import numpy as np
from ..strategy import ConnectionStrategy
from ...reporting import report, warn
from ...exceptions import *
[docs]class ConnectomeMossyDCN(ConnectionStrategy):
"""
Implementation for the connection between mossy fibers and DCN cells.
"""
casts = {"convergence": int}
required = ["convergence"]
[docs] def validate(self):
pass
def connect(self):
# Source and target neurons are extracted
mossy_cell_type = self.from_cell_types[0]
dcn_cell_type = self.to_cell_types[0]
mossy = self.scaffold.entities_by_type[mossy_cell_type.name]
dcn_cells = self.scaffold.cells_by_type[dcn_cell_type.name]
convergence = self.convergence
if convergence > len(mossy):
convergence = len(mossy)
warn(
"Convergence for MF-DCN saturated at MF number. Network too small",
ConnectivityWarning,
)
mf_dcn = np.zeros((convergence * len(dcn_cells), 2))
for i, dcn in enumerate(dcn_cells):
connected_mfs = np.random.choice(mossy, convergence, replace=False)
range_i = range(i * convergence, (i + 1) * convergence)
mf_dcn[range_i, 0] = connected_mfs.astype(int)
mf_dcn[range_i, 1] = dcn[0]
self.scaffold.connect_cells(self, mf_dcn)
