diff --git a/data/.ipynb_checkpoints/data_exploration-checkpoint.ipynb b/data/.ipynb_checkpoints/data_exploration-checkpoint.ipynb
new file mode 100644
index 0000000..5f2e91d
--- /dev/null
+++ b/data/.ipynb_checkpoints/data_exploration-checkpoint.ipynb
@@ -0,0 +1,608 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data1 = pd.read_csv('./set1_log.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\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>metric_type</th>\n",
+       "      <th>sensor_type</th>\n",
+       "      <th>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>1.049204</td>\n",
+       "      <td>1.365288</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.167861</td>\n",
+       "      <td>0.757524</td>\n",
+       "      <td>7.107009</td>\n",
+       "      <td>1.312864</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541760</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>1.754769</td>\n",
+       "      <td>0.305894</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  metric_type sensor_type        px        py        vx        vy        ro  \\\n",
+       "0  prediction        none  0.362243  0.630340  1.000000  1.000000  0.000000   \n",
+       "1      update       radar  0.362243  0.630340  1.000000  1.000000  0.727013   \n",
+       "2  prediction        none  1.167861  0.757524  7.107009  1.312864  0.000000   \n",
+       "3  prediction        none  1.673310  0.528441  9.541760 -0.006111  0.000000   \n",
+       "4      update       radar  1.673310  0.528441  9.541759 -0.006111  1.754769   \n",
+       "\n",
+       "        phi    ro_dot  \n",
+       "0  0.000000  0.000000  \n",
+       "1  1.049204  1.365288  \n",
+       "2  0.000000  0.000000  \n",
+       "3  0.000000  0.000000  \n",
+       "4  0.305894  9.096972  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "\n",
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+       "        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>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-3.178678</td>\n",
+       "      <td>5.724229</td>\n",
+       "      <td>-0.300265</td>\n",
+       "      <td>0.345483</td>\n",
+       "      <td>17.536219</td>\n",
+       "      <td>0.378578</td>\n",
+       "      <td>0.713055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>15.269733</td>\n",
+       "      <td>9.170799</td>\n",
+       "      <td>3.785738</td>\n",
+       "      <td>3.286478</td>\n",
+       "      <td>7.180043</td>\n",
+       "      <td>2.022048</td>\n",
+       "      <td>3.499638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-26.701517</td>\n",
+       "      <td>-9.652123</td>\n",
+       "      <td>-5.257915</td>\n",
+       "      <td>-5.088145</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>-3.125148</td>\n",
+       "      <td>-4.759574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-16.632866</td>\n",
+       "      <td>-0.439151</td>\n",
+       "      <td>-3.682999</td>\n",
+       "      <td>-2.771378</td>\n",
+       "      <td>11.861627</td>\n",
+       "      <td>-2.534892</td>\n",
+       "      <td>-2.888640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-3.041072</td>\n",
+       "      <td>5.795924</td>\n",
+       "      <td>-1.866272</td>\n",
+       "      <td>0.879739</td>\n",
+       "      <td>18.810812</td>\n",
+       "      <td>0.752738</td>\n",
+       "      <td>0.767197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>10.554383</td>\n",
+       "      <td>11.737187</td>\n",
+       "      <td>3.965151</td>\n",
+       "      <td>3.234874</td>\n",
+       "      <td>24.110367</td>\n",
+       "      <td>2.000041</td>\n",
+       "      <td>4.279956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>20.415537</td>\n",
+       "      <td>21.148319</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>5.226411</td>\n",
+       "      <td>26.726410</td>\n",
+       "      <td>3.136907</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               px          py          vx          vy          ro         phi  \\\n",
+       "count  249.000000  249.000000  249.000000  249.000000  249.000000  249.000000   \n",
+       "mean    -3.178678    5.724229   -0.300265    0.345483   17.536219    0.378578   \n",
+       "std     15.269733    9.170799    3.785738    3.286478    7.180043    2.022048   \n",
+       "min    -26.701517   -9.652123   -5.257915   -5.088145    0.727013   -3.125148   \n",
+       "25%    -16.632866   -0.439151   -3.682999   -2.771378   11.861627   -2.534892   \n",
+       "50%     -3.041072    5.795924   -1.866272    0.879739   18.810812    0.752738   \n",
+       "75%     10.554383   11.737187    3.965151    3.234874   24.110367    2.000041   \n",
+       "max     20.415537   21.148319    9.541759    5.226411   26.726410    3.136907   \n",
+       "\n",
+       "           ro_dot  \n",
+       "count  249.000000  \n",
+       "mean     0.713055  \n",
+       "std      3.499638  \n",
+       "min     -4.759574  \n",
+       "25%     -2.888640  \n",
+       "50%      0.767197  \n",
+       "75%      4.279956  \n",
+       "max      9.096972  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data1[data1[\"sensor_type\"]==\"radar\"].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\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>metric_type</th>\n",
+       "      <th>sensor_type</th>\n",
+       "      <th>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>1.049204</td>\n",
+       "      <td>1.365288</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.167861</td>\n",
+       "      <td>0.757524</td>\n",
+       "      <td>7.107009</td>\n",
+       "      <td>1.312864</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541760</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>1.754769</td>\n",
+       "      <td>0.305894</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  metric_type sensor_type        px        py        vx        vy        ro  \\\n",
+       "0  prediction        none  0.362243  0.630340  1.000000  1.000000  0.000000   \n",
+       "1      update       radar  0.362243  0.630340  1.000000  1.000000  0.727013   \n",
+       "2  prediction        none  1.167861  0.757524  7.107009  1.312864  0.000000   \n",
+       "3  prediction        none  1.673310  0.528441  9.541760 -0.006111  0.000000   \n",
+       "4      update       radar  1.673310  0.528441  9.541759 -0.006111  1.754769   \n",
+       "\n",
+       "        phi    ro_dot  \n",
+       "0  0.000000  0.000000  \n",
+       "1  1.049204  1.365288  \n",
+       "2  0.000000  0.000000  \n",
+       "3  0.000000  0.000000  \n",
+       "4  0.305894  9.096972  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data2 = pd.read_csv('./set1_log.csv')\n",
+    "data2.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\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>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-3.178678</td>\n",
+       "      <td>5.724229</td>\n",
+       "      <td>-0.300265</td>\n",
+       "      <td>0.345483</td>\n",
+       "      <td>17.536219</td>\n",
+       "      <td>0.378578</td>\n",
+       "      <td>0.713055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>15.269733</td>\n",
+       "      <td>9.170799</td>\n",
+       "      <td>3.785738</td>\n",
+       "      <td>3.286478</td>\n",
+       "      <td>7.180043</td>\n",
+       "      <td>2.022048</td>\n",
+       "      <td>3.499638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-26.701517</td>\n",
+       "      <td>-9.652123</td>\n",
+       "      <td>-5.257915</td>\n",
+       "      <td>-5.088145</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>-3.125148</td>\n",
+       "      <td>-4.759574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-16.632866</td>\n",
+       "      <td>-0.439151</td>\n",
+       "      <td>-3.682999</td>\n",
+       "      <td>-2.771378</td>\n",
+       "      <td>11.861627</td>\n",
+       "      <td>-2.534892</td>\n",
+       "      <td>-2.888640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-3.041072</td>\n",
+       "      <td>5.795924</td>\n",
+       "      <td>-1.866272</td>\n",
+       "      <td>0.879739</td>\n",
+       "      <td>18.810812</td>\n",
+       "      <td>0.752738</td>\n",
+       "      <td>0.767197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>10.554383</td>\n",
+       "      <td>11.737187</td>\n",
+       "      <td>3.965151</td>\n",
+       "      <td>3.234874</td>\n",
+       "      <td>24.110367</td>\n",
+       "      <td>2.000041</td>\n",
+       "      <td>4.279956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>20.415537</td>\n",
+       "      <td>21.148319</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>5.226411</td>\n",
+       "      <td>26.726410</td>\n",
+       "      <td>3.136907</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               px          py          vx          vy          ro         phi  \\\n",
+       "count  249.000000  249.000000  249.000000  249.000000  249.000000  249.000000   \n",
+       "mean    -3.178678    5.724229   -0.300265    0.345483   17.536219    0.378578   \n",
+       "std     15.269733    9.170799    3.785738    3.286478    7.180043    2.022048   \n",
+       "min    -26.701517   -9.652123   -5.257915   -5.088145    0.727013   -3.125148   \n",
+       "25%    -16.632866   -0.439151   -3.682999   -2.771378   11.861627   -2.534892   \n",
+       "50%     -3.041072    5.795924   -1.866272    0.879739   18.810812    0.752738   \n",
+       "75%     10.554383   11.737187    3.965151    3.234874   24.110367    2.000041   \n",
+       "max     20.415537   21.148319    9.541759    5.226411   26.726410    3.136907   \n",
+       "\n",
+       "           ro_dot  \n",
+       "count  249.000000  \n",
+       "mean     0.713055  \n",
+       "std      3.499638  \n",
+       "min     -4.759574  \n",
+       "25%     -2.888640  \n",
+       "50%      0.767197  \n",
+       "75%      4.279956  \n",
+       "max      9.096972  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data2[data2[\"sensor_type\"]==\"radar\"].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/data/data_exploration.ipynb b/data/data_exploration.ipynb
new file mode 100644
index 0000000..5f2e91d
--- /dev/null
+++ b/data/data_exploration.ipynb
@@ -0,0 +1,608 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data1 = pd.read_csv('./set1_log.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\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>metric_type</th>\n",
+       "      <th>sensor_type</th>\n",
+       "      <th>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>1.049204</td>\n",
+       "      <td>1.365288</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.167861</td>\n",
+       "      <td>0.757524</td>\n",
+       "      <td>7.107009</td>\n",
+       "      <td>1.312864</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541760</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>1.754769</td>\n",
+       "      <td>0.305894</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  metric_type sensor_type        px        py        vx        vy        ro  \\\n",
+       "0  prediction        none  0.362243  0.630340  1.000000  1.000000  0.000000   \n",
+       "1      update       radar  0.362243  0.630340  1.000000  1.000000  0.727013   \n",
+       "2  prediction        none  1.167861  0.757524  7.107009  1.312864  0.000000   \n",
+       "3  prediction        none  1.673310  0.528441  9.541760 -0.006111  0.000000   \n",
+       "4      update       radar  1.673310  0.528441  9.541759 -0.006111  1.754769   \n",
+       "\n",
+       "        phi    ro_dot  \n",
+       "0  0.000000  0.000000  \n",
+       "1  1.049204  1.365288  \n",
+       "2  0.000000  0.000000  \n",
+       "3  0.000000  0.000000  \n",
+       "4  0.305894  9.096972  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data1.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\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>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-3.178678</td>\n",
+       "      <td>5.724229</td>\n",
+       "      <td>-0.300265</td>\n",
+       "      <td>0.345483</td>\n",
+       "      <td>17.536219</td>\n",
+       "      <td>0.378578</td>\n",
+       "      <td>0.713055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>15.269733</td>\n",
+       "      <td>9.170799</td>\n",
+       "      <td>3.785738</td>\n",
+       "      <td>3.286478</td>\n",
+       "      <td>7.180043</td>\n",
+       "      <td>2.022048</td>\n",
+       "      <td>3.499638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-26.701517</td>\n",
+       "      <td>-9.652123</td>\n",
+       "      <td>-5.257915</td>\n",
+       "      <td>-5.088145</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>-3.125148</td>\n",
+       "      <td>-4.759574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-16.632866</td>\n",
+       "      <td>-0.439151</td>\n",
+       "      <td>-3.682999</td>\n",
+       "      <td>-2.771378</td>\n",
+       "      <td>11.861627</td>\n",
+       "      <td>-2.534892</td>\n",
+       "      <td>-2.888640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-3.041072</td>\n",
+       "      <td>5.795924</td>\n",
+       "      <td>-1.866272</td>\n",
+       "      <td>0.879739</td>\n",
+       "      <td>18.810812</td>\n",
+       "      <td>0.752738</td>\n",
+       "      <td>0.767197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>10.554383</td>\n",
+       "      <td>11.737187</td>\n",
+       "      <td>3.965151</td>\n",
+       "      <td>3.234874</td>\n",
+       "      <td>24.110367</td>\n",
+       "      <td>2.000041</td>\n",
+       "      <td>4.279956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>20.415537</td>\n",
+       "      <td>21.148319</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>5.226411</td>\n",
+       "      <td>26.726410</td>\n",
+       "      <td>3.136907</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               px          py          vx          vy          ro         phi  \\\n",
+       "count  249.000000  249.000000  249.000000  249.000000  249.000000  249.000000   \n",
+       "mean    -3.178678    5.724229   -0.300265    0.345483   17.536219    0.378578   \n",
+       "std     15.269733    9.170799    3.785738    3.286478    7.180043    2.022048   \n",
+       "min    -26.701517   -9.652123   -5.257915   -5.088145    0.727013   -3.125148   \n",
+       "25%    -16.632866   -0.439151   -3.682999   -2.771378   11.861627   -2.534892   \n",
+       "50%     -3.041072    5.795924   -1.866272    0.879739   18.810812    0.752738   \n",
+       "75%     10.554383   11.737187    3.965151    3.234874   24.110367    2.000041   \n",
+       "max     20.415537   21.148319    9.541759    5.226411   26.726410    3.136907   \n",
+       "\n",
+       "           ro_dot  \n",
+       "count  249.000000  \n",
+       "mean     0.713055  \n",
+       "std      3.499638  \n",
+       "min     -4.759574  \n",
+       "25%     -2.888640  \n",
+       "50%      0.767197  \n",
+       "75%      4.279956  \n",
+       "max      9.096972  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data1[data1[\"sensor_type\"]==\"radar\"].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\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>metric_type</th>\n",
+       "      <th>sensor_type</th>\n",
+       "      <th>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>0.362243</td>\n",
+       "      <td>0.630340</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>1.049204</td>\n",
+       "      <td>1.365288</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.167861</td>\n",
+       "      <td>0.757524</td>\n",
+       "      <td>7.107009</td>\n",
+       "      <td>1.312864</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>prediction</td>\n",
+       "      <td>none</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541760</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>update</td>\n",
+       "      <td>radar</td>\n",
+       "      <td>1.673310</td>\n",
+       "      <td>0.528441</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>-0.006111</td>\n",
+       "      <td>1.754769</td>\n",
+       "      <td>0.305894</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  metric_type sensor_type        px        py        vx        vy        ro  \\\n",
+       "0  prediction        none  0.362243  0.630340  1.000000  1.000000  0.000000   \n",
+       "1      update       radar  0.362243  0.630340  1.000000  1.000000  0.727013   \n",
+       "2  prediction        none  1.167861  0.757524  7.107009  1.312864  0.000000   \n",
+       "3  prediction        none  1.673310  0.528441  9.541760 -0.006111  0.000000   \n",
+       "4      update       radar  1.673310  0.528441  9.541759 -0.006111  1.754769   \n",
+       "\n",
+       "        phi    ro_dot  \n",
+       "0  0.000000  0.000000  \n",
+       "1  1.049204  1.365288  \n",
+       "2  0.000000  0.000000  \n",
+       "3  0.000000  0.000000  \n",
+       "4  0.305894  9.096972  "
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data2 = pd.read_csv('./set1_log.csv')\n",
+    "data2.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\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>px</th>\n",
+       "      <th>py</th>\n",
+       "      <th>vx</th>\n",
+       "      <th>vy</th>\n",
+       "      <th>ro</th>\n",
+       "      <th>phi</th>\n",
+       "      <th>ro_dot</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "      <td>249.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>-3.178678</td>\n",
+       "      <td>5.724229</td>\n",
+       "      <td>-0.300265</td>\n",
+       "      <td>0.345483</td>\n",
+       "      <td>17.536219</td>\n",
+       "      <td>0.378578</td>\n",
+       "      <td>0.713055</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>15.269733</td>\n",
+       "      <td>9.170799</td>\n",
+       "      <td>3.785738</td>\n",
+       "      <td>3.286478</td>\n",
+       "      <td>7.180043</td>\n",
+       "      <td>2.022048</td>\n",
+       "      <td>3.499638</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>-26.701517</td>\n",
+       "      <td>-9.652123</td>\n",
+       "      <td>-5.257915</td>\n",
+       "      <td>-5.088145</td>\n",
+       "      <td>0.727013</td>\n",
+       "      <td>-3.125148</td>\n",
+       "      <td>-4.759574</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>-16.632866</td>\n",
+       "      <td>-0.439151</td>\n",
+       "      <td>-3.682999</td>\n",
+       "      <td>-2.771378</td>\n",
+       "      <td>11.861627</td>\n",
+       "      <td>-2.534892</td>\n",
+       "      <td>-2.888640</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>-3.041072</td>\n",
+       "      <td>5.795924</td>\n",
+       "      <td>-1.866272</td>\n",
+       "      <td>0.879739</td>\n",
+       "      <td>18.810812</td>\n",
+       "      <td>0.752738</td>\n",
+       "      <td>0.767197</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>10.554383</td>\n",
+       "      <td>11.737187</td>\n",
+       "      <td>3.965151</td>\n",
+       "      <td>3.234874</td>\n",
+       "      <td>24.110367</td>\n",
+       "      <td>2.000041</td>\n",
+       "      <td>4.279956</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>20.415537</td>\n",
+       "      <td>21.148319</td>\n",
+       "      <td>9.541759</td>\n",
+       "      <td>5.226411</td>\n",
+       "      <td>26.726410</td>\n",
+       "      <td>3.136907</td>\n",
+       "      <td>9.096972</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               px          py          vx          vy          ro         phi  \\\n",
+       "count  249.000000  249.000000  249.000000  249.000000  249.000000  249.000000   \n",
+       "mean    -3.178678    5.724229   -0.300265    0.345483   17.536219    0.378578   \n",
+       "std     15.269733    9.170799    3.785738    3.286478    7.180043    2.022048   \n",
+       "min    -26.701517   -9.652123   -5.257915   -5.088145    0.727013   -3.125148   \n",
+       "25%    -16.632866   -0.439151   -3.682999   -2.771378   11.861627   -2.534892   \n",
+       "50%     -3.041072    5.795924   -1.866272    0.879739   18.810812    0.752738   \n",
+       "75%     10.554383   11.737187    3.965151    3.234874   24.110367    2.000041   \n",
+       "max     20.415537   21.148319    9.541759    5.226411   26.726410    3.136907   \n",
+       "\n",
+       "           ro_dot  \n",
+       "count  249.000000  \n",
+       "mean     0.713055  \n",
+       "std      3.499638  \n",
+       "min     -4.759574  \n",
+       "25%     -2.888640  \n",
+       "50%      0.767197  \n",
+       "75%      4.279956  \n",
+       "max      9.096972  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data2[data2[\"sensor_type\"]==\"radar\"].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/data/set1_log.csv b/data/set1_log.csv
new file mode 100644
index 0000000..d8bb9aa
--- /dev/null
+++ b/data/set1_log.csv
@@ -0,0 +1,748 @@
+metric_type,sensor_type,px,py,vx,vy,ro,phi,ro_dot
+prediction,none,0.362243,0.630340,1.000000,1.000000,0,0,0
+update,radar,0.362243,0.630340,1.000000,1.000000,0.727013,1.049204,1.365288
+prediction,none,1.167861,0.757524,7.107009,1.312864,0,0,0
+prediction,none,1.673310,0.528441,9.541760,-0.006111,0,0,0
+update,radar,1.673310,0.528441,9.541759,-0.006111,1.754769,0.305894,9.096972
+prediction,none,1.272956,0.663154,4.515409,2.532624,0,0,0
+prediction,none,1.596399,0.762810,4.816007,2.121984,0,0,0
+update,radar,1.596399,0.762810,4.816007,2.121984,1.769285,0.445756,5.260283
+prediction,none,1.976963,0.675651,5.301550,1.178577,0,0,0
+prediction,none,2.288169,0.723639,5.406968,1.054135,0,0,0
+update,radar,2.288169,0.723639,5.406968,1.054135,2.399869,0.306300,5.473161
+prediction,none,2.529593,0.726807,5.237527,0.846112,0,0,0
+prediction,none,2.818465,0.754477,5.292923,0.767386,0,0,0
+update,radar,2.818465,0.754476,5.292923,0.767386,2.917701,0.261558,5.311337
+prediction,none,3.103347,0.732858,5.305495,0.536329,0,0,0
+prediction,none,3.354049,0.744884,5.283793,0.496364,0,0,0
+update,radar,3.354048,0.744884,5.283793,0.496363,3.435767,0.218538,5.265733
+prediction,none,3.656858,0.655225,5.340503,0.105602,0,0,0
+prediction,none,3.978381,0.577405,5.452643,-0.172434,0,0,0
+update,radar,3.978381,0.577405,5.452643,-0.172434,4.020063,0.144129,5.371340
+prediction,none,4.259252,0.598390,5.477919,-0.081440,0,0,0
+prediction,none,4.542868,0.587815,5.495336,-0.102603,0,0,0
+update,radar,4.542869,0.587815,5.495336,-0.102603,4.580740,0.128678,5.436736
+prediction,none,4.790828,0.606661,5.334138,-0.043420,0,0,0
+prediction,none,4.970251,0.697596,5.174719,0.232642,0,0,0
+update,radar,4.970251,0.697596,5.174719,0.232642,5.018967,0.139443,5.156826
+prediction,none,5.216139,0.688014,5.036676,0.157885,0,0,0
+prediction,none,5.523114,0.676256,5.131245,0.099638,0,0,0
+update,radar,5.523114,0.676256,5.131245,0.099638,5.564361,0.121835,5.105318
+prediction,none,5.792134,0.683604,5.268531,0.117975,0,0,0
+prediction,none,6.095856,0.691767,5.335176,0.122148,0,0,0
+update,radar,6.095856,0.691767,5.335176,0.122148,6.134982,0.112998,5.314925
+prediction,none,6.327701,0.622851,5.137880,-0.093614,0,0,0
+prediction,none,6.579297,0.726539,5.115164,0.195297,0,0,0
+update,radar,6.579298,0.726539,5.115164,0.195297,6.619291,0.109982,5.105695
+prediction,none,6.826748,0.757440,5.063002,0.248186,0,0,0
+prediction,none,7.073006,0.755775,5.053194,0.211674,0,0,0
+update,radar,7.073007,0.755775,5.053194,0.211674,7.113271,0.106449,5.047081
+prediction,none,7.306143,0.735766,4.880702,0.118798,0,0,0
+prediction,none,7.515045,0.825335,4.813117,0.336249,0,0,0
+update,radar,7.515045,0.825335,4.813117,0.336249,7.560230,0.109386,4.821058
+prediction,none,7.832824,0.839076,5.158957,0.346262,0,0,0
+prediction,none,8.088683,0.812607,5.160043,0.234821,0,0,0
+update,radar,8.088683,0.812607,5.160043,0.234821,8.129399,0.100126,5.157671
+prediction,none,8.327454,0.828345,4.978868,0.232338,0,0,0
+prediction,none,8.562001,0.846334,4.954307,0.249253,0,0,0
+update,radar,8.562001,0.846334,4.954308,0.249253,8.603728,0.098528,4.954799
+prediction,none,8.849380,0.949585,5.232486,0.497549,0,0,0
+prediction,none,9.090369,1.015224,5.194460,0.600731,0,0,0
+update,radar,9.090368,1.015224,5.194460,0.600731,9.146883,0.111220,5.229042
+prediction,none,9.385228,1.054248,5.243085,0.619941,0,0,0
+prediction,none,9.624487,1.086274,5.204877,0.624131,0,0,0
+update,radar,9.624487,1.086274,5.204877,0.624131,9.685595,0.112390,5.242037
+prediction,none,9.908336,1.166166,5.255362,0.745495,0,0,0
+prediction,none,10.189163,1.312316,5.275458,1.012243,0,0,0
+update,radar,10.189162,1.312316,5.275458,1.012244,10.273325,0.128090,5.361544
+prediction,none,10.421645,1.399964,5.018176,1.080675,0,0,0
+prediction,none,10.640220,1.482533,4.961470,1.153727,0,0,0
+update,radar,10.640220,1.482533,4.961470,1.153727,10.743006,0.138442,5.073214
+prediction,none,10.858389,1.555710,4.726494,1.169216,0,0,0
+prediction,none,11.074801,1.575340,4.697068,1.077250,0,0,0
+update,radar,11.074800,1.575340,4.697069,1.077250,11.186282,0.141298,4.801965
+prediction,none,11.355699,1.616475,4.888459,1.056493,0,0,0
+prediction,none,11.641765,1.661599,4.958967,1.032432,0,0,0
+update,radar,11.641765,1.661599,4.958967,1.032432,11.759745,0.141770,5.055094
+prediction,none,11.868316,1.700803,4.862381,0.995978,0,0,0
+prediction,none,12.093871,1.772309,4.830734,1.050582,0,0,0
+update,radar,12.093871,1.772309,4.830734,1.050582,12.223043,0.145510,4.932015
+prediction,none,12.362996,1.860613,4.992443,1.151813,0,0,0
+prediction,none,12.607867,1.887090,4.987749,1.077807,0,0,0
+update,radar,12.607867,1.887090,4.987750,1.077807,12.748311,0.148573,5.092345
+prediction,none,12.872850,1.935037,5.094338,1.073579,0,0,0
+prediction,none,13.068545,2.100173,4.983831,1.348077,0,0,0
+update,radar,13.068545,2.100173,4.983831,1.348077,13.236223,0.159342,5.134593
+prediction,none,13.347422,2.212569,5.133551,1.470142,0,0,0
+prediction,none,13.549914,2.378366,5.032747,1.697786,0,0,0
+update,radar,13.549914,2.378366,5.032747,1.697786,13.757064,0.173756,5.250484
+prediction,none,13.704270,2.511192,4.617425,1.782873,0,0,0
+prediction,none,13.954837,2.643887,4.645581,1.883195,0,0,0
+update,radar,13.954838,2.643887,4.645581,1.883195,14.203086,0.187241,4.914937
+prediction,none,14.172768,2.743062,4.584630,1.890485,0,0,0
+prediction,none,14.400888,2.921431,4.572649,2.088942,0,0,0
+update,radar,14.400887,2.921431,4.572649,2.088942,14.694227,0.200149,4.896678
+prediction,none,14.663002,3.027720,4.743491,2.111477,0,0,0
+prediction,none,14.868185,3.090308,4.694831,2.016297,0,0,0
+update,radar,14.868185,3.090308,4.694831,2.016297,15.185946,0.204929,5.006906
+prediction,none,15.105664,3.245439,4.743948,2.156371,0,0,0
+prediction,none,15.316123,3.469524,4.683267,2.434671,0,0,0
+update,radar,15.316123,3.469524,4.683267,2.434671,15.704178,0.222768,5.105434
+prediction,none,15.518045,3.621634,4.469158,2.476342,0,0,0
+prediction,none,15.732417,3.834803,4.441312,2.687292,0,0,0
+update,radar,15.732417,3.834803,4.441312,2.687292,16.193043,0.239089,4.951375
+prediction,none,15.941715,3.943423,4.368037,2.614994,0,0,0
+prediction,none,16.163879,4.097119,4.371102,2.667595,0,0,0
+update,radar,16.163879,4.097118,4.371102,2.667595,16.675053,0.248245,4.892543
+prediction,none,16.352491,4.227815,4.151699,2.623373,0,0,0
+prediction,none,16.544073,4.453894,4.109802,2.847507,0,0,0
+update,radar,16.544073,4.453894,4.109802,2.847507,17.133112,0.262979,4.708740
+prediction,none,16.760262,4.598554,4.130096,2.850848,0,0,0
+prediction,none,16.932336,4.782625,4.064370,2.955444,0,0,0
+update,radar,16.932337,4.782625,4.064370,2.955443,17.594816,0.275284,4.714687
+prediction,none,17.073410,4.928483,3.682636,2.885004,0,0,0
+prediction,none,17.225033,5.199283,3.605637,3.185048,0,0,0
+update,radar,17.225033,5.199283,3.605637,3.185048,17.992617,0.293148,4.372192
+prediction,none,17.399338,5.331084,3.553420,3.107718,0,0,0
+prediction,none,17.548661,5.538540,3.495351,3.234874,0,0,0
+update,radar,17.548662,5.538540,3.495351,3.234874,18.401928,0.305716,4.306898
+prediction,none,17.708135,5.660633,3.394783,3.120025,0,0,0
+prediction,none,17.895640,5.795924,3.429364,3.067715,0,0,0
+update,radar,17.895639,5.795924,3.429364,3.067715,18.810812,0.313213,4.207735
+prediction,none,18.042474,5.952784,3.267873,3.042752,0,0,0
+prediction,none,18.207201,6.191736,3.253962,3.240361,0,0,0
+update,radar,18.207201,6.191736,3.253962,3.240361,19.231218,0.327802,4.123971
+prediction,none,18.364942,6.376504,3.223975,3.288280,0,0,0
+prediction,none,18.474885,6.673616,3.108985,3.604688,0,0,0
+update,radar,18.474884,6.673616,3.108985,3.604688,19.643282,0.346641,4.148718
+prediction,none,18.608002,6.860045,2.977187,3.590814,0,0,0
+prediction,none,18.751101,7.002270,2.974551,3.508058,0,0,0
+update,radar,18.751101,7.002270,2.974550,3.508058,20.015882,0.357396,4.013836
+prediction,none,18.910610,7.189955,3.021305,3.544728,0,0,0
+prediction,none,19.110685,7.345401,3.112052,3.480673,0,0,0
+update,radar,19.110685,7.345400,3.112052,3.480673,20.473719,0.366952,4.153636
+prediction,none,19.194008,7.499970,2.782684,3.376263,0,0,0
+prediction,none,19.264465,7.839633,2.625150,3.781554,0,0,0
+update,radar,19.264465,7.839633,2.625150,3.781554,20.798544,0.386482,3.856910
+prediction,none,19.391648,8.020903,2.596954,3.755381,0,0,0
+prediction,none,19.456952,8.276557,2.467581,3.927735,0,0,0
+update,radar,19.456951,8.276558,2.467581,3.927735,21.144133,0.402191,3.808136
+prediction,none,19.559248,8.464664,2.427710,3.914105,0,0,0
+prediction,none,19.648944,8.613886,2.381704,3.820750,0,0,0
+update,radar,19.648945,8.613886,2.381704,3.820750,21.454138,0.413157,3.715343
+prediction,none,19.743755,8.785785,2.236133,3.736944,0,0,0
+prediction,none,19.902717,8.991877,2.316025,3.764168,0,0,0
+update,radar,19.902718,8.991877,2.316025,3.764168,21.839689,0.424343,3.660406
+prediction,none,19.977514,9.180739,2.102562,3.713843,0,0,0
+prediction,none,20.095845,9.464357,2.102867,3.926198,0,0,0
+update,radar,20.095846,9.464357,2.102867,3.926198,22.212994,0.440148,3.575288
+prediction,none,20.139374,9.646362,1.805371,3.822002,0,0,0
+prediction,none,20.207902,9.943552,1.740263,4.063207,0,0,0
+update,radar,20.207903,9.943552,1.740263,4.063207,22.521847,0.457278,3.355399
+prediction,none,20.268702,10.193770,1.687751,4.181000,0,0,0
+prediction,none,20.301962,10.525567,1.564351,4.467862,0,0,0
+update,radar,20.301962,10.525567,1.564350,4.467862,22.868258,0.478299,3.445219
+prediction,none,20.310225,10.727465,1.238763,4.334896,0,0,0
+prediction,none,20.356837,11.052721,1.182972,4.576972,0,0,0
+update,radar,20.356836,11.052721,1.182972,4.576972,23.163839,0.497414,3.223540
+prediction,none,20.376939,11.308272,1.041983,4.615043,0,0,0
+prediction,none,20.410477,11.561634,1.001859,4.670722,0,0,0
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diff --git a/data/set2_log.csv b/data/set2_log.csv
new file mode 100644
index 0000000..31c11e7
--- /dev/null
+++ b/data/set2_log.csv
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