{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7bc26663-300c-4b6c-a1c0-2a3945bc1b4b",
   "metadata": {},
   "source": [
    "## Tutorial A5: Annotations\n",
    "\n",
    "> TOMTOM/FIMO\n",
    "\n",
    "When we talk about using machine learning models to discover biological principles, in many settings the machine learning models are not the final product. Rather, discovering the building blocks that drive model predictions and the syntax of these building blocks can be far more informative for understanding the genome and also doing downstream design. These building blocks are called \"annotations\" and are a superset of seqlets, which are contiguous spans of high-attribution characters (although the precise definition might change across methods), FIMO hit calls, which are motif matches based on a PWM that only account for the sequence content and do not care about attributions, and Contribution-Weight Matrix (CWM)-based hits that account for both sequence content and attribution weight (contribution and attribution are mostly synonymous). Basically, an annotation here has the same meaning as it does when talking about genes/genomes -- it is a start position, an end position, and optionally a label as to what is happening there.\n",
    "\n",
    "Let's start off by loading the Beluga model, creating a synthetic sequence that has two AP-1 motifs in it and an ETV6 motif, and calculating attributions. After calculating attributions, we are done with the Beluga model!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f62dd3ab-55ae-45db-ae60-3c6d94ab2ca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA+kAAADtCAYAAADDRDT0AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAB5QUlEQVR4nO3dd1hT1xsH8G/YGxniQEFFwQEq7j3AXVv3qtVWrVZb9dfa1lGttY6ittparXXUumvdW+uqWsW9EXFPHGxkQ0ju74+TQSBBQBCE7+d5eJLce3NzkkNy73vOe86VSZIkgYiIiIiIiIgKnVFhF4CIiIiIiIiIBAbpREREREREREUEg3QiIiIiIiKiIoJBOhEREREREVERwSCdiIiIiIiIqIhgkE5ERERERERURDBIJyIiIiIiIioiGKQTERERERERFREM0omIiIiIiIiKCAbpREQl3LZt2+Dl5aX58/HxQfPmzTFo0CAsXboUUVFRhV1EHeryBgUFGdwmNDQUXl5eWLFihWbZ2bNndd5nxr+xY8di4sSJBtdn/Js4caLOax05cgQ1a9ZEdHQ0AOD58+eYNm0aOnbsiNq1a6NRo0Z49913MWXKFDx//lzzvIULF8LLy0vzvMy6du2KQYMG6V0XHR0Nb2/vbD+HzO/H29sbHTt2xK+//orU1FSDn11u3bhxAx988AHq168PLy8vrFq1yuC2hj5DtUWLFmm2CQ0Nzbcy5ob6/+Ts2bMF+jqDBg3KUr9eXl5YuHBhgbxeWFgYFi5ciJCQkCzr1P+LRERUNJgUdgGIiKhoCAgIQJUqVZCeno6oqChcvHgRy5cvx59//omff/4ZzZo1K+wi5otx48ahcePGOstKlSoFIyMj9O/fX7MsODgY06dPz7K9o6OjznMPHjyIBg0awNHRES9evECPHj1gZ2eHIUOGoHLlykhISMDdu3exf/9+PHnyBOXKlXvt97Br1y7I5XIAwJYtW+Dj46N3OwsLC6xevRoA8PLlS+zduxe//fYb7t+/j19++eW1ywEA33zzDZKTkzF//nzY29vD1dU12+2tra3xzz//YMqUKbCxsdEslyQJ27dvh42NDRISEvKlbHlRq1YtbNy4EVWrVn3jr71x40aULVu2QPYdHh6ORYsWwdXVFTVq1NBZ16dPH7Rs2bJAXpeIiHKPQToREQEAqlWrphPsdezYER999BHef/99jB49GgcPHoSzs3MhljB/uLu7o27dunrXubm5ae6re5uz214ul+Pff//F559/DgDYtGkTYmJisHnzZlSsWFGzXbt27TBy5Egolcp8eQ9bt26Fk5MTypcvj71792LSpEmwsLDIsp2RkZFO2Vu3bo2nT59i//79mDRpEsqUKfPaZblz5w769OmD1q1b52h7f39/HDx4EPv27UPfvn01y8+cOYPQ0FD07dsXmzZteu1yqSUnJ8PS0jLH29vY2Bis74JWWK9btmzZAmscICKi3GO6OxERGVS+fHlMmDABiYmJ+Pvvv3XWBQUFYeTIkWjUqBF8fHzQvXt37Nu3L8s+IiIiMHXqVLRq1Qre3t7w8/PDokWLkJ6ertlGnZ6+fPly/P7772jTpg18fHzQs2dPnD59usDfZ16dPn0a8fHxaNeuHQAgNjYWRkZGcHJy0ru9kdHrH3avXr2K27dvo1u3bujbty/i4+Nx4MCBHD+/Tp06AICnT59mu93t27cxatQoNGzYED4+PujWrRu2b9+uWa8edpCeno4NGzZo0tRfxdbWFu3atcPWrVt1lm/ZsgX16tVDpUqVsjwnMDAQo0aNQqtWreDj44P27dtj6tSpWYYKqNO2g4ODMXbsWDRs2BDt27cHAKSlpWH27Nlo3rw56tSpg4EDB+L69evw8/PTSb/Xl+4+ceJE+Pr64tGjRxg+fDh8fX3RunVrzJ49G2lpaTplWLRoEfr06YNGjRqhXr166NGjBzZv3gxJkl752WROd/fz8zM47EJdvkePHmHSpEno0KED6tSpg5YtW2LkyJG4deuWznvq3bs3AGDSpEmafahfS1+6u1KpxPLly9GpUyd4e3ujadOmGD9+PF68eKGz3aBBg9C1a1dcu3YN77//PurUqQN/f38sW7Ys3xqliIhKGvakExFRtlq3bg1jY2NcuHBBs+zMmTP4+OOPUadOHUybNg22trbYt28fvvjiC6SkpKBnz54ARIDep08fGBkZ4bPPPoObmxsuX76M33//HU+fPkVAQIDOa61fvx7ly5fHN998A6VSiT/++APDhw/H2rVr4evrmy/vR6lU6jQQAICJSd4OhwcPHkTdunU1PdJ169bF+vXrMWbMGHz00Ufw9fXVSenOaXmys2XLFgBAr169ULZsWfzwww/YsmULunXrlqPnP378GEDWtP2M7t+/j/79+8PJyQmTJ0+Gg4MDdu3ahYkTJyIyMhLDhw9HmzZtsHHjRvTr1w8dO3bE0KFDc/weevfujY8++gj37t2Dh4cH4uLicOjQIXz33XeIjY3VW2ZfX1/06dMHtra2ePr0KVauXIn3338fu3fvhqmpqc72Y8aMQZcuXdC/f38kJSUBEMHpvn378PHHH6NJkya4e/cuRo8enePUerlcjlGjRqF3794YOnQozp8/j8WLF8PGxgajR4/WbPf06VP069cP5cuXBwBcuXIFM2fORFhYmM52ObFo0SKdRgClUonvvvsOoaGhmv2Hh4ejVKlS+PLLL+Ho6IiXL19i+/bt6Nu3L7Zv344qVaqgVq1aCAgIwKRJkzBq1Ci0adMGALLtPZ82bRo2btyIDz74AG3atMHTp0+xYMECnDt3Dtu2bdP5/4mIiMDXX3+NIUOGYPTo0Th06BDmzZsHFxcXdO/ePVfvmYiIGKQTEdErWFlZwcHBAeHh4Zpl33//PapVq4bVq1drAtyWLVsiJiYG8+fPR/fu3WFkZISFCxdqxkKrg4qmTZvCwsICc+bMwbBhw3TG/ioUCqxcuRLm5uYAgBYtWsDf3x+//vorVq5cmS/v54svvsiy7ODBg3B3d8/VfhQKBQ4fPoxPPvlEs+zdd9/FhQsXsHnzZpw8eRIymQxVqlRBy5YtMWjQIFSoUCHLfpo3b27wNRo1aqTzODk5Gfv27UPdunU1n1unTp2wY8cOPH78WCddX03dABAXF4c9e/bg8OHD8PHx0dtjrbZo0SLI5XKsWbNGM4a+devWiIuLw2+//Yb+/fvD0dFRE6g5OzvnKlW7SZMmqFChArZs2YIJEyZg9+7dMDY2RqdOnbJkbADAgAEDNPclSYKvry8aNWqEtm3b4r///oO/v7/O9t27d8fYsWM1j+/evYs9e/Zg+PDh+PLLLwGIz93Z2Rnjxo3LUZnlcjnGjBmDzp07AxD/x9evX8eePXt0gu+MDU9KpRKNGjWCJElYs2YNPvvsM8hkshy9HgDUrFlT5/GMGTNw//59LF68WDOcomHDhmjYsKFmG4VCgdatW6Nr167YuHEjJk2aBBsbG1SrVg2AGNLxqrq6d+8eNm7ciPfffx/ffvutTnn69OmD1atX63yPYmNjsXz5ctSuXRsA0KxZM5w7dw67d+9mkE5ElAcM0omI6JUypuo+evQI9+/fx4QJEwBApxe4VatWOHr0KB48eAAPDw8cO3YMjRs3houLS5bt5syZg3PnzukE6R06dNAE6IAYH9y2bVvs2bMHCoUCxsbGr/1evvrqKzRp0kRnWV4mczt37hxiYmI06dQAIJPJMH36dHzyySc4fvw4rl+/jgsXLmDVqlXYuHEjli1bliXwXrVqld7edn3B4/79+5GQkIBevXpplvXq1Qvbt2/H1q1bszRAJCUloVatWjrla9WqFWbMmJHteztz5gyaNm2a5XPp0aMH/vvvP1y+fBmtWrXKdh/Zkclk6NGjBzZs2IAvv/wSW7duRefOnWFtba13+6ioKCxYsADHjx9HeHi4Thr1vXv3sgTpHTp00Hl87tw5ANAE2GodO3bMcRaFTCaDn5+fzjIvLy+cOXNGZ9np06exdOlSBAUFZemlj4qKyvO8DsuWLcO6deswc+ZMnfH/6enp+OOPP7Br1y48fvxYM6EgID6bvFCn0vfo0UNnee3ateHh4YHTp0/r/K+VLl1aE6CreXl56Z1JnoiIXo1BOhERZSspKQmxsbHw9PQEAERGRgIA5syZgzlz5uh9TkxMDAARlBw9elQnUNS3nZq+AMbZ2RlyuRxJSUmwtbXN8/tQq1ixosHZ0HPjwIEDqFWrlt7ecVdXV7z//vuax/v27cOXX36JuXPnatLV1by8vPSmnmdsrFDbsmULzM3N0bJlS8TFxWme7+rqiu3bt2Ps2LE6DRkWFhZYt24dAMDMzAyurq6vTL8HRM9o6dKlsyx3cXHRrH9dvXr1wm+//YYlS5YgODgYU6ZM0budUqnE0KFDER4ejk8//RSenp6wtLSEJEno27ev3svJqcuZ8f0AWf+/TExMUKpUqRyV19LSMkudmJmZ6bz+tWvXMGzYMDRq1AgzZsxA2bJlYWpqisOHD2PJkiVISUnJ0WtltnPnTsyfPx+fffYZ+vTpo7Nu9uzZWL9+PYYPH46GDRvC3t4eMpkMU6ZMyfOl9tSfV+bPUb3s2bNnOsv0fYaZPxsiIso5BulERJStY8eOQaFQaHqAHRwcAACffPKJTi9yRpUrV9Zs6+XlpZn9PLPMQYC6ASDzMlNTU1hZWeX1LeQ7pVKJw4cPG7yOeWZdunTBsmXLcOfOnTy/5oMHD3Dx4kUA0IwpzuzkyZM6vaxGRkZ5apAoVaoUIiIisixXD3lQ/w+8jnLlyqFZs2b47bffULlyZdSrV0/vdrdv38bNmzcxe/ZsnZ7dR48e5fi11EFkZGSkzoz26enp+dLgoLZ3716YmJhg6dKlOgH94cOH87zPwMBATJ48GT169NBJ4VfbtWsXunfvniXzIiYmBnZ2dnl6TfXnFR4enmXcenh4eL7UPxERGcYgnYiIDHr27Bnmzp0LW1tbzTXEq1SpgkqVKuHmzZuvHM/bpk0bHD9+HG5ubrC3t3/l6x08eBDjx4/XBDgJCQk4evQoGjRokC+p7vnl0qVLiIiIyJJWHR4errf3MTExEc+fP9e7LqfUPfAzZ87MMvY8JSUFn332GbZu3ZrjS6Flp2nTpjh06BDCwsJ0gtqdO3fC0tIy3y4VNmTIEJibm6NTp04Gt1GP4TYzM9NZrm/suiHqMdv79u3Tyeo4cOBAribtexWZTAZjY2OdWfxTUlKwa9euPO0vJCQEY8aMQePGjQ0OUZDJZFkmzjt27BjCwsJ05llQf3456c1XDwfZtWuXThr7tWvXcO/ePYwcOTLX74WIiHKOQToREQEQ17tWKBRIT09HdHQ0Lly4gG3btsHY2BiLFi3SScn+/vvvMXz4cAwbNgw9evRAmTJl8PLlS9y7dw/BwcH49ddfAQBjx47FqVOn0L9/fwwaNAiVK1dGWloaQkND8d9//+H777/X6akzNjbGkCFDMGTIEM0loBISEjBmzJgs5T1z5ozey4jlR5D6KgcOHICnp6cmY0BtyZIluHTpErp06YLq1avDwsICoaGhWLduHWJjYzF+/Pg8vV56ejp27twJDw+PLOnOam3btsW///6L6OjobGduz4nPPvsMR48exeDBg/HZZ5/B3t4eu3fvxrFjx/D111/ny7ADQEwM2KJFi2y3qVKlCtzc3DBv3jxIkgR7e3scPXoUgYGBOX6datWqoWvXrli5ciWMjY3RpEkT3LlzBytXroStrW2uJnPLTuvWrbFy5Up8+eWX6NevH2JjY7FixYosDQw5kZCQgOHDh8PCwgLDhg3D9evXddZXrVoVNjY2aNOmjWYWd/Xl51asWJGlB9zNzQ0WFhbYvXs3PDw8YGVlBRcXF51GGLUqVaqgX79+WLduHYyMjNCqVSvN7O7lypXDRx99lOv3Q0REOccgnYiIAIhLVAGAqakp7Ozs4OHhgeHDh6NPnz5Zgr4mTZpg8+bNWLJkCX744QfExcWhVKlS8PDw0Jmcy8XFBVu2bMHixYuxYsUKhIWFwdraGq6urmjZsmWWdNyBAwciNTUVM2fORFRUFKpVq4alS5eifv36Wcr7008/6X0fR44ced2P4pUOHTqkM3mbmvoyaHv37sWKFSsQHx8Pe3t71KpVC8uWLctzA8KxY8cQERGB4cOHG9ymb9++OHjwIHbu3IkhQ4bk6XXUqlSpgr///hvz58/H9OnTkZKSAg8PDwQEBGgur/emmJqaYsmSJZg1axamTp0KExMTNG3aFKtWrTKY9q9PQEAASpcujS1btmDVqlWoUaMGfvnlF3z88cd5TgvPrGnTpvjhhx+wfPlyjBw5EmXKlEHfvn3h6OiIyZMn52pfsbGxmiEH+upzzZo1aNy4MSZPngwTExMsW7YMSUlJqFmzJhYuXIgFCxbobG9paYkffvgBixYtwrBhwyCXyzF69Gi9DWCAuARbxYoVsWXLFvz111+wsbFBy5Yt8eWXXzLdnYiogMmkjFP2EhERFYLQ0FD4+/tj/PjxGDZsWGEXJ1vXrl1Dnz59sGvXLnh5eRV2ceg1XLp0CQMGDMBPP/2Ed999t7CLQ0REBIA96URERLlSu3Zt3Lp1q7CLQbkUGBiIy5cvw9vbG+bm5rh16xaWLVuGSpUqZZlbgIiIqDAxSCciIqJiz8bGBoGBgVizZg0SExPh4OCAVq1aYdy4cXovd0dERFRYmO5OREREREREVEQYvXoTIiIiIiIiInoTGKQTERERERERFREM0omIiIiIiIiKCAbpREREREREREVEiQ7SlUolrl27BqVSWdhFoTeA9V2ysL5LFtZ3ycM6L1lY3yUL67tkYX1nVaKDdEmSIJfLwQnuSwbWd8nC+i5ZWN8lD+u8ZGF9lyys75KF9Z1ViQ7SiYiIiIiIiIoSBulERERERERERQSDdCIiIiIiIqIigkE6ERERERERURHBIJ2IiIiIiIioiGCQTkRERERERFREMEgnIiIiIiIiKiIYpBMREREREREVEQzSiYiIiIiIiIoIBulERERERERERQSDdCIiIiIiIqIigkE6ERERERERURHBIJ2IiIiIiIioiGCQTkRERERERFREMEgnIiIiIiIiKiIYpBMREREREREVEQzSiYiIiIiIiIoIBulERERERERERQSDdCIiIiIiIqIigkE6ERERERERURHBIJ2IiIiIiIioiGCQTkRERERERFREFHqQvn79evj5+cHHxwc9e/bEhQsXDG578OBBDBkyBE2aNEG9evXQr18/nDhx4g2WloiIiIiIiKjgFGqQvm/fPgQEBGDUqFHYsWMH6tevj+HDh+PZs2d6tz9//jyaNWuGZcuWYdu2bWjcuDFGjRqFGzduvOGSExEREREREeW/Qg3SV65ciV69eqFPnz7w8PDA5MmTUbZsWWzYsEHv9pMnT8bw4cNRu3ZtVKpUCePGjYO7uzv+/fffN1xyIiIiIiIiovxnUlgvnJaWhuDgYIwYMUJnefPmzXH58uUc7UOpVCIxMRGlSpXK1WsrlUpIkgSFQgEAmlsq3ljfJQvru2RhfZc8rPOShfVdsrC+S5aSVN/GxsY52q7QgvSYmBgoFAo4OTnpLHd2dkZERESO9vHnn38iOTkZnTt3ztVrX79+HXK5XPM4KCgoV8+ntxvru2RhfZcsrO+Sh3VesrC+SxbWd8lSEuq7fv36Odqu0IJ0NZlMpvNYkqQsy/TZs2cPFi1ahMWLF2cJ9F/F29tb05MeFBQEHx+fHLdq0NuL9V2ysL5LFtZ3ycM6L1lY3yUL67tkYX1nVWhBuoODA4yNjREZGamzPCoqCs7Oztk+d9++fZg8eTIWLFiAZs2a5fq1jYx0h+IbGxvzH6IEYX2XLKzvkoX1XfKwzksW1nfJwvouWVjfWoU2cZyZmRlq1aqFwMBAneWnTp2Cr6+vweft2bMHEydOxLx589CmTZsCLiURERERERHRm1Oo6e5DhgzB+PHj4e3tDV9fX2zcuBHPnz9H//79AQDz5s1DWFgY5s6dC0AE6BMmTMA333yDOnXqaMauW1hYwNbWttDeBxEREREREVF+KNQgvUuXLoiJicHixYsRHh4OT09PLFu2DK6urgCAiIgIPH/+XLP9xo0bkZ6ejunTp2P69Oma5T169MDs2bPfePmJiIiIiIiI8lOhTxw3cOBADBw4UO+6zIH32rVr30SRiIiIiIiIiApFoY1JJyIiIiIiIiJdDNKJiIiIiIiIiggG6URERERERERFBIN0IiIiIiIioiKCQToRERERERFREcEgnYiIiIiIiKiIYJBOREREREREVEQwSCciIiIiIiIqIkxy+4TIyEjMmTMHp0+fRnR0NCRJ0lkfEhKSb4UjIiIiIiIiKklyHaRPnDgRz58/x6effgoXF5eCKBMRERERERFRiZTrIP3ixYv466+/UKNGjYIoDxEREREREVGJlesx6eXKlcuS4k5EREREREREry/XQfo333yDefPmITQ0tCDKQ0RERERERFRi5Trd/YsvvkBycjLat28PCwsLmJqa6qw/d+5cvhWOiIiIiIiIqCTJdZD+zTffFEQ5iIiIiIiIiEq8XAfpPXr0KIhyEBEREREREZV4uQ7SAUChUODw4cO4d+8eZDIZqlatCj8/PxgbG+d3+YiIiIiIiIhKjFwH6Y8ePcKIESMQFhaGypUrQ5IkLF26FGXLlsWyZcvg5uZWEOUkIiIiIiIiKvZyPbv7zJkzUbFiRRw7dgzbt2/Hjh07cPToUVSoUAEzZ84siDISERERERERlQi5DtLPnz+Pr7/+GqVKldIsc3BwwFdffYXz58/nZ9mIiIiIiIiISpRcB+lmZmZITEzMsjwxMTHL5diIiIiIiIiIKOdyHaS3adMGU6dOxdWrVyFJEiRJwpUrVzBt2jT4+fkVRBmJiIiIiIiISoRcTxw3ZcoUTJgwAf369YOJiXi6QqGAn58fJk+enO8FJCIiIiIiIiopch2k29nZ4ffff8fDhw9x//59SJKEqlWrwt3dvSDKR0RERERERFRi5Ok66QBQqVIlVKpUKR+LQkRERERERFSy5ShIDwgIwP/+9z9YWVkhICAg220nTZqULwUjIiIiIiIiKmlyFKTfuHED6enpmvtERERERERElP9yFKSvXbtW730iIiIiIiIiyj+5vgTbpEmTkJCQkGV5UlISU92JiIiIiIiIXkOug/QdO3YgNTU1y/KUlBTs3LkzXwpFREREREREVBLlOEhPSEhAfHw8JElCYmIiEhISNH8vX77Ef//9B0dHx4IsKxERERFRiZecDAwZAjx+XNglIaKCkONLsDVo0AAymQwymQwdO3bMsl4mk2HMmDH5WjgiIiIiItI1dy6wahUgSeKWiIqXHAfpa9asgSRJ+PDDD7Fw4ULY29tr1pmamqJ8+fIoU6ZMgRSSiIiIiIiE7dvF7datwJIlgIVF4ZaHiPJXjoP0Ro0aAQCOHDmC8uXLQyaTFVihiIiIiIgoq5cvgWvXxP2EBODECaB9+8ItExHlrxwH6WrPnj3Ds2fPDK5v2LDhaxWIiIiIiIj0O31apLmrnTnDIJ2ouMl1kD5o0KAsyzL2qoeEhLxeiYiIiIiISK+TJ3UfX7xYOOUgooKT6yD9/PnzOo/lcjlCQkKwYMECfPHFF/lWMCIiIiIi0hUcrPs4OblwykFEBSfXQbqtrW2WZc2bN4eZmRkCAgKwbdu2fCkYERERERHpeviwsEtARAUtx9dJfxVHR0c8ePAgv3ZHRERERESZMEgnKv5y3ZN+8+bNLMvCw8OxfPlyeHl55UuhiIiIiIhIV2ys+COi4i3XQXr37t0hk8kgZZxWEkDdunUxa9asfCsYERERERFpPXlS2CUgojch10H6kSNHdB4bGRnB0dER5ubm+VYoIiIiIiLSFRFR2CUgojch10G6q6trQZSDiIiIiIiywSCdqGTIdZAOAKdPn8aqVatw7949yGQyVKlSBR9++CGaNWuW3+UjIiIiIiLoBunu7sDjx4VXFiIqOLme3X3dunX4+OOPYW1tjcGDB2PQoEGwsbHBiBEjsG7duoIoIxERERFRiRcZqb2/ezcwalThlYWICk6ue9KXLl2KSZMm4YMPPtBZXq9ePfz+++9Zlr/K+vXrsWLFCkRERKBatWr45ptv0KBBA73bhoeHY86cObh+/ToePXqEQYMGYfLkybl9C0REREREbx11kO7gANSqBQwaBHz3XeGWiYjyX6570hMSEtCyZcssy5s3b47ExMRc7Wvfvn0ICAjAqFGjsGPHDtSvXx/Dhw/Hs2fP9G6flpYGBwcHjBo1CtWrV89t0YmIiIiI3lrx8eK2eXPAyAioXx+wssqwQdIz4NRAIJHTwBO9zXIdpPv5+eHQoUNZlh85cgRt27bN1b5WrlyJXr16oU+fPvDw8MDkyZNRtmxZbNiwQe/2FSpUwJQpU9C9e3fY2trmtuhERERERG+tpCRxW7++uDU11d4HAFweBzz6C7j42RsvGxHlnxylu69Zs0Zz38PDA0uWLMG5c+dQt25dAMDVq1dx6dIlDBkyJMcvnJaWhuDgYIwYMUJnefPmzXH58uUc7ycvlEolJEmCQqEAAM0tFW+s75KF9V2ysL5LHtZ5ycL6FpRKwNpaTBqn/ii8vVX3lXLg+THAyBp4fhR4eR+wcS/M4uYZ67tkKUn1bWxsnKPtZJIkSa/ayM/PL2c7k8myXEfdkLCwMLRq1QobNmxAvXr1NMuXLFmC7du348CBA9k+f9CgQahevXqexqRfu3YNcrk8188jIiIiIiIiyov6OqkvhuWoJ/3ff/99rcJkRyaT6TyWJCnLsvzm7e2t6UkPCgqCj49Pjls16O3F+i7i7O31L3/5Mk+7Y32XLKzvkod1XrKwvoV27YDz54FjxwBfX7EsPR0wMQEQ/AMQMke7set7QNO1hVHM18b6LllY31nl6Trp+cHBwQHGxsaIzHgtCQBRUVFwdnYu0Nc2MtIdim9sbMx/iBKE9V1EGZp48jXrivVdsrC+Sx7WeclS0us7OlocLu3ttYdHzcfx8jKgzHAsVcS/9jG0sJX0+i5pWN9aOQrSAwIC8L///Q9WVlYICAjIdttJkybl6IXNzMxQq1YtBAYGon379prlp06dgr+/f472QURERAUrLCEMMSkxqFyqMsxNzAu7OEQlWnKyuLWz07My/s4bLQsRFZwcBek3btxAenq65r4huU1THzJkCMaPHw9vb2/4+vpi48aNeP78Ofr37w8AmDdvHsLCwjB37lzNc0JCQgAAiYmJiI6ORkhICExNTVG1atVcvTYRERG92rRj07Dk4hJcGnEJvuV8C7s4RCWaenb3LEG6pAQS7r7x8hBRwchRkL527Vq9919Xly5dEBMTg8WLFyM8PByenp5YtmwZXF1dAQARERF4/vy5znO6d++uuR8cHIw9e/bA1dW1QMfNE1HJIEnA1q2Avz/g4FDYpSEqGhLliTq3RFR4kpPF+HMLi0wrUsIBRUqhlImI8l+uxqSnp6ejdu3a2LFjBzw9PfOlAAMHDsTAgQP1rps9e3aWZbdu3cqX1yWiEshQto/qIhdz5gCTJgEdOwL//PMGy0VUhCXJk3RuiajwJCWJXvQsh7OUF4VSHiIqGEav3kTLxMQE5cuXh1KpLKjyEBEVCqUSWLRI3D9wADh7tnDLQ1RUMEgnKhqUSiAlxcB49OQMQbppqTdVJCIqILkK0gFg1KhRmDdvHmJjYwugOEREhePECeDpU+3jDRsKryxERQmDdKKiIUWVzW5jo29lmPb+OzcAt/5vpExEVDByfQm2tWvX4tGjR2jZsiXKly8PKysrnfXbt2/Pt8IREb0p27bpPmZPOpGgGZOexjHpRIVJPWmcmZmelanh4tapEWBZDqj+BXB9xhsrGxHlr1wH6f7+/rmexZ2IqKi7dEn3sWqYOlGJx550oqJB3ZOu9zLS6QnitlwncevYALAs/0bKRUT5L9dB+pgxYwqiHERU0qmjYnUj4BuMkpVK4OrVN/ZyRG+VNxGk/37+dzyJe4If/H8osNcgetupp4Qy0Xf2nq7KdLGrIW5lRkDplm+kXESU/3I9Jt3f3x8xMTFZlsfFxcHf3z9fCkVE9CaFhgLx8YVdCqKiSZ3mXpBB+vJLyxFwMgBpirQCew2it506SNffk64K0q0raZc5Ny3oIhFRAcl1kP706VO9s7unpaUhLCxMzzOIiIq2hw8LuwRERZc6OC/I66QnpIlUXY57JzIsRz3p5qW1y2yqFHiZiKhg5Djd/ciRI5r7J06cgK2treaxUqnE6dOn4erqmr+lIyJ6Ax490t6vU4dBO5GaJEm5S3c3NGfNK4avqIP0hLQEOFg65KqMRCVFjnrSzTJ8fziHFNFbK8dB+meffaa5P3HiRN2dmJjA1dU1y3IiooL2x6U/cOHZBQT4B+T55D5jkL5zp5jZff78fCog0dsiPRG49Svg1gewrQoASFWkQoIIsAsy3T1jkE5E+uWoJ93U/o2Vh4gKTo6D9Js3bwIA/Pz8sGXLFjg6OhZYoYiIcmrXrV3YfXs3xjUd9+ogPePkdBl69sLHitsWLQB3d8DVFVi3roAKTFRUXfgMeLAauLsY6BIMmNpp0s8tTCwKLEiXJIlBOlEOZNuTrkgUAbqRvpVE9LbJ9Zj0sWPHwsbGJsvytLQ07NixIz/KRESUY3GpcTq3efHypbj18xO3JibAO+9o1wc+DsSxh8fyvH+iIi81Cnj0t7ifFArcXiTuqgJzJ0unAhuTnpyerOmtZ5BOZNgre9LNOFSEqLjIdZA+adIkxOuZBjkxMRGTJk3Kl0IREeVUfJr4PYpPzfv07HGq+L5GDe2ylhmuXPPB9g/Q7e9ued4/UZH3eCOgTNU+Dt0GIEOQbuVUYD3pGQNzBulEhqkTwIz0nb2nJzLVnagYyXWQLkkSZHomoggLC9OZTI6I6E1QB+fqYD0v1EF6xYraZRkD9rjUOMSnxkMpZb2yBVGxEHFS97HqUmgZe9IZpBMVLvXpt56LLIkg3cjsjZaHiApOjsekd+/eHTKZDDKZDB9++CFMMuTaKBQKhIaGomXGriciojcgP3vSnZ21y9QnQ5IkIS41DhIkJKYlwtacjZFUDEWd07tYneLuZOWEsMSCucwqg3SinFH3oKen61mpTAWMTN9oeYio4OQ4SG/Xrh0AICQkBC1atIC1tbVmnampKVxdXeHm5pb/JSQiykZ+9qSXLp11XUp6CtKV4owoLjWOQToVP4oUIOG+3lU6Y9IL6BrmDNKJDFuwAFizRlxxpFw5sUyh0LOhpARkOT6tJ6IiLsff5tGjRwMAXF1d0aVLF5ibmwMA4uPjsWvXLqxYsQI3b95ESEhIwZSUiCgThVKh6el7nYnj4uLEbLmlSulZl2G/calxcIVrnl+HqEhKeACoJm6DjQeQ/FSzSh2kO1s55yzdPeMVFDI+zu7lVYG5rZktg3SiDK5eBT7/XNzv0wf45x9xX29PuqQEjBikExUXuf429+jRAwBw+vRpbN26FYcOHUL58uXRoUMHzJo1K98LSERkSMYT+tdNd3dy0j8Zz8vUl3rvExUb6l50I1Og3Ukg8hQQNA0ANL3nb2JMehmbMgzSiTKYPl17PyIC2Cbmc9Tfk44MPen3VwPP9gAmNkCTlQVdTCIqALkK0l+8eIFt27Zh69atSE5ORufOnZGeno6FCxeiatWqBVVGIiIg7SXwbC9Qth1g4QJAN8U9r+nu6elAUpI2jTCzzD3pRMVOari4rdALsCwLVOgBhG4HIHrSjWXGsDO3Q5I8yeDksa8jIS0BMsjgbOXMIJ1IJTER2L1bd1l0tLh9ZU967DXgyRbAzLFAy0hEBSfHQfrw4cNx8eJFtGnTBt9++y1atmwJY2Nj/P333wVZPiIi4cIo4NEGwMoN6HQRMHfW9J7bm9vnuSc9SdU5aGpgvh0G6VTspcWKWxfV5K8yGeA+EIAI0i1NLWFlagUJElLSU2BpapmvLx+fGg8rUyvYmNm81twSREWWoYatbIaDnDgByOX6d8Mx6UTFX44vwRYYGIg+ffpg7NixaNOmDYyNjQuyXEREWmFHRYAOAEmPgesiB1B9Ql/Othzi0vIWQKtPdhikU7Enk+n/k8eK9TbVtNuW8QMggnQrUytYmVppHr8OuVyMq33yRLssIS0B1mbWsDa1Zk86kcqFC1mXqYN0vT3pUAIynpsTFRc5DtLXr1+PxMRE9OrVC3369MG6desQrc67ISIqSHd+130cGwRAOw69rE3ZPPekq4N0MwOXl41LjYMMMjhaOjJIp+JJ3ZNumWHMh7H4QiTKE2FlaqXpPX/dIP2bb4DOnQEfH+DWLbEsIS0BNmY2sDZjkE6kFiQOczA1BQICgPLlAfXVj/WPSTcCJL0riOgtlOMg3dfXFzNnzsTJkyfRr18/7N27F61atYJSqURgYCASEnhgJaICICmBsMN6V6mD5rI2ZfOcJpuTnnQbMxvYmdsxSKfiSa6aENEy68QMSfIkWJpY5ktP+vHjwLx54v7Ll8AXX4j7CWkJsDZlTzpRRupGrGHDgIkTgZUrtceptDQ9T5AZAZLeLnaNtDQgNTV/y0lEBSPHQbqapaUlevfujQ0bNmDXrl0YMmQIli9fjmbNmmHkyJEFUUYiKskS7gNpMXpXqQPzstav35OeXZBua24LWzNbBulUPKXFipndzRyyrFKnu1uaiJ509SUP82L+fN0huHfuiFumu9PbSCkpEZ0cXWD/s+Gq+Rw/+kjctm8P1K4t7uvtF5MZAUrDQfqNG0CZMqJHPjAwX4tKRAUg10F6RlWqVMH48eNx/PhxzJ8/P7/KRESkpUptB2RAs7+Bir01q9QTTtlb2Oe5J12pFLcmBubbiUuNg62ZLWzNGaRTMSWPBUztxUl+JonyRM3EcUDee9KTk4EDB/SvS5CretKZ7k5vkbvRd+E01wmDtw/Osi4lBdiwQf+4ch0G5omQJCAyUlwW1NdXu2mPHoCFhbhsaFaGe9ITE4HevYHYWDFDfL9+2klTiahoeq0gXc3Y2Bjt2rXDkiVL8mN3RERaiQ/EbeXBgHs/oMkqwNIVgOhJtzGzgY2ZjcEAetYs4MULw7tXT8SjDtYzY086FXvpCYCRud5Vmp701xyTfvmyNs3WwkJ3smv1mHQbMxsG6fTWiEyK1LlVkyTgk0+A998HGjUCtm9XLcyYRpL5cSbx8WKSRVdX3flSbGwAKysRpGd5ejY96WvXAiEh2sdPnwJhYTl5l7n0eDNwqAVwa0G274+IXi1fgnQiogKTEiFuK3QXtybWgOdoAKInXX1ynzndfedOcTt3LtCypaGeB0B9oQq9Y/zAnnQqRgwFCkoFYKR/5sT8mt394kVxa2oKXLkCnDqlHWLCdHd6G0UkimNTRFKEzvLVq4E1a8R9SQLGjcvDvlW7dHPLus7SUszunpKSaYXM2GBP+ubNuS9DrsVcA858CEQGApc+B+6y447odTBIJ6KiLU3VS2FXU7vMqTGADAG0mS3kSjlS00VXXVSU6MlQu3tX1ZuhhzpIz3w9WrW41DjYmdvBzowTx1ExJaVrg/Swo8D5T8WfIkUzcZxmTHqa7pj0X34RabT//Zf9Szx8KG4//BDw8gKaNAFGjBDLNBPHmVkjOT0ZCiVnqKaiTx2cq4N1tUWLdLdLzMM0DpGqw17FilnXWYn2sqwNz8bm2iDd53ugylAA4th2+rRYbGcHeHjkvjw5cm0SoEjWPn66u4BeiKhkYJBOREWbuifdOkOXgipXNmO6u/oxAPz1lxgDm5GhdPacBOm25uxJp2JMytCTHhsE3P1d/CnTkZhm+BJsP/0kZmjfulVManXpkuGXUA858fPTLhsyRNxmnN0deL3J6YjeFHWae3RytKZh6flzbdbIa+1bFaTb22ddZym+inqCdCtAoRpTYmoDGIsNg4O1x8PNm0Xae9u2r19GHWkvgecH83mnRCUbg3QiKtpSIwGLsoCxRZZVmYN0dRD9zz/abfT1RGSUoyDdjGPSqRiTFICR/pkT1T3pJkYmMDUy1QTpjx8DEyZot0tLA44eNfwS6iDdy0u7TB2AZLxOuvoxUVGn7kGXICE6ORoAcPKkdv369aLB2NCVQ8STJd1hKKr76lR2i6yHPU1P+suX2mVyOcRQMHnWY9Tjx+K2USOgQwdRnl9+efX7y5Wos9pe/PJdAHOXfH4BopLHwHzGRERFRGokYOaod1V8ajzszO20Pemp8ZAkMd5VLSgI+O47w7tXnwS9MkhnTzoVVzIjEajrkSRPwr2Ye1h3bR2MjYw1vdxr1xrOTtHn+XNxqy/VNuOYdPVjoqIuIikCTpZOiEqOQkRSBEpbl9Zc27xXLzFxHJD9xKWGpKvi3eyC9MgM89XdvQvUMLEGEh9m2f7ZM3HbrJl2We3aufv+ZhYaCuzfDzRsCNStCyDmslhRoSfQYou4dOq1KXl/ASJiTzoRFXGKZL296IDoSVenoqsfx8aKy8yYqyarlsmAadMMj8MzNxez52ZOj1fLPLu7xBlrqbiRmQBK/TMnJsmTsP/ufgzaPggp6SmannT15dTc3IA//9Rev9mQFy8AW9us6buSJOmMSQcYpNPbITIpEp5Onpr7APDkiVjXpYt2u4zzo+SUutHYXM9FF9Tp7qGh2mU3bgAwtgbkLwFJN/pWB+kZs1gAcXm3vLhxA2jcWMwpUb8+sG4dgOSnYqXnaHHQtfUAak7Idj9ElD0G6URUtEnpYkIcAHh+CLgyEbg6GYAIoG1MbXR60tUnSXXqaHdhaipmeDfEzk70SuiLvzP2pCskBZLTDUTzRG8rmbHBID3z+PAkeRIkSczQDohZrIcMEUNM9I2fVXv5ErC2zro8TZGGdGU6e9LprRORFAEvZxH5qlPf1YFzrVra7dQ937mhUCW26EuVV+9PfawDxLhzmFiLAD1d9/ujDtI9PXNfjsyUSqBPH+0+lUpg1SoAyaoFDnW1G2e8T0S5xiCdiIo2ZTpgpOpJjzwJhMwBbv4EQPcSbIDoSVefuGTuNch4XebM7OzE5WySMl1dKjU9FamKVE1POgCmvFPxY2QCKLOO95AkKcsl15LkSYiJEddxLlMGaNVKLC9XDhg4UP/uFQpxMq/uAcxIHZBvubEF80/P11lGVJRFJEbAzc4N5sbmmpne1UF69eqvt28T1WBUfZcGVX+P1BPUpaWpJm00UUXvabE626uvh+6of9RYrhw7puq1zyz5mRiHbuZg+MnSa+TXE5VADNKJqIiTxJhZPeLT4qGQFJrAOS41TjNJTpUqOX8FOztxG6F7JR3NbPHqnnT1axAVK8aW2p70Kh8BNUSaakp65gsxi571R4/E/Tp1dBu/9AXhgDZ1N7sgff/d/fjzyp86y+j1SZIYjtCoEdCzJzRjpun1RSZFwsnKCU5WTpp09+fPRe93dlklOaHuQU9NzbrOVhyKEBgoGr8uXFAN1zJRpaqk6h7I1PvIS49+ZrtVV1WrVg149AjYtUu13+RngJWr/icpFcClL4GN5sCuKsCzfa9fEKISgBPHEVHRZmQCKLOeqUiShPjUePx46kf8eOpHAKJnPVU14636RCYnMgbplSppl6sD8nsx9zQnYQzSqdgxLaUayyoBpnaaiRr1XQotSZ6kueZ5jRo52716GIn6SgoZ6QvIGaTnn2nTgOnTxf3z50VaNAP115csT0aiPBFOlk5wsnTSpLunpuZPMKzuSU/J2k4GZ2dxGxsrJkZds0a1wlgVpCc+BBzra7bPrpEst65fF7c//ijmo3BzA9zdAdxNBKwMXEolaCpwa76qbA+As0OBHnmYTY+ohGGQTkRFm8xEe+3XDFLSU6DINCN1fFo8oOoQzM0JiTpIzzgL74sXQBxEQD7pyCTNcgbpVOyY2gOKFCA9XgTpKknyrPMvJMmTEKlqCHPIJrNVZ/eqXkF9kzO+TpCeqGpDUCr1NwCUdE+fAj/8oLss85Aeyht1eru6J139OC0t59+L7KgDfX1BeunS2vtduojx4R06QNuTHqfbCpPd+PbcunNH3LZpo11WuzaA23JxnXYACA4A7i0DTGyBDmeA2wvEcouyYiLYnEy+mp4I3PodQFsg5grgXP9Vz8g3qanA/Pli3o0WLcTEf2Zmb+zliTSY7k5EBSc1Crj5C3D7NyD5ed72YWQqAggAsK8F2IrB5vqC5fjU+Dz1GqiD9Iw9TCdO6H+NnATp4eHAV18BAwYAq1e/3qVuiPLsZTDw4ojeayfrMCslblPCdBZnHo+uXqYeJ2tjk7NiqAPo/ArSJQlYvFg7EVa9eqoxuaRj0yZxKS8vL3Gt7Pv3AV/fwi5V4XsW/wx3o+9C+RpjpNWZVc5WznC2ctY8zq8GI3VveXR01nUZg3T1BG4AABPVF/LFIZ3t1cG5voA/W5IEhB0Dnu4G0l4iJUX8H1WtqiedX0oHjFSRbFqM6M1PegyE/ycC7tItgHfvAd2eAOU7Z/+6qVHAP/WB69PE4yNtgPATuSx83iQkiJnrv/lGfH/GjgVmzHgjL02UBXvSiQyRlEDoTpGe5dQYcG6W/exjpCvmCnC0I5AaLh5fnQh0vQ1YlgOSw0TrelosUK4j4Pqe4c/WzFFcKx0A3PoC0ZeAWz9rxotnFJcaBxvVr5q+sXyGqIP0s2e1yw4cALrXyX2QHhwsWt9jY8Xjv/8Wl7oZNCjn5SF6LUoFcOFT0ZsFiN7xVrsAl9b6t88YpNtW0yxO0nMlg8S0RE1DmL5rOOsjk4lGs/wK0jduBD77TDtb/IMHwOHDIlgnLXXDxbRpQEVVJvLatYVWnCKj07pOCAoPwp0xd1DVsWqe9qFOb1enu9+NvgtA9LjmR7aCOkjPOIO7WsYgXYeFakXESREox1wBoA3Sc1UueTxwspc24De1R2T1U5CkmvpfX6Z/WBriQsRt9S+1E9s1XJb9awfPAuJvAcalVAsk7TlAAfvpJ+DqVfGb1aSJOJ4nZh31Q/RGsCedCKLBWKeVOT0Z+NcfONkTuPwlcLgFcPvXQivfW+nCpyJAt64kGjnSE0SL+ssQYG914EYAcPd34ER3IHS74f2YlxaT0mTq9YhPzRqkx6fFa9LScnNCop71du9eMWv15cti7J3BnnSZTP8fgDFjRIDu7g6MHCnGuOuboZeKgNgg4MnWLOmhb717S1UBukzMuCyPE73qhpiqusUS7ussTkzTPyY9Lz1zZcqI70Xm70JegvSZM8XtgAHiduLEvF/zuTi7dk3ctmunXfa6E5q97eQKOW5G3gQABIUF5Xk/OunuGcak53eQrp4INSPDQXpZcSulA7s9gMhAANrGrFwFm9e/FwG6kTlg7Q7IXyIlRmTD6Z3vxchMpLJnpg7SS7fQLjN+Re74440idb7dcfG42d/aAL+ArV8vbjduBE6dAu7e1dP4x1nq6Q3hYY1KNKUS+PlnwNVV9PRUqyZ6UHF7ARB+TEyEUu0zwN77jbXk5reY5Bjcjb6r94S7wCSFApGnRXDe5YYYl9bmoJhF+uoEQB4LlOsM1JkjJrgxcI1mAIC5s1ifKRVXX096fFq85gQiNyckbm7iNjlZnPAPHy4e5zbdPTISOHpUBP2XLgG//y4m9qn/5obTUU4o04HTg4H9tYGTvUWjUfCswi5V/rn/p+jZ8j8K9AwD/P/TnsDrY1pK3Ead11ms7kn/490/cPCDg+hVoxeS5EmahrCEXMzvVq6c+L1VzwyvltsgPTJS9G5VqAAsWiSWTZoEjBiR87K8NkkCoi+Lz0uR2xziN+fePaBUKW3AR8CtqFuQK+UwMTJBUHjeg3R1envn9Z2xLmgdIpMiIUkSnJxE41VuMrn0sbYWmSrPn+sG/ZGR2qyILDJ+x9NiNHfLlxe3Oqnx2ZEk4MFqcTm1zteA9x4CbQ9DaSJaeEz05eCa2opGeADw/Ayo2FvcTwoVAby5s9ivpFT9GRiXnhwmGuUr9BDD2wCRHl+2Qw4Ln3cxMSIor1IF6K0qfunSwAcfqDa4vxLY6Q78bQLsrwuEHS3wMlHJxiCdSrTZs4Fx40QPT8uWohf1yBEAT7aJltyOF4AGi4BOV0Sq9Vto/KHxqLawGlZeWfnmXjT6grj1+BgwUQ0OL9cesHARrfMOvkDrPUDN8UD7M0Dplob3Za46w8zUy6e3Jz01HhUqiPv6eiAMcXfX3l+8WHv9WYNBuiTpnmSoHp85Ix727KntnbexAerWzXlZKH9t2wb4+YmGmDZtVI1wd5cCD9cCtp5AzW+A8l2BxFz8wxQGSRI94q8KChUpQMxVMYxEnd7u0hKo2NPwc9TfsUcbxPOV4jXUY9L9q/ijvUd7eDl5IUmepAn6YmL07Uy/sqr44e5d7TKlUgTkMsjQt1Zf9K3VF85WztkG6efOidt33tENFtRDVgrcyxvAP3WBA/WAg42A7eXEsiJGkkRwV6pUYZekaAkKC4KRzAhtKrXJEqQnJIjfizVrDFwLPAN1z/mpJ6fw+OVjpCpSkZCWoAmgM/6f54VMpm1cUf/PKxTAli0iG0Lv5HQWZfTuy1V1ZTS9s/qnRAAXxwI73YDdVYHzo4C4m6JTwn0AYKea+KGsPyxcGwAQ50lZX7sckKTKzbd2F8PaAPF7os7UebIZ+NtY/CXc0//GX6qmjy/dTHf5GxhqeOWKuG3RQs/LPd4sZqVPjRCdD4kPgecHC7xM+SqbDEAqmjgmnUoshQKYN0+kp509C/j4iNbvoCspwMMrQPl3RVAJAEbGQCmfQi1vXp18clLcPj6J0Y1Gv/oJynQx2UtKGGBTBXBsIN6/JAFRZ4H4O6LFvnQLbQCemfqktVRd0WqeruoKeBksDtoVemqvfW5kYvj6qoA2gAj/DyjdXLNYHUD/0vEX2Jnb4Y/LfyA+LV7TKx4S8uq3qpbxsmsZxaXGwcTIBLXL1AYABIcHZ9uTrn5NHwP/KrGxwM6dQGioCBq7ds2fmYBJv8WLxdhlOzvRCPf4sZgjoOMHW0RWR7sT2u94Xic2zAtlOhB2RPQyWbuLRipjc8PbvzgMXBkPxFwW35vSrQC/I9rvUEZxN0W6q1PjnJfHprK4TYsCTvYBokRrk3p2dytTK81tojxR833JzXesnOqc/fx5oLNq3qiDB4F4i3jYmttiY++NAICO6zqKLBkDJ4+hS0XjmPp7/kZJEhDYXwQSnmMBOy8xb0lBZFlJkpht38gMMM7h4H8DuyGt6+HXUblUZdQrWw+7bu/SLN+wQczinTEA/ecfoGNH/ftRp7tnXlahgkjlCgkBaqk6giUpb7FQ2bLiWPH776KBccMGbeNzpUp6Gsksy4r09Exjw9U96RkbHuRyIDlJAbszXUSjunNTwMwJeLBG+9vh2FBnP+oGH/V8K7qvXV6k16dGA+aO2uUyIyDTVViypc4AMM+Q03/2Y6B8e6DS++Lc4sFaMZTOpipQ6QPA2lBqQe6oP0+9wwluLxKfbccLgH1NQJ4AvMx7JkZBkySRxXfokGgMbdwYaFXYhaJcK7lBesRJIPgnwPZbYGclwKkO0Hyz4aCDip2LF8XMqT17aoMqc3OgQa0XwH25CFAB4OF60WpqXQmoNLCwipsnEYkRuBl5E63cW+HE4xOQJAky1dlCSEQItt/cjkaujdCuimrQYmwQcLyrmJXVxFacJNaaAnj9DzjWWRzMTWzE2LOy7YE2+/W/sEIVlJuVEqlrO1UHUa/Pxa216gz72hQxQY1LK6BiL/37slQF8LcXAJ6jNcGUOt3943ofw9rMGuefnceh+4c0PRnq8ZiAOGBdvWq4R7tyZdErl56uuzwuNQ4V7Crg4gjRtd5gWYNsg3R1WqK+3qtdu8QY2tRUMTvuixdizNvvvxvc3Vtn4dmFWH11Nf7X+H8YVKdwZ8pTKoFZs0Qj3LlzYoZrSQLu31MAF08DZdtpA3RA2/NT0OJuAcc6AomPRANUWozIOGm4BAqlAm6/uCEyKRL3x96Hq52r6OH/711xAl1/oQjaHm1Qnfnr2b9cFWWYO4nbg43Fa7r1BRoZmLDJurL2/rM9mrvq66Srg3RLU0skyZPg5iYBkOHqVd0AJCnJ8DWi1YHCypXiygdKpbjWsu+EBFibWmu2szGzQXhiuMGPTz2mPT+uRZ1rcTfFiXm10UB91WWlqo7KfrhOXjzZLq4tre5VdKgHtA80HKzriQBlAGxspVxlO7y2vEajb1BQeBBqlq6JmqVrYt7peUhJT0FspAU++kikmO/aJcYgnzihHb9/6xawf7821bxbN226e0aRSZGoUEGcN5w8qU2Z3r9fXCott2rUAC5cELOM29iI2zFjxLpKlcTcKTpkRuK8JU639Uz93Tt4UBx/zM2Bv/4C2vuegV30BfH/3GCh2Cj5OfD8H3HfTBVsb3MB0uNhV/1LlC49E7duie+hzmXJLFUvEnNJ/LaqmdgA8pfif8O6kmjcjziZzbtWat+L2pPNgKWz+O071U+Uy8FXZOWlJwB1MgxVyun/YFqsaJCI+E8MDXKoByn9fwD0NJYqUkTDZfl3RIAOAKY2omEDEFl+j/4WkwybuwCu7wLOTV5dhgKSng68/z6webM4F3FxEcP4rl2XNA1HkMmytOClK9ORkJYAc2NzWJoyFioKSmaQnvgIONoesKkJ2EKcuITtVx1o+Y9ZUjx8KG6rVcu0Qt3qa6SaHen+StHrVcbvrQvSTz05BQAY22gsem/ujUcvH6FSqUoAgN/O/4bfzv+GeuXqaYJQXPhMBA0dzgNODcQBO/GhGK8bfQFovhGo2EeMPYs6Z/iFjVQHuvRE1YmlDEDGFHHVAfjeH6qx5pLhIL2Ut7hNCQO2lxUNAEZmiE+NhwwyTQBha2aL+NR4ODuLE/iMPSJ//CGCcENBurk5ULOmbmAPiCDd1kw7S46tuW22Qbr6sm8vX+oul8vFmFmZTKTUeXuLZXrTD99iyy8tR0hkCFZeWVnoQXpQkBiD+e67IkAHxOfv4ZYAnE/VnlRe+gJ4ukekdbbea3B/crmYWPDGDTHfQbVq4iQ8p5ch07jyNZD8QgzzcG4MpL0E4kQX1+nQ03gW/wxWplbYdWsXRjUcBTzeJE4Sm64FyrQV+/AYrtnd/jv7sef2Hrzn9R46Vu2o/d1Sz8wujxcnyepsFn3M7EWqbJZLsIl9WKoarzXBum0KbG0tERYG/Pcf0Lq1+Kz37QM+/lj/S9QWySh4+FA0jIaHi+9otbQE2JhpP0RrU2uR7q7+rVCfcKse264WD/Vdmio/xceLSaSuXxf3q1YF/vfuWdgBQLkOojzhqomtbKpoGx5fV9xNILAP4NQI8D8uhl0925v9ZFUGPiuvhiLIe/pUm/KskZ4IPNsvGmSNLUXvqWM20+O/DAaCpgHR58Vzbb2Axn8ARhZinpEXR0QmhlVFoN4v2Q+vKERB4UHoV6sfapSuAYWkQEhECAK3+iItDfjuO/F7AQD9+4vbyZPFtea9vERvZGCg+F+PqKSnJz0xApVV7V0rVojLd5mbizkT8hKke3tr7//5Z9Z12zPMt6pptLKtphukm1hpLlX4/DkwYQLw3nuioez2NtWY6ipDxRUh0uPE8dpIdSBTN7YrUlTDYNJRtSpw+rSYc6WJKg6NigKcrFTjzG79ApTxF9lCAGDjIc6pEh+K/2mP4ZogXZJEQ/XVq+KYWakS8F5DO1gDokdeTabK5Ls2RTTad74qxstLSiDpqfhtuz4deLRePDZzAKp+AtT5Qf8Hm54EHGwCJD8FqgwTv3/PdsPBejCAsojM3P6SEibiAxsP8fj6DDFzvn1N8V6PdRQZUeU6i+/TzXlAi836Xzs7klIci6LPi99tm8qAW3/AUv8wBkO2bBEBeo8eIvvC3FzMBaJ3wr8MFp5diHEHx+E9r/ews//O3Jef8l3JHJP+8C/xg9PgN/G4XAeg/q/ii0rFV2KouI0IBBIfw9REnMhkmaFYnV6d/ELcVv9S++P8ljnx+ASqOVZDx6odYSQzwolH4lqjCqUCW25sQc8aPXHp+SVx+Zi0GCDiBODWRwTocbe1B7ynu4FSdURvXPJTEVSYan/x99/Zjz8v/4noZNWBVd0zl3APsKoAdL0jHqvHpiWrZrBptFycIGbHroZo6Qa0Jw0QPek2ZjaazAAbMxvEp8VDJhMnU2rduok0xlepUyfrsrjUONiZawe72pnbZRukV68uboMzTaR95gwQFiYOmuoTL1NT3ZOwt93d6LsICg/C540/x3+P/tPb01Sgkp6K27DjQPxdREeJ73eZzOc36t7IdNW4Z5mpOAnLZkz6s2eiV2vIECAuTvRMnDwJ3LkDcbJ2fiRwxA841AI49QGQZGCGJmW66KUq30UE6PF3xHdJ9R3YcXMHapWuhfe83sOOWzvEc2JVLUdOTcT250YA5z8BEsSg12+PfouVV1biu2Pfie2sVMFi4gNx2/60OIF8FccGWRYlyZNgZmwGYyNx4Wd1kJ6cnqRp8Bo8WAQknTplbZzKqGGGzNkDB7S9gAlpCbA20/aka4J0A9TfGfW8EQXh6VNxDfZvvxXzVXTuLHogYyJVBwv19aj/bSv+Hv2Vfy/+aIMIahouBZybA3bVxTFIfQ3qXFBniB04oF32/DnEZSx3VRIzeKuvaX1jtuEdpb0EDjUXv+fNNwGdLgM1JwIwAv57TwRdrXcDfRKAVnu0/4NFTHxqPB7GPsSRB0cwJ3AOABG031EdnjIPU7pzBwgIEMeT69eB1avFxKDffCMC8mG+w5A6JRVhX4nGrYikCDRVd64mAA0aiGPC8zyOpMl4HMusRQvdxw3UX1/7TAeV0i1RsaK2N33BAsDfX2QFGClUaRYWpYHE+8BWR/Gn/u1IUN12f6Zp/FM3eP7wgxgyGBYmGiHgoGrgebYXONRUTF4JiP9fAAj7V6dYSUkytG4NtG2rvVTgoUPAmRBVT3XMJe3GMlPxex1/S0woZ+YAvPhX9F7H3wKuTgJu/gjUmQ30jgU6XTJ8uUlAXNEj/pY4/6j/C+DzPdDuBOo0FgeLwMBMnczq8w91xkzMJeDpDjEEL3iGyDrseEFk1zRdK2ajB0RK/NPdYg6Ue3+KyXQNkSTgWCfg9EAAkpg0L/FhnlLq1Y0348eLAB0Qv2PqeXIMWRe0DjWca2DfnX1v/vhNehV6kL5+/Xr4+fnBx8cHPXv2xIULF7Ld/ty5c+jZsyd8fHzg7++PDRs25P5Fk1XBmjqQ2OooZmt8ti/3+0qNEge3wP7A6UFixuB74sdJLhc/PgcOiB6Gy5fFjxoSH4ttggOA4B+A+6sBBa/RBEkJKOX5v9+UcOBwa+C/ruJx5Cng6iT41hQ/QurJvjTM7EUvwYuD4qS6fGfNrKn374vLajVoIHqD+vbVtrgXNEkSJworVgBz5ohU0S1bkO1kICcfn4RSUmLG8RmwMbPByceiBfvE4xMISwxDgH8AyliXwebgzdqZWU1VQenlL4GDDYFzw8UBUh2U3/tDHISPiBFOj2Ifodvf3TDh8AT8GPij2MZRNZ3540ytydYVxcH+marH0vXdV598mljpTR2LT43X6YGzMbNBkjwJCqUC7dtrtzt2LGfjMjt10n3s7q7qSTfP0JNuln1PurpnYds2bcCSnKwdu2v5ivaIwqKeZEpzeSxJKXrGgn8ALn8NXJsqxt5mY3vIdjhaOmJKqykwMTLB7lu7C77ggAggjnUW2VEAEHMRCP4BrqXECeb9+5m2NzYX3++os+KN+84Fyvpn+xLz54uZsn//XUw2+b//iewM3yo3gAMNxYRuTVYDbf4BPMdoe7MzU8rFn4nqfyp4lgh+Tg2EJEnYcXMHulTrgi5Vu+Dog6N4mfJS24ilSBYnibHXgHvLgeQXuPz8Mi4+v4iFnRfi7NOz4pJSVuVF6v7T3eK4YmYveqJexSnTd8zKDYkKuSYwB7Q96onyRM1Y3cePRe950CvOJcuWBXx9sy5PSNNNd7c2yz5Ir11bzHp9+LCoE0D0dB8/nv3r58aiRWI4yi+/AF9/LX7jZ84E3GuqGjviVbOCtTlgcB8a6cnAww3AlQnAuU+Ay18Bz/4xvL06m8HSFYi9CmyxFX9hR3L9PtQNI99+K3o/jx8H+vWDCCwUKUD7U6IBoMpQoPYMbe9nZs/2iGyMWt+K3tCnu0WPYcwVEURUGSpSf59sB14c0E4gVsRcDxfDBy48u4BtIdsAiInk1POCRGTqHD+r+ono0EF3kkJzc5Ha7mLtAjNjMzhbOcNYZozIpEjUqKENiGNicncFhMyaNtVePi2zJk10LzuoPvagTKbfsjLtIJOJ95BZuqmqoImPRSaNz3Tx2Npd/IaFbhUfgKkN1GNr1MfW3btFw3b16qrfWKdG2mN51FntuHgHVet30HdAxCmRKQLgz7V2OHEC+P578Vs6aZLIFvDvWlEE4U+2ifNrDXW2iOq37P6fwNkh4jf08UbAuZnIdIy5IrKPVK+jlzrTwLGBaNzdWxPYWxNOqXtRpYqY9G+36vAVHQ1s3FVOlClG1bLYcrt2stvYIDFfkakdcOd34EAj0XAXfgLY6QrcWyGyYWTG4ntjSOQpkb7vPQ2oPVNktbj1F5kRuaTueMrN+caNiBu49PwSfuvyG6xMrbApeFOuX5fyX6EG6fv27UNAQABGjRqFHTt2oH79+hg+fDieGbhOxJMnTzBixAjUr18fO3bswMiRIzFr1iwcOJCDA2VGpVQ/Gup03carRct1XmZYOdoeuL9KjBWsPUtMJmNTGX/9BTg5iYO8XC5+1C9fBlLv7xLXr0x+KnosXd8TX37VD9qCMwvw3ob3MPnIZEjFaMaXqCiRZtW1qzhh+OEHYMYMIORaguiFOtxKpDKFzBW3+Tlb7r0/xLijZqreDkkC7KqjUrkIeHuLA/GcOSL98t9/RRCMsu1EHQX2Ax5v0TTsdO8uxlTu3CkCsU2bRDrRm/Dpp6KlPz0d6NNHNBA4OsLgTONJ8iRcfH4R92LuYe6puYhLjdNMIrcpeBMsTCzw+/nfYW1mjU03Non0X6sKYpIqZbroGXFpI/bp3FQcoJLDAJ9pgNc4zcvNOjELdcvWxYJOC7Dw3EIxntTOS4w/e/y3+AxvqNLOjMzEwS3iP1Hv91fpv7ZqZurLuaiVfydrAK26H58Wjw8+yP11k997T/eg1ru3nnT3VwTpLi6ihyMiAmjUCPjyS5Fin5Ym9r1/v24a/uucwOWH334TgdNHH4kelh9/BBYuhGiYOdlb1LvX52IogpF5tr+R225ug5HMCEN3DYW5iTm23RQnwadPA1OnilTSn38Wv4n//CPGiX/5pQh4f/xRTOL4xx95eBOPN4ne6YZLxGOlHLCphGpuUfDyEt9p9SEiMVE02qBsOzGO8NpkcZsxtVIPdZ1lmeQv7KiYpK3apyID5/g7wKXPgfCj+ndkYimOP+HHRPDWZJUmLfhGxA3ci7mHvXf2YuG5hZAr5dh/d78YZgOIYTf2tQCfGZrd/XHpD5S3LQ8vZy+UsS6DPy6pPsCyHUUQdbQdcH1mljR2vdz76T6uMgRJ8mSdIF19P0mehMGDc/8dG5RpBISlpQjS9aa7G2BqKn6H09LErP2A+K6dPZu7smRHrmorVvdCabi0Et+DWz+Lxt8ME1kadLSdGF9e+UMRCFcalP3cNw6qloyIk+Lkv1XeG7v69hVp0M+eAc2aicnHHjyA6D03tgJMrIHIM8CJnuIyhGkGvgfqzAG56rcv8bEYGhV9DoBMO9mXMkWk+j5YlecyFyT1bO5jG43F/xr/D1UdqyIoPEiT4v7bb9rvemysdkz61au6+1EoFYhOjoaTpZj3wUhmBEdLR0QkRsDISGSX5Aczs6ydAFVUU+XY2Wmzv2xtM/Ssl26mzRYyMgcq9gCgv0xpjqqIO2SOaAx07aZ6nqk49kdfFL9p177VdKC89562RzY4OMMkcqY2It07I3MnEQhbVxLnU4ebAzcCAAAxseLHw8VF9ymQycR5cWo4cEg1w7syRTRsWrsDz/eLBqZm60TDACAuIZkaLY5PyjTRU37tWz2fqIqtKh0g9qooY60pInCXx2k+7x49RMaBpydw9pyR+B2OOAHcXSZeS92pYVsViL8NKFLFPD3W7uJzu71QlKXFVqBUbTFcUB6vzdDMTH0eZKr6rt1ZLD6vmz8bfh8GqH8XN2foI0lP15M1msH6a+thZmyGkMgQuNm7Yd21dbl+3dcRFaXtzAgJyT4rqyQp1CB95cqV6NWrF/r06QMPDw9MnjwZZcuWNdg7/vfff6NcuXKYPHkyPDw80KdPH/Ts2RN/Zh6s8ypu/cSPxjnVuD51rx4AuUKOX878gtknZ+OHEz9oLkFjkMwIYqytUqTwXh4HnHof+/aJH/shQ0Rg6u8PfPghYJH+UDvzrqk9cPd34EQ3IOwoNgRtwITDE9C7Zm8svrAYP576MXfvqwhbvRqYO1ekDc6YIdLFvv0WqFHmvEgFch8gxg8ZWwPPD+Sp18Bgj7JjfQAyIHSH2M62qmZSnl9/FSd9EyeKtFh/f9U44ZoTxURNodvE+MDER4CpHdzcxAnc1ati4iNJ0tNTl1HSM/Fj/WANEHZM/L34VzteNDNFqkhnPfU+8GgjcHO+aIF+sg1BQaI1v0ULcaB2d88+He7c03NIV6bjwAcH8OSLJ1jQaQFuRNxAWEIYtoZsRf1y9ZGcngzfsr648uIKbkffBWpOEpMVHWggTsJeqvK2q38pDjgHG4rgWpV1cj/mPlZeWYnwxHAsPLcQSfIk0ZsuMwLqzhWf++NN2tQ3cxeg9g/iJODuUtESrkzTXqfZkKqjxOWyAHFyWSdAk+6upr4fnxqPihXFpGFqjo6GZ+nVPN9GZEcA4rPt3j33Y9IBEeTa2AC3b4se2Nu3xUnU5Mlipl4fH2DoUNGzMWFC9mUqSHK56L2IjRU9xJMmiTKOHg0x67iJlRhqkBQqxlEf72xwX0/jnuJM6Bn4V/ZHVYeqaFOpDQ7eO4iL1xLRrJmY0XvaNOCLL4DPPwfatRN/mzaJAP3rr0XA/vHHyP1lYhzqiP8ndS+FUyMg6DvIos9h3jzxnenUScwG7uIifotQY7yYfOhGgGg0jfgv24yOMWNEj9bo0WLCpWPHgF9/Be4ndxAnjyE/iVTg+gvEBEOGTsQA8duS9Bj4x1d8l6JEdLnz1k7Ymtmid43e6Fy1M6o6VsXOWzvFCau9D3DlK5FOf2U8ACBJnoL1QetRyqIUJv87GY6Wjlh7bS1S0lMA72/F8SXiBBD0rTihtNA3ZXEGttXErPGAaHDw+hxJ8iRN7zmgG6RXrCjqTs3MTHtymN3nqOnxg/jdzZLubmaNxLREKLMZgz17tvi9VgcIz55lmsTqNX36qZhw6YsvRKPtoUOigelqsLX4jYwLAXaWB3aoeiL1zuAHcYBIjRLBsGV50et27mPgzIfabTL/f7v1F+cnp98HLv5PTFyaWQ4nZ3NyAn76SXdzZ2eIRqXUcPH/Z2zxykwSlOss0pavTgRu/wY41BXLTe0A9/4isyPoO/FYnRpsyIsj4n093gQ83StSlp9sAyQlkuXJWHphKRafX4w9t/fke0dFUFgQ3O3dsaDzAvzS6Re85/kegsKDUK8eMHCgyHysXFk0aFSoII7x3bqJyeT69hUNmePGAQELoiBBgrOVs2bfzlbOmhnfJ0/WTZ0fOjTvZZ4yRduL7+GR4ZrdAHqppnHp0ydDg5Kxhfaa4pU+EJ1AEGnlI0dqn/vee0BZLx/RAP50F7CttDYbCVAdp81FUBw8E4AEWLjAxkZkmmRsoFPPN4G6c8X/OiDOAeovFLe+P+lOBGfriWHDzeDsLM4DV60SE/WtWKG63Jz3VHFOkJLhd9TWQ1wuM+4msL+OyFqNVU2sWP1LMWzozIfiSgvqbEBDKvYSQxjPfqyaZ0GbwTthghjapFSKBt6oKJG5g1pTRUPG+U+AbU7iOUamQPWvxbn/0fbiHFM9lM+llWhMeLBSTFBqVQG4s0jn+vU6XNqIRtjr08X5ovv7OhlZkiRBoVRAoXz1TPkffSQyHGbNEpkPQ4eKxgZ15lFmSkmJ9UHrUd25Oo4+PIqyNmVxOvQ0bkfcw4IF4v9m0ybxO3jokGh4N2TPHhHzTJ8uOrP27BHfH0NB94MHomzvvKOdXV8uF0OOqBAnjktLS0NwcDBGjBihs7x58+a4nGXKSuHKlSto3ly35bply5bYunUr5HI5TE0NpBhmojSxheR/Bor764A0QKFUAr4LEW9TG7P//RamMlP4V/HHmdAzmHhwIia3nAwLUwskpCbA1NgUcoUcpsamsDO3g2mrA+JyEJcniR8ha0+gXDcsWyZSbjdtEv+kpqbiSz9p0qewa1YBeLIDeLITgAyoOhbhRi7YeuMnLO68GGWtymLZO8uwPmg9bla7iWpOuUt3ufriKhRKBeqVF2OEQuNCcTvqNqo6VsXd6Lto5d4KJkYmiEqKwtWwq2hSoQnMjazw4IHoTU5JET0c7lXSEJJ4ArVK10JZW5HufS70HKzNrFGtVC3cvy9SgczMxEmAsTFg7hqClykv0aSiOBN7GPsQj14+wqeftoKrqwynT4v0JgsL8Xm827UlarTcJ1LkLk8RP4J2dQFrL9XYgKxOnBBBcs2aoqXbWJX9VFc9Nbe6+Tvjr4J/IBSPtwMyQPF4J+D5NWBXD61aKXDjhghSHj4U+/zkE0BhXg7oeFWMc0p6JnpMqgzBxo0K7NghUqHWrhWvXbkyMO1nA/MZPDkDxIcCpeyAdLn4YX8ZBBhZQ3KsDwnakxAZZJDBCHBsAsTfAyQjwKwsEHcPMHqAvXsV2LhRnCiYm4sDt4WFSMMEoM2LU31uUYlR6O7ZHa3dWsPEyATvVH0Hh6sdRuDjQDQu3xgz285ELZdaSE1PhVKpxI2wG/Dw+kT8Dz/aCCS+ANw/Ej1sDnWBdudFD0niI6B0G6DOPBy9fxQDaw3E8veWw0hmhG0h27DlxhYkpSbB3LUn0Pa4aBE2tRUnDOqepw5XRI+LIgUo10k0nKnrO9P7EIyBRqtEYO/xMWBdFbWcasHdzh0K1XaV7Crh3WrvQqlUQqFQYMQIBa5fBwYMUGDMGHFSr9mltbXe/68FC8T//vDh4iSkqWtTNCrfSPMadV3qopVbK81jfWX18RGTi82bJ4IHf38xq7uxMdC8uRii8OyZOIh++CEQkxiH8KRwmBiZQK6Qw8zEDGWsy+DZYwu8eCEm08k4k7WdvRIp6SlIV6bDWGYMpaSEhYkFTKEQY5YBwMRO9HykPIfc2gOBEbfhZu+GUualoJAUCAoPQq3StXDpUhls2SJOTJydxXt2cgI+GbpR/K5d+Vakh1tWAqpPxq2wG4hKjkYzN9HDEZYQhuvh15GuTMe71d7F4s6LYW9hj9C4UIxRjoHc/joOHmyAQ4fECYP6q+npKcb97dghTkLLlhW/Ifb2wIcGvsfxSbEICguCk5UTbM1s8STuCUpZlIKnUz3I2p2F4qHoNlDc/ROo9gXg3BKdPBS4elVkv9y/Lxpfhg4FFBau4n/w9i/i/7lUHTGBkIHfnBo1ROv+mjUiCyAxUZwwW5WpAoX7ReDBaiBopsjI8vwaUmk/3A2/iejkaLjZuyEqOQop8hTUdKkJqwp9AL+K4jrtSeFAhb5Axd5IuLobXzb+ElNaTQEAVLavjEP3DyEdppC1PSZ60iNPA9Z2gNdXuJJmjlZurbC4y2KUsy2Hp3FPMXr/aFx5dgUNXRsCHa4CIbPFLMblOoqTvmy/YwAa/AHcmCVmeza2hZejF0xlppr/9zJWZfButXdhJjODQqHA//4nfv9PnxYncrVrZ/qOZXoNmQxYt05kUjVuLFKvT//TEJVKVdK8Rg2nGuharStS0lJgbmKudz8VKoihPz//LJb99JMCH31ksPpw/NFxVLSriCoOohvyWtg1yBVy1C9fX+/27u6ivlevFseb+HjRMOroCCjKTQbs64lx6DIjwKUV0ir2xcm7h1DTuabmWHni0QmUsy2Hqm2Pibq++JU46bavC9jVNFwXxjaA/xlxch91QTSW1VsMODTRfY6+N6vnsxoxQkx69+ef4nMbNw5QuPQC/AJFmvDNRSKwqrsAMLI18CEaA/6nRepu+GmR+Vd9CuDaD/CqBJTpJNJ7o68DFfuJS2ymJYnvg5GpKrtLIf4BlDIAZuJWmQLEBAHJz/DMojrmnvsdbvZuqF++Pvbc2oPbEbcxssFI8X8AaP5HFAqFttdUUorLeEoSACUgM0Zg6DmUti4NTyfRsHs9/DqS5clwMHfAB94faPbjV8kPd6LuIDE1AX/+aYk+fcR43oQEEWg0by4a+HbuFMHJsWPiM2zQOBnvPnwXng6emn11rdoV9ub2UCgUsLQUv20zZ4rfunHjsv9e6NRfpuUVK2qz9r75RpxLqjf5/HMxLGP8+ExPq/MzYOEKeE/XWfHTT+L4JpOJ312lBKDRGqBsF9HwbmIjsozKvSc+0w6XgZAfRceS63tAhe6AQoG+fUXD8/r1YkjF6NGql7H2AJpsFPMquL8PlOkoVpTvDrTYI34nbT0Br/+hjJkVgoMVWLtWDMPYtUs0pLZqBSgs3YEOl6AIFq2AiiabgAqqVnarqmL/aTFAlZFApQEiuLWuBjzZAjzcLI5X9YcY/kEwsgT8T4lgOPIMYGwG1P4RcGkHa3MFzp4VjXLXrokhByNHAgqLWuI39fYC0XjgUB/wGCZ64v1Pid+D8FOAnQ/g+SVQoRtg5QE82w2E7hfH0ZrfAWZlDJRLBvidFL/zzw6L+Xc8xkBy64fzj07j4L2DcLJyQlRSFJysnNDNqxvK2pTHw4diXgC5XBy/LS2B+vXFhHybN4s5FBITxXuoWFH/OdCDmAeo7VIb01pPQ52ydZCanopB2wfh2oursLWtBFvbrO2Cz1+GIyg8COnKdBipGmC8Xbzh7l4O9eqJcxaZTJRJksT5vr63Xa6caKi5dg24c0eBOnWA27cVcHPLsL2+c3p9ksOBxHuiM0hmAigSAEUaQmX2uB37EG0qtYGRzAjJ8mScenIKtcvURmlr/Y3XJx6dQHnb8vBwFPNRnQ09C1tzW9in1cSzZ+I8ycJCvD+lEkiyuIsX8S/Qwl2ktDyLe4abUTfRqrwvTBIfiMZ8U1vRiJQWDeNybbN/LyoyqZByqsPCwtCqVSts2LAB9eppZxRdsmQJtm/frjeFvWPHjujRowdGZmgOvHTpEgYMGIATJ07AJUvejH6BgYGwsLB4/TdBRERERERElAP16+tvIM6s0C/BJsvUPJPxOs453V7f8uw0bdpUpI4oFAgKCoKPjw+M1d2xRVlOW5MAdFrXCS7WLuharStG7x+N8yPOw91eTHqz6soqhCWEoVGFRmhbqS1SUkTvxvXrYuZca2vRMlSzJmBSPgitVrXC+p7rsfzScsggw7Z+27J97cS0RPxy5hekpqeiZ82eqFu27uu938zyOFjlratvei2s74Lx+/nf8eu5XzG07lCsvLISp4edhr2Fge/qG8T6LnkM1nmmY6VcIYffaj+0cG+B21G3YWdmh5XdV+Z7eWafmI1jj44hNT0VG3pt0PSqU/5QlCuHoP37c/QdH7JjCOLS4hCbHIt65erhxw7FZ/hgScHf9JyJi9OON7ex0c28e5vkur5zERP9GPgjll9ajt0DdqPNqjaY33E+BvgMyPY5z+Ke4cD9A7AwtkCfWn1gYpR9yByXGoevD36NdGU6ulTrgl41e736PbxCoQXpDg4OMDY2RmSmCxJGRUXB2dlZ73OcnZ0RkWn6zejoaJiYmKBUqVI5fm2jTLPdGBsbvx0/ALmYZWpOhzlo/EdjnHp6Cp80/ARVHKto1g2rP0xnW2vr7C5RVRd9avXB+CPjcTf6Lq58cuWVn5WdpR2mtp2a47IaVECzar019U35gvWdvz5r/Bnuxd7DhRcXsLzbcjhav+K6Lm8Y67vkyVLniYnqFZr1y7otw5CdQ2BhYoEV3VYUyP/I5DaTMRmT832/pJIk5gjKyXf8t66/Yf7p+TAxMsHXzb/mb8JbjL/p2csyoelb7pX1nblTVj1pQzaJ4Z83+xxLLy9F17+7opJjJQysM/CVnbsVHSri4/of57TYcLBywB/d8zL7rWGFFqSbmZmhVq1aCAwMRPsM10s6deoU/P31T2JSt25dHD2qO2vuyZMn4e3tnePx6CVFvXL1sKPfDkQlR6FnjZ6vta8f/H/AxuCNcLV1RS2XWvlUQiJ6G8lkMvzcKfczzhK9MXpO1rxdvHF++PlCKAy9NvXJtHo8t729aIjJ5qTc1twW37X57g0UjojeqDyM0rYwscDO/jsRHB6Mhq4Nc5V9XZgKNd19yJAhGD9+PLy9veHr64uNGzfi+fPn6K+6BsK8efMQFhaGuXPnAgD69++P9evXIyAgAH379sXly5exdetWzJs3rzDfRpH1juc7+bKfMjZlMLbx2HzZFxEREVGOqU/KFQrgyhWR3sqeVSLKhdplaqN2mdqv3rAIKdQgvUuXLoiJicHixYsRHh4OT09PLFu2DK6urgCAiIgIPH/+XLN9xYoVsWzZMgQEBGD9+vVwcXHB5MmT0fFV11YiIiIiIiIiegsU+sRxAwcOxMCBA/Wumz17dpZljRo1wvbt2wu6WERERERERERvnNGrNyEiIiIiIiKiN4FBOhEREREREVERwSCdiIiIiIiIqIhgkE5ERERERERURDBIJyIiIiIiIioiGKQTERERERERFREM0omIiIiIiIiKCJkkSVJhF4KIiIiIiIiI2JNOREREREREVGQwSCciIiIiIiIqIhikExERERERERURDNKJiIiIiIiIiggG6URERERERERFBIN0IiIiIiIioiKCQToRERERERFREcEgnYiIiIiIiKiIYJBOREREREREVEQwSCciIiIiIiIqIkp0kL5+/Xr4+fnBx8cHPXv2xIULFwq7SJQPli5dil69esHX1xdNmzbFp59+ivv37+tsI0kSFi5ciBYtWqB27doYNGgQ7ty5U0glpvyydOlSeHl5YdasWZplrOviJywsDF999RUaN26MOnXqoFu3brh+/bpmPeu8+EhPT8fPP/8MPz8/1K5dG/7+/li0aBGUSqVmG9b32+v8+fMYOXIkWrRoAS8vLxw+fFhnfU7qNi0tDTNmzEDjxo1Rt25djBw5Ei9evHiTb4NyKLv6lsvl+PHHH/Huu++ibt26aNGiBcaPH4+wsDCdfbC+3x6v+n5nNHXqVHh5eWHVqlU6y0tyfZfYIH3fvn0ICAjAqFGjsGPHDtSvXx/Dhw/Hs2fPCrto9JrOnTuHgQMHYtOmTVi5ciUUCgWGDRuGpKQkzTbLly/HypUrMXXqVGzZsgXOzs4YMmQIEhISCrHk9DquXbuGjRs3wsvLS2c567p4efnyJQYMGABTU1MsX74ce/fuxcSJE2FnZ6fZhnVefCxfvhx///03pk6din379uHrr7/GihUrsHbtWp1tWN9vp6SkJHh5eWHq1Kl61+ekbmfNmoVDhw7h559/xl9//YWkpCR88sknUCgUb+ptUA5lV98pKSm4ceMGRo0ahW3btmHRokV4+PAhRo0apbMd6/vt8arvt9rhw4dx9epVuLi4ZFlXoutbKqF69+4tTZ06VWdZp06dpJ9++qmQSkQFJSoqSvL09JTOnTsnSZIkKZVKqXnz5tLSpUs126Smpkr169eXNmzYUFjFpNeQkJAgdejQQQoMDJQ++OADaebMmZIksa6Lox9//FEaMGCAwfWs8+JlxIgR0qRJk3SWjR49Wvrqq68kSWJ9Fyeenp7SoUOHNI9zUrdxcXFSrVq1pL1792q2efHihVS9enXpv//+e3OFp1zLXN/6XL16VfL09JSePn0qSRLr+21mqL5fvHghtWzZUrp9+7bUtm1baeXKlZp1Jb2+S2RPelpaGoKDg9GiRQud5c2bN8fly5cLqVRUUOLj4wEA9vb2AIDQ0FBERETo1L+ZmRkaNmzI+n9LTZ8+Ha1bt0azZs10lrOui59///0X3t7eGDt2LJo2bYru3btj06ZNmvWs8+Klfv36OHPmDB48eAAAuHnzJi5evIjWrVsDYH0XZzmp2+vXr0Mul6N58+aabcqUKYNq1aqx/ouBhIQEyGQyTaYU67t4USqV+PrrrzFs2DBUq1Yty/qSXt8mhV2AwhATEwOFQgEnJyed5c7OzoiIiCikUlFBkCQJAQEBqF+/Pjw9PQFAU8f66p/DHd4+e/fuxY0bN7Bly5Ys61jXxc+TJ0+wYcMGDBkyBCNHjsS1a9cwc+ZMmJmZoXv37qzzYmb48OGIj49H586dYWxsDIVCgS+++AJdu3YFwO94cZaTuo2MjISpqammET7jNpGRkW+moFQgUlNT8dNPP6Fr166wsbEBwPoubpYvXw4TExMMHjxY7/qSXt8lMkhXk8lkOo8lScqyjN5u06dPx+3bt/HXX39lWaev/unt8vz5c8yaNQt//vknzM3NDW7Hui4+JEmCt7c3xo0bBwCoWbMm7t69iw0bNqB79+6a7VjnxcO+ffuwa9cuzJs3D1WrVkVISAgCAgLg4uKCHj16aLZjfRdfealb1v/bTS6X44svvoAkSZg2bdort2d9v32uX7+ONWvWYNu2bbmOvUpKfZfIdHcHBwcYGxtnaYWJioqCs7NzIZWK8tuMGTPw77//YvXq1ShbtqxmeenSpQGA9V8MBAcHIyoqCj179kTNmjVRs2ZNnDt3DmvXrkXNmjU19cm6Lj5Kly4NDw8PnWVVqlTR9Kzx+128zJ07FyNGjMA777wDLy8vdO/eHR9++CGWLl0KgPVdnOWkbp2dnSGXy/Hy5UuD29DbRS6X4/PPP0doaCj+/PNPTS86wPouTi5cuICoqCi0bdtWc/729OlTzJkzB35+fgBY3yUySDczM0OtWrUQGBios/zUqVPw9fUtpFJRfpEkCdOnT8fBgwexevVqVKxYUWd9hQoVULp0aZ36T0tLw/nz51n/b5kmTZpg9+7d2LFjh+bP29sb7777Lnbs2IGKFSuyrouZevXqacYnqz18+BCurq4A+P0ublJSUrL0shgbG2t6UljfxVdO6tbb2xumpqY624SHh+POnTus/7eQOkB/9OgRVq1aBQcHB531rO/io1u3bti1a5fO+ZuLiwuGDRuGP/74AwDru8Smuw8ZMgTjx4+Ht7c3fH19sXHjRjx//hz9+/cv7KLRa/r++++xZ88eLF68GNbW1ppxbba2trCwsIBMJsPgwYOxdOlSVKpUCe7u7li6dCksLCw04xzp7WBjY6OZa0DNysoKpUqV0ixnXRcvH374IQYMGIAlS5agc+fOuHbtGjZt2oTp06cDAL/fxUzbtm2xZMkSlC9fXpPuvnLlSvTq1QsA6/ttl5iYiMePH2seh4aGIiQkBPb29ihfvvwr69bW1ha9evXCnDlz4ODgAHt7e8yZMweenp5ZJhKlwpddfbu4uGDs2LG4ceMGli5dCoVCoTl/s7e3h5mZGev7LfOq73fmRhhTU1M4OzujSpUqAPj9lkklJbFfj/Xr12PFihUIDw+Hp6cnJk2ahIYNGxZ2seg1Zb5OtlpAQAB69uwJQPS2L1q0CBs3bsTLly9Rp04dTJ06NUvAR2+fQYMGoXr16pg8eTIA1nVxdPToUcyfPx8PHz5EhQoVMGTIEPTt21eznnVefCQkJGDBggU4fPgwoqKi4OLignfeeQefffYZzMzMALC+32Znz57VO2lUjx49MHv27BzVbWpqKubOnYs9e/YgJSUFTZs2xXfffYdy5cq9ybdCOZBdfY8ePRr+/v56n7dmzRo0btwYAOv7bfKq73dmfn5+GDx4MD766CPNspJc3yU6SCciIiIiIiIqSkrkmHQiIiIiIiKioohBOhEREREREVERwSCdiIiIiIiIqIhgkE5ERERERERURDBIJyIiIiIiIioiGKQTERERERERFREM0omIiIiIiIiKCAbpREREREREREUEg3QiIqJibNCgQZg1a1ZhFyNfTZw4EZ9++qnmcXF8j0REVHKZFHYBiIiIiqqIiAgsXboUx48fx4sXL2Brawt3d3e899576N69OywtLQu7iK+0cOFCmJi83uH+0aNHWLJkCQIDAxEdHQ0XFxfUrVsXQ4YMgY+PTz6VNO/y4z3q2+fhw4exc+fOfN0vERHRqzBIJyIi0uPJkycYMGAAbG1t8cUXX8DLywvp6el4+PAhtm7dChcXF/j7+xd2MV+pVKlSr/X8oKAgfPTRR6hWrRqmT5+OKlWqIDExEUeOHMGcOXOwbt26/CmoHnK5HKampq/c7nXfIxERUVHCdHciIiI9pk2bBmNjY2zduhVdunSBh4cHvLy80LFjRyxbtgx+fn6abePj4/Htt9+iadOmqFevHgYPHoybN29q1i9cuBDdunXDjh074Ofnh/r16+OLL75AQkKCZpu0tDTMnDkTTZs2hY+PDwYMGIBr165p1p89exZeXl44ceIEunfvjtq1a2Pw4MGIiorC8ePH0blzZ9SrVw/jxo1DcnKy5nmZU8HT0tIwd+5ctG7dGt7e3ujQoQM2b96s9zOQJAmTJk2Cu7s7/vrrL7Rp0wZubm6oUaMGRo8ejcWLF2u2vXXrFgYPHozatWujcePG+Pbbb5GYmKhZr1QqsWjRIrRq1Qre3t7o1q0b/vvvP8360NBQeHl5Yd++fRg0aBB8fHywa9cuKBQKBAQEoEGDBmjcuDHmzp0LSZJ0ypn5Pfr5+WHJkiWYNGkSfH190aZNG2zcuFHnOT/++CM6duyIOnXqwN/fH7/88gvkcjkAYNu2bVi0aBFu3rwJLy8veHl5Ydu2bTmqayIiotfFIJ2IiCiTmJgYBAYGYuDAgbCystK7jUwmAyAC2REjRiAiIgLLli3Dtm3bUKtWLXz44YeIjY3VbP/48WMcOXIES5YswdKlS3H+/HksX75cs37u3Lk4cOAAZs+eje3bt8Pd3R0ff/yxzj4AYNGiRfj222/x999/48WLF/j888+xZs0azJs3D8uWLUNgYCDWrl1r8L2NHz8e+/btw5QpU7B//358//33sLa21rttSEgI7ty5g6FDh8LIKOspg52dHQAgOTkZH3/8Mezt7bFlyxb88ssvOHXqFGbMmKHZds2aNVi5ciUmTJiAXbt2oUWLFvj000/x8OFDnX3+9NNPGDRoEPbt24cWLVrgzz//xNatWzFr1iz89ddfePnyJQ4dOmTw/amtXLkS3t7e2LFjB95//31MmzYN9+7d06y3trZGQEAA9u7di8mTJ2Pz5s1YtWoVAKBLly4YOnQoqlWrhpMnT+LkyZPo0qVLjuuaiIjodTBIJyIiyuTx48eQJAmVK1fWWd64cWP4+vrC19cXP/74IwDgzJkzuH37Nn799Vf4+PigUqVKmDBhAuzs7HDgwAHNcyVJQkBAADw9PdGgQQO89957OH36NAAgKSkJf//9N8aPH4/WrVujatWqmDFjBszNzbFlyxadMnz++eeoX78+atasid69e+PcuXOYNm0aatasiQYNGqBjx444e/as3vf14MED7N+/Hz/88APat2+PihUromnTpujSpYve7dUBdJUqVbL9vHbv3o3U1FTMmTMHnp6eaNq0KaZOnYqdO3ciMjISALBixQoMHz4c77zzDqpUqYKvv/4a1atXx+rVq3X29eGHH6JDhw6oWLEiypQpg9WrV2PEiBHo2LEjPDw88P3338PW1jbb8gBAq1atMHDgQLi7u2P48OFwcHDAuXPnNOs//fRT1KtXDxUqVICfnx+GDBmC/fv3AwAsLCxgZWUFY2NjlC5dGqVLl4aFhUWO65qIiOh1cEw6ERGRAerecrUtW7ZAqVTiq6++QlpaGgAgODgYSUlJaNy4sc62KSkpePz4seaxq6srbGxsNI9dXFwQFRUFQDQKyOVy1KtXT7Pe1NQUtWvX1un9BQAvLy/NfScnJ1haWqJixYqaZc7OzggKCtL7fkJCQmBsbIyGDRvm6P2rZf4cMrt37x68vLx0sg7q1asHpVKJBw8ewMLCAuHh4TrvT71N5lRxb29vzf34+HhERETA19dXs8zExATe3t5ZUt4zy/g5yWQyODs7az5vAPjnn3+wevVqPH78GElJSUhPT9epH31yWtdERESvg0E6ERFRJm5ubpDJZLh//77OcnUwbGFhoVmmVCpRunRpvSnmGXt89c0+njnQzBwMS5KUZVnG/chksiz7lclkUCqVet9XxnLnRKVKlQCIILxGjRoGt9NXzozl0Xff0PMMDS/ILX2fi/rzvnLlCsaNG4cxY8agRYsWsLW1xd69e7Fy5cps95nTuiYiInodTHcnIiLKxMHBAc2bN8e6deuQlJSU7ba1atVCZGQkjI2N4e7urvPn6OiYo9dzc3ODqakpLl68qFkml8tx/fp1eHh4vNZ7ycjT0xNKpRLnz5/P0fY1atRA1apV8eeff+oN/OPi4gAAVatWxc2bN3U+q0uXLsHIyAiVKlWCjY0NXFxcdN4fAFy+fDnb92dra4vSpUvjypUrmmXp6ekIDg7OUfkNuXTpEsqXL49Ro0Zp0tafPXums42pqWmW95wfdU1ERPQqDNKJiIj0+O6776BQKNCrVy/s27cP9+7dw/3797Fz507cv38fxsbGAIBmzZqhbt26+Oyzz3DixAmEhobi0qVL+Pnnnw2mnWdmZWWFAQMGYO7cufjvv/9w9+5dfPvtt0hJSUHv3r3z7T1VqFABPXr0wDfffIPDhw/jyZMnOHv2LPbt26d3e5lMhoCAADx8+BADBw7E8ePH8eTJE9y8eRO///47Pv30UwDAu+++CzMzM0ycOBG3b9/GmTNnMGPGDHTr1g3Ozs4AgGHDhmH58uXYt28f7t+/j59++gk3b97E4MGDsy3z4MGDsXz5chw6dAj37t3D999/r2kcyCs3Nzc8f/4ce/fuxePHj7FmzRocPnxYZxtXV1eEhoYiJCQE0dHRSEtLy5e6JiIiehWmuxMREenh5uaG7du3Y+nSpZg3bx7CwsJgamqKqlWrYujQoXj//fcBiEB22bJl+OWXX/DNN98gJiYGzs7OaNCggSZAzYmvvvoKkiRh/PjxSExMhLe3N/744w/Y29vn6/uaNm0a5s+fj2nTpiE2Nhbly5fHJ598YnD72rVrY+vWrViyZAmmTJmCmJgYuLi4wNfXF9988w0AwNLSEitWrMCsWbPQu3dvWFpaokOHDpg4caJmP4MHD0ZCQgJmz56N6OhoeHh4YPHixZqUekOGDh2KiIgITJw4EUZGRujVqxfat2+P+Pj4PH8G7dq1w4cffojp06cjLS0Nbdq0wahRo7Bo0SLNNh07dsShQ4cwePBgxMXFISAgAD179syXuiYiIsqOTHrVzCtERERERERE9EYw3Z2IiIiIiIioiGCQTkRERERERFREMEgnIiIiIiIiKiIYpBMREREREREVEQzSiYiIiIiIiIoIBulERERERERERQSDdCIiIiIiIqIigkE6ERERERERURHBIJ2IiIiIiIioiGCQTkRERERERFREMEgnIiIiIiIiKiL+D5RGkTYnETK0AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import seaborn; seaborn.set_style('whitegrid')\n",
    "\n",
    "import numpy\n",
    "import torch\n",
    "from model import Beluga\n",
    "\n",
    "from tangermeme.utils import random_one_hot\n",
    "from tangermeme.ersatz import multisubstitute\n",
    "from tangermeme.deep_lift_shap import deep_lift_shap\n",
    "from tangermeme.plot import plot_logo\n",
    "\n",
    "model = Beluga()\n",
    "model.load_state_dict(torch.load(\"deepsea.beluga.torch\"))\n",
    "\n",
    "X = random_one_hot((1, 4, 2000), random_state=0).type(torch.float32)  \n",
    "X = multisubstitute(X, [\"GTGACTCATC\", \"GTGACTCATC\", \"ACTTCCGCG\"], [25, 25])\n",
    "X_attr = deep_lift_shap(model, X, device='cpu', n_shuffles=20, target=57, random_state=0)\n",
    "\n",
    "plt.figure(figsize=(12, 2))\n",
    "ax = plt.subplot(111)\n",
    "plot_logo(X_attr[0, :, 925:1075], ax=ax)\n",
    "plt.ylim(-0.025, 0.25)\n",
    "\n",
    "plt.xlabel(\"Genomic Coordinate\")\n",
    "plt.ylabel(\"Attribution\")\n",
    "plt.title(\"DeepLIFT/SHAP of Marginalization\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a612c147-d893-4777-aece-0a4e7ada0c58",
   "metadata": {},
   "source": [
    "#### Deriving Annotations from Seqlets\n",
    "\n",
    "Annotations are represented in tangermeme as a three-column tensor of indexes that reference a tensor of sequences. Basically, if `X` is a one-hot encoded tensor of sequences with shape `(n_examples, len(alphabet), length)`, then `X_annotations` will be a three column tensor of shape `(n_annotations, 3)` where the first column is the example_idx in `X`, the second column is the start position (0-indexed), and the third column is the end position (also 0-indexed). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c0c94ef6-5154-445d-85ad-73f607c8ef95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5, 5)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.seqlet import recursive_seqlets\n",
    "\n",
    "seqlets = recursive_seqlets(X_attr.sum(dim=1), additional_flanks=5)\n",
    "seqlets.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6669bed-89f9-42f1-b207-a3ed6dae99a2",
   "metadata": {},
   "source": [
    "At this point, we have coordinates but we might not know what is really happening at these positions. Are these seqlets known motifs? Have we discovered something new?\n",
    "\n",
    "We can look into this more by mapping each seqlet to a known database of motifs using TOMTOM. Please see the tutorial on TOMTOM if you'd like to know more about it, and how to use it directly, but at a high level it is an algorithm for mapping one set of PWMs to another set of PWMs and finding statistically significant matches. Here, one of our sets of PWMs is one-hot encoded -- the sequences under the seqlets -- but the algorithm is still valuable because it properly constructs background distributions, accounts for sequence length and information content, and handles overhangs.\n",
    "\n",
    "We can do this mapping using the `annotate_seqlets` command. This command takes the original one-hot encoded sequences, the set of seqlets, and a motif database (either a dictionary where keys are motif names and values are PWMs or a filename of a MEME-formatted file) and outputs the motif index (or indexes) that best match/es each seqlet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0ef9f814-dbef-457a-894d-3f5020fca30a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[ 639],\n",
       "         [1243],\n",
       "         [1743],\n",
       "         [ 357],\n",
       "         [1295]], dtype=torch.int32),\n",
       " tensor([[3.8022e-05],\n",
       "         [2.3365e-05],\n",
       "         [7.1939e-04],\n",
       "         [5.6394e-06],\n",
       "         [8.7449e-06]], dtype=torch.float64))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.annotate import annotate_seqlets\n",
    "\n",
    "annotate_seqlets(X, seqlets, \"motifs.meme.txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46f5c071-2a2a-4d51-9492-cd04b01a9637",
   "metadata": {},
   "source": [
    "There are two outputs: the index in the motif database of the best match and the p-value for that match. It looks like all of the matches have a pretty high p-value. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1360a101-017d-4758-bc28-f8d10c9299d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Jdp2.mouse_bZIP_1',\n",
       " 'ETV6_MA0645.1',\n",
       " 'VENTX_MA0724.1',\n",
       " 'FOS_MOUSE.H11MO.0.A',\n",
       " 'JUND_MA0491.1']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.io import read_meme\n",
    "\n",
    "motifs = read_meme(\"motifs.meme.txt\")\n",
    "motif_names = list(motifs.keys())\n",
    "motif_idxs, motif_pvalues = annotate_seqlets(X, seqlets, motifs)\n",
    "\n",
    "[motif_names[idx] for idx in motif_idxs]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0bf9c7d7-a09a-44ae-a6ff-3f146a2cc24a",
   "metadata": {},
   "source": [
    "Looks like we have two AP-1 hits (the last two are both AP-1 family, even though the names are different) and then other hits for the other motifs. It also looks like the ETV6 motif is found.\n",
    "\n",
    "If we wanted to visualize this better, we could make a copy of the seqlets dataframe, change the names in the first column to be the discovered motif matches, and use the `plot_logo` command again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "78591fc7-c2af-423a-9f45-f1fea3d285c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seqlet_annotations = seqlets.copy()\n",
    "seqlet_annotations['example_idx'] = [motif_names[idx] for idx in motif_idxs]\n",
    "\n",
    "plt.figure(figsize=(12, 2))\n",
    "ax = plt.subplot(111)\n",
    "plot_logo(X_attr[0], ax=ax, start=925, end=1075, annotations=seqlet_annotations, score_key='attribution', ylim=0.15)\n",
    "plt.ylim(-0.05, 0.15)\n",
    "\n",
    "plt.xlabel(\"Genomic Coordinate\")\n",
    "plt.ylabel(\"Attribution\")\n",
    "plt.title(\"DeepLIFT/SHAP of Marginalization\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f33368b3-2013-4e4b-815f-639bdf23fa42",
   "metadata": {},
   "source": [
    "As expected, the seqlets called over the inserted AP-1 motifs now match to AP-1 in the database and the one corresponding to ETV6 is called ETV6! At this point, we now have annotations in the sense that we have the seqlet coordinates and, for each seqlet, we have an assignment to a motif.\n",
    "\n",
    "Note that no motif discovery was done here. The only steps that were performed were calculating attributions, calling seqlets, and mapping those seqlets to a known database to get labels for the annotations. Importantly, the seqlet calling step is done entirely on attributions with no knowledge of sequence content, and the mapping to a database is done only on sequence content with no knowledge of the attributions.\n",
    "\n",
    "Sometimes, you would like to map a seqlet to multiple patterns to see whether there are any other closely related hits. The `annotate_seqlets` function is mostly a wrapper around running TOMTOM and so you can pass any argument into it and they will be passed along to TOMTOM. For instance, you can pass `n_nearest=5` and you will get the five best motif matches for each motif ranked by the p-value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7183ae15-e182-4206-9739-57031c9b4aea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[ 639, 1364,  578,  707,  210],\n",
       "         [1243,  786, 1269,  952,  130],\n",
       "         [1743, 1142,  686, 1582, 1285],\n",
       "         [ 357, 1295, 1075, 1203, 1005],\n",
       "         [1295,  707,  210,  639, 1364]], dtype=torch.int32),\n",
       " tensor([[3.8022e-05, 6.7897e-05, 6.7897e-05, 7.7329e-05, 7.7329e-05],\n",
       "         [2.3365e-05, 2.3365e-05, 1.2413e-04, 1.2689e-04, 1.3772e-04],\n",
       "         [7.1939e-04, 7.1939e-04, 2.2012e-03, 2.3998e-03, 2.7296e-03],\n",
       "         [5.6394e-06, 7.7946e-06, 1.0170e-05, 1.0848e-05, 1.0848e-05],\n",
       "         [8.7449e-06, 1.7248e-05, 1.7248e-05, 2.0561e-05, 2.3947e-05]],\n",
       "        dtype=torch.float64))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annotate_seqlets(X, seqlets, \"motifs.meme.txt\", n_nearest=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fc07539-a6b5-4f74-8c50-f7b68de32b5c",
   "metadata": {},
   "source": [
    "#### FIMO-based Annotations\n",
    "\n",
    "An orthogonal way to calculate annotations is to run FIMO, which scans a set of PWMs against explicitly one-hot encoded sequences. A strength of this approach is that it does not rely on a seqlet calling algorithm, which can be imprecise or yield noisy seqlets. However, a weakness of this approach is that it does not natively consider attributions at all, although one can sum the attribution values across the identified hits after those spans are identified. Another important point is that this algorithm does not account for edge overhangs as well as TOMTOM and so is not the best algorithm to use with seqlets, but does account for motif length and information content. Overall, if one wants to run a database of motifs against long sequences to identify sequence hits and then subsequently score each hit using attributions, this is a simple approach."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ad831649-ecb2-49a7-815f-438bcad51502",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/users/jmschr/github/tangermeme/tangermeme/tools/fimo.py:367: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  hits = pandas.concat(hits)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>motif_name</th>\n",
       "      <th>motif_idx</th>\n",
       "      <th>sequence_name</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>strand</th>\n",
       "      <th>score</th>\n",
       "      <th>p-value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DNASE_6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1831</td>\n",
       "      <td>1861</td>\n",
       "      <td>+</td>\n",
       "      <td>11.908878</td>\n",
       "      <td>0.000049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DNASE_2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1831</td>\n",
       "      <td>1861</td>\n",
       "      <td>+</td>\n",
       "      <td>12.146909</td>\n",
       "      <td>0.000012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TN5_7</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1424</td>\n",
       "      <td>1454</td>\n",
       "      <td>+</td>\n",
       "      <td>12.363324</td>\n",
       "      <td>0.000010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TN5_5</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1746</td>\n",
       "      <td>1776</td>\n",
       "      <td>-</td>\n",
       "      <td>12.449126</td>\n",
       "      <td>0.000010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TN5_4</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1746</td>\n",
       "      <td>1776</td>\n",
       "      <td>-</td>\n",
       "      <td>12.449126</td>\n",
       "      <td>0.000010</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>898</th>\n",
       "      <td>ZIC3_MA0697.1</td>\n",
       "      <td>2170</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
       "      <td>96</td>\n",
       "      <td>+</td>\n",
       "      <td>8.837521</td>\n",
       "      <td>0.000074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>899</th>\n",
       "      <td>ESR2_MA0258.2</td>\n",
       "      <td>2171</td>\n",
       "      <td>0</td>\n",
       "      <td>1045</td>\n",
       "      <td>1060</td>\n",
       "      <td>-</td>\n",
       "      <td>12.674289</td>\n",
       "      <td>0.000026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>EPAS1_MOUSE.H11MO.0.C</td>\n",
       "      <td>2181</td>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>176</td>\n",
       "      <td>+</td>\n",
       "      <td>11.515308</td>\n",
       "      <td>0.000069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>901</th>\n",
       "      <td>BACH1_MOUSE.H11MO.0.C</td>\n",
       "      <td>2184</td>\n",
       "      <td>0</td>\n",
       "      <td>993</td>\n",
       "      <td>1007</td>\n",
       "      <td>-</td>\n",
       "      <td>4.745783</td>\n",
       "      <td>0.000022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>902</th>\n",
       "      <td>HINFP_MOUSE.H11MO.0.C</td>\n",
       "      <td>2191</td>\n",
       "      <td>0</td>\n",
       "      <td>1286</td>\n",
       "      <td>1302</td>\n",
       "      <td>+</td>\n",
       "      <td>9.842318</td>\n",
       "      <td>0.000099</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>903 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                motif_name  motif_idx sequence_name start   end strand  \\\n",
       "0                  DNASE_6          0             0  1831  1861      +   \n",
       "1                  DNASE_2          4             0  1831  1861      +   \n",
       "2                    TN5_7          8             0  1424  1454      +   \n",
       "3                    TN5_5          9             0  1746  1776      -   \n",
       "4                    TN5_4         10             0  1746  1776      -   \n",
       "..                     ...        ...           ...   ...   ...    ...   \n",
       "898          ZIC3_MA0697.1       2170             0    81    96      +   \n",
       "899          ESR2_MA0258.2       2171             0  1045  1060      -   \n",
       "900  EPAS1_MOUSE.H11MO.0.C       2181             0   167   176      +   \n",
       "901  BACH1_MOUSE.H11MO.0.C       2184             0   993  1007      -   \n",
       "902  HINFP_MOUSE.H11MO.0.C       2191             0  1286  1302      +   \n",
       "\n",
       "         score   p-value  \n",
       "0    11.908878  0.000049  \n",
       "1    12.146909  0.000012  \n",
       "2    12.363324  0.000010  \n",
       "3    12.449126  0.000010  \n",
       "4    12.449126  0.000010  \n",
       "..         ...       ...  \n",
       "898   8.837521  0.000074  \n",
       "899  12.674289  0.000026  \n",
       "900  11.515308  0.000069  \n",
       "901   4.745783  0.000022  \n",
       "902   9.842318  0.000099  \n",
       "\n",
       "[903 rows x 8 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.tools.fimo import fimo\n",
    "\n",
    "hits = fimo(\"motifs.meme.txt\", X, dim=1)[0]\n",
    "hits"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7786ad5c-e723-480a-ac71-3acfa4a8f666",
   "metadata": {},
   "source": [
    "A challenge with this approach is that, as you can see, there will usually be hundreds of hits to each sequence. Hence, the next step is usually to extract attribution values for each hit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "171fbc6d-90fd-4f17-b395-9418892a40d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>motif_name</th>\n",
       "      <th>motif_idx</th>\n",
       "      <th>sequence_name</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>strand</th>\n",
       "      <th>score</th>\n",
       "      <th>p-value</th>\n",
       "      <th>attribution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>325</th>\n",
       "      <td>HIF1A_MA1106.1</td>\n",
       "      <td>721</td>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>177</td>\n",
       "      <td>+</td>\n",
       "      <td>13.151028</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>-0.035880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>TEAD1_MOUSE.H11MO.0.A</td>\n",
       "      <td>390</td>\n",
       "      <td>0</td>\n",
       "      <td>174</td>\n",
       "      <td>185</td>\n",
       "      <td>-</td>\n",
       "      <td>11.532274</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>-0.034053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>EPAS1_HUMAN.H11MO.0.B</td>\n",
       "      <td>1362</td>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>176</td>\n",
       "      <td>+</td>\n",
       "      <td>11.515308</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>-0.032816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>900</th>\n",
       "      <td>EPAS1_MOUSE.H11MO.0.C</td>\n",
       "      <td>2181</td>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>176</td>\n",
       "      <td>+</td>\n",
       "      <td>11.515308</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>-0.032816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>ARNT_HUMAN.H11MO.0.B</td>\n",
       "      <td>1658</td>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>176</td>\n",
       "      <td>+</td>\n",
       "      <td>11.572852</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>-0.032816</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>FLI1_MOUSE.H11MO.0.A</td>\n",
       "      <td>475</td>\n",
       "      <td>0</td>\n",
       "      <td>1029</td>\n",
       "      <td>1043</td>\n",
       "      <td>-</td>\n",
       "      <td>13.670665</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.677990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>GABPA_MOUSE.H11MO.0.A</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>1029</td>\n",
       "      <td>1043</td>\n",
       "      <td>-</td>\n",
       "      <td>15.298798</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.677990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>ETS1_MOUSE.H11MO.0.A</td>\n",
       "      <td>536</td>\n",
       "      <td>0</td>\n",
       "      <td>1029</td>\n",
       "      <td>1043</td>\n",
       "      <td>-</td>\n",
       "      <td>12.022456</td>\n",
       "      <td>0.000041</td>\n",
       "      <td>0.677990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>574</th>\n",
       "      <td>ELF1_MOUSE.H11MO.0.A</td>\n",
       "      <td>1269</td>\n",
       "      <td>0</td>\n",
       "      <td>1029</td>\n",
       "      <td>1043</td>\n",
       "      <td>-</td>\n",
       "      <td>15.052783</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.677990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>GABPA_HUMAN.H11MO.0.A</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>1029</td>\n",
       "      <td>1043</td>\n",
       "      <td>-</td>\n",
       "      <td>14.470218</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.677990</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>903 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                motif_name  motif_idx sequence_name start   end strand  \\\n",
       "325         HIF1A_MA1106.1        721             0   167   177      +   \n",
       "174  TEAD1_MOUSE.H11MO.0.A        390             0   174   185      -   \n",
       "614  EPAS1_HUMAN.H11MO.0.B       1362             0   167   176      +   \n",
       "900  EPAS1_MOUSE.H11MO.0.C       2181             0   167   176      +   \n",
       "717   ARNT_HUMAN.H11MO.0.B       1658             0   167   176      +   \n",
       "..                     ...        ...           ...   ...   ...    ...   \n",
       "210   FLI1_MOUSE.H11MO.0.A        475             0  1029  1043      -   \n",
       "50   GABPA_MOUSE.H11MO.0.A        130             0  1029  1043      -   \n",
       "233   ETS1_MOUSE.H11MO.0.A        536             0  1029  1043      -   \n",
       "574   ELF1_MOUSE.H11MO.0.A       1269             0  1029  1043      -   \n",
       "12   GABPA_HUMAN.H11MO.0.A         29             0  1029  1043      -   \n",
       "\n",
       "         score   p-value  attribution  \n",
       "325  13.151028  0.000004    -0.035880  \n",
       "174  11.532274  0.000061    -0.034053  \n",
       "614  11.515308  0.000069    -0.032816  \n",
       "900  11.515308  0.000069    -0.032816  \n",
       "717  11.572852  0.000057    -0.032816  \n",
       "..         ...       ...          ...  \n",
       "210  13.670665  0.000014     0.677990  \n",
       "50   15.298798  0.000004     0.677990  \n",
       "233  12.022456  0.000041     0.677990  \n",
       "574  15.052783  0.000005     0.677990  \n",
       "12   14.470218  0.000008     0.677990  \n",
       "\n",
       "[903 rows x 9 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hits['attribution'] = [X_attr[0, :, start:end].sum().item() for start, end in hits[['start', 'end']].values]\n",
    "hits = hits.sort_values(\"attribution\")\n",
    "hits"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f4b7c43-3329-4832-8276-b8358a522856",
   "metadata": {},
   "source": [
    "If we want to take a more comprehensive view of the attribution scores, we can plot this score in ascending order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f172415a-4653-48a5-b575-bd331048bb3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(hits['attribution'].values)\n",
    "plt.xlabel(\"Hit (Sorted by Attribution)\")\n",
    "plt.ylabel(\"Attribution Sum\")\n",
    "plt.title(\"Attribution Score per Hit\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "703a192d-edc9-4cc7-a919-88ceca37af65",
   "metadata": {},
   "source": [
    "It looks like most of the motifs have low attribution but that there is a sudden jump in score that lasts for over 100 of the hits. Fortunately, this is not because there are over 100 distinct motif instances that have high attribution -- because we generated our sequence synthetically, we know that is not the case! What it does mean, though, is that there are many FIMO hits that overlap each other, and in some cases are actually identical. This is because some motif databases are full of redundant or even identical motifs. Sometimes this is because the same protein has been profiled multiple times, but usually it is because multiple proteins (potentially in the same family) have the same DNA binding domain and so actual bind in very similar or identical places along the genome. You can see this in the dataframe just above, where all five of the bottom motifs seem to have hits at the exact same coordinates."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43e59d08-4a0e-4acf-a346-e479c1b3f26b",
   "metadata": {},
   "source": [
    "#### Counting Annotations\n",
    "\n",
    "Now that we have two methods for getting annotations, we need methods for operating on sets of annotations. The simplest one is to count the number and type of annotations per example so that one can get a sense globally for what annotations are influential at all. This function, `count_annotations`, will take in either a tensor with the example index and the annotation index as columns, or a tuple where the first vector is the example indexes and the second vectro is the annotation indexes, and return a matrix of size `(n_examples, n_annotations)` that has the count of the number of annotations in each sequence.\n",
    "\n",
    "We can use either the seqlet calling + TOMTOM annotations or the FIMO annotations here. Each one will require a small amount of preprocessing. For the seqlet calling + TOMTOM annotations, we need to concatenate the sequence index (from the seqlet caller) with the annotation index (from the annotation function)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "51e3e301-172e-404a-9b98-abb1df231f1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1, 1744])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.annotate import count_annotations\n",
    "\n",
    "y = count_annotations((seqlets['example_idx'], motif_idxs[:, 0]))\n",
    "y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0f101f3-4d6c-4dd9-b0a4-58094b079010",
   "metadata": {},
   "source": [
    "Since we only have a single example, the first dimension is just that one example, and the second dimension is the maximum observed annotation index in the set of indexes. If we are concerned that we might not see the highest index annotation in our set, and know what either dimension should be beforehand, we can pass that shape in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a260b853-76c0-4436-beb2-3bdc3291384e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([3, 2193]), torch.uint8)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = count_annotations((seqlets['example_idx'], motif_idxs[:, 0]), shape=(3, len(motif_names)))\n",
    "y.shape, y.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f6abbb4-4dbb-4bac-9d4f-c823f91bb744",
   "metadata": {},
   "source": [
    "Regardless, the tensor should sum to the number of seqlets/annotations that were being used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f913e72b-2305-4009-b323-40b7ee64e911",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(5)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92b5e182-d767-483e-9a69-795623669194",
   "metadata": {},
   "source": [
    "Note that this count matrix is likely to be extremely sparse and that, as the number of examples grows to be very large, this tensor will take up a large amount of space. That is why by default the dtype for the tensor it uint8. This decreases the amount of space taken up significantly, although it does cap the number of counts of each annotation in each example that are possible. If you want to change the dtype you can just pass that in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ceb95be5-8e6c-48a4-b8d2-c0cd6728f8a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([1, 1744]), torch.float32)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = count_annotations((seqlets['example_idx'], motif_idxs[:, 0]), dtype=torch.float32) \n",
    "y.shape, y.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9028b245-ff54-48b3-a877-58936d953784",
   "metadata": {},
   "source": [
    "One might wonder if it were possible to return a sparse matrix instead of a dense matrix. But.. the two vectors being passed in *are* a sparse matrix, even if all the matrix operations aren't yet wrapped around it. If you really need a sparse matrix, you can easily create a `scipy.sparse.coo` or PyTorch sparse tensor.\n",
    "\n",
    "In lieu of complete sparse tensor support, you can get sums along either of the two dimensions without instantiating the entire tensor. If you want the total number of times an annotation is seen you can use `dim=0`, and if you want the total annotations per example, you can use `dim=1`. This follows from what you would pass into `torch.sum` if you wanted to reduce the full tensor into one of those dimensions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "71e34834-b884-4022-9ae2-f659557bdcc8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([1744]), torch.uint8)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = count_annotations((seqlets['example_idx'], motif_idxs[:, 0]), dim=0) \n",
    "y.shape, y.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4e4bf7cd-525f-46cd-b18c-68d88a0cc5e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([1]), torch.uint8)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = count_annotations((seqlets['example_idx'], motif_idxs[:, 0]), dim=1) \n",
    "y.shape, y.dtype"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38d349ea-d749-4fac-869d-db5eb3277298",
   "metadata": {},
   "source": [
    "This functionality provides a simple way to explore what a machine learning model has learned. First, calculate attributions and call seqlets. Then, rather than using those seqlets to do de novo pattern discovery with TF-MoDISco, which may be robust but also overkill if you just want to inspect the general concepts learned by the model, you simply map those seqlets to some database of known motifs. Finally, you count the number of times each annotation shows up in your database. \n",
    "\n",
    "Here is the entirety of the code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "93c1c55c-77a1-4e17-bfd2-43e0f4be3e5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['FOS_MOUSE.H11MO.0.A', 'Jdp2.mouse_bZIP_1', 'ETV6_MA0645.1',\n",
       "       'JUND_MA0491.1', 'VENTX_MA0724.1'], dtype='<U29')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = Beluga()\n",
    "model.load_state_dict(torch.load(\"deepsea.beluga.torch\"))\n",
    "\n",
    "motifs = read_meme(\"motifs.meme.txt\")\n",
    "motif_names = numpy.array(list(motifs.keys()))\n",
    "\n",
    "X_attr = deep_lift_shap(model, X, device='cpu', n_shuffles=20, target=57, random_state=0)\n",
    "\n",
    "seqlets = recursive_seqlets(X_attr.sum(dim=1), additional_flanks=5)\n",
    "motif_idxs, _ = annotate_seqlets(X, seqlets, motifs)\n",
    "\n",
    "y = count_annotations((seqlets['example_idx'], motif_idxs[:, 0]), shape=(1, len(motif_names)), dim=0)\n",
    "motif_names[y > 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cf2b3e1-3a29-48fc-a3d2-9a0f1d841241",
   "metadata": {},
   "source": [
    "In just a few seconds and a few lines of code, we can pull out the three motifs that we added to the sequence (plus the two negative seqlets that have been discussed in the seqlet tutorial). "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8d393e3-924f-439e-bb67-8707fea22360",
   "metadata": {},
   "source": [
    "So far, we have focused on seqlet calling + TOMTOM for our set of annotations. But, as mentioned earlier, we can also use FIMO + attribution thresholding to get a set of annotations. Remember that there were many hundreds of motif matches when just running FIMO against the randomly generated sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b9f493d2-9fb1-4b79-b6ac-281736ceac70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(903, 9)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hits.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f441ba46-2ded-4946-a893-846a4b0bb4f3",
   "metadata": {},
   "source": [
    "An initial step we can take is to filter these 903 hits down using attribution scores -- basically, say that a motif hit must also have some amount of attribution within it to be kept. This will remove spurious motif htis that are not thought to be relevant by the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0600e415-ee28-4763-9f8e-2a9340ebc84e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(156, 9)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hits_thresh = hits[hits['attribution'] > 0.5]\n",
    "hits_thresh.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "919d34f1-5aad-4136-886e-9d129824f54d",
   "metadata": {},
   "source": [
    "Even with a fairly stringest attribution threshold, we are still getting over a hundred motif hits! Why is this happening? Well, to get a sense for that, let's take a look at the region where we substituted in the three motifs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "100b7f1b-d195-49b8-bda3-34b5e5b07716",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 2))\n",
    "ax = plt.subplot(111)\n",
    "plot_logo(X_attr[0], ax=ax, start=925, end=1075, annotations=hits_thresh, score_key='attribution', ylim=0.15)\n",
    "plt.ylim(-0.05, 0.15)\n",
    "\n",
    "plt.xlabel(\"Genomic Coordinate\")\n",
    "plt.ylabel(\"Attribution\")\n",
    "plt.title(\"DeepLIFT/SHAP of Marginalization\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbf38459-b8f7-4206-96af-aac49b9f757f",
   "metadata": {},
   "source": [
    "Well.. that looks like a lot of motifs mapping to the same region. But this makes sense because the JASPAR database we are using as our motif collection is extremely redundant. Each motif in it is not a unique PWM, but rather is the output from a single experiment and these experiments may evaluate proteins whose DNA binding properties are similar. This means that it is not simple to determine which of these proteins is actually binding to the site. After all, the one with the highest p-value or the highest attribution sum across the span might be best by only a tiny amount that is driven more by experimental noise than by real biology. Because many proteins could potentially be binding to this site, one may not want to toss aside matches.\n",
    "\n",
    "An important point is that the seqlet calling + TOMTOM approach only *appears* to avoid this issue but does not *actually* avoid the issue. Because we constrain the number of matches that TOMTOM returns, we definitionally only get that number of matches even when there are others that have similarly significant hits.\n",
    "\n",
    "Regardless of these points, we can still use the same `count_annotations` function as before to get a similar matrix. Remember, it does not matter how you get your annotations -- you can even define them by hand!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "aa5d4933-069e-4f64-9e38-a235d26d11d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([1, 2185]), tensor(156))"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = count_annotations((hits_thresh['sequence_name'].astype(int), hits_thresh['motif_idx']))\n",
    "y.shape, y.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bb0b54d-5ab2-4068-9f61-5260366b1995",
   "metadata": {},
   "source": [
    "#### Pairwise Annotations\n",
    "\n",
    "Having a count of the number of annotations per example, or an aggregation across either of the two axes, can be useful as a first glance at what is being picked up by the model. Another level of understanding is looking at what pairs of annotations co-occur in sequences. This starts to delve into the more complex syntax underlying the annotations. After all, if a pair of motifs frequently co-occurs, that may indicate either a shared regulatory code or that multiple regulatory codes must use the same region. Regardless, something to look into!\n",
    "\n",
    "You can calculate a square matrix of pairwise annotations using the `pairwise_annotations` function, which has the same required signature as `count_annotations`. This function will return a square matrix that is symmetric and the total counts is equal to twice the number of *pairs* in the data set minus those on the diagonal. Basically, an interaction between index 5 and index 7 is counted in both `y[5, 7]` and `y[7, 5]`, but an interaction between index 5 and 5 is only counted once in `y[5, 5]`. This means that taking the upper or lower triangles will yield a matrix whose sum is equal to the number of pairs in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e58f0b94-4437-44d6-b57a-70e1a14be1f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([1744, 1744]), tensor(20))"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.annotate import pairwise_annotations\n",
    "\n",
    "y = pairwise_annotations((seqlets['example_idx'], motif_idxs[:, 0]))\n",
    "y.shape, y.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ede58d9-4963-44d0-a5ee-31737e2d8507",
   "metadata": {},
   "source": [
    "We cannot easily visualize a (1744, 1744) sized matrix, but we can filter out the rows and columns with no interactions and visualize that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4a723e36-9aa7-4506-9838-0004e484ff4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r_idxs = y.sum(dim=1) > 0\n",
    "c_idxs = y.sum(dim=0) > 0\n",
    "\n",
    "plt.figure(figsize=(5, 5))\n",
    "plt.imshow(y[r_idxs][:, c_idxs], cmap='Reds', vmin=0, vmax=1)\n",
    "plt.xticks(range(5), motif_names[:1744][c_idxs], rotation=90, fontsize=8)\n",
    "plt.yticks(range(5), motif_names[:1744][r_idxs], fontsize=8)\n",
    "plt.grid(False)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ba2fd49-f300-4dca-b3b2-132eed203bb5",
   "metadata": {},
   "source": [
    "Remember that there were five annotations and each were of a different motif. Hence, the sum of this matrix is 20 which is twice the number of pairs (for 5, there are (5*4)/2=10 pairs) minus the sum of the diagonal, which is zero, because there are no repeated annotations.\n",
    "\n",
    "In some situations, what we actually want is an *ordered* matrix where the counts are structured such that the row index is the annotation that appears earlier in the list and the column index is later in the list. Reconsider the annotations we have: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a4e45c79-a37c-44af-b622-45ed81ec4f92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Jdp2.mouse_bZIP_1', 'ETV6_MA0645.1', 'VENTX_MA0724.1',\n",
       "       'FOS_MOUSE.H11MO.0.A', 'JUND_MA0491.1'], dtype='<U29')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "motif_names[motif_idxs[:, 0]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faaa8ca5-b359-4214-b646-e944416751d3",
   "metadata": {},
   "source": [
    "When we consider the ordering, that is saying that we want `y[Jdp2..., ETV6...] = 1` but not the inverse, and then we want `y[Jdp2..., VENTX...] = 1`, etc. Then, we want `y[ETV6..., VENTX...] = 1` without setting `y[ETV6..., Jdp2...] = 1`. Again, we only count interactions between annotations and annotations that come after them in the ordering in the same example. Since we separate out annotations by example index, this still does not create pairs across example boundaries and so the example order doesn't matter, but within each example the order matters. \n",
    "\n",
    "We can calculate this ordered pairwise matrix by setting `symmetric=False`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b00b6bd9-a8fc-420d-ab5c-f3b3600383ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([1744, 1744]), tensor(10))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = pairwise_annotations((seqlets['example_idx'], motif_idxs[:, 0]), symmetric=False)\n",
    "y.shape, y.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11cbca2e-7597-4eae-b0fe-8da8e6af83e7",
   "metadata": {},
   "source": [
    "Now, we can see that `y` has the same shape but it has half the contacts. This is because contacts are not copied across the diagonal to force symmetry.\n",
    "\n",
    "Let's take a look at what the returned matrix looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "d430d2ea-7d87-47f9-83e4-a32a3a7ecafa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5, 5))\n",
    "plt.imshow(y[r_idxs][:, c_idxs], cmap='Reds', vmin=0, vmax=1)\n",
    "plt.xticks(range(5), motif_names[:1744][r_idxs], rotation=90, fontsize=8)\n",
    "plt.yticks(range(5), motif_names[:1744][c_idxs], fontsize=8)\n",
    "plt.grid(False)\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb47d909-43e3-44c6-b610-5919d702ceb3",
   "metadata": {},
   "source": [
    "In this matrix, we can see that Jdp2, which is the first returned annotation, fills out every element other than itself, whereas FOS, which is the second to last, only has a connection with JUND, the last element. It is important to keep in mind that the order matters a great deal, so you should make sure that you have ordered the elements correctly according to some notion you care about before setting `symmetric=False`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7f0bfee-931b-4003-99d7-77eef6be3916",
   "metadata": {},
   "source": [
    "#### Pairwise Annotation Spacing\n",
    "\n",
    "Taking this idea even further, one can consider not only whether pairs of annotations occur in the same examples, but what their *spacings* are. This adds a third dimension of spacing to the tensor, where the first two are annotation indexes. Because calculating spacing requires coordinates, the `pairwise_annotation_spacing` function requires the start (inclusive) and end (non-inclusive) positions of the annotation in addition to the example and annotation indexes. Further, the seqlets must be ordered first by their `example_idx` and then secondly by their `start` position. This reduces the amount of time needed to calculate distance pairs. However, because this can mean changing the order of the seqlets with respect to order of the annotation index vector, you can add the annotations to the seqlet dataframe before sorting and just pass in a four-column dataframe instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cf3ab290-7242-4726-b51f-3b3ef09acf45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1744, 1744, 100])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from tangermeme.annotate import pairwise_annotations_spacing\n",
    "\n",
    "seqlets['motif_idx'] = motif_idxs[:, 0]\n",
    "sorted_seqlets  = seqlets.sort_values(['example_idx', 'start'])\n",
    "\n",
    "y = pairwise_annotations_spacing(sorted_seqlets[['example_idx', 'motif_idx', 'start', 'end']])\n",
    "y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c06c375-552d-4859-9f29-8994e4da4e25",
   "metadata": {},
   "source": [
    "Note the final dimension here of 100. This is the limit on the distance between seqlets within the same example that is allowed. Unfortunately, creating a `(1744, 1744, 2000)` tensor would take up a lot of memory and so the default is lower and seqlet pairs further away from the limit are ignored. If we want to raise the limit we can just pass in an alternate `max_distance`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5a7b0864-d108-48c7-a022-a6076920216b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([1744, 1744, 150])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = pairwise_annotations_spacing(sorted_seqlets[['example_idx', 'motif_idx', 'start', 'end']], max_distance=150)\n",
    "y.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25b66fb7-1272-43f8-b346-e1a9d6c3f3e3",
   "metadata": {},
   "source": [
    "Now, let's take a look at the returned values. We can't easily visualize this returned tensor but we can return the index along the distance length that pairs were found. Normally, we would want to look at the count values but, here, because that count value will only be 1 (since each motif only appears once) we can just look at the argmax. Again, we will only select the rows and columns of this pairwise matrix corresponding to motifs that were passed in, for convenience of viewing. Let's also print out the motif names that those rows and columns correspond to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "00a631ba-fa9d-4dec-b968-ad0f7ebe8f68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[ 0,  0, 56, 21, 15],\n",
       "         [ 0,  0,  0,  0,  0],\n",
       "         [56,  0,  0, 21, 86],\n",
       "         [21,  0, 21,  0, 51],\n",
       "         [15,  0, 86, 51,  0]]),\n",
       " array(['FOS_MOUSE.H11MO.0.A', 'Jdp2.mouse_bZIP_1', 'ETV6_MA0645.1',\n",
       "        'JUND_MA0491.1', 'VENTX_MA0724.1'], dtype='<U29'))"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y[r_idxs][:, c_idxs].argmax(axis=-1), motif_names[:1744][c_idxs]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "082d4865-0299-4be6-a3ea-6c09afaf69ac",
   "metadata": {},
   "source": [
    "Now, let's take a peek at the sorted seqlet list to see if this corresponds with our expectations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8d9b447a-1944-47dc-81f2-c7fcdbf410fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>example_idx</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>attribution</th>\n",
       "      <th>p-value</th>\n",
       "      <th>motif_idx</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>927</td>\n",
       "      <td>942</td>\n",
       "      <td>-0.001295</td>\n",
       "      <td>5.285412e-03</td>\n",
       "      <td>1743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>957</td>\n",
       "      <td>972</td>\n",
       "      <td>0.643915</td>\n",
       "      <td>6.717850e-03</td>\n",
       "      <td>357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>993</td>\n",
       "      <td>1007</td>\n",
       "      <td>0.548725</td>\n",
       "      <td>8.579600e-03</td>\n",
       "      <td>1295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1028</td>\n",
       "      <td>1044</td>\n",
       "      <td>0.727307</td>\n",
       "      <td>4.798464e-03</td>\n",
       "      <td>1243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1573</td>\n",
       "      <td>1588</td>\n",
       "      <td>-0.032544</td>\n",
       "      <td>4.662937e-15</td>\n",
       "      <td>639</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   example_idx  start   end  attribution       p-value  motif_idx\n",
       "2            0    927   942    -0.001295  5.285412e-03       1743\n",
       "3            0    957   972     0.643915  6.717850e-03        357\n",
       "4            0    993  1007     0.548725  8.579600e-03       1295\n",
       "1            0   1028  1044     0.727307  4.798464e-03       1243\n",
       "0            0   1573  1588    -0.032544  4.662937e-15        639"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_seqlets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b099a6b-5834-4f63-b5e5-af37017b0220",
   "metadata": {},
   "source": [
    "The first row of our pairwise spacing matrix corresponds to `FOS`. There is no other `FOS` motif and the `Jdp2` motif is too far away to be counted, and so both are 0s in that first row. The third column is `ETV6` and there is, indeed, a 56 bp spacing between the end of the `FOS` motif and the start of the `ETV6` motif."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3ee66543-60e4-4e1c-8359-445ff2158510",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "56"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1028 - 972"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf737003-208c-4511-b76f-d04237866ce8",
   "metadata": {},
   "source": [
    "Next, there is a 26 bp spacing between the start of `JUND` at 993 and the end of `FOS` at 972. Finally, there is a 15 bp spacing between the end of `VENTX` and the start of `FOS` at 957. This point is important: this function will not tell you the relative spacing between the two, just the absolute spacing."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}