about.py

import os
from huggingface_hub import HfApi

PROBLEM_TYPES = ["unconditional", "conditional"]
TOKEN = os.environ.get("HF_TOKEN")
CACHE_PATH=os.getenv("HF_HOME", ".")
API = HfApi(token=TOKEN)
organization="LeMaterial"
submissions_repo = f'{organization}/lemat-gen-bench-submissions'
results_repo = f'{organization}/lemat-genbench-results'

# Column display names mapping
COLUMN_DISPLAY_NAMES = {
    'model_name': 'Model',
    'n_structures': 'Total Structures',
    # Validity metrics
    'overall_valid_count': 'Valid',
    'charge_neutral_count': 'Charge Neutral',
    'distance_valid_count': 'Distance Valid',
    'plausibility_valid_count': 'Plausibility Valid',
    # Uniqueness and Novelty
    'unique_count': 'Unique',
    'novel_count': 'Novel',
    # Energy-based metrics
    'mean_formation_energy': 'Formation Energy (eV)',
    'formation_energy_std': 'Formation Energy Std',
    'stability_mean_above_hull': 'E Above Hull (eV)',
    'stability_std_e_above_hull': 'E Above Hull Std',
    'mean_relaxation_RMSD': 'Relaxation RMSD (Å)',
    'relaxation_RMSE_std': 'Relaxation RMSD Std',
    # Stability metrics
    'stable_count': 'Stable',
    'unique_in_stable_count': 'Unique in Stable',
    'sun_count': 'SUN',
    # Metastability metrics
    'metastable_count': 'Metastable',
    'unique_in_metastable_count': 'Unique in Metastable',
    'msun_count': 'MSUN',
    # Distribution metrics
    'JSDistance': 'JS Distance',
    'MMD': 'MMD',
    'FrechetDistance': 'FID',
    # Diversity metrics
    'element_diversity': 'Element Diversity',
    'space_group_diversity': 'Space Group Diversity',
    'site_diversity': 'Atomic Site Diversity',
    'physical_size_diversity': 'Crystal Size Diversity',
    # HHI metrics
    'hhi_production_mean': 'HHI Production',
    'hhi_reserve_mean': 'HHI Reserve',
    'hhi_combined_mean': 'HHI Combined',
}

# Metrics that can be shown as percentages (count-based metrics)
COUNT_BASED_METRICS = [
    'overall_valid_count',
    'charge_neutral_count',
    'distance_valid_count',
    'plausibility_valid_count',
    'unique_count',
    'novel_count',
    'stable_count',
    'unique_in_stable_count',
    'sun_count',
    'metastable_count',
    'unique_in_metastable_count',
    'msun_count',
]

# Metric groups for organized display
METRIC_GROUPS = {
    'Validity ↑': [
        'overall_valid_count',
        'charge_neutral_count',
        'distance_valid_count',
        'plausibility_valid_count',
    ],
    'Uniqueness & Novelty ↑': [
        'unique_count',
        'novel_count',
    ],
    'Energy Metrics ↓': [
        'stability_mean_above_hull',
        'stability_std_e_above_hull',
        'mean_formation_energy',
        'formation_energy_std',
        'mean_relaxation_RMSD',
        'relaxation_RMSE_std',
    ],
    'Stability ↑': [
        'stable_count',
        'unique_in_stable_count',
        'sun_count',
    ],
    'Metastability ↑': [
        'metastable_count',
        'unique_in_metastable_count',
        'msun_count',
    ],
    'Distribution ↓': [
        'JSDistance',
        'MMD',
        'FrechetDistance',
    ],
    'Diversity ↑': [
        'element_diversity',
        'space_group_diversity',
        'site_diversity',
        'physical_size_diversity',
    ],
    'HHI ↓': [
        'hhi_production_mean',
        'hhi_reserve_mean',
    ],
}

# Color coding for metric families (background colors with transparency)
METRIC_GROUP_COLORS = {
    'Validity ↑': 'rgba(33, 150, 243, 0.15)',           # Light blue with transparency
    'Uniqueness & Novelty ↑': 'rgba(156, 39, 176, 0.15)', # Light purple with transparency
    'Energy Metrics ↓': 'rgba(255, 152, 0, 0.15)',      # Light orange with transparency
    'Stability ↑': 'rgba(76, 175, 80, 0.15)',           # Light green with transparency
    'Metastability ↑': 'rgba(139, 195, 74, 0.15)',      # Light lime with transparency
    'Distribution ↓': 'rgba(233, 30, 99, 0.15)',        # Light pink with transparency
    'Diversity ↑': 'rgba(0, 188, 212, 0.15)',           # Light cyan with transparency
    'HHI ↓': 'rgba(255, 193, 7, 0.15)',                 # Light amber with transparency
}

# Map each column to its group for styling
def get_column_to_group_mapping():
    """Returns a dict mapping column names to their metric group."""
    col_to_group = {}
    for group_name, cols in METRIC_GROUPS.items():
        for col in cols:
            col_to_group[col] = group_name
    return col_to_group

COLUMN_TO_GROUP = get_column_to_group_mapping()

# Compact view columns (most important metrics visible without scrolling)
COMPACT_VIEW_COLUMNS = [
    'model_name',
    'overall_valid_count',
    'unique_count',
    'novel_count',
    'stable_count',
    'metastable_count',
    'sun_count',
    'msun_count',
    'stability_mean_above_hull',
    'mean_formation_energy',
    'mean_relaxation_RMSD',
]

# Full view columns (all metrics organized by groups)
FULL_VIEW_COLUMNS = ['model_name', 'n_structures']
for group_name, cols in METRIC_GROUPS.items():
    FULL_VIEW_COLUMNS.extend(cols)

# Default columns for backward compatibility
DEFAULT_COLUMNS = COMPACT_VIEW_COLUMNS