L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

physo

physo

Use PhySO for symbolic regression, class symbolic regression, toolkit-level expression workflows, and benchmark problem loaders.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: physo description: "Use PhySO for symbolic regression, class symbolic regression, toolkit-level expression workflows, and benchmark problem loaders." read_when: "Use when the user names physo, PhySO, symbolic regression, ClassSR, toolkit expression helpers, or benchmark problem loaders." disable-model-invocation: true metadata: disco-role: operating license: MIT

PhySO

Use this skill when working with the physo package, the scientific Python symbolic-regression library.

Install and Import Check

Run scripts/physo_skill_doctor.py to confirm the installed package, key public exports, and the CPU scientific stack used by the verified baseline. The checked baseline was PhySO 1.2.0 on CPU; this skill does not claim CUDA verification. Import-time LaTeX warnings are expected when optional display tools are missing.

Route by Task

  • One dataset with X, y, units, y_weights, candidate_wrapper, run presets, logging, or Pareto inspection: use sub-skills/sr/SKILL.md.
  • Multiple realizations with shared class constants or realization-specific constants: use sub-skills/class-sr/SKILL.md.
  • Prefix expressions, libraries, tokens, Program/VectPrograms, random sampling, constant optimization, display, or result reloads: use sub-skills/toolkit/SKILL.md.
  • Feynman/Class benchmark problems, sample generation, metadata, or symbolic equivalence checks: use sub-skills/benchmarks/SKILL.md.

Shared References

Common Starting Points

  • Start with the doctor script when the environment or package import is uncertain.
  • Route to a sub-skill before drafting commands or code for a user workflow.
  • Use the sub-skill smoke scripts for route-specific tiny checks after the environment is known to be usable.
  • If the user asks for benchmark reproduction, training-scale sweeps, or maintainer jobfiles, stop at the boundary and keep this runtime skill focused on day-to-day package workflows.

Boundaries

This skill is self-contained. It does not depend on opening the source checkout at runtime, and it does not cover repo maintenance, release automation, or long benchmark campaigns.

Skills enregistrées