How to change my y-axis?

I want to change my y-axis so in the below from 0 to 100, and why my result give me the square (like grid) in the middle

[Torsten]

I want to change my y-axis so in the below from 0 to 100

Your y-axis is from 0 to 100. Or do you want to reverse it such that 0 is at the bottom and 100 is at the top ?

x = 0:0.1:5;
y = 0:1:100;
f = x.'*y;
contourf(x,y,f.')
colorbar

[Samar]

Hello @cindyawati cindyawati,

Can you share your code snippet. It would be better if we want to know why the code gives the squares (like grid) in the middle.

[cindyawati cindyawati]

hello @Samar this is my code

% Hyperthermia Simulation with an Improved Biological Model
clear; clc; close all;

%% Parameter Model
alpha = 0.5;           % thermal conductivity (cm^2/s)
Q = 0.1;                 % hot source (W/cm^3)
r0 = 0.03;               % cancer growth (1/s)
beta = 0.02;             % temperature sensitivity
Topt = 37;               % temperarature for cancer growth (Celsius)
K = 1e6;                 % capacity of cancer
N0 = 1e4;                % amount of cancer at the begining
omega_b = 0.01;          % blood cooling (1/s)
T_blood = 37;            % temperatur of blood (Celsius)
death_threshold = 45;    % the boundary temperature above which cells die(Celsius)
death_rate = 0.05;       % The rate of cell death if the temperature is too high
time = 0:0.1:100;        % time simulation(second)
x = 0:0.1:5;            % spatial position (cm)
[X, T] = meshgrid(x, time); %  grid 2D

%% Temperature Initialization
T_t = zeros(length(time), length(x));   % temperature at t
T_t(:, 1) = T_blood;                    % temperature initial
%% Iteration Time for Temperature Distribution
for t = 2:length(time)
    for i = 2:length(x)-1
        % Equation of heat with cooling of blood
        T_t(t, i) = T_t(t-1, i) + alpha * (T_t(t-1, i+1) - 2 * T_t(t-1, i) + T_t(t-1, i-1)) ...
                    - omega_b * (T_t(t-1, i) - T_blood) + Q;
    end
    % Set boundary conditions
    T_t(t, 1) = T_t(t, 2);             % limit left
    T_t(t, end) = T_t(t, end-1);       % limit right
end

%% Tumor Growth Model
N = zeros(length(time), 1); % Number of tumor cells
N(1) = N0;                  % Initial cell number

for t = 2:length(time)
    % Tissue center temperature
    T_mid = T_t(t, ceil(length(x)/2));
    
    % Correction of tumor growth rate with temperature
    r_t = r0 * exp(-beta * (T_mid - Topt)^2);
    
    % If the temperature exceeds the threshold for cell death
    if T_mid > death_threshold
        r_t = r_t - death_rate;
    end
    
    % Tumor cell growth model
    N(t) = N(t-1) + r_t * N(t-1) * (1 - N(t-1)/K);
end

%% Plot result
figure;

% temperature distribution
subplot(1, 2, 1);
imagesc(x, time, T_t);
xlabel('Position (cm)');
ylabel('Time (s)');
title('Temperature Distribution in Tissue');
colorbar;
caxis([T_blood 45]);  % Range temperature
%colormap('hot');

% cancer growth
subplot(1, 2, 2);
plot(time, N, 'LineWidth', 2);
xlabel('Time (s)');
ylabel('Number of Tumor Cells');
title('Tumor Growth vs Time');

%grid on;

%% result
fprintf('Simulasi selesai. \n');

Simulasi selesai. 

fprintf('Jumlah sel tumor awal: %.2f\n', N0);

Jumlah sel tumor awal: 10000.00

fprintf('Jumlah sel tumor akhir: %.2f\n', N(end));

Jumlah sel tumor akhir: 0.00

fprintf('Suhu akhir di tengah jaringan: %.2f °C\n', T_t(end, ceil(length(x)/2)));

Suhu akhir di tengah jaringan: -18.68 °C

[cindyawati cindyawati]

hi @Torsten. Yes I want to reverse it such that 0 is at the bottom and 100 is at the top. Thank you

[Voss]

% Hyperthermia Simulation with an Improved Biological Model
clear; clc; close all;

%% Parameter Model
alpha = 0.5;           % thermal conductivity (cm^2/s)
Q = 0.1;                 % hot source (W/cm^3)
r0 = 0.03;               % cancer growth (1/s)
beta = 0.02;             % temperature sensitivity
Topt = 37;               % temperarature for cancer growth (Celsius)
K = 1e6;                 % capacity of cancer
N0 = 1e4;                % amount of cancer at the begining
omega_b = 0.01;          % blood cooling (1/s)
T_blood = 37;            % temperatur of blood (Celsius)
death_threshold = 45;    % the boundary temperature above which cells die(Celsius)
death_rate = 0.05;       % The rate of cell death if the temperature is too high
time = 0:0.1:100;        % time simulation(second)
x = 0:0.1:5;            % spatial position (cm)
[X, T] = meshgrid(x, time); %  grid 2D

%% Temperature Initialization
T_t = zeros(length(time), length(x));   % temperature at t
T_t(:, 1) = T_blood;                    % temperature initial
%% Iteration Time for Temperature Distribution
for t = 2:length(time)
    for i = 2:length(x)-1
        % Equation of heat with cooling of blood
        T_t(t, i) = T_t(t-1, i) + alpha * (T_t(t-1, i+1) - 2 * T_t(t-1, i) + T_t(t-1, i-1)) ...
                    - omega_b * (T_t(t-1, i) - T_blood) + Q;
    end
    % Set boundary conditions
    T_t(t, 1) = T_t(t, 2);             % limit left
    T_t(t, end) = T_t(t, end-1);       % limit right
end

%% Tumor Growth Model
N = zeros(length(time), 1); % Number of tumor cells
N(1) = N0;                  % Initial cell number

for t = 2:length(time)
    % Tissue center temperature
    T_mid = T_t(t, ceil(length(x)/2));
    
    % Correction of tumor growth rate with temperature
    r_t = r0 * exp(-beta * (T_mid - Topt)^2);
    
    % If the temperature exceeds the threshold for cell death
    if T_mid > death_threshold
        r_t = r_t - death_rate;
    end
    
    % Tumor cell growth model
    N(t) = N(t-1) + r_t * N(t-1) * (1 - N(t-1)/K);
end

%% Plot result
figure;

% temperature distribution
subplot(1, 2, 1);
imagesc(x, time, T_t);
set(gca, 'YDir', 'normal');
xlabel('Position (cm)');
ylabel('Time (s)');
title('Temperature Distribution in Tissue');
colorbar;
caxis([T_blood 45]);  % Range temperature
%colormap('hot');

% cancer growth
subplot(1, 2, 2);
plot(time, N, 'LineWidth', 2);
xlabel('Time (s)');
ylabel('Number of Tumor Cells');
title('Tumor Growth vs Time');

%grid on;

%% result
fprintf('Simulasi selesai. \n');

Simulasi selesai. 

fprintf('Jumlah sel tumor awal: %.2f\n', N0);

Jumlah sel tumor awal: 10000.00

fprintf('Jumlah sel tumor akhir: %.2f\n', N(end));

Jumlah sel tumor akhir: 0.00

fprintf('Suhu akhir di tengah jaringan: %.2f °C\n', T_t(end, ceil(length(x)/2)));

Suhu akhir di tengah jaringan: -18.68 °C

Answer 1

[Malay Agarwal]

Hi @cindyawati cindyawati,

To reverse the direction of the y-axis, you can use the following command:

set(gca, 'YDir', 'normal');

By default, the imagesc function changes the y-axis direction to "reverse", which is why 0 is at the top and 100 is at the bottom. The above command changes the direction back to "normal". I have attached your code with this modification. Here is the result:

tmp

Simulasi selesai. 
Jumlah sel tumor awal: 10000.00
Jumlah sel tumor akhir: 0.00
Suhu akhir di tengah jaringan: -18.68 °C

Refer to the following answer from MathWorks Support team for more details: https://www.mathworks.com/matlabcentral/answers/94170-how-can-i-reverse-the-y-axis-when-i-use-the-image-or-imagesc-function-to-display-an-image-in-matlab

Hope this helps!

[cindyawati cindyawati]

thank you @Malay Agarwal but if I use your code the y axis for tumor growth vs time graph is reverse again. I mean 0 in the top but 4 in the bottom. For temperature distribution graph the y axis is correct but no for tumor growth vs time graph

[Malay Agarwal]

You can call the command again for the second plot and it should reverse that as well.

[Voss]

Or just avoid calling

set(gca, 'YDir', 'reverse');

on the second subplot.

Answer 2

[Ishaan]

Hello @cindyawati cindyawati,

I understand that you intend to flip the y-axis ticks and fix the grid like pattern towards the (current) bottom of the plot. To reproduce the plot, I isolated the code snippet that generated the figure you provided.

alpha = 0.5; % thermal conductivity (cm^2/s) 
Q = 0.1; % hot source (W/cm^3) 
omega_b = 0.01; % blood cooling (1/s) 
T_blood = 37; % temperatur of blood (Celsius) 
time = 0:0.1:100; % time simulation(second) 
x = 0:0.1:5; % spatial position (cm) 
%% Temperature Initialization 
T_t = zeros(length(time), length(x)); % temperature at t 
T_t(:, 1) = T_blood; % temperature initial 
%% Iteration Time for Temperature Distribution 
for t = 2:length(time) 
    for i = 2:length(x)-1 
        % Equation of heat with cooling of blood 
        T_t(t, i) = T_t(t-1, i) + alpha * (T_t(t-1, i+1) - 2 * T_t(t-1, i) + T_t(t-1, i-1)) ... 
            - omega_b * (T_t(t-1, i) - T_blood) + Q; 
    end 
    % Set boundary conditions 
    T_t(t, 1) = T_t(t, 2); % limit left 
    T_t(t, end) = T_t(t, end-1); % limit right 
end 
imagesc(x, time, T_t); 
colorbar; 
caxis([T_blood 45]); % Range temperature 

Firstly, to change your y-axis order, you can flip the time variable like this.

time = 100:-0.1:0;

NOTE: This will flip the plot generated as well.

Alternatively, you can use the other methods mentioned to flip the y-axis.

Upon inspecting the image ”matrix (T_t)”, near the square (like grid) I notice that adjacent values have large differences.

T_t(970:979, 18:24) 

This is leading to the grid like output. I also noticed that the top row of `T_t` is initialized to 0 and is never modified in the loop.

Hence, you will need to cross-check the equation of heat with cooling of blood as that is generating the “T_t” matrix.

[cindyawati cindyawati]

thank you @Ishaan I already try but the image still like grid. I still confused why give like a grid. For y-axis its already solved

[Ishaan]

Hello @cindyawati cindyawati,

I suggest you to check some sections of the "T_t" matrix and verify if the values are as you expect. As the graph is plotted according to the matrix data.

To clarify, "T_t(412:414, 9:11)" is:

Notice that there is very less difference in adjacent values. This is the yellow area of the graph.

For the values in the bell bottom, the difference between adjacent values is large, "99.2591" and "-4.8532". Hence the grid like pattern of alternate blue and yellow values.