Lugovtsov/5.4.2-beta-spectrum/plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "e790f4e5-04de-47f5-9620-dcb717e467e7",
   "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",
    "\n",
    "matplotlib.rcParams.update({\n",
    "    'figure.figsize': [6, 4],\n",
    "    'savefig.facecolor': 'white',\n",
    "    'figure.dpi': 150.0,\n",
    "    'font.size': 12.0,\n",
    "})\n",
    "\n",
    "def line(x, k, b):\n",
    "    return k*x + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "3a850101-4426-439a-b7d8-2d621361bb90",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframes = []\n",
    "for i in range(1, 4):\n",
    "    dataframes.append(pd.read_csv(f\"data_setup_{i}.csv\", sep=\"\\t\"))\n",
    "x_name, y_name = dataframes[0].columns\n",
    "\n",
    "background = pd.read_csv(\"background_radiation.csv\", sep=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "91439fc9-0550-451f-b2e3-b32ffa0da18f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for df, bg in zip(dataframes, background.iterrows()):\n",
    "    level, dev = bg[1]\n",
    "    I = df[x_name]\n",
    "    nu = df[y_name] - level\n",
    "    \n",
    "    plt.plot(I, nu, \".--\")\n",
    "\n",
    "plt.xlabel(\"Ток через линзу, А\")\n",
    "plt.ylabel(y_name)\n",
    "    \n",
    "plt.savefig(\"all_setups-NU_on_I.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "7234fe24-4b9b-4553-bf81-8c1505ce3ae4",
   "metadata": {},
   "outputs": [],
   "source": [
    "c = 3e10\n",
    "m_e = 9.11e-28\n",
    "T_k = 0.624e6 # энергия электронов внутрненней конверсии, эВ\n",
    "def p2T(p):\n",
    "    return (p**2 * c**2 + m_e**2 * c**4)**.5 - m_e * c**2\n",
    "def T2p(T):\n",
    "    return ((T + m_e*c**2)**2 - m_e**2*c**4)**.5/c\n",
    "    \n",
    "p_k = T2p(T_k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "9ddd6b63-d441-4ba3-b000-a5f268cc5157",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for df, bg in zip(dataframes, background.iterrows()):\n",
    "    level, dev = bg[1]\n",
    "    I = df[x_name]\n",
    "    nu = df[y_name] - level\n",
    "    \n",
    "    idxmax = nu[16:].idxmax()\n",
    "    k = p_k / I[idxmax]\n",
    "    \n",
    "    plt.errorbar(I*k, nu, xerr=0, yerr=dev, fmt=\".--\", label=fr\"$k=$ {k:.2e} МэВ/($c\\cdot$A)\")\n",
    "    # plt.plot(I*k, nu, \".--\", label=fr\"$k={k:.2f}$ МэВ/А\")\n",
    "    # plt.plot(I[idxmax]*k, nu[idxmax], \"x\")\n",
    "\n",
    "plt.axvline(p_k, c=\"C3\", label=fr\"Конв. пик, $T_k=$ {T_k:.2e} эВ\")\n",
    "    \n",
    "plt.xlabel(r\"Импульс электронов, эВ/$c$\")\n",
    "plt.ylabel(y_name)\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"all_setups-NU_on_p.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "31811c4a-9169-4109-98cb-a5de7d85656f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for df, bg in zip(dataframes, background.iterrows()):\n",
    "    level, dev = bg[1]\n",
    "    I = df[x_name]\n",
    "    nu = df[y_name] - level\n",
    "    \n",
    "    idxmax = nu[16:].idxmax()\n",
    "    k = p_k / I[idxmax]\n",
    "    p = I*k\n",
    "    plt.errorbar(p2T(p)*1e-6, nu, xerr=0, yerr=dev, fmt=\".--\")\n",
    "\n",
    "plt.axvline(T_k*1e-6, c=\"C3\", label=fr\"Конв. пик, $T_k=$ {T_k:.2e} эВ\")\n",
    "    \n",
    "plt.xlabel(r\"Энергия электронов, МэВ\")\n",
    "plt.ylabel(y_name)\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"all_setups-NU_on_T.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89ad0f0e-ba9e-42d7-b5a5-c60f8ec9f6e8",
   "metadata": {},
   "source": [
    "### График Ферми"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "8c302eaf-f3ba-40f6-a7d8-a9f528916dcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "line(1, 1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "16c9ae84-657a-4395-a3c3-036d0f46ba4a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, (df, bg) in enumerate(zip(dataframes, background.iterrows())):\n",
    "    level, dev = bg[1]\n",
    "    I = df[x_name]\n",
    "    nu = df[y_name] - level\n",
    "    \n",
    "    idxmax = nu[16:].idxmax()\n",
    "    k = p_k / I[idxmax]\n",
    "    p = I*k\n",
    "    T = p2T(p)*1e-6\n",
    "    \n",
    "    idxs = (T>2.5e-1) * (T<5.5e-1)\n",
    "    (k, b), _ = curve_fit(line, T[idxs], (nu**0.5 / p**(3/2))[idxs])\n",
    "    \n",
    "    plt.plot(T[idxs], (nu**0.5 / p**(3/2))[idxs], \".\", c=f\"C{i}\")\n",
    "    plt.plot(T[idxs], line(T[idxs], k,b), c=f\"C{i}\", label=r\"$T_\\text{max}=$\" + f\" {-b/k:.2f} МэВ\")\n",
    "    # plt.plot(I[idxmax]*k, nu[idxmax], \"x\")\n",
    "\n",
    "plt.xlabel(\"Энергия электронов, МэВ\")\n",
    "plt.ylabel(\"у.е.\")\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(\"all_setups-fermi.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6806f06e-fd65-4aea-9a8e-74523980ac76",
   "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}