ESPRESSO_W189_extraction_of_spectra_to_cross_correlate.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Note: this tutorial is based on yet unpublished data and pipelines. Please do not share without explicit permission."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Goal of this workshop**: \n",
    "\n",
    "Get acquainted with reduction of optical data, with a particular focus on ESPRESSO and on the differences with nIR data. The following notebook is fully functional, provided that you have: (1) python 3 and some very common packages that can be installed with anaconda; (2) some ESPRESSO data already processed through the ESO pipelines.\n",
    "\n",
    "For the latter, I give you all the steps that you can apply yourself to any set of public or proprietary data to which you have access. This is a very disk space and time consuming process, thus I do not provide the reduced data here.\n",
    "\n",
    "You will get this notebook and, on request and on collaborative basis, the full pipeline that I am writing for this reduction. This is a highly modular pipeline (to complement it with stuff like PCA and other methods) and compatible with ESPRESSO, HARPS-N and MAROON-X. I plan to make it public, it is currently in development but is already functional (with this same code, I have published my Pino et al., 2020 paper).\n",
    "\n",
    "Write me to lorenzo.pino@inaf.it if interested!!!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data format and preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ESO pipelines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unlike with MAROON-X, we do not have an efficient team of people giving us the data in a usable form. We have to prepare our own data, using ESO pipelines.\n",
    "\n",
    "ESO pipelines are a bit messy to install, but the ESO support team is very responsive and will help you in the process. I managed to install the pipelines on a Mac relatively effortlessly.\n",
    "\n",
    "ESO pipelines are called \"recipes\", and can be run in different environments. Esorex is a command line tool. However, there is a convenient API called Esoreflex, which wraps Esorex in a more immediate form. This is what I use for the ESPRESSO pipelines.\n",
    "\n",
    "From the README: Data reduction is demanding in terms of system resources. The user should have at least 16 GB of RAM, and 1 TB of free disk space. Better is to have 32 GB of RAM and 4 TB of free disk space. Please note that only the demo requires 30 GB of free space to be installed and generates additional 10 GB of products. This sets also minimum root directory space requirements for RPM installation. Data reduction for SINGLE modes (in particular not binned data) is slow, and may take 45 min. As some recipes parallelise code using OpenMP, data reduction is faster on multi-core systems.\n",
    "\n",
    "... Yes, it is kind of a nightmare.\n",
    "\n",
    "Create a folder tree:\n",
    "1. ESPRESSO_observations/\\<Run_name\\>/data_with_raw_calibs\n",
    "2. ESPRESSO_observations/\\<Run_name\\>/reflex_end_products"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data download"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step 0 is to get the data from the ESO archive. There is a user friendly version of the archive (science portal) that contains pre-reduced spectra. These are good for a quick look, but not for science. So, we instead use the raw data portal (http://archive.eso.org/eso/eso_archive_main.html)\n",
    "\n",
    "Let's search for WASP-189b, and select the ESPRESSO instrument. To make sure you do not lose any data, click on the Program ID. You will find that there are two public runs. The pipeline works with both, but let's use  0103.C-0889(C) which focuses on the dayside. In the window that opens, click on \"FileList\". That gives you a list of all science exposures in that run. We \"Mark all\", and \"Request marked datasets (new service)\".\n",
    "\n",
    "We will not just need the science exposures, but also the calibrations, in order to run the pipeline. So let's \"run association\" of the **raw** calibrations (not processed). After the associatiton is done (it takes a while), we can download everything. I recommend the shell script.\n",
    "\n",
    "Place the script for each run in the \"data_with_raw_calibs\", change permissions if needed (chmod u+x <script_name>) and run. You are downloading about 10 GB of data, so it may take a while. After everything is done, unzip the archives.\n",
    "\n",
    "You should have lots of fits files. Most of them are calibrations, and may contain a date that does not coincide with the observational night. The observations have an associated raw2raw.xml, which associates the calibrations to the exposure. If some files are missing, repeat the process."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using esoreflex"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You will need a configuration file of type \".kar\". If you installed your ESO pipelines, you'll have an example to follow. In this drive (https://drive.google.com/drive/u/2/folders/1Xfu2wWyn8WO1DgOQsYmxj8gBMTMWUJ-W) I placed one example that I use.\n",
    "\n",
    "1. Change the RAW_DATA_DIR and END-PRODUCTS-DIR according to your tree;\n",
    "22. Tools -> Animate at Runtime -> 10\n",
    "\n",
    "Launch!\n",
    "\n",
    "Esoreflex requires some interaction. First, it will read the files, and present you with boxes to tick to select the files you'd like to reduce. If they are greyd out, it means that it could not find the calibrations. Go back to previous steps, and/or check your directory tree.\n",
    "\n",
    "If you use a new .kar starting from the ESPRESSO pipeline examples, you will get a pop-up window. This shows the extracted spectra given the setup you curerently have. If this is satisfactory, click the option \"Use the parameters above as initial values in the subsequent executions of this receipe\". In this way you'll have no more pop-ups, and esoreflex will run on its own. In my own .kar files, I have already disabled the pop-up window, so you will not get it.\n",
    "\n",
    "A little trick: you can interrupt the execution of the pipeline and resume at a different moment. Esoreflex knows which files you have reduced or not, and by default it should not overwrite them. If you wish to overwrite, find the \"lazy mode\" and disable it (so Esoreflex will actually do everything from the beginning.\n",
    "\n",
    "This will take quite a while to run, and ESO claims that it runs faster on multi-core computers because there is some internal parallelization. I never tested that."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Output of esoreflex "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the output folder, esoreflex creates a folder with the date and time on which the workflow was called. So if you do parts of the analysis on different times, you will have the results under different folders. Within this folder you will find one subfolder for each exposure, which contains the final products. Only some of them are useful for us.\n",
    "\n",
    "ESPRESSO has two fibers. Fiber A contains the spectra of the planet, and fiber B can be placed on different sources depending on the observer's choice. Usually, it is placed on sky, to monitor telluric emission.\n",
    "\n",
    "**<OB_name>_S2D_BLAZE_A_<Esposure_UT_time>**: gives the blaze function in fiber A.\n",
    "\n",
    "**<OB_name>_S2D_SKYSUB_A_<Esposure_UT_time>**: gives the 2-dimensional spectra from fiber A, after subtracting fiber B. This is necessary to remove the telluric emission lines, but it could in some cases introduce extra noise. This is what I am currently using and is suggested, but you may explore the impact of avoiding the sky subtraction.\n",
    "\n",
    "In addition, there are many other files, for both fiber A and B. For example, there are flux calibrated spectra (currently, Feb 2022, ESPRESSO flux calibration is not completely reliable, and not accurate enough to recover the flux at the precision needed for exoplanet atmosphere applications). Finally, there are CCFs calculated by the pipeline with an algorithm which is very similar to the one I will give you in the next notebook (but much slower!).\n",
    "\n",
    "From here on, we are on our own and we can start the data reduction."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data reduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compared to nIR data, optical data can be seen as \"easier\", in the sense that we have less telluric contamination. We have more contamination from the star, but if this is well behaved it is relatively simple to correct for (but this depends on application).\n",
    "\n",
    "I thus provide you with a very simple data reduction pipeline, which *does not correct for tellurics*, and is already sufficient to reproduce results from the literature (e.g., Ehrenreich et al., 2021; Pino et al., 2020). Of course, this can be improved."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Reading and preparing data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are the operations that I suggest to perform before performing a retrieval on optical data:\n",
    "\n",
    "1) Read data;\n",
    "\n",
    "2) Apply color correction;\n",
    "\n",
    "3) Move to the stellar rest frame to remove stellar lines;\n",
    "\n",
    "4) Additional flattening and filtering of outliers.\n",
    "\n",
    "These operations have been already mostly covered by Matteo and Megan. A pipeline such as theirs, works also on optical data. Here, I adopt a simplified version of those pipelines, which skips steps 2 and 4, to show you that we still get the result. While sub-optimal, I think this is interesting to see how reliable these detections are."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we import libraries, and open the fits files. Some tidying now will spare headaches later!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Reading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from astropy.io import fits\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from astropy import visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Working with fits files. Works with different kinds of inputs (SKYSUB or not etc).\n",
    "\n",
    "def read_sorted_hdus(input_data_directory, data_type, target_name):\n",
    "    \"\"\"S2D hdu structure (works for any S2D file):\n",
    "\n",
    "    1: science\n",
    "    2: errors\n",
    "    3: data quality flag\n",
    "    4: wavelength vacuum\n",
    "    5: wavelength air\n",
    "    6: pixel width vacuum\n",
    "    7: pixel width air\n",
    "    \"\"\"\n",
    "    \n",
    "    # Get all data in folder of the specified type\n",
    "    import glob\n",
    "    data_files = np.array(glob.glob(input_data_directory + '*_{}_*'.format(data_type)))\n",
    "    \n",
    "    # Read date and time from the filename (standardized)\n",
    "    date_time_observations = get_date_time_observations(data_files, data_type=data_type)\n",
    "    \n",
    "    # Sort exposures in time\n",
    "    time_sorted_exposures_mask = compute_time_sorted_exposures_mask(date_time_observations)\n",
    "    data_files_sorted = data_files[time_sorted_exposures_mask]\n",
    "\n",
    "    # Open the fits and return them. Not the cheapest in terms of memory, but we'll use some of the info in the headers\n",
    "    hdus = []\n",
    "    for file_name in data_files_sorted:\n",
    "        hdu = fits.open(file_name)\n",
    "        if hdu[0].header['HIERARCH ESO OBS TARG NAME'] == target_name:\n",
    "            hdus.append(hdu)    \n",
    "\n",
    "    return hdus\n",
    "\n",
    "def get_date_time_observations(data_files, data_type):\n",
    "    \"\"\" Extract the date and time of an expsure from its name.\n",
    "    \"\"\"\n",
    "    import re\n",
    "    re.compile(data_type)\n",
    "\n",
    "    date_time_observations = [] \n",
    "\n",
    "    for file in data_files:\n",
    "        start = re.search(data_type + '_', file).end()\n",
    "\n",
    "        date = file[start:start+10]\n",
    "        time = file[start+11:start+23]\n",
    "\n",
    "        date_time_observations.append([date, time])\n",
    "\n",
    "    return date_time_observations\n",
    "\n",
    "def compute_time_sorted_exposures_mask(date_time_observations):\n",
    "    \"\"\" From strings to datetime objects\n",
    "    \"\"\"\n",
    "\n",
    "    date_time_observations_datetime=[]\n",
    "    from datetime import datetime\n",
    "    for dt in date_time_observations:\n",
    "        date_time_observations_datetime.append(datetime.strptime(dt[0] + ' ' + dt[1][:-4], \"%Y-%m-%d %H:%M:%S\"))    \n",
    "\n",
    "    return np.argsort(date_time_observations_datetime)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "141"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_data_directory = '/data2/pino/Data/observations/ESPRESSO/W189b_2019-06-02/'\n",
    "data_type='S2D_SKYSUB_A'\n",
    "target_name='HD 133112' # From the header of ESPRESSO files\n",
    "\n",
    "# Read the sorted hdus\n",
    "hdus_S2D = read_sorted_hdus(input_data_directory = input_data_directory, data_type=data_type, target_name=target_name)\n",
    "\n",
    "len(hdus_S2D)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMPLE  =                    T / file does conform to FITS standard             \n",
       "BITPIX  =                    8 / number of bits per data pixel                  \n",
       "NAXIS   =                    0 / number of data axes                            \n",
       "EXTEND  =                    T / FITS dataset may contain extensions            \n",
       "COMMENT   FITS (Flexible Image Transport System) format is defined in 'Astronomy\n",
       "COMMENT   and Astrophysics', volume 376, page 359; bibcode: 2001A&A...376..359H \n",
       "DATE    = '2020-10-08T23:02:05' / file creation date (YYYY-MM-DDThh:mm:ss UT)   \n",
       "ORIGIN  = 'ESO-PARANAL'        / European Southern Observatory                  \n",
       "TELESCOP= 'ESO-VLT-U2'         / ESO <TEL>                                      \n",
       "INSTRUME= 'ESPRESSO'           / Instrument used.                               \n",
       "OBJECT  = 'HD 133112'          / Original target.                               \n",
       "RA      =           225.687392 / [deg] 15:02:44.9 RA (J2000) pointing           \n",
       "DEC     =             -3.03237 / [deg] -03:01:56.5 DEC (J2000) pointing         \n",
       "EQUINOX =                2000. / Standard FK5                                   \n",
       "RADECSYS= 'FK5     '           / Coordinate system                              \n",
       "EXPTIME =                  80. / Integration time                               \n",
       "MJD-OBS =        58636.0241087 / Obs start                                      \n",
       "DATE-OBS= '2019-06-02T00:34:42.991' / Observing date                            \n",
       "UTC     =                2068. / [s] 00:34:28.000 UTC                           \n",
       "LST     =            45218.213 / [s] 12:33:38.213 LST                           \n",
       "PI-COI  = 'UNKNOWN '           / PI-COI name.                                   \n",
       "OBSERVER= 'UNKNOWN '           / Name of observer.                              \n",
       "ARCFILE = 'ESPRE.2019-06-02T00:34:42.992.fits' / Archive File Name              \n",
       "DATAMD5 = 'cc99db95e2cbaefa97ea8eedc494c1a0' / MD5 checksum                     \n",
       "PIPEFILE= 'ESPRESSO_S2D_SKYSUB_A.fits' / Filename of data product               \n",
       "HIERARCH ESO OBS AIRM =    1.8 / Req. max. airmass                              \n",
       "HIERARCH ESO OBS AMBI FWHM = 1.8 / Req. max. seeing                             \n",
       "HIERARCH ESO OBS AMBI TRANS = '3THN    ' / Req. sky transparency                \n",
       "HIERARCH ESO OBS ATM = 'NATM    ' / Req. Atmospheric Turbulence Model           \n",
       "HIERARCH ESO OBS CONTAINER ID = 2439662 / Scheduling container ID               \n",
       "HIERARCH ESO OBS CONTAINER TYPE = 'U       ' / Scheduling container type        \n",
       "HIERARCH ESO OBS CONTRAST = 0. / Req. contrast                                  \n",
       "HIERARCH ESO OBS DID = 'ESO-VLT-DIC.OBS-2.0' / OBS Dictionary                   \n",
       "HIERARCH ESO OBS EXECTIME = 18040 / Expected execution time                     \n",
       "HIERARCH ESO OBS GRP = '0       ' / linked blocks                               \n",
       "HIERARCH ESO OBS ID =  2440488 / Observation block ID                           \n",
       "HIERARCH ESO OBS MOON DIST = 30 / Req. min. angular dist. from moon [deg]       \n",
       "HIERARCH ESO OBS MOON FLI = 1. / Req. max. fractional lunar illum.              \n",
       "HIERARCH ESO OBS NAME = 'WASP-189b-day-1' / OB name                             \n",
       "HIERARCH ESO OBS NTPL =      2 / Number of templates within OB                  \n",
       "HIERARCH ESO OBS OBSERVER = 'UNKNOWN ' / Observer Name                          \n",
       "HIERARCH ESO OBS PI-COI ID = 82841 / ESO internal PI-COI ID                     \n",
       "HIERARCH ESO OBS PI-COI NAME = 'UNKNOWN ' / PI-COI name                         \n",
       "HIERARCH ESO OBS PROG ID = '0103.C-0889(C)' / ESO program identification        \n",
       "HIERARCH ESO OBS START = '2019-06-02T00:30:09' / OB start time                  \n",
       "HIERARCH ESO OBS STREHLRATIO = 0. / Req. strehl ratio                           \n",
       "HIERARCH ESO OBS TARG NAME = 'HD 133112' / OB target name                       \n",
       "HIERARCH ESO OBS TPLNO =     2 / Template number within OB                      \n",
       "HIERARCH ESO OBS TWILIGHT = 20 / Req. twilight                                  \n",
       "HIERARCH ESO OBS WATERVAPOUR = 5. / Req. water vapour                           \n",
       "HIERARCH ESO TPL DID = 'ESO-VLT-DIC.TPL-1.9' / Data dictionary for TPL          \n",
       "HIERARCH ESO TPL EXPNO =     1 / Exposure number within template                \n",
       "HIERARCH ESO TPL ID = 'ESPRESSO_singleHR_obs' / Template signature ID           \n",
       "HIERARCH ESO TPL NAME = 'ESPRESSO_singleHR_obs' / Template name                 \n",
       "HIERARCH ESO TPL NEXP =    141 / Number of exposures within template            \n",
       "HIERARCH ESO TPL PRESEQ = 'ESPRESSO_obs.seq' / Sequencer script                 \n",
       "HIERARCH ESO TPL START = '2019-06-02T00:34:16' / TPL start time                 \n",
       "HIERARCH ESO TPL VERSION = '$Revision: 316244 $' / Version of the template      \n",
       "HIERARCH ESO TEL2 AIRM END = 1.337 / Airmass at end                             \n",
       "HIERARCH ESO TEL2 AIRM START = 1.346 / Airmass at start                         \n",
       "HIERARCH ESO TEL2 ALT = 47.946 / [deg] Alt angle at start                       \n",
       "HIERARCH ESO TEL2 AMBI FWHM END = 1.01 / [arcsec] Observatory Seeing queried fro\n",
       "HIERARCH ESO TEL2 AMBI FWHM START = 1.21 / [arcsec] Observatory Seeing queried f\n",
       "HIERARCH ESO TEL2 AMBI IRSKY TEMP = -97.2 / Temperature of the IR sky, from radi\n",
       "HIERARCH ESO TEL2 AMBI IWV END = 1.56 / Integrated Water Vapor                  \n",
       "HIERARCH ESO TEL2 AMBI IWV START = 1.59 / Integrated Water Vapor                \n",
       "HIERARCH ESO TEL2 AMBI IWV30D END = 1.71 / IWV at 30deg elev.                   \n",
       "HIERARCH ESO TEL2 AMBI IWV30D START = 1.71 / IWV at 30deg elev.                 \n",
       "HIERARCH ESO TEL2 AMBI IWV30DSTD END = 0.04 / IWV at 30deg elev.                \n",
       "HIERARCH ESO TEL2 AMBI IWV30DSTD START = 0.04 / IWV at 30deg elev.              \n",
       "HIERARCH ESO TEL2 AMBI IWVSTD END = 0.01 / Standard Deviation of Integrated Wate\n",
       "HIERARCH ESO TEL2 AMBI IWVSTD START = 0.01 / Standard Deviation of Integrated Wa\n",
       "HIERARCH ESO TEL2 AMBI PRES END = 744.8 / [hPa] Observatory ambient air pressur \n",
       "HIERARCH ESO TEL2 AMBI PRES START = 744.8 / [hPa] Observatory ambient air press \n",
       "HIERARCH ESO TEL2 AMBI RHUM = 23. / [%] Observatory ambient relative humidity q \n",
       "HIERARCH ESO TEL2 AMBI TAU0 = 0.0022 / [s] Average coherence time               \n",
       "HIERARCH ESO TEL2 AMBI TEMP = 8.33 / [deg C] Observatory ambient temperature que\n",
       "HIERARCH ESO TEL2 AMBI WINDDIR = 105. / [deg] Observatory ambient wind directio \n",
       "HIERARCH ESO TEL2 AMBI WINDSP = 4.25 / [m/s] Observatory ambient wind speed quer\n",
       "HIERARCH ESO TEL2 AZ =  245.23 / [deg] Az angle at start S=0,W=90               \n",
       "HIERARCH ESO TEL2 CHOP ST =  F / True when chopping is active                   \n",
       "HIERARCH ESO TEL2 DATE = '2000-01-01T00:00:00' / TCS installation date          \n",
       "HIERARCH ESO TEL2 DID = 'ESO-VLT-DIC.TCS' / Data dictionary for TELi            \n",
       "HIERARCH ESO TEL2 DOME STATUS = 'FULLY-OPEN' / Dome status                      \n",
       "HIERARCH ESO TEL2 FO POS =  0. / Adapter focus position during tracking         \n",
       "HIERARCH ESO TEL2 FOCU ID = 'NB      ' / Telescope focus station ID             \n",
       "HIERARCH ESO TEL2 FOCU LEN = 120. / [m] Focal length                            \n",
       "HIERARCH ESO TEL2 FOCU SCALE = 1.718 / [arcsec/mm] Focal scale                  \n",
       "HIERARCH ESO TEL2 FOCU VALUE = -29.036 / [mm] M2 setting                        \n",
       "HIERARCH ESO TEL2 GEOELEV = 2648. / [m] Elevation above sea level               \n",
       "HIERARCH ESO TEL2 GEOLAT = -24.6272 / [deg] Tel geo latitute (+=North)          \n",
       "HIERARCH ESO TEL2 GEOLON = -70.4048 / [deg] Tel geo longitude (+=East)          \n",
       "HIERARCH ESO TEL2 IA FWHM = 1.04 / [arcsec] Delivered seeing corrected by airmas\n",
       "HIERARCH ESO TEL2 IA FWHMLIN = 1.22 / Delivered seeing on IA detector (linear fi\n",
       "HIERARCH ESO TEL2 IA FWHMLINOBS = 1.45 / Delivered seeing on IA detector (linear\n",
       "HIERARCH ESO TEL2 ID = 'v 318664' / TCS version number                          \n",
       "HIERARCH ESO TEL2 MOON DEC = 14.84867 / [deg] 14:50:55.1 DEC (J2000)            \n",
       "HIERARCH ESO TEL2 MOON RA = 51.826562 / [deg] 03:27:18.3 RA (J2000)             \n",
       "HIERARCH ESO TEL2 OPER = 'I, Condor' / Telescope Operator                       \n",
       "HIERARCH ESO TEL2 PARANG END = -124.529 / [deg] Parallactic angle at end        \n",
       "HIERARCH ESO TEL2 PARANG START = -124.245 / [deg] Parallactic angle at start    \n",
       "HIERARCH ESO TEL2 TARG ALPHA = 150244.86 / Alpha coordinate for the target      \n",
       "HIERARCH ESO TEL2 TARG COORDTYPE = 'M       ' / Coordinate type (M=mean A=appare\n",
       "HIERARCH ESO TEL2 TARG DELTA = -30152.9 / Delta coordinate for the target       \n",
       "HIERARCH ESO TEL2 TARG EPOCH = 2000. / [yr] Epoch 1950 or 2000                  \n",
       "HIERARCH ESO TEL2 TARG EPOCHSYSTEM = 'J       ' / Epoch system (J=Julian / B=Bes\n",
       "HIERARCH ESO TEL2 TARG EQUINOX = 2000. / [yr] Equinox                           \n",
       "HIERARCH ESO TEL2 TARG PARALLAX = 0. / [arcsec] Parallax                        \n",
       "HIERARCH ESO TEL2 TARG PMA = -0.0506 / [arcsec/yr] Proper Motion Alpha          \n",
       "HIERARCH ESO TEL2 TARG PMD = -0.0238 / [arcsec/yr] Proper motion Delta          \n",
       "HIERARCH ESO TEL2 TARG RADVEL = 0. / [km/s] Radial velocity                     \n",
       "HIERARCH ESO TEL2 TH M1 TEMP = 7.87 / [deg C] M1 superficial temperature        \n",
       "HIERARCH ESO TEL2 TRAK STATUS = 'NORMAL  ' / Tracking status                    \n",
       "HIERARCH ESO INS DATE = '2012-10-16' / Instrument release date (yyyy-mm-dd).    \n",
       "HIERARCH ESO INS MODE = 'SINGLEHR' / Instrument mode used.                      \n",
       "HIERARCH ESO INS2 ADC1 DEC = -30623.62729 / [deg] Telescope desclination.       \n",
       "HIERARCH ESO INS2 ADC1 ENC = 32661 / [Enc] ADC absolute position.               \n",
       "HIERARCH ESO INS2 ADC1 ID =  0 / ADC unique id                                  \n",
       "HIERARCH ESO INS2 ADC1 MODE = 'AUTO    ' / ADC mode.                            \n",
       "HIERARCH ESO INS2 ADC1 NAME = 'ADC UT2 wheel 1' / ADC name                      \n",
       "HIERARCH ESO INS2 ADC1 POS = 55.958055 / [deg] Position in user units           \n",
       "HIERARCH ESO INS2 ADC1 POSANG = 55.9581 / Position angle [deg].                 \n",
       "HIERARCH ESO INS2 ADC1 RA = 150345.811609 / [deg] Telescope right ascension.    \n",
       "HIERARCH ESO INS2 ADC1 SENS1 = 744.8 / [mbar] Pressure.                         \n",
       "HIERARCH ESO INS2 ADC1 TEMP = 8.4 / [C] Temperature.                            \n",
       "HIERARCH ESO INS2 ADC2 DEC = -30623.62729 / [deg] Telescope desclination.       \n",
       "HIERARCH ESO INS2 ADC2 ENC = 154114 / [Enc] ADC absolute position.              \n",
       "HIERARCH ESO INS2 ADC2 ID =  0 / ADC unique id                                  \n",
       "HIERARCH ESO INS2 ADC2 MODE = 'AUTO    ' / ADC mode.                            \n",
       "HIERARCH ESO INS2 ADC2 NAME = 'ADC UT2 wheel 2' / ADC name                      \n",
       "HIERARCH ESO INS2 ADC2 POS = 264.038861 / [deg] Position in user units          \n",
       "HIERARCH ESO INS2 ADC2 POSANG = 264.0389 / Position angle [deg].                \n",
       "HIERARCH ESO INS2 ADC2 RA = 150345.811609 / [deg] Telescope right ascension.    \n",
       "HIERARCH ESO INS2 ADC2 SENS1 = 744.8 / [mbar] Pressure.                         \n",
       "HIERARCH ESO INS2 ADC2 TEMP = 8.4 / [C] Temperature.                            \n",
       "HIERARCH ESO INS2 CALSEL ENC = 29959 / [Enc] Component absolute position.       \n",
       "HIERARCH ESO INS2 CALSEL ID = 'TRG_SKY ' / Unique ID.                           \n",
       "HIERARCH ESO INS2 CALSEL NAME = 'TRG_SKY ' / FE Calibration selector.           \n",
       "HIERARCH ESO INS2 CALSEL NO = 1 / CALSEL slot number.                           \n",
       "HIERARCH ESO INS2 CALSEL POS = 14.9795 / [mm] Component position.               \n",
       "HIERARCH ESO INS2 CALSEL TYPE = 'MASK    ' / OPTIi element.                     \n",
       "HIERARCH ESO INS2 DID1 = 'ICS2_ICS-296578' / Data dictionary for INS.           \n",
       "HIERARCH ESO INS2 DID2 = 'PRIMARY-FITS-1.2' / Data dictionary for INS.          \n",
       "HIERARCH ESO INS2 FILT1 ENC = 78519 / [Enc] FS Filter wheel absolute position.  \n",
       "HIERARCH ESO INS2 FILT1 ID = 'ND_200-0.50' / FS Filter unique id.               \n",
       "HIERARCH ESO INS2 FILT1 NAME = 'FSND20  ' / FS Filter name.                     \n",
       "HIERARCH ESO INS2 FILT1 NO = 3 / FS Filter wheel position index.                \n",
       "HIERARCH ESO INS2 FILT1 POS = 120.0005 / [deg] Component position.              \n",
       "HIERARCH ESO INS2 FILT1 TYPE = 'FILTER  ' / FS OPTIi element.                   \n",
       "HIERARCH ESO INS2 FOCU ENC = 28005 / [Enc] Absolute position.                   \n",
       "HIERARCH ESO INS2 FOCU ID =  0 / Unique id                                      \n",
       "HIERARCH ESO INS2 FOCU NAME = 'Focusing stage UT2' / Name                       \n",
       "HIERARCH ESO INS2 FOCU POS = 14. / [mm] Position.                               \n",
       "HIERARCH ESO INS2 ID = 'ESPRESSO/ICS2' / Instrument ID.                         \n",
       "HIERARCH ESO INS2 PATH = '        ' / Optical path used.                        \n",
       "HIERARCH ESO INS2 SWSIM = 'NORMAL  ' / Software simulation.                     \n",
       "HIERARCH ESO INS2 TILT1 ENG2ARCX = 0.00029 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT1 ENG2ARCY = 0.0002 / Conversion factor from engineering  \n",
       "HIERARCH ESO INS2 TILT1 ENG2MRADX = 0.0004 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT1 ENG2MRADY = 0.0004 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT1 ID = 'iops2   ' / FS/PS id.                             \n",
       "HIERARCH ESO INS2 TILT1 MODE = 'REF     ' / Device mode.                        \n",
       "HIERARCH ESO INS2 TILT1 NAME = 'I/O Pupil stabil 2' / Device description.       \n",
       "HIERARCH ESO INS2 TILT1 VAL1 = 16278. / Piezo axis  numeric value.              \n",
       "HIERARCH ESO INS2 TILT1 VAL2 = 18182. / Piezo axis  numeric value.              \n",
       "HIERARCH ESO INS2 TILT2 ENG2ARCX = 0.00022 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT2 ENG2ARCY = 0.00015 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT2 ENG2MRADX = 0.0004 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT2 ENG2MRADY = 0.0004 / Conversion factor from engineering \n",
       "HIERARCH ESO INS2 TILT2 ID = 'iofs2   ' / FS/PS id.                             \n",
       "HIERARCH ESO INS2 TILT2 MODE = 'AUTO    ' / Device mode.                        \n",
       "HIERARCH ESO INS2 TILT2 NAME = 'I/O Field stabil 2' / Device description.       \n",
       "HIERARCH ESO INS2 TILT2 VAL1 = 16174. / Piezo axis  numeric value.              \n",
       "HIERARCH ESO INS2 TILT2 VAL2 = 13349. / Piezo axis  numeric value.              \n",
       "HIERARCH ESO INS5 DID1 = 'ICS5_ICS-315386' / Data dictionary for INS.           \n",
       "HIERARCH ESO INS5 DID2 = 'PRIMARY-FITS-1.2' / Data dictionary for INS.          \n",
       "HIERARCH ESO INS5 FESELA ENC = 310802 / [Enc] Absolute position.                \n",
       "HIERARCH ESO INS5 FESELA ID = '1       ' / Unique ID.                           \n",
       "HIERARCH ESO INS5 FESELA NAME = 'FE1_LD  ' / Name.                              \n",
       "HIERARCH ESO INS5 FESELA NO = 1 / Slot number.                                  \n",
       "HIERARCH ESO INS5 FESELA POS = 155.401 / [mm] Component position.               \n",
       "HIERARCH ESO INS5 FESELA TYPE = 'MASK    ' / Element.                           \n",
       "HIERARCH ESO INS5 FESELB ENC = 69238 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 FESELB ID = '17      ' / Unique ID.                           \n",
       "HIERARCH ESO INS5 FESELB NAME = 'FE1_FP  ' / Name.                              \n",
       "HIERARCH ESO INS5 FESELB NO = 17 / Slot number.                                 \n",
       "HIERARCH ESO INS5 FESELB POS = 34.619 / [mm] Component position.                \n",
       "HIERARCH ESO INS5 FESELB TYPE = 'MASK    ' / Element.                           \n",
       "HIERARCH ESO INS5 FILT2 ENC = 117778 / [Enc] EM Filter wheel absolute position. \n",
       "HIERARCH ESO INS5 FILT2 ID = 'ND1_ID  ' / EM Filter unique id.                  \n",
       "HIERARCH ESO INS5 FILT2 NAME = 'EMND00  ' / EM Filter name.                     \n",
       "HIERARCH ESO INS5 FILT2 NO = 1 / EM Filter wheel position index.                \n",
       "HIERARCH ESO INS5 FILT2 POS = 180. / [deg] Component position.                  \n",
       "HIERARCH ESO INS5 FILT2 TYPE = 'FREE    ' / Element.                            \n",
       "HIERARCH ESO INS5 ID = 'ESPRESSO/ICS5' / Instrument ID.                         \n",
       "HIERARCH ESO INS5 LAMP4 FREQ = 18000000000. / [Hz] Absolute frequency           \n",
       "HIERARCH ESO INS5 LAMP4 FREQOFFS = 7350000000. / [Hz] Offset of first comb      \n",
       "HIERARCH ESO INS5 LAMP4 ID = 'LFC1    ' / LFC instance ID                       \n",
       "HIERARCH ESO INS5 LAMP4 LEVEL = -13. / Level                                    \n",
       "HIERARCH ESO INS5 LAMP4 NAME = 'LFC red ' / LFC instance name                   \n",
       "HIERARCH ESO INS5 LAMP4 STABLE = F / Light OK since reset                       \n",
       "HIERARCH ESO INS5 LAMP4 STAT = 'OFF     ' / Status of LFC                       \n",
       "HIERARCH ESO INS5 LAMP5 ID = 'FPCS    ' / Lamp ID.                              \n",
       "HIERARCH ESO INS5 LAMP5 NAME = 'FPCS_Lamp' / Lamp name.                         \n",
       "HIERARCH ESO INS5 LAMP5 ST = T / Lamp activated.                                \n",
       "HIERARCH ESO INS5 LAMP5 STAT = 'ON      ' / Lamp activated.                     \n",
       "HIERARCH ESO INS5 LAMP5 TIME = 23980. / Time [sec] lamp was on.                 \n",
       "HIERARCH ESO INS5 LSELA ENC = 152001 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 LSELA ID = '7       ' / Unique ID.                            \n",
       "HIERARCH ESO INS5 LSELA NAME = 'DARK    ' / Name.                               \n",
       "HIERARCH ESO INS5 LSELA NO = 7 / Slot number.                                   \n",
       "HIERARCH ESO INS5 LSELA POS = 76.0005 / [mm] Component position.                \n",
       "HIERARCH ESO INS5 LSELA TYPE = 'MASK    ' / Element.                            \n",
       "HIERARCH ESO INS5 LSELB ENC = 152015 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 LSELB ID = '7       ' / Unique ID.                            \n",
       "HIERARCH ESO INS5 LSELB NAME = 'DARK    ' / Name.                               \n",
       "HIERARCH ESO INS5 LSELB NO = 7 / Slot number.                                   \n",
       "HIERARCH ESO INS5 LSELB POS = 76.0075 / [mm] Component position.                \n",
       "HIERARCH ESO INS5 LSELB TYPE = 'MASK    ' / Element.                            \n",
       "HIERARCH ESO INS5 MODSEL ENC = 1184824 / [Enc] Component absolute position.     \n",
       "HIERARCH ESO INS5 MODSEL ID = 'UT2HR   ' / Unique ID.                           \n",
       "HIERARCH ESO INS5 MODSEL NAME = 'UT2HR   ' / MODSEL name.                       \n",
       "HIERARCH ESO INS5 MODSEL NO = 3 / MODSEL slot number.                           \n",
       "HIERARCH ESO INS5 MODSEL POS = 118.4824 / [deg] Component position.             \n",
       "HIERARCH ESO INS5 MODSEL TYPE = 'MASK    ' / MODSEL element.                    \n",
       "HIERARCH ESO INS5 PATH = '        ' / Optical path used.                        \n",
       "HIERARCH ESO INS5 PRES100 VAL = 6.17E-06 / [mbar] Blue cryostat pressure.       \n",
       "HIERARCH ESO INS5 PRES101 VAL = 4.767E-06 / [mbar] Red cryostat pressure.       \n",
       "HIERARCH ESO INS5 PRES102 VAL = 0. / [mbar] Cryopump1 cryostat pressure.        \n",
       "HIERARCH ESO INS5 PRES103 VAL = 290.6 / [mbar] Cryopump2 cryostat pressure.     \n",
       "HIERARCH ESO INS5 PRES104 VAL = 1.721E-06 / [mbar] Manifold vacuum pressure.    \n",
       "HIERARCH ESO INS5 PRES105 VAL = 888900. / [mbar] Pre vacuum pressure.           \n",
       "HIERARCH ESO INS5 PRES106 VAL = 6.321E-07 / [mbar] Vessel vacuum pressure.      \n",
       "HIERARCH ESO INS5 PRES107 VAL = 9.078E-06 / [mbar] Fabry-Perot vacuum pressure. \n",
       "HIERARCH ESO INS5 SENS1 VAL = 13.5 / [%] VV regulator heater output.            \n",
       "HIERARCH ESO INS5 SENS101 VAL = 95.592514 / [K] Blue cryostat cold plate temp.  \n",
       "HIERARCH ESO INS5 SENS109 VAL = 95.831123 / [K] Red cryostat cold plate temp.   \n",
       "HIERARCH ESO INS5 SENS150 VAL = 66.599998 / [%] Blue detector mount heat.       \n",
       "HIERARCH ESO INS5 SENS151 VAL = 18.509386 / [%] Blue detector table heater.     \n",
       "HIERARCH ESO INS5 SENS152 VAL = 60.5 / [%] Red detector mount heat.             \n",
       "HIERARCH ESO INS5 SENS153 VAL = 12.094555 / [%] Red detector table heater.      \n",
       "HIERARCH ESO INS5 SENS154 VAL = 9.0E-06 / [%] Blue detector front flange heater \n",
       "HIERARCH ESO INS5 SENS155 VAL = 9.0E-06 / [%] Red detector front flange heater. \n",
       "HIERARCH ESO INS5 SENS2 VAL = 2.6 / [%] FP regulator heater output.             \n",
       "HIERARCH ESO INS5 SENSOR1 ID = 'topt    ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR1 NAME = 'Optical components (Lake 218)' / Sensor device\n",
       "HIERARCH ESO INS5 SENSOR10 ID = 'cab3    ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR10 NAME = 'Thermal Cabinet cooling controller' / Sensor \n",
       "HIERARCH ESO INS5 SENSOR11 ID = 'dis1    ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR11 NAME = 'Digital signals 1' / Sensor device common nam\n",
       "HIERARCH ESO INS5 SENSOR12 ID = 'dis2    ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR12 NAME = 'Digital signals 2' / Sensor device common nam\n",
       "HIERARCH ESO INS5 SENSOR13 ID = 'alpiq   ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR13 NAME = '2T enclosure sensors' / Sensor device common \n",
       "HIERARCH ESO INS5 SENSOR14 ID = 'tencl   ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR14 NAME = 'Housekeeping (Lake 218)' / Sensor device comm\n",
       "HIERARCH ESO INS5 SENSOR15 ID = 'cryohf  ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR15 NAME = 'VCS system high-freq samp' / Sensor device co\n",
       "HIERARCH ESO INS5 SENSOR16 ID = 'vccc    ' / Sensor device unique id.           \n",
       "HIERARCH ESO INS5 SENSOR16 NAME = 'Vacuum Cabinet Cooling Controller' / Sensor d\n",
       "HIERARCH ESO INS5 SENSOR2 ID = 'tbenc   ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR2 NAME = 'Optical bench (Lake 218)' / Sensor device comm\n",
       "HIERARCH ESO INS5 SENSOR3 ID = 'tvv     ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR3 NAME = 'Vacuum Vessel (Lake 218)' / Sensor device comm\n",
       "HIERARCH ESO INS5 SENSOR4 ID = 'regvv   ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR4 NAME = 'Lakeshore 336' / Sensor device common name.   \n",
       "HIERARCH ESO INS5 SENSOR5 ID = 'reg3T   ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR5 NAME = 'Lakeshore 336' / Sensor device common name.   \n",
       "HIERARCH ESO INS5 SENSOR6 ID = 'cryo    ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR6 NAME = 'VCS system' / Sensor device common name.      \n",
       "HIERARCH ESO INS5 SENSOR7 ID = 'tfe     ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR7 NAME = 'FEs temperature sensors' / Sensor device commo\n",
       "HIERARCH ESO INS5 SENSOR8 ID = 'cab1    ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR8 NAME = 'Main Cabinet cooling controller' / Sensor devi\n",
       "HIERARCH ESO INS5 SENSOR9 ID = 'cab2    ' / Sensor device unique id.            \n",
       "HIERARCH ESO INS5 SENSOR9 NAME = 'Calibration Cabinet cooling controller' / Sens\n",
       "HIERARCH ESO INS5 SHUSEL CFG = 'HR      ' / Device configuration.               \n",
       "HIERARCH ESO INS5 SHUSEL ID = 'shusel  ' / Unique ID.                           \n",
       "HIERARCH ESO INS5 SHUSEL MODE = 'OPER    ' / Device mode.                       \n",
       "HIERARCH ESO INS5 SHUSEL NAME = 'Shutter selector' / Name.                      \n",
       "HIERARCH ESO INS5 SHUSEL ST = 'CLOSED  ' / Device status.                       \n",
       "HIERARCH ESO INS5 SWSIM = 'NORMAL  ' / Software simulation.                     \n",
       "HIERARCH ESO INS5 TEMP1 VAL = 18.76 / [C] Main collimator.                      \n",
       "HIERARCH ESO INS5 TEMP10 VAL = 18.645 / [C] Near echelle grating.               \n",
       "HIERARCH ESO INS5 TEMP100 VAL = 96.251907 / [K] Blue cryostat sorption pump temp\n",
       "HIERARCH ESO INS5 TEMP101 VAL = 19.004999 / [C] Blue front flange temp.         \n",
       "HIERARCH ESO INS5 TEMP102 VAL = 98.975769 / [K] Red cryostat sorption pump temp.\n",
       "HIERARCH ESO INS5 TEMP103 VAL = 19.004999 / [C] Red front flange temp.          \n",
       "HIERARCH ESO INS5 TEMP104 VAL = 0. / [K] Cryopump1 cold plate temp.             \n",
       "HIERARCH ESO INS5 TEMP105 VAL = 0. / [K] Cryopump1 sorption pump temp.          \n",
       "HIERARCH ESO INS5 TEMP106 VAL = 0. / [K] Cryopump1 2nd stage temp.              \n",
       "HIERARCH ESO INS5 TEMP107 VAL = 0. / [K] Cryopump2 cold plate temp.             \n",
       "HIERARCH ESO INS5 TEMP108 VAL = 0. / [K] Cryopump2 sorption pump temp.          \n",
       "HIERARCH ESO INS5 TEMP109 VAL = 0. / [K] Cryopump2 2nd stage temp.              \n",
       "HIERARCH ESO INS5 TEMP11 VAL = 18.507 / [C] Near red camera.                    \n",
       "HIERARCH ESO INS5 TEMP12 VAL = 18.581 / [C] Near blue camera.                   \n",
       "HIERARCH ESO INS5 TEMP13 VAL = 18.561 / [C] Optical bench feet 1.               \n",
       "HIERARCH ESO INS5 TEMP14 VAL = 18.564 / [C] Optical bench feet 2.               \n",
       "HIERARCH ESO INS5 TEMP15 VAL = 18.608 / [C] Optical bench feet 3.               \n",
       "HIERARCH ESO INS5 TEMP150 VAL = 148. / [K] Blue detector mount temp.            \n",
       "HIERARCH ESO INS5 TEMP151 VAL = 154.917999 / [K] Blue detector package temp.    \n",
       "HIERARCH ESO INS5 TEMP152 VAL = 146.49765 / [K] Blue detector table temp.       \n",
       "HIERARCH ESO INS5 TEMP153 VAL = 147.522995 / [K] Red detector mount temp.       \n",
       "HIERARCH ESO INS5 TEMP154 VAL = 156.695999 / [K] Red detector package temp.     \n",
       "HIERARCH ESO INS5 TEMP155 VAL = 147.189285 / [K] Red detector table temp.       \n",
       "HIERARCH ESO INS5 TEMP16 VAL = 18.535 / [C] Pupil slicer.                       \n",
       "HIERARCH ESO INS5 TEMP17 VAL = 18.642 / [C] Shield 1.                           \n",
       "HIERARCH ESO INS5 TEMP18 VAL = 18.668 / [C] Shield 2.                           \n",
       "HIERARCH ESO INS5 TEMP2 VAL = 18.644 / [C] Echelle grating.                     \n",
       "HIERARCH ESO INS5 TEMP25 VAL = 19.487 / [C] 3T up.                              \n",
       "HIERARCH ESO INS5 TEMP26 VAL = 18.653 / [C] 3T down.                            \n",
       "HIERARCH ESO INS5 TEMP29 VAL = 16.642 / [C] 2T env 1.                           \n",
       "HIERARCH ESO INS5 TEMP3 VAL = 18.628 / [C] Cross disperser blue.                \n",
       "HIERARCH ESO INS5 TEMP30 VAL = 16.576 / [C] 2T env 2.                           \n",
       "HIERARCH ESO INS5 TEMP31 VAL = 12.922 / [C] 1T env 1.                           \n",
       "HIERARCH ESO INS5 TEMP32 VAL = 13.654 / [C] 1T env 2.                           \n",
       "HIERARCH ESO INS5 TEMP33 REF = 19. / Temperature sensor reference value [C].    \n",
       "HIERARCH ESO INS5 TEMP33 VAL = 19.002 / [C] VV feet T-sensor primary.           \n",
       "HIERARCH ESO INS5 TEMP34 VAL = 19.017 / [C] VV feet T-sensor secondary.         \n",
       "HIERARCH ESO INS5 TEMP35 VAL = 24.755 / [C] FP T-sensor secondary.              \n",
       "HIERARCH ESO INS5 TEMP36 REF = 25. / [C] FP T-setpoint.                         \n",
       "HIERARCH ESO INS5 TEMP36 VAL = 25.001 / [C] FP T-sensor primary.                \n",
       "HIERARCH ESO INS5 TEMP37 REF = 19. / [C] 3T T-setpoint.                         \n",
       "HIERARCH ESO INS5 TEMP37 VAL = 19.001 / [C] 3T T-sensor primary.                \n",
       "HIERARCH ESO INS5 TEMP38 VAL = 19.091 / [C] 3T T-sensor secondary.              \n",
       "HIERARCH ESO INS5 TEMP4 VAL = 18.614 / [C] Cross disperser red.                 \n",
       "HIERARCH ESO INS5 TEMP41 VAL = 12. / [C] FE1 Bench bottom.                      \n",
       "HIERARCH ESO INS5 TEMP42 VAL = 12. / [C] FE1 Bench top.                         \n",
       "HIERARCH ESO INS5 TEMP43 VAL = 10.6 / [C] FE1 TCCD field.                       \n",
       "HIERARCH ESO INS5 TEMP44 VAL = 10.5 / [C] FE1 TCCD pupil.                       \n",
       "HIERARCH ESO INS5 TEMP47 VAL = 12.3 / [C] FE2 Bench bottom.                     \n",
       "HIERARCH ESO INS5 TEMP48 VAL = 12.4 / [C] FE2 Bench top.                        \n",
       "HIERARCH ESO INS5 TEMP49 VAL = 10.7 / [C] FE2 TCCD field.                       \n",
       "HIERARCH ESO INS5 TEMP5 VAL = 18.62 / [C] Dichroic.                             \n",
       "HIERARCH ESO INS5 TEMP50 VAL = 14.3 / [C] FE2 TCCD pupil.                       \n",
       "HIERARCH ESO INS5 TEMP53 VAL = 12.1 / [C] FE3 Bench bottom.                     \n",
       "HIERARCH ESO INS5 TEMP54 VAL = 12. / [C] FE3 Bench top.                         \n",
       "HIERARCH ESO INS5 TEMP55 VAL = 9.7 / [C] FE3 TCCD field.                        \n",
       "HIERARCH ESO INS5 TEMP56 VAL = 10. / [C] FE3 TCCD pupil.                        \n",
       "HIERARCH ESO INS5 TEMP59 VAL = 12.1 / [C] FE4 Bench bottom.                     \n",
       "HIERARCH ESO INS5 TEMP6 VAL = 18.691 / [C] Field mirror.                        \n",
       "HIERARCH ESO INS5 TEMP60 VAL = 12.3 / [C] FE4 Bench top.                        \n",
       "HIERARCH ESO INS5 TEMP61 VAL = 10.8 / [C] FE4 TCCD field.                       \n",
       "HIERARCH ESO INS5 TEMP62 VAL = 10.8 / [C] FE4 TCCD pupil.                       \n",
       "HIERARCH ESO INS5 TEMP65 VAL = 11.6 / [C] Spectro Bench EM.                     \n",
       "HIERARCH ESO INS5 TEMP66 VAL = 11.1 / [C] Spectro TCCD EM.                      \n",
       "HIERARCH ESO INS5 TEMP7 VAL = 18.539 / [C] Transfer coll. blue.                 \n",
       "HIERARCH ESO INS5 TEMP8 VAL = 18.492 / [C] Transfer coll. red.                  \n",
       "HIERARCH ESO INS5 TEMP83 VAL = 14.072 / [C] Calibration unit cabinet ambinet    \n",
       "HIERARCH ESO INS5 TEMP9 VAL = 18.705 / [C] Near main collimator.                \n",
       "HIERARCH ESO INS5 VFILT1 DEN = 0.4 / [D] Position.                              \n",
       "HIERARCH ESO INS5 VFILT1 ENC = 82445 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 VFILT1 ID = 'ndfila1 ' / Device unique ID.                    \n",
       "HIERARCH ESO INS5 VFILT1 NAME = 'Var ND filter cal A wheel 1' / Variable density\n",
       "HIERARCH ESO INS5 VFILT1 POS = 126.0006 / [deg] Position.                       \n",
       "HIERARCH ESO INS5 VFILT2 DEN = 0.4 / [D] Position.                              \n",
       "HIERARCH ESO INS5 VFILT2 ENC = 82445 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 VFILT2 ID = 'ndfila2 ' / Device unique ID.                    \n",
       "HIERARCH ESO INS5 VFILT2 NAME = 'Var ND filter CAL A wheel 2' / Variable density\n",
       "HIERARCH ESO INS5 VFILT2 POS = 126.0006 / [deg] Position.                       \n",
       "HIERARCH ESO INS5 VFILT3 DEN = 0.4 / [D] Position.                              \n",
       "HIERARCH ESO INS5 VFILT3 ENC = 82739 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 VFILT3 ID = 'ndfilb1 ' / Device unique ID.                    \n",
       "HIERARCH ESO INS5 VFILT3 NAME = 'Var ND filter CAL B wheel 1' / Variable density\n",
       "HIERARCH ESO INS5 VFILT3 POS = 126.4499 / [deg] Position.                       \n",
       "HIERARCH ESO INS5 VFILT4 DEN = 0.4 / [D] Position.                              \n",
       "HIERARCH ESO INS5 VFILT4 ENC = 82739 / [Enc] Absolute position.                 \n",
       "HIERARCH ESO INS5 VFILT4 ID = 'ndfilb2 ' / Device unique ID.                    \n",
       "HIERARCH ESO INS5 VFILT4 NAME = 'Var ND filter CAL B wheel 2' / Variable density\n",
       "HIERARCH ESO INS5 VFILT4 POS = 126.4499 / [deg] Position.                       \n",
       "HIERARCH ESO DET BINX =      1 / Setup binning factor along X                   \n",
       "HIERARCH ESO DET BINY =      1 / Setup binning factor along Y                   \n",
       "HIERARCH ESO DET CHIPS =     2 / Number of chips in the mosaic                  \n",
       "HIERARCH ESO DET CON PWIPE = T / Periodic wipe                                  \n",
       "HIERARCH ESO DET DEV1 BOARD1 BCKPL = '000010805281' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV1 BOARD1 REV = '5.6.4   ' / Revision                        \n",
       "HIERARCH ESO DET DEV1 BOARD1 SERNO = '000013A6E838' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV1 BOARD1 TRANS = '0000163DF28F' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV1 BOARD1 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV1 BOARD1 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV1 BOARD2 BCKPL = '000010805281' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV1 BOARD2 REV = '5.6.4   ' / Revision                        \n",
       "HIERARCH ESO DET DEV1 BOARD2 SERNO = '000011AA6C53' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV1 BOARD2 TRANS = '0000163DFF54' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV1 BOARD2 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV1 BOARD2 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV1 BOARD3 BCKPL = '000010805281' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV1 BOARD3 REV = '5.6.4   ' / Revision                        \n",
       "HIERARCH ESO DET DEV1 BOARD3 SERNO = '00001458856D' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV1 BOARD3 TRANS = '0000163DEBE4' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV1 BOARD3 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV1 BOARD3 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV1 BOARD4 BCKPL = '000010805281' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV1 BOARD4 REV = '5.6.4   ' / Revision                        \n",
       "HIERARCH ESO DET DEV1 BOARD4 SERNO = '000013A6DAE3' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV1 BOARD4 TRANS = '0000163DD7F8' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV1 BOARD4 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV1 BOARD4 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV1 CHIPS = 1 / Number of chips in the mosaic                 \n",
       "HIERARCH ESO DET DEV1 EXP RDTTIME = 18.844 / [s] Image readout time             \n",
       "HIERARCH ESO DET DEV1 EXP XFERTIM = 18.812 / [s] Image transfer time            \n",
       "HIERARCH ESO DET DEV1 ID = 'ESPRESSO-BLUE' / Detector system Id                 \n",
       "HIERARCH ESO DET DEV1 OUTPUTS = 16 / Number of outputs                          \n",
       "HIERARCH ESO DET DEV1 REV = '0.4.1   ' / Revision                               \n",
       "HIERARCH ESO DET DEV1 SHUT ID = 'ShEspresso' / Shutter unique identifier        \n",
       "HIERARCH ESO DET DEV1 SHUT TMCLOS = 0.011 / [s] Time taken to close shutter     \n",
       "HIERARCH ESO DET DEV1 SHUT TMOPEN = 0.021 / [s] Time taken to open shutter      \n",
       "HIERARCH ESO DET DEV1 SHUT TYPE = 'Illy    ' / Shutter type                     \n",
       "HIERARCH ESO DET DEV1 SOFW BASE = '306134  ' / Base software version            \n",
       "HIERARCH ESO DET DEV1 SOFW DETMOD = '315314  ' / Detector module revision       \n",
       "HIERARCH ESO DET DEV1 SOFW MODE = 'NORMAL  ' / Software operational mode        \n",
       "HIERARCH ESO DET DEV1 SOFW OPT = '306134  ' / Optical software version          \n",
       "HIERARCH ESO DET DEV2 BOARD1 BCKPL = '00001080525C' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV2 BOARD1 SERNO = '000014587F6F' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV2 BOARD1 TRANS = '0000163E0D9B' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV2 BOARD1 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV2 BOARD1 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV2 BOARD2 BCKPL = '00001080525C' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV2 BOARD2 SERNO = '0000163DBCC3' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV2 BOARD2 TRANS = '0000163DA9FA' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV2 BOARD2 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV2 BOARD2 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV2 BOARD3 BCKPL = '00001080525C' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV2 BOARD3 SERNO = '0000163DECA8' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV2 BOARD3 TRANS = '0000163DAACD' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV2 BOARD3 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV2 BOARD3 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV2 BOARD4 BCKPL = '00001080525C' / Serial no (backplane)     \n",
       "HIERARCH ESO DET DEV2 BOARD4 SERNO = '0000163DA5E4' / Serial no (board)         \n",
       "HIERARCH ESO DET DEV2 BOARD4 TRANS = '00001216DA39' / Serial no (transition boar\n",
       "HIERARCH ESO DET DEV2 BOARD4 TYPE = 'FEB     ' / Type                           \n",
       "HIERARCH ESO DET DEV2 BOARD4 VERSION = 1 / Version                              \n",
       "HIERARCH ESO DET DEV2 CHIPS = 1 / Number of chips in the mosaic                 \n",
       "HIERARCH ESO DET DEV2 EXP RDTTIME = 18.844 / [s] Image readout time             \n",
       "HIERARCH ESO DET DEV2 EXP XFERTIM = 18.807 / [s] Image transfer time            \n",
       "HIERARCH ESO DET DEV2 ID = 'ESPRESSO-RED' / Detector system Id                  \n",
       "HIERARCH ESO DET DEV2 OUTPUTS = 16 / Number of outputs                          \n",
       "HIERARCH ESO DET DEV2 REV = '0.4.1   ' / Revision                               \n",
       "HIERARCH ESO DET DEV2 SHUT ID = 'dummy   ' / Shutter unique identifier          \n",
       "HIERARCH ESO DET DEV2 SHUT TMCLOS = 0. / [s] Time taken to close shutter        \n",
       "HIERARCH ESO DET DEV2 SHUT TMOPEN = 0. / [s] Time taken to open shutter         \n",
       "HIERARCH ESO DET DEV2 SHUT TYPE = 'nostatus' / Shutter type                     \n",
       "HIERARCH ESO DET DEV2 SOFW BASE = '306134  ' / Base software version            \n",
       "HIERARCH ESO DET DEV2 SOFW DETMOD = '315314  ' / Detector module revision       \n",
       "HIERARCH ESO DET DEV2 SOFW MODE = 'NORMAL  ' / Software operational mode        \n",
       "HIERARCH ESO DET DEV2 SOFW OPT = '306134  ' / Optical software version          \n",
       "HIERARCH ESO DET DID = 'ESO-VLT-DIC.NGCDCS,ESO-VLT-DIC.NGCCON' / Used di        \n",
       "HIERARCH ESO DET DIT1 =    80. / [s] Actual subintegration time                 \n",
       "HIERARCH ESO DET DKTM =    80. / [s] Dark current time                          \n",
       "HIERARCH ESO DET EXP NO =   16 / Unique exposure ID number                      \n",
       "HIERARCH ESO DET EXP TYPE = 'Normal  ' / Exposure type                          \n",
       "HIERARCH ESO DET NAME = 'ESPRESSO-BLUE' / Name of detector system               \n",
       "HIERARCH ESO DET NDIT =      1 / Number of Sub-Integrations                     \n",
       "HIERARCH ESO DET OUTPUTS =  32 / Number of outputs                              \n",
       "HIERARCH ESO DET READ CURID = 9 / Used readout mode id                          \n",
       "HIERARCH ESO DET READ CURNAME = 'Fast    ' / Used readout mode name             \n",
       "HIERARCH ESO DET UIT1 =    80. / [s] User defined subintegration ti             \n",
       "HIERARCH ESO PRO CATG = 'S2D_SKYSUB_A' / Category of pipeline product frame     \n",
       "HIERARCH ESO PRO ANCESTOR = 'ESPRE.2019-06-02T00:34:42.992.fits'                \n",
       "HIERARCH ESO PRO DID = 'PRO-1.16' / Data dictionary for PRO                     \n",
       "HIERARCH ESO PRO TYPE = 'REDUCED ' / Product type                               \n",
       "HIERARCH ESO PRO TECH = 'ECHELLE ' / Observation technique                      \n",
       "HIERARCH ESO PRO SCIENCE =   T / Scientific product if T                        \n",
       "HIERARCH ESO PRO REC1 ID = 'espdr_sci_red' / Pipeline recipe (unique) identifier\n",
       "HIERARCH ESO PRO REC1 DRS ID = 'cpl-7.1.3' / Data Reduction System identifier   \n",
       "HIERARCH ESO PRO REC1 PIPE ID = 'espdr/2.2.1' / Pipeline (unique) identifier    \n",
       "HIERARCH ESO PRO REC1 RAW1 NAME = 'ESPRE.2019-06-02T00:34:42.992.fits' / File na\n",
       "HIERARCH ESO PRO REC1 RAW1 CATG = 'OBJ_SKY ' / Category of raw frame            \n",
       "HIERARCH ESO PRO DATANCOM =  1 / Number of combined frames                      \n",
       "HIERARCH ESO PRO REC1 CAL1 NAME = 'ESPRESSO_1x1_CCD_geom_config.fits' / File nam\n",
       "HIERARCH ESO PRO REC1 CAL1 CATG = 'CCD_GEOM' / Category of calibration frame    \n",
       "HIERARCH ESO PRO REC1 CAL2 NAME= 'ESPRESSO_SINGLEHR_1x1_reduced_inst_config_201'\n",
       "HIERARCH ESO PRO REC1 CAL2 CATG = 'INST_CONFIG' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL3 NAME = 'ESPRESSO_master_bias_res.fits' / File name of\n",
       "HIERARCH ESO PRO REC1 CAL3 CATG = 'MASTER_BIAS_RES' / Category of calibration fr\n",
       "HIERARCH ESO PRO REC1 CAL3 DATAMD5 = '7032800c7c2814655bd07a206ac9898a' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL4 NAME = 'ESPRESSO_hot_pixels.fits' / File name of cali\n",
       "HIERARCH ESO PRO REC1 CAL4 CATG = 'HOT_PIXEL_MASK' / Category of calibration fra\n",
       "HIERARCH ESO PRO REC1 CAL4 DATAMD5 = '911ea9496fdf55d8fcab167b7e2b9b14' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL5 NAME = 'ESPRESSO_bad_pixels.fits' / File name of cali\n",
       "HIERARCH ESO PRO REC1 CAL5 CATG = 'BAD_PIXEL_MASK' / Category of calibration fra\n",
       "HIERARCH ESO PRO REC1 CAL5 DATAMD5 = '1c8719641d8e27dd61ad45076467da7e' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL6 NAME = 'ESPRESSO_ORDER_TABLE_A.fits' / File name of c\n",
       "HIERARCH ESO PRO REC1 CAL6 CATG = 'ORDER_TABLE_A' / Category of calibration fram\n",
       "HIERARCH ESO PRO REC1 CAL6 DATAMD5 = '43e85456514c3f4a48ab0f8d9535f135' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL7 NAME = 'ESPRESSO_ORDER_TABLE_B.fits' / File name of c\n",
       "HIERARCH ESO PRO REC1 CAL7 CATG = 'ORDER_TABLE_B' / Category of calibration fram\n",
       "HIERARCH ESO PRO REC1 CAL7 DATAMD5 = '4d3c77bbb6ed9e3862fbbb44ebffc202' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL8 NAME = 'ESPRESSO_ORDER_PROFILE_A.fits' / File name of\n",
       "HIERARCH ESO PRO REC1 CAL8 CATG = 'ORDER_PROFILE_A' / Category of calibration fr\n",
       "HIERARCH ESO PRO REC1 CAL8 DATAMD5 = '5f9f45f27ba3e3be81f4d909bcf149e1' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL9 NAME = 'ESPRESSO_ORDER_PROFILE_B.fits' / File name of\n",
       "HIERARCH ESO PRO REC1 CAL9 CATG = 'ORDER_PROFILE_B' / Category of calibration fr\n",
       "HIERARCH ESO PRO REC1 CAL9 DATAMD5 = 'ae0666f99aad72e5187e2352ea571acc' / MD5 si\n",
       "HIERARCH ESO PRO REC1 CAL10 NAME = 'ESPRESSO_FLAT_A.fits' / File name of calibra\n",
       "HIERARCH ESO PRO REC1 CAL10 CATG = 'FSPECTRUM_A' / Category of calibration frame\n",
       "HIERARCH ESO PRO REC1 CAL10 DATAMD5 = 'ffe79bd939c2e0de5df8bb5ca54a25cb' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL11 NAME = 'ESPRESSO_FLAT_B.fits' / File name of calibra\n",
       "HIERARCH ESO PRO REC1 CAL11 CATG = 'FSPECTRUM_B' / Category of calibration frame\n",
       "HIERARCH ESO PRO REC1 CAL11 DATAMD5 = '44c8868fcdaf4aa6e34a8c06c3dd9b85' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL12 NAME = 'ESPRESSO_BLAZE_A.fits' / File name of calibr\n",
       "HIERARCH ESO PRO REC1 CAL12 CATG = 'BLAZE_A ' / Category of calibration frame   \n",
       "HIERARCH ESO PRO REC1 CAL12 DATAMD5 = '2c28c494626b0d47f8d59dfe0ba26530' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL13 NAME = 'ESPRESSO_BLAZE_B.fits' / File name of calibr\n",
       "HIERARCH ESO PRO REC1 CAL13 CATG = 'BLAZE_B ' / Category of calibration frame   \n",
       "HIERARCH ESO PRO REC1 CAL13 DATAMD5 = '714062db1f5ee15354ffc0da540e4b9c' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL14 NAME = 'ESPRESSO_WAVE_MATRIX_A.fits' / File name of \n",
       "HIERARCH ESO PRO REC1 CAL14 CATG = 'WAVE_MATRIX_THAR_FP_A' / Category of calibra\n",
       "HIERARCH ESO PRO REC1 CAL14 DATAMD5 = 'f3acce9f424092bc643c946cb7497fb8' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL15 NAME = 'ESPRESSO_WAVE_MATRIX_B.fits' / File name of \n",
       "HIERARCH ESO PRO REC1 CAL15 CATG = 'WAVE_MATRIX_FP_THAR_B' / Category of calibra\n",
       "HIERARCH ESO PRO REC1 CAL15 DATAMD5 = 'b4a3450c4afb4a7a99bafe594caf9cc0' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL16 NAME = 'ESPRESSO_DLL_MATRIX_A.fits' / File name of c\n",
       "HIERARCH ESO PRO REC1 CAL16 CATG = 'DLL_MATRIX_THAR_FP_A' / Category of calibrat\n",
       "HIERARCH ESO PRO REC1 CAL16 DATAMD5 = '8b4a82318eee18550ac6bb9be3436b6a' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL17 NAME = 'ESPRESSO_DLL_MATRIX_B.fits' / File name of c\n",
       "HIERARCH ESO PRO REC1 CAL17 CATG = 'DLL_MATRIX_FP_THAR_B' / Category of calibrat\n",
       "HIERARCH ESO PRO REC1 CAL17 DATAMD5 = '7ee5d45180ac1c79f0e7f71b20ea329c' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL18 NAME = 'ESPRESSO_REL_EFF_B.fits' / File name of cali\n",
       "HIERARCH ESO PRO REC1 CAL18 CATG = 'REL_EFF_B' / Category of calibration frame  \n",
       "HIERARCH ESO PRO REC1 CAL18 DATAMD5 = 'e6c1e4824a9ecdef5db7da2c36cfabdb' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL19 NAME = 'ESPRESSO_ABS_EFF_A.fits' / File name of cali\n",
       "HIERARCH ESO PRO REC1 CAL19 CATG = 'ABS_EFF_A' / Category of calibration frame  \n",
       "HIERARCH ESO PRO REC1 CAL19 DATAMD5 = '7bd24893f9b7acb502fb413135a7e07a' / MD5 s\n",
       "HIERARCH ESO PRO REC1 CAL20 NAME = 'ESPRESSO_EXTINCTION_TABLE.fits' / File name \n",
       "HIERARCH ESO PRO REC1 CAL20 CATG = 'EXT_TABLE' / Category of calibration frame  \n",
       "HIERARCH ESO PRO REC1 CAL21 NAME = 'ESPRESSO_mask_lut.fits' / File name of calib\n",
       "HIERARCH ESO PRO REC1 CAL21 CATG = 'MASK_LUT' / Category of calibration frame   \n",
       "HIERARCH ESO PRO REC1 CAL22 NAME = 'ESPRESSO_SINGLEHR_1x1_FLUX_TEMPLATE.fits'   \n",
       "HIERARCH ESO PRO REC1 CAL22 CATG = 'FLUX_TEMPLATE' / Category of calibration fra\n",
       "HIERARCH ESO PRO REC1 CAL23 NAME = 'ESPRESSO_F9.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL23 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL24 NAME = 'ESPRESSO_G2.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL24 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL25 NAME = 'ESPRESSO_G8.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL25 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL26 NAME = 'ESPRESSO_G9.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL26 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL27 NAME = 'ESPRESSO_K2.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL27 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL28 NAME = 'ESPRESSO_K6.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL28 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL29 NAME = 'ESPRESSO_M0.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL29 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL30 NAME = 'ESPRESSO_M2.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL30 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL31 NAME = 'ESPRESSO_M3.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL31 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL32 NAME = 'ESPRESSO_M4.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL32 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 CAL33 NAME = 'ESPRESSO_M5.fits' / File name of calibration\n",
       "HIERARCH ESO PRO REC1 CAL33 CATG = 'MASK_TABLE' / Category of calibration frame \n",
       "HIERARCH ESO PRO REC1 PARAM1 NAME = 'ovsc_sig_clip_method' / method for sigma cl\n",
       "HIERARCH ESO PRO REC1 PARAM1 VALUE = 'mean    ' / Default: 'mean'               \n",
       "HIERARCH ESO PRO REC1 PARAM2 NAME = 'ovsc_ksigma' / ksigma for sigma clipping in\n",
       "HIERARCH ESO PRO REC1 PARAM2 VALUE = '4       ' / Default: 4                    \n",
       "HIERARCH ESO PRO REC1 PARAM3 NAME = 'ovsc_max_iter' / maximal number of iteratio\n",
       "HIERARCH ESO PRO REC1 PARAM3 VALUE = '10      ' / Default: 10                   \n",
       "HIERARCH ESO PRO REC1 PARAM4 NAME = 'background_sw' / Background subtraction act\n",
       "HIERARCH ESO PRO REC1 PARAM4 VALUE = 'off     ' / Default: 'on'                 \n",
       "HIERARCH ESO PRO REC1 PARAM5 NAME = 'sci_bkgr_grid_size_x' / Grid size in x used\n",
       "HIERARCH ESO PRO REC1 PARAM5 VALUE = '577     ' / Default: 577                  \n",
       "HIERARCH ESO PRO REC1 PARAM6 NAME = 'sci_bkgr_grid_size_y' / Grid size in y used\n",
       "HIERARCH ESO PRO REC1 PARAM6 VALUE = '256     ' / Default: 256                  \n",
       "HIERARCH ESO PRO REC1 PARAM7 NAME = 'wave_cal_source' / Wavelength calibration s\n",
       "HIERARCH ESO PRO REC1 PARAM7 VALUE = 'THAR    ' / Default: 'THAR'               \n",
       "HIERARCH ESO PRO REC1 PARAM8 NAME = 'mask_table_id' / Mask table to be used, def\n",
       "HIERARCH ESO PRO REC1 PARAM8 VALUE = 'XX      ' / Default: 'XX'                 \n",
       "HIERARCH ESO PRO REC1 PARAM9 NAME = 'rv_center' / Approximate RV. In case of def\n",
       "HIERARCH ESO PRO REC1 PARAM9 VALUE = '-9999   ' / Default: -9999                \n",
       "HIERARCH ESO PRO REC1 PARAM10 NAME = 'rv_range' / Range for the RV table.       \n",
       "HIERARCH ESO PRO REC1 PARAM10 VALUE = '20      ' / Default: 20                  \n",
       "HIERARCH ESO PRO REC1 PARAM11 NAME = 'rv_step ' / Range's step for the RV table.\n",
       "HIERARCH ESO PRO REC1 PARAM11 VALUE = '0.5     ' / Default: 0.5                 \n",
       "HIERARCH ESO PRO REC1 PARAM12 NAME = 'extraction_method' / Method used to extrac\n",
       "HIERARCH ESO PRO REC1 PARAM12 VALUE = 'horne   ' / Default: 'horne'             \n",
       "HIERARCH ESO PRO REC1 PARAM13 NAME = 'ksigma_cosmic' / ksigma for removing cosmi\n",
       "HIERARCH ESO PRO REC1 PARAM13 VALUE = '3.5     ' / Default: 3.5                 \n",
       "HIERARCH ESO PRO REC1 PARAM14 NAME = 'bias_res_removal_sw' / Flag indicating to \n",
       "HIERARCH ESO PRO REC1 PARAM14 VALUE = 'on      ' / Default: 'on'                \n",
       "HIERARCH ESO PRO REC1 PARAM15 NAME = 'flux_correction_type' / Flux correction: N\n",
       "HIERARCH ESO PRO REC1 PARAM15 VALUE = 'AUTO    ' / Default: 'AUTO'              \n",
       "HIERARCH ESO PRO REC1 PARAM16 NAME = 'drift_correction_sw' / Drift correction ac\n",
       "HIERARCH ESO PRO REC1 PARAM16 VALUE = 'on      ' / Default: 'on'                \n",
       "HIERARCH ESO PRO REC1 PARAM17 NAME = 'drift_method_fp' / Method adopted to compu\n",
       "HIERARCH ESO PRO REC1 PARAM17 VALUE = 'flux_global_drift_global_sequential_fit' \n",
       "HIERARCH ESO PRO REC1 PARAM18 NAME = 'drift_space' / Space to compute drift (pix\n",
       "HIERARCH ESO PRO REC1 PARAM18 VALUE = 'pixel   ' / Default: 'pixel'             \n",
       "HIERARCH ESO PRO REC1 PARAM19 NAME = 'drift_ksigma' / ksigma for computing drift\n",
       "HIERARCH ESO PRO REC1 PARAM19 VALUE = '50      ' / Default: 50                  \n",
       "HIERARCH ESO PRO REC1 PARAM20 NAME = 'sky_sub_method' / Method used to subtract \n",
       "HIERARCH ESO PRO REC1 PARAM20 VALUE = 'pixel-by-pixel' / Default: 'pixel-by-pixe\n",
       "HIERARCH ESO PRO REC1 PARAM21 NAME = 'sky_sub_sliding_box_size' / Sliding box si\n",
       "HIERARCH ESO PRO REC1 PARAM21 VALUE = '200     ' / Default: 50                  \n",
       "HIERARCH ESO PRO REC1 PARAM22 NAME = 'slit_loss' / Slit loss in flux calibration\n",
       "HIERARCH ESO PRO REC1 PARAM22 VALUE = '-1      ' / Default: -1                  \n",
       "HIERARCH ESO ADA2 ABSROT END = 88.06623 / [deg] Abs rot angle at exp end        \n",
       "HIERARCH ESO ADA2 ABSROT PPOS = 'NEG     ' / sign of probe position             \n",
       "HIERARCH ESO ADA2 ABSROT START = 88.06623 / [deg] Abs rot angle at exp start    \n",
       "HIERARCH ESO ADA2 GUID DEC = -3.10771 / [deg] -03:06:27.7 Guide star DEC J2000  \n",
       "HIERARCH ESO ADA2 GUID RA = 225.627471 / [deg] 15:02:30.5 Guide star RA J2000   \n",
       "HIERARCH ESO ADA2 GUID STATUS = 'ON      ' / Status of autoguider               \n",
       "HIERARCH ESO ADA2 POSANG =  0. / [deg] Position angle at start                  \n",
       "HIERARCH ESO OCS ACQ2 FWHMX = 27.71 / FWHM X (in pixel) after tel. preset.      \n",
       "HIERARCH ESO OCS ACQ2 FWHMX ARCSEC = 1.15 / FWHM X (in arcsec) after tel. pr    \n",
       "HIERARCH ESO OCS ACQ2 FWHMY = 23.06 / FWHM Y (in pixel) after tel. preset.      \n",
       "HIERARCH ESO OCS ACQ2 FWHMY ARCSEC = 0.96 / FWHM Y (in arcsec) after tel. pr    \n",
       "HIERARCH ESO OCS ACQ2 POSX = 231.94 / pos. X (in pixel) after tel. preset.      \n",
       "HIERARCH ESO OCS ACQ2 POSY = 316.51 / pos. Y (in pixel) after tel. preset.      \n",
       "HIERARCH ESO OCS DET1 IMGNAME = 'ESPRESSO_SINGLEHR_OBS' / Data File Name.       \n",
       "HIERARCH ESO OCS EM EXPTIME = 3.72 / EM exposure time.                          \n",
       "HIERARCH ESO OCS EM NSAMPLE = 22 / No of EM samples during the science exposure.\n",
       "HIERARCH ESO OCS EM OBJ0 CTMAX = 240148. / Obj-i channel max val.               \n",
       "HIERARCH ESO OCS EM OBJ0 CTMEAN = 192620.275 / Obj-i channel mean val.          \n",
       "HIERARCH ESO OCS EM OBJ0 CTMIN = 44391. / Obj-i channel min val.                \n",
       "HIERARCH ESO OCS EM OBJ0 CTRMS = 7941.132 / Obj-i channel rms val.              \n",
       "HIERARCH ESO OCS EM OBJ0 CTTOT = 4237646.04882 / Obj-i channel tot val.         \n",
       "HIERARCH ESO OCS EM OBJ0 QCTMMEAN = T / Obj-i channel TMMEAN quality ctrl flag. \n",
       "HIERARCH ESO OCS EM OBJ0 SNR = 3810.744261 / Obj-i channel final SNR.           \n",
       "HIERARCH ESO OCS EM OBJ0 TMMEAN = 0.523 / Obj-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM OBJ1 CTMAX = 1399723. / Obj-i channel max val.              \n",
       "HIERARCH ESO OCS EM OBJ1 CTMEAN = 1126375.448 / Obj-i channel mean val.         \n",
       "HIERARCH ESO OCS EM OBJ1 CTMIN = 262941. / Obj-i channel min val.               \n",
       "HIERARCH ESO OCS EM OBJ1 CTRMS = 46394.096 / Obj-i channel rms val.             \n",
       "HIERARCH ESO OCS EM OBJ1 CTTOT = 24780259.86595 / Obj-i channel tot val.        \n",
       "HIERARCH ESO OCS EM OBJ1 QCTMMEAN = T / Obj-i channel TMMEAN quality ctrl flag. \n",
       "HIERARCH ESO OCS EM OBJ1 SNR = 9455.57899 / Obj-i channel final SNR.            \n",
       "HIERARCH ESO OCS EM OBJ1 TMMEAN = 0.524 / Obj-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM OBJ2 CTMAX = 1987582. / Obj-i channel max val.              \n",
       "HIERARCH ESO OCS EM OBJ2 CTMEAN = 1601673.286 / Obj-i channel mean val.         \n",
       "HIERARCH ESO OCS EM OBJ2 CTMIN = 375075. / Obj-i channel min val.               \n",
       "HIERARCH ESO OCS EM OBJ2 CTRMS = 65511.987 / Obj-i channel rms val.             \n",
       "HIERARCH ESO OCS EM OBJ2 CTTOT = 35236812.292713 / Obj-i channel tot val.       \n",
       "HIERARCH ESO OCS EM OBJ2 EFFICIENCY = 0.641039 / Obj-i channel efficiency       \n",
       "HIERARCH ESO OCS EM OBJ2 EXPECTED = 2498560. / Obj-1 channel expected coun      \n",
       "HIERARCH ESO OCS EM OBJ2 QCTMMEAN = T / Obj-i channel TMMEAN quality ctrl flag. \n",
       "HIERARCH ESO OCS EM OBJ2 SNR = 11339.315406 / Obj-i channel final SNR.          \n",
       "HIERARCH ESO OCS EM OBJ2 TMMEAN = 0.523 / Obj-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM OBJ3 CTMAX = 686390. / Obj-i channel max val.               \n",
       "HIERARCH ESO OCS EM OBJ3 CTMEAN = 552517.269 / Obj-i channel mean val.          \n",
       "HIERARCH ESO OCS EM OBJ3 CTMIN = 127164. / Obj-i channel min val.               \n",
       "HIERARCH ESO OCS EM OBJ3 CTRMS = 22635.416 / Obj-i channel rms val.             \n",
       "HIERARCH ESO OCS EM OBJ3 CTTOT = 12155379.923795 / Obj-i channel tot val.       \n",
       "HIERARCH ESO OCS EM OBJ3 QCTMMEAN = T / Obj-i channel TMMEAN quality ctrl flag. \n",
       "HIERARCH ESO OCS EM OBJ3 SNR = 6492.030712 / Obj-i channel final SNR.           \n",
       "HIERARCH ESO OCS EM OBJ3 TMMEAN = 0.523 / Obj-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM REF0 CTMAX = 663. / Ref-i channel max val.                  \n",
       "HIERARCH ESO OCS EM REF0 CTMEAN = -128.814 / Ref-i channel mean val.            \n",
       "HIERARCH ESO OCS EM REF0 CTMIN = -598. / Ref-i channel min val.                 \n",
       "HIERARCH ESO OCS EM REF0 CTRMS = 69.113 / Ref-i channel rms val.                \n",
       "HIERARCH ESO OCS EM REF0 CTTOT = -2833.911991 / Ref-i channel tot val.          \n",
       "HIERARCH ESO OCS EM REF0 SNR = -99999.999 / Ref-i channel final SNR.            \n",
       "HIERARCH ESO OCS EM REF0 TMMEAN = 0.446 / Ref-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM REF1 CTMAX = 1699. / Ref-i channel max val.                 \n",
       "HIERARCH ESO OCS EM REF1 CTMEAN = -39.93 / Ref-i channel mean val.              \n",
       "HIERARCH ESO OCS EM REF1 CTMIN = -724. / Ref-i channel min val.                 \n",
       "HIERARCH ESO OCS EM REF1 CTRMS = 112.11 / Ref-i channel rms val.                \n",
       "HIERARCH ESO OCS EM REF1 CTTOT = -878.451325 / Ref-i channel tot val.           \n",
       "HIERARCH ESO OCS EM REF1 SNR = -99999.999 / Ref-i channel final SNR.            \n",
       "HIERARCH ESO OCS EM REF1 TMMEAN = 0.756 / Ref-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM REF2 CTMAX = 1633. / Ref-i channel max val.                 \n",
       "HIERARCH ESO OCS EM REF2 CTMEAN = 220.617 / Ref-i channel mean val.             \n",
       "HIERARCH ESO OCS EM REF2 CTMIN = -1184. / Ref-i channel min val.                \n",
       "HIERARCH ESO OCS EM REF2 CTRMS = 170.402 / Ref-i channel rms val.               \n",
       "HIERARCH ESO OCS EM REF2 CTTOT = 4853.568768 / Ref-i channel tot val.           \n",
       "HIERARCH ESO OCS EM REF2 SNR = 9.494801 / Ref-i channel final SNR.              \n",
       "HIERARCH ESO OCS EM REF2 TMMEAN = 0.181 / Ref-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM REF3 CTMAX = 225. / Ref-i channel max val.                  \n",
       "HIERARCH ESO OCS EM REF3 CTMEAN = -291.449 / Ref-i channel mean val.            \n",
       "HIERARCH ESO OCS EM REF3 CTMIN = -938. / Ref-i channel min val.                 \n",
       "HIERARCH ESO OCS EM REF3 CTRMS = 63.874 / Ref-i channel rms val.                \n",
       "HIERARCH ESO OCS EM REF3 CTTOT = -6411.87533 / Ref-i channel tot val.           \n",
       "HIERARCH ESO OCS EM REF3 SNR = -99999.999 / Ref-i channel final SNR.            \n",
       "HIERARCH ESO OCS EM REF3 TMMEAN = 0.368 / Ref-i channel mean time val.          \n",
       "HIERARCH ESO OCS EM TABLE =  T / flag to create the EM bin Table.               \n",
       "HIERARCH ESO OCS ENABLED FE = '2       ' / Enabled front end IDs                \n",
       "HIERARCH ESO OCS OBJ BV = 0.17 / Target color index (B-V).                      \n",
       "HIERARCH ESO OCS OBJ MV = 6.618 / Target V magnitude.                           \n",
       "HIERARCH ESO OCS OBJ RV = -22.4 / Target radial velocity.                       \n",
       "HIERARCH ESO OCS OBJ SP TYPE = 'A4/5IV/V' / Target spectral type.               \n",
       "HIERARCH ESO OCS OBJ Z EM = 0. / Target redshit from emission lines.            \n",
       "HIERARCH ESO OCS STABIL2 FIBERX = 112. / fiber X position.                      \n",
       "HIERARCH ESO OCS STABIL2 FIBERY = 111. / fiber Y position.                      \n",
       "HIERARCH ESO OCS TCCD FS INTIM = T / flag to create the FS integrated image.    \n",
       "HIERARCH ESO OCS TEL NO =    1 / Number of active telescopes (1 - 4).           \n",
       "HIERARCH ESO OCS TEL1 ST =   F / Availability of the telescope.                 \n",
       "HIERARCH ESO OCS TEL2 ST =   T / Availability of the telescope.                 \n",
       "HIERARCH ESO OCS TEL3 ST =   F / Availability of the telescope.                 \n",
       "HIERARCH ESO OCS TEL4 ST =   F / Availability of the telescope.                 \n",
       "HIERARCH ESO OCS WAVECAL SOURCE = 'THAR    ' / Calibration frame to be associate\n",
       "HIERARCH ESO RV STEP =     0.5 / Coordinate increment per pixel                 \n",
       "HIERARCH ESO RV START =  -42.4 / Coordinate at reference pixel                  \n",
       "HIERARCH ESO QC EXT0 ROX0 ROY0 BIAS RON = 5.10280080635889 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX0 ROY1 BIAS RON = 5.49850789594775 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX1 ROY0 BIAS RON = 5.33622310645138 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX1 ROY1 BIAS RON = 4.78314923519768 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX2 ROY0 BIAS RON = 5.21749875528287 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX2 ROY1 BIAS RON = 5.11758581304404 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX3 ROY0 BIAS RON = 5.68545353437639 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX3 ROY1 BIAS RON = 4.69005223215305 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX4 ROY0 BIAS RON = 4.87886073810397 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX4 ROY1 BIAS RON = 5.90951953467146 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX5 ROY0 BIAS RON = 4.97827762159947 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX5 ROY1 BIAS RON = 5.76127087665883 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX6 ROY0 BIAS RON = 5.15244998379074 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX6 ROY1 BIAS RON = 5.55018566448092 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX7 ROY0 BIAS RON = 5.53043196649166 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT0 ROX7 ROY1 BIAS RON = 5.26701763977042 / RON[ADU] for ext 0,\n",
       "HIERARCH ESO QC EXT1 ROX0 ROY0 BIAS RON = 4.1429589785672 / RON[ADU] for ext 1, \n",
       "HIERARCH ESO QC EXT1 ROX0 ROY1 BIAS RON = 4.32187480322318 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX1 ROY0 BIAS RON = 4.35889894354071 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX1 ROY1 BIAS RON = 4.25816000791756 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX2 ROY0 BIAS RON = 4.52936332554924 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX2 ROY1 BIAS RON = 4.19784583249775 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX3 ROY0 BIAS RON = 4.84405137466472 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX3 ROY1 BIAS RON = 4.12994904287448 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX4 ROY0 BIAS RON = 4.12982002873439 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX4 ROY1 BIAS RON = 4.29243272107309 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX5 ROY0 BIAS RON = 4.29466649145243 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX5 ROY1 BIAS RON = 4.23889652955798 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX6 ROY0 BIAS RON = 4.54526350035469 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX6 ROY1 BIAS RON = 4.25365295912472 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX7 ROY0 BIAS RON = 4.93957520841179 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT1 ROX7 ROY1 BIAS RON = 4.07872236485662 / RON[ADU] for ext 1,\n",
       "HIERARCH ESO QC EXT0 ROX0 ROY0 MAX FLUX = 2294. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX0 ROY1 MAX FLUX = 2170. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX1 ROY0 MAX FLUX = 2262. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX1 ROY1 MAX FLUX = 2126. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX2 ROY0 MAX FLUX = 2207. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX2 ROY1 MAX FLUX = 2030. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX3 ROY0 MAX FLUX = 2175. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX3 ROY1 MAX FLUX = 2070. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX4 ROY0 MAX FLUX = 2044. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX4 ROY1 MAX FLUX = 2030. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX5 ROY0 MAX FLUX = 1756. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX5 ROY1 MAX FLUX = 1694. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX6 ROY0 MAX FLUX = 1626. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX6 ROY1 MAX FLUX = 1646. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX7 ROY0 MAX FLUX = 1359. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT0 ROX7 ROY1 MAX FLUX = 1370. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX0 ROY0 MAX FLUX = 1978. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX0 ROY1 MAX FLUX = 1875. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX1 ROY0 MAX FLUX = 2220. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX1 ROY1 MAX FLUX = 2110. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX2 ROY0 MAX FLUX = 2351. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX2 ROY1 MAX FLUX = 2291. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX3 ROY0 MAX FLUX = 2463. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX3 ROY1 MAX FLUX = 2375. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX4 ROY0 MAX FLUX = 2468. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX4 ROY1 MAX FLUX = 2411. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX5 ROY0 MAX FLUX = 2538. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX5 ROY1 MAX FLUX = 2466. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX6 ROY0 MAX FLUX = 2562. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX6 ROY1 MAX FLUX = 2466. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX7 ROY0 MAX FLUX = 2383. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC EXT1 ROX7 ROY1 MAX FLUX = 2282. / Max flux [ADU], raw image     \n",
       "HIERARCH ESO QC SATURATION CHECK = 1 / Saturation [ADU] QC                      \n",
       "HIERARCH ESO QC ORDER1 COSMIC NB = 219 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER2 COSMIC NB = 260 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER3 COSMIC NB = 81 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER4 COSMIC NB = 99 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER5 COSMIC NB = 116 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER6 COSMIC NB = 122 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER7 COSMIC NB = 54 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER8 COSMIC NB = 64 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER9 COSMIC NB = 69 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER10 COSMIC NB = 64 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER11 COSMIC NB = 18 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER12 COSMIC NB = 33 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER13 COSMIC NB = 85 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER14 COSMIC NB = 125 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER15 COSMIC NB = 24 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER16 COSMIC NB = 60 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER17 COSMIC NB = 5 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER18 COSMIC NB = 4 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER19 COSMIC NB = 3 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER20 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER21 COSMIC NB = 11 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER22 COSMIC NB = 8 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER23 COSMIC NB = 5 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER24 COSMIC NB = 27 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER25 COSMIC NB = 3 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER26 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER27 COSMIC NB = 1 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER28 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER29 COSMIC NB = 1 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER30 COSMIC NB = 1 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER31 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER32 COSMIC NB = 17 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER33 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER34 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER35 COSMIC NB = 1 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER36 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER37 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER38 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER39 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER40 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER41 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER42 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER43 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER44 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER45 COSMIC NB = 3 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER46 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER47 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER48 COSMIC NB = 3 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER49 COSMIC NB = 1 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER50 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER51 COSMIC NB = 1 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER52 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER53 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER54 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER55 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER56 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER57 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER58 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER59 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER60 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER61 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER62 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER63 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER64 COSMIC NB = 3 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER65 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER66 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER67 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER68 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER69 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER70 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER71 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER72 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER73 COSMIC NB = 14 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER74 COSMIC NB = 18 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER75 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER76 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER77 COSMIC NB = 4 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER78 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER79 COSMIC NB = 3 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER80 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER81 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER82 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER83 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER84 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER85 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER86 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER87 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER88 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER89 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER90 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER91 COSMIC NB = 654 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER92 COSMIC NB = 896 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER93 COSMIC NB = 64 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER94 COSMIC NB = 100 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER95 COSMIC NB = 2 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER96 COSMIC NB = 4 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER97 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER98 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER99 COSMIC NB = 0 / Cosmics number in the order             \n",
       "HIERARCH ESO QC ORDER100 COSMIC NB = 7 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER101 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER102 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER103 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER104 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER105 COSMIC NB = 20 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER106 COSMIC NB = 1 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER107 COSMIC NB = 2 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER108 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER109 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER110 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER111 COSMIC NB = 2 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER112 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER113 COSMIC NB = 11 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER114 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER115 COSMIC NB = 5 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER116 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER117 COSMIC NB = 1 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER118 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER119 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER120 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER121 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER122 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER123 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER124 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER125 COSMIC NB = 1 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER126 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER127 COSMIC NB = 10 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER128 COSMIC NB = 10 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER129 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER130 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER131 COSMIC NB = 5 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER132 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER133 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER134 COSMIC NB = 18 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER135 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER136 COSMIC NB = 7 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER137 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER138 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER139 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER140 COSMIC NB = 5 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER141 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER142 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER143 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER144 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER145 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER146 COSMIC NB = 5 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER147 COSMIC NB = 22 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER148 COSMIC NB = 24 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER149 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER150 COSMIC NB = 16 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER151 COSMIC NB = 15 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER152 COSMIC NB = 11 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER153 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER154 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER155 COSMIC NB = 5 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER156 COSMIC NB = 6 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER157 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER158 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER159 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER160 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER161 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER162 COSMIC NB = 3 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER163 COSMIC NB = 44 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER164 COSMIC NB = 29 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER165 COSMIC NB = 7 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER166 COSMIC NB = 11 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER167 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER168 COSMIC NB = 5 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER169 COSMIC NB = 14 / Cosmics number in the order           \n",
       "HIERARCH ESO QC ORDER170 COSMIC NB = 0 / Cosmics number in the order            \n",
       "HIERARCH ESO QC ORDER1 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER2 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER3 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER4 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER5 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER6 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER7 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER8 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER9 COSMIC NB2 = 0 / Number of cosmics found in each order (2\n",
       "HIERARCH ESO QC ORDER10 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER11 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER12 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER13 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER14 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER15 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER16 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER17 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER18 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER19 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER20 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER21 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER22 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER23 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER24 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER25 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER26 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER27 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER28 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER29 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER30 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER31 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER32 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER33 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER34 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER35 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER36 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER37 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER38 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER39 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER40 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER41 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER42 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER43 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER44 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER45 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER46 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER47 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER48 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER49 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER50 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER51 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER52 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER53 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER54 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER55 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER56 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER57 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER58 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER59 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER60 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER61 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER62 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER63 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER64 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER65 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER66 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER67 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER68 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER69 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER70 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER71 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER72 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER73 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER74 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER75 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER76 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER77 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER78 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER79 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER80 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER81 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER82 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER83 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER84 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER85 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER86 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER87 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER88 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER89 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER90 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER91 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER92 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER93 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER94 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER95 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER96 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER97 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER98 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER99 COSMIC NB2 = 0 / Number of cosmics found in each order (\n",
       "HIERARCH ESO QC ORDER100 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER101 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER102 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER103 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER104 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER105 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER106 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER107 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER108 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER109 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER110 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER111 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER112 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER113 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER114 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER115 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER116 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER117 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER118 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER119 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER120 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER121 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER122 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER123 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER124 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER125 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER126 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER127 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER128 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER129 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER130 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER131 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER132 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER133 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER134 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER135 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER136 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER137 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER138 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER139 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER140 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER141 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER142 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER143 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER144 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER145 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER146 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER147 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER148 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER149 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER150 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER151 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER152 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER153 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER154 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER155 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER156 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER157 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER158 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER159 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER160 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER161 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER162 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER163 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER164 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER165 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER166 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER167 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER168 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER169 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER170 COSMIC NB2 = 0 / Number of cosmics found in each order \n",
       "HIERARCH ESO QC ORDER1 SNR = 18.0702997964358 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER2 SNR = 16.8821668419073 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER3 SNR = 21.2509754318397 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER4 SNR = 20.1991682299804 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER5 SNR = 32.1663794399602 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER6 SNR = 30.7496350062817 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER7 SNR = 34.7684125755878 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER8 SNR = 33.4552219629854 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER9 SNR = 35.5012840879116 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER10 SNR = 34.1045560814128 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER11 SNR = 46.28309033909 / SNR in the order                 \n",
       "HIERARCH ESO QC ORDER12 SNR = 44.5584045488272 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER13 SNR = 44.4871366704534 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER14 SNR = 43.0234760893502 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER15 SNR = 39.2791305385188 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER16 SNR = 37.6798853993747 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER17 SNR = 56.4908502045273 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER18 SNR = 54.5441670768434 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER19 SNR = 59.4026028751448 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER20 SNR = 57.4176452269737 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER21 SNR = 62.7984279342968 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER22 SNR = 60.7740233166368 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER23 SNR = 59.0707723582939 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER24 SNR = 57.1006549181956 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER25 SNR = 51.7085717652878 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER26 SNR = 50.065412719862 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER27 SNR = 68.4338290961708 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER28 SNR = 65.961330349563 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER29 SNR = 71.2743940623726 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER30 SNR = 69.1571699863865 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER31 SNR = 73.0338402524418 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER32 SNR = 70.4482642239705 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER33 SNR = 74.0066903600408 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER34 SNR = 71.3117155739295 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER35 SNR = 76.4763512695258 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER36 SNR = 73.8117291526091 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER37 SNR = 75.4970298682603 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER38 SNR = 72.95287510022 / SNR in the order                 \n",
       "HIERARCH ESO QC ORDER39 SNR = 72.5325457074172 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER40 SNR = 70.0051553248833 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER41 SNR = 52.0224770067854 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER42 SNR = 50.2437370626768 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER43 SNR = 74.4539313170395 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER44 SNR = 71.8045605476235 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER45 SNR = 84.5939980406399 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER46 SNR = 81.9601472619074 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER47 SNR = 87.4203621406461 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER48 SNR = 84.6893432576425 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER49 SNR = 86.7822549805663 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER50 SNR = 84.1064222765704 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER51 SNR = 92.6336137635857 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER52 SNR = 89.6329907551945 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER53 SNR = 94.0615260308639 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER54 SNR = 90.9571179545262 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER55 SNR = 93.9253471818469 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER56 SNR = 91.1188288248954 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER57 SNR = 95.3832682704451 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER58 SNR = 92.6666694406091 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER59 SNR = 96.5918371807261 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER60 SNR = 93.3950370682275 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER61 SNR = 98.5270264899109 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER62 SNR = 95.7993486062936 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER63 SNR = 99.1609962793945 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER64 SNR = 96.3082140864543 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER65 SNR = 99.0002073552613 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER66 SNR = 96.3196093383532 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER67 SNR = 99.126034561848 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER68 SNR = 96.7084822848734 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER69 SNR = 94.4456938807242 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER70 SNR = 91.9633958740785 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER71 SNR = 52.0295563264844 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER72 SNR = 50.2732733125669 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER73 SNR = 96.5904502693309 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER74 SNR = 94.0488562618506 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER75 SNR = 98.9458939956459 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER76 SNR = 96.4380449301955 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER77 SNR = 101.262132412634 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER78 SNR = 98.6235958232374 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER79 SNR = 99.6165151141615 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER80 SNR = 97.4243462617897 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER81 SNR = 104.492694556218 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER82 SNR = 101.948936704165 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER83 SNR = 103.915415919218 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER84 SNR = 101.26886794176 / SNR in the order                \n",
       "HIERARCH ESO QC ORDER85 SNR = 101.311598337354 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER86 SNR = 98.6372315869043 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER87 SNR = 99.0244387799495 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER88 SNR = 96.7039190934557 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER89 SNR = 90.1991206697366 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER90 SNR = 86.7557294506043 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER91 SNR = 38.0019169473636 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER92 SNR = 39.6692878219314 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER93 SNR = 94.4969041686448 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER94 SNR = 93.6166551685676 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER95 SNR = 98.8566128990249 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER96 SNR = 97.0463578916491 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER97 SNR = 108.048208506273 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER98 SNR = 105.822281234525 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER99 SNR = 109.974509743769 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER100 SNR = 107.600973173618 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER101 SNR = 113.797750449718 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER102 SNR = 110.998478333566 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER103 SNR = 113.386416958911 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER104 SNR = 110.239674130726 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER105 SNR = 113.34187717232 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER106 SNR = 110.204480903348 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER107 SNR = 116.501681924093 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER108 SNR = 113.136824877503 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER109 SNR = 117.805119590279 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER110 SNR = 113.767254261673 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER111 SNR = 115.972067195764 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER112 SNR = 112.038910329766 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER113 SNR = 115.236901584535 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER114 SNR = 111.484735442353 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER115 SNR = 118.279640417651 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER116 SNR = 114.273441142225 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER117 SNR = 111.51600429725 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER118 SNR = 107.383190533767 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER119 SNR = 115.478166051974 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER120 SNR = 111.299424498063 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER121 SNR = 115.221549505606 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER122 SNR = 110.682377157002 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER123 SNR = 114.166350306744 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER124 SNR = 109.986339259342 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER125 SNR = 115.097631675571 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER126 SNR = 110.592888681279 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER127 SNR = 116.287345983686 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER128 SNR = 111.634959498289 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER129 SNR = 113.213693720589 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER130 SNR = 108.648554101886 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER131 SNR = 113.054356372275 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER132 SNR = 108.496634561526 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER133 SNR = 113.917101900239 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER134 SNR = 109.195630475232 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER135 SNR = 111.481775610435 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER136 SNR = 107.09560733071 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER137 SNR = 110.674562038853 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER138 SNR = 106.023432119423 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER139 SNR = 108.779811935268 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER140 SNR = 104.056219016807 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER141 SNR = 112.904177066372 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER142 SNR = 108.089944863399 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER143 SNR = 112.163314450126 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER144 SNR = 107.502446533581 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER145 SNR = 112.01308138028 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER146 SNR = 107.056553267998 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER147 SNR = 104.695084079007 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER148 SNR = 99.7180940895677 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER149 SNR = 108.716236342642 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER150 SNR = 104.012418587568 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER151 SNR = 108.847940153784 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER152 SNR = 103.694068675248 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER153 SNR = 107.453473998186 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER154 SNR = 102.522602370561 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER155 SNR = 105.331695172838 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER156 SNR = 100.533014454066 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER157 SNR = 103.488077980493 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER158 SNR = 98.9504763552449 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER159 SNR = 101.25684549728 / SNR in the order               \n",
       "HIERARCH ESO QC ORDER160 SNR = 96.6058093782921 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER161 SNR = 99.2074624646586 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER162 SNR = 94.7990530499834 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER163 SNR = 95.6534161225009 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER164 SNR = 90.3224855427976 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER165 SNR = 78.6928574412678 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER166 SNR = 74.7488601589947 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER167 SNR = 86.8202218883337 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER168 SNR = 83.6486414171027 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER169 SNR = 82.4957554960721 / SNR in the order              \n",
       "HIERARCH ESO QC ORDER170 SNR = 78.2683088840318 / SNR in the order              \n",
       "HIERARCH ESO QC BERV = -12.393848389226 / Barycentric correction [km/s]         \n",
       "HIERARCH ESO QC BJD = 2458636.53045197 / Barycentric Julian date (TDB) [JD]     \n",
       "HIERARCH ESO QC BERVMAX = 31.0984107925636 / Barycentric max [km/s]             \n",
       "HIERARCH ESO QC THAR LAMP OFFSET AR = -9999.9 / TH lamp offset AR [m/s]         \n",
       "HIERARCH ESO QC THAR LAMP OFFSET AR1 = -9999.9 / TH lamp offset AR1 [m/s]       \n",
       "HIERARCH ESO QC THAR LAMP OFFSET AR2 = -9999.9 / TH lamp offset AR2 [m/s]       \n",
       "HIERARCH ESO QC EXT0 BKGR MEAN = -9999.9 / Bkgr mean [e-] in the extension      \n",
       "HIERARCH ESO QC EXT0 BKGR MIN = -9999.9 / Bkgr min [e-] in the extension        \n",
       "HIERARCH ESO QC EXT0 BKGR MAX = -9999.9 / Bkgr max [e-] in the extension        \n",
       "HIERARCH ESO QC EXT1 BKGR MEAN = -9999.9 / Bkgr mean [e-] in the extension      \n",
       "HIERARCH ESO QC EXT1 BKGR MIN = -9999.9 / Bkgr min [e-] in the extension        \n",
       "HIERARCH ESO QC EXT1 BKGR MAX = -9999.9 / Bkgr max [e-] in the extension        \n",
       "HIERARCH ESO QC ORDER1 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER2 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER3 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER4 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER5 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER6 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER7 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER8 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER9 FLUX CORR = 0. / Flux corr for the order                 \n",
       "HIERARCH ESO QC ORDER10 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER11 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER12 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER13 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER14 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER15 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER16 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER17 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER18 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER19 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER20 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER21 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER22 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER23 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER24 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER25 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER26 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER27 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER28 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER29 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER30 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER31 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER32 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER33 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER34 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER35 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER36 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER37 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER38 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER39 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER40 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER41 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER42 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER43 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER44 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER45 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER46 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER47 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER48 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER49 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER50 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER51 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER52 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER53 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER54 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER55 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER56 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER57 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER58 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER59 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER60 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER61 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER62 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER63 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER64 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER65 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER66 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER67 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER68 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER69 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER70 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER71 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER72 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER73 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER74 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER75 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER76 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER77 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER78 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER79 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER80 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER81 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER82 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER83 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER84 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER85 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER86 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER87 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER88 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER89 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER90 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER91 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER92 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER93 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER94 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER95 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER96 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER97 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER98 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER99 FLUX CORR = 0. / Flux corr for the order                \n",
       "HIERARCH ESO QC ORDER100 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER101 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER102 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER103 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER104 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER105 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER106 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER107 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER108 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER109 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER110 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER111 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER112 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER113 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER114 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER115 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER116 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER117 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER118 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER119 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER120 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER121 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER122 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER123 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER124 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER125 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER126 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER127 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER128 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER129 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER130 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER131 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER132 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER133 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER134 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER135 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER136 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER137 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER138 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER139 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER140 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER141 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER142 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER143 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER144 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER145 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER146 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER147 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER148 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER149 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER150 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER151 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER152 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER153 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER154 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER155 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER156 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER157 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER158 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER159 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER160 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER161 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER162 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER163 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER164 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER165 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER166 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER167 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER168 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER169 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC ORDER170 FLUX CORR = 0. / Flux corr for the order               \n",
       "HIERARCH ESO QC FLUX CORR MIN = 0. / Min of flux correction                     \n",
       "HIERARCH ESO QC FLUX CORR MAX = 0. / Max of flux correction                     \n",
       "HIERARCH ESO QC SCIRED FLUX CORR CHECK = 0 / Flux correction QC                 \n",
       "HIERARCH ESO QC CCF RV = -23.2116485143618 / Radial velocity [km/s]             \n",
       "HIERARCH ESO QC CCF RV ERROR = 0.074732488151709 / Uncertainty on radial velocit\n",
       "HIERARCH ESO QC CCF FWHM = 12081.4747205952 / CCF FWHM [km/s]                   \n",
       "HIERARCH ESO QC CCF FWHM ERROR = 0.149464976303418 / Uncertainty on CCF FWHM [km\n",
       "HIERARCH ESO QC CCF CONTRAST = 98.6076291844472 / CCF contrast %                \n",
       "HIERARCH ESO QC CCF CONTRAST ERROR = 0.00121991621885905 / CCF contrast error % \n",
       "HIERARCH ESO QC CCF CONTINUUM = 367212817.126352 / CCF continuum level [e-]     \n",
       "HIERARCH ESO QC CCF MASK = 'G2      ' / CCF mask used                           \n",
       "HIERARCH ESO QC CCF FLUX ASYMMETRY = 0. / CCF asymmetry (km/s)                  \n",
       "HIERARCH ESO QC CCF FLUX ASYMMETRY ERROR = 0. / CCF asymmetry error (km/s)      \n",
       "HIERARCH ESO QC CCF BIS SPAN = 1.39996814141341E-09 / CCF bisector span (km/s)  \n",
       "HIERARCH ESO QC CCF BIS SPAN ERROR = 0.149464976303418 / CCF bisector span error\n",
       "HIERARCH ESO QC SCIRED CHECK = 1 / SCIRED global QC                             \n",
       "CHECKSUM= 'SgKTUZKQSfKQSZKQ'   / HDU checksum updated 2020-10-08T23:02:18       \n",
       "DATASUM = '         0'         / data unit checksum updated 2020-10-08T23:02:18 "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdus_S2D[0][0].header"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we load the actual spectra."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_S2D(hdus):\n",
    "    \"\"\"S2D hdu structure (works for any S2D file):\n",
    "\n",
    "    1: science\n",
    "    2: errors\n",
    "    3: data quality flag\n",
    "    4: wavelength vacuum\n",
    "    5: wavelength air\n",
    "    6: pixel width vacuum\n",
    "    7: pixel width air\n",
    "\n",
    "    Output: (exposure, order, pixel)\n",
    "\n",
    "    Every physical order is represented twice in the S2D spectrum.\n",
    "\n",
    "    From the manual:\n",
    "    In the case of ESPRESSO, pupil slicing and anamorphic magnification are used to achieve high spectral resolution while using a grating with the same size as that of HARPS. The slit image on the detector is made of two ellipsoidal slices aligned in cross-dispersion direction. For the modes with the two slices of an order well separated on the CCD (SINGLEHR11, SINGLEHR21 and SINGLEUHR), each slice is extracted separately and treated as if it was an independent interference order. This results in each physical order being represented twice in the S2D extracted spectrum.\n",
    "    \"\"\"\n",
    "\n",
    "\n",
    "    S2D_wavelengths_vacuum_bary = []\n",
    "    S2D_spectra = []\n",
    "    S2D_errors = []\n",
    "\n",
    "    for n, hdu in enumerate(hdus):\n",
    "        try:\n",
    "            S2D_wavelengths_vacuum_bary.append(hdu[4].data)\n",
    "        except:\n",
    "            import pdb\n",
    "            pdb.set_trace()\n",
    "        S2D_spectra.append(hdu[1].data)\n",
    "        S2D_errors.append(hdu[2].data)\n",
    "\n",
    "    return np.array(S2D_wavelengths_vacuum_bary), np.array(S2D_spectra), np.array(S2D_errors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(141, 170, 9111)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# (n_exposures, n_orders, n_pixels)\n",
    "S2D_wavelengths_vacuum_bary, S2D_spectra, S2D_errors = read_S2D(hdus_S2D)\n",
    "np.shape(S2D_wavelengths_vacuum_bary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to look at the spectra. Since we will do that many times, let's define functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# (exposure, order, pixel)\n",
    "\n",
    "def plot_single_exposure(S2D_spectra, exp_index, cmap = matplotlib.cm.get_cmap('Blues')):\n",
    "\n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111)\n",
    "\n",
    "    norm = visualization.ImageNormalize(S2D_spectra[exp_index], interval=visualization.ZScaleInterval())\n",
    "    imshow = ax.imshow(S2D_spectra[exp_index], norm=norm, origin='lower', aspect='auto', cmap=cmap, interpolation='none')\n",
    "    ax.set_xlabel('Pixel')\n",
    "    ax.set_ylabel('order')\n",
    "    fig.colorbar(imshow)\n",
    "    fig.tight_layout()\n",
    "    \n",
    "    return fig, ax\n",
    "\n",
    "def plot_single_order(S2D_spectra, order_index, cmap = matplotlib.cm.get_cmap('Blues')):\n",
    "    \n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111)\n",
    "\n",
    "    norm = visualization.ImageNormalize(S2D_spectra[:,order_index], interval=visualization.ZScaleInterval())\n",
    "    imshow = ax.imshow(S2D_spectra[:,order_index], norm=norm, origin='lower', aspect='auto', cmap=cmap, interpolation='none')\n",
    "    ax.set_xlabel('Pixel')\n",
    "    ax.set_ylabel('Exposure')\n",
    "    fig.colorbar(imshow)\n",
    "    fig.tight_layout()\n",
    "    \n",
    "    return fig, ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_exp, ax_exp = plot_single_exposure(S2D_spectra, exp_index=11)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the 2 CCDs have different useful pixel numbers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_order, ax_order = plot_single_order(S2D_spectra, order_index=130)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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": [
    "for w,s in zip(S2D_wavelengths_vacuum_bary[10], S2D_spectra[10]):\n",
    "    plt.plot(w, s)\n",
    "    \n",
    "plt.ylim(0, 20000)\n",
    "plt.xlim(4000, 4200)\n",
    "plt.show()"
   ]
  },
  {
   "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": [
    "for n,(ww,ss) in enumerate(zip(S2D_wavelengths_vacuum_bary, S2D_spectra)):\n",
    "    plt.plot(np.average(ww, axis=1), np.average(ss, axis=1)/np.max(np.average(ss, axis=1)), color='C{}'.format(n))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Color-correction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make the shape of the spectra consistent throughout the orders. This is not super-critical, and for the purpose of this tutorial I leave it out."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Removal of stellar lines "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If your goal is to apply a Brogi&Line-style likelihood framework, this is a necessary step. However, with some other retrieval frameworks (e.g., Pino et al., 2020), it is possible to do this at a later stage, directly on the cross-correlation function. You could thus potentially cross-correlate at this stage (maybe include photoelectrons -> flux conversion, see later)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we create a common wavelength grid which on which we will provide the final spectra."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#\n",
    "# Read BERV\n",
    "#\n",
    "\n",
    "BERVs = []\n",
    "for hdu in hdus_S2D:\n",
    "    BERVs.append(hdu[0].header['ESO QC BERV'])\n",
    "\n",
    "#\n",
    "# Calculate the laboratory vacuum wavelength solution, which we will use as a fixed, common grid throughout the analysis.\n",
    "#\n",
    "\n",
    "S2D_wavelengths_vacuum_laboratory = []\n",
    "\n",
    "# The pipeline provides the wavelength array already shifted in the barycentric rest frame, so we shift it back.\n",
    "\n",
    "from astropy.constants import c\n",
    "c = (c.to('km s-1')).value\n",
    "\n",
    "for n in range(len(S2D_wavelengths_vacuum_bary)):\n",
    "    S2D_wavelengths_vacuum_laboratory.append(S2D_wavelengths_vacuum_bary[n] - S2D_wavelengths_vacuum_bary[n]*BERVs[n]/c)\n",
    "S2D_wavelengths_vacuum_laboratory = np.array(S2D_wavelengths_vacuum_laboratory)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we have to consider that the star is moving around the center of mass of the system. Thus, rather than calculating the spectra in the barycentric rest frame, we need to move to a system where the star is stationary.\n",
    "\n",
    "To do that, we need to know which planetary phases we are sampling, and calculate the corresponding stellar shift. In the process, we also calculate and store the planet phases and the planet velocitie which we will use in the following.\n",
    "\n",
    "We need to take care of the time conversions: the known ephemerid is given in BJD TDB, so we need to convert our exposure times to that same time scale and format. We use astropy for that. To do so, we calculate the BJD TDB time of every exposure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy import time\n",
    "from astropy.coordinates import SkyCoord, EarthLocation\n",
    "\n",
    "target_coordinates = SkyCoord.from_name(target_name)\n",
    "site = EarthLocation.of_site('paranal')\n",
    "\n",
    "time_observations = []\n",
    "\n",
    "for hdu in hdus_S2D:\n",
    "    exp_start=hdu[0].header['MJD-OBS']\n",
    "    exp_dur=hdu[0].header['EXPTIME']\n",
    "    time_observations.append(exp_start + exp_dur/(60.*60.*24.))\n",
    "\n",
    "time_observations=time.Time(np.array(time_observations), format='mjd', scale='utc', location=site)\n",
    "\n",
    "# We compute the time travel difference to the barycenter of the Solar System\n",
    "dt_bary = time_observations.light_travel_time(target_coordinates)\n",
    "\n",
    "# For the barycentric times, which are of our interest, the correct scale is TDB. (https://docs.astropy.org/en/stable/time/index.html#barycentric-and-heliocentric-light-travel-time-corrections).\n",
    "bjd_time_observations = time_observations.tdb + dt_bary  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we calculate the planet phases, the planet velocities and the stellar velocities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "T0 =   2456706.4545 # BJD TDB;\n",
    "P_days = 2.7240330\n",
    "r_AU = 0.05053\n",
    "\n",
    "phases = ((bjd_time_observations.jd-T0)/P_days)%1\n",
    "phases = np.where(phases < 0.5, 1+phases, phases) # To have them as a monotic sequence\n",
    "\n",
    "r_km = r_AU*1.496e8\n",
    "P_sec = P_days*24.*60.*60.\n",
    "v_max = 2*np.pi*r_km/P_sec\n",
    "planetary_velocities_during_transit = v_max*np.sin(phases*2.*np.pi)\n",
    "\n",
    "k_star = 0.175 # km/s\n",
    "stellar_phases = 0.5+phases # Change the sign of the RV for the star.\n",
    "stellar_velocities_during_transit = k_star*np.sin(stellar_phases*2.*np.pi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we calculate the shift in wavelength in a rest frame which is stationary with respect to the star.\n",
    "$$\\lambda_\\mathrm{emit} = \\lambda_\\mathrm{obs} / (1 + v_\\mathrm{emit}/c)\\sim\\lambda_\\mathrm{obs}\\cdot (1 - v_\\mathrm{emit}/c)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "S2D_wavelengths_vacuum_bary_stationary_star = []\n",
    "\n",
    "for n in range(len(S2D_wavelengths_vacuum_bary)):\n",
    "    S2D_wavelengths_vacuum_bary_stationary_star.append(S2D_wavelengths_vacuum_bary[n] - S2D_wavelengths_vacuum_bary[n]*stellar_velocities_during_transit[n]/c)\n",
    "S2D_wavelengths_vacuum_bary_stationary_star = np.array(S2D_wavelengths_vacuum_bary_stationary_star)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now move the spectra to the reference frame which co-moves with the star. The star does not move in this reference frame, thus it's best removed here.\n",
    "\n",
    "Practically, we express these shifted spectra onto the commong wavelength grid (S2D_wavelengths_vacuum_laboratory), to be able to work with them as a time-series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "S2D_spectra_stellar_rest_frame = []\n",
    "for n in range(len(S2D_spectra)):\n",
    "    S2D_spectra_stellar_rest_frame.append([np.interp(w, wn, s) for w, wn, s in zip(S2D_wavelengths_vacuum_laboratory[n], S2D_wavelengths_vacuum_bary_stationary_star[n], S2D_spectra[n])])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You may have noticed that adjacent orders do not \"match\". That is becasue the units we have been working on is \"total photoelectrons received during the exposure time\". In this specific pipeline we could work in photoelectrons, but I think for some cases it may be better to work in units of energy which is also more closely related to flux (flux = energy per unit time, area, solid angle). So let's calcuate howmuch energy has been deposited in every single pixel.\n",
    "\n",
    "For each pixel, we have to multiply by the total number of photons that hit it by the energy carreid by that photon. This is $h\\nu$ or $\\hbar/\\lambda$. We neglect the constants, because we will normalize everything anyways. Note that we are assuming a single energy for all photoeleectrons falling on one pixel. You can verify yourself that this is a good approximation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "wave_bins = []\n",
    "\n",
    "for n,w in enumerate(S2D_wavelengths_vacuum_laboratory[0]):\n",
    "    \n",
    "    #Compute the symmetric bins that cover the entire axis of wavelegths for a given set of wavelengths where the spectrum is known.\n",
    "    #First bin extrapolated as identical to the second, and last bin to the previous.\n",
    "    \n",
    "    wave_bins.append([])\n",
    "    wave_bins[n] = [ [(w[i-1] + w[i])/2.,(w[i] + w[i+1])/2.] for i in range(1,len(w)-1)]\n",
    "    wave_bins[n].insert(0, [w[0] - (w[1] - w[0])/2., w[0] + (w[1] - w[0])/2. ])\n",
    "    wave_bins[n].append([w[-1] - (w[-1] - w[-2])/2., w[-1] + (w[-1] - w[-2])/2. ])\n",
    "\n",
    "wave_bins = np.array(wave_bins)\n",
    "    \n",
    "S2D_spectra_stellar_rest_frame = S2D_spectra_stellar_rest_frame/np.diff(wave_bins, axis=2)[:,:,0][None,:] # Now this is unit of total energy deposited in the pixel during the exposure time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now verify that the downwar slope is gone, and each order naturally goes into the next one. Spectral lines now have the correct shape. The \"jumps\" you can still see are not real, and are instead due to the high noise found in the blue part of each order because of the blaze function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8/fXX2NglD58PPh3f9DxTNf/BFvXnxVnUm7Q2MVaVK9oCziTZtFsV/ZrmnH569vALjmNL627f/hNl+a1d5D1928CpyK1/H6n9xmt+ZiCwAmAYBgCwZcsWNDRIu3jf++drPvPX1R3A8vLgg8PY+pajpUWaI1+RNxBH0jKwLbWX3+X8R9wKAMiO98+6vdnHvoTKYj+siezYXKKYXVT7m+M4pqt9zSHHZXprZiXQppPs/gcm9MGXt5+Onh1S/H62P7ACiFCKG5pkQadLGptxsD5w51vNtmbM2z4PTd5C5jEnLf96+jl8/PHH+GiBtOi716Ie8coB6dN8vJ92Fb5d8CW65ATn/GxsX2na5bH8Ln7dF7Npvtfrqa8MAD6Xu5qYkvmEav4aJOB4XDvFa9YrtJl4xlotGNhFWluxjX9Y0z2BwAogQhn021b0X+78YAYu34JTVwTufvfDnR/i6dVPY+62ub4zMycVe/bsQXW9NL1RsM93pKtWWgShVMklcgBsPPAr/t7j737fd29b57pB586Sz/yLMtNkeWYkfx+UbACA3+XfxbLeCjEG7PQ682s0WOKVL7rGN+52uqZHW4Y61x4+efs/mu7RCiuAk4RgN9c/tfopAIBlWwFEi3df6szJRWvIxVZeeukl2XmKLUHxvku2NuOenf5PjyhxtI/yM1y56YBn5+TuU27CWeInPBs/S5a+b0wuAGCg2IA/5Z+li4wyrPJ1g65n/OA4biGNU1DTFgIPaoib5TI9NKlwprayNcKuIBgAQGyzQP4hgZHvf4aSki7I/D+O6RMtrFq1SnZeVlYmO79rxj3YuX83PvxQviegoF4/nz4fpnn355Mr9iK2MAlw86JgIcL7Z90KIvkCb2JcGuaJSQCAdu20j2oCpdES5/9N1ljpn4GwAmAAAPOec/b6G3bq58+dCT3FhXtRW1WJ3EFDQ1K+NTkWfftKfu9J2CB0mvv3h/yjByGEvJF/oavkkdRqVd44NW7sDmi18AmEU079EOvXTHGcdzprqeP4snSVKSCTwVNAJxn763z7YmdOLubOuAOfPBGa4CEZGRkAACLCPffcgzzo48LZXwYe8uzFT+k+0us9FkssLBb9+7jFF0lBX+pipWmrNW37Y0F+Pc4XTr9Hvdt6LgK/2+K5ic5oWAFEIN6sfbS45fWFzcZrACcDFceOYs+61b4zeuH2253WL23atEG8ji3Gw5WLNeWziBbFfrwlkGkXLdz4g9fL6UMvAwCUx6bihn6P47oBT2Jsl1F4doBzc9dd3Tp63Lc3P0A30CGEFUAEcrRBX1PNxsJC2XnpuhWqeauXLUPZO/oHpmCCZ9H/NsnO37jjJix89jE0eukw1FXX+vWMGJXpFne2jvG+O3j96H64vv80n+XkVB/G8zV3oLZWMonMsWugUyh0kb5kNvoKWGNiMSlN2ry2KPNMlMWmAQAyM8ZinpiEeWISiAi3DLhHdh/16BkScYOBFUAE4i2gRoPNW7huFWLkw+SEshoce/oZj+fYampwcPrNOPbU0/4/gwkJrj38nb8pm/CWHKzCpp++Q1OjfHqwpqYGz/zrWT+fqK1+pccpL27OH9QDh8cORlZCHBJy03yWc+G6Ndix7lzH/P/q0QMxf1AuPjtDPapWOHhx4DDVa0TSyKSobQdZelaG+dYFWAFEIK7Nss2tkd5aXe93ebtP7PVIK3v7bTQfPy5LO/7fWR75GOM4vn8fFj7r9CJpa3Q6K2tpcjbUG75fih/m/BfLF7wru/+dAEZyJHwrgMIzB6leS421wmK3hadYNdcMTixuBs5EhHHpaYgPkfXMzY3afO/ExDj9Cqk1ovGJbi4rrOazuWEFEIG4fhIvFB7B7hr/G31Xmm3Km3lEY5NsFNBcEURQ6oZq/PzcVZjyog6bchgAQN2JKtVrJYecLhq2L3vLnt8Zx7empgbFxcWye05p6i47v+GGGxRK9m762S+uAgkKLqNb6ePFKygA3Lx0IXpWSt5B29dWeM0bCg52PBsA8HJ7TzfUauw/a7D9SFJo6elnAJCU14w8p0KhIJpbW4iaalYABlNcVY+3XnsJaz/+l+Z75h0qReymMlBNM54tLEZhkJY/FpVqsOecc1Ay62XHedXCzx3HtS6eGzWx+lWMr1mE60qeC0jGaEYIgZ07d8LmNr1na3Yq7rrsHmhs1wHC1fUwWZCY2dvRZJOLo7TnnvP8HYa2dMeA5hzEixhcXX8Gunb1DF1I8G4gcEeaM4BLPDzrZZKbcuguCjzyjNu4GacVbMLkNUu8PisUtI6oB2crexVVItbuvtliicHoUT9hQH9pI935yUfwSSfJ8ueVLlNBQZjPUoisWVkBhJmymkZc9sCL+PYbqTEd9+RXuP7QPzB8y+NAiTYTuxV7S9Ht6H7kLddnIczixYNixaefKqYf+ufj8gQhgAovu0LtH9ZF1uCsUqKR1atWY/78+Xh1ttyPzLFCaeqOLHFobtseDZ26Ys0iqUE9UXoMJ/qcguKMNqjuK1mnnCiR9/jd6Xz/CFx+7zX4U9J56H6fsquDTIt352/dYp2LyltHZsmuJQjPBefzlzkXrnuX7gUBsAobBh3aCwuAmJjwTpuc1StTOlBpcO/t+rzjeFbfrngkT/43JiXlwmqVzEO7JiaiOiYZPU7/Fo/3uBmWIPYk0Hj/3WRogRVAmCnd8Ss+j38YF6yahi2HKpFHh50XP52uqYzDjU34Nf6v+DX+rwCAliA3ZFq89UxUFpybd7opqw3zgBcGAFs+US6n6rByOuOV3bt345tvpZi7x4rlDto2fbIIWUn5qOrtnHNfPl/qfa769HVZ3rzci3FgyybU1zQ5PH660qs5CzFpCYhJi0fnGSMQ017ZNcOgduqO1maJG5GfdbHjPCUpR3Y9Jc7TjXP/5q6wCGlUMW7LRlxzzTWy6zfeeKPq80LBfRf0AQAkqCxP9Oo51nE8uVN73Nq1g3JGAB1jpe+q1poIQRaP3cp+MfLWwO/1AisAO1u3bkVVlfqcql7kf+n0A/7Ey6/ii3iXDTwVyjb835dUokhmyiefCvjbruD8sZCXnklLZaWmMk589Qm2L8hC5b9uU86w9o1ARItaioqKMHPmTMyb5xmVq5VDed2ws5s8Gpe1gzR1cbRgqyx9Q+JR2GLj8PINE1Ff77lmdMW0P2iSy2pVCaoCYPL4dUhJUXfjbFGoZsOa8zB92Ze4ZelCpKamoWdPualk586dcfnll2uSTQ9ao3GdkqMcc+BPp3VXTFeirVW+tkbBzOPEJeH4Hz73nc9PfCoAInqTiIqJSNFXKxGNJaJKItpg/xc636UhYunSpfjoo4/w1ltvOdJK5+9A6QL1YNdeObgaWP6SZ/pR+SucZnVfEHWpIK+MBv7VW8q3eR/OXbPTcalvgzOEXnb9MRzXELzDG1YvIwBRV6d6rX6b3fuoECiaJ72rwyuV3eDK2PmNX/JFI2t8rLHs26kcjLwsVTJBVB63SfXr99XrZKlZGZ2Q0EvD7xYkSlMgWXc7N09NmDAh5DKstvXWlE9tVBwXE3ifOSXWt8M7b2T2HyvFDtARLX/N2wAu8JHnFyHEEPu/x3zkNR2LF0s7Eitdert1G4+jbsNxtVu888a5wA//AHZ+K5032RtRtx7+hVa3j9y10hVvA6qPYk+t1Fsrb3Yuvv3xqLMBbVNeEZiMLlg2vO8zT+26dR5p+66QnG3h67u937zMbYF7vrE23JGA2l4PIQRampvw+Svqv1lLiw3N7Tt73pskjRZq3YK4TL/9Fu1yqaTHwffmxKuz2nukJXRwLrYmJ8tHF2OatDXW/pAUp3FNYaB353TakCu8nonGOn5TwqcCEEIsA1DmK9/JQKuVxdGjR7EsZpvXuKSa+HAasOZ14IlOwP7fgJ/Vg0gAAGqkRbrqaqcztjErPQNR31j1heO47WYNgTt8YNmwwGeekpdfVr3WsuIt2fnhL/4JNLlMM/zstmDMKLJx40YcOSK5B1ZTAB/O/wBzZ/wNFe3Ud/DWnWhEfcdsj/TETtLu3N+3bgxYxnZW5X0A57VTblh3nzEQz/fOwfC2Sbgnt5Ninv79JblaFUBSkrTbOP9ayddPUFMngRIT/Kat7Gx5R0c/36n6odcawGgi2khE3xCR6h5wIppORGuJaO3x4/73rhceK8fvVf5tXfdFxReeTqbmz5+PXTFHUI3g7OvR0gB8LW0HF6tmA8VbfdwgUVvvbNSPLhvrNa/rGsLQki04uvQs79Y4CmipBLY69XexvVA+X3pwzlvA3Mu9l1epwQ96lCCEwA8//IDPPvsMr776qiNNie27duBY6VGv5c17RHl3b6nlBJJi2qKJnKPJSRde7pesCRZludqqTI20ibHij1np+GpYL8cGMHeuuOIK3HrrrWjXTpqGat9eGilYksK8cWqqfFRly+gTVHFxcRkYl1QSVBmhRg8FsB5ANyHEYAD/BbBQLaMQYo4QYrgQYnhmZqbfD7pl235cuE5fV8XVv3mxTtGx42HTqP4rmpqx6MM5/hUuBM4qW4NvtkoLsE1r3lbN2tjYhN3PnoWSJbMdaaSlb+LF/YR1nXzo3rYgDiVFTh/zdWWx2L4gC5M6OKcl5q303H0crRQfOorly5drzl+X671hKktT/6zH51zvOI4VVgwcOUTzc0OF1WpFx46eztNaycnJUb2mF41dRgN9LpKlWW7y7hROC+0S1f8uMxC0AhBCVAkhqu3HiwDEElFG0JKFiUrSPqLYXl2HOQe921KrITRGCRq+ZBX+VPyF4rXm5hOK6QDwweZ7Hcexy/8FPNMdmJkKHJXvFSj+5ink125AxpIZmuRpRTVKWL2y5VSzi/Ys/F5S9v98idBcL1W5rUXlQE3wvaMv/v0k3vnb7b4zmpg335JPoQkhvPp78kUDqRsFzE9wKpo+qdotWnxxeQf9FpFbp4RSU6U1i/bt2yMnoSM6xoRuoTouR8G3T0JbYITTNLvKiwWUGlnJ6Y7joKeUQ0DQCoCIOpF9ko6IRtjLLA223HDxZaq6a4JNVvmi7bg1O/FwwWEsK/N/JT5mm4p9vBsFyz0tIRLLpIbfZlPe8fvsJoUhf5192Wa2M+6oEAJdfv+3M0+LNushYbOhfrPyprOm8kOK6S2VyjbPuxd2woGl7ZF2aAnwXB6wO7he1u7Vv6HkQGFQZRhBXV0dfl+yGu++/jYaWty8dQrvDv/0oufIvrqVdWYHz13DgTJq1Cg8+OCDDgWgLyrv9XQVH0AXOB0figDs+Cd2dCqtMPykfqPFDHQ+gBUAehNRERHdSES3EFGr6cBkAFuIaCOAlwBMFeGovTpQfPw7JI/YjZozy9Cxs2RmabPZHPM122OcjVujyzb8KRv3oVnrnI4OzN0wA5bSBjSpPHNaxSLvBZRIu0O/fdEtzOPj6Vi5t9TnTJe7u2hXNk6/SDF9jzUOmJkKUVfhca3mSALurnpTOpmnh7UFsOqzD31nMhHvv/8+Pl+yCHuLCj2u2eqaw6IAeg/z7rLZKIgIcXEh8vWvRrLKpIXF2egLg8M3hgItVkBXCSE6CyFihRBdhBBvCCFmCyFm26/PEkL0F0IMFkKMEkL8FgpBf/l1lOP4QM0J7DpRoZhv44la3Lq1EC0+PqAjRYex89ev8QQ9hrl0A+bmT0J8wgk89thjqFRwslXdVCM7f2C3sh12KDjduhUjtqzClhp1v+5emTUMqCvHhRWepoMvvjXPpwIoPaC+7pK8W9la4nn7gh5qlaeI9nwV/Nxo2WHnb/Crm6dLs3PwoPpCfc3qIxB+bu8eXutp9eOLhITg7NKjjQXj1C3htGG+frHpdwLXtLTg3/uOoq7ROas0YvUenLm2EDUtLR4N/Q2b9+Gz4gr8XKq+q3fPhp149fU5+EOa09vhXuqJ5CTPqZ1W09CqKrkFz9zD4Z3lWoh/oDmIqYG1u5UbnPlW36EEj9b4b2r61DvSmsFP237y+14AqFz8M7YPG4Z9n6vbuzc3BqgQDaa83LtX1eeXvokdu/zbhLi1OLD37C+GNmE6PXx7whDgttXA0Gv9um/qMP9DOuYmuoxkzNf+m18BPLfvKJ4rPIqvcZnHtbxlm3Hdik/Q0FiCtw6V4JCLu4RrN+/Dj4e3KZY5d+F8pGV6Noj9B0gbwgSAygRpwae1wX3oQBB+PHRCkiSAgC8Ahn96RsDPLW0IXNklvPaoX/mby8tRt3EjDt96G1BTi/oZj6Olusb3jYCHt0yzUlqqX+chZcc6JO7fgZg6dSdtiQojuAdvvlchZ7RAQGZv4LJZwIxC4O/aTNLTYv03S022Gt9ueMP0CqC2RfqoP6BrFK//2NAT3ZYX4YFdRbhyo9ymf+mOFzzyt/pAf7rfXzyu3Y1ZQGIDdnbsivkjz8Wh1Aw0l0n27z9Vec7/HTzi6Ztj/3F9t2q7UtXUghYDGrn31gfuxyd9tXf/76407N2H3aNPQ+GV8g00+66copjffTT0zr33KOY7mWnXqSdiaqXGP7Pc021HTFUZYmo8R8NxnVNCLltEkNgOiAnteoN7UBszYXoF4A8FtQ045BIvtwSeCztblv+uev8x6oxFp45EcVtp/roiKQW2ZhXzRwCn7ujmkba7KDAzUS08sLcCLx0I0D1FENz/cWiUTm2lvEe1V8UXTNOevZi34n+e6fVyK6ayQ7uDDoIeDvTc2ZrTf7TjuP6Y57SRpb4WIPk6zalNebo9H4CHS2QzQ4G0xdcuBCa+6jObGs92aZ3yM58iML0CCOaVfUZSz9Fms6Gurg4ff/wxlm1cgYYY9dX8A5SLbVmSfbSItaHWizM0AKhrkTeOyfWhUwBUcACvH/I+fXBb7wexro/34f0LzVfoKZYDssp/LV/RA0u3ae+FnnK9p3O97+Z87JG2a+Wvmss0CqGTBVn75nR0HXA64tPuwqDzn8EV93v6YYwrP464Nn+UNXy9WoJosBXWoKZ29vTxY2aEvzs888YBg4PxX0X255oP8yuAIN/a4fpGvP/1Ilyw8Ht8d1DaQv/10JGa7t2T0wllFWWo8TIK6L5sExaXOF0lWZR83upEfGUtynx4/vyk0/kYNvUf2HuDovNWAACddb/eogEAsq4+FXUdnfJt35rmNX/1/qSgnld5zHM38bZlPwdVZjiw1QbnvbWV6+66HvFJsSAiJKTEovsQz81MZJPqbicXo4X25+k3Angv34Z2AcyN+40B7oD0wghXRloxvQIIlhd//wr3pnTBzk7d8OWQ05Gbux7FSdo2Kh+JyYKw2fDVMe++V67afMBx7C26lr8sbXOK7Pz0pk2wetm8dXfGXx3HPbqqb5+/81z9vSwCQNsH52Lwac4pqgMtGudWbd7DDDqyKQQyUaLyuPdRm9E0NwYXwrOV1PQU5A7KwNire2P05VKj3mFfoeN6fovkfI0oEdVVThficUP9d8PizvPdmjAnpwhnZw8NuizGOEyvAILdPv1OfQ/Z+f3d/PNWbRMC9+9S3u3qSkuL5FKisdF3Xq28e87LmND5P47zvuUF2LzSOX1z9YBnHMfvdLgE7/efKLu/RWHn4s5+dwIACm8JjS8ea7zz9+q2w3fPsLnOgsY9SzWVvXPwEJlLCtGibJ467+EVOLy7Aod3V2gqN9ys/cBz6spfLms4FYC0ntD/jGzExEm/dV29071GbrnU9SSLZO9PTZKVnNcIcBrJT07ApT0vNsZTZ7AYJDJPAQWA0S/N1mJDHZw92RGpyv5A9hbNBwDM2K+fxC/2740N+YMd5zfFfIP2LU6Ljp/aj8TLXaZib2I2nu75Z4/7LX/3bCB7T5EUYG6ndIyq/y8And/xdG2NeSsNjRYc2fQTmsu0eRzfMlF557ErdWXPY/7fr8Fn/17vlyzhIrHRf58y7mQK5YhVkx58DNbqSsQfKcTK41/i2mecayfJezYjZed6GP9VRRdmVpGmVwChplO1d6uauqNy++peScq7J1fWpGB/XQOETj2iLwbPREqMFTaXXvx2m9u0DhEez7sVp414H+Wxnn5TyBqLldcWqD7j/ivPxpKWwarXAyJriGJyS7ry1NWBkiR03fwyaqu0KYCYXcphMyMJmw4NcFk/ZXPj3MGnIOngbsRVSCOBmLg4TPg/KWYwCQGKkL0SoYOVnyumVwCh/rkuX+fdDe/2ZvkO4PMypJ5XeyH3ZLmkogEjV27XTQGMG+IMldcgJKulvhb/Y/+OysvEkhzJTfS21DNl1y4fmo3THlkC3KjuEE8vEk6vRHqfE8g+za2hX5MCgsD6I/LoaCkTL0PWM0+jedL5HmXZamqwvY9vR2ZNNT+YzlGcsNkgArJFlDNo2sWq1yY95AzAI4RA90H6Oec1o0fLSMGM785wBVBQUODYnKWEPBi6/iTGJ2L89rWq1+9NP9VxPMayFudlpKLorMGYmS93pft1g9TL8kcBtHQ7XfVaG9eIRAoNRo3QHrEo+/w78GHzWaib8F+Pa8HEOPWHvIQGdBhyAm271mN9nuc76ni9c20m78cfkfPU00i97DIMfOIFj7w7hw33SFOipXEz5j/sn9vrUHOirBQ2X/axPqAG74GKcgf5WJjVoR1SC+7CKMFmoIocP34c7733Hl555RVHWn1ZDRY88jpOlEhD3F/K1be4B8uo+pW49PJL0atYm2O3UdmSO4UYC2FKTh7u664c4k4Tw66Hdco76tftjcTRcUMUF3OboN30Lr9LJ0z55xcY1jtX8z3tpin7Sfl4DCFh8CDPCz5qkmt7cZrNewyGuC7+OzZTo7FOmxuJcPHabdf73RBk2drhoYceQk6L1JOPP+6HoYEZW50ow8yq0lAF8LJLnNmGSqlR+GjWe9hBRfj3rP+o3aYbwzcVoE8fKbpSUoNv08HbuufLzu9WiHGqeZPJsOskF7SXevbKpYKcX26S8DQbXGrTee7ejY733aeY3hij/Pd1ud4zCLkaSXHqZp8VClsDenypHCBHK+VHzaUEhJ/+nP50y42IjY3FeU2DcHX9Geie41tBdu4pmfrGJSm44jBzi3QyY0Iv+YZPAbWy+QXJEdseW/hixTbXpTjM2P6wbrHP/ElW36+rRauJXWu+U6YBDx2FsJ8/lHYzCjMGyxZT/93B0w/SV+lneqQFy/8muMiuslgoVBqPlHTnlBR1k09R9Jok/02TMtWn9XZc7+m0Lj4/H13f8TJa8sHb98xAfU3oRpJa+fkdKWZBk82/ac24LGnHdOZfB6NlODDl4ad83jPlkadwzVMvoE17z/l/M85FhwtN4U/1fygAcw7GDFMA7p4bvxJrsGOtfMG1ujq0H+3kiZMAAOPHjkNiUyNuWboQIws3I6OxBINt6zSVkewWJLveonVu3qUljU0E3fAdTrTNx8Ex1yL+zz8Csc6e23M9b/C4+4c+Y5GfpH0dQCsiRppuUqusxalA9jPPeKS72oPnnup0d/zfiy3A2fJ5+DZd6tHtXGXrq3GjlLfcJ48c4U1sr9iaC/HyDVPR1KBtw1mo+H2RFLOgpVE9tKc7PXv2dBwndEpFn8lna7K9j4mLQ8ceznunPOJbaTChwcwDLsMUgJJP9AVffSQ7X/Jd6Lb1n79lJQYMHggAaNfe6ctk6P49mLziV4xcLjc3fL278kd7X657D8v7z73KZg/o3d4tHmvOCLS5ey3ePXUgOse77aCN9VwDuDCnMx4OgROulvZ2+3Ih8Mxkz+oxsf+ViMvN9byxxzjHYUKMQFMPadrqcToKa6KniWpSepNHGgCkDz5VMR0AjuQEZz8/+7YPsXdD+J3puUN++AIaNWqU70wayOk3EDHxbaQTM3ZFw4jfvoBOYgxTAA0atvWv3azvRp59o5wuEHJLne4dMjM9t8ZbbPJXc6GKxc7FHf2LbLWoZSQwsxJo/RgD5PyMVJybkYrPh/bE98N7BVWWK13nvovOT/wTlvh49BzlaYLZoVMPhbsADJePUgYMK0W38SVIT26WwuqNvMV5cUahLO93TU6ncAkx6lGqmvK6+P4DvCBsZVj0ymrY1ALch5CVn37gOCaNsWUvPfsi2QggWHKHnC0dmHAu2hcnR5NtvvceBi9O5uDlmBokJibiuuWLQG59gI6dlBvxDuIoiqkTFiY/Cit9ppgnO0HeWycfNt7tkvSJK9o6CzAyTQe/7naRL+85EandegLdpEanqb2nkso940KPtITsFCA5XZZmsQJJHexz3adMA+qrgFWzpXO3Rr7rJ85drbEW9fczaNTFqFiy0+efo0ZTzTcAgB9f34Pzbr4j4HL8pbG+Dss/mOs4twltCig1KzReNiN1DSBS5W7FjNKbZhE41Ew6YwwA4NqxE5DQLJ9+ICLEx3vOp09b/zXmiUkYNvRNzc9JE97D/f31HP9763nxntMlEzLS/C7HX0ih35UYI61NdH37bUda+t2PeC8oNhFo01F+HgCdpt2ADjOCt+vfueKXoMvwh9qKCtm5Tag79Js5cya6t3QAAFh1jyYVyf3oyJXdzJJHjQJopf8YZfPJSy65BABw++23O9Kqq9NRufUxxMa281rmruHOBu3RPr48bfpfHf7dz3PXa6yb2+nX+3sGp9GKI7KWm2gZifL1jcTFC5AUK9lpJo+SXGrHdeuGNhPk/nn2nOHFhNdLD98XZLEg/fo/4ZdTg3Mj3egjxoPevHGnp58mVzJsbfC3v/0NM+zK7fSmPhjVlI9u3QL/Tb0RzD40M/Zi/cEQKyATY0oFMCpniK7lDa1zer5Us6AYMGAAZs6ciYyMDLSxOBuYXm62/0q0bdMby/L3Yd2ILuiaFNzcvhIjU5OxqO0Yx/mR2HSPPHpUa/ce/1V9rpKd53aWK8++O7Yj77tvPd5pVUeVhcu7tgH3esanbeXdKdpcFnR95HHfmUxCkwbXz1d0PxvJyclITJQ6EvGIxYCWrrp72tSzuLD3aiNZ9lZMqHtMqQD6n+cZ2MKdDsK7j35XLu0hX+QdNGgQBgwYoJp/cu/zHMcJHbQ16L26TER2soYGLID4o0SEG/NmOs7Lr1nokScU63qt0z0AcDRN+30J6S6Ltffudh6nZgNJ6vPa196kbfPfBT2VQ0eake9eecFnnnaT5dOCHf4yFJn/F7qNfsHVFRO2Yn4SbisgpalUs2CoAhjcvT/uu+I2ZLXIp1hyctSDmbTSHVIA+BHiN8wRnm4LzhI/oeiMXni1SyFu7jVGdu2KK67A5MmTVcvuOsnF1YGeLeuZ9wFDrg7oVtE2Dmd2n4Nbez2Eft08XTGE4rNsne4BgCV3eW7QUqNv57bYPOp5NA+9HkjpoJwpwdM0tF9XbT5+IokjBZ5xF3qNli+kx7nt54jLTkF8V2V3z/qgz3iRiXwMswLKzMzExOv+ACEErku9HnFd26DogV+Q0Mv7fHsrV+NtWITAdLyMODRivPgOP5PTbHG0dRNiYpJwWf7lfstGLg7SdGlYYxKByW8AfXz7svfGrq69sVvkwzM8eugsJKxdstBSdBgzRj7g130DL7jRe4bhNwBvf+A9jxfieqiYo2rEZmuBxaL3IqsnVW5+e9qkd0D+qQOwpMi50VD/xV7GjJjRismwEUBsrLQYSESI79YWRITsh0cjY1p/Tfef1vsu3I7/IA6NaN/udAxIkS8MnpnvfeEtdCj8yNd+FnTj/9Up0lrEU/lqDuhC0yNLGSHN58elpulbcN7ZyLtIOaKXFrp/9mlQj//PVZcFdb8WbAqhLq9+6n/ORfcw07qmYNTzoxfzegM11T4Ai4uNfLyIRQMp7xYFgHZpzoXGIUPehmXzbUir/gb98u7G8oYcnKISmMRvdPlYgi9jeGoy9p05CAkqQecHtZEUYHaMvhYunWY+gvSbbkRMO20jM810PwNxbZwNZKOfNdESH4+ktBzUVvgfI6GVpuJixHZQmaLSgbqqKtl5fNpfEBtngt4+K4CwYubJMp8jACJ6k4iKiWiLynUiopeIqICINhHRKUr5/CUuVt1c8J89s5Cc3AOnn74K48cVgIiQ0+Vq9MZOjOo0AA/1Ck3Q84DJ0Wc7f6LVomoZ0iMpHrGiAWOT9HV1YImLQ3yQ0y1ayJ75qN/3tM8Kbgd00f/dFtT93igu3IvZN8vXpqY8OBpxiabqc/nPSaA7DHMFYULFq2UK6G0AF3i5fiGAfPu/6YDiFLXfXDjO0w1BK31T7OZycRmOBrF9+zE4e/weJMQH4aM/FFw6C7CEZ6aNEHnfpzVRGgW0v+gSv++NS5T7Boprcw1yBpyl+f4T27b5/UwtCJvA3BnyncajJj+KDt1CubCrAQ7iYihm/DZ9tkxCiGUAvAVsvQzAu0JiJYA0ItLuHF6FvqcpBB0B8MWAthjTTn9be3dG9pNMUf21xSZ3LW/Vx/XDyUru+BJ0HFYBS6L/u4PdF9UsMR0wdtrNiEnUZrG0rmcfv5+phS/+85ZH2qgrfETpCiO6dERZmWjHxK9Kj65pNgDXidgie5oHRDSdiNYS0drjx71PVag1vCMyQz8dAQDdO3UNy3P0J4Cv28ChaVybFrTP9x4hTBUVscnq6dxPibLEBhQXepppBsP6b75CwWrPBWqrSiyJcY3ajB70QI92yIy9WLNj4vZfFwWg9Pcp1hMhxBwhxHAhxHAlD5wnA55tqZl/fgkzmqdpw1VuqSqThTDlIfXpQ3e2LdPX5fjit2d7pLXLUu60nN04AHm2ME5ZOqyAwvdIXYlUuR2Y7w/QQwEUAXDdudUFwGEdykVex9D4QtFEa7vt99filj//XD2k0f70YOqY+XWVDOHi1KZjXl8MOScHGV1S0KlHNi68Y46mMtZ9vTBE0jmZ/NA/FNNTzspB1qOjQ/58D4IMSh/JGOMLyLxmoHoogC8ATLNbA40CUCmE0CWu4yVTLtejGGPx4vpAb4Kv3JGlAVzt2ac8PBNjJuc7pg77jdE/WI4v1KaT2mbIR7utcpOVYImPcKsgxidm/qp81j4img9gLIAMIioC8AiAWAAQQswGsAjABAAFAGoBXK+XcGnp7QDs95mPsWPmmhYKXBRAXEJgLqb1xN3yBwAuuvM+AyRRhnScAjKzfxtGOz4VgBDiKh/XBYDQGVQbhR4fy1DPYO6hx4wDzdBAdlcOyWnKm9QSUtqgvvoEOvboh2N71U0+D28/gKy+oVn073PamSEpNziip46YCTO+dVN6AzUHOvRwNIb+05fo6ZnFJ0kO5S65+yHF69c89QIuvfch/PGfT6HHqXerlvPR0w8GLcuRggKPtDvnqririNhVWOZkI6IUwD9CEAQ9pBhgKx1NTUvr35qk4qcotUNH5J86GharFeld1OtOc30FGlsag5Ll/Yf+KjtvlzUMMXE+XH+Hu3pET9/AVJj5tUeUArita+j8trjj+NG4txYBBP+J7Xt5lg5yOBl8vu+lMKPm0W226K3TxkYEM997jxgFkCGKjRbBf/pPNOCh5qtkIcMP5dzvdO+jx9WLvkTVDz+g4tPPfJZVu2YNRIvTkV3B2lWy692G/BlDzjHfRkJ9NoJFfv0SBu1iNuObixgFEHYCrSP2Rum+pj8DPcbqJg6jjpaedPvOyV6vF6cm49Bf7sCRB72vB9SsWIH9107DgT85e/ifPycPUTnp/kthjVH/tAxrCFobviAEMFz2CMTMokeMApiKuYY81xbgFJBRHgeja8bKbk+v4QvT4gO/NUfTUfVwo40HJa8ntWvWAACqSso98mj2H2VYYN2oqiSMFyJGAXSnIqNFMD0Bz29Ghdbw/TeushsZFJx9jmoecvPs+tptcpfPN8+eH4BskYeJO7WmxYyfmekVwJkJkleJqWf9aLAkWpF+5Z6ZKQbL4QcGVcyWvlJUrrKk7sEVpFNrVGZ3M44Wz0hezmd5f1hKGDzVBopjBsiEDVG4MNIVhBkxvQLoGlMNK5phDUP8Vlf8dQPtzui8dJ0kCSNhnqxsulQKHbGr48UB3e9PQ9bac8/u0w9XznwaY3YFFo7SVuP0XGrzpii8YXALHFxIyCjWHgFi5jUA0zsiibTqFslWEsbV0+Cck2lR1haLFbe8OhcJKW1gjYnBibpq9DuShm2d4/161rEnn3Qc/++292TXbn/rQ7/KYncKRmHUezdf22D6EYBRROqnab4q5o0g37KfPdnktHawxkh9nj6bNqLPpD965Pmhf57m8urLP3IcX/vsLMQnJfklT9jRtStqxCbHyKrdTszrhpsVgBoBzpd6RAQLI1GrtAJo2CguDulXT4U1boAsvSnAMXGHbrma8xpVQ5wezk3YEvlAr7rNKwByWAGEDB5m+qK13SaDRE5IiUVMkmcM4bp43y68G6w+3DwwTAQQEQqAV+5PUvSakgiwmLiEGNwy6zwkJk2Wpdcn+FYAi4ee7TjuPnRMYAKEGx02gkU6Rn7VZpzCMr0CMHq4HGnRk8xXxdQJdhFUj6mMmFgrRq9/VZa2JseGI4/M9HqfrWmX43jijPuDliOsBPPeIqmCMT4xvQIAIq0vzl+I/wT3zoI12W03fYrsvNlKqPjggxA+P3LrSORK7iTcu/TN3H6ZXgEY53sk2PuN+Nkj7fMM9h3p8/dmXzEV47fJnQ02k/qncaR9Z12eG6ziCvR5eoycwi37yQBPAQWMgWsA5vvNThocbYjB02wUG4uEphOytD3ZvVTz/961o+P4z6+8HSqxQgZXaaYV0ysAISKtp8GfV9hofdVB9kZjMjI80vakN6G5XO7orX6bPaykcCqLtume9/oiAq0wmSAw84Y/0ysAwCArIPP+Zl4J5E0ZNjQ12TRCcpN8V/CRB+WhJut37kJEY67XbQhG7tMxI6ZXAEZbAQXaOBrlDjoowj0nHXQJdnfQOr3rwfv2yM4PbNrq9jgRpNMKN8JcRVrfkwgqIhg3oIFixg14plcAAHdctCKNlMxXydTR55fVq36k1TXIzkvi5UFkag/sw3eDejrOr3lmnk5PjjzMPK1hOkw20nXF9AogkpozADzB6wcOq5SgCwpaFEUKMuWfR8mC+RAu25YzcwJ0/WxUHeF4MIZg3uY/AhSAYQS4a9L5bRv0s0fgxx3ovGwo1i7yjnlG+GouL4doakJsRbUs3WKN1M8nAisJExIipAZHXoU1atQXUW9Kp5ekp016lzK5OeixNauwe/RpOHTv32DzsjcgEIzzFhVRteSkwYxvPUIUgBGYeeCmTKRJ7JQ30FCWOgkCIOf11wEAyY1NsvTl990HADjx3XfYn5nlSM+oS9Pv4WGCdFZg4US/NYfwN8Nm/i4jokYY8gIDDp9nRj1/shN8DUk53enQLSbxDMfxkXapjuP96bGO44F7NwT8LKNrSDD77hxbL3SRJMCHB42Zm+TwokkBENEFRLSTiAqIyMPzFRGNJaJKItpg//ewXgIa/bEESkSagYYdnZzB6Tzfdtb6zxzH9bHO1rI2zvm5JDQHGA5SRiTXkUiW3RjM6FbSpwIgIiuAlwFcCKAfgKuIqJ9C1l+EEEPs/x7TU0hj3EFHJpH0ppyuIIKUWqe2qMsrLwMA4hsrQ/vISPqRzALrm5CgZQQwAkCBEGKvEKIRwAIAl4VWLCdGbwQz2k/NSU3QPXd9a0eb8ePRZ9tW9Nm+Tddy1Qm3Mzj7ASugsGJm3aVFAWQDOOhyXmRPc2c0EW0kom+IqL8u0jF+EuBGMIPs0nXbB6AjZLGc9J4u2QrIIEy4R0iLAlD6Gtz/kvUAugkhBgP4L4CFigURTSeitUS09vjx45oENOydRaQ76MCe6WgQDGr3gp3iC0WDnVvZwXF8tG0y6mKtjvO0lu66PCPsVUSPIYAJGzF/MHI62YxvTosCKAKQ43LeBcBh1wxCiCohRLX9eBGAWCLycJMohJgjhBguhBiemZmpWUgjQ0JG1wTQyd3z9YdOx7c4jvd37IbdnZwxALof2W+ESIxOCIPiMJgRLQpgDYB8IupORHEApgL4wjUDEXUi+19JRCPs5ZbqLWwkYLS3wYi0Pgr0nQl9ncG5klrr3PVbmtSAovZOT6GdS3cHVbZRTsGc4RfM2BdljMCnAhBCNAO4HcB3ALYD+FAIsZWIbiGiW+zZJgPYQkQbAbwEYKrQqZZzVfUXfmN60OOjD40WQX9M3BONCkw4fRajJZN9WmeRW9psl+NZAGbpK5q9bBgzBRSJFhORaC5r0yHgTyjatZi2bfUv1CxwTPgwY17FGxE7gSML/kT8J1BncKEjplOnEJbORBPmbf5ZAagS6MKNCUd5Jy86hYRUwhIXp3uZTiI/ApuZGzVvRKrcoYIVgCrBzgEZU9UiTQEFJ25ozVdJWD3SztipzXxZU/kGRWAzY2QqLei1f8EoQwkzvvWIUACROLdthAKIzPcEBPtphCo6VZ9iz7T4phoAQHNEfDnK6KIAeEFZM2Z+VaavxpHXpBkpsYlrmgrB9MZC/aY7l3tqgPbnnoOyvllo1GQ+oYxhO3HN3BKFEX4LTkyvAABjfjC9/JSFn4gT2DTO4NxJaKjwSEvs0wfVuR57HBnGJzYTfpumVwDGv7IALVQiqLcVsRuDDNDO7a+/HiCdJp3CXEUit1OjJ8Z5FTAjplcAgEFz2+b9zbwS1Jsy4G8ObkEutPUirls3jNjjXPTNrKqFJT7eyx0mR5ffN6q1R0CYuSkxvQIQOmwUCogAg8Ib270y52Kqb4ILCUmW0FTjHl99CautwXF+SuFR+wMJFMyrNroNNfr5gaBj1TTszzfh0Mv0CiByMbPeZ7RAsbGIcZkes+r8AUecwkWE+poyCeZr/jW6gmCYUKHHPoBQNqRt6hsxbN8RpFfXoTE10Z5qj2MghKk9PbrjjL9gxqbo5MU4Re8bVgAqBL5pxmhvoBGICYfGrnSsqgUA9PppGYDgx3bGxbgIcFrTS1FMZGP6KSCjnMFFLBH3qnTYBxCm1siakiI91xLZPengNoJF5t/cirEBYcz37kyvAAwjArs4kSexhPk+C9+QiDyXChFYpZkQY3oFII0AmJOZSIu+aeY53fARye+AI4K1YnoFYDh+LwFEVxDJYAnKqsTAHjgh8CG90VMBETZwYUJIhCgArrFaMbpxCYigWyRjttRG2rvmkQvjjukVgHEGE0Eu9Bkw7Iu2xfJw/LWpV1wBAMj6179cUkknSxr2BaGVSFZeZm5kI8IMNHJ/+shAGDhtFVRT1LoTOIQNadaTTyDrySfkiTqaUxpCMArASOWhh9J1+S9jbuUEIHK/sYjEsMWqQBVQZK4BGOYNunUDWxBl8PcYOGZcHTS9AgAi1BmciVf+meCI2F9WV8Ej9i2wEnPB/ArA6F8rAudLIwkR1Hx6aENCqmJ3Bhdpi8AOdJtKYSId8ysAgwh80cnYaQkmfAS6EaxVcYR9kOh4YIQqLkZ3TK8AhMt/mZOP4PYBSP8Lu4UIT+8xAWDGneOmVwASxn1wgf9k3Ehox3wfhhaCnwIypo7YTNgQhY/w/+28EzgIBMigRWDz/mjeMKOlQahwNMBht6enCPUFFJl1mgkdplcAEdc7jLBGgfGfiG9GI3ETm54YJLsZjQZMrwAMGwG0Pj+iGnSBiFOYQNBKM/w7aiN5XyoisopE9gs3L6ZXABIGuFUI8s1w6LyTGX3iAYRfbwW/EYzxH4uJR0sRogC4yp6sRKSijECRGUYJw3wBbT1Rhf4//egzX7UlG21QG3J5qosLUf3KOY5zCwSmCwGseBeHV2grg4iQhuYQSejJvs3Lcfimmx3nc+xTKcvwqKb7iQALCBabQFooBFTh3RmPo7Rou3RiGwvsKseKZVdquleAQBap32JrqQ+RhMr8+N5X2FCwBcKah98n9wAef0H7zRarQ2+0GLBUP+W3L7AtIxli+p14s+4g8NNBbTeSRTbFVo+kEEmozrZlH+HcyqcAAIcfmaX5PiLyMBHuIspQgVw9xfNJ+foV+PCxVwAAyzTe0/pthhoyao6biE4A2GnIw/0jA0CJ0UJogOXUl0iQMxJkBFhOvekthGijR0FGegPdKYQYbuDzNUFEa1lO/WA59SMSZARYTr0horV6lRUhawAMwzCM3rACYBiGiVKMVABzDHy2P7Cc+sJy6kckyAiwnHqjm5yGLQIzDMMwxsJTQAzDMFEKKwCGYZgoRXcFQERWIvqdiL6yn7cnoh+IaLf9/+1c8j5ARAVEtJOIzndJH0ZEm+3XXqIQOHvRKicRnUtE6+zyrCOi8S5lLLHLvsH+r4OBcuYSUZ2LLLNdygjp+/RDxqtd5NtARDYiGmK/ZsS7/AMRbbXLMdwtr5nqpqKcJqybanIaVjf9lNNs9fM5ItpBRJuI6DMiSnPJq0/9FELo+g/A3QDeB/CV/fxZAPfbj+8H8Iz9uB+AjQDiAXQHsAeA1X5tNYDRkDbdfwPgQgPlHAogy348AMAhlzKWABiut2wBypkLYItKGSF9n1pldLtnIIC9Br/LvgB6uz/bhHVTTU6z1U01OQ2rm/7IacL6eR6AGPvxMwhB26nrCICIugC4CMDrLsmXAXjHfvwOgMtd0hcIIRqEEPsAFAAYQUSdAbQVQqwQ0l/0rss9YZdTCPG7EOKwPX0rgAQiitdTHj3k9FJGSN9nEDJeBWC+XnL4QklOIcR2IYTSbnRT1U01Oc1WN728T7UyTPU+3TBD/fxeCNHqW2YlgC72Y93qp95TQC8AuA/yuCQdhRBHAMD+/9ahUzYAV4ckRfa0bPuxe7pRcroyCcDvQogGl7S37EPCf4Rg+OqvnN3tQ8ilRHSGPS3U79NfGVu5Ep4fWLjfpRpmq5taMEPd9IYRdRMI/H2arX7eAKlHD+hYP3VTAER0MYBiIcQ6rbcopAkv6boQgJyt9/WHNAy72SX5aiHEQABn2P9da6CcRwB0FUIMhX0oSURtEcL3GcS7HAmgVgixxSXZTO+S66a+coa9bgInT/0koocANAOY15qkkC2g+qnnCGAMgEuJqBDAAgDjieg9AMfsQ5PWIV+xPX8RgByX+7sAOGxP76KQbpScrcOzzwBME0LsaU0XQhyy//8EpLm7EUbJaR8OltqP10GaF+yF0L5Pv9+lnalw610Z9C7VMFvdVMVkdVMRg+qm33K6YJr6SUTXAbgYkgJqbcz1q58hWswYC+dCxnOQLwg+az/uD/lCxl44FzLWABgF50LGBAPlTLPLOcnt3hgAGfbjWAAfA7jFQDkzXd5fDwCHALQP1/vUIqP93GKvqD2MfpcuaUsgX7Q0Vd30Iqep6qYXOQ2tm1rlNFv9BHABgG0AMt3y6FY/df8DFP6IdAA/Adht/397l3wPQeoN7ITLajWA4QC22K/Ngn3HshFyAvg7gBoAG1z+dQCQDGAdgE2QFuBebP0RDJJzkl2OjQDWA7gknO/Tj998LICVbvca9S4n2j/2BgDHAHxn0rqpKKcJ66aanIbWTT9/dzPVzwJIc/2tv+1svesnu4JgGIaJUngnMMMwTJTCCoBhGCZKYQXAMAwTpbACYBiGiVJYATAMw0QprAAYhmGiFFYADMMwUcr/AyTKdLQa2xCDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for w,s in zip(S2D_wavelengths_vacuum_laboratory[10], S2D_spectra_stellar_rest_frame[10]):\n",
    "    plt.plot(w, s)\n",
    "    \n",
    "np.save('S2D_spectra_stellar_rest_frame_with_star_included_W189', S2D_spectra_stellar_rest_frame)\n",
    "    \n",
    "plt.ylim(1.e3, 3.e6)\n",
    "plt.xlim(4000, 4200)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our spectra are finally ready to remove the stellar lines. To do that, we use the same trick employed by PCA. Since telluric correction is much less important in the optical, we ignore that, and we can use a much simpler method. We simply build a master spectrum by taking a median in time of all the spectra, while we are in the star rest frame. The planet is moving, and it is not removed. Tellurics are not removed because they vary in time.\n",
    "\n",
    "However, right now, the trick would not work because we have variable throughput during the night, and the median would give nonsense results. So let's first bring all the spectra to a common level. We do this order by order, because we did not perform a color-correction. I do this order by order also when I do perform the color-correction, because I think this is the most reliable way (color-correction still corrects inter-order continuum variations)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(141, 170, 9111)\n",
      "(141, 170, 9111)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Take the two central quartes of each order\n",
    "i1 = 2277\n",
    "i2=6833\n",
    "\n",
    "S2D_spectra_stellar_rest_frame_rescaled = []\n",
    "for s in S2D_spectra_stellar_rest_frame:\n",
    "    S2D_spectra_stellar_rest_frame_rescaled.append(s/np.average(s[:,i1:i2], axis=1)[:,None])\n",
    "S2D_spectra_stellar_rest_frame_rescaled = np.array(S2D_spectra_stellar_rest_frame_rescaled)\n",
    "\n",
    "    \n",
    "print(np.shape(S2D_spectra_stellar_rest_frame))\n",
    "print(np.shape(S2D_spectra_stellar_rest_frame_rescaled))\n",
    "    \n",
    "fig_order, ax_order = plot_single_order(S2D_spectra_stellar_rest_frame, order_index=130)\n",
    "fig_order_rescaled, ax_order_rescaled = plot_single_order(S2D_spectra_stellar_rest_frame_rescaled, order_index=130)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that the spectra are **rescaled** we can  **normalize** them by a master stellar spectrum (which contains some tellurics as well)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-34-4379e080b332>:4: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  S2D_spectra_stellar_rest_frame_normalized.append(s/median_S2D_spectra_stellar_rest_frame_rescaled)\n",
      "<ipython-input-34-4379e080b332>:4: RuntimeWarning: invalid value encountered in true_divide\n",
      "  S2D_spectra_stellar_rest_frame_normalized.append(s/median_S2D_spectra_stellar_rest_frame_rescaled)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(-0.1, 1.5)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "S2D_spectra_stellar_rest_frame_normalized = []\n",
    "median_S2D_spectra_stellar_rest_frame_rescaled = np.median(S2D_spectra_stellar_rest_frame_rescaled, axis=0)\n",
    "for s in S2D_spectra_stellar_rest_frame_rescaled:\n",
    "    S2D_spectra_stellar_rest_frame_normalized.append(s/median_S2D_spectra_stellar_rest_frame_rescaled)\n",
    "S2D_spectra_stellar_rest_frame_normalized = np.array(S2D_spectra_stellar_rest_frame_normalized)\n",
    "\n",
    "fig_order_normalized, ax_order_normalized = plot_single_order(S2D_spectra_stellar_rest_frame_normalized, order_index=131)\n",
    "\n",
    "# Plot master ontop of one exposure\n",
    "plt.figure()\n",
    "for o in range(170):\n",
    "    plt.plot(S2D_wavelengths_vacuum_laboratory[50, o], S2D_spectra_stellar_rest_frame_rescaled[50, o], 'k', S2D_wavelengths_vacuum_laboratory[50, o], median_S2D_spectra_stellar_rest_frame_rescaled[o], 'r')\n",
    "\n",
    "plt.xlim(4000, 4050)\n",
    "plt.ylim(-0.1, 1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remember that the first orders have less pixels? When we divide by zero we get a warning. If we are not extremely careful, our cross-correlations and likelihoods will make no sense. I thus prefer to set nans to zeros, which is the null value for the binary mask cross-correlations (if you use other methods, you may need to set it to one, or other values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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": [
    "S2D_spectra_stellar_rest_frame_normalized = np.nan_to_num(S2D_spectra_stellar_rest_frame_normalized)\n",
    "\n",
    "# Plot final spectra\n",
    "plt.figure()\n",
    "for o in range(170):\n",
    "    plt.plot(S2D_wavelengths_vacuum_laboratory[50, o], S2D_spectra_stellar_rest_frame_normalized[50, o], 'k')\n",
    "\n",
    "plt.xlim(4100, 4200)\n",
    "plt.ylim(-0.1, 1.5)\n",
    "\n",
    "np.save('S2D_wavelengths_vacuum_laboratory_W189', S2D_wavelengths_vacuum_laboratory)\n",
    "np.save('S2D_spectra_barycentric_normalized_W189', S2D_spectra_stellar_rest_frame_normalized)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we are ready to cross-correlate! Of course, you should be aware that we have not corrected for tellurics. While this can be fine for the bluest orders, for example if you focus on neutral iron, or it could be fine for a quick look, you probably want to implement a telluric correction or at least mask out the contaminated regions before proceeding.\n",
    "\n",
    "Also, note how the singal to noise is strongly varying with wavelength. This is something that we need to consider when cross-correlating with yout favorite method. Did you already guess why the noise in the blue parts of the order is so high?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4100.0, 4200.0)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "import glob\n",
    "data_files_A_blaze = glob.glob(input_data_directory + '*BLAZE_A_*')\n",
    "blaze_profiles = fits.open(data_files_A_blaze[0])[1].data\n",
    "\n",
    "for w, b in zip(S2D_wavelengths_vacuum_laboratory[0], blaze_profiles):\n",
    "    plt.plot(w, b, 'k')\n",
    "    \n",
    "plt.xlim(4100, 4200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Typically, two more operations can be performed on data, which will improve the significance. ESPRESSO is a good instruments, thus the improvement is only marginal. I do not include them here. In the full pipeline, I will implement those methods.\n",
    "1. High-pass filtering to remove smooth variations (imperfect blaze correction or color-correction, ...)\n",
    "2. Removal of outliers (cosmic rays etc).\n",
    "In ESPRESSO, the first step is important for publishing since there is an effect called \"wiggles\", which are low frequency oscillations observed ontop of the specrta, with phase change typically occurring at half of the night."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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