fsrs4anki_simulator.ipynb

{
  "cells": [
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "jmXx-hS9ZMVj"
      },
      "source": [
        "# FSRS4Anki v4.12.3 Simulator"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "lurCmW0Jqz3s"
      },
      "source": [
        "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/v4.12.3/fsrs4anki_simulator.ipynb)\n",
        "\n",
        "↑ Click the above button to open the simulator on Google Colab.\n",
        "\n",
        "> If you can't see the button and are located in the Chinese Mainland, please use a proxy or VPN."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "BtW1uBOm6Djf"
      },
      "outputs": [],
      "source": [
        "# parameters for FSRS\n",
        "w = [1.1008, 1.2746, 5.7619, 10.5114, 5.3148, 1.5796, 1.244, 0.003, 1.5741, 0.1741, 1.0137, 2.7279, 0.0114, 0.3071, 0.3981, 0.0, 1.9569]\n",
        "requestRetention = 0.82  # recommended setting: 0.8 ~ 0.9\n",
        "\n",
        "# parameters for Anki\n",
        "graduatingInterval = 1\n",
        "easyInterval = 4\n",
        "easyBonus = 1.3\n",
        "hardInterval = 1.2\n",
        "intervalModifier = 1\n",
        "newInterval = 0\n",
        "minimumInterval = 1\n",
        "leechThreshold = 8\n",
        "leechSuspend = False\n",
        "\n",
        "# common parameters\n",
        "maximumInterval = 36500\n",
        "new_cards_limits = 20\n",
        "review_limits = 400\n",
        "max_time_limts = 10000\n",
        "learn_days = 300\n",
        "deck_size = 20000\n",
        "\n",
        "# get the true time from review logs\n",
        "filename = \"collection-2022-09-18@13-21-58.colpkg\"\n",
        "\n",
        "# smooth curves\n",
        "moving_average_period = 14\n",
        "\n",
        "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
        "filter_out_suspended_cards = False\n",
        "\n",
        "# Red: 1, Orange: 2, Green: 3, Blue: 4, Pink: 5, Turquoise: 6, Purple: 7\n",
        "# Set it to [1, 2] if you don't want the optimizer to use the review logs from cards with red or orange flag.\n",
        "filter_out_flags = []\n",
        "\n",
        "schedulers = [\"anki\", \"fsrs\"] # You can disable anki by removing it from this list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Note: you may need to restart the kernel to use updated packages.\n",
            "Deck file extracted successfully!\n",
            "revlog.csv saved.\n",
            "average time for failed reviews: 33.7s\n",
            "average time for recalled reviews: 10.6s\n",
            "average time for `hard`, `good` and `easy` reviews: 14.5s, 10.3s, 6.9s\n",
            "average time for learning a new card: 25.7s\n",
            "Ratio of `hard`, `good` and `easy` ratings for recalled reviews: 0.08, 0.90, 0.02\n",
            "Ratio of `again`, `hard`, `good` and `easy` ratings for new cards: 0.21, 0.02, 0.48, 0.28\n"
          ]
        }
      ],
      "source": [
        "%pip install -q fsrs_optimizer==4.22.0\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import random\n",
        "\n",
        "# for local development\n",
        "# import os\n",
        "# import sys\n",
        "# sys.path.insert(0, os.path.abspath('../fsrs-optimizer/src/fsrs_optimizer/'))\n",
        "import fsrs_optimizer as optimizer\n",
        "\n",
        "optimizer = optimizer.Optimizer()\n",
        "optimizer.anki_extract(filename, filter_out_suspended_cards, filter_out_flags)\n",
        "\n",
        "New = 0\n",
        "Learning = 1\n",
        "Review = 2\n",
        "Relearning = 3\n",
        "\n",
        "df = pd.read_csv(\"./revlog.csv\")\n",
        "df.sort_values(by=[\"card_id\", \"review_time\"], inplace=True, ignore_index=True)\n",
        "\n",
        "new_card_revlog = df[\n",
        "    (df[\"review_state\"] == New) & (df[\"review_rating\"].isin([1, 2, 3, 4]))\n",
        "]\n",
        "first_rating_prob = np.zeros(4)\n",
        "first_rating_prob[new_card_revlog[\"review_rating\"].value_counts().index - 1] = (\n",
        "    new_card_revlog[\"review_rating\"].value_counts()\n",
        "    / new_card_revlog[\"review_rating\"].count()\n",
        ")\n",
        "recall_card_revlog = df[\n",
        "    (df[\"review_state\"] == Review) & (df[\"review_rating\"].isin([2, 3, 4]))\n",
        "]\n",
        "review_rating_prob = np.zeros(3)\n",
        "review_rating_prob[recall_card_revlog[\"review_rating\"].value_counts().index - 2] = (\n",
        "    recall_card_revlog[\"review_rating\"].value_counts()\n",
        "    / recall_card_revlog[\"review_rating\"].count()\n",
        ")\n",
        "\n",
        "df[\"review_state\"] = df[\"review_state\"].map(\n",
        "    lambda x: x if x != New else Learning)\n",
        "\n",
        "recall_costs = np.zeros(3)\n",
        "recall_costs_df = recall_card_revlog.groupby(by=\"review_rating\")[\n",
        "    \"review_duration\"\n",
        "].mean()\n",
        "recall_costs[recall_costs_df.index - 2] = recall_costs_df / 1000\n",
        "\n",
        "state_sequence = np.array(df[\"review_state\"])\n",
        "duration_sequence = np.array(df[\"review_duration\"])\n",
        "learn_cost = round(\n",
        "    df[df[\"review_state\"] == Learning][\"review_duration\"].sum()\n",
        "    / len(df[\"card_id\"].unique())\n",
        "    / 1000,\n",
        "    1,\n",
        ")\n",
        "\n",
        "state_block = dict()\n",
        "state_count = dict()\n",
        "state_duration = dict()\n",
        "last_state = state_sequence[0]\n",
        "state_block[last_state] = 1\n",
        "state_count[last_state] = 1\n",
        "state_duration[last_state] = duration_sequence[0]\n",
        "for i, state in enumerate(state_sequence[1:]):\n",
        "    state_count[state] = state_count.setdefault(state, 0) + 1\n",
        "    state_duration[state] = state_duration.setdefault(\n",
        "        state, 0) + duration_sequence[i]\n",
        "    if state != last_state:\n",
        "        state_block[state] = state_block.setdefault(state, 0) + 1\n",
        "    last_state = state\n",
        "\n",
        "recall_cost = round(state_duration[Review] / state_count[Review] / 1000, 1)\n",
        "\n",
        "if Relearning in state_count and Relearning in state_block:\n",
        "    forget_cost = round(\n",
        "        state_duration[Relearning] /\n",
        "        state_block[Relearning] / 1000 + recall_cost,\n",
        "        1,\n",
        "    )\n",
        "\n",
        "print(f\"average time for failed reviews: {forget_cost}s\")\n",
        "print(f\"average time for recalled reviews: {recall_cost}s\")\n",
        "print(\n",
        "    \"average time for `hard`, `good` and `easy` reviews: %.1fs, %.1fs, %.1fs\"\n",
        "    % tuple(recall_costs)\n",
        ")\n",
        "print(f\"average time for learning a new card: {learn_cost}s\")\n",
        "print(\n",
        "    \"Ratio of `hard`, `good` and `easy` ratings for recalled reviews: %.2f, %.2f, %.2f\"\n",
        "    % tuple(review_rating_prob)\n",
        ")\n",
        "print(\n",
        "    \"Ratio of `again`, `hard`, `good` and `easy` ratings for new cards: %.2f, %.2f, %.2f, %.2f\"\n",
        "    % tuple(first_rating_prob)\n",
        ")\n",
        "\n",
        "\n",
        "def generate_rating(review_type):\n",
        "    if review_type == \"new\":\n",
        "        return np.random.choice([1, 2, 3, 4], p=first_rating_prob)\n",
        "    elif review_type == \"recall\":\n",
        "        return np.random.choice([2, 3, 4], p=review_rating_prob)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "bbcc4e2444a64839a199ca10fe39876c",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "  0%|          | 0/300 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "scheduler: anki\n",
            "learned cards: 6000\n",
            "time in minutes: 10827.4\n",
            "remembered cards: 5650\n",
            "time per remembered card: 1.92\n",
            "leeches: 17\n"
          ]
        },
        {
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              "model_id": "a40d5dd0a3bb439a9d32b59b9a82dc6e",
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              "version_minor": 0
            },
            "text/plain": [
              "  0%|          | 0/300 [00:00<?, ?it/s]"
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          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "scheduler: fsrs\n",
            "learned cards: 6000\n",
            "time in minutes: 8537.0\n",
            "remembered cards: 5469\n",
            "time per remembered card: 1.56\n",
            "leeches: 34\n"
          ]
        },
        {
          "data": {
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kSRPc3Nxo3749X3zxBWlpaRw5coT33nvvnvddq1YtAE6cOHHP88x1tx9WuYNe72Rvb2/R65vDnHoHcHJyumfSZ47r16+TnJyc57MzZMgQdu/ezauvvkqjRo1Mn79evXrlG6Q4atQoXnrpJa5fv052djZ79+7lyy+/vO91/fz8ALUV4EGSreTkZN59912effZZUlJSTC1xaWlpKIrC5cuXcXV1vesvX3Ps3LmTRx99lA4dOvDVV18RFBSEVqtl/vz5+R5/79mzJwEBAfz666906NCBX3/9lcDAwDyDgf39/Tl69CgbNmxg3bp1rFu3jvnz5zNq1KgCB7c/SBxDhw5l6tSpLF26lJdffpnff/8dLy+vPEmQ0WjE39+/wHFEQL4E4d8tJbkiIyPp2rUrtWrV4pNPPiEkJARHR0f++usvPv300wIHtd6P0Wike/fuvPbaawUer1GjRp7t3D8iypUrZ/a1hHkkQRHY29sza9YsOnfuzJdffsl///tfqlSpAqjdGQU9+XCnoUOHMmPGDP744w8CAgJISUnJMziuIFWrVgXUH6D3u0alSpWoVKkSO3fu5OLFi6anjjp06MCUKVNYunQpBoPhngNkQf1hU7NmTVatWsXnn39+30m2QkNDOX78OEajMc8v6bNnz5qOw+1m36SkpDzvf9AWFnjwv9AuXLiQ56mKtLQ0oqKiTIM6zal3S/vll18ATEnvrVu32Lx5MzNmzOCtt94ynZfbynOnYcOGMWXKFH777TcyMzPRarX3fWoLbiemly5don79+mbHfevWLdLS0pg9ezazZ8/Od7xy5co89thjrFy5ssD3535OCrqvc+fO5dn+448/cHZ2ZsOGDXlaNefPn5/vvfb29owYMYIFCxbwwQcfsHLlSiZMmJAvAXZ0dKRfv37069cPo9HIs88+y7fffsu0adPu2vpkThyVK1emRYsWLFmyhOeff57ly5fTv3//PO+rWrUqmzZtom3btgUmH4Xx559/kp2dzerVq6lUqZJp/53dQ7n1HRERkaclJiEhIV8rZdWqVUlLSyv0/4VLly4Bt1tRhfXIGBQBqE9JtGjRgs8++4ysrCz8/f3p1KkT3377LVFRUfnOj4uLy7Ndu3Zt6tevz5IlS1iyZAlBQUH3TRZ69uyJp6cn//vf//KN4C/oGu3bt2fLli3s37/flKA0atQIDw8P3n//fdNjkPczY8YMEhISeOqpp9Dr9fmOb9y40fRodJ8+fYiOjs7Tv67X65kzZw7u7u507NgRUH8g2tvb5+uv/uqrr+4bz924uroC+ZOe+/nuu+/y1OfXX3+NXq+nd+/egPn1bilbtmzhnXfeoXLlyqZHlXN/kd7Z9fLZZ58VWEa5cuVMEwsuXLiQXr16Feov2aZNm+Lo6FjgEzOF4e/vz4oVK/J9de7cGWdnZ1asWMHUqVPv+v6goCAaNWrETz/9lKfbKjw8nNOnT+c5197eHo1Gk6f17fLly3dNfkaOHMmtW7eYNGkSaWlp+cbj/PtxbQA7OzsaNGgAkKfb5k7mxjF06FD27t3LvHnziI+Pz5c4DhkyBIPBwDvvvJPvvXq9vlCf84I+L8nJyfmSpq5du+Lg4JDv8eOCWtuGDBnCnj172LBhQ75jSUlJ+X5GHDp0CC8vL+rWrXvfeMXDkRYUYfLqq6/y+OOPs2DBAp5++mnmzp1Lu3btqF+/PhMmTKBKlSrExMSwZ88erl+/zrFjx/K8f+jQobz11ls4Ozszfvz4+3YLeHp68vXXXzNy5EiaNGnCsGHDKF++PFevXmXt2rW0bds2zw+U9u3bm6YXz+3ysbe3p02bNmzYsIFOnTrh6Oh43/scOnQoJ06c4L333uPIkSMMHz6c0NBQEhISWL9+PZs3bzY1YU+cOJFvv/2WMWPGcOjQIcLCwli2bBl///03n332mWmwrZeXF48//jhz5sxBo9FQtWpV1qxZk6//2hwuLi7UqVOHJUuWUKNGDXx9falXr949BwGDOpiza9euDBkyhHPnzvHVV1/Rrl07Hn30UcD8en8Q69at4+zZs+j1emJiYtiyZQvh4eGEhoayevVqnJ2dTbF06NCB2bNno9PpqFChAhs3bjT9lVqQUaNGmebWKOiXXUGcnZ3p0aMHmzZtYubMmXmOHT9+3DS3T0REhKk7B6Bhw4b069cPV1dX+vfvn6/clStXsn///gKP3WnWrFn07duXdu3aMW7cOBITE5kzZw5169bNszZQ3759+eSTT+jVqxcjRowgNjaWuXPnUq1atQJn4W3cuDH16tVj6dKl1K5dO9+j1E899RSJiYl06dKFihUrcuXKFebMmUOjRo3u2QpgbhxDhgzhlVde4ZVXXsHX1zdfi0THjh2ZNGkSs2bN4ujRo/To0QOtVsuFCxdYunQpn3/+eZ45UwrSo0cPU2tQbkL2/fff4+/vn+cPqYCAAF566SU+/vhjHn30UXr16sWxY8dYt24d5cqVy9M6+eqrr7J69WoeeeQRxowZQ9OmTUlPT+fEiRMsW7aMy5cv50mCw8PD6devn4xBKQo2fIJI2MC9HgM1GAxK1apVlapVq5oeSYyMjFRGjRqlBAYGKlqtVqlQoYLyyCOPKMuWLcv3/gsXLiiAAii7du2667VzHzPOtXXrVqVnz56Kl5eX4uzsrFStWlUZM2aMcvDgwTznnTp1SgGU2rVr59n/7rvvKoAybdo0s+pi8+bNymOPPab4+/srDg4OSvny5ZV+/fqZHsfNFRMTo4wdO1YpV66c4ujoqNSvXz/PY8O54uLilEGDBimurq6Kj4+PMmnSJOXkyZMFPmZc0KOpb7/9tnLnf8ndu3crTZs2VRwdHe/7yHFu/W7fvl2ZOHGi4uPjo7i7uytPPPGEkpCQkO/8wtS7OY/R/juG3C9HR0clMDBQ6d69u/L555+bHsv+t+vXrysDBgxQvL29FS8vL+Xxxx9Xbt68edf7zc7OVnx8fBQvLy8lMzOz0LEtX75c0Wg0+R4bvTPmf3/9+3HUgphbP3/88YdSu3ZtxcnJSalTp46yfPnyAmeS/fHHH5Xq1asrTk5OSq1atZT58+cX+PnIlfso+f/+9798x5YtW6b06NFD8ff3VxwdHZVKlSopkyZNUqKiou4br7lxtG3bVgGUp5566q5lfvfdd0rTpk0VFxcXxcPDQ6lfv77y2muvKTdv3jSdExoaqvTt27fA969evVpp0KCB4uzsrISFhSkffPCBMm/evHw/W/R6vTJt2jQlMDBQcXFxUbp06aKcOXNG8fPzU55++uk8ZaampipTp05VqlWrpjg6OirlypVT2rRpo3z00Ud5Htk/c+aMaZoGYX0aRZHp8IQoDRYsWMDYsWM5cOCAaQB0aaTX6wkODqZfv378+OOPhX6fwWCgTp06DBkypNAtLyXF559/zuTJk7l8+XKesRkir6SkJHx8fHj33Xf5v//7P7Pf//LLL7Njxw4OHTokLShFQMagCCFKlJUrVxIXF8eoUaPMep+9vT0zZ85k7ty5ebpUSjpFUfjxxx/p2LGjJCf/kpmZmW9f7timTp06mV1eQkICP/zwA++++64kJ0VExqAIIUqEffv2cfz4cd555x0aN25sGqBsjqFDhxbqqZ+SID09ndWrV7N161ZOnDjBqlWrbB1SsbJkyRIWLFhAnz59cHd3Z9euXfz222/06NGDtm3bml2en59fqUpsSwJJUIQQJcLXX3/Nr7/+SqNGjfIsvlhWxcXFMWLECLy9vXnjjTdMg6CFqkGDBjg4ODB79mxSUlJMA2dzB0CL4k/GoAghhBCi2JExKEIIIYQodiRBEUIIIUSxUyLHoBiNRm7evImHh4eMphZCCCFKCEVRSE1NJTg4+L6TeZbIBOXmzZuEhITYOgwhhBBCPIBr167dd+FOsxKUWbNmsXz5cs6ePYuLiwtt2rThgw8+oGbNmqZzsrKy+M9//sPixYvJzs6mZ8+efPXVVwQEBJjOuXr1Ks888wxbt27F3d2d0aNHM2vWrHuufPtvudOLX7t2Ld/S8A9Lp9OxceNG0zTM4u6krgpP6so8Ul+FJ3VlHqmvwrNGXaWkpBASEmL6PX4vZiUo27dv57nnnqN58+bo9XreeOMNevTowenTp3FzcwNg8uTJrF27lqVLl+Ll5cXzzz/PwIED+fvvvwF1Nse+ffsSGBjI7t27iYqKYtSoUWi1Wv73v/8VKo7cbh1PT0+rJCiurq54enrKh/c+pK4KT+rKPFJfhSd1ZR6pr8KzZl0VZniGWQnK+vXr82wvWLAAf39/Dh06RIcOHUhOTubHH39k0aJFdOnSBVCX5q5duzZ79+6lVatWbNy4kdOnT7Np0yYCAgJo1KgR77zzDq+//jrTp08v1GJvQgghhCjdHmoMSu6y4b6+voC6DLVOp8uzimWtWrWoVKkSe/bsoVWrVuzZs4f69evn6fLp2bMnzzzzDKdOnaJx48b5rpOdnZ1nWfCUlBRAze4KWi7+YeSWZ+lySyOpq8KTujKP1FfhSV2ZR+qr8KxRV+aU9cAJitFo5OWXX6Zt27am5d+jo6NxdHTE29s7z7kBAQFER0ebzvl3cpJ7PPdYQWbNmsWMGTPy7d+4cSOurq4Pegv3FB4ebpVySyOpq8KTujKP1FfhSV2ZR+qr8CxZVxkZGYU+94ETlOeee46TJ0+ya9euBy2i0KZOncqUKVNM27mDbHr06HHXMSiKomAwGDAYDJgzWa5er2f37t20adOm0IN2SwONRoODgwP29vaFfo9OpyM8PJzu3btLX+59SF2ZR+qr8KSuzCP1VXjWqKvcHpDCeKDfwM8//zxr1qxhx44deR4TCgwMJCcnh6SkpDytKDExMQQGBprO2b9/f57yYmJiTMcK4uTkhJOTU779Wq22wErLyckhKirKrEwtl6IoBAYGEhUVVebmWNFoNFSsWBF3d3ez3ne3fweRn9SVeaS+Ck/qyjxSX4VnyboypxyzEhRFUXjhhRdYsWIF27Zto3LlynmON23aFK1Wy+bNmxk0aBAA586d4+rVq7Ru3RqA1q1b89577xEbG4u/vz+gNh95enpSp04dc8IpkNFo5NKlS9jb2xMcHIyjo6NZiYbRaCQtLQ13d/f7TiJTmiiKQlxcHNevX6d69epmtaQIIYQQlmZWgvLcc8+xaNEiVq1ahYeHh2nMiJeXFy4uLnh5eTF+/HimTJmCr68vnp6evPDCC7Ru3ZpWrVoB0KNHD+rUqcPIkSOZPXs20dHRvPnmmzz33HMFtpKYKycnB6PRSEhIyAONTzEajeTk5ODs7FymEhSA8uXLc/nyZXQ6nSQoQgghbMqsBOXrr78GoFOnTnn2z58/nzFjxgDw6aefYmdnx6BBg/JM1JbL3t6eNWvW8Mwzz9C6dWvc3NwYPXo0M2fOfLg7uUNZSy4soax1aQkhhCi+zO7iuR9nZ2fmzp3L3Llz73pOaGgof/31lzmXFkIIIUQZIs0MQgghhCh2JEEpRRYsWJBvDpp/27ZtGxqNhqSkpCKLSQghhHgQkqCUIW3atCEqKgovLy9bhyKEEELckyQoZYijoyOBgYEyGFYIIQTJmTq+3hbJrfQcW4dSoDKRoCiKQkaOvtBfmTkGs86/25c5M9iCuhhju3bt8Pb2xs/Pj0ceeYTIyEgALl++jEajYfny5XTu3BlXV1caNmzInj177lpeXFwczZo1Y8CAAWRnZ0sXjxBCCJO5WyP4YP1Z3l17xtahFKhMzOWeqTNQ560NRX7d0zN74upY+CpOT09nypQpNGjQgLS0NN566y0GDBjA0aNHTef83//9Hx999BHVq1fn//7v/xg+fDgRERH5puW/du0a3bt3p1WrVvz4448yr4kQQog89kQmALDhVDTv6erhrC1evyfKRIJSUuTOvptr3rx5lC9fntOnT5umn3/llVfo27cvADNmzKBu3bpERERQq1Yt0/vOnTtH9+7dGTBgAJ999pl06QghhMgjLVvPqZvJptfbzsXSq16QjaPKq0wkKC5ae07P7Fmoc41GI6kpqXh4ejz0ZG8uZmajFy5c4K233mLfvn3Ex8djNBoBuHr1qmkZgAYNGpjODwpSP0yxsbGmBCUzM5P27dszYsQIPvvss4eKXwghRMm3/mQUb6w4ibODHW2rleODQQ04fOUWxn+NQlh97KYkKLag0WgK3dViNBrRO9rj6uhQ5LPR9uvXj9DQUL7//nuCg4MxGo3Uq1ePnJzbA5j+vdBSbstIbiID6sKK3bp1Y82aNbz66qtUqFCh6G5ACCFEsZKRo+etVadI/Gcg7NJD12lfozwXYlIBqB3kyZmoFDafieVaYgYhvuYvEWMtZWKQbEmQkJDAuXPnePPNN+natSu1a9fm1q1bZpdjZ2fHL7/8QtOmTencuTM3b960QrRCCCFKgu93XCI2NZuKPi5M7FAFgNnrz7LzQjwAo1qH0qKyL9l6Iy8tPoLeYLxXcUVKEpRiwsfHBz8/P7777jsiIiLYsmULU6ZMeaCy7O3tWbhwIQ0bNqRLly6mRR2FEEKUDceuJfHol7v4dNN5AF7vVYvJ3WoQ4OnE9VuZHL2WBEDzMF8+frwhHk4OHL6axILdl8nMMXDwcqLZT6JamiQoxYSdnR2LFy/m0KFD1KtXj8mTJ/Phhx8+cHkODg789ttv1K1bly5duhAbG2vBaIUQQhRXN5IyGbfgAMevJ2OngSHNKvJIgyBcHO2Z8WhdPJ0dKO/hxKAmFala3o0QX1de662OY1x26Dorjtxg8Dd7eHHJcZveR5kYg1JSdOvWjdOnT+fZ9+8M9s5s1tvbO8++MWPGmFaVBjVJ+eOPP0zb/v7+Ns+IhRBCWI/eYOTpXw6RkJ5D7SBPfh7XgvIeTqbjveoFFTgY9tEGwcz88xRno1NNrS5NKnlD0o2iCj0faUERQgghSom1J6I4cSMZLxct341smic5uRcvVy3tq5cHIC41GzdHewY3CbZmqPclCYoQQghRAsWmZuWZpt5oVPhySwQAEztUMfuJnL71b7esDG5aEQ9n7T3Otj5JUIQQQogSJjlTR/dPdvDo3F1k6w2AOiPshdg0PJ0dGNk61Owyu9cNwEVrj72dhtFtwiwcsflkDIoQQghRwpy4nkxypo7kTB0bTsXQp14gH208B8CYtpXxfIDWD09nLUsmtSJbb6RKeXd0Op2lwzaLJChCCCFECXM6Ktn0etG+K6Rk6oiMS8fXzZGn2ld+4HIbVPS2QHSWIQmKEEIIUcKciUo1vd57MZHj19WE5aWu1R+o9aQ4kjEoQgghRAlz+mYKAL5ujgBk5BhoXMmbES0r2TIsi5IWFCGEEKIEydIZiIhLA2DemObsuhBH40o+tKzsi4N96Wl3kARFCCGEKEEiYtMwGBV8XLU0rOhFoxBvW4dkFaUn1SoFFEVh4sSJ+Pr6otFoOHr0qK1DEkIIUczkdu/UCfY0rWpfGkkLSjGyfv16FixYwLZt26hSpQrlypWzdUhCCCGKmb0XEwCoE+Rp40isSxKUYiQyMpKgoCDatGlj9ntzcnJwdHS0QlRCCCGKi4OXE1l+RF0fp0fdQBtHY11lo4tHUSAnvfBfugzzzr/blxkL840ZM4YXXniBq1evotFoCAsLY9myZdSvXx8XFxf8/Pzo1q0b6enppvP79+/Pe++9R3BwMDVr1gTgq6++onr16jg7OxMQEMDgwYOtUqVCCCGsLyNHj9Go/i65kpDOa8vUFYaHNKtI8zBfW4ZmdWWjBUWXAf8r3KJHdoC3pa77xk1wdCvUqZ9//jlVq1blu+++48CBA+h0OqpUqcLs2bMZMGAAqamp7Ny5M89qxJs3b8bT05Pw8HAADh48yIsvvsgvv/xCmzZtSExMZOfOnZa6GyGEEEVk3Ykovt4eyfHrydjbafBxdSQ1S0e23kh5Dyfe6FPb1iFaXdlIUEoALy8vPDw8sLe3JzAwkMOHD6PX6xk4cCChoeqaCvXr18/zHjc3N3744QdT187y5ctxc3PjkUcewcPDg9DQUBo3blzk9yKEEGWd3mBkw6kYcgwG6gZ7USPAg6SMHPZeTMSoKLSs7Iufe8ErDe+JTOCZhYdN2wajQnxaNgCtq/gxe3ADvF1Lf5d+2UhQtK5qa0YhGI1GUlJT8fTwwM7uIXvAtOatJPlvDRs2pGvXrtSvX5+ePXvSo0cPBg8ejI+Pj+mc+vXr5xl30r17d0JDQ6lSpQq9evWiV69eDBgwAFfXB49DCCFE4RiNCt/uuEhSZg57IhNMs7sCdKxRnhM3kkn8Z/VhPzdHfn+6NVXLu+cpQ1EUZm84C0DfBkG89UgdFAUS0rNRFKhbyp/c+beykaBoNIXuasFoBK1BPf9hE5SHYG9vT3h4OLt372bjxo3MmTOH//u//2Pfvn1Urqyus+DmlveePDw8OHz4MNu2bWPjxo289dZbTJ8+nQMHDuDt7W2DuxBCiLIj/EwMH6w/a9r2dHagVqAnh67eYvv5OAAq+bpiMCrcSMpk6Ld7qRPsSfNQH8a3r4yrowN/nYjmyNUknLV2vP1IHfw9nQEI9HK2yT3ZUtlIUEoojUZD27Ztadu2LW+99RahoaGsWLGCKVOm3PU9Dg4OdOvWjW7duvH222/j7e3Nli1bGDhwYBFGLoQQZU/46RgAGlfypkVlX8a1rUyApzMXYlL5alsk1fzdmdC+CqlZOoZ8u4fIuHR2nI9jx/k4ftl7heZhvqw/FQ3A2LaVTclJWSUJSjG1b98+Nm/eTI8ePfD392ffvn3ExcVRu/bdB0atWbOGixcv0qFDB3x8fPjrr78wGo2mJ3yEEEJYh8GosOVsLACv9qxJm6q357GqHuDBp0Mbmbb93J1Y+Vxbtp6L41Z6Dt/vvMj1W5msPREFQL+GwbzUtXqRxl8cmd2HsWPHDvr160dwcDAajYaVK1fmOa7RaAr8+vDDD03nhIWF5Tv+/vvvP/TNlCaenp7s2LGDPn36UKNGDd58800+/vhjevfufdf3eHt7s3z5crp06ULt2rX55ptv+O2336hbt24RRi6EEKXfpfh0UrJ0pu0jV2+RmJ6Dp7NDoR7/9XDW8mjDYEa3CWPTlI78MKoZz3euxtwRTfhiWCOctfbWDL9EMLsFJT09nYYNGzJu3LgCuw2ioqLybK9bt47x48czaNCgPPtnzpzJhAkTTNseHh7mhlLqvPzyy7z88ssA1K5dm/Xr19/13AULFuTb165dO7Zt22ad4IQQQpCtNzDrr7Ms2H0ZF609/RtX4L+9a7H+pNo107mWP1ozF+xz1trTrU4A3eoEWCPkEsvsBKV37973/Cs+MDDvzHarVq2ic+fOVKlSJc9+Dw+PfOcKIYQQxZWiKDzz62FTV06mzsBv+6+y9WwsMalZAPQs5bO7FiWrjkGJiYlh7dq1/PTTT/mOvf/++7zzzjtUqlSJESNGMHnyZBwcCg4nOzub7Oxs03ZKirpQkk6nQ6fT5TlXp9OhKApGoxGj0Wh2zLkToeWWUZYYjUYURUGn02Fvf//mxdy6v/PfQOQndWUeqa/Ck7oyz8PU18qjN9lyNhZHBzvmDGuIq9ae15afJCpZTU6GN69I1xp+pebfwhqfLXPK0iiKGfOx3/lmjYYVK1bQv3//Ao/Pnj2b999/n5s3b+LsfHs08ieffEKTJk3w9fVl9+7dTJ06lbFjx/LJJ58UWM706dOZMWNGvv2LFi3KN8eHg4MDgYGBhISEyNo0ZsrJyeHatWtER0ej1+ttHY4QQhQLJxI1HIzXcC5JQ6ZBwyOVDHSvoP7qTMmBddftCHNXaOn/wL9Oy4yMjAxGjBhBcnIynp73XuzQqglKrVq16N69O3PmzLlnOfPmzWPSpEmkpaXh5JR/Zr2CWlBCQkKIj4/Pd4NZWVlcu3aNsLCwPElRYSmKQmpqKh4eHmVmMpxcWVlZXL58mZCQkELVnU6nIzw8nO7du6PVaosgwpJL6so8Ul+FJ3VlHnPqS1EUPtkUwTc7Lpn21QnyYNmklmaPMymJrPHZSklJoVy5coVKUKzWxbNz507OnTvHkiVL7ntuy5Yt0ev1XL58ucBHYp2cnApMXLRabb5KMxgMpieDHmQm2NxunQd9f0mWW28F1eu9mHt+WSZ1ZR6pr8KTujJPYeprzfGbpuRkZKtQWlT2pVvtAFwcy9YTNpb8bJlTjtUSlB9//JGmTZvSsGHD+5579OhR7Ozs8Pf3f+jr5t58RkYGLi4uD11eWZKTo07BXJjxJ0IIUdr9vPsKAJM6VmFq79K/OF9xY3aCkpaWRkREhGn70qVLHD16FF9fXypVqgSoTThLly7l448/zvf+PXv2sG/fPjp37oyHhwd79uxh8uTJPPnkk3nWmXlQ9vb2eHt7ExurjrJ2dXU1q6vGaDSSk5NDVlZWmWpBMRqNxMXF4erqetfBykIIUVaci05l/+VE7O00jG1T2dbhlElm/yY6ePAgnTt3Nm3nTrs+evRo09wcixcvRlEUhg8fnu/9Tk5OLF68mOnTp5OdnU3lypWZPHnyPadvN1fu48u5SYo5FEUhMzMTFxeXMjcGxc7OjkqVKpW5+xZCiDv9uldtPeleO6BMroNTHJidoHTq1In7jaudOHEiEydOLPBYkyZN2Lt3r7mXNYtGoyEoKAh/f3+zH4/S6XTs2LGDDh06lLn+XEdHxzLVaiSEEAVJz9az4sgNAJ5sFWrjaMquUt2Wb29vb/Z4Cnt7e/R6Pc7OzmUuQRFCCAErj94gLVtPlXJutKnqZ+twyiz5c1kIIYT4h6Io/LJH7d4Z0bISdnbS5W0rkqAIIYQQ/9h/KZGz0ak4a+14vGmIrcMp0yRBEUIIIVBbTz5YfxaAAY0r4uUq3fy2VKrHoAghhCheriVmYGenoYJ38ZqnKiVLx6ojNzh8NQkXrT0vd6tu65DKPElQhBBCFImz0Sn0n/s3RgW+HdmUzjX98x3/de8VxrWtTJXy7kUW18kbyQz8ejc5enUm8QkdqhDgKY8W25okKEIIIawuS2fgpd+OkqVTk4BJPx+iUYg3oX6uNA/zxcXRnjdXniQ5U8eJ68msfK5tkc3JtPzwDXL0RnxctXSvE8DTHasUyXXFvUmCIoQQwqoURWHaypOci0mlnLsjjSv5EH46hv2XE9l/OZGlh67nOf/Y9WQ2nIqmV72gIolt89kYAGYNrF8k1xSFIwmKEEIIq/pySwRLD13HTgOfDGlE++rlOHItiZtJmZy+mcLRa0nEp2VTJ8gTXzcn5v19idnrz9E8zBc/9/wLxVrSxfh0riRkoLXX0K56eateS5hHEhQhhBBWExGbyiebzgMw47F6dKihJgFNKvnQpJIPjzQIznN+SpaO1cducDE+nb5f7MLBXoOPqyMLxja3SrKy5Yy6JEqrKn64O8mvxOJEHjMWQghhNd9uv4iiQLfaAYwsxLTxns5aFk9sRaifK9EpWVy/lcmJG8k89fNBsnQGi8ZmNCqsPREFQJda/vc5WxQ1SReFEEJYRVRyJiuPqmvaPNu5aqHfV83fg9XPtSP8TAyODnZMW3mSI1eTePrXQ3zzZFOcteYtYXKna2mw+MB1olOzOXotCUcHO3rWDXyoMoXlSYIihBDC4vQGI2+vOoXOoNCysi9NKvmY9X4vVy2Dm1YEINDTmVHz9rHtXBzjfzrAB4MaUNHH9YHiik/LZu5pezJPnDbtm/FoXYKL2bwsQrp4hBBCWJjBqPDf5SfYeDoGR3s7XutV66HKa1HZl/ljWuCitefviAS6frydiT8fZOOpaLPL+mD9eTINGjycHdBoYHiLEIY1lyntiyNpQRFCCGExWToDU34/yl8norHTwBfDG9M01LzWk4K0rurHiufaMH31KfZeTGTj6Rg2no5hxbNtaFzI1pk9kQmsPBaFBoUFo5tSL8QHR3u7IptvRZhHWlCEEEJYzBvLT/DXiWgc7e34YnhjetWz3NiOWoGe/DahFSufa0unmurTQN9sj7zr+SlZOjJy9ACkZ+t5ddkxANoEKDSo6IWTg70kJ8WYtKAIIYSwiFVHb7D8yA3sNPDD6GamR4otSaPR0CjEmzf71mbbuTg2no4hIjaNav63p8Y/dOUWryw9xqX4dBwd7BjTJoyz0alcv5VJBW9nHg1Ns3hcwvKkBUUIIcRDOXkjmSd+2MuU39UWihe6VLdKcvJv1fw96FEnAEWBN1eeID1bz4HLiWw/H8dTPx3gUnw6ADl6I9/tuMiO83HYaWDWgLo4P9xDQKKISAuKEEKIB3YuOpUnfthHcqYOgB51AnihS7UiufZ/etTk74h49l5MpPE74abF/gAaVvRiwdgW7L+cyOL9V6no48rgphWpE+jGX2eLJDzxkCRBEUII8UAycvSMnref5EwdTSp58+nQRoT6uRXZ9WsGevDD6OaMnr/ftNifq6MD5Tyc+H5UU3zcHOlZNzDPHCc6na7I4hMPRxIUIYQQD2TXhXiiU7II9HRm/pgWeLlqizyG1lX9WPFsG27cyqRTTX8cHWTkQmkhCYoQQogHsvVcHAA96wbYJDnJVTfYi7rBXja7vrAOSVCEEEIUyg87L/LDzktU9HFhYJOKbD+nLrTXSdaxEVYgCYoQQoj7+nLLBT7aqK5KHJ2SxcErtwBwcrCjdRU/W4YmSinprBNCCHFPW8/FmpKTF7pUY3Tr26sSt6nq99CL9wlREGlBEUIIcVfp2XreXHESgDFtwvhPj5oYjQo3krLYdCaGfg2DbRyhKK0kQRFCCHFX7649w42kTCr6uPBar5oA2Nlp+HZkUy7EplIzwMPGEYrSSrp4hBCiDPv35GZ3WrTvKr/tv4pGA7MG1sfV8fbftPZ2GmoFespaNsJqpAVFCCFsLEdv5Kfdl1mw+zKPNQrm1Z41rf6L32BUeHXpMVYdu8mIFpXo3zgYT2ct1fzduZqYwewN5/jrRBQAr/SoSfvq1p26Xog7SYIihBA2lKM38uQP+9h/ORGAr7ZFkp6tp0moDw0qeuPv4cTBK7doUMELHzfHB7rGH4eus+TgNV7tWZOmlXw4G53KDzsvsvzIDQB+2XuFX/ZeAaBlZV9O3UwhLVtdBfiJlpV4tlNVC9ypEOaRBEUIIWzog/Vn2X85EQ8nBx5pGMRv+6/x054r/LRHTRi09hp0BoXq/u58O7IpX2+LpFUVPwY0rsC+S4k42ikk58DaE9FsOhtHbEo27/SvR81AdWyI0agwe8NZYlKyGfbdXtydHEzr5thpYEr3Guy4EE90chZRyZnsu6QmSs3DfJj5WD1qB3napmJEmScJihBC2MjuyHh+3HUJgE+GNqJ7nQAaV/Lhz2M3Sc/Wc+x6MjqDgp0GLsSm0f3THRiMCksPXeeT8PPcSMr8pyQHOHTcVO7j3+xm3pjmNAvz5ci1W8SkZKPRqN06yZk6XB3taRbmy6hWoXSrE8DzXaoDcDk+na+2RRBWzo2J7avgYC/DFIXtSIIihBA28tPuywAMbxFC9zoBAAxpFsKQZiEAJGXkkJShIyYlixE/7MNgVAjwdCI2NZsbSZm4Ozmg0UBqlp4a/u50ruXPwSu3OHTlFqPn7WfRhFb8dSIagEcbBjO+XWUMRoV6FbzQFpB8hJVzY/bghkVz80Lch9np8Y4dO+jXrx/BwcFoNBpWrlyZ5/iYMWPQaDR5vnr16pXnnMTERJ544gk8PT3x9vZm/PjxpKWlPdSNCCFESRKbmsXmM+pU8WPaVC7wHG9XR8LKudGyih9zhjdmZKtQ1r3UgZ/HteClrtXZ+konDkztzOwWeta+0IapfWrz6/iWtKnqR3qOgVHz9rPin3EmfeoH0aCiN40r+RSYnAhR3JjdgpKenk7Dhg0ZN24cAwcOLPCcXr16MX/+fNO2k5NTnuNPPPEEUVFRhIeHo9PpGDt2LBMnTmTRokXmhiOEECVKls7AtnOxbD8fh96o0LiSt2m8yL30qR9En/pBALSvXt70VI1Op8PpXxO5ujja892oZjzxwz6OXUsCwNXRno415CkcUbKYnaD07t2b3r173/McJycnAgMDCzx25swZ1q9fz4EDB2jWrBkAc+bMoU+fPnz00UcEB8ushEKI0iVbb2DRvqtExKax8XQMcanZpmPDmodY/HruTg4smdiK1UdvsuZEFN3rBMh09KLEscoYlG3btuHv74+Pjw9dunTh3Xffxc9PXUxqz549eHt7m5ITgG7dumFnZ8e+ffsYMGBAvvKys7PJzr79HzolJQVQ/3LQ6XQWjT23PEuXWxpJXRWe1JV5Slt9vbPmDL/uu2baDvJyJsDTifLuTvSu4/9Q93m3urIHBjQKZECjwAKPl1Wl7bNlTdaoK3PKsniC0qtXLwYOHEjlypWJjIzkjTfeoHfv3uzZswd7e3uio6Px98+7NLeDgwO+vr5ER0cXWOasWbOYMWNGvv0bN27E1dXV0rcAQHh4uFXKLY2krgpP6so8paG+rqTCwpP2gIZOQUYquSs09E3DwU4dd7d1002LXKc01FVRkvoqPEvWVUZGRqHPtXiCMmzYMNPr+vXr06BBA6pWrcq2bdvo2rXrA5U5depUpkyZYtpOSUkhJCSEHj164Olp2Wf0dTod4eHhdO/eHa1Wa9GySxupq8KTujJPaakvvcHIwG/2oZBK/4ZBfDi4vsWvUVrqqqhIfRWeNeoqtwekMKz+mHGVKlUoV64cERERdO3alcDAQGJjY/Oco9frSUxMvOu4FScnp3wDbQG0Wq3VPmDWLLu0kboqPKkr85T0+vpp70XORKfi5aLlzX51rXovJb2uiprUV+FZsq7MKcfqz5pdv36dhIQEgoLU0eetW7cmKSmJQ4cOmc7ZsmULRqORli1bWjscIYQoEmejU/gk/DwAb/SpRTn3/H9kCSHuzuwWlLS0NCIiIkzbly5d4ujRo/j6+uLr68uMGTMYNGgQgYGBREZG8tprr1GtWjV69uwJQO3atenVqxcTJkzgm2++QafT8fzzzzNs2DB5gkcIYWJU4Gx0KomZBq4kpJOSqWNUmzA8nYvvX706g5EVR25w+Motlh++QY7BSPMwHx5vavkndYQo7cxOUA4ePEjnzp1N27ljQ0aPHs3XX3/N8ePH+emnn0hKSiI4OJgePXrwzjvv5OmiWbhwIc8//zxdu3bFzs6OQYMG8cUXX1jgdoQQpcHei4l8cMye6L178uzfHZnAgrEtcHQonhONvbH8BEsPXTdtd6nlzweDGmBnZ92ViYUojcxOUDp16oSiKHc9vmHDhvuW4evrK5OyCSEKdPx6EqMXHMSoaHBztCfE15WKPi7siUxgd2QCryw9xkePNyx2ScrSg9dYeug6dhoY364yrav60bmmPxqNJCdCPAhZi0cIUazMXn8OowJ1vI38/GxnynmqUwlsPRfLUz8dZPWxm1xOSKeSryutqvjxZKtQm8Walq0nLUtPZFwa/7fiJKCuDpy7+J4Q4sFJgiKEKBbORKWw5WwsuyLi0dprGFzZiJfL7fEmnWv68+PoZryw6AjHrydz/Hoya45HUcHbhc61/O9RsnUkpufQb84ubiRlotGAokCvuoE826lakcciRGkkCYoQwiZ0BiP/++sM1f098HLR8tyiw6Zjw5pVxM/uUr73dKrpz5oX27H2RBTHryWz/lQ0ry47xopn2xLia51JGwtiNCq8vOQoN5IyATU5aV+9HJ8PbyTjTYSwEElQhBA2se5kNPP/vgxA7u/0xpW8qRfsxctdqrBra/4EBSDUz41nO1UjS2eg/9y/ORudSu/Pd9Kisi9JGTlMe6QOjSv5WC1uRVGY8ecpdpyPw1lrx6IJrdAA9Sp4ySrBQliQJChCCJtYeeSG6bXxnxaIBWNbYG+nKdR6Hc5ae74f1YzJS45y8MottpxVJ4Ac/9NBXu9Vk6uJGYxqHUaAp7NF4lUUhQuxaczdGsGqozfRaOD9gQ1oYsVkSIiyTBIUIUSRS0jLZsf5OAA+GFSfG7cyGd++CvZmdo+E+LqyZFJr1p2MIjE9h6UHr3PiRjKv/3ECgDXHo/htQiuCvV0AdaDtqiM3GNk6lKahvvct/+SNZD7ffIGbSZlcS8wgJUsPgEYDHwxqQP/GFcyKVwhReJKgCCGK3NoTUeiNCvUreDG0eaWHKsveTsMjDdRJHnvVDWTUvP1k641k6QxcScigx6c7aFvNj7RsPX9HJADw5/EopvauxVPtqwCQpTOwJzKBehW8KO+hztm080IcT/9yiPQcQ55rdanlz1PtKtOyit9DxS2EuDdJUIQQRerUzWQ+/WcK+McaWXb2aH9PZ9a/3AGAG0mZjJ2/n/MxaWw4FQOoLR+NQrw5cjWJd9eeoUVlX6r5uzNuwQH2XkxEo4EWYb5U8nVl2eHrKAq0qerHhPZVCPRypnI5N5y19haNWQhRMElQhBBF5nxMKk/8sI+kDB0NK3oxvMXDtZ7cSwVvF9a/1IEj15I4dCURNycHmlTyoVagB5OXHGXl0Zu8vfoUGuDw1SS09hp0BoV9lxLZdykRgCHNKvJO/3o4OUhSIkRRkwRFCFEkbiZlMnrefjU5CfHml/EtcHOy7o8gOzsNTUN9aBqadyDrq71qse5kNEeuJgHg4eTAT+Nb4O/hxPqT0ZyOSqFfw2A61yz6+VWEECpJUIQQVpOlM3AtMYPyHk6MmrefqOQsqvm789PY5jZd9K+CtwvPda7GJ+HnaVHZl9mDGhBWzg3ANC5FCGFbkqAIIazCYFQY9eN+9l9OxNXRnowcAwGeTvw0rgXero62Do8XulRjUNOKBHk6y+RqQhRDkqAIIazih50X2X9ZHcuRkWPAw9mBn8a1oMI/j/zamkajKTaxCCHykwRFCGFxF2JS+fifJ3Xe7lcHb1ct9St4Uc3fw8aRCSFKCklQhBAWpTcY+c/SY+TojXSuWZ4xbcLQaKQLRQhhHlk4QghhUd9sj+T49WQ8nR14f1ADSU6EEA9EEhQhhMWcj0nl880XAJjxWF2LrYMjhCh7JEERQliE3mDk1aXH0BkUutX2p38jWadGCPHgJEERooyJiE1jT2RCoc5VFIXvd1zk5cVHSM7Iu8Lwon1XeW7hYZIycgCY9/cljl1PxsPZgXf715euHSHEQ5FBskKUIetORPHS4qPkGIzMHtyAIc1C7nqu0ajw9upT/LL3CgBp2Xq+H9UMjUbDyRvJTFt1EoNRwdPFgQntq/DxRvWpnWl96xDoJV07QoiHIwmKEKWc0ahgZ6dhx/k4nl10GEVR97+54iTXEjNwcbQnPjWHyLg0HOw0jG4TRssqvkxdfoLlh2+g0YCDnYZNZ2KZ8edpxrQJY+ryExiMakG/7b/GlrOxZOuNtK9ejsebVbTh3QohSgtJUIQopa4lZvBJ+HnWHL/J6NZhbDsfh6LAwMYVSMvWs/F0DHO2ROR73+azsabX9nYaPhnSkPRsA2+sOMGC3ZdZsPsyAJ7ODrSs4kf46RhiUrKp6OPCrIHStSOEsAxJUIQohQxGhRE/7OVaYiYAP+y6BICPq5bpj9XFwU7Dwr1XuRifjs5gxNfNkTA/Ny7EpvLb/qtk6Yy4Otrz2dBG9KgbCICfuyPvrj3NtcRMmlTy5tWetagV6MFMp9NULe/G+HZVcHGUVX+FEJYhCYoQpdDhq7e4lpiJh7MDw5qH8P1ONUF5sWt10yJ9EzoUvCje//WpTWJGDu5ODrg63v4R0bNuIN1rB5ChM+D+r1WIPx3ayHo3IoQosyRBEaIU2ngqGoCutfx5o09tfNwcuXErkydaht73vQ72dvh7FDzI1c5Okyc5EUIIa5GfNEKUAqduJjPjz9M806kqnWqUZ+PpGAB61A1Eo9HwbKdqNo5QCCHMIwmKECVcls7AC78d4WJcOpGxaXwzsilXEjJwtLejQ43ytg5PCCEeiCQoQpRgh6/e4sddl7gYlw5AQnoOT3y/D4C21fykO0YIUWLJTLJClFC/H7jGwK92s/Z4FADPdKoKQI7BSAVvF6b2qW3L8IQQ4qHIn1dClEAGo8KcreqifB1qlGdkq1C61wkgwMOJa7cyebFLdbxctTaOUgghHpwkKEKUQJvPxHAtMRNvVy3fPtnUNP/ImLaVbRyZEEJYhnTxCFHCXEvM4Mut6gyww5pXksnRhBClktkJyo4dO+jXrx/BwcFoNBpWrlxpOqbT6Xj99depX78+bm5uBAcHM2rUKG7evJmnjLCwMDQaTZ6v999//6FvRojSbsOpaDp/tI3j15NxcrBjVOv7z2sihBAlkdkJSnp6Og0bNmTu3Ln5jmVkZHD48GGmTZvG4cOHWb58OefOnePRRx/Nd+7MmTOJiooyfb3wwgsPdgdClBG30nN4Y/kJ9EaFVlV8+X1Sa4K9XWwdlhBCWIXZY1B69+5N7969Czzm5eVFeHh4nn1ffvklLVq04OrVq1SqVMm038PDg8DAQHMvL0SZ9e7aMySk51AzwIOfx7XE0UF6aIUQZroQDlvfgyajoOlYKMaLe1p9kGxycjIajQZvb+88+99//33eeecdKlWqxIgRI5g8eTIODgWHk52dTXZ2tmk7JSUFULuUdDqdRePNLc/S5ZZGUleF97B1dTEunT8OX0ejgXceq41GMaDTGSwZYrEin63Ck7oyT5mur9jTOPw+Go0uHW4ewXhxB4ZHvwL7gp/4s0ZdmVOWRlEU5UEvpNFoWLFiBf379y/weFZWFm3btqVWrVosXLjQtP+TTz6hSZMm+Pr6snv3bqZOncrYsWP55JNPCixn+vTpzJgxI9/+RYsW4erq+qDhC1FiLLtox84YO+r5GJlQy2jrcIQQJYxrdgxtIj7ALSeeVOdg3LJisMPANZ/WHA6dBJqiaZHNyMhgxIgRJCcn4+npec9zrZag6HQ6Bg0axPXr19m2bds9A5k3bx6TJk0iLS0NJyenfMcLakEJCQkhPj7+vjdoLp1OR3h4ON27d0erlXkk7kXqqvAepq5SMnW0/2gHGTkGfhrTlDZV/awUZfEhn63Ck7oyT5msr4QLOPzyGJr0WBSfyujHbEBz8xD2S0eiMeoxtPsPxo5T873NGnWVkpJCuXLlCpWgWKWLR6fTMWTIEK5cucKWLVvuG0TLli3R6/VcvnyZmjVr5jvu5ORUYOKi1Wqt9gGzZtmljdRV4T1IXS3dfZWMHAM1AzzoUDMATTHuM7Y0+WwVntSVecpUfe3+DNJjIaA+mieXofUIAK8+8NhXsGIi9n9/hn3tvlChaYFvt2RdmVOOxdt0cpOTCxcusGnTJvz87v/X3tGjR7Gzs8Pf39/S4QhRoqVk6fhmeyQAT7WvXKaSEyHEQ1AUyEgEo0EdGAvQZzZ4/OvhlIZDod5gUAyw4hnITrNNrHdhdgtKWloaERERpu1Lly5x9OhRfH19CQoKYvDgwRw+fJg1a9ZgMBiIjo4GwNfXF0dHR/bs2cO+ffvo3LkzHh4e7Nmzh8mTJ/Pkk0/i4+NjuTsTooQ6dOUW52NS8XHVsv18HEkZOqqWd2NA4wq2Dk0IUVydXg0OTlCjJ9y6DKtfgEs7oMFQyEwEZ2+o2CL/+/p8CJd3Qvw5WPkMtH4evCqCl+1/3pidoBw8eJDOnTubtqdMmQLA6NGjmT59OqtXrwagUaNGed63detWOnXqhJOTE4sXL2b69OlkZ2dTuXJlJk+ebCpHiLIsMi6NYd/tQWfIOzTslR41cbCXx4qFEAW4tAN+H6m+rtMfLmwEXYa6fXyJ+r1aN7Av4Fe+qy8M+QUW9IUzq9UvOwfo/zXUHlAk4d+N2QlKp06duNe42vuNuW3SpAl79+4197JClFoGo4K9ndp1M+uvM+gMCpV8XSnn7ohRgUYh3vSqJ3MGCSH+kZWiJiFVOoOLD2x88/ax0yvV76HtIDsFoo+r2zV63b28Si3h0S/gz5fA0V1tcVk+AbtuUUCYlW7i/mSxQCFs6IedF3l/3Vk+HtKQcu5ObDoTi4OdhnljmlPN393W4QkhiqO1/4ETv4PWDfxrQ9QxcPSAjq/B8d+h6WhoNh5uHIIfu4GdFqp1vXeZjUZAw+Hq2JUNb8C+ryEhAhTbLachCYoQRehyQjqOWi2hfm5sPhPDe3+dQVHg/XVn8XJRR7c/2SpUkhMhRMHSE263kujS4cZB9XWH/0DbF9WvXCHNYcRSdSI2V9/7l63RqF+9ZkFoa4xVe8L6DRa/hcKSBEWIInIzA179cg86g5E2Vf3YfykRRVF/HkQlZxGVnIWnswMvda1u61CFEEXBoIPrB9QBrP61Czft/PHFYMiBoIbQ411IiwXPChDSsuDza/QwPy6NBuo8BjaebVcSFCGKgMGosCTSnhy9Ogvs3xEJAPSsG0DLyn7MXHMagBe7VsfHzdFmcQohisi59bBiEmQlqdvlaqgJR42ed3+PQQ+Hf1ZfNxkNlTtYPUxbkgRFCCtLTM/hvbWnuJymwc3Jno8GN2TfpUT6NgiieZgv2XoD609Go9HAqNZhtg5XCGFtigLrX1eTE1c/df6R+POwaAi0mAi9Z+dvTclMgmXjIO4saF2h/mBbRF6kJEERworiUrPp+8VOYlPVpRre6FWT3vWD6F0/yHSOk4M9vz/d2lYhCiGK2o1D6lwlWld4+YQ6mdr2D2DPXNj/HfjXgWZjb59vNMLS0XBxm/qegd+Ds5etoi8ykqAIYUVvrTpJbGo2ob6u9AtMZUizirYOSQhhayeWqd9r9gFHN/V1z/fA3R/C34J1r6vjUxo/oSYkf3+mJicOLjD2LwhubKvIi5QkKEJYyV8nolh3MhoHOw1fDGvA5SO7bB2SEMLWctLh1Ar19Z3dNK1fgKv74NxaWPeq2g3k6K7OZwLq0zVlJDkBSVCEsChFUcjSGcnUGXhr1UkAnu1UlTpBnlw+YuPghBC2YdDDjtkQcwqu7oWMePXJnapd8p5nZwePL4AjP8Pfn0PSVTU5cXCBZuOg6RgbBG87kqAIYSErj9xg7tYILsSmUc7difi0HGoEuPNcl2qgGG0dnhDCVg7NV8eY5PIOhUc+VdfOuZODIzR/Sp1oLT1OfYy4XA11fxkjCYoQFrAnMoGXlxw1bcenZWOngdmDG+LkYI9OJwmKEKWe0QBHF4FfVdDYwx9PqfOb3DikHm/+FFTvobac2GvvXZZGo45Jcfe3ftzFlCQoQjwkRVGYveEsAI82DOalbtXZdDqGsHJuNArxtm1wQpRV+hz4fRQkXoTxG9Q1a6zJoFfnNTn5zwBYOwcw6iH5qrrtVw16vX//xESYSIIixEMKPx3DkatJuGjtefOR2vh7OFO1o0xVL4RNrf8vnF+nvj6+FFpOVF9npajzkFjampfV5MTOQS3fqIeqXSE1Sp3jpOcsSU7MJAmKEA8hKSOHt1adAmBs2zD8PZxtHJEQgtOr4OCPt7eP/AK1H4FN09EeX0ITn9ag9Ll9buwZaPsyaAv5/zf5BvzYHWo/Cr3fVx8bPvILaOxgyM9qa0n0CXW6eI0dZCSCe3mL32ZpJwmKEA9IURTeWHGC6JQsKpdz47nO1WwdkhDCaIRt76uvm46FI79C9HGY2wqykwEIubUHw+a31IRk16fqufEXoMUEiD2tzkFy4zDoMqD5eKjcMe/MrmfXQsoNdcXf8jUh/G11f/tXoFZf9XX5mrfPl+TkgUiCIoSZrt/KwNvVkYOXE/nrhDrPyefDGuHmJP+dhODGIdjxMdQfBHUHFm4BPEsw6NRrx5xUkwwnT+g2HTIT1VaS7GQIaoihSjfs//4Y+31f336vxk7tnskdP/JvZ1arj/f2+/z2vtwVhEHt2gGo2AI6vm6FGyu75CeqEGY4eSOZgV/vxtPZAW9X9bG/MW3CaFDR27aBCVEcKAr8+ZLavXFurdr1MXTh7STFEslK/AVYO0Vdv8YzGOoOUJOSo79BWvTt81pMABdvaP08XAhXu2P6fYYRB05fjqKe4SQae63ayqKxg9XPq5OiVWqtPtJbvpY6XuXA93BoAYS2gwaPq2VfP5g3psAGMGIJ2MuvVEuS2hSikIxGhbdWnSRHbyQ+LYf4tBzcnRx4Vrp2RFlz+W/ISoaQluDqezvxuLRDTU7s/5nf49xfsO8bOLYIHJxhxO/q+feTchN0merjunfaNku9DsDNw3B2ze1jzt5qS4qrH7R6Tt0X0gKmXgc7e3Vbp+Oify9q9fkCrfZfg1ardVMTmjvnJnH1Va+5dopalpMHJEaqx4Ytgmv7oe1LhbsvYRZJUIQopBVHbnD4ahJujvYEeDpzMT6diR2q4OtW9iZQEmVYzClY0Bf450kYeyeo2Qv6fw2756j7mowEj0DY8i5smHr7vYufgJEr1CQgLUY9507pCfB1W7VrpkYv6PoWBNRVj6XFwenV6ut+X6hPx1zYqLZ21BsINfuqT9FoNHlba3KTk3vxCCh4f/tXIHILXNsHyydCu5fV/X7V1PEmuWNOhMVJgiJEIaRk6Zi1Tp3r5IWu1RnaLITdkQn0qlfAD1ghSrP93wOK2h2SkwaGbHWMx5U9kB4LaKDVs+ARBAfmQepNcPRQE4aru+GHrup7r+2FFpOg9wd5k4m/P1WTE4Dz69UEpNWz0ONdOLoQjDoIbgJNR6vn9HzPuvdr7wADv4Nv2qsx/zZM3V+xuXWvKyRBEaIwvth0gfi0bKqUc2Nc28o4OtjRt0GQrcMSomjos2Htf0DrAseXqPuGL4YKTeD6AVgyUk1O7LTQ453bXTOPfAqbpkPPd9WWlqWj1fEiufZ/qyY5NftAzd5qq8r+79VjfT6CyzvV5GfPl+p4kwP/PDrcbGyR3ToAPmHQ9xNY/tTtfRWaFm0MZZAkKELcx/VbGSzYfRmAtx+ti6ODnW0DEqKoHV2ozvORq3xtCGuntnxU6QRj1qiDVJuMvN0dA2rXT81et7ef3Qdb3lHf5x0Km2eoZR9dCPUfV8ed6LPUgarNn1IHuu76J8nZ8IZahmcFqDeoKO46rwaPg5sfbJ8NqdFQ65Gij6GMkQRFiPtYczwKvVGhZWVfOtaQ+QxEGWPQ3Z4rxMlTXV233ct5u2WCGqpf9+NeHh794vZ2+ZrqnCLHFsOJpeo+O23ebp/WL8DJ5epcJo7u6tMyjm4WuTWzVe2SfwViYTWSoAhxH2uPRwHwaKNgG0ciRBHKTlPXlkmIgKSr4FYenj8IGQkFP13zIHIHmZavBeHT1H1d38qb7Ng7wOML1JaLpmMgsL5lri2KPUlQhLiHy/HpnLiRjL2dhl51ZUCsKEPWv573Ed42L6qP4bp4W/5abV6ArCQw5KjzltzJryoM/Nby1xXFmiQoQtzD2hNq60mbqn74uTvd52whSgGjEfZ/p04Rjwb6fKg+kVOzj/WuqdGoLSdC/IskKELcxfVbGXyzXZ2QqV8D6d4RZcCtK7BsrDplPED7KepAVSFsQBIUIQqQmWNg8pKjpGbpaVzJm4FNKtg6JCGs6+I2WDZOHWPi5AkdX1PnHxHCRiRBEeIOx68n8crSY5yPScPdyYHPhzbGwV4eLRallEGvjjc58IO6HdRQncLdq6Jt4xJlniQoQvwjJiWL/1txkk1nYgAo7+HEnOGNqeTnauPIhLCinR/fTk6ajVdnbHWUz7ywPUlQhAB2nI/j5SVHSUzPwU4D/RtV4I2+tSknA2NFaXZ1L2z/QH392FfQ+AnbxiPEv0iCIso0o1Fh7tYIPtl0HkWBOkGefDG8EdX8PWwdmhDmyUoBxQXstRB3FrxC7v1I8Nm16uJ3ikGdxVWSE1HMSIIiyqzkTB3/+f0om87EAjC8RSXe7lcHZ20hVj4VohjxSY/A4bMJ6jwi9o7qAn6O7tByEnR4DbTOed9weZe6sjAKhLVX15kRopgxe+Tfjh076NevH8HBwWg0GlauXJnnuKIovPXWWwQFBeHi4kK3bt24cOFCnnMSExN54okn8PT0xNvbm/Hjx5OWlvZQNyKEObJ0BkbN28+mM7E4Otgxe3ADZg2sL8mJKHn02TS6+iMaQzagqMmJg7O6CN/Oj+G3oZCTfvv87DRY+ax6br3BMHIFOHvaKnoh7srsBCU9PZ2GDRsyd+7cAo/Pnj2bL774gm+++YZ9+/bh5uZGz549ycrKMp3zxBNPcOrUKcLDw1mzZg07duxg4sSJD34XQtyD0aiQkqUD4Fx0Kl9uucDziw5z7FoSXi5a/ni6DUOahdg4SiEejN2eOXhm3UDJnYr+hcPwRhQ8/hNo3dTHh38ZAJlJ6hs2vAFJV8CrEvT7TO0SEqIYMruLp3fv3vTu3bvAY4qi8Nlnn/Hmm2/y2GOPAfDzzz8TEBDAypUrGTZsGGfOnGH9+vUcOHCAZs2aATBnzhz69OnDRx99RHCwTIglLCdbb+Cpnw7yd0Q8/RtX4K8TUWTpjADYaWDuiCbUr+hl4yiFeEDZadjtU/9YNHR7B4dy1W8fq9tfXfl34SC4tg9+ekRdgffwT4AGHvsSnGSslSi+LDoG5dKlS0RHR9OtWzfTPi8vL1q2bMmePXsYNmwYe/bswdvb25ScAHTr1g07Ozv27dvHgAED8pWbnZ1Ndna2aTslJQUAnU6HTqez5C2YyrN0uaVRcamrtGw9c7ZE4ufuSK+6AVTydeVKYga7IxPYeSGBnRfiAVh++AYAjUO8CPZ2oVut8rQM8yqS+ItLXZUUUl//ostEExGOUqGpmnCAOtbEqMfu2G/YZ6eS5hSIXY1+KHfWV2AjeGIlDr89jib6BESfUN/e7j8YQ9pAGaxf+WwVnjXqypyyLJqgREdHAxAQEJBnf0BAgOlYdHQ0/v7+eYNwcMDX19d0zp1mzZrFjBkz8u3fuHEjrq7WeV4/PDzcKuWWRkVZVxl6cLG/vRK7osCC83YcTVR7Kz/aeJ6aXgoRKRr0inqSHQq9QowcTbCjsofCoOAE7O2A69f56/qRIosd5HNlrrJeX0FJB2hw7Wec9cnk2LtxOngI7tnRhCTuwlGfht7eBXvgYvnuXNq0+a7luIZNpVrMGkJu7SHOozb70+rBX38V3Y0UQ2X9s2UOS9ZVRkZGoc8tEU/xTJ06lSlTppi2U1JSCAkJoUePHnh6WnZwl06nIzw8nO7du6PVSt/svRR1XW07H8cri47SOMSbb55ohIezlp/3XuVo4lm09hqaVPJm36VbnE1WE5NGIV4EezkzsHEwHWuUt3p89yKfK/NIfQFJV3D4diIafRaKvSOOhnQaXZuf5xStIQPF0YNrvu0KUVejURSFckCf3Ay/DJLPVuFZo65ye0AKw6IJSmCguhx9TEwMQUFBpv0xMTE0atTIdE5sbGye9+n1ehITE03vv5OTkxNOTvknzNJqtVb7gFmz7NKmKOoqNUvHtFVn0BkU9l++xegFh5n5WF1mbzgPwNTetRnXrjJnolJYtO8qTUK96d+oAppi9oNYPlfmKdP1Ff4m6LMgrD2a4b/B5plwaac6FX2dR8HZC/Z/h6FGH/RXXMp2XT0Aqa/Cs2RdmVOORROUypUrExgYyObNm00JSUpKCvv27eOZZ54BoHXr1iQlJXHo0CGaNm0KwJYtWzAajbRs2dKS4YgSLktn4HRUCjeTMlm8/xrRKVlU8HYhS2fgxI1kBn69G0WBttX8GNs2DIDaQZ6807+ebQMX4mEoCvz9GZxfB3Za6PuxOpi1z4f5zw1rp447uVK2u2tE6WR2gpKWlkZERIRp+9KlSxw9ehRfX18qVarEyy+/zLvvvkv16tWpXLky06ZNIzg4mP79+wNQu3ZtevXqxYQJE/jmm2/Q6XQ8//zzDBs2TJ7gESZbz8YydfkJolNuP55up4HZgxsQ4OnMkz/sIzolCycHO/43oH6xaykR4oFtex+2v6++7jwVyte0bTxC2IjZCcrBgwfp3LmzaTt3bMjo0aNZsGABr732Gunp6UycOJGkpCTatWvH+vXrcXa+PZPhwoULef755+natSt2dnYMGjSIL774wgK3I0qDFUeuM3nJMQB83RwJ8XGhaagvA5tUoF4F9ZHgpU+35qON5+hTP4hQPzdbhiuE5aREqZOrgbpoX5sXbBuPEDZkdoLSqVMnFEW563GNRsPMmTOZOXPmXc/x9fVl0aJF5l5alAFXEtJ5c8VJQJ16/q1H6uDimH921xBfVz4f1riowxPCuvZ/C0YdVGotyYko88yeSVYIa4mITeOpnw6SnmOgRZgv7/avV2ByIoRF5KTDxe2QdM3Wkaiy0+DgPPV16+dtG4sQxUCJeMxYlH77LyUyZv5+MnIMlHN34pOhDbG3k3ElwoL0OeoEOnYOcGIZhL8FqTfVY1U6wYjfweGfpwUVBY79BtcPgqMrNH8KfMKsF5vRAKufh6xk8K0CNQuerVuIskQSFGETG05FExmXxtBmIWTqDDzz6yEycgy0quLLF8Ma4+/pfP9ChLif47+DPhsC6sDiJyE7FbwqQtwZ9biLD2SlqOvV7PxEHZSqy4LVL8CJ32+Xc3I5jFsP3pWsE+eG/4NTK/55aucTsJOWQyEkQRFWF5eazXc7IrmamIGPqyOVy7kxa91ZAD7bdAGDUcFgVKgb7Mn8MS2kW0dYRtQxWD4h//64M+oieu0nq10p59bBsrHq4FTvSnDwR7hxCDT20GIiRGyChAvwUz8Y+isE1rdsnImX1LEnAIO+h6qd732+EGWEJCjCqmJSshj+/V4uxqXnOxbo6Wx6jLhKeTe+HdlUkhNhOUcW5t0ObQedXoeESKjREzz/mdag7gA4vgTOr4dVz6r7XHzU1YCrdITkGzC/N9y6DN93hWELoXp3y8W5ew4oRqjWTY1FCAFIgiKsSGcwMnrefi7GpRPs5czTnaqyJzKBdSejGdY8hP8NqE9EXBqezloCPJ1kLhNhOfrs2100g+eBkxdUbq+OMancIe+5Gg0M/E7t4jmzGpw84fH56lgQAK8KMGErrJgEEeGw8U01mXjYz6uiqKsMH/0nkWr78sOVJ0QpIwmKsJqf91zhbHQqfm6OLJnUmhBfV0a1DiMzx2BqKakRIMu9Cys4vx4yb4FHENTpf/8xHc5e0H2G+lUQNz8Y/CN8UhfizsKFjepYlnI11bITIsC3Ktjd8WBk7Fk4NB9iToGDs/rocJWOanKyfAKcWKqeV7E5hLV76NsWojSRBEVYXLbewP5LiXy2SV0n59WeNQnxvb3qtHTjCKvKToNN/yQaDYdbbsCpsxc0GQV758LiEWDUQ3ATcPdXE6Jq3WHYInBwVM8/tQKWjgX+NW/Ulb9hfDgkXVGTEzsHqD8Eurz58C0yQpQykqAIi0rJ0jH4692cj0kDoG6wJ483C7FxVKJUSr4BqVHgFQIeAZAaA8cWqQvqJUaCZwXLT3bW6mnY942anADcPHz7WES4Oti27ydq4rH2P4ACVbuoScixRXBpB/w6CDT/tLS0eRG6vW3ZGIUoJSRBERajKAqvLT3O+Zg0vFy0dK3lz+TuNWQ+E2F5+7+Hda+DYgA0aiJydq2amIC6b+B34Opr2et6V1IHyd66oo5l2fAGZCZCoyfUR4XPrlGf+nHxgYwE8K8Dw5eorSo1esIP3W7H6B4I7adYNj4hShFJUMRDyV31ICI2lffXnWPTmRi09hp+HteChiHeNo1NlEKKApvehr8/V7fd/CE9Fnb/s5aXZ0V1krOwttYb0/HvSdRGrbz9OqCeGtv1A2rLjsYe+n1xu8vH1RcmbYfTq+DyLmg8Ul2lWAhRIElQxAM5eSOZ//5xnAvR9nx8bifXbmUCYG+n4Z3H6klyIqxj58e3k5Nu09UnXw7NV7tTHD3gyT/Av5ZtYgtrq44viTsLKTfUFpLAennPcfKAxk+qX0KIe5IERZjFYFT4dkckn4afR2dQAA3XbmVib6ehc01/Xu9Vk+ryZI6whhuHYMs76uue/4PWz6mvm42DsA7qL3+PANvFB+pAV//a6pcQ4qFIgiIK5eSNZGb8eYqriRnEpGQD0KOOPw0dblKncUsaVfLFx83RxlGKUm3HR+r3+kNuJye5ylUr+niEEFYlCYq4L0VReGvVSQ5fTQLAzdGe6Y/W5bEGAaxbd5N21fzQarW2DVKUbtcOwLm/AA10fM3W0QghioAkKOK+dlyI5/DVJJwc7Jg/pjl1K3jh5aJFp9PZOjRR2kUdg7UvQ8wJdbveQChX3aYhCSGKhiQo4p50BiOfbDwHwJOtQmlTrZyNIxKlXuYtSLhMnRuLcTi+CQw56rwhlVpD95m2jk4IUUQkQRF3ZTAqTPn9GMeuJ+PqaM/THavaOiRRmuWkw+oX4OQfaAFTO0nNvvDoHHW6eSFEmSEJirirebsu8eexmzjYaZj7RBPKezjZOiRRGulz1LlBdn4McWcAUJw8iXUMw6/XqzjU6SfTwAtRBkmCIgpkMCos2H0ZgLf61aFzTX/bBiRKp5SbsPiJ21PGu5WHob+iD2rK3r/+ok+N3pKcCFFGSYIiCrTjfBw3kjLxctEyRNbSEdaQFgffd4XUm+DsDa2eVec0cS8PMgBbiDJPEhRRoIX7rgIwqElFnLWy+rCwgl2fqsmJb1V1BljfyraOSAhRjEiCIvK5GJfGlrMxAIxoWcnG0YhSR5+tdu0c/FHd7vOhJCdCiHwkQRH5zNkSgVGBLrX8qebvbutwRGmSeAm+7QjZyep2SEuo2sW2MQkhiiU7WwcgipeI2DRWHb0BwORuNWwcjSh19n51Ozmxc1AX/JNBsEKIAkgLijDRG4y8sfwERgW61wmgfkUvW4ckSpOsZDi6SH097DcIawfOnraNSQhRbEmCIkw+Dj/P/suJuDs58EYfWY1VPCCjEaKOwPVDENoaAuuDosCeryAnDcrXhpry+LAQ4t4kQREAXIhJ5ZvtkQB8MKgBlcu52TgiUSKlxcLvo+DqHnXb0QP6fQaHf4JLO9R9rZ6W5EQIcV+SoAgAvtoWiaJAjzoB9G0QZOtwREmTlQJHfoHdcyA1CrRu6nwmty7DH+PVc+ydoO1L0HiUTUMVQpQMkqAIriSkmwbGvtBFVooVZkpPgAV9IO6suu1XHYYvBo8A+PkxuHEI6jymLvTnE2bTUIUQJYckKGXc8etJPL/oCEYFOtcsLwNjhSrxEiRGQpUuYGenjiu5cRCij4OjO9QbDDEn4dRyuBCuJiceQdDxNWgwFBz/6SIct0FtUfGW+XSEEOaRBKUM23E+jgk/HyRbb6SijwtvPlLH1iGJ4uDMn7B8IugyoEJTCGoIF7erCUuug/PV9XMMOeq2qx+MWg3l73g03V4ryYkQ4oFYfB6UsLAwNBpNvq/nnnsOgE6dOuU79vTTT1s6DHEfey8m8NQ/yUnnmuVZ+2J7qpaXSdnKvAubYMmTanKCRu2eOThPTU4cPaBad3Bwhmt71eSkSmfo+jZM2JI/ORFCiIdg8RaUAwcOYDAYTNsnT56ke/fuPP7446Z9EyZMYObMmaZtV1dXS4ch7kFRFN5Zc5ocvZHudQKYO6IJjg4yZ1+ZZ9DDhqnq64YjoMubcHQhGPXgUxlq9wMnd7iyB9ZOUWeA7T4T7GStJiGE5Vk8QSlfvnye7ffff5+qVavSsWNH0z5XV1cCAwMtfWlRSLsi4jl1MwUXrT2zBzWQ5KSsMxrVFpFzf0H8eXDxhd7vg7OXOqbkTqGt4dk9RR+nEKJMseoYlJycHH799VemTJmC5l/zHixcuJBff/2VwMBA+vXrx7Rp0+7ZipKdnU12drZpOyUlBQCdTofOwsuy55Zn6XKLi8wcA19svgDA400r4O6oeeB7Le11ZUnFpq6yU7Ff/xqai1tBY4dSoSmkx2F346DpFEP7VzDau4INYy029VUCSF2ZR+qr8KxRV+aUpVEURbHYle/w+++/M2LECK5evUpwcDAA3333HaGhoQQHB3P8+HFef/11WrRowfLly+9azvTp05kxY0a+/YsWLZLuITNEpsC88/ak6TTYaRSmNTbg62TrqERRcc5JpHXkh3hm3ch3TG/nRKJbNVKcQzhdYQiKRsbPCyEsLyMjgxEjRpCcnIyn572XurBqgtKzZ08cHR35888/73rOli1b6Nq1KxEREVStWrXAcwpqQQkJCSE+Pv6+N2gunU5HeHg43bt3R6vVWrRsW1IUhUfn7uFsTBoVvZ15o3ctutfxf6gyS2tdWYPN6yo7FYefH0ETewrFPQDDI3PA2RNNxCYwGjA2G6c+JlxM2Ly+ShCpK/NIfRWeNeoqJSWFcuXKFSpBsdqfSVeuXGHTpk33bBkBaNmyJcA9ExQnJyecnPL/qa/Vaq32AbNm2baw80IcZ2PScHW0Z+2LHfBytdy9lba6siab1JVBByuegthT4OaPZnw4Dj6h6rGw1gAU12Gu8tkqPKkr80h9FZ4l68qccqw2OnL+/Pn4+/vTt2/fe5539OhRAIKCis9fb6XR9zsvATCkWYhFkxNRzCkKrP0PRG4GrSuMWAK5yYkQQhRjVmlBMRqNzJ8/n9GjR+PgcPsSkZGRLFq0iD59+uDn58fx48eZPHkyHTp0oEGDBtYIpcxTFIVPws+z43wcdhoY17ayrUMSRengPHWhPo0dDJ4HFZrYOiIhhCgUqyQomzZt4urVq4wbNy7PfkdHRzZt2sRnn31Geno6ISEhDBo0iDfffNMaYQjgh52XmLMlAoBXetakkp8MKi6RFAX2fwc5adD2ZTi9CnSZ0PiJu78n8SJs/Of/VveZULN3kYQqhBCWYJUEpUePHhQ09jYkJITt27db45KiAEajwoLdlwH4b+9aPN2x4DE+ogQ4/BOs+2dOkgub4Opu9bVXBajSKf/5Bh2seEadETasPbR6rshCFUIIS5BnCUuxfZcSuZGUiYezA2PahNk6HAGQGg23ItTv8efg2n5IiIR+n0PNXrfPMxrg8k4IagRRx+Cvf02YlpucgNpCMnGHWta2WZB0FdzKqwv6XdurTk//2Jfqgn9CCFGCSIJSiv1x+DoAjzQIwllbXJ/TKCN0GdS5sRiHL8eDsYCJiv58CYK3Q+wZCGsH4W/D3rng4AL6TPWc6j0htA1seRcaPwkn/4DoE/DHOIjcAlnJ+csd+B34hFn11oQQwhokQSmlEtNzWHciCoCBTSraOBphv+5Vqsf+pW74VQPPYPCrDoH1YfccdTG+z+qrC/CFtYer/0wln5ucNB0LPd5V18JpOQm0LlCuhrp2zqkV6jkhLdXxKRe3wcll0P4/UKtPUd+qEEJYhCQopZDRqDB5yVHScwzUCHCnWaiPrUMq224exe7EEgD0g+bjUG8A/GvpB7wrwa8D1eQE1K4dUFcO7vRf9Qmcfz99o3VRv7d+FgLqqAmKvSN0mwGOrmpS0md2EdyYEEJYjyQopYzBqK5UvP18HE4OdnwxvHGedZCElRkNkJ0CLj6QngCHF8BJdbLCaz5tCKzVL29yAlCtK/T/GnLS1QX6lk9Qk5LuM9UE5F6qdCp4kKwQQpRwkqCUInqDkUm/HGLz2VgA3u1fj1qBll0KQNzh3Ho1GSlXHVZMgovb1ZaQbtPVbpboEwAo9k6cCR7MXdfwbjTi9mu38mqCcr/kRAghSjFJUEqRJQevsflsLM5aOz56vCGPNAi2dUil25k/YcmT6mvvUEi6cvvYprfV765+0GwchtD2ZJ5MKly5VTtbNEwhhCiJJEEpJdKy9XwafgGA//aqJcmJtaREwS8DwMlDfaQ3V9IVcPaGJ5bBmVXqwFc0MPB7qNYVRaeDk3/ZKmohhChxJEEpBXQGI2+vOkV8WjZhfq6MaClrrViF0ah248Sdub3Ptyq0fg7OrIaub0GFplCxGZSrCe7+6vgSIYQQZpMEpYRLy9Yz8eeD7I5MQKOBN/vWwdFBJuWyin3fwKXt6twkdfvD9YPq4NaQ5tB8/O3zNBpoMtJmYQohRGkgCUoJlpqlY/S8/Ry+moSboz2fDWtMtzoBtg6rdEqNga3vqa97vgvNn7JtPEIIUcpJglJCKYrCC78d4fDVJLxctPw6viX1K3rZOqzSa/NMdaG+4CbQdNz9zxdCCPFQpC+ghFqw+zLbzqlznUhyYmVHF8HRX9XXvWfLujZCCFEEpAWlhFEUhYX7rjLrr7MA/F/f2pKc3E9WsjofiW8V8AjKP1FannNTICtJXWwvNQqO/Qa7v1SPtXpWHW8ihBDC6iRBKWE+DT/PF1siAOjXMJiRreSJnXvKTIJ5PSFOTehw8oSQFtDvC/CqAIqiLtDn4g03j8KycbfXv/m35k9Bz/8VYeBCCFG2SYJSgkQlZ/LNjosAvNarJk93qCrT2N9LTjr8PlJNThxc1Bles1MgYhMsHg7tX1HnK7m+X525FQ0oBvW1YlRbUSo2V5OTWn3v3fIihBDCoiRBKUG+3BJBjt5IizBfnukoyUmBUmPg78/AqFennY8/pyYa49arq/9Gn4BFQyDqmJq8ANhpwahTX9cbDAO+VRMUB0eb3YYQQpR1kqCUEFcTMlhy4BoA/+lRQ5KTglzdC7+PhrTo2/vcA+HxBRBYX92u2Awe/wkWPq6u/Nt4JLR6Rh2nEn8BavYGO3ubhC+EEOI2SVBKiM83X0BvVGhfvRwtq/jZOpziRVFg/3ew4Q215aR8bajeDTT20Pp5cC+f9/zK7eE/Z0HreruVxCMQytcs+tiFEEIUSBKUEiAiNo0VR64D8J8e8ks0nxPLYN1r6uu6A+HROeDkfu/3uHhbPSwhhBAPThKUEmDu1giMCnSvE0CjEG9bh1O8ZCapLScAbV+CbjNkMKsQQpQCMuNUMXcrPYe1x6MAeL5zNRtHUwxt/R+kx4Jfdej8f5KcCCFEKSEJSjH3x+Hr5BiM1KvgSUNpPcnr5lE48L36uu9H4OBk03CEEEJYjiQoxZiiKPy2/yoAw1tUsnE0xYw+G/56RX0cuO5AqNLJ1hEJIYSwIBmDUowduHyLyLh0XLT2PNow2NbhFB/Hf4f1UyEjHhw9ZIZXIYQohSRBKcYW/9N68mjDYDyctTaOpphIjYbVL4A+CzyCoc+H4Blk66iEEEJYmCQoxVRSRg5rTqiDY4e3lO4dk12fqclJxRYwdh3Yy0dYCCFKIxmDUkytOHKDHL2R2kGeNJTVilXJN+DgPPV156mSnAghRCkmCUoxpDcYWbD7MgDDW4TItPYARiOseg4M2VCpNVTpbOuIhBBCWJEkKMXQn8dvciUhAx9XLYObVrR1OMXDvq/h4lZ1VeJ+X8h8J0IIUcpJglLMGI0KX26JAOCp9lVwdZRuDBIiYfNM9XWv/0H5GraNRwghhNVJglLM7LgQR2RcOh7ODoxsHWrrcGxPUeDPl9SBsVU6Q9Oxto5ICCFEEZAEpZj54/ANAAY1qYinPFoMp5bD5Z1q184jn0rXjhBClBEWT1CmT5+ORqPJ81WrVi3T8aysLJ577jn8/Pxwd3dn0KBBxMTEWDqMEiklS8fGU9EADGxSwcbRFAOKAjs/VV+3exl8K9s0HCGEEEXHKi0odevWJSoqyvS1a9cu07HJkyfz559/snTpUrZv387NmzcZOHCgNcIocdadiCJbb6Savzv1K8ijxURuhpgToHWDFhNtHY0QQogiZJURmA4ODgQGBubbn5yczI8//siiRYvo0qULAPPnz6d27drs3buXVq1aFVhednY22dnZpu2UlBQAdDodOp3OorHnlmfpcu8nI0fPN9siAejfMAi9Xl+k138QVq0rowH7re9jBxgaj8So9YAi/jexJFt9rkoqqa/Ck7oyj9RX4VmjrswpS6MoimKxK6N28Xz44Yd4eXnh7OxM69atmTVrFpUqVWLLli107dqVW7du4e3tbXpPaGgoL7/8MpMnT75rmTNmzMi3f9GiRbi6uloyfJtZctGO3TF2eGkVXm9owK2MDz+pFrOGujd/R2/nxObaH5Dl6GvrkIQQQjykjIwMRowYQXJyMp6envc81+ItKC1btmTBggXUrFmTqKgoZsyYQfv27Tl58iTR0dE4OjrmSU4AAgICiI6OvmuZU6dOZcqUKabtlJQUQkJC6NGjx31v0Fw6nY7w8HC6d++OVls0WcKJG8ns3rMPjQa+eKIZbar6Fcl1H5bV6irmFA7zlquve8+mS6MnLFe2jdjic1WSSX0VntSVeaS+Cs8adZXbA1IYFk9QevfubXrdoEEDWrZsSWhoKL///jsuLi4PVKaTkxNOTk759mu1Wqt9wKxZ9p1WH1cHCT/SIJiOtfJ3jRV3Fq+rfXPBqIeafXFoNrpUPblTlJ+r0kDqq/Ckrswj9VV4lqwrc8qx+mPG3t7e1KhRg4iICAIDA8nJySEpKSnPOTExMQWOWSkLDEaFtf8sCti/UbCNoykGUqLg1Ar1dcdXS1VyIoQQovCsnqCkpaURGRlJUFAQTZs2RavVsnnzZtPxc+fOcfXqVVq3bm3tUIqlfRcTiEvNxstFS/vq5W0dju0d+AGMOghpBcGNbR2NEEIIG7F4F88rr7xCv379CA0N5ebNm7z99tvY29szfPhwvLy8GD9+PFOmTMHX1xdPT09eeOEFWrdufdcneEq7VUdvAtCnfiCODmV03rzMJLh+AM6tu71acaunbRqSEEII27J4gnL9+nWGDx9OQkIC5cuXp127duzdu5fy5dXWgU8//RQ7OzsGDRpEdnY2PXv25KuvvrJ0GCXCrfQcVh1TZ47t36gMTsymz4bts2HfN5CTdnt/07FQ+1HbxSWEEMLmLJ6gLF68+J7HnZ2dmTt3LnPnzrX0pUucX/deIUtnpG6wJy0ql8HHaNe9Dofmq699wiCoETQdDVW72DIqIYQQxYAslWsjWToDP+25AsCE9lXQlObBoLpMOPkHVGoNflXVKexPLLudnAz4FuoPAbsy2sUlhBAiH0lQbGTbuVji07IJ9HSmb4MgW4djPYoCK59VF/2z00Ll9hB3HlKuq8fbvAANh9k2RiGEEMWOJCg2En46FoC+DYLQ2pfAloPkG2huHsMr4/K9zzvwg5qcgPp0TuQW9bXWFeoPhi7TrBqmEEKIkkkSFBswGBW2nlMTlG61A2wczQPY8SFseQ8HFDpgh/FSPajQUB3o6hN2+7wDP8Bfr6qve86CgLoQfx7KVYeKLcCxdCxTIIQQwvIkQbGBI1dvkZieg5eLlmZhPrYO594URU00Ei+Bb2VIiFCfugEU9wDs0mLQLBulPpFj1EG5mmoCkngJYk+pZTQbB62eUSddq9LRhjcjhBCipJAExQbCz6hT23euWb54d+8oCmx8E/Z8mf9YpzfQt3iGtC874JNxSd2nsYP4c+oXgJ0DdHwdOsiMsEIIIcwjCYoNbDqtJihdi2v3jtEI4dPg2GLIiFf3NRgG2ang5KEOdG30BOj17Ksyhe4+V7Gv1gX8a8PlXZAaDU6eUKMHuBTzFiIhhBDFkiQoRSwyLo3IuHS09ho61SymU9vv+uR2q4nWDXq/D01GFXhqttYLY4fXsc9dAKp2vyIKUgghRGkmCUoRC/+n9aR11XJ4OBeTlTQvboO/Pwf/OmDQwYHv1f29PlDHjzg42jQ8IYQQZY8kKEVs46loAHrUKSbdO2f+hGXjwJBz+xFgULtwZD0cIYQQNiIJShGKTc3iyLUkALoXhwTl2BJY+QwoBqjRCzyDAQ1U7iBdNUIIIWxKEpQitPlMLIoCDUO8CfB0tm0wp1bCikmAoraW9PsC7OXjIIQQongoxs+4lj7FpntHn6M+PoyijjF59EtJToQQQhQrkqAUkbRsPX9HJADFIEE58gskXwP3QOj5P1mkTwghRLEjfzYXkR3n48gxGKlczo1q/u5FH0DsGYg6pk41f/CfVYTbTwGtS9HHIoQQQtyHJChFJLd7p3udADRFPatq7Bn4toP6pE6ucjWhyeiijUMIIYQoJElQisi+S4kART85m6LA2v+oyYlfNajQDKp1hZp9QGvjgbpCCCHEXUiCUgRiU7KISs7CTgMNK3oX7cWPLYYrf4PWFUauAO9KRXt9IYQQ4gHI6MgicOx6MgDV/T1wcyrCnDA1Gtb/V33d4VVJToQQQpQYkqAUgWP/TM7WoKJX0V3UaIDVL0JWEgQ1gjYvFN21hRBCiIckCUoROHY9CVAnaLM6RYG0WHX6+gsbwN4R+n8N9sVk3R8hhBCiEGQMipUpisLxf7p4Glk7QUm6Br8Ng5iT6radFgZ8CwF1rHtdIYQQwsIkQbGiP4/dZNG+qyRn6nB0sKNmoIf1LpYWB7/0h4QIQAPla0LvD6BKJ+tdUwghhLASSVCs5FpiBq8sPUa23ghA8zAftPZW6lFTFFg+QU1OvEJg7DrwDrHOtYQQQogiIAmKlcz48zTZeiNNQ30Y1TqUttXKWe9ixxbDxa3g4AxP/iHJiRBCiBJPEhQr2Hwmhk1nYnCw0/D+wPpUD7Bi186Nw7cfJe70X7VrRwghhCjh5CkeC8vSGZj+5ykAxrerbL3kRFHg0E8wv7f6KHFwE2j9vHWuJYQQQhQxaUGxsK+2RnAtMZMgL2de7FrdOhfRZ8OSkepjxADVe8KgH+RRYiGEEKWGJCgWtPdiAl9ujQBg2iN1rDdr7IEf1OTEwRk6/x+0fg7s7K1zLSGEEMIGJEGxkOjkLF787QhGBQY2rkDveoHWuVDmLdg+W33d50NoMso61xFCCCFsSMagWEB0chbDv99LbGo21f3deXdAPTQajXUutuU9dcyJfx1o9IR1riGEEELYmCQoD8loVJj4y0EuxadT0ceF+WOb4+popYap06vhwPfq657vSbeOEEKIUsviCcqsWbNo3rw5Hh4e+Pv7079/f86dO5fnnE6dOqHRaPJ8Pf3005YOpUgsO3Sd49eT8XBy4LcJrajo42r5ixj0sO87WPmMut3mRajaxfLXEUIIIYoJi/+pv337dp577jmaN2+OXq/njTfeoEePHpw+fRo3NzfTeRMmTGDmzJmmbVdXK/xit7LULB2zN6jJ14tdqxPia4V7yMmAxSPUidgAKneArm9Z/jpCCCFEMWLxBGX9+vV5thcsWIC/vz+HDh2iQ4cOpv2urq4EBlppIGkR+d9fZ4lPy6ZyOTdGtwmz/AUMelg8HC5uA60b9JgJTcaAvYxtFkIIUbpZ/TddcrK6kq+vr2+e/QsXLuTXX38lMDCQfv36MW3atLu2omRnZ5OdnW3aTklJAUCn06HT6Swab2559yt32/k4ftt/FYB3Hq2NRjGg0xksGovm7J84XNyG4uiGYdgSlJBWYFTAaNl7flCFrSshdWUuqa/Ck7oyj9RX4VmjrswpS6MoimKxK9/BaDTy6KOPkpSUxK5du0z7v/vuO0JDQwkODub48eO8/vrrtGjRguXLlxdYzvTp05kxY0a+/YsWLbJJ15BRgfeO2BOfraFTkJEBYUarXKfFxU8JSj7C+YBHOBM8xCrXEEIIIYpKRkYGI0aMIDk5GU9Pz3uea9UE5ZlnnmHdunXs2rWLihUr3vW8LVu20LVrVyIiIqhatWq+4wW1oISEhBAfH3/fGzSXTqcjPDyc7t27o9UWPDPrzoh4xv10GA9nB3a92sE6T+2kx+PwRT00Rj26iX8XyzV2ClNXQiV1ZR6pr8KTujKP1FfhWaOuUlJSKFeuXKESFKt18Tz//POsWbOGHTt23DM5AWjZsiXAXRMUJycnnJyc8u3XarVW+4Ddq+wlB28AMKhJRbzcXKxyfc6uAqMeghujDa5nnWtYiDX/HUobqSvzSH0VntSVeaS+Cs+SdWVOORZPUBRF4YUXXmDFihVs27aNypUr3/c9R48eBSAoKMjS4VhcTEoWm87EAjCiZSXrXejEUvV7g2HWu4YQQghRTFk8QXnuuedYtGgRq1atwsPDg+joaAC8vLxwcXEhMjKSRYsW0adPH/z8/Dh+/DiTJ0+mQ4cONGjQwNLhWNzvB65hMCo0D/OhhrVWKk66BjcOAhqoO8A61xBCCCGKMYsnKF9//TWgTsb2b/Pnz2fMmDE4OjqyadMmPvvsM9LT0wkJCWHQoEG8+eablg7F4gxGxfTkzhMtQ613oTN/qt9D24BHgPWuI4QQQhRTVuniuZeQkBC2b99u6csWie3nY7mZnIWPq5Ze1loMEOD0KvV7ncesdw0hhBCiGJO1eMywaJ/aejKoSUWctVZaBychEq7tVV/X7medawghhBDFnCQohZScqWPbuTgAhrUIsc5F9NmwbJz6ukpn8Ay2znWEEEKIYk4SlELaejYWvVGhur871fytNDg2/C2IOgouvvDYl9a5hhBCCFECSIJSSBtOqU8j9axrpbEnF7fDvm/U1wO+Ba97zx0jhBBClGaSoBRCls5g6t6xSoKSnQarnldfNxsHNXpY/hpCCCFECSIJSiHsjownU2eggrcL9SpYdmp9AI4uhOSr4FUJus+0fPlCCCFECSMJSiGcvqmuntyysi8ajcayhRuNsP879XWbF8DJSuNbhBBCiBJEEpRCiIxLB6Cqv7vlC7+4FRIiwNEDGg23fPlCCCFECSQJSiFExqUBULW8FRKU3NaTRiOk9UQIIYT4hyQo96EoChdzW1DKu1m28MRLcH6D+rrFRMuWLYQQQpRgkqDcR2xqNmnZeuztNFTyc7Vs4Qd+ABSo2hXKVbNs2UIIIUQJJgnKfeR274T4uODkYMHp7bPT4Mgv6uuWkyxXrhBCCFEKSIJyH6YBspYefxL+FmQlg28VqNbdsmULIYQQJZwkKPcRGfvPAFlLPsFzbh0c/FF93fdjsJN/BiGEEOLf5DfjfVyMV1tQqpSz0ADZzFuw+kX1devnoWoXy5QrhBBClCKSoNxDXGo2R67eAqCapVpQwt+C9FgoVwO6vmWZMoUQQohSRhKUe5j+5ylSs/TUCfKkUYj3wxd4ZQ8c/ll93e8LcHB6+DKFEEKIUkgSlLvYczGBtcejsLfTMHtwAxzsH7KqjAZY95r6usloCG398EEKIYQQpZQkKHex4VQsAI83rUi9Cl4PX+DRhRB9HJy8pGtHCCGEuA9JUO5iV0QCAF1rBzx8YUYDbJ+tvu70OriVe/gyhRBCiFJMEpQCxGfBlcQMHOw0tKri+/AFnl8PydfAxReajXv48oQQQohSThKUApxL1gDQpJIPHs7ahy9w//fq9yYjQevy8OUJIYQQpZyDrQMojs4mqQlK++oP0RWTkQhrp8CZNWDUARppPRFCCCEKSRKUAlxOVROUNtUeMEFJiISfHoWU67f3NRgKPmEPH5wQQghRBkiCcodsvZEUnZqgPNDssenx8OsgNTnxrQL9vwHfyuBW3sKRCiGEEKWXJCh3iE7JAsBFa4e36wOMP1k+EW5dAu9KMG4DuPtbOEIhhBCi9JNBsneISlITlCAvZzQajXlvvrwLIjeDnRaeWCbJiRBCCPGAJEG5w83kTACCvB7gaZuts9TvTUZB+ZoWjEoIIYQoWyRBuUNUcjagtqCY5fhSuLIL7B2h/X+sEJkQQghRdsgYlDtE/dOCEny/BCX2jDoBW0YiKEbY9626v/Xz4FXBylEKIYQQpZskKHe4+c8YlMCCEpTMJIg/D9f2w+YZYMjJe7zuAOgyzfpBCiGEEKWcJCh3iEpWE5Rg738SlJtH4MQyiDoGV/eAUX/75LD2ENgAFAN4BkPLp8FOes2EEEKIhyUJyr8oinI7QfFyBl0m/DoYMuJvn+RZEdz8oOEIaDkJzH3SRwghhBD3ZdM/9+fOnUtYWBjOzs60bNmS/fv32zIcUrL0pOcYAAj0dIZjv6nJiWcF6PcFvHgEppyCSTug1dOSnAghhBBWYrMEZcmSJUyZMoW3336bw4cP07BhQ3r27ElsbKytQuJmkjpA1s1BwUWrgT1z1QNtXoCmo9WZYYUQQghhdTbr4vnkk0+YMGECY8eOBeCbb75h7dq1zJs3j//+9795zs3OziY7O9u0nZKSAoBOp0On01ksppRzO3nL4Wc8tAp28z+GhAgUZy/09YaCBa9TWuTWvSX/DUorqSvzSH0VntSVeaS+Cs8adWVOWRpFURSLXbmQcnJycHV1ZdmyZfTv39+0f/To0SQlJbFq1ao850+fPp0ZM2bkK2fRokW4urpaLC7dxa0MTp5v2jZix/GQ0Vwp19li1xBCCCHKqoyMDEaMGEFycjKenp73PNcmLSjx8fEYDAYCAgLy7A8ICODs2bP5zp86dSpTpkwxbaekpBASEkKPHj3ue4PmuHDUg92HDeSkJdGmRXM09QZS1z2Auha7Qumi0+kIDw+ne/fuaLUPsG5RGSJ1ZR6pr8KTujKP1FfhWaOucntACqNEPMXj5OSEk5NTvv1ardaiH7A6zbuga9Sev/76C02rPv/f3t3GtFW+YQC/WqSVyUqHBdrKQNgmy+RFZdI0xmmk4SWLQecHnHzAl2zZhETdXNxMBPULy0yML1nmBxPxg9l0Rlxc3CLC6DLtUBDCXpQMUkUdBWUBOhjjpbcf/HNiB4OSP/ScrdcvaQLneTi7z8Vz4KY8rFy8IVrsz8PNjFktDPMKHbNaGOYVusXMaiHnUWWTrMViQVRUFPr6+oKO9/X1wWq1qlESERERaYgqDYrBYEBubi4aGhqUY4FAAA0NDXA6nWqURERERBqi2q94duzYgfLycqxfvx55eXl45513MDIyovxVDxEREUUu1RqU0tJS/PXXX6iqqoLP58M999yD48ePz9g4S0RERJFH1U2ylZWVqKysVLMEIiIi0iC+sh0RERFpDhsUIiIi0hw2KERERKQ5bFCIiIhIc9igEBERkeawQSEiIiLNYYNCREREmsMGhYiIiDTnhng142uJCICFvWxzqCYmJjA6Oorh4WG+0uU8mFXomNXCMK/QMauFYV6hW4qspr9vT38fn8sN2aD4/X4AwMqVK1WuhIiIiBbK7/cjLi5uzjk6CaWN0ZhAIICLFy9i+fLl0Ol0i3ru4eFhrFy5Er///jtMJtOinvtmw6xCx6wWhnmFjlktDPMK3VJkJSLw+/2w2+3Q6+feZXJDPoOi1+uRnJy8pP+GyWTi4g0Rswods1oY5hU6ZrUwzCt0i53VfM+cTOMmWSIiItIcNihERESkOWxQrmE0GlFdXQ2j0ah2KZrHrELHrBaGeYWOWS0M8wqd2lndkJtkiYiI6ObGZ1CIiIhIc9igEBERkeawQSEiIiLNYYNCREREmsMGhYiIiDSHDcp/7N+/H3feeSduvfVWOBwO/PDDD2qXpLrXX38dOp0u6LF27VplfGxsDBUVFbj99tsRGxuLJ554An19fSpWHF4nT57Eo48+CrvdDp1Ohy+//DJoXERQVVUFm82GmJgYuFwuXLhwIWjOpUuXUFZWBpPJBLPZjOeeew6XL18O41WEx3xZPf300zPWWlFRUdCcSMmqpqYG999/P5YvX47ExEQ89thj6OzsDJoTyr3X09ODjRs3YtmyZUhMTMSuXbswOTkZzksJi1Dyevjhh2esr23btgXNiYS8Dhw4gOzsbOV/h3U6nTh27JgyrqV1xQblfz799FPs2LED1dXV+Omnn5CTk4PCwkL09/erXZrq7r77bvT29iqPU6dOKWMvvfQSvvrqKxw+fBhutxsXL17Epk2bVKw2vEZGRpCTk4P9+/fPOr5v3z689957+OCDD9Dc3IzbbrsNhYWFGBsbU+aUlZXh3LlzqK+vx9GjR3Hy5Els3bo1XJcQNvNlBQBFRUVBa+3gwYNB45GSldvtRkVFBU6fPo36+npMTEygoKAAIyMjypz57r2pqSls3LgR4+Pj+P777/Hxxx+jtrYWVVVValzSkgolLwDYsmVL0Prat2+fMhYpeSUnJ2Pv3r1obW1FS0sLHnnkEZSUlODcuXMANLauhEREJC8vTyoqKpT3p6amxG63S01NjYpVqa+6ulpycnJmHRscHJTo6Gg5fPiwcuznn38WAOLxeMJUoXYAkLq6OuX9QCAgVqtV3nrrLeXY4OCgGI1GOXjwoIiInD9/XgDIjz/+qMw5duyY6HQ6+fPPP8NWe7hdm5WISHl5uZSUlFz3YyI1KxGR/v5+ASBut1tEQrv3vv76a9Hr9eLz+ZQ5Bw4cEJPJJFevXg3vBYTZtXmJiDz00EPywgsvXPdjIjmvFStWyIcffqi5dcVnUACMj4+jtbUVLpdLOabX6+FyueDxeFSsTBsuXLgAu92O9PR0lJWVoaenBwDQ2tqKiYmJoNzWrl2LlJQU5gbA6/XC5/MF5RMXFweHw6Hk4/F4YDabsX79emWOy+WCXq9Hc3Nz2GtWW1NTExITE5GRkYHt27djYGBAGYvkrIaGhgAA8fHxAEK79zweD7KyspCUlKTMKSwsxPDwsPLT8s3q2rymffLJJ7BYLMjMzMSePXswOjqqjEViXlNTUzh06BBGRkbgdDo1t65uyFczXmx///03pqamggIHgKSkJPzyyy8qVaUNDocDtbW1yMjIQG9vL9544w08+OCDOHv2LHw+HwwGA8xmc9DHJCUlwefzqVOwhkxnMNu6mh7z+XxITEwMGr/lllsQHx8fcRkWFRVh06ZNSEtLQ3d3N1599VUUFxfD4/EgKioqYrMKBAJ48cUX8cADDyAzMxMAQrr3fD7frGtveuxmNVteAPDUU08hNTUVdrsdHR0deOWVV9DZ2YkvvvgCQGTldebMGTidToyNjSE2NhZ1dXVYt24d2tvbNbWu2KDQnIqLi5W3s7Oz4XA4kJqais8++wwxMTEqVkY3myeffFJ5OysrC9nZ2Vi1ahWampqQn5+vYmXqqqiowNmzZ4P2ftH1XS+v/+5VysrKgs1mQ35+Prq7u7Fq1apwl6mqjIwMtLe3Y2hoCJ9//jnKy8vhdrvVLmsG/ooHgMViQVRU1Iydyn19fbBarSpVpU1msxl33XUXurq6YLVaMT4+jsHBwaA5zO1f0xnMta6sVuuMjdiTk5O4dOlSxGeYnp4Oi8WCrq4uAJGZVWVlJY4ePYoTJ04gOTlZOR7KvWe1Wmdde9NjN6Pr5TUbh8MBAEHrK1LyMhgMWL16NXJzc1FTU4OcnBy8++67mltXbFDw7ycrNzcXDQ0NyrFAIICGhgY4nU4VK9Oey5cvo7u7GzabDbm5uYiOjg7KrbOzEz09PcwNQFpaGqxWa1A+w8PDaG5uVvJxOp0YHBxEa2urMqexsRGBQED5Ahqp/vjjDwwMDMBmswGIrKxEBJWVlairq0NjYyPS0tKCxkO595xOJ86cORPU1NXX18NkMmHdunXhuZAwmS+v2bS3twNA0PqKlLyuFQgEcPXqVe2tq0XdcnsDO3TokBiNRqmtrZXz58/L1q1bxWw2B+1UjkQ7d+6UpqYm8Xq98t1334nL5RKLxSL9/f0iIrJt2zZJSUmRxsZGaWlpEafTKU6nU+Wqw8fv90tbW5u0tbUJAHn77belra1NfvvtNxER2bt3r5jNZjly5Ih0dHRISUmJpKWlyZUrV5RzFBUVyb333ivNzc1y6tQpWbNmjWzevFmtS1oyc2Xl9/vl5ZdfFo/HI16vV7799lu57777ZM2aNTI2NqacI1Ky2r59u8TFxUlTU5P09vYqj9HRUWXOfPfe5OSkZGZmSkFBgbS3t8vx48clISFB9uzZo8YlLan58urq6pI333xTWlpaxOv1ypEjRyQ9PV02bNignCNS8tq9e7e43W7xer3S0dEhu3fvFp1OJ998842IaGtdsUH5j/fff19SUlLEYDBIXl6enD59Wu2SVFdaWio2m00MBoPccccdUlpaKl1dXcr4lStX5Pnnn5cVK1bIsmXL5PHHH5fe3l4VKw6vEydOCIAZj/LychH590+NX3vtNUlKShKj0Sj5+fnS2dkZdI6BgQHZvHmzxMbGislkkmeeeUb8fr8KV7O05spqdHRUCgoKJCEhQaKjoyU1NVW2bNky4weESMlqtpwAyEcffaTMCeXe+/XXX6W4uFhiYmLEYrHIzp07ZWJiIsxXs/Tmy6unp0c2bNgg8fHxYjQaZfXq1bJr1y4ZGhoKOk8k5PXss89KamqqGAwGSUhIkPz8fKU5EdHWutKJiCzuczJERERE/x/uQSEiIiLNYYNCREREmsMGhYiIiDSHDQoRERFpDhsUIiIi0hw2KERERKQ5bFCIiIhIc9igEBERkeawQSEiIiLNYYNCREREmsMGhYiIiDTnH/UCKHX9BP0mAAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from fsrs_optimizer import lineToTensor, FSRS\n",
        "import torch\n",
        "from tqdm.auto import tqdm\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "class Collection:\n",
        "    def __init__(self):\n",
        "        self.model = FSRS(w)\n",
        "        self.model.eval()\n",
        "\n",
        "    def states(self, t_history, r_history):\n",
        "        with torch.no_grad():\n",
        "            line_tensor = lineToTensor(\n",
        "                list(zip([str(t_history)], [str(r_history)]))[0]\n",
        "            ).unsqueeze(1)\n",
        "            output_t = self.model(line_tensor)\n",
        "            return output_t[-1][0]\n",
        "\n",
        "    def next_states(self, states, t, r):\n",
        "        with torch.no_grad():\n",
        "            return self.model.step(torch.FloatTensor([[t, r]]), states.unsqueeze(0))[0]\n",
        "\n",
        "    def init(self):\n",
        "        t = 0\n",
        "        r = generate_rating(\"new\")\n",
        "        p = round(first_rating_prob[r - 1], 2)\n",
        "        new_states = self.states(t, r)\n",
        "        return r, t, p, new_states\n",
        "\n",
        "\n",
        "feature_list = [\n",
        "    \"difficulty\",\n",
        "    \"stability\",\n",
        "    \"retrievability\",\n",
        "    \"delta_t\",\n",
        "    \"reps\",\n",
        "    \"lapses\",\n",
        "    \"last_date\",\n",
        "    \"due\",\n",
        "    \"r_history\",\n",
        "    \"t_history\",\n",
        "    \"p_history\",\n",
        "    \"states\",\n",
        "    \"time\",\n",
        "    \"factor\",\n",
        "]\n",
        "field_map = {key: i for i, key in enumerate(feature_list)}\n",
        "\n",
        "\n",
        "def fsrs4anki_scheduler(stability):\n",
        "    def constrain_interval(stability):\n",
        "        if stability > 0:\n",
        "            return min(\n",
        "                max(1, round(9 * stability * (1 / requestRetention - 1))),\n",
        "                maximumInterval,\n",
        "            )\n",
        "        else:\n",
        "            return 1\n",
        "\n",
        "    interval = constrain_interval(stability)\n",
        "    return interval\n",
        "\n",
        "\n",
        "def anki_scheduler(interval, real_interval, factor, rating):\n",
        "    if factor is None:\n",
        "        return (graduatingInterval, 2.5) if rating != 4 else (easyInterval, 2.5)\n",
        "    delay = real_interval - interval\n",
        "    again_interval = min(\n",
        "        max(round(interval * newInterval * intervalModifier + 0.01), minimumInterval),\n",
        "        maximumInterval,\n",
        "    )\n",
        "    hard_interval = min(\n",
        "        max(\n",
        "            round(interval * hardInterval * intervalModifier + 0.01),\n",
        "            interval + 1,\n",
        "            minimumInterval,\n",
        "        ),\n",
        "        maximumInterval,\n",
        "    )\n",
        "    good_interval = min(\n",
        "        max(\n",
        "            round((interval + delay / 2) * factor * intervalModifier + 0.01),\n",
        "            hard_interval + 1,\n",
        "            minimumInterval,\n",
        "        ),\n",
        "        maximumInterval,\n",
        "    )\n",
        "    easy_interval = min(\n",
        "        max(\n",
        "            round(real_interval * factor * intervalModifier * easyBonus + 0.01),\n",
        "            good_interval + 1,\n",
        "            minimumInterval,\n",
        "        ),\n",
        "        maximumInterval,\n",
        "    )\n",
        "    if rating == 1:\n",
        "        return again_interval, max(factor - 0.2, 1.3)\n",
        "    if rating == 2:\n",
        "        return hard_interval, max(factor - 0.15, 1.3)\n",
        "    if rating == 3:\n",
        "        return good_interval, max(factor, 1.3)\n",
        "    if rating == 4:\n",
        "        return easy_interval, max(factor + 0.15, 1.3)\n",
        "    return maximumInterval, factor\n",
        "\n",
        "\n",
        "def scheduler(scheduler_name, fsrs_inputs, anki_inputs):\n",
        "    if scheduler_name == \"anki\":\n",
        "        return anki_scheduler(*anki_inputs)\n",
        "    elif scheduler_name == \"fsrs\":\n",
        "        return fsrs4anki_scheduler(fsrs_inputs), 2.5\n",
        "    return None\n",
        "\n",
        "\n",
        "for scheduler_name in schedulers:\n",
        "    new_card_per_day = np.array([0] * learn_days)\n",
        "    new_card_per_day_average_per_period = np.array([0.0] * learn_days)\n",
        "    review_card_per_day = np.array([0.0] * learn_days)\n",
        "    review_card_per_day_average_per_period = np.array([0.0] * learn_days)\n",
        "    time_per_day = np.array([0.0] * learn_days)\n",
        "    time_per_day_average_per_period = np.array([0.0] * learn_days)\n",
        "    learned_per_day = np.array([0.0] * learn_days)\n",
        "    retention_per_day = np.array([0.0] * learn_days)\n",
        "    expected_memorization_per_day = np.array([0.0] * learn_days)\n",
        "\n",
        "    card = pd.DataFrame(\n",
        "        np.zeros((deck_size, len(feature_list))),\n",
        "        index=range(deck_size),\n",
        "        columns=feature_list,\n",
        "    )\n",
        "    card[\"states\"] = card[\"states\"].astype(object)\n",
        "\n",
        "    card[\"r_history\"] = card[\"r_history\"].astype(str)\n",
        "    card[\"t_history\"] = card[\"t_history\"].astype(str)\n",
        "    card[\"p_history\"] = card[\"p_history\"].astype(str)\n",
        "    card[\"reps\"] = 0\n",
        "    card[\"lapses\"] = 0\n",
        "    card[\"due\"] = learn_days\n",
        "\n",
        "    student = Collection()\n",
        "    random.seed(2022)\n",
        "    for day in tqdm(range(learn_days)):\n",
        "        reviewed = 0\n",
        "        learned = 0\n",
        "        review_time_today = 0\n",
        "        learn_time_today = 0\n",
        "\n",
        "        card[\"delta_t\"] = day - card[\"last_date\"]\n",
        "        card[\"retrievability\"] = np.power(\n",
        "            1 + card[\"delta_t\"] / (9 * card[\"stability\"]), -1\n",
        "        )\n",
        "        need_review = (\n",
        "            card[card[\"due\"] <= day]\n",
        "            if leechSuspend == False\n",
        "            else card[(card[\"due\"] <= day) & (card[\"lapses\"] < leechThreshold)]\n",
        "        )\n",
        "        retention_per_day[day] = need_review[\"retrievability\"].mean()\n",
        "        for idx in need_review.index:\n",
        "            if (\n",
        "                reviewed >= review_limits\n",
        "                or review_time_today + learn_time_today >= max_time_limts\n",
        "            ):\n",
        "                break\n",
        "\n",
        "            reviewed += 1\n",
        "            last_date = card.iat[idx, field_map[\"last_date\"]]\n",
        "            due = card.iat[idx, field_map[\"due\"]]\n",
        "            factor = card.iat[idx, field_map[\"factor\"]]\n",
        "            card.iat[idx, field_map[\"last_date\"]] = day\n",
        "            ivl = card.iat[idx, field_map[\"delta_t\"]]\n",
        "            card.iat[idx, field_map[\"t_history\"]] += f\",{ivl}\"\n",
        "\n",
        "            stability = card.iat[idx, field_map[\"stability\"]]\n",
        "            retrievability = card.iat[idx, field_map[\"retrievability\"]]\n",
        "            card.iat[idx, field_map[\"p_history\"]] += f\",{retrievability:.2f}\"\n",
        "            reps = card.iat[idx, field_map[\"reps\"]]\n",
        "            lapses = card.iat[idx, field_map[\"lapses\"]]\n",
        "            states = card.iat[idx, field_map[\"states\"]]\n",
        "\n",
        "            if random.random() < retrievability:\n",
        "                rating = generate_rating(\"recall\")\n",
        "                recall_time = recall_costs[rating - 2]\n",
        "                review_time_today += recall_time\n",
        "                card.iat[idx, field_map[\"r_history\"]] += f\",{rating}\"\n",
        "                new_states = student.next_states(states, ivl, rating)\n",
        "                new_stability = float(new_states[0])\n",
        "                new_difficulty = float(new_states[1])\n",
        "                card.iat[idx, field_map[\"stability\"]] = new_stability\n",
        "                card.iat[idx, field_map[\"difficulty\"]] = new_difficulty\n",
        "                card.iat[idx, field_map[\"states\"]] = new_states\n",
        "                card.iat[idx, field_map[\"reps\"]] = reps + 1\n",
        "                card.iat[idx, field_map[\"time\"]] += recall_time\n",
        "\n",
        "                delta_t, factor = scheduler(\n",
        "                    scheduler_name,\n",
        "                    new_stability,\n",
        "                    (due - last_date, ivl, factor, rating),\n",
        "                )\n",
        "                card.iat[idx, field_map[\"factor\"]] = factor\n",
        "                card.iat[idx, field_map[\"due\"]] = day + delta_t\n",
        "\n",
        "            else:\n",
        "                review_time_today += forget_cost\n",
        "\n",
        "                rating = 1\n",
        "                card.iat[idx, field_map[\"r_history\"]] += f\",{rating}\"\n",
        "\n",
        "                new_states = student.next_states(states, ivl, 1)\n",
        "                new_stability = float(new_states[0])\n",
        "                new_difficulty = float(new_states[1])\n",
        "\n",
        "                card.iat[idx, field_map[\"stability\"]] = new_stability\n",
        "                card.iat[idx, field_map[\"difficulty\"]] = new_difficulty\n",
        "                card.iat[idx, field_map[\"states\"]] = new_states\n",
        "\n",
        "                reps = 0\n",
        "                lapses = lapses + 1\n",
        "\n",
        "                card.iat[idx, field_map[\"reps\"]] = reps\n",
        "                card.iat[idx, field_map[\"lapses\"]] = lapses\n",
        "\n",
        "                delta_t, factor = scheduler(\n",
        "                    scheduler_name,\n",
        "                    new_stability,\n",
        "                    (due - last_date, ivl, factor, rating),\n",
        "                )\n",
        "                card.iat[idx, field_map[\"due\"]] = day + delta_t\n",
        "                card.iat[idx, field_map[\"factor\"]] = factor\n",
        "                card.iat[idx, field_map[\"time\"]] += forget_cost\n",
        "\n",
        "        need_learn = card[card[\"stability\"] == 0]\n",
        "\n",
        "        for idx in need_learn.index:\n",
        "            if (\n",
        "                learned >= new_cards_limits\n",
        "                or review_time_today + learn_time_today >= max_time_limts\n",
        "            ):\n",
        "                break\n",
        "            learned += 1\n",
        "            learn_time_today += learn_cost\n",
        "            card.iat[idx, field_map[\"last_date\"]] = day\n",
        "\n",
        "            card.iat[idx, field_map[\"reps\"]] = 1\n",
        "            card.iat[idx, field_map[\"lapses\"]] = 0\n",
        "\n",
        "            r, t, p, new_states = student.init()\n",
        "            new_stability = float(new_states[0])\n",
        "            new_difficulty = float(new_states[1])\n",
        "\n",
        "            card.iat[idx, field_map[\"r_history\"]] = str(r)\n",
        "            card.iat[idx, field_map[\"t_history\"]] = str(t)\n",
        "            card.iat[idx, field_map[\"p_history\"]] = str(p)\n",
        "            card.iat[idx, field_map[\"stability\"]] = new_stability\n",
        "            card.iat[idx, field_map[\"difficulty\"]] = new_difficulty\n",
        "            card.iat[idx, field_map[\"states\"]] = new_states\n",
        "\n",
        "            delta_t, factor = scheduler(\n",
        "                scheduler_name, new_stability, (None, None, None, r)\n",
        "            )\n",
        "            card.iat[idx, field_map[\"due\"]] = day + delta_t\n",
        "            card.iat[idx, field_map[\"time\"]] = learn_cost\n",
        "            card.iat[idx, field_map[\"factor\"]] = factor\n",
        "\n",
        "        new_card_per_day[day] = learned\n",
        "        review_card_per_day[day] = reviewed\n",
        "        learned_per_day[day] = learned_per_day[day - 1] + learned\n",
        "        time_per_day[day] = review_time_today + learn_time_today\n",
        "        expected_memorization_per_day[day] = sum(\n",
        "            card[card[\"retrievability\"] > 0][\"retrievability\"]\n",
        "        )\n",
        "\n",
        "        if day >= moving_average_period:\n",
        "            new_card_per_day_average_per_period[day] = np.true_divide(\n",
        "                new_card_per_day[day - moving_average_period: day].sum(),\n",
        "                moving_average_period,\n",
        "            )\n",
        "            review_card_per_day_average_per_period[day] = np.true_divide(\n",
        "                review_card_per_day[day - moving_average_period: day].sum(),\n",
        "                moving_average_period,\n",
        "            )\n",
        "            time_per_day_average_per_period[day] = np.true_divide(\n",
        "                time_per_day[day - moving_average_period: day].sum(),\n",
        "                moving_average_period,\n",
        "            )\n",
        "        else:\n",
        "            new_card_per_day_average_per_period[day] = np.true_divide(\n",
        "                new_card_per_day[: day + 1].sum(), day + 1\n",
        "            )\n",
        "            review_card_per_day_average_per_period[day] = np.true_divide(\n",
        "                review_card_per_day[: day + 1].sum(), day + 1\n",
        "            )\n",
        "            time_per_day_average_per_period[day] = np.true_divide(\n",
        "                time_per_day[: day + 1].sum(), day + 1\n",
        "            )\n",
        "\n",
        "    total_learned = sum(new_card_per_day)\n",
        "    total_time = sum(time_per_day)\n",
        "    total_remembered = int(card[\"retrievability\"].sum())\n",
        "    total_leeches = len(card[card[\"lapses\"] >= leechThreshold])\n",
        "\n",
        "    plt.figure(1)\n",
        "    plt.plot(review_card_per_day_average_per_period, label=f\"{scheduler_name}\")\n",
        "    plt.figure(2)\n",
        "    plt.plot(time_per_day_average_per_period / 60, label=f\"{scheduler_name}\")\n",
        "    plt.figure(3)\n",
        "    plt.plot(learned_per_day, label=f\"{scheduler_name}\")\n",
        "    plt.figure(4)\n",
        "    plt.plot(retention_per_day, label=f\"{scheduler_name}\")\n",
        "    plt.figure(5)\n",
        "    plt.plot(expected_memorization_per_day, label=f\"{scheduler_name}\")\n",
        "\n",
        "    print(\"scheduler:\", scheduler_name)\n",
        "    print(\"learned cards:\", total_learned)\n",
        "    print(\"time in minutes:\", round(total_time / 60, 1))\n",
        "    print(\"remembered cards:\", total_remembered)\n",
        "    print(\"time per remembered card:\", round(\n",
        "        total_time / 60 / total_remembered, 2))\n",
        "    print(\"leeches:\", total_leeches)\n",
        "\n",
        "    save = card[card[\"retrievability\"] > 0].copy()\n",
        "    save[\"stability\"] = round(save[\"stability\"], 2)\n",
        "    save[\"retrievability\"] = round(save[\"retrievability\"], 2)\n",
        "    save[\"difficulty\"] = round(save[\"difficulty\"], 2)\n",
        "    save[\"factor\"] = round(save[\"factor\"], 2)\n",
        "    save[\"time\"] = round(save[\"time\"], 2)\n",
        "\n",
        "    save.to_csv(f\"./simulator-{scheduler_name}.tsv\", index=False, sep=\"\\t\")\n",
        "\n",
        "plt.figure(1)\n",
        "plt.title(f\"Review Count per Day ({moving_average_period} days average)\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.figure(2)\n",
        "plt.title(f\"Time Cost in minutes per Day ({moving_average_period} days average)\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.figure(3)\n",
        "plt.title(f\"Cumulative Learn Count per Day\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.figure(4)\n",
        "plt.title(\"Retention per Day\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.figure(5)\n",
        "plt.title(f\"Memorized Count per Day\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.show()\n",
        "plt.close(\"all\")"
      ]
    }
  ],
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      "authorship_tag": "ABX9TyOm4HfyD2iOIc2PUtxA92by",
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      "provenance": []
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