def get_path_nest(script_name, keys, par=None): if not par: par = default_params.Inhibition() path = par.get_path_data() file_name = path + script_name + '/' + '_'.join(keys) + '/nest/' # file_name = home + '/results/papers/inhibition/network/' + script_name data_to_disk.mkdir(file_name) return file_name
def get_file_name_figs(script_name, par=None): if not par: par = default_params.Inhibition() path = par.get_path_figure() file_name = path + script_name # file_name = path +'/fig/'+ script_name # file_name_figs = home + '/results/papers/inhibition/network/fig/' + script_name return file_name
def simulate(nest_model, neuron_type): par=default_params.Inhibition(**{'perturbations':op.get()[0]}) kw={'model':nest_model, 'n':1, 'mm':{"withgid": True, 'to_file':False, 'to_memory':True, 'record_from':['V_m'] }, 'params':par.dic[neuron_type]} n=my_population.MyNetworkNode(**kw) model=kwargs.get('model', 'iaf_neuron') n=kwargs.get('n', 1) params=kwargs.get('params',{})
def _run_GP_STN_network(self): script_name = self.script_name par = default_params.Inhibition() params = self.get_params_as_dic() d = par.dic['nest'][self.neuron] for key, val in params['Model parameters'].items(): if key not in d.keys(): continue d[key] = val pp(d) delay = 3. kw = { 'gi_amp': 1, 'gi_n': 300, 'gi_st_delay': delay, 'gi_gi_delay': 1., 'local_num_threads': 4, 'sim_time': 3500.0, 'st_gi_delay': delay, 'st_amp': 0, 'st_n': 100, } kwhash = kw.copy() kwhash.update(d) s = str(hash(frozenset(kwhash.items()))) kw['file_name'] = dr.HOME_DATA + '/' + script_name + '/' + 'run_GP_STN_network' + '_' + s kw['file_name_figs'] = dr.HOME_DATA + '/fig/' + script_name + '/' + 'run_GP_STN_network' + '_' + s kw['p_st'] = d from_disk = os.path.isdir(kw['file_name']) * 2 from scripts_inhibition import GP_STN_oscillations GP_STN_oscillations.main(from_disk=from_disk, kw=kw, net='Net_0', script_name=__file__.split('/')[-1][0:-3], setup=GP_STN_oscillations.Setup(50, 20))
from core import my_nest from core import misc from core.my_population import MyNetworkNode import pprint pp = pprint.pprint from core.network.manager import get_storage_list, save, load from core import directories as dir from core import data_to_disk import os path = dir.HOME_DATA + '/' + __file__.split('/')[-1][0:-3] if not os.path.isdir(path): data_to_disk.mkdir(path) par = default_params.Inhibition() setup = Setup(50, 20) def gs_builder(*args, **kwargs): import matplotlib.gridspec as gridspec n_rows = kwargs.get('n_rows', 2) n_cols = kwargs.get('n_cols', 1) order = kwargs.get('order', 'col') gs = gridspec.GridSpec(n_rows, n_cols) gs.update(wspace=kwargs.get('wspace', 0.1), hspace=kwargs.get('hspace', 0.1)) iterator = [ [slice(0, 1), slice(0, 1)],
def _run_neuron(self): script_name = self.script_name par = default_params.Inhibition() params = self.get_params_as_dic() d = par.dic['nest'][self.neuron] for key, val in params['Model parameters'].items(): if key not in d.keys(): continue d[key] = val kw = { 'ahp_curr': tuple( numpy.arange(self.ahp_curr_start, self.ahp_curr_stop, self.ahp_curr_step)), 'ahp_I_e': .5, 'I_E': 0.0, 'if_I_vec': tuple( numpy.arange(self.if_I_vec_start, self.if_I_vec_stop, self.if_I_vec_step)), 'irf_curr': (self.irf_curr_0, self.irf_curr_1, self.irf_curr_2), 'iv_I_vec': tuple( numpy.arange(self.iv_I_vec_start, self.iv_I_vec_stop, self.iv_I_vec_step)), 'model': 'my_aeif_cond_exp', 'nc_V': tuple(numpy.arange(self.nc_V_start, self.nc_V_stop, self.nc_V_step)), 'rs_curr': (self.rs_curr_0, self.rs_curr_1, self.rs_curr_2, self.rs_curr_3, self.rs_curr_4, self.rs_curr_5), 'rs_time': (self.rs_time_0, self.rs_time_1, self.rs_time_2, self.rs_time_3, self.rs_time_4, self.rs_time_5), 'rs_I_e': self.rs_I_e, } # pp(d) kwhash = kw.copy() kwhash.update(d) s = str(hash(frozenset(kwhash.items()))) kw['if_params'] = d kw['iv_params'] = d kw['nc_params'] = d kw['rs_params'] = d kw['file_name'] = dr.HOME_DATA + '/' + script_name + '/' + 'run_neuron' + '_' + s kw['file_name_figs'] = dr.HOME_DATA + '/fig/' + script_name + '/' + 'run_neuron' + '_' + s from_disk = os.path.isdir(kw['file_name']) # main(*args, **kwargs) base_neuron.main(from_disk=from_disk, kw=kw, net='Net_0', script_name=script_name, setup=base_neuron.Setup(50, 20))
''' Created on Aug 26, 2015 @author: mikael ''' import fig_01_and_02_pert as op from core.network import default_params import pprint pp = pprint.pprint par = default_params.Inhibition(**{'perturbations': op.get()[0]}) pp(par.dic['nest'].keys()) #Look at MSN D1 (high or low gabaa reversal potential E_rev) print('MSN D1') pp(par.dic['nest']['M1_low']) #I am using low # pp(par.dic['nest']['M1_high']) print('MSN D2') pp(par.dic['nest']['M2_low']) #I am using low print('FSN') pp(par.dic['nest']['FS'])