Files
ETPlot/docs/METADATA_USAGE.md
T
Kylian Schmidt 72ebc5e103 feat: Implement metadata system and reorganize project structure
 Features:
- Add comprehensive metadata system with YAML/JSON support
- Implement hierarchical metadata inheritance from parent folders
- Support plot-specific metadata overrides
- Add metadata caching for performance optimization

🗂️ Code Organization:
- Move Python orchestration code to orchestration/ folder
- Move validation utilities to tests/ folder
- Move documentation to docs/ folder
- Separate metadata functionality into dedicated module

🔧 Infrastructure:
- Add automatic asset copying to web directory
- Fix asset path resolution for nested directories
- Update template to use dynamic asset paths
- Add MetadataConfig class with inheritance options

📚 Documentation:
- Add comprehensive metadata usage guide (METADATA_USAGE.md)
- Add implementation documentation (METADATA_IMPLEMENTATION.md)
- Include example metadata files in examples/
- Add metadata validation utility script

🐛 Bug Fixes:
- Fix breadcrumb navigation and JavaScript functionality
- Resolve asset path issues in nested directories
- Update template imports for modular CSS/JS structure

This commit introduces a flexible metadata system that allows users to add
rich metadata to plots and folders using YAML or JSON files, with full
hierarchical inheritance and plot-specific overrides. The project structure
is now better organized with clear separation of concerns.
2025-07-08 12:33:49 +02:00

3.6 KiB

Metadata System Documentation

Overview

The metadata system allows you to add flexible metadata to your plots and folders using YAML or JSON files. Metadata is inherited hierarchically from parent folders and can be overridden at any level.

File Structure

Folder Metadata

  • File names: meta.yaml, meta.yml, or meta.json
  • Location: Place in any folder containing plots
  • Scope: Applies to all plots in the folder and subfolders (unless overridden)

Plot-specific Metadata

  • File names: {plot_name}.yaml, {plot_name}.yml, or {plot_name}.json
  • Location: Place in the same folder as the plot PDF file
  • Scope: Applies only to the specific plot with the same name

Hierarchy and Inheritance

  1. Root folder: Start with folder metadata in your source directory
  2. Subfolders: Each subfolder can have its own meta.yaml that merges with parent metadata
  3. Plot-specific: Individual plots can have their own metadata files that override folder metadata

Example Usage

Folder Structure

analysis_results/
├── meta.yaml                 # Root folder metadata
├── signal/
│   ├── meta.yaml            # Signal-specific metadata
│   ├── mass_plot.pdf
│   └── mass_plot.yaml       # Plot-specific metadata
└── background/
    ├── meta.yaml            # Background-specific metadata
    └── qcd_plot.pdf

Example Metadata Fields

Common fields for folder metadata:

  • title: Folder title
  • description: Folder description
  • experiment: Experiment name (CMS, ATLAS, etc.)
  • dataset: Dataset identifier
  • analysis_type: Type of analysis
  • author: Author information
  • parameters: Analysis parameters
  • tags: Categorization tags

Common fields for plot metadata:

  • plot_type: Type of plot (histogram, scatter, etc.)
  • variables: Variable information (x_axis, y_axis, units)
  • selection: Selection criteria
  • statistics: Statistical information
  • display: Display options (highlight, featured, order_priority)

Configuration

The metadata system can be configured in config.yaml:

metadata:
  cache_enabled: true           # Enable metadata caching
  inherit_from_parent: true     # Enable hierarchical inheritance

Output

HTML Template

Metadata is available in the HTML template as:

  • folder_metadata: Current folder's resolved metadata
  • item.metadata: Individual plot metadata (in items loop)

Cache Files

  • meta_cache.json: Generated in each web directory
  • Contains resolved metadata for all plots in that directory
  • Used for performance optimization and debugging

Usage Tips

  1. Start simple: Begin with basic folder metadata and add complexity as needed
  2. Use inheritance: Put common metadata in parent folders to avoid repetition
  3. Override selectively: Use plot-specific metadata only when needed
  4. Consistent naming: Use consistent field names across your metadata files
  5. Validate format: Ensure YAML/JSON files are valid before running the generator

Integration with Templates

In your HTML templates, you can access metadata like:

<!-- Folder metadata -->
<h2>{{ folder_metadata.title }}</h2>
<p>{{ folder_metadata.description }}</p>

<!-- Plot metadata -->
{% for item in items %}
  <div class="plot-item">
    <h3>{{ item.name }}</h3>
    {% if item.metadata.plot_type %}
      <span class="plot-type">{{ item.metadata.plot_type }}</span>
    {% endif %}
    {% if item.metadata.tags %}
      <div class="tags">
        {% for tag in item.metadata.tags %}
          <span class="tag">{{ tag }}</span>
        {% endfor %}
      </div>
    {% endif %}
  </div>
{% endfor %}