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 check_preferences(self):
"""Return True if preferences are OK (e.g., directories exist)"""
path = self.__image_edit_box.GetValue()
if not os.path.isdir(path):
if (wx.MessageBox(
('The Default Input Folder is "%s", but '
"the directory does not exist. Do you want to "
"create it?") % path,
"Warning, cannot run pipeline",
style=wx.YES_NO,
) == wx.NO):
return False, "Image directory does not exist"
os.makedirs(path)
set_default_image_directory(path)
path = self.__output_edit_box.GetValue()
if not os.path.isdir(path):
if (wx.MessageBox(
('The Default Output Folder is "%s", but '
"the directory does not exist. Do you want to "
"create it?") % path,
"Warning, cannot run pipeline",
style=wx.YES_NO,
) == wx.NO):
return False, "Output directory does not exist"
os.makedirs(path)
set_default_output_directory(path)
return True, "OK"
def enter_batch_mode(self, workspace):
"""Restore the image set list from its setting as we go into batch mode"""
pipeline = workspace.pipeline
assert isinstance(pipeline, cpp.Pipeline)
assert not self.distributed_mode, "Distributed mode no longer supported"
default_output_directory = self.custom_output_directory.value
default_image_directory = self.default_image_directory.value
if os.path.isdir(default_output_directory):
cpprefs.set_default_output_directory(default_output_directory)
else:
logger.info(
'Batch file default output directory, "%s", does not exist' %
default_output_directory)
if os.path.isdir(default_image_directory):
cpprefs.set_default_image_directory(default_image_directory)
else:
logger.info(
'Batch file default input directory "%s", does not exist' %
default_image_directory)
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 main(args=None):
"""Run CellProfiler
args - command-line arguments, e.g., sys.argv
"""
if args is None:
args = sys.argv
set_awt_headless(True)
exit_code = 0
switches = ("--work-announce", "--knime-bridge-address")
if any(
[any([arg.startswith(switch) for switch in switches])
for arg in args]):
set_headless()
aw_parse_args()
main()
return exit_code
options, args = parse_args(args)
if options.temp_dir is not None:
if not os.path.exists(options.temp_dir):
os.makedirs(options.temp_dir)
set_temporary_directory(options.temp_dir, globally=False)
temp_dir = get_temporary_directory()
to_clean = []
if options.pipeline_filename:
o = urllib.parse.urlparse(options.pipeline_filename)
if o[0] in ("ftp", "http", "https"):
from urllib.request import urlopen
temp_pipe_file = tempfile.NamedTemporaryFile(mode="w+b",
suffix=".cppipe",
dir=temp_dir,
delete=False)
downloaded_pipeline = urlopen(options.pipeline_filename)
for line in downloaded_pipeline:
temp_pipe_file.write(line)
options.pipeline_filename = temp_pipe_file.name
to_clean.append(os.path.join(temp_dir, temp_pipe_file.name))
if options.image_set_file:
o = urllib.parse.urlparse(options.image_set_file)
if o[0] in ("ftp", "http", "https"):
from urllib.request import urlopen
temp_set_file = tempfile.NamedTemporaryFile(mode="w+b",
suffix=".csv",
dir=temp_dir,
delete=False)
downloaded_set_csv = urlopen(options.image_set_file)
for line in downloaded_set_csv:
temp_set_file.write(line)
options.image_set_file = temp_set_file.name
to_clean.append(os.path.join(temp_dir, temp_set_file.name))
if options.data_file:
o = urllib.parse.urlparse(options.data_file)
if o[0] in ("ftp", "http", "https"):
from urllib.request import urlopen
temp_data_file = tempfile.NamedTemporaryFile(mode="w+b",
suffix=".csv",
dir=temp_dir,
delete=False)
downloaded_data_csv = urlopen(options.data_file)
for line in downloaded_data_csv:
temp_data_file.write(line)
options.data_file = temp_data_file.name
to_clean.append(os.path.join(temp_dir, temp_data_file.name))
if options.print_version:
__version__(exit_code)
if (not options.show_gui) or options.write_schema_and_exit:
set_headless()
options.run_pipeline = True
if options.batch_commands_file:
set_headless()
options.run_pipeline = False
options.show_gui = False
set_log_level(options)
if options.print_groups_file is not None:
print_groups(options.print_groups_file)
if options.batch_commands_file is not None:
try:
nr_per_batch = int(options.images_per_batch)
except ValueError:
logging.warning(
"non-integer argument to --images-per-batch. Defaulting to 1.")
nr_per_batch = 1
get_batch_commands(options.batch_commands_file, nr_per_batch)
if options.omero_credentials is not None:
set_omero_credentials_from_string(options.omero_credentials)
if options.plugins_directory is not None:
set_plugin_directory(options.plugins_directory, globally=False)
if not options.allow_schema_write:
set_allow_schema_write(False)
if options.output_directory:
if not os.path.exists(options.output_directory):
os.makedirs(options.output_directory)
set_default_output_directory(options.output_directory)
if options.image_directory:
set_default_image_directory(options.image_directory)
if options.run_pipeline and not options.pipeline_filename:
raise ValueError("You must specify a pipeline filename to run")
if options.data_file is not None:
set_data_file(os.path.abspath(options.data_file))
try:
if not options.show_gui:
start_java()
if options.image_set_file is not None:
set_image_set_file(options.image_set_file)
#
# Handle command-line tasks that that need to load the modules to run
#
if options.print_measurements:
print_measurements(options)
if options.write_schema_and_exit:
write_schema(options.pipeline_filename)
if options.show_gui:
matplotlib.use("WXAgg")
import cellprofiler.gui.app
if options.pipeline_filename:
if is_workspace_file(options.pipeline_filename):
workspace_path = os.path.expanduser(
options.pipeline_filename)
pipeline_path = None
else:
pipeline_path = os.path.expanduser(
options.pipeline_filename)
workspace_path = None
else:
workspace_path = None
pipeline_path = None
app = cellprofiler.gui.app.App(0,
workspace_path=workspace_path,
pipeline_path=pipeline_path)
if options.run_pipeline:
app.frame.pipeline_controller.do_analyze_images()
app.MainLoop()
return
elif options.run_pipeline:
exit_code = run_pipeline_headless(options, args)
finally:
# Cleanup the temp files we made, if any
if len(to_clean) > 0:
for each_temp in to_clean:
os.remove(each_temp)
# If anything goes wrong during the startup sequence headlessly, the JVM needs
# to be explicitly closed
if not options.show_gui:
stop_cellprofiler()
return exit_code
