def retina_reduce(info, activity_retina, collation):
collation.insert_columns(retina_activity=activity_retina)
s = Select(collation)
s.view(int_keys=['time'],
float_keys=['retina_density', 'cortex_density', 'V1_activity', 'retina_activity'])
condition = (s.retina_density > 2.0) & (s.time == 1)
result = np.mean(s[condition].retina_activity)
print "Average std. of retina activity vs cortex density for retina density of 2.0 (@time=1): %f" % result
return collation
def V1_reduce(info, activity_V1, accumulator):
import pylab
collation = Collate(*info, V1_activity=activity_V1)
s = Select(collation)
s.view(float_keys=['time', 'retina_density', 'cortex_density', 'V1_activity'])
condition = (s.cortex_density > 0.5) & (s.retina_density == 2.0)
pylab.plot(s[condition].V1_activity, s[condition].cortex_density)
pylab.title('Mean activity (cortex) against cortex density at time = 1.0 for retina density=2')
[root_directory, _] = info
figure_path = os.path.join(root_directory, 'cluster_figures')
try: os.mkdir(figure_path)
except :pass
pylab.savefig(os.path.join(figure_path, 'rd2_mean_activity.png'))
print "Saved figure rd2_mean_activity.png in folder cluster_figures"
return collation
