def test_es_values():
image = Image([[1, 2], [2, 1]])
es_img = es(image)
k = 1 / (2 * (2**0.5))
res = np.array([[[k, k], [-k, k]], [[k, -k], [-k, -k]]])
assert_allclose(es_img.pixels, res)
image = Image([[0, 0], [0, 0]])
es_img = es(image)
res = np.array([[[np.nan, np.nan], [np.nan, np.nan]],
[[np.nan, np.nan], [np.nan, np.nan]]])
assert_allclose(es_img.pixels, res)
def test_es_values():
image = Image([[1, 2], [2, 1]])
es_img = es(image)
k = 1 / (2 * (2**0.5))
res = np.array([[[k, k], [-k, k]], [[k, -k], [-k, -k]]])
assert_allclose(es_img.pixels, res)
image = Image([[0, 0], [0, 0]])
es_img = es(image)
res = np.array([[[np.nan, np.nan], [np.nan, np.nan]],
[[np.nan, np.nan], [np.nan, np.nan]]])
assert_allclose(es_img.pixels, res)
def test_es_channels():
n_cases = 3
channels = np.random.randint(1, 10, [n_cases, 1])
for i in range(n_cases):
image = Image(np.random.randn(channels[i, 0], 40, 40))
es_img = es(image)
assert_allclose(es_img.shape, image.shape)
assert_allclose(es_img.n_channels, 2 * channels[i, 0])
def test_es_channels():
n_cases = 3
channels = np.random.randint(1, 10, [n_cases, 1])
for i in range(n_cases):
image = Image(np.random.randn(channels[i, 0], 40, 40))
es_img = es(image)
assert_allclose(es_img.shape, image.shape)
assert_allclose(es_img.n_channels, 2 * channels[i, 0])
def test_es_values():
image = Image([[1., 2.], [2., 1.]])
es_img = es(image)
k = 1.0 / (2 * (2 ** 0.5))
res = np.array([[[k, -k], [k, -k]], [[k, k], [-k, -k]]])
assert_allclose(es_img.pixels, res)
def test_es_values():
image = Image([[1., 2.], [2., 1.]])
es_img = es(image)
k = 1.0 / (2 * (2**0.5))
res = np.array([[[k, -k], [k, -k]], [[k, k], [-k, -k]]])
assert_allclose(es_img.pixels, res)
