Optimal methods for gridding 3D velocity-data?

Hi Jakob,

I followed your instructions to implement the code, if you run this code based on your modifications, you will be able to effectively interpolate and extrapolate velocities for the specified points within the 3D matrix A, enabling you to visualize and analyze the velocity distribution in a structured manner.

% Define the size of the matrix A A = zeros(800, 800, 180);

% Define the known points with coordinates (X,Y,Z) and velocities (U,V,W) % For demonstration purposes, let's assume 'points' is a 1500x6 matrix points = rand(1500, 6); % Random data, replace with actual data

% Interpolate and extrapolate velocities for all points within matrix A for i = 1:size(points, 1) x = points(i, 1); y = points(i, 2); z = points(i, 3); u = points(i, 4); v = points(i, 5); w = points(i, 6);

    % Perform linear interpolation to fill matrix A with velocity data
    x_idx = round(x);
    y_idx = round(y);
    z_idx = round(z);

    % Check if the indices are within the matrix bounds
    if x_idx >= 1 && x_idx <= size(A, 1) && y_idx >= 1 && y_idx <= size(A, 2) && z_idx >= 1 && z_idx <= size(A, 3)
        A(x_idx, y_idx, z_idx) = u; % Linear interpolation for velocity 'u'
    end
end

% Display the filled matrix A disp(A);

Please see attached results.