def _importProject(self, importedFilePath, newProjectFile, newProjectFilePath):
"""
Load the data from a project and save it to a different project file.
importedFilePath - The path to a (not open) .ilp file to import data from
newProjectFile - An hdf5 handle to a new .ilp to load data into (must be open already)
newProjectFilePath - The path to the new .ilp we're loading.
"""
importedFile = h5py.File(importedFilePath, "r")
self.workflow = self._workflowClass(
self._shell, self._headless, self._workflow_cmdline_args, self._project_creation_args
)
self.currentProjectFile = newProjectFile
self.currentProjectPath = newProjectFilePath
self.currentProjectIsReadOnly = False
try:
serializers = [serializer for aplt in self._applets for serializer in aplt.dataSerializers]
newProject = Project(newProjectFile)
newProject.populateFrom(importedFile, [s.topGroupName for s in serializers])
for serializer in serializers:
serializer.ignoreDirty = True
serializer.deserializeFromHdf5(self.currentProjectFile, newProjectFilePath, self._headless)
serializer.ignoreDirty = False
self.closed = False
newProject.updateWorkflowName(self.workflow.workflowName)
newProject.updateVersion()
newProject.flush()
self.workflow.onProjectLoaded(self)
self.workflow.handleAppletStateUpdateRequested()
except:
self._closeCurrentProject()
raise
def importAsLocalDataset(
self, project_file: h5py.File, progress_signal: Callable[[int], None] = lambda x: None
) -> str:
project = Project(project_file)
inner_path = project.local_data_group.name + "/" + self.legacy_datasetId
if project_file.get(inner_path) is not None:
return inner_path
self.dumpToHdf5(h5_file=project_file, inner_path=inner_path, progress_signal=progress_signal)
return inner_path
def saveProject(self, force_all_save=False):
"""
Update the project file with the state of the current workflow settings.
Must not be called if the project file was opened in read-only mode.
"""
logger.debug("Save Project triggered")
assert self.currentProjectFile != None
assert self.currentProjectPath != None
assert not self.currentProjectIsReadOnly, "Can't save a read-only project"
# Minor GUI nicety: Pre-activate the progress signals for dirty applets so
# the progress manager treats these tasks as a group instead of several sequential jobs.
for aplt in self._applets:
for ser in aplt.dataSerializers:
if ser.isDirty():
aplt.progressSignal(0)
try:
# Applet serializable items are given the whole file (root group) for now
file_changed = False
for aplt in self._applets:
for serializer in aplt.dataSerializers:
assert (
serializer.base_initialized
), "AppletSerializer subclasses must call AppletSerializer.__init__ upon construction."
if force_all_save or serializer.isDirty(
) or serializer.shouldSerialize(self.currentProjectFile):
serializer.serializeToHdf5(self.currentProjectFile,
self.currentProjectPath)
file_changed = True
if file_changed:
Project(self.currentProjectFile).updateVersion()
# save the current workflow as standard workflow
if "workflowName" in self.currentProjectFile:
del self.currentProjectFile["workflowName"]
self.currentProjectFile.create_dataset(
"workflowName",
data=self.workflow.workflowName.encode("utf-8"))
except Exception as err:
log_exception(
logger,
"Project Save Action failed due to the exception shown above.")
raise ProjectManager.SaveError(str(err))
finally:
# save current time
if "time" in self.currentProjectFile:
del self.currentProjectFile["time"]
self.currentProjectFile.create_dataset(
"time", data=time.ctime().encode("utf-8"))
# Flush any changes we made to disk, but don't close the file.
self.currentProjectFile.flush()
for applet in self._applets:
applet.progressSignal(100)
def _deserialize(self, mygroup, slot):
logger.debug("Deserializing BlockSlot: {}".format(self.name))
num = len(mygroup)
if len(self.inslot) < num:
self.inslot.resize(num)
# Annoyingly, some applets store their groups with names like, img0,img1,img2,..,img9,img10,img11
# which means that sorted() needs a special key to avoid sorting img10 before img2
# We have to find the index and sort according to its numerical value.
index_capture = re.compile(r"[^0-9]*(\d*).*")
def extract_index(s):
return int(index_capture.match(s).groups()[0])
for index, t in enumerate(
sorted(list(mygroup.items()),
key=lambda k_v: extract_index(k_v[0]))):
groupName, labelGroup = t
for blockData in list(labelGroup.values()):
slicing = stringToSlicing(blockData.attrs["blockSlice"])
# If it is suppose to be a masked array,
# deserialize the pieces and rebuild the masked array.
assert slot[index].meta.has_mask == mygroup.attrs.get(
"meta.has_mask"), (
"The slot and stored data have different values for" +
" `has_mask`. They are" +
" `bool(slot[index].meta.has_mask)`=" +
repr(bool(slot[index].meta.has_mask)) + " and" +
' `mygroup.attrs.get("meta.has_mask", False)`=' +
repr(mygroup.attrs.get("meta.has_mask", False)) +
". Please fix this to proceed with deserialization.")
if slot[index].meta.has_mask:
blockArray = numpy.ma.masked_array(
blockData["data"][()],
mask=blockData["mask"][()],
fill_value=blockData["fill_value"][()],
shrink=False,
)
else:
blockArray = blockData[...]
blockArray, slicing = self.reshape_datablock_and_slicing_for_input(
blockArray, slicing, self.inslot[index],
Project(mygroup.file))
self.inslot[index][slicing] = blockArray
def deserialize(self, group):
super().deserialize(group)
if self.deserialization_requires_data_conversion(Project(group.file)):
self.ignoreDirty = False
self.dirty = True