How to plot the mean value of X corresponding to each Y value?

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Hello!
I want to plot a vertical profile of temperature (so Y-axis is depth (m) and X-axis is temperature (ºC)). Because I have many measurements for each depth, what I get is a profile made of a cloud of points:
However, I would like to get a linear profile, so I guess I would need to plot each X mean value for each Y, right?
Could someone please help me on that?
Thanks a lot!
  3 Kommentare
Alejandra Uguet de Resayre
Alejandra Uguet de Resayre am 11 Jan. 2023
It doesn't let me attach the mat file because it is too big (more than 5MB).
What I mean is that from that cloud of points I want to get something like this instead, like a single line thing, so I guess that's the mean value of X for each Y.
Thank you for answering!! <3 <3 <3
Star Strider
Star Strider am 11 Jan. 2023
@Alejandra Uguet de Resayre — Please see my latest Comment to my Answer. It produces the result matching the plot you posted.

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Akzeptierte Antwort

Star Strider
Star Strider am 11 Jan. 2023
I am not certain what you want.
Perhaps something like this —
x = ones(9,1)*linspace(13, 19, 50); % Create Data
y = 8E+2*(1-exp(-5*(x-13)))-1E+3 + randn(9,size(x,2))*75; % Create Data
T = x(:); % Temperature (Assume Column Vector)
D = y(:); % Depth (Assume Column Vector)
NBins = 14; % Change This To Change Temperature Resolution
[N,Edges,Dpthv] = histcounts(D, NBins);
Ctrs = Edges(1:end-1) + mean(diff(Edges)); % Depth Centers
% Tvct = linspace(min(T), max(T), NBins);
TempMean = accumarray(Dpthv, T, [], @mean) % Calculate Mean Temperature At Each Depth
TempMean = 14×1
13.0000 13.0000 13.0000 13.0000 13.1224 13.1224 13.1224 13.1837 13.6234 15.5923
figure
plot(T, D, '.r', 'DisplayName','Data')
hold on
plot(TempMean, Ctrs, '.-b', 'DisplayName','Mean Temperature')
hold off
grid
xlabel('Temperature (°C)')
ylabel ('Depth (m)')
legend('Location','best')
The blue line plots depth as a function of the mean temperature.
.
  9 Kommentare
Alejandra Uguet de Resayre
Alejandra Uguet de Resayre am 13 Jan. 2023
You all are right :) Thank you both for your time invested, it helped me so much.

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Mathieu NOE
Mathieu NOE am 11 Jan. 2023
hello
yes i'm coming late in the show... nevertheles I am here !!
just for the fun and FYI
your data could be decimated up to factor 100 without loss of quality I think
without decimation :
with decimation factor 50
code
load('matlab.mat');
temp = candec18tCopy.theta;
depth = -candec18tCopy.dep;
% remove nan's
idx = isnan(temp);
temp(idx) = [];
depth(idx) = [];
% sort
[temp,id] = sort(temp,'ascend');
depth = depth(id);
% unique
[temp,IA,IC] = unique(temp);
depth = depth(IA);
% decimation
decim_fact = 50; % test with 1 to 100
ind = 1:decim_fact:numel(depth);
temp = temp(ind);
depth = depth(ind);
% remove data below 13.25
ind = (temp<13.25);
temp(ind) = [];
depth(ind) = [];
depth_s = smoothdata(depth,'movmedian',round(10000/decim_fact));
plot(temp,depth,'*r',temp,depth_s,'-b')

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