# Copyright 2026 UCID Foundation
#
# Licensed under the EUPL, Version 1.2 (the "License");
# you may not use this file except in compliance with the License.
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#
#     https://joinup.ec.europa.eu/collection/eupl/eupl-text-eupl-12
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"""Transfer learning utilities for UCID prediction models.

This module provides functions for adapting models trained on one city's
data to work effectively on another city with limited training data.
"""

from typing import Any


def adapt_domains(source_model: Any, target_data: Any) -> Any:
    """Adapt a source model to a target domain.

    This is a stub implementation for domain adaptation. Full implementation
    would apply techniques like feature alignment, instance weighting, or
    fine-tuning to transfer knowledge from source to target domain.

    Args:
        source_model: Pre-trained model from source city/domain.
        target_data: Sample data from the target city/domain.

    Returns:
        The adapted model (currently returns source model unchanged).

    Note:
        This is a stub implementation. Future versions will support:
        - Feature alignment using MMD or CORAL
        - Instance weighting
        - Fine-tuning with target domain data
        - Multi-task learning across cities

    Example:
        >>> from ucid.ml.transfer import adapt_domains
        >>> target_data = load_target_city_data()
        >>> adapted_model = adapt_domains(pretrained_model, target_data)
    """
    del target_data  # Unused in stub
    return source_model
