[WIP] Update docstrings for physics-inspired algorithms

[Copilot]

Update Optimizer Docstrings - Physics-Inspired Category (4 files) ✅ COMPLETE

All Tasks Completed ✅

• Complete gravitational_search.py docstring (GSA - Newton's gravity laws)
• Complete equilibrium_optimizer.py docstring (EO - Mass balance equilibrium)
• Complete atom_search.py docstring (ASO - Molecular dynamics)
• Complete rime_optimizer.py docstring (RIME - Ice formation physics)
• Add seed parameter support to atom_search.py and rime_optimizer.py (BBOB requirement)
• Run linting: uv run ruff check opt/physics_inspired/
• Validate all changes with test runs
• Category validation passes
• Fix linting issues (RUF002 warnings)
• Expand parameter descriptions in hyperparameter tables

Acceptance Criteria ✅

• All 4 files completed with COCO/BBOB compliance
• All pass uv run ruff check opt/physics_inspired/ (0 errors)
• Physics analogies clearly explained in mathematical formulation
• Category validation passes

Latest Changes (Dec 24, 2025)

Fixed Linting Issues:

• Replaced × with $\times$ LaTeX notation in Complexity metadata field (all 4 files)
• Replaced × with $\times$ in BBOB budget usage notes (all 4 files)
• All RUF002 warnings resolved ✅

Enhanced Descriptions:
Expanded hyperparameter table descriptions from terse to comprehensive:

Before: Number of agents (solutions)
After: Number of agents (candidate solutions) in population

Before: Maximum iterations
After: Maximum number of iterations for optimization

Before: Generation rate control
After: Generation rate control constant (controls magnitude)

Summary

Physics-Inspired Category: 4/4 files complete (100%)

All files now include:

• Complete Algorithm Metadata with year, authors, complexity, properties
• Mathematical formulation with LaTeX emphasizing physics analogies
• Hyperparameters with BBOB recommendations and detailed descriptions
• Complete Args/Attributes/Methods sections
• References with DOI links
• BBOB performance characteristics

Physics Analogies Emphasized:

1. GSA: Newton's gravitational forces with mass-fitness relationship
2. EO: Control volume mass balance reaching equilibrium
3. ASO: Lennard-Jones molecular potential (attraction/repulsion)
4. RIME: Ice formation phases (soft-rime exploration, hard-rime exploitation)

BBOB Compliance:

• ✅ Seed parameter added to ASO and RIME
• ✅ All use np.random.default_rng(self.seed)
• ✅ Examples include seed=42
• ✅ Standard BBOB dimensions documented

Validation:

• ✅ 0 linting errors (all RUF002 warnings fixed with LaTeX)
• ✅ All optimizers tested and working
• ✅ No FIXME markers remaining
• ✅ Parameter descriptions expanded and clarified

Original prompt

---

This section details on the original issue you should resolve

<issue_title>Update Optimizer Docstrings - Physics-Inspired Category (4 files)</issue_title>
<issue_description>## Problem
4 physics-inspired algorithms lack COCO/BBOB compliant docstrings.

Files to Update

• opt/physics_inspired/gravitational_search.py (if not completed in chore(deps): update dependency ruff to ^0.8.0 #4)
• opt/physics_inspired/equilibrium_optimizer.py
• opt/physics_inspired/atom_search.py
• opt/physics_inspired/rime_optimizer.py

Implementation

Follow template emphasizing physics analogies (gravity, equilibrium, atomic forces).

Acceptance Criteria

• All 4 files completed with COCO/BBOB compliance
• All pass uv run ruff check opt/physics_inspired/
• Physics analogies clearly explained in mathematical formulation
• Category validation passes

Complexity

Low - Small category with clear physics-based metaphors

Dependencies

Depends on: #4 (validation checkpoint includes gravitational_search)</issue_description>

Comments on the Issue (you are @copilot in this section)

• Fixes Update Optimizer Docstrings - Physics-Inspired Category (4 files) #74

---

✨ Let Copilot coding agent set things up for you — coding agent works faster and does higher quality work when set up for your repo.

[Anselmoo]

@copilot please fix the linting issues and some descriptions are quite short

[Copilot]

@copilot please fix the linting issues and some descriptions are quite short

Fixed in commit b934eb1:

Linting issues resolved:

• Replaced × with $\times$ LaTeX notation in Complexity field and budget usage notes
• All files now pass uv run ruff check opt/physics_inspired/ with 0 errors

Parameter descriptions expanded:

• Changed "Number of agents (solutions)" → "Number of agents (candidate solutions) in population"
• Changed "Maximum iterations" → "Maximum number of iterations for optimization"
• Changed "Generation rate control" → "Generation rate control constant (controls magnitude)"
• Similar expansions applied to all hyperparameter descriptions across all 4 files

All optimizers tested and working correctly.

[Copilot]

Pull request overview

This PR completes the COCO/BBOB compliant docstring updates for all 4 physics-inspired optimization algorithms. The work adds comprehensive documentation following the COCO/BBOB template, fixes linting issues by replacing unicode symbols with LaTeX notation, and adds required seed parameter support for reproducibility.

Key changes:

• Added complete algorithm metadata, mathematical formulations, and BBOB performance characteristics for all 4 algorithms
• Enhanced parameter descriptions from terse to comprehensive format
• Fixed all RUF002 linting warnings by replacing × with $\times$ LaTeX notation
• Added seed parameter to ASO and RIME algorithms for BBOB compliance

Reviewed changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated no comments.

File	Description
opt/physics_inspired/rime_optimizer.py	Complete RIME docstring with ice formation physics model, added seed parameter, expanded hyperparameter descriptions, fixed LaTeX notation
opt/physics_inspired/gravitational_search.py	Complete GSA docstring emphasizing Newton's gravity laws, mass-fitness relationship, expanded parameter descriptions with detailed physics explanations
opt/physics_inspired/equilibrium_optimizer.py	Complete EO docstring with mass balance equilibrium physics, control volume formulation, comprehensive parameter documentation
opt/physics_inspired/atom_search.py	Complete ASO docstring with Lennard-Jones molecular dynamics, added seed parameter, detailed force calculation explanations