def upload_neurons():
try:
conn = sqlite3.connect(SQLITE_DB_LOC)
cur = conn.cursor()
ev = P.Evidence(title="C. elegans sqlite database")
w = P.Worm()
n = P.Network()
w.neuron_network(n)
# insert neurons.
# save
cur.execute("""
SELECT DISTINCT a.Entity FROM tblrelationship, tblentity a, tblentity b
where EnID1=a.id and Relation = '1515' and EnID2='1'
""")
for r in cur.fetchall():
neuron_name = str(r[0])
n.neuron(P.Neuron(name=neuron_name))
ev.asserts(n)
ev.save()
#second step, get the relationships between them and add them to the graph
print("uploaded neurons")
except Exception:
traceback.print_exc()
finally:
conn.close()
def do_insert(config="default.conf", logging=False):
if config:
if isinstance(config, P.Configure):
pass
elif isinstance(config, str):
config = P.Configure.open(config)
elif isinstance(config, dict):
config = P.Configure().copy(config)
else:
raise Exception("Invalid configuration object " + str(config))
P.connect(conf=config, do_logging=logging)
try:
w = P.Worm()
net = P.Network()
w.neuron_network(net)
w.save()
upload_neurons()
upload_muscles()
upload_lineage_and_descriptions()
upload_synapses()
upload_receptors_and_innexins()
upload_types()
serialize_as_n3()
#infer()
except:
traceback.print_exc()
finally:
P.disconnect()
def main():
c = Configure()
c['neuronscsv'] = 'https://raw.github.com/openworm/data-viz/master/HivePlots/neurons.csv'
c['connectomecsv'] = 'https://raw.github.com/openworm/data-viz/master/HivePlots/connectome.csv'
c['sqldb'] = '/home/markw/work/openworm/PyOpenWorm/db/celegans.db'
c = Data(c)
net = PyOpenWorm.Network(c)
nml_doc = NeuroMLDocument(id="IafNet")
ns = net.neurons()
nml_net = neuroml.Network(id="IafNet")
nml_doc.networks.append(nml_net)
for n in [net.aneuron_nocheck(n) for n in ns]:
s(nml_doc, nml_net, n)
syn0 = ExpOneSynapse(id="syn0", gbase="65nS", erev="0mV", tau_decay="3ms")
for k in net.synapses():
n1 = net.aneuron_nocheck(k[0])
n2 = net.aneuron_nocheck(k[1])
connect(nml_net, n1, n2, 'syn0')
f = "test.nml"
writers.NeuroMLWriter.write(nml_doc, f)
v(f)
def get_neuron_network(self):
"""
Get the network object
:returns: An object to work with the network of the worm
:rtype: PyOpenWorm.Network
"""
return PyOpenWorm.Network()
def upload_receptors_and_innexins():
try:
conn = sqlite3.connect(SQLITE_DB_LOC)
cur = conn.cursor()
w = P.Worm()
n = P.Network()
w.neuron_network(n)
# insert neurons.
# save
# get the receptor (354) and innexin (355)
cur.execute("""
SELECT DISTINCT a.Entity, b.Entity
FROM
tblrelationship q,
tblrelationship r,
tblentity a,
tblentity b
where q.EnID1=a.id and q.Relation = '1515' and q.EnID2='1'
and r.EnID1=a.id and r.Relation = '354' and r.EnID2=b.id
""")
for r in cur.fetchall():
neuron_name = str(r[0])
receptor = str(r[1])
neur = P.Neuron(name=neuron_name)
neur.receptor(receptor)
n.neuron(neur)
cur.execute("""
SELECT DISTINCT a.Entity, b.Entity
FROM
tblrelationship q,
tblrelationship r,
tblentity a,
tblentity b
where q.EnID1=a.id and q.Relation = '1515' and q.EnID2='1'
and r.EnID1=a.id and r.Relation = '355' and r.EnID2=b.id
""")
for r in cur.fetchall():
neuron_name = str(r[0])
innexin = str(r[1])
neur = P.Neuron(name=neuron_name)
neur.innexin(innexin)
n.neuron(neur)
n.save()
#second step, get the relationships between them and add them to the graph
except Exception:
traceback.print_exc()
finally:
conn.close()
def do_insert(config="default.conf", logging=False):
global SQLITE_EVIDENCE
global WORM
global NETWORK
if config:
if isinstance(config, P.Configure):
pass
elif isinstance(config, str):
config = P.Configure.open(config)
elif isinstance(config, dict):
config = P.Configure().copy(config)
else:
raise Exception("Invalid configuration object " + str(config))
P.connect(conf=config, do_logging=logging)
SQLITE_EVIDENCE = P.Evidence(key="C_elegans_SQLite_DB",
title="C. elegans sqlite database")
try:
WORM = P.Worm()
NETWORK = P.Network()
WORM.neuron_network(NETWORK)
NETWORK.worm(WORM)
upload_neurons()
upload_muscles()
upload_lineage_and_descriptions()
upload_connections()
upload_receptors_types_neurotransmitters_neuropeptides_innexins()
upload_additional_receptors_neurotransmitters_neuropeptides_innexins()
print("Saving...")
WORM.save()
#infer()
print("Serializing...")
serialize_as_n3()
except Exception:
traceback.print_exc()
finally:
P.disconnect()
def upload_synapses():
try:
conn = sqlite3.connect(SQLITE_DB_LOC)
cur = conn.cursor()
w = P.Worm()
n = P.Network()
w.neuron_network(n)
#second step, get the relationships between them and add them to the graph
cur.execute("SELECT DISTINCT a.Entity, b.Entity, Weight, Relation FROM tblrelationship, tblentity a, tblentity b where EnID1=a.id and EnID2=b.id and (Relation = '356' OR Relation = '357')")
for r in cur.fetchall():
#all items are numbers -- need to be converted to a string
first = str(r[0])
second = str(r[1])
third = str(r[2])
syntype = str(r[3])
if syntype == '356':
syntype = 'send'
else:
syntype = 'gapjunction'
try:
weight = int(third)
# NMJs have negative weights. we only want the synaptic connections
if weight < 0:
syntype = 'gapjunction'
weight = -1 * weight
except:
weight = None
if weight:
c = P.Connection(pre_cell=first, post_cell=second, number=weight, syntype=syntype)
n.synapse(c)
e = P.Evidence(author='*****@*****.**')
e.asserts(w)
e.save()
except Exception, e:
traceback.print_exc()
def test_network_as_networkx(self):
self.assertTrue(
isinstance(PyOpenWorm.Network().as_networkx(), networkx.DiGraph))
def test_neuron_Syn_degree(self):
self.assertEquals(PyOpenWorm.Network().aneuron('AVAL').Syn_degree(),
74)
def test_neuron_name(self):
self.assertEquals(PyOpenWorm.Network().aneuron('AVAL').name(), 'AVAL')
self.assertEquals(PyOpenWorm.Network().aneuron('AVAR').name(), 'AVAR')
def test_neuron_type(self):
self.assertEquals(PyOpenWorm.Network().aneuron('AVAL').type(),
'interneuron')
self.assertEquals(PyOpenWorm.Network().aneuron('DD5').type(), 'motor')
self.assertEquals(PyOpenWorm.Network().aneuron('PHAL').type(),
'sensory')
def test_network_neurons(self):
self.assertTrue('AVAL' in PyOpenWorm.Network().neurons())
self.assertTrue('DD5' in PyOpenWorm.Network().neurons())
self.assertEquals(len(PyOpenWorm.Network().neurons()), 302)
def test_network_aneuron(self):
self.assertTrue(
isinstance(PyOpenWorm.Network().aneuron('AVAL'),
PyOpenWorm.Neuron))
def test_network(self):
self.assertTrue(isinstance(PyOpenWorm.Network(), PyOpenWorm.Network))
def upload_synapses():
import re
search_string = re.compile(r'\w+[0]+[1-9]+')
replace_string = re.compile(r'[0]+')
def normalize(name):
# normalize neuron names to match those used at other points
# see #137 for elaboration
# if there are zeroes in the middle of a name, remove them
if re.match(search_string, name):
name = replace_string.sub('', name)
return name
import xlrd
try:
w = P.Worm()
n = P.Network()
w.neuron_network(n)
combining_dict = {}
# Get synapses and gap junctions and add them to the graph
s = xlrd.open_workbook('../aux_data/NeuronConnect.xls').sheets()[0]
for row in range(1, s.nrows):
if s.cell(row, 2).value in ('S', 'Sp', 'EJ'):
#We're not going to include 'receives' ('R', 'Rp') since they're just the inverse of 'sends'
#Also omitting 'NMJ' for the time being (no model in db)
pre = normalize(s.cell(row, 0).value)
post = normalize(s.cell(row, 1).value)
num = int(s.cell(row, 3).value)
if s.cell(row, 2).value == 'EJ':
syntype = 'gapJunction'
elif s.cell(row, 2).value in ('S', 'Sp'):
syntype = 'send'
# Add them to a dict to make sure Sends ('S') and Send-polys ('Sp') are summed.
# keying by connection pairs as a string (e.g. 'SDQL,AVAL,send').
# values are lists of the form [pre, post, number, syntype].
string_key = '{},{},{}'.format(pre, post, syntype)
if string_key in combining_dict.keys():
# if key already there, add to number
num += combining_dict[string_key][2]
combining_dict[string_key] = [pre, post, num, syntype]
for entry in combining_dict:
pre, post, num, syntype = combining_dict[entry]
c = P.Connection(pre_cell=pre,
post_cell=post,
number=num,
syntype=syntype)
n.synapse(c)
e = P.Evidence(
uri='http://www.wormatlas.org/neuronalwiring.html#Connectivitydata'
)
e.asserts(n)
e.save()
print('uploaded synapses')
except Exception, e:
traceback.print_exc()
# n.neighbor(b) # Otherwise, the neuron (b) in the connected class on the same side as
# # n (i.e., the one for which the last character in its name matches the
# # last in n's name) in the neighbor
# n.name()[:-1] == nc.name()
#
# Setting up the data
#
ev = P.Evidence(
title=
"A Hub-and-Spoke Circuit Drives Pheromone Attraction and Social Behavior in C. elegans",
uri="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760495/",
year=2009)
w = P.Worm("C. elegans")
net = P.Network()
w.neuron_network(net)
ev.asserts(w)
def setup(name, type):
n = NeuronClass(name)
n.type(type)
n.member(P.Neuron(name + "R"))
n.member(P.Neuron(name + "L"))
net.neuron(n)
return n
rmg = setup("RMG", 'interneuron')
