Chart.ylabel("RMS Error")
Chart("set logscale y")
Chart.title("3 Restarts, 10 Iterations each")
histories = [1000, 5000, 10000, 50000, 100000]
bins = 50
halfwidth = 0.5
iterations = 3
restarts = 10
geo = Geometry.Geometry(bins, [[0, 2*halfwidth]])
xs = CrossSection.CrossSection(xS=0.5, nu=1.0, xF=0.5, xG=0)
uSource = fissionSource.histogramSource(scipy.ones(bins), geo)
# Deterministic
sn3 = procOUTSN.procOutsn(sys.argv[1])
csHeight, csCenters = sn3.coursenSNFS(geo)
snSource = fissionSource.histogramSource(csHeight, geo)
gnuData = {}
for h in histories:
print "\nHistories %i" %h
amc = arnoldiMC.arnoldiMC(geo, xs, h, storeVectors=True)
# Values, Vectors = amc.arnoldi(uSource, iterations)
Values, Vectors = amc.ERAM(uSource, restarts, iterations)
# Values, Vectors = amc.ERAM(snSource, restarts, iterations)
vAMprime = []
for i in xrange(1, len(amc.vectorStorage)+1):
vAMprime.append(scipy.stats.mean(amc.vectorStorage[:i]))
vAM = [abs(v)/sum(abs(v)) for v in vAMprime]
elif options.source == 'pright':
s = scipy.zeros(options.bins)
s[-1] = 1
elif options.source == 'pcenter':
mid = int(options.bins/2.0)
s = scipy.zeros(options.bins)
s[mid] = 1
else:
s = eval(options.source)
try:
source = fissionSource.histogramSource(s, geo)
except:
raise ValueError, "Unsupported source distribution: %s" %options.source
for key in options.__dict__:
print "%10s: %s" %(key, options.__dict__[key])
print "source %s" %source
if options.run:
# SN3
sn3 = procOUTSN.procOutsn("LarsenComparison/HW%.0f.0.OUTSN" %(options.width/2))
csHeight, csCenters = sn3.coursenSNFS(geo)
amc = arnoldiMC.arnoldiMC(geo, xs, options.H, verbose=options.verbose,
storeVectors=True)
Values, Vectors = amc.arnoldi(source, options.I)
Movie()
uSource = fissionSource.histogramSource(scipy.ones(bins), geo)
amc = arnoldiMC.arnoldiMC(geo, xs, histories, storeVectors=True)
Values, Vectors = amc.ERAM(uSource, restarts, iterations)
meanVector = scipy.stats.mean(amc.vectorStorage)
vAM = abs(meanVector)/sum(abs(meanVector))
vData = Gnuplot.Data(amc.geo.centers, vAM, with='histeps',
title='Arnoldi')
v1Vect = abs(Vectors[:,-1])/sum(abs(Vectors[:,-1]))
v1Data = Gnuplot.Data(amc.geo.centers, v1Vect, with='histeps',
title = '1st Vector')
# Chart.replot(vData)
gnuData['meanV1'] = (amc.geo.centers, vAM)
# Deterministic
sn3 = procOUTSN.procOutsn("LarsenComparison/HW%.1f.OUTSN" %halfwidth)
csHeight, csCenters = sn3.coursenSNFS(geo)
snData = Gnuplot.Data(csCenters, csHeight, with='histeps',
title='SN3')
# Chart.replot(snData)
gnuData['SN'] = (csCenters, csHeight)
for i in xrange(3):
gplotData = Gnuplot.Data(amc.geo.centers, Vectors[:,-(i+1)],
with='histeps', title='Vector%i' %i)
Chart.replot(gplotData)
gnuData['Vector%i' %i] = (amc.geo.centers, Vectors[:,-(i+1)])
gnuFile = gnuplotFile.gnuplotFile(sys.argv[1], gnuData)
mid = int(options.bins / 2.0)
s = scipy.zeros(options.bins)
s[mid] = 1
else:
s = eval(options.source)
try:
source = fissionSource.histogramSource(s, geo)
except:
raise ValueError, "Unsupported source distribution: %s" % options.source
for key in options.__dict__:
print "%10s: %s" % (key, options.__dict__[key])
print "source %s" % source
if options.run:
# SN3
sn3 = procOUTSN.procOutsn("LarsenComparison/HW%.0f.0.OUTSN" %
(options.width / 2))
csHeight, csCenters = sn3.coursenSNFS(geo)
amc = arnoldiMC.arnoldiMC(geo,
xs,
options.H,
verbose=options.verbose,
storeVectors=True)
Values, Vectors = amc.arnoldi(source, options.I)
Movie()