def _generate_cell_indices_seg_ids(pop_id, indices_segids, network):
a = {}
pop = network.get_child(pop_id, 'populations')
if not isinstance(indices_segids, str) or not ':' in indices_segids:
seg_ids = None
indices = indices_segids
else:
indices = indices_segids.split(':')[0]
seg_id_info = indices_segids.split(':')[1]
l = parse_list_like(seg_id_info)
print_v('Parsed %s as %s'%(seg_id_info, l))
seg_ids = l
if indices=='*':
size = evaluate(pop.size, network.parameters)
for index in range(size):
a[index] = seg_ids
else:
l = parse_list_like(indices)
print_v('Parsed %s (full: %s) as %s'%(indices,indices_segids, l))
for index in l:
a[index] = seg_ids
return a
def load_network_json(filename):
data = load_json(filename)
print_v("Loaded network specification from %s" % filename)
net = Network()
net = _parse_element(data, net)
return net
def load_network_json(filename):
"""
Load a NeuroMLlite network JSON file
"""
data = load_json(filename)
print_v("Loaded network specification from %s"%filename)
net = Network()
net = _parse_element(data, net)
return net
def load_simulation_json(filename):
import json
with open(filename, 'r') as f:
data = json.load(f, object_hook=ascii_encode_dict)
print_v("Loaded simulation specification from %s" % filename)
sim = Simulation()
sim = _parse_element(data, sim)
return sim