@staticmethod
    def log_likelihood(X, parameters):
        """
        Calculates the log likelihood of the data X given mean mu and precision
        kappa.
        Inputs:
            X: a column of data (numpy)
            parameters: a dict with the following keys
                mu: the Von Mises mean
                kappa: the precision of the Von Mises
        """
        check_data_type_column_data(X)
        check_model_params_dict(parameters)

        log_likelihood = numpy.sum(vonmises.logpdf(X-math.pi, parameters['mu']*math.pi, parameters['kappa']))

        return log_likelihood
dataset/ETHPy150Open probcomp/crosscat/src/tests/component_model_extensions/CyclicComponentModel.py/p_CyclicComponentModel.log_likelihood/operator `-` -> `*`