def chainexpr(chain, cse, b, bt, short=1e-8):
child = chain[-1]
if len(chain) == 1:
a_i = -1.0 / half_life(child, False)
b = ensure_cse(a_i, b, cse)
terms = B_EXPR.format(b=b_from_a(cse, a_i))
else:
k, a = k_a(chain, short=short)
if k is None:
return None, b, bt
terms = []
for k_i, a_i in zip(k, a):
if k_i == 1.0 and a_i == 0.0:
term = str(1.0 - bt) # a slight optimization
bt = 1
elif a_i == 0.0:
if not np.isnan(k_i):
if bt < 1:
if k_i + bt < 1:
term = '{0:e}'.format(k_i) # another slight optimization
bt += k_i
else:
term = '{0:e}'.format(1.0 - bt)
bt = 1.0
else:
term = '0'
else:
term = '0'
else:
b = ensure_cse(a_i, b, cse)
term = kbexpr(k_i, b_from_a(cse, a_i))
terms.append(term)
terms = ' + '.join(terms)
return CHAIN_EXPR.format(terms), b, bt
def test_transmuters_cram():
n0 = {"H3": 1.0}
A = -cram.DECAY_MATRIX * data.half_life("H3")
n1 = transmuters.cram(A, n0, order=16)
assert_equal(2, len(n1))
assert_almost_equal(0.5, n1[nucname.id("H3")])
assert_almost_equal(0.5, n1[nucname.id("He3")])
def chainexpr(chain, cse, b, bt, short=1e-8):
child = chain[-1]
if len(chain) == 1:
a_i = -1.0 / half_life(child, False)
b = ensure_cse(a_i, b, cse)
terms = B_EXPR.format(b=b_from_a(cse, a_i))
else:
k, a = k_a(chain, short=short)
if k is None:
return None, b, bt
terms = []
for k_i, a_i in zip(k, a):
if k_i == 1.0 and a_i == 0.0:
term = str(1.0 - bt) # a slight optimization
bt = 1
elif a_i == 0.0:
if not np.isnan(k_i):
if bt < 1:
if k_i + bt < 1:
term = '{0:e}'.format(
k_i) # another slight optimization
bt += k_i
else:
term = '{0:e}'.format(1.0 - bt)
bt = 1.0
else:
term = '0'
else:
term = '0'
else:
b = ensure_cse(a_i, b, cse)
term = kbexpr(k_i, b_from_a(cse, a_i))
terms.append(term)
terms = ' + '.join(terms)
return CHAIN_EXPR.format(terms), b, bt
def k_a_from_hl(chain, short=1e-16, small=1e-16):
hl = np.array([half_life(n, False) for n in chain])
hl = hl[~np.isnan(hl)]
outerdiff = hl - hl[:, np.newaxis]
outerzeros = outerdiff == 0.0
a = -1.0 / hl
gamma = np.prod([branch_ratio(p, c) for p, c in zip(chain[:-1], chain[1:])])
if gamma == 0.0 or np.isnan(gamma):
return None, None, None
ends_stable = np.isinf(hl[-1])
k = (
k_from_hl_stable(hl, gamma, outerdiff, outerzeros)
if ends_stable
else k_from_hl_unstable(hl, gamma, outerdiff, outerzeros)
)
t_term = np.zeros(len(k), dtype=bool)
asmask = almost_stable_mask(hl, k)
if np.any(asmask):
# handle case some nuclide is effectively stable and
# we obtained an overflow through the normal method
k, a, t_term = (
k_almost_stable(hl, a, gamma, asmask)
if ends_stable
else k_almost_unstable(hl, a, gamma, asmask)
)
else:
k, a, t_term = hl_degeneracy(hl, k, a, outerzeros)
# filtering makes compiling faster by pre-ignoring negligible species
# in this chain. They'll still be picked up in their own chains.
mask = k_filter(k, t_term, small=small)
if mask.sum() == 0:
return None, None, None
return k[mask], a[mask], t_term[mask]
def hl_relerr(nuc):
"""Half-life relative error."""
dhl = data.half_life(nuc) or np.inf
ohl = t9_half_life(nuc) or np.inf
if np.isinf(ohl) and np.isinf(dhl):
return 0.0
hlre = np.abs(ohl - dhl) * 2 / (ohl + dhl)
return np.inf if np.isnan(hlre) else hlre
def hl_relerr(nuc):
"""Half-life relative error."""
dhl = data.half_life(nuc) or np.inf
ohl = t9_half_life(nuc) or np.inf
if np.isinf(ohl) and np.isinf(dhl):
return 0.0
hlre = np.abs(ohl - dhl) * 2 / (ohl + dhl)
return np.inf if np.isnan(hlre) else hlre
def _ensure_nl(self, rc):
"Validate the tracked nuclides in the run control."
if isinstance(rc.track_nucs, basestring):
track_nucs = self.load_nuc_file(rc.track_nucs)
else:
track_nucs = [nucname.id(nuc) for nuc in rc.track_nucs]
avg_timestep = 60*60*24*np.mean(rc.burn_times[1:]-rc.burn_times[:-1])
min_halflife = rc.track_nuc_threshold * avg_timestep
track_nucs = [nucid for nucid in track_nucs
if half_life(nucid) > min_halflife]
rc.track_nucs = sorted(set(track_nucs))
def k_a(chain, short=1e-8):
# gather data
hl = np.array([half_life(n, False) for n in chain])
a = -1.0 / hl
dc = np.array(list(map(lambda nuc: decay_const(nuc, False), chain)))
if np.isnan(dc).any():
# NaNs are bad, mmmkay. Nones mean we should skip
return None, None
ends_stable = (dc[-1] < 1e-16) # check if last nuclide is a stable species
# compute cij -> ci in prep for k
cij = dc[:, np.newaxis] / (dc[:, np.newaxis] - dc)
if ends_stable:
cij[-1] = -1.0 / dc # adjustment for stable end nuclide
mask = np.ones(len(chain), dtype=bool)
cij[mask, mask] = 1.0 # identity is ignored, set to unity
ci = cij.prod(axis=0)
# compute k
if ends_stable:
k = dc * ci
k[-1] = 1.0
else:
k = (dc / dc[-1]) * ci
if np.isinf(k).any():
# if this happens then something wen very wrong, skip
return None, None
# compute and apply branch ratios
gamma = np.prod(
[all_branch_ratio(p, c) for p, c in zip(chain[:-1], chain[1:])])
if gamma == 0.0 or np.isnan(gamma):
return None, None
k *= gamma
# half-life filter, makes compiling faster by pre-ignoring negligible species
# in this chain. They'll still be picked up in their own chains.
if ends_stable:
mask = (hl[:-1] / hl[:-1].sum()) > short
mask = np.append(mask, True)
else:
mask = (hl / hl.sum()) > short
if mask.sum() < 2:
mask = np.ones(len(chain), dtype=bool)
return k[mask], a[mask]
def k_a(chain, short=1e-8):
# gather data
hl = np.array([half_life(n, False) for n in chain])
a = -1.0 / hl
dc = np.array(list(map(lambda nuc: decay_const(nuc, False), chain)))
if np.isnan(dc).any():
# NaNs are bad, mmmkay. Nones mean we should skip
return None, None
ends_stable = (dc[-1] < 1e-16) # check if last nuclide is a stable species
# compute cij -> ci in prep for k
cij = dc[:, np.newaxis] / (dc[:, np.newaxis] - dc)
if ends_stable:
cij[-1] = -1.0 / dc # adjustment for stable end nuclide
mask = np.ones(len(chain), dtype=bool)
cij[mask, mask] = 1.0 # identity is ignored, set to unity
ci = cij.prod(axis=0)
# compute k
if ends_stable:
k = dc * ci
k[-1] = 1.0
else:
k = (dc / dc[-1]) * ci
if np.isinf(k).any():
# if this happens then something wen very wrong, skip
return None, None
# compute and apply branch ratios
gamma = np.prod([all_branch_ratio(p, c) for p, c in zip(chain[:-1], chain[1:])])
if gamma == 0.0 or np.isnan(gamma):
return None, None
k *= gamma
# half-life filter, makes compiling faster by pre-ignoring negligible species
# in this chain. They'll still be picked up in their own chains.
if ends_stable:
mask = (hl[:-1] / hl[:-1].sum()) > short
mask = np.append(mask, True)
else:
mask = (hl / hl.sum()) > short
if mask.sum() < 2:
mask = np.ones(len(chain), dtype=bool)
return k[mask], a[mask]
def chainexpr(chain, cse, b, bt, short=1e-16, small=1e-16):
child = chain[-1]
if len(chain) == 1:
a_i = -1.0 / half_life(child, False)
b = ensure_cse(a_i, b, cse)
terms = B_EXPR.format(b=b_from_a(cse, a_i))
else:
k, a, t_term = k_a_from_hl(chain, short=short, small=small)
if k is None:
return None, b, bt
terms = []
for k_i, a_i, t_term_i in zip(k, a, t_term):
if k_i == 1.0 and a_i == 0.0:
term = str(1.0 - bt) # a slight optimization
bt = 1
elif a_i == 0.0:
if not np.isnan(k_i):
if bt < 1:
if k_i + bt < 1:
term = "{0:.17e}".format(k_i) # another slight optimization
bt += k_i
else:
term = "{0:.17e}".format(1.0 - bt)
bt = 1.0
else:
term = "0"
else:
term = "0"
else:
b = ensure_cse(a_i, b, cse)
term = kbexpr(k_i, b_from_a(cse, a_i))
# multiply by t if needed
if t_term_i:
term += "*t"
terms.append(term)
terms = " + ".join(terms)
return CHAIN_EXPR.format(terms), b, bt
nums = len(child)
if nums == 1:
IDS.append(child[0])
j += 1
generation.append(j)
parent_to_child.append(str(iso) + '-->' + str(child[0]))
parent_text.append(
str(nucname.name(IDS[i])) + '-->' + str(nucname.name(child[0])))
if nums == 2:
IDS.append(child[0])
parent_to_child.append(str(iso) + '-->' + str(child[0]))
parent_text.append(
str(nucname.name(IDS[i])) + '-->' + str(nucname.name(child[0])))
IDS.append(child[1])
parent_to_child.append(str(iso) + '-->' + str(child[1]))
parent_text.append(
str(nucname.name(IDS[i])) + '-->' + str(nucname.name(child[1])))
j += 1
generation.append(j)
generation.append(j)
half_lives = []
for i in IDS:
half_life = data.half_life(str(i))
half_lives.append(half_life)
nuclide_data = zip(IDS, generation, half_lives, parent_text)
print(list(nuclide_data))
print('Parent to child relationship:' + str(parent_text))
print(parent_to_child)
print('generations:' + str(generation))
print('list of nucname.ids:' + str(IDS))
def gendecay(decays, branches, metastable_cutoff=1.0):
"""This computes ORIGEN TAPE9 decay data based on ENSDF data.
Parameters
----------
decays : list
decay list from parse_ensdf()
branches : list
branches list from parse_ensdf()
metastable_cutoff : float, optional
minimum lifetime of metastable state (in seconds) to be included.
Returns
-------
t9 : dict
a TAPE9 dictionary for the decay library
"""
t9 = {1: {'_type': 'decay', 'title': 'PyNE Decay Data for Activation Products'},
2: {'_type': 'decay', 'title': 'PyNE Decay Data for Actinides & Daughters'},
3: {'_type': 'decay', 'title': 'PyNE Decay Data for Fission Products'},
}
for nlb, lib in t9.items():
for field in origen22.DECAY_FIELDS:
lib[field] = {}
longest = {}
longest2 = {}
for item in decays:
nuc = nucname.id(item[0])
key = nucname.zzaaam(nuc)
if _is_metastable_beta_decay_0(item, metastable_cutoff):
if 'B-' in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key, item[6]/100.0)
if 'B+' in item[5] or "EC" in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_plus_or_electron_capture_x', nuc,
key, item[6]/100.0)
if _is_metastable_beta_decay_x(item, metastable_cutoff):
key += 1
longest2[key] = longest2.get(key, 0)
if item[1] == longest2[key]:
if 'B-' in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key,
item[6]/100.0)
#item[6]*item[8]/100.0)
if 'B+' in item[5] or "EC" in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_plus_or_electron_capture_x', nuc,
key, item[6]/100.0)
#key, item[6]*item[8]/100.0)
elif item[1] > longest2[key]:
longest2[key] = item[1]
if 'B-' in item[5]:
#_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key, item[6]*item[8]/100.0)
_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key, item[6]/100.0)
if 'B+' in item[5] or "EC" in item[5]:
_eq_decay_t9(t9, 'frac_beta_plus_or_electron_capture_x', nuc,
key, item[6]/100.0)
#key, item[6]*item[8]/100.0)
for item in branches:
nuc = nucname.id(item[0])
key = nucname.zzaaam(nuc)
if (item[1] == 0) and (item[2] > metastable_cutoff):
_set_branch_item(t9, nuc, key, item)
if (item[1] != 0) and (item[2] > metastable_cutoff):
key += 1
longest[key] = longest.get(key, 0)
if (item[2] <= longest[key]):
continue
_set_branch_item(t9, nuc, key, item)
for nucs, hl in zip([origen22.ACTIVATION_PRODUCT_NUCS,
origen22.ACTINIDE_AND_DAUGHTER_NUCS,
origen22.FISSION_PRODUCT_NUCS],
[t9[i]['half_life'] for i in range(1, 4)]):
for nuc in nucs:
key = nucname.zzaaam(nuc)
if key not in hl:
hl[key] = data.half_life(nuc)
return t9
def gendecay(decays, branches, metastable_cutoff=1.0):
"""This computes ORIGEN TAPE9 decay data based on ENSDF data.
Parameters
----------
decays : list
decay list from parse_ensdf()
branches : list
branches list from parse_ensdf()
metastable_cutoff : float, optional
minimum lifetime of metastable state (in seconds) to be included.
Returns
-------
t9 : dict
a TAPE9 dictionary for the decay library
"""
t9 = {
1: {
'_type': 'decay',
'title': 'PyNE Decay Data for Activation Products'
},
2: {
'_type': 'decay',
'title': 'PyNE Decay Data for Actinides & Daughters'
},
3: {
'_type': 'decay',
'title': 'PyNE Decay Data for Fission Products'
},
}
for nlb, lib in t9.items():
for field in origen22.DECAY_FIELDS:
lib[field] = {}
longest = {}
longest2 = {}
for item in decays:
nuc = nucname.id(item[0])
key = nucname.zzaaam(nuc)
if _is_metastable_beta_decay_0(item, metastable_cutoff):
if 'B-' in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key,
item[6] / 100.0)
if 'B+' in item[5] or "EC" in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_plus_or_electron_capture_x',
nuc, key, item[6] / 100.0)
if _is_metastable_beta_decay_x(item, metastable_cutoff):
key += 1
longest2[key] = longest2.get(key, 0)
if item[1] == longest2[key]:
if 'B-' in item[5]:
_plus_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key,
item[6] / 100.0)
#item[6]*item[8]/100.0)
if 'B+' in item[5] or "EC" in item[5]:
_plus_eq_decay_t9(t9,
'frac_beta_plus_or_electron_capture_x',
nuc, key, item[6] / 100.0)
#key, item[6]*item[8]/100.0)
elif item[1] > longest2[key]:
longest2[key] = item[1]
if 'B-' in item[5]:
#_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key, item[6]*item[8]/100.0)
_eq_decay_t9(t9, 'frac_beta_minus_x', nuc, key,
item[6] / 100.0)
if 'B+' in item[5] or "EC" in item[5]:
_eq_decay_t9(t9, 'frac_beta_plus_or_electron_capture_x',
nuc, key, item[6] / 100.0)
#key, item[6]*item[8]/100.0)
for item in branches:
nuc = nucname.id(item[0])
key = nucname.zzaaam(nuc)
if (item[1] == 0) and (item[2] > metastable_cutoff):
_set_branch_item(t9, nuc, key, item)
if (item[1] != 0) and (item[2] > metastable_cutoff):
key += 1
longest[key] = longest.get(key, 0)
if (item[2] <= longest[key]):
continue
_set_branch_item(t9, nuc, key, item)
for nucs, hl in zip([
origen22.ACTIVATION_PRODUCT_NUCS,
origen22.ACTINIDE_AND_DAUGHTER_NUCS, origen22.FISSION_PRODUCT_NUCS
], [t9[i]['half_life'] for i in range(1, 4)]):
for nuc in nucs:
key = nucname.zzaaam(nuc)
if key not in hl:
hl[key] = data.half_life(nuc)
return t9
print(np.log(2)/data.decay_const('922340000')/3.15e7)
print('-------Np-239 to Pu-239 test--------')
print(data.decay_const('932390'))
print(data.decay_children('932390'))
print(data.decay_const('932390'))
print(data.decay_children('932390'))
print(data.branch_ratio(932390,942390))
print('-------U-240 decay test--------')
print(np.log(2)/data.decay_const('922400')/3600)
print(data.branch_ratio('922400','932400', use_metastable=False))
print('-----U234 Capture Test-----')
print(float('922350')-float('922340') == 10)
print('-----Mass Test-----')
print(nucname.anum('922350'))
print('-----Name Test-----')
print(nucname.serpent('922350'))
print('-------U-236 test--------')
print(data.decay_const('922360'))
print(data.half_life('922360')/(3.15e7))
print('-------Np-234 to U-234 test--------')
print(data.decay_const('932340'))
print(data.decay_children('932340'))
print(data.branch_ratio(932340,922340))
def test_half_life():
assert_equal(data.half_life('H1'), np.inf)
assert_equal(data.half_life(922350001), 1560.0)
def get_half_life(self):
return [data.half_life(nuc_id) for nuc_id in self.keys()]
def test_half_life():
assert_equal(data.half_life('H1'), np.inf)
assert_equal(data.half_life(922351), 1560.0)
def test_half_life():
assert_equal(data.half_life("H1"), np.inf)
assert_equal(data.half_life(922351), 1560.0)
def test_half_life():
assert_equal(data.half_life("H1"), np.inf)
assert_equal(data.half_life(922350001), 1560.0)
assert_equal(data.half_life("Eu151"), np.inf)
