if rank > 0:
return
b = avgp[0] / maxp[0]
print 'Load Balance = %g' % b
print '\n ',
for i in header:
print '%12s' % i,
print '\n avg ',
for i in avgp:
print '%12.2f' % i,
print '\n max ',
for i in maxp:
print '%12.2f' % i,
print ''
if __name__ == '__main__':
import common
import util
common.nmitral = 1
common.ncell = 2
import net_mitral_centric as nmc
nmc.build_net_roundrobin(getmodel())
pc.spike_record(-1, spikevec, idvec)
from odorstim import OdorStim
from odors import odors
ods = OdorStim(odors['Apple'])
ods.setup(nmc.mitrals, 10., 20., 100.)
prun(200.)
util.finish()
header = ['comp','spk','split','gap']
for i in p:
avgp.append(pc.allreduce(i, 1)/nhost)
maxp.append(pc.allreduce(i, 2))
if rank > 0:
return
b = avgp[0]/maxp[0]
print 'Load Balance = %g'% b
print '\n ',
for i in header: print '%12s'%i,
print '\n avg ',
for i in avgp: print '%12.2f'%i,
print '\n max ',
for i in maxp: print '%12.2f'%i,
print ''
if __name__ == '__main__':
import common
import util
common.nmitral = 1
common.ncell = 2
import net_mitral_centric as nmc
nmc.build_net_roundrobin(getmodel())
pc.spike_record(-1, spikevec, idvec)
from odorstim import OdorStim
from odors import odors
ods = OdorStim(odors['Apple'])
ods.setup(nmc.mitrals, 10., 20., 100.)
prun(200.)
util.finish()