Lugovtsov/3.6.1-spectrum/processing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "afd9cde8-c7b3-4c87-85d4-fdb3246a2424",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "6f36ba20-5efd-4afb-98f4-ff87eac8a1e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def line(x, k, b):\n",
    "    return x*k + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "17d7c03e-5547-4505-85d6-733678982f80",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(r\"raw-data/data.csv\")\n",
    "\n",
    "rev_nu_0 = df['rev_nu_0']\n",
    "tau = df['tau']\n",
    "\n",
    "delta_rev_nu_0 = df['Delta_rev_nu_0']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "ec64aa59-2e42-4311-9b3b-f4daa99b8071",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt, cov = curve_fit(line, tau, rev_nu_0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6922d03a-70b0-450e-be7a-626e92ecc348",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4.5), dpi=200)\n",
    "\n",
    "plt.minorticks_on()\n",
    "plt.grid(which='minor', linestyle=':', color='0.9')\n",
    "plt.grid(which='major', linestyle='-', color='0.8', linewidth=0.3)\n",
    "\n",
    "plt.errorbar(tau, rev_nu_0, yerr=delta_rev_nu_0, linestyle='', marker='.', markersize=10, label=\"Experiment\", color=\"tab:blue\", alpha=0.3)\n",
    "plt.plot(tau, line(tau, opt[0], opt[1]), label=r\"Fitting\", color=\"tab:blue\", linestyle='-')\n",
    "\n",
    "plt.ylabel(r\"$1/\\nu_0$, мкс\", fontsize=14)\n",
    "plt.xlabel(r\"$\\tau$, мкс\", fontsize=14)\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(r\"images\\data.png\", facecolor=\"white\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59d3e6e3-0861-4ded-a70b-9e85890e7168",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "df2005d7-8ad7-441a-83c0-8ebda7901ce2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(r\"raw-data/plot2.csv\")\n",
    "\n",
    "m = df['m']\n",
    "k = df['k']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c52f43da-bb84-446a-b81a-b465d37290ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt, cov = curve_fit(line, m, k)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "15b4a580-5da3-4c54-b918-414f50268e5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4.5), dpi=200)\n",
    "\n",
    "plt.minorticks_on()\n",
    "plt.grid(which='minor', linestyle=':', color='0.9')\n",
    "plt.grid(which='major', linestyle='-', color='0.8', linewidth=0.3)\n",
    "\n",
    "plt.errorbar(m, k, linestyle='', marker='.', markersize=10, label=\"Experiment\", color=\"tab:blue\", alpha=0.3)\n",
    "plt.plot(m, line(m, opt[0], opt[1]), label=r\"Fitting\", color=\"tab:blue\", linestyle='-')\n",
    "\n",
    "plt.ylabel(r\"$k$\", fontsize=18)\n",
    "plt.xlabel(r\"$m$\", fontsize=18)\n",
    "\n",
    "plt.legend()\n",
    "plt.savefig(r\"images\\plot2.png\", facecolor=\"white\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fac6d1b6-3b03-42c1-8911-12b2f7279f41",
   "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": "3.10.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}