def METHOD_NAME(self):
    im_nuclei_stain_data = np.load(
        os.path.join(datastore.fetch('Easy1_nuclei_stain.npz')))
    im_nuclei_stain = im_nuclei_stain_data['Easy1_nuclei_stain']
    im_nuclei_fgnd_mask_data = np.load(
        os.path.join(datastore.fetch('Easy1_nuclei_fgnd_mask.npz')))
    im_nuclei_fgnd_mask = im_nuclei_fgnd_mask_data['Easy1_nuclei_fgnd_mask']
    sigma_min = 10.0 / np.sqrt(2.0)
    sigma_max = 40.0 / np.sqrt(2.0)
    im_dog_max, im_sigma_max = cdog(im_nuclei_stain,
                                    im_nuclei_fgnd_mask,
                                    sigma_min, sigma_max)
    im_dog_max_gtruth_data = np.load(
        os.path.join(datastore.fetch('Easy1_cdog_max.npz')))
    im_dog_max_gtruth = im_dog_max_gtruth_data['Easy1_cdog_max']
    assert_array_almost_equal_neighborhood_lines(im_dog_max, im_dog_max_gtruth, decimal=4)
    compare_maxima(im_dog_max, im_dog_max_gtruth)
    im_sigma_max_gtruth_data = np.load(
        os.path.join(datastore.fetch('Easy1_cdog_sigma_max.npz')))
    im_sigma_max_gtruth = im_sigma_max_gtruth_data['Easy1_cdog_sigma_max']
    assert_array_almost_equal_neighborhood_lines(im_sigma_max, im_sigma_max_gtruth, decimal=4)