{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysing Spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tardis.visualization import plot_util as pu\n",
    "from astropy import units as u"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Every simulation run requires [atomic data](io/configuration/components/atomic/atomic_data.rst) and a [configuration file](io/configuration/index.rst). \n",
    "\n",
    "## Atomic Data\n",
    "\n",
    "We recommend using the [kurucz_cd23_chianti_H_He.h5](https://github.com/tardis-sn/tardis-regression-data/raw/main/atom_data/kurucz_cd23_chianti_H_He.h5) dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tardis.io.atom_data import download_atom_data\n",
    "\n",
    "# We download the atomic data needed to run the simulation\n",
    "download_atom_data(\"kurucz_cd23_chianti_H_He\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also obtain a copy of the atomic data from the [tardis-regression-data](https://github.com/tardis-sn/tardis-regression-data/tree/main/atom_data) repository.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example Configuration File\n",
    "\n",
    "The configuration file [tardis_example.yml](https://github.com/tardis-sn/tardis/tree/master/docs/tardis_example.yml) is used throughout this Quickstart.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!wget -q -nc https://raw.githubusercontent.com/tardis-sn/tardis/master/docs/tardis_example.yml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!cat tardis_example.yml"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the Simulation\n",
    "\n",
    "To run the simulation, import the `run_tardis` function and create the `sim` object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note:**\n",
    "\n",
    "Get more information about the [progress bars](io/output/progress_bars.rst), [logging configuration](io/optional/tutorial_logging_configuration.ipynb), and [convergence plots](io/visualization/tutorial_convergence_plot.ipynb).\n",
    "\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tardis import run_tardis\n",
    "\n",
    "sim = run_tardis(\n",
    "    \"tardis_example.yml\",\n",
    "    log_level=\"ERROR\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HDF\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TARDIS can save simulation data to HDF files for later analysis. The code below shows how to load a simulation from an HDF file. This is useful when you want to analyze simulation results without re-running the simulation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import astropy.units as u\n",
    "# import pandas as pd\n",
    "\n",
    "# hdf_fpath = \"add_file_path_here\"\n",
    "# with pd.HDFStore(hdf_fpath, \"r\") as hdf:\n",
    "#     sim = u.Quantity(hdf[\"/simulation\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate integrated spectrum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note:**\n",
    "\n",
    "It takes about a minute to calculate. Please be patient while it runs.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "spectrum_integrated = sim.spectrum_solver.spectrum_integrated"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the Spectrum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will plot the spectrum using matplotlib and plotly. The plots show the luminosity density as a function of wavelength.\n",
    "\n",
    "- $\\textbf{Wavelength } [\\overset{\\circ}{A}]$: The x-axis represents the wavelength in Angstroms.\n",
    "- $\\textbf{Luminosity density} [erg\\;s^{-1}\\;\\overset{\\circ}{A^{-1}}]$: The y-axis represents the luminosity density in erg per second per Angstrom."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We use Matplotlib to create a static plot of the ***formal integral spectrum*** that was calculated in the previous step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Create a new figure with specified dimensions\n",
    "plt.figure(figsize=(10, 6.5))\n",
    "\n",
    "spectrum_integrated.plot(label=\"Formal integral\")  # Plot spectrum from formal integral solution\n",
    "\n",
    "xlabel = pu.axis_label_in_latex(\"Wavelength\", u.AA)\n",
    "ylabel = pu.axis_label_in_latex(\n",
    "    \"Luminosity density\", u.Unit(\"erg/(s AA)\"), only_text=True\n",
    ")\n",
    "# Set title, labels, and template\n",
    "plt.xlim(500, 9000)\n",
    "plt.title(\"TARDIS example model spectrum\")\n",
    "plt.xlabel(xlabel)\n",
    "plt.ylabel(ylabel)\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotly\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, we use Plotly to create an interactive plot of the ***virtual packet spectrum*** generated by the TARDIS simulation.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "# Create a new figure for plotting the spectrum\n",
    "fig = go.Figure()\n",
    "\n",
    "# Plot the wavelength spectrum\n",
    "fig.add_trace(\n",
    "    go.Scatter(\n",
    "        x=sim.spectrum_solver.spectrum_virtual_packets.wavelength,\n",
    "        y=sim.spectrum_solver.spectrum_virtual_packets.luminosity_density_lambda,\n",
    "        mode=\"lines\",\n",
    "        name=\"Spectrum\"\n",
    "    )\n",
    ")\n",
    "\n",
    "xlabel = pu.axis_label_in_latex(\"Wavelength\", u.AA)\n",
    "ylabel = pu.axis_label_in_latex(\n",
    "    \"Luminosity density\", u.Unit(\"erg/(s AA)\"), only_text=True\n",
    ")\n",
    "# Set title, labels, and template\n",
    "fig.update_layout(\n",
    "    title=\"TARDIS example model spectrum\",\n",
    "    xaxis_title=xlabel,\n",
    "    yaxis_title=ylabel,\n",
    "    xaxis_range=[500, 9000],\n",
    "    showlegend=True,\n",
    "    template=\"plotly_white\"\n",
    ")\n",
    "\n",
    "# Display the plot\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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