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| title: Differ Hug | |
| emoji: 📊 | |
| colorFrom: gray | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 5.31.0 | |
| python_version: "3.11" | |
| app_file: app.py | |
| pinned: false | |
| # Differ Hug: ODE Research Platform | |
| An interactive platform for exploring and analyzing ordinary differential equations (ODEs), focused on gene regulatory systems and numerical diagnostics. | |
| ## Features | |
| ### ode System | |
| - **Gene Regulatory ODE System**: Cooperative sigmoidal activation model | |
| - **Numerical Integration**: High-precision DOP853 solver with RK45 fallback | |
| - **Initial Conditions**: Circular/sector-based ensembles with controllable center and radius | |
| ### Diagnostics & Metrics | |
| - **FTLE**: Finite-Time Lyapunov Exponent with R² reliability metric | |
| - **Hurst Exponent**: Rescaled range (R/S) analysis for time series | |
| - **Curvature Statistics**: Mean, median, std, p10, p90 of curvature radius | |
| - **Path Length**: Total arclength of trajectories | |
| - **Local Z-score**: Nearest-neighbor analysis of curvature metrics | |
| - **Anomaly Score**: Combined robust z-scores for outlying trajectories | |
| ### Visualization | |
| - **Phase Portrait**: Trajectories in phase space with annotations | |
| - **Time Series**: x(t) and y(t) evolution over time | |
| - **Shadowing Analysis**: Perturbation growth visualization | |
| - **Metrics Table**: Full diagnostic output with highlighting | |
| ## Requirements | |
| ``` | |
| gradio>=4.44.1 | |
| numpy>=1.24.0 | |
| scipy>=1.10.0 | |
| matplotlib>=3.7.0 | |
| pandas (optional for extended functionality) | |
| ``` | |
| ## Usage | |
| Run the application locally: | |
| ```bash | |
| python app.py | |
| ``` | |
| The app will be available at `http://localhost:7860` | |
| ## ODE System | |
| The gene regulatory system: | |
| $$ | |
| \begin{cases} | |
| \displaystyle \frac{dx}{dt} = \frac{K\,x^{1/\alpha}}{b^{1/\alpha} + x^{1/\alpha}} - \gamma_1\,x,\\[10pt] | |
| \displaystyle \frac{dy}{dt} = \frac{K\,y^{1/\alpha}}{b^{1/\alpha} + y^{1/\alpha}} - \gamma_2\,y. | |
| \end{cases} | |
| $$ | |
| ### Parameters | |
| - **alpha**: Controls sigmoid steepness (1/alpha = Hill coefficient) | |
| - **K**: Maximum activation rate | |
| - **b**: Half-activation constant | |
| - **gamma1, gamma2**: Decay rates | |
| ## Project Structure | |
| ``` | |
| differ-hug/ | |
| ├── app.py # Gradio UI entry point | |
| ├── differ_hug/ # Core computation package | |
| │ ├── __init__.py | |
| │ ├── compute.py # Numerical computation functions | |
| │ ├── plotting.py # Visualization functions | |
| │ ├── params.py # Parameter serialization | |
| │ └── docs.py # Documentation helpers | |
| └── differential_equations_streamlit_src/ # Original Streamlit code (archived) | |
| ``` | |
| ## Migration Notes | |
| This is a Gradio port of the original Streamlit implementation. Key changes: | |
| - Replaced `streamlit` with `gradio` | |
| - Separated computation logic from UI | |
| - Preserved all numerical diagnostics | |
| - Made torch-based neural network solvers optional | |
| ## Citation | |
| If you use this tool in your research, please cite: | |
| ```bibtex | |
| @software{differ_hug, | |
| author = {Krizhanovsky, Andrey}, | |
| title = {Differ Hug: ODE Research Platform}, | |
| url = {https://huggingface.co/spaces/componavt/differ-hug}, | |
| year = {2026} | |
| } | |
| ``` | |