In [1]:

    

import os
import json
import warnings
import numpy as np


    

In [2]:

    

origen_libs = '/home/scopatz/origen22/libs'
tape9 = 'decay.lib'
lib = os.path.join(origen_libs, tape9)


    

In [3]:

    

from pyne import utils
utils.toggle_warnings()
warnings.simplefilter('ignore')
from pyne.origen22 import parse_tape9
from pyne import nucname


    

In [4]:

    

toname = lambda nuc: nucname.name(nucname.zzaaam_to_id(int(nuc)))
ln2 = np.log(2.0)


    

In [5]:

    

t9 = parse_tape9(lib)


    

In [6]:

    

nlb = tuple(sorted(t9.keys()))


    

In [7]:

    

nlb


    

    
Out[7]:





(1, 2, 3)

In [8]:

    

t9[3]['half_life']


    

    
Out[8]:





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 591390: 15840.000000000002,
 591400: 203.40000000000001,
 591410: inf,
 591420: 68870.0,
 591421: 876.0,
 591430: 1172000.0,
 591440: 1037.0,
 591441: 432.0,
 591450: 21530.0,
 591460: 1452.0,
 591470: 720.0,
 591480: 138.0,
 591490: 138.0,
 591500: 12.4,
 591510: 4.0,
 591520: 8.3179999999999996,
 591530: 7.7430000000000003,
 591540: 1.3069999999999999,
 591550: 1.891,
 591560: 0.51039999999999996,
 591570: 0.67789999999999995,
 591580: 0.26290000000000002,
 591590: 0.31409999999999999,
 601410: 9000.0,
 601420: inf,
 601430: inf,
 601440: 6.6229999999999998e+22,
 601450: inf,
 601460: inf,
 601470: 955600.0,
 601480: inf,
 601490: 6228.0,
 601500: inf,
 601510: 744.0,
 601520: 690.0,
 601530: 67.540000000000006,
 601540: 40.0,
 601550: 26.059999999999999,
 601560: 58.490000000000002,
 601570: 4.149,
 601580: 7.8890000000000002,
 601590: 1.4079999999999999,
 601600: 2.121,
 601610: 0.55579999999999996,
 611450: 558600000.0,
 611460: 173563093.0,
 611470: 82790000.0,
 611480: 464000.0,
 611481: 3568000.0,
 611490: 191100.0,
 611500: 9648.0,
 611510: 102200.0,
 611520: 246.0,
 611521: 450.0,
 611530: 324.0,
 611540: 168.0,
 611541: 108.0,
 611550: 36.560000000000002,
 611560: 13.1,
 611570: 68.019999999999996,
 611580: 3.8010000000000002,
 611590: 4.2300000000000004,
 611600: 0.99629999999999996,
 611610: 1.1879999999999999,
 611620: 0.39989999999999998,
 621450: 29380000.0,
 621460: 2208984820000000.0,
 621470: 3.377e+18,
 621480: 2.5249999999999999e+23,
 621490: 3.1540000000000001e+23,
 621500: inf,
 621510: 2840000000.0,
 621520: inf,
 621530: 168100.0,
 621540: inf,
 621550: 1332.0,
 621560: 33840.0,
 621570: 480.0,
 621580: 2639.0,
 621590: 162.19999999999999,
 621600: 349.10000000000002,
 621610: 12.880000000000001,
 621620: 19.59,
 621630: 2.5630000000000002,
 621640: 4.2469999999999999,
 621650: 0.9274,
 631490: 8043839.9999999991,
 631500: 1136049336.0,
 631510: inf,
 631520: 429200000.0,
 631521: 33550.0,
 631530: inf,
 631540: 271400000.0,
 631550: 156500000.0,
 631560: 1312000.0,
 631570: 54720.0,
 631580: 2754.0,
 631590: 1086.0,
 631600: 51.0,
 631610: 42.060000000000002,
 631620: 269.80000000000001,
 631630: 14.84,
 631640: 2.1699999999999999,
 631650: 2.548,
 641520: 3.408e+21,
 641530: 20910000.0,
 641540: inf,
 641550: inf,
 641551: 0.031,
 641560: inf,
 641570: inf,
 641580: inf,
 641590: 66960.0,
 641600: inf,
 641610: 222.0,
 641620: 600.0,
 641630: 92.769999999999996,
 641640: 1301.0,
 641650: 100.2,
 651590: inf,
 651600: 6247000.0,
 651610: 597900.0,
 651620: 448.19999999999999,
 651621: 8028.0,
 651630: 1170.0,
 651631: 420.0,
 651640: 180.0,
 651650: 32.75,
 661600: inf,
 661610: inf,
 661620: inf,
 661630: inf,
 661640: inf,
 661650: 8460.0,
 661651: 75.359999999999999,
 661660: 293400.0,
 671650: inf,
 671660: 96480.0,
 671661: 37870000000.0,
 681660: inf,
 681670: inf,
 681671: 2.2999999999999998,
 681680: inf,
 681690: 812160.0,
 681700: inf,
 681710: 27070.0,
 681720: 176400.0,
 691690: inf,
 691700: 11110000.0,
 691701: 4.0999999999999997e-06,
 691710: 60590000.0,
 691720: 228960.0,
 701680: inf,
 701690: 2766000.0,
 701700: inf,
 701710: inf,
 701720: inf}

In [12]:

    

DECAY_RXS = ['bminus', 'bplus', 'ec', 'alpha', 'it', 'sf', 'bminus_n']
paroff = {'frac_beta_minus': 10000000, 'frac_beta_minus_x': 10000001, 
  'frac_beta_plus_or_electron_capture': -10000000,
  'frac_beta_plus_or_electron_capture_x': -9999999,
  'frac_alpha': -20040000,
  'frac_isomeric_transition': -1,
  #'frac_spont_fiss': 0,
  'frac_beta_n': 9990000}
paroffm = {'frac_beta_minus': 9999999, 'frac_beta_minus_x': 10000000, 
  'frac_beta_plus_or_electron_capture': -10000001,
  'frac_beta_plus_or_electron_capture_x': -10000000,
  'frac_alpha': -20040001,
  'frac_isomeric_transition': -1,
  #'frac_spont_fiss': 0,
  'frac_beta_n': 9989999}
lambdas = {}
gamma_maps = {}
nucs = set()
for n in nlb:
    lambdas.update({'lambda_' + toname(nuc): ln2/val for nuc, val in t9[n]['half_life'].items() if nuc != 162500})
    for key in t9[n]:
        if not key.startswith('frac_') or key == 'frac_natural_abund' or key == 'frac_spont_fiss':
            continue
        for nuc, val in t9[n][key].items():
            if val < 1e-16:
                continue  # forbidden decay
            nname = toname(nuc)
            if lambdas['lambda_' + nname] < 1e-16:
                continue  # stable nuclide
            if nname not in gamma_maps:
                gamma_maps[nname] = {}
            poff = paroff if int(nuc)%10 == 0 else paroffm
            child = nucname.zzaaam_to_id(int(nuc)) + poff[key]
            cname = nucname.name(child)
            gname = 'gamma_{0}_{1}_{2}'.format(nname, cname, key[5:])
            gamma_maps[nname][gname] = val
            nucs.add(nname)
            nucs.add(cname)
            
# add β- decays
for key, val in lambdas.items():
    if val < 1e-16:
        continue  # stable nuclide
    _, _, nname = key.rpartition('_')
    if nname not in gamma_maps:
        gamma_maps[nname] = {}
    gamma_total = sum(gamma_maps[nname].values())
    if gamma_total < 1.0:
        parid = nucname.id(nname)
        poff = paroff if parid%10 == 0 else paroffm
        child = parid + poff['frac_beta_minus']
        cname = nucname.name(child)
        gname = 'gamma_{0}_{1}_{2}'.format(nname, cname, 'beta_minus')
        gamma_maps[nname][gname] = 1.0 - gamma_total
        nucs.add(nname)
        nucs.add(cname)


    

In [13]:

    

symbols = dict(lambdas)
for val in gamma_maps.values():
    symbols.update(val)


    

In [14]:

    

with open('transmute_data.json', 'r') as f:
    data = json.load(f)
data['symbols'] = symbols
nucs |= set(data['nucs']) 
data['nucs'] = sorted(nucs, key=nucname.id)
with open('transmute_data.json', 'w') as f:
    json.dump(data, f, indent='    ', sort_keys=True)


    

In [ ]: