def test_points_v01():
mat = N.arange(12, dtype='d').reshape(3, 4)
print('Input matrix (numpy)')
print(mat)
print()
#
# Create transformations
#
points = C.Points(mat)
identity = C.Identity()
identity.identity.source(points.points.points)
res = identity.identity.target.data()
dt = identity.identity.target.datatype()
#
# Dump
#
print('Eigen dump (C++)')
identity.dump()
print()
print('Points output')
print(points.points.points.data())
print('Result (C++ Data to numpy)')
print(res, res.dtype)
print()
print('Datatype:', str(dt))
assert N.allclose(mat, res), "C++ and Python results doesn't match"
def test_points_v02():
arr = N.arange(12, dtype=context.current_precision_short())
points = C.Points(arr)
identity = C.Identity()
points >> identity
out = identity.single()
for i in range(arr.size):
points.set(arr, i)
assert (out.data() == arr[:i]).all()
def build(self):
for idx in self.nidx:
reac, = idx.current_values()
name = "snf_correction" + idx.current_format()
try:
_snf_energy, _snf_spectra = list(
map(C.Points, self.snf_raw_data[reac]))
except KeyError:
# U238 doesn't have offequilibrium correction so just pass 1.
_snf_energy, _snf_spectra = list(
map(C.Points, self.snf_raw_data['average']))
_snf_energy.points.setLabel(
"Original energies for SNF spectrum of {}".format(reac))
snf_spectra = C.InterpLinear(
labels='Correction for spectra in {}'.format(reac))
snf_spectra.set_overflow_strategy(
R.GNA.Interpolation.Strategy.Constant)
snf_spectra.set_underflow_strategy(
R.GNA.Interpolation.Strategy.Constant)
insegment = snf_spectra.transformations.front()
insegment.setLabel("Segments")
interpolator_trans = snf_spectra.transformations.back()
interpolator_trans.setLabel(
"Interpolated SNF correction for {}".format(reac))
passthrough = C.Identity(
labels="Nominal spectra for {}".format(reac))
_snf_energy >> (insegment.edges, interpolator_trans.x)
_snf_spectra >> interpolator_trans.y
self.set_input('snf_correction',
idx, (insegment.points, interpolator_trans.newx),
argument_number=0)
self.set_input('snf_correction',
idx, (passthrough.single_input()),
argument_number=1)
snap = C.Snapshot(
passthrough.single(),
labels='Snapshot of nominal spectra for SNF in {}'.format(
reac))
product = C.Product(
outputs=[snap.single(),
interpolator_trans.single()],
labels='Product of nominal spectrum to SNF correction in {}'.
format(reac))
par_name = "snf_scale"
self.reqparameter(par_name,
idx,
central=1.,
relsigma=1,
labels="SNF norm for reactor {0}".format(reac))
outputs = [product.single()]
weights = ['.'.join((par_name, idx.current_format()))]
with self.namespace:
final_sum = C.WeightedSum(
weights,
outputs,
labels='SNF spectrum from {0} reactor'.format(reac))
self.context.objects[name] = final_sum
self.set_output("snf_correction", idx, final_sum.single())
def build(self):
for idx in self.nidx.iterate():
if 'isotope' in idx.names()[0]:
iso, reac = idx.current_values()
else:
reac, iso = idx.current_values()
name = "offeq_correction." + idx.current_format()
try:
_offeq_energy, _offeq_spectra = list(map(C.Points, self.offeq_raw_spectra[iso]))
_offeq_energy.points.setLabel("Original energies for offeq spectrum of {}".format(iso))
except KeyError:
# U238 doesn't have offequilibrium correction so just pass 1.
if iso != 'U238':
raise
passthrough = C.Identity(labels='Nominal {0} spectrum in {1} reactor'.format(iso, reac))
self.context.objects[name] = passthrough
dummy = C.Identity() #just to serve 1 input
self.set_input('offeq_correction', idx, dummy.single_input(), argument_number=0)
self.set_input('offeq_correction', idx, passthrough.single_input(), argument_number=1)
self.set_output("offeq_correction", idx, passthrough.single())
continue
offeq_spectra = C.InterpLinear(labels='Correction for {} spectra'.format(iso))
offeq_spectra.set_overflow_strategy(R.GNA.Interpolation.Strategy.Constant)
offeq_spectra.set_underflow_strategy(R.GNA.Interpolation.Strategy.Constant)
insegment = offeq_spectra.transformations.front()
insegment.setLabel("Offequilibrium segments")
interpolator_trans = offeq_spectra.transformations.back()
interpolator_trans.setLabel("Interpolated spectral correction for {}".format(iso))
passthrough = C.Identity(labels="Nominal {0} spectrum in {1} reactor".format(iso, reac))
_offeq_energy >> (insegment.edges, interpolator_trans.x)
_offeq_spectra >> interpolator_trans.y
# Enu
self.set_input('offeq_correction', idx, (insegment.points, interpolator_trans.newx),
argument_number=0)
# Anue spectra
self.set_input('offeq_correction', idx, ( passthrough.single_input()), argument_number=1)
par_name = "offeq_scale"
self.reqparameter(par_name, idx, central=1., relsigma=0.3,
labels="Offequilibrium norm for reactor {1} and iso "
"{0}".format(iso, reac))
self.reqparameter("dummy_scale", idx, central=1,
fixed=True, labels="Dummy weight for reactor {1} and iso "
"{0} for offeq correction".format(iso, reac))
snap = C.Snapshot(passthrough.single(), labels='Snapshot of {} spectra in reac {}'.format(iso, reac))
prod = C.Product(labels='Product of initial {} spectra and '
'offequilibrium corr in {} reactor'.format(iso, reac))
prod.multiply(interpolator_trans.single())
prod.multiply(snap.single())
outputs = [passthrough.single(), prod.single()]
weights = ['.'.join(("dummy_scale", idx.current_format())),
'.'.join((par_name, idx.current_format()))]
with self.namespace:
final_sum = C.WeightedSum(weights, outputs, labels='Corrected to offequilibrium '
'{0} spectrum in {1} reactor'.format(iso, reac))
self.context.objects[name] = final_sum
self.set_output("offeq_correction", idx, final_sum.single())
mat = N.matrix(N.arange(16.0).reshape(4, 4))
print('Raw matrix')
print(mat)
print('Sum over rows')
print(mat.A.sum(axis=0))
print('Raw normalized matrix')
print(mat.A / mat.A.sum(axis=0))
pmat = C.Points(mat)
rd = R.RenormalizeDiag(opts.ndiag, int(opts.offdiag), int(opts.upper))
rd.renorm.inmat(pmat.points)
idt = C.Identity()
idt.identity.source(rd.renorm.outmat)
idt0 = C.Identity()
idt0.identity.source(pmat.points)
idt.identity.target.data()
idt0.identity.target.data()
if opts.upper:
print('Upper triangle mode')
print('Input (Eigen)')
idt0.dump()
print('Output (Eigen)')