#iterate over each cell type, and create populationulation object
for i, y in enumerate(params.y):
#create population:
pop = Population(
#parent class
cellParams = params.yCellParams[y],
rand_rot_axis = params.rand_rot_axis[y],
simulationParams = params.simulationParams,
populationParams = params.populationParams[y],
y = y,
layerBoundaries = params.layerBoundaries,
electrodeParams = params.electrodeParams,
savelist = params.savelist,
savefolder = params.savefolder,
calculateCSD = params.calculateCSD,
dt_output = params.dt_output,
POPULATIONSEED = SIMULATIONSEED + i,
#daughter class kwargs
X = params.X,
networkSim = networkSim,
k_yXL = params.k_yXL[y],
synParams = params.synParams[y],
synDelayLoc = params.synDelayLoc[y],
synDelayScale = params.synDelayScale[y],
J_yX = params.J_yX[y],
tau_yX = params.tau_yX[y],
recordSingleContribFrac = params.recordSingleContribFrac,
)
#run population simulation and collect the data
pop.run()
pop.collect_data()
if properrun:
#iterate over each cell type, and create populationulation object
for i, Y in enumerate(PS.X):
#create population:
pop = Population(
cellParams = PS.cellParams[Y],
rand_rot_axis = PS.rand_rot_axis[Y],
simulationParams = PS.simulationParams,
populationParams = PS.populationParams[Y],
y = Y,
layerBoundaries = PS.layerBoundaries,
electrodeParams = PS.electrodeParams,
savelist = PS.savelist,
savefolder = PS.savefolder,
calculateCSD = PS.calculateCSD,
dt_output = PS.dt_output,
POPULATIONSEED = SIMULATIONSEED + i,
X = PS.X,
networkSim = networkSim,
k_yXL = PS.k_yXL[Y],
synParams = PS.synParams[Y],
synDelayLoc = PS.synDelayLoc[Y],
synDelayScale = PS.synDelayScale[Y],
J_yX = PS.J_yX[Y],
tau_yX = PS.tau_yX[Y],
)
#run population simulation and collect the data
pop.run()
pop.collect_data()
#iterate over each cell type, and create populationulation object
for i, Y in enumerate(PSET['X']):
#create population:
pop = Population(
cellParams = PSET['cellParams'][Y],
rand_rot_axis = PSET['rand_rot_axis'][Y],
simulationParams = PSET['simulationParams'],
populationParams = PSET['populationParams'][Y],
y = Y,
layerBoundaries = PSET['layerBoundaries'],
electrodeParams = PSET['electrodeParams'],
savelist = PSET['savelist'],
savefolder = output_path,
calculateCSD = PSET['calculateCSD'],
dt_output = PSET['dt_output'],
POPULATIONSEED = SIMULATIONSEED + i,
X = PSET['X'],
networkSim = networkSim,
k_yXL = PSET['k_yXL'][Y],
synParams = PSET['synParams'][Y],
synDelayLoc = PSET['synDelayLoc'][Y],
synDelayScale = PSET['synDelayScale'][Y],
J_yX = PSET['J_yX'][Y],
tau_yX = PSET['tau_yX'][Y],
)
#run population simulation and collect the data
pop.run()
pop.collect_data()
#iterate over each cell type, and create populationulation object
for i, y in enumerate(params.y):
#create population:
pop = Population(
#parent class
cellParams = params.yCellParams[y],
rand_rot_axis = params.rand_rot_axis[y],
simulationParams = params.simulationParams,
populationParams = params.populationParams[y],
y = y,
layerBoundaries = params.layerBoundaries,
electrodeParams = params.electrodeParams,
savelist = params.savelist,
savefolder = params.savefolder,
calculateCSD = params.calculateCSD,
dt_output = params.dt_output,
POPULATIONSEED = SIMULATIONSEED + i,
#daughter class kwargs
X = params.X,
networkSim = networkSim,
k_yXL = params.k_yXL[y],
synParams = params.synParams[y],
synDelayLoc = params.synDelayLoc[y],
synDelayScale = params.synDelayScale[y],
J_yX = params.J_yX[y],
tau_yX = params.tau_yX[y],
recordSingleContribFrac = params.recordSingleContribFrac,
)
#run population simulation and collect the data
pop.run()
pop.collect_data()
def __init__(
self,
topology_connections={
'EX': {
'edge_wrap': True,
'extent': [4000., 4000.],
'allow_autapses': True,
'kernel': {
'exponential': {
'a': 1.,
'c': 0.0,
'tau': 300.
}
},
'mask': {
'circular': {
'radius': 2000.
}
},
'delays': {
'linear': {
'c': 1.,
'a': 2.
}
},
},
'IN': {
'edge_wrap': True,
'extent': [4000., 4000.],
'allow_autapses': True,
'kernel': {
'exponential': {
'a': 1.,
'c': 0.0,
'tau': 300.
}
},
'mask': {
'circular': {
'radius': 2000.
}
},
'delays': {
'linear': {
'c': 1.,
'a': 2.
}
},
},
},
**kwargs):
'''
Initialization of class TopoPopulation, for dealing with networks
created using the NEST topology library (distance dependent
connectivity).
Inherited of class hybridLFPy.Population
Arguments
---------
topology_connections : dict
nested dictionary with topology-connection parameters for each
presynaptic population
Returns
-------
object : populations.TopoPopulation
population object with connections, delays, positions, simulation
methods
See also
--------
hybridLFPy.Population
'''
#set networkSim attribute so that monkey-patched methods can work
self.networkSim = kwargs['networkSim']
self.topology_connections = topology_connections
#initialize parent class
Population.__init__(self, **kwargs)