def test_03_02_load_using_bioformats(self):
path = os.path.join(example_images_directory(), 'ExampleSBSImages',
'Channel1-01-A-01.tif')
data = F.load_using_bioformats(path, rescale=False)
expected_0_10_0_10 = np.array(
[[ 0, 7, 7, 6, 5, 8, 4, 2, 1, 2],
[ 0, 8, 8, 7, 6, 10, 4, 2, 2, 2],
[ 0, 9, 9, 7, 8, 8, 2, 1, 3, 2],
[ 0, 10, 9, 8, 10, 6, 2, 2, 3, 2],
[ 0, 10, 10, 10, 9, 4, 2, 2, 2, 2],
[ 0, 9, 9, 10, 8, 3, 2, 4, 2, 2],
[ 0, 9, 9, 10, 8, 2, 2, 4, 3, 2],
[ 0, 9, 8, 9, 7, 4, 2, 2, 2, 2],
[ 0, 10, 11, 9, 9, 4, 2, 2, 2, 2],
[ 0, 12, 13, 12, 9, 4, 2, 2, 2, 2]], dtype=np.uint8)
expected_n10_n10 = np.array(
[[2, 1, 1, 1, 2, 2, 1, 2, 1, 2],
[1, 2, 2, 2, 2, 1, 1, 1, 2, 1],
[1, 1, 1, 2, 1, 2, 2, 2, 2, 1],
[2, 2, 2, 2, 3, 2, 2, 2, 2, 1],
[1, 2, 2, 1, 1, 1, 1, 1, 2, 2],
[2, 1, 2, 2, 2, 1, 1, 2, 2, 2],
[2, 2, 3, 2, 2, 1, 2, 2, 2, 1],
[3, 3, 1, 2, 2, 2, 2, 3, 2, 2],
[3, 2, 2, 2, 2, 2, 2, 2, 3, 3],
[5, 2, 3, 3, 2, 2, 2, 3, 2, 2]], dtype=np.uint8)
self.assertTrue(np.all(expected_0_10_0_10 == data[:10,:10]))
self.assertTrue(np.all(expected_n10_n10 == data[-10:,-10:]))
def test_03_02_load_using_bioformats(self):
path = os.path.join(os.path.dirname(__file__), "Channel1-01-A-01.tif")
data = F.load_using_bioformats(path, rescale=False)
expected_0_10_0_10 = np.array(
[
[0, 7, 7, 6, 5, 8, 4, 2, 1, 2],
[0, 8, 8, 7, 6, 10, 4, 2, 2, 2],
[0, 9, 9, 7, 8, 8, 2, 1, 3, 2],
[0, 10, 9, 8, 10, 6, 2, 2, 3, 2],
[0, 10, 10, 10, 9, 4, 2, 2, 2, 2],
[0, 9, 9, 10, 8, 3, 2, 4, 2, 2],
[0, 9, 9, 10, 8, 2, 2, 4, 3, 2],
[0, 9, 8, 9, 7, 4, 2, 2, 2, 2],
[0, 10, 11, 9, 9, 4, 2, 2, 2, 2],
[0, 12, 13, 12, 9, 4, 2, 2, 2, 2],
],
dtype=np.uint8,
)
expected_n10_n10 = np.array(
[
[2, 1, 1, 1, 2, 2, 1, 2, 1, 2],
[1, 2, 2, 2, 2, 1, 1, 1, 2, 1],
[1, 1, 1, 2, 1, 2, 2, 2, 2, 1],
[2, 2, 2, 2, 3, 2, 2, 2, 2, 1],
[1, 2, 2, 1, 1, 1, 1, 1, 2, 2],
[2, 1, 2, 2, 2, 1, 1, 2, 2, 2],
[2, 2, 3, 2, 2, 1, 2, 2, 2, 1],
[3, 3, 1, 2, 2, 2, 2, 3, 2, 2],
[3, 2, 2, 2, 2, 2, 2, 2, 3, 3],
[5, 2, 3, 3, 2, 2, 2, 3, 2, 2],
],
dtype=np.uint8,
)
self.assertTrue(np.all(expected_0_10_0_10 == data[:10, :10]))
self.assertTrue(np.all(expected_n10_n10 == data[-10:, -10:]))
def test_03_02_load_using_bioformats(self):
path = os.path.join(example_images_directory(), 'ExampleSBSImages',
'Channel1-01-A-01.tif')
data = F.load_using_bioformats(path, rescale=False)
expected_0_10_0_10 = np.array(
[[ 0, 7, 7, 6, 5, 8, 4, 2, 1, 2],
[ 0, 8, 8, 7, 6, 10, 4, 2, 2, 2],
[ 0, 9, 9, 7, 8, 8, 2, 1, 3, 2],
[ 0, 10, 9, 8, 10, 6, 2, 2, 3, 2],
[ 0, 10, 10, 10, 9, 4, 2, 2, 2, 2],
[ 0, 9, 9, 10, 8, 3, 2, 4, 2, 2],
[ 0, 9, 9, 10, 8, 2, 2, 4, 3, 2],
[ 0, 9, 8, 9, 7, 4, 2, 2, 2, 2],
[ 0, 10, 11, 9, 9, 4, 2, 2, 2, 2],
[ 0, 12, 13, 12, 9, 4, 2, 2, 2, 2]], dtype=np.uint8)
expected_n10_n10 = np.array(
[[2, 1, 1, 1, 2, 2, 1, 2, 1, 2],
[1, 2, 2, 2, 2, 1, 1, 1, 2, 1],
[1, 1, 1, 2, 1, 2, 2, 2, 2, 1],
[2, 2, 2, 2, 3, 2, 2, 2, 2, 1],
[1, 2, 2, 1, 1, 1, 1, 1, 2, 2],
[2, 1, 2, 2, 2, 1, 1, 2, 2, 2],
[2, 2, 3, 2, 2, 1, 2, 2, 2, 1],
[3, 3, 1, 2, 2, 2, 2, 3, 2, 2],
[3, 2, 2, 2, 2, 2, 2, 2, 3, 3],
[5, 2, 3, 3, 2, 2, 2, 3, 2, 2]], dtype=np.uint8)
self.assertTrue(np.all(expected_0_10_0_10 == data[:10,:10]))
self.assertTrue(np.all(expected_n10_n10 == data[-10:,-10:]))
def test_01_03_write_color_tiff(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (9, 11, 3))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale = False)
np.testing.assert_array_equal(img, result)
def test_01_02_write_monchrome_16_bit__tiff(self):
r = np.random.RandomState()
r.seed(102)
img = r.randint(0, 4096, size=(21, 24))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT16)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_01_write_monochrome_8_bit_tif(self):
r = np.random.RandomState()
r.seed(101)
img = r.randint(0, 256, (11, 33)).astype(np.uint8)
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_03_write_color_tiff(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (9, 11, 3))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_02_write_monchrome_16_bit__tiff(self):
r = np.random.RandomState()
r.seed(102)
img = r.randint(0, 4096, size=(21, 24))
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT16)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_01_01_write_monochrome_8_bit_tif(self):
r = np.random.RandomState()
r.seed(101)
img = r.randint(0, 256, (11, 33)).astype(np.uint8)
path = self.get_tempfilename(".tif")
W.write_image(path, img, OME.PT_UINT8)
result = load_using_bioformats(path, rescale=False)
np.testing.assert_array_equal(img, result)
def test_02_01_write_movie(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (7, 23, 11))
path = self.get_tempfilename(".tif")
for i in range(img.shape[0]):
W.write_image(path, img[i], OME.PT_UINT8, t=i, size_t = img.shape[0])
for i in range(img.shape[0]):
result = load_using_bioformats(path, t=i, rescale = False)
np.testing.assert_array_equal(img[i], result)
def test_02_01_write_movie(self):
r = np.random.RandomState()
r.seed(103)
img = r.randint(0, 256, (7, 23, 11))
path = self.get_tempfilename(".tif")
for i in range(img.shape[0]):
W.write_image(path, img[i], OME.PT_UINT8, t=i, size_t=img.shape[0])
for i in range(img.shape[0]):
result = load_using_bioformats(path, t=i, rescale=False)
np.testing.assert_array_equal(img[i], result)
