docs/quickstart/quickstart.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# STARDIS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Necessary Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-01-12T00:13:43.539653Z",
     "start_time": "2022-01-12T00:13:40.679189Z"
    }
   },
   "outputs": [
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      "text/plain": [
       "Iterations:          0/? [00:00<?, ?it/s]"
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     "metadata": {},
     "output_type": "display_data"
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       "Packets:             0/? [00:00<?, ?it/s]"
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from tardis.io.atom_data.util import download_atom_data\n",
    "\n",
    "from stardis.base import run_stardis\n",
    "\n",
    "from astropy import units as u, constants as const"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download Atomic Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "download_atom_data('kurucz_cd23_chianti_H_He')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The STARDIS Configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "STARDIS uses [YAML](https://yaml.org/) files for the configuration. The configuration file called `stardis_example.yml` used here can be found\n",
    "[here](https://github.com/tardis-sn/stardis/tree/main/docs/quickstart),\n",
    "along with any other files from this Quickstart. Below, we present an\n",
    "example for instructions for customizing the configuration for your\n",
    "needs.\n",
    "\n",
    "``` yaml\n",
    "stardis_config_version: 1.0\n",
    "atom_data: <filepath to atomic data file>\n",
    "model:\n",
    "    type: marcs # more options will be available in the future\n",
    "    fname: <filepath to MARCS model file>\n",
    "    final_atomic_number: <atomic number of largest element considered> # may be up to 30\n",
    "opacity:\n",
    "    file: # reads a bound-free or free-free opacity file, omit if none\n",
    "        <species1>_<either bf for bound-free or ff for free-free>: <filepath to opacity file>\n",
    "        <species2>_<either bf for bound-free or ff for free-free>: <filepath to opacity file>\n",
    "        ...\n",
    "    bf: # uses the hydrogenic approximation for bound-free opacity, omit if none\n",
    "        <species1>: {} # there will eventually be options to include files with gaunt factors or departure coefficients\n",
    "        <species2>: {}\n",
    "        ...\n",
    "    ff: # uses the hydrogenic approximation for free-free opacity, omit if none\n",
    "        <species1>: {} # there will eventually be options to include files with gaunt factors or departure coefficients\n",
    "        <species2>: {}\n",
    "        ...\n",
    "    rayleigh: <list of species considered for rayleigh scattering> # may include H, He, and/or H2, omit or use [] for none\n",
    "    disable_electron_scattering: <True or False>\n",
    "    line: # settings for line interaction opacity, at least one subfield is required\n",
    "        disable: <True or False>\n",
    "        broadening: <list of non-thermal broadening sources considered> # may include radiation, linear_stark, quadratic_stark, and/or van_der_waals, omit or use [] for none\n",
    "        min: <minimum resonance frequency or wavelength of lines considered> # must have units, such as Hz or AA\n",
    "        max: <maximum resonance frequency or wavelength of lines considered> # must have units, such as Hz or AA\n",
    "        broadening_range: <maximum distance in frquency space to the resonant frequency for line broadening to be considered> # necessary for computational efficiency and must have units, 1e13 Hz recommended\n",
    "no_of_thetas: <number of angles to sample for raytracing>\n",
    "```\n",
    "\n",
    "In fields where an atomic species is requested, the species must be in\n",
    "the form `<atomic symbol>_<ionization roman numeral>`. For example,\n",
    "`H_I` for neutral hydrogen, or `Si_III` for twice-ionized silicon.\n",
    "\n",
    "Additionally, in the opacity file section, the following entries are\n",
    "valid:\n",
    "\n",
    "-   `Hminus_bf`\n",
    "-   `Hminus_ff`\n",
    "-   `Heminus_ff`\n",
    "-   `H2minus_ff`\n",
    "-   `H2plus_ff`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Opacity File Format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "STARDIS can read and interpolate continuum opacity cross-section files\n",
    "for bound-free or free-free absorption (technically, for free-free\n",
    "absorption the files would provide the cross-section per electron\n",
    "density). The files must be one of the following formats:\n",
    "\n",
    "``` csv\n",
    "wavelength_1, cross-section_1\n",
    "wavelength_2, cross-section_2\n",
    "wavelength_3, cross-section_3\n",
    "...\n",
    "```\n",
    "\n",
    "or\n",
    "\n",
    "``` csv\n",
    ", temperature_1, temperature_2, temperature_3, ...\n",
    "wavelength_1, cross-section_11, cross-section_12, cross-section_13, ...\n",
    "wavelength_2, cross-section_21, cross-section_22, cross-section_23, ...\n",
    "wavelength_3, cross-section_31, cross-section_32, cross-section_33, ...\n",
    "...\n",
    "```\n",
    "\n",
    "Note the leading comma in the latter format. Temperatures must be in\n",
    "Kelvin, wavelengths in Angstroms, and cross-sections in cm² for\n",
    "bound-free or cm⁵ for free-free (once again because free-free opacity\n",
    "files provide the cross-section per electron density).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Array of Wavelengths and Run STARDIS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main function, ``run_stardis()``, requires as its first argument the name of a configuration file, which will be described below. The second argument is an array of the frequencies or wavelengths for which you are requesting the flux density, times an appropriate astropy quantity (such as Hertz or Angstroms). Note that this must be an array times a quantity, **not** an array of astropy quantities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tracing_lambdas = np.mgrid[6540:6590:.01]* u.Angstrom\n",
    "\n",
    "sim = run_stardis('stardis_example.yml', tracing_lambdas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot spectra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(sim.lambdas, sim.spectrum_lambda)\n",
    "\n",
    "plt.xlim((6540,6590))\n",
    "plt.title(\"STARDIS Solar Spectrum\")\n",
    "plt.xlabel(\"Wavelength [$\\AA$]\")\n",
    "plt.ylabel(\"Flux density [erg/s/cm$^2$/$\\AA$]\")\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
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