def perturbations():
sim_time = 10000.0
size = 20000.0
threads = 1
freqs = [1., 2.0]
path = ('/home/mikael/results/papers/inhibition' +
'/network/simulate_inhibition_ZZZ4/')
l = op.get()[-3:]
for i in range(len(l)):
l[i] += pl(
{
'simu': {
'sim_time': sim_time,
'sim_stop': sim_time,
'threads': threads
},
'netw': {
'size': size
}
}, '=')
damp = process(path, freqs)
for key in sorted(damp.keys()):
val = damp[key]
print numpy.round(val, 2), key
ll = []
for i, _l in enumerate(l):
for j, _ in enumerate(freqs):
amp = [numpy.round(damp[_l.name][j], 2), 1]
d = {
'type': 'oscillation2',
'params': {
'p_amplitude_mod': amp[0],
'p_amplitude0': amp[1],
'freq': 20.
}
}
_ll = deepcopy(_l)
dd = {}
for key in ['C1', 'C2', 'CF', 'CS']:
dd = misc.dict_update(dd, {'netw': {'input': {key: d}}})
_ll += pl(dd, '=', **{'name': 'amp_{0}-{1}'.format(*amp)})
ll.append(_ll)
return ll, threads
def pert_add_oscillations(**kwargs):
amp_base = kwargs.get('amp_base') # Scaling of base frequency
amp_base_skip = kwargs.get(
'amp_base_skip',
[]) #skip amplitude modulation for nuclies in this list
do_reset = kwargs.get(
'do_reset',
True) #reset simulations between runs in engine.py with nest.reset
down_vec = kwargs.get('down_vec') #?
freqs = kwargs.get('freqs') # Frequency amplitude modulation
freq_oscillation = kwargs.get('freq_oscillation')
external_input_mod = kwargs.get('external_input_mod', [])
input_mod = kwargs.get('input_mod', ['C1', 'C2', 'CF', 'CS'])
no_mod = kwargs.get('no_mod', [])
local_num_threads = kwargs.get('local_num_threads')
null_down = kwargs.get('null_down', False)
null_down_STN = kwargs.get('null_down_stn', False)
path_rate_runs = kwargs.get('path_rate_runs')
perturbation_list = kwargs.get('perturbation_list')
sim_time = kwargs.get('sim_time')
size = kwargs.get('size')
STN_amp_mod = kwargs.get('STN_amp_mod', [1.])
tuning_freq_amp_to = kwargs.get('tuning_freq_amp_to', 'M1')
l = perturbation_list
for i in range(len(l)):
l[i] += pl(
{
'simu': {
'do_reset': do_reset,
'sd_params': {
'to_file': True,
'to_memory': False
},
'sim_time': sim_time,
'sim_stop': sim_time,
'local_num_threads': local_num_threads
},
'netw': {
'size': size
}
}, '=')
kw_process = {'freqs': freqs, 'tuning_freq_amp_to': tuning_freq_amp_to}
damp = process(path_rate_runs, **kw_process)
for key in sorted(damp.keys()):
val = damp[key]
print key, numpy.round(val, 2)
ll = []
for j, i, STN_amp, _l in iterator_oscillations(freqs, STN_amp_mod, l):
amp = [numpy.round(damp[_l.name][j], 2), amp_base[j]]
_l = deepcopy(_l)
dd = {}
for key in input_mod:
if key in ['C1', 'C2', 'CF']:
factor = 1
elif key in ['CS']:
factor = STN_amp
if null_down:
down = -1.
elif null_down_STN and key in ['CS']:
down = -1
elif down_vec:
down = down_vec[j]
else:
down = -amp[0] * factor
if key not in amp_base_skip:
amp0 = amp[1]
else:
amp0 = 1.
if amp0 > 1.0:
pass
upp = amp[0]
# print amp, amp0
if (key in no_mod): upp, down = 0., 0.
d = {
'type': 'oscillation2',
'params': {
'p_amplitude_upp': upp * factor,
'p_amplitude_down': down,
'p_amplitude0': amp0,
'freq': freq_oscillation
}
}
dd = misc.dict_update(dd, {'netw': {'input': {key: d}}})
if STN_amp != 1:
_l += pl(
dd, '=',
**{'name': 'amp_{0}_{1}_stn_{2}'.format(upp, amp[1], STN_amp)})
elif down_vec:
_l += pl(dd, '=',
**{'name': 'amp_{0}_{1}_{2}'.format(upp, down, amp[1])})
else:
_l += pl(dd, '=', **{'name': 'amp_{0}_{1}'.format(*[upp, amp[1]])})
if external_input_mod:
dd = {}
for key in external_input_mod:
dd = misc.dict_update(dd, {'node': {key: {'rate': amp0}}})
_l += pl(dd, '*', **{'name': 'EIEA_{0}'.format(amp0)})
ll.append(_l)
return ll
def get_setup_args_and_kwargs(i_p_list, **kwargs):
amp_base = kwargs.get('amp_base')
amp_base_skip = kwargs.get('amp_base_skip')
duration = kwargs.get('duration')
freqs = kwargs.get('freqs')
freq_oscillations = kwargs.get('freq_oscillations')
home = kwargs.get('home')
home_data = kwargs.get('home_data')
home_module = kwargs.get('home_module')
input_type = kwargs.get('input_type', 'burst3')
labels = kwargs.get('labels', [
'Only D1', 'D1,D2', 'MSN lesioned (D1, D2)',
'FSN lesioned (D1, D2)', 'GPe TA lesioned (D1,D2)'
])
laptime = kwargs.get('laptime')
l_mean_rate_slices = kwargs.get('l_mean_rate_slices')
local_num_threads = kwargs.get('local_num_threads')
other_scenario = kwargs.get('other_scenario', False)
# oscillation_returbations_index=kwargs.get('oscillation_returbations_index')
p_pulses = kwargs.get('p_pulses')
path_rate_runs = kwargs.get('path_rate_runs')
perturbation_list = kwargs.get('perturbation_list')
props_conn = kwargs.get('proportion_connected', 1.)
res = kwargs.get('res')
rep = kwargs.get('rep')
STN_amp_mod = kwargs.get('STN_amp_mod')
threshold = kwargs.get('threshold')
time_bin = kwargs.get('time_bin')
tuning_freq_amp_to = kwargs.get('tuning_freq_amp_to')
kw_process = {'freqs': freqs, 'tuning_freq_amp_to': tuning_freq_amp_to}
damp = process(path_rate_runs, **kw_process) #freq in kwargs
for key in sorted(damp.keys()):
val = damp[key]
print key, numpy.round(val, 2)
freqs = numpy.round(damp[perturbation_list[0].name][0], 2)
if type(props_conn) == list:
print i_p_list
pc = props_conn[i_p_list]
else:
pc = props_conn
kwargs = {
'amp_base': amp_base,
'amp_base_skip': amp_base_skip,
'duration': duration,
'freqs': freqs,
'freq_oscillations': freq_oscillations,
'home': home,
'home_data': home_data,
'home_module': home_module,
'input_type': input_type,
'l_mean_rate_slices': l_mean_rate_slices,
'labels': labels,
'laptime': laptime,
'local_num_threads': local_num_threads,
'other_scenario': other_scenario,
'proportion_connected': pc,
'p_pulses': p_pulses,
'resolution': res,
'repetition': rep,
'STN_amp_mod': STN_amp_mod,
'threshold': threshold,
'time_bin': time_bin,
}
return [], kwargs
