def test_benford_correlation(self):
        # A test with list of random values
        np.random.seed(42)
        random_list = np.random.uniform(size=100)

        # Fibonacci series is known to match the Newcomb-Benford's Distribution
        fibonacci_list = [0, 1]
        for i in range(2, 200):
            fibonacci_list.append(fibonacci_list[i - 1] + fibonacci_list[i - 2])

        # A list of equally distributed digits (returns NaN)
        equal_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]

        # A list containing NaN
        list_with_nan = [
            1.354,
            0.058,
            0.055,
            0.99,
            3.15,
            np.nan,
            0.3,
            2.3,
            0,
            0.59,
            0.74,
        ]

        self.assertAlmostEqual(benford_correlation(random_list), 0.39458056)
        self.assertAlmostEqual(benford_correlation(fibonacci_list), 0.998003988)
        self.assertAlmostEqual(benford_correlation(list_with_nan), 0.10357511)
        self.assertIsNaN(benford_correlation(equal_list))