def METHOD_NAME(self):
    """
    Here we construct a source of white noise.
    Then code tests that the average noise power in the real domain,
    is equivalent to the sum of the magnitudes squared
    of all frequency coefficients in the Fourier domain.
    These are calculated by WhiteNoiseEstimator and
    AnisotropicNoiseEstimator respectively.
    See Parseval/Plancherel's Theorem.
    """
    wht_noise = np.random.randn(1024, 128, 128).astype(self.dtype)
    src = ArrayImageSource(wht_noise)
    wht_noise_estimator = WhiteNoiseEstimator(src, batchSize=512)
    wht_noise_variance = wht_noise_estimator.estimate()
    noise_estimator = AnisotropicNoiseEstimator(src, batchSize=512)
    noise_variance = noise_estimator.estimate()
    self.assertTrue(np.allclose(noise_variance, wht_noise_variance))