def __expand_collection_parameter( trans, input_key, incoming_val, collections_to_match ):
# If subcollectin multirun of data_collection param - value will
# be "hdca_id|subcollection_type" else it will just be hdca_id
if "|" in incoming_val:
encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 )
else:
try:
src = incoming_val[ "src" ]
if src != "hdca":
raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src )
encoded_hdc_id = incoming_val[ "id" ]
subcollection_type = incoming_val.get( 'map_over_type', None )
except TypeError:
encoded_hdc_id = incoming_val
subcollection_type = None
hdc_id = trans.app.security.decode_id( encoded_hdc_id )
hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id )
collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type )
if subcollection_type is not None:
from galaxy.dataset_collections import subcollections
subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type )
return subcollection_elements
else:
hdas = []
for element in hdc.collection.dataset_elements:
hda = element.dataset_instance
hda.element_identifier = element.element_identifier
hdas.append( hda )
return hdas
def collection_classifier( input_key ):
multirun_key = "%s|__collection_multirun__" % input_key
if multirun_key in incoming:
incoming_val = incoming[ multirun_key ]
# If subcollectin multirun of data_collection param - value will
# be "hdca_id|subcollection_type" else it will just be hdca_id
if "|" in incoming_val:
encoded_hdc_id, subcollection_type = incoming_val.split( "|", 1 )
else:
try:
src = incoming_val[ "src" ]
if src != "hdca":
raise exceptions.ToolMetaParameterException( "Invalid dataset collection source type %s" % src )
encoded_hdc_id = incoming_val[ "id" ]
except TypeError:
encoded_hdc_id = incoming_val
subcollection_type = None
hdc_id = trans.app.security.decode_id( encoded_hdc_id )
hdc = trans.sa_session.query( model.HistoryDatasetCollectionAssociation ).get( hdc_id )
collections_to_match.add( input_key, hdc, subcollection_type=subcollection_type )
if subcollection_type is not None:
from galaxy.dataset_collections import subcollections
subcollection_elements = subcollections.split_dataset_collection_instance( hdc, subcollection_type )
return permutations.input_classification.MATCHED, subcollection_elements
else:
hdas = hdc.collection.dataset_instances
return permutations.input_classification.MATCHED, hdas
else:
return permutations.input_classification.SINGLE, incoming[ input_key ]
def __expand_collection_parameter(trans, input_key, incoming_val,
collections_to_match):
# If subcollectin multirun of data_collection param - value will
# be "hdca_id|subcollection_type" else it will just be hdca_id
if "|" in incoming_val:
encoded_hdc_id, subcollection_type = incoming_val.split("|", 1)
else:
try:
src = incoming_val["src"]
if src != "hdca":
raise exceptions.ToolMetaParameterException(
"Invalid dataset collection source type %s" % src)
encoded_hdc_id = incoming_val["id"]
subcollection_type = incoming_val.get('map_over_type', None)
except TypeError:
encoded_hdc_id = incoming_val
subcollection_type = None
hdc_id = trans.app.security.decode_id(encoded_hdc_id)
hdc = trans.sa_session.query(
model.HistoryDatasetCollectionAssociation).get(hdc_id)
collections_to_match.add(input_key,
hdc,
subcollection_type=subcollection_type)
if subcollection_type is not None:
from galaxy.dataset_collections import subcollections
subcollection_elements = subcollections.split_dataset_collection_instance(
hdc, subcollection_type)
return subcollection_elements
else:
hdas = hdc.collection.dataset_instances
return hdas
def collection_classifier(input_key):
multirun_key = "%s|__collection_multirun__" % input_key
if multirun_key in incoming:
incoming_val = incoming[multirun_key]
# If subcollectin multirun of data_collection param - value will
# be "hdca_id|subcollection_type" else it will just be hdca_id
if "|" in incoming_val:
encoded_hdc_id, subcollection_type = incoming_val.split("|", 1)
else:
try:
src = incoming_val["src"]
if src != "hdca":
raise exceptions.ToolMetaParameterException(
"Invalid dataset collection source type %s" % src)
encoded_hdc_id = incoming_val["id"]
except TypeError:
encoded_hdc_id = incoming_val
subcollection_type = None
hdc_id = trans.app.security.decode_id(encoded_hdc_id)
hdc = trans.sa_session.query(
model.HistoryDatasetCollectionAssociation).get(hdc_id)
collections_to_match.add(input_key,
hdc,
subcollection_type=subcollection_type)
if subcollection_type is not None:
from galaxy.dataset_collections import subcollections
subcollection_elements = subcollections.split_dataset_collection_instance(
hdc, subcollection_type)
return permutations.input_classification.MATCHED, subcollection_elements
else:
hdas = hdc.collection.dataset_instances
return permutations.input_classification.MATCHED, hdas
else:
return permutations.input_classification.SINGLE, incoming[
input_key]