def test_int(self):
# test for uint8
im = np.zeros((2, 2), np.float)
im = Image(im)
nt.assert_array_almost_equal(im.int().image, np.zeros((2, 2),
np.uint8))
im = np.ones((2, 2), np.float)
im = Image(im)
nt.assert_array_almost_equal(im.int().image, 255 * np.ones(
(2, 2)).astype(np.uint8))
# tests for shape
im = np.random.randint(1, 255, (3, 5), int)
im = Image(im)
imi = im.int()
nt.assert_array_almost_equal(imi.shape, im.shape)
im = np.random.randint(1, 255, (3, 5, 3), int)
im = Image(im)
imi = im.int()
nt.assert_array_almost_equal(imi.shape, im.shape)
im = np.random.randint(1, 255, (3, 5, 3, 10), int)
im = Image(im)
imi = im.int()
nt.assert_array_almost_equal(imi.shape, im.shape)
def test_window(self):
im = np.array([[3, 5, 8, 10, 9], [7, 10, 3, 6, 3], [7, 4, 6, 2, 9],
[2, 6, 7, 2, 3], [2, 3, 9, 3, 10]])
im = Image(im)
se = np.ones((1, 1))
# se must be same number of dimensions as input image for scipy
# TODO maybe detect this in im.window and perform this line?
# test with different input formats
nt.assert_array_almost_equal(im.window(se, np.sum).image, im.image)
nt.assert_array_almost_equal(
im.int('uint8').window(se, np.sum).image, im.image)
nt.assert_array_almost_equal(
im.int('uint16').window(se, np.sum).image, im.image)
se = np.array([[1, 1, 1], [1, 0, 1], [1, 1, 1]])
out = np.array([[43, 47, 57, 56, 59], [46, 43, 51, 50, 57],
[45, 48, 40, 39, 31], [33, 40, 35, 49, 48],
[22, 40, 36, 53, 44]])
nt.assert_array_almost_equal(im.window(se, np.sum).image, out)
def test_morph1(self):
# test simple case
im = Image(np.array([[1, 2], [3, 4]]))
se = 1
nt.assert_array_almost_equal(im.morph(se, 'min').image, im.image)
nt.assert_array_almost_equal(im.morph(se, 'max').image, im.image)
nt.assert_array_almost_equal(
im.morph(se, oper='min', opt='replicate').image, im.image)
nt.assert_array_almost_equal(
im.morph(se, oper='min', opt='none').image, im.image)
# test different input formats
nt.assert_array_almost_equal(
im.int('uint8').morph(se, 'min').image, im.image)
nt.assert_array_almost_equal(
im.int('uint16').morph(se, 'min').image, im.image)
nt.assert_array_almost_equal(im.float().morph(se, 'min').image * 255,
im.image)
im = np.array([[1, 0, 1], [0, 1, 0], [1, 1, 0]])
im = Image(im.astype(bool))
nt.assert_array_almost_equal(im.morph(se, 'min').image, im.image)