examples/waveforms_start.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate the gravitational-wave waveform for a binary merger ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "# Install the software we need\n",
    "import sys\n",
    "!{sys.executable} -m pip install pycbc ligo-common --no-cache-dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pylab\n",
    "from pycbc.waveform import get_td_waveform\n",
    "\n",
    "# The mass of the component objects solar masses\n",
    "m1 = 20\n",
    "m2 = 20 \n",
    "\n",
    "# Start the waveform from 20 Hz\n",
    "f_lower = 20\n",
    "\n",
    "# The model of the gravitational-wave signal we are using\n",
    "approximant = \"SEOBNRv4\"\n",
    "\n",
    "# The time between samples that we want\n",
    "delta_t = 1.0 / 4096\n",
    "\n",
    "# Distance in million parsecs (1 parsec ~ 3.3 light years)\n",
    "# This ignores redshift due to expansion of the universe (luminosity distance)\n",
    "distance = 100 \n",
    "\n",
    "#Generate the waveform. \n",
    "#Like electromagnetic radiation, gravitational-waves have two\n",
    "#polarizations.\n",
    "#We call them the \"plus\" polarization and a \"cross\" polarization\n",
    "hp, hc = get_td_waveform(approximant=approximant,\n",
    "                         mass1=m1, mass2=m2,\n",
    "                         delta_t=delta_t, f_lower=f_lower,\n",
    "                         distance=distance)\n",
    "pylab.figure(1)\n",
    "pylab.plot(hp.sample_times, hp, label='Plus polarization')\n",
    "pylab.legend()\n",
    "pylab.xlabel('Time (s)')\n",
    "pylab.ylabel('Strain')\n",
    "pylab.show()\n",
    "# The plot below will show the strain for a source that is located\n",
    "# directly above a detector. We will show later tutorial\n",
    "# how this maps to non-optimal sky locations and real detector \n",
    "# antenna patters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's zoom in on the time that the binary merges\n",
    "pylab.figure(2)\n",
    "hp_merge = hp[len(hp)-500:]\n",
    "pylab.plot(hp_merge.sample_times, hp_merge, label='Plus polarization')\n",
    "pylab.legend()\n",
    "pylab.xlabel('Time (s)')\n",
    "pylab.ylabel('Strain')\n",
    "pylab.show()\n",
    "# You can see the signal as it evolves from the 'inspiral'\n",
    "# stage to the 'merger' and finally when it 'rings down' (like a bell!)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's zoom in on the time that the binary merges\n",
    "# Below we show the orthognal \"cross\" polarization of the gravitational\n",
    "# wave also overlaid.\n",
    "pylab.figure(3)\n",
    "hc_merge = hc[len(hc)-500:]\n",
    "pylab.plot(hp_merge.sample_times, hp_merge, label=\"Plus polarization\")\n",
    "pylab.plot(hc_merge.sample_times, hc_merge, label='Cross polarization')\n",
    "pylab.legend()\n",
    "pylab.xlabel('Time (s)')\n",
    "pylab.ylabel('Strain')\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}