def name_to_sid_map(db_connection=None, neuron_type = 'all'):
if db_connection is None:
db_connection = connect.Connection()
name_to_nid = name_to_nid_map(db_connection)
nid_to_sid = db_connection.con.nid_to_sid_map()
name_to_sid = {name: nid_to_sid[nid][0] for (name, nid) in name_to_nid.iteritems()}
return name_to_sid
def get_types_of_neurons(neurons, db_connection=None):
"""Takes a dictionary or list of neurons, and returns
"""
if db_connection is None:
db_connection = connect.Connection()
left_orns = get_neurons_of_type('Left ORN', db_connection)
right_orns = get_neurons_of_type('Right ORN', db_connection)
pns = get_neurons_of_type('DM6 PN', db_connection)
lns = get_neurons_of_type('LN', db_connection)
plns = get_neurons_of_type('potential LN', db_connection )
neuron_types = {'Left ORN': [], 'Right ORN': [], 'DM6 PN': [], 'LN': [], 'Other': []}
if isinstance(neurons, dict):
neurons = neurons.iteritems()
for n in neurons:
if isinstance(n, (list, tuple)):
nname = n[0]
elif isinstance(n, (str, unicode)):
nname = n
if nname in left_orns:
neuron_types['Left ORN'].append(n)
elif nname in right_orns:
neuron_types['Right ORN'].append(n)
elif nname in pns:
neuron_types['DM6 PN'].append(n)
else:
neuron_types['LN'].append(n)
return neuron_types
def name_to_nid_map(db_connection=None, neuron_type = 'all'):
if db_connection is None:
db_connection = connect.Connection()
annotation_list = db_connection.con.annotations()
nids = [i[3] for i in annotation_list]
nnames = [i[0] for i in annotation_list]
name_to_id = dict(zip(nnames, nids))
return name_to_id
def run(self):
while True:
self.s.listen(5)
try:
conn, addr = self.s.accept()
except Exception:
pass
else:
th = connect.Connection(conn, addr)
th.start()
def get_neurons_of_type(annotation, db_connection=None):
"""Returns a list of neuron names for neurons containing a specified annotation.
example annotations: 'DM6 ORN', 'Left ORN', 'Right ORN', 'LN', 'DM6 PN'
"""
if db_connection is None:
db_connection = connect.Connection()
annotation_list = db_connection.con.annotations()
if annotation != 'all':
nnames = [neuron[0] for neuron in annotation_list if annotation in [annot['name'] for annot in neuron[1]]]
elif annotation == 'all':
nnames = [neuron[0] for neuron in annotation_list]
return nnames
def run(self):
while True:
conn, addr = self.s.accept()
connect.Connection(conn, addr).start()
def sid_to_name_map(db_connection=None, neuron_type = 'all'):
if db_connection is None:
db_connection = connect.Connection()
name_to_sid = name_to_sid_map(db_connection)
sid_to_name = {sid: name for (name, sid) in name_to_sid.iteritems()}
return sid_to_name
import connect
import neuron_tools
import numpy as np
import bargraph
import stacked
DB_CONNECTION = connect.Connection()
print "Fetching adjacency matrix"
ADJ = dict()
ADJ['matrix'], ADJ['sk_ids'] = DB_CONNECTION.con.adjacency_matrix()
ADJ['matrix'] = np.array(ADJ['matrix'], int)
NAME_TO_SID = neuron_tools.name_to_sid_map(DB_CONNECTION)
SID_TO_NAME = neuron_tools.sid_to_name_map(DB_CONNECTION)
print "Initialization complete"
class Neuron(object):
"""
Neuron object holds synapse information and does analyses on their connections
"""
def __init__(self, sid):
self.sid = sid
self.adj_index = ADJ['sk_ids'].index(self.sid)
pre_slice = ADJ['matrix'][:, self.adj_index]
post_slice = ADJ['matrix'][self.adj_index, :]
self.contacts = dict()
self.contacts['pre'] = self.get_contacts(pre_slice, ADJ['sk_ids'],
post_slice)
self.contacts['post'] = self.get_contacts(post_slice, ADJ['sk_ids'],
pre_slice)
self.get_contact_types()
#!/usr/bin/env python
'''quick_adj.py: super quick script for fetching and saving adjacency matrix
and skeleton IDs/neuron names.'''
import connect
import numpy as np
import json
if __name__ == "__main__":
db_connection = connect.Connection()
adj = dict()
adj_m, adj['skids'] = db_connection.con.adjacency_matrix()
adj_m = np.array(adj_m, int)
# Go from sk_ids to neuron ids, necessary for name lookup in wiring_diagram
sid_to_nid = db_connection.con.sid_to_nid_map()
adj['nids'] = [sid_to_nid[sid] for sid in adj['skids']]
# Use wiring_diagram to get names from nids
annot_diag = db_connection.con.annotation_diagram()
nids = [i['id'] for i in annot_diag['nodes']]
nnames = [i['name'] for i in annot_diag['nodes']]
nid_to_nname = dict(zip(nids, nnames))
# Add neuron names to adj dict
adj['nnames'] = [nid_to_nname[nid] for nid in adj['nids']]
# adj_nnames = adj['nnames']
# adj_nids = adj['nids']
# adj_skids = adj['skids']