Lugovtsov/vaki-autoelectron-emission/plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3e9c91d2-a8a3-4cf4-a3bd-682f4979776a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# %load /home/glebi/git/experiment-automation/processing_tools.py\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "import scienceplots\n",
    "\n",
    "plt.style.use(['science', 'russian-font'])\n",
    "plt.style.use([\"bright\"])\n",
    "\n",
    "matplotlib.rcParams.update({\n",
    "    'figure.figsize': [6, 4],\n",
    "    'savefig.facecolor': 'white',\n",
    "    'figure.dpi': 200.0,\n",
    "    'font.size': 12.0,\n",
    "})\n",
    "\n",
    "def line_func(x, arg1, arg2):\n",
    "    return x * arg1 + arg2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5e765906-9269-4ba2-81ba-fb2fd3d798f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABBgAAALUCAYAAAChG4GcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAB7CAAAewgFu0HU+AACgt0lEQVR4nOzdeXxU933v//doJCTAoGEx9mAMaISxxzYxjASxE8iCNLazqYmRRNqo7W1rNHGSLr8mlqy0KeIuxSK5t8tNG0a4y2112yCJODdJkxiNcBLIBpoBm8RyMBoWY8bGRgyyMRLSzPn9QTWRjJaRdKSjGb2ej4cfj5M53+/5fkQM5rznu9gMwzAEAAAAAAAwARlWFwAAAAAAAFIfAQMAAAAAAJgwAgYAAAAAADBhBAwAAAAAAGDCCBgAAAAAAMCEETAAAAAAAIAJI2AAAAAAAAATRsAAAAAAAAAmjIABAAAAAABMGAEDAAAAAACYsEyrC5hMZWVlWr9+vaqqqsbULxqNqr6+Xnv37lU0GpXD4ZAk1dTUqLS0dMS+zc3N8vv9gz7zer1jrgEAAAAAgFSSVgFDNBpVOBzW3r17VV9fr2g0KpfLNaZn1NfXq7q6WpWVlWptbU2EC9FoVNu2bVNnZ6cqKyuH7Ov1etXZ2ammpqbEuP398vPz1dLSMuZ6AAAAAABIBWmzRMJmsykvL0/V1dXKz88f14v8rl275PP51NTUpLq6ukS4IEmBQECBQEDV1dVD9i0rK1NbW5taW1sHje1wONTU1CSHwyGv1zvmmgAAAAAASAVpEzAYhqFLly6ppaVFlZWVWrhw4Zj6Nzc3q7q6WlVVVSouLr7hfktLi6LRqKLR6A33AoGAmpubVVlZOSiUGKimpkbhcHjYgAIAAAAAgFSWNgHDRPQvY5CuBwFD6V820dTUdMO9/j0XRpqh0L93Q319/UTLBQAAAABg2kmrPRjGa+fOnYpGoyotLR12BoLL5bph88Z+zc3NiTYjcTgcikajCgQCQ86SAAAAAAAgVTGDQb+eVTCePRICgUDierSAof9+KBQa8zgAAAAAAExnM34GQzgcTuyrUFhYmPisublZHR0dcjgc2rp1qzwez5D9+8OC4WY+DNS/L8SRI0fGXe8bb7yhZ555RitXrtTs2bPH/RwAAAAAAJJx9epVnT59Wg899JAWL148bLsZHzAMnIHgcDhUX1+vjo4O+Xw+uVwuhUIhbdu2TS6XS3v27LkhSLh48eKYxxxqo8hkPfPMM6qoqBh3fwAAAAAAxqOhoUGf+tSnhr0/4wOGjo6OxHUoFFJHR4fq6uoSn3k8HrW2tiovL095eXk6derUoJBhLGFBf7/Ozs5x17ty5UpJ0n/7b/9NeXl5Q7ZZvHixbr755lGf1d7eroqKCjU0NMjtdo+7pskwXWubrnVJ1DZe07W26VqXRG3jMV3rkqhtvKZrbdO1LonaxmO61iVR23hN19qma10StY3XeGp7/fXX9cYbbwx579SpU/rSl76UeB8dzowPGAYGBH6/Xy0tLTe0cTgcqqurk8/nU3V19aDNHscTFkxkBkP/sogvfelLw7bZvn27amtrk36m2+0edgmI1aZrbdO1Lonaxmu61jZd65KobTyma10StY3XdK1tutYlUdt4TNe6JGobr+la23StS6K28RpLbbW1tdqxY8eIbUZbpj/jA4aBRvqF7z/1ob6+Xj6fL9G2f1+FqTZSEuV0Oqe4GgAAAABAKvP5fCopKRnyXv+MiNHM+IBh4HKHkU6RGHhChN/vT8xiSGZzx8lgRkrmdDq1ffv2aRlITOfapqvp/GtGbWM3Xeua7qbrr9t0rUuitnQznX/NqG3spmtd0910/nWbrrVN17qk6V3bdDaeXzen0znxX2cjTRUXFxuSjKqqqhHb1dXVGZIMSUZHR8eIbR0OhyHJ8Hg8N/R3OBxJ1zSw/1gFg0FDkhEMBsf9DIwfv/4Avw8Aw+D3AcDvAWBm/T5I9mfNmFg8kfoGzkwYTf9yiIF7KPTPYEhmX4X+/RrGMiYAAAAAAKlgxgcMA5cZjBYS9AcEA5dFDAwLRuvff5+AAQAAAACQbmZ8wOByuRKBQTgcTrpPv8LCwsT1aCdK9D9/pL0eML2xBgzg9wEg8fsA4PcAwO+Docz4gEGSysvLJY0cMESj0cQMhK1btyY+dzgciVkQo/Xvb99/IgVSj9PpVG1tLX+IYEbj9wHA7wOA3wMAvw+GQsAgqbq6WpK0d+/eYdsEAgFJ15dUlJaWDrpXU1MjSWpqahq2f2NjoySpsrJyQrUCAAAAADAdpX3AkMzmiy6XS1VVVQqFQmpubh6yTX8IMVSIUFpaqtLSUtXX1w87i6Gurk4Oh0N1dXXJFw8AAAAAQIpIy4AhFAqpra1N0vWZB8nsrVBXV6fKykqVlZWpvr4+8Xk4HE7smRAMBofdoHHPnj0qLi6W1+sdNF40Gh3UHwAAAACAdJRpdQFm8Xq9amtru2HGQjgcVn5+vqTr+x+Ul5fL7/cP+Qy/36+ysjLV1dUlZiwsXLhQpaWlamlpGXF8h8OhlpYWNTc3y+fzDTq+0uv1qqqqamI/IAAAAAAA01jaBAyjBQDJKi4untAmjP3LJQAAAAAAmEnScokEAAAAAACYWgQMAAAAAABgwggYAAAAAADAhBEwAAAAAACACUubTR5nmvb29sS10+mU0+m0sBoAAAAAQDqJRCKKRCKSBr9/joSAIUVVVFQkrrdv367a2lrrigEAAAAApBW/368dO3aMqQ8BQ4pqaGiQ2+2WJGYvAAAAAABM5fP5VFJSIun6DIaBX3IPh4AhRbndbnk8HqvLAAAAAACMUzxuqKcvpuxMuzIybFaXM8h4luITMAAAAAAAMIU6zke179AJHTx+Tt29MeVk2bVpzTJt2bha+UsdVpc3bgQMAAAAAABMkQPHzmpX42HF4kbis+7emFpCZ3Tg2FlVlW/Q5rXLLaxw/DimEgAAAACAKdBxPnpDuDBQLG5oV+NhdZyPTm1hJiFgAAAAAABgCuw7dGLYcKFfLG5o36ETU1SRuQgYAAAAAACYZPG4oYPHzyXV9uDxc4qPEkRMRwQMAAAAAABMsp6+mLp7Y0m17e6NqacvubbTCQEDAAAAAACTLDvTrpwse1Jtc7Lsys5Mru10QsAAAAAAAMAky8iwadOaZUm13bRmmTIybJNckfkIGAAAAAAAmAJbNq6WfZTgwJ5h05aNq6eoInMRMAAAAAAAMAXylzr0uZJ1w963Z9hUVb5B+UsdU1eUiTKtLgAAAAAAgJli0fzZysmy6373Uv2s/by6e2PKybJr05pl2rJxdcqGCxIBAwAAAAAAU+aBu5eq8Uslmj0rU/G4oZ6+mLIz7Sm558I7sUQCAAAAAIApcOmtbl3rjWn2rOvf9Wdk2DR7VmZahAsSAQMAAAAAAFOi/j+e1+frf2B1GZOGgAEAAAAAgEn25tvX9KPjL+u999xmdSmThj0YUlR7e3vi2ul0yul0WlgNAAAAAGAkrcfOKhY39GDBSqtLSUokElEkEpE0+P1zJAQMKaqioiJxvX37dtXW1lpXDAAAAABgWIZh6HuHw7rfvVQL5+VYXU5S/H6/duzYMaY+BAwpqqGhQW63W5KYvQAAAAAA09hbV3s1K8uuD63Ps7qUpPl8PpWUlEi6PoNh4JfcwyFgSFFut1sej8fqMgAAAAAAo5g3Z5b+92eLZBiG1aUkbTxL8dnkEQAAAACASfJ2T69eOHNRhmHIZkuP4yiHQ8AAAAAAAMAk+cFzL+tPdh/Qxa5uq0uZdAQMAAAAAABMku8dOaXC1bdqce5sq0uZdAQMAAAAAABMgnAkqhdf7tRHNrisLmVKEDAAAAAAADAJvnv4lBbOy9G775oZJ/8RMAAAAAAAMAmWOOao7H13KtM+M169OaYSAAAAAIBJUP7+O60uYUrNjBgFAAAAAIAp9L0jp/TG5atWlzGlCBgAAAAAADDR2Qtd+l/72nT89OtWlzKlCBgAAAAAADDR946c0vw5s/Tee26zupQpRcAAAAAAAIBJrvXF1BI6La9nhWZl2q0uZ0o
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_csv(\"VAH.csv\")\n",
    "cols = df.columns\n",
    "\n",
    "plt.plot(df[cols[0]] * 1e-3, df[cols[1]]*1e-1, marker=\".\", lw=.5, ls=\"--\")\n",
    "plt.xlabel(\"Напряжение, кВ\")\n",
    "plt.ylabel(\"Сила тока, мкА\")\n",
    "\n",
    "plt.savefig(\"hand-VAH.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d084ce30-37aa-440c-ab41-591ab094d21f",
   "metadata": {},
   "source": [
    "сопротивление нашей цепи"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5b0cd085-4398-4b10-b6cc-3147d4e616f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13991140.642303433"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1263.4 / (903e-7)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd1ec375-3bdd-4bcb-88a0-fa6dcf173ec4",
   "metadata": {},
   "source": [
    "максимальное напряжение на резисторе, который снимает ток"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cfe69bd0-e5c9-45af-826b-22e759bc6eca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.32"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1600e-7 * 52e3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a53d766-e438-4378-b7b0-db3c46578f2c",
   "metadata": {},
   "source": [
    "аналитическая функция вах"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8a4273c4-db67-40b9-b887-926d8e6866e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# def vah_func(u):\n",
    "#     return S_e * (1.537e10 / )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f5605a-6a22-49de-98a2-bc83e9d8d49b",
   "metadata": {},
   "source": [
    "обработка данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "87f15973-cb08-477e-a81d-2a81e1536105",
   "metadata": {},
   "outputs": [],
   "source": [
    "U_min = 900\n",
    "R = 26.99e3 # Ом\n",
    "\n",
    "column_names = [\"Voltage\", \"Current\"]\n",
    "\n",
    "experiment_names = [\"Первая серия измерений\", \"Вторая серия измерений\"]\n",
    "file_idxs = [[1, 2, 3], [4, 5]]\n",
    "\n",
    "dots_result = [None, None]\n",
    "ex_result = [None, None]\n",
    "\n",
    "for num, (ex_name, f_idxs) in enumerate(zip(experiment_names, file_idxs)):\n",
    "    result = pd.DataFrame(columns=column_names)\n",
    "\n",
    "    for i in f_idxs:\n",
    "        df = pd.read_csv(f\"RISING-{i}.csv\", header = None)\n",
    "        df = df.loc[lambda x : x[4] > U_min]\n",
    "\n",
    "        U = df[4] # В\n",
    "        U_cur = df[10]\n",
    "        I = U_cur / R # А\n",
    "\n",
    "        result = pd.concat([result, pd.concat(dict(zip(column_names, [U, I])), axis=1)], ignore_index=True)\n",
    "    \n",
    "    result[\"Current\"] -= min(result[\"Current\"])\n",
    "    ex_result[num] = result.groupby(\"Voltage\").mean().reset_index()\n",
    "    dots_result[num] = result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "24817123-a6cd-47a5-a153-7d4e6ab68135",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for num, (ex_name, dots, line) in enumerate(zip(experiment_names, dots_result, ex_result)):\n",
    "    plt.plot(dots[\"Voltage\"]*1e-3, dots[\"Current\"]*1e6, alpha=0.01, ls=\"\", marker=\".\", markersize=2, color=f\"C{num}\")\n",
    "    plt.plot(line[\"Voltage\"]*1e-3, line[\"Current\"]*1e6, lw=1.5, alpha=1, color=f\"C{num}\", label=ex_name)\n",
    "else:\n",
    "    df = pd.read_csv(\"VAH.csv\")\n",
    "    cols = df.columns\n",
    "    plt.plot(df[cols[0]]*1e-3, df[cols[1]]*1e-1, marker=\".\", lw=1, markersize=3, ls=\"--\", color=\"C2\", label=\"Ручные измерения\")\n",
    "    \n",
    "plt.xlabel(fr\"Напряжение, кВ\")\n",
    "plt.ylabel(fr\"Сила тока, мкА\")\n",
    "# plt.yscale(\"log\")\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"all-VAH.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c61ec35-5368-4a1c-8708-9f5b08d969f7",
   "metadata": {},
   "source": [
    "### Прямые с осциллографа"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f964e34e-f019-49d3-9815-86764aad6a64",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:     k= -10.50\tb= -15.26\n",
      "1:     k= -7.50\tb= -17.57\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABE0AAAL1CAYAAAAy1hoDAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAB7CAAAewgFu0HU+AADj+klEQVR4nOz9a1Bbd54v/H7X0pK4G3E3FxskGRNsJbaFb3Hcl8RiMj1NUs+ehng/Zdd+zosJpN+dOs+06eznVCfpqrOz8cx+3mYg/eyqM2Wfmhim9zkTpnsn4KST2A62kcA2MbGxJHzB2NiAMLYBIdY6LxQpCCQhgUBCfD9VVBzx13/9tLSwWV/9L4KiKAqIiIiIiIiIiMiPGOsCiIiIiIiIiIjiEUMTIiIiIiIiIqIAGJoQEREREREREQXA0ISIiIiIiIiIKACGJkREREREREREATA0ISIiIiIiIiIKgKEJEREREREREVEAUqwLoI3l8ePH+Oyzz1BWVoaUlJRYl0NEREREREQJbmpqCoODg3j99deRm5sb0XMZmtCa+uyzz3D8+PFYl0FEREREREQbzKlTp3Ds2LGInsPQhNZUWVkZAM/FWllZ6fe9/v5+HD9+POD34kE818fali+e64vn2oD4ro+1LV881xfPtQHxXR9rW754ri+eawPiuz7WtnzxXF881wbEd33xXBuw8vq8z/fej0aCoQmtKe+UnMrKSphMpoBtQn0vHsRzfaxt+eK5vniuDYjv+ljb8sVzffFcGxDf9bG25Yvn+uK5NiC+62NtyxfP9cVzbUB81xfPtQErr285S0RwIVgiIiIiIiIiogAYmlDcKCwsxHvvvYfCwsJYlxJQPNcXz7XFu3g+d/FcGxDf9cVzbfEuns9dPNcGxHd98VxbvIvncxfPtQHxXV881xbv4vncxXNtQHzXF8+1xZqgKIoS6yJo47BaraiqqoLFYonrYV8UPXzPifzxZ4LIH38miPzxZ4JosZX+XKzk+RxpQkREREREREQUAEMTIiIiIiIiIqIAGJoQ0ari/Egif/yZIPLHnwkif/yZIFoslj8XXNOE1hTnaBIREREREdFa4pomRERERERERERRxtCEiIiIiIiIiCgAhiZERERERERERAEwNCEiIiIiIiIiCoChCRERERERERFRAAxNiIiIiIiIiIgCYGhCRERERERERBQAQxMiIiIiIiIiogAYmhARERERERERBSDFugDamPr7+31/LiwsRGFhYQyrISIiIiIiokQyPDyM4eFhAP73n5FiaEIxcfz4cd+f33vvPbz//vuxK4aIiIiIiIgSSnNzMz744IMV98PQhGLi1KlTqKysBACOMiEiIiIiIqKoamhowJtvvgnAM9Jk/gf3kWBoQjFRWVkJk8kU6zKIiIiIiIgoAUVrGQiGJkRxTJFluAccUCYmIWRmQCrXQRC5fjMREREREdFaYGhCFKdcPX2YOtMOeczpe0zM0SKlrgaaPcbYFUZERERERLRB8CNrojjk6unDs+bTfoEJAMijTjxrPg1XT19sCiMiIiIiItpAGJoQrRJFljF7wwbXpV7M3rBBkeWwnzd1ph1QlCANFEydaQ+7PyIiIiIiIloeTs8hWgUrmVrjHnAsGmGykDzmhHvAAXWFIQrVEhERERERUSAcaUIUZSudWqNMTIZ1nHDbERERERER0fIwNCGKomhMrREyM8I6VrjtiIiIiIiIaHkYmhBFUSRTa4KRynUQs7Uh+xBztJDKdRHVttw1VoiIiIiIiDYqrmlCFEXRmFojiCJS3qrBs+bTgUesCAJS6mogiOFnnty+mIiIElFDQwNaWlqi3q9er4fNZot6v0REtP5wpAnRAisZkRGtqTWaPUakNRxbNOJEzNEireFYREEHty8mIqJE1dzcDEVRYLPZYDKZFj2+1JfFYvHrz2Kx+PojIiICONKEyM9KR2R4p9aEmqIT7tQazR4j1Lt2wD3ggDIxCSEzA1K5LqIRJuGusaLetSOifomIiOKJXq/H0aNHYbVaAQB79+4N63nzgxaz2ez3/0RERABHmhD5hByR8U+nwhqR4Z1aA0EI0iCyqTWCKEJdYYBm/26oKwwRBxvRWGOFiIiIiIjIy2q1wmAwoLq6etH3qqurYTAYfCF2ImBoQoQwRmQAeP7/+f9BdruX7CuaU2tWitsXExERERFRNDU3N8Nut6OzsxOdnZ2+x61WKzo7O2G329Hc3BzDCqOL03OIEN6IDOXJJKba/oTkn+yHWJgfctRHNKbWRAO3LyYiIiIiomiqqqoC4JkaOX86pF6vX9QmETA0IUL4Iy0ERYbLeg1CejrUFXpPeBJkKo53ak0sRXONFSIiil9zsoI+xyOMTk4jJyMZRl0eVGKQqaJEREQrUF9fD4vFgpaWFmRlZUGr1QIAnE6n7/v19fWxKzDKGJoQIfyRFmrTi1Dl52L2hh0uy1UIGelQbw8dnsTSamxfTERE8eVc3xA+au/FiPO577ECbSreqdmNw8biGFZGRESJqrm5GY2NjWhra/PtOGYwGFBbW+s34iQRMDQhQmQjMgRRRNLBPZDHnJi96QlPxE0ZkCr0EAvy4i480ewxAg3HVrQrEBERxadzfUP4/ekLi3Lxh87n+P3pC/jdsUMMToiIaEWcTicaGxuDft+7fklDQwOampoCtmlqavKNSFlvGJoQYXkjMsRsLZIOmjzhyQ0bXJevQMzcBGm7HmJBblyFJ/GyxgoREUXPnKzgo/beULvK46P2Xry8o4hTdaLEe+PQ3d0NvV7vG4re0NCA2tpav7Z1dXWw2+1wOp0YGxtDfX09mpqa0NbW5rvBGBsbAwAcPXoUJ06cCHhMbz/zd6Kora1FdnY2xsbG4HQ6YbfbYTab0dDQEHLb5M7OTr8bmrGxMZjNZrz77rth3cxYrVbfApAA/J7T2dnpOx+AZwvnurq6qAzRP3nyJD755BMA8L3uo0ePor6+Pmjda/1eOZ1OvP3224veK5PJBL1ej9bWVr9jBWrz8ccfL3o9a3XOo1U/ABw5cgStra3o7OxEa2ur39SNsbEx3xbhC9+HhoYGdHd3+/rWarVwOBxLXpudnZ2oq6vznYtQ5yEWP8PLOX40349oXZfNzc2wWq04cuQInE6n7/nz/87xXqvV1dWw2+3QarU4e/bs+t/OXSFaQxaLRQGgWCyWWJcS0Iz1muL87YfKWH2j78v57ofKjPXaks91Px5Tps9fVp7/2+fK9FddivvBI0WW5TWomoiINqLeWw8Vc+OZJb96bz2MdalroqmpSQEQ8e8Z3ueYzeaQ7VpbWxWtVqucOHHC7/GOjg4FgFJfX7+o/fya6uvrlRMnTijNzc1+7SwWi6LVahW9Xh+ybrPZrABQamtrF31vfHxc0ev1CgClqakp4PPr6+sX1Tg+Pu7rt6OjI+ix57czm83K+Ph4wDbe1xqqr0jYbDbFZDIper1esdlsft/r6OgIes5i/V6ZTKYlrynv+TSZTAG/H6tzrigrq99bk1arVVpbWwM+98SJEwqAgO+roniuVW8NC9/DQOrr6xWtVrvkz36sr4tIj+8Vjespmv3U1taGrHd+m0B/X8XKSu5DGZrQmor30ERRFEWem1Nc399SZi72KK7vbyny3FxEz3c/GlWmz13yhCffXFTcDxmeEBFR9J3tuR1WaHK253asS10TqxmatLa2hrwBaG5uVgAsuplSFM8N3VJ1eX8/AhDwJlJRfrzRDHajEqqPUAGDoii+wCXYsee/hlC8bQLd4EfKZrP5br4D1TU+Pq7U1tYuurmLh/fK20+om0rvOQ/WJhbnfOGxl1O/NzRZ6mfQewMf6Oa8qanJ9z5ptdqQ/dhsNqW5udlXT7DzEOvrIhrHD/V+RKvNUtdlOP14Q6Cl+llrK7kP5dh8ogW8u95o9u+GusIQ8RQWVW42NIf2QnPQBECA62IPXOe7MfdoFEqwMdREREQRyslIjmo7Csw7TB5A0Ln63mkAgeb8e6cWmM3moEPUTSaTb2h/XV3dsuqcv/Di/CH2ANDR0QG73Y6qqiq/6Rxe3mkB3ikHC3mnIKzlegQNDQ0APOc
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "opt_arr = []\n",
    "for num, (ex_name, line) in enumerate(zip(experiment_names, ex_result)):\n",
    "    x = 1e3 / line[\"Voltage\"]\n",
    "    y = np.log(line[\"Current\"]) - 2 * np.log(line[\"Voltage\"])\n",
    "    \n",
    "    popt, pcov = curve_fit(line_func, x, y)\n",
    "    print(f\"{num}:     k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
    "    opt_arr.append(popt)\n",
    "    \n",
    "    plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C{num}\", label=ex_name)\n",
    "    plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C{num}\")\n",
    "\n",
    "plt.xlabel(r\"$\\dfrac {10^3} U$\")\n",
    "plt.ylabel(r\"$\\log \\dfrac I {U^2}$\")\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"osc-NORDGAME-FAULER.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb204b4f-dc40-4da5-bb0f-465162d6460f",
   "metadata": {},
   "source": [
    "### Прямая ручная"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6b0c2a09-1033-43c5-baa4-02616c6bdb91",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1:     k= -11.41\tb= -14.52\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.read_csv(\"VAH.csv\")\n",
    "cols = df.columns\n",
    "\n",
    "volt_h = df[cols[0]]\n",
    "curr_h = df[cols[1]]*1e-7\n",
    "\n",
    "x = 1e3 / volt_h\n",
    "y = np.log(curr_h) - 2 * np.log(volt_h)\n",
    "\n",
    "popt, pcov = curve_fit(line_func, x, y)\n",
    "print(f\"{num}:     k= {popt[0]:.2f}\\tb= {popt[1]:.2f}\")\n",
    "opt_arr.append(popt)\n",
    "\n",
    "plt.plot(x, y, ls=\"\", marker=\".\", markersize=5, color=f\"C2\", label=\"Ручные измерения\")\n",
    "plt.plot(x, line_func(x, *popt), lw=0.5, alpha=.5, color=f\"C2\")\n",
    "\n",
    "plt.xlabel(r\"$\\dfrac {10^3} U$\")\n",
    "plt.ylabel(r\"$\\log \\dfrac I {U^2}$\")\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"hand-NORDGAME-FAULER.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a212083d-2d53-4522-860d-8eba58766461",
   "metadata": {},
   "source": [
    "### Все вместе"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d668aa7a-0a40-475b-9876-698f4bc62c0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABEkAAAL1CAYAAAA7Pbp5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAB7CAAAewgFu0HU+AAEAAElEQVR4nOz9e1Rc95k3+H53XUEgKBBI3CSgQEJISLIKyTfJsS0VcZxIfjsdiNLdpM9Mzxj8Zq2302eddWB8Zjq+zFrjQVlnkvScyTmFT/eZTni7O4F03LZycSjZcSRZtkWVZAtJlkQV94sAVRVIXKpq79rnD7zLXKqggILi8v2sxRLs67MviPo9+7efnyDLsgwiIiIiIiIiok1OFesAiIiIiIiIiIjWAiZJiIiIiIiIiIjAJAkREREREREREQAmSYiIiIiIiIiIADBJQkREREREREQEgEkSIiIiIiIiIiIATJIQEREREREREQEANLEOgDaX4eFhvPvuu8jLy0N8fHyswyEiIiIiIqINbmJiAh0dHXjuueeQlpY277JMktCqevfdd1FZWRnrMIiIiIiIiGiTaWhowF/91V/NuwyTJLSq8vLyAEzdnMXFxfMue+vWLVRWVka07EpjLGs3jrUUy1qJg7Gs7TjWUixrJY61FMtaiYOxrO041lIsayUOxrK241hLsayVOBjL2o4j2rEo21Lao/NhkoRWlfKKTXFxMUwmU0TrLGbZlcZY1m4cwNqJZa3EATCWtRwHsHZiWStxAGsnlrUSB8BY1nIcwNqJZa3EATCWtRwHsHZiWStxAIxlLccBRDeWSEo+sHArERERERERERGYJKE1LDMzE6+88goyMzNjHQpjWePWyjlZK3EwlrVvrZyTtRLHWoplrcSx1qyV87JW4lhLsayVONaatXJe1kocaymWtRLHWrNWzstaiSOWsQiyLMurukfa1Ox2O0pLS2Gz2dZM9y1aGl5LWm94z9J6w3uW1hves7Te8J7dPBZzrdmThIiIiIiIiIgITJIQEREREREREQFgkoSIlmgtva9IFAnes7Te8J6l9Yb3LK03vGcpFNYkoVXF9/6IiIiIiIhoNbEmCRERERERERHRIjFJQkREREREREQEJkmIiIiIiIiIiAAwSUJEREREREREBIBJEiIiIiIiIiIiAEySEBEREREREREBYJKEiIiIiIiIiAgAkyRERERERERERACYJCEiIiIiIiIiAsAkCRERERERERERAEAT6wBoc7p161bw+8zMTGRmZsYwGiIiIiIiItpI+vv70d/fD2Bm+3MhTJJQTFRWVga/f+WVV/Dqq6/GLhgiIiIiIiLaUCwWC1577bVFr8ckCcVEQ0MDiouLAYC9SIiIiIiIiCiqqqur8cILLwCY6kky/UH9fJgkoZgoLi6GyWSKdRhERERERES0AS21rAMLtxIRERERERERgT1JiNYUn70Vk+eskIZdUKelIu6UGTpTSazDIiIiIiIi2hTYk4RojfDZWzFmaYDUOwB4fZB6BzBmaYDvamusQyMiIiIiItoU2JOEKMqW2htk8pw19PR3rNAdZm8SIiIiIiKilcaeJERRtJzeINKwa1HTiYiIiIiIKLqYJCGKovl6gyxEnZa6qOlEREREREQUXUySEEXRcnqDxJ0yh55+OvR0IiIiIiIiii4mSYhCCLg8kO67F73ecnqD6EwlSHipEursDECvgzo7AwkvVS6qHonP3orR138M99/+AKOv/xg+O4u+EhHRxlVdXQ1BEKL+VVBQEOtDIyKiGGGShGgWr+06Rut+itG//yE8tf8LJt//ELIsR7TucnuD6A6XIOkHf4eUf3gdST/4u0UnSDg6DhERbSYWiwWyLMPhcMBkMs2ZvtCXzWabsT2bzRbcHhERbU5MkhBN47O3Yrz+v0L2jAJSALJnFBP/9jbG/+uvIfUOQA4E5l0/Gr1Blmo59VCIiIjWM6PRiDNnzgR/PnLkSETrTU+smM3mGT8TEdHmxCGAiaYJl2jwX7sBVfJWCAlboCnIhTonE4JaHXJZ3eGSmAzZy9FxiIiIiIhopdntdlRUVMBoNKK5uXnGvLKyMjidTjQ2Nq7bxDN7khBNEy6hII9PTP07Ng7/Z7fgfe8SREcnZL+4muHNi6PjEBERERHRSrNYLHA6nbBarbBav3zIbLfbYbVa4XQ6YbFYYhjh8jBJQjRNuISCKi0Vqmnz5Ekv/DfvwHv+Ivy3HZB9vtUKMSyOjkNERERERCuttLQUwNSrjtNfbzQajXOWWY+YJCGaJlyiIf6bX4P+iVLojz8Kdcb24HTZ74d4x4lJ60X4W29DnphcrVDniGU9FCIiIiIi2hyqqqpQVVUFp9OJlJSUGV/T569XrElCNI3OVAK8VInJd6yQhl1Qp6Ui7rQ5mGhQpSRDd/QQAg8eQnR0QurpB2QZkCSI7V0QO3ugzs6ApjAPqsSE1Y8/RvVQiIiIiIho87BYLKitrUVTU1NwRLCCggKUl5fP6FGyHjFJQjRLJIkG1dZE6B7Zj8AeIyRnF8SuXkCSgEAAUncfpO5+qDO3Q7M7D6rkpFWKnIiINqsLrT34ufUmBlxjyEhNwHfN+/BUSU6swyIiog3A4/GgtrY27Hyl/kh1dTXq6upCLlNXVweDwbAS4UUdkyREy6DaEg9VSRE0u/MhtndB6uiB7PcDkCH134PUfw+q9DRoCnOh2pYCQRBiHTIREW0wF1p78HrD5eDP7QMjeL3hMl6pfBLHS7JjGNnGozQUWlpaYDQa4fF4AEw1DMrLy2csW1FRAafTCY/HA5fLhaqqKtTV1aGpqSnYoHC5pgrGnzlzBjU1NSH3qWzHbrcHp5WXlyM1NRUulwsejwdOpxNmsxnV1dXzjiZhtVpnNGBcLhfMZjNefvnliBovdrs9WLARwIx1rFZr8HwAU0MqV1RURKXL/dmzZ/GLX/wCAILHfebMGVRVVYWNe7WvlcfjwYsvvjjnWplMJhiNRjQ2Ns7YV6hl3nzzzTnHs1rnPFrxA8DJkyfR2NgIq9WKxsbGYMzK+VWG7J59Haqrq9HS0hLctsFgQHt7+4L3ptVqRUVFRfBczHceYvE7vJT9R/N6ROu+tFgssNvtOHnyJDweT3D96f/nKPeqMsKNwWDA+fPn198oNzLRKrLZbDIA2WazxTqUFRHw+WX/3XZ54t0P5PG3/zDja/LCJ7LYPygHAoFYh0lERBvIiz96VzbX/nLO14s/ejfWoa2quro6GcCiP2co65jN5nmXa2xslA0Gg1xTUzNjenNzswxArqqqmrP89Jiqqqrkmpoa2WKxzFjOZrPJBoNBNhqN88ZtNptlAHJ5efmceW63WzYajTIAua6uLuT6VVVVc2J0u93B7TY3N4fd9/TlzGaz7Ha7Qy6jHOt821oMh8Mhm0wm2Wg0yg6HY8a85ubmsOcs1tfKZDIteE8p59NkMoWcH6tzLsvLi1+JyWAwyI2NjSHXrampkQGEvK6yPHWvKjHMvoahVFVVyQaDYcHf/VjfF4vdvyIa91M0t1NeXj5vvNOXCfX/Vawsph3KJAmtKuXmbGhokG02m2yz2eS+vr5YhxV1AVGU/e1d8kTzhTnJkon3P5T93X1yQJJiHSYREW0Ap//+30MmSU7//b/HOrRVtZJJksbGxnk/8FssFhnAnMaTLE814BaKS/l8BCBko1GWv2xYhmuYzLeN+RIKsiwHEyzh9j39GOajLBOqQb9YDocj2NgOFZfb7ZbLy8vnNObWwrVStjNfI1I55+GWicU5n73vpcSvJEkW+h1UGuyhGuN1dXXB62QwGObdjsPhkC0WSzCecOch1vdFNPY/3/WI1jIL3ZeRbEdJ+iy0ndXQ19cXbHM2NDRE/PeBo9tQTFRWVqK0tBSlpaXregztcAS1Gpq8ndCfeBLawyUQtiYG58kPHsJ/tRXe9z+E2NENWZJiGCkREa13GamhC4WHm06Lo3R7BxD2XXulW3+od/aVVwXMZnPYLucmkynYVb+iomJJcU4vlDi9yzwANDc3w+l0orS0dMbrGQqlm3+4z2TKKwWrWU+guroawNQ5D1UE8o033kB
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for num, (ex_name, line) in enumerate(zip(experiment_names, ex_result)):\n",
    "    x = 1e3 / line[\"Voltage\"]\n",
    "    y = np.log(line[\"Current\"]) - 2 * np.log(line[\"Voltage\"])\n",
    "    \n",
    "    plt.plot(x, y, ls=\"\", marker=\".\", markersize=3, color=f\"C{num}\", label=ex_name)\n",
    "    plt.plot(x, line_func(x, *(opt_arr[num])), lw=1, alpha=.5, color=f\"C{num}\")\n",
    "else:\n",
    "    x = 1e3 / volt_h\n",
    "    y = np.log(curr_h) - 2 * np.log(volt_h)\n",
    "\n",
    "    plt.plot(x, y, ls=\"\", marker=\".\", markersize=2, color=f\"C2\", label=\"Ручные измерения\")\n",
    "    plt.plot(x, line_func(x, *(opt_arr[-1])), lw=1, alpha=.8, color=f\"C2\")\n",
    "    \n",
    "plt.xlabel(r\"$\\dfrac {10^3} U$\")\n",
    "plt.ylabel(r\"$\\log \\dfrac I {U^2}$\")\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"osc-NORDGAME-FAULER.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31fee377-ff25-4382-8f41-228790745a73",
   "metadata": {},
   "source": [
    "Угол наклона полученной прямой получается по формуле\n",
    "\n",
    "$\\tan \\alpha = -0.683 \\cdot \\dfrac {\\phi^\\frac 3 2} \\beta$\n",
    "\n",
    "зная $\\phi = 4.5$ эВ -- работу выхода, находим $\\beta$ -- форм-фактор острия:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "21ac3719-9a57-4f80-9858-fc3c018fb1ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "beta:\t6.21e-04\n",
      "beta:\t8.69e-04\n"
     ]
    }
   ],
   "source": [
    "for opt in opt_arr:\n",
    "    tan_a = opt[0]\n",
    "    beta = -0.683 * (4.5**(3/2)) / tan_a\n",
    "    print(f\"beta:\\t{beta:.2e}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8dfd4820-1065-4364-abe3-498825506a74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = 900\n",
    "U_min = 800\n",
    "\n",
    "for i in range(1, 4):\n",
    "    df = pd.read_csv(f\"BOTH-{i}.csv\", header = None)\n",
    "    data = [None, None]\n",
    "    df = df.loc[lambda x : x[4] > U_min]\n",
    "    \n",
    "    data[0] = df.loc[lambda x : x.index < idx]\n",
    "    data[1] = df.loc[lambda x : x.index >= idx]\n",
    "    \n",
    "    for (i, d) in enumerate(data):\n",
    "        U = d[4] * 1e-3 # кВ\n",
    "        U_res = d[10]\n",
    "        R = 26.99e3 # Ом\n",
    "        I = U_res / R * 1e6 # мкА\n",
    "\n",
    "        plt.plot(U, I, lw=5, alpha=0.2, ls=\"\", marker=\"o\", markersize=4, color=f\"C{i}\")\n",
    "    \n",
    "    \n",
    "plt.xlabel(fr\"Напряжение, кВ\")\n",
    "plt.ylabel(fr\"Сила тока, мкА\")\n",
    "# plt.yscale(\"log\")\n",
    "\n",
    "plt.savefig(\"both-RAW-DATA.png\")\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}