Plot contour3 of data consist x, y, phi

Hello,

I need guidance related to contour3 ploting of my data. I have a matrix contains as below data:

x y phi s

1 1 1 0

1 1 2 0

1 1 3 0

1 2 1 0

1 2 2 1

1 2 3 1

2 1 1 0

2 1 2 1

.....

which x varies from 1 to 4, y varies from 1 to 2, phi varies from 1 to 3 and s could have just 0 and 1 (my matrix is 689689 by 4, and this is just a sample of my data). I need to contour3 of my data for the rows which just s=1. So for first step I have to filter my data. The rest of my data which has x, y and phi in each row represents a point. I need to contour3 plot for each level of phi which contains lots of point in that level of phi. I tried to plot it but it create a contour3 for each point in each level (For example, I have more than 1000 points which has same phi so in each level of contour3 for a phi it creates 1000 contour3 around each point!). But I need a contour3 for more than 1000 point on each level. It would be great if you could guide me. Thanks.

Answer 1

[Namnendra]

Hi Foroogh,

I understand that you want to create a `contour3` plot for your data. To do this, you need to follow these steps:

1. Filter the Data: Extract the rows where `s = 1`.

2. Separate Data by `phi` Levels: For each unique value of `phi`, extract the corresponding `x`, `y`, and `s` values.

3. Create a Grid for Contouring: Use `x` and `y` to create a grid, and interpolate `s` values onto this grid.

4. Plot the Contours: Use the `contour3` function to plot the contours for each `phi` level.

Here is a step-by-step guide using MATLAB code:

Step 1: Filter the Data

Assuming your data is stored in a matrix `data`:

% Sample data matrix
data = [
    1  1  1  0;
    1  1  2  0;
    1  1  3  0;
    1  2  1  0;
    1  2  2  1;
    1  2  3  1;
    2  1  1  0;
    2  1  2  1;
    % ... (more data)
    ];

% Filter rows where s == 1
filteredData = data(data(:, 4) == 1, :);

Step 2: Separate Data by `phi` Levels

% Unique phi levels
phiLevels = unique(filteredData(:, 3));

% Initialize cell array to store data for each phi level
phiData = cell(length(phiLevels), 1);

for i = 1:length(phiLevels)
    phi = phiLevels(i);
    phiData{i} = filteredData(filteredData(:, 3) == phi, :);
end

Step 3: Create a Grid for Contouring

For each `phi` level, create a grid and interpolate `s` values:

% Define the grid resolution
gridResolution = 0.1; % Adjust as needed

[Xq, Yq] = meshgrid(min(data(:, 1)):gridResolution:max(data(:, 1)), ...
    min(data(:, 2)):gridResolution:max(data(:, 2)));

% Initialize cell array to store interpolated grids
interpolatedGrids = cell(length(phiLevels), 1);

for i = 1:length(phiLevels)
    phiPoints = phiData{i};
    X = phiPoints(:, 1);
    Y = phiPoints(:, 2);
    S = phiPoints(:, 4);
    
    % Interpolate s values onto the grid
    Sq = griddata(X, Y, S, Xq, Yq, 'natural');
    
    % Store the interpolated grid
    interpolatedGrids{i} = Sq;
end

Step 4: Plot the Contours

Use `contour3` to plot the contours for each `phi` level:

figure;
hold on;

for i = 1:length(phiLevels)
    phi = phiLevels(i);
    Sq = interpolatedGrids{i};
    
    % Plot contour3 for the current phi level
    contour3(Xq, Yq, Sq, 'DisplayName', ['phi = ', num2str(phi)]);
end

hold off;
xlabel('X');
ylabel('Y');
zlabel('S');
legend('show');
title('Contour3 Plot for Different Phi Levels');

Explanation

1. Filtering: The data is filtered to include only rows where `s = 1`.

2. Separation by `phi` Levels: The filtered data is separated into different groups based on the unique values of `phi`.

3. Grid Creation and Interpolation: For each `phi` level, a grid is created using `meshgrid`, and the `griddata` function is used to interpolate `s` values onto this grid.

4. Plotting: The `contour3` function is used to plot the contours for each `phi` level. The `DisplayName` property is used to label each contour plot with its corresponding `phi` value.

This approach ensures that you get a single contour plot for each `phi` level, rather than individual contours for each data point. Adjust the `gridResolution` as needed to get the desired level of detail in your contour plots.

I hope the above information helps you.

Thank you.