two other notebooks to test for SO https://stackoverflow.com/q/77969756/8508004 saying not rendering R kernel well

RECENT_RUNtest_millefy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example usage of Millefy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“replacing previous import ‘IRanges::shift’ by ‘data.table::shift’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::distance’ by ‘destiny::distance’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘data.table::first’ by ‘dplyr::first’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::desc’ by ‘dplyr::desc’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::slice’ by ‘dplyr::slice’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::intersect’ by ‘dplyr::intersect’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘data.table::last’ by ‘dplyr::last’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::union’ by ‘dplyr::union’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘data.table::between’ by ‘dplyr::between’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::collapse’ by ‘dplyr::collapse’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘IRanges::setdiff’ by ‘dplyr::setdiff’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘GenomicRanges::subtract’ by ‘magrittr::subtract’ when loading ‘millefy’”\n",
      "Warning message:\n",
      "“replacing previous import ‘magrittr::extract’ by ‘tidyr::extract’ when loading ‘millefy’”\n"
     ]
    }
   ],
   "source": [
    "library(millefy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BigWig files (scRNA-seq samples)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"/srv/conda/envs/notebook/lib/R/library/millefy/extdata/RamDA_00h_A06.bw\"\n",
      "[2] \"/srv/conda/envs/notebook/lib/R/library/millefy/extdata/RamDA_00h_A07.bw\"\n",
      "[3] \"/srv/conda/envs/notebook/lib/R/library/millefy/extdata/RamDA_00h_A08.bw\"\n",
      "[4] \"/srv/conda/envs/notebook/lib/R/library/millefy/extdata/RamDA_12h_A06.bw\"\n",
      "[5] \"/srv/conda/envs/notebook/lib/R/library/millefy/extdata/RamDA_12h_A07.bw\"\n",
      "[6] \"/srv/conda/envs/notebook/lib/R/library/millefy/extdata/RamDA_12h_A08.bw\"\n"
     ]
    }
   ],
   "source": [
    "# Path to bigWig files\n",
    "bwfiles = Sys.glob(file.path(system.file(\"extdata\", package=\"millefy\"), \"*.bw\"))\n",
    "print(bwfiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Group labels for bigWig files (same length as bwfiles)\n",
    "groups = c(\"00h\", \"00h\", \"00h\", \"12h\", \"12h\", \"12h\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      00h       12h \n",
      "\"#FFFF00\" \"#FF7F00\" \n"
     ]
    }
   ],
   "source": [
    "# Color labels for bigWig files (A named vector with the same length as the number of kinds of \\\\code{groups})\n",
    "color_labels <- colorRampPalette(c(\"yellow\", \"red\"))(length(unique(groups))+1)[1:length(unique(groups))]\n",
    "names(color_labels)  <- unique(groups)\n",
    "print(color_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GTF file (gene models)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load gene models (It takes a little time)\n",
    "path_gtf = system.file(\"extdata\", \"example.gtf\", package=\"millefy\")\n",
    "dt_gtf_exon <- gtfToDtExon(path_gtf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set tracks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set tracks\n",
    "## Single-cell track\n",
    "max_value = 7000\n",
    "scTrackBw <- list(path_bam_files = bwfiles, groups = groups, group_colors = color_labels, max_value = max_value, isBw=TRUE)\n",
    "\n",
    "## Gene annotation track\n",
    "geneTrack1 <- list(path_gtf = path_gtf, dt_gtf = dt_gtf_exon, label = \"GENCODE\")\n",
    "\n",
    "\n",
    "# Prepare arguments for millefyPlot()\n",
    "## List of tracks\n",
    "tdlist <- list(scTrackBw, geneTrack1)\n",
    "\n",
    "## List of track types\n",
    "tt <- c(\"sc\", \"gene\")\n",
    "\n",
    "## List of track hights\n",
    "heights = c(12, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set a location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Location to visualize\n",
    "chr =  \"chr19\" # character\n",
    "start = 5824708 # integer\n",
    "end = 5845478 # integer\n",
    "\n",
    "text_main = \"mESC 00h, 12h (Neat1)\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Default\n",
    "When we don't set the sc_sort_destiny parameter (default), the order of single cells is the order of bwfiles.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Begin millefyPlot: 2024-02-11 22:21:30.112953\"\n",
      "[1] \"title\" \"sc\"    \"avg\"   \"gene\"  \"axis\" \n",
      "[1] \"Importing BigWig: 2024-02-11 22:21:30.678757\"\n",
      "[1] \"Finished millefyPlot: 2024-02-11 22:21:35.096269\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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0Oa9TmAQ3n11VePdmAHZXX2mjVrek/M\n/hy7PjM/8MAD1tb7/OaJZDK5ZMmSiRMnDho0yOVyDR8+/IILLnjggQeyvwLub3/721e/+tXy\n8nKXy1VeXv61r32ts7Nz5MiRBQUFvddz//33jxo1ysqy7KVyJMeq97689NJLh99lAB+mnJ5e\nn4QHgFPOTTfd9NBDD7355pvH9uP3PmTvvPPOyJEjp0+ffphXtE8J6XS6srKyoKDgwI/uAuhH\nvMcOwKlt7dq1N9xwwylRdZIGDx585513PvPMMwe+bn5qWb58+Ztvvrl48eL+HgiA9+A9dgBO\nbdYnBk4hN954Y2dn5549e07pD5P29PQ8+OCDU6ZM6e+BAHgPXooFAAAwBC/FAgAAGIKwAwAA\nMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcA\nAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIO\nAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCE\nHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADDEgP4eAAAA/WzTpk0PPvhgf4/i\nFDZ//vzzzjuvv0cBibADAODFF1985plnLrnkH3t6lP0jqadHmYykvn/3nu3AP9aCR/XHWvPR\nbugYNtd7/Ue7oUNtLjf3uUAgQNidJAg7AABUVlb24IMPp9PKZGT9LSmdVu8p2b8PP1E6ipmz\n3/ZZ6siXzS74QQ8yu2CfKU7n9v45ZzgY3mMHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAA\nhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAA\nAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGGNDfAwAAoP81\nNzffcMP1PT3K/pHU06NMRlLfv3vPduAfa8Gj+mOt+Wg3dAyb673+o93QoTaXSu2Qpn/wpwhH\nhLADAHzUzZgx480335S0e3drR0fH6aefXlxc3N+DOiLvvvvutm3bst8OHTo0EAhkMpnGxsZk\nMjlixIiBAwdKOpIpWUe/+OxZs2Z9qLuNQ8vpsfIbAICPtkcfffShhx6aP3/+4sWLly1b9slP\nfrK/R/T+3nnnnaeeesr6+nvf+96999576aWXXnPNNel0uqam5gc/+MGmTZsKCwuPZEp2nce5\nOPoXYQcAgCSNHTv2F7/4xZgxY1atWrVixYpf/epX/T2io9DR0VFZWdna2hqNRqurq3ft2uVw\nOG666aYzzzxzzpw57zvlxhtvtNbz9ttvH8/i6Hd8eAIAAKXT6TfffHPMmDGSJkyYsGnTpv4e\n0dFZuXLl7NmzXS7X1q1bR48e7XA49PcdOZIp2fUc5+Lod4QdAACKRqMej8f6etCgQeFwuH/H\nc7Qef/zxuXPnSnrnnXe8Xq810dqRI5mSXc9xLo5+R9gBAKCCgoJEImF9HY1GfT5f/47nqDQ3\nNzc1NU2fPl3S4MGDY7GYNd3akSOZkl3VcS6OfkfYAQAgh8NRUVHxl7/8RVJtbe3YsWP7e0RH\n4Yknnrjiiius10Y//vGP/+Uvf0mn0/r7jhzJlOyqjnNx9Ds+PAEAgCQtW7bsoYce+tKXvrRk\nyZJly5ZNnTq1v0d0pKqqqpYuXTphwgTr23nz5qXT6XHjxv3whz/cvHnz4MGDj2TKpEmTnnvu\nuSFDhhzb4v17BJDlWLRoUX+PAQCA/jdu3Ljhw4e/9dZbt9xyy6RJk/p7OEcqkUgkEokrr7wy\nO2X27NnWxMWLF/v9/iOcEgqFJk2alJeXd2yL4yTBM3YAAACG4D12AAAAhiDsAAAADMHvij2p\n5PT3AHp7n9fok0ml08rP3//F3r1KpeR0Kj9fqZRyc5Wfr+5udXUp9+//g2hokM+nESPspYJB\nJRIaMcKeOR5XJrN/ZqdTeXmS1N2tcFiFhXK7JSkSUWurrB+iNHCghgyRpJYWNTSovFySAgG5\n3WpstL92OuV0KplUfv7+8VujLSmxl21tlccjv98ef0uLJBUW2rv29x/YJMkeZFubOjs1dKhK\nShSP24O3/paUSsn6/TrWROsL6+CkUvZIcnPldsvhUDKp9nbFYvJ4VFBgT4xE5HTau2at0zqY\n1uKJhKzfY9nSojPP3D9DPK5EQpGIzjzz4GctOx5LJKJkUsXFcjjes6E+i0iKRhWPKxBQIqF0\nWl7v/tnicTkccrvV1iavV7GYvQu5uXI4lE5LUiwm6wdd5efb+2idSmvlDodCIUWjqqhQJGKf\nFOu879yp7ds1ebJ9KKwjkB1kPG4fUkufkfeRTNoHufds3d1qbpbDobIyWT+94Qh/MZJ1GfS5\nMKzjkN2v3qNKp/dfgb3PgjVndi96j62tzb47pFLy+RSLyemU223Pk0zuv5dZ9u5VYaF9KvsM\n9cCTlb3bWquyttJ76+m0QqH9F3/vcWZH5XRKUiajdFqxmHw+BYPyeuX1qrVViYScTpWVKR5X\nLGavKhKRz9d397N3nN4DsEaYySge19atCoVUU6NAQLGYUikNG2bPkGUdH+ta6uzU8OH2IS0p\nec+dPR5XOKxUSjt3qrJSRUVKpRSL2Q8v6bQSCeXmKhazH7isI9/RofLyvhdY78eltjY5nSos\nVCik+nqlUho9WuGwurtVWCivd/9ovV4lErLek5bJKBSSwyGfT01NcjoVCCiZlKSODkmqrFQk\nosZGFRfL51MyuX8vWlvldmvgQPtEdHQolVJRkTIZNTertVV//KMaGjRvnqqrJampSdGoQiFl\nMioo0IQJcrvV3KxgUNOnq71dmzeruFjhsIqKNH26nE6tXSuHQwUF9omLRhUIaOhQdXYqFLIf\nVAMBBQIHuerQj3jGDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAE\nYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABg\nCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAA\nwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0A\nAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7\nAAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQ\ndgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACG\nIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAA\nDEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEPk9PT09PcYkJXT3wPore+F\nEYvJ6VRzs9xu+Xzq7lZnp1wuNTcrk1FBgWKx/TMXFio3V5J27dLw4XK71dGhlhatXy+fT9On\nK5mU36/8fLW1KRpVWZkkbdmiREJut4JBvfKKLrxQFRWqqFBjo7ZtU2Gh3G7F43I4NHWqNm+W\nJLdbgYA8HjkcSqe1dq3Gj1cwKEnRqCIRVVervFx5eeruVm2t2tsVjSocVlmZJk5UXZ2ef15l\nZaqqUjSqtWtVVqZYTKGQ5szRrFn6zW+UTmvsWHk8ikTk9UpSe7ucTjkcamhQRYWGDrXXfP75\nCgSUTtv74verulovv6xt2/TpTyuVUnu7hg/Xzp3y+exh7N2r/Hy53QqFVFam8nLFYuroUCql\n6mo5nWpvV3e3JHm9ymQUiymRUFuburpUXq7CQnvBcFiplEIhVVQok9Fvf6szz1RFhXJz9eqr\nKi6W262WFo0apdZWVVQonVYsptpadXVp9mz5/UoktHmzEgmNHq3RoxUOKxZTQ4OGD9d55ykY\nVEuLMhnl5qqrS9u3y+PRqFFyuyUpN1ft7QoEFAiouVmhkFIpFRRowwZNnmyfXEkbNiiR0LRp\nCgZVVqaSEqXTqq9XW5t8Pknq6pLfr9ZWDR2qwkLF43rwQXm9qqxUQYFKSuzLLJORx6NkUrGY\n9uxRW5vGj1dRkdrbFYvJ7Zbfr0BAiYRcLm3dKpdLhYX2PiaTWrVKmYyqqpRIqLJSublqbVVz\ns8rK5HarqEiJhIJB/f73amnRZZfpqqsUi+2/xqzj5vOpslL5+QoG5XJp1y6ddZZ27FBbm7xe\nBQJyOvXccyot1ac/rVBIwaDq6zV6tMrK5PXK41F7u9rbtW2bioslqbFR4bCuvFLhsEaNUjqt\n116T36+CAuXna/t2hcP2gj6fWlvldKq4WOGwli9XTY06OjR5sqZPt++n1p1oyxZVVqqwUC6X\nJCUS2rlTyaQqKrRli5xO+2KbPFlut9rbtWaNSks1YYJ9N/T51NQkn0+FhfbVGwzq1Vc1dqwm\nT5bHo1BI9fVqbFQgoOpqtbTYd5+GBqVSGj9eLpd8PjU02MckHtcvfqGiIo0YoURCf/yjRo2y\nB+bzKZm0LyqPx961LVsUDKqjQ5ImT1Y0qnRabreSSSWTuukmxWKaOlVz5qiy0j7706Zpzx6F\nQvJ65XCoqEhOp33HcbsVicjjUWOj6uvV3q6KCjmd8niUSqm4WFOnqrtbqZSiUb36qnw+JRJq\nb1ckIp9P4bA+/Wn98pdyOvWDHygSUWGhurv1+9+rsVHnn69YTE1N8vuVyai9XY2NGj5c55yz\n/3GjsFAbN+qXv1QioUsu0ZQp6upSba0GDtSuXSoq0qhRSiZVX69IRBMmSFJZmf0gWVysaFS5\nuSorU3u7Ghrk8aigQMOGyeVScbFqa5VMqrFRyaQee0wdHbr+ek2erJYW1dVp9GiVlmrpUtXW\nSlJRkbxeVVWpokJut84/X16vVq9WXp6mTdPrr+uyy5Sbq3XrlErZj3hDh2rYMOXm2vcv647v\ndtu7Zv2NkwTP2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwA\nAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHY\nAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiC\nsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAw\nBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAA\nYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4A\nAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQd\nAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEI\nOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGCInJ6env4eA7Jy+nsAvR3ywohE\nFAopHNaOHdqwQeeeq/HjNWqUnn9eiYQkpdPauFEjRqi7W16vRoxQS4tSKdXV6bHHJOmuu7Rz\npy69VA6HUimVlWnjRoXDikQUCGjDBm3ebK/T71cgIJdL9fVav17t7Wps1AUX2Ou5/HL9+tea\nNk2jRumCC/TlL0uSx6PWVkkqKpLbrXBYt9wir1d//KO2btWECaqpUVeXtm9XKKSyMu3YoY0b\nVVSkWExut8rKlEpp3TqVl2vlSjU2qrFRgYBaWuT1KhBQVZXq65VOq7lZHR2KRNTRodpaTZig\nykpNnapAQN3dSiQUjSqVUjyuVErBoJqblUgoHFZpqaZPV1mZNm/W1q1avVodHT4H3gYAACAA\nSURBVPrsZ9XRoQ0bJKm8XN/5jubMUXOznnxSHo/8fjU3KxpVa6u9Lb9fr78ut1vFxdq4UaGQ\n5sxRXZ38fpWXq6JCHR32uWhuVjCosjJt3br/1JSWqqZG1dX6/e/l9Wr2bIVC2rNHkYi8Xn3u\nc3rlFdXVadYsJRJyOu3z/tpr8vn00kv2gS0t1ejRCgS0c6cWLFAwqC1bNGyYNmxQLKa2NnV0\n6LbbVFGhhQu1Y4cWLJDTqZdfVm2tPv5xLV6sqVPV3KymJn3zm6qr08UXa8IEvfaaiopUXKxw\nWKtWqaNDX/2q8vJ0zz3KZDR5slIpzZwpv1/hsH74Q4XDcjo1bZp+/3tJ+tKXNGeOurqUSqm0\nVI89poICjR8vj0dVVYpG9fzzcrvV0qJAQD6fCgvV0qKyMhUXa+1arVqlUaNUVianU42NmjVL\nl16qcFiplHw+OZ3askUNDRo1Sk6n3G5JCoW0dq3GjlUopOXLVVGhESNUUKBhw1RaqtZWrVol\nSS0t+vznNWWKRozQ8uWaMEH19dq4UYGA0mklEqqqUiymxkZddZVWrVJBgbxepVJyu7V9u3bu\n1MSJSiQUi6mrS06n2tq0a5eGD5fXK4dDs2apqsoeZ/boFRbqrLMUjUqSy6VEQu3tam5Wa6vC\nYS1YoERCLS0qLNSWLdq4Ueefr3nztHq16uoUiai1VaNGqaJCkYiCQW3apIED9elPKxzW0qX2\nA8LEiQoE5HTaB1bSV76i0aP1yCNyOjV/vtxuvfqqdu5UTY2+/31VVKiiQsmk6up0ww1qblZ1\ntfx+bd2qigr7/uv1qrtbjY1atEiS/H7NnKnmZjU2as8eVVXJ51MwqJ07lUrZd5myMq1bJ59P\nU6YolbJP68sva+hQLV+uW27Rpk32gK2TYo28sFCxmDZsUHm5HnlE3d2qq1NNjdat0/r1KixU\nWZna2vTss5I0cKA6O3XNNfrZz9TWpkxGoZBqa+XxqKFBHR1qaVFlpTo6lExq3Tq1t0tSZaUa\nGvSpT8nr1bPPyuPRggVyuxWNauNGVVSotlaNjZJ0223yeJROS1JdncJhzZoln08//akSCRUU\nqLpal10mj0e1tWpult+vnTvldOrVV+V2y+XSrl32qiwej5xOlZWpvt7+1nqIljRtmiZMsB91\n589Xba2WLNH55+uOO9TYKIdDPp8uukiScnM1d64WLtSqVdq8WYWFmjpVfr/cblVUaMsWTZig\nkhJ5PEf6Tws+aDxjBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiC\nsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAw\nBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAA\nYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4A\nAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQd\nAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEI\nOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABD\nEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAA\nhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCFyenp6+nsM+LtFOf09gl4W\nHfLCiMclKT9f8bgSCUlyu9Xdrbw8OZ1yuxWPy+2Ww6F4XO3tKiiQ2y1JDofcbiWTSqeVSCiV\nkscjp1PRqGIxBQLyeiUpFLLX6fUqHld+vrq7lUpJUiajYFBOpxwODR2qVErhsNxu+XxKJBQO\nKxbT6NGS1N2tREJOpyQlk3K7lUiouPhw+2KNzZLJKDfX3osD53e71d4uSQUFcjiUmytJqZTy\n8+3ZIhGlUvs3l13KOgiS0mklk4rF1NGh3FyVldnj7OxULCa/Xz5f3033HoPTqbw8hUL2rqXT\ncjiUTsvrtc+I16t0WqmU0mm53fbAsjvbe1XWUSosPNy5zkql5HSqo0PptEaMsLfee1WSPJ79\nm0sk9n/bm7Xv1lnr7pbXq1RKHR32IbWuoljMPunt7SottU9ln/H3Zh3SA2fIHvw+x7O5Wem0\nCgoUjcrtlsu1/0D1Wdy63pLJvofOOgu9pxy4FYt1AfdZ3Po2FlM8bi9lXTDZqz3Luj6zRzu7\n3ZYWeTz7r9XsPeVQh6jPflmrlfpeHn2+yNqxQ7m58vlUWGjfVWMxSfZh93oVi8njkfSe8753\nrxwOOZ1yOvffYa0Dbg117973HPnsLliHJZnUzp3KzVVxsZxO+xBZg29pUTCokhIVFCgcVnGx\n0mnt3CmfT0VF9t05lbIfZyQ1NiqZ1IgRamhQbq4CATU32zvidisc1uTJ9ono7lZDgxwOnXWW\nGhvt8Vv3pvx8FRUd/AhnRx4Kqb3dvnsOG6aCAm3Zoq4u1dQoGpXPJ5dL0agcDnk82rBBr7yi\n1laNH68rr9x/iuvqlE4rFlMopD17NG2aUikVFOicc5RMqr5eQ4cqENDGjcpk5PcrHldjo0pK\nFAzK7VZurkIhdXWpokJ+v5qb5XDI67XvX83NKi6W12uvqqpK6bQkdXaqqsreHbdbLS1KpdTe\nrnRaFRXq6FBRkRwO+yxY9+JQSCUl9iMYThI8YwcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYA\nAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDs\nAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB\n2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAY\ngrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAA\nMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcA\nAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIO\nAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCE\nHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAh\ncnp6evp7DPi7RTn9PYJeFr3PhZFMKhxWQYHy8w8+QzAoSYGAJKXTSqeVl6dkUqmUvN79s8Vi\n+2/tPf1IxGJyOpVKyemU261YTLm5am6W369EQpmM4nH5/ZLslcdikpSbq0zG/trnU3u72tpU\nUiKPR263uruVlyePR8nk/l1LJhWPy+GQwyGv196L3Fw5nerqUjKp3FwNGaJYbP/iDkffoVo8\nHiUS9pTs/lpfWPMc9CBYW7T+DoXk8ejMM/ffmk4rkbA3GovJ5VJXlyTF48pkDnKOYjHF4/bI\n/f6DHPxIRImE/H45HEqn1dysaFR+v302rTW4XMrL2z82af9ZsE6K17t/YNYuZzcRDNqj7b3R\nUMheiTXdOpuZjNraFAgoP/8gxyceVyIht3v/xHhc0eh7xtnneFqrtdYWiaijQ6Wl9hq2bVNh\noXy+g1yi2RNn7WOfm3rPvHevfTCzl3oyqaYmDRu2/wrsM6TubiUSfQ9R72OYStlnYcQI+1Af\nuFPWxAPvXwfKXorZ2WIxxWJqadHo0YpG5fGosFDd3erqsk/T3r3as0dOp5xOFRfL5VIsps5O\n5ebaJ8vrfc/81nnx+Q5+L8heGOl032tAUjwut3v/gsGgQiF5vSoutpe1rmpJW7ZIUk2NOjrk\n8SgYlNcrh8Mef+8T195uD7KPeFytrUqnFQjI6dx/N7EelKxV9T4voZBSKft+0fswxmL77/LW\n8LxetbUpGlVpqX2xWavyet/zwJjdR+tq9Pl05pn2wenuViYjt3v/gtmj1/uLlhYVFtpri8WU\nTCoSkcMht1uBgIJBRSLKz1dRkaJR+8g3NOj55zV2rKZMUSJhPwh0ddnXtnXvkPafo3BYsZhG\njz742exzj8DJgGfsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQ\ndgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACG\nIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAA\nDEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEA\nABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrAD\nAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARh\nBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAI\nwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIOAADA\nEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMMSA/h4ATjGxmCR5vUqnJSmV\n0vbtys1VYaEiEXV0KBaTz6eCAnV0KJVSLCaPR6mUEgm98ora23XBBaquVkODyspUXCyvV8mk\nwmFlMkomlUrZU4JBOZ2S5HDI41Frq2IxRaMaPlwOh/x+eTyqq5PfL7dbubnKZCTJ51NHh+rr\n7U37fAoElJurigp1d+sXv5DPp+pqlZYqEFB3t+rrFQopENDrrysY1OjRmj5dq1ervl7XXKP8\nfDU1qb1dBQVyu7Vli9xuTZ2qYFCJhJxOFRUpL0/ptFIpBYMKBuX1SpLfr0RCXq9iMcVi9mzx\nuFIpNTYqmdSECXI6FY/bR8nnUzCosjKlUvZByK45kVA8rkxGPp/icQWDKihQSYkkRSJqbNSo\nUQqHFQqpuFjd3XI4lEwqFlNhoQIBScpkFAzaa25v1/btqqpSSYlyc+2j5HCoq0sulzo67C0m\nk/J4FArJ7VZ7u1pblZur0lJ7AA6HfTHU18vlksOhdFoTJkhSe7tCIUnyeJSfr1BIZWXavl3N\nzaqo0Nix9oLBoLZv15w5ikQUDiuVksejcNhes8ejzZslqaJCiYTCYUkKBNTYqEhEPp98PiUS\nKiiwD0s4rO5u5eUpGFRursrK1NamTEbxuBwO+4xYl67XK69XkYhiMW3ZIo9H1dWS1Nam7m55\nvQoGtXmzvZTXq8ZGlZaqulqJhH3ZW+uJxdTYKL/fnpJOK5mU16tMRl1dGjJETU1KJOTzKRaT\ny2UfZ2vOcFhNTfaVn2VdLdaUeFzRqPx+eymXSy0t2rFD6bQcDpWW2ne6SET5+fL75XTK4VBu\nrr2J7J5aX7S1KRqV16uCAqVSam/XqFH2Jqy7RiZjn+jCQjU0yO2Wy2WvavVqnXOOSkvldKq9\nXem0fD41N2v7dmUy8npVXi5J0aicThUXy+Oxd3DLFrW2qrRUiYTmzlVXl30Shw5VXZ2amlRW\nplhMra0qLpbLpZISFRTI61VurvLyJGngQEnatUvJpEpLVVio11+X16vWVoVCOv98eTxyOrV+\nvcJhTZ6snTsViSiRkMejZFJbttgXVWurMhlNnqzmZns3CwoUDqu2Vsmk5szR2rVqaFB1tWbN\nUjQqn0+plJqb1d4uj0evvqrGRo0YoYoKe/c7OlRUpOnT7Xt3OKxt2+yBWYd3zRql03r2WZWW\n2pd0TY28XvthKpFQe7vicX3+8/L7dfvtKijQrl2SdOmlqqzUvHn2MfR69eSTkuR0auNGPfec\nCgq0YoX8fq1bp6eeksej8eNVWqqtW1VRIUnf/a6i0f0X1cCB6uy071CJhM49V6mUtm61b734\nYq1ZI59P992nsjL5/fL75fNp/nw9/rgkXXONJk58z4P/Zz+r66+Xw6GiIiUSKi5WPK49e1RT\no2HDDvavBfoJz9gBAAAYgrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDs\nAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB\n2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAY\ngrADAAAwBGEHAABgCMIOAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAA\nMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcA\nAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgCMIO\nAADAEIQdAACAIQg7AAAAQxB2AAAAhiDsAAAADEHYAQAAGIKwAwAAMARhBwAAYAjCDgAAwBCE\nHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAh\nCDsAAABDEHYAAACGIOwAAAAMQdgBAAAYgrADAAAwBGEHAABgiJyenp7+HgMAAABOAJ6xAwAA\nMARhBwAAYAjCDgAAwBCEHQAAgCEIOwAAAEMQdgAAAIYg7AAAAAxB2AEAABiCsAMAADAEYQcA\nAGAIwg4AAMAQA/p7AOgtp78H0Bu/RBgAgFMMz9gBAGCUb3/7WG6CGXjGDgAAnHgvvfTSn/70\np3POOeeiiy76r//6r2Qy6fP5vvSlL/3kJz9JJpOTJk2aOHHiE088EQwGa2pqpk2bll3we9/7\n3vjx42fOnNl7qQceeEDSnj177rnnnn7bpVMBz9gBAIATrKen5+GHHy4sLDz77LMlPf/88/F4\nvLOzs6Oj48033/yP//iPJUuWdHV11dbWfvWrX125cmV2wRUrVnzsYx9rb2/vvZSkm2666dxz\nz62srOyvPTpVEHYAAOAEe/fdd1tbW6+66qo777yzp6fnsssuu+mmm+rr630+Xzqdvvfee0Oh\nUGdnp9frlZSTY7/F/K233nr66afr6+vXrFnTeynr1l/+8pdXXXVVv+3SKYKXYgEAwAnm8XhG\njRr1xz/+0e12d3d3P/PMM2VlZel0Ojc398orrwyFQnl5eUOGDGlvb//DH/5g5d3atWsvuOCC\np5566pVXXnnrrbd6LyVp9+7dxcXFbre7v/fsZJfT08OHH08efCoWAHC8vv1t3XnnUd90wr37\n7rtbtmwZM2aM2+3eu3dvY2Pjueee63K5Ghoaenp6zjnnHEnxePyNN94YO3bsgAED3njjDet1\n22g0mkwm/X5/76Xefvttp9M5ePDgD2n0pyzC7qRC2AEAjteh6i37kdgPre3w4eM9dgAAAIYg\n7AAAAAxB2AEATlX8uN1D4ch8ZBF2AAAAhiDsAAAwH8/hfUQQdvhQ8cgC4ETh8eTIcaw+Ogg7\nAMBHzkkVOt/+9gcynpNqH/GhIewAAKcw8qWPIzkgHDSDEXYn0owZM77xjW/09ygAc/DPD3D8\nuB99pJgQdhs3bnQ4HJMnTz6xq/35z39+1llnuVyu0aNHP/fcc0d4E8zA4+DJg3PxEWfYBXDS\n7s5BB3bSjhaHYULYPfLII1/5yle2bNnS0NBwotb5wgsvXHvttdddd93rr79+0UUXXXrppXV1\nde97EwDgA3VCUuND65V+D6MP6N17OJmd8mH37rvvPv744wsXLrz88suXLVtmTXz44Yf9fv++\nffuys82dO/fiiy+WlEgk5s+f7/V6i4uL77jjjquvvnrBggUHrva+++777Gc/e+utt44ZM+bu\nu++uqqp64IEH3vcmSel0+tZbbx0yZEhJScntt9/Or+IFgFOdlUdHG0kUFfrFKR92v/71r8vK\nyqqqqubNm/fzn/88lUpJuuKKKyKRyIsvvmjNE4/Hn3322S9+8YuSvv71r7/44ourVq3asGFD\nKBQ66AupPT09r7322owZM7JTZs6c+X//93+Hv8mydOnSnJycl156acmSJffff//TTz/9wew3\n3scxPKTyX9tTFGfNeB/QKc6u9kO+hE6qK7b3YHg11gynfNgtXbp03rx5kv7hH/7B4/GsXr1a\n0uDBgy+88MIVK1ZY8zzzzDMDBgyYPXt2IpF45JFH7rnnngsuuOCss876yU9+MmjQoAPXGYvF\n4vG43+/PTvnYxz7W1tZ2+JssVVVV1tN4X/jCF2bNmpWNSxyVD/9xlgevDxNH2xicypMNZwT/\nn737Dmjq+v8GfgKIbELCFgRlIyoIFVDrKCAquHDWPXDUUff2W23dWmcVB+BA0boVpFocaJWK\n4kAQLYIiuECWIFMg9/nj/HqfNIHIDoT366/ccc79nJOQfDh3nKad2CUlJUVGRo4aNYoQwuFw\nRo8eHRAQQDeNGTPmwoULhYWFhJDg4OChQ4cqKSklJyd/+fLF2dmZ7qOgoODg4FDFY3E4nKps\ncnR0ZF8bGRmlp6dXs00AAE1Jw2cSlZ0VbVQ5jfBwoLSGBiXDP7SySkHaAdRKQEBAeXl569at\n6SK9oO3NmzfGxsbe3t7y8vIXL150c3O7du1aeHg4u8NXqaurq6qqCudkHz9+pKN0EjZRioqK\n7GsOhyMQCGrVQqgE/T5ataqClcKLIjtIqKqyRWgwVXy/oKlj32gZfsdrfymeyFecDPcV1Lkm\nPGJXVlZ25MiRDRs2xPzryZMnHTp0OHToECFESUlpyJAhwcHBJ0+e1NfX79GjByGkbdu2ioqK\n9+7dY2t4/PixeM0cDsfFxUX4LOrVq1e7dOkieRM0vK/+x9kksrQG/r+5SfRJjcl26xqDWvaw\ndN+gGtwA0YTUX9NktcdkVRMesQsLC8vMzJwyZQqfz2dXjhw5cu/evStXrpSTkxs9erSnp2dy\ncvKoUaPk5OQIISoqKlOmTFm6dKmenp6xsfGWLVvy8vIqPMe6cOHCfv36bdq0ycvL69ixY7Gx\nsQcOHPjqJqgK/OtZIeGvTvRP1dF+q7/fs8b/XkgxyJqNkdfsELX/F07ynQHiwQuPLNZeZX3V\nmO9XaCRhQHU14RG7wMDAXr16CWd1hJBhw4alpKTQEbWePXvq6+s/e/aM3g9Lbd68+bvvvhs4\ncKCrq6uOjo67u7uSkpJ45X369Dl8+HBAQICjo+OlS5fOnj3LXjwnYRPUIal/30nxuQY1u6W3\nIVVxbOCrN9zV4LggRV/tf6mPh4mMydV+fLG63wPS6oGGOSj+AJuEJpzYhYSE0CvnhLVt25Zh\nmN69exNC5OTk3rx5wzBM+/bt2R1UVFQOHTr0+fPnzMzMNWvWxMbGmpubV1j/uHHjEhMTS0pK\nnj59OmDAgKpsunbt2saNG9nF3bt3X7hwofYtlRl19dNe43rqPM+orPJ6VVkPVOXEtPj4ViNJ\nIms84tKENP6TmDL5kLZG+5cu/gcrOS9sJDeLNJX3vTlrwqdiayY2NvbFixcuLi4FBQXbtm1L\nT08fNmyYtIOCelTh6aF6PX/XMBp/8I3kd6jGGn4QtLrnMUXGperjhGzN7kCqVtl60rQ+bDUg\n8w2EGmvCI3Y1IxAI1q5da2Vl5eLikpiY+NdffxkaGko7KPiPqv/DWrPK6/ALsbpV1f7oNRtg\nkzDIV0/B1N+vTn3/njXwG9Q8f56lfsa2PjTAZ75evxvZqmp2QgAaj2Y3Ymdvbx8TEyPtKJq7\n2gxO1EltdaK6w34VXqZdf+eJJPdJww9HVWu3OnmQjeQD1d9nprqV1+y9qP07WNlg9lc/nFW5\n0k7CIcT3lPmnn9S5urqIsGaV4J1q5JrdiB00EvinULI6+dmuczW4Z6K+96lBKamciK/lQZv6\nxQNfvXqsXpvW1OsHqBYkdlAvGvj/yKp8sdbtScwa1FMnIdU34ZDEx8mqUqquwqi/zO+r9dTV\n73Qtz9RL+Oen9h+nao26gbRIK2VEqtqkIbGDutdUkpiqE/+aa7A2Ch+6ni7pq81PeF0lvvWq\nBqfLq1tWcmpY45SrIf9q6uNfo1pq0l8aANLS7K6xg7olcrFFtX6ThC+vaVrqdmikMWu0F9PU\nJlcT3lSzix0bslvq+xwiqcLfYG1iaIqf/+bzB15jTffbuzlAYgc1x173UyfPZ2/83491+HNe\ng7E3aanlj1wjf1vrMLyajXfWqwo/sY35HWkM/0g05v5pbBrD+wXikNiBlEn+GpXKpU51oml9\n5dX+9B9+DivU2Dqz8V8m0aiCaYQaW/80rS+6ZgKJHUA1VOs6pMb2Fdx8NEDP1/L3rME+GzWI\ns9l+bpttw+tPQUFBQkJChw4dFBQUxNdU9lq6McsA3DwBNSSSweA7ERqzev2I4sMPUKF58+bl\n5eWtWLGiwjWVvYZaQmIH0Eg1k3S5gW/8rMN7eJvKu9PkAm5C0KWk8k7IysrS19fv2bNnfn6+\n+JrKXjdc3LILY55QE/g6g9qTgU9RI7xhovEcFJo5NTW1z58/E0IYhhFfU9lr6cUrOzjox8aE\nI+0AhFX6wcCPBDQrIhNeNf7Pf1OJE2RGZddxnjhx4sOHD46Ojj169NizksBKQAAAIABJREFU\nZ8/MmTOF11T2umFjl0FI7BqVJpDY4dcCmi0kTAAVwo2xjQoSu0alUSd2+D0DAIAKIbdrPJDY\nNSarG1NitxofDAAAgCYGd8UCAAAAyAjcFQsAAAB1LyIiIjo62tbW1tvbe8+ePcXFxTweb+LE\niX5+fsXFxV26dHFxcTlx4sT79+8dHR179uzJFtywYYOTk5OHh4dwqR07dhBCPnz4sGnTJqk1\nqSnAiB0AAADUMYZh9u/fz+Vyra2tCSFhYWEFBQX5+fmZmZmJiYnz58/fvn17SUnJ/fv3FyxY\ncOrUKbZgcHCwrq5uenq6cClCyNy5c+3t7W1sbKTVoqYCiR0AAADUsaKiordv344cOXLVqlUM\nwwwZMmTu3LmxsbE8Hq+8vHzLli0ZGRn5+fnq6uqEEA7n/y4xf/369blz52JjY8PDw4VL0a2/\n//77yJEjpdakJgKnYgEAAKCOqaioWFlZ3bt3T0lJ6cuXL+fPnzcxMSkvL5eTkxsxYkRGRoai\noiKfz09PT7916xZN765fv+7m5nb27Nk7d+68fv1auBQh5N27dzo6OkpKStJuWWOHu2IbE9wV\nCwAAsqKoqOjp06ft27dXUlLKyspKSkqyt7dv2bLl8+fPGYaxtbUlhBQUFPzzzz8dO3ZUUFD4\n559/6Hnb3Nzc4uJiPT094VIfP35s0aKFlpaWtJvV2CGxa0yQ2AEAAEAt4Bo7AAAAABmBxA4A\nAABARiCxAwAAaC4wOaTMQ2IHAAAAICOQ2AEAAADICCR2AAAAzQjOxso2JHYAAAAAMgKJHQAA\nAICMQGJXl9zd3ZcuXSrtKAAAAKCZkoXE7vHjx/Ly8l27dq3DOq9fv+7t7W1gYMDhcI4dOya8\nac+ePd26ddPS0uLxeB4eHvfv36/D4wIAQHODi96gDslCYufv7z9jxoynT58+f/68ruosKCiw\nt7ffs2eP+Kbg4OC+ffueOnXq1KlThBAPD4/U1NS6Oi4AAECdQL7YPDX5xK6oqOj48eNTpkwZ\nOnRoYGAgXbl//349Pb2ysjJ2t1GjRg0cOJAQUlhYOGnSJHV1dR0dnRUrVowePdrX11e82gED\nBqxdu9bHx0d8099//71ixQoPDw93d/ezZ88WFBRcu3aN3VpeXr5kyRI+n6+vr798+XJMxQsA\nABLUbfqFZA6afGJ35swZExOTDh06jB07NigoqLS0lBAyfPjwT58+sflWQUHBxYsXx4wZQwhZ\nvHjxtWvXLly4EBkZmZGRERoaWpujl5aWMgyjo6PDrgkICOBwOBEREdu3b9+6deu5c+dqUz8A\nAEAN0AwPeV4z1OQTu4CAgLFjxxJCevTooaKiEhISQgjR0tLq27dvcHAw3ef8+fMKCgr9+/cv\nLCz09/fftGmTm5ubpaWln5+fhoZGbY4+Z84cS0tLT09Pdk2HDh02btzYoUOH77//vk+fPsKD\neQAAAPXt55/rMp+r29qgATTtxC4pKSkyMnLUqFGEEA6HM3r06ICAALppzJgxFy5cKCwsJIQE\nBwcPHTpUSUkpOTn5y5cvzs7OdB8FBQUHB4caH33x4sU3btwICQlRVFRkVzo6OrKvjYyM0tPT\na1w/AAA0E3WSPFVYiXBmJr6D5OMipWuKmnZiFxAQUF5e3rp1awUFBQUFhY0bN4aHh79584YQ\n4u3tLS8vf/HixY8fP167do2eh63DK97mzp0bHBx88+ZNCwsL4fXCSR6HwxEIBHV1RAAAaFrq\nKjGqfT0iA2+VvQYZ0IQTu7KysiNHjmzYsCHmX0+ePOnQocOhQ4cIIUpKSkOGDAkODj558qS+\nvn6PHj0IIW3btlVUVLx37x5bw+PHj6t7XIFAMHXq1LNnz966dcvS0rJuGwUAAABQYwrSDqDm\nwsLCMjMzp0yZwufz2ZUjR47cu3fvypUr5eTkRo8e7enpmZycPGrUKDk5OUKIiorKlClTli5d\nqqenZ2xsvGXLlry8PA6HI155fn5+UlISfZ2amhoTE8Pn842NjQkhEydOPHfuXFBQUH5+fkxM\nDCFEX19fX1+/IdoMAABNRJ3f7rpqVV1W2ISODtXShEfsAgMDe/XqJZzVEUKGDRuWkpJCb1no\n2bOnvr7+s2fP6HlYavPmzd99993AgQNdXV11dHTc3d2VlJTEK4+KinJwcKBX4K1YscLBweHn\nf/9GT548mZ+f7+Pj4/Cvffv21WM7AQAAvgZnVIFqwiN29AZYEW3btmUvpJOTk6PX2wlTUVE5\ndOgQPV0rEAgsLS3pWVoR7u7ulV2QV1xcXFlIIvfA7t69W2ILAABANlUxzUI2BnWuCSd2NRMb\nG/vixQsXF5eCgoJt27alp6cPGzZM2kEBAABUrAGSP3oInGyVDU34VGzNCASCtWvXWllZubi4\nJCYm/vXXX4aGhtIOCgAAZIfIPacimZmEh4+I11PZPg0/1IfBxaai2SV29vb2MTExBQUFOTk5\nN27cqM1z7AAAoKlrmHylzh8aXOHr6lZSWcYJTVqzS+wAAEA2NM5EREJUktM7pFlQJ5DYAQAA\nVKwxZ1eY7Asq1OxungAAAKCQGFUI3dKkYcQOAACal2olLvWxc51fcodUDFhI7EBm4ZsOoA7V\neX4j3b9Q4WSo6pFIPWaAr0JiB7Kplt+A+AKFxqYxfCardTNmXT2nQ1oNl+4wWFNpdWP4WIII\nJHbQcBr+i1LkiBUene5Ts3/fm48675PGMEaCN1oyyX8v1S0oXklV9vxq5cJ/tlWJrcYHbZiv\nr9o82a4BVPe+3YKCgkePHpWVlVW4prLXUEtI7KAe1fkc2FX5WqnWAwWqG0CdaxJPGW2wB31B\nZaSeUtQsyRPfVJU14lsrPIpISldZccnPCq4sjJp1eHP4DFcrs5w3b15eXt6KFSsqXFPZa6gl\nJHZQX+ppPF/C929l3zh1kueJDDA0khMllcVT9Su4axNGjcdIqvIzXGHNddjtFSYK9TR221R+\n72vzeWiA4wqP8301HfzqZ6lu1WH90h2Tq6KqBJmVlaWvr9+zZ8/8/HzxNZW9rvfQmwE87gRq\njv3DZmcYrNY/6NWal1AkmxEuW68/9tWqn+4puV3i+4jXX5sZG4V/zMTrET//VWHMFZYVP0RV\ntgp/NqrYriqOqdSJqqSkFYZd9eZUMYyq1Cb+ya9xDFVsV+3ftSrWU7f9Wa+aUKgNo7IOUVNT\n+/z5MyGEYRjxNZW9brCwZRgH/diIrOZIOwIhq7/+waj9Dy39OpCcIIrsU3tVTwq/emgJO1SW\nVFVRZT+6VQyswqq+2pDaHKUGkdS4/sp+VitMmiXvXOPDVZbEs0cUb6P468pqk/CvS2Xv5lcT\ncfboIi/Eq5IQdoOR4kGpqnwzVGXPZqKyj9+JEyc+fPjg6OjYo0ePPXv2zJw5U3hNZa8bNnYZ\nhMSuMWlSiR2+zupVw/9yNMBPaVVSzNrUXB8ZdoX1SDhQDfLFusqkxTM2ybVJJXlq5KrYJ/X3\nSW6iMITZqCCxa0yaQmKHLzKoMWQSDQZdDQ0JiV2jgsQOAAAAQEbgrlgAAAAAGYHEDgAAoBoC\nAgLU1dXd3d3d3d33798fEBDA4XDOnTtHCHFwcDh69GhUVJS6unr37t1NTEx+++03usOxY8cI\nIWvWrOFwOHfu3Fm1apW7uzut0Nzc/I8//hAutX37dlq/goKCu7v74MGDy8rKdHR0XFxctLS0\nsrOza7MYHR2toqIiLy+fkpJCCElMTFRRUenZs6eamtrDhw/PnDnTpk0bJycnFRWVlJQUka00\nYGdnZ1VVVUKISFWsytYTQrp37x4eHk4I+fbbb2lU2traa9euray3Fy1apK+vb29vz+VyCwsL\nReKR3FJCiKurq5mZWYcOHehBK6xTcv8kJye3a9eulp+ZBsUAAABAJUpLSw8cOCC8xt/fv337\n9sKLPB7P0tKSYRh7e/ugoKDhw4ePHz9eeAdtbe1u3boxDNOuXTs+n3/79u2ffvrJzc2N7mBm\nZhYWFiZSilJRUaEvdu3a1blzZ4ZhvLy85s6dW5tFWqG2tvbr168Zhlm/fj2Nbfjw4dOmTWMP\n7erqunHjRvGtCQkJNjY2ampq7J5sVSLE15eUlOjp6TEMExQUZGhoyK5PTU199epVVFRUeHh4\nfHx8eXl5cHBwWloaLUL3sbGxOXjwoEg8klt648YNa2vrrKwskcBE6pTcPwzDmJiYpKamijew\nccKIHQAAQAViY2M9PDz4fH5ISIjIpsLCwjt37ty5c+fjx4+EkLZt2+bk5Dx79oxu7dSp06lT\np2bPnp2cnEzXmJqavnr1SiAQ5ObmqqurV3g48VLC7t6926FDB0KIi4tLTExMbRZFah4+fHh+\nfn5ERMS9e/f69OlDCMnMzLx69WpJScnIkSPFt06aNGn9+vU16lESEhLC5XIJIadPn+7fvz8h\n5N27d9HR0XRN7969f/75ZxcXly5duuzbt8/W1pYQoqioSMumpaV16NBBJB7JLT179uybN28c\nHBy4XO4///zDhiFSp+T+IYR07NgxMDCwZk1ueEjsAAAA/iM5OdnExMTLy6tr165ZWVmhoaEi\nO7x582bChAkTJky4ePEiXfPDDz/MmDGDvl6yZMnq1avDw8MtLCz2799PVxoZGc2YMcPR0bGy\ng1ZYilVYWKisrEwIUVVVLS4urs2iSM1FRUUvX7709fUtLCyk5xzPnj07derUZ8+eZWdni2xN\nSUn58OHDoEGDatCrhJD4+PhWrVoRQj59+qSlpUUI2blzZ//+/X18fAghNjY2d+7ccXFx6dix\n419//aWhofHy5UtacPLkySYmJo6OjiLxSG5pVlaWnp5eSkrKmDFj5s+fn5ycHB0d/e7dO5E6\nJfcPIaR169YJCQk1a3LDQ2IHAADwH0pKSpqamsXFxampqfRSLRFWVlZJSUlJSUlTpkyha1at\nWvX48eMvX77QxcWLFyckJKxevXrXrl10ja+vr7+///z58+mitrZ2QUEBfV1UVGRoaFhhKZaR\nkdGHDx8IISkpKbq6urVZFKl53bp1ffv2ffny5bhx42huOm3atOTk5IEDB27evFlk69SpU318\nfKKjo8vLyyscWZRMQ0ODTjJhZWUVGxtLCNm8efNPP/1Et+ro6BBCVFVVjY2NCSGKioq0848c\nORISEhIZGSkereSWGhsb0461s7NLT0/fvHnzhAkTDhw4IFKn5P4hhBQUFKipqVW3sdKCxA4A\nAOA/DAwMYmNj6cVe1tbWrq6uXy0iJyfXt29fer7P398/LCysrKzs9u3bdICKEDJ58uSpU6d2\n796dLg4aNOjp06eJiYl37tzJy8vr0KFDhaVY06dPv3HjRmZm5unTpydNmlSbRZGazc3N//nn\nH4FA8ODBAx0dnb///jsxMTE7O/vhw4eOjo4iW1u3bh0SEjJmzJiSkpKfxZ6UmJ6eLp6SCvPy\n8qIp1Lp1627dunX06NEvX748efJEQpHY2NjZs2dHRkaqqKiIRyu5pTNnznz69Gl2dvaRI0e6\ndOmyd+/e+Pj4n3/+WaROyf1DCImLi+vdu7eEIBsXaV/kBwAA0KiFh4cLL4aEhGhpafF4PB6P\nN2bMmJCQkJEjRzIMk5GRwefzL1++fPr0aUtLSx0dHVdX16ysLHYHyt3d/cmTJwzD7Nq1y8jI\nyNTU9MKFCwzDiJSiO9vY2LAFly5damho6OvrW/tFHo9Hm7Bly5by8nIPDw89PT0XF5fc3Nzj\nx48bGRnp6emNHj2aYRiRrWww7dq1E6/qwYMHXbt2FV8v3HsGBgbp6ekMw0RFRdnZ2enp6bm6\nusbHxx89enTOnDkMwyxYsODgwYMMw3h5eT1//nzlypVsbwcGBorHI7ml69atMzQ0dHd3Ly0t\nZWMQqVNy/zAMo6+vL+nz0cjgAcUAAADQQHbt2iUQCObOnSvtQKrq6tWrYWFhO3bskHYgVYXE\nDgAAAP6jqKjI1tY2NzeXEKKgoHD16tWOHTtKOyioElxjBwAAAP9RWFj4+vXrFW45+4flfMrO\noBfGQZOAxA4AAAD+QyAQEEJ625JhjkRejnxMS5N2RFBVCtIOAAAAABoXOTk5QsizD+RLGREw\nREdPT9oRQVVhxA4AAKBis2bN4vF4fD6fz+eHhYXNmjXL3t6ebqLXnKWkpNjb2+vq6nbq1OnL\nly+zZs0yNzenOyxfvtzExIQQ8v3339OZZAkhdnZ2IqUOHjxI66cH8vDwIIT069fP2Nj44MGD\ntFSNFy9evGhpaWltbU03paen29vbGxgYLF68mBCyevVqelD2eS5sWSUlJTk5uZH+xGk9+VJG\nMjMzRapiVbaeEDJ8+PA3b94QQvz8/MzMzAwMDIYMGVJYWFhZb2/evNnY2NjY2PjMmTOEEB8f\nH9ozWlpasbGxEqKtsC0V1im5f+bPny88pWxTJe3bcgEAABopT0/PBQsWCC/KycldvnyZYRgN\nDQ2GYezt7efNm1dSUrJ79+6SkhJPT08FBYX79+8zDGNqaqqqqsowjJOT0549e2gNdIpVkVIM\nwwQFBdna2tJ9lixZ4uLikpSUpKamVlJSUpvFsLCwbdu20TAYhunXr9+gQYOysrJUVVXfvn07\nbty42bNns60TKZufn5+dnf3u3TtlZWWGYUSqYlW2PiMjw9TUlDaNy+XeunXr7du3EydOfPTo\nUWW9/csvv9y9e/fy5cvCtRUUFNAAJEcrsrWyOiX3z5MnT9h3oelCYgcAAMA8fvzYzc3N09NT\neKV4Yvftt9/SR7jRxM7IyGj79u3CO9jb2w8fPjwjI8PMzIzuI57YiZRi/pvYWVtbnz17lmEY\nW1vb4ODg2iwKH5RhmH79+q1Zs4ZhGH19/bi4uHHjxuno6HTt2jUuLk78uLTIunXrOnXqxMbJ\nViVCfP2SJUuGDh3KMIy5ubm/v7/wpvHjx48bN65Vq1YrVqyYNGmSvr4+fZgci2ZyIgFIjlZk\nqzhap+T+YRiGz+eXl5dXWENTgVOxAADQfAkEgk2bNrVu3ZrODBsSEiKyQ2BgoLm5ubm5OZ1B\nq1evXmlpaewcpqtWrVq8eLG6uvqECRPoGjoz/ebNm/v06VPZQcVLCfv06RM9n6utrf3q1ava\nLIrUHBAQsGPHjtatWxsZGdnZ2Y0YMWLfvn29evXq0qWL+HFpkeDg4AonY/iqqKgoOvNsRkYG\nPb/s6elpZWV15syZpKSk169fP336dPv27aqqqhEREcuXL2cLrl27ls4DJhKA5GhFtopg65Tc\nP4QQLpcbFRVVg/Y2HkjsAACg+frxxx+XLVs2ZcqUd+/e/fzzz4qKiiI79OnT5/Dhw4cPH2an\n+ZowYQKdU5UQ4uvrW1xcfOTIkTNnzuzfv58QoqioqKysfPz48SVLltB95OXly8rKhOsULyVM\nUVExPz+fEPLlyxcNDY3aLIrU7OPj4+zsfODAgVevXsXExPTr18/Hx2fNmjWqqqrPnj0TLysQ\nCJKTk6dNm1aDji0qKqJzvyopKX38+JEQsnPnTi6XGxcXRwgZP348l8vV0NBYsWKFtbV1eXk5\nLRUdHb1ly5Y///yTLgoHIDlaka1dunSxsrK6cuWKSJ2S+4fukJOTU4P2Nh5I7AAAoPnavXv3\nqVOnTp06pa2tPWHCBJqCCGvVqlW3bt26devG5nzr16+PioqiuUhZWZmcnJyPj0/nzp3pRLGE\nkOHDh3M4HDqTPSHExMQkJiaGEJKenq6goFBZKVbbtm2vX79OCElOTu7Zs2dtFkVqfv/+/fz5\n8/v06dOmTZubN2+y6/Pz87W1tcXL+vv7m5iY0Jiry8jIKD4+nhDSuXPnrVu3EkKsra3V1dXp\n1hYtWtAXLVu2ZItkZ2d7enoeO3bMzMyMrqkwgMqiFd56+PDh06dPd+vWTaROyf1DCMnJyWHv\nj2mqpH0uGAAAQPrS09PHjh07ePBg4ZWenp6tW7d2c3Nzc3O7du2ap6fnTz/9xDDMwIEDORwO\nwzC2trbt2rVzcXFRUVFJSkpid6DoNXZJSUnq6updunTh8/lLly4VL8X89xq7u3fvamhoODg4\nWFhY1HIxMjLSzc1NXl7ezc3t/fv3y5Yt4/P53377raqqalpaWvfu3Z2cnIyMjBwdHcXLMgzz\nzTff0GvyxKuaN2/e5MmTxdezbT9//jy9Ni4rK0tPT8/Kyqpbt24aGhpnz57t2rVrUFAQwzD6\n+vo5OTkMw2hrazMM4+TkxOPxaG8XFBSIBCA5WpGtLJE6JfdPaWmpnp5ebT5FjQGmFAMAAKhY\nVFQUe8WVl5dXVlYWn8+3sLDIzMw8efLkzJkzBQJBWFhYbm7ugAEDNDQ0oqKi6A60yIkTJ77/\n/ntCyKdPny5dumRvb08fdyJSihDy4cOHuLi43r1704Lv3r27d+/egAED6GBVjRdTUlLOnz9P\n65w0aZKGhsbjx49jY2MHDhzI5XKzs7MvXrxoZGREr4ETr+r06dNeXl4qKiqEEJGqXr16VVpa\n+s0334gfgu09Q0PDpKQkWjwiIiIzM9PT01NDQ+Ovv/6ysLAwMDC4cOGCt7e3goLCmTNnhg4d\nGhoayl68OGPGDEVFReEAJEcrvpUSr1NC/+zevfvFixeHDx+u8QemMUBiBwAA0HwJBIJTp07l\n5eURQiwtLSs8QQlNCBI7AACA5ispKcnCwsKET4q+kBYard6+fSvtiKBWcPMEAABA80Xv2P17\nMdkxghQXF0s7HKgtJHYAAADNV1lp6f9//d/HskBTVJN7mAEAAEA2KLZsSQhZco58yCX0NgVo\n0jBiBwAAzZ2Ojg6Xy+Xz+bq6unTRwcGBEJKSkqKnp0cIWbRoEZfL1dbWpre16ujoWFpa0rJ6\nenp0MgP2IW137twxMTERKTVhwgQ+n08fX8zn81etWnXlyhUej6elpXXo0CFCSG0W6b2lNGZC\nyKpVqzQ1Nblc7vz58wkhjo6OXC5XTU3t119/Fd/6/PlzRUXFk49a5Kl/M23aNJGaWSKHYBUW\nFtK7gD98+GBpacnj8bhcrqurq4TetrCw0NTU1NDQOHPmDCHE0tKSz+dzuVz6TLs2bdrQ9+LH\nH38UD15ksbI6JfdP+/bt6TwisknKj1sBAABocBkZGcKL2traCQkJwouqqqpv3759/fq1rq4u\nwzAqKir0yWpv376lO2hra5eUlKSlpWloaJiZmTFCU47evn27devW4qUYhvH29mbnqjc2Nr52\n7VpCQgKPx6vlYnx8/L59++zt7WnNmpqar169ys3NpdPb0xiePHnC5XLFt0qumSVyCNaCBQum\nTZvGMIydnd306dPpygMHDkjo/Fu3bjEMc/bsWUNDQ3bl6tWrnZycGIYxNTV98uQJu14keJHF\nyuqU3D/bt28fOHCghAibNIzYAQBAc5GSkuLj48Plck+cOCF5z8GDB7PzhhFCysvLf/vtt+Li\nYnZiMXt7+3379m3cuNHZ2bmySsRLCcvJyXFzc7O0tPzy5UstF21tbeXl5dmaW7VqlZ6enpGR\noaSkRMj/nWDNycmh44giWyXXzBI5BOvChQsjRowghCQlJe3du5eunDJlCiFEW1vb2dlZQ0Nj\n1qxZbdq0UVdXv3DhAiGke/fuhJCWLVvKyf3/JOTEiRO+vr6EEA6H06tXr1atWkVHR4sHL7LI\nEqlTcv9MnTr177//ruxda+qQ2AEAgOw7efKkpaVl586djYyMUlNTZ8+eLbKDk5OTlpZWmzZt\n6OIvv/xy8+ZNNrnx8/P79ddf1dTUBg4cSNfMmjUrKCjo0qVLEydOrOyg4qWEMf8+bkxBQSEz\nM7M2iyI1jx8/vnv37jY2Nj/88ANdY2Zm5ubmNmjQIPGt1apZXEZGhrOzc3FxMYfDIYQUFhbq\n6OgoKytnZmaWlpbu3LmTJnyPHz8+cODAhg0b2IK+vr7Lli2jr8vKylJTUydPnkwIuXXrVlZW\n1tKlS318fMSDF18UxtYpuRUqKioiaatMkd5gIQAAQAPx8vJSVVVdsGABPZcnQvxUbFpaWt++\nfceOHUtPxVKpqamKioqvX7+mOxgaGpqaml67do2eitXQ0CgqKmIY5vLly3SNSCnmv6di2VO3\n9EVtFhmG8ff3Z081KisrJyUlZWRkqKiolJeX05Xx8fFKSkriW79aM0v4ECwNDQ3apbRyisfj\npaWl0YnCGIbh8/kMw9y/f9/Kyoqu8fT07N27N7v/7t272RnVWMIBsMELL7548UJXV5d9g4Tr\nlNw/DMNoamoyMgojdgAAIPsuXboUFxf38uXLVq1aOTs7x8TEfLXInj17zp07R1/TM3etWrVS\nUFBg56QfOHDg+PHj2f1btWp15MgRQsj58+dtbGwqK8Xicrm3bt1KTExUVFSs5aIIOTk5AwMD\nLpcrEAgEAkF+fj4hRFtbu0WLFuJbJdecnJxcWFgooZd0dHTu3btHCDE3N583bx5dKRAIhPeh\ng3nk34G0VatWJSQk/Pnnn+wOBw8eHDNmDH2dnp5OCPnjjz+UlZUJISLBCy9aWFikp6fT/UXq\nlNw/hYWFtDbZJO3MEgAAoEHt3Lnz1KlTwmu0tbU1NTV5PB6Px8vJyaEDcgzD2NnZ0QEhQ0ND\nHo+noaHRv39/5t8hPVqWHbG7e/cuvanC0NCQ3i0hUor574jdpUuXtLS0uFyuv79/LRenTp2q\nqqoqLy9PI5kzZw6Xy9XU1PTx8WEYxsjIiIaxbt068a2SazY1Nf3999/FD8GaO3fu2LFjGYZ5\n//69hYUFn8+n9xSXlJSwI3b0xf379y0tLRmGUVBQUFdX5/F4dnZ2dAdlZWV2JFVfX5/L5Wpo\naJw+fVo8eJFFlkidkvtn27Zt7DsiezClGAAAANRQYWGhjY1NSkqKtAOphvbt21+4cMHMzEza\ngdQLJHYAAAAyrrCw0NvbOy8vjy7q6+uHhoayZ0hBliCxAwAAkHHv3r0zMjJa2Jtoq5HXmWTf\nX6SsrKzCx5dAU4cpxQAAAGQcnQR26rfEQpfcTiT7/pJ2QFBvcFeaerfrAAAgAElEQVQsAACA\njBO/JxdkFRK7WomPjx87dqyRkVHLli1bt27dt2/f8+fPs7d5m5qacv5r1qxZwptu3rzJVrV2\n7Vpra2t2MS4u7vvvvzcwMFBSUrKwsBg9evSTJ0/YrdHR0QMGDODxeC1btrS2tl6zZk1JSQm7\nlT2ukpJS69athwwZcvnyZeGwJQQGAACyhz71w/J/hDONdP+VtGjRAhfYySokdjUXHh7u5OT0\n6tWrX3/9NTIy8tChQ/369fvll19iY2PZfaZNm/ZYCPuUbUKIkpLS4sWLK7zG8erVq507d373\n7t2uXbvu3r27b98+Ho+3YMECuvWPP/7o1q2bsrLyhQsXHj16tGjRIj8/vz59+pSWlrI1zJw5\n8/nz59HR0fv37+fxeN7e3osWLRI+hITAAABAWJ8+fdzd3f38/Pz8/D58+NCnTx85ObmXL18S\nQjQ1NQkh/fv3d3R03Lp1q5ubW2FhYZ8+feTl5T98+EAIsbW1pc9j++abb/z8/GiF6urqIqX+\n+ecfPz+/CRMmGBgY+Pn5Xbly5ejRo4aGhsuWLePz+YSQ2izu2LFj6NChysrKDx48ePDgwb59\n+5YvX75v374WLVrQZ9Tl5eUpKys7ODgQQqZMmWJhYbFhwwZVVdX8/PxBgwZNmzZtzJgx2tra\nhBBfX9927dotXrzYwMBAuIt27NjRo0cPNTU1ka4rKytr3bo17UORTpOsZ8+eAQEBEmqW3OTt\n27fPmzfvhx9+UFVVJYScO3euV69eVX2/mzrpPm2l6SoqKjIwMOjTp49AIBDZVFZWRl+YmJis\nWrWqwuImJiazZs1SVlY+efIkXbNmzRr6SO7i4uIKa/748SM9rr6+vpeXl/Cmhw8fcjicbdu2\nVXbc3bt3E0Lu3bv31cAAAJq5PXv2zJkzR3iNp6fnggULhBfNzc09PDwYhtHQ0GAYxtDQMCws\nTHgHU1PTOXPmlJaWGhsb032cnJz27NlDd6DTIYiUYhgmKCiInYChU6dOBw4cYBjG1NT0zz//\nrM2i8EFZR48ebdOmDX09cuTIXr160YkZunXrtn37doZhjI2N7969y+6voqLCMIy+vv7jx4/p\ni6ioKJGuE5+sYufOnbSjxDuNYZh169YNHDiQ1vPo0aPhw4ePGDEiLS2tqKiIy+VaWlrOnDm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Yhs/nE0J0dXWzs7NFyn758iUxMVFCL3Xr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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "l <- millefyPlot(track_data=tdlist, track_type=tt, heights=heights,\n",
    "          sc_type = \"heatmap\",\n",
    "          chr = chr, start = start, end = end,\n",
    "          sc_avg = TRUE, sc_avg_height = 1,\n",
    "          title = text_main)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Replot ('all-cell' mode)\n",
    "When we set sc_sort_destiny = 'all', all single cells are reordered by diffusion maps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Begin millefyPlot: 2024-02-11 22:21:35.685461\"\n",
      "[1] \"title\" \"sc\"    \"avg\"   \"gene\"  \"axis\" \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in DiffusionMap(as.ExpressionSet(as.data.frame(mat))):\n",
      "“You have 990 genes. Consider passing e.g. n_pcs = 50 to speed up computation.”\n",
      "Warning message:\n",
      "“'as(<dsCMatrix>, \"dsTMatrix\")' is deprecated.\n",
      "Use 'as(., \"TsparseMatrix\")' instead.\n",
      "See help(\"Deprecated\") and help(\"Matrix-deprecated\").”\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigenvalue of DC1: 0.274219\n",
      "[1] \"Finished millefyPlot: 2024-02-11 22:21:36.910424\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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AEAABiCsAMAADAEYQcAAGAIwg4AAMAQhB0AAIAhCDsAAABDEHYAAACGIOwAAAAM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\nRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "millefy_adjust(sc_sort_destiny = 'all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Replot ('group-wise' mode)\n",
    "When we set sc_sort_destiny = 'group', all single cells in each group are reordered by diffusion maps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Begin millefyPlot: 2024-02-11 22:21:37.494289\"\n",
      "[1] \"title\" \"sc\"    \"avg\"   \"gene\"  \"axis\" \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in DiffusionMap(as.ExpressionSet(as.data.frame(mat))):\n",
      "“You have 990 genes. Consider passing e.g. n_pcs = 50 to speed up computation.”\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigenvalue of DC1: 0.274219\n",
      "[1] \"Finished millefyPlot: 2024-02-11 22:21:41.810153\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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vrc5/Sb38jp1I9+pPZ2FRSoq0vPP6+GBp11liIR7dwpn0+plFpb1dCg4cN1+uk9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\nV59qtfMAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "millefy_adjust(sc_sort_destiny = 'group')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Replot (Change scale of averaged single-cell read coverage track)\n",
    "Using `sc_avg_scale`, you can change the scale of the averaged single-cell read coverage tracks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Begin millefyPlot: 2024-02-11 22:21:42.387223\"\n",
      "[1] \"title\" \"sc\"    \"avg\"   \"gene\"  \"axis\" \n",
      "[1] \"Finished millefyPlot: 2024-02-11 22:21:42.906597\"\n"
     ]
    },
    {
     "data": {
      "image/png": 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fTxj+vnP5fTqe9+V+GwCgrU3a3f/U4NDbr4YkWjamyUz6d0Wu3tamjQ6NE6//ze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dvWHDhoqKClkHUhNcLnfr1q2ampqEkHXr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\nAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "millefy_adjust(sc_avg_scale = 7000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sessionInfo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "R version 4.3.2 (2023-10-31)\n",
       "Platform: x86_64-conda-linux-gnu (64-bit)\n",
       "Running under: Ubuntu 22.04.3 LTS\n",
       "\n",
       "Matrix products: default\n",
       "BLAS/LAPACK: /srv/conda/envs/notebook/lib/libopenblasp-r0.3.25.so;  LAPACK version 3.11.0\n",
       "\n",
       "locale:\n",
       " [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              \n",
       " [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    \n",
       " [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   \n",
       " [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 \n",
       " [9] LC_ADDRESS=C               LC_TELEPHONE=C            \n",
       "[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       \n",
       "\n",
       "time zone: /UTC\n",
       "tzcode source: system (glibc)\n",
       "\n",
       "attached base packages:\n",
       "[1] stats     graphics  grDevices utils     datasets  methods   base     \n",
       "\n",
       "other attached packages:\n",
       "[1] millefy_0.1.9\n",
       "\n",
       "loaded via a namespace (and not attached):\n",
       "  [1] bitops_1.0-7                rlang_1.1.2                \n",
       "  [3] magrittr_2.0.3              destiny_3.14.0             \n",
       "  [5] matrixStats_1.1.0           e1071_1.7-13               \n",
       "  [7] compiler_4.3.2              vctrs_0.6.4                \n",
       "  [9] stringr_1.5.1               pkgconfig_2.0.3            \n",
       " [11] crayon_1.5.2                fastmap_1.1.1              \n",
       " [13] XVector_0.40.0              utf8_1.2.4                 \n",
       " [15] Rsamtools_2.16.0            purrr_1.0.2                \n",
       " [17] zlibbioc_1.46.0             GenomeInfoDb_1.36.1        \n",
       " [19] jsonlite_1.8.7              DelayedArray_0.26.6        \n",
       " [21] smoother_1.1                uuid_1.1-1                 \n",
       " [23] BiocParallel_1.34.2         irlba_2.3.5.1              \n",
       " [25] parallel_4.3.2              R6_2.5.1                   \n",
       " [27] stringi_1.8.2               vcd_1.4-11                 \n",
       " [29] ranger_0.16.0               rtracklayer_1.60.0         \n",
       " [31] car_3.1-2                   boot_1.3-28.1              \n",
       " [33] lmtest_0.9-40               GenomicRanges_1.52.0       \n",
       " [35] Rcpp_1.0.11                 IRkernel_1.3.2             \n",
       " [37] SummarizedExperiment_1.30.2 zoo_1.8-12                 \n",
       " [39] base64enc_0.1-3             IRanges_2.34.1             \n",
       " [41] Matrix_1.6-4                nnet_7.3-19                \n",
       " [43] tidyselect_1.2.0            yaml_2.3.7                 \n",
       " [45] abind_1.4-5                 codetools_0.2-19           \n",
       " [47] curl_5.1.0                  lattice_0.22-5             \n",
       " [49] tibble_3.2.1                withr_2.5.2                \n",
       " [51] Biobase_2.60.0              evaluate_0.23              \n",
       " [53] proxy_0.4-27                xts_0.13.1                 \n",
       " [55] RcppEigen_0.3.3.9.4         Biostrings_2.68.1          \n",
       " [57] pillar_1.9.0                MatrixGenerics_1.12.2      \n",
       " [59] carData_3.0-5               VIM_6.2.2                  \n",
       " [61] stats4_4.3.2                generics_0.1.3             \n",
       " [63] TTR_0.24.4                  RcppHNSW_0.5.0             \n",
       " [65] sp_2.1-2                    RCurl_1.98-1.13            \n",
       " [67] IRdisplay_1.1               S4Vectors_0.38.1           \n",
       " [69] ggplot2_3.4.4               munsell_0.5.0              \n",
       " [71] scales_1.3.0                laeken_0.5.2               \n",
       " [73] class_7.3-22                glue_1.6.2                 \n",
       " [75] scatterplot3d_0.3-44        tools_4.3.2                \n",
       " [77] BiocIO_1.10.0               hexbin_1.28.3              \n",
       " [79] robustbase_0.99-1           data.table_1.14.8          \n",
       " [81] RSpectra_0.16-1             GenomicAlignments_1.36.0   \n",
       " [83] pbdZMQ_0.3-10               XML_3.99-0.16              \n",
       " [85] grid_4.3.2                  tidyr_1.3.0                \n",
       " [87] colorspace_2.1-0            SingleCellExperiment_1.22.0\n",
       " [89] GenomeInfoDbData_1.2.10     repr_1.1.6                 \n",
       " [91] restfulr_0.0.15             cli_3.6.1                  \n",
       " [93] knn.covertree_1.0           fansi_1.0.5                \n",
       " [95] ggthemes_5.0.0              S4Arrays_1.0.4             \n",
       " [97] dplyr_1.1.4                 pcaMethods_1.92.0          \n",
       " [99] gtable_0.3.4                DEoptimR_1.1-3             \n",
       "[101] digest_0.6.33               BiocGenerics_0.46.0        \n",
       "[103] ggplot.multistats_1.0.0     rjson_0.2.21               \n",
       "[105] htmltools_0.5.7             lifecycle_1.0.4            \n",
       "[107] MASS_7.3-60                "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sessionInfo()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "--------------------\n",
    "\n",
    "Above was the end of [the original notebook by the Millefy developer](https://nbviewer.org/github/yuifu/datascience-notebook-millefy/blob/master/examples/test_millefy.ipynb), \n",
    "I, Wayne, have included as part of the `millefy-binder` repository another notebook that does much the same but in two different ways, starting with BAM files. The idea being that should help anyone looking to use Millefy with BAM files.  \n",
    "The example BAM files used are in the developer provided `extdata` directory.\n",
    "  \n",
    "Click [here to open `test_millefy_with_included_bam_files.ipynb`](./test_millefy_with_included_bam_files.ipynb).  \n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
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   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
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  }
 },
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}

RECENT_RUNtest_millefy_with_included_bam_files.ipynb