Grafy baka.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "922a07c1-9e05-44d7-9256-831b1971ace1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from tabulate import tabulate\n",
    "import matplotlib\n",
    "\n",
    "def reject_outliers(data, m=2):\n",
    "    return data[abs(data - np.mean(data)) < m * np.std(data)]"
   ]
  },
  {
   "cell_type": "raw",
   "id": "58236450-efe0-44ad-9c64-ab894d204f75",
   "metadata": {},
   "source": [
    "matplotlib.use(\"pgf\")\n",
    "matplotlib.rcParams.update({\n",
    "    \"pgf.texsystem\": \"pdflatex\",\n",
    "    'font.family': 'serif',\n",
    "    'text.usetex': True,\n",
    "    'pgf.rcfonts': False,\n",
    "})\n",
    "\n",
    "\n",
    "#Direct input \n",
    "plt.rcParams['text.latex.preamble']=[r\"\\usepackage{lmodern}\"]\n",
    "#Options\n",
    "params = {'text.usetex' : True,\n",
    "          'font.size' : 11,\n",
    "          'font.family' : 'lmodern',\n",
    "          'text.latex.unicode': True,\n",
    "          }\n",
    "plt.rcParams.update(params) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "b73fa393-aad9-4e31-acff-c5005b0cbbdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['text.latex.preamble']=r\"\\usepackage{mlmodern}\"\n",
    "plt.rcParams[\"text.usetex\"] = True\n",
    "plt.rcParams[\"font.size\"] = 11\n",
    "plt.rcParams[\"font.family\"] = 'mlmodern'\n",
    "#plt.rcParams[\"mathtext.fontset\"] = \"cm\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "27c7d60e-e4d7-46ab-acfd-49e8db25af36",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "$\\left|01\\right\\rangle$\n"
     ]
    }
   ],
   "source": [
    "def ket(s):\n",
    "    return r\"$\\left|{}\\right\\rangle$\".format(s)\n",
    "\n",
    "print(ket(\"01\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "88e7d723-a35c-4c71-abe4-c1cbc64f6388",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 415x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def addlabels(x,y):\n",
    "    for i in range(len(x)):\n",
    "        plt.text(i, y[i]+10, r\"${}$\".format(str(y[i])), ha = 'center')\n",
    "\n",
    "plt.figure(figsize = (4.15,2.5))\n",
    "\n",
    "x = np.array([ket(\"00\"), ket(\"01\"), ket(\"10\"), ket(\"11\")])\n",
    "y = np.array([500, 0, 0, 500])\n",
    "\n",
    "plt.bar(x,y, color = \"dimgrey\", edgecolor = \"black\")\n",
    "addlabels(x, y)\n",
    "\n",
    "plt.ylim(0, 600)\n",
    "\n",
    "plt.ylabel(\"Počet výstřelů\")\n",
    "plt.xlabel(\"Stav\")\n",
    "\n",
    "plt.savefig('measurement_plot.pdf', bbox_inches = \"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee657546-8f49-4f2d-ac66-5156013c247c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "9a450275-859a-4f8a-a563-786724806de1",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_raw = np.loadtxt(\"./data/test_aer_simulator_cobyla.csv\", delimiter=\",\")\n",
    "data = reject_outliers(data_raw.T[0])\n",
    "#print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "20bf1fa0-6cf7-4352-84bb-000ba577a658",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 415x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_raw = np.loadtxt(\"./data/test_aer_simulator_cobyla.csv\", delimiter=\",\")\n",
    "#data_raw = np.loadtxt(\"./data/omega562_aer_simulator_cobyla.csv\", delimiter=\",\")\n",
    "#data = reject_outliers(data.T[0])\n",
    "data = data_raw.T[0]\n",
    "\n",
    "plt.figure(figsize = (4.15,2.5))\n",
    "\n",
    "counts, bins = np.histogram(data, bins=20, range=(480,520))\n",
    "plt.hist(bins[:-1], bins, weights=counts, color = \"dimgrey\", edgecolor = \"black\")\n",
    "\n",
    "plt.xticks(np.arange(479,522,1), minor = True)\n",
    "plt.yticks(np.arange(0,120,5), minor = True)\n",
    "\n",
    "plt.xlim(479,521)\n",
    "\n",
    "#plt.xlim(400, 600)\n",
    "\n",
    "plt.ylabel(\"Počet\", labelpad=.1)\n",
    "plt.xlabel(\"Vazebná energie [MeV]\", labelpad=.2)\n",
    "\n",
    "plt.savefig('Aer_cobyla_1000.pdf', bbox_inches = \"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "5ceff290-bfa4-47cc-9f8d-e926bb7f73d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 415x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_raw = np.loadtxt(\"./data/omega562_fake_sherbrooke_cobyla.csv\", delimiter=\",\")\n",
    "#data = reject_outliers(data.T[0])\n",
    "data = data_raw.T[0] - 5\n",
    "\n",
    "plt.figure(figsize = (4.15,2.5))\n",
    "\n",
    "counts, bins = np.histogram(data, bins=20, range=(550,630) )\n",
    "\n",
    "plt.xticks(np.arange(545,640,2.5), minor = True)\n",
    "plt.yticks(np.arange(0,10,.5), minor = True)\n",
    "\n",
    "plt.xlim(545,635)\n",
    "\n",
    "plt.hist(bins[:-1], bins, weights=counts, color = \"dimgrey\", edgecolor = \"black\")\n",
    "\n",
    "#plt.xlim(400, 600)\n",
    "\n",
    "plt.ylabel(\"Počet\", labelpad=3)\n",
    "plt.xlabel(\"Vazebná energie [MeV]\", labelpad=.2)\n",
    "\n",
    "plt.savefig('Sherbrooke_cobyla_100.pdf', bbox_inches = \"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "6dae43a2-364d-42c3-bb45-8306f8069786",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "598.2217533507827\n",
      "26.353287347756964\n",
      "2.006119048842524\n"
     ]
    }
   ],
   "source": [
    "m=0.5\n",
    "\n",
    "print( np.mean(reject_outliers(data_raw.T[0], m)) )\n",
    "print( np.std(reject_outliers(data_raw.T[0], m)) )\n",
    "print( np.sqrt(np.sum(data_raw.T[1]**2))/100 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d976701-0188-4c39-ba4d-ac3ce655911c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8dca8631-0b84-4b19-8f56-d962ca66e0b5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "0086bf80-baf0-4ed4-bf7f-ef13db446407",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lWq32vba1tTXwdSIiWpxQJhZd1xGPx2GaJhKJxMBtHMfpuyeMJEkTT+QTEZFYoRsK03XdTxiKoqBQKKBYLPbd5+XNmzcT77vT6aDT6fjPeVMyIiLxQnfG0n3jMACQZRmVSqVvu+3t7b6zk1FnK4VCAZubm/5jZ2dn1nCJiOiaUCWWcrmMaDQ61nDWoJVfzWYzcEVYPp/HxcWF/zg/P58lXCIiGiBUiUVRFGia5g+FOY4Dy7L8eRbTNFEulwH8uCS5e4Lfsiyk0+mh+19fX8fGxkbPg4iIxApVYpFlGbIsI5fLwTRNJJNJaJrmz6/ouo5CoeBvXyqVcHBwAMuycHh4CFmWe5YfExHR4oVy8t6yLFSrVei63jO0dX2uRdM0qKqK4+NjKIoSeDElEREtRugSC3A1JDbu1fOSJPWtGCMiouUJ1VDYorAIJRHR/KxkYmERSiKi+VnJxEJERPPDxEJEREIxsRARkVBMLEREJFQolxuvkrOzMzQajanaPn/+XHA0NK1p/xai/oaz7Ofu3bu4f/++kDiIgBVNLEdHRzg6OsLbt2+XGsfZ2RkePnyIy8vLpcZB0/vhhx+wtraGTz755MYe/86dO3jx4gWTCwmzkoklk8kgk8mg3W5jc3NzaXE0Gg1cXl5ib28PkUhk4vavX7/mkukl63Q6cF13aX/DWY/farVwcnKCRqPBxELCrGRiCZtIJIJ79+5N3K7Vas0hGprGsv+G0x6faB44eU9EREIxsRARkVBMLEREJNRKJhYWoSQimp+VTCwsQklEND8rmViIiGh+mFiIiEgoJhYiIhKKiYWIiITilfczYhFJIqJeoU0sjuNAkqS57FtUEUoWkSQi6he6xGKaJnRdhyzLOD4+Rj6fRzabHbhtOp3G8fEx4vE4ms0mHMdBvV4feQxRRShZRJKIqF+oEovjONB1HZVKBQCQy+UQjUYhyzI0TRvYRlVVAEAikRiagOZt2QUIiYjCJFSJxTRNmKYJ27Yhy7L/MAxjaGIplUoLjpKIiIKEalWYqqrIZrOQZdl/rdlsBs612LaNYrEIy7IWECEREY0SqsQiSRJ0XfefW5YFx3GQz+eHttF1HfF4HKZpIpFIBO6/0+mg3W73PIiISKxQJZbrkskkdF2HoigD39d1HYZhQFEUZLNZVKtVFIvFofsrFArY3Nz0Hzs7O/MKnYhoZYU2sSSTSWiaFjgh32w2e57LsuxP/A+Sz+dxcXHhP87Pz4XFS0REV0KZWHK5HHZ3d/1hsUFnIeVyGdFoFI7jjL3f9fV1bGxs9DyIiEis0CWWw8ND2LYNVVVhWRZM00StVgNwtWqsXC4DABRFgaZp/sS+4ziwLGvkPAsREc1X6JYb53I5APATCAD/zEXXdTSbTWia5i9FzuVySCQS0HUdmqYhlUotJXYiIroSqsSiqurAK+e95cfX5090XYdlWahWq4GT/EREtDihSiwAeq5hGYeiKEwoRDOapSDq3bt3cf/+fYHRLNYshWSB2T//rMcXEYNooUssiyCqCCXRTffDDz9gbW0Nn3zyydT7uHPnDl68eBGqH7ZxiSgkO8vnF1XINmx/g5VMLKKKUBLddJ1OB67rTl1ItdVq4eTkBI1GIzQ/apOYtZDsrJ9/1uOLiGEeVjKxEFGvaQup3hbL/vzLPr5ooVtuTERENxsTCxERCcXEQkREQjGxEBGRUCuZWI6OjvDBBx9gd3d32aEQEd06K5lYMpkMvvvuO95vnohoDlYysRAR0fwwsRARkVBMLEREJBSvvCeimc1SxLLT6WB9fX0p7WeJm4ZbycTCIpREYogoYrm2tgbXdZfWnsRbycTCIpREYsxaxPL169c4PT1densSayUTCxGJNW0RxVarFYr2JBYn74mISCgmFiIiEoqJhYiIhGJiISIioUKbWBzHmcu2AItQEhHNU+gSi23biMViKBQKSCQSKBaLQrbtxiKURETzE7rlxolEAoZhQFVVAFfLCOPxOBRFmWlbIiJajFCdsViWBdu2/UQBAKqqwjCMmbYlIqLFCVViqVarfa9tbW0NfH2SbYmIaHFCNRTmOA4kSep5TZKkgZPzk2zr6XQ66HQ6/vOLiwsAwF//+lf85Cc/mTjev//97wCAf/7zn/jvf/87cXvvql+2n659GGJg+9Vu7/3e1Go1/Pvf/564/ay/ISJi+M9//gMAYuutuSGSzWZdSZL6XpNleaZtPZ999pkLgA8++OCDj2uPer0u5ofcdd1QnbFsb2/3nXEMOwOZZFtPPp/H7373u57tf/7zn+Ps7CywGOXu7u7IFWTjbCNqX+12Gzs7Ozg/P8fGxsZcjzXuNuNsx7gZ9zjbhTHucba5qXFfXFzg/v372NraCtxuEqFKLINWczWbzYGvT7KtZ319feB9GzY3NwO/CO+++27g++NuI3pfGxsbC4lb5GcDGDfjvnlxjxszcHPjfucdcVPuoZq891Z4WZblv2ZZFtLpNADANE2Uy+WxthUpk8kI2Ub0vhZ1LJGfTdR+GDfjXmTcomIWebxFxz0RYYNqgpRKJVdRFLdWq7m6rruqqvrvqarqKooy1rbjuLi4cAG4FxcXwuJfBMa9WIx7sRj3Ys0j7lCdsQCApmk4OTlBtVqFoiioVCr+e5VKBbVabaxtx7G+vo7PPvtsptuiLgPjXizGvViMe7HmEfea6/KenkREJE7ozliIiOhmY2IhIiKhVj6xDLv2ZdJS/IsW9vi6da/cGyaMn2ecuMMsqE/D2N+eMMc2DPu6161NLOl0GpFIBIlEArFYDNFotOf9YrGIRCLhl9y3bRvA9KX4lx33qHbLjDsWiyESiSAajfY8vEKiYe3voLjD3N+2bSOZTKJQKCCZTCKXy/W8F9b+Dop7mf0ddGzLsob2Z5j7OihuEX0dqgskRfOudUkkEshms/7rpmnCMAx/hVkkEkG5XEY2mw1FKf5p4g5qtyiDjm/bNhRFwf7+vr9dvV73X49Go6Hs71FxD2u3SMOOn06ne1ZIJpNJmKYJVVVD/f0Oijuo3SIMOrbjONjb20OpVIKqqnAcBw8ePICqqpBlObR9PSruYe0mImzhcsikUqmh70mS5JZKJf+5VyOnVqu517tE07TAfYk2Tdyj2i3CsONXKpWemF33qk9brVao+zso7qB2ixJ0fAB+nK7rurquu4ZhhLq/XXd43KPazduwY5dKpb7+VFXVzWazoe7roLiD2k3iVp+x2LYN0zR7/pdgmiYcx4Esyzg8PIQkSUilUgDCU4p/0riD2i077u775QDA4eEh9vf3IUlSqPs7KO6gdos07PiyLCMWi8EwDGxtbeHp06c4OTnB8fFx3z7C0t/A8LhHtVtWzN4wdDdJkmCa5sDho7D0dVDcQe0mcWvnWABA13XE43GYpolEIgHgxwnZQqEATdMgyzKi0Sgcx5mqFH8Y4g5qt+y4uzmOg6dPn0LTNP95WPu72/W4x203b8OO7w0nJRIJf8jD69cw9/ewuEe1W1bM3g9ud//Zth3635KguIPaTWTmc56Q6j6ldt2rYSTDMNxsNusCcGu1mv+eoihuKpWaqhS/aNPEHdRuUcY5fjabdXVd73ke1v6+HlN33OO2m6eg41cqFVfTNP87I8uy22q1Qt/fw+Ie1W7ego6tKIr/3fCGv2RZDn1fD4t7VLtx3dozlmaz2fNclmVUKhX/FPX6KbhpmlOV4hdtmriD2i3KOMcvFos9Q0xh7u9u1+Met908DTu+bdtIp9MolUrQdd1f6HFwcBDq/g6KO6jdMmMGrm6uVa/XkU6n/YUGsiyHuq+B4XGPajeuW5lYyuVy3zCRx+u86+9JkjRVKX6Rpo07qN0ijHN8y7L6hgfC3N+eQXGHub/L5XLPkJ2iKDAMA5Zlhbq/g+JeZn+Pc2zDMGAYBrLZLGzbRiKRCHVfewbFLayvpzvJCrd6ve5qmuY/b7VaLgD/dE6SJLdSqfjve6euruv2DTfJstyzbRjjHtVu2XG7rusahtG36sd1w93frjs47jD3d6lU6qvyXalU/CHTsPZ3UNzL7O+gY7daLVeSJL8/a7WaK0mS/10Ja18HxS2qr29lYnHdq/HMbDbrVioVV1XVns6qVCr+HzmbzQotxb+suIPaLTtu171aOjro/zFh7m/XHR53mPs7lUq5qVTKrVQqrmEYrqqq/o9dmPs7KO5l9nfQsWVZ9hPj9cQR5r4OiltEX9/q6saWZaFarQ5cMuc4Do6PjyHLct/4edB7izBt3EHtFmFU3KZp9q2s8t4Lc38PizvM/R20XDTM/R0U9zL7e9ixve9Hs9nExx9/3LcSLKx9PSruWfv6VicWIiJavFs5eU9ERMtzq6+8J6LJ2baNcrk8sLrDopTLZdi2DVVVlzLMSLNhYqG56K6W6jhOTyE7x3FQLBb9cV3RP17lchmnp6eIRqNC9u1dK7SMMfJlME0Tp6en2N/fh2VZPZ9/2I98sVj0l6gOK1o4yXdClmXU63UAg5elU7hxKIzmIh6Po1QqIZ1O900MAleVgnVdx9bWlvBjexeOiriAzrKspZRrmUU6nZ455kQi4ZcOkmUZuVzOv1jxOtM0/crEQUlgku+EV4mZbiYmFpoL7wK3QSRJQjQaRalUGrjaSsSx4/H4zPtxHAcHBweoVCo36mwlFosJ+1GWJAmapkFRFFiWNfDmZ5VKBbIsQ1GUwH5a5neCFouJhebG+7EZ9GMy6n+3YeHds+ImSaVSwu9X4i07vf63dBwH29vbY+/nNnwnaDTOsdBcpdNppNNp2Lbtl6W5XjHVG7ZyHAfRaNT/UbQsC4VCAQD8ITNJkqDrOoCrSWbv38BVRdbuIRbHcXB4eIh6vQ5JkpDP5yFJEorFIkqlEhRFwe7urj9k1t1+WEzDDItlnGMNa3t4eIhKpeL31enpKb788ku/Sq53h8VYLIZarYZqtYpf//rX+POf/wxFUcbup3Gl02nkcrmepHB8fAxN0wYmimHHHec7QTfczJd3EgXwSkJ4JXNc9+oK6+4SKd1lMBRF8bf1qjp7+5Ekya/I6j33rhi+XhIklUq5kiT5N0PzqhZ4x9E0refGaalUqucK42ExDfuMQbEEHSuobavVclVV9UuDKIribyfLsr8/r1KtV6IjlUr17CMotkEMw+gr4eH9zQD03ADNKxXTXRZpnM816jvhtbleVZpuBg6F0Vx5Y/TdK4KazWbP/5hlWfYrqu7v7/urkBzHQTqdBnBV5VaWZf/Mwdtf921rTdPsuYlRPB7vudWqdwbhHXNra8sfz4/FYj1th8U0yKhYgo4V1FaSJH/oSFEU1Go1qKoK27Z7bpEcj8d7hpG6bzI1Tj+Ny/tbemcn3n3TJ+2Tcb4TdLNxKIzmLp1Oo1wu+z8s3feRB67mMbxhne4fvO4kYpomXr586b93enoKAH47AH2Tvtd/qLzy395+vaTj6a7oOiymQcaJZdixpmkryzIkSfKHkqrVal+fThLbJLwVZ97Nz7qHuiY57qjvBN1sTCw0d97ZgmEYcBynZxmwN7Zeq9WgKAoODw/x9OlT/4e32Wz69+mQJAm5XA66rmN3dxeWZQ39YRtk0F39BhkV0/V9TBPLrG0//vhjlEollEol7O/vD50DmiW2Qby/pTf3Ncyo4wZ9J+jm41AYLUQqlUK5XO5b9eNNbHuv1+t1v0BetVpFIpFAKpXy/7frDUlpmuYPCXlyuVzP8+tnGtVq1R9aCzIqpuvGiWWYadtWq1V/Iv16Unnz5o2Q2DyO4/Tc/CmVSuHw8LDvLKP7jG+c4w77TtAtsOxJHloN9XrdBeBPpnsqlYoLwNV13dV13b+lq6Zp7m9/+9ue91RV7bm1q1fy25vk757o9Uqwp1Ipf+LYe99rJ0mSXx5cURQXgF+2fVhM1yeYR8Uy6lhBbQ3DcCVJciVJ8rf1aJrmAvAfXunz7uN5E/BB/TRI9+R9d7zegoN6ve7fsqFer7upVKrnlrzj/H2CvhPd7Tl5fzOxujEtjHcL1EEsy/LnDrr/53v9NqlbW1sDS3wPKg3v7cubi/Dajbo7nrfdoJhGDaVdj2XcY41q22w2/bkWbwm1N4nunU0dHBz0zEON2v8w3qS6Vw7Htm1sbW31xNDNe3/QMUcdN+g74dULE31NDs0fEwvRDZNOpxGLxXrqoDmOgwcPHqDVas28/+uJZVmYWG4uTt4T3TC6ruPg4AC1Wg2xWMxfoVUqlZYdGhEAnrEQ3Wjdw3WilMtl5HI5f3n2MiSTSViWhVwut/QzJ5ocEwsREQnF5cZERCQUEwsREQnFxEJEREIxsRARkVBMLEREJBQTCxERCcXEQkREQjGxEBGRUEwsREQk1P8D33XF65FqRDsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 415x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_raw = np.loadtxt(\"./data/omega562_fake_sherbrooke_cobyla_10k shots.csv\", delimiter=\",\")\n",
    "#data = reject_outliers(data.T[0])\n",
    "data = data_raw.T[0] - 5\n",
    "\n",
    "plt.figure(figsize = (4.15,2.5))\n",
    "\n",
    "counts, bins = np.histogram(data, bins=20, range=(560,595) )\n",
    "\n",
    "plt.xticks(np.arange(560,600,1), minor = True)\n",
    "plt.yticks(np.arange(0,14,.5), minor = True)\n",
    "\n",
    "#plt.xlim(545,635)\n",
    "\n",
    "plt.hist(bins[:-1], bins, weights=counts, color = \"dimgrey\", edgecolor = \"black\")\n",
    "\n",
    "plt.xlim(560, 595)\n",
    "\n",
    "plt.ylabel(\"Počet\", labelpad=3)\n",
    "plt.xlabel(\"Vazebná energie [MeV]\", labelpad=.2)\n",
    "\n",
    "plt.savefig('Sherbrooke_cobyla_100.pdf', bbox_inches = \"tight\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "59d0f24d-59db-440c-bf14-87de8de3d80e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "578.3951888965807\n",
      "6.592521377109258\n",
      "0.5631865400546625\n"
     ]
    }
   ],
   "source": [
    "m=0.5\n",
    "\n",
    "print( np.mean(reject_outliers(data_raw.T[0], m)) )\n",
    "print( np.std(reject_outliers(data_raw.T[0], m)) )\n",
    "print( np.sqrt(np.sum(data_raw.T[1]**2))/100 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f7cc8c3-2a04-48dd-86df-cf857eefcfd0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26573547-0c9d-4a5a-9afb-b1e9e52c9c10",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "751923fe-208a-4950-95d3-2d6bfb02b7cf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe926da2-8b65-4a28-991d-93c03724dbde",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "70cffb8c-99f7-4e44-93c2-ff20a721f0a8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95f12436-c783-4a18-8714-06c8d16734b4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "d7417fd9-ed90-4986-88ed-724a59c2a9a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_raw = np.loadtxt(\"./data/conv_plot_run_1_Nelder-Mead.csv\", delimiter=\",\")\n",
    "#data = reject_outliers(data_raw.T[0])\n",
    "#print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "id": "53d75cb2-6861-47d3-b7ca-a66ef135e1d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "552.6250504318151 +- 8.583499460143287\n"
     ]
    }
   ],
   "source": [
    "minimum = min(data_raw.T[0])\n",
    "err = data_raw.T[1][np.where(data_raw.T[0] == minimum)][0]\n",
    "print(\"{} +- {}\".format(minimum,err))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "4fdeeb54-7b14-4e7b-9b59-e4dfa271ba96",
   "metadata": {},
   "outputs": [],
   "source": [
    "energy = data_raw.T[0]\n",
    "iters = np.arange(len(energy))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "e74d76d5-b9bb-42c0-ad7b-f7fe572f27ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8,5))\n",
    "\n",
    "plt.plot(iters[::],energy[::],color = 'k',marker = '', linestyle = \"dashed\", linewidth = 1)\n",
    "#plt.plot(x_range,func(x_range,I0,shift,K), color = 'k', linestyle = 'dashed', label = r\"Proložení křivkou: $I = I_0 \\cdot (\\cos(\\varphi + \\Theta))^2 + K$\")\n",
    "\n",
    "#plt.legend(loc='upper left', fontsize=10)\n",
    "\n",
    "#handles, labels = plt.gca().get_legend_handles_labels()\n",
    "#order = [1,0]\n",
    "#plt.legend([handles[idx] for idx in order],[labels[idx] for idx in order], loc='upper left', fontsize=11)\n",
    "\n",
    "plt.yticks(np.arange(525,1350,25), minor = True)\n",
    "#plt.xticks(np.arange(0,46,5))\n",
    "plt.xticks(np.arange(0,110,5), minor=True)\n",
    "\n",
    "plt.xlim(0,100)\n",
    "\n",
    "plt.ylabel(\"Vazebná energie \" + \"[MeV]\")\n",
    "plt.xlabel(\"Počet evaluací cost funkce [-]\")\n",
    "\n",
    "plt.savefig('convergence.pdf', bbox_inches = 'tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8f4983e-b450-4de6-9a10-f2b2b1a06be0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "id": "d2cce762-4b29-4f53-ab2a-dcfde5218fc6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_raw = np.loadtxt(\"./data/conv_plot_cobyla_run_1_cobyla.csv\", delimiter=\",\")\n",
    "#data = reject_outliers(data_raw.T[0])\n",
    "#print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "a1e7613f-4754-4649-b679-6748d043389e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "562.6297999302496 +- 5.352725227742764\n"
     ]
    }
   ],
   "source": [
    "minimum = min(data_raw.T[0])\n",
    "err = data_raw.T[1][np.where(data_raw.T[0] == minimum)][0]\n",
    "print(\"{} +- {}\".format(minimum,err))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "72af1679-cb25-48d6-8400-fd5648a6d13f",
   "metadata": {},
   "outputs": [],
   "source": [
    "energy = data_raw.T[0]\n",
    "iters = np.arange(len(energy))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "b010a94c-87c2-476b-be68-7c5c2cf86964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (8,5))\n",
    "\n",
    "plt.plot(iters[::],energy[::],color = 'k',marker = '', linestyle = \"dashed\", linewidth = 1)\n",
    "#plt.plot(x_range,func(x_range,I0,shift,K), color = 'k', linestyle = 'dashed', label = r\"Proložení křivkou: $I = I_0 \\cdot (\\cos(\\varphi + \\Theta))^2 + K$\")\n",
    "\n",
    "#plt.legend(loc='upper left', fontsize=10)\n",
    "\n",
    "#handles, labels = plt.gca().get_legend_handles_labels()\n",
    "#order = [1,0]\n",
    "#plt.legend([handles[idx] for idx in order],[labels[idx] for idx in order], loc='upper left', fontsize=11)\n",
    "\n",
    "plt.yticks(np.arange(500,2100,50), minor = True)\n",
    "#plt.xticks(np.arange(0,46,5))\n",
    "plt.xticks(np.arange(0,37,1), minor=True)\n",
    "\n",
    "plt.xlim(0,36)\n",
    "\n",
    "plt.ylabel(\"Vazebná energie \" + \"[MeV]\")\n",
    "plt.xlabel(\"Počet evaluací cost funkce [-]\")\n",
    "\n",
    "plt.savefig('convergence2.pdf', bbox_inches = 'tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59b6c134-6de7-4c15-a65f-ca6df0a18ae6",
   "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": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}