import sys
import pickle
import time
from peakdet import peakdet
import numpy as np
# Loads a list with path points for each time-series point
time1 = time.time()
def extract_spiketimes(neuron_type, condition, ntrial, nrun):
'''
Extract Spike Times from NEUORN's voltage trace
Nneurons: number of neurons to be analyzed
condition: Specific Lesion
ntrial: mouse ID
nrun: number of trial/run
'''
dt = 0.1
filepath = '../'+condition+'/Trial_'+str(ntrial)+'/Run_'+str(nrun)
# Peakdet parameters
delta = 1
if neuron_type == '_pvsoma_':
Nneurons = 130
thres = 0
elif neuron_type == '_bcell_':
Nneurons = 8
thres = 0
elif neuron_type == '_vipcck_' or neuron_type == '_vipcrnvm_':
Nneurons = 1
thres = 0
elif neuron_type == '_vipcr_':
Nneurons = 4
thres = 0
else:
Nneurons = 2
thres = 0
print(Nneurons)
spiketimes_all = []
for n_neuron in range(Nneurons):
filename = filepath+'/Trial_'+ntrial+'_Run_' + \
nrun+neuron_type+str(n_neuron)+'.dat'
path = np.loadtxt('../make_inputs_linear_track/runs_produced_by_python_ec_rand_stops/run_'
+ nrun+'/path.txt', 'int', delimiter=' ')
tot_time = np.sum(np.bincount(path[:, 0])) # in ms
data = np.loadtxt(filename)
# remove the first 400ms
data = data[int(400/dt):int(tot_time/dt)+1]
maxtab, mintab = peakdet(data, delta, thres)
if maxtab.size != 0:
spiketimes = [round(float(i*dt), 1) for i in maxtab[:, 0]]
else:
spiketimes = []
spiketimes.insert(0, str(n_neuron))
spiketimes_all.append(spiketimes)
# Saves the list in a pickle file at the specified Run directory
filewrite = filepath + '/spiketimes' + neuron_type + '.pkl'
with open(filewrite, 'wb') as handle:
pickle.dump(spiketimes_all, handle, protocol=pickle.HIGHEST_PROTOCOL)
ntype = sys.argv[1]
cond = sys.argv[2]
trial = sys.argv[3]
run = sys.argv[4]
results = extract_spiketimes(ntype, cond, trial, run)
print("\nEverything was ok for pyramidals. Case: " +
cond+" "+str(trial)+" "+str(run))
time2 = time.time()
duration = round(time2-time1, 3)
print("\n The analysis run for "+str(duration)+" seconds")