feat(web): add 3D ECG visualization with interactive effects #1148
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Summary of ChangesHello @engyashraf410-ux, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request introduces a novel web-based 3D ECG visualization tool, significantly enhancing how electrocardiogram data can be presented and interacted with. It provides an engaging and dynamic representation of heart activity, offering a more immersive analytical experience through interactive elements and animations. Highlights
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Code Review
This pull request introduces an impressive 3D ECG visualization application using Dash and Plotly. The interactive effects and animations are well-implemented. My review focuses on a critical security concern, a couple of potential runtime errors, and a refactoring suggestion to improve data consistency and efficiency. Overall, this is a great addition.
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| if __name__ == '__main__': | ||
| app.run_server(debug=True, host='0.0.0.0', port=8050) No newline at end of file |
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Running a Dash application with debug=True in a production environment is a significant security vulnerability. When debug mode is on, Dash exposes a web-based debugger that can be used to execute arbitrary Python code on the server. This should be set to False in production. For development, it's better to control this with an environment variable.
| app.run_server(debug=True, host='0.0.0.0', port=8050) | |
| app.run_server(debug=False, host='0.0.0.0', port=8050) |
| def create_frames(num_frames=50): | ||
| frames = [] | ||
| t, ecg = generate_ecg_data() |
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The generate_ecg_data() function is called inside create_frames() and also at the top level (line 45). This can lead to inconsistencies between the initial plot and the animation due to random noise. It's more efficient and consistent to generate the data once and pass it to this function.
After applying this suggestion, you'll also need to update the call on line 56 to frames=create_frames(t, ecg).
| def create_frames(num_frames=50): | |
| frames = [] | |
| t, ecg = generate_ecg_data() | |
| def create_frames(t, ecg, num_frames=50): | |
| frames = [] |
| pulse_scale = 1 + 0.3 * np.sin(2 * np.pi * i / num_frames) | ||
| x, y, z = create_3d_data(t, ecg, pulse_scale) | ||
| # Color gradient based on amplitude | ||
| colors = np.abs(y) * 255 / np.max(np.abs(y)) |
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This line has a potential division-by-zero error if np.max(np.abs(y)) is 0. This can happen if the ecg signal is all zeros, which would raise a RuntimeWarning and result in NaN values for colors. To prevent this, you can add a small epsilon to the denominator to ensure it's never zero.
| colors = np.abs(y) * 255 / np.max(np.abs(y)) | |
| colors = np.abs(y) * 255 / (np.max(np.abs(y)) + 1e-12) |
| # Initial figure | ||
| t, ecg = generate_ecg_data() | ||
| x, y, z = create_3d_data(t, ecg) | ||
| colors = np.abs(y) * 255 / np.max(np.abs(y)) |
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This line has a potential division-by-zero error if np.max(np.abs(y)) is 0. This can happen if the ecg signal is all zeros, which would raise a RuntimeWarning and result in NaN values for colors. To prevent this, you can add a small epsilon to the denominator to ensure it's never zero.
| colors = np.abs(y) * 255 / np.max(np.abs(y)) | |
| colors = np.abs(y) * 255 / (np.max(np.abs(y)) + 1e-12) |
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Description
This PR aims at adding this feature...
Proposed Changes
I changed the
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