Tutorial blm

[yomichi]

1. Fix misc.permutation_importance and blm.Model.permutation_importance

2. Added a tutorial how to use blm.Model

   • Thanks to @39lovemiku

3. Update of blm.Model.predict_sampling(X, N=n)

   • Fix a bug that N=1 returns N=X.shape[0] result
   • Becomes to return a (n, X.shape[0]) array instead of (X.shape[0], n) to achieve the consistency with gp.Model.predict_sampling(), which returns (n, X.shape[0])

[Copilot]

Pull request overview

This PR updates PHYSBO’s permutation-importance implementation to support models (notably BLM) whose get_post_fmean API takes only query points, and extends the Gaussian process tutorial notebooks to demonstrate building/using blm.Model.

Changes:

• Add query_only option to misc.get_permutation_importance() to support BLM-style get_post_fmean(X_query) calls.
• Update blm.Model.get_permutation_importance() to use query_only=True.
• Extend JP/EN GP tutorial notebooks with a new section demonstrating gp.export_blm() and basic BLM usage (including permutation importance).

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 3 comments.

File	Description
src/physbo/misc/permutation_importance.py	Adds query_only branch for BLM-style prediction API (but still has a critical MPI feature-splitting bug).
src/physbo/blm/core/_model.py	Routes BLM permutation importance through the updated helper with query_only=True.
docs/sphinx/manual/ja/source/notebook/tutorial_Gaussian_process.ipynb	Adds BLM tutorial section (includes very large stored outputs).
docs/sphinx/manual/en/source/notebook/tutorial_Gaussian_process.ipynb	Adds BLM tutorial section (includes very large stored outputs).

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[yomichi]

After seeing copilot's review, I find that blm.Model.predict_sampling(X) returns N x N matrix (N=X.shape[0]) while we expect an N x 1 matrix (vector)... I will fix it

[Copilot]

Pull request overview

Copilot reviewed 7 out of 7 changed files in this pull request and generated 2 comments.

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