def create_cells(self, cellindex): """Create and layout N cells in the network.""" cells = {} position_factor = 1e3 sim_params = hf.get_net_params(hf.get_tempdata_address()) mn_pos_x = sim_params[10] mn_pos_y = sim_params[11] mn_pos_z = sim_params[12] cell = Mn() '''cell.set_pos(mn_pos_x[0] + cellindex * position_factor, mn_pos_y[0] + cellindex * position_factor, mn_pos_z[0] + cellindex * position_factor) ''' cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"Mn" : cell}) self.cellPositions['Mn'].append([cell.somapos[0], cell.somapos[1], cell.somapos[2]]) cell = Ia(n_nodes = hf.get_n_nodes_from_mat('E:\\Google Drive\\Github\\tempdata\\move_root_um_move_root_points_cs.mat',0)) cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"Ia" : cell}) self.cellPositions['Ia'].append([cell.somapos[0], cell.somapos[1], cell.somapos[2]]) cell = Ib(n_nodes = hf.get_n_nodes_from_mat('E:\\Google Drive\\Github\\tempdata\\move_root_um_move_root_points_cs.mat',1)) cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"Ib" : cell}) self.cellPositions['Ib'].append([cell.somapos[0], cell.somapos[1], cell.somapos[2]]) cell = IaInt() cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"IaInt" : cell}) self.cellPositions['IaInt'].append([cell.somapos[0], cell.somapos[1], cell.somapos[2]]) cell = IbInt() cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"IbInt" : cell}) self.cellPositions['IbInt'].append([cell.somapos[0], cell.somapos[1], cell.somapos[2]]) cell = Ren() cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"Ren" : cell}) self.cellPositions['Ren'].append([cell.somapos[0], cell.somapos[1], cell.somapos[2]]) for key, value in cells.iteritems(): value.tstopms = self.cellParameters['tstopms'] return cells
def __init__(self, *args, **kwargs): ''' class initialization POPULATION_SIZE : int, number of cells cellParameters : dict populationParameters : dict synapseParameters : dict ''' super(Ia_network, self).__init__(*args, **kwargs) self.cellPositions = { 'Mn' : [], 'Ia' : [] } self.cellRotations = { 'Mn' : [], 'Ia' : [] } sim_params = hf.get_net_params(hf.get_tempdata_address()) dummy_Ia = Ia(n_nodes = hf.get_n_nodes_from_mat('E:\\Google Drive\\Github\\tempdata\\move_root_um_move_root_points_cs.mat',0)) dummy_Mn = Mn() self.cellMorphologies = { 'Mn' : dummy_Mn.morphology_address, 'Ia' : dummy_Ia.morphology_address } del dummy_Ia, dummy_Mn
def __init__(self, *args, **kwargs): ''' class initialization POPULATION_SIZE : int, number of cells cellParameters : dict populationParameters : dict synapseParameters : dict ''' super(Ia_network, self).__init__(*args, **kwargs) self.cellPositions = {'Mn': [], 'Ia': []} self.cellRotations = {'Mn': [], 'Ia': []} sim_params = hf.get_net_params(hf.get_tempdata_address()) dummy_Ia = Ia(n_nodes=sim_params[0][0]) dummy_Mn = Mn() self.cellMorphologies = { 'Mn': dummy_Mn.morphology_address, 'Ia': dummy_Ia.morphology_address } del dummy_Ia, dummy_Mn
def create_cells(self, cellindex): """Create and layout N cells in the network.""" cells = {} position_factor = 1e3 sim_params = hf.get_net_params(hf.get_tempdata_address()) mn_pos_x = sim_params[10] mn_pos_y = sim_params[11] mn_pos_z = sim_params[12] cell = Mn() '''cell.set_pos(mn_pos_x[0] + cellindex * position_factor, mn_pos_y[0] + cellindex * position_factor, mn_pos_z[0] + cellindex * position_factor) ''' cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"Mn": cell}) self.cellPositions['Mn'].append( [cell.somapos[0], cell.somapos[1], cell.somapos[2]]) cell = Ia(n_nodes=sim_params[0][0]) cell.set_pos(cellindex * position_factor, cellindex * position_factor, cellindex * position_factor) cells.update({"Ia": cell}) self.cellPositions['Ia'].append( [cell.somapos[0], cell.somapos[1], cell.somapos[2]]) return cells
def __init__(self): self.sim_params = hf.get_net_params(hf.get_tempdata_address()) self.n_nodes = self.sim_params[0][0] self.diameter = self.sim_params[4][0] self.inl = self.sim_params[5][0] self.length = self.sim_params[4][0] self.d_lambda = 0.1 super(Ia, self).__init__()
def create_cells(self, cellindex): """Create and layout N cells in the network.""" cells = {} position_factor = 1e3 sim_params = hf.get_net_params(hf.get_tempdata_address()) mn_pos_x = sim_params[10] mn_pos_y = sim_params[11] mn_pos_z = sim_params[12] if cellindex = self.populationParameters['size'] - 1: cell = Mn(is_last_in_network = True)
def create_cells(self, N): """Create and layout N cells in the network.""" self.cells = [] r = 50 # Radius of cell locations from origin (0,0,0) in microns N = self._N position_factor = 5e3; sim_params = hf.get_net_params(hf.get_tempdata_address()) mn_pos_x = sim_params[10] mn_pos_y = sim_params[11] mn_pos_z = sim_params[12] for i in range(N): cell = Mn() cell.set_position(mn_pos_x[0]+i * position_factor,mn_pos_y[0]+i * position_factor,mn_pos_z[0]+i * position_factor) self.cells.append(cell) for i in range(N): cell = Ia() cell.set_position(i * position_factor,i * position_factor,i * position_factor) self.cells.append(cell)
def create_cells(self, N): """Create and layout N cells in the network.""" self.cells = [] r = 50 # Radius of cell locations from origin (0,0,0) in microns N = self._N position_factor = 5e3 sim_params = hf.get_net_params(hf.get_tempdata_address()) mn_pos_x = sim_params[10] mn_pos_y = sim_params[11] mn_pos_z = sim_params[12] for i in range(N): cell = Mn() cell.set_position(mn_pos_x[0] + i * position_factor, mn_pos_y[0] + i * position_factor, mn_pos_z[0] + i * position_factor) self.cells.append(cell) for i in range(N): cell = Ia() cell.set_position(i * position_factor, i * position_factor, i * position_factor) self.cells.append(cell)
from neuron import gui else: h.load_file('noload.hoc') from scipy import signal from scipy.interpolate import interp1d from mpi4py import MPI from matplotlib import pyplot from neuronpy.graphics import spikeplot import helper_functions as hf from Ia_network_LFPy import Ia_network as Ia_net os.chdir('E:\\Google Drive\\Github\\Spinal-Cord-Modeling\\Python') tempdata_address = hf.get_tempdata_address() mn_geom_address = hf.get_mn_geom_address() Ia_geom_file = tempdata_address + "Ia_geometry" mn_geom_file = mn_geom_address + "motoneuron_geometry" mod_geom_file = tempdata_address + "model_tree.neu" sim_params = hf.get_net_params(tempdata_address) # sim_params[0] = n_nodes # sim_params[1] = start_time # sim_params[2] = dur_time # sim_params[3] = interval_time # sim_params[4] = diameter # sim_params[5] = inl # sim_params[6] = points_per_node # sim_params[7] = ampstart
import scipy from scipy.interpolate import interp1d from mpi4py import MPI from matplotlib import pyplot from neuronpy.graphics import spikeplot import helper_functions as hf from Ia_Clarke_LFPy import Ia_Clarke as Ia_net import numpy as np import cPickle as pickle import scipy os.chdir('E:\\Google Drive\\Github\\Spinal-Cord-Modeling\\Python') tempdata_address = hf.get_tempdata_address() mn_geom_address = hf.get_mn_geom_address() Ib_geom_file = tempdata_address + "Ib_geometry" mn_geom_file = mn_geom_address + "motoneuron_geometry" mod_geom_file = tempdata_address + "model_tree.neu" sim_params = hf.get_net_params(tempdata_address) # sim_params[0] = n_nodes # sim_params[1] = start_time # sim_params[2] = dur_time # sim_params[3] = interval_time # sim_params[4] = diameter # sim_params[5] = inl # sim_params[6] = points_per_node # sim_params[7] = ampstart