def _deserializeFromHdf5(self, topGroup, groupVersion, hdf5File,
projectFilePath):
with Tracer(traceLogger):
self._projectFilePath = projectFilePath
self.initWithoutTopGroup(hdf5File, projectFilePath)
infoDir = topGroup['infos']
self.mainOperator.Dataset.resize(len(infoDir))
for index, (infoGroupName,
infoGroup) in enumerate(sorted(infoDir.items())):
datasetInfo = DatasetInfo()
# Make a reverse-lookup of the location storage strings
LocationLookup = {
v: k
for k, v in self.LocationStrings.items()
}
datasetInfo.location = LocationLookup[str(
infoGroup['location'].value)]
# Write to the 'private' members to avoid resetting the dataset id
datasetInfo._filePath = str(infoGroup['filePath'].value)
datasetInfo._datasetId = str(infoGroup['datasetId'].value)
# Deserialize the "allow labels" flag
try:
datasetInfo.allowLabels = infoGroup['allowLabels'].value
except KeyError:
pass
# Deserialize the axisorder (if present)
try:
datasetInfo.axisorder = infoGroup['axisorder'].value
except KeyError:
if ilastik.utility.globals.ImportOptions.default_axis_order is not None:
datasetInfo.axisorder = ilastik.utility.globals.ImportOptions.default_axis_order
# If the data is supposed to be in the project,
# check for it now.
if datasetInfo.location == DatasetInfo.Location.ProjectInternal:
if not datasetInfo.datasetId in topGroup[
'local_data'].keys():
raise RuntimeError(
"Corrupt project file. Could not find data for " +
infoGroupName)
# If the data is supposed to exist outside the project, make sure it really does.
if datasetInfo.location == DatasetInfo.Location.FileSystem:
filePath = PathComponents(
datasetInfo.filePath,
os.path.split(projectFilePath)[0]).externalPath
if not os.path.exists(filePath):
raise RuntimeError("Could not find external data: " +
filePath)
# Give the new info to the operator
self.mainOperator.Dataset[index].setValue(datasetInfo)
self._dirty = False
def configure_operator_with_parsed_args(self, parsed_args):
"""
Helper function for headless workflows.
Configures this applet's top-level operator according to the settings provided in ``parsed_args``.
:param parsed_args: Must be an ``argparse.Namespace`` as returned by :py:meth:`parse_known_cmdline_args()`.
"""
# TODO: Support image stack inputs by checking for globstrings and converting to hdf5.
input_paths = parsed_args.input_files
input_infos = []
for p in input_paths:
info = DatasetInfo()
info.location = DatasetInfo.Location.FileSystem
# Convert all paths to absolute
# (otherwise they are relative to the project file, which probably isn't what the user meant)
comp = PathComponents(p)
comp.externalPath = os.path.abspath(comp.externalPath)
info.filePath = comp.totalPath()
info.nickname = comp.filenameBase
input_infos.append(info)
opDataSelection = self.topLevelOperator
opDataSelection.DatasetGroup.resize( len(input_infos) )
for lane_index, info in enumerate(input_infos):
# Only one dataset role in pixel classification
opDataSelection.DatasetGroup[lane_index][0].setValue( info )
def configure_operator_with_parsed_args(self, parsed_args):
"""
Helper function for headless workflows.
Configures this applet's top-level operator according to the settings provided in ``parsed_args``.
:param parsed_args: Must be an ``argparse.Namespace`` as returned by :py:meth:`parse_known_cmdline_args()`.
"""
input_paths = parsed_args.input_files
# If the user doesn't want image stacks to be copied inte the project file,
# we generate hdf5 volumes in a temporary directory and use those files instead.
if parsed_args.preconvert_stacks:
import tempfile
input_paths = self.convertStacksToH5( input_paths, tempfile.gettempdir() )
input_infos = []
for p in input_paths:
info = DatasetInfo()
info.location = DatasetInfo.Location.FileSystem
# Convert all paths to absolute
# (otherwise they are relative to the project file, which probably isn't what the user meant)
comp = PathComponents(p)
comp.externalPath = os.path.abspath(comp.externalPath)
info.filePath = comp.totalPath()
info.nickname = comp.filenameBase
input_infos.append(info)
opDataSelection = self.topLevelOperator
opDataSelection.DatasetGroup.resize( len(input_infos) )
for lane_index, info in enumerate(input_infos):
# Only one dataset role in pixel classification
opDataSelection.DatasetGroup[lane_index][0].setValue( info )
def _deserializeFromHdf5(self, topGroup, groupVersion, hdf5File, projectFilePath, headless):
self._projectFilePath = projectFilePath
self.initWithoutTopGroup(hdf5File, projectFilePath)
# normally the serializer is not dirty after loading a project file
# however, when the file was corrupted, the user has the possibility
# to save the fixed file after loading it.
dirty = False
infoDir = topGroup['infos']
self.topLevelOperator.Dataset.resize( len(infoDir) )
for index, (infoGroupName, infoGroup) in enumerate( sorted(infoDir.items()) ):
datasetInfo = DatasetInfo()
# Make a reverse-lookup of the location storage strings
LocationLookup = { v:k for k,v in self.LocationStrings.items() }
datasetInfo.location = LocationLookup[ str(infoGroup['location'].value) ]
# Write to the 'private' members to avoid resetting the dataset id
datasetInfo._filePath = str(infoGroup['filePath'].value)
datasetInfo._datasetId = str(infoGroup['datasetId'].value)
# Deserialize the "allow labels" flag
try:
datasetInfo.allowLabels = infoGroup['allowLabels'].value
except KeyError:
pass
# Deserialize the axisorder (if present)
try:
datasetInfo.axisorder = infoGroup['axisorder'].value
except KeyError:
pass
# If the data is supposed to be in the project,
# check for it now.
if datasetInfo.location == DatasetInfo.Location.ProjectInternal:
if not datasetInfo.datasetId in topGroup['local_data'].keys():
raise RuntimeError("Corrupt project file. Could not find data for " + infoGroupName)
# If the data is supposed to exist outside the project, make sure it really does.
if datasetInfo.location == DatasetInfo.Location.FileSystem:
pathData = PathComponents( datasetInfo.filePath, os.path.split(projectFilePath)[0])
filePath = pathData.externalPath
if not os.path.exists(filePath):
if headless:
raise RuntimeError("Could not find data at " + filePath)
filt = "Image files (" + ' '.join('*.' + x for x in OpDataSelection.SupportedExtensions) + ')'
newpath = self.repairFile(filePath, filt)
newpath = newpath+pathData.internalPath
datasetInfo._filePath = getPathVariants(newpath , os.path.split(projectFilePath)[0])[0]
dirty = True
# Give the new info to the operator
self.topLevelOperator.Dataset[index].setValue(datasetInfo)
self._dirty = dirty
def deserializeFromHdf5(self, hdf5File, projectFilePath, headless=False):
# Check the overall file version
ilastikVersion = hdf5File["ilastikVersion"].value
# This is the v0.5 import deserializer. Don't work with 0.6 projects (or anything else).
if ilastikVersion != 0.5:
return
# The 'working directory' for the purpose of constructing absolute
# paths from relative paths is the project file's directory.
projectDir = os.path.split(projectFilePath)[0]
self.topLevelOperator.WorkingDirectory.setValue(projectDir)
# Access the top group and the info group
try:
#dataset = hdf5File["DataSets"]["dataItem00"]["data"]
dataDir = hdf5File["DataSets"]
except KeyError:
# If our group (or subgroup) doesn't exist, then make sure the operator is empty
self.topLevelOperator.DatasetGroup.resize(0)
return
self.topLevelOperator.DatasetGroup.resize(len(dataDir))
for index, (datasetDirName,
datasetDir) in enumerate(sorted(dataDir.items())):
datasetInfo = DatasetInfo()
# We'll set up the link to the dataset in the old project file,
# but we'll set the location to ProjectInternal so that it will
# be copied to the new file when the project is saved.
datasetInfo.location = DatasetInfo.Location.ProjectInternal
# Some older versions of ilastik 0.5 stored the data in tzyxc order.
# Some power-users can enable a command-line flag that tells us to
# transpose the data back to txyzc order when we import the old project.
default_axis_order = ilastik.utility.globals.ImportOptions.default_axis_order
if default_axis_order is not None:
import warnings
warnings.warn(
"Using a strange axis order to import ilastik 0.5 projects: {}"
.format(default_axis_order))
datasetInfo.axistags = vigra.defaultAxistags(
default_axis_order)
# Write to the 'private' members to avoid resetting the dataset id
totalDatasetPath = str(projectFilePath + '/DataSets/' +
datasetDirName + '/data')
datasetInfo._filePath = totalDatasetPath
datasetInfo._datasetId = datasetDirName # Use the old dataset name as the new dataset id
datasetInfo.nickname = "{} (imported from v0.5)".format(
datasetDirName)
# Give the new info to the operator
self.topLevelOperator.DatasetGroup[index][0].setValue(datasetInfo)
def deserializeFromHdf5(self, hdf5File, projectFilePath):
with Tracer(traceLogger):
# Check the overall file version
ilastikVersion = hdf5File["ilastikVersion"].value
# This is the v0.5 import deserializer. Don't work with 0.6 projects (or anything else).
if ilastikVersion != 0.5:
return
# The 'working directory' for the purpose of constructing absolute
# paths from relative paths is the project file's directory.
projectDir = os.path.split(projectFilePath)[0]
self.mainOperator.WorkingDirectory.setValue(projectDir)
# These project file inputs are required, but are not used because the data is treated as "external"
self.mainOperator.ProjectDataGroup.setValue('DataSets')
self.mainOperator.ProjectFile.setValue(hdf5File)
# Access the top group and the info group
try:
#dataset = hdf5File["DataSets"]["dataItem00"]["data"]
dataDir = hdf5File["DataSets"]
except KeyError:
# If our group (or subgroup) doesn't exist, then make sure the operator is empty
self.mainOperator.Dataset.resize(0)
return
self.mainOperator.Dataset.resize(len(dataDir))
for index, (datasetDirName,
datasetDir) in enumerate(sorted(dataDir.items())):
datasetInfo = DatasetInfo()
# Since we are importing from a 0.5 file, all datasets will be external
# to the project (pulled in from the old file as hdf5 datasets)
datasetInfo.location = DatasetInfo.Location.FileSystem
# Some older versions of ilastik 0.5 stored the data in tzyxc order.
# Some power-users can enable a command-line flag that tells us to
# transpose the data back to txyzc order when we import the old project.
if ilastik.utility.globals.ImportOptions.default_axis_order is not None:
datasetInfo.axisorder = ilastik.utility.globals.ImportOptions.default_axis_order
# Write to the 'private' members to avoid resetting the dataset id
totalDatasetPath = projectFilePath + '/DataSets/' + datasetDirName + '/data'
datasetInfo._filePath = str(totalDatasetPath)
datasetInfo._datasetId = datasetDirName # Use the old dataset name as the new dataset id
# Give the new info to the operator
self.mainOperator.Dataset[index].setValue(datasetInfo)
def deserializeFromHdf5(self, hdf5File, projectFilePath, headless = False):
# Check the overall file version
ilastikVersion = hdf5File["ilastikVersion"].value
# This is the v0.5 import deserializer. Don't work with 0.6 projects (or anything else).
if ilastikVersion != 0.5:
return
# The 'working directory' for the purpose of constructing absolute
# paths from relative paths is the project file's directory.
projectDir = os.path.split(projectFilePath)[0]
self.topLevelOperator.WorkingDirectory.setValue( projectDir )
# Access the top group and the info group
try:
#dataset = hdf5File["DataSets"]["dataItem00"]["data"]
dataDir = hdf5File["DataSets"]
except KeyError:
# If our group (or subgroup) doesn't exist, then make sure the operator is empty
self.topLevelOperator.DatasetGroup.resize( 0 )
return
self.topLevelOperator.DatasetGroup.resize( len(dataDir) )
for index, (datasetDirName, datasetDir) in enumerate( sorted(dataDir.items()) ):
datasetInfo = DatasetInfo()
# We'll set up the link to the dataset in the old project file,
# but we'll set the location to ProjectInternal so that it will
# be copied to the new file when the project is saved.
datasetInfo.location = DatasetInfo.Location.ProjectInternal
# Some older versions of ilastik 0.5 stored the data in tzyxc order.
# Some power-users can enable a command-line flag that tells us to
# transpose the data back to txyzc order when we import the old project.
default_axis_order = ilastik.utility.globals.ImportOptions.default_axis_order
if default_axis_order is not None:
import warnings
warnings.warn( "Using a strange axis order to import ilastik 0.5 projects: {}".format( default_axis_order ) )
datasetInfo.axistags = vigra.defaultAxistags(default_axis_order)
# Write to the 'private' members to avoid resetting the dataset id
totalDatasetPath = projectFilePath + '/DataSets/' + datasetDirName + '/data'
datasetInfo._filePath = totalDatasetPath
datasetInfo._datasetId = datasetDirName # Use the old dataset name as the new dataset id
datasetInfo.nickname = "{} (imported from v0.5)".format( datasetDirName )
# Give the new info to the operator
self.topLevelOperator.DatasetGroup[index][0].setValue(datasetInfo)
def deserializeFromHdf5(self, hdf5File, projectFilePath):
with Tracer(traceLogger):
# Check the overall file version
ilastikVersion = hdf5File["ilastikVersion"].value
# This is the v0.5 import deserializer. Don't work with 0.6 projects (or anything else).
if ilastikVersion != 0.5:
return
# The 'working directory' for the purpose of constructing absolute
# paths from relative paths is the project file's directory.
projectDir = os.path.split(projectFilePath)[0]
self.mainOperator.WorkingDirectory.setValue( projectDir )
# These project file inputs are required, but are not used because the data is treated as "external"
self.mainOperator.ProjectDataGroup.setValue( 'DataSets' )
self.mainOperator.ProjectFile.setValue(hdf5File)
# Access the top group and the info group
try:
#dataset = hdf5File["DataSets"]["dataItem00"]["data"]
dataDir = hdf5File["DataSets"]
except KeyError:
# If our group (or subgroup) doesn't exist, then make sure the operator is empty
self.mainOperator.Dataset.resize( 0 )
return
self.mainOperator.Dataset.resize( len(dataDir) )
for index, (datasetDirName, datasetDir) in enumerate( sorted(dataDir.items()) ):
datasetInfo = DatasetInfo()
# Since we are importing from a 0.5 file, all datasets will be external
# to the project (pulled in from the old file as hdf5 datasets)
datasetInfo.location = DatasetInfo.Location.FileSystem
# Some older versions of ilastik 0.5 stored the data in tzyxc order.
# Some power-users can enable a command-line flag that tells us to
# transpose the data back to txyzc order when we import the old project.
if ilastik.utility.globals.ImportOptions.default_axis_order is not None:
datasetInfo.axisorder = ilastik.utility.globals.ImportOptions.default_axis_order
# Write to the 'private' members to avoid resetting the dataset id
totalDatasetPath = projectFilePath + '/DataSets/' + datasetDirName + '/data'
datasetInfo._filePath = str(totalDatasetPath)
datasetInfo._datasetId = datasetDirName # Use the old dataset name as the new dataset id
# Give the new info to the operator
self.mainOperator.Dataset[index].setValue(datasetInfo)
def _deserializeFromHdf5(self, topGroup, groupVersion, hdf5File, projectFilePath):
with Tracer(traceLogger):
self._projectFilePath = projectFilePath
self.initWithoutTopGroup(hdf5File, projectFilePath)
infoDir = topGroup['infos']
self.mainOperator.Dataset.resize( len(infoDir) )
for index, (infoGroupName, infoGroup) in enumerate( sorted(infoDir.items()) ):
datasetInfo = DatasetInfo()
# Make a reverse-lookup of the location storage strings
LocationLookup = { v:k for k,v in self.LocationStrings.items() }
datasetInfo.location = LocationLookup[ str(infoGroup['location'].value) ]
# Write to the 'private' members to avoid resetting the dataset id
datasetInfo._filePath = str(infoGroup['filePath'].value)
datasetInfo._datasetId = str(infoGroup['datasetId'].value)
# Deserialize the "allow labels" flag
try:
datasetInfo.allowLabels = infoGroup['allowLabels'].value
except KeyError:
pass
# Deserialize the axisorder (if present)
try:
datasetInfo.axisorder = infoGroup['axisorder'].value
except KeyError:
if ilastik.utility.globals.ImportOptions.default_axis_order is not None:
datasetInfo.axisorder = ilastik.utility.globals.ImportOptions.default_axis_order
# If the data is supposed to be in the project,
# check for it now.
if datasetInfo.location == DatasetInfo.Location.ProjectInternal:
if not datasetInfo.datasetId in topGroup['local_data'].keys():
raise RuntimeError("Corrupt project file. Could not find data for " + infoGroupName)
# If the data is supposed to exist outside the project, make sure it really does.
if datasetInfo.location == DatasetInfo.Location.FileSystem:
filePath = PathComponents( datasetInfo.filePath, os.path.split(projectFilePath)[0] ).externalPath
if not os.path.exists(filePath):
raise RuntimeError("Could not find external data: " + filePath)
# Give the new info to the operator
self.mainOperator.Dataset[index].setValue(datasetInfo)
self._dirty = False
def create_default_headless_dataset_info(cls, filepath):
"""
filepath may be a globstring or a full hdf5 path+dataset
"""
comp = PathComponents(filepath)
nickname = comp.filenameBase
# Remove globstring syntax.
if '*' in nickname:
nickname = nickname.replace('*', '')
if os.path.pathsep in nickname:
nickname = PathComponents(nickname.split(os.path.pathsep)[0]).fileNameBase
info = DatasetInfo()
info.location = DatasetInfo.Location.FileSystem
info.nickname = nickname
info.filePath = filepath
# Convert all (non-url) paths to absolute
# (otherwise they are relative to the project file, which probably isn't what the user meant)
if not isUrl(filepath):
comp.externalPath = os.path.abspath(comp.externalPath)
info.filePath = comp.totalPath()
return info
def _readDatasetInfo(self, infoGroup, localDataGroup, projectFilePath, headless):
# Unready datasets are represented with an empty group.
if len( infoGroup ) == 0:
return None, False
datasetInfo = DatasetInfo()
# Make a reverse-lookup of the location storage strings
LocationLookup = { v:k for k,v in self.LocationStrings.items() }
datasetInfo.location = LocationLookup[ str(infoGroup['location'].value) ]
# Write to the 'private' members to avoid resetting the dataset id
datasetInfo._filePath = infoGroup['filePath'].value
datasetInfo._datasetId = infoGroup['datasetId'].value
try:
datasetInfo.allowLabels = infoGroup['allowLabels'].value
except KeyError:
pass
try:
datasetInfo.drange = tuple( infoGroup['drange'].value )
except KeyError:
pass
try:
datasetInfo.nickname = infoGroup['nickname'].value
except KeyError:
datasetInfo.nickname = PathComponents(datasetInfo.filePath).filenameBase
try:
tags = vigra.AxisTags.fromJSON( infoGroup['axistags'].value )
datasetInfo.axistags = tags
except KeyError:
# Old projects just have an 'axisorder' field instead of full axistags
try:
axisorder = infoGroup['axisorder'].value
datasetInfo.axistags = vigra.defaultAxistags(axisorder)
except KeyError:
pass
# If the data is supposed to be in the project,
# check for it now.
if datasetInfo.location == DatasetInfo.Location.ProjectInternal:
if not datasetInfo.datasetId in localDataGroup.keys():
raise RuntimeError("Corrupt project file. Could not find data for " + infoGroup.name)
dirty = False
# If the data is supposed to exist outside the project, make sure it really does.
if datasetInfo.location == DatasetInfo.Location.FileSystem and not isUrl(datasetInfo.filePath):
pathData = PathComponents( datasetInfo.filePath, os.path.split(projectFilePath)[0])
filePath = pathData.externalPath
if not os.path.exists(filePath):
if headless:
raise RuntimeError("Could not find data at " + filePath)
filt = "Image files (" + ' '.join('*.' + x for x in OpDataSelection.SupportedExtensions) + ')'
newpath = self.repairFile(filePath, filt)
if pathData.internalPath is not None:
newpath += pathData.internalPath
datasetInfo._filePath = getPathVariants(newpath , os.path.split(projectFilePath)[0])[0]
dirty = True
return datasetInfo, dirty
def _readDatasetInfo(self, infoGroup, localDataGroup, projectFilePath, headless):
# Unready datasets are represented with an empty group.
if len( infoGroup ) == 0:
return None, False
datasetInfo = DatasetInfo()
# Make a reverse-lookup of the location storage strings
LocationLookup = { v:k for k,v in self.LocationStrings.items() }
datasetInfo.location = LocationLookup[ str(infoGroup['location'].value) ]
# Write to the 'private' members to avoid resetting the dataset id
datasetInfo._filePath = infoGroup['filePath'].value
datasetInfo._datasetId = infoGroup['datasetId'].value
try:
datasetInfo.allowLabels = infoGroup['allowLabels'].value
except KeyError:
pass
try:
datasetInfo.drange = tuple( infoGroup['drange'].value )
except KeyError:
pass
try:
datasetInfo.nickname = infoGroup['nickname'].value
except KeyError:
datasetInfo.nickname = PathComponents(datasetInfo.filePath).filenameBase
try:
datasetInfo.fromstack = infoGroup['fromstack'].value
except KeyError:
# Guess based on the storage setting and original filepath
datasetInfo.fromstack = ( datasetInfo.location == DatasetInfo.Location.ProjectInternal
and ( ('?' in datasetInfo._filePath) or (os.path.pathsep in datasetInfo._filePath) ) )
try:
tags = vigra.AxisTags.fromJSON( infoGroup['axistags'].value )
datasetInfo.axistags = tags
except KeyError:
# Old projects just have an 'axisorder' field instead of full axistags
try:
axisorder = infoGroup['axisorder'].value
datasetInfo.axistags = vigra.defaultAxistags(axisorder)
except KeyError:
pass
try:
start, stop = map( tuple, infoGroup['subvolume_roi'].value )
datasetInfo.subvolume_roi = (start, stop)
except KeyError:
pass
# If the data is supposed to be in the project,
# check for it now.
if datasetInfo.location == DatasetInfo.Location.ProjectInternal:
if not datasetInfo.datasetId in localDataGroup.keys():
raise RuntimeError("Corrupt project file. Could not find data for " + infoGroup.name)
dirty = False
# If the data is supposed to exist outside the project, make sure it really does.
if datasetInfo.location == DatasetInfo.Location.FileSystem and not isUrl(datasetInfo.filePath):
pathData = PathComponents( datasetInfo.filePath, os.path.split(projectFilePath)[0])
filePath = pathData.externalPath
if not os.path.exists(filePath):
if headless:
raise RuntimeError("Could not find data at " + filePath)
filt = "Image files (" + ' '.join('*.' + x for x in OpDataSelection.SupportedExtensions) + ')'
newpath = self.repairFile(filePath, filt)
if pathData.internalPath is not None:
newpath += pathData.internalPath
datasetInfo._filePath = getPathVariants(newpath , os.path.split(projectFilePath)[0])[0]
dirty = True
return datasetInfo, dirty
def configure_operator_with_parsed_args(self, parsed_args):
"""
Helper function for headless workflows.
Configures this applet's top-level operator according to the settings provided in ``parsed_args``.
:param parsed_args: Must be an ``argparse.Namespace`` as returned by :py:meth:`parse_known_cmdline_args()`.
"""
role_names = self.topLevelOperator.DatasetRoles.value
role_paths = collections.OrderedDict()
if role_names:
for role_index, role_name in enumerate(role_names):
arg_name = self._role_name_to_arg_name(role_name)
input_paths = getattr(parsed_args, arg_name)
role_paths[role_index] = input_paths
if parsed_args.input_files:
# We allow the file list to go to the 'default' role, but only if no other roles were explicitly configured.
for role_index, input_paths in role_paths.items():
if input_paths:
# FIXME: This error message could be more helpful.
role_args = map(self._role_name_to_arg_name, role_names)
role_args = map(lambda s: '--' + s, role_args)
role_args_str = ", ".join(role_args)
raise Exception(
"Invalid command line arguments: All roles must be configured explicitly.\n"
"Use the following flags to specify which files are matched with which inputs:\n"
+ role_args_str)
role_paths = {0: parsed_args.input_files}
for role_index, input_paths in role_paths.items():
# If the user doesn't want image stacks to be copied into the project file,
# we generate hdf5 volumes in a temporary directory and use those files instead.
if parsed_args.preconvert_stacks:
import tempfile
input_paths = self.convertStacksToH5(input_paths,
tempfile.gettempdir())
input_infos = []
for p in input_paths:
info = DatasetInfo()
info.location = DatasetInfo.Location.FileSystem
info.filePath = p
comp = PathComponents(p)
# Convert all (non-url) paths to absolute
# (otherwise they are relative to the project file, which probably isn't what the user meant)
if not isUrl(p):
comp.externalPath = os.path.abspath(comp.externalPath)
info.filePath = comp.totalPath()
info.nickname = comp.filenameBase
# Remove globstring syntax.
if '*' in info.nickname:
info.nickname = info.nickname.replace('*', '')
if os.path.pathsep in info.nickname:
info.nickname = PathComponents(
info.nickname.split(os.path.pathsep)[0]).fileNameBase
input_infos.append(info)
opDataSelection = self.topLevelOperator
existing_lanes = len(opDataSelection.DatasetGroup)
opDataSelection.DatasetGroup.resize(
max(len(input_infos), existing_lanes))
for lane_index, info in enumerate(input_infos):
opDataSelection.DatasetGroup[lane_index][role_index].setValue(
info)
need_warning = False
for lane_index in range(len(input_infos)):
output_slot = opDataSelection.ImageGroup[lane_index][
role_index]
if output_slot.meta.prefer_2d:
need_warning = True
break
if need_warning:
logger.warn(
"*******************************************************************************************"
)
logger.warn(
"Some of your input data is stored in a format that is not efficient for 3D access patterns."
)
logger.warn(
"Performance may suffer as a result. For best performance, use a chunked HDF5 volume."
)
logger.warn(
"*******************************************************************************************"
)
def configure_operator_with_parsed_args(self, parsed_args):
"""
Helper function for headless workflows.
Configures this applet's top-level operator according to the settings provided in ``parsed_args``.
:param parsed_args: Must be an ``argparse.Namespace`` as returned by :py:meth:`parse_known_cmdline_args()`.
"""
role_names = self.topLevelOperator.DatasetRoles.value
role_paths = collections.OrderedDict()
if role_names:
for role_index, role_name in enumerate(role_names):
arg_name = self._role_name_to_arg_name(role_name)
input_paths = getattr(parsed_args, arg_name)
role_paths[role_index] = input_paths
if parsed_args.input_files:
# We allow the file list to go to the 'default' role, but only if no other roles were explicitly configured.
for role_index, input_paths in role_paths.items():
if input_paths:
# FIXME: This error message could be more helpful.
role_args = map( self._role_name_to_arg_name, role_names )
role_args = map( lambda s: '--' + s, role_args )
role_args_str = ", ".join( role_args )
raise Exception("Invalid command line arguments: All roles must be configured explicitly.\n"
"Use the following flags to specify which files are matched with which inputs:\n"
+ role_args_str )
role_paths = { 0 : parsed_args.input_files }
for role_index, input_paths in role_paths.items():
# If the user doesn't want image stacks to be copied into the project file,
# we generate hdf5 volumes in a temporary directory and use those files instead.
if parsed_args.preconvert_stacks:
import tempfile
input_paths = self.convertStacksToH5( input_paths, tempfile.gettempdir() )
input_infos = []
for p in input_paths:
info = DatasetInfo()
info.location = DatasetInfo.Location.FileSystem
info.filePath = p
comp = PathComponents(p)
# Convert all (non-url) paths to absolute
# (otherwise they are relative to the project file, which probably isn't what the user meant)
if not isUrl(p):
comp.externalPath = os.path.abspath(comp.externalPath)
info.filePath = comp.totalPath()
info.nickname = comp.filenameBase
# Remove globstring syntax.
if '*' in info.nickname:
info.nickname = info.nickname.replace('*', '')
if os.path.pathsep in info.nickname:
info.nickname = PathComponents(info.nickname.split(os.path.pathsep)[0]).fileNameBase
input_infos.append(info)
opDataSelection = self.topLevelOperator
existing_lanes = len(opDataSelection.DatasetGroup)
opDataSelection.DatasetGroup.resize( max(len(input_infos), existing_lanes) )
for lane_index, info in enumerate(input_infos):
opDataSelection.DatasetGroup[lane_index][role_index].setValue( info )
need_warning = False
for lane_index in range(len(input_infos)):
output_slot = opDataSelection.ImageGroup[lane_index][role_index]
if output_slot.meta.prefer_2d:
need_warning = True
break
if need_warning:
logger.warn("*******************************************************************************************")
logger.warn("Some of your input data is stored in a format that is not efficient for 3D access patterns.")
logger.warn("Performance may suffer as a result. For best performance, use a chunked HDF5 volume.")
logger.warn("*******************************************************************************************")
