def preprocess_edge_types(network, edge_population):
# Fix for sonata/300_pointneurons
EdgeAdaptor.preprocess_edge_types(network, edge_population)
edge_types_table = edge_population.types_table
edge_type_ids = np.unique(edge_population.type_ids)
for et_id in edge_type_ids:
edge_type = edge_types_table[et_id]
if 'model_template' in edge_types_table.columns:
model_template = edge_type['model_template']
if model_template.startswith('nest'):
edge_type['model_template'] = model_template[5:]
def patch_adaptor(adaptor, edge_group):
edge_adaptor = EdgeAdaptor.patch_adaptor(adaptor, edge_group)
if 'weight_function' not in edge_group.all_columns and 'syn_weight' in edge_group.all_columns:
adaptor.syn_weight = types.MethodType(point_syn_weight, adaptor)
return edge_adaptor
def patch_adaptor(cls, adaptor, edge_group):
edge_adaptor = EdgeAdaptor.patch_adaptor(adaptor, edge_group)
if 'sec_id' in edge_group.all_columns:
edge_adaptor.aff_sec_id = types.MethodType(aff_sec_id_old, adaptor)
elif 'afferent_section_id' in edge_group.all_columns:
edge_adaptor.aff_sec_id = types.MethodType(aff_sec_id, adaptor)
else:
edge_adaptor.aff_sec_id = types.MethodType(ret_none_function,
adaptor)
if 'sec_x' in edge_group.all_columns:
edge_adaptor.aff_sec_pos = types.MethodType(
aff_sec_pos_old, adaptor)
elif 'afferent_section_pos' in edge_group.all_columns:
edge_adaptor.aff_sec_pos = types.MethodType(aff_sec_pos, adaptor)
else:
edge_adaptor.aff_sec_pos = types.MethodType(
ret_none_function, adaptor)
return edge_adaptor