def test_child():
assert_equal(rxname.child("U235", "absorption"), 922360000)
assert_equal(rxname.child(922350000, "absorption"), 922360000)
assert_equal(rxname.child("Co58M", "gamma"), 270590000)
assert_equal(rxname.child("Co58M", "gamma_1"), 270590001)
assert_equal(rxname.child("Co58M", "gamma_1", "n"), 270590001)
assert_equal(rxname.child("Co58M", "gamma_1", b"n"), 270590001)
def test_child():
assert_equal(rxname.child("U235", "absorption"), 922360000)
assert_equal(rxname.child(922350000, "absorption"), 922360000)
def _traversal(self, nuc, A, out, depth=0):
"""Nuclide transmutation traversal method.
This method will traverse the reaction tree recursively, using a DFS
algorithm. On termination, the method will return all number densities
after a given time that are a result of the starting nuclide.
Parameters
----------
nuc : int
ID of the active nuclide for the traversal.
A : NumPy 2-dimensional array
Current state of the coupled equation matrix.
out : dict
A dictionary containing the final recorded number densities for each
nuclide. Keys are nuclide names in integer id form. Values are
number densities for the coupled nuclide in float format. This is
modified in place.
depth : int
Current depth of traversal (root at 0). Should never be provided by user.
"""
t = self.t
tol = self.tol
phi = self.xscache['phi_g'][0]
temp = self.temp
xscache = self.xscache
if self.log is not None:
self._log_tree(depth, nuc, 1.0)
prod = {}
# decay info
lam = data.decay_const(nuc)
decay_branches = {} if lam == 0 else self._decay_branches(nuc)
for decay_child, branch_ratio in decay_branches.items():
prod[decay_child] = lam * branch_ratio
# reaction daughters
for rx in self.rxs:
try:
child = rxname.child(nuc, rx)
except RuntimeError:
continue
child_xs = xscache[nuc, rx, temp][0]
rr = utils.from_barns(child_xs, 'cm2') * phi # reaction rate
prod[child] = rr + prod.get(child, 0.0)
# Cycle production dictionary
for child in prod:
# Grow matrix
d = self._get_destruction(child)
B = self._grow_matrix(A, prod[child], d)
# Create initial density vector
n = B.shape[0]
N0 = np.zeros((n, 1), dtype=float)
N0[0] = 1.0
# Compute matrix exponential and dot with density vector
eB = linalg.expm(B * t)
N_final = np.dot(eB, N0) # <-- DENSE
#N_final = eB.dot(N0) # <-- SPARSE
if self.log is not None:
self._log_tree(depth + 1, child, N_final[-1])
# Check against tolerance and continue traversal
if N_final[-1] > tol:
self._traversal(child, B, out, depth=depth + 1)
# On recursion exit or truncation, write data from this nuclide
outval = N_final[-1, 0] + out.get(child, 0.0)
if 0.0 < outval:
out[child] = outval
def test_child():
assert_equal(rxname.child("U235", "absorption"), 922360000)
assert_equal(rxname.child(922350000, "absorption"), 922360000)
def _traversal(self, nuc, A, out, depth=0):
"""Nuclide transmutation traversal method.
This method will traverse the reaction tree recursively, using a DFS
algorithm. On termination, the method will return all number densities
after a given time that are a result of the starting nuclide.
Parameters
----------
nuc : int
ID of the active nuclide for the traversal.
A : NumPy 2-dimensional array
Current state of the coupled equation matrix.
out : dict
A dictionary containing the final recorded number densities for each
nuclide. Keys are nuclide names in integer id form. Values are
number densities for the coupled nuclide in float format. This is
modified in place.
depth : int
Current depth of traversal (root at 0). Should never be provided by user.
"""
t = self.t
tol = self.tol
phi = self.xscache['phi_g'][0]
temp = self.temp
xscache = self.xscache
if self.log is not None:
self._log_tree(depth, nuc, 1.0)
prod = {}
# decay info
lam = data.decay_const(nuc)
decay_branches = {} if lam == 0 else self._decay_branches(nuc)
for decay_child, branch_ratio in decay_branches.items():
prod[decay_child] = lam * branch_ratio
# reaction daughters
for rx in self.rxs:
try:
child = rxname.child(nuc, rx)
except RuntimeError:
continue
child_xs = xscache[nuc, rx, temp][0]
rr = utils.from_barns(child_xs, 'cm2') * phi # reaction rate
prod[child] = rr + prod.get(child, 0.0)
# Cycle production dictionary
for child in prod:
# Grow matrix
d = self._get_destruction(child)
B = self._grow_matrix(A, prod[child], d)
# Create initial density vector
n = B.shape[0]
N0 = np.zeros((n, 1), dtype=float)
N0[0] = 1.0
# Compute matrix exponential and dot with density vector
eB = linalg.expm(B * t)
N_final = np.dot(eB, N0) # <-- DENSE
#N_final = eB.dot(N0) # <-- SPARSE
if self.log is not None:
self._log_tree(depth+1, child, N_final[-1])
# Check against tolerance and continue traversal
if N_final[-1] > tol:
self._traversal(child, B, out, depth=depth+1)
# On recursion exit or truncation, write data from this nuclide
outval = N_final[-1,0] + out.get(child, 0.0)
if 0.0 < outval:
out[child] = outval
def cross_section_data(t9, nlb=None, nucs=None):
"""Gets decay data from a TAPE9.
Parameters
----------
t9 : dict
A TAPE9 dict that contains the decay data.
nlb : tuple of ints or None, optional
The cross section library numbers. If None, this will attempt to discover
the numbers in the library.
nucs : set or None, optional
The known set of nuclides.
Returns
-------
nucs : set
The set of nuclide names.
sigma_ij : dict
Mapping from (i, j) nuclide name tuples to the cross section for this
reaction. Note that this does not include the fission cross section [barns].
sigma_fission : dict
Mapping from fissionable nuclide names to the fission cross section [barns].
fission_product_yields : dict
Mapping from (i, j) nuclide name tuples to the fission product yields for
that nuclide.
"""
if rxname.child("Am242M", "gamma") != 952430000:
raise RuntimeError("Pyne version too old. Need version 0.5.4 or newer")
nlb = find_nlb(t9, nlb=nlb)
nucs = set() if nucs is None else nucs
sigma_ij = {}
alpha_ij = {}
sigma_fission = {}
fission_product_yields = {}
for n in nlb:
# grab sigma_ij cross sections
for rx in t9[n]:
if not rx.startswith('sigma_') or rx == 'sigma_f':
continue
_, _, orx = rx.partition('_')
xs_rs = ORIGEN_TO_XS[orx]
for nuc in t9[n][rx]:
val = t9[n][rx][nuc]
if val == 0:
continue
nname = nucname.name(int(nuc))
try:
child = nucname.name(rxname.child(nname, xs_rs))
except RuntimeError:
continue
nucs.add(nname)
nucs.add(child)
sigma_ij[nname, child] = val
if rx == 'sigma_alpha':
alpha_ij[nname, "He4"] = val
# grab the fission cross section
if 'sigma_f' in t9[n]:
rx = 'sigma_f'
for nuc in t9[n][rx]:
val = t9[n][rx][nuc]
if val == 0:
continue
nname = nucname.name(int(nuc))
nucs.add(nname)
sigma_fission[nname] = val
# grab the fission product yields
for rx in t9[n]:
if not rx.endswith('_fiss_yield'):
continue
fromnuc, *_ = rx.partition('_')
fromnuc = nucname.name(fromnuc)
for k, v in t9[n][rx].items():
if v == 0:
continue
tonuc = nucname.name(nucname.zzaaam_to_id(int(k)))
# origen yields are in percent
nucs.add(fromnuc)
nucs.add(tonuc)
fission_product_yields[fromnuc, tonuc] = v / 100
return nucs, sigma_ij, sigma_fission, fission_product_yields, alpha_ij
