def execute_merge_files(mm):
input_files = []
output_fd, output_file = tempfile.mkstemp(".mat")
pipeline = cellprofiler.pipeline.Pipeline()
li = cellprofiler.modules.loadimages.LoadImages()
li.module_num = 1
pipeline.add_module(li)
for m in mm:
input_fd, input_file = tempfile.mkstemp(".mat")
pipeline.save_measurements(input_file, m)
input_files.append((input_fd, input_file))
cellprofiler.modules.mergeoutputfiles.MergeOutputFiles.merge_files(
output_file, [x[1] for x in input_files]
)
m = cellprofiler.measurement.load_measurements(output_file)
os.close(output_fd)
os.remove(output_file)
for fd, filename in input_files:
os.close(fd)
os.remove(filename)
return m
def run_pipeline_headless(options, args):
"""
Run a CellProfiler pipeline in headless mode
"""
if options.first_image_set is not None:
if not options.first_image_set.isdigit():
raise ValueError(
"The --first-image-set option takes a numeric argument")
else:
image_set_start = int(options.first_image_set)
else:
image_set_start = None
image_set_numbers = None
if options.last_image_set is not None:
if not options.last_image_set.isdigit():
raise ValueError(
"The --last-image-set option takes a numeric argument")
else:
image_set_end = int(options.last_image_set)
if image_set_start is None:
image_set_numbers = numpy.arange(1, image_set_end + 1)
else:
image_set_numbers = numpy.arange(image_set_start,
image_set_end + 1)
else:
image_set_end = None
if (options.pipeline_filename is not None) and (
not options.pipeline_filename.lower().startswith('http')):
options.pipeline_filename = os.path.expanduser(
options.pipeline_filename)
pipeline = cellprofiler.pipeline.Pipeline()
initial_measurements = None
try:
if h5py.is_hdf5(options.pipeline_filename):
initial_measurements = cellprofiler.measurement.load_measurements(
options.pipeline_filename, image_numbers=image_set_numbers)
except:
logging.root.info("Failed to load measurements from pipeline")
if initial_measurements is not None:
pipeline_text = initial_measurements.get_experiment_measurement(
cellprofiler.pipeline.M_PIPELINE)
pipeline_text = pipeline_text.encode('us-ascii')
pipeline.load(cStringIO.StringIO(pipeline_text))
if not pipeline.in_batch_mode():
#
# Need file list in order to call prepare_run
#
with h5py.File(options.pipeline_filename, "r") as src:
if cellprofiler.utilities.hdf5_dict.HDF5FileList.has_file_list(
src):
cellprofiler.utilities.hdf5_dict.HDF5FileList.copy(
src, initial_measurements.hdf5_dict.hdf5_file)
else:
pipeline.load(options.pipeline_filename)
if options.groups is not None:
kvs = [x.split('=') for x in options.groups.split(',')]
groups = dict(kvs)
else:
groups = None
file_list = cellprofiler.preferences.get_image_set_file()
if file_list is not None:
pipeline.read_file_list(file_list)
#
# Fixup CreateBatchFiles with any command-line input or output directories
#
if pipeline.in_batch_mode():
create_batch_files = [
m for m in pipeline.modules() if m.is_create_batch_module()
]
if len(create_batch_files) > 0:
create_batch_files = create_batch_files[0]
if options.output_directory is not None:
create_batch_files.custom_output_directory.value = options.output_directory
if options.image_directory is not None:
create_batch_files.default_image_directory.value = options.image_directory
use_hdf5 = len(args) > 0 and not args[0].lower().endswith(".mat")
measurements = pipeline.run(
image_set_start=image_set_start,
image_set_end=image_set_end,
grouping=groups,
measurements_filename=None if not use_hdf5 else args[0],
initial_measurements=initial_measurements)
if len(args) > 0 and not use_hdf5:
pipeline.save_measurements(args[0], measurements)
if options.done_file is not None:
if measurements is not None and measurements.has_feature(
cellprofiler.measurement.EXPERIMENT,
cellprofiler.pipeline.EXIT_STATUS):
done_text = measurements.get_experiment_measurement(
cellprofiler.pipeline.EXIT_STATUS)
exit_code = (0 if done_text == "Complete" else -1)
else:
done_text = "Failure"
exit_code = -1
fd = open(options.done_file, "wt")
fd.write("%s\n" % done_text)
fd.close()
else:
exit_code = 0
if measurements is not None:
measurements.close()
return exit_code
def run_pipeline_headless(options, args):
"""
Run a CellProfiler pipeline in headless mode
"""
if options.first_image_set is not None:
if not options.first_image_set.isdigit():
raise ValueError("The --first-image-set option takes a numeric argument")
else:
image_set_start = int(options.first_image_set)
else:
image_set_start = None
image_set_numbers = None
if options.last_image_set is not None:
if not options.last_image_set.isdigit():
raise ValueError("The --last-image-set option takes a numeric argument")
else:
image_set_end = int(options.last_image_set)
if image_set_start is None:
image_set_numbers = numpy.arange(1, image_set_end + 1)
else:
image_set_numbers = numpy.arange(image_set_start, image_set_end + 1)
else:
image_set_end = None
if (options.pipeline_filename is not None) and (not options.pipeline_filename.lower().startswith('http')):
options.pipeline_filename = os.path.expanduser(options.pipeline_filename)
pipeline = cellprofiler.pipeline.Pipeline()
initial_measurements = None
try:
if h5py.is_hdf5(options.pipeline_filename):
initial_measurements = cellprofiler.measurement.load_measurements(options.pipeline_filename, image_numbers=image_set_numbers)
except:
logging.root.info("Failed to load measurements from pipeline")
if initial_measurements is not None:
pipeline_text = initial_measurements.get_experiment_measurement(cellprofiler.pipeline.M_PIPELINE)
pipeline_text = pipeline_text.encode('us-ascii')
pipeline.load(cStringIO.StringIO(pipeline_text))
if not pipeline.in_batch_mode():
#
# Need file list in order to call prepare_run
#
with h5py.File(options.pipeline_filename, "r") as src:
if cellprofiler.utilities.hdf5_dict.HDF5FileList.has_file_list(src):
cellprofiler.utilities.hdf5_dict.HDF5FileList.copy(src, initial_measurements.hdf5_dict.hdf5_file)
else:
pipeline.load(options.pipeline_filename)
if options.groups is not None:
kvs = [x.split('=') for x in options.groups.split(',')]
groups = dict(kvs)
else:
groups = None
file_list = cellprofiler.preferences.get_image_set_file()
if file_list is not None:
pipeline.read_file_list(file_list)
#
# Fixup CreateBatchFiles with any command-line input or output directories
#
if pipeline.in_batch_mode():
create_batch_files = [m for m in pipeline.modules() if m.is_create_batch_module()]
if len(create_batch_files) > 0:
create_batch_files = create_batch_files[0]
if options.output_directory is not None:
create_batch_files.custom_output_directory.value = options.output_directory
if options.image_directory is not None:
create_batch_files.default_image_directory.value = options.image_directory
use_hdf5 = len(args) > 0 and not args[0].lower().endswith(".mat")
measurements = pipeline.run(
image_set_start=image_set_start,
image_set_end=image_set_end,
grouping=groups,
measurements_filename=None if not use_hdf5 else args[0],
initial_measurements=initial_measurements
)
if len(args) > 0 and not use_hdf5:
pipeline.save_measurements(args[0], measurements)
if options.done_file is not None:
if measurements is not None and measurements.has_feature(cellprofiler.measurement.EXPERIMENT, cellprofiler.pipeline.EXIT_STATUS):
done_text = measurements.get_experiment_measurement(cellprofiler.pipeline.EXIT_STATUS)
exit_code = (0 if done_text == "Complete" else -1)
else:
done_text = "Failure"
exit_code = -1
fd = open(options.done_file, "wt")
fd.write("%s\n" % done_text)
fd.close()
else:
exit_code = 0
if measurements is not None:
measurements.close()
return exit_code