Plotter_Notebook.ipynb

{
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    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rgOzfypn0PUR",
        "outputId": "c73604b9-35e2-4599-cc51-f8c7e57996f7"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: OSMPythonTools in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from -r requirements.txt (line 1)) (0.3.5)\n",
            "Requirement already satisfied: pydeck in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from -r requirements.txt (line 2)) (0.8.0)\n",
            "Requirement already satisfied: pandas in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from -r requirements.txt (line 3)) (1.5.3)\n",
            "Requirement already satisfied: geojson in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (3.0.1)\n",
            "Requirement already satisfied: numpy in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (1.24.2)\n",
            "Requirement already satisfied: beautifulsoup4 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (4.12.0)\n",
            "Requirement already satisfied: xarray in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (2023.3.0)\n",
            "Requirement already satisfied: matplotlib in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (3.7.1)\n",
            "Requirement already satisfied: ujson in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (5.7.0)\n",
            "Requirement already satisfied: lxml in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from OSMPythonTools->-r requirements.txt (line 1)) (4.9.2)\n",
            "Requirement already satisfied: jinja2>=2.10.1 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from pydeck->-r requirements.txt (line 2)) (3.1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from pandas->-r requirements.txt (line 3)) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from pandas->-r requirements.txt (line 3)) (2023.2)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from jinja2>=2.10.1->pydeck->-r requirements.txt (line 2)) (2.1.2)\n",
            "Requirement already satisfied: six>=1.5 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from python-dateutil>=2.8.1->pandas->-r requirements.txt (line 3)) (1.16.0)\n",
            "Requirement already satisfied: soupsieve>1.2 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from beautifulsoup4->OSMPythonTools->-r requirements.txt (line 1)) (2.4)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (1.4.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (23.0)\n",
            "Requirement already satisfied: importlib-resources>=3.2.0 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (5.12.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (3.0.9)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (9.4.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (0.11.0)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (1.0.7)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (4.39.3)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /home/rsiddique/.pyenv/versions/3.9.8/lib/python3.9/site-packages (from importlib-resources>=3.2.0->matplotlib->OSMPythonTools->-r requirements.txt (line 1)) (3.15.0)\n",
            "\u001b[33mWARNING: You are using pip version 21.2.4; however, version 23.0.1 is available.\n",
            "You should consider upgrading via the '/home/rsiddique/.pyenv/versions/3.9.8/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
            "Note: you may need to restart the kernel to use updated packages.\n"
          ]
        }
      ],
      "source": [
        "%pip install -r requirements.txt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "L4iIihOuwVeG",
        "tags": []
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import json\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from scipy.linalg import inv\n",
        "f = open('tester_log_metdata.json')\n",
        "metadata = json.load(f)\n",
        "f2 = open('tester_log_pathdata.json')\n",
        "pathdata = json.load(f2)\n",
        "\n",
        "alldata = pathdata\n",
        "for key in metadata:\n",
        "    alldata[key] = metadata[key]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nefV4CtGXG1X",
        "outputId": "a487fc18-113c-407d-fba3-4380b31164fa"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "dict_keys(['identifier', 'cloudIdentifier', 'hasValidTransform', 'transform'])\n",
            "dict_keys(['GARAnchorUUID', 'altitude', 'geoAnchorTransform', 'altitudeUncertainty', 'latitude', 'horizontalUncertainty', 'heading', 'longitude', 'headingUncertainty'])\n"
          ]
        },
        {
          "ename": "ValueError",
          "evalue": "setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (66, 4) + inhomogeneous part.",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[6], line 4\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39mprint\u001b[39m(alldata[\u001b[39m'\u001b[39m\u001b[39mgarAnchors\u001b[39m\u001b[39m'\u001b[39m][\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m][\u001b[39m0\u001b[39m]\u001b[39m.\u001b[39mkeys())\n\u001b[1;32m      2\u001b[0m \u001b[39mprint\u001b[39m(alldata[\u001b[39m'\u001b[39m\u001b[39msavedRouteGeospatialLocations\u001b[39m\u001b[39m'\u001b[39m][\u001b[39m0\u001b[39m]\u001b[39m.\u001b[39mkeys())\n\u001b[0;32m----> 4\u001b[0m lat_long \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39;49marray(\u001b[39mlist\u001b[39;49m(\u001b[39mmap\u001b[39;49m(\u001b[39mlambda\u001b[39;49;00m x: (x[\u001b[39m'\u001b[39;49m\u001b[39mGARAnchorUUID\u001b[39;49m\u001b[39m'\u001b[39;49m], x[\u001b[39m'\u001b[39;49m\u001b[39mlongitude\u001b[39;49m\u001b[39m'\u001b[39;49m], x[\u001b[39m'\u001b[39;49m\u001b[39mlatitude\u001b[39;49m\u001b[39m'\u001b[39;49m], x[\u001b[39m'\u001b[39;49m\u001b[39mgeoAnchorTransform\u001b[39;49m\u001b[39m'\u001b[39;49m]), alldata[\u001b[39m'\u001b[39;49m\u001b[39msavedRouteGeospatialLocations\u001b[39;49m\u001b[39m'\u001b[39;49m])))\n\u001b[1;32m      5\u001b[0m lat_long_only \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray(\u001b[39mlist\u001b[39m(\u001b[39mmap\u001b[39m(\u001b[39mlambda\u001b[39;00m x: (x[\u001b[39m1\u001b[39m],x[\u001b[39m2\u001b[39m]), lat_long)))\n\u001b[1;32m      6\u001b[0m lat_long_poses \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray(\u001b[39mlist\u001b[39m(\u001b[39mmap\u001b[39m(\u001b[39mlambda\u001b[39;00m x: (x[\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m]), lat_long)))\n",
            "\u001b[0;31mValueError\u001b[0m: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (66, 4) + inhomogeneous part."
          ]
        }
      ],
      "source": [
        "print(alldata['garAnchors'][-1][0].keys())\n",
        "print(alldata['savedRouteGeospatialLocations'][0].keys())\n",
        "\n",
        "lat_long = np.array(list(map(lambda x: (x['GARAnchorUUID'], x['longitude'], x['latitude'], x['geoAnchorTransform']), alldata['savedRouteGeospatialLocations'])), dtype=object)\n",
        "lat_long_only = np.array(list(map(lambda x: (x[1],x[2]), lat_long)))\n",
        "lat_long_poses = np.array(list(map(lambda x: (x[-1]), lat_long)))\n",
        "gar_anchors = np.array(list(map(lambda x: (x['identifier'], x['transform']), alldata['garAnchors'][-1])), dtype=object)\n",
        "\n",
        "# filter and sort gar_anchors to match corresponding ID for lat_long points\n",
        "gar_anchors_filtered = []\n",
        "for x in lat_long:\n",
        "  for y in gar_anchors:\n",
        "    if x[0] == y[0]:  # if IDs match\n",
        "      gar_anchors_filtered.append(y)\n",
        "print(gar_anchors_filtered[0][-1])\n",
        "gar_anchors_poses_filtered = np.array(list(map(lambda x: (x[-1]), gar_anchors_filtered)))\n",
        "df = pd.DataFrame(lat_long, columns=['ID','lon', 'lat', 'pose'])\n",
        "df.keys()\n",
        "print(len(gar_anchors_poses_filtered))\n",
        "print(len(lat_long_poses))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 384
        },
        "id": "V-HcAebCXG1Y",
        "outputId": "a055ee32-802e-4bf9-8056-a0e51ce20ccc"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[-71.26406787  42.29330984]\n",
            "[[18.88207693 41.69474501]\n",
            " [32.06094632 41.60258985]\n",
            " [35.41955458 41.60261009]\n",
            " [19.06522225 41.60246656]\n",
            " [21.1975719  41.63342331]]\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7ffa1e4948e0>]"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "lat_long_poses_reshaped = np.array(list(map(lambda x: np.array(x).reshape(4,4).T, lat_long_poses)))\n",
        "gar_anchors_poses_filtered_reshaped = np.array(list(map(lambda x: np.array(x).reshape(4,4).T, gar_anchors_poses_filtered)))\n",
        "# pose_difference = inv(query_pose) @ train_pose\n",
        "pose_difference = np.array(list(map(lambda x: inv(x[0]) @ x[1], zip(lat_long_poses_reshaped, gar_anchors_poses_filtered_reshaped))))\n",
        "lat_long_only_reshaped = np.hstack(\n",
        "            (lat_long_only, np.ones((lat_long_only.shape[0], 2)))\n",
        "        ).T\n",
        "# print(lat_long_only_reshaped.T[0].shape)\n",
        "# print(inv(pose_difference[0]).shape)\n",
        "transformed_lat_long = np.array(list(map(lambda x: inv(x[0]) @ x[1].T, zip(pose_difference, lat_long_only_reshaped.T))))\n",
        "new_lat_long = np.array(list(map(lambda x: (x[0], x[1]), transformed_lat_long)))\n",
        "print(lat_long_only[0])\n",
        "print(new_lat_long[0:5])\n",
        "new_df = pd.DataFrame(new_lat_long, columns=['lon', 'lat'])\n",
        "new_df_x = np.array([x[0] for x in new_lat_long])\n",
        "new_df_y = np.array([x[1] for x in new_lat_long])\n",
        "plt.plot(new_df_x, new_df_y)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ZU6cjHZluJZv",
        "outputId": "ba4fa1d4-97f0-4418-b93d-cf4a55b0989d",
        "tags": []
      },
      "outputs": [
        {
          "data": {
            "text/html": [
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              "        <iframe\n",
              "            width=\"100%\"\n",
              "            height=500\n",
              "            frameborder=\"0\"\n",
              "            srcdoc=\"&lt;!DOCTYPE html&gt;\n",
              "&lt;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",
              "    &lt;title&gt;pydeck&lt;/title&gt;\n",
              "        &lt;script src=&quot;https://api.tiles.mapbox.com/mapbox-gl-js/v1.13.0/mapbox-gl.js&quot;&gt;&lt;/script&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;script src=&#x27;https://cdn.jsdelivr.net/npm/@deck.gl/jupyter-widget@~8.8.*/dist/index.js&#x27;&gt;&lt;/script&gt;\n",
              "    &lt;style&gt;\n",
              "    body {\n",
              "  margin: 0;\n",
              "  padding: 0;\n",
              "  overflow: hidden;\n",
              "}\n",
              "\n",
              "#deck-container {\n",
              "  width: 100vw;\n",
              "  height: 100vh;\n",
              "}\n",
              "\n",
              "#deck-container canvas {\n",
              "  z-index: 1;\n",
              "  background: none;\n",
              "}\n",
              "    &lt;/style&gt;\n",
              "  &lt;/head&gt;\n",
              "  &lt;body&gt;\n",
              "    &lt;div id=&quot;deck-container&quot;&gt;\n",
              "    &lt;/div&gt;\n",
              "  &lt;/body&gt;\n",
              "  &lt;script&gt;\n",
              "    const container = document.getElementById(&#x27;deck-container&#x27;);\n",
              "    const jsonInput = {\n",
              "  &quot;initialViewState&quot;: {\n",
              "    &quot;bearing&quot;: -27.36,\n",
              "    &quot;latitude&quot;: 42.29339,\n",
              "    &quot;longitude&quot;: -71.263974,\n",
              "    &quot;maxZoom&quot;: 20,\n",
              "    &quot;pitch&quot;: 40.5,\n",
              "    &quot;zoom&quot;: 19\n",
              "  },\n",
              "  &quot;layers&quot;: [\n",
              "    {\n",
              "      &quot;@@type&quot;: &quot;ScatterplotLayer&quot;,\n",
              "      &quot;data&quot;: [\n",
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              "      &quot;getRadius&quot;: 0.2,\n",
              "      &quot;id&quot;: &quot;73922829-da27-46e2-8e6d-57eb1cf5f599&quot;,\n",
              "      &quot;pickable&quot;: true\n",
              "    },\n",
              "    {\n",
              "      &quot;@@type&quot;: &quot;ScatterplotLayer&quot;,\n",
              "      &quot;data&quot;: [\n",
              "        {\n",
              "          &quot;lat&quot;: 41.69474501128548,\n",
              "          &quot;lon&quot;: 18.882076930725532\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.60258985496544,\n",
              "          &quot;lon&quot;: 32.06094631757303\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.60261008635917,\n",
              "          &quot;lon&quot;: 35.41955458337791\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.60246655993933,\n",
              "          &quot;lon&quot;: 19.065222252947848\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.633423306154235,\n",
              "          &quot;lon&quot;: 21.197571904255337\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.653767363996415,\n",
              "          &quot;lon&quot;: 15.403077157299794\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.65377087766811,\n",
              "          &quot;lon&quot;: 17.006240379973963\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.662699806188485,\n",
              "          &quot;lon&quot;: 21.151018427474973\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.67322449975738,\n",
              "          &quot;lon&quot;: 17.00821614769452\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.678356985150046,\n",
              "          &quot;lon&quot;: 23.257459372838895\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.699325915252906,\n",
              "          &quot;lon&quot;: 21.57539279945782\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.74494989510912,\n",
              "          &quot;lon&quot;: 23.32756383548862\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.74215674071491,\n",
              "          &quot;lon&quot;: 26.733633754721048\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.76235693647306,\n",
              "          &quot;lon&quot;: 29.233393562551388\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.78123192614944,\n",
              "          &quot;lon&quot;: 28.77824125483027\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.78120909575144,\n",
              "          &quot;lon&quot;: 22.27652408314549\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.87611026134055,\n",
              "          &quot;lon&quot;: 24.034191178299807\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.8760856598559,\n",
              "          &quot;lon&quot;: 22.712727926081875\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.876042702441715,\n",
              "          &quot;lon&quot;: 17.942971301179394\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.876065388441276,\n",
              "          &quot;lon&quot;: 20.41042878003153\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.87598664232095,\n",
              "          &quot;lon&quot;: 17.21010056525154\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.875539443338454,\n",
              "          &quot;lon&quot;: 20.240104093421376\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.873292453452486,\n",
              "          &quot;lon&quot;: 19.16833740972189\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.87267186835817,\n",
              "          &quot;lon&quot;: 30.058498094139708\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.87270448909773,\n",
              "          &quot;lon&quot;: 30.2476695437909\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.88497152467832,\n",
              "          &quot;lon&quot;: 26.445931047680887\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.89836090979245,\n",
              "          &quot;lon&quot;: 23.380387445701523\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.89836555439471,\n",
              "          &quot;lon&quot;: 22.51061989131733\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.89842058321677,\n",
              "          &quot;lon&quot;: 19.16739003041978\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.89846160977486,\n",
              "          &quot;lon&quot;: 5.207408415609265\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.898323914736814,\n",
              "          &quot;lon&quot;: 2.5379349949715646\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.95155313449731,\n",
              "          &quot;lon&quot;: 5.9818199040476365\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.95300269234151,\n",
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              "          &quot;lat&quot;: 41.953002942832946,\n",
              "          &quot;lon&quot;: 13.660978486593578\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.90456744192224,\n",
              "          &quot;lon&quot;: 10.483470676603595\n",
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              "          &quot;lon&quot;: 21.59472074490447\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.91571496363936,\n",
              "          &quot;lon&quot;: 30.009844918413325\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.915702969485864,\n",
              "          &quot;lon&quot;: 29.04340649447121\n",
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              "        {\n",
              "          &quot;lat&quot;: 41.915686608232576,\n",
              "          &quot;lon&quot;: 36.1766627750541\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.981644247711905,\n",
              "          &quot;lon&quot;: 38.067415219568346\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.98163654449232,\n",
              "          &quot;lon&quot;: 39.09814339343517\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 41.98155330460014,\n",
              "          &quot;lon&quot;: 44.27064529971804\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.1440468654222,\n",
              "          &quot;lon&quot;: 34.29299624442358\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.144045997605424,\n",
              "          &quot;lon&quot;: 37.58069232804644\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.14403888331703,\n",
              "          &quot;lon&quot;: 29.7798042650561\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.09839418574423,\n",
              "          &quot;lon&quot;: 32.371487336006524\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.07684662555146,\n",
              "          &quot;lon&quot;: 30.299127167606482\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.076826455517356,\n",
              "          &quot;lon&quot;: 27.748345079112404\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.076786449020666,\n",
              "          &quot;lon&quot;: 24.802710331097042\n",
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              "        {\n",
              "          &quot;lat&quot;: 42.07673560617822,\n",
              "          &quot;lon&quot;: 11.413622147047072\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.07669820671694,\n",
              "          &quot;lon&quot;: 14.601641632100726\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.09234808904111,\n",
              "          &quot;lon&quot;: 11.094468084163434\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.09234310002858,\n",
              "          &quot;lon&quot;: 19.575611517022768\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.09231458617922,\n",
              "          &quot;lon&quot;: 19.002708468948608\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18409397240504,\n",
              "          &quot;lon&quot;: 7.672581705942047\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18408793831115,\n",
              "          &quot;lon&quot;: 21.934688052023063\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.184083075438465,\n",
              "          &quot;lon&quot;: 17.11639060502989\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18407798312848,\n",
              "          &quot;lon&quot;: 22.266043679787785\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.184092256373916,\n",
              "          &quot;lon&quot;: 21.354206501110458\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.184122160158594,\n",
              "          &quot;lon&quot;: 22.453545645184512\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18415205789324,\n",
              "          &quot;lon&quot;: 17.049045323265936\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18417842574649,\n",
              "          &quot;lon&quot;: 21.111233067454233\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.1841800391653,\n",
              "          &quot;lon&quot;: 34.326895757412\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18417072988858,\n",
              "          &quot;lon&quot;: 41.51182751957974\n",
              "        },\n",
              "        {\n",
              "          &quot;lat&quot;: 42.18418792081178,\n",
              "          &quot;lon&quot;: 48.98545345475198\n",
              "        }\n",
              "      ],\n",
              "      &quot;getFillColor&quot;: [\n",
              "        0,\n",
              "        255,\n",
              "        0\n",
              "      ],\n",
              "      &quot;getPosition&quot;: &quot;@@=[lon, lat]&quot;,\n",
              "      &quot;getRadius&quot;: 0.2,\n",
              "      &quot;id&quot;: &quot;79987a66-b964-417a-baca-a7e558a7bdec&quot;,\n",
              "      &quot;pickable&quot;: true\n",
              "    }\n",
              "  ],\n",
              "  &quot;mapProvider&quot;: &quot;carto&quot;,\n",
              "  &quot;mapStyle&quot;: &quot;https://basemaps.cartocdn.com/gl/dark-matter-gl-style/style.json&quot;,\n",
              "  &quot;views&quot;: [\n",
              "    {\n",
              "      &quot;@@type&quot;: &quot;MapView&quot;,\n",
              "      &quot;controller&quot;: true\n",
              "    }\n",
              "  ]\n",
              "};\n",
              "    const tooltip = {&#x27;text&#x27;: &#x27;coords&#x27;};\n",
              "    const customLibraries = null;\n",
              "    const configuration = null;\n",
              "\n",
              "    const deckInstance = createDeck({\n",
              "                  container,\n",
              "      jsonInput,\n",
              "      tooltip,\n",
              "      customLibraries,\n",
              "      configuration\n",
              "    });\n",
              "\n",
              "  &lt;/script&gt;\n",
              "&lt;/html&gt;\"\n",
              "        ></iframe>\n",
              "    "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# your code here\n",
        "from OSMPythonTools.overpass import overpassQueryBuilder, Overpass\n",
        "import pydeck as pdk\n",
        "import pandas as pd\n",
        "\n",
        "# bounding box for area\n",
        "bbox = [-71.263053,42.289025,-71.257710,42.292009]\n",
        "\n",
        "# query for all satellite_dishes in the area\n",
        "overpass = Overpass()\n",
        "query = overpassQueryBuilder(bbox=bbox, elementType='node', selector='\"man_made\"=\"satellite_dish\"', out='body')\n",
        "result = overpass.query(query)\n",
        "\n",
        "# convert result data to JSON\n",
        "JSON = result.toJSON()  \n",
        "satellite_dishes = JSON['elements']\n",
        "\n",
        "# create viewState and set paratmeters to lat and long near Sweden\n",
        "view_state = pdk.ViewState(\n",
        "    latitude=42.293390,\n",
        "    longitude=-71.263974,\n",
        "    zoom=19,\n",
        "    max_zoom=20,\n",
        "    pitch=40.5,\n",
        "    bearing=-27.36\n",
        ")\n",
        "\n",
        "# create pydeck layer for the satellite_dishes\n",
        "layer = pdk.Layer(\n",
        "    'ScatterplotLayer',\n",
        "    data=df,\n",
        "    get_position='[lon, lat]',\n",
        "    get_radius=0.2,\n",
        "    get_fill_color=[255, 140, 0],\n",
        "    pickable=True\n",
        ")\n",
        "# create pydeck layer for the city locations\n",
        "layer_2 = pdk.Layer(\n",
        "    'ScatterplotLayer',\n",
        "    data=new_df,\n",
        "    get_position='[lon, lat]',\n",
        "    get_radius=0.2,\n",
        "    get_fill_color=[0, 255, 0],\n",
        "    pickable=True\n",
        ")\n",
        "\n",
        "# create pydeck map\n",
        "r = pdk.Deck(layers=[layer, layer_2], initial_view_state=view_state, tooltip={\"text\": \"coords\"})\n",
        "r.to_html('locations.html')\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cm_YZI53XG1a"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.9.8 64-bit ('3.9.8')",
      "language": "python",
      "name": "python3"
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    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.8"
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    "vscode": {
      "interpreter": {
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