Motion of a square
3 Comments
Accepted Answer
0 Comments
More Answers (1)
Hi @Mattia ,
It seems that @Voss provided better suggestions. However, upon analyzing your code and going through your txt file data points, I finally decided to modify the code to execute it and expected the plot as you mentioned in your comments. Please see attached.
Now, please see my comments below regarding a detailed review of your code.
Data Importation
Your code begins by importing data from a specified text file using a custom function, importfile which reads the coordinates for four points, which are expected to be structured in eight columns (four for x-coordinates and four for y-coordinates).
Considerations
- Make sure that the file path is correct and accessible.
- Validate the format of the text file to confirm that it matches the expected structure (i.e., tab-delimited values).
Setting Up the Simulation Environment
figure; axis equal; grid on; xlim([-1000 3000]); ylim([-1000 2000]); hold on;
fill([-3000 3000 3000 -3000], [-3000 -3000 3000 3000], [0.4 0.4 0.4], 'EdgeColor', 'none');
This section of your code initializes a figure with specific axis limits and creates a gray background.
Considerations
- Adjust axis limits based on actual data ranges to ensure all points are visible.
- The fixed size of the gray area might need to be dynamic if your input data varies significantly.
Simulation Loop
The loop iterates through each frame of data, calculating the centroid and orientation of the square based on the four input points.
for i = 1:length(x1) centerX = (x1(i) + x2(i) + x3(i) + x4(i)) / 4; centerY = (y1(i) + y2(i) + y3(i) + y4(i)) / 4;
dx = x3(i) - x1(i); dy = y3(i) - y1(i); angle = atan2(dy, dx);
Key Operations
Centroid Calculation: This correctly averages the coordinates of the four points. Orientation Calculation: Using atan2 provides an accurate angle for rotation.
Square Construction
The vertices of the square are defined and rotated according to the calculated angle:
R = [cos(angle), -sin(angle); sin(angle), cos(angle)]; vertices = [-sideLength/2, -sideLength/2; sideLength/2, -sideLength/2; sideLength/2, sideLength/2; -sideLength/2, sideLength/2]'; rotatedVertices = R * vertices;
Considerations
- The sideLength is hard-coded; consider making it dynamic based on your application needs or parameters from your dataset.
Visualization Update
Each iteration updates the visualization by filling in the square and plotting the internal points:
fill(X, Y, [0 0 0], 'EdgeColor', 'none'); plot([x1(i), x2(i), x3(i), x4(i)], [y1(i), y2(i), y3(i), y4(i)], 'wo', ... 'MarkerSize', 4, 'MarkerFaceColor', 'w', 'MarkerEdgeColor', 'w');
Suggestions
- Consider using drawnow instead of pause for more responsive updates.
- Make sure that cla effectively clears only what is necessary to avoid flickering.
Now, if you consider working with large datasets or high frame rates, then I will suggest optimizing rendering performance by reducing graphical overhead or utilizing efficient plotting functions. Make sure to implement checks to handle cases where data may be missing or improperly formatted and add UI elements such as sliders or buttons for real-time adjustments during simulation.
Hope this helps. If you have any further questions or need clarification on specific sections, feel free to ask!
2 Comments
See Also
Categories
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!