{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "670d8735",
   "metadata": {},
   "source": [
    "# Removing the baseline from cross dispersed data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "58dbf559",
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.io import fits\n",
    "import numpy as np\n",
    "from scipy.ndimage import median_filter\n",
    "\n",
    "\n",
    "# import SPM or COM file of high-medium or high-low observations\n",
    "file_name = \"./reprocessTest/F0866_EX_SPE_750106275_EXEELONEXEECHL_COM_80029.fits\"\n",
    "hdul = fits.open(file_name)\n",
    "\n",
    "#Uncomment below to check to see structure\n",
    "#hdul.info()\n",
    "\n",
    "header = hdul[0].header\n",
    "#Smoothing parameter for median filtering\n",
    "smoothParam = 100\n",
    "\n",
    "#Loop over all orders\n",
    "for j in range(header['NORDERS']):\n",
    "    ordnum = f'{j + 1:02d}'\n",
    "    \n",
    "    #Divide out the baseline from the error plane first,\n",
    "    #since we'll be overwriting the flux_order array directly\n",
    "    hdul[f'SPECTRAL_ERROR_ORDER_{ordnum}'].data = (hdul[f'SPECTRAL_ERROR_ORDER_{ordnum}'].data/\n",
    "                                                   median_filter(hdul[f'SPECTRAL_FLUX_ORDER_{ordnum}'].data,smoothParam))\n",
    "\n",
    "    #No divide out the baseline from flux_order planes\n",
    "    hdul[f'SPECTRAL_FLUX_ORDER_{ordnum}'].data = (hdul[f'SPECTRAL_FLUX_ORDER_{ordnum}'].data/\n",
    "                                                  median_filter(hdul[f'SPECTRAL_FLUX_ORDER_{ordnum}'].data,smoothParam))\n",
    "#Write out same file name\n",
    "hdul.writeto(file_name,overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5e8013a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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