"""
This module provides the main acceptance function used in ReCom Markov chains.
Dependencies:
- random: For random number generation for probabilistic acceptance.
Last Updated: 11 Jan 2024
"""
import random
from gerrychain.partition import Partition
[docs]def always_accept(partition: Partition) -> bool:
    return True 
[docs]def cut_edge_accept(partition: Partition) -> bool:
    """
    Always accepts the flip if the number of cut_edges increases.
    Otherwise, uses the Metropolis criterion to decide.
    :param partition: The current partition to accept a flip from.
    :type partition: Partition
    :returns: True if accepted, False to remain in place
    :rtype: bool
    """
    bound = 1.0
    if partition.parent is not None:
        bound = min(1, len(partition.parent["cut_edges"]) / len(partition["cut_edges"]))
    return random.random() < bound