{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the notebook `LSS_AGN-01_preparation` we prepared a simulated data cube of an AGN for \"observation\" with Scopesim/METIS. If you do not have the files `AGN_sim_prepared.fits` and `AGN_sim_rotated_50.fits`, please run the first notebook before proceeding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib.colors import LogNorm\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scopesim as sim\n",
    "sim.bug_report()\n",
    "\n",
    "# Edit this path if you have a custom install directory, otherwise comment it out. [For ReadTheDocs only]\n",
    "sim.rc.__config__[\"!SIM.file.local_packages_path\"] = \"../../../\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you haven't got the instrument packages yet, uncomment the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sim.download_package([\"instruments/METIS\", \"telescopes/ELT\", \"locations/Armazones\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cmd = sim.UserCommands(use_instrument=\"METIS\", set_modes=['lss_n'],\n",
    "                      properties={\"!OBS.exptime\": 3600,\n",
    "                                 \"!SIM.spectral.spectral_bin_width\": 3.0e-3})\n",
    "metis = sim.OpticalTrain(cmd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create two `Source` objects from the files. The first one is with the original field orientation, the second one has the field rotated by 50 degrees. We also define a `Source` that represents blank sky for background subtraction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cube_01 = \"AGN_sim_prepared.fits\"\n",
    "cube_02 = \"AGN_sim_rotated_50.fits\"\n",
    "\n",
    "src_01 = sim.Source(cube=cube_01)\n",
    "src_02 = sim.Source(cube=cube_02)\n",
    "\n",
    "sky = sim.source.source_templates.empty_sky()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We observe each of the two sources and the blank sky; this takes a few minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "metis.observe(src_01, update=True)\n",
    "hdul_01 = metis.readout(detector_readout_mode=\"auto\")[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "metis.observe(src_02, update=True)\n",
    "hdul_02 = metis.readout(detector_readout_mode=\"auto\")[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "metis.observe(sky, update=True)\n",
    "hdul_sky = metis.readout(detector_readout_mode=\"auto\")[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The difference between the background-subtracted 2D-spectra of the two sources is significant. Compare to the images in the first notebook, `LSS_AGN-01_preparation.ipynb`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "plt.subplot(121)\n",
    "plt.imshow(hdul_01[1].data - hdul_sky[1].data + 1e5, origin='lower', norm=LogNorm(vmin=1e5, vmax=5e8))\n",
    "plt.subplot(122)\n",
    "plt.imshow(hdul_02[1].data - hdul_sky[1].data + 1e5, origin='lower', norm=LogNorm(vmin=1e5, vmax=5e8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the simulation results in FITS files for analysis with external tools."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hdul_01.writeto(\"AGN_prepared-scopesim_lss_n.fits\", overwrite=True)\n",
    "hdul_02.writeto(\"AGN_rotated_50-scopesim_lss_n.fits\", overwrite=True)\n",
    "hdul_sky.writeto(\"AGN_background-scopesim_lss_n.fits\", overwrite=True)"
   ]
  }
 ],
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