def test_li_camera_image():
    image = skimage.img_as_ubyte(data.camera())
    threshold = threshold_li(image)
    ce_actual = _cross_entropy(image, threshold)
    assert 62 < threshold_li(image) < 63
    assert ce_actual < _cross_entropy(image, threshold + 1)
    assert ce_actual < _cross_entropy(image, threshold - 1)

def test_li_coins_image():
    image = skimage.img_as_ubyte(data.coins())
    threshold = threshold_li(image)
    ce_actual = _cross_entropy(image, threshold)
    assert 94 < threshold_li(image) < 95
    assert ce_actual < _cross_entropy(image, threshold + 1)
    # in the case of the coins image, the minimum cross-entropy is achieved one
    # threshold below that found by the iterative method. Not sure why that is
    # but `threshold_li` does find the stationary point of the function (ie the
    # tolerance can be reduced arbitrarily but the exact same threshold is
    # found), so my guess some kind of histogram binning effect.
    assert ce_actual < _cross_entropy(image, threshold - 2)

def test_li_astro_image():
    image = skimage.img_as_ubyte(data.astronaut())
    threshold = threshold_li(image)
    ce_actual = _cross_entropy(image, threshold)
    assert 64 < threshold < 65
    assert ce_actual < _cross_entropy(image, threshold + 1)
    assert ce_actual < _cross_entropy(image, threshold - 1)

def test_li_coins_image_as_float():
    coins = skimage.img_as_float(data.coins())
    assert 0.37 < threshold_li(coins) < 0.38

def test_li_coins_image():
    coins = skimage.img_as_ubyte(data.coins())
    assert 95 < threshold_li(coins) < 97

def test_li_camera_image():
    camera = skimage.img_as_ubyte(data.camera())
    assert 63 < threshold_li(camera) < 65

 def test_li_constant_image(self):
     with pytest.raises(ValueError):
         threshold_li(np.ones((10,10)))

 def test_li_constant_image(self):
     assert threshold_li(np.ones((10, 10))) == 1.

 def test_li_negative_int(self):
     image = self.image - 2
     assert int(threshold_li(image)) == 0

def test_li_constant_image_with_nan():
    image = np.array([8, 8, 8, 8, np.nan])
    assert threshold_li(image) == 8

def test_li_inf_minus_inf():
    image = np.array([np.inf, -np.inf])
    assert threshold_li(image) == 0

def test_li_inf_image():
    image = np.array([np.inf, np.nan])
    assert threshold_li(image) == np.inf

def test_li_nan_image():
    image = np.full((5, 5), np.nan)
    assert np.isnan(threshold_li(image))

def test_li_coins_image_as_float():
    coins = skimage.img_as_float(data.coins())
    assert 94/255 < threshold_li(coins) < 95/255

def test_li_astro_image():
    img = skimage.img_as_ubyte(data.astronaut())
    assert 66 < threshold_li(img) < 68

 def test_li(self):
     assert int(threshold_li(self.image)) == 2

 def test_li(self):
     assert 2 < threshold_li(self.image) < 3

 def test_li_float_image(self):
     image = np.float64(self.image)
     assert 2 <= threshold_li(image) < 3

 def test_li_float_image(self):
     image = self.image.astype(float)
     assert 2 < threshold_li(image) < 3