def loss_callback(var, literals, nprint=50, nsave=50, maxiter=500, t0=time()):
print('Callback')
#losses = literals['losses']
loss = var[0]
reconmeshes = var[1]
#nit = len(losses) %(maxiter*2)
#losses.append(loss)
nit, losses = var[2]
if nit % nprint == 0:
print('Time taken for iterations %d = ' % nit, time() - t0)
print(nit, " - Loss, chisq, prior, grad : ", loss)
fname = optfolder + '/%d.png' % nit
stime = time()
#dg.savehalofig(literals['truemeshes'], reconmeshes[0], fname, literals['hgraph'], boxsize=bs, title='%s'%loss)
dg.makefig(literals['truemeshes'],
reconmeshes,
fname,
boxsize=bs,
title='%s' % loss)
print('Time taken to make figure = ', time() - stime)
if nit % nsave == 0:
np.save(optfolder + '/iter%d.f4' % nit, reconmeshes)
np.savetxt(optfolder + '/losses.txt', np.array(losses))
print('Called')
def checkiter(mode, optfolder, R0=0):
print('\nChecking mode = %s\n' % mode)
meshs, meshf, meshd = session.run([linmesh, final, samples],
{Rsm: R0})
title = session.run([loss, chisq, prior, grad], {Rsm: R0})
np.save(optfolder + '/%s%d.f4' % (mode, R0), meshs)
dg.makefig(literals['truemeshes'], [meshs, meshf, meshd],
optfolder + '%s%d.png' % (mode, R0),
boxsize=bs,
title='%s' % title)
initlin = g.get_tensor_by_name('initlin:0')
session.run(initlinop, {initlin:initsplit[ii]})
init, recon = [], []
if anneal:
pass
else:
optfolder = ofolder + '/vox%02d'%ii
try: os.makedirs(optfolder)
except:pass
print('Output in ofolder = \n%s'%optfolder)
meshs, meshf, meshd = session.run([linmesh, final, samples])
title = session.run([loss, chisq, prior, grad])
np.save(optfolder + '/init.f4', meshs)
dg.makefig(literals['truemeshes'], [meshs, meshf, meshd], optfolder+'%s.png'%('init'), boxsize=bs, title='%s'%title)
optimizer.minimize(session, loss_callback=lcallback, fetches=[[[loss, chisq, prior, grad],
[linmesh, final, samples]]])
meshs, meshf, meshd = session.run([linmesh, final, samples])
title = session.run([loss, chisq, prior, grad])
reconsplit[ii] = meshs
np.save(optfolder + '/recon.f4', meshs)
dg.makefig(literals['truemeshes'], [meshs, meshf, meshd], optfolder+'%s.png'%('recon'), boxsize=bs, title='%s'%title)
initval = dtools.uncubify(np.stack(reconsplit, axis=0), [nc,nc,nc])
recong = rmods.graphhposft1(config, modpath, data, pad, maxiter=maxiter, gtol=gtol, anneal=anneal, resnorm=resnorm)
losses = []
literals = {'losses':losses, 'truemeshes':truemeshes, 'bs':bs, 'nc':nc}
tstart = time()
