Summary and info Classes; Interface, navigation, bug fixes. #472
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* complete mathematical background and to to go further * mixture model * fit algorithm * estimate algorithm * convergence * add link for rhat
- Switch Sphinx theme to 'furo': cleaner interface - CSS Improvements: - Force white background on logos for visibility in dark mode. - Refactor example gallery to a simple bulleted list. - Add responsive styling for Pandas DataFrames (scrollable, dark mode colors). - JS: Disable hover tooltips on gallery links. - Makefile: Fix syntax error and improve doc build rule. - Dependencies: Update poetry.lock and pyproject.toml.
…erence styling for Sphinx docs Enhanced class and method separation with distinct vertical lines and highlight blocks Swapped primary and secondary colors for indentation and highlighting Reduced and tightened spacing between parameters, attributes, and returns for clarity Removed third-level indentation and unnecessary/old CSS rules Improved visibility and differentiation of important API sections Added bullet markers for parameter names Fixed alignment of vertical lines and highlight blocks for class/method headers Cleaned up and consolidated CSS for maintainability
- Suppress deprecation warnings in . - Update calls in examples to use - Fix warnings, update examples and improve logging - Fix initialization in plot_03_joint.py by adding . - Silence seed setting log and improve duration formatting precision in . - Update execution times: now we show 2 decimals to the second.
- Remove unused Dataset imports across examples - Fix PEP 8 import formatting (remove blank lines within import groups) - Simplify plot_02_parkinson patient_trajectories call - Add new data_summary.ipynb documenting Data and Dataset classes and link in quickstart
- Added `summary()` method to `BaseModel` to print a structured overview of model parameters.
- Displays metadata including features, sources, clusters, and fit metrics (e.g., log-likelihood).
- Categorizes parameters into Population, Individual (Random Effects), and Noise groups.
- Implemented smart formatting:
- Groups consecutive 1D parameters with shared axes.
- Aligns columns for 2D parameters.
- Sorts tables by column count to optimize layout.
- Added support for ANSI bold text and text wrapping for long lists.
- `model.summary()` now returns a feat: Enhance model summary with rich object and programmatic access Refactors `model.summary()` to return a new `Summary` data object instead of printing directly. This provides a richer, more interactive experience. Key changes: - `model.summary()` now returns a object. - The object auto-prints when not assigned to a variable, preserving the old fire-and-forget behavior. - When assigned (), it provides programmatic access to attributes. - A new method allows fetching any model parameter by name. - A method is included to guide users on available attributes (`summary.help()`). - now captures dataset and training metadata. - and now persist and restore this new metadata. - The method was also added to provide a quick overview of model configuration and data statistics.
…), the test failed. For now we will just skip testing the from the new keys in this test, TODO: create a separate test for summary() and info()
MendezSebastianP
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Here is the Readthedocs link if you want to check the changes in the page.
Changes in the documentations:
Examples gallerymake doc-quickimprove doc build rule: it builds faster, to use after building a first time.