import numpy as np
from ..strategy import ConnectionStrategy
[docs]class ConnectomePFInterneuron(ConnectionStrategy):
"""
Legacy implementation for the connections between parallel fibers and a molecular layer interneuron cell_type.
"""
[docs] def validate(self):
pass
def connect(self):
# Gather information for the legacy code block below.
granule_cell_type = self.from_cell_types[0]
interneuron_cell_type = self.to_cell_types[0]
granules = self.scaffold.cells_by_type[granule_cell_type.name]
interneurons = self.scaffold.cells_by_type[interneuron_cell_type.name]
first_granule = int(granules[0, 0])
dendrite_radius = interneuron_cell_type.morphology.dendrite_radius
# Spoof fixed pf height of 150 µm
pf_heights = 150 + granules[:, 3]
def connectome_pf_inter(first_granule, interneurons, granules, r_sb, h_pf):
pf_interneuron = np.zeros((0, 2))
# for each interneuron find all the parallel fibers that fall into the sphere with centre the cell soma and appropriate radius
for i in interneurons:
# find all cells that satisfy the condition
interneuron_matrix = (
((granules[:, 2] - i[2]) ** 2) + ((h_pf - i[3]) ** 2) - (r_sb ** 2)
).__le__(0)
# indexes of interneurons that can potentially be connected
good_pf = np.where(interneuron_matrix)[0]
matrix = np.zeros((len(good_pf), 2))
matrix[:, 1] = i[0]
matrix[:, 0] = good_pf + first_granule
pf_interneuron = np.vstack((pf_interneuron, matrix))
return pf_interneuron
result = connectome_pf_inter(
first_granule, interneurons, granules, dendrite_radius, pf_heights
)
self.scaffold.connect_cells(self, result)
