HajimeKawahara/exojax

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documents/analysis/t_grid.ipynb

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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The reason why we use E grid instead of T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Tarr = np.linspace(100,5000, 100)\n",
    "Earr = np.logspace(2,4.,1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from exojax.utils.constants import hcperk, Tref\n",
    "def East(T):\n",
    "    return -1. / (hcperk * (1. / T - 1. / Tref))\n",
    "\n",
    "def f(E,T):\n",
    "    return np.exp(E/East(T))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(Earr,f(Earr,1100)/f(Earr,1000),label=\"$f(E,1100K)/f(E,1000K)$\")\n",
    "plt.plot(Earr,f(Earr,900)/f(Earr,1000),label=\"$f(E,900K)/f(E,1000K)$\",ls=\"dashed\")\n",
    "plt.plot(Earr,f(Earr,600)/f(Earr,500),label=\"$f(E,600K)/f(E,500K)$\")\n",
    "plt.plot(Earr,f(Earr,400)/f(Earr,500),label=\"$f(E,400K)/f(E,500K)$\",ls=\"dashed\")\n",
    "plt.ylim(0.0,4.0)\n",
    "plt.legend()\n",
    "plt.axhline(1.0,color=\"gray\")\n",
    "plt.xlabel(\"E ($\\mathrm{cm}^{-1}$)\")\n",
    "plt.xscale(\"log\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(Tarr,f(1100,Tarr)/f(1000,Tarr),label=\"$f (E+100\\mathrm{cm^{-1}},T) / f (E,T)$\")\n",
    "plt.plot(Tarr,f(900,Tarr)/f(1000,Tarr),label=\"$f (E-100\\mathrm{cm^{-1}},T) / f (E,T)$\",ls=\"dashed\")\n",
    "#plt.plot(Tarr,s(200,Tarr)/s(300,Tarr),label=\"\")\n",
    "#plt.plot(Tarr,s(400,Tarr)/s(300,Tarr),label=\"\",ls=\"dashed\")\n",
    "#does not depend on E but Delta E\n",
    "plt.legend()\n",
    "plt.axhline(1.0,color=\"gray\")\n",
    "plt.axvline(296,alpha=0.3,color=\"red\")\n",
    "plt.text(296+10,2.,\"$T_\\mathrm{ref}=296K$\",color=\"red\",rotation=\"vertical\",alpha=0.6)\n",
    "plt.xlabel(\"T (K)\")\n",
    "plt.xscale(\"log\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.8 ('base')",
   "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": "3.8.8"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "72bc7f8b1808a6f5ada3c6a20601509b8b1843160436d276d47f2ba819b3753b"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}