def predictive_probability_multistate(self, M_c, X_L_list, X_D_list, Y, Q): """Calculate probability of cells jointly taking values given a latent state. :param Y: A list of constraints to apply when querying. Each constraint is a triplet of (r,d,v): r is the row index, d is the column index and v is the value of the constraint :type Y: list of lists :param Q: A list of values to query. Each value is triplet of (r,d,v): r is the row index, d is the column index, and v is the value at which the density is evaluated. :type Q: list of lists :returns: float -- joint log probabilities of the values specified by Q """ return su.predictive_probability_multistate( M_c, X_L_list, X_D_list, Y, Q)
def predictive_probability_multistate(self, M_c, X_L_list, X_D_list, Y, Q): """Calculate the probability of cellS jointly taking values given a latent state :param M_c: The column metadata :type M_c: dict :param X_L_list: list of the latent variables associated with the latent state :type X_L_list: list of dict :param X_D_list: list of the particular cluster assignments of each row in each view :type X_D_list: list of list of lists :param Y: A list of constraints to apply when querying. Each constraint is a triplet of (r,d,v): r is the row index, d is the column index and v is the value of the constraint :type Y: list of lists :param Q: A list of values to query. Each value is triplet of (r,d,v): r is the row index, d is the column index, and v is the value at which the density is evaluated. :type Q: list of lists :returns: float -- joint log probabilities of the values specified by Q """ return su.predictive_probability_multistate(M_c, X_L_list, X_D_list, Y, Q)