Each of the eight v2.0 companion notebooks (10_bsde through
17_generative_calibration) now follows the mandatory pedagogical
sandwich structure:
PRE markdown : theorem / model / pivot equation / what the cell verifies
CODE cell : labelled prints + at least one matplotlib figure
POST markdown: expected result, graph reading, conclusion
Each notebook carries at least one concrete real-world example
(heat plate, inverted pendulum, opinion polarization, collective
decision, OU drift under Cauchy noise, mixture vs gaussian MMD, etc.)
Generator script: scripts/enrich_v2_notebooks.py
Doc plots refreshed via scripts/inject_doc_plots.py.
Add scripts/inject_doc_plots.py that scans every .md and .rst page under
docs/source/, executes each Python code-block in an isolated namespace
with a non-interactive matplotlib backend, captures every figure
produced, and inserts an inline image directive immediately after the
code-block. Markers AUTO-PLOT-BEGIN/END make the injection idempotent
on re-runs. Blocks that fail to execute or produce no figure are left
untouched.
Add a transparent __getattr__ fallback in python/optimizr/__init__.py
that forwards any unresolved top-level attribute to the compiled _core
extension. This lets all v1.x and v2.0 doc samples that use
'from optimizr import X' (estimate_ou_params_py, linear_bsde_constant_coeffs,
mmd_gaussian, ...) execute as written.
Augment the OU Parameter Estimation example
(docs/source/algorithms/optimal_control.md) with a two-panel
visualization (simulated path plus empirical/theoretical autocorrelation).
Net effect: 14 doc pages now display matplotlib plots inline directly
under the code that produced them -- including the OU page, point
processes, Grid Search, HMM, MCMC, plus the 8 v2.0 RST pages.
PyO3 abi3 bindings for the 13 v2.0.0 functions across 8 module groups:
bsde, pde, stochastic_control, optimal_control::quadratic_impact_control,
mean_field::mckean_vlasov, agent_based, inference, optimization.
8 executed companion notebooks under examples/notebooks/10_bsde.ipynb …
17_generative_calibration.ipynb (cell outputs and matplotlib figures
preserved as proof-of-work; verified against analytic ground truths).
8 Sphinx RST pages under docs/source/algorithms/{bsde,pde,stochastic_control,
quadratic_impact_control,mckean_vlasov,agent_based,robust_drift,
generative_calibration_hooks}.rst with .. math:: derivations and inline
.. image:: directives placed immediately after each .. code-block:: python
so each plot appears directly under the code that produced it.
18 PNG plot assets under docs/source/_static/v2/<group>/.
index.rst extended with a new 'v2.0 Generic Stochastic Control & PDE'
toctree caption.
Forbidden-vocabulary audit on new src/, docs/source/algorithms/ and
binding files: zero matches.
All previously stable APIs untouched; v2.0.0 is additive at the binding
level — no v1.x function signature was changed.
ThotDjehuty