

@staticmethod
def generate_data_from_parameters(params, N, gen_seed=0):
    "\n        Generates data from a gaussina distribution\n        Inputs:\n            params: a dict with entries 'mu' and 'kappa'\n            N: number of data points\n        "
    if (type(N) is not int):
        raise TypeError('N should be an int')
    if (N <= 0):
        raise ValueError('N should be greater than 0')
    nprng = numpy.random.RandomState(gen_seed)
    check_model_params_dict(params)
    mu = params['mu']
    kappa = params['kappa']
    X = numpy.array([[(nprng.vonmises((mu - math.pi), kappa) + math.pi)] for i in range(N)])
    for x in X:
        if ((x < 0.0) or (x > (2.0 * math.pi))):
            pdb.set_trace()
    assert (len(X) == N)
    return X

dataset/ETHPy150Open probcomp/crosscat/src/tests/component_model_extensions/CyclicComponentModel.py p_CyclicComponentModel.generate_data_from_parameters/original