def test_13_05_extra_lines_skip_rows(self):
#
# Regression test of issue #1211 - extra line at end / blank lines
# Different code path from 13_04
#
path = os.path.join(example_images_directory(), "ExampleSBSImages")
file_names = ['Channel2-01-A-01.tif',
'Channel2-02-A-02.tif']
csv_text = '''"Image_FileName_DNA","Image_PathName_DNA"
"%s","%s"
"%s","%s"
''' % (file_names[0], path, file_names[1], path)
pipeline, module, filename = self.make_pipeline(csv_text)
try:
assert isinstance(module, L.LoadData)
m = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module, m, cpo.ObjectSet(),
m, cpi.ImageSetList())
module.wants_rows.value = True
module.row_range.min = 2
module.row_range.max = 3
self.assertTrue(module.prepare_run(workspace))
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertEqual(m.image_set_count, 1)
self.assertTrue('FileName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m[cpmeas.IMAGE, 'FileName_DNA', 1], file_names[0])
finally:
os.remove(filename)
def test_13_05_extra_lines_skip_rows(self):
#
# Regression test of issue #1211 - extra line at end / blank lines
# Different code path from 13_04
#
path = os.path.join(example_images_directory(), "ExampleSBSImages")
file_names = ['Channel2-01-A-01.tif',
'Channel2-02-A-02.tif']
csv_text = '''"Image_FileName_DNA","Image_PathName_DNA"
"%s","%s"
"%s","%s"
''' % (file_names[0], path, file_names[1], path)
pipeline, module, filename = self.make_pipeline(csv_text)
try:
assert isinstance(module, L.LoadData)
m = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module, m, cpo.ObjectSet(),
m, cpi.ImageSetList())
module.wants_rows.value = True
module.row_range.min = 2
module.row_range.max = 3
self.assertTrue(module.prepare_run(workspace))
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertEqual(m.image_set_count, 1)
self.assertTrue('FileName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m[cpmeas.IMAGE, 'FileName_DNA', 1], file_names[0])
finally:
os.remove(filename)
def test_13_04_extra_lines(self):
#
# Regression test of issue #1211 - extra line at end / blank lines
#
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
file_name = 'Channel2-01-A-01.tif'
csv_text = '''"Image_FileName_DNA","Image_PathName_DNA"
"%s","%s"
''' % (file_name, dir)
pipeline, module, filename = self.make_pipeline(csv_text)
try:
assert isinstance(module, L.LoadData)
m = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module, m, cpo.ObjectSet(), m,
cpi.ImageSetList())
self.assertTrue(module.prepare_run(workspace))
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertEqual(m.image_set_count, 1)
self.assertTrue(
'FileName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m[cpmeas.IMAGE, 'FileName_DNA', 1], file_name)
finally:
os.remove(filename)
def setUpClass(cls):
maybe_download_sbs()
cls.test_folder = "loaddata"
cls.test_path = os.path.join(
example_images_directory(), cls.test_folder)
cls.test_filename = "image.tif"
cls.test_shape = (13, 15)
path = maybe_download_example_image([cls.test_folder],
cls.test_filename,
shape=cls.test_shape)
with open(path, "rb") as fd:
cls.test_md5 = hashlib.md5(fd.read()).hexdigest()
def setUpClass(cls):
maybe_download_sbs()
cls.test_folder = "loaddata"
cls.test_path = os.path.join(
example_images_directory(), cls.test_folder)
cls.test_filename = "image.tif"
cls.test_shape = (13, 15)
path = maybe_download_example_image([cls.test_folder],
cls.test_filename,
shape=cls.test_shape)
with open(path, "rb") as fd:
cls.test_md5 = hashlib.md5(fd.read()).hexdigest()
def test_11_01_load_objects(self):
r = np.random.RandomState()
r.seed(1101)
labels = r.randint(0, 10, size=(30, 20)).astype(np.uint8)
handle, name = tempfile.mkstemp(".png")
write_image(name, labels, PT_UINT8)
os.close(handle)
png_path, png_file = os.path.split(name)
sbs_dir = os.path.join(example_images_directory(), "ExampleSBSImages")
csv_text = """%s_%s,%s_%s,%s_DNA,%s_DNA
%s,%s,Channel2-01-A-01.tif,%s
""" % (L.C_OBJECTS_FILE_NAME, OBJECTS_NAME,
L.C_OBJECTS_PATH_NAME, OBJECTS_NAME,
L.C_FILE_NAME, L.C_PATH_NAME,
png_file, png_path, sbs_dir)
pipeline, module, csv_name = self.make_pipeline(csv_text)
assert isinstance(pipeline, cpp.Pipeline)
assert isinstance(module, L.LoadData)
module.wants_images.value = True
try:
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(
pipeline, module, None, None, measurements, image_set_list)
pipeline.prepare_run(workspace)
key_names, g = pipeline.get_groupings(workspace)
self.assertEqual(len(g), 1)
module.prepare_group(workspace, g[0][0], g[0][1])
image_set = image_set_list.get_image_set(g[0][1][0] - 1)
object_set = cpo.ObjectSet()
workspace = cpw.Workspace(pipeline, module, image_set,
object_set, measurements, image_set_list)
module.run(workspace)
objects = object_set.get_objects(OBJECTS_NAME)
self.assertTrue(np.all(objects.segmented == labels))
self.assertEqual(measurements.get_current_image_measurement(
cellprofiler.measurement.FF_COUNT % OBJECTS_NAME), 9)
for feature in (cellprofiler.measurement.M_LOCATION_CENTER_X,
cellprofiler.measurement.M_LOCATION_CENTER_Y,
cellprofiler.measurement.M_NUMBER_OBJECT_NUMBER):
value = measurements.get_current_measurement(
OBJECTS_NAME, feature)
self.assertEqual(len(value), 9)
finally:
clear_image_reader_cache()
os.remove(name)
os.remove(csv_name)
def test_11_01_load_objects(self):
r = np.random.RandomState()
r.seed(1101)
labels = r.randint(0, 10, size=(30, 20)).astype(np.uint8)
handle, name = tempfile.mkstemp(".png")
write_image(name, labels, PT_UINT8)
os.close(handle)
png_path, png_file = os.path.split(name)
sbs_dir = os.path.join(example_images_directory(), "ExampleSBSImages")
csv_text = """%s_%s,%s_%s,%s_DNA,%s_DNA
%s,%s,Channel2-01-A-01.tif,%s
""" % (L.C_OBJECTS_FILE_NAME, OBJECTS_NAME,
L.C_OBJECTS_PATH_NAME, OBJECTS_NAME,
L.C_FILE_NAME, L.C_PATH_NAME,
png_file, png_path, sbs_dir)
pipeline, module, csv_name = self.make_pipeline(csv_text)
assert isinstance(pipeline, cpp.Pipeline)
assert isinstance(module, L.LoadData)
module.wants_images.value = True
try:
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(
pipeline, module, None, None, measurements, image_set_list)
pipeline.prepare_run(workspace)
key_names, g = pipeline.get_groupings(workspace)
self.assertEqual(len(g), 1)
module.prepare_group(workspace, g[0][0], g[0][1])
image_set = image_set_list.get_image_set(g[0][1][0] - 1)
object_set = cpo.ObjectSet()
workspace = cpw.Workspace(pipeline, module, image_set,
object_set, measurements, image_set_list)
module.run(workspace)
objects = object_set.get_objects(OBJECTS_NAME)
self.assertTrue(np.all(objects.segmented == labels))
self.assertEqual(measurements.get_current_image_measurement(
L.I.FF_COUNT % OBJECTS_NAME), 9)
for feature in (L.I.M_LOCATION_CENTER_X,
L.I.M_LOCATION_CENTER_Y,
L.I.M_NUMBER_OBJECT_NUMBER):
value = measurements.get_current_measurement(
OBJECTS_NAME, feature)
self.assertEqual(len(value), 9)
finally:
clear_image_reader_cache()
os.remove(name)
os.remove(csv_name)
def test_08_01_get_groupings(self):
'''Test the get_groupings method'''
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
pattern = 'Channel1-[0-9]{2}-(?P<ROW>[A-H])-(?P<COL>[0-9]{2})\\.tif'
csv_text = '"Image_FileName_Cytoplasm","Image_PathName_Cytoplasm","Metadata_ROW","Metadata_COL"\n'
for filename in os.listdir(dir):
match = re.match(pattern, filename)
if match:
csv_text += ('"%s","%s","%s","%s"\n' %
(filename, dir, match.group("ROW"),
match.group("COL")))
pipeline, module, filename = self.make_pipeline(csv_text)
self.assertTrue(isinstance(module, L.LoadText))
module.wants_images.value = True
module.wants_image_groupings.value = True
module.metadata_fields.value = "ROW"
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module, None,
None, measurements, image_set_list)
module.prepare_run(workspace)
keys, groupings = module.get_groupings(workspace)
self.assertEqual(len(keys), 1)
self.assertEqual(keys[0], "Metadata_ROW")
self.assertEqual(len(groupings), 8)
my_rows = [g[0]["Metadata_ROW"] for g in groupings]
my_rows.sort()
self.assertEqual(''.join(my_rows), 'ABCDEFGH')
for grouping in groupings:
row = grouping[0]["Metadata_ROW"]
module.prepare_group(cpw.Workspace(
pipeline, module, None, None, measurements, image_set_list),
grouping[0], grouping[1])
for image_number in grouping[1]:
image_set = image_set_list.get_image_set(image_number - 1)
measurements.next_image_set(image_number)
workspace = cpw.Workspace(pipeline, module, image_set,
cpo.ObjectSet(), measurements,
image_set_list)
module.run(workspace)
provider = image_set.get_image_provider("Cytoplasm")
match = re.search(pattern, provider.get_filename())
self.assertTrue(match)
self.assertEqual(row, match.group("ROW"))
def test_08_01_get_groupings(self):
'''Test the get_groupings method'''
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
pattern = 'Channel1-[0-9]{2}-(?P<ROW>[A-H])-(?P<COL>[0-9]{2})\\.tif'
csv_text = '"Image_FileName_Cytoplasm","Image_PathName_Cytoplasm","Metadata_ROW","Metadata_COL"\n'
for filename in os.listdir(dir):
match = re.match(pattern, filename)
if match:
csv_text += ('"%s","%s","%s","%s"\n' %
(filename, dir, match.group("ROW"),
match.group("COL")))
pipeline, module, filename = self.make_pipeline(csv_text)
self.assertTrue(isinstance(module, L.LoadText))
module.wants_images.value = True
module.wants_image_groupings.value = True
module.metadata_fields.value = "ROW"
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module, None,
None, measurements, image_set_list)
module.prepare_run(workspace)
keys, groupings = module.get_groupings(workspace)
self.assertEqual(len(keys), 1)
self.assertEqual(keys[0], "Metadata_ROW")
self.assertEqual(len(groupings), 8)
my_rows = [g[0]["Metadata_ROW"] for g in groupings]
my_rows.sort()
self.assertEqual(''.join(my_rows), 'ABCDEFGH')
for grouping in groupings:
row = grouping[0]["Metadata_ROW"]
module.prepare_group(cpw.Workspace(
pipeline, module, None, None, measurements, image_set_list),
grouping[0], grouping[1])
for image_number in grouping[1]:
image_set = image_set_list.get_image_set(image_number - 1)
measurements.next_image_set(image_number)
workspace = cpw.Workspace(pipeline, module, image_set,
cpo.ObjectSet(), measurements,
image_set_list)
module.run(workspace)
provider = image_set.get_image_provider("Cytoplasm")
match = re.search(pattern, provider.get_filename())
self.assertTrue(match)
self.assertEqual(row, match.group("ROW"))
def test_13_04_extra_lines(self):
#
# Regression test of issue #1211 - extra line at end / blank lines
#
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
file_name = 'Channel2-01-A-01.tif'
csv_text = '''"Image_FileName_DNA","Image_PathName_DNA"
"%s","%s"
''' % (file_name, dir)
pipeline, module, filename = self.make_pipeline(csv_text)
try:
assert isinstance(module, L.LoadData)
m = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, module, m, cpo.ObjectSet(),
m, cpi.ImageSetList())
self.assertTrue(module.prepare_run(workspace))
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertEqual(m.image_set_count, 1)
self.assertTrue('FileName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m[cpmeas.IMAGE, 'FileName_DNA', 1], file_name)
finally:
os.remove(filename)
def example_dir(self):
return example_images_directory()
def test_03_01_save_and_load(self):
"""Save a pipeline to batch data, open it to check and load it"""
data = ("eJztWW1PGkEQXhC1WtPYTzb9tB+llROoGiWNgi9NSYUSIbZGbbvCApvu7ZJ7"
"UWlj0o/9Wf1J/QndxTs4tsoBRS3JHbkcMzfPPDOzs8uxl8uU9jPbcFWLw1ym"
"FKsSimGBIqvKDT0FmbUEdwyMLFyBnKVgycYwY9dgIgET8dTqRmolCZPx+AYY"
"7ghlc0/EJf4cgClxfSTOsHNr0pFDnlPKRWxZhNXMSRABzxz9L3EeIoOgM4oP"
"EbWx2aFw9VlW5aVmo30rxys2xXmke43Fkbf1M2yY76su0LldIJeYFsk3rKTg"
"mh3gc2ISzhy841/Vtnm5pfDKOhTmOnUIKXWQdVnw6KX9W9Cxj9xQt6ce+3lH"
"JqxCzknFRhQSHdXaUbTGwcffRJe/CXAk0BKX9sHNK3HIs4QvrdjeJSpbUEdW"
"uS79rPv4mVb8SLmcOrGw3ugr/lAXPgRe9Zl3uAsXBnkO+sp7VolXyrscMm5B"
"28T91/02/lHgphSce7i4GdCJ0y/fOSVfKe9RE1/UsYE1TXP91H38rCh+pCzG"
"uYwpbRhcLlHGiWXY7OuJaCC9ISZ3q5NdqbhdzLZb+yH4hpmXy3I2ioVtGTFE"
"myYZxbwcdpzvu68eku8+cGmf/GZAdz9IeaeOGMM0ERtx3P30z24+c6d86jqc"
"uOP8Il18EdE/DP8L3w8fvnegezyl/Glxq/BaPljhTe1l9LOUPoj15YBfbB5n"
"YoXTqKvZ4dTW2eZxPLZx+j2xlLy6Ni4SgWwpozfmPUj8fuvhuhK/lGUMRxgZ"
"TmArV9GYVOU4s+qOLunodlGzo3mgeZMcxbwZir9p8QZFpj4C/kHnUfKO+YJ5"
"NJ7z6OPsYP8rxuV3NcAFuAAX4P43XNqD63c/pLUZUzO43YCEVXBjnPINcOON"
"S4OgXwPc8DipvO35Ut2/kfZfQO9+ewG6+03K3s04TW9topsa5ahyvYut7Yuv"
"Wc+Gdj/P52sKz9ptPOXWK5AzuU8tb5ja9TuRbal4Q1rvCNT6zdzA561DWHwW"
"pnvXXa13Zxx+bw3DFwn9zffYBxdxKidxP8Fg47zYw97NbVj7P/nFW+E=")
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.LoadExceptionEvent))
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
T.maybe_download_sbs()
for windows_mode in ((False,
True) if sys.platform.startswith("win") else
(False, )):
pipeline = cpp.Pipeline()
pipeline.add_listener(callback)
pipeline.load(StringIO(zlib.decompress(base64.b64decode(data))))
ipath = os.path.join(T.example_images_directory(),
"ExampleSBSImages")
bpath = tempfile.mkdtemp()
bfile = os.path.join(bpath, C.F_BATCH_DATA)
hfile = os.path.join(bpath, C.F_BATCH_DATA_H5)
try:
li = pipeline.modules()[0]
self.assertTrue(isinstance(li, LI.LoadImages))
module = pipeline.modules()[1]
self.assertTrue(isinstance(module, C.CreateBatchFiles))
li.location.dir_choice = cps.ABSOLUTE_FOLDER_NAME
li.location.custom_path = ipath
module.wants_default_output_directory.value = False
module.custom_output_directory.value = bpath
module.remote_host_is_windows.value = windows_mode
self.assertEqual(len(module.mappings), 1)
mapping = module.mappings[0]
mapping.local_directory.value = ipath
self.assertFalse(pipeline.in_batch_mode())
measurements = cpmeas.Measurements(mode="memory")
image_set_list = cpi.ImageSetList()
result = pipeline.prepare_run(
cpw.Workspace(pipeline, None, None, None, measurements,
image_set_list))
self.assertFalse(pipeline.in_batch_mode())
self.assertFalse(result)
self.assertFalse(module.batch_mode.value)
self.assertTrue(
measurements.has_feature(cpmeas.EXPERIMENT,
cpp.M_PIPELINE))
pipeline = cpp.Pipeline()
pipeline.add_listener(callback)
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements(mode="memory")
workspace = cpw.Workspace(pipeline, None, None, None,
cpmeas.Measurements(),
image_set_list)
workspace.load(hfile, True)
measurements = workspace.measurements
self.assertTrue(pipeline.in_batch_mode())
module = pipeline.modules()[1]
self.assertTrue(isinstance(module, C.CreateBatchFiles))
self.assertTrue(module.batch_mode.value)
image_numbers = measurements.get_image_numbers()
self.assertTrue(
[x == i + 1 for i, x in enumerate(image_numbers)])
pipeline.prepare_run(workspace)
pipeline.prepare_group(workspace, {}, list(range(1, 97)))
for i in range(96):
image_set = image_set_list.get_image_set(i)
for image_name in ("DNA", "Cytoplasm"):
pathname = measurements.get_measurement(
cpmeas.IMAGE, "PathName_" + image_name, i + 1)
self.assertEqual(
pathname,
"\\imaging\\analysis"
if windows_mode else "/imaging/analysis",
)
measurements.close()
finally:
if os.path.exists(bfile):
os.unlink(bfile)
if os.path.exists(hfile):
os.unlink(hfile)
os.rmdir(bpath)
def test_03_01_save_and_load(self):
'''Save a pipeline to batch data, open it to check and load it'''
data = ('eJztWW1PGkEQXhC1WtPYTzb9tB+llROoGiWNgi9NSYUSIbZGbbvCApvu7ZJ7'
'UWlj0o/9Wf1J/QndxTs4tsoBRS3JHbkcMzfPPDOzs8uxl8uU9jPbcFWLw1ym'
'FKsSimGBIqvKDT0FmbUEdwyMLFyBnKVgycYwY9dgIgET8dTqRmolCZPx+AYY'
'7ghlc0/EJf4cgClxfSTOsHNr0pFDnlPKRWxZhNXMSRABzxz9L3EeIoOgM4oP'
'EbWx2aFw9VlW5aVmo30rxys2xXmke43Fkbf1M2yY76su0LldIJeYFsk3rKTg'
'mh3gc2ISzhy841/Vtnm5pfDKOhTmOnUIKXWQdVnw6KX9W9Cxj9xQt6ce+3lH'
'JqxCzknFRhQSHdXaUbTGwcffRJe/CXAk0BKX9sHNK3HIs4QvrdjeJSpbUEdW'
'uS79rPv4mVb8SLmcOrGw3ugr/lAXPgRe9Zl3uAsXBnkO+sp7VolXyrscMm5B'
'28T91/02/lHgphSce7i4GdCJ0y/fOSVfKe9RE1/UsYE1TXP91H38rCh+pCzG'
'uYwpbRhcLlHGiWXY7OuJaCC9ISZ3q5NdqbhdzLZb+yH4hpmXy3I2ioVtGTFE'
'myYZxbwcdpzvu68eku8+cGmf/GZAdz9IeaeOGMM0ERtx3P30z24+c6d86jqc'
'uOP8Il18EdE/DP8L3w8fvnegezyl/Glxq/BaPljhTe1l9LOUPoj15YBfbB5n'
'YoXTqKvZ4dTW2eZxPLZx+j2xlLy6Ni4SgWwpozfmPUj8fuvhuhK/lGUMRxgZ'
'TmArV9GYVOU4s+qOLunodlGzo3mgeZMcxbwZir9p8QZFpj4C/kHnUfKO+YJ5'
'NJ7z6OPsYP8rxuV3NcAFuAAX4P43XNqD63c/pLUZUzO43YCEVXBjnPINcOON'
'S4OgXwPc8DipvO35Ut2/kfZfQO9+ewG6+03K3s04TW9topsa5ahyvYut7Yuv'
'Wc+Gdj/P52sKz9ptPOXWK5AzuU8tb5ja9TuRbal4Q1rvCNT6zdzA561DWHwW'
'pnvXXa13Zxx+bw3DFwn9zffYBxdxKidxP8Fg47zYw97NbVj7P/nFW+E=')
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.LoadExceptionEvent))
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
T.maybe_download_sbs()
for windows_mode in ((False, True) if sys.platform.startswith("win")
else (False,)):
pipeline = cpp.Pipeline()
pipeline.add_listener(callback)
pipeline.load(StringIO(zlib.decompress(base64.b64decode(data))))
ipath = os.path.join(T.example_images_directory(), 'ExampleSBSImages')
bpath = tempfile.mkdtemp()
bfile = os.path.join(bpath, C.F_BATCH_DATA)
hfile = os.path.join(bpath, C.F_BATCH_DATA_H5)
try:
li = pipeline.modules()[0]
self.assertTrue(isinstance(li, LI.LoadImages))
module = pipeline.modules()[1]
self.assertTrue(isinstance(module, C.CreateBatchFiles))
li.location.dir_choice = LI.ABSOLUTE_FOLDER_NAME
li.location.custom_path = ipath
module.wants_default_output_directory.value = False
module.custom_output_directory.value = bpath
module.remote_host_is_windows.value = windows_mode
self.assertEqual(len(module.mappings), 1)
mapping = module.mappings[0]
mapping.local_directory.value = ipath
self.assertFalse(pipeline.in_batch_mode())
measurements = cpmeas.Measurements(mode="memory")
image_set_list = cpi.ImageSetList()
result = pipeline.prepare_run(
cpw.Workspace(pipeline, None, None, None,
measurements, image_set_list))
self.assertFalse(pipeline.in_batch_mode())
self.assertFalse(result)
self.assertFalse(module.batch_mode.value)
self.assertTrue(measurements.has_feature(
cpmeas.EXPERIMENT, cpp.M_PIPELINE))
pipeline = cpp.Pipeline()
pipeline.add_listener(callback)
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements(mode="memory")
workspace = cpw.Workspace(pipeline, None, None, None,
cpmeas.Measurements(),
image_set_list)
workspace.load(hfile, True)
measurements = workspace.measurements
self.assertTrue(pipeline.in_batch_mode())
module = pipeline.modules()[1]
self.assertTrue(isinstance(module, C.CreateBatchFiles))
self.assertTrue(module.batch_mode.value)
image_numbers = measurements.get_image_numbers()
self.assertTrue([x == i + 1 for i, x in enumerate(image_numbers)])
pipeline.prepare_run(workspace)
pipeline.prepare_group(workspace, {}, range(1, 97))
for i in range(96):
image_set = image_set_list.get_image_set(i)
for image_name in ('DNA', 'Cytoplasm'):
pathname = measurements.get_measurement(
cpmeas.IMAGE, "PathName_" + image_name, i + 1)
self.assertEqual(pathname,
'\\imaging\\analysis' if windows_mode
else '/imaging/analysis')
measurements.close()
finally:
if os.path.exists(bfile):
os.unlink(bfile)
if os.path.exists(hfile):
os.unlink(hfile)
os.rmdir(bpath)
