{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Possible STARDIS Outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Necessary Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from stardis.base import run_stardis\n",
    "\n",
    "from astropy import units as u, constants as const"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting Result Options"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "STARDIS simulations contain a variety of information, and depending on your needs you can have different parts of a simulation returned.\n",
    "\n",
    "There are three parts of the simulation you can choose to return:\n",
    "\n",
    "- Stellar_Model\n",
    "- Stellar_Plasma\n",
    "- Stellar_Radiation_Field\n",
    "\n",
    "Regardless of which are set to return, the simulation will always produce the stellar spectrum (such as the one displayed in the quickstart notebook)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To access these different parts of the model, you need to declare what you want to be returned in your configuration YAML file. This notebook uses a YAML file named `stardis_outputs_config.yml` which has the following lines:\n",
    "\n",
    "``` yaml\n",
    "        ...\n",
    "no_of_thetas: 20\n",
    "result_options: # <----- \n",
    "    return_model: True # <----- defaults to False\n",
    "    return_plasma: True # <----- defaults to False\n",
    "    return_radiation_field: True # <----- defaults to True\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating Example Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: 'erg/cm2/s' contains multiple slashes, which is discouraged by the FITS standard [astropy.units.format.generic]\n"
     ]
    }
   ],
   "source": [
    "tracing_lambdas = np.mgrid[6540:6590:.01]* u.Angstrom\n",
    "\n",
    "sim = run_stardis('stardis_outputs_config.yml', tracing_lambdas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stellar Model\n",
    "\n",
    "The stellar model is based on the information derived from the MARCS file for your star, and you can access it to verify STARDIS correctly processed the file. In the below example we are using the stellar model to look at simulated depths in our star in centimeters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$[-12340000,~-10630000,~-9171000,~-7926000,~-6851000,~-5907000,~-5478000,~-5063000,~-4651000,~-4229000,~-3778000,~-3266000,~-2648000,~-1898000,~-1015000,~-0,~1146000,~2411000,~3776000,~5215000,~6700000,~8210000,~9728000,~11240000,~12750000,~14250000,~15730000,~17210000,~18680000,~20130000,~21580000,~23020000,~24450000,~25880000,~27300000,~28710000,~30120000,~31520000,~32920000,~34310000,~35690000,~37070000,~38440000,~39810000,~41180000,~42530000,~45300000,~48050000,~50780000,~53490000,~56180000,~58840000,~61490000,~64110000,~66720000,~69310000] \\; \\mathrm{cm}$"
      ],
      "text/plain": [
       "<Quantity [-12340000., -10630000.,  -9171000.,  -7926000.,  -6851000.,\n",
       "            -5907000.,  -5478000.,  -5063000.,  -4651000.,  -4229000.,\n",
       "            -3778000.,  -3266000.,  -2648000.,  -1898000.,  -1015000.,\n",
       "                  -0.,   1146000.,   2411000.,   3776000.,   5215000.,\n",
       "             6700000.,   8210000.,   9728000.,  11240000.,  12750000.,\n",
       "            14250000.,  15730000.,  17210000.,  18680000.,  20130000.,\n",
       "            21580000.,  23020000.,  24450000.,  25880000.,  27300000.,\n",
       "            28710000.,  30120000.,  31520000.,  32920000.,  34310000.,\n",
       "            35690000.,  37070000.,  38440000.,  39810000.,  41180000.,\n",
       "            42530000.,  45300000.,  48050000.,  50780000.,  53490000.,\n",
       "            56180000.,  58840000.,  61490000.,  64110000.,  66720000.,\n",
       "            69310000.] cm>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.stellar_model.geometry.r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stellar Plasma\n",
    "\n",
    "The stellar plasma is generated from the stellar model, and in it we can find information about the makeup and qualities of the plasma in our simulated star. Here is an example of us looking at the density of ions at different depths within our star. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>atomic_number</th>\n",
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       "      <td>1.295592e+17</td>\n",
       "      <td>1.277547e+17</td>\n",
       "      <td>1.267249e+17</td>\n",
       "      <td>1.264809e+17</td>\n",
       "      <td>1.267312e+17</td>\n",
       "      <td>1.272488e+17</td>\n",
       "      <td>1.280748e+17</td>\n",
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       "      <td>...</td>\n",
       "      <td>3.966417e+15</td>\n",
       "      <td>3.116191e+15</td>\n",
       "      <td>2.447204e+15</td>\n",
       "      <td>1.920907e+15</td>\n",
       "      <td>1.507041e+15</td>\n",
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       "      <td>7.247400e+14</td>\n",
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       "      <td>4.413455e+14</td>\n",
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       "      <td>5.006329e+15</td>\n",
       "      <td>3.898646e+15</td>\n",
       "      <td>2.999333e+15</td>\n",
       "      <td>2.260427e+15</td>\n",
       "      <td>1.644337e+15</td>\n",
       "      <td>1.367509e+15</td>\n",
       "      <td>1.110215e+15</td>\n",
       "      <td>8.708180e+14</td>\n",
       "      <td>6.501580e+14</td>\n",
       "      <td>...</td>\n",
       "      <td>3.478357e+09</td>\n",
       "      <td>2.392115e+09</td>\n",
       "      <td>1.629784e+09</td>\n",
       "      <td>1.100527e+09</td>\n",
       "      <td>7.368918e+08</td>\n",
       "      <td>4.895196e+08</td>\n",
       "      <td>3.230976e+08</td>\n",
       "      <td>2.125878e+08</td>\n",
       "      <td>1.401980e+08</td>\n",
       "      <td>9.814634e+07</td>\n",
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       "      <td>1.167746e+16</td>\n",
       "      <td>1.135911e+16</td>\n",
       "      <td>1.112897e+16</td>\n",
       "      <td>1.097843e+16</td>\n",
       "      <td>1.090522e+16</td>\n",
       "      <td>1.090297e+16</td>\n",
       "      <td>1.092512e+16</td>\n",
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       "      <td>3.375972e+14</td>\n",
       "      <td>2.652311e+14</td>\n",
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       "      <td>1.634958e+14</td>\n",
       "      <td>1.282700e+14</td>\n",
       "      <td>1.005715e+14</td>\n",
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       "      <td>6.168539e+13</td>\n",
       "      <td>4.823782e+13</td>\n",
       "      <td>3.756461e+13</td>\n",
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       "      <td>3.353671e+09</td>\n",
       "      <td>1.817801e+09</td>\n",
       "      <td>9.521732e+08</td>\n",
       "      <td>4.719585e+08</td>\n",
       "      <td>2.133037e+08</td>\n",
       "      <td>1.343820e+08</td>\n",
       "      <td>7.961535e+07</td>\n",
       "      <td>4.322331e+07</td>\n",
       "      <td>2.071727e+07</td>\n",
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       "      <td>4.557768e-04</td>\n",
       "      <td>2.346949e-04</td>\n",
       "      <td>1.187835e-04</td>\n",
       "      <td>5.913624e-05</td>\n",
       "      <td>2.898587e-05</td>\n",
       "      <td>1.400182e-05</td>\n",
       "      <td>6.683730e-06</td>\n",
       "      <td>3.172236e-06</td>\n",
       "      <td>1.512106e-06</td>\n",
       "      <td>8.051582e-07</td>\n",
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       "      <td>8.158929e-16</td>\n",
       "      <td>6.613797e-17</td>\n",
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       "      <td>7.112620e-19</td>\n",
       "      <td>1.065274e-19</td>\n",
       "      <td>1.157150e-20</td>\n",
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       "      <td>...</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
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       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>495 rows × 56 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    0             1             2   \\\n",
       "atomic_number ion_number                                             \n",
       "1             0           1.357488e+17  1.321919e+17  1.295592e+17   \n",
       "              1           6.385172e+15  5.006329e+15  3.898646e+15   \n",
       "2             0           1.209755e+16  1.167746e+16  1.135911e+16   \n",
       "              1           6.058951e+09  3.353671e+09  1.817801e+09   \n",
       "              2           5.581645e-13  7.050644e-14  8.127889e-15   \n",
       "...                                ...           ...           ...   \n",
       "30            26          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              27          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              28          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              29          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              30          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "\n",
       "                                    3             4             5   \\\n",
       "atomic_number ion_number                                             \n",
       "1             0           1.277547e+17  1.267249e+17  1.264809e+17   \n",
       "              1           2.999333e+15  2.260427e+15  1.644337e+15   \n",
       "2             0           1.112897e+16  1.097843e+16  1.090522e+16   \n",
       "              1           9.521732e+08  4.719585e+08  2.133037e+08   \n",
       "              2           8.158929e-16  6.613797e-17  3.784828e-18   \n",
       "...                                ...           ...           ...   \n",
       "30            26          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              27          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              28          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              29          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              30          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "\n",
       "                                    6             7             8   \\\n",
       "atomic_number ion_number                                             \n",
       "1             0           1.267312e+17  1.272488e+17  1.280748e+17   \n",
       "              1           1.367509e+15  1.110215e+15  8.708180e+14   \n",
       "2             0           1.090297e+16  1.092512e+16  1.097505e+16   \n",
       "              1           1.343820e+08  7.961535e+07  4.322331e+07   \n",
       "              2           7.112620e-19  1.065274e-19  1.157150e-20   \n",
       "...                                ...           ...           ...   \n",
       "30            26          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              27          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              28          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              29          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              30          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "\n",
       "                                    9   ...            46            47  \\\n",
       "atomic_number ion_number                ...                               \n",
       "1             0           1.292835e+17  ...  3.966417e+15  3.116191e+15   \n",
       "              1           6.501580e+14  ...  3.478357e+09  2.392115e+09   \n",
       "2             0           1.105915e+16  ...  3.375972e+14  2.652311e+14   \n",
       "              1           2.071727e+07  ...  4.557768e-04  2.346949e-04   \n",
       "              2           0.000000e+00  ...  0.000000e+00  0.000000e+00   \n",
       "...                                ...  ...           ...           ...   \n",
       "30            26          0.000000e+00  ...  0.000000e+00  0.000000e+00   \n",
       "              27          0.000000e+00  ...  0.000000e+00  0.000000e+00   \n",
       "              28          0.000000e+00  ...  0.000000e+00  0.000000e+00   \n",
       "              29          0.000000e+00  ...  0.000000e+00  0.000000e+00   \n",
       "              30          0.000000e+00  ...  0.000000e+00  0.000000e+00   \n",
       "\n",
       "                                    48            49            50  \\\n",
       "atomic_number ion_number                                             \n",
       "1             0           2.447204e+15  1.920907e+15  1.507041e+15   \n",
       "              1           1.629784e+09  1.100527e+09  7.368918e+08   \n",
       "2             0           2.082910e+14  1.634958e+14  1.282700e+14   \n",
       "              1           1.187835e-04  5.913624e-05  2.898587e-05   \n",
       "              2           0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "...                                ...           ...           ...   \n",
       "30            26          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              27          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              28          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              29          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              30          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "\n",
       "                                    51            52            53  \\\n",
       "atomic_number ion_number                                             \n",
       "1             0           1.181611e+15  9.258287e+14  7.247400e+14   \n",
       "              1           4.895196e+08  3.230976e+08  2.125878e+08   \n",
       "2             0           1.005715e+14  7.880083e+13  6.168539e+13   \n",
       "              1           1.400182e-05  6.683730e-06  3.172236e-06   \n",
       "              2           0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "...                                ...           ...           ...   \n",
       "30            26          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              27          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              28          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              29          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "              30          0.000000e+00  0.000000e+00  0.000000e+00   \n",
       "\n",
       "                                    54            55  \n",
       "atomic_number ion_number                              \n",
       "1             0           5.667448e+14  4.413455e+14  \n",
       "              1           1.401980e+08  9.814634e+07  \n",
       "2             0           4.823782e+13  3.756461e+13  \n",
       "              1           1.512106e-06  8.051582e-07  \n",
       "              2           0.000000e+00  0.000000e+00  \n",
       "...                                ...           ...  \n",
       "30            26          0.000000e+00  0.000000e+00  \n",
       "              27          0.000000e+00  0.000000e+00  \n",
       "              28          0.000000e+00  0.000000e+00  \n",
       "              29          0.000000e+00  0.000000e+00  \n",
       "              30          0.000000e+00  0.000000e+00  \n",
       "\n",
       "[495 rows x 56 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.stellar_plasma.ion_number_density"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stellar Radiation Field\n",
    "\n",
    "The stellar radiation field contains information on how light interacts with your star's atmosphere in the simulation. The example below demonstrates `sim.stellar_radiation_field.opacities.opacities_dict` which contains a dictionary of each source of opacity and how much it contributes to the overall opacity at each wavelength at each depth.\n",
    "\n",
    "\n",
    "This is a breakdown of how `opacities_dict` stores this information\n",
    "``` python\n",
    "opacities_dict['opacity_source'][depth_point_index, wavelength_index]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.19396613e-04, 1.19494544e-04, 1.19592622e-04, ...,\n",
       "        1.14524418e-04, 1.14429656e-04, 1.14335151e-04],\n",
       "       [7.09791352e-05, 7.10375408e-05, 7.10960379e-05, ...,\n",
       "        6.80940449e-05, 6.80365774e-05, 6.79793243e-05],\n",
       "       [4.17916048e-05, 4.18262293e-05, 4.18609110e-05, ...,\n",
       "        4.00929725e-05, 4.00584543e-05, 4.00241044e-05],\n",
       "       ...,\n",
       "       [6.53995312e-17, 6.55267275e-17, 6.56543559e-17, ...,\n",
       "        5.56712932e-13, 5.44563628e-13, 4.43041798e-13],\n",
       "       [2.54061313e-17, 2.54694767e-17, 2.55330590e-17, ...,\n",
       "        3.73815457e-13, 3.65601935e-13, 2.97017936e-13],\n",
       "       [1.43116146e-17, 1.43472978e-17, 1.43831146e-17, ...,\n",
       "        2.47687524e-13, 2.42214851e-13, 1.96544874e-13]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alpha_lines = sim.stellar_radiation_field.opacities.opacities_dict['alpha_line_at_nu']\n",
    "\n",
    "for depth_point in range(1, len(alpha_lines), 12):\n",
    "\n",
    "    plt.plot(sim.lambdas, alpha_lines[depth_point], label=f'layer {depth_point}')\n",
    "plt.xlabel('Wavelength (Angstrom)')\n",
    "plt.ylabel('Opacity')\n",
    "plt.title('Alpha Line Opacity at different depths')\n",
    "plt.legend()\n",
    "plt.yscale('log')\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "stardis",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}