{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b41a6dcf",
   "metadata": {},
   "source": [
    "# Heating and Cooling in UCLCHEM\n",
    "\n",
    "This notebook demonstheating how to use UCLCHEM with heating and cooling mechanisms enabled. UCLCHEM includes a comprehensive set of heating and cooling processes that can significantly affect the temperature evolution and chemistry in astrophysical environments.\n",
    "\n",
    "## Overview\n",
    "\n",
    "UCLCHEM can track gas temperature changes due to:\n",
    "\n",
    "**Heating processes:**\n",
    "- Photoelectric heating from PAHs and dust grains\n",
    "- H₂ formation heating\n",
    "- H₂ photodissociation heating\n",
    "- Cosmic ray heating\n",
    "- Chemical reaction enthalpy (optional)\n",
    "- X-ray heating\n",
    "- Turbulent heating\n",
    "- And more...\n",
    "\n",
    "**Cooling processes:**\n",
    "- Line cooling (CO, H₂O, OH, etc.)\n",
    "- Continuum cooling from dust\n",
    "- Atomic fine structure cooling (C⁺, O, etc.)\n",
    "- Recombination cooling\n",
    "- And more...\n",
    "\n",
    "By default, heating is enabled (`heatingFlag=True`), but you can turn it off or customize which processes are included."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9ef70f78",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:48:45.736611Z",
     "iopub.status.busy": "2026-01-27T12:48:45.736132Z",
     "iopub.status.idle": "2026-01-27T12:48:47.058216Z",
     "shell.execute_reply": "2026-01-27T12:48:47.057284Z"
    }
   },
   "outputs": [],
   "source": [
    "import uclchem\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47341628",
   "metadata": {},
   "source": [
    "## Example 1: Basic Model with Heating Enabled\n",
    "\n",
    "Let's start with a simple cloud model with heating and cooling enabled (the default behavior). We'll model a molecular cloud core at constant density."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7de004d1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:48:47.060393Z",
     "iopub.status.busy": "2026-01-27T12:48:47.060069Z",
     "iopub.status.idle": "2026-01-27T12:49:50.105536Z",
     "shell.execute_reply": "2026-01-27T12:49:50.104688Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model completed with flag: -1\n",
      "Error: Model failed to complete\n"
     ]
    }
   ],
   "source": [
    "# Define parameters for a molecular cloud with heating enabled\n",
    "param_dict_heating = {\n",
    "    \"initialDens\": 1e4,  # Initial density (cm^-3)\n",
    "    \"initialTemp\": 10.0,  # Initial temperature (K)\n",
    "    \"finalTime\": 1.0e6,  # Final time (years)\n",
    "    \"baseAv\": 10.0,  # Visual extinction\n",
    "    \"rout\": 0.1,  # Outer radius (pc)\n",
    "    \"freefall\": False,  # Keep constant density\n",
    "    \"heatingFlag\": True,  # Enable heating (default)\n",
    "}\n",
    "\n",
    "# Run the model using the Cloud class\n",
    "cloud = uclchem.model.Cloud(param_dict=param_dict_heating)\n",
    "\n",
    "# Extract data from the model object\n",
    "physics, abundances = cloud.get_dataframes(joined=False)\n",
    "_, _, rates = cloud.get_dataframes(joined=False, with_rates=True)\n",
    "_, _, heating = cloud.get_dataframes(joined=False, with_heating=True)\n",
    "start_abund = cloud.next_starting_chemistry_array\n",
    "flag = 0 if cloud.has_attr(\"_data\") else -1\n",
    "\n",
    "print(f\"Model completed with flag: {flag}\")\n",
    "if flag < 0:\n",
    "    print(f\"Error: Model failed to complete\")\n",
    "else:\n",
    "    print(\"Success! Model completed.\")\n",
    "    print(\n",
    "        f\"\\nTemperature range: {physics['gasTemp'].min():.2f} - {physics['gasTemp'].max():.2f} K\"\n",
    "    )\n",
    "    print(\n",
    "        f\"Density range: {physics['Density'].min():.2e} - {physics['Density'].max():.2e} cm^-3\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0bd075b",
   "metadata": {},
   "source": [
    "### Visualizing Temperature Evolution\n",
    "\n",
    "The `physics` DataFrame contains physical properties including gas temperature. Let's plot how temperature evolves over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8697e3f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:50.107407Z",
     "iopub.status.busy": "2026-01-27T12:49:50.107144Z",
     "iopub.status.idle": "2026-01-27T12:49:50.334465Z",
     "shell.execute_reply": "2026-01-27T12:49:50.333673Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot temperature evolution\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "ax.plot(physics[\"Time\"], physics[\"gasTemp\"], linewidth=2, color=\"darkred\")\n",
    "ax.set_xlabel(\"Time (years)\", fontsize=12)\n",
    "ax.set_ylabel(\"Gas Temperature (K)\", fontsize=12)\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_title(\"Gas Temperature Evolution with Heating/Cooling\", fontsize=14)\n",
    "ax.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b53931e",
   "metadata": {},
   "source": [
    "## Example 2: Comparing Heating On vs Off\n",
    "\n",
    "To see the impact of heating/cooling processes, let's run two models side by side: one with heating enabled and one without."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c01d6c48",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:50.336091Z",
     "iopub.status.busy": "2026-01-27T12:49:50.335916Z",
     "iopub.status.idle": "2026-01-27T12:49:54.016135Z",
     "shell.execute_reply": "2026-01-27T12:49:54.015397Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No heating model completed with flag: -1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Final temperatures:\n",
      "  With heating: 13.10 K\n",
      "  Without heating: 10.00 K\n"
     ]
    }
   ],
   "source": [
    "# Model WITHOUT heating\n",
    "param_dict_no_heating = param_dict_heating.copy()\n",
    "param_dict_no_heating[\"heatingFlag\"] = False\n",
    "\n",
    "cloud_no_heat = uclchem.model.Cloud(param_dict=param_dict_no_heating)\n",
    "\n",
    "# Extract data\n",
    "physics_no_heat, abundances_no_heat = cloud_no_heat.get_dataframes(joined=False)\n",
    "_, _, rates_no_heat = cloud_no_heat.get_dataframes(joined=False, with_rates=True)\n",
    "_, _, heating_no_heat = cloud_no_heat.get_dataframes(joined=False, with_heating=True)\n",
    "flag_no_heat = 0 if cloud_no_heat.has_attr(\"_data\") else -1\n",
    "\n",
    "print(f\"No heating model completed with flag: {flag_no_heat}\")\n",
    "\n",
    "# Compare the two runs\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# Temperature comparison\n",
    "axes[0].plot(physics[\"Time\"], physics[\"gasTemp\"], label=\"Heating ON\", linewidth=2)\n",
    "axes[0].plot(\n",
    "    physics_no_heat[\"Time\"],\n",
    "    physics_no_heat[\"gasTemp\"],\n",
    "    label=\"Heating OFF\",\n",
    "    linewidth=2,\n",
    "    linestyle=\"--\",\n",
    ")\n",
    "axes[0].set_xlabel(\"Time (years)\", fontsize=12)\n",
    "axes[0].set_ylabel(\"Gas Temperature (K)\", fontsize=12)\n",
    "axes[0].set_xscale(\"log\")\n",
    "axes[0].set_title(\"Temperature Evolution\", fontsize=14)\n",
    "axes[0].legend()\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# Compare a key chemical species (CO)\n",
    "axes[1].plot(physics[\"Time\"], abundances[\"H2O\"], label=\"Heating ON\", linewidth=2)\n",
    "axes[1].plot(\n",
    "    physics_no_heat[\"Time\"],\n",
    "    abundances_no_heat[\"H2O\"],\n",
    "    label=\"Heating OFF\",\n",
    "    linewidth=2,\n",
    "    linestyle=\"--\",\n",
    ")\n",
    "axes[1].set_xlabel(\"Time (years)\", fontsize=12)\n",
    "axes[1].set_ylabel(\"H$_2$O Abundance\", fontsize=12)\n",
    "axes[1].set_xscale(\"log\")\n",
    "axes[1].set_yscale(\"log\")\n",
    "axes[1].set_title(\"CO Abundance Evolution\", fontsize=14)\n",
    "axes[1].legend()\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\nFinal temperatures:\")\n",
    "print(f\"  With heating: {physics['gasTemp'].iloc[-1]:.2f} K\")\n",
    "print(f\"  Without heating: {physics_no_heat['gasTemp'].iloc[-1]:.2f} K\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc563c69",
   "metadata": {},
   "source": [
    "## Example 3: Accessing Heating and Cooling Rates\n",
    "\n",
    "UCLCHEM can return detailed heating and cooling rates when you use `return_dataframe=True` with the rates arrays. The `heating` DataFrame includes individual contributions from each heating and cooling process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7e12c4bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:54.017724Z",
     "iopub.status.busy": "2026-01-27T12:49:54.017554Z",
     "iopub.status.idle": "2026-01-27T12:49:54.021836Z",
     "shell.execute_reply": "2026-01-27T12:49:54.021232Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available heating/cooling columns:\n",
      "['Time', 'AtomicLineEmission Cooling', 'H2CollisionallyInduced Cooling', 'Compton Cooling', 'ContinuumEmission Cooling', 'MolecularLine Cooling', 'H Line Cooling', 'C+ Line Cooling', 'O Line Cooling', 'C Line Cooling', 'CO Line Cooling', 'p-H2 Line Cooling', 'o-H2 Line Cooling', 'PhotoelectricBakes Heating', 'PhotoelectricWeingartner Heating', 'H2Formation Heating', 'H2Photodissociation Heating', 'H2FUVPumping Heating', 'CarbonIonization Heating', 'CosmicRay Heating'] ...\n",
      "\n",
      "Found 10 heating processes\n",
      "Found 12 cooling processes\n",
      "\n",
      "Heating processes:\n",
      "  - PhotoelectricBakes Heating\n",
      "  - PhotoelectricWeingartner Heating\n",
      "  - H2Formation Heating\n",
      "  - H2Photodissociation Heating\n",
      "  - H2FUVPumping Heating\n",
      "  - CarbonIonization Heating\n",
      "  - CosmicRay Heating\n",
      "  - Turbulent Heating\n",
      "  - GasGrainCollisions Heating\n",
      "  - Chemical Heating\n"
     ]
    }
   ],
   "source": [
    "# The heating DataFrame contains heating and cooling information\n",
    "print(\"Available heating/cooling columns:\")\n",
    "print(heating.columns.tolist()[:20], \"...\")  # Show first 20 columns\n",
    "\n",
    "# Extract heating and cooling columns\n",
    "heating_cols = [\n",
    "    col for col in heating.columns if \"heating\" in col.lower() and col != \"Time\"\n",
    "]\n",
    "cooling_cols = [col for col in heating.columns if \"cooling\" in col.lower()]\n",
    "\n",
    "print(f\"\\nFound {len(heating_cols)} heating processes\")\n",
    "print(f\"Found {len(cooling_cols)} cooling processes\")\n",
    "\n",
    "# Show the heating processes\n",
    "print(\"\\nHeating processes:\")\n",
    "for col in heating_cols[:10]:  # Show first 10\n",
    "    print(f\"  - {col}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0776d57f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:54.023583Z",
     "iopub.status.busy": "2026-01-27T12:49:54.023421Z",
     "iopub.status.idle": "2026-01-27T12:49:54.083287Z",
     "shell.execute_reply": "2026-01-27T12:49:54.082476Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>AtomicLineEmission Cooling</th>\n",
       "      <th>H2CollisionallyInduced Cooling</th>\n",
       "      <th>Compton Cooling</th>\n",
       "      <th>ContinuumEmission Cooling</th>\n",
       "      <th>MolecularLine Cooling</th>\n",
       "      <th>H Line Cooling</th>\n",
       "      <th>C+ Line Cooling</th>\n",
       "      <th>O Line Cooling</th>\n",
       "      <th>C Line Cooling</th>\n",
       "      <th>...</th>\n",
       "      <th>PhotoelectricBakes Heating</th>\n",
       "      <th>PhotoelectricWeingartner Heating</th>\n",
       "      <th>H2Formation Heating</th>\n",
       "      <th>H2Photodissociation Heating</th>\n",
       "      <th>H2FUVPumping Heating</th>\n",
       "      <th>CarbonIonization Heating</th>\n",
       "      <th>CosmicRay Heating</th>\n",
       "      <th>Turbulent Heating</th>\n",
       "      <th>GasGrainCollisions Heating</th>\n",
       "      <th>Chemical Heating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000e-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.487719e-35</td>\n",
       "      <td>2.985107e-63</td>\n",
       "      <td>1.166008e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.310983e-25</td>\n",
       "      <td>8.348479e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100196e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755034e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.513450e-48</td>\n",
       "      <td>1.041415e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.000000e-06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.487719e-35</td>\n",
       "      <td>2.985107e-63</td>\n",
       "      <td>1.165998e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.310983e-25</td>\n",
       "      <td>8.348376e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100196e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755034e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.515769e-48</td>\n",
       "      <td>3.030519e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.310917e-34</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.000000e-05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.487720e-35</td>\n",
       "      <td>2.985108e-63</td>\n",
       "      <td>1.166017e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.310984e-25</td>\n",
       "      <td>8.348549e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100196e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755034e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.536644e-48</td>\n",
       "      <td>3.030519e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.315356e-33</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.000000e-04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.487720e-35</td>\n",
       "      <td>2.985108e-63</td>\n",
       "      <td>1.166017e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.310997e-25</td>\n",
       "      <td>8.348518e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100196e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755034e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.745404e-48</td>\n",
       "      <td>3.030519e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.315801e-32</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.000000e-03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.487723e-35</td>\n",
       "      <td>2.985113e-63</td>\n",
       "      <td>1.166047e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.311123e-25</td>\n",
       "      <td>8.348392e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100197e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755034e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.833985e-48</td>\n",
       "      <td>3.030519e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.315847e-31</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.000000e-02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.487753e-35</td>\n",
       "      <td>2.985165e-63</td>\n",
       "      <td>1.166447e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.312383e-25</td>\n",
       "      <td>8.348272e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100209e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755033e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.780588e-47</td>\n",
       "      <td>3.030519e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.315871e-30</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.000000e-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.488048e-35</td>\n",
       "      <td>2.985680e-63</td>\n",
       "      <td>1.170624e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.324984e-25</td>\n",
       "      <td>8.348308e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.100331e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755032e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.406090e-46</td>\n",
       "      <td>3.030519e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.316070e-29</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.490966e-35</td>\n",
       "      <td>2.990834e-63</td>\n",
       "      <td>1.212569e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.453174e-25</td>\n",
       "      <td>8.349198e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.101548e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.755022e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.374056e-45</td>\n",
       "      <td>3.030524e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.318054e-28</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.000000e+01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.759661e-35</td>\n",
       "      <td>3.506024e-63</td>\n",
       "      <td>4.150609e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.574924e-24</td>\n",
       "      <td>8.431027e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.219336e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.821641e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.880749e-43</td>\n",
       "      <td>3.031307e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-8.135891e-26</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.055043e-34</td>\n",
       "      <td>1.601465e-62</td>\n",
       "      <td>3.574683e-23</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.009385e-23</td>\n",
       "      <td>9.058431e-25</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.175190e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.492683e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.383387e-42</td>\n",
       "      <td>3.039901e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.244761e-24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.400875e-34</td>\n",
       "      <td>6.085257e-62</td>\n",
       "      <td>1.135321e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.100815e-23</td>\n",
       "      <td>5.470146e-24</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.343722e-34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.138866e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.101764e-42</td>\n",
       "      <td>3.049794e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-3.113675e-24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.757610e-34</td>\n",
       "      <td>1.811043e-61</td>\n",
       "      <td>3.515446e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.358660e-22</td>\n",
       "      <td>4.441004e-23</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.443247e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.695782e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.324994e-43</td>\n",
       "      <td>3.060225e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-5.500991e-24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.105001e-34</td>\n",
       "      <td>4.446628e-61</td>\n",
       "      <td>7.458767e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.532101e-22</td>\n",
       "      <td>1.789472e-22</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.496413e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.163665e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.203232e-43</td>\n",
       "      <td>3.071104e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-8.215717e-24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>5.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.407529e-34</td>\n",
       "      <td>8.920321e-61</td>\n",
       "      <td>1.306477e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.266848e-22</td>\n",
       "      <td>4.213907e-22</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.793595e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.523852e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.333908e-43</td>\n",
       "      <td>3.081609e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.087112e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.661447e-34</td>\n",
       "      <td>1.556181e-60</td>\n",
       "      <td>2.158357e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.067836e-21</td>\n",
       "      <td>8.894247e-22</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.270724e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.803286e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.677252e-43</td>\n",
       "      <td>3.092336e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.338619e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.854768e-34</td>\n",
       "      <td>2.397368e-60</td>\n",
       "      <td>3.159351e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.384716e-21</td>\n",
       "      <td>1.530278e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.769924e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.009663e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.179980e-43</td>\n",
       "      <td>3.103177e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.560455e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.978954e-34</td>\n",
       "      <td>3.301719e-60</td>\n",
       "      <td>4.100755e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.647955e-21</td>\n",
       "      <td>2.169177e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.107446e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.151321e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.800996e-43</td>\n",
       "      <td>3.114127e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.740943e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>9.000000e+02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.044740e-34</td>\n",
       "      <td>4.146650e-60</td>\n",
       "      <td>4.851508e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.848526e-21</td>\n",
       "      <td>2.687133e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.178149e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.242572e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.504575e-43</td>\n",
       "      <td>3.124652e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.878358e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.067780e-34</td>\n",
       "      <td>4.905845e-60</td>\n",
       "      <td>5.435084e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.996990e-21</td>\n",
       "      <td>3.095256e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.001629e-32</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.301227e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.272374e-43</td>\n",
       "      <td>3.135140e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.984741e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.467887e-34</td>\n",
       "      <td>7.783575e-60</td>\n",
       "      <td>7.158947e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.241113e-21</td>\n",
       "      <td>4.432453e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.141973e-32</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.266573e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.011086e-43</td>\n",
       "      <td>3.236002e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.299937e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>3.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.820954e-34</td>\n",
       "      <td>8.009917e-60</td>\n",
       "      <td>6.976409e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.989355e-21</td>\n",
       "      <td>4.428172e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.009954e-32</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.026947e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.493836e-43</td>\n",
       "      <td>3.334018e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.320682e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.372166e-34</td>\n",
       "      <td>8.246560e-60</td>\n",
       "      <td>6.741901e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.737476e-21</td>\n",
       "      <td>4.386935e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.017462e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.808183e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.866661e-43</td>\n",
       "      <td>3.423660e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.341900e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.670979e-35</td>\n",
       "      <td>8.646406e-60</td>\n",
       "      <td>6.471724e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.433629e-21</td>\n",
       "      <td>4.354515e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.879750e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.552151e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.506612e-43</td>\n",
       "      <td>3.530211e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.376720e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>6.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.343128e-35</td>\n",
       "      <td>9.009782e-60</td>\n",
       "      <td>6.282857e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.215406e-21</td>\n",
       "      <td>4.337732e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.097726e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.364602e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.247799e-43</td>\n",
       "      <td>3.608807e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.407316e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>7.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.236676e-35</td>\n",
       "      <td>9.366566e-60</td>\n",
       "      <td>6.087725e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.824387e-22</td>\n",
       "      <td>4.327748e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.206339e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.152176e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.077879e-43</td>\n",
       "      <td>3.696188e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.436455e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>8.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.483939e-35</td>\n",
       "      <td>9.690435e-60</td>\n",
       "      <td>5.873014e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.596486e-22</td>\n",
       "      <td>4.288640e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.245737e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.927502e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.960742e-43</td>\n",
       "      <td>3.787153e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.462183e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>9.000000e+03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.364401e-35</td>\n",
       "      <td>9.907898e-60</td>\n",
       "      <td>5.693158e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.021007e-22</td>\n",
       "      <td>4.232427e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.448098e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.747900e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.877779e-43</td>\n",
       "      <td>3.858925e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.479093e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.453536e-35</td>\n",
       "      <td>1.012338e-59</td>\n",
       "      <td>5.505157e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.645704e-22</td>\n",
       "      <td>4.151556e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.604903e-33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.569542e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.820920e-43</td>\n",
       "      <td>3.929932e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.495572e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.204058e-39</td>\n",
       "      <td>9.139427e-60</td>\n",
       "      <td>3.878880e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.305229e-23</td>\n",
       "      <td>2.890876e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.653598e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.856126e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.441808e-43</td>\n",
       "      <td>4.575572e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.418004e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.484861e-39</td>\n",
       "      <td>6.895284e-60</td>\n",
       "      <td>2.675511e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.759183e-24</td>\n",
       "      <td>1.749193e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.126339e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.638103e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.469465e-43</td>\n",
       "      <td>5.025666e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-2.213788e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>4.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.234427e-39</td>\n",
       "      <td>4.832719e-60</td>\n",
       "      <td>1.832680e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.572568e-24</td>\n",
       "      <td>1.021949e-21</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.998565e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.795690e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.673782e-43</td>\n",
       "      <td>5.338339e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.975061e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>5.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.040223e-39</td>\n",
       "      <td>3.376957e-60</td>\n",
       "      <td>1.272224e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.534769e-24</td>\n",
       "      <td>5.831385e-22</td>\n",
       "      <td>...</td>\n",
       "      <td>-5.067806e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.223275e-21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.890581e-43</td>\n",
       "      <td>5.554960e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.754193e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>6.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.790441e-39</td>\n",
       "      <td>2.149618e-60</td>\n",
       "      <td>8.669902e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.213588e-25</td>\n",
       "      <td>3.233932e-22</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.078814e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.210216e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.060460e-43</td>\n",
       "      <td>5.708481e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.502153e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>7.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.516961e-39</td>\n",
       "      <td>1.373554e-60</td>\n",
       "      <td>5.982514e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.672829e-25</td>\n",
       "      <td>1.734893e-22</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.258633e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.519997e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.211900e-43</td>\n",
       "      <td>5.814173e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.278964e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>8.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.242211e-39</td>\n",
       "      <td>8.855227e-61</td>\n",
       "      <td>4.042568e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.495755e-25</td>\n",
       "      <td>7.468949e-23</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.595692e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.679853e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.297568e-43</td>\n",
       "      <td>5.888991e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-1.084044e-23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>9.000000e+04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.995400e-39</td>\n",
       "      <td>5.752553e-61</td>\n",
       "      <td>2.916422e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.215726e-25</td>\n",
       "      <td>3.747202e-23</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.070925e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.459149e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.314728e-43</td>\n",
       "      <td>5.940267e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.137865e-24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.718757e-39</td>\n",
       "      <td>3.377529e-61</td>\n",
       "      <td>2.064114e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.316863e-25</td>\n",
       "      <td>2.313840e-23</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.561223e-35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.638731e-22</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.280947e-43</td>\n",
       "      <td>5.975159e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-7.304371e-24</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.999688e-40</td>\n",
       "      <td>1.201838e-62</td>\n",
       "      <td>1.454990e-23</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.415171e-27</td>\n",
       "      <td>9.396016e-26</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.845361e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.770210e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.099910e-44</td>\n",
       "      <td>6.052441e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-9.600920e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>3.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.359658e-40</td>\n",
       "      <td>6.879358e-63</td>\n",
       "      <td>6.778661e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.819628e-27</td>\n",
       "      <td>5.280131e-26</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.786389e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.076531e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.438185e-44</td>\n",
       "      <td>6.054109e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-5.000709e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>4.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.659641e-40</td>\n",
       "      <td>6.440042e-63</td>\n",
       "      <td>6.199081e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.091460e-26</td>\n",
       "      <td>3.836571e-26</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.772020e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.561210e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.476274e-44</td>\n",
       "      <td>6.054055e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-4.529640e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>5.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.399018e-40</td>\n",
       "      <td>6.397197e-63</td>\n",
       "      <td>6.057769e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.448423e-26</td>\n",
       "      <td>3.022693e-26</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.857734e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.326686e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.606737e-44</td>\n",
       "      <td>6.053935e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-4.482787e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>6.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.164150e-40</td>\n",
       "      <td>6.878532e-63</td>\n",
       "      <td>5.882461e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.288786e-26</td>\n",
       "      <td>1.689517e-26</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.223251e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.313387e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.519789e-44</td>\n",
       "      <td>6.053515e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-4.999839e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>7.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.191312e-39</td>\n",
       "      <td>7.337220e-63</td>\n",
       "      <td>5.807951e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.361776e-26</td>\n",
       "      <td>1.299020e-26</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.546136e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.351541e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.320935e-44</td>\n",
       "      <td>6.053298e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-5.474699e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>8.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.871863e-39</td>\n",
       "      <td>8.073298e-63</td>\n",
       "      <td>5.716142e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.403425e-26</td>\n",
       "      <td>9.700345e-27</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.188680e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.418687e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.124983e-44</td>\n",
       "      <td>6.053076e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-6.204216e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>9.000000e+05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.665854e-39</td>\n",
       "      <td>8.603579e-63</td>\n",
       "      <td>5.637955e-24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.404294e-26</td>\n",
       "      <td>8.219155e-27</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.779656e-36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.467853e-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.035242e-44</td>\n",
       "      <td>6.052969e-24</td>\n",
       "      <td>7.000000e-40</td>\n",
       "      <td>-6.707517e-25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Time  AtomicLineEmission Cooling  H2CollisionallyInduced Cooling  \\\n",
       "0   1.000000e-07                         0.0                             0.0   \n",
       "1   1.000000e-06                         0.0                             0.0   \n",
       "2   1.000000e-05                         0.0                             0.0   \n",
       "3   1.000000e-04                         0.0                             0.0   \n",
       "4   1.000000e-03                         0.0                             0.0   \n",
       "5   1.000000e-02                         0.0                             0.0   \n",
       "6   1.000000e-01                         0.0                             0.0   \n",
       "7   1.000000e+00                         0.0                             0.0   \n",
       "8   1.000000e+01                         0.0                             0.0   \n",
       "9   1.000000e+02                         0.0                             0.0   \n",
       "10  2.000000e+02                         0.0                             0.0   \n",
       "11  3.000000e+02                         0.0                             0.0   \n",
       "12  4.000000e+02                         0.0                             0.0   \n",
       "13  5.000000e+02                         0.0                             0.0   \n",
       "14  6.000000e+02                         0.0                             0.0   \n",
       "15  7.000000e+02                         0.0                             0.0   \n",
       "16  8.000000e+02                         0.0                             0.0   \n",
       "17  9.000000e+02                         0.0                             0.0   \n",
       "18  1.000000e+03                         0.0                             0.0   \n",
       "19  2.000000e+03                         0.0                             0.0   \n",
       "20  3.000000e+03                         0.0                             0.0   \n",
       "21  4.000000e+03                         0.0                             0.0   \n",
       "22  5.000000e+03                         0.0                             0.0   \n",
       "23  6.000000e+03                         0.0                             0.0   \n",
       "24  7.000000e+03                         0.0                             0.0   \n",
       "25  8.000000e+03                         0.0                             0.0   \n",
       "26  9.000000e+03                         0.0                             0.0   \n",
       "27  1.000000e+04                         0.0                             0.0   \n",
       "28  2.000000e+04                         0.0                             0.0   \n",
       "29  3.000000e+04                         0.0                             0.0   \n",
       "30  4.000000e+04                         0.0                             0.0   \n",
       "31  5.000000e+04                         0.0                             0.0   \n",
       "32  6.000000e+04                         0.0                             0.0   \n",
       "33  7.000000e+04                         0.0                             0.0   \n",
       "34  8.000000e+04                         0.0                             0.0   \n",
       "35  9.000000e+04                         0.0                             0.0   \n",
       "36  1.000000e+05                         0.0                             0.0   \n",
       "37  2.000000e+05                         0.0                             0.0   \n",
       "38  3.000000e+05                         0.0                             0.0   \n",
       "39  4.000000e+05                         0.0                             0.0   \n",
       "40  5.000000e+05                         0.0                             0.0   \n",
       "41  6.000000e+05                         0.0                             0.0   \n",
       "42  7.000000e+05                         0.0                             0.0   \n",
       "43  8.000000e+05                         0.0                             0.0   \n",
       "44  9.000000e+05                         0.0                             0.0   \n",
       "\n",
       "    Compton Cooling  ContinuumEmission Cooling  MolecularLine Cooling  \\\n",
       "0      7.487719e-35               2.985107e-63           1.166008e-24   \n",
       "1      7.487719e-35               2.985107e-63           1.165998e-24   \n",
       "2      7.487720e-35               2.985108e-63           1.166017e-24   \n",
       "3      7.487720e-35               2.985108e-63           1.166017e-24   \n",
       "4      7.487723e-35               2.985113e-63           1.166047e-24   \n",
       "5      7.487753e-35               2.985165e-63           1.166447e-24   \n",
       "6      7.488048e-35               2.985680e-63           1.170624e-24   \n",
       "7      7.490966e-35               2.990834e-63           1.212569e-24   \n",
       "8      7.759661e-35               3.506024e-63           4.150609e-24   \n",
       "9      1.055043e-34               1.601465e-62           3.574683e-23   \n",
       "10     1.400875e-34               6.085257e-62           1.135321e-22   \n",
       "11     1.757610e-34               1.811043e-61           3.515446e-22   \n",
       "12     2.105001e-34               4.446628e-61           7.458767e-22   \n",
       "13     2.407529e-34               8.920321e-61           1.306477e-21   \n",
       "14     2.661447e-34               1.556181e-60           2.158357e-21   \n",
       "15     2.854768e-34               2.397368e-60           3.159351e-21   \n",
       "16     2.978954e-34               3.301719e-60           4.100755e-21   \n",
       "17     3.044740e-34               4.146650e-60           4.851508e-21   \n",
       "18     3.067780e-34               4.905845e-60           5.435084e-21   \n",
       "19     2.467887e-34               7.783575e-60           7.158947e-21   \n",
       "20     1.820954e-34               8.009917e-60           6.976409e-21   \n",
       "21     1.372166e-34               8.246560e-60           6.741901e-21   \n",
       "22     9.670979e-35               8.646406e-60           6.471724e-21   \n",
       "23     7.343128e-35               9.009782e-60           6.282857e-21   \n",
       "24     5.236676e-35               9.366566e-60           6.087725e-21   \n",
       "25     3.483939e-35               9.690435e-60           5.873014e-21   \n",
       "26     2.364401e-35               9.907898e-60           5.693158e-21   \n",
       "27     1.453536e-35               1.012338e-59           5.505157e-21   \n",
       "28     4.204058e-39               9.139427e-60           3.878880e-21   \n",
       "29     3.484861e-39               6.895284e-60           2.675511e-21   \n",
       "30     3.234427e-39               4.832719e-60           1.832680e-21   \n",
       "31     3.040223e-39               3.376957e-60           1.272224e-21   \n",
       "32     2.790441e-39               2.149618e-60           8.669902e-22   \n",
       "33     2.516961e-39               1.373554e-60           5.982514e-22   \n",
       "34     2.242211e-39               8.855227e-61           4.042568e-22   \n",
       "35     1.995400e-39               5.752553e-61           2.916422e-22   \n",
       "36     1.718757e-39               3.377529e-61           2.064114e-22   \n",
       "37     8.999688e-40               1.201838e-62           1.454990e-23   \n",
       "38     5.359658e-40               6.879358e-63           6.778661e-24   \n",
       "39     5.659641e-40               6.440042e-63           6.199081e-24   \n",
       "40     6.399018e-40               6.397197e-63           6.057769e-24   \n",
       "41     9.164150e-40               6.878532e-63           5.882461e-24   \n",
       "42     1.191312e-39               7.337220e-63           5.807951e-24   \n",
       "43     1.871863e-39               8.073298e-63           5.716142e-24   \n",
       "44     2.665854e-39               8.603579e-63           5.637955e-24   \n",
       "\n",
       "    H Line Cooling  C+ Line Cooling  O Line Cooling  C Line Cooling  ...  \\\n",
       "0              0.0              0.0    3.310983e-25    8.348479e-25  ...   \n",
       "1              0.0              0.0    3.310983e-25    8.348376e-25  ...   \n",
       "2              0.0              0.0    3.310984e-25    8.348549e-25  ...   \n",
       "3              0.0              0.0    3.310997e-25    8.348518e-25  ...   \n",
       "4              0.0              0.0    3.311123e-25    8.348392e-25  ...   \n",
       "5              0.0              0.0    3.312383e-25    8.348272e-25  ...   \n",
       "6              0.0              0.0    3.324984e-25    8.348308e-25  ...   \n",
       "7              0.0              0.0    3.453174e-25    8.349198e-25  ...   \n",
       "8              0.0              0.0    1.574924e-24    8.431027e-25  ...   \n",
       "9              0.0              0.0    2.009385e-23    9.058431e-25  ...   \n",
       "10             0.0              0.0    7.100815e-23    5.470146e-24  ...   \n",
       "11             0.0              0.0    2.358660e-22    4.441004e-23  ...   \n",
       "12             0.0              0.0    4.532101e-22    1.789472e-22  ...   \n",
       "13             0.0              0.0    7.266848e-22    4.213907e-22  ...   \n",
       "14             0.0              0.0    1.067836e-21    8.894247e-22  ...   \n",
       "15             0.0              0.0    1.384716e-21    1.530278e-21  ...   \n",
       "16             0.0              0.0    1.647955e-21    2.169177e-21  ...   \n",
       "17             0.0              0.0    1.848526e-21    2.687133e-21  ...   \n",
       "18             0.0              0.0    1.996990e-21    3.095256e-21  ...   \n",
       "19             0.0              0.0    2.241113e-21    4.432453e-21  ...   \n",
       "20             0.0              0.0    1.989355e-21    4.428172e-21  ...   \n",
       "21             0.0              0.0    1.737476e-21    4.386935e-21  ...   \n",
       "22             0.0              0.0    1.433629e-21    4.354515e-21  ...   \n",
       "23             0.0              0.0    1.215406e-21    4.337732e-21  ...   \n",
       "24             0.0              0.0    9.824387e-22    4.327748e-21  ...   \n",
       "25             0.0              0.0    7.596486e-22    4.288640e-21  ...   \n",
       "26             0.0              0.0    6.021007e-22    4.232427e-21  ...   \n",
       "27             0.0              0.0    4.645704e-22    4.151556e-21  ...   \n",
       "28             0.0              0.0    1.305229e-23    2.890876e-21  ...   \n",
       "29             0.0              0.0    4.759183e-24    1.749193e-21  ...   \n",
       "30             0.0              0.0    2.572568e-24    1.021949e-21  ...   \n",
       "31             0.0              0.0    1.534769e-24    5.831385e-22  ...   \n",
       "32             0.0              0.0    9.213588e-25    3.233932e-22  ...   \n",
       "33             0.0              0.0    5.672829e-25    1.734893e-22  ...   \n",
       "34             0.0              0.0    3.495755e-25    7.468949e-23  ...   \n",
       "35             0.0              0.0    2.215726e-25    3.747202e-23  ...   \n",
       "36             0.0              0.0    1.316863e-25    2.313840e-23  ...   \n",
       "37             0.0              0.0    7.415171e-27    9.396016e-26  ...   \n",
       "38             0.0              0.0    8.819628e-27    5.280131e-26  ...   \n",
       "39             0.0              0.0    1.091460e-26    3.836571e-26  ...   \n",
       "40             0.0              0.0    1.448423e-26    3.022693e-26  ...   \n",
       "41             0.0              0.0    2.288786e-26    1.689517e-26  ...   \n",
       "42             0.0              0.0    2.361776e-26    1.299020e-26  ...   \n",
       "43             0.0              0.0    2.403425e-26    9.700345e-27  ...   \n",
       "44             0.0              0.0    2.404294e-26    8.219155e-27  ...   \n",
       "\n",
       "    PhotoelectricBakes Heating  PhotoelectricWeingartner Heating  \\\n",
       "0                -1.100196e-34                               0.0   \n",
       "1                -1.100196e-34                               0.0   \n",
       "2                -1.100196e-34                               0.0   \n",
       "3                -1.100196e-34                               0.0   \n",
       "4                -1.100197e-34                               0.0   \n",
       "5                -1.100209e-34                               0.0   \n",
       "6                -1.100331e-34                               0.0   \n",
       "7                -1.101548e-34                               0.0   \n",
       "8                -1.219336e-34                               0.0   \n",
       "9                -3.175190e-34                               0.0   \n",
       "10               -7.343722e-34                               0.0   \n",
       "11               -1.443247e-33                               0.0   \n",
       "12               -2.496413e-33                               0.0   \n",
       "13               -3.793595e-33                               0.0   \n",
       "14               -5.270724e-33                               0.0   \n",
       "15               -6.769924e-33                               0.0   \n",
       "16               -8.107446e-33                               0.0   \n",
       "17               -9.178149e-33                               0.0   \n",
       "18               -1.001629e-32                               0.0   \n",
       "19               -1.141973e-32                               0.0   \n",
       "20               -1.009954e-32                               0.0   \n",
       "21               -9.017462e-33                               0.0   \n",
       "22               -7.879750e-33                               0.0   \n",
       "23               -7.097726e-33                               0.0   \n",
       "24               -6.206339e-33                               0.0   \n",
       "25               -5.245737e-33                               0.0   \n",
       "26               -4.448098e-33                               0.0   \n",
       "27               -3.604903e-33                               0.0   \n",
       "28               -8.653598e-35                               0.0   \n",
       "29               -7.126339e-35                               0.0   \n",
       "30               -5.998565e-35                               0.0   \n",
       "31               -5.067806e-35                               0.0   \n",
       "32               -4.078814e-35                               0.0   \n",
       "33               -3.258633e-35                               0.0   \n",
       "34               -2.595692e-35                               0.0   \n",
       "35               -2.070925e-35                               0.0   \n",
       "36               -1.561223e-35                               0.0   \n",
       "37               -2.845361e-36                               0.0   \n",
       "38               -1.786389e-36                               0.0   \n",
       "39               -1.772020e-36                               0.0   \n",
       "40               -1.857734e-36                               0.0   \n",
       "41               -2.223251e-36                               0.0   \n",
       "42               -2.546136e-36                               0.0   \n",
       "43               -3.188680e-36                               0.0   \n",
       "44               -3.779656e-36                               0.0   \n",
       "\n",
       "    H2Formation Heating  H2Photodissociation Heating  H2FUVPumping Heating  \\\n",
       "0          3.755034e-21                          0.0                   0.0   \n",
       "1          3.755034e-21                          0.0                   0.0   \n",
       "2          3.755034e-21                          0.0                   0.0   \n",
       "3          3.755034e-21                          0.0                   0.0   \n",
       "4          3.755034e-21                          0.0                   0.0   \n",
       "5          3.755033e-21                          0.0                   0.0   \n",
       "6          3.755032e-21                          0.0                   0.0   \n",
       "7          3.755022e-21                          0.0                   0.0   \n",
       "8          3.821641e-21                          0.0                   0.0   \n",
       "9          4.492683e-21                          0.0                   0.0   \n",
       "10         5.138866e-21                          0.0                   0.0   \n",
       "11         5.695782e-21                          0.0                   0.0   \n",
       "12         6.163665e-21                          0.0                   0.0   \n",
       "13         6.523852e-21                          0.0                   0.0   \n",
       "14         6.803286e-21                          0.0                   0.0   \n",
       "15         7.009663e-21                          0.0                   0.0   \n",
       "16         7.151321e-21                          0.0                   0.0   \n",
       "17         7.242572e-21                          0.0                   0.0   \n",
       "18         7.301227e-21                          0.0                   0.0   \n",
       "19         7.266573e-21                          0.0                   0.0   \n",
       "20         7.026947e-21                          0.0                   0.0   \n",
       "21         6.808183e-21                          0.0                   0.0   \n",
       "22         6.552151e-21                          0.0                   0.0   \n",
       "23         6.364602e-21                          0.0                   0.0   \n",
       "24         6.152176e-21                          0.0                   0.0   \n",
       "25         5.927502e-21                          0.0                   0.0   \n",
       "26         5.747900e-21                          0.0                   0.0   \n",
       "27         5.569542e-21                          0.0                   0.0   \n",
       "28         3.856126e-21                          0.0                   0.0   \n",
       "29         2.638103e-21                          0.0                   0.0   \n",
       "30         1.795690e-21                          0.0                   0.0   \n",
       "31         1.223275e-21                          0.0                   0.0   \n",
       "32         8.210216e-22                          0.0                   0.0   \n",
       "33         5.519997e-22                          0.0                   0.0   \n",
       "34         3.679853e-22                          0.0                   0.0   \n",
       "35         2.459149e-22                          0.0                   0.0   \n",
       "36         1.638731e-22                          0.0                   0.0   \n",
       "37         3.770210e-24                          0.0                   0.0   \n",
       "38         7.076531e-25                          0.0                   0.0   \n",
       "39         5.561210e-25                          0.0                   0.0   \n",
       "40         5.326686e-25                          0.0                   0.0   \n",
       "41         5.313387e-25                          0.0                   0.0   \n",
       "42         5.351541e-25                          0.0                   0.0   \n",
       "43         5.418687e-25                          0.0                   0.0   \n",
       "44         5.467853e-25                          0.0                   0.0   \n",
       "\n",
       "    CarbonIonization Heating  CosmicRay Heating  Turbulent Heating  \\\n",
       "0               4.513450e-48       1.041415e-24       7.000000e-40   \n",
       "1               4.515769e-48       3.030519e-24       7.000000e-40   \n",
       "2               4.536644e-48       3.030519e-24       7.000000e-40   \n",
       "3               4.745404e-48       3.030519e-24       7.000000e-40   \n",
       "4               6.833985e-48       3.030519e-24       7.000000e-40   \n",
       "5               2.780588e-47       3.030519e-24       7.000000e-40   \n",
       "6               2.406090e-46       3.030519e-24       7.000000e-40   \n",
       "7               2.374056e-45       3.030524e-24       7.000000e-40   \n",
       "8               1.880749e-43       3.031307e-24       7.000000e-40   \n",
       "9               1.383387e-42       3.039901e-24       7.000000e-40   \n",
       "10              1.101764e-42       3.049794e-24       7.000000e-40   \n",
       "11              9.324994e-43       3.060225e-24       7.000000e-40   \n",
       "12              8.203232e-43       3.071104e-24       7.000000e-40   \n",
       "13              7.333908e-43       3.081609e-24       7.000000e-40   \n",
       "14              6.677252e-43       3.092336e-24       7.000000e-40   \n",
       "15              6.179980e-43       3.103177e-24       7.000000e-40   \n",
       "16              5.800996e-43       3.114127e-24       7.000000e-40   \n",
       "17              5.504575e-43       3.124652e-24       7.000000e-40   \n",
       "18              5.272374e-43       3.135140e-24       7.000000e-40   \n",
       "19              6.011086e-43       3.236002e-24       7.000000e-40   \n",
       "20              4.493836e-43       3.334018e-24       7.000000e-40   \n",
       "21              3.866661e-43       3.423660e-24       7.000000e-40   \n",
       "22              3.506612e-43       3.530211e-24       7.000000e-40   \n",
       "23              3.247799e-43       3.608807e-24       7.000000e-40   \n",
       "24              3.077879e-43       3.696188e-24       7.000000e-40   \n",
       "25              2.960742e-43       3.787153e-24       7.000000e-40   \n",
       "26              2.877779e-43       3.858925e-24       7.000000e-40   \n",
       "27              2.820920e-43       3.929932e-24       7.000000e-40   \n",
       "28              2.441808e-43       4.575572e-24       7.000000e-40   \n",
       "29              2.469465e-43       5.025666e-24       7.000000e-40   \n",
       "30              2.673782e-43       5.338339e-24       7.000000e-40   \n",
       "31              2.890581e-43       5.554960e-24       7.000000e-40   \n",
       "32              3.060460e-43       5.708481e-24       7.000000e-40   \n",
       "33              3.211900e-43       5.814173e-24       7.000000e-40   \n",
       "34              3.297568e-43       5.888991e-24       7.000000e-40   \n",
       "35              3.314728e-43       5.940267e-24       7.000000e-40   \n",
       "36              3.280947e-43       5.975159e-24       7.000000e-40   \n",
       "37              5.099910e-44       6.052441e-24       7.000000e-40   \n",
       "38              1.438185e-44       6.054109e-24       7.000000e-40   \n",
       "39              1.476274e-44       6.054055e-24       7.000000e-40   \n",
       "40              1.606737e-44       6.053935e-24       7.000000e-40   \n",
       "41              1.519789e-44       6.053515e-24       7.000000e-40   \n",
       "42              1.320935e-44       6.053298e-24       7.000000e-40   \n",
       "43              1.124983e-44       6.053076e-24       7.000000e-40   \n",
       "44              1.035242e-44       6.052969e-24       7.000000e-40   \n",
       "\n",
       "    GasGrainCollisions Heating  Chemical Heating  \n",
       "0                 0.000000e+00               0.0  \n",
       "1                -9.310917e-34               0.0  \n",
       "2                -9.315356e-33               0.0  \n",
       "3                -9.315801e-32               0.0  \n",
       "4                -9.315847e-31               0.0  \n",
       "5                -9.315871e-30               0.0  \n",
       "6                -9.316070e-29               0.0  \n",
       "7                -9.318054e-28               0.0  \n",
       "8                -8.135891e-26               0.0  \n",
       "9                -1.244761e-24               0.0  \n",
       "10               -3.113675e-24               0.0  \n",
       "11               -5.500991e-24               0.0  \n",
       "12               -8.215717e-24               0.0  \n",
       "13               -1.087112e-23               0.0  \n",
       "14               -1.338619e-23               0.0  \n",
       "15               -1.560455e-23               0.0  \n",
       "16               -1.740943e-23               0.0  \n",
       "17               -1.878358e-23               0.0  \n",
       "18               -1.984741e-23               0.0  \n",
       "19               -2.299937e-23               0.0  \n",
       "20               -2.320682e-23               0.0  \n",
       "21               -2.341900e-23               0.0  \n",
       "22               -2.376720e-23               0.0  \n",
       "23               -2.407316e-23               0.0  \n",
       "24               -2.436455e-23               0.0  \n",
       "25               -2.462183e-23               0.0  \n",
       "26               -2.479093e-23               0.0  \n",
       "27               -2.495572e-23               0.0  \n",
       "28               -2.418004e-23               0.0  \n",
       "29               -2.213788e-23               0.0  \n",
       "30               -1.975061e-23               0.0  \n",
       "31               -1.754193e-23               0.0  \n",
       "32               -1.502153e-23               0.0  \n",
       "33               -1.278964e-23               0.0  \n",
       "34               -1.084044e-23               0.0  \n",
       "35               -9.137865e-24               0.0  \n",
       "36               -7.304371e-24               0.0  \n",
       "37               -9.600920e-25               0.0  \n",
       "38               -5.000709e-25               0.0  \n",
       "39               -4.529640e-25               0.0  \n",
       "40               -4.482787e-25               0.0  \n",
       "41               -4.999839e-25               0.0  \n",
       "42               -5.474699e-25               0.0  \n",
       "43               -6.204216e-25               0.0  \n",
       "44               -6.707517e-25               0.0  \n",
       "\n",
       "[45 rows x 23 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heating"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f805632",
   "metadata": {},
   "source": [
    "### Plotting Individual Heating and Cooling Contributions\n",
    "\n",
    "Let's visualize the dominant heating and cooling processes over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a9a0d0f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:54.084891Z",
     "iopub.status.busy": "2026-01-27T12:49:54.084721Z",
     "iopub.status.idle": "2026-01-27T12:49:54.488292Z",
     "shell.execute_reply": "2026-01-27T12:49:54.487407Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VwcHBWr16tZycnBQZGSknJyf98MMP+u2339SpUyctXrxYiYmJ+uyzz7Rt2zbFxcXpueeeU1RU1HWvefToUV25ckUpKSmqX7++Pv74Y9WuXbvA57p8+bJmzZqlpKQka0FKkrp37259v3LlSutIJ19fX8XGxqphw4Yym82aOHGiNm/eLEnq1q2b5syZU2iB+qlTp+rixYuaN2+e4uLitGrVKtWpU0dHjhyRm5ub1q5da31y5ZQpU7R69WrVqlVLERERWrVqlU6cOGHHTxQAAAAAgIrBrul70u9/cP/3v//VqlWrNGPGDM2YMUOrV6/Wf//7X02ZMqUkY7ytZVzN08UruQ573ajgdeDAATVv3lx169Yt8vjmzZu1fPly7dy5UwcPHlT16tU1ceJE6/H9+/drxYoV+vHHH5WZmamoqCh9/PHHOnLkiI4ePWot7EjSnj179OWXX+ro0aNKT0/X3Llz1bt3b/Xr108TJkxQcnKyoqKibnjNPXv2KC4uTkeOHJGPj4+WLFlSKO7Dhw/L1dVV/v5FF+QOHTqkCRMmaPPmzfr+++913333KSoqSpIUGxurffv2KSkpScnJyUpJSdHcuXOvex8lad++fXrttdf0/fffKzw8XDNnzpQkbdq0SevXr9e3336rvXv36tdff71hXwAAAAAAVHR2jZS6pm7duho8eHBJxYIieFWtcuNGZdh/fHy8Bg0aZJ3G98wzzxQYRdWjRw/rCKugoCC5ubnJw8NDktSuXTsdO3bM2vbRRx+1Hhs+fLjeffddvfzyyzd9zZ49e6pOnTqSpE6dOungwYM3/bkSExPVs2dPNWzYUNLvowOnT58us9ms+Ph4RUZGys3NTZIUHR2thQsXKiYm5rp9durUSX5+ftb38+fPl/T7lMGBAwcW+OyJiYk3HTMAAAAAABXJLRWl/vOf/2jTpk365ZdfJElNmjRRnz591LVr1xIJDrru1LrSEBQUpGPHjun8+fPWQs/1mEymAtvu7u7W987OzoW28/Pzbe7L3msWdQ1/f3/l5ubqyJEjxY6WsjUWW+O09bPb2h8AAAAAABWZXdP3cnNzNWDAAIWFhentt9/Wtm3btG3bNr399tsKCwvTX//6V+XlOW4dJJSeZs2aacCAARo+fLj1aXuGYWj9+vX6+eefFR4errVr1+rSpUuSpCVLlqhHjx52Xevjjz9WVlaWzGaz3n//fYWHh0uSPD09lZGRYW1XEtesUaOGxo8fr+jo6ALT5RITE7V3715169ZNW7Zs0enTpyX9/iS97t27y9nZWeHh4VqxYoVyc3OVn5+vZcuW2f2ZJSksLEzr169XVlaWDMPQ8uXL7e4LAAAAAICKwq6RUtOmTdOGDRs0fvx4jRs3TvXq1ZMkpaWlac6cOZo9e7amT5+u1157rUSDRdlYvny5Xn/9dYWEhMjFxUUWi0VdunRR9+7d1atXLx06dEidOnUqsOi4PTp06KCIiAidO3dOnTp10pgxYyRJTz75pCIjI7Vx40Y9++yzioqKKpFrTp8+XXXr1lVERITMZrNMJpMCAwM1c+ZM+fr6avbs2erZs6ek3xc6X7p0qSRpxIgRSklJUVBQkCQpNDTUGqs9+vbtqz179igwMFA1a9ZU165dS+WphgAAAAAAlCWTYRjGzZ7k5+en0NBQvf/++0Uej4yM1FdffcXTw67j0qVL8vLyUkZGhjw9PSVJ2dnZSk1NlZ+fX4GpXreDyMhIBQYG3lJxp7wzDEP5+flycXEpNEUvMzNTHh4eMgxD48aN09WrV7Vo0aIyivT2zsWKymKxKC0tTT4+PnJysvsZFkCxyDE4EvkFRyK/4GjkGBypouZXUTWPotj1if73v/8pJCSk2OMhISE6c+aMPV0Dt6UhQ4aoXbt28vf318mTJxllCAAAAACo9OyavteoUSN99dVXGjlyZJHH//Of/6hRo0a3FBhuL3FxcWUdQpnasGFDWYcAAAAAAECpsmuk1NChQ7V27VqNHDlSP/74o8xmsywWi3788Uc988wzWrdunSIjI0s4VAAAAAAAAFQWdo2Uevnll5WSkqLY2FgtXbrUOq/RYrHIMAwNHTpUL7/8cokGCgAAAAAAgMrDrqKUs7Oz4uLiNHbsWP373//WL7/8Iklq0qSJevfurTZt2pRokAAAAAAAAKhc7CpKXdOmTRsKUAAAAAAAALhpNq8plZ2drZEjR2r+/PnXbffuu+/qmWeeUV5e3i0Hh/KhadOm8vHxKfAzTUxMlMlk0pgxY254fmRkpObNm+eQ2OLi4tS/f3+7zi0ursWLF2v27Nm3FlgRFi5cqMDAQPn7+ysoKEiDBw/WyZMn7e7vj/E7KmYAAAAAABzF5pFSsbGxiouL05EjR67brk+fPnrxxRfVpk0bPfPMM7ccIMqHxo0b67PPPtOAAQMkSe+9957at29fxlHZz2w2F3usuKdK3oopU6Zo69at+uKLL9S0aVOZTCYlJCTozJkzaty48S3374iYAQAAAABwJJuLUmvXrtWAAQN05513XrfdXXfdpYEDB+rDDz+kKFUStrwkXb3ouP6r1pR6vnnDZsOGDdPy5cs1YMAAZWRkaPfu3Ro8eLAyMzMl/V7kmThxojZv3ixJ6tatm+bMmSNXV9cC/eTl5enVV1/V9u3blZubqxYtWmjJkiWqVauWMjIyNG7cOO3evVvOzs4KDg7W8uXLNXXqVF28eNE6KmjBggXav3+/4uLiCvR95swZDR48WJcuXVJ2dra6deumd999V05OToqLi9MHH3yg2rVr66efflJsbGyxn/WP14uLi9OqVavk7e2tQ4cOyc3NTWvXrrX+e7By5UotWLBAeXl5qlGjhubPn6+2bdsW6O/y5cuaNWuW9u/fr0aNGln3d+/e3fp+5cqV1pFOvr6+io2NVcOGDW2+rzcT85QpU7R69WrVqlVLERERWrVqlU6cOFHs/QAAAAAAwBFsnr538OBB3X///Ta1ve+++/T999/bHVR5curUKYWGhsrf319t2rTRunXrrMdSU1PVrVs3+fv7KyAgQJcvXy75AK5elK6mO/B10aYw/vKXv+jEiRM6ffq0PvzwQw0cOFDOzs7W47Gxsdq3b5+SkpKUnJyslJQUzZ07t1A/s2fPVvXq1bV3714lJycrICBAr7zyiiRpzJgxcnV11ffff6/vvvtOM2fOvKlbVbNmTX3++edKSkrS999/rxMnTmjt2rXW43v27NGMGTN08OBBderUyeZ+9+3bZz0vPDzcGtfOnTv14YcfaseOHTpw4IDeeOMNPfbYY4XOP3z4sFxdXeXv719k/4cOHdKECRO0efNmff/997rvvvsUFRUlyfb7amvMmzZt0vr16/Xtt99q7969+vXXX22+DwAAAAAAlCSbi1K5ubmFRmcUx9XVVTk5OXYHVZ64uLho3rx5OnLkiLZu3aoxY8ZYi0+RkZGaPn26jhw5ov/85z9yc3Mr+QCq1pSq1nbgq6bNoTz55JOKi4vT8uXL9dRTTxU4Fh8fr8jISLm5ucnFxUXR0dHatm1boT42btyoVatWKTAwUIGBgfrwww+VmpoqSfriiy80fvx4OTn9npbe3t43dassFotiYmLUtm1btWvXTvv371dycrL1+H333ae77777pvqUpE6dOsnPz8/6PiUlRZL06aef6rvvvlNISIgCAwM1evRopaen6+rVqzfVf2Jionr27KmGDRtKkkaNGqXt27fLbDbbfF9tjTkhIUEDBw6Uh4eHTCaThg8fflOxAgAAAABQUmyevtegQQMdOnTIpraHDh1SgwYN7A6qPLnjjjt0xx13SJLq16+vunXrKj09XSdOnFCVKlXUuXNnSVLt2rUdE4ANU+tKy5AhQxQUFKQWLVqoefPm121rMpmK3G8YhubPn68ePXrYfF0XF5cCa0BlZ2cX2e6dd95RWlqa9uzZI3d3d40dO7ZA2xo1ath8zT9yd3e3vnd2dlZ+fr6k3z/L0KFDNWPGjOue7+/vr9zcXB05ckQtWrS44fWKu3c3OmZLzPb2BwAAAABASbN5pFR4eLhWrFihtLS067ZLS0vTihUr9MADD9xycDeyY8cOPfjgg2rQoIFMJpM2btxYZLuFCxeqadOmcnd3V0hIiPbu3WvX9ZKSkmQ2m+Xr66tjx46pRo0aevDBBxUUFHTDwkRl0KBBA7355ptFTqu7lh+5ubnKz8/XsmXLiiw89e/fX3PnztWVK1ckSVeuXNHhw4clSf369dPbb78ti8UiSTp37pwkqVmzZtq/f7/MZrOuXLmi9evXFxnfhQsXVL9+fbm7u+vMmTMFplo6Qr9+/bRq1SrrE/QsFov2799fqF2NGjU0fvx4jRgxosB0ucTERO3du1fdunXTli1bdPr0aUm/P0mve/fucnZ2tvm+2iosLEzr169XVlaWDMPQ8uXL7e4LAAAAAIBbYfNIqZiYGK1atUphYWF67733FBISUqjNnj17FBUVpezsbE2YMKFEAy3K5cuX1bZtWz311FN65JFHimyzZs0ajR07VosXL1ZISIjmzZuniIgI/fjjj/Lx8ZEkBQYGFjmSZOvWrdYRX+np6RoyZIiWLl0qScrPz9fXX3+t5ORk+fj4qGfPnurQoUOxxbicnJwCUxovXbok6fdCxrUijMVikWEY1ld5ci2myMjIAtvXXtHR0Tp+/LiCgoIkSV27dtULL7xg/RzX2r344ovKzs5WSEiIdZTOiy++KH9/f73zzjv6+9//roCAAFWpUkXt27fX0qVL9fDDD2vdunVq2bKlGjVqpMDAQF29erXAfTIMQ88//7wGDhyoVq1aqUGDBgoPDy90P/98X6dOnaq3337buv3OO+8U+mx/PO+P/7z//vs1c+ZMPfzww8rPz1dubq569+6t4ODgQvdv2rRpqlOnjvr06SOLxSKTyaTAwEC99dZb8vX11axZs9SzZ09J/7fQ+c3cV1tj7tOnj3bv3q3AwEDVrFlTXbp0Uc2aNQvdl2v9/DE/Ub5d+/7g5wVHIcfgSOQXHIn8gqORY3CkippftsZrMm6i+rFp0yYNHjxYly9f1p133qmAgAB5eHgoMzNThw4dUkpKiqpVq6Z//etfevDBB+0O3h4mk0kbNmxQ//79C+wPCQlRhw4dtGDBAkm/3xhfX1+NHj1aEydOtKnvnJwcPfDAA4qOjtaTTz4pSdq1a5emTp2qL7/8UpKsT04rrhg3depUTZs2rdD+n376SR4eHpJ+fzJdRkaGmjRpUmD6FSoHwzBkNpvl7OxcptPmMjMz5eHhYS0SXr161frvxzXZ2dn65Zdf5OXlpSpVqpRRpLgZFotFGRkZ8vLysq7LBpQkcgyORH7BkcgvOBo5BkeqqPmVmZmpFi1aKCMjQ56ensW2s3mklCT16dNH33//vWbOnKkvvviiwHS5Bg0aKDo6Wi+++KL10fNlLTc3V0lJSXrppZes+5ycnBQeHq5du3bZ1Me10UFhYWHWgpQkdejQQWlpabpw4YK8vLy0Y8cOPf3008X289JLL2ns2LHW7UuXLsnX11fe3t7WH1B2drYyMzPl4uIiF5eb+tGgAinrIs/w4cN14sQJZWdnq1WrVlq0aFGhfHNxcZGTk5Pq1KlDgbSCuDYCz9vbu0L9xwoVBzkGRyK/4EjkFxyNHIMjVdT8svXvyJuufDRt2lSLFi3SokWLlJmZqUuXLsnT09M62qc8+e2332Q2m1WvXr0C++vVq6cffvjBpj527typNWvWqE2bNtYi3MqVKxUQEKAZM2aoS5cuMgxDPXr0UN++fYvtx83Nrcin8zk5OVkTy8nJSSaTyfpC5WIYhvXnWpY/3w0bNtywzbUc/GN+ovzjZwZHI8fgSOQXHIn8gqORY3CkiphftsZ6S8NxPDw8SrwYNXHixCIX0v6jo0eP6p577inR6xbn/vvvL3YuZK9evdSrV69SiQMAAAAAAKAyKXdzxMaNG2ddTLs4tk4PrFu3rpydnXX27NkC+8+ePav69evbGyIAAAAAAABuUbkrSnl7e8vb27tE+nJ1dVVwcLASEhKsC6BbLBYlJCToueeeK5FrAAAAAAAA4OaVu6LUzcjKytLx48et26mpqUpOTlbt2rXVuHFjSdLYsWM1dOhQtW/fXh07dtS8efN0+fJlDRs2rKzCBgAAAAAAuO1V6KLU/v371a1bN+v2tafbDR06VHFxcZKkQYMG6dy5c5o8ebLOnDmjwMBAbdmypdDi5wAAAAAAACg9FWfp9iKEhobKMIxCr2sFqWuee+45/fLLL8rJydGePXsUEhJSNgFXULm5uYqJiVGzZs3UsmVLBQQE6IMPPii2fWRkpObNm1do/+LFizV79uwSj2/hwoVq3bq1WrZsqaCgIA0ePFgnT560u78/xu+omAEAAAAAuN1V6JFSKB2RkZHKycnRd999p+rVq+vEiRPq1auX8vPzNXz4cJv7GTlyZInHNmXKFG3dulVbtmxRo0aNJEkJCQk6c+aMdQrnrXBEzAAAAAAAgKJUuTdz70xdyr3ksP49XT0V0zGm2OPHjh3Txo0bderUKVWvXl2S1LRpU82ZM0cjR468qaLU1KlTdfHiRc2bN09xcXFatWqVvL29dejQIbm5uWnt2rXWJyuuXLlSCxYsUF5enmrUqKH58+erbdu2Bfq7fPmyZs2apaSkJGtBSpK6d+9ufb9y5UrrSCdfX1/FxsaqYcOGMpvNmjhxojZv3ixJ6tatm+bMmSNXV1e7Y54yZYpWr16tWrVqKSIiQqtWrdKJEydsvj8AAAAAANxOKvT0vdvBpdxLysjJcNjrRgWvb7/9Vs2bN1edOnUK7O/UqZNOnTqlc+fO2f3Z9u3bpxkzZujgwYMKDw/XzJkzJUk7d+7Uhx9+qB07dujAgQN644039NhjjxU6//Dhw3J1dZW/v3+R/R86dEgTJkzQ5s2b9f333+u+++5TVFSUJCk2Nlb79u1TUlKSkpOTlZKSorlz59od86ZNm7R+/Xp9++232rt3r3799Vd7bwsAAAAAALcFRkqVc56unhW6/+vp1KmT/Pz8rO/nz58vSfr000/13XffFVj7Kz09XVevXlXVqlVt7j8xMVE9e/ZUw4YNJUmjRo3S9OnTZTabFR8fr8jISLm5uUmSoqOjtXDhQsXEFD9q7HoxJyQkaODAgfLw8JAkDR8+XImJiTbHCgAAAADA7YaiVDl3val1paFdu3Y6duyYzp8/X2C01K5du+Tr6ytvb2+7+3Z3d7e+d3Z2Vn5+viTJMAwNHTpUM2bMuO75/v7+ys3N1ZEjR4odLfVHJpPJrmO2xGxvfwAAAAAA3K6Yvofrat68uR588EGNGDFCV65ckSSdOHFC48aN06uvvuqQa/br10+rVq2yPkHPYrFo//79hdrVqFFD48ePV3R0dIHpcomJidq7d6+6deumLVu26PTp05J+f5Je9+7d5ezsrPDwcK1YsUK5ubnKz8/XsmXL1KNHD7tjDgsL0/r165WVlSXDMLR8+XK7+wIAAAAA4HbASCnc0IoVK/TKK68oICBArq6ucnZ21oQJE/TUU08Ve87UqVP19ttvW7dtWa/pms6dO2vWrFl6+OGHlZ+fr9zcXPXp00ft27cv1Hb69OmqW7euIiIiZDabZTKZFBgYqJkzZ8rX11ezZ89Wz549Jf2+0PnSpUslSSNGjFBKSoqCgoIkSaGhoRozZozNMf5Z3759tWfPHgUGBqpmzZrq2rWratasaXd/AAAAAABUdibDMIyyDuJ2dOnSJXl5eSkjI0Oenr+v65Sdna3U1FT5+fkVmCaGiiEzM1MeHh4yDEPjxo3T1atXtWjRIutxwzCUn58vFxeXcj+9j1yseCwWi9LS0uTj4yMnJwbBouSRY3Ak8guORH7B0cgxOFJFza+iah5FYaQUUEKGDBmiEydOKDs7W61atdLixYvLOiQAAAAAAMotilJACdmwYUNZhwAAAAAAQIVRccZ+AQAAAAAAoNKgKAUAAAAAAIBSR1EKAAAAAAAApY6iFAAAAAAAAEodRSncUH5+vqZNm6Z77rlHrVu3VmBgoEaMGKGLFy8WahsZGal58+YV2r948WLNnj27xGNbuHChWrdurZYtWyooKEiDBw/WyZMn7e7vj/E7KmYAAAAAAMDT92CD4cOHKz09Xbt27VKtWrVkGIY+/vhjpaenq2bNmjb1MXLkyBKPa8qUKdq6dau2bNmiRo0aSZISEhJ05swZNW7c+Jb7d0TMAAAAAADgd4yUwnUdP35c69at0/vvv69atWpJkkwmkwYOHKg777zT5n6mTp2qMWPGSJLi4uIUHh6uwYMHKyAgQO3bt9fPP/9sbbty5UqFhIQoKChIXbp00XfffVeov8uXL2vWrFl67733rAUpSerevbs6duxo7adNmzZq06aN+vTpo19//VWSZDabNWHCBLVu3VqtW7fW6NGjlZube0sxT5kyRc2aNVOHDh30yiuvqGnTpjbfGwAAAAAAbkeMlCrnzr75pswZlxzWv7OXp+q99FKxxw8cOKDmzZurbt26JXrdffv2KTk5WX5+fpo4caJmzpypJUuWaOfOnfrwww+1Y8cOubm56euvv9Zjjz2mw4cPFzj/8OHDcnV1lb+/f5H9Hzp0SBMmTFBSUpIaNmyoN954Q1FRUdq8ebNiY2O1b98+JSUlydnZWf369dPcuXMVExNjV8ybNm3S+vXr9e2336pGjRp66qmnSuw+AQAAAABQWTFSqpwzZ1yS+eJFx70cWPC6nk6dOsnPz8/6PiUlRZL06aef6rvvvlNISIgCAwM1evRopaen6+rVqzfVf2Jionr27KmGDRtKkkaNGqXt27fLbDYrPj5ekZGRcnNzk4uLi6Kjo7Vt2za7Y05ISNDAgQPl4eEhk8mk4cOH31SsAAAAAADcjhgpVc45e3mWaf9BQUE6duyYzp8/rzp16pTYdd3d3f8vBmdn5efnS5IMw9DQoUM1Y8aM657v7++v3NxcHTlypNjRUn9kMpnsOmZLzPb2BwAAAADA7YyiVDl3val1paFZs2YaMGCAhg8frri4ONWsWVOGYeiTTz5Ru3btbmpdKVv069dPjz/+uEaOHKnGjRvLYrHowIEDat++fYF2NWrU0Pjx4xUdHa21a9daR0QlJiaqevXq6tatm9544w2dPn1aDRo00OLFi9W9e3c5OzsrPDxcK1as0GOPPSYnJyctW7ZMPXr0sDvmsLAwvfzyyxo3bpyqV6+u5cuX39I9AAAAAADgdkBRCje0fPlyvf766woJCZGLi4ssFou6dOmi7t27F9l+6tSpevvtt63bc+fOtflanTt31qxZs/Twww8rPz9fubm56tOnT6GilCRNnz5ddevWVUREhMxms0wmkwIDAzVz5kz5+vpq9uzZ6tmzpyTJ19dXS5culSSNGDFCKSkpCgoKkiSFhoZaFzS3R9++fbVnzx4FBgaqZs2a6tq1q81PJQQAAAAA4HZlMgzDKOsgbkeXLl2Sl5eXMjIy5On5+xS67Oxspaamys/Pr8BUMZR/mZmZ8vDwkGEYGjdunK5evapFixYVaGMYhvLz8+Xi4lLup/iRixWPxWJRWlqafHx85OTEcoEoeeQYHIn8giORX3A0cgyOVFHzq6iaR1EYKQWUgCFDhujEiRPKzs5Wq1attHjx4rIOCQAAAACAco2iFFACNmzYUNYhAAAAAABQoVScsV8AAAAAAACoNChKAQAAAAAAoNRRlAIAAAAAAECpoygFAAAAAACAUkdRCgAAAAAAAKWOohRuKD8/X9OmTdM999yj1q1bKzAwUCNGjNDFixclSb/++qv+9re/6c4771Tz5s3VtWtX7d69u9j+mjZtquTk5EL7o6KilJiYWKKxZ2VlacyYMWrWrJnatm2rdu3aafz48crLy7O7zz/G74iYAQAAAAC4HbiUdQAo/4YPH6709HTt2rVLtWrVkmEY+vjjj5Wenq4qVaooNDRUUVFR+uijjyRJCQkJevDBB5WYmKjWrVvbfJ1ly5aVaNyGYahv375q3ry5Dh48qKpVqyovL0/vvfeecnJyVKVKlVu+RknHDAAAAADA7YKiVDn3/609ppwr9o/quRG3alV0/6PNiz1+/PhxrVu3TidPnlStWrUkSSaTSQMHDpT0e1GmVq1aiomJsZ7TvXt3DRs2TLNmzdKKFStsjiU0NFRjxoxR//79FRkZKTc3Nx0/flynTp1S69at9dFHH8nV1VV5eXl69dVXtX37duXm5qpFixZasmSJNb5rtm/fruPHj2vr1q1ydXWVJFWpUkUjR46UJJnNZk2cOFGbN2+WJHXr1k1z5syRq6ur0tLSNHLkSB07dkyGYWj06NF6+umn7Y45MzNTUVFRSk5Olo+Pj/z9/ZWTk6O4uDib7w8AAAAAAJUJ0/fKuZwrecq+7LjXjQpeBw4cUPPmzVW3bt1ij3fq1KnQ/k6dOikpKemWPntycrI+//xzHT16VGfPntX69eslSbNnz1b16tW1d+9eJScnKyAgQK+88kqh85OSkhQcHGwtSP1ZbGys9u3bp6SkJCUnJyslJUVz586VJI0ePVp33323Dh48qO3bt+v111+/7pTEG8U8ffp0Va1aVQcPHtSmTZv0zTff2HtbAAAAAACoFBgpVc65Vbv1KWZl2f+tePjhh1WtWjVJUseOHZWSkiJJ2rhxozIyMqwFn9zcXDVt2vSm+4+Pj7eObpKk6OhoLVy4UDExMYqPj7cW1Xx8fPTII48oPj5e9957r10xJyQk6J133pHJZJKHh4cGDRqk48eP33TMAAAAAABUFhSlyrnrTa0rDUFBQTp27JjOnz+vOnXqFHk8Nja20P5du3YpKCjolq7t7u5ufe/s7Kz8/HxJv68VNX/+fPXo0eO65wcHB2v+/PnKzc0tdrTUH5lMJruO2RKzvf0BAAAAAFBZMX0P19WsWTMNGDBAw4cPtz5tzzAMrV+/Xj///LMGDx6s8+fPa+bMmdZztm/fruXLl2vChAkOial///6aO3eurly5Ikm6cuWKDh8+XKhdWFiY/Pz89Pzzzys7O1vS708SjI2NVVZWlsLDw7VixQrl5uYqPz9fy5Ytsxa6wsPDtXTpUknSuXPn9Mknn+iBBx6wO+awsDB98MEHMgxDWVlZWrt2rd19AQAAAABQGTBSCje0fPlyvf766woJCZGLi4ssFou6dOmi7t27q3r16vrqq680btw4+fn5ycXFRXfccYc+++wztWnTptg+IyIiCjz9zpb1mq6JiYlRTk6OQkJCrCOOYmJi1KpVqwLtTCaTNm3apEmTJqlVq1aqWrWqLBaL+vTpI3d3d40YMUIpKSnWEV3XFi2XpHfffVfPPPOMAgICZBiGJk2apJCQEJtj/LPJkydr+PDhCggIkLe3t9q2bauaNWva3R8AAAAAABWdyTAMo6yDuB1dunRJXl5eysjIkKenpyQpOztbqamp8vPzKzANDBVfXl6e8vPz5eLiopycHPXs2VOjR4/WoEGDyjq0IpGLFY/FYlFaWpp8fHzk5MQgWJQ8cgyORH7BkcgvOBo5BkeqqPlVVM2jKIyUAkrBhQsX1KtXL+Xn5ysnJ0cPPfSQHn300bIOCwAAAACAMkNRCigFPj4+2r9/v3W0FAudAwAAAABudxVn7BcAAAAAAAAqDYpSAAAAAAAAKHUUpQAAAAAAAFDqKEoBAAAAAACg1FGUAgAAAAAAQKmjKIUS1bRpUyUnJxfYFxoaqo0bN0qS3n33XbVu3VoBAQFq06aNVq1adVN9SVJUVJQSExNLMGopKytLY8aMUbNmzdS2bVu1a9dO48ePV15ent19/jF+R8QMAAAAAEBF5lLWAeD20qpVK+3cuVNeXl46deqU2rVrp06dOumuu+6yuY9ly5aVaEyGYahv375q3ry5Dh48qKpVqyovL0/vvfeecnJyVKVKlVu+xrJly2QYhvLz80sgYgAAAAAAKj6KUuVc4gdLlXM5y2H9u1WvoW5Do6/bxmQyadKkSdq0aZMuX76sKVOm6PHHH7fret27d7e+9/X1Vf369XXq1KmbKkqFhoZqzJgx6t+/vyIjI+Xm5qbjx4/r1KlTat26tT766CO5uroqLy9Pr776qrZv367c3Fy1aNFCS5YsUa1atQr0t337dh0/flxbt26Vq6urJKlKlSoaOXKkJMlsNmvixInavHmzJKlbt26aM2eOXF1dlZaWppEjR+rYsWMyDEOjR4/W008/XWTML7zwgvr27athw4YVG3NmZqaioqL03XffydvbW/7+/srJyVFcXNzN3moAAAAAAMo1ilLlXM7lLF3NvFTWYchkMunbb7/Vzz//rPbt2+svf/mLmjZtWmTbQYMGqWrVqtbt48ePF9kuPj5eFy5cUIcOHW4ptuTkZCUmJsrNzU1dunTR+vXrNXjwYM2ePVvVq1fX3r17JUmvvfaaXnnlFS1cuLDA+UlJSQoODrYWpP4sNjZW+/btU1JSkpydndWvXz/NnTtXMTExGj16tO6++2598sknSktLU3BwsNq2bat7773XrpinT5+uqlWr6ujRo8rKytJ9992n4ODgW7o/AAAAAACURxSlyjm36jXKRf9RUVGSpDvvvFNdunTRjh07ii1KrVmzRoGBgdbt0NDQQm0OHjyoYcOGac2aNapevfrNhl3Aww8/rGrVqkmSOnbsqJSUFEnSxo0blZGRofXr10uScnNzi435euLj460jsiQpOjpaCxcuVExMjOLj45WUlCRJ8vHx0SOPPKL4+PgbFqWKizkhIUFz586VyWSSh4eHBg0aVGxRDwAAAACAioyiVDl3o6l1ZcVkMmnFihV65513JEkvvPCChg0bZtO5R44cUd++fbV8+XLdf//9txyLu7u79b2zs7N13SbDMDR//nz16NHjuucHBwdr/vz5ys3NLXa01B+ZTCa7jtkSs739AQAAAABQ0fD0Pdjk/ffflySdOHFCX3/9tTp37qwhQ4YoOTlZycnJNhekjh49qt69eys2NlYPPPCAI0NW//79NXfuXF25ckWSdOXKFR0+fLhQu7CwMPn5+en5559Xdna2JCk/P1+xsbHKyspSeHi4VqxYodzcXOXn52vZsmXWQld4eLiWLl0qSTp37pw++eSTW/pcYWFh+uCDD2QYhrKysrR27Vq7+wIAAAAAoDyjKAWbmM1mtWvXTj169NC7775r1zQ4SXr++eeVkZGhmJgYBQYGKjAwUF9++WWx7SMiItSoUSPr67///a/N14qJiVGHDh0UEhKiNm3a6N5771VycnKhdiaTSZs2bZKrq6tatWql1q1bq02bNjp27Jjc3d01YsQIBQUFKSgoSIGBgWratKnGjBkjSXr33Xd19OhRBQQEqFu3bpo0aZJCQkJu9rZYTZ48WZmZmWrZsqV69uyptm3bqmbNmnb3BwAAAABAeWUyDMMo6yBuR5cuXZKXl5cyMjLk6ekpScrOzlZqaqr8/PwKTO8qayaTSRcuXKA4cosMw1B+fr5cXFyKnZaXl5cns9ksd3d3Xb58WRERERo9erQGDRpUqrGW11xE8SwWi9LS0uTj4yMnJ/5/A0oeOQZHIr/gSOQXHI0cgyNV1PwqquZRFNaUAsqRCxcuqFevXjKbzcrOztZDDz2kRx99tKzDAgAAAACgxFGUwg0xmK70+Pj4WJ/mBwAAAABAZVZxxn4BAAAAAACg0qAoBQAAAAAAgFJHUQoAAAAAAACljqIUAAAAAAAASh1FKZSopk2bKjk5ucC+0NBQbdy4UZL07rvvqnXr1goICFCbNm20atWqm+pLkqKiopSYmFiCUUtZWVkaM2aMmjVrprZt26pdu3YaP3688vLy7O7zj/E7ImYAAAAAACoynr6HUtWqVSvt3LlTXl5eOnXqlNq1a6dOnTrprrvusrmPZcuWlWhMhmGob9++at68uQ4ePKiqVasqLy9P7733nnJyclSlSpVbvsayZctkGIby8/NLIGIAAAAAACo+ilLl3MXPU2S56rhChlNVF9V88PoFoS+//FIvvfSS8vPzVatWLS1atEj+/v52Xa979+7W976+vqpfv75OnTp1U0Wp0NBQjRkzRv3791dkZKTc3Nx0/PhxnTp1Sq1bt9ZHH30kV1dX5eXl6dVXX9X27duVm5urFi1aaMmSJapVq1aB/rZv367jx49r69atcnV1lSRVqVJFI0eOlCSZzWZNnDhRmzdvliR169ZNc+bMkaurq9LS0jRy5EgdO3ZMhmFo9OjRevrpp4uM+YUXXlDfvn01bNiwYmPOzMxUVFSUvvvuO3l7e8vf3185OTmKi4u72VsNAAAAAEC5xvS9Gzh16pRCQ0Pl7++vNm3aaN26ddfdX9IsV/NlueLA1w0KXmlpaXrsscf0wQcf6Pvvv9eIESP017/+VYZhFHvOoEGDFBgYaH3t37+/yHbx8fG6cOGCOnTocEv3KDk5WZ9//rmOHj2qs2fPav369ZKk2bNnq3r16tq7d6+Sk5MVEBCgV155pdD5SUlJCg4Othak/iw2Nlb79u1TUlKSkpOTlZKSorlz50qSRo8erbvvvlsHDx7U9u3b9frrr2v37t12xzx9+nRVrVpVR48e1b///W9988039t4WAAAAAADKNUZK3YCLi4vmzZunwMBAnTlzRsHBwerdu3ex+6tXr16i13eq6tgf0Y3637NnjwICAhQQECBJevzxx/Xss8/q119/VaNGjYo8Z82aNQoMDLRuh4aGFmpz8OBBDRs2TGvWrLnle/bwww+rWrVqkqSOHTsqJSVFkrRx40ZlZGRYCz65ublq2rTpTfcfHx9vHZElSdHR0Vq4cKFiYmIUHx+vpKQkSZKPj48eeeQRxcfH695777Ur5oSEBM2dO1cmk0keHh4aNGiQjh8/ftMxAwAAAABQ3lGUuoE77rhDd9xxhySpfv36qlu3rtLT0+Xr61vk/pIuSt1oal1ZWrFihd555x1J0gsvvKBhw4bZdN6RI0fUt29fLV++XPfff/8tx+Hu7m597+zsbF23yTAMzZ8/Xz169Lju+cHBwZo/f75yc3OLHS31RyaTya5jtsRsb38AAAAAAFQ0FXr63o4dO/Tggw+qQYMGMplM1ie8/dnChQvVtGlTubu7KyQkRHv37rXreklJSTKbzfL19bVpf2Vw77336uDBgzp06JAk6aOPPlLDhg3VsGFDDRkyRMnJyUpOTra5IHX06FH17t1bsbGxeuCBBxwZuvr376+5c+fqypUrkqQrV67o8OHDhdqFhYXJz89Pzz//vLKzsyVJ+fn5io2NVVZWlsLDw7VixQrl5uYqPz9fy5Ytsxa6wsPDtXTpUknSuXPn9Mknn9zS5woLC9MHH3wgwzCUlZWltWvX2t0XAAAAAADlWYUeKXX58mW1bdtWTz31lB555JEi26xZs0Zjx47V4sWLFRISonnz5ikiIkI//vijfHx8JEmBgYFFjlTZunWrGjRoIElKT0/XkCFDrAWIa4rb/2c5OTnKycmxbl+6dEmSZLFYZLFYrO8Nw7C+yoO6detq1apVGjJkiHWh82uFkuJiLCr+a/uef/55ZWRkKCYmRjExMZKkt956SxEREUX2FRERUeDpd7t27Sp0jaLeG4ahF198UdnZ2QoJCbGOOHrxxReLXKT9iy++0KRJk9SqVStVrVpVFotFvXv3lpubm6Kjo3X8+HEFBQVJkrp27aoXXnhBhmHoH//4h0aNGqWAgAAZhqGXX35ZHTt2LDK2P96z4mJ+9dVXFRUVpZYtW6pu3bpq27atvLy8Sj0frsXzx/xE+Xbt+4OfFxyFHIMjkV9wJPILjkaOwZEqan7ZGq/JKC/Vj1tkMpm0YcMG9e/fv8D+kJAQdejQQQsWLJD0+43x9fXV6NGjNXHiRJv6zsnJ0QMPPKDo6Gg9+eSTN9xflKlTp2ratGmF9v/000/y8PCQJOXl5SkjI0NNmjQpML0LlYNhGDKbzXJ2di52Wl5eXp7MZrPc3d11+fJl9enTR6NGjdKjjz5aqrFmZ2frl19+kZeXV4GiIMovi8WijIwMeXl5ycmpQg+CRTlFjsGRyC84EvkFRyPH4EgVNb8yMzPVokULZWRkyNPTs9h2FXqk1I3k5uYqKSlJL730knWfk5OTwsPDrSNubsQwDEVGRiosLKxA4am4/cV56aWXNHbsWOv2pUuX5OvrK29vb+sPKDs7W5mZmXJxcZGLS6X+0dzWrlfkSU9PV+/evWU2m5Wdna1+/fpp8ODBpb62lIuLi5ycnFSnTh0KpBWExWKRyWSSt7d3hfqPFSoOcgyORH7BkcgvOBo5BkeqqPll69+Rlbry8dtvv8lsNqtevXoF9terV08//PCDTX3s3LlTa9asUZs2baxrVq1cuVIZGRlF7r/2lLo/c3Nzsz697Y+cnJysieXk5CSTyWR9oXIxDMP6cy3u51uvXj3r0/zK0rUc/GN+ovzjZwZHI8fgSOQXHIn8gqORY3CkiphftsZa7opSEydO1MyZM6/b5ujRo7rnnntKJZ7777+/2LmQjprTWUlmVKICIwcBAAAAAI5W7opS48aNU2Rk5HXb3HnnnTb1VbduXTk7O+vs2bMF9p89e1b169e3N0SHcXZ2lvT7tMOqVauWcTS4neXm5kr6v5wEAAAAAKCklbuilLe3t7y9vUukL1dXVwUHByshIcG6ALrFYlFCQoKee+65ErlGSXJxcVG1atV07tw5ValSpUINzcONGYah/Px8ubi4lOvpmRaLRefOnVO1atVY2wwAAAAA4DAV+i/OrKwsHT9+3Lqdmpqq5ORk1a5dW40bN5YkjR07VkOHDlX79u3VsWNHzZs3T5cvX9awYcPKKuximUwm3XHHHUpNTdUvv/xS1uGghF17jOe1tcPKMycnJzVu3LjcxwkAAAAAqLgqdFFq//796tatm3X72tPthg4dqri4OEnSoEGDdO7cOU2ePFlnzpxRYGCgtmzZUmjx8/LC1dVVzZs3t06fQuVhsVh0/vx51alTp9yPgnN1dS33MQIAAAAAKrYKXZQKDQ21aUHm5557rlxO1yuOk5OTzY9PRMVhsVhUpUoVubu7U/ABAAAAANz2+MsYAAAAAAAApa5Cj5SqyK6N8Lp06VIZR4LSYrFYlJmZyUgpOAT5BUcjx+BI5BccifyCo5FjcKSKml/Xah03mt1GUaqMZGZmSpJ8fX3LOBIAAAAAAICSl5mZKS8vr2KPmwxbFmVCibNYLDp9+rQ8PDx4wtlt4tKlS/L19dWpU6fk6elZ1uGgkiG/4GjkGByJ/IIjkV9wNHIMjlRR88swDGVmZqpBgwbXHeHFSKky4uTkpEaNGpV1GCgDnp6eFerLBBUL+QVHI8fgSOQXHIn8gqORY3Ckiphf1xshdU3FmZAIAAAAAACASoOiFAAAAAAAAEodRSmglLi5uWnKlClyc3Mr61BQCZFfcDRyDI5EfsGRyC84GjkGR6rs+cVC5wAAAAAAACh1jJQCAAAAAABAqaMoBQAAAAAAgFJHUQoAAAAAAACljqIUAAAAAAAASh1FKQAAAAAAAJQ6ilJAOZSamqpu3brJ399fAQEBunz5clmHhEroypUratKkicaPH1/WoaASOXXqlEJDQ+Xv7682bdpo3bp1ZR0SKrgvvvhCd999t5o3b65ly5aVdTioZPjOQmngdy44SmX4u9FkGIZR1kEAKKhr1656/fXX1blzZ6Wnp8vT01MuLi5lHRYqmUmTJun48ePy9fXV22+/XdbhoJL43//+p7NnzyowMFBnzpxRcHCwfvrpJ1WvXr2sQ0MFlJ+fL39/fyUmJsrLy0vBwcH65ptvVKdOnbIODZUE31koDfzOBUepDH83MlIKKGcOHz6sKlWqqHPnzpKk2rVrV7gvFpR/x44d0w8//KBevXqVdSioZO644w4FBgZKkurXr6+6desqPT29bINChbV37161atVKDRs2VI0aNdSrVy9t3bq1rMNCJcJ3FhyN37ngKJXl70aKUsBN2rFjhx588EE1aNBAJpNJGzduLNRm4cKFatq0qdzd3RUSEqK9e/fa3P+xY8dUo0YNPfjggwoKCtKMGTNKMHpUBI7OMUkaP3683nzzzRKKGBVJaeTXNUlJSTKbzfL19b3FqFFR3Wq+nT59Wg0bNrRuN2zYUL/++mtphI4KoiS/0/jOwp+VRH7xOxeKc6v5VVn+bqQoBdyky5cvq23btlq4cGGRx9esWaOxY8dqypQpOnDggNq2bauIiAilpaVZ2wQGBqp169aFXqdPn1Z+fr6+/vpr/fOf/9SuXbu0bds2bdu2rbQ+HsoBR+fYp59+qhYtWqhFixal9ZFQjjg6v65JT0/XkCFDFBsb6/DPhPKrJPINuJ6SyjG+s1CUW80vfufC9dxqflWavxsNAHaTZGzYsKHAvo4dOxrPPvusddtsNhsNGjQw3nzzTZv6/Oabb4wePXpYt2fNmmXMmjWrROJFxeOIHJs4caLRqFEjo0mTJkadOnUMT09PY9q0aSUZNioIR+SXYRhGdna20blzZ2PFihUlFSoqAXvybefOnUb//v2tx1944QVj9erVpRIvKh57v9P4zoIt7MkvfueCrezJr8rydyMjpYASlJubq6SkJIWHh1v3OTk5KTw8XLt27bKpjw4dOigtLU0XLlyQxWLRjh071LJlS0eFjAqmJHLszTff1KlTp3TixAm9/fbbio6O1uTJkx0VMiqQksgvwzAUGRmpsLAwPfnkk44KFZWALfnWsWNHHTp0SL/++quysrK0efNmRURElFXIqGBsyTG+s2AvW/KL37lgL1vyq7L83UhRCihBv/32m8xms+rVq1dgf7169XTmzBmb+nBxcdGMGTPUpUsXtWnTRs2bN1ffvn0dES4qoJLIMaA4JZFfO3fu1Jo1a7Rx40YFBgYqMDBQBw8edES4qOBsyTcXFxfNmTNH3bp1U2BgoMaNG8eT92AzW3KM7yzYi9/J4Ei2/jeyMvzdWPGWZgduA7169eIJHSgVkZGRZR0CKpn7779fFoulrMNAJdKvXz/169evrMNAJcV3FkoLv3PBESrD342MlAJKUN26deXs7KyzZ88W2H/27FnVr1+/jKJCZUKOwZHIL5Qm8g2ORo7BkcgvONLtlF8UpYAS5OrqquDgYCUkJFj3WSwWJSQkqFOnTmUYGSoLcgyORH6hNJFvcDRyDI5EfsGRbqf8YvoecJOysrJ0/Phx63ZqaqqSk5NVu3ZtNW7cWGPHjtXQoUPVvn17dezYUfPmzdPly5c1bNiwMowaFQk5Bkciv1CayDc4GjkGRyK/4Ejk1/+vrB//B1Q0iYmJhqRCr6FDh1rbzJ8/32jcuLHh6upqdOzY0di9e3fZBYwKhxyDI5FfKE3kGxyNHIMjkV9wJPLrdybDMAwH170AAAAAAACAAlhTCgAAAAAAAKWOohQAAAAAAABKHUUpAAAAAAAAlDqKUgAAAAAAACh1FKUAAAAAAABQ6ihKAQAAAAAAoNRRlAIAAAAAAECpoygFAAAAAACAUkdRCgAAAAAAAKWOohQAAMAtioyMVNOmTcs6jELWrl2r2rVrKysrq6xDuSXnz59X9erV9e9//7usQwEAACWIohQAAEARTCaTTa+vvvqqrEMtktls1pQpUzR69GjVqFGjrMO5JXXq1FFUVJReffXVsg4FAACUIJNhGEZZBwEAAFDerFq1qsD2ihUrtG3bNq1cubLA/gceeEC1a9eWxWKRm5tbaYZ4XRs3btQjjzyiU6dOqWHDhmUdzi07evSo/P39lZCQoLCwsLIOBwAAlACKUgAAADZ47rnntHDhQlWUX50eeughpaen6+uvvy7rUIp15coVVatWzeb2AQEBateunVasWOHAqAAAQGlh+h4AAMAt+vOaUidOnJDJZNLbb7+thQsX6s4771S1atXUo0cPnTp1SoZh6LXXXlOjRo1UtWpVawHpzzZv3qzOnTurevXq8vDwUJ8+fXT48OEbxpOdna0tW7YoPDy8wP6uXbuqbdu2RZ5z9913KyIiwrptsVg0b948tWrVSu7u7qpXr56efvppXbhwocB5n376qfr06aMGDRrIzc1Nd911l1577TWZzeYC7UJDQ9W6dWslJSWpS5cuqlatml5++WVJ0v79+xUREaG6deuqatWq8vPz01NPPVUoxgceeECff/55hSkMAgCA63Mp6wAAAAAqq9WrVys3N1ejR49Wenq6Zs2apUcffVRhYWH66quvFBMTo+PHj2v+/PkaP368li9fbj135cqVGjp0qCIiIjRz5kxduXJFixYt0v33369vv/32ugurJyUlKTc3V0FBQQX2P/nkk4qOjtahQ4fUunVr6/59+/bpp59+0iuvvGLd9/TTTysuLk7Dhg3T888/r9TUVC1YsEDffvutdu7cqSpVqkiS4uLiVKNGDY0dO1Y1atTQ9u3bNXnyZF26dEmzZ88ucP3z58+rV69e+tvf/qYnnnhC9erVU1pamnr06CFvb29NnDhRNWvW1IkTJ/TJJ58U+lzBwcGaO3euDh8+XCB+AABQQRkAAAC4oWeffdYo7lenoUOHGk2aNLFup6amGpIMb29v4+LFi9b9L730kiHJaNu2rZGXl2fdP3jwYMPV1dXIzs42DMMwMjMzjZo1axrR0dEFrnPmzBnDy8ur0P4/W7ZsmSHJOHjwYIH9Fy9eNNzd3Y2YmJgC+59//nmjevXqRlZWlmEYhvH1118bkozVq1cXaLdly5ZC+69cuVLo+k8//bRRrVo16+cxDMPo2rWrIclYvHhxgbYbNmwwJBn79u277mcyDMP45ptvDEnGmjVrbtgWAACUf0zfAwAAcJCBAwfKy8vLuh0SEiJJeuKJJ+Ti4lJgf25urn799VdJ0rZt23Tx4kUNHjxYv/32m/Xl7OyskJAQJSYmXve658+flyTVqlWrwH4vLy899NBD+vDDD61T4Mxms9asWaP+/furevXqkqR169bJy8tLDzzwQIHrBwcHq0aNGgWuX7VqVev7zMxM/fbbb+rcubOuXLmiH374ocD13dzcNGzYsAL7atasKUn64osvlJeXd93Pde3z/Pbbb9dtBwAAKgam7wEAADhI48aNC2xfK1D5+voWuf/aek3Hjh2TpGKfMufp6WnT9Y0i1l4aMmSI1qxZo6+//lpdunRRfHy8zp49qyeffNLa5tixY8rIyJCPj0+R/aalpVnfHz58WK+88oq2b9+uS5cuFWiXkZFRYLthw4ZydXUtsK9r164aMGCApk2bprlz5yo0NFT9+/fXY489Vuhphtc+j8lksuHTAwCA8o6iFAAAgIM4Ozvf1P5rRReLxSLp93Wl6tevX6jdH0dZFaVOnTqSfi9yNWrUqMCxiIgI1atXT6tWrVKXLl20atUq1a9fv8Ci6BaLRT4+Plq9enWR/Xt7e0uSLl68qK5du8rT01PTp0/XXXfdJXd3dx04cEAxMTHWz3HNH0dVXWMymfTxxx9r9+7d+vzzz/Xll1/qqaee0pw5c7R7927VqFHD2vZa0a5u3brX/fwAAKBioCgFAABQztx1112SJB8fn0JP0LPFPffcI0lKTU1VQEBAgWPOzs567LHHFBcXp5kzZ2rjxo2Kjo4uUCi76667FB8fr7/85S9FFpKu+eqrr3T+/Hl98skn6tKli3V/amrqTcd877336t5779Ubb7yhf/3rX3r88cf10UcfKSoqqlC/LVu2vOn+AQBA+cOaUgAAAOVMRESEPD09NWPGjCLXWTp37tx1zw8ODparq6v2799f5PEnn3xSFy5c0NNPP62srCw98cQTBY4/+uijMpvNeu211wqdm5+fr4sXL0r6vxFff5wmmJubq3/+85/Xje+PLly4UGiaYWBgoCQpJyenwP6kpCR5eXmpVatWNvcPAADKL0ZKAQAAlDOenp5atGiRnnzySQUFBelvf/ubvL29dfLkSW3atEl/+ctftGDBgmLPd3d3V48ePRQfH6/p06cXOt6uXTu1bt1a69atU8uWLRUUFFTgeNeuXfX000/rzTffVHJysnr06KEqVaro2LFjWrdunf7xj3/or3/9q+677z7VqlVLQ4cO1fPPPy+TyaSVK1cWuZZVcT744AP985//1MMPP6y77rpLmZmZWrp0qTw9PdW7d+8Cbbdt26YHH3yQNaUAAKgkKEoBAACUQ4899pgaNGigt956S7Nnz1ZOTo4aNmyozp07F3qCXVGeeuopDRgwQKdOnSq0sLr0+4LnL774YoEFzv9o8eLFCg4O1pIlS/Tyyy/LxcVFTZs21RNPPKG//OUvkn5fu+qLL77QuHHj9Morr6hWrVp64okn1L17d0VERNj0Obt27aq9e/fqo48+0tmzZ+Xl5aWOHTtq9erV8vPzs7b74YcfdOjQIc2bN8+mfgEAQPlnMm7mf2UBAACgQjCbzfL399ejjz5a5DS8f/zjH/r73/+uEydOFHpKYHk0ZswY7dixQ0lJSYyUAgCgkqAoBQAAUEmtWbNGzzzzjE6ePFngKXaGYaht27aqU6eOEhMTyzBC25w/f15NmjTR2rVrC03pAwAAFRdFKQAAgNvE5cuX9dlnnykxMVFLly7Vp59+qn79+pV1WAAA4DZFUQoAAOA2ceLECfn5+almzZoaNWqU3njjjbIOCQAA3MYoSgEAAAAAAKDUOZV1AAAAAAAAALj9UJQCAAAAAABAqaMoBQAAAAAAgFJHUQoAAAAAAACljqIUAAAAAAAASh1FKQAAAAAAAJQ6ilIAAAAAAAAodRSlAAAAAAAAUOr+H64tdnEzYX0OAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 1, figsize=(12, 10))\n",
    "\n",
    "# Plot heating processes\n",
    "time = physics[\"Time\"]\n",
    "for col in heating_cols:\n",
    "    # Only plot processes with significant contribution\n",
    "    max_val = heating[col].abs().max()\n",
    "    if max_val > 1e-30:  # Filter out negligible contributions\n",
    "        label = col.replace(\"_heating\", \"\").replace(\"_\", \" \")\n",
    "        axes[0].plot(time, heating[col], label=label, linewidth=2, alpha=0.7)\n",
    "\n",
    "axes[0].set_xlabel(\"Time (years)\", fontsize=12)\n",
    "axes[0].set_ylabel(\"Heating Rate (erg cm⁻³ s⁻¹)\", fontsize=12)\n",
    "axes[0].set_xscale(\"log\")\n",
    "axes[0].set_yscale(\"symlog\", linthresh=1e-30)\n",
    "axes[0].set_title(\"Heating Processes\", fontsize=14)\n",
    "axes[0].legend(fontsize=8, loc=\"best\")\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# Plot cooling processes (select major ones to avoid cluttering)\n",
    "for col in cooling_cols:\n",
    "    max_val = heating[col].abs().max()\n",
    "    if max_val > 1e-40:\n",
    "        label = col.replace(\"_cooling\", \"\").replace(\"_\", \" \")\n",
    "        axes[1].plot(time, heating[col], label=label, linewidth=2, alpha=0.7)\n",
    "\n",
    "axes[1].set_xlabel(\"Time (years)\", fontsize=12)\n",
    "axes[1].set_ylabel(\"Cooling Rate (erg cm⁻³ s⁻¹)\", fontsize=12)\n",
    "axes[1].set_xscale(\"log\")\n",
    "axes[1].set_yscale(\"symlog\", linthresh=1e-30)\n",
    "axes[1].set_title(\"Major Cooling Processes\", fontsize=14)\n",
    "axes[1].legend(fontsize=8, loc=\"best\")\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f60a8160",
   "metadata": {},
   "source": [
    "## Example 4: Writing Heating Rates to a File\n",
    "\n",
    "You can also save heating and cooling rates directly to a file during the model run using the `heatingFile` parameter. This requires not running any other cells to memory before!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "93074962",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:54.490217Z",
     "iopub.status.busy": "2026-01-27T12:49:54.490029Z",
     "iopub.status.idle": "2026-01-27T12:49:54.493015Z",
     "shell.execute_reply": "2026-01-27T12:49:54.492281Z"
    }
   },
   "outputs": [],
   "source": [
    "# You can uncomment the cel below to run a model to disk.\n",
    "\n",
    "# # Run model with heating file output\n",
    "# param_dict_with_file = param_dict_heating.copy()\n",
    "# param_dict_with_file[\"outputFile\"] = \"../examples/test-output/heating_demo.dat\"\n",
    "# param_dict_with_file[\"heatingFile\"] = \"../examples/test-output/heating_rates.dat\"\n",
    "\n",
    "\n",
    "# result = uclchem.model.cloud(\n",
    "#     param_dict=param_dict_with_file, out_species=[\"CO\", \"H2O\", \"OH\"]\n",
    "# )\n",
    "\n",
    "# print(f\"Model completed with flag: {result[0]}\")\n",
    "# print(f\"Final CO abundance: {result[1]:.2e}\")\n",
    "# print(f\"Final H2O abundance: {result[2]:.2e}\")\n",
    "# print(f\"Final OH abundance: {result[3]:.2e}\")\n",
    "\n",
    "# # Read the heating file\n",
    "# if os.path.exists(\"../examples/test-output/heating_rates.dat\"):\n",
    "#     print(\"\\nHeating rates file created successfully!\")\n",
    "#     heating_df = pd.read_csv(\"../examples/test-output/heating_rates.dat\")\n",
    "#     print(f\"File contains {len(heating_df)} time steps\")\n",
    "#     print(f\"Columns: {heating_df.columns.tolist()[:10]}...\")  # Show first 10 columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e7ba9c7",
   "metadata": {},
   "source": [
    "## Example 5: Different Physical Conditions\n",
    "\n",
    "Let's explore how heating and cooling behave under different physical conditions. We'll compare a dense, cold core with a less dense, warmer environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1ced1b19",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-01-27T12:49:54.494625Z",
     "iopub.status.busy": "2026-01-27T12:49:54.494464Z",
     "iopub.status.idle": "2026-01-27T12:52:22.911237Z",
     "shell.execute_reply": "2026-01-27T12:52:22.910552Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running cold core model...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running warm cloud model...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Cold core flag: -1, Warm cloud flag: -1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Final temperatures:\n",
      "  Cold core: 11.06 K\n",
      "  Warm cloud: 20.32 K\n"
     ]
    }
   ],
   "source": [
    "# Dense, cold core (like Example 1)\n",
    "param_cold_core = {\n",
    "    \"initialDens\": 1e5,\n",
    "    \"initialTemp\": 10.0,\n",
    "    \"finalTime\": 1.0e6,\n",
    "    \"baseAv\": 20.0,\n",
    "    \"rout\": 0.05,\n",
    "    \"freefall\": False,\n",
    "    \"heatingFlag\": True,\n",
    "}\n",
    "\n",
    "# Less dense, warmer cloud\n",
    "param_warm_cloud = {\n",
    "    \"initialDens\": 1e3,\n",
    "    \"initialTemp\": 30.0,\n",
    "    \"finalTime\": 1.0e6,\n",
    "    \"baseAv\": 5.0,\n",
    "    \"rout\": 0.5,\n",
    "    \"freefall\": False,\n",
    "    \"heatingFlag\": True,\n",
    "}\n",
    "\n",
    "# Run both models\n",
    "print(\"Running cold core model...\")\n",
    "cloud_cold = uclchem.model.Cloud(param_dict=param_cold_core)\n",
    "phys_cold, abund_cold = cloud_cold.get_dataframes(joined=False)\n",
    "_, _, rates_cold = cloud_cold.get_dataframes(joined=False, with_rates=True)\n",
    "_, _, heating_cold = cloud_cold.get_dataframes(joined=False, with_heating=True)\n",
    "flag_cold = 0 if cloud_cold.has_attr(\"_data\") else -1\n",
    "\n",
    "print(\"Running warm cloud model...\")\n",
    "cloud_warm = uclchem.model.Cloud(param_dict=param_warm_cloud)\n",
    "phys_warm, abund_warm = cloud_warm.get_dataframes(joined=False)\n",
    "_, _, rates_warm = cloud_warm.get_dataframes(joined=False, with_rates=True)\n",
    "_, _, heating_warm = cloud_warm.get_dataframes(joined=False, with_heating=True)\n",
    "flag_warm = 0 if cloud_warm.has_attr(\"_data\") else -1\n",
    "\n",
    "print(f\"\\nCold core flag: {flag_cold}, Warm cloud flag: {flag_warm}\")\n",
    "\n",
    "# Compare temperature evolution\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "axes[0].plot(\n",
    "    phys_cold[\"Time\"],\n",
    "    phys_cold[\"gasTemp\"],\n",
    "    label=f\"Dense Core (n={param_cold_core['initialDens']:.0e})\",\n",
    "    linewidth=2,\n",
    ")\n",
    "axes[0].plot(\n",
    "    phys_warm[\"Time\"],\n",
    "    phys_warm[\"gasTemp\"],\n",
    "    label=f\"Diffuse Cloud (n={param_warm_cloud['initialDens']:.0e})\",\n",
    "    linewidth=2,\n",
    ")\n",
    "axes[0].set_xlabel(\"Time (years)\", fontsize=12)\n",
    "axes[0].set_ylabel(\"Gas Temperature (K)\", fontsize=12)\n",
    "axes[0].set_xscale(\"log\")\n",
    "axes[0].set_title(\"Temperature Evolution\", fontsize=14)\n",
    "axes[0].legend()\n",
    "axes[0].grid(True, alpha=0.3)\n",
    "\n",
    "# Compare CO abundance\n",
    "axes[1].plot(phys_cold[\"Time\"], abund_cold[\"CO\"], label=\"Dense Core\", linewidth=2)\n",
    "axes[1].plot(phys_warm[\"Time\"], abund_warm[\"CO\"], label=\"Diffuse Cloud\", linewidth=2)\n",
    "axes[1].set_xlabel(\"Time (years)\", fontsize=12)\n",
    "axes[1].set_ylabel(\"CO Abundance\", fontsize=12)\n",
    "axes[1].set_xscale(\"log\")\n",
    "axes[1].set_yscale(\"log\")\n",
    "axes[1].set_title(\"CO Abundance\", fontsize=14)\n",
    "axes[1].legend()\n",
    "axes[1].grid(True, alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\nFinal temperatures:\")\n",
    "print(f\"  Cold core: {phys_cold['gasTemp'].iloc[-1]:.2f} K\")\n",
    "print(f\"  Warm cloud: {phys_warm['gasTemp'].iloc[-1]:.2f} K\")"
   ]
  },
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   "id": "317ec9e4",
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   "source": [
    "## Summary of Key Heating and Cooling Processes\n",
    "\n",
    "UCLCHEM includes the following heating and cooling mechanisms:\n",
    "\n",
    "### Major Heating Processes:\n",
    "1. **Photoelectric heating** - from PAHs and dust grains (Bakes & Tielens 1994)\n",
    "2. **H₂ formation heating** - energy released during H₂ formation on grains\n",
    "3. **H₂ photodissociation heating** - kinetic energy from photodissociation\n",
    "4. **Cosmic ray heating** - direct and indirect (via ionization)\n",
    "5. **Chemical reaction enthalpy** - exothermic reactions (optional, requires network configuration)\n",
    "6. **X-ray heating** - in environments with X-ray sources\n",
    "7. **Turbulent heating** - dissipation of turbulent energy\n",
    "8. **Viscous heating** - for shock models\n",
    "\n",
    "### Major Cooling Processes:\n",
    "1. **Molecular line cooling** - CO, H₂O, OH, and other molecules\n",
    "2. **Atomic fine structure cooling** - C⁺, O, C, etc.\n",
    "3. **Dust continuum cooling** - gas-grain collisional cooling\n",
    "4. **H₂ line cooling** - rovibrational transitions\n",
    "5. **Recombination cooling** - electronic to kinetic energy\n",
    "6. **Ly-α cooling** - Lyman-alpha photon emission\n",
    "\n",
    "### Key Parameters:\n",
    "- `heatingFlag`: Enable/disable all heating processes (default: `True`)\n",
    "- `heatingFile`: Path to write detailed heating/cooling rates\n",
    "- `initialTemp`: Starting gas temperature\n",
    "- `baseAv`: Visual extinction (affects radiation field attenuation)\n",
    "- `zeta`: Cosmic ray ionization rate\n",
    "\n",
    "For a complete list of processes and their equations, see the `HEATING_COOLING_SUMMARY.md` documentation file."
   ]
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    "## Advanced: Chemical Reaction Enthalpy\n",
    "\n",
    "UCLCHEM can optionally include the enthalpy changes from chemical reactions as a heating/cooling source. This requires configuring the chemical network at build time using MakeRates.\n",
    "\n",
    "**Note:** This feature requires rebuilding UCLCHEM with specific settings in the `user_settings.yaml` file. The main settings are:\n",
    "\n",
    "- `add_delta_enthalpy`: Can be `False`, `GAS`, or `ALL`\n",
    "  - `False`: No reaction enthalpy (default)\n",
    "  - `GAS`: Include enthalpy from gas-phase reactions only\n",
    "  - `ALL`: Include enthalpy from all reactions (gas + surface)\n",
    "\n",
    "To enable reaction enthalpy:\n",
    "```yaml\n",
    "# In Makerates/user_settings.yaml\n",
    "add_delta_enthalpy: GAS\n",
    "```\n",
    "\n",
    "Then rebuild:\n",
    "```bash\n",
    "cd Makerates\n",
    "python MakeRates.py\n",
    "cd ..\n",
    "pip install .\n",
    "```\n",
    "\n",
    "For more details, see the `heating_cooling_benchmarks/` directory which contains examples with different enthalpy configurations."
   ]
  },
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   "cell_type": "markdown",
   "id": "9ce7510c",
   "metadata": {},
   "source": [
    "## Tips for Using Heating and Cooling\n",
    "\n",
    "1. **Always check convergence**: Use `return_dataframe=True` and inspect temperature evolution to ensure physical results\n",
    "\n",
    "2. **Monitor element conservation**: Use `uclchem.analysis.check_element_conservation()` to verify model accuracy\n",
    "\n",
    "3. **Save heating rates for analysis**: Use `heatingFile` parameter to save detailed heating/cooling contributions\n",
    "\n",
    "4. **Choose appropriate tolerances**: If you see unphysical temperature spikes, try adjusting `reltol` and `abstol` parameters\n",
    "\n",
    "5. **Consider your environment**: Different astrophysical environments have different dominant heating/cooling processes:\n",
    "   - **Dense cores**: Line cooling (CO, H₂O) dominates\n",
    "   - **Diffuse clouds**: Photoelectric heating and fine-structure cooling\n",
    "   - **Shock regions**: Viscous/turbulent heating important\n",
    "   - **PDRs**: Strong FUV field means photoelectric heating dominates\n",
    "\n",
    "6. **Radiation field matters**: The `baseAv` parameter controls UV attenuation, which significantly affects photoelectric heating and photodissociation rates\n",
    "\n",
    "## Next Steps\n",
    "\n",
    "- Check out [7_heating_cooling_settings.ipynb](7_heating_cooling_settings.ipynb) for more advanced configuration options\n",
    "- See `HEATING_COOLING_SUMMARY.md` for detailed equations and references\n",
    "- Explore the `heating_cooling_benchmarks/` directory for systematic comparisons"
   ]
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