{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c0e2d1b2-9d9b-49d2-bbaf-f2a6b9d3dd44",
   "metadata": {},
   "source": [
    "# Exoplanets: primary transit\n",
    "\n",
    "In this example, we show how archNEMESIS can be used to construct input files and calculate forward models useful for exoplanet primary transit observations. Here, we show an example of how to initialise all the classes from scratch, so that users can adapt the notebook according to their own needs. The planet is assumed not to have aerosols, but this can be easily adapted to include these features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d6cb5c1a-c963-438e-8edf-a9171a786418",
   "metadata": {},
   "outputs": [],
   "source": [
    "import archnemesis as ans\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "012e6e10-607a-4a3d-a13e-fbe67f742cd9",
   "metadata": {},
   "source": [
    "## 1. Creating the input files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dadeacb6-0d8e-47d4-b619-b56c047d99f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "runname = \"exoplanet\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4532c906-489c-44e6-9556-11fb0731377d",
   "metadata": {},
   "source": [
    "### Defining planet characteristics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8275e64c-baf7-4a68-9e91-6e221c6793d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Astronomical constants\n",
    "AU = 1.495978707e+11      # m astronomical unit\n",
    "R_SUN = 6.95700e8         # m solar radius\n",
    "R_JUP = 6.9911e7          # m Jupiter radius\n",
    "R_JUP_E = 7.1492e7        # m nominal equatorial Jupiter radius\n",
    "M_SUN = 1.98847542e+30    # kg solar mass\n",
    "M_JUP = 1.898e27          # kg Jupiter mass\n",
    "R_EAR_E = 6.3781e6          # m Earth radius\n",
    "M_EAR = 5.9722e24         # kg Earth mass\n",
    "G = 6.6743e-11            # m3 kg-1 s-2 Gravitational constant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9a84c83c-769c-4153-a8f0-ad83495303de",
   "metadata": {},
   "outputs": [],
   "source": [
    "# L98-59 d\n",
    "R_star = 0.303 * R_SUN # m M3V star, 80 day rotation period, >0.8 Gyr\n",
    "M_plt = 1.94 * M_EAR # kg\n",
    "R_plt = 1.521 * R_EAR_E # m\n",
    "SMA = 0.0486 * AU # m\n",
    "T_star = 3415.0 # K\n",
    "g_plt = G * M_plt / R_plt**2\n",
    "T_eq = T_star * (R_star/(2*SMA))**0.5\n",
    "T_int = 200.0 # randomly set"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3991b9b-acd1-4ca3-b103-bcec537c04ad",
   "metadata": {},
   "source": [
    "### 1.2. Atmosphere"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "54af8066-cc9f-450a-b639-6828722d1f95",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Atmosphere = ans.Atmosphere_0()\n",
    "\n",
    "Atmosphere.NP = 50   #Number of points in vertical profiles\n",
    "Atmosphere.LATITUDE = 0. ; Atmosphere.LONGITUDE = 0.\n",
    "Atmosphere.IPLANET = -1  #Custom planet\n",
    "\n",
    "#Planetary parameters\n",
    "Atmosphere.PLANET_MASS = M_plt\n",
    "Atmosphere.PLANET_RADIUS = R_plt / 1.0e3  #km\n",
    "\n",
    "#Defining the pressure profile\n",
    "Atmosphere.edit_P(np.logspace(1, -7, Atmosphere.NP) * 101325.) # in Pa\n",
    "Atmosphere.edit_H(np.linspace(0.,100.,Atmosphere.NP) * 1.0e3) # dummy height profile (it will be calculated hydrostatically)\n",
    "\n",
    "#Defining the gaseous abundances\n",
    "gasID = np.array([1,2,5,11,6, 9,23,26,39,40],dtype='int32') #H2O,CO2,CO,NH3,CH4,SO2,HCN,C2H2,H2(inactive),He(inactive)\n",
    "isoID = np.zeros(len(gasID),dtype='int32')\n",
    "\n",
    "abundances_active = np.array([1.0e-3, 1.0e-4, 1.0e-3, 1.0e-4, 1.0e-2, 1.0e-3, 1.0e-8, 1.0e-6])\n",
    "abundance_inactive = 1. - np.sum(abundances_active)\n",
    "h2_frac = 0.8547\n",
    "h2_vmr = abundance_inactive * h2_frac ; he_vmr = abundance_inactive * (1. - h2_frac)\n",
    "abundances = np.zeros(len(gasID))\n",
    "abundances[0:len(abundances_active)] = abundances_active\n",
    "abundances[-2] = h2_vmr\n",
    "abundances[-1] = he_vmr\n",
    "\n",
    "Atmosphere.NVMR = len(gasID)\n",
    "Atmosphere.ID = gasID\n",
    "Atmosphere.ISO = isoID\n",
    "\n",
    "vmr = np.zeros((Atmosphere.NP,Atmosphere.NVMR))\n",
    "vmr[:,:] = abundances[None,:]\n",
    "Atmosphere.edit_VMR(vmr)\n",
    "Atmosphere.AMFORM = 2  #Molecular weight calculated internally based on gaseous abundances\n",
    "Atmosphere.calc_molwt()\n",
    "\n",
    "#Calculating the temperature profile using the parameterisation of Parmentier and Guillot (2014)\n",
    "k, g1, g2, alpha, beta = 1.0e-2, 1.0e1, 1.0e1, 0.5, 1.0\n",
    "Atmosphere, xmap = ans.Models[43].calculate(Atmosphere,alpha,beta,k,g1,g2,T_star,R_star,SMA,T_int)\n",
    "\n",
    "#Calculating altitudes based on hydrostatic equilibrium equation\n",
    "Atmosphere.adjust_hydrostatH()\n",
    "\n",
    "#Calculating the aerosols in the atmosphere (no clouds)\n",
    "Atmosphere.NDUST = 1\n",
    "dust = np.zeros((Atmosphere.NP,Atmosphere.NDUST))   #m-3\n",
    "Atmosphere.edit_DUST(dust)\n",
    "\n",
    "Atmosphere.assess()\n",
    "Atmosphere.plot_Atm()\n",
    "Atmosphere.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7e65f97-ccb0-4e95-b156-827a13eed5df",
   "metadata": {},
   "source": [
    "### 1.2. Spectroscopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f06c74bd-d718-4824-b390-e54c2ed13c3a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING :: read_header :: Spectroscopy_0.py-564 :: self.NGAS=8 self.LOCATION=PathRedirectList(['/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/H2O_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/CO2_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/CO_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/NH3_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/CH4_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/SO2_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/HCN_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/C2H2_R1000.kta'], redirects = {})\n",
      "INFO :: summary_info :: Spectroscopy_0.py-233 :: Calculation type ILBL ::  (<SpectralCalculationMode.K_TABLES: 0>, ' (k-distribution)')\n",
      "INFO :: summary_info :: Spectroscopy_0.py-234 :: Number of radiatively-active gaseous species ::  8\n",
      "INFO :: summary_info :: Spectroscopy_0.py-241 :: Gaseous species ::  ['H2O', 'CO2', 'CO', 'NH3', 'CH4', 'SO2', 'HCN', 'H2O']\n",
      "INFO :: summary_info :: Spectroscopy_0.py-243 :: Number of g-ordinates ::  20\n",
      "INFO :: summary_info :: Spectroscopy_0.py-245 :: Number of spectral points ::  5119\n",
      "INFO :: summary_info :: Spectroscopy_0.py-246 :: Wavelength range ::  (0.3001500070095062, '-', 49.997337341308594)\n",
      "INFO :: summary_info :: Spectroscopy_0.py-247 :: Step size ::  0.0003001391887664795\n",
      "INFO :: summary_info :: Spectroscopy_0.py-249 :: Spectral resolution of the k-tables (FWHM) ::  0.0\n",
      "INFO :: summary_info :: Spectroscopy_0.py-251 :: Number of temperature levels ::  27\n",
      "INFO :: summary_info :: Spectroscopy_0.py-252 :: Temperature range ::  (100.0, '-', 3400.0)\n",
      "INFO :: summary_info :: Spectroscopy_0.py-254 :: Number of pressure levels ::  22\n",
      "INFO :: summary_info :: Spectroscopy_0.py-255 :: Pressure range ::  (1e-05, '-', 100.0)\n"
     ]
    }
   ],
   "source": [
    "#Initialising spectroscopy class with ILBL = 0 (k-tables)\n",
    "Spectroscopy = ans.Spectroscopy_0(ILBL=0)\n",
    "\n",
    "Spectroscopy.NGAS = 8  #Number of radiatively active gases\n",
    "specdir = '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/'\n",
    "Spectroscopy.LOCATION = [specdir+'H2O_R1000.kta',\n",
    "                         specdir+'CO2_R1000.kta',\n",
    "                         specdir+'CO_R1000.kta',\n",
    "                         specdir+'NH3_R1000.kta',\n",
    "                         specdir+'CH4_R1000.kta',\n",
    "                         specdir+'SO2_R1000.kta',\n",
    "                         specdir+'HCN_R1000.kta',\n",
    "                         specdir+'C2H2_R1000.kta']\n",
    "\n",
    "#Reading the header information\n",
    "Spectroscopy.read_header()\n",
    "\n",
    "#Printing summary information\n",
    "Spectroscopy.summary_info()\n",
    "Spectroscopy.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cda61fd1-90b9-46d2-b95a-bff9a76ed3be",
   "metadata": {},
   "source": [
    "### 1.3. Measurement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "542c5693-d779-4b06-9940-ed7bb41377dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO :: summary_info :: Measurement_0.py-422 :: Spectral resolution of the measurement is account for in the k-tables\n",
      "INFO :: summary_info :: Measurement_0.py-432 :: Field-of-view centered at ::  ('Latitude', 0.0, '- Longitude', 0.0)\n",
      "INFO :: summary_info :: Measurement_0.py-433 :: There are  (1, 'geometries in the measurement vector')\n",
      "INFO :: summary_info :: Measurement_0.py-435 :: \n",
      "INFO :: summary_info :: Measurement_0.py-436 :: GEOMETRY 1\n",
      "INFO :: summary_info :: Measurement_0.py-437 :: Minimum wavelength/wavenumber :: 0.5002095103263855 um/19991.623097039927 cm^-1 - Maximum wavelength/wavenumber :: 34.993003845214844 um/285.77140860022115 cm^-1\n",
      "INFO :: summary_info :: Measurement_0.py-466 :: Limb-viewing or solar occultation measurement. Latitude ::  (0.0, ' - Longitude :: ', 0.0, ' - Tangent height :: ', 0.0)\n"
     ]
    }
   ],
   "source": [
    "#Initialising the class\n",
    "Measurement = ans.Measurement_0()\n",
    "\n",
    "Measurement.ISPACE = 1  #Wavelength (um)\n",
    "Measurement.NGEOM = 1   #Number of geometries (just one spectrum)\n",
    "Measurement.FWHM = 0.0  #Assuming no instrumental broadening\n",
    "Measurement.IFORM = 2   #Transit depth (Area_planet/Area_star*100)\n",
    "\n",
    "#Defining the spectral range\n",
    "vmin = 0.5 ; vmax = 35.\n",
    "vconvx = Spectroscopy.WAVE[ (Spectroscopy.WAVE>=vmin) & (Spectroscopy.WAVE<=vmax) ]\n",
    "nconvx = len(vconvx)\n",
    "\n",
    "vconv = np.zeros((nconvx,Measurement.NGEOM))\n",
    "vconv[:,0] = vconvx\n",
    "\n",
    "Measurement.NCONV = np.zeros(Measurement.NGEOM,dtype='int32') + nconvx\n",
    "Measurement.edit_VCONV(vconv)\n",
    "Measurement.edit_MEAS(np.ones(vconv.shape))     #Dummy arrays for the measured spectrum since we are only simulating\n",
    "Measurement.edit_ERRMEAS(np.ones(vconv.shape))  \n",
    "\n",
    "#Initialising the arrays with the geometry (not important for primary transits since it is accounted for in the forward model)\n",
    "Measurement.calc_geometry_primary_transit()\n",
    "\n",
    "#Checking that everything is consistent\n",
    "Measurement.summary_info()\n",
    "\n",
    "#Writing file\n",
    "Measurement.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce29982c-9fd9-43a4-86af-e27c7341845b",
   "metadata": {},
   "source": [
    "### 1.4. Surface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "341d560c-cdde-4e81-b0d0-216a60e9d6c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Initialising and creating dummy surface class\n",
    "Surface = ans.Surface_0()\n",
    "Surface.GASGIANT = True   #No surface\n",
    "Surface.TSURF = 0.0\n",
    "Surface.GALB = 0.0\n",
    "Surface.LOWBC = 0\n",
    "Surface.assess()\n",
    "Surface.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7f87cff-fc09-41f8-8d8d-0bd9dcf90723",
   "metadata": {},
   "source": [
    "### 1.5. Scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4f2f6fe0-c21d-4b2c-87ec-b6effa228e89",
   "metadata": {},
   "outputs": [],
   "source": [
    "Scatter = ans.Scatter_0()\n",
    "Scatter.ISCAT = 0   #No scattering\n",
    "\n",
    "#Now we initialise the arrays, but they won't be used since there are no aerosols in the atmosphere\n",
    "Scatter.initialise_arrays(NDUST=1,NWAVE=2,NTHETA=5)\n",
    "Scatter.WAVE = np.linspace(Spectroscopy.WAVE.min(),Spectroscopy.WAVE.max(),Scatter.NWAVE)\n",
    "Scatter.assess()\n",
    "Scatter.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75d57ed3-feca-4388-813d-93a583e9c9eb",
   "metadata": {},
   "source": [
    "### 1.6. CIA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "64aa419e-a5c2-48c9-ad82-160ef2d7cbb5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Initialising the CIA class\n",
    "CIA = ans.CIA_0()\n",
    "\n",
    "#Indicating the name of the CIA file\n",
    "CIA.CIATABLE = \"exocia_hitran12_200-3800K.h5\"\n",
    "\n",
    "#Writing information to file\n",
    "CIA.assess()\n",
    "CIA.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72f751e1-2143-44b5-bd6c-28cacd9137a6",
   "metadata": {},
   "source": [
    "### 1.7. Stellar spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3d0e1f5f-b663-458b-8e33-7ed9edcd2b09",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Initialising class\n",
    "Stellar = ans.Stellar_0()\n",
    "\n",
    "#Defining the planet-star distance\n",
    "Stellar.DIST = SMA / AU   #Star-Planet distance (AU)\n",
    "\n",
    "#Writing the information into HDF5 file\n",
    "Stellar.write_hdf5(runname,solfile='solar_noaa_wl_2024.txt')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9519b19b-837f-4e71-983c-4f2aebf2d88a",
   "metadata": {},
   "source": [
    "### 1.8. Layering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dafca33c-0db7-4940-a071-d3dc9b9121ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Initialising class\n",
    "Layer = ans.Layer_0()\n",
    "\n",
    "Layer.NLAY =  31     #Number of atmospheric layers\n",
    "Layer.LAYHT = 0.0    #Altitude of lowest layer in atmosphere\n",
    "Layer.LAYINT = 1     #Curtis-Godson layer integration\n",
    "Layer.LAYTYP = 1     #Layers divided by equal changes in log(pressure)\n",
    "\n",
    "Layer.write_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4557f5bb-dbfd-4175-8add-8308e2a40005",
   "metadata": {},
   "source": [
    "### 1.9. Retrieval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "910d0b59-3e22-4d89-a6bc-5c3bb29c20c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "Retrieval = ans.OptimalEstimation_0(IRET=0)\n",
    "\n",
    "Retrieval.NITER = -1       #Number of iterations\n",
    "Retrieval.PHILIMIT = 0.1   #Convergence criterion\n",
    "Retrieval.NCORES = 1       #Number of available cores\n",
    "\n",
    "Retrieval.assess_input()\n",
    "Retrieval.write_input_hdf5(runname)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f0a1e02-2058-454c-8519-912f05289527",
   "metadata": {},
   "source": [
    "### 1.10. Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a562dcd1-a1a2-4775-a948-a895c53b7bed",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Retrieving a scaling factor for the CO2 abundance\n",
    "f = open(runname+\".apr\",\"w\")\n",
    "\n",
    "NVAR = 1\n",
    "\n",
    "f.write(\"#Exoplanet example \\n\")\n",
    "f.write(str(NVAR)+\" \\n\")\n",
    "f.write(\"2 0 2 \\n\")\n",
    "f.write(\"1.0 0.5 \\n\")\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83ae4520-aaa4-4c8d-8493-58e5cd930344",
   "metadata": {},
   "source": [
    "## 2. Running forward model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8dd21501-808e-437e-aabc-aad7f6c0073d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING :: read_hdf5 :: Layer_0.py-379 :: When reading file \"exoplanet.h5\", could not find element \"Layer/BASEH\" setting returned value to \"None\"\n",
      "WARNING :: read_hdf5 :: Layer_0.py-380 :: When reading file \"exoplanet.h5\", could not find element \"Layer/BASEP\" setting returned value to \"None\"\n",
      "WARNING :: read_hdf5 :: Layer_0.py-381 :: When reading file \"exoplanet.h5\", could not find element \"Layer/TAUTOT\" setting returned value to \"None\"\n",
      "WARNING :: read_header :: Spectroscopy_0.py-564 :: self.NGAS=8 self.LOCATION=PathRedirectList(['/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/H2O_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/CO2_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/CO_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/NH3_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/CH4_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/SO2_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/HCN_R1000.kta', '/exomars/retrievals/nemesis/spectroscopy/Ktables/Exoplanets/Jake/R1000/C2H2_R1000.kta'], redirects = {})\n",
      "INFO :: read_apr :: Variables_0.py-823 :: \n",
      "Variables_0 :: read_apr :: varident [2 0 2]. Constructed model \"Model2\" (id=2)\n",
      "INFO :: read_apr :: Variables_0.py-826 ::   Model2:\n",
      "  |- id : 2\n",
      "  |- parent classes: PreRTModelBase\n",
      "  |- description: In this model, the atmospheric parameters are scaled using a\n",
      "  |               single factor with  respect to the vertical profiles in the\n",
      "  |               reference atmosphere\n",
      "  |- n_state_vector_entries : 1\n",
      "  |- state_vector_slice : slice(0, 1, None)\n",
      "  |- state_vector_start : 0\n",
      "  |- target : 0\n",
      "  |- Parameters:\n",
      "  |  |- scaling_factor :\n",
      "  |  |  |- slice : slice(0, 1, None)\n",
      "  |  |  |- unit : PROFILE_TYPE\n",
      "  |  |  |- description: Scaling factor applied to the reference profile\n",
      "  |  |  |- apriori value : 1.0\n"
     ]
    }
   ],
   "source": [
    "#Reading the input files\n",
    "Atmosphere,Measurement,Spectroscopy,Scatter,Stellar,Surface,CIA,Layer,Variables,Retrieval,Telluric = ans.Files.read_input_files_hdf5(runname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d0296083-f23c-4f75-ae0c-8736741cfbb3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO :: __init__ :: ForwardModel_0.py-256 :: Checking atmospheric gasses have spectroscopy data.\n",
      "WARNING :: __init__ :: ForwardModel_0.py-303 :: Not all atmospheric gasses have spectroscopy data.\n",
      "# WARNING #########################################################################\n",
      "\n",
      "The following atmospheric gasses ARE NOT PRESENT in the spectroscopy data and WILL NOT CONTRIBUTE TO OPACITY:\n",
      "\n",
      "    C2H2 (id 26) isotopologue 0\n",
      "    H2 (id 39) isotopologue 0\n",
      "    He (id 40) isotopologue 0\n",
      "\n",
      "To deactivate this warning place a path to a k-table file for these gasses in one of the following locations (depending upon your input file type):\n",
      "\n",
      "    [HDF5 Input]\n",
      "        In the \"wasp121.h5\" file, add an entry to \"/Spectroscopy/LOCATION\"\n",
      "        and update \"/Spectroscopy/NGAS\" appropriately.\n",
      "\n",
      "    [LEGACY Input]\n",
      "        Add an entry to the \"wasp121.kls\" file.\n",
      "\n",
      "# END WARNING #####################################################################\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1809 :: Calculating forward model for primary transit observation\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1837 :: Running CIRSrad for primary transit observation\n",
      "INFO :: calculate_vertical_cia_opacity :: ForwardModel_0.py-3765 :: Calculating self.CIAX opacity\n",
      "WARNING :: calc_tau_cia :: ForwardModel_0.py-4336 ::  in CIA :: Calculation wavelengths expand a larger range than in CIA table\n",
      "INFO :: calculate_layer_opacity :: ForwardModel_0.py-3834 :: CIRSrad :: Aerosol optical depths at  (0.5002095103263855, ' :: ', array([0.]))\n",
      "INFO :: calculate_layer_opacity :: ForwardModel_0.py-3852 :: Calculating TOTAL opacity\n",
      "INFO :: calculate_layer_opacity :: ForwardModel_0.py-3869 :: CIRSradg :: Calculating TOTAL line-of-sight opacity\n",
      "INFO :: CIRSrad :: ForwardModel_0.py-4201 :: CIRSrad :: IMODM = <PathCalc.PLANCK_FUNCTION_AT_BIN_CENTRE: 8192>\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1890 :: Convolving spectra and gradients with instrument line shape\n"
     ]
    }
   ],
   "source": [
    "ForwardModel = ans.ForwardModel_0(Atmosphere=Atmosphere,Surface=Surface,Measurement=Measurement,Spectroscopy=Spectroscopy,Stellar=Stellar,Scatter=Scatter,CIA=CIA,Layer=Layer,Variables=Variables,Telluric=Telluric)\n",
    "\n",
    "SPECONV = ForwardModel.nemesisPTfm()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3db7cc36-e6a8-4622-9d05-e87184db6593",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax1 = plt.subplots(1,1,figsize=(10,4))\n",
    "\n",
    "ax1.plot(Measurement.VCONV[:,0],SPECONV,c='black',linewidth=1.)\n",
    "ax1.grid()\n",
    "ax1.set_xlabel('Wavelength ($\\mu$m)')\n",
    "ax1.set_ylabel('Transit depth (%)')\n",
    "ax1.set_facecolor('lightgray')\n",
    "plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80354125-eb34-4d0c-88b2-ee00206dde8d",
   "metadata": {},
   "source": [
    "## 3. Calculating Jacobian matrix\n",
    "\n",
    "In this example we show how we can calculate the Jacobian matrix as for any other forward model type using the functionality of the ForwardModel class. Here, since we have indicated that the parameter in the state vector is a scaling factor for the CO$_2$ abundance, the Jacobian matrix will only have one element, showing the sensitivity to the CO$_2$ abundance. The Jacobian matrix for any other models can be calculated just by specifying the information in the .apr file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c5983475-7e70-4237-96e1-e2d4e2a48fc9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO :: jacobian_nemesis :: ForwardModel_0.py-2191 :: Calculating analytical part of the Jacobian :: Calling nemesisfmg \n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1809 :: Calculating forward model for primary transit observation\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1840 :: Running CIRSradg for primary transit observation\n",
      "INFO :: calculate_vertical_cia_opacity :: ForwardModel_0.py-3765 :: Calculating self.CIAX opacity\n",
      "WARNING :: calc_tau_cia :: ForwardModel_0.py-4336 ::  in CIA :: Calculation wavelengths expand a larger range than in CIA table\n",
      "INFO :: calculate_layer_opacity :: ForwardModel_0.py-3834 :: CIRSrad :: Aerosol optical depths at  (0.5002095103263855, ' :: ', array([0.]))\n",
      "INFO :: calculate_layer_opacity :: ForwardModel_0.py-3852 :: Calculating TOTAL opacity\n",
      "INFO :: calculate_layer_opacity :: ForwardModel_0.py-3869 :: CIRSradg :: Calculating TOTAL line-of-sight opacity\n",
      "INFO :: CIRSrad :: ForwardModel_0.py-4201 :: CIRSrad :: IMODM = <PathCalc.PLANCK_FUNCTION_AT_BIN_CENTRE: 8192>\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1844 :: Mapping gradients from Layer to Profile\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1856 :: Mapping gradients from Profile to State Vector\n",
      "INFO :: nemesisPTfm :: ForwardModel_0.py-1890 :: Convolving spectra and gradients with instrument line shape\n"
     ]
    }
   ],
   "source": [
    "ForwardModel = ans.ForwardModel_0(Atmosphere=Atmosphere,Surface=Surface,Measurement=Measurement,Spectroscopy=Spectroscopy,Stellar=Stellar,Scatter=Scatter,CIA=CIA,Layer=Layer,Variables=Variables,Telluric=Telluric)\n",
    "\n",
    "YN,KK = ForwardModel.jacobian_nemesis(nemesisPT=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "64731509-a1b0-4e47-b18f-85f63cf11df8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2) = plt.subplots(2,1,figsize=(10,6),sharex=True)\n",
    "\n",
    "ax1.plot(Measurement.VCONV[:,0],YN,c='black',linewidth=1.)\n",
    "ax1.grid()\n",
    "ax2.plot(Measurement.VCONV[:,0],KK,c='black',linewidth=1.)\n",
    "ax2.grid()\n",
    "ax2.set_xlabel('Wavelength ($\\mu$m)')\n",
    "ax1.set_ylabel('Transit depth (%)')\n",
    "ax2.set_ylabel('Jacobian matrix (dR/dx)')\n",
    "ax1.set_facecolor('lightgray')\n",
    "ax2.set_facecolor('lightgray')\n",
    "plt.tight_layout()"
   ]
  }
 ],
 "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": "3.11.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}