Visualizing line plot with histogram density

I have multiples line plots which overlaps each other and I would like to plot my data something like the figure below to represent my data more quantitatively. Please assist me to plot this figure.

This is what I have so far.

% Generate sample data

numProfiles = 300; % Number of temperature profiles

numAltitudes = 101; % Number of altitude points (from 0km to 100km with 1km increment)

altitude = 0:1:100; % Altitude values in km

temperatures = zeros(numAltitudes, numProfiles);

% Generate temperatures with increased variation in specific altitude ranges

baseTemperature = 200 + altitude' * 3; % Base temperature profile

% Generate variations for each profile

for i = 1:numProfiles

variation = zeros(numAltitudes, 1);

% Add varying magnitudes of variation at different altitude points

for j = 1:numAltitudes

if altitude(j) < 20

variation(j) = randn * 50; % Large variation

elseif altitude(j) < 50

variation(j) = randn * 10; % Increased variation

elseif altitude(j) < 70

variation(j) = randn * 3; % Moderate variation

else

variation(j) = randn * 1; % Very small variation

end

end

temperatures(:, i) = baseTemperature + variation;

end

% Create histogram bins to get data density for each slice of altitude

nbins = 40;

bins = linspace( min(temperatures(:)), max(temperatures(:)), nbins );

hc = NaN(numAltitudes,nbins-1);

for i = 1:numAltitudes

hc(i,:) = histcounts(temperatures(i,:), bins);

end

% Get the centre value of each histogram bin

temps = (bins(1:end-1)+bins(2:end))/2;

% Get the x/y values as a mesh to plot the surface

[x,y] = meshgrid( temps, altitude );

% Plotting

figure;

subplot(1,2,1);

hold on;

colors = lines(numProfiles); % Generate a color map with distinct colors

for i = 1:numProfiles

plot(temperatures(:, i),altitude, 'Color', colors(i, :)); % Assign distinct color to each plot

end

% Customize the plot

ylabel('Altitude (km)');

xlabel('Temperature (K)');

grid on;

% Plot a surface with no edges, where the z-direction indicates density

% Viewed from "above", this will look like a heatmap

subplot(1,2,2);

surface(x, y, hc);

ylabel('Altitude (km)');

xlabel('Temperature (K)');

% Create a colour map which fades from white -> blue -> green -> yellow -> red

c = interp1( 1:5, [1,1,1; 0,0.5,1; 0.2,1,0.2; 1,1,0; 1,0,0], linspace(1,5,20) );

colormap(c);

colorbar;

My current figure looks something like this.

Answer 1

[Image Analyst]

Try this:

% Initialization steps.
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format short g;
format compact;
fontSize = 15;
fprintf('Beginning to run %s.m ...\n', mfilename);
% Generate sample data
numProfiles = 300;    % Number of temperature profiles
numAltitudes = 101;   % Number of altitude points (from 0km to 100km with 1km increment)
altitude = 0:1:100;   % Altitude values in km
temperatures = zeros(numAltitudes, numProfiles);
% Generate temperatures with increased variation in specific altitude ranges
baseTemperature = 200 + altitude' * 3;     % Base temperature profile
% Generate variations for each profile
for i = 1:numProfiles
    variation = zeros(numAltitudes, 1);
    % Add varying magnitudes of variation at different altitude points
    for j = 1:numAltitudes
        if altitude(j) < 20
            variation(j) = randn * 50;          % Large variation
        elseif altitude(j) < 50
            variation(j) = randn * 10;          % Increased variation
        elseif altitude(j) < 70
            variation(j) = randn * 3;           % Moderate variation
        else
            variation(j) = randn * 1;           % Very small variation
        end
    end
    temperatures(:, i) = baseTemperature + variation;
end
% Create histogram bins to get data density for each slice of altitude
nbins = 40;
bins = linspace( min(temperatures(:)), max(temperatures(:)), nbins );
hc = NaN(numAltitudes,nbins-1);
for i = 1:numAltitudes
    hc(i,:) = histcounts(temperatures(i,:), bins);
end
% Get the centre value of each histogram bin
temps = (bins(1:end-1)+bins(2:end))/2;
% Get the x/y values as a mesh to plot the surface
[x,y] = meshgrid( temps, altitude );
% Plotting
figure;
subplot(1,2,1);
hold on;
colors = lines(numProfiles);  % Generate a color map with distinct colors
for i = 1:numProfiles
    plot(temperatures(:, i),altitude, 'Color', colors(i, :)); % Assign distinct color to each plot
end
% Customize the plot
ylabel('Altitude (km)');
xlabel('Temperature (K)');
grid on;

% Get mean temperature
meanTemperature = mean(temperatures, 2)';
% Plot mean temperature over other plots.
hold on;
plot(meanTemperature, altitude, 'k-', 'LineWidth', 4);

% Plot a surface with no edges, where the z-direction indicates density
% Viewed from "above", this will look like a heatmap
subplot(1,2,2);
surface(x, y, hc);
ylabel('Altitude (km)');
xlabel('Temperature (K)');
% Create a colour map which fades from white -> blue -> green -> yellow -> red
c = interp1( 1:5, [1,1,1; 0,0.5,1; 0.2,1,0.2; 1,1,0; 1,0,0], linspace(1,5,20) );
colormap(c);
colorbar;
% Plot mean temperature over surface.
hold on;
plot(meanTemperature, altitude, 'k-', 'LineWidth', 4);

% Maximize window
g = gcf;
g.WindowState = 'maximized';