docs/source/gallery/Example 3-Trajectory processing using TransBigData.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3 Trajectory processing using TransBigData"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "For vehicle trajectory data, the TransBigData library provides a comprehensive set of trajectory data processing methods starting from version 0.5.0 and above. These methods include preprocessing and drift correction of trajectory data, segmentation of stops and trips, grid-based representation, visualization, and more. This article will introduce how to use the TransBigData library for processing trajectory data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.5.0'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import transbigdata as tbd\n",
    "# ensure tbd version is above 0.5.0\n",
    "tbd.__version__"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trajectory Quality\n",
    "First, we read the data and observe the basic information to check for any missing values. Using the built-in methods of a DataFrame, we can easily view the basic information of the data, including data types, number of fields, number of rows, and the presence of missing values. The code is as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>time</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>OpenStatus</th>\n",
       "      <th>speed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>34745</td>\n",
       "      <td>2023-05-29 20:27:43</td>\n",
       "      <td>113.806847</td>\n",
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       "      <td>2023-05-29 20:24:07</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>2023-05-29 20:10:06</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>544994</th>\n",
       "      <td>28265</td>\n",
       "      <td>2023-05-29 21:35:13</td>\n",
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       "      <td>18</td>\n",
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       "      <td>22.690100</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>544997</th>\n",
       "      <td>28265</td>\n",
       "      <td>2023-05-29 21:19:12</td>\n",
       "      <td>114.352600</td>\n",
       "      <td>22.728399</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>544998</th>\n",
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       "      <td>2023-05-29 19:08:06</td>\n",
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       "      <td>22.621700</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>544999 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id                time         lon        lat  OpenStatus  speed\n",
       "0       34745 2023-05-29 20:27:43  113.806847  22.623249           1     27\n",
       "1       34745 2023-05-29 20:24:07  113.809898  22.627399           0      0\n",
       "2       34745 2023-05-29 20:24:27  113.809898  22.627399           0      0\n",
       "3       34745 2023-05-29 20:22:07  113.811348  22.628067           0      0\n",
       "4       34745 2023-05-29 20:10:06  113.819885  22.647800           0     54\n",
       "...       ...                 ...         ...        ...         ...    ...\n",
       "544994  28265 2023-05-29 21:35:13  114.321503  22.709499           0     18\n",
       "544995  28265 2023-05-29 09:08:02  114.322701  22.681700           0      0\n",
       "544996  28265 2023-05-29 09:14:31  114.336700  22.690100           0      0\n",
       "544997  28265 2023-05-29 21:19:12  114.352600  22.728399           0      0\n",
       "544998  28265 2023-05-29 19:08:06  114.137703  22.621700           0      0\n",
       "\n",
       "[544999 rows x 6 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the data\n",
    "data = pd.read_csv('data/TaxiData-Sample.csv', header=None)\n",
    "data.columns = ['id', 'time', 'lon', 'lat', 'OpenStatus', 'speed']\n",
    "# Convert the time format\n",
    "data['time'] = pd.to_datetime(data['time'])\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 544999 entries, 0 to 544998\n",
      "Data columns (total 6 columns):\n",
      " #   Column      Non-Null Count   Dtype         \n",
      "---  ------      --------------   -----         \n",
      " 0   id          544999 non-null  int64         \n",
      " 1   time        544999 non-null  datetime64[ns]\n",
      " 2   lon         544999 non-null  float64       \n",
      " 3   lat         544999 non-null  float64       \n",
      " 4   OpenStatus  544999 non-null  int64         \n",
      " 5   speed       544999 non-null  int64         \n",
      "dtypes: datetime64[ns](1), float64(2), int64(3)\n",
      "memory usage: 24.9 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In it, the data types of the data fields, the number of non-null values, and the memory usage are listed. In the \"Non-Null\" column, the number of non-null values for each field is listed. If the number of non-null values for a field is less than the total number of rows, it indicates the presence of missing values in that field."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will use TransBigData to generate a data quality report and observe the number of vehicles in the data, the observation time period, and the sampling interval:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Amount of data\n",
      "-----------------\n",
      "Total number of data items:  544999\n",
      "Total number of individuals:  180\n",
      "Data volume of individuals(Mean):  3027.7722\n",
      "Data volume of individuals(Upper quartile):  4056.25\n",
      "Data volume of individuals(Median):  2600.5\n",
      "Data volume of individuals(Lower quartile):  1595.75\n",
      "\n",
      "Data time period\n",
      "-----------------\n",
      "Start time:  2023-05-29 00:00:00\n",
      "End time:  2023-05-29 23:59:59\n",
      "\n",
      "Sampling interval\n",
      "-----------------\n",
      "Mean:  27.995 s\n",
      "Upper quartile:  30.0 s\n",
      "Median:  20.0 s\n",
      "Lower quartile:  15.0 s\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 2400x900 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate data quality report\n",
    "tbd.data_summary(data,col=['id', 'time'],show_sample_duration=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Redundancy Elimination\n",
    "\n",
    "Redundancy elimination is an important step in cleaning trajectory data. It reduces the data volume and improves data processing efficiency without affecting the information contained in the data. In practical trajectory data processing, you may encounter the following two types of redundancy:\n",
    "\n",
    "1. **Redundancy of Duplicate Data at the Same Moment**:\n",
    "\n",
    "In a trajectory dataset, there may be multiple trajectory data entries for the same vehicle at the same moment. This can happen when the sampling interval is too short compared to the precision of the time field in the dataset. For example, if the sampling interval is 1 second, but the time field in the dataset has a precision of 1 minute, it can result in multiple trajectory data entries for the same vehicle within the same minute. Not removing these redundant data can cause difficulties in subsequent processing. The method to eliminate this redundancy is straightforward: keep only one trajectory data entry for the same vehicle at the same moment.\n",
    "\n",
    "2. **Redundancy of Vehicle Stops**:\n",
    "\n",
    "In vehicle trajectory data, the sampling interval is usually very short, such as collecting data every few seconds. This means that data is continuously generated for vehicles, whether they are moving or stationary. In practical applications, the focus is often on the trajectory of vehicles during trips, rather than during stops. For each instance of a vehicle stopping, we only need to know the start and end times of the stop. The data generated during the middle part of the stop, at the same location, is redundant and can be removed to reduce the overall data size. For a sequence of consecutive n data entries (n>=3) with the same location, we only need to keep the first and last entries, as the intermediate data is redundant. In the code, it is sufficient to compare the vehicle ID and the latitude-longitude of each data entry with the previous and next trajectory entries. If they are the same, the data can be removed.\n",
    "\n",
    "However, the redundancy elimination method mentioned above for vehicle stops does not consider the information carried by fields other than the vehicle ID, time, and latitude-longitude. For example, in the case of taxi vehicles, passengers may board the taxi during a stop, changing the status from \"vacant\" to \"occupied.\" In such cases, this information needs to be preserved.\n",
    "\n",
    "TransBigData provides a function, `tbd.traj_clean_redundant()`, for trajectory data redundancy elimination. It can handle the mentioned redundancy situations and can also detect redundancy in fields other than the vehicle ID and latitude-longitude. The code is as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "544999"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data volume before Redundancy Elimination\n",
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "421099"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data redundancy removal to reduce data size and improve computational efficiency in subsequent steps\n",
    "#\n",
    "data = tbd.traj_clean_redundant(\n",
    "    data,\n",
    "    col=['id', 'time', 'lon', 'lat', 'speed']  # Apart from vehicle ID, time, longitude, and latitude, consider whether the speed field has redundancy\n",
    ")\n",
    "len(data)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code snippet performs data redundancy removal to reduce the data size and improve computational efficiency. The `traj_clean_redundant` function from the `tbd` module is used for this purpose. The function takes the `data` variable as input and specifies the columns (`col`) to consider for redundancy removal, including the vehicle ID, time, longitude, latitude, and optionally the speed field. The result is stored back in the `data` variable, and the length of the updated data is outputted."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Drift Cleaning\n",
    "\n",
    "In vehicle trajectory data, deviations and errors may occur between the collected vehicle trajectory data and the actual situations due to factors such as errors in data collection devices, environmental interferences, device malfunctions, unstable GPS signals, insufficient satellite coverage, and signal obstructions. This results in a discrepancy between the actual positions and the collected positions of the trajectory data, known as data drift in vehicle trajectory data. In the data, data drift is manifested by significant distances between the trajectory data points and the actual positions, often accompanied by sudden jumps. This drift can affect subsequent spatial analysis and spatial statistics, requiring the cleaning of vehicle trajectory data to ensure data accuracy and usability.\n",
    "\n",
    "To clean vehicle trajectory data for drift, one approach is to remove trajectory data points outside the defined study area. The study area can be defined in two ways: either by specifying the bottom-left and top-right coordinates to determine the boundary range (bounds) or by using a geographic information file (geojson or shapefile) that represents the study area.\n",
    "\n",
    "To remove drift data using a geojson or shapefile, you first need to read the geojson or shapefile as a `GeoDataFrame` type in GeoPandas. Then, you can use the `intersects()` method provided by GeoPandas to determine if the trajectory data is within the study area. However, this method requires performing spatial geometry matching for each trajectory data point, which can be time-consuming for large datasets. The `tbd.clean_outofshape()` method provided in the TransBigData package offers a more efficient approach. It first maps the trajectory data to the corresponding grid using built-in grid partitioning methods and then performs spatial matching based on the grid, significantly improving the cleaning efficiency.\n",
    "\n",
    "Here is an example code snippet using TransBigData's `clean_outofshape()` method for data drift cleaning:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Read the research area range\n",
    "sz = gpd.read_file('Data/sz.json')\n",
    "sz.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "419448"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data drift removal\n",
    "# Removing data outside the study area\n",
    "data = tbd.clean_outofshape(data, sz, col=['lon', 'lat'], accuracy=500)\n",
    "len(data)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cleaning trajectory drift within the study area requires assessing and cleaning based on the continuous changes in trajectories. There are three common approaches for cleaning:\n",
    "\n",
    "1. Velocity threshold method: If the velocity between the current trajectory data and the previous and subsequent trajectories exceeds a threshold, it is considered drift.\n",
    "2. Distance threshold method: If the distance between the current trajectory data and the previous and subsequent trajectories exceeds a threshold, it is considered drift.\n",
    "3. Angle threshold method: If the angle formed by the previous, current, and subsequent trajectories is smaller than a threshold, it is considered drift.\n",
    "\n",
    "In TransBigData, the `tbd.traj_clean_drift()` method is provided to clean trajectory data for multiple vehicles. This method integrates distance, velocity, and angle thresholds into a single function.\n",
    "\n",
    "Here is an example code snippet using TransBigData's `traj_clean_drift()` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "405286"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Drift cleaning within the study area using speed, distance, and angle as criteria\n",
    "data = tbd.traj_clean_drift(\n",
    "    data,  # Trajectory data, can include data for multiple vehicles, distinguished by ID\n",
    "    col=['id', 'time', 'lon', 'lat'],  # Column names of the trajectory data\n",
    "    speedlimit=80,  # Speed threshold in km/h, set to None to skip speed-based filtering\n",
    "    dislimit=4000,  # Distance threshold in meters, set to None to skip distance-based filtering\n",
    "    anglelimit=30)  # Angle threshold in degrees, set to None to skip angle-based filtering\n",
    "len(data)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stops and Trips Extracting\n",
    "\n",
    "In long-term continuous observations of vehicle trajectory data, a common requirement is to extract the stops and trips from the trajectory data. The stops can be analyzed to determine the duration and location of the vehicle's parking, while the trips can be further analyzed to extract information such as the origin and destination of each trip, the travel path, travel duration, travel distance, and travel speed. In this section, we will explain how to identify stops and trips from vehicle trajectories, extract the trajectory information for each trip, and generate trajectory lines.\n",
    "\n",
    "In vehicle trajectory data, stops and trips are typically identified using a time threshold method. The approach is as follows: to avoid fluctuations in the trajectory data, we need to predefine a grid in the geographical space. If the duration between two consecutive data points exceeds our set threshold (usually 30 minutes), we consider it as a stop. The time period between two stops is considered a trip, as shown in the figure below.\n",
    "\n",
    "![StopsandTrips](./images/stops_and_trips.png \"Stops and Trips\")\n",
    "\n",
    "After cleaning the trajectory data, we need to define a grid coordinate system and convert the trajectory data into grid-based representation to identify stops and trips.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'slon': 113.75,\n",
       " 'slat': 22.4,\n",
       " 'deltalon': 0.0009743362892898221,\n",
       " 'deltalat': 0.0008993210412845813,\n",
       " 'theta': 0,\n",
       " 'method': 'rect',\n",
       " 'gridsize': 100}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the grid parameters\n",
    "bounds = [113.75, 22.4, 114.62, 22.86]\n",
    "params = tbd.area_to_params(bounds,accuracy = 100)\n",
    "params"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The identification of stops and trips has been provided in the TransBigData package through the `tbd.traj_stay_move()` function. Here is the code:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(545, 725)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Identify stay and move\n",
    "stay, move = tbd.traj_stay_move(data, params, col=['id', 'time', 'lon', 'lat'], activitytime=1800) \n",
    "len(stay), len(move)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the code, `data` represents the cleaned trajectory data. The `traj_stay_move()` function is used to identify stops and trips based on the specified stop threshold. It returns two outputs: `stops` and `trips`, which contain the identified stops and trips, respectively. You can utilize these data for further analysis.\n",
    "\n",
    "Note: The `tbd.traj_stay_move()` function does not remove trips with a duration of 0. This is because some trajectory data may have long sampling intervals, which may not capture the travel process between two stops. As a result, the calculated duration for those trips would be 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
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       "\n",
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       "[545 rows x 9 columns]"
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     "execution_count": 13,
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  {
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       "           id  SLONCOL  SLATCOL               stime        slon       slat  \\\n",
       "0       22396      253      326 2023-05-29 00:00:29  113.996719  22.693333   \n",
       "23320   22396      262      284 2023-05-29 07:56:32  114.005547  22.655800   \n",
       "51327   22396       50      429 2023-05-29 16:44:57  113.798630  22.786167   \n",
       "54670   22413      145      431 2023-05-29 00:00:09  113.891403  22.787300   \n",
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       "...       ...      ...      ...                 ...         ...        ...   \n",
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       "\n",
       "                     etime        elon       elat  ELONCOL  ELATCOL  duration  \\\n",
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       "23320  2023-05-29 12:51:23  113.798630  22.786167     50.0    429.0   17691.0   \n",
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       "54670  2023-05-29 01:25:13  113.891701  22.787399    145.0    431.0     152.0   \n",
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       "\n",
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       "\n",
       "[725 rows x 13 columns]"
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     "execution_count": 14,
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   "metadata": {},
   "source": [
    "Based on the stops and trips information, you can slice the trajectory data to extract the trajectory points during stops and trips. Since you have already performed redundancy elimination earlier, the redundant trajectory points during stops have been removed. As a result, the trajectory data during stops will have significantly fewer data points compared to the trajectory data during trips."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trajectory slicing"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By the preceding code, parking and travel information has been successfully extracted from the data. However, in the obtained travel information, only the time, latitude, and longitude information of the starting and ending points of each trip are included, without the travel trajectory information. In order to further analyze the travel trajectories of vehicles, it is necessary to extract the trajectory data from the time periods of each trip, that is, slice the trajectory dataset based on the travel information. In the previously calculated travel information, each travel record has a travel ID, start time, and end time columns. The result of trajectory slicing is to extract the trajectory points during the trip and assign a travel ID label to each trajectory point.\n",
    "\n",
    "The idea of trajectory slicing is illustrated in the diagram below. A flag column is created for the trajectory data to mark whether each row is within the desired time period for slicing. Then, each travel record in the travel data is decomposed into a start time record (flag label of 1) and an end time record (flag label of -1), which are inserted into the trajectory data. Next, the flag column is grouped and summed by vehicle to obtain the flag1 column. In the result, the rows where the flag1 column value is 1 (travel) and the flag column value is 0 (non-temporarily inserted data) are the desired trajectory data.\n",
    "\n",
    "![trajslice](./images/trajslice.png \"trajslice\")\n",
    "\n",
    "The code for slicing the trajectory data can be performed by using `tbd.traj_slice`, the code example is as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
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       "           id                time         lon        lat  OpenStatus  speed  \\\n",
       "23320   22396 2023-05-29 06:10:09  114.005547  22.655800         0.0    1.0   \n",
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       "\n",
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract trajectory points during parking\n",
    "stay_points = tbd.traj_slice(data, stay, traj_col=['id', 'time'], slice_col=[\n",
    "                             'id', 'stime', 'etime', 'stayid'])\n",
    "stay_points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       "           id                time         lon        lat  OpenStatus  speed  \\\n",
       "0       22396 2023-05-29 00:00:29  113.996719  22.693333         1.0   20.0   \n",
       "27      22396 2023-05-29 00:01:01  113.995514  22.695032         1.0   34.0   \n",
       "28      22396 2023-05-29 00:01:09  113.995430  22.695766         1.0   41.0   \n",
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       "30      22396 2023-05-29 00:02:21  113.995430  22.696650         1.0   17.0   \n",
       "...       ...                 ...         ...        ...         ...    ...   \n",
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       "132778  36805 2023-05-29 23:53:51  114.120354  22.544300         0.0    0.0   \n",
       "\n",
       "        moveid  \n",
       "0          0.0  \n",
       "27         0.0  \n",
       "28         0.0  \n",
       "29         0.0  \n",
       "30         0.0  \n",
       "...        ...  \n",
       "132774   724.0  \n",
       "132775   724.0  \n",
       "132776   724.0  \n",
       "132777   724.0  \n",
       "132778   724.0  \n",
       "\n",
       "[397892 rows x 7 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract trajectory points during travel\n",
    "move_points = tbd.traj_slice(data, move, traj_col=['id', 'time'], slice_col=[\n",
    "                             'id', 'stime', 'etime', 'moveid'])\n",
    "move_points"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trajectory densification and sparsification "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To facilitate subsequent tasks such as matching the travel paths in the trajectory data with the road network, we perform densification or sparsification of the trajectory points during the travel process. At this stage, we specify the ID column as the travel ID (moveid) column, meaning that when performing the densification or sparsification operation on the trajectory points, we consider each travel separately. The code for this operation is as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
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       "      <td>36805.0</td>\n",
       "      <td>2023-05-29 23:53:21</td>\n",
       "      <td>114.120354</td>\n",
       "      <td>22.544300</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>724.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4175974</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2023-05-29 23:53:30</td>\n",
       "      <td>114.120354</td>\n",
       "      <td>22.544300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>724.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4175975</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2023-05-29 23:53:45</td>\n",
       "      <td>114.120354</td>\n",
       "      <td>22.544300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>724.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397891</th>\n",
       "      <td>36805.0</td>\n",
       "      <td>2023-05-29 23:53:51</td>\n",
       "      <td>114.120354</td>\n",
       "      <td>22.544300</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>724.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1211070 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id                time         lon        lat  OpenStatus  \\\n",
       "0        22396.0 2023-05-29 00:00:29  113.996719  22.693333         1.0   \n",
       "2            NaN 2023-05-29 00:00:30  113.996681  22.693386         NaN   \n",
       "3            NaN 2023-05-29 00:00:45  113.996116  22.694183         NaN   \n",
       "4            NaN 2023-05-29 00:01:00  113.995552  22.694979         NaN   \n",
       "1        22396.0 2023-05-29 00:01:01  113.995514  22.695032         1.0   \n",
       "...          ...                 ...         ...        ...         ...   \n",
       "397889   36805.0 2023-05-29 23:53:15  114.120354  22.544300         1.0   \n",
       "397890   36805.0 2023-05-29 23:53:21  114.120354  22.544300         1.0   \n",
       "4175974      NaN 2023-05-29 23:53:30  114.120354  22.544300         NaN   \n",
       "4175975      NaN 2023-05-29 23:53:45  114.120354  22.544300         NaN   \n",
       "397891   36805.0 2023-05-29 23:53:51  114.120354  22.544300         0.0   \n",
       "\n",
       "         speed  moveid  \n",
       "0         20.0     0.0  \n",
       "2          NaN     0.0  \n",
       "3          NaN     0.0  \n",
       "4          NaN     0.0  \n",
       "1         34.0     0.0  \n",
       "...        ...     ...  \n",
       "397889     1.0   724.0  \n",
       "397890     0.0   724.0  \n",
       "4175974    NaN   724.0  \n",
       "4175975    NaN   724.0  \n",
       "397891     0.0   724.0  \n",
       "\n",
       "[1211070 rows x 7 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Trajectory densification\n",
    "move_points_densified = tbd.traj_densify(\n",
    "    move_points, col=['moveid', 'time', 'lon', 'lat'], timegap=15)\n",
    "move_points_densified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
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       "           id                time         lon        lat  OpenStatus  speed  \\\n",
       "0       22396 2023-05-29 00:00:29  113.996719  22.693333         1.0   20.0   \n",
       "4       22396 2023-05-29 00:02:21  113.995430  22.696650         1.0   17.0   \n",
       "7       22396 2023-05-29 00:04:21  113.992348  22.696733         0.0   36.0   \n",
       "10      22396 2023-05-29 00:06:21  113.986366  22.691000         0.0   48.0   \n",
       "12      22396 2023-05-29 00:08:21  113.989586  22.681749         0.0   43.0   \n",
       "...       ...                 ...         ...        ...         ...    ...   \n",
       "397822  36805 2023-05-29 23:45:27  114.091217  22.540768         0.0   11.0   \n",
       "397835  36805 2023-05-29 23:47:21  114.093002  22.543383         1.0    0.0   \n",
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       "397890  36805 2023-05-29 23:53:21  114.120354  22.544300         1.0    0.0   \n",
       "\n",
       "        moveid  \n",
       "0          0.0  \n",
       "4          0.0  \n",
       "7          0.0  \n",
       "10         0.0  \n",
       "12         0.0  \n",
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       "397822   724.0  \n",
       "397835   724.0  \n",
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       "397875   724.0  \n",
       "397890   724.0  \n",
       "\n",
       "[90172 rows x 7 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Trajectory sparsification\n",
    "move_points_sparsified = tbd.traj_sparsify(\n",
    "    move_points, col=['moveid', 'time', 'lon', 'lat'],  timegap=120)\n",
    "move_points_sparsified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a function to plot the trajectory\n",
    "def plot_traj(traj):\n",
    "    import folium\n",
    "    # 1. Create a map with the center at the average coordinates of the trajectory\n",
    "    m = folium.Map(location=[traj['lat'].mean(), traj['lon'].mean()],  # Map center\n",
    "                zoom_start=14,  # Map zoom level\n",
    "                tiles='cartodbpositron')  # Map style\n",
    "    # 2. Add the trajectory\n",
    "    folium.PolyLine(\n",
    "        traj[['lat', 'lon']].values.tolist(),  # Trajectory coordinates\n",
    "        color='red',  # Trajectory color\n",
    "        weight=2.5,  # Trajectory width\n",
    "        opacity=1).add_to(m)  # Trajectory opacity, add to the map after creating the trajectory\n",
    "    # 3. Add trajectory points\n",
    "    for i in range(len(traj)):\n",
    "        folium.CircleMarker(\n",
    "            location=[traj['lat'].iloc[i], traj['lon'].iloc[i]],  # Trajectory point coordinates\n",
    "            radius=3,  # Trajectory point radius\n",
    "            color='red',  # Trajectory point color\n",
    "        ).add_to(m)  # Fill opacity, add to the map after creating the trajectory point\n",
    "    # 4. Add start and end markers\n",
    "    folium.Marker([traj['lat'].iloc[0], traj['lon'].iloc[0]],  # Start point coordinates\n",
    "                popup='Start',  # Start marker label\n",
    "                icon=folium.Icon(color='green')).add_to(m)  # Start marker color\n",
    "    folium.Marker([traj['lat'].iloc[-1], traj['lon'].iloc[-1]],\n",
    "                popup='End',\n",
    "                icon=folium.Icon(color='red')).add_to(m)\n",
    "    # 5. Display the map, directly in Jupyter Notebook\n",
    "    return m\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
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       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
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       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css&quot;/&gt;\n",
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       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_6ec401ea36ce0849ed3a861ff305b73e {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_6ec401ea36ce0849ed3a861ff305b73e&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
       "&lt;script&gt;    \n",
       "    \n",
       "            var map_6ec401ea36ce0849ed3a861ff305b73e = L.map(\n",
       "                &quot;map_6ec401ea36ce0849ed3a861ff305b73e&quot;,\n",
       "                {\n",
       "                    center: [22.538999852941178, 113.97351458823528],\n",
       "                    crs: L.CRS.EPSG3857,\n",
       "                    zoom: 14,\n",
       "                    zoomControl: true,\n",
       "                    preferCanvas: false,\n",
       "                }\n",
       "            );\n",
       "\n",
       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_c6899989c2e99fb881c33ac9ecfa1ba2 = L.tileLayer(\n",
       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var poly_line_a71821197d9d9b1570ffe5bdb658040d = L.polyline(\n",
       "                [[22.542999, 113.94848600000002], [22.5431, 113.950516], [22.543182, 113.952881], [22.543217, 113.95443], [22.543283, 113.956398], [22.543217, 113.958649], [22.542517, 113.95948], [22.541082, 113.959381], [22.541082, 113.959381], [22.542933, 113.959999], [22.542334, 113.961998], [22.541967, 113.96303600000002], [22.541967, 113.96303600000002], [22.541651, 113.963882], [22.54050100000001, 113.96685], [22.539568, 113.969521], [22.538967, 113.971069], [22.538433, 113.972534], [22.537582, 113.974403], [22.536833, 113.976021], [22.536266, 113.977982], [22.5362, 113.980164], [22.53615, 113.982086], [22.536133, 113.98317], [22.536133, 113.983467], [22.536133, 113.985153], [22.536066, 113.986969], [22.535566, 113.989632], [22.534967, 113.991936], [22.534582, 113.995201], [22.534883, 113.997681], [22.535217000000006, 113.999969], [22.5355, 114.00132], [22.535784, 114.00281499999998]],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;noClip&quot;: false, &quot;opacity&quot;: 1, &quot;smoothFactor&quot;: 1.0, &quot;stroke&quot;: true, &quot;weight&quot;: 2.5}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_fbf13cde3a2a21fb2884a1a5b86e4e08 = L.circleMarker(\n",
       "                [22.542999, 113.94848600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_f907517f74bfcd4a2b66c5dc68024757 = L.circleMarker(\n",
       "                [22.5431, 113.950516],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_67669911dd361c04b10d50e9f4b1f2eb = L.circleMarker(\n",
       "                [22.543182, 113.952881],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_e291c0be07e09ef2138802e3df252a63 = L.circleMarker(\n",
       "                [22.543217, 113.95443],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_34d715d52c8ddf4a97693c065702ca2b = L.circleMarker(\n",
       "                [22.543283, 113.956398],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_c799b944a18c7cc914252634609d9546 = L.circleMarker(\n",
       "                [22.543217, 113.958649],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_8f3c45745cf91cea697954a3887dff90 = L.circleMarker(\n",
       "                [22.542517, 113.95948],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bfc1a7389748b274dbcf0939292712ea = L.circleMarker(\n",
       "                [22.541082, 113.959381],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_da710420304486ef9d3d5342605fce68 = L.circleMarker(\n",
       "                [22.541082, 113.959381],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_ee828ed2e4063092401145e949a4d10f = L.circleMarker(\n",
       "                [22.542933, 113.959999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_2d1d356001b2feab256864d0931814ad = L.circleMarker(\n",
       "                [22.542334, 113.961998],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_ca383c2df69d8b0cd8d88a7cefd9b4e3 = L.circleMarker(\n",
       "                [22.541967, 113.96303600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_0b25b6c0dcf98cd0bc278d87e198c32c = L.circleMarker(\n",
       "                [22.541967, 113.96303600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_237dda7d38d1dbd5bbe87ceb7c3a0fc9 = L.circleMarker(\n",
       "                [22.541651, 113.963882],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_ed153d000839c3675c06ea2afbccf748 = L.circleMarker(\n",
       "                [22.54050100000001, 113.96685],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_84d913f9992263f2cba25174c71e2964 = L.circleMarker(\n",
       "                [22.539568, 113.969521],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_1199ce996e442e2d2d1482e365f4dda9 = L.circleMarker(\n",
       "                [22.538967, 113.971069],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_ad5c3326a59c0e4621fa9d78c3c1347c = L.circleMarker(\n",
       "                [22.538433, 113.972534],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_140762778a11f41a3a9460bfa6c9980a = L.circleMarker(\n",
       "                [22.537582, 113.974403],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_4a7a467aaff08923b36bb24fc9acb4a6 = L.circleMarker(\n",
       "                [22.536833, 113.976021],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_c38b14dab13e959f52b835606115d845 = L.circleMarker(\n",
       "                [22.536266, 113.977982],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bffe75545d55250e7685f10c27b9e236 = L.circleMarker(\n",
       "                [22.5362, 113.980164],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_9730a11c4378d07713ce0a54c3b1a6a7 = L.circleMarker(\n",
       "                [22.53615, 113.982086],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_c5dcfbe3f6383273fbbf04f5847da962 = L.circleMarker(\n",
       "                [22.536133, 113.98317],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_e4b640f9d507548a708b9fdd978f4ee1 = L.circleMarker(\n",
       "                [22.536133, 113.983467],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_6566bcfe9c186b2aa6d24cc9f5e0e016 = L.circleMarker(\n",
       "                [22.536133, 113.985153],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_7e060c7c41c4bc9e5f6eda7711b9b61d = L.circleMarker(\n",
       "                [22.536066, 113.986969],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_58b8da3a417e369072516e79d07d16b9 = L.circleMarker(\n",
       "                [22.535566, 113.989632],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bf8e1373b369b4712505ad64f2580186 = L.circleMarker(\n",
       "                [22.534967, 113.991936],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_3f34fcf8742fa4a8737be53c1a510bc1 = L.circleMarker(\n",
       "                [22.534582, 113.995201],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_eb099c8a31565c05bc19b89c0482b397 = L.circleMarker(\n",
       "                [22.534883, 113.997681],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_033d336019268b948f772fb52d49563a = L.circleMarker(\n",
       "                [22.535217000000006, 113.999969],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_9d2b46ad86b56925c5282404064f4d20 = L.circleMarker(\n",
       "                [22.5355, 114.00132],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var circle_marker_5e68beb7237b68f355c6967241d72ac7 = L.circleMarker(\n",
       "                [22.535784, 114.00281499999998],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var marker_7bc4102cdbd7f9fd58548ec09c021bec = L.marker(\n",
       "                [22.542999, 113.94848600000002],\n",
       "                {}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var icon_3b099cca1e263a5400cfe31a8c895262 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;info-sign&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_7bc4102cdbd7f9fd58548ec09c021bec.setIcon(icon_3b099cca1e263a5400cfe31a8c895262);\n",
       "        \n",
       "    \n",
       "        var popup_176e79a46c4ee6ba5a28c815048fbe17 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_0056bd80ead423ab3057444e7346d220 = $(`&lt;div id=&quot;html_0056bd80ead423ab3057444e7346d220&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;起点&lt;/div&gt;`)[0];\n",
       "                popup_176e79a46c4ee6ba5a28c815048fbe17.setContent(html_0056bd80ead423ab3057444e7346d220);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_7bc4102cdbd7f9fd58548ec09c021bec.bindPopup(popup_176e79a46c4ee6ba5a28c815048fbe17)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_a67364b92535d55e338fbd648bbe3e79 = L.marker(\n",
       "                [22.535784, 114.00281499999998],\n",
       "                {}\n",
       "            ).addTo(map_6ec401ea36ce0849ed3a861ff305b73e);\n",
       "        \n",
       "    \n",
       "            var icon_2fafaf5852ab01c3f5098cae8e40f237 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;info-sign&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;red&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_a67364b92535d55e338fbd648bbe3e79.setIcon(icon_2fafaf5852ab01c3f5098cae8e40f237);\n",
       "        \n",
       "    \n",
       "        var popup_76e79aece86660d76a7942a53cf775bf = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_673b1235a1c4c622e59a2862de5ab214 = $(`&lt;div id=&quot;html_673b1235a1c4c622e59a2862de5ab214&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;终点&lt;/div&gt;`)[0];\n",
       "                popup_76e79aece86660d76a7942a53cf775bf.setContent(html_673b1235a1c4c622e59a2862de5ab214);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_a67364b92535d55e338fbd648bbe3e79.bindPopup(popup_76e79aece86660d76a7942a53cf775bf)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "&lt;/script&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2ae9ffa90>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moveid = 51\n",
    "# Original trajectory\n",
    "traj = move_points[move_points['moveid']==moveid]\n",
    "plot_traj(traj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe srcdoc=\"&lt;!DOCTYPE html&gt;\n",
       "&lt;head&gt;    \n",
       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
       "    \n",
       "        &lt;script&gt;\n",
       "            L_NO_TOUCH = false;\n",
       "            L_DISABLE_3D = false;\n",
       "        &lt;/script&gt;\n",
       "    \n",
       "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css&quot;/&gt;\n",
       "    \n",
       "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
       "            &lt;style&gt;\n",
       "                #map_102a464cef9ec65aaf0f359a68bed981 {\n",
       "                    position: relative;\n",
       "                    width: 100.0%;\n",
       "                    height: 100.0%;\n",
       "                    left: 0.0%;\n",
       "                    top: 0.0%;\n",
       "                }\n",
       "            &lt;/style&gt;\n",
       "        \n",
       "&lt;/head&gt;\n",
       "&lt;body&gt;    \n",
       "    \n",
       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_102a464cef9ec65aaf0f359a68bed981&quot; &gt;&lt;/div&gt;\n",
       "        \n",
       "&lt;/body&gt;\n",
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       "    \n",
       "            var map_102a464cef9ec65aaf0f359a68bed981 = L.map(\n",
       "                &quot;map_102a464cef9ec65aaf0f359a68bed981&quot;,\n",
       "                {\n",
       "                    center: [22.53917817291394, 113.97263821467695],\n",
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       "            \n",
       "\n",
       "        \n",
       "    \n",
       "            var tile_layer_1bf6bf5780e9c28b9019769968190433 = L.tileLayer(\n",
       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var poly_line_765286d89e7cee66d6d81439bf082fc8 = L.polyline(\n",
       "                [[22.542999, 113.94848600000002], [22.543024837209302, 113.94900530232559], [22.543060069767442, 113.94971344186047], [22.54309530232558, 113.95042158139535], [22.5431, 113.950516], [22.5431533, 113.95205325], [22.543182, 113.952881], [22.543196000000002, 113.9535006], [22.543217, 113.95443], [22.543226899999997, 113.9547252], [22.5432764, 113.9562012], [22.543283, 113.956398], [22.5432401, 113.95786115], [22.543217, 113.958649], [22.542937, 113.9589814], [22.542517, 113.95948], [22.54230175, 113.95946515], [22.5412255, 113.95939089999999], [22.541082, 113.959381], [22.541082, 113.959381], [22.541082, 113.959381], [22.5418224, 113.9596282], [22.542933, 113.959999], [22.542843150000003, 113.96029885], [22.5423939, 113.9617981], [22.542334, 113.961998], [22.54209545, 113.96267270000001], [22.541967, 113.96303600000002], [22.541967, 113.96303600000002], [22.541967, 113.96303600000002], [22.541925782608697, 113.9631463478261], [22.541719695652176, 113.96369808695653], [22.541651, 113.963882], [22.541076000000004, 113.96536599999999], [22.54050100000001, 113.96685], [22.540309250000007, 113.967377375], [22.539734000000003, 113.9689595], [22.539158750000002, 113.970541625], [22.538967, 113.971069], [22.5387, 113.9718015], [22.538433, 113.972534], [22.538233, 113.97296987499999], [22.537633, 113.9742775], [22.537033, 113.97558512500001], [22.536833, 113.976021], [22.5365495, 113.9770015], [22.536266, 113.977982], [22.536251500000002, 113.978495], [22.536208000000002, 113.98003399999999], [22.536164499999998, 113.981573], [22.53615, 113.982086], [22.5361415, 113.982628], [22.536133, 113.98317], [22.536133, 113.983467], [22.536133, 113.9835513], [22.536133, 113.98481579999999], [22.536133, 113.985153], [22.536096150000002, 113.9861518], [22.536066, 113.986969], [22.535916, 113.9877679], [22.535566, 113.989632], [22.53553605, 113.9897472], [22.535086800000002, 113.9914752], [22.534967, 113.991936], [22.53475525, 113.99373175], [22.534582, 113.995201], [22.5346723, 113.99594499999999], [22.534883, 113.997681], [22.534898904761906, 113.99778995238096], [22.53513747619048, 113.99942423809523], [22.535217000000006, 113.999969], [22.5353585, 114.00064449999999], [22.5355, 114.00132], [22.53550000000594, 114.00131999998626], [22.535500000023763, 114.00131999994505]],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;noClip&quot;: false, &quot;opacity&quot;: 1, &quot;smoothFactor&quot;: 1.0, &quot;stroke&quot;: true, &quot;weight&quot;: 2.5}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_fa134ba259f43e0532a6a4dc9cdc050e = L.circleMarker(\n",
       "                [22.542999, 113.94848600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_be56581623da3d069b24638dc81adcfd = L.circleMarker(\n",
       "                [22.543024837209302, 113.94900530232559],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_1bd4600c85e33dad7017a16dcf5596a6 = L.circleMarker(\n",
       "                [22.543060069767442, 113.94971344186047],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_23683d79f10d3992276cd1f719abf4ad = L.circleMarker(\n",
       "                [22.54309530232558, 113.95042158139535],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_d7a0af7f6fe44af987ba09663cc6e395 = L.circleMarker(\n",
       "                [22.5431, 113.950516],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_2bcfaee7b9de607cb36f823963374b40 = L.circleMarker(\n",
       "                [22.5431533, 113.95205325],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_194f7755daa1a69b920380fae3f6e24e = L.circleMarker(\n",
       "                [22.543182, 113.952881],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bfc7fba0043c3d052162bfec90833d44 = L.circleMarker(\n",
       "                [22.543196000000002, 113.9535006],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_42df1f88d3d7e092689c19b637dde912 = L.circleMarker(\n",
       "                [22.543217, 113.95443],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_a6a7a4799a481aff798993f77069f82c = L.circleMarker(\n",
       "                [22.543226899999997, 113.9547252],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bafd57ab7293fce203fd68738988071d = L.circleMarker(\n",
       "                [22.5432764, 113.9562012],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_87d5f099788944326d654b537ef16869 = L.circleMarker(\n",
       "                [22.543283, 113.956398],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_72fafb62b42ad750ecb338b9dbf52a8f = L.circleMarker(\n",
       "                [22.5432401, 113.95786115],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_e41da78aa2e7991a0fd748a08aee1e1e = L.circleMarker(\n",
       "                [22.543217, 113.958649],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_9a641b4264482fd0f8891b27449f3616 = L.circleMarker(\n",
       "                [22.542937, 113.9589814],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_66b83caff5f1ec83795696d6ceb413f4 = L.circleMarker(\n",
       "                [22.542517, 113.95948],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_09182f4254f1f6f4743607021968ecfe = L.circleMarker(\n",
       "                [22.54230175, 113.95946515],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_0bc87b5d06e8b50a9ff183c69772891a = L.circleMarker(\n",
       "                [22.5412255, 113.95939089999999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_5b783a25529dff76806e0c2547b85015 = L.circleMarker(\n",
       "                [22.541082, 113.959381],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_a86a137414d159294772787887c3a79b = L.circleMarker(\n",
       "                [22.541082, 113.959381],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_924e477667628ec909a3599ea26d17dd = L.circleMarker(\n",
       "                [22.541082, 113.959381],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_5b8dd20df27e19d5792af0819086c85c = L.circleMarker(\n",
       "                [22.5418224, 113.9596282],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_898debf2f66060b846450860bd6299fc = L.circleMarker(\n",
       "                [22.542933, 113.959999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_255a353c8cfcf88ce5e84d1443802fd9 = L.circleMarker(\n",
       "                [22.542843150000003, 113.96029885],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_5c24045e54da4066f2ee63849a5aefaf = L.circleMarker(\n",
       "                [22.5423939, 113.9617981],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_0055551ec973e0ccc973fee5d38f584b = L.circleMarker(\n",
       "                [22.542334, 113.961998],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bc167dc5387703f17142f57b5aad1b4c = L.circleMarker(\n",
       "                [22.54209545, 113.96267270000001],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_a207e15a2d3a0f6d668dba5cea3cfbd7 = L.circleMarker(\n",
       "                [22.541967, 113.96303600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_12feced88770e543532dc911584787f4 = L.circleMarker(\n",
       "                [22.541967, 113.96303600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_6d1b667aa082fe7600cf93a5c58f19da = L.circleMarker(\n",
       "                [22.541967, 113.96303600000002],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_3bd121d9a5c64de0851e60d874ff8bb2 = L.circleMarker(\n",
       "                [22.541925782608697, 113.9631463478261],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_7cae737876c4974d7baa26076c66e5d8 = L.circleMarker(\n",
       "                [22.541719695652176, 113.96369808695653],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_35db18ff3f5a64839a0628614f680b58 = L.circleMarker(\n",
       "                [22.541651, 113.963882],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_050d3ee9094b3f2c7a17677d22c271fb = L.circleMarker(\n",
       "                [22.541076000000004, 113.96536599999999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_918272e57aeda229c614d3847bab69be = L.circleMarker(\n",
       "                [22.54050100000001, 113.96685],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_f4145e0d7327d2a3c30520e9d2905eb1 = L.circleMarker(\n",
       "                [22.540309250000007, 113.967377375],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_34f9f00f6c822e61e41610ada098630b = L.circleMarker(\n",
       "                [22.539734000000003, 113.9689595],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_ffbf7e2d08dfb4744bfe1dafc898100a = L.circleMarker(\n",
       "                [22.539158750000002, 113.970541625],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_d77874ef3fab60250ffe76d574fa78fc = L.circleMarker(\n",
       "                [22.538967, 113.971069],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_c19f097bf4f8b585c3fa837b6be9135a = L.circleMarker(\n",
       "                [22.5387, 113.9718015],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_b0f38f7f6a6729465a7e6a83c84ea903 = L.circleMarker(\n",
       "                [22.538433, 113.972534],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bcadcb588b7d6bd522464c3d4a08ec59 = L.circleMarker(\n",
       "                [22.538233, 113.97296987499999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_d8adeaf64774b5a63c17a4f85d0f7eca = L.circleMarker(\n",
       "                [22.537633, 113.9742775],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_a37ae29d4b4a2d01330d96c4ce062848 = L.circleMarker(\n",
       "                [22.537033, 113.97558512500001],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_1d691b58f4dad665fdb7f44d4e68fefd = L.circleMarker(\n",
       "                [22.536833, 113.976021],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_05fc2664ce22613bb2d077518ef01a6e = L.circleMarker(\n",
       "                [22.5365495, 113.9770015],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_3f1406443ab7c50a310453236273a63b = L.circleMarker(\n",
       "                [22.536266, 113.977982],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_f80424a5ebaf8a806497ac8072235ce7 = L.circleMarker(\n",
       "                [22.536251500000002, 113.978495],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_c56da0e14d715e6994810c5d461c0141 = L.circleMarker(\n",
       "                [22.536208000000002, 113.98003399999999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_0c5dc13231eaab48ddd48243074b42df = L.circleMarker(\n",
       "                [22.536164499999998, 113.981573],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_7e6acb60b2eb6a657fa46b623c0c49f1 = L.circleMarker(\n",
       "                [22.53615, 113.982086],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_77baf217262601a98af59cf438682b79 = L.circleMarker(\n",
       "                [22.5361415, 113.982628],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_1bc6700e920bf700c63c42b47ef7dd3f = L.circleMarker(\n",
       "                [22.536133, 113.98317],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_11add03a3436af85d55aee27113d7cb7 = L.circleMarker(\n",
       "                [22.536133, 113.983467],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_ddeb682453a429b62c4773d4474ffbcb = L.circleMarker(\n",
       "                [22.536133, 113.9835513],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_7ee1ed8396d54aac20c4479bea66ac02 = L.circleMarker(\n",
       "                [22.536133, 113.98481579999999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_bd5cfa44c61f4493d8a51134a80a2799 = L.circleMarker(\n",
       "                [22.536133, 113.985153],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_3e92c6fe156d06bb2a4764d02f525004 = L.circleMarker(\n",
       "                [22.536096150000002, 113.9861518],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_4903b65d470c3e6a6da4d2004d1da2c9 = L.circleMarker(\n",
       "                [22.536066, 113.986969],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_871677f79025adb722bc9959cf86b478 = L.circleMarker(\n",
       "                [22.535916, 113.9877679],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_6d143096b367df977749daedd5346992 = L.circleMarker(\n",
       "                [22.535566, 113.989632],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_183a5f5df676751dec1912101bf93449 = L.circleMarker(\n",
       "                [22.53553605, 113.9897472],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_1f2f30b460be72c3438acc9b20537eed = L.circleMarker(\n",
       "                [22.535086800000002, 113.9914752],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_a5a42bd87fd278ca60e4e47238f8fa87 = L.circleMarker(\n",
       "                [22.534967, 113.991936],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_6c16bbb00fdfe2da726c668603325a09 = L.circleMarker(\n",
       "                [22.53475525, 113.99373175],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_24c1933fc30adbafdc751a43c34bb8e0 = L.circleMarker(\n",
       "                [22.534582, 113.995201],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_6195f6b0d3b4e370a9ac2786f6bc1366 = L.circleMarker(\n",
       "                [22.5346723, 113.99594499999999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_de556ba3e9de246f275ff5149335afe4 = L.circleMarker(\n",
       "                [22.534883, 113.997681],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_16351ba854046b2a3b7ae964e82bf712 = L.circleMarker(\n",
       "                [22.534898904761906, 113.99778995238096],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_746cb935d36544d0f63d1613383c3b93 = L.circleMarker(\n",
       "                [22.53513747619048, 113.99942423809523],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_34d02a4c1cfe19b29767e5d25408f5ab = L.circleMarker(\n",
       "                [22.535217000000006, 113.999969],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_f29dc3124d9a4bac295c15bf2fa2e2cb = L.circleMarker(\n",
       "                [22.5353585, 114.00064449999999],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_b103cd377e75dbf81eb01693730de6db = L.circleMarker(\n",
       "                [22.5355, 114.00132],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_3059081a41c03ba6338084f0a40926bd = L.circleMarker(\n",
       "                [22.53550000000594, 114.00131999998626],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var circle_marker_b2afde1bf84dc60c56dee2165006b99c = L.circleMarker(\n",
       "                [22.535500000023763, 114.00131999994505],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var marker_352950b6290b923299284b382b20b2db = L.marker(\n",
       "                [22.542999, 113.94848600000002],\n",
       "                {}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var icon_20216e1894fc3fbd3e09d481b3f85333 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;info-sign&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;green&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_352950b6290b923299284b382b20b2db.setIcon(icon_20216e1894fc3fbd3e09d481b3f85333);\n",
       "        \n",
       "    \n",
       "        var popup_2133bdb2920500607b1ea5d5c66dda8f = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_0b6c47bbc0c0540d12b3cdddeb50bbcb = $(`&lt;div id=&quot;html_0b6c47bbc0c0540d12b3cdddeb50bbcb&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;起点&lt;/div&gt;`)[0];\n",
       "                popup_2133bdb2920500607b1ea5d5c66dda8f.setContent(html_0b6c47bbc0c0540d12b3cdddeb50bbcb);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_352950b6290b923299284b382b20b2db.bindPopup(popup_2133bdb2920500607b1ea5d5c66dda8f)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_3817844e14428ca099c9c167cde31639 = L.marker(\n",
       "                [22.535500000023763, 114.00131999994505],\n",
       "                {}\n",
       "            ).addTo(map_102a464cef9ec65aaf0f359a68bed981);\n",
       "        \n",
       "    \n",
       "            var icon_ab25920c775c77f7fadde34fb8ced8c6 = L.AwesomeMarkers.icon(\n",
       "                {&quot;extraClasses&quot;: &quot;fa-rotate-0&quot;, &quot;icon&quot;: &quot;info-sign&quot;, &quot;iconColor&quot;: &quot;white&quot;, &quot;markerColor&quot;: &quot;red&quot;, &quot;prefix&quot;: &quot;glyphicon&quot;}\n",
       "            );\n",
       "            marker_3817844e14428ca099c9c167cde31639.setIcon(icon_ab25920c775c77f7fadde34fb8ced8c6);\n",
       "        \n",
       "    \n",
       "        var popup_dd935970b56e722b711d1b7fe700ac2c = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            \n",
       "                var html_e1d57f4c8b61ef242cce23f838f65dd5 = $(`&lt;div id=&quot;html_e1d57f4c8b61ef242cce23f838f65dd5&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;终点&lt;/div&gt;`)[0];\n",
       "                popup_dd935970b56e722b711d1b7fe700ac2c.setContent(html_e1d57f4c8b61ef242cce23f838f65dd5);\n",
       "            \n",
       "        \n",
       "\n",
       "        marker_3817844e14428ca099c9c167cde31639.bindPopup(popup_dd935970b56e722b711d1b7fe700ac2c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "&lt;/script&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x2af4fc970>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Densified trajectory\n",
    "traj = move_points_densified[move_points_densified['moveid']==moveid]\n",
    "plot_traj(traj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css&quot;/&gt;\n",
       "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css&quot;/&gt;\n",
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       "                    width: 100.0%;\n",
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       "            ).addTo(map_7e49adfa246b6b6e237c41413d6311ac);\n",
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       "                [22.5355, 114.00132],\n",
       "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 3, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
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       "\n",
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      ],
      "text/plain": [
       "<folium.folium.Map at 0x2ae4a8f40>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sparsified trajectory\n",
    "traj = move_points_sparsified[move_points_sparsified['moveid']==moveid]\n",
    "plot_traj(traj)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trajectory smoothing\n",
    "\n",
    "When processing vehicle trajectory data, the trajectory points represent \"observations\" of the actual \"state\" of the vehicle. Due to errors, the observed data may deviate from the actual state of the vehicle.\n",
    "\n",
    "How can we obtain a more accurate estimation of the actual state of the vehicle? Consider the method mentioned in the previous section for detecting trajectory drift, which involves comparing the position of a trajectory point with the position of previous trajectory points to check for significant and unreasonable jumps. This approach is essentially based on predicting the possible future positions of the vehicle based on its previous trajectory. If the next recorded trajectory point deviates significantly from the expected position, it can be determined that the trajectory is abnormal.\n",
    "\n",
    "This method shares similarities with the concept of Kalman filtering. Kalman filtering is a linear quadratic estimation algorithm used for state estimation in linear dynamic systems. It combines the previous state estimation (i.e., the predicted position of the current trajectory point) with the current observation data (recorded position of the current trajectory point) to obtain an optimal estimate of the current state.\n",
    "\n",
    "The implementation of Kalman filtering involves predicting the current value using the previous optimal result and then correcting the current value using the observed value to obtain the optimal result. This method effectively reduces the impact of noise, allowing for a more accurate estimation of the actual state of the vehicle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "move_id =51\n",
    "traj = move_points[move_points['moveid'] == move_id].copy()\n",
    "traj_smoothed = tbd.traj_smooth(traj,col = ['id','time','lon', 'lat'],proj=False,process_noise_std = 0.01, measurement_noise_std = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "<folium.folium.Map at 0x2af969340>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot the trajectory\n",
    "import folium\n",
    "m = folium.Map(location=[traj['lat'].mean(), traj['lon'].mean()], \n",
    "            zoom_start=14,  \n",
    "            tiles='cartodbpositron')  \n",
    "# original trajectory\n",
    "folium.PolyLine(\n",
    "    traj[['lat', 'lon']].values.tolist(),  \n",
    "    color='red', \n",
    "    weight=2.5,\n",
    "    opacity=1).add_to(m) \n",
    "# smoothed trajectory\n",
    "folium.PolyLine(\n",
    "    traj_smoothed[['lat', 'lon']].values.tolist(), \n",
    "    color='blue',\n",
    "    weight=2.5, \n",
    "    opacity=1).add_to(m) \n",
    "m"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The goal of the Kalman filter is to optimize the observed values by estimating the system state while considering the uncertainties of both the observation noise and the system dynamics. It has advantages in smoothing trajectory data by reducing noise effects and minimizing fluctuations within a small range. However, the Kalman filter cannot completely eliminate all noise or handle trajectory drift.\n",
    "\n",
    "The Kalman filter is suitable for cases where the noise in the trajectory data is relatively stable, meaning the noise variance remains constant. It is particularly effective in smoothing small-scale fluctuations caused by measurement errors in trajectory data.\n",
    "\n",
    "However, the effectiveness of the Kalman filter is limited when significant drift occurs in the trajectory. Drift points are treated as observations and have a significant impact on state estimation, which the Kalman filter cannot directly handle.\n",
    "\n",
    "Furthermore, the Kalman filter requires the specification of covariance matrices for process and observation errors, and these parameter settings affect the smoothing effect. Improper covariance matrix settings can result in significant deviations in the smoothed trajectory data, especially when dealing with trajectory data that may deviate from the road network.\n",
    "\n",
    "When processing trajectory data, a common approach is to first remove drift, then perform smoothing, and finally conduct road network matching. The rationale behind this approach is as follows:\n",
    "\n",
    "- The drift removal step eliminates obvious drift points in the data, which are large noise components. The presence of drift points can significantly interfere with subsequent processing steps. Removing or correcting drift points ensures the accuracy and reliability of subsequent processing.\n",
    "- After drift removal, the trajectory data may still contain some noise and fluctuations. To reduce the impact of these noise and fluctuations, smoothing can be applied to further process the trajectory data, making it smoother, more continuous, and maintaining the overall trend of the trajectory.\n",
    "- Finally, the smoothed trajectory is more stable and better suited for road network matching. It reduces errors caused by noise and fluctuations, thereby improving the accuracy and reliability of road network matching."
   ]
  }
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