manuscript_results_hhid.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "98327d4f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:32.521117Z",
     "start_time": "2023-11-28T22:57:29.111555Z"
    }
   },
   "outputs": [],
   "source": [
    "import glob\n",
    "import os\n",
    "import pandas as pd\n",
    "import csv\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from collections import deque\n",
    "\n",
    "import re\n",
    "\n",
    "from datetime import datetime\n",
    "from datetime import timedelta\n",
    "from datetime import date\n",
    "import numpy as np\n",
    "import matplotlib.dates as mdates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a8cce6ae",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:32.534328Z",
     "start_time": "2023-11-28T22:57:32.524269Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "#Manuscript figure width requirements\n",
    "plt.rcParams['font.size'] = 7\n",
    "plt.rcParams['font.family'] = 'Arial'\n",
    "figsize_2colw = 175/25.4\n",
    "figsize_1colw= 85/25.4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c9460bd",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "18af5c17",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:32.743999Z",
     "start_time": "2023-11-28T22:57:32.537917Z"
    }
   },
   "outputs": [],
   "source": [
    "#This assumes results are 1 level down from root directory\n",
    "\n",
    "data_directory = '/home/kel2158/Projects/COVIDHerit/data/'\n",
    "results_directory = '/home/kel2158/Projects/COVIDHerit/results/12_29_21'\n",
    "\n",
    "revision_results_directory = '/home/kel2158/Projects/COVIDHerit/results/revisions_7_23'\n",
    "\n",
    "figure_directory = '/home/kel2158/Projects/COVIDHerit/figures'\n",
    "#NYC wide hospitalizations and case data from https://www1.nyc.gov/site/doh/covid/covid-19-data-totals.page\n",
    "\n",
    "nyc_covid_hosp_file = data_directory + 'hosp-by-day.csv'\n",
    "nyc_covid_cases_file = data_directory + 'cases-by-day.csv'\n",
    "fam_size_file = data_directory +'/12_29_21/fam_size.txt'\n",
    "\n",
    "\n",
    "\n",
    "#All results used in figures output in a single file\n",
    "figure_results = '/home/kel2158/Projects/COVIDHerit/figures/modelresults.csv'\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1eae7323",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:32.886302Z",
     "start_time": "2023-11-28T22:57:32.748392Z"
    }
   },
   "outputs": [],
   "source": [
    "fam_size_df = pd.read_csv(fam_size_file,sep=\" \")\n",
    "\n",
    "pheno2sampsize = dict(zip( fam_size_df[\"pheno\"],fam_size_df[\"famcount\"] ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "302e7712",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.007688Z",
     "start_time": "2023-11-28T22:57:32.889756Z"
    }
   },
   "outputs": [],
   "source": [
    "#Process Data\n",
    "def create_solar_df(h2_results, header):\n",
    "    '''function that takes in results as deque and turns them as a dataframe'''\n",
    "\n",
    "    header.extend([\"file\",\"directory\"])\n",
    "    df = pd.DataFrame(results,columns=header)\n",
    "    \n",
    "    #Turn into floats and ints from strings\n",
    "    for col in ['estimate', 'estimate_lower','estimate_upper', 'solarerr', 'solarpval','posa']:\n",
    "        df[col].update( df[col].astype(float) )\n",
    "\n",
    "\n",
    "    df[\"num_families\"].update( df[\"num_families\"].astype(int))\n",
    "\n",
    "\n",
    "    clean_model_name = {\"ACE_h2o\":\"Heritability\",\"ACE_Shared_Env\":\"Shared Environment\"}\n",
    "   \n",
    "    df[\"model_clean\"] = df[\"model\"].map(clean_model_name)\n",
    "    \n",
    "    #Remove AE only models since not used\n",
    "    df = df[ df[\"model_clean\"].notnull() ] \n",
    "\n",
    "    return(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "72ae2afd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.126265Z",
     "start_time": "2023-11-28T22:57:33.011830Z"
    }
   },
   "outputs": [],
   "source": [
    "def process_file(file_path, results, incomplete_rows, header):\n",
    "    '''Function that takes in a file path, already pulled results \n",
    "    and incomplete results and a header if we have it and returns \n",
    "    concatenated resultsin the form of a deque'''   \n",
    "    \n",
    "    with open(file_path) as f:\n",
    "        reader = csv.reader(f, delimiter='\\t')\n",
    "        \n",
    "        try:\n",
    "            header = next(reader)[0].split(\",\")\n",
    "            for row in reader:\n",
    "                row_split = row[0].split(\",\")\n",
    "                file_name = os.path.basename(file_path)\n",
    "                directory_name = os.path.basename(os.path.dirname(file_path))\n",
    "                \n",
    "                row_split.append(file_name)\n",
    "                row_split.append(directory_name)\n",
    "\n",
    "                if len(row_split) == 15:\n",
    "                    results.append(tuple(row_split))\n",
    "                else:\n",
    "                    incomplete_rows.append(tuple(row_split))\n",
    "\n",
    "\n",
    "        except StopIteration:\n",
    "            # Handle the case when there are no rows in the CSV file\n",
    "            pass\n",
    "        \n",
    "    return results, incomplete_rows, header\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "82ff4557",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.308065Z",
     "start_time": "2023-11-28T22:57:33.130458Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    }
   ],
   "source": [
    "#Load all cov data\n",
    "\n",
    "results = deque()\n",
    "incomplete_rows = deque()\n",
    "header = None\n",
    "\n",
    "# Process file paths matching pattern */*/*results.csv\n",
    "for file_path in glob.glob(f'{results_directory}/*/*/*results.csv', recursive=True):\n",
    "    results, incomplete_rows, header = process_file(file_path, results, incomplete_rows, header)\n",
    "\n",
    "# Process file paths matching pattern */*results.csv\n",
    "for file_path in glob.glob(f'{results_directory}/*/*results.csv', recursive=True):\n",
    "    results, incomplete_rows, header = process_file(file_path,results, incomplete_rows, header)\n",
    "\n",
    "solar_df = create_solar_df(results, header)\n",
    "print(len( incomplete_rows ) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "16ce904e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.453264Z",
     "start_time": "2023-11-28T22:57:33.316843Z"
    }
   },
   "outputs": [],
   "source": [
    "#Load no sex or age data\n",
    "\n",
    "results = deque()\n",
    "incomplete_rows = deque()\n",
    "header = None\n",
    "\n",
    "# # Process file paths matching pattern */*/*results.csv\n",
    "# for file_path in glob.glob(f'{revision_results_directory}/*/*/*results.csv', recursive=True):\n",
    "#     results, incomplete_rows, header = process_file(file_path, results, incomplete_rows, header)\n",
    "\n",
    "# Process file paths matching pattern */*results.csv\n",
    "for file_path in glob.glob(f'{revision_results_directory}/*/*results.csv', recursive=True):\n",
    "    results, incomplete_rows, header = process_file(file_path,results, incomplete_rows, header)\n",
    "\n",
    "solar_rev_df = create_solar_df(results, header)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f06da73",
   "metadata": {},
   "source": [
    "## NYC Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d51911b2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.539661Z",
     "start_time": "2023-11-28T22:57:33.457775Z"
    }
   },
   "outputs": [],
   "source": [
    "file = nyc_covid_cases_file\n",
    "nyc_case_df = pd.read_csv(file)\n",
    "\n",
    "file = nyc_covid_hosp_file\n",
    "nyc_df = pd.read_csv(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c55461c3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.662206Z",
     "start_time": "2023-11-28T22:57:33.542929Z"
    }
   },
   "outputs": [],
   "source": [
    "#get in datetime\n",
    "pull_date_from_nycases = lambda date: datetime.strptime(date, '%m/%d/%Y' ).date()\n",
    "\n",
    "nyc_df[\"date_cln\"] = nyc_df[\"date_of_interest\"].apply(pull_date_from_nycases)\n",
    "nyc_case_df[\"date_cln\"] = nyc_case_df[\"date_of_interest\"].apply(pull_date_from_nycases)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "83e016b4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.776455Z",
     "start_time": "2023-11-28T22:57:33.665262Z"
    }
   },
   "outputs": [],
   "source": [
    "#Get the weeks\n",
    "pull_date_from_trait = lambda trait: datetime.strptime(trait.replace(\"covid_cswitch_weekly_\",\"\"), '%m_%d_%Y' ).date()\n",
    "\n",
    "weeks = list( set( solar_df[ solar_df[\"trait\"].str.contains(\"covid_cswitch_weekly_\") ]\\\n",
    "                  [\"trait\"].apply(pull_date_from_trait) ))\n",
    "\n",
    "weeks.sort()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38aaa462",
   "metadata": {},
   "source": [
    "## Graphing Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b8a90de5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.897641Z",
     "start_time": "2023-11-28T22:57:33.779761Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.rc(\"axes.spines\", top=False, right=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ac2db2ee",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:33.973137Z",
     "start_time": "2023-11-28T22:57:33.900766Z"
    }
   },
   "outputs": [],
   "source": [
    "#Manuscript figure width requirements\n",
    "figsize_2colw = 175/25.4\n",
    "figsize_1col= 85/25.4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5feeab61",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.047264Z",
     "start_time": "2023-11-28T22:57:33.977441Z"
    }
   },
   "outputs": [],
   "source": [
    "regex = r'(\\d+_\\d+_\\d+)'\n",
    "\n",
    "pull_date = lambda trait_name: datetime.strptime(re.findall(regex, trait_name)[0]\\\n",
    "                                                 ,'%Y-%m-%d').date()\n",
    "\n",
    "pull_date_window = lambda trait_name: datetime.strptime(re.findall(regex, trait_name)[0]\\\n",
    "                                                 ,'%m_%d_%Y').date()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "eb975f88",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.167494Z",
     "start_time": "2023-11-28T22:57:34.050584Z"
    }
   },
   "outputs": [],
   "source": [
    "#Function to map the colors as a list from the input list of x variables\n",
    "def pltcolor(posas):\n",
    "    cols = []\n",
    "    for posa in posas:\n",
    "        if posa < 0.2:\n",
    "            cols.append('red')\n",
    "        elif posa < 0.8:\n",
    "            cols.append('orange')\n",
    "        else:\n",
    "            cols.append('green')\n",
    "    return cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9999cdea",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.283312Z",
     "start_time": "2023-11-28T22:57:34.171140Z"
    }
   },
   "outputs": [],
   "source": [
    "def pull_graph_vals(df, model, x):\n",
    "    model_data = df[df[\"model_clean\"] == model]\n",
    "    \n",
    "    lower_err = model_data[\"estimate\"] - model_data[\"estimate_lower\"]\n",
    "    upper_err = model_data[\"estimate_upper\"] - model_data[\"estimate\"]\n",
    "    err = [lower_err, upper_err]\n",
    "    \n",
    "    x_values = model_data[x]\n",
    "    y_values = model_data[\"estimate\"]\n",
    "    \n",
    "    posa_color = pltcolor(model_data[\"posa\"])\n",
    "    \n",
    "    num_fams = model_data[\"num_families\"].astype(int).values\n",
    "    \n",
    "    return err, x_values, y_values, posa_color, num_fams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7ac2fedb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.412565Z",
     "start_time": "2023-11-28T22:57:34.287838Z"
    }
   },
   "outputs": [],
   "source": [
    "def autolabel(rects, ax):\n",
    "    \"\"\"\n",
    "    Attach a text label above each bar displaying its height\n",
    "    \"\"\"\n",
    "    for num, rect in enumerate(rects):\n",
    "        height = rect.get_height()\n",
    "\n",
    "        # If there are a whole bunch of labels, only include every fifth\n",
    "        if len(rects) >= 12 and num % 5 != 0:\n",
    "            continue\n",
    "\n",
    "        ax.text(rect.get_x() + rect.get_width() / 2., 1.05 * height,\n",
    "                '%d' % int(height),\n",
    "                ha='center', va='bottom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7cb898ff",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.516962Z",
     "start_time": "2023-11-28T22:57:34.416837Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.rcParams['font.size'] = 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dd9c41e2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.639112Z",
     "start_time": "2023-11-28T22:57:34.521204Z"
    }
   },
   "outputs": [],
   "source": [
    "def create_graph(df, x_value_col, plot_title, model_type=\"ace\", hide_error=False, use_fam=True, \\\n",
    "                 remove_scatter_markers=False, fig_width_columns=2,dates_x_axis=False):\n",
    "    \"\"\"Takes in dataframes for a specific trait and graphs it\"\"\"\n",
    "    \n",
    "    if fig_width_columns == 2:\n",
    "        fig_width = 175/25.4\n",
    "    else:\n",
    "        fig_width = 85/25.4\n",
    "\n",
    "    if use_fam:\n",
    "        fig, axs = plt.subplots(nrows=2, ncols=1, gridspec_kw={'height_ratios': [3, 1]})\n",
    "        ax1 = axs[0]\n",
    "        ax2 = axs[1]\n",
    "        fig.set_size_inches(175/25.4, 6)\n",
    "        \n",
    "        # Format the x-axis labels to be month then year if dates are used\n",
    "        if dates_x_axis:\n",
    "            ax1.xaxis.set_major_formatter(mdates.DateFormatter(\"%b %Y\"))\n",
    "            ax2.xaxis.set_major_formatter(mdates.DateFormatter(\"%b %Y\"))\n",
    "        \n",
    "    else:\n",
    "        fig, axs = plt.subplots(nrows=1, ncols=1)\n",
    "        ax1 = axs\n",
    "        fig.set_size_inches(175/25.4, 4.5)\n",
    "    \n",
    "    if model_type == \"ace\":\n",
    "        model_lst = ['Heritability', 'Shared Environment']\n",
    "    \n",
    "    elif model_type == \"ae\":\n",
    "        model_lst = ['AE']\n",
    "    \n",
    "    else:\n",
    "        model_type == \"all\"\n",
    "        model_lst = ['Heritability', 'Shared Environment', 'AE']\n",
    "    \n",
    "    num_fams_lst = []\n",
    "    \n",
    "    for model in model_lst:\n",
    "        err, x, y, posa_color, num_fams = pull_graph_vals(df, model, x_value_col)\n",
    "        \n",
    "        if remove_scatter_markers:\n",
    "            p1 = ax1.scatter(x=x, y=y, c=posa_color, s=0.001)\n",
    "        else:\n",
    "            p1 = ax1.scatter(x=x, y=y, c=posa_color)\n",
    "        \n",
    "        ax1.set_ylabel(\"Estimate\")\n",
    "        \n",
    "        if hide_error:\n",
    "            ax1.errorbar(x, y, linestyle='--', elinewidth=0.4, label=model)\n",
    "        else:\n",
    "            p2 = ax1.errorbar(x, y, yerr=err, linestyle='--', elinewidth=0.4, label=model)\n",
    "            ax1.set_ylim([0, 1])\n",
    "        \n",
    "        ax1.legend(frameon=False)\n",
    "        \n",
    "        ax2.set_xlim(ax1.get_xlim())\n",
    "        \n",
    "        num_fams_lst.extend(list(zip(x, num_fams)))\n",
    "    \n",
    "    bar_width = 0.08 if x_value_col != \"date\" else 5\n",
    "        \n",
    "    \n",
    "    fam_df = pd.DataFrame(num_fams_lst, columns=[x_value_col, \"num_fams\"]).sort_values(by=x_value_col)\n",
    "    fam_df.drop_duplicates(inplace=True)\n",
    "    \n",
    "    if use_fam:\n",
    "        rec = ax2.bar(fam_df[x_value_col], fam_df[\"num_fams\"], width=bar_width, color=\"white\", edgecolor='grey')\n",
    "        ax2.set_ylabel(\"Number of Families\")\n",
    "        ax2.set_xlabel(\"Percent Families Included\" if x_value_col != \"date\" else \"Date Cutoff\")\n",
    "        autolabel(rec, ax2)\n",
    "\n",
    "    fig.suptitle(plot_title)\n",
    "    plt.show()\n",
    "    sns.despine(fig)\n",
    "    \n",
    "    df.to_csv(figure_results, mode='a', header=True, index=False)\n",
    "\n",
    "    \n",
    "    return fig, axs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9290c443",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bccf798d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.752866Z",
     "start_time": "2023-11-28T22:57:34.642055Z"
    }
   },
   "outputs": [],
   "source": [
    "def create_graph(df, x_value_col, plot_title, model_type=\"ace\", hide_error=False, use_fam=True, \\\n",
    "                 remove_scatter_markers=False, fig_width_columns=2,dates_x_axis=False):\n",
    "    \"\"\"Takes in dataframes for a specific trait and graphs it\"\"\"\n",
    "    \n",
    "    if fig_width_columns == 2:\n",
    "        fig_width = 175/25.4\n",
    "    else:\n",
    "        fig_width = 85/25.4\n",
    "\n",
    "    if use_fam:\n",
    "        fig, axs = plt.subplots(nrows=2, ncols=1, gridspec_kw={'height_ratios': [3, 1]})\n",
    "        ax1 = axs[0]\n",
    "        ax2 = axs[1]\n",
    "        fig.set_size_inches(175/25.4, 6)\n",
    "        \n",
    "        # Format the x-axis labels to be month then year if dates are used\n",
    "        if dates_x_axis:\n",
    "            ax1.xaxis.set_major_formatter(mdates.DateFormatter(\"%b %Y\"))\n",
    "            ax2.xaxis.set_major_formatter(mdates.DateFormatter(\"%b %Y\"))\n",
    "        \n",
    "        else:\n",
    "            ticks = np.arange(0.2, 1.0, 0.1)\n",
    "            ax1.set_xticks(ticks)\n",
    "            ax1.set_xticklabels([f\"{tick:.1f}\" for tick in ticks])\n",
    "\n",
    "            ax2.set_xticks(ticks)\n",
    "            ax2.set_xticklabels([f\"{tick:.1f}\" for tick in ticks])\n",
    "\n",
    "            ax1.set_xlim([0.1, 1])\n",
    "            ax2.set_xlim(ax1.get_xlim())\n",
    "        \n",
    "    else:\n",
    "        fig, axs = plt.subplots(nrows=1, ncols=1)\n",
    "        ax1 = axs\n",
    "        fig.set_size_inches(175/25.4, 4.5)\n",
    "    \n",
    "    if model_type == \"ace\":\n",
    "        model_lst = ['Heritability', 'Shared Environment']\n",
    "    \n",
    "    elif model_type == \"ae\":\n",
    "        model_lst = ['AE']\n",
    "    \n",
    "    else:\n",
    "        model_type == \"all\"\n",
    "        model_lst = ['Heritability', 'Shared Environment', 'AE']\n",
    "    \n",
    "    num_fams_lst = []\n",
    "    \n",
    "    for model in model_lst:\n",
    "        err, x, y, posa_color, num_fams = pull_graph_vals(df, model, x_value_col)\n",
    "        \n",
    "        if remove_scatter_markers:\n",
    "            p1 = ax1.scatter(x=x, y=y, c=posa_color, s=0.001)\n",
    "        else:\n",
    "            p1 = ax1.scatter(x=x, y=y, c=posa_color)\n",
    "        \n",
    "        ax1.set_ylabel(\"Estimate\")\n",
    "        \n",
    "        if hide_error:\n",
    "            ax1.errorbar(x, y, linestyle='--', elinewidth=0.4, label=model)\n",
    "        else:\n",
    "            p2 = ax1.errorbar(x, y, yerr=err, linestyle='--', elinewidth=0.4, label=model)\n",
    "            ax1.set_ylim([0, 1])\n",
    "        \n",
    "        ax1.legend(frameon=False)\n",
    "        \n",
    "        \n",
    "        ax2.set_xlim(ax1.get_xlim())\n",
    "        \n",
    "        num_fams_lst.extend(list(zip(x, num_fams)))\n",
    "    \n",
    "    bar_width = 0.08 if x_value_col != \"date\" else 5\n",
    "        \n",
    "    \n",
    "    fam_df = pd.DataFrame(num_fams_lst, columns=[x_value_col, \"num_fams\"]).sort_values(by=x_value_col)\n",
    "    fam_df.drop_duplicates(inplace=True)\n",
    "    \n",
    "    if use_fam:      \n",
    "        rec = ax2.bar(fam_df[x_value_col], fam_df[\"num_fams\"], width=bar_width, color=\"white\", edgecolor='grey')\n",
    "        ax2.set_ylabel(\"Number of Families\")\n",
    "        ax2.set_xlabel(\"Percent Families Included\" if x_value_col != \"date\" else \"Date Cutoff\")\n",
    "        autolabel(rec, ax2)\n",
    "\n",
    "    fig.suptitle(plot_title)\n",
    "    plt.show()\n",
    "    sns.despine(fig)\n",
    "    \n",
    "    df.to_csv(figure_results, mode='a', header=True, index=False)\n",
    "\n",
    "    \n",
    "    return fig, axs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "515e3c40",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:34.893047Z",
     "start_time": "2023-11-28T22:57:34.756669Z"
    }
   },
   "outputs": [],
   "source": [
    "# Initialize a list to keep track of all figures\n",
    "all_figures = []\n",
    "\n",
    "# Create a function to save a figure and add it to the list\n",
    "def save_and_track_figure(fig, filename, save_directory = figure_directory):\n",
    "    \n",
    "    # Combine the save_directory and filename to create the full path\n",
    "    save_path = os.path.join(save_directory, filename)\n",
    "    fig.patch.set_facecolor('white')\n",
    "    \n",
    "    # Save the figure with the full path\n",
    "    fig.savefig(save_path, dpi=300, bbox_inches=\"tight\")\n",
    "    \n",
    "    # Append the saved file path to the list of saved figures\n",
    "    all_figures.append(save_path)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f53a0f8",
   "metadata": {},
   "source": [
    "## All Cov Graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6465556e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:35.018272Z",
     "start_time": "2023-11-28T22:57:34.896937Z"
    }
   },
   "outputs": [],
   "source": [
    "clean_pheno_titles = {'covid':\"SARS-CoV-2 Susceptibility\",\n",
    " 'covid_noproband':\"SARS-CoV-2  Susceptibility, No Proband Requirement\",\n",
    " 'days_hosp':\"Days Hospitalized\",\n",
    " 'hosp_stat':\"Hospitalization Status\",\n",
    " 'hosp_stat_nopro':'Hospitalization Status, No Proband Requirement',\n",
    " 'covid_highdeg_fam':'SARS-CoV-2  Susceptibility, High Degree Families',\n",
    " 'covid_highdeg_nopro':'SARS-CoV-2 Susceptibility, High Degree Families, No Proband Requirement',\n",
    " 'dayshosp_noage' : 'Days Hospitalized, No Age Covariate',\n",
    " 'dayshosp_nosex': 'Days Hospitalized, No Sex Covariate',\n",
    " 'dayshosp_nosex_noage': 'Days Hospitalized, No Sex Or Age Covariates',\n",
    " 'covid_noage': 'SARS-CoV-2  Susceptibility, No Age Covariate',\n",
    " 'covid_nosex': 'SARS-CoV-2  Susceptibility, No Sex Covariate',\n",
    " 'covid_nosex_noage': 'SARS-CoV-2  Susceptibility, No Sex or Age Covariate',\n",
    "                      \"covid_coprocessc2h2\":\"Permuted COVID Status\", \n",
    "                      \"days_hosp_coprocessc2h2\":\"Permuted Days Hospitalized\"\n",
    "                    \n",
    "                     \n",
    "                     }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ee4ddd63",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:39.668430Z",
     "start_time": "2023-11-28T22:57:35.024809Z"
    },
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 496.063x108 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Partition by phenotype\n",
    "df_holder = solar_df[ ( solar_df[\"trait\"].str.contains( \"covid_cswitch_weekly\" ) == True ) &\n",
    "                        ( solar_df[\"directory\"] == \"cummulative_classswitch\")\n",
    "                        ].copy()\n",
    "\n",
    "#Makes no difference, all had over 30 converged\n",
    "# df_holder = df_holder[ df_holder[\"num_converged\"].astype(int) > 30 ]\n",
    "\n",
    "\n",
    "#Pull date cases/controls are included through from phenotype name\n",
    "df_holder[\"date\"] = df_holder[\"trait\"].apply( pull_date_window )\n",
    "\n",
    "#sort by the number of families \n",
    "df_holder.sort_values(by=\"num_families\",inplace=True)\n",
    "\n",
    "\n",
    "\n",
    "#get graph\n",
    "fig = create_graph(df_holder,\"date\",\"COVID Susceptibility Cumulative\", remove_scatter_markers = True,\n",
    "                  dates_x_axis=True)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "save_and_track_figure(fig[0], \"covid_cumulative.pdf\")\n",
    "\n",
    "#Graph cases by week in NYC\n",
    "fig, axs= plt.subplots(nrows=1,ncols=1)\n",
    "fig.set_size_inches(175/25.4, 1.5)\n",
    "\n",
    "# Format the x-axis labels to be month then year\n",
    "\n",
    "axs.xaxis.set_major_formatter(mdates.DateFormatter(\"%b %Y\"))\n",
    "\n",
    "\n",
    "\n",
    "x = nyc_case_df[ (nyc_case_df[\"date_cln\"] >= weeks[0]) &\n",
    "                        (nyc_case_df[\"date_cln\"] <= weeks[-1] + timedelta(days=7))\n",
    "                        ][\"date_cln\"]\n",
    "\n",
    "y = nyc_case_df[ (nyc_case_df[\"date_cln\"] >= weeks[0]) &\n",
    "                        (nyc_case_df[\"date_cln\"] <= weeks[-1] + timedelta(days=7))\n",
    "                        ][\"ALL_CASE_COUNT_7DAY_AVG\"]\n",
    "\n",
    "\n",
    "adm_plt = axs.bar(x,y, width=0.1, color=\"white\",edgecolor='grey')\n",
    "\n",
    "\n",
    "axs.set_xlabel(\"Week\")\n",
    "axs.set_ylabel(\"NYC Cases - 7 Day Average\")\n",
    "\n",
    "\n",
    "sns.despine()\n",
    "\n",
    "#Phase 4 repopen July 19th, 2020\n",
    "plt.axvline(x = datetime(2020, 7, 19).date(), color = 'black', label = 'NYC Phase 4 Reopen')\n",
    "plt.text(datetime(2020, 7, 19).date(), max(y)+ 500, 'NYC Phase 4 Reopen', ha='center', va='bottom')\n",
    "\n",
    "#Elementary kids return to school September 29, 2020\n",
    "plt.axvline(x = datetime(2020, 9, 29).date(), color = 'black', label = 'Elementary Return to School')\n",
    "plt.text(datetime(2020, 9, 29).date(), max(y)+ 1500, 'Elementary Return to School', ha='center', va='bottom')\n",
    "\n",
    "plt.axvline(x=datetime(2021, 2, 14).date(), color='black')\n",
    "plt.text(datetime(2021, 2, 14).date(), max(y)+ 500, 'Vaccines - Underlying Conditions', ha='center', va='bottom')\n",
    "\n",
    "plt.axvline(x=datetime(2021, 4, 6).date(), color='black')\n",
    "plt.text(datetime(2021, 4, 6).date(), max(y)+ 1500, 'Vaccines - 16+', ha='center', va='bottom')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "save_and_track_figure(fig, \"covid_trends.pdf\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bd8ddcfe",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:39.679367Z",
     "start_time": "2023-11-28T22:57:39.671974Z"
    }
   },
   "outputs": [],
   "source": [
    "#Get lsit of all phenotypes in results\n",
    "phenos_lst = solar_df[\"trait\"].unique()\n",
    "\n",
    "#Finds phenos in df that contains these words (really groupings of phenos)\n",
    "\n",
    "phenos = [\"covid\",\"covid_noproband\",\"days_hosp\",\"hosp_stat\",\"hosp_stat_nopro\",\\\n",
    "                   \"covid_highdeg_fam\",\"covid_highdeg_nopro\"\n",
    "                   \n",
    "                  ]\n",
    "\n",
    "permuted_phenos = [ \"covid_coprocessc2h2\", \"days_hosp_coprocessc2h2\" ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9402df0a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:44.510382Z",
     "start_time": "2023-11-28T22:57:39.683408Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for pheno in phenos:\n",
    "    \n",
    "    #Partition by phenotype\n",
    "    df_holder = solar_df[ solar_df[\"trait\"] == pheno ].copy()\n",
    "    \n",
    "    #Assumes includes max 90% families for SOLARSTRAP\n",
    "    num_total_fams = pheno2sampsize[pheno]\n",
    "        \n",
    "\n",
    "    #Calc percent fams included per solar iteration\n",
    "    df_holder[\"fam_percent\"] = df_holder[\"num_families\"]/num_total_fams\n",
    "    df_holder[\"fam_percent\"].update( df_holder[\"fam_percent\"].apply(round,ndigits=2) )\n",
    "    \n",
    "    \n",
    "    #sort by the number of families \n",
    "    df_holder.sort_values(by=\"num_families\",inplace=True)\n",
    "    \n",
    "    #get graph\n",
    "    fig,axs = create_graph(df_holder,\"fam_percent\",clean_pheno_titles[pheno],fig_width_columns=1)\n",
    "\n",
    "    fig_name = pheno + \"_stability.pdf\"\n",
    "    \n",
    "    save_and_track_figure(fig, fig_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c30ccb8b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:44.524059Z",
     "start_time": "2023-11-28T22:57:44.513381Z"
    }
   },
   "outputs": [],
   "source": [
    "def graph_percent_fam(df, pheno, directory ):\n",
    "    #Partition by phenotype\n",
    "    df_holder = df[ ( df[\"directory\"] == directory )&\\\n",
    "                  ( df[\"trait\"] == pheno )].copy()\n",
    "    \n",
    "    #Assumes includes max 90% families for SOLARSTRAP\n",
    "    num_total_fams = pheno2sampsize[pheno]\n",
    "        \n",
    "    clean_name = clean_pheno_titles[directory]\n",
    "    \n",
    "    #Calc percent fams included per solar iteration\n",
    "    df_holder[\"fam_percent\"] = df_holder[\"num_families\"]/num_total_fams\n",
    "    df_holder[\"fam_percent\"].update( df_holder[\"fam_percent\"].apply(round,ndigits=2) )\n",
    "    \n",
    "    \n",
    "    #sort by the number of families \n",
    "    df_holder.sort_values(by=\"num_families\",inplace=True)\n",
    "    \n",
    "    #get graph and save to folder\n",
    "    fig,axs = create_graph(df_holder,\"fam_percent\",clean_name,fig_width_columns=1)\n",
    "    figure_name = clean_name + \".pdf\"\n",
    "    figure_name = str.replace(figure_name, \" \", \"_\").lower()\n",
    "    \n",
    "    save_and_track_figure(fig, figure_name)\n",
    "    \n",
    "    df_holder.to_csv(figure_results, mode='a', header=False, index=False)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ecccabd2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:46.748743Z",
     "start_time": "2023-11-28T22:57:44.526588Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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TWImISOAprEREJPAUViIiEngKKxERCTyFlYiIBJ7CSuQAaE6QSMVSWImISOAprEREJPAUVlWcuqtEpCpQWImISOAprEREJPAUViIiEngKKxERCTyFlYiIBJ7CSkREAk9hJSIigaewEhGRwFNYiYhI4CmsJDgKs6EwJ9pViEgAxUXyYGbWB7g8/PRa59wWM+sPnAOkATc559ZF8pzRsnj9dgDaNYlyIfviHCxeBJs3Q2ovqF072hUVb9sS+PpiWLHBP2/ZFI5+FlIOiW5dIhIYkW5ZjcKH1dPAsPC284AMYCOwPsLnk5KsWgVdu5J0w3CSHrgW0tPhwQejXdXeCjLhwz6wYRq4Av9Y/5nfVpgX7epEJCAiHVaxzrkcYC2QHt7WDrgTmA8MLu5FZjbKzKab2fQNGzZEuKRq6pRTYMECyM2BrCzIyYF77oEPPii3UzrnyMorICMnn02ZeazPyGH1lmy2ZuUDkF8YYu7qrcxeuYUZyzfx9U+/8tW0t1iZlQKEyAolsiKvEbhCyM+A1f8pt1pFpHKJaDcgkGVmifig2tHdt9o5l2dmmyghHJ1zE4AJAD179nQRrqn6WbgQFi0iMyaez9O7kx2bSLt5KyAzk/v/9Q2btzWmoNCRH3IUhkJ0b16Hkb9pDcAlk74jIzufgpCjIBSioNBxQufGXH/8oQD0vv9j8gpC5BeGKAz5Y1zUuwW3ntyJ7PxCOt2xdxheM7At15/Qns2ZeQx9/Ms99tbhD42P4PKGy9hSUJPRK/7IPzfNZkT9dxmU8ROx5f1eiUilEOmwmgA8CcQDU8ysE/CKmT0d3n9VhM8ne9icmcdHs9bywdCb+Lx5N/LiEuj1y1zG8CoA05Ias3HxRmJjjPjYGOJijCa1knc7RkJcDDXC++JijPqpCTv3DWjfkBiD+NgYYmOMuFijV8u6/nWxMdxyUoedr4uLjSE+1ujcpBYAtWrE8+QFPYiPNWJjYoiPMeI2fk7zJdMBqBe3hYvqTea/GUczatkfab4JLtr8E+cddQg1EiL9X1VEKhNzLlgNmZ49e7rp06dHu4xSLZ71BQDtDu8X5Upg4/Zc6qcmAnDFCzOYMm8dTbZt5MSFX9ElbymdNy2lw7zlkJQEt94Kt90W5YqLCOXDu11g+zLmZDYHoGPKGj7M/y2Tsq5k/tpt/O8PA0lLiic7r5DkhGC0tXbcI6xrs1pRrmR3Qa2rLCpz7RIxVtIO/blaSS3bmMkH89YxZd46Zq3cwuc3HkvzujUYM7AtVx3bhq4fvIlN+ieLWzcAHCQnQ+PGMGZMtEvfXUw8nPg1zLoVfvwGzIg7dChDut3DkPg01mfkkJYUj3OOM/7xFQ3SErm4b0sGHNqQmJgS/1+LSBWjsKpk5q7eyg2vzWbBum0AdGlak98ff+jOFkeXpuG/Si+9BDp1hKfHwuYtcOFouOIKqFkzOoXvS0Id6PUPaBK+o3GRv6wb1kwCIL/QMbRbOi98vZxLJk2nZb0aXNi7JWf3bEZaUnw0qpZqTK3AiqewCrBQyDFz5RY+mLeOLk1rcephTUivlUTN5HhuH9qJEzo1onndGiUfoHdvSC7wnwegu/JgJMTFMGZgOy7v34Ypc9cxadoy/vTOfOqkxHNG92Y45zBTS0ukqlJYBdC0JRt5f+46Ppi3jvXbcomPNUb2a82phzWhXmoir17eO9olRk18bAynHNaEUw5rwg+rttC+cRoAT33xE9OW/sqIPi35TbsG6iIUqWIUVgGQk1/I/LUZHHFIHQD++uFCFqzdxoD2DTixc2OO7dCQWsnq6tpTt2a1d36eHB/LvDUZjHj2O1o3SGFEn5aceUQzUhP1X1ykKtBPcpRsy8nn04Ub+GDuOj5duJ6CQsf024+jZlI8Y4cdTsO0pMCMfKsMLujdkmFHHsJ7c9by7Fc/c8fb8/hi8UaeurBntEsTkQgoc1iZWSzQBljvnNtSbhVVA2/PWs2Nr/1AXmGI+qmJnNG9KYO7NKZGvA+nFvVSolxh5ZQQF8Pp3ZtyevemzFyxmbgYPwd9zZZs7nh7HiP6tKRv23q6tiXVSlUZDLI/LavHgVTgn2b2W+fcqHKqqUpZsyXbDzGfu45Lj2nFCZ0b06VpLS7s3YLBXRrT/ZA6xOr6SsR1D3epAizdsJ2ZKzbz0Y+/0K5hKiP6tuSM7k010VikEtmfn9Z8YJVz7gMzO6W8Cgq8TZtg4kT48Vto0QIat/Pzl4rIKwjx1Bc/8cG8dfwQ/qumfaM0QuEJ2G0apHLb0E4VXnp11a9dA766ZSDv/rCWZ6f9zK1vzeWRDxfx5c0D1dUqUknsT1gtA4aZ2UvA0vIpJ+B+/hl69YLMTGjdAGbPhr9NxH3xBfPqtWDV5mwGd2lMfKzxr+9WUiclgZsHd+DEzo1o3SA12tVXa0nxsfy2RzPOPKIp36/YzA+rtu4MqrEfLeKoVvU4unVddRGKBNT+hNVM/Np/scBx5VNOwF13nW9ZhUIUYsxPbc7LPQfwwTNzWJ20kvqpiZzQqRExMcaU6/qpmymAzIweLerSo4Vfz3BLVh7P/285Yz9aTIfGaVzctyWnHd6UpHi1uESCpNTfpmbWBHgAOByYFd68BXizvIoKrI8+glAIgGc6ns6rbY4noSCffstmcu0NF3Nc1yY75/coqCqH2jUSmHbLQCbPXsOzXy3j5jfmcP/7C5hwQU96taob7fJEJKzU36jOuTXAhWa247atBlTuYSUHKinJ3xsKGLTqW9ptWcG5n08hjUJ49U6IifTtwaQiJMXHck7P5pzdoxnf/ryJF79ZQftGfrLx1z/9SowZR7as47sI8zNgyVOwcCYkN4HUC6B21yh/ByJV3/78+f8okAj8BHQCBpZLRUF2ySXw979DTg6tt62m9bbVPqjOOUdBVQWYGUe1rsdRrevt3Pb4J4v5asmvdEqvyYij6nPqmlNIyl8D25qAxcKWcdD3JWh2WhQrF6n69uc37CpgLPAa/vpV9XPPPdC/P9So4VcxT0yCI46AceOiXZmUk4kXHsn9Z3alMOS46d8/0WfGn/jn+v5+pyuEwiz4+lIIFUa3UJEqbn9aVj8BvwK3ApnlU07AJSXBlCkwdy588R6kp8PpF0S7KilHyQmx/F+vQzj3yOb878WhPLuyO/HmFwdem1+PSStPoWONNXT4YSYd2nbdeV8xEYms/QmrF4AuwDggWHdsrGhdukDB5mhXIRXIzOjT8Ff6xP4ZgDlZbdiYX4cvtnXnjc3HwSu/AL9QPzWRJy/oQY8WdfglI4eN23Np2zCVxDiNLhQ5GPsTVk8A74Q/r95hJdVT+2vhm5FQ6DsWutZYwredL+HXtAEs7PAKP67bxoK1GTStnQzAf2av4d53fyQ2xmhdP4UO6TXp0DiNC3u30D24RPbT/s6z+hbILadaRIKtxbmwaQYs+jvEpQKFULMj9Qa+QJ/k+vRpW3+3Lz+5WzrptZJZsC6DH9duY+aKzbw3Zy2XHtMKgEc/WsxXSzfSoXEaHRrXpEN6Gu0bpZGileJF9rI/PxU9gAR8q8oBfyqXikSCygyOeAg63gALpkNifeh4lN9ejPRayZzcLZmTu6Xv3JaZW7BzwnGt5DgKQ443v1/N9tzlANRPTWD6bccD8N6ctcQYdGhck0Pq1tj3Pbqcg2UvwYzXoSAbOveFDtdBfFpkvneRKNufsJoH/BXIoTp3A65ZA489Bj/NhuaHQK1m0KpVtKuSipTcGBqE77y8n8szFW01jejbihF9WxEKOVZvyWbBum1sy8nfuf+xjxezYN02f8r4WNo3TuO4jg0ZM7AdAFl5Bbsmn08fDT89D9vC61TO/wyWvwyDZ0Bc8gF+oyLBsT9hVR+/8voOl0S4luBbuBCOOgqys6FdY1i4CCa8BJ98AkceGe3qpAIlbfzBf9Ks30EfKybGaF63Bs3r1tht+1tX9WXx+m0sWLuNH9dlsGDtNjZuzwPAOUfv+z+hRkIsHRrE0SEjlw6JPagRk03j+E1QmAOZK3xgtal+P6pS9ZQprMzsZGBGOdcSfL/7HWRk+C4XgMIC2L4drrwSpk+Pbm1S5SQnxNKtWe3d7oi8Q0HIcdWANixYt40fV6zgy02nku/iGFbzAy6r/TZbE1I4e+FfaLAyRINmM2mQlkiDtESOaduATk1qkl8YIiM7nzo1EvbdvSgSEGVtWa3GL2C7Jfy8SblUE3RTp+4MqtRmeaQ1z4eYeJg/E/LyICEhuvVVcpFsrVR18bExXN6/jX/yy2byPj2TnzJrsSHT38cr18XTKmktG1xHZqzYzPqMXHILQtxzehydmtRkyfrtnPToF8TGGPVTE2iYlkSDtERG/aY1R7eux4ZtuXz786adIdcgLZGUhNjyW5W+IBPW/de3COsNguT00l8j1UpZFrJNB34L/Ab4DL824DHAK+VbWgClpPguQCAmzpFYpwDOTIZCB68Mg06nwBEjtPSSVKyG/UlIqkUHt5LYXP/HVMP4LTzZ+hEYMhvS2uKcY3tuwc4bfdZLTeDOUzqxYVsuG7fnsmFbLuu35ZBf6Bdqnrt6K6Nf+n630yTHx/L0iJ70aVOf2Su38NqMlTRITdot0No3Stv/e4T9MhU+OwWyWgMOfh4J3e6CTjcf5BsjVUlZFrJda2ZPAT8CXwEh4C/lXVggXXklPPQQZGeTsSyRjGUJtMvaCGd0hS3L4NunoGf4+sDCKdCwA9RpGc2KpTqwGDjuU/j8dNia7Qd9JNaHo5+DtLb+S8x2m9vVMC2Ji/uWPDDo6Nb1mHJdv93CbMO2XJrX8dfVVm3O5t0f1rI5K3+3171/bT86ptfk1ekrefKzpTRIS9zZamuQlsh5Rx1CzaR4NmfmURBy1E0sIPazU6Fgu29dAYRyYM6foNFAqKdrweKVqRvQObfCzBoD8cDf8Nev7irHuoLp9tv9IIvJk/36gAWF0Ow3cM+bfq3A7PCqFgV58MalkLcdGneDjqdCx6HQoMN+jx6rTto11A0qD1hqK9+K+voNKMyF3sMg5sBXzUhOiPVzvxoXv//kbumc3C2dvIIQv2buCrMW9XyY1UtJ4NBGaWzYlsvsVVvYuC2XzLxCzj2yOQBPffET/5i6lBhz1Iv9Bw3iNpEUk8tt6RMBWJpZj4LvX6PFgCN0bzEB9m80YEt8V+A/gMHlUk3QxcfDv/4Fy5bB1P/429kPPnvX/hrh+x/FJcAVX8KCd+DH/8Cn9/rHoDuh3/X+nlhmCi6JvKSG/uNBBNX+SIiLIb1WMum1dh8eP6hjIwZ1bLTbtszcAmqEuwgHd2lM41pJbFj5PRuXf8+GvFRW5zcgDr8g8N/Xn81bi/pjn0yhSa1kWtavQYfGNbl9aCcANm7PpWZSPAlx6nKvLso6GjANv0L76fgWVafyK6kSaNkSDj98319TtxX0udo/tq3zwdWir9/306cw+WroMBQ6ngKH9IZYrVogVVvROWY7Rzl2T4V/nw+hHOZktdm5f3T6Oww4aiDLCg9l2a+Z/LQxkx9Wbdm1/5/fM335ZprWTqZV/RRa1U/hsOa1OKN7M8AP7S+3wSASFWX9DTnOOXehmY3F3y14XblVVBWlNYYjL9v1PLEmpB8O3z8H3z4JyXWhwxA44c+QXDtaVYpUvKT6cMQjMPP3/v5grhDiUmjbvBttjznJX48rxsV9W9KrVV1+3pjJsl8zmb5sEz9tzNwZVsf/7XNCztGqng+ylvVTOLx5bbo0jcB9Y0OFsP1niKtB0O9Du3LrSqatmkvzms3pGvBaS7O/f87XdM6FzKz6rmARCc2PhP97CfIyYclHvqtw+f8gMbw0zqyXIS4R2h2/a5tIVXXoldCwH0x/wy8S3O04aHz8PrvJB3dJZ3CXXcPbnXNk5++6p9jgzo1Zsn47y37N5KulG8nJD3Hukc154LfdCIUcp477kqa1k2lZP4XW9VNoWS+FQxulUSellOknq9+Dr0f4lUJcISxNg36vQ41mB/suRFRBqICL/30xr//4OjVce/JDBfRu3ZQ3z3mTlISUaJd3QMoaVqlm1hpIC3/UlfBISEiBTqf5h3O7fji/GQ9rZ0FsIrQZ6AdntB+y65qYSFVTuwt08IMvSN//FoCZ7Vp6CrjhxPY7Pw+FHOsycnauEZeZV0DjmsksWb+dTxasJ7/Q7/ndcYdy7XHt2JSZx+1vz6VVPd8i29HNWKfgJ+zLs/0NNwtq+oNtWggfD4KhCwJ1DfqBLx/gjR/fIKcgh1BoOwCfL/ucq9+/mmdOeybK1R2YsobVbOACYG744+xyq6i6KvoffeQnsOLrXQM0Fr0Ph50HZzzhQ23bOqipSZMiZRETYzSpvWsASFpSPBMv6glAYcixZks2P23MpHkd/zW/bs9l3uqtTJm7jsLQrk6kh3rO5axQHityG/HypsHUiMnmm8wusDERpnzKkN69aVI7mSXrt/Hxj+t3huOOBW9+26MpDdOSmLt6K1MXrt+5b8fXXXB0C+qkJDBj+SY+X7TR7y9ygFH925CaGMdXSzYybenGvV5/3XHtSIyL5eMff2H8p7+QmH8uiUAhm8iNnUtOYQ4vzXmJCadMIC6m8l0jL+vQ9bvLuxApIiYWWvb1jxPv862sHYuRrp8PT/SBpj394IyOp0C9NiUfKxSC/IIKKVvkYERjBZPYYtZlbNcojak3Hkt+YYiVm7L8AI8NmfTY9gpsKWBBTkte3nQijiLX01Zn0/nQLJrUTmbemgzuf3/BXuc6pm19GqYlMXvVFh76cNFe+4d2Sw+H1WYe/XjxbvvM4PyjW5CaGMd3yzYx/rOfsCL7DGP0sW1JjIPvlm0mNvtY0sIxlhX7JbnMBXz3YH5hfqUMK3MuWJefevbs6aZXgnX2Fs/6AoB2h1fw0kDb1sHMF32La+0sv61hJzjrWT8JeYecHLj+ehZ//REUFtAuNwHGj4cBAyq23v2xZqb/2KR7dOsog6j9+5ciqHWVReBrX/h3mHUzFGYxY3t78lw8nWr8jMUkYENmklyzOXGxMeQXhnauBGLhSDGDhNgYYmKMwpCjMOR2dqYYvhszxvzHHb+TD2Y04ykvn8K7i97F4UgI+T9m82KW0rVhV3648ocDfw/KX4nfdOWL1+ourTH85gb/2LICFrwLC9/3tyoB+P552LAQXvoWXvsKWjfw2xcuhJNPhq+/hq5do1e/SGXVegQseASy15AQU0ACBdRKAFqfB3Va7Pyy+NgY4mNLnv8VG2M7l70qTiSG3D98wsN8ueJLsvKzIASxFkdKfApPDn3yoI8dLZpRV5nVPgSOvhIumgyJ4TEvGxbCN09Cq2/hylgadM8iuUF4SZycHPhL9VwpS+SgxafCSTOgw/WQ0gJqdYJeT0DPx0t/bQU7tN6hzLtqHr87+ncckd6DMzueyewrZtO7ee9ol3bA1LKqak78MyT2h5vPhhaF1Dw0j/jUEEzFX7/6eVaUC6watDRUNZVQBw6/D+pv9c+bBXfuUpO0Jjxw3APM6eBrbVM3uLWWRURbVmbWx8yeCz9qF9ne0cw+jOS5ZB+6HAE/5MFr2fz0n1qsnx6+eFw7HgathH/0ga8ehYw10a1TRKSMIt0NOAq4HHgaGAZgZonASGBDhM8lJalfHy65BGrUwBUaBdnhf+bYJDjqFkioAf+9Ax7pBM+dCr/Mj269IpVM0sYfdo1elAoR6bCKdc7lAGuBHROBbgIeYdd0gL2Y2Sgzm25m0zdsUKZFxOOPw913Q926kJgIxx8PU6fBkFvgso/g6u+h/82wddWuJZ6W/w8W/9ffAVlK5py/SWAoFO1KRKqNSF+zygq3pNKBdWZWA+gNNAV6mdlA59wne77IOTcBmAB+6HqEa6qeYmLghhtod94g/3zP4eD12sCxf4ABt+yakPz1OD8kPqUBdDkLDhvm1zAM0Mz8qFvzPnw3GjatAouHrqOg+1/8HaNFpNxEOqwmAE/i73s1BWjpnBsCYGYvFhdUlVVO/W7RLiEyigbRb5+BxR/CD6/A9Kfhmyf8pONhL0avviDZ+DV88VsozAYX49eGW/Ik5GfA0U9HuzqRKi2iYeWcmwGMKGHf8EieS8pBXIJfh7DjUH8jyXn/3rWQbl4WvHqBv5Fkp9Oq5+rwc//su/+Ktv0Ls2HZS3DEQ36kmFRtWxfA9Kth0U++NV1wAhz+4K4VZqTcaOi6FC+5DvS8eNfzLcth8zL4zzXw3o3QfjB0OxfaHudDrqrKWOtXClkzC2Z9DdtTIKUAauf50MozqJEAmSsDEVYaUl+Osn+BD3tD/lZwzf213SVPQcYCGBjcwc7RWMaqPCispGwadoQx02HN9zD7XzD3dZj/Noz6DJocDrnb/SrylfX6lnN+KP/aWZC7DQ4712+fdDJsWgoYpKRASibUCA9A2R4HWxKhUSGktIpW5VJRloz3LWscsYUhvzBQKAc2fAlb5/tJwlJuFFZSdmbQtId/nPhnWPYlpB/m971/M6z4H3QbBt3Ohrqto1trWX3/Asz/t285ZfmVrElrsiusTvqLXx2kURfIWQEf9IKCAsiJgRqFkOdgXSy8fQ2c8igk1YzWdyLl7dcZPqw2J9Dq1wy/iN22FKgXq7CqAAorOTCx8dDm2F3P2xzruwqn3g9T74PmR/m7I3c7J3o1gm8xbVnuw2jtbN9yWv8jXPuD777cuMgvDnzoiX7kY5PDoVHnXa9vd9yuzxM7wXFfwMwbYNU3/rrdb26BX3Lh0z/7Y589aVeAS9VStzvM/AS2xrI9MZ7cuFjqh7ZDYSHU7AhZm+Cd63zXeJtBUKtptCuuUhRWEhldz/KPratgzmu+q3D19z6sQiF/T662x/k7IJcX52Dzzz6UWg/w193+Nw4+vNXvj4nz3Zltj4O87RBXF47/E5xwT9nPUbc7DPp49xXi2wMt+sCbIyF7S4S/KYk656AwH9pdCbPHQnI26wprgRn1626FBn2hdmf//33ld757HKBhZ2g7CHqNgtrNo/otVAUKK4msWs3gmN9B3+ugMM9vWzENXjkPkmpB5zN8V2Hzo/1csB02fAXzx4HFQOK1UO/Isp1v8zL4bmK41TQbcsJrtp33Ghx6gv9lEZ/sW0wNO0N80u6vj9Q1tha94eoZu8J43lv+Ls9JlXs9tmov81d451pISPM3Pz31f36e3aJlfjRg64v9SFCApkfA9fN9y33JR7Dkv/D1E3DERX7/z1/AxoXQ9vjdVmmXslFYSfkw2/WLu/nRMPxN+OFf8MOrMGOSXzH+gn/7ycnTr4OlEyEzBzDY+JZf2fqwcIsnFPKDHNbM2jUyr+fFviWXl+lXmW/UGTqf6UMp/XB/jy/wLamGHSvme97x/W5dDW+OgrR03y3Y9IiKOX8lF7iRjIs/grev8t17A2/zLaxaneC4T6G+v/cWe957ywwadfKPvtfsGngEfsL9t+FbdNRr51v47cJdhpV1YFIFUlhJ+YuN8y2ctoP8D++Cd2Dhez6wNs2E6RN9KywBiAlBVg7MehhaXQgJjfwahnnb/LHikvxghx0/3A06wh9WB2v4fK2mMOJdeO1iePoE38141BX6hVRZ5GXBf2/3LfYGHeH81yH9ABcBSCwSwCc9CL1G+lbX4v/C9Gf851eHbza76EM/MKleG/1fKYbCSipWYqofabdjtN3qybDNQWYy4PxwYGeQWghr3oEOv4OjLvc/xOmHQYP2fnDHDjExEBOgoNqheS+44gv491Uw5RZY+S2c9Yx+CVUG2Ztgzutw9FUw6M69u44PlBnUb+cfR1/pQ3HrKr8vVAhvXua7seu09K2utsdBq9/saplVcworia7YJGheANl+SDAhIKUQUuL9PoBBt0e1xANWoy7838vw9T/89Q0FVXCFCmHuG9D1bH/d9ervIaVe+Z4zoQY0ONR/HhPr5ywu+QiWfAyzXvItuz7X+JZ5QZ7vCm/Qodr+P1JYSXQdcg7MuQsSQ35VCICkkO86bHZmVEuLCDPoPXrX8/mTYcsKv62a/tIJnE0/w1uXw8pv/AjSdseXGlTlcn2tbivfTdhrJBTk+nmLNcPD31d+A88NhZrNwl3qx/kRr9VoXp/CSqIrtRX0fAKmX+kDCiC2EI5+DpIbRbe28rBoCsz6p59Qffo/fOtLosM5/2/x/s1gsXDmRB9UQRCX6MNoh4Yd/aTzJR/5kabfP+enYoyaCo27+i7F+OTd/gD6YvkX3PLxLSSu3kSDGg0ZnnwDp7Q/pcK/lUhRWEn0tRkBTYfCnPF+6Hq3KwOxzl65OG0cNO4GH94G4/vB2c/661tS8d67Eb57Clr2g9OfCPZcqJT60GOEfxTmw6rvYOmnfgAIwCf3+iXQ2h4HbQfxZXwCg984l6z8LI5wMWzdtohz35jOU6c8xXldz4vmd3LAFFYSDEn1oenJ/vOqGlTg//I9+gpofqQfLfjMYLhyGjTsEO3Kqg/n/L9Dx6F+vtPRo3ef8xd0sfF+EnqLPru2tTwGtq2FBe/CrH/SG3gFx6lFepqz8rO44cMb+L8u/4dVwi5ohVVVt+dNFyUYmvbwowXnvL4rqEKF/kK7lI+8LN+iTa7jB+20HrB7V1tl1mGIf4QKYfX3PPjsQPKLuZP1hqwNZBdkUyO+RhSKPDiV6M8JkSomqRYcean//Jf58PcjYfm06NZUVa2eAU/28zcVLczzrauqKCYWmh/JpDrp3GW5e+2uEV+DpLgIDcWvYAorkSBwIcDBpKHw+UN+1Q45eIUF8Nlf/OTs/Gy4cLIfCl4Ju8H2x53979yr9VQjvgY39bmJGKucv/YrZ9UiVU3jLn6eTefT4ZN74J+/he0bol1V5bdpqQ+rTqfDlV9B6/7RrqhCnN/tfB4+/mHqJtclITaBlPgUbup7E3/o94dol3bAdM1KJCiSasJvn/aj096/Gb6dAANvjXZVlY9zsPwrP+igQXs/gGXH5Ntq5Iojr2Bkj5FkLPuctIQ04pr1jHZJB0VhJRIkZn6R3kN677qB5ZaVULOJBl+UReZGmHwNLHwXLvqPX66oGgbVDrExsdRJqh3tMiJCYSUSRDtGCOZuh2eH+NUNfjsRUhtGt64gW/QBvD3ar693wp+hxTHRrkgiSNesRIIsIQX63+QXwn2iL/z0WbQrCqYPb4eXzoGUhn5Vhz5jKtfcKSmV/jVFgswMjrgARn7i5wc9fxp8ep+fTyO7NOoCfa6GUZ/6e5tJlaNuQJHKoFEn/4v43Rv8AqfVXWEBfPGQ7xbteQkcNgwYFu2qpBwprEQqi4QUf2v1/Gw/2GLbOlg/H9oMjHZlFevXpf5OzKun77plvFR56gYUqWzik/3HqffDC2fCx/f4lkZhLqz/EtZ+BDlVcI6WczD9WRh/DPy62N/M8tTHol2VVBC1rEQqqxPvh1C4O2zJFEibB/nhlS8W3wGH3w8drotqiRG1dha8cx206u9XSa/VNNoVSQVSy0qkskqo4W85cto4+GUuLC2ErGwozIRQDsy+FX6dHu0qD96vS/3HJt3honfggn8rqKohhZUER5PuWiX+QDSsA62ApEKID7estsTDxkKY+gd/d+Kfv4CNS6JaZqnyt0Pupl2LzOZuh/9c6xf4Xf2939aqn4akV1PqBhSp7AoyIdFB02zICf8i35IAebGw4VuYc4Hf1qo/XDTZfz7uKMje7IfDJ9X2H1v1g96j/f7vX4C4JL89Obw/pb5fKT7SstfBtOGw8kvAYO4h0OoP8Mmj/pbzfa/RcHRRWIkckCC1ABsNhFD+7ttaZEJMChw+Fmr3gpwtEJe8a3/nMyFjtQ+snC2QsQq2rt61/70boCBn92MecZEf0BAKweNH+LUMk+vsCrxDT4T2J/nBHoum7Aq5HY/4ZPbiHHx8LGxbsmul+WXLYMY1fompEe/4Nf6k2lNYiVR2SfX9YIrZt4Ll+duNxKdCg2Og/cXFryk44OZ9H/O6uT7EsjeHH1v8XXXB3w+qeS+/LXuzD7mcLVCzqQ+rrF/hX+fvfczj7oJjfgcZa+D1S3yAkQMbVoPFQDyQEAIDaoag/+kKqkgI0h9WB0FhdYC6NiuH7hCRA9XhOmjYD2b8BQq2Q5fLoOmpB774bWoD/yhOfBKcOaHk1ybXgcs/3xVyOwJvx1p9hXkQE+cX6N2+CrKBUBLUzfFhVSfPh27O8gOrXaokhZVIVVG3Bxz/r2hXAXEJkH5YyfvrtPTdewBbf4QpPaCgyPU2A2JToMFvyrtSqUQ0rEZEoqdWR0gfDHE1fEgBWDwk1oNWF0S1NAkWhZWIRNcx/4Kud0GNZpBQH9pcBoOn++tuImHqBhSR6IqJh043Qu3j/PPKMCCgMtRYxSisRCQYFACyD+oGFBGRwItoWJlZHzN7LvyoHd52vpmNM7OXzUwLeomIyH6LdMtqFHA58DS77oS2zTk3GngV6BPh84mISDUQ6bCKdc7lAGuBdADn3GQzawCcAbxT3IvMbJSZTTez6Rs2VMH78IiIyEGJdFhlmVkiPqjWAZhZW+A+4BrnXHZxL3LOTXDO9XTO9WzQoIRZ8yIiUm1FOqwmAE/iuwIzzawT8AxQB/i7mQ2I8PlERKQaiOjQdefcDGDEHpu1ZoqIiBwUDV0XEZHAU1iJiEjgKaxERCTwFFYiIhJ4CisREQk8hZWIiASewkpERAJPYSUiIoGnsBIRkcBTWImISOAprEREJPAUViIiEngKKxERCTyFlYiIBJ7CSkREAk9hJSIigaewEhGRwFNYiYhI4CmsREQk8BRWIiISeAorEREJPIWViIgEnsJKREQCT2ElIiKBp7ASEZHAU1iJiEjgKaxERCTwFFYiIhJ4CisREQk8hZWIiASewkpERAJPYSUiIoGnsBIRkcBTWImISOAprEREJPAUViIiEngKKxERCTyFlYiIBF5cJA9mZn2Ay8NPr3XObTGzM4HB+GC8wjlXEMlziohI1RfpltUofFg9DQwLbzvHOTcK+BwYFOHziYhINRDRlhUQ65zLMbO1wMDwtvzwx7VA0+JeZGaj8EEHsN3MFka4rvJSH9gY7SLKoLLUCaq1PFSWOkG1lpfKUusU59zg4nZEOqyyzCwRSAfWhbcVhj8W3bYb59wEYEKEayl3ZjbdOdcz2nWUprLUCaq1PFSWOkG1lpfKVGtJIh1WE4AngXhgipl1Al4zs6cAY9f1LBERkTKLaFg552YAI/bYPB94N5LnERGR6kVD1w9OZem6rCx1gmotD5WlTlCt5aUy1Vosc85FuwYREZF9UstKREQCT2ElIiKBp7AqIzPrY2bPhR+1w9vON7NxZvaymRU7hywaSqh1iJk9ZWbPmFlylEsEiq8zvL2jmX0YxdL2UsJ7epqZvWdmk8ysa5RL3KmEWvuH/68+b2aNo1wiUGKd94bfz9lmNiTKJe5UQq1DzWysmb1SCX7+f2dmT5jZA2YW6VHgFUJhVXbFrc6xzTk3GngV6BOtwopRXK0h4ApgAdA+SnXtaa86w/P0RgIbolhXcYp7T4/Czx3MBJZGqa7iFFfreUAGfmLo+ijVtae96nTO3QZcD0x1zr0Xxdr2VNx7egzQFqhLsCbcFldrb+fclcB3wInRKuxgKKzKLtY5l4NfiSMdwDk32cwaAGcA70SzuD0UV+sUYAhwGrA8irUVtVedwE3AI0DQRv4UV+sb+D8A3mbvKRvRVFyt7YA78VNJil0hIAqKqxNgDPBEdEoqUXG1TgZOBd4Ejo5WYcUortYXzGwi0A+/mkWlo7Aqu71W5zCztsB9wDXOuexoFreH4mrt65z7D3ANcHE0iytitzrNrAbQG7gN6GVmA/f56opV3OosPfErtGwm8hPsD0Zxta52zuUBmwjOz31xdQK0cs4tiFJNJSmu1uudcyF8L0C9qFW2t+JqTXLOXQbMBVZGrbKDoKHrZWRmPYCrCa/OAcwAxuO7VHKAic65qVErsIgSau2OX68xDrjHObckehV6xdXpnJsf3veic254NOsrqoT3tAMwFN8KvME5tzl6Fe5SQq2tgDPDX3KVcy43SuXtVEKdvwB3OeeujmZteyqh1v5AL3wX++hwaybqSvn5d8CocMhWKgorEREJvKB0B4iIiJRIYSUiIoGnsBIRkcBTWImISOAprEREJPAUViIiEngKKxERCTyFlYiIBJ7CSkREAk9hJSIigaewEhGpYsxsYHiV9d3uDxe+r9VYM/unmaVGt8r9o7ASEalCwneD6A4kFXN/uKXOueuA6UDH6FR4YBRWIiJViHNuiXPu4fDT3e4PF74HX1ugE3419kojSPfgERGRyNlxf7im7Lo/3HZgODCmst0mRC0rEZGqKcs5N8Q5dwXwLfAp8E/8jSKfNrPOUa1uP+l+ViIiEniB6wYcPHiwmzJlSrTLEBGRimcl7QhcN+DGjRujXYKIiARM4MJKRERkT4HrBhQRCaJPPvmEl156iWOPPZZp06axadMmHnroIb766iumTZvG1q1b+cc//kFycnLEzjl27Fi2bt0aseMdjFq1anHddddF7fwKKxGRUixZsoSZM2eSk5NDWloa48aN46233mLatGm8/fbbNGzYkNatW0c0qAC2bt3KnXfeGdFjHqi77747qudXN6CISCnatm3L73//ewBOPfVUNmzYwFtvvcXQoUNZsWIFjzzyCLm5ucyfPz/KlVZdalmJiOyHJUuW8OCDD/LYY4+RnJxMixYtMDPq1q1LKFSp5tlWKmVqWZlZicMJRUSqk0suuYTNmzczZswYpk6dyoABA7jyyitZvnw5nTtXqnm2lco+W1Zmdh/wEvComc13zl1dMWWJiATPiy++uNe2AQMGcNlll0WhmuqltJZVCjAA+FP5lyIiIlK80sJqC9ATyAAyy70aERGRYpQ2wOIZ/Kq9Dr/MvIhIxOyYu/TXv/6Vk046iS+//JKtW7dyzTXXEB8fz+jRoznyyCMjft6gzF+K9tylyqS0sLob2AbMBB4Dzi33ikSkWig6d+nRRx+ldu3aALz++utcdtll9OnTh6uuuqpcwioo85eiPXepMimtGzAD2OacWwjkV0A9IlJNFJ27dNddd9G4cWPArw+anp5OYmIiOTk50SxRAqS0sPoA6Gpmk4E3KqAeEanmmjZtyrp168jNzSUhISHa5UhAlNgNaGYnA42Bf4c31a2IgkSkejvzzDMZM2YMEydO3NnyEtnXNatV+OtVIiLlZsfcpUmTJgFQs2ZNnn/++ShWJEG0r7C6AT8KcMfqFQ74vNwrEhER2cO+wupmILJLCIuIiByAfYXViUDzPbZpJQuRAHrllVf48MMPSUtL495772XVqlVce+21fPjhhxVWg+YuSXkqMaycc8+a2XFAP3QrEZFAmzx5Ms8//zyzZ8/mmWeeYfny5TRo0KBCa9DcJSlPpU0KPgu4P/y5K+daROQAXX311YwcOZJDDjmEmJgYrr/+em655ZZolyUSMaWF1QZgCJAbfv7Mvr7YzAYC5wHvAYPxLbIrgMuBjkCec+76gylYRPa2du1aJk6cyLvvvsu5557L2rVr+fbbb/nkk08YOHBgtMsTOWilhVUb4GN8q2qfLSszawt0B5KAc5xz55rZhcAgoF/4+R1m1j68IoaIREjt2rUZMWIEoVCI9evXk5qayvDhwxVUUmWUFlZZ+NuEZJd2IOfcEuBhM3uRXUszrQWa7vE8HdgtrMxsFDAK4JBDDilr7SISNnDgwL2Cqbh7L4lUVqUNnPgCqAc0Cz/KqjD8MR1YB4T2eL4b59wE51xP51zPir4oLCIiwVdayyof341n4UdZp5W/ZmZPhV9zOdDUzMYBOc65BQdarIiIVE+lhdUQ4CP8LUJGleWAzrnh4U/fLbL56fBDpNIaO3Yss2bNYvHixQwZMoRVq1ZRq1Yt7r33XuLiSvtRKvs5NFdJZG9laVktxYdW7XKvRiTArrvuOvLy8hgzZgyzZ8/m1Vdf5Y033uCDDz7g5JNPjsg5NFdJpHilhdWt+GHrzYHvyr8ckWB7+eWXOfPMM8nPz+eyyy4jNTWV7t27R7sskSqvxAEWZjbRObcGGOqce8k591EF1iUSSJ9//jknnngiOTk5TJw4kS5dutC8+Z6rkolIpO1rNOCOu571r4hCRCqDrKwszIy8vDwuvfRSvv76awYMGBDtskSqvH11A6aHV6RoEv6Ic+6TiilLJJhefvllAM4//3zOP//8KFcjUn3sK6xexF+rejn8UWsDiohIVOxr1fXnKrIQERGRkpQYVmbW2Dm312oTIlWB5jOJVC776gZ80sx+xXcHArpmJZE3f/58Hn30UXJzczniiCOYM2cOhYWFjBs3juTk8rtRteYziVQu+xoN+Bj+tvbN2P+1AUXKZOLEiTRt2pTExERat27N+PHj6dChAwsXamF+EdmlxLByzn0MPA4cBxzPHiuli0TCkiVLGDNmDGeffTYrVqzgvffe4+2336ZFixbRLk1EAqS0VddHARcXeYhEVMOGDUlJSaFu3bps2LCBU045hccee4xnn3022qWJSICUttxSHP4WITH4LkGRiLriiisYOXIkoVCIk046iUsvvZSCggJuv/32aJcmIgFSWljdCdyAv9XHveVfjlQ3PXv25Pnnd915RhNtRaQ4+wwr59xS4KYKqkUqOQ0HF5Hyss+wMrP6zrmNFVWMVG4aDi4i5aW0ARYPVkgVEnG//PILPXv25LbbbmPEiBEcdthhvPfee9EuS0TkgJR2zSrNzN4EtgM45y4s/5LkYDnn+Mtf/kKLFi2499572bRpE3fffTdDhgyJdmkiIgektJbVjcCrwN/Cn0slMH78eIYPH75zBYi///3vXHnllVGuSkTkwJXWsrob2AbMBB4Fzi3LQc3sMPyE4p+A/wAn4oPxCudcwQFXK2Xy3//+l9mzZ/Ptt9/y2muv8fPPP9OhQ4dolyUicsBKa1llANuccwuB/P047lHAOqAQGO2cGwV8Dgw6oCplv7z55puMHz+eXr16MXDgQFJTU6NdkojIQSktrD4AuprZZOCN/Tjul8BI/ACNX8Pb1gLpxX2xmY0ys+lmNn3Dhg37cRrZlxdffJF69erx+OOPR7sUEZGDUlo34E/hRwEwdz+Oezg+nDYDseFt6fjW1l6ccxOACQA9e/bUTR6L0NwlEZHSw+oW4Hp8d95dwHVlPO4y/DWrfOBjM3sKvwrG5QdSZHWmuUsiIvu++WIb/K3s6wO5+3NQ59w0YNrBlRY8M2bM4PHHH985NHzevHm89NJLTJw4MdqliYhUaftqWQ0HfgaGhZ9vKv9ygi0nJ4exY8fy4Ycf8sILL2Bm5OTkRLssEZEqb1/3s7ob+Ap/zSme0rsMq7y+ffvy448/8tBDD3HWWWfx+9//PtoliYhUC6WNBjwLeAaYGH5Ua9999x09evTg/fff55FHHol2OSIi1UZpraUNwBB2XbN6pnzLCbaMjAwuueQSEhISGDVqVLTLERGpNkoLqzbAx/iBFtV+SPmgQYMYNGj3ec0vvvhilKoREak+SgurLCAFyK6AWipMUOYugeYviYiURWlh9QX+tvZVSlDmLoHmL4mIlEVpYTWgyOfbgedL+DoREZFyU9pt7S8GMLNawB8rpCIREZE9lHZb+4HhT+OBLuVfjoiIyN5K6wZsjh8FWACMLv9yRERE9ravtQGLjkBwQFvgT+VekYiIyB721bKaFP5YA7gf+KHcqxERESlGiWHlnFtuZr2AW4F7nXPfVVxZIiIiu+yrG/AeoCt+FGC2mbV2zv1UYZWJiIiE7asbsACYCfwWf+NEh65ZiYhIFOyrG1BLK4iISCCUdosQERGRqFNYiYhI4FVIWJlZHzN7LvyoXRHnFBGRqqOiWlajgMuBp4FhFXROERGpIsy58r+nopm94Jy7wMzaAec75+7aY/8ofKABtAcWlntRkVEf2BjtIsqgstQJqrU8VJY6QbWWl8pS60bn3ODidpS2NmCkZJlZIpAOrNtzp3NuAjChgmqJGDOb7pzrGe06SlNZ6gTVWh4qS52gWstLZaq1JBUVVhOAJ/Grt19eQecUEZEqokLCyjk3AxhREecSEZGqR0PXD05l6bqsLHWCai0PlaVOUK3lpTLVWqwKGWAhIiJyMNSyEhGRwFNYiYhI4Cmsyqi4VTjM7HwzG2dmL5tZ0yiXuFMJtQ4xs6fM7BkzS45yiUDJK5uYWUcz+zCKpe2lhPf0NDN7z8wmmVnXKJe4Uwm19g//X33ezBpHuUSgxDrvDb+fs81sSJRL3KmEWoea2Vgze6US/Pz/zsyeMLMHzKyiRoFHlMKq7IpbhWObc2408CrQJ1qFFaO4WkPAFcAC/MTrINirzvB8vJHAhijWVZzi3tOj8PMGM4GlUaqrOMXVeh6QgZ8Yuj5Kde1przqdc7cB1wNTnXPvRbG2PRX3nh4DtAXqEqwJt8XV2ts5dyXwHXBitAo7GAqrsot1zuUAa/GTm3HOTTazBsAZwDvRLG4PxdU6BRgCnAYsj2JtRe1VJ3AT8Aj+/mlBUlytb+D/AHibYE3NKK7WdsCdwHyg2BUCoqC4OgHGAE9Ep6QSFVfrZOBU4E3g6GgVVozian3BzCYC/fCrWVQ6Cquy22sVDjNrC9wHXOOcy45mcXsorta+zrn/ANcAF0ezuCJ2q9PMagC9gduAXmY2MKrV7a64VVh6AoXAZipugn1ZFFfraudcHrCJ4Pzcl7SyTSvn3IIo1VSS4mq93jkXwvcC1ItaZXsrrtYk59xlwFxgZdQqOwgaul5GZtYDuBq/CscUYAYwHt+lkgNMdM5NjVqBRZRQa3dgIP6X6j3OuSXRq9Arrk7n3Pzwvhedc8OjWV9RJbynHYCh+FbgDc65zdGrcJcSam0FnBn+kqucc7lRKm+nEur8BbjLOXd1NGvbUwm19gd64bvYR4dbM1FXys+/A0aFQ7ZSUViJiEjgBaU7QEREpEQKKxERCTyFlYiIBJ7CSiQCzKxJtGsQqcoUVlJtmNldZvbv8Mz+180sJULHbQFcVeR5SzObY2Yvhh9tynic7uFVESaZWZyZ3b4fNbxYhq+5KzzdoqT9k/a1ukFZziFSXoI0N0SkItzgnFtiZjcBnc3sGKAlfpjvNcBs4F1gGjAIP3/mcuAeIBZYBkzHDw1eiJ94uQnob2a1nXNbwud5O7waA+b9A//H4Xbg78CzwCwgFVgD5ANfAkWXQmofDpffh8/9byANOBaoCYwIz53aycxmhL8uHRgNPAQkUWSFjR3TAszsLmAScFn4eEeF9/85/DwTuAt4Cj+XrHbpb69I+VDLSqqbB83sGfws/oX45Wiy8CHQBljknLsRON05Nwa4FR8OzfBB0yt8nM+cc38MP/8q/HxLkfOcEm6pPIj/o/Bl4EOgR3j/9/gQqu2cu5OSl8C6HD+PbxPwG+CQ8OdP4ick72m5c+6e8PfTAVgfXhLsvyUcPxWo45y7BvgB6IwPrczw+3EifnWWa8N1iESFWlZS3dy8Y0K0mdUCfnbO3WJmg/ETvLeHvy42/DEVqAV85Jx7wszOC2/PCn8spPilof5TpGXVCr9e21h8CwUg2zkXMrMdk3OthHpj8TfO+xk4CfgJPwn1j8A2fOgVVbSu+CK1Fb2mtuNctfeofcf3MiP8npwTPhfOOWdmxYWjSIVQWEm15ZzbamZLzWwckAh8UGT3f8zsCaAGvntwvJl1wYfGmj0OtRnoZ2ZNnHN77gMfILWBC/Hdc/vTozEev6RXDn5h0s7ACfhgKW3ZnDnAqHAX5I9Ftq8Mb2uHb0FtMLOxQBf82oF1zOyx8Dlvx3/vffDhJxIVWsFCREQCT9esREQk8BRWIiISeAorEREJPIWViIgEnsJKREQCT2ElIiKB9/9EUDnbP4VVEgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Graph days hospitalized\n",
    "# graph_percent_fam(solar_df, \"days_hosp\", \"days_hosp\")\n",
    "graph_percent_fam(solar_rev_df, \"days_hosp\", \"dayshosp_noage\")\n",
    "graph_percent_fam(solar_rev_df, \"days_hosp\", \"dayshosp_nosex\")\n",
    "graph_percent_fam(solar_rev_df, \"days_hosp\", \"dayshosp_nosex_noage\")\n",
    "# graph_percent_fam(solar_rev_df, \"days_hosp\", \"dayshosp_female\")\n",
    "# graph_percent_fam(solar_rev_df, \"days_hosp\", \"dayshosp_notfemale\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b82ae399",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:47.942153Z",
     "start_time": "2023-11-28T22:57:46.751237Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for pheno in permuted_phenos:\n",
    "    graph_percent_fam(solar_rev_df, pheno, pheno)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "272ca540",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:49.917215Z",
     "start_time": "2023-11-28T22:57:47.945122Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Graph days hospitalized\n",
    "# graph_percent_fam(solar_df, \"covid\", \"covid\")\n",
    "graph_percent_fam(solar_rev_df, \"covid\", \"covid_noage\")\n",
    "graph_percent_fam(solar_rev_df, \"covid\", \"covid_nosex\")\n",
    "graph_percent_fam(solar_rev_df, \"covid\", \"covid_nosex_noage\")\n",
    "# graph_percent_fam(solar_rev_df, \"covid\", \"female\")\n",
    "# graph_percent_fam(solar_rev_df, \"covid\", \"covid_notfemale\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "314fa91f",
   "metadata": {},
   "source": [
    "## Modeled without controlling for sex and age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "19b5ecd1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:56.384240Z",
     "start_time": "2023-11-28T22:57:49.919714Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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JYEIIIfySJDBXyAjTQgjhcxpcAnNozfHslLoOQwghRC01uARmObKV6PfGw9aFdR2KcIWUfoUQFWhwCYzDG1D2HMg6XteReI5c9IUQDUDDS2BJZjRn8jLrNg4hhBC10vASWH6O+Z2TXrdxeJOUyIQQ9VDDS2B5WeZ3TlrdxiGEEKJWGl4Cy3be+0roU6dhCCGEqJ0GmMDSoMu55kcIIYTfangTWl7+IdhzIS8bAoLrOpqqyfxlQghRroZXAlMKvrkN5v+rriMRQghRCw2rBHZ8N/zyJKQdhoDQuo7Gt0nJTwjh4xpWCezYTtjyLWi7/7ZCLN0kXprICyEaKI8mMKXUEKXU286faOeyMUqp55VS85VSzT15/DLSk8zvqBa+mcDqWzKqb69HCOFTPF0CmwpcB8wBxjuXDQU6ADHAEQ8fv6TCBNbSNxOYEEIIl3k6gVm11tlAIhDvXLYAOB/4DDi5vI2UUlOVUiuUUiuSk5PdF036YbAGQtthcPKN7tuvMHylxOUrcQghPMrTCSxTKRWESV6HnMtu01o7gGQgtryNtNaztNYDtNYD4uLi3BeNdkBEPLQaBKff7b79NgSSFIQQPsbTrRBnATOBAOB7pVQ3YJFS6i3AAdzk4eOXNOpx6HUpOPJNdWJIDFjLeQukBZ5vk/+PEAIPJzCt9UpgYqnFG4HXPHncKu38BRY/Ajcth7jOdRdHXV2IfSkBuCMWX3o9QgivaVj9wD662iSskEbmsTTk8C5XEo0kIyGEixpOPzB7Pmz8EtIOQaCzE3POibqNSQghRI01nASWeQTQpvQVEGaWSQms4ZJGKUL4vYaTwAr6gIXGFCuB1SKBNfQLoL+9fn+LVwhRpYaXwEIaQXA0jHwA4nvXaUg+RS7wQgg/04AacWiIaQ+hjSEgBE69ra4DEkIIUQsNJ4F1PNP8FJQyUvaaUTkimnnmeNKaTgghPKrhVCGW9sZIWPKEd48p1XRCCOE2DSeB/fgAfDa16HFQhLRCFEIIP9ZwqhAProL8nKIqvYaUwH5/ARq1kepMIUS90nBKYOnJEFZsYOCGlMAO/QNr59d1FEII4VYNKIEdhvCmRY/dncB8+f5WTDtw5NV1FEII4VYNowrRkQ9ZxyC8SdGykyZBTrr5u762GMw+AR9eYapOM45AbmZRJ24hhPBzDaMElpcFbU6Fxp2KlnU4A7pfUGchecW6D2HXr+b+F8CxnXUajhBCuFPDSGBBETDxa+hxYdGytMOwbzloXXdxeZLWsPwNSOhnkjXA0e11G5MQQrhRw0hg5VkzD+acaarX6qPENXBkCwycYkpg/5oPXc+r66iEEMJtGkYC2/4TvNTfTKVSICjS/K6vLRE3fGHGfew+DqwBZsQRi7WuoxJCCLdpGAks7bCpPitIWmCqFcH/5wTLPArf3A6bvylZHdpyIAy/x4z7CLDjZ1j6fJ2EKIQQntAwEljWMQiMKNkCrzCB+XkJLCgaolrA/Mth7rlwYKVZ3uVcGFRs5JH9f8OfL9dJiEII4QkNI4FllmpCD0UJLDfd+/G4w9Yf4PcXwWqFIdPg3GfhyFZ4YwR8OhlyMkquH9USMpIhO7Vu4hVCCDdrGAks63jZBNakG1z8Zsmm9f4icR18dCX884lphGKxmX5tt6yG0+4wfb6ObC65TVQL8/vojrL7y8uCZa+bZvdbF5p1HPmefx1CCFELDaMjc9Nu0KhtyWVhjaHHRebvEwe8HxOwLcmU/jomVLDClu/gy5vhkrfM451LYPdS+PNVU6Ka8Bmk7itaPygCRsww1YelRTU3v4/thNj2JZ/burBoqKm/XjO/m3aH856vyctyL4cdtIwiIoQoq2EksIFTy46yYc+DPb8XdfL1JVrDb8/A4kehcQcICDfL/3oNtn5vku+Vn5vfxRNYZSKbm5JaelLZBNa0BwyYBF1Gm4YuR7ZCWiI+UUDXQH4u7F8BLQbUdTRCCB9S/xOY1qBU2eWOfHhnLJzxILQb7u2oKpaXBZ9cAxs+h56XwEmTweKM/+K3YOOXJhlFt6zefm1BcO8h06S+9JiNjTtAvyvN3wl9TQvGg6tN9WT2CQiOLLs/b/lqGiRthKAouHUdhETXXSxCCJ/iA1+xPSwjCd4cBes/KbncFgzKCjlpbEtKL6zOq1Naw9LnTB+uMx+GC98wiadAYCg06QLBETXbvzWg7LLcDNMgJDez7PJ3LzT3xupK5jGTvNqeBjmpdRuLEMLn1P8Elnkc8rMhoNQgtkr53pQq2g79JsAVn8Ap08svOdbGhs/hwytL9hfbtwzevwSSNpRcNzAMYtrCxgXujaE69vxufve8BLqMMff+slLqLh4hhE+p/wks65j5XXwqlQJBkUUj0vsCiw2iWkHHMzyz/xMHYdMCU5opsPcvUBbTKrO0tqfB4fV1Nwjwrt9MSTmuCwz7r5TChBAlNKAE1qTsc0ERvjMSx7FdpjPywTWeO0ZsB/M7tViryz1/QLOepsRVWptTze9NX3kupsrsXmoamFgDIL63KYXt/9szAzD78nxuQohy1f9GHJnHze/iszEXOPcZCAqHQyleDalcW783JaTwcuJ0lxhn68PUfaaZvD3PtO7rf3X560fGm8Sx6StTGvMmraHHOKBYNeq41yEw3AxULIRo8Op/AmvUyvSLCggu+1zrweb3od9qfZgyfbqq239py3cQ3dq0MPSURq1Nw5XU/eZx4jrIz4JWJ1e8zVmPll868zSlTKfs4qWigtFTso6DNdD7MQkhfEr9T2BthkHroeU/d3C1c4T6cPcfN/M4rJ0HlkBo3r/ydbNTTYOFnpe4P47irAHQ4iSTxMA0mb/hD9Mp+lg5I3RAUcnL29VrSZtNCbC09GT0B/9CN+uF5eoFRYMVCyEanPp/D0xR8TQiK96Cr6ZXvQ+HHbKPlT8MU3lOHITtP5jm8DuXVL3+jsWmX1qrwa7tvzYmLYQB15i/LRZTlVhVP6+9y8wwU970yTXw8cSyy8Pj0IOux7L/b3jvEt9qRSqE8Kr6n8Aq42ozeosVfn0W3r3A9I+qyoo3zWzIygoHVlW9flRL6HeVGfLKW7SG7+82yakq23+EZTO914Q9K8X0/2pTfsnZ0v0CGHGvaYDy9vl1N0CxNPwQok418AQWCXmZpv9VMWU6Nq+dD8FRkLLXDO9UmfwcWDnXlKban+5aAmsxAM5/yTSj97StP8DH15iGEH+9amZtrkrX80A7YM9Sj4cHQOJa87ugFWR5OpwBl70HhzfAmve8E5cfW78/lfX7ZSYCUb808ARmGgVY8rIqX69g1PcBk8x4hPv+rnjdjQvMtCU9xkFcZ0g7CCcSK1zdlpkEyVs80zS8PBYLHN9lGo2Aa9WWzXpBRLyZFNMbEtdAQFjZ8StL63wOXPs9WX0nkJWXbSb13PCF+V8JIeo9SWCAJT+z4nXSk830JI07mXETIxNgwc1gzy1//eWzTHP15v0hriuEN6t0tPuoXd/Aa0O8dy+noC/Yth8gtHHR48ooZTpXH1hpRsPwtINrTMvI8oa+Kq15PwIDwgm0Bppq24+vNkNg/f4COBy1CkNKLUL4toadwDqNgimLsQc1qnidQ87qrMYdTWOHMc+ZC2s594NUQXXkwClmdIum3eE/WyodRT3s0HJofYr3BsyNagkWZ2JodbLrw1X1mwjtR5bfMtDdRswwPy6yWixYLRYzBNeVX0DzfmbYrGpUeZY3HmbwkXUEH1nn8j4AuS8mhBc17AQWHgfN+6Mr+6af6LyAFZRUOp0NU39hW3ogOw4cKrGqDgiFKYth4HVmQRXJISAjkaC0faYqzFssVgiJMn9Xp9WjxQoj74Pu48xjVxpO2HNg7Qcw7yIze/SRbeZeWlVi25skVF1Wm7nvOOJeUwW52s33xiQ5CeFT6n8/sMpkHoPNX2PLCiE/rFn562QdIze8OXtSFR0Lllms4Min+dJ7Yd1zMOQWLHm2osYglmLfC1a+DSvmwNRfyuw67NBy80ens932klzSfqRpIXnyDTXbftuP8NFVcPZjld+nUgGmw/GRrbD9J7MsKNIk7HEzixK8w276fSWuhX8+NiXSqu5/VcYWDKfcAu1Or/k+hBA+z6MJTCk1BHAWR5iutU5RSg0DLgUigP9qrQ9VuANPSz8MC6YRfNKdpFeUwM56lD1x5Qyuaw3gRKszCN73HXx4BW1sYShHHnRZa+6TFZe4ttwBcUMP/U1OeAuCYtq54cVUw0nXgiOv4v5xVWne3wzNtfBuM9Bu6wpKchaLGb9w9++mIUizXnDQ2SrTmbzs39+F5eAaVH62WW4NNEmutjqdXbskKITweZ6uQpyKSWBzgPHOZZcDJ4AjQJKHj1+5wlaIlTTigKKRK0otS21/HkxbDRe/RW5EczKaDiibvAqqwsppTn/opDs53P/2mkReO9agolmeayI0Bs55yvx+94KiFo3lsQVB6yGw+WszbNXwu+DCWeY5hwMCwtCdz4ELXoMb/oRrvoUh02oeW3GHN8AfL7lnXz5OGpyIhsjTCcyqtc4GEoGCu/8dgQeAjcCo8jZSSk1VSq1QSq1ITk72XHRVtULcvwLmjiEgbV/F+7DaoMeF7B/2LIcG3VP2+biuYAsxLfhKcQRGkNOoY9lt/EFEEzj/FTMNy/wriu4VlufMh6Hj2aZlYPFEbrFgHXkfllOmQ5/LTUdud/aF27oQfpjh+ggqQgi/4ukElqmUCsIkr4KqwgNa61zgWEXH11rP0loP0FoPiIvz4OjsgaYUUmEJbP8K2P0bjoBaDGZrtZkR3Q8Wu3Dn58I7Ywk9vKLm+/UFIdFw9Vdw7tNmShYwfbCO7jBToWz/yXQCz06Fi2abBhzf3GZevzf0/pdpDbrmfe8cTwjhVZ5uxDELmAkEAN8rpboB85VSc5zP3+jh41fOYoXA8IpLYIlrIawJ9uCYau+6xOj03c6H43uKntz6nRkjscmw6sfsa4LCYcC15u+kjfDltDIjm9DjYmh5Epw+A5I3eS+2yHjTYGXtB6bhSME9P61N6Swyvlr3ycrMOCCEqFMeTWBa65XAxFKLNwLfePK41TJ1Ccd2bi3/uUPrTOmptgbfZH4XNMFe+TZENiezaQ2aivuytETod7VJVhHxpuQV1tg8BtMZuuMZYPPiVCh9LjcDAx9cbfrj5aSbjugbPjcNPfpVMBdaDUmSE8J7GnYzeoDGHXHsL9sQUtlzIXmz+5q4OxyQmwk5qWb0+WH/Lb9xiD9rP9L8LijV+EKfqc6jIbqVaXGasgc+uw6OboNB10Ov8VVvXwlJVkLULUlg/3xG+P6NpLcoWZ1nyUuHtsOg5clQRSNFl7zUl9TITuQHxxAL0PdK2L271ruVi2gVAoLhlrWw8XP4/AYICDWjdXhr5JM6UtAisWeLqDqORAjPqfcjcZQ3RFAJK+cSvfPrMovtwTFw5WfQ6Sz3BBLTnuDjW8mJagenTIfolu7Zrw+p8r2uKxYLhMWYmbmv+wXaDYNju+CDfxV1sBZC+J16n8CqFBRRfiOO0g0Raqt5fwLT9pLZpB+c+ZDLm/lqUvDVuCoUEGnuRUa1MI9DY809u8Mb6jYuIUSNSQILiiy3GX2L3+4y90vcpXk/lHYQmuTC/GDC/SylPurBkWY0/sMb6yYeIUStSQIrrwSm7QSl7jQjTbhL8/4ARO5b7L59itqJaQtJUgITwl/VqBGHUsoKtAeStNYpbo3I24IjzYSWxSaUDEw7gMWeY8buc5fwJuwd9iy5kW1xYQYu95IxAcvYlpRO4+AWNNr1Ldjz6zocIUQN1LQV4ktAOPCeUuoirfVUN8bkXUOmsTOsT4lFQanOoYfc0QesmJxGndy6P3/jay0mM+P60CgqCvIyPHaM7YkpxEWFEhXqxb5vQjQQNa1CzAP2a60XAl4aF8hDgqNwBEWVmLsr6PgWHJZAMwuz8Ki6bAyS2bQ/nPcCBHumqXlWrp0zXvidq+cs88j+hWjoaprAdgMjlFLvA8fdF04dSNpM7MZ3sGYXvYyMpgNJaXeuGcdQ1G8OO2R55iO89XAaAGsOnCDf7sJEnl4mI9gLf1fTBLYaGAlc7/zbfx3fTczWj7BlHSlclNW0H0d7TKrDoHxPTUpK3tqmVvudNQy+uMmlfUTuXkjQUddbLfZuGc0Ll/UBYMUe//6eJ4QvqlYCU0olKKXeAV4EXgNeBoZ7IC7vKT6lyvHd8MN9WHL9qH+TpyT0bRiNP2Lam0GItR3sldSGb/uRxv/MMaPbu8Dh0GitGdm1KYFWCz9uPOymgIUQBapVR6a1PghcpZRq5VykAP8eq6ZwUssMWPwobPoaNbIfpo2K73GpIURDSDzu0qQbbPySLzelkWYP5KH+5ayTeQy+vIn80Dhyo9qbFqvF7pmW59t/Enn2h628O3kQM6/sT/cE7w5dFXzEOT9bi1O9elwhvKmmVYgvAK8DdwDPuy2auuBMYKFH1sP6j2HwTdhDGtdxUKI2qlUN2bQboNmzZzfLDmnu+nQdf+08WvS81vD1vyHzGIf63U5A+n549eTyO0Dn5xKa+DdozTfrEjmRnU+zyGBO79KEJpHBbnltQogiNU1g+zGJ62P8/R5YkPlmHL3zKzO80CnT6zggUYKnqzKbdAMgMmMP7aIs/LHjKHd8spb0HNM3LPzAr7DxCzj9bnKj25EfEmtGtv/uvyX6DpKbCfP/RfNlDxG491d+3pLE6J7NsFoUWmveX7aXb9Yleu51CNEA1TSB7QSOAtOBJu4Lpw6ExpB40t3m72F31uko5V5rUt5Q7m+5olFbjg/6L6vs7eja2Mozl/Zm//EsHvu22MSbHc6AIeaLjSMwEkbcB7t/I/zAb+b57FSYdyFsX4TdFkLqga1k5zk4t2c8AEopPvx7L2/8ttPbr06Ieq2mCexdIAJ4BXjLfeHUAaXICEvgeOuzof81dR1N3WmoSc1iYVnLa9mkW9M2yspJbWKYcmo73l+2l78P5phpdq74pGSXiv4TIb43jf+Zg8pOg0UPw/6/4eI32X32XJ5yXEFcRBAD2hQNRXZG16as2ZdC0ols779GIeqpmiaw14DWQAvnj1/LjWhBUp8bvTtTsHCfWibf3PTjjAzeQqsoczrcdmYnbo7+k4MrvsZhzyvbYMNiJX/UkwRkH8W++XsY+YCZY6zHhTgCwhjRJoA7zuyE1VK03ZndmwKwaHNSjeMUQpRUm35gy4HfgKXuC6duaK3JzvO9jqaifOsd7VjvaOe2/Z2vlzCHhwjPTwEgOG0Pt+XPZlLUKiwVtDZ8/2AzLsudwe/h57Aqyc6D62OwO8w9sXFHZ3Pp3gdLrN+5aQQtY0KkOb0QblTTBNYfGA9cCUxwXzh1469EB1d/k82hVKne8Ue1HlGiqWnIEXhijxmZ4/MbsFgDSRn4b7SysvdoydkKjqbn8PTCLeTE9WRo+zD+3HGUuX/sZvr81fy8J4/0fAts+hqyTxRuo5TirG7NSMvOw+HQeFvwkXVFTeuFqCdqOlbSBuApIBvw/tnoRjn5dnamQEqO5rkft/K/i904An01ZTf2zrHLm26+oU5Bn51n56rPU/kICDqxG/58Bfb9BeNmkq8bM3tNNj9+tZSFt55WuM1TC7eQmWvnpn6hKKW46fQO2CyKx7/bzNdAZqtB3Gr/CrZ+D70uLdzuntFdS1QrCiFqp6YlsMaYEenfAGa7LxzvS83M470NuQRb4eOV+9hyKK2uQxLFeHq8vm2H01mebCPLFkVo8hr4+f+gyxjoNR6AUe0CyMy1c+en69Bas+WonQ9X7OOaU9rQOspauJ/rhrXn8XE9iAiATp27Q2Rz2PB5iWMVJC9fHBdRCH9U7QSmlDoXWAn8XuzHb6U5+/tM6h1MeJCN/32/uY4jErWV3biXy6XZzYdMNV9WRGusOanwrw9gzHOFDTdaRlq5+5wu/Lwlme925tEq0sL0kR25ZWTHMvv616DWfHphBB1jA6DbBbD9J9PEvpjZv+3k1Cd/dnsSkypC0RDVpAR2AEgGtjl/PDeZkhekZ5sE1izMVAUt3pzEnlR7HUclvGXLoTSCbBZOdLucpJ5ToP0ICC/ZtfGqwW04pUMsr63OJiVHc+sZnYgIDih3f6qg0Ufv8TD03+aeWjHxUSEkpmazUgb3FaLWqnUPTCkVD1wEnAb8ghkLcSgw3/2heUfBiAuhAYpLhrRhcPtYQo6sr+OoKuZKyaKh3s+qiS2H0+jYNJy8uO5lkk0Bi0Xx1MW9GffiYg6eyHFtx/G9y50QdVjnOAKtFn7adJhB7WJrE7oQDV51B/NNVEq9AWzCVB06gCc9EZi3pGUXJbDgACu9WkSz7Qhk5/t125RaK50Ea9LAxFvb1EbnphGEB9uAw2Cp+HRIiA7h+TPDCAuoRqVFfg7s+BlaDy6cNDM8yMbg9rH8uPEw94zuWlRiE0JUW7WrELXWe4FmQADwKnC7u4PypqEdGzNrVBgtI4reivf+yWT6jzKlSn1S0X2xGWO6cesZrs283TjESoitGgkncR18MB42fl1i8RndmrL7aCbb62gmaiHqi5o2o2+DqUZ8FRjltmjqQHiQjbbR1lJLLexMzSctO6/Cex3CPbxd4iou3zlnl8dKQS0GQEQCbPwS+l1RuPisbk05mp5DZIh8toSojZq0QoxwbncBcBjo5uaYvGrlnmN8uS0XXWxk8Q4xJqFtSpQm9fXZV9tz6f3QDxzPqGQiy9pQCrqNhV1LIKfos9Q0Mphbz+hEU5liRYhaqUkrxFe01jdjRqRfAxxya0Re9uPGJGauzi7xLbx9I5PANhx0X/8jh0Pz1toM9qbmu22f/qY6zdu9YVeKA4tFER3qwZJQ1/PAngPbfiyxODvPzo8bD3M03cVGIUKIMmrakRkgUmvtwM9H4kjPySMsoGQVUmywolGwYsPBExVsVX07ktN5f5OdV1Z5f7gqT3cG9kfZjXuxMyOYzk0jPNuQotXJENoYdv1SYvHuoxlMeWcFP8jYiELUWE0SWLhSqh0Q4fwd7uaYvCo9O5/SX8CVUpzXIZB+rRq57ThrnQnkxn4hbtunqDmH1uw9lkmXZhGePZDFClN/hnOfK7G4c9MIWjSSwX2FqI2aNOJYixnE9x/n77VujcjL0nPyy21ZdmWPIDr2aeW246zbn0KoDVpGWsjJtxNkK91wxL/4UlWgS+zZ5Bf7uCel5ZCVZ6dzMy9MYBpd9nOklOLMbk15b9leMnPzCQ2saXsqIRqumjSjf6j0jycCc5eq7rukZecTGlB+FVJqVl5hR+faWrsvhY4xVt5cl8OYF5eWaDRSGV+7b+SvjmfmceN7q/ls1X4AAiyKS/q3YGBb95WyK/Xj/eanmDO7NSU338GvW494JwYh6pna3AOrF16f0J97h5St1juU7qD3Qz/w1dqDbjlO75bRDOzcmmYJrdmWlM7fu+vfUEK+mmz/3n0MuwqkcUQwt320lvu++IfIkACuGtyGDk08XIVY4EQirHoH7EVfiE5qE0NksI2/dh71TgxC1DMNPoE1CgskNqTs29AkTBERZHNbS8SHx/bg/N4JDO3QmIggGx8s3+uW/fpq0vAVh09kM37mn/yw4RCPjO3B1NPa8e5fe5j41nISUzOr3oG7dD0Pso7DnqKxrwOsFr6dfioPnOfXPVGEqDMNvuL9lZ+3E5uTT/9mJd8Ki1J0S4g0LRHb1O4Yadl5hDnvcQQHWBnbN4GPV+znyrZhRATWn6GEPl2xiyVbj9EmLpxmkcEoIDY8iPjoYBqHB2F3aLw9Hdbnqw/g0DCsUxOsFsU9o7vSp2U0N763inl/7uKs7vE13ne1vjh0GAm2ENj0FbQbVri4RaPQGh+/vpKxPIWrGnwJ7IVF21h1qPz7XN0TotiUeKJwqvjqKF4yenDBRs54tqgZ9WUntSIn38Gi3Xk1C9rHFNzPO6dHMxIahXA0PZdFm5OY//c+Xv55O4dPmK4Dj3+3kaveXEZmrnf6wmmt+XjFPga0bkTzRkXVxKN7xvP+5EHcNKKz249ZYYk4MMwksc1fg6NoKhWtNQ98+Q+v/Lzd7bFURaZgEf7OoyUwpdQQ4Drnw+la6xTn8q7AC1rrszx5/Krk5NvJzXdU2Iije0Ik2XkO9qc5SkxeWF1r96fQtnFY4eMezaN44sKetLXvqvE+fcWqvcd58vvNzLxyAKHBIdx9TrfCb86r9xzneGYeHZtEsG5/Cst2HScuPJCQAO+0wFy9L4UdyRk8cWG7Ms/VZIiwWlfV9v4XhMZCbjoEm9aPSil2H83kl63J3Di8vQzuK0Q1eLoENhWTwOYA4wGUUkHAFMycYnUqI8dMn1G6I3OBwe1j+b9xPYgKqvqikphu53BG2ek40rLz2JGcTq8W0SWWXzawFTHl3HvzJyt2H+PyN/4iMTWbE1llS5M2q4W4iCCOZeQy5Z0VNIkI4tlL+5S4SNud4xF6wk8bDxMcYOHcXjWvJnSrrmPg/BcLk1eBgsF9dyTL4L5CVIen74FZtdbZSqlEYIRz2X+BZ4EnKtpIKTUVk/xo1cp9fbFKSy+cSqX85xOiQ7hiUGu2ram4wcXKPcd549edLNyQQeMQ+PNkBzZrUWJafyAVraF3y7L1+Uv3ZpOUqbmzT61eRvVpu/mphT93JvPEd1voGh/J3GsGEhcRREpm2QYvufkOpr67grTsfJ64sBfhQTb2H8+kRaNQHA7NVW8uQyno26oRPRKiiAy20aO5e+593HF2Zy7u38K3BmTWGg6tg2a9Cmd9PqNrE+77An7YeNh7rSKFqAc8ncAynSWueOCQUioUGAw0BwYqpUZorReX3khrPQuYBTBgwACPDVVVfDLLiuw7lsmqQ/n0K9XIw27P579LcliX/AdRIQEMa2UjOx9SsvJoHB5UuN465w3pXi2iOXA8q8Q+fj9gZ1mindvtJZOep6Vl5VaYtF3x186jPPn9VjrGhTF/6smVJgibVdEqJpSwQBvv/LmbDQdP0DImhB/+PQyLRfGvQS3YdjiDgynZ/LbtCHaHpmuzML67dXjNA3RSStEuzscGilk7H764Hq7/HZr1AMwszT2bR/HTxsPcOLxDHQcohP/wdAKbBczEzB32PdBGaz0aQCk1r7zk5U1d4yPY8NDZ7P7njwrXeXXJDhaszeGDyX1LLLfqfLrEKMad3I1LB7Tk4KY/AUokL4CT28Vy1zldiAkLLJPATm4eyE97sli1N4WBbWPc9Kqq9n/fb2PLoTQW3T6M1rFhVW9QSsuYUE5qE8O0ER0qL9048njl5538sMnUFjePDmF45zjG9kkonMZkTM8W0NO0OMvKtfPpyr10ia99KeTJhZsZ2CaGaSM71npfbtXhDECZ1ojOBAZwyYAWbDucjsOhsXi7qaYfkpaKAjycwLTWK4GJFTw3wZPHdoVSirAgG4HWii8YPZpH8sHyvSSlmVHDc/Lt7DqSgdUWzJS+0LFP2xLr7z2aSUCxoan6tIymT8vocvc9IN6GVcGizYe9msD2Hs0k36H58O99/HdUF5e3O5qeg8OhaR4dwj2ju7q0zfBOsZzVI4Eh7WM5mm6mLanoohMSaKV3y9q/D0lp2SzddoS+bhzLEtx0sQyPg9ZDTAI7/e7CxVcNblP7fddjkrBEefy7FUEtrdmXwqNfb+REjqPCdbonmBOm4Ab7K4u3M+bFpey0dSzTKi0zT3PW87/w2pId5nFuPst2HiU7r/z7TWEBil5NrCzalOSOl+OSrFw7ac6q0793H3N5u6S0bP7zyVoe+mqD6wezBNCzZWMu7t+ChGjXBzGe//de3v5jt+vHcVq28yh3frKOWz5YjVJwcb8W1d5HcR2bhNOxSfWqIHu2iKr6Itv1PEjaAEd3lFjscGh2Hcmobpg+T2ZDEJ7SoBPYhoOpzF66i9yK8xddmkVgUbAzOYNNiSd4dckOzu+dUO4FOTRAMbpHPJ+u3E9mbj7/HDjB+Fl/Fd4HK8/JCTZsFkVatnf6hO0+ai6QjcMDWbsvtcLkWtrbv+8kIyefS09q6cnwAHPB+2jFPpfXz3PkkefI443fdvH1uoMMahvLYxd0p1Ws652EvTqiSZcx5vemr0osfvqHLYx6/lev9ZPzFZLgRE016ARW0AoxrJzR6AsEB1hp2SiUbUlp3PnpOqJCArhvTMVD/1w1pA0ZuXZ+3pzE1qQ0LMpUQ1bkgk6BfH/raV5rKbfb+Q3/jK5NybU7+OdA1ReO7Dw7f+9J5bSOcYUlUk/q0TyKjYknSM2sPKlrrXn2hy3sO5aJ1pqHx3ZnxYwz+feZneje3A3Vhwl9zY+7RbeEqxbAoOtKLB7aoTE5MrivEC5r2AksJx+lILjUncDS38ZvPaMTLRqFsm5/Kg+N7U6jsMAK99mnZTS9WkTxzfpEth1Oo1PTiEqnyrA4m1Ln2yspBrpRx6bhTDi5NWd0bQrAcheqEZduO0JWnp3B7Rt7OjwAejaPQmtYtqviQW7tDs2dn67jxcXbWbYzlUBrIAnRIYQE+sk0Ne2GQUDJUvxJbc3gvj9tkjnCqktKcQ1Tg05gadn5hAfZqhz9oEOTUKKDFaN7NuPcnlV3ir1qcBsSU7NZtTeF3qU6MJfns1X76f/oT2S4aeqWynRoEsH4AS1pGhnMpzcM4ZohbavcZsnWJMICrfTy0g30zs0iCLJZ+Gtn+ck1z+7gqYWb+WjFfm4Z2ZHLvFCtWR6X7ndVxJ4PS56Afz4rXBRgtTCiSxMWb06q0fBlQjQ0DTqB5eTbiQhyoSGm1lzStymvXN7PpaF+xvSK5/ELewJmGpWqtIoJJTUrj1V7PT/FysaDJ0h1jprRv3Ujl0osD57Xnacu7k2Al/qqBVgtDO8cV+5zdofmka//4fcdR5lxblduO7OTfw6/ZLXBhi9gxZslFp/RrSnHMnJZuaf+TbdTwFdKS74Sh6i5+p/AdD44cst96vELe/HbnSPKfa4EZQVbqMsXyuAAK+1jg3jqgk6c2a1plev3bdWIRqEBLlXn1dZVby4vbOGXmJrFUws3V9nyzWa10DLGu6Omz7xyAPeXM81IalYeFoti8tA2TD617BiHfqXreWZ6lYyie17DOzdhztUDvFbaFcKf1fsE9vGK/Vw+Z2WF4+1ZPdRpNCAgkC4JUcRFBFW5rtWiOL1zE1buPu7RqqO07DyOpOcUtqDMy9e88vMOlm6vuNHAi4u28ewPWzwWU1Ucpf5vMWGBPHheT8b2qV0TeZ/Q9TzQDtjybeGi8CAbI7s2JdhLAx4L4c/qfQKz2Wyk5RT1fSru2R+21Ki/UXnKNsNWYKk6eRUY2bUpaTn5bD50wi3xlGf3ETOBY0J0MAAtY0JoEhHEigpKfg6tefevPWxL8v4gs1prxr7yO28uLRqxf+We4+w5Wo/6STXrCdGtyzSnT0rL5tkft9bLPmHeJFWE9V+9T2DRoabF4BHnSBrFfbM+keW7PF9t54rTOjXmkv4tiA1zPelV1y7nxT8hypTAlFKc1DaGvyt4DzYlniA5LYdRPZp5LKaKKKUID7KyztnM3+7Q3PHJWm58b5VHRq+vVYOMmlIKel5iWiMWe012h+bFRdv4/p9D3o2nnvNWQpPE6T31PoE1ciaw5HISWHqOaYXoCyKCA7hqcGuaRXounoI+YPHOEhjASa0bcTA1m6S07DLr/7njKIHOlnF14eS2sew+kkFadh5frzvIzuQMbjq9g3822qjIyPvg0ncKR6aHosF9f9woCczbJPn4l3qfwKJDTAfhI+llG3Jk5NgJL90JrC458li+I4k7P1lHTn7tpjspz5he8bx8eV+CbEX3Vwa0iSEiyEZiaskEprXmz51HGdqxcZ1NRzK4fSwaM6L/C4u20blpBKO6e7806BVZJVsdntG1Kav3pZT7xcuXSQIoq7z3RN4n96j3CaxxeBBndG1Cs6iSVXMOhy4sgXl1GKHKWALZk2rnwxX7+Nesv0g6UbZUVBvt4sIZ0yuhxLJu8ZGseeCsMv3VsvLsdEuI5IK+zd0aQ3X0ahFNoM3Ca7/sYGdyBtPP6Fg/R2r/7Rl4tjvkFc1WcGa3pmgNi7zYqVkuqsLf1PsEFh5sY/rITvRvXXKU86w8OzFhgUTXZmIsD7ikf0tevaIfmxLTOP/l39l6OK3wuUWbDvPW0h0s31Wzyay/WnuQfccySyyzWFS5LTFDA23cfmZnzu+dUOY5bwm0WbhsQEuaRATRs3lU/S19JfSDvAzYUTS7UNf4CDo2CedoRvldQOpKQ09ynnr9Df19rSkfqj/zHK012Xn2Ek2Tw4JsrLrvTACf++CM7hlPm9gwpr67grs/X8cnUwcCJgF9uSaRL9YmkhAdxjkujApS4ERWHtM+WM2Mc7syqG1sied+3pLEQws2cGa3pny6aj87ktMJD1TcOKzqUTo87ZL+8VzSJ5auLZvWz9IXQJuhEBxtWiN2ORcwjVgW3npa/X3N9Yi3pnqRKWXKqvclMIDbP17LTe+tquswqqVbQiQLbh7KqG5x5OSbFmoPje3B/Kkn07lpBNPnr2HptrL9t/LtDtbvO1qmP9nBVFM91bZx2QksI4MD2H00kzd+28VHK/ZxPDPXjN+ofODjoaxgsXl1xmqvswZA59GmP5i9aADjguTlrXEya0JKDqIu1eOrQpGI4ACS00veDN+elMZ1765gU6Ln+l1Vpap7bzFhgUw5rRPBgaYlZVRIAKGBNu4f0512cWH85+O15Oabi5vWmp82HubM537lni83sXpPyeR2MMUksDblJLD+rRvx4mV9eGviSWx46Gy+nnYqE09pD8oXCugKLBUPnlxvdD0PslNh928lFl/+xl/c/dn6OgpKCN/mC1coj4sODWBzqUR1MCWbhRsOM+XUdiVa5fmD8GAb71w7kKMZueTbNduT0vm/bzfy185jtIsLY/qIjgxoW3IswYMp2VgUtGwUypZDaWX22baxmbixXjVR9yftT4cxz0Oz3iUWx0UEFQ7u66lRY0TFpNquZrz1vjWIElij0ACOpOeW6ACb7hyZw6ea0VdDk8hgusZHou25fLJyD1sPp/PI2O4svPU0znCOv1hQOgNThdgyJpRAW4P4l/ufgBAYcA2Elbw/eUbXphzNyPXKQM9C1ERdViP759W7mqJDA8m1OziRlU+Us9VhwWSW4UE2jud7ZzZkT0jPddClWQSvXXkSkcX6a/3v+82EBVmZeeUAACYPbefSuIyiDuWkw/qPoMVAaNYDgOGd4wiwKn7ceJiT2sRUsQMh3M+XS6EN4ut4t/hIbhnRAYrVwBSMjRgR5FvN6KsrIiSYC/q2KpG8AJpFBvPjxsOF975iwgLpllDxzNDCB2gHfHcnrHm/cFFEcAAnt4vlp40yyWVD4kqpRhrQNJAE1qlpBLed1ZmokKKLfKDNQvPoEMKC/Ov+l6tG9WiGBj5Yvpe07Dw+Wbm/fg2EWx8FR0K7001z+mLV3dcObcvU09p5fZJLX7hAHsvI5YPle3ngq/Xc+uFqPl25H4ADKem8uGizR8bFFP6jQVQhaq05kp5DoM1SWFK58uTWXHly6zqOzHOaRgYzsksTPli+jyYRwbz9525GdG1C69iyrRCFD+l6HmxbCIlrIaEPAKd3dmEsyvx8tKX+fB/NyM3hyjnL+GOH6RLSNDKIFtEhhDonYD2SnsuPm47w9bpEzqvDzvb1jS9XF5an/nziK5GWnc+AR3/ikxX76zoUr7pycBuOpOfw6SrzuttK8vJ9nUeb/nelplg5fCKb79YnVrjZruN53PJjJvuPZ1a4jr9w4CBfZxMZEsB1p7Xj62lDeePKATx4fo/Czvs9EhrRPi6Mx77dRGZu2amSRMPQIBJYeLCNAKsq0Rfs2R+3cucn64A6mkrDC07t0JjHxvWkaWQwNouieaOQug5JVCUs1ozMcXx3icUfLN/Lje+vKndw3zy7A7stkP3pDq6YvYzDbh5D05vm/r6LnUmZRAVF8crl/fjvqC70aB5VpnuH1aKYelp7ElOzefXnHXUUrf+rSTWxL1QtF2gQCcyiFLFhQSXmBFu/P4VNbpw80heToMWiuHxQK05k5dEsKlj6EfmLKz6Bi+eUWFQwuO/izSUbc2Tn2TnlicX8k2znseGhHEnLYcLsZaRk++7oHRX5YvUBHvxqI9/9U3FJs7hu8ZGM69ucWb/uJDE1q8Rzu49kkJmfSY49h6Pp/jWivyf5UvJxhwaRwAAaRwSWKIH50lxgnrb/eAaBVklefsPm7O7gKEpC3eIjaR4dwo8bk0qs+tOmwySl5dAy0kLXWBtzJp7E3mOZ3P1LJum5vtnAwe7QZRqkrNufwh2frOXkdjFcP6y9y/u665wujOvbnGDnYARaa15atI2Rz/7C1sQsUjIcnPbkz9z92XrSsv23u0xN1LdkVZ4Gk8DiwoM4UiyBpWU3nAQ26ZQ23DrS9YuC8AE/PgBvnVP4UCnFmd2asnR7Mlm5RXPFfbxiPwlRwfRpYi7gJ7eLZeaV/WkUBFbMBdsTc8vV1I7kdKa8+zcXv/5HYVXnX7uO8PDXG2kdG8bMCQMIqMa4l00jg/nfxb1oFBZInt3BbR+t5Zkft3J+7wS6xTciIjiAfw1sxUcr9nH9vJXM+2sXn67cX/ieeLtlp3CvhnEFB64Y1JqM3PzCbyTpOfl+OwpHdfVv07iuQxDVFdII9v0FKXshuhVgRuWY+8duVu87zpD2jUlMzeLXbcncfHoHrJaiktnwzk1IyAhGKUVSWjZnPvsrpzaHCzoG0rGuXg+wKfEEV85ZRp5dM6Z3PHHhpqS5bOdRIoJtvDXxJDPQwLHq73vXkXRumb8GgNvP7MTNIzrwz4ETBGJhxphuXNS/Bbd9tJoPVxzgwxUHOK93AnmOPGb+upM/th8nISqE+OhgAqzQNT6SrvER9XsA6XqiYVzBoXB4pYIE1rZxmLTKE76r63nw0wOw6WsYfCMAg9rFsOyekTSNDAbgs1UH0Bou7t+C3H0lqxYLGj3k2zVndWvKF6v38+2OPGbFHS48F7xp2+E0Hvp6I8EBFh4e24OWjUILR9u/+fROALSMCa3x/o9n5hATFsDDY3uUmbQVTFJ68qI+ZOfZaRIZRKDNgs1io3fzKJpGhHIwJZvE1Cx2H81g5Z4U/n1GZwB+336EqJAAusRHVFkyzM6zk56TT74jH6Vgzb4UmkeHoLX2yhij/tYE3h0aTAJLz8ln95EM8uwOAqwW3p00yOsxNKQPlqil2PbQpLtpTu9MYAFWS2HyAjNvXFRIAK1jw9i2r9T22oEtM4mEtS/z1EW3c2nLFO79JZOb3l/Fu5MGMbCtd4el2no4jYhgG+9PPpnUrJL3otzRuKhfq1jevia2ynMsOMBa2BdSoTi1Y7MS26zdl8KxjFyUUmitmfP7LpLTcnjs202c0qEx7ePC6dsqmp5E8eWaA2xPSmf13mPsPZbFgZRszusVzxUnJ2B3aCbMXka+QxMWZKVVTAhjejXnnB7NaBcXXuvXK4wGk8B+3pzEtA9W8/K/+nqlM68kK1Fr3c6HJU9AehKEm87Me49m8sCCf7h5REf6t25U7vxuLHqYRkePmNE8Nr0DR7cR3eYy/m9YKHf+rvltW7JbEtjhE9m8umQrV57cAojihnkrWbMvhSCbwmqxkJPvoFPTCKYOa86onk25eWRHwoNsPt2wwKIUjZ1Vm0opJp3Smie+30paTj7fbzhUuN6ux0fz6s872JaURmx4IK1jQ7mgT3MGtYsl2BZAvt3BnIknsSMpneW7j7L1UBpPLdxCgFUxNS6cAyknWLbzBDuS04mLCCIlM4/m0dLNpboaTAIr+FCmZOYRHZrHOS/8xvSRHRnVo55OUy/8X/cLAVViYtHosACWbj/C37uP8/qE/gztWOr+5tEd8PsLBLQ6g6TeN9E4vhUsfpSEQ1tRJ93NFzeNIMLZeKl01VbwEdMvkhanVhnaiew8rn5zObuPZjDa2bm4d8to0nPyyMq10zQyhCCbhbaNw7ApKxZl8ctGU9uTi6YeGtMrnsxcOyO6xKKUYt7kQc6pmsw6BV9a1+9PxWa1MKxTHMM6xRUOwtw0MqiwGnL30Qze+mN3iWN1bBLGJ9efUjjguKia/32iaqhgJPbjmbnE5QSxKfEEWXk178Ff30pY9e311AtxnWD4nSUWRQYH0KtFNCv3HGfB2gNlE9jiR8AayNEul4NScNodEBFP6IJptPj9HoL7/QVKsfnQCf6zKIMRrQPpYk0kJiyQ9FQ7CeFVN1zIszu4Yd5Ktielc9+YbrSJjQDg+mHtOaW9iaf458mXS1xVuXpwe64e3L5EcipQ3dkdmhSr/h3Srhnzp8QRFxlE0okcFm1KZOGGJLLz7UQhCcxVDSeBFSuBZTqbIYf7+Uj0dcnfEl7peP0m/rws2LEYWp8CIdEADGsfw8o9xxnXt0WJVYOOb4ENn8OwO7EHF6si7DuBw3u3EH7wD8g8ChHNyMlzsOeEgxdXZsPKVYWrPj08kG6VhOPQmhcXbeP37Ud55pLedGoa4cYX23AopQgLstE+Lpz2ceGEB9kY06sFTSODybc7SM3KKzH4uChfg0lgkSE2Aq0WUrJyC8dO88cqDdHAHN4A8y+HcbOg93gAbhzZiVPax9K/fdHklx2bhMOydyEsDoZMg01rSuwmrfVZpLU+i44Rpsq8d8toProggtQcTVSbvhxNz2XvtrX0bmrOiYUbDhEdEkBoYMlzJHXPGlbsyuCOsztzUf8Wfl268jUFjVke+mojP248zH1jumGzKvYczaRFoxCy87MJsgbx69Zk2jcJ91rrRl/WYK7gSimevrQ32qFJcg4pFdFA+oEJP5bQDyISYNOCwgRms1ro3z6u7LqDroPgaAiqpFSUfcJM2wLYLIrYEEXHePN4W0YgAImpWdz03ipiwgK5uH8LvlhzgBW7j/HOtYOID87ijXNCOHmwdIz3lIv6t+CzVfu56f2ikvE1p7Th7B7RJKVrJr+9EoDgAAvn927G/y7q02ATWYO6gp/fO4H1+1NJz8lnUNsYGoUF1nVIDYor1XY1qdrzm+rAmrBYoOsYWPUu5GZAYAUtaHNyILYTtBxQ4a4abZkP34yHO3eDreLPfnxUCPOnnswtH6zi1SU7CLJZ6NMymqMZOWALp7GNBnvB9IY+LaP538U9+Xv3MU5qE0vrmDBaNw5lz5FMApSD+VNPZntSOgvWHuCjFQdp0SicW0bWrot6dp6dVXuO89nq/Ww9nIbWih7NI3n8wl5k5Wdx3+dbsFosJEQHY7MqgmwWhnVqwoX9WmDXdh5asAGrxUp2vp3sPAcdmoRy3Wnt3PSOVKxBJbCdyemsP5BKrxbRXOEDc4HV1YXXly74vhSLz+p6HiyfBdsXmab1pe1bDn88D/2vKVzUsUnZvka5Ea0gLwMOroZWlfeDHNAmhpf+1Z8DKZmc3aMZQc6xBrcdKLledVouCte1jgmndUx4mfMj0Gahf4tGnNwulp7No3hh0TZ+2nSYqdVMFg6HZt/xTPId+Wg0l836izX7UrAoaB0bSpvYMJpFmmb9VmWlc7MI0nPsHEjJZt+xDHLtmmCbjQv7tQA0+Q5NSKCFyJAAQgKsxEXYvPIlx6MJTCk1BLjO+XC61jpFKXUFMASIAf6jtT5Q4Q7cbNavO1m44RDvXFv5ySsXVd/W4P4/rYZASAzs+rX8BLZ2PuxcDEOnVbqbrNju5o/dv1WZwMBcLNs2Di9MXjXliSTX4D4D5bAoxS0jOtKhaTjBAdYq74ll5dr5desh/t5jBvnNzLXz1jV9sVkV00Z0wKIUoYFWQgNtJd7fQGsgU04t2xKz4LFV2XhsXO86aXnq6RLYVEwCGwiMB2YCaVrrm5RS4zCJ7GMPx1CocXgQqVl5fLRiH7d/vIYf/j3MW4f2e3LBqENWG1z3K0S1KPucPQ82fgGth0BA5UMxOYKioEk32PM78J8qDyulK99ntSjCg2xk5dp58KsN9EiIINfekpaNQnBojcWZ0BasPcjdn64jI9dOZLCN07s0YVinOAIsgQRaLYzsWrabgD/wdAKzaq2zlVKJwAgArfUCpVQcMI6i0lkJSqmpmORHq1at3BZMXEQQDg07j2SUOzGgqB1fSXK+EodbRbcsf/muX0zT+A4jKt28sEqxzVBYPc8kvorWqYaIrZ8RkJUMfaR0VZeUAq0dvPPXPt75y4wrFmBVTDmlBT1b9KJjk3DG9Eqgd8tousVH0qdVNOB/Cas0TyewTKVUEBAPHAJQSnUA7gRu0VpnlbeR1noWMAtgwIABbpvvoGA0joMpWQ1mJHpRjyy8Fyw2OPOhomX/fAZBUdDSxbE9e10GTXuAI79GCau0/LAmNNv4Jqz9EHqP91ipTRr3VC44wMqD5/dk//EsQgOt7D+eyeq9KbSJNaXyrvGR/O/iXn6fsErz9FV8FqbaMAD4XinVDXgdSAJeVkrN1lov8XAMhQp6zh9MyfLJATXr2wlX315PnUs7BDt/hpH3g8V5Xyq8CfS7Eqwutqht0d/8lMdhh2M7YdlMSNlLx6PbQdkg5k1odTJQrJS2cQHE9yIrfjBZsd0J+eY2aFFxC8jielp2Ov/qW/4KB1eb3wl9K19WfJ+S4LAoRauY0MLX1adl/UpW5fFoAtNarwQmllp8miePWZku8RE8dH535v6xm/Cg2t2Yrit+O6KEqL2u58E/n8DeP01VIMAZD1Z/Pyl7IXkrhMWWXK7zIS8Tdv1m5iBr1st0pH7nApi+FiKc07AkbYKvpkOXc+l4ynQ4+wH4bCp8cg0dRz9VJplWVdKrUamtioRWU946n+S8dY8GVY8WGRxAv1aN+OdAKvEy8nOl5ATzQR3OAFuwmWKlzVAzcG+jtqavWGmVXdh/f8G0XLzqC1MlCbD8DXOfLb433LbBLDu4GnLSIDu1KHllHoMf74eIZnDus5Cyx5QCL3jVjBiy/hPoc3m1XlZNqjLz17yPOrIN65WfmxtALpTaPFVKq+pLpZxLntPgphxdvusoJ7WJ4bYzO9V1KEJUT1A4tB9pElhOGrx2Cix6qOrtSmszFHLT4chW83j3Uvj2P7D5m3KOGWFKfgBbF5oklZ0K4+dBaLHxFrucC5fMhR4XVT+e6kregvXv2Vh3/mwSprvY88n/6SHsiesrXKVniyiPJCRP7be+a1AlMICZv+6kW0Ikl55UQasuHyMfalFCn3+Z0s8/n0J+FnQ8y7XtipdMWjurHw+uhdiO8M3tpsqwqpJTfjYEhMCg601JrbTu48jZtwxH1glCKhs1pCpak394A7ZmvYru9RUX0x41ZJqZrfqnB0zydEVV1Y5r38e29Fn0ug/h5hUQWPMZomurvPPeEyW70tW3NanOdSVWT2lwCaxRaCBLtiTz4qJttR5+RQiv63qe+Xn/MjNGYqvB1d9HeBw07gyJa8zj5M3wrw9N9WRluo01ia4SAfl5qM+nQt8JMPK+6scGODYuwPb7c3BgJYx5zlQRFtDa9IvrPg5i2sNXt8Cy16H96dU/UPGElpcFPz8OEc1QJw7A4kdh1GNlk5677r154B6eKwmu9LLS1bflVedWuV8P3Y90RYOrQpQBfIXfyzwGW7+DHheWf//LFW2Gwr5lsPJN6DIGOo9yS2iWoDBU0+7w5yum1WR15WZgWfU2BIbDyrfg5/8r8Ryvn2qqMgHie8GFs2HglNoHnpMGzfvBsDvhlOlw0iTXtz24uugiXpPny1unJtt4Sk2O46XYGlwCC7KZlyxTqQi/tfJd87v7uJrv49Tb4Pql0PcqGPWE69sl9K36m/ZJk8CRD0uqsd8Cu5dCdgqMetxMC9OuWMlq5dtw+B8IKzaJZ69LzH067Sizq8zcTPLXfGDu2VUlvAlc9p55bd3HQWx7U9orp8N3lbyVWGpy3CrW0cf3kpPvP4M8NMAEZurUgwP8sxl9TcgN4nrmlGkw9TeX+12VK6oFxLaGcx6veJSPmopMgAHXwqp34Mi26m3b6Wz413xo1hPOehTanGKW7/rVdCHofzU0L9WPLWkzfHyNad5/aD18dBXkZhKQuhfr37PhjRGm20BF1n8CR7aXXOZwwMdXw9Lnqhe/J1U3Mbq6viMfNnwBb52L+vgqHIcqbsRSozg8qMElsNM6mXmUIkOkBCb8lMUCCb1qv5+ASLAG1X4/5TntDtPgY817rm9z4qD5Hd6k5PJNX5mm+9oBIx8ou11kAuScQP94P8waDrt/h6PbCIjrghrzHGSlwOyRpv9caRlH4Mub4Zf/lVxusZh7bFu+LX+72tAae/I2kzjqWP72n9DvX2aSdepeGHQ9IY07QU66meXAxzW4BJbQKJjhnWNp27iGLaT8gJS4RJ0Lj4OpS8pPOOVJT4IX+8KyWWWfaz+S/E6jyD/z4ZJN9wsER2I/aQoqIxl6Xgo3/13USjK+l4kjpi36+3vIL91VYNU74MiD0+8pu9/hd5kk9stT5r6ju/z5MtbPp+BY8oQp6ZXDnrSZ/IJ7fZ6Sm4H1z1fRoTGm1HvLGuh9mZnw9Jvb4d0Ly5ZMy5HnyCcrLxuO7zbVrl7U4BJY08ggrh/eiu4JcoH3B5KMvaj0/S1X7ndVpnFH04Iw+0TVF7aVc00Jq7zGJIGh2Ibfha1txYP4WLuMNh2zx71WNslFt4RrvsfR8Ux0QcftpE3ojyeiN39t5lGLaVt2p7YgOP1uyDlhLuju0vU8aHESlu0/wcJ7yr43237C8vWt2D09n1ZgGGrsy1jOfQY6n1Oyy8KIGWANMNWx+dnlb++ww69PYc1Jx5J11PRL/OhK82XESxpcArNgISyg/pa+hPCqqpLcgVXo9y5Bf3GDGe0j40jJ5+15kLgOvfV7OGlylc30KxUcXfFzgaFYT7+HgE5nm8f5OeiwOHSjtjDsvxVvF9sB+l1t5lCrSavK4nb9ZkpcjdrAOU+aTt/LXoPfni5aZ93H8MF4VFRLgpoPMMlt12/l7s6RehCdk179OPKyYMWbZt+RCaYRTGnRLeGi2ZC0EX57tmySzc+GD6+ExY9i2bmEoPCmptp46w/wykDY9qNXSmMNLoHVhJQChKihZr2w97sSlZ9tRvt4uhOOb24nv6Bl4K9Pmb5cthA41Y2lnKok9MEy+iksF88pe8+tmBx7LrmNO5rYgl24BhzfQ1ZuOjn2XDi4BjZ8bprob/4a3h5jui2AKZkOvgl6jTf37Bz5pnP6Z5NN377znjMlyQ2fm+3+eKnkcRwO+O4O+PAK2Pil669ba3O/75vbi/oBVqTDSFONuu0H8rd+b5ZlHIU9f8BX/zb3B0f9D7pfYIYkG3qradka2xH7hs/Jtee6HlcNSUsGIYT7lC6NWW3Y+k4wHZutgabF34bPcdicY5F2PQ+UBZr1Ltk83kdYlAXrjkWmRPH9XaZ/2ugnIb5PyQ7WYNb5ZBJBXUbjOGkyrHkfls9EKwtojepwBvS9smh9ZYGxr4B2kLfzF2wr3kR1GQMXzYHkTWadbmNNs/4fZsCASZB5BC54DQLDsJxyiynVfnSVWaff1RASXfkLWvU27FwCZz5i/ldVtSY87b/kp+5HxbQ3j/cshYX3oK1BqPHzoOuYkvuI6wTXfo99x2ICPNVAqBhJYEIIzyqe1Jp2x3LGAxSOV9+sJzjy8fDdnhoLsNhg+N2m+vDQejOG5Bc3wpbvzHiQYEo1q+eZarlmPbB0Ox+LxQpnPwY9LkKvegeHPQfb+S+Z+2rFWQMAsAdHos97kcDu40rei7JYYdwsyM2EFXNM4jiwEtqeZuaAa97fJKQl/4MdP8PYlyqu0l33sbnX2OEM08fOFRYLtuKdutudjmPMc+iwJli7jqlgGyuBXvoyIglMCFG3Sl9wy7sAV7WOJ4cxUhaY+osZsmqhs7Vi17Hmd24m+oPLUOmHoeclcN6LcGSLec5qg1aDsNgCzb2agIpnwAi2BZnO0+WN/WgLhEvfIe+XJwhoM9QkrwIWm7n31Hk0/Pp0xaXYjKNmCpz4PuaeX00biARHYqmDIaMqIglMCFE/uTPJWaww+CYcEfE4jmzD1vNis/zIVnRACI5B12Md9UTNE0NVAoIJ6Da24uebdodTbjF/H98D6z4097CUs5lDWCxc8ZFp6enq5Kd+QBKYEEK4yBLTFktM26JEldAHyyVzzd+ebvbuqvUfmzEk9y2Hk66FTQfMvao2Q6u+5+VKkpcSmBBC1DFXqirdsU1NY6mpU28HtBlRf9cSsIVC6yHldwL3VOxeSnL1PoFJ83chhFfV5J5edZ+vbB2lzH2xvGzTbP+iOUXJqyaJxYdKXKXV+wQmhBD1QnWT3sj7ajwnm7+QBCaEEBXx4dKHkJE4hBBC+KkGVwKTe2JCCFE/SAlMCCGEX5IEJoQQwi9JAhNCCOGXJIEJIYTwS5LAhBBC+CVJYEIIIfySJDAhhBB+SRKYEEIIvyQJTAghhF+SBCaEEMIvSQITQgjhlySBCSGE8EuSwIQQQvglSWBCCCH8kiQwIYQQfsmj84EppYYA1zkfTtdapyilLgRGYZLn9VrrfE/GIIQQon7ydAlsKiaBzQHGO5ddqrWeCvwKjPTw8YUQQtRTnp6R2aq1zlZKJQIjnMvynL8TgeblbaSUmopJfgDpSqktng2zUo2BI3V4/IpIXK7zxZjA9+LytXgKSFzV44tx1TSm77XWoyp60tMJLFMpFQTEA4ecy+zO38WXlaC1ngXM8nBsLlFKrdBaD6jrOEqTuFznizGB78Xla/EUkLiqxxfj8lRMnk5gs4CZQADwvVKqG/CxUuoNQFF0f0wIIYSoFo8mMK31SmBiqcUbgW88eVwhhBD1nzSjr5pPVGWWQ+JynS/GBL4Xl6/FU0Diqh5fjMsjMSmttSf2K4QQQniUlMCEEEL4JUlgQggh/JKnWyH6BKXUg0B7rfWVzsfLgXu01j+5sG1P4Hbnw/eBdIqNLgKcCwwBYoD/ABcAXYFcrfVt1YhxLjC59MgkSql5WusJXo6lE/CQc/+pWuv/uLhdGPAykAbsx3RgfxHT9+8VILuy+LXWKZXs+0HAprWeoZRqA0zUWj/oQkwW57GzAAdwD6Y+Phf4ClgB/M/5/O/AH87Xbgce0FrvcuW1O481l3L+hxWsW633Smv9g1JqBHC51npyFft+kBp83pVSI4HLgFDgSaA9xUbNAaYBrYE4zP8tC3gJ+MyFfdcoJue61frca60PKKXuBpK11rOr2n+x48zFzedgLWLxyjlYg8+Vx89BrfU7zvf5Ua312Mr23SASmFOUUioYaIn5J6KUug1oB7TAfAjv0VpPV0rNAq7T5gZhI+BWTLP/R4Ew57oDMaOLJGqtb1JKjcN8cE/VWl+mlLpfKdVZa12tTtgFJ4tSaq7WemKpp70Vy0jgQ631F0qp85VSIcANQBtMl4hbgJXAPCBEa/2Qc7tY4AWt9Rql1PvAxcBsTFJ4FXi7ivhnVhFXL6XUIOCw873qQFGymQlMAa5x/uzUWi8BIoD5WutfnDGdDvyitX5LKfUesAe4H9gLvINJ+DOc+7wBuNvF96yAUkq9irnop2MuJm8CS4BArfWMmrxXSqmdQF8g2MU4qvq8XwL8BGwBbnRetEMxAwj0Ac4C+js/P1dhPhM7tNbPKaX+jXmfejjjc5VXzkGlVI5zm+RqxFbInedgLWLxyjlYg8+Vx89BpdQC4FKcn5HKNKQqxO+A0cA44DPnsl8x3wCCnT9hSqnOwB7niYPW+lfMhegRzMXIqrXOxowkEq+1XqCUinPu92tKjjQS784X4MVY3gBaKaVexlzMAjEnZybmw9geWK+1fhKIVEpFOuPb6zxxrnMevzHmhM4BgquK34W47sUkl1Dn4+swJc1JmBLCUmAQMBjzv0Vrneo8cc4DVhXEVLBDrfU6rfVu4AHn6y54vjb/vw+AH4D+zsdrtNYPY0ovBcet1nultd6utX6mGjFU9XlPAI5rracWlDi01l9h3ttbMBe6Ep8f5+erA9ANWKm1fgtY5saY3HIOaq0XAN9WIy6XeTEWr5yDNfhcefwc1FqnaK3vo+jzV6GGlMAWA8OBKCDFuexeIAfYgflG8hnm28q7BRs5v/m8AszUWm+i1OgizhP6MeAWrXVBERkqGWmkOKXUBOefAZhvMQXfaKPLWdejsRQzBXhba30z5oTpA+zSWt+F+caXVCzOYIpGV8FZXXJca/0+cABo5owxt6r4XYgrC/Ot93Hn44LPr3b+/SlwOXBMa13w2lFKTQLaaK2fLoip6CllUUo9A/ystf6l2PMuv2el/octMKWYPcBx5/JM5297qe2q815Vlyuf9/RS8TTGVAner7VOotSoOUqpgZjkdnPx99fNMbnjHKwWD5+DNeWtc7C6vHEOuqwhVSHaMRf09RQVlzOBsUB3zIf1B8wI+XuLbXc3prrkTqXU75QcXeQ6zLerJOBlpdRs4Fel1CtAttZ6swtxhSulvgD2aq21UipbKfUS5X/793QsBX7DFOVPYN6zV4GznPsKAhYCA5RSzwOHtNYZAM669InA30qpoZhvai8Dk4FnXIi/SlrrZUqp9c6HMzF159mYb5PHlVKtgCcK1nfeS7gf+M1Z9XE1MEEpdSrmIjkRU6XR1LnsLcwJagPucPH9KvwfYj5T0cBVmP9huV8Sq/teaa1fczGWAq583kt7FnN/63Hn6yk9as5mYDkwRyn1uNZ6gwdiqvU56Ky2qg6PnYM1iKWAV87BGnyuPH4Oaq0fcTUW6QdWjFJqPjBLa724rmPxdarYjW0h3EXOQdfJOSgJTAghhJ9qSPfAhBBC1COSwIQQQvglSWBCCCH8kiQwIYQQfkkSmBBCCL8kCUwIIYRfkgQmhBDCL0kCE0II4ZckgQkhhPBLksCEEEL4JUlgQgghyqWUGqGUmq2UaqSU+kspZVNKRSql3lBKvayUmqSUau18PEcpdY4345MEJoQQogzn1DAFk11Op2gKnOaY0eM7Atsxo9sPwExMutOrMcpgvkII4f+cU6lcjpkG6DtgKGYKm7+ATZjJR9OAMzBTxazVWv/Xhf0WzlCNmZalGWa6oVTg/zDzix0EmgLji80O7XFSAhNCCD9XSWmpI0WTXa7WWs/TWk8EdgEP1vBwl2GS2AkgDLgBM0dZMhBbw33WSEOa0FIIIepceSUlrXW+cyblZK31bKXUY5ikEA1MqWoGbK31duAZZ2npQWdpCcys4FdhZgh/H7hEKTUMWKO1zix/b1X6AnjKue83MAnyZSADMxu11/h8FeKoUaP0999/X9dhCCEamMWLF/P+++8zevRovv/+exwOB6+//jozZswgIyODhIQE7r77bp566imSkpJITk5m7ty5le5z+/btfPnll6xevZoOHTrw119/8fXXX/Ptt9+ydOlSOnXqxKRJk/jmm28YM2YM06dPZ8aMGcTFxbkU84QJE5g3bx4TJ05k9uzZrF27lvz8fAYNGlT43LRp03jiiScICwtzw7vkcaqyJ32+CvHIkSN1HYIQwsctXryYyZMn89lnnzF16lQmT55Mfn4+b775Jv/5z3+47LLLSEtLY+LEiUycOJG2bduSnJxc4f62b9/O6tWryc7O5qOPPmLWrFmcdtppLFq0iB07dvDSSy8RGBjIhg0b+PLLL0lMTHQpIXTo0IHbb78dgAcffJBmzZoBcP755zN69GgAlFKMGTOG5cuXExgY6HLyKk+bNm147rnnuP7667n88ssBc031k+RVJalCFEJ4TUWlms8++4w//viD1NRUXn31VebMmcOuXbvIysri1VdfrXSfpZPN/Pnzeeedd1i0aBE//PADWmvsdjsRERHMnTuXpUuXMnjw4EoTQ0GimTBhAgEBAQDEx8dz4MABRo0axQ033EB2djYDBgzgiSeeYOjQoUycOJGcnByCgoJq/T59/fXXLF++nCeffLJa282bNw+gsCQYGxvL/PnzS6zzwQcf1Do+XyEJTAjhFZUlmi+//JImTZrQrl07AgMD+fHHH2nVqhW9evWqcr+VJZubb76ZoUOHctddd7Fnzx5at27NrFmzePPNN12O22q1ApCYmEizZs1IS0vjtddeY8aMGYSEhPDmm28ydOhQIiMjSU9Pr3UCS0lJ4YYbbmDYsGFceeWVPPPMMzRt2rRW+3Sn559/ntTUVACioqIAKn186623eiwWSWBCCK+oLNHs3buXefPmcd9997Fs2TICAwN56aWXuOaaa7j88suJjIx06Rilk81zzz3H0KFDiYuL4+jRoyilaNeuHTab65e+Sy65hClTpqC1ZubMmbzwwgtcd911REZGMnDgQObMmcO0adOIiYkhNta1RnilS0oAw4cPZ/jw4QDs27fP5fhqoybJKDU1lQceeACAhx4yLeareuwpksCEEF5XOtG0bt0apRQxMTFERkYSHR0NFF1EXVU62fz+++/ccMMN2Gw2+vXrx6effkrPnj1d3l9Bojn33HMLl912220l1pk5c2a1YvSWqpKTryWjmpAEJoTwutKJZv/+/dxwww0EBgbSvXt32rRpw80330xcXJzLpa/yks0jjzxSYp2LLrrIfS+iDpVOTrfeemuZZa4kJ3/nUgJTSint6+3thRBuNX/+fH744QciIiJo3LgxBw8eJCoqikcffRSbzcbixYt5++23efvtt6u13/ISzeTJk5k8eXLh43vvvdc9L8JPVVV6Ki85lbesvqs0gTk7070PvKCU2qi1nuadsIQQdW3BggW88847rF27llGjRpGcnMynn37KwoULOfnkk1m8eDF2u73qHTVwnrrPJKougYUBw4GHgYs9Ho0QwmdMmzaNKVOm0KpVK26++WYmT55MeHg4ffv25fHHH+eBBx7ghhtuqOswy+VKFRtUnkiKP67JNvXlPpMvqyqBpWBGGf4dM0yIEKKBSExMZPbs2fz888+sXLmS2bNnM3v2bOx2O9u2beOOO+5g+fLlrF27lt69e7vtuK40PnBXFZurj2uyjSQjz6sqgb0JDAY08KznwxFC+Iro6GgmTpyIw+HgrLPOYtKkSSilmDVrFtdeey1ghi6qTvJyV+MDqWITUHUCewgz/P5q4EXMKMRCCB9SvLFFv379+P333wtHuLDZbDz++OPExcWVaCThihEjRjBixIjCx1dffXWZdQoaZFTEleTUEBsfCPeoKoGdANK11luUUnlV7azYKMvfAqMwYy1eD1yHmfQsV2t9m1LqIcwoy0la6/+rRfxCNHjlNbYoGOEiJyeH48eP12o8vepwJWEJ4S5VJbCFwPVKqQWY6sQKlZqP5lKt9WVKqauAkcCpzsf3K6V6Ay211tcqpV5XSoVrrdPd8FqEaJCKN7YoGPy6YISLiRMnEhkZyfbt291+3PKqAyVhCW+qMIEppc7FTFr2hXNRTGU7Kj4fDVBQWkvETD9d/HEPIMn5+CjQGCiRwJRSU4GpAK1atXLtlQjRQBVvbNGyZcvCZQUjnddUTRpKCOFNlZXA9mPuf9VEQeeQeOAQ4Cj2+AtgmPNxHFBmvhSt9SxgFsCAAQOkA7UQlSje2OKll14qMcJFbUhDCeHrKktg/8G0PiyYUEwDv7q434+VUm84t70OaK6UegXI1lqvU0rtUkq9BOyU6kMhaqd0Y4uxY8eWeL74ILEVKV7aguqPQShEXagsgd0JhFR3h1rrCc4/vym2eI7zp2Cdx6u7XyGE+1TW2AKkhCX8Q2UJ7GygZallD3swFiGEl8j9K1EfVJjAtNZvKaXOAE7FNIcXQviBiqoDSzfIEMLfVdWM/mKgoLpPGlMI4Qcqqg6UEpeob6pKYMnAaCDH+dj1ebiFEF5RXnN3IRqCqhJYe2ARpvQlJTAhfJDczxINVVUJLBMzpUqWF2IRQrhASlxCGFUlsN+AWG8EIoRwjZS4hDCqSmB5mLEMlfPnHY9HJIQQQrigqubxozGlsBcw1YlCCCGET3ClBLYDk8iiPR6NED5s48aNvPDCC+Tk5NC3b18WLlxIkyZNuP322/n111/ZtGkTgYGBPPuszP0qhDdUVQK7F9gI7AHe8nw4Qviu2bNn07x5c4KCgtizZw/NmjUjLCyM9u3b89tvv/Hyyy8THR3Nli1b6jpUIRqEChOYUmq21vogMEZr/b7W+icvxiWEz9m+fTs333wzl1xyCbGxsbz++uuMHTuWuXPnEhAQAJh5uBITE+s4UiEahspKYIHO38MqWUeIBqNJkyaEhYURExNDeHg4VquVRo0akZ+fj8ViTiV3zMMlhHBNZffA4pVSI4AE52+01ou9E5YQvuf6669nypQpOBwOxo0bx5QpU1BK8fTTTxMWFsZNN91EcHAwXbp0qetQhWgQKktg8zCj0X/g/C0jcQi/sHbtWqZNm0a7du3Ytm0bHTt2ZPXq1Tz++OOMHj2axx9/nLi4OCZPnlyt/Q4YMIB33inqSXLRRRcV/j1p0iQmTZpUYv3SHY5vvfXWmr8oIUQZlY1G/7Y3AxENU/FkM27cOGbOnFnYsq9nz541SjbLli2jWbNmWK1WPv/8c2w2Gw899BCjR49mwYIFHD9+nLi4OLe/lsrm2JIOx0K4X4UJTCnVTGt9yJvBCN9VPNFcffXVNGvWjOnTp/PDDz/w3HPPsWfPHpKTk5k5cybh4eEu77d4slm4cCHNmjUjJCSE9u3b1zjZDB06lPHjx3P48GGefvppwsPDueGGGwA4//zziYyMZPv27dXaZ3kkYQlRtyqrQpyplDqKqUoE5B6YPyieaM4880z++OMPjh07xtNPP81HH33klkTTrVs3/ve//xUmlvbt2/Pvf/+b5557jk2bNnHSSSe5vN/iyeamm27im2++YcmSJcydO5cbb7yxRslmzZo1xMfHFzaw2LVrl0fuS0nCEqJuVZbAXgQmAy28FItwg+KJxm6388orr/D555/zxx9/uC3RNGvWjH379nHXXXcBplSzfft2Nm7cyPTp06sVb/Fks2LFihIt+2qqTZs2TJs2jYCAAG6++Wbmzp1b430VkPtZQvieyu6BLVJKZQHXY8ZBfNlrUTUghw8f5txzz+WKK65g69atREVF8eijjzJjxgwyMjJISEjg7rvvdnl/xRPN7NmzSU5O5vPPP2fmzJmEhITUOtEEBQVx+umn8+ijj7J8+XIWL15MeHg48+bN4+WXXy5sTu6q4slmxowZJVr21dSQIUMYMmRI4eP+/fuXeH748OEMHz680n1I9aAQvq+qoaSmAtdQlMCWeTyiBkRrzZNPPknr1q35888/+eijj/j0009ZuHAhO3bs4OOPP+aZZ55hw4YNdO/e3aV9Fi/RbN++nXvuuYcXX3yRkJAQli9f7pZEM2fOHNq2bcuECRM4/fTT6dSpEwMHDmTSpEncfffdLscKZZNNaa4kG3eQhCWE/6kqgdkw06lYgBDPh9OwvP7660yYMIFnnnmG8ePHM3nyZMLDw+nbty+jRo3ihhtuIDs7mwEDBri8z+KJ5u+//2bQoEHcfPPNTJo0ialTp7o10cybZ26Pbtu2zeX9eEN582VV9vjWW2+VhCWEH6oqgT0A/AdTAnvU8+H4roKqvhUrVrBp06bCFnhAjfsV/fjjj6xdu5bly5czduxYZs+ezezZs2nZsiVHjx7ltddeY8aMGbRs2dLlfVZWovF2oqlJIqnuNsUfFywrLxlV9VgI4X8qTWBa6x3Af6u7U6VUb+AlYCfwFXA2phR3PXAd0BXI1VrfVt1914XiVX05OTm88cYbhS3watOv6LPPPgNgwoQJ5ObmMmnSJJRSXHvttTz//PNcd911REZG0q5dO7e+ntKqSho1SSwVlWqqelyTbQoeF18mhKj/Kk1gSqnGWusjNdjvIOAQYAdu0lqPUEpdhZkc81St9WVKqfuVUp211j4/dHfxqr4nn3yS2267rUQLvNr2KyqoirviiisKl912m2u53R2lHFeShpRqhBC+pqoqxP8Bk6pYpzxLgQ+BpsD/OZclAs0xc4wVPI4HyiQwpdRUTAMSWrVqVYPDu1fxqr5PP/2UAwcOFLbAGzFiRI32WTyJQPWry9xdyhFCCH9TVQKLUEp9BqQDaK2vcnG/fTAJ6jhgdS6Lx5TKHMUe/1bexlrrWcAsgAEDBtT5GIzFq/q2bt1a+Hd1kldlpR6ofnWZJB4hRENXVQK7AxiMKSUdrMZ+d2PugeUBi5RSb2AaglwHNFdKvQJka603VzviOlRQ1Vf67/KaekuzbCGE8KyqEthDQBqwGngBuMyVnWqt/wD+qODpOc6fekUSlhBCeFdVCewEkK613qKUyqti3QajvGGFJGEJIYR3VZXAFgLXK6UWAG96IR6fJKUrIYTwPVUlsJ3On3zgH8+H4xskYQkhhO+rKoHdBdyG6c/1IHCrh+PxCZKwhBDC91U2oWV7QAONgRyvReRlMk2GEEL4p8pKYBOAXcB45+Njng+n9hYtWsT8+fPJzMxk4MCBLFy4sNIp6qW0JYQQ/qmy+cAeUkqdAZyKGcewzjsUuyIzM5NZs2axZs0ahgwZwr/+9a8SU9T/+OOPhIeHc+DAgcLRLYQQQvifqiaFuhjT+nC288fnnXfeeWRmZvLiiy+yZMkSXn/9dcaOHcvcuXM5//zzadWqFeeffz4PPPBAiaGchBBC+JeqElgyMBozCO8Zng+n9o4cOcK0adN4+OGHWbNmjVumqBdCCOF7qmqF2B5YhKk+9IsqxNtuu43k5GTuvvtuzj//fLdMUS+EEML3VJXAMoEwIMsLsbjFO++8U+LxpZdeWuJx27Ztqz3xpBBCCN9TVQL7DYj1RiCeUt58WUIIIfxfVQlseLG/04F3KljPZ0kzeSGEqJ8qTWBa62sAlFJRwD1eiUgIIYRwQaUJTClVMGNjANDD8+EIIYQQrqmqCrElpvVhPnCT58MRQgghXFPZWIgPFHuogQ7Awx6PSAghhHBBZSWwuc7focDjwDqPRyOEEEK4qLKxEPcopQYC9wKPaq3/9l5YQgghROUqq0J8BOiJaX2YpZRqp7Xe6bXIhBBCiEpUVoWYD6wGLgIU5j6Y3AMTQgjhEyqdTsWbgQghhBDVUdVo9EIIIYRPkgQmhBDCL9VJAlNKDVFKve38ia6LGIQQQvi3uiqBTQWuA+YA4+soBiGEEH5Mae39eSqVUu9qra9USnUErtBaP1jq+amYJAfQGdji5RCLawwcqcPjV0Ticp0vxgS+F5evxVNA4qoeX4yrpjEd0VqPqujJqsZC9JRMpVQQEA8cKv2k1noWMMvrUZVDKbVCaz2gruMoTeJynS/GBL4Xl6/FU0Diqh5fjMtTMdVVApsFzMSMcn9dHcUghBDCj9VJAtNarwQm1sWxhRBC1A/SjL5qPlGVWQ6Jy3W+GBP4Xly+Fk8Biat6fDEuj8RUJ404hBBCiNqSEpgQQgi/JAlMCCGEX6qrVohepZR6EGivtb7S+Xg5cI/W+icXtu0J3O58+D6QTlHLyenAucAQIAb4D3AB0BXI1VrfVo0Y5wKTtdb5pZbP01pP8HIsnYCHnPtP1Vr/x8XtwoCXgTRgP6aj+otAHvAKkF1Z/FrrlEr2/SBg01rPUEq1ASaW7j9YwXYW57GzAAdmeqBZQC7wFbAC+J/z+d+BP5yv3Q48oLXe5cprdx5rLuX8DytYt1rvldb6B6XUCOByrfXkKvb9IDX4vCulRgKXYSaxfRJoD4zCfNG9HpgGtAbiMP+3LOAl4DMX9l2jmJzrVutzr7U+oJS6G0jWWs+uav/FjjMXN5+DtYjFK+dgDT5XHj8HtdbvON/nR7XWYyvbd4NIYE5RSqlgoCXmn4hS6jagHdAC8yG8R2s9XSk1C7hOmxuEjYBbMVPKPAqEOdcdiBlFJFFrfZNSahzmg3uq1voypdT9SqnOWutqdcIuOFmUUnO11hNLPe2tWEYCH2qtv1BKna+UCgFuANpguj7cAqwE5gEhxWYuiAVe0FqvUUq9D1wMzMYkhVeBt6uIf2YVcfVSSg0CDjvfqw4UJZuZwBTgGufPTq31EiACmK+1/sUZ0+nAL1rrt5RS7wF7gPuBvcA7mIQ/w7nPG4C7XXzPCiil1KuYi3465mLyJrAECNRaz6jJe6WU2gn0BYJdjKOqz/slwE+YQQJudF60QzEDCPQBzgL6Oz8/V2E+Ezu01s8ppf6NeZ96OONzlVfOQaVUjnOb5GrEVsid52AtYvHKOViDz5XHz0Gl1ALgUpyfkco0pCrE74DRwDjgM+eyXzHfAIKdP2FKqc7AHueJg9b6V8yF6BHMxciqtc4GEoF4rfUCpVScc79fY77pUPC8O1+AF2N5A2illHoZczELxJycmZgPY3tgvdb6SSBSKRXpjG+v88S5znn8xpgTOgcIrip+F+K6F5NcQp2Pr8OUNCdhSghLgUHAYMz/Fq11qvPEOQ9YVRBTwQ611uu01ruBB5yvu+D52vz/PgB+APo7H6/RWj+MKb0UHLda75XWervW+plqxFDV5z0BOK61nlpQ4tBaf4V5b2/BXOhKfH6cn68OQDdgpdb6LWCZG2NyyzmotV4AfFuNuFzmxVi8cg7W4HPl8XNQa52itb6Pos9fhRpSAlsMDAeigBTnsnuBHGAH5hvJZ5hvK+8WbOT85vMKMFNrvYlSo4g4T+jHgFu01gVFZKhglJHSlFITnH8GYL7FFHyjjS5nXY/GUswU4G2t9c2YE6YPsEtrfRfmG19SsTiDnXEXxHg35sL4PnAAaOaMMbeq+F2IKwvzrfdx5+OCz692/v0pcDlwTGtd8NpRSk0C2mitny6IqegpZVFKPQP8rLX+pdjzLr9npf6HLTClmD3AcefyTOdve6ntqvNeVZcrn/f0UvE0xlQJ3q+1TioWb8HnayAmud1c/P11c0zuOAerxcPnYE156xysLm+cgy5rSFWIdswFfT1FxeVMYCzQHfNh/QG4Xmu9t9h2d2OqS+5USv1O2VFEvsV8mF5WSs0GflVKvQJka603uxBXuFLqC2Cv1lorpbKVUi9R/rd/T8dS4DdMUf4E5j17FTjLua8gYCEwQCn1PHBIa50B4KxLnwj8rZQaivmm9jIwGXjGhfirpLVeppRa73w4E1N3no35NnlcKdUKeKJgfee9hPuB35xVH1cDE5RSp2IukhMxVRpNncvewpygNuAOF9+vwv8h5jMVDVyF+R+W+yWxuu+V1vo1F2Mp4MrnvbRnMfe3Hne+no+VUm9gLpTXAZuB5cAcpdTjWusNHoip1uegs9qqOjx2DtYglgJeOQdr8Lny+DmotX7E1VikH1gxSqn5wCyt9eK6jsXXqWI3toVwFzkHXSfnoCQwIYQQfqoh3QMTQghRj0gCE0II4ZckgQlRR5RSUcp0PK3NPuKVUtXpiyVEvdGQWiEK4TXKjFrQB9NU3YHplFu6WfWtwHvA9gr20Q7TSTQH0/LsOq11ZqnVHsM0uS49esSrmObKvYDFWuuqOokL4XckgQnhOf/RWm9XSp0ETFFKbcKMgBEP3AkMBTKUUpuBs4FIzPBVu53bPwTcprVOVkoNAVorpe7VZpSIiZjm2v2AC5ydZ3tjmqc/DpwKfILpdPyyd16uEN4lVYhCeN56oDOwD9MJdRtwEmbsxS8wIxhkYEprg4ttF6C1TgbQWv9RTsfTTGC1cx9DtdbXY/ohdQPWajO80Fqt9W+eeVlC1C0pgQnheQMwSesmzGgU6zCdg4v3YbkH6ETRED0A2UqpxlrrI0qps5zrlx4lomAfxe+DyRdT0SBIAhPCc55WSmU4/74eMwzTSMzgrn8DOzGjN7yJGUg40LlOgf8D3lBKpQJW57pdlVJvYqob12Dun90ALFVKvYg5p2/HjMUnRL0mHZmFEEL4JalqEEII4ZckgQkhhPBLksCEEEL4JUlgQggh/JIkMCGEEH5JEpgQQgi/9P/gDln1Y7P0VwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 496.063x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 496.063x108 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#No minimum number of converged runs required since only one instance had fewer than 30 converged runs for 2 of the below (23)\n",
    "\n",
    "#Partition by phenotype\n",
    "df_holder = solar_rev_df[ ( solar_rev_df[\"trait\"].str.contains( \"covid_cswitch_weekly\" ) == True ) &\n",
    "                        ( solar_rev_df[\"directory\"] == \"cummulative_classswitch_noage\")\n",
    "                        ].copy()\n",
    "\n",
    "\n",
    "#Pull date cases/controls are included through from phenotype name\n",
    "df_holder[\"date\"] = df_holder[\"trait\"].apply( pull_date_window )\n",
    "\n",
    "#sort by the number of families \n",
    "df_holder.sort_values(by=\"num_families\",inplace=True)\n",
    "\n",
    "#get graph\n",
    "fig = create_graph(df_holder,\"date\",\"COVID Susceptibility Cumulative, No Age\", remove_scatter_markers = True,dates_x_axis=True)\n",
    "\n",
    "save_and_track_figure(fig[0], \"noage_covid_cumulative.pdf\")\n",
    "\n",
    "##################\n",
    "\n",
    "\n",
    "#Partition by phenotype\n",
    "df_holder = solar_rev_df[ ( solar_rev_df[\"trait\"].str.contains( \"covid_cswitch_weekly\" ) == True ) &\n",
    "                        ( solar_rev_df[\"directory\"] == \"cummulative_classswitch_nosex\")\n",
    "                        ].copy()\n",
    "\n",
    "\n",
    "\n",
    "#Pull date cases/controls are included through from phenotype name\n",
    "df_holder[\"date\"] = df_holder[\"trait\"].apply( pull_date_window )\n",
    "\n",
    "#sort by the number of families \n",
    "df_holder.sort_values(by=\"num_families\",inplace=True)\n",
    "\n",
    "#get graph\n",
    "fig = create_graph(df_holder,\"date\",\"COVID Susceptibility Cumulative, No Sex\", remove_scatter_markers = True,dates_x_axis=True)\n",
    "\n",
    "save_and_track_figure(fig[0], \"nosex_covid_cumulative.pdf\")\n",
    "\n",
    "##################\n",
    "\n",
    "#Partition by phenotype\n",
    "df_holder = solar_rev_df[ ( solar_rev_df[\"trait\"].str.contains( \"covid_cswitch_weekly\" ) == True ) &\n",
    "                        ( solar_rev_df[\"directory\"] == \"cummulative_classswitch_nosex_noage\")\n",
    "                        ].copy()\n",
    "\n",
    "\n",
    "#Pull date cases/controls are included through from phenotype name\n",
    "df_holder[\"date\"] = df_holder[\"trait\"].apply( pull_date_window )\n",
    "\n",
    "#sort by the number of families \n",
    "df_holder.sort_values(by=\"num_families\",inplace=True)\n",
    "\n",
    "# #get graph\n",
    "fig = create_graph(df_holder,\"date\",\"COVID Susceptibility Cumulative, No Sex or Age\", remove_scatter_markers = True,dates_x_axis=True)\n",
    "\n",
    "save_and_track_figure(fig[0], \"nosex_noage_covid_cumulative.pdf\")\n",
    "\n",
    "##################\n",
    "\n",
    "#Used in manuscript\n",
    "fig, axs= plt.subplots(nrows=1,ncols=1)\n",
    "fig.set_size_inches(175/25.4, 1.5)\n",
    "\n",
    "# Format the x-axis labels to be month then year\n",
    "\n",
    "axs.xaxis.set_major_formatter(mdates.DateFormatter(\"%b %Y\"))\n",
    "\n",
    "\n",
    "x = nyc_case_df[ (nyc_case_df[\"date_cln\"] >= weeks[0]) &\n",
    "                        (nyc_case_df[\"date_cln\"] <= weeks[-1] + timedelta(days=7))\n",
    "                        ][\"date_cln\"]\n",
    "\n",
    "y = nyc_case_df[ (nyc_case_df[\"date_cln\"] >= weeks[0]) &\n",
    "                        (nyc_case_df[\"date_cln\"] <= weeks[-1] + timedelta(days=7))\n",
    "                        ][\"ALL_CASE_COUNT_7DAY_AVG\"]\n",
    "\n",
    "adm_plt = axs.bar(x,y, width=0.1, color=\"white\",edgecolor='grey')\n",
    "\n",
    "\n",
    "axs.set_xlabel(\"Week\")\n",
    "axs.set_ylabel(\"NYC Cases - 7 Day Average\")\n",
    "\n",
    "sns.despine()\n",
    "\n",
    "\n",
    "#Phase 4 repopen July 19th, 2020\n",
    "plt.axvline(x = datetime(2020, 7, 19).date(), color = 'black', label = 'NYC Phase 4 Reopen')\n",
    "plt.text(datetime(2020, 7, 19).date(), max(y)+ 500, 'NYC Phase 4 Reopen', ha='center', va='bottom')\n",
    "\n",
    "#Elementary kids return to school September 29, 2020\n",
    "plt.axvline(x = datetime(2020, 9, 29).date(), color = 'black', label = 'Elementary Return to School')\n",
    "plt.text(datetime(2020, 9, 29).date(), max(y)+ 1500, 'Elementary Retrun to School', ha='center', va='bottom')\n",
    "\n",
    "\n",
    "# plt.axvline(x=datetime(2020, 12, 14).date(), color='black')\n",
    "# plt.text(datetime(2020, 12, 14).date(), max(y)+ 500, '1st vaccination in NYC', ha='center', va='bottom')\n",
    "\n",
    "plt.axvline(x=datetime(2021, 2, 14).date(), color='black')\n",
    "plt.text(datetime(2021, 2, 14).date(), max(y)+ 500, 'Vaccines - Underlying Conditions', ha='center', va='bottom')\n",
    "\n",
    "plt.axvline(x=datetime(2021, 4, 6).date(), color='black')\n",
    "plt.text(datetime(2021, 4, 6).date(), max(y)+ 1500, 'Vaccines - 16+', ha='center', va='bottom')\n",
    "\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed912065",
   "metadata": {},
   "source": [
    "## Get reporting estimates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8fb87f75",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:56.453919Z",
     "start_time": "2023-11-28T22:57:56.388219Z"
    }
   },
   "outputs": [],
   "source": [
    "trait_maxposa_df =solar_df[solar_df[\"model\"] == \"ACE_h2o\"].groupby([\"trait\"]).\\\n",
    "agg({ \"posa\":\"max\"}).reset_index()\n",
    "\n",
    "top_posa_df = pd.merge(trait_maxposa_df, solar_df, how='left', left_on=['trait','posa'], right_on = ['trait','posa'])\n",
    "\n",
    "#Limit to those that aren't cumulative or weekly\n",
    "top_posa_df = top_posa_df[ ~top_posa_df[\"trait\"].str.contains(\"window|weekly\",regex=True )]\n",
    "reporting_cols = [\"trait\",\"model\",\"estimate\",\"estimate_lower\",\"estimate_upper\",\"posa\",\"num_converged\",\"num_significant\",\"num_families\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5c5f5207",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:56.592537Z",
     "start_time": "2023-11-28T22:57:56.457449Z"
    }
   },
   "outputs": [],
   "source": [
    "models = [\"ACE_h2o\", \"ACE_Shared_Env\"]\n",
    "best_est_list = []\n",
    "lowqual_ests = []\n",
    "missing_ests = []\n",
    "\n",
    "for pheno in phenos:\n",
    "    for model in models:\n",
    "        # First get above 80% posas\n",
    "        holder_df = solar_df[(solar_df[\"trait\"] == pheno) &\n",
    "                             (solar_df[\"model\"] == model) &\n",
    "                             (solar_df[\"posa\"] > 0.8)].sort_values(by=\"num_families\")\n",
    "\n",
    "        # If we have no estimate with a posa over 0.8, use highest estimate we have\n",
    "        if len(holder_df) == 0:\n",
    "            holder_df = top_posa_df[(top_posa_df[\"trait\"] == pheno) &\n",
    "                                    (top_posa_df[\"model\"] == model)]\n",
    "\n",
    "        else:\n",
    "            # Else pick the estimate with posa above 0.8 with fewest number of families to limit ascertainment bias\n",
    "            holder_df = holder_df[holder_df[\"num_families\"] == holder_df[\"num_families\"].min()]\n",
    "\n",
    "        if len(holder_df) > 0:\n",
    "            best_est_list.append(holder_df)\n",
    "\n",
    "        else:\n",
    "            missing_ests.append((pheno, model))\n",
    "\n",
    "best_est_dfs = pd.concat(best_est_list)\n",
    "best_est_dfs[\"total_samp\"] = best_est_dfs[\"trait\"].map(pheno2sampsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "3d6094a2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:56.729294Z",
     "start_time": "2023-11-28T22:57:56.595406Z"
    }
   },
   "outputs": [],
   "source": [
    "#Lowest and highest cumulative estimates\n",
    "cswitch_high_ace = solar_df[ (solar_df[\"trait\"].str.contains(\"cswitch\") & (solar_df[\"model\"] == \"ACE_h2o\")) ][\"estimate\"].max()\n",
    "cswitch_high_ace_trait = solar_df[ solar_df[\"estimate\"] == cswitch_high_ace][\"trait\"]\n",
    "\n",
    "cswitch_low_ace = solar_df[ (solar_df[\"trait\"].str.contains(\"cswitch\") & (solar_df[\"model\"] == \"ACE_h2o\")) ][\"estimate\"].min()\n",
    "cswitch_low_ace_trait = solar_df[ solar_df[\"estimate\"] == cswitch_low_ace][\"trait\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5cbc7c68",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:56.871666Z",
     "start_time": "2023-11-28T22:57:56.731984Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trait</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>num_families</th>\n",
       "      <th>model</th>\n",
       "      <th>estimate</th>\n",
       "      <th>estimate_lower</th>\n",
       "      <th>estimate_upper</th>\n",
       "      <th>solarerr</th>\n",
       "      <th>solarpval</th>\n",
       "      <th>num_attempts</th>\n",
       "      <th>num_converged</th>\n",
       "      <th>num_significant</th>\n",
       "      <th>posa</th>\n",
       "      <th>file</th>\n",
       "      <th>directory</th>\n",
       "      <th>model_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>633</th>\n",
       "      <td>covid_cswitch_weekly_10_06_2020</td>\n",
       "      <td>ALL</td>\n",
       "      <td>553</td>\n",
       "      <td>ACE_h2o</td>\n",
       "      <td>0.328873</td>\n",
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       "      <td>0.994898</td>\n",
       "      <td>ZIHAR_solar_strap_results.csv</td>\n",
       "      <td>cummulative_classswitch</td>\n",
       "      <td>Heritability</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>634</th>\n",
       "      <td>covid_cswitch_weekly_10_06_2020</td>\n",
       "      <td>ALL</td>\n",
       "      <td>553</td>\n",
       "      <td>ACE_Shared_Env</td>\n",
       "      <td>0.671127</td>\n",
       "      <td>0.541489</td>\n",
       "      <td>0.802477</td>\n",
       "      <td>0.323686</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>195</td>\n",
       "      <td>0.994898</td>\n",
       "      <td>ZIHAR_solar_strap_results.csv</td>\n",
       "      <td>cummulative_classswitch</td>\n",
       "      <td>Shared Environment</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trait ethnicity num_families           model  \\\n",
       "633  covid_cswitch_weekly_10_06_2020       ALL          553         ACE_h2o   \n",
       "634  covid_cswitch_weekly_10_06_2020       ALL          553  ACE_Shared_Env   \n",
       "\n",
       "     estimate estimate_lower estimate_upper  solarerr solarpval num_attempts  \\\n",
       "633  0.328873       0.197523       0.458511  0.323686  0.000332          200   \n",
       "634  0.671127       0.541489       0.802477  0.323686       0.0          200   \n",
       "\n",
       "    num_converged num_significant      posa                           file  \\\n",
       "633           196             195  0.994898  ZIHAR_solar_strap_results.csv   \n",
       "634           196             195  0.994898  ZIHAR_solar_strap_results.csv   \n",
       "\n",
       "                   directory         model_clean  \n",
       "633  cummulative_classswitch        Heritability  \n",
       "634  cummulative_classswitch  Shared Environment  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solar_df[ solar_df[\"trait\"] == cswitch_low_ace_trait.values[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "61d71203",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-28T22:57:57.016122Z",
     "start_time": "2023-11-28T22:57:56.878396Z"
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   },
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trait</th>\n",
       "      <th>ethnicity</th>\n",
       "      <th>num_families</th>\n",
       "      <th>model</th>\n",
       "      <th>estimate</th>\n",
       "      <th>estimate_lower</th>\n",
       "      <th>estimate_upper</th>\n",
       "      <th>solarerr</th>\n",
       "      <th>solarpval</th>\n",
       "      <th>num_attempts</th>\n",
       "      <th>num_converged</th>\n",
       "      <th>num_significant</th>\n",
       "      <th>posa</th>\n",
       "      <th>file</th>\n",
       "      <th>directory</th>\n",
       "      <th>model_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>579</th>\n",
       "      <td>covid_cswitch_weekly_08_17_2021</td>\n",
       "      <td>ALL</td>\n",
       "      <td>1130</td>\n",
       "      <td>ACE_h2o</td>\n",
       "      <td>0.697004</td>\n",
       "      <td>0.634759</td>\n",
       "      <td>0.737944</td>\n",
       "      <td>0.050161</td>\n",
       "      <td>0.0</td>\n",
       "      <td>200</td>\n",
       "      <td>195</td>\n",
       "      <td>195</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JHNTP_solar_strap_results.csv</td>\n",
       "      <td>cummulative_classswitch</td>\n",
       "      <td>Heritability</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>580</th>\n",
       "      <td>covid_cswitch_weekly_08_17_2021</td>\n",
       "      <td>ALL</td>\n",
       "      <td>1130</td>\n",
       "      <td>ACE_Shared_Env</td>\n",
       "      <td>0.302996</td>\n",
       "      <td>0.245423</td>\n",
       "      <td>0.352153</td>\n",
       "      <td>0.050161</td>\n",
       "      <td>0.0</td>\n",
       "      <td>200</td>\n",
       "      <td>195</td>\n",
       "      <td>195</td>\n",
       "      <td>1.0</td>\n",
       "      <td>JHNTP_solar_strap_results.csv</td>\n",
       "      <td>cummulative_classswitch</td>\n",
       "      <td>Shared Environment</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               trait ethnicity num_families           model  \\\n",
       "579  covid_cswitch_weekly_08_17_2021       ALL         1130         ACE_h2o   \n",
       "580  covid_cswitch_weekly_08_17_2021       ALL         1130  ACE_Shared_Env   \n",
       "\n",
       "     estimate estimate_lower estimate_upper  solarerr solarpval num_attempts  \\\n",
       "579  0.697004       0.634759       0.737944  0.050161       0.0          200   \n",
       "580  0.302996       0.245423       0.352153  0.050161       0.0          200   \n",
       "\n",
       "    num_converged num_significant posa                           file  \\\n",
       "579           195             195  1.0  JHNTP_solar_strap_results.csv   \n",
       "580           195             195  1.0  JHNTP_solar_strap_results.csv   \n",
       "\n",
       "                   directory         model_clean  \n",
       "579  cummulative_classswitch        Heritability  \n",
       "580  cummulative_classswitch  Shared Environment  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solar_df[ solar_df[\"trait\"] == cswitch_high_ace_trait.values[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44d74a26",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c6969ffb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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