def SimSpikingStimulus(stim1, stim2, time=1000, t_sim=None):
'''
Times must be sorted. ex: times = [0, 1, 2] ; scale = [1,0] *poisson*:
integer, output is a poisson process with mean data/poisson, scaled by
*poisson*.
'''
n = stim1.shape[1]
SL = pyST.SpikeList(id_list=range(n+n-2))
times = range(0, len(stim1)*time, time)
for i in range(n):
if np.any(stim1[:, i] > 0):
SL[i] = pyST.STCreate.inh_poisson_generator(stim1[:, i],
times,
t_stop=t_sim)
for i in range(n-2):
if np.any(stim2[:, i] > 0):
SL[n+i] = pyST.STCreate.inh_poisson_generator(stim2[:, i-n+2],
times,
t_stop=t_sim)
plus_times1 = np.array([100]*32)+np.arange(0,2*time*32,2*time)
plus_times2 = np.array([2*time]*32)+np.arange(0,2*time*32,2*time)
plus_times = np.concatenate([plus_times1,plus_times2])
minus_times1 = np.array([time]*32)+np.arange(0,2*time*32,2*time)
minus_times2 = np.array([time+100]*32)+np.arange(0,2*time*32,2*time)
minus_times = np.concatenate([minus_times1,minus_times2])
SL[0] = pyST.SpikeTrain(np.sort(plus_times))
SL[1] = pyST.SpikeTrain(np.sort(minus_times))
return SL
def SimSpikingStimulus(t_sim=None):
SL = pyST.SpikeList(id_list=[0, 1, 2, 3])
spk_train0 = [60, 110]
spk_train1 = [10, 75, 140]
spk_train2 = [15, 80, 135]
spk_train3 = [20, 130]
SL[0] = pyST.SpikeTrain(spk_train0, t_start=1)
SL[1] = pyST.SpikeTrain(spk_train1, t_start=1)
SL[2] = pyST.SpikeTrain(spk_train2, t_start=1)
SL[3] = pyST.SpikeTrain(spk_train3, t_start=1)
return SL