main.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/ssghost/23ff1872fe2e93f6df7582e874abdf00/main.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install drawdata"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XdKhBvIOQYq6",
        "outputId": "328d6863-878f-4769-f17f-58cc451248f5"
      },
      "id": "XdKhBvIOQYq6",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting drawdata\n",
            "  Downloading drawdata-0.3.7-py2.py3-none-any.whl.metadata (4.1 kB)\n",
            "Collecting anywidget>=0.9.2 (from drawdata)\n",
            "  Downloading anywidget-0.9.13-py3-none-any.whl.metadata (7.2 kB)\n",
            "Requirement already satisfied: ipywidgets>=7.6.0 in /usr/local/lib/python3.11/dist-packages (from anywidget>=0.9.2->drawdata) (7.7.1)\n",
            "Collecting psygnal>=0.8.1 (from anywidget>=0.9.2->drawdata)\n",
            "  Downloading psygnal-0.12.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (7.7 kB)\n",
            "Requirement already satisfied: typing-extensions>=4.2.0 in /usr/local/lib/python3.11/dist-packages (from anywidget>=0.9.2->drawdata) (4.12.2)\n",
            "Requirement already satisfied: ipykernel>=4.5.1 in /usr/local/lib/python3.11/dist-packages (from ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (5.5.6)\n",
            "Requirement already satisfied: ipython-genutils~=0.2.0 in /usr/local/lib/python3.11/dist-packages (from ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.2.0)\n",
            "Requirement already satisfied: traitlets>=4.3.1 in /usr/local/lib/python3.11/dist-packages (from ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (5.7.1)\n",
            "Requirement already satisfied: widgetsnbextension~=3.6.0 in /usr/local/lib/python3.11/dist-packages (from ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.6.10)\n",
            "Requirement already satisfied: ipython>=4.0.0 in /usr/local/lib/python3.11/dist-packages (from ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (7.34.0)\n",
            "Requirement already satisfied: jupyterlab-widgets>=1.0.0 in /usr/local/lib/python3.11/dist-packages (from ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.0.13)\n",
            "Requirement already satisfied: jupyter-client in /usr/local/lib/python3.11/dist-packages (from ipykernel>=4.5.1->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (6.1.12)\n",
            "Requirement already satisfied: tornado>=4.2 in /usr/local/lib/python3.11/dist-packages (from ipykernel>=4.5.1->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (6.4.2)\n",
            "Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (75.1.0)\n",
            "Collecting jedi>=0.16 (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata)\n",
            "  Downloading jedi-0.19.2-py2.py3-none-any.whl.metadata (22 kB)\n",
            "Requirement already satisfied: decorator in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (4.4.2)\n",
            "Requirement already satisfied: pickleshare in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.7.5)\n",
            "Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.0.50)\n",
            "Requirement already satisfied: pygments in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (2.18.0)\n",
            "Requirement already satisfied: backcall in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.2.0)\n",
            "Requirement already satisfied: matplotlib-inline in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.1.7)\n",
            "Requirement already satisfied: pexpect>4.3 in /usr/local/lib/python3.11/dist-packages (from ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (4.9.0)\n",
            "Requirement already satisfied: notebook>=4.4.1 in /usr/local/lib/python3.11/dist-packages (from widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (6.5.5)\n",
            "Requirement already satisfied: parso<0.9.0,>=0.8.4 in /usr/local/lib/python3.11/dist-packages (from jedi>=0.16->ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.8.4)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.1.5)\n",
            "Requirement already satisfied: pyzmq<25,>=17 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (24.0.1)\n",
            "Requirement already satisfied: argon2-cffi in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (23.1.0)\n",
            "Requirement already satisfied: jupyter-core>=4.6.1 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (5.7.2)\n",
            "Requirement already satisfied: nbformat in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (5.10.4)\n",
            "Requirement already satisfied: nbconvert>=5 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (7.16.6)\n",
            "Requirement already satisfied: nest-asyncio>=1.5 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.6.0)\n",
            "Requirement already satisfied: Send2Trash>=1.8.0 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.8.3)\n",
            "Requirement already satisfied: terminado>=0.8.3 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.18.1)\n",
            "Requirement already satisfied: prometheus-client in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.21.1)\n",
            "Requirement already satisfied: nbclassic>=0.4.7 in /usr/local/lib/python3.11/dist-packages (from notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.2.0)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.11/dist-packages (from jupyter-client->ipykernel>=4.5.1->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (2.8.2)\n",
            "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.11/dist-packages (from pexpect>4.3->ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.7.0)\n",
            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.11/dist-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=4.0.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.2.13)\n",
            "Requirement already satisfied: platformdirs>=2.5 in /usr/local/lib/python3.11/dist-packages (from jupyter-core>=4.6.1->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (4.3.6)\n",
            "Requirement already satisfied: notebook-shim>=0.2.3 in /usr/local/lib/python3.11/dist-packages (from nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.2.4)\n",
            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (4.13.3)\n",
            "Requirement already satisfied: bleach!=5.0.0 in /usr/local/lib/python3.11/dist-packages (from bleach[css]!=5.0.0->nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (6.2.0)\n",
            "Requirement already satisfied: defusedxml in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.7.1)\n",
            "Requirement already satisfied: jupyterlab-pygments in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.3.0)\n",
            "Requirement already satisfied: markupsafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.0.2)\n",
            "Requirement already satisfied: mistune<4,>=2.0.3 in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.1.1)\n",
            "Requirement already satisfied: nbclient>=0.5.0 in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.10.2)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (24.2)\n",
            "Requirement already satisfied: pandocfilters>=1.4.1 in /usr/local/lib/python3.11/dist-packages (from nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.5.1)\n",
            "Requirement already satisfied: fastjsonschema>=2.15 in /usr/local/lib/python3.11/dist-packages (from nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (2.21.1)\n",
            "Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.11/dist-packages (from nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (4.23.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.1->jupyter-client->ipykernel>=4.5.1->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.17.0)\n",
            "Requirement already satisfied: argon2-cffi-bindings in /usr/local/lib/python3.11/dist-packages (from argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (21.2.0)\n",
            "Requirement already satisfied: webencodings in /usr/local/lib/python3.11/dist-packages (from bleach!=5.0.0->bleach[css]!=5.0.0->nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.5.1)\n",
            "Requirement already satisfied: tinycss2<1.5,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from bleach[css]!=5.0.0->nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.4.0)\n",
            "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.11/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (25.1.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.11/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (2024.10.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.11/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.36.2)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.11/dist-packages (from jsonschema>=2.6->nbformat->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (0.22.3)\n",
            "Requirement already satisfied: jupyter-server<3,>=1.8 in /usr/local/lib/python3.11/dist-packages (from notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.24.0)\n",
            "Requirement already satisfied: cffi>=1.0.1 in /usr/local/lib/python3.11/dist-packages (from argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.17.1)\n",
            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.11/dist-packages (from beautifulsoup4->nbconvert>=5->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (2.6)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.11/dist-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (2.22)\n",
            "Requirement already satisfied: anyio<4,>=3.1.0 in /usr/local/lib/python3.11/dist-packages (from jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.7.1)\n",
            "Requirement already satisfied: websocket-client in /usr/local/lib/python3.11/dist-packages (from jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.8.0)\n",
            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.11/dist-packages (from anyio<4,>=3.1.0->jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (3.10)\n",
            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.11/dist-packages (from anyio<4,>=3.1.0->jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets>=7.6.0->anywidget>=0.9.2->drawdata) (1.3.1)\n",
            "Downloading drawdata-0.3.7-py2.py3-none-any.whl (234 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m234.8/234.8 kB\u001b[0m \u001b[31m11.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading anywidget-0.9.13-py3-none-any.whl (213 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m213.7/213.7 kB\u001b[0m \u001b[31m20.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading psygnal-0.12.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (765 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m765.5/765.5 kB\u001b[0m \u001b[31m39.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hDownloading jedi-0.19.2-py2.py3-none-any.whl (1.6 MB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m65.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: psygnal, jedi, anywidget, drawdata\n",
            "Successfully installed anywidget-0.9.13 drawdata-0.3.7 jedi-0.19.2 psygnal-0.12.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "id": "d89cf99c-5c28-4b17-876f-225c2adc28ae",
      "metadata": {
        "id": "d89cf99c-5c28-4b17-876f-225c2adc28ae"
      },
      "outputs": [],
      "source": [
        "from drawdata import ScatterWidget"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "4bae7d3a-5237-4f81-9566-d9e098012982",
      "metadata": {
        "id": "4bae7d3a-5237-4f81-9566-d9e098012982"
      },
      "outputs": [],
      "source": [
        "widget = ScatterWidget()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "55a6a9af-9760-4cf3-b606-ec4f4b40db7f",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592,
          "referenced_widgets": [
            "df56234ad95a49569987e15754906408",
            "69d102cfd35d4a36972116071e260a00"
          ]
        },
        "id": "55a6a9af-9760-4cf3-b606-ec4f4b40db7f",
        "outputId": "8310dbb4-bee2-4e56-8e8e-fd471b99733a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "ScatterWidget()"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "df56234ad95a49569987e15754906408"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "widget"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "21c01e83-7bfd-4f92-964d-a4ef57ebba5b",
      "metadata": {
        "id": "21c01e83-7bfd-4f92-964d-a4ef57ebba5b"
      },
      "outputs": [],
      "source": [
        "df = widget.data_as_pandas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "id": "478f5591-b1bb-4b39-95b0-911d5dc0444f",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "478f5591-b1bb-4b39-95b0-911d5dc0444f",
        "outputId": "c099459b-5a62-4170-def6-970e9f262979"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              x           y    color label\n",
              "0    283.064793  349.289221  #1f77b4     a\n",
              "1    282.363829  345.211391  #1f77b4     a\n",
              "2    274.640547  314.885856  #1f77b4     a\n",
              "3    285.779866  313.097930  #1f77b4     a\n",
              "4    288.233605  317.574798  #1f77b4     a\n",
              "..          ...         ...      ...   ...\n",
              "219  662.161097  192.538946  #ff7f0e     b\n",
              "220  663.321686  219.590487  #ff7f0e     b\n",
              "221  645.590949  215.748950  #ff7f0e     b\n",
              "222  646.632505  163.575488  #ff7f0e     b\n",
              "223  649.388514  159.371035  #ff7f0e     b\n",
              "\n",
              "[224 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-991e41c9-c1e5-4855-92c0-d8a6003ac347\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "      <th>color</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>283.064793</td>\n",
              "      <td>349.289221</td>\n",
              "      <td>#1f77b4</td>\n",
              "      <td>a</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>282.363829</td>\n",
              "      <td>345.211391</td>\n",
              "      <td>#1f77b4</td>\n",
              "      <td>a</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>274.640547</td>\n",
              "      <td>314.885856</td>\n",
              "      <td>#1f77b4</td>\n",
              "      <td>a</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>285.779866</td>\n",
              "      <td>313.097930</td>\n",
              "      <td>#1f77b4</td>\n",
              "      <td>a</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>288.233605</td>\n",
              "      <td>317.574798</td>\n",
              "      <td>#1f77b4</td>\n",
              "      <td>a</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>662.161097</td>\n",
              "      <td>192.538946</td>\n",
              "      <td>#ff7f0e</td>\n",
              "      <td>b</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>220</th>\n",
              "      <td>663.321686</td>\n",
              "      <td>219.590487</td>\n",
              "      <td>#ff7f0e</td>\n",
              "      <td>b</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>221</th>\n",
              "      <td>645.590949</td>\n",
              "      <td>215.748950</td>\n",
              "      <td>#ff7f0e</td>\n",
              "      <td>b</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>222</th>\n",
              "      <td>646.632505</td>\n",
              "      <td>163.575488</td>\n",
              "      <td>#ff7f0e</td>\n",
              "      <td>b</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>649.388514</td>\n",
              "      <td>159.371035</td>\n",
              "      <td>#ff7f0e</td>\n",
              "      <td>b</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>224 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-991e41c9-c1e5-4855-92c0-d8a6003ac347')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-991e41c9-c1e5-4855-92c0-d8a6003ac347 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-991e41c9-c1e5-4855-92c0-d8a6003ac347');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-b8db8fce-5d44-48dd-ae38-979de0e7571f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b8db8fce-5d44-48dd-ae38-979de0e7571f')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b8db8fce-5d44-48dd-ae38-979de0e7571f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_8d2d963c-f41d-4acc-8c6a-89e226319d41\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_8d2d963c-f41d-4acc-8c6a-89e226319d41 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 224,\n  \"fields\": [\n    {\n      \"column\": \"x\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 158.18543824567095,\n        \"min\": 204.36925486392008,\n        \"max\": 747.1937680188677,\n        \"num_unique_values\": 224,\n        \"samples\": [\n          461.98982280637586,\n          431.8596604291314,\n          489.8679167571748\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"y\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 84.1021538889479,\n        \"min\": 72.93287398172316,\n        \"max\": 409.83510629547527,\n        \"num_unique_values\": 224,\n        \"samples\": [\n          276.37796834345386,\n          312.08844141143186,\n          199.46428535792683\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"color\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"#ff7f0e\",\n          \"#1f77b4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"label\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"b\",\n          \"a\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "id": "e4fd2f4c-7a0f-4b14-aca8-6174635c26e3",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "e4fd2f4c-7a0f-4b14-aca8-6174635c26e3",
        "outputId": "9cad7f26-b92b-4125-e09e-4d37e3df030a"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjsAAAHHCAYAAABZbpmkAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3XdYFNcawOHf7AJL7x0EFSt2sWHvvcSuscWa2BKjJkajiSVq1BijsUYTNfbYe++9966ICFIE6X13z/2D6yoBjAVYxHnv43PD1G+WZfebM+d8RxJCCGQymUwmk8nyKYW+A5DJZDKZTCbLSXKyI5PJZDKZLF+Tkx2ZTCaTyWT5mpzsyGQymUwmy9fkZEcmk8lkMlm+Jic7MplMJpPJ8jU52ZHJZDKZTJavycmOTCaTyWSyfE1OdmQymUwmk+VrcrIj++j5+/sjSRLLli3TdygyWa6QJInx48fr7fx169albt266ZaFhobSoUMH7OzskCSJ3377jSNHjiBJEkeOHNFLnLL8Q052ZPnasmXLkCSJCxcu6DuUHHXixAmaNWuGm5sbxsbGeHh40KpVK1avXq3v0LLVrl273uhLOiwsDAMDA7p3757lNrGxsZiYmNCuXbtsjBBu3brF+PHj8ff3z9bjvokrV67QvXt3ChQogEqlwtbWloYNG7J06VI0Gk2ux/M2vv76a/bu3cvo0aNZsWIFTZs21XdIsnzEQN8ByGT65unpSWJiIoaGhvoO5Z2sX7+ezp07U758eb766itsbGx49OgRx44dY/HixXz66af6DjHb7Nq1i3nz5v1nwuPo6EijRo3YunUrCQkJmJqaZthm06ZNJCUlvTYhehe3bt1iwoQJ1K1bl4IFC2brsV9nyZIlfPHFFzg5OdGjRw+KFi1KbGwsBw8epG/fvgQHBzNmzJhci+d19u3bl2HZoUOHaNOmDSNHjtQtK1asGImJiRgZGeVmeLJ8SE52ZB89SZIwNjbWdxivldUXNsD48ePx9vbmzJkzGb4UwsLCciO8HBcfH4+Zmdlb7dOtWzf27NnDtm3b6NKlS4b1q1evxsrKihYtWmRXmDnqde+BM2fO8MUXX+Dr68uuXbuwsLDQrRs2bBgXLlzgxo0buRXqf8oseQkLC8Pa2jrdMoVCka1/m+/yPpLlE0Imy8eWLl0qAHH+/Pkst3n06JEAxNKlS3XLevXqJczMzERgYKBo06aNMDMzE/b29mLEiBFCrVan21+j0YhZs2YJb29voVKphKOjoxgwYIB4/vx5uu22bNkimjdvLlxcXISRkZEoXLiwmDhxYobj1alTR5QqVUpcuHBB1KpVS5iYmIivvvoqy/hVKpX47LPP/vO1OHz4sADE4cOH3/j6Hz58KBo3bixMTU2Fi4uLmDBhgtBqtRn2nTFjhvj111+Fh4eHMDY2FrVr1xbXr1/PEMPBgwdFzZo1hampqbCyshKtW7cWt27dSrfNjz/+KABx8+ZN0bVrV2FtbS3Kly8vevXqJYAM/7ISFxcnzMzMRKtWrTKsCw0NFUqlUvTt21e37MyZM6JJkybC0tJSmJiYiNq1a4sTJ05k2DcwMFD06dNH93ssWLCg+OKLL0RycrLu/fbvf6++5vPmzRPe3t7CyMhIuLi4iEGDBonIyMh053jb90DTpk2FgYGBePz4cZbbvAoQP/74o+5nf39/MXDgQFGsWDFhbGwsbG1tRYcOHcSjR4/S7ZeSkiLGjx8vihQpIlQqlbC1tRU1atQQ+/bt020THBwsPvvsM+Hm5iaMjIyEs7OzaN26dbpj1alTR9SpU0cIIbJ8zYTI+j37Jr+rrN5Hso+T3LIjk2VBo9HQpEkTqlatyi+//MKBAweYOXMmXl5eDBw4ULfd559/zrJly+jduzdffvkljx49Yu7cuVy+fJmTJ0/qHo8tW7YMc3Nzhg8fjrm5OYcOHeKHH34gJiaGGTNmpDt3REQEzZo1o0uXLnTv3h0nJ6cs4/T09OTgwYMEBgbi7u6erdfftGlTqlWrxvTp09mzZw8//vgjarWaiRMnptv277//JjY2lsGDB5OUlMTs2bOpX78+169f18V+4MABmjVrRuHChRk/fjyJiYn8/vvv1KhRg0uXLmV45NOxY0eKFi3KlClTEEJQoUIFnj59yv79+1mxYsV/xm9mZkabNm3YsGEDz58/x9bWVrdu3bp1aDQaunXrBqQ9QmnWrBk+Pj78+OOPKBQKli5dSv369Tl+/DhVqlQB4OnTp1SpUoWoqCgGDBhAiRIlCAoKYsOGDSQkJFC7dm2+/PJL5syZw5gxYyhZsiSA7v/Hjx/PhAkTaNiwIQMHDuTu3bssWLCA8+fPp3uvwJu/BxISEjh48CC1a9fGw8PjP1+XzJw/f55Tp07RpUsX3N3d8ff3Z8GCBdStW5dbt27pWpTGjx/P1KlT6devH1WqVCEmJoYLFy5w6dIlGjVqBED79u25efMmQ4cOpWDBgoSFhbF//34CAgIyfaxXu3ZtVqxYQY8ePWjUqBE9e/Z8baxv+rt64d/vI9lHSt/ZlkyWk96nZQcQEydOTLdthQoVhI+Pj+7n48ePC0CsWrUq3XZ79uzJsDwhISHDuT///HNhamoqkpKSdMvq1KkjALFw4cI3usY///xTAMLIyEjUq1dPjBs3Thw/flxoNJp0271tyw4ghg4dqlum1WpFixYthJGRkXj27Fm6fU1MTERgYKBu27NnzwpAfP3117pl5cuXF46OjiIiIkK37OrVq0KhUIiePXvqlr24I+/atWuGax08ePBrW3P+befOnQIQixYtSre8WrVqws3NTWg0GqHVakXRokVFkyZN0rVaJSQkiEKFColGjRrplvXs2VMoFIpM308v9l2/fn2mr3NYWJgwMjISjRs3Tve7mTt3rgDEX3/9pVv2Nu+Bq1evCuC1LT//xr9adjJ7b54+fVoA4u+//9YtK1eunGjRokWWx42MjNS19L3Oqy07r8Y0ePDgdMv+/Z59m9/V695Hso+PPBpLJnuNL774It3PtWrVws/PT/fz+vXrsbKyolGjRoSHh+v++fj4YG5uzuHDh3XbmpiY6P47NjaW8PBwatWqRUJCAnfu3El3HpVKRe/evd8oxj59+rBnzx7q1q3LiRMnmDRpErVq1aJo0aKcOnXqXS5bZ8iQIbr/liSJIUOGkJKSwoEDB9Jt98knn+Dm5qb7uUqVKlStWpVdu3YBEBwczJUrV/jss8/StbCULVuWRo0a6bZ71b9f+3fRuHFjHBwc0o1Ke/ToEWfOnKFr164oFAquXLnC/fv3+fTTT4mIiND9DuPj42nQoAHHjh1Dq9Wi1WrZsmULrVq1olKlShnOJUnSa2M5cOAAKSkpDBs2DIXi5Udv//79sbS0ZOfOnem2f9P3QExMDEC6fjpv69X3ZmpqKhERERQpUgRra2suXbqkW2dtbc3Nmze5f/9+lscxMjLiyJEjREZGvnM8WXnT39WrsuN9JPvwyY+xZLIsGBsb4+DgkG6ZjY1Nug/x+/fvEx0djaOjY6bHeLWD8M2bNxk7diyHDh3SfUG9EB0dne5nNze3txqB0qRJE5o0aUJCQgIXL15k3bp1LFy4kJYtW3Lnzp0s43sdhUJB4cKF0y0rVqwYQIZh1UWLFs2wf7Fixfjnn38AePz4MQDFixfPsF3JkiXZu3dvhs6jhQoVeuuY/83AwIDOnTszf/58goKCcHNz0yU+Lx5hvfji7tWrV5bHiY6OJiUlhZiYGEqXLv1OsWT1GhgZGVG4cGHd+hfe9D1gaWkJpCXQ7yoxMZGpU6eydOlSgoKC0j3uefW9OXHiRNq0aUOxYsUoXbo0TZs2pUePHpQtWxZIS9CmTZvGiBEjcHJyolq1arRs2ZKePXvi7Oz8zvG98Ka/KxsbG93P2fE+kn345GRHJsuCUqn8z220Wi2Ojo6sWrUq0/UvkqWoqCjq1KmDpaUlEydOxMvLC2NjYy5dusSoUaMy3I2+eqf9NkxNTalVqxa1atXC3t6eCRMmsHv3bnr16pVly0Nerb/yrq/Bv3Xv3p25c+eyZs0aRo4cyZo1a/D29qZ8+fIAutd+xowZumX/Zm5uzvPnz7Mlnjf1ptdfpEgRDAwMuH79+jufa+jQoSxdupRhw4bh6+uLlZUVkiTRpUuXdO/N2rVr8/DhQ7Zu3cq+fftYsmQJs2bNYuHChfTr1w9IG/3VqlUrtmzZwt69exk3bhxTp07l0KFDVKhQ4Z1jhDf/Xb0qu95Hsg+bnOzIZO/By8uLAwcOUKNGjdd+qB45coSIiAg2bdpE7dq1dcsfPXqUY7G9eNQSHBwMoLvbjYqKSrfdv1sUXtBqtfj5+elacwDu3bsHkKGjaWaPNe7du6fbztPTE4C7d+9m2O7OnTvY29u/0ZDg/3pUlJmqVavi5eXF6tWradSoETdv3mTy5Mm69V5eXkBaC0nDhg2zPI6DgwOWlpb/OYQ7qxhffQ1ebTFLSUnh0aNHrz3365iamlK/fn0OHTrEkydPKFCgwFsfY8OGDfTq1YuZM2fqliUlJWV4rwDY2trSu3dvevfuTVxcHLVr12b8+PG6ZAfSXtMRI0YwYsQI7t+/T/ny5Zk5cyYrV658p2t89bjw378rmezf5D47Mtl76NSpExqNhkmTJmVYp1ardV8WL1qJXn08kJKSwvz58987hoMHD2a6/EU/mBePTTw9PVEqlRw7dizddq+LYe7cubr/FkIwd+5cDA0NadCgQbrttmzZQlBQkO7nc+fOcfbsWZo1awaAi4sL5cuXZ/ny5em+QG/cuMG+ffto3rz5G1wpuoQosy/h1+nWrRuXL1/mxx9/RJKkdIUWfXx88PLy4pdffiEuLi7Dvs+ePQPSHut98sknbN++PdOK3C9+t1nF2LBhQ4yMjJgzZ06698Gff/5JdHT0e9X7+fHHHxFC0KNHj0yv4eLFiyxfvjzL/ZVKZYaRSr///nuGVr+IiIh0P5ubm1OkSBGSk5OBtJFhSUlJ6bbx8vLCwsJCt837eNPflUz2b3LLjuyj8Ndff7Fnz54My7/66qv3Om6dOnX4/PPPmTp1KleuXKFx48YYGhpy//591q9fz+zZs+nQoQPVq1fHxsaGXr168eWXXyJJEitWrMiWobBt2rShUKFCtGrVCi8vL+Lj4zlw4ADbt2+ncuXKtGrVCgArKys6duzI77//jiRJeHl5sWPHjiwLDxobG7Nnzx569epF1apV2b17Nzt37mTMmDEZ+jIVKVKEmjVrMnDgQJKTk/ntt9+ws7Pj22+/1W0zY8YMmjVrhq+vL3379tUNPbeysnrjeZp8fHwA+PLLL2nSpAlKpTLTgoH/1r17dyZOnMjWrVupUaNGupYphULBkiVLaNasGaVKlaJ37964ubkRFBTE4cOHsbS0ZPv27QBMmTKFffv2UadOHQYMGEDJkiUJDg5m/fr1nDhxAmtra8qXL49SqWTatGlER0ejUqmoX78+jo6OjB49mgkTJtC0aVNat27N3bt3mT9/PpUrV36vSs7Vq1dn3rx5DBo0iBIlSqSroHzkyBG2bdvGTz/9lOX+LVu2ZMWKFVhZWeHt7c3p06c5cOAAdnZ26bbz9vambt26+Pj4YGtry4ULF9iwYYOuI/u9e/do0KABnTp1wtvbGwMDAzZv3kxoaOgb/Z7+y9v8rmSydPQ3EEwmy3lZFSx78e/JkyevLar3by+Gs/7bH3/8IXx8fISJiYmwsLAQZcqUEd9++614+vSpbpuTJ0+KatWqCRMTE+Hq6iq+/fZbsXfv3gzDlF8UlHtTa9asEV26dBFeXl7CxMREGBsbC29vb/H999+LmJiYdNs+e/ZMtG/fXpiamgobGxvx+eefixs3brxRUUEnJyfx448/phs2/WpRwZkzZ4oCBQoIlUolatWqJa5evZoh1gMHDogaNWoIExMTYWlpKVq1apVlUcEXw9tfpVarxdChQ4WDg4OQJOmthqFXrlxZAGL+/PmZrr98+bJo166dsLOzEyqVSnh6eopOnTqJgwcPptvu8ePHomfPnsLBwUGoVCpRuHBhMXjwYJGcnKzbZvHixaJw4cJCqVRm+P3OnTtXlChRQhgaGgonJycxcODALIsKvq2LFy+KTz/9VLi6ugpDQ0NhY2MjGjRoIJYvX57u98a/hp5HRkaK3r17C3t7e2Fubi6aNGki7ty5Izw9PUWvXr102/3000+iSpUqwtraWpiYmIgSJUqIyZMni5SUFCGEEOHh4WLw4MGiRIkSwszMTFhZWYmqVauKf/75J8P1vcvQ8xfe5Hf1uveR7OMjCSFXWZLJZOl99tlnbNiwIdNHBa/y9/enUKFCzJgxI92cRjKZTJaXyH12ZDKZTCaT5WtysiOTyWQymSxfk5MdmUwmk8lk+ZrcZ0cmk8lkMlm+JrfsyGQymUwmy9fkZEcmk8lkMlm+JhcVJK0s/tOnT7GwsHincvQymUwmk8lynxCC2NhYXF1dUSiybr+Rkx3g6dOn7zSfjEwmk8lkMv178uQJ7u7uWa6Xkx3AwsICgK2r9mNm+t+TEcryJiEEjdrVpChlcKNQpttc4wzFKhXlp++n53J0MplM3+48CsM/LpYkZ0O07o/xtgumokMB3E0K//fOsjwpNjaBUsW66b7HsyInO7ycpdjM1AwzM3M9RyN7H4U9ixAdEIEnxTKs0wg1sYpIShQtKf+eZbKPzK2HoZzXxqItKrB3DaOBZwoeZsXwMC2i79Bk2eC/uqDIHZRl+UqHNl14Jp4SLoLTLRdC8IAbqEUqrZu101N0MplMH3Zcuc+x+BBsy5lSt+xNGnhGU9OhqpzofETklh1ZvtKqWVtOnT3GyXPHccINe+GCGjUhigCitOGMHDwGF2c3fYcpk8lyWXmfgkg2apzMzKnpUFXf4chymZzsyPIVA6UBU3/8lQ3b1rJhyxpuhJwDwKdMFbp1mohv5Zp6jlAmk8lkuU1OdmT5joGBIV3a9aBz2+4kJCZgYGCAykil77BkMplMpidysiPLtyRJkkfXyWQymSzvdFD++eefkSSJYcOG6ZYlJSUxePBg7OzsMDc3p3379oSGhqbbLyAggBYtWmBqaoqjoyPffPMNarU6l6OXvan4hHg2bV/H2MnfMHbyN2zYtpb4+Dh9hyWTyWSyfCxPtOycP3+eRYsWUbZs2XTLv/76a3bu3Mn69euxsrJiyJAhtGvXjpMnTwKg0Who0aIFzs7OnDp1iuDgYHr27ImhoSFTpkzRx6XIXuPazSuMHDuEuPhYbBT2ICQOHd3Hwj/nMH3SHCqWraTvEGUymUyWD+k92YmLi6Nbt24sXryYn376Sbc8OjqaP//8k9WrV1O/fn0Ali5dSsmSJTlz5gzVqlVj37593Lp1iwMHDuDk5ET58uWZNGkSo0aNYvz48RgZGenrsj4YcfGxbNu9iV37thEZFYmTozNtmrejacNW2drP5VlEGF+PGYhxsik1qImxMAUgiURuJ59n5PeDWf3nFpwdXbLtnB+DxMQEjp0+TMTzcOxs7antWw8TE1N9hyWTyWR5it4fYw0ePJgWLVrQsGHDdMsvXrxIampquuUlSpTAw8OD06dPA3D69GnKlCmDk5OTbpsmTZoQExPDzZs3szxncnIyMTEx6f59jMLCQ/lsYGfmLf6NuMdJWEU5EH4/gp9/m8TgkX2JT4jPtnNt3bmB1OQUymh9MZZefhkbSyaU0fqiSdWwecc/2Xa+j8Gm7eto2aUB438ezcIlvzP+59G07NKADdvW6js0mUwmy1P0muysXbuWS5cuMXXq1AzrQkJCMDIywtraOt1yJycnQkJCdNu8mui8WP9iXVamTp2KlZWV7t/HOi/WhKmjiXwWSTXRiDJUxUsqRTlqUJm63Lt3hzmLfsm2cx07dQQ7rQuGUsbWNgPJEHutG8dOHM628+V323ZvYsbvk7FJdKQGzagjWlODZtgkOjFz7hS27tqg7xBlMpksz9BbsvPkyRO++uorVq1ahbGxca6ee/To0URHR+v+PXnyJFfPnxc8eHSPS9cv4KUpjamUfuoEK8kOD20xdu/fTnRMdLacLyUlGQMMs1xvgAHJKcnZcq78Tq1OZeFfv+OMByUlH0yktBFnJpIZJaWKOOPBor/mkpqaqudIZTLZhyQqKo75czfRpMGXVK/cl56fTuDQgQsIIfQd2nvTW7Jz8eJFwsLCqFixIgYGBhgYGHD06FHmzJmDgYEBTk5OpKSkEBUVlW6/0NBQnJ2dAXB2ds4wOuvFzy+2yYxKpcLS0jLdv4/N9ZtXkZBwIPNqwk64kapO4d7D29lyvhLFvIlSPsv0j0YIQaQyjJIlSmXLufK7S1cvEBmd+fxfAJ4UIzLmORevnsvlyGQy2Yfq4YMgalXrz49jF+FqG0h93xge3b9EuzZjGDJwJlqtVt8hvhe9JTsNGjTg+vXrXLlyRfevUqVKdOvWTfffhoaGHDx4ULfP3bt3CQgIwNfXFwBfX1+uX79OWFiYbpv9+/djaWmJt7d3rl/Th0ShkBD//19mXixXSNnzFmnfugtxmhj8uZthXQD3idVE0751l2w514dKCMHT4EAe+N0jLj42y+2iY6IAMCHzGkKmmKfbTiaTyV5Hq9XSvcsPmKriuXfKkw1/ujD7J0cuH3Bj2RwnVq/cx8L5W/Qd5nvR22gsCwsLSpcunW6ZmZkZdnZ2uuV9+/Zl+PDh2NraYmlpydChQ/H19aVatWoANG7cGG9vb3r06MH06dMJCQlh7NixDB48GJVKrpj7OhXLVQYglCe4UjDD+hACMFGZUKJY9rS2lPEuR5/un/PXykVESqE4aN2QkAhTBPFchNGjc5+Peuj50ZOHWPL3fB48ugeAoYEhjeo1Y2Cfr7C3c0i3rYuzKwAxPMcWpwzHiuZ52nZO8hxgMpnsvx05dInbt59wdIs7Hu4vuxtIkkSPjpYcPJ7IogUb+WLQJygUeh/X9E7ydNSzZs2iZcuWtG/fntq1a+Ps7MymTZt065VKJTt27ECpVOLr60v37t3p2bMnEydO1GPUH4YCbp7UqFqHh4obxIjn6daFi2ACpPt80rJjtlYg7t9zMNPGz8bD24N70lXuSldwL+HGlHEzGdR32H/uL4QgPOIZwaFPUavzT3+Ubbs38t2EYUT6R1MWXypTD091cQ4d3E//L7sT8Tw83falSpTF070Qj6Q7aEX6pmWt0OIv3cbDrSBlvMvl5mXIZLIP1PFjV3FzMaJGlcz7z3ZqY85j/2cEBIRmuv5DoPc6O686cuRIup+NjY2ZN28e8+bNy3IfT09Pdu3alcOR5U/jvpnEl98O4JzfIWwlR0y05sQrookSEfhWqskXvb/M9nPWrl6P2tXrodFogLSE9U3sP7yb5WuW8ND/PgA2lra0a92JHl36ftDzXsXExjBz7lTcKEQJURFJkgCwwg4nbQEuRBxhyYoFjPpqnG4fSZL49quxfPXd51wSRymgLYo5VsQTQ4DiHrFSNBO+nKI7lkz2Mbv18OUXdCL++gskDxMirWtDVnSrPuB+ynm6ZUeWs6wsrVk8ZyU/fjsFr3KFMSloQOkqZZg+YQ4zJv6eo0UZlUrlGyc6y9Ys5oepo4h5HEcZqlGempjF2LBs1RKGjxlESkpKjsWZ0/Yd3oVaraYwpTIkJyaSGW7aQuzev52kpMR06yqWq8zcGUtwK+rKdc5wmr1c4zSuRV35fdofVKpQNTcvQybLk249DMUvNoaAAvEEKC7jaHgHDzM7fYeV42JjEwgJjiA19c2mTvKtUZonQcmcu5z5iNgNO+Jwd7ejgIdjdoaZq/JUy44s9xkZGdG0YUuaNmyp71AyFRDoz6Klv1OIknhRCv6fD9jjjJNw5/L142zdtYGOn3yq30Df0ZOgx5grLVFpMm8+tsYOv5RbRERG4Obinm5dudIVWfL7KgIC/Ql/Ho69rT0e7gVzIWqZLO+79TCUY/EhaAsIvEtqKGMdjYeZJx6mRfQdWo45e+Ymv85Yzb69acPFra1N6d6zOSO/7Yq1jUWW+zVsVAkvLxcGjHzG3rUuODu+TA027ojl739i+WF83ze+Qc2L5GRHlqdt3bURlcKYgtoSGdbZSA444MrGbes+2GTHwsyCJG0iWqHNdORbEmktOuZm5hnWveDhXlBOcmSy/3vRmhOoSMC2ciSl7YNwMjOnpkP+bu3ctfM0PT+dgHdxFXOn2uPmYsCJs0ksXraFA/vOsHv/b9jYZl5mRalUsnLtBD5p+Q1Fqj2mfQszXJ0NOHo6mbMXE2jXvjZDvmqfy1eUveTHWLI87fGTR1hobVBKmd9R2AgHAoIef7BFrxrWbUqKNpkQAjKs0wotQQo/KpWvipWlde4HJ5N9gPxiY0hyMcS2nCml7YOo7OiZ7xOdhIQkBn8+nRYNTTm3240velnTqrE508bZc3qnG6EhIUz56e/XHqOkd0FOnl3MyFG9uHrPjn92GGBhW5IVa35gybIxH3SrDsgtO7I8ztTElFRFcpYd45JJwlhlnGVn3KTkJE6cPsKz8DBsbeyoVb0epnloosyCHoVpWKcph48dQCs0uFAQpaQkXsTyULpBHNH06f65vsOUyT4o7u42SDZqnMzM8/Vjqxe2bj5OVFQ8M370xNAw/Wdh8SJGDPrMkjl/7mPCT/0wNc16xgJ7B2tGfNOVEd90zemQc52c7MjytLo1G7L/yB5ieI6lZJtunUaoCVU+oWHdJpnuu233Jn5f9AtxCXEYKgxJ1aZiYmzKF72H0qltt9wI/42M/WYSSqWSfYd28UC6jhJDkknERGXK5FG/UOEjrj8kk+UXT5+G89fi7WzfeoyEhCRKlCxI736tada82nuPnLxz+zGFPIzxKpj5oJIGtUyY/NtzngaFU6Soe6bb5HfyYyxZnla7ej0KexbhuvIsESJU97gqXsRyTXEajSKVru17Zthv94HtTJ01HssEO6rTlDqiDTVohl2SC7MWTGNjHpoZXGWkon+vwbi7eqAWajSkYiSpSExK4Pc/fsXP/4G+Q5TJZO/h0sW7VK/cjz8WrKemTyzd22qJDr/Np51+ZPAXv7z3VAymZsZERqtJTc28CTwsIq3Uh4nph1um433JyY4sTzMwMGT2z4soWLgglznOKeUezir3c5q9qM2S+XXKfAp5eqXbR6PRsGDJbJxwpySVdBOdmkhmlJAq4EpB/lg2L88MWY9PiGfIyL48D43EhzrUEW2oJVpSmXrEhsYx5Jt+PI+M0HeYMpnsHSQnp9Ct8w8U9xL4nfPgj5lO/DQ6rS/N8t+dWLNqP38t2fFe52jZqgaRUWr+2ZZxmhkhBH+siKWiTxHc3Bwy2fvjID/GkuV59nYO/Dl3NVeuX+TUueOkpqZSoqg39Wo3yrSg4NWbl3n2PIzK1EOSJFJEMhGEokGNOZZ4UJQzcfs5d+k0NavV0cMVpbdr/zZCn4XgS5N0M9BbYUc5bQ1Ox+5ly84Nct8dmewDtG3LCYKDI9m/1hMb6/SdfLt3sGTH/gQWzd9E3/6t3vlxVqnShWjeshqDvzuPSiXRtpk5SqVExHMNP0yP4NDxeFat654dl/PBkpMd2QdBkiQqlK30Rv1XYv4/AaYKU+6KKwThh5aXzcTmWAF5Z6LMA4f3YC+56CbwfJVKMsZB68r+Q7vlZEcm+wCdPXOTUiVMKFks8/407VuasX7bUyLCo7F3sH7n8yxa8h39PptM5/7ncXU2wtnRgJt3kxBCYtacL2nRsvo7Hzs/kJOdfEStUXP2wilCQp9iZWlN9aq189TIo9zi7Jg2UeYtzhPJMwrhjTuFMcSI54TxgOuAlG0zur+vuLhYVMJYVzDx31SYEJ/wPPOVMpksT5MkCa0m69IY/5855707KVtYmLJu42QuXbzLlk3HiI1NoF1XN7p0bfheSVR+ISc7+cSxU4eZPnsSEZHhKCQFWqHFRGVCnx5f0K3jZx/VPEnFi5akgIsHT4IDKEFF3KXCunV2OGElbDnNPs5ePEWzRq30GGmaggULcyHoHEIjMv09xSgiKFSgkB4ik8lk76tm7XIsXrSNqzeTKVcq42P3dVviKF3aE1u7zAv+va2KPsWp6FM8W46Vn+SNW1vZezl9/gTfTRiGIsqIKjSgPu2oQTPsk92Yt2QWK/9Zqu8Qc5UkSXiXLI0BhrhSMMN6A8mQAnhx8OjePNFJ+ZMWHYjRRBHM4wzrwsRTnmuf8UnLjnqITCaTvRAXl8iqFfuYPGk5837fSFDQszfar3kLXzwLOtLryzCCgl/OVaXVCub+GcW2vXF8MbjDR3VDqg9yy84HTgjBvMW/YYMDZYWv7g/GRDKjOOWRhMSfKxbSrmUnzF4z5UB+Y2iowlxhiUJkns+bYoFaoyY+IQ4jI9tMt8ktlcpXpWXjT9ixbyuRPMNJFEBCIoxAgqXH1PGtT72aDfUao0z2MVuzaj+jRv5OXFwyLk5GRESm8sP3i+nbvxVTpn2BgUHW1YUNDQ1Yu/4n2rUeRZFqj2nZyBRHeyWHTiRz72ESg4a0o1uPxrl4NR8nOdn5wPkH+PHQ/x7lqJ7pnYEHxQhIecDRU4do3qi1HiLUD0cHRxKIQyPUKKWMb/NYojBWmWBhnvXkeLlFkiRGDx+PV+GirN2wgivhJwCwtbajf9vBdO/UW2+l2qNjojh4dC8RkeHY2TrQoHYTrCytdOvVGjWPAx6h1WrxKFAw09FxMlluufUwVPffifhnyzF37jjFwAEz6NHRkgnfOONZwJDYOC1/rIhm9ORtKBQSP88Y9NpjlPQuyOnzS1i5Yi87th3nQWAi5SsVYvbCVvhWL50tcb6OVqslMTEZExMVCsXH+UBHTnY+cJHRkUBaS0VmjCUTDCUDov6/3ceieaM2LF35B094QEHSTyKaLJIIVvrTrFFLDAwM9RRhegqFgi7tetCxzacEhz5FCIGLsysGSv38iQoh+Hvtn/y5YgEajQZjhQlJ2kR+mz+d/r0G0bV9T9Zs/Ju1G1fwPCqtBpC5qQVtW3Wib48v5KRHluteTAAaUCCeBMVlGlhH42Fm917HFEIwddJSGtUxY+lsR90NpYW5ghEDbVCrBT9M38bXI7rg5Pz6FmJrGwuGfNmBIV92eK+Y3sbTp+HM/vUf1q7eS3R0IhYWxnT5tDFfDe+Eu7tjrsWRF8jJzgfOycEZgBiekywSCSMINamYYo4rBdGgIVWk4uTooudIc5ebizvdOn3Gyn+WkigS/j8aS8VzQvFX3sXUwpTPuvbXd5gZKJVK3F0L6DsM1m1eycKlc/CkGJ4Uw0hrTLJI4rH6LvP//I0jJw5y++4NXClIRUqhQEFYQhCr/1nOnXs3+XXyvDyTSMryvx1X7hOoSEBbQFC37M20ObHM7N57XqwH9wO5ceMxk/92ybTl/POeVvw44znbt52g3wD9tJynpqrZvvUE69bs59mzSFxdHenWswnFihWgZdMRpKbE8XkPc8qUtOTW3RSWrNrN1s1H2b3/N7yKuOklZn2Qk50PnJuLO6VLluPO7SuoScUEM1SY8IynPOI25lhhaW6VJ4rn5bZBfYdhbWXDirV/cTbWDwAJiSrlq/Ptl9/j+P9EUZZeckoyf61YhBuFKSqV1S1XScYUoxzxIoZbd6/jTSVcpYK69dbYYy9cOH/5GHsP7aJF4zZ6iF72MXnRmpPkYoitR6RulvPsmvwzOjoOAA+3zBN3ayslVpYGREfHZ8v53lZ0dDwd237HubN3qVHFlArFDbhyI4iuHU9hb2+BlXkKx/a44+z48qv+y/7W1G0bzJCBM9i9/ze9xK0PcrKTD0iAQFCeGtjhjCRJqEUqj7jNY+7Rvn6Xj/KxgiRJdOv4GZ0+6cb121dJSkqkkEdhXJw/nruZd3Hh8lli42MoTbUstzHBHBc8Myy3lRyxl5zZsmODnOzIctyLREfrnEoDz2g8zLIv0QHw8HBGqVRw8nwiZb0zfobefZBCeEQqhQu7Zts538awIb9y785Djm9zp3plE93yRSuiGfRtGLMmOKVLdAAc7Q2Y8K01XQbc4tbNR3iX+jjKWsjJzgfu3sM7XL99ldJUxV56+ajKQDKkiChDvBTDlasXESLzGi4fA0NDQyrKM4e/sbi4tPl1jMm8IGUKydhgn+X7yVJrS+DTgLc6p0aj4dyl09x7cAcjQyN8q9SioMfH8SEsez/u7jZINmlDurMz0QFwdLKhWfNqzJx/kY4tLbC3ezlQQKMRjP05Ant7C5q39M3W876JgIBQtmw+wfxpDukSHQBb67ROyE3rmWW6b7P6actv3pCTHdkH4vjpIxgpVDhqM7ZWSJKEqyjEtcenCQkLxsVJP3cfsg/Liz5DUYRjR+aP+hJJyHL/JBLeapTbrbs3GDvpG4LDglApjdEIDXP++IVa1erx46jJH1XJBFneM2nKABrX/5KqzYL4+nNLqvoY4/8kld+XxHD6QiJLV4xFpcp8KoicdOLYVYQQfNou49+aiXHajUhktAZbm4wjOZ9HppVtVhnnftz6Iic7H7jk5GQMFUZZ1pMxxEi3nUy/wsJDOXx8PzGx0bi5FKBezYaY5MHpPLxLlKGwZxEePbmDtdYBpfTK3axQo5ZSiRVRxIlozCWrdPsmiyTCFEF81qDfG53rSVAAQ7/tj1GyCZWph6XGFoGWUAI5e+4kI8cNZd4vf360w2Vl+leosCv7D//O+HFLGDH+JGp12jx7VauVYNPWz6hbv6Je4tJo0uJYsymGTbviiYrWUKSQEf26WVK7mgnmZhJ/rophyvf2Gfb9a00MpqZG1KlbIbfD1hs52fnAFSlclHh1LPHEYCZlLDceQSgmxqY4O8qdcfVFrVEzZ9EvbNy6FgkJI4UxiZoEZs6dysihY2jWMOOUFeERz9i+ZzM371zHwMCAKj6+NKnfAjPTzJuls5MkSYwa9gNDv+3HBQ5TQFsEMyyJJ4YnigdoFKk427hw9fkpimnKYU/a49MowrmnvIqluSVtW3Z6o3OtWr8MkSIor62BgZTWCVRCiQueGGlVXL5xggtXzlGlYtb9h2SynFawkAvLVo7jeUQMgYHPsLG1oEAB/Q7dLlTYFaUSBo56Rv1aJpQqoeL0+UTqb4qld1dLqlQwZsb8SAp6GNK7iyWGhhJqteDv9TFMnRPJwMHtsbLK+c+TvEJOdj5wdWs0xMrCmvtx1ygjfNPdhceJaJ4qHvFJ0/YYG5u85iiynPT7opls2LoWL1EKdwpjoDUkkXj8km4xcfr3mJuZU8u3nm77Q8f2Mf7n0Wg1Ahthj1bScuzkIRYvm8dvPy+keJGSOR5z2VLlWThrOQv+nM35y2d0y6tWqM7APl9ia2vPmAkjuHrnFEYKFZIkkaxJwtOlED+Pn4WtzX/XNxFCsO/gTpw1nrpE51W2OGGhtGL/4d1ysiPLE2ztLLNtDqv3IYRg0vglONobsGetK6VLqHTLl/8TS7+vQ1EZSRQq5MrAb58ycWYUxYsYcu9hKk9DUujyaUN+nNhXz1eRu+Rk5wNnZGTExDHTGDluKOfFQVw0nqgwJYpnhCie4OlRiP69Bus7zI9WeMQzNm5bi5fwpqD0cnI+E8kMb1GJFCmJRUvnUrNaXSRJ4t7DO/wwZRQOwpXiogKGUtpjyETiuRF3lq9Gfc6Gv3dibpbzlZ9LFivFnGl/8CwijOeREdjZ2GNv56Bbv3jOCm7euc75y2fQarSULVUen/JV3rgjvFarJTE5EWMyv7uUJAkjjQkxsdHZcj0yWX5x8cIdzp65w9a/XXSJDqT9zXzW2ZITZxNZszmBvYdmExIcwZpV+wkJjuCTCrZ0+bQRZct56TF6/ZCTnXygio8vi+esYMXavzhy4gAarQYbS1t6tu7Dp+17yR08/0WtTmXvoV1s3r6ewKcBmJtZ0KRhc9q36vJGLRJv48jJgwghcKNwhnWSJOEuvLjqf4onQY/xcC/I2o0rUUkmeGsro5Be9lMxkcwoo63Gqbg97N6/nY6ffJqtcb6Og50jDnaZN9mXKlGGUiXKvNNxlUolDnZOREdE4EbGESFaoSFOGY2bi/s7HV8my6+OHL6MtZWBblTVv3Vrb8HSNTE8C4ukdJnCTP7581yOMO+Rk518oniRkvw0dgZqdSrJKSmYmph+tEPNXyc5JZmRY4dw4co57CVn7IQrSbGJrFj9F5u3r2feL39SyDP77nri4mIwVKgw1GY+6uHF8O7Y/w/3PnnmKI4a93SJjm5byRQbHDlx9liuJjs5qW3Ljvy1YiEe2qIZOjsH8IBkTSKtm7XTU3QyWd6k0WgxMJDIqt++kaGk206WRh7ikM8YGBhiZmomJzpZ+HPFQi5fvUhFalGeGhSWvPGWfKimbYI6Vsvo8V8jhMi287m7epCsSSRexGa6PpoIFJJCVxZArVZj8Jp7EKUwIDUlJdvi07dObbvhWaAQlxTH8BO3iBGRPBdh3OQcD7hO9069KeiRsVVMJvuYValSkvCIVE6eS8p0/eZdcdjYmFGkaN5tFdVqtRw+eJHP+02nXevvGDroV86cvpmtn7+vkpMd2UcjOSWZzdv/wU0UwlZK/1hGJRlTTFuOx0H+XLxyLtvOWat6PSzNrXgoZfwjThHJBCgfUKNaHd3jsxLFvIlQhGZ2KDRCTZTiGd4lcn6W5NxiZmrGgllLada0FUGGDznHQS5xDI1dCiOHjGFQ32H6DlEmy3Pq1KtA8eJuDB4dTugzdbp1h04ksGB5DJ/1aYlxHq2jk5CQRKd239O29WhuXDqBtfE9Th87TNOGX9O/91RSU9X/fZC3JD/Gkn00Ap74E5cQSwl8Ml1vjT0qpTHXbl6hUoWq2XJOlZGKUcPGMXbyN1ySjuEuvDDBlGie80T5AENTA778fKRu+46fdGX0teEE8Qg36WU/FiEE97lGqkjhkxYdsyW2qOhINm3/hz0HdhATG42LkyuftOxAs4atMTLK+Q/JB373+GfLas5fPAMIalWvS7XKNSlepCSFPL1QKjMWQ5PJZKBQKFi+ajxtWoykmG8AnduY4eluyMnzSew9HE/9BhX47vse+g4zS98Mn8upk1fY+rcLLRqmPYnQagVrNsfSZ9hR3As4MX5S9o4Wk5Md2UfjRWE6LVk/xxZCoFBmb4Nn/dqNmWVqzh/L53H9btowbqVCSS3fegzu93W6Wc7r1GhAu1ad2bR9HWHSE+y0LmjREKYMJFYTzaivxmXLrOiBT58waHhvIqMicdC6YYcbEXGRTPttErv2bee3qQtytODh7gPb+WnGOFQKE+w1LkhInD5xioNH9zF8yGiKFC6WY+eWyfKDEiU9OX76D5Ys3s7mDQeJPhBPocIFmLewJZ261MfQMG9+vYcER7BuzQGmj7OlZaOXg2cUColu7S25eSeF+Yu3MnLUp5ibZ1/JlLz5ashkOcDToxB2NvaERj7Bloyji8IJJkWbTOUK2V/TpWql6lStVJ3gkCBiYqNxcnTB2somw3aSJDFyyBjKl67IP5tXc/v+TZQKBVUr1aBr+x5UyIY5voQQjJ00ksToJKppG2MsvfxAiSKCq3dOsOCvOQwf/N17nyszj5884qcZ43AWHpTQVNR1xhaastznGr/OnYp38dJ4F88/j+tkspzg6GTDmLE9GTO252u3E0Jw7OgVVv29h4CAEGxsrejYqT4tW9fAyCjzGd1zytEjl1GrtfTslHm9op6dLJk2N5JzZ25Sv2H2zWkoJzuyj4aB0oAu7bszf8lsrIQdLnjqOnLHiWjuKa9Sumi5HP2SdXF2+89Z1yVJolG9ZjSq1yxHYrhx+xp3H96mAjXTJToA1pId7toibN+zmc97D82Ris2btq/DUFJRQlRIN+pMkiSKirKEK4NZv3UNP347OdvPLZN9bNRqDV/0m8aG9UfwLmZMpfKGPHj0mD69zlDRpygbNk/N1UKJKSlp/XHMTDNvQTc3S/tMTsnmfjtyB+UPnEajITgkiJCwYLRaeZjhf/m0w2c0b9yaW1zgnPIAt8QFLnOcMxzA0cWRKT/OzPcj2W7cuoqBwhBbnDJd74gbScmJPHx0P0fOf+nqRey0TiikjH1yJEnCXuPClasXcuTcsvzj1sNQAhUJBKjDSMRf3+HkWdN/XsXmTUdZOd+Za0fcWTrbmePb3Di1swAB/v4MHDAtV+OpUDHtEfX2fXGZrt++Lx6lUkHZctk7g73csvOBUmvUrN34N/9sWs2z52EAuDm707VDT9q16pzvv7DflUKh4PsRE2nWsBVbd23kSVAAlhYufFFvMA3rNsVYZazvEHOcQqlACIFAIJHxffKiT1NOdRCWJAlB1sNLBQIyef9GPA9n2+5NXLp6HiEEFcpVok2z9umqOss+Djuu3CdQkYBtOVNKu57Dycycmg7ZM6ggP0lKSmHJoi0M6WNF17bpq65XrWjMzPG29Bp6nnt3AyhW3CNXYipdpjC+1b0ZPfkhvpVMcHV+mYbc90vhp1lRtGjpi6trxglM34ec7HyAtFot4yZ/y9GTh3ARHpSnBgJBaOgTfpk7hYf+D/hm6PdywpMFSZLwKV8Fn/JV9B2KXlQqXxWNUBNGEM5k7OwcQgCW5lYULVw8k73fX+WKVdngvxaNVo1SSv8RpBVawpXBNPJpkm756XPHGT1xOOpUDbYirb/V1euXWLH2TyaPm0mNqrVzJFZZ3nLrYSh+sTEEFIjH3jWK0vY3qOzoiYdp9rYC5BdXr9zn+fM4urVP+zt/8CiF67dTMDGWqF3NhI6tzOk3PIwjhy/nWrIDsOCPUbRo8jWlaj+hewczShQx4srNZNZsjsfd3YlfZn2Z7eeUk50P0KHj+zly4gBl8cVRetn/wwFXrHFg845/aFS3abZ0ZpXlP16FilK5QjWuX72KqdYcSymto7QQglACCZQe0ueTz3Ns+Hn7Vp1Zv2U1t8QFvEUlXcKjFRrucJlkbSId27ysEP00OJDvJnyNldoeb1FJN19YqjaF26kXGD1hOKuXbM6WUWqyvOvWw1COxYegLSCwd42igWc0HmYfT6IT+TyGtWsOcuvmI0xMVbRoWZ3adcq/9qb2RQXlZxFqmnQO4sCxBN06aysFX/azRqHI/UrLBQu5cPj4AhYt2MLa1XtZvPI5bu52jPi2Hf0GtMbaOvunOJJETpUr/IDExMRgZWXFgc2nPoh5pAaP7If/DX8qiox3s0IIzioP4FurOhPH5O6zWNmHIzLqOUO+6Y/f4/tYS/aYCDPildHEaKJoUKcp47+bgoEy5+6Fjp48xLjJ3yBpFdhpnZGQiFCGkqpNZuw3k2jWsJVu27mLf2X9xjXU0DbL0BKkEWpOKfbQrl0nvhww8t+nkeUjO67cx76yI5KNmiLWJz6qx1Yb/jnM0EG/oNFoKFfKmIjnGvweJ1O5SnFWr5uIg2PGkZ0A0dHxFC/cCSNDDQ52Sn4YYUvjuqZEPNeyZFU0sxdHIQQcODKbSpVL5vJVZY+YmHg8XNoSHR2NpWXWHa3lDsofoMcBflhpM5+wUpIkrDR2PHrsl8tRyT4UGo2GvYd2kpCQ1kEwSoTz3DAUdy93fpu6iEljpuVoogNQp0Z91v65lY7tu2Je2ATTQiratGrL6iWb0yU6AKfPncBe65oh0QFQSgbYa104deZ4jsYrk+nLiePXGND3Z9o1N+bxRU/O7HLj3ukC7PvHjYBHfnTtNC7LKRasrMwoWNAFpRKObXWnewdLHO0NKFnMiJkTHJg1Ma2/m4VFztXUyivkZOcDZGpqRjKJWa5PkZJyZMiw7MOn1WoZP200cxb+ghRuSFl8KUNVrNR23Lp3g3MXT+VaXy9XF3eG9B/O3BlLaN6oFfce3mXitLHMmPMTD/zu6bbTqDUoXvNRpUCJRp395eVlsrxg9q9rKVvKmKWznXC0T0v4JUmiQS1TVsxz5ML5exw7ciXTfTUaDYGBoQzsZYWzY8abhQE9LLGzNWDt6gM5eQl5gpzsfIAa1mvKM0UQKSI5w7oEEUe4CKZhvaZ6iEyW1x0+cYADR/ZQmqqUogqOkhtOUgHK4ktRyrJ6w3Ju3r6Wa/Hce3iHTp+1ZO7iXwm6HkzkvRh2795Bjy86sPKfvwAoU7ocz5Whmd69CiF4rgylTOkKuRazTJZbEhOTObD/Iv0+NUepzHgTUr+mCV4FVezYfjLT/WNjE4mLS6ZsKVWm61UqBSWKGPH0aUS2xp0XyR2UP0DtWnZi47Z1XI0/SXFtBSwlG4QQRBPBHeUlHG2cMjwKkMkANm37B1uFI04i42zIHhTlqfIRm3b8Q6mSZXM8lqTkJL4ePQjiFdQQzVD9v8ChVqPFj1vMW/IbhQsWpX2rLuzYu4UHXKeIKKNreRJC8JAbxGti6dCmS47HK5PltuSkFIQQ2NtlXgZCkiTs7ZQkJKTd+IYER7B82W6OHLqAVqvFp5I3JiaG3Lmfkun+qamCB49S8an+ss/PvbsB3L79GFMTFTVqlcXUNH+U45Bbdj5A9nYOzJ2+GBM7Fec4yGnFXk4r93KBI9i72jP3lz/lx1iyTD3yf4C1NvP6FS/6ez30y5ligv924MgenkdFUEpbRZfoACgkBV6UwkZhz6p/llGimDdffv4Nj7nHOeVB/MQt/MQtzisP4s9dhg4YIU8tIctXnoVF8tOEpdSo2g8DAzhwNCHz7cLVXL6eRImSnhw9fJlK5T9j9q+rcLMLwMs1iLWrtpGUlMrC5bE8j9Rk2H/5PzGEPkulc9eG3L/3hBZNhlOlYj96dZtEx3Zj8S7ShRnTVuWLgrV6bdlZsGABCxYswN/fH4BSpUrxww8/0KxZWpn8unXrcvTo0XT7fP755yxcuFD3c0BAAAMHDuTw4cOYm5vTq1cvpk6dioFB/m60KupVnPV/7+TU2eNcvXEJhUJBpfJVqVyxmm7Cy/clhODilXMcP32Y5ORkvAoXo1nDlpibWfz3zrI8ydjYhJSYjI8/X0iRkjE1zd5iXlk5f+kM1go7TEXGEZCSJOGodefy9QtoNBq6tu9B8aIlWbdpJZeunAegQrlKdGnXnYrlKudYjC/+Bq7fuopCoaByxWpyYiXLUY8fh9CyyXCiIiPp3sGcx09MWbE+lt5dLanm8/KmQKsVjPopAoVCScOGPjSq/yXVKxmwZqEb1lZpLUGJiVo++yqULbviqNv2KZO+s6FpPVPC/z8aa8rsSD7t3ghzCxMa1B6MvU0qaxY507CWKc8iNPyxIpopk5bzPCKGqdMH6uslyRZ6zQjc3d35+eefKVq0KEIIli9fTps2bbh8+TKlSpUCoH///kycOFG3j6npy17jGo2GFi1a4OzszKlTpwgODqZnz54YGhoyZcqUXL+e3GagNKB29XrUrl4v24/9PDKCb8YN5da9G5gpLTDEiO3azcxf8hvjvplE/dqNs/2cspzXoG5j/tmwmiLa0hhI6ScATBTxRBBCrzq9cyUWrVaLIpMKzi8o+H+lZ6EFlFQsW4mKuVg7yj/Aj+/Gf83jwEeolMYIIVi4dA5lSpZjyg+/ypWbZTliyBczMJBiuXG0AO6uhiQmamnaJYgG7YPo0dGCRnXSkpW/Vsdy8VoSC/74hm3bTqLVqtMlOgAmJgpWzXemYKXHhD03ol3v4FfWGfLFoHaMn9SPr7+cjZFBMkc3u+semdnaKJk5wQE3FwO+mbCZAV+0oVBh11x/PbKLXpOdVq3S9yuZPHkyCxYs4MyZM7pkx9TUFGdn50z337dvH7du3eLAgQM4OTlRvnx5Jk2axKhRoxg/fnyOFUXL77RaLSPGDsHf7xEVqIWtxhFJkkgWidxLucoPU0bhYO9EGe9y+g5V9pbat+7C5u3ruZp8khLaiphJaXUpYsRzbisvYm/lQLMGLYmLj2XLzvVs372FiOfPsLOxp2WztrRt2THbWvbKeJfj0LF9JIskVFLGfgHPpGCKe3ljYJC7szJDWrI/eERfUuM0+FAHa01aa1c4wdy7d5Wh3/Rj2cJ/UBll3vFTJnsXd24/5vix66xZ5Iy7a9r73sREwe41bsxcGMnsP6JYvDIGgPoNKrBlRxfq1K1As0bDaN7AJF2i84KBgUSPjuas3ARHT85PK0pooqJuvQpY21iQkpLKhn8O8t0Qi0z7Bg3sZcXk36JYs/rAf86unpflmT47Go2GtWvXEh8fj6+vr275qlWrsLe3p3Tp0owePZqEhJfPLk+fPk2ZMmVwcno5oWGTJk2IiYnh5s2bWZ4rOTmZmJiYdP9kL527dJo792/iramEneSk6xCqkkwoJapgJlnw99o/9Ryl7F04O7ow++eFSBaC0+zjnPIAZxT7OMchrBwtmfvLEpJTkukz+FMW/vk7qU+1uCQWJjUYFv31O70HdyXieXi2xNKsUSuMVcbcli6iEen7EwSJR4SLYDq365Yt53pbG7evJSY2hvKamthIDkiShCRJOEiulNNUxz/wEQeO7NFLbLL869LFuwC0apS+z6WpqYJxw+24diRtSoc/l49h07Zp1KmbNgpRq9ViZJh1K6mRoYRGo6Vc+SJ07daIT9rVxtom7aYlOiqOxMRUynhnnribmCgoWtiI4KfZ83evL3rv2HL9+nV8fX1JSkrC3NyczZs34+3tDcCnn36Kp6cnrq6uXLt2jVGjRnH37l02bdoEQEhISLpEB9D9HBISkuU5p06dyoQJE3Loij58R08ewlxphY3GgVSRQgpJGKLCSFKhkBQ4azw5efYYqampGBrm/l237P2UKlmWzav2cuTkgbS+KJJEpQpVqV6lNkqlkm9++JLw0GdUEQ0xkyx48aSpkCjJ5dBjTPl1PDN/mvvecViYWzLlh1/59scvOa3dg4PGDUOMeK4II0qE80mLjjRt0PK9z/Mu9h3cjaPWLdMWJ3PJCjvJiX2HdtGicRs9RCfLbzQaDcv+2sXM6asAiE8QmJhk3C4hMa38guW/igBWrlKa1SsekJioxcQkfRuGEILNuxKoUtUn03ObmhljYKDg9yVR3LqbQvOGZpR7Zah6UpKWh/6p1GmUeZXmD4Xek53ixYtz5coVoqOj2bBhA7169eLo0aN4e3szYMAA3XZlypTBxcWFBg0a8PDhQ7y8vN75nKNHj2b48OG6n2NiYihQQJ5X54WkpESUWgU3OEsYQboZqu2EE4UphREqhNCSqpaTnQ+VkZERjes1p3G95umWB4c+5eSZo5SgYlqi8wpTyZxCGm9OnzvO0+BAXF0yDl9/W1UrVWfFog2s37qGYycOEZOSQvEiJWjfZhy1fOvqbTLb2LgY7HDLcr1Ka0JMrNwinFtuPQwlUJFAgjoMR/LX667RaOj32VS2bjlO0/omhIXC3+tjGP5FxuRixfpYzM1VVPUtlW553/4tWTh/E0PGPGPRDEcMDF6WZ5j063Nu3k3i598+yXC8M6dv0u+zn1Crtdy4m8Kl68mM/TmCpvVNWTnPGRtrJUtWxfA8Mm3E1odM78mOkZERRYqkTeTm4+PD+fPnmT17NosWLcqwbdWqaXOhPHjwAC8vL5ydnTl37ly6bUJDQwGy7OcDoFKpUKnkZ+1ZsbayIUZEkUwyRSmLBdYkEMcTHnCRI9jggIOdEybGmdx6yD5ot+7eQCBwIPOOiA64cosL3Lp7I1uSHQAP94KMGDyaEYNHZ8vxsoObawHC7mXebC+EIFYZSSl371yO6uPzYpbzQEUCtpUjKW1/Aycz83w1L9aaVQfYvOkY65e40K6FOQNGhPLDtAiKFDKkVWMzJElCqxX8sy2OaXMj+WJQeywt0z/mKlTYlXkLRzLo8184fCKZzp+YYmQosXlXAjfvJlG2XBG+GvwLkiRRq05FBnzRBgMDJR0++Y4KpZVsXepB+dIqUlMFm3fHMXhUGE27BtGgpgkz5kfTp28LihZ7fYPA4YMXWbRwMxfO3cbAQEG9BlX4YlBbypXPGxO16j3Z+TetVktycuZDY69cuQKAi4sLAL6+vkyePJmwsDAcHR0B2L9/P5aWlrpHYbK3d/vuDYwxowr1dTNM2+CAi/DgMid4ThgDWg3R2123LOco/1+2QEvmdTVeLFcqMy9yll980qIDU+6O5zlh2EqO6dYF85hYTTRtmrXTU3QfhxeJTkCBeOxdoyhtH0Rlx/w3y/lfS7bStL457VqklWCY/ZMDT0PVtP0sGO9iRpQoasSVmyn4+afwSdta/DChT6bH6dy1ISVKFmTh/M2s3JRWssHJyRXwIzriCW2bm6DRwMadB1ixfA/VfEthYyXYucoFM9O0v3tDQ4lOrS2ws1HSuFMQN+5o+XpEF8aMe33H5J8mLuOXaaspV9qEIb1NSEoSrN1yjH/WHmTh4m/p2Ll+tr5m70Kvyc7o0aNp1qwZHh4exMbGsnr1ao4cOcLevXt5+PAhq1evpnnz5tjZ2XHt2jW+/vprateuTdmyadVdGzdujLe3Nz169GD69OmEhIQwduxYBg8eLLfcvKOg4ECu3rxMKaroEp0XFJISL1GaCxymaJHieopQlpPKl/HBwMCQEPVjClIiw/oQHmOgNKB8mcyf/+cXzRq2ZO/BXVy5dgo3UQhH3BFoCSGAp/jTvFHrHK3v87G79TCUY/EhaAsIvEtqKGMdjYdZ/kt0AG5cf8SMH2x1P5uYKNi+wpVDJxJZsT6GvYcTMDCyZte+MfhWL/3am8xy5Yuw4I9vALh86R71aw9lSF8rfp3goJtuYsaPgv4jQlm18TrjhtvqEp1X1a9pQvEiKspVqsG48a8vRXFw/wV+mbaan8faMXKQjS6+Cd8K+o8IY9DnM6hSzRtPz6yftuQGvY7GCgsLo2fPnhQvXpwGDRpw/vx59u7dS6NGjTAyMuLAgQM0btyYEiVKMGLECNq3b8/27dt1+yuVSnbs2IFSqcTX15fu3bvTs2fPdHV5ZG8nINAfABsyLyxnhS0KSUFIyNNcjEqWW6ytbGjRuA3+iruEi2DdfFRCCCJECI8Ut2neuA021rb/caQPm4GBITMnz6Vrxx5EmAZzgcNc5CiJ1jEM6vcV34+YKLds5iC/2BjK+xTEp2QBylgHUtOhar5MdABMTIx4HpV+NOKLiT6XzXGmmJeKij4lqF6jzFu95xYt2IKnu1G6RAfSWm/mTnFAqwV318zbOyRJwtNdSWJi5tNMvOqPhZupUNYkXaIDaUPe5051wNREYtmfO9847pyi15adP//MevhygQIFMlRPzoynpye7du3KzrA+ai9qqCSRiDGmGdankIxWaOUqyvnYsIHfEhL6lLMXT2KltMVEY06iIo5o7XMql6vG1wO/1XeIuUJlpGJwv6/p22MgAYH+KBQKChYopJe6P7L8q0kzX/7+5yTfDbXFyCh9MnPnfgonziYwb6FvFntn7cypa7RrYZLpBKLm5kqsLBScPJdIn65WGdYnJmq5cDWFHp/9dxHB8+duMayfaaaJmJmpgsZ1jTl3NutSMLklz9TZkeUN3sVL42DnRCAPMl0fyAOMDI2oXrVWLkcmyy3GKmN+nTyfmT/Nw6dGJRxK2uBTw4dfJs1l1pQFGH9kHdONVcYU8ypBkULF5ERHlu0GD+1AUIiaTweGEPpMrVt+7VYy7fqE4lnQkXYd6rz1cSUJXjelVeGCBqzeFMeVGxn7yM5cEMnzSDU9P2v2n+dRKhUkp4gs1ycnCwwM9N/HL891UJbpl1KppF/PgUydNR4jYUxBSmAkqVCLVAJ5iD936dG+DxbmlvoOVZaDFAoF1avUonqVvJHUCiG4dPU8/gF+GBubUL1KrXz/KE32cShXvgjLVv5A/95T8PTxp2pFE2LjBVdvJFLYy5lNW6diYvL2fVBr1q7Ihh2HmDZO6Iaiv5CQoOVRgAZbWyvqtXvK4N4WNG9oRnSMlqVrY9i4I45RY7rjVSTr8gsv1KtfibVbTvHjSNsMrUjhERr2Hklk9Pe5N81LVuRkR5ZB62btiIuPZeFfcwjU+GGqNCNJm4hWaOjUthsDeg15q+MJIXgWHkqqWo2Tg5N8dyx7KzduX2XCz98TGByAAgVatCgUCqpU9GXi6GlYWMiJtyzvEEJw6MBFlizexvWr9zBSGdKkafXXzi3VvIUvN+6sYs3qA1y+eBcPI0O+HlWFFq2qY2j431/Tz8IiWbF8D8eOXkYIQbXqZWjbvg6rV+5j4Kgw5k111D0iS0zU0ntYGAmJsGPvz6xYvod5y/YwdU4kAEWLujJ3wed06/Fm8x9+MbgdDdcfYeC3Ycz+yUFX1DDiuYbOn4dibKyiR6+mb3SsnCSJFz0QP2IxMTFYWVlxYPMpzMwyzsD8sYqOiWLf4d2EhgVjbWVD43rNcHR48x71Qgh2H9jOirV/4f/EDwArC2vate5Mr6795HmFZP/pwaN79BvaHVO1OYW1pbDGnlRSCMKPh9xCqVAwZMBwOrftLncYzkd2XLmPfWVHJBs1RaxPfDB1dYQQfP/dIubP3US50iY0r29MdKyWdVsTSEySWL1uInXrV8zWcx49fJluXX5ArU6lcR0TlErYdyQJjVZBrz4tWLJoG3Y2Slo3MUGjhS27E4hPEPy5/Htata4JQHx8Iv6PQjA2NqKwl+tb/y2tXrmPoYN+xdJCQdN6JiQmCfYcTkClUrFm/U9Ur1EmW6/5VTEx8Xi4tCU6OhpLy6xvfORkBznZySl/LJ/H0lWLcJRccRaeKFHyjGCCpceUL1uRWVMWyBWYZa81euJwLpw+R2VNfZRS+jvcQPGQO1wG0jpVd27bXR8hvhEhBDduX+OB3z1UKhXVKtXA1sZO32HlWR9qsrN541F695zMnMkODOptpUsaEhK0dOgXwumLWq7dXoW1dfZ8zwQFPaNqxT74+hiwar4TdrZpfWNiYjX0Gx7G9n2JrFwznv37L3Dm1NW0ooK1K9JvQKtsn8H8kd9Tlv65k/PnbmJgYED9BpXo3rMJDo7ZO82EEILdu86w7M/t3L3jj0plxL17T/8z2ZEfY8lyhJ//A5auWoQXpShESd38SnY44yTcuXTtONt2b6R96y76DVQGpBXzvHDlHEdPHiQ5OQmvgkVp3rg1VpbWeospMTGBY6cOUURbJkOiA+BCQR5yE2NMWbxsPm2atc8znacfPLpHSGgw1lbWGBoaMWn6WB7639etN1Aa0Lp5e4Z98a2c8OcjixZsol5NMwb3sU633NRUwV+/OeLp48+aVfsZOLhttpxv6Z87QahZ94cbVpYvOwFbWihZMdeJgpUC2L//AjNmDs6W871OocKuTJzcP0fPodVqGfzFL6xZdYDKFUzp0krFk+BY7t37733lZEeWI7bu2oCx0hRPTcbigzaSA464smnbP3Kykwc8j4xg5Ngh3L5/E3OlJYYYsVu7gwV/zWHM8PE0baifyThj42PRarWYkvldsFJSohKmmGJBaOITTp07Tv3ab9bPIKdcu3mFX+dO5e7D27plCkmBGZZUoCa2OJFKCk81j9iyYwOxsTFMHDNNjxHLsotWq+XsmTv8PjXzGmXOjgbUrGrCmdM3si3ZOXzwPG2amqZLdF5QqRR0amPKrn1ngLRkJzY2gQvnbqNWayhbrghOzh9WJ/8lf2xn7eoDLP/die4d0lpxYmI1rN4Y+5/7ysmOLEf4P/HHQmODQsq8uoG1sMfvqf5rL3zshBCMHDuER36PqEhtbDQOSJJEikjmvuYaE2d8j4O9Iz7lq+R6bFaW1hgZGhGTGok9LhnWq0UqicTihBthSERFR+Z6jK+6fusqQ77ph5nWgnJUxxIbbnGRWBFFRWrrKpIboUob5SiM2X9kN906fUbxIiX1GrsseygUEhp11uvV6rSRjm/i7p0A7tx5jJmpMTVqlc10RJZarcbEOOv+NSbGCjQaDSkpqUwav5Slf24nLi5tqLmBgYJP2tZm+swh2Nplbyf/pKQU/ll7kNUr9xASHI6jky1duzWhc9eGmJoav9MxhRAsmr+RTm0sdInO25Dr7MhyhJmpGamKpCzXJ5OIiXHGooWy3HXhyllu37+Jt6YStpKjro+BkaTCW1TCUrJhxdq/9BKbykhFkwYteKp4RLLI+F56zD20aLHEBoHA2Sl7+yC8rdkLZ2CqNaeCtjYOkiuGqIjkGe4UzjD1CoAzHpgoTdl7UP/VZWXvT6FQULNWGdZsiSezrrCPn6Ry6nwideqWf+1x7t4JoFmjYVT16UevbpPo0PZ7ShbpzK8z1mQ4rk+lUuw8kERqasbzCSHYuieRij7e9O89lYXzNzK0jyk3j3nid64gv/xox5FDJ2nVbDixsQnvde2vioqKo3njr/lqyCxsTAPo3FKNo1UQI4b9TpMGX/E84t1mrX8WFsXDhyF0aPlu/Z3kZEeWI+rXakSUNoIYkfFuWy3UhCqf0LBuEz1EJnvVsVOHMVdaYoNDhnWSJOGi9eTspVMkJSXqITro230gphamnOcQQeIRiSKeaBHBTXGeR9ymICUIlPyws7Gnis/bV5nNLgGB/ty8cw0PbTGUUtojBS0atGgwJfNq4wpJgYkwIzLqeW6GKstBg4Z24MyFBCb88hy1+mUCEh6h4dNBYdjamtOhU9aTYvo/CqZ542FEPfNj7R/OPLtVmBtHPenR3oiJ45fy49gl6bbv278VIWGpjJoUni4REkLw06zn3HuYRJVqpdi65QQr5jnx02h7ShQ1wrOAIUP7WXNoowv37wdm63QO33w9h0cPH3F2dwF2rHRlyvf2bF3uwoV9BQgOCmTY0FnvdNwXA8Q02ncbUyUnO7IcUadGAwp5eHFdeYYIEaL7Q4wT0VxTnAIDQZf2PfQc5cdFrU7l4pVzHDlxgPsP7wKQlJSEIUZZDjU1JK3pPDnlv+fIyQlOjs78MWcFRUoW5TYXOcluznOYCEJxpzDRRBAughk5dAwGSv09lQ99FgKABda6ZUoMMMCQWKIy3UcjNMQTi6ODUy5EKMsNTZpW5ccJfZj063OKVAvg85GhdPk8GM9K/tx9KLFu42TMzbPuRD9t6kpMVCkc3eJKx1YW2NooKVnMiN9+cmDKGDt+n72Bx49DdNuXKl2I6TMHM3txFGXqBDLp1wim/Pacio2CGD/jOcO/6crpk9cpUUSVaYtIqeIq2rcwY+Xf2TPlUkhwBJs3HWP8SBt8yqV/XFWulIqJ39qwY/spAgJC3/rY9g7WlCjhzrotce8Um5zsyHKEoaEhc6b9QcHCBbnMCU4pd3NGuY8z7AcLDbN+XkgBN099h/nR2LJzA627NmbIt/0YPXE4PQd25LOBnTEzMyNaG0mKyFgyHuA5odjZ2GNhrr+50Nxc3Fk8ewVTf5yFp3tBAFJIIhA/rDwsmDHpd+rWbKi3+ABsrdOGkSfwsqOkJEm44MlTHpEkMj4mCOQBydokWjRuk+kxY2JjOHBkDzv2buHmneuZPhqR5T1fj+zCkRPzqNeoPhdu2RMQ5s633/Xi/OWl+FQqkeV+iYnJbNpwmIG9LHRDyF81pK81FuZK1q05AIBareH4sas4OtkwZ97XFPX2YfaSZGYuTECjcMbDw4FfZ6xh29YThDxLZeHyaLSZtIpULKvi6dOIbLn28+dvo1ZraZ/Fo6ZOrc3RagXnztx662NLksSgoR3ZvCuOBcui3vrvQe6gLMsx9nYO/Dl3NVdvXOL0+ROkqlPxLlaaOjUayMNtc9GajSuYs2gGznhQhfIYY0o0Efg/usPmgPUolBL3NdfwFpXStfBEiwhCpCf0afX5G3eqzEl1azSgbo0G+Ac8IuxZCDbWthQpXCxPFBMsXLAIXgWLEvD4PnbCWRdTQYoTRhDnOUxhURI7nEkhmSD8COIRXdr1wOP/CdwLao2ahX/NYf2W1aSkvmxRK1qoOOO+/YmiXhlHOMrylvIVijJn3vC32icqKo7kZDVlvDMvtmpmqqBwQSOCn0awasU+Jo1fQkhIlG59mbKFWLVuIps3HmXxom20bW7O9LHOKCRYvz2OoWOeceFqMkt+dUz3N3Pnfgr2DhknA30XL46bVR7yYq6ud/2T7dGrKTeu+zFk9Fbm/hVLvRoqAp++pkf4q7HJRQVfFhX87usfCQwKQGWkoma1upQo5q3v0GSy9xIXH0vLTvVxTC1Acal8unUaoeaC4giOBRzwC3iApWSDi9YTQ1Q8J5QQxRO8i5dmzvQ/MFa92wiKj8mZCycZ/v0g7HGmkCiJBTYkEs9DbhFKQIbtJSTKeJena4ce1KnRQPdFMXXWBLbv2URBUSKtc/P/fx9+iltoVKn8NW91hgQpv7j1MBS/2BgCFQnYVo6ktH0QTmbmH0xRwfeRkJBEQbe2TBplw8hBGQvxJSZqca/wGJ/K5Th08GKGiT6tLBXEJ4BarWXezw580cs63f4r1sfw2ZehbP3bhZaN0lpeAgJTKVXnCV8N78ao0e9flDMsNJJSxT9l6hgbvv4i4zXMXxrFsHERXLu9Aje3jP0EX6XRaIgIj8HYxAhLSzPdciEEJ09cZ+mS7dy98wiVsYqLF+7LFZTfxItkB8DMwAK1SCVZk0Sl8lWZPG4mlvLcO7IP1LbdG/l51kRq0hyVlLGvwFPhzy0uMHncTLbt2sS5i6cQCOxtHGjXujNdO/SUE523cPz0YWbMmcKziJd9EsxMzRnQazChz0JYvWE51go7HLXuSEg8UzzluTaMHp37MKjvMPwD/Oja7xOKU4ECkle6Y6tFKqfZh1qRirFKRcXyVejSrjsVy1XO7cvMES8SnYAC8di7RtHAMxoPMzs8TIvoO7RcM6DPVM6ePMnlg+4Zauf8tiiSEePDMTRUYGggmPq9PT06WmBqomDngXi++ymcR49TKVzQiFvHPTJt8azcJAB7WyVbl7uydW8co3+KRCNZcvjYfOzss6d1Z+CA6ezcdoQdK52pUeXlZ87ZS0k0/zSYho1rsmTZmCz3j4tL5LeZa1m+dCfPnqWN3KpTtxzDR35KnXoVMmz/ptNFyI+xXlGZ+lhpbNEKLc94yrVrV/hm3FAWzlqWJ5rKZbK39Sw8DGOlKSpt5p0izUn7gHNxcuW3qQtISk4iNTUFM1PzPPHo6kNTy7ce1avU5vzlM4SGBWNlaU21yjXx83/ArKHTKIw3hbQldZ8nBUQRHnOPFev+oqpPdc5fPoNKaYybpmCGYxtIhrgLL/y0N3FK9ODqucscP32Yr774hi7tPuzO/juu3CdQkYC2gKBu2Zs4mZl/dIlOTEw8ffq3Zu+eM9Rt95RJo2xoUNOU0HANi/6O5pf5UZQt58W1qw/ZvNSVZg1etnZ80sycKhWMKVL1EY3qmGT5fdWwtimzFkVi4vkAgBo1S7Ng8ahME52EhCT8Hj7FyMiAIkXd3/jzYPrMIfj7PaV2m1vUqW5K2ZJG3LibyuET8VSqXIyZs7/Kct+4uETatBjJ7Vt+9O5iToNaLjyL0LB45T0+afUdCxd/Q+eu79Y/T052XmH2/yGiCkmBE+4YaA24fOsEF6+co1KF/N+MKst/bG3sSdYmkiKSMJIyttDEk3bn9KKDrbHKOM+35Gg0GuIT4jE1McHAIO/1/VIqlVSrVCPdso3b1mKqNKeQpmSGLyIPihKiDGDDtrVYmFtggjkKKWMHVQAzLBEI3PGikMabB1xn9sIZVCjjQ/GiH+Zj9x1X7pPkYoitsymlXc9R2dHzo0pyThy/xq8zVnHoYNo8b9ZWJoQ8M6ZNz2DdNubmKkZ8+yl7dp2hZFEjmtbPWKPM1dkAWxsloc80WZ4r9JkaSZKwsTGhTr1KjBnbEw+P9KMB4+MT+WnCMlav3EN0dFrJCc+Cjgz9qhN9+7f6zxt/CwtTtu6awdbNx1m9ci8HTj3DydmehYsb07Z9bVSqjDWnXvjt13XcvuXHkU2u6UZz9elqSd+vwxg2dBaNm1TBxlYuKpitbHHCXGnFwWP79B2KTPZO6tduhFJpwGPuZ1inFRoCFQ+pWLYyTo5vPpu9vjyPjGDWgmk0bleTJu1rUr91NSZMG4N/wCN9h/af7ty9ha3GMdMvCkmSsNU4cvvOTRzsHUkQsWhE5p0u44hCgRKD/5cL8KI0pkozNm5fl9OXkKPc3W3wdLBNa9H5iBKdLZuO0abFt0Q/u8OC6Y5sWe7CZ51VJCbEUaSoC7Nmf8Xfq3/g9oN1fD+uF2q1mpLFsi4VUbm8MVv3xPE0JOP7JzxCwz9b46hZxZi+XVWcPXmGOjUGcnD/Bd02iYnJtGs9ihXLtvFFD2NObHdnz1pXalRMZOTXcxk3ZvEbXZeRkSEdO9dn8/ZpnL7wF1t2TKfLpw1fm+hoNBr+XrqD3l3MMwxbVygkpo2zQ61Ws3bNwTeK4d/kZOc1JElCJYyJT3i3cf0ymb5ZWVrTp/sAHnOXO+IyCSIWrdDyXIRxWTpBgiKWgX2/1HeY/yksPJQ+g7uydetGHBLdKEM1PNXFOXbkCH2GdOXmnev6DvG1DA2NUJP1qBE1aowMDWnWsDWp2hSe8DDDNikibbi9Cx66aVgUkgJbjTPXb17NsdhlOSMmJp6hg36hQyszTu9yY0APK1o1NmfmBAdObHclLOQZDx8G0bpNTSws0lpyypQtwqVrSZkOIQcwNZEQQqJ5t2Cu3HhZTuLGnWSafRqEmamCFfOcmTbOngdnClCvhorePScRHR0PpE0seuniPfavTysG6FvJhEZ1zFgxz5mZ4+2ZO2cD169lfG9mh8jnsYSFxVC/ZuaV9R3tDSjrbcLtW/7vdHw52XkNtVATQyQecj0Y2QesV9f+DB0wgkjTUE6xl0Ns4hLHMHcx5befF1G6ZDl9h/ifZs2fRkxkLJW19SkqlcVJcqegVIIqmgaoUkyY8POYPF2HplaNuoQrgkkVGYszqoWaZ4ogatesj7trAbp26MkDrnNHXCZORJMskggWjznPEUBQiPTzaGlQ67WgouzdbFx/mISEZKaPs0OpTN9SU7qEiv7dzVn59y6Sk1++Z3r3bYH/EzWrN2Wc+PLugxQ27YyjeYsaxCZa4tMoAO9aTyhe3Z9y9QJ4Fq5h9xpXnB3T3ivGxgoWzXAgISFJV7vn76U7aNvcjCoVMj7KHtLXGjcXI5YvzZ4ChP9m/P+5v8LCM38MJ4Qg/LnmnefWkpOdLAgheMQt1CKVlk2zZ4ZamUwfJEni0w692LHuENPGz2bsyEks/HUZ65Zuo2LZSvoO7z+FRzzj2MlDeGiKYSylv+szkAzx0pbmydPHXLp6Xk8R/rdPmndApVJxXXE6XYHBZJHEDekMkoFEu5adABjSfzgD+3xFtNkzzrCf4+zgJucxxoRK1Ev3GqhFKuGKYKpXq5Xr1yR7Pxcv3KWYlwp318z7nTWoZUpUVAKhoWlT7qSkpHLjuh+2tmb0/ioUS68HdB4QzOETCcz9M4parQNxdrHn9wUjuHBlOX+v/oEa9Rry4FEqn/e04t7pglQsmz5RcHU2oGpFE86fTSvy5+cXTM0qmScTBgYSVSoY8sjvaTa+Ci+Zm5tQv0EF/lwVi0aT8cZlz6EEHj9JpvUnNd/p+PLtwCsecgMH4YaaVJ5K/oSLYIb0G46zY8YZl2WyD42xypja1evpO4y39vjJI7RCix2ZT6tgjT1KyYCHj+7rZXb2N2Fna8+vU+YzcuwQTsbv1s1FFiWFY6wyZsaEObi6uANpyWnPLn3p3K47V29cJujpE36d9zOGWkMMxcs+D6kihZvSeRQGEm3/nyjJ8r6oyFhGDJvDpo1HsbVWoNGIDC07gK6jsZmpMcnJKXTpMI6jR67QuokZ9Wo4EByq5q81MWzaGQdItPmkFjN+HYKVVdoordZtatKseTX+WryDst5GGBll3s8nKRmUBmkd4q2szHgcmJpl7E+CtBQo8m4Tcb6Jr0d+SpsW39L7q1Cm/2CPs6MBWq1gz+EEen/1jOo1SuFbvfQ7HVtOdl4RrHjME23a80gvj6J81W06Des21XNUMtnH7cXosFSSgYwftBrUaIUGlSrzyrN5RdlS5dm8cg97Du7g4tXzIATlylSkeaPWWJhnHF2iMlJRpWI1qFgNRwcnvp80gpPq3dhoHQDBc+kZhkaGTB8/R74h+0AkJibzSatvCfB/zMiB1syYH8XWPfG0a5H+fa3VChavjKV6jVLY2VsxbepKTp28yr5/XKlX42XL3phhtrTuEcyNe0oWLvk2QwdgQ0MDatUuw6qND/m8p1WGjs137qdw8WoCn3/pA0DbDvVYsX4X3w+zzVDn59T5RC5cTeSr7+pk50uSTq3a5Vi0ZBRfDfmVdVv9KeNtQniEhidByVSvUYqVaya8cxkYOdl5hQnmxBGDUqmkwydd5ETnNTQaDZIkybVYZDmueDFvbK3tCIp6hBV2GdYH8QiFQkH1qrX1EN3bMTMzp33rLrRv3eWt9qtRtTYb/97Ntt2buHztAkgS7ct1pFXTttjaZHxNZHnTujUHuHbVj3N73KlQxpirt1LoPyIUhQJaNzFDoZAIC1czZkoEpy8ksGFzN9RqDUuXbOOzzhbpEh1Im0Ji/jQHvGs9Zuvm43Tq0iDDOQd/2ZEuHX5g7NQIfhxpp2vhCQhMpcsXoRQoYE+btmmPQQcNacc/a/bTpEswcybbU6WCMWq1YOueOAZ/F0FFn6I0a+6bo69Rx871adS4MmvXHODunQBMTFS0alOTar6l3qvenVxBmZcVlO1xxQk3InnGU/yZPmEOtXzr6ju8PEMIwZ6DO1i3aRV3H9xCkhRUrlCVTzv0omql6voOT5aPrd+yml/n/4wXpfCgKErJAK3QEsoT7kiXaNGkDaOHj9d3mLJ3sOPKfewrOyLZqClifSJfTw3RpMGX2FsEsu3vtJa46BgNnfqHcOBYAm4uBthaK7h9PwVDQ0N+mfUV3Xo05smTMMqU6M6OlekLCb7Ku9YT6jVuxs8zBma6/vff1jPu+8U4ORjSoJYxz6O07D+agKOjNZu2TaOkd0Hdtlcu36NX94k89g/DycGIpGQt0TFq6tQtx1/Lx2ZbpeXsIldQfgdJxHOT81hjj41kz9KVi+Rk5/+EELo5e+wVLpSgIlqh4d6Vewy79AXDBn5L57bvP7eKTJaZDm26EhEZzt9r/uSJ4gFmWJKkSCBRE0/9mo0ZMSTr8vMyWV4REhxOvcovOyRbWSrZs9aVs5eS2Lgjjr1HErCzs+bMhSW6wnlGhmlf03EJ2kyPKYQgPkGLkVHWX+dDh3WkYePKLP1rJzeuPcDYWMXPM6rTuWuDdPNOAZSvUIxL15ZzYP8FLl28i5GRIQ0bVaZc+Q+7/pGc7LyiEnWJ4TlXOY25sOL2/ZuEhYfiaJ95x8j8IjU1ldi4GMzNLDAyyrzo05ETB9i+ZxPeVMJVFIT/tyYW0BbhPteYvWAGVX1qUNCjUO4FLsu3ngQFcP7yGTQaDaVKlKFksVJ80ftLWjdtx459W3VTMTSp3/yDrRws+/g4Odtx425QumWSJFHNx4RqPiZcvvEUR9dC6SoEOzrZUKZMQVasD6djK4sMxzx8MpHApyk0bPz6OdJKehdk+i+D3yhOpVJJk6ZVadI0/7SyycnOv9hKThQVZbhDWunuxMSE/9gjvaTkJPz80+YdKVywSJ4uvR8SFsyyVX+w5+AOklOSMTQwpEGdJvTuNiDDrMobtq7FVuGQlui8QpIkiojShCoC2bJzPcMGfpt7FyDLd2LjYpg0YxzHTx9GQkKSFGiFhhJFSjHx+2kUcPNgQK83+8CWyfKart2aMGLY71y9mUy5Uuk71J+5mMjhE/H88WfjdMslSeLLr7vQv8/PTPo1glFDbHX9bi5fT6LPsGdUqOhFrdp5v16WPsnJTiac8eQOlzEwMMTJ4c3K6KekpLBkxQI2bV+nq7hsbmpBu9ad6NdjEIaGeWsOnydBAQz4qgdJ8cm4abwwx5oEdQzHjhzh+KkjzP/1L4p5ldBtf/fBbZy1BXUtOq9SSEqstfbcuXcr9y5Alu+oNWq+HjOI+/fu4k0lnCiAQiiIIIQHj64zaHhvli/8R+6Qm0+8mOU8ycWQAMVlShsG4WGWvwu4du7akKV/bqdRp0AmfmtNx1YWaLWCdVvj+GF6JFWqFueTdhk72nfsXB8/v6eM/+lv5i+NpXplI4LDtJy9mEjJkgVYtW6SPFn1f5CH0mRC8f+XpYx3OYyNM58t+lUajYbvJgxj1T/LsE9wpTL1qUx9bBOcWbluGd+NH4ZGk/XkbPow7bdJpMarqaKpT2HJG0fJVVeRVplsxE/Tx+kq0j6PjECdqkZN1vUXNJI6y0dgsvxLCEFSchJabeb9Cd7GidNHuHnnGmW01XCVCqKUlEiShL3kQgVNLaKjo9i4fW02RC3Tt1sPQzkWH0JAgXi0Hv408Iz+KCYANTU1ZuuOGdSqU42hY8JxLOWHc5lHjBgfQZNmtVi/+WeMjDK/MR41ujtnLy6hfeeWxKaWwKmAD38tH8PRUwtxdbXP5Sv58MgtO5kIJ2222X49Mu/Z/m9HTx7k9PkTlKcG9tLLehdW2GIrHDl1/jjHTh2iXq1GORLv23oSFMDFq2cpRZUMM2EbSIYU1pbkyqOT3L53E2dHF/oO7UZqairBPMZLeGeYkTlJJPBcCqVn9c9y8Spk+hSfEM/ajX+zecd6IiLDMTQwpH7txvTs0pfCBd/tC2vPwZ1YK+ywEQ4Z1qkkExy1Bdi1dzv9e8qPsT5kO67cJ1CRgG25tFnOnczM8/UIrH+zsbVk2cpxBAaGce7MrbQ+O9VL4+Ly3y2WxUt4MHX6m30vydKTk51/SRKJ3JeuUbJIKSqWe32Hrxe27tyIjcIBe5GxsJe95IKNZM/WnRvzTLLz6HFa4URbHDNdb/v/SrV+/g/YsnM9URGRlMOXq5ziOmcpKXwwktKeNyeIOG4ozmJlYU2zhi1z5wJkehUbF8PA4X14HPAIJ20BSlGIJHUCx48e5cjxA8yauoAK7zANRVTUc4y1Zpk+KgUwxYzA2JD3jF6mTzuu3CfJxRBb57RE52NozcmKu7sj7h0y/wyWZT852XnFXa4QrniKtY0tP42d8cb7BT0NxEJrneWHtIXWhsCnT7InyGzw4tFcKsmoyNiBOq1SbVrHuL0Hd1JAUxQ7yZkyoho3OMtxdmIt7NCiIZrnmBtbMPfnvzA3yzhS4GMghCA6JgohBNZWNvn+2fmiZXN5EuBPJW1dzKWXNTc8NEW5Kk4xbvK3bFm1FwODt+un5uLsxsM7fgiNyPQ1jJWicHaQKwV/6NzdbZBs1DiZmX+0iY4s98l9dl6htkuix6d9WL5gnW6emjdhaWVFkpT1qK0kKQErK+tsiDB7lCtdAQszSwLxy3R9IH4YGRrhWaAgKakpunl8HCRXatKCIpTGECOMMcNIYUzr5u0o6lU8Ny8hTxBCsG33Jj7t15ZmHevQvFNdOn3Wio3b1mZLH5a8KDExgZ17t+KmLZwu0QFQSgYU1ZYlIjKcE2eOvvWxWzVtS5wmmhAy3hjEiijCCKJNy/bvHLtMJvt4ycnOK9Ys2Uz/noOxsbZ9q/2aNmhBOMEkiLgM6xJEHOEE0zQPPeJRGano3rk3gTzEX9xFI9QAaIWGJ+Ih/tIdOrTpioNd2uOsZJJ0+xpKRnhKxSgr+eJNJQRaLC3yVkXN3CCEYNaCaUydNZ6EwGTKUJUyVCM1RMsvc6cyZeaP5Mfi5E9DgkhKTsSOzEcpWkjWmBqYce/h3bc+doWylWhUtxm3pPPcE1eJEZHEixj8xR0uK45TtHBx2jTLvWTneWQEfv4PiI6JzrVzymSynCE/xsoGLRq3Yd2mVVwJP0FRTVnsSWtqDyeY+8prONu70rxRaz1HmV6Pzn2IjolizYa/CVDcw1SyIJE4kjVJtGrSjoF9v8JAaUDxIt4EPfTDUbhleLQQQgCp2hTq184bfZFy0+VrF1i/ZTUlqIA7XrpHmE64Y89jdu7fSt1aDalZLecmzdMHI6O0vlpZjczTCi2p2tR3GpknSRI/jJpMAXcP/tm0moCE+wAYGhjRtGELvvx85BuNjnxfN29fY+HS37lw5SwACklB7er1+aLPUDwLyEUzZblPCMGVy/e5fu0hRkaG1G/gg6OTjb7D+qDIyU42MDMzZ/7Mv/h+0kiu3j2FoSKtr0KqNpVSRcoyedwvmJlmPqeJvkiSxNABI2jXqjO7928jLDwUWxs7mjZoSUGPwrrt+vUcyDc/DOU2F/ESpVBJJmiFlhACuK+4SsNaTSnglr9rY2Rm0471mCutcNMUzrDORfIkUPJj0/Z1+S7ZcXctQAFXT54G++uS+leFEUiqNuWdr9tAaUD/noPp0bkvd+/fQqPR4FWoGFaWudN6ePHKOb4eMxATrTneVMIUc2JFFOdPn+XC5TMs+u3vdx5tJpO9izu3HzPo82lcuvhAt8zQUEmPnk2ZOmNghpnOZZmTk51s4uTozJLfV3Lr7g2uXL8IpDXLlyxWSs+RvZ6bizv9eg7Kcn3NanX4fsREfvl9MiGpAZgrLUkWSSRrkqhfszHfj5yYi9HmHX5+97HW2GfZGdlGa89DvweZrvuQSZJEr0/78dMv43jITQpSHKVkgBCCCEK5p7iKb8WaFClU7L3OY6wyplzpitkU9ZvRarVM/uVHLLQ2lNfW0JVYsMYeZ60HF5OOMnPuVOb98meuxiX7eAUEhNKy6XCc7FLZtsKVJnVNiY7RsnRtDD9M3014eBTLV/2Q7wdFZAc52clm3sVL4128tL7DyFYtm3xCnRr12X94N0+CAjAzNaNBnSYU8vTSd2h6Y2JqSjyRWa5PJhkTk5x/5KIPLRq3IexZKIuXzyNI4YcF1iQrEonTxFDe24cJY37Wd4jv5OLVcwSHBVGZeulqSalFKiEEoNAquHTtPHMX/0r3Tr2xtpIfI8hy1u+/rUdBEoc2FsDeLu09aWerZOQgG9xcDOg+6CQXL9yhUuWSeo4075OTHdkbsTC3pF2rzvoOI8+oX7sR8+/NJlkkopLSJzUpIplwRRA96vbRU3Q5r3e3ATSu35wdezYT+PQJZmbmNKzTBJ/yVT7Yu8wngY+RkLDk5QCFaBHBFU6iJhVr7LHFkTUbVrBh61qm/DCT6lVq6TFiWX4mhGDdmn0M6mWuS3Re1am1Od9PVbF29QE52XkDcrIjk72Dlk3asvqf5VyNPUVJrQ8WkjUAcSKGO4qLGJuY0LZFJ/0GmcPcXNz5vPdQfYeRbczMzBEIUkhChQkpIpnLnMAMS8pQFWPJFEhLZm+nXuS78V+zYtF6udOyLEekpKQSE5NEsSKZ91dTKiWKFDLg2bOo3A3sAyUPPZfJ3oGVpRW/z1iMqZ0xZznAWcV+zikPcIZ9GFgpmDPtD+ztMk57IMu7qlephcpQxRPSKowH4YcWDeWorkt0AIwkFaVFVZRCyYZt8lxdspxhZGSInZ05V28kZ7o+NVVw806qPC/WG5JbdmQflaDgQMKfP8PB1uGtCkdmpnDBIqz/eycnTh/hwpVzCCGoUMaHOjUa5LlZ7mX/zcLckq4de7Fs9WKUQskzgrHHVTc1yquUkhIHjRvHTx5hxODReohWlt9JkkS3Hs1Y9tdmhg2wxsM9/WfKklXRhISl0K1HEz1F+GGRkx3ZR+HqzcvM+2MW129f0S0r612BIQOGU8a73Dsf10BpQN2aDalbs2E2RCnTt/49B5GSkszajSsQAsyxzHJbAwyIV2deb0gmyw5Dv+rA1i1HqdXmKWO/tqZ5AzMiozX8tTqGOUui6N2nOaXLZCx/IctIr4+xFixYQNmyZbG0tMTS0hJfX192796tW5+UlMTgwYOxs7PD3Nyc9u3bExoamu4YAQEBtGjRAlNTUxwdHfnmm29Qq9W5fSmyPOzStQsMGdmXgLtPKENVqtGY0lTl8Z3HDB7Zh8vXLug7xA9SdEw0azb8zXcTvmb0xK9Zv3UN8fEZq4h/SBQKBUMHjGDzqr2ULlmGCCkUrcg49YcQgghFKN7F83ZpCdmHzcHRht37f6NsxYoMGvUMj4qPKFcvgL83pDJ6bE9mzv5S3yF+MCShx5r227dvR6lUUrRoUYQQLF++nBkzZnD58mVKlSrFwIED2blzJ8uWLcPKyoohQ4agUCg4efIkABqNhvLly+Ps7MyMGTMIDg6mZ8+e9O/fnylTprxxHDExMVhZWXFg8ynMzMxz6nJleiCEoGufNsQ8jaeCqIVCepnfa4WGy9IJrAtYsmrxpg92FJE+nLt4mu8mDCM5ORkbHBAIIsUzzMzMmfnTPMqWKq/vEN/bA7979PiiA54Uowhl0r0/AsR97nGVWVMWUK1SDT1G+WHZceU+9pUdkWzUFLE+QU2HqvoOKUdEPo/h+nU/lEoFFSoWw9Q044TLbyswMIxbN/xRGRtSpao3JiYZH69+jGJi4vFwaUt0dDSWllm3xOo12cmMra0tM2bMoEOHDjg4OLB69Wo6dOgAwJ07dyhZsiSnT5+mWrVq7N69m5YtW/L06VOcnNLmcVq4cCGjRo3i2bNnb1yyXk528q/rt64yYFgPKlILW8kpw/oIEcpljrNk9kpKlSyrhwg/PEHBgXTr1xYLtQ0lRSVUUtoHeZJI5JbiHMmqRNYt3Yad7YffcXLNxhXMWTQDK4Utjlp3JCTCFU95rn1Gt46fMaT/cH2H+Nb8A/w4fvoIScmJeBUsSu3q9d56hvp3cethKH6xMSRUAEeHGMpYB+a7ZCcmJp7vv1vE+nUHSUpKe8RpbWVKn/6tGT22J4aGcs+R7PamyU6eeeU1Gg3r168nPj4eX19fLl68SGpqKg0bvuwLUaJECTw8PHTJzunTpylTpowu0QFo0qQJAwcO5ObNm1SoUCHTcyUnJ5Oc/LKHe0xMTM5dmEyvnoYEAmCFXabrrf5fU+VpSJCc7Lyh9VtWo1VrEQLOcRCFUOKAC+54UUbry8nkXWzdtZE+3T/Xd6jvrWv7HngVKsrq9cu5dPUcWiEoXbIs37QbTZ0aDfQd3ltJSExg4rQxHD11CEOFIQaSEYmaeGyt7Jgw5mcqVci5xOPWw1COxYegLSDwdtBQxjoQD7PM/yY/VImJybRt9S0P7j1i3NdWtG1uTnKKYNXGWH77bR0PHwSybOU4uQVZT/Se7Fy/fh1fX1+SkpIwNzdn8+bNeHt7c+XKFYyMjLC2tk63vZOTEyEhIQCEhISkS3RerH+xLitTp05lwoQJ2XshsjzpxYzsicRjTsZ6FYnEp9tO9npCCHbs2UKqSCWFJFzwRE0qwTwmCD/KUQM7rQsnTh/JU8mOEILQZyGkpqbi5OD8VhOVVqlYjSoVq+mO8yF+WQkhGDNxBJcun8ebyjhr3VFISuKI5n7sNYZ/P5glv6+kmFeJbD3vi9acQEUCtpUjKW0fhJOZeb5r0QFYsXwPVy4/4PROd3zKvXxsVdZbRaXyKroMOMHRw5epWz93p0GRpdF7nZ3ixYtz5coVzp49y8CBA+nVqxe3bt3K0XOOHj2a6Oho3b8nT57k6Plk+uNTrgpWFtY85n6m6wO4j42lLT7lK+dyZB+mfYd3EZ8YRwkqUIUGFJFKU0KqQE2aY4Ud1ziNAiUpKSn6DlVn78GddOvfjrbdm9Cpd0tadq7P/D9/Iykp8a2P9SEmOpD2OPfsxZOU1PrgKnnqpsMwl6woq62OShizfM2SbD3ni0QnoEC8LtGp7OiZLxMdgJV/76J1E7N0ic4LHVqaU6qEMSuW785kT1lu0HuyY2RkRJEiRfDx8WHq1KmUK1eO2bNn4+zsTEpKClFRUem2Dw0NxdnZGQBnZ+cMo7Ne/Pxim8yoVCrdCLAX/2T5k5GREQN6DyEYf+6IyySJBACSRAJ3xGWCecyA3kNypc9CXiCE4Pqtq2zbvZG9h3YSHRP9Vvuv3bgSWxxxl7zSffErJQO8qYwGNeHSU0qWyBujlJau+oPx00YT9ySRsvhSkVrYxDuxZv0Khn47gKTkJH2HmCsOHt2DqdIcB1wzrFNKSlw0BTl64iCpqdk3lN4vNoYkF0N8ShaggWc0lR098TDNvzPGBz4Jo1K5zDsNS5KET1lDnjzJ+omDLGfp/THWv2m1WpKTk/Hx8cHQ0JCDBw/Svn17AO7evUtAQAC+vr4A+Pr6MnnyZMLCwnB0dARg//79WFpa4u3trbdrkOUt7Vp2IiUlmUVL5xKY7IeRwogUTQrGRiq6tfkMd9cCBAUH4vaeRQbzursPbjNx2lj8Hr9s5TI0MKJd604M6T8cA+XrPw7UGjV37t+kBJk3wxtLJlgKW6JFBO1bdcnW2N/Fk6DH/LF8LoUoiRel4P+5mS1OOGnduXj3KJu2r+PTDr30G2guiI2LRSVMsmyZMsYUjVZDUnJithbEdHe3AdJKgeTnRAfAzs6K+4+yLr1w/5EGWwfr3AtIlo5ek53Ro0fTrFkzPDw8iI2NZfXq1Rw5coS9e/diZWVF3759GT58OLa2tlhaWjJ06FB8fX2pVi3t+Xnjxo3x9vamR48eTJ8+nZCQEMaOHcvgwYNRqeRhebKXurTrQaum7Thy4gARz8MJf/6MM+dOsmr9MlatXwZAxbKVGTbwW4p6FddvsDng8ZNHDBrRB8NkFRWohS2OpJBMkNqP9ZtXEx8Xx/cjJ772GBJS2pflawZwCrQU9SpOiWL6v9nYtnsTKqUxBTUZ+6FYSXY44s6mbR9HsuPu6kEce1CLVAykjMlMFOFYmlthZiqPRn1XHbs0ZNYvKxk/0pYCbulf49MXEjl9PoGlf8vFR/VFr4+xwsLC6NmzJ8WLF6dBgwacP3+evXv30qhRIwBmzZpFy5Ytad++PbVr18bZ2ZlNmzbp9lcqlezYsQOlUomvry/du3enZ8+eTJz4+g9t2cfJzNSMFo3b4OTgzPotq0kMTqYCtahOU0pThfs37vP5sJ488Lun71Cz3dJVf0CKRAVtLewkJyRJQiUZU1jyppgox459W/AP8HvtMZRKJeVKVSRUEUhmFSsSRBwxRNKhddecuoxMxcfHsWnHP0yfM4nZC2dw6doFhBAEPPHHQmONUso4YzSAjXAgKCQQrTZj0cD8pmWTNmiEhkfczrAuXsQQogigTYv2KBR679nwwerXvzUODrbUbx/Mlt1xqNWCxEQtS9dG07pnCJUqF6Nla7kmk77kuTo7+iDX2fl4JKck06pzA8wSrCglqqRr1leLVC4qjlK8bHF+n75Yj1Fmr+SUZBq28aWgpgQFpYytHFqh4aRyN507dmNgn69ee6zjpw/z7Y9fURhvClFS9/qliCSuKU4jWQg2rdiNsbFJjlzLvx09eYgJP48mKTkJSwMbUkUKCZo4vIuXwcnJmYsnLlBFZD5E3E/cIlj1iEPbz+ZKrPq28p+lzFsyCwfJFTdRCEOMiCCUIIUfLq4uLJq9AkuL7Ou/+LEUEHyVv38wn/edytkzdzAwkNBqBVottGjpy7yFI7G2sdB3iPnOB1dnRybLDcdPHSY2PoYy+Gbov2AgGVJAW5QLV84SEhaMs6OLnqLMXvHxcag1akzJ/INWISkxwZzIqOf/eaxavvX4/LMhLFo2lxBlADYaB1JJIUIKwczUnNmTF+VaonPj9lW+nzQCO+GCD2Ux1pgihOA5ody+f5GYmGhitJFEEY61lL7AoUaoCVEG0KDuxzOJYvdOvXGwc2TpykVcCUqrQq8yVNG0USsG9vkqWxOdj1XBgi7sPTiHK5fvc/7cbQwMFNSpW4HCXm76Du2jJyc7so9KSNhTjBQqTEXmX/xW2AAQ+iwk25Od8IhnBIUEYmFmQSFPr1wbxmxhbonKyJjYlCgcyfihqxFqEkQsjvZOpKamcuHKWWJionF2dqWsd/kMcX726QCqVarJph3ruHP3FiqVJR1qdKRV07ZYW9nkyjUBrFi3FFPJgtLaKrppQCRJwg5nvLWVuRR8DHeXAtwIO0txTQXscUGSpP+xd9bRUZxtH75mN+7uioUEd3d3p7i3xaVYodBSKKWlpVAo0CKFAsXd3d01aIC4QIjr7s58f6SEL282aJINZK5zek6ZZ+aZ32x2Z+65n1tIlOJ5qLiBRqmmZ5d++aa3INCsUSuaNmxJSFgQaWlpODu5YmpiqmtZHx1Pn4QTHByFra0Fvn5e2X4j5SsUp3yF4jpSJ6MN2diRKVRYWlijEtNJIzWzzcH/J5mMbApLc6tcO2dwaBDz//yFMxdPZsa6eLp582X/4TSo0yTXzpMT+vr6tGjShv37d+OmKZrtuoN4hEpMR09Pn7bdGxMbH5M55u7iyfhR31ClQvUsx5Qs4cfkr3RXmFOtVnH6/HGKiWWy9Dt7iTX2mCktKVOqPKHWIdzwP4uR0hiloE+SOh5rcxt+m7oIL4/C1zFaEATcXT11LeOj5Pq1B0yZ9BenT93K3FamjBdTpw2iafOqOlQm8ybkaDSZQkW9Wo3Q19cnWEuRQUmSCBYeUbyID57uXrlyvpCwYD4f2Ytrl67iI1WgOk0oT22SQlOYPGMsu/Zvy5XzvIl+3T/HxMyEq8oThElPSZNSSJBiuStdJYDbVK5Yjb9WLsA43oJqNKYB7alIXZLCUxgzeShXC1hneJVKhSiKGJBzXRMDyRCNRsOfc1ey7Pc1dPusN+07dGT6pJ/ZsfYQFctWzmfVMh8z1689oFWzsSS8eMiaRU7cO+PJrjUu2FlG8VnnqezccVrXEmVeg+zZkSlUWJhb0KfbQJatXowkSXhQHEPBmEQpjseCPzE8Y8rAabm2xLRo+TxUyWoqiw0wEDIezGZYYis5cpcrzF34Ew3rNs3zpQRHByf++n0Vv86fyYWrZzO3W5pb8UXH4axavxxXiuArvKqhY4MDVpIdV6WTLFzyG8v/WJunGt8FIyNj7G0deREdhRMe2cZVUjrxQgzeXhnLhaV8y8q9z2Q+iEkTFlHcW+DUDldMTDL8BMWLGNC8gQldBkUw4av5tGhZXW72WUCR/yoyhY4BvQYjCApWrVtGoOoheoIStaTG2sKGH0fNoUaV2rlynrj4WE6eOUpRsXSmofMSQRAoIvlxJi2QoycP0qZ5h1w55+twc3Fn3k9/EhYewpOgxxgZGlHGrzzHTh8iNS0FL7LXF1IICjzE4tx8cI7A4Cd4unvnuc63QRAEOrbtyrKVi3CVvLEUXjWVlCSJAG4jCRJtmuX95yrz6RPwKJRzZ/1Z95dTpqHzEoVCYNp4G8o3DOLwoUu0aFlDRyplXods7MgUOgRBYECvL+naoQenzh0nLj4WFyc3alatnattI6KeRaIRNZmd1f8XI8EEY4UpYRGhuXbOt8HF2Q2X/1ctOvrFc/QVBhhL2r1Lplhk7ldQjB3IKBR59vwprt0/hZPogS1OqEgnXBFIjPiMCcOmYmtj9+aJZHId/4CMtj1B6igciNexmg8nKDCjzUPVCtnj/ADK+BpiaKggKDBS67iM7pGNHZlCi5mpOS0at8mz+V91XE/GEtts42pJRZqYqvOO63a29qjEdFJIwljIbvAk/fewsrO1z29pr8XI0Ij5P//Fmo0r2LpzIyHxGUURy/lWZGr3adSoWkfHCgsnu68/JESRjOguUd/lDo6mZniYZv/+f0zY2Gb8Rh89UeHlnv2FKCRMRVqaiI2NnL5fUJGNHRmZPMLRwYkyvuUJvh+Ag+iaLWsohMdIiDSqm/cZWa+jTvX6mBib8jTlHiWlilnilURJJEjxgFLFy+Dh5qU7kTlgZGTMoD5D6d/zS2LjYjAwMMDcTH7g6IKXXc5DFMmZXc4dTc0+iWKCZcsVxcfHlXlLYmlUJ3uPsbl/xWJmZkjzltVzmEFG18jZWDIyecgX/YYRL73gtnCeRCmjw7hKSueJdJcA4Q6d2nXDwd5JpxqNjU0YNmg0oTzhDheJl2JQSyqipUiuCadIFOIY/sVXOtX4JpRKJbY2drKhoyNeGjpB7knYVInJ7HL+KRg6kLH0PWXaQPYdSaLn0EjuPUwHIDRczfjvnzFvSSxjx/fE3NxEx0plckJuF4HcLkImbzl59hizfptGbHwMBkpD1KIKQRDo3L77W3Ubzy927d/Gn3/P50VsdOY2TzdvJoyaQsVyVXSoTKags/v6Q1Kd9XEvY04xq9N4mNp+kl3ON204ytfj/yA6OhEzUyVJyRpMTAwYO74nY8Z1y7dCoTKveNt2EbKxg2zsyOQ9KpWKMxdOEBIWhKmJOfVqNcTGuuDFMajVKq7dukJcfBzODs74lSwj38Bl3khh6oOVlpbO/n0XCA6KxM7Oipata2BhIVeh1hVybywZmQKEvr4+9Ws31rWMN6Knp5+tWrKMjMwrDA0NaNdeDn7/2JBjdmRkZD4aEhLjiY2LQXZIy8jIvAuyZ+cjIj09nZPnjhEY9BhjYxPq1myIm4u7rmXJyAAZxfw0GnWu1ip6yZGTB1m9/m/uP/IHwMnBha4detKlffcCE/MkIyNTcJHvEh8Jew7uZN6in0lMTsBYaYpKSmfBkjk0a9CKr7/6DiND7cWuZGTymkePH7Bm4wqOnjyESp2Ok70zHdp0pWv7HhgZGX/w/Cv+XcKSf/7AVuFIKaqgQMnzZ2EsWDKHG7evMnPKryiVyly4EhkZmU8V2dgp4Jw+f4IFf/1GUOgTABQosNbY401JooniyIkDpKvS+fHbOTpWKvMuvIiJZuuuDew/vIf4hDhcnNxo37ozLZu0xcDAQNfy3pqLV88zbspwDCRDPDTFMcSY2GfPWLLiD06eOcqC2UsxNn7/dNxHTx6w5J8/KIIfRSQ/+C9W2hE37CU3Tpw5wsFje/O0OKSMjMzHjxyzU4DZfWA7478dQUJoImWoTmXq440vzwjnKqewx4USYkZvo0dPHuharsxbEhTylN5fduGftcuRIpQ4JLnz4nEsP/8+g5ETPyc1NUXXEt+KtPQ0vp05AUuNDVU1jfEWfHERvPATqlBRqsf9h/dYsXbJB51j+57NGCtN8KJktjEHwQVbhSNbdmz4oHPIyMh8+sjGTgElITGeXxfMxAUvKlIXR8ENK8EOb8GXqjREjYrH+OOEB4ZKI44cP6BryTJvgSRJfDNjHOkJKmqITfETKuMt+FKOmlSmHnfu3mbxivm6lvlWHD91mLiEWIpL5VAKWZeRLAUbXEQvtu/ejEqleu9zBDx+iIXGNlv16ZdYiw48CQx47/kLC2qNmsioCF7ERMvB3TI649rVBwwfMoe6Nb+kSYPh/PLzv0RFxuTLueVlrAJEfEI8j58+RE9Pjzv3bqNSqShK6Wx1TowFU9ykogTxkBKUw0gwISEpQUeqZd6Fm3eu8ejJAypQB0MhazyLlWCHm1iUXXu38mW/EZh8wPJPfnA/4C5mehaYasy1jtviRFDSQyKfRbx3IL2JsQlqIT3HcRVpGBoa5jheWElKTmLzjnVs372ZyOfhCAiIkghAcW8f+nQfSOP6zV87h0ql4sTZo5w+d5y09FSKFfGhTfMOONg55sclyHxizPllHTOmrcDD1YBmDYyIS5D47ZfVLJy/ic3bZ1G5im+enl82dgoACYnxLFjyG/sP70alzrixG+gbYCyYYYj2wGNr7HjCXRKJI1ETh6uznJX1MXDL/wb6CgNsRAet4w648jTtHk+ePqKUb9l8VvduGOobopbUSJKktfCgmgyPzofEINWr3ZCzl06TRAKmQlajSiOpiVQG06peu8xtSUmJnDp3nJi4GJwcnKhVrd5HFQOVG8QnxDP0q/48DXqMg+RGCcqTQiJhBAISz55EM/XHCYSEB9Ov++da5wiPDGPUxC8JDgvEUmGDnqTP6bMnWbHmLyaMmkrbFh3z96JkPmoO7L/AjGkr+HasDVPG2KBUZtwvnkdraN8/gm6dp3D9zhrMzD48oSEnZGNHx6SkJDN83CCePn2Ch1gCe1wQUXNPdY0kEhARtbrwU8mI6wjhMQqlghaNW+e3dJn3QKlQIiEiISGQ3UAQyXj7VnwE2UW1qtdl5bqlPCcce1yyjEmSRLgQSDGvEtjbajfs3oYm9VuwYs0Sbr04h6+mMpaCDQDJUiL3FdeQlBKfdeiJJEn8u2kFy1f/RWpaCnoKPdSiGgtzK74aNpFmDVt90LV+TMz/6xeCg4OoIjXETLDM3O4lleQqJ1Gjwgsf/lqxgIZ1mmRr8KrWqBnz9WBeRL6gGo0xl6wytosqHnKTn+Z+j4uTK5UrfLpVkkVR5PjRq+zZfZbk5DT8SnnTo2cTbO0s33ywTDYWLdhMjSomfDvWJsuLkZ2tkrWLHChaLZBNG47Qf2DePcfkmB0ds23PpoxlDbEO3kJJzAQLLAQb/KiMBjURBGU7RpREgglAH0PCecrIweOxsrTWgXqZd6VKxeqoRTXPCNM6HkEQluZWFPUqDkBiUgLXbl7mxp1rpKal5qfUN1KqZFnKlarIfeU1YqRnmbEgGklNALd5LoXTt/ugD2o3YWxswoJflmHtaM0ljnJecYhLiqOc5QDpxin89uMi3F09Wbv5HxYum4d9miu1aUl9qT01aIpxojnTfprE8dOHc+uyCzRx8XEcPLoXD7F4FkMHwEAwpARlSSQOaxwwVBixY++WbHOcOX+SwNCnlNJUwVywytyuJ+hTkopYKKxZs3FlHl+J7oiKjKFx/eF0bDeZU0cP8/TBWX74fhmlfHqwfm3h+B7lJqIocurkTbq3N9V6L/Bw06dmFWNOnriRpzpkz46O2bFnCw64ZrmpAJgJljhIbtzjKpIk4YQHSkFJspTIQ26RQAxODi4M/+IrGtVtqhvxMu9MsSIlqFSuKndu3cBYNMVCyDBSJUkigiBCecznHYeh1qj5ff5s9hzYQZoqDQBTEzO6tOvOwN6D86Rw37siCAI/TZvLV5OHcuXhCSyUVuiLRiQoYlCJ6QwbNPqNcSFvg5uLO+uWb+fsxVNcuHIWjUZDqZJlaFyvGUZGxiSnJLN81WLcKYaPUD7zOFPBgtJSVTSCmoVL51GvVqNPvs/X06AAVGoVdjhrHbfGAQVKEonDXLTmadDjbPucuXACC6U1FqJNtjFBEHASPbh49SwqlQp9fd1/D3MTURTp3nUK4SFBHN3iSt0axgiCwPNoDRNmPGfIF7/g4mpH3XrldS31o0KSQPEaZ7WeXsZnn5fIxo6OiYwKx1MqiZYVDUpRhXMc4C5XeKS4hb5gQLImEX09A7q378PwQV+hUMjOuY+N6ZN/ZuTEL7n49Ag2OGAoGZOojCVBE0ezhq34rGMvRk38kvsP7uIuFsMBV0REIpKDWLV+OU+Dn/Dj1DkF4sFtZWnNsgX/cuHyGY6cOkRychKebl60ad4BF2e3XDuPUqmkTo361KlRP9vY2QsnSUlLwYPi2cYEQcBDKsbV8FPcf3iXkiX8ck1TQeSlEaxBrXVcRERCRIEClSIdE+PsDSxVKhV6Us6PBj30kSQJtfrTM3ZOHLvGlcsPObLFlXo1XyUI2NkqWfabA7fvqvj9t/WysfMOKBQKqlUvyZbdQQzpa5VtPCJKzekLKfwwq3Se6pCNHR1jbm5J8otErWNKQYmhYES58uVITk3B/94tAFTqdNZtXsXlKxf4duJMihUpkZ+SZT4QG2tb/v5jLcdOHWL/kT3ExcVS2tWPti06Uql8Vbbv2cydezepTH0shVed0S2wxlKy5fjpw1y4cpbqlWvp8CpeoVAoqFG1DjWq6qY5Ymx8LApBgTHaO0+bkBHYHBcfm4+qdEOJoiWxsrAmLD4QS2yzjEmSRDiBSEgYYkScGE2DOtmb0xYv6sPBo/tIl9IwELJnukULEbg6umdWx959/SEhimSS1VGU1r8ImOXJteUHe/eco5i3EfVqZA+UVSgEBvQwY9jXV0lOTsXEpPBVrQ8KiuTQgYukpqZTukwR6tYr/1YvXYOHdqJf7x9YsCyW4QMtM49JShbpNzIKExMjuvVokqfaZWNHx7Ro0poNm9bgLfpiKGT98cRIz4iTXqAWNdy5exMvqSSuFEEfA14QyeNAf4Z81Y+/F67H3dVDR1cg8z4YGBjQrFErmjXKHji7Y88W7ATnbA8ryMjWslBas2v/tgJj7OgaJwdnREkkgdhsy8EAcbwAwNFB+9LOp4S+vj49uvRl0fLfMZMsccKDMJ4QymOSSQQE9DHkvuIGRdyLUbdmg2xztGrajr9WLOCB+jp+UpUsCRLPpQgihVBGdRjH3cdRPE6IJ9VZHxuPGErb3aaKgyceJsXy8Ypzl+TkNGysFTk+wG1tMtZi0tNUhcrYSU5OZfSIeWzeeAyFAgwMFCQnayhRwpUlf0+ifIXXv3C361CHEaM6M3rqZpatTaB1Y2Ni40U27kwiLV3B2g0zsLLKWyNZXgPRMV3b98TU3IzrylNESxEZzRQlDWHSU24pzlPMqwRXrl/ER6pAEcEPQ8EIhaDATnCmglgHTZrEqvXLdH0ZMrlIRFQY5pL2gHNBEDDTWBIWFpLPqgou1SvXxMbKlifC3WwF8zSShiDFA0qVLIuXh7eOFOYvPbv0o0OrztznGqfYzSNuYYE1vlSiCL4oEEiX0ujf60utsV+WFlZ8N/FHnglhXFQe4al0n1DpCTc5zw3hLDWq1Ma3VANOJkUQ5J6E6PGURp5xH72hA+BXyovrt1N59lz7MuCh48m4utpgYandi/gpIkkS/XvPYM/OE8z/0Y4X94sQ/8ibY1vdsDB5QfvWE3gcEPraOQRBYMaPX7Bt5yw8i1Zg7Q4Fh8+Y0L1XO85cWEq9BhXy/DoESS6nSXx8PJaWlhzedhZT0/x3wT4NesLUmeN59OQBSkEPCRFREqlTvQFOTs7s2rWNmpoWWlPQH0t3CdZ7yNGd5wpE0KrMh9O1XxvUYVBKqKJ1/KpwkhIVSzD3x0X5rOzd0Gg0qDVqDA3yvujf8dOHmTxjLNbY4yEVxwRzEoghUPGANGUyC+f8TamSZfJcR0Fi5pzv2HtgJxWpg5Vgl7ldI2m4KZxFbZbGjnWHcvz73Ll7kzWbVnL63HHUGjWebt50bt8dA9fyhOmnYVPOhNIuF3E0NaO2/aeRhv4iOp5SPt3p1MqIv+c5ZtaDATh7KYXGXcIY/3Ufxk3ooUOV+cu5s7dp0eQrNi1zpmOrrM/HuHgNZeqH0KhZQ+Yv/Eon+uLjk/Bw7kBcXBwWFhY57icvYxUAvDy8mTfrTzZsW8PToCfY2tjRtUNPvD2KMOOXKRhjlmO5fFPMUanTSUpOxtJCrgHxKdCyaRuWr/qTVLEURkLWKspx0gteSFE0bzxGR+rezI0711iz/m/OXjqFKIq4OrnTuX03OrftlmcGef3ajZkz4w/+WDqX64FnMreX863AqCET8C1R6o1zpKalsufAdnbs2UJEVDgW5pa0aNqGjq27Ym2VPTOpIKNWqzh55iiueGcxdCAjFrCEVJ5zCQc4fuqw1qVUgFK+ZZn17W9IkoQoipmd5Xdff0j5Sl4I1upPytABsLG1YMGicXwx8Cdu31czsLsZtjZKDp1IZu3WRCpV9mXYiE66lpmvbN54FG8PQ9q3yO7NsrRQMrCHGb8uPsq8BaMLdMKMbOzoGLVGzcKlc9m8Yx0ajQalQg+1qOLMuRN8M2469nYOJEsJaCRNtv5DAAnEYmxojKlp3rtVJUnKTDctCJlAnyodWndl2+7NXIs5RTFNGexwRkIkklDucw2AC5fP0qheM/SUBesnfPDYXqb9NAlzhRXFxDLoYcCLyEgW/DWH85fO8sv0+XmWwVOjah2qV6nN46ePiI2LwcHeKVss2/PoZ4RHhmFuZo6nu/f/C5RMYtTEL/C/fxt7wQUHyYOUpERWrlnKjt2bWTx3Ja65mF2W1zx7HkV8YhxF0e7NMhXMMVdacu+hf47GzksEQcg0dAoDnbs2wNnFlt9/W8/Ib64gSRJubrZMmNSXocM7YmxccNqTiKJIfHwyJiaGGBjkze/qxYsEvD31UCi03/OLeOqTnJxOWpqqQH02/0vBulMWQn5fPJstuzZSRPLFlSIYSIbEE0NAzB3GTR3OtxNmkiamEkIAnmQNAkuTUghXBNK6Wbs8fejFxsWwdvMqdu7dQlxCLMZGJrRo0oZeXfrh7OSaZ+ctrFhaWLF4zt8MHtOPGy/OIqAAJCQkbHHCBgf2H9mNna09QweO1rXcTGJiX/DDL1NxwgM/TeVMQ8IFT6IlTy5dPcPmnevp3qn3e83/6MkDNm77l9PnTqBWqylZwo8u7btTu3r9zHMJgkBR7+wp6MGhgcz/81fOXDyZGdfj7VGUL/uPoF6thixc+hsPHt6nMg2wxCazFEQRsRTX404x9Yfx/L1w3Xvp1gV6/xmU6hxS0CVJQi2p0NcvXK003pZatctSq3ZZUlMzHuIWFiYF6gUv5kU8837byOp/9vLiRSL6+kratqvNV+N7UKp07sameXg48u/xdNLSRAwNs3tuLt9Ixd7eAiOjgv1dKrg+p0JAeGQYW3ZtoJhUGm/BNzPN00KwppxUExPJnJ37tvJZh1485Cb3pGskSLGkSSmESU+5ojyJqYUpfT4bkGcan0VHMWBYD9ZvWo1Fgh1+VMYx1YO9e3fSb2g3Ap48zLNzF2YsLa1JTErAGU+KU4YSlKMGTakg1MZTKIGn5MPGbWtJStJetkAX7Dm4A1EjUlwqm+3BYCs44oAbm7eve6+u2yfOHKXf0G4cOXQIizh7HJLceXjjERO+G8XcxT+/ds6QsGA+H9mba5eu4iOVpzpNKE8t4oOT+Pr70WzdtYE9B3fgLhbLbEfxEiPBmKKa0tx9eIc7/5V++Biws7GnmHcJIoRArePRRJCiSaZ29Xr5rOzjwsjIAEtL7ZV/dcXzZ7E0azSKFcu20qezHuuXOPHD19bcuHKeJg1GcOb0zVw9X68+zXgerWL+sthsY4+epPPPhiT69Gv12s8oPV3Flk3HGDPyd0aPmMf6tYdJTc25wW9eIBs7OuTIif0oBT3cKJJtTCEocBOLcvn6BXp17c/g/iOJM33GBQ5zij34c5ky5cqw9PdVONg75ZnGOQt+JDY6hqpiI3yE8rgIXhQTSlNN0wSSFUz7adJ7PbxkXs/VG5dISUvBG188hOK4C8UwFV4F37niTVp6KpevX9Shyqw8evwAS8FGa20WAFvJkbDIENLese3Fi5hops6cgJ3oRHVNU4oLZfAWfKks1ackFdi0PaNmUU4sXPobqmQNlcT6uAlFMRMssROcKS/VwlnwZP5fc0hXpeOAdi+lHc4oBT1u383bcva5iSAI9Ok2kGdSOI+k22gkTeZYrBTNPeU1SpcsRxm/cjpUKfM+fDd1GTHRUVzc78qc7+3p0saccUOtuX7EjSrl9fhy4CzUas0b59FoNG917y5ewp2Ro7vw9Q/RDBwTydlLKdx9kM5vf8ZQp20YTs4ODB+ZcxzT7VuPqVS2LwP7zeLimaNcvXCMwZ/PpnypXly5fO+drv1DkJexdEhcfBxGCmOUOVQrfVkkLTEpgb7dB9GtU29u3rlGWloa3p5F8zyG4Fl0FCfPHcNHKo+xkDUmSF8wyHDxPznNnXs3Ke0r3zRzk7T0jBYR+mh3Db/cnpZecPplGRgYoBZUkMP9U0U6giCgp/dut52d+7ciaURKShWzBeq7CUWJEkLZsPVfGmppmxIbF8PJs8coLpXNZoQJgkARyY/w9Azvx8smrP+L9F/VYWUBi496E00atCA8Mow//55PmOIJFqI1KmUacZoYSniW5Ofv5xUoj8WnRlxcEieOXyMlORW/Ut6UKVv0g+eMjU1ky6ZjfDfWguJFst4bjI0V/PqdLVWaBXPwwEVatqqR7fj0dBXLluxi5fKdPHgQhpGRPq3b1GLE6K6UK59z2YDvfxiEk7MtC+ZtYOX6jLIX+vpKOnSsy8yfBmNtoz0L6kV0PB3bTsTZIZ3dqzwoXTLjN3j/UToDxjyjU7uvOXtpGS4udlqPz00+rl/vJ4aTgzPJmkTSpNRsBQUB4olBqdTD1ibji2BoYEiVCtVfO+ez6Cg2bV/HgcO7SUhKwMXJlQ6tu9C6eYd3TgF+/OQRkpQRJ6INWxwREHgQcF82dnKZYt4Z8VnRROKEe7bxaCKz7FcQqF29Prv2byOOF9mWgyRJIkIZRPWKtd45I+vO3ZtYSnboC9oNPzvRmTv3tS8xRT6LQJTEjDgcLRgLpuhJBmhQEUEQFmSvbxRJCKIkUrn8x5d11KfbQBrUacKu/dsIDH6CiYkJDes0oWbVuoUq6Dg/Uas1zJi2gqV/bSc5+dVSTdVqPixYNB6fku9fAPbJ4zBSU1U0rmuidbxiWSPsbPXxv/Mkm7GTlpbOZ52mcPrUDTq1NmPclw5EPdOwcsM5mjQ4xep102jWXPt3XBAEhg7vyBeD23HzxiNSU9MpUcIdO3ur1+pd/c9+4uISuHrQE2fHV+aGTzEDdq92wrtKIH8v282Ub/u90+fwPsjGjg5p0qAl8//6lSequ/hIWctup0tphCof07BOY8zNcq4d8P95/PQRQ8cOICUpGQfRHVcciA98wZyFP3Hw6D7mzVqMsbH2H4k29A0yHi5qVFrH1agySs/nQx2VwoaXhzflS1fiof9drEX7LMZwupTKE4U/ZUtWoIhXwSniVrNaHbzci3An7CKlNFUzDR6VlM5DbpIgxtL7PeLLFAoFkpBzk0AREWUOKa8W5hnlGFJIxkKLwaOWVGhQY4ARQTzCQrLBEbfM32KcFM0jxS1qVqrz0RYldHf1YOjAUbqWUWgYM3Iea9cc5OsR1gzqaYGdjZKDJ5KZ+lMgLZuO5sjJhaSnqVixfA93/Z9gbGJEq9a16Ni53hurMr/MdoqO0b5MlZIikpSs0Ros/Mf8LZw9c5P9611oUOvVc2DsEGs++yKCz/v/yJ0H6zA3z/kZoaenpGIln7f5GADYveskbZqaZDF0XmJtpaRLW1P27DyZL8aOHLOjQyzMLRjx5ThCCOAW53khRZEkJRAqPeGK4jj6Jnp82X/kW80lSRKTv/8KKQmqi80oKVTAS/ChLDWoJNXD/95t/ly54J30lSpZBgszS0J5onU8jKcoFUqqVar5TvPKvB2Tx36PgbkeFxVHeCTdJkIK5pF0m4vKI+iZKflm3Pe6lpgFPaUe82b9iYOLA5c4ykXFEa4KJzkt7CVKGcLU8T9QoWzld563WqWaxEjPSJWSs41JkkSUMoSqFbO77AGcHV3w8ylDiBCgNT4hhABAogr1sceZ21zgPAe5I13iinCCSxzDy9ubbyfOfGfdMp8mgYERzJzxD4P6zWLs6PmcPnUz87vlf+cJq/85wIIf7Zk+0RYPN31MTBS0b2HG8W0uGOilM6jvLKpWHMTm9buxNX1E0oubDB8yh5pVB/Hkcdhrz13Cx52iRZ1Y9m+C1vG12xJISRFp1TrrPVkURVYs20nvzmZZDB0AAwOB+TPtSExMZfPGox/wyWQnJTkVe9ucPYj2NkpSUtJy9Zw5IRs7OqZz225MmzgLPUeBq5zkHAe4x1XKVSrP0vlr3jou58r1iwSGPqW4WC5LbEK6lEYsz1GKemzevp6J00Zz+dqFtwpMMzQwpHuXPoTwmGDpEaKU8XYtSRKRUghPFP60aNIWO1v797t4mdfi7urBioXrad26HZFGQdzmApGGgbRs2ZYVi9bj4eala4nZcHRwYvWSzfz03TzqNKpLpboV+bzfUHasPUSLxm3ea85mjVpjYW7JbcUF0qSUzO0aScMDbhCviaF7l745Hv9l/xHE8pxbwnmSpHggw9v0RLpLAHdwoyhGgillqUFRSpFEAkYeevhV9mXG5Nksnb8GSwur99Iu82nx6+y1lC/VlyWLNvAs9CLHDh6idfNxdGgzkfj4JDasO4KDnT79u2X3xtvaKPmitxlXr95jwjArAq94sHGpM8e2unLnpCf6QhxdO05+bXCxQqFgzLiebN6VwNSfnpOYlHFP1mgkNu9O4Ktvo+nYqS7eRVyyHBf9PI6QkGhaNNJej83dVZ+ypYy5eSPgAz6d7JT0K8Lhk6mIYvbnjSRJHDyZio9v/nhM5WWsAkCzRq1o0qAFDx/fJyk5CTdnt3fOsLpz7xYGCkOsxFeBXolSHFc5hZp07HDBUDLi6vkrnDx7lI5tPmPc8MlvDFDs89lAnj+PYsuuDQQqH2AqmpOqTCZJk0DtqvUZN2Lye12zzNvh6ODEuOGT+Wro16SkpmBsZFygq5RChoenXq2G1KvVMFfmMzUxZe6sxYz+ejBnkvZhIzmiRI9Y5TPSxTTGj5hCxdd4jKpWrM6PU+cwa+50ziUcRCnpIZLxQHGnGMUpC2TEJXhJJXki3KVj28/o3LZbruiX+TRYu+YgP3y/km9G2zBxhDWmJgokSWLP4SR6D7vN4M9/xsLCjOJF9DEw0H5f9S1hgCjC+GHWWWrWlCxuwJqFDlRrEcyB/ReyeWb+P736NCMiIpofZ/zDH38nULqkAcFhGoJD02jWoioLFo/NdoyBYcayVnxiDkH4kkR8vCZXCxPu3XOOC+duExycxh/LYxn5edZ4uJUb4rl2M4WN37XNtXO+DtnYKSAoFAp8ivm+9/FKpfK/rBEJAQFRErnBWQwwpBqNMBSMAZBEiVCesHXXBkoU9aFdy85v1DVuxDd0aN2V3Qe2ExkVjrWVDc0bt6G0b/Z6KjJ5g0KhwNSk8DQf/F98S5Ri0z972HNwB2fOn0ClSqdByfp0aN3lrTxc9Ws3pmbVuqze+DfLVi3Ci5K4UyxbYoCIBlES0X/HjLHCgH9AJI8T4glRJJOsuEZp/VAg/3sJ6gJJkpj761o6tDRj+kTbzO2CINC6iRkLfhTpO+I8ffq14H6AKscCfLfvpmNsJGBhnn1pp3J5I3yLG3Hk0OXXGjsA4yb04LPujfl39QGePgmnbBVzOnetT6XKJbXeky0tTalRw48V657Sp4t5tn1OnkvhcWAazVvkThD+jm0n6dd7Jk3qmVClrBljvn3OoRPJdOtgjkIhsHlXItv3JdK3XwuaNNPeAzC3kRuBovtGoLnBg4B79B3SlTJUx1FwI0oK5SbnqEZjzAWrbPvf5DzGLnqs+3uHbLDIFBpS01Jp060R1kmO+Ajls42HSI+5L1xjy6p9ODu6ZJ+gkPLS0AlyT8LOJZbSdqGfRJfzt+XRwxAqlx/A7jUuWpeC0tMlHEo9pU+/tiz8Yyu//2DP8IFWWfaJeq6mdN1AKpY1Yv967TWdqjYPxa98XRYsyv2mmvv3nadb528Z9bkV0yfaYmaaYYxdup5K54GR2Dq4cezUog/2HKtUasr69qRaeRWbljkhCLB6UwK/L43l+u2M+BxTUwN+/Hkoffq1+ODnz9s2Ai3Y/nCZt6ZE0ZJULFuVh8obxEkviOEZJphpNXQAHCU3AkOfEhP7In+FysjoECNDIz7r0JNgArgqneSydIJr0imCpUdESaEEKG7TsE5T2dD5f/gHRHIyKYIg9yT8fDU08owrVIYOkBlEa2OtPdjWwEDAzFSBmYUJgz5vw5hvnzNh+jMeBKQT/ULDum0J1G0XRkISGBtpf7gHhai4diuFipXyppxE8xbV+fnXoSxYHod7hUBadA+lYpMQqrcIxtLaiXWbfsiVJfKjR64QHh7Dt2NtUCiEjAKXXS24csiD6HtFWPWHI0lJ6VSt5pevL9o6NXZmzZpFlSpVMDc3x8HBgfbt23P//v0s+9Svn9H35v//N3jw4Cz7BAUF0apVK0xMTHBwcGD8+PGo1dp7wnzK/DBlNu6eHlziKFGE5FTbDQAB2ZsjUzgxMTEFJOKJwRAjJCTuc52bnKdo0eJM+mqajhUWHHZff8jJpAhsyplQv+wdyliFUNu+WqEydAC8vJ0xNTXgwLEkreM37qQRHplOqdJF+HnOUMZ/3ZNla9PwrR2IQ6nH9BoagbO7DyNGd2PP4WR2Hsja5iUlRWTIxGdYWBjT5bNGeXYdXw5pz/U7q/hiaFcMLSviU7omq9d9y4mzf+VaYb+Q4CgUCijrlz39PS5exP9+Ru2hZUt2EvMiPlfO+TbodGH6xIkTDBs2jCpVqqBWq5k8eTJNmzbF398/Sxfvzz//nOnTp2f+28TkVeqcRqOhVatWODk5cfbsWcLDw+nTpw/6+vr8+OOP+Xo9usbayoblC9Zy4swR/t28knsP/EmU4jATLLPtGyWE4OrkjrWV9mJrMjKfIucunWbBkjl4UoKilEIhZLypp0hJ3FScI/rFc/Tfsejhp075Sl4I1mocTc2obf/xFVbMDczNTfise1PmL9tP59Zm+Pm8ynhNThb56rtoXFysadGyOkqlkknf9GHk6C6cOXWLlNQ0/Py8KF7CHbVaw8P7gXTod4am9U1pVt+YZ9EaVm9O4kWsxNoN0zEzM87Ta/HwcMzTujZ2dpaIIjwJUlPEM+O3pNFIjPn2GYtWxGFsLODhqseqlXv4d/UBvv/hc74c0j7P9LxEp8bO/v37s/x75cqVODg4cOXKFerWrZu53cTEBCcn7dlJBw8exN/fn8OHD+Po6Ej58uWZMWMGEydOZNq0aRgYFOxOrLmNvr4+jes3p37tRnTs3ZK7MVcoJ9bKTEeXJIkIgogghHGdJuk0XkcURS5cPsP+I3uIiYvB2dGZNs07UKqkHPgskzf8u/EfrBR2FBPLZPmOGQumlBarci76IMdOHaJZo1Y6VClTEPl2Wn8unLtJ9Zah9OlqRs0qRgSFqFn2byKRzyU2bv0eff1Xj1RTU2OaNq8KQER4NPPnbiQk9BmlShehYmVfdu88ybe/PMXY2JBWrRsxZHhHSvp66uryco0mzapiZWXCr4tiWPSzAwBf//CcP/+J45dv7fiijyWmJgoin6mZOe8FE8ctwsrKjM+6N85TXQUq5SAuLg4AG5us3oZ///2XNWvW4OTkRJs2bZg6dWqmd+fcuXOUKVMGR0fHzP2bNWvGkCFDuHPnDhUqVMi/CyhA6Onp88uM+Yyc8AVnk/djL7pggCGxyufEaV7Qqmk7OrTuqjN9SclJjJ86gmu3LmOhsMZINMFfeZud+7bSsklbJn/1vVzOXiZXUWvUXL15kRL/U638JaaCBVaCLecvn5GNHZlsWFmbs/fQ7/wxfzOrVuxm8cpIDAz0aN+xLqO/+gy/UtnrxUiSxC8//8vsWWswMBDw9jAgJExFXLyagYNac+DI75/cfc7ExIivv+nL1+MXA9C/uwV//B3Hd2NtGTP4Vfq5o70ev/9gT1iEhp9nraLLZw3ztKxGgTF2RFFk9OjR1KpVi9KlS2du79GjB56enri4uHDz5k0mTpzI/fv32bp1KwARERFZDB0g898RERFaz5WWlkZa2quqjfHx+bdumJ/4FPNl3fLtbNuziSPHD5KSkkApr1J0bPsZNavW0an3ZNZv07h95yYVqION6IAgCEgaiXAC2XdoFy7ObgzsNfjNE8nIvCWSKCFJEorXhCoqUKLRFL54P5m3w9LSlG+m9mXylD4kJ6diZGTwWmNl2ZJd/DhjFZNHWTNuqDWWFkpSUkSW/RvP2Gl7MDUzZvrMz/PxCvKHl8tSP/3wD3+tCkYQYHDf7OEUgiAwbIAljTuHcvNGAOUrFM8zTQXG2Bk2bBi3b9/m9OnTWbZ/8cUXmf9fpkwZnJ2dadSoEQEBARQt+n5dZGfNmsX33xesUvt5hY21LQN7DS5QhkN4RChHTx7EhwrYCq8MVUEQcMGLBCmWDVvW0Ktrf5313QoODSQiKhwrC2uKFSkhL6t9Aujr61PMuwTPn4bjSva38DQplVieU8q3rA7UyXxMCIKAqenrY2tUKjW//fIv/bpZMOPrV8G/xsYKRgyy4kWshtkLt/PVuG5YWZvntWQiI16wetV+zp+9jSBAnbrl6dm7GbZ22Y2QD0UQBAYP7UCffi0YO2oB27cewdZGu1Ho5pxhhiQkZG8Hk5sUiNTz4cOHs3v3bo4dO4ab2+vbI1SrlhEg9+jRIwCcnJyIjIzMss/Lf+cU5zNp0iTi4uIy/wsODv7QS5B5By5ePQeAM9q7/zrjSUJSPHfv385PWQD437/NF6P60LV/G0ZO/II+Q7rQ8/OOnLlwMt+15BWpaansPbSTRct/Z8W/S3gSmLsl4gsyXTv05JkUToQUlGW7KGm4J1zFwMCQlk3yp6KrzKfN5Uv3CA+P0erRgAxPR2qqioMHLua5lv37zlOhTB/mzF6FkXAXPc1dfpj+NxXK9OHUyRt5dl4TEyPad6pLSqrIlRupWvc5cS4FQRDwLuKcZzpAx54dSZIYMWIE27Zt4/jx43h7v7lHxvXr1wFwds74YGrUqMHMmTOJiorCwSEjGOrQoUNYWFjg5+endQ5DQ0MMDeVO3f9L9IvnnL14itS0VIoXKUG50hXzxKOhUqsRBAGFpN3S1/vva6lSa++2nlfcuXeLYWMHYKQxpQzVMceKFBIJCn7I+KkjmDn1VxrUaZKvmnKbk2ePMeOXKSQmJWKqZ4ZKTGfJP39Qv1Zjvp3wA8bGOXc8/hRo1bQd129dYe+hnYQJT7ERHVChIkoZglpQ8dPUuZib5VyYTEbmbUn8z1PhZK/9Pudgp0ShgMTEFK3juUXAo1D69pxOs/pG/D3PDWurDD1Rz9X0HBpFj65TuXD171xLPf9fGjWujJubLZN/fMGu1c5ZWmk8j9Yw+484mjarjJubQ56c/yU6NXaGDRvG2rVr2bFjB+bm5pkxNpaWlhgbGxMQEMDatWtp2bIltra23Lx5kzFjxlC3bl3Kls1wNTdt2hQ/Pz969+7N7NmziYiIYMqUKQwbNkw2aN6S9PR0fls4i90HtqMRNSgEBaIk4unmzbSvZ1GyhHaj8X3xLVEKURKJJgI7slvzzwhHT6lHMe+8Ka6VE3MX/YyRxpSKYj2U/6Ukm2CGjeTILc7zy/wfqVOjPnofaWryjdtXmTz9K2wlJ8pSCxONGaIkEkEQp8+d4LtZk5g9/Xddy8xTFAoFU8bNoEbVOmzevo5Hj++jr29I09ot+KxDT7w9329pXEbmfynu4w7A8bMp9O6S/Z5x8lwKogglfLR7uHOLv/7cjoWZwNrFjhgbv1rMcbDTY9NSRzwqBrLy771MntInT86vp6dkwaJxfNZ5CjVahTB8oAVFPQ24ciOV35fFk5puxKzZQ/Pk3Fl05PkZXsPixRnR2vXr18+yfcWKFfTr1w8DAwMOHz7MvHnzSEpKwt3dnU6dOjFlypTMfZVKJbt372bIkCHUqFEDU1NT+vbtm6Uuj8zrmT57MsdPHaGIVAoXvNCT9InhGQFhtxk2fiArFq7L1Q7bfj6l8SnqS8DT25hrrLP0J0qU4glSPKBx/eb5WgPoadAT7ty7SRmqZxo6LxEEgSKSH+fjDnHu0hnq1Kifb7pykxVrlmCKJaWlaiiEjJueQlDgghcKUcGp88e4/+juB/Vo+xgQBIHG9ZrRuF4zXUuR+YTx8nKmYaMKzJznT4uGptjZvrqvJCeLfD0zGgsLIzy9HF8zy4dz5OAFurQ1yWLovMTKUkm75iYcOXQhz4wdgAaNKrF7/xx+mvkPg8ZcA0BfX0m79nWY8l1/vLzzdgkLCsAy1utwd3fnxIkTb5zH09OTvXv35pasQsW9B/4cOXmQUlTBWXhV48EGByzEOlxMP8w/65YxdfwPuXZOQRCY/s3PDB7TjwsJh3AU3THBjHhiiBJC8HDzYvSQibl2vrchMiocAAustY6bCZYoUBLx334fG4lJCVy4epaSVMw0dP4/DrhhpLzFkRMHP3ljR0Ymr5AkiSuX73Hy+HVESaJrt8ZMmfSI8o2CGDHQkgplDHn4WMUff8cSGKzGykJJyyZjOHJiIQ6O2u89H4parcbUJOfwXFMTAZUq70MGqlbzY+vOn3kWFUNMTAKOTrZYWuZfc+N3DlDu27cvJ09+OsGahZ0DR/dgrDTFSUuwsJ6gj7PGi0PH9qPO5XRcDzcv/vlzI1079yDZKpYA5W0ERw1f9B/O0t9XY2mR+xkCr8PK0gqAFBK1jqdKyYiSBisLq/wTlYskJ2eUuTdCewaJQlBgKBiTlKz9+mVkZF5PWNhzmjceReP6o5g/dzWL5v/L4M9/wcTEkPBINd/9Ek2L7mGM+fYZpXwMOLfXnYsH3EhMiGXB75vyTFeFir7sOpii1bmgUknsOZxKxUq5G6rwv0iSxPVrD9m18zQPH4ZQtJhrvho68B6enbi4OBo3boynpyf9+/enb9++uLpq7+AqU/CJjY/BGJMcA5FNMEOlTiclJTnXAzftbR0YNmgMwwaNydV534cSxXzxcPUiKOwh1pJDts8jkAcYG5lQq3o9HSn8MKytbDExMiU29bnWOKl0KZUETRzurnkbPyDzcfCyy3mIIplkxTVK64cCZrqWVWBJTk6lfavxpCQ9Y8cqZ1o0NEWhyMg06jIwAjsbJffPehIbL2JjpcDC/NWSVr/PzFi5ah/TZ36eJwkhnw9uR6tmp5j1ewyTRllnnkOSJL6Z9ZywiHQGft4m18/7krNnbjFx7AJu3Xqauc3Dw46p0wbR5bOGeXbe/+WdPTvbt28nNDSUIUOGsGHDBry8vGjRogWbN2/OF1eYTO7iZO9MEgloJI3W8XhiMDU2w8Q4f63w/EYQBIYOGs1zKYLbwgUSpYxCk6lSMvel6wTziIG9B2PykWYr6evr07p5O8IUT0mWsnpvJEkiAH+USiUtGufdTS8vkSSJxKQEkpJkz9SH8tLQCXJPwqZKTGaX88LaF+tt2LThKA8fhrL3XydaNzFDqcxoWl2/pgm1qhpRuqQBVpZKvNz1sxg6AOVKGRITk0RqanqeaKtVuyyTpvRh6s/RVG8Ryuw/XjDr9xeUbxTCnMWxzJo9hDJl8yYw/9zZ27RvPQEzo0h2r3Eh8nYRzux2o3KZVD4f8BNrVh3Ik/NqQ5DeFDjzBq5evcqKFStYtmwZZmZm9OrVi6FDh1K8eN5VQsxt4uPjsbS05PC2s5iaFq63l+DQILr2b00xyuAl+GQZS5WSuaQ4Svt2nRk9ZIKOFOYvh47tY84fs4hLiEUp6KGR1BgbGjOg92B6dun3URcXjIuPZdCIXjyLjMJVLIINDqSRSpjwhGgpkomjvqV9q866lvlOSJLE3kM7WbdpFQGBDwEo6lWc7p370LJJ24/676ULdl9/SIgiGdFVon7ZOziamuFhalvoupy/K+1ajceQR+xb55JtbNSUKLbuSeTpZW+UyuzfxymznvPHihSCwnfk6ff18MFL/LloK+fP3UYQBOrUK8+QYZ2oU7dcnp2zcf3hKDTBHN/qgqHhK9+KJEn0GxnJ3qMS/g/XY2T0/j0s4+OT8HDuQFxcHBYWOa8+fFCAcnh4OIcOHeLQoUMolUpatmzJrVu38PPzY/bs2YwZo/vlCZnX4+7qQa+u/VmzcQUpUiIueKOPAS+IJFD5AEtrK/p0G6hrmflGkwYtqF+7MWcunCTyWThWltbUrl4fU5OP37NlaWHFkt9XseSfhew7tIvH6f4A+BT1Y0KvydSt2UDHCt8NSZL4beEsNu9cj73gQimqABAVGMoPv07lwaN7jB4yQTZ43pKXho5NORNKu1ws1F3O35XY2HiqltZeT6dnJwv+WB7H+u0J9OyU9WH8PFrD8rWJdOvRIs+/p42bVqFx0yp5eo7/z4P7QVy+9IDNy52zGDqQ4Un/ZrQNazYHcmDfedp1qJvDLLnHOxs7KpWKnTt3smLFCg4ePEjZsmUZPXo0PXr0yLSqtm3bxoABA2Rj5yNh6MDR2FjZsnr931yKPwpkBKzWqVafr4Z9jY21rY4V5i/6+vrUr91I1zLyBGsrGyaOmsqIL8YS9SwCYyMTHB20Vxov6Fy6doHNO9dTkoq4UQT+e1Y440kwj9i4/V/q1mxApfJVdSv0I6J8JS8Ea7Vs6Lwj3t5unLsSjiRJ2YyWKuUNcXJQMnB0FCFhagZ0t8DKUsm+o0l882MMIkaMGN1FR8rzjvCwaCBjmU4bJYoaYGysIOy//fKadzZ2nJ2dEUWR7t27c/HiRcqXL59tnwYNGmBlZZUL8mTyA0EQ6N65D13ad8f//h1S01Lx9iyCvW3eVrSU0R0mxiZ4eRTRtYwPYuvO9VgorXHVZK+87kZRwpRP2bp7o2zsyOQ5ffu3pEPbU6zdmt17c+RUChFRGuo1qMC0X28y+cdXD/fKVUqwZ90EPDzyttaOLrB3sALg7sN0inhmL6r4NFhFSoqIw3/75TXvbOzMnTuXLl26YGRklOM+VlZWPHny5IOEyeQ/enr6lC1VXtcyZGTeiocBD7DS2Gl1/wuCgJXGjoeP7utAmUxho37DinTt1pB+I49x+kIK3TtYoKcHW/cksmhlPI2bVGL95h+IjUng2NGrpKamU6Zs0Tzt8q1rfP28KFvOm18WRtKsvgl6ell/p7P/iMHS0pgWrWrki553NnZ69+6dFzpkZGRk3gkjIyNSyDmDRUU65kYfZ/aczMeFIAgsXjIeX18v/lq8lSWrQwCwsTFj2IiuTJzcCz09JXb2Vvmabq1LBEFg+g9f0qn9ZNr0DufbsdZULmfEoycq5vwZw4p18cyeMwwTk5wdJ7mJTisoy8jIyLwvDes2YeW/y0gX0zAQssYFpEtpPBfCaFd3sI7UyRQ2lEolY8Z1Y/iozjy4H4woihQv4f5BmUYfO/UbVmTdxulMGDef2m1CMrfb2poxZ96IPK3v87/Ixo5MJunp6WzZtYF1m1cRExuNvr4BVSpWY8yQr3FyzPveJTIy70L7Vl1Yv3UNN1PO4itWxlQwByBJisdfcQUTE1PatuikY5UyhQ19fT1Klc4eR1ZYadq8Ko2bruLUyRsEB0Vha2dBw0aVMDTMXyNQNnZkAEhJSWbgiJ48CQpAQMACG0SNhpNnj3H63El+/n4etT/S6sEFkeSUZB4+vo+AQImiPhgZaW/jIJMztjZ2zP95CeO+Gc65uANYKmwAiThNDLaWdsz54a9Cl0koI1MQUSgU1KtfQacaZGNHBoDZ82fwJCgAO5zwpXJmJ/IkKYGb0jkmTRvDvs0nMDMz17HSj5vUtFT+/Hs+O/duISUtBQBTYzM6tOnCF32Ho6+fPWtBJmd8S5Ri67/7OXbyENdvXQGgQtnKNKjTBAODwrt8ICMjkxXZ2JEhOSWZQ8f2Y4AhZaiBUnhVHMtUMKeCVJvT4l6Wr1nMqMGFo5JyXqBWqxg3ZQQ3bl3BTSyGI25ISESmBLN20yoeP3nE7OnzUSq1FyeT0Y6hgSHNG7emeePWupYiIyNTQJGNHRmePH2EKIq44ZnF0HmJkWCCreTImfMnsxk7kiRx7dYV9hzYTkRkONbWNrRo3IbqlWvJD+3/4ciJg1y5cYGK1MVGeFXDyAJrrCV7zl46xenzJ6hXq3Bka8jIyMjkF7KxI4PiP6NEj5zd/voYoNGIWbap1Sqm/TSZIycPYKa0wFRjwSPlI46cOEDFslX4ZcaCj7ZxZl6wY+8WbBWO2EjZizXaCc5YCXbs2Ls5X4wdtUbN3oM72LJzI08CAzA0MKRB3cZ079QHb8+8aQooIyMjoyveueu5zKdHMe8SKJVKnhOudVyUNDwnklJ+ZbJsX/LPIo6dOkRpqlJN04QyQnWqaBpSgTrcun2Dn+dNzw/5Hw1h4SGYi1Y5jpuLVoSFhea5DrVaxaTvv2LW3OnEPI7DW+2LXbIrhw8dpN/Qz7h45Vyea5CRkZHJT2RjpxDyLDqKxX//ToeezWnSvhZfjOpN8aI+xBFNuBSYZV9JkgjgDmrS6d/ji8ztKSnJbN6xDg+pOE6CR2YVW0EQsBUcKSL6cfj4fqKeReTrtRVkLC2tSRGSchxPEZLypc3Kxu1rOXvhJOWpSTlq4iEUp5hQmuqapliobZk8fSzJKcl5rkNGRkYmv5CNnUJGwJOH9P6iM+s2rkb5zAinZE+iA2K4++AOBvqG3OES16TThEpPCJYCuMRRAnnAoD5Dsyxv3Lp7k5TUZJzx1HoeZzwRJZFL1y7k16UVeJo3bs0zwkiWErONJUpxPJciaN44b4tsSZLEpu3rcMQdOyFr7SSloMRHKk9yShKHju3NUx0yMjIy+Yls7BQiRFHk62ljkJIEaojN8BUq4iWUpBy1qEQ9NGo1fj6lSTdN5i5XuM81bDys+fm7eQzslbUSrUajBkCB9iDkl9vValXeXtRHRJvm7XFycOG68jRRUiiiJCJKIpFSCDeUZ/B086J5o1Z5qiE+IY6IqDDsJO1FIo0FUyyUNvjfv52nOmQKFv4BkZn/n8JT3QmRkckj5ADlQsSlq+cJCQ+iMvWzlde3FuxxlYoQFBzI7o1HUQgKBIWAnlL7V6RE0ZIoFUqeiWF4kL2Z3cv4Hz+fMtnG/pfA4Cds3rmeM+dOoFKpKOVbhs7tulO5QrX3uMqCi5mpOYvm/M3UmeO5efccSkEPkNBIGir6VWb6N7PzvLjgy7+nBnWO+2hQo6cn1/spLPgHRHIyKQLRXSJZcY1GVnF4mMrFGGU+LWRjpxBx+95NjJTGWGq038gccCUo+SHBIYEUK1LitXPZ2thRv04TTp86ga3oiKlgkTmWKqUQoLxDmRLlKF7U57XznLlwkknfj0Ep6WGvccUQJVcvXOXE2aP06/45X/Yf8e4XWoBxdHBiye+ruf/Qn+u3ryIgULFclTd+3rmFqakZpUqWJfxBEM6iZ7aO4XFSNImaOGpWrZMvego6Uc8j2bZrI8dOHSY1NZXixXzo1PYzqlWqqbXb+sfG7usPCVEkY1POhNIuF3E0NaO2/af1kvGxEBUZQ2xsAo5OtlhamupazieHbOwUIpQKBaIk5jgukjH2tvVxxg2fRMDjB1wMOYIDbphJliSTSJQiBCtLK777etZrj38RE803M8ZirbGnlFQts8ZPUU1pAnnAynVLKeVb9pNsU+FT3A+f4n46OXevrv2ZNH0MAdzGW/LL/NwTpXj8lZfxdPameuVaOtFWkLh99wajvh6MKk2FveiCEebcirnB6fPH6djmM8YNn/zRGjz+AZE8Togn1VkfG48YStvdpoqDJx4mxXQtrdBx7uxtfpr5DyeO3wDAwEBJ+w51+ea7/nh6OulY3aeDHLNTiKhSsQbpYlqOKeYRBGFv44C7m/ag4//FytKaZfPXMHjgCJROEkH691HZJdOre39WLt6Aq7Pba4/ftX8bapUGX6lylmKGgiDgJfhgpbBjw9Y1b3+BMm9F/dqNGDZoDE+5z1nlPm5I57jCCc5zECt7S36bubDQF4RMTUtl3JQRGKaZUFNsjp9QmeJCWSprGuJLRbbu2sDeQzt1LfO9eWnoiE4qGnnGyYaOjjh04CJtW44n8cUDVvzuyPFtbsycZM3ZU2do2mAET59ov1fLvDuyZ6cQ4edTmjK+5Xjw4AZGGhPMBSsgI0MnjCeEEcjIzmNzjNPRhqmpGb26DqBX1wHvrOfmnWtYS3boC9qLGdqLLty8c+2d55V5M7269qdOjfrs2LuFgKePMDYyol6tRjSs2xRDA8M3T/CJc+TEAeIS4qhJsyzfT0EQcKUIz4lg3eZVtGraTocqPww3N2sE64zYLdnQyX9UKjUjhv5K47pGbFvhjL5+hpewTnVjenU2p0bLMCZ//SdrN3yvY6WfBrKxU4gQBIEfv/2NERM+50LwYWwEBwxFY+KVMSRp4mnXohOfdeyVj3oUSEg5jkuICILsfMwrPN29GfnlOF3LKJBcu3UFS6UNJqKZ1nEHyZU7Ty+RnJIsVwmXeS8O7L9AREQsP/7rkWnovMTBTo/xwywYMfk8EeHRODnLAeMfimzsFDLsbO1ZuXgDx04e4uCxfSQkxFHerSztWnWmrF/5fI1BqFS+KucuniJNSs3ssv4SSZKIUoZSuXzVfNMjI/MSAQFea4hL/+0nU9i5fy+IhQs2s3vnaZKT0yjp68GAQW3p0aspeno5LwcHPAzF0kKPsn7aPal1qxsjihJPn0bIxk4uIBs7hZCC0iW6VdN2LF+1mDtpFykjVs9cLhAlkQBuE6+JoXvnPjrVKFM4qVSuCrsPbCOJBEwF82zjUUIoPkX9MJa9OoWaE8eu0a3LFGytBb7sZYqDnRFHTkcyavhc9u45w+q109DX1/6YtbA0ISlZQ0ysBmur7EZRSHjGEqO5ufwdyw3kNQIZnWFhbsGvPywgxSCRM4p93JIu4C9d4ZxyP4E8YNTg8VSSPTsyOqBB3SbYWtvhr7hMupSauV2SJAKlBzyXwuneubcOFcromqSkFPr1nk6dagbcO+3OD5PsGPm5NTv+cWbXahcOH7zEnwu35Xh8y1Y1AYGla+KyjUmSxMIVcZQo4YpfKa+8u4hChOzZkdEp5ctUYtPK3ezYu4UzF06iSk+nWqlWdGz9Wb7VnpGR+V8MDQyZM3MhIyd+yZnE/dhJzuhjQKzyGYmaeHp26UfTBi11LVNGh2zZfJzY2CQWz/bC2Dir36BFI1O6dzBn6ZLtDBvZCYUiu1/B0cmGgZ+3ZerPOzA0EBjUyxJTEwURUWqmz3nB7oNJ/P3PqLcOLbjr/5SD+y+SrlJRrlxxGjWpVOizKv8/srEjo3NsbewY0OtLBvT6UtdSZGQy8Snmy/rl29m1fxvH/ysqWLNYbTq26Uq50hV1Le+9SExKIDg0iGcREdiIdjk0e5F5G65deUDZUsZ4uWuvNt62mSmrN4UT/TwOewdrrftMnzmIxIQkxk47xLezY3C01ycwJA0DA33mzBtBx87136gjNjaRLwfN4sC+S5iaKDE2VvA8WoWXtwN//zOVipVeX9i1sCAbOzIyMjI5YG1lQ59uA+nTbaCupXwQcfGxLFw2lwNH9pCuSgfA5l9nmnzZk6L9Ld5wtIw29A30SE6WkCRJq/clMUn8b7/sxlBsTAJz52xg9T97efEiEUEAN3dXylUowbDqfnTsXB8rK+2ZgP8fURTp3nkK9+4+YPVCRzq3NkdfHy5dT2P01Gg6tJnAsVOLKFLU9cMv+CNHNnZkPlpexERz4cpZ0tLSKF6kBH4ly3y0FW3zAlEUuXT1PEdPHSQpOQkPNy/aNO+As6OLrqXJ5CMJifEMHt2XsLBw3MXi2OKEinTCop6yYfqvKOMbUGdmdV3L/Oho3LgKSxbv4PyVVGpUztrTTpIkVm9OpEpVn2xGS8yLeFo1+4rgoDAG9jCjVlVnQsPVLFkdxbYtoXTp2uCtDB2Ao4evcO6cP4c2udKw9qtA5qoVjNi/zgm/OiEsXLCFOfNGfvgFf+QIkiTlnF9ZSIiPj8fS0pLD285iavp2XzIZ3aFSqZj352x27t2CWvOqoWUx7xJ8N/FHOdaHjDf5sVOGc+feTcyVlhhIRiQQi0pKZ9igMfTs0k/XEmXyib9WLODfDSupLDbI0sMO4LHkzxPBn2u3/sHL21lHCj9ONBoNdap/SWpSJNv/caSUT0YKeVqayA9zX/Dj7zGsWvstbdvVznLc2NHz2bppP6d2uOJb4lXByvR0iY4Dwrl0Q8GdB+swNNRebPX/M/jz2dy6epobR920vuhN/ek5i/5J42no9g+72AJMfHwSHs4diIuLw8IiZy+lnI0l89Ex/Zdv2L57M16aktSlDY3oRHlqExX4jCFj+xMaHqJriTpn8vRxPHrwgIrUpaqmMRWkOtQSW+AhFeePpb9x+Ph+XUuUyQckSWL7ns04ih7ZDB0AT0qgrzBgzSr5+/CuKJVK1m+ZiULfhrL1g6jbLpTOA8PwqBTEj7/HMG36wGyGTlJSChvWHWL4AIsshg6AgYHAnGl2PH+ewK4dZ95KQ2xsIp5uyhw92h5u+sTGJiP7NORlrAJP1PNINm1fy/7De0hIjMfZ0YV2rTrRvmVnjIyM3zzBJ8a9B/4cPr4fP6rgIrzq4WWHE5aiDRdSD7N6/XK+HvOdDlXqFv/7t7l68yJlqYGN4JC5XSnoUUwqQ5KQwMq1S2lUr5m87PcePHr8gO17NxMcEoiZmTmN6jalbs0G6Olljc24dvMym3eu547/TZRKPWpVr0vndt3wcPPKN62pqSnExsfgSnGt40pBDzPJiqdPIvJN06eEh4cjpy8sZce2k+zacYb4lFS6dvek34CWlPDxyLZ/cFAUiYlpNK5rr3U+n2IGeLobctf/6Vud39vbma0br5CeLmFgkP23fP5KKl7eDvLvHNnYKdA8CQxgyFf9SUlKxkF0xxon4kNesOCvORw8so8FvyzF1MRU1zLzlX1HdmGsNMVJ455tTF8wwFnjyf4juxk/ckqBTLu8ffcGazev4vzF06g1akoW96NL+x40rt88125Ip8+fwEhpjL0me2yOIAg4S57cenqeZ88jcbCXuyq/LZIksWj5PNZsXIGx0hQzjRXpilSOnjxIMe8S/P7TX9hYZ1S6Xb56MctWL8ZMaYmtxhENGnbu2sb2PZuY9d1calWrmy+aDQwM0dfTJ1WdlOM1pSuTsbQqXPeR3MTIyIDPujfms+6N37ivsUnGUtezaI3W8fR0idg4TeZ+b6JPvxYsXriNBctjGTska8bXjTtprN+eyISvO73VXJ868jJWAUWSJL6ZMQ4xCaqLTSkpVMBTKEEZqlNZasCjgAcsWjZX1zLzndjYGIwlUxQ59MwyxZy09DRS01K1juuSfYd38cXoPlw6exGXtCJ4q/0Iux/Bt7Mm8vO86bnmak5PT0NP0M/ReNInw32elp6eK+crLOzYu4U1G1dQnDLU0DSjnFCDKlIDqtCAkMBgJk8fC8C5S6dZtnoxRSlFNU1jigtlKSlUoKbYHGuNA9/MGMuLmOh80axUKqlcsR5hikA0kjrb+HPCSVQn0qlLg3zRU9jx8HCkTBkvlq6J1/p737Qrgbh4Na1a13yr+Xz9vBg5ugsTpj+nz/AIjpxK5tL1VKb9Ek2DjmGU9PXmiyHtc/kqPk5kY6eAcv3WFZ4EBVBcLIvB//SNshCscReLsefgTpKSEnWkUDc42DuSJMQjStrfjBKIxdTYDOMCtsQXGRXBzDnf4Sx5Uk3TGG/BFw+hOBWkOvhRmR37tnDkxIFcOVfxIj4kquNJkhK0jj8nHFMTMxxlr85bI4oiazb8jZPgjqfgk8XYthRsKSFW4Madq/jfv82Grf9iqbDFi5JZDE6loMRXqoRGpWHnvi35pr1Mndao9VRcV5whXnoBgEbSECY9xV95iQYNK1GjZul801OYEQSBsRN6ceBYEmO/e05sXMZ9TBQltu1NZPikaFq2ro6vn9dbz/n9D4P4de5wTl8xomnXUKq3CGbukiS6dGvBjj2/YmZWsO6FukJexiqg+N+/jb7CAGtR+9quPS48TvfnSVAApX3L5bM63dGqaXvWbFxBMAF4kjXrKlVKJkIRRIcWXbRWLNUlO/ZtQSEpKEG5bB4XF8GLSCGITdvX0bh+8w8+V/06jbFc9DMPE29QRqqBUni1nBcvxRCueEqXlj0wMHhztsfHRHJKMtt2b2THni1ERIVjYW5Jy6Zt6Nq+J3a22n9Hb0toeAihESGUp5bW7p/2OGOoNOLcpdPcuH0VN7GYVs+avmCAlWTP9VtX3+n8gcFP2LprA1euXUIQBCpVqEqntp/h7ur5xmPtHd0ZMmcuq2ZM42LUUYyURqhFNWpRTZtWtVm0ZJwc05GPtO9Yl58ihjBl0l8s/TeB0iUNCY/UEByaRuMmlfhr2dfvNJ8gCAz6oi39B7biwf1g0tJUFC3mmqWnlkajQaMRMdBS86ewIBs7BRSlUokoiUhI/3VgzooGzX/7Fa4/oZeHN13b92Tj9rWkSEm44o0+BkQTQaDyARZWlvTq2l/XMrPhf/82lqIteoL2m42t6MzdB3dy5VyGBoZM/2Y246YM56J0GGeNJ4YYE8MzIoUQShT1YWDvIblyroJCfEI8Q8cO4ElgAI644i35khKTxIZNa9i9fzuLf1uBp7v3e8+vVqsAUOZwyxQEAQVK1CrVf/3SX7ckqb0IXU4cOLqHGbOnoIcBtmKGN2578GY271zPtIk/vpWB7F26DN/uW0vs9ZWIQXoYGhrQomV1ihV3e2sdMrnH4KEd6NCxHmvXHCQgIJRKNUzo2Lk+lauUfG/DU6lUZvMInT51kwXzNnDo4GVEUcLX151BX7anb/+Wr+3I/ilSuJ6UHwkPA+6DJKGR1EQSgjPZo/rDCcTawoZi3oWvpsyoweOxtbHj340rCUkMAEBAoGalOowfOQVbGzsdK8yOvp4+oiDmOK5GjZ5e7v0cq1aszt9/rGX1hr85duoQKrUKe1tHBrUdwmfte35y3brn//ULwUGBVJUaYiZYZnpfvMSSXE88zbczJ7Jy8Yb3fpC4OLthamLG8+RwrMnuJYqXYkjRJOHrU5pKFapx89INvDQ+2c6XLqXxQnhGpfLd3+q8TwIDmDF7Cg6iG75URPGfl06j0XBPuMK0nyZRvKjPWxlyCqWSqo18qG1f7a3OLZO3ODrZMGZctzybf/U/+xk5bC5lSxkxZ5ot5uYK9h6OYfxXf3Di2FVWrC6YSRx5hWzsFCDuPfDnp3nTuf/IP3Pbfa5hLJlgJWQ8wCVJIoynhPKEoV1Goa9f+NySCoWCPt0G8lnHXtz2v0F6ehreXsVwcii4RdFqVq3DmfMnSCEJYyFr5oskSUQpQ3I9Q6dYkRJ8P+knvpv4I2q1+pNbtnpJXHwsB4/uxVMsmWHo/D8MBSOKakpx/fEZ7ty7+d5LvoYGhrRv1ZkNW/7FXnTFSrDNHFNLKh4obuBg40TNanUwMzXj9PnjPOIWRaXSmfE9aknFHcVFDA0MadO8w1udd/PO9egLhvhSKUuc0Mv4nxfCM7bu2sCYoe+29CHzaRMa+owxI+cxsIcFi2fbo1BkGN39u1my80AinQacZfU/++k3oJWOleYfsrFTQHj05AFDx/ZHX2VEOWpihR2JxHGL81zmOBZYYyyZkqiMI0mTQJvmHQt9FVxDA0Mqla+qaxlvRbNGrVj2zyJuJ1ygtFgt0+BRSyoeCDdIFhPo1ql3npxboVB8soYOQMDTRxmeK7Qbu7Y4oRSU3L1/562MnYiocF7ERGNnY5clNX9Q7yHcunODq3dPYI8LlpIdaSQTqQxGYaDg12+XoKfUo2K5KoweMoF5i2cTpQzFRuOABg3RinD09PX4dcYfWFpYvdW1XbpyHjuNs9bsQ4WgxE505uKV8281l0zhYdXKfRgZCvzynW2mofOSts3MaN3ElOVLdxYqY0enUZyzZs2iSpUqmJub4+DgQPv27bl//36WfVJTUxk2bBi2traYmZnRqVMnIiMjs+wTFBREq1atMDExwcHBgfHjx6NWZ0+zLMj8uXw+SpU+FcV62Asu6AsGWAv21KYV9jiTIMXi4GdHg8aNWTJvNZPGfFfggnBlcsbE2IR5P/2J0lzgLPu5ykmuS2c4o9hLpCKEbyfMpFTJMrqW+VHy0hX/Mo7tfxHRIEoiyjcsE97yv8HgMf3o0KsZA0f0oF3Ppgwf/zn3HmR4Wo2MjJk/ewmjBo/H2M2AJ3p3iDGLpHXr9qz6c1OWv99nHXqxavEmmjZrgZGXPlbFzOjdYwDrV+ykYrkqb31tbypHIGTs9NbzyRQObt96TK2qRliYa1+matHIhNu3niKKOS+tf2ro1LNz4sQJhg0bRpUqVVCr1UyePJmmTZvi7++PqWnGm++YMWPYs2cPmzZtwtLSkuHDh9OxY0fOnMkop63RaGjVqhVOTk6cPXuW8PBw+vTpg76+Pj/++KMuL++tiYl9wdmLp/ChAnpC1j+JQlDgK1XmtLCXpg1b0rlt3q3xyuQtxYv6sGnVHg4e3cvZi6dQqdLxK9mWdi06ycX9PoCSxf2wMLMkPDEQC6yzjUcQDEDVijVynOPqjUuMnjQYE9Gc0lTFFAsSiePhrQcMHtOXhb8up5RvWQwNDOnaoSddO/R8o67iRX34evS3739hQKUKVTkYtQ9RI2bz7oiSyHNlBC3Lt/6gc8h8ehga6vMsNGcjODZOg6GhXqHKwtOpsbN/f9Z+LCtXrsTBwYErV65Qt25d4uLiWL58OWvXrqVhw4YArFixAl9fX86fP0/16tU5ePAg/v7+HD58GEdHR8qXL8+MGTOYOHEi06ZN+yjc9y9iopGQMMNS67iBYIix0oRnzyO1jst8PJgYm9C+VWfat+qsaymfDIYGhnTt2JPlqxZjLlnhjGfmTfyFFEWA4jZ1qzfEzSV71W3I8J78NHc65horyku1M4OAzbHCQXTjKieZ/fsP/PPnxny7ppd0btuNnfu2cJ/r+EjlMw0eURK5zzXSxBQ6yS9AMv9Di5Y1+HzACW7fS6N0yazVmNVqiX82JtG8RfVCZewUqHWQuLg4AGxsbAC4cuUKKpWKxo1fleEuWbIkHh4enDt3DoBz585RpkwZHB0dM/dp1qwZ8fHx3LmjPZU3LS2N+Pj4LP/pEmsrGwQEktCuQyWlk6pJxta64GUZycgUBPp1/5wWTdrgz2XOKw9yUzrPReEoVzlJyZJ+TBk/Pcdjb965RnBYIF6Sb6ah8xKloMRL9OHB43s8CLiX15eRjWJFSvD16O8IE55wTnmA+9J17kvXOac8QJjwlG/GTqeIV7F81yVTsGnbvjZFijrReWAkN+6kZW5/Hq2h38hIHj1JZ/iowvXCVWAClEVRZPTo0dSqVYvSpTOqeUZERGBgYICVlVWWfR0dHYmIiMjc5/8bOi/HX45pY9asWXz//fe5fAXvj421LVUr1cT/2h2cRHeU/7OUFcQDBIWQKwXnPkVS01I5cuIA5y+dQa1R4edThtbN2mNtZaNraTL5hFKpZMq4GbRv1YVd+7cSFh6KlZU1zRu1pkaV2q9NsQ0Jy1jmssJW67jlf9vDwkMoUbRk7ot/A21bdMS3RCk27VjHlWsXAWhasTmd23WnWJHCV3pC5s0YGhqwZftPdG4/iYqNg6hQ1hgLM4HzV1IRBCVL/55ESko6vbt/z5XL/ujpKWjQqCpfDmmPXylvJEni6pX7rPv3EOHh0Tg52dC9ZxMqVX7/OkC6psAYO8OGDeP27ducPn06z881adIkvvrqq8x/x8fH4+6u3cWdXwwZMIIvR/flGqfwFv2wIiPTI5gAgnnEwO6DM5sMyrwi4MlDRn89mOcxz7FW2KGQFJw6c4Kl/yzi+0mzaFCnia4lyuQTgiBQxq8cZfzeLb3cwtwCgBSSMcU823gqyQCYmWYfyy+KF/Vh8lfTdHZ+mY8P7yIunL+ynD27zrJ/33nS01VMblGcnr2bsmzpLvr3mUkpHyP6dTEmNU3Dhh1HWLvmIH8uncCBfefZuOEYnu6G+BbX4/B+NcuX7qZzl/osXjoBff0CYzq8NQVC8fDhw9m9ezcnT57Eze1VRU8nJyfS09OJjY3N4t2JjIzEyckpc5+LFy9mme9lttbLff4XQ0NDDA3frqtsfuFT3I/5s5cy67dpXAs+lbnd1NiMYT1H07NLwasKrGuSU5IZOfFL1PEaatIUEynjYaSS0rmnucrUmRNY/sdafIr56lipTEGmSsUamJmYE5z8kJJUzDYexENsrGwpXyb7mIxMfiFJEmfP3OLYkStoNCKVqpSkeYvqr62ErK+vR/uOdWnf8VUNr2NHrvDTzNXMmGjLpFHWmZ6aHydL9BsVyecDfkKphBW/O9KzkzlKpYBGI7FuWwKDvjqBg6MNP/48OM+vN7fRqbEjSRIjRoxg27ZtHD9+HG/vrFVAK1WqhL6+PkeOHKFTp4w29ffv3ycoKIgaNTIyK2rUqMHMmTOJiorCwcEBgEOHDmFhYYGfn1/+XtAHUrZUedYu28adezcJDg3C1MSMqhWrY1TAmloWFPYf2U1MbDQ1aZ6lUJ++YEApqSoXFIdYv3UN302YqUOVMgUdI0MjBvQezPy/fkEp6eFBCQwFI1KlFJ5yjwiC+Lrft+jpFb4CnjK5jyiKpKWpMDLKSJ45eeI627acID4+iSJFXendtzmenllf1ENDn9G7+3dcvfIIR3sDDA0F5s5Jw8PDjlVrp1G+wtsvZ/65eBvlyxhnMXQA9PUFfp5qy6YdCXw9woY+XS0yx5RKgV6dLQh4quKXRbuYMKkXVlZmH/hJ5C86NXaGDRvG2rVr2bFjB+bm5pkxNpaWlhgbG2NpacnAgQP56quvsLGxwcLCghEjRlCjRg2qV68OQNOmTfHz86N3797Mnj2biIgIpkyZwrBhwwqc9+ZtEASB0r7lClVzz/fl7PmT2AgOGGOabUwhKHDQuHH67PH8Fybz0dGtYy9UqnSWr15MkOohhgoj0jSpGBgYMnrgBNq1LFzBnDK5T8CjUOb9toEtm46SnJyOnZ05JqZGBAU+o5i3IW4uehw5eIY5s9cx5bt+jB2f0VIkNTWdjm0mkJz4jP3rXWhc1wRBELh6M5WhXz+nQ5uJnDz3F+7uDm+l48K524z90kRr7M2VG2loROjXzULLkdC/mwXT57zg1MnrtGlb+/0/DB2gU2Nn8eLFANSvXz/L9hUrVtCvXz8A5s6di0KhoFOnTqSlpdGsWTMWLVqUua9SqWT37t0MGTKEGjVqYGpqSt++fZk+PefsC5lPg3RVOgpJT2sXagA99FH918BRRuZ1CIJAn24Dad+qC8dOHST6RTT2dg40rNMEU9Pce4ONi49l94HtnDp3nPT0dHx9StGxdVeKehfPtXP8f3Zff0iIIplkdRSl9S8CH9fb+KfCtasPaN96POamGsYPNcPbQ5/vf43meXQie/51oVmDDOMjKVnkp/kvmDFtBa6u9nTr0ZhtW05w/34o1496UMb31Qt8xbJG7FvrTPEaQSxZvJ0ZP37xVlqUSgUqtfYaPGnpGdstzbUnaltZZmxPT/v47quC9KYSnYWA+Ph4LC0tObztbK7e2GTyloXL5rJx81pqiS2yZbABXBNO4VrShb/m/aMDdTKfMunp6ew+uJ3tuzYREh6MmYkZzRq3oku77jkWiLz74A6jvx5MYlIidpITSvSIVT4jRZPMyC/G0b1zn3fWEREVzrWblxFFkTJ+5fBw8wLAPyCSxwnxhCiSsakSQ2m7UBxNzeQmoDpAFEWqVuiPtXksBzc4Y2Gu5KZ/GhUaBfHvYie6tc8e+N6xfzj3n1px7vJyunWeSmr8bY5ucdU6/6gpUew4qMete+veSs/AvjO5de0Cd066ZWslcfFqCjVahbDqD0d6dsru3Vm7NZ7ewyK5eHUZJXyyN6jWBfHxSXg4dyAuLg4LC+0eKSggAcoyBZ+ExHjuPvAHSaJkiVKZGSy6pH2rLvy7aSUPuYWPVD6LWzZcCiRaimRUu69eM4OMzLuTmprCmMlDuXH7KvaCC65SUVJTk9m4eS07925l4a/Ls6WEJ6ckM2bSEBTJetSSWmAoGAEgakQCuM38Jb9SxKsY1SrXfCsNiUkJzPrte46dPpSlpUTVijX5rOtIXij0CXJPws4llkaecXiYeuJhItfj0QUnj1/n0aNwTmx3y2zfsPtgEpYWCjq10v5yPaCHOe36hPD0STjx8Yl4O+UchOzmrEdCfPJb6xk8rCNNG55k5DfPmDPNDkPDDG9NTKyGKT/HYGCg4NvZsdSvaYKr8ysTISxCzXezY6lbr2yBMXTeBdnYkXktqakpLFj6G7v3byNdlQ6Agb4BrZq2Y8QXYzE2NsnV86nVKk6cPcbZCydRqVX4FPOlVdN2WFlmbwPg6uzG+BFTmD1/BvHKFzhq3FGix3NFOM+lcFo3bS/XJpLJdZatXsxt/5tUoh5W2GUuoxYR/biRfIavvx/DxhW7svSuO3h0L/EJcdSkeaahAxmxZcWkMsQqolm7+Z+3MnbUahWjvx7Mw4cP8JHK44QHAgJRhHLj+nXuBY2mxc/f07TsYxxNzfAwtZUNHR1y69ZjzEyV1Kr66u+ekipibqZAX1/7GryNVYZxk5KSRrHiHpw8EoBGI6FUZt//xLlUihZ3y7Y9J6pU9WXeglGMGfk7m3cl06KRESmpEnsOp6BU6rNoyUSmTVlC2QbB9PvMjFIlDfC/n87KDYmYmFowf9HYd/wECgaysSOTI2q1irFThnPz9jU8RB+ccAMEIlXB7N63nceBASz4eSn6+rmTpRISFszor78kNCIES6UNSkmPI8cPsmTlH0z7WnvNnA6tu+Dp7sXaTf9w/spZRFFDiSK+DOkwjBaN23y0BbBkCiapaals37MZV9EbKyFrRXMDwZDiYlkuhx/n4tVzVK9cK3Ps0rXzWAl2WoPpBUHAUXTjyvWLSJL0xu/ssVOHuXP/FpWpn0WDM55YiDZciD5Emv8NHBs5y8tWBQAjIwPS0kWSUyRMTTL+tuVKGxLye4zWdg4A+48mY25uhKeXE/0GtGT1P/tZ+HcsIz/P+tJ35FQy+48mMX9hm3fS1Ld/S2rULM3ypbu5cukOevp6jB5bhT59W+DkbEudOuVYuGALa9bs5/nzKGxtzejVtz3DRnTCyfnjrPcmGzsyOXL01CGu3rxERepiI7yK9PfGFyvRjiu3T3DkxAGaN/7wRoTp6emMnPAFCdEJVKMx5qJVxnYpjQfq60ydOYGl89fgW6JUtmMrlqtCxXJVkCQJSZKydYNPSIxn94EdHDl+gOTkJLy9i9K+VWcql68mG0My70RIaBBJyYn44qJ13BJbjJTG3Ll7M4uxI4oahNd05xFQIP73/X3Td3LvoV1YK+yxkrK3jzEVzLHHlQvb9zNohFybqyDQpFkVJoyFNZsT+LJPRv/Dds3McHFSMmbqM3aucsHY+NV349bdNP74O55uPVthampMpcolGTq8I2O+3cq5K2n06myOkaHA9n2JLF+bQKPGlejWo3FOp8+REj4e/PzrUCCjDMyZ07f49pslBASEYGFhRodO9bl5918MDPRfW8vnY6FA9caSKVjs2rcNG4VDFkPnJdaCPbYKR3bu25or5zp26hDhUaGU1lTDXLDK3G4gGOInVcFYMGXtptcHGguCkM3QCQx+Qo+BHfhjyRye3Y9GFQyXzlxk5MQv+Pn3Gcjx+TLvwsu2EyJijvuIkpitPUVp33LE8px0KU3rMc8VYfj5lM72/dVGdPQzTMScEylMJXMSomPeOI9M/uDl5UynzvUY/3002/clIooS+voCy+c6cuZiCr61A/lp/gvWbI5nyIRIarYOxcPLnSnf9sucY+ZPX/Lb7yO5ctuMtr3DaNo1lM17JEZ91YN/N3z/QRWNRVFk1PC5tG4+jhtXzlGuRCR6mgeMGj6XujW+JDLyRS58CrpH9uzI5EhEZDimokWOqd1moiURkeG5cq5T549jpbDDTMre+V0hKHDUuHPq7LF3mlOj0TBuygjS4lXUlJpjJGTEF0kaiTCesmPvZooXKSF3jZZ5azzcvLC3dSQiOhAbsr8EPCecdDGN6pWz1iBp3aw9S/9ZxF3VFUpL1VD+v4ajIVIA0VIkxc2LcfXmZSqUqfRa746jgxO3A29DDnZ6ghCHtZP9+12gTJ7w+8IxxMcn0mnAZYp4GuLlocdN/3TS0sHUwoXpv4WRlqbG2dmaEaO7M3xkZ8zNX8VDCoLAgEGt6TegJUFBkWjUIh6ejrnStmHxwm2s/mc/S+Y4MKC7ReZ37+6DdFr1DKdPj2kcPv7HR+8Flz07MjliY21DipCU43iykJhr/brS09PQE3P+4epjQLpa9U6emPOXzxASHkRJTYVMQwcybhyugjdOgjvrNq9CFHN+S5eR+f8olUp6dOlDGIGESAFZvo/xUgz3ldcp61eBkiWyVm+3tLBi1rdziFU+55zyAA+kGzyW/LkgHeYe1zDAiBtXrjNs3AAGj+lHXHxsjhpaN+9ArBhNtJS90XG8FMNzKYxqHVvm2jXLfDimpsZs2DKTfYd+o0HTJlg6VKZX345cvv43568sI/z5bsKf78L/4XomfdMni6Hz/1EoFHh5OVO0mGuuGDoajYY/F26mT1cLBvawzGLQ+JYwYPFsO65cfsiF8/4ffC5dI3t2ZHKkRZO2/Ow/g0TiMBOyelwSpTieE06/prkTF1CsiA/nL5xFLarR01IzJ1qIpKhXsXd6u7hy4yKmSnMsNNq7nztI7tyMOEt4ZCj3Ht7l0eMHGBoaUqd6/Twr8ibz8dO1fU+CQgLZtnsjwcpHmGusSFOkEiM9o6hbcX78do7W42pUrcPqvzaxacc6jhw/QFx8LAYYUYoqOOEBIkQTwd17V5jw7Sj+nLtS6/e9dvV6VK1Yg6vXzuMhlcAJDxQoiCSEp4r7uBYpTtU2zYDLefxJyLwLgiBQo2ZpatQsnW1MoVBgbJz/Ff8fB4QRHBxN9w7aY9Ca1DPBzlaf48euUr1G9njJjwnZ2JHJkeaNWrFp+1quB5+miFgaRzLSG6MIIUB5B08Xb1o0frcsgJxo16IT/6xbyiNu4iNVyHKTfyaF8YxwBrab+m6TSgBCjgbSy62DRvQiNj4GE6UZKimdv1YsoGbVukyf9JNcZFImGwqFggkjp9CySRt27N1CcEgQFhYWNK7fnPq1GmNgYJDjsZ7u3owbPpmngY95dCuAymL9LN9PO5zxFStx3f8MN25fpXyZStnmUCqV/Pz97/yxZA679m/jsSrjrVupUOJbriY9pk/CwNgo23EyMv+LRpPh1TbIIQVeEEBPKWTu9zEjGzsyOWJkZMwfvyxjxuwpnLt8Gn8uZY5VK1+Lbyf8kGt1dhwdnJgwcgo/zZtOgiIWR9EDPfSIFiKIIpR6tRrSulmHd5qzXOmKrNuyinhisBCy1+kJ5QkCAspEA6rTBDPRElESiSKEy5fPM3HaaBbMXvrRr1XL5A3v28MuKSmRKzcu4ov22BxbnDBRmnHizFGtxg5kNC8dN+Ibvug3gjt3byBKEr4lSnE28AXGZuaA+p11yRQ+ihR1wc7OnG17k6hXM/u9/NzlVCKi0qle/ZVXR6PRcOzIVQICQrGwMKVFy+pYWWevAl3QkI0dmddibWXDbz8uIijkKddvXUGSJMqXqYSnu/ebD35H2rXsjKuzO2s2ruTi1bNIkoSHixdjO0yiXavO2TJc3kSt6nVxsnfmfvQ1yok1Mfh/xdwipWCeE46JYEZZsWZmwKhCUOCEB0pRjys3znL91hUqlK2cq9cpU7hJS8/IyNJH+7KFIAgYYEhqWuob57Iwt6BG1TqvNgR+GpkzMvmDgYE+/Qe15fff1tGqiQlN6r2qA/XsuZphk6IpVsyZBo0qAnDsyBVGjfiNoMBnGBgoSE8XMTbWZ+jwznzzbd+3yibUFbKxI/NWeLh5ZfbdyUsqV6hG5QrVUGvUaDQaDA3efx1bT6nHLzMWMHz8IM4m7cdedMUQI2IV0cRKzxEEARfJO0tmzEvscMZUac7hEwdkY+ctCAx+QlBIIGamZpQpVR49pXxryQlLCyssza14kRCJg5Z6PWlSKvFiDEU8i+pAnUx+ERuTwL9rDnLowAXS0tKpULEkAwa1ptg7VEPODcZN6M71q/dp3u0yjeuaUqeaIcFhatZvT8LYxJQde6ahUCi4cP4On3WeQt3qRmz8050q5Y2IfKZm4d9x/PjrOtLTVW/djFQXFFwzTKZQo6fU+yBD5yXFipRg7bJt9Ov1BUbueiTbxuFTvgTff/0TkiRhhLHW4wRBwFAyJikp8YM1fMo8evyAwWP60m1gOyZ8N5Kh4wbQoUcztu/ZrGtpBRalUkmH1l2IUAQRL2WthyNJEg+Fm+jr6+dKsU6Zgsn1aw+oVK4v06YuwUz/IV6OwWxct4sqFQaybMnOfNViaGjAuk0z+HPpBJJUniz8R83xC6YMGdGNU+f+wq9Uhhd/5vQVlPYxYNdqZ6qUz/CSO9rrMX2iLTMm2rJ44VbCw6PzVfu7IL9+yXzy2FjbMrDXYAb2Gpy5TZIk5i2aTWx8dEYmzP+gltQkCLG4ubjnp9SPiieBAXw5pi/KNH3KUB0rbEklheCYR/z8+3SSU5Lo0bmvrmUWSPp0G8j5y2e5GnASJ9EDGxxIJ5VwRSDxUgzTxs7C3Ozdmu3uvv6QEEUyyeooSutfBOTg+oJIQkIyXTpMpqinyNa/vXB2zHgMp6WJTJwRzbgxf+BT0pM6dd89Hux90dNT0q1H4xwrMYeHR3PyxE1WznfEwCB7nNnQ/pb8MC+GbVtOMHR4x7yW+17Inh2ZQokgCLRr3ZkIRRCJUly28afcRS2paN383YKiCxN/rliAkKakklgPR8ENQ8EYS8GG0kJVPCjOn38vIC4++2crA8bGJiz8dTm9uw8g0eIFNznHPa7hU96HP35ZTtMGb18nxz8gkt3XH5LqrI9NlRhKu1ykioOn3BergLJpw1GioxPY8JdDpqEDYGioYO4MO8qWMmbRH1t0qDA7L6LjASheRHsfREsLJY72+kQ/L7i/d9mzI1No6dWlHyfPHOVq8ElcxSLY4oiKdMKEpzwjjKEDRuPk4KxrmQWS2LgYTp07RgmpPHpC9hugFz6EaAI4fHyfXKE6B0yMTfii7zAG9hpMfEIcRoZG75zd6B8QycmkCER3CTuXWBp5xuFh6il3OdchkiRx7eoDLl28i56ekgYNK1KkqGvm+NEjV6hbwxgPt+y/G0EQ6NnRlO9+uZKfkt+Is7MtSqWCKzfSqF4p+9J/eKSa0PB03NwLbuVu2diRKbSYmprx59yV/LliAXsP7uRJ2l0APF28mNZrFs0atdKxwvwjPiGecxdPkZSShKebFxXKVn5tZkX0i+dIkoQ52dt7ABgIRhgrTYl6HplXkj8ZlEol1lbaC1++jpfLVjblTCjtchFHUzPZm6NjHgeE0uOzb7l3NxilEiQRBAWULlOMbTtnYWNriUajwcgw53IWRoYCarXmrZrC5hc2tha0bFWDeUsu06OjOdZWr5I6JEli5rwXGBjo06FTfd2JfAOysSNTqDE3s2D8iG8YNmgM4RGhGBgY4ubiXmBuMnmNRqPhr5V/sGHratJV6QgISEi4OrkxZfyMHOu8WFlm1C1KJhErsnffVknppGpS3ushLvP2lK/khWCtlg2dAsCzqBga1x9BbEwiRTz16NPVAktzBXuPJHPoxCOqVhyA/8P1VKniyy8/XyQmVpPFaHjJtn3JVKlassDdg779fgBNG16nVptQvh5hRZ3qxgSHqlmwPJatexKZPWcYVlYFN05MjtmRkSFjSaGod3HcXT0K3E0mL/n9r19Ys+FvXFVFqUNrGtKRytQnOSqNUV9/yf2H2nvi2NrYUaVCdUIUAWgkTbbxYB6BINGkfou8vgQZmQLB7/M2ERubSJe2Zvif8mLqV7aM/Nya/etdWfunE9HRCUya+Ce9+jQHlAye8Iz09Ky9/v5aFcfxM0l8MbjgxQoWL+HO/sO/4+LhR/9RkRSr9pQGHUO46m/Cn0sn8MXgdrqW+FoE6V06K36ixMfHY2lpyeFtZ+X2ADKFhvCIUDr1aUkxyuAplMgyppE0XFYcpWzlcvz6wx9aj79z7xZDvuqPmcaSIpIfVtiRRgrBPCKQh/T+bABDB47Kj0splOy+/hC7Kg4I1mqKWZ2WPTs6xtu9I8mJSQRf88bWJrvHpnWvUM5fFXgSso3du87Qv/cPODko6d7BFHNTBbsPp3DhSjJfDG7Hz78OLdAvXU+fhvP0cTgWlqaUr1Bcp8UE4+OT8HDuQFxcHBYWOWcwystYMjKFlEPH96On0MNNLJJtTCkocRWLcvbiKeLi47C0yB6bU6pkGX7/6U9mzvmOK+EnMrcbGRoz6LMh9O9RcAuMycjkNgnxydSpbqTV0AFo19yMfUei0Gg0tG5Ti+OnF/HX4m2s2nzuv6KCPqzd2J4WLasXaEMHwMvLGS+vjyt5QzZ2ZGQKKbFxMRgpTFBK2m8DJpghIRGfEKvV2AGoULYym1bu5tqtK4SEBmJiYkaNKrUxNTHVur+MzKeKqakRiUnZl3RfkpQkolAImV6QUqW9mb/wq/ySV+iRjR0ZmUKKg70jyZokVFI6+kL2Tt0JxKKn1MPGyva18wiCQMWylakot9WQKcQ0a1GdjeuPcu9hOiWLZ/09iaLEivXxVK7iU+C9Nm9LQkIyly/eRa3WULZcMRydCnYyghygLCNTSGnaoCWCAp5yL9uYSkonVPmYhnWbynFsMjJvwU+/DMXYWI9OA8J49CQ9c3tSssjIb55x5346U78boEOFuUN6uoqpk5fgV7wbHdpOokvHKZTy6cHAvjMLdFFB2diRkSmk2Fjb8kW/4QTygDvSReKkaFKlZMKlQK4ojqNnrOTzvsN0LVNG5qPAxsaCXft/IzRSSclagdRrH0yHfmE4l3nMX6vimTNvJHXqlde1zA9CkiQG9fuRvxZvZcQAY/xPefLkkhdzptly8thZ2rQYS0JCsq5lakVexpKR+QCeBj3h8PF9JCTG4+LsRvNGrbG0sNK1rLem92cDMDM15+/Vf3Ip5ljm9kplqjF+5GS5N5iMzDtQuXJJ7j/eyJp/9rNt60nCY9QM/LIMAz9vg6en01vNkZ6uYse2U6xfe5CoyGicnO3p2bs5rdvWQk9Pe/BzfnHyxHV27jjDhqVOdG5tnrl9+EArGtY2pnKzEFYu38OI0V10qFI7cuo5cuq5zLuTnp7Oj3OnceDIbgwUhhgpjEnUJKBUKhg5eDydP7IWCWqNmjv3bpGcnISHmxeuzm66liTzBuTU80+PuLgkunT4mosX7lOvpgl+JfS56a/izMVkatcpw4YtP2Bqmr1dQ37xxcCfuX31DDePu2mNPeozPILLty24cHVFvmmSU89lZPKQXxbM5PDRffhSEWfRE4WkJF1K47Hanzl//IiVhRWN6zfXtcy3Rk+pR7lSFXQtQ0bmoyY5OZX0NBWWVmbvFYj81ch5PLgXwOldbtSo/MqoOX42mXZ9/Jk0YbFOM7hCQyIpW0ovx2srX9qQnQej81nV2yHH7MjIvCMRUeHsObidolIZXIUiKIQM17KBYIgP5bEXnFm2ajGy01RGpnBw4tg1OrSZiIt9W7zcOlHWtwdzf11PWlr6mw/+j9DQZ2zbepIfvrbOYugA1K9pwpQxVmxYd1inQcD29tY8CMg5vf7+o3Ts7LWXqdA1srEjI/OOnDhzBAUKXPDKNiYIAq5SEQJDnhAY/DTfteUlcfFxrFy3lK792tC0Q216ft6JDdvWkJJSMAMSZWTyg9X/7Kd9m4kkvLjHop8dWPeXE41qqZg1cyVdO37z1gbP2dO3EEWJbu3NtY53a29OWpqaCxe0t3DJD7r1bMLVmykcOZX9Nx8cqmLdtiS69WimA2VvRjZ2ZGTekZSUZPQVBugJ2leBDcl4K0tOScpPWXlKZFQE/YZ+xrKVi1GHgUOSB0lBKcz/81e+GN2H+IR4XUuUkcl3IiNe8NWo3xnYw5Jze1z5so8lXduas3yuI/vXOXP2zC2W/LnzreZ66QlW5hCDrKcnZNlPFzRpWoU6dcvSaUAEi1bEEp+gIT1dYtOuBBp0DMfWzppBn7fRmb7XIRs7MjLviKe7N6maFBIl7e7kGJ6hVCg/qSDf73+eTHx0PNWlJpQSquAtlKQM1akiNSQoMIjfFs7StUQZmXzn39UH0NOT+HmqLQpF1jiWejVN6NrWlL+X7XiruapW80MQBDbvTtQ6vmV3Inp6CipV8vlg3e+LUqlk3aYZ1GtYjVFTnmNd4jHGno/o9kUErp7F2X1gLrZ28jKWjMwnQe3q9bG2tOGRcBtRErOMpUopBCsf0bBukwKdgp6QGM/uA9tZtX45+w7vIvk1S1GPnz7i2q3LFNWUxljI2gbCXLDCUyzB4eP7eRFTMAMTPzX8AyLZff0hQe5JBCmuYa6/Hw/T11e5lskb7tx+QtUKxlhZvnLHpKdLbN6dwI/zXgDw5HEkqalvXsry8namecuqTJkVg//9tCxj12+n8f2cGDp0rIuTs+7+1mq1hunf/c3e3efQ1wcbKz0EAUxMDOjWoxkeHo460/Ym5GwsGZl3RF9fn6njZzD+u5Fclo7hKnpjhClxRBOmfIK5lQXDPy+YPW8kSWLNxhUsX7WYdFU6BkpD0jRpGBvNZMQXY+nQOnt9jNt3bwJgj4vWOR1w5aF4k/sP/alRtU6e6i/s+AdEcjIpAtFdws9XQxmrODxMPfEwKaZraYUSYxNDnr949cKz+1AiX4yNIvKZBntbJXEJGgRg4tg/+GXuCAwM9F8734KFY2nXahzlGwXTtpkpfiUMuHk3nT2Hkihbrgi/zB2Zx1f0eqZOXsLypTv5aYotX/S2xNxMQVCIiu/nvGD4kDlYWJrStl1tnWrMCdnYkZF5D2pUrcPiOStZvvpPLl45i4SEob4hzRu3ZmCfIdjbOuhaolbWb13DouXz8KA4npTAUDQmhSSepN5j9vwZGBoa0rJJ2yzHKP8LIhARUWhxBouI/+0n307yCv+ASB4nxBOiSMamSgyl7UJxNDWTa+vomFZtarJm1QHOXU5Bo4FOA8Jp3tCUWZNt8fMxJCFR5O+1cXw98yBqjcjCP8e9dj47eysOHF3Aun8Pse7f/Vy6+QJnZxfmzGtOtx5NMDY2zKcry05kxAuW/rWD6RNsGDvEOnO7h5s+y35zIDxSw88zV9Kmba0C2f9LLiqIXFRQ5sOIT4gnKSkBaysbjIx0V/DrTaSmptD6s0ZYpzhSUshaU0eSJG5zAdFWxbY1+zMNHMhIte/Yuzk+UgXchCLZ5g2Q7hBu+JTdG47K3c7ziN3XH5LqrI/opKK0y0WqOMjenJyIj0/i9KmbpKWmU6q0NyV8PPLsXBqNhvq1hhATHYajvQASnN3jnhlM/JLF/8Qy/OtnXL25giJFXfNMT17y97LdTBi7gIhb3lhbZY+i3nskiTa9wjh/eSklfT3zTdfbFhWUY3ZkZD4QC3MLnJ1cC7ShA3D+8lmSUhLxoHi2MUEQ8KA4z6IjueV/PcuYk4MzDeo0IUBxmxjpWeZ2SZKIksIIFB7QoXUX2dDJQ9yKOODmZo2nvQ2OpmayoaMFtVrDtKnL8S32GT26fkf/PjOpWnEQbVqM5cnjsDw5p1KpZOO2WVhYO3HlRhpDB1hlM3QA+nW1wMJcj61bTuSJjvwgLjYRczOlVkMHwMM1w7MbH18ws1BlY0dGppAQn5CRPWaMdqPE6L/t2tLIJ435Dp8SvlzhBJeF49yRLnFJeZSbnKVm1doMGTAq74TLyLwFI4f9xh/zNzL6czMCLnrx4n4R/l3sRHjwA1o2HUNY2PM8Oa+zsy3/rPkOAC937Uu5xsYKnBz0iI3Rnmn1MVCkmCsxsepswdMvOX0hBYVCKLBByvIiu4xMIcHFKcN9Hkc0VthlG4/nRZb9/j9mpuYsnruC0+eOs/fQTv6vvfsOr/H8Hzj+PifjZO9NEkTMELHSoEZDrdq7oZRSSlFaalfValWNKqWK1qou1IjG1jZi16qRCBEkQXZkneT5/ZGvo/klvl/VJCfj87quXFfy3M95zue+Hed8zv3c4+HDh9R2qUmXDj1o2jAAtVq+Nwn9+fNcOJs3hrD6UyeGvfpk6nP/7pa0bmZK/TbRLPvsexZ8MgqAm5H3OHTwNFptLo2b1MKvYY1/9fyubg6YmBhx/FQGrZuZFSiPidNy41YmVao+22agpVHHTi/g6GjFtPnxfP+VS74erAcPc1j0RTIdO72g19li/40kO0JUEA19m+DqVInI+3/hqzRHrXqSoOQoWm6qr1CzWh2qVyv8jd/QwJDWLdrSukXbkgpZiGeyZVMIbi7GDO5bcMyGi5MhQwdYsGbTPt6fNoixb33KLzv/QKVSMDBQkZ2t0LhJDVavnfLc42ksLEzp2bs1n399hNf6WuHm8uSjVVEUPvjkIUZGhvTu+9Jz17G4xNx7yIb1e/nt6DkAmrWoz+DXO+Hmlv8LkbGxEUs+n8Brr35Iqx53eHuYNVU9jAg7nc6S1ck8yjRhzrwReqjBs5GvY0KUEagh7lcAADTWSURBVFlZWRw6FsLWn75l34HdpD36Z/fG1Wo1k8fPIFH9gDPqI8Qq0aQqSdxTojitPkKGQRrvjZ1WTNELUXxiY+Op5W1U6HgZAJ9axiQmPqJvjykcPRzGl4scSbruRVqkFzu+cSU5PoouHSdyPy7huWOYNnMIakMLAjrfYenqBM5dzGT3/jReGXiPNRuTmbdwFDY2pWsCzL7gMPzqvcayxZtwtLyBo+UNPl+yhUb1BxO893iB8zu/0oyfds5HZVSVoFExNOt8m/c+jKdh0xcIObS8VA++lp4dIcqAfQd3s3jFQpJTEjFQGZKjaDHRmDJs0EiC+gx55qme/o2bsWzhGr5Y8xkXrj55M2vo04QxIyZQu0bd4qqCEMXG2dmOsN+z0WqVQhOei1eyMDMz5sSJqxz6qTItA55MJnilnQUN65lQ58UoVn+5k2kzBj9XDJUqORJ8YBmzpq1h0pxjaLV5Y4Tq1vVgw8Z36Naj5fNVrpjcvHmPwUEf8nIrDeuXOWFtlTfwODklh9fHxTFk4BxCT66harX862u1au1Hq9Z+REfHkRCfQqVKjtjZP30WVGkhU8+RqeeidDv82wGmfPgOzip3qim1MVdZkaE84hbXuE04b4+YyKu9//kbdPTd28QnPMTRwQlX58IXDBSlw7nkJDLsQWWrpbrNb7K+zv/z57lwWjV/izWLnRg6IP92BTFxWuq3icbaxhE7qwTC9ha+jcuoSbHsO6bhz0ub/nU8Dx8kcetWDJaWZlT3rlwq152ZMXU1GzdsJ+q0J2Zm+W/ypKfn4tk4iv5BXZm74E09RfhsysTU86NHj9KlSxfc3NxQqVRs3749X/mQIXnfWP/+06FDh3znxMfHExQUhJWVFTY2NgwbNozU1LI74l2Iv1MUhRVrFuOgcsVHaYq5Ku8/s4nKjJqqBlTGi6++WflcO49XdnOnft0GkuiIMs+3QXUGBLVl1KT7zFz4kJu3s0lOyWHr9hRadb+LkbE59g6WeFd9+s0M72rGxD9MKZJ47B2sadioJt413EtlogNwcP8JenYyK5DoQN7ssZ6dTDl04IQeIiseek120tLS8PX1ZcWKFU89p0OHDty7d0/3s2XLlnzlQUFBXLp0iZCQEHbt2sXRo0cZMaL0DpIS4p+4ev0vou/dxkPxLvRN05MapGc84vewo3qITojSY/kXE3lrTG+WrEnFq+lNbGvcIGhUDC6Va7A3ZAnVvCpz5kL2U3cNP30+E3d3xxKOWn9ycnIwMXl6ImaiUaPV5pRgRMVLr2N2OnbsSMeOHf/rORqNBheXwqfr/fXXXwQHB3Py5EkaN24MwPLly+nUqROLFi3CzU2+sYqyLTE5b8CkGYXfXjVVmaNGTWJyYglGJUTpY2howIdzhzNx0qscO3qOzIwsfOp5UbNW3grKgwZ35LstB9j8UwpBvfLf7vjzUiY/7krlgzmv6iN0vWjUpC6//HqYzz7Mm5X2dzk5Cjv3pdO8dRM9RVf0Sv1srMOHD+Pk5ETNmjUZNWoUDx8+2Vk5NDQUGxsbXaID0LZtW9RqNWFhYfoIV4gi5eKUl7An/WcNnP8vRUkkV8nFxcm1JMMSJehyRKzu93Ru6i+QMsLa2pxXujSnV582ukQHoHmLevTp25rXx8Xx7gf3OXcxk6vhWXz8eTyBve9Sp25VhgztpMfIS9bwN7sRFZ3FlLkP8vV2KYrC9AUPuRWdyfA3u/3j6yqKQkT4Hc6cvsqD+4lFGPG/U6pnY3Xo0IGePXtStWpVIiIimDp1Kh07diQ0NBQDAwNiYmJwcsq/4aKhoSF2dnbExMQ89bqZmZlkZj5ZBTI5ueCKsUKUBlU8qlK3Vn2irl3DIdcVA9WTpdoVReGG6jJ21va80KS5HqMUxeXxBqBRNvdwUCcSaJOEh3npXLSttFOpVKxcM5kq1SqxZtXPfPZlFAAaTd76N3MXjMTcvHRv+VKUGvh5M//jUUyZtJI9+zPo09UMlQq+3/mIy9cymLvgzX+82OKe3aHM/2g9F85HAmBgoOaVLs2YPXc4Varo9wtZqU52+vfvr/u9Xr161K9fHy8vLw4fPkxgYOBzX3f+/PnMnj27KEIUoti989ZkRk8cymkO45lbA0tseUQKUarrJHCfeWMXYyg7jpc7u85dJ1r9iFx3hdb1L+XtiWVuL/ti/QuGhgZMmzGYCe/25+yZa2i1Ofj4VCsTU6eLw6jRPfBtUJ0vv/iZLzb8CUCz5o34ZHkPmreo/4+utWVTCKNGfELblubM2eCKu5sRf5xMZ9EXJ2j/0gX2HVym14SnTL1DVqtWDQcHB8LDwwkMDMTFxYW4uLh852i1WuLj4586zgdgypQpTJgwQfd3cnIy7u7uxRa3EP9G3Vr1+GLxOpau/ITzl5/cnq3mUZ1pw2fRrOmLeoxOFLXHvTnR6kfYNUnAx+EOzuYWMt28CJmaamjWvJ6+wygVmjWv96/bIjU1ncnvLmdQHyvWLXXSTaZo4KOhdxcL/DvcYc6sr1m7QX+LlpapZCc6OpqHDx/i6pqXHQYEBJCYmMjp06dp1KgRAAcPHiQ3Nxd//6e/MWg0GjQaTYnELERRqFPThy+XbOD2nVvExsVgY2OLV5XCZ2iJsutxopPhaoSdixmBnjfxMPeU3hxRqu34+RipqZl8OMmlwHuSk4Mh40dYMfmj30iIT8bWTj+9aHpNdlJTUwkPD9f9HRkZyblz57Czs8POzo7Zs2fTq1cvXFxciIiIYNKkSVSvXp327dsDULt2bTp06MDw4cNZtWoV2dnZjBkzhv79+8tMLFEuuVfyxL2Sp77DEMWocjUnMuwhwzZcbluJMiEy8i6VXI3xqGxUaPkLjU3Jzn7AnTsP9Jbs6HU21qlTp/Dz88PPzw+ACRMm4Ofnx8yZMzEwMOD8+fN07dqVGjVqMGzYMBo1asSxY8fy9cps2rSJWrVqERgYSKdOnWjRogWrV6/WV5WEEEIUs/txCcyf+w2NfQfj5dGTl1q+xfqvd5OZmaXv0CokGxsLHsRrSU3LLbT85u3svPNs9bdDgWwXgWwXIYQoHS5HxJLlaKLr2elcKV16dv6f8OvRdOk4kZTkZPp1M8/beftsJrtD0nghoA7f/zyvQs2qKg1u347Dt84gPplpz/g3bfOV5eQotO5xl1xDT4L3Ly3y537W7SLK1JgdIYQQFZeiKLz+2hxsLNI5FeyBi9OTj7A/TqbTof8V5nywngWfjNJjlBWPu7sTrw/tzOSPdpOTC8MHWmFlacC1iCymzX/I8dPp/LTj+TZYLSqlflFBIYQQAuB46CUunI9kyUf2+RIdgGZNTBk33IpN3+4lNTVdTxFWXAs/Hc3rw7owZW48zj43ca13i9otbnHkOKz7djqtX2qo1/ikZ0cIIUSZcDLsMpYWBrzUovDbVD06WTBvaQJX/rpJ4ya1Szi60kOrzWHP7lCC9xwnIyMTH59qDHytA07Otk99TFRULF99uZM9u34jIyOTuj5eDBvejXbtmzzTrE9DQwM+WTyGd97tzy87fiM5OY1q1dzo3KU5JibGRVm95yLJjhBCiBKjKArJyY8wNjbE1PSfLQGiNlCTkws5OaAu5L5EZlbeEFRDQ4OChRXE7dtx9On+PleuRFO/ril2Nmo+2X2MBfO+Ycnyd3h14MsFHhP6x0X69pyKgVpLv27m2Nmo2Xf4In17nWTYG6+waMnbz7zMhZubA2+O6l7Etfr35DaWEEKIYpeZmcXSxdvwrTsQT7ceuDp0oWfXyRw5dFZ3TkJ8Muf/jODWrcK3+2ndpiGPHuWwPTi10PLNP6Xg6GhFnbpVi6UOpZ1Wm0O/nlNIT40jbK87Z/dX5sAPbtw+U4WgXuaMHvkpvx07n+8xaWnpBPWbScN6aiJPevDFQic+muLAieBKfLnIibVf7WLLphA91ajoSLIjhBCiWGVlZdO/9ww++vBrWvtnsnmVCysWOJL88Ardu0xm6eJtDBs8lxrV+tGy2Sh867xGYKvRhOw7ke86PvWq0bqNL+OmPeTM+QzdcUVR2PhDMqs2JDNiVA+MjQtf76W82xccxuXLt9m62pnGDUx0x21tDFi9yAlfHxOWL/ku32N+2HaIhIRUvl7ihJXlkx4xlUrFG0HWdG5nwaovfiyxOhQXuY0lhBCiWK1etYNjR88RvNWNNs3NdMdHDLJm0OhY5nzwFS7OxiycbkuzpqZERWezYt0d+vaaweq1k+nT7yXdY9Z8PZWe3d6nSftIWgaYUdXDgBNnsvnregZ9+7/EhHf7FxZChRC85zh1a5nS1M+kQJlareL1fhaMn3GK7GwtRkZ5H//HQy/RuIEZVdwLTxB7vWLO0HGRPHqUgZlZweuWFZLsCCGEKFZff7WTvl0t8iU6kPcBnJ2di6ODASeCK+HsmPeR1KSBCT06WfDamFjem7CMzl2a6T5oHZ1s2X94OTt+PsYP2w5y+UYSPn6VWLi0Iy+29NWNLYmLTSA+PhkXFztsbC1LtsJ6kpmRha3108fW2FirURQlX7KjUqnIyXn6cntaraI7ryyT21hCCCGKTUZGFjciYmjbyqxAWUJiDjt/TePdUba6ROcxtVrFnPftSUp6xI6fj+Ur02iM6ds/kG0/zSXk8OesWTeFlq0aoFKpOHniL3p0mUyNav14ofFwqlfpw5CBc4gIv1Os9SwNfOpV4+S5DB48zCm0fO/BR3h5ueQbGN6yVQPOnE/nanjhq09v3Z5Gk6Y1//Fg8tJGkh0hhBDFxsjIAAMDNfHxBT+Ao+5oyc6GZk0Ln0pe1cOISq4abty4+0zPdfjgGTq3n0Bi3BW+XurMsZ2VWTTLnj9Pn6Bdm7e5djXqX9WltHt14MuoVAZMmHW/QG9NyJE0fvgllWEjuufrpenesyVubrYMGh1HTJxWdzwnR+Hjz+M5eCyN0W/3KbE6FBe5jSWEEKLYGBgY0KGjP+u2nuXtN2wwNHzyQWtjlfd9O+pOdqHjTFLTcnmYoMXa2vx/Pk9OTg5jx3xKC38Tdm90xdg473maNTElqJclLbreYfK7K/j5l4VFVLP/LiE+mUMHz/DoUSZ1farSwM+72G8FOTja8PnKdxkxbAF/Xs7m9X4W2NoasO/QI37clUqblxoy/M2u+R5jYmLM1h/m0avbZKo1vcUr7cywt1UTciSTyKhM3p38Kt17tizWuEuCJDtCCFGKhKcnkKvNxknfgRShcRP60bFdGIPHxrJ4tgPOjoYoisKdGC2mJiqWrUmkZycL1Or8ycDaTUlkZubSrcf//rA9fPAsUbfu891Kd12i85idrQGT37Zh6Liz3Lx5jypVXIu0fn+Xna1l1vSv+PqrX8jIyNYd92voxYpVk4p9Wnzvvm2o7O7E8iXbmDQnjJycXLy93ZgzbyBvjOiiG6vzd/V9vQg7/TUbvwlmz+7fCY/O4IUXvVgzvEu5WZxRkh0hhCgFdp27TrT6EXbVzfBxO4GzuQVgr++wikRT/zqsXT+Vt978mB933aSRrymJSblcuZ5BlSpO/HEyjoGjY/nofXuqeRqRmpbL2k1JTP4onsFDOuLu/r9Tv/DwaIyN1TRpUPjYkpYv5N0qu3mjeJOdcWM+Y9vW/Ux/x5Y3gqyxtzUg5Ogjps67Q+f2Ezh07AuqVC2+5wd4IaAuLwTMJicnB602B43mf69gbGdvxdh3+jL2nb7FGpu+SLIjhBB6dDkilhspyWS4GmHnkYCPw0WaOHmWu93Ou/dsSavWDdiyeT8XzkdgYmLMnIUBBLZrzM8/HmHi+KVs23ETNxcN8YlaMjNzGTykIx8vHvNM17eyMicrK5e4BzkFBjsDRN/NG49iaVVwoHRRuXjhBps3hrDqEyeGD7TWHe/c1pxmjU2o3yaaTz/ZwvIvJhRbDH9nYGCAgUHFXU3671SKojx9zlkFkZycjLW1Nft//gNzcwt9hyOEqCAuR8RyNC2G3EoKDm6JBHom4WFuX+4SnWfx6FEGO7f/xo0bd7G2NqdbjxepXPnZb+YlxCdT23sA746yZPak/D1iiqLQb0QMoWeMuXh1M+rC9pooAjOnreG7Tdu5ddoTI6OC43PmLH7Iws9TuB2zs0JvaVGUkpPT8HDtQVJSElZWVk89T3p2hBBCDx736DRoUoUM23Dq2STRwtFf32HpjZmZCf1fbfvcj7e1s2LoG12Yu+QnzM1UjBxsjZWlAbH3tcxdEs+Pu1KxtDThflwizi52RRj5E3FxCXhVMSo00QGo5W1Meno2qSmPKszaP6WFTD0XQgg9qVztSc+Fh3n5GJ+jTx6ezgBMX/AQt/qRVPePxLNRJF9vTuaj9+3Izcnm67W7iu353dwcuBqRTUZGbqHl5y9lYmlpgoVl8d1KE4WTZEcIIUSJUxSFE2GXGTv6M3p3n8rI4R9z5NBZ/s3Iip3bj/LKyxbcOFGFDyfb06erJZ/NceT22apMGWdP327m7PjpcNFV4v8ZENSOh/HZrNqQVKAsJk7Lmo2p9H/1ZbmFpQdyG0sIIUSJ0mpzeGvEx2z77hDVPDXUq23Inydz2Lp5P+1ebsyGTTOfax+m1NRH1PMyoLKbERNG2hYor+RiSGrqo6KoQqG8a7gz8q3uvDt7Ozdvaxk+yAoHu7x1buYsTsTQ2IJ3KvDeXfokyY4QQogSNW/OBn768TDrlzkT1MsStVqFoijsCknj1VFnmTTxcz5f+e4/vq63twdHQ++hKEqhC/gd/iOD6t41iqIKTzVv4UgcHG1Ysex7lq99smLzS4F+LF46Hjc3h2J9flE4uY0lhBCixKSmpvPV6u1MGGnDoD5WuoUEVSoVXV62YM4kW7Zu3k/MvYcFHpuWls7aNb/w8ktv06BuEB3bjWfjN/vIzMzb12nIsFf463oGazcnF3js9r2p/Bb2iCFDXynW+qnVat6d9CqXr2/l553z2bxtNmcvrOennQuLfX0d8XSS7AghhCgxJ8Muk5ycwWt9Cp8mPLifFVptLocPnc13/MH9RF5u8zaTJn6Oi80d+r6ixdL4Fm+/9SldOk4kOTmNFi/W5/WhnXjz3TgGvhXDrpBUgg+mMXxiLH2Hx9Ctewu6dm9REtXE1FRDm8BGdOocQNVqbiXynOLp5DaWEEKIEpOV/Z/F/SwKn55tbqb+z3nZ+Y6PeWsRD+LucWa/Oz61nqySHHYmgw79I5gyaSUrVr3Lp0vHUrtuVVau+IEtP98DoHJle2bMGsqYcb2LbY0dUbpJsiOEEKLE1KvvhYGBml9C0hg12KZA+a6QNAD8/J6MrYm8cZfgPSdYu8Q5X6ID4N/QhOnv2DB9wQFmz3kDB0cbRozsxhsjuhAdfZ/c3Fzc3Z1kJeEKTlJcIYQQJcbNzYHOrwTw0eJEwiOz8pXdi9UydV48AQF1qFffS3c89I+LAPTpUvgK9326WJCVlcPp01d1x9RqNR4ezlSp4lohEh1FUTgeeonRIz+la6d3eX3QR+zZHUpOTo6+QysVpGdHCCFEiVr02Vg6vTwev7bRvNrDnAY+Gq6GZ/PN96mYW1iybfWkfOc/nlmVW/hafeT+Z2keFYXfGivvcnJyGDPqU7Zs2o9XFQ2NfI2ICM/h1b5HCQiow9Yf52Jtba7vMPVKenaEEEJPwtMTiNLG6TuMEufkbMv+w58zfmIQv/6mYfyMh/ywB4YO78WhYysLDOgNaO6DSqXiux0phV7vu+0pmJgY0bhJrZIIv9RZ9PEWvttygK+XOnPld3e2rHLlxL7KHPixEn9dvsbboxbpO0S9k41AkY1AhRAla9e560SrH2Hna4aP2wmczS0q9L5Yz2LQgA/447eTBG9xoWH9JwsOHg1Np8uge/Tu254ln4/XX4B6kpGRRR3v/gzsachncxwLlH+9JYkRE+9z5vy6cjkr7Fk3ApWeHSGEKCGXI2LZde46Ue5p2DVJwMftBE2cPCXReQbLVkzA3dODJu1v06H/XcZPv0+bnndo0zMaX7/azF34pr5DfCqtNofo6DjiYhOK/Nrnzl4nPj6VQX0K31h0QHdLDAzg0MEzRf7cZYmM2RFCiBJwOSKWo2kx5Lor1KmdQz2bJDzMPfEwq67v0MoEWzsrgvcv5cfvD7N18z5Cfo/HrVJV1q7vQNfuL2JkVPo+zjIysliy+DvWr/2FmJhEABr4eTHunf706NWqSJ5Dq80bgGxmWnjfhUajwsBARfZ/pvxXVKXv1SGEEOXM5YhYbqQk06BJFTJsw6lnEy29Oc/BxMSYoEEvEzTo5QJlWm0Omzf9yvq1v3D9WjTm5hq6dG/NW6N76OX2TWZmFv16TeN46AVe729J53ZuJKfksuG7GF5/bS43I+8VyT5ZdetWQaMxZOe+VGp52xUo33foEZmZuTRsVPNfP1dZJrexhBCiBFSu5qT73cPcXo+RlD9ZWdkE9ZvJuNGf4WIbw8wJFrzaXcWOH/bQstlIjodeKvGY1q3dze+/nSd4ixsrFjjRKdCc/t0t2bvFjanjbPnwg3VEhN/5189ja2dF774v8fGKJM5fzsxXFntfy3uz42ng51VhB28/JsmOEEKIMm350h84eOA0uze58cu3rkwYacsnsxy5FupBg7pqBgd9oNs/q6Rs+HoXPTpZ0DLAtEDZtPF22NoY8M36vWi1Of/6FtPcBSNx93THv2M0A9+KYenqBN6eGkftFrdJSDHhq3XTCt0YtSKRZEcIIUSZlZOTw9rV2xnc14L2bfKvJWNpoWblQkdiY5P4ZcfvJRaToihcvRpN62YmhZabmKjx8jRg07fBONp0wtGmE62aj2TTt7/yPBOkbWws2PPrEmZ88AZn/7JmxsfJ/LLfkGEjenP4t5VU9678b6tU5smYHSGEEGVWTEw8d+8m0LVD4eNyatcwpmZ1E06dvELvvm1KJCaVSoWFhYbY+4WvXrx4VQInz2XSxE/FBxMdMDZWsX1vHKNHLuJ46AWWrZjwj3tiLCxMeXtcb94e17soqlDuSM+OEEKIMsvwP1tBpGcUvryyoiikZygYGpbslhFdurVkw3dppKfnj+vS1Uzem/2ASWNsCd1dmVFDbBj2qjW/fOvK10ud+XbDPnbu+K1EY60IJNkRQghRZjk52+Lj48nGH1ILLT8amk5UdCZt2zUu0bjGjO1N3MNceg6N0e0BpigKMxY8xN5Ozez37Av03gzua0WzJmasXb2jRGOtCCTZEUIIUWapVCrGjOvHL/tSWbAsnuzsJ2NeLl3NZOj4B9SrX5WWrRuUaFy161Rhy7Y5hJ3NpWazW9R5MYoqjaPYFZJG+9bmGBsXfpuqU6ApFy9ElGisFYGM2RFCCFGm9RsQSHh4NNPmb2bFuhRa+BtzLzaXY8cf4e3txuZtc1CrS/a7/YXzEUyZtIKkpHSMjFRci8hEUcDe3pKEpKfsaAokJOVgYmIMwKNHGez4+Rjh16OxsDCla/cX8apeqaSqUK5IsiOEEKJMU6lUTJ85hG7dX2TDuj1cvXILcztTVq5uSY9erXTJQ0m5GXmPrp3epUrlXEK+r0Sb5qakPVL4ZlsyE2Y94NfDCrfvZONeySjf4zIyctn0YxqdurZnx/ZjjBv9KUlJj/CorOFhvJbZs76mb782LPtiYonXqayTZEcIIUS5UK++F4s+e1vfYbD0s21ojLII2eaOrU3ewGgLcxVvvW6DpYWaYe/E0m1wDFu/dKaGV17Sci9Wy5vv3ScxGRo3qcXrgz6iRydzFkyvQjVPI9LTc9n4YwrjZxwhN1fhq/VT9VnFMkeSHSGEEKKIKIrCD9sOMHaYpS7R+bugXpZMnx/PjSiF2i1u0cTPDI0xHD+djqmpho1bPmDJ4q00bmDCllUuGBjkje0xNVUzfKA1Wq3CmCmHebFVAzp2CsDJ2Tbf9YP3Hmf1yp85dfIv1Go1bV5qzKgxPWnqX6dE6l9ayQBlIYQQoohkZ2tJScnAq6pRoeVqtYraNYxp2boRK1e/R9WaATi7N2XOvJFcuLIZ3wbV+e3YBUYNttIlOnnXVZg27wHT5j8EYNyYJdSpMYA3hszj4YMkAGbPXEv/3jNJTbjKlLfNGT/chMvnT9A+8B2+2bC3+CtfiknPjhBCCFFEjI2NcHa25tS5DAb3tSpQnpWl8OelLPoMcGVAUDsGBLVDq83h8MEzbP/pCFlZeVtHuFd68vGsKAqDx8bw465UJoy0ZVBvS8zM1OwMTmXe0t/p2ukG708bwmeffseiWQ68M/JJb8+08XaMmXKfd95eSosW9anmVTEHOOu1Z+fo0aN06dIFNzc3VCoV27dvz1euKAozZ87E1dUVU1NT2rZty/Xr1/OdEx8fT1BQEFZWVtjY2DBs2DBSUwtfb0EIIYQoboMGd+Kbbam69XX+7ot1icQ9yGbga+0B2L3rDxrUHUjvHtN4Z+xSJk1cgYEafg9L1z3m2PEMvtueyrqlzsyf5kCdmhqquBsxdrgth35yIzw8mjmz19Gwvinj37TJ93xqtYrFsx2wtlLz9Ve7i7XepZlek520tDR8fX1ZsWJFoeUff/wxy5YtY9WqVYSFhWFubk779u3JyMjQnRMUFMSlS5cICQlh165dHD16lBEjRpRUFYQQ4r+6HBHLjZRkwtMTiFKfxcnoir5DEsVs9Nu9cHVz5sWud1nyZQJXw7MIO5PByPdimfjBA0aN7kHtOlUI2XeCQQNm06BOBif3uZN9pzrXQj3x9jJiyZpEbt3OBmDd1iRqeBkxoIdlgeeqXcOYPl3MuXXzDl3bmxa6zYSJiZr2rU05ffJysde9tNLrbayOHTvSsWPHQssURWHJkiVMnz6dbt26AfDNN9/g7OzM9u3b6d+/P3/99RfBwcGcPHmSxo3zVsdcvnw5nTp1YtGiRbi5Fb5XihBClITHiU6UexoObokEeibhYe6Jh1l1fYdWYT18kERk5F3MzU2pVdvzuXYDvxl5jytXbmFqqsH/hboFpoHb2lmx59fPmDp5Fe/PPcrEDx4A4OxszZx5IxgztheKojB75hpaNTPlp69ddeNzvKoYc+CHytR98RZN2kcxYaQtl65k4VtX89RYG9bTsOXnFNLTn76JaHqGgkEJb5lRmpTaMTuRkZHExMTQtm1b3TFra2v8/f0JDQ2lf//+hIaGYmNjo0t0ANq2bYtarSYsLIwePXoUeu3MzEwyMzN1fycnJxdfRYQQFdKuc9eJVj8i112hdf1LOJtb4GFuL4mOnty9+4AZU75kx/ZjaLV5i/p5e7vx3vuD6Ns/8JmucTPyHhPHL+XA/jO6Y/b2Fowd35+x7/TJl4w4OtmyZt0U5i0cyZUrUZiYGNPAzxsjo7yP3YsXbnDx4i12bXTLNxAZwMXJkL1b3QjoFM3sTxPJysohM0tBUZRCE56rEdmYm5uw5ec0Zk+yx8go/zn3H2jZe/ARU6f7P1tjlUOldjZWTEwMAM7OzvmOOzs768piYmJwcnLKV25oaIidnZ3unMLMnz8fa2tr3Y+7u3sRRy+EqKguR8TqEh27Jgm6RKeFo78kOnoSc+8hHQLHcvz3UD6eYcfZAx7s3eJG3erJjBi2kBXLf/yf17hz5z4d240n8volvl7qzO2zVTmz34O+XQyYNeMrZk5bU+jjHJ1sebGlL02a1tYlOgAP7icCULN64YsDNvUzRaNRM3XGEBZ9NoaLV7I4cCy9wHl3Y7Rs/imVHj3bcDdWy9DxsaSkPlmhOfa+lj7DYzE1NdGNE6qISm3PTnGaMmUKEyZM0P2dnJwsCY8QoshUruaEgz1kWGtp4iS3rfRt4fyNpKclcerXSlR2y5sSXr+OhnatzHj3gwfMnvkVffu9hKOT7VOv8enHW8jJTuVYcGVcnPI+Ot1cDPl8vhMelQyZOu9Hhg3vQpWqrs8Uk1slBwDOXcykmmfBaep/XcsiMzMXr+qVcHGxx9BQRc/X77JwhgMDe1thaqLil1/TePeD+xgZmzB91hBav9SQN99YwM59N2nb0oTMLNh/9BHm5qZ89+Nc7B2s/2nTlRultmfHxcUFgNjY2HzHY2NjdWUuLi7ExcXlK9dqtcTHx+vOKYxGo8HKyirfjxBCiPInIyOLbVtDGDXEUpfoPKZSqZg23g61WmHrlgNPvUZ2tpbvtoTw5muWukTn78YMtcHayoBNG3995rhq1PSgqX9NFn6eSEZG/r2yFEVhzmfxODhY8nL7psye+RV1vI3p3NacsdPuY+MdgYlHOL2H3eP2XS0pyWkcP36JHr1acebCBka93Z/EDG+y1bWZOXs4Zy98g/8LdZ85tvKo1PbsVK1aFRcXFw4cOECDBg2AvB6YsLAwRo0aBUBAQACJiYmcPn2aRo0aAXDw4EFyc3Px96+49yaFEELkefAgkbS0LPwbmhRabmdrgHc1Dbdu3nvqNZKT0khLy8S3rl2h5WZmamp4GXP3zoN/FNtH80fRtdN7tOl1l6njbGhU34TrN7JY/GUiu35NY/XaycTExPPbsQt8u8IZFydDftqTSvUqhrRrbU7ntmao1So+/jyBwUFz2Lj1Azp1DmDajMH/KI6KQK/JTmpqKuHh4bq/IyMjOXfuHHZ2dnh4eDB+/Hg++ugjvL29qVq1KjNmzMDNzY3u3bsDULt2bTp06MDw4cNZtWoV2dnZjBkzhv79+8tMLCGEEFhZmaNSqYj8zzTu/y8rS+FujBYb24LTuh8ztzDBwEDF1fCC6+Y8vkbEzSyatbb5R7E19a/Djt0fM2XSCroPfvJZ6OXlyoaN79CtR0uOh14CwLeOMa+OiqV5E1P2fVcp3yDkl1qY0X3wPd5/73Pad2iKgUHFnXX1NHpNdk6dOkWbNm10fz8eRzN48GDWr1/PpEmTSEtLY8SIESQmJtKiRQuCg4MxMXmSoW/atIkxY8YQGBiIWq2mV69eLFu2rMTrIoQQovSxsjLn5Q5NWLn+PEP7W6HR5B+9sfHHZB7GZ9O7T5unXCFv5lROjsKqDUmMGmKNtVX+ZGL9d8k8jNfSt/9L/zg+/xfqcvDoF1y6GMnt27E4OFjTsFFN1Oq8OJ2cbADYvf8RF69kEbzVrcBsKwMDFdMn2NGs821+O3qeVm38/nEc5Z1ek53WrVujKE9fF0ClUvHhhx/y4YcfPvUcOzs7Nm/eXBzhCSGEKAcmTxlEx3bv0G1wDAtn2ONbV0NKai7rtyYz+aOH9O3Xhlq1PZ/6+OC9YdjaGJKSlktgrzt8NMWedq3MeBCfw+pvk/hocTwA1jYWzx1jXZ+q1PWpWuB4Na9KNGlak3VbIwHw8yn8dlzDehoAbt+OK7S8oiu1A5SFEEKIotCwUU22fj+HS9eNadg2Csc6N3GqG8mEWQ/o278dy1dO/K+Pz8rMxtbakAM/VEYBOgfdxbhyOG71I1mwPIFuHcwByMwo/DbXvzXrw+FE3My7DXftRuHP8fi44396gkR+pXaAshBCCFFU2gQ24s/Lm9gXHMa1K1GYW5jSuUszKld2+p+PrVffi2VLMjDRqDj1qzsnzmZy8UomZqZqXm5lxoLl8djamlOpsmOxxN7ixfps/X4OgwbM4pMVCfy0ziTf4oKKovDJigScnKxo81LDYomhrJOeHSGEEBWCkZEhr3RpzoT3BvDmqO7PlOgAdO3eAicna8ZOf0BGhoJ/QxOGvWrNgB6W3IjK5stvUnhtSGc0msIXCCwK7do3ZcXqyezcl0bQqBguXc1EURSuRWTxxoQ4vv0+hemzhmFsXHDNHiE9O0IIIcR/pdEYs2bdVPr3no5Pq2iGDrDA1cUgbzfyHan4NvBm0pSgYo+jV+/W5GhzmD5lJd/tiEKthtxcsLOzYMnycbw2pPC9JoUkO0IIIcT/1Kq1HweOfM7ypd8zf/kR0tOzqVLViSnT+jBiVDfMzAofOFzU+vYPpHvPluwPOcW9uw9wcral3ctNC2xGKvJTKf9tOlQFkZycjLW1Nft//gNz8+cfTS+EqNge73Ke4WpErsdNfBzuyHYR5ZCiKGi1Ofn2uhL6kZychodrD5KSkv7rbgjyLyWEEEXgckQsR9NiyHVXcHBLJNAzCQ9zSXTKI5VKJYlOGSP/WkII8S/pdjn3NcPH7QTO5hZ4mNtLoiNEKSHJjhBCPKe/37ay80jAx+Gi3LYSohSSZEcIIf6FytWcyLCHDOuHkugIUUrJOjtCCCGEKNck2RFCCCFEuSbJjhBCCCHKNUl2hBBCCFGuSbIjhBBCiHJNkh0hhBBClGuS7AghhBCiXJN1doQQQlR4t27FcD8uARdXeypXdtJ3OKKISbIjhBCiwgr94yIfzvyK0NDLumOtWvsy+6PhNPCrocfIRFGS21hCCCEqpCOHztKt83toMyLZvMqFswc8WL/MmYS4q3R6eQKnTv6l7xBFEZGeHSGEeA6P98WKsrmHgzoRH6M7gKe+wxLPKDc3lwnjltC8qYY9m9wwNlYBUL+Oht6vWNC6510mTVzOwaNf6DlSURSkZ0cIIf6hyxGxHE2LIco9jTq1cwj0TJJ9scqYP36/SETEPT54106X6Dxmaqpm+js2nDkdzsULN/QUoShK0rMjhBD/wK5z14lWP8LO1wwftxM4m1vQwtFf32GJfyjyxl0AXmhkUmj5Cw3zjkdG3sWnXrUSi0sUD0l2AEVRAEh7lKbnSIQQpVnwhQgyXIwwdwIvq2PUNnWnsqYaycny3lHWaEyMAbh4JZNqnkYFyi9dzco7z9hY/n1LsZSUR8CTz/GnUSn/64wKIDo6Gnd3d32HIYQQQojncPv2bSpXrvzUckl2yBuodvfuXSwtLVGpVP/7AeIfSU5Oxt3dndu3b2NlZaXvcMo1aeuSI21dcqStS05Za2tFUUhJScHNzQ21+unDkOU2FqBWq/9rRiiKhpWVVZn4z1MeSFuXHGnrkiNtXXLKUltbW1v/z3NkNpYQQgghyjVJdoQQQghRrkmyI4qdRqNh1qxZaDQafYdS7klblxxp65IjbV1yymtbywBlIYQQQpRr0rMjhBBCiHJNkh0hhBBClGuS7AghhBCiXJNkRwghhBDlmiQ74rmsXLmS+vXr6xaeCggIYO/evbryjIwMRo8ejb29PRYWFvTq1YvY2Nh814iKiqJz586YmZnh5OTEe++9h1arLemqlCkLFixApVIxfvx43TFp66LzwQcfoFKp8v3UqlVLVy5tXbTu3LnDwIEDsbe3x9TUlHr16nHq1ClduaIozJw5E1dXV0xNTWnbti3Xr1/Pd434+HiCgoKwsrLCxsaGYcOGkZqaWtJVKdWqVKlS4HWtUqkYPXo0UEFe14oQz2Hnzp3K7t27lWvXrilXr15Vpk6dqhgZGSkXL15UFEVRRo4cqbi7uysHDhxQTp06pbzwwgtKs2bNdI/XarWKj4+P0rZtW+Xs2bPKnj17FAcHB2XKlCn6qlKpd+LECaVKlSpK/fr1lXHjxumOS1sXnVmzZil169ZV7t27p/u5f/++rlzauujEx8crnp6eypAhQ5SwsDDlxo0byr59+5Tw8HDdOQsWLFCsra2V7du3K3/++afStWtXpWrVqkp6errunA4dOii+vr7K8ePHlWPHjinVq1dXBgwYoI8qlVpxcXH5XtMhISEKoBw6dEhRlIrxupZkRxQZW1tb5auvvlISExMVIyMj5fvvv9eV/fXXXwqghIaGKoqiKHv27FHUarUSExOjO2flypWKlZWVkpmZWeKxl3YpKSmKt7e3EhISorRq1UqX7EhbF61Zs2Ypvr6+hZZJWxetyZMnKy1atHhqeW5uruLi4qJ88sknumOJiYmKRqNRtmzZoiiKoly+fFkBlJMnT+rO2bt3r6JSqZQ7d+4UX/Bl3Lhx4xQvLy8lNze3wryu5TaW+NdycnLYunUraWlpBAQEcPr0abKzs2nbtq3unFq1auHh4UFoaCgAoaGh1KtXD2dnZ9057du3Jzk5mUuXLpV4HUq70aNH07lz53xtCkhbF4Pr16/j5uZGtWrVCAoKIioqCpC2Lmo7d+6kcePG9OnTBycnJ/z8/FizZo2uPDIykpiYmHztbW1tjb+/f772trGxoXHjxrpz2rZti1qtJiwsrOQqU4ZkZWWxceNGhg4dikqlqjCva0l2xHO7cOECFhYWaDQaRo4cyc8//0ydOnWIiYnB2NgYGxubfOc7OzsTExMDQExMTL7/OI/LH5eJJ7Zu3cqZM2eYP39+gTJp66Ll7+/P+vXrCQ4OZuXKlURGRvLiiy+SkpIibV3Ebty4wcqVK/H29mbfvn2MGjWKsWPHsmHDBuBJexXWnn9vbycnp3zlhoaG2NnZSXs/xfbt20lMTGTIkCFAxXkPkV3PxXOrWbMm586dIykpiR9++IHBgwdz5MgRfYdVrty+fZtx48YREhKCiYmJvsMp9zp27Kj7vX79+vj7++Pp6cm2bdswNTXVY2TlT25uLo0bN2bevHkA+Pn5cfHiRVatWsXgwYP1HF35tXbtWjp27Iibm5u+QylR0rMjnpuxsTHVq1enUaNGzJ8/H19fX5YuXYqLiwtZWVkkJibmOz82NhYXFxcAXFxcCoz2f/z343NE3q2TuLg4GjZsiKGhIYaGhhw5coRly5ZhaGiIs7OztHUxsrGxoUaNGoSHh8vruoi5urpSp06dfMdq166tu234uL0Ka8+/t3dcXFy+cq1WS3x8vLR3IW7dusX+/ft54403dMcqyutakh1RZHJzc8nMzKRRo0YYGRlx4MABXdnVq1eJiooiICAAgICAAC5cuJDvjSokJAQrK6sCb4AVWWBgIBcuXODcuXO6n8aNGxMUFKT7Xdq6+KSmphIREYGrq6u8rotY8+bNuXr1ar5j165dw9PTE4CqVavi4uKSr72Tk5MJCwvL196JiYmcPn1ad87BgwfJzc3F39+/BGpRtqxbtw4nJyc6d+6sO1ZhXtf6HiEtyqb3339fOXLkiBIZGamcP39eef/99xWVSqX8+uuviqLkTWX08PBQDh48qJw6dUoJCAhQAgICdI9/PJXx5ZdfVs6dO6cEBwcrjo6OZWoqo778fTaWokhbF6WJEycqhw8fViIjI5Xff/9dadu2reLg4KDExcUpiiJtXZROnDihGBoaKnPnzlWuX7+ubNq0STEzM1M2btyoO2fBggWKjY2NsmPHDuX8+fNKt27dCp167ufnp4SFhSm//fab4u3tLVPPC5GTk6N4eHgokydPLlBWEV7XkuyI5zJ06FDF09NTMTY2VhwdHZXAwEBdoqMoipKenq689dZbiq2trWJmZqb06NFDuXfvXr5r3Lx5U+nYsaNiamqqODg4KBMnTlSys7NLuiplzv9PdqSti06/fv0UV1dXxdjYWKlUqZLSr1+/fOu+SFsXrV9++UXx8fFRNBqNUqtWLWX16tX5ynNzc5UZM2Yozs7OikajUQIDA5WrV6/mO+fhw4fKgAEDFAsLC8XKykp5/fXXlZSUlJKsRpmwb98+BSjQfopSMV7XKkVRFH33LgkhhBBCFBcZsyOEEEKIck2SHSGEEEKUa5LsCCGEEKJck2RHCCGEEOWaJDtCCCGEKNck2RFCCCFEuSbJjhBCCCHKNUl2hBBCCFGuSbIjhBBCiHJNkh0hhBBClGuS7Aghyp379+/j4uLCvHnzdMf++OMPjI2N8+3uLISoGGRvLCFEubRnzx66d+/OH3/8Qc2aNWnQoAHdunVj8eLF+g5NCFHCJNkRQpRbo0ePZv/+/TRu3JgLFy5w8uRJNBqNvsMSQpQwSXaEEOVWeno6Pj4+3L59m9OnT1OvXj19hySE0AMZsyOEKLciIiK4e/cuubm53Lx5U9/hCCH0RHp2hBDlUlZWFk2bNqVBgwbUrFmTJUuWcOHCBZycnPQdmhCihEmyI4Qol9577z1++OEH/vzzTywsLGjVqhXW1tbs2rVL36EJIUqY3MYSQpQ7hw8fZsmSJXz77bdYWVmhVqv59ttvOXbsGCtXrtR3eEKIEiY9O0IIIYQo16RnRwghhBDlmiQ7QgghhCjXJNkRQgghRLkmyY4QQgghyjVJdoQQQghRrkmyI4QQQohyTZIdIYQQQpRrkuwIIYQQolyTZEcIIYQQ5ZokO0IIIYQo1yTZEUIIIUS5JsmOEEIIIcq1/wM17/iOS6qinQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.svm import LinearSVC, SVC\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.inspection import DecisionBoundaryDisplay\n",
        "\n",
        "label_encoder = LabelEncoder()\n",
        "df['label_encoded'] = label_encoder.fit_transform(df['label'])\n",
        "\n",
        "X = df[['x', 'y']].values\n",
        "y = df['label_encoded'].values\n",
        "\n",
        "classifiers = {\n",
        "    'Logistic Regression': LogisticRegression(),\n",
        "    'Random Forest Classifier': RandomForestClassifier(n_jobs=-1),\n",
        "    'Linear Support Vector Classifier': LinearSVC(),\n",
        "    'Support Vector Classifier with RBF Kernel': SVC(kernel='rbf'),\n",
        "    'K-Neighbors Classifier': KNeighborsClassifier()\n",
        "}\n",
        "\n",
        "for name, clf in classifiers.items():\n",
        "    clf.fit(X, y)\n",
        "    disp = DecisionBoundaryDisplay.from_estimator(\n",
        "        clf, X,\n",
        "        response_method=\"predict\",\n",
        "        xlabel='x',\n",
        "        ylabel='y',\n",
        "        alpha=0.3\n",
        "    )\n",
        "\n",
        "    disp.ax_.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k')\n",
        "    disp.ax_.set_title(name)\n",
        "    plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "id": "901227bf-750c-42a1-b079-877b4b2e8889",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 711,
          "referenced_widgets": [
            "9d617b8bd36944dda26f66258216c786",
            "5647aa57343f4a5a9e5b3e04110394cf",
            "d95789dcdde14bddbe5c235630ada34c",
            "3e0a9169f25040a5aedd490f99d2356f",
            "56f012236bdb437d82be5ebea568b57d",
            "7792b176772a48129d05e4e3fdd14447",
            "d05743582e2e4ec98d39da78d05f7fbc",
            "453330696a044853bc0e0947246c58f9",
            "1605e26aa29747ea9147094d45515c1d",
            "55fc7bea63484304ba020c23f80bf0bd",
            "fe2d54c3d49044d9a8008ed9b5eac7e9"
          ]
        },
        "id": "901227bf-750c-42a1-b079-877b4b2e8889",
        "outputId": "8cb90483-c0de-4541-b0c3-03f2b6ebac88"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "HBox(children=(VBox(children=(ScatterWidget(), RadioButtons(description='Classifier:', options=('Logistic Regr…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9d617b8bd36944dda26f66258216c786"
            }
          },
          "metadata": {
            "application/vnd.jupyter.widget-view+json": {
              "colab": {
                "custom_widget_manager": {
                  "url": "https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"
                }
              }
            }
          }
        }
      ],
      "source": [
        "import warnings\n",
        "from sklearn.exceptions import ConvergenceWarning\n",
        "\n",
        "warnings.filterwarnings(\"ignore\", category=ConvergenceWarning)\n",
        "\n",
        "import ipywidgets\n",
        "from sklearn.inspection import DecisionBoundaryDisplay\n",
        "from IPython.display import HTML\n",
        "\n",
        "output = ipywidgets.Output()\n",
        "widget3 = ScatterWidget()\n",
        "\n",
        "classifier_selector = ipywidgets.RadioButtons(\n",
        "    options=['Logistic Regression', 'Random Forest', 'SVC Poly', 'SVC RBF'],\n",
        "    description='Classifier:',\n",
        ")\n",
        "\n",
        "@output.capture(clear_output=True)\n",
        "def on_change(change):\n",
        "    df = widget3.data_as_pandas\n",
        "    if len(df) and (df['color'].nunique() > 1):\n",
        "        X = df[['x', 'y']].values\n",
        "        y = df['color']\n",
        "        display(HTML(\"<br><br><br>\"))\n",
        "        fig = plt.figure(figsize=(12, 12))\n",
        "\n",
        "        if classifier_selector.value == 'Logistic Regression':\n",
        "            classifier = LogisticRegression().fit(X, y)\n",
        "        elif classifier_selector.value == 'SVC Poly':\n",
        "            classifier = SVC(kernel='poly').fit(X, y)\n",
        "        elif classifier_selector.value == 'SVC RBF':\n",
        "            classifier = SVC(kernel='rbf').fit(X, y)\n",
        "        else:\n",
        "            classifier = RandomForestClassifier().fit(X, y)\n",
        "\n",
        "        disp = DecisionBoundaryDisplay.from_estimator(\n",
        "            classifier,\n",
        "            X,\n",
        "            response_method=\"predict\",\n",
        "            xlabel=\"x\", ylabel=\"y\",\n",
        "            alpha=0.5,\n",
        "        )\n",
        "        disp.ax_.scatter(X[:, 0], X[:, 1], c=y, edgecolor=\"k\")\n",
        "        plt.title(f\"{classifier.__class__.__name__}\")\n",
        "        plt.show()\n",
        "\n",
        "widget3.observe(on_change, names=[\"data\"])\n",
        "classifier_selector.observe(on_change, names=\"value\")\n",
        "on_change(None)\n",
        "\n",
        "ipywidgets.HBox([ipywidgets.VBox([widget3, classifier_selector]), output])"
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "4uhSR9qkRywY"
      },
      "id": "4uhSR9qkRywY",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.12"
    },
    "colab": {
      "provenance": [],
      "gpuType": "T4",
      "include_colab_link": true
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "df56234ad95a49569987e15754906408": {
          "model_module": "anywidget",
          "model_name": "AnyModel",
          "model_module_version": "~0.9.*",
          "state": {
            "_anywidget_id": "drawdata.ScatterWidget",
            "_css": "fieldset.toolbar{\n    font-family: Arial, Helvetica, sans-serif;\n    font-size: medium;\n}\n\nbutton.toolbarbtn{\n    font-family: Arial, Helvetica, sans-serif;\n    font-size: medium;\n    padding: 4px 8px;\n    margin-right: 4px;\n    background: linear-gradient(to bottom, #f5f5f5, #e5e5e5);\n    border: 1px solid #ccc;\n    border-radius: 4px;\n    color: #333;\n    font-size: 14px;\n    cursor: pointer;\n    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.1);\n}\n\nbutton.toolbarbtn:hover{\n    background: linear-gradient(to bottom, #e5e5e5, #f5f5f5);\n}\n\nspan.count{\n    font-family: Arial, Helvetica, sans-serif;\n    font-size: medium;\n    margin-right: 4px; \n    padding-right: 7px; \n    padding-left: 7px;\n    padding-top: 3px;\n    padding-bottom: 3px;\n    border-radius: 8px;\n}",
            "_dom_classes": [],
            "_esm": "var __create = Object.create;\nvar __defProp = Object.defineProperty;\nvar __getOwnPropDesc = Object.getOwnPropertyDescriptor;\nvar __getOwnPropNames = Object.getOwnPropertyNames;\nvar __getProtoOf = Object.getPrototypeOf;\nvar __hasOwnProp = Object.prototype.hasOwnProperty;\nvar __commonJS = (cb, mod) => function __require() {\n  return mod || (0, cb[__getOwnPropNames(cb)[0]])((mod = { exports: {} }).exports, mod), mod.exports;\n};\nvar __copyProps = (to, from, except, desc) => {\n  if (from && typeof from === \"object\" || typeof from === \"function\") {\n    for (let key of __getOwnPropNames(from))\n      if (!__hasOwnProp.call(to, key) && key !== except)\n        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });\n  }\n  return to;\n};\nvar __toESM = (mod, isNodeMode, target) => (target = mod != null ? __create(__getProtoOf(mod)) : {}, __copyProps(\n  // If the importer is in node compatibility mode or this is not an ESM\n  // file that has been converted to a CommonJS file using a Babel-\n  // compatible transform (i.e. \"__esModule\" has not been set), then set\n  // \"default\" to the CommonJS \"module.exports\" for node compatibility.\n  isNodeMode || !mod || !mod.__esModule ? __defProp(target, \"default\", { value: mod, enumerable: true }) : target,\n  mod\n));\n\n// js/d3.v7.js\nvar require_d3_v7 = __commonJS({\n  \"js/d3.v7.js\"(exports, module) {\n    !function(t, n) {\n      \"object\" == typeof exports && \"undefined\" != typeof module ? n(exports) : \"function\" == typeof define && define.amd ? define([\"exports\"], n) : n((t = \"undefined\" != typeof globalThis ? globalThis : t || self).d3 = t.d3 || {});\n    }(exports, function(t) {\n      \"use strict\";\n      function n(t2, n2) {\n        return null == t2 || null == n2 ? NaN : t2 < n2 ? -1 : t2 > n2 ? 1 : t2 >= n2 ? 0 : NaN;\n      }\n      function e(t2, n2) {\n        return null == t2 || null == n2 ? NaN : n2 < t2 ? -1 : n2 > t2 ? 1 : n2 >= t2 ? 0 : NaN;\n      }\n      function r(t2) {\n        let r2, o2, a2;\n        function u2(t3, n2, e2 = 0, i2 = t3.length) {\n          if (e2 < i2) {\n            if (0 !== r2(n2, n2))\n              return i2;\n            do {\n              const r3 = e2 + i2 >>> 1;\n              o2(t3[r3], n2) < 0 ? e2 = r3 + 1 : i2 = r3;\n            } while (e2 < i2);\n          }\n          return e2;\n        }\n        return 2 !== t2.length ? (r2 = n, o2 = (e2, r3) => n(t2(e2), r3), a2 = (n2, e2) => t2(n2) - e2) : (r2 = t2 === n || t2 === e ? t2 : i, o2 = t2, a2 = t2), { left: u2, center: function(t3, n2, e2 = 0, r3 = t3.length) {\n          const i2 = u2(t3, n2, e2, r3 - 1);\n          return i2 > e2 && a2(t3[i2 - 1], n2) > -a2(t3[i2], n2) ? i2 - 1 : i2;\n        }, right: function(t3, n2, e2 = 0, i2 = t3.length) {\n          if (e2 < i2) {\n            if (0 !== r2(n2, n2))\n              return i2;\n            do {\n              const r3 = e2 + i2 >>> 1;\n              o2(t3[r3], n2) <= 0 ? e2 = r3 + 1 : i2 = r3;\n            } while (e2 < i2);\n          }\n          return e2;\n        } };\n      }\n      function i() {\n        return 0;\n      }\n      function o(t2) {\n        return null === t2 ? NaN : +t2;\n      }\n      const a = r(n), u = a.right, c = a.left, f = r(o).center;\n      var s = u;\n      const l = d(y), h = d(function(t2) {\n        const n2 = y(t2);\n        return (t3, e2, r2, i2, o2) => {\n          n2(t3, e2, (r2 <<= 2) + 0, (i2 <<= 2) + 0, o2 <<= 2), n2(t3, e2, r2 + 1, i2 + 1, o2), n2(t3, e2, r2 + 2, i2 + 2, o2), n2(t3, e2, r2 + 3, i2 + 3, o2);\n        };\n      });\n      function d(t2) {\n        return function(n2, e2, r2 = e2) {\n          if (!((e2 = +e2) >= 0))\n            throw new RangeError(\"invalid rx\");\n          if (!((r2 = +r2) >= 0))\n            throw new RangeError(\"invalid ry\");\n          let { data: i2, width: o2, height: a2 } = n2;\n          if (!((o2 = Math.floor(o2)) >= 0))\n            throw new RangeError(\"invalid width\");\n          if (!((a2 = Math.floor(void 0 !== a2 ? a2 : i2.length / o2)) >= 0))\n            throw new RangeError(\"invalid height\");\n          if (!o2 || !a2 || !e2 && !r2)\n            return n2;\n          const u2 = e2 && t2(e2), c2 = r2 && t2(r2), f2 = i2.slice();\n          return u2 && c2 ? (p(u2, f2, i2, o2, a2), p(u2, i2, f2, o2, a2), p(u2, f2, i2, o2, a2), g(c2, i2, f2, o2, a2), g(c2, f2, i2, o2, a2), g(c2, i2, f2, o2, a2)) : u2 ? (p(u2, i2, f2, o2, a2), p(u2, f2, i2, o2, a2), p(u2, i2, f2, o2, a2)) : c2 && (g(c2, i2, f2, o2, a2), g(c2, f2, i2, o2, a2), g(c2, i2, f2, o2, a2)), n2;\n        };\n      }\n      function p(t2, n2, e2, r2, i2) {\n        for (let o2 = 0, a2 = r2 * i2; o2 < a2; )\n          t2(n2, e2, o2, o2 += r2, 1);\n      }\n      function g(t2, n2, e2, r2, i2) {\n        for (let o2 = 0, a2 = r2 * i2; o2 < r2; ++o2)\n          t2(n2, e2, o2, o2 + a2, r2);\n      }\n      function y(t2) {\n        const n2 = Math.floor(t2);\n        if (n2 === t2)\n          return function(t3) {\n            const n3 = 2 * t3 + 1;\n            return (e3, r3, i2, o2, a2) => {\n              if (!((o2 -= a2) >= i2))\n                return;\n              let u2 = t3 * r3[i2];\n              const c2 = a2 * t3;\n              for (let t4 = i2, n4 = i2 + c2; t4 < n4; t4 += a2)\n                u2 += r3[Math.min(o2, t4)];\n              for (let t4 = i2, f2 = o2; t4 <= f2; t4 += a2)\n                u2 += r3[Math.min(o2, t4 + c2)], e3[t4] = u2 / n3, u2 -= r3[Math.max(i2, t4 - c2)];\n            };\n          }(t2);\n        const e2 = t2 - n2, r2 = 2 * t2 + 1;\n        return (t3, i2, o2, a2, u2) => {\n          if (!((a2 -= u2) >= o2))\n            return;\n          let c2 = n2 * i2[o2];\n          const f2 = u2 * n2, s2 = f2 + u2;\n          for (let t4 = o2, n3 = o2 + f2; t4 < n3; t4 += u2)\n            c2 += i2[Math.min(a2, t4)];\n          for (let n3 = o2, l2 = a2; n3 <= l2; n3 += u2)\n            c2 += i2[Math.min(a2, n3 + f2)], t3[n3] = (c2 + e2 * (i2[Math.max(o2, n3 - s2)] + i2[Math.min(a2, n3 + s2)])) / r2, c2 -= i2[Math.max(o2, n3 - f2)];\n        };\n      }\n      function v(t2, n2) {\n        let e2 = 0;\n        if (void 0 === n2)\n          for (let n3 of t2)\n            null != n3 && (n3 = +n3) >= n3 && ++e2;\n        else {\n          let r2 = -1;\n          for (let i2 of t2)\n            null != (i2 = n2(i2, ++r2, t2)) && (i2 = +i2) >= i2 && ++e2;\n        }\n        return e2;\n      }\n      function _(t2) {\n        return 0 | t2.length;\n      }\n      function b(t2) {\n        return !(t2 > 0);\n      }\n      function m(t2) {\n        return \"object\" != typeof t2 || \"length\" in t2 ? t2 : Array.from(t2);\n      }\n      function x(t2, n2) {\n        let e2, r2 = 0, i2 = 0, o2 = 0;\n        if (void 0 === n2)\n          for (let n3 of t2)\n            null != n3 && (n3 = +n3) >= n3 && (e2 = n3 - i2, i2 += e2 / ++r2, o2 += e2 * (n3 - i2));\n        else {\n          let a2 = -1;\n          for (let u2 of t2)\n            null != (u2 = n2(u2, ++a2, t2)) && (u2 = +u2) >= u2 && (e2 = u2 - i2, i2 += e2 / ++r2, o2 += e2 * (u2 - i2));\n        }\n        if (r2 > 1)\n          return o2 / (r2 - 1);\n      }\n      function w(t2, n2) {\n        const e2 = x(t2, n2);\n        return e2 ? Math.sqrt(e2) : e2;\n      }\n      function M(t2, n2) {\n        let e2, r2;\n        if (void 0 === n2)\n          for (const n3 of t2)\n            null != n3 && (void 0 === e2 ? n3 >= n3 && (e2 = r2 = n3) : (e2 > n3 && (e2 = n3), r2 < n3 && (r2 = n3)));\n        else {\n          let i2 = -1;\n          for (let o2 of t2)\n            null != (o2 = n2(o2, ++i2, t2)) && (void 0 === e2 ? o2 >= o2 && (e2 = r2 = o2) : (e2 > o2 && (e2 = o2), r2 < o2 && (r2 = o2)));\n        }\n        return [e2, r2];\n      }\n      class T {\n        constructor() {\n          this._partials = new Float64Array(32), this._n = 0;\n        }\n        add(t2) {\n          const n2 = this._partials;\n          let e2 = 0;\n          for (let r2 = 0; r2 < this._n && r2 < 32; r2++) {\n            const i2 = n2[r2], o2 = t2 + i2, a2 = Math.abs(t2) < Math.abs(i2) ? t2 - (o2 - i2) : i2 - (o2 - t2);\n            a2 && (n2[e2++] = a2), t2 = o2;\n          }\n          return n2[e2] = t2, this._n = e2 + 1, this;\n        }\n        valueOf() {\n          const t2 = this._partials;\n          let n2, e2, r2, i2 = this._n, o2 = 0;\n          if (i2 > 0) {\n            for (o2 = t2[--i2]; i2 > 0 && (n2 = o2, e2 = t2[--i2], o2 = n2 + e2, r2 = e2 - (o2 - n2), !r2); )\n              ;\n            i2 > 0 && (r2 < 0 && t2[i2 - 1] < 0 || r2 > 0 && t2[i2 - 1] > 0) && (e2 = 2 * r2, n2 = o2 + e2, e2 == n2 - o2 && (o2 = n2));\n          }\n          return o2;\n        }\n      }\n      class InternMap extends Map {\n        constructor(t2, n2 = N) {\n          if (super(), Object.defineProperties(this, { _intern: { value: /* @__PURE__ */ new Map() }, _key: { value: n2 } }), null != t2)\n            for (const [n3, e2] of t2)\n              this.set(n3, e2);\n        }\n        get(t2) {\n          return super.get(A(this, t2));\n        }\n        has(t2) {\n          return super.has(A(this, t2));\n        }\n        set(t2, n2) {\n          return super.set(S(this, t2), n2);\n        }\n        delete(t2) {\n          return super.delete(E(this, t2));\n        }\n      }\n      class InternSet extends Set {\n        constructor(t2, n2 = N) {\n          if (super(), Object.defineProperties(this, { _intern: { value: /* @__PURE__ */ new Map() }, _key: { value: n2 } }), null != t2)\n            for (const n3 of t2)\n              this.add(n3);\n        }\n        has(t2) {\n          return super.has(A(this, t2));\n        }\n        add(t2) {\n          return super.add(S(this, t2));\n        }\n        delete(t2) {\n          return super.delete(E(this, t2));\n        }\n      }\n      function A({ _intern: t2, _key: n2 }, e2) {\n        const r2 = n2(e2);\n        return t2.has(r2) ? t2.get(r2) : e2;\n      }\n      function S({ _intern: t2, _key: n2 }, e2) {\n        const r2 = n2(e2);\n        return t2.has(r2) ? t2.get(r2) : (t2.set(r2, e2), e2);\n      }\n      function E({ _intern: t2, _key: n2 }, e2) {\n        const r2 = n2(e2);\n        return t2.has(r2) && (e2 = t2.get(r2), t2.delete(r2)), e2;\n      }\n      function N(t2) {\n        return null !== t2 && \"object\" == typeof t2 ? t2.valueOf() : t2;\n      }\n      function k(t2) {\n        return t2;\n      }\n      function C(t2, ...n2) {\n        return F(t2, k, k, n2);\n      }\n      function P(t2, ...n2) {\n        return F(t2, Array.from, k, n2);\n      }\n      function z(t2, n2) {\n        for (let e2 = 1, r2 = n2.length; e2 < r2; ++e2)\n          t2 = t2.flatMap((t3) => t3.pop().map(([n3, e3]) => [...t3, n3, e3]));\n        return t2;\n      }\n      function $(t2, n2, ...e2) {\n        return F(t2, k, n2, e2);\n      }\n      function D(t2, n2, ...e2) {\n        return F(t2, Array.from, n2, e2);\n      }\n      function R(t2) {\n        if (1 !== t2.length)\n          throw new Error(\"duplicate key\");\n        return t2[0];\n      }\n      function F(t2, n2, e2, r2) {\n        return function t3(i2, o2) {\n          if (o2 >= r2.length)\n            return e2(i2);\n          const a2 = new InternMap(), u2 = r2[o2++];\n          let c2 = -1;\n          for (const t4 of i2) {\n            const n3 = u2(t4, ++c2, i2), e3 = a2.get(n3);\n            e3 ? e3.push(t4) : a2.set(n3, [t4]);\n          }\n          for (const [n3, e3] of a2)\n            a2.set(n3, t3(e3, o2));\n          return n2(a2);\n        }(t2, 0);\n      }\n      function q(t2, n2) {\n        return Array.from(n2, (n3) => t2[n3]);\n      }\n      function U(t2, ...n2) {\n        if (\"function\" != typeof t2[Symbol.iterator])\n          throw new TypeError(\"values is not iterable\");\n        t2 = Array.from(t2);\n        let [e2] = n2;\n        if (e2 && 2 !== e2.length || n2.length > 1) {\n          const r2 = Uint32Array.from(t2, (t3, n3) => n3);\n          return n2.length > 1 ? (n2 = n2.map((n3) => t2.map(n3)), r2.sort((t3, e3) => {\n            for (const r3 of n2) {\n              const n3 = O(r3[t3], r3[e3]);\n              if (n3)\n                return n3;\n            }\n          })) : (e2 = t2.map(e2), r2.sort((t3, n3) => O(e2[t3], e2[n3]))), q(t2, r2);\n        }\n        return t2.sort(I(e2));\n      }\n      function I(t2 = n) {\n        if (t2 === n)\n          return O;\n        if (\"function\" != typeof t2)\n          throw new TypeError(\"compare is not a function\");\n        return (n2, e2) => {\n          const r2 = t2(n2, e2);\n          return r2 || 0 === r2 ? r2 : (0 === t2(e2, e2)) - (0 === t2(n2, n2));\n        };\n      }\n      function O(t2, n2) {\n        return (null == t2 || !(t2 >= t2)) - (null == n2 || !(n2 >= n2)) || (t2 < n2 ? -1 : t2 > n2 ? 1 : 0);\n      }\n      var B = Array.prototype.slice;\n      function Y(t2) {\n        return () => t2;\n      }\n      const L = Math.sqrt(50), j = Math.sqrt(10), H = Math.sqrt(2);\n      function X(t2, n2, e2) {\n        const r2 = (n2 - t2) / Math.max(0, e2), i2 = Math.floor(Math.log10(r2)), o2 = r2 / Math.pow(10, i2), a2 = o2 >= L ? 10 : o2 >= j ? 5 : o2 >= H ? 2 : 1;\n        let u2, c2, f2;\n        return i2 < 0 ? (f2 = Math.pow(10, -i2) / a2, u2 = Math.round(t2 * f2), c2 = Math.round(n2 * f2), u2 / f2 < t2 && ++u2, c2 / f2 > n2 && --c2, f2 = -f2) : (f2 = Math.pow(10, i2) * a2, u2 = Math.round(t2 / f2), c2 = Math.round(n2 / f2), u2 * f2 < t2 && ++u2, c2 * f2 > n2 && --c2), c2 < u2 && 0.5 <= e2 && e2 < 2 ? X(t2, n2, 2 * e2) : [u2, c2, f2];\n      }\n      function G(t2, n2, e2) {\n        if (!((e2 = +e2) > 0))\n          return [];\n        if ((t2 = +t2) === (n2 = +n2))\n          return [t2];\n        const r2 = n2 < t2, [i2, o2, a2] = r2 ? X(n2, t2, e2) : X(t2, n2, e2);\n        if (!(o2 >= i2))\n          return [];\n        const u2 = o2 - i2 + 1, c2 = new Array(u2);\n        if (r2)\n          if (a2 < 0)\n            for (let t3 = 0; t3 < u2; ++t3)\n              c2[t3] = (o2 - t3) / -a2;\n          else\n            for (let t3 = 0; t3 < u2; ++t3)\n              c2[t3] = (o2 - t3) * a2;\n        else if (a2 < 0)\n          for (let t3 = 0; t3 < u2; ++t3)\n            c2[t3] = (i2 + t3) / -a2;\n        else\n          for (let t3 = 0; t3 < u2; ++t3)\n            c2[t3] = (i2 + t3) * a2;\n        return c2;\n      }\n      function V(t2, n2, e2) {\n        return X(t2 = +t2, n2 = +n2, e2 = +e2)[2];\n      }\n      function W(t2, n2, e2) {\n        e2 = +e2;\n        const r2 = (n2 = +n2) < (t2 = +t2), i2 = r2 ? V(n2, t2, e2) : V(t2, n2, e2);\n        return (r2 ? -1 : 1) * (i2 < 0 ? 1 / -i2 : i2);\n      }\n      function Z(t2, n2, e2) {\n        let r2;\n        for (; ; ) {\n          const i2 = V(t2, n2, e2);\n          if (i2 === r2 || 0 === i2 || !isFinite(i2))\n            return [t2, n2];\n          i2 > 0 ? (t2 = Math.floor(t2 / i2) * i2, n2 = Math.ceil(n2 / i2) * i2) : i2 < 0 && (t2 = Math.ceil(t2 * i2) / i2, n2 = Math.floor(n2 * i2) / i2), r2 = i2;\n        }\n      }\n      function K(t2) {\n        return Math.max(1, Math.ceil(Math.log(v(t2)) / Math.LN2) + 1);\n      }\n      function Q() {\n        var t2 = k, n2 = M, e2 = K;\n        function r2(r3) {\n          Array.isArray(r3) || (r3 = Array.from(r3));\n          var i2, o2, a2, u2 = r3.length, c2 = new Array(u2);\n          for (i2 = 0; i2 < u2; ++i2)\n            c2[i2] = t2(r3[i2], i2, r3);\n          var f2 = n2(c2), l2 = f2[0], h2 = f2[1], d2 = e2(c2, l2, h2);\n          if (!Array.isArray(d2)) {\n            const t3 = h2, e3 = +d2;\n            if (n2 === M && ([l2, h2] = Z(l2, h2, e3)), (d2 = G(l2, h2, e3))[0] <= l2 && (a2 = V(l2, h2, e3)), d2[d2.length - 1] >= h2)\n              if (t3 >= h2 && n2 === M) {\n                const t4 = V(l2, h2, e3);\n                isFinite(t4) && (t4 > 0 ? h2 = (Math.floor(h2 / t4) + 1) * t4 : t4 < 0 && (h2 = (Math.ceil(h2 * -t4) + 1) / -t4));\n              } else\n                d2.pop();\n          }\n          for (var p2 = d2.length, g2 = 0, y2 = p2; d2[g2] <= l2; )\n            ++g2;\n          for (; d2[y2 - 1] > h2; )\n            --y2;\n          (g2 || y2 < p2) && (d2 = d2.slice(g2, y2), p2 = y2 - g2);\n          var v2, _2 = new Array(p2 + 1);\n          for (i2 = 0; i2 <= p2; ++i2)\n            (v2 = _2[i2] = []).x0 = i2 > 0 ? d2[i2 - 1] : l2, v2.x1 = i2 < p2 ? d2[i2] : h2;\n          if (isFinite(a2)) {\n            if (a2 > 0)\n              for (i2 = 0; i2 < u2; ++i2)\n                null != (o2 = c2[i2]) && l2 <= o2 && o2 <= h2 && _2[Math.min(p2, Math.floor((o2 - l2) / a2))].push(r3[i2]);\n            else if (a2 < 0) {\n              for (i2 = 0; i2 < u2; ++i2)\n                if (null != (o2 = c2[i2]) && l2 <= o2 && o2 <= h2) {\n                  const t3 = Math.floor((l2 - o2) * a2);\n                  _2[Math.min(p2, t3 + (d2[t3] <= o2))].push(r3[i2]);\n                }\n            }\n          } else\n            for (i2 = 0; i2 < u2; ++i2)\n              null != (o2 = c2[i2]) && l2 <= o2 && o2 <= h2 && _2[s(d2, o2, 0, p2)].push(r3[i2]);\n          return _2;\n        }\n        return r2.value = function(n3) {\n          return arguments.length ? (t2 = \"function\" == typeof n3 ? n3 : Y(n3), r2) : t2;\n        }, r2.domain = function(t3) {\n          return arguments.length ? (n2 = \"function\" == typeof t3 ? t3 : Y([t3[0], t3[1]]), r2) : n2;\n        }, r2.thresholds = function(t3) {\n          return arguments.length ? (e2 = \"function\" == typeof t3 ? t3 : Y(Array.isArray(t3) ? B.call(t3) : t3), r2) : e2;\n        }, r2;\n      }\n      function J(t2, n2) {\n        let e2;\n        if (void 0 === n2)\n          for (const n3 of t2)\n            null != n3 && (e2 < n3 || void 0 === e2 && n3 >= n3) && (e2 = n3);\n        else {\n          let r2 = -1;\n          for (let i2 of t2)\n            null != (i2 = n2(i2, ++r2, t2)) && (e2 < i2 || void 0 === e2 && i2 >= i2) && (e2 = i2);\n        }\n        return e2;\n      }\n      function tt(t2, n2) {\n        let e2, r2 = -1, i2 = -1;\n        if (void 0 === n2)\n          for (const n3 of t2)\n            ++i2, null != n3 && (e2 < n3 || void 0 === e2 && n3 >= n3) && (e2 = n3, r2 = i2);\n        else\n          for (let o2 of t2)\n            null != (o2 = n2(o2, ++i2, t2)) && (e2 < o2 || void 0 === e2 && o2 >= o2) && (e2 = o2, r2 = i2);\n        return r2;\n      }\n      function nt(t2, n2) {\n        let e2;\n        if (void 0 === n2)\n          for (const n3 of t2)\n            null != n3 && (e2 > n3 || void 0 === e2 && n3 >= n3) && (e2 = n3);\n        else {\n          let r2 = -1;\n          for (let i2 of t2)\n            null != (i2 = n2(i2, ++r2, t2)) && (e2 > i2 || void 0 === e2 && i2 >= i2) && (e2 = i2);\n        }\n        return e2;\n      }\n      function et(t2, n2) {\n        let e2, r2 = -1, i2 = -1;\n        if (void 0 === n2)\n          for (const n3 of t2)\n            ++i2, null != n3 && (e2 > n3 || void 0 === e2 && n3 >= n3) && (e2 = n3, r2 = i2);\n        else\n          for (let o2 of t2)\n            null != (o2 = n2(o2, ++i2, t2)) && (e2 > o2 || void 0 === e2 && o2 >= o2) && (e2 = o2, r2 = i2);\n        return r2;\n      }\n      function rt(t2, n2, e2 = 0, r2 = 1 / 0, i2) {\n        if (n2 = Math.floor(n2), e2 = Math.floor(Math.max(0, e2)), r2 = Math.floor(Math.min(t2.length - 1, r2)), !(e2 <= n2 && n2 <= r2))\n          return t2;\n        for (i2 = void 0 === i2 ? O : I(i2); r2 > e2; ) {\n          if (r2 - e2 > 600) {\n            const o3 = r2 - e2 + 1, a3 = n2 - e2 + 1, u3 = Math.log(o3), c2 = 0.5 * Math.exp(2 * u3 / 3), f2 = 0.5 * Math.sqrt(u3 * c2 * (o3 - c2) / o3) * (a3 - o3 / 2 < 0 ? -1 : 1);\n            rt(t2, n2, Math.max(e2, Math.floor(n2 - a3 * c2 / o3 + f2)), Math.min(r2, Math.floor(n2 + (o3 - a3) * c2 / o3 + f2)), i2);\n          }\n          const o2 = t2[n2];\n          let a2 = e2, u2 = r2;\n          for (it(t2, e2, n2), i2(t2[r2], o2) > 0 && it(t2, e2, r2); a2 < u2; ) {\n            for (it(t2, a2, u2), ++a2, --u2; i2(t2[a2], o2) < 0; )\n              ++a2;\n            for (; i2(t2[u2], o2) > 0; )\n              --u2;\n          }\n          0 === i2(t2[e2], o2) ? it(t2, e2, u2) : (++u2, it(t2, u2, r2)), u2 <= n2 && (e2 = u2 + 1), n2 <= u2 && (r2 = u2 - 1);\n        }\n        return t2;\n      }\n      function it(t2, n2, e2) {\n        const r2 = t2[n2];\n        t2[n2] = t2[e2], t2[e2] = r2;\n      }\n      function ot(t2, e2 = n) {\n        let r2, i2 = false;\n        if (1 === e2.length) {\n          let o2;\n          for (const a2 of t2) {\n            const t3 = e2(a2);\n            (i2 ? n(t3, o2) > 0 : 0 === n(t3, t3)) && (r2 = a2, o2 = t3, i2 = true);\n          }\n        } else\n          for (const n2 of t2)\n            (i2 ? e2(n2, r2) > 0 : 0 === e2(n2, n2)) && (r2 = n2, i2 = true);\n        return r2;\n      }\n      function at(t2, n2, e2) {\n        if (t2 = Float64Array.from(function* (t3, n3) {\n          if (void 0 === n3)\n            for (let n4 of t3)\n              null != n4 && (n4 = +n4) >= n4 && (yield n4);\n          else {\n            let e3 = -1;\n            for (let r3 of t3)\n              null != (r3 = n3(r3, ++e3, t3)) && (r3 = +r3) >= r3 && (yield r3);\n          }\n        }(t2, e2)), (r2 = t2.length) && !isNaN(n2 = +n2)) {\n          if (n2 <= 0 || r2 < 2)\n            return nt(t2);\n          if (n2 >= 1)\n            return J(t2);\n          var r2, i2 = (r2 - 1) * n2, o2 = Math.floor(i2), a2 = J(rt(t2, o2).subarray(0, o2 + 1));\n          return a2 + (nt(t2.subarray(o2 + 1)) - a2) * (i2 - o2);\n        }\n      }\n      function ut(t2, n2, e2 = o) {\n        if ((r2 = t2.length) && !isNaN(n2 = +n2)) {\n          if (n2 <= 0 || r2 < 2)\n            return +e2(t2[0], 0, t2);\n          if (n2 >= 1)\n            return +e2(t2[r2 - 1], r2 - 1, t2);\n          var r2, i2 = (r2 - 1) * n2, a2 = Math.floor(i2), u2 = +e2(t2[a2], a2, t2);\n          return u2 + (+e2(t2[a2 + 1], a2 + 1, t2) - u2) * (i2 - a2);\n        }\n      }\n      function ct(t2, n2, e2 = o) {\n        if (!isNaN(n2 = +n2)) {\n          if (r2 = Float64Array.from(t2, (n3, r3) => o(e2(t2[r3], r3, t2))), n2 <= 0)\n            return et(r2);\n          if (n2 >= 1)\n            return tt(r2);\n          var r2, i2 = Uint32Array.from(t2, (t3, n3) => n3), a2 = r2.length - 1, u2 = Math.floor(a2 * n2);\n          return rt(i2, u2, 0, a2, (t3, n3) => O(r2[t3], r2[n3])), (u2 = ot(i2.subarray(0, u2 + 1), (t3) => r2[t3])) >= 0 ? u2 : -1;\n        }\n      }\n      function ft(t2) {\n        return Array.from(function* (t3) {\n          for (const n2 of t3)\n            yield* n2;\n        }(t2));\n      }\n      function st(t2, n2) {\n        return [t2, n2];\n      }\n      function lt(t2, n2, e2) {\n        t2 = +t2, n2 = +n2, e2 = (i2 = arguments.length) < 2 ? (n2 = t2, t2 = 0, 1) : i2 < 3 ? 1 : +e2;\n        for (var r2 = -1, i2 = 0 | Math.max(0, Math.ceil((n2 - t2) / e2)), o2 = new Array(i2); ++r2 < i2; )\n          o2[r2] = t2 + r2 * e2;\n        return o2;\n      }\n      function ht(t2, e2 = n) {\n        if (1 === e2.length)\n          return et(t2, e2);\n        let r2, i2 = -1, o2 = -1;\n        for (const n2 of t2)\n          ++o2, (i2 < 0 ? 0 === e2(n2, n2) : e2(n2, r2) < 0) && (r2 = n2, i2 = o2);\n        return i2;\n      }\n      var dt = pt(Math.random);\n      function pt(t2) {\n        return function(n2, e2 = 0, r2 = n2.length) {\n          let i2 = r2 - (e2 = +e2);\n          for (; i2; ) {\n            const r3 = t2() * i2-- | 0, o2 = n2[i2 + e2];\n            n2[i2 + e2] = n2[r3 + e2], n2[r3 + e2] = o2;\n          }\n          return n2;\n        };\n      }\n      function gt(t2) {\n        if (!(i2 = t2.length))\n          return [];\n        for (var n2 = -1, e2 = nt(t2, yt), r2 = new Array(e2); ++n2 < e2; )\n          for (var i2, o2 = -1, a2 = r2[n2] = new Array(i2); ++o2 < i2; )\n            a2[o2] = t2[o2][n2];\n        return r2;\n      }\n      function yt(t2) {\n        return t2.length;\n      }\n      function vt(t2) {\n        return t2 instanceof InternSet ? t2 : new InternSet(t2);\n      }\n      function _t(t2, n2) {\n        const e2 = t2[Symbol.iterator](), r2 = /* @__PURE__ */ new Set();\n        for (const t3 of n2) {\n          const n3 = bt(t3);\n          if (r2.has(n3))\n            continue;\n          let i2, o2;\n          for (; { value: i2, done: o2 } = e2.next(); ) {\n            if (o2)\n              return false;\n            const t4 = bt(i2);\n            if (r2.add(t4), Object.is(n3, t4))\n              break;\n          }\n        }\n        return true;\n      }\n      function bt(t2) {\n        return null !== t2 && \"object\" == typeof t2 ? t2.valueOf() : t2;\n      }\n      function mt(t2) {\n        return t2;\n      }\n      var xt = 1, wt = 2, Mt = 3, Tt = 4, At = 1e-6;\n      function St(t2) {\n        return \"translate(\" + t2 + \",0)\";\n      }\n      function Et(t2) {\n        return \"translate(0,\" + t2 + \")\";\n      }\n      function Nt(t2) {\n        return (n2) => +t2(n2);\n      }\n      function kt(t2, n2) {\n        return n2 = Math.max(0, t2.bandwidth() - 2 * n2) / 2, t2.round() && (n2 = Math.round(n2)), (e2) => +t2(e2) + n2;\n      }\n      function Ct() {\n        return !this.__axis;\n      }\n      function Pt(t2, n2) {\n        var e2 = [], r2 = null, i2 = null, o2 = 6, a2 = 6, u2 = 3, c2 = \"undefined\" != typeof window && window.devicePixelRatio > 1 ? 0 : 0.5, f2 = t2 === xt || t2 === Tt ? -1 : 1, s2 = t2 === Tt || t2 === wt ? \"x\" : \"y\", l2 = t2 === xt || t2 === Mt ? St : Et;\n        function h2(h3) {\n          var d2 = null == r2 ? n2.ticks ? n2.ticks.apply(n2, e2) : n2.domain() : r2, p2 = null == i2 ? n2.tickFormat ? n2.tickFormat.apply(n2, e2) : mt : i2, g2 = Math.max(o2, 0) + u2, y2 = n2.range(), v2 = +y2[0] + c2, _2 = +y2[y2.length - 1] + c2, b2 = (n2.bandwidth ? kt : Nt)(n2.copy(), c2), m2 = h3.selection ? h3.selection() : h3, x2 = m2.selectAll(\".domain\").data([null]), w2 = m2.selectAll(\".tick\").data(d2, n2).order(), M2 = w2.exit(), T2 = w2.enter().append(\"g\").attr(\"class\", \"tick\"), A2 = w2.select(\"line\"), S2 = w2.select(\"text\");\n          x2 = x2.merge(x2.enter().insert(\"path\", \".tick\").attr(\"class\", \"domain\").attr(\"stroke\", \"currentColor\")), w2 = w2.merge(T2), A2 = A2.merge(T2.append(\"line\").attr(\"stroke\", \"currentColor\").attr(s2 + \"2\", f2 * o2)), S2 = S2.merge(T2.append(\"text\").attr(\"fill\", \"currentColor\").attr(s2, f2 * g2).attr(\"dy\", t2 === xt ? \"0em\" : t2 === Mt ? \"0.71em\" : \"0.32em\")), h3 !== m2 && (x2 = x2.transition(h3), w2 = w2.transition(h3), A2 = A2.transition(h3), S2 = S2.transition(h3), M2 = M2.transition(h3).attr(\"opacity\", At).attr(\"transform\", function(t3) {\n            return isFinite(t3 = b2(t3)) ? l2(t3 + c2) : this.getAttribute(\"transform\");\n          }), T2.attr(\"opacity\", At).attr(\"transform\", function(t3) {\n            var n3 = this.parentNode.__axis;\n            return l2((n3 && isFinite(n3 = n3(t3)) ? n3 : b2(t3)) + c2);\n          })), M2.remove(), x2.attr(\"d\", t2 === Tt || t2 === wt ? a2 ? \"M\" + f2 * a2 + \",\" + v2 + \"H\" + c2 + \"V\" + _2 + \"H\" + f2 * a2 : \"M\" + c2 + \",\" + v2 + \"V\" + _2 : a2 ? \"M\" + v2 + \",\" + f2 * a2 + \"V\" + c2 + \"H\" + _2 + \"V\" + f2 * a2 : \"M\" + v2 + \",\" + c2 + \"H\" + _2), w2.attr(\"opacity\", 1).attr(\"transform\", function(t3) {\n            return l2(b2(t3) + c2);\n          }), A2.attr(s2 + \"2\", f2 * o2), S2.attr(s2, f2 * g2).text(p2), m2.filter(Ct).attr(\"fill\", \"none\").attr(\"font-size\", 10).attr(\"font-family\", \"sans-serif\").attr(\"text-anchor\", t2 === wt ? \"start\" : t2 === Tt ? \"end\" : \"middle\"), m2.each(function() {\n            this.__axis = b2;\n          });\n        }\n        return h2.scale = function(t3) {\n          return arguments.length ? (n2 = t3, h2) : n2;\n        }, h2.ticks = function() {\n          return e2 = Array.from(arguments), h2;\n        }, h2.tickArguments = function(t3) {\n          return arguments.length ? (e2 = null == t3 ? [] : Array.from(t3), h2) : e2.slice();\n        }, h2.tickValues = function(t3) {\n          return arguments.length ? (r2 = null == t3 ? null : Array.from(t3), h2) : r2 && r2.slice();\n        }, h2.tickFormat = function(t3) {\n          return arguments.length ? (i2 = t3, h2) : i2;\n        }, h2.tickSize = function(t3) {\n          return arguments.length ? (o2 = a2 = +t3, h2) : o2;\n        }, h2.tickSizeInner = function(t3) {\n          return arguments.length ? (o2 = +t3, h2) : o2;\n        }, h2.tickSizeOuter = function(t3) {\n          return arguments.length ? (a2 = +t3, h2) : a2;\n        }, h2.tickPadding = function(t3) {\n          return arguments.length ? (u2 = +t3, h2) : u2;\n        }, h2.offset = function(t3) {\n          return arguments.length ? (c2 = +t3, h2) : c2;\n        }, h2;\n      }\n      var zt = { value: () => {\n      } };\n      function $t() {\n        for (var t2, n2 = 0, e2 = arguments.length, r2 = {}; n2 < e2; ++n2) {\n          if (!(t2 = arguments[n2] + \"\") || t2 in r2 || /[\\s.]/.test(t2))\n            throw new Error(\"illegal type: \" + t2);\n          r2[t2] = [];\n        }\n        return new Dt(r2);\n      }\n      function Dt(t2) {\n        this._ = t2;\n      }\n      function Rt(t2, n2) {\n        for (var e2, r2 = 0, i2 = t2.length; r2 < i2; ++r2)\n          if ((e2 = t2[r2]).name === n2)\n            return e2.value;\n      }\n      function Ft(t2, n2, e2) {\n        for (var r2 = 0, i2 = t2.length; r2 < i2; ++r2)\n          if (t2[r2].name === n2) {\n            t2[r2] = zt, t2 = t2.slice(0, r2).concat(t2.slice(r2 + 1));\n            break;\n          }\n        return null != e2 && t2.push({ name: n2, value: e2 }), t2;\n      }\n      Dt.prototype = $t.prototype = { constructor: Dt, on: function(t2, n2) {\n        var e2, r2, i2 = this._, o2 = (r2 = i2, (t2 + \"\").trim().split(/^|\\s+/).map(function(t3) {\n          var n3 = \"\", e3 = t3.indexOf(\".\");\n          if (e3 >= 0 && (n3 = t3.slice(e3 + 1), t3 = t3.slice(0, e3)), t3 && !r2.hasOwnProperty(t3))\n            throw new Error(\"unknown type: \" + t3);\n          return { type: t3, name: n3 };\n        })), a2 = -1, u2 = o2.length;\n        if (!(arguments.length < 2)) {\n          if (null != n2 && \"function\" != typeof n2)\n            throw new Error(\"invalid callback: \" + n2);\n          for (; ++a2 < u2; )\n            if (e2 = (t2 = o2[a2]).type)\n              i2[e2] = Ft(i2[e2], t2.name, n2);\n            else if (null == n2)\n              for (e2 in i2)\n                i2[e2] = Ft(i2[e2], t2.name, null);\n          return this;\n        }\n        for (; ++a2 < u2; )\n          if ((e2 = (t2 = o2[a2]).type) && (e2 = Rt(i2[e2], t2.name)))\n            return e2;\n      }, copy: function() {\n        var t2 = {}, n2 = this._;\n        for (var e2 in n2)\n          t2[e2] = n2[e2].slice();\n        return new Dt(t2);\n      }, call: function(t2, n2) {\n        if ((e2 = arguments.length - 2) > 0)\n          for (var e2, r2, i2 = new Array(e2), o2 = 0; o2 < e2; ++o2)\n            i2[o2] = arguments[o2 + 2];\n        if (!this._.hasOwnProperty(t2))\n          throw new Error(\"unknown type: \" + t2);\n        for (o2 = 0, e2 = (r2 = this._[t2]).length; o2 < e2; ++o2)\n          r2[o2].value.apply(n2, i2);\n      }, apply: function(t2, n2, e2) {\n        if (!this._.hasOwnProperty(t2))\n          throw new Error(\"unknown type: \" + t2);\n        for (var r2 = this._[t2], i2 = 0, o2 = r2.length; i2 < o2; ++i2)\n          r2[i2].value.apply(n2, e2);\n      } };\n      var qt = \"http://www.w3.org/1999/xhtml\", Ut = { svg: \"http://www.w3.org/2000/svg\", xhtml: qt, xlink: \"http://www.w3.org/1999/xlink\", xml: \"http://www.w3.org/XML/1998/namespace\", xmlns: \"http://www.w3.org/2000/xmlns/\" };\n      function It(t2) {\n        var n2 = t2 += \"\", e2 = n2.indexOf(\":\");\n        return e2 >= 0 && \"xmlns\" !== (n2 = t2.slice(0, e2)) && (t2 = t2.slice(e2 + 1)), Ut.hasOwnProperty(n2) ? { space: Ut[n2], local: t2 } : t2;\n      }\n      function Ot(t2) {\n        return function() {\n          var n2 = this.ownerDocument, e2 = this.namespaceURI;\n          return e2 === qt && n2.documentElement.namespaceURI === qt ? n2.createElement(t2) : n2.createElementNS(e2, t2);\n        };\n      }\n      function Bt(t2) {\n        return function() {\n          return this.ownerDocument.createElementNS(t2.space, t2.local);\n        };\n      }\n      function Yt(t2) {\n        var n2 = It(t2);\n        return (n2.local ? Bt : Ot)(n2);\n      }\n      function Lt() {\n      }\n      function jt(t2) {\n        return null == t2 ? Lt : function() {\n          return this.querySelector(t2);\n        };\n      }\n      function Ht(t2) {\n        return null == t2 ? [] : Array.isArray(t2) ? t2 : Array.from(t2);\n      }\n      function Xt() {\n        return [];\n      }\n      function Gt(t2) {\n        return null == t2 ? Xt : function() {\n          return this.querySelectorAll(t2);\n        };\n      }\n      function Vt(t2) {\n        return function() {\n          return this.matches(t2);\n        };\n      }\n      function Wt(t2) {\n        return function(n2) {\n          return n2.matches(t2);\n        };\n      }\n      var Zt = Array.prototype.find;\n      function Kt() {\n        return this.firstElementChild;\n      }\n      var Qt = Array.prototype.filter;\n      function Jt() {\n        return Array.from(this.children);\n      }\n      function tn(t2) {\n        return new Array(t2.length);\n      }\n      function nn(t2, n2) {\n        this.ownerDocument = t2.ownerDocument, this.namespaceURI = t2.namespaceURI, this._next = null, this._parent = t2, this.__data__ = n2;\n      }\n      function en(t2, n2, e2, r2, i2, o2) {\n        for (var a2, u2 = 0, c2 = n2.length, f2 = o2.length; u2 < f2; ++u2)\n          (a2 = n2[u2]) ? (a2.__data__ = o2[u2], r2[u2] = a2) : e2[u2] = new nn(t2, o2[u2]);\n        for (; u2 < c2; ++u2)\n          (a2 = n2[u2]) && (i2[u2] = a2);\n      }\n      function rn(t2, n2, e2, r2, i2, o2, a2) {\n        var u2, c2, f2, s2 = /* @__PURE__ */ new Map(), l2 = n2.length, h2 = o2.length, d2 = new Array(l2);\n        for (u2 = 0; u2 < l2; ++u2)\n          (c2 = n2[u2]) && (d2[u2] = f2 = a2.call(c2, c2.__data__, u2, n2) + \"\", s2.has(f2) ? i2[u2] = c2 : s2.set(f2, c2));\n        for (u2 = 0; u2 < h2; ++u2)\n          f2 = a2.call(t2, o2[u2], u2, o2) + \"\", (c2 = s2.get(f2)) ? (r2[u2] = c2, c2.__data__ = o2[u2], s2.delete(f2)) : e2[u2] = new nn(t2, o2[u2]);\n        for (u2 = 0; u2 < l2; ++u2)\n          (c2 = n2[u2]) && s2.get(d2[u2]) === c2 && (i2[u2] = c2);\n      }\n      function on(t2) {\n        return t2.__data__;\n      }\n      function an(t2) {\n        return \"object\" == typeof t2 && \"length\" in t2 ? t2 : Array.from(t2);\n      }\n      function un(t2, n2) {\n        return t2 < n2 ? -1 : t2 > n2 ? 1 : t2 >= n2 ? 0 : NaN;\n      }\n      function cn(t2) {\n        return function() {\n          this.removeAttribute(t2);\n        };\n      }\n      function fn(t2) {\n        return function() {\n          this.removeAttributeNS(t2.space, t2.local);\n        };\n      }\n      function sn(t2, n2) {\n        return function() {\n          this.setAttribute(t2, n2);\n        };\n      }\n      function ln(t2, n2) {\n        return function() {\n          this.setAttributeNS(t2.space, t2.local, n2);\n        };\n      }\n      function hn(t2, n2) {\n        return function() {\n          var e2 = n2.apply(this, arguments);\n          null == e2 ? this.removeAttribute(t2) : this.setAttribute(t2, e2);\n        };\n      }\n      function dn(t2, n2) {\n        return function() {\n          var e2 = n2.apply(this, arguments);\n          null == e2 ? this.removeAttributeNS(t2.space, t2.local) : this.setAttributeNS(t2.space, t2.local, e2);\n        };\n      }\n      function pn(t2) {\n        return t2.ownerDocument && t2.ownerDocument.defaultView || t2.document && t2 || t2.defaultView;\n      }\n      function gn(t2) {\n        return function() {\n          this.style.removeProperty(t2);\n        };\n      }\n      function yn(t2, n2, e2) {\n        return function() {\n          this.style.setProperty(t2, n2, e2);\n        };\n      }\n      function vn(t2, n2, e2) {\n        return function() {\n          var r2 = n2.apply(this, arguments);\n          null == r2 ? this.style.removeProperty(t2) : this.style.setProperty(t2, r2, e2);\n        };\n      }\n      function _n(t2, n2) {\n        return t2.style.getPropertyValue(n2) || pn(t2).getComputedStyle(t2, null).getPropertyValue(n2);\n      }\n      function bn(t2) {\n        return function() {\n          delete this[t2];\n        };\n      }\n      function mn(t2, n2) {\n        return function() {\n          this[t2] = n2;\n        };\n      }\n      function xn(t2, n2) {\n        return function() {\n          var e2 = n2.apply(this, arguments);\n          null == e2 ? delete this[t2] : this[t2] = e2;\n        };\n      }\n      function wn(t2) {\n        return t2.trim().split(/^|\\s+/);\n      }\n      function Mn(t2) {\n        return t2.classList || new Tn(t2);\n      }\n      function Tn(t2) {\n        this._node = t2, this._names = wn(t2.getAttribute(\"class\") || \"\");\n      }\n      function An(t2, n2) {\n        for (var e2 = Mn(t2), r2 = -1, i2 = n2.length; ++r2 < i2; )\n          e2.add(n2[r2]);\n      }\n      function Sn(t2, n2) {\n        for (var e2 = Mn(t2), r2 = -1, i2 = n2.length; ++r2 < i2; )\n          e2.remove(n2[r2]);\n      }\n      function En(t2) {\n        return function() {\n          An(this, t2);\n        };\n      }\n      function Nn(t2) {\n        return function() {\n          Sn(this, t2);\n        };\n      }\n      function kn(t2, n2) {\n        return function() {\n          (n2.apply(this, arguments) ? An : Sn)(this, t2);\n        };\n      }\n      function Cn() {\n        this.textContent = \"\";\n      }\n      function Pn(t2) {\n        return function() {\n          this.textContent = t2;\n        };\n      }\n      function zn(t2) {\n        return function() {\n          var n2 = t2.apply(this, arguments);\n          this.textContent = null == n2 ? \"\" : n2;\n        };\n      }\n      function $n() {\n        this.innerHTML = \"\";\n      }\n      function Dn(t2) {\n        return function() {\n          this.innerHTML = t2;\n        };\n      }\n      function Rn(t2) {\n        return function() {\n          var n2 = t2.apply(this, arguments);\n          this.innerHTML = null == n2 ? \"\" : n2;\n        };\n      }\n      function Fn() {\n        this.nextSibling && this.parentNode.appendChild(this);\n      }\n      function qn() {\n        this.previousSibling && this.parentNode.insertBefore(this, this.parentNode.firstChild);\n      }\n      function Un() {\n        return null;\n      }\n      function In() {\n        var t2 = this.parentNode;\n        t2 && t2.removeChild(this);\n      }\n      function On() {\n        var t2 = this.cloneNode(false), n2 = this.parentNode;\n        return n2 ? n2.insertBefore(t2, this.nextSibling) : t2;\n      }\n      function Bn() {\n        var t2 = this.cloneNode(true), n2 = this.parentNode;\n        return n2 ? n2.insertBefore(t2, this.nextSibling) : t2;\n      }\n      function Yn(t2) {\n        return function() {\n          var n2 = this.__on;\n          if (n2) {\n            for (var e2, r2 = 0, i2 = -1, o2 = n2.length; r2 < o2; ++r2)\n              e2 = n2[r2], t2.type && e2.type !== t2.type || e2.name !== t2.name ? n2[++i2] = e2 : this.removeEventListener(e2.type, e2.listener, e2.options);\n            ++i2 ? n2.length = i2 : delete this.__on;\n          }\n        };\n      }\n      function Ln(t2, n2, e2) {\n        return function() {\n          var r2, i2 = this.__on, o2 = /* @__PURE__ */ function(t3) {\n            return function(n3) {\n              t3.call(this, n3, this.__data__);\n            };\n          }(n2);\n          if (i2) {\n            for (var a2 = 0, u2 = i2.length; a2 < u2; ++a2)\n              if ((r2 = i2[a2]).type === t2.type && r2.name === t2.name)\n                return this.removeEventListener(r2.type, r2.listener, r2.options), this.addEventListener(r2.type, r2.listener = o2, r2.options = e2), void (r2.value = n2);\n          }\n          this.addEventListener(t2.type, o2, e2), r2 = { type: t2.type, name: t2.name, value: n2, listener: o2, options: e2 }, i2 ? i2.push(r2) : this.__on = [r2];\n        };\n      }\n      function jn(t2, n2, e2) {\n        var r2 = pn(t2), i2 = r2.CustomEvent;\n        \"function\" == typeof i2 ? i2 = new i2(n2, e2) : (i2 = r2.document.createEvent(\"Event\"), e2 ? (i2.initEvent(n2, e2.bubbles, e2.cancelable), i2.detail = e2.detail) : i2.initEvent(n2, false, false)), t2.dispatchEvent(i2);\n      }\n      function Hn(t2, n2) {\n        return function() {\n          return jn(this, t2, n2);\n        };\n      }\n      function Xn(t2, n2) {\n        return function() {\n          return jn(this, t2, n2.apply(this, arguments));\n        };\n      }\n      nn.prototype = { constructor: nn, appendChild: function(t2) {\n        return this._parent.insertBefore(t2, this._next);\n      }, insertBefore: function(t2, n2) {\n        return this._parent.insertBefore(t2, n2);\n      }, querySelector: function(t2) {\n        return this._parent.querySelector(t2);\n      }, querySelectorAll: function(t2) {\n        return this._parent.querySelectorAll(t2);\n      } }, Tn.prototype = { add: function(t2) {\n        this._names.indexOf(t2) < 0 && (this._names.push(t2), this._node.setAttribute(\"class\", this._names.join(\" \")));\n      }, remove: function(t2) {\n        var n2 = this._names.indexOf(t2);\n        n2 >= 0 && (this._names.splice(n2, 1), this._node.setAttribute(\"class\", this._names.join(\" \")));\n      }, contains: function(t2) {\n        return this._names.indexOf(t2) >= 0;\n      } };\n      var Gn = [null];\n      function Vn(t2, n2) {\n        this._groups = t2, this._parents = n2;\n      }\n      function Wn() {\n        return new Vn([[document.documentElement]], Gn);\n      }\n      function Zn(t2) {\n        return \"string\" == typeof t2 ? new Vn([[document.querySelector(t2)]], [document.documentElement]) : new Vn([[t2]], Gn);\n      }\n      Vn.prototype = Wn.prototype = { constructor: Vn, select: function(t2) {\n        \"function\" != typeof t2 && (t2 = jt(t2));\n        for (var n2 = this._groups, e2 = n2.length, r2 = new Array(e2), i2 = 0; i2 < e2; ++i2)\n          for (var o2, a2, u2 = n2[i2], c2 = u2.length, f2 = r2[i2] = new Array(c2), s2 = 0; s2 < c2; ++s2)\n            (o2 = u2[s2]) && (a2 = t2.call(o2, o2.__data__, s2, u2)) && (\"__data__\" in o2 && (a2.__data__ = o2.__data__), f2[s2] = a2);\n        return new Vn(r2, this._parents);\n      }, selectAll: function(t2) {\n        t2 = \"function\" == typeof t2 ? /* @__PURE__ */ function(t3) {\n          return function() {\n            return Ht(t3.apply(this, arguments));\n          };\n        }(t2) : Gt(t2);\n        for (var n2 = this._groups, e2 = n2.length, r2 = [], i2 = [], o2 = 0; o2 < e2; ++o2)\n          for (var a2, u2 = n2[o2], c2 = u2.length, f2 = 0; f2 < c2; ++f2)\n            (a2 = u2[f2]) && (r2.push(t2.call(a2, a2.__data__, f2, u2)), i2.push(a2));\n        return new Vn(r2, i2);\n      }, selectChild: function(t2) {\n        return this.select(null == t2 ? Kt : /* @__PURE__ */ function(t3) {\n          return function() {\n            return Zt.call(this.children, t3);\n          };\n        }(\"function\" == typeof t2 ? t2 : Wt(t2)));\n      }, selectChildren: function(t2) {\n        return this.selectAll(null == t2 ? Jt : /* @__PURE__ */ function(t3) {\n          return function() {\n            return Qt.call(this.children, t3);\n          };\n        }(\"function\" == typeof t2 ? t2 : Wt(t2)));\n      }, filter: function(t2) {\n        \"function\" != typeof t2 && (t2 = Vt(t2));\n        for (var n2 = this._groups, e2 = n2.length, r2 = new Array(e2), i2 = 0; i2 < e2; ++i2)\n          for (var o2, a2 = n2[i2], u2 = a2.length, c2 = r2[i2] = [], f2 = 0; f2 < u2; ++f2)\n            (o2 = a2[f2]) && t2.call(o2, o2.__data__, f2, a2) && c2.push(o2);\n        return new Vn(r2, this._parents);\n      }, data: function(t2, n2) {\n        if (!arguments.length)\n          return Array.from(this, on);\n        var e2 = n2 ? rn : en, r2 = this._parents, i2 = this._groups;\n        \"function\" != typeof t2 && (t2 = /* @__PURE__ */ function(t3) {\n          return function() {\n            return t3;\n          };\n        }(t2));\n        for (var o2 = i2.length, a2 = new Array(o2), u2 = new Array(o2), c2 = new Array(o2), f2 = 0; f2 < o2; ++f2) {\n          var s2 = r2[f2], l2 = i2[f2], h2 = l2.length, d2 = an(t2.call(s2, s2 && s2.__data__, f2, r2)), p2 = d2.length, g2 = u2[f2] = new Array(p2), y2 = a2[f2] = new Array(p2);\n          e2(s2, l2, g2, y2, c2[f2] = new Array(h2), d2, n2);\n          for (var v2, _2, b2 = 0, m2 = 0; b2 < p2; ++b2)\n            if (v2 = g2[b2]) {\n              for (b2 >= m2 && (m2 = b2 + 1); !(_2 = y2[m2]) && ++m2 < p2; )\n                ;\n              v2._next = _2 || null;\n            }\n        }\n        return (a2 = new Vn(a2, r2))._enter = u2, a2._exit = c2, a2;\n      }, enter: function() {\n        return new Vn(this._enter || this._groups.map(tn), this._parents);\n      }, exit: function() {\n        return new Vn(this._exit || this._groups.map(tn), this._parents);\n      }, join: function(t2, n2, e2) {\n        var r2 = this.enter(), i2 = this, o2 = this.exit();\n        return \"function\" == typeof t2 ? (r2 = t2(r2)) && (r2 = r2.selection()) : r2 = r2.append(t2 + \"\"), null != n2 && (i2 = n2(i2)) && (i2 = i2.selection()), null == e2 ? o2.remove() : e2(o2), r2 && i2 ? r2.merge(i2).order() : i2;\n      }, merge: function(t2) {\n        for (var n2 = t2.selection ? t2.selection() : t2, e2 = this._groups, r2 = n2._groups, i2 = e2.length, o2 = r2.length, a2 = Math.min(i2, o2), u2 = new Array(i2), c2 = 0; c2 < a2; ++c2)\n          for (var f2, s2 = e2[c2], l2 = r2[c2], h2 = s2.length, d2 = u2[c2] = new Array(h2), p2 = 0; p2 < h2; ++p2)\n            (f2 = s2[p2] || l2[p2]) && (d2[p2] = f2);\n        for (; c2 < i2; ++c2)\n          u2[c2] = e2[c2];\n        return new Vn(u2, this._parents);\n      }, selection: function() {\n        return this;\n      }, order: function() {\n        for (var t2 = this._groups, n2 = -1, e2 = t2.length; ++n2 < e2; )\n          for (var r2, i2 = t2[n2], o2 = i2.length - 1, a2 = i2[o2]; --o2 >= 0; )\n            (r2 = i2[o2]) && (a2 && 4 ^ r2.compareDocumentPosition(a2) && a2.parentNode.insertBefore(r2, a2), a2 = r2);\n        return this;\n      }, sort: function(t2) {\n        function n2(n3, e3) {\n          return n3 && e3 ? t2(n3.__data__, e3.__data__) : !n3 - !e3;\n        }\n        t2 || (t2 = un);\n        for (var e2 = this._groups, r2 = e2.length, i2 = new Array(r2), o2 = 0; o2 < r2; ++o2) {\n          for (var a2, u2 = e2[o2], c2 = u2.length, f2 = i2[o2] = new Array(c2), s2 = 0; s2 < c2; ++s2)\n            (a2 = u2[s2]) && (f2[s2] = a2);\n          f2.sort(n2);\n        }\n        return new Vn(i2, this._parents).order();\n      }, call: function() {\n        var t2 = arguments[0];\n        return arguments[0] = this, t2.apply(null, arguments), this;\n      }, nodes: function() {\n        return Array.from(this);\n      }, node: function() {\n        for (var t2 = this._groups, n2 = 0, e2 = t2.length; n2 < e2; ++n2)\n          for (var r2 = t2[n2], i2 = 0, o2 = r2.length; i2 < o2; ++i2) {\n            var a2 = r2[i2];\n            if (a2)\n              return a2;\n          }\n        return null;\n      }, size: function() {\n        let t2 = 0;\n        for (const n2 of this)\n          ++t2;\n        return t2;\n      }, empty: function() {\n        return !this.node();\n      }, each: function(t2) {\n        for (var n2 = this._groups, e2 = 0, r2 = n2.length; e2 < r2; ++e2)\n          for (var i2, o2 = n2[e2], a2 = 0, u2 = o2.length; a2 < u2; ++a2)\n            (i2 = o2[a2]) && t2.call(i2, i2.__data__, a2, o2);\n        return this;\n      }, attr: function(t2, n2) {\n        var e2 = It(t2);\n        if (arguments.length < 2) {\n          var r2 = this.node();\n          return e2.local ? r2.getAttributeNS(e2.space, e2.local) : r2.getAttribute(e2);\n        }\n        return this.each((null == n2 ? e2.local ? fn : cn : \"function\" == typeof n2 ? e2.local ? dn : hn : e2.local ? ln : sn)(e2, n2));\n      }, style: function(t2, n2, e2) {\n        return arguments.length > 1 ? this.each((null == n2 ? gn : \"function\" == typeof n2 ? vn : yn)(t2, n2, null == e2 ? \"\" : e2)) : _n(this.node(), t2);\n      }, property: function(t2, n2) {\n        return arguments.length > 1 ? this.each((null == n2 ? bn : \"function\" == typeof n2 ? xn : mn)(t2, n2)) : this.node()[t2];\n      }, classed: function(t2, n2) {\n        var e2 = wn(t2 + \"\");\n        if (arguments.length < 2) {\n          for (var r2 = Mn(this.node()), i2 = -1, o2 = e2.length; ++i2 < o2; )\n            if (!r2.contains(e2[i2]))\n              return false;\n          return true;\n        }\n        return this.each((\"function\" == typeof n2 ? kn : n2 ? En : Nn)(e2, n2));\n      }, text: function(t2) {\n        return arguments.length ? this.each(null == t2 ? Cn : (\"function\" == typeof t2 ? zn : Pn)(t2)) : this.node().textContent;\n      }, html: function(t2) {\n        return arguments.length ? this.each(null == t2 ? $n : (\"function\" == typeof t2 ? Rn : Dn)(t2)) : this.node().innerHTML;\n      }, raise: function() {\n        return this.each(Fn);\n      }, lower: function() {\n        return this.each(qn);\n      }, append: function(t2) {\n        var n2 = \"function\" == typeof t2 ? t2 : Yt(t2);\n        return this.select(function() {\n          return this.appendChild(n2.apply(this, arguments));\n        });\n      }, insert: function(t2, n2) {\n        var e2 = \"function\" == typeof t2 ? t2 : Yt(t2), r2 = null == n2 ? Un : \"function\" == typeof n2 ? n2 : jt(n2);\n        return this.select(function() {\n          return this.insertBefore(e2.apply(this, arguments), r2.apply(this, arguments) || null);\n        });\n      }, remove: function() {\n        return this.each(In);\n      }, clone: function(t2) {\n        return this.select(t2 ? Bn : On);\n      }, datum: function(t2) {\n        return arguments.length ? this.property(\"__data__\", t2) : this.node().__data__;\n      }, on: function(t2, n2, e2) {\n        var r2, i2, o2 = function(t3) {\n          return t3.trim().split(/^|\\s+/).map(function(t4) {\n            var n3 = \"\", e3 = t4.indexOf(\".\");\n            return e3 >= 0 && (n3 = t4.slice(e3 + 1), t4 = t4.slice(0, e3)), { type: t4, name: n3 };\n          });\n        }(t2 + \"\"), a2 = o2.length;\n        if (!(arguments.length < 2)) {\n          for (u2 = n2 ? Ln : Yn, r2 = 0; r2 < a2; ++r2)\n            this.each(u2(o2[r2], n2, e2));\n          return this;\n        }\n        var u2 = this.node().__on;\n        if (u2) {\n          for (var c2, f2 = 0, s2 = u2.length; f2 < s2; ++f2)\n            for (r2 = 0, c2 = u2[f2]; r2 < a2; ++r2)\n              if ((i2 = o2[r2]).type === c2.type && i2.name === c2.name)\n                return c2.value;\n        }\n      }, dispatch: function(t2, n2) {\n        return this.each((\"function\" == typeof n2 ? Xn : Hn)(t2, n2));\n      }, [Symbol.iterator]: function* () {\n        for (var t2 = this._groups, n2 = 0, e2 = t2.length; n2 < e2; ++n2)\n          for (var r2, i2 = t2[n2], o2 = 0, a2 = i2.length; o2 < a2; ++o2)\n            (r2 = i2[o2]) && (yield r2);\n      } };\n      var Kn = 0;\n      function Qn() {\n        return new Jn();\n      }\n      function Jn() {\n        this._ = \"@\" + (++Kn).toString(36);\n      }\n      function te(t2) {\n        let n2;\n        for (; n2 = t2.sourceEvent; )\n          t2 = n2;\n        return t2;\n      }\n      function ne(t2, n2) {\n        if (t2 = te(t2), void 0 === n2 && (n2 = t2.currentTarget), n2) {\n          var e2 = n2.ownerSVGElement || n2;\n          if (e2.createSVGPoint) {\n            var r2 = e2.createSVGPoint();\n            return r2.x = t2.clientX, r2.y = t2.clientY, [(r2 = r2.matrixTransform(n2.getScreenCTM().inverse())).x, r2.y];\n          }\n          if (n2.getBoundingClientRect) {\n            var i2 = n2.getBoundingClientRect();\n            return [t2.clientX - i2.left - n2.clientLeft, t2.clientY - i2.top - n2.clientTop];\n          }\n        }\n        return [t2.pageX, t2.pageY];\n      }\n      Jn.prototype = Qn.prototype = { constructor: Jn, get: function(t2) {\n        for (var n2 = this._; !(n2 in t2); )\n          if (!(t2 = t2.parentNode))\n            return;\n        return t2[n2];\n      }, set: function(t2, n2) {\n        return t2[this._] = n2;\n      }, remove: function(t2) {\n        return this._ in t2 && delete t2[this._];\n      }, toString: function() {\n        return this._;\n      } };\n      const ee = { passive: false }, re = { capture: true, passive: false };\n      function ie(t2) {\n        t2.stopImmediatePropagation();\n      }\n      function oe(t2) {\n        t2.preventDefault(), t2.stopImmediatePropagation();\n      }\n      function ae(t2) {\n        var n2 = t2.document.documentElement, e2 = Zn(t2).on(\"dragstart.drag\", oe, re);\n        \"onselectstart\" in n2 ? e2.on(\"selectstart.drag\", oe, re) : (n2.__noselect = n2.style.MozUserSelect, n2.style.MozUserSelect = \"none\");\n      }\n      function ue(t2, n2) {\n        var e2 = t2.document.documentElement, r2 = Zn(t2).on(\"dragstart.drag\", null);\n        n2 && (r2.on(\"click.drag\", oe, re), setTimeout(function() {\n          r2.on(\"click.drag\", null);\n        }, 0)), \"onselectstart\" in e2 ? r2.on(\"selectstart.drag\", null) : (e2.style.MozUserSelect = e2.__noselect, delete e2.__noselect);\n      }\n      var ce = (t2) => () => t2;\n      function fe(t2, { sourceEvent: n2, subject: e2, target: r2, identifier: i2, active: o2, x: a2, y: u2, dx: c2, dy: f2, dispatch: s2 }) {\n        Object.defineProperties(this, { type: { value: t2, enumerable: true, configurable: true }, sourceEvent: { value: n2, enumerable: true, configurable: true }, subject: { value: e2, enumerable: true, configurable: true }, target: { value: r2, enumerable: true, configurable: true }, identifier: { value: i2, enumerable: true, configurable: true }, active: { value: o2, enumerable: true, configurable: true }, x: { value: a2, enumerable: true, configurable: true }, y: { value: u2, enumerable: true, configurable: true }, dx: { value: c2, enumerable: true, configurable: true }, dy: { value: f2, enumerable: true, configurable: true }, _: { value: s2 } });\n      }\n      function se(t2) {\n        return !t2.ctrlKey && !t2.button;\n      }\n      function le() {\n        return this.parentNode;\n      }\n      function he(t2, n2) {\n        return null == n2 ? { x: t2.x, y: t2.y } : n2;\n      }\n      function de() {\n        return navigator.maxTouchPoints || \"ontouchstart\" in this;\n      }\n      function pe(t2, n2, e2) {\n        t2.prototype = n2.prototype = e2, e2.constructor = t2;\n      }\n      function ge(t2, n2) {\n        var e2 = Object.create(t2.prototype);\n        for (var r2 in n2)\n          e2[r2] = n2[r2];\n        return e2;\n      }\n      function ye() {\n      }\n      fe.prototype.on = function() {\n        var t2 = this._.on.apply(this._, arguments);\n        return t2 === this._ ? this : t2;\n      };\n      var ve = 0.7, _e = 1 / ve, be = \"\\\\s*([+-]?\\\\d+)\\\\s*\", me = \"\\\\s*([+-]?(?:\\\\d*\\\\.)?\\\\d+(?:[eE][+-]?\\\\d+)?)\\\\s*\", xe = \"\\\\s*([+-]?(?:\\\\d*\\\\.)?\\\\d+(?:[eE][+-]?\\\\d+)?)%\\\\s*\", we = /^#([0-9a-f]{3,8})$/, Me = new RegExp(`^rgb\\\\(${be},${be},${be}\\\\)$`), Te = new RegExp(`^rgb\\\\(${xe},${xe},${xe}\\\\)$`), Ae = new RegExp(`^rgba\\\\(${be},${be},${be},${me}\\\\)$`), Se = new RegExp(`^rgba\\\\(${xe},${xe},${xe},${me}\\\\)$`), Ee = new RegExp(`^hsl\\\\(${me},${xe},${xe}\\\\)$`), Ne = new RegExp(`^hsla\\\\(${me},${xe},${xe},${me}\\\\)$`), ke = { aliceblue: 15792383, antiquewhite: 16444375, aqua: 65535, aquamarine: 8388564, azure: 15794175, beige: 16119260, bisque: 16770244, black: 0, blanchedalmond: 16772045, blue: 255, blueviolet: 9055202, brown: 10824234, burlywood: 14596231, cadetblue: 6266528, chartreuse: 8388352, chocolate: 13789470, coral: 16744272, cornflowerblue: 6591981, cornsilk: 16775388, crimson: 14423100, cyan: 65535, darkblue: 139, darkcyan: 35723, darkgoldenrod: 12092939, darkgray: 11119017, darkgreen: 25600, darkgrey: 11119017, darkkhaki: 12433259, darkmagenta: 9109643, darkolivegreen: 5597999, darkorange: 16747520, darkorchid: 10040012, darkred: 9109504, darksalmon: 15308410, darkseagreen: 9419919, darkslateblue: 4734347, darkslategray: 3100495, darkslategrey: 3100495, darkturquoise: 52945, darkviolet: 9699539, deeppink: 16716947, deepskyblue: 49151, dimgray: 6908265, dimgrey: 6908265, dodgerblue: 2003199, firebrick: 11674146, floralwhite: 16775920, forestgreen: 2263842, fuchsia: 16711935, gainsboro: 14474460, ghostwhite: 16316671, gold: 16766720, goldenrod: 14329120, gray: 8421504, green: 32768, greenyellow: 11403055, grey: 8421504, honeydew: 15794160, hotpink: 16738740, indianred: 13458524, indigo: 4915330, ivory: 16777200, khaki: 15787660, lavender: 15132410, lavenderblush: 16773365, lawngreen: 8190976, lemonchiffon: 16775885, lightblue: 11393254, lightcoral: 15761536, lightcyan: 14745599, lightgoldenrodyellow: 16448210, lightgray: 13882323, lightgreen: 9498256, lightgrey: 13882323, lightpink: 16758465, lightsalmon: 16752762, lightseagreen: 2142890, lightskyblue: 8900346, lightslategray: 7833753, lightslategrey: 7833753, lightsteelblue: 11584734, lightyellow: 16777184, lime: 65280, limegreen: 3329330, linen: 16445670, magenta: 16711935, maroon: 8388608, mediumaquamarine: 6737322, mediumblue: 205, mediumorchid: 12211667, mediumpurple: 9662683, mediumseagreen: 3978097, mediumslateblue: 8087790, mediumspringgreen: 64154, mediumturquoise: 4772300, mediumvioletred: 13047173, midnightblue: 1644912, mintcream: 16121850, mistyrose: 16770273, moccasin: 16770229, navajowhite: 16768685, navy: 128, oldlace: 16643558, olive: 8421376, olivedrab: 7048739, orange: 16753920, orangered: 16729344, orchid: 14315734, palegoldenrod: 15657130, palegreen: 10025880, paleturquoise: 11529966, palevioletred: 14381203, papayawhip: 16773077, peachpuff: 16767673, peru: 13468991, pink: 16761035, plum: 14524637, powderblue: 11591910, purple: 8388736, rebeccapurple: 6697881, red: 16711680, rosybrown: 12357519, royalblue: 4286945, saddlebrown: 9127187, salmon: 16416882, sandybrown: 16032864, seagreen: 3050327, seashell: 16774638, sienna: 10506797, silver: 12632256, skyblue: 8900331, slateblue: 6970061, slategray: 7372944, slategrey: 7372944, snow: 16775930, springgreen: 65407, steelblue: 4620980, tan: 13808780, teal: 32896, thistle: 14204888, tomato: 16737095, turquoise: 4251856, violet: 15631086, wheat: 16113331, white: 16777215, whitesmoke: 16119285, yellow: 16776960, yellowgreen: 10145074 };\n      function Ce() {\n        return this.rgb().formatHex();\n      }\n      function Pe() {\n        return this.rgb().formatRgb();\n      }\n      function ze(t2) {\n        var n2, e2;\n        return t2 = (t2 + \"\").trim().toLowerCase(), (n2 = we.exec(t2)) ? (e2 = n2[1].length, n2 = parseInt(n2[1], 16), 6 === e2 ? $e(n2) : 3 === e2 ? new qe(n2 >> 8 & 15 | n2 >> 4 & 240, n2 >> 4 & 15 | 240 & n2, (15 & n2) << 4 | 15 & n2, 1) : 8 === e2 ? De(n2 >> 24 & 255, n2 >> 16 & 255, n2 >> 8 & 255, (255 & n2) / 255) : 4 === e2 ? De(n2 >> 12 & 15 | n2 >> 8 & 240, n2 >> 8 & 15 | n2 >> 4 & 240, n2 >> 4 & 15 | 240 & n2, ((15 & n2) << 4 | 15 & n2) / 255) : null) : (n2 = Me.exec(t2)) ? new qe(n2[1], n2[2], n2[3], 1) : (n2 = Te.exec(t2)) ? new qe(255 * n2[1] / 100, 255 * n2[2] / 100, 255 * n2[3] / 100, 1) : (n2 = Ae.exec(t2)) ? De(n2[1], n2[2], n2[3], n2[4]) : (n2 = Se.exec(t2)) ? De(255 * n2[1] / 100, 255 * n2[2] / 100, 255 * n2[3] / 100, n2[4]) : (n2 = Ee.exec(t2)) ? Le(n2[1], n2[2] / 100, n2[3] / 100, 1) : (n2 = Ne.exec(t2)) ? Le(n2[1], n2[2] / 100, n2[3] / 100, n2[4]) : ke.hasOwnProperty(t2) ? $e(ke[t2]) : \"transparent\" === t2 ? new qe(NaN, NaN, NaN, 0) : null;\n      }\n      function $e(t2) {\n        return new qe(t2 >> 16 & 255, t2 >> 8 & 255, 255 & t2, 1);\n      }\n      function De(t2, n2, e2, r2) {\n        return r2 <= 0 && (t2 = n2 = e2 = NaN), new qe(t2, n2, e2, r2);\n      }\n      function Re(t2) {\n        return t2 instanceof ye || (t2 = ze(t2)), t2 ? new qe((t2 = t2.rgb()).r, t2.g, t2.b, t2.opacity) : new qe();\n      }\n      function Fe(t2, n2, e2, r2) {\n        return 1 === arguments.length ? Re(t2) : new qe(t2, n2, e2, null == r2 ? 1 : r2);\n      }\n      function qe(t2, n2, e2, r2) {\n        this.r = +t2, this.g = +n2, this.b = +e2, this.opacity = +r2;\n      }\n      function Ue() {\n        return `#${Ye(this.r)}${Ye(this.g)}${Ye(this.b)}`;\n      }\n      function Ie() {\n        const t2 = Oe(this.opacity);\n        return `${1 === t2 ? \"rgb(\" : \"rgba(\"}${Be(this.r)}, ${Be(this.g)}, ${Be(this.b)}${1 === t2 ? \")\" : `, ${t2})`}`;\n      }\n      function Oe(t2) {\n        return isNaN(t2) ? 1 : Math.max(0, Math.min(1, t2));\n      }\n      function Be(t2) {\n        return Math.max(0, Math.min(255, Math.round(t2) || 0));\n      }\n      function Ye(t2) {\n        return ((t2 = Be(t2)) < 16 ? \"0\" : \"\") + t2.toString(16);\n      }\n      function Le(t2, n2, e2, r2) {\n        return r2 <= 0 ? t2 = n2 = e2 = NaN : e2 <= 0 || e2 >= 1 ? t2 = n2 = NaN : n2 <= 0 && (t2 = NaN), new Xe(t2, n2, e2, r2);\n      }\n      function je(t2) {\n        if (t2 instanceof Xe)\n          return new Xe(t2.h, t2.s, t2.l, t2.opacity);\n        if (t2 instanceof ye || (t2 = ze(t2)), !t2)\n          return new Xe();\n        if (t2 instanceof Xe)\n          return t2;\n        var n2 = (t2 = t2.rgb()).r / 255, e2 = t2.g / 255, r2 = t2.b / 255, i2 = Math.min(n2, e2, r2), o2 = Math.max(n2, e2, r2), a2 = NaN, u2 = o2 - i2, c2 = (o2 + i2) / 2;\n        return u2 ? (a2 = n2 === o2 ? (e2 - r2) / u2 + 6 * (e2 < r2) : e2 === o2 ? (r2 - n2) / u2 + 2 : (n2 - e2) / u2 + 4, u2 /= c2 < 0.5 ? o2 + i2 : 2 - o2 - i2, a2 *= 60) : u2 = c2 > 0 && c2 < 1 ? 0 : a2, new Xe(a2, u2, c2, t2.opacity);\n      }\n      function He(t2, n2, e2, r2) {\n        return 1 === arguments.length ? je(t2) : new Xe(t2, n2, e2, null == r2 ? 1 : r2);\n      }\n      function Xe(t2, n2, e2, r2) {\n        this.h = +t2, this.s = +n2, this.l = +e2, this.opacity = +r2;\n      }\n      function Ge(t2) {\n        return (t2 = (t2 || 0) % 360) < 0 ? t2 + 360 : t2;\n      }\n      function Ve(t2) {\n        return Math.max(0, Math.min(1, t2 || 0));\n      }\n      function We(t2, n2, e2) {\n        return 255 * (t2 < 60 ? n2 + (e2 - n2) * t2 / 60 : t2 < 180 ? e2 : t2 < 240 ? n2 + (e2 - n2) * (240 - t2) / 60 : n2);\n      }\n      pe(ye, ze, { copy(t2) {\n        return Object.assign(new this.constructor(), this, t2);\n      }, displayable() {\n        return this.rgb().displayable();\n      }, hex: Ce, formatHex: Ce, formatHex8: function() {\n        return this.rgb().formatHex8();\n      }, formatHsl: function() {\n        return je(this).formatHsl();\n      }, formatRgb: Pe, toString: Pe }), pe(qe, Fe, ge(ye, { brighter(t2) {\n        return t2 = null == t2 ? _e : Math.pow(_e, t2), new qe(this.r * t2, this.g * t2, this.b * t2, this.opacity);\n      }, darker(t2) {\n        return t2 = null == t2 ? ve : Math.pow(ve, t2), new qe(this.r * t2, this.g * t2, this.b * t2, this.opacity);\n      }, rgb() {\n        return this;\n      }, clamp() {\n        return new qe(Be(this.r), Be(this.g), Be(this.b), Oe(this.opacity));\n      }, displayable() {\n        return -0.5 <= this.r && this.r < 255.5 && -0.5 <= this.g && this.g < 255.5 && -0.5 <= this.b && this.b < 255.5 && 0 <= this.opacity && this.opacity <= 1;\n      }, hex: Ue, formatHex: Ue, formatHex8: function() {\n        return `#${Ye(this.r)}${Ye(this.g)}${Ye(this.b)}${Ye(255 * (isNaN(this.opacity) ? 1 : this.opacity))}`;\n      }, formatRgb: Ie, toString: Ie })), pe(Xe, He, ge(ye, { brighter(t2) {\n        return t2 = null == t2 ? _e : Math.pow(_e, t2), new Xe(this.h, this.s, this.l * t2, this.opacity);\n      }, darker(t2) {\n        return t2 = null == t2 ? ve : Math.pow(ve, t2), new Xe(this.h, this.s, this.l * t2, this.opacity);\n      }, rgb() {\n        var t2 = this.h % 360 + 360 * (this.h < 0), n2 = isNaN(t2) || isNaN(this.s) ? 0 : this.s, e2 = this.l, r2 = e2 + (e2 < 0.5 ? e2 : 1 - e2) * n2, i2 = 2 * e2 - r2;\n        return new qe(We(t2 >= 240 ? t2 - 240 : t2 + 120, i2, r2), We(t2, i2, r2), We(t2 < 120 ? t2 + 240 : t2 - 120, i2, r2), this.opacity);\n      }, clamp() {\n        return new Xe(Ge(this.h), Ve(this.s), Ve(this.l), Oe(this.opacity));\n      }, displayable() {\n        return (0 <= this.s && this.s <= 1 || isNaN(this.s)) && 0 <= this.l && this.l <= 1 && 0 <= this.opacity && this.opacity <= 1;\n      }, formatHsl() {\n        const t2 = Oe(this.opacity);\n        return `${1 === t2 ? \"hsl(\" : \"hsla(\"}${Ge(this.h)}, ${100 * Ve(this.s)}%, ${100 * Ve(this.l)}%${1 === t2 ? \")\" : `, ${t2})`}`;\n      } }));\n      const Ze = Math.PI / 180, Ke = 180 / Math.PI, Qe = 0.96422, Je = 1, tr = 0.82521, nr = 4 / 29, er = 6 / 29, rr = 3 * er * er, ir = er * er * er;\n      function or(t2) {\n        if (t2 instanceof ur)\n          return new ur(t2.l, t2.a, t2.b, t2.opacity);\n        if (t2 instanceof pr)\n          return gr(t2);\n        t2 instanceof qe || (t2 = Re(t2));\n        var n2, e2, r2 = lr(t2.r), i2 = lr(t2.g), o2 = lr(t2.b), a2 = cr((0.2225045 * r2 + 0.7168786 * i2 + 0.0606169 * o2) / Je);\n        return r2 === i2 && i2 === o2 ? n2 = e2 = a2 : (n2 = cr((0.4360747 * r2 + 0.3850649 * i2 + 0.1430804 * o2) / Qe), e2 = cr((0.0139322 * r2 + 0.0971045 * i2 + 0.7141733 * o2) / tr)), new ur(116 * a2 - 16, 500 * (n2 - a2), 200 * (a2 - e2), t2.opacity);\n      }\n      function ar(t2, n2, e2, r2) {\n        return 1 === arguments.length ? or(t2) : new ur(t2, n2, e2, null == r2 ? 1 : r2);\n      }\n      function ur(t2, n2, e2, r2) {\n        this.l = +t2, this.a = +n2, this.b = +e2, this.opacity = +r2;\n      }\n      function cr(t2) {\n        return t2 > ir ? Math.pow(t2, 1 / 3) : t2 / rr + nr;\n      }\n      function fr(t2) {\n        return t2 > er ? t2 * t2 * t2 : rr * (t2 - nr);\n      }\n      function sr(t2) {\n        return 255 * (t2 <= 31308e-7 ? 12.92 * t2 : 1.055 * Math.pow(t2, 1 / 2.4) - 0.055);\n      }\n      function lr(t2) {\n        return (t2 /= 255) <= 0.04045 ? t2 / 12.92 : Math.pow((t2 + 0.055) / 1.055, 2.4);\n      }\n      function hr(t2) {\n        if (t2 instanceof pr)\n          return new pr(t2.h, t2.c, t2.l, t2.opacity);\n        if (t2 instanceof ur || (t2 = or(t2)), 0 === t2.a && 0 === t2.b)\n          return new pr(NaN, 0 < t2.l && t2.l < 100 ? 0 : NaN, t2.l, t2.opacity);\n        var n2 = Math.atan2(t2.b, t2.a) * Ke;\n        return new pr(n2 < 0 ? n2 + 360 : n2, Math.sqrt(t2.a * t2.a + t2.b * t2.b), t2.l, t2.opacity);\n      }\n      function dr(t2, n2, e2, r2) {\n        return 1 === arguments.length ? hr(t2) : new pr(t2, n2, e2, null == r2 ? 1 : r2);\n      }\n      function pr(t2, n2, e2, r2) {\n        this.h = +t2, this.c = +n2, this.l = +e2, this.opacity = +r2;\n      }\n      function gr(t2) {\n        if (isNaN(t2.h))\n          return new ur(t2.l, 0, 0, t2.opacity);\n        var n2 = t2.h * Ze;\n        return new ur(t2.l, Math.cos(n2) * t2.c, Math.sin(n2) * t2.c, t2.opacity);\n      }\n      pe(ur, ar, ge(ye, { brighter(t2) {\n        return new ur(this.l + 18 * (null == t2 ? 1 : t2), this.a, this.b, this.opacity);\n      }, darker(t2) {\n        return new ur(this.l - 18 * (null == t2 ? 1 : t2), this.a, this.b, this.opacity);\n      }, rgb() {\n        var t2 = (this.l + 16) / 116, n2 = isNaN(this.a) ? t2 : t2 + this.a / 500, e2 = isNaN(this.b) ? t2 : t2 - this.b / 200;\n        return new qe(sr(3.1338561 * (n2 = Qe * fr(n2)) - 1.6168667 * (t2 = Je * fr(t2)) - 0.4906146 * (e2 = tr * fr(e2))), sr(-0.9787684 * n2 + 1.9161415 * t2 + 0.033454 * e2), sr(0.0719453 * n2 - 0.2289914 * t2 + 1.4052427 * e2), this.opacity);\n      } })), pe(pr, dr, ge(ye, { brighter(t2) {\n        return new pr(this.h, this.c, this.l + 18 * (null == t2 ? 1 : t2), this.opacity);\n      }, darker(t2) {\n        return new pr(this.h, this.c, this.l - 18 * (null == t2 ? 1 : t2), this.opacity);\n      }, rgb() {\n        return gr(this).rgb();\n      } }));\n      var yr = -0.14861, vr = 1.78277, _r = -0.29227, br = -0.90649, mr = 1.97294, xr = mr * br, wr = mr * vr, Mr = vr * _r - br * yr;\n      function Tr(t2, n2, e2, r2) {\n        return 1 === arguments.length ? function(t3) {\n          if (t3 instanceof Ar)\n            return new Ar(t3.h, t3.s, t3.l, t3.opacity);\n          t3 instanceof qe || (t3 = Re(t3));\n          var n3 = t3.r / 255, e3 = t3.g / 255, r3 = t3.b / 255, i2 = (Mr * r3 + xr * n3 - wr * e3) / (Mr + xr - wr), o2 = r3 - i2, a2 = (mr * (e3 - i2) - _r * o2) / br, u2 = Math.sqrt(a2 * a2 + o2 * o2) / (mr * i2 * (1 - i2)), c2 = u2 ? Math.atan2(a2, o2) * Ke - 120 : NaN;\n          return new Ar(c2 < 0 ? c2 + 360 : c2, u2, i2, t3.opacity);\n        }(t2) : new Ar(t2, n2, e2, null == r2 ? 1 : r2);\n      }\n      function Ar(t2, n2, e2, r2) {\n        this.h = +t2, this.s = +n2, this.l = +e2, this.opacity = +r2;\n      }\n      function Sr(t2, n2, e2, r2, i2) {\n        var o2 = t2 * t2, a2 = o2 * t2;\n        return ((1 - 3 * t2 + 3 * o2 - a2) * n2 + (4 - 6 * o2 + 3 * a2) * e2 + (1 + 3 * t2 + 3 * o2 - 3 * a2) * r2 + a2 * i2) / 6;\n      }\n      function Er(t2) {\n        var n2 = t2.length - 1;\n        return function(e2) {\n          var r2 = e2 <= 0 ? e2 = 0 : e2 >= 1 ? (e2 = 1, n2 - 1) : Math.floor(e2 * n2), i2 = t2[r2], o2 = t2[r2 + 1], a2 = r2 > 0 ? t2[r2 - 1] : 2 * i2 - o2, u2 = r2 < n2 - 1 ? t2[r2 + 2] : 2 * o2 - i2;\n          return Sr((e2 - r2 / n2) * n2, a2, i2, o2, u2);\n        };\n      }\n      function Nr(t2) {\n        var n2 = t2.length;\n        return function(e2) {\n          var r2 = Math.floor(((e2 %= 1) < 0 ? ++e2 : e2) * n2), i2 = t2[(r2 + n2 - 1) % n2], o2 = t2[r2 % n2], a2 = t2[(r2 + 1) % n2], u2 = t2[(r2 + 2) % n2];\n          return Sr((e2 - r2 / n2) * n2, i2, o2, a2, u2);\n        };\n      }\n      pe(Ar, Tr, ge(ye, { brighter(t2) {\n        return t2 = null == t2 ? _e : Math.pow(_e, t2), new Ar(this.h, this.s, this.l * t2, this.opacity);\n      }, darker(t2) {\n        return t2 = null == t2 ? ve : Math.pow(ve, t2), new Ar(this.h, this.s, this.l * t2, this.opacity);\n      }, rgb() {\n        var t2 = isNaN(this.h) ? 0 : (this.h + 120) * Ze, n2 = +this.l, e2 = isNaN(this.s) ? 0 : this.s * n2 * (1 - n2), r2 = Math.cos(t2), i2 = Math.sin(t2);\n        return new qe(255 * (n2 + e2 * (yr * r2 + vr * i2)), 255 * (n2 + e2 * (_r * r2 + br * i2)), 255 * (n2 + e2 * (mr * r2)), this.opacity);\n      } }));\n      var kr = (t2) => () => t2;\n      function Cr(t2, n2) {\n        return function(e2) {\n          return t2 + e2 * n2;\n        };\n      }\n      function Pr(t2, n2) {\n        var e2 = n2 - t2;\n        return e2 ? Cr(t2, e2 > 180 || e2 < -180 ? e2 - 360 * Math.round(e2 / 360) : e2) : kr(isNaN(t2) ? n2 : t2);\n      }\n      function zr(t2) {\n        return 1 == (t2 = +t2) ? $r : function(n2, e2) {\n          return e2 - n2 ? function(t3, n3, e3) {\n            return t3 = Math.pow(t3, e3), n3 = Math.pow(n3, e3) - t3, e3 = 1 / e3, function(r2) {\n              return Math.pow(t3 + r2 * n3, e3);\n            };\n          }(n2, e2, t2) : kr(isNaN(n2) ? e2 : n2);\n        };\n      }\n      function $r(t2, n2) {\n        var e2 = n2 - t2;\n        return e2 ? Cr(t2, e2) : kr(isNaN(t2) ? n2 : t2);\n      }\n      var Dr = function t2(n2) {\n        var e2 = zr(n2);\n        function r2(t3, n3) {\n          var r3 = e2((t3 = Fe(t3)).r, (n3 = Fe(n3)).r), i2 = e2(t3.g, n3.g), o2 = e2(t3.b, n3.b), a2 = $r(t3.opacity, n3.opacity);\n          return function(n4) {\n            return t3.r = r3(n4), t3.g = i2(n4), t3.b = o2(n4), t3.opacity = a2(n4), t3 + \"\";\n          };\n        }\n        return r2.gamma = t2, r2;\n      }(1);\n      function Rr(t2) {\n        return function(n2) {\n          var e2, r2, i2 = n2.length, o2 = new Array(i2), a2 = new Array(i2), u2 = new Array(i2);\n          for (e2 = 0; e2 < i2; ++e2)\n            r2 = Fe(n2[e2]), o2[e2] = r2.r || 0, a2[e2] = r2.g || 0, u2[e2] = r2.b || 0;\n          return o2 = t2(o2), a2 = t2(a2), u2 = t2(u2), r2.opacity = 1, function(t3) {\n            return r2.r = o2(t3), r2.g = a2(t3), r2.b = u2(t3), r2 + \"\";\n          };\n        };\n      }\n      var Fr = Rr(Er), qr = Rr(Nr);\n      function Ur(t2, n2) {\n        n2 || (n2 = []);\n        var e2, r2 = t2 ? Math.min(n2.length, t2.length) : 0, i2 = n2.slice();\n        return function(o2) {\n          for (e2 = 0; e2 < r2; ++e2)\n            i2[e2] = t2[e2] * (1 - o2) + n2[e2] * o2;\n          return i2;\n        };\n      }\n      function Ir(t2) {\n        return ArrayBuffer.isView(t2) && !(t2 instanceof DataView);\n      }\n      function Or(t2, n2) {\n        var e2, r2 = n2 ? n2.length : 0, i2 = t2 ? Math.min(r2, t2.length) : 0, o2 = new Array(i2), a2 = new Array(r2);\n        for (e2 = 0; e2 < i2; ++e2)\n          o2[e2] = Gr(t2[e2], n2[e2]);\n        for (; e2 < r2; ++e2)\n          a2[e2] = n2[e2];\n        return function(t3) {\n          for (e2 = 0; e2 < i2; ++e2)\n            a2[e2] = o2[e2](t3);\n          return a2;\n        };\n      }\n      function Br(t2, n2) {\n        var e2 = /* @__PURE__ */ new Date();\n        return t2 = +t2, n2 = +n2, function(r2) {\n          return e2.setTime(t2 * (1 - r2) + n2 * r2), e2;\n        };\n      }\n      function Yr(t2, n2) {\n        return t2 = +t2, n2 = +n2, function(e2) {\n          return t2 * (1 - e2) + n2 * e2;\n        };\n      }\n      function Lr(t2, n2) {\n        var e2, r2 = {}, i2 = {};\n        for (e2 in null !== t2 && \"object\" == typeof t2 || (t2 = {}), null !== n2 && \"object\" == typeof n2 || (n2 = {}), n2)\n          e2 in t2 ? r2[e2] = Gr(t2[e2], n2[e2]) : i2[e2] = n2[e2];\n        return function(t3) {\n          for (e2 in r2)\n            i2[e2] = r2[e2](t3);\n          return i2;\n        };\n      }\n      var jr = /[-+]?(?:\\d+\\.?\\d*|\\.?\\d+)(?:[eE][-+]?\\d+)?/g, Hr = new RegExp(jr.source, \"g\");\n      function Xr(t2, n2) {\n        var e2, r2, i2, o2 = jr.lastIndex = Hr.lastIndex = 0, a2 = -1, u2 = [], c2 = [];\n        for (t2 += \"\", n2 += \"\"; (e2 = jr.exec(t2)) && (r2 = Hr.exec(n2)); )\n          (i2 = r2.index) > o2 && (i2 = n2.slice(o2, i2), u2[a2] ? u2[a2] += i2 : u2[++a2] = i2), (e2 = e2[0]) === (r2 = r2[0]) ? u2[a2] ? u2[a2] += r2 : u2[++a2] = r2 : (u2[++a2] = null, c2.push({ i: a2, x: Yr(e2, r2) })), o2 = Hr.lastIndex;\n        return o2 < n2.length && (i2 = n2.slice(o2), u2[a2] ? u2[a2] += i2 : u2[++a2] = i2), u2.length < 2 ? c2[0] ? /* @__PURE__ */ function(t3) {\n          return function(n3) {\n            return t3(n3) + \"\";\n          };\n        }(c2[0].x) : /* @__PURE__ */ function(t3) {\n          return function() {\n            return t3;\n          };\n        }(n2) : (n2 = c2.length, function(t3) {\n          for (var e3, r3 = 0; r3 < n2; ++r3)\n            u2[(e3 = c2[r3]).i] = e3.x(t3);\n          return u2.join(\"\");\n        });\n      }\n      function Gr(t2, n2) {\n        var e2, r2 = typeof n2;\n        return null == n2 || \"boolean\" === r2 ? kr(n2) : (\"number\" === r2 ? Yr : \"string\" === r2 ? (e2 = ze(n2)) ? (n2 = e2, Dr) : Xr : n2 instanceof ze ? Dr : n2 instanceof Date ? Br : Ir(n2) ? Ur : Array.isArray(n2) ? Or : \"function\" != typeof n2.valueOf && \"function\" != typeof n2.toString || isNaN(n2) ? Lr : Yr)(t2, n2);\n      }\n      function Vr(t2, n2) {\n        return t2 = +t2, n2 = +n2, function(e2) {\n          return Math.round(t2 * (1 - e2) + n2 * e2);\n        };\n      }\n      var Wr, Zr = 180 / Math.PI, Kr = { translateX: 0, translateY: 0, rotate: 0, skewX: 0, scaleX: 1, scaleY: 1 };\n      function Qr(t2, n2, e2, r2, i2, o2) {\n        var a2, u2, c2;\n        return (a2 = Math.sqrt(t2 * t2 + n2 * n2)) && (t2 /= a2, n2 /= a2), (c2 = t2 * e2 + n2 * r2) && (e2 -= t2 * c2, r2 -= n2 * c2), (u2 = Math.sqrt(e2 * e2 + r2 * r2)) && (e2 /= u2, r2 /= u2, c2 /= u2), t2 * r2 < n2 * e2 && (t2 = -t2, n2 = -n2, c2 = -c2, a2 = -a2), { translateX: i2, translateY: o2, rotate: Math.atan2(n2, t2) * Zr, skewX: Math.atan(c2) * Zr, scaleX: a2, scaleY: u2 };\n      }\n      function Jr(t2, n2, e2, r2) {\n        function i2(t3) {\n          return t3.length ? t3.pop() + \" \" : \"\";\n        }\n        return function(o2, a2) {\n          var u2 = [], c2 = [];\n          return o2 = t2(o2), a2 = t2(a2), function(t3, r3, i3, o3, a3, u3) {\n            if (t3 !== i3 || r3 !== o3) {\n              var c3 = a3.push(\"translate(\", null, n2, null, e2);\n              u3.push({ i: c3 - 4, x: Yr(t3, i3) }, { i: c3 - 2, x: Yr(r3, o3) });\n            } else\n              (i3 || o3) && a3.push(\"translate(\" + i3 + n2 + o3 + e2);\n          }(o2.translateX, o2.translateY, a2.translateX, a2.translateY, u2, c2), function(t3, n3, e3, o3) {\n            t3 !== n3 ? (t3 - n3 > 180 ? n3 += 360 : n3 - t3 > 180 && (t3 += 360), o3.push({ i: e3.push(i2(e3) + \"rotate(\", null, r2) - 2, x: Yr(t3, n3) })) : n3 && e3.push(i2(e3) + \"rotate(\" + n3 + r2);\n          }(o2.rotate, a2.rotate, u2, c2), function(t3, n3, e3, o3) {\n            t3 !== n3 ? o3.push({ i: e3.push(i2(e3) + \"skewX(\", null, r2) - 2, x: Yr(t3, n3) }) : n3 && e3.push(i2(e3) + \"skewX(\" + n3 + r2);\n          }(o2.skewX, a2.skewX, u2, c2), function(t3, n3, e3, r3, o3, a3) {\n            if (t3 !== e3 || n3 !== r3) {\n              var u3 = o3.push(i2(o3) + \"scale(\", null, \",\", null, \")\");\n              a3.push({ i: u3 - 4, x: Yr(t3, e3) }, { i: u3 - 2, x: Yr(n3, r3) });\n            } else\n              1 === e3 && 1 === r3 || o3.push(i2(o3) + \"scale(\" + e3 + \",\" + r3 + \")\");\n          }(o2.scaleX, o2.scaleY, a2.scaleX, a2.scaleY, u2, c2), o2 = a2 = null, function(t3) {\n            for (var n3, e3 = -1, r3 = c2.length; ++e3 < r3; )\n              u2[(n3 = c2[e3]).i] = n3.x(t3);\n            return u2.join(\"\");\n          };\n        };\n      }\n      var ti = Jr(function(t2) {\n        const n2 = new (\"function\" == typeof DOMMatrix ? DOMMatrix : WebKitCSSMatrix)(t2 + \"\");\n        return n2.isIdentity ? Kr : Qr(n2.a, n2.b, n2.c, n2.d, n2.e, n2.f);\n      }, \"px, \", \"px)\", \"deg)\"), ni = Jr(function(t2) {\n        return null == t2 ? Kr : (Wr || (Wr = document.createElementNS(\"http://www.w3.org/2000/svg\", \"g\")), Wr.setAttribute(\"transform\", t2), (t2 = Wr.transform.baseVal.consolidate()) ? Qr((t2 = t2.matrix).a, t2.b, t2.c, t2.d, t2.e, t2.f) : Kr);\n      }, \", \", \")\", \")\");\n      function ei(t2) {\n        return ((t2 = Math.exp(t2)) + 1 / t2) / 2;\n      }\n      var ri = function t2(n2, e2, r2) {\n        function i2(t3, i3) {\n          var o2, a2, u2 = t3[0], c2 = t3[1], f2 = t3[2], s2 = i3[0], l2 = i3[1], h2 = i3[2], d2 = s2 - u2, p2 = l2 - c2, g2 = d2 * d2 + p2 * p2;\n          if (g2 < 1e-12)\n            a2 = Math.log(h2 / f2) / n2, o2 = function(t4) {\n              return [u2 + t4 * d2, c2 + t4 * p2, f2 * Math.exp(n2 * t4 * a2)];\n            };\n          else {\n            var y2 = Math.sqrt(g2), v2 = (h2 * h2 - f2 * f2 + r2 * g2) / (2 * f2 * e2 * y2), _2 = (h2 * h2 - f2 * f2 - r2 * g2) / (2 * h2 * e2 * y2), b2 = Math.log(Math.sqrt(v2 * v2 + 1) - v2), m2 = Math.log(Math.sqrt(_2 * _2 + 1) - _2);\n            a2 = (m2 - b2) / n2, o2 = function(t4) {\n              var r3 = t4 * a2, i4 = ei(b2), o3 = f2 / (e2 * y2) * (i4 * function(t5) {\n                return ((t5 = Math.exp(2 * t5)) - 1) / (t5 + 1);\n              }(n2 * r3 + b2) - function(t5) {\n                return ((t5 = Math.exp(t5)) - 1 / t5) / 2;\n              }(b2));\n              return [u2 + o3 * d2, c2 + o3 * p2, f2 * i4 / ei(n2 * r3 + b2)];\n            };\n          }\n          return o2.duration = 1e3 * a2 * n2 / Math.SQRT2, o2;\n        }\n        return i2.rho = function(n3) {\n          var e3 = Math.max(1e-3, +n3), r3 = e3 * e3;\n          return t2(e3, r3, r3 * r3);\n        }, i2;\n      }(Math.SQRT2, 2, 4);\n      function ii(t2) {\n        return function(n2, e2) {\n          var r2 = t2((n2 = He(n2)).h, (e2 = He(e2)).h), i2 = $r(n2.s, e2.s), o2 = $r(n2.l, e2.l), a2 = $r(n2.opacity, e2.opacity);\n          return function(t3) {\n            return n2.h = r2(t3), n2.s = i2(t3), n2.l = o2(t3), n2.opacity = a2(t3), n2 + \"\";\n          };\n        };\n      }\n      var oi = ii(Pr), ai = ii($r);\n      function ui(t2) {\n        return function(n2, e2) {\n          var r2 = t2((n2 = dr(n2)).h, (e2 = dr(e2)).h), i2 = $r(n2.c, e2.c), o2 = $r(n2.l, e2.l), a2 = $r(n2.opacity, e2.opacity);\n          return function(t3) {\n            return n2.h = r2(t3), n2.c = i2(t3), n2.l = o2(t3), n2.opacity = a2(t3), n2 + \"\";\n          };\n        };\n      }\n      var ci = ui(Pr), fi = ui($r);\n      function si(t2) {\n        return function n2(e2) {\n          function r2(n3, r3) {\n            var i2 = t2((n3 = Tr(n3)).h, (r3 = Tr(r3)).h), o2 = $r(n3.s, r3.s), a2 = $r(n3.l, r3.l), u2 = $r(n3.opacity, r3.opacity);\n            return function(t3) {\n              return n3.h = i2(t3), n3.s = o2(t3), n3.l = a2(Math.pow(t3, e2)), n3.opacity = u2(t3), n3 + \"\";\n            };\n          }\n          return e2 = +e2, r2.gamma = n2, r2;\n        }(1);\n      }\n      var li = si(Pr), hi = si($r);\n      function di(t2, n2) {\n        void 0 === n2 && (n2 = t2, t2 = Gr);\n        for (var e2 = 0, r2 = n2.length - 1, i2 = n2[0], o2 = new Array(r2 < 0 ? 0 : r2); e2 < r2; )\n          o2[e2] = t2(i2, i2 = n2[++e2]);\n        return function(t3) {\n          var n3 = Math.max(0, Math.min(r2 - 1, Math.floor(t3 *= r2)));\n          return o2[n3](t3 - n3);\n        };\n      }\n      var pi, gi, yi = 0, vi = 0, _i = 0, bi = 1e3, mi = 0, xi = 0, wi = 0, Mi = \"object\" == typeof performance && performance.now ? performance : Date, Ti = \"object\" == typeof window && window.requestAnimationFrame ? window.requestAnimationFrame.bind(window) : function(t2) {\n        setTimeout(t2, 17);\n      };\n      function Ai() {\n        return xi || (Ti(Si), xi = Mi.now() + wi);\n      }\n      function Si() {\n        xi = 0;\n      }\n      function Ei() {\n        this._call = this._time = this._next = null;\n      }\n      function Ni(t2, n2, e2) {\n        var r2 = new Ei();\n        return r2.restart(t2, n2, e2), r2;\n      }\n      function ki() {\n        Ai(), ++yi;\n        for (var t2, n2 = pi; n2; )\n          (t2 = xi - n2._time) >= 0 && n2._call.call(void 0, t2), n2 = n2._next;\n        --yi;\n      }\n      function Ci() {\n        xi = (mi = Mi.now()) + wi, yi = vi = 0;\n        try {\n          ki();\n        } finally {\n          yi = 0, function() {\n            var t2, n2, e2 = pi, r2 = 1 / 0;\n            for (; e2; )\n              e2._call ? (r2 > e2._time && (r2 = e2._time), t2 = e2, e2 = e2._next) : (n2 = e2._next, e2._next = null, e2 = t2 ? t2._next = n2 : pi = n2);\n            gi = t2, zi(r2);\n          }(), xi = 0;\n        }\n      }\n      function Pi() {\n        var t2 = Mi.now(), n2 = t2 - mi;\n        n2 > bi && (wi -= n2, mi = t2);\n      }\n      function zi(t2) {\n        yi || (vi && (vi = clearTimeout(vi)), t2 - xi > 24 ? (t2 < 1 / 0 && (vi = setTimeout(Ci, t2 - Mi.now() - wi)), _i && (_i = clearInterval(_i))) : (_i || (mi = Mi.now(), _i = setInterval(Pi, bi)), yi = 1, Ti(Ci)));\n      }\n      function $i(t2, n2, e2) {\n        var r2 = new Ei();\n        return n2 = null == n2 ? 0 : +n2, r2.restart((e3) => {\n          r2.stop(), t2(e3 + n2);\n        }, n2, e2), r2;\n      }\n      Ei.prototype = Ni.prototype = { constructor: Ei, restart: function(t2, n2, e2) {\n        if (\"function\" != typeof t2)\n          throw new TypeError(\"callback is not a function\");\n        e2 = (null == e2 ? Ai() : +e2) + (null == n2 ? 0 : +n2), this._next || gi === this || (gi ? gi._next = this : pi = this, gi = this), this._call = t2, this._time = e2, zi();\n      }, stop: function() {\n        this._call && (this._call = null, this._time = 1 / 0, zi());\n      } };\n      var Di = $t(\"start\", \"end\", \"cancel\", \"interrupt\"), Ri = [], Fi = 0, qi = 1, Ui = 2, Ii = 3, Oi = 4, Bi = 5, Yi = 6;\n      function Li(t2, n2, e2, r2, i2, o2) {\n        var a2 = t2.__transition;\n        if (a2) {\n          if (e2 in a2)\n            return;\n        } else\n          t2.__transition = {};\n        !function(t3, n3, e3) {\n          var r3, i3 = t3.__transition;\n          function o3(t4) {\n            e3.state = qi, e3.timer.restart(a3, e3.delay, e3.time), e3.delay <= t4 && a3(t4 - e3.delay);\n          }\n          function a3(o4) {\n            var f2, s2, l2, h2;\n            if (e3.state !== qi)\n              return c2();\n            for (f2 in i3)\n              if ((h2 = i3[f2]).name === e3.name) {\n                if (h2.state === Ii)\n                  return $i(a3);\n                h2.state === Oi ? (h2.state = Yi, h2.timer.stop(), h2.on.call(\"interrupt\", t3, t3.__data__, h2.index, h2.group), delete i3[f2]) : +f2 < n3 && (h2.state = Yi, h2.timer.stop(), h2.on.call(\"cancel\", t3, t3.__data__, h2.index, h2.group), delete i3[f2]);\n              }\n            if ($i(function() {\n              e3.state === Ii && (e3.state = Oi, e3.timer.restart(u2, e3.delay, e3.time), u2(o4));\n            }), e3.state = Ui, e3.on.call(\"start\", t3, t3.__data__, e3.index, e3.group), e3.state === Ui) {\n              for (e3.state = Ii, r3 = new Array(l2 = e3.tween.length), f2 = 0, s2 = -1; f2 < l2; ++f2)\n                (h2 = e3.tween[f2].value.call(t3, t3.__data__, e3.index, e3.group)) && (r3[++s2] = h2);\n              r3.length = s2 + 1;\n            }\n          }\n          function u2(n4) {\n            for (var i4 = n4 < e3.duration ? e3.ease.call(null, n4 / e3.duration) : (e3.timer.restart(c2), e3.state = Bi, 1), o4 = -1, a4 = r3.length; ++o4 < a4; )\n              r3[o4].call(t3, i4);\n            e3.state === Bi && (e3.on.call(\"end\", t3, t3.__data__, e3.index, e3.group), c2());\n          }\n          function c2() {\n            for (var r4 in e3.state = Yi, e3.timer.stop(), delete i3[n3], i3)\n              return;\n            delete t3.__transition;\n          }\n          i3[n3] = e3, e3.timer = Ni(o3, 0, e3.time);\n        }(t2, e2, { name: n2, index: r2, group: i2, on: Di, tween: Ri, time: o2.time, delay: o2.delay, duration: o2.duration, ease: o2.ease, timer: null, state: Fi });\n      }\n      function ji(t2, n2) {\n        var e2 = Xi(t2, n2);\n        if (e2.state > Fi)\n          throw new Error(\"too late; already scheduled\");\n        return e2;\n      }\n      function Hi(t2, n2) {\n        var e2 = Xi(t2, n2);\n        if (e2.state > Ii)\n          throw new Error(\"too late; already running\");\n        return e2;\n      }\n      function Xi(t2, n2) {\n        var e2 = t2.__transition;\n        if (!e2 || !(e2 = e2[n2]))\n          throw new Error(\"transition not found\");\n        return e2;\n      }\n      function Gi(t2, n2) {\n        var e2, r2, i2, o2 = t2.__transition, a2 = true;\n        if (o2) {\n          for (i2 in n2 = null == n2 ? null : n2 + \"\", o2)\n            (e2 = o2[i2]).name === n2 ? (r2 = e2.state > Ui && e2.state < Bi, e2.state = Yi, e2.timer.stop(), e2.on.call(r2 ? \"interrupt\" : \"cancel\", t2, t2.__data__, e2.index, e2.group), delete o2[i2]) : a2 = false;\n          a2 && delete t2.__transition;\n        }\n      }\n      function Vi(t2, n2) {\n        var e2, r2;\n        return function() {\n          var i2 = Hi(this, t2), o2 = i2.tween;\n          if (o2 !== e2) {\n            for (var a2 = 0, u2 = (r2 = e2 = o2).length; a2 < u2; ++a2)\n              if (r2[a2].name === n2) {\n                (r2 = r2.slice()).splice(a2, 1);\n                break;\n              }\n          }\n          i2.tween = r2;\n        };\n      }\n      function Wi(t2, n2, e2) {\n        var r2, i2;\n        if (\"function\" != typeof e2)\n          throw new Error();\n        return function() {\n          var o2 = Hi(this, t2), a2 = o2.tween;\n          if (a2 !== r2) {\n            i2 = (r2 = a2).slice();\n            for (var u2 = { name: n2, value: e2 }, c2 = 0, f2 = i2.length; c2 < f2; ++c2)\n              if (i2[c2].name === n2) {\n                i2[c2] = u2;\n                break;\n              }\n            c2 === f2 && i2.push(u2);\n          }\n          o2.tween = i2;\n        };\n      }\n      function Zi(t2, n2, e2) {\n        var r2 = t2._id;\n        return t2.each(function() {\n          var t3 = Hi(this, r2);\n          (t3.value || (t3.value = {}))[n2] = e2.apply(this, arguments);\n        }), function(t3) {\n          return Xi(t3, r2).value[n2];\n        };\n      }\n      function Ki(t2, n2) {\n        var e2;\n        return (\"number\" == typeof n2 ? Yr : n2 instanceof ze ? Dr : (e2 = ze(n2)) ? (n2 = e2, Dr) : Xr)(t2, n2);\n      }\n      function Qi(t2) {\n        return function() {\n          this.removeAttribute(t2);\n        };\n      }\n      function Ji(t2) {\n        return function() {\n          this.removeAttributeNS(t2.space, t2.local);\n        };\n      }\n      function to(t2, n2, e2) {\n        var r2, i2, o2 = e2 + \"\";\n        return function() {\n          var a2 = this.getAttribute(t2);\n          return a2 === o2 ? null : a2 === r2 ? i2 : i2 = n2(r2 = a2, e2);\n        };\n      }\n      function no(t2, n2, e2) {\n        var r2, i2, o2 = e2 + \"\";\n        return function() {\n          var a2 = this.getAttributeNS(t2.space, t2.local);\n          return a2 === o2 ? null : a2 === r2 ? i2 : i2 = n2(r2 = a2, e2);\n        };\n      }\n      function eo(t2, n2, e2) {\n        var r2, i2, o2;\n        return function() {\n          var a2, u2, c2 = e2(this);\n          if (null != c2)\n            return (a2 = this.getAttribute(t2)) === (u2 = c2 + \"\") ? null : a2 === r2 && u2 === i2 ? o2 : (i2 = u2, o2 = n2(r2 = a2, c2));\n          this.removeAttribute(t2);\n        };\n      }\n      function ro(t2, n2, e2) {\n        var r2, i2, o2;\n        return function() {\n          var a2, u2, c2 = e2(this);\n          if (null != c2)\n            return (a2 = this.getAttributeNS(t2.space, t2.local)) === (u2 = c2 + \"\") ? null : a2 === r2 && u2 === i2 ? o2 : (i2 = u2, o2 = n2(r2 = a2, c2));\n          this.removeAttributeNS(t2.space, t2.local);\n        };\n      }\n      function io(t2, n2) {\n        var e2, r2;\n        function i2() {\n          var i3 = n2.apply(this, arguments);\n          return i3 !== r2 && (e2 = (r2 = i3) && /* @__PURE__ */ function(t3, n3) {\n            return function(e3) {\n              this.setAttributeNS(t3.space, t3.local, n3.call(this, e3));\n            };\n          }(t2, i3)), e2;\n        }\n        return i2._value = n2, i2;\n      }\n      function oo(t2, n2) {\n        var e2, r2;\n        function i2() {\n          var i3 = n2.apply(this, arguments);\n          return i3 !== r2 && (e2 = (r2 = i3) && /* @__PURE__ */ function(t3, n3) {\n            return function(e3) {\n              this.setAttribute(t3, n3.call(this, e3));\n            };\n          }(t2, i3)), e2;\n        }\n        return i2._value = n2, i2;\n      }\n      function ao(t2, n2) {\n        return function() {\n          ji(this, t2).delay = +n2.apply(this, arguments);\n        };\n      }\n      function uo(t2, n2) {\n        return n2 = +n2, function() {\n          ji(this, t2).delay = n2;\n        };\n      }\n      function co(t2, n2) {\n        return function() {\n          Hi(this, t2).duration = +n2.apply(this, arguments);\n        };\n      }\n      function fo(t2, n2) {\n        return n2 = +n2, function() {\n          Hi(this, t2).duration = n2;\n        };\n      }\n      var so = Wn.prototype.constructor;\n      function lo(t2) {\n        return function() {\n          this.style.removeProperty(t2);\n        };\n      }\n      var ho = 0;\n      function po(t2, n2, e2, r2) {\n        this._groups = t2, this._parents = n2, this._name = e2, this._id = r2;\n      }\n      function go(t2) {\n        return Wn().transition(t2);\n      }\n      function yo() {\n        return ++ho;\n      }\n      var vo = Wn.prototype;\n      po.prototype = go.prototype = { constructor: po, select: function(t2) {\n        var n2 = this._name, e2 = this._id;\n        \"function\" != typeof t2 && (t2 = jt(t2));\n        for (var r2 = this._groups, i2 = r2.length, o2 = new Array(i2), a2 = 0; a2 < i2; ++a2)\n          for (var u2, c2, f2 = r2[a2], s2 = f2.length, l2 = o2[a2] = new Array(s2), h2 = 0; h2 < s2; ++h2)\n            (u2 = f2[h2]) && (c2 = t2.call(u2, u2.__data__, h2, f2)) && (\"__data__\" in u2 && (c2.__data__ = u2.__data__), l2[h2] = c2, Li(l2[h2], n2, e2, h2, l2, Xi(u2, e2)));\n        return new po(o2, this._parents, n2, e2);\n      }, selectAll: function(t2) {\n        var n2 = this._name, e2 = this._id;\n        \"function\" != typeof t2 && (t2 = Gt(t2));\n        for (var r2 = this._groups, i2 = r2.length, o2 = [], a2 = [], u2 = 0; u2 < i2; ++u2)\n          for (var c2, f2 = r2[u2], s2 = f2.length, l2 = 0; l2 < s2; ++l2)\n            if (c2 = f2[l2]) {\n              for (var h2, d2 = t2.call(c2, c2.__data__, l2, f2), p2 = Xi(c2, e2), g2 = 0, y2 = d2.length; g2 < y2; ++g2)\n                (h2 = d2[g2]) && Li(h2, n2, e2, g2, d2, p2);\n              o2.push(d2), a2.push(c2);\n            }\n        return new po(o2, a2, n2, e2);\n      }, selectChild: vo.selectChild, selectChildren: vo.selectChildren, filter: function(t2) {\n        \"function\" != typeof t2 && (t2 = Vt(t2));\n        for (var n2 = this._groups, e2 = n2.length, r2 = new Array(e2), i2 = 0; i2 < e2; ++i2)\n          for (var o2, a2 = n2[i2], u2 = a2.length, c2 = r2[i2] = [], f2 = 0; f2 < u2; ++f2)\n            (o2 = a2[f2]) && t2.call(o2, o2.__data__, f2, a2) && c2.push(o2);\n        return new po(r2, this._parents, this._name, this._id);\n      }, merge: function(t2) {\n        if (t2._id !== this._id)\n          throw new Error();\n        for (var n2 = this._groups, e2 = t2._groups, r2 = n2.length, i2 = e2.length, o2 = Math.min(r2, i2), a2 = new Array(r2), u2 = 0; u2 < o2; ++u2)\n          for (var c2, f2 = n2[u2], s2 = e2[u2], l2 = f2.length, h2 = a2[u2] = new Array(l2), d2 = 0; d2 < l2; ++d2)\n            (c2 = f2[d2] || s2[d2]) && (h2[d2] = c2);\n        for (; u2 < r2; ++u2)\n          a2[u2] = n2[u2];\n        return new po(a2, this._parents, this._name, this._id);\n      }, selection: function() {\n        return new so(this._groups, this._parents);\n      }, transition: function() {\n        for (var t2 = this._name, n2 = this._id, e2 = yo(), r2 = this._groups, i2 = r2.length, o2 = 0; o2 < i2; ++o2)\n          for (var a2, u2 = r2[o2], c2 = u2.length, f2 = 0; f2 < c2; ++f2)\n            if (a2 = u2[f2]) {\n              var s2 = Xi(a2, n2);\n              Li(a2, t2, e2, f2, u2, { time: s2.time + s2.delay + s2.duration, delay: 0, duration: s2.duration, ease: s2.ease });\n            }\n        return new po(r2, this._parents, t2, e2);\n      }, call: vo.call, nodes: vo.nodes, node: vo.node, size: vo.size, empty: vo.empty, each: vo.each, on: function(t2, n2) {\n        var e2 = this._id;\n        return arguments.length < 2 ? Xi(this.node(), e2).on.on(t2) : this.each(function(t3, n3, e3) {\n          var r2, i2, o2 = function(t4) {\n            return (t4 + \"\").trim().split(/^|\\s+/).every(function(t5) {\n              var n4 = t5.indexOf(\".\");\n              return n4 >= 0 && (t5 = t5.slice(0, n4)), !t5 || \"start\" === t5;\n            });\n          }(n3) ? ji : Hi;\n          return function() {\n            var a2 = o2(this, t3), u2 = a2.on;\n            u2 !== r2 && (i2 = (r2 = u2).copy()).on(n3, e3), a2.on = i2;\n          };\n        }(e2, t2, n2));\n      }, attr: function(t2, n2) {\n        var e2 = It(t2), r2 = \"transform\" === e2 ? ni : Ki;\n        return this.attrTween(t2, \"function\" == typeof n2 ? (e2.local ? ro : eo)(e2, r2, Zi(this, \"attr.\" + t2, n2)) : null == n2 ? (e2.local ? Ji : Qi)(e2) : (e2.local ? no : to)(e2, r2, n2));\n      }, attrTween: function(t2, n2) {\n        var e2 = \"attr.\" + t2;\n        if (arguments.length < 2)\n          return (e2 = this.tween(e2)) && e2._value;\n        if (null == n2)\n          return this.tween(e2, null);\n        if (\"function\" != typeof n2)\n          throw new Error();\n        var r2 = It(t2);\n        return this.tween(e2, (r2.local ? io : oo)(r2, n2));\n      }, style: function(t2, n2, e2) {\n        var r2 = \"transform\" == (t2 += \"\") ? ti : Ki;\n        return null == n2 ? this.styleTween(t2, /* @__PURE__ */ function(t3, n3) {\n          var e3, r3, i2;\n          return function() {\n            var o2 = _n(this, t3), a2 = (this.style.removeProperty(t3), _n(this, t3));\n            return o2 === a2 ? null : o2 === e3 && a2 === r3 ? i2 : i2 = n3(e3 = o2, r3 = a2);\n          };\n        }(t2, r2)).on(\"end.style.\" + t2, lo(t2)) : \"function\" == typeof n2 ? this.styleTween(t2, /* @__PURE__ */ function(t3, n3, e3) {\n          var r3, i2, o2;\n          return function() {\n            var a2 = _n(this, t3), u2 = e3(this), c2 = u2 + \"\";\n            return null == u2 && (this.style.removeProperty(t3), c2 = u2 = _n(this, t3)), a2 === c2 ? null : a2 === r3 && c2 === i2 ? o2 : (i2 = c2, o2 = n3(r3 = a2, u2));\n          };\n        }(t2, r2, Zi(this, \"style.\" + t2, n2))).each(function(t3, n3) {\n          var e3, r3, i2, o2, a2 = \"style.\" + n3, u2 = \"end.\" + a2;\n          return function() {\n            var c2 = Hi(this, t3), f2 = c2.on, s2 = null == c2.value[a2] ? o2 || (o2 = lo(n3)) : void 0;\n            f2 === e3 && i2 === s2 || (r3 = (e3 = f2).copy()).on(u2, i2 = s2), c2.on = r3;\n          };\n        }(this._id, t2)) : this.styleTween(t2, function(t3, n3, e3) {\n          var r3, i2, o2 = e3 + \"\";\n          return function() {\n            var a2 = _n(this, t3);\n            return a2 === o2 ? null : a2 === r3 ? i2 : i2 = n3(r3 = a2, e3);\n          };\n        }(t2, r2, n2), e2).on(\"end.style.\" + t2, null);\n      }, styleTween: function(t2, n2, e2) {\n        var r2 = \"style.\" + (t2 += \"\");\n        if (arguments.length < 2)\n          return (r2 = this.tween(r2)) && r2._value;\n        if (null == n2)\n          return this.tween(r2, null);\n        if (\"function\" != typeof n2)\n          throw new Error();\n        return this.tween(r2, function(t3, n3, e3) {\n          var r3, i2;\n          function o2() {\n            var o3 = n3.apply(this, arguments);\n            return o3 !== i2 && (r3 = (i2 = o3) && /* @__PURE__ */ function(t4, n4, e4) {\n              return function(r4) {\n                this.style.setProperty(t4, n4.call(this, r4), e4);\n              };\n            }(t3, o3, e3)), r3;\n          }\n          return o2._value = n3, o2;\n        }(t2, n2, null == e2 ? \"\" : e2));\n      }, text: function(t2) {\n        return this.tween(\"text\", \"function\" == typeof t2 ? /* @__PURE__ */ function(t3) {\n          return function() {\n            var n2 = t3(this);\n            this.textContent = null == n2 ? \"\" : n2;\n          };\n        }(Zi(this, \"text\", t2)) : /* @__PURE__ */ function(t3) {\n          return function() {\n            this.textContent = t3;\n          };\n        }(null == t2 ? \"\" : t2 + \"\"));\n      }, textTween: function(t2) {\n        var n2 = \"text\";\n        if (arguments.length < 1)\n          return (n2 = this.tween(n2)) && n2._value;\n        if (null == t2)\n          return this.tween(n2, null);\n        if (\"function\" != typeof t2)\n          throw new Error();\n        return this.tween(n2, function(t3) {\n          var n3, e2;\n          function r2() {\n            var r3 = t3.apply(this, arguments);\n            return r3 !== e2 && (n3 = (e2 = r3) && /* @__PURE__ */ function(t4) {\n              return function(n4) {\n                this.textContent = t4.call(this, n4);\n              };\n            }(r3)), n3;\n          }\n          return r2._value = t3, r2;\n        }(t2));\n      }, remove: function() {\n        return this.on(\"end.remove\", /* @__PURE__ */ function(t2) {\n          return function() {\n            var n2 = this.parentNode;\n            for (var e2 in this.__transition)\n              if (+e2 !== t2)\n                return;\n            n2 && n2.removeChild(this);\n          };\n        }(this._id));\n      }, tween: function(t2, n2) {\n        var e2 = this._id;\n        if (t2 += \"\", arguments.length < 2) {\n          for (var r2, i2 = Xi(this.node(), e2).tween, o2 = 0, a2 = i2.length; o2 < a2; ++o2)\n            if ((r2 = i2[o2]).name === t2)\n              return r2.value;\n          return null;\n        }\n        return this.each((null == n2 ? Vi : Wi)(e2, t2, n2));\n      }, delay: function(t2) {\n        var n2 = this._id;\n        return arguments.length ? this.each((\"function\" == typeof t2 ? ao : uo)(n2, t2)) : Xi(this.node(), n2).delay;\n      }, duration: function(t2) {\n        var n2 = this._id;\n        return arguments.length ? this.each((\"function\" == typeof t2 ? co : fo)(n2, t2)) : Xi(this.node(), n2).duration;\n      }, ease: function(t2) {\n        var n2 = this._id;\n        return arguments.length ? this.each(function(t3, n3) {\n          if (\"function\" != typeof n3)\n            throw new Error();\n          return function() {\n            Hi(this, t3).ease = n3;\n          };\n        }(n2, t2)) : Xi(this.node(), n2).ease;\n      }, easeVarying: function(t2) {\n        if (\"function\" != typeof t2)\n          throw new Error();\n        return this.each(/* @__PURE__ */ function(t3, n2) {\n          return function() {\n            var e2 = n2.apply(this, arguments);\n            if (\"function\" != typeof e2)\n              throw new Error();\n            Hi(this, t3).ease = e2;\n          };\n        }(this._id, t2));\n      }, end: function() {\n        var t2, n2, e2 = this, r2 = e2._id, i2 = e2.size();\n        return new Promise(function(o2, a2) {\n          var u2 = { value: a2 }, c2 = { value: function() {\n            0 == --i2 && o2();\n          } };\n          e2.each(function() {\n            var e3 = Hi(this, r2), i3 = e3.on;\n            i3 !== t2 && ((n2 = (t2 = i3).copy())._.cancel.push(u2), n2._.interrupt.push(u2), n2._.end.push(c2)), e3.on = n2;\n          }), 0 === i2 && o2();\n        });\n      }, [Symbol.iterator]: vo[Symbol.iterator] };\n      function _o(t2) {\n        return ((t2 *= 2) <= 1 ? t2 * t2 : --t2 * (2 - t2) + 1) / 2;\n      }\n      function bo(t2) {\n        return ((t2 *= 2) <= 1 ? t2 * t2 * t2 : (t2 -= 2) * t2 * t2 + 2) / 2;\n      }\n      var mo = function t2(n2) {\n        function e2(t3) {\n          return Math.pow(t3, n2);\n        }\n        return n2 = +n2, e2.exponent = t2, e2;\n      }(3), xo = function t2(n2) {\n        function e2(t3) {\n          return 1 - Math.pow(1 - t3, n2);\n        }\n        return n2 = +n2, e2.exponent = t2, e2;\n      }(3), wo = function t2(n2) {\n        function e2(t3) {\n          return ((t3 *= 2) <= 1 ? Math.pow(t3, n2) : 2 - Math.pow(2 - t3, n2)) / 2;\n        }\n        return n2 = +n2, e2.exponent = t2, e2;\n      }(3), Mo = Math.PI, To = Mo / 2;\n      function Ao(t2) {\n        return (1 - Math.cos(Mo * t2)) / 2;\n      }\n      function So(t2) {\n        return 1.0009775171065494 * (Math.pow(2, -10 * t2) - 9765625e-10);\n      }\n      function Eo(t2) {\n        return ((t2 *= 2) <= 1 ? So(1 - t2) : 2 - So(t2 - 1)) / 2;\n      }\n      function No(t2) {\n        return ((t2 *= 2) <= 1 ? 1 - Math.sqrt(1 - t2 * t2) : Math.sqrt(1 - (t2 -= 2) * t2) + 1) / 2;\n      }\n      var ko = 4 / 11, Co = 6 / 11, Po = 8 / 11, zo = 3 / 4, $o = 9 / 11, Do = 10 / 11, Ro = 15 / 16, Fo = 21 / 22, qo = 63 / 64, Uo = 1 / ko / ko;\n      function Io(t2) {\n        return (t2 = +t2) < ko ? Uo * t2 * t2 : t2 < Po ? Uo * (t2 -= Co) * t2 + zo : t2 < Do ? Uo * (t2 -= $o) * t2 + Ro : Uo * (t2 -= Fo) * t2 + qo;\n      }\n      var Oo = 1.70158, Bo = function t2(n2) {\n        function e2(t3) {\n          return (t3 = +t3) * t3 * (n2 * (t3 - 1) + t3);\n        }\n        return n2 = +n2, e2.overshoot = t2, e2;\n      }(Oo), Yo = function t2(n2) {\n        function e2(t3) {\n          return --t3 * t3 * ((t3 + 1) * n2 + t3) + 1;\n        }\n        return n2 = +n2, e2.overshoot = t2, e2;\n      }(Oo), Lo = function t2(n2) {\n        function e2(t3) {\n          return ((t3 *= 2) < 1 ? t3 * t3 * ((n2 + 1) * t3 - n2) : (t3 -= 2) * t3 * ((n2 + 1) * t3 + n2) + 2) / 2;\n        }\n        return n2 = +n2, e2.overshoot = t2, e2;\n      }(Oo), jo = 2 * Math.PI, Ho = function t2(n2, e2) {\n        var r2 = Math.asin(1 / (n2 = Math.max(1, n2))) * (e2 /= jo);\n        function i2(t3) {\n          return n2 * So(- --t3) * Math.sin((r2 - t3) / e2);\n        }\n        return i2.amplitude = function(n3) {\n          return t2(n3, e2 * jo);\n        }, i2.period = function(e3) {\n          return t2(n2, e3);\n        }, i2;\n      }(1, 0.3), Xo = function t2(n2, e2) {\n        var r2 = Math.asin(1 / (n2 = Math.max(1, n2))) * (e2 /= jo);\n        function i2(t3) {\n          return 1 - n2 * So(t3 = +t3) * Math.sin((t3 + r2) / e2);\n        }\n        return i2.amplitude = function(n3) {\n          return t2(n3, e2 * jo);\n        }, i2.period = function(e3) {\n          return t2(n2, e3);\n        }, i2;\n      }(1, 0.3), Go = function t2(n2, e2) {\n        var r2 = Math.asin(1 / (n2 = Math.max(1, n2))) * (e2 /= jo);\n        function i2(t3) {\n          return ((t3 = 2 * t3 - 1) < 0 ? n2 * So(-t3) * Math.sin((r2 - t3) / e2) : 2 - n2 * So(t3) * Math.sin((r2 + t3) / e2)) / 2;\n        }\n        return i2.amplitude = function(n3) {\n          return t2(n3, e2 * jo);\n        }, i2.period = function(e3) {\n          return t2(n2, e3);\n        }, i2;\n      }(1, 0.3), Vo = { time: null, delay: 0, duration: 250, ease: bo };\n      function Wo(t2, n2) {\n        for (var e2; !(e2 = t2.__transition) || !(e2 = e2[n2]); )\n          if (!(t2 = t2.parentNode))\n            throw new Error(`transition ${n2} not found`);\n        return e2;\n      }\n      Wn.prototype.interrupt = function(t2) {\n        return this.each(function() {\n          Gi(this, t2);\n        });\n      }, Wn.prototype.transition = function(t2) {\n        var n2, e2;\n        t2 instanceof po ? (n2 = t2._id, t2 = t2._name) : (n2 = yo(), (e2 = Vo).time = Ai(), t2 = null == t2 ? null : t2 + \"\");\n        for (var r2 = this._groups, i2 = r2.length, o2 = 0; o2 < i2; ++o2)\n          for (var a2, u2 = r2[o2], c2 = u2.length, f2 = 0; f2 < c2; ++f2)\n            (a2 = u2[f2]) && Li(a2, t2, n2, f2, u2, e2 || Wo(a2, n2));\n        return new po(r2, this._parents, t2, n2);\n      };\n      var Zo = [null];\n      var Ko = (t2) => () => t2;\n      function Qo(t2, { sourceEvent: n2, target: e2, selection: r2, mode: i2, dispatch: o2 }) {\n        Object.defineProperties(this, { type: { value: t2, enumerable: true, configurable: true }, sourceEvent: { value: n2, enumerable: true, configurable: true }, target: { value: e2, enumerable: true, configurable: true }, selection: { value: r2, enumerable: true, configurable: true }, mode: { value: i2, enumerable: true, configurable: true }, _: { value: o2 } });\n      }\n      function Jo(t2) {\n        t2.preventDefault(), t2.stopImmediatePropagation();\n      }\n      var ta = { name: \"drag\" }, na = { name: \"space\" }, ea = { name: \"handle\" }, ra = { name: \"center\" };\n      const { abs: ia, max: oa, min: aa } = Math;\n      function ua(t2) {\n        return [+t2[0], +t2[1]];\n      }\n      function ca(t2) {\n        return [ua(t2[0]), ua(t2[1])];\n      }\n      var fa = { name: \"x\", handles: [\"w\", \"e\"].map(va), input: function(t2, n2) {\n        return null == t2 ? null : [[+t2[0], n2[0][1]], [+t2[1], n2[1][1]]];\n      }, output: function(t2) {\n        return t2 && [t2[0][0], t2[1][0]];\n      } }, sa = { name: \"y\", handles: [\"n\", \"s\"].map(va), input: function(t2, n2) {\n        return null == t2 ? null : [[n2[0][0], +t2[0]], [n2[1][0], +t2[1]]];\n      }, output: function(t2) {\n        return t2 && [t2[0][1], t2[1][1]];\n      } }, la = { name: \"xy\", handles: [\"n\", \"w\", \"e\", \"s\", \"nw\", \"ne\", \"sw\", \"se\"].map(va), input: function(t2) {\n        return null == t2 ? null : ca(t2);\n      }, output: function(t2) {\n        return t2;\n      } }, ha = { overlay: \"crosshair\", selection: \"move\", n: \"ns-resize\", e: \"ew-resize\", s: \"ns-resize\", w: \"ew-resize\", nw: \"nwse-resize\", ne: \"nesw-resize\", se: \"nwse-resize\", sw: \"nesw-resize\" }, da = { e: \"w\", w: \"e\", nw: \"ne\", ne: \"nw\", se: \"sw\", sw: \"se\" }, pa = { n: \"s\", s: \"n\", nw: \"sw\", ne: \"se\", se: \"ne\", sw: \"nw\" }, ga = { overlay: 1, selection: 1, n: null, e: 1, s: null, w: -1, nw: -1, ne: 1, se: 1, sw: -1 }, ya = { overlay: 1, selection: 1, n: -1, e: null, s: 1, w: null, nw: -1, ne: -1, se: 1, sw: 1 };\n      function va(t2) {\n        return { type: t2 };\n      }\n      function _a(t2) {\n        return !t2.ctrlKey && !t2.button;\n      }\n      function ba() {\n        var t2 = this.ownerSVGElement || this;\n        return t2.hasAttribute(\"viewBox\") ? [[(t2 = t2.viewBox.baseVal).x, t2.y], [t2.x + t2.width, t2.y + t2.height]] : [[0, 0], [t2.width.baseVal.value, t2.height.baseVal.value]];\n      }\n      function ma() {\n        return navigator.maxTouchPoints || \"ontouchstart\" in this;\n      }\n      function xa(t2) {\n        for (; !t2.__brush; )\n          if (!(t2 = t2.parentNode))\n            return;\n        return t2.__brush;\n      }\n      function wa(t2) {\n        var n2, e2 = ba, r2 = _a, i2 = ma, o2 = true, a2 = $t(\"start\", \"brush\", \"end\"), u2 = 6;\n        function c2(n3) {\n          var e3 = n3.property(\"__brush\", g2).selectAll(\".overlay\").data([va(\"overlay\")]);\n          e3.enter().append(\"rect\").attr(\"class\", \"overlay\").attr(\"pointer-events\", \"all\").attr(\"cursor\", ha.overlay).merge(e3).each(function() {\n            var t3 = xa(this).extent;\n            Zn(this).attr(\"x\", t3[0][0]).attr(\"y\", t3[0][1]).attr(\"width\", t3[1][0] - t3[0][0]).attr(\"height\", t3[1][1] - t3[0][1]);\n          }), n3.selectAll(\".selection\").data([va(\"selection\")]).enter().append(\"rect\").attr(\"class\", \"selection\").attr(\"cursor\", ha.selection).attr(\"fill\", \"#777\").attr(\"fill-opacity\", 0.3).attr(\"stroke\", \"#fff\").attr(\"shape-rendering\", \"crispEdges\");\n          var r3 = n3.selectAll(\".handle\").data(t2.handles, function(t3) {\n            return t3.type;\n          });\n          r3.exit().remove(), r3.enter().append(\"rect\").attr(\"class\", function(t3) {\n            return \"handle handle--\" + t3.type;\n          }).attr(\"cursor\", function(t3) {\n            return ha[t3.type];\n          }), n3.each(f2).attr(\"fill\", \"none\").attr(\"pointer-events\", \"all\").on(\"mousedown.brush\", h2).filter(i2).on(\"touchstart.brush\", h2).on(\"touchmove.brush\", d2).on(\"touchend.brush touchcancel.brush\", p2).style(\"touch-action\", \"none\").style(\"-webkit-tap-highlight-color\", \"rgba(0,0,0,0)\");\n        }\n        function f2() {\n          var t3 = Zn(this), n3 = xa(this).selection;\n          n3 ? (t3.selectAll(\".selection\").style(\"display\", null).attr(\"x\", n3[0][0]).attr(\"y\", n3[0][1]).attr(\"width\", n3[1][0] - n3[0][0]).attr(\"height\", n3[1][1] - n3[0][1]), t3.selectAll(\".handle\").style(\"display\", null).attr(\"x\", function(t4) {\n            return \"e\" === t4.type[t4.type.length - 1] ? n3[1][0] - u2 / 2 : n3[0][0] - u2 / 2;\n          }).attr(\"y\", function(t4) {\n            return \"s\" === t4.type[0] ? n3[1][1] - u2 / 2 : n3[0][1] - u2 / 2;\n          }).attr(\"width\", function(t4) {\n            return \"n\" === t4.type || \"s\" === t4.type ? n3[1][0] - n3[0][0] + u2 : u2;\n          }).attr(\"height\", function(t4) {\n            return \"e\" === t4.type || \"w\" === t4.type ? n3[1][1] - n3[0][1] + u2 : u2;\n          })) : t3.selectAll(\".selection,.handle\").style(\"display\", \"none\").attr(\"x\", null).attr(\"y\", null).attr(\"width\", null).attr(\"height\", null);\n        }\n        function s2(t3, n3, e3) {\n          var r3 = t3.__brush.emitter;\n          return !r3 || e3 && r3.clean ? new l2(t3, n3, e3) : r3;\n        }\n        function l2(t3, n3, e3) {\n          this.that = t3, this.args = n3, this.state = t3.__brush, this.active = 0, this.clean = e3;\n        }\n        function h2(e3) {\n          if ((!n2 || e3.touches) && r2.apply(this, arguments)) {\n            var i3, a3, u3, c3, l3, h3, d4, p3, g3, y2, v2, _2 = this, b2 = e3.target.__data__.type, m2 = \"selection\" === (o2 && e3.metaKey ? b2 = \"overlay\" : b2) ? ta : o2 && e3.altKey ? ra : ea, x2 = t2 === sa ? null : ga[b2], w2 = t2 === fa ? null : ya[b2], M2 = xa(_2), T2 = M2.extent, A2 = M2.selection, S2 = T2[0][0], E2 = T2[0][1], N2 = T2[1][0], k2 = T2[1][1], C2 = 0, P2 = 0, z2 = x2 && w2 && o2 && e3.shiftKey, $2 = Array.from(e3.touches || [e3], (t3) => {\n              const n3 = t3.identifier;\n              return (t3 = ne(t3, _2)).point0 = t3.slice(), t3.identifier = n3, t3;\n            });\n            Gi(_2);\n            var D2 = s2(_2, arguments, true).beforestart();\n            if (\"overlay\" === b2) {\n              A2 && (g3 = true);\n              const n3 = [$2[0], $2[1] || $2[0]];\n              M2.selection = A2 = [[i3 = t2 === sa ? S2 : aa(n3[0][0], n3[1][0]), u3 = t2 === fa ? E2 : aa(n3[0][1], n3[1][1])], [l3 = t2 === sa ? N2 : oa(n3[0][0], n3[1][0]), d4 = t2 === fa ? k2 : oa(n3[0][1], n3[1][1])]], $2.length > 1 && I2(e3);\n            } else\n              i3 = A2[0][0], u3 = A2[0][1], l3 = A2[1][0], d4 = A2[1][1];\n            a3 = i3, c3 = u3, h3 = l3, p3 = d4;\n            var R2 = Zn(_2).attr(\"pointer-events\", \"none\"), F2 = R2.selectAll(\".overlay\").attr(\"cursor\", ha[b2]);\n            if (e3.touches)\n              D2.moved = U2, D2.ended = O2;\n            else {\n              var q2 = Zn(e3.view).on(\"mousemove.brush\", U2, true).on(\"mouseup.brush\", O2, true);\n              o2 && q2.on(\"keydown.brush\", function(t3) {\n                switch (t3.keyCode) {\n                  case 16:\n                    z2 = x2 && w2;\n                    break;\n                  case 18:\n                    m2 === ea && (x2 && (l3 = h3 - C2 * x2, i3 = a3 + C2 * x2), w2 && (d4 = p3 - P2 * w2, u3 = c3 + P2 * w2), m2 = ra, I2(t3));\n                    break;\n                  case 32:\n                    m2 !== ea && m2 !== ra || (x2 < 0 ? l3 = h3 - C2 : x2 > 0 && (i3 = a3 - C2), w2 < 0 ? d4 = p3 - P2 : w2 > 0 && (u3 = c3 - P2), m2 = na, F2.attr(\"cursor\", ha.selection), I2(t3));\n                    break;\n                  default:\n                    return;\n                }\n                Jo(t3);\n              }, true).on(\"keyup.brush\", function(t3) {\n                switch (t3.keyCode) {\n                  case 16:\n                    z2 && (y2 = v2 = z2 = false, I2(t3));\n                    break;\n                  case 18:\n                    m2 === ra && (x2 < 0 ? l3 = h3 : x2 > 0 && (i3 = a3), w2 < 0 ? d4 = p3 : w2 > 0 && (u3 = c3), m2 = ea, I2(t3));\n                    break;\n                  case 32:\n                    m2 === na && (t3.altKey ? (x2 && (l3 = h3 - C2 * x2, i3 = a3 + C2 * x2), w2 && (d4 = p3 - P2 * w2, u3 = c3 + P2 * w2), m2 = ra) : (x2 < 0 ? l3 = h3 : x2 > 0 && (i3 = a3), w2 < 0 ? d4 = p3 : w2 > 0 && (u3 = c3), m2 = ea), F2.attr(\"cursor\", ha[b2]), I2(t3));\n                    break;\n                  default:\n                    return;\n                }\n                Jo(t3);\n              }, true), ae(e3.view);\n            }\n            f2.call(_2), D2.start(e3, m2.name);\n          }\n          function U2(t3) {\n            for (const n3 of t3.changedTouches || [t3])\n              for (const t4 of $2)\n                t4.identifier === n3.identifier && (t4.cur = ne(n3, _2));\n            if (z2 && !y2 && !v2 && 1 === $2.length) {\n              const t4 = $2[0];\n              ia(t4.cur[0] - t4[0]) > ia(t4.cur[1] - t4[1]) ? v2 = true : y2 = true;\n            }\n            for (const t4 of $2)\n              t4.cur && (t4[0] = t4.cur[0], t4[1] = t4.cur[1]);\n            g3 = true, Jo(t3), I2(t3);\n          }\n          function I2(t3) {\n            const n3 = $2[0], e4 = n3.point0;\n            var r3;\n            switch (C2 = n3[0] - e4[0], P2 = n3[1] - e4[1], m2) {\n              case na:\n              case ta:\n                x2 && (C2 = oa(S2 - i3, aa(N2 - l3, C2)), a3 = i3 + C2, h3 = l3 + C2), w2 && (P2 = oa(E2 - u3, aa(k2 - d4, P2)), c3 = u3 + P2, p3 = d4 + P2);\n                break;\n              case ea:\n                $2[1] ? (x2 && (a3 = oa(S2, aa(N2, $2[0][0])), h3 = oa(S2, aa(N2, $2[1][0])), x2 = 1), w2 && (c3 = oa(E2, aa(k2, $2[0][1])), p3 = oa(E2, aa(k2, $2[1][1])), w2 = 1)) : (x2 < 0 ? (C2 = oa(S2 - i3, aa(N2 - i3, C2)), a3 = i3 + C2, h3 = l3) : x2 > 0 && (C2 = oa(S2 - l3, aa(N2 - l3, C2)), a3 = i3, h3 = l3 + C2), w2 < 0 ? (P2 = oa(E2 - u3, aa(k2 - u3, P2)), c3 = u3 + P2, p3 = d4) : w2 > 0 && (P2 = oa(E2 - d4, aa(k2 - d4, P2)), c3 = u3, p3 = d4 + P2));\n                break;\n              case ra:\n                x2 && (a3 = oa(S2, aa(N2, i3 - C2 * x2)), h3 = oa(S2, aa(N2, l3 + C2 * x2))), w2 && (c3 = oa(E2, aa(k2, u3 - P2 * w2)), p3 = oa(E2, aa(k2, d4 + P2 * w2)));\n            }\n            h3 < a3 && (x2 *= -1, r3 = i3, i3 = l3, l3 = r3, r3 = a3, a3 = h3, h3 = r3, b2 in da && F2.attr(\"cursor\", ha[b2 = da[b2]])), p3 < c3 && (w2 *= -1, r3 = u3, u3 = d4, d4 = r3, r3 = c3, c3 = p3, p3 = r3, b2 in pa && F2.attr(\"cursor\", ha[b2 = pa[b2]])), M2.selection && (A2 = M2.selection), y2 && (a3 = A2[0][0], h3 = A2[1][0]), v2 && (c3 = A2[0][1], p3 = A2[1][1]), A2[0][0] === a3 && A2[0][1] === c3 && A2[1][0] === h3 && A2[1][1] === p3 || (M2.selection = [[a3, c3], [h3, p3]], f2.call(_2), D2.brush(t3, m2.name));\n          }\n          function O2(t3) {\n            if (function(t4) {\n              t4.stopImmediatePropagation();\n            }(t3), t3.touches) {\n              if (t3.touches.length)\n                return;\n              n2 && clearTimeout(n2), n2 = setTimeout(function() {\n                n2 = null;\n              }, 500);\n            } else\n              ue(t3.view, g3), q2.on(\"keydown.brush keyup.brush mousemove.brush mouseup.brush\", null);\n            R2.attr(\"pointer-events\", \"all\"), F2.attr(\"cursor\", ha.overlay), M2.selection && (A2 = M2.selection), function(t4) {\n              return t4[0][0] === t4[1][0] || t4[0][1] === t4[1][1];\n            }(A2) && (M2.selection = null, f2.call(_2)), D2.end(t3, m2.name);\n          }\n        }\n        function d2(t3) {\n          s2(this, arguments).moved(t3);\n        }\n        function p2(t3) {\n          s2(this, arguments).ended(t3);\n        }\n        function g2() {\n          var n3 = this.__brush || { selection: null };\n          return n3.extent = ca(e2.apply(this, arguments)), n3.dim = t2, n3;\n        }\n        return c2.move = function(n3, e3, r3) {\n          n3.tween ? n3.on(\"start.brush\", function(t3) {\n            s2(this, arguments).beforestart().start(t3);\n          }).on(\"interrupt.brush end.brush\", function(t3) {\n            s2(this, arguments).end(t3);\n          }).tween(\"brush\", function() {\n            var n4 = this, r4 = n4.__brush, i3 = s2(n4, arguments), o3 = r4.selection, a3 = t2.input(\"function\" == typeof e3 ? e3.apply(this, arguments) : e3, r4.extent), u3 = Gr(o3, a3);\n            function c3(t3) {\n              r4.selection = 1 === t3 && null === a3 ? null : u3(t3), f2.call(n4), i3.brush();\n            }\n            return null !== o3 && null !== a3 ? c3 : c3(1);\n          }) : n3.each(function() {\n            var n4 = this, i3 = arguments, o3 = n4.__brush, a3 = t2.input(\"function\" == typeof e3 ? e3.apply(n4, i3) : e3, o3.extent), u3 = s2(n4, i3).beforestart();\n            Gi(n4), o3.selection = null === a3 ? null : a3, f2.call(n4), u3.start(r3).brush(r3).end(r3);\n          });\n        }, c2.clear = function(t3, n3) {\n          c2.move(t3, null, n3);\n        }, l2.prototype = { beforestart: function() {\n          return 1 == ++this.active && (this.state.emitter = this, this.starting = true), this;\n        }, start: function(t3, n3) {\n          return this.starting ? (this.starting = false, this.emit(\"start\", t3, n3)) : this.emit(\"brush\", t3), this;\n        }, brush: function(t3, n3) {\n          return this.emit(\"brush\", t3, n3), this;\n        }, end: function(t3, n3) {\n          return 0 == --this.active && (delete this.state.emitter, this.emit(\"end\", t3, n3)), this;\n        }, emit: function(n3, e3, r3) {\n          var i3 = Zn(this.that).datum();\n          a2.call(n3, this.that, new Qo(n3, { sourceEvent: e3, target: c2, selection: t2.output(this.state.selection), mode: r3, dispatch: a2 }), i3);\n        } }, c2.extent = function(t3) {\n          return arguments.length ? (e2 = \"function\" == typeof t3 ? t3 : Ko(ca(t3)), c2) : e2;\n        }, c2.filter = function(t3) {\n          return arguments.length ? (r2 = \"function\" == typeof t3 ? t3 : Ko(!!t3), c2) : r2;\n        }, c2.touchable = function(t3) {\n          return arguments.length ? (i2 = \"function\" == typeof t3 ? t3 : Ko(!!t3), c2) : i2;\n        }, c2.handleSize = function(t3) {\n          return arguments.length ? (u2 = +t3, c2) : u2;\n        }, c2.keyModifiers = function(t3) {\n          return arguments.length ? (o2 = !!t3, c2) : o2;\n        }, c2.on = function() {\n          var t3 = a2.on.apply(a2, arguments);\n          return t3 === a2 ? c2 : t3;\n        }, c2;\n      }\n      var Ma = Math.abs, Ta = Math.cos, Aa = Math.sin, Sa = Math.PI, Ea = Sa / 2, Na = 2 * Sa, ka = Math.max, Ca = 1e-12;\n      function Pa(t2, n2) {\n        return Array.from({ length: n2 - t2 }, (n3, e2) => t2 + e2);\n      }\n      function za(t2, n2) {\n        var e2 = 0, r2 = null, i2 = null, o2 = null;\n        function a2(a3) {\n          var u2, c2 = a3.length, f2 = new Array(c2), s2 = Pa(0, c2), l2 = new Array(c2 * c2), h2 = new Array(c2), d2 = 0;\n          a3 = Float64Array.from({ length: c2 * c2 }, n2 ? (t3, n3) => a3[n3 % c2][n3 / c2 | 0] : (t3, n3) => a3[n3 / c2 | 0][n3 % c2]);\n          for (let n3 = 0; n3 < c2; ++n3) {\n            let e3 = 0;\n            for (let r3 = 0; r3 < c2; ++r3)\n              e3 += a3[n3 * c2 + r3] + t2 * a3[r3 * c2 + n3];\n            d2 += f2[n3] = e3;\n          }\n          u2 = (d2 = ka(0, Na - e2 * c2) / d2) ? e2 : Na / c2;\n          {\n            let n3 = 0;\n            r2 && s2.sort((t3, n4) => r2(f2[t3], f2[n4]));\n            for (const e3 of s2) {\n              const r3 = n3;\n              if (t2) {\n                const t3 = Pa(1 + ~c2, c2).filter((t4) => t4 < 0 ? a3[~t4 * c2 + e3] : a3[e3 * c2 + t4]);\n                i2 && t3.sort((t4, n4) => i2(t4 < 0 ? -a3[~t4 * c2 + e3] : a3[e3 * c2 + t4], n4 < 0 ? -a3[~n4 * c2 + e3] : a3[e3 * c2 + n4]));\n                for (const r4 of t3)\n                  if (r4 < 0) {\n                    (l2[~r4 * c2 + e3] || (l2[~r4 * c2 + e3] = { source: null, target: null })).target = { index: e3, startAngle: n3, endAngle: n3 += a3[~r4 * c2 + e3] * d2, value: a3[~r4 * c2 + e3] };\n                  } else {\n                    (l2[e3 * c2 + r4] || (l2[e3 * c2 + r4] = { source: null, target: null })).source = { index: e3, startAngle: n3, endAngle: n3 += a3[e3 * c2 + r4] * d2, value: a3[e3 * c2 + r4] };\n                  }\n                h2[e3] = { index: e3, startAngle: r3, endAngle: n3, value: f2[e3] };\n              } else {\n                const t3 = Pa(0, c2).filter((t4) => a3[e3 * c2 + t4] || a3[t4 * c2 + e3]);\n                i2 && t3.sort((t4, n4) => i2(a3[e3 * c2 + t4], a3[e3 * c2 + n4]));\n                for (const r4 of t3) {\n                  let t4;\n                  if (e3 < r4 ? (t4 = l2[e3 * c2 + r4] || (l2[e3 * c2 + r4] = { source: null, target: null }), t4.source = { index: e3, startAngle: n3, endAngle: n3 += a3[e3 * c2 + r4] * d2, value: a3[e3 * c2 + r4] }) : (t4 = l2[r4 * c2 + e3] || (l2[r4 * c2 + e3] = { source: null, target: null }), t4.target = { index: e3, startAngle: n3, endAngle: n3 += a3[e3 * c2 + r4] * d2, value: a3[e3 * c2 + r4] }, e3 === r4 && (t4.source = t4.target)), t4.source && t4.target && t4.source.value < t4.target.value) {\n                    const n4 = t4.source;\n                    t4.source = t4.target, t4.target = n4;\n                  }\n                }\n                h2[e3] = { index: e3, startAngle: r3, endAngle: n3, value: f2[e3] };\n              }\n              n3 += u2;\n            }\n          }\n          return (l2 = Object.values(l2)).groups = h2, o2 ? l2.sort(o2) : l2;\n        }\n        return a2.padAngle = function(t3) {\n          return arguments.length ? (e2 = ka(0, t3), a2) : e2;\n        }, a2.sortGroups = function(t3) {\n          return arguments.length ? (r2 = t3, a2) : r2;\n        }, a2.sortSubgroups = function(t3) {\n          return arguments.length ? (i2 = t3, a2) : i2;\n        }, a2.sortChords = function(t3) {\n          return arguments.length ? (null == t3 ? o2 = null : (n3 = t3, o2 = function(t4, e3) {\n            return n3(t4.source.value + t4.target.value, e3.source.value + e3.target.value);\n          })._ = t3, a2) : o2 && o2._;\n          var n3;\n        }, a2;\n      }\n      const $a = Math.PI, Da = 2 * $a, Ra = 1e-6, Fa = Da - Ra;\n      function qa(t2) {\n        this._ += t2[0];\n        for (let n2 = 1, e2 = t2.length; n2 < e2; ++n2)\n          this._ += arguments[n2] + t2[n2];\n      }\n      let Ua = class {\n        constructor(t2) {\n          this._x0 = this._y0 = this._x1 = this._y1 = null, this._ = \"\", this._append = null == t2 ? qa : function(t3) {\n            let n2 = Math.floor(t3);\n            if (!(n2 >= 0))\n              throw new Error(`invalid digits: ${t3}`);\n            if (n2 > 15)\n              return qa;\n            const e2 = 10 ** n2;\n            return function(t4) {\n              this._ += t4[0];\n              for (let n3 = 1, r2 = t4.length; n3 < r2; ++n3)\n                this._ += Math.round(arguments[n3] * e2) / e2 + t4[n3];\n            };\n          }(t2);\n        }\n        moveTo(t2, n2) {\n          this._append`M${this._x0 = this._x1 = +t2},${this._y0 = this._y1 = +n2}`;\n        }\n        closePath() {\n          null !== this._x1 && (this._x1 = this._x0, this._y1 = this._y0, this._append`Z`);\n        }\n        lineTo(t2, n2) {\n          this._append`L${this._x1 = +t2},${this._y1 = +n2}`;\n        }\n        quadraticCurveTo(t2, n2, e2, r2) {\n          this._append`Q${+t2},${+n2},${this._x1 = +e2},${this._y1 = +r2}`;\n        }\n        bezierCurveTo(t2, n2, e2, r2, i2, o2) {\n          this._append`C${+t2},${+n2},${+e2},${+r2},${this._x1 = +i2},${this._y1 = +o2}`;\n        }\n        arcTo(t2, n2, e2, r2, i2) {\n          if (t2 = +t2, n2 = +n2, e2 = +e2, r2 = +r2, (i2 = +i2) < 0)\n            throw new Error(`negative radius: ${i2}`);\n          let o2 = this._x1, a2 = this._y1, u2 = e2 - t2, c2 = r2 - n2, f2 = o2 - t2, s2 = a2 - n2, l2 = f2 * f2 + s2 * s2;\n          if (null === this._x1)\n            this._append`M${this._x1 = t2},${this._y1 = n2}`;\n          else if (l2 > Ra)\n            if (Math.abs(s2 * u2 - c2 * f2) > Ra && i2) {\n              let h2 = e2 - o2, d2 = r2 - a2, p2 = u2 * u2 + c2 * c2, g2 = h2 * h2 + d2 * d2, y2 = Math.sqrt(p2), v2 = Math.sqrt(l2), _2 = i2 * Math.tan(($a - Math.acos((p2 + l2 - g2) / (2 * y2 * v2))) / 2), b2 = _2 / v2, m2 = _2 / y2;\n              Math.abs(b2 - 1) > Ra && this._append`L${t2 + b2 * f2},${n2 + b2 * s2}`, this._append`A${i2},${i2},0,0,${+(s2 * h2 > f2 * d2)},${this._x1 = t2 + m2 * u2},${this._y1 = n2 + m2 * c2}`;\n            } else\n              this._append`L${this._x1 = t2},${this._y1 = n2}`;\n          else\n            ;\n        }\n        arc(t2, n2, e2, r2, i2, o2) {\n          if (t2 = +t2, n2 = +n2, o2 = !!o2, (e2 = +e2) < 0)\n            throw new Error(`negative radius: ${e2}`);\n          let a2 = e2 * Math.cos(r2), u2 = e2 * Math.sin(r2), c2 = t2 + a2, f2 = n2 + u2, s2 = 1 ^ o2, l2 = o2 ? r2 - i2 : i2 - r2;\n          null === this._x1 ? this._append`M${c2},${f2}` : (Math.abs(this._x1 - c2) > Ra || Math.abs(this._y1 - f2) > Ra) && this._append`L${c2},${f2}`, e2 && (l2 < 0 && (l2 = l2 % Da + Da), l2 > Fa ? this._append`A${e2},${e2},0,1,${s2},${t2 - a2},${n2 - u2}A${e2},${e2},0,1,${s2},${this._x1 = c2},${this._y1 = f2}` : l2 > Ra && this._append`A${e2},${e2},0,${+(l2 >= $a)},${s2},${this._x1 = t2 + e2 * Math.cos(i2)},${this._y1 = n2 + e2 * Math.sin(i2)}`);\n        }\n        rect(t2, n2, e2, r2) {\n          this._append`M${this._x0 = this._x1 = +t2},${this._y0 = this._y1 = +n2}h${e2 = +e2}v${+r2}h${-e2}Z`;\n        }\n        toString() {\n          return this._;\n        }\n      };\n      function Ia() {\n        return new Ua();\n      }\n      Ia.prototype = Ua.prototype;\n      var Oa = Array.prototype.slice;\n      function Ba(t2) {\n        return function() {\n          return t2;\n        };\n      }\n      function Ya(t2) {\n        return t2.source;\n      }\n      function La(t2) {\n        return t2.target;\n      }\n      function ja(t2) {\n        return t2.radius;\n      }\n      function Ha(t2) {\n        return t2.startAngle;\n      }\n      function Xa(t2) {\n        return t2.endAngle;\n      }\n      function Ga() {\n        return 0;\n      }\n      function Va() {\n        return 10;\n      }\n      function Wa(t2) {\n        var n2 = Ya, e2 = La, r2 = ja, i2 = ja, o2 = Ha, a2 = Xa, u2 = Ga, c2 = null;\n        function f2() {\n          var f3, s2 = n2.apply(this, arguments), l2 = e2.apply(this, arguments), h2 = u2.apply(this, arguments) / 2, d2 = Oa.call(arguments), p2 = +r2.apply(this, (d2[0] = s2, d2)), g2 = o2.apply(this, d2) - Ea, y2 = a2.apply(this, d2) - Ea, v2 = +i2.apply(this, (d2[0] = l2, d2)), _2 = o2.apply(this, d2) - Ea, b2 = a2.apply(this, d2) - Ea;\n          if (c2 || (c2 = f3 = Ia()), h2 > Ca && (Ma(y2 - g2) > 2 * h2 + Ca ? y2 > g2 ? (g2 += h2, y2 -= h2) : (g2 -= h2, y2 += h2) : g2 = y2 = (g2 + y2) / 2, Ma(b2 - _2) > 2 * h2 + Ca ? b2 > _2 ? (_2 += h2, b2 -= h2) : (_2 -= h2, b2 += h2) : _2 = b2 = (_2 + b2) / 2), c2.moveTo(p2 * Ta(g2), p2 * Aa(g2)), c2.arc(0, 0, p2, g2, y2), g2 !== _2 || y2 !== b2)\n            if (t2) {\n              var m2 = v2 - +t2.apply(this, arguments), x2 = (_2 + b2) / 2;\n              c2.quadraticCurveTo(0, 0, m2 * Ta(_2), m2 * Aa(_2)), c2.lineTo(v2 * Ta(x2), v2 * Aa(x2)), c2.lineTo(m2 * Ta(b2), m2 * Aa(b2));\n            } else\n              c2.quadraticCurveTo(0, 0, v2 * Ta(_2), v2 * Aa(_2)), c2.arc(0, 0, v2, _2, b2);\n          if (c2.quadraticCurveTo(0, 0, p2 * Ta(g2), p2 * Aa(g2)), c2.closePath(), f3)\n            return c2 = null, f3 + \"\" || null;\n        }\n        return t2 && (f2.headRadius = function(n3) {\n          return arguments.length ? (t2 = \"function\" == typeof n3 ? n3 : Ba(+n3), f2) : t2;\n        }), f2.radius = function(t3) {\n          return arguments.length ? (r2 = i2 = \"function\" == typeof t3 ? t3 : Ba(+t3), f2) : r2;\n        }, f2.sourceRadius = function(t3) {\n          return arguments.length ? (r2 = \"function\" == typeof t3 ? t3 : Ba(+t3), f2) : r2;\n        }, f2.targetRadius = function(t3) {\n          return arguments.length ? (i2 = \"function\" == typeof t3 ? t3 : Ba(+t3), f2) : i2;\n        }, f2.startAngle = function(t3) {\n          return arguments.length ? (o2 = \"function\" == typeof t3 ? t3 : Ba(+t3), f2) : o2;\n        }, f2.endAngle = function(t3) {\n          return arguments.length ? (a2 = \"function\" == typeof t3 ? t3 : Ba(+t3), f2) : a2;\n        }, f2.padAngle = function(t3) {\n          return arguments.length ? (u2 = \"function\" == typeof t3 ? t3 : Ba(+t3), f2) : u2;\n        }, f2.source = function(t3) {\n          return arguments.length ? (n2 = t3, f2) : n2;\n        }, f2.target = function(t3) {\n          return arguments.length ? (e2 = t3, f2) : e2;\n        }, f2.context = function(t3) {\n          return arguments.length ? (c2 = null == t3 ? null : t3, f2) : c2;\n        }, f2;\n      }\n      var Za = Array.prototype.slice;\n      function Ka(t2, n2) {\n        return t2 - n2;\n      }\n      var Qa = (t2) => () => t2;\n      function Ja(t2, n2) {\n        for (var e2, r2 = -1, i2 = n2.length; ++r2 < i2; )\n          if (e2 = tu(t2, n2[r2]))\n            return e2;\n        return 0;\n      }\n      function tu(t2, n2) {\n        for (var e2 = n2[0], r2 = n2[1], i2 = -1, o2 = 0, a2 = t2.length, u2 = a2 - 1; o2 < a2; u2 = o2++) {\n          var c2 = t2[o2], f2 = c2[0], s2 = c2[1], l2 = t2[u2], h2 = l2[0], d2 = l2[1];\n          if (nu(c2, l2, n2))\n            return 0;\n          s2 > r2 != d2 > r2 && e2 < (h2 - f2) * (r2 - s2) / (d2 - s2) + f2 && (i2 = -i2);\n        }\n        return i2;\n      }\n      function nu(t2, n2, e2) {\n        var r2, i2, o2, a2;\n        return function(t3, n3, e3) {\n          return (n3[0] - t3[0]) * (e3[1] - t3[1]) == (e3[0] - t3[0]) * (n3[1] - t3[1]);\n        }(t2, n2, e2) && (i2 = t2[r2 = +(t2[0] === n2[0])], o2 = e2[r2], a2 = n2[r2], i2 <= o2 && o2 <= a2 || a2 <= o2 && o2 <= i2);\n      }\n      function eu() {\n      }\n      var ru = [[], [[[1, 1.5], [0.5, 1]]], [[[1.5, 1], [1, 1.5]]], [[[1.5, 1], [0.5, 1]]], [[[1, 0.5], [1.5, 1]]], [[[1, 1.5], [0.5, 1]], [[1, 0.5], [1.5, 1]]], [[[1, 0.5], [1, 1.5]]], [[[1, 0.5], [0.5, 1]]], [[[0.5, 1], [1, 0.5]]], [[[1, 1.5], [1, 0.5]]], [[[0.5, 1], [1, 0.5]], [[1.5, 1], [1, 1.5]]], [[[1.5, 1], [1, 0.5]]], [[[0.5, 1], [1.5, 1]]], [[[1, 1.5], [1.5, 1]]], [[[0.5, 1], [1, 1.5]]], []];\n      function iu() {\n        var t2 = 1, n2 = 1, e2 = K, r2 = u2;\n        function i2(t3) {\n          var n3 = e2(t3);\n          if (Array.isArray(n3))\n            n3 = n3.slice().sort(Ka);\n          else {\n            const e3 = M(t3, ou);\n            for (n3 = G(...Z(e3[0], e3[1], n3), n3); n3[n3.length - 1] >= e3[1]; )\n              n3.pop();\n            for (; n3[1] < e3[0]; )\n              n3.shift();\n          }\n          return n3.map((n4) => o2(t3, n4));\n        }\n        function o2(e3, i3) {\n          const o3 = null == i3 ? NaN : +i3;\n          if (isNaN(o3))\n            throw new Error(`invalid value: ${i3}`);\n          var u3 = [], c2 = [];\n          return function(e4, r3, i4) {\n            var o4, u4, c3, f2, s2, l2, h2 = new Array(), d2 = new Array();\n            o4 = u4 = -1, f2 = au(e4[0], r3), ru[f2 << 1].forEach(p2);\n            for (; ++o4 < t2 - 1; )\n              c3 = f2, f2 = au(e4[o4 + 1], r3), ru[c3 | f2 << 1].forEach(p2);\n            ru[f2 << 0].forEach(p2);\n            for (; ++u4 < n2 - 1; ) {\n              for (o4 = -1, f2 = au(e4[u4 * t2 + t2], r3), s2 = au(e4[u4 * t2], r3), ru[f2 << 1 | s2 << 2].forEach(p2); ++o4 < t2 - 1; )\n                c3 = f2, f2 = au(e4[u4 * t2 + t2 + o4 + 1], r3), l2 = s2, s2 = au(e4[u4 * t2 + o4 + 1], r3), ru[c3 | f2 << 1 | s2 << 2 | l2 << 3].forEach(p2);\n              ru[f2 | s2 << 3].forEach(p2);\n            }\n            o4 = -1, s2 = e4[u4 * t2] >= r3, ru[s2 << 2].forEach(p2);\n            for (; ++o4 < t2 - 1; )\n              l2 = s2, s2 = au(e4[u4 * t2 + o4 + 1], r3), ru[s2 << 2 | l2 << 3].forEach(p2);\n            function p2(t3) {\n              var n3, e5, r4 = [t3[0][0] + o4, t3[0][1] + u4], c4 = [t3[1][0] + o4, t3[1][1] + u4], f3 = a2(r4), s3 = a2(c4);\n              (n3 = d2[f3]) ? (e5 = h2[s3]) ? (delete d2[n3.end], delete h2[e5.start], n3 === e5 ? (n3.ring.push(c4), i4(n3.ring)) : h2[n3.start] = d2[e5.end] = { start: n3.start, end: e5.end, ring: n3.ring.concat(e5.ring) }) : (delete d2[n3.end], n3.ring.push(c4), d2[n3.end = s3] = n3) : (n3 = h2[s3]) ? (e5 = d2[f3]) ? (delete h2[n3.start], delete d2[e5.end], n3 === e5 ? (n3.ring.push(c4), i4(n3.ring)) : h2[e5.start] = d2[n3.end] = { start: e5.start, end: n3.end, ring: e5.ring.concat(n3.ring) }) : (delete h2[n3.start], n3.ring.unshift(r4), h2[n3.start = f3] = n3) : h2[f3] = d2[s3] = { start: f3, end: s3, ring: [r4, c4] };\n            }\n            ru[s2 << 3].forEach(p2);\n          }(e3, o3, function(t3) {\n            r2(t3, e3, o3), function(t4) {\n              for (var n3 = 0, e4 = t4.length, r3 = t4[e4 - 1][1] * t4[0][0] - t4[e4 - 1][0] * t4[0][1]; ++n3 < e4; )\n                r3 += t4[n3 - 1][1] * t4[n3][0] - t4[n3 - 1][0] * t4[n3][1];\n              return r3;\n            }(t3) > 0 ? u3.push([t3]) : c2.push(t3);\n          }), c2.forEach(function(t3) {\n            for (var n3, e4 = 0, r3 = u3.length; e4 < r3; ++e4)\n              if (-1 !== Ja((n3 = u3[e4])[0], t3))\n                return void n3.push(t3);\n          }), { type: \"MultiPolygon\", value: i3, coordinates: u3 };\n        }\n        function a2(n3) {\n          return 2 * n3[0] + n3[1] * (t2 + 1) * 4;\n        }\n        function u2(e3, r3, i3) {\n          e3.forEach(function(e4) {\n            var o3 = e4[0], a3 = e4[1], u3 = 0 | o3, c2 = 0 | a3, f2 = uu(r3[c2 * t2 + u3]);\n            o3 > 0 && o3 < t2 && u3 === o3 && (e4[0] = cu(o3, uu(r3[c2 * t2 + u3 - 1]), f2, i3)), a3 > 0 && a3 < n2 && c2 === a3 && (e4[1] = cu(a3, uu(r3[(c2 - 1) * t2 + u3]), f2, i3));\n          });\n        }\n        return i2.contour = o2, i2.size = function(e3) {\n          if (!arguments.length)\n            return [t2, n2];\n          var r3 = Math.floor(e3[0]), o3 = Math.floor(e3[1]);\n          if (!(r3 >= 0 && o3 >= 0))\n            throw new Error(\"invalid size\");\n          return t2 = r3, n2 = o3, i2;\n        }, i2.thresholds = function(t3) {\n          return arguments.length ? (e2 = \"function\" == typeof t3 ? t3 : Array.isArray(t3) ? Qa(Za.call(t3)) : Qa(t3), i2) : e2;\n        }, i2.smooth = function(t3) {\n          return arguments.length ? (r2 = t3 ? u2 : eu, i2) : r2 === u2;\n        }, i2;\n      }\n      function ou(t2) {\n        return isFinite(t2) ? t2 : NaN;\n      }\n      function au(t2, n2) {\n        return null != t2 && +t2 >= n2;\n      }\n      function uu(t2) {\n        return null == t2 || isNaN(t2 = +t2) ? -1 / 0 : t2;\n      }\n      function cu(t2, n2, e2, r2) {\n        const i2 = r2 - n2, o2 = e2 - n2, a2 = isFinite(i2) || isFinite(o2) ? i2 / o2 : Math.sign(i2) / Math.sign(o2);\n        return isNaN(a2) ? t2 : t2 + a2 - 0.5;\n      }\n      function fu(t2) {\n        return t2[0];\n      }\n      function su(t2) {\n        return t2[1];\n      }\n      function lu() {\n        return 1;\n      }\n      const hu = 134217729, du = 33306690738754706e-32;\n      function pu(t2, n2, e2, r2, i2) {\n        let o2, a2, u2, c2, f2 = n2[0], s2 = r2[0], l2 = 0, h2 = 0;\n        s2 > f2 == s2 > -f2 ? (o2 = f2, f2 = n2[++l2]) : (o2 = s2, s2 = r2[++h2]);\n        let d2 = 0;\n        if (l2 < t2 && h2 < e2)\n          for (s2 > f2 == s2 > -f2 ? (a2 = f2 + o2, u2 = o2 - (a2 - f2), f2 = n2[++l2]) : (a2 = s2 + o2, u2 = o2 - (a2 - s2), s2 = r2[++h2]), o2 = a2, 0 !== u2 && (i2[d2++] = u2); l2 < t2 && h2 < e2; )\n            s2 > f2 == s2 > -f2 ? (a2 = o2 + f2, c2 = a2 - o2, u2 = o2 - (a2 - c2) + (f2 - c2), f2 = n2[++l2]) : (a2 = o2 + s2, c2 = a2 - o2, u2 = o2 - (a2 - c2) + (s2 - c2), s2 = r2[++h2]), o2 = a2, 0 !== u2 && (i2[d2++] = u2);\n        for (; l2 < t2; )\n          a2 = o2 + f2, c2 = a2 - o2, u2 = o2 - (a2 - c2) + (f2 - c2), f2 = n2[++l2], o2 = a2, 0 !== u2 && (i2[d2++] = u2);\n        for (; h2 < e2; )\n          a2 = o2 + s2, c2 = a2 - o2, u2 = o2 - (a2 - c2) + (s2 - c2), s2 = r2[++h2], o2 = a2, 0 !== u2 && (i2[d2++] = u2);\n        return 0 === o2 && 0 !== d2 || (i2[d2++] = o2), d2;\n      }\n      function gu(t2) {\n        return new Float64Array(t2);\n      }\n      const yu = 22204460492503146e-32, vu = 11093356479670487e-47, _u = gu(4), bu = gu(8), mu = gu(12), xu = gu(16), wu = gu(4);\n      function Mu(t2, n2, e2, r2, i2, o2) {\n        const a2 = (n2 - o2) * (e2 - i2), u2 = (t2 - i2) * (r2 - o2), c2 = a2 - u2, f2 = Math.abs(a2 + u2);\n        return Math.abs(c2) >= 33306690738754716e-32 * f2 ? c2 : -function(t3, n3, e3, r3, i3, o3, a3) {\n          let u3, c3, f3, s2, l2, h2, d2, p2, g2, y2, v2, _2, b2, m2, x2, w2, M2, T2;\n          const A2 = t3 - i3, S2 = e3 - i3, E2 = n3 - o3, N2 = r3 - o3;\n          m2 = A2 * N2, h2 = hu * A2, d2 = h2 - (h2 - A2), p2 = A2 - d2, h2 = hu * N2, g2 = h2 - (h2 - N2), y2 = N2 - g2, x2 = p2 * y2 - (m2 - d2 * g2 - p2 * g2 - d2 * y2), w2 = E2 * S2, h2 = hu * E2, d2 = h2 - (h2 - E2), p2 = E2 - d2, h2 = hu * S2, g2 = h2 - (h2 - S2), y2 = S2 - g2, M2 = p2 * y2 - (w2 - d2 * g2 - p2 * g2 - d2 * y2), v2 = x2 - M2, l2 = x2 - v2, _u[0] = x2 - (v2 + l2) + (l2 - M2), _2 = m2 + v2, l2 = _2 - m2, b2 = m2 - (_2 - l2) + (v2 - l2), v2 = b2 - w2, l2 = b2 - v2, _u[1] = b2 - (v2 + l2) + (l2 - w2), T2 = _2 + v2, l2 = T2 - _2, _u[2] = _2 - (T2 - l2) + (v2 - l2), _u[3] = T2;\n          let k2 = function(t4, n4) {\n            let e4 = n4[0];\n            for (let r4 = 1; r4 < t4; r4++)\n              e4 += n4[r4];\n            return e4;\n          }(4, _u), C2 = yu * a3;\n          if (k2 >= C2 || -k2 >= C2)\n            return k2;\n          if (l2 = t3 - A2, u3 = t3 - (A2 + l2) + (l2 - i3), l2 = e3 - S2, f3 = e3 - (S2 + l2) + (l2 - i3), l2 = n3 - E2, c3 = n3 - (E2 + l2) + (l2 - o3), l2 = r3 - N2, s2 = r3 - (N2 + l2) + (l2 - o3), 0 === u3 && 0 === c3 && 0 === f3 && 0 === s2)\n            return k2;\n          if (C2 = vu * a3 + du * Math.abs(k2), k2 += A2 * s2 + N2 * u3 - (E2 * f3 + S2 * c3), k2 >= C2 || -k2 >= C2)\n            return k2;\n          m2 = u3 * N2, h2 = hu * u3, d2 = h2 - (h2 - u3), p2 = u3 - d2, h2 = hu * N2, g2 = h2 - (h2 - N2), y2 = N2 - g2, x2 = p2 * y2 - (m2 - d2 * g2 - p2 * g2 - d2 * y2), w2 = c3 * S2, h2 = hu * c3, d2 = h2 - (h2 - c3), p2 = c3 - d2, h2 = hu * S2, g2 = h2 - (h2 - S2), y2 = S2 - g2, M2 = p2 * y2 - (w2 - d2 * g2 - p2 * g2 - d2 * y2), v2 = x2 - M2, l2 = x2 - v2, wu[0] = x2 - (v2 + l2) + (l2 - M2), _2 = m2 + v2, l2 = _2 - m2, b2 = m2 - (_2 - l2) + (v2 - l2), v2 = b2 - w2, l2 = b2 - v2, wu[1] = b2 - (v2 + l2) + (l2 - w2), T2 = _2 + v2, l2 = T2 - _2, wu[2] = _2 - (T2 - l2) + (v2 - l2), wu[3] = T2;\n          const P2 = pu(4, _u, 4, wu, bu);\n          m2 = A2 * s2, h2 = hu * A2, d2 = h2 - (h2 - A2), p2 = A2 - d2, h2 = hu * s2, g2 = h2 - (h2 - s2), y2 = s2 - g2, x2 = p2 * y2 - (m2 - d2 * g2 - p2 * g2 - d2 * y2), w2 = E2 * f3, h2 = hu * E2, d2 = h2 - (h2 - E2), p2 = E2 - d2, h2 = hu * f3, g2 = h2 - (h2 - f3), y2 = f3 - g2, M2 = p2 * y2 - (w2 - d2 * g2 - p2 * g2 - d2 * y2), v2 = x2 - M2, l2 = x2 - v2, wu[0] = x2 - (v2 + l2) + (l2 - M2), _2 = m2 + v2, l2 = _2 - m2, b2 = m2 - (_2 - l2) + (v2 - l2), v2 = b2 - w2, l2 = b2 - v2, wu[1] = b2 - (v2 + l2) + (l2 - w2), T2 = _2 + v2, l2 = T2 - _2, wu[2] = _2 - (T2 - l2) + (v2 - l2), wu[3] = T2;\n          const z2 = pu(P2, bu, 4, wu, mu);\n          m2 = u3 * s2, h2 = hu * u3, d2 = h2 - (h2 - u3), p2 = u3 - d2, h2 = hu * s2, g2 = h2 - (h2 - s2), y2 = s2 - g2, x2 = p2 * y2 - (m2 - d2 * g2 - p2 * g2 - d2 * y2), w2 = c3 * f3, h2 = hu * c3, d2 = h2 - (h2 - c3), p2 = c3 - d2, h2 = hu * f3, g2 = h2 - (h2 - f3), y2 = f3 - g2, M2 = p2 * y2 - (w2 - d2 * g2 - p2 * g2 - d2 * y2), v2 = x2 - M2, l2 = x2 - v2, wu[0] = x2 - (v2 + l2) + (l2 - M2), _2 = m2 + v2, l2 = _2 - m2, b2 = m2 - (_2 - l2) + (v2 - l2), v2 = b2 - w2, l2 = b2 - v2, wu[1] = b2 - (v2 + l2) + (l2 - w2), T2 = _2 + v2, l2 = T2 - _2, wu[2] = _2 - (T2 - l2) + (v2 - l2), wu[3] = T2;\n          const $2 = pu(z2, mu, 4, wu, xu);\n          return xu[$2 - 1];\n        }(t2, n2, e2, r2, i2, o2, f2);\n      }\n      const Tu = Math.pow(2, -52), Au = new Uint32Array(512);\n      class Su {\n        static from(t2, n2 = zu, e2 = $u) {\n          const r2 = t2.length, i2 = new Float64Array(2 * r2);\n          for (let o2 = 0; o2 < r2; o2++) {\n            const r3 = t2[o2];\n            i2[2 * o2] = n2(r3), i2[2 * o2 + 1] = e2(r3);\n          }\n          return new Su(i2);\n        }\n        constructor(t2) {\n          const n2 = t2.length >> 1;\n          if (n2 > 0 && \"number\" != typeof t2[0])\n            throw new Error(\"Expected coords to contain numbers.\");\n          this.coords = t2;\n          const e2 = Math.max(2 * n2 - 5, 0);\n          this._triangles = new Uint32Array(3 * e2), this._halfedges = new Int32Array(3 * e2), this._hashSize = Math.ceil(Math.sqrt(n2)), this._hullPrev = new Uint32Array(n2), this._hullNext = new Uint32Array(n2), this._hullTri = new Uint32Array(n2), this._hullHash = new Int32Array(this._hashSize).fill(-1), this._ids = new Uint32Array(n2), this._dists = new Float64Array(n2), this.update();\n        }\n        update() {\n          const { coords: t2, _hullPrev: n2, _hullNext: e2, _hullTri: r2, _hullHash: i2 } = this, o2 = t2.length >> 1;\n          let a2 = 1 / 0, u2 = 1 / 0, c2 = -1 / 0, f2 = -1 / 0;\n          for (let n3 = 0; n3 < o2; n3++) {\n            const e3 = t2[2 * n3], r3 = t2[2 * n3 + 1];\n            e3 < a2 && (a2 = e3), r3 < u2 && (u2 = r3), e3 > c2 && (c2 = e3), r3 > f2 && (f2 = r3), this._ids[n3] = n3;\n          }\n          const s2 = (a2 + c2) / 2, l2 = (u2 + f2) / 2;\n          let h2, d2, p2, g2 = 1 / 0;\n          for (let n3 = 0; n3 < o2; n3++) {\n            const e3 = Eu(s2, l2, t2[2 * n3], t2[2 * n3 + 1]);\n            e3 < g2 && (h2 = n3, g2 = e3);\n          }\n          const y2 = t2[2 * h2], v2 = t2[2 * h2 + 1];\n          g2 = 1 / 0;\n          for (let n3 = 0; n3 < o2; n3++) {\n            if (n3 === h2)\n              continue;\n            const e3 = Eu(y2, v2, t2[2 * n3], t2[2 * n3 + 1]);\n            e3 < g2 && e3 > 0 && (d2 = n3, g2 = e3);\n          }\n          let _2 = t2[2 * d2], b2 = t2[2 * d2 + 1], m2 = 1 / 0;\n          for (let n3 = 0; n3 < o2; n3++) {\n            if (n3 === h2 || n3 === d2)\n              continue;\n            const e3 = ku(y2, v2, _2, b2, t2[2 * n3], t2[2 * n3 + 1]);\n            e3 < m2 && (p2 = n3, m2 = e3);\n          }\n          let x2 = t2[2 * p2], w2 = t2[2 * p2 + 1];\n          if (m2 === 1 / 0) {\n            for (let n4 = 0; n4 < o2; n4++)\n              this._dists[n4] = t2[2 * n4] - t2[0] || t2[2 * n4 + 1] - t2[1];\n            Cu(this._ids, this._dists, 0, o2 - 1);\n            const n3 = new Uint32Array(o2);\n            let e3 = 0;\n            for (let t3 = 0, r3 = -1 / 0; t3 < o2; t3++) {\n              const i3 = this._ids[t3];\n              this._dists[i3] > r3 && (n3[e3++] = i3, r3 = this._dists[i3]);\n            }\n            return this.hull = n3.subarray(0, e3), this.triangles = new Uint32Array(0), void (this.halfedges = new Uint32Array(0));\n          }\n          if (Mu(y2, v2, _2, b2, x2, w2) < 0) {\n            const t3 = d2, n3 = _2, e3 = b2;\n            d2 = p2, _2 = x2, b2 = w2, p2 = t3, x2 = n3, w2 = e3;\n          }\n          const M2 = function(t3, n3, e3, r3, i3, o3) {\n            const a3 = e3 - t3, u3 = r3 - n3, c3 = i3 - t3, f3 = o3 - n3, s3 = a3 * a3 + u3 * u3, l3 = c3 * c3 + f3 * f3, h3 = 0.5 / (a3 * f3 - u3 * c3), d4 = t3 + (f3 * s3 - u3 * l3) * h3, p3 = n3 + (a3 * l3 - c3 * s3) * h3;\n            return { x: d4, y: p3 };\n          }(y2, v2, _2, b2, x2, w2);\n          this._cx = M2.x, this._cy = M2.y;\n          for (let n3 = 0; n3 < o2; n3++)\n            this._dists[n3] = Eu(t2[2 * n3], t2[2 * n3 + 1], M2.x, M2.y);\n          Cu(this._ids, this._dists, 0, o2 - 1), this._hullStart = h2;\n          let T2 = 3;\n          e2[h2] = n2[p2] = d2, e2[d2] = n2[h2] = p2, e2[p2] = n2[d2] = h2, r2[h2] = 0, r2[d2] = 1, r2[p2] = 2, i2.fill(-1), i2[this._hashKey(y2, v2)] = h2, i2[this._hashKey(_2, b2)] = d2, i2[this._hashKey(x2, w2)] = p2, this.trianglesLen = 0, this._addTriangle(h2, d2, p2, -1, -1, -1);\n          for (let o3, a3, u3 = 0; u3 < this._ids.length; u3++) {\n            const c3 = this._ids[u3], f3 = t2[2 * c3], s3 = t2[2 * c3 + 1];\n            if (u3 > 0 && Math.abs(f3 - o3) <= Tu && Math.abs(s3 - a3) <= Tu)\n              continue;\n            if (o3 = f3, a3 = s3, c3 === h2 || c3 === d2 || c3 === p2)\n              continue;\n            let l3 = 0;\n            for (let t3 = 0, n3 = this._hashKey(f3, s3); t3 < this._hashSize && (l3 = i2[(n3 + t3) % this._hashSize], -1 === l3 || l3 === e2[l3]); t3++)\n              ;\n            l3 = n2[l3];\n            let g3, y3 = l3;\n            for (; g3 = e2[y3], Mu(f3, s3, t2[2 * y3], t2[2 * y3 + 1], t2[2 * g3], t2[2 * g3 + 1]) >= 0; )\n              if (y3 = g3, y3 === l3) {\n                y3 = -1;\n                break;\n              }\n            if (-1 === y3)\n              continue;\n            let v3 = this._addTriangle(y3, c3, e2[y3], -1, -1, r2[y3]);\n            r2[c3] = this._legalize(v3 + 2), r2[y3] = v3, T2++;\n            let _3 = e2[y3];\n            for (; g3 = e2[_3], Mu(f3, s3, t2[2 * _3], t2[2 * _3 + 1], t2[2 * g3], t2[2 * g3 + 1]) < 0; )\n              v3 = this._addTriangle(_3, c3, g3, r2[c3], -1, r2[_3]), r2[c3] = this._legalize(v3 + 2), e2[_3] = _3, T2--, _3 = g3;\n            if (y3 === l3)\n              for (; g3 = n2[y3], Mu(f3, s3, t2[2 * g3], t2[2 * g3 + 1], t2[2 * y3], t2[2 * y3 + 1]) < 0; )\n                v3 = this._addTriangle(g3, c3, y3, -1, r2[y3], r2[g3]), this._legalize(v3 + 2), r2[g3] = v3, e2[y3] = y3, T2--, y3 = g3;\n            this._hullStart = n2[c3] = y3, e2[y3] = n2[_3] = c3, e2[c3] = _3, i2[this._hashKey(f3, s3)] = c3, i2[this._hashKey(t2[2 * y3], t2[2 * y3 + 1])] = y3;\n          }\n          this.hull = new Uint32Array(T2);\n          for (let t3 = 0, n3 = this._hullStart; t3 < T2; t3++)\n            this.hull[t3] = n3, n3 = e2[n3];\n          this.triangles = this._triangles.subarray(0, this.trianglesLen), this.halfedges = this._halfedges.subarray(0, this.trianglesLen);\n        }\n        _hashKey(t2, n2) {\n          return Math.floor(function(t3, n3) {\n            const e2 = t3 / (Math.abs(t3) + Math.abs(n3));\n            return (n3 > 0 ? 3 - e2 : 1 + e2) / 4;\n          }(t2 - this._cx, n2 - this._cy) * this._hashSize) % this._hashSize;\n        }\n        _legalize(t2) {\n          const { _triangles: n2, _halfedges: e2, coords: r2 } = this;\n          let i2 = 0, o2 = 0;\n          for (; ; ) {\n            const a2 = e2[t2], u2 = t2 - t2 % 3;\n            if (o2 = u2 + (t2 + 2) % 3, -1 === a2) {\n              if (0 === i2)\n                break;\n              t2 = Au[--i2];\n              continue;\n            }\n            const c2 = a2 - a2 % 3, f2 = u2 + (t2 + 1) % 3, s2 = c2 + (a2 + 2) % 3, l2 = n2[o2], h2 = n2[t2], d2 = n2[f2], p2 = n2[s2];\n            if (Nu(r2[2 * l2], r2[2 * l2 + 1], r2[2 * h2], r2[2 * h2 + 1], r2[2 * d2], r2[2 * d2 + 1], r2[2 * p2], r2[2 * p2 + 1])) {\n              n2[t2] = p2, n2[a2] = l2;\n              const r3 = e2[s2];\n              if (-1 === r3) {\n                let n3 = this._hullStart;\n                do {\n                  if (this._hullTri[n3] === s2) {\n                    this._hullTri[n3] = t2;\n                    break;\n                  }\n                  n3 = this._hullPrev[n3];\n                } while (n3 !== this._hullStart);\n              }\n              this._link(t2, r3), this._link(a2, e2[o2]), this._link(o2, s2);\n              const u3 = c2 + (a2 + 1) % 3;\n              i2 < Au.length && (Au[i2++] = u3);\n            } else {\n              if (0 === i2)\n                break;\n              t2 = Au[--i2];\n            }\n          }\n          return o2;\n        }\n        _link(t2, n2) {\n          this._halfedges[t2] = n2, -1 !== n2 && (this._halfedges[n2] = t2);\n        }\n        _addTriangle(t2, n2, e2, r2, i2, o2) {\n          const a2 = this.trianglesLen;\n          return this._triangles[a2] = t2, this._triangles[a2 + 1] = n2, this._triangles[a2 + 2] = e2, this._link(a2, r2), this._link(a2 + 1, i2), this._link(a2 + 2, o2), this.trianglesLen += 3, a2;\n        }\n      }\n      function Eu(t2, n2, e2, r2) {\n        const i2 = t2 - e2, o2 = n2 - r2;\n        return i2 * i2 + o2 * o2;\n      }\n      function Nu(t2, n2, e2, r2, i2, o2, a2, u2) {\n        const c2 = t2 - a2, f2 = n2 - u2, s2 = e2 - a2, l2 = r2 - u2, h2 = i2 - a2, d2 = o2 - u2, p2 = s2 * s2 + l2 * l2, g2 = h2 * h2 + d2 * d2;\n        return c2 * (l2 * g2 - p2 * d2) - f2 * (s2 * g2 - p2 * h2) + (c2 * c2 + f2 * f2) * (s2 * d2 - l2 * h2) < 0;\n      }\n      function ku(t2, n2, e2, r2, i2, o2) {\n        const a2 = e2 - t2, u2 = r2 - n2, c2 = i2 - t2, f2 = o2 - n2, s2 = a2 * a2 + u2 * u2, l2 = c2 * c2 + f2 * f2, h2 = 0.5 / (a2 * f2 - u2 * c2), d2 = (f2 * s2 - u2 * l2) * h2, p2 = (a2 * l2 - c2 * s2) * h2;\n        return d2 * d2 + p2 * p2;\n      }\n      function Cu(t2, n2, e2, r2) {\n        if (r2 - e2 <= 20)\n          for (let i2 = e2 + 1; i2 <= r2; i2++) {\n            const r3 = t2[i2], o2 = n2[r3];\n            let a2 = i2 - 1;\n            for (; a2 >= e2 && n2[t2[a2]] > o2; )\n              t2[a2 + 1] = t2[a2--];\n            t2[a2 + 1] = r3;\n          }\n        else {\n          let i2 = e2 + 1, o2 = r2;\n          Pu(t2, e2 + r2 >> 1, i2), n2[t2[e2]] > n2[t2[r2]] && Pu(t2, e2, r2), n2[t2[i2]] > n2[t2[r2]] && Pu(t2, i2, r2), n2[t2[e2]] > n2[t2[i2]] && Pu(t2, e2, i2);\n          const a2 = t2[i2], u2 = n2[a2];\n          for (; ; ) {\n            do {\n              i2++;\n            } while (n2[t2[i2]] < u2);\n            do {\n              o2--;\n            } while (n2[t2[o2]] > u2);\n            if (o2 < i2)\n              break;\n            Pu(t2, i2, o2);\n          }\n          t2[e2 + 1] = t2[o2], t2[o2] = a2, r2 - i2 + 1 >= o2 - e2 ? (Cu(t2, n2, i2, r2), Cu(t2, n2, e2, o2 - 1)) : (Cu(t2, n2, e2, o2 - 1), Cu(t2, n2, i2, r2));\n        }\n      }\n      function Pu(t2, n2, e2) {\n        const r2 = t2[n2];\n        t2[n2] = t2[e2], t2[e2] = r2;\n      }\n      function zu(t2) {\n        return t2[0];\n      }\n      function $u(t2) {\n        return t2[1];\n      }\n      const Du = 1e-6;\n      class Ru {\n        constructor() {\n          this._x0 = this._y0 = this._x1 = this._y1 = null, this._ = \"\";\n        }\n        moveTo(t2, n2) {\n          this._ += `M${this._x0 = this._x1 = +t2},${this._y0 = this._y1 = +n2}`;\n        }\n        closePath() {\n          null !== this._x1 && (this._x1 = this._x0, this._y1 = this._y0, this._ += \"Z\");\n        }\n        lineTo(t2, n2) {\n          this._ += `L${this._x1 = +t2},${this._y1 = +n2}`;\n        }\n        arc(t2, n2, e2) {\n          const r2 = (t2 = +t2) + (e2 = +e2), i2 = n2 = +n2;\n          if (e2 < 0)\n            throw new Error(\"negative radius\");\n          null === this._x1 ? this._ += `M${r2},${i2}` : (Math.abs(this._x1 - r2) > Du || Math.abs(this._y1 - i2) > Du) && (this._ += \"L\" + r2 + \",\" + i2), e2 && (this._ += `A${e2},${e2},0,1,1,${t2 - e2},${n2}A${e2},${e2},0,1,1,${this._x1 = r2},${this._y1 = i2}`);\n        }\n        rect(t2, n2, e2, r2) {\n          this._ += `M${this._x0 = this._x1 = +t2},${this._y0 = this._y1 = +n2}h${+e2}v${+r2}h${-e2}Z`;\n        }\n        value() {\n          return this._ || null;\n        }\n      }\n      class Fu {\n        constructor() {\n          this._ = [];\n        }\n        moveTo(t2, n2) {\n          this._.push([t2, n2]);\n        }\n        closePath() {\n          this._.push(this._[0].slice());\n        }\n        lineTo(t2, n2) {\n          this._.push([t2, n2]);\n        }\n        value() {\n          return this._.length ? this._ : null;\n        }\n      }\n      class qu {\n        constructor(t2, [n2, e2, r2, i2] = [0, 0, 960, 500]) {\n          if (!((r2 = +r2) >= (n2 = +n2) && (i2 = +i2) >= (e2 = +e2)))\n            throw new Error(\"invalid bounds\");\n          this.delaunay = t2, this._circumcenters = new Float64Array(2 * t2.points.length), this.vectors = new Float64Array(2 * t2.points.length), this.xmax = r2, this.xmin = n2, this.ymax = i2, this.ymin = e2, this._init();\n        }\n        update() {\n          return this.delaunay.update(), this._init(), this;\n        }\n        _init() {\n          const { delaunay: { points: t2, hull: n2, triangles: e2 }, vectors: r2 } = this;\n          let i2, o2;\n          const a2 = this.circumcenters = this._circumcenters.subarray(0, e2.length / 3 * 2);\n          for (let r3, u3, c3 = 0, f3 = 0, s3 = e2.length; c3 < s3; c3 += 3, f3 += 2) {\n            const s4 = 2 * e2[c3], l3 = 2 * e2[c3 + 1], h3 = 2 * e2[c3 + 2], d4 = t2[s4], p2 = t2[s4 + 1], g2 = t2[l3], y2 = t2[l3 + 1], v2 = t2[h3], _2 = t2[h3 + 1], b2 = g2 - d4, m2 = y2 - p2, x2 = v2 - d4, w2 = _2 - p2, M2 = 2 * (b2 * w2 - m2 * x2);\n            if (Math.abs(M2) < 1e-9) {\n              if (void 0 === i2) {\n                i2 = o2 = 0;\n                for (const e4 of n2)\n                  i2 += t2[2 * e4], o2 += t2[2 * e4 + 1];\n                i2 /= n2.length, o2 /= n2.length;\n              }\n              const e3 = 1e9 * Math.sign((i2 - d4) * w2 - (o2 - p2) * x2);\n              r3 = (d4 + v2) / 2 - e3 * w2, u3 = (p2 + _2) / 2 + e3 * x2;\n            } else {\n              const t3 = 1 / M2, n3 = b2 * b2 + m2 * m2, e3 = x2 * x2 + w2 * w2;\n              r3 = d4 + (w2 * n3 - m2 * e3) * t3, u3 = p2 + (b2 * e3 - x2 * n3) * t3;\n            }\n            a2[f3] = r3, a2[f3 + 1] = u3;\n          }\n          let u2, c2, f2, s2 = n2[n2.length - 1], l2 = 4 * s2, h2 = t2[2 * s2], d2 = t2[2 * s2 + 1];\n          r2.fill(0);\n          for (let e3 = 0; e3 < n2.length; ++e3)\n            s2 = n2[e3], u2 = l2, c2 = h2, f2 = d2, l2 = 4 * s2, h2 = t2[2 * s2], d2 = t2[2 * s2 + 1], r2[u2 + 2] = r2[l2] = f2 - d2, r2[u2 + 3] = r2[l2 + 1] = h2 - c2;\n        }\n        render(t2) {\n          const n2 = null == t2 ? t2 = new Ru() : void 0, { delaunay: { halfedges: e2, inedges: r2, hull: i2 }, circumcenters: o2, vectors: a2 } = this;\n          if (i2.length <= 1)\n            return null;\n          for (let n3 = 0, r3 = e2.length; n3 < r3; ++n3) {\n            const r4 = e2[n3];\n            if (r4 < n3)\n              continue;\n            const i3 = 2 * Math.floor(n3 / 3), a3 = 2 * Math.floor(r4 / 3), u3 = o2[i3], c3 = o2[i3 + 1], f2 = o2[a3], s2 = o2[a3 + 1];\n            this._renderSegment(u3, c3, f2, s2, t2);\n          }\n          let u2, c2 = i2[i2.length - 1];\n          for (let n3 = 0; n3 < i2.length; ++n3) {\n            u2 = c2, c2 = i2[n3];\n            const e3 = 2 * Math.floor(r2[c2] / 3), f2 = o2[e3], s2 = o2[e3 + 1], l2 = 4 * u2, h2 = this._project(f2, s2, a2[l2 + 2], a2[l2 + 3]);\n            h2 && this._renderSegment(f2, s2, h2[0], h2[1], t2);\n          }\n          return n2 && n2.value();\n        }\n        renderBounds(t2) {\n          const n2 = null == t2 ? t2 = new Ru() : void 0;\n          return t2.rect(this.xmin, this.ymin, this.xmax - this.xmin, this.ymax - this.ymin), n2 && n2.value();\n        }\n        renderCell(t2, n2) {\n          const e2 = null == n2 ? n2 = new Ru() : void 0, r2 = this._clip(t2);\n          if (null === r2 || !r2.length)\n            return;\n          n2.moveTo(r2[0], r2[1]);\n          let i2 = r2.length;\n          for (; r2[0] === r2[i2 - 2] && r2[1] === r2[i2 - 1] && i2 > 1; )\n            i2 -= 2;\n          for (let t3 = 2; t3 < i2; t3 += 2)\n            r2[t3] === r2[t3 - 2] && r2[t3 + 1] === r2[t3 - 1] || n2.lineTo(r2[t3], r2[t3 + 1]);\n          return n2.closePath(), e2 && e2.value();\n        }\n        *cellPolygons() {\n          const { delaunay: { points: t2 } } = this;\n          for (let n2 = 0, e2 = t2.length / 2; n2 < e2; ++n2) {\n            const t3 = this.cellPolygon(n2);\n            t3 && (t3.index = n2, yield t3);\n          }\n        }\n        cellPolygon(t2) {\n          const n2 = new Fu();\n          return this.renderCell(t2, n2), n2.value();\n        }\n        _renderSegment(t2, n2, e2, r2, i2) {\n          let o2;\n          const a2 = this._regioncode(t2, n2), u2 = this._regioncode(e2, r2);\n          0 === a2 && 0 === u2 ? (i2.moveTo(t2, n2), i2.lineTo(e2, r2)) : (o2 = this._clipSegment(t2, n2, e2, r2, a2, u2)) && (i2.moveTo(o2[0], o2[1]), i2.lineTo(o2[2], o2[3]));\n        }\n        contains(t2, n2, e2) {\n          return (n2 = +n2) == n2 && (e2 = +e2) == e2 && this.delaunay._step(t2, n2, e2) === t2;\n        }\n        *neighbors(t2) {\n          const n2 = this._clip(t2);\n          if (n2)\n            for (const e2 of this.delaunay.neighbors(t2)) {\n              const t3 = this._clip(e2);\n              if (t3) {\n                t:\n                  for (let r2 = 0, i2 = n2.length; r2 < i2; r2 += 2)\n                    for (let o2 = 0, a2 = t3.length; o2 < a2; o2 += 2)\n                      if (n2[r2] === t3[o2] && n2[r2 + 1] === t3[o2 + 1] && n2[(r2 + 2) % i2] === t3[(o2 + a2 - 2) % a2] && n2[(r2 + 3) % i2] === t3[(o2 + a2 - 1) % a2]) {\n                        yield e2;\n                        break t;\n                      }\n              }\n            }\n        }\n        _cell(t2) {\n          const { circumcenters: n2, delaunay: { inedges: e2, halfedges: r2, triangles: i2 } } = this, o2 = e2[t2];\n          if (-1 === o2)\n            return null;\n          const a2 = [];\n          let u2 = o2;\n          do {\n            const e3 = Math.floor(u2 / 3);\n            if (a2.push(n2[2 * e3], n2[2 * e3 + 1]), u2 = u2 % 3 == 2 ? u2 - 2 : u2 + 1, i2[u2] !== t2)\n              break;\n            u2 = r2[u2];\n          } while (u2 !== o2 && -1 !== u2);\n          return a2;\n        }\n        _clip(t2) {\n          if (0 === t2 && 1 === this.delaunay.hull.length)\n            return [this.xmax, this.ymin, this.xmax, this.ymax, this.xmin, this.ymax, this.xmin, this.ymin];\n          const n2 = this._cell(t2);\n          if (null === n2)\n            return null;\n          const { vectors: e2 } = this, r2 = 4 * t2;\n          return this._simplify(e2[r2] || e2[r2 + 1] ? this._clipInfinite(t2, n2, e2[r2], e2[r2 + 1], e2[r2 + 2], e2[r2 + 3]) : this._clipFinite(t2, n2));\n        }\n        _clipFinite(t2, n2) {\n          const e2 = n2.length;\n          let r2, i2, o2, a2, u2 = null, c2 = n2[e2 - 2], f2 = n2[e2 - 1], s2 = this._regioncode(c2, f2), l2 = 0;\n          for (let h2 = 0; h2 < e2; h2 += 2)\n            if (r2 = c2, i2 = f2, c2 = n2[h2], f2 = n2[h2 + 1], o2 = s2, s2 = this._regioncode(c2, f2), 0 === o2 && 0 === s2)\n              a2 = l2, l2 = 0, u2 ? u2.push(c2, f2) : u2 = [c2, f2];\n            else {\n              let n3, e3, h3, d2, p2;\n              if (0 === o2) {\n                if (null === (n3 = this._clipSegment(r2, i2, c2, f2, o2, s2)))\n                  continue;\n                [e3, h3, d2, p2] = n3;\n              } else {\n                if (null === (n3 = this._clipSegment(c2, f2, r2, i2, s2, o2)))\n                  continue;\n                [d2, p2, e3, h3] = n3, a2 = l2, l2 = this._edgecode(e3, h3), a2 && l2 && this._edge(t2, a2, l2, u2, u2.length), u2 ? u2.push(e3, h3) : u2 = [e3, h3];\n              }\n              a2 = l2, l2 = this._edgecode(d2, p2), a2 && l2 && this._edge(t2, a2, l2, u2, u2.length), u2 ? u2.push(d2, p2) : u2 = [d2, p2];\n            }\n          if (u2)\n            a2 = l2, l2 = this._edgecode(u2[0], u2[1]), a2 && l2 && this._edge(t2, a2, l2, u2, u2.length);\n          else if (this.contains(t2, (this.xmin + this.xmax) / 2, (this.ymin + this.ymax) / 2))\n            return [this.xmax, this.ymin, this.xmax, this.ymax, this.xmin, this.ymax, this.xmin, this.ymin];\n          return u2;\n        }\n        _clipSegment(t2, n2, e2, r2, i2, o2) {\n          const a2 = i2 < o2;\n          for (a2 && ([t2, n2, e2, r2, i2, o2] = [e2, r2, t2, n2, o2, i2]); ; ) {\n            if (0 === i2 && 0 === o2)\n              return a2 ? [e2, r2, t2, n2] : [t2, n2, e2, r2];\n            if (i2 & o2)\n              return null;\n            let u2, c2, f2 = i2 || o2;\n            8 & f2 ? (u2 = t2 + (e2 - t2) * (this.ymax - n2) / (r2 - n2), c2 = this.ymax) : 4 & f2 ? (u2 = t2 + (e2 - t2) * (this.ymin - n2) / (r2 - n2), c2 = this.ymin) : 2 & f2 ? (c2 = n2 + (r2 - n2) * (this.xmax - t2) / (e2 - t2), u2 = this.xmax) : (c2 = n2 + (r2 - n2) * (this.xmin - t2) / (e2 - t2), u2 = this.xmin), i2 ? (t2 = u2, n2 = c2, i2 = this._regioncode(t2, n2)) : (e2 = u2, r2 = c2, o2 = this._regioncode(e2, r2));\n          }\n        }\n        _clipInfinite(t2, n2, e2, r2, i2, o2) {\n          let a2, u2 = Array.from(n2);\n          if ((a2 = this._project(u2[0], u2[1], e2, r2)) && u2.unshift(a2[0], a2[1]), (a2 = this._project(u2[u2.length - 2], u2[u2.length - 1], i2, o2)) && u2.push(a2[0], a2[1]), u2 = this._clipFinite(t2, u2))\n            for (let n3, e3 = 0, r3 = u2.length, i3 = this._edgecode(u2[r3 - 2], u2[r3 - 1]); e3 < r3; e3 += 2)\n              n3 = i3, i3 = this._edgecode(u2[e3], u2[e3 + 1]), n3 && i3 && (e3 = this._edge(t2, n3, i3, u2, e3), r3 = u2.length);\n          else\n            this.contains(t2, (this.xmin + this.xmax) / 2, (this.ymin + this.ymax) / 2) && (u2 = [this.xmin, this.ymin, this.xmax, this.ymin, this.xmax, this.ymax, this.xmin, this.ymax]);\n          return u2;\n        }\n        _edge(t2, n2, e2, r2, i2) {\n          for (; n2 !== e2; ) {\n            let e3, o2;\n            switch (n2) {\n              case 5:\n                n2 = 4;\n                continue;\n              case 4:\n                n2 = 6, e3 = this.xmax, o2 = this.ymin;\n                break;\n              case 6:\n                n2 = 2;\n                continue;\n              case 2:\n                n2 = 10, e3 = this.xmax, o2 = this.ymax;\n                break;\n              case 10:\n                n2 = 8;\n                continue;\n              case 8:\n                n2 = 9, e3 = this.xmin, o2 = this.ymax;\n                break;\n              case 9:\n                n2 = 1;\n                continue;\n              case 1:\n                n2 = 5, e3 = this.xmin, o2 = this.ymin;\n            }\n            r2[i2] === e3 && r2[i2 + 1] === o2 || !this.contains(t2, e3, o2) || (r2.splice(i2, 0, e3, o2), i2 += 2);\n          }\n          return i2;\n        }\n        _project(t2, n2, e2, r2) {\n          let i2, o2, a2, u2 = 1 / 0;\n          if (r2 < 0) {\n            if (n2 <= this.ymin)\n              return null;\n            (i2 = (this.ymin - n2) / r2) < u2 && (a2 = this.ymin, o2 = t2 + (u2 = i2) * e2);\n          } else if (r2 > 0) {\n            if (n2 >= this.ymax)\n              return null;\n            (i2 = (this.ymax - n2) / r2) < u2 && (a2 = this.ymax, o2 = t2 + (u2 = i2) * e2);\n          }\n          if (e2 > 0) {\n            if (t2 >= this.xmax)\n              return null;\n            (i2 = (this.xmax - t2) / e2) < u2 && (o2 = this.xmax, a2 = n2 + (u2 = i2) * r2);\n          } else if (e2 < 0) {\n            if (t2 <= this.xmin)\n              return null;\n            (i2 = (this.xmin - t2) / e2) < u2 && (o2 = this.xmin, a2 = n2 + (u2 = i2) * r2);\n          }\n          return [o2, a2];\n        }\n        _edgecode(t2, n2) {\n          return (t2 === this.xmin ? 1 : t2 === this.xmax ? 2 : 0) | (n2 === this.ymin ? 4 : n2 === this.ymax ? 8 : 0);\n        }\n        _regioncode(t2, n2) {\n          return (t2 < this.xmin ? 1 : t2 > this.xmax ? 2 : 0) | (n2 < this.ymin ? 4 : n2 > this.ymax ? 8 : 0);\n        }\n        _simplify(t2) {\n          if (t2 && t2.length > 4) {\n            for (let n2 = 0; n2 < t2.length; n2 += 2) {\n              const e2 = (n2 + 2) % t2.length, r2 = (n2 + 4) % t2.length;\n              (t2[n2] === t2[e2] && t2[e2] === t2[r2] || t2[n2 + 1] === t2[e2 + 1] && t2[e2 + 1] === t2[r2 + 1]) && (t2.splice(e2, 2), n2 -= 2);\n            }\n            t2.length || (t2 = null);\n          }\n          return t2;\n        }\n      }\n      const Uu = 2 * Math.PI, Iu = Math.pow;\n      function Ou(t2) {\n        return t2[0];\n      }\n      function Bu(t2) {\n        return t2[1];\n      }\n      function Yu(t2, n2, e2) {\n        return [t2 + Math.sin(t2 + n2) * e2, n2 + Math.cos(t2 - n2) * e2];\n      }\n      class Lu {\n        static from(t2, n2 = Ou, e2 = Bu, r2) {\n          return new Lu(\"length\" in t2 ? function(t3, n3, e3, r3) {\n            const i2 = t3.length, o2 = new Float64Array(2 * i2);\n            for (let a2 = 0; a2 < i2; ++a2) {\n              const i3 = t3[a2];\n              o2[2 * a2] = n3.call(r3, i3, a2, t3), o2[2 * a2 + 1] = e3.call(r3, i3, a2, t3);\n            }\n            return o2;\n          }(t2, n2, e2, r2) : Float64Array.from(function* (t3, n3, e3, r3) {\n            let i2 = 0;\n            for (const o2 of t3)\n              yield n3.call(r3, o2, i2, t3), yield e3.call(r3, o2, i2, t3), ++i2;\n          }(t2, n2, e2, r2)));\n        }\n        constructor(t2) {\n          this._delaunator = new Su(t2), this.inedges = new Int32Array(t2.length / 2), this._hullIndex = new Int32Array(t2.length / 2), this.points = this._delaunator.coords, this._init();\n        }\n        update() {\n          return this._delaunator.update(), this._init(), this;\n        }\n        _init() {\n          const t2 = this._delaunator, n2 = this.points;\n          if (t2.hull && t2.hull.length > 2 && function(t3) {\n            const { triangles: n3, coords: e3 } = t3;\n            for (let t4 = 0; t4 < n3.length; t4 += 3) {\n              const r3 = 2 * n3[t4], i3 = 2 * n3[t4 + 1], o3 = 2 * n3[t4 + 2];\n              if ((e3[o3] - e3[r3]) * (e3[i3 + 1] - e3[r3 + 1]) - (e3[i3] - e3[r3]) * (e3[o3 + 1] - e3[r3 + 1]) > 1e-10)\n                return false;\n            }\n            return true;\n          }(t2)) {\n            this.collinear = Int32Array.from({ length: n2.length / 2 }, (t4, n3) => n3).sort((t4, e4) => n2[2 * t4] - n2[2 * e4] || n2[2 * t4 + 1] - n2[2 * e4 + 1]);\n            const t3 = this.collinear[0], e3 = this.collinear[this.collinear.length - 1], r3 = [n2[2 * t3], n2[2 * t3 + 1], n2[2 * e3], n2[2 * e3 + 1]], i3 = 1e-8 * Math.hypot(r3[3] - r3[1], r3[2] - r3[0]);\n            for (let t4 = 0, e4 = n2.length / 2; t4 < e4; ++t4) {\n              const e5 = Yu(n2[2 * t4], n2[2 * t4 + 1], i3);\n              n2[2 * t4] = e5[0], n2[2 * t4 + 1] = e5[1];\n            }\n            this._delaunator = new Su(n2);\n          } else\n            delete this.collinear;\n          const e2 = this.halfedges = this._delaunator.halfedges, r2 = this.hull = this._delaunator.hull, i2 = this.triangles = this._delaunator.triangles, o2 = this.inedges.fill(-1), a2 = this._hullIndex.fill(-1);\n          for (let t3 = 0, n3 = e2.length; t3 < n3; ++t3) {\n            const n4 = i2[t3 % 3 == 2 ? t3 - 2 : t3 + 1];\n            -1 !== e2[t3] && -1 !== o2[n4] || (o2[n4] = t3);\n          }\n          for (let t3 = 0, n3 = r2.length; t3 < n3; ++t3)\n            a2[r2[t3]] = t3;\n          r2.length <= 2 && r2.length > 0 && (this.triangles = new Int32Array(3).fill(-1), this.halfedges = new Int32Array(3).fill(-1), this.triangles[0] = r2[0], o2[r2[0]] = 1, 2 === r2.length && (o2[r2[1]] = 0, this.triangles[1] = r2[1], this.triangles[2] = r2[1]));\n        }\n        voronoi(t2) {\n          return new qu(this, t2);\n        }\n        *neighbors(t2) {\n          const { inedges: n2, hull: e2, _hullIndex: r2, halfedges: i2, triangles: o2, collinear: a2 } = this;\n          if (a2) {\n            const n3 = a2.indexOf(t2);\n            return n3 > 0 && (yield a2[n3 - 1]), void (n3 < a2.length - 1 && (yield a2[n3 + 1]));\n          }\n          const u2 = n2[t2];\n          if (-1 === u2)\n            return;\n          let c2 = u2, f2 = -1;\n          do {\n            if (yield f2 = o2[c2], c2 = c2 % 3 == 2 ? c2 - 2 : c2 + 1, o2[c2] !== t2)\n              return;\n            if (c2 = i2[c2], -1 === c2) {\n              const n3 = e2[(r2[t2] + 1) % e2.length];\n              return void (n3 !== f2 && (yield n3));\n            }\n          } while (c2 !== u2);\n        }\n        find(t2, n2, e2 = 0) {\n          if ((t2 = +t2) != t2 || (n2 = +n2) != n2)\n            return -1;\n          const r2 = e2;\n          let i2;\n          for (; (i2 = this._step(e2, t2, n2)) >= 0 && i2 !== e2 && i2 !== r2; )\n            e2 = i2;\n          return i2;\n        }\n        _step(t2, n2, e2) {\n          const { inedges: r2, hull: i2, _hullIndex: o2, halfedges: a2, triangles: u2, points: c2 } = this;\n          if (-1 === r2[t2] || !c2.length)\n            return (t2 + 1) % (c2.length >> 1);\n          let f2 = t2, s2 = Iu(n2 - c2[2 * t2], 2) + Iu(e2 - c2[2 * t2 + 1], 2);\n          const l2 = r2[t2];\n          let h2 = l2;\n          do {\n            let r3 = u2[h2];\n            const l3 = Iu(n2 - c2[2 * r3], 2) + Iu(e2 - c2[2 * r3 + 1], 2);\n            if (l3 < s2 && (s2 = l3, f2 = r3), h2 = h2 % 3 == 2 ? h2 - 2 : h2 + 1, u2[h2] !== t2)\n              break;\n            if (h2 = a2[h2], -1 === h2) {\n              if (h2 = i2[(o2[t2] + 1) % i2.length], h2 !== r3 && Iu(n2 - c2[2 * h2], 2) + Iu(e2 - c2[2 * h2 + 1], 2) < s2)\n                return h2;\n              break;\n            }\n          } while (h2 !== l2);\n          return f2;\n        }\n        render(t2) {\n          const n2 = null == t2 ? t2 = new Ru() : void 0, { points: e2, halfedges: r2, triangles: i2 } = this;\n          for (let n3 = 0, o2 = r2.length; n3 < o2; ++n3) {\n            const o3 = r2[n3];\n            if (o3 < n3)\n              continue;\n            const a2 = 2 * i2[n3], u2 = 2 * i2[o3];\n            t2.moveTo(e2[a2], e2[a2 + 1]), t2.lineTo(e2[u2], e2[u2 + 1]);\n          }\n          return this.renderHull(t2), n2 && n2.value();\n        }\n        renderPoints(t2, n2) {\n          void 0 !== n2 || t2 && \"function\" == typeof t2.moveTo || (n2 = t2, t2 = null), n2 = null == n2 ? 2 : +n2;\n          const e2 = null == t2 ? t2 = new Ru() : void 0, { points: r2 } = this;\n          for (let e3 = 0, i2 = r2.length; e3 < i2; e3 += 2) {\n            const i3 = r2[e3], o2 = r2[e3 + 1];\n            t2.moveTo(i3 + n2, o2), t2.arc(i3, o2, n2, 0, Uu);\n          }\n          return e2 && e2.value();\n        }\n        renderHull(t2) {\n          const n2 = null == t2 ? t2 = new Ru() : void 0, { hull: e2, points: r2 } = this, i2 = 2 * e2[0], o2 = e2.length;\n          t2.moveTo(r2[i2], r2[i2 + 1]);\n          for (let n3 = 1; n3 < o2; ++n3) {\n            const i3 = 2 * e2[n3];\n            t2.lineTo(r2[i3], r2[i3 + 1]);\n          }\n          return t2.closePath(), n2 && n2.value();\n        }\n        hullPolygon() {\n          const t2 = new Fu();\n          return this.renderHull(t2), t2.value();\n        }\n        renderTriangle(t2, n2) {\n          const e2 = null == n2 ? n2 = new Ru() : void 0, { points: r2, triangles: i2 } = this, o2 = 2 * i2[t2 *= 3], a2 = 2 * i2[t2 + 1], u2 = 2 * i2[t2 + 2];\n          return n2.moveTo(r2[o2], r2[o2 + 1]), n2.lineTo(r2[a2], r2[a2 + 1]), n2.lineTo(r2[u2], r2[u2 + 1]), n2.closePath(), e2 && e2.value();\n        }\n        *trianglePolygons() {\n          const { triangles: t2 } = this;\n          for (let n2 = 0, e2 = t2.length / 3; n2 < e2; ++n2)\n            yield this.trianglePolygon(n2);\n        }\n        trianglePolygon(t2) {\n          const n2 = new Fu();\n          return this.renderTriangle(t2, n2), n2.value();\n        }\n      }\n      var ju = {}, Hu = {}, Xu = 34, Gu = 10, Vu = 13;\n      function Wu(t2) {\n        return new Function(\"d\", \"return {\" + t2.map(function(t3, n2) {\n          return JSON.stringify(t3) + \": d[\" + n2 + '] || \"\"';\n        }).join(\",\") + \"}\");\n      }\n      function Zu(t2) {\n        var n2 = /* @__PURE__ */ Object.create(null), e2 = [];\n        return t2.forEach(function(t3) {\n          for (var r2 in t3)\n            r2 in n2 || e2.push(n2[r2] = r2);\n        }), e2;\n      }\n      function Ku(t2, n2) {\n        var e2 = t2 + \"\", r2 = e2.length;\n        return r2 < n2 ? new Array(n2 - r2 + 1).join(0) + e2 : e2;\n      }\n      function Qu(t2) {\n        var n2, e2 = t2.getUTCHours(), r2 = t2.getUTCMinutes(), i2 = t2.getUTCSeconds(), o2 = t2.getUTCMilliseconds();\n        return isNaN(t2) ? \"Invalid Date\" : ((n2 = t2.getUTCFullYear()) < 0 ? \"-\" + Ku(-n2, 6) : n2 > 9999 ? \"+\" + Ku(n2, 6) : Ku(n2, 4)) + \"-\" + Ku(t2.getUTCMonth() + 1, 2) + \"-\" + Ku(t2.getUTCDate(), 2) + (o2 ? \"T\" + Ku(e2, 2) + \":\" + Ku(r2, 2) + \":\" + Ku(i2, 2) + \".\" + Ku(o2, 3) + \"Z\" : i2 ? \"T\" + Ku(e2, 2) + \":\" + Ku(r2, 2) + \":\" + Ku(i2, 2) + \"Z\" : r2 || e2 ? \"T\" + Ku(e2, 2) + \":\" + Ku(r2, 2) + \"Z\" : \"\");\n      }\n      function Ju(t2) {\n        var n2 = new RegExp('[\"' + t2 + \"\\n\\r]\"), e2 = t2.charCodeAt(0);\n        function r2(t3, n3) {\n          var r3, i3 = [], o3 = t3.length, a3 = 0, u2 = 0, c2 = o3 <= 0, f2 = false;\n          function s2() {\n            if (c2)\n              return Hu;\n            if (f2)\n              return f2 = false, ju;\n            var n4, r4, i4 = a3;\n            if (t3.charCodeAt(i4) === Xu) {\n              for (; a3++ < o3 && t3.charCodeAt(a3) !== Xu || t3.charCodeAt(++a3) === Xu; )\n                ;\n              return (n4 = a3) >= o3 ? c2 = true : (r4 = t3.charCodeAt(a3++)) === Gu ? f2 = true : r4 === Vu && (f2 = true, t3.charCodeAt(a3) === Gu && ++a3), t3.slice(i4 + 1, n4 - 1).replace(/\"\"/g, '\"');\n            }\n            for (; a3 < o3; ) {\n              if ((r4 = t3.charCodeAt(n4 = a3++)) === Gu)\n                f2 = true;\n              else if (r4 === Vu)\n                f2 = true, t3.charCodeAt(a3) === Gu && ++a3;\n              else if (r4 !== e2)\n                continue;\n              return t3.slice(i4, n4);\n            }\n            return c2 = true, t3.slice(i4, o3);\n          }\n          for (t3.charCodeAt(o3 - 1) === Gu && --o3, t3.charCodeAt(o3 - 1) === Vu && --o3; (r3 = s2()) !== Hu; ) {\n            for (var l2 = []; r3 !== ju && r3 !== Hu; )\n              l2.push(r3), r3 = s2();\n            n3 && null == (l2 = n3(l2, u2++)) || i3.push(l2);\n          }\n          return i3;\n        }\n        function i2(n3, e3) {\n          return n3.map(function(n4) {\n            return e3.map(function(t3) {\n              return a2(n4[t3]);\n            }).join(t2);\n          });\n        }\n        function o2(n3) {\n          return n3.map(a2).join(t2);\n        }\n        function a2(t3) {\n          return null == t3 ? \"\" : t3 instanceof Date ? Qu(t3) : n2.test(t3 += \"\") ? '\"' + t3.replace(/\"/g, '\"\"') + '\"' : t3;\n        }\n        return { parse: function(t3, n3) {\n          var e3, i3, o3 = r2(t3, function(t4, r3) {\n            if (e3)\n              return e3(t4, r3 - 1);\n            i3 = t4, e3 = n3 ? function(t5, n4) {\n              var e4 = Wu(t5);\n              return function(r4, i4) {\n                return n4(e4(r4), i4, t5);\n              };\n            }(t4, n3) : Wu(t4);\n          });\n          return o3.columns = i3 || [], o3;\n        }, parseRows: r2, format: function(n3, e3) {\n          return null == e3 && (e3 = Zu(n3)), [e3.map(a2).join(t2)].concat(i2(n3, e3)).join(\"\\n\");\n        }, formatBody: function(t3, n3) {\n          return null == n3 && (n3 = Zu(t3)), i2(t3, n3).join(\"\\n\");\n        }, formatRows: function(t3) {\n          return t3.map(o2).join(\"\\n\");\n        }, formatRow: o2, formatValue: a2 };\n      }\n      var tc = Ju(\",\"), nc = tc.parse, ec = tc.parseRows, rc = tc.format, ic = tc.formatBody, oc = tc.formatRows, ac = tc.formatRow, uc = tc.formatValue, cc = Ju(\"\t\"), fc = cc.parse, sc = cc.parseRows, lc = cc.format, hc = cc.formatBody, dc = cc.formatRows, pc = cc.formatRow, gc = cc.formatValue;\n      const yc = (/* @__PURE__ */ new Date(\"2019-01-01T00:00\")).getHours() || (/* @__PURE__ */ new Date(\"2019-07-01T00:00\")).getHours();\n      function vc(t2) {\n        if (!t2.ok)\n          throw new Error(t2.status + \" \" + t2.statusText);\n        return t2.blob();\n      }\n      function _c(t2) {\n        if (!t2.ok)\n          throw new Error(t2.status + \" \" + t2.statusText);\n        return t2.arrayBuffer();\n      }\n      function bc(t2) {\n        if (!t2.ok)\n          throw new Error(t2.status + \" \" + t2.statusText);\n        return t2.text();\n      }\n      function mc(t2, n2) {\n        return fetch(t2, n2).then(bc);\n      }\n      function xc(t2) {\n        return function(n2, e2, r2) {\n          return 2 === arguments.length && \"function\" == typeof e2 && (r2 = e2, e2 = void 0), mc(n2, e2).then(function(n3) {\n            return t2(n3, r2);\n          });\n        };\n      }\n      var wc = xc(nc), Mc = xc(fc);\n      function Tc(t2) {\n        if (!t2.ok)\n          throw new Error(t2.status + \" \" + t2.statusText);\n        if (204 !== t2.status && 205 !== t2.status)\n          return t2.json();\n      }\n      function Ac(t2) {\n        return (n2, e2) => mc(n2, e2).then((n3) => new DOMParser().parseFromString(n3, t2));\n      }\n      var Sc = Ac(\"application/xml\"), Ec = Ac(\"text/html\"), Nc = Ac(\"image/svg+xml\");\n      function kc(t2, n2, e2, r2) {\n        if (isNaN(n2) || isNaN(e2))\n          return t2;\n        var i2, o2, a2, u2, c2, f2, s2, l2, h2, d2 = t2._root, p2 = { data: r2 }, g2 = t2._x0, y2 = t2._y0, v2 = t2._x1, _2 = t2._y1;\n        if (!d2)\n          return t2._root = p2, t2;\n        for (; d2.length; )\n          if ((f2 = n2 >= (o2 = (g2 + v2) / 2)) ? g2 = o2 : v2 = o2, (s2 = e2 >= (a2 = (y2 + _2) / 2)) ? y2 = a2 : _2 = a2, i2 = d2, !(d2 = d2[l2 = s2 << 1 | f2]))\n            return i2[l2] = p2, t2;\n        if (u2 = +t2._x.call(null, d2.data), c2 = +t2._y.call(null, d2.data), n2 === u2 && e2 === c2)\n          return p2.next = d2, i2 ? i2[l2] = p2 : t2._root = p2, t2;\n        do {\n          i2 = i2 ? i2[l2] = new Array(4) : t2._root = new Array(4), (f2 = n2 >= (o2 = (g2 + v2) / 2)) ? g2 = o2 : v2 = o2, (s2 = e2 >= (a2 = (y2 + _2) / 2)) ? y2 = a2 : _2 = a2;\n        } while ((l2 = s2 << 1 | f2) == (h2 = (c2 >= a2) << 1 | u2 >= o2));\n        return i2[h2] = d2, i2[l2] = p2, t2;\n      }\n      function Cc(t2, n2, e2, r2, i2) {\n        this.node = t2, this.x0 = n2, this.y0 = e2, this.x1 = r2, this.y1 = i2;\n      }\n      function Pc(t2) {\n        return t2[0];\n      }\n      function zc(t2) {\n        return t2[1];\n      }\n      function $c(t2, n2, e2) {\n        var r2 = new Dc(null == n2 ? Pc : n2, null == e2 ? zc : e2, NaN, NaN, NaN, NaN);\n        return null == t2 ? r2 : r2.addAll(t2);\n      }\n      function Dc(t2, n2, e2, r2, i2, o2) {\n        this._x = t2, this._y = n2, this._x0 = e2, this._y0 = r2, this._x1 = i2, this._y1 = o2, this._root = void 0;\n      }\n      function Rc(t2) {\n        for (var n2 = { data: t2.data }, e2 = n2; t2 = t2.next; )\n          e2 = e2.next = { data: t2.data };\n        return n2;\n      }\n      var Fc = $c.prototype = Dc.prototype;\n      function qc(t2) {\n        return function() {\n          return t2;\n        };\n      }\n      function Uc(t2) {\n        return 1e-6 * (t2() - 0.5);\n      }\n      function Ic(t2) {\n        return t2.x + t2.vx;\n      }\n      function Oc(t2) {\n        return t2.y + t2.vy;\n      }\n      function Bc(t2) {\n        return t2.index;\n      }\n      function Yc(t2, n2) {\n        var e2 = t2.get(n2);\n        if (!e2)\n          throw new Error(\"node not found: \" + n2);\n        return e2;\n      }\n      Fc.copy = function() {\n        var t2, n2, e2 = new Dc(this._x, this._y, this._x0, this._y0, this._x1, this._y1), r2 = this._root;\n        if (!r2)\n          return e2;\n        if (!r2.length)\n          return e2._root = Rc(r2), e2;\n        for (t2 = [{ source: r2, target: e2._root = new Array(4) }]; r2 = t2.pop(); )\n          for (var i2 = 0; i2 < 4; ++i2)\n            (n2 = r2.source[i2]) && (n2.length ? t2.push({ source: n2, target: r2.target[i2] = new Array(4) }) : r2.target[i2] = Rc(n2));\n        return e2;\n      }, Fc.add = function(t2) {\n        const n2 = +this._x.call(null, t2), e2 = +this._y.call(null, t2);\n        return kc(this.cover(n2, e2), n2, e2, t2);\n      }, Fc.addAll = function(t2) {\n        var n2, e2, r2, i2, o2 = t2.length, a2 = new Array(o2), u2 = new Array(o2), c2 = 1 / 0, f2 = 1 / 0, s2 = -1 / 0, l2 = -1 / 0;\n        for (e2 = 0; e2 < o2; ++e2)\n          isNaN(r2 = +this._x.call(null, n2 = t2[e2])) || isNaN(i2 = +this._y.call(null, n2)) || (a2[e2] = r2, u2[e2] = i2, r2 < c2 && (c2 = r2), r2 > s2 && (s2 = r2), i2 < f2 && (f2 = i2), i2 > l2 && (l2 = i2));\n        if (c2 > s2 || f2 > l2)\n          return this;\n        for (this.cover(c2, f2).cover(s2, l2), e2 = 0; e2 < o2; ++e2)\n          kc(this, a2[e2], u2[e2], t2[e2]);\n        return this;\n      }, Fc.cover = function(t2, n2) {\n        if (isNaN(t2 = +t2) || isNaN(n2 = +n2))\n          return this;\n        var e2 = this._x0, r2 = this._y0, i2 = this._x1, o2 = this._y1;\n        if (isNaN(e2))\n          i2 = (e2 = Math.floor(t2)) + 1, o2 = (r2 = Math.floor(n2)) + 1;\n        else {\n          for (var a2, u2, c2 = i2 - e2 || 1, f2 = this._root; e2 > t2 || t2 >= i2 || r2 > n2 || n2 >= o2; )\n            switch (u2 = (n2 < r2) << 1 | t2 < e2, (a2 = new Array(4))[u2] = f2, f2 = a2, c2 *= 2, u2) {\n              case 0:\n                i2 = e2 + c2, o2 = r2 + c2;\n                break;\n              case 1:\n                e2 = i2 - c2, o2 = r2 + c2;\n                break;\n              case 2:\n                i2 = e2 + c2, r2 = o2 - c2;\n                break;\n              case 3:\n                e2 = i2 - c2, r2 = o2 - c2;\n            }\n          this._root && this._root.length && (this._root = f2);\n        }\n        return this._x0 = e2, this._y0 = r2, this._x1 = i2, this._y1 = o2, this;\n      }, Fc.data = function() {\n        var t2 = [];\n        return this.visit(function(n2) {\n          if (!n2.length)\n            do {\n              t2.push(n2.data);\n            } while (n2 = n2.next);\n        }), t2;\n      }, Fc.extent = function(t2) {\n        return arguments.length ? this.cover(+t2[0][0], +t2[0][1]).cover(+t2[1][0], +t2[1][1]) : isNaN(this._x0) ? void 0 : [[this._x0, this._y0], [this._x1, this._y1]];\n      }, Fc.find = function(t2, n2, e2) {\n        var r2, i2, o2, a2, u2, c2, f2, s2 = this._x0, l2 = this._y0, h2 = this._x1, d2 = this._y1, p2 = [], g2 = this._root;\n        for (g2 && p2.push(new Cc(g2, s2, l2, h2, d2)), null == e2 ? e2 = 1 / 0 : (s2 = t2 - e2, l2 = n2 - e2, h2 = t2 + e2, d2 = n2 + e2, e2 *= e2); c2 = p2.pop(); )\n          if (!(!(g2 = c2.node) || (i2 = c2.x0) > h2 || (o2 = c2.y0) > d2 || (a2 = c2.x1) < s2 || (u2 = c2.y1) < l2))\n            if (g2.length) {\n              var y2 = (i2 + a2) / 2, v2 = (o2 + u2) / 2;\n              p2.push(new Cc(g2[3], y2, v2, a2, u2), new Cc(g2[2], i2, v2, y2, u2), new Cc(g2[1], y2, o2, a2, v2), new Cc(g2[0], i2, o2, y2, v2)), (f2 = (n2 >= v2) << 1 | t2 >= y2) && (c2 = p2[p2.length - 1], p2[p2.length - 1] = p2[p2.length - 1 - f2], p2[p2.length - 1 - f2] = c2);\n            } else {\n              var _2 = t2 - +this._x.call(null, g2.data), b2 = n2 - +this._y.call(null, g2.data), m2 = _2 * _2 + b2 * b2;\n              if (m2 < e2) {\n                var x2 = Math.sqrt(e2 = m2);\n                s2 = t2 - x2, l2 = n2 - x2, h2 = t2 + x2, d2 = n2 + x2, r2 = g2.data;\n              }\n            }\n        return r2;\n      }, Fc.remove = function(t2) {\n        if (isNaN(o2 = +this._x.call(null, t2)) || isNaN(a2 = +this._y.call(null, t2)))\n          return this;\n        var n2, e2, r2, i2, o2, a2, u2, c2, f2, s2, l2, h2, d2 = this._root, p2 = this._x0, g2 = this._y0, y2 = this._x1, v2 = this._y1;\n        if (!d2)\n          return this;\n        if (d2.length)\n          for (; ; ) {\n            if ((f2 = o2 >= (u2 = (p2 + y2) / 2)) ? p2 = u2 : y2 = u2, (s2 = a2 >= (c2 = (g2 + v2) / 2)) ? g2 = c2 : v2 = c2, n2 = d2, !(d2 = d2[l2 = s2 << 1 | f2]))\n              return this;\n            if (!d2.length)\n              break;\n            (n2[l2 + 1 & 3] || n2[l2 + 2 & 3] || n2[l2 + 3 & 3]) && (e2 = n2, h2 = l2);\n          }\n        for (; d2.data !== t2; )\n          if (r2 = d2, !(d2 = d2.next))\n            return this;\n        return (i2 = d2.next) && delete d2.next, r2 ? (i2 ? r2.next = i2 : delete r2.next, this) : n2 ? (i2 ? n2[l2] = i2 : delete n2[l2], (d2 = n2[0] || n2[1] || n2[2] || n2[3]) && d2 === (n2[3] || n2[2] || n2[1] || n2[0]) && !d2.length && (e2 ? e2[h2] = d2 : this._root = d2), this) : (this._root = i2, this);\n      }, Fc.removeAll = function(t2) {\n        for (var n2 = 0, e2 = t2.length; n2 < e2; ++n2)\n          this.remove(t2[n2]);\n        return this;\n      }, Fc.root = function() {\n        return this._root;\n      }, Fc.size = function() {\n        var t2 = 0;\n        return this.visit(function(n2) {\n          if (!n2.length)\n            do {\n              ++t2;\n            } while (n2 = n2.next);\n        }), t2;\n      }, Fc.visit = function(t2) {\n        var n2, e2, r2, i2, o2, a2, u2 = [], c2 = this._root;\n        for (c2 && u2.push(new Cc(c2, this._x0, this._y0, this._x1, this._y1)); n2 = u2.pop(); )\n          if (!t2(c2 = n2.node, r2 = n2.x0, i2 = n2.y0, o2 = n2.x1, a2 = n2.y1) && c2.length) {\n            var f2 = (r2 + o2) / 2, s2 = (i2 + a2) / 2;\n            (e2 = c2[3]) && u2.push(new Cc(e2, f2, s2, o2, a2)), (e2 = c2[2]) && u2.push(new Cc(e2, r2, s2, f2, a2)), (e2 = c2[1]) && u2.push(new Cc(e2, f2, i2, o2, s2)), (e2 = c2[0]) && u2.push(new Cc(e2, r2, i2, f2, s2));\n          }\n        return this;\n      }, Fc.visitAfter = function(t2) {\n        var n2, e2 = [], r2 = [];\n        for (this._root && e2.push(new Cc(this._root, this._x0, this._y0, this._x1, this._y1)); n2 = e2.pop(); ) {\n          var i2 = n2.node;\n          if (i2.length) {\n            var o2, a2 = n2.x0, u2 = n2.y0, c2 = n2.x1, f2 = n2.y1, s2 = (a2 + c2) / 2, l2 = (u2 + f2) / 2;\n            (o2 = i2[0]) && e2.push(new Cc(o2, a2, u2, s2, l2)), (o2 = i2[1]) && e2.push(new Cc(o2, s2, u2, c2, l2)), (o2 = i2[2]) && e2.push(new Cc(o2, a2, l2, s2, f2)), (o2 = i2[3]) && e2.push(new Cc(o2, s2, l2, c2, f2));\n          }\n          r2.push(n2);\n        }\n        for (; n2 = r2.pop(); )\n          t2(n2.node, n2.x0, n2.y0, n2.x1, n2.y1);\n        return this;\n      }, Fc.x = function(t2) {\n        return arguments.length ? (this._x = t2, this) : this._x;\n      }, Fc.y = function(t2) {\n        return arguments.length ? (this._y = t2, this) : this._y;\n      };\n      const Lc = 1664525, jc = 1013904223, Hc = 4294967296;\n      function Xc(t2) {\n        return t2.x;\n      }\n      function Gc(t2) {\n        return t2.y;\n      }\n      var Vc = Math.PI * (3 - Math.sqrt(5));\n      function Wc(t2, n2) {\n        if ((e2 = (t2 = n2 ? t2.toExponential(n2 - 1) : t2.toExponential()).indexOf(\"e\")) < 0)\n          return null;\n        var e2, r2 = t2.slice(0, e2);\n        return [r2.length > 1 ? r2[0] + r2.slice(2) : r2, +t2.slice(e2 + 1)];\n      }\n      function Zc(t2) {\n        return (t2 = Wc(Math.abs(t2))) ? t2[1] : NaN;\n      }\n      var Kc, Qc = /^(?:(.)?([<>=^]))?([+\\-( ])?([$#])?(0)?(\\d+)?(,)?(\\.\\d+)?(~)?([a-z%])?$/i;\n      function Jc(t2) {\n        if (!(n2 = Qc.exec(t2)))\n          throw new Error(\"invalid format: \" + t2);\n        var n2;\n        return new tf({ fill: n2[1], align: n2[2], sign: n2[3], symbol: n2[4], zero: n2[5], width: n2[6], comma: n2[7], precision: n2[8] && n2[8].slice(1), trim: n2[9], type: n2[10] });\n      }\n      function tf(t2) {\n        this.fill = void 0 === t2.fill ? \" \" : t2.fill + \"\", this.align = void 0 === t2.align ? \">\" : t2.align + \"\", this.sign = void 0 === t2.sign ? \"-\" : t2.sign + \"\", this.symbol = void 0 === t2.symbol ? \"\" : t2.symbol + \"\", this.zero = !!t2.zero, this.width = void 0 === t2.width ? void 0 : +t2.width, this.comma = !!t2.comma, this.precision = void 0 === t2.precision ? void 0 : +t2.precision, this.trim = !!t2.trim, this.type = void 0 === t2.type ? \"\" : t2.type + \"\";\n      }\n      function nf(t2, n2) {\n        var e2 = Wc(t2, n2);\n        if (!e2)\n          return t2 + \"\";\n        var r2 = e2[0], i2 = e2[1];\n        return i2 < 0 ? \"0.\" + new Array(-i2).join(\"0\") + r2 : r2.length > i2 + 1 ? r2.slice(0, i2 + 1) + \".\" + r2.slice(i2 + 1) : r2 + new Array(i2 - r2.length + 2).join(\"0\");\n      }\n      Jc.prototype = tf.prototype, tf.prototype.toString = function() {\n        return this.fill + this.align + this.sign + this.symbol + (this.zero ? \"0\" : \"\") + (void 0 === this.width ? \"\" : Math.max(1, 0 | this.width)) + (this.comma ? \",\" : \"\") + (void 0 === this.precision ? \"\" : \".\" + Math.max(0, 0 | this.precision)) + (this.trim ? \"~\" : \"\") + this.type;\n      };\n      var ef = { \"%\": (t2, n2) => (100 * t2).toFixed(n2), b: (t2) => Math.round(t2).toString(2), c: (t2) => t2 + \"\", d: function(t2) {\n        return Math.abs(t2 = Math.round(t2)) >= 1e21 ? t2.toLocaleString(\"en\").replace(/,/g, \"\") : t2.toString(10);\n      }, e: (t2, n2) => t2.toExponential(n2), f: (t2, n2) => t2.toFixed(n2), g: (t2, n2) => t2.toPrecision(n2), o: (t2) => Math.round(t2).toString(8), p: (t2, n2) => nf(100 * t2, n2), r: nf, s: function(t2, n2) {\n        var e2 = Wc(t2, n2);\n        if (!e2)\n          return t2 + \"\";\n        var r2 = e2[0], i2 = e2[1], o2 = i2 - (Kc = 3 * Math.max(-8, Math.min(8, Math.floor(i2 / 3)))) + 1, a2 = r2.length;\n        return o2 === a2 ? r2 : o2 > a2 ? r2 + new Array(o2 - a2 + 1).join(\"0\") : o2 > 0 ? r2.slice(0, o2) + \".\" + r2.slice(o2) : \"0.\" + new Array(1 - o2).join(\"0\") + Wc(t2, Math.max(0, n2 + o2 - 1))[0];\n      }, X: (t2) => Math.round(t2).toString(16).toUpperCase(), x: (t2) => Math.round(t2).toString(16) };\n      function rf(t2) {\n        return t2;\n      }\n      var of, af = Array.prototype.map, uf = [\"y\", \"z\", \"a\", \"f\", \"p\", \"n\", \"\\xB5\", \"m\", \"\", \"k\", \"M\", \"G\", \"T\", \"P\", \"E\", \"Z\", \"Y\"];\n      function cf(t2) {\n        var n2, e2, r2 = void 0 === t2.grouping || void 0 === t2.thousands ? rf : (n2 = af.call(t2.grouping, Number), e2 = t2.thousands + \"\", function(t3, r3) {\n          for (var i3 = t3.length, o3 = [], a3 = 0, u3 = n2[0], c3 = 0; i3 > 0 && u3 > 0 && (c3 + u3 + 1 > r3 && (u3 = Math.max(1, r3 - c3)), o3.push(t3.substring(i3 -= u3, i3 + u3)), !((c3 += u3 + 1) > r3)); )\n            u3 = n2[a3 = (a3 + 1) % n2.length];\n          return o3.reverse().join(e2);\n        }), i2 = void 0 === t2.currency ? \"\" : t2.currency[0] + \"\", o2 = void 0 === t2.currency ? \"\" : t2.currency[1] + \"\", a2 = void 0 === t2.decimal ? \".\" : t2.decimal + \"\", u2 = void 0 === t2.numerals ? rf : /* @__PURE__ */ function(t3) {\n          return function(n3) {\n            return n3.replace(/[0-9]/g, function(n4) {\n              return t3[+n4];\n            });\n          };\n        }(af.call(t2.numerals, String)), c2 = void 0 === t2.percent ? \"%\" : t2.percent + \"\", f2 = void 0 === t2.minus ? \"\\u2212\" : t2.minus + \"\", s2 = void 0 === t2.nan ? \"NaN\" : t2.nan + \"\";\n        function l2(t3) {\n          var n3 = (t3 = Jc(t3)).fill, e3 = t3.align, l3 = t3.sign, h2 = t3.symbol, d2 = t3.zero, p2 = t3.width, g2 = t3.comma, y2 = t3.precision, v2 = t3.trim, _2 = t3.type;\n          \"n\" === _2 ? (g2 = true, _2 = \"g\") : ef[_2] || (void 0 === y2 && (y2 = 12), v2 = true, _2 = \"g\"), (d2 || \"0\" === n3 && \"=\" === e3) && (d2 = true, n3 = \"0\", e3 = \"=\");\n          var b2 = \"$\" === h2 ? i2 : \"#\" === h2 && /[boxX]/.test(_2) ? \"0\" + _2.toLowerCase() : \"\", m2 = \"$\" === h2 ? o2 : /[%p]/.test(_2) ? c2 : \"\", x2 = ef[_2], w2 = /[defgprs%]/.test(_2);\n          function M2(t4) {\n            var i3, o3, c3, h3 = b2, M3 = m2;\n            if (\"c\" === _2)\n              M3 = x2(t4) + M3, t4 = \"\";\n            else {\n              var T2 = (t4 = +t4) < 0 || 1 / t4 < 0;\n              if (t4 = isNaN(t4) ? s2 : x2(Math.abs(t4), y2), v2 && (t4 = function(t5) {\n                t:\n                  for (var n4, e4 = t5.length, r3 = 1, i4 = -1; r3 < e4; ++r3)\n                    switch (t5[r3]) {\n                      case \".\":\n                        i4 = n4 = r3;\n                        break;\n                      case \"0\":\n                        0 === i4 && (i4 = r3), n4 = r3;\n                        break;\n                      default:\n                        if (!+t5[r3])\n                          break t;\n                        i4 > 0 && (i4 = 0);\n                    }\n                return i4 > 0 ? t5.slice(0, i4) + t5.slice(n4 + 1) : t5;\n              }(t4)), T2 && 0 == +t4 && \"+\" !== l3 && (T2 = false), h3 = (T2 ? \"(\" === l3 ? l3 : f2 : \"-\" === l3 || \"(\" === l3 ? \"\" : l3) + h3, M3 = (\"s\" === _2 ? uf[8 + Kc / 3] : \"\") + M3 + (T2 && \"(\" === l3 ? \")\" : \"\"), w2) {\n                for (i3 = -1, o3 = t4.length; ++i3 < o3; )\n                  if (48 > (c3 = t4.charCodeAt(i3)) || c3 > 57) {\n                    M3 = (46 === c3 ? a2 + t4.slice(i3 + 1) : t4.slice(i3)) + M3, t4 = t4.slice(0, i3);\n                    break;\n                  }\n              }\n            }\n            g2 && !d2 && (t4 = r2(t4, 1 / 0));\n            var A2 = h3.length + t4.length + M3.length, S2 = A2 < p2 ? new Array(p2 - A2 + 1).join(n3) : \"\";\n            switch (g2 && d2 && (t4 = r2(S2 + t4, S2.length ? p2 - M3.length : 1 / 0), S2 = \"\"), e3) {\n              case \"<\":\n                t4 = h3 + t4 + M3 + S2;\n                break;\n              case \"=\":\n                t4 = h3 + S2 + t4 + M3;\n                break;\n              case \"^\":\n                t4 = S2.slice(0, A2 = S2.length >> 1) + h3 + t4 + M3 + S2.slice(A2);\n                break;\n              default:\n                t4 = S2 + h3 + t4 + M3;\n            }\n            return u2(t4);\n          }\n          return y2 = void 0 === y2 ? 6 : /[gprs]/.test(_2) ? Math.max(1, Math.min(21, y2)) : Math.max(0, Math.min(20, y2)), M2.toString = function() {\n            return t3 + \"\";\n          }, M2;\n        }\n        return { format: l2, formatPrefix: function(t3, n3) {\n          var e3 = l2(((t3 = Jc(t3)).type = \"f\", t3)), r3 = 3 * Math.max(-8, Math.min(8, Math.floor(Zc(n3) / 3))), i3 = Math.pow(10, -r3), o3 = uf[8 + r3 / 3];\n          return function(t4) {\n            return e3(i3 * t4) + o3;\n          };\n        } };\n      }\n      function ff(n2) {\n        return of = cf(n2), t.format = of.format, t.formatPrefix = of.formatPrefix, of;\n      }\n      function sf(t2) {\n        return Math.max(0, -Zc(Math.abs(t2)));\n      }\n      function lf(t2, n2) {\n        return Math.max(0, 3 * Math.max(-8, Math.min(8, Math.floor(Zc(n2) / 3))) - Zc(Math.abs(t2)));\n      }\n      function hf(t2, n2) {\n        return t2 = Math.abs(t2), n2 = Math.abs(n2) - t2, Math.max(0, Zc(n2) - Zc(t2)) + 1;\n      }\n      t.format = void 0, t.formatPrefix = void 0, ff({ thousands: \",\", grouping: [3], currency: [\"$\", \"\"] });\n      var df = 1e-6, pf = 1e-12, gf = Math.PI, yf = gf / 2, vf = gf / 4, _f = 2 * gf, bf = 180 / gf, mf = gf / 180, xf = Math.abs, wf = Math.atan, Mf = Math.atan2, Tf = Math.cos, Af = Math.ceil, Sf = Math.exp, Ef = Math.hypot, Nf = Math.log, kf = Math.pow, Cf = Math.sin, Pf = Math.sign || function(t2) {\n        return t2 > 0 ? 1 : t2 < 0 ? -1 : 0;\n      }, zf = Math.sqrt, $f = Math.tan;\n      function Df(t2) {\n        return t2 > 1 ? 0 : t2 < -1 ? gf : Math.acos(t2);\n      }\n      function Rf(t2) {\n        return t2 > 1 ? yf : t2 < -1 ? -yf : Math.asin(t2);\n      }\n      function Ff(t2) {\n        return (t2 = Cf(t2 / 2)) * t2;\n      }\n      function qf() {\n      }\n      function Uf(t2, n2) {\n        t2 && Of.hasOwnProperty(t2.type) && Of[t2.type](t2, n2);\n      }\n      var If = { Feature: function(t2, n2) {\n        Uf(t2.geometry, n2);\n      }, FeatureCollection: function(t2, n2) {\n        for (var e2 = t2.features, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          Uf(e2[r2].geometry, n2);\n      } }, Of = { Sphere: function(t2, n2) {\n        n2.sphere();\n      }, Point: function(t2, n2) {\n        t2 = t2.coordinates, n2.point(t2[0], t2[1], t2[2]);\n      }, MultiPoint: function(t2, n2) {\n        for (var e2 = t2.coordinates, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          t2 = e2[r2], n2.point(t2[0], t2[1], t2[2]);\n      }, LineString: function(t2, n2) {\n        Bf(t2.coordinates, n2, 0);\n      }, MultiLineString: function(t2, n2) {\n        for (var e2 = t2.coordinates, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          Bf(e2[r2], n2, 0);\n      }, Polygon: function(t2, n2) {\n        Yf(t2.coordinates, n2);\n      }, MultiPolygon: function(t2, n2) {\n        for (var e2 = t2.coordinates, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          Yf(e2[r2], n2);\n      }, GeometryCollection: function(t2, n2) {\n        for (var e2 = t2.geometries, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          Uf(e2[r2], n2);\n      } };\n      function Bf(t2, n2, e2) {\n        var r2, i2 = -1, o2 = t2.length - e2;\n        for (n2.lineStart(); ++i2 < o2; )\n          r2 = t2[i2], n2.point(r2[0], r2[1], r2[2]);\n        n2.lineEnd();\n      }\n      function Yf(t2, n2) {\n        var e2 = -1, r2 = t2.length;\n        for (n2.polygonStart(); ++e2 < r2; )\n          Bf(t2[e2], n2, 1);\n        n2.polygonEnd();\n      }\n      function Lf(t2, n2) {\n        t2 && If.hasOwnProperty(t2.type) ? If[t2.type](t2, n2) : Uf(t2, n2);\n      }\n      var jf, Hf, Xf, Gf, Vf, Wf, Zf, Kf, Qf, Jf, ts, ns, es, rs, is, os, as = new T(), us = new T(), cs = { point: qf, lineStart: qf, lineEnd: qf, polygonStart: function() {\n        as = new T(), cs.lineStart = fs, cs.lineEnd = ss;\n      }, polygonEnd: function() {\n        var t2 = +as;\n        us.add(t2 < 0 ? _f + t2 : t2), this.lineStart = this.lineEnd = this.point = qf;\n      }, sphere: function() {\n        us.add(_f);\n      } };\n      function fs() {\n        cs.point = ls;\n      }\n      function ss() {\n        hs(jf, Hf);\n      }\n      function ls(t2, n2) {\n        cs.point = hs, jf = t2, Hf = n2, Xf = t2 *= mf, Gf = Tf(n2 = (n2 *= mf) / 2 + vf), Vf = Cf(n2);\n      }\n      function hs(t2, n2) {\n        var e2 = (t2 *= mf) - Xf, r2 = e2 >= 0 ? 1 : -1, i2 = r2 * e2, o2 = Tf(n2 = (n2 *= mf) / 2 + vf), a2 = Cf(n2), u2 = Vf * a2, c2 = Gf * o2 + u2 * Tf(i2), f2 = u2 * r2 * Cf(i2);\n        as.add(Mf(f2, c2)), Xf = t2, Gf = o2, Vf = a2;\n      }\n      function ds(t2) {\n        return [Mf(t2[1], t2[0]), Rf(t2[2])];\n      }\n      function ps(t2) {\n        var n2 = t2[0], e2 = t2[1], r2 = Tf(e2);\n        return [r2 * Tf(n2), r2 * Cf(n2), Cf(e2)];\n      }\n      function gs(t2, n2) {\n        return t2[0] * n2[0] + t2[1] * n2[1] + t2[2] * n2[2];\n      }\n      function ys(t2, n2) {\n        return [t2[1] * n2[2] - t2[2] * n2[1], t2[2] * n2[0] - t2[0] * n2[2], t2[0] * n2[1] - t2[1] * n2[0]];\n      }\n      function vs(t2, n2) {\n        t2[0] += n2[0], t2[1] += n2[1], t2[2] += n2[2];\n      }\n      function _s(t2, n2) {\n        return [t2[0] * n2, t2[1] * n2, t2[2] * n2];\n      }\n      function bs(t2) {\n        var n2 = zf(t2[0] * t2[0] + t2[1] * t2[1] + t2[2] * t2[2]);\n        t2[0] /= n2, t2[1] /= n2, t2[2] /= n2;\n      }\n      var ms, xs, ws, Ms, Ts, As, Ss, Es, Ns, ks, Cs, Ps, zs, $s, Ds, Rs, Fs = { point: qs, lineStart: Is, lineEnd: Os, polygonStart: function() {\n        Fs.point = Bs, Fs.lineStart = Ys, Fs.lineEnd = Ls, rs = new T(), cs.polygonStart();\n      }, polygonEnd: function() {\n        cs.polygonEnd(), Fs.point = qs, Fs.lineStart = Is, Fs.lineEnd = Os, as < 0 ? (Wf = -(Kf = 180), Zf = -(Qf = 90)) : rs > df ? Qf = 90 : rs < -df && (Zf = -90), os[0] = Wf, os[1] = Kf;\n      }, sphere: function() {\n        Wf = -(Kf = 180), Zf = -(Qf = 90);\n      } };\n      function qs(t2, n2) {\n        is.push(os = [Wf = t2, Kf = t2]), n2 < Zf && (Zf = n2), n2 > Qf && (Qf = n2);\n      }\n      function Us(t2, n2) {\n        var e2 = ps([t2 * mf, n2 * mf]);\n        if (es) {\n          var r2 = ys(es, e2), i2 = ys([r2[1], -r2[0], 0], r2);\n          bs(i2), i2 = ds(i2);\n          var o2, a2 = t2 - Jf, u2 = a2 > 0 ? 1 : -1, c2 = i2[0] * bf * u2, f2 = xf(a2) > 180;\n          f2 ^ (u2 * Jf < c2 && c2 < u2 * t2) ? (o2 = i2[1] * bf) > Qf && (Qf = o2) : f2 ^ (u2 * Jf < (c2 = (c2 + 360) % 360 - 180) && c2 < u2 * t2) ? (o2 = -i2[1] * bf) < Zf && (Zf = o2) : (n2 < Zf && (Zf = n2), n2 > Qf && (Qf = n2)), f2 ? t2 < Jf ? js(Wf, t2) > js(Wf, Kf) && (Kf = t2) : js(t2, Kf) > js(Wf, Kf) && (Wf = t2) : Kf >= Wf ? (t2 < Wf && (Wf = t2), t2 > Kf && (Kf = t2)) : t2 > Jf ? js(Wf, t2) > js(Wf, Kf) && (Kf = t2) : js(t2, Kf) > js(Wf, Kf) && (Wf = t2);\n        } else\n          is.push(os = [Wf = t2, Kf = t2]);\n        n2 < Zf && (Zf = n2), n2 > Qf && (Qf = n2), es = e2, Jf = t2;\n      }\n      function Is() {\n        Fs.point = Us;\n      }\n      function Os() {\n        os[0] = Wf, os[1] = Kf, Fs.point = qs, es = null;\n      }\n      function Bs(t2, n2) {\n        if (es) {\n          var e2 = t2 - Jf;\n          rs.add(xf(e2) > 180 ? e2 + (e2 > 0 ? 360 : -360) : e2);\n        } else\n          ts = t2, ns = n2;\n        cs.point(t2, n2), Us(t2, n2);\n      }\n      function Ys() {\n        cs.lineStart();\n      }\n      function Ls() {\n        Bs(ts, ns), cs.lineEnd(), xf(rs) > df && (Wf = -(Kf = 180)), os[0] = Wf, os[1] = Kf, es = null;\n      }\n      function js(t2, n2) {\n        return (n2 -= t2) < 0 ? n2 + 360 : n2;\n      }\n      function Hs(t2, n2) {\n        return t2[0] - n2[0];\n      }\n      function Xs(t2, n2) {\n        return t2[0] <= t2[1] ? t2[0] <= n2 && n2 <= t2[1] : n2 < t2[0] || t2[1] < n2;\n      }\n      var Gs = { sphere: qf, point: Vs, lineStart: Zs, lineEnd: Js, polygonStart: function() {\n        Gs.lineStart = tl, Gs.lineEnd = nl;\n      }, polygonEnd: function() {\n        Gs.lineStart = Zs, Gs.lineEnd = Js;\n      } };\n      function Vs(t2, n2) {\n        t2 *= mf;\n        var e2 = Tf(n2 *= mf);\n        Ws(e2 * Tf(t2), e2 * Cf(t2), Cf(n2));\n      }\n      function Ws(t2, n2, e2) {\n        ++ms, ws += (t2 - ws) / ms, Ms += (n2 - Ms) / ms, Ts += (e2 - Ts) / ms;\n      }\n      function Zs() {\n        Gs.point = Ks;\n      }\n      function Ks(t2, n2) {\n        t2 *= mf;\n        var e2 = Tf(n2 *= mf);\n        $s = e2 * Tf(t2), Ds = e2 * Cf(t2), Rs = Cf(n2), Gs.point = Qs, Ws($s, Ds, Rs);\n      }\n      function Qs(t2, n2) {\n        t2 *= mf;\n        var e2 = Tf(n2 *= mf), r2 = e2 * Tf(t2), i2 = e2 * Cf(t2), o2 = Cf(n2), a2 = Mf(zf((a2 = Ds * o2 - Rs * i2) * a2 + (a2 = Rs * r2 - $s * o2) * a2 + (a2 = $s * i2 - Ds * r2) * a2), $s * r2 + Ds * i2 + Rs * o2);\n        xs += a2, As += a2 * ($s + ($s = r2)), Ss += a2 * (Ds + (Ds = i2)), Es += a2 * (Rs + (Rs = o2)), Ws($s, Ds, Rs);\n      }\n      function Js() {\n        Gs.point = Vs;\n      }\n      function tl() {\n        Gs.point = el;\n      }\n      function nl() {\n        rl(Ps, zs), Gs.point = Vs;\n      }\n      function el(t2, n2) {\n        Ps = t2, zs = n2, t2 *= mf, n2 *= mf, Gs.point = rl;\n        var e2 = Tf(n2);\n        $s = e2 * Tf(t2), Ds = e2 * Cf(t2), Rs = Cf(n2), Ws($s, Ds, Rs);\n      }\n      function rl(t2, n2) {\n        t2 *= mf;\n        var e2 = Tf(n2 *= mf), r2 = e2 * Tf(t2), i2 = e2 * Cf(t2), o2 = Cf(n2), a2 = Ds * o2 - Rs * i2, u2 = Rs * r2 - $s * o2, c2 = $s * i2 - Ds * r2, f2 = Ef(a2, u2, c2), s2 = Rf(f2), l2 = f2 && -s2 / f2;\n        Ns.add(l2 * a2), ks.add(l2 * u2), Cs.add(l2 * c2), xs += s2, As += s2 * ($s + ($s = r2)), Ss += s2 * (Ds + (Ds = i2)), Es += s2 * (Rs + (Rs = o2)), Ws($s, Ds, Rs);\n      }\n      function il(t2) {\n        return function() {\n          return t2;\n        };\n      }\n      function ol(t2, n2) {\n        function e2(e3, r2) {\n          return e3 = t2(e3, r2), n2(e3[0], e3[1]);\n        }\n        return t2.invert && n2.invert && (e2.invert = function(e3, r2) {\n          return (e3 = n2.invert(e3, r2)) && t2.invert(e3[0], e3[1]);\n        }), e2;\n      }\n      function al(t2, n2) {\n        return xf(t2) > gf && (t2 -= Math.round(t2 / _f) * _f), [t2, n2];\n      }\n      function ul(t2, n2, e2) {\n        return (t2 %= _f) ? n2 || e2 ? ol(fl(t2), sl(n2, e2)) : fl(t2) : n2 || e2 ? sl(n2, e2) : al;\n      }\n      function cl(t2) {\n        return function(n2, e2) {\n          return xf(n2 += t2) > gf && (n2 -= Math.round(n2 / _f) * _f), [n2, e2];\n        };\n      }\n      function fl(t2) {\n        var n2 = cl(t2);\n        return n2.invert = cl(-t2), n2;\n      }\n      function sl(t2, n2) {\n        var e2 = Tf(t2), r2 = Cf(t2), i2 = Tf(n2), o2 = Cf(n2);\n        function a2(t3, n3) {\n          var a3 = Tf(n3), u2 = Tf(t3) * a3, c2 = Cf(t3) * a3, f2 = Cf(n3), s2 = f2 * e2 + u2 * r2;\n          return [Mf(c2 * i2 - s2 * o2, u2 * e2 - f2 * r2), Rf(s2 * i2 + c2 * o2)];\n        }\n        return a2.invert = function(t3, n3) {\n          var a3 = Tf(n3), u2 = Tf(t3) * a3, c2 = Cf(t3) * a3, f2 = Cf(n3), s2 = f2 * i2 - c2 * o2;\n          return [Mf(c2 * i2 + f2 * o2, u2 * e2 + s2 * r2), Rf(s2 * e2 - u2 * r2)];\n        }, a2;\n      }\n      function ll(t2) {\n        function n2(n3) {\n          return (n3 = t2(n3[0] * mf, n3[1] * mf))[0] *= bf, n3[1] *= bf, n3;\n        }\n        return t2 = ul(t2[0] * mf, t2[1] * mf, t2.length > 2 ? t2[2] * mf : 0), n2.invert = function(n3) {\n          return (n3 = t2.invert(n3[0] * mf, n3[1] * mf))[0] *= bf, n3[1] *= bf, n3;\n        }, n2;\n      }\n      function hl(t2, n2, e2, r2, i2, o2) {\n        if (e2) {\n          var a2 = Tf(n2), u2 = Cf(n2), c2 = r2 * e2;\n          null == i2 ? (i2 = n2 + r2 * _f, o2 = n2 - c2 / 2) : (i2 = dl(a2, i2), o2 = dl(a2, o2), (r2 > 0 ? i2 < o2 : i2 > o2) && (i2 += r2 * _f));\n          for (var f2, s2 = i2; r2 > 0 ? s2 > o2 : s2 < o2; s2 -= c2)\n            f2 = ds([a2, -u2 * Tf(s2), -u2 * Cf(s2)]), t2.point(f2[0], f2[1]);\n        }\n      }\n      function dl(t2, n2) {\n        (n2 = ps(n2))[0] -= t2, bs(n2);\n        var e2 = Df(-n2[1]);\n        return ((-n2[2] < 0 ? -e2 : e2) + _f - df) % _f;\n      }\n      function pl() {\n        var t2, n2 = [];\n        return { point: function(n3, e2, r2) {\n          t2.push([n3, e2, r2]);\n        }, lineStart: function() {\n          n2.push(t2 = []);\n        }, lineEnd: qf, rejoin: function() {\n          n2.length > 1 && n2.push(n2.pop().concat(n2.shift()));\n        }, result: function() {\n          var e2 = n2;\n          return n2 = [], t2 = null, e2;\n        } };\n      }\n      function gl(t2, n2) {\n        return xf(t2[0] - n2[0]) < df && xf(t2[1] - n2[1]) < df;\n      }\n      function yl(t2, n2, e2, r2) {\n        this.x = t2, this.z = n2, this.o = e2, this.e = r2, this.v = false, this.n = this.p = null;\n      }\n      function vl(t2, n2, e2, r2, i2) {\n        var o2, a2, u2 = [], c2 = [];\n        if (t2.forEach(function(t3) {\n          if (!((n3 = t3.length - 1) <= 0)) {\n            var n3, e3, r3 = t3[0], a3 = t3[n3];\n            if (gl(r3, a3)) {\n              if (!r3[2] && !a3[2]) {\n                for (i2.lineStart(), o2 = 0; o2 < n3; ++o2)\n                  i2.point((r3 = t3[o2])[0], r3[1]);\n                return void i2.lineEnd();\n              }\n              a3[0] += 2 * df;\n            }\n            u2.push(e3 = new yl(r3, t3, null, true)), c2.push(e3.o = new yl(r3, null, e3, false)), u2.push(e3 = new yl(a3, t3, null, false)), c2.push(e3.o = new yl(a3, null, e3, true));\n          }\n        }), u2.length) {\n          for (c2.sort(n2), _l(u2), _l(c2), o2 = 0, a2 = c2.length; o2 < a2; ++o2)\n            c2[o2].e = e2 = !e2;\n          for (var f2, s2, l2 = u2[0]; ; ) {\n            for (var h2 = l2, d2 = true; h2.v; )\n              if ((h2 = h2.n) === l2)\n                return;\n            f2 = h2.z, i2.lineStart();\n            do {\n              if (h2.v = h2.o.v = true, h2.e) {\n                if (d2)\n                  for (o2 = 0, a2 = f2.length; o2 < a2; ++o2)\n                    i2.point((s2 = f2[o2])[0], s2[1]);\n                else\n                  r2(h2.x, h2.n.x, 1, i2);\n                h2 = h2.n;\n              } else {\n                if (d2)\n                  for (f2 = h2.p.z, o2 = f2.length - 1; o2 >= 0; --o2)\n                    i2.point((s2 = f2[o2])[0], s2[1]);\n                else\n                  r2(h2.x, h2.p.x, -1, i2);\n                h2 = h2.p;\n              }\n              f2 = (h2 = h2.o).z, d2 = !d2;\n            } while (!h2.v);\n            i2.lineEnd();\n          }\n        }\n      }\n      function _l(t2) {\n        if (n2 = t2.length) {\n          for (var n2, e2, r2 = 0, i2 = t2[0]; ++r2 < n2; )\n            i2.n = e2 = t2[r2], e2.p = i2, i2 = e2;\n          i2.n = e2 = t2[0], e2.p = i2;\n        }\n      }\n      function bl(t2) {\n        return xf(t2[0]) <= gf ? t2[0] : Pf(t2[0]) * ((xf(t2[0]) + gf) % _f - gf);\n      }\n      function ml(t2, n2) {\n        var e2 = bl(n2), r2 = n2[1], i2 = Cf(r2), o2 = [Cf(e2), -Tf(e2), 0], a2 = 0, u2 = 0, c2 = new T();\n        1 === i2 ? r2 = yf + df : -1 === i2 && (r2 = -yf - df);\n        for (var f2 = 0, s2 = t2.length; f2 < s2; ++f2)\n          if (h2 = (l2 = t2[f2]).length)\n            for (var l2, h2, d2 = l2[h2 - 1], p2 = bl(d2), g2 = d2[1] / 2 + vf, y2 = Cf(g2), v2 = Tf(g2), _2 = 0; _2 < h2; ++_2, p2 = m2, y2 = w2, v2 = M2, d2 = b2) {\n              var b2 = l2[_2], m2 = bl(b2), x2 = b2[1] / 2 + vf, w2 = Cf(x2), M2 = Tf(x2), A2 = m2 - p2, S2 = A2 >= 0 ? 1 : -1, E2 = S2 * A2, N2 = E2 > gf, k2 = y2 * w2;\n              if (c2.add(Mf(k2 * S2 * Cf(E2), v2 * M2 + k2 * Tf(E2))), a2 += N2 ? A2 + S2 * _f : A2, N2 ^ p2 >= e2 ^ m2 >= e2) {\n                var C2 = ys(ps(d2), ps(b2));\n                bs(C2);\n                var P2 = ys(o2, C2);\n                bs(P2);\n                var z2 = (N2 ^ A2 >= 0 ? -1 : 1) * Rf(P2[2]);\n                (r2 > z2 || r2 === z2 && (C2[0] || C2[1])) && (u2 += N2 ^ A2 >= 0 ? 1 : -1);\n              }\n            }\n        return (a2 < -df || a2 < df && c2 < -pf) ^ 1 & u2;\n      }\n      function xl(t2, n2, e2, r2) {\n        return function(i2) {\n          var o2, a2, u2, c2 = n2(i2), f2 = pl(), s2 = n2(f2), l2 = false, h2 = { point: d2, lineStart: g2, lineEnd: y2, polygonStart: function() {\n            h2.point = v2, h2.lineStart = _2, h2.lineEnd = b2, a2 = [], o2 = [];\n          }, polygonEnd: function() {\n            h2.point = d2, h2.lineStart = g2, h2.lineEnd = y2, a2 = ft(a2);\n            var t3 = ml(o2, r2);\n            a2.length ? (l2 || (i2.polygonStart(), l2 = true), vl(a2, Ml, t3, e2, i2)) : t3 && (l2 || (i2.polygonStart(), l2 = true), i2.lineStart(), e2(null, null, 1, i2), i2.lineEnd()), l2 && (i2.polygonEnd(), l2 = false), a2 = o2 = null;\n          }, sphere: function() {\n            i2.polygonStart(), i2.lineStart(), e2(null, null, 1, i2), i2.lineEnd(), i2.polygonEnd();\n          } };\n          function d2(n3, e3) {\n            t2(n3, e3) && i2.point(n3, e3);\n          }\n          function p2(t3, n3) {\n            c2.point(t3, n3);\n          }\n          function g2() {\n            h2.point = p2, c2.lineStart();\n          }\n          function y2() {\n            h2.point = d2, c2.lineEnd();\n          }\n          function v2(t3, n3) {\n            u2.push([t3, n3]), s2.point(t3, n3);\n          }\n          function _2() {\n            s2.lineStart(), u2 = [];\n          }\n          function b2() {\n            v2(u2[0][0], u2[0][1]), s2.lineEnd();\n            var t3, n3, e3, r3, c3 = s2.clean(), h3 = f2.result(), d4 = h3.length;\n            if (u2.pop(), o2.push(u2), u2 = null, d4)\n              if (1 & c3) {\n                if ((n3 = (e3 = h3[0]).length - 1) > 0) {\n                  for (l2 || (i2.polygonStart(), l2 = true), i2.lineStart(), t3 = 0; t3 < n3; ++t3)\n                    i2.point((r3 = e3[t3])[0], r3[1]);\n                  i2.lineEnd();\n                }\n              } else\n                d4 > 1 && 2 & c3 && h3.push(h3.pop().concat(h3.shift())), a2.push(h3.filter(wl));\n          }\n          return h2;\n        };\n      }\n      function wl(t2) {\n        return t2.length > 1;\n      }\n      function Ml(t2, n2) {\n        return ((t2 = t2.x)[0] < 0 ? t2[1] - yf - df : yf - t2[1]) - ((n2 = n2.x)[0] < 0 ? n2[1] - yf - df : yf - n2[1]);\n      }\n      al.invert = al;\n      var Tl = xl(function() {\n        return true;\n      }, function(t2) {\n        var n2, e2 = NaN, r2 = NaN, i2 = NaN;\n        return { lineStart: function() {\n          t2.lineStart(), n2 = 1;\n        }, point: function(o2, a2) {\n          var u2 = o2 > 0 ? gf : -gf, c2 = xf(o2 - e2);\n          xf(c2 - gf) < df ? (t2.point(e2, r2 = (r2 + a2) / 2 > 0 ? yf : -yf), t2.point(i2, r2), t2.lineEnd(), t2.lineStart(), t2.point(u2, r2), t2.point(o2, r2), n2 = 0) : i2 !== u2 && c2 >= gf && (xf(e2 - i2) < df && (e2 -= i2 * df), xf(o2 - u2) < df && (o2 -= u2 * df), r2 = function(t3, n3, e3, r3) {\n            var i3, o3, a3 = Cf(t3 - e3);\n            return xf(a3) > df ? wf((Cf(n3) * (o3 = Tf(r3)) * Cf(e3) - Cf(r3) * (i3 = Tf(n3)) * Cf(t3)) / (i3 * o3 * a3)) : (n3 + r3) / 2;\n          }(e2, r2, o2, a2), t2.point(i2, r2), t2.lineEnd(), t2.lineStart(), t2.point(u2, r2), n2 = 0), t2.point(e2 = o2, r2 = a2), i2 = u2;\n        }, lineEnd: function() {\n          t2.lineEnd(), e2 = r2 = NaN;\n        }, clean: function() {\n          return 2 - n2;\n        } };\n      }, function(t2, n2, e2, r2) {\n        var i2;\n        if (null == t2)\n          i2 = e2 * yf, r2.point(-gf, i2), r2.point(0, i2), r2.point(gf, i2), r2.point(gf, 0), r2.point(gf, -i2), r2.point(0, -i2), r2.point(-gf, -i2), r2.point(-gf, 0), r2.point(-gf, i2);\n        else if (xf(t2[0] - n2[0]) > df) {\n          var o2 = t2[0] < n2[0] ? gf : -gf;\n          i2 = e2 * o2 / 2, r2.point(-o2, i2), r2.point(0, i2), r2.point(o2, i2);\n        } else\n          r2.point(n2[0], n2[1]);\n      }, [-gf, -yf]);\n      function Al(t2) {\n        var n2 = Tf(t2), e2 = 6 * mf, r2 = n2 > 0, i2 = xf(n2) > df;\n        function o2(t3, e3) {\n          return Tf(t3) * Tf(e3) > n2;\n        }\n        function a2(t3, e3, r3) {\n          var i3 = [1, 0, 0], o3 = ys(ps(t3), ps(e3)), a3 = gs(o3, o3), u3 = o3[0], c2 = a3 - u3 * u3;\n          if (!c2)\n            return !r3 && t3;\n          var f2 = n2 * a3 / c2, s2 = -n2 * u3 / c2, l2 = ys(i3, o3), h2 = _s(i3, f2);\n          vs(h2, _s(o3, s2));\n          var d2 = l2, p2 = gs(h2, d2), g2 = gs(d2, d2), y2 = p2 * p2 - g2 * (gs(h2, h2) - 1);\n          if (!(y2 < 0)) {\n            var v2 = zf(y2), _2 = _s(d2, (-p2 - v2) / g2);\n            if (vs(_2, h2), _2 = ds(_2), !r3)\n              return _2;\n            var b2, m2 = t3[0], x2 = e3[0], w2 = t3[1], M2 = e3[1];\n            x2 < m2 && (b2 = m2, m2 = x2, x2 = b2);\n            var T2 = x2 - m2, A2 = xf(T2 - gf) < df;\n            if (!A2 && M2 < w2 && (b2 = w2, w2 = M2, M2 = b2), A2 || T2 < df ? A2 ? w2 + M2 > 0 ^ _2[1] < (xf(_2[0] - m2) < df ? w2 : M2) : w2 <= _2[1] && _2[1] <= M2 : T2 > gf ^ (m2 <= _2[0] && _2[0] <= x2)) {\n              var S2 = _s(d2, (-p2 + v2) / g2);\n              return vs(S2, h2), [_2, ds(S2)];\n            }\n          }\n        }\n        function u2(n3, e3) {\n          var i3 = r2 ? t2 : gf - t2, o3 = 0;\n          return n3 < -i3 ? o3 |= 1 : n3 > i3 && (o3 |= 2), e3 < -i3 ? o3 |= 4 : e3 > i3 && (o3 |= 8), o3;\n        }\n        return xl(o2, function(t3) {\n          var n3, e3, c2, f2, s2;\n          return { lineStart: function() {\n            f2 = c2 = false, s2 = 1;\n          }, point: function(l2, h2) {\n            var d2, p2 = [l2, h2], g2 = o2(l2, h2), y2 = r2 ? g2 ? 0 : u2(l2, h2) : g2 ? u2(l2 + (l2 < 0 ? gf : -gf), h2) : 0;\n            if (!n3 && (f2 = c2 = g2) && t3.lineStart(), g2 !== c2 && (!(d2 = a2(n3, p2)) || gl(n3, d2) || gl(p2, d2)) && (p2[2] = 1), g2 !== c2)\n              s2 = 0, g2 ? (t3.lineStart(), d2 = a2(p2, n3), t3.point(d2[0], d2[1])) : (d2 = a2(n3, p2), t3.point(d2[0], d2[1], 2), t3.lineEnd()), n3 = d2;\n            else if (i2 && n3 && r2 ^ g2) {\n              var v2;\n              y2 & e3 || !(v2 = a2(p2, n3, true)) || (s2 = 0, r2 ? (t3.lineStart(), t3.point(v2[0][0], v2[0][1]), t3.point(v2[1][0], v2[1][1]), t3.lineEnd()) : (t3.point(v2[1][0], v2[1][1]), t3.lineEnd(), t3.lineStart(), t3.point(v2[0][0], v2[0][1], 3)));\n            }\n            !g2 || n3 && gl(n3, p2) || t3.point(p2[0], p2[1]), n3 = p2, c2 = g2, e3 = y2;\n          }, lineEnd: function() {\n            c2 && t3.lineEnd(), n3 = null;\n          }, clean: function() {\n            return s2 | (f2 && c2) << 1;\n          } };\n        }, function(n3, r3, i3, o3) {\n          hl(o3, t2, e2, i3, n3, r3);\n        }, r2 ? [0, -t2] : [-gf, t2 - gf]);\n      }\n      var Sl, El, Nl, kl, Cl = 1e9, Pl = -Cl;\n      function zl(t2, n2, e2, r2) {\n        function i2(i3, o3) {\n          return t2 <= i3 && i3 <= e2 && n2 <= o3 && o3 <= r2;\n        }\n        function o2(i3, o3, u3, f2) {\n          var s2 = 0, l2 = 0;\n          if (null == i3 || (s2 = a2(i3, u3)) !== (l2 = a2(o3, u3)) || c2(i3, o3) < 0 ^ u3 > 0)\n            do {\n              f2.point(0 === s2 || 3 === s2 ? t2 : e2, s2 > 1 ? r2 : n2);\n            } while ((s2 = (s2 + u3 + 4) % 4) !== l2);\n          else\n            f2.point(o3[0], o3[1]);\n        }\n        function a2(r3, i3) {\n          return xf(r3[0] - t2) < df ? i3 > 0 ? 0 : 3 : xf(r3[0] - e2) < df ? i3 > 0 ? 2 : 1 : xf(r3[1] - n2) < df ? i3 > 0 ? 1 : 0 : i3 > 0 ? 3 : 2;\n        }\n        function u2(t3, n3) {\n          return c2(t3.x, n3.x);\n        }\n        function c2(t3, n3) {\n          var e3 = a2(t3, 1), r3 = a2(n3, 1);\n          return e3 !== r3 ? e3 - r3 : 0 === e3 ? n3[1] - t3[1] : 1 === e3 ? t3[0] - n3[0] : 2 === e3 ? t3[1] - n3[1] : n3[0] - t3[0];\n        }\n        return function(a3) {\n          var c3, f2, s2, l2, h2, d2, p2, g2, y2, v2, _2, b2 = a3, m2 = pl(), x2 = { point: w2, lineStart: function() {\n            x2.point = M2, f2 && f2.push(s2 = []);\n            v2 = true, y2 = false, p2 = g2 = NaN;\n          }, lineEnd: function() {\n            c3 && (M2(l2, h2), d2 && y2 && m2.rejoin(), c3.push(m2.result()));\n            x2.point = w2, y2 && b2.lineEnd();\n          }, polygonStart: function() {\n            b2 = m2, c3 = [], f2 = [], _2 = true;\n          }, polygonEnd: function() {\n            var n3 = function() {\n              for (var n4 = 0, e4 = 0, i4 = f2.length; e4 < i4; ++e4)\n                for (var o3, a4, u3 = f2[e4], c4 = 1, s3 = u3.length, l3 = u3[0], h3 = l3[0], d4 = l3[1]; c4 < s3; ++c4)\n                  o3 = h3, a4 = d4, h3 = (l3 = u3[c4])[0], d4 = l3[1], a4 <= r2 ? d4 > r2 && (h3 - o3) * (r2 - a4) > (d4 - a4) * (t2 - o3) && ++n4 : d4 <= r2 && (h3 - o3) * (r2 - a4) < (d4 - a4) * (t2 - o3) && --n4;\n              return n4;\n            }(), e3 = _2 && n3, i3 = (c3 = ft(c3)).length;\n            (e3 || i3) && (a3.polygonStart(), e3 && (a3.lineStart(), o2(null, null, 1, a3), a3.lineEnd()), i3 && vl(c3, u2, n3, o2, a3), a3.polygonEnd());\n            b2 = a3, c3 = f2 = s2 = null;\n          } };\n          function w2(t3, n3) {\n            i2(t3, n3) && b2.point(t3, n3);\n          }\n          function M2(o3, a4) {\n            var u3 = i2(o3, a4);\n            if (f2 && s2.push([o3, a4]), v2)\n              l2 = o3, h2 = a4, d2 = u3, v2 = false, u3 && (b2.lineStart(), b2.point(o3, a4));\n            else if (u3 && y2)\n              b2.point(o3, a4);\n            else {\n              var c4 = [p2 = Math.max(Pl, Math.min(Cl, p2)), g2 = Math.max(Pl, Math.min(Cl, g2))], m3 = [o3 = Math.max(Pl, Math.min(Cl, o3)), a4 = Math.max(Pl, Math.min(Cl, a4))];\n              !function(t3, n3, e3, r3, i3, o4) {\n                var a5, u4 = t3[0], c5 = t3[1], f3 = 0, s3 = 1, l3 = n3[0] - u4, h3 = n3[1] - c5;\n                if (a5 = e3 - u4, l3 || !(a5 > 0)) {\n                  if (a5 /= l3, l3 < 0) {\n                    if (a5 < f3)\n                      return;\n                    a5 < s3 && (s3 = a5);\n                  } else if (l3 > 0) {\n                    if (a5 > s3)\n                      return;\n                    a5 > f3 && (f3 = a5);\n                  }\n                  if (a5 = i3 - u4, l3 || !(a5 < 0)) {\n                    if (a5 /= l3, l3 < 0) {\n                      if (a5 > s3)\n                        return;\n                      a5 > f3 && (f3 = a5);\n                    } else if (l3 > 0) {\n                      if (a5 < f3)\n                        return;\n                      a5 < s3 && (s3 = a5);\n                    }\n                    if (a5 = r3 - c5, h3 || !(a5 > 0)) {\n                      if (a5 /= h3, h3 < 0) {\n                        if (a5 < f3)\n                          return;\n                        a5 < s3 && (s3 = a5);\n                      } else if (h3 > 0) {\n                        if (a5 > s3)\n                          return;\n                        a5 > f3 && (f3 = a5);\n                      }\n                      if (a5 = o4 - c5, h3 || !(a5 < 0)) {\n                        if (a5 /= h3, h3 < 0) {\n                          if (a5 > s3)\n                            return;\n                          a5 > f3 && (f3 = a5);\n                        } else if (h3 > 0) {\n                          if (a5 < f3)\n                            return;\n                          a5 < s3 && (s3 = a5);\n                        }\n                        return f3 > 0 && (t3[0] = u4 + f3 * l3, t3[1] = c5 + f3 * h3), s3 < 1 && (n3[0] = u4 + s3 * l3, n3[1] = c5 + s3 * h3), true;\n                      }\n                    }\n                  }\n                }\n              }(c4, m3, t2, n2, e2, r2) ? u3 && (b2.lineStart(), b2.point(o3, a4), _2 = false) : (y2 || (b2.lineStart(), b2.point(c4[0], c4[1])), b2.point(m3[0], m3[1]), u3 || b2.lineEnd(), _2 = false);\n            }\n            p2 = o3, g2 = a4, y2 = u3;\n          }\n          return x2;\n        };\n      }\n      var $l = { sphere: qf, point: qf, lineStart: function() {\n        $l.point = Rl, $l.lineEnd = Dl;\n      }, lineEnd: qf, polygonStart: qf, polygonEnd: qf };\n      function Dl() {\n        $l.point = $l.lineEnd = qf;\n      }\n      function Rl(t2, n2) {\n        El = t2 *= mf, Nl = Cf(n2 *= mf), kl = Tf(n2), $l.point = Fl;\n      }\n      function Fl(t2, n2) {\n        t2 *= mf;\n        var e2 = Cf(n2 *= mf), r2 = Tf(n2), i2 = xf(t2 - El), o2 = Tf(i2), a2 = r2 * Cf(i2), u2 = kl * e2 - Nl * r2 * o2, c2 = Nl * e2 + kl * r2 * o2;\n        Sl.add(Mf(zf(a2 * a2 + u2 * u2), c2)), El = t2, Nl = e2, kl = r2;\n      }\n      function ql(t2) {\n        return Sl = new T(), Lf(t2, $l), +Sl;\n      }\n      var Ul = [null, null], Il = { type: \"LineString\", coordinates: Ul };\n      function Ol(t2, n2) {\n        return Ul[0] = t2, Ul[1] = n2, ql(Il);\n      }\n      var Bl = { Feature: function(t2, n2) {\n        return Ll(t2.geometry, n2);\n      }, FeatureCollection: function(t2, n2) {\n        for (var e2 = t2.features, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          if (Ll(e2[r2].geometry, n2))\n            return true;\n        return false;\n      } }, Yl = { Sphere: function() {\n        return true;\n      }, Point: function(t2, n2) {\n        return jl(t2.coordinates, n2);\n      }, MultiPoint: function(t2, n2) {\n        for (var e2 = t2.coordinates, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          if (jl(e2[r2], n2))\n            return true;\n        return false;\n      }, LineString: function(t2, n2) {\n        return Hl(t2.coordinates, n2);\n      }, MultiLineString: function(t2, n2) {\n        for (var e2 = t2.coordinates, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          if (Hl(e2[r2], n2))\n            return true;\n        return false;\n      }, Polygon: function(t2, n2) {\n        return Xl(t2.coordinates, n2);\n      }, MultiPolygon: function(t2, n2) {\n        for (var e2 = t2.coordinates, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          if (Xl(e2[r2], n2))\n            return true;\n        return false;\n      }, GeometryCollection: function(t2, n2) {\n        for (var e2 = t2.geometries, r2 = -1, i2 = e2.length; ++r2 < i2; )\n          if (Ll(e2[r2], n2))\n            return true;\n        return false;\n      } };\n      function Ll(t2, n2) {\n        return !(!t2 || !Yl.hasOwnProperty(t2.type)) && Yl[t2.type](t2, n2);\n      }\n      function jl(t2, n2) {\n        return 0 === Ol(t2, n2);\n      }\n      function Hl(t2, n2) {\n        for (var e2, r2, i2, o2 = 0, a2 = t2.length; o2 < a2; o2++) {\n          if (0 === (r2 = Ol(t2[o2], n2)))\n            return true;\n          if (o2 > 0 && (i2 = Ol(t2[o2], t2[o2 - 1])) > 0 && e2 <= i2 && r2 <= i2 && (e2 + r2 - i2) * (1 - Math.pow((e2 - r2) / i2, 2)) < pf * i2)\n            return true;\n          e2 = r2;\n        }\n        return false;\n      }\n      function Xl(t2, n2) {\n        return !!ml(t2.map(Gl), Vl(n2));\n      }\n      function Gl(t2) {\n        return (t2 = t2.map(Vl)).pop(), t2;\n      }\n      function Vl(t2) {\n        return [t2[0] * mf, t2[1] * mf];\n      }\n      function Wl(t2, n2, e2) {\n        var r2 = lt(t2, n2 - df, e2).concat(n2);\n        return function(t3) {\n          return r2.map(function(n3) {\n            return [t3, n3];\n          });\n        };\n      }\n      function Zl(t2, n2, e2) {\n        var r2 = lt(t2, n2 - df, e2).concat(n2);\n        return function(t3) {\n          return r2.map(function(n3) {\n            return [n3, t3];\n          });\n        };\n      }\n      function Kl() {\n        var t2, n2, e2, r2, i2, o2, a2, u2, c2, f2, s2, l2, h2 = 10, d2 = h2, p2 = 90, g2 = 360, y2 = 2.5;\n        function v2() {\n          return { type: \"MultiLineString\", coordinates: _2() };\n        }\n        function _2() {\n          return lt(Af(r2 / p2) * p2, e2, p2).map(s2).concat(lt(Af(u2 / g2) * g2, a2, g2).map(l2)).concat(lt(Af(n2 / h2) * h2, t2, h2).filter(function(t3) {\n            return xf(t3 % p2) > df;\n          }).map(c2)).concat(lt(Af(o2 / d2) * d2, i2, d2).filter(function(t3) {\n            return xf(t3 % g2) > df;\n          }).map(f2));\n        }\n        return v2.lines = function() {\n          return _2().map(function(t3) {\n            return { type: \"LineString\", coordinates: t3 };\n          });\n        }, v2.outline = function() {\n          return { type: \"Polygon\", coordinates: [s2(r2).concat(l2(a2).slice(1), s2(e2).reverse().slice(1), l2(u2).reverse().slice(1))] };\n        }, v2.extent = function(t3) {\n          return arguments.length ? v2.extentMajor(t3).extentMinor(t3) : v2.extentMinor();\n        }, v2.extentMajor = function(t3) {\n          return arguments.length ? (r2 = +t3[0][0], e2 = +t3[1][0], u2 = +t3[0][1], a2 = +t3[1][1], r2 > e2 && (t3 = r2, r2 = e2, e2 = t3), u2 > a2 && (t3 = u2, u2 = a2, a2 = t3), v2.precision(y2)) : [[r2, u2], [e2, a2]];\n        }, v2.extentMinor = function(e3) {\n          return arguments.length ? (n2 = +e3[0][0], t2 = +e3[1][0], o2 = +e3[0][1], i2 = +e3[1][1], n2 > t2 && (e3 = n2, n2 = t2, t2 = e3), o2 > i2 && (e3 = o2, o2 = i2, i2 = e3), v2.precision(y2)) : [[n2, o2], [t2, i2]];\n        }, v2.step = function(t3) {\n          return arguments.length ? v2.stepMajor(t3).stepMinor(t3) : v2.stepMinor();\n        }, v2.stepMajor = function(t3) {\n          return arguments.length ? (p2 = +t3[0], g2 = +t3[1], v2) : [p2, g2];\n        }, v2.stepMinor = function(t3) {\n          return arguments.length ? (h2 = +t3[0], d2 = +t3[1], v2) : [h2, d2];\n        }, v2.precision = function(h3) {\n          return arguments.length ? (y2 = +h3, c2 = Wl(o2, i2, 90), f2 = Zl(n2, t2, y2), s2 = Wl(u2, a2, 90), l2 = Zl(r2, e2, y2), v2) : y2;\n        }, v2.extentMajor([[-180, -90 + df], [180, 90 - df]]).extentMinor([[-180, -80 - df], [180, 80 + df]]);\n      }\n      var Ql, Jl, th, nh, eh = (t2) => t2, rh = new T(), ih = new T(), oh = { point: qf, lineStart: qf, lineEnd: qf, polygonStart: function() {\n        oh.lineStart = ah, oh.lineEnd = fh;\n      }, polygonEnd: function() {\n        oh.lineStart = oh.lineEnd = oh.point = qf, rh.add(xf(ih)), ih = new T();\n      }, result: function() {\n        var t2 = rh / 2;\n        return rh = new T(), t2;\n      } };\n      function ah() {\n        oh.point = uh;\n      }\n      function uh(t2, n2) {\n        oh.point = ch, Ql = th = t2, Jl = nh = n2;\n      }\n      function ch(t2, n2) {\n        ih.add(nh * t2 - th * n2), th = t2, nh = n2;\n      }\n      function fh() {\n        ch(Ql, Jl);\n      }\n      var sh = oh, lh = 1 / 0, hh = lh, dh = -lh, ph = dh, gh = { point: function(t2, n2) {\n        t2 < lh && (lh = t2);\n        t2 > dh && (dh = t2);\n        n2 < hh && (hh = n2);\n        n2 > ph && (ph = n2);\n      }, lineStart: qf, lineEnd: qf, polygonStart: qf, polygonEnd: qf, result: function() {\n        var t2 = [[lh, hh], [dh, ph]];\n        return dh = ph = -(hh = lh = 1 / 0), t2;\n      } };\n      var yh, vh, _h, bh, mh = gh, xh = 0, wh = 0, Mh = 0, Th = 0, Ah = 0, Sh = 0, Eh = 0, Nh = 0, kh = 0, Ch = { point: Ph, lineStart: zh, lineEnd: Rh, polygonStart: function() {\n        Ch.lineStart = Fh, Ch.lineEnd = qh;\n      }, polygonEnd: function() {\n        Ch.point = Ph, Ch.lineStart = zh, Ch.lineEnd = Rh;\n      }, result: function() {\n        var t2 = kh ? [Eh / kh, Nh / kh] : Sh ? [Th / Sh, Ah / Sh] : Mh ? [xh / Mh, wh / Mh] : [NaN, NaN];\n        return xh = wh = Mh = Th = Ah = Sh = Eh = Nh = kh = 0, t2;\n      } };\n      function Ph(t2, n2) {\n        xh += t2, wh += n2, ++Mh;\n      }\n      function zh() {\n        Ch.point = $h;\n      }\n      function $h(t2, n2) {\n        Ch.point = Dh, Ph(_h = t2, bh = n2);\n      }\n      function Dh(t2, n2) {\n        var e2 = t2 - _h, r2 = n2 - bh, i2 = zf(e2 * e2 + r2 * r2);\n        Th += i2 * (_h + t2) / 2, Ah += i2 * (bh + n2) / 2, Sh += i2, Ph(_h = t2, bh = n2);\n      }\n      function Rh() {\n        Ch.point = Ph;\n      }\n      function Fh() {\n        Ch.point = Uh;\n      }\n      function qh() {\n        Ih(yh, vh);\n      }\n      function Uh(t2, n2) {\n        Ch.point = Ih, Ph(yh = _h = t2, vh = bh = n2);\n      }\n      function Ih(t2, n2) {\n        var e2 = t2 - _h, r2 = n2 - bh, i2 = zf(e2 * e2 + r2 * r2);\n        Th += i2 * (_h + t2) / 2, Ah += i2 * (bh + n2) / 2, Sh += i2, Eh += (i2 = bh * t2 - _h * n2) * (_h + t2), Nh += i2 * (bh + n2), kh += 3 * i2, Ph(_h = t2, bh = n2);\n      }\n      var Oh = Ch;\n      function Bh(t2) {\n        this._context = t2;\n      }\n      Bh.prototype = { _radius: 4.5, pointRadius: function(t2) {\n        return this._radius = t2, this;\n      }, polygonStart: function() {\n        this._line = 0;\n      }, polygonEnd: function() {\n        this._line = NaN;\n      }, lineStart: function() {\n        this._point = 0;\n      }, lineEnd: function() {\n        0 === this._line && this._context.closePath(), this._point = NaN;\n      }, point: function(t2, n2) {\n        switch (this._point) {\n          case 0:\n            this._context.moveTo(t2, n2), this._point = 1;\n            break;\n          case 1:\n            this._context.lineTo(t2, n2);\n            break;\n          default:\n            this._context.moveTo(t2 + this._radius, n2), this._context.arc(t2, n2, this._radius, 0, _f);\n        }\n      }, result: qf };\n      var Yh, Lh, jh, Hh, Xh, Gh = new T(), Vh = { point: qf, lineStart: function() {\n        Vh.point = Wh;\n      }, lineEnd: function() {\n        Yh && Zh(Lh, jh), Vh.point = qf;\n      }, polygonStart: function() {\n        Yh = true;\n      }, polygonEnd: function() {\n        Yh = null;\n      }, result: function() {\n        var t2 = +Gh;\n        return Gh = new T(), t2;\n      } };\n      function Wh(t2, n2) {\n        Vh.point = Zh, Lh = Hh = t2, jh = Xh = n2;\n      }\n      function Zh(t2, n2) {\n        Hh -= t2, Xh -= n2, Gh.add(zf(Hh * Hh + Xh * Xh)), Hh = t2, Xh = n2;\n      }\n      var Kh = Vh;\n      let Qh, Jh, td, nd;\n      class ed {\n        constructor(t2) {\n          this._append = null == t2 ? rd : function(t3) {\n            const n2 = Math.floor(t3);\n            if (!(n2 >= 0))\n              throw new RangeError(`invalid digits: ${t3}`);\n            if (n2 > 15)\n              return rd;\n            if (n2 !== Qh) {\n              const t4 = 10 ** n2;\n              Qh = n2, Jh = function(n3) {\n                let e2 = 1;\n                this._ += n3[0];\n                for (const r2 = n3.length; e2 < r2; ++e2)\n                  this._ += Math.round(arguments[e2] * t4) / t4 + n3[e2];\n              };\n            }\n            return Jh;\n          }(t2), this._radius = 4.5, this._ = \"\";\n        }\n        pointRadius(t2) {\n          return this._radius = +t2, this;\n        }\n        polygonStart() {\n          this._line = 0;\n        }\n        polygonEnd() {\n          this._line = NaN;\n        }\n        lineStart() {\n          this._point = 0;\n        }\n        lineEnd() {\n          0 === this._line && (this._ += \"Z\"), this._point = NaN;\n        }\n        point(t2, n2) {\n          switch (this._point) {\n            case 0:\n              this._append`M${t2},${n2}`, this._point = 1;\n              break;\n            case 1:\n              this._append`L${t2},${n2}`;\n              break;\n            default:\n              if (this._append`M${t2},${n2}`, this._radius !== td || this._append !== Jh) {\n                const t3 = this._radius, n3 = this._;\n                this._ = \"\", this._append`m0,${t3}a${t3},${t3} 0 1,1 0,${-2 * t3}a${t3},${t3} 0 1,1 0,${2 * t3}z`, td = t3, Jh = this._append, nd = this._, this._ = n3;\n              }\n              this._ += nd;\n          }\n        }\n        result() {\n          const t2 = this._;\n          return this._ = \"\", t2.length ? t2 : null;\n        }\n      }\n      function rd(t2) {\n        let n2 = 1;\n        this._ += t2[0];\n        for (const e2 = t2.length; n2 < e2; ++n2)\n          this._ += arguments[n2] + t2[n2];\n      }\n      function id(t2) {\n        return function(n2) {\n          var e2 = new od();\n          for (var r2 in t2)\n            e2[r2] = t2[r2];\n          return e2.stream = n2, e2;\n        };\n      }\n      function od() {\n      }\n      function ad(t2, n2, e2) {\n        var r2 = t2.clipExtent && t2.clipExtent();\n        return t2.scale(150).translate([0, 0]), null != r2 && t2.clipExtent(null), Lf(e2, t2.stream(mh)), n2(mh.result()), null != r2 && t2.clipExtent(r2), t2;\n      }\n      function ud(t2, n2, e2) {\n        return ad(t2, function(e3) {\n          var r2 = n2[1][0] - n2[0][0], i2 = n2[1][1] - n2[0][1], o2 = Math.min(r2 / (e3[1][0] - e3[0][0]), i2 / (e3[1][1] - e3[0][1])), a2 = +n2[0][0] + (r2 - o2 * (e3[1][0] + e3[0][0])) / 2, u2 = +n2[0][1] + (i2 - o2 * (e3[1][1] + e3[0][1])) / 2;\n          t2.scale(150 * o2).translate([a2, u2]);\n        }, e2);\n      }\n      function cd(t2, n2, e2) {\n        return ud(t2, [[0, 0], n2], e2);\n      }\n      function fd(t2, n2, e2) {\n        return ad(t2, function(e3) {\n          var r2 = +n2, i2 = r2 / (e3[1][0] - e3[0][0]), o2 = (r2 - i2 * (e3[1][0] + e3[0][0])) / 2, a2 = -i2 * e3[0][1];\n          t2.scale(150 * i2).translate([o2, a2]);\n        }, e2);\n      }\n      function sd(t2, n2, e2) {\n        return ad(t2, function(e3) {\n          var r2 = +n2, i2 = r2 / (e3[1][1] - e3[0][1]), o2 = -i2 * e3[0][0], a2 = (r2 - i2 * (e3[1][1] + e3[0][1])) / 2;\n          t2.scale(150 * i2).translate([o2, a2]);\n        }, e2);\n      }\n      od.prototype = { constructor: od, point: function(t2, n2) {\n        this.stream.point(t2, n2);\n      }, sphere: function() {\n        this.stream.sphere();\n      }, lineStart: function() {\n        this.stream.lineStart();\n      }, lineEnd: function() {\n        this.stream.lineEnd();\n      }, polygonStart: function() {\n        this.stream.polygonStart();\n      }, polygonEnd: function() {\n        this.stream.polygonEnd();\n      } };\n      var ld = 16, hd = Tf(30 * mf);\n      function dd(t2, n2) {\n        return +n2 ? /* @__PURE__ */ function(t3, n3) {\n          function e2(r2, i2, o2, a2, u2, c2, f2, s2, l2, h2, d2, p2, g2, y2) {\n            var v2 = f2 - r2, _2 = s2 - i2, b2 = v2 * v2 + _2 * _2;\n            if (b2 > 4 * n3 && g2--) {\n              var m2 = a2 + h2, x2 = u2 + d2, w2 = c2 + p2, M2 = zf(m2 * m2 + x2 * x2 + w2 * w2), T2 = Rf(w2 /= M2), A2 = xf(xf(w2) - 1) < df || xf(o2 - l2) < df ? (o2 + l2) / 2 : Mf(x2, m2), S2 = t3(A2, T2), E2 = S2[0], N2 = S2[1], k2 = E2 - r2, C2 = N2 - i2, P2 = _2 * k2 - v2 * C2;\n              (P2 * P2 / b2 > n3 || xf((v2 * k2 + _2 * C2) / b2 - 0.5) > 0.3 || a2 * h2 + u2 * d2 + c2 * p2 < hd) && (e2(r2, i2, o2, a2, u2, c2, E2, N2, A2, m2 /= M2, x2 /= M2, w2, g2, y2), y2.point(E2, N2), e2(E2, N2, A2, m2, x2, w2, f2, s2, l2, h2, d2, p2, g2, y2));\n            }\n          }\n          return function(n4) {\n            var r2, i2, o2, a2, u2, c2, f2, s2, l2, h2, d2, p2, g2 = { point: y2, lineStart: v2, lineEnd: b2, polygonStart: function() {\n              n4.polygonStart(), g2.lineStart = m2;\n            }, polygonEnd: function() {\n              n4.polygonEnd(), g2.lineStart = v2;\n            } };\n            function y2(e3, r3) {\n              e3 = t3(e3, r3), n4.point(e3[0], e3[1]);\n            }\n            function v2() {\n              s2 = NaN, g2.point = _2, n4.lineStart();\n            }\n            function _2(r3, i3) {\n              var o3 = ps([r3, i3]), a3 = t3(r3, i3);\n              e2(s2, l2, f2, h2, d2, p2, s2 = a3[0], l2 = a3[1], f2 = r3, h2 = o3[0], d2 = o3[1], p2 = o3[2], ld, n4), n4.point(s2, l2);\n            }\n            function b2() {\n              g2.point = y2, n4.lineEnd();\n            }\n            function m2() {\n              v2(), g2.point = x2, g2.lineEnd = w2;\n            }\n            function x2(t4, n5) {\n              _2(r2 = t4, n5), i2 = s2, o2 = l2, a2 = h2, u2 = d2, c2 = p2, g2.point = _2;\n            }\n            function w2() {\n              e2(s2, l2, f2, h2, d2, p2, i2, o2, r2, a2, u2, c2, ld, n4), g2.lineEnd = b2, b2();\n            }\n            return g2;\n          };\n        }(t2, n2) : function(t3) {\n          return id({ point: function(n3, e2) {\n            n3 = t3(n3, e2), this.stream.point(n3[0], n3[1]);\n          } });\n        }(t2);\n      }\n      var pd = id({ point: function(t2, n2) {\n        this.stream.point(t2 * mf, n2 * mf);\n      } });\n      function gd(t2, n2, e2, r2, i2, o2) {\n        if (!o2)\n          return function(t3, n3, e3, r3, i3) {\n            function o3(o4, a3) {\n              return [n3 + t3 * (o4 *= r3), e3 - t3 * (a3 *= i3)];\n            }\n            return o3.invert = function(o4, a3) {\n              return [(o4 - n3) / t3 * r3, (e3 - a3) / t3 * i3];\n            }, o3;\n          }(t2, n2, e2, r2, i2);\n        var a2 = Tf(o2), u2 = Cf(o2), c2 = a2 * t2, f2 = u2 * t2, s2 = a2 / t2, l2 = u2 / t2, h2 = (u2 * e2 - a2 * n2) / t2, d2 = (u2 * n2 + a2 * e2) / t2;\n        function p2(t3, o3) {\n          return [c2 * (t3 *= r2) - f2 * (o3 *= i2) + n2, e2 - f2 * t3 - c2 * o3];\n        }\n        return p2.invert = function(t3, n3) {\n          return [r2 * (s2 * t3 - l2 * n3 + h2), i2 * (d2 - l2 * t3 - s2 * n3)];\n        }, p2;\n      }\n      function yd(t2) {\n        return vd(function() {\n          return t2;\n        })();\n      }\n      function vd(t2) {\n        var n2, e2, r2, i2, o2, a2, u2, c2, f2, s2, l2 = 150, h2 = 480, d2 = 250, p2 = 0, g2 = 0, y2 = 0, v2 = 0, _2 = 0, b2 = 0, m2 = 1, x2 = 1, w2 = null, M2 = Tl, T2 = null, A2 = eh, S2 = 0.5;\n        function E2(t3) {\n          return c2(t3[0] * mf, t3[1] * mf);\n        }\n        function N2(t3) {\n          return (t3 = c2.invert(t3[0], t3[1])) && [t3[0] * bf, t3[1] * bf];\n        }\n        function k2() {\n          var t3 = gd(l2, 0, 0, m2, x2, b2).apply(null, n2(p2, g2)), r3 = gd(l2, h2 - t3[0], d2 - t3[1], m2, x2, b2);\n          return e2 = ul(y2, v2, _2), u2 = ol(n2, r3), c2 = ol(e2, u2), a2 = dd(u2, S2), C2();\n        }\n        function C2() {\n          return f2 = s2 = null, E2;\n        }\n        return E2.stream = function(t3) {\n          return f2 && s2 === t3 ? f2 : f2 = pd(function(t4) {\n            return id({ point: function(n3, e3) {\n              var r3 = t4(n3, e3);\n              return this.stream.point(r3[0], r3[1]);\n            } });\n          }(e2)(M2(a2(A2(s2 = t3)))));\n        }, E2.preclip = function(t3) {\n          return arguments.length ? (M2 = t3, w2 = void 0, C2()) : M2;\n        }, E2.postclip = function(t3) {\n          return arguments.length ? (A2 = t3, T2 = r2 = i2 = o2 = null, C2()) : A2;\n        }, E2.clipAngle = function(t3) {\n          return arguments.length ? (M2 = +t3 ? Al(w2 = t3 * mf) : (w2 = null, Tl), C2()) : w2 * bf;\n        }, E2.clipExtent = function(t3) {\n          return arguments.length ? (A2 = null == t3 ? (T2 = r2 = i2 = o2 = null, eh) : zl(T2 = +t3[0][0], r2 = +t3[0][1], i2 = +t3[1][0], o2 = +t3[1][1]), C2()) : null == T2 ? null : [[T2, r2], [i2, o2]];\n        }, E2.scale = function(t3) {\n          return arguments.length ? (l2 = +t3, k2()) : l2;\n        }, E2.translate = function(t3) {\n          return arguments.length ? (h2 = +t3[0], d2 = +t3[1], k2()) : [h2, d2];\n        }, E2.center = function(t3) {\n          return arguments.length ? (p2 = t3[0] % 360 * mf, g2 = t3[1] % 360 * mf, k2()) : [p2 * bf, g2 * bf];\n        }, E2.rotate = function(t3) {\n          return arguments.length ? (y2 = t3[0] % 360 * mf, v2 = t3[1] % 360 * mf, _2 = t3.length > 2 ? t3[2] % 360 * mf : 0, k2()) : [y2 * bf, v2 * bf, _2 * bf];\n        }, E2.angle = function(t3) {\n          return arguments.length ? (b2 = t3 % 360 * mf, k2()) : b2 * bf;\n        }, E2.reflectX = function(t3) {\n          return arguments.length ? (m2 = t3 ? -1 : 1, k2()) : m2 < 0;\n        }, E2.reflectY = function(t3) {\n          return arguments.length ? (x2 = t3 ? -1 : 1, k2()) : x2 < 0;\n        }, E2.precision = function(t3) {\n          return arguments.length ? (a2 = dd(u2, S2 = t3 * t3), C2()) : zf(S2);\n        }, E2.fitExtent = function(t3, n3) {\n          return ud(E2, t3, n3);\n        }, E2.fitSize = function(t3, n3) {\n          return cd(E2, t3, n3);\n        }, E2.fitWidth = function(t3, n3) {\n          return fd(E2, t3, n3);\n        }, E2.fitHeight = function(t3, n3) {\n          return sd(E2, t3, n3);\n        }, function() {\n          return n2 = t2.apply(this, arguments), E2.invert = n2.invert && N2, k2();\n        };\n      }\n      function _d(t2) {\n        var n2 = 0, e2 = gf / 3, r2 = vd(t2), i2 = r2(n2, e2);\n        return i2.parallels = function(t3) {\n          return arguments.length ? r2(n2 = t3[0] * mf, e2 = t3[1] * mf) : [n2 * bf, e2 * bf];\n        }, i2;\n      }\n      function bd(t2, n2) {\n        var e2 = Cf(t2), r2 = (e2 + Cf(n2)) / 2;\n        if (xf(r2) < df)\n          return function(t3) {\n            var n3 = Tf(t3);\n            function e3(t4, e4) {\n              return [t4 * n3, Cf(e4) / n3];\n            }\n            return e3.invert = function(t4, e4) {\n              return [t4 / n3, Rf(e4 * n3)];\n            }, e3;\n          }(t2);\n        var i2 = 1 + e2 * (2 * r2 - e2), o2 = zf(i2) / r2;\n        function a2(t3, n3) {\n          var e3 = zf(i2 - 2 * r2 * Cf(n3)) / r2;\n          return [e3 * Cf(t3 *= r2), o2 - e3 * Tf(t3)];\n        }\n        return a2.invert = function(t3, n3) {\n          var e3 = o2 - n3, a3 = Mf(t3, xf(e3)) * Pf(e3);\n          return e3 * r2 < 0 && (a3 -= gf * Pf(t3) * Pf(e3)), [a3 / r2, Rf((i2 - (t3 * t3 + e3 * e3) * r2 * r2) / (2 * r2))];\n        }, a2;\n      }\n      function md() {\n        return _d(bd).scale(155.424).center([0, 33.6442]);\n      }\n      function xd() {\n        return md().parallels([29.5, 45.5]).scale(1070).translate([480, 250]).rotate([96, 0]).center([-0.6, 38.7]);\n      }\n      function wd(t2) {\n        return function(n2, e2) {\n          var r2 = Tf(n2), i2 = Tf(e2), o2 = t2(r2 * i2);\n          return o2 === 1 / 0 ? [2, 0] : [o2 * i2 * Cf(n2), o2 * Cf(e2)];\n        };\n      }\n      function Md(t2) {\n        return function(n2, e2) {\n          var r2 = zf(n2 * n2 + e2 * e2), i2 = t2(r2), o2 = Cf(i2), a2 = Tf(i2);\n          return [Mf(n2 * o2, r2 * a2), Rf(r2 && e2 * o2 / r2)];\n        };\n      }\n      var Td = wd(function(t2) {\n        return zf(2 / (1 + t2));\n      });\n      Td.invert = Md(function(t2) {\n        return 2 * Rf(t2 / 2);\n      });\n      var Ad = wd(function(t2) {\n        return (t2 = Df(t2)) && t2 / Cf(t2);\n      });\n      function Sd(t2, n2) {\n        return [t2, Nf($f((yf + n2) / 2))];\n      }\n      function Ed(t2) {\n        var n2, e2, r2, i2 = yd(t2), o2 = i2.center, a2 = i2.scale, u2 = i2.translate, c2 = i2.clipExtent, f2 = null;\n        function s2() {\n          var o3 = gf * a2(), u3 = i2(ll(i2.rotate()).invert([0, 0]));\n          return c2(null == f2 ? [[u3[0] - o3, u3[1] - o3], [u3[0] + o3, u3[1] + o3]] : t2 === Sd ? [[Math.max(u3[0] - o3, f2), n2], [Math.min(u3[0] + o3, e2), r2]] : [[f2, Math.max(u3[1] - o3, n2)], [e2, Math.min(u3[1] + o3, r2)]]);\n        }\n        return i2.scale = function(t3) {\n          return arguments.length ? (a2(t3), s2()) : a2();\n        }, i2.translate = function(t3) {\n          return arguments.length ? (u2(t3), s2()) : u2();\n        }, i2.center = function(t3) {\n          return arguments.length ? (o2(t3), s2()) : o2();\n        }, i2.clipExtent = function(t3) {\n          return arguments.length ? (null == t3 ? f2 = n2 = e2 = r2 = null : (f2 = +t3[0][0], n2 = +t3[0][1], e2 = +t3[1][0], r2 = +t3[1][1]), s2()) : null == f2 ? null : [[f2, n2], [e2, r2]];\n        }, s2();\n      }\n      function Nd(t2) {\n        return $f((yf + t2) / 2);\n      }\n      function kd(t2, n2) {\n        var e2 = Tf(t2), r2 = t2 === n2 ? Cf(t2) : Nf(e2 / Tf(n2)) / Nf(Nd(n2) / Nd(t2)), i2 = e2 * kf(Nd(t2), r2) / r2;\n        if (!r2)\n          return Sd;\n        function o2(t3, n3) {\n          i2 > 0 ? n3 < -yf + df && (n3 = -yf + df) : n3 > yf - df && (n3 = yf - df);\n          var e3 = i2 / kf(Nd(n3), r2);\n          return [e3 * Cf(r2 * t3), i2 - e3 * Tf(r2 * t3)];\n        }\n        return o2.invert = function(t3, n3) {\n          var e3 = i2 - n3, o3 = Pf(r2) * zf(t3 * t3 + e3 * e3), a2 = Mf(t3, xf(e3)) * Pf(e3);\n          return e3 * r2 < 0 && (a2 -= gf * Pf(t3) * Pf(e3)), [a2 / r2, 2 * wf(kf(i2 / o3, 1 / r2)) - yf];\n        }, o2;\n      }\n      function Cd(t2, n2) {\n        return [t2, n2];\n      }\n      function Pd(t2, n2) {\n        var e2 = Tf(t2), r2 = t2 === n2 ? Cf(t2) : (e2 - Tf(n2)) / (n2 - t2), i2 = e2 / r2 + t2;\n        if (xf(r2) < df)\n          return Cd;\n        function o2(t3, n3) {\n          var e3 = i2 - n3, o3 = r2 * t3;\n          return [e3 * Cf(o3), i2 - e3 * Tf(o3)];\n        }\n        return o2.invert = function(t3, n3) {\n          var e3 = i2 - n3, o3 = Mf(t3, xf(e3)) * Pf(e3);\n          return e3 * r2 < 0 && (o3 -= gf * Pf(t3) * Pf(e3)), [o3 / r2, i2 - Pf(r2) * zf(t3 * t3 + e3 * e3)];\n        }, o2;\n      }\n      Ad.invert = Md(function(t2) {\n        return t2;\n      }), Sd.invert = function(t2, n2) {\n        return [t2, 2 * wf(Sf(n2)) - yf];\n      }, Cd.invert = Cd;\n      var zd = 1.340264, $d = -0.081106, Dd = 893e-6, Rd = 3796e-6, Fd = zf(3) / 2;\n      function qd(t2, n2) {\n        var e2 = Rf(Fd * Cf(n2)), r2 = e2 * e2, i2 = r2 * r2 * r2;\n        return [t2 * Tf(e2) / (Fd * (zd + 3 * $d * r2 + i2 * (7 * Dd + 9 * Rd * r2))), e2 * (zd + $d * r2 + i2 * (Dd + Rd * r2))];\n      }\n      function Ud(t2, n2) {\n        var e2 = Tf(n2), r2 = Tf(t2) * e2;\n        return [e2 * Cf(t2) / r2, Cf(n2) / r2];\n      }\n      function Id(t2, n2) {\n        var e2 = n2 * n2, r2 = e2 * e2;\n        return [t2 * (0.8707 - 0.131979 * e2 + r2 * (r2 * (3971e-6 * e2 - 1529e-6 * r2) - 0.013791)), n2 * (1.007226 + e2 * (0.015085 + r2 * (0.028874 * e2 - 0.044475 - 5916e-6 * r2)))];\n      }\n      function Od(t2, n2) {\n        return [Tf(n2) * Cf(t2), Cf(n2)];\n      }\n      function Bd(t2, n2) {\n        var e2 = Tf(n2), r2 = 1 + Tf(t2) * e2;\n        return [e2 * Cf(t2) / r2, Cf(n2) / r2];\n      }\n      function Yd(t2, n2) {\n        return [Nf($f((yf + n2) / 2)), -t2];\n      }\n      function Ld(t2, n2) {\n        return t2.parent === n2.parent ? 1 : 2;\n      }\n      function jd(t2, n2) {\n        return t2 + n2.x;\n      }\n      function Hd(t2, n2) {\n        return Math.max(t2, n2.y);\n      }\n      function Xd(t2) {\n        var n2 = 0, e2 = t2.children, r2 = e2 && e2.length;\n        if (r2)\n          for (; --r2 >= 0; )\n            n2 += e2[r2].value;\n        else\n          n2 = 1;\n        t2.value = n2;\n      }\n      function Gd(t2, n2) {\n        t2 instanceof Map ? (t2 = [void 0, t2], void 0 === n2 && (n2 = Wd)) : void 0 === n2 && (n2 = Vd);\n        for (var e2, r2, i2, o2, a2, u2 = new Qd(t2), c2 = [u2]; e2 = c2.pop(); )\n          if ((i2 = n2(e2.data)) && (a2 = (i2 = Array.from(i2)).length))\n            for (e2.children = i2, o2 = a2 - 1; o2 >= 0; --o2)\n              c2.push(r2 = i2[o2] = new Qd(i2[o2])), r2.parent = e2, r2.depth = e2.depth + 1;\n        return u2.eachBefore(Kd);\n      }\n      function Vd(t2) {\n        return t2.children;\n      }\n      function Wd(t2) {\n        return Array.isArray(t2) ? t2[1] : null;\n      }\n      function Zd(t2) {\n        void 0 !== t2.data.value && (t2.value = t2.data.value), t2.data = t2.data.data;\n      }\n      function Kd(t2) {\n        var n2 = 0;\n        do {\n          t2.height = n2;\n        } while ((t2 = t2.parent) && t2.height < ++n2);\n      }\n      function Qd(t2) {\n        this.data = t2, this.depth = this.height = 0, this.parent = null;\n      }\n      function Jd(t2) {\n        return null == t2 ? null : tp(t2);\n      }\n      function tp(t2) {\n        if (\"function\" != typeof t2)\n          throw new Error();\n        return t2;\n      }\n      function np() {\n        return 0;\n      }\n      function ep(t2) {\n        return function() {\n          return t2;\n        };\n      }\n      qd.invert = function(t2, n2) {\n        for (var e2, r2 = n2, i2 = r2 * r2, o2 = i2 * i2 * i2, a2 = 0; a2 < 12 && (o2 = (i2 = (r2 -= e2 = (r2 * (zd + $d * i2 + o2 * (Dd + Rd * i2)) - n2) / (zd + 3 * $d * i2 + o2 * (7 * Dd + 9 * Rd * i2))) * r2) * i2 * i2, !(xf(e2) < pf)); ++a2)\n          ;\n        return [Fd * t2 * (zd + 3 * $d * i2 + o2 * (7 * Dd + 9 * Rd * i2)) / Tf(r2), Rf(Cf(r2) / Fd)];\n      }, Ud.invert = Md(wf), Id.invert = function(t2, n2) {\n        var e2, r2 = n2, i2 = 25;\n        do {\n          var o2 = r2 * r2, a2 = o2 * o2;\n          r2 -= e2 = (r2 * (1.007226 + o2 * (0.015085 + a2 * (0.028874 * o2 - 0.044475 - 5916e-6 * a2))) - n2) / (1.007226 + o2 * (0.045255 + a2 * (0.259866 * o2 - 0.311325 - 5916e-6 * 11 * a2)));\n        } while (xf(e2) > df && --i2 > 0);\n        return [t2 / (0.8707 + (o2 = r2 * r2) * (o2 * (o2 * o2 * o2 * (3971e-6 - 1529e-6 * o2) - 0.013791) - 0.131979)), r2];\n      }, Od.invert = Md(Rf), Bd.invert = Md(function(t2) {\n        return 2 * wf(t2);\n      }), Yd.invert = function(t2, n2) {\n        return [-n2, 2 * wf(Sf(t2)) - yf];\n      }, Qd.prototype = Gd.prototype = { constructor: Qd, count: function() {\n        return this.eachAfter(Xd);\n      }, each: function(t2, n2) {\n        let e2 = -1;\n        for (const r2 of this)\n          t2.call(n2, r2, ++e2, this);\n        return this;\n      }, eachAfter: function(t2, n2) {\n        for (var e2, r2, i2, o2 = this, a2 = [o2], u2 = [], c2 = -1; o2 = a2.pop(); )\n          if (u2.push(o2), e2 = o2.children)\n            for (r2 = 0, i2 = e2.length; r2 < i2; ++r2)\n              a2.push(e2[r2]);\n        for (; o2 = u2.pop(); )\n          t2.call(n2, o2, ++c2, this);\n        return this;\n      }, eachBefore: function(t2, n2) {\n        for (var e2, r2, i2 = this, o2 = [i2], a2 = -1; i2 = o2.pop(); )\n          if (t2.call(n2, i2, ++a2, this), e2 = i2.children)\n            for (r2 = e2.length - 1; r2 >= 0; --r2)\n              o2.push(e2[r2]);\n        return this;\n      }, find: function(t2, n2) {\n        let e2 = -1;\n        for (const r2 of this)\n          if (t2.call(n2, r2, ++e2, this))\n            return r2;\n      }, sum: function(t2) {\n        return this.eachAfter(function(n2) {\n          for (var e2 = +t2(n2.data) || 0, r2 = n2.children, i2 = r2 && r2.length; --i2 >= 0; )\n            e2 += r2[i2].value;\n          n2.value = e2;\n        });\n      }, sort: function(t2) {\n        return this.eachBefore(function(n2) {\n          n2.children && n2.children.sort(t2);\n        });\n      }, path: function(t2) {\n        for (var n2 = this, e2 = function(t3, n3) {\n          if (t3 === n3)\n            return t3;\n          var e3 = t3.ancestors(), r3 = n3.ancestors(), i3 = null;\n          t3 = e3.pop(), n3 = r3.pop();\n          for (; t3 === n3; )\n            i3 = t3, t3 = e3.pop(), n3 = r3.pop();\n          return i3;\n        }(n2, t2), r2 = [n2]; n2 !== e2; )\n          n2 = n2.parent, r2.push(n2);\n        for (var i2 = r2.length; t2 !== e2; )\n          r2.splice(i2, 0, t2), t2 = t2.parent;\n        return r2;\n      }, ancestors: function() {\n        for (var t2 = this, n2 = [t2]; t2 = t2.parent; )\n          n2.push(t2);\n        return n2;\n      }, descendants: function() {\n        return Array.from(this);\n      }, leaves: function() {\n        var t2 = [];\n        return this.eachBefore(function(n2) {\n          n2.children || t2.push(n2);\n        }), t2;\n      }, links: function() {\n        var t2 = this, n2 = [];\n        return t2.each(function(e2) {\n          e2 !== t2 && n2.push({ source: e2.parent, target: e2 });\n        }), n2;\n      }, copy: function() {\n        return Gd(this).eachBefore(Zd);\n      }, [Symbol.iterator]: function* () {\n        var t2, n2, e2, r2, i2 = this, o2 = [i2];\n        do {\n          for (t2 = o2.reverse(), o2 = []; i2 = t2.pop(); )\n            if (yield i2, n2 = i2.children)\n              for (e2 = 0, r2 = n2.length; e2 < r2; ++e2)\n                o2.push(n2[e2]);\n        } while (o2.length);\n      } };\n      const rp = 1664525, ip = 1013904223, op = 4294967296;\n      function ap() {\n        let t2 = 1;\n        return () => (t2 = (rp * t2 + ip) % op) / op;\n      }\n      function up(t2, n2) {\n        for (var e2, r2, i2 = 0, o2 = (t2 = function(t3, n3) {\n          let e3, r3, i3 = t3.length;\n          for (; i3; )\n            r3 = n3() * i3-- | 0, e3 = t3[i3], t3[i3] = t3[r3], t3[r3] = e3;\n          return t3;\n        }(Array.from(t2), n2)).length, a2 = []; i2 < o2; )\n          e2 = t2[i2], r2 && sp(r2, e2) ? ++i2 : (r2 = hp(a2 = cp(a2, e2)), i2 = 0);\n        return r2;\n      }\n      function cp(t2, n2) {\n        var e2, r2;\n        if (lp(n2, t2))\n          return [n2];\n        for (e2 = 0; e2 < t2.length; ++e2)\n          if (fp(n2, t2[e2]) && lp(dp(t2[e2], n2), t2))\n            return [t2[e2], n2];\n        for (e2 = 0; e2 < t2.length - 1; ++e2)\n          for (r2 = e2 + 1; r2 < t2.length; ++r2)\n            if (fp(dp(t2[e2], t2[r2]), n2) && fp(dp(t2[e2], n2), t2[r2]) && fp(dp(t2[r2], n2), t2[e2]) && lp(pp(t2[e2], t2[r2], n2), t2))\n              return [t2[e2], t2[r2], n2];\n        throw new Error();\n      }\n      function fp(t2, n2) {\n        var e2 = t2.r - n2.r, r2 = n2.x - t2.x, i2 = n2.y - t2.y;\n        return e2 < 0 || e2 * e2 < r2 * r2 + i2 * i2;\n      }\n      function sp(t2, n2) {\n        var e2 = t2.r - n2.r + 1e-9 * Math.max(t2.r, n2.r, 1), r2 = n2.x - t2.x, i2 = n2.y - t2.y;\n        return e2 > 0 && e2 * e2 > r2 * r2 + i2 * i2;\n      }\n      function lp(t2, n2) {\n        for (var e2 = 0; e2 < n2.length; ++e2)\n          if (!sp(t2, n2[e2]))\n            return false;\n        return true;\n      }\n      function hp(t2) {\n        switch (t2.length) {\n          case 1:\n            return function(t3) {\n              return { x: t3.x, y: t3.y, r: t3.r };\n            }(t2[0]);\n          case 2:\n            return dp(t2[0], t2[1]);\n          case 3:\n            return pp(t2[0], t2[1], t2[2]);\n        }\n      }\n      function dp(t2, n2) {\n        var e2 = t2.x, r2 = t2.y, i2 = t2.r, o2 = n2.x, a2 = n2.y, u2 = n2.r, c2 = o2 - e2, f2 = a2 - r2, s2 = u2 - i2, l2 = Math.sqrt(c2 * c2 + f2 * f2);\n        return { x: (e2 + o2 + c2 / l2 * s2) / 2, y: (r2 + a2 + f2 / l2 * s2) / 2, r: (l2 + i2 + u2) / 2 };\n      }\n      function pp(t2, n2, e2) {\n        var r2 = t2.x, i2 = t2.y, o2 = t2.r, a2 = n2.x, u2 = n2.y, c2 = n2.r, f2 = e2.x, s2 = e2.y, l2 = e2.r, h2 = r2 - a2, d2 = r2 - f2, p2 = i2 - u2, g2 = i2 - s2, y2 = c2 - o2, v2 = l2 - o2, _2 = r2 * r2 + i2 * i2 - o2 * o2, b2 = _2 - a2 * a2 - u2 * u2 + c2 * c2, m2 = _2 - f2 * f2 - s2 * s2 + l2 * l2, x2 = d2 * p2 - h2 * g2, w2 = (p2 * m2 - g2 * b2) / (2 * x2) - r2, M2 = (g2 * y2 - p2 * v2) / x2, T2 = (d2 * b2 - h2 * m2) / (2 * x2) - i2, A2 = (h2 * v2 - d2 * y2) / x2, S2 = M2 * M2 + A2 * A2 - 1, E2 = 2 * (o2 + w2 * M2 + T2 * A2), N2 = w2 * w2 + T2 * T2 - o2 * o2, k2 = -(Math.abs(S2) > 1e-6 ? (E2 + Math.sqrt(E2 * E2 - 4 * S2 * N2)) / (2 * S2) : N2 / E2);\n        return { x: r2 + w2 + M2 * k2, y: i2 + T2 + A2 * k2, r: k2 };\n      }\n      function gp(t2, n2, e2) {\n        var r2, i2, o2, a2, u2 = t2.x - n2.x, c2 = t2.y - n2.y, f2 = u2 * u2 + c2 * c2;\n        f2 ? (i2 = n2.r + e2.r, i2 *= i2, a2 = t2.r + e2.r, i2 > (a2 *= a2) ? (r2 = (f2 + a2 - i2) / (2 * f2), o2 = Math.sqrt(Math.max(0, a2 / f2 - r2 * r2)), e2.x = t2.x - r2 * u2 - o2 * c2, e2.y = t2.y - r2 * c2 + o2 * u2) : (r2 = (f2 + i2 - a2) / (2 * f2), o2 = Math.sqrt(Math.max(0, i2 / f2 - r2 * r2)), e2.x = n2.x + r2 * u2 - o2 * c2, e2.y = n2.y + r2 * c2 + o2 * u2)) : (e2.x = n2.x + e2.r, e2.y = n2.y);\n      }\n      function yp(t2, n2) {\n        var e2 = t2.r + n2.r - 1e-6, r2 = n2.x - t2.x, i2 = n2.y - t2.y;\n        return e2 > 0 && e2 * e2 > r2 * r2 + i2 * i2;\n      }\n      function vp(t2) {\n        var n2 = t2._, e2 = t2.next._, r2 = n2.r + e2.r, i2 = (n2.x * e2.r + e2.x * n2.r) / r2, o2 = (n2.y * e2.r + e2.y * n2.r) / r2;\n        return i2 * i2 + o2 * o2;\n      }\n      function _p(t2) {\n        this._ = t2, this.next = null, this.previous = null;\n      }\n      function bp(t2, n2) {\n        if (!(o2 = (t2 = function(t3) {\n          return \"object\" == typeof t3 && \"length\" in t3 ? t3 : Array.from(t3);\n        }(t2)).length))\n          return 0;\n        var e2, r2, i2, o2, a2, u2, c2, f2, s2, l2, h2;\n        if ((e2 = t2[0]).x = 0, e2.y = 0, !(o2 > 1))\n          return e2.r;\n        if (r2 = t2[1], e2.x = -r2.r, r2.x = e2.r, r2.y = 0, !(o2 > 2))\n          return e2.r + r2.r;\n        gp(r2, e2, i2 = t2[2]), e2 = new _p(e2), r2 = new _p(r2), i2 = new _p(i2), e2.next = i2.previous = r2, r2.next = e2.previous = i2, i2.next = r2.previous = e2;\n        t:\n          for (c2 = 3; c2 < o2; ++c2) {\n            gp(e2._, r2._, i2 = t2[c2]), i2 = new _p(i2), f2 = r2.next, s2 = e2.previous, l2 = r2._.r, h2 = e2._.r;\n            do {\n              if (l2 <= h2) {\n                if (yp(f2._, i2._)) {\n                  r2 = f2, e2.next = r2, r2.previous = e2, --c2;\n                  continue t;\n                }\n                l2 += f2._.r, f2 = f2.next;\n              } else {\n                if (yp(s2._, i2._)) {\n                  (e2 = s2).next = r2, r2.previous = e2, --c2;\n                  continue t;\n                }\n                h2 += s2._.r, s2 = s2.previous;\n              }\n            } while (f2 !== s2.next);\n            for (i2.previous = e2, i2.next = r2, e2.next = r2.previous = r2 = i2, a2 = vp(e2); (i2 = i2.next) !== r2; )\n              (u2 = vp(i2)) < a2 && (e2 = i2, a2 = u2);\n            r2 = e2.next;\n          }\n        for (e2 = [r2._], i2 = r2; (i2 = i2.next) !== r2; )\n          e2.push(i2._);\n        for (i2 = up(e2, n2), c2 = 0; c2 < o2; ++c2)\n          (e2 = t2[c2]).x -= i2.x, e2.y -= i2.y;\n        return i2.r;\n      }\n      function mp(t2) {\n        return Math.sqrt(t2.value);\n      }\n      function xp(t2) {\n        return function(n2) {\n          n2.children || (n2.r = Math.max(0, +t2(n2) || 0));\n        };\n      }\n      function wp(t2, n2, e2) {\n        return function(r2) {\n          if (i2 = r2.children) {\n            var i2, o2, a2, u2 = i2.length, c2 = t2(r2) * n2 || 0;\n            if (c2)\n              for (o2 = 0; o2 < u2; ++o2)\n                i2[o2].r += c2;\n            if (a2 = bp(i2, e2), c2)\n              for (o2 = 0; o2 < u2; ++o2)\n                i2[o2].r -= c2;\n            r2.r = a2 + c2;\n          }\n        };\n      }\n      function Mp(t2) {\n        return function(n2) {\n          var e2 = n2.parent;\n          n2.r *= t2, e2 && (n2.x = e2.x + t2 * n2.x, n2.y = e2.y + t2 * n2.y);\n        };\n      }\n      function Tp(t2) {\n        t2.x0 = Math.round(t2.x0), t2.y0 = Math.round(t2.y0), t2.x1 = Math.round(t2.x1), t2.y1 = Math.round(t2.y1);\n      }\n      function Ap(t2, n2, e2, r2, i2) {\n        for (var o2, a2 = t2.children, u2 = -1, c2 = a2.length, f2 = t2.value && (r2 - n2) / t2.value; ++u2 < c2; )\n          (o2 = a2[u2]).y0 = e2, o2.y1 = i2, o2.x0 = n2, o2.x1 = n2 += o2.value * f2;\n      }\n      var Sp = { depth: -1 }, Ep = {}, Np = {};\n      function kp(t2) {\n        return t2.id;\n      }\n      function Cp(t2) {\n        return t2.parentId;\n      }\n      function Pp(t2) {\n        let n2 = t2.length;\n        if (n2 < 2)\n          return \"\";\n        for (; --n2 > 1 && !zp(t2, n2); )\n          ;\n        return t2.slice(0, n2);\n      }\n      function zp(t2, n2) {\n        if (\"/\" === t2[n2]) {\n          let e2 = 0;\n          for (; n2 > 0 && \"\\\\\" === t2[--n2]; )\n            ++e2;\n          if (0 == (1 & e2))\n            return true;\n        }\n        return false;\n      }\n      function $p(t2, n2) {\n        return t2.parent === n2.parent ? 1 : 2;\n      }\n      function Dp(t2) {\n        var n2 = t2.children;\n        return n2 ? n2[0] : t2.t;\n      }\n      function Rp(t2) {\n        var n2 = t2.children;\n        return n2 ? n2[n2.length - 1] : t2.t;\n      }\n      function Fp(t2, n2, e2) {\n        var r2 = e2 / (n2.i - t2.i);\n        n2.c -= r2, n2.s += e2, t2.c += r2, n2.z += e2, n2.m += e2;\n      }\n      function qp(t2, n2, e2) {\n        return t2.a.parent === n2.parent ? t2.a : e2;\n      }\n      function Up(t2, n2) {\n        this._ = t2, this.parent = null, this.children = null, this.A = null, this.a = this, this.z = 0, this.m = 0, this.c = 0, this.s = 0, this.t = null, this.i = n2;\n      }\n      function Ip(t2, n2, e2, r2, i2) {\n        for (var o2, a2 = t2.children, u2 = -1, c2 = a2.length, f2 = t2.value && (i2 - e2) / t2.value; ++u2 < c2; )\n          (o2 = a2[u2]).x0 = n2, o2.x1 = r2, o2.y0 = e2, o2.y1 = e2 += o2.value * f2;\n      }\n      Up.prototype = Object.create(Qd.prototype);\n      var Op = (1 + Math.sqrt(5)) / 2;\n      function Bp(t2, n2, e2, r2, i2, o2) {\n        for (var a2, u2, c2, f2, s2, l2, h2, d2, p2, g2, y2, v2 = [], _2 = n2.children, b2 = 0, m2 = 0, x2 = _2.length, w2 = n2.value; b2 < x2; ) {\n          c2 = i2 - e2, f2 = o2 - r2;\n          do {\n            s2 = _2[m2++].value;\n          } while (!s2 && m2 < x2);\n          for (l2 = h2 = s2, y2 = s2 * s2 * (g2 = Math.max(f2 / c2, c2 / f2) / (w2 * t2)), p2 = Math.max(h2 / y2, y2 / l2); m2 < x2; ++m2) {\n            if (s2 += u2 = _2[m2].value, u2 < l2 && (l2 = u2), u2 > h2 && (h2 = u2), y2 = s2 * s2 * g2, (d2 = Math.max(h2 / y2, y2 / l2)) > p2) {\n              s2 -= u2;\n              break;\n            }\n            p2 = d2;\n          }\n          v2.push(a2 = { value: s2, dice: c2 < f2, children: _2.slice(b2, m2) }), a2.dice ? Ap(a2, e2, r2, i2, w2 ? r2 += f2 * s2 / w2 : o2) : Ip(a2, e2, r2, w2 ? e2 += c2 * s2 / w2 : i2, o2), w2 -= s2, b2 = m2;\n        }\n        return v2;\n      }\n      var Yp = function t2(n2) {\n        function e2(t3, e3, r2, i2, o2) {\n          Bp(n2, t3, e3, r2, i2, o2);\n        }\n        return e2.ratio = function(n3) {\n          return t2((n3 = +n3) > 1 ? n3 : 1);\n        }, e2;\n      }(Op);\n      var Lp = function t2(n2) {\n        function e2(t3, e3, r2, i2, o2) {\n          if ((a2 = t3._squarify) && a2.ratio === n2)\n            for (var a2, u2, c2, f2, s2, l2 = -1, h2 = a2.length, d2 = t3.value; ++l2 < h2; ) {\n              for (c2 = (u2 = a2[l2]).children, f2 = u2.value = 0, s2 = c2.length; f2 < s2; ++f2)\n                u2.value += c2[f2].value;\n              u2.dice ? Ap(u2, e3, r2, i2, d2 ? r2 += (o2 - r2) * u2.value / d2 : o2) : Ip(u2, e3, r2, d2 ? e3 += (i2 - e3) * u2.value / d2 : i2, o2), d2 -= u2.value;\n            }\n          else\n            t3._squarify = a2 = Bp(n2, t3, e3, r2, i2, o2), a2.ratio = n2;\n        }\n        return e2.ratio = function(n3) {\n          return t2((n3 = +n3) > 1 ? n3 : 1);\n        }, e2;\n      }(Op);\n      function jp(t2, n2, e2) {\n        return (n2[0] - t2[0]) * (e2[1] - t2[1]) - (n2[1] - t2[1]) * (e2[0] - t2[0]);\n      }\n      function Hp(t2, n2) {\n        return t2[0] - n2[0] || t2[1] - n2[1];\n      }\n      function Xp(t2) {\n        const n2 = t2.length, e2 = [0, 1];\n        let r2, i2 = 2;\n        for (r2 = 2; r2 < n2; ++r2) {\n          for (; i2 > 1 && jp(t2[e2[i2 - 2]], t2[e2[i2 - 1]], t2[r2]) <= 0; )\n            --i2;\n          e2[i2++] = r2;\n        }\n        return e2.slice(0, i2);\n      }\n      var Gp = Math.random, Vp = function t2(n2) {\n        function e2(t3, e3) {\n          return t3 = null == t3 ? 0 : +t3, e3 = null == e3 ? 1 : +e3, 1 === arguments.length ? (e3 = t3, t3 = 0) : e3 -= t3, function() {\n            return n2() * e3 + t3;\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), Wp = function t2(n2) {\n        function e2(t3, e3) {\n          return arguments.length < 2 && (e3 = t3, t3 = 0), t3 = Math.floor(t3), e3 = Math.floor(e3) - t3, function() {\n            return Math.floor(n2() * e3 + t3);\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), Zp = function t2(n2) {\n        function e2(t3, e3) {\n          var r2, i2;\n          return t3 = null == t3 ? 0 : +t3, e3 = null == e3 ? 1 : +e3, function() {\n            var o2;\n            if (null != r2)\n              o2 = r2, r2 = null;\n            else\n              do {\n                r2 = 2 * n2() - 1, o2 = 2 * n2() - 1, i2 = r2 * r2 + o2 * o2;\n              } while (!i2 || i2 > 1);\n            return t3 + e3 * o2 * Math.sqrt(-2 * Math.log(i2) / i2);\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), Kp = function t2(n2) {\n        var e2 = Zp.source(n2);\n        function r2() {\n          var t3 = e2.apply(this, arguments);\n          return function() {\n            return Math.exp(t3());\n          };\n        }\n        return r2.source = t2, r2;\n      }(Gp), Qp = function t2(n2) {\n        function e2(t3) {\n          return (t3 = +t3) <= 0 ? () => 0 : function() {\n            for (var e3 = 0, r2 = t3; r2 > 1; --r2)\n              e3 += n2();\n            return e3 + r2 * n2();\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), Jp = function t2(n2) {\n        var e2 = Qp.source(n2);\n        function r2(t3) {\n          if (0 == (t3 = +t3))\n            return n2;\n          var r3 = e2(t3);\n          return function() {\n            return r3() / t3;\n          };\n        }\n        return r2.source = t2, r2;\n      }(Gp), tg = function t2(n2) {\n        function e2(t3) {\n          return function() {\n            return -Math.log1p(-n2()) / t3;\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), ng = function t2(n2) {\n        function e2(t3) {\n          if ((t3 = +t3) < 0)\n            throw new RangeError(\"invalid alpha\");\n          return t3 = 1 / -t3, function() {\n            return Math.pow(1 - n2(), t3);\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), eg = function t2(n2) {\n        function e2(t3) {\n          if ((t3 = +t3) < 0 || t3 > 1)\n            throw new RangeError(\"invalid p\");\n          return function() {\n            return Math.floor(n2() + t3);\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), rg = function t2(n2) {\n        function e2(t3) {\n          if ((t3 = +t3) < 0 || t3 > 1)\n            throw new RangeError(\"invalid p\");\n          return 0 === t3 ? () => 1 / 0 : 1 === t3 ? () => 1 : (t3 = Math.log1p(-t3), function() {\n            return 1 + Math.floor(Math.log1p(-n2()) / t3);\n          });\n        }\n        return e2.source = t2, e2;\n      }(Gp), ig = function t2(n2) {\n        var e2 = Zp.source(n2)();\n        function r2(t3, r3) {\n          if ((t3 = +t3) < 0)\n            throw new RangeError(\"invalid k\");\n          if (0 === t3)\n            return () => 0;\n          if (r3 = null == r3 ? 1 : +r3, 1 === t3)\n            return () => -Math.log1p(-n2()) * r3;\n          var i2 = (t3 < 1 ? t3 + 1 : t3) - 1 / 3, o2 = 1 / (3 * Math.sqrt(i2)), a2 = t3 < 1 ? () => Math.pow(n2(), 1 / t3) : () => 1;\n          return function() {\n            do {\n              do {\n                var t4 = e2(), u2 = 1 + o2 * t4;\n              } while (u2 <= 0);\n              u2 *= u2 * u2;\n              var c2 = 1 - n2();\n            } while (c2 >= 1 - 0.0331 * t4 * t4 * t4 * t4 && Math.log(c2) >= 0.5 * t4 * t4 + i2 * (1 - u2 + Math.log(u2)));\n            return i2 * u2 * a2() * r3;\n          };\n        }\n        return r2.source = t2, r2;\n      }(Gp), og = function t2(n2) {\n        var e2 = ig.source(n2);\n        function r2(t3, n3) {\n          var r3 = e2(t3), i2 = e2(n3);\n          return function() {\n            var t4 = r3();\n            return 0 === t4 ? 0 : t4 / (t4 + i2());\n          };\n        }\n        return r2.source = t2, r2;\n      }(Gp), ag = function t2(n2) {\n        var e2 = rg.source(n2), r2 = og.source(n2);\n        function i2(t3, n3) {\n          return t3 = +t3, (n3 = +n3) >= 1 ? () => t3 : n3 <= 0 ? () => 0 : function() {\n            for (var i3 = 0, o2 = t3, a2 = n3; o2 * a2 > 16 && o2 * (1 - a2) > 16; ) {\n              var u2 = Math.floor((o2 + 1) * a2), c2 = r2(u2, o2 - u2 + 1)();\n              c2 <= a2 ? (i3 += u2, o2 -= u2, a2 = (a2 - c2) / (1 - c2)) : (o2 = u2 - 1, a2 /= c2);\n            }\n            for (var f2 = a2 < 0.5, s2 = e2(f2 ? a2 : 1 - a2), l2 = s2(), h2 = 0; l2 <= o2; ++h2)\n              l2 += s2();\n            return i3 + (f2 ? h2 : o2 - h2);\n          };\n        }\n        return i2.source = t2, i2;\n      }(Gp), ug = function t2(n2) {\n        function e2(t3, e3, r2) {\n          var i2;\n          return 0 == (t3 = +t3) ? i2 = (t4) => -Math.log(t4) : (t3 = 1 / t3, i2 = (n3) => Math.pow(n3, t3)), e3 = null == e3 ? 0 : +e3, r2 = null == r2 ? 1 : +r2, function() {\n            return e3 + r2 * i2(-Math.log1p(-n2()));\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), cg = function t2(n2) {\n        function e2(t3, e3) {\n          return t3 = null == t3 ? 0 : +t3, e3 = null == e3 ? 1 : +e3, function() {\n            return t3 + e3 * Math.tan(Math.PI * n2());\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), fg = function t2(n2) {\n        function e2(t3, e3) {\n          return t3 = null == t3 ? 0 : +t3, e3 = null == e3 ? 1 : +e3, function() {\n            var r2 = n2();\n            return t3 + e3 * Math.log(r2 / (1 - r2));\n          };\n        }\n        return e2.source = t2, e2;\n      }(Gp), sg = function t2(n2) {\n        var e2 = ig.source(n2), r2 = ag.source(n2);\n        function i2(t3) {\n          return function() {\n            for (var i3 = 0, o2 = t3; o2 > 16; ) {\n              var a2 = Math.floor(0.875 * o2), u2 = e2(a2)();\n              if (u2 > o2)\n                return i3 + r2(a2 - 1, o2 / u2)();\n              i3 += a2, o2 -= u2;\n            }\n            for (var c2 = -Math.log1p(-n2()), f2 = 0; c2 <= o2; ++f2)\n              c2 -= Math.log1p(-n2());\n            return i3 + f2;\n          };\n        }\n        return i2.source = t2, i2;\n      }(Gp);\n      const lg = 1 / 4294967296;\n      function hg(t2, n2) {\n        switch (arguments.length) {\n          case 0:\n            break;\n          case 1:\n            this.range(t2);\n            break;\n          default:\n            this.range(n2).domain(t2);\n        }\n        return this;\n      }\n      function dg(t2, n2) {\n        switch (arguments.length) {\n          case 0:\n            break;\n          case 1:\n            \"function\" == typeof t2 ? this.interpolator(t2) : this.range(t2);\n            break;\n          default:\n            this.domain(t2), \"function\" == typeof n2 ? this.interpolator(n2) : this.range(n2);\n        }\n        return this;\n      }\n      const pg = Symbol(\"implicit\");\n      function gg() {\n        var t2 = new InternMap(), n2 = [], e2 = [], r2 = pg;\n        function i2(i3) {\n          let o2 = t2.get(i3);\n          if (void 0 === o2) {\n            if (r2 !== pg)\n              return r2;\n            t2.set(i3, o2 = n2.push(i3) - 1);\n          }\n          return e2[o2 % e2.length];\n        }\n        return i2.domain = function(e3) {\n          if (!arguments.length)\n            return n2.slice();\n          n2 = [], t2 = new InternMap();\n          for (const r3 of e3)\n            t2.has(r3) || t2.set(r3, n2.push(r3) - 1);\n          return i2;\n        }, i2.range = function(t3) {\n          return arguments.length ? (e2 = Array.from(t3), i2) : e2.slice();\n        }, i2.unknown = function(t3) {\n          return arguments.length ? (r2 = t3, i2) : r2;\n        }, i2.copy = function() {\n          return gg(n2, e2).unknown(r2);\n        }, hg.apply(i2, arguments), i2;\n      }\n      function yg() {\n        var t2, n2, e2 = gg().unknown(void 0), r2 = e2.domain, i2 = e2.range, o2 = 0, a2 = 1, u2 = false, c2 = 0, f2 = 0, s2 = 0.5;\n        function l2() {\n          var e3 = r2().length, l3 = a2 < o2, h2 = l3 ? a2 : o2, d2 = l3 ? o2 : a2;\n          t2 = (d2 - h2) / Math.max(1, e3 - c2 + 2 * f2), u2 && (t2 = Math.floor(t2)), h2 += (d2 - h2 - t2 * (e3 - c2)) * s2, n2 = t2 * (1 - c2), u2 && (h2 = Math.round(h2), n2 = Math.round(n2));\n          var p2 = lt(e3).map(function(n3) {\n            return h2 + t2 * n3;\n          });\n          return i2(l3 ? p2.reverse() : p2);\n        }\n        return delete e2.unknown, e2.domain = function(t3) {\n          return arguments.length ? (r2(t3), l2()) : r2();\n        }, e2.range = function(t3) {\n          return arguments.length ? ([o2, a2] = t3, o2 = +o2, a2 = +a2, l2()) : [o2, a2];\n        }, e2.rangeRound = function(t3) {\n          return [o2, a2] = t3, o2 = +o2, a2 = +a2, u2 = true, l2();\n        }, e2.bandwidth = function() {\n          return n2;\n        }, e2.step = function() {\n          return t2;\n        }, e2.round = function(t3) {\n          return arguments.length ? (u2 = !!t3, l2()) : u2;\n        }, e2.padding = function(t3) {\n          return arguments.length ? (c2 = Math.min(1, f2 = +t3), l2()) : c2;\n        }, e2.paddingInner = function(t3) {\n          return arguments.length ? (c2 = Math.min(1, t3), l2()) : c2;\n        }, e2.paddingOuter = function(t3) {\n          return arguments.length ? (f2 = +t3, l2()) : f2;\n        }, e2.align = function(t3) {\n          return arguments.length ? (s2 = Math.max(0, Math.min(1, t3)), l2()) : s2;\n        }, e2.copy = function() {\n          return yg(r2(), [o2, a2]).round(u2).paddingInner(c2).paddingOuter(f2).align(s2);\n        }, hg.apply(l2(), arguments);\n      }\n      function vg(t2) {\n        var n2 = t2.copy;\n        return t2.padding = t2.paddingOuter, delete t2.paddingInner, delete t2.paddingOuter, t2.copy = function() {\n          return vg(n2());\n        }, t2;\n      }\n      function _g(t2) {\n        return +t2;\n      }\n      var bg = [0, 1];\n      function mg(t2) {\n        return t2;\n      }\n      function xg(t2, n2) {\n        return (n2 -= t2 = +t2) ? function(e2) {\n          return (e2 - t2) / n2;\n        } : /* @__PURE__ */ function(t3) {\n          return function() {\n            return t3;\n          };\n        }(isNaN(n2) ? NaN : 0.5);\n      }\n      function wg(t2, n2, e2) {\n        var r2 = t2[0], i2 = t2[1], o2 = n2[0], a2 = n2[1];\n        return i2 < r2 ? (r2 = xg(i2, r2), o2 = e2(a2, o2)) : (r2 = xg(r2, i2), o2 = e2(o2, a2)), function(t3) {\n          return o2(r2(t3));\n        };\n      }\n      function Mg(t2, n2, e2) {\n        var r2 = Math.min(t2.length, n2.length) - 1, i2 = new Array(r2), o2 = new Array(r2), a2 = -1;\n        for (t2[r2] < t2[0] && (t2 = t2.slice().reverse(), n2 = n2.slice().reverse()); ++a2 < r2; )\n          i2[a2] = xg(t2[a2], t2[a2 + 1]), o2[a2] = e2(n2[a2], n2[a2 + 1]);\n        return function(n3) {\n          var e3 = s(t2, n3, 1, r2) - 1;\n          return o2[e3](i2[e3](n3));\n        };\n      }\n      function Tg(t2, n2) {\n        return n2.domain(t2.domain()).range(t2.range()).interpolate(t2.interpolate()).clamp(t2.clamp()).unknown(t2.unknown());\n      }\n      function Ag() {\n        var t2, n2, e2, r2, i2, o2, a2 = bg, u2 = bg, c2 = Gr, f2 = mg;\n        function s2() {\n          var t3 = Math.min(a2.length, u2.length);\n          return f2 !== mg && (f2 = function(t4, n3) {\n            var e3;\n            return t4 > n3 && (e3 = t4, t4 = n3, n3 = e3), function(e4) {\n              return Math.max(t4, Math.min(n3, e4));\n            };\n          }(a2[0], a2[t3 - 1])), r2 = t3 > 2 ? Mg : wg, i2 = o2 = null, l2;\n        }\n        function l2(n3) {\n          return null == n3 || isNaN(n3 = +n3) ? e2 : (i2 || (i2 = r2(a2.map(t2), u2, c2)))(t2(f2(n3)));\n        }\n        return l2.invert = function(e3) {\n          return f2(n2((o2 || (o2 = r2(u2, a2.map(t2), Yr)))(e3)));\n        }, l2.domain = function(t3) {\n          return arguments.length ? (a2 = Array.from(t3, _g), s2()) : a2.slice();\n        }, l2.range = function(t3) {\n          return arguments.length ? (u2 = Array.from(t3), s2()) : u2.slice();\n        }, l2.rangeRound = function(t3) {\n          return u2 = Array.from(t3), c2 = Vr, s2();\n        }, l2.clamp = function(t3) {\n          return arguments.length ? (f2 = !!t3 || mg, s2()) : f2 !== mg;\n        }, l2.interpolate = function(t3) {\n          return arguments.length ? (c2 = t3, s2()) : c2;\n        }, l2.unknown = function(t3) {\n          return arguments.length ? (e2 = t3, l2) : e2;\n        }, function(e3, r3) {\n          return t2 = e3, n2 = r3, s2();\n        };\n      }\n      function Sg() {\n        return Ag()(mg, mg);\n      }\n      function Eg(n2, e2, r2, i2) {\n        var o2, a2 = W(n2, e2, r2);\n        switch ((i2 = Jc(null == i2 ? \",f\" : i2)).type) {\n          case \"s\":\n            var u2 = Math.max(Math.abs(n2), Math.abs(e2));\n            return null != i2.precision || isNaN(o2 = lf(a2, u2)) || (i2.precision = o2), t.formatPrefix(i2, u2);\n          case \"\":\n          case \"e\":\n          case \"g\":\n          case \"p\":\n          case \"r\":\n            null != i2.precision || isNaN(o2 = hf(a2, Math.max(Math.abs(n2), Math.abs(e2)))) || (i2.precision = o2 - (\"e\" === i2.type));\n            break;\n          case \"f\":\n          case \"%\":\n            null != i2.precision || isNaN(o2 = sf(a2)) || (i2.precision = o2 - 2 * (\"%\" === i2.type));\n        }\n        return t.format(i2);\n      }\n      function Ng(t2) {\n        var n2 = t2.domain;\n        return t2.ticks = function(t3) {\n          var e2 = n2();\n          return G(e2[0], e2[e2.length - 1], null == t3 ? 10 : t3);\n        }, t2.tickFormat = function(t3, e2) {\n          var r2 = n2();\n          return Eg(r2[0], r2[r2.length - 1], null == t3 ? 10 : t3, e2);\n        }, t2.nice = function(e2) {\n          null == e2 && (e2 = 10);\n          var r2, i2, o2 = n2(), a2 = 0, u2 = o2.length - 1, c2 = o2[a2], f2 = o2[u2], s2 = 10;\n          for (f2 < c2 && (i2 = c2, c2 = f2, f2 = i2, i2 = a2, a2 = u2, u2 = i2); s2-- > 0; ) {\n            if ((i2 = V(c2, f2, e2)) === r2)\n              return o2[a2] = c2, o2[u2] = f2, n2(o2);\n            if (i2 > 0)\n              c2 = Math.floor(c2 / i2) * i2, f2 = Math.ceil(f2 / i2) * i2;\n            else {\n              if (!(i2 < 0))\n                break;\n              c2 = Math.ceil(c2 * i2) / i2, f2 = Math.floor(f2 * i2) / i2;\n            }\n            r2 = i2;\n          }\n          return t2;\n        }, t2;\n      }\n      function kg(t2, n2) {\n        var e2, r2 = 0, i2 = (t2 = t2.slice()).length - 1, o2 = t2[r2], a2 = t2[i2];\n        return a2 < o2 && (e2 = r2, r2 = i2, i2 = e2, e2 = o2, o2 = a2, a2 = e2), t2[r2] = n2.floor(o2), t2[i2] = n2.ceil(a2), t2;\n      }\n      function Cg(t2) {\n        return Math.log(t2);\n      }\n      function Pg(t2) {\n        return Math.exp(t2);\n      }\n      function zg(t2) {\n        return -Math.log(-t2);\n      }\n      function $g(t2) {\n        return -Math.exp(-t2);\n      }\n      function Dg(t2) {\n        return isFinite(t2) ? +(\"1e\" + t2) : t2 < 0 ? 0 : t2;\n      }\n      function Rg(t2) {\n        return (n2, e2) => -t2(-n2, e2);\n      }\n      function Fg(n2) {\n        const e2 = n2(Cg, Pg), r2 = e2.domain;\n        let i2, o2, a2 = 10;\n        function u2() {\n          return i2 = function(t2) {\n            return t2 === Math.E ? Math.log : 10 === t2 && Math.log10 || 2 === t2 && Math.log2 || (t2 = Math.log(t2), (n3) => Math.log(n3) / t2);\n          }(a2), o2 = /* @__PURE__ */ function(t2) {\n            return 10 === t2 ? Dg : t2 === Math.E ? Math.exp : (n3) => Math.pow(t2, n3);\n          }(a2), r2()[0] < 0 ? (i2 = Rg(i2), o2 = Rg(o2), n2(zg, $g)) : n2(Cg, Pg), e2;\n        }\n        return e2.base = function(t2) {\n          return arguments.length ? (a2 = +t2, u2()) : a2;\n        }, e2.domain = function(t2) {\n          return arguments.length ? (r2(t2), u2()) : r2();\n        }, e2.ticks = (t2) => {\n          const n3 = r2();\n          let e3 = n3[0], u3 = n3[n3.length - 1];\n          const c2 = u3 < e3;\n          c2 && ([e3, u3] = [u3, e3]);\n          let f2, s2, l2 = i2(e3), h2 = i2(u3);\n          const d2 = null == t2 ? 10 : +t2;\n          let p2 = [];\n          if (!(a2 % 1) && h2 - l2 < d2) {\n            if (l2 = Math.floor(l2), h2 = Math.ceil(h2), e3 > 0) {\n              for (; l2 <= h2; ++l2)\n                for (f2 = 1; f2 < a2; ++f2)\n                  if (s2 = l2 < 0 ? f2 / o2(-l2) : f2 * o2(l2), !(s2 < e3)) {\n                    if (s2 > u3)\n                      break;\n                    p2.push(s2);\n                  }\n            } else\n              for (; l2 <= h2; ++l2)\n                for (f2 = a2 - 1; f2 >= 1; --f2)\n                  if (s2 = l2 > 0 ? f2 / o2(-l2) : f2 * o2(l2), !(s2 < e3)) {\n                    if (s2 > u3)\n                      break;\n                    p2.push(s2);\n                  }\n            2 * p2.length < d2 && (p2 = G(e3, u3, d2));\n          } else\n            p2 = G(l2, h2, Math.min(h2 - l2, d2)).map(o2);\n          return c2 ? p2.reverse() : p2;\n        }, e2.tickFormat = (n3, r3) => {\n          if (null == n3 && (n3 = 10), null == r3 && (r3 = 10 === a2 ? \"s\" : \",\"), \"function\" != typeof r3 && (a2 % 1 || null != (r3 = Jc(r3)).precision || (r3.trim = true), r3 = t.format(r3)), n3 === 1 / 0)\n            return r3;\n          const u3 = Math.max(1, a2 * n3 / e2.ticks().length);\n          return (t2) => {\n            let n4 = t2 / o2(Math.round(i2(t2)));\n            return n4 * a2 < a2 - 0.5 && (n4 *= a2), n4 <= u3 ? r3(t2) : \"\";\n          };\n        }, e2.nice = () => r2(kg(r2(), { floor: (t2) => o2(Math.floor(i2(t2))), ceil: (t2) => o2(Math.ceil(i2(t2))) })), e2;\n      }\n      function qg(t2) {\n        return function(n2) {\n          return Math.sign(n2) * Math.log1p(Math.abs(n2 / t2));\n        };\n      }\n      function Ug(t2) {\n        return function(n2) {\n          return Math.sign(n2) * Math.expm1(Math.abs(n2)) * t2;\n        };\n      }\n      function Ig(t2) {\n        var n2 = 1, e2 = t2(qg(n2), Ug(n2));\n        return e2.constant = function(e3) {\n          return arguments.length ? t2(qg(n2 = +e3), Ug(n2)) : n2;\n        }, Ng(e2);\n      }\n      function Og(t2) {\n        return function(n2) {\n          return n2 < 0 ? -Math.pow(-n2, t2) : Math.pow(n2, t2);\n        };\n      }\n      function Bg(t2) {\n        return t2 < 0 ? -Math.sqrt(-t2) : Math.sqrt(t2);\n      }\n      function Yg(t2) {\n        return t2 < 0 ? -t2 * t2 : t2 * t2;\n      }\n      function Lg(t2) {\n        var n2 = t2(mg, mg), e2 = 1;\n        return n2.exponent = function(n3) {\n          return arguments.length ? 1 === (e2 = +n3) ? t2(mg, mg) : 0.5 === e2 ? t2(Bg, Yg) : t2(Og(e2), Og(1 / e2)) : e2;\n        }, Ng(n2);\n      }\n      function jg() {\n        var t2 = Lg(Ag());\n        return t2.copy = function() {\n          return Tg(t2, jg()).exponent(t2.exponent());\n        }, hg.apply(t2, arguments), t2;\n      }\n      function Hg(t2) {\n        return Math.sign(t2) * t2 * t2;\n      }\n      const Xg = /* @__PURE__ */ new Date(), Gg = /* @__PURE__ */ new Date();\n      function Vg(t2, n2, e2, r2) {\n        function i2(n3) {\n          return t2(n3 = 0 === arguments.length ? /* @__PURE__ */ new Date() : /* @__PURE__ */ new Date(+n3)), n3;\n        }\n        return i2.floor = (n3) => (t2(n3 = /* @__PURE__ */ new Date(+n3)), n3), i2.ceil = (e3) => (t2(e3 = new Date(e3 - 1)), n2(e3, 1), t2(e3), e3), i2.round = (t3) => {\n          const n3 = i2(t3), e3 = i2.ceil(t3);\n          return t3 - n3 < e3 - t3 ? n3 : e3;\n        }, i2.offset = (t3, e3) => (n2(t3 = /* @__PURE__ */ new Date(+t3), null == e3 ? 1 : Math.floor(e3)), t3), i2.range = (e3, r3, o2) => {\n          const a2 = [];\n          if (e3 = i2.ceil(e3), o2 = null == o2 ? 1 : Math.floor(o2), !(e3 < r3 && o2 > 0))\n            return a2;\n          let u2;\n          do {\n            a2.push(u2 = /* @__PURE__ */ new Date(+e3)), n2(e3, o2), t2(e3);\n          } while (u2 < e3 && e3 < r3);\n          return a2;\n        }, i2.filter = (e3) => Vg((n3) => {\n          if (n3 >= n3)\n            for (; t2(n3), !e3(n3); )\n              n3.setTime(n3 - 1);\n        }, (t3, r3) => {\n          if (t3 >= t3)\n            if (r3 < 0)\n              for (; ++r3 <= 0; )\n                for (; n2(t3, -1), !e3(t3); )\n                  ;\n            else\n              for (; --r3 >= 0; )\n                for (; n2(t3, 1), !e3(t3); )\n                  ;\n        }), e2 && (i2.count = (n3, r3) => (Xg.setTime(+n3), Gg.setTime(+r3), t2(Xg), t2(Gg), Math.floor(e2(Xg, Gg))), i2.every = (t3) => (t3 = Math.floor(t3), isFinite(t3) && t3 > 0 ? t3 > 1 ? i2.filter(r2 ? (n3) => r2(n3) % t3 == 0 : (n3) => i2.count(0, n3) % t3 == 0) : i2 : null)), i2;\n      }\n      const Wg = Vg(() => {\n      }, (t2, n2) => {\n        t2.setTime(+t2 + n2);\n      }, (t2, n2) => n2 - t2);\n      Wg.every = (t2) => (t2 = Math.floor(t2), isFinite(t2) && t2 > 0 ? t2 > 1 ? Vg((n2) => {\n        n2.setTime(Math.floor(n2 / t2) * t2);\n      }, (n2, e2) => {\n        n2.setTime(+n2 + e2 * t2);\n      }, (n2, e2) => (e2 - n2) / t2) : Wg : null);\n      const Zg = Wg.range, Kg = 1e3, Qg = 6e4, Jg = 36e5, ty = 864e5, ny = 6048e5, ey = 2592e6, ry = 31536e6, iy = Vg((t2) => {\n        t2.setTime(t2 - t2.getMilliseconds());\n      }, (t2, n2) => {\n        t2.setTime(+t2 + n2 * Kg);\n      }, (t2, n2) => (n2 - t2) / Kg, (t2) => t2.getUTCSeconds()), oy = iy.range, ay = Vg((t2) => {\n        t2.setTime(t2 - t2.getMilliseconds() - t2.getSeconds() * Kg);\n      }, (t2, n2) => {\n        t2.setTime(+t2 + n2 * Qg);\n      }, (t2, n2) => (n2 - t2) / Qg, (t2) => t2.getMinutes()), uy = ay.range, cy = Vg((t2) => {\n        t2.setUTCSeconds(0, 0);\n      }, (t2, n2) => {\n        t2.setTime(+t2 + n2 * Qg);\n      }, (t2, n2) => (n2 - t2) / Qg, (t2) => t2.getUTCMinutes()), fy = cy.range, sy = Vg((t2) => {\n        t2.setTime(t2 - t2.getMilliseconds() - t2.getSeconds() * Kg - t2.getMinutes() * Qg);\n      }, (t2, n2) => {\n        t2.setTime(+t2 + n2 * Jg);\n      }, (t2, n2) => (n2 - t2) / Jg, (t2) => t2.getHours()), ly = sy.range, hy = Vg((t2) => {\n        t2.setUTCMinutes(0, 0, 0);\n      }, (t2, n2) => {\n        t2.setTime(+t2 + n2 * Jg);\n      }, (t2, n2) => (n2 - t2) / Jg, (t2) => t2.getUTCHours()), dy = hy.range, py = Vg((t2) => t2.setHours(0, 0, 0, 0), (t2, n2) => t2.setDate(t2.getDate() + n2), (t2, n2) => (n2 - t2 - (n2.getTimezoneOffset() - t2.getTimezoneOffset()) * Qg) / ty, (t2) => t2.getDate() - 1), gy = py.range, yy = Vg((t2) => {\n        t2.setUTCHours(0, 0, 0, 0);\n      }, (t2, n2) => {\n        t2.setUTCDate(t2.getUTCDate() + n2);\n      }, (t2, n2) => (n2 - t2) / ty, (t2) => t2.getUTCDate() - 1), vy = yy.range, _y = Vg((t2) => {\n        t2.setUTCHours(0, 0, 0, 0);\n      }, (t2, n2) => {\n        t2.setUTCDate(t2.getUTCDate() + n2);\n      }, (t2, n2) => (n2 - t2) / ty, (t2) => Math.floor(t2 / ty)), by = _y.range;\n      function my(t2) {\n        return Vg((n2) => {\n          n2.setDate(n2.getDate() - (n2.getDay() + 7 - t2) % 7), n2.setHours(0, 0, 0, 0);\n        }, (t3, n2) => {\n          t3.setDate(t3.getDate() + 7 * n2);\n        }, (t3, n2) => (n2 - t3 - (n2.getTimezoneOffset() - t3.getTimezoneOffset()) * Qg) / ny);\n      }\n      const xy = my(0), wy = my(1), My = my(2), Ty = my(3), Ay = my(4), Sy = my(5), Ey = my(6), Ny = xy.range, ky = wy.range, Cy = My.range, Py = Ty.range, zy = Ay.range, $y = Sy.range, Dy = Ey.range;\n      function Ry(t2) {\n        return Vg((n2) => {\n          n2.setUTCDate(n2.getUTCDate() - (n2.getUTCDay() + 7 - t2) % 7), n2.setUTCHours(0, 0, 0, 0);\n        }, (t3, n2) => {\n          t3.setUTCDate(t3.getUTCDate() + 7 * n2);\n        }, (t3, n2) => (n2 - t3) / ny);\n      }\n      const Fy = Ry(0), qy = Ry(1), Uy = Ry(2), Iy = Ry(3), Oy = Ry(4), By = Ry(5), Yy = Ry(6), Ly = Fy.range, jy = qy.range, Hy = Uy.range, Xy = Iy.range, Gy = Oy.range, Vy = By.range, Wy = Yy.range, Zy = Vg((t2) => {\n        t2.setDate(1), t2.setHours(0, 0, 0, 0);\n      }, (t2, n2) => {\n        t2.setMonth(t2.getMonth() + n2);\n      }, (t2, n2) => n2.getMonth() - t2.getMonth() + 12 * (n2.getFullYear() - t2.getFullYear()), (t2) => t2.getMonth()), Ky = Zy.range, Qy = Vg((t2) => {\n        t2.setUTCDate(1), t2.setUTCHours(0, 0, 0, 0);\n      }, (t2, n2) => {\n        t2.setUTCMonth(t2.getUTCMonth() + n2);\n      }, (t2, n2) => n2.getUTCMonth() - t2.getUTCMonth() + 12 * (n2.getUTCFullYear() - t2.getUTCFullYear()), (t2) => t2.getUTCMonth()), Jy = Qy.range, tv = Vg((t2) => {\n        t2.setMonth(0, 1), t2.setHours(0, 0, 0, 0);\n      }, (t2, n2) => {\n        t2.setFullYear(t2.getFullYear() + n2);\n      }, (t2, n2) => n2.getFullYear() - t2.getFullYear(), (t2) => t2.getFullYear());\n      tv.every = (t2) => isFinite(t2 = Math.floor(t2)) && t2 > 0 ? Vg((n2) => {\n        n2.setFullYear(Math.floor(n2.getFullYear() / t2) * t2), n2.setMonth(0, 1), n2.setHours(0, 0, 0, 0);\n      }, (n2, e2) => {\n        n2.setFullYear(n2.getFullYear() + e2 * t2);\n      }) : null;\n      const nv = tv.range, ev = Vg((t2) => {\n        t2.setUTCMonth(0, 1), t2.setUTCHours(0, 0, 0, 0);\n      }, (t2, n2) => {\n        t2.setUTCFullYear(t2.getUTCFullYear() + n2);\n      }, (t2, n2) => n2.getUTCFullYear() - t2.getUTCFullYear(), (t2) => t2.getUTCFullYear());\n      ev.every = (t2) => isFinite(t2 = Math.floor(t2)) && t2 > 0 ? Vg((n2) => {\n        n2.setUTCFullYear(Math.floor(n2.getUTCFullYear() / t2) * t2), n2.setUTCMonth(0, 1), n2.setUTCHours(0, 0, 0, 0);\n      }, (n2, e2) => {\n        n2.setUTCFullYear(n2.getUTCFullYear() + e2 * t2);\n      }) : null;\n      const rv = ev.range;\n      function iv(t2, n2, e2, i2, o2, a2) {\n        const u2 = [[iy, 1, Kg], [iy, 5, 5e3], [iy, 15, 15e3], [iy, 30, 3e4], [a2, 1, Qg], [a2, 5, 3e5], [a2, 15, 9e5], [a2, 30, 18e5], [o2, 1, Jg], [o2, 3, 108e5], [o2, 6, 216e5], [o2, 12, 432e5], [i2, 1, ty], [i2, 2, 1728e5], [e2, 1, ny], [n2, 1, ey], [n2, 3, 7776e6], [t2, 1, ry]];\n        function c2(n3, e3, i3) {\n          const o3 = Math.abs(e3 - n3) / i3, a3 = r(([, , t3]) => t3).right(u2, o3);\n          if (a3 === u2.length)\n            return t2.every(W(n3 / ry, e3 / ry, i3));\n          if (0 === a3)\n            return Wg.every(Math.max(W(n3, e3, i3), 1));\n          const [c3, f2] = u2[o3 / u2[a3 - 1][2] < u2[a3][2] / o3 ? a3 - 1 : a3];\n          return c3.every(f2);\n        }\n        return [function(t3, n3, e3) {\n          const r2 = n3 < t3;\n          r2 && ([t3, n3] = [n3, t3]);\n          const i3 = e3 && \"function\" == typeof e3.range ? e3 : c2(t3, n3, e3), o3 = i3 ? i3.range(t3, +n3 + 1) : [];\n          return r2 ? o3.reverse() : o3;\n        }, c2];\n      }\n      const [ov, av] = iv(ev, Qy, Fy, _y, hy, cy), [uv, cv] = iv(tv, Zy, xy, py, sy, ay);\n      function fv(t2) {\n        if (0 <= t2.y && t2.y < 100) {\n          var n2 = new Date(-1, t2.m, t2.d, t2.H, t2.M, t2.S, t2.L);\n          return n2.setFullYear(t2.y), n2;\n        }\n        return new Date(t2.y, t2.m, t2.d, t2.H, t2.M, t2.S, t2.L);\n      }\n      function sv(t2) {\n        if (0 <= t2.y && t2.y < 100) {\n          var n2 = new Date(Date.UTC(-1, t2.m, t2.d, t2.H, t2.M, t2.S, t2.L));\n          return n2.setUTCFullYear(t2.y), n2;\n        }\n        return new Date(Date.UTC(t2.y, t2.m, t2.d, t2.H, t2.M, t2.S, t2.L));\n      }\n      function lv(t2, n2, e2) {\n        return { y: t2, m: n2, d: e2, H: 0, M: 0, S: 0, L: 0 };\n      }\n      function hv(t2) {\n        var n2 = t2.dateTime, e2 = t2.date, r2 = t2.time, i2 = t2.periods, o2 = t2.days, a2 = t2.shortDays, u2 = t2.months, c2 = t2.shortMonths, f2 = mv(i2), s2 = xv(i2), l2 = mv(o2), h2 = xv(o2), d2 = mv(a2), p2 = xv(a2), g2 = mv(u2), y2 = xv(u2), v2 = mv(c2), _2 = xv(c2), b2 = { a: function(t3) {\n          return a2[t3.getDay()];\n        }, A: function(t3) {\n          return o2[t3.getDay()];\n        }, b: function(t3) {\n          return c2[t3.getMonth()];\n        }, B: function(t3) {\n          return u2[t3.getMonth()];\n        }, c: null, d: Yv, e: Yv, f: Gv, g: i_, G: a_, H: Lv, I: jv, j: Hv, L: Xv, m: Vv, M: Wv, p: function(t3) {\n          return i2[+(t3.getHours() >= 12)];\n        }, q: function(t3) {\n          return 1 + ~~(t3.getMonth() / 3);\n        }, Q: k_, s: C_, S: Zv, u: Kv, U: Qv, V: t_, w: n_, W: e_, x: null, X: null, y: r_, Y: o_, Z: u_, \"%\": N_ }, m2 = { a: function(t3) {\n          return a2[t3.getUTCDay()];\n        }, A: function(t3) {\n          return o2[t3.getUTCDay()];\n        }, b: function(t3) {\n          return c2[t3.getUTCMonth()];\n        }, B: function(t3) {\n          return u2[t3.getUTCMonth()];\n        }, c: null, d: c_, e: c_, f: d_, g: T_, G: S_, H: f_, I: s_, j: l_, L: h_, m: p_, M: g_, p: function(t3) {\n          return i2[+(t3.getUTCHours() >= 12)];\n        }, q: function(t3) {\n          return 1 + ~~(t3.getUTCMonth() / 3);\n        }, Q: k_, s: C_, S: y_, u: v_, U: __, V: m_, w: x_, W: w_, x: null, X: null, y: M_, Y: A_, Z: E_, \"%\": N_ }, x2 = { a: function(t3, n3, e3) {\n          var r3 = d2.exec(n3.slice(e3));\n          return r3 ? (t3.w = p2.get(r3[0].toLowerCase()), e3 + r3[0].length) : -1;\n        }, A: function(t3, n3, e3) {\n          var r3 = l2.exec(n3.slice(e3));\n          return r3 ? (t3.w = h2.get(r3[0].toLowerCase()), e3 + r3[0].length) : -1;\n        }, b: function(t3, n3, e3) {\n          var r3 = v2.exec(n3.slice(e3));\n          return r3 ? (t3.m = _2.get(r3[0].toLowerCase()), e3 + r3[0].length) : -1;\n        }, B: function(t3, n3, e3) {\n          var r3 = g2.exec(n3.slice(e3));\n          return r3 ? (t3.m = y2.get(r3[0].toLowerCase()), e3 + r3[0].length) : -1;\n        }, c: function(t3, e3, r3) {\n          return T2(t3, n2, e3, r3);\n        }, d: zv, e: zv, f: Uv, g: Nv, G: Ev, H: Dv, I: Dv, j: $v, L: qv, m: Pv, M: Rv, p: function(t3, n3, e3) {\n          var r3 = f2.exec(n3.slice(e3));\n          return r3 ? (t3.p = s2.get(r3[0].toLowerCase()), e3 + r3[0].length) : -1;\n        }, q: Cv, Q: Ov, s: Bv, S: Fv, u: Mv, U: Tv, V: Av, w: wv, W: Sv, x: function(t3, n3, r3) {\n          return T2(t3, e2, n3, r3);\n        }, X: function(t3, n3, e3) {\n          return T2(t3, r2, n3, e3);\n        }, y: Nv, Y: Ev, Z: kv, \"%\": Iv };\n        function w2(t3, n3) {\n          return function(e3) {\n            var r3, i3, o3, a3 = [], u3 = -1, c3 = 0, f3 = t3.length;\n            for (e3 instanceof Date || (e3 = /* @__PURE__ */ new Date(+e3)); ++u3 < f3; )\n              37 === t3.charCodeAt(u3) && (a3.push(t3.slice(c3, u3)), null != (i3 = pv[r3 = t3.charAt(++u3)]) ? r3 = t3.charAt(++u3) : i3 = \"e\" === r3 ? \" \" : \"0\", (o3 = n3[r3]) && (r3 = o3(e3, i3)), a3.push(r3), c3 = u3 + 1);\n            return a3.push(t3.slice(c3, u3)), a3.join(\"\");\n          };\n        }\n        function M2(t3, n3) {\n          return function(e3) {\n            var r3, i3, o3 = lv(1900, void 0, 1);\n            if (T2(o3, t3, e3 += \"\", 0) != e3.length)\n              return null;\n            if (\"Q\" in o3)\n              return new Date(o3.Q);\n            if (\"s\" in o3)\n              return new Date(1e3 * o3.s + (\"L\" in o3 ? o3.L : 0));\n            if (n3 && !(\"Z\" in o3) && (o3.Z = 0), \"p\" in o3 && (o3.H = o3.H % 12 + 12 * o3.p), void 0 === o3.m && (o3.m = \"q\" in o3 ? o3.q : 0), \"V\" in o3) {\n              if (o3.V < 1 || o3.V > 53)\n                return null;\n              \"w\" in o3 || (o3.w = 1), \"Z\" in o3 ? (i3 = (r3 = sv(lv(o3.y, 0, 1))).getUTCDay(), r3 = i3 > 4 || 0 === i3 ? qy.ceil(r3) : qy(r3), r3 = yy.offset(r3, 7 * (o3.V - 1)), o3.y = r3.getUTCFullYear(), o3.m = r3.getUTCMonth(), o3.d = r3.getUTCDate() + (o3.w + 6) % 7) : (i3 = (r3 = fv(lv(o3.y, 0, 1))).getDay(), r3 = i3 > 4 || 0 === i3 ? wy.ceil(r3) : wy(r3), r3 = py.offset(r3, 7 * (o3.V - 1)), o3.y = r3.getFullYear(), o3.m = r3.getMonth(), o3.d = r3.getDate() + (o3.w + 6) % 7);\n            } else\n              (\"W\" in o3 || \"U\" in o3) && (\"w\" in o3 || (o3.w = \"u\" in o3 ? o3.u % 7 : \"W\" in o3 ? 1 : 0), i3 = \"Z\" in o3 ? sv(lv(o3.y, 0, 1)).getUTCDay() : fv(lv(o3.y, 0, 1)).getDay(), o3.m = 0, o3.d = \"W\" in o3 ? (o3.w + 6) % 7 + 7 * o3.W - (i3 + 5) % 7 : o3.w + 7 * o3.U - (i3 + 6) % 7);\n            return \"Z\" in o3 ? (o3.H += o3.Z / 100 | 0, o3.M += o3.Z % 100, sv(o3)) : fv(o3);\n          };\n        }\n        function T2(t3, n3, e3, r3) {\n          for (var i3, o3, a3 = 0, u3 = n3.length, c3 = e3.length; a3 < u3; ) {\n            if (r3 >= c3)\n              return -1;\n            if (37 === (i3 = n3.charCodeAt(a3++))) {\n              if (i3 = n3.charAt(a3++), !(o3 = x2[i3 in pv ? n3.charAt(a3++) : i3]) || (r3 = o3(t3, e3, r3)) < 0)\n                return -1;\n            } else if (i3 != e3.charCodeAt(r3++))\n              return -1;\n          }\n          return r3;\n        }\n        return b2.x = w2(e2, b2), b2.X = w2(r2, b2), b2.c = w2(n2, b2), m2.x = w2(e2, m2), m2.X = w2(r2, m2), m2.c = w2(n2, m2), { format: function(t3) {\n          var n3 = w2(t3 += \"\", b2);\n          return n3.toString = function() {\n            return t3;\n          }, n3;\n        }, parse: function(t3) {\n          var n3 = M2(t3 += \"\", false);\n          return n3.toString = function() {\n            return t3;\n          }, n3;\n        }, utcFormat: function(t3) {\n          var n3 = w2(t3 += \"\", m2);\n          return n3.toString = function() {\n            return t3;\n          }, n3;\n        }, utcParse: function(t3) {\n          var n3 = M2(t3 += \"\", true);\n          return n3.toString = function() {\n            return t3;\n          }, n3;\n        } };\n      }\n      var dv, pv = { \"-\": \"\", _: \" \", 0: \"0\" }, gv = /^\\s*\\d+/, yv = /^%/, vv = /[\\\\^$*+?|[\\]().{}]/g;\n      function _v(t2, n2, e2) {\n        var r2 = t2 < 0 ? \"-\" : \"\", i2 = (r2 ? -t2 : t2) + \"\", o2 = i2.length;\n        return r2 + (o2 < e2 ? new Array(e2 - o2 + 1).join(n2) + i2 : i2);\n      }\n      function bv(t2) {\n        return t2.replace(vv, \"\\\\$&\");\n      }\n      function mv(t2) {\n        return new RegExp(\"^(?:\" + t2.map(bv).join(\"|\") + \")\", \"i\");\n      }\n      function xv(t2) {\n        return new Map(t2.map((t3, n2) => [t3.toLowerCase(), n2]));\n      }\n      function wv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 1));\n        return r2 ? (t2.w = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Mv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 1));\n        return r2 ? (t2.u = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Tv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.U = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Av(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.V = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Sv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.W = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Ev(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 4));\n        return r2 ? (t2.y = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Nv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.y = +r2[0] + (+r2[0] > 68 ? 1900 : 2e3), e2 + r2[0].length) : -1;\n      }\n      function kv(t2, n2, e2) {\n        var r2 = /^(Z)|([+-]\\d\\d)(?::?(\\d\\d))?/.exec(n2.slice(e2, e2 + 6));\n        return r2 ? (t2.Z = r2[1] ? 0 : -(r2[2] + (r2[3] || \"00\")), e2 + r2[0].length) : -1;\n      }\n      function Cv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 1));\n        return r2 ? (t2.q = 3 * r2[0] - 3, e2 + r2[0].length) : -1;\n      }\n      function Pv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.m = r2[0] - 1, e2 + r2[0].length) : -1;\n      }\n      function zv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.d = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function $v(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 3));\n        return r2 ? (t2.m = 0, t2.d = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Dv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.H = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Rv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.M = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Fv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 2));\n        return r2 ? (t2.S = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function qv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 3));\n        return r2 ? (t2.L = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Uv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2, e2 + 6));\n        return r2 ? (t2.L = Math.floor(r2[0] / 1e3), e2 + r2[0].length) : -1;\n      }\n      function Iv(t2, n2, e2) {\n        var r2 = yv.exec(n2.slice(e2, e2 + 1));\n        return r2 ? e2 + r2[0].length : -1;\n      }\n      function Ov(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2));\n        return r2 ? (t2.Q = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Bv(t2, n2, e2) {\n        var r2 = gv.exec(n2.slice(e2));\n        return r2 ? (t2.s = +r2[0], e2 + r2[0].length) : -1;\n      }\n      function Yv(t2, n2) {\n        return _v(t2.getDate(), n2, 2);\n      }\n      function Lv(t2, n2) {\n        return _v(t2.getHours(), n2, 2);\n      }\n      function jv(t2, n2) {\n        return _v(t2.getHours() % 12 || 12, n2, 2);\n      }\n      function Hv(t2, n2) {\n        return _v(1 + py.count(tv(t2), t2), n2, 3);\n      }\n      function Xv(t2, n2) {\n        return _v(t2.getMilliseconds(), n2, 3);\n      }\n      function Gv(t2, n2) {\n        return Xv(t2, n2) + \"000\";\n      }\n      function Vv(t2, n2) {\n        return _v(t2.getMonth() + 1, n2, 2);\n      }\n      function Wv(t2, n2) {\n        return _v(t2.getMinutes(), n2, 2);\n      }\n      function Zv(t2, n2) {\n        return _v(t2.getSeconds(), n2, 2);\n      }\n      function Kv(t2) {\n        var n2 = t2.getDay();\n        return 0 === n2 ? 7 : n2;\n      }\n      function Qv(t2, n2) {\n        return _v(xy.count(tv(t2) - 1, t2), n2, 2);\n      }\n      function Jv(t2) {\n        var n2 = t2.getDay();\n        return n2 >= 4 || 0 === n2 ? Ay(t2) : Ay.ceil(t2);\n      }\n      function t_(t2, n2) {\n        return t2 = Jv(t2), _v(Ay.count(tv(t2), t2) + (4 === tv(t2).getDay()), n2, 2);\n      }\n      function n_(t2) {\n        return t2.getDay();\n      }\n      function e_(t2, n2) {\n        return _v(wy.count(tv(t2) - 1, t2), n2, 2);\n      }\n      function r_(t2, n2) {\n        return _v(t2.getFullYear() % 100, n2, 2);\n      }\n      function i_(t2, n2) {\n        return _v((t2 = Jv(t2)).getFullYear() % 100, n2, 2);\n      }\n      function o_(t2, n2) {\n        return _v(t2.getFullYear() % 1e4, n2, 4);\n      }\n      function a_(t2, n2) {\n        var e2 = t2.getDay();\n        return _v((t2 = e2 >= 4 || 0 === e2 ? Ay(t2) : Ay.ceil(t2)).getFullYear() % 1e4, n2, 4);\n      }\n      function u_(t2) {\n        var n2 = t2.getTimezoneOffset();\n        return (n2 > 0 ? \"-\" : (n2 *= -1, \"+\")) + _v(n2 / 60 | 0, \"0\", 2) + _v(n2 % 60, \"0\", 2);\n      }\n      function c_(t2, n2) {\n        return _v(t2.getUTCDate(), n2, 2);\n      }\n      function f_(t2, n2) {\n        return _v(t2.getUTCHours(), n2, 2);\n      }\n      function s_(t2, n2) {\n        return _v(t2.getUTCHours() % 12 || 12, n2, 2);\n      }\n      function l_(t2, n2) {\n        return _v(1 + yy.count(ev(t2), t2), n2, 3);\n      }\n      function h_(t2, n2) {\n        return _v(t2.getUTCMilliseconds(), n2, 3);\n      }\n      function d_(t2, n2) {\n        return h_(t2, n2) + \"000\";\n      }\n      function p_(t2, n2) {\n        return _v(t2.getUTCMonth() + 1, n2, 2);\n      }\n      function g_(t2, n2) {\n        return _v(t2.getUTCMinutes(), n2, 2);\n      }\n      function y_(t2, n2) {\n        return _v(t2.getUTCSeconds(), n2, 2);\n      }\n      function v_(t2) {\n        var n2 = t2.getUTCDay();\n        return 0 === n2 ? 7 : n2;\n      }\n      function __(t2, n2) {\n        return _v(Fy.count(ev(t2) - 1, t2), n2, 2);\n      }\n      function b_(t2) {\n        var n2 = t2.getUTCDay();\n        return n2 >= 4 || 0 === n2 ? Oy(t2) : Oy.ceil(t2);\n      }\n      function m_(t2, n2) {\n        return t2 = b_(t2), _v(Oy.count(ev(t2), t2) + (4 === ev(t2).getUTCDay()), n2, 2);\n      }\n      function x_(t2) {\n        return t2.getUTCDay();\n      }\n      function w_(t2, n2) {\n        return _v(qy.count(ev(t2) - 1, t2), n2, 2);\n      }\n      function M_(t2, n2) {\n        return _v(t2.getUTCFullYear() % 100, n2, 2);\n      }\n      function T_(t2, n2) {\n        return _v((t2 = b_(t2)).getUTCFullYear() % 100, n2, 2);\n      }\n      function A_(t2, n2) {\n        return _v(t2.getUTCFullYear() % 1e4, n2, 4);\n      }\n      function S_(t2, n2) {\n        var e2 = t2.getUTCDay();\n        return _v((t2 = e2 >= 4 || 0 === e2 ? Oy(t2) : Oy.ceil(t2)).getUTCFullYear() % 1e4, n2, 4);\n      }\n      function E_() {\n        return \"+0000\";\n      }\n      function N_() {\n        return \"%\";\n      }\n      function k_(t2) {\n        return +t2;\n      }\n      function C_(t2) {\n        return Math.floor(+t2 / 1e3);\n      }\n      function P_(n2) {\n        return dv = hv(n2), t.timeFormat = dv.format, t.timeParse = dv.parse, t.utcFormat = dv.utcFormat, t.utcParse = dv.utcParse, dv;\n      }\n      t.timeFormat = void 0, t.timeParse = void 0, t.utcFormat = void 0, t.utcParse = void 0, P_({ dateTime: \"%x, %X\", date: \"%-m/%-d/%Y\", time: \"%-I:%M:%S %p\", periods: [\"AM\", \"PM\"], days: [\"Sunday\", \"Monday\", \"Tuesday\", \"Wednesday\", \"Thursday\", \"Friday\", \"Saturday\"], shortDays: [\"Sun\", \"Mon\", \"Tue\", \"Wed\", \"Thu\", \"Fri\", \"Sat\"], months: [\"January\", \"February\", \"March\", \"April\", \"May\", \"June\", \"July\", \"August\", \"September\", \"October\", \"November\", \"December\"], shortMonths: [\"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\", \"Sep\", \"Oct\", \"Nov\", \"Dec\"] });\n      var z_ = \"%Y-%m-%dT%H:%M:%S.%LZ\";\n      var $_ = Date.prototype.toISOString ? function(t2) {\n        return t2.toISOString();\n      } : t.utcFormat(z_), D_ = $_;\n      var R_ = +/* @__PURE__ */ new Date(\"2000-01-01T00:00:00.000Z\") ? function(t2) {\n        var n2 = new Date(t2);\n        return isNaN(n2) ? null : n2;\n      } : t.utcParse(z_), F_ = R_;\n      function q_(t2) {\n        return new Date(t2);\n      }\n      function U_(t2) {\n        return t2 instanceof Date ? +t2 : +/* @__PURE__ */ new Date(+t2);\n      }\n      function I_(t2, n2, e2, r2, i2, o2, a2, u2, c2, f2) {\n        var s2 = Sg(), l2 = s2.invert, h2 = s2.domain, d2 = f2(\".%L\"), p2 = f2(\":%S\"), g2 = f2(\"%I:%M\"), y2 = f2(\"%I %p\"), v2 = f2(\"%a %d\"), _2 = f2(\"%b %d\"), b2 = f2(\"%B\"), m2 = f2(\"%Y\");\n        function x2(t3) {\n          return (c2(t3) < t3 ? d2 : u2(t3) < t3 ? p2 : a2(t3) < t3 ? g2 : o2(t3) < t3 ? y2 : r2(t3) < t3 ? i2(t3) < t3 ? v2 : _2 : e2(t3) < t3 ? b2 : m2)(t3);\n        }\n        return s2.invert = function(t3) {\n          return new Date(l2(t3));\n        }, s2.domain = function(t3) {\n          return arguments.length ? h2(Array.from(t3, U_)) : h2().map(q_);\n        }, s2.ticks = function(n3) {\n          var e3 = h2();\n          return t2(e3[0], e3[e3.length - 1], null == n3 ? 10 : n3);\n        }, s2.tickFormat = function(t3, n3) {\n          return null == n3 ? x2 : f2(n3);\n        }, s2.nice = function(t3) {\n          var e3 = h2();\n          return t3 && \"function\" == typeof t3.range || (t3 = n2(e3[0], e3[e3.length - 1], null == t3 ? 10 : t3)), t3 ? h2(kg(e3, t3)) : s2;\n        }, s2.copy = function() {\n          return Tg(s2, I_(t2, n2, e2, r2, i2, o2, a2, u2, c2, f2));\n        }, s2;\n      }\n      function O_() {\n        var t2, n2, e2, r2, i2, o2 = 0, a2 = 1, u2 = mg, c2 = false;\n        function f2(n3) {\n          return null == n3 || isNaN(n3 = +n3) ? i2 : u2(0 === e2 ? 0.5 : (n3 = (r2(n3) - t2) * e2, c2 ? Math.max(0, Math.min(1, n3)) : n3));\n        }\n        function s2(t3) {\n          return function(n3) {\n            var e3, r3;\n            return arguments.length ? ([e3, r3] = n3, u2 = t3(e3, r3), f2) : [u2(0), u2(1)];\n          };\n        }\n        return f2.domain = function(i3) {\n          return arguments.length ? ([o2, a2] = i3, t2 = r2(o2 = +o2), n2 = r2(a2 = +a2), e2 = t2 === n2 ? 0 : 1 / (n2 - t2), f2) : [o2, a2];\n        }, f2.clamp = function(t3) {\n          return arguments.length ? (c2 = !!t3, f2) : c2;\n        }, f2.interpolator = function(t3) {\n          return arguments.length ? (u2 = t3, f2) : u2;\n        }, f2.range = s2(Gr), f2.rangeRound = s2(Vr), f2.unknown = function(t3) {\n          return arguments.length ? (i2 = t3, f2) : i2;\n        }, function(i3) {\n          return r2 = i3, t2 = i3(o2), n2 = i3(a2), e2 = t2 === n2 ? 0 : 1 / (n2 - t2), f2;\n        };\n      }\n      function B_(t2, n2) {\n        return n2.domain(t2.domain()).interpolator(t2.interpolator()).clamp(t2.clamp()).unknown(t2.unknown());\n      }\n      function Y_() {\n        var t2 = Lg(O_());\n        return t2.copy = function() {\n          return B_(t2, Y_()).exponent(t2.exponent());\n        }, dg.apply(t2, arguments);\n      }\n      function L_() {\n        var t2, n2, e2, r2, i2, o2, a2, u2 = 0, c2 = 0.5, f2 = 1, s2 = 1, l2 = mg, h2 = false;\n        function d2(t3) {\n          return isNaN(t3 = +t3) ? a2 : (t3 = 0.5 + ((t3 = +o2(t3)) - n2) * (s2 * t3 < s2 * n2 ? r2 : i2), l2(h2 ? Math.max(0, Math.min(1, t3)) : t3));\n        }\n        function p2(t3) {\n          return function(n3) {\n            var e3, r3, i3;\n            return arguments.length ? ([e3, r3, i3] = n3, l2 = di(t3, [e3, r3, i3]), d2) : [l2(0), l2(0.5), l2(1)];\n          };\n        }\n        return d2.domain = function(a3) {\n          return arguments.length ? ([u2, c2, f2] = a3, t2 = o2(u2 = +u2), n2 = o2(c2 = +c2), e2 = o2(f2 = +f2), r2 = t2 === n2 ? 0 : 0.5 / (n2 - t2), i2 = n2 === e2 ? 0 : 0.5 / (e2 - n2), s2 = n2 < t2 ? -1 : 1, d2) : [u2, c2, f2];\n        }, d2.clamp = function(t3) {\n          return arguments.length ? (h2 = !!t3, d2) : h2;\n        }, d2.interpolator = function(t3) {\n          return arguments.length ? (l2 = t3, d2) : l2;\n        }, d2.range = p2(Gr), d2.rangeRound = p2(Vr), d2.unknown = function(t3) {\n          return arguments.length ? (a2 = t3, d2) : a2;\n        }, function(a3) {\n          return o2 = a3, t2 = a3(u2), n2 = a3(c2), e2 = a3(f2), r2 = t2 === n2 ? 0 : 0.5 / (n2 - t2), i2 = n2 === e2 ? 0 : 0.5 / (e2 - n2), s2 = n2 < t2 ? -1 : 1, d2;\n        };\n      }\n      function j_() {\n        var t2 = Lg(L_());\n        return t2.copy = function() {\n          return B_(t2, j_()).exponent(t2.exponent());\n        }, dg.apply(t2, arguments);\n      }\n      function H_(t2) {\n        for (var n2 = t2.length / 6 | 0, e2 = new Array(n2), r2 = 0; r2 < n2; )\n          e2[r2] = \"#\" + t2.slice(6 * r2, 6 * ++r2);\n        return e2;\n      }\n      var X_ = H_(\"1f77b4ff7f0e2ca02cd627289467bd8c564be377c27f7f7fbcbd2217becf\"), G_ = H_(\"7fc97fbeaed4fdc086ffff99386cb0f0027fbf5b17666666\"), V_ = H_(\"1b9e77d95f027570b3e7298a66a61ee6ab02a6761d666666\"), W_ = H_(\"a6cee31f78b4b2df8a33a02cfb9a99e31a1cfdbf6fff7f00cab2d66a3d9affff99b15928\"), Z_ = H_(\"fbb4aeb3cde3ccebc5decbe4fed9a6ffffcce5d8bdfddaecf2f2f2\"), K_ = H_(\"b3e2cdfdcdaccbd5e8f4cae4e6f5c9fff2aef1e2cccccccc\"), Q_ = H_(\"e41a1c377eb84daf4a984ea3ff7f00ffff33a65628f781bf999999\"), J_ = H_(\"66c2a5fc8d628da0cbe78ac3a6d854ffd92fe5c494b3b3b3\"), tb = H_(\"8dd3c7ffffb3bebadafb807280b1d3fdb462b3de69fccde5d9d9d9bc80bdccebc5ffed6f\"), nb = H_(\"4e79a7f28e2ce1575976b7b259a14fedc949af7aa1ff9da79c755fbab0ab\"), eb = (t2) => Fr(t2[t2.length - 1]), rb = new Array(3).concat(\"d8b365f5f5f55ab4ac\", \"a6611adfc27d80cdc1018571\", \"a6611adfc27df5f5f580cdc1018571\", \"8c510ad8b365f6e8c3c7eae55ab4ac01665e\", \"8c510ad8b365f6e8c3f5f5f5c7eae55ab4ac01665e\", \"8c510abf812ddfc27df6e8c3c7eae580cdc135978f01665e\", \"8c510abf812ddfc27df6e8c3f5f5f5c7eae580cdc135978f01665e\", \"5430058c510abf812ddfc27df6e8c3c7eae580cdc135978f01665e003c30\", \"5430058c510abf812ddfc27df6e8c3f5f5f5c7eae580cdc135978f01665e003c30\").map(H_), ib = eb(rb), ob = new Array(3).concat(\"af8dc3f7f7f77fbf7b\", \"7b3294c2a5cfa6dba0008837\", \"7b3294c2a5cff7f7f7a6dba0008837\", \"762a83af8dc3e7d4e8d9f0d37fbf7b1b7837\", \"762a83af8dc3e7d4e8f7f7f7d9f0d37fbf7b1b7837\", \"762a839970abc2a5cfe7d4e8d9f0d3a6dba05aae611b7837\", \"762a839970abc2a5cfe7d4e8f7f7f7d9f0d3a6dba05aae611b7837\", \"40004b762a839970abc2a5cfe7d4e8d9f0d3a6dba05aae611b783700441b\", \"40004b762a839970abc2a5cfe7d4e8f7f7f7d9f0d3a6dba05aae611b783700441b\").map(H_), ab = eb(ob), ub = new Array(3).concat(\"e9a3c9f7f7f7a1d76a\", \"d01c8bf1b6dab8e1864dac26\", \"d01c8bf1b6daf7f7f7b8e1864dac26\", \"c51b7de9a3c9fde0efe6f5d0a1d76a4d9221\", \"c51b7de9a3c9fde0eff7f7f7e6f5d0a1d76a4d9221\", \"c51b7dde77aef1b6dafde0efe6f5d0b8e1867fbc414d9221\", \"c51b7dde77aef1b6dafde0eff7f7f7e6f5d0b8e1867fbc414d9221\", \"8e0152c51b7dde77aef1b6dafde0efe6f5d0b8e1867fbc414d9221276419\", \"8e0152c51b7dde77aef1b6dafde0eff7f7f7e6f5d0b8e1867fbc414d9221276419\").map(H_), cb = eb(ub), fb = new Array(3).concat(\"998ec3f7f7f7f1a340\", \"5e3c99b2abd2fdb863e66101\", \"5e3c99b2abd2f7f7f7fdb863e66101\", \"542788998ec3d8daebfee0b6f1a340b35806\", \"542788998ec3d8daebf7f7f7fee0b6f1a340b35806\", \"5427888073acb2abd2d8daebfee0b6fdb863e08214b35806\", \"5427888073acb2abd2d8daebf7f7f7fee0b6fdb863e08214b35806\", \"2d004b5427888073acb2abd2d8daebfee0b6fdb863e08214b358067f3b08\", \"2d004b5427888073acb2abd2d8daebf7f7f7fee0b6fdb863e08214b358067f3b08\").map(H_), sb = eb(fb), lb = new Array(3).concat(\"ef8a62f7f7f767a9cf\", \"ca0020f4a58292c5de0571b0\", \"ca0020f4a582f7f7f792c5de0571b0\", \"b2182bef8a62fddbc7d1e5f067a9cf2166ac\", \"b2182bef8a62fddbc7f7f7f7d1e5f067a9cf2166ac\", \"b2182bd6604df4a582fddbc7d1e5f092c5de4393c32166ac\", \"b2182bd6604df4a582fddbc7f7f7f7d1e5f092c5de4393c32166ac\", \"67001fb2182bd6604df4a582fddbc7d1e5f092c5de4393c32166ac053061\", \"67001fb2182bd6604df4a582fddbc7f7f7f7d1e5f092c5de4393c32166ac053061\").map(H_), hb = eb(lb), db = new Array(3).concat(\"ef8a62ffffff999999\", \"ca0020f4a582bababa404040\", \"ca0020f4a582ffffffbababa404040\", \"b2182bef8a62fddbc7e0e0e09999994d4d4d\", \"b2182bef8a62fddbc7ffffffe0e0e09999994d4d4d\", \"b2182bd6604df4a582fddbc7e0e0e0bababa8787874d4d4d\", \"b2182bd6604df4a582fddbc7ffffffe0e0e0bababa8787874d4d4d\", \"67001fb2182bd6604df4a582fddbc7e0e0e0bababa8787874d4d4d1a1a1a\", \"67001fb2182bd6604df4a582fddbc7ffffffe0e0e0bababa8787874d4d4d1a1a1a\").map(H_), pb = eb(db), gb = new Array(3).concat(\"fc8d59ffffbf91bfdb\", \"d7191cfdae61abd9e92c7bb6\", \"d7191cfdae61ffffbfabd9e92c7bb6\", \"d73027fc8d59fee090e0f3f891bfdb4575b4\", \"d73027fc8d59fee090ffffbfe0f3f891bfdb4575b4\", \"d73027f46d43fdae61fee090e0f3f8abd9e974add14575b4\", \"d73027f46d43fdae61fee090ffffbfe0f3f8abd9e974add14575b4\", \"a50026d73027f46d43fdae61fee090e0f3f8abd9e974add14575b4313695\", \"a50026d73027f46d43fdae61fee090ffffbfe0f3f8abd9e974add14575b4313695\").map(H_), yb = eb(gb), vb = new Array(3).concat(\"fc8d59ffffbf91cf60\", \"d7191cfdae61a6d96a1a9641\", \"d7191cfdae61ffffbfa6d96a1a9641\", \"d73027fc8d59fee08bd9ef8b91cf601a9850\", \"d73027fc8d59fee08bffffbfd9ef8b91cf601a9850\", \"d73027f46d43fdae61fee08bd9ef8ba6d96a66bd631a9850\", \"d73027f46d43fdae61fee08bffffbfd9ef8ba6d96a66bd631a9850\", \"a50026d73027f46d43fdae61fee08bd9ef8ba6d96a66bd631a9850006837\", \"a50026d73027f46d43fdae61fee08bffffbfd9ef8ba6d96a66bd631a9850006837\").map(H_), _b = eb(vb), bb = new Array(3).concat(\"fc8d59ffffbf99d594\", \"d7191cfdae61abdda42b83ba\", \"d7191cfdae61ffffbfabdda42b83ba\", \"d53e4ffc8d59fee08be6f59899d5943288bd\", \"d53e4ffc8d59fee08bffffbfe6f59899d5943288bd\", \"d53e4ff46d43fdae61fee08be6f598abdda466c2a53288bd\", \"d53e4ff46d43fdae61fee08bffffbfe6f598abdda466c2a53288bd\", \"9e0142d53e4ff46d43fdae61fee08be6f598abdda466c2a53288bd5e4fa2\", \"9e0142d53e4ff46d43fdae61fee08bffffbfe6f598abdda466c2a53288bd5e4fa2\").map(H_), mb = eb(bb), xb = new Array(3).concat(\"e5f5f999d8c92ca25f\", \"edf8fbb2e2e266c2a4238b45\", \"edf8fbb2e2e266c2a42ca25f006d2c\", \"edf8fbccece699d8c966c2a42ca25f006d2c\", \"edf8fbccece699d8c966c2a441ae76238b45005824\", \"f7fcfde5f5f9ccece699d8c966c2a441ae76238b45005824\", \"f7fcfde5f5f9ccece699d8c966c2a441ae76238b45006d2c00441b\").map(H_), wb = eb(xb), Mb = new Array(3).concat(\"e0ecf49ebcda8856a7\", \"edf8fbb3cde38c96c688419d\", \"edf8fbb3cde38c96c68856a7810f7c\", \"edf8fbbfd3e69ebcda8c96c68856a7810f7c\", \"edf8fbbfd3e69ebcda8c96c68c6bb188419d6e016b\", \"f7fcfde0ecf4bfd3e69ebcda8c96c68c6bb188419d6e016b\", \"f7fcfde0ecf4bfd3e69ebcda8c96c68c6bb188419d810f7c4d004b\").map(H_), Tb = eb(Mb), Ab = new Array(3).concat(\"e0f3dba8ddb543a2ca\", \"f0f9e8bae4bc7bccc42b8cbe\", \"f0f9e8bae4bc7bccc443a2ca0868ac\", \"f0f9e8ccebc5a8ddb57bccc443a2ca0868ac\", \"f0f9e8ccebc5a8ddb57bccc44eb3d32b8cbe08589e\", \"f7fcf0e0f3dbccebc5a8ddb57bccc44eb3d32b8cbe08589e\", \"f7fcf0e0f3dbccebc5a8ddb57bccc44eb3d32b8cbe0868ac084081\").map(H_), Sb = eb(Ab), Eb = new Array(3).concat(\"fee8c8fdbb84e34a33\", \"fef0d9fdcc8afc8d59d7301f\", \"fef0d9fdcc8afc8d59e34a33b30000\", \"fef0d9fdd49efdbb84fc8d59e34a33b30000\", \"fef0d9fdd49efdbb84fc8d59ef6548d7301f990000\", \"fff7ecfee8c8fdd49efdbb84fc8d59ef6548d7301f990000\", \"fff7ecfee8c8fdd49efdbb84fc8d59ef6548d7301fb300007f0000\").map(H_), Nb = eb(Eb), kb = new Array(3).concat(\"ece2f0a6bddb1c9099\", \"f6eff7bdc9e167a9cf02818a\", \"f6eff7bdc9e167a9cf1c9099016c59\", \"f6eff7d0d1e6a6bddb67a9cf1c9099016c59\", \"f6eff7d0d1e6a6bddb67a9cf3690c002818a016450\", \"fff7fbece2f0d0d1e6a6bddb67a9cf3690c002818a016450\", \"fff7fbece2f0d0d1e6a6bddb67a9cf3690c002818a016c59014636\").map(H_), Cb = eb(kb), Pb = new Array(3).concat(\"ece7f2a6bddb2b8cbe\", \"f1eef6bdc9e174a9cf0570b0\", \"f1eef6bdc9e174a9cf2b8cbe045a8d\", \"f1eef6d0d1e6a6bddb74a9cf2b8cbe045a8d\", \"f1eef6d0d1e6a6bddb74a9cf3690c00570b0034e7b\", \"fff7fbece7f2d0d1e6a6bddb74a9cf3690c00570b0034e7b\", \"fff7fbece7f2d0d1e6a6bddb74a9cf3690c00570b0045a8d023858\").map(H_), zb = eb(Pb), $b = new Array(3).concat(\"e7e1efc994c7dd1c77\", \"f1eef6d7b5d8df65b0ce1256\", \"f1eef6d7b5d8df65b0dd1c77980043\", \"f1eef6d4b9dac994c7df65b0dd1c77980043\", \"f1eef6d4b9dac994c7df65b0e7298ace125691003f\", \"f7f4f9e7e1efd4b9dac994c7df65b0e7298ace125691003f\", \"f7f4f9e7e1efd4b9dac994c7df65b0e7298ace125698004367001f\").map(H_), Db = eb($b), Rb = new Array(3).concat(\"fde0ddfa9fb5c51b8a\", \"feebe2fbb4b9f768a1ae017e\", \"feebe2fbb4b9f768a1c51b8a7a0177\", \"feebe2fcc5c0fa9fb5f768a1c51b8a7a0177\", \"feebe2fcc5c0fa9fb5f768a1dd3497ae017e7a0177\", \"fff7f3fde0ddfcc5c0fa9fb5f768a1dd3497ae017e7a0177\", \"fff7f3fde0ddfcc5c0fa9fb5f768a1dd3497ae017e7a017749006a\").map(H_), Fb = eb(Rb), qb = new Array(3).concat(\"edf8b17fcdbb2c7fb8\", \"ffffcca1dab441b6c4225ea8\", \"ffffcca1dab441b6c42c7fb8253494\", \"ffffccc7e9b47fcdbb41b6c42c7fb8253494\", \"ffffccc7e9b47fcdbb41b6c41d91c0225ea80c2c84\", \"ffffd9edf8b1c7e9b47fcdbb41b6c41d91c0225ea80c2c84\", \"ffffd9edf8b1c7e9b47fcdbb41b6c41d91c0225ea8253494081d58\").map(H_), Ub = eb(qb), Ib = new Array(3).concat(\"f7fcb9addd8e31a354\", \"ffffccc2e69978c679238443\", \"ffffccc2e69978c67931a354006837\", \"ffffccd9f0a3addd8e78c67931a354006837\", \"ffffccd9f0a3addd8e78c67941ab5d238443005a32\", \"ffffe5f7fcb9d9f0a3addd8e78c67941ab5d238443005a32\", \"ffffe5f7fcb9d9f0a3addd8e78c67941ab5d238443006837004529\").map(H_), Ob = eb(Ib), Bb = new Array(3).concat(\"fff7bcfec44fd95f0e\", \"ffffd4fed98efe9929cc4c02\", \"ffffd4fed98efe9929d95f0e993404\", \"ffffd4fee391fec44ffe9929d95f0e993404\", \"ffffd4fee391fec44ffe9929ec7014cc4c028c2d04\", \"ffffe5fff7bcfee391fec44ffe9929ec7014cc4c028c2d04\", \"ffffe5fff7bcfee391fec44ffe9929ec7014cc4c02993404662506\").map(H_), Yb = eb(Bb), Lb = new Array(3).concat(\"ffeda0feb24cf03b20\", \"ffffb2fecc5cfd8d3ce31a1c\", \"ffffb2fecc5cfd8d3cf03b20bd0026\", \"ffffb2fed976feb24cfd8d3cf03b20bd0026\", \"ffffb2fed976feb24cfd8d3cfc4e2ae31a1cb10026\", \"ffffccffeda0fed976feb24cfd8d3cfc4e2ae31a1cb10026\", \"ffffccffeda0fed976feb24cfd8d3cfc4e2ae31a1cbd0026800026\").map(H_), jb = eb(Lb), Hb = new Array(3).concat(\"deebf79ecae13182bd\", \"eff3ffbdd7e76baed62171b5\", \"eff3ffbdd7e76baed63182bd08519c\", \"eff3ffc6dbef9ecae16baed63182bd08519c\", \"eff3ffc6dbef9ecae16baed64292c62171b5084594\", \"f7fbffdeebf7c6dbef9ecae16baed64292c62171b5084594\", \"f7fbffdeebf7c6dbef9ecae16baed64292c62171b508519c08306b\").map(H_), Xb = eb(Hb), Gb = new Array(3).concat(\"e5f5e0a1d99b31a354\", \"edf8e9bae4b374c476238b45\", \"edf8e9bae4b374c47631a354006d2c\", \"edf8e9c7e9c0a1d99b74c47631a354006d2c\", \"edf8e9c7e9c0a1d99b74c47641ab5d238b45005a32\", \"f7fcf5e5f5e0c7e9c0a1d99b74c47641ab5d238b45005a32\", \"f7fcf5e5f5e0c7e9c0a1d99b74c47641ab5d238b45006d2c00441b\").map(H_), Vb = eb(Gb), Wb = new Array(3).concat(\"f0f0f0bdbdbd636363\", \"f7f7f7cccccc969696525252\", \"f7f7f7cccccc969696636363252525\", \"f7f7f7d9d9d9bdbdbd969696636363252525\", \"f7f7f7d9d9d9bdbdbd969696737373525252252525\", \"fffffff0f0f0d9d9d9bdbdbd969696737373525252252525\", \"fffffff0f0f0d9d9d9bdbdbd969696737373525252252525000000\").map(H_), Zb = eb(Wb), Kb = new Array(3).concat(\"efedf5bcbddc756bb1\", \"f2f0f7cbc9e29e9ac86a51a3\", \"f2f0f7cbc9e29e9ac8756bb154278f\", \"f2f0f7dadaebbcbddc9e9ac8756bb154278f\", \"f2f0f7dadaebbcbddc9e9ac8807dba6a51a34a1486\", \"fcfbfdefedf5dadaebbcbddc9e9ac8807dba6a51a34a1486\", \"fcfbfdefedf5dadaebbcbddc9e9ac8807dba6a51a354278f3f007d\").map(H_), Qb = eb(Kb), Jb = new Array(3).concat(\"fee0d2fc9272de2d26\", \"fee5d9fcae91fb6a4acb181d\", \"fee5d9fcae91fb6a4ade2d26a50f15\", \"fee5d9fcbba1fc9272fb6a4ade2d26a50f15\", \"fee5d9fcbba1fc9272fb6a4aef3b2ccb181d99000d\", \"fff5f0fee0d2fcbba1fc9272fb6a4aef3b2ccb181d99000d\", \"fff5f0fee0d2fcbba1fc9272fb6a4aef3b2ccb181da50f1567000d\").map(H_), tm = eb(Jb), nm = new Array(3).concat(\"fee6cefdae6be6550d\", \"feeddefdbe85fd8d3cd94701\", \"feeddefdbe85fd8d3ce6550da63603\", \"feeddefdd0a2fdae6bfd8d3ce6550da63603\", \"feeddefdd0a2fdae6bfd8d3cf16913d948018c2d04\", \"fff5ebfee6cefdd0a2fdae6bfd8d3cf16913d948018c2d04\", \"fff5ebfee6cefdd0a2fdae6bfd8d3cf16913d94801a636037f2704\").map(H_), em = eb(nm);\n      var rm = hi(Tr(300, 0.5, 0), Tr(-240, 0.5, 1)), im = hi(Tr(-100, 0.75, 0.35), Tr(80, 1.5, 0.8)), om = hi(Tr(260, 0.75, 0.35), Tr(80, 1.5, 0.8)), am = Tr();\n      var um = Fe(), cm = Math.PI / 3, fm = 2 * Math.PI / 3;\n      function sm(t2) {\n        var n2 = t2.length;\n        return function(e2) {\n          return t2[Math.max(0, Math.min(n2 - 1, Math.floor(e2 * n2)))];\n        };\n      }\n      var lm = sm(H_(\"44015444025645045745055946075a46085c460a5d460b5e470d60470e6147106347116447136548146748166848176948186a481a6c481b6d481c6e481d6f481f70482071482173482374482475482576482677482878482979472a7a472c7a472d7b472e7c472f7d46307e46327e46337f463480453581453781453882443983443a83443b84433d84433e85423f854240864241864142874144874045884046883f47883f48893e49893e4a893e4c8a3d4d8a3d4e8a3c4f8a3c508b3b518b3b528b3a538b3a548c39558c39568c38588c38598c375a8c375b8d365c8d365d8d355e8d355f8d34608d34618d33628d33638d32648e32658e31668e31678e31688e30698e306a8e2f6b8e2f6c8e2e6d8e2e6e8e2e6f8e2d708e2d718e2c718e2c728e2c738e2b748e2b758e2a768e2a778e2a788e29798e297a8e297b8e287c8e287d8e277e8e277f8e27808e26818e26828e26828e25838e25848e25858e24868e24878e23888e23898e238a8d228b8d228c8d228d8d218e8d218f8d21908d21918c20928c20928c20938c1f948c1f958b1f968b1f978b1f988b1f998a1f9a8a1e9b8a1e9c891e9d891f9e891f9f881fa0881fa1881fa1871fa28720a38620a48621a58521a68522a78522a88423a98324aa8325ab8225ac8226ad8127ad8128ae8029af7f2ab07f2cb17e2db27d2eb37c2fb47c31b57b32b67a34b67935b77937b87838b9773aba763bbb753dbc743fbc7340bd7242be7144bf7046c06f48c16e4ac16d4cc26c4ec36b50c46a52c56954c56856c66758c7655ac8645cc8635ec96260ca6063cb5f65cb5e67cc5c69cd5b6ccd5a6ece5870cf5773d05675d05477d1537ad1517cd2507fd34e81d34d84d44b86d54989d5488bd6468ed64590d74393d74195d84098d83e9bd93c9dd93ba0da39a2da37a5db36a8db34aadc32addc30b0dd2fb2dd2db5de2bb8de29bade28bddf26c0df25c2df23c5e021c8e020cae11fcde11dd0e11cd2e21bd5e21ad8e219dae319dde318dfe318e2e418e5e419e7e419eae51aece51befe51cf1e51df4e61ef6e620f8e621fbe723fde725\")), hm = sm(H_(\"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\")), dm = sm(H_(\"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\")), pm = sm(H_(\"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\"));\n      function gm(t2) {\n        return function() {\n          return t2;\n        };\n      }\n      const ym = Math.abs, vm = Math.atan2, _m = Math.cos, bm = Math.max, mm = Math.min, xm = Math.sin, wm = Math.sqrt, Mm = 1e-12, Tm = Math.PI, Am = Tm / 2, Sm = 2 * Tm;\n      function Em(t2) {\n        return t2 >= 1 ? Am : t2 <= -1 ? -Am : Math.asin(t2);\n      }\n      function Nm(t2) {\n        let n2 = 3;\n        return t2.digits = function(e2) {\n          if (!arguments.length)\n            return n2;\n          if (null == e2)\n            n2 = null;\n          else {\n            const t3 = Math.floor(e2);\n            if (!(t3 >= 0))\n              throw new RangeError(`invalid digits: ${e2}`);\n            n2 = t3;\n          }\n          return t2;\n        }, () => new Ua(n2);\n      }\n      function km(t2) {\n        return t2.innerRadius;\n      }\n      function Cm(t2) {\n        return t2.outerRadius;\n      }\n      function Pm(t2) {\n        return t2.startAngle;\n      }\n      function zm(t2) {\n        return t2.endAngle;\n      }\n      function $m(t2) {\n        return t2 && t2.padAngle;\n      }\n      function Dm(t2, n2, e2, r2, i2, o2, a2) {\n        var u2 = t2 - e2, c2 = n2 - r2, f2 = (a2 ? o2 : -o2) / wm(u2 * u2 + c2 * c2), s2 = f2 * c2, l2 = -f2 * u2, h2 = t2 + s2, d2 = n2 + l2, p2 = e2 + s2, g2 = r2 + l2, y2 = (h2 + p2) / 2, v2 = (d2 + g2) / 2, _2 = p2 - h2, b2 = g2 - d2, m2 = _2 * _2 + b2 * b2, x2 = i2 - o2, w2 = h2 * g2 - p2 * d2, M2 = (b2 < 0 ? -1 : 1) * wm(bm(0, x2 * x2 * m2 - w2 * w2)), T2 = (w2 * b2 - _2 * M2) / m2, A2 = (-w2 * _2 - b2 * M2) / m2, S2 = (w2 * b2 + _2 * M2) / m2, E2 = (-w2 * _2 + b2 * M2) / m2, N2 = T2 - y2, k2 = A2 - v2, C2 = S2 - y2, P2 = E2 - v2;\n        return N2 * N2 + k2 * k2 > C2 * C2 + P2 * P2 && (T2 = S2, A2 = E2), { cx: T2, cy: A2, x01: -s2, y01: -l2, x11: T2 * (i2 / x2 - 1), y11: A2 * (i2 / x2 - 1) };\n      }\n      var Rm = Array.prototype.slice;\n      function Fm(t2) {\n        return \"object\" == typeof t2 && \"length\" in t2 ? t2 : Array.from(t2);\n      }\n      function qm(t2) {\n        this._context = t2;\n      }\n      function Um(t2) {\n        return new qm(t2);\n      }\n      function Im(t2) {\n        return t2[0];\n      }\n      function Om(t2) {\n        return t2[1];\n      }\n      function Bm(t2, n2) {\n        var e2 = gm(true), r2 = null, i2 = Um, o2 = null, a2 = Nm(u2);\n        function u2(u3) {\n          var c2, f2, s2, l2 = (u3 = Fm(u3)).length, h2 = false;\n          for (null == r2 && (o2 = i2(s2 = a2())), c2 = 0; c2 <= l2; ++c2)\n            !(c2 < l2 && e2(f2 = u3[c2], c2, u3)) === h2 && ((h2 = !h2) ? o2.lineStart() : o2.lineEnd()), h2 && o2.point(+t2(f2, c2, u3), +n2(f2, c2, u3));\n          if (s2)\n            return o2 = null, s2 + \"\" || null;\n        }\n        return t2 = \"function\" == typeof t2 ? t2 : void 0 === t2 ? Im : gm(t2), n2 = \"function\" == typeof n2 ? n2 : void 0 === n2 ? Om : gm(n2), u2.x = function(n3) {\n          return arguments.length ? (t2 = \"function\" == typeof n3 ? n3 : gm(+n3), u2) : t2;\n        }, u2.y = function(t3) {\n          return arguments.length ? (n2 = \"function\" == typeof t3 ? t3 : gm(+t3), u2) : n2;\n        }, u2.defined = function(t3) {\n          return arguments.length ? (e2 = \"function\" == typeof t3 ? t3 : gm(!!t3), u2) : e2;\n        }, u2.curve = function(t3) {\n          return arguments.length ? (i2 = t3, null != r2 && (o2 = i2(r2)), u2) : i2;\n        }, u2.context = function(t3) {\n          return arguments.length ? (null == t3 ? r2 = o2 = null : o2 = i2(r2 = t3), u2) : r2;\n        }, u2;\n      }\n      function Ym(t2, n2, e2) {\n        var r2 = null, i2 = gm(true), o2 = null, a2 = Um, u2 = null, c2 = Nm(f2);\n        function f2(f3) {\n          var s3, l2, h2, d2, p2, g2 = (f3 = Fm(f3)).length, y2 = false, v2 = new Array(g2), _2 = new Array(g2);\n          for (null == o2 && (u2 = a2(p2 = c2())), s3 = 0; s3 <= g2; ++s3) {\n            if (!(s3 < g2 && i2(d2 = f3[s3], s3, f3)) === y2)\n              if (y2 = !y2)\n                l2 = s3, u2.areaStart(), u2.lineStart();\n              else {\n                for (u2.lineEnd(), u2.lineStart(), h2 = s3 - 1; h2 >= l2; --h2)\n                  u2.point(v2[h2], _2[h2]);\n                u2.lineEnd(), u2.areaEnd();\n              }\n            y2 && (v2[s3] = +t2(d2, s3, f3), _2[s3] = +n2(d2, s3, f3), u2.point(r2 ? +r2(d2, s3, f3) : v2[s3], e2 ? +e2(d2, s3, f3) : _2[s3]));\n          }\n          if (p2)\n            return u2 = null, p2 + \"\" || null;\n        }\n        function s2() {\n          return Bm().defined(i2).curve(a2).context(o2);\n        }\n        return t2 = \"function\" == typeof t2 ? t2 : void 0 === t2 ? Im : gm(+t2), n2 = \"function\" == typeof n2 ? n2 : gm(void 0 === n2 ? 0 : +n2), e2 = \"function\" == typeof e2 ? e2 : void 0 === e2 ? Om : gm(+e2), f2.x = function(n3) {\n          return arguments.length ? (t2 = \"function\" == typeof n3 ? n3 : gm(+n3), r2 = null, f2) : t2;\n        }, f2.x0 = function(n3) {\n          return arguments.length ? (t2 = \"function\" == typeof n3 ? n3 : gm(+n3), f2) : t2;\n        }, f2.x1 = function(t3) {\n          return arguments.length ? (r2 = null == t3 ? null : \"function\" == typeof t3 ? t3 : gm(+t3), f2) : r2;\n        }, f2.y = function(t3) {\n          return arguments.length ? (n2 = \"function\" == typeof t3 ? t3 : gm(+t3), e2 = null, f2) : n2;\n        }, f2.y0 = function(t3) {\n          return arguments.length ? (n2 = \"function\" == typeof t3 ? t3 : gm(+t3), f2) : n2;\n        }, f2.y1 = function(t3) {\n          return arguments.length ? (e2 = null == t3 ? null : \"function\" == typeof t3 ? t3 : gm(+t3), f2) : e2;\n        }, f2.lineX0 = f2.lineY0 = function() {\n          return s2().x(t2).y(n2);\n        }, f2.lineY1 = function() {\n          return s2().x(t2).y(e2);\n        }, f2.lineX1 = function() {\n          return s2().x(r2).y(n2);\n        }, f2.defined = function(t3) {\n          return arguments.length ? (i2 = \"function\" == typeof t3 ? t3 : gm(!!t3), f2) : i2;\n        }, f2.curve = function(t3) {\n          return arguments.length ? (a2 = t3, null != o2 && (u2 = a2(o2)), f2) : a2;\n        }, f2.context = function(t3) {\n          return arguments.length ? (null == t3 ? o2 = u2 = null : u2 = a2(o2 = t3), f2) : o2;\n        }, f2;\n      }\n      function Lm(t2, n2) {\n        return n2 < t2 ? -1 : n2 > t2 ? 1 : n2 >= t2 ? 0 : NaN;\n      }\n      function jm(t2) {\n        return t2;\n      }\n      qm.prototype = { areaStart: function() {\n        this._line = 0;\n      }, areaEnd: function() {\n        this._line = NaN;\n      }, lineStart: function() {\n        this._point = 0;\n      }, lineEnd: function() {\n        (this._line || 0 !== this._line && 1 === this._point) && this._context.closePath(), this._line = 1 - this._line;\n      }, point: function(t2, n2) {\n        switch (t2 = +t2, n2 = +n2, this._point) {\n          case 0:\n            this._point = 1, this._line ? this._context.lineTo(t2, n2) : this._context.moveTo(t2, n2);\n            break;\n          case 1:\n            this._point = 2;\n          default:\n            this._context.lineTo(t2, n2);\n        }\n      } };\n      var Hm = Gm(Um);\n      function Xm(t2) {\n        this._curve = t2;\n      }\n      function Gm(t2) {\n        function n2(n3) {\n          return new Xm(t2(n3));\n        }\n        return n2._curve = t2, n2;\n      }\n      function Vm(t2) {\n        var n2 = t2.curve;\n        return t2.angle = t2.x, delete t2.x, t2.radius = t2.y, delete t2.y, t2.curve = function(t3) {\n          return arguments.length ? n2(Gm(t3)) : n2()._curve;\n        }, t2;\n      }\n      function Wm() {\n        return Vm(Bm().curve(Hm));\n      }\n      function Zm() {\n        var t2 = Ym().curve(Hm), n2 = t2.curve, e2 = t2.lineX0, r2 = t2.lineX1, i2 = t2.lineY0, o2 = t2.lineY1;\n        return t2.angle = t2.x, delete t2.x, t2.startAngle = t2.x0, delete t2.x0, t2.endAngle = t2.x1, delete t2.x1, t2.radius = t2.y, delete t2.y, t2.innerRadius = t2.y0, delete t2.y0, t2.outerRadius = t2.y1, delete t2.y1, t2.lineStartAngle = function() {\n          return Vm(e2());\n        }, delete t2.lineX0, t2.lineEndAngle = function() {\n          return Vm(r2());\n        }, delete t2.lineX1, t2.lineInnerRadius = function() {\n          return Vm(i2());\n        }, delete t2.lineY0, t2.lineOuterRadius = function() {\n          return Vm(o2());\n        }, delete t2.lineY1, t2.curve = function(t3) {\n          return arguments.length ? n2(Gm(t3)) : n2()._curve;\n        }, t2;\n      }\n      function Km(t2, n2) {\n        return [(n2 = +n2) * Math.cos(t2 -= Math.PI / 2), n2 * Math.sin(t2)];\n      }\n      Xm.prototype = { areaStart: function() {\n        this._curve.areaStart();\n      }, areaEnd: function() {\n        this._curve.areaEnd();\n      }, lineStart: function() {\n        this._curve.lineStart();\n      }, lineEnd: function() {\n        this._curve.lineEnd();\n      }, point: function(t2, n2) {\n        this._curve.point(n2 * Math.sin(t2), n2 * -Math.cos(t2));\n      } };\n      class Qm {\n        constructor(t2, n2) {\n          this._context = t2, this._x = n2;\n        }\n        areaStart() {\n          this._line = 0;\n        }\n        areaEnd() {\n          this._line = NaN;\n        }\n        lineStart() {\n          this._point = 0;\n        }\n        lineEnd() {\n          (this._line || 0 !== this._line && 1 === this._point) && this._context.closePath(), this._line = 1 - this._line;\n        }\n        point(t2, n2) {\n          switch (t2 = +t2, n2 = +n2, this._point) {\n            case 0:\n              this._point = 1, this._line ? this._context.lineTo(t2, n2) : this._context.moveTo(t2, n2);\n              break;\n            case 1:\n              this._point = 2;\n            default:\n              this._x ? this._context.bezierCurveTo(this._x0 = (this._x0 + t2) / 2, this._y0, this._x0, n2, t2, n2) : this._context.bezierCurveTo(this._x0, this._y0 = (this._y0 + n2) / 2, t2, this._y0, t2, n2);\n          }\n          this._x0 = t2, this._y0 = n2;\n        }\n      }\n      class Jm {\n        constructor(t2) {\n          this._context = t2;\n        }\n        lineStart() {\n          this._point = 0;\n        }\n        lineEnd() {\n        }\n        point(t2, n2) {\n          if (t2 = +t2, n2 = +n2, 0 === this._point)\n            this._point = 1;\n          else {\n            const e2 = Km(this._x0, this._y0), r2 = Km(this._x0, this._y0 = (this._y0 + n2) / 2), i2 = Km(t2, this._y0), o2 = Km(t2, n2);\n            this._context.moveTo(...e2), this._context.bezierCurveTo(...r2, ...i2, ...o2);\n          }\n          this._x0 = t2, this._y0 = n2;\n        }\n      }\n      function tx(t2) {\n        return new Qm(t2, true);\n      }\n      function nx(t2) {\n        return new Qm(t2, false);\n      }\n      function ex(t2) {\n        return new Jm(t2);\n      }\n      function rx(t2) {\n        return t2.source;\n      }\n      function ix(t2) {\n        return t2.target;\n      }\n      function ox(t2) {\n        let n2 = rx, e2 = ix, r2 = Im, i2 = Om, o2 = null, a2 = null, u2 = Nm(c2);\n        function c2() {\n          let c3;\n          const f2 = Rm.call(arguments), s2 = n2.apply(this, f2), l2 = e2.apply(this, f2);\n          if (null == o2 && (a2 = t2(c3 = u2())), a2.lineStart(), f2[0] = s2, a2.point(+r2.apply(this, f2), +i2.apply(this, f2)), f2[0] = l2, a2.point(+r2.apply(this, f2), +i2.apply(this, f2)), a2.lineEnd(), c3)\n            return a2 = null, c3 + \"\" || null;\n        }\n        return c2.source = function(t3) {\n          return arguments.length ? (n2 = t3, c2) : n2;\n        }, c2.target = function(t3) {\n          return arguments.length ? (e2 = t3, c2) : e2;\n        }, c2.x = function(t3) {\n          return arguments.length ? (r2 = \"function\" == typeof t3 ? t3 : gm(+t3), c2) : r2;\n        }, c2.y = function(t3) {\n          return arguments.length ? (i2 = \"function\" == typeof t3 ? t3 : gm(+t3), c2) : i2;\n        }, c2.context = function(n3) {\n          return arguments.length ? (null == n3 ? o2 = a2 = null : a2 = t2(o2 = n3), c2) : o2;\n        }, c2;\n      }\n      const ax = wm(3);\n      var ux = { draw(t2, n2) {\n        const e2 = 0.59436 * wm(n2 + mm(n2 / 28, 0.75)), r2 = e2 / 2, i2 = r2 * ax;\n        t2.moveTo(0, e2), t2.lineTo(0, -e2), t2.moveTo(-i2, -r2), t2.lineTo(i2, r2), t2.moveTo(-i2, r2), t2.lineTo(i2, -r2);\n      } }, cx = { draw(t2, n2) {\n        const e2 = wm(n2 / Tm);\n        t2.moveTo(e2, 0), t2.arc(0, 0, e2, 0, Sm);\n      } }, fx = { draw(t2, n2) {\n        const e2 = wm(n2 / 5) / 2;\n        t2.moveTo(-3 * e2, -e2), t2.lineTo(-e2, -e2), t2.lineTo(-e2, -3 * e2), t2.lineTo(e2, -3 * e2), t2.lineTo(e2, -e2), t2.lineTo(3 * e2, -e2), t2.lineTo(3 * e2, e2), t2.lineTo(e2, e2), t2.lineTo(e2, 3 * e2), t2.lineTo(-e2, 3 * e2), t2.lineTo(-e2, e2), t2.lineTo(-3 * e2, e2), t2.closePath();\n      } };\n      const sx = wm(1 / 3), lx = 2 * sx;\n      var hx = { draw(t2, n2) {\n        const e2 = wm(n2 / lx), r2 = e2 * sx;\n        t2.moveTo(0, -e2), t2.lineTo(r2, 0), t2.lineTo(0, e2), t2.lineTo(-r2, 0), t2.closePath();\n      } }, dx = { draw(t2, n2) {\n        const e2 = 0.62625 * wm(n2);\n        t2.moveTo(0, -e2), t2.lineTo(e2, 0), t2.lineTo(0, e2), t2.lineTo(-e2, 0), t2.closePath();\n      } }, px = { draw(t2, n2) {\n        const e2 = 0.87559 * wm(n2 - mm(n2 / 7, 2));\n        t2.moveTo(-e2, 0), t2.lineTo(e2, 0), t2.moveTo(0, e2), t2.lineTo(0, -e2);\n      } }, gx = { draw(t2, n2) {\n        const e2 = wm(n2), r2 = -e2 / 2;\n        t2.rect(r2, r2, e2, e2);\n      } }, yx = { draw(t2, n2) {\n        const e2 = 0.4431 * wm(n2);\n        t2.moveTo(e2, e2), t2.lineTo(e2, -e2), t2.lineTo(-e2, -e2), t2.lineTo(-e2, e2), t2.closePath();\n      } };\n      const vx = xm(Tm / 10) / xm(7 * Tm / 10), _x = xm(Sm / 10) * vx, bx = -_m(Sm / 10) * vx;\n      var mx = { draw(t2, n2) {\n        const e2 = wm(0.8908130915292852 * n2), r2 = _x * e2, i2 = bx * e2;\n        t2.moveTo(0, -e2), t2.lineTo(r2, i2);\n        for (let n3 = 1; n3 < 5; ++n3) {\n          const o2 = Sm * n3 / 5, a2 = _m(o2), u2 = xm(o2);\n          t2.lineTo(u2 * e2, -a2 * e2), t2.lineTo(a2 * r2 - u2 * i2, u2 * r2 + a2 * i2);\n        }\n        t2.closePath();\n      } };\n      const xx = wm(3);\n      var wx = { draw(t2, n2) {\n        const e2 = -wm(n2 / (3 * xx));\n        t2.moveTo(0, 2 * e2), t2.lineTo(-xx * e2, -e2), t2.lineTo(xx * e2, -e2), t2.closePath();\n      } };\n      const Mx = wm(3);\n      var Tx = { draw(t2, n2) {\n        const e2 = 0.6824 * wm(n2), r2 = e2 / 2,