def load(self, filename, load_pipeline):
'''Load a workspace from a .cpi file
filename - path to file to load
load_pipeline - true to load the pipeline from the file, false to
use the current pipeline.
'''
import shutil
from .pipeline import M_PIPELINE, M_DEFAULT_INPUT_FOLDER, \
M_DEFAULT_OUTPUT_FOLDER
import cellprofiler.measurements as cpmeas
from cellprofiler.preferences import set_default_image_directory, \
set_default_output_directory
if self.__measurements is not None:
self.close()
self.__loading = True
try:
#
# Copy the file to a temporary location before opening
#
fd, self.__filename = cpmeas.make_temporary_file()
os.close(fd)
shutil.copyfile(filename, self.__filename)
self.__measurements = cpmeas.Measurements(
filename = self.__filename, mode = "r+")
if self.__file_list is not None:
self.__file_list.remove_notification_callback(
self.__on_file_list_changed)
self.__file_list = HDF5FileList(self.measurements.hdf5_dict.hdf5_file)
self.__file_list.add_notification_callback(self.__on_file_list_changed)
if load_pipeline and self.__measurements.has_feature(
cpmeas.EXPERIMENT, M_PIPELINE):
pipeline_txt = self.__measurements.get_experiment_measurement(
M_PIPELINE).encode("utf-8")
self.pipeline.load(StringIO(pipeline_txt))
elif load_pipeline:
self.pipeline.clear()
else:
fd = StringIO()
self.pipeline.savetxt(fd, save_image_plane_details = False)
self.__measurements.add_experiment_measurement(
M_PIPELINE, fd.getvalue())
for feature, function in (
(M_DEFAULT_INPUT_FOLDER, set_default_image_directory),
(M_DEFAULT_OUTPUT_FOLDER, set_default_output_directory)):
if self.measurements.has_feature(cpmeas.EXPERIMENT, feature):
path = self.measurements[cpmeas.EXPERIMENT, feature]
if os.path.isdir(path):
function(path)
finally:
self.__loading = False
self.notify(self.WorkspaceLoadedEvent(self))
def load(self, filename, load_pipeline):
'''Load a workspace from a .cpi file
filename - path to file to load
load_pipeline - true to load the pipeline from the file, false to
use the current pipeline.
'''
import shutil
from .pipeline import M_PIPELINE
import cellprofiler.measurements as cpmeas
if self.__measurements is not None:
self.close()
#
# Copy the file to a temporary location before opening
#
fd, self.__filename = cpmeas.make_temporary_file()
os.close(fd)
shutil.copyfile(filename, self.__filename)
self.__measurements = cpmeas.Measurements(filename=self.__filename,
mode="r+")
if self.__file_list is not None:
self.__file_list.remove_notification_callback(
self.__on_file_list_changed)
self.__file_list = HDF5FileList(self.measurements.hdf5_dict.hdf5_file)
self.__file_list.add_notification_callback(self.__on_file_list_changed)
if load_pipeline and self.__measurements.has_feature(
cpmeas.EXPERIMENT, M_PIPELINE):
pipeline_txt = self.__measurements.get_experiment_measurement(
M_PIPELINE).encode("utf-8")
self.pipeline.load(StringIO(pipeline_txt))
elif load_pipeline:
self.pipeline.clear()
else:
fd = StringIO()
self.pipeline.savetxt(fd, save_image_plane_details=False)
self.__measurements.add_experiment_measurement(
M_PIPELINE, fd.getvalue())
self.notify(self.WorkspaceLoadedEvent(self))
def load(self, filename, load_pipeline):
'''Load a workspace from a .cpi file
filename - path to file to load
load_pipeline - true to load the pipeline from the file, false to
use the current pipeline.
'''
import shutil
from .pipeline import M_PIPELINE
import cellprofiler.measurements as cpmeas
if self.__measurements is not None:
self.close()
#
# Copy the file to a temporary location before opening
#
fd, self.__filename = cpmeas.make_temporary_file()
os.close(fd)
shutil.copyfile(filename, self.__filename)
self.__measurements = cpmeas.Measurements(
filename = self.__filename, mode = "r+")
if self.__file_list is not None:
self.__file_list.remove_notification_callback(
self.__on_file_list_changed)
self.__file_list = HDF5FileList(self.measurements.hdf5_dict.hdf5_file)
self.__file_list.add_notification_callback(self.__on_file_list_changed)
if load_pipeline and self.__measurements.has_feature(
cpmeas.EXPERIMENT, M_PIPELINE):
pipeline_txt = self.__measurements.get_experiment_measurement(
M_PIPELINE).encode("utf-8")
self.pipeline.load(StringIO(pipeline_txt))
elif load_pipeline:
self.pipeline.clear()
else:
fd = StringIO()
self.pipeline.savetxt(fd, save_image_plane_details = False)
self.__measurements.add_experiment_measurement(
M_PIPELINE, fd.getvalue())
self.notify(self.WorkspaceLoadedEvent(self))
def load(self, filename, load_pipeline):
'''Load a workspace from a .cpi file
filename - path to file to load
load_pipeline - true to load the pipeline from the file, false to
use the current pipeline.
'''
import shutil
from .pipeline import M_PIPELINE, M_DEFAULT_INPUT_FOLDER, \
M_DEFAULT_OUTPUT_FOLDER
import cellprofiler.measurements as cpmeas
from cellprofiler.preferences import set_default_image_directory, \
set_default_output_directory
image_set_and_measurements_are_same = False
if self.__measurements is not None:
image_set_and_measurements_are_same = (id(
self.__measurements) == id(self.__image_set))
self.close()
self.__loading = True
try:
#
# Copy the file to a temporary location before opening
#
fd, self.__filename = cpmeas.make_temporary_file()
os.close(fd)
shutil.copyfile(filename, self.__filename)
self.__measurements = cpmeas.Measurements(filename=self.__filename,
mode="r+")
if self.__file_list is not None:
self.__file_list.remove_notification_callback(
self.__on_file_list_changed)
self.__file_list = HDF5FileList(
self.measurements.hdf5_dict.hdf5_file)
self.__file_list.add_notification_callback(
self.__on_file_list_changed)
if load_pipeline and self.__measurements.has_feature(
cpmeas.EXPERIMENT, M_PIPELINE):
pipeline_txt = self.__measurements.get_experiment_measurement(
M_PIPELINE).encode("utf-8")
self.pipeline.load(StringIO(pipeline_txt))
elif load_pipeline:
self.pipeline.clear()
else:
fd = StringIO()
self.pipeline.savetxt(fd, save_image_plane_details=False)
self.__measurements.add_experiment_measurement(
M_PIPELINE, fd.getvalue())
for feature, function in ((M_DEFAULT_INPUT_FOLDER,
set_default_image_directory),
(M_DEFAULT_OUTPUT_FOLDER,
set_default_output_directory)):
if self.measurements.has_feature(cpmeas.EXPERIMENT, feature):
path = self.measurements[cpmeas.EXPERIMENT, feature]
if os.path.isdir(path):
function(path)
if image_set_and_measurements_are_same:
self.__image_set = self.__measurements
finally:
self.__loading = False
self.notify(self.WorkspaceLoadedEvent(self))
