docs(v2.0.0-alpha.3): inline plot injection across the entire doc tree
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.
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@@ -40,6 +40,16 @@ Generic interacting-agent simulator (`consensus_dynamics`) — linear bounded-co
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ax.set_title('Bounded-confidence consensus, α = 0.3')
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fig.tight_layout(); plt.show()
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.. AUTO-PLOT-BEGIN
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.. image:: ../_static/auto/algorithms__agent_based/block_03_fig_01.png
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:align: center
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:width: 80%
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.. AUTO-PLOT-END
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.. image:: ../_static/v2/agent_based/plot_01.png
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:align: center
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:width: 80%
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@@ -56,6 +66,16 @@ Generic interacting-agent simulator (`consensus_dynamics`) — linear bounded-co
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ax.set_title('Convergence rate vs averaging weight α'); ax.legend(); ax.grid(alpha=0.3)
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fig.tight_layout(); plt.show()
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.. AUTO-PLOT-BEGIN
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.. image:: ../_static/auto/algorithms__agent_based/block_04_fig_01.png
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:align: center
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:width: 80%
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.. AUTO-PLOT-END
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.. image:: ../_static/v2/agent_based/plot_02.png
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:align: center
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:width: 80%
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