{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using the spectral library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "--- Description of libraries\n",
      "--------------------------------------------------------------------------------\n",
      "Key         :  A\n",
      "Description :  solar metallicity, 3800-11000 A, Teff = 3500-20000 K, logg = 0-5\n",
      "--------------------------------------------------------------------------------\n",
      "Model filename:  diskint_teff_5750_logg_45_p00.fits.gz\n"
     ]
    },
    {
     "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 numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "from PyAstronomy import pyasl\n",
    "import os\n",
    "\n",
    "sl = pyasl.SpectralLib()\n",
    "\n",
    "# List available libraries\n",
    "sl.listDescription()\n",
    "\n",
    "# Disk-integrated spectrum for Teff, logg, and metallicty\n",
    "sdifn = sl.requestModel(5750, 4.5, 0.0, nex=\"diskint\")\n",
    "\n",
    "print(\"Model filename: \", os.path.basename(sdifn))\n",
    "\n",
    "w, f = sl.read1dFitsSpec(sdifn)\n",
    "\n",
    "plt.xlabel(\"Wavelength [$\\AA$]\")\n",
    "plt.ylabel(\"Astrophysical flux [erg/cm**2/s/A]\")\n",
    "plt.plot(w, f, 'b.-')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Limb-angle resolved Halpha line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available cos(theta) = mu angles:  [0.001 0.1   0.2   0.3   0.4   0.5   0.6   0.7   0.8   0.9   1.   ]\n"
     ]
    },
    {
     "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": [
    "wlmin = 6564-20\n",
    "wlmax = 6564+20\n",
    "indi = (w > wlmin) & (w < wlmax)\n",
    "\n",
    "# Specific intensity resolved w.r.t. viewing angle\n",
    "# for Teff, logg, and metallicty\n",
    "musfn = sl.requestModel(5750, 4.5, 0.0, nex=\"muspecs\")\n",
    "\n",
    "w, mus, intens = sl.readMuFits(musfn)\n",
    "\n",
    "print(\"Available cos(theta) = mu angles: \", mus)\n",
    "\n",
    "# Plot specific intensity\n",
    "for i, mu in enumerate(mus):\n",
    "    plt.plot(w[indi], intens[indi,i], label=\"mu = %3.1f\" % mu)\n",
    "plt.xlabel(\"Wavelength [$\\AA$]\")\n",
    "plt.ylabel(\"Specific intensity\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manuel disk integration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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": [
    "# Real (not astrophysical) flux\n",
    "rf = np.zeros_like(w)\n",
    "\n",
    "for i in range(len(mus)-1):\n",
    "    # rf += I*mu*dmu\n",
    "    rf += (intens[::,i]*mus[i] + intens[::,i+1]*mus[i+1])/2 * (mus[i+1] - mus[i])\n",
    "rf *= 2*np.pi\n",
    "# Astrophysical flux\n",
    "af = rf/np.pi\n",
    "\n",
    "plt.plot(w[::10], f[::10], 'g:', label=\"Disk-integrated library flux\")\n",
    "plt.plot(w[::10], af[::10], 'b.:', label=\"Astrophysical flux (integral)\")\n",
    "plt.plot(w[::10], pyasl.planck(5750, w[::10]*1e-10)*1e-7/np.pi, 'r--', label=\"Planck\") \n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Listing available content"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------------------------------------------------------\n",
      "--- Inventory\n",
      "--------------------------------------------------------------------------------\n",
      "(10000.0, 2.0, 0.0, 'diskint') diskint_teff_10000_logg_20_p00.fits.gz\n",
      "(10000.0, 3.0, 0.0, 'diskint') diskint_teff_10000_logg_30_p00.fits.gz\n",
      "(10000.0, 3.5, 0.0, 'diskint') diskint_teff_10000_logg_35_p00.fits.gz\n",
      "(10000.0, 4.0, 0.0, 'diskint') diskint_teff_10000_logg_40_p00.fits.gz\n",
      "(10000.0, 4.5, 0.0, 'diskint') diskint_teff_10000_logg_45_p00.fits.gz\n",
      "(10000.0, 5.0, 0.0, 'diskint') diskint_teff_10000_logg_50_p00.fits.gz\n",
      "(12000.0, 3.0, 0.0, 'diskint') diskint_teff_12000_logg_30_p00.fits.gz\n",
      "(12000.0, 3.5, 0.0, 'diskint') diskint_teff_12000_logg_35_p00.fits.gz\n",
      "(12000.0, 4.0, 0.0, 'diskint') diskint_teff_12000_logg_40_p00.fits.gz\n",
      "(12000.0, 4.5, 0.0, 'diskint') diskint_teff_12000_logg_45_p00.fits.gz\n",
      "(12000.0, 5.0, 0.0, 'diskint') diskint_teff_12000_logg_50_p00.fits.gz\n",
      "(15000.0, 3.0, 0.0, 'diskint') diskint_teff_15000_logg_30_p00.fits.gz\n",
      "(15000.0, 3.5, 0.0, 'diskint') diskint_teff_15000_logg_35_p00.fits.gz\n",
      "(15000.0, 4.0, 0.0, 'diskint') diskint_teff_15000_logg_40_p00.fits.gz\n",
      "(15000.0, 4.5, 0.0, 'diskint') diskint_teff_15000_logg_45_p00.fits.gz\n",
      "(15000.0, 5.0, 0.0, 'diskint') diskint_teff_15000_logg_50_p00.fits.gz\n",
      "(20000.0, 3.0, 0.0, 'diskint') diskint_teff_20000_logg_30_p00.fits.gz\n",
      "(20000.0, 3.5, 0.0, 'diskint') diskint_teff_20000_logg_35_p00.fits.gz\n",
      "(20000.0, 4.0, 0.0, 'diskint') diskint_teff_20000_logg_40_p00.fits.gz\n",
      "(20000.0, 4.5, 0.0, 'diskint') diskint_teff_20000_logg_45_p00.fits.gz\n",
      "(20000.0, 5.0, 0.0, 'diskint') diskint_teff_20000_logg_50_p00.fits.gz\n",
      "(3500.0, 0.0, 0.0, 'diskint') diskint_teff_3500_logg_00_p00.fits.gz\n",
      "(3500.0, 1.0, 0.0, 'diskint') diskint_teff_3500_logg_10_p00.fits.gz\n",
      "(3500.0, 2.0, 0.0, 'diskint') diskint_teff_3500_logg_20_p00.fits.gz\n",
      "(3500.0, 3.0, 0.0, 'diskint') diskint_teff_3500_logg_30_p00.fits.gz\n",
      "(3500.0, 3.5, 0.0, 'diskint') diskint_teff_3500_logg_35_p00.fits.gz\n",
      "(3500.0, 4.0, 0.0, 'diskint') diskint_teff_3500_logg_40_p00.fits.gz\n",
      "(3500.0, 4.5, 0.0, 'diskint') diskint_teff_3500_logg_45_p00.fits.gz\n",
      "(3500.0, 5.0, 0.0, 'diskint') diskint_teff_3500_logg_50_p00.fits.gz\n",
      "(3750.0, 0.0, 0.0, 'diskint') diskint_teff_3750_logg_00_p00.fits.gz\n",
      "(3750.0, 1.0, 0.0, 'diskint') diskint_teff_3750_logg_10_p00.fits.gz\n",
      "(3750.0, 2.0, 0.0, 'diskint') diskint_teff_3750_logg_20_p00.fits.gz\n",
      "(3750.0, 3.0, 0.0, 'diskint') diskint_teff_3750_logg_30_p00.fits.gz\n",
      "(3750.0, 3.5, 0.0, 'diskint') diskint_teff_3750_logg_35_p00.fits.gz\n",
      "(3750.0, 4.0, 0.0, 'diskint') diskint_teff_3750_logg_40_p00.fits.gz\n",
      "(3750.0, 4.5, 0.0, 'diskint') diskint_teff_3750_logg_45_p00.fits.gz\n",
      "(3750.0, 5.0, 0.0, 'diskint') diskint_teff_3750_logg_50_p00.fits.gz\n",
      "(4000.0, 0.0, 0.0, 'diskint') diskint_teff_4000_logg_00_p00.fits.gz\n",
      "(4000.0, 1.0, 0.0, 'diskint') diskint_teff_4000_logg_10_p00.fits.gz\n",
      "(4000.0, 2.0, 0.0, 'diskint') diskint_teff_4000_logg_20_p00.fits.gz\n",
      "(4000.0, 3.0, 0.0, 'diskint') diskint_teff_4000_logg_30_p00.fits.gz\n",
      "(4000.0, 3.5, 0.0, 'diskint') diskint_teff_4000_logg_35_p00.fits.gz\n",
      "(4000.0, 4.0, 0.0, 'diskint') diskint_teff_4000_logg_40_p00.fits.gz\n",
      "(4000.0, 4.5, 0.0, 'diskint') diskint_teff_4000_logg_45_p00.fits.gz\n",
      "(4000.0, 5.0, 0.0, 'diskint') diskint_teff_4000_logg_50_p00.fits.gz\n",
      "(4250.0, 0.0, 0.0, 'diskint') diskint_teff_4250_logg_00_p00.fits.gz\n",
      "(4250.0, 1.0, 0.0, 'diskint') diskint_teff_4250_logg_10_p00.fits.gz\n",
      "(4250.0, 2.0, 0.0, 'diskint') diskint_teff_4250_logg_20_p00.fits.gz\n",
      "(4250.0, 3.0, 0.0, 'diskint') diskint_teff_4250_logg_30_p00.fits.gz\n",
      "(4250.0, 3.5, 0.0, 'diskint') diskint_teff_4250_logg_35_p00.fits.gz\n",
      "(4250.0, 4.0, 0.0, 'diskint') diskint_teff_4250_logg_40_p00.fits.gz\n",
      "(4250.0, 4.5, 0.0, 'diskint') diskint_teff_4250_logg_45_p00.fits.gz\n",
      "(4250.0, 5.0, 0.0, 'diskint') diskint_teff_4250_logg_50_p00.fits.gz\n",
      "(4500.0, 0.0, 0.0, 'diskint') diskint_teff_4500_logg_00_p00.fits.gz\n",
      "(4500.0, 1.0, 0.0, 'diskint') diskint_teff_4500_logg_10_p00.fits.gz\n",
      "(4500.0, 2.0, 0.0, 'diskint') diskint_teff_4500_logg_20_p00.fits.gz\n",
      "(4500.0, 3.0, 0.0, 'diskint') diskint_teff_4500_logg_30_p00.fits.gz\n",
      "(4500.0, 3.5, 0.0, 'diskint') diskint_teff_4500_logg_35_p00.fits.gz\n",
      "(4500.0, 4.0, 0.0, 'diskint') diskint_teff_4500_logg_40_p00.fits.gz\n",
      "(4500.0, 4.5, 0.0, 'diskint') diskint_teff_4500_logg_45_p00.fits.gz\n",
      "(4500.0, 5.0, 0.0, 'diskint') diskint_teff_4500_logg_50_p00.fits.gz\n",
      "(4750.0, 0.0, 0.0, 'diskint') diskint_teff_4750_logg_00_p00.fits.gz\n",
      "(4750.0, 1.0, 0.0, 'diskint') diskint_teff_4750_logg_10_p00.fits.gz\n",
      "(4750.0, 2.0, 0.0, 'diskint') diskint_teff_4750_logg_20_p00.fits.gz\n",
      "(4750.0, 3.0, 0.0, 'diskint') diskint_teff_4750_logg_30_p00.fits.gz\n",
      "(4750.0, 3.5, 0.0, 'diskint') diskint_teff_4750_logg_35_p00.fits.gz\n",
      "(4750.0, 4.0, 0.0, 'diskint') diskint_teff_4750_logg_40_p00.fits.gz\n",
      "(4750.0, 4.5, 0.0, 'diskint') diskint_teff_4750_logg_45_p00.fits.gz\n",
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      "(4000.0, 4.5, 0.0, 'muspecs') muspecs_teff_4000_logg_45_p00.fits.gz\n",
      "(4000.0, 5.0, 0.0, 'muspecs') muspecs_teff_4000_logg_50_p00.fits.gz\n",
      "(4250.0, 0.0, 0.0, 'muspecs') muspecs_teff_4250_logg_00_p00.fits.gz\n",
      "(4250.0, 1.0, 0.0, 'muspecs') muspecs_teff_4250_logg_10_p00.fits.gz\n",
      "(4250.0, 2.0, 0.0, 'muspecs') muspecs_teff_4250_logg_20_p00.fits.gz\n",
      "(4250.0, 3.0, 0.0, 'muspecs') muspecs_teff_4250_logg_30_p00.fits.gz\n",
      "(4250.0, 3.5, 0.0, 'muspecs') muspecs_teff_4250_logg_35_p00.fits.gz\n",
      "(4250.0, 4.0, 0.0, 'muspecs') muspecs_teff_4250_logg_40_p00.fits.gz\n",
      "(4250.0, 4.5, 0.0, 'muspecs') muspecs_teff_4250_logg_45_p00.fits.gz\n",
      "(4250.0, 5.0, 0.0, 'muspecs') muspecs_teff_4250_logg_50_p00.fits.gz\n",
      "(4500.0, 0.0, 0.0, 'muspecs') muspecs_teff_4500_logg_00_p00.fits.gz\n",
      "(4500.0, 1.0, 0.0, 'muspecs') muspecs_teff_4500_logg_10_p00.fits.gz\n",
      "(4500.0, 2.0, 0.0, 'muspecs') muspecs_teff_4500_logg_20_p00.fits.gz\n",
      "(4500.0, 3.0, 0.0, 'muspecs') muspecs_teff_4500_logg_30_p00.fits.gz\n",
      "(4500.0, 3.5, 0.0, 'muspecs') muspecs_teff_4500_logg_35_p00.fits.gz\n",
      "(4500.0, 4.0, 0.0, 'muspecs') muspecs_teff_4500_logg_40_p00.fits.gz\n",
      "(4500.0, 4.5, 0.0, 'muspecs') muspecs_teff_4500_logg_45_p00.fits.gz\n",
      "(4500.0, 5.0, 0.0, 'muspecs') muspecs_teff_4500_logg_50_p00.fits.gz\n",
      "(4750.0, 0.0, 0.0, 'muspecs') muspecs_teff_4750_logg_00_p00.fits.gz\n",
      "(4750.0, 1.0, 0.0, 'muspecs') muspecs_teff_4750_logg_10_p00.fits.gz\n",
      "(4750.0, 2.0, 0.0, 'muspecs') muspecs_teff_4750_logg_20_p00.fits.gz\n",
      "(4750.0, 3.0, 0.0, 'muspecs') muspecs_teff_4750_logg_30_p00.fits.gz\n",
      "(4750.0, 3.5, 0.0, 'muspecs') muspecs_teff_4750_logg_35_p00.fits.gz\n",
      "(4750.0, 4.0, 0.0, 'muspecs') muspecs_teff_4750_logg_40_p00.fits.gz\n",
      "(4750.0, 4.5, 0.0, 'muspecs') muspecs_teff_4750_logg_45_p00.fits.gz\n",
      "(4750.0, 5.0, 0.0, 'muspecs') muspecs_teff_4750_logg_50_p00.fits.gz\n",
      "(5000.0, 0.0, 0.0, 'muspecs') muspecs_teff_5000_logg_00_p00.fits.gz\n",
      "(5000.0, 1.0, 0.0, 'muspecs') muspecs_teff_5000_logg_10_p00.fits.gz\n",
      "(5000.0, 2.0, 0.0, 'muspecs') muspecs_teff_5000_logg_20_p00.fits.gz\n",
      "(5000.0, 3.0, 0.0, 'muspecs') muspecs_teff_5000_logg_30_p00.fits.gz\n",
      "(5000.0, 3.5, 0.0, 'muspecs') muspecs_teff_5000_logg_35_p00.fits.gz\n",
      "(5000.0, 4.0, 0.0, 'muspecs') muspecs_teff_5000_logg_40_p00.fits.gz\n",
      "(5000.0, 4.5, 0.0, 'muspecs') muspecs_teff_5000_logg_45_p00.fits.gz\n",
      "(5000.0, 5.0, 0.0, 'muspecs') muspecs_teff_5000_logg_50_p00.fits.gz\n",
      "(5250.0, 0.0, 0.0, 'muspecs') muspecs_teff_5250_logg_00_p00.fits.gz\n",
      "(5250.0, 1.0, 0.0, 'muspecs') muspecs_teff_5250_logg_10_p00.fits.gz\n",
      "(5250.0, 2.0, 0.0, 'muspecs') muspecs_teff_5250_logg_20_p00.fits.gz\n",
      "(5250.0, 3.0, 0.0, 'muspecs') muspecs_teff_5250_logg_30_p00.fits.gz\n",
      "(5250.0, 3.5, 0.0, 'muspecs') muspecs_teff_5250_logg_35_p00.fits.gz\n",
      "(5250.0, 4.0, 0.0, 'muspecs') muspecs_teff_5250_logg_40_p00.fits.gz\n",
      "(5250.0, 4.5, 0.0, 'muspecs') muspecs_teff_5250_logg_45_p00.fits.gz\n",
      "(5250.0, 5.0, 0.0, 'muspecs') muspecs_teff_5250_logg_50_p00.fits.gz\n",
      "(5500.0, 0.0, 0.0, 'muspecs') muspecs_teff_5500_logg_00_p00.fits.gz\n",
      "(5500.0, 1.0, 0.0, 'muspecs') muspecs_teff_5500_logg_10_p00.fits.gz\n",
      "(5500.0, 2.0, 0.0, 'muspecs') muspecs_teff_5500_logg_20_p00.fits.gz\n",
      "(5500.0, 3.0, 0.0, 'muspecs') muspecs_teff_5500_logg_30_p00.fits.gz\n",
      "(5500.0, 3.5, 0.0, 'muspecs') muspecs_teff_5500_logg_35_p00.fits.gz\n",
      "(5500.0, 4.0, 0.0, 'muspecs') muspecs_teff_5500_logg_40_p00.fits.gz\n",
      "(5500.0, 4.5, 0.0, 'muspecs') muspecs_teff_5500_logg_45_p00.fits.gz\n",
      "(5500.0, 5.0, 0.0, 'muspecs') muspecs_teff_5500_logg_50_p00.fits.gz\n",
      "(5750.0, 0.0, 0.0, 'muspecs') muspecs_teff_5750_logg_00_p00.fits.gz\n",
      "(5750.0, 1.0, 0.0, 'muspecs') muspecs_teff_5750_logg_10_p00.fits.gz\n",
      "(5750.0, 2.0, 0.0, 'muspecs') muspecs_teff_5750_logg_20_p00.fits.gz\n",
      "(5750.0, 3.0, 0.0, 'muspecs') muspecs_teff_5750_logg_30_p00.fits.gz\n",
      "(5750.0, 3.5, 0.0, 'muspecs') muspecs_teff_5750_logg_35_p00.fits.gz\n",
      "(5750.0, 4.0, 0.0, 'muspecs') muspecs_teff_5750_logg_40_p00.fits.gz\n",
      "(5750.0, 4.5, 0.0, 'muspecs') muspecs_teff_5750_logg_45_p00.fits.gz\n",
      "(5750.0, 5.0, 0.0, 'muspecs') muspecs_teff_5750_logg_50_p00.fits.gz\n",
      "(6000.0, 0.0, 0.0, 'muspecs') muspecs_teff_6000_logg_00_p00.fits.gz\n",
      "(6000.0, 1.0, 0.0, 'muspecs') muspecs_teff_6000_logg_10_p00.fits.gz\n",
      "(6000.0, 2.0, 0.0, 'muspecs') muspecs_teff_6000_logg_20_p00.fits.gz\n",
      "(6000.0, 3.0, 0.0, 'muspecs') muspecs_teff_6000_logg_30_p00.fits.gz\n",
      "(6000.0, 3.5, 0.0, 'muspecs') muspecs_teff_6000_logg_35_p00.fits.gz\n",
      "(6000.0, 4.0, 0.0, 'muspecs') muspecs_teff_6000_logg_40_p00.fits.gz\n",
      "(6000.0, 4.5, 0.0, 'muspecs') muspecs_teff_6000_logg_45_p00.fits.gz\n",
      "(6000.0, 5.0, 0.0, 'muspecs') muspecs_teff_6000_logg_50_p00.fits.gz\n",
      "(6250.0, 1.0, 0.0, 'muspecs') muspecs_teff_6250_logg_10_p00.fits.gz\n",
      "(6250.0, 2.0, 0.0, 'muspecs') muspecs_teff_6250_logg_20_p00.fits.gz\n",
      "(6250.0, 3.0, 0.0, 'muspecs') muspecs_teff_6250_logg_30_p00.fits.gz\n",
      "(6250.0, 3.5, 0.0, 'muspecs') muspecs_teff_6250_logg_35_p00.fits.gz\n",
      "(6250.0, 4.0, 0.0, 'muspecs') muspecs_teff_6250_logg_40_p00.fits.gz\n",
      "(6250.0, 4.5, 0.0, 'muspecs') muspecs_teff_6250_logg_45_p00.fits.gz\n",
      "(6250.0, 5.0, 0.0, 'muspecs') muspecs_teff_6250_logg_50_p00.fits.gz\n",
      "(6500.0, 1.0, 0.0, 'muspecs') muspecs_teff_6500_logg_10_p00.fits.gz\n",
      "(6500.0, 2.0, 0.0, 'muspecs') muspecs_teff_6500_logg_20_p00.fits.gz\n",
      "(6500.0, 3.0, 0.0, 'muspecs') muspecs_teff_6500_logg_30_p00.fits.gz\n",
      "(6500.0, 3.5, 0.0, 'muspecs') muspecs_teff_6500_logg_35_p00.fits.gz\n",
      "(6500.0, 4.0, 0.0, 'muspecs') muspecs_teff_6500_logg_40_p00.fits.gz\n",
      "(6500.0, 4.5, 0.0, 'muspecs') muspecs_teff_6500_logg_45_p00.fits.gz\n",
      "(6500.0, 5.0, 0.0, 'muspecs') muspecs_teff_6500_logg_50_p00.fits.gz\n",
      "(6750.0, 1.0, 0.0, 'muspecs') muspecs_teff_6750_logg_10_p00.fits.gz\n",
      "(6750.0, 2.0, 0.0, 'muspecs') muspecs_teff_6750_logg_20_p00.fits.gz\n",
      "(6750.0, 3.0, 0.0, 'muspecs') muspecs_teff_6750_logg_30_p00.fits.gz\n",
      "(6750.0, 3.5, 0.0, 'muspecs') muspecs_teff_6750_logg_35_p00.fits.gz\n",
      "(6750.0, 4.0, 0.0, 'muspecs') muspecs_teff_6750_logg_40_p00.fits.gz\n",
      "(6750.0, 4.5, 0.0, 'muspecs') muspecs_teff_6750_logg_45_p00.fits.gz\n",
      "(6750.0, 5.0, 0.0, 'muspecs') muspecs_teff_6750_logg_50_p00.fits.gz\n",
      "(7000.0, 1.0, 0.0, 'muspecs') muspecs_teff_7000_logg_10_p00.fits.gz\n",
      "(7000.0, 2.0, 0.0, 'muspecs') muspecs_teff_7000_logg_20_p00.fits.gz\n",
      "(7000.0, 3.0, 0.0, 'muspecs') muspecs_teff_7000_logg_30_p00.fits.gz\n",
      "(7000.0, 3.5, 0.0, 'muspecs') muspecs_teff_7000_logg_35_p00.fits.gz\n",
      "(7000.0, 4.0, 0.0, 'muspecs') muspecs_teff_7000_logg_40_p00.fits.gz\n",
      "(7000.0, 4.5, 0.0, 'muspecs') muspecs_teff_7000_logg_45_p00.fits.gz\n",
      "(7000.0, 5.0, 0.0, 'muspecs') muspecs_teff_7000_logg_50_p00.fits.gz\n",
      "(7250.0, 1.0, 0.0, 'muspecs') muspecs_teff_7250_logg_10_p00.fits.gz\n",
      "(7250.0, 2.0, 0.0, 'muspecs') muspecs_teff_7250_logg_20_p00.fits.gz\n",
      "(7250.0, 3.0, 0.0, 'muspecs') muspecs_teff_7250_logg_30_p00.fits.gz\n",
      "(7250.0, 3.5, 0.0, 'muspecs') muspecs_teff_7250_logg_35_p00.fits.gz\n",
      "(7250.0, 4.0, 0.0, 'muspecs') muspecs_teff_7250_logg_40_p00.fits.gz\n",
      "(7250.0, 4.5, 0.0, 'muspecs') muspecs_teff_7250_logg_45_p00.fits.gz\n",
      "(7250.0, 5.0, 0.0, 'muspecs') muspecs_teff_7250_logg_50_p00.fits.gz\n",
      "(7500.0, 1.0, 0.0, 'muspecs') muspecs_teff_7500_logg_10_p00.fits.gz\n",
      "(7500.0, 2.0, 0.0, 'muspecs') muspecs_teff_7500_logg_20_p00.fits.gz\n",
      "(7500.0, 3.0, 0.0, 'muspecs') muspecs_teff_7500_logg_30_p00.fits.gz\n",
      "(7500.0, 3.5, 0.0, 'muspecs') muspecs_teff_7500_logg_35_p00.fits.gz\n",
      "(7500.0, 4.0, 0.0, 'muspecs') muspecs_teff_7500_logg_40_p00.fits.gz\n",
      "(7500.0, 4.5, 0.0, 'muspecs') muspecs_teff_7500_logg_45_p00.fits.gz\n",
      "(7500.0, 5.0, 0.0, 'muspecs') muspecs_teff_7500_logg_50_p00.fits.gz\n",
      "(7750.0, 1.0, 0.0, 'muspecs') muspecs_teff_7750_logg_10_p00.fits.gz\n",
      "(7750.0, 2.0, 0.0, 'muspecs') muspecs_teff_7750_logg_20_p00.fits.gz\n",
      "(7750.0, 3.0, 0.0, 'muspecs') muspecs_teff_7750_logg_30_p00.fits.gz\n",
      "(7750.0, 3.5, 0.0, 'muspecs') muspecs_teff_7750_logg_35_p00.fits.gz\n",
      "(7750.0, 4.0, 0.0, 'muspecs') muspecs_teff_7750_logg_40_p00.fits.gz\n",
      "(7750.0, 4.5, 0.0, 'muspecs') muspecs_teff_7750_logg_45_p00.fits.gz\n",
      "(7750.0, 5.0, 0.0, 'muspecs') muspecs_teff_7750_logg_50_p00.fits.gz\n",
      "(8000.0, 1.0, 0.0, 'muspecs') muspecs_teff_8000_logg_10_p00.fits.gz\n",
      "(8000.0, 2.0, 0.0, 'muspecs') muspecs_teff_8000_logg_20_p00.fits.gz\n",
      "(8000.0, 3.0, 0.0, 'muspecs') muspecs_teff_8000_logg_30_p00.fits.gz\n",
      "(8000.0, 3.5, 0.0, 'muspecs') muspecs_teff_8000_logg_35_p00.fits.gz\n",
      "(8000.0, 4.0, 0.0, 'muspecs') muspecs_teff_8000_logg_40_p00.fits.gz\n",
      "(8000.0, 4.5, 0.0, 'muspecs') muspecs_teff_8000_logg_45_p00.fits.gz\n",
      "(8000.0, 5.0, 0.0, 'muspecs') muspecs_teff_8000_logg_50_p00.fits.gz\n",
      "(8250.0, 1.0, 0.0, 'muspecs') muspecs_teff_8250_logg_10_p00.fits.gz\n",
      "(8250.0, 2.0, 0.0, 'muspecs') muspecs_teff_8250_logg_20_p00.fits.gz\n",
      "(8250.0, 3.0, 0.0, 'muspecs') muspecs_teff_8250_logg_30_p00.fits.gz\n",
      "(8250.0, 3.5, 0.0, 'muspecs') muspecs_teff_8250_logg_35_p00.fits.gz\n",
      "(8250.0, 4.0, 0.0, 'muspecs') muspecs_teff_8250_logg_40_p00.fits.gz\n",
      "(8250.0, 4.5, 0.0, 'muspecs') muspecs_teff_8250_logg_45_p00.fits.gz\n",
      "(8250.0, 5.0, 0.0, 'muspecs') muspecs_teff_8250_logg_50_p00.fits.gz\n",
      "(8500.0, 2.0, 0.0, 'muspecs') muspecs_teff_8500_logg_20_p00.fits.gz\n",
      "(8500.0, 3.0, 0.0, 'muspecs') muspecs_teff_8500_logg_30_p00.fits.gz\n",
      "(8500.0, 3.5, 0.0, 'muspecs') muspecs_teff_8500_logg_35_p00.fits.gz\n",
      "(8500.0, 4.0, 0.0, 'muspecs') muspecs_teff_8500_logg_40_p00.fits.gz\n",
      "(8500.0, 4.5, 0.0, 'muspecs') muspecs_teff_8500_logg_45_p00.fits.gz\n",
      "(8500.0, 5.0, 0.0, 'muspecs') muspecs_teff_8500_logg_50_p00.fits.gz\n",
      "(8750.0, 2.0, 0.0, 'muspecs') muspecs_teff_8750_logg_20_p00.fits.gz\n",
      "(8750.0, 3.0, 0.0, 'muspecs') muspecs_teff_8750_logg_30_p00.fits.gz\n",
      "(8750.0, 3.5, 0.0, 'muspecs') muspecs_teff_8750_logg_35_p00.fits.gz\n",
      "(8750.0, 4.0, 0.0, 'muspecs') muspecs_teff_8750_logg_40_p00.fits.gz\n",
      "(8750.0, 4.5, 0.0, 'muspecs') muspecs_teff_8750_logg_45_p00.fits.gz\n",
      "(8750.0, 5.0, 0.0, 'muspecs') muspecs_teff_8750_logg_50_p00.fits.gz\n",
      "(9000.0, 2.0, 0.0, 'muspecs') muspecs_teff_9000_logg_20_p00.fits.gz\n",
      "(9000.0, 3.0, 0.0, 'muspecs') muspecs_teff_9000_logg_30_p00.fits.gz\n",
      "(9000.0, 3.5, 0.0, 'muspecs') muspecs_teff_9000_logg_35_p00.fits.gz\n",
      "(9000.0, 4.0, 0.0, 'muspecs') muspecs_teff_9000_logg_40_p00.fits.gz\n",
      "(9000.0, 4.5, 0.0, 'muspecs') muspecs_teff_9000_logg_45_p00.fits.gz\n",
      "(9000.0, 5.0, 0.0, 'muspecs') muspecs_teff_9000_logg_50_p00.fits.gz\n",
      "(9250.0, 2.0, 0.0, 'muspecs') muspecs_teff_9250_logg_20_p00.fits.gz\n",
      "(9250.0, 3.0, 0.0, 'muspecs') muspecs_teff_9250_logg_30_p00.fits.gz\n",
      "(9250.0, 3.5, 0.0, 'muspecs') muspecs_teff_9250_logg_35_p00.fits.gz\n",
      "(9250.0, 4.0, 0.0, 'muspecs') muspecs_teff_9250_logg_40_p00.fits.gz\n",
      "(9250.0, 4.5, 0.0, 'muspecs') muspecs_teff_9250_logg_45_p00.fits.gz\n",
      "(9250.0, 5.0, 0.0, 'muspecs') muspecs_teff_9250_logg_50_p00.fits.gz\n",
      "(9500.0, 2.0, 0.0, 'muspecs') muspecs_teff_9500_logg_20_p00.fits.gz\n",
      "(9500.0, 3.0, 0.0, 'muspecs') muspecs_teff_9500_logg_30_p00.fits.gz\n",
      "(9500.0, 3.5, 0.0, 'muspecs') muspecs_teff_9500_logg_35_p00.fits.gz\n",
      "(9500.0, 4.0, 0.0, 'muspecs') muspecs_teff_9500_logg_40_p00.fits.gz\n",
      "(9500.0, 4.5, 0.0, 'muspecs') muspecs_teff_9500_logg_45_p00.fits.gz\n",
      "(9500.0, 5.0, 0.0, 'muspecs') muspecs_teff_9500_logg_50_p00.fits.gz\n",
      "(9750.0, 2.0, 0.0, 'muspecs') muspecs_teff_9750_logg_20_p00.fits.gz\n",
      "(9750.0, 3.0, 0.0, 'muspecs') muspecs_teff_9750_logg_30_p00.fits.gz\n",
      "(9750.0, 3.5, 0.0, 'muspecs') muspecs_teff_9750_logg_35_p00.fits.gz\n",
      "(9750.0, 4.0, 0.0, 'muspecs') muspecs_teff_9750_logg_40_p00.fits.gz\n",
      "(9750.0, 4.5, 0.0, 'muspecs') muspecs_teff_9750_logg_45_p00.fits.gz\n",
      "(9750.0, 5.0, 0.0, 'muspecs') muspecs_teff_9750_logg_50_p00.fits.gz\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "sl.listInventory()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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    "version": 3
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   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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