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'])
