doc/source/notebooks/petitRADTRANS.ipynb

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   "source": [
    "# petitRADTRANS Interface"
   ]
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   "source": [
    "You can find this notebook (and data) on [GitHub](https://github.com/exorad/gcm_toolkit/tree/main/doc/source/notebooks).\n",
    "We demonstrate the use of `gcm_toolkit` with `petitRADTRANS` on a set of data of HD209458b simulations from [Schneider et al. (2022)](https://ui.adsabs.harvard.edu/abs/2022arXiv220209183S/abstract)."
   ]
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   "source": [
    "## Phase Curve\n",
    "\n",
    "**NOTE**: phasecurves require [petitRADTRANS](https://petitradtrans.readthedocs.io/en/latest/) AND [prt_phasecure](https://prt-phasecurve.readthedocs.io/en/latest/)"
   ]
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    }
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   "source": [
    "Lets start with getting some gcmdata:"
   ]
  },
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   "source": [
    "import matplotlib.pyplot as plt\n",
    "from gcm_toolkit import GCMT\n",
    "import numpy as np\n",
    "from petitRADTRANS import Radtrans\n",
    "import astropy.constants as const\n",
    "import astropy.units as u"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Lets start with getting some gcmdata:"
   ]
  },
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     "text": [
      "--2022-08-23 08:49:13--  https://figshare.com/ndownloader/files/36234516\n",
      "Resolving figshare.com (figshare.com)... 52.30.212.171, 34.250.160.50\n",
      "Connecting to figshare.com (figshare.com)|52.30.212.171|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/36234516/HD2.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20220823/eu-west-1/s3/aws4_request&X-Amz-Date=20220823T064913Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=21232a3389137bcdbb4c7c0cf4fa1f27b58aeb1e4078b60f27c26b9453b552e4 [following]\n",
      "--2022-08-23 08:49:13--  https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/36234516/HD2.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20220823/eu-west-1/s3/aws4_request&X-Amz-Date=20220823T064913Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=21232a3389137bcdbb4c7c0cf4fa1f27b58aeb1e4078b60f27c26b9453b552e4\n",
      "Resolving s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)... 52.92.0.88\n",
      "Connecting to s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)|52.92.0.88|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 18459732 (18M) [application/gzip]\n",
      "Saving to: ‘HD2.tar.gz’\n",
      "\n",
      "HD2.tar.gz          100%[===================>]  17.60M  14.5MB/s    in 1.2s    \n",
      "\n",
      "2022-08-23 08:49:15 (14.5 MB/s) - ‘HD2.tar.gz’ saved [18459732/18459732]\n",
      "\n"
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   "source": [
    "!wget -O HD2.tar.gz https://figshare.com/ndownloader/files/36234516\n",
    "!tar -xf HD2.tar.gz"
   ]
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   "source": [
    "When loading the data, we make sure to use a low resolution of 15 degrees, since we need to calculate a lot of individual spectra."
   ]
  },
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   "execution_count": 3,
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     "text": [
      "\u001b[94m================================================================================\u001b[0m\n",
      "\u001b[93m                             Welcome to gcm_toolkit\u001b[0m\n",
      "\u001b[94m================================================================================\u001b[0m\n",
      "\u001b[94m[STAT] Set up gcm_toolkit\u001b[0m\n",
      "\u001b[94m   [INFO] pressure units: bar\u001b[0m\n",
      "\u001b[94m   [INFO] time units: day\u001b[0m\n",
      "\u001b[94m[STAT] Read in raw MITgcm data\u001b[0m\n",
      "\u001b[94m   [INFO] File path: HD2_test/run\u001b[0m\n",
      "\u001b[94m   [INFO] Iterations: 38016000, 41472000\u001b[0m\n",
      "time needed to build regridder: 0.34761476516723633\n",
      "Regridder will use conservative method\n",
      "\u001b[94m   [INFO] Tag: HD2\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "data = 'HD2_test/run'   # path to data\n",
    "tools = GCMT(p_unit='bar', time_unit='day')  # create a GCMT object\n",
    "tools.read_raw('MITgcm', data, iters=\"all\", prefix=['T','U','V','W'], tag='HD2', d_lat=15, d_lon=15)"
   ]
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   "source": [
    "Lets make sure we setup petitRADTRANS to get going. We will do the calculation only in the IR range where spitzer is located. You can of cause do the phase curve also for a broader wavelengthcoverage, or with exo-k low resolution opacities."
   ]
  },
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   "execution_count": 4,
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Emission scattering is enabled: enforcing test_ck_shuffle_comp = True\n",
      "  Read line opacities of H2O_Exomol...\n",
      " Done.\n",
      "  Read line opacities of Na_allard...\n",
      " Done.\n",
      "  Read line opacities of K_allard...\n",
      " Done.\n",
      "  Read line opacities of CO2...\n",
      " Done.\n",
      "  Read line opacities of CH4...\n",
      " Done.\n",
      "  Read line opacities of NH3...\n",
      " Done.\n",
      "  Read line opacities of CO_all_iso_Chubb...\n",
      " Done.\n",
      "  Read line opacities of H2S...\n",
      " Done.\n",
      "  Read line opacities of HCN...\n",
      " Done.\n",
      "  Read line opacities of SiO...\n",
      " Done.\n",
      "  Read line opacities of PH3...\n",
      " Done.\n",
      "  Read line opacities of TiO_all_Exomol...\n",
      " Done.\n",
      "  Read line opacities of VO...\n",
      " Done.\n",
      "  Read line opacities of FeH...\n",
      " Done.\n",
      "\n",
      "  Read CIA opacities for H2-H2...\n",
      "  Read CIA opacities for H2-He...\n",
      "Done.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pRT = Radtrans(line_species=['H2O_Exomol', 'Na_allard', 'K_allard', 'CO2', 'CH4', 'NH3', 'CO_all_iso_Chubb', 'H2S', 'HCN', 'SiO', 'PH3', 'TiO_all_Exomol', 'VO', 'FeH'],\n",
    "               rayleigh_species=['H2', 'He'],\n",
    "               continuum_opacities=['H2-H2', 'H2-He', 'H-'],\n",
    "               wlen_bords_micron=[3.5, 4.6],\n",
    "               do_scat_emis=True)\n",
    "# Note: the pRT.setup_opa_structure is done by tools internally"
   ]
  },
  {
   "cell_type": "markdown",
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     "name": "#%% md\n"
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   },
   "source": [
    "Set some arguments for petitradtrans. Check the [docs](https://prt-phasecurve.readthedocs.io/en/latest/notebooks/tutorial.html#Creating-the-spectra) to see what arguments need to be set. The gravity can be obtained from the GCMT dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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   "source": [
    "MMW = const.R.si.value / 3590 * 1000\n",
    "Rstar = 1.203*const.R_sun.cgs.value\n",
    "Tstar = 6092.0\n",
    "semimajoraxis = (0.04747 * u.au).cgs.value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
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   },
   "source": [
    "Set the phases (from 0 to 1 is a full phasecurve, where 0.5 is the nightside and 0.0=1.0 is the dayside) for which you want to integrate the spectra.\n",
    "\n",
    "We also need to create the interface object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
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     "outputs_hidden": false
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    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "phases = np.linspace(0,1,50)\n",
    "interface = tools.get_prt_interface(pRT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Lets link the gcm data to the interface. At this point we also need to decide at which timestep we want to do the calculation. We decide here to use the latest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
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    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "interface.set_data(time=12000, tag='HD2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "We can now decide on the chemistry that we want to use. We currently only support pRTs poorman chemistry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "interface.chem_from_poorman('T', co_ratio=0.55, feh_ratio=0.0)  # the temperature key sets the gcm key used for the temperature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "We can now calculate the spectrum and save it to a file. This step will take some time, depending on the resolution that you chose."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
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    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████| 288/288 [09:34<00:00,  1.99s/it]\n"
     ]
    }
   ],
   "source": [
    "filename = 'spectrum.nc'\n",
    "interface.calc_phase_spectrum(mmw=MMW, filename=filename, Rstar=Rstar, Tstar=Tstar, semimajoraxis=semimajoraxis, normalize=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "The final planet to star flux ratio needs to be accounted for the planetary and stellar radii (see e.g., Sing et al. 2018, eq.2)\n",
    "\n",
    "$\\frac{\\Delta f}{f} = \\left(\\frac{R_\\mathrm{pla}}{R_\\mathrm{star}}\\right)^2 \\frac{F_\\mathrm{pla}}{F_\\mathrm{star}}$ \n",
    "\n",
    "`interface.calc_phase_spectrum` does this automatically for you. Set `normalize=False`, if you prefer the uncorrected spectrum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "ph = interface.phase_curve(phases,filename=filename)require"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Lets do some nice plots. Lets start with the emission spectra:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Dayside = phase == 0\n",
    "(ph*1e6).sel(phase=0).plot()\n",
    "plt.xscale('log')\n",
    "plt.yscale('linear')\n",
    "plt.xlim([3.5,4.6])\n",
    "plt.ylim([500,3000])\n",
    "plt.ylabel(r'$F_\\mathrm{pl}/F_\\mathrm{star}$ [ppm]')\n",
    "plt.xlabel('$\\lambda$ [$\\mu$m]')\n",
    "plt.title('Dayside emission spectrum')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Here are some phasecurves in the spitzer wavelengths:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 4.5 mu m plot\n",
    "l = 4.5\n",
    "\n",
    "(ph*1e6).interp(wlen=l).plot()\n",
    "plt.axvline(0.5, label='nightside', ls=':', color='black')\n",
    "plt.axvline(0.0, label='dayside', ls=':', color='orange')\n",
    "plt.xlabel('phase')\n",
    "plt.ylabel(r'$F_\\mathrm{pl}/F_\\mathrm{star}$ [ppm]')\n",
    "plt.title(r'Phasecurve at {:.2f}$\\mu$m'.format(l))\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# 3.6 mu m plot\n",
    "l = 3.6\n",
    "(ph*1e6).interp(wlen=l).plot()\n",
    "plt.axvline(0.5, label='nightside', ls=':', color='black')\n",
    "plt.axvline(0.0, label='dayside', ls=':', color='orange')\n",
    "plt.xlabel('phase')\n",
    "plt.ylabel(r'$F_\\mathrm{pl}/F_\\mathrm{star}$ [ppm]')\n",
    "plt.title(r'Phasecurve at {:.2f}$\\mu$m'.format(l))\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transit Spectrum\n",
    "\n",
    "Next we show how to calculate a transmission spectrum using the petitRADTRANS interface of gcm_toolkit. We use the same data as for the phase curve and start by setting up gcm_toolkit and petitRADTRANS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2023-02-27 06:45:38--  https://figshare.com/ndownloader/files/36234516\n",
      "Resolving figshare.com (figshare.com)... 34.252.222.205, 54.217.34.18, 2a05:d018:1f4:d000:647c:7301:fad1:b2b9, ...\n",
      "Connecting to figshare.com (figshare.com)|34.252.222.205|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/36234516/HD2.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20230227/eu-west-1/s3/aws4_request&X-Amz-Date=20230227T054538Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=f3173652eeecb44749cd6f18cb6c495b531eb4216ce94dfcc78c32d0155e5df1 [following]\n",
      "--2023-02-27 06:45:38--  https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/36234516/HD2.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIYCQYOYV5JSSROOA/20230227/eu-west-1/s3/aws4_request&X-Amz-Date=20230227T054538Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=f3173652eeecb44749cd6f18cb6c495b531eb4216ce94dfcc78c32d0155e5df1\n",
      "Resolving s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)... 52.218.29.83, 52.218.120.72, 52.218.36.82, ...\n",
      "Connecting to s3-eu-west-1.amazonaws.com (s3-eu-west-1.amazonaws.com)|52.218.29.83|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 18459732 (18M) [application/gzip]\n",
      "Saving to: ‘HD2.tar.gz’\n",
      "\n",
      "HD2.tar.gz          100%[===================>]  17.60M  2.34MB/s    in 5.7s    \n",
      "\n",
      "2023-02-27 06:45:44 (3.10 MB/s) - ‘HD2.tar.gz’ saved [18459732/18459732]\n",
      "\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.FinderInfo'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.lastuseddate#PS'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.FinderInfo'\n",
      "tar: Ignoring unknown extended header keyword 'SCHILY.fflags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'LIBARCHIVE.xattr.com.apple.metadata:_kMDItemUserTags'\n",
      "tar: Ignoring unknown extended header keyword 'SCHILY.fflags'\n",
      "\u001b[94m================================================================================\u001b[0m\n",
      "\u001b[93m                             Welcome to gcm_toolkit\u001b[0m\n",
      "\u001b[94m================================================================================\u001b[0m\n",
      "\u001b[94m[STAT] Set up gcm_toolkit\u001b[0m\n",
      "\u001b[94m   [INFO] pressure units: bar\u001b[0m\n",
      "\u001b[94m   [INFO] time units: day\u001b[0m\n",
      "\u001b[94m[STAT] Read in raw MITgcm data\u001b[0m\n",
      "\u001b[94m   [INFO] File path: HD2_test/run\u001b[0m\n",
      "\u001b[94m   [INFO] Iterations: 41472000, 38016000\u001b[0m\n",
      "time needed to build regridder: 2.923800468444824\n",
      "Regridder will use conservative method\n",
      "\u001b[94m   [INFO] Tag: HD2\u001b[0m\n",
      "  Read line opacities of H2O_Exomol...\n",
      " Done.\n",
      "  Read line opacities of Na_allard...\n",
      " Done.\n",
      "  Read line opacities of K_allard...\n",
      " Done.\n",
      "  Read line opacities of CO2...\n",
      " Done.\n",
      "  Read line opacities of CH4...\n",
      " Done.\n",
      "  Read line opacities of NH3...\n",
      " Done.\n",
      "  Read line opacities of CO_all_iso_Chubb...\n",
      " Done.\n",
      "  Read line opacities of H2S...\n",
      " Done.\n",
      "  Read line opacities of HCN...\n",
      " Done.\n",
      "  Read line opacities of SiO...\n",
      " Done.\n",
      "  Read line opacities of PH3...\n",
      " Done.\n",
      "  Read line opacities of TiO_all_Exomol...\n",
      " Done.\n",
      "  Read line opacities of VO...\n",
      " Done.\n",
      "  Read line opacities of FeH...\n",
      " Done.\n",
      "\n",
      "  Read CIA opacities for H2-H2...\n",
      "  Read CIA opacities for H2-He...\n",
      " Done.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# get data\n",
    "!wget -O HD2.tar.gz https://figshare.com/ndownloader/files/36234516\n",
    "!tar -xf HD2.tar.gz\n",
    "\n",
    "# initialise gcm_tookit\n",
    "data = 'HD2_test/run'   # path to data\n",
    "tools = GCMT(p_unit='bar', time_unit='day')  # create a GCMT object\n",
    "tools.read_raw('MITgcm', data, iters=\"all\", prefix=['T','U','V','W'], tag='HD2', d_lat=1, d_lon=1)\n",
    "\n",
    "# initialise petitRADTRANS\n",
    "pRT = Radtrans(line_species=['H2O_Exomol', 'Na_allard', 'K_allard', 'CO2', 'CH4', 'NH3', 'CO_all_iso_Chubb', 'H2S', 'HCN', 'SiO', 'PH3', 'TiO_all_Exomol', 'VO', 'FeH'],\n",
    "               rayleigh_species=['H2', 'He'],\n",
    "               continuum_opacities=['H2-H2', 'H2-He', 'H-'],\n",
    "               wlen_bords_micron=[0.3, 10])\n",
    "\n",
    "# connect petitRADTRANS and gcm_toolkit\n",
    "interface = tools.get_prt_interface(pRT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To calculate a transit spectrum, the data has to be prepared. For this, we use the set_data function by setting terminator_avg to True. Furthermore, we need to decide the longitudinal opening angle. This will define over which longitudinal angle around the terminators the temperature will be averaged. Furthermore, we need to set the number of latitudinal points per terminator. For each of this point, a transmission spectrum will be calculated and averaged for the final spectrum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "interface.set_data(time=12000, tag='HD2', terminator_avg=True, lat_points=1, lon_resolution=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, the chemistry needs to be calculated. This again is the same as for the phase curve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "interface.chem_from_poorman('T', co_ratio=0.55, feh_ratio=0.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After everything is set up, the transit spectrum can be calculated using the calc_transit_spoectrum function. The only remaining parameter that needs to be given is the mean molecular weight of the atmosphere.\n",
    "\n",
    "**Note:** The wavelength is given in micron and the spectra is the planet radius in cm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:         (lon: 2, lat: 1, Z: 47)\n",
      "Coordinates:\n",
      "  * lon             (lon) int64 -90 90\n",
      "  * lat             (lat) float64 0.0\n",
      "  * Z               (Z) float64 650.0 550.0 450.0 ... 3.633e-05 2.471e-05 1e-05\n",
      "Data variables: (12/23)\n",
      "    T               (lon, lat, Z) float64 4e+03 4e+03 ... 1.227e+03 1.391e+03\n",
      "    H2              (lon, lat, Z) float64 0.7128 0.7106 0.7078 ... 0.7381 0.7374\n",
      "    He              (lon, lat, Z) float64 0.2495 0.2495 0.2495 ... 0.2495 0.2495\n",
      "    CO              (lon, lat, Z) float64 0.004843 0.004976 ... 0.005521\n",
      "    H2O             (lon, lat, Z) float64 0.003063 0.002967 ... 0.002459\n",
      "    HCN             (lon, lat, Z) float64 7.453e-05 6.743e-05 ... 2.196e-12\n",
      "    ...              ...\n",
      "    e-              (lon, lat, Z) float64 1.339e-10 1.448e-10 ... 1.546e-12\n",
      "    H-              (lon, lat, Z) float64 5.911e-08 5.861e-08 ... 2.002e-16\n",
      "    H               (lon, lat, Z) float64 0.02501 0.02719 ... 0.0005425\n",
      "    FeH             (lon, lat, Z) float64 0.0001677 0.0001554 ... 2.58e-09\n",
      "    MMW             (lon, lat, Z) float64 2.266 2.261 2.253 ... 2.331 2.324 2.33\n",
      "    nabla_ad        (lon, lat, Z) float64 0.1711 0.1682 0.1647 ... 0.2765 0.246\n",
      "Attributes:\n",
      "    p_unit:   bar\n",
      "<xarray.Dataset>\n",
      "Dimensions:         (lon: 2, lat: 1, Z: 47)\n",
      "Coordinates:\n",
      "  * lon             (lon) int64 -90 90\n",
      "  * lat             (lat) float64 0.0\n",
      "  * Z               (Z) float64 650.0 550.0 450.0 ... 3.633e-05 2.471e-05 1e-05\n",
      "Data variables: (12/23)\n",
      "    T               (lon, lat, Z) float64 4e+03 4e+03 ... 1.227e+03 1.391e+03\n",
      "    H2              (lon, lat, Z) float64 0.7128 0.7106 0.7078 ... 0.7381 0.7374\n",
      "    He              (lon, lat, Z) float64 0.2495 0.2495 0.2495 ... 0.2495 0.2495\n",
      "    CO              (lon, lat, Z) float64 0.004843 0.004976 ... 0.005521\n",
      "    H2O             (lon, lat, Z) float64 0.003063 0.002967 ... 0.002459\n",
      "    HCN             (lon, lat, Z) float64 7.453e-05 6.743e-05 ... 2.196e-12\n",
      "    ...              ...\n",
      "    e-              (lon, lat, Z) float64 1.339e-10 1.448e-10 ... 1.546e-12\n",
      "    H-              (lon, lat, Z) float64 5.911e-08 5.861e-08 ... 2.002e-16\n",
      "    H               (lon, lat, Z) float64 0.02501 0.02719 ... 0.0005425\n",
      "    FeH             (lon, lat, Z) float64 0.0001677 0.0001554 ... 2.58e-09\n",
      "    MMW             (lon, lat, Z) float64 2.266 2.261 2.253 ... 2.331 2.324 2.33\n",
      "    nabla_ad        (lon, lat, Z) float64 0.1711 0.1682 0.1647 ... 0.2765 0.246\n",
      "Attributes:\n",
      "    p_unit:   bar\n"
     ]
    }
   ],
   "source": [
    "wave, spectra = interface.calc_transit_spectrum(2.33)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The final transmission spectrum is shown below. We divided by the radius of Jupiter to give the transit depth in Jupiter radii."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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": [
    "plt.figure()\n",
    "plt.plot(wave, spectra/6991100000)\n",
    "plt.xscale('log')\n",
    "plt.xlabel('Wavelength [micron]')\n",
    "plt.ylabel('Transit radius [R$_J$]')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}