def run(fnames):
# Call the C NSAT
print('Begin %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
cfg = nsat.ConfigurationNSAT.readfileb(fnames.pickled)
nsat.run_c_nsat(fnames)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, fnames)
states = c_nsat_reader.read_c_nsat_states()
states_core0 = states[0][1]
# np.save('states', states_core0)
in_spikelist = SL
ifname = fnames.events + '_core_0.dat'
out_spikelist = nsat.importAER(nsat.read_from_file(ifname),
sim_ticks=sim_ticks,
id_list=[0])
# Plot the results
fig = plt.figure(figsize=(10, 10))
for i in range(1, 9):
ax = fig.add_subplot(8, 1, i)
ax.plot(states_core0[:-1, 15, i - 1], 'b', lw=1.5)
# fig = plt.figure(figsize=(10, 10))
# for i in range(1, 9):
# ax = fig.add_subplot(8, 1, i)
# ax.plot(states_core0[:-1, 16, i-1], 'b', lw=1.5)
# out_spikelist.raster_plot()
plt.savefig('/tmp/%s.png' %
(os.path.splitext(os.path.basename(__file__))[0]))
plt.close()
print('End %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
def run():
# Call the C NSAT
print('Begin %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
cfg = nsat.ConfigurationNSAT.readfileb(nsat.fnames.pickled)
nsat.run_c_nsat()
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, nsat.fnames)
states = c_nsat_reader.read_c_nsat_states()
time_core0, states_core0 = states[0][0], states[0][1]
out_spikelist = nsat.importAER(nsat.read_from_file(nsat.fnames.events +
'_core_0.dat'),
sim_ticks=sim_ticks,
id_list=[0])
# Plot the results
fig = plt.figure(figsize=(10, 10))
for i in range(1, 9):
ax = fig.add_subplot(8, 1, i)
ax.plot(states_core0[:, 0, i - 1], 'b', lw=2)
plt.savefig('/tmp/%s.png' %
(os.path.splitext(os.path.basename(__file__))[0]))
plt.close()
print('Begin %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
def run():
# Call the C NSAT
print('Begin %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
cfg = nsat.ConfigurationNSAT.readfileb(nsat.fnames.pickled)
nsat.run_c_nsat()
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, nsat.fnames)
states = c_nsat_reader.read_c_nsat_states()
states_core0 = states[0][1]
# wt = c_nsat_reader.read_c_nsat_weights_evo(0)[:, 1, 1]
wt, pids = c_nsat_reader.read_synaptic_weights_history(post=[0])
in_spikelist = SL
out_spikelist = nsat.importAER(nsat.read_from_file(nsat.fnames.events+'_core_0.dat'),
sim_ticks=sim_ticks,
id_list=[0])
# Plot the results
fig = plt.figure(figsize=(10, 10))
i = 1
ax = fig.add_subplot(4, 1, i)
ax.plot(states_core0[:-1, 0, i - 1], 'b', lw=3, label='$V_m$')
ax.set_ylabel('$V_m$')
ax.set_xticks([])
plt.locator_params(axis='y', nbins=4)
i = 2
ax = fig.add_subplot(4, 1, i)
ax.plot(states_core0[:-1, 0, i - 1], 'b', lw=3, label='$I_{syn}$')
ax.set_ylabel('$I_{syn}$')
ax.set_xticks([])
plt.locator_params(axis='y', nbins=4)
for t in SL[0].spike_times:
plt.axvline(t, color='k')
i = 4
ax = fig.add_subplot(4, 1, i)
for t in SL[0].spike_times:
plt.axvline(t, color='k')
ax.plot(states_core0[:-1, 0, 2], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$x_m$')
plt.axhline(0, color='b', alpha=.5, linewidth=3)
plt.locator_params(axis='y', nbins=4)
i = 3
ax = fig.add_subplot(4, 1, i)
for t in SL[0].spike_times:
plt.axvline(t, color='k')
ax.plot(wt[0][:, 1, 1], 'r', lw=3)
ax.set_ylabel('$w$')
ax.set_xticks([])
plt.locator_params(axis='y', nbins=4)
plt.savefig('/tmp/%s.png' % (os.path.splitext(os.path.basename(__file__))[0]))
plt.close()
print('End %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
def run():
# Call the C NSAT
print('Begin %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
cfg = nsat.ConfigurationNSAT.readfileb(nsat.fnames.pickled)
nsat.run_c_nsat()
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, nsat.fnames)
states = c_nsat_reader.read_c_nsat_states()
states_core0 = states[0][1]
plt.figure()
for i in range(1, 5):
plt.subplot(4, 1, i)
plt.plot(states_core0[:, :, i - 1])
plt.figure()
S = np.maximum(states_core0[:, :, 0], 0)
plt.imshow(
S,
interpolation='spline36',
cmap=plt.get_cmap('gray'), #plt.cm.gray,
aspect='auto',
origin='lower')
spks = nsat.importAER(nsat.read_from_file(nsat.fnames.events +
'_core_0.dat'),
sim_ticks=sim_ticks,
id_list=list(range(cfg.core_cfgs[0].n_neurons)))
try:
raster = spks.raster_plot()
raster.savefig('/tmp/%s_raster.png' %
(os.path.splitext(os.path.basename(__file__))[0]))
raster.close()
except:
print('test_nf: Failed to generate /tmp/%s_raster.png' %
(os.path.splitext(os.path.basename(__file__))[0]))
# Plot the results
# events = spks.convert()
# mat = np.zeros((sim_ticks, N_NEURONS[0]))
# print(mat.shape)
# print(len(events[0]))
# print(len(events[1]))
# mat[events[0].astype('i'), events[1].astype('i')] = 1
plt.savefig('/tmp/%s.png' %
(os.path.splitext(os.path.basename(__file__))[0]))
plt.close()
print('End %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
def run(fnames):
# Call the C NSAT
print('Begin %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
cfg = nsat.ConfigurationNSAT.readfileb(fnames.pickled)
nsat.run_c_nsat(fnames)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, fnames)
states = c_nsat_reader.read_c_nsat_states()
time_core0, states_core0 = states[0][0], states[0][1]
wt, _ = c_nsat_reader.read_c_nsat_weights_evo([0, 1])
wt = wt[0]
out_spikelist = nsat.importAER(nsat.read_from_file(fnames.events +
'_core_0.dat'),
sim_ticks=sim_ticks)
# Plot the results
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(4, 2, 1)
ax.plot(states_core0[:-1, 0, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 2)
ax.plot(states_core0[:-1, 1, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 3)
ax.plot(states_core0[:-1, 0, 1], 'b', lw=3, label='$I_{syn}$')
ax.set_ylabel('$I_{syn}$')
ax = fig.add_subplot(4, 2, 4)
ax.plot(states_core0[:-1, 1, 1], 'b', lw=3, label='$I_{syn}$')
ax.set_ylabel('$I_{syn}$')
ax = fig.add_subplot(4, 2, 5)
ax.plot(states_core0[:-1, 0, 2], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$x_m$')
ax = fig.add_subplot(4, 2, 6)
ax.plot(states_core0[:-1, 1, 2], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$x_m$')
ax = fig.add_subplot(4, 2, 7)
ax.plot(wt[:, 1, 1], 'r', lw=3)
ax.set_ylabel('$w$')
ax = fig.add_subplot(4, 2, 8)
ax.plot(wt[:, 0, 1], 'r', lw=3)
ax.set_ylabel('$w$')
fig = plt.figure(figsize=(10, 5))
plt.plot(wt[:, 0, 1], 'r', lw=2, zorder=10)
plt.plot(wt[:, 1, 1], 'y', lw=2, zorder=10)
# for i in out_spikelist[0].spike_times:
# plt.axvline(i, color='k', lw=1, zorder=0)
# for i in out_spikelist[1].spike_times:
# plt.axvline(i, color='b', lw=1, zorder=0)
plt.savefig('/tmp/%s.png' %
(os.path.splitext(os.path.basename(__file__))[0]))
plt.close()
print('End %s:run()' % (os.path.splitext(os.path.basename(__file__))[0]))
# intel_fpga_writer.write()
# intel_fpga_writer.write_globals()
# Call the C NSAT
print("Running C NSAT!")
nsat.run_c_nsat(c_nsat_writer.fname)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, c_nsat_writer.fname)
#ww = np.array(c_nsat_reader.read_c_nsat_synaptic_weights()[0])
states = c_nsat_reader.read_c_nsat_states()
time_core0, states_core0 = states[0][0], states[0][1]
# wt = c_nsat_reader.read_c_nsat_weights_evo(2)[0]
wt = c_nsat_reader.read_c_nsat_syn_evo()[0][0]
spk = nsat.importAER(nsat.read_from_file(c_nsat_writer.fname.events +
'_core_0.dat'),
sim_ticks=sim_ticks)
spk.raster_plot()
print((SL[0].spike_times))
print((SL[1].spike_times))
print((spk[0].spike_times))
#fig = plt.figure()
#ax = fig.add_subplot(111)
#ax.plot(ww[:N_INPUTS[0], N_INPUTS[0], 1], 'k.')
# Plot the results
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(4, 2, 1)
## intel_fpga_writer = nsat.IntelFPGAWriter(cfg, path='.',
## prefix='test_two_neurons_stdp')
## intel_fpga_writer.write()
## intel_fpga_writer.write_globals()
# Call the C NSAT
print("Running C NSAT!")
nsat.run_c_nsat(c_nsat_writer.fname)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, c_nsat_writer.fname)
states = c_nsat_reader.read_c_nsat_states()
time_core0, states_core0 = states[0][0], states[0][1]
wt = c_nsat_reader.read_c_nsat_weights_evo(2)[0]
out_spikelist = nsat.importAER(
nsat.read_from_file(c_nsat_writer.fname.events + '_core_0.dat'),
sim_ticks=sim_ticks,
id_list=[0])
# Plot the results
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(4, 2, 1)
ax.plot(states_core0[:-1, 0, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 2)
ax.plot(states_core0[:-1, 1, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 3)
c_nsat_writer = nsat.C_NSATWriter(cfg, path='/tmp', prefix='test_td')
c_nsat_writer.write()
# Call the C NSAT
print("Running C NSAT!")
nsat.run_c_nsat(c_nsat_writer.fname)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, c_nsat_writer.fname)
states = c_nsat_reader.read_c_nsat_states()
states_core0 = states[0][1]
# np.save('states', states_core0)
in_spikelist = SL
ifname = c_nsat_writer.fname.events + '_core_0.dat'
out_spikelist = nsat.importAER(nsat.read_from_file(ifname),
sim_ticks=sim_ticks,
id_list=[0])
# Plot the results
fig = plt.figure(figsize=(10, 10))
for i in range(1, 9):
ax = fig.add_subplot(8, 1, i)
ax.plot(states_core0[:-1, 15, i - 1], 'b', lw=1.5)
# fig = plt.figure(figsize=(10, 10))
# for i in range(1, 9):
# ax = fig.add_subplot(8, 1, i)
# ax.plot(states_core0[:-1, 16, i-1], 'b', lw=1.5)
# out_spikelist.raster_plot()
# Call the C NSAT
print("Running C NSAT!")
nsat.run_c_nsat(c_nsat_writer.fname)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, c_nsat_writer.fname)
states = c_nsat_reader.read_c_nsat_states()
time_core0, states_core0 = states[0][0], states[0][1]
wt = c_nsat_reader.read_c_nsat_weights_evo([0, 1])[0]
# cfg.write_hex_weights_monitors(wt[:, 0, 1])
# out_spikelist = nsat.importAER(nsat.read_from_file(c_nsat_writer.fname.events+'_core_0.dat'),
# sim_ticks=sim_ticks, id_list=[0])
out_spikelist = nsat.importAER(
nsat.read_from_file(c_nsat_writer.fname.events +
'_core_0.dat'.encode('utf-8')),
sim_ticks=sim_ticks)
# Plot the results
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(4, 2, 1)
ax.plot(states_core0[:-1, 0, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 2)
ax.plot(states_core0[:-1, 1, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 3)
ax.plot(states_core0[:-1, 0, 1], 'b', lw=3, label='$I_{syn}$')
# intel_fpga_writer.write_globals()
# Call the C NSAT
print("Running C NSAT!")
nsat.run_c_nsat(c_nsat_writer.fname)
# Load the results (read binary files)
c_nsat_reader = nsat.C_NSATReader(cfg, c_nsat_writer.fname)
states = c_nsat_reader.read_c_nsat_states()
time_core0, states_core0 = states[0][0], states[0][1]
wt = c_nsat_reader.read_c_nsat_weights_evo([0, 1])[0]
# cfg.write_hex_weights_monitors(wt[:, 0, 1])
# out_spikelist = nsat.importAER(nsat.read_from_file(c_nsat_writer.fname.events+'_core_0.dat'),
# sim_ticks=sim_ticks, id_list=[0])
out_spikelist = nsat.importAER(nsat.read_from_file(c_nsat_writer.fname.events+'_core_0.dat'.encode('utf-8')),
sim_ticks=sim_ticks)
# Plot the results
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(4, 2, 1)
ax.plot(states_core0[:-1, 0, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 2)
ax.plot(states_core0[:-1, 1, 0], 'b', lw=3, label='$x_m$')
ax.set_ylabel('$V_m$')
ax = fig.add_subplot(4, 2, 3)
ax.plot(states_core0[:-1, 0, 1], 'b', lw=3, label='$I_{syn}$')
copyfile(
fname_train.shared_mem + '_core_0.dat',
fname_test.syn_wgt_table + '_core_0.dat',
)
# c_nsat_writer_test.write_L0connectivity()
# c_nsat_writer_train.write_L0connectivity()
s = c_nsat_reader_train.read_stats()[0]
stats_nsat.append(s)
#stats_ext.append(n_ext)
if test_every > 0:
if i % test_every == test_every - 1:
nsat.run_c_nsat(fname_test)
test_spikelist = nsat.importAER(
nsat.read_from_file(fname_test.events + '_core_0.dat'),
sim_ticks=sim_ticks_test,
id_list=np.arange(sP, sP + Np))
pip.append([
i,
float(
sum(
np.argmax(test_spikelist.id_slice(range(
sP, sP + Np)).firing_rate(t_sample_test).T,
axis=1) == targets_classify[:N_test])) /
N_test * 100
])
print exp_name
print pip
if __name__ == '__main__':
n_epoch = 50
e = []
print("############## Training ##############")
for i in range(n_epoch):
# Call the C NSAT for learning
print("Epoch #: ", i)
c_nsat_writer_train.fname.stats_nsat = '/tmp/test_eCD_stats_nsat'+str(i)
nsat.run_c_nsat(c_nsat_writer_train.fname)
if n_epoch > 1:
shutil.copyfile(fname_train.shared_mem+'_core_0.dat',
fname_train.syn_wgt_table+'_core_0.dat',)
shutil.copyfile(fname_train.shared_mem+'_core_0.dat',
fname_test.syn_wgt_table+'_core_0.dat',)
nsat.run_c_nsat(c_nsat_writer_test.fname)
test_spk = nsat.importAER(nsat.read_from_file(c_nsat_writer_test.fname.events+'_core_0.dat'), sim_ticks=sim_ticks_test)
train_spk = nsat.importAER(nsat.read_from_file(c_nsat_writer_train.fname.events+'_core_0.dat'), sim_ticks=sim_ticks_train)
sl = test_spk.id_slice([16, 17])
mm = np.argmax(sl.firing_rate(time_bin=test_duration), axis=0)[::2]
print(100*sum(labels[::2] != mm)/32.0)
e.append(sum(labels[::2] != mm) / 32.0)
e = np.array(e)
np.save('/tmp/error_full', e)
# fig = plt.figure()
# ax = fig.add_subplot(111)
# ax.plot(e, 'x-k', lw=2)
W_new = c_nsat_reader_train.read_c_nsat_weights()[0]
r, c = Ns+Ne+Ni, Ns+Ne+Ni+Nv
W = W_new[(Ns+Ne+Ni):(Ns+Ne+Ni+Nv), (Ns+Ne+Ni+Nv):, 1]
