def test_03_02_pipeline_preferences(self):
#
# Walk the worker up through pipelines and preferences.
#
self.awthread = self.AWThread(self.announce_addr)
self.awthread.start()
self.set_work_socket()
self.awthread.ex(self.awthread.aw.do_job,
cpanalysis.WorkReply(
image_set_numbers = [1],
worker_runs_post_group = False,
wants_dictionary = True))
#
# The worker should ask for the pipeline and preferences next.
#
req = self.awthread.recv(self.work_socket)
self.assertIsInstance(req, cpanalysis.PipelinePreferencesRequest)
self.assertEqual(req.analysis_id, self.analysis_id)
maybe_download_example_image(["ExampleSBSImages"],
"Channel1-01-A-01.tif")
maybe_download_example_image(["ExampleHT29"],
"AS_09125_050116030001_D03f00d0.tif")
input_dir = os.path.normcase(
os.path.join(example_images_directory(), "ExampleSBSImages"))
output_dir = os.path.normcase(
os.path.join(example_images_directory(), "ExampleHT29"))
cpprefs.set_default_image_directory(input_dir)
input_dir = cpprefs.get_default_image_directory()
cpprefs.set_default_output_directory(output_dir)
output_dir = cpprefs.get_default_output_directory()
preferences = {cpprefs.DEFAULT_IMAGE_DIRECTORY:
cpprefs.config_read(cpprefs.DEFAULT_IMAGE_DIRECTORY),
cpprefs.DEFAULT_OUTPUT_DIRECTORY:
cpprefs.config_read(cpprefs.DEFAULT_OUTPUT_DIRECTORY)}
cpprefs.set_default_image_directory(example_images_directory())
cpprefs.set_default_output_directory(example_images_directory())
rep = cpanalysis.Reply(
pipeline_blob = np.array(GOOD_PIPELINE),
preferences = preferences)
req.reply(rep)
#
# Get the next request so that we know the worker has
# processed the preferences.
#
req = self.awthread.recv(self.work_socket)
self.assertEqual(cpprefs.get_default_image_directory(),
input_dir)
self.assertEqual(cpprefs.get_default_output_directory(),
output_dir)
self.assertIn(self.analysis_id,
self.awthread.aw.pipelines_and_preferences)
pipe, prefs = self.awthread.aw.pipelines_and_preferences[
self.analysis_id]
self.assertEqual(len(pipe.modules()), 7)
#
# Cancel and check for exit
#
req.reply(cpanalysis.ServerExited())
self.assertRaises(cpp.CancelledException, self.awthread.ecute)
def test_13_01_load_filename(self):
#
# Load a file, only specifying the FileName in the CSV
#
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
file_name = 'Channel2-01-A-01.tif'
csv_text = '''"Image_FileName_DNA"
"%s"
'''% file_name
pipeline, module, filename = self.make_pipeline(csv_text)
assert isinstance(module, L.LoadData)
module.image_directory.dir_choice = cps.ABSOLUTE_FOLDER_NAME
module.image_directory.custom_path = dir
m = cpmeas.Measurements(mode="memory")
workspace = cpw.Workspace(pipeline, module, m, cpo.ObjectSet(),
m, cpi.ImageSetList())
self.assertTrue(module.prepare_run(workspace))
self.assertEqual(m.get_measurement(cpmeas.IMAGE, "FileName_DNA", 1),
file_name)
path = m.get_measurement(cpmeas.IMAGE, "PathName_DNA", 1)
self.assertEqual(path, dir)
self.assertEqual(m.get_measurement(cpmeas.IMAGE, "URL_DNA", 1),
L.pathname2url(os.path.join(dir, file_name)))
module.prepare_group(workspace, {}, [1])
module.run(workspace)
img = workspace.image_set.get_image("DNA", must_be_grayscale=True)
self.assertEqual(tuple(img.pixel_data.shape), (640, 640))
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_10_01_scaling(self):
'''Test loading an image scaled and unscaled'''
d = os.path.join(example_images_directory(), "ExampleSpecklesImages")
file_name = "1-162hrh2ax2.tif"
csv_text = ("Image_FileName_MyFile,Image_PathName_MyFile\n"
"%s,%s\n" % (file_name, d))
c0_image = []
for rescale in (False, True):
pipeline, module, filename = self.make_pipeline(csv_text)
try:
module.rescale.value = rescale
def callback(workspace):
imgset = workspace.image_set
image = imgset.get_image("MyFile")
pixels = image.pixel_data
c0_image.append(pixels.copy())
c0 = C0()
c0.callback = callback
c0.module_num = 2
pipeline.add_module(c0)
pipeline.run()
finally:
os.remove(filename)
unscaled, scaled = c0_image
np.testing.assert_almost_equal(unscaled * 65535. / 4095., scaled)
def test_01_06_get_temp_current_image(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
W.set_temp_current_image(ip)
ip_other = W.get_temp_current_image()
self.assertEqual(ip.getID(), ip_other.getID())
def test_03_01_read_tif(self):
path = os.path.join(example_images_directory(), 'ExampleSBSImages',
'Channel1-01-A-01.tif')
ImageReader = F.make_image_reader_class()
FormatTools = F.make_format_tools_class()
reader = ImageReader()
reader.setId(path)
data = reader.openBytes(0)
data.shape = (reader.getSizeY(), reader.getSizeX())
#
# Data as read by cellprofiler.modules.loadimages.load_using_PIL
#
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_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_10_01_scaling(self):
'''Test loading an image scaled and unscaled'''
d = os.path.join(example_images_directory(), "ExampleSpecklesImages")
file_name = "1-162hrh2ax2.tif"
csv_text = ("Image_FileName_MyFile,Image_PathName_MyFile\n"
"%s,%s\n" % (file_name, d))
c0_image = []
for rescale in (False, True):
pipeline, module, filename = self.make_pipeline(csv_text)
try:
module.rescale.value = rescale
def callback(workspace):
imgset = workspace.image_set
image = imgset.get_image("MyFile")
pixels = image.pixel_data
c0_image.append(pixels.copy())
c0 = C0()
c0.callback = callback
c0.module_num = 2
pipeline.add_module(c0)
pipeline.run()
finally:
os.remove(filename)
unscaled, scaled = c0_image
np.testing.assert_almost_equal(unscaled * 65535. / 4095., scaled)
def test_01_03_get_image_by_id(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
ip.show()
ip_other = W.get_image_by_id(ip.getID())
self.assertEqual(ip_other.getID(), ip.getID())
def test_04_01_load_file(self):
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)
c0_ran = [False]
def callback(workspace):
imgset = workspace.image_set
image = imgset.get_image("DNA")
pixels = image.pixel_data
self.assertEqual(pixels.shape[0],640)
c0_ran[0] = True
c0 = C0()
c0.callback = callback
c0.module_num = 2
pipeline.add_module(c0)
try:
m = pipeline.run()
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertTrue(c0_ran[0])
hexdigest = m.get_current_image_measurement('MD5Digest_DNA')
self.assertEqual(hexdigest, "67880f6269fbf438d4b9c92256aa1d8f")
self.assertTrue('PathName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('PathName_DNA'),
dir)
self.assertTrue('FileName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('FileName_DNA'),
file_name)
finally:
os.remove(filename)
def setUpClass(self):
from cellprofiler.modules.tests import \
example_images_directory, maybe_download_example_image
self.root_dir = example_images_directory()
self.file_name = maybe_download_example_image(["ExampleSBSImages"],
"Channel1-01-A-01.tif")
J.attach()
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_01_03_get_image_by_id(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
ip.show()
ip_other = W.get_image_by_id(ip.getID())
self.assertEqual(ip_other.getID(), ip.getID())
def setUpClass(self):
from cellprofiler.modules.tests import \
example_images_directory, maybe_download_example_image
self.root_dir = example_images_directory()
self.file_name = maybe_download_example_image(
["ExampleSBSImages"], "Channel1-01-A-01.tif")
J.attach()
def test_01_06_get_temp_current_image(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
W.set_temp_current_image(ip)
ip_other = W.get_temp_current_image()
self.assertEqual(ip.getID(), ip_other.getID())
def test_01_02_get_id_list(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
W.set_current_image(ip)
id_list = W.get_id_list()
self.assertTrue(ip.getID() in id_list)
def test_02_01_load_one(self):
path = os.path.join(example_images_directory(), "ExampleSpecklesImages")
cpprefs.set_default_image_directory(path)
file_name = "1-162hrh2ax2.tif"
workspace, module = self.make_workspace([file_name])
assert isinstance(module, L.LoadSingleImage)
module.prepare_run(workspace)
module.run(workspace)
m = workspace.measurements
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertEqual(m.image_set_count, 1)
f = m.get_all_measurements(cpmeas.IMAGE,
"_".join((L.C_FILE_NAME, self.get_image_name(0))))
self.assertEqual(len(f), 1)
self.assertEqual(f[0], file_name)
p = m.get_all_measurements(cpmeas.IMAGE,
"_".join((L.C_PATH_NAME, self.get_image_name(0))))
self.assertEqual(len(p), 1)
self.assertEqual(p[0], path)
s = m.get_all_measurements(cpmeas.IMAGE,
"_".join((L.C_SCALING, self.get_image_name(0))))
self.assertEqual(len(s), 1)
self.assertEqual(s[0], 4095)
md = m.get_all_measurements(cpmeas.IMAGE,
"_".join((L.C_MD5_DIGEST, self.get_image_name(0))))
self.assertEqual(len(md), 1)
md5 = hashlib.md5()
image = workspace.image_set.get_image(self.get_image_name(0))
md5.update(np.ascontiguousarray(image.pixel_data).data)
self.assertEqual(md5.hexdigest(), md[0])
def get_measurements_for_good_pipeline(nimages=1, group_numbers=None):
'''Get an appropriately initialized measurements structure for the good pipeline'''
path = os.path.join(example_images_directory(), "ExampleSBSImages")
m = cpmeas.Measurements()
if group_numbers is None:
group_numbers = [1] * nimages
group_indexes = [1]
last_group_number = group_numbers[0]
group_index = 1
for group_number in group_numbers:
if group_number == last_group_number:
group_index += 1
else:
group_index = 1
group_indexes.append(group_index)
for i in range(1, nimages + 1):
filename = ("Channel2-%02d-%s-%02d.tif" % (i, "ABCDEFGH"[int(
(i - 1) / 12)], ((i - 1) % 12) + 1))
url = pathname2url(os.path.join(path, filename))
m[cpmeas.IMAGE, cpmeas.C_FILE_NAME + "_DNA", i] = filename
m[cpmeas.IMAGE, cpmeas.C_PATH_NAME + "_DNA", i] = path
m[cpmeas.IMAGE, cpmeas.C_URL + "_DNA", i] = url
m[cpmeas.IMAGE, cpmeas.GROUP_NUMBER, i] = group_numbers[i - 1]
m[cpmeas.IMAGE, cpmeas.GROUP_INDEX, i] = group_indexes[i - 1]
pipeline = cpp.Pipeline()
pipeline.loadtxt(StringIO(GOOD_PIPELINE))
pipeline.write_pipeline_measurement(m)
return m
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 test_13_01_load_filename(self):
#
# Load a file, only specifying the FileName in the CSV
#
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
file_name = 'Channel2-01-A-01.tif'
csv_text = '''"Image_FileName_DNA"
"%s"
''' % file_name
pipeline, module, filename = self.make_pipeline(csv_text)
assert isinstance(module, L.LoadData)
module.image_directory.dir_choice = cps.ABSOLUTE_FOLDER_NAME
module.image_directory.custom_path = dir
m = cpmeas.Measurements(mode="memory")
workspace = cpw.Workspace(pipeline, module, m, cpo.ObjectSet(), m,
cpi.ImageSetList())
self.assertTrue(module.prepare_run(workspace))
self.assertEqual(m.get_measurement(cpmeas.IMAGE, "FileName_DNA", 1),
file_name)
path = m.get_measurement(cpmeas.IMAGE, "PathName_DNA", 1)
self.assertEqual(path, dir)
self.assertEqual(m.get_measurement(cpmeas.IMAGE, "URL_DNA", 1),
L.pathname2url(os.path.join(dir, file_name)))
module.prepare_group(workspace, {}, [1])
module.run(workspace)
img = workspace.image_set.get_image("DNA", must_be_grayscale=True)
self.assertEqual(tuple(img.pixel_data.shape), (640, 640))
def get_measurements_for_good_pipeline(nimages = 1,
group_numbers = None):
'''Get an appropriately initialized measurements structure for the good pipeline'''
path = os.path.join(example_images_directory(), "ExampleSBSImages")
m = cpmeas.Measurements()
if group_numbers is None:
group_numbers = [1] * nimages
group_indexes = [1]
last_group_number = group_numbers[0]
group_index = 1
for group_number in group_numbers:
if group_number == last_group_number:
group_index += 1
else:
group_index = 1
group_indexes.append(group_index)
for i in range(1, nimages+1):
filename = ("Channel2-%02d-%s-%02d.tif" %
(i, "ABCDEFGH"[int((i-1) / 12)], ((i-1) % 12) + 1))
url = pathname2url(os.path.join(path, filename))
m[cpmeas.IMAGE, cpmeas.C_FILE_NAME + "_DNA", i] = filename
m[cpmeas.IMAGE, cpmeas.C_PATH_NAME + "_DNA", i] = path
m[cpmeas.IMAGE, cpmeas.C_URL+"_DNA", i] = url
m[cpmeas.IMAGE, cpmeas.GROUP_NUMBER, i] = group_numbers[i-1]
m[cpmeas.IMAGE, cpmeas.GROUP_INDEX, i] = group_indexes[i-1]
pipeline = cpp.Pipeline()
pipeline.loadtxt(StringIO(GOOD_PIPELINE))
pipeline.write_pipeline_measurement(m)
return m
def setUpClass(cls):
from cellprofiler.modules.tests \
import example_images_directory, maybe_download_sbs
maybe_download_sbs()
cls.root_dir = example_images_directory()
J.attach()
def test_03_03_measurement_columns(self):
'''Check that results of get_measurement_columns match the actual column names output'''
data = 'eJztW91u2zYUph0naFqgSHexBesNd9d2iSA7SZcEQ2vPXjcPsRs0Xn8wbJgi0TEHWjQkKrU39N32GHuEXe4RJtqyJXFyJMuSJ6cSQEiH5seP5/DwHEqyWrXOWe0beCTJsFXr7HcxQfCcKKxLjf4pHFATD/dg3UAKQxqk+ilsUR3+YBFYPoDlw1P55PTgEFZk+QTEOArN1n37tHsMwJZ9vmOXovPTpiMXPIXLF4gxrF+Zm6AEdp36P+3yWjGwcknQa4VYyHQppvVNvUs7o8HspxbVLILaSt/b2D7aVv8SGebL7hTo/HyOh4hc4N+RoMK02St0jU1MdQfv9C/WzngpE3i5HXqfu3YoCHYo2eWhp563/x647UsBdnvgab/jyFjX8DXWLIVA3FeuZqPg/ckh/W34+tsAjXZtjDsOwW0J49ga21klCEfjLfjwBVBxxlsNwe0IvLx00JDtfztUVAb7ClN7SYw/DL8p4LlcR4SYEe0+T/9FcQcRcSUfrgSe7h3KUey9LejJ5Td24DDMHtKc+mX0jWPn5tnZj62IvKJ/v7NXR1y96yNGB0Qx+wvoPW99heGKPlwRtGk0vnm4MH3vCfpy+SUzLfgdoZcKmemblN3C4txnQj9cbqCuYhEGmzzIwQY2kMqoMVrKDxbFlSU58fi4JeCnxxS/7bFbNYQ36jzGyTOyJI+PvbJz4RlX2vEy6flbNF7aupfTjM/z9Et6nhaNH2U5Xnw/WlLvtOYnAHcUR7+nIJrf3wH++eFyvafoOiKVuPG0qTOkm5iNnPoo/dwV+uFyg0KdMmiZyO0nblyKmweT0n9RfjkgDiSpr+gv5Yi4uOtP9Os21VGaeSZoXl7wG03dvv1awk5fxbRT0P5oEX3fhvB9IejL5V+kJ/uPnp9//Yq+fyZ9+Xh8Xafk2U/y/snPf1Q+PF7ADnH3qUH5vvOeQtXeb5nOneAydumF8B8L/FzmdniHFMMxxOGHiWlaVGc91zjjuoYycmuSjGNx8uYbhK96/JnINX8AoKvz/HgR+y2RHyLls7h+E2THF9RAVwa1dG15vcP407q/Cto/xI3raeaDqPf7WdGvGjLOpPJBmnl6nfJB0vl8XeL/qvN+1uJEVtb7qvSTpaP/fZxpP39Jcj+2alxW9lFZm+e0909xcX/turiCgAt637RK+4xfTnEDDaL3E7Se6OVvSGVuR+uyLjzjhljX0CDF/tZlnd12XBWsZp1E7edjs9tt0TercTDXN8fluOzgwvYRnwD/uuIytRjBOvrPRiLN9b0jjIMXN35PRrFOds9a/Lxt+THHZQOXlfiS4/K4m+M+XlwV3Oznef7LcTkux+W424X7u+DixPcbXPa+N+ftf/XwBOWJJ8CfJ7isIkIGBuXfTRlSf/xxjykRqmiTr2ukM/uy6fnQhvMMQniqAk91Hg/WkM5wdzQwbDaL0b7CsCo1ndpzu7Y2reW8vRDeoPfzN/KaSKW6phijGefFtCYKX0Xgq8zj6yPFtAzE0JDZJ6k1ETsT0bWr10+2A/i88120pU8fPrh7k38B4Pcr19/+eR6Hb2OjWLgP/P/zuheCKwG/n4/9Gizm149uaD/VMavt/wXhfSus'
# alternate data: 1 image, 1 object, tex scale=3, gabor angles=6
# data = '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'
cpprefs.set_default_image_directory(
os.path.join(example_images_directory(), "ExampleSBSImages"))
fd = StringIO(zlib.decompress(base64.b64decode(data)))
pipeline = cpp.Pipeline()
pipeline.load(fd)
module = pipeline.modules()[3]
measurements = pipeline.run(image_set_end=1)
for x in module.get_measurement_columns(pipeline):
assert x[1] in measurements.get_feature_names(
x[0]
), '%s does not match any measurement output by pipeline' % (
str(x))
for obname in measurements.get_object_names():
for m in measurements.get_feature_names(obname):
if m.startswith(M.TEXTURE):
assert (
obname, m, 'float'
) in module.get_measurement_columns(
pipeline
), 'no entry matching %s in get_measurement_columns.' % (
(obname, m, 'float'))
def test_01_02_get_id_list(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
W.set_current_image(ip)
id_list = W.get_id_list()
self.assertTrue(ip.getID() in id_list)
def test_04_01_load_file(self):
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)
c0_ran = [False]
def callback(workspace):
imgset = workspace.image_set
image = imgset.get_image("DNA")
pixels = image.pixel_data
self.assertEqual(pixels.shape[0],640)
c0_ran[0] = True
c0 = C0()
c0.callback = callback
c0.module_num = 2
pipeline.add_module(c0)
try:
m = pipeline.run()
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertTrue(c0_ran[0])
hexdigest = m.get_current_image_measurement('MD5Digest_DNA')
self.assertEqual(hexdigest, "67880f6269fbf438d4b9c92256aa1d8f")
self.assertTrue('PathName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('PathName_DNA'),
dir)
self.assertTrue('FileName_DNA' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('FileName_DNA'),
file_name)
finally:
os.remove(filename)
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 setUpClass(cls):
from cellprofiler.modules.tests \
import example_images_directory, maybe_download_sbs
maybe_download_sbs()
cls.root_dir = example_images_directory()
J.attach()
def test_03_08_load_mask(self):
path = os.path.join(example_images_directory(), "ExampleSBSImages",
"Channel2-01-A-01.tif")
workspace = self.run_workspace(path, N.LOAD_AS_MASK)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (640, 640))
self.assertEqual(np.sum(~pixel_data), 627)
def test_03_03_initial_measurements(self):
#
# Walk to the initial measurements
#
self.awthread = self.AWThread(self.announce_addr)
self.awthread.start()
self.set_work_socket()
self.awthread.ex(
self.awthread.aw.do_job,
cpanalysis.WorkReply(image_set_numbers=[1],
worker_runs_post_group=False,
wants_dictionary=True))
#
# The worker should ask for the pipeline and preferences next.
#
req = self.awthread.recv(self.work_socket)
self.assertIsInstance(req, cpanalysis.PipelinePreferencesRequest)
self.assertEqual(req.analysis_id, self.analysis_id)
input_dir = os.path.join(example_images_directory(),
"ExampleSBSImages")
cpprefs.set_default_image_directory(input_dir)
preferences = {
cpprefs.DEFAULT_IMAGE_DIRECTORY:
cpprefs.config_read(cpprefs.DEFAULT_IMAGE_DIRECTORY)
}
rep = cpanalysis.Reply(pipeline_blob=np.array(GOOD_PIPELINE),
preferences=preferences)
req.reply(rep)
#
# The worker asks for the initial measurements.
#
req = self.awthread.recv(self.work_socket)
self.assertIsInstance(req, cpanalysis.InitialMeasurementsRequest)
self.assertEqual(req.analysis_id, self.analysis_id)
m = get_measurements_for_good_pipeline()
try:
req.reply(cpanalysis.Reply(buf=m.file_contents()))
req = self.awthread.recv(self.work_socket)
#
# Check that they were installed
#
self.assertIn(self.analysis_id,
self.awthread.aw.initial_measurements)
cm = self.awthread.aw.initial_measurements[self.analysis_id]
for object_name in m.get_object_names():
for feature_name in m.get_feature_names(object_name):
self.assertTrue(cm.has_feature(object_name, feature_name))
self.assertEqual(cm[object_name, feature_name, 1],
m[object_name, feature_name, 1])
#
# Cancel and check for exit
#
req.reply(cpanalysis.ServerExited())
self.assertRaises(cpaw.CancelledException, self.awthread.ecute)
finally:
m.close()
def test_03_05_load_color_as_monochrome(self):
path = os.path.join(example_images_directory(), "ExampleGrayToColor",
"AS_09125_050116030001_D03f00d0.tif")
workspace = self.run_workspace(path, N.LOAD_AS_GRAYSCALE_IMAGE)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (512, 512))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1))
def test_01_04_get_image_by_name(self):
file_name = os.path.join(example_images_directory(), "ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
title = W.make_unique_name("Whatever")
ip.setTitle(title)
self.assertEqual(ip.getTitle(), title)
ip.show()
ip_other = W.get_image_by_name(title)
self.assertEqual(ip_other.getID(), ip.getID())
def test_03_07_load_raw(self):
path = os.path.join(example_images_directory(),
"ExampleSpecklesImages", "1-162hrh2ax2.tif")
workspace = self.run_workspace(path, N.LOAD_AS_ILLUMINATION_FUNCTION)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (1000, 1200))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1. / 16.))
def test_03_08_load_mask(self):
path = os.path.join(example_images_directory(),
"ExampleSBSImages",
"Channel2-01-A-01.tif")
workspace = self.run_workspace(path, N.LOAD_AS_MASK)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (640, 640))
self.assertEqual(np.sum(~pixel_data), 627)
def test_03_03_initial_measurements(self):
#
# Walk to the initial measurements
#
self.awthread = self.AWThread(self.announce_addr)
self.awthread.start()
self.set_work_socket()
self.awthread.ex(self.awthread.aw.do_job,
cpanalysis.WorkReply(
image_set_numbers = [1],
worker_runs_post_group = False,
wants_dictionary = True))
#
# The worker should ask for the pipeline and preferences next.
#
req = self.awthread.recv(self.work_socket)
self.assertIsInstance(req, cpanalysis.PipelinePreferencesRequest)
self.assertEqual(req.analysis_id, self.analysis_id)
input_dir = os.path.join(example_images_directory(), "ExampleSBSImages")
cpprefs.set_default_image_directory(input_dir)
preferences = {cpprefs.DEFAULT_IMAGE_DIRECTORY:
cpprefs.config_read(cpprefs.DEFAULT_IMAGE_DIRECTORY) }
rep = cpanalysis.Reply(
pipeline_blob = np.array(GOOD_PIPELINE),
preferences = preferences)
req.reply(rep)
#
# The worker asks for the initial measurements.
#
req = self.awthread.recv(self.work_socket)
self.assertIsInstance(req, cpanalysis.InitialMeasurementsRequest)
self.assertEqual(req.analysis_id, self.analysis_id)
m = get_measurements_for_good_pipeline()
try:
req.reply(cpanalysis.Reply(buf = m.file_contents()))
req = self.awthread.recv(self.work_socket)
#
# Check that they were installed
#
self.assertIn(self.analysis_id,
self.awthread.aw.initial_measurements)
cm = self.awthread.aw.initial_measurements[self.analysis_id]
for object_name in m.get_object_names():
for feature_name in m.get_feature_names(object_name):
self.assertTrue(cm.has_feature(object_name, feature_name))
self.assertEqual(cm[object_name, feature_name, 1],
m[object_name, feature_name, 1])
#
# Cancel and check for exit
#
req.reply(cpanalysis.ServerExited())
self.assertRaises(cpaw.CancelledException, self.awthread.ecute)
finally:
m.close()
def test_03_05_load_color_as_monochrome(self):
path = os.path.join(example_images_directory(),
"ExampleGrayToColor",
"AS_09125_050116030001_D03f00d0.tif")
workspace = self.run_workspace(path, N.LOAD_AS_GRAYSCALE_IMAGE)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (512, 512))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1))
def test_03_07_load_raw(self):
path = os.path.join(example_images_directory(),
"ExampleSpecklesImages",
"1-162hrh2ax2.tif")
workspace = self.run_workspace(path, N.LOAD_AS_ILLUMINATION_FUNCTION)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (1000, 1200))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1. / 16.))
def test_01_04_get_image_by_name(self):
file_name = os.path.join(example_images_directory(),
"ExampleSBSImages", "Channel1-01-A-01.tif")
ip = I.load_imageplus(file_name)
title = W.make_unique_name("Whatever")
ip.setTitle(title)
self.assertEqual(ip.getTitle(), title)
ip.show()
ip_other = W.get_image_by_name(title)
self.assertEqual(ip_other.getID(), ip.getID())
def test_03_02_load_monochrome_as_color(self):
path = os.path.join(example_images_directory(), "ExampleGrayToColor",
"AS_09125_050116030001_D03f00d0.tif")
workspace = self.run_workspace(path, N.LOAD_AS_COLOR_IMAGE)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (512, 512, 3))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1))
np.testing.assert_equal(pixel_data[:, :, 0], pixel_data[:, :, 1])
np.testing.assert_equal(pixel_data[:, :, 0], pixel_data[:, :, 2])
def test_03_02_load_monochrome_as_color(self):
path = os.path.join(example_images_directory(),
"ExampleGrayToColor",
"AS_09125_050116030001_D03f00d0.tif")
workspace = self.run_workspace(path, N.LOAD_AS_COLOR_IMAGE)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (512, 512, 3))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1))
np.testing.assert_equal(pixel_data[:, :, 0], pixel_data[:, :, 1])
np.testing.assert_equal(pixel_data[:, :, 0], pixel_data[:, :, 2])
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_02_02_scale(self):
'''Load an image twice, as scaled and unscaled'''
path = os.path.join(example_images_directory(), "ExampleSpecklesImages")
cpprefs.set_default_image_directory(path)
file_names = ["1-162hrh2ax2.tif", "1-162hrh2ax2.tif"]
workspace, module = self.make_workspace(file_names)
self.assertTrue(isinstance(module, L.LoadSingleImage))
module.file_settings[0].rescale.value = False
module.file_settings[1].rescale.value = True
module.run(workspace)
unscaled, scaled = [workspace.image_set.get_image(self.get_image_name(i)).pixel_data
for i in range(2)]
np.testing.assert_almost_equal(unscaled * 65535. / 4095., scaled)
def test_02_02_scale(self):
'''Load an image twice, as scaled and unscaled'''
path = os.path.join(example_images_directory(), "ExampleSpecklesImages")
cpprefs.set_default_image_directory(path)
file_names = ["1-162hrh2ax2.tif", "1-162hrh2ax2.tif"]
workspace, module = self.make_workspace(file_names)
self.assertTrue(isinstance(module, L.LoadSingleImage))
module.file_settings[0].rescale.value = False
module.file_settings[1].rescale.value = True
module.run(workspace)
unscaled, scaled = [workspace.image_set.get_image(self.get_image_name(i)).pixel_data
for i in range(2)]
np.testing.assert_almost_equal(unscaled * 65535. / 4095., scaled)
def test_09_01_load_bcb_file(self):
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
file_name = 'Channel2-01-A-01.tif'
csv_text = '''ELN_RUN_ID,CBIP_RUN_ID,ASSAY_PLATE_BARCODE,\
MX_PLATE_ID,ASSAY_WELL_POSITION,ASSAY_WELL_ROLE,SITE_X,SITE_Y,\
MICROSCOPE,SOURCE_DESCRIPTION,DATE_CREATED,FILE_PATH,FILE_NAME,\
CPD_PLATE_MAP_NAME,CPD_WELL_POSITION,BROAD_ID,\
CPD_MMOL_CONC,SOURCE_NAME,SOURCE_COMPOUND_NAME,CPD_SMILES
"4012-10-W01-01-02","4254","BR00021547","20777","N01","COMPOUND",\
"2","2","GS IX Micro","DAPI","2010/03/19 06:01:12","%s",\
"%s","C-4012-00-D80-001_Rev3","N01",\
"BRD-K71194192-001-01-6","2.132352941","ChemBridge","",\
"Oc1ccnc(SCC(=O)Nc2ccc(Oc3ccccc3)cc2)n1"
''' % (dir, file_name)
pipeline, module, filename = self.make_pipeline(csv_text)
c0_ran = [False]
def callback(workspace):
imgset = workspace.image_set
image = imgset.get_image("DAPI")
pixels = image.pixel_data
self.assertEqual(pixels.shape[0], 640)
c0_ran[0] = True
c0 = C0()
c0.callback = callback
c0.module_num = 2
pipeline.add_module(c0)
try:
m = pipeline.run()
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertTrue(c0_ran[0])
hexdigest = m.get_current_image_measurement('MD5Digest_DAPI')
#
# This appears to be tristable, depending on whether PIL or
# Bioformats or Subimager loads it (???)
#
self.assertTrue(
(hexdigest == u'f7d75e4ba3ca1385dfe09c111261359e')
or (hexdigest == '1a37c43914c7ceb7d9cac503a5c1c767'))
self.assertTrue(
'PathName_DAPI' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('PathName_DAPI'),
dir)
self.assertTrue(
'FileName_DAPI' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('FileName_DAPI'),
file_name)
finally:
os.remove(filename)
def test_03_01_load_color(self):
path = os.path.join(example_images_directory(), "ExampleColorToGray",
"AS_09125_050116030001_D03f00_color.tif")
workspace = self.run_workspace(path, N.LOAD_AS_COLOR_IMAGE)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (512, 512, 3))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1))
m = workspace.measurements
self.assertEqual(m[cpmeas.IMAGE, C_MD5_DIGEST + "_" + IMAGE_NAME],
"16729de931dc40f5ca19621598a3e7d6")
self.assertEqual(m[cpmeas.IMAGE, C_HEIGHT + "_" + IMAGE_NAME], 512)
self.assertEqual(m[cpmeas.IMAGE, C_WIDTH + "_" + IMAGE_NAME], 512)
def test_03_09_load_objects(self):
path = os.path.join(example_images_directory(), "ExampleSBSImages",
"Channel2-01-A-01.tif")
workspace = self.run_workspace(path, N.LOAD_AS_OBJECTS)
o = workspace.object_set.get_objects(OBJECTS_NAME)
assert isinstance(o, N.cpo.Objects)
areas = o.areas
self.assertEqual(areas[0], 9)
self.assertEqual(areas[1], 321)
self.assertEqual(areas[2], 2655)
m = workspace.measurements
self.assertEqual(m[cpmeas.IMAGE, C_MD5_DIGEST + "_" + OBJECTS_NAME],
"67880f6269fbf438d4b9c92256aa1d8f")
self.assertEqual(m[cpmeas.IMAGE, C_WIDTH + "_" + OBJECTS_NAME], 640)
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")
fd = os.fdopen(handle, "wb")
img = PIL.Image.fromarray(labels, "L")
img.save(fd, "PNG")
fd.close()
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_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")
fd = os.fdopen(handle, "wb")
img = PIL.Image.fromarray(labels, "L")
img.save(fd, "PNG")
fd.close()
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_03_09_load_objects(self):
path = os.path.join(example_images_directory(),
"ExampleSBSImages",
"Channel2-01-A-01.tif")
workspace = self.run_workspace(path, N.LOAD_AS_OBJECTS)
o = workspace.object_set.get_objects(OBJECTS_NAME)
assert isinstance(o, N.cpo.Objects)
areas = o.areas
self.assertEqual(areas[0], 9)
self.assertEqual(areas[1], 321)
self.assertEqual(areas[2], 2655)
m = workspace.measurements
self.assertEqual(m[cpmeas.IMAGE, C_MD5_DIGEST + "_" + OBJECTS_NAME],
"67880f6269fbf438d4b9c92256aa1d8f")
self.assertEqual(m[cpmeas.IMAGE, C_WIDTH + "_" + OBJECTS_NAME], 640)
def test_03_01_load_color(self):
path = os.path.join(example_images_directory(),
"ExampleColorToGray",
"AS_09125_050116030001_D03f00_color.tif")
workspace = self.run_workspace(path, N.LOAD_AS_COLOR_IMAGE)
image = workspace.image_set.get_image(IMAGE_NAME)
pixel_data = image.pixel_data
self.assertSequenceEqual(pixel_data.shape, (512, 512, 3))
self.assertTrue(np.all(pixel_data >= 0))
self.assertTrue(np.all(pixel_data <= 1))
m = workspace.measurements
self.assertEqual(m[cpmeas.IMAGE, C_MD5_DIGEST + "_" + IMAGE_NAME],
"16729de931dc40f5ca19621598a3e7d6")
self.assertEqual(m[cpmeas.IMAGE, C_HEIGHT + "_" + IMAGE_NAME], 512)
self.assertEqual(m[cpmeas.IMAGE, C_WIDTH + "_" + IMAGE_NAME], 512)
def test_02_01_make_image_reader(self):
path = os.path.join(example_images_directory(), 'ExampleSBSImages',
'Channel1-01-A-01.tif')
ImageReader = F.make_image_reader_class()
FormatTools = F.make_format_tools_class()
reader = ImageReader()
reader.setId(path)
self.assertEqual(reader.getDimensionOrder(), "XYCZT")
self.assertEqual(640, reader.getSizeX())
self.assertEqual(640, reader.getSizeY())
self.assertEqual(reader.getImageCount(), 1)
self.assertEqual(reader.getSizeC(), 1)
self.assertEqual(reader.getSizeT(), 1)
self.assertEqual(reader.getSizeZ(), 1)
self.assertEqual(reader.getPixelType(), FormatTools.UINT8)
self.assertEqual(reader.getRGBChannelCount(), 1)
def test_02_01_make_image_reader(self):
path = os.path.join(example_images_directory(), 'ExampleSBSImages',
'Channel1-01-A-01.tif')
ImageReader = F.make_image_reader_class()
FormatTools = F.make_format_tools_class()
reader = ImageReader()
reader.setId(path)
self.assertEqual(reader.getDimensionOrder(), "XYCZT")
self.assertEqual(640, reader.getSizeX())
self.assertEqual(640, reader.getSizeY())
self.assertEqual(reader.getImageCount(), 1)
self.assertEqual(reader.getSizeC(), 1)
self.assertEqual(reader.getSizeT(), 1)
self.assertEqual(reader.getSizeZ(), 1)
self.assertEqual(reader.getPixelType(), FormatTools.UINT8)
self.assertEqual(reader.getRGBChannelCount(), 1)
def test_02_01_make_image_reader(self):
path = os.path.join(example_images_directory(), "ExampleSBSImages", "Channel1-01-A-01.tif")
ImageReader = F.make_image_reader_class()
FormatTools = F.make_format_tools_class()
reader = ImageReader()
reader.setId(path)
self.assertEqual(reader.getDimensionOrder(), "XYCZT")
metadata = J.jdictionary_to_string_dictionary(reader.getMetadata())
self.assertEqual(int(metadata["ImageWidth"]), reader.getSizeX())
self.assertEqual(int(metadata["ImageLength"]), reader.getSizeY())
self.assertEqual(reader.getImageCount(), 1)
self.assertEqual(reader.getSizeC(), 1)
self.assertEqual(reader.getSizeT(), 1)
self.assertEqual(reader.getSizeZ(), 1)
self.assertEqual(reader.getPixelType(), FormatTools.UINT8)
self.assertEqual(reader.getRGBChannelCount(), 1)
def get_measurements_for_good_pipeline(nimages = 1,
group_numbers = None):
'''Get an appropriately initialized measurements structure for the good pipeline'''
path = os.path.join(example_images_directory(), "ExampleSBSImages")
m = cpmeas.Measurements()
if group_numbers is None:
group_numbers = [1] * nimages
group_indexes = [1]
last_group_number = group_numbers[0]
group_index = 1
for group_number in group_numbers:
if group_number == last_group_number:
group_index += 1
else:
group_index = 1
group_indexes.append(group_index)
for i in range(1, nimages+1):
filename = ("Channel2-%02d-%s-%02d.tif" %
(i, "ABCDEFGH"[int((i-1) / 12)], ((i-1) % 12) + 1))
url = pathname2url(os.path.join(path, filename))
m[cpmeas.IMAGE, cpmeas.C_FILE_NAME + "_DNA", i] = filename
m[cpmeas.IMAGE, cpmeas.C_PATH_NAME + "_DNA", i] = path
m[cpmeas.IMAGE, cpmeas.C_URL+"_DNA", i] = url
m[cpmeas.IMAGE, cpmeas.GROUP_NUMBER, i] = group_numbers[i-1]
m[cpmeas.IMAGE, cpmeas.GROUP_INDEX, i] = group_indexes[i-1]
jblob = J.run_script("""
importPackage(Packages.org.cellprofiler.imageset);
importPackage(Packages.org.cellprofiler.imageset.filter);
var imageFile=new ImageFile(new java.net.URI(url));
var imageFileDetails = new ImageFileDetails(imageFile);
var imageSeries=new ImageSeries(imageFile, 0);
var imageSeriesDetails = new ImageSeriesDetails(imageSeries, imageFileDetails);
var imagePlane=new ImagePlane(imageSeries, 0, ImagePlane.ALWAYS_MONOCHROME);
var ipd = new ImagePlaneDetails(imagePlane, imageSeriesDetails);
var stack = ImagePlaneDetailsStack.makeMonochromeStack(ipd);
var stacks = java.util.Collections.singletonList(stack);
var keys = java.util.Collections.singletonList(imageNumber);
var imageSet = new ImageSet(stacks, keys);
imageSet.compress(java.util.Collections.singletonList("DNA"), null);
""", dict(url=url, imageNumber = str(i)))
blob = J.get_env().get_byte_array_elements(jblob)
m[cpmeas.IMAGE, M_IMAGE_SET, i, blob.dtype] = blob
pipeline = cpp.Pipeline()
pipeline.loadtxt(StringIO(GOOD_PIPELINE))
pipeline.write_pipeline_measurement(m)
return m
def test_09_01_load_bcb_file(self):
dir = os.path.join(example_images_directory(), "ExampleSBSImages")
file_name = 'Channel2-01-A-01.tif'
csv_text = '''ELN_RUN_ID,CBIP_RUN_ID,ASSAY_PLATE_BARCODE,\
MX_PLATE_ID,ASSAY_WELL_POSITION,ASSAY_WELL_ROLE,SITE_X,SITE_Y,\
MICROSCOPE,SOURCE_DESCRIPTION,DATE_CREATED,FILE_PATH,FILE_NAME,\
CPD_PLATE_MAP_NAME,CPD_WELL_POSITION,BROAD_ID,\
CPD_MMOL_CONC,SOURCE_NAME,SOURCE_COMPOUND_NAME,CPD_SMILES
"4012-10-W01-01-02","4254","BR00021547","20777","N01","COMPOUND",\
"2","2","GS IX Micro","DAPI","2010/03/19 06:01:12","%s",\
"%s","C-4012-00-D80-001_Rev3","N01",\
"BRD-K71194192-001-01-6","2.132352941","ChemBridge","",\
"Oc1ccnc(SCC(=O)Nc2ccc(Oc3ccccc3)cc2)n1"
'''%(dir,file_name)
pipeline, module, filename = self.make_pipeline(csv_text)
c0_ran = [False]
def callback(workspace):
imgset = workspace.image_set
image = imgset.get_image("DAPI")
pixels = image.pixel_data
self.assertEqual(pixels.shape[0],640)
c0_ran[0] = True
c0 = C0()
c0.callback = callback
c0.module_num = 2
pipeline.add_module(c0)
try:
m = pipeline.run()
self.assertTrue(isinstance(m, cpmeas.Measurements))
self.assertTrue(c0_ran[0])
hexdigest = m.get_current_image_measurement('MD5Digest_DAPI')
#
# This appears to be tristable, depending on whether PIL or
# Bioformats or Subimager loads it (???)
#
self.assertTrue((hexdigest == u'f7d75e4ba3ca1385dfe09c111261359e') or
(hexdigest == '1a37c43914c7ceb7d9cac503a5c1c767'))
self.assertTrue('PathName_DAPI' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('PathName_DAPI'),
dir)
self.assertTrue('FileName_DAPI' in m.get_feature_names(cpmeas.IMAGE))
self.assertEqual(m.get_current_image_measurement('FileName_DAPI'),
file_name)
finally:
os.remove(filename)
def test_02_03_prepare_run(self):
# regression test for issue #673 and #1161
#
# If LoadSingleImage appears first, pathname data does not show
# up in the measurements.
#
maybe_download_sbs()
folder = "ExampleSBSImages"
path = os.path.join(example_images_directory(), folder)
filename = "Channel1-01-A-01.tif"
pipeline = cpp.Pipeline()
lsi = L.LoadSingleImage()
lsi.module_num = 1
lsi.directory.dir_choice = cps.ABSOLUTE_FOLDER_NAME
lsi.directory.custom_path = path
lsi.file_settings[0].image_name.value = self.get_image_name(0)
lsi.file_settings[0].file_name.value = filename
pipeline.add_module(lsi)
li = LI.LoadImages()
li.module_num = 2
pipeline.add_module(li)
li.match_method.value = LI.MS_EXACT_MATCH
li.location.dir_choice = cps.ABSOLUTE_FOLDER_NAME
li.location.custom_path = path
li.images[0].common_text.value = "Channel2-"
m = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, lsi, m, cpo.ObjectSet(), m,
cpi.ImageSetList())
self.assertTrue(pipeline.prepare_run(workspace))
self.assertGreater(m.image_set_count, 1)
pipeline.prepare_group(workspace, {}, m.get_image_numbers())
#
# Skip to the second image set
#
m.next_image_set(2)
lsi.run(workspace)
#
# Are the measurements populated?
#
m_file = "_".join((cpmeas.C_FILE_NAME, self.get_image_name(0)))
self.assertEqual(m[cpmeas.IMAGE, m_file,2], filename)
#
# Can we retrieve the image?
#
pixel_data = m.get_image(self.get_image_name(0)).pixel_data
self.assertEqual(tuple(pixel_data.shape), (640, 640))
def test_05_01_align_self(self):
'''Align an image from the fly screen against itself.
This is a regression test for the bug, IMG-284
'''
fly_file = '01_POS002_D.TIF'
fly_dir = "ExampleFlyImages"
path = os.path.join(example_images_directory(), fly_dir, fly_file)
image = load_using_PIL(path)
image = image[0:300,0:300] # make smaller so as to be faster
workspace, module = self.make_workspace((image, image),(None,None))
module.alignment_method.value = A.M_MUTUAL_INFORMATION
module.crop_mode.value = A.C_PAD
module.run(workspace)
m = workspace.measurements
self.assertEqual(m.get_current_image_measurement('Align_Xshift_Aligned1'), 0)
self.assertEqual(m.get_current_image_measurement('Align_Yshift_Aligned1'), 0)