def analyze(conn, plate, pipeline):
warnings.filterwarnings('ignore')
print("analyzing...")
# Set Cell Output Directory
new_output_directory = os.path.normcase(tempfile.mkdtemp())
cpprefs.set_default_output_directory(new_output_directory)
wells = list(plate.listChildren())
wells = wells[0:5] # use the first 5 wells
for count, well in enumerate(wells):
# Load a single Image per Well
image = well.getImage(0)
print(image.getName())
pixels = image.getPrimaryPixels()
size_c = image.getSizeC()
# For each Image in OMERO, we copy pipeline and inject image modules
pipeline_copy = pipeline.copy()
# Inject image for each Channel (pipeline only handles 2 channels)
for c in range(0, size_c):
plane = pixels.getPlane(0, c, 0)
image_name = image.getName()
# Name of the channel expected in the pipeline
if c == 0:
image_name = 'OrigBlue'
if c == 1:
image_name = 'OrigGreen'
inject_image_module = InjectImage(image_name, plane)
inject_image_module.set_module_num(1)
pipeline_copy.add_module(inject_image_module)
pipeline_copy.run()
# Results obtained as CSV from Cell Profiler
path = new_output_directory + '/Nuclei.csv'
save_results(conn, path, image)
print("analysis done")
def test_01_01_get_from_image_set(self):
image = numpy.zeros((10,10),dtype=float)
image_set_list = cellprofiler.cpimage.ImageSetList()
ii = InjectImage("my_image", image)
pipeline = cellprofiler.pipeline.Pipeline()
ii.prepare_run(cpw.Workspace(pipeline, ii, None, None,
cpmeas.Measurements(), image_set_list))
ii.prepare_group(pipeline, image_set_list, {}, [1])
image_set = image_set_list.get_image_set(0)
self.assertTrue(image_set,"No image set returned from ImageSetList.GetImageSet")
my_image = image_set.get_image("my_image")
self.assertTrue(my_image, "No image returned from ImageSet.GetImage")
self.assertEqual(my_image.image.shape[0],10,"Wrong image shape")
def analyze(plate, pipeline):
warnings.filterwarnings('ignore')
print("analyzing...")
# Set Cell Output Directory
new_output_directory = os.path.normcase(tempfile.mkdtemp())
cpprefs.set_default_output_directory(new_output_directory)
files = list()
wells = list(plate.listChildren())
wells = wells[0:5] # use the first 5 wells
plate_id = plate.getId()
for count, well in enumerate(wells):
# Load a single Image per Well
image = well.getImage(0)
print(image.getName())
data = load_dask_array_from_s3(plate_id,
(well.row + 1) * (well.column + 1) - 1)
size_c = image.getSizeC()
# For each Image in OMERO, we copy pipeline and inject image modules
pipeline_copy = pipeline.copy()
# Inject image for each Channel (pipeline only handles 2 channels)
for c in range(0, size_c):
plane = data[0, c, 0, :, :]
image_name = image.getName()
# Name of the channel expected in the pipeline
if c == 0:
image_name = 'OrigBlue'
if c == 1:
image_name = 'OrigGreen'
inject_image_module = InjectImage(image_name, plane)
inject_image_module.set_module_num(1)
pipeline_copy.add_module(inject_image_module)
pipeline_copy.run()
# Results obtained as CSV from Cell Profiler
path = new_output_directory + '/Nuclei.csv'
files.append(path)
print("analysis done")
return files
def test_01_01_get_from_image_set(self):
image = numpy.zeros((10,10),dtype=float)
ii = InjectImage("my_image", image)
pipeline = cellprofiler.pipeline.Pipeline()
measurements = cpmeas.Measurements()
workspace = cpw.Workspace(pipeline, ii, measurements, None,
measurements,
cellprofiler.cpimage.ImageSetList())
ii.prepare_run(workspace)
ii.prepare_group(workspace, {}, [1])
ii.run(workspace)
image_set = workspace.image_set
self.assertTrue(image_set,"No image set returned from ImageSetList.GetImageSet")
my_image = image_set.get_image("my_image")
self.assertTrue(my_image, "No image returned from ImageSet.GetImage")
self.assertEqual(my_image.image.shape[0],10,"Wrong image shape")
def make_workspace(self, input_image, input_mask=None,
reference_image=None, reference_mask=None,
measurement=None):
pipeline = cpp.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
object_set = cpo.ObjectSet()
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
measurements = cpmeas.Measurements()
module_number = 1
module = R.RescaleIntensity()
module.image_name.value = INPUT_NAME
if isinstance(input_image, (tuple, list)):
first_input_image = input_image[0]
else:
first_input_image = input_image
if isinstance(input_mask, (tuple, list)):
first_input_mask = input_mask[0]
else:
first_input_mask = input_mask
if first_input_mask is None:
image = cpi.Image(first_input_image)
else:
image = cpi.Image(first_input_image, first_input_mask)
ii = InjectImage(INPUT_NAME, input_image, input_mask)
ii.module_num = module_number
module_number += 1
pipeline.add_module(ii)
image_set.add(INPUT_NAME, image)
module.rescaled_image_name.value = OUTPUT_NAME
if reference_image is not None:
module.matching_image_name.value = REFERENCE_NAME
if reference_mask is None:
image = cpi.Image(reference_image)
else:
image = cpi.Image(reference_image, mask=reference_mask)
image_set.add(REFERENCE_NAME, image)
ii = InjectImage(REFERENCE_NAME, reference_image, reference_mask)
ii.module_num = module_number
module_number += 1
pipeline.add_module(ii)
module.module_num = module_number
pipeline.add_module(module)
if measurement is not None:
module.divisor_measurement.value = MEASUREMENT_NAME
measurements.add_image_measurement(MEASUREMENT_NAME, measurement)
workspace = cpw.Workspace(pipeline,
module,
image_set,
object_set,
measurements,
image_set_list)
return workspace, module
def test_00_00_init(self):
image = numpy.zeros((10,10),dtype=float)
x = InjectImage("my_image", image)
