Source code for BiMMSBM.core.exclusive_metadata

from .metadata_layer import metadata_layer



class exclusive_metadata(metadata_layer):
    """
    Class for handling exclusive metadata in a nodes layer.

    This class inherits from metadata_layer and adds functionality for handling
    exclusive metadata, where each node can only have one attribute from a set
    of possible attributes.

    

    Attributes
    ----------
    lambda_val : float
        Metadata visibility parameter
    meta_name : str
        Name of the metadata column in the node_layer class
    N_att : int
        Number of different categorical attributes of the metadata.
    dict_codes : dict
        A dictionary to store codes related to the metadata.
        Codes are integers ranged from 0 to N_att-1.
    links : 2D NumPy array
        Array representing links between nodes and metadata using its codes.
    qka : np.array
        Probability matrix between groups and attributes
    masks_att_list : list
        List of arrays of ints where the array number att has all the index positions of links that connects the attribute att

    Methods
    -------
    __len__()
        Returns the number of different categorical attributes.
    __str__()
        Returns the name of the metadata.

    """


    def __init__(self, lambda_val, meta_name):
        """
        Initialization of the exclusive_metadata class

        Parameters
        ----------
        lambda_val: float
            Metadata visibility
        meta_name: str
            Name of the metadata column in the node_layer class
        """
        super().__init__(lambda_val, meta_name)


    @property
    def qka(self):
        """
        Probability matrix between groups and attributes.

        Returns
        -------
        np.array
            Matrix of probabilities between groups and attributes
        """
        return self._qka

    @qka.setter
    def qka(self, qka):
        """
        Setter for the qka property.

        Parameters
        ----------
        qka : np.array
            Matrix of probabilities between groups and attributes

        Returns
        -------
        None
        """
        self._qka = qka