import numpy as np
from ..strategy import ConnectionStrategy
[docs]class ConnectomeAscAxonPurkinje(ConnectionStrategy):
"""
Legacy implementation for the connections between ascending axons and purkinje cells.
"""
[docs] def validate(self):
pass
def connect(self):
# Gather information for the legacy code block below.
granule_cell_type = self.from_cell_types[0]
purkinje_cell_type = self.to_cell_types[0]
granules = self.scaffold.cells_by_type[granule_cell_type.name]
purkinjes = self.scaffold.cells_by_type[purkinje_cell_type.name]
first_granule = int(granules[0, 0])
OoB_value = (
self.scaffold.configuration.X * 1000.0
) # Any arbitrarily large value outside of simulation volume
purkinje_extension_x = purkinje_cell_type.placement.extension_x
purkinje_extension_z = purkinje_cell_type.placement.extension_z
def connectome_aa_pc(first_granule, granules, purkinjes, x_pc, z_pc, OoB_value):
aa_pc = np.zeros((0, 2))
new_granules = np.copy(granules)
# for all Purkinje cells: calculate and choose which granules fall into the area of PC dendritic tree, then delete them from successive computations, since 1 ascending axon is connected to only 1 PC
for i in purkinjes:
# ascending axon falls into the z range of values?
bool_vector = (new_granules[:, 4]).__ge__(i[4] - z_pc / 2.0) & (
new_granules[:, 4]
).__le__(i[4] + z_pc / 2.0)
# ascending axon falls into the x range of values?
bool_vector = bool_vector & (
(new_granules[:, 2]).__ge__(i[2] - x_pc / 2.0)
& (new_granules[:, 2]).__le__(i[2] + x_pc / 2.0)
)
good_aa = np.where(bool_vector)[
0
] # finds indexes of ascending axons that, on the selected axis, have the correct sum value
# construction of the output matrix: the first column has the GrC id, while the second column has the PC id
matrix = np.zeros((len(good_aa), 2))
matrix[:, 1] = i[0]
matrix[:, 0] = good_aa + first_granule
aa_pc = np.vstack((aa_pc, matrix))
new_granules[
good_aa, :
] = OoB_value # update the granules matrix used for computation by deleting the coordinates of connected ones
return aa_pc
result = connectome_aa_pc(
first_granule,
granules,
purkinjes,
purkinje_extension_x,
purkinje_extension_z,
OoB_value,
)
self.scaffold.connect_cells(self, result)
