def get_volts(mtype, etype, param_ind, nsamples):
all_volts = []
my_model = get_model('BBP', log, m_type=mtype, e_type=etype, cell_i=0)
param_set = make_paramset(my_model, param_ind, nsamples)
#param_name = my_model.PARAM_NAMES[param_ind]
for i in range(nsamples):
params = param_set[i]
my_model = get_model('BBP', log, mtype, etype, 0, *params)
my_model.DEFAULT_PARAMS = False
volts = my_model.simulate(stim, 0.02)
all_volts.append(volts)
return all_volts
def main():
NTHREADS = 128
m_type = sys.argv[1]
e_type = sys.argv[2]
nsamples = int(sys.argv[3])
try:
procid = int(os.environ['SLURM_PROCID'])
print("in cori")
except:
print("not in cori")
procid = 0
my_model = get_model('BBP', log, m_type=m_type, e_type=e_type, cell_i=1)
def_vals = my_model.DEFAULT_PARAMS
pnames = [
my_model.PARAM_NAMES[i] for i in range(len(def_vals))
if def_vals[i] > 0
]
threads_per_param = int(NTHREADS / len(pnames))
samples_per_thread = int(nsamples / threads_per_param) + 1
p_ind = procid % (len(pnames))
adjusted_param = my_model.PARAM_NAMES[p_ind]
print("working on " + adjusted_param + "will be sampled " +
str(samples_per_thread * threads_per_param))
all_volts = get_volts(m_type, e_type, p_ind, samples_per_thread)
pkl_fn = m_type + '_' + e_type + adjusted_param + '_' + str(
procid) + '.pkl'
with open(pkl_fn, 'wb') as output:
pkl.dump(all_volts, output)
def get_volts(mtype, etype, param_ind, nsamples):
all_volts = []
my_model = get_model('BBP', log, m_type=mtype, e_type=etype, cell_i=1)
param_set = make_paramset(my_model, param_ind, nsamples)
#param_name = my_model.PARAM_NAMES[param_ind]
for i in range(nsamples):
s_time = time.time()
print("working on param_ind" + str(param_ind) + " sample" + str(i))
params = param_set[i]
my_model = get_model('BBP', log, mtype, etype, 1, *params)
my_model.DEFAULT_PARAMS = False
volts = my_model.simulate(stim, 0.025)
all_volts.append(volts)
end_time = time.time()
etime = end_time - s_time
print("done param_ind" + str(param_ind) + " sample" + str(i) +
str(etime))
return all_volts
def main(m_type,e_type):
nsamples = 2
try:
procid = int(os.environ['SLURM_PROCID'])
print("in cori")
nsamples = 20
except:
print("not in cori")
procid = 0
nsamples = 2
my_model = get_model('BBP',log,m_type=m_type,e_type=e_type,cell_i=1)
adjusted_param = my_model.PARAM_NAMES[procid]
print("working on " + adjusted_param)
all_volts = get_volts(m_type,e_type,procid,nsamples)
pkl_fn=m_type + e_type + adjusted_param +'.pkl'
with open(pkl_fn, 'wb') as output:
pkl.dump(all_volts,output)
def main():
short_name = None
m_type = sys.argv[1]
e_type = sys.argv[2]
try:
short_name = sys.argv[3]
except:
print('no short name')
short_name = None
files_loc = './output/' + m_type + '_' + e_type + '/'
my_model = get_model('BBP', log, m_type=m_type, e_type=e_type, cell_i=0)
def_vals = my_model.DEFAULT_PARAMS
ECDS = test_sensitivity(files_loc, my_model)
#if short_name is not None:
if short_name is not None:
ml_results = get_ml_results(short_name, list(ECDS.keys()))
analyze_ecds(ECDS, def_vals, files_loc, ml_results)
else:
analyze_ecds_no_ML(ECDS, def_vals, files_loc)
def test_sensitivity(mtype, etype):
my_model = get_model('BBP', log, m_type=mtype, e_type=etype, cell_i=0)
def_volts = my_model.simulate(stim, 0.02)
param_names = my_model.PARAM_NAMES
all_ECDS = {}
for i in range(len(param_names)):
adjusted_param = my_model.PARAM_NAMES[i]
all_volts = get_volts(mtype, etype, i, 5)
curr_errs = check_param_sensitivity(all_volts, def_volts,
adjusted_param)
curr_ECDs = [ls[-1] for ls in curr_errs]
all_ECDS[adjusted_param] = curr_ECDs
pkl_fn = mtype + etype + adjusted_param + '.pkl'
with open(pkl_fn, 'wb') as output:
pkl.dump(def_volts, output)
pkl.dump(all_volts, output)
pkl_fn = mtype + etype + 'sensitivity.pkl'
with open(pkl_fn, 'wb') as output:
pkl.dump(all_ECDS, output)
pkl.dump(param_names)
import logging as log
from neuron import h
from run import get_model
from get_rec_points import get_rec_points
import sys
# model = get_model('BBP', log, 'L4_BTC', 'cNAC', 0)
m_type = sys.argv[1]
e_type = sys.argv[2]
model = get_model('BBP', log, m_type, e_type, 0)
x = get_rec_points(model.entire_cell)
y = get_rec_points(model.entire_cell)
print("First time: {}".format(x))
print("Second time: {}".format(y))
print("First time: {} rec points".format(len(x)))
print("Second time: {} rec points".format(len(y)))
h("segcount=0")
h('forall {segcount+=1}')
print("total number of segments")
h("print segcount")
ax_dend.axhline(threshold_dend, color='red')
ax_dend.grid()
ax_soma.grid()
ax_soma.title.set_text('Somatic Parameters')
means_soma = np.clip(means_soma, 0, ymx_soma)
STDs_soma = np.clip(STDs_soma, 0, ymx_soma / 2)
ax_soma.errorbar(range(len(pnames_soma)),
means_soma,
STDs_soma,
linestyle='None',
marker='s')
ax_soma.set_xticks(range(len(pnames_soma)))
ax_soma.set_xticklabels(pnames_soma)
ax_soma.axhline(threshold_soma, color='red')
fig_name = mtype + etype + str(nsamples) + 'Analysis.pdf'
fig.savefig(fig_name)
plt.show()
return params_sensitivity_dict
nsamples = 50
mtype = 'L1_DAC'
etype = 'bNAC'
my_model = get_model('BBP', log, m_type=mtype, e_type=etype, cell_i=1)
#def_volts = my_model.simulate(stim,0.02)
def_volts = None
def_vals = my_model.DEFAULT_PARAMS
ECDS = test_sensitivity(mtype, etype, def_volts, nsamples)
analyze_ecds(ECDS, def_vals)
def get_cur():
user = raw_input('Please input user_name: ')
database = raw_input('Please input a name of the database: ')
table_name = raw_input('Please input a name of the data table: ')
return get_model(user, database, table_name)