test-numeric-x-axis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "from financial_canvas.figures.Line import Line\n",
    "from financial_canvas import indicators_glyphs\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import yfinance as yf\n",
    "from bokeh.layouts import column\n",
    "from bokeh.io import output_notebook, output_file, show\n",
    "\n",
    "output_notebook()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "ticker = yf.Ticker(\"AAPL\")\n",
    "df = ticker.history(start='2017-01-01', end='2020-12-31')\n",
    "df.columns = map(str.lower, df.columns)\n",
    "df"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                  open        high         low       close     volume  \\\n",
       "Date                                                                    \n",
       "2017-01-03   27.289880   27.414782   27.044789   27.372362  115127600   \n",
       "2017-01-04   27.301662   27.457201   27.278096   27.341724   84472400   \n",
       "2017-01-05   27.318161   27.539686   27.292238   27.480770   88774400   \n",
       "2017-01-06   27.520829   27.846046   27.447774   27.787130  127007600   \n",
       "2017-01-09   27.796556   28.145340   27.794201   28.041647  134247600   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2020-12-23  131.541950  131.810676  130.168399  130.347565   88223700   \n",
       "2020-12-24  130.705875  132.835866  130.486902  131.352829   54930100   \n",
       "2020-12-28  133.363396  136.697720  132.885629  136.050766  124486200   \n",
       "2020-12-29  137.404410  138.140939  133.711753  134.239273  121047300   \n",
       "2020-12-30  134.945952  135.354039  132.776139  133.094650   96452100   \n",
       "\n",
       "            dividends  stock splits  \n",
       "Date                                 \n",
       "2017-01-03        0.0           0.0  \n",
       "2017-01-04        0.0           0.0  \n",
       "2017-01-05        0.0           0.0  \n",
       "2017-01-06        0.0           0.0  \n",
       "2017-01-09        0.0           0.0  \n",
       "...               ...           ...  \n",
       "2020-12-23        0.0           0.0  \n",
       "2020-12-24        0.0           0.0  \n",
       "2020-12-28        0.0           0.0  \n",
       "2020-12-29        0.0           0.0  \n",
       "2020-12-30        0.0           0.0  \n",
       "\n",
       "[1006 rows x 7 columns]"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>dividends</th>\n",
       "      <th>stock splits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>27.289880</td>\n",
       "      <td>27.414782</td>\n",
       "      <td>27.044789</td>\n",
       "      <td>27.372362</td>\n",
       "      <td>115127600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>27.301662</td>\n",
       "      <td>27.457201</td>\n",
       "      <td>27.278096</td>\n",
       "      <td>27.341724</td>\n",
       "      <td>84472400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>27.318161</td>\n",
       "      <td>27.539686</td>\n",
       "      <td>27.292238</td>\n",
       "      <td>27.480770</td>\n",
       "      <td>88774400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-06</th>\n",
       "      <td>27.520829</td>\n",
       "      <td>27.846046</td>\n",
       "      <td>27.447774</td>\n",
       "      <td>27.787130</td>\n",
       "      <td>127007600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-09</th>\n",
       "      <td>27.796556</td>\n",
       "      <td>28.145340</td>\n",
       "      <td>27.794201</td>\n",
       "      <td>28.041647</td>\n",
       "      <td>134247600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-23</th>\n",
       "      <td>131.541950</td>\n",
       "      <td>131.810676</td>\n",
       "      <td>130.168399</td>\n",
       "      <td>130.347565</td>\n",
       "      <td>88223700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-24</th>\n",
       "      <td>130.705875</td>\n",
       "      <td>132.835866</td>\n",
       "      <td>130.486902</td>\n",
       "      <td>131.352829</td>\n",
       "      <td>54930100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-28</th>\n",
       "      <td>133.363396</td>\n",
       "      <td>136.697720</td>\n",
       "      <td>132.885629</td>\n",
       "      <td>136.050766</td>\n",
       "      <td>124486200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-29</th>\n",
       "      <td>137.404410</td>\n",
       "      <td>138.140939</td>\n",
       "      <td>133.711753</td>\n",
       "      <td>134.239273</td>\n",
       "      <td>121047300</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>134.945952</td>\n",
       "      <td>135.354039</td>\n",
       "      <td>132.776139</td>\n",
       "      <td>133.094650</td>\n",
       "      <td>96452100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1006 rows × 7 columns</p>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "lengths = []\n",
    "avg_prices = []\n",
    "for i in range(1, 1000):\n",
    "    lengths.append(i)\n",
    "    avg_prices.append(df.tail(i).close.mean())\n",
    "\n",
    "mas = pd.DataFrame(data=avg_prices, index=lengths)\n",
    "mas.columns = ['avg_price']\n",
    "mas.index.name = 'length'\n",
    "mas.index = -mas.index\n",
    "mas.sort_index(inplace=True)\n",
    "mas['open'] = None \n",
    "mas['open'] = mas['open'].astype('float64')\n",
    "mas.at[-5, 'open'] = 150.0\n",
    "mas.info()"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 999 entries, -999 to -1\n",
      "Data columns (total 2 columns):\n",
      " #   Column     Non-Null Count  Dtype  \n",
      "---  ------     --------------  -----  \n",
      " 0   avg_price  999 non-null    float64\n",
      " 1   open       1 non-null      float64\n",
      "dtypes: float64(2)\n",
      "memory usage: 55.7 KB\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "numeric_line = Line(mas, figure_args=dict(tools=\"pan,wheel_zoom,box_zoom,save,reset\"), column_name='avg_price')\n",
    "numeric_line.p.diamond('index', 'open', legend_label='open', size=9, source=numeric_line.sources['main'][0])\n",
    "numeric_line.add_hover({'open': 'Open'})\n",
    "# adding glyphs not supported\n",
    "# numeric_line.p.y_range_resize_columns.append('open')\n",
    "\n",
    "\n",
    "datetime_line = Line(df, column_name='close')\n",
    "\n",
    "# output_file('some.html')\n",
    "show(column(children=[numeric_line.p, datetime_line.p], sizing_mode='scale_both'))"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"b46b39c9-3e98-4c56-9bb2-7645264a7bfb\" data-root-id=\"1849\"></div>\n"
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     "data": {
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      "application/javascript": "(function(root) {\n  function embed_document(root) {\n    \n  var docs_json = {\"1724d117-67fb-489b-a1a9-8913ca347c1c\":{\"defs\":[],\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1712\"},{\"id\":\"1785\"}],\"sizing_mode\":\"scale_both\"},\"id\":\"1849\",\"type\":\"Column\"},{\"attributes\":{},\"id\":\"1788\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1792\",\"type\":\"LinearScale\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"marker\":{\"value\":\"diamond\"},\"size\":{\"value\":9},\"x\":{\"field\":\"index\"},\"y\":{\"field\":\"open\"}},\"id\":\"1767\",\"type\":\"Scatter\"},{\"attributes\":{\"num_minor_ticks\":5,\"tickers\":[{\"id\":\"1833\"},{\"id\":\"1834\"},{\"id\":\"1835\"},{\"id\":\"1836\"},{\"id\":\"1837\"},{\"id\":\"1838\"},{\"id\":\"1839\"},{\"id\":\"1840\"},{\"id\":\"1841\"},{\"id\":\"1842\"},{\"id\":\"1843\"},{\"id\":\"1844\"}]},\"id\":\"1795\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"axis_line_width\":0,\"formatter\":{\"id\":\"1813\"},\"major_label_policy\":{\"id\":\"1826\"},\"major_tick_in\":0,\"major_tick_line_color\":null,\"major_tick_out\":8,\"minor_tick_line_color\":null,\"ticker\":{\"id\":\"1795\"}},\"id\":\"1794\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"source\":{\"id\":\"1710\"}},\"id\":\"1769\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1790\",\"type\":\"LinearScale\"},{\"attributes\":{\"axis\":{\"id\":\"1794\"},\"ticker\":null},\"id\":\"1797\",\"type\":\"Grid\"},{\"attributes\":{\"line_color\":\"gray\",\"line_dash\":[6],\"location\":0},\"id\":\"1744\",\"type\":\"Span\"},{\"attributes\":{\"label\":{\"value\":\"open\"},\"renderers\":[{\"id\":\"1768\"}]},\"id\":\"1781\",\"type\":\"LegendItem\"},{\"attributes\":{\"days\":[\"%d/%m/%Y\"],\"hours\":[\"%H:%M\"],\"minutes\":[\"%H:%M\"],\"months\":[\"%m/%Y\"]},\"id\":\"1813\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{},\"id\":\"1732\",\"type\":\"SaveTool\"},{\"attributes\":{\"axis_line_width\":0,\"formatter\":{\"id\":\"1828\"},\"major_label_policy\":{\"id\":\"1829\"},\"major_tick_in\":0,\"major_tick_line_color\":null,\"major_tick_out\":8,\"minor_tick_line_color\":null,\"ticker\":{\"id\":\"1799\"}},\"id\":\"1798\",\"type\":\"LinearAxis\"},{\"attributes\":{\"args\":{\"columns\":[\"avg_price\"],\"source\":{\"id\":\"1710\"},\"unique_name\":140364869699520,\"y_range\":{\"id\":\"1715\"}},\"code\":\"const timeout_name = '_autoscale_timeout_' + unique_name;\\n\\nclearTimeout(window[timeout_name]);\\n\\nwindow[timeout_name] = setTimeout(function () {\\n  let index = source.data.index;\\n  let start = cb_obj.start;\\n  let end = cb_obj.end;\\n  let min = 1e100;\\n  let max = -1e10;\\n\\n  for (let column of columns) {\\n    for (var i = 0; i < index.length; ++i) {\\n      if (\\n        !isNaN(source.data[column][i]) &&\\n        start <= index[i] &&\\n        index[i] <= end\\n      ) {\\n        max = Math.max(source.data[column][i], max);\\n        min = Math.min(source.data[column][i], min);\\n      }\\n    }\\n  }\\n\\n  // console.log(\\\"min, max: \\\", min, max);\\n  // console.log(\\\"start, end: \\\", start, end);\\n  // console.log(\\\"source.data \\\", source.data);\\n\\n  var pad = (max - min) * 0.05;\\n\\n  y_range.start = min - pad;\\n  y_range.end = max + pad;\\n}, 200);\\n\"},\"id\":\"1764\",\"type\":\"CustomJS\"},{\"attributes\":{\"axis\":{\"id\":\"1721\"},\"ticker\":null},\"id\":\"1724\",\"type\":\"Grid\"},{\"attributes\":{\"data_source\":{\"id\":\"1710\"},\"glyph\":{\"id\":\"1766\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1767\"},\"view\":{\"id\":\"1769\"}},\"id\":\"1768\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"axis\":{\"id\":\"1798\"},\"dimension\":1,\"ticker\":null},\"id\":\"1801\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1799\",\"type\":\"BasicTicker\"},{\"attributes\":{\"source\":{\"id\":\"1783\"}},\"id\":\"1822\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1733\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1803\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1802\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1722\",\"type\":\"BasicTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"1806\"}},\"id\":\"1804\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1805\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1717\",\"type\":\"LinearScale\"},{\"attributes\":{\"data\":{\"avg_price\":{\"__ndarray__\":\"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3niZ2QgAAQN3wJnZCAABAdDoodkIAAADajCh2QgAAwD/fKHZCAACApTEpdkIAAEALhCl2QgAAgDx7KnZCAABAos0qdkIAAAAIICt2QgAAwG1yK3ZCAACA08QrdkIAAMAEvCx2QgAAgGoOLXZCAABA0GAtdkIAAAA2sy12QgAAwJsFLnZCAAAAzfwudkIAAMAyTy92QgAAgJihL3ZCAABA/vMvdkIAAABkRjB2QgAAQJU9MXZCAAAA+48xdkIAAMBg4jF2QgAAgMY0MnZCAABALIcydkIAAIBdfjN2QgAAQMPQM3ZCAAAAKSM0dkIAAMCOdTR2QgAAgPTHNHZCAADAJb81dkIAAICLETZ2QgAAQPFjNnZCAAAAV7Y2dkIAAMC8CDd2QgAAAO7/N3ZCAADAU1I4dkIAAIC5pDh2QgAAQB/3OHZCAAAAhUk5dkIAAAAckzp2QgAAwIHlOnZCAACA5zc7dkIAAEBNijt2QgAAgH6BPHZCAABA5NM8dkIAAABKJj12QgAAwK94PXZCAACAFcs9dkIAAMBGwj52QgAAgKwUP3ZCAABAEmc/dkIAAAB4uT92QgAAwN0LQHZCAAAADwNBdkIAAMB0VUF2QgAAgNqnQXZCAABAQPpBdkIAAACmTEJ2QgAAQNdDQ3ZCAAAAPZZDdkIAAMCi6EN2QgAAgAg7RHZCAABAbo1EdkIAAICfhEV2QgAAQAXXRXZCAADA0HtGdkIAAIA2zkZ2QgAAwGfFR3ZCAACAzRdIdkIAAEAzakh2QgAAAJm8SHZCAADA/g5JdkIAAAAwBkp2QgAAwJVYSnZCAACA+6pKdkIAAEBh/Up2QgAAAMdPS3ZCAABA+EZMdkIAAABemUx2QgAAwMPrTHZCAACAKT5NdkIAAECPkE12QgAAgMCHTnZCAABAJtpOdkIAAACMLE92QgAAwPF+T3ZCAACAV9FPdkIAAMCIyFB2QgAAgO4aUXZCAABAVG1RdkIAAAC6v1F2QgAAwB8SUnZCAAAAUQlTdkIAAMC2W1N2QgAAgByuU3ZCAABAggBUdkIAAADoUlR2QgAAQBlKVXZCAAAAf5xVdkIAAMDk7lV2QgAAgEpBVnZCAABAsJNWdkIAAIDhild2QgAAQEfdV3ZCAAAArS9YdkIAAMASglh2QgAAgHjUWHZCAACADx5adkIAAEB1cFp2QgAAANvCWnZCAADAQBVbdkIAAAByDFx2QgAAwNdeXHZCAACAPbFcdkIAAECjA112QgAAAAlWXXZCAABAOk1edkIAAACgn152QgAAwAXyXnZCAACAa0RfdkIAAEDRll92QgAAgAKOYHZCAABAaOBgdkIAAADOMmF2QgAAwDOFYXZCAACAmddhdkIAAMDKzmJ2QgAAgDAhY3ZCAABAlnNjdkIAAAD8xWN2QgAAwGEYZHZCAAAAkw9ldkIAAMD4YWV2QgAAgF60ZXZCAABAxAZmdkIAAAAqWWZ2QgAAQFtQZ3ZCAAAAwaJndkIAAMAm9Wd2QgAAgIxHaHZCAABA8plodkIAAIAjkWl2QgAAQInjaXZCAAAA7zVqdkIAAMBUiGp2QgAAgLraanZCAADA69FrdkIAAIBRJGx2QgAAQLd2bHZCAAAAHclsdkIAAMCCG212QgAAALQSbnZCAADAGWVudkIAAIB/t252QgAAQOUJb3ZCAAAAS1xvdkIAAEB8U3B2QgAAAOKlcHZCAADAR/hwdkIAAICtSnF2QgAAQBOdcXZCAACARJRydkIAAECq5nJ2QgAAABA5c3ZCAACA291zdkIAAMAM1XR2QgAAgHIndXZCAABA2Hl1dkIAAAA+zHV2QgAAwKMednZCAAAA1RV3dkIAAMA6aHd2QgAAQAYNeHZCAAAAbF94dkIAAECdVnl2QgAAAAOpeXZCAADAaPt5dkIAAIDOTXp2QgAAQDSgenZCAACAZZd7dkIAAEDL6Xt2QgAAADE8fHZCAADAlo58dkIAAID84Hx2QgAAwC3YfXZCAABA+Xx+dkIAAABfz352QgAAwMQhf3ZCAAAA9hiAdkIAAIDBvYB2QgAAQCcQgXZCAAAAjWKBdkIAAEC+WYJ2QgAAACSsgnZCAADAif6CdkIAAIDvUIN2QgAAQFWjg3ZCAACAhpqEdkIAAEDs7IR2QgAAAFI/hXZCAADAt5GFdkIAAIAd5IV2QgAAgLQth3ZCAABAGoCHdkIAAACA0od2QgAAwOUkiHZCAAAAFxyJdkIAAMB8bol2QgAAgOLAiXZCAABASBOKdkIAAACuZYp2QgAAQN9ci3ZCAAAARa+LdkIAAMCqAYx2QgAAgBBUjHZCAABAdqaMdkIAAICnnY12QgAAQA3wjXZCAAAAc0KOdkIAAMDYlI52QgAAgD7njnZCAACA1TCQdkIAAEA7g5B2QgAAAKHVkHZCAADABiiRdkIAAAA4H5J2QgAAwJ1xknZCAACAA8SSdkIAAEBpFpN2QgAAAM9ok3ZCAABAAGCUdkIAAABmspR2QgAAwMsElXZCAACAMVeVdkIAAECXqZV2QgAAgMiglnZCAABALvOWdkIAAACURZd2QgAAwPmXl3ZCAACAX+qXdkIAAMCQ4Zh2QgAAgPYzmXZCAABAXIaZdkIAAADC2Jl2QgAAwCcrmnZCAAAAWSKbdkIAAMC+dJt2QgAAgCTHm3ZCAABAihmcdkIAAADwa5x2QgAAQCFjnXZCAAAAh7WddkIAAMDsB552QgAAgFJannZCAABAuKyedkIAAIDpo592QgAAQE/2n3ZCAAAAtUigdkIAAMAam6B2QgAAgIDtoHZCAADAseShdkIAAIAXN6J2QgAAQH2JonZCAAAA49uidkIAAAB6JaR2QgAAwN93pHZCAACARcqkdkIAAECrHKV2QgAAABFvpXZCAABAQmamdkIAAACouKZ2QgAAwA0Lp3ZCAACAc12ndkIAAEDZr6d2QgAAgAqnqHZCAABAcPmodkIAAADWS6l2QgAAwDueqXZCAACAofCpdkIAAMDS56p2QgAAgDg6q3ZCAABAnoyrdkIAAAAE36t2QgAAwGkxrHZCAAAAmyitdkIAAMAAe612QgAAgGbNrXZCAABAzB+udkIAAAAycq52QgAAAMm7r3ZCAADALg6wdkIAAICUYLB2QgAAQPqysHZCAACAK6qxdkIAAECR/LF2QgAAAPdOsnZCAADAXKGydkIAAIDC87J2QgAAwPPqs3ZCAACAWT20dkIAAEC/j7R2QgAAACXitHZCAADAijS1dkIAAAC8K7Z2QgAAwCF+tnZCAACAh9C2dkIAAEDtIrd2QgAAAFN1t3ZCAABAhGy4dkIAAADqvrh2QgAAwE8RuXZCAACAtWO5dkIAAEAbtrl2QgAAgEytunZCAABAsv+6dkIAAAAYUrt2QgAAgOP2u3ZCAADAFO68dkIAAIB6QL12QgAAQOCSvXZCAAAARuW9dkIAAMCrN752QgAAAN0uv3ZCAADAQoG/dkIAAICo0792QgAAQA4mwHZCAAAAdHjAdkIAAEClb8F2QgAAAAvCwXZCAADAcBTCdkIAAIDWZsJ2QgAAQDy5wnZCAACAbbDDdkIAAEDTAsR2QgAAADlVxHZCAADAnqfEdkIAAIAE+sR2QgAAwDXxxXZCAACAm0PGdkIAAEABlsZ2QgAAAGfoxnZCAADAzDrHdkIAAAD+Mch2QgAAwGOEyHZCAACAydbIdkIAAEAvKcl2QgAAAJV7yXZCAABAxnLKdkIAAAAsxcp2QgAAwJEXy3ZCAACA92nLdkIAAEBdvMt2QgAAgI6zzHZCAABA9AXNdkIAAABaWM12QgAAwL+qzXZCAACAJf3NdkIAAIC8Rs92QgAAQCKZz3ZCAAAAiOvPdkIAAMDtPdB2QgAAAB810XZCAADAhIfRdkIAAIDq2dF2QgAAQFAs0nZCAAAAtn7SdkIAAEDnddN2QgAAAE3I03ZCAADAshrUdkIAAIAYbdR2QgAAQH6/1HZCAACAr7bVdkIAAEAVCdZ2QgAAAHtb1nZCAADA4K3WdkIAAIBGANd2QgAAwHf313ZCAACA3UnYdkIAAEBDnNh2QgAAAKnu2HZCAADADkHZdkIAAABAONp2QgAAwKWK2nZCAACAC93adkIAAEBxL9t2QgAAANeB23ZCAABACHncdkIAAABuy9x2QgAAwNMd3XZCAACAOXDddkIAAECfwt12QgAAgNC53nZCAABANgzfdkIAAACcXt92QgAAwAGx33ZCAACAZwPgdkIAAMCY+uB2QgAAgP5M4XZCAABAZJ/hdkIAAADK8eF2QgAAwC9E4nZCAAAAYTvjdkIAAMDGjeN2QgAAgCzg43ZCAABAkjLkdkIAAAD4hOR2QgAAQCl85XZCAAAAj87ldkIAAMD0IOZ2QgAAgFpz5nZCAABAwMXmdkIAAIDxvOd2QgAAQFcP6HZCAAAAvWHodkIAAMAitOh2QgAAgIgG6XZCAADAuf3pdkIAAIAfUOp2QgAAQIWi6nZCAADAUEfrdkIAAACCPux2QgAAwOeQ7HZCAACATePsdkIAAECzNe12QgAAABmI7XZCAABASn/udkIAAACw0e52QgAAwBUk73ZCAACAe3bvdkIAAEDhyO92QgAAgBLA8HZCAABAeBLxdkIAAADeZPF2QgAAwEO38XZCAACAqQnydkIAAMDaAPN2QgAAgEBT83ZCAAAADPjzdkIAAMBxSvR2QgAAAKNB9XZCAADACJT1dkIAAEDUOPZ2QgAAADqL9nZCAABAa4L3dkIAAADR1Pd2QgAAwDYn+HZCAACAnHn4dkIAAEACzPh2QgAAgDPD+XZCAABAmRX6dkIAAAD/Z/p2QgAAwGS6+nZCAACAygz7dkIAAIBhVvx2QgAAQMeo/HZCAAAALfv8dkIAAMCSTf12QgAAAMRE/nZCAADAKZf+dkIAAICP6f52QgAAQPU7/3ZCAAAAW47/dkIAAECMhQB3QgAAAPLXAHdCAADAVyoBd0IAAIC9fAF3QgA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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[1006]},\"open\":{\"__ndarray__\":\"x/aWlTVKO0DbDvK3OU07QGwyBgdzUTtAGiXBDFWFO0CqQdwc68s7QD/Jy3Fj/TtAaiUADpT7O0AXjqZVOwU8QJGIqZvmETxAALjAvnLjO0CZ00lamEc8QHat5aRlIzxAzRAYl75iPECboQhKmEc8QMhfAzpyLDxAaAMp1+5gPEBOeVGtWKw8QPuXmFyzyDxA8e/+yrN/PEBXlzeH+Yw8QEd7Cr+27z1A0O+tXAcpPkAGDSHx7zw+QF5nFHhobj5A3JXLA3nDPkB7i/PjVvQ+QMbooOHfKD9AykThEPRZP0B+ypDbhH8/QFJV5honlz9A6+4Egq4JQEC3BGDEOQ5AQDrFRj3q+T9ApRjrDTEfQECiH1UtQCVAQJnsFWgIQkBAvNDGNn8VQECFmniAwjpAQIBAZFzxOEBAEbqucHtRQEAh74xEaJFAQNtjV+lxbEBAosB4CVJ+QEBQH6+x7XRAQEYuypCYcUBAxDNCMTxrQEAXnRUCr3pAQFwpCTKRbkBAX1WgADN8QEDwHQwaiH9AQP6QeEk4p0BADCmburOvQED1THt3hp1AQBUs7oBU0UBAT1uk1tyMQECQ1BoqlLdAQGL3a6vZvkBAqHvwMO1+QEAM3DT8+axAQI/dmNfkAEFAwm24b1gQQUADuOoyGwJBQBSZBMLNAUFAHRwTZ97zQEA6uoIeQRFBQN1C7ORfE0FAWxOGGWkCQUChMM2keP5AQGM/JBh66kBA4jxrYeHBQECIS5+rRctAQG0U3XM+vkBACsOLoB+8QEBKLH6zXMpAQHljiCRetkBAz0kWFVTbQEDpWVw0cftAQBZalv7cB0FAJ5qpFNQYQUAk5d5nKghBQHJSpwhRDUFAOm0aU+orQUB3VHYJ1nVBQKCRXVfCOkFAIidFvO9WQUBqR/V1NF5BQP81+0j6okFAEwTU25s1QkCf1/KRVi5CQGSR8+imHUJAFg2jPBliQkBHRQwN84lCQN80/33Sh0JA/+hfMKNAQkCN67mrwflBQH78NaHxOUJANkGiNc5MQkCGHgQOL2hCQGn/B93vR0JAWj4OWZdEQkAjUocVzkxCQNHYajEpO0JAY7nvc+RLQkBNIV5KjjNCQFE/Gx0HQEJAUI003yVXQkCjmt85w0lCQIeJ1J3Va0JAq00dhNRyQkANnOJVAXFCQIQ8RYGHUUFAzni677l8QUASqMPAEYdBQEUPwAPpB0FA6mKarecVQUDDaJXyQBJBQCqzIK7nc0FAxtrhHdZKQUDR7PQmcVJBQJztu6n4PkFAGGy2/Ad9QUANiwVIUjtBQFfmabmAK0FA7Ee89zEyQUC4l2cqSSpBQBO1DfpdN0FABe7ItCoTQUDXygUCyf5AQI/YcPgh+0BAZo/vTvEfQUDwWBzrzTJBQMRE3rJ7VUFAqJnnsTpKQUDvyHYRXpVBQOSZiYg5r0FAIQ/gAsm6QUCBqKQPueFBQHyFAsvAAEJAWvArMtHSQUBC0N8SxORBQLKtcwThCUJAZKdk+Ac5QkDNN74eM0VCQJyekpXGz0FAG72iYBTQQUAMS5xOvrdBQOfz/xpt7UJALjQxbZapQkBBwSe9xotCQKgbZFrkqUJAbqspsr3YQkBO625R0exCQCb9iqBjE0NAluSal5uuQkA+KCourQFDQLabSIWZKkNAX45UC7FRQ0Dk2YEbUyZDQOLejTgW1UJA7Zn7ARjKQkASAFQ4Y+BCQNyi0o0K+kJAkAJUhpMjQ0ApCDsawQtDQLGSdgK4GkNAWlUdUn8ZQ0CusjY3f4pDQAweYSechUNAy1J8ewmpQ0Az5wcw+IhDQOpqjes0aUNAIo4r1kVWQ0D2rhFMtTBDQHo3vrC2JUNARSDyaidmQ0BH4qcpeRJDQMwEWg2Z90JAhQZcp7fnQkDZM7mizRlDQLARdmV6B0NA0Ghl5k7WQkCwgphmLJZCQPl9RIsSFEJAUnksJLzkQUA1ZPEXZxtCQPlb8k4YWUJAeiWXzNdbQkACMvAtE0dCQEPGHVckZ0JAxollAoJfQkA+wXkx51NCQKjseiqzZEJAdsGtMdN8QkBjdNS1epZCQDmyNhUdnkJA3du9vV2bQkBP/MzU+KZCQPXWwKmTskJA1d/ZKE/WQkB9AcyYuQ9DQIJjFF1FI0NAtFfeITCzQkCPZKJ46a5CQJ6yGHF2t0JAyVnQcSOlQkCVjI/nErhCQDJZdKTYwUJAEaWJdMIAQ0CsCa/qPo1DQMM9iUG2B0RASTKiBuBDREBc6U5lAuBDQKp8GPcBwkRAQUdi6jmQREBMQphRQr9EQEPB384p1kRAO+w1PujjREBTXSTRIfdEQLKx3AzJxURA9sjCoa+3REBhHSdOl1lEQJGHmjutfkRAN59ZDmN6REDPa7k+ZmNEQKDs8vNqckRA1LK8r37BREBZW4yS0/ZEQAfSohxL9URAhxwSb07eREDyyZvoHqtEQNWpLHywZ0RA7XH2ZPpYREAz4ge2haZEQGmnlvCyPURAINX6dOINREB1h+W4xzxEQBDRIHGHaURAUGRYjf1BREAeDdc8aJxEQKAOWqQip0RAzY0hDBKkRECu1l4fxclEQIqCUlIV8ERAYCaISa70REA0MMqsxu9EQF1qLSpS2kRA2gkly/PpREDYumXkB3NEQNURv2qTXURAZ5C4JSl5RECo7HHRcmpEQJlux/lpX0RA3c/K8g2oREADhYaWXKhEQDECCnzyw0RA////n9bfRECqupz49+VEQCosGyJdu0RAPH92dDHnREBIB8db7RdFQP77xE2lTEVAiaQ8GgIXRUAzaVK8s3lFQLMmEipoYkVAVRXuskE6RUDKxQqFQTpFQE6FfAC5OEVAQqub473kREBDMHKJz5dEQIYFqfZpX0RAxvQ4RIHRQ0Clc7Rmk/pDQKfEX27FA0RApfGRCenfQ0BADUvGbAxDQHfpgoqMiUJApsiGDbiGQ0CBUqPy5TBDQPH+2UbV4UJAdSaQW9cNQ0CtuirdA3hDQENPJ1yPmUNAPu4rgUppREDRYfcSYrhEQKziO8jXrkRAmVXuE9nGRECy0LRDJqdEQOQ4AQCz4ERAvWE2/SwzRUCLhufYzodFQJ4bwQC7jEVA4+slwpJ2RUBRJy+b7MVEQLCCFYMXEEVAujoApS9jRUD6AOpYyAdFQIAoR7lmGEVAS+PINLlkRUBog0axbaxFQBGNNAI280VAfq39MFqtRUDRYIGJV3VFQIy7ZTD1eUVAjB6l6QZRRUAAAAAABBFFQNo+BCHcCkVAl7OWHsFvREDy+Lq5ND5EQMqJGuNbNERAsi0PiQHhREBY7txHHxtEQPFBtHdbLERAnmemylkIREDpfRXyHydEQI6fkpwv0kNAjwm9PSe/REAckcBLm41EQPtqdK8PbERA8ur0ZRTMREB8MWK7YbREQIVo06uy2ERAM1bD8dsCRUALftJ9jQpFQKt+b8p7N0VAoZFOSBtgRUB1prWzd+NEQFZIM0o4gkRAKlMNgzIOREB3At/Ef+pDQFzihECijENAwc54HMy6Q0Cu55/KGrdDQGJqjwuOfUNAjp2P0EUBRED1/uI3tRBFQAaxlPq1JEVAvMX8u6VtRUAKVEg760JGQMDWP6gSPUZAi2eMwhRtRkCsqhUDtJFGQEDK7PoL3kZAHeuprzfPRkCP5FYVU4pGQAyakvNjdEZAUzis1AOwRkC/CVHF/ZZGQIIGbPYDsEZAtdHcWsG7RkArQa6BCn1GQCNomKfNx0ZAu+9b4B63RkAwsu9VqKNGQJ7vQjFdp0ZAofuO3+qXRkAVrHv6tK9GQLResM93IEdAcgT4V6VMR0DvaVI/8l1HQPWufIqzbUdAJs1MuvIRR0Bnhu9ighdHQOkUkW++GEdADKrpfpA4R0B7psTWrx1HQHPuhJm67kZAD7/NcE6sRkBGAr+kqFdGQFAi8XoKfUZAWv7MTNiYRkDxyvlE73VGQAE1DGbnIUZANY8E0zwVRkCyuFI2cFpGQF3jUJ+HN0ZAt4twzy97RkByOytX4S5GQGQ1FfeGqUZAf4FYpl1bRkAMa+8xT2BGQLyxP99a3kZAkCEIy7wDR0DVOIUIdr9GQD2XLzJI30ZAby6gDSsPR0CkWl7dwhxHQDbOEVYU5kZAzu0pKsskR0BFkfi8OeRGQLpaUPXKJEdA78FOJM8CR0Dbm+WkfTlHQHSGLfZVTEdATX4xlzh8R0ANtecu9odHQCdC9ed/KEdA0lJD6hH3RkAzkEGX3AdIQBtuxU+oNEhAXI494+v7SEC4vXCK4xlJQNf0kTirQklAPBb4eqXdSED/VaDpJ0lJQPEUQ06VHElAlizVdglZSUBBhvvgY3NJQOmBc1Y/VklAWeLUua6kSUAE8GeME9lJQEGbT6qLaUpAMNxtGz5BSkCbrduTie1JQP/HqnqW/klAD3n+Fgs7SkCp9/YzGExKQO0srsfBhUpAhiIQgBmpSkAiEDL/NAlLQF57EcNFbktA51izWS2pS0D/3EyjKLtLQMEIO5yXZUtAc3OtvM3dSkDhZImm5sFKQDPM51zBZkpAGE9hjpk9S0AdUFCUkxFLQI69Y+m1VktAM5S6vhrnSkCOkMk3719KQA5maEnydUpAP7wc2eOrSkB6DTCqobxKQC6eZf3cQUpAmbZ+3bKcSkBVHtHSc8NKQFL09m/gGktAoc/M9PI4S0AbTnF46ppLQPYq4/02hUtAUeW2EAXcS0CV8mW4pvJLQJDXnuU5m0tAG6DACvfoSkBd3dgvTBVLQEJ7Hcu4TUtA2r5d3Y76SUCMoT+heLFKQJxwsG9pyEpAEt6MAkeDSkDN548LwetKQAiLHswaYkpAvl3FGE5oSkCAuZuV8J1KQL6ACasrI0pACZXrHQ71SkDsJT9ydF1KQMeJejFXJUpAy6oQkFaLSkDKr3mnFJJJQG90KHe5Q0pABXw2fP+GSkAlU8SpemBJQEbyxqe3vUhAYg0xwu5zSEAwvWvLffFIQPkbTNqFhElA/y3/fbT6SEC/WpWr7i5IQMwjQYumSUdA/MefW0WQR0Ck1pGo2uRGQLdRRvB+JkdAiqJa2PAWR0DW8cvgIK1FQMHdS2lw10VAbv/p/mtCRUBZgEjupCxFQNjue1u210RAFbuxuRt6RUApaGy3lzJGQFbQQz3c6EVAJ5vGAJdqRkBCutiiZP1FQMrJVp5930RA1yA4kk8VRUDF2RlRLw1EQH4pbVBh3ERA51/BIS61REAA2WUn+7dEQGfyDVKgiURAeIbsay8bREDa5RPsARlEQH1eXKRLLERAf1aY7hN+Q0Ack02s8g9DQJ9i4zL6AEJAWt8hFKUFQkB0JfAcN/BCQNa2f/bbI0NABu0Q7eZDQ0BxMOtPqdJCQMxRmMQ/f0FAsb6FxFuQQUBE4L+6FhJCQAAA5NDXLEJABneJAKpiQkCThh2/TohCQIawrTohlEJALzbPAfpUQkBYQc+M7kJCQJnVf+5ZmkJAcp83wDG9QkAVbHi72yNDQNipAPfyAUNAt4s8nKO7QkApUNpSZbpCQA7vdNoD5UJAHfYjDKnuQkCHTaLA+PxCQHN4ZfK91kNA00dN67cvREB9+T6GKUpEQKdAqhIpWERAq3p4TLYBRUAlDEv8ZTlFQOn6c49m80RAMejG09yfREAzqB6SOeBEQJ+rvVaLwkRAgf5u9djqREBOYoLtW7ZEQBrEnwl55kRAYNYM2Vu2REDUhn1lmeREQD1c2Fao90RAtdof5MjwREAALGqNZEFFQIqAWkxVM0VATcdUK7YjRUARCTN0ZEZFQM07WnokRUVArY432zFxRUCR1HxcAXlFQGGDAbVTUUVAdkkx+1Q4RUD8sAy/aslEQChtFITyakVALgicE9v3RUAzSx4xJz5GQGSaWFW0cUZA9l7vB2OPRkDXcYmaEa1GQI0o7pi9/EZA9jP/04C6RkBwQzCx6jBHQMrFWPYh10dAdPAF5ndfR0A54rwHKGRHQOb01Mg8CUdAUkVjV3wPR0CtDQL8+ipHQIHh4iyIY0dAUlcO1VhSR0B5dmx+1ZVHQOVykKTyxUdAIXv/HtD5R0BjvXNs4PhHQC2mahm6ckhA1BR5g3w/SEDiG/waSYNIQDFuIXq7T0hAERJ/m1w8SEC/HDpW21dIQL8dTyBbWkhAbWEKaTXKSECjfsnKJcFIQJj/MFAj80hA/kRshq5OSUCcBGpgHz5JQLj6J1PSAUlAENXHKTPySECW7IlaVchIQDHH7WtqnUlAGYxcRSqcSUAqTDGl+LxJQO+KSIzD7khAeQkd3nAgSUB4l+4gF6RIQGcuapY5dUhAXyvKq98vSECzUnk5VP9GQG9rJTyO1kZAYIBwBSrSRkD2Fi0uVERHQDkOF23d5kZAXv/RG+p7RkDIk7BzO7FGQK03IGOrn0ZA+KBUdD0HRkA05ED5yBNGQEKESsaj60VAR0SjsDqdRUDEs4ZdN81FQOrKzF9Fl0VAMQtWIIODRUDijoIffn5FQATo9u2/k0ZAvxRK8xxuRkBWTNAvsdlGQD43aODrf0dAZjmxu5TfR0Ad11EUCsNHQDGcADKQ2kdAlJ96Q8R3R0BFkxFzG6JHQORQcMfnBEhAQdbDSMF2SEAnVJGUZYxIQBGiJr4nW0hATPCxIwBTSECH4/PxjE9IQCCIVsnZOkhA1H+DEuOJ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splits\":{\"__ndarray__\":\"                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            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