EBL-spectrum.ipynb 65.4 KB
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZkAAAESCAYAAAAv0qjVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa4bee6f210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "from scipy.optimize import curve_fit\n",
    "import matplotlib.pyplot as plt\n",
    "from modules.constants import *\n",
    "\n",
    "fig1 = plt.figure()\n",
    "ax = fig1.add_subplot(111)\n",
    "\n",
    "z=2\n",
    "\n",
    "# ==== Dominguez ====\n",
    "lamb,lambdaI = np.loadtxt(\"EBL_files/lambdaI_Dominguez.dat\",unpack=True,usecols=[0,15])\n",
    "#lamb,lambdaI =np.loadtxt(\"EBL_files/lambdaI_Dominguez.dat\",unpack=True,usecols=[0,1])\n",
    "hv = h*c/(lamb*1e-4)  # erg\n",
    "density = 1e-6*(4*pi/c)*lambdaI/(hv**2) /(erg_to_GeV*1e9) *(1+z)**3\n",
    "hv = hv *(erg_to_GeV*1e9)\n",
    "ax.plot(hv,density*hv**2,\"--b\",label=\"Dominguez et Al\")\n",
    "\n",
    "# ==== Kneiske and Doll - \"best fit\" ====\n",
    "hv,density = np.loadtxt(\"EBL_files/n_bestfit10.dat\",unpack=True,usecols=[0,1])\n",
    "ax.plot(hv,density*hv**2,\"--r\",label=\"Kneiske et Doll - 'best fit'\")\n",
    "\n",
    "# ==== Kneiske and Doll - \"lower limit\" ====\n",
    "hv,density = np.loadtxt(\"EBL_files/n_lowerlimit10.dat\",unpack=True,usecols=[0,179])\n",
    "#hv,density =np.loadtxt(\"EBL_files/n_lowerlimit10.dat\",unpack=True,usecols=[0,1])\n",
    "density=density*(1+z)**3\n",
    "ax.plot(hv,density*hv**2,\"--g\",label=\"Kneiske and Doll - 'lower limit'\")\n",
    "\n",
    "# ==== Fransceschini ====\n",
    "hv,density = np.loadtxt(\"EBL_files/n_Fra.dat\",unpack=True,usecols=[0,11])\n",
    "#hv,density = np.loadtxt(\"EBL_files/n_Fra.dat\",unpack=True,usecols=[0,1])\n",
    "density=density*(1+z)**3\n",
    "ax.plot(hv,density*hv**2,\"--c\",label=\"Fraceschini\")\n",
    "\n",
    "# ==== Finke ====\n",
    "hv,density = np.loadtxt(\"EBL_files/n_Finke.dat\",unpack=True,usecols=[0,201])\n",
    "#hv,density = np.loadtxt(\"EBL_files/n_Finke.dat\",unpack=True,usecols=[0,1])\n",
    "density=density*(1+z)**3\n",
    "ax.plot(hv,density*hv**2,\"--m\",label=\"Finke et Al\")\n",
    "\n",
    "# ==== Gilmore ====\n",
    "hv,density = np.loadtxt(\"EBL_files/n_Gil.dat\",unpack=True,usecols=[0,14])\n",
    "#hv,density = np.loadtxt(\"EBL_files/n_Gil.dat\",unpack=True,usecols=[0,1])\n",
    "ax.plot(hv,density*hv**2,\"--y\",label=\"Gilmore et Al\")\n",
    "\n",
    "#==== CMB ====\n",
    "def nCMB(E,z):\n",
    "   kTcmb = k*Tcmb*erg_to_GeV*1e9*(1+z)\n",
    "   theta = E/kTcmb\n",
    "   nCMB=(hb*c*erg_to_GeV*1e9)**(-3) *(E/np.pi)**2 /(np.exp(theta)-1)    \n",
    "   return nCMB\n",
    "\n",
    "hv = np.logspace(-4,-1,1000)\n",
    "ax.plot(hv,nCMB(hv,z)*hv**2,\"-k\",label=\"CMB\")\n",
    "\n",
    "ax.set_xscale('log')\n",
    "ax.set_yscale('log')\n",
    "ax.grid(b=True,which='major')\n",
    "ax.legend(loc=\"best\")#,frameon=False,framealpha=0.5)\n",
    "ax.set_xlabel(\"energy [eV]\")\n",
    "ax.set_ylabel(\"$n$ [photon.eV.cm$^{-3}$]\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZ0AAAEPCAYAAACZcRnqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMyuMk46ZmRXGScfMzArjpGNmZoX5H9x2Zf4gH41dAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa4bee6f350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#==== Dominguez vs redshift ==================================================================\n",
    "fig2 = plt.figure()\n",
    "ax2 = fig2.add_subplot(111)\n",
    "\n",
    "z = np.loadtxt(\"EBL_files/z_Dominguez.dat\",unpack=True,usecols=[0])\n",
    "for z_index in [1,9,12,15,17]:\n",
    "   lamb,lambdaI = np.loadtxt(\"EBL_files/lambdaI_Dominguez.dat\",unpack=True,usecols=[0,z_index])\n",
    "   hv = h*c/(lamb*1e-4)  # erg\n",
    "   density = 1e-6*(4*pi/c)*lambdaI/(hv**2) /(erg_to_GeV*1e9) *(1+z[z_index])**3\n",
    "   hv = hv *(erg_to_GeV*1e9)\n",
    "   p=ax2.plot(hv,density*hv**2,\"--\")\n",
    "   # CMB\n",
    "   hv = np.logspace(-4,-1,1000)\n",
    "   ax2.plot(hv,nCMB(hv,z[z_index])*hv**2,color=p[0].get_color(),linestyle='-',label=\"z=\"+str(z[z_index-1]))\n",
    "\n",
    "ax2.set_xscale('log')\n",
    "ax2.set_yscale('log')\n",
    "ax2.grid(b=True,which='major')\n",
    "ax2.legend(loc=\"best\")#,frameon=False,framealpha=0.5)\n",
    "ax2.set_xlabel(\"energy [eV]\")\n",
    "ax2.set_ylabel(\"$n$ [photon.eV.cm$^{-3}$]\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}