def METHOD_NAME(self):
    # Tests distance function
    log_pdf = pints.toy.AnnulusLogPDF()
    samples = log_pdf.sample(100)
    d = list(map(lambda x: np.linalg.norm(x), samples))
    dist = (np.abs(np.var(d) - log_pdf.var_normed()) +
            np.abs(np.mean(d) - log_pdf.mean_normed()))
    self.assertEqual(log_pdf.distance(samples), dist)
    f = log_pdf
    self.assertTrue(f.distance(samples) > 0)
    x = np.ones((100, 4))
    self.assertRaises(ValueError, f.distance, x)
    x = np.ones((100, 6))
    self.assertRaises(ValueError, f.distance, x)
    x = np.ones((100, 5, 2))
    self.assertRaises(ValueError, f.distance, x)
    log_pdf = pints.toy.AnnulusLogPDF(5, 20, 3)
    samples = log_pdf.sample(100)
    d = list(map(lambda x: np.linalg.norm(x), samples))
    dist = (np.abs(np.var(d) - log_pdf.var_normed()) +
            np.abs(np.mean(d) - log_pdf.mean_normed()))
    self.assertEqual(log_pdf.distance(samples), dist)
    f = log_pdf
    self.assertTrue(f.distance(samples) > 0)
    x = np.ones((100, 4))
    self.assertRaises(ValueError, f.distance, x)
    x = np.ones((100, 6))
    self.assertRaises(ValueError, f.distance, x)
    x = np.ones((100, 5, 2))
    self.assertRaises(ValueError, f.distance, x)