{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "782a9046",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T21:43:14.399679Z",
     "start_time": "2023-03-01T21:43:14.295272Z"
    }
   },
   "outputs": [],
   "source": [
    "import h5py    \n",
    "import numpy as np    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dbc80769",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T21:45:56.061690Z",
     "start_time": "2023-03-01T21:45:56.059736Z"
    }
   },
   "outputs": [],
   "source": [
    "fn_cms = \"/hhh-vol/data/cms/v12/hhh_testing.h5\"\n",
    "fn_delphes = \"/hhh-vol/data/delphes/v2/hhh_testing.h5\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "59f480e0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T21:46:17.122579Z",
     "start_time": "2023-03-01T21:45:56.399709Z"
    }
   },
   "outputs": [],
   "source": [
    "f1 = h5py.File(fn_cms, 'r+')   \n",
    "f2 = h5py.File(fn_delphes, 'r+')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "10b7bfbe",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T21:51:12.627915Z",
     "start_time": "2023-03-01T21:51:12.478212Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "551124be",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T21:54:26.269403Z",
     "start_time": "2023-03-01T21:54:25.296704Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.5569e+04, 1.1444e+04, 7.4270e+03, 4.4000e+03, 2.2700e+03,\n",
       "        1.4960e+03, 1.4900e+02, 5.9000e+01, 1.1000e+01, 4.0000e+00]),\n",
       " array([-1. ,  0.2,  1.4,  2.6,  3.8,  5. ,  6.2,  7.4,  8.6,  9.8, 11. ]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(1,2, figsize=(10,5))\n",
    "ax1.hist(f1[\"TARGETS/h2/b1\"])\n",
    "ax2.hist(f2[\"TARGETS/h2/b1\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "591a5fc6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-03-01T21:56:38.742103Z",
     "start_time": "2023-03-01T21:56:38.736114Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-1\n",
      "-1\n"
     ]
    }
   ],
   "source": [
    "print(np.min(f1[\"TARGETS/h3/b1\"]))\n",
    "print(np.min(f2[\"TARGETS/h3/b1\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c04b614a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}