pierrelouisbescond/fPCA_French_Temperatures.ipynb

## fPCA_French_Temperatures.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dataset creation with French temperatures by regions in 2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>Region</th>\n",
       "      <th>06</th>\n",
       "      <th>25</th>\n",
       "      <th>59</th>\n",
       "      <th>62</th>\n",
       "      <th>83</th>\n",
       "      <th>85</th>\n",
       "      <th>75</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>2019-01-01</th>\n",
       "      <td>15.21</td>\n",
       "      <td>5.9</td>\n",
       "      <td>9.45</td>\n",
       "      <td>9.80</td>\n",
       "      <td>15.56</td>\n",
       "      <td>8.35</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-02</th>\n",
       "      <td>15.40</td>\n",
       "      <td>5.3</td>\n",
       "      <td>7.80</td>\n",
       "      <td>6.80</td>\n",
       "      <td>15.21</td>\n",
       "      <td>9.40</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-03</th>\n",
       "      <td>12.83</td>\n",
       "      <td>3.1</td>\n",
       "      <td>6.85</td>\n",
       "      <td>5.85</td>\n",
       "      <td>13.46</td>\n",
       "      <td>6.55</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04</th>\n",
       "      <td>12.34</td>\n",
       "      <td>3.7</td>\n",
       "      <td>6.00</td>\n",
       "      <td>5.70</td>\n",
       "      <td>12.46</td>\n",
       "      <td>5.80</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-05</th>\n",
       "      <td>13.08</td>\n",
       "      <td>2.3</td>\n",
       "      <td>6.80</td>\n",
       "      <td>6.80</td>\n",
       "      <td>12.59</td>\n",
       "      <td>4.75</td>\n",
       "      <td>5.9</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>2019-12-27</th>\n",
       "      <td>14.41</td>\n",
       "      <td>9.9</td>\n",
       "      <td>9.00</td>\n",
       "      <td>9.55</td>\n",
       "      <td>16.50</td>\n",
       "      <td>12.85</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-28</th>\n",
       "      <td>14.65</td>\n",
       "      <td>6.2</td>\n",
       "      <td>7.80</td>\n",
       "      <td>7.70</td>\n",
       "      <td>15.15</td>\n",
       "      <td>11.15</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-29</th>\n",
       "      <td>13.68</td>\n",
       "      <td>4.3</td>\n",
       "      <td>5.10</td>\n",
       "      <td>6.40</td>\n",
       "      <td>13.93</td>\n",
       "      <td>7.60</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-30</th>\n",
       "      <td>13.29</td>\n",
       "      <td>1.6</td>\n",
       "      <td>8.45</td>\n",
       "      <td>9.25</td>\n",
       "      <td>14.35</td>\n",
       "      <td>10.15</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>13.33</td>\n",
       "      <td>4.9</td>\n",
       "      <td>7.25</td>\n",
       "      <td>8.90</td>\n",
       "      <td>14.08</td>\n",
       "      <td>10.60</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Region         06   25    59    62     83     85    75\n",
       "Date                                                  \n",
       "2019-01-01  15.21  5.9  9.45  9.80  15.56   8.35   8.8\n",
       "2019-01-02  15.40  5.3  7.80  6.80  15.21   9.40   7.2\n",
       "2019-01-03  12.83  3.1  6.85  5.85  13.46   6.55   6.6\n",
       "2019-01-04  12.34  3.7  6.00  5.70  12.46   5.80   6.0\n",
       "2019-01-05  13.08  2.3  6.80  6.80  12.59   4.75   5.9\n",
       "...           ...  ...   ...   ...    ...    ...   ...\n",
       "2019-12-27  14.41  9.9  9.00  9.55  16.50  12.85  10.0\n",
       "2019-12-28  14.65  6.2  7.80  7.70  15.15  11.15   8.6\n",
       "2019-12-29  13.68  4.3  5.10  6.40  13.93   7.60   6.2\n",
       "2019-12-30  13.29  1.6  8.45  9.25  14.35  10.15   8.3\n",
       "2019-12-31  13.33  4.9  7.25  8.90  14.08  10.60   5.4\n",
       "\n",
       "[365 rows x 7 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import the CSV file with only useful columns\n",
    "df = pd.read_csv(\"temperature-quotidienne-departementale.csv\", sep=\";\", usecols=[0, 1, 4])\n",
    "\n",
    "# Rename columns to simplify syntax\n",
    "df = df.rename(columns={\"Code INSEE département\": \"Region\", \"TMax (°C)\": \"Temp\"})\n",
    "\n",
    "# Select 2019 records only\n",
    "df = df[(df[\"Date\"] >= \"2019-01-01\") & (df[\"Date\"] <= \"2019-12-31\")]\n",
    "\n",
    "# Pivot table to get \"Date\" as index and regions as columns\n",
    "df = df.pivot(index='Date', columns='Region', values='Temp')\n",
    "\n",
    "# Select a set of regions across France\n",
    "df = df[[\"06\", \"25\", \"59\", \"62\", \"83\", \"85\", \"75\"]]\n",
    "\n",
    "display(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the Pandas dataframe to a Numpy array with time-series only\n",
    "f = df.to_numpy().astype(float)\n",
    "\n",
    "# Create a float vector between 0 and 1 for time index\n",
    "time = np.linspace(0, 1, len(f))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FDASRSF package installation and use on the dataset"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "!pip install fdasrsf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fdasrsf import fPCA, time_warping, fdawarp, fdahpca"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Functional Alignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initializing...\n",
      "Compute Karcher Mean of 7 function in SRSF space...\n",
      "updating step: r=1\n",
      "updating step: r=2\n",
      "updating step: r=3\n",
      "updating step: r=4\n",
      "updating step: r=5\n",
      "updating step: r=6\n",
      "updating step: r=7\n",
      "updating step: r=8\n",
      "updating step: r=9\n",
      "updating step: r=10\n",
      "updating step: r=11\n",
      "updating step: r=12\n",
      "updating step: r=13\n",
      "updating step: r=14\n",
      "updating step: r=15\n",
      "updating step: r=16\n",
      "updating step: r=17\n",
      "updating step: r=18\n",
      "updating step: r=19\n",
      "updating step: r=20\n",
      "maximal number of iterations is reached\n"
     ]
    }
   ],
   "source": [
    "# Align time-series\n",
    "warp_f = time_warping.fdawarp(f, time)\n",
    "warp_f.srsf_align()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RwknTWCbHXNqJMS8HWXxJagFRWY767stQmIfmkefxibZhLFzE6eq+TOAaHCqcDo3nyq5Bro7aIrL4ktQC6qdzoKgA7ZPT8Q84imfZMVLLAxmt689+Wz4VXYcTGxng6pgtJs/qS1IzxMljcGQ/2t/disl7A07rcb6osBOl74lFtVEVM6pdlR5k8SXpokR1Jerf3wYfP3x7qmTbz/FZbTHxuhiiRDcKvCPoHuyeb9ldjCy+JF2EWPgpVFXg+dSjFFrSWGk/xyDrCBLFlZyxe+LdI9zVEX8VWXxJugDhdKIuX4TYsRHjneMIcKxkh93CkNpErtQPJcOqokuIQ3GDT9r9GvLkniT9jCgtpuwvMxHHDxFw70C8wwrYWRPEWHUUXTRdOVitEpjYr03nyLvUZPEl6SdE/hnUv85C1FjxffI6vL2z2Vzcm2FeseiFno11OmJG9nCLz9S3RvtOL0mXkMg6gvqnF1G0KuaZU/HxzibtbDiJXj1xCpUM/0Dih/dCq23/tWnRFj89PZ0FCxagqipJSUncdNNNDe4vLi7mww8/xGKxoKoqd9xxB4MHD74sgSXpUhNOJ2LLGsTi+eh7hBF0bQia6g2cLDMS7hWHBx6cjPAnNDTG1VEvmWaLr6oq8+fP56WXXsJkMjFjxgwSEhLo0qVL/Zhvv/2WkSNHMmHCBHJzc3n77bdl8aV2QZQUoX78DmQfxzCxL34DFRxaI0uPxjAhNApfxYcT5loCQge4Ouol1Wzxs7KyCAsLIzQ0FIDExETS0tIaFF9RFKxWKwBWq5XAwMDLFFeSLh1xOgv13VdAqPg+eT0+hpPUGuLYldeV34WZqcbCia4e+JgGujrqJdds8UtLSzGZTPW3TSYTmZmZDcZMmjSJN998k1WrVlFbW8vLL798wXWlpKSQkpICwOzZszGbzc0H1OlaNM4V3DkbyHwX4yw5R8n7r6Mx+hA0cwb6s/9ABF/JvtP+jNP7k+08g6b3OKK7XuGSfM1p7WvXbPGFEI2W/fzjhtu2bWPs2LFcf/31HD9+nA8++IA5c+Y0OvOZnJxMcnJy/e3i4uJmA5rN5haNcwV3zgYy38WoyxcjKsvRvvI2muLFqIoHWzI8GeftS44zn5zQBGK9DW77+rX0tYuIiLjg8mZPT5pMJkpKSupvl5SUNNqVX79+PSNHjgQgPj4eu91OVVVVs6EkyRVESRFi4wq0/XsTqK4Cp5Wd2SMZ5xVMniggL7QfIwZe/m+sdaVmix8TE0NBQQFFRUU4HA5SU1NJSEhoMMZsNnPo0CEAcnNzsdvt+Pm5xzTCkvRTwmpBff91PMwK5t96Q10F3+yJINEURr4mj1PhAVzR5cJbyY6k2V19rVbL1KlTeeutt1BVlXHjxtG1a1cWLlxITEwMCQkJ3HPPPXz88ccsX74cgGnTprn17CNS5yQs1agf/wlvcxX+V0dSWadjwQ4j1/QJQ1Wc7A8oZWDob10ds00o4kIH8W0kPz+/2THufJzqztlA5vuRsFkR635ArFmCzxAjvonB5FYF8NkBJ91727hbP4nDXiUE9BhTv8HqKK9dU8f48pJdqUMTB9JQ//U+VFVgvGkgvj3sZFV04z9Hz+I78BRXilupUwRBcVchOtFeavu/9lCSmqDu2ow6700INKGZ8Q6GXp6cLg/gm8Lj+A/MJFL0phtdqYmIQGjb/jvqXUkWX+qQhK0G8eVHENMTzQt/otxZik6tZsOZOoxRhYQ7k5ikuwaHhx6LqX3Mk3cpyV19qUMSqevAWo3m1vspLbMRVrOSI9gp71bEKMdVjBBDcOq1lEZHQTv/pN2vIYsvdTji+CHEym8hpidKTE/y1i8mpEsNh2s9uJcbCBaBWAMDqOjS+XbxfySLL3UIwulE7E1FbFkDR/ZDkBnN5Ac4W5KP3SedopqBTBb9KFcVzsVEYQ/o3NeZyOJL7ZpQVdi3A3Xpv+FsHgQFo9x0F0ryjeQVnsB4eivXekxGCME+9Jj6xuHhqXd1bJeTxZfaJSEEInU9YtmXUFYM4V3RPDYDBg5H0WjYufUgY7wq8dPFUq3LwBkWTbi5433K7teSxZfaHVFVgVj0T8SODeeP4yfdjzIkEUWjxelQ2bRyK7eEe6Bo9GzW/pdR3lAWcI2rY7sVWXypXRFVlah/ehHOFaBcfxvKdVNQNOdP0NmdKulbtnJbhC9VShWZHqsYZPCnMnQKqs7fxcndiyy+1G4IW835L60sPYfm2TdR4vvW31dRU0f2/rXcGHgFOWoewj+LARo/Srs+jdB6uTC1e+p8b2BK7Zb47AM4lYXm4ecblP50SQ3F6Ru5xusKjtRmczaoG+FqPjbfQbL0TZDFl9oFUVGG2JOKMvFmlIHD65fvPFaJ4chBrvIOZ6/tCPk+PelmdqAgqDPEuzCxe5PFl9oFsXUtCBVl5Lj6ZZvSK+hTlM0AH2+2O9Kwhg6kV594vKr2oWo8sXt1dWFi9yaLL7k9kZWBWPkNDBiGEnF+DjxLjZ3Qip3E+2rYJlKxhyTQPToWY/FKvCyHsQZcBYo8hdUU+cpIbkvU1SKWfYVYuwxMwWjufAyAnKIMvM5kMN6/ByccpyH0KmK79saneAWG8i1Y/YZjDRzXzNo7N1l8yS0JpxP1r6/B8UMooyei3Ho/ireB9IwURtZ5EKjrwY7qM4QMSaKbtzdaewne5Vup8RtKdfCN7fp77dqCLL7knrIyzpf+zkfRjD1/8U166jqSDAE4hMryGjuDrry2frjemoWCwBowWpa+BWTxJbckTh4DQEm4ktraOk7vXM01ftEUqEVk+kUxaFBsg/EetlM4tb449aYLrU76GVl8ye2I2lpE+k4IiaBa40XlznWM9YvmsOMkmh6jifX92Tc1CRUPaxZ13t3l1r6F5Fl9ya2IvNOoMx+Ck8c4l3Qb6t5Uhvp1YZfzMH6Dfov/z0sP6GtOonFWU2vs2HPhX0qy+JLbEKqK+t3n4LCz7e43MRu09PQJYqO6g9CBN6LVejR6jOK04FOyEqfWl1pjTxekbp/krr7kFoS9Duc//kL+qWOcvHoQE3zKCND4sVLdTI9+d6PXel/gQSqBeZ+gtZdQEXY7aBr/xyBdmCy+5HJCdXJq3tvsCK6Gu3UkaLwwq0H815bN4OHT0CgX3jH1sB5DV1dIRegU6oy92zh1+yaLL7mUEIKU774ht085hshiPBwR9LGNJlfVMWjodU2WXlFr8SleiVMXSK1PvzZO3f7JY3zJpQoKCsgxpmGILCY+4GpCcv6A2UPLKaMRrbaJP08h8CtchNZeQmXI70DpnBNmtoYsvuRSRw99h/GKQrqVRZFTcjXxBitOARGxoU0+Rms/h6clA0tQEnZDTBum7Thk8SWXyT6yhULzHoTFkx3KQyhnKugbWI3F4IOXt2eTj9PWnQOgzhDXVlE7HHmML7nEkTPbSC+Zj1BgW/Zt3Ojr5O5IC+WqJ7XdIi/6WJ39/JdFOvXBbRG1Q5LFl9pcdsFB9pf/A6fDk4pTd/FaSFf6BVZT7PTC1q8bGo+L/1nqbDk4tT5ydp1WaFHx09PTWbBgAaqqkpSUxE033dRoTGpqKosXL0ZRFKKionj66acveVipY9ia9TU6X4Wehb/nqisg0LOaMv8g6qLC0TTzdVae1QfxshzGEjCmjdJ2TM0WX1VV5s+fz0svvYTJZGLGjBkkJCTQpUuX+jEFBQUsXbqUN954Ax8fHyoqKi5raKl9EkLw37Xb6BrmZHTt/XTp4sDusFMSE0etr2+zj9fZcvEt+ha7Z1cspt+0QeKOq9mTe1lZWYSFhREaGopOpyMxMZG0tLQGY9atW8fEiRPx8fEBwN9fTmUsNWSpc/DdDwcYEZjL7eqdBOsCKN24lCIPtUWl11tPEJj7EULjff4qPfkWXqs0u8UvLS3FZPrfRx1NJhOZmZkNxuTn5wPw8ssvo6oqkyZNYuDAxt9akpKSQkpKCgCzZ8/GbDY3H1Cna9E4V3DnbOA++Y4VVnJkWwoPdPXFi17k+drxWLuWuuwMzEPfQOPbzPfYCSdK3nLwMqH0mUGQ3ueyZ3aX164prc3XbPGFEI2WKT/76KOqqhQUFPDqq69SWlrKK6+8wpw5czAajQ3GJScnk5ycXH+7uLi42YBms7lF41zBnbOBe+Q7U1RN0LFMJgeGkq+epUhnxbQkhdpjB/F95DlKa+ug9iIZhcBYshpjTQHlYXdTV2EDbJc9tzu8dhfT0nwREREXXN5s8U0mEyUlJfW3S0pKCAxs+NHIoKAg4uPj0el0hISEEBERQUFBAbGxsT9fndSJHM/IoW9lIYE+OtZr1uJhCSfqi8Vg8EG57WG8J96M9Sd/W40IgbFkFcbyzdT4DaPO2KvtwndwzR7jx8TEUFBQQFFREQ6Hg9TUVBISEhqMGTZsGIcOHQKgsrKSgoICQkObvvJK6vg2rE+lv/UMBk+Vb3T/QTHHErXwv3BFDJpZ89AkXddoz/GndLY8/AoXYizfjNVvOFXBN8lJNi6hZrf4Wq2WqVOn8tZbb6GqKuPGjaNr164sXLiQmJgYEhISGDBgAPv37+f3v/89Go2Gu+66C98WnLCROqYtG3dzTaCKj2JghcdO4qPuIXjPGUSNBc3tD6Nc5Jjes/oQhrJN6GtzURUPLAFjsJgmyNJfYoq40EF8G/nxpODFuPOxljtnA9fk27PjOMkeFQiNyoEAHVdEDwHA+c6LUF2F5rV59Vv6n+fzrNqHf+EiHPpgavxHYPMd7LKLdDrKv+2vPsaXpJYQQrBr/VZuCPKlXLGQ5ltB/+gbz993Ng8yM1Buuqvp3Xu1Dp/iVdg9u1LW5RH5dt1lJj+kI7WaEIJNy1ZzfZAv55RzpPlX06/79efvc9hRv/gbeHqjjEpuch3eFTvQOiupNl8jS98GZPGlVhFCsGlNKpOuCKVUKeZIiEL/bteh/N8EGiJ1HRw7iHL7QygBQU2sRMVQsZM6r27YvaPbLnwnJosvtcrG1TuYHGykTFPCBsMBYsPGNrhfbF4DXbqhJCZd8PGKoxrfc8vQOkqpCUhsg8QSyGN8qRWO78lmcoiBUqWENd6pjI17qcFUWaKsBE5nodxyb+Nje+GE3B8w5y1HEQ6s/iPl9NhtSBZf+lXOnSpglFJJsb2CpcavGRrxeKP58cSmlQAo/YY0eryxdAOasnXYfPphCfoNTg/52fq2JIsv/SKqqrJn926G1jmo9fJgmeFrAn17Eu4zoH6MEAKx6lvE8kUoI8aidIlusA69NQtD2QaEeQSVATe28W8ggSy+9As4nU5WrlpFDxUiul7BUs1/8fAOZESXx+p35YXVgrpgLqTvRBl6Fco9T/5vBUJgKNuAT+laHHoTmqgpUHH5r7uXGpPFl1osdc9+NCWljOk/kP2afZQZahkT9TweWkP9GPH1x3BwN8ptD6GM/8llucKJT/FKDBXbqPEdRFXwTZj1PrTFB26kxmTxpRax1jow5BdyU59+lFDCUd9CkqNeQvuTb68RdjsifSdKYhKapOvrlytOK/5nv8ajJgurfyLV5muhifnypbYhiy81S6gqeTsyuD66Cydry0jxXMiI0D80LH1VBeLbz8BWgzL0qvrlGnsZAfn/RGsvozLkd9j8Ei70FFIbk8WXLkqoKsW7TjDGX2FPzVG2+C4nyNANk/f5j1wLazVixWLExpVQV4sy4WaUXudP9GnrzhGQ9wmKcFAe+aC8OMeNyOJLTRKqSsXOkwzwtpFOOlt91xNrSqJ38A0oioI4fQL14z9BcRHKsKtQrp2MEt4VAMVpw7/gcxQEZZGP4PSUH9N2J7L40gXVOlROpWYyzq+ONM1OdmtOcW2PORj0QYi6WtRvP0OsWQK+AWimv40S+5NJMlQ7/mf/jdZeSnnkg7L0bkgWX2qkqNrOni1ZPBDuIEM5RIaulOt6vorGVou6dQUiZRkUFaCMSkaZNBXF+L858DT2UvwLF6K3naEidDJ2724u/E2kpsjiSw3sz6/Ckn6ae8IcFFDEDv0RJvR6FXZtRf3yI6ixQJduaH7/OkrvhhOqelQfxq9wMSgKFaG3U+vb30W/hdQcWXyp3qojxfQ9m8dvIzScFrms9VjH6NgZsPRrxIpFENsbzW0PokQ1nkvRu1mAjO8AABnzSURBVGwzviUrsXt2oSLsDlR94AWeQXIXsvgSAAWVtYwrzycqQGELWzjkdZTx3WdgPFOCumIRSmISyt3TUHT6Bo9T1FqMJWsxVGzD5tOPypBJoNE38SySu5DFl3CqgkMH8rnXR2EFyznjVURy91cw6E2oS+eB0Rfl9ocblF5xWjCWrMW7as//fbpuBNXm6+WFOe2ELL7E2pR0bjM7qKCWkxTx25hX8NYHoG5edX4SjTsfQ/HyPj9YqHhX7MBYuhZFrcPmNwSb72D5Hn07I4vfyW1ev5V7g32oUCys5zjX930bHRrUL/9+/qKc2N4ooyecHywEvkXf4V21hzrvWKrM18m36topWfxOqqqqis3bvue20GgqlUrSzSqJXR4GQF04H7FxJcqEm1BuuhtFc34OPEPZRryr9mAJHI8lKFlOed2OyeJ3QjU1Vs7s/i/3h/XCIVSOBQbRs0tPhKoiNixHpCxDGXcNmklT6x/jXb4Nn9I12HwGYAlKkqVv52TxO5mqgiICzh7iN4H9yXLmUx45hIgwM+JsHurnH0BmBvQdjHLr/cD5k3iG8q0YyzZSa+xNZeit8gReByCL34nYckvpdi6POsWbRfm7CU6YRI8QH9QdGxH/ngc6Pcp9T51/607Y8Tu7EM/qAyio1PgOoSrkZjn1dQchi99JOBxOAooyqdbY+OTUXjyd0YwK9ED9998Qm1dBXG80Dz+PEmACIfA7twTP6v3UBIzC5jMQh2eE3L3vQGTxO4HMYiteJ9MY7hHEt+WHKDujZdiAQNQ/z4Ts4ygTbzn/LTe6838OXpW78KpKpzooGWvQhafFlto3WfwOrrrWgWfWAYZ7BbHJupv0I3UM7xLGwB/+BVYLmsdeRBn8f/PZC4FX5W58zy2j1hCPNXCcS7NLl48sfgdVY1dZcqCAmuPp3BdgZGNdKvtOmrjXcgLPlSshKhbNU6+idD3/6TnFUYXvuWV4WQ5T5x1LRdid8iReByaL3wEtP1bG5+nn8HI6WNYTTnGKPZm+/C7tO7SI81fijZ5Q//68otYSmPcRWkcl1aarsQZcKU/idXCy+B1MVomNBbuLSPbWcnvEWQyaYHZVnePWEwfQGH3QPPsmiimkwWO8y1PR2Uspi3gQuyHGRcmlttSifbn09HSefvppnnzySZYuXdrkuB07djB58mROnDhxyQJKv8wP+8qYrA1kYuABevkGs1XZwbBuV6HJOYky9reNSu9RfRhj6Vpqjb1l6TuRZouvqirz589n5syZvPfee2zbto3c3NxG42pqali5ciVxcXGXJajUvIN5FkKKVLqHrWVUYBzHdNlE+g5DO/ct8PFFGTq6wXhtXSF+hYtweHahInSKi1JLrtBs8bOysggLCyM0NBSdTkdiYiJpaWmNxi1cuJAbbrgBvV5+FtsVzlbVsXFTPn0jV3NNQC/y1CJCCEf359dBp0Pz3P9DCTT97wFC4Fe4CDQeVITfBT+ZKlvq+Jo9xi8tLcVk+t8fjMlkIjMzs8GY7OxsiouLGTJkCN9//32T60pJSSElJQWA2bNnYzabmw+o07VonCu4U7YfUjbzRNxZIvVDKdRVEBg/kpKn7kQf35eAF99G4xfQ8AFlB9DU5qN2v5egkO4uyexOr9/PuXM2aH2+ZosvhGi07KdfeayqKp999hnTpk1r9smSk5NJTk6uv11cXNzsY8xmc4vGuYI7ZLPZbBzdtJ2HQkxYFW/SvE4TEX8Npcu+AgHOe5+itM4BP8mpqLUEnfkChz6YUiW2wX1tyR1ev6a4czZoeb6IiIgLLm92V99kMlFSUlJ/u6SkhMDA/82nZrPZyMnJ4bXXXuPxxx8nMzOTd955R57gawO5ubl895+vGRfsQ4Emn42B54jseR2KRoM4vBd9fB8U08++flqo+BZ9h9ZRRlXILaDIN3Y6o2b/1WNiYigoKKCoqIigoCBSU1N56qmn6u83GAzMnz+//vasWbO4++67iYmRZ4gvJ6vVyvf//YG7Bkeh1+hI89AwNOoGAMTxQ3DmBB5THmj0lZSG8s14VR+gyvRbOWtOJ9Zs8bVaLVOnTuWtt95CVVXGjRtH165dWbhwITExMSQkyO9Ca2t2u4O0lO080LcP0V4B7NBmMbTXzQCIGivq5x9CcBiG6yZhq6n93wNVO4byrdQaelATOLqJtUudQYv28wYPHszgwYMbLJsy5cJv/8yaNavVoaSmlZVWk7lhE5O6dcEm7KzWLicydjIA4tBe1K8/huJCNE++gsboC5ZqdHVn0dqL8bBmonFasAbI0nd28gCvnTm5/SDXd+/C0WqVjf7fYzA46OvVDbE3FfXvs8EciubZt1Di+4CjhqCcv6Kznz9HI1Cw+fST324jyeK3G0JQsC+Ha8IN5FXbWOvrgdCepG/APSiKgnP5IgjrguaVv6L8eC1F4Xp09hIqQ36H3esKnPogeTJPAlp4ya7kYkJQdiCbIZoKjpSWsM/oRUTQRrSKB1EBiYiTx+DMSZTx19aXXlFrUYq2UecVjc0vAadHiCy9VE/+JbQD5w6fYoCwsDEnh9SSYnr1PEFexV76h0xBt2UT6pJ//98luVcBoK85hW/RN2AvxRp+tYvTS+5IFt/N5Zw6x3BHNbsKK1hz+jQjbvTlRMVmeoqhxP9tDSL3FPToh+aex9F4e2AsXoF3+VZUXQCi1x+os7vv1WeS68jiu7FqSy3dzp3lHHbWWFcRPlTLicpUujt70+eDFAgOQ3l4OpqBAzBW7sD7dCoa1UaN3zCqzddg8o902VV5knuTxXdjJzJz+K0eFmkXY4zPBY038cow+n20FeWK7uifnYGxOhWvM++gCAe1xt5YAsfj8Ip0dXTJzcniu6nCiioS1LOUapwcOa6jV+hzJEb5If48AwID8Lt/FIb8D0BRsPkOwhpw5fkTeJLUArL4bqimpga/zO2YdKF8kbudbjXXMmz3MsS3x/CM8cX3hl7obXup8RuKJSgZVefn6shSOyOL72byz1QRlr+fSK8wVpYdJC6tmMiC2Wjjogm8qzse/g6cio2K0Nuo9R3g6rhSOyWL70aKCm1wZC/hIf5871zFgK+2oenRF80THxHgWIvemkml+RZsfoPke/JSq8gLeNyEwy44tiWVwSGBHNCm47UnDe3Em9E8+yaehgo8LRlYgsZj8x8qSy+1miy+m0hZuI5xEd6UqOVsYxPRA+9Dc+t96OvO4lf4Hxz6kPPTXkvSJSA3HW7gYMp2ukUUEWLox/eapfSLvAOfwDH4Fi3Bq3I3qtZIecR9cksvXTLyL8nFsncfJMAnm+Fe/cgQZ+gWcydBhmj8C77Aw3qUGv8RWALHIXS+ro4qdSCy+C4ihGDHtykMD/eii7Efe+z5BA+6Gr1Sh1/BZ3haj1MVfAM1/iNdHVXqgGTxXUBYqti/agfXdwvGqTj4XvM9/Qc8go91P8bSFDSOCqqCb6TGf4Sro0odlCx+GxNZGWQfyueamDCyreWk+H1Fd09fIs7MQUHg8AijPPIhOR+edFnJ4rchkZ9D+YbtXDl0GPvOlZIbf4yaagsjddFY/YZQZ4jF7nWF/JZa6bKTxW8joigfn7TdRA4dRk5VFbmR3Sm1fk2YxpPKLg+h6oNcHVHqROSmpQ2IvanoPp6Df1QsqXm5/PVUMXGG/1CqWujiN1KWXmpzcot/GYmifMSKxTh2bsHj3ulUOqykGTYxpHs5qy0W/HQBRIbd4eqYUicki38ZiEN7UL/7HHKyKfONQHv340R5efGddjGe3mdR0BPvN5ye4fei13q5Oq7UCcniX0Kithbx5d9x7NxKQdwEcq9+BpP5OOMNZrbV7eE3QSqeul6Uh9+L0zPM1XGlTkwW/xIRqhP1kz9TdSKP3ePfpwYDQSFbGOPblSzHaWKvCMa7+jglkfJEnuR68uTeJSIW/4uqrDx2jnwN1ctITJ9crvY1Uem0kOEIxL/2GHavaFl6yS3I4l8C4mweFTv3sXPEqyieniSM0hNUmYk33qy2WEnsbUBnP4dNTpwhuQlZ/FYStTYqvv6anYNfROPlSf8ROv67fT59DF057DzLxH5eBBQtwu4ZKWfMkdyGPMZvpbqFn7En4Do0Xp4MHqVj+c553HFFL3SqnoiuwfiWfIvN2JfK0Mmg0bs6riQBsvitknsolx11idT4hDDwShu7c97noS7jCVSDqAyBgKr/UucVRWXYFPlZesmttOivMT09nQULFqCqKklJSdx0000N7v/hhx9Yt24dWq0WPz8/HnvsMYKDgy9LYHdRmG9n1xYbXnoD/QdWc7rwa27TXI/q1FEUJjDVLMbhGU5F2F2y9JLbafYYX1VV5s+fz8yZM3nvvffYtm0bubm5DcZER0cze/Zs/vKXvzBixAi++OKLyxbYHdTWquzfZcHXksfw2u+pqF7H78TVVNocHAzpgr+6BadHMOWRDyF0Pq6OK0mNNFv8rKwswsLCCA0NRafTkZiYSFpaWoMxffv2xdPTE4C4uDhKS0svT1o3cXh3NXU2J/1P/wdrvzgm6hLIsp2jsmdvevieQF+bT43vYITG09VRJemCmt0HLS0txWQy1d82mUxkZmY2OX79+vUMHDjwgvelpKSQkpICwOzZszGbm/9CR51O16JxbaUqv5iy/FquDThK5M2TEQh2OY/RN/ku9Ln/QSneifDvhbHb1Rh1BpdmdbfX7ufcOZ87Z4PW52u2+EKIRssURbng2M2bN3Py5ElmzZp1wfuTk5NJTk6uv13cgi90NJvNLRrXFkRxIQXrM5kSE4BG8WNr3W4yPI9wTZ+n0GTMhroiqoMmYA0cA+VWwOrSvO702l2IO+dz52zQ8nwREREXXN5s8U0mEyUlJfW3S0pKCAwMbDTuwIEDLFmyhFmzZqHXd7y3rcSZk5Su2c2gIb04W1PHwlObof8eBviPICTvU1B0lEfcj90Q5+qoktSsZo/xY2JiKCgooKioCIfDQWpqKgkJCQ3GZGdn88knnzB9+nT8/f0vW1hXUTeswPL3D4gb2JvSWidraxej7b8XP0VLgu00To8QSrs+IUsvtRvNbvG1Wi1Tp07lrbfeQlVVxo0bR9euXVm4cCExMTEkJCTwxRdfYLPZePfdd4HzuyEvvPDCZQ9/uQmrBfHdZ4hNq9Df+hIeWpUUFlIWkku01p/xEddi10ZjMcSDonV1XElqMUVc6CC+jeTn5zc7xlXHWuLEUdR//BnKiimccA+DYmLJ0Bxkq24tid7xmKOnExwS3iGOA13FnfO5czZog2P8zkaoKmLNEsSSf0NQMEemvkg/DwtOxUGBfjeTjEOxd3kQIS+/ldoxWfyfEIX5qF99DBn7YEgix666ncS6ArwUE2f0mxl0xWPUGePkLLhSuyeLDwiHA7FiEWLFN6DTo9z5KHm9hzA47zgaxYNTHivwjZmK3TPc1VEl6ZLo9MUXpefOH8ufOIoybAzK5KlY9FZCj+8gQIkmU7OWgO734ZSllzqQTl18IQTqB2/AuUKUh55DM2w0x4/vokvNKaLpxWHbQXwGTcPp6dor8CTpUuvcB6vHD0PuKZTJU8+X/kQakTWniBW92FeVh1f/yehl6aUOqNNu8UVVBeo/3wVTCMqwqygqO0J0Vf75LX1NEbpeSXgbOu3LI3VwnXKLLxwO1I/fgcoKNI+9SEVlDSGncriCaE44MtD2HYPJLN+ukzquzln8RfPh2EGUe57gLE5Ccg4RogRzUrMV/YAb8fOVW3qpY+t0xRdHDyA2LEdJvpEq/270K63GV2vguH41xrib0enlN9tIHV+n2rSJvDOoC+aCORR9/zH0qq0iV1OI1WMroRG3UOt94csbJamj6RTFFzYrYtlXiPU/gMGH0ntfYEBtDbs1O8nQpnJt8K3U+ic0vyJJ6iA6RfHVd1+BU5koV02gclgifWrsFFFKtjjM6G4zqJUfp5U6mQ5ffHE2D7KPo0y6n5IuAfSuEVRQwXZ7FqOGvufqeJLkEh3+5J44vA+BQobRRO86P6qpZLmlkqFDH3V1NElymQ6/xa8+fZaaW14g2WikXCkhXVtH8qgbXR1LklyqQ2/xK87VENCvG4PCfTmtZLOhYjs9+17t6liS5HIdtvi2wmICTu8gTB9CumYv35StJyj0d66OJUluoUMWXz2VRVX2esJ1ZnYom1m6v4hBIY/So0dPV0eTJLfQ4Y7xrXW1WIrW089rOKeVo+zJ7cJdv/sNBoP8lJ0k/ahDFT+/shYyljLIaxgVlJNpiOXmawe5OpYkuZ0Os6u/O7cce8a3JHj1Jods8r2N9I6TpZekC2n3xRdC8M3h41iK5jDcqw95ZOI0xBDYQ16CK0lNade7+jaHyj/3LmGo12EmaK7DIeqwh47Au4m5xCVJOq/dbvELq+t4de1uRnof5Ub1ZhRhIz8yCg9ZeklqVrssvioEH2w+xn3haxnv/A21FLHHyw+PkBBXR5OkdqFd7uqf3LOGP16xm2DHGBShsKZcMHjsQFfHkqR2o90Vv+zcMeIM+/GtG4dO6ElV7Qwem4SiKK6OJkntRrva1T+UX4LI30Zo3UTqhIM0vYaeQxJl6SXpF2o3W/yC8mK6nd1CnGYoJ+wnsYb0Jyaqm6tjSVK71C62+IcLsgnI3kqcJpZTzj3oDVGYZOkl6Vdr0RY/PT2dBQsWoKoqSUlJ3HTTTQ3ut9vtzJs3j5MnT+Lr68szzzxDyCU6w/7Vzp1cVXWAGCWWHHU3Ht2TIbDrJVm3JHVWzW7xVVVl/vz5zJw5k/fee49t27aRm5vbYMz69esxGo188MEHXHvttXz55ZeXJNyBM0cZXr2TGGI5Yt2PvddtsvSSdAk0W/ysrCzCwsIIDQ1Fp9ORmJhIWlpagzG7d+9m7NixAIwYMYJDhw4hhGhVMKe9jt4lx+gl+rG37DhqVDJe3t6tWqckSec1u6tfWlqKyWSqv20ymcjMzGxyjFarxWAwUFVVhZ+fX4NxKSkppKSkADB79mzMZnOTz6s67ZxwWtmrphM18UF8/Xxb/lu1EZ1Od9HfwdVkvl/PnbNB6/M1W/wLbbl//vZZS8YAJCcnk5ycXH+7uLj4os8dmHA7ZrOZ4uJiaotrm4va5n7M5q5kvl/PnbNBy/NFNHEJe7O7+iaTiZKSkvrbJSUlBAYGNjnG6XRitVrx8fFpNpQkSa7RbPFjYmIoKCigqKgIh8NBamoqCQkNP/I6ZMgQNm7cCMCOHTvo06ePvKhGktxYs7v6Wq2WqVOn8tZbb6GqKuPGjaNr164sXLiQmJgYEhISGD9+PPPmzePJJ5/Ex8eHZ555pi2yS5L0KymitaffWyE/P7/ZMe58rOXO2UDmaw13zgZtcIwvSVLHI4svSZ2QLL4kdUKy+JLUCbn05J4kSa7h9lv8F1980dURmuTO2UDmaw13zgatz+f2xZck6dKTxZekTkg7a9asWa4O0Zzu3bu7OkKT3DkbyHyt4c7ZoHX55Mk9SeqE5K6+JHVCsviS1Am5zfTarpzQs7XZfvjhB9atW4dWq8XPz4/HHnuM4ODgNsnWknw/2rFjB++++y5vv/02MTExbpMtNTWVxYsXoygKUVFRPP30022SrSX5iouL+fDDD7FYLKiqyh133MHgwYPbJNvf/vY39u7di7+/P3PmzGl0vxCCBQsWsG/fPjw9PZk2bVrLj/uFG3A6neKJJ54QZ8+eFXa7XTz33HMiJyenwZhVq1aJjz/+WAghxNatW8W7777rNtkOHjwobDabEEKI1atXt1m2luYTQgir1SpeeeUVMXPmTJGVleU22fLz88Xzzz8vqqqqhBBClJeXt0m2lub76KOPxOrVq4UQQuTk5Ihp06a1Wb7Dhw+LEydOiD/84Q8XvH/Pnj3irbfeEqqqimPHjokZM2a0eN1usavvqgk9L1W2vn374unpCUBcXBylpaWXPdcvyQewcOFCbrjhBvR6vVtlW7duHRMnTqyfscnf39+t8imKgtVqBcBqtTaafepy6t2790Vnstq9ezejR49GURTi4+OxWCyUlZW1aN1uUfwLTej58/I0NaGnO2T7qfXr1zNwYNt9gWdL8mVnZ1NcXMyQIUPaLFdLs+Xn51NQUMDLL7/MH//4R9LT090q36RJk9iyZQuPPvoob7/9NlOnTm2zfM0pLS1tMOFmc3+bP+UWxb/QlvvXTuh5qf2S5928eTMnT57khhtuuNyx6jWXT1VVPvvsM+655542y/Sjlrx2qqpSUFDAq6++ytNPP81HH32ExWJxm3zbtm1j7NixfPTRR8yYMYMPPvgAVVXbJF9zWtMJtyi+O0/o2ZJsAAcOHGDJkiVMnz69TXenm8tns9nIycnhtdde4/HHHyczM5N33nmHEydOuDwbQFBQEEOHDkWn0xESEkJERAQFBQWXPVtL861fv56RI0cCEB8fj91ub5M9zZYwmUwNZuFp6m/zQtyi+O48oWdLsmVnZ/PJJ58wffr0Nj1GbUk+g8HA/Pnz+fDDD/nwww+Ji4tj+vTpbXJWvyWv3bBhwzh06BAAlZWVFBQUEBoaetmztTSf2Wyuz5ebm4vdbm/0fRGukpCQwObNmxFCcPz4cQwGQ4uL7zZX7u3du5fPPvusfkLPW265pcGEnnV1dcybN4/s7Oz6CT3b6g+kuWxvvPEGZ86cISAgADj/x/LCCy+0SbaW5PupWbNmcffdd7fZ23nNZRNC8Pnnn5Oeno5Go+GWW25h1KhRbZKtJflyc3P5+OOPsdlsANx1110MGDCgTbLNnTuXjIwMqqqq8Pf3Z/LkyTgcDgAmTJiAEIL58+ezf/9+PDw8mDZtWov/Xd2m+JIktR232NWXJKltyeJLUickiy9JnZAsviR1QrL4ktQJyeJLUickiy9JndD/B90WWzdOSPkkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "warp_f.plot()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Functional Principal Components Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define the FPCA as a vertical analysis\n",
    "fPCA_analysis = fPCA.fdavpca(warp_f)\n",
    "\n",
    "# Run the FPCA on a 3 components basis\n",
    "fPCA_analysis.calc_fpca(no=3)\n",
    "fPCA_analysis.plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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h=1;for(c=l(t,u,t.length,e),u=0;u<o;u++)h*=e;this.imuln(h),this.words[0]+c<67108864?this.words[0]+=c:this._iaddn(c)}},i.prototype.copy=function(t){t.words=new Array(this.length);for(var e=0;e<this.length;e++)t.words[e]=this.words[e];t.length=this.length,t.negative=this.negative,t.red=this.red},i.prototype.clone=function(){var t=new i(null);return this.copy(t),t},i.prototype._expand=function(t){for(;this.length<t;)this.words[this.length++]=0;return this},i.prototype.strip=function(){for(;this.length>1&&0===this.words[this.length-1];)this.length--;return this._normSign()},i.prototype._normSign=function(){return 1===this.length&&0===this.words[0]&&(this.negative=0),this},i.prototype.inspect=function(){return(this.red?\"<BN-R: \":\"<BN: \")+this.toString(16)+\">\"};var c=[\"\",\"0\",\"00\",\"000\",\"0000\",\"00000\",\"000000\",\"0000000\",\"00000000\",\"000000000\",\"0000000000\",\"00000000000\",\"000000000000\",\"0000000000000\",\"00000000000000\",\"000000000000000\",\"0000000000000000\",\"00000000000000000\",\"000000000000000000\",\"0000000000000000000\",\"00000000000000000000\",\"000000000000000000000\",\"0000000000000000000000\",\"00000000000000000000000\",\"000000000000000000000000\",\"0000000000000000000000000\"],u=[0,0,25,16,12,11,10,9,8,8,7,7,7,7,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5],h=[0,0,33554432,43046721,16777216,48828125,60466176,40353607,16777216,43046721,1e7,19487171,35831808,62748517,7529536,11390625,16777216,24137569,34012224,47045881,64e6,4084101,5153632,6436343,7962624,9765625,11881376,14348907,17210368,20511149,243e5,28629151,33554432,39135393,45435424,52521875,60466176];function f(t,e,r){r.negative=e.negative^t.negative;var n=t.length+e.length|0;r.length=n,n=n-1|0;var a=0|t.words[0],i=0|e.words[0],o=a*i,s=67108863&o,l=o/67108864|0;r.words[0]=s;for(var c=1;c<n;c++){for(var u=l>>>26,h=67108863&l,f=Math.min(c,e.length-1),p=Math.max(0,c-t.length+1);p<=f;p++){var d=c-p|0;u+=(o=(a=0|t.words[d])*(i=0|e.words[p])+h)/67108864|0,h=67108863&o}r.words[c]=0|h,l=0|u}return 0!==l?r.words[c]=0|l:r.length--,r.strip()}i.prototype.toString=function(t,e){var r;if(e=0|e||1,16===(t=t||10)||\"hex\"===t){r=\"\";for(var a=0,i=0,o=0;o<this.length;o++){var s=this.words[o],l=(16777215&(s<<a|i)).toString(16);r=0!==(i=s>>>24-a&16777215)||o!==this.length-1?c[6-l.length]+l+r:l+r,(a+=2)>=26&&(a-=26,o--)}for(0!==i&&(r=i.toString(16)+r);r.length%e!=0;)r=\"0\"+r;return 0!==this.negative&&(r=\"-\"+r),r}if(t===(0|t)&&t>=2&&t<=36){var f=u[t],p=h[t];r=\"\";var d=this.clone();for(d.negative=0;!d.isZero();){var g=d.modn(p).toString(t);r=(d=d.idivn(p)).isZero()?g+r:c[f-g.length]+g+r}for(this.isZero()&&(r=\"0\"+r);r.length%e!=0;)r=\"0\"+r;return 0!==this.negative&&(r=\"-\"+r),r}n(!1,\"Base should be between 2 and 36\")},i.prototype.toNumber=function(){var t=this.words[0];return 2===this.length?t+=67108864*this.words[1]:3===this.length&&1===this.words[2]?t+=4503599627370496+67108864*this.words[1]:this.length>2&&n(!1,\"Number can only safely store up to 53 bits\"),0!==this.negative?-t:t},i.prototype.toJSON=function(){return this.toString(16)},i.prototype.toBuffer=function(t,e){return n(\"undefined\"!=typeof o),this.toArrayLike(o,t,e)},i.prototype.toArray=function(t,e){return this.toArrayLike(Array,t,e)},i.prototype.toArrayLike=function(t,e,r){var a=this.byteLength(),i=r||Math.max(1,a);n(a<=i,\"byte array longer than desired length\"),n(i>0,\"Requested array length <= 0\"),this.strip();var o,s,l=\"le\"===e,c=new t(i),u=this.clone();if(l){for(s=0;!u.isZero();s++)o=u.andln(255),u.iushrn(8),c[s]=o;for(;s<i;s++)c[s]=0}else{for(s=0;s<i-a;s++)c[s]=0;for(s=0;!u.isZero();s++)o=u.andln(255),u.iushrn(8),c[i-s-1]=o}return c},Math.clz32?i.prototype._countBits=function(t){return 32-Math.clz32(t)}:i.prototype._countBits=function(t){var e=t,r=0;return e>=4096&&(r+=13,e>>>=13),e>=64&&(r+=7,e>>>=7),e>=8&&(r+=4,e>>>=4),e>=2&&(r+=2,e>>>=2),r+e},i.prototype._zeroBits=function(t){if(0===t)return 26;var e=t,r=0;return 0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},i.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},i.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;e<this.length;e++){var r=this._zeroBits(this.words[e]);if(t+=r,26!==r)break}return t},i.prototype.byteLength=function(){return Math.ceil(this.bitLength()/8)},i.prototype.toTwos=function(t){return 0!==this.negative?this.abs().inotn(t).iaddn(1):this.clone()},i.prototype.fromTwos=function(t){return this.testn(t-1)?this.notn(t).iaddn(1).ineg():this.clone()},i.prototype.isNeg=function(){return 0!==this.negative},i.prototype.neg=function(){return this.clone().ineg()},i.prototype.ineg=function(){return this.isZero()||(this.negative^=1),this},i.prototype.iuor=function(t){for(;this.length<t.length;)this.words[this.length++]=0;for(var e=0;e<t.length;e++)this.words[e]=this.words[e]|t.words[e];return this.strip()},i.prototype.ior=function(t){return n(0==(this.negative|t.negative)),this.iuor(t)},i.prototype.or=function(t){return this.length>t.length?this.clone().ior(t):t.clone().ior(this)},i.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},i.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;r<e.length;r++)this.words[r]=this.words[r]&t.words[r];return this.length=e.length,this.strip()},i.prototype.iand=function(t){return n(0==(this.negative|t.negative)),this.iuand(t)},i.prototype.and=function(t){return this.length>t.length?this.clone().iand(t):t.clone().iand(this)},i.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},i.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},i.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},i.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},i.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},i.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var a=0;a<e;a++)this.words[a]=67108863&~this.words[a];return r>0&&(this.words[a]=~this.words[a]&67108863>>26-r),this.strip()},i.prototype.notn=function(t){return this.clone().inotn(t)},i.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,a=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<a:this.words[r]&~(1<<a),this.strip()},i.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var a=0,i=0;i<n.length;i++)e=(0|r.words[i])+(0|n.words[i])+a,this.words[i]=67108863&e,a=e>>>26;for(;0!==a&&i<r.length;i++)e=(0|r.words[i])+a,this.words[i]=67108863&e,a=e>>>26;if(this.length=r.length,0!==a)this.words[this.length]=a,this.length++;else if(r!==this)for(;i<r.length;i++)this.words[i]=r.words[i];return this},i.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,a=this.cmp(t);if(0===a)return this.negative=0,this.length=1,this.words[0]=0,this;a>0?(r=this,n=t):(r=t,n=this);for(var i=0,o=0;o<n.length;o++)i=(e=(0|r.words[o])-(0|n.words[o])+i)>>26,this.words[o]=67108863&e;for(;0!==i&&o<r.length;o++)i=(e=(0|r.words[o])+i)>>26,this.words[o]=67108863&e;if(0===i&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,a,i,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],h=8191&u,f=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,v=0|o[2],m=8191&v,y=v>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],k=8191&w,T=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],C=8191&E,L=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],V=8191&j,U=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,at=0|s[6],it=8191&at,ot=at>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ht=8191&ut,ft=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var vt=(c+(n=Math.imul(h,V))|0)+((8191&(a=(a=Math.imul(h,U))+Math.imul(f,V)|0))<<13)|0;c=((i=Math.imul(f,U))+(a>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(d,V),a=(a=Math.imul(d,U))+Math.imul(g,V)|0,i=Math.imul(g,U);var mt=(c+(n=n+Math.imul(h,H)|0)|0)+((8191&(a=(a=a+Math.imul(h,G)|0)+Math.imul(f,H)|0))<<13)|0;c=((i=i+Math.imul(f,G)|0)+(a>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(m,V),a=(a=Math.imul(m,U))+Math.imul(y,V)|0,i=Math.imul(y,U),n=n+Math.imul(d,H)|0,a=(a=a+Math.imul(d,G)|0)+Math.imul(g,H)|0,i=i+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(h,W)|0)|0)+((8191&(a=(a=a+Math.imul(h,X)|0)+Math.imul(f,W)|0))<<13)|0;c=((i=i+Math.imul(f,X)|0)+(a>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,V),a=(a=Math.imul(b,U))+Math.imul(_,V)|0,i=Math.imul(_,U),n=n+Math.imul(m,H)|0,a=(a=a+Math.imul(m,G)|0)+Math.imul(y,H)|0,i=i+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,a=(a=a+Math.imul(d,X)|0)+Math.imul(g,W)|0,i=i+Math.imul(g,X)|0;var xt=(c+(n=n+Math.imul(h,J)|0)|0)+((8191&(a=(a=a+Math.imul(h,K)|0)+Math.imul(f,J)|0))<<13)|0;c=((i=i+Math.imul(f,K)|0)+(a>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(k,V),a=(a=Math.imul(k,U))+Math.imul(T,V)|0,i=Math.imul(T,U),n=n+Math.imul(b,H)|0,a=(a=a+Math.imul(b,G)|0)+Math.imul(_,H)|0,i=i+Math.imul(_,G)|0,n=n+Math.imul(m,W)|0,a=(a=a+Math.imul(m,X)|0)+Math.imul(y,W)|0,i=i+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,a=(a=a+Math.imul(d,K)|0)+Math.imul(g,J)|0,i=i+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(h,$)|0)|0)+((8191&(a=(a=a+Math.imul(h,tt)|0)+Math.imul(f,$)|0))<<13)|0;c=((i=i+Math.imul(f,tt)|0)+(a>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,V),a=(a=Math.imul(M,U))+Math.imul(S,V)|0,i=Math.imul(S,U),n=n+Math.imul(k,H)|0,a=(a=a+Math.imul(k,G)|0)+Math.imul(T,H)|0,i=i+Math.imul(T,G)|0,n=n+Math.imul(b,W)|0,a=(a=a+Math.imul(b,X)|0)+Math.imul(_,W)|0,i=i+Math.imul(_,X)|0,n=n+Math.imul(m,J)|0,a=(a=a+Math.imul(m,K)|0)+Math.imul(y,J)|0,i=i+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,a=(a=a+Math.imul(d,tt)|0)+Math.imul(g,$)|0,i=i+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(h,rt)|0)|0)+((8191&(a=(a=a+Math.imul(h,nt)|0)+Math.imul(f,rt)|0))<<13)|0;c=((i=i+Math.imul(f,nt)|0)+(a>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(C,V),a=(a=Math.imul(C,U))+Math.imul(L,V)|0,i=Math.imul(L,U),n=n+Math.imul(M,H)|0,a=(a=a+Math.imul(M,G)|0)+Math.imul(S,H)|0,i=i+Math.imul(S,G)|0,n=n+Math.imul(k,W)|0,a=(a=a+Math.imul(k,X)|0)+Math.imul(T,W)|0,i=i+Math.imul(T,X)|0,n=n+Math.imul(b,J)|0,a=(a=a+Math.imul(b,K)|0)+Math.imul(_,J)|0,i=i+Math.imul(_,K)|0,n=n+Math.imul(m,$)|0,a=(a=a+Math.imul(m,tt)|0)+Math.imul(y,$)|0,i=i+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,a=(a=a+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,i=i+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(h,it)|0)|0)+((8191&(a=(a=a+Math.imul(h,ot)|0)+Math.imul(f,it)|0))<<13)|0;c=((i=i+Math.imul(f,ot)|0)+(a>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,V),a=(a=Math.imul(O,U))+Math.imul(I,V)|0,i=Math.imul(I,U),n=n+Math.imul(C,H)|0,a=(a=a+Math.imul(C,G)|0)+Math.imul(L,H)|0,i=i+Math.imul(L,G)|0,n=n+Math.imul(M,W)|0,a=(a=a+Math.imul(M,X)|0)+Math.imul(S,W)|0,i=i+Math.imul(S,X)|0,n=n+Math.imul(k,J)|0,a=(a=a+Math.imul(k,K)|0)+Math.imul(T,J)|0,i=i+Math.imul(T,K)|0,n=n+Math.imul(b,$)|0,a=(a=a+Math.imul(b,tt)|0)+Math.imul(_,$)|0,i=i+Math.imul(_,tt)|0,n=n+Math.imul(m,rt)|0,a=(a=a+Math.imul(m,nt)|0)+Math.imul(y,rt)|0,i=i+Math.imul(y,nt)|0,n=n+Math.imul(d,it)|0,a=(a=a+Math.imul(d,ot)|0)+Math.imul(g,it)|0,i=i+Math.imul(g,ot)|0;var kt=(c+(n=n+Math.imul(h,lt)|0)|0)+((8191&(a=(a=a+Math.imul(h,ct)|0)+Math.imul(f,lt)|0))<<13)|0;c=((i=i+Math.imul(f,ct)|0)+(a>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(D,V),a=(a=Math.imul(D,U))+Math.imul(R,V)|0,i=Math.imul(R,U),n=n+Math.imul(O,H)|0,a=(a=a+Math.imul(O,G)|0)+Math.imul(I,H)|0,i=i+Math.imul(I,G)|0,n=n+Math.imul(C,W)|0,a=(a=a+Math.imul(C,X)|0)+Math.imul(L,W)|0,i=i+Math.imul(L,X)|0,n=n+Math.imul(M,J)|0,a=(a=a+Math.imul(M,K)|0)+Math.imul(S,J)|0,i=i+Math.imul(S,K)|0,n=n+Math.imul(k,$)|0,a=(a=a+Math.imul(k,tt)|0)+Math.imul(T,$)|0,i=i+Math.imul(T,tt)|0,n=n+Math.imul(b,rt)|0,a=(a=a+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,i=i+Math.imul(_,nt)|0,n=n+Math.imul(m,it)|0,a=(a=a+Math.imul(m,ot)|0)+Math.imul(y,it)|0,i=i+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,a=(a=a+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,i=i+Math.imul(g,ct)|0;var Tt=(c+(n=n+Math.imul(h,ht)|0)|0)+((8191&(a=(a=a+Math.imul(h,ft)|0)+Math.imul(f,ht)|0))<<13)|0;c=((i=i+Math.imul(f,ft)|0)+(a>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(B,V),a=(a=Math.imul(B,U))+Math.imul(N,V)|0,i=Math.imul(N,U),n=n+Math.imul(D,H)|0,a=(a=a+Math.imul(D,G)|0)+Math.imul(R,H)|0,i=i+Math.imul(R,G)|0,n=n+Math.imul(O,W)|0,a=(a=a+Math.imul(O,X)|0)+Math.imul(I,W)|0,i=i+Math.imul(I,X)|0,n=n+Math.imul(C,J)|0,a=(a=a+Math.imul(C,K)|0)+Math.imul(L,J)|0,i=i+Math.imul(L,K)|0,n=n+Math.imul(M,$)|0,a=(a=a+Math.imul(M,tt)|0)+Math.imul(S,$)|0,i=i+Math.imul(S,tt)|0,n=n+Math.imul(k,rt)|0,a=(a=a+Math.imul(k,nt)|0)+Math.imul(T,rt)|0,i=i+Math.imul(T,nt)|0,n=n+Math.imul(b,it)|0,a=(a=a+Math.imul(b,ot)|0)+Math.imul(_,it)|0,i=i+Math.imul(_,ot)|0,n=n+Math.imul(m,lt)|0,a=(a=a+Math.imul(m,ct)|0)+Math.imul(y,lt)|0,i=i+Math.imul(y,ct)|0,n=n+Math.imul(d,ht)|0,a=(a=a+Math.imul(d,ft)|0)+Math.imul(g,ht)|0,i=i+Math.imul(g,ft)|0;var At=(c+(n=n+Math.imul(h,dt)|0)|0)+((8191&(a=(a=a+Math.imul(h,gt)|0)+Math.imul(f,dt)|0))<<13)|0;c=((i=i+Math.imul(f,gt)|0)+(a>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),a=(a=Math.imul(B,G))+Math.imul(N,H)|0,i=Math.imul(N,G),n=n+Math.imul(D,W)|0,a=(a=a+Math.imul(D,X)|0)+Math.imul(R,W)|0,i=i+Math.imul(R,X)|0,n=n+Math.imul(O,J)|0,a=(a=a+Math.imul(O,K)|0)+Math.imul(I,J)|0,i=i+Math.imul(I,K)|0,n=n+Math.imul(C,$)|0,a=(a=a+Math.imul(C,tt)|0)+Math.imul(L,$)|0,i=i+Math.imul(L,tt)|0,n=n+Math.imul(M,rt)|0,a=(a=a+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,i=i+Math.imul(S,nt)|0,n=n+Math.imul(k,it)|0,a=(a=a+Math.imul(k,ot)|0)+Math.imul(T,it)|0,i=i+Math.imul(T,ot)|0,n=n+Math.imul(b,lt)|0,a=(a=a+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,i=i+Math.imul(_,ct)|0,n=n+Math.imul(m,ht)|0,a=(a=a+Math.imul(m,ft)|0)+Math.imul(y,ht)|0,i=i+Math.imul(y,ft)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(a=(a=a+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((i=i+Math.imul(g,gt)|0)+(a>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),a=(a=Math.imul(B,X))+Math.imul(N,W)|0,i=Math.imul(N,X),n=n+Math.imul(D,J)|0,a=(a=a+Math.imul(D,K)|0)+Math.imul(R,J)|0,i=i+Math.imul(R,K)|0,n=n+Math.imul(O,$)|0,a=(a=a+Math.imul(O,tt)|0)+Math.imul(I,$)|0,i=i+Math.imul(I,tt)|0,n=n+Math.imul(C,rt)|0,a=(a=a+Math.imul(C,nt)|0)+Math.imul(L,rt)|0,i=i+Math.imul(L,nt)|0,n=n+Math.imul(M,it)|0,a=(a=a+Math.imul(M,ot)|0)+Math.imul(S,it)|0,i=i+Math.imul(S,ot)|0,n=n+Math.imul(k,lt)|0,a=(a=a+Math.imul(k,ct)|0)+Math.imul(T,lt)|0,i=i+Math.imul(T,ct)|0,n=n+Math.imul(b,ht)|0,a=(a=a+Math.imul(b,ft)|0)+Math.imul(_,ht)|0,i=i+Math.imul(_,ft)|0;var St=(c+(n=n+Math.imul(m,dt)|0)|0)+((8191&(a=(a=a+Math.imul(m,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((i=i+Math.imul(y,gt)|0)+(a>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),a=(a=Math.imul(B,K))+Math.imul(N,J)|0,i=Math.imul(N,K),n=n+Math.imul(D,$)|0,a=(a=a+Math.imul(D,tt)|0)+Math.imul(R,$)|0,i=i+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,a=(a=a+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,i=i+Math.imul(I,nt)|0,n=n+Math.imul(C,it)|0,a=(a=a+Math.imul(C,ot)|0)+Math.imul(L,it)|0,i=i+Math.imul(L,ot)|0,n=n+Math.imul(M,lt)|0,a=(a=a+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,i=i+Math.imul(S,ct)|0,n=n+Math.imul(k,ht)|0,a=(a=a+Math.imul(k,ft)|0)+Math.imul(T,ht)|0,i=i+Math.imul(T,ft)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(a=(a=a+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((i=i+Math.imul(_,gt)|0)+(a>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),a=(a=Math.imul(B,tt))+Math.imul(N,$)|0,i=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,a=(a=a+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,i=i+Math.imul(R,nt)|0,n=n+Math.imul(O,it)|0,a=(a=a+Math.imul(O,ot)|0)+Math.imul(I,it)|0,i=i+Math.imul(I,ot)|0,n=n+Math.imul(C,lt)|0,a=(a=a+Math.imul(C,ct)|0)+Math.imul(L,lt)|0,i=i+Math.imul(L,ct)|0,n=n+Math.imul(M,ht)|0,a=(a=a+Math.imul(M,ft)|0)+Math.imul(S,ht)|0,i=i+Math.imul(S,ft)|0;var Ct=(c+(n=n+Math.imul(k,dt)|0)|0)+((8191&(a=(a=a+Math.imul(k,gt)|0)+Math.imul(T,dt)|0))<<13)|0;c=((i=i+Math.imul(T,gt)|0)+(a>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,rt),a=(a=Math.imul(B,nt))+Math.imul(N,rt)|0,i=Math.imul(N,nt),n=n+Math.imul(D,it)|0,a=(a=a+Math.imul(D,ot)|0)+Math.imul(R,it)|0,i=i+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,a=(a=a+Math.imul(O,ct)|0)+Math.imul(I,lt)|0,i=i+Math.imul(I,ct)|0,n=n+Math.imul(C,ht)|0,a=(a=a+Math.imul(C,ft)|0)+Math.imul(L,ht)|0,i=i+Math.imul(L,ft)|0;var Lt=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(a=(a=a+Math.imul(M,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((i=i+Math.imul(S,gt)|0)+(a>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,it),a=(a=Math.imul(B,ot))+Math.imul(N,it)|0,i=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,a=(a=a+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,i=i+Math.imul(R,ct)|0,n=n+Math.imul(O,ht)|0,a=(a=a+Math.imul(O,ft)|0)+Math.imul(I,ht)|0,i=i+Math.imul(I,ft)|0;var Pt=(c+(n=n+Math.imul(C,dt)|0)|0)+((8191&(a=(a=a+Math.imul(C,gt)|0)+Math.imul(L,dt)|0))<<13)|0;c=((i=i+Math.imul(L,gt)|0)+(a>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),a=(a=Math.imul(B,ct))+Math.imul(N,lt)|0,i=Math.imul(N,ct),n=n+Math.imul(D,ht)|0,a=(a=a+Math.imul(D,ft)|0)+Math.imul(R,ht)|0,i=i+Math.imul(R,ft)|0;var Ot=(c+(n=n+Math.imul(O,dt)|0)|0)+((8191&(a=(a=a+Math.imul(O,gt)|0)+Math.imul(I,dt)|0))<<13)|0;c=((i=i+Math.imul(I,gt)|0)+(a>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ht),a=(a=Math.imul(B,ft))+Math.imul(N,ht)|0,i=Math.imul(N,ft);var It=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(a=(a=a+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((i=i+Math.imul(R,gt)|0)+(a>>>13)|0)+(It>>>26)|0,It&=67108863;var zt=(c+(n=Math.imul(B,dt))|0)+((8191&(a=(a=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((i=Math.imul(N,gt))+(a>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=vt,l[1]=mt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=kt,l[8]=Tt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Ct,l[14]=Lt,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=zt,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=f),i.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?f(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,a=0,i=0;i<r.length-1;i++){var o=a;a=0;for(var s=67108863&n,l=Math.min(i,e.length-1),c=Math.max(0,i-t.length+1);c<=l;c++){var u=i-c,h=(0|t.words[u])*(0|e.words[c]),f=67108863&h;s=67108863&(f=f+s|0),a+=(o=(o=o+(h/67108864|0)|0)+(f>>>26)|0)>>>26,o&=67108863}r.words[i]=s,n=o,o=a}return 0!==n?r.words[i]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=i.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,a=0;a<e;a++)n|=(1&t)<<e-a-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,a,i){for(var o=0;o<i;o++)n[o]=e[t[o]],a[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,a,i){this.permute(i,t,e,r,n,a);for(var o=1;o<a;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<a;u+=s)for(var h=l,f=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],v=r[u+p+o],m=n[u+p+o],y=h*v-f*m;m=h*m+f*v,v=y,r[u+p]=d+v,n[u+p]=g+m,r[u+p+o]=d-v,n[u+p+o]=g-m,p!==s&&(y=l*h-c*f,f=l*f+c*h,h=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,a=0;for(r=r/2|0;r;r>>>=1)a++;return 1<<a+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var a=t[n];t[n]=t[r-n-1],t[r-n-1]=a,a=e[n],e[n]=-e[r-n-1],e[r-n-1]=-a}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var a=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&a,r=a<67108864?0:a/67108864|0}return t},g.prototype.convert13b=function(t,e,r,a){for(var i=0,o=0;o<e;o++)i+=0|t[o],r[2*o]=8191&i,i>>>=13,r[2*o+1]=8191&i,i>>>=13;for(o=2*e;o<a;++o)r[o]=0;n(0===i),n(0==(-8192&i))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),a=this.makeRBT(n),i=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),h=new Array(n),f=r.words;f.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,i,s,l,n,a),this.transform(c,i,u,h,n,a);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*h[p];l[p]=s[p]*h[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,f,i,n,a),this.conjugate(f,i,n),this.normalize13b(f,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.mulf=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),d(this,t,e)},i.prototype.imul=function(t){return this.clone().mulTo(t,this)},i.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var a=(0|this.words[r])*t,i=(67108863&a)+(67108863&e);e>>=26,e+=a/67108864|0,e+=i>>>26,this.words[r]=67108863&i}return 0!==e&&(this.words[r]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.imul(this.clone())},i.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,a=r%26;e[r]=(t.words[n]&1<<a)>>>a}return e}(t);if(0===e.length)return new i(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var a=r.sqr();n<e.length;n++,a=a.sqr())0!==e[n]&&(r=r.mul(a));return r},i.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,a=(t-r)/26,i=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&i,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==a){for(e=this.length-1;e>=0;e--)this.words[e+a]=this.words[e];for(e=0;e<a;e++)this.words[e]=0;this.length+=a}return this.strip()},i.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},i.prototype.iushrn=function(t,e,r){var a;n(\"number\"==typeof t&&t>=0),a=e?(e-e%26)/26:0;var i=t%26,o=Math.min((t-i)/26,this.length),s=67108863^67108863>>>i<<i,l=r;if(a-=o,a=Math.max(0,a),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=a);c--){var h=0|this.words[c];this.words[c]=u<<26-i|h>>>i,u=h&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},i.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.ushln=function(t){return this.clone().iushln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.ushrn=function(t){return this.clone().iushrn(t)},i.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,a=1<<e;return!(this.length<=r)&&!!(this.words[r]&a)},i.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var a=67108863^67108863>>>e<<e;this.words[this.length-1]&=a}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.negative=0,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,r){var a,i,o=t.length+r;this._expand(o);var s=0;for(a=0;a<t.length;a++){i=(0|this.words[a+r])+s;var l=(0|t.words[a])*e;s=((i-=67108863&l)>>26)-(l/67108864|0),this.words[a+r]=67108863&i}for(;a<this.length-r;a++)s=(i=(0|this.words[a+r])+s)>>26,this.words[a+r]=67108863&i;if(0===s)return this.strip();for(n(-1===s),s=0,a=0;a<this.length;a++)s=(i=-(0|this.words[a])+s)>>26,this.words[a]=67108863&i;return this.negative=1,this.strip()},i.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),a=t,o=0|a.words[a.length-1];0!==(r=26-this._countBits(o))&&(a=a.ushln(r),n.iushln(r),o=0|a.words[a.length-1]);var s,l=n.length-a.length;if(\"mod\"!==e){(s=new i(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(a,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var h=l-1;h>=0;h--){var f=67108864*(0|n.words[a.length+h])+(0|n.words[a.length+h-1]);for(f=Math.min(f/o|0,67108863),n._ishlnsubmul(a,f,h);0!==n.negative;)f--,n.negative=0,n._ishlnsubmul(a,1,h),n.isZero()||(n.negative^=1);s&&(s.words[h]=f)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},i.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new i(0),mod:new i(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(a=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:a,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(a=s.div.neg()),{div:a,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e);var a,o,s},i.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},i.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},i.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),a=t.andln(1),i=r.cmp(n);return i<0||1===a&&0===i?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,a=this.length-1;a>=0;a--)r=(e*r+(0|this.words[a]))%t;return r},i.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var a=(0|this.words[r])+67108864*e;this.words[r]=a/t|0,e=a%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),h=e.clone();!e.isZero();){for(var f=0,p=1;0==(e.words[0]&p)&&f<26;++f,p<<=1);if(f>0)for(e.iushrn(f);f-- >0;)(a.isOdd()||o.isOdd())&&(a.iadd(u),o.isub(h)),a.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(h)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),a.isub(s),o.isub(l)):(r.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},i.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var a,o=new i(1),s=new i(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var h=0,f=1;0==(r.words[0]&f)&&h<26;++h,f<<=1);if(h>0)for(r.iushrn(h);h-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(a=0===e.cmpn(1)?o:s).cmpn(0)<0&&a.iadd(t),a},i.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var a=e.cmp(r);if(a<0){var i=e;e=r,r=i}else if(0===a||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},i.prototype.invm=function(t){return this.egcd(t).a.umod(t)},i.prototype.isEven=function(){return 0==(1&this.words[0])},i.prototype.isOdd=function(){return 1==(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,a=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=a,this;for(var i=a,o=r;0!==i&&o<this.length;o++){var s=0|this.words[o];i=(s+=i)>>>26,s&=67108863,this.words[o]=s}return 0!==i&&(this.words[o]=i,this.length++),this},i.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},i.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var a=0|this.words[0];e=a===t?0:a<t?-1:1}return 0!==this.negative?0|-e:e},i.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],a=0|t.words[r];if(n!==a){n<a?e=-1:n>a&&(e=1);break}}return e},i.prototype.gtn=function(t){return 1===this.cmpn(t)},i.prototype.gt=function(t){return 1===this.cmp(t)},i.prototype.gten=function(t){return this.cmpn(t)>=0},i.prototype.gte=function(t){return this.cmp(t)>=0},i.prototype.ltn=function(t){return-1===this.cmpn(t)},i.prototype.lt=function(t){return-1===this.cmp(t)},i.prototype.lten=function(t){return this.cmpn(t)<=0},i.prototype.lte=function(t){return this.cmp(t)<=0},i.prototype.eqn=function(t){return 0===this.cmpn(t)},i.prototype.eq=function(t){return 0===this.cmp(t)},i.red=function(t){return new w(t)},i.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},i.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},i.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},i.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},i.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},i.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},i.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},i.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},i.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},i.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},i.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},i.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},i.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},i.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var v={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new i(e,16),this.n=this.p.bitLength(),this.k=new i(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function x(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function b(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function _(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function w(t){if(\"string\"==typeof t){var e=i._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){w.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new i(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new i(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},a(y,m),y.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var a=t.words[9];for(e.words[e.length++]=4194303&a,n=10;n<t.length;n++){var i=0|t.words[n];t.words[n-10]=(4194303&i)<<4|a>>>22,a=i}a>>>=22,t.words[n-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},y.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},a(x,m),a(b,m),a(_,m),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,a=67108863&n;n>>>=26,t.words[r]=a,e=n}return 0!==e&&(t.words[t.length++]=e),t},i._prime=function(t){if(v[t])return v[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return v[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},w.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},w.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},w.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},w.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},w.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},w.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},w.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},w.prototype.isqr=function(t){return this.imul(t,t.clone())},w.prototype.sqr=function(t){return this.mul(t,t)},w.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new i(1)).iushrn(2);return this.pow(t,r)}for(var a=this.m.subn(1),o=0;!a.isZero()&&0===a.andln(1);)o++,a.iushrn(1);n(!a.isZero());var s=new i(1).toRed(this),l=s.redNeg(),c=this.m.subn(1).iushrn(1),u=this.m.bitLength();for(u=new i(2*u*u).toRed(this);0!==this.pow(u,c).cmp(l);)u.redIAdd(l);for(var h=this.pow(u,a),f=this.pow(t,a.addn(1).iushrn(1)),p=this.pow(t,a),d=o;0!==p.cmp(s);){for(var g=p,v=0;0!==g.cmp(s);v++)g=g.redSqr();n(v<d);var m=this.pow(h,new i(1).iushln(d-v-1));f=f.redMul(m),h=m.redSqr(),p=p.redMul(h),d=v}return f},w.prototype.invm=function(t){var e=t._invmp(this.m);return 0!==e.negative?(e.negative=0,this.imod(e).redNeg()):this.imod(e)},w.prototype.pow=function(t,e){if(e.isZero())return new i(1).toRed(this);if(0===e.cmpn(1))return t.clone();var r=new Array(16);r[0]=new i(1).toRed(this),r[1]=t;for(var n=2;n<r.length;n++)r[n]=this.mul(r[n-1],t);var a=r[0],o=0,s=0,l=e.bitLength()%26;for(0===l&&(l=26),n=e.length-1;n>=0;n--){for(var c=e.words[n],u=l-1;u>=0;u--){var h=c>>u&1;a!==r[0]&&(a=this.sqr(a)),0!==h||0!==o?(o<<=1,o|=h,(4===++s||0===n&&0===u)&&(a=this.mul(a,r[o]),s=0,o=0)):s=0}l=26}return a},w.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},w.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},i.mont=function(t){return new k(t)},a(k,w),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).iushrn(this.shift),i=a;return a.cmp(this.m)>=0?i=a.isub(this.m):a.cmpn(0)<0&&(i=a.iadd(this.m)),i._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new i(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),a=r.isub(n).iushrn(this.shift),o=a;return a.cmp(this.m)>=0?o=a.isub(this.m):a.cmpn(0)<0&&(o=a.iadd(this.m)),o._forceRed(this)},k.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(\"undefined\"==typeof e||e,this)},{buffer:104}],96:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,a=t.length,i=0;for(e=0;e<a;++e)i+=t[e].length;var o=new Array(i),s=0;for(e=0;e<a;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),h=0;for(n=0;n<c;++n)n!==r&&(u[h++]=l[n]);if(1&r){var f=u[1];u[1]=u[0],u[0]=f}}}return o}},{}],97:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return n=[],c(a=t,a,u,!0),n;case 2:return\"function\"==typeof e?c(t,t,e,!0):function(t,e){return n=[],c(t,e,u,!1),n}(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}var a};var 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n=t(\"typedarray-pool\"),a=t(\"bit-twiddle\"),i=t(\"./brute\"),o=i.partial,s=i.full,l=t(\"./sweep\"),c=t(\"./median\"),u=t(\"./partition\"),h=128,f=1<<22,p=1<<22,d=u(\"!(lo>=p0)&&!(p1>=hi)\",[\"p0\",\"p1\"]),g=u(\"lo===p0\",[\"p0\"]),v=u(\"lo<p0\",[\"p0\"]),m=u(\"hi<=p0\",[\"p0\"]),y=u(\"lo<=p0&&p0<=hi\",[\"p0\"]),x=u(\"lo<p0&&p0<=hi\",[\"p0\"]),b=6,_=2,w=n.mallocInt32(1024),k=n.mallocDouble(1024);function T(t,e,r,n,a,i,o,s,l){var c=b*t;w[c]=e,w[c+1]=r,w[c+2]=n,w[c+3]=a,w[c+4]=i,w[c+5]=o;var u=_*t;k[u]=s,k[u+1]=l}function A(t,e,r,n,a,i,o,s,l,c,u){var h=2*t,f=l*h,p=c[f+e];t:for(var d=a,g=a*h;d<i;++d,g+=h){var v=o[g+e],m=o[g+e+t];if(!(p<v||m<p)&&(!n||p!==v)){for(var y,x=s[d],b=e+1;b<t;++b){v=o[g+b],m=o[g+b+t];var _=c[f+b],w=c[f+b+t];if(m<_||w<v)continue t}if(void 0!==(y=n?r(u,x):r(x,u)))return y}}}function M(t,e,r,n,a,i,o,s,l,c){var u=2*t,h=s*u,f=l[h+e];t:for(var p=n,d=n*u;p<a;++p,d+=u){var g=o[p];if(g!==c){var v=i[d+e],m=i[d+e+t];if(!(f<v||m<f)){for(var 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n=t(\"./partition\")(\"lo<p0\",[\"p0\"]),a=8;function i(t,e,r,n,a,i){for(var o=2*t,s=o*(r+1)+e,l=r+1;l<n;++l,s+=o)for(var c=a[s],u=l,h=o*(l-1);u>r&&a[h+e]>c;--u,h-=o){for(var f=h,p=h+o,d=0;d<o;++d,++f,++p){var g=a[f];a[f]=a[p],a[p]=g}var v=i[u];i[u]=i[u-1],i[u-1]=v}}},{\"./partition\":101}],101:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=\"abcdef\".split(\"\").concat(e),a=[];t.indexOf(\"lo\")>=0&&a.push(\"lo=e[k+n]\");t.indexOf(\"hi\")>=0&&a.push(\"hi=e[k+o]\");return r.push(n.replace(\"_\",a.join()).replace(\"$\",t)),Function.apply(void 0,r)};var n=\"for(var j=2*a,k=j*c,l=k,m=c,n=b,o=a+b,p=c;d>p;++p,k+=j){var _;if($)if(m===p)m+=1,l+=j;else{for(var s=0;j>s;++s){var t=e[k+s];e[k+s]=e[l],e[l++]=t}var u=f[p];f[p]=f[m],f[m++]=u}}return m\"},{}],102:[function(t,e,r){\"use strict\";e.exports=function(t,e){e<=4*n?a(0,e-1,t):function t(e,r,h){var 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c=(i=r.right=o(i)).right=o(i.right),r.right=i.left,i.left=r,i.right=c,i._color=r._color,e._color=a,r._color=a,c._color=a,l(r),l(i),u>1&&((h=t[u-2]).left===r?h.left=i:h.right=i),void(t[u-1]=i);if(i.left&&i.left._color===n)return c=(i=r.right=o(i)).left=o(i.left),r.right=c.left,i.left=c.right,c.left=r,c.right=i,c._color=r._color,r._color=a,i._color=a,e._color=a,l(r),l(i),l(c),u>1&&((h=t[u-2]).left===r?h.left=c:h.right=c),void(t[u-1]=c);if(i._color===a){if(r._color===n)return r._color=a,void(r.right=s(n,i));r.right=s(n,i);continue}i=o(i),r.right=i.left,i.left=r,i._color=r._color,r._color=n,l(r),l(i),u>1&&((h=t[u-2]).left===r?h.left=i:h.right=i),t[u-1]=i,t[u]=r,u+1<t.length?t[u+1]=e:t.push(e),u+=2}else{if((i=r.left).left&&i.left._color===n)return c=(i=r.left=o(i)).left=o(i.left),r.left=i.right,i.right=r,i.left=c,i._color=r._color,e._color=a,r._color=a,c._color=a,l(r),l(i),u>1&&((h=t[u-2]).right===r?h.right=i:h.left=i),void(t[u-1]=i);if(i.right&&i.right._color===n)return c=(i=r.left=o(i)).right=o(i.right),r.left=c.right,i.right=c.left,c.right=r,c.left=i,c._color=r._color,r._color=a,i._color=a,e._color=a,l(r),l(i),l(c),u>1&&((h=t[u-2]).right===r?h.right=c:h.left=c),void(t[u-1]=c);if(i._color===a){if(r._color===n)return r._color=a,void(r.left=s(n,i));r.left=s(n,i);continue}var h;i=o(i),r.left=i.right,i.right=r,i._color=r._color,r._color=n,l(r),l(i),u>1&&((h=t[u-2]).right===r?h.right=i:h.left=i),t[u-1]=i,t[u]=r,u+1<t.length?t[u+1]=e:t.push(e),u+=2}}}(e),g.left===r?g.left=null:g.right=null,new c(this.tree._compare,e[0])},Object.defineProperty(f,\"key\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(f,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(f,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),f.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),f.update=function(t){var e=this._stack;if(0===e.length)throw new Error(\"Can't update empty node!\");var r=new Array(e.length),n=e[e.length-1];r[r.length-1]=new i(n._color,n.key,t,n.left,n.right,n._count);for(var a=e.length-2;a>=0;--a)(n=e[a]).left===e[a+1]?r[a]=new i(n._color,n.key,n.value,r[a+1],n.right,n._count):r[a]=new i(n._color,n.key,n.value,n.left,r[a+1],n._count);return new c(this.tree._compare,r[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},{}],232:[function(t,e,r){var n=[.9999999999998099,676.5203681218851,-1259.1392167224028,771.3234287776531,-176.6150291621406,12.507343278686905,-.13857109526572012,9984369578019572e-21,1.5056327351493116e-7],a=607/128,i=[.9999999999999971,57.15623566586292,-59.59796035547549,14.136097974741746,-.4919138160976202,3399464998481189e-20,4652362892704858e-20,-9837447530487956e-20,.0001580887032249125,-.00021026444172410488,.00021743961811521265,-.0001643181065367639,8441822398385275e-20,-26190838401581408e-21,36899182659531625e-22];function o(t){if(t<0)return Number(\"0/0\");for(var e=i[0],r=i.length-1;r>0;--r)e+=i[r]/(t+r);var n=t+a+.5;return.5*Math.log(2*Math.PI)+(t+.5)*Math.log(n)-n+Math.log(e)-Math.log(t)}e.exports=function t(e){if(e<.5)return Math.PI/(Math.sin(Math.PI*e)*t(1-e));if(e>100)return Math.exp(o(e));e-=1;for(var r=n[0],a=1;a<9;a++)r+=n[a]/(e+a);var i=e+7+.5;return Math.sqrt(2*Math.PI)*Math.pow(i,e+.5)*Math.exp(-i)*r},e.exports.log=o},{}],233:[function(t,e,r){e.exports=function(t,e){if(\"string\"!=typeof t)throw new TypeError(\"must specify type string\");if(e=e||{},\"undefined\"==typeof document&&!e.canvas)return null;var r=e.canvas||document.createElement(\"canvas\");\"number\"==typeof e.width&&(r.width=e.width);\"number\"==typeof e.height&&(r.height=e.height);var n,a=e;try{var i=[t];0===t.indexOf(\"webgl\")&&i.push(\"experimental-\"+t);for(var o=0;o<i.length;o++)if(n=r.getContext(i[o],a))return n}catch(t){n=null}return n||null}},{}],234:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=new u(t);return r.update(e),r};var n=t(\"./lib/text.js\"),a=t(\"./lib/lines.js\"),i=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=i(t)}var h=u.prototype;function f(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}h.update=function(t){function e(e,r,n){if(n in t){var a,i=t[n],o=this[n];(e?Array.isArray(i)&&Array.isArray(i[0]):Array.isArray(i))?this[n]=a=[r(i[0]),r(i[1]),r(i[2])]:this[n]=a=[r(i),r(i),r(i)];for(var s=0;s<3;++s)if(a[s]!==o[s])return!0}return!1}t=t||{};var r,i=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]}),u=!1,h=!1;if(\"bounds\"in t)for(var f=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)f[p][d]!==this.bounds[p][d]&&(h=!0),this.bounds[p][d]=f[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else i(\"tickSpacing\")&&(this.autoTicks=!0,h=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),h=!0,u=!0,this._firstInit=!1),h&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort(function(t,e){return t.x-e.x});s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),i(\"tickSize\"),i(\"tickAngle\"),i(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),i(\"labelSize\"),i(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),i(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),i(\"lineTickLength\"),i(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),i(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),i(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=a(this.gl,this.bounds,this.ticks))};var p=[new f,new f,new f];function d(t,e,r,n,a){for(var i=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var h=i,f=s,p=o,d=l;c&1<<u&&(h=s,f=i,p=l,d=o),h[u]=r[0][u],f[u]=r[1][u],a[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],v={model:l,view:l,projection:l,_ortho:!1};h.isOpaque=function(){return!0},h.isTransparent=function(){return!1},h.drawTransparent=function(t){};var m=[0,0,0],y=[0,0,0],x=[0,0,0];h.draw=function(t){t=t||v;for(var e=this.gl,r=t.model||l,n=t.view||l,a=t.projection||l,i=this.bounds,s=t._ortho||!1,u=o(r,n,a,i,s),h=u.cubeEdges,f=u.axis,b=n[12],_=n[13],w=n[14],k=n[15],T=(s?2:1)*this.pixelRatio*(a[3]*b+a[7]*_+a[11]*w+a[15]*k)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=h[A],this.lastCubeProps.axis[A]=f[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,h,f);e=this.gl;var S,E=g;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=f[A]:E[A]=0;this._background.draw(r,n,a,i,E,this.backgroundColor),this._lines.bind(r,n,a,this);for(A=0;A<3;++A){var C=[0,0,0];f[A]>0?C[A]=i[1][A]:C[A]=i[0][A];for(var L=0;L<2;++L){var P=(A+1+L)%3,O=(A+1+(1^L))%3;this.gridEnable[P]&&this._lines.drawGrid(P,O,this.bounds,C,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(L=0;L<2;++L){P=(A+1+L)%3,O=(A+1+(1^L))%3;this.zeroEnable[O]&&Math.min(i[0][O],i[1][O])<=0&&Math.max(i[0][O],i[1][O])>=0&&this._lines.drawZero(P,O,this.bounds,C,this.zeroLineColor[O],this.zeroLineWidth[O]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var I=c(m,M[A].primalMinor),z=c(y,M[A].mirrorMinor),D=this.lineTickLength;for(L=0;L<3;++L){var R=T/r[5*L];I[L]*=D[L]*R,z[L]*=D[L]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,I,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,a,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,a=(t+2)%3,i=e[n],o=e[a],s=r[n],l=r[a];i>0&&l>0?N(n):i>0&&l<0?N(n):i<0&&l>0?N(n):i<0&&l<0?N(n):o>0&&s>0?N(a):o>0&&s<0?N(a):o<0&&s>0?N(a):o<0&&s<0&&N(a)}for(A=0;A<3;++A){var V=M[A].primalMinor,U=M[A].mirrorMinor,q=c(x,M[A].primalOffset);for(L=0;L<3;++L)this.lineTickEnable[A]&&(q[L]+=T*V[L]*Math.max(this.lineTickLength[L],0)/r[5*L]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,F=1,\"auto\"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(A,V,U);for(L=0;L<3;++L)q[L]+=T*V[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),\"auto\"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(L=0;L<3;++L)q[L]+=T*V[L]*this.labelPad[L]/r[5*L];q[A]+=.5*(i[0][A]+i[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},h.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":235,\"./lib/cube.js\":236,\"./lib/lines.js\":237,\"./lib/text.js\":239,\"./lib/ticks.js\":240}],235:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,h=[0,0,0],f=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),h[l]=p,f[l]=p;for(var d=-1;d<=1;d+=2){h[c]=d;for(var g=-1;g<=1;g+=2)h[u]=g,e.push(h[0],h[1],h[2],f[0],f[1],f[2]),s+=1}var v=c;c=u,u=v}var m=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=a(t,[{buffer:m,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:m,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=i(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,m,x,b)};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,a,i){for(var o=!1,s=0;s<3;++s)o=o||a[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:a,colors:i},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":238,\"gl-buffer\":242,\"gl-vao\":328}],236:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,i,p){a(s,e,t),a(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=i[x][2];for(var b=0;b<2;++b){u[1]=i[b][1];for(var _=0;_<2;++_)u[0]=i[_][0],f(l[y],u,s),y+=1}}for(var w=-1,x=0;x<8;++x){for(var k=l[x][3],T=0;T<3;++T)c[x][T]=l[x][T]/k;p&&(c[x][2]*=-1),k<0&&(w<0?w=x:c[x][2]<c[w][2]&&(w=x))}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,C=-1,L=0;L<2;++L){var P=L<<A,O=P+(L<<M)+(1-L<<S),I=P+(1-L<<M)+(L<<S);o(c[P],c[O],c[I],h)<0||(L?E=1:C=1)}if(E<0||C<0)C>E&&(w|=1<<A);else{for(var L=0;L<2;++L){var P=L<<A,O=P+(L<<M)+(1-L<<S),I=P+(1-L<<M)+(L<<S),z=d([l[P],l[O],l[I],l[P+(1<<M)+(1<<S)]]);L?E=z:C=z}C>E&&(w|=1<<A)}}}for(var D=7^w,R=-1,x=0;x<8;++x)x!==w&&x!==D&&(R<0?R=x:c[R][1]>c[x][1]&&(R=x));for(var F=-1,x=0;x<3;++x){var B=R^1<<x;if(B!==w&&B!==D){F<0&&(F=B);var S=c[B];S[0]<c[F][0]&&(F=B)}}for(var N=-1,x=0;x<3;++x){var B=R^1<<x;if(B!==w&&B!==D&&B!==F){N<0&&(N=B);var S=c[B];S[0]>c[N][0]&&(N=B)}}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^N)]=R&N;var V=7^N;V===w||V===D?(V=7^F,j[n.log2(N^V)]=V&N):j[n.log2(F^V)]=V&F;for(var U=v,q=w,A=0;A<3;++A)U[A]=q&1<<A?-1:1;return m};var n=t(\"bit-twiddle\"),a=t(\"gl-mat4/multiply\"),i=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),h=[0,0,0];function f(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var a=0;a<3;++a)t[n]+=e[a]*r[4*a+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=i.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],a=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-a,h=l[0]/l[3]-n,f=l[1]/l[3]-a;o+=Math.abs(c*f-u*h)}return o}var g=[1,1,1],v=[0,0,0],m={cubeEdges:g,axis:v}},{\"bit-twiddle\":93,\"gl-mat4/multiply\":268,\"robust-orientation\":511,\"split-polygon\":528}],237:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var h=0;h<3;++h){for(var f=o.length/3|0,d=0;d<r[h].length;++d){var g=+r[h][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=o.length/3|0;s[h]=f,l[h]=v-f;for(var f=o.length/3|0,m=0;m<r[h].length;++m){var g=+r[h][m].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var v=o.length/3|0;c[h]=f,u[h]=v-f}var y=n(t,new Float32Array(o)),x=a(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=i(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function h(t){return t[0]=t[1]=t[2]=0,t}function f(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,a,i,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=a,this.tickOffset=i,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,a){var i=h(s);this.shader.uniforms.majorAxis=s,i[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=i;var o,u=f(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=n,(o=h(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=h(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,a){if(this.tickCount[t]){var i=h(o);i[t]=1,this.shader.uniforms.majorAxis=i,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=a;var s=h(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,a,i){if(this.gridCount[t]){var u=h(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=f(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=h(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=h(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=a,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,a,i){var o=h(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=f(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=h(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=a,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":238,\"gl-buffer\":242,\"gl-vao\":328}],238:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),a=t(\"gl-shader\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return a(t,i,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n    flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n                vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n    beta += applyAlignOption(clipAngle, flip * PI);\\n  }\\n\\n  //Compute plane offset\\n  vec2 planeCoord = position.xy * pixelScale;\\n\\n  mat2 planeXform = scale * mat2(\\n     cos(beta), sin(beta),\\n    -sin(beta), cos(beta)\\n  );\\n\\n  vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n  //Compute clip position\\n  vec3 clipPosition = project(dataPosition);\\n\\n  //Apply text offset in clip coordinates\\n  clipPosition += vec3(viewOffset, 0.0);\\n\\n  //Done\\n  gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.text=function(t){return a(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n  vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n  vec3 realNormal = signAxis * normal;\\n\\n  if(dot(realNormal, enable) > 0.0) {\\n    vec3 minRange = min(bounds[0], bounds[1]);\\n    vec3 maxRange = max(bounds[0], bounds[1]);\\n    vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n    gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n  } else {\\n    gl_Position = vec4(0,0,0,0);\\n  }\\n\\n  colorChannel = abs(realNormal);\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n  gl_FragColor = colorChannel.x * colors[0] +\\n                 colorChannel.y * colors[1] +\\n                 colorChannel.z * colors[2];\\n}\"]);r.bg=function(t){return a(t,c,u,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},{\"gl-shader\":302,glslify:410}],239:[function(t,e,r){(function(r){\"use strict\";e.exports=function(t,e,r,i,s,l){var u=n(t),h=a(t,[{buffer:u,size:3}]),f=o(t);f.attributes.position.location=0;var p=new c(t,f,u,h);return p.update(e,r,i,s,l),p};var n=t(\"gl-buffer\"),a=t(\"gl-vao\"),i=t(\"vectorize-text\"),o=t(\"./shaders\").text,s=window||r.global||{},l=s.__TEXT_CACHE||{};s.__TEXT_CACHE={};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}var u=c.prototype,h=[0,0];u.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var a=this.shader.uniforms;a.model=t,a.view=e,a.projection=r,a.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},u.unbind=function(){this.vao.unbind()},u.update=function(t,e,r,n,a){var o=[];function s(t,e,r,n,a,s){var c=l[r];c||(c=l[r]={});var u=c[e];u||(u=c[e]=function(t,e){try{return i(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:a,styletags:s}));for(var h=(n||12)/12,f=u.positions,p=u.cells,d=0,g=p.length;d<g;++d)for(var v=p[d],m=2;m>=0;--m){var y=f[v[m]];o.push(h*y[0],-h*y[1],t)}}for(var c=[0,0,0],u=[0,0,0],h=[0,0,0],f=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){h[d]=o.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),f[d]=(o.length/3|0)-h[d],c[d]=o.length/3|0;for(var g=0;g<n[d].length;++g)n[d][g].text&&s(n[d][g].x,n[d][g].text,n[d][g].font||a,n[d][g].fontSize||12,1.25,p);u[d]=(o.length/3|0)-c[d]}this.buffer.update(o),this.tickOffset=c,this.tickCount=u,this.labelOffset=h,this.labelCount=f},u.drawTicks=function(t,e,r,n,a,i,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=i,this.shader.uniforms.color=a,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},u.drawLabel=function(t,e,r,n,a,i,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=i,this.shader.uniforms.color=a,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},u.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this,t(\"_process\"))},{\"./shaders\":238,_process:483,\"gl-buffer\":242,\"gl-vao\":328,\"vectorize-text\":551}],240:[function(t,e,r){\"use strict\";function n(t,e){var r=t+\"\",n=r.indexOf(\".\"),a=0;n>=0&&(a=r.length-n-1);var i=Math.pow(10,a),o=Math.round(t*e*i),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/i,c=o%i;o<0?(l=0|-Math.ceil(l),c=0|-c):(l=0|Math.floor(l),c|=0);var u=\"\"+l;if(o<0&&(u=\"-\"+u),a){for(var h=\"\"+c;h.length<a;)h=\"0\"+h;return u+\".\"+h}return u}r.create=function(t,e){for(var r=[],a=0;a<3;++a){for(var i=[],o=(t[0][a],t[1][a],0);o*e[a]<=t[1][a];++o)i.push({x:o*e[a],text:n(e[a],o)});for(var o=-1;o*e[a]>=t[0][a];--o)i.push({x:o*e[a],text:n(e[a],o)});r.push(i)}return r},r.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;n<t[r].length;++n){var a=t[r][n],i=e[r][n];if(a.x!==i.x||a.text!==i.text||a.font!==i.font||a.fontColor!==i.fontColor||a.fontSize!==i.fontSize||a.dx!==i.dx||a.dy!==i.dy)return!1}}return!0}},{}],241:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,l,h){var f=e.model||c,p=e.view||c,m=e.projection||c,y=e._ortho||!1,x=t.bounds,b=(h=h||i(f,p,m,x,y)).axis;o(u,p,f),o(u,m,u);for(var _=g,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var k=n(s(u,u));s(u,u);for(var T=0;T<3;++T){var A=(T+1)%3,M=(T+2)%3,S=v;t:for(var w=0;w<2;++w){var E=[];if(b[T]<0!=!!w){S[T]=x[w][T];for(var C=0;C<2;++C){S[A]=x[C^w][A];for(var L=0;L<2;++L)S[M]=x[L^C^w][M],E.push(S.slice())}for(var P=y?5:4,C=P;C===P;++C){if(0===E.length)continue t;E=a.positive(E,k[C])}for(var C=0;C<E.length;++C)for(var M=E[C],O=d(v,u,M,r,l),L=0;L<3;++L)_[L].lo=Math.min(_[L].lo,M[L]),_[L].hi=Math.max(_[L].hi,M[L]),L!==T&&(_[L].pixelsPerDataUnit=Math.min(_[L].pixelsPerDataUnit,Math.abs(O[L])))}}}return _};var n=t(\"extract-frustum-planes\"),a=t(\"split-polygon\"),i=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function h(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var f=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,a){for(var i=0;i<3;++i){for(var o=f,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[i]+=1,l(s,s,e),s[3]<0&&(t[i]=1/0),o[i]-=1,l(o,o,e),o[3]<0&&(t[i]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,h=(o[1]/o[3]-s[1]/s[3])*a;t[i]=.25*Math.sqrt(u*u+h*h)}return t}var g=[new h(1/0,-1/0,1/0),new h(1/0,-1/0,1/0),new h(1/0,-1/0,1/0)],v=[0,0,0]},{\"./lib/cube.js\":236,\"extract-frustum-planes\":225,\"gl-mat4/multiply\":268,\"gl-mat4/transpose\":277,\"gl-vec4/transformMat4\":399,\"split-polygon\":528}],242:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),a=t(\"ndarray-ops\"),i=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,a){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=a}var l=s.prototype;function c(t,e,r,n,a,i){var o=a.length*a.BYTES_PER_ELEMENT;if(i<0)return t.bufferData(e,a,n),o;if(o+i>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,i,a),r}function u(t,e){for(var r=n.malloc(t.length,e),a=t.length,i=0;i<a;++i)r[i]=t[i];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&\"undefined\"!=typeof t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=i(s,t.shape);a.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var h;h=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?h:h.subarray(0,t.length),e),n.free(h)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var a=t.createBuffer(),i=new s(t,r,a,0,n);return i.update(e),i}},{ndarray:451,\"ndarray-ops\":445,\"typedarray-pool\":546}],243:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),a=function(t,e){for(var r=0;r<t.length;r++)if(t[r]>=e)return r-1;return r},i=n.create(),o=n.create(),s=function(t,e,r){return t<e?e:t>r?r:t},l=function(t,e,r,l){var c=t[0],u=t[1],h=t[2],f=r[0].length,p=r[1].length,d=r[2].length,g=a(r[0],c),v=a(r[1],u),m=a(r[2],h),y=g+1,x=v+1,b=m+1;if(l&&(g=s(g,0,f-1),y=s(y,0,f-1),v=s(v,0,p-1),x=s(x,0,p-1),m=s(m,0,d-1),b=s(b,0,d-1)),g<0||v<0||m<0||y>=f||x>=p||b>=d)return n.create();var _=(c-r[0][g])/(r[0][y]-r[0][g]),w=(u-r[1][v])/(r[1][x]-r[1][v]),k=(h-r[2][m])/(r[2][b]-r[2][m]);(_<0||_>1||isNaN(_))&&(_=0),(w<0||w>1||isNaN(w))&&(w=0),(k<0||k>1||isNaN(k))&&(k=0);var T=m*f*p,A=b*f*p,M=v*f,S=x*f,E=g,C=y,L=e[M+T+E],P=e[M+T+C],O=e[S+T+E],I=e[S+T+C],z=e[M+A+E],D=e[M+A+C],R=e[S+A+E],F=e[S+A+C],B=n.create();return n.lerp(B,L,P,_),n.lerp(i,O,I,_),n.lerp(B,B,i,w),n.lerp(i,z,D,_),n.lerp(o,R,F,_),n.lerp(i,i,o,w),n.lerp(B,B,i,k),B};e.exports=function(t,e){var r;r=t.positions?t.positions:function(t){for(var e=t[0],r=t[1],n=t[2],a=[],i=0;i<n.length;i++)for(var o=0;o<r.length;o++)for(var s=0;s<e.length;s++)a.push([n[i],r[o],e[s]]);return a}(t.meshgrid);var a=t.meshgrid,i=t.vectors,o={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vertexNormals:[],vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),o;for(var s=0,c=1/0,u=-1/0,h=1/0,f=-1/0,p=1/0,d=-1/0,g=null,v=null,m=[],y=1/0,x=0;x<r.length;x++){var b,_=r[x];c=Math.min(_[0],c),u=Math.max(_[0],u),h=Math.min(_[1],h),f=Math.max(_[1],f),p=Math.min(_[2],p),d=Math.max(_[2],d),b=a?l(_,i,a,!0):i[x],n.length(b)>s&&(s=n.length(b)),x&&(y=Math.min(y,2*n.distance(g,_)/(n.length(v)+n.length(b)))),g=_,v=b,m.push(b)}var w=[c,h,p],k=[u,f,d];e&&(e[0]=w,e[1]=k),0===s&&(s=1);var T=1/s;isFinite(y)&&!isNaN(y)||(y=1),o.vectorScale=y;var A=function(t,e,r){var a=n.create();return void 0!==t&&n.set(a,t,e,r),a}(0,1,0),M=t.coneSize||.5;t.absoluteConeSize&&(M=t.absoluteConeSize*T),o.coneScale=M;x=0;for(var S=0;x<r.length;x++)for(var E=(_=r[x])[0],C=_[1],L=_[2],P=m[x],O=n.length(P)*T,I=0;I<8;I++){o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.positions.push([E,C,L,S++]),o.vectors.push(P),o.vectors.push(P),o.vectors.push(P),o.vectors.push(P),o.vectors.push(P),o.vectors.push(P),o.vertexIntensity.push(O,O,O),o.vertexIntensity.push(O,O,O),o.vertexNormals.push(A,A,A),o.vertexNormals.push(A,A,A);var z=o.positions.length;o.cells.push([z-6,z-5,z-4],[z-3,z-2,z-1])}return o},e.exports.createConeMesh=t(\"./lib/conemesh\")},{\"./lib/conemesh\":244,\"gl-vec3\":347}],244:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),a=t(\"gl-buffer\"),i=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),h=t(\"colormap\"),f=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./shaders\"),g=d.meshShader,v=d.pickShader,m=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function y(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,v,y,x,b,_,w,k,T){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=a,this.triangleVectors=i,this.triangleColors=s,this.triangleNormals=c,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=u,this.triangleCount=0,this.lineWidth=1,this.edgePositions=h,this.edgeColors=p,this.edgeUVs=d,this.edgeIds=f,this.edgeVAO=g,this.edgeCount=0,this.pointPositions=v,this.pointColors=x,this.pointUVs=b,this.pointSizes=_,this.pointIds=y,this.pointVAO=w,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=k,this.contourVAO=T,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=m,this._view=m,this._projection=m,this._resolution=[1,1]}var x=y.prototype;function b(t){var e=n(t,v.vertex,v.fragment,null,v.attributes);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.vector.location=5,e}x.isOpaque=function(){return this.opacity>=1},x.isTransparent=function(){return this.opacity<1},x.pickSlots=1,x.setPickBase=function(t){this.pickId=t},x.highlight=function(t){if(t&&this.contourEnable){for(var e=f(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,a=e.vertexWeights,i=r.length,o=p.mallocFloat32(6*i),s=0,l=0;l<i;++l)for(var c=r[l],u=0;u<2;++u){var h=c[0];2===c.length&&(h=c[u]);for(var d=n[h][0],g=n[h][1],v=a[h],m=1-v,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=v*y[b]+m*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},x.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=h({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var a=e[n],i=0;i<3;++i)r[4*n+i]=a[i];r[4*n+3]=255*a[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,a=t.vectors;if(n&&r&&a){var i=[],l=[],c=[],f=[],p=[],d=[],g=[],v=[],m=[],y=[],x=[],b=[],_=[],w=[],k=[];this.cells=r,this.positions=n;var T=t.vertexNormals,A=t.cellNormals,M=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,S=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!A&&(A=s.faceNormals(r,n,S)),A||T||(T=s.vertexNormals(r,n,M));var E=t.vertexColors,C=t.cellColors,L=t.meshColor||[1,1,1,1],P=t.vertexUVs,O=t.vertexIntensity,I=t.cellUVs,z=t.cellIntensity,D=1/0,R=-1/0;if(!P&&!I)if(O)if(t.vertexIntensityBounds)D=+t.vertexIntensityBounds[0],R=+t.vertexIntensityBounds[1];else for(var F=0;F<O.length;++F){var B=O[F];D=Math.min(D,B),R=Math.max(R,B)}else if(z)for(F=0;F<z.length;++F){B=z[F];D=Math.min(D,B),R=Math.max(R,B)}else for(F=0;F<n.length;++F){B=n[F][2];D=Math.min(D,B),R=Math.max(R,B)}this.intensity=O||(z?function(t,e,r){for(var n=new Array(e),a=0;a<e;++a)n[a]=0;var i=t.length;for(a=0;a<i;++a)for(var o=t[a],s=0;s<o.length;++s)n[o[s]]=r[a];return n}(r,n.length,z):function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n));var N=t.pointSizes,j=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(F=0;F<n.length;++F)for(var V=n[F],U=0;U<3;++U)!isNaN(V[U])&&isFinite(V[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],V[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],V[U]));var q=0,H=0,G=0;t:for(F=0;F<r.length;++F){var Y=r[F];switch(Y.length){case 1:for(V=n[X=Y[0]],U=0;U<3;++U)if(isNaN(V[U])||!isFinite(V[U]))continue t;x.push(V[0],V[1],V[2],V[3]),3===(Z=E?E[X]:C?C[F]:L).length?b.push(Z[0],Z[1],Z[2],1):b.push(Z[0],Z[1],Z[2],Z[3]),J=P?P[X]:O?[(O[X]-D)/(R-D),0]:I?I[F]:z?[(z[F]-D)/(R-D),0]:[(V[2]-D)/(R-D),0],_.push(J[0],J[1]),N?w.push(N[X]):w.push(j),k.push(F),G+=1;break;case 2:for(U=0;U<2;++U){V=n[X=Y[U]];for(var W=0;W<3;++W)if(isNaN(V[W])||!isFinite(V[W]))continue t}for(U=0;U<2;++U){V=n[X=Y[U]];g.push(V[0],V[1],V[2]),3===(Z=E?E[X]:C?C[F]:L).length?v.push(Z[0],Z[1],Z[2],1):v.push(Z[0],Z[1],Z[2],Z[3]),J=P?P[X]:O?[(O[X]-D)/(R-D),0]:I?I[F]:z?[(z[F]-D)/(R-D),0]:[(V[2]-D)/(R-D),0],m.push(J[0],J[1]),y.push(F)}H+=1;break;case 3:for(U=0;U<3;++U)for(V=n[X=Y[U]],W=0;W<3;++W)if(isNaN(V[W])||!isFinite(V[W]))continue t;for(U=0;U<3;++U){var X;V=n[X=Y[2-U]];i.push(V[0],V[1],V[2],V[3]);var Z,J,K,Q=a[X];l.push(Q[0],Q[1],Q[2]),3===(Z=E?E[X]:C?C[F]:L).length?c.push(Z[0],Z[1],Z[2],1):c.push(Z[0],Z[1],Z[2],Z[3]),J=P?P[X]:O?[(O[X]-D)/(R-D),0]:I?I[F]:z?[(z[F]-D)/(R-D),0]:[(V[2]-D)/(R-D),0],p.push(J[0],J[1]),K=T?T[X]:A[F],f.push(K[0],K[1],K[2]),d.push(F)}q+=1}}this.pointCount=G,this.edgeCount=H,this.triangleCount=q,this.pointPositions.update(x),this.pointColors.update(b),this.pointUVs.update(_),this.pointSizes.update(w),this.pointIds.update(new Uint32Array(k)),this.edgePositions.update(g),this.edgeColors.update(v),this.edgeUVs.update(m),this.edgeIds.update(new Uint32Array(y)),this.trianglePositions.update(i),this.triangleVectors.update(l),this.triangleColors.update(c),this.triangleUVs.update(p),this.triangleNormals.update(f),this.triangleIds.update(new Uint32Array(d))}},x.drawTransparent=x.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||m,n=t.view||m,a=t.projection||m,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:a,inverseModel:m.slice(),clipBounds:i,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var f=u[12+o],p=0;p<3;++p)f+=u[4*p+o]*this.lightPosition[p];s.lightPosition[o]=f/h}if(this.triangleCount>0){var d=this.triShader;d.bind(),d.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},x.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||m,n=t.view||m,a=t.projection||m,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(a),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:a,clipBounds:i,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind())},x.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3);return{index:Math.floor(r[1]/48),position:n,dataCoordinate:n}},x.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=e.triShader||function(t){var e=n(t,g.vertex,g.fragment,null,g.attributes);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.vector.location=5,e}(t),s=b(t),l=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));l.generateMipmap(),l.minFilter=t.LINEAR_MIPMAP_LINEAR,l.magFilter=t.LINEAR;var c=a(t),h=a(t),f=a(t),p=a(t),d=a(t),v=a(t),m=i(t,[{buffer:c,type:t.FLOAT,size:4},{buffer:v,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:f,type:t.FLOAT,size:4},{buffer:p,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:3},{buffer:h,type:t.FLOAT,size:3}]),x=a(t),_=a(t),w=a(t),k=a(t),T=i(t,[{buffer:x,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),A=a(t),M=a(t),S=a(t),E=a(t),C=a(t),L=i(t,[{buffer:A,type:t.FLOAT,size:3},{buffer:C,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:M,type:t.FLOAT,size:4},{buffer:S,type:t.FLOAT,size:2},{buffer:E,type:t.FLOAT,size:1}]),P=a(t),O=new y(t,l,r,s,c,h,v,f,p,d,m,x,k,_,w,T,A,C,M,S,E,L,P,i(t,[{buffer:P,type:t.FLOAT,size:3}]));return O.update(e),O}},{\"./shaders\":245,colormap:127,\"gl-buffer\":242,\"gl-mat4/invert\":266,\"gl-mat4/multiply\":268,\"gl-shader\":302,\"gl-texture2d\":323,\"gl-vao\":328,ndarray:451,normals:454,\"simplicial-complex-contour\":519,\"typedarray-pool\":546}],245:[function(t,e,r){var n=t(\"glslify\"),a=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\nuniform float vectorScale;\\nuniform float coneScale;\\n\\nuniform float coneOffset;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data\\n           , f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal,0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),i=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular\\n            , opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data\\n           , f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.