Lugovtsov/5.2.4-beta-spectrum/plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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": 51,
   "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": 66,
   "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": [
    "T_k = 0.624e6 # энергия электронов внутрненней конверсии, эВ\n",
    "\n",
    "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 = T_k / I[idxmax]\n",
    "    \n",
    "    plt.plot(I*k, nu, \"--\")\n",
    "    # plt.plot(I[idxmax]*k, nu[idxmax], \"x\")\n",
    "\n",
    "plt.xlabel(\"Энергия электронов, эВ\")\n",
    "plt.ylabel(y_name)\n",
    "    \n",
    "plt.savefig(\"all_setups-NU_on_EV.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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 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 = T_k / I[idxmax]\n",
    "    T = I*k\n",
    "    p = T / 3e10\n",
    "    \n",
    "    plt.plot(T, nu**0.5 / p**(3/2), \"--\")\n",
    "    # plt.plot(I[idxmax]*k, nu[idxmax], \"x\")\n",
    "\n",
    "plt.xlabel(\"Энергия электронов, эВ\")\n",
    "plt.ylabel(\"у.е.\")\n",
    "    \n",
    "plt.savefig(\"all_setups-NU_on_EV.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ce99e8f7-9f0a-4db0-bcf9-c08bf46abf51",
   "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
}