import numpy as np
[docs]class NodeRow(object):
@property
def with_dynamics_params(self):
return False
[docs]class EdgeRow(object):
@property
def with_dynamics_params(self):
return False
[docs]class NodesFile(object):
def __init__(self, N):
self._network_name = 'test_bionet'
self._version = None
self._iter_index = 0
self._nrows = 0
self._node_types_table = None
self._N = N
self._rot_delta = 360.0/float(N)
self._node_types_table = {
101: {
'pop_name': 'bio_exc', 'node_type_id': 101, 'model_type': 'biophysical',
'morphology': 'be_morphology.swc',
'dynamics_params': 'be_dynamics.json',
'ei': 'e'
},
102: {
'pop_name': 'point_exc', 'node_type_id': 102, 'model_type': 'point_IntFire1',
'dynamics_params': 'pe_dynamics.json',
'ei': 'e'
},
103: {
'pop_name': 'bio_inh', 'node_type_id': 103, 'model_type': 'biophysical',
'morphology': 'bi_morphology.swc',
'dynamics_params': 'bi_dynamics.json',
'ei': 'i'
},
104: {
'pop_name': 'point_inh', 'node_type_id': 104, 'model_type': 'point_IntFire1',
'dynamics_params': 'bi_dynamics.json',
'ei': 'i'
}
}
@property
def name(self):
"""name of network containing these nodes"""
return self._network_name
@property
def version(self):
return self._version
@property
def gids(self):
raise NotImplementedError()
@property
def node_types_table(self):
return self._node_types_table
[docs] def load(self, nodes_file, node_types_file):
raise NotImplementedError()
[docs] def get_node(self, gid, cache=False):
return self[gid]
def __len__(self):
return self._N
def __iter__(self):
self._iter_index = 0
return self
[docs] def next(self):
if self._iter_index >= len(self):
raise StopIteration
node_row = self[self._iter_index]
self._iter_index += 1
return node_row
def __getitem__(self, gid):
node_props = {'positions': np.random.rand(3), 'rotation': self._rot_delta*gid, 'weight': 0.0001*gid}
return NodeRow(gid, node_props, self.__get_node_type_props(gid))
def __get_node_type_props(self, gid):
if gid <= self._N/4:
return self._node_types_table[101]
elif gid <= self._N/2:
return self._node_types_table[102]
elif gid <= self._N*3/4:
return self._node_types_table[103]
else:
return self._node_types_table[104]
[docs]class EdgesFile(object):
def __init__(self, target_nodes, source_nodes):
self._target_nodes = target_nodes
self._source_nodes = source_nodes
self._edge_type_props = [
{
'node_type_id': 1,
'target_query': 'model_type="biophysical"', 'source_query': 'ei="e"',
'syn_weight': .10,
'syn_targets': ['dend', 'apical'],
'dynamics_params': 'biophys_exc.json'
},
{
'node_type_id': 2,
'target_query': 'model_type="point_IntFire1"', 'source_query': 'ei="e"',
'syn_weight': .20,
'dynamics_params': 'point_exc.json'
},
{
'node_type_id': 3,
'target_query': 'model_type="biophysical"', 'source_query': 'ei="i"',
'syn_weight': -.10,
'syn_targets': ['soma', 'dend'],
'dynamics_params': 'biophys_inh.json'
},
{
'node_type_id': 4,
'target_query': 'model_type="point_IntFire1"', 'source_query': 'ei="i"',
'syn_weight': -.20,
'dynamics_params': 'point_inh.json'
}
]
@property
def source_network(self):
"""Name of network containing the source gids"""
return self._source_nodes.name
@property
def target_network(self):
"""Name of network containing the target gids"""
return self._target_nodes.name
[docs] def load(self, edges_file, edge_types_file):
raise NotImplementedError()
[docs] def edges_itr(self, target_gid):
trg_node = self._target_nodes[target_gid]
for src_node in self._source_nodes:
edge_props = {'syn_weight': trg_node['weight']}
#edge_type_props = {'edge_type_id': 1}
yield EdgeRow(trg_node.gid, src_node.gid, edge_props, self.__get_edge_type_prop(src_node, trg_node))
#def __init__(self, trg_gid, src_gid, edge_props={}, edge_type_props={}):
#raise NotImplementedError()
def __len__(self):
return len(self._source_nodes)*len(self._target_nodes)
def __get_edge_type_prop(self, source_node, target_node):
indx = 0 if source_node['ei'] == 'e' else 2
indx += 0 if target_node['model_type'] == 'biophysical' else 1
return self._edge_type_props[indx]
