quantile filter example.ipynb

quantile-filter-example.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/gist/iampatgrady/e27ff1818f4d6233b1a882a672f8e330/quantile-filter-example.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "93o0Q0QTM6Yp"
      },
      "outputs": [],
      "source": [
        "from google.colab import auth\n",
        "auth.authenticate_user()\n",
        "credentials = None\n",
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@markdown variables\n",
        "billable_id='as-dev-pat' #@param {type:\"string\"}\n",
        "project_id='bigquery-public-data' #@param {type:\"string\"}\n",
        "#bucket_id='as-dev-pat-mta-test' #@param {type:\"string\"}\n",
        "analytics_property='ga4_obfuscated_sample_ecommerce' #@param {type:\"string\"}\n",
        "start_date = \"2020-11-01\" #@param {type:\"date\"}\n",
        "end_date = \"2021-01-31\" #@param {type:\"date\"}\n",
        "start_date = start_date.replace(\"-\",\"\")\n",
        "end_date = end_date.replace(\"-\",\"\")\n",
        "#artifact_prefix='mta_itp_test' #@param {type:\"string\"}\n",
        "\n",
        "from google.cloud.bigquery import magics\n",
        "magics.context.project = billable_id\n",
        "\n",
        "import os\n",
        "os.environ[\"GOOGLE_CLOUD_PROJECT\"] = billable_id\n",
        "\n",
        "params = {\"start_date\": start_date, \"end_date\": end_date}"
      ],
      "metadata": {
        "id": "fUlc3oXONyze",
        "cellView": "form"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#@title  { run: \"auto\" }\n",
        "#@markdown query\n",
        "#event_list = \"buy_flow\", \"provider_cta_click\", \"call_cta_click\" #@param {type:\"raw\"}\n",
        "\n",
        "sql = '''\n",
        "WITH R AS (\n",
        "  SELECT  user_pseudo_id, max(event_timestamp) as recency \n",
        "  from (\n",
        "    SELECT event_timestamp, user_pseudo_id  FROM `{0}.{1}.events_*`\n",
        "  )\n",
        "  group by user_pseudo_id\n",
        "), F as (\n",
        "\tSELECT\n",
        "\t\tuser_pseudo_id, \n",
        "\t\tevent_timestamp, \n",
        "\t\tcount(user_pseudo_id) as totalevents \n",
        "\tfrom (\n",
        "\t\tSELECT event_timestamp, user_pseudo_id FROM `{0}.{1}.events_*` \n",
        "\t)\n",
        "\tGROUP BY user_pseudo_id, event_timestamp\n",
        "), RF AS (\n",
        "  SELECT F.user_pseudo_id, DATE(Timestamp_micros(R.recency)) as recency , \n",
        "  FROM F \n",
        "\tJOIN R ON F.user_pseudo_id=R.user_pseudo_id\n",
        "), agg_data as(\n",
        "  select \n",
        "  \tDATE_DIFF(PARSE_DATE(\"%Y%m%d\", \"{2}\"),recency,day) as recency, \n",
        "  \tcount(user_pseudo_id) as frequency, \n",
        "  \tuser_pseudo_id\n",
        "  from RF\n",
        "  group by user_pseudo_id,recency\n",
        ")\n",
        "select\n",
        "  ML.QUANTILE_BUCKETIZE(1/if(recency=0,1,recency), 5) OVER() as recency_quant_bucket, -- inverse ratio; 0,1=1\n",
        "  1/if(recency=0,1,recency) as recency_inverted, -- inverse ratio; 0,1=1,\n",
        "  recency,\n",
        "  ML.QUANTILE_BUCKETIZE(frequency, 5) OVER() frequency_quant_bucket,\n",
        "  frequency,\n",
        "  user_pseudo_id\n",
        "from agg_data\n",
        "'''\n",
        "sql = sql.format(project_id,analytics_property,end_date)\n",
        "df = pd.io.gbq.read_gbq(\n",
        "    query=sql,\n",
        "    project_id=billable_id,\n",
        "    use_bqstorage_api=True,\n",
        "    progress_bar_type=\"tqdm_notebook\",\n",
        "    credentials=credentials\n",
        "  )\n",
        "rf_df = df.copy()\n",
        "\n",
        "show_sql = False #@param {type:\"boolean\"}\n",
        "if(show_sql):\n",
        "    print(sql)"
      ],
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      "execution_count": 19,
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            "text/plain": [
              "Downloading:   0%|          |"
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    {
      "cell_type": "code",
      "source": [
        "#@title  { run: \"auto\" }\n",
        "#@markdown filter outliers\n",
        "_percentile = 96 #@param {type:\"slider\", min:80, max:100, step:1}\n",
        "rf_df_copy = rf_df.set_index('user_pseudo_id').copy()\n",
        "rf_filter = rf_df_copy[\n",
        "    (rf_df_copy.recency < np.percentile(rf_df_copy.recency,_percentile)) &\n",
        "    (rf_df_copy.frequency < np.percentile(rf_df_copy.frequency,_percentile))\n",
        "]\n",
        "print(\"started with:\", len(rf_df_copy), \"ended with:\",len(rf_filter), \"filtered:\",len(rf_df_copy)-len(rf_filter))\n",
        "_ = rf_df_copy.drop('recency_inverted', axis=1).plot(kind='hist',subplots=True,title='Before filter', figsize=(8,5),bins=16)\n",
        "_ = rf_filter.drop('recency_inverted', axis=1).plot(kind='hist',subplots=True,title='After filter', figsize=(8,5),bins=16)"
      ],
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        "id": "hHJUd68PNYj4",
        "colab": {
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          "height": 990
        },
        "cellView": "form",
        "outputId": "85222119-bf77-42c2-8c43-a2cbe825cd06"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "started with: 270154 ended with: 248241 filtered: 21913\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 2 Axes>"
            ],
            "image/png": 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NFRcXpxdffNGsCQ8P1+rVqzVu3DjNnTtXLVu21Ntvv22uES1JQ4YM0dGjRzV16lTl5+erW7duSktLc/ix4cV6AQAAqJwD3aBBg1ruBOdTeW3Ky8tdDtEWwzCMmmwK52ez2eTn56eioqIr9rAV7kQDAHBlnTx5UgcPHlR4eLi8vb1rux2cw4WuUXXzmtsscQcAAADUFYRoAAAAwEluscQdAADAteBKT7NkKuXlw51oAAAAwEmEaAAAAJxTWVlZbbfgtgjRAAAAkHR62eHExESNHTtWzZs3V0xMjHbt2qW7775bjRo1UmBgoB5++GH99NNP5nvsdrtmzpyptm3bysvLS61atdJf/vIXc/zQoUP6wx/+IH9/fzVt2lT33XeffvjhB3N85MiRGjhwoP76178qODhYzZo1U0JCgsPj0ktLSzVp0iSFhobKy8tLbdu21TvvvCPDMNS2bVv99a9/dfgc2dnZslgs+u677y7bd0WIBgAAgGnRokWyWq3auHGjXn31Vd11113q3r27tm7dqrS0NBUUFOgPf/iDWT9lyhS9+uqr+vOf/6z//Oc/WrJkifmcjfLycsXExKhx48b64osvtHHjRjVq1Ej9+/d3uMu9du1aHThwQGvXrtWiRYuUmpqq1NRUc3zEiBF6//33NW/ePH377bd688031ahRI1ksFj3yyCNKSUlx+AwpKSm6/fbb1bZt28v2PfHDQgAAAJjatWunmTNnSpJefvllde/eXa+88oo5/u677yo0NFT79u1TcHCw5s6dq/nz5ysuLk6S1KZNG/Xq1UuStHTpUtntdr399tvmo89TUlLk7++vdevWqV+/fpKkJk2aaP78+fL09FSHDh0UGxurjIwMPfbYY9q3b5+WLVum9PR0RUdHS5Kuu+46s5+RI0dq6tSp2rJli3r27Kny8nItWbKkyt3pmkaIBgAAgCkiIsL88/bt27V27Vo1atSoSt2BAwdUWFio0tJS9e3b95zH2r59u7777js1btzYYf/Jkyd14MABc/uGG25weHJgcHCwdu7cKen01AxPT0/dcccd5zxHSEiIYmNj9e6776pnz576+OOPVVpaqt///vfV/9AuIEQDAADA1LBhQ/PPxcXFuvfeezVjxowqdcHBwfr+++8veKzi4mJFRERo8eLFVcZatGhh/rl+/foOYxaLRXa7XZLk4+Nz0Z4fffRRPfzww3r99deVkpKiIUOGXPbHrhOiAQAAcE433XST/vnPfyosLEz16lWNje3atZOPj48yMjL06KOPnvP9S5cuVUBAwAUfoX0hXbp0kd1u1/r1683pHGcbMGCAGjZsqIULFyotLU0bNmxw6VzO4IeFAAAAOKeEhAQdO3ZMw4YN09dff60DBw7os88+06hRo1RRUSFvb29NmjRJEydO1HvvvacDBw7oq6++0jvvvCNJGj58uJo3b6777rtPX3zxhQ4ePKh169bpT3/6kw4fPlytHsLCwhQXF6dHHnlEK1euNI+xbNkys8bT01MjR47UlClT1K5dO0VFRV2W7+NM3IkGAAC4QuraEwRDQkK0ceNGTZo0Sf369VNpaalat26t/v37y8Pj9L3YP//5z6pXr56mTp2q3NxcBQcHa/To0ZKkBg0aaMOGDZo0aZIGDRqkEydO6De/+Y369u3r1J3phQsX6plnntEf//hH/fzzz2rVqpWeeeYZh5r4+Hi98sorGjVqVM19ARdgMQzDuCJngmw2m/z8/FRUVOTyf9Jw1pV+vOiF1LW/OAAAcMXJkyd18OBBhYeHy9vbu7bbuWZ88cUX6tu3rw4dOmQusXc+F7pG1c1r3IkGAABAnVVaWqqjR49q2rRp+v3vf3/RAF1TmBMNAACAOuv9999X69atVVhYaK5vfSUQogEAAFBnjRw5UhUVFcrKytJvfvObK3ZeQjQAAADgJEI0AADAZVD5sBC4n5q4NvywEAAAoAZZrVZ5eHgoNzdXLVq0kNVqlcViqe22IMkwDJWVleno0aPy8PCQ1Wp1+ViEaAAAgBrk4eGh8PBw5eXlKTc3t7bbwTk0aNBArVq1Mte6dgUhGgAAoIZZrVa1atVKp06dUkVFRW23gzN4enqqXr16l/xfBwjRAAAAl4HFYlH9+vVVv3792m4FlwE/LAQAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxUqyF6w4YNuvfeexUSEiKLxaKVK1c6jI8cOVIWi8Xh1b9/f4eaY8eOafjw4fL19ZW/v7/i4+NVXFzsULNjxw717t1b3t7eCg0N1cyZM6v0snz5cnXo0EHe3t7q0qWLPvnkE4dxwzA0depUBQcHy8fHR9HR0dq/f3/NfBEAAACoU2o1RJeUlKhr165asGDBeWv69++vvLw88/X+++87jA8fPly7d+9Wenq6Vq1apQ0bNujxxx83x202m/r166fWrVsrKytLs2bN0rRp0/TWW2+ZNZs2bdKwYcMUHx+vbdu2aeDAgRo4cKB27dpl1sycOVPz5s1TcnKyNm/erIYNGyomJkYnT56swW8EAAAAdYHFMAyjtpuQTj9ffsWKFRo4cKC5b+TIkSosLKxyh7rSt99+q06dOunrr79Wjx49JElpaWkaMGCADh8+rJCQEC1cuFDPPvus8vPzZbVaJUmTJ0/WypUrtWfPHknSkCFDVFJSolWrVpnHvuWWW9StWzclJyfLMAyFhIRo/PjxmjBhgiSpqKhIgYGBSk1N1dChQ6v1GW02m/z8/FRUVCRfX19nvyKXhE1efUXOUx0/vBpb2y0AAABcUHXzmtvPiV63bp0CAgLUvn17Pfnkk/r555/NsczMTPn7+5sBWpKio6Pl4eGhzZs3mzW33367GaAlKSYmRnv37tXx48fNmujoaIfzxsTEKDMzU5J08OBB5efnO9T4+fkpMjLSrDmX0tJS2Ww2hxcAAADqPrcO0f3799d7772njIwMzZgxQ+vXr9fdd9+tiooKSVJ+fr4CAgIc3lOvXj01bdpU+fn5Zk1gYKBDTeX2xWrOHD/zfeeqOZfp06fLz8/PfIWGhjr1+QEAAOCe6tV2Axdy5jSJLl266MYbb1SbNm20bt069e3btxY7q54pU6YoKSnJ3LbZbARpAACAq4Bb34k+23XXXafmzZvru+++kyQFBQXpyJEjDjWnTp3SsWPHFBQUZNYUFBQ41FRuX6zmzPEz33eumnPx8vKSr6+vwwsAAAB1X50K0YcPH9bPP/+s4OBgSVJUVJQKCwuVlZVl1qxZs0Z2u12RkZFmzYYNG1ReXm7WpKenq3379mrSpIlZk5GR4XCu9PR0RUVFSZLCw8MVFBTkUGOz2bR582azBgAAANeOWg3RxcXFys7OVnZ2tqTTP+DLzs5WTk6OiouL9fTTT+urr77SDz/8oIyMDN13331q27atYmJiJEkdO3ZU//799dhjj2nLli3auHGjEhMTNXToUIWEhEiSHnzwQVmtVsXHx2v37t1aunSp5s6d6zDNYsyYMUpLS9Nrr72mPXv2aNq0adq6dasSExMlnV45ZOzYsXr55Zf10UcfaefOnRoxYoRCQkIcVhMBAADAtaFW50Rv3bpVffr0Mbcrg21cXJwWLlyoHTt2aNGiRSosLFRISIj69eunl156SV5eXuZ7Fi9erMTERPXt21ceHh4aPHiw5s2bZ477+fnp888/V0JCgiIiItS8eXNNnTrVYS3pW2+9VUuWLNFzzz2nZ555Ru3atdPKlSvVuXNns2bixIkqKSnR448/rsLCQvXq1UtpaWny9va+nF8RAAAA3JDbrBN9LWCdaNaJBgAA7u2yrhP9/fffu9wYAAAAUNe5FKLbtm2rPn366B//+AePvQYAAMA1x6UQ/c033+jGG29UUlKSgoKC9MQTT2jLli013RsAAADgllwK0d26ddPcuXOVm5urd999V3l5eerVq5c6d+6s2bNn6+jRozXdJwAAAOA2LmmJu3r16mnQoEFavny5ZsyYoe+++04TJkxQaGioRowYoby8vJrqEwAAAHAblxSit27dqj/+8Y8KDg7W7NmzNWHCBB04cEDp6enKzc3VfffdV1N9AgAAAG7DpXWiZ8+erZSUFO3du1cDBgzQe++9pwEDBsjD43QmDw8PV2pqqsLCwmqyVwAAAMAtuBSiFy5cqEceeUQjR440H8F9toCAAL3zzjuX1BwAAADgjlwK0fv3779ojdVqVVxcnCuHBwAAANyaS3OiU1JStHz58ir7ly9frkWLFl1yUwAAAIA7cylET58+Xc2bN6+yPyAgQK+88solNwUAAAC4M5dCdE5OjsLDw6vsb926tXJyci65KQAAAMCduRSiAwICtGPHjir7t2/frmbNml1yUwAAAIA7cylEDxs2TH/605+0du1aVVRUqKKiQmvWrNGYMWM0dOjQmu4RAAAAcCsurc7x0ksv6YcfflDfvn1Vr97pQ9jtdo0YMYI50QAAALjquRSirVarli5dqpdeeknbt2+Xj4+PunTpotatW9d0fwAAAIDbcSlEV7r++ut1/fXX11QvAAAAQJ3gUoiuqKhQamqqMjIydOTIEdntdofxNWvW1EhzAAAAgDtyKUSPGTNGqampio2NVefOnWWxWGq6LwAAAMBtuRSiP/jgAy1btkwDBgyo6X4AAAAAt+fSEndWq1Vt27at6V4AAACAOsGlED1+/HjNnTtXhmHUdD8AAACA23NpOseXX36ptWvX6tNPP9UNN9yg+vXrO4x/+OGHNdIcAAAA4I5cCtH+/v66//77a7oXAAAAoE5wKUSnpKTUdB8AAABAneHSnGhJOnXqlP7973/rzTff1IkTJyRJubm5Ki4urrHmAAAAAHfk0p3oH3/8Uf3791dOTo5KS0v129/+Vo0bN9aMGTNUWlqq5OTkmu4TAAAAcBsu3YkeM2aMevTooePHj8vHx8fcf//99ysjI6PGmgMAAADckUt3or/44gtt2rRJVqvVYX9YWJj++9//1khjAAAAgLty6U603W5XRUVFlf2HDx9W48aNL7kpAAAAwJ25FKL79eunOXPmmNsWi0XFxcV6/vnneRQ4AAAArnouhejXXntNGzduVKdOnXTy5Ek9+OCD5lSOGTNmVPs4GzZs0L333quQkBBZLBatXLnSYdwwDE2dOlXBwcHy8fFRdHS09u/f71Bz7NgxDR8+XL6+vvL391d8fHyVFUJ27Nih3r17y9vbW6GhoZo5c2aVXpYvX64OHTrI29tbXbp00SeffOJ0LwAAALg2uBSiW7Zsqe3bt+uZZ57RuHHj1L17d7366qvatm2bAgICqn2ckpISde3aVQsWLDjn+MyZMzVv3jwlJydr8+bNatiwoWJiYnTy5EmzZvjw4dq9e7fS09O1atUqbdiwQY8//rg5brPZ1K9fP7Vu3VpZWVmaNWuWpk2bprfeesus2bRpk4YNG6b4+Hht27ZNAwcO1MCBA7Vr1y6negEAAMC1wWIYhlHbTUinp4SsWLFCAwcOlHT6zm9ISIjGjx+vCRMmSJKKiooUGBio1NRUDR06VN9++606deqkr7/+Wj169JAkpaWlacCAATp8+LBCQkK0cOFCPfvss8rPzzd/CDl58mStXLlSe/bskSQNGTJEJSUlWrVqldnPLbfcom7duik5OblavVSHzWaTn5+fioqK5OvrWyPf28WETV59Rc5THT+8GlvbLQAAAFxQdfOaS6tzvPfeexccHzFihCuHdXDw4EHl5+crOjra3Ofn56fIyEhlZmZq6NChyszMlL+/vxmgJSk6OloeHh7avHmz7r//fmVmZur22293WEkkJiZGM2bM0PHjx9WkSRNlZmYqKSnJ4fwxMTHm9JLq9HIupaWlKi0tNbdtNtslfScAAABwDy6F6DFjxjhsl5eX65dffpHValWDBg1qJETn5+dLkgIDAx32BwYGmmP5+flVpo/Uq1dPTZs2dagJDw+vcozKsSZNmig/P/+i57lYL+cyffp0vfDCCxf/sAAAAKhTXJoTffz4cYdXcXGx9u7dq169eun999+v6R7rrClTpqioqMh8HTp0qLZbAgAAQA1wKUSfS7t27fTqq69WuUvtqqCgIElSQUGBw/6CggJzLCgoSEeOHHEYP3XqlI4dO+ZQc65jnHmO89WcOX6xXs7Fy8tLvr6+Di8AAADUfTUWoqXTUylyc3Nr5Fjh4eEKCgpyeIy4zWbT5s2bFRUVJUmKiopSYWGhsrKyzJo1a9bIbrcrMjLSrNmwYYPKy8vNmvT0dLVv315NmjQxa85+XHl6erp5nur0AgAAgGuHS3OiP/roI4dtwzCUl5en+fPn67bbbqv2cYqLi/Xdd9+Z2wcPHlR2draaNm2qVq1aaezYsXr55ZfVrl07hYeH689//rNCQkLMFTw6duyo/v3767HHHlNycrLKy8uVmJiooUOHKiQkRJL04IMP6oUXXlB8fLwmTZqkXbt2ae7cuXr99dfN844ZM0Z33HGHXnvtNcXGxuqDDz7Q1q1bzWXwLBbLRXsBAADAtcOlEH12cLRYLGrRooXuuusuvfbaa9U+ztatW9WnTx9zu3KFjLi4OKWmpmrixIkqKSnR448/rsLCQvXq1UtpaWny9vY237N48WIlJiaqb9++8vDw0ODBgzVv3jxz3M/PT59//rkSEhIUERGh5s2ba+rUqQ5rSd96661asmSJnnvuOT3zzDNq166dVq5cqc6dO5s11ekFAAAA1wa3WSf6WsA60awTDQAA3Ft181qNzokGAAAArgUuTec4+8EkFzJ79mxXTgEAAAC4LZdC9LZt27Rt2zaVl5erffv2kqR9+/bJ09NTN910k1lnsVhqpksAAADAjbgUou+99141btxYixYtMpeJO378uEaNGqXevXtr/PjxNdokAAAA4E5cmhP92muvafr06WaAlqQmTZro5Zdfdmp1DgAAAKAucilE22w2HT16tMr+o0eP6sSJE5fcFAAAAODOXArR999/v0aNGqUPP/xQhw8f1uHDh/XPf/5T8fHxGjRoUE33CAAAALgVl+ZEJycna8KECXrwwQfNx2nXq1dP8fHxmjVrVo02CAAAALgbl0J0gwYN9MYbb2jWrFk6cOCAJKlNmzZq2LBhjTYHAAAAuKNLethKXl6e8vLy1K5dOzVs2FA8/BAAAADXApdC9M8//6y+ffvq+uuv14ABA5SXlydJio+PZ3k7AAAAXPVcCtHjxo1T/fr1lZOTowYNGpj7hwwZorS0tBprDgAAAHBHLs2J/vzzz/XZZ5+pZcuWDvvbtWunH3/8sUYaAwAAANyVS3eiS0pKHO5AVzp27Ji8vLwuuSkAAADAnbkUonv37q333nvP3LZYLLLb7Zo5c6b69OlTY80BAAAA7sil6RwzZ85U3759tXXrVpWVlWnixInavXu3jh07po0bN9Z0j7hKhE1eXdstOPjh1djabgEAANRRLt2J7ty5s/bt26devXrpvvvuU0lJiQYNGqRt27apTZs2Nd0jAAAA4FacvhNdXl6u/v37Kzk5Wc8+++zl6AkAAABwa07fia5fv7527NhxOXoBAAAA6gSXpnM89NBDeuedd2q6FwAAAKBOcOmHhadOndK7776rf//734qIiFDDhg0dxmfPnl0jzQEAAADuyKkQ/f333yssLEy7du3STTfdJEnat2+fQ43FYqm57gAAAAA35FSIbteunfLy8rR27VpJpx/zPW/ePAUGBl6W5gAAAAB35NScaMMwHLY//fRTlZSU1GhDAAAAgLtz6YeFlc4O1QAAAMC1wKkQbbFYqsx5Zg40AAAArjVOzYk2DEMjR46Ul5eXJOnkyZMaPXp0ldU5Pvzww5rrEAAAAHAzToXouLg4h+2HHnqoRpsBAAAA6gKnQnRKSsrl6gMAAACoMy7ph4UAAADAtYgQDQAAADiJEA0AAAA4ya1D9LRp08xl9SpfHTp0MMdPnjyphIQENWvWTI0aNdLgwYNVUFDgcIycnBzFxsaqQYMGCggI0NNPP61Tp0451Kxbt0433XSTvLy81LZtW6WmplbpZcGCBQoLC5O3t7ciIyO1ZcuWy/KZAQAA4P7cOkRL0g033KC8vDzz9eWXX5pj48aN08cff6zly5dr/fr1ys3N1aBBg8zxiooKxcbGqqysTJs2bdKiRYuUmpqqqVOnmjUHDx5UbGys+vTpo+zsbI0dO1aPPvqoPvvsM7Nm6dKlSkpK0vPPP69vvvlGXbt2VUxMjI4cOXJlvgQAAAC4FYvhxo8dnDZtmlauXKns7OwqY0VFRWrRooWWLFmiBx54QJK0Z88edezYUZmZmbrlllv06aef6p577lFubq4CAwMlScnJyZo0aZKOHj0qq9WqSZMmafXq1dq1a5d57KFDh6qwsFBpaWmSpMjISN18882aP3++JMlutys0NFRPPfWUJk+eXO3PY7PZ5Ofnp6KiIvn6+rr6tTglbPLqK3KeuuiHV2NruwUAAOBmqpvX3P5O9P79+xUSEqLrrrtOw4cPV05OjiQpKytL5eXlio6ONms7dOigVq1aKTMzU5KUmZmpLl26mAFakmJiYmSz2bR7926z5sxjVNZUHqOsrExZWVkONR4eHoqOjjZrzqe0tFQ2m83hBQAAgLrPrUN0ZGSkUlNTlZaWpoULF+rgwYPq3bu3Tpw4ofz8fFmtVvn7+zu8JzAwUPn5+ZKk/Px8hwBdOV45dqEam82mX3/9VT/99JMqKirOWVN5jPOZPn26/Pz8zFdoaKjT3wEAAADcj1MPW7nS7r77bvPPN954oyIjI9W6dWstW7ZMPj4+tdhZ9UyZMkVJSUnmts1mI0gDAABcBdz6TvTZ/P39df311+u7775TUFCQysrKVFhY6FBTUFCgoKAgSVJQUFCV1Toqty9W4+vrKx8fHzVv3lyenp7nrKk8xvl4eXnJ19fX4QUAAIC6r06F6OLiYh04cEDBwcGKiIhQ/fr1lZGRYY7v3btXOTk5ioqKkiRFRUVp586dDqtopKeny9fXV506dTJrzjxGZU3lMaxWqyIiIhxq7Ha7MjIyzBoAAABcW9w6RE+YMEHr16/XDz/8oE2bNun++++Xp6enhg0bJj8/P8XHxyspKUlr165VVlaWRo0apaioKN1yyy2SpH79+qlTp056+OGHtX37dn322Wd67rnnlJCQIC8vL0nS6NGj9f3332vixInas2eP3njjDS1btkzjxo0z+0hKStLf//53LVq0SN9++62efPJJlZSUaNSoUbXyvQAAAKB2ufWc6MOHD2vYsGH6+eef1aJFC/Xq1UtfffWVWrRoIUl6/fXX5eHhocGDB6u0tFQxMTF64403zPd7enpq1apVevLJJxUVFaWGDRsqLi5OL774olkTHh6u1atXa9y4cZo7d65atmypt99+WzExMWbNkCFDdPToUU2dOlX5+fnq1q2b0tLSqvzYEAAAANcGt14n+mrDOtHuhXWiAQDA2a6adaIBAAAAd0OIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiHbSggULFBYWJm9vb0VGRmrLli213RIAAACuMEK0E5YuXaqkpCQ9//zz+uabb9S1a1fFxMToyJEjtd0aAAAArqB6td1AXTJ79mw99thjGjVqlCQpOTlZq1ev1rvvvqvJkydXqS8tLVVpaam5XVRUJEmy2WxXpmFJ9tJfrti56poreR0AAEDdUJkPDMO4YB0huprKysqUlZWlKVOmmPs8PDwUHR2tzMzMc75n+vTpeuGFF6rsDw0NvWx9ovr85tR2BwAAwF2dOHFCfn5+5x0nRFfTTz/9pIqKCgUGBjrsDwwM1J49e875nilTpigpKcncttvtOnbsmJo1ayaLxXJZ+5VO/5tUaGioDh06JF9f38t+PlweXMerA9fx6sB1vDpwHeu+y3kNDcPQiRMnFBIScsE6QvRl5OXlJS8vL4d9/v7+V7wPX19f/pK4CnAdrw5cx6sD1/HqwHWs+y7XNbzQHehK/LCwmpo3by5PT08VFBQ47C8oKFBQUFAtdQUAAIDaQIiuJqvVqoiICGVkZJj77Ha7MjIyFBUVVYudAQAA4EpjOocTkpKSFBcXpx49eqhnz56aM2eOSkpKzNU63I2Xl5eef/75KlNKULdwHa8OXMerA9fx6sB1rPvc4RpajIut3wEH8+fP16xZs5Sfn69u3bpp3rx5ioyMrO22AAAAcAURogEAAAAnMScaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHASIRoAAABwEiEaAAAAcBIhGgAAAHBSvdpu4Fpit9uVm5urxo0by2Kx1HY7AAAAOIthGDpx4oRCQkLk4XH++82E6CsoNzdXoaGhtd0GAAAALuLQoUNq2bLleccJ0VdQ48aNJZ2+KL6+vrXcDQAAAM5ms9kUGhpq5rbzIURfQZVTOHx9fQnRAAAAbuxiU2/5YSEAAADgJEI0AAAA4CRCNAAAAOAk5kQDAABcQEVFhcrLy2u7DdSQ+vXry9PT85KPQ4gGAAA4B8MwlJ+fr8LCwtpuBTXM399fQUFBl/TcDkI0AADAOVQG6ICAADVo0IAHpV0FDMPQL7/8oiNHjkiSgoODXT4WIfpqN82vtjv4P9OKarsDAACqpaKiwgzQzZo1q+12UIN8fHwkSUeOHFFAQIDLUzv4YSEAAMBZKudAN2jQoJY7weVQeV0vZa47IRoAAOA8mMJxdaqJ61qrIXr69Om6+eab1bhxYwUEBGjgwIHau3evQ82dd94pi8Xi8Bo9erRDTU5OjmJjY9WgQQMFBATo6aef1qlTpxxq1q1bp5tuukleXl5q27atUlNTq/SzYMEChYWFydvbW5GRkdqyZYvD+MmTJ5WQkKBmzZqpUaNGGjx4sAoKCmrmywAAAECdUashev369UpISNBXX32l9PR0lZeXq1+/fiopKXGoe+yxx5SXl2e+Zs6caY5VVFQoNjZWZWVl2rRpkxYtWqTU1FRNnTrVrDl48KBiY2PVp08fZWdna+zYsXr00Uf12WefmTVLly5VUlKSnn/+eX3zzTfq2rWrYmJizInnkjRu3Dh9/PHHWr58udavX6/c3FwNGjToMn5DAAAAcEcWwzCM2m6i0tGjRxUQEKD169fr9ttvl3T6TnS3bt00Z86cc77n008/1T333KPc3FwFBgZKkpKTkzVp0iQdPXpUVqtVkyZN0urVq7Vr1y7zfUOHDlVhYaHS0tIkSZGRkbr55ps1f/58SZLdbldoaKieeuopTZ48WUVFRWrRooWWLFmiBx54QJK0Z88edezYUZmZmbrlllsu+vlsNpv8/PxUVFQkX19fl78np/DDQgAAnHby5EkdPHhQ4eHh8vb2dhy80v9sdfKfn4Zh6IknntD//u//6vjx49q2bZu6det2eXqroy50faub19xqTnRR0en/kzRt2tRh/+LFi9W8eXN17txZU6ZM0S+//GKOZWZmqkuXLmaAlqSYmBjZbDbt3r3brImOjnY4ZkxMjDIzMyVJZWVlysrKcqjx8PBQdHS0WZOVlaXy8nKHmg4dOqhVq1ZmzdlKS0tls9kcXgAAAJdTWlqaUlNTtWrVKuXl5alz58613dJVyW2WuLPb7Ro7dqxuu+02h4v94IMPqnXr1goJCdGOHTs0adIk7d27Vx9++KGk02s4nhmgJZnb+fn5F6yx2Wz69ddfdfz4cVVUVJyzZs+ePeYxrFar/P39q9RUnuds06dP1wsvvODkNwEAAOC6AwcOKDg4WLfeeus5x8vKymS1Wq9wV1cft7kTnZCQoF27dumDDz5w2P/4448rJiZGXbp00fDhw/Xee+9pxYoVOnDgQC11Wn1TpkxRUVGR+Tp06FBttwQAAK5iI0eO1FNPPaWcnBxZLBaFhYXpzjvvVGJiosaOHavmzZsrJiZGkrRr1y7dfffdatSokQIDA/Xwww/rp59+Mo9VUlKiESNGqFGjRgoODtZrr72mO++8U2PHjjVrLBaLVq5c6dCDv7+/wwIOhw4d0h/+8Af5+/uradOmuu+++/TDDz849Dxw4ED99a9/VXBwsJo1a6aEhASH5edKS0s1adIkhYaGmotEvPPOOzIMQ23bttVf//pXhx6ys7NlsVj03XffXfqXeh5uEaITExO1atUqrV27Vi1btrxgbWRkpCSZX0pQUFCVFTIqt4OCgi5Y4+vrKx8fHzVv3lyenp7nrDnzGGVlZVUe/Xlmzdm8vLzk6+vr8AIAALhc5s6dqxdffFEtW7ZUXl6evv76a0nSokWLZLVatXHjRiUnJ6uwsFB33XWXunfvrq1btyotLU0FBQX6wx/+YB7r6aef1vr16/Wvf/1Ln3/+udatW6dvvvnGqX7Ky8sVExOjxo0b64svvtDGjRvVqFEj9e/fX2VlZWbd2rVrdeDAAa1du9ZcJOLMID5ixAi9//77mjdvnr799lu9+eabatSokSwWix555BGlpKQ4nDclJUW333672rZt68K3WD21GqINw1BiYqJWrFihNWvWKDw8/KLvyc7OlvR/j2mMiorSzp07HVbRSE9Pl6+vrzp16mTWZGRkOBwnPT1dUVFRkiSr1aqIiAiHGrvdroyMDLMmIiJC9evXd6jZu3evcnJyzBoAAIDa5Ofnp8aNG8vT01NBQUFq0aKFJKldu3aaOXOm2rdvr/bt22v+/Pnq3r27XnnlFXXo0EHdu3fXu+++q7Vr12rfvn0qLi7WO++8o7/+9a/q27evunTpokWLFlVZQvhili5dKrvdrrfffltdunRRx44dlZKSopycHK1bt86sa9KkiebPn68OHTronnvuUWxsrJm59u3bp2XLlundd9/V/fffr+uuu059+/bVkCFDJJ2+k713715zaeLy8nItWbJEjzzySA18o+dXq3OiExIStGTJEv3rX/9S48aNzbnFfn5+8vHx0YEDB7RkyRINGDBAzZo1044dOzRu3DjdfvvtuvHGGyVJ/fr1U6dOnfTwww9r5syZys/P13PPPaeEhAR5eXlJkkaPHq358+dr4sSJeuSRR7RmzRotW7ZMq1evNntJSkpSXFycevTooZ49e2rOnDkqKSnRqFGjzJ7i4+OVlJSkpk2bytfXV0899ZSioqKqtTIHAABAbYmIiHDY3r59u9auXatGjRpVqT1w4IB+/fVXlZWVmTMApNMLP7Rv396p827fvl3fffedGjdu7LD/5MmTDlNzb7jhBofHbwcHB2vnzp2STt9A9fT01B133HHOc4SEhCg2NlbvvvuuevbsqY8//lilpaX6/e9/71SvzqrVEL1w4UJJp5exO1NKSopGjhwpq9Wqf//732agDQ0N1eDBg/Xcc8+ZtZ6enlq1apWefPJJRUVFqWHDhoqLi9OLL75o1oSHh2v16tUaN26c5s6dq5YtW+rtt9825wRJ0pAhQ3T06FFNnTpV+fn56tatm9LS0hx+bPj666/Lw8NDgwcPVmlpqWJiYvTGG29cpm8HAACgZjRs2NBhu7i4WPfee69mzJhRpTY4OLjac4ktFovOXi35zLnMxcXFioiI0OLFi6u8t/IuuSTVr1+/ynHtdrskycfH56J9PProo3r44Yf1+uuvKyUlRUOGDLnsj2yv1RB9sSWqQ0NDtX79+osep3Xr1vrkk08uWHPnnXdq27ZtF6xJTExUYmLiece9vb21YMECLViw4KI9AQAAuKubbrpJ//znPxUWFqZ69arGwTZt2qh+/fravHmzWrVqJUk6fvy49u3b53BHuEWLFsrLyzO39+/f77AU8U033aSlS5cqICDA5d+GdenSRXa7XevXr6+yZHGlAQMGqGHDhlq4cKHS0tK0YcMGl87lDLf4YSEAAACunISEBB07dkzDhg3T119/rQMHDuizzz7TqFGjVFFRoUaNGik+Pl5PP/201qxZo127dmnkyJHy8HCMjnfddZfmz5+vbdu2aevWrRo9erTDXeXhw4erefPmuu+++/TFF1/o4MGDWrdunf70pz/p8OHD1eo1LCxMcXFxeuSRR7Ry5UrzGMuWLTNrPD09NXLkSE2ZMkXt2rW7Ir9Xc5t1ogEAAOqEq+AJvCEhIdq4caMmTZqkfv36qbS0VK1bt1b//v3NoDxr1ixz2kfjxo01fvx488F4lV577TWNGjVKvXv3VkhIiObOnausrCxzvEGDBtqwYYMmTZqkQYMG6cSJE/rNb36jvn37OnVneuHChXrmmWf0xz/+UT///LNatWqlZ555xqEmPj5er7zyivl7tsvNrR77fbXjsd91/y8dAMC14YKP/b6G3XnnnerWrZvmzJlT261U8cUXX6hv3746dOhQlQfona0mHvvNnWgAAADUWaWlpTp69KimTZum3//+9xcN0DWFOdEAAACos95//321bt1ahYWFmjlz5hU7L3eiAQAAUC1nPiDFXYwcOVIjR4684uflTjQAAADgJEI0AADAeVQ+8ANXl5q4rkznAAAAOIvVapWHh4dyc3PVokULWa1WWSyW2m4Ll8gwDJWVleno0aPy8PCQ1Wp1+ViEaAAAgLN4eHgoPDxceXl5ys3Nre12UMMaNGigVq1aVXl4jDMI0QAAAOdgtVrVqlUrnTp1ShUVFbXdDmqIp6en6tWrd8n/ZYEQDQAAcB4Wi0X169d3eJQ1IPHDQgAAAMBphGgAAADASYRoAAAAwEmEaAAAAMBJhGgAAADASYRoAAAAwEmEaAAAAMBJhGgAAADASYRoAAAAwEm1GqKnT5+um2++WY0bN1ZAQIAGDhyovXv3OtScPHlSCQkJatasmRo1aqTBgweroKDAoSYnJ0exsbFq0KCBAgIC9PTTT+vUqVMONevWrdNNN90kLy8vtW3bVqmpqVX6WbBggcLCwuTt7a3IyEht2bLF6V4AAABw9avVEL1+/XolJCToq6++Unp6usrLy9WvXz+VlJSYNePGjdPHH3+s5cuXa/369crNzdWgQYPM8YqKCsXGxqqsrEybNm3SokWLlJqaqqlTp5o1Bw8eVGxsrPr06aPs7GyNHTtWjz76qD777DOzZunSpUpKStLzzz+vb775Rl27dlVMTIyOHDlS7V4AAABwbbAYhmHUdhOVjh49qoCAAK1fv1633367ioqK1KJFCy1ZskQPPPCAJGnPnj3q2LGjMjMzdcstt+jTTz/VPffco9zcXAUGBkqSkpOTNWnSJB09elRWq1WTJk3S6tWrtWvXLvNcQ4cOVWFhodLS0iRJkZGRuvnmmzV//nxJkt1uV2hoqJ566ilNnjy5Wr1cjM1mk5+fn4qKiuTr61uj3915TfO7MuepjmlFtd0BAADABVU3r7nVnOiiotMhq2nTppKkrKwslZeXKzo62qzp0KGDWrVqpczMTElSZmamunTpYgZoSYqJiZHNZtPu3bvNmjOPUVlTeYyysjJlZWU51Hh4eCg6OtqsqU4vZystLZXNZnN4AQAAoO5zmxBtt9s1duxY3XbbbercubMkKT8/X1arVf7+/g61gYGBys/PN2vODNCV45VjF6qx2Wz69ddf9dNPP6miouKcNWce42K9nG369Ony8/MzX6GhodX8NgAAAODO3CZEJyQkaNeuXfrggw9qu5UaM2XKFBUVFZmvQ4cO1XZLAAAAqAH1arsBSUpMTNSqVau0YcMGtWzZ0twfFBSksrIyFRYWOtwBLigoUFBQkFlz9ioalStmnFlz9ioaBQUF8vX1lY+Pjzw9PeXp6XnOmjOPcbFezubl5SUvLy8nvgkAAADUBbV6J9owDCUmJmrFihVas2aNwsPDHcYjIiJUv359ZWRkmPv27t2rnJwcRUVFSZKioqK0c+dOh1U00tPT5evrq06dOpk1Zx6jsqbyGFarVREREQ41drtdGRkZZk11egEAAMC1oVbvRCckJGjJkiX617/+pcaNG5tzi/38/OTj4yM/Pz/Fx8crKSlJTZs2la+vr5566ilFRUWZq2H069dPnTp10sMPP6yZM2cqPz9fzz33nBISEsy7wKNHj9b8+fM1ceJEPfLII1qzZo2WLVum1atXm70kJSUpLi5OPXr0UM+ePTVnzhyVlJRo1KhRZk8X6wUAAADXhloN0QsXLpQk3XnnnQ77U1JSNHLkSEnS66+/Lg8PDw0ePFilpaWKiYnRG2+8YdZ6enpq1apVevLJJxUVFaWGDRsqLi5OL774olkTHh6u1atXa9y4cZo7d65atmypt99+WzExMWbNkCFDdPToUU2dOlX5+fnq1q2b0tLSHH5seLFeAAAAcG1wq3Wir3asE8060QAAwL1d1nWiv//+e5cbAwAAAOo6l0J027Zt1adPH/3jH//QyZMna7onAAAAwK25FKK/+eYb3XjjjUpKSlJQUJCeeOKJKsvMAQAAAFcrl0J0t27dNHfuXOXm5urdd99VXl6eevXqpc6dO2v27Nk6evRoTfcJAAAAuI1LWie6Xr16GjRokJYvX64ZM2bou+++04QJExQaGqoRI0YoLy+vpvoEAAAA3MYlheitW7fqj3/8o4KDgzV79mxNmDBBBw4cUHp6unJzc3XffffVVJ8AAACA23BpnejZs2crJSVFe/fu1YABA/Tee+9pwIAB8vA4ncnDw8OVmpqqsLCwmuwVAAAAcAsuheiFCxfqkUce0ciRIxUcHHzOmoCAAL3zzjuX1BwAAADgjlwK0fv3779ojdVqVVxcnCuHBwAAANyaS3OiU1JStHz58ir7ly9frkWLFl1yUwAAAIA7cylET58+Xc2bN6+yPyAgQK+88solNwUAAAC4M5dCdE5OjsLDw6vsb926tXJyci65KQAAAMCduRSiAwICtGPHjir7t2/frmbNml1yUwAAAIA7cylEDxs2TH/605+0du1aVVRUqKKiQmvWrNGYMWM0dOjQmu4RAAAAcCsurc7x0ksv6YcfflDfvn1Vr97pQ9jtdo0YMYI50QAAALjquRSirVarli5dqpdeeknbt2+Xj4+PunTpotatW9d0fwAAAIDbcSlEV7r++ut1/fXX11QvAAAAQJ3gUoiuqKhQamqqMjIydOTIEdntdofxNWvW1EhzAAAAgDtyKUSPGTNGqampio2NVefOnWWxWGq6LwAAAMBtuRSiP/jgAy1btkwDBgyo6X4AAAAAt+fSEndWq1Vt27at6V4AAACAOsGlED1+/HjNnTtXhmFc0sk3bNige++9VyEhIbJYLFq5cqXD+MiRI2WxWBxe/fv3d6g5duyYhg8fLl9fX/n7+ys+Pl7FxcUONTt27FDv3r3l7e2t0NBQzZw5s0ovy5cvV4cOHeTt7a0uXbrok08+cRg3DENTp05VcHCwfHx8FB0drf3791/S5wcAAEDd5FKI/vLLL7V48WK1adNG9957rwYNGuTwqq6SkhJ17dpVCxYsOG9N//79lZeXZ77ef/99h/Hhw4dr9+7dSk9P16pVq7RhwwY9/vjj5rjNZlO/fv3UunVrZWVladasWZo2bZreeusts2bTpk0aNmyY4uPjtW3bNg0cOFADBw7Url27zJqZM2dq3rx5Sk5O1ubNm9WwYUPFxMTo5MmT1f68AAAAuDpYDBduJ48aNeqC4ykpKc43YrFoxYoVGjhwoLlv5MiRKiwsrHKHutK3336rTp066euvv1aPHj0kSWlpaRowYIAOHz6skJAQLVy4UM8++6zy8/NltVolSZMnT9bKlSu1Z88eSdKQIUNUUlKiVatWmce+5ZZb1K1bNyUnJ8swDIWEhGj8+PGaMGGCJKmoqEiBgYFKTU2t9lMabTab/Pz8VFRUJF9fX2e/ItdM87sy56mOaUW13QEAAMAFVTevufTDQldCsqvWrVungIAANWnSRHfddZdefvllNWvWTJKUmZkpf39/M0BLUnR0tDw8PLR582bdf//9yszM1O23324GaEmKiYnRjBkzdPz4cTVp0kSZmZlKSkpyOG9MTIwZ3g8ePKj8/HxFR0eb435+foqMjFRmZuZ5Q3RpaalKS0vNbZvNdsnfBwAAAGqfS9M5JOnUqVP697//rTfffFMnTpyQJOXm5laZj3wp+vfvr/fee08ZGRmaMWOG1q9fr7vvvlsVFRWSpPz8fAUEBDi8p169emratKny8/PNmsDAQIeayu2L1Zw5fub7zlVzLtOnT5efn5/5Cg0NderzAwAAwD25dCf6xx9/VP/+/ZWTk6PS0lL99re/VePGjTVjxgyVlpYqOTm5Rpo78w5vly5ddOONN6pNmzZat26d+vbtWyPnuJymTJnicIfbZrMRpAEAAK4CLt2JHjNmjHr06KHjx4/Lx8fH3H///fcrIyOjxpo723XXXafmzZvru+++kyQFBQXpyJEjDjWnTp3SsWPHFBQUZNYUFBQ41FRuX6zmzPEz33eumnPx8vKSr6+vwwsAAAB1n0sh+osvvtBzzz3nMM9YksLCwvTf//63Rho7l8OHD+vnn39WcHCwJCkqKkqFhYXKysoya9asWSO73a7IyEizZsOGDSovLzdr0tPT1b59ezVp0sSsOTv8p6enKyoqSpIUHh6uoKAghxqbzabNmzebNQAAALh2uBSi7Xa7OS/5TIcPH1bjxo2rfZzi4mJlZ2crOztb0ukf8GVnZysnJ0fFxcV6+umn9dVXX+mHH35QRkaG7rvvPrVt21YxMTGSpI4dO6p///567LHHtGXLFm3cuFGJiYkaOnSoQkJCJEkPPvigrFar4uPjtXv3bi1dulRz5851mGYxZswYpaWl6bXXXtOePXs0bdo0bd26VYmJiZJOrxwyduxYvfzyy/roo4+0c+dOjRgxQiEhIQ6riQAAAODa4FKI7tevn+bMmWNuWywWFRcX6/nnn3fqUeBbt25V9+7d1b17d0lSUlKSunfvrqlTp8rT01M7duzQ7373O11//fWKj49XRESEvvjiC3l5eZnHWLx4sTp06KC+fftqwIAB6tWrl8Ma0H5+fvr888918OBBRUREaPz48Zo6darDWtK33nqrlixZorfeektdu3bV//7v/2rlypXq3LmzWTNx4kQ99dRTevzxx3XzzTeruLhYaWlp8vb2duUrBAAAQB3m0jrRhw8fVkxMjAzD0P79+9WjRw/t379fzZs314YNG6qsmIHTWCeadaIBAIB7u6zrRLds2VLbt2/XBx98oB07dqi4uFjx8fEaPny4ww8NAQAAgKuRSyFaOr0e80MPPVSTvQAAAAB1gksh+r333rvg+IgRI1xqBgAAAKgLXArRY8aMcdguLy/XL7/8IqvVqgYNGhCiAQAAcFVzaXWO48ePO7yKi4u1d+9e9erVS++//35N9wgAAAC4FZdC9Lm0a9dOr776apW71AAAAMDVpsZCtHT6x4a5ubk1eUgAAADA7bg0J/qjjz5y2DYMQ3l5eZo/f75uu+22GmkMAAAAcFcuheizH3VtsVjUokUL3XXXXXrttddqoi8AAADAbbkUou12e033AQAAANQZNTonGgAAALgWuHQnOikpqdq1s2fPduUUAAAAgNtyKURv27ZN27ZtU3l5udq3by9J2rdvnzw9PXXTTTeZdRaLpWa6BAAAANyISyH63nvvVePGjbVo0SI1adJE0ukHsIwaNUq9e/fW+PHja7RJAAAAwJ1YDMMwnH3Tb37zG33++ee64YYbHPbv2rVL/fr1Y63o87DZbPLz81NRUZF8fX2vzEmn+V2Z81THtKLa7gAAAOCCqpvXXPphoc1m09GjR6vsP3r0qE6cOOHKIQEAAIA6w6UQff/992vUqFH68MMPdfjwYR0+fFj//Oc/FR8fr0GDBtV0jwAAAIBbcWlOdHJysiZMmKAHH3xQ5eXlpw9Ur57i4+M1a9asGm0QAAAAcDcuzYmuVFJSogMHDkiS2rRpo4YNG9ZYY1cj5kQzJxoAALi3yzonulJeXp7y8vLUrl07NWzYUJeQxwEAAIA6w6UQ/fPPP6tv3766/vrrNWDAAOXl5UmS4uPjWd4OAAAAVz2XQvS4ceNUv3595eTkqEGDBub+IUOGKC0trdrH2bBhg+69916FhITIYrFo5cqVDuOGYWjq1KkKDg6Wj4+PoqOjtX//foeaY8eOafjw4fL19ZW/v7/i4+NVXFzsULNjxw717t1b3t7eCg0N1cyZM6v0snz5cnXo0EHe3t7q0qWLPvnkE6d7AQAAwLXBpRD9+eefa8aMGWrZsqXD/nbt2unHH3+s9nFKSkrUtWtXLViw4JzjM2fO1Lx585ScnKzNmzerYcOGiomJ0cmTJ82a4cOHa/fu3UpPT9eqVau0YcMGPf744+a4zWZTv3791Lp1a2VlZWnWrFmaNm2a3nrrLbNm06ZNGjZsmOLj47Vt2zYNHDhQAwcO1K5du5zqBQAAANcGl35Y2LhxY33zzTdq166dGjdurO3bt+u6667T1q1bFRMTo59//tn5RiwWrVixQgMHDpR0+s5vSEiIxo8frwkTJkiSioqKFBgYqNTUVA0dOlTffvutOnXqpK+//lo9evSQJKWlpWnAgAE6fPiwQkJCtHDhQj377LPKz8+X1WqVJE2ePFkrV67Unj17JJ2+g15SUqJVq1aZ/dxyyy3q1q2bkpOTq9VLdfDDQn5YCAAA3Ntl/WFh79699d5775nbFotFdrtdM2fOVJ8+fVw5ZBUHDx5Ufn6+oqOjzX1+fn6KjIxUZmamJCkzM1P+/v5mgJak6OhoeXh4aPPmzWbN7bffbgZoSYqJidHevXt1/Phxs+bM81TWVJ6nOr2cS2lpqWw2m8MLAAAAdZ9L60TPnDlTffv21datW1VWVqaJEydq9+7dOnbsmDZu3FgjjeXn50uSAgMDHfYHBgaaY/n5+QoICHAYr1evnpo2bepQEx4eXuUYlWNNmjRRfn7+Rc9zsV7OZfr06XrhhRcu/mEBAABQp7h0J7pz587at2+fevXqpfvuu08lJSUaNGiQtm3bpjZt2tR0j3XWlClTVFRUZL4OHTpU2y0BAACgBjh9J7q8vFz9+/dXcnKynn322cvRkyQpKChIklRQUKDg4GBzf0FBgbp162bWHDlyxOF9p06d0rFjx8z3BwUFqaCgwKGmcvtiNWeOX6yXc/Hy8pKXl1e1Pi8AAADqDqfvRNevX187duy4HL04CA8PV1BQkDIyMsx9NptNmzdvVlRUlCQpKipKhYWFysrKMmvWrFkju92uyMhIs2bDhg3m48klKT09Xe3bt1eTJk3MmjPPU1lTeZ7q9AIAAIBrh0vTOR566CG98847l3zy4uJiZWdnKzs7W9LpH/BlZ2crJydHFotFY8eO1csvv6yPPvpIO3fu1IgRIxQSEmKu4NGxY0f1799fjz32mLZs2aKNGzcqMTFRQ4cOVUhIiCTpwQcflNVqVXx8vHbv3q2lS5dq7ty5SkpKMvsYM2aM0tLS9Nprr2nPnj2aNm2atm7dqsTEREmqVi8AAAC4drj0w8JTp07p3Xff1b///W9FRESoYcOGDuOzZ8+u1nG2bt3qsJpHZbCNi4tTamqqJk6cqJKSEj3++OMqLCxUr169lJaWJm9vb/M9ixcvVmJiovr27SsPDw8NHjxY8+bNM8f9/Pz0+eefKyEhQREREWrevLmmTp3qsJb0rbfeqiVLlui5557TM888o3bt2mnlypXq3LmzWVOdXgAAAHBtcGqd6O+//15hYWHq27fv+Q9osWjNmjU10tzVhnWiWScaAAC4t+rmNafuRLdr1055eXlau3atpNMPKZk3b16Vpd8AAACAq5lTc6LPvmn96aefqqSkpEYbAgAAANydSz8srOTCE8MBAACAOs+pEG2xWGSxWKrsAwAAAK4lTs2JNgxDI0eONB8gcvLkSY0ePbrK6hwffvhhzXUIAAAAuBmnQnRcXJzD9kMPPVSjzQAAAAB1gVMhOiUl5XL1AQAAANQZl/TDQgAAAOBaRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnOTWIXratGmyWCwOrw4dOpjjJ0+eVEJCgpo1a6ZGjRpp8ODBKigocDhGTk6OYmNj1aBBAwUEBOjpp5/WqVOnHGrWrVunm266SV5eXmrbtq1SU1Or9LJgwQKFhYXJ29tbkZGR2rJly2X5zAAAAHB/bh2iJemGG25QXl6e+fryyy/NsXHjxunjjz/W8uXLtX79euXm5mrQoEHmeEVFhWJjY1VWVqZNmzZp0aJFSk1N1dSpU82agwcPKjY2Vn369FF2drbGjh2rRx99VJ999plZs3TpUiUlJen555/XN998o65duyomJkZHjhy5Ml8CAAAA3IrFMAyjtps4n2nTpmnlypXKzs6uMlZUVKQWLVpoyZIleuCBByRJe/bsUceOHZWZmalbbrlFn376qe655x7l5uYqMDBQkpScnKxJkybp6NGjslqtmjRpklavXq1du3aZxx46dKgKCwuVlpYmSYqMjNTNN9+s+fPnS5LsdrtCQ0P11FNPafLkyeftv7S0VKWlpea2zWZTaGioioqK5Ovre8nfT7VM87sy56mOaUW13QEAAMAF2Ww2+fn5XTSvuf2d6P379yskJETXXXedhg8frpycHElSVlaWysvLFR0dbdZ26NBBrVq1UmZmpiQpMzNTXbp0MQO0JMXExMhms2n37t1mzZnHqKypPEZZWZmysrIcajw8PBQdHW3WnM/06dPl5+dnvkJDQy/hmwAAAIC7cOsQHRkZqdTUVKWlpWnhwoU6ePCgevfurRMnTig/P19Wq1X+/v4O7wkMDFR+fr4kKT8/3yFAV45Xjl2oxmaz6ddff9VPP/2kioqKc9ZUHuN8pkyZoqKiIvN16NAhp78DAAAAuJ96td3Ahdx9993mn2+88UZFRkaqdevWWrZsmXx8fGqxs+rx8vKSl5dXbbcBAACAGubWd6LP5u/vr+uvv17fffedgoKCVFZWpsLCQoeagoICBQUFSZKCgoKqrNZRuX2xGl9fX/n4+Kh58+by9PQ8Z03lMQAAAHBtqVMhuri4WAcOHFBwcLAiIiJUv359ZWRkmON79+5VTk6OoqKiJElRUVHauXOnwyoa6enp8vX1VadOncyaM49RWVN5DKvVqoiICIcau92ujIwMswYAAADXFrcO0RMmTND69ev1ww8/aNOmTbr//vvl6empYcOGyc/PT/Hx8UpKStLatWuVlZWlUaNGKSoqSrfccoskqV+/furUqZMefvhhbd++XZ999pmee+45JSQkmNMsRo8ere+//14TJ07Unj179MYbb2jZsmUaN26c2UdSUpL+/ve/a9GiRfr222/15JNPqqSkRKNGjaqV7wUAAAC1y63nRB8+fFjDhg3Tzz//rBYtWqhXr1766quv1KJFC0nS66+/Lg8PDw0ePFilpaWKiYnRG2+8Yb7f09NTq1at0pNPPqmoqCg1bNhQcXFxevHFF82a8PBwrV69WuPGjdPcuXPVsmVLvf3224qJiTFrhgwZoqNHj2rq1KnKz89Xt27dlJaWVuXHhgAAALg2uPU60Veb6q47WKNYJxoAAKDarpp1ogEAAAB3Q4gGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxEiAYAAACcRIgGAAAAnESIBgAAAJxUr7YbqGsWLFigWbNmKT8/X127dtXf/vY39ezZs7bbqhum+dV2B46mFdV2BwAAoI7iTrQTli5dqqSkJD3//PP65ptv1LVrV8XExOjIkSO13RoAAACuIIthGEZtN1FXREZG6uabb9b8+fMlSXa7XaGhoXrqqac0efLkKvWlpaUqLS01t4uKitSqVSsdOnRIvr6+V6bp6S2vzHlw9ZhyuLY7AACg1thsNoWGhqqwsFB+fuf/r+hM56imsrIyZWVlacqUKeY+Dw8PRUdHKzMz85zvmT59ul544YUq+0NDQy9bn8Ale9XNpt0AAFALTpw4QYiuCT/99JMqKioUGBjosD8wMFB79uw553umTJmipKQkc9tut+vYsWNq1qyZLBbLZe1X+r9/k7qid75R47iOVweu49WB63h14DrWfZfzGhqGoRMnTigkJOSCdYToy8jLy0teXl4O+/z9/a94H76+vvwlcRXgOl4duI5XB67j1YHrWPddrmt4oTvQlfhhYTU1b95cnp6eKigocNhfUFCgoKCgWuoKAAAAtYEQXU1Wq1URERHKyMgw99ntdmVkZCgqKqoWOwMAAMCVxnQOJyQlJSkuLk49evRQz549NWfOHJWUlGjUqFG13do5eXl56fnnn68ypQR1C9fx6sB1vDpwHa8OXMe6zx2uIUvcOWn+/Pnmw1a6deumefPmKTIysrbbAgAAwBVEiAYAAACcxJxoAAAAwEmEaAAAAMBJhGgAAADASYRoAAAAwEmE6KvYggULFBYWJm9vb0VGRmrLli213RL+v+nTp+vmm29W48aNFRAQoIEDB2rv3r0ONSdPnlRCQoKaNWumRo0aafDgwVUe9pOTk6PY2Fg1aNBAAQEBevrpp3Xq1Kkr+VHw/7366quyWCwaO3asuY9rWDf897//1UMPPaRmzZrJx8dHXbp00datW81xwzA0depUBQcHy8fHR9HR0dq/f7/DMY4dO6bhw4fL19dX/v7+io+PV3Fx8ZX+KNesiooK/fnPf1Z4eLh8fHzUpk0bvfTSSzpz7QSuo/vZsGGD7r33XoWEhMhisWjlypUO4zV1zXbs2KHevXvL29tboaGhmjlzZs18AANXpQ8++MCwWq3Gu+++a+zevdt47LHHDH9/f6OgoKC2W4NhGDExMUZKSoqxa9cuIzs72xgwYIDRqlUro7i42KwZPXq0ERoaamRkZBhbt241brnlFuPWW281x0+dOmV07tzZiI6ONrZt22Z88sknRvPmzY0pU6bUxke6pm3ZssUICwszbrzxRmPMmDHmfq6h+zt27JjRunVrY+TIkcbmzZuN77//3vjss8+M7777zqx59dVXDT8/P2PlypXG9u3bjd/97ndGeHi48euvv5o1/fv3N7p27Wp89dVXxhdffGG0bdvWGDZsWG18pGvSX/7yF6NZs2bGqlWrjIMHDxrLly83GjVqZMydO9es4Tq6n08++cR49tlnjQ8//NCQZKxYscJhvCauWVFRkREYGGgMHz7c2LVrl/H+++8bPj4+xptvvnnJ/ROir1I9e/Y0EhISzO2KigojJCTEmD59ei12hfM5cuSIIclYv369YRiGUVhYaNSvX99Yvny5WfPtt98akozMzEzDME7/5ePh4WHk5+ebNQsXLjR8fX2N0tLSK/sBrmEnTpww2rVrZ6Snpxt33HGHGaK5hnXDpEmTjF69ep133G63G0FBQcasWbPMfYWFhYaXl5fx/vvvG4ZhGP/5z38MScbXX39t1nz66aeGxWIx/vvf/16+5mGKjY01HnnkEYd9gwYNMoYPH24YBtexLjg7RNfUNXvjjTeMJk2aOPydOmnSJKN9+/aX3DPTOa5CZWVlysrKUnR0tLnPw8ND0dHRyszMrMXOcD5FRUWSpKZNm0qSsrKyVF5e7nANO3TooFatWpnXMDMzU126dFFgYKBZExMTI5vNpt27d1/B7q9tCQkJio2NdbhWEtewrvjoo4/Uo0cP/f73v1dAQIC6d++uv//97+b4wYMHlZ+f73Ad/fz8FBkZ6XAd/f391aNHD7MmOjpaHh4e2rx585X7MNewW2+9VRkZGdq3b58kafv27fryyy919913S+I61kU1dc0yMzN1++23y2q1mjUxMTHau3evjh8/fkk98tjvq9BPP/2kiooKh38wS1JgYKD27NlTS13hfOx2u8aOHavbbrtNnTt3liTl5+fLarXK39/foTYwMFD5+flmzbmuceUYLr8PPvhA33zzjb7++usqY1zDuuH777/XwoULlZSUpGeeeUZff/21/vSnP8lqtSouLs68Due6Tmdex4CAAIfxevXqqWnTplzHK2Ty5Mmy2Wzq0KGDPD09VVFRob/85S8aPny4JHEd66Caumb5+fkKDw+vcozKsSZNmrjcIyEaqGUJCQnatWuXvvzyy9puBU44dOiQxowZo/T0dHl7e9d2O3CR3W5Xjx499Morr0iSunfvrl27dik5OVlxcXG13B2qa9myZVq8eLGWLFmiG264QdnZ2Ro7dqxCQkK4jrhsmM5xFWrevLk8PT2rrAJQUFCgoKCgWuoK55KYmKhVq1Zp7dq1atmypbk/KChIZWVlKiwsdKg/8xoGBQWd8xpXjuHyysrK0pEjR3TTTTepXr16qlevntavX6958+apXr16CgwM5BrWAcHBwerUqZPDvo4dOyonJ0fS/12HC/19GhQUpCNHjjiMnzp1SseOHeM6XiFPP/20Jk+erKFDh6pLly56+OGHNW7cOE2fPl0S17Euqqlrdjn/niVEX4WsVqsiIiKUkZFh7rPb7crIyFBUVFQtdoZKhmEoMTFRK1as0Jo1a6r8p6aIiAjVr1/f4Rru3btXOTk55jWMiorSzp07Hf4CSU9Pl6+vb5VQgJrXt29f7dy5U9nZ2earR48eGj58uPlnrqH7u+2226osL7lv3z61bt1akhQeHq6goCCH62iz2bR582aH61hYWKisrCyzZs2aNbLb7YqMjLwCnwK//PKLPDwcI42np6fsdrskrmNdVFPXLCoqShs2bFB5eblZk56ervbt21/SVA5JLHF3tfrggw8MLy8vIzU11fjPf/5jPP7444a/v7/DKgCoPU8++aTh5+dnrFu3zsjLyzNfv/zyi1kzevRoo1WrVsaaNWuMrVu3GlFRUUZUVJQ5Xrk8Wr9+/Yzs7GwjLS3NaNGiBcuj1aIzV+cwDK5hXbBlyxajXr16xl/+8hdj//79xuLFi40GDRoY//jHP8yaV1991fD39zf+9a9/GTt27DDuu+++cy6z1b17d2Pz5s3Gl19+abRr146l0a6guLg44ze/+Y25xN2HH35oNG/e3Jg4caJZw3V0PydOnDC2bdtmbNu2zZBkzJ4929i2bZvx448/GoZRM9essLDQCAwMNB5++GFj165dxgcffGA0aNCAJe5wYX/729+MVq1aGVar1ejZs6fx1Vdf1XZL+P8knfOVkpJi1vz666/GH//4R6NJkyZGgwYNjPvvv9/Iy8tzOM4PP/xg3H333YaPj4/RvHlzY/z48UZ5efkV/jSodHaI5hrWDR9//LHRuXNnw8vLy+jQoYPx1ltvOYzb7Xbjz3/+sxEYGGh4eXkZffv2Nfbu3etQ8/PPPxvDhg0zGjVqZPj6+hqjRo0yTpw4cSU/xjXNZrMZY8aMMVq1amV4e3sb1113nfHss886LGvGdXQ/a9euPec/C+Pi4gzDqLlrtn37dqNXr16Gl5eX8Zvf/MZ49dVXa6R/i2Gc8TgfAAAAABfFnGgAAADASYRoAAAAwEmEaAAAAMBJhGgAAADASYRoAAAAwEmEaAAAAMBJhGgAAADASYRoAAAAwEmEaAAAAMBJhGgAAADASYRoAAAAwEn/D3Hftj4B1/eWAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x500 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-jPJloiKOz-A"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}