{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "46d48b51-b649-4bc7-875b-648dcd6d2f56",
   "metadata": {},
   "source": [
    "# Create perturbed $^{239}$Pu thermal FY files using CEA evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "80083589-cecb-4332-8aa9-02278c5a9663",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:04.033293Z",
     "iopub.status.busy": "2026-02-24T13:55:04.033058Z",
     "iopub.status.idle": "2026-02-24T13:55:05.833613Z",
     "shell.execute_reply": "2026-02-24T13:55:05.832683Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Failed to extract font properties from /usr/share/fonts/truetype/noto/NotoColorEmoji.ttf: Can not load face (unknown file format; error code 0x2)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "generated new fontManager\n"
     ]
    }
   ],
   "source": [
    "import sandy\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from os.path import join, dirname\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import random, sys"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7f2d039-5285-4b0e-9f84-55294a747dce",
   "metadata": {},
   "source": [
    "## Extract FYs and covariance data for Pu239 thermal fission"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d572351b-4450-4c30-8d81-b3cd1a0cb310",
   "metadata": {},
   "source": [
    "If you don't find these files, download them from the [NEA GITLAB repository](https://git.oecd-nea.org/databank/nds/jeff/jeff-lab/fission-yields-pu-239-th)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4e7b4c6d-5c73-4e80-b90a-1ea90137cc87",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:05.835733Z",
     "iopub.status.busy": "2026-02-24T13:55:05.835437Z",
     "iopub.status.idle": "2026-02-24T13:55:05.923515Z",
     "shell.execute_reply": "2026-02-24T13:55:05.922597Z"
    }
   },
   "outputs": [],
   "source": [
    "path = join(dirname(sandy.__file__), 'appendix', 'fission_yields')\n",
    "\n",
    "file_eval = r\"jeff-4t3_cea_pu9_cons_28-09-2023.stn\"\n",
    "file_cov = r\"jeff-4t3_cea_pu9th_cons_28-09-2023_ind_corr\"\n",
    "tape = sandy.Endf6.from_file(join(path, file_eval))\n",
    "nfpy = sandy.Fy.from_endf6(tape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cb8852d0-e541-4580-a4ea-e4139267f513",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:05.925382Z",
     "iopub.status.busy": "2026-02-24T13:55:05.925198Z",
     "iopub.status.idle": "2026-02-24T13:55:06.185104Z",
     "shell.execute_reply": "2026-02-24T13:55:06.184242Z"
    }
   },
   "outputs": [],
   "source": [
    "idx = nfpy.data.query(f\"E==0.0253 & MT==454\").index\n",
    "ifyth = nfpy.data.loc[idx]\n",
    "\n",
    "corr = pd.read_csv(join(path, file_cov), sep=r\"\\s+\", header=None)\n",
    "u = np.triu(corr, k=1)\n",
    "corr = u + u.T + np.diag(np.diag(corr))                                                # must do this because the matrix is not symmetric\n",
    "acov = sandy.corr2cov(corr, ifyth.DFY.values)                                          # absolute covariance matrix\n",
    "cov = np.divide(acov, ifyth.FY.values.reshape(-1, 1) @ ifyth.FY.values.reshape(1, -1)) # convert to relative terms\n",
    "cov = sandy.CategoryCov(pd.DataFrame(cov, index=ifyth.ZAP.values, columns=ifyth.ZAP.values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ce955aa8-843b-479c-a15c-69ee6f978e60",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:06.187496Z",
     "iopub.status.busy": "2026-02-24T13:55:06.187305Z",
     "iopub.status.idle": "2026-02-24T13:55:07.616752Z",
     "shell.execute_reply": "2026-02-24T13:55:07.615902Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "sns.heatmap(corr, vmin=-1, vmax=1, cmap=\"bwr\", ax=ax)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c338b9d-f74b-4f20-922e-37f04c0326e2",
   "metadata": {},
   "source": [
    "## Generate perturbation coefficients and write them to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "57d4f1b7-2762-4153-a814-9fe09c3fe994",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:07.618483Z",
     "iopub.status.busy": "2026-02-24T13:55:07.618317Z",
     "iopub.status.idle": "2026-02-24T13:55:09.784769Z",
     "shell.execute_reply": "2026-02-24T13:55:09.783989Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:  Condition COV + 1 > 0 for Lognormal sampling is not respected.\n",
      "    2/597871 covariance coefficients are set to -1+eps.\n",
      "    The smallest covariance is -1.05256\n",
      "    \n"
     ]
    }
   ],
   "source": [
    "seed = random.randrange(2**32 - 1)    # create a seed\n",
    "seed = 1444271357                     # or use always the same\n",
    "nsmp = 1000                           # sample size\n",
    "smp = cov.sampling(nsmp, seed=seed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a0aaa60b-0c9f-4993-91ea-e66db301e0f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:09.787095Z",
     "iopub.status.busy": "2026-02-24T13:55:09.786910Z",
     "iopub.status.idle": "2026-02-24T13:55:25.268959Z",
     "shell.execute_reply": "2026-02-24T13:55:25.268099Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.ExcelWriter('PERT_94239TH_MF8_MT454.xlsx') as writer:\n",
    "    pd.DataFrame([[seed]]).to_excel(writer, sheet_name='SEED', columns=None, index=False)\n",
    "    smp.data.to_excel(writer, sheet_name='IFY_TH')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea504633-a1fc-462b-8808-9a45f8361d52",
   "metadata": {},
   "source": [
    "## Read coefficients from perturbation file and generate random FY ENDF-6 files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17d1ac55-f384-4484-a0bb-7a4cc2dee76b",
   "metadata": {},
   "source": [
    "Skip the part above if you already have the file of perturbations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "632bbf34-9030-4b70-bc5b-51501b3dff77",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:25.271373Z",
     "iopub.status.busy": "2026-02-24T13:55:25.271186Z",
     "iopub.status.idle": "2026-02-24T13:55:33.961237Z",
     "shell.execute_reply": "2026-02-24T13:55:33.960430Z"
    }
   },
   "outputs": [],
   "source": [
    "smp = pd.read_excel(\"PERT_94239TH_MF8_MT454.xlsx\", sheet_name=\"IFY_TH\", index_col=0)\n",
    "smp = sandy.Samples(smp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ee52ce9c-f451-409c-b686-9bf83a446728",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:33.963287Z",
     "iopub.status.busy": "2026-02-24T13:55:33.963112Z",
     "iopub.status.idle": "2026-02-24T13:55:33.969961Z",
     "shell.execute_reply": "2026-02-24T13:55:33.969260Z"
    }
   },
   "outputs": [],
   "source": [
    "idx_ify = nfpy.data.query(f\"E==0.0253 & MT==454\").index\n",
    "idx_cfy = nfpy.data.query(f\"E==0.0253 & MT==459\").index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b52f4587-052f-4bcf-96ee-aeea456829b6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:55:33.971645Z",
     "iopub.status.busy": "2026-02-24T13:55:33.971463Z",
     "iopub.status.idle": "2026-02-24T13:56:31.749758Z",
     "shell.execute_reply": "2026-02-24T13:56:31.748855Z"
    }
   },
   "outputs": [],
   "source": [
    "tape_rdd = sandy.get_endf6_file(\"jeff_33\", \"decay\", \"all\")\n",
    "rdd = sandy.DecayData.from_endf6(tape_rdd)  # this can take a while"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ced64de5-69c9-4571-90f1-4b6d2394f2ff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:56:31.751669Z",
     "iopub.status.busy": "2026-02-24T13:56:31.751479Z",
     "iopub.status.idle": "2026-02-24T13:56:51.845372Z",
     "shell.execute_reply": "2026-02-24T13:56:51.844483Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_0.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_1.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_2.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_3.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_4.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_5.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_6.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_7.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_8.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_9.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_10.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_11.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_12.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_13.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_14.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_15.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_16.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_17.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_18.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_19.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_20.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_21.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_22.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_23.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_24.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_25.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_26.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_27.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_28.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_29.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_30.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_31.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_32.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_33.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_34.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_35.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_36.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_37.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_38.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_39.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_40.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_41.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_42.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_43.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_44.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_45.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_46.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_47.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_48.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_49.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_50.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_51.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_52.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_53.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_54.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_55.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_56.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_57.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_58.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_59.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_60.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_61.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_62.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_63.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_64.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_65.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_66.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_67.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_68.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_69.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_70.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_71.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_72.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_73.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_74.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_75.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_76.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_77.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_78.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_79.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_80.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_81.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_82.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_83.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_84.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_85.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_86.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_87.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_88.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_89.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_90.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_91.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_92.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_93.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_94.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_95.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_96.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_97.jeff4t3'...\n",
      "writing file 'pu239_fy_cea_cons_98.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_99.jeff4t3'...\n"
     ]
    }
   ],
   "source": [
    "smp_min = 0   # write ENDF-6 file only in the sample range [smp_min, smp_max]\n",
    "smp_max = 99\n",
    "file_template = \"pu239_fy_cea_cons_{}.jeff4t3\"\n",
    "for ismp in range(smp_min, smp_max+1):\n",
    "    file = file_template.format(ismp)\n",
    "    f = sandy.Fy(nfpy.data.copy())\n",
    "    f.data.loc[idx_ify, \"DFY\"] = f.data.loc[idx_ify, \"FY\"]            # just for me, i copy the original IFYs where uncertainties should be, so i can compare them to the perturbed ones (anyways I don't use uncertainties)\n",
    "    f.data.loc[idx_cfy, \"DFY\"] = f.data.loc[idx_cfy, \"FY\"]            # same but for CFYs\n",
    "    f.data.loc[idx_ify, \"FY\"] *= smp.data[ismp].values                # IMPORTANT, this does not update the CFYs, which in random ENDF-6 file are inconsistent with the perturbed IFYs\n",
    "    # f = f.apply_qmatrix(942390, 0.0253, rdd, keep_fy_index=True)      # Run this if you want to update the CFYs (slower), or else comment it out\n",
    "    print(f\"writing file '{file}'...\")\n",
    "    f.to_endf6(tape).to_file(file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "337a51c3-8c9c-46d8-9ab4-46b7d6d1958d",
   "metadata": {},
   "source": [
    "## Compare sample estimates of mass yields with deterministic uncertainty propagation (sandwich formula) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6e97e07-dedb-48f1-b59f-4d0ae97e31c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:56:51.847182Z",
     "iopub.status.busy": "2026-02-24T13:56:51.847006Z",
     "iopub.status.idle": "2026-02-24T13:57:03.028484Z",
     "shell.execute_reply": "2026-02-24T13:57:03.027701Z"
    }
   },
   "outputs": [],
   "source": [
    "mfy = {}\n",
    "for ismp in range(smp_min, smp_max+1):\n",
    "    mfy[ismp] = sandy.Fy.from_endf6(sandy.Endf6.from_file(f\"pu239_fy_cea_cons_{ismp}.jeff4t3\")).get_mass_yield(zam=942390, e=0.0253)\n",
    "mfy = pd.DataFrame(mfy).rename_axis(\"SMP\", axis=1)\n",
    "\n",
    "S = sandy.Fy(nfpy.data.query(\"MT==454 and E==0.0253\")).get_mass_yield_sensitivity()\n",
    "C = pd.DataFrame(acov, index=ifyth.ZAP.values, columns=ifyth.ZAP.values)\n",
    "cov_mfy = sandy.CategoryCov(S @ C @ S.T)\n",
    "\n",
    "mu = nfpy.get_mass_yield(zam=942390, e=0.0253)\n",
    "sigma = cov_mfy.get_std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "261f5b3a-645b-4966-a06b-2d97862e1bf9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-02-24T13:57:03.030463Z",
     "iopub.status.busy": "2026-02-24T13:57:03.030244Z",
     "iopub.status.idle": "2026-02-24T13:57:03.355744Z",
     "shell.execute_reply": "2026-02-24T13:57:03.354842Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 2, figsize=(10, 5), sharex=True)\n",
    "\n",
    "ax = axs[0]\n",
    "ax.errorbar(x=mfy.index, y=mfy.T.mean(), yerr=mfy.T.std(), marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"blue\", color=\"dodgerblue\", label=\"sample estimate\")\n",
    "ax.errorbar(x=mu.index, y=mu.values, yerr=sigma.values, marker=\"s\", ms=4, linestyle=\"none\", capsize=2, ecolor=\"k\", color=\"k\", alpha=.4, label=\"original data\")\n",
    "ax.set(ylabel=\"mass yields\", xlabel=\"A\")\n",
    "\n",
    "ax = axs[1]\n",
    "diff_mean = (mfy.T.mean() / mu  - 1) * 100\n",
    "diff_std = (mfy.T.std() / sigma - 1) * 100\n",
    "ax.errorbar(x=diff_mean.index, y=diff_mean.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"dodgerblue\", label=\"$\\\\frac{m- \\\\mu}{\\\\mu} \\\\times 100$\")\n",
    "ax.errorbar(x=diff_std.index, y=diff_std.values, marker=\"s\", ms=4, linestyle=\"none\", color=\"tomato\", label=\"$\\\\frac{s- \\\\sigma}{\\\\sigma} \\\\times 100$\")\n",
    "ax.set(ylim=[-100, 100], ylabel=\"relative difference / $\\\\%$\", xlabel=\"A\")\n",
    "ax.legend()\n",
    "fig.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sandy-devel",
   "language": "python",
   "name": "sandy-devel"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}