import numpy as np


class ConditionalIntensityMatrix:
    """
    Abstracts the Conditional Intesity matrix of a node as aggregation of the state residence times vector
    and state transition matrix and the actual CIM matrix.

    :_state_residence_times: state residence times vector
    :_state_transition_matrix: the transitions count matrix
    :_cim: the actual cim of the node
    """
    def __init__(self, state_residence_times: np.array, state_transition_matrix: np.array):
        """
        Parameters:
            :_state_residence_times: state residence times vector
            :_state_transition_matrix: the transitions count matrix
        """
        self._state_residence_times = state_residence_times
        self._state_transition_matrix = state_transition_matrix
        self._cim = self.state_transition_matrix.astype(np.float64)

    def compute_cim_coefficients(self):
        """
        Compute the coefficients of the matrix _cim by using the following equality q_xx' = M[x, x'] / T[x]

        Parameters:
            void
        Returns:
            void
        """
        np.fill_diagonal(self._cim, self._cim.diagonal() * -1)
        self._cim = ((self._cim.T + 1) / (self._state_residence_times + 1)).T

    @property
    def state_residence_times(self) -> np.ndarray:
        return self._state_residence_times

    @property
    def state_transition_matrix(self) -> np.ndarray:
        return self._state_transition_matrix

    @property
    def cim(self) -> np.ndarray:
        return self._cim

    def __repr__(self):
        return 'CIM:\n' + str(self.cim)