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, dlog)
stats.methods = stats_cluster
sorn.stats = stats
# Run experiments
experiment.reset(sorn)
sorn.stats.start()
dlog.progress("Start inner loop")
for n in range(c.N_iterations):
experiment.reset(sorn)
stats.clear()
dlog.progress("Inner Iteration %d of %d at param %.3f" %
(n + 1, c.N_iterations, tmp))
pickle_objects = experiment.run(sorn)
# Save sources etc
for key in pickle_objects:
filename = os.path.join(
c.logfilepath, "%s_%s_%.3f.pickle" %
(key, c.cluster.vary_param, current_param))
# using reference directly doesn't work
topickle = pickle_objects[key]
pickle.dump(topickle, gzip.open(filename, "wb"),
pickle.HIGHEST_PROTOCOL)
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,dlog)
stats.methods = stats_cluster
sorn.stats = stats
# Run experiments
experiment.reset(sorn)
sorn.stats.start()
dlog.progress("Start inner loop")
for n in range(c.N_iterations):
experiment.reset(sorn)
stats.clear()
dlog.progress("Inner Iteration %d of %d at param %.3f"%(n+1,
c.N_iterations,tmp))
pickle_objects = experiment.run(sorn)
# Save sources etc
for key in pickle_objects:
filename = os.path.join(c.logfilepath,"%s_%s_%.3f.pickle"
%(key,c.cluster.vary_param,current_param))
# using reference directly doesn't work
topickle = pickle_objects[key]
pickle.dump(topickle, gzip.open(filename,"wb"),
pickle.HIGHEST_PROTOCOL)
