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229 | class Cook2020DataReader(ConnectomeDataset):
"""
Reader of data from Cook et al. 2020 - The connectome of the Caenorhabditis elegans pharynx
Returns:
(Cook2020DataReader): The initialized Cook et al 2020 pharyngeal connectome reader
"""
cells = []
conns = []
def __init__(self):
ConnectomeDataset.__init__(self)
cells, neuron_conns = self.read_data()
for conn in neuron_conns:
self.add_connection_info(
conn,
check_overwritten_connections=True,
append_existing_connections=True,
)
def read_data(self):
"""
Returns:
(tuple[list, list]): List of cells (str) and list of connections (``ConnectionInfo``) which have been read in
"""
with open(filename, "r") as f:
reader = csv.DictReader(f)
print_("Opened file: " + filename)
for row in reader:
pre = str.strip(row["Source"])
if is_potential_muscle(pre):
pre = convert_to_preferred_muscle_name(pre)
post = str.strip(row["Target"])
if is_potential_muscle(post):
post = convert_to_preferred_muscle_name(post)
if is_marginal_cell(post):
post = convert_to_preferred_phar_cell_name(post)
num = float(row["Weight"])
syntype = str.strip(row["Type"])
if syntype == "Electrical":
syntype = ELECTRICAL_SYN_TYPE
else:
syntype = CHEMICAL_SYN_TYPE
synclass = (
GENERIC_ELEC_SYN_CLASS
if syntype == ELECTRICAL_SYN_TYPE
else GENERIC_CHEM_SYN_CLASS
)
self.conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
# Add post -> pre conn for gap junction connections
if syntype == ELECTRICAL_SYN_TYPE:
self.conns.append(ConnectionInfo(post, pre, num, syntype, synclass))
if pre not in self.cells:
self.cells.append(pre)
if post not in self.cells:
self.cells.append(post)
with open(filename2, "r") as f:
reader = csv.DictReader(f)
print_("Opened file: " + filename)
for row in reader:
pre = str.strip(row["Source"])
if is_potential_muscle(pre):
pre = convert_to_preferred_muscle_name(pre)
if is_marginal_cell(pre):
pre = convert_to_preferred_phar_cell_name(pre)
post = str.strip(row["Target"])
if is_potential_muscle(post):
post = convert_to_preferred_muscle_name(post)
if is_marginal_cell(post):
post = convert_to_preferred_phar_cell_name(post)
num = float(row["Weight"])
syntype = ELECTRICAL_SYN_TYPE
synclass = GENERIC_ELEC_SYN_CLASS
self.conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
# Add post -> pre conn for gap junction connections
self.conns.append(ConnectionInfo(post, pre, num, syntype, synclass))
if pre not in self.cells:
self.cells.append(pre)
if post not in self.cells:
self.cells.append(post)
return self.cells, self.conns
'''def read_muscle_data(self):
"""
Returns:
neurons (:obj:`list` of :obj:`str`): List of motor neurons. Each neuron has at least one connection with a post-synaptic muscle cell.
muscles (:obj:`list` of :obj:`str`): List of muscle cells.
conns (:obj:`list` of :obj:`ConnectionInfo`): List of neuron-muscle connections.
"""
neurons = []
muscles = []
conns = []
with open(filename, "r") as f:
reader = csv.DictReader(f)
print_("Opened file: " + filename)
for row in reader:
pre = str.strip(row["Source"])
if is_potential_muscle(pre):
pre = convert_to_preferred_muscle_name(pre)
if is_marginal_cell(pre):
pre = convert_to_preferred_phar_cell_name(pre)
post = str.strip(row["Target"])
if is_potential_muscle(post):
post = convert_to_preferred_muscle_name(post)
if is_marginal_cell(post):
post = convert_to_preferred_phar_cell_name(post)
num = float(row["Weight"])
syntype = str.strip(row["Type"])
if syntype == "Electrical":
syntype = ELECTRICAL_SYN_TYPE
synclass = (
GENERIC_ELEC_SYN_CLASS
if syntype == ELECTRICAL_SYN_TYPE
else GENERIC_CHEM_SYN_CLASS
)
conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
# Add post -> pre conn for gap junction connections
if syntype == ELECTRICAL_SYN_TYPE:
conns.append(ConnectionInfo(post, pre, num, syntype, synclass))
if is_known_muscle(post):
if post in PREFERRED_MUSCLE_NAMES and post not in muscles:
muscles.append(post)
if pre in PREFERRED_HERM_NEURON_NAMES and pre not in neurons:
neurons.append(pre)
with open(filename2, "r") as f:
reader = csv.DictReader(f)
print_("Opened file: " + filename2)
for row in reader:
pre = str.strip(row["Source"])
if is_potential_muscle(pre):
pre = convert_to_preferred_muscle_name(pre)
if is_marginal_cell(pre):
pre = convert_to_preferred_phar_cell_name(pre)
post = str.strip(row["Target"])
if is_potential_muscle(post):
post = convert_to_preferred_muscle_name(post)
if is_marginal_cell(post):
post = convert_to_preferred_phar_cell_name(post)
num = float(row["Weight"])
syntype = "Electrical"
synclass = (
GENERIC_ELEC_SYN_CLASS
if "Electrical" in syntype
else GENERIC_CHEM_SYN_CLASS
)
if syntype == "Electrical":
conns.append(ConnectionInfo(pre, post, num, syntype, synclass))
conns.append(ConnectionInfo(post, pre, num, syntype, synclass))
if is_known_muscle(post):
if post in PREFERRED_MUSCLE_NAMES and post not in muscles:
muscles.append(post)
if pre in PREFERRED_HERM_NEURON_NAMES and pre not in neurons:
neurons.append(pre)
return neurons, muscles, conns'''
def read_muscle_data(self):
return self._read_muscle_data()
|