def METHOD_NAME():
    cam = img_as_float(camera())
    data_signed = cam * 2. - 1.   # Same image, on range [-1, 1]
    amount = 0.15
    cam_noisy = random_noise(cam, rng=42, mode='pepper', amount=amount)
    peppermask = cam != cam_noisy
    # Ensure all changes are to 1.0
    assert_allclose(cam_noisy[peppermask], np.zeros(peppermask.sum()))
    # Ensure approximately correct amount of noise was added
    proportion = float(peppermask.sum()) / (cam.shape[0] * cam.shape[1])
    tolerance = 1e-2
    assert abs(amount - proportion) <= tolerance
    # Check to make sure pepper gets added properly to signed images
    orig_zeros = (data_signed == -1).sum()
    cam_noisy_signed = random_noise(data_signed, rng=42, mode='pepper',
                                    amount=.15)
    proportion = (float((cam_noisy_signed == -1).sum() - orig_zeros) /
                  (cam.shape[0] * cam.shape[1]))
    assert abs(amount - proportion) <= tolerance