{
 "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": "2024-09-27T09:43:54.485588Z",
     "iopub.status.busy": "2024-09-27T09:43:54.485407Z",
     "iopub.status.idle": "2024-09-27T09:43:55.306815Z",
     "shell.execute_reply": "2024-09-27T09:43:55.306136Z"
    }
   },
   "outputs": [],
   "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": "2024-09-27T09:43:55.308998Z",
     "iopub.status.busy": "2024-09-27T09:43:55.308757Z",
     "iopub.status.idle": "2024-09-27T09:43:55.384240Z",
     "shell.execute_reply": "2024-09-27T09:43:55.383684Z"
    }
   },
   "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": "2024-09-27T09:43:55.386080Z",
     "iopub.status.busy": "2024-09-27T09:43:55.385908Z",
     "iopub.status.idle": "2024-09-27T09:43:55.581763Z",
     "shell.execute_reply": "2024-09-27T09:43:55.581245Z"
    }
   },
   "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": "2024-09-27T09:43:55.583936Z",
     "iopub.status.busy": "2024-09-27T09:43:55.583589Z",
     "iopub.status.idle": "2024-09-27T09:43:57.070594Z",
     "shell.execute_reply": "2024-09-27T09:43:57.070086Z"
    }
   },
   "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": "2024-09-27T09:43:57.072474Z",
     "iopub.status.busy": "2024-09-27T09:43:57.072120Z",
     "iopub.status.idle": "2024-09-27T09:43:59.246274Z",
     "shell.execute_reply": "2024-09-27T09:43:59.245721Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:  Condition COV + 1 > 0 for Lognormal sampling is not respected\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": "2024-09-27T09:43:59.248329Z",
     "iopub.status.busy": "2024-09-27T09:43:59.247983Z",
     "iopub.status.idle": "2024-09-27T09:44:16.156644Z",
     "shell.execute_reply": "2024-09-27T09:44:16.156061Z"
    }
   },
   "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": "2024-09-27T09:44:16.158601Z",
     "iopub.status.busy": "2024-09-27T09:44:16.158406Z",
     "iopub.status.idle": "2024-09-27T09:44:24.647307Z",
     "shell.execute_reply": "2024-09-27T09:44:24.646690Z"
    }
   },
   "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": "2024-09-27T09:44:24.649579Z",
     "iopub.status.busy": "2024-09-27T09:44:24.649212Z",
     "iopub.status.idle": "2024-09-27T09:44:24.656155Z",
     "shell.execute_reply": "2024-09-27T09:44:24.655710Z"
    }
   },
   "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": "2024-09-27T09:44:24.657872Z",
     "iopub.status.busy": "2024-09-27T09:44:24.657561Z",
     "iopub.status.idle": "2024-09-27T09:45:10.815263Z",
     "shell.execute_reply": "2024-09-27T09:45:10.814646Z"
    }
   },
   "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": "2024-09-27T09:45:10.817290Z",
     "iopub.status.busy": "2024-09-27T09:45:10.817108Z",
     "iopub.status.idle": "2024-09-27T09:45:35.652912Z",
     "shell.execute_reply": "2024-09-27T09:45:35.652286Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_0.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_1.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_2.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_3.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_4.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_5.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_6.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_7.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_8.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_9.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_10.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_11.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_12.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_13.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_14.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_15.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_16.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_17.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_18.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_19.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_20.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_21.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_22.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_23.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_24.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_25.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_26.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_27.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_28.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_29.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_30.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_31.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_32.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_33.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_34.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_35.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_36.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_37.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_38.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_39.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_40.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_41.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_42.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_43.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_44.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_45.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_46.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_47.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_48.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_49.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_50.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_51.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_52.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_53.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_54.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_73.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_74.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_75.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_76.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_77.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_78.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_79.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_80.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_81.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_82.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_83.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_84.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_85.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_86.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_90.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_91.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_92.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_93.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_94.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_95.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_96.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "writing file 'pu239_fy_cea_cons_97.jeff4t3'...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "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": "2024-09-27T09:45:35.654754Z",
     "iopub.status.busy": "2024-09-27T09:45:35.654573Z",
     "iopub.status.idle": "2024-09-27T09:45:46.470485Z",
     "shell.execute_reply": "2024-09-27T09:45:46.469954Z"
    }
   },
   "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": "2024-09-27T09:45:46.473197Z",
     "iopub.status.busy": "2024-09-27T09:45:46.472989Z",
     "iopub.status.idle": "2024-09-27T09:45:46.831247Z",
     "shell.execute_reply": "2024-09-27T09:45:46.830643Z"
    }
   },
   "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": "3.11.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}