def main(tally_id, score_id, batch_start, batch_end, name):
# read in statepoint header data
sp = statepoint.StatePoint('statepoint.ref.binary')
# read in results
sp.read_results()
# extract reference mean
mean_ref = extract_mean(sp, tally_id, score_id)
# write gnuplot file
write_src_gnuplot('testsrc_pin', 'Pin mesh', mean_ref,
np.size(mean_ref, 0))
# preallocate arrays
hists = np.zeros(batch_end - batch_start + 1)
norms = np.zeros(batch_end - batch_start + 1)
i = batch_start
while i <= batch_end:
# process statepoint
sp = statepoint.StatePoint('statepoint.' + str(i) + '.binary')
sp.read_results()
# extract mean
mean = extract_mean(sp, tally_id, score_id)
# calculate L2 norm
norm = np.linalg.norm(mean - mean_ref)
# get history information
n_inactive = sp.n_inactive
current_batch = sp.current_batch
n_particles = sp.n_particles
gen_per_batch = sp.gen_per_batch
n_histories = (current_batch -
n_inactive) * n_particles * gen_per_batch
# batch in vectors
hists[i - batch_start] = n_histories
norms[i - batch_start] = norm
# print
print 'Batch: ' + str(i) + ' Histories: ' + str(
n_histories) + ' Norm: ' + str(norm)
i += 1
# write out gnuplot file
write_norm_gnuplot(name, hists, norms, np.size(hists))
def process_tallies(self):
# get statepoint filename
spfile = glob.glob('tmpdir/minicore_outputs/statepoint*')[0]
# extract all means
sp = statepoint.StatePoint(spfile)
# plot
sp.read_results()
# extract distributions
nfiss = self.extract_mean(sp, 1, 'nu-fission')
flux2 = self.extract_mean(sp, 2, 'flux')
flux1 = self.extract_mean(sp, 3, 'flux')
# write out data
self.write_gnuplot_data(nfiss, flux1, flux2)
# run gnuplot
Popen(['gnuplot','tmpdir/minicore_outputs/nfiss.plot'])
Popen(['gnuplot','tmpdir/minicore_outputs/flux1.plot'])
Popen(['gnuplot','tmpdir/minicore_outputs/flux2.plot'])
self.emit(SIGNAL("new output plots"),
["tmpdir/minicore_outputs/nfiss.png",
"tmpdir/minicore_outputs/flux1.png"])
#!/usr/bin/env python
import sys
# import statepoint
sys.path.insert(0, '../../src/utils')
import statepoint
# read in statepoint file
if len(sys.argv) > 1:
sp = statepoint.StatePoint(sys.argv[1])
else:
sp = statepoint.StatePoint('statepoint.09.binary')
sp.read_results()
# set up output string
outstr = ''
# write out k-combined
outstr += 'k-combined:\n'
outstr += "{0:12.6E} {1:12.6E}\n".format(sp.k_combined[0], sp.k_combined[1])
# write results to file
with open('results_test.dat','w') as fh:
fh.write(outstr)
def main():
print "Loading statepoint..."
sp = statepoint.StatePoint('statepoint.300.binary')
print "Parsing statepoint..."
sp.read_results()
print "\nAvailable Tallies:"
for tally in sp.tallies:
print "\tTally {}".format(tally.id)
print "\t\tscores: {}".format(" ".join(tally.scores))
print "\t\tfilters: {}".format(" ".join(tally.filters.keys()))
## Loop through the mesh for tally 1 and create plots
print "Extracting Mesh Values from Tally 1..."
tallyid = 0 # tally 1
score = 0 # flux is zero see (order of tally.filters.keys())
# get mesh dimensions
meshid = sp.tallies[tallyid].filters['mesh'].bins[0]
for i, m in enumerate(sp.meshes):
if m.id == meshid:
mesh = m
nx, ny, nz = mesh.dimension
# loop through mesh and extract values
thermal = {}
fast = {}
for x in range(1, nx + 1):
for y in range(1, ny + 1):
for z in range(1, nz + 1):
val, err = sp.get_value(tallyid, [('mesh', (x, y, z)),
('energyin', 0)], score)
thermal[(x, y, z)] = val
val, err = sp.get_value(tallyid, [('mesh', (x, y, z)),
('energyin', 1)], score)
fast[(x, y, z)] = val
# write gnuplot datafile with axially-integrated values
print "Making gnuplots ..."
with open('meshdata.dat', 'w') as fh:
for x in range(1, nx + 1):
for y in range(1, ny + 1):
thermalval = 0.
fastval = 0.
for z in range(1, nz + 1):
thermalval += thermal[(x, y, z)]
fastval += fast[(x, y, z)]
fh.write("{} {} {} {}\n".format(x, y, thermalval, fastval))
# write gnuplot file and make plots
with open('tmp.gnuplot', 'w') as fh:
fh.write(r"""set terminal png size 800,400
set output 'fluxplot.png'
set nokey
set autoscale fix
set multiplot layout 1,2 title "Pin Mesh Axially-Integrated Flux Tally"
set title "Thermal"
plot 'meshdata.dat' using 1:2:3 with image
set title "Fast"
plot 'meshdata.dat' using 1:2:4 with image
""")
os.system("gnuplot < tmp.gnuplot")
# make 3d silo file
print "Making 3D SILO File ..."
sm.init_silo("fluxtally.silo")
sm.init_mesh(
'tally_mesh',
nx,
ny,
nz,
-85.8774,
-85.8774,
-81.662, # lower left of mesh
1.63576,
1.63576,
8.1662) # width of mesh cells
sm.init_var('flux_tally_thermal')
for x in range(1, nx + 1):
for y in range(1, ny + 1):
for z in range(1, nz + 1):
sm.set_value(float(thermal[(x, y, z)]), x, y, z)
sm.finalize_var()
sm.init_var('flux_tally_fast')
for x in range(1, nx + 1):
for y in range(1, ny + 1):
for z in range(1, nz + 1):
sm.set_value(float(fast[(x, y, z)]), x, y, z)
sm.finalize_var()
sm.finalize_mesh()
sm.finalize_silo()