{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading SNOwGLoBES-Format Model Files\n",
    "\n",
    "Demonstrate how `snewpy` can read files in the tabular `.dat` input format used by `SNOwGLoBES` and plot the data.\n",
    "\n",
    "Note: These files only contain time-integrated fluences, not the full information that is available in all other models. Accordingly, much of the functionality of `snewpy` is not available for these files.\n",
    "\n",
    "At the moment the class only reads the NoOsc files inside the tarfiles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from snewpy.models.ccsn import SNOwGLoBES\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "mpl.rc('font', size=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Functions\n",
    "\n",
    "Two functions are provided:\n",
    "1. One to plot the spectrum (number flux, actually fluence) at a given time.\n",
    "1. One to plot the fluence in 2D vs. energy and time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_spectrum(snmodel, time=0.):\n",
    "    \"\"\"Plot spectrum (count/cm2) from SNOwGLoBES model at a given time.\n",
    "    \"\"\"\n",
    "    fig, axes = plt.subplots(2,3, figsize=(14,8), sharex=True, sharey=True,\n",
    "                             gridspec_kw={'wspace':0, 'hspace':0})\n",
    "\n",
    "    for ax, (flavor, fl) in zip(axes.flatten(), snmodel.get_fluence(time).items()): \n",
    "        ax.plot(snmodel.energy, fl, label=flavor)\n",
    "        ax.legend()\n",
    "        ax.grid(ls=':')\n",
    "\n",
    "    axes[0,0].set(ylabel='fluence [cm$^{-2}$ (0.2 MeV)$^{-1}$]')\n",
    "    axes[1,0].set(xlabel='energy [MeV]', xlim=(-0.5,10.5))\n",
    "    fig.tight_layout()\n",
    "    return fig\n",
    "\n",
    "def plot_fluence(snmodel, log=False):\n",
    "    \"\"\"Plot the fluence (count/cm2) vs energy and time.\n",
    "    \"\"\"\n",
    "    fig, axes = plt.subplots(2,3, figsize=(14,8), sharex=True, sharey=True,\n",
    "                             gridspec_kw={'wspace':0, 'hspace':0})\n",
    "\n",
    "    if log:\n",
    "        norm = mpl.colors.LogNorm(vmin=1., vmax=snmodel.fmax)\n",
    "    else:\n",
    "        norm = mpl.colors.Normalize(vmin=0., vmax=snmodel.fmax)\n",
    "        \n",
    "    for ax, (flavor, fl) in zip(axes.flatten(), snmodel.flux.items()): \n",
    "        im = ax.imshow(fl, extent=[snmodel.time[0], snmodel.time[-1], snmodel.energy[0], snmodel.energy[-1]],\n",
    "                       origin='lower', cmap='Blues', norm=norm,\n",
    "                       aspect='auto')\n",
    "        ax.text(0.8,0.9, flavor, fontsize=12, transform=ax.transAxes)\n",
    "        ax.grid(ls=':')\n",
    "\n",
    "    axes[0,0].set(xlim=(snmodel.time[0], snmodel.time[-1]),\n",
    "                  ylim=(0,10), ylabel='energy [MeV]')\n",
    "    axes[1,0].set(xlabel='time [s]')\n",
    "\n",
    "    fig.tight_layout()\n",
    "    fig.subplots_adjust(right=0.8)\n",
    "    cb_ax = fig.add_axes([0.82, 0.1, 0.02, 0.85])\n",
    "    cb = fig.colorbar(im, cax=cb_ax)\n",
    "    cb.set_label('fluence [cm$^{-2}$ (0.2 MeV)$^{-1}$]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PISN Models\n",
    "\n",
    "Plot the spectrum at $t=0$ and the total fluence for some of the PISN models.\n",
    "\n",
    "### 150$M_{\\odot}$ Progenitor, Helm EOS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**May 2026: the following cells are BROKEN and need to be fixed in a new PR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn1 = SNOwGLoBES('../../models/PISN/PISN_150Msun_EOS=Helm_NeutrinoFlux.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn1, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn1, time=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 150$M_\\odot$ Progenitor, SFHo EOS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn2 = SNOwGLoBES('../../models/PISN/PISN_150Msun_EOS=SFHo_NeutrinoFlux.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn2, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn2, time=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 250$M_\\odot$ Progenitor, Helm EOS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn3 = SNOwGLoBES('../../models/PISN/PISN_250Msun_EOS=Helm_NeutrinoFlux.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn3, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn3, time=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 250$M_\\odot$ Progenitor, SFHo EOS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn4 = SNOwGLoBES('../../models/PISN/PISN_250Msun_EOS=SFHo_NeutrinoFlux.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn4, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn4, time=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Type Ia Models\n",
    "\n",
    "### GCD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn5 = SNOwGLoBES('../../models/Type_Ia/GCD_NeutrinoFlux.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn5, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn5, time=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DDT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn6 = SNOwGLoBES('../../models/Type_Ia/DDT_NeutrinoFlux.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn6, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn6, time=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nakazato CCSN Model\n",
    "\n",
    "Load the Nakazato CCSN model written to SNOwGLoBES format using the `generate_*` functions in `snewpy.snowglobes`.\n",
    "\n",
    "Note that the Nakazato SNOwGLoBES tarball is not uploaded to GitHub. If you want to repeat this, generate it yourself the converter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sn7 = SNOwGLoBES('../../models/Nakazato_2013/nakazato-LS220-BH-z0.004-s30.0.SNOformat.tar.bz2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_fluence(sn7, log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fig = plot_spectrum(sn7, time=0)"
   ]
  }
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