index_syn = perceptron_pop.synapses["learning"].addr['syntype'] == syn
index_tot = index_syn & index_syn_neu
this_syn = perceptron_pop.synapses["learning"][index_tot]
stim = this_syn.spiketrains_poisson(165, duration=650)
#stimulus virtual synapse post neuron
index_syn_neu_virt = perceptron_pop.synapses["virtual_exc"].addr[
'neu'] == neu
syn_virt = perceptron_pop.synapses["virtual_exc"][index_syn_neu_virt]
stim_v = syn_virt.spiketrains_poisson(100, duration=650)
final_stim = pyNCS.pyST.merge_sequencers(stim_v, stim)
nsetup.stimulate(final_stim, send_reset_event=False)
#
osc_a = pyAgilent.Agilent(host="172.19.10.159")
osc_a._send_command('WAV:FORM RAW')
osc_b = pyAgilent.Agilent(host="172.19.10.156")
osc_b._send_command('WAV:FORM RAW')
membrane = osc_b._read_data_from_channel(2)
weight = osc_b._read_data_from_channel(1)
pre = stim[1].raw_data()[:, 0] #osc_b._read_data_from_channel(3)
up = osc_a._read_data_from_channel(2)
dn = osc_a._read_data_from_channel(3)
calc = osc_b._read_data_from_channel(4)
time = np.linspace(0, 1000, len(membrane))
creq = osc_a._read_data_from_channel(4)
post_exc = stim_v[1].raw_data()[:, 0]
figure()
import pyAgilent
from pylab import *
import matplotlib
import numpy as np
import sys
#init oscilloscope
osc = pyAgilent.Agilent(host="172.19.10.159");
#osc._send_command('WAV:FORM ASC');
#osc._send_command('WAV:POIN:MODE RAW');
#osc._send_command('WAV:POINTS 2000000');
osc.engage()
up = osc._read_data_from_channel(2)
dn = osc._read_data_from_channel(1)
amp = osc._read_data_from_channel(4)
gout = osc._read_data_from_channel(3)
time_up = np.linspace(0,5,len(up))
time_dn = np.linspace(0,5,len(dn))
time_amp = np.linspace(0,5,len(amp))
time_gout = np.linspace(0,5,len(gout))
np.savetxt('sine_100/time_up.txt', time_up )
np.savetxt('sine_100/up.txt', up)
np.savetxt('sine_100/time_dn.txt', time_dn )
np.savetxt('sine_100/dn.txt', dn)
np.savetxt('sine_100/time_amp.txt', time_amp )
np.savetxt('sine_100/amp.txt', amp)
np.savetxt('sine_100/time_gout.txt', time_gout )