 11-Mar-2003.
% Last Revision: 21-Mar-2003.
% Dept. Mechanical & Aerospace Engineering, NC State University.
% $Revision: 1.1 $ $Date: 3/21/2003 10:33 AM $
if length(x) ~= length(y)
error('Two input data should have the same length.');
end
if (nargin < 2)||(nargin > 3),
error('Please see help for INPUT DATA.');
elseif (nargin == 2)
interpMethod = 'linear';
end
% Find the extreme maxim values
% and the corresponding indexes
%----------------------------------------------------
extrMaxIndex = find(diff(sign(diff(y)))==-2)+1;
extrMaxValue = y(extrMaxIndex);
% Find the extreme minim values
% and the corresponding indexes
%----------------------------------------------------
extrMinIndex = find(diff(sign(diff(y)))==+2)+1;
extrMinValue = y(extrMinIndex);
up = extrMaxValue;
up_x = x(extrMaxIndex);
down = extrMinValue;
down_x = x(extrMinIndex);
% Interpolation of the upper/down envelope data
%----------------------------------------------------
up = interp1(up_x,up,x,interpMethod);
down = interp1(down_x,down,x,interpMethod);
end
1 Comment
Mathieu NOE
on 5 Jun 2023
Finally, maybe this is the best solution, without too much hassle :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1403059/image.png)
data = readmatrix('data.txt');
t = data(:,1);
x = data(:,2);
% remove duplicates
[t,ia,ic] = unique(t);
x = x(ia);
% "detrend" the signal by removing the smoothed data (slightly amplified to
% remove the small peaks from selection)
xm = 1.15*smoothdata(x,'movmedian',30);
xd = x - xm;
id = xd<0;
xd(id) = 0;
tf = islocalmax(xd,'MinSeparation',10); % option 3 with islocalmax (you can also try with find peaks)
tt = t(tf);
xt = x(tf);
plot(t,x,tt,xt)
See Also
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!