decay_analysis.ipynb

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     "text": [
      "/home/scopatz/miniconda/lib/python3.6/importlib/_bootstrap.py:219: QAWarning: pyne.data is not yet QA compliant.\n",
      "  return f(*args, **kwds)\n",
      "/home/scopatz/miniconda/lib/python3.6/importlib/_bootstrap.py:219: QAWarning: pyne.material is not yet QA compliant.\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import pyne\n",
    "from decay_compare import *\n",
    "from pyne import data\n",
    "from pyne import rxname\n",
    "import tables as tb"
   ]
  },
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      "Running nuc Ga75\n",
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      "Running nuc Fm242\n",
      "Running nuc Fm243\n",
      "Running nuc Fm244\n",
      "Running nuc Fm245\n",
      "Running nuc Fm246\n",
      "Running nuc Fm247\n",
      "Running nuc Fm248\n",
      "Running nuc Fm249\n",
      "Running nuc Fm250\n",
      "Running nuc Fm251\n",
      "Running nuc Fm252\n",
      "Running nuc Fm253\n",
      "Running nuc Fm254\n",
      "Running nuc Fm255\n",
      "Running nuc Fm256\n",
      "Running nuc Fm257\n",
      "Running nuc Fm258\n",
      "Running nuc Fm259\n",
      "Running nuc Fm260\n",
      "Running nuc Md245\n",
      "Running nuc Md246\n",
      "Running nuc Md247\n",
      "Running nuc Md248\n",
      "Running nuc Md249\n",
      "Running nuc Md250\n",
      "Running nuc Md251\n",
      "Running nuc Md252\n",
      "Running nuc Md253\n",
      "Running nuc Md254\n",
      "Running nuc Md255\n",
      "Running nuc Md256\n",
      "Running nuc Md257\n",
      "Running nuc Md258\n",
      "Running nuc Md259\n",
      "Running nuc Md260\n",
      "Running nuc Md261\n",
      "Running nuc Md262\n",
      "Running nuc No248\n",
      "Running nuc No249\n",
      "Running nuc No250\n",
      "Running nuc No251\n",
      "Running nuc No252\n",
      "Running nuc No253\n",
      "Running nuc No254\n",
      "Running nuc No255\n",
      "Running nuc No256\n",
      "Running nuc No257\n",
      "Running nuc No258\n",
      "Running nuc No259\n",
      "Running nuc No260\n",
      "Running nuc No261\n",
      "Running nuc No262\n",
      "Running nuc No263\n",
      "Running nuc No264\n",
      "Running nuc Lr251\n",
      "Running nuc Lr252\n",
      "Running nuc Lr253\n",
      "Running nuc Lr254\n",
      "Running nuc Lr255\n",
      "Running nuc Lr256\n",
      "Running nuc Lr257\n",
      "Running nuc Lr258\n",
      "Running nuc Lr259\n",
      "Running nuc Lr260\n",
      "Running nuc Lr261\n",
      "Running nuc Lr262\n",
      "Running nuc Lr263\n",
      "Running nuc Lr264\n",
      "Running nuc Lr265\n",
      "Running nuc Lr266\n",
      "Running nuc Rf253\n",
      "Running nuc Rf254\n",
      "Running nuc Rf255\n",
      "Running nuc Rf256\n",
      "Running nuc Rf257\n",
      "Running nuc Rf258\n",
      "Running nuc Rf259\n",
      "Running nuc Rf260\n",
      "Running nuc Rf261\n",
      "Running nuc Rf262\n",
      "Running nuc Rf263\n",
      "Running nuc Rf264\n",
      "Running nuc Rf265\n",
      "Running nuc Rf266\n",
      "Running nuc Rf267\n",
      "Running nuc Rf268\n",
      "Running nuc Db255\n",
      "Running nuc Db256\n",
      "Running nuc Db257\n",
      "Running nuc Db258\n",
      "Running nuc Db259\n",
      "Running nuc Db260\n",
      "Running nuc Db261\n",
      "Running nuc Db262\n",
      "Running nuc Db263\n",
      "Running nuc Db264\n",
      "Running nuc Db265\n",
      "Running nuc Db266\n",
      "Running nuc Db267\n",
      "Running nuc Db268\n",
      "Running nuc Db269\n",
      "Running nuc Db270\n",
      "Running nuc Sg258\n",
      "Running nuc Sg259\n",
      "Running nuc Sg260\n",
      "Running nuc Sg261\n",
      "Running nuc Sg262\n",
      "Running nuc Sg263\n",
      "Running nuc Sg264\n",
      "Running nuc Sg265\n",
      "Running nuc Sg266\n",
      "Running nuc Sg267\n",
      "Running nuc Sg268\n",
      "Running nuc Sg269\n",
      "Running nuc Sg270\n",
      "Running nuc Sg271\n",
      "Running nuc Sg272\n",
      "Running nuc Sg273\n",
      "Running nuc Bh260\n",
      "Running nuc Bh261\n",
      "Running nuc Bh262\n",
      "Running nuc Bh263\n",
      "Running nuc Bh264\n",
      "Running nuc Bh265\n",
      "Running nuc Bh266\n",
      "Running nuc Bh267\n",
      "Running nuc Bh268\n",
      "Running nuc Bh269\n",
      "Running nuc Bh270\n",
      "Running nuc Bh271\n",
      "Running nuc Bh272\n",
      "Running nuc Bh273\n",
      "Running nuc Bh274\n",
      "Running nuc Bh275\n",
      "Running nuc Hs263\n",
      "Running nuc Hs264\n",
      "Running nuc Hs265\n",
      "Running nuc Hs266\n",
      "Running nuc Hs267\n",
      "Running nuc Hs268\n",
      "Running nuc Hs269\n",
      "Running nuc Hs270\n",
      "Running nuc Hs271\n",
      "Running nuc Hs272\n",
      "Running nuc Hs273\n",
      "Running nuc Hs274\n",
      "Running nuc Hs275\n",
      "Running nuc Hs276\n",
      "Running nuc Hs277\n",
      "Running nuc Mt265\n",
      "Running nuc Mt266\n",
      "Running nuc Mt267\n",
      "Running nuc Mt268\n",
      "Running nuc Mt269\n",
      "Running nuc Mt270\n",
      "Running nuc Mt271\n",
      "Running nuc Mt272\n",
      "Running nuc Mt273\n",
      "Running nuc Mt274\n",
      "Running nuc Mt275\n",
      "Running nuc Mt276\n",
      "Running nuc Mt277\n",
      "Running nuc Mt278\n",
      "Running nuc Mt279\n",
      "Running nuc Ds267\n",
      "Running nuc Ds268\n",
      "Running nuc Ds269\n",
      "Running nuc Ds270\n",
      "Running nuc Ds271\n",
      "Running nuc Ds272\n",
      "Running nuc Ds273\n",
      "Running nuc Ds274\n",
      "Running nuc Ds275\n",
      "Running nuc Ds276\n",
      "Running nuc Ds277\n",
      "Running nuc Ds278\n",
      "Running nuc Ds279\n",
      "Running nuc Ds280\n",
      "Running nuc Ds281\n",
      "Running nuc Rg272\n",
      "Running nuc Rg273\n",
      "Running nuc Rg274\n",
      "Running nuc Rg275\n",
      "Running nuc Rg276\n",
      "Running nuc Rg277\n",
      "Running nuc Rg278\n",
      "Running nuc Rg279\n",
      "Running nuc Rg280\n",
      "Running nuc Rg281\n",
      "Running nuc Rg282\n",
      "Running nuc Rg283\n",
      "Running nuc Cn276\n",
      "Running nuc Cn277\n",
      "Running nuc Cn278\n",
      "Running nuc Cn279\n",
      "Running nuc Cn280\n",
      "Running nuc Cn281\n",
      "Running nuc Cn282\n",
      "Running nuc Cn283\n",
      "Running nuc Cn284\n",
      "Running nuc Cn285\n",
      "Running nuc Fl285\n",
      "Running nuc Fl286\n",
      "Running nuc Fl287\n",
      "Running nuc Fl288\n",
      "Running nuc Fl289\n",
      "Running nuc Lv289\n",
      "Running nuc Lv290\n",
      "Running nuc Lv291\n",
      "Running nuc Lv292\n",
      "Running nuc Lv293\n",
      "CPU times: user 25min 12s, sys: 3.22 s, total: 25min 15s\n",
      "Wall time: 25min 20s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "nucs = cram.NUCS\n",
    "#n = 34\n",
    "#nucs = cram.NUCS[100*n:100*(n+1)]\n",
    "#nucs = cram.NUCS[:100*(n+1)]\n",
    "# degenerate cases\n",
    "#nucs = ['Lu153', 'Tm149', 'Pt183', 'Os179', 'Ir172', 'Re168']\n",
    "#nucs = ['Ir172']\n",
    "# run custom\n",
    "#nucs = ['Ra233', 'Ac225']\n",
    "#nucs = ['Es254', 'U238']\n",
    "batemans, crammeds, diagexps = run_nuclides(nucs=nucs, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "NNUCS = len(crammeds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = np.zeros((NTIMES, NNUCS), dtype=float)\n",
    "c = np.zeros((NTIMES, NNUCS), dtype=float)\n",
    "d = np.zeros((NTIMES, NNUCS), dtype=float)\n",
    "for n, nuc in enumerate(nucs):\n",
    "    b[:, n] = batemans[nuc][nuc]\n",
    "    c[:, n] = crammeds[nuc][nuc]\n",
    "    d[:, n] = diagexps[nuc][nuc]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "diagdiff = np.abs(d - c)\n",
    "mu_diagdiff = diagdiff.mean(axis=1)\n",
    "sigma_diagdiff = diagdiff.std(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.000000000000000000e+00,   3.754636572365821893e-15,\n",
       "         3.717442428019598886e-15,   3.557125436531985541e-15,\n",
       "         3.511898542297126667e-15,   3.316436173827032667e-15,\n",
       "         3.074008905767086993e-15,   3.040453912315323736e-15,\n",
       "         2.753163233576432814e-15,   2.646253934999197766e-15,\n",
       "         2.550450534346675417e-15,   2.275927021597371577e-15,\n",
       "         2.115858468759241220e-15,   2.074379557643371600e-15,\n",
       "         1.881691100316992526e-15,   1.908998858300780856e-15,\n",
       "         1.850891313682815425e-15,   1.807656279627915365e-15,\n",
       "         1.668549158336787183e-15,   1.655956402438337158e-15,\n",
       "         1.675573274832228151e-15,   1.719418883646557701e-15,\n",
       "         1.558330505800380177e-15,   1.530539833787811531e-15,\n",
       "         1.629457828976885520e-15,   1.563532764321689354e-15,\n",
       "         1.552495971326724039e-15,   1.504360660898114525e-15,\n",
       "         1.509002260671749429e-15,   1.533679967883295593e-15,\n",
       "         1.423079750611544782e-15,   1.466250530545314315e-15,\n",
       "         1.425179953631980715e-15,   1.452354042783757887e-15,\n",
       "         1.461818382891744827e-15,   1.449580443123617914e-15,\n",
       "         1.479679261841886232e-15,   1.400764316884040167e-15,\n",
       "         1.419663552074469919e-15,   1.420258058996230194e-15])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sigma_diagdiff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Difference plot for all nuclides\n",
    "\n",
    "The red line is the mean difference with $1\\sigma$ error bars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff1c3397cf8>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Bqf9HmngbV904/PIm4jpXnf5uQ1GMp8tBw6a0HtOZdYE0K8KhzXbyNmN1nAJvloXrpKiN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3/5S9xx6qm485RTMD8+vuK6l0pItDQyMhJeRiAOMfZASpqdmppKlS8gfsBtkZxrtRrq9fpAwkGy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\nDxNVz12MHiI4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1c843e668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(TIMES[1:], diagdiff[1:, :], color='gray', alpha=0.01)\n",
    "plt.errorbar(TIMES[1:], mu_diagdiff[1:], yerr=sigma_diagdiff[1:], color='red', capsize=5, label='mean')\n",
    "plt.axis([TIMES[1]*0.75, TIMES[-1]*1.25, 0.0, 2e-14])\n",
    "plt.xscale('log')\n",
    "#plt.yscale('log')\n",
    "plt.xlabel('time [s]')\n",
    "plt.ylabel('Difference, $\\\\left|e^{-\\\\lambda t} - r_{k,k}\\\\right|$')\n",
    "plt.legend(loc=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bateman Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bateman_diff_plot(nuc, batemans, crammeds):\n",
    "    try:\n",
    "        bateman = batemans[nuc]\n",
    "        crammed = crammeds[nuc]\n",
    "    except KeyError:\n",
    "        print('Nuclide not in data!')\n",
    "        return\n",
    "    diff = diff_nuclide(bateman, crammed, abs=True)\n",
    "    d = np.zeros((NTIMES, len(diff)), dtype=float)\n",
    "    for i, (n, arr) in enumerate(diff.items()):\n",
    "        if data.fpyield(nuc, n) > 0:\n",
    "            print('skipping', n)\n",
    "            continue\n",
    "        plt.plot(TIMES, arr, label=n)\n",
    "        d[:,i] = arr\n",
    "    mu = d.mean(axis=1)\n",
    "    sigma = d.std(axis=1)\n",
    "    #plt.errorbar(TIMES, mu, yerr=sigma, capsize=5, color='black', label='mean')\n",
    "    plt.xscale('log')\n",
    "    #plt.yscale('log')\n",
    "    #plt.axis([TIMES[1]*0.75, TIMES[-1]*1.25, 1e-18, 1e-6])\n",
    "    plt.xlabel('time [s]')\n",
    "    plt.ylabel('Difference, $\\\\left|e^{-\\\\lambda t} - r_{k,k}\\\\right|$')\n",
    "    plt.legend(loc=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "#bateman_diff_plot('I131', batemans=batemans, crammeds=crammeds)\n",
    "\n",
    "#bateman_diff_plot('Sr90', batemans=batemans, crammeds=crammeds)\n",
    "\n",
    "#bateman_diff_plot('H3', batemans=batemans, crammeds=crammeds)\n",
    "\n",
    "#bateman_diff_plot('U235', batemans=batemans, crammeds=crammeds)\n",
    "\n",
    "#bateman_diff_plot('Se86', batemans=batemans, crammeds=crammeds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Histogram of errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lu153 -> Ho149\n",
      "Lu153 -> Er149\n",
      "Ta157 -> Ho149\n",
      "Ta157 -> Er149\n",
      "Ta157 -> Tm149\n",
      "Ir172 -> W168\n",
      "Ir172 -> Ta168\n",
      "Pt172 -> W168\n",
      "Pt172 -> Re168\n",
      "Pt183 -> Re179\n",
      "Au183 -> Re179\n",
      "Hg176 -> W168\n",
      "Hg176 -> Re168\n",
      "Hg183 -> Re179\n",
      "Hg183 -> W179\n",
      "Tl177 -> W168\n",
      "Tl177 -> Re168\n",
      "Pb180 -> W168\n",
      "Pb180 -> Re168\n",
      "Cf255 -> Pb207\n",
      "Es254 -> Pb206\n",
      "Es256 -> Pb208\n",
      "Md256 -> Pb208\n",
      "Md258 -> Bi209\n",
      "Md258 -> Pb206\n",
      "No255 -> Pb207\n",
      "Lr259 -> Pb207\n",
      "Lr260 -> Pb208\n",
      "Rf259 -> Pb207\n",
      "Rf263 -> Pb207\n",
      "Db263 -> Pb207\n",
      "Bh267 -> Pb207\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(40, 32968)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff_arrs = []\n",
    "for nuc in nucs:\n",
    "    diff = diff_nuclide(batemans[nuc], crammeds[nuc], abs=True, include_missing=False)\n",
    "    diff_arr = np.empty((NTIMES, len(diff)), dtype=float)\n",
    "    for i, (n, d) in enumerate(diff.items()):\n",
    "        diff_arr[:,i] = d\n",
    "        if np.abs(d).max() >= 1e-4:\n",
    "            print(nuc, '->', n)\n",
    "    diff_arrs.append(diff_arr)\n",
    "diff_arrs = np.concatenate(diff_arrs, axis=1)\n",
    "diff_arrs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kDWGg+9Rk5heBL9Zcy8C8T40kSapq5V2BnSgsSZKqWhlqJEmSqgw1kiSpCIYaSZJUhFaG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\nDDWSJKkIhhpJklQEQ40kSSrC/wfk0qg8YXACdAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1c04c5e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,6))\n",
    "diff_vals = np.array(diff_arrs.flat)\n",
    "diff_vals[diff_vals < 1e-32] = 2e-32  # put very small values in lowest bin\n",
    "plt.hist(diff_vals, bins=np.logspace(-32, 0, 33), log=True)\n",
    "plt.xscale('log')\n",
    "plt.axis([1e-32, 1, 1e0, 1e6])\n",
    "plt.xlabel('Difference, $\\\\left|b - r_{k,k}\\\\right|$')\n",
    "plt.ylabel('Count')\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  1.000000000000000056e-32,   1.000000000000000083e-31,\n",
       "         1.000000000000000083e-30,   9.999999999999999432e-30,\n",
       "         9.999999999999999712e-29,   1.000000000000000038e-27,\n",
       "         1.000000000000000038e-26,   1.000000000000000038e-25,\n",
       "         9.999999999999999237e-25,   9.999999999999999604e-24,\n",
       "         1.000000000000000049e-22,   9.999999999999999075e-22,\n",
       "         9.999999999999999452e-21,   9.999999999999999752e-20,\n",
       "         1.000000000000000072e-18,   1.000000000000000072e-17,\n",
       "         9.999999999999999791e-17,   1.000000000000000078e-15,\n",
       "         9.999999999999999988e-15,   1.000000000000000030e-13,\n",
       "         9.999999999999999799e-13,   9.999999999999999395e-12,\n",
       "         1.000000000000000036e-10,   1.000000000000000062e-09,\n",
       "         1.000000000000000021e-08,   9.999999999999999547e-08,\n",
       "         9.999999999999999547e-07,   1.000000000000000082e-05,\n",
       "         1.000000000000000048e-04,   1.000000000000000021e-03,\n",
       "         1.000000000000000021e-02,   1.000000000000000056e-01,\n",
       "         1.000000000000000000e+00])"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.logspace(-32, 0, 33)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.hist?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cf255 -> Pb207\n",
      "\n",
      "CRAM\n",
      " [  0.000000000000000000e+00   0.000000000000000000e+00\n",
      "   0.000000000000000000e+00   0.000000000000000000e+00\n",
      "   0.000000000000000000e+00   0.000000000000000000e+00\n",
      "   0.000000000000000000e+00   0.000000000000000000e+00\n",
      "   3.004583109322537932e-75   1.901573144939713906e-67\n",
      "   8.432717180894103755e-61   1.278447750229402520e-54\n",
      "   6.100252125592471640e-49   7.448231824836584918e-44\n",
      "   2.266639913889272887e-39   2.105327708546501611e-35\n",
      "   9.744806983185536680e-32   3.249349899553046306e-28\n",
      "   8.498673205925198696e-25   1.590584745355534388e-21\n",
      "   2.009649896353452238e-18   1.765718531184143617e-15\n",
      "   9.816590489077626649e-13   2.807394559572073110e-10\n",
      "   3.208009302313451451e-08   1.159486261223195409e-06\n",
      "   1.786540712746881516e-05   1.975579101872099229e-04\n",
      "   1.864266280642392628e-03   1.422742523436097868e-02\n",
      "   7.359499917796145929e-02   2.513481354671422419e-01\n",
      "   6.186546277433677687e-01   9.547967670517173433e-01\n",
      "   9.999056985014812549e-01   9.999587782097556499e-01\n",
      "   9.999587782097794086e-01   9.999587782098001698e-01\n",
      "   9.999587782097537625e-01   9.999587782097431043e-01]\n",
      "Bateman\n",
      " [  0.000000000000000000e+00   3.656898539523271030e-16\n",
      "   9.875313863339782293e-16   3.077337069030385977e-15\n",
      "   9.932972569130657624e-15   3.117196018177439918e-14\n",
      "   9.866388807078134612e-14   3.119237809526450381e-13\n",
      "   9.866650212396165700e-13   3.119765316840459279e-12\n",
      "   9.865804112619887651e-12   3.119834307556788562e-11\n",
      "   9.865767817321957116e-11   3.119830186178885263e-10\n",
      "   9.865769224339525338e-10   3.119830024626090351e-09\n",
      "   9.865768717752461795e-09   3.119829966361481674e-08\n",
      "   9.865768271097511062e-08   3.119829529497435071e-07\n",
      "   9.865763895184108595e-07   3.119825148543693859e-06\n",
      "   9.865720093013512063e-06   3.119781347317362796e-05\n",
      "   9.865282090571356687e-05   3.119343379102616602e-04\n",
      "   9.860903491502128783e-04   3.114968202768394600e-03\n",
      "   9.817259722736056821e-03   3.071663537084032974e-02\n",
      "   9.394700405703754198e-02   2.680043951740114783e-01\n",
      "   6.271384871865388622e-01   9.558016030976103083e-01\n",
      "   9.999068795030031653e-01   9.999587782097538735e-01\n",
      "   9.999587782097822952e-01   9.999587782097821842e-01\n",
      "   9.999587782097822952e-01   9.999587782097819622e-01]\n",
      "Diff\n",
      " [  0.000000000000000000e+00   3.656898539523271030e-16\n",
      "   9.875313863339782293e-16   3.077337069030385977e-15\n",
      "   9.932972569130657624e-15   3.117196018177439918e-14\n",
      "   9.866388807078134612e-14   3.119237809526450381e-13\n",
      "   9.866650212396165700e-13   3.119765316840459279e-12\n",
      "   9.865804112619887651e-12   3.119834307556788562e-11\n",
      "   9.865767817321957116e-11   3.119830186178885263e-10\n",
      "   9.865769224339525338e-10   3.119830024626090351e-09\n",
      "   9.865768717752461795e-09   3.119829966361481674e-08\n",
      "   9.865768271097511062e-08   3.119829529497419189e-07\n",
      "   9.865763895164012739e-07   3.119825146777975330e-06\n",
      "   9.865719111354462768e-06   3.119753273371767401e-05\n",
      "   9.862074081269043549e-05   3.107748516490384445e-04\n",
      "   9.682249420227440496e-04   2.917410292581184596e-03\n",
      "   7.952993442093663976e-03   1.648921013647935280e-02\n",
      "   2.035200487907608269e-02   1.665625970686923640e-02\n",
      "   8.483859443171093417e-03   1.004836045892965046e-03\n",
      "   1.181001521910474139e-06  -1.776356839400250465e-15\n",
      "   2.886579864025407005e-15  -1.798561299892753595e-14\n",
      "   2.853273173286652309e-14   3.885780586188047891e-14]\n"
     ]
    },
    {
     "data": {
      "image/png": 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TImeqalZBJEknAU97lSR1YnFIkjqxOCRJnTzjiiPJC5PclOT2JL84HvvRJO9N8uEkPzQH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1c0e97eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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20L17d0aNGsWyZcuafU+RiOifCaq6SFVXAstofkTrEgIJ5YKygO31lXE6kw7A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\nGIXgAQAARiF4AACAUQgeAABg1P8D7OPpY2ojOPMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff1c0d72710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nuc = 'Cf255'\n",
    "ouc = 'Pb207'\n",
    "print(nuc + ' -> ' + ouc + '\\n')\n",
    "print('CRAM\\n', crammeds[nuc][ouc])\n",
    "print('Bateman\\n', batemans[nuc][ouc])\n",
    "differs = batemans[nuc][ouc] - crammeds[nuc][ouc]\n",
    "print('Diff\\n', differs)\n",
    "plt.hist(np.abs(differs), bins=np.logspace(-32, 0, 33), log=True)\n",
    "plt.xscale('log')\n",
    "plt.axis([1e-32, 1, 1e0, 1e5])\n",
    "plt.xlabel('Difference, $\\\\left|b - r_{k,k}\\\\right|$')\n",
    "plt.ylabel('Count')\n",
    "plt.figure()\n",
    "bateman_diff_plot(nuc, batemans=batemans, crammeds=crammeds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "for ouc in batemans[nuc].keys():\n",
    "    value = crammeds[nuc][ouc]\n",
    "    if np.all(value == 0.0):\n",
    "        print(nuc, ouc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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