

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