Misc_plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "register_matplotlib_converters()\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>long</th>\n",
       "      <th>lat</th>\n",
       "      <th>aperture</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ambrym</td>\n",
       "      <td>168.12</td>\n",
       "      <td>-16.25</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>anatahan</td>\n",
       "      <td>145.67</td>\n",
       "      <td>16.35</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>aoba</td>\n",
       "      <td>167.83</td>\n",
       "      <td>-15.40</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>arenal</td>\n",
       "      <td>-84.71</td>\n",
       "      <td>10.46</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>asama</td>\n",
       "      <td>138.53</td>\n",
       "      <td>36.40</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       name    long    lat  aperture\n",
       "0    ambrym  168.12 -16.25       0.2\n",
       "1  anatahan  145.67  16.35       0.2\n",
       "2      aoba  167.83 -15.40       0.2\n",
       "3    arenal  -84.71  10.46       0.2\n",
       "4     asama  138.53  36.40       0.2"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_loc = pd.read_csv(\"data/volcanoes.txt\", delimiter='\\s', header=None, engine='python');\n",
    "\n",
    "df_loc.columns = [\"name\", \"long\", \"lat\", \"aperture\"]\n",
    "\n",
    "df_loc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "target = df_loc[df_loc.name == 'kilauea'].values.flatten()\n",
    "data_dir = f\"data/{target[0]}/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\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>index</th>\n",
       "      <th>UNIX_Time</th>\n",
       "      <th>Sat</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>...</th>\n",
       "      <th>SunZen</th>\n",
       "      <th>SunAzi</th>\n",
       "      <th>Line</th>\n",
       "      <th>Samp</th>\n",
       "      <th>Ratio</th>\n",
       "      <th>Glint</th>\n",
       "      <th>Excess</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Err</th>\n",
       "      <th>datetime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>71860</td>\n",
       "      <td>951512100</td>\n",
       "      <td>T</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>55</td>\n",
       "      <td>-155.367538</td>\n",
       "      <td>19.778879</td>\n",
       "      <td>...</td>\n",
       "      <td>37.76</td>\n",
       "      <td>137.23</td>\n",
       "      <td>327</td>\n",
       "      <td>205</td>\n",
       "      <td>-0.58</td>\n",
       "      <td>75.460</td>\n",
       "      <td>57.119</td>\n",
       "      <td>276.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2000-02-25 20:55:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>71859</td>\n",
       "      <td>951512100</td>\n",
       "      <td>T</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "      <td>20</td>\n",
       "      <td>55</td>\n",
       "      <td>-155.351715</td>\n",
       "      <td>19.777077</td>\n",
       "      <td>...</td>\n",
       "      <td>37.76</td>\n",
       "      <td>137.25</td>\n",
       "      <td>327</td>\n",
       "      <td>206</td>\n",
       "      <td>-0.41</td>\n",
       "      <td>75.392</td>\n",
       "      <td>83.206</td>\n",
       "      <td>276.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2000-02-25 20:55:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>71858</td>\n",
       "      <td>951557099</td>\n",
       "      <td>T</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>-155.053894</td>\n",
       "      <td>19.342176</td>\n",
       "      <td>...</td>\n",
       "      <td>161.06</td>\n",
       "      <td>-59.89</td>\n",
       "      <td>1145</td>\n",
       "      <td>69</td>\n",
       "      <td>-0.79</td>\n",
       "      <td>137.327</td>\n",
       "      <td>11.860</td>\n",
       "      <td>289.2</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2000-02-26 09:25:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>71855</td>\n",
       "      <td>951600899</td>\n",
       "      <td>T</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>-155.027740</td>\n",
       "      <td>19.336313</td>\n",
       "      <td>...</td>\n",
       "      <td>31.05</td>\n",
       "      <td>151.53</td>\n",
       "      <td>1532</td>\n",
       "      <td>1148</td>\n",
       "      <td>-0.56</td>\n",
       "      <td>32.510</td>\n",
       "      <td>51.439</td>\n",
       "      <td>289.2</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2000-02-26 21:35:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>71857</td>\n",
       "      <td>951600899</td>\n",
       "      <td>T</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>35</td>\n",
       "      <td>-155.096741</td>\n",
       "      <td>19.372599</td>\n",
       "      <td>...</td>\n",
       "      <td>31.11</td>\n",
       "      <td>151.45</td>\n",
       "      <td>1530</td>\n",
       "      <td>1144</td>\n",
       "      <td>-0.26</td>\n",
       "      <td>32.356</td>\n",
       "      <td>114.117</td>\n",
       "      <td>288.4</td>\n",
       "      <td>4.7</td>\n",
       "      <td>2000-02-26 21:35:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   index  UNIX_Time Sat  Year  Month  Day  Hour  Minute   Longitude  \\\n",
       "0  71860  951512100   T  2000      2   25    20      55 -155.367538   \n",
       "1  71859  951512100   T  2000      2   25    20      55 -155.351715   \n",
       "2  71858  951557099   T  2000      2   26     9      25 -155.053894   \n",
       "3  71855  951600899   T  2000      2   26    21      35 -155.027740   \n",
       "4  71857  951600899   T  2000      2   26    21      35 -155.096741   \n",
       "\n",
       "    Latitude  ...  SunZen  SunAzi  Line  Samp  Ratio    Glint   Excess   Temp  \\\n",
       "0  19.778879  ...   37.76  137.23   327   205  -0.58   75.460   57.119  276.8   \n",
       "1  19.777077  ...   37.76  137.25   327   206  -0.41   75.392   83.206  276.8   \n",
       "2  19.342176  ...  161.06  -59.89  1145    69  -0.79  137.327   11.860  289.2   \n",
       "3  19.336313  ...   31.05  151.53  1532  1148  -0.56   32.510   51.439  289.2   \n",
       "4  19.372599  ...   31.11  151.45  1530  1144  -0.26   32.356  114.117  288.4   \n",
       "\n",
       "   Err            datetime  \n",
       "0  5.6 2000-02-25 20:55:00  \n",
       "1  5.6 2000-02-25 20:55:00  \n",
       "2  5.9 2000-02-26 09:25:00  \n",
       "3  5.9 2000-02-26 21:35:00  \n",
       "4  4.7 2000-02-26 21:35:00  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(data_dir+\"data.csv\", index_col=0)\n",
    "df[\"datetime\"] = pd.to_datetime(df[\"datetime\"])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spatial and Temporal Data around Target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(16,9))\n",
    "\n",
    "scatter = ax[0].scatter(df.Longitude, df.Latitude, c=df.datetime)#, cmap=plt.cm.autumn)\n",
    "cbar = fig.colorbar(scatter, ax=ax[0], orientation='horizontal')\n",
    "cbar.set_label('UNIX Time')\n",
    "\n",
    "#ax[0].add_artist(plt.Circle(target[1:3], target[3]/2., color=]'k', fill=False))\n",
    "ax[0].set_title(\"Spatial Measurements\")\n",
    "ax[0].set_xlabel(\"Longitude\")\n",
    "ax[0].set_ylabel(\"Latitude\")\n",
    "\n",
    "scatter = ax[1].plot_date(df.datetime, df.B21)\n",
    "\n",
    "ax[1].set_title(\"Temporal Measurements\")\n",
    "ax[1].set_xlabel(\"Date\")\n",
    "plt.xticks(rotation=20)\n",
    "ax[1].set_ylabel(\"B21\")\n",
    "\n",
    "fig.suptitle(f\"Measurements from {df.Year.min()}-{df.Month.min()}-{df.Day.min()} to {df.Year.max()}-{df.Month.max()}-{df.Day.max()}\")\n",
    "plt.savefig(f\"{data_dir}/spatial_temporal.png\", bbox_inches='tight', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Temperature Difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16, 9))\n",
    "ax = plt.gca()\n",
    "\n",
    "temp_diff_day = df[\"Temp\"][df[\"Hour\"].between(6, 18)].diff()\n",
    "temp_diff_night = df[\"Temp\"][~df[\"Hour\"].between(6, 18)].diff()\n",
    "\n",
    "day = ax.hist(temp_diff_day, color='r', label='Day', alpha=0.7, linewidth=1.2, edgecolor='k')\n",
    "night = ax.hist(temp_diff_night, color='b', label='Night', alpha=0.7, linewidth=1.2, edgecolor='k')\n",
    "\n",
    "ax.set_title(\"Temperature Difference\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:vp]",
   "language": "python",
   "name": "conda-env-vp-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}