def runSORN(c, src):
# Initialize experiment (source and statictics)
(source, stats_single, _) = experiment.start(src)
# Initialize SORN network, has simulation() and step() function
sorn = Sorn(c, source)
# Create a StatsCollection and fill it with methods for all statistics
# that should be tracked (and later plotted)
stats = StatsCollection(sorn)
stats.methods = stats_single
sorn.stats = stats
# Datalog is used to store all results and parameters
#stats.dlog.set_handler('*',utils.StoreToH5,
# utils.logfilename("result.h5"))
#stats.dlog.append('c', utils.unbunchify(c))
#stats.dlog.set_handler('*',utils.TextPrinter)
# Final experimental preparations
experiment.reset(sorn)
# Start stats
sorn.stats.start()
sorn.stats.clear()
# Run experiment once
pickle_objects = experiment.run(sorn)
# Save sources etc
for key in pickle_objects:
filename = os.path.join(c.logfilepath, "%s.pickle" % key)
topickle = pickle_objects[key]
pickle.dump(topickle, gzip.open(filename, "wb"),
pickle.HIGHEST_PROTOCOL)
# Control: Firing-rate model: Substitute spikes by drawing random spikes
# according to firing rate for each inputindex
if sorn.c.stats.control_rates:
experiment.control_rates(sorn)
# Report stats and close
stats.single_report()
stats.disable = True
#stats.dlog.close()
sorn.quicksave(filename=os.path.join(c.logfilepath, 'net.pickle'))
# Start stats
sorn.stats.start()
sorn.stats.clear()
# Run experiment once
pickle_objects = experiment.run(sorn)
# Save sources etc
for key in pickle_objects:
filename = os.path.join(c.logfilepath, "%s.pickle" % key)
topickle = pickle_objects[key]
pickle.dump(topickle, gzip.open(filename, "wb"), pickle.HIGHEST_PROTOCOL)
# Control: Firing-rate model: Substitute spikes by drawing random spikes
# according to firing rate for each inputindex
if sorn.c.stats.control_rates:
experiment.control_rates(sorn)
# Report stats and close
stats.single_report()
stats.disable = True
stats.dlog.close()
sorn.quicksave(filename=os.path.join(c.logfilepath, "net.pickle"))
# Plot data collected by stats
# ~ dest_directory = os.path.join(dest_directory,'common')
experiment.plot_single(dest_directory, os.path.join("common", "result.h5"))
# Display figures
plt.show()
# Start stats
sorn.stats.start()
sorn.stats.clear()
# Run experiment once
pickle_objects = experiment.run(sorn)
# Save sources etc
for key in pickle_objects:
filename = os.path.join(c.logfilepath, "%s.pickle" % key)
topickle = pickle_objects[key]
pickle.dump(topickle, gzip.open(filename, "wb"), pickle.HIGHEST_PROTOCOL)
# Control: Firing-rate model: Substitute spikes by drawing random spikes
# according to firing rate for each inputindex
if sorn.c.stats.control_rates:
experiment.control_rates(sorn)
# Report stats and close
stats.single_report()
stats.disable = True
stats.dlog.close()
sorn.quicksave(filename=os.path.join(c.logfilepath, 'net.pickle'))
# Plot data collected by stats
#~ dest_directory = os.path.join(dest_directory,'common')
experiment.plot_single(dest_directory, os.path.join('common', 'result.h5'))
# Display figures
plt.show()
