creating spatial heat map in matlab for one variable with x,y coordinates

Hi @Supraja,

After going through your comments, the key steps involve calculating the distance between consecutive points, determining the time intervals, and then computing the velocity. Additionally, you need to visualize the velocity as a spatial heatmap to identify regions of velocity drop. I will suggest the following step by step approach that will help you accomplish your task. Use the Euclidean distance formula to compute the distance between consecutive points. If the time intervals are uniform, you can use a constant time value; otherwise, you will need to provide the time data. Velocity will be calculated as distance divided by time. Finally, use a heatmap to represent the velocity across the arena. Here is a complete MATLAB code that implements the above steps:

% Sample Data
x_coords = [117.415351867676, 117.722839355469, 118.030349731445, ...
          118.337844848633, 118.645355224609, 118.952865600586, ...
          119.260368347168, 119.567871093750, 119.875373840332];

y_coords = [2.01796388626099, 2.38077235221863, 2.74358034133911, ...
          3.10638880729675, 3.46919679641724, 3.83200550079346, ...
          4.19481325149536, 4.55762195587158, 4.92043018341064];

% Assuming uniform time intervals (e.g., 1 second)
time_interval = 1; % seconds

% Number of points
num_points = length(x_coords);

% Preallocate distance and velocity arrays
distances = zeros(num_points - 1, 1);
velocities = zeros(num_points - 1, 1);

% Calculate distances and velocities
for i = 1:num_points - 1
  % Calculate distance using Euclidean formula
  distances(i) = sqrt((x_coords(i+1) - x_coords(i))^2 + ...
                      (y_coords(i+1) - y_coords(i))^2);

    % Calculate velocity
    velocities(i) = distances(i) / time_interval;
  end

% Display the calculated velocities
disp('Calculated Velocities:');
disp(velocities);

% Create a heatmap of velocities
figure;
scatter(x_coords(1:end-1), y_coords(1:end-1), 100, velocities, 'filled');
colorbar;
title('Velocity Heatmap');
xlabel('X Coordinates');
ylabel('Y Coordinates');
axis equal;
grid on;

Please see attached.

My suggestions for best practices for future code development

Vectorization: Instead of using a for loop, consider vectorized operations for better performance, especially with large datasets. MATLAB is optimized for matrix operations.

Memory Management: Ensure that your data does not exceed MATLAB's memory limits. If you encounter memory issues, consider processing the data in smaller chunks.

Error Handling: Implement error handling to manage unexpected inputs or conditions gracefully.

By following the outlined steps and utilizing the provided code, you should be able to effectively analyze the velocity changes across the arena and identify regions of interest.

If you have further questions or need additional assistance, feel free to ask!