This commit introduces a resilient fallback mechanism for all third-party JavaScript libraries, ensuring the application remains functional even if local files are unavailable.
Previously, the application would fail to load if any of the JavaScript files in the `/vendor` directory were missing or failed to load. This change implements an "offline-first, online-fallback" strategy.
The implementation checks for the existence of each library's global object (e.g., `window.p5`) immediately after attempting to load the local script. If the object is not found, indicating a load failure, a new `<script>` tag is dynamically and asynchronously created and appended to the document's head. This new script then loads the library from its public CDN.
This approach was chosen after evaluating two other methods:
1. The `<script onerror="...">` attribute was found to be unreliable, as local development servers often return a 404 HTML page (with a `200 OK` status and `text/html` MIME type) instead of a network error, which does not trigger the `onerror` event.
2. Using `document.write()` was functional but generated numerous parser-blocking warnings in the browser console and is considered a poor practice for performance.
The final implementation is non-blocking and follows modern web development best practices, making the application significantly more resilient for both development and production environments.
2.) feat(visualization): Add advanced overlays and robust large-file streaming
This commit introduces several major features and critical bug fixes to the visualizer, significantly enhancing its analytical capabilities and performance.
The primary focus was on adding more detailed visualization overlays from the Kalman filter and implementing a robust solution for handling very large JSON files that were previously crashing the application.
### New Features
- **Covariance Ellipse Overlay:**
- A "Show Covariance" checkbox has been added to the UI.
- When enabled, the visualizer now draws the 95% confidence ellipse for each track's predicted position, derived from the `covarianceP` matrix. This provides a real-time view of the Kalman filter's positional uncertainty.
- **Predicted vs. Corrected Position Markers:**
- A "Show Predicted Position" checkbox has been added.
- This feature displays the filter's raw prediction (red cross) alongside the final corrected position (blue cross), making it easy to visualize the predict-correct cycle and analyze the filter's behavior during object acceleration or maneuvers.
### Bug Fixes & Performance Enhancements
- **Fix: Marker for Lost Tracks:**
- The main track marker (blue cross) now correctly disappears if its `correctedPosition` is null for a given frame. This provides a clear and intuitive visual cue that a track has been temporarily "lost" and is coasting on predictions alone.
- **Fix: Large JSON File Parsing (Streaming & Web Worker):**
- Resolved a critical "Maximum call stack size exceeded" error that occurred when loading JSON files larger than ~30MB.
- The entire file loading and parsing pipeline has been refactored to use a Web Worker. This moves the CPU-intensive parsing off the main UI thread, preventing the page from freezing.
- The worker streams the file and uses a lightweight parser (Clarinet.js) to build the data object, ensuring low memory usage and a responsive interface.
- **feat: Add Progress Bar for File Loading:**
- To provide feedback during the new streaming process, a progress bar is now displayed in the modal, showing the real-time progress of the file parsing operation.
RUSHIL AMBARISH KADU