def precreate_output_collections(self, history, params):
# params is just one sample tool param execution with parallelized
# collection replaced with a specific dataset. Need to replace this
# with the collection and wrap everything up so can evaluate output
# label.
trans = self.trans
params.update(
self.collection_info.collections
) # Replace datasets with source collections for labelling outputs.
collection_instances = {}
implicit_inputs = self.implicit_inputs
implicit_collection_jobs = model.ImplicitCollectionJobs()
for output_name, output in self.tool.outputs.items():
if filter_output(output, self.example_params):
continue
output_collection_name = self.output_name(trans, history, params,
output)
effective_structure = self._mapped_output_structure(trans, output)
collection_instance = trans.app.dataset_collections_service.precreate_dataset_collection_instance(
trans=trans,
parent=history,
name=output_collection_name,
implicit_inputs=implicit_inputs,
implicit_output_name=output_name,
structure=effective_structure,
)
collection_instance.implicit_collection_jobs = implicit_collection_jobs
collection_instances[output_name] = collection_instance
trans.sa_session.add(collection_instance)
# Needed to flush the association created just above with
# job.add_output_dataset_collection.
trans.sa_session.flush()
self.implicit_collections = collection_instances
def precreate_output_collections(self, history, params):
# params is just one sample tool param execution with parallelized
# collection replaced with a specific dataset. Need to replace this
# with the collection and wrap everything up so can evaluate output
# label.
trans = self.trans
params.update(self.collection_info.collections) # Replace datasets with source collections for labelling outputs.
collection_instances = {}
implicit_inputs = self.implicit_inputs
implicit_collection_jobs = model.ImplicitCollectionJobs()
for output_name, output in self.tool.outputs.items():
if filter_output(output, self.example_params):
continue
output_collection_name = self.output_name(trans, history, params, output)
effective_structure = self._mapped_output_structure(trans, output)
collection_instance = trans.app.dataset_collections_service.precreate_dataset_collection_instance(
trans=trans,
parent=history,
name=output_collection_name,
structure=effective_structure,
implicit_inputs=implicit_inputs,
implicit_output_name=output_name,
)
collection_instance.implicit_collection_jobs = implicit_collection_jobs
collection_instances[output_name] = collection_instance
trans.sa_session.add(collection_instance)
# Needed to flush the association created just above with
# job.add_output_dataset_collection.
trans.sa_session.flush()
self.implicit_collections = collection_instances
def precreate_output_collections(self, history, params):
# params is just one sample tool param execution with parallelized
# collection replaced with a specific dataset. Need to replace this
# with the collection and wrap everything up so can evaluate output
# label.
trans = self.trans
params.update(
self.collection_info.collections
) # Replace datasets with source collections for labelling outputs.
collection_instances = {}
implicit_inputs = self.implicit_inputs
implicit_collection_jobs = model.ImplicitCollectionJobs()
# trying to guess these filters at the collection levell is tricky because
# the filter condition could vary from element to element. Just do best we
# we can for now.
example_params = self.example_params.copy()
# walk through and optional replace runtime values with None, assume they
# would have been replaced by now if they were going to be set.
def replace_optional_runtime_values(path, key, value):
if is_runtime_value(value):
return key, None
return key, value
example_params = remap(example_params,
visit=replace_optional_runtime_values)
for output_name, output in self.tool.outputs.items():
if filter_output(self.tool, output, example_params):
continue
output_collection_name = self.output_name(trans, history, params,
output)
effective_structure = self._mapped_output_structure(trans, output)
collection_instance = trans.app.dataset_collection_manager.precreate_dataset_collection_instance(
trans=trans,
parent=history,
name=output_collection_name,
structure=effective_structure,
implicit_inputs=implicit_inputs,
implicit_output_name=output_name,
completed_collection=self.completed_jobs,
)
collection_instance.implicit_collection_jobs = implicit_collection_jobs
collection_instances[output_name] = collection_instance
trans.sa_session.add(collection_instance)
# Needed to flush the association created just above with
# job.add_output_dataset_collection.
trans.sa_session.flush()
self.implicit_collections = collection_instances