def simulate(from_disk=0,
kw={},
net='Net_0',
script_name=__file__.split('/')[-1][0:-3],
setup=Setup(50, 20)):
setup = Setup(50, 20)
file_name = kw.get('file_name', dr.HOME_DATA + '/' + script_name)
file_name_figs = kw.get('file_name_figs',
dr.HOME_DATA + '/fig/' + script_name)
sd = get_storage_list([net], file_name, '')[0]
d = {}
if from_disk == 0:
print net
dd = {net: simulate_network(**kw)}
dd = compute_attrs(dd, net, setup)
save(sd, dd)
if from_disk == 1:
filt = [net] + ['gi', 'st', 'gi_st'] + ['spike_signal']
dd = load(sd, *filt)
pp(dd)
dd = compute_attrs(dd, net, setup)
save(sd, dd)
elif from_disk == 2:
filt = [net] + ['gi', 'st', 'gi_st'
] + ['firing_rate', 'phases_diff_with_cohere']
dd = load(sd, *filt)
d = misc.dict_update(d, dd)
return d, file_name_figs
def simulate(from_disk=0,
kw={},
net='Net_0',
script_name=__file__.split('/')[-1][0:-3],
setup=Setup(50,20) ):
setup=Setup(50,20)
file_name = kw.get('file_name', dr.HOME_DATA+'/'+script_name)
file_name_figs = kw.get('file_name_figs', dr.HOME_DATA+'/fig/'+script_name)
sd=get_storage_list([net], file_name, '')[0]
d={}
if from_disk==0:
print net
dd={net:simulate_network(**kw)}
dd=compute_attrs(dd, net, setup)
save(sd, dd)
if from_disk==1:
filt= [net]+['gi','st', 'gi_st']+['spike_signal']
dd = load(sd, *filt)
pp(dd)
dd=compute_attrs(dd, net, setup)
save(sd, dd)
elif from_disk==2:
filt = [net]+['gi','st', 'gi_st']+['firing_rate', 'phases_diff_with_cohere']
dd = load(sd, *filt)
d = misc.dict_update(d, dd)
return d, file_name_figs
def simulate(builder, from_disk, perturbation_list, script_name, setup):
home = expanduser("~")
# file_name = get_file_name(script_name, home)
# file_name_figs = get_file_name_figs(script_name, home)
#
d_firing_rate = setup.firing_rate()
attr = ['firing_rate', 'mean_rate_slices']
attr_conn=['conn_matrix']
models=['M1', 'M2']
models_conn=['M1_M1_gaba', 'M1_M2_gaba',
'M2_M1_gaba', 'M2_M2_gaba']
sets = ['set_0']
info, nets, intervals, rep, x = get_networks(builder,
**setup.builder())
key=nets.keys()[0]
file_name = get_file_name(script_name, nets[key].par)
file_name_figs = get_file_name_figs(script_name, nets[key].par)
path_nest=get_path_nest(script_name, nets.keys(), nets[key].par)
for net in nets.values():
net.set_path_nest(path_nest)
kwargs_dic = {'firing_rate':d_firing_rate,
'mean_rate_slices': {'intervals':intervals[1],
'repetition':rep,
'set_0':{'x':x},
'sets':[0]}}
# add_perturbations(perturbation_list, nets)
# sd = get_storage(file_name, info)
#
# # _, d1 = main_loop_conn(from_disk, attr_conn, models_conn,
# # sets, nets, kwargs_dic, sd)
d1={}
# from_disks, d2 = main_loop(from_disk, attr, models,
# sets, nets, kwargs_dic, sd)
#
add_perturbations(perturbation_list, nets)
# Adding nets no file name
sd_list=get_storage_list(nets, file_name, info)
from_disks, d2 = main_loop(from_disk, attr, models,
sets, nets, kwargs_dic, sd_list)
d=misc.dict_update(d1,d2)
if from_disk==2:
d=cmp_mean_rate_diff(d, models, [['Net_0', 'Net_5'],
['Net_1', 'Net_6'],
['Net_2', 'Net_7'],
['Net_3', 'Net_8'],
['Net_4', 'Net_9']], x)
return file_name, file_name_figs, from_disks, d, models
def simulate(builder,
from_disk,
perturbation_list,
script_name,
setup):
# file_name = get_file_name(script_name, home)
# file_name_figs = get_file_name_figs(script_name, home)
attr = ['mean_rate_slices']
models = ['M1', 'M2', 'FS', 'GI', 'GA', 'ST', 'SN']
sets = []
info, nets, intervals, amplitudes, rep = get_networks(builder,
setup.builder(),
setup.director(),
setup.default_params())
key=nets.keys()[0]
file_name = get_file_name(script_name, nets[key].par)
file_name_figs = get_file_name_figs(script_name, nets[key].par)
path_nest=get_path_nest(script_name, nets.keys(), nets[key].par)
for net in nets.values():
net.set_path_nest(path_nest)
d_firing_rate = setup.firing_rate()
kwargs_dic = {'firing_rate':d_firing_rate,
'mean_rate_slices':{'intervals':intervals[1],
'repetition':rep,
'x':amplitudes}}
add_perturbations(perturbation_list, nets)
for p in sorted(perturbation_list.list):
print p
# sd = get_storage(file_name, info)
# Adding nets no file name
sd_list=get_storage_list(nets, file_name, info)
from_disks, d = main_loop(from_disk, attr, models,
sets, nets, kwargs_dic, sd_list)
# from_disks, d = main_loop(from_disk, attr, models,
# sets, nets, kwargs_dic, sd)
return file_name_figs, from_disks, d, models
def main(*args, **kwargs):
setup=kwargs.get( 'setup')#, Setup())
script_name=kwargs.get('script_name')#,__file__.split('/')[-1][0:-3])
builder=kwargs.get('builder')
info, nets, _ = get_networks(builder,
setup.builder(),
setup.director(),
setup.engine(),
setup.default_params())
perturbation_list=kwargs.get('perturbation_list')#,op.get()[0])
perturbation_list+=pl(setup.par(), '=', **{'name':setup.tp_name})
print perturbation_list
for p in sorted(perturbation_list.list):
print p
add_perturbations(perturbation_list, nets)
key=nets.keys()[0]
file_name = get_file_name(script_name, nets[key].par)
path_nest=get_path_nest(script_name, nets.keys(), nets[key].par)
print nets.keys()
for net in nets.values():
net.set_path_nest(path_nest)
net.set_opt(setup.opt[net.name])
# Adding nets no file name
sd_list=get_storage_list(nets.keys(), file_name, info)
for net, sd in zip(nets, sd_list):
nl=Network_list(nets.values())
#nd.add(name, **kwargs)
kwargs={'model':nl,
'call_get_x0':'get_x0',
'call_get_error':'sim_optimization',
'verbose':True,}
f=Fmin('GA_GI_ST_opt', **kwargs)
h=f.fmin()
dd={setup.tp_name.split('_')[0]:{net:{'opt':h}}}
save(sd, dd)
def simulate(
from_disk=0,
kw={},
net='Net_0',
script_name=__file__.split('/')[-1][0:-3],
setup=Setup(50, 20),
):
file_name = kw.get('file_name', dr.HOME_DATA + '/' + script_name)
file_name_figs = kw.get('file_name_figs',
dr.HOME_DATA + '/fig/' + script_name)
sd = get_storage_list([net], file_name, '')[0]
d = {}
if from_disk == 0:
print net
dd = {}
for call in kw.get('calls', [
simulate_irregular_firing,
simulate_ahp,
simulate_IV,
simulate_IF,
get_nullcline,
simulate_rebound_spike,
]):
misc.dict_update(dd, {net: call(**kw)})
save(sd, dd)
elif from_disk == 1:
filt = kw.get('filter', [net] + ['IV', 'IF', 'ahp', 'nullcline'] +
['rs_scatter'] +
['rs_voltage_{0}'.format(i) for i in range(6)] +
['irf_voltage_{0}'.format(i) for i in range(3)])
dd = load(sd, *filt)
d = misc.dict_update(d, dd)
return d, file_name_figs
def simulate(from_disk=0,
kw={},
net='Net_0',
script_name=__file__.split('/')[-1][0:-3],
setup=Setup(50,20),
):
file_name = kw.get('file_name', dr.HOME_DATA+'/'+script_name)
file_name_figs = kw.get('file_name_figs', dr.HOME_DATA+'/fig/'+script_name)
sd=get_storage_list([net], file_name, '')[0]
d={}
if from_disk==0:
print net
dd={}
for call in kw.get('calls',[simulate_irregular_firing,
simulate_ahp,
simulate_IV,
simulate_IF,
get_nullcline,
simulate_rebound_spike,]):
misc.dict_update(dd,{net:call(**kw)})
save(sd, dd)
elif from_disk==1:
filt = kw.get('filter', [net]+['IV', 'IF', 'ahp', 'nullcline']
+['rs_scatter']+['rs_voltage_{0}'.format(i) for i in range(6)]
+['irf_voltage_{0}'.format(i) for i in range(3)])
dd = load(sd, *filt)
d = misc.dict_update(d, dd)
return d, file_name_figs
def main(*args, **kwargs):
setup=kwargs.get('setup')#, Setup())
script_name=kwargs.get('script_name')#,__file__.split('/')[-1][0:-3])
builder=kwargs.get('builder')
info, nets, _ = get_networks(builder,
setup.builder(),
setup.director(),
setup.engine(),
setup.default_params())
perturbation_list=kwargs.get('perturbation_list')
perturbation_list+=pl(target_perturbations()[setup.tp_name], '=', **{'name':setup.tp_name})
perturbation_list+=pl(setup.par(), '=', **{'name':setup.tp_name})
add_perturbations(perturbation_list, nets)
key=nets.keys()[0]
file_name = get_file_name(script_name, nets[key].par)
path_nest=get_path_nest(script_name, nets.keys(), nets[key].par)
for val in nets.values():
for key in sorted(val.par['nest'].keys()):
val2=val.par['nest'][key]
if 'weight' in val2.keys():
print key, val2['weight']
for key in sorted(val.par['node'].keys()):
val2=val.par['node'][key]
if 'spike_setup' in val2.keys():
print key, val2['spike_setup']
if 'rate' in val2.keys():
print key, val2['rate']
print setup.tp_name, nets.keys()
pp(nets['Net_1'].par['nest']['GA_GA_gaba']['weight'])
for net in nets.values():
net.set_path_nest(path_nest)
pp(nets['Net_1'].par['nest']['GA_GA_gaba']['weight'])
net.set_opt(setup.opt[net.name])
pp(nets['Net_1'].par['nest']['GA_GA_gaba']['weight'])
# vt=net.voltage_trace()
# import pylab
# ax=pylab.subplot(111)
# vt.plot_voltage_trace(ax)
# pylab.show()
sd_list=get_storage_list(nets.keys(), file_name, info)
for net, sd in zip(nets.values(), sd_list):
nl=Network_list([net])
# pp(net.par.dic['node']['STp'])
kwargs={'model':nl,
'call_get_x0':'get_x0',
'call_get_error':'sim_optimization',
'verbose':True,}
kwargs_fmin={'maxiter':100,
'maxfun':100,
'full_output':1,
'retall':1,
'xtol':.0001,
'ftol':.0001,
'disp':0}
kwargs_fmin={}
kwargs['kwargs_fmin']=kwargs_fmin
f=Fmin('GA_opt', **kwargs)
h=f.fmin()
dd={setup.tp_name.split('_')[0]:{net.name:{'opt':h}}}
save(sd, dd)
]:
kw = {
'gi_amp': 1,
'gi_n': 600,
'gi_st_delay': delay,
'gi_gi_delay': 1.,
'st_gi_delay': delay,
'p_st': p_st,
'sim_time': 3500.0,
'st_amp': 0,
'st_n': 200
}
kw_list.append(kw)
nets = ['Net_{0:0>2}'.format(i) for i in range(len(kw_list))]
sd_list = get_storage_list(nets, path, '')
d = {}
for net, sd, kw in zip(nets, sd_list, kw_list):
if from_disk == 0: # and net=='Net_05':
print net
dd = {net: simulate_network(**kw)}
dd = compute_attrs(dd, net)
save(sd, dd)
if from_disk == 1:
filt = [net] + ['gi', 'st', 'gi_st'] + ['spike_signal']
dd = load(sd, *filt)
pp(dd)
dd = compute_attrs(dd, net)
'if_params':p_st,
'iv_params':p_st,
'iv_I_vec': numpy.arange(-200,0,10),
'model':'my_aeif_cond_exp',
'nc_params':p_st,
'nc_V':numpy.arange(-80,-0,1)}
kw_list.append(kw)
nets=['Net_{0:0>2}'.format(i) for i in range(len(kw_list))]
sd_list=get_storage_list(nets, path, '')
d={}
for net, sd, kw in zip(nets, sd_list, kw_list):
if from_disk==0:# and net=='Net_05':
print net
dd={}
for call in [
simulate_IV,
simulate_IF,
get_nullcline,
simulate_rebound_spike,
]:
misc.dict_update(dd,{net:call(**kw)})
def simulate(builder, from_disk, perturbation_list, script_name, setup):
d_firing_rate = setup.firing_rate()
d_mrs = setup.mean_rate_slices()
attr = [
'firing_rate',
'mean_rate_slices'
]
models = ['M1', 'M2', 'FS', 'ST', 'GA', 'GI', 'SN']
sets = ['set_0', 'set_1']
info, nets, intervals, rep, x_set, y_set = get_networks(builder,
setup.builder(),
setup.director(),
setup.default_params())
add_perturbations(perturbation_list, nets)
for p in sorted(perturbation_list.list):
print p
print nets.keys()
key=nets.keys()[0]
file_name = get_file_name(script_name, nets[key].par)
file_name_figs = get_file_name_figs(script_name, nets[key].par)
path_nest=get_path_nest(script_name, nets.keys(), nets[key].par)
for net in nets.values():
net.set_path_nest(path_nest)
x=range(len(x_set))
xticklabels=[str(a)+'*'+str(b) for a, b in zip(x_set, y_set) ]
d_mrs.update({'intervals':intervals[1],
'repetition':rep,
'set_0':{'x':x, 'xticklabels':xticklabels, 'x_set':x_set},
'set_1':{'x':x, 'xticklabels':xticklabels, 'x_set':y_set},
'sets':[0, 1]})
# d_firing_rate['mean_rate_slices']=d_mrs
#
# d=d_mrs.copy()
# d['intervals']=[[v[0], v[0]+100] for v in intervals[1]]
# d_firing_rate['mean_rate_slices_0']=d
#
# d=d_mrs.copy()
# d['intervals']=[[v[1]-100, v[1]] for v in intervals[1]]
#
# d_firing_rate['mean_rate_slices_1']=d
#
kwargs_dic = {
'firing_rate':d_firing_rate,
'mean_rate_slices': d_mrs
}
# Adding nets no file name
sd_list=get_storage_list(nets, file_name, info)
from_disks, d = main_loop(from_disk, attr, models,
sets, nets, kwargs_dic, sd_list,
**{'attrs_load':['mean_rate_slices']})
return file_name, file_name_figs, from_disks, d, models
def plot(file_name, figs, setup, flag, **k):
nets = ['Net_0', 'Net_1']
attr = ['firing_rate', 'mean_rates', 'spike_statistic']
attr2 = ['psd', 'activity_histogram', 'activity_histogram_stat']
attr_coher = ['phase_diff', 'phases_diff_with_cohere', 'mean_coherence']
models = ['M1', 'M2', 'FS', 'GI', 'GA', 'ST', 'SN', 'GP']
models_coher = [
'GI_GA',
'GI_GI',
'GA_GA',
'GA_ST',
'GI_ST',
'GP_GP',
'ST_ST',
'GP_ST',
]
# Adding nets no file name
sd_list = get_storage_list(nets, file_name, '')
d = {}
for sd, net in zip(sd_list, nets):
filt = ([net] + models + models_coher + attr + attr2 + attr_coher)
dd = load(sd, *filt)
# cmp_statistical_test(models, dd)
d = misc.dict_update(d, dd)
kw = setup.plot_summed2()
kw['alphas'] = [1., 1.]
kw['coherence_xcut'] = [0, 50]
kw['coherence_color'] = ['grey', 'k']
kw['coherence_p_conf95_linestyle'] = '--'
kw['hatchs_ti_ti'] = ['', '']
kw['label_model'] = 'Black=Model'
kw['label_exp'] = 'White=Exp., Mallet et al 2008'
kw['linewidth'] = 1.
kw['set_text_on_bars'] = False
kw['top_label'] = False
kw['phases_diff_with_cohere_colors'] = ['grey', 'k']
kw['phases_diff_with_cohere_xcut'] = [-numpy.pi * 0.97, numpy.pi**0.97]
kw['phases_diff_with_cohere_remove_peaks'] = True
kw['scale'] = 1
kw['spk_stats_color_axis'] = 1
kw['spk_stats_colors'] = ['k', 'w']
kw['spk_stats_colors_ti_ta'] = ['k', 'w']
kw['xlim_cohere'] = [-1, 51]
kw.update(k)
figs.append(base_oscillation.show_summed2(d, **kw))
kw = setup.plot_summed_STN()
kw['alphas'] = [1., 1.]
kw['coherence_color'] = ['grey', 'k']
kw['coherence_p_conf95_linestyle'] = '--'
kw['hatchs_ti_ti'] = ['', '']
kw['label_model'] = 'Black=Model'
kw['label_exp'] = 'White=Exp., Mallet et al 2008'
kw['linewidth'] = 1.
kw['phases_diff_with_cohere_xcut'] = [-numpy.pi * 0.97, numpy.pi**0.97]
kw['phases_diff_with_cohere_remove_peaks'] = True
kw['phases_diff_with_cohere_colors'] = ['grey', 'k']
kw['scale'] = 1
kw['set_text_on_bars'] = False
kw['spk_stats_colors'] = ['k', 'w']
kw['spk_stats_colors_ti_ta'] = ['k', 'w']
kw['spk_stats_color_axis'] = 1
kw['top_label'] = False
kw['xlim_cohere'] = [-1, 51]
if flag == 'slow_wave':
kw['ylim_cohere'] = [0, 1.0]
elif flag == 'beta':
kw['ylim_cohere'] = [0, 0.4]
kw['coherence_xcut'] = [0, 50]
kw.update(k)
figs.append(base_oscillation.show_summed_STN(d, **kw))
return figs
def main(*args, **kwargs):
setup = kwargs.get('setup') #, Setup())
script_name = kwargs.get('script_name') #,__file__.split('/')[-1][0:-3])
builder = kwargs.get('builder')
info, nets, _ = get_networks(builder, setup.builder(), setup.director(),
setup.engine(), setup.default_params())
perturbation_list = kwargs.get('perturbation_list')
perturbation_list += pl(target_perturbations()[setup.tp_name], '=',
**{'name': setup.tp_name})
perturbation_list += pl(setup.par(), '=', **{'name': setup.tp_name})
add_perturbations(perturbation_list, nets)
key = nets.keys()[0]
file_name = get_file_name(script_name, nets[key].par)
path_nest = get_path_nest(script_name, nets.keys(), nets[key].par)
for val in nets.values():
for key in sorted(val.par['nest'].keys()):
val2 = val.par['nest'][key]
if 'weight' in val2.keys():
print key, val2['weight']
for key in sorted(val.par['node'].keys()):
val2 = val.par['node'][key]
if 'spike_setup' in val2.keys():
print key, val2['spike_setup']
if 'rate' in val2.keys():
print key, val2['rate']
print setup.tp_name, nets.keys()
pp(nets['Net_1'].par['nest']['GA_GA_gaba']['weight'])
for net in nets.values():
net.set_path_nest(path_nest)
pp(nets['Net_1'].par['nest']['GA_GA_gaba']['weight'])
net.set_opt(setup.opt[net.name])
pp(nets['Net_1'].par['nest']['GA_GA_gaba']['weight'])
# vt=net.voltage_trace()
# import pylab
# ax=pylab.subplot(111)
# vt.plot_voltage_trace(ax)
# pylab.show()
sd_list = get_storage_list(nets.keys(), file_name, info)
for net, sd in zip(nets.values(), sd_list):
nl = Network_list([net])
# pp(net.par.dic['node']['STp'])
kwargs = {
'model': nl,
'call_get_x0': 'get_x0',
'call_get_error': 'sim_optimization',
'verbose': True,
}
kwargs_fmin = {
'maxiter': 100,
'maxfun': 100,
'full_output': 1,
'retall': 1,
'xtol': .0001,
'ftol': .0001,
'disp': 0
}
kwargs_fmin = {}
kwargs['kwargs_fmin'] = kwargs_fmin
f = Fmin('GA_opt', **kwargs)
h = f.fmin()
dd = {setup.tp_name.split('_')[0]: {net.name: {'opt': h}}}
save(sd, dd)
attr2=['psd',
'activity_histogram',
'activity_histogram_stat']
attr_coher = [
'phase_diff',
'phases_diff_with_cohere',
'mean_coherence'
]
models = ['M1', 'M2', 'FS', 'GI', 'GA', 'ST', 'SN', 'GP']
models_coher = ['GI_GA', 'GI_GI', 'GA_GA', 'GA_ST', 'GI_ST', 'GP_GP',
'ST_ST', 'GP_ST',]
# Adding nets no file name
sd_list=get_storage_list(nets, file_name, '')
d = {}
for sd, net in zip(sd_list, nets):
filt = ([net]
+ models + models_coher
+ attr + attr2 + attr_coher)
dd = load(sd, *filt)
# cmp_statistical_test(models, dd)
d = misc.dict_update(d, dd)
def plot(file_name, figs, setup, flag, **k):
nets=['Net_0', 'Net_1']
attr = [
'firing_rate',
'mean_rates',
'spike_statistic'
]
attr2=['psd',
'activity_histogram',
'activity_histogram_stat']
attr_coher = [
'phase_diff',
'phases_diff_with_cohere',
'mean_coherence'
]
models = ['M1', 'M2', 'FS', 'GI', 'GA', 'ST', 'SN', 'GP']
models_coher = ['GI_GA', 'GI_GI', 'GA_GA', 'GA_ST', 'GI_ST', 'GP_GP',
'ST_ST', 'GP_ST',]
# Adding nets no file name
sd_list=get_storage_list(nets, file_name, '')
d = {}
for sd, net in zip(sd_list, nets):
filt = ([net]
+ models + models_coher
+ attr + attr2 + attr_coher)
dd = load(sd, *filt)
# cmp_statistical_test(models, dd)
d = misc.dict_update(d, dd)
kw=setup.plot_summed2()
kw['alphas']=[1.,1.]
kw['coherence_xcut']=[0,50]
kw['coherence_color']=['grey', 'k']
kw['coherence_p_conf95_linestyle']='--'
kw['hatchs_ti_ti']=['','']
kw['label_model']='Black=Model'
kw['label_exp']='White=Exp., Mallet et al 2008'
kw['linewidth']=1.
kw['set_text_on_bars']=False
kw['top_label']=False
kw['phases_diff_with_cohere_colors']=['grey','k']
kw['phases_diff_with_cohere_xcut']=[-numpy.pi*0.97, numpy.pi**0.97]
kw['phases_diff_with_cohere_remove_peaks']=True
kw['scale']=1
kw['spk_stats_color_axis']=1
kw['spk_stats_colors']=['k', 'w']
kw['spk_stats_colors_ti_ta']=['k','w']
kw['xlim_cohere']=[-1, 51]
kw.update(k)
figs.append(base_oscillation.show_summed2(d, **kw))
kw=setup.plot_summed_STN()
kw['alphas']=[1.,1.]
kw['coherence_color']=['grey','k']
kw['coherence_p_conf95_linestyle']='--'
kw['hatchs_ti_ti']=['','']
kw['label_model']='Black=Model'
kw['label_exp']='White=Exp., Mallet et al 2008'
kw['linewidth']=1.
kw['phases_diff_with_cohere_xcut']=[-numpy.pi*0.97, numpy.pi**0.97]
kw['phases_diff_with_cohere_remove_peaks']=True
kw['phases_diff_with_cohere_colors']=['grey','k']
kw['scale']=1
kw['set_text_on_bars']=False
kw['spk_stats_colors']=['k', 'w']
kw['spk_stats_colors_ti_ta']=['k','w']
kw['spk_stats_color_axis']=1
kw['top_label']=False
kw['xlim_cohere']=[-1, 51]
if flag=='slow_wave':
kw['ylim_cohere']=[0, 1.0]
elif flag=='beta':
kw['ylim_cohere']=[0, 0.4]
kw['coherence_xcut']=[0,50]
kw.update(k)
figs.append(base_oscillation.show_summed_STN(d, **kw))
return figs
