4_HBN_all.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "262294e1-74b1-4d08-815f-6ac553be2837",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.set_option('max_colwidth', 100)\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from itertools import cycle\n",
    "from sklearn import svm, datasets\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import label_binarize\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import itertools\n",
    "import scipy.stats as st\n",
    "import csv\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5e1b0c2e-db8a-4767-9bc5-b033021eb596",
   "metadata": {},
   "outputs": [],
   "source": [
    "path_to_consensusfile = '../../data/HBN/9994_ConsensusDx_20210310.csv'\n",
    "path_to_demosfile = '../../data/HBN/9994_Basic_Demos_20210310.csv'\n",
    "path_to_cbclfile = '../../data/HBN/9994_CBCL_20210310.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8dff83e3-3deb-44ed-955f-ecfdd62c2b98",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_all_data(path_to_consensusfile, path_to_demosfile, path_to_cbclfile, hypothesis, measure, sex, do_print=False):\n",
    "    # this is very messy. I don't have time to clean it up and make it pretty, but it works.\n",
    "    # I'm not sure if it would work for other waves of HBN data.\n",
    "    consensusfile = pd.read_csv(path_to_consensusfile, sep=',', header=0, low_memory=False)\n",
    "    demosfile = pd.read_csv(path_to_demosfile, sep=',', header=0, low_memory=False)\n",
    "    cbclfile = pd.read_csv(path_to_cbclfile, sep=',', header=0, low_memory=False)\n",
    "    # prepping consensusfile and demosfile\n",
    "    names_columns = consensusfile.loc[0].to_dict()\n",
    "    consensusfile = consensusfile.drop(0)\n",
    "    if do_print:\n",
    "        print('ALL DATA:')\n",
    "        print(consensusfile.shape)\n",
    "    names_columns_demos = demosfile.loc[0].to_dict()\n",
    "    demosfile = demosfile.drop(0)\n",
    "    # We know that if we merge consensusfile and demosfile now, we will get some meaningless stuff\n",
    "    # Demosfile - look at duplicated rows\n",
    "    dupl = demosfile.duplicated(subset=['EID'])\n",
    "    dupl_frame = dupl.to_frame()\n",
    "    dupl_frame.columns = ['TrueOrFalse']\n",
    "    dupl2 = dupl_frame.groupby(['TrueOrFalse'])['TrueOrFalse'].count()\n",
    "    result_df= dupl_frame.loc[dupl_frame['TrueOrFalse']==True]\n",
    "    # identifying EID of repeated items\n",
    "    # take rows which had \"true\" in the result_df file\n",
    "    # look them up in the demosfile\n",
    "    # result:\n",
    "    # print(demosfile.loc[[1829]]['EID']) # EID = NDAREN522YEV\n",
    "    # print(demosfile.loc[[1836]]['EID']) # EID = NDARRG499ZWN\n",
    "    # print(demosfile.loc[[1841]]['EID']) # EID = NDARDD394RRX\n",
    "    # print(demosfile.loc[[2971]]['EID']) # EID = NDARPF042DD2\n",
    "    # print(demosfile.loc[[3162]]['EID']) # EID = NDARPL406KX4\n",
    "    '''if do_print:\n",
    "        for x in ['NDAREN522YEV', 'NDARRG499ZWN', 'NDARDD394RRX', 'NDARPF042DD2','NDARPL406KX4']:\n",
    "            print(demosfile.loc[demosfile['EID']==x])'''\n",
    "    # let's just drop repeated rows in the second file\n",
    "    # EID = NDAREN522YEV: Rows are identical except release number. Drop the first one (release 3)\n",
    "    # --> drop row id 1094\n",
    "    # EID = NDARRG499ZWN: Rows are identical except for partiipant status (release 6: lost to follow up). Keeping row 2\n",
    "    # --> drop row id 1836\n",
    "    # EID = NDARDD394RRX Rows are identical except release number. drop the first one (release 3)\n",
    "    # --> drop row id 1133\n",
    "    # EID = NDARPF042DD2 Participant status differens. Keeping the second row where the status is complete\n",
    "    # --> drop row 2520\n",
    "    # EID = NDARPL406KX4 Participant status differs. Keeping row 2 where the status is complete\n",
    "    # --> drop row 990\n",
    "    demosfile = demosfile.drop([990, 1094, 1133, 1836, 2520])\n",
    "    if do_print:\n",
    "        print(demosfile.shape)\n",
    "    ### Now we can merge consensusfile and demosfile (but we still have some cleaning to do because consensusfile had repeated rows)\n",
    "    consensus_and_demos_2 = pd.merge(consensusfile, demosfile, on='EID', indicator=True)\n",
    "    if do_print:\n",
    "        print(consensusfile.nunique())\n",
    "        print('\\n')\n",
    "        print(demosfile.nunique())\n",
    "        print('\\n')\n",
    "        print(consensus_and_demos_2.nunique())\n",
    "        # consensusfile: Anonymized ID = 3617, EID = 3615\n",
    "        # demosfile: Anonymized ID = 3628, EID = 3628\n",
    "        # consensus_and_demos_2: Anonymized ID = 3617, EID = 3615\n",
    "        # checking where repeated rows ends\n",
    "        print(consensus_and_demos_2.loc[[5136]])\n",
    "        print('\\n')\n",
    "        print(consensus_and_demos_2.loc[[5137]])\n",
    "        print('\\n')\n",
    "        print(consensus_and_demos_2.loc[[5138]])\n",
    "    ### Splitting the file up until the last repeated row. After splitting, only keep the even rows in the first part. \n",
    "    ### Keep all rows in the 2nd part (there are no reppetitions there)\n",
    "    consensus_and_demos_2 = consensus_and_demos_2.reset_index(drop=True)\n",
    "    consensus_and_demos_2_part1 = consensus_and_demos_2.loc[:5136]\n",
    "    consensus_and_demos_2_part1_evens = consensus_and_demos_2_part1.iloc[::2, :]\n",
    "    consensus_and_demos_2_part2 = consensus_and_demos_2.loc[5137:]\n",
    "    consensus_and_demos_3 = pd.concat([consensus_and_demos_2_part1_evens, consensus_and_demos_2_part2], ignore_index=True, sort=False)\n",
    "    if do_print:\n",
    "        consensus_and_demos_3.shape\n",
    "    consensusfile = consensusfile.reset_index(drop=True)\n",
    "    consensusfile_part1 = consensusfile.loc[:5136]\n",
    "    consensusfile_part1_evens = consensusfile_part1.iloc[::2, :]\n",
    "    consensusfile_part2 = consensusfile.loc[5137:]\n",
    "    consensusfile_3 = pd.concat([consensusfile_part1_evens, consensusfile_part2], ignore_index=True, sort=False)\n",
    "    # First, let's add the indicator column\n",
    "    consensusfile_3['currently_depressed_DX_01'] = ((consensusfile_3.DX_01 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_01 == \"Dysthymia\") | (consensusfile_3.DX_01 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_01 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_01 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_01_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_02'] = ((consensusfile_3.DX_02 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_02 == \"Dysthymia\") | (consensusfile_3.DX_02 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_02 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_02 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_02_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_03'] = ((consensusfile_3.DX_03 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_03 == \"Dysthymia\") | (consensusfile_3.DX_03 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_03 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_03 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_03_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_04'] = ((consensusfile_3.DX_04 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_04 == \"Dysthymia\") | (consensusfile_3.DX_04 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_04 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_04 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_04_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_05'] = ((consensusfile_3.DX_05 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_05 == \"Dysthymia\") | (consensusfile_3.DX_05 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_05 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_05 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_05_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_06'] = ((consensusfile_3.DX_06 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_06 == \"Dysthymia\") | (consensusfile_3.DX_06 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_06 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_06 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_06_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_07'] = ((consensusfile_3.DX_07 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_07 == \"Dysthymia\") | (consensusfile_3.DX_07 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_07 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_07 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_07_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_08'] = ((consensusfile_3.DX_08 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_08 == \"Dysthymia\") | (consensusfile_3.DX_08 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_08 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_08 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_08_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_09'] = ((consensusfile_3.DX_09 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_09 == \"Dysthymia\") | (consensusfile_3.DX_09 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_09 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_09 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_09_Rem != 1)\n",
    "    consensusfile_3['currently_depressed_DX_10'] = ((consensusfile_3.DX_10 == \"Major Depressive Disorder\") | ((consensusfile_3.DX_10 == \"Dysthymia\") | (consensusfile_3.DX_10 == \"Persistent Depressive Disorder (Dysthymia)\"))  | (consensusfile_3.DX_10 == \"Other Specified Depressive Disorder\") | (consensusfile_3.DX_10 == \"Unspecified Depressive Disorder\")) & (consensusfile_3.DX_10_Rem != 1)\n",
    "    consensusfile_3['currently_depressed'] = (consensusfile_3.currently_depressed_DX_01 == True) | (consensusfile_3.currently_depressed_DX_02 == True) | (consensusfile_3.currently_depressed_DX_03 == True) | (consensusfile_3.currently_depressed_DX_04 == True) | (consensusfile_3.currently_depressed_DX_05 == True) | (consensusfile_3.currently_depressed_DX_06 == True) | (consensusfile_3.currently_depressed_DX_07 == True) | (consensusfile_3.currently_depressed_DX_08 == True) | (consensusfile_3.currently_depressed_DX_09 == True) | (consensusfile_3.currently_depressed_DX_10 == True)\n",
    "    #if do_print:\n",
    "        #consensusfile_3['currently_depressed'].value_counts()\n",
    "    # now let's merge\n",
    "    # Demosfile is already clean from our previous efforts\n",
    "    consensus_and_demos_4 = pd.merge(consensusfile_3, demosfile, on='EID', indicator=True)\n",
    "    # DEPRESSED_9-13 - consensus_and_demos_4     \n",
    "    consensus_and_demos_4[\"depressed_9-13\"] = (consensus_and_demos_4.currently_depressed == True) & ((consensus_and_demos_4.Age.astype(float) >= 8.0) & (consensus_and_demos_4.Age.astype(float) <= 13.0))\n",
    "    consensus_and_demos_current = consensus_and_demos_4\n",
    "    consensus_and_demos_current = consensus_and_demos_current.replace(np.nan, 'Healthy', regex=True)\n",
    "    consensus_and_demos_current['healthy'] = ((consensus_and_demos_current.DX_01 == \"No Diagnosis Given\") | (consensus_and_demos_current.DX_01 == \"Healthy\")) & \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_06 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_07 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_08 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_09 == \"Healthy\") & \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Healthy\")\n",
    "    consensus_and_demos_current[\"healthy_9-13\"] = (consensus_and_demos_current.healthy == True) & ((consensus_and_demos_current.Age.astype(float) >= 8.0) & (consensus_and_demos_current.Age.astype(float) <= 13.0))\n",
    "    if do_print:\n",
    "        print('overall healthy')\n",
    "        print(consensus_and_demos_current[\"healthy_9-13\"].value_counts())\n",
    "    consensus_and_demos_current['anxiety_DX_01'] = ((consensus_and_demos_current.DX_01 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Other Specified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Unspecified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Panic Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Agoraphobia\") & \\\n",
    "                                                (consensus_and_demos_current.DX_01_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_01'] = ((consensus_and_demos_current.DX_01 == \"ADHD-Combined Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"ADHD-Inattentive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"ADHD-Hyperactive/Impulsive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_01 == \"Unspecified Attention-Deficit/Hyperactivity Disorder\")  & \\\n",
    "                                                (consensus_and_demos_current.DX_01_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_02'] = ((consensus_and_demos_current.DX_02 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Other Specified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Unspecified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Panic Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Agoraphobia\") & \\\n",
    "                                                (consensus_and_demos_current.DX_02_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_02'] = ((consensus_and_demos_current.DX_02 == \"ADHD-Combined Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"ADHD-Inattentive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"ADHD-Hyperactive/Impulsive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_02 == \"Unspecified Attention-Deficit/Hyperactivity Disorder\")  & \\\n",
    "                                                (consensus_and_demos_current.DX_02_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_03'] = ((consensus_and_demos_current.DX_03 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Other Specified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Agoraphobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Panic Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_03 == \"Unspecified Anxiety Disorder\") & \\\n",
    "                                                (consensus_and_demos_current.DX_03_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_03'] = ((consensus_and_demos_current.DX_03 == \"ADHD-Inattentive Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_03 == \"ADHD-Combined Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_03 == \"ADHD-Hyperactive/Impulsive Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_03 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") & \\\n",
    "                                             (consensus_and_demos_current.DX_03_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_04'] = ((consensus_and_demos_current.DX_04 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Other Specified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Agoraphobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Panic Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_04 == \"Unspecified Anxiety Disorder\") & \\\n",
    "                                                (consensus_and_demos_current.DX_04_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_04'] = ((consensus_and_demos_current.DX_04 == \"ADHD-Inattentive Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_04 == \"ADHD-Combined Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_04 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") & \\\n",
    "                                             (consensus_and_demos_current.DX_04_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_05'] = ((consensus_and_demos_current.DX_05 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Other Specified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Agoraphobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_05 == \"Unspecified Anxiety Disorder\") & \\\n",
    "                                                (consensus_and_demos_current.DX_05_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_05'] = ((consensus_and_demos_current.DX_05 == \"ADHD-Inattentive Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_05 == \"ADHD-Combined Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_05 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") & \\\n",
    "                                             (consensus_and_demos_current.DX_05_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_06'] = ((consensus_and_demos_current.DX_06 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_06 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_06 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_06 == \"Panic Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_06 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_06 == \"Unspecified Anxiety Disorder\") & \\\n",
    "                                                (consensus_and_demos_current.DX_06_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_06'] = ((consensus_and_demos_current.DX_06 == \"ADHD-Inattentive Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_06 == \"ADHD-Combined Type\") & \\\n",
    "                                            (consensus_and_demos_current.DX_06_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_07'] = ((consensus_and_demos_current.DX_07 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_07 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_07 == \"Agoraphobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_07 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_07 == \"Social Anxiety (Social Phobia)\") & \\\n",
    "                                                (consensus_and_demos_current.DX_07_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_07'] = ((consensus_and_demos_current.DX_07 == \"ADHD-Inattentive Type\") | \\\n",
    "                                             (consensus_and_demos_current.DX_07 == \"ADHD-Combined Type\") & \\\n",
    "                                            (consensus_and_demos_current.DX_07_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_08'] = ((consensus_and_demos_current.DX_08 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_08 == \"Separation Anxiety\") & \\\n",
    "                                                (consensus_and_demos_current.DX_08_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_08'] = ((consensus_and_demos_current.DX_08 == \"ADHD-Combined Type\") & \\\n",
    "                                                (consensus_and_demos_current.DX_08_Rem != 1))\n",
    "    consensus_and_demos_current['anxiety_DX_09'] = ((consensus_and_demos_current.DX_09 == \"Specific Phobia\") & \\\n",
    "                                                (consensus_and_demos_current.DX_09_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_09'] = ((consensus_and_demos_current.DX_09 == \"ADHD-Combined Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_09 == \"ADHD-Inattentive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_09 == \"ADHD-Hyperactive/Impulsive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_09 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_09 == \"Unspecified Attention-Deficit/Hyperactivity Disorder\")  & \\\n",
    "                                                (consensus_and_demos_current.DX_09_Rem != 1))\n",
    "    # this is just for consistency and so we don't get an error when we call for the DX_10 column\n",
    "    consensus_and_demos_current['anxiety_DX_10'] = ((consensus_and_demos_current.DX_10 == \"Generalized Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Social Anxiety (Social Phobia)\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Specific Phobia\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Other Specified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Separation Anxiety\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Unspecified Anxiety Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Panic Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Agoraphobia\") & \\\n",
    "                                                (consensus_and_demos_current.DX_10_Rem != 1))\n",
    "    consensus_and_demos_current['ADHD_DX_10'] = ((consensus_and_demos_current.DX_10 == \"ADHD-Combined Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"ADHD-Inattentive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"ADHD-Hyperactive/Impulsive Type\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Other Specified Attention-Deficit/Hyperactivity Disorder\") | \\\n",
    "                                                (consensus_and_demos_current.DX_10 == \"Unspecified Attention-Deficit/Hyperactivity Disorder\")  & \\\n",
    "                                                (consensus_and_demos_current.DX_10_Rem != 1))\n",
    "    # Now adding it all together\n",
    "    consensus_and_demos_current['anxiety'] = (consensus_and_demos_current.anxiety_DX_01 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_02 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_03 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_04 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_05 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_06 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_07 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_08 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_09 == True) | \\\n",
    "                                                        (consensus_and_demos_current.anxiety_DX_10 == True)\n",
    "    consensus_and_demos_current['ADHD'] = (consensus_and_demos_current.ADHD_DX_01 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_02 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_03 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_04 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_05 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_06 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_07 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_08 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_09 == True) | \\\n",
    "                                                            (consensus_and_demos_current.ADHD_DX_10 == True)\n",
    "    if do_print:\n",
    "        print(consensus_and_demos_current[\"anxiety\"].value_counts())\n",
    "        print(consensus_and_demos_current[\"ADHD\"].value_counts())\n",
    "    consensus_and_demos_current['anxiety_or_ADHD'] = (consensus_and_demos_current.anxiety == True) | (consensus_and_demos_current.ADHD == True)\n",
    "    if do_print:\n",
    "        print(consensus_and_demos_current[\"anxiety_or_ADHD\"].value_counts())\n",
    "    consensus_and_demos_current['depressionYES_anxietyADHDNO'] = (consensus_and_demos_current.currently_depressed == True) & (consensus_and_demos_current.anxiety_or_ADHD == False)\n",
    "    consensus_and_demos_current['depressionNO_anxietyADHDYES'] = (consensus_and_demos_current.currently_depressed == False) & (consensus_and_demos_current.anxiety_or_ADHD == True)\n",
    "    if do_print:\n",
    "        print(consensus_and_demos_current[\"currently_depressed\"].value_counts())\n",
    "        print(consensus_and_demos_current[\"depressionYES_anxietyADHDNO\"].value_counts())\n",
    "        print(consensus_and_demos_current[\"depressionNO_anxietyADHDYES\"].value_counts())\n",
    "\n",
    "    if do_print:\n",
    "        print('\\nAFTER REMOVING DUPLICATES AND MISSING DATA')\n",
    "        print(consensus_and_demos_current.shape)\n",
    "    # AGE\n",
    "    if do_print:\n",
    "        print('\\nRIGHT AGE')\n",
    "        a =  ((consensus_and_demos_current.Age.astype(float) >= 8.0) & (consensus_and_demos_current.Age.astype(float) <= 13.0))\n",
    "        print(a.shape)\n",
    "    \n",
    "    # AGE\n",
    "    consensus_and_demos_current[\"depressed_9-13\"] = (consensus_and_demos_current.currently_depressed == True) & ((consensus_and_demos_current.Age.astype(float) >= 8.0) & (consensus_and_demos_current.Age.astype(float) <= 13.0))\n",
    "    consensus_and_demos_current[\"healthy_9-13\"] = (consensus_and_demos_current.healthy == True) & ((consensus_and_demos_current.Age.astype(float) >= 8.0) & (consensus_and_demos_current.Age.astype(float) <= 13.0))\n",
    "    consensus_and_demos_current[\"depressionYES_anxietyADHDNO_9-13\"] = (consensus_and_demos_current.depressionYES_anxietyADHDNO == True) & ((consensus_and_demos_current.Age.astype(float) >= 8.0) & (consensus_and_demos_current.Age.astype(float) <= 13.0))\n",
    "    consensus_and_demos_current[\"depressionNO_anxietyADHDYES_9-13\"] = (consensus_and_demos_current.depressionNO_anxietyADHDYES == True) & ((consensus_and_demos_current.Age.astype(float) >= 8.0) & (consensus_and_demos_current.Age.astype(float) <= 13.0))\n",
    "    if do_print:\n",
    "        print('\\nDEPRESSION 9 to 13 (<=13)')\n",
    "        print(consensus_and_demos_current[\"depressed_9-13\"].value_counts())\n",
    "        print('\\nHEALTHY 9 to 13 (<=13)')\n",
    "        print(consensus_and_demos_current[\"healthy_9-13\"].value_counts())\n",
    "        print('\\ndepressionYES_anxietyADHDNO 9 to 13 (<=13)')\n",
    "        print(consensus_and_demos_current[\"depressionYES_anxietyADHDNO_9-13\"].value_counts())\n",
    "        print('\\ndepressionNO_anxietyADHDYES 9 to 13 (<=13)')\n",
    "        print(consensus_and_demos_current[\"depressionNO_anxietyADHDYES_9-13\"].value_counts())\n",
    "\n",
    "    # NOW START CBCL\n",
    "    cbclfile = pd.read_csv(path_to_cbclfile, sep=',', header=0, low_memory=False)\n",
    "    names_columns_cbcl = cbclfile.loc[0].to_dict()\n",
    "    cbclfile = cbclfile.drop(0)\n",
    "    if do_print:\n",
    "        print(cbclfile.shape)\n",
    "    cbcl_relevant = cbclfile[['CBCL_AD', 'CBCL_WD','CBCL_05', 'CBCL_14', 'CBCL_18', 'CBCL_24', 'CBCL_35', 'CBCL_52', 'CBCL_54', 'CBCL_76', 'CBCL_77', 'CBCL_91', 'CBCL_100', 'CBCL_102', 'CBCL_103']]\n",
    "    # checking for missing values\n",
    "    where_are_NaNs = pd.isna(cbcl_relevant)\n",
    "    cbcl_relevant_replacednans = cbcl_relevant.copy()\n",
    "    cbcl_relevant_replacednans[where_are_NaNs] = 99\n",
    "    relevant_cbcl_columns = ['CBCL_AD', 'CBCL_WD','CBCL_05', 'CBCL_14', 'CBCL_18', 'CBCL_24', 'CBCL_35', 'CBCL_52', 'CBCL_54', 'CBCL_76', 'CBCL_77', 'CBCL_91', 'CBCL_100', 'CBCL_102', 'CBCL_103']\n",
    "    if do_print:\n",
    "        for cbcl_column in relevant_cbcl_columns:\n",
    "            print(cbcl_relevant_replacednans[cbcl_column].value_counts())\n",
    "    # Ok we have a few nans\n",
    "    # We need to remove them, but before we do, lets add the ids\n",
    "    cbcl_relevant = cbcl_relevant_replacednans.copy()\n",
    "    cbcl_relevant = cbcl_relevant.astype(int)\n",
    "    if do_print:\n",
    "        for value in relevant_cbcl_columns:\n",
    "            print(cbcl_relevant[value].dtypes) \n",
    "    cbcl_relevant['EID'] = cbclfile['EID']\n",
    "    my_hbn_check = pd.merge(consensus_and_demos_current, cbcl_relevant, on='EID')\n",
    "    checkage = my_hbn_check[(my_hbn_check[relevant_cbcl_columns] == 99).any(axis=1)]\n",
    "    if do_print:\n",
    "        print(checkage.Age.astype(float).value_counts())\n",
    "    # so we have some missing data in our age group. how many?\n",
    "    checkage['age_9to13'] = (checkage.Age.astype(float) >= 8.0) & (checkage.Age.astype(float) <= 13.0)\n",
    "    if do_print:\n",
    "        print(checkage.age_9to13.value_counts())\n",
    "    # let's remove the rows where cbcl = 99\n",
    "    my_hbn_check = my_hbn_check[~(my_hbn_check[relevant_cbcl_columns] == 99).any(axis=1)]\n",
    "    if do_print:\n",
    "        print(my_hbn_check.shape)\n",
    "    cbclaff_columns = ['CBCL_05', 'CBCL_14', 'CBCL_18', 'CBCL_24', 'CBCL_35', 'CBCL_52', 'CBCL_54', 'CBCL_76', 'CBCL_77', 'CBCL_91', 'CBCL_100', 'CBCL_102', 'CBCL_103']\n",
    "    my_hbn_check['CBCL_depressed'] = np.sum(my_hbn_check[cbclaff_columns], axis=1)\n",
    "    my_hbn_check.head()\n",
    "    my_hbn = my_hbn_check.copy()\n",
    "    # MERGING CONSENSUS_AND_DEMOS_CURRENT WITH CBCL_RELEVANT\n",
    "    my_hbn[\"depressed_9-13\"] = (my_hbn.currently_depressed == True) & ((my_hbn.Age.astype(float) >= 8.0) & (my_hbn.Age.astype(float) <= 13.0))\n",
    "    my_hbn[\"healthy_9-13\"] = (my_hbn.healthy == True) & ((my_hbn.Age.astype(float) >= 8.0) & (my_hbn.Age.astype(float) <= 13.0))\n",
    "    my_hbn[\"depressionYES_anxietyADHDNO_9-13\"] = (my_hbn.depressionYES_anxietyADHDNO == True) & ((my_hbn.Age.astype(float) >= 8.0) & (my_hbn.Age.astype(float) <= 13.0))\n",
    "    my_hbn[\"depressionNO_anxietyADHDYES_9-13\"] = (my_hbn.depressionNO_anxietyADHDYES == True) & ((my_hbn.Age.astype(float) >= 8.0) & (my_hbn.Age.astype(float) <= 13.0))\n",
    "    if do_print:\n",
    "        print('\\nDEPRESSION 9 to 13 (<=13)')\n",
    "        print(my_hbn[\"depressed_9-13\"].value_counts())\n",
    "        print('\\nHEALTHY 9 to 13 (<=13)')\n",
    "        print(my_hbn[\"healthy_9-13\"].value_counts())\n",
    "        print('\\ndepressionYES_anxietyADHDNO 9 to 13 (<=13)')\n",
    "        print(my_hbn[\"depressionYES_anxietyADHDNO_9-13\"].value_counts())\n",
    "        print('\\ndepressionNO_anxietyADHDYES 9 to 13 (<=13)')\n",
    "        print(my_hbn[\"depressionNO_anxietyADHDYES_9-13\"].value_counts())\n",
    "    my_hbn['gs_depression'] = my_hbn['depressed_9-13'].astype(int)\n",
    "    # We only have Hyp 1 and Hyp 2a, so positive cases are the same\n",
    "    is_gs_pos =  my_hbn['gs_depression']==1\n",
    "    pos_gs_all = my_hbn[is_gs_pos]\n",
    "    # Negatives differ\n",
    "    if hypothesis == '1':\n",
    "        is_gs_neg = my_hbn['healthy_9-13']==1\n",
    "    elif hypothesis == '2a':\n",
    "        is_gs_neg = my_hbn['depressionNO_anxietyADHDYES_9-13']==1\n",
    "    neg_gs_all = my_hbn[is_gs_neg]\n",
    "    # Randomly choose the neg_ksads subsample\n",
    "    num_pos = pos_gs_all.shape[0]\n",
    "    num_neg = neg_gs_all.shape[0]\n",
    "    if num_neg < num_pos*10-num_pos:\n",
    "        size_subsample = num_neg\n",
    "    else:\n",
    "        size_subsample = num_pos*10-num_pos\n",
    "    neg_gs_subsample = neg_gs_all.sample(n = size_subsample, random_state = 4)\n",
    "    # print ('\\nOverall size of subsample n = %d' % size_subsample)\n",
    "    # mix positives and negatives\n",
    "    frames = [pos_gs_all, neg_gs_subsample]\n",
    "    my_subsample = pd.concat(frames)\n",
    "    my_subsample = my_subsample.sample(frac = 1)\n",
    "\n",
    "    # MEASURE\n",
    "    if measure == 'cbclaff':\n",
    "        my_subsample['input_measure'] = my_subsample['CBCL_depressed']\n",
    "    elif measure == 'anxiousdep':\n",
    "        my_subsample['input_measure'] = my_subsample['CBCL_AD']\n",
    "    elif measure == 'withdrawndep':\n",
    "        my_subsample['input_measure'] = my_subsample['CBCL_WD']\n",
    "        \n",
    "    # GENDER\n",
    "    if do_print:\n",
    "        print(my_subsample.Sex.value_counts())\n",
    "    # Sex: 1 = Female, 0 = Male\n",
    "    if sex == 'boys':\n",
    "        s = '0'\n",
    "    elif sex == 'girls':\n",
    "        s = '1'\n",
    "    if sex == 'both':\n",
    "        data_to_return = my_subsample\n",
    "    else:\n",
    "        data_to_return = my_subsample[my_subsample['Sex'] == s]\n",
    "    data_pos_sex = data_to_return[data_to_return['gs_depression']==1]\n",
    "\n",
    "    print('\\nMeasure = %s' % measure)\n",
    "    print('Sex = %s' % sex)\n",
    "    print('Hypothesis = %s' % hypothesis)\n",
    "\n",
    "    print('\\nSex = %s in final sample n = %d' % (sex, data_to_return.shape[0]))\n",
    "    print('positive %s in final sample n = %d' % (sex, data_pos_sex.shape[0]))\n",
    "    \n",
    "    return data_to_return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2a8388b0-50a8-4719-93bd-ab20e9888fd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# -----------------\n",
    "# ANALYSIS FUNCTONS\n",
    "# -----------------\n",
    "\n",
    "# help function for bootstrapping\n",
    "def gen_auc_boots(scores, truth, nboots, rng=None):\n",
    "    if rng is None:\n",
    "        rng = np.random.default_rng()\n",
    "    boot_res = []\n",
    "    for pp in range(nboots):\n",
    "        boot_ind = rng.choice(range(len(truth)), size=truth.size, replace=True)\n",
    "        boot_truth = truth.iloc[boot_ind]\n",
    "        boot_score = scores.iloc[boot_ind]\n",
    "        boot_res.append(roc_auc_score(boot_truth, boot_score))\n",
    "    return np.array(boot_res)\n",
    "\n",
    "# main analysis function\n",
    "def run_aucroc_and_plot(my_dat, path_to_save_plots, name_to_save, mymeasure, hypothesis, nboots=100, target_auc=0.8, do_print = False):\n",
    "    # [TODO] CHANGE TARGET_AUC FOR HYP 2B\n",
    "    # using https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html#sphx-glr-auto-examples-model-selection-plot-roc-py\n",
    "    print('BEGIN AUCROC...')\n",
    "    if do_print:\n",
    "        print(my_dat.head())\n",
    "    y_measure_df = my_dat['input_measure']    \n",
    "    # we only have hyp 1 and 2a, no need for loop here\n",
    "    y_true_df = my_dat['gs_depression']\n",
    "    if do_print:\n",
    "        print(my_dat.head())        \n",
    "    sample_auc_score = roc_auc_score(y_true_df, y_measure_df)\n",
    "    print('\\nSingle AUCROC score without bootstrapping:')\n",
    "    print(sample_auc_score)\n",
    "    #print('\\nSingle AUCROC score without bootstrapping = %d' % (sample_auc_score))\n",
    "    # plotting\n",
    "    # Compute ROC curve and ROC area for each class\n",
    "    fpr = dict()\n",
    "    tpr = dict()\n",
    "    roc_auc = dict()\n",
    "    fpr, tpr, _ = roc_curve(y_true_df, y_measure_df)\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    plt.figure()\n",
    "    lw = 2\n",
    "    plt.plot(\n",
    "        fpr,\n",
    "        tpr,\n",
    "        color=\"darkorange\",\n",
    "        lw=lw,\n",
    "        label=\"ROC curve (area = %0.2f)\" % roc_auc,\n",
    "    )\n",
    "    plt.plot([0, 1], [0, 1], color=\"navy\", lw=lw, linestyle=\"--\")\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel(\"False Positive Rate\")\n",
    "    plt.ylabel(\"True Positive Rate\")\n",
    "    plt.title(\"Receiver operating characteristic\")\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show()\n",
    "    # We save the data for future plotting of all hypotheses in one figure, for the paper\n",
    "    with open(path_to_save_plots+name_to_save+'_true.npy', 'wb') as f:\n",
    "        np.save(f, y_true_df)\n",
    "    with open(path_to_save_plots+name_to_save+'_'+mymeasure+'.npy', 'wb') as f:\n",
    "        np.save(f, y_measure_df)\n",
    "    # bootstrapping\n",
    "    boot_ind = np.random.choice(range(len(y_true_df)), size=y_true_df.size, replace=True)\n",
    "    boot_truth = y_true_df.iloc[boot_ind]\n",
    "    boot_score = y_measure_df.iloc[boot_ind]\n",
    "    rng = np.random.default_rng()\n",
    "    boots = gen_auc_boots(y_measure_df, y_true_df, nboots=1000, rng=rng)\n",
    "    boots = np.hstack([boots, np.array([sample_auc_score])])\n",
    "    #print('min bootstrapping aucroc = %d' % (min(boots)))\n",
    "    #print('max bootstrapping aucroc = %d' % (max(boots)))  \n",
    "    print('min bootstrapping aucroc:')\n",
    "    print(min(boots))\n",
    "    print('max bootstrapping aucroc:')\n",
    "    print(max(boots))\n",
    "    p_onesided = (boots >= target_auc).mean()\n",
    "    print('p_onesided = %d' % (p_onesided))  \n",
    "    p_twosided1 = (boots > target_auc).mean()\n",
    "    p_twosided2 = (boots < target_auc).mean()\n",
    "    p_twosided = min(p_twosided1, p_twosided2)*2\n",
    "    print('p_twosided = %d' % (p_twosided))  \n",
    "    boots_mean_AUCROC = np.mean(boots)\n",
    "    q_25 = np.quantile(boots, .025)\n",
    "    q_75 = np.quantile(boots, .975)\n",
    "    #print('boots_mean_AUCROC = %d(%d, %d)' % (boots_mean_AUCROC, q_25, q_75)) # why is this not working?\n",
    "    print('boots_mean_AUCROC =')\n",
    "    print(str(boots_mean_AUCROC)+'('+str(q_25)+','+str(q_75)+')') # this is so ugly omg but at least it's working\n",
    "    # for confusion matrix for optimal thresholds:\n",
    "    y_true = y_true_df.tolist()\n",
    "    y_measure = y_measure_df.tolist()\n",
    "    print('\\n...END AUCROC')\n",
    "    return (y_true, y_measure, boots_mean_AUCROC, str(q_25), str(q_75), p_onesided, p_twosided)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "0d41e82e-937a-42f0-9977-eb412aea1586",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = cbclaff\n",
      "Sex = both\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = both in final sample n = 173\n",
      "positive both in final sample n = 68\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8884453781512605\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7822510822510822\n",
      "max bootstrapping aucroc:\n",
      "0.9643178410794603\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8886788274190327(0.8302721088435374,0.9383050351288057)\n",
      "\n",
      "...END AUCROC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = cbclaff\n",
      "Sex = both\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = both in final sample n = 680\n",
      "positive both in final sample n = 68\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.7360029796232218\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.6349878502001144\n",
      "max bootstrapping aucroc:\n",
      "0.8332188644688645\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.7366304982885501(0.6788870523415977,0.7949889258028793)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = cbclaff\n",
      "Sex = boys\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = boys in final sample n = 102\n",
      "positive boys in final sample n = 50\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8863461538461539\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7983934169278997\n",
      "max bootstrapping aucroc:\n",
      "0.9613015017327684\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8856390872547281(0.8228174603174602,0.9412783981517134)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = cbclaff\n",
      "Sex = boys\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = boys in final sample n = 470\n",
      "positive boys in final sample n = 50\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.7477142857142858\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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m6PV6zp07x/r16wkICDBdqkuLv78/kydPxtbWlkGDBqUYUPCTTz5h9+7dNGjQgNdff50qVapw7949jh49ys6dO7l3794zfV86duxIy5YtmTBhAleuXKFmzZr89ttvbN68mXfeeSfFLcjVqlXDz8/P7PZ5wOyDMzOyvvTSS3z00UcMHDiQxo0bc/LkSVavXm06m5ekbNmyFCpUiIULF+Lo6IiDgwMNGjRIdx+ptMyYMYNOnTrRpEkTBg4cSHh4OF9//TXVqlUzK45S4+TkxBdffMHgwYOpV68evXr1wsXFhRMnTvDw4cNUx416kpdeeomNGzfSpUsXOnTowOXLl1m4cCFVqlR5apaMHqNly5b07duXL7/8kgsXLtCuXTsMBgP79u2jZcuWDB8+HAAfHx927tzJnDlz8PT0pHTp0jRo0CBLfk5///13hg8fTvfu3alQoQKJiYmsWrXKVHglSSvTf2X2+yPyuOy+TU2I55F0m+zff/+d4jG9Xq/Kli2rypYtqxITE5VSSl26dEn169dPubu7KysrK1W8eHH10ksvqR9//NFs37t376rhw4er4sWLK2tra1WiRAnVv39/s1uE4+Pj1aeffqqqVq2qbGxslIuLi/Lx8VFTp05VERERpu3+e/t8kgsXLphuT9+/f3+qry80NFS99dZbysvLS1lZWSl3d3fVunVrtXjxYtM2SbceP+1W48c9ePBAjRo1Snl6eiorKytVvnx5NXv27BS3EgPqrbfeUt9//70qX768srGxUbVr1zbd5pyZWWNjY9WYMWOUh4eHsrOzU02aNFGBgYHK19dX+fr6mm27efNmVaVKFVWgQAGzW+nTun1+9uzZKZ4PUFOmTDFrW7t2rapUqZKysbFR1apVU1u2bFHdunVTlSpVevI39JEtW7aoxo0bKzs7O+Xk5KTq16+vfvjhB9Pjvr6+qmrVqin2+29ug8GgZsyYoUqVKmX6nm/dujVDry+9x1DKeKv97NmzVaVKlZS1tbUqWrSoevHFF9WRI0dM25w7d041b95c2dnZKcDsZ/p53/v/3j4fHBysXnvtNVW2bFlla2urChcurFq2bKl27txptl9amf57+3ySp70/QiillMw1JoQw0el0vPXWWykuo+UntWrVomjRovzvf//TOooQIhtIHyEhRL6UkJCQol/Knj17OHHiBC1atNAmlBAi20kfISFEvnTjxg3atGlDnz598PT05Ny5cyxcuBB3d3eGDh2qdTwhRDaRQkgIkS+5uLjg4+PDt99+y507d3BwcKBDhw588sknzz2goxAi95A+QkIIIYTIt6SPkBBCCCHyLSmEhBBCCJFv5bs+QgaDgZs3b+Lo6CizEAshhBC5hFKKBw8e4OnpmWJA2ueR7wqhmzdvPnWCTCGEEELkTNeuXcvUiXjzXSGUNOnktWvXcHJy0jiNEEIIIdIjMjISLy8vs8mjM0O+K4SSLoc5OTlJISSEEELkMpndrUU6SwshhBAi35JCSAghhBD5lhRCQgghhMi3pBASQgghRL4lhZAQQggh8i0phIQQQgiRb0khJIQQQoh8SwohIYQQQuRbUggJIYQQIt+SQkgIIYQQ+ZamhdAff/xBx44d8fT0RKfT8fPPPz91nz179lCnTh1sbGwoV64cy5cvz/KcQgghhMibNC2EoqOjqVmzJvPnz0/X9pcvX6ZDhw60bNmS48eP88477zB48GACAgKyOKkQQggh8iJNJ1198cUXefHFF9O9/cKFCyldujSff/45AJUrV2b//v188cUX+Pn5ZVVMIYQQQuRRuWr2+cDAQNq0aWPW5ufnxzvvvKNNICGEEEJknfgHEHYaw51TnN53PEueIlcVQiEhIRQrVsysrVixYkRGRhITE4OdnV2KfeLi4oiLizOtR0ZGZnlOIYQQQmRAQgzcOwthp+DuaeO/YafgwVVuRRZk4LrO7L3kniVPnasKoWcxc+ZMpk6dqnUMIYQQQujjIfx8cqGTVPTcvwSoFJtvPlWRwRteJizaAYjNkki5qhByd3cnNDTUrC00NBQnJ6dUzwYBjBs3jtGjR5vWIyMj8fLyytKcQgghRL5mSDQWN4+f3bl72lgEGRLTdYg7cW70/qE70XHGUsWtiBW372Z+1FxVCDVq1Ijt27ebtf3vf/+jUaNGae5jY2ODjY1NVkcTQggh8h9lgMh/HxU7p+Huo6Ln3jnQxz19f4ACdlCkCrhWgyJVTf8WdfRirtsxXn/9Fzp3rsScOb6UKfNxpr8ETQuhqKgoLl68aFq/fPkyx48fp3DhwpQsWZJx48Zx48YNVq5cCcDQoUP5+uuvef/993nttdf4/fffWb9+Pdu2bdPqJQghhBB5n1IQdeOxMzyPip67ZyAhOn3HsLSGwpXMih1cq4GTN1hYotcbSEw0YGOTXJoMGlQbLy8n2rYty4MHD7LkpWlaCB0+fJiWLVua1pMuYfXv35/ly5dz69Ytrl69anq8dOnSbNu2jVGjRjFv3jxKlCjBt99+K7fOCyGEEJnl4e3/nOF59G9cRPr211mCS/kUZ3goVA4srVLd5dq1CPr1+5lq1Yry1Vftkw+l0+HnVy4zXlXacZVSKXsn5WGRkZE4OzsTERGBk5OT1nGEEEIIbcSGpyx2wk5DzJ10HkAHzqWNhc7jRY9LRSiQ/i4p69efZsiQrdy/b+wMvW1bL9q3L59iu6z6/M5VfYSEEEIIkUHxUcZLWGGnzIueqJvpP4ajV3Khk1T0FKkMVg7PHCsyMo6RI39lxYoTpjYvLyccHa2f+ZjPQgohIYQQIi9IiDF2Uk7qx5P0b+SV9B/Dvpj52R3XasaOzDbOmRo1MPAaffpsIjg43NTm71+VBQs64OKS+l3gWUUKISGEECI30Sckj8XzeNFz/6LxLq70sHWBItVS9uOxd83S6ImJBqZP/4OPP/4Dvd7YM8fR0Zr589vTp08NdDpdlj5/aqQQEkIIIXIigx4iglMOPhh+HgwJ6TuGVcGUxY5rNXBwh2wuOu7efUjHjj8QGHjd1Na4sRfff9+F0qVdsjXL46QQEkIIIbSkDBB5NeXgg/fOQmI6R1MuYAuFq4Br1eQzPa5VwbFkthc8aSlUyJYCBSwAsLTUMXmyL+PHNzO1aUUKISGEECI7KAXRt1Je0go7DQlR6TuGhRUUrvio2Hms6HEuDRaWWZv/OVlaWrBqVRe6dl3P/PntadiwhNaRACmEhBBCiKwReQ2u74Wbf0LYSWPRExv+9P0AdBZQqPxjxc6jS1qFyqc5Fk9Os3fvFezsrKhfv7iprVSpQhw+/LomfYHSIoWQEEII8byUgojLxsLn+l64tjf9d2s5lzYvdopUNY7AXMA2SyNnlfh4PVOm7ObTTw9QurQLx48PwdExeVyhnFQEgRRCQgghRMYpBfeC4MYfxqLn+l7jFBRPUrD4o0LnsaKncGWwLpg9mbNBUFAYvXpt5OjRWwAEB4ezYMFh3n+/icbJ0iaFkBBCCPE0ymDsy3P9j0dnff6Ah6Fpb29pAx4NoYQvlGgOxXzAtlC2xc1uSimWLDnKO+/sICbGOLu8lZUF06e3YsyYxhqnezIphIQQQoj/Mujhzonkouf6Poi9m/b2BezBszF4+RqLH/d6ufbSVkbduRPN66//wubNQaa2ihWLsGZNN+rU8dAwWfpIISSEEELoE+D2UeNlrht/wI39T55k1NoRijd9dMbH13jGJ5d0Ys5MAQEXGTBgMyEhyXe9DR3qw+ef+2Fvnzu+H1IICSGEyH8S4yDk7+TOzTf/hITotLe3dYHizY2Xubx8oWhNsMjfH6GhoVF07ryO2FjjpTBXV3uWLn2Zjh0rapwsY/L3uyiEECJ/SIiBW38lFz63/nryYIV2RY0FT/FHhY9rNeMt7cKkWLGCfPJJa955JwA/v7IsX94Zd/fc1/FbCiEhhBB5T3yU8SxP0q3sIYeePC1FQc/ky1wlmhtvX89ht3lrzWBQ6PUGrKySB24cMaIBJUo40aVLZSwscuf3SwohIYQQuV/sfWO/nqS7ukKPgNKnvb1TKfPCp1BZKXye4NatBwwYsJlatYrx6acvmNotLHR061ZFw2TPTwohIYQQuU/M3UdFz6PC5/ZxQKW9faFyxqLH61Hh41Qqu5Lmeps3n2PQoC3cvRvD//53CT+/crRqVVrrWJlGCiEhhBA5X3SIsehJuqsr7NSTty9SxVjwJJ3xKeiZPTnzkOjoeMaM+Y1Fi46Y2ooVy319gJ5GCiEhhBA5z4Pryf17rv8B4UFP2FgHRWs8Vvg0A3u3bIuaFx05cpNevTZy/nzy2EmdOlXk229fxtXVXsNkmU8KISGEENpSyjgvV9JUFdf3GuftSovOAtzqJJ/tKd4U7ApnW9y8TK838NlnfzJx4m4SEw0A2NtbMXeuH4MH18lx84RlBimEhBBCZC+lIPx8cv+ea3sh6nra21sUgGL1kvv3eDYBG6fsy5tPhIU9pHv3DezZc8XU5uPjwZo13ahQoYh2wbKYFEJCCCGyljLA3TPJl7lu/GHs85MWSxvwaJB8V5dnQ7ByyL68+ZSzsw1RUfGA8Qa6sWOb8uGHLbC2tnzKnrmbFEJCCCEyl0EPd/5Jvsz11Hm67IzzdCXd1eVeP9/M05WTWFlZsnp1Vzp3XsuCBR3w9fXWOlK2kEJICCHE89EnwO1jyYVPeubp8mySXPgU8wFL6+zLKwAIDLyGvb0VNWu6m9oqVCjCqVNv5trBEZ+FFEJCCCEyJjEOQg8n9++5eSAd83Q1S76ry61Wvp+nS0uJiQamT/+Djz/+gwoVinD48BtmE6TmpyIIpBASQgjxNKZ5uh51br4V+PR5uko0Ty58ilaXebpyiODgcPr02UhgoLFz+tmzYXzzzd+8+25jjZNpRwohIYQQ5kzzdD0qfEIOgT4+7e0dPMxHbS5cWaaryGGUUqxa9Q/Dh2/nwQPje2lpqWPKFF/eeaehxum0JYWQEELkd1E34dYh45mepHm6DIlpb+9Y8lHRkzRPVzkpfHKw8PAYhg7dxvr1p01tZcu68P33XWnYsISGyXIGKYSEECI/ib1v7N8TcghC/jb+G3XzyfsUKpt8K7uXr8zTlYvs2XOFvn03cf16pKlt4MBazJvXDkdHGw2T5RxSCAkhRF6VGGucjDTkUHLhE37+6fsVrmw+T5dj8SyPKjLfrVsP8PP7nvh4PQAuLrYsWvQS3btX1ThZziKFkBBC5AUGvXHQwqSzPCF/Q9g/T77EBcZb2d3rGUdu9qhvnK5C5unKEzw8HJkyxZcJE36nZUtvVq7sQokSMiL3f0khJIQQuU3S3Fwhfxv79oT+bezX86Rb2ME4Vk/RWsYBC93rGf8tXEHu6MojlFIYDApLy+T384MPmuDl5UTv3jXy3W3x6SWFkBBC5HQPbz860/PY2Z6YsKfspIMiVZILHvd6xhnaZeDCPOnOnWhef/0Xatd2Z8qUFqZ2S0sL+vatqV2wXEAKISGEyEnio4xndx4veiKvPH0/p1LmRU8xH+NlL5HnBQRcZMCAzYSERLF163nati1Lo0ZeWsfKNaQQEkIIrejjIeyk8fJWUuFz76xxktInsS1i7M+T1K/HvZ7068mHYmMTGTduJ3PnHjS1ubjYmcYJEukjhZAQQmQHZYDwC+a3rd8+Dvq4J+9XwN54difpTI9HfXDylnF78rmTJ0Pp3XsjJ0/eNrX5+ZVl+fLOuLsX1DBZ7iOFkBBCZIUHN8yLntDDT56IFIzzb7lWN+/MXKSyzMslTAwGxVdfHeSDD3YSF2e8Ld7GxpJZs15g+PD60iH6Gcj/LiGEeF6x4RDyn0EKo289fT+XCv/pzFwLrOyyPK7Ine7efUjv3hsJCLhkaqte3Y01a7pRrZpcGn1WUggJIURGJMTAnePmRU/4hafv5+BhLHiS+va41zXOyi5EOjk4WHPjxgPT+qhRDZkxozW2tvJR/jzkuyeEEGkxJKYySOHJpw9SaOMMxeo+OtPz6GyPjM4snpOtbQHWrOlKp05rWbjwJdq2Lat1pDxBCiEhhADjIIURl82LntAjkPjwyftZ2oBbbfNLXC7lZZBC8dyOHLmJg4M1lSq5mtqqVy/G+fMjKFBAfr4yixRCQoj8SSm4sQ/+3ZVc+MTeffI+OotHgxQ+1pnZtZoMUigylV5v4LPP/mTixN1Uq+bGX38NwsYm+eNaiqDMJYWQECJ/SYyFcz/A0blw558nb+vkbX7bulsdsJZbk0XWuXYtgr59N7F3778AHD8ewjff/M2oUY00TpZ3SSEkhMgfHt6G4wvgxDfG5f+yK2p+ecu9HtgXzf6cIt9av/40Q4Zs5f79WMA4VNTYsU156636GifL26QQEkLkbWGn4MgXcHZ1ysELPRpAzTehRHPjFBUySKHQQGRkHCNH/sqKFSdMbV5eTqxa1QVfX2/tguUTUggJIfIeZYDLO4wF0NWd5o/pLKF8N/AZBZ4NtcknxCOBgdfo02cTwcHhpjZ//6osWNABFxcZUyo7SCEkhMg7Eh7CmVXG/j/3zpk/Zu0E1V+HOiOMZ3+E0NiNG5G0aLGC+HjjCNGOjtbMn9+ePn1qoJOzk9lGCiEhRO4XdROOz4cTCyH2nvljzmWgzttQbaDMxi5ylOLFnXj33UbMmLGfxo29+P77LpQuLYNsZjcphIQQuVfoUePlr6B1YEgwf6xEc6gzCsp2BAtLbfIJ8RilFIDZ2Z4PP2xByZLODBpUR26L14gUQkKI3MWgh0u/wNEv4Pof5o9ZFICKPY39f4rV0SafEKkID49h6NBt1KvnybvvNja1W1lZMmRIXQ2TCSmEhBC5Q/wDOLUMjs6DiGDzx2wLQ82hUOstKOipTT4h0rBnzxX69t3E9euRbNp0ltatS1O7tofWscQjUggJIXK2yH/h6Fdw6luIizB/rHAlqPMOVOkLVvaaxBMiLfHxeiZP3s2sWQd4dFWMggWtCQmJ0jaYMCOFkBAiZ7oZaOz/c2EjKL35Y6VeMF7+8vaTOb1EjhQUFEavXhs5evSWqa1lS29WruxCiRJOGiYT/yWFkBAi5zAkwvmfjP1/bh00f8zSBir3AZ93jPN7CZEDKaVYvPgIo0YFEBOTCICVlQXTp7dizJjGWFjIbfE5jRRCQgjtxd6Hk0vg2Ffw4Jr5Y/Zuxr4/NYcal4XIoe7di2HgwM1s2RJkaqtYsQhr1nSjTh3pE5RTSSEkhNBO+EVj5+fTyyAh2vwx1+rGy1+VXoUCttrkEyIDbGwsOXcuzLQ+bFhdPvusLfb2VhqmEk8jhZAQInspBdf3Gvv/XPoFUOaPl+lgHP+nZCuZ+0vkKg4O1qxe3ZVOndaycGEHOnasqHUkkQ5SCAkhsoc+Hs6tNU5/cfuY+WMF7KFqf+MI0IXlw0PkDidPhuLgYE2ZMsmjQdet60lw8EhsbOTjNbeQd0oIkbUehsE/i+D41xAdYv5YweJQazjUeAPsCmuTT4gMMhgUX311kA8+2Ent2h7s2zfQbFRoKYJyF3m3hBBZ4+5Z49mfMyshMdb8sWJ1jf1/KnQHS+k/IXKPW7ceMGDAZn777RIAf/11nQUL/mbEiAYaJxPPSvMBOObPn4+3tze2trY0aNCAQ4cOPXH7uXPnUrFiRezs7PDy8mLUqFHExsY+cR8hRDZRCq78Bj+9CMurwD+Lk4sgnQWU7wr++6D3IajcS4ogkats3nyO6tUXmIoggFGjGvL66z4aphLPS9MzQuvWrWP06NEsXLiQBg0aMHfuXPz8/AgKCsLNLeVtsmvWrGHs2LEsXbqUxo0bc/78eQYMGIBOp2POnDkavAIhBAAJMXB2tfEM0N3T5o9ZO0K1QVBnJDiX1iSeEM8jOjqeMWN+Y9GiI6Y2D4+CLF/embZty2qYTGQGnUqaDlcDDRo0oF69enz99dcAGAwGvLy8GDFiBGPHjk2x/fDhwzl79iy7du0ytY0ZM4aDBw+yf//+dD1nZGQkzs7ORERE4OQko3sK8VyiQ+D4N3BiAcSEmT/m5G0sfqoNAhv5vyZypyNHbtKr10bOn79rauvcuRJLlnTE1VWmdclOWfX5rdkZofj4eI4cOcK4ceNMbRYWFrRp04bAwMBU92ncuDHff/89hw4don79+gQHB7N9+3b69u2b5vPExcURFxdnWo+MjMy8FyFEfnX7hHH053M/GO8Ge5xnE2P/n3KdjLPBC5FLXbsWQePGS4mPN07xYm9vxbx57Rg0qDY6Gdohz9Dst1RYWBh6vZ5ixYqZtRcrVoxz586luk+vXr0ICwujadOmKKVITExk6NChjB8/Ps3nmTlzJlOnTs3U7ELkS8oAwduM4/9c223+mM4SKvYwToDqUV+TeEJkNi8vZ958sy5z5x7Ex8eDNWu6UaFCEa1jiUyWq/5c27NnDzNmzOCbb76hQYMGXLx4kbfffpuPP/6YSZMmpbrPuHHjGD16tGk9MjISLy+v7IosRO6XEA2nlsOxeRB+wfwxm0JQYwjUHg6OJbRIJ0SmUkqZne2ZObMNJUs689Zb9bG2ttQwmcgqmhVCrq6uWFpaEhoaatYeGhqKu7t7qvtMmjSJvn37MnjwYACqV69OdHQ0b7zxBhMmTMDCIuVNcDY2NtjY2GT+CxAir3tw3Tj31z+LIe6++WMu5Y1nf6r2BysHLdIJkakiI+MYOfJX6tcvzptv1jO129oWYNSoRhomE1lNs0LI2toaHx8fdu3aRefOnQFjZ+ldu3YxfPjwVPd5+PBhimLH0tJYoWvY51uIvOXWIePlr/MbQOnNH/Nqaez/U6aD8XZ4IfKAwMBr9O69kcuX77Nu3WlatvSmcuWiWscS2UTTS2OjR4+mf//+1K1bl/r16zN37lyio6MZOHAgAP369aN48eLMnDkTgI4dOzJnzhxq165tujQ2adIkOnbsaCqIhBDPwJAIF382FkA3/zR/zNLaOPFpnXfArZYG4YTIGomJBqZN+4Np0/5Arzf+MW1lZcGlS+FSCOUjmhZC/v7+3Llzh8mTJxMSEkKtWrXYsWOHqQP11atXzc4ATZw4EZ1Ox8SJE7lx4wZFixalY8eOTJ8+XauXIETupZTx8teFH+HolxB5xfxxO1eoOQxqvQkOqV+uFiK3Cg4Op0+fjQQGXje1NW7sxfffd6F0aZcn7CnyGk3HEdKCjCMk8h2l4OFtCDtlHOww7FTycnwqw0kUqWKc/b1yb7Cyy/68QmQhpRQrV55g+PBfiYoyDv1gaalj8mRfxo9vZjZnmMhZ8tw4QkKILBBzL7nYefzf/w52mBrvdsb+P6VeABkjReRB9+/HMmTIVtavTx79vEwZF1av7krDhnLXY34lhZAQuVH8A7h7xvzsTtgpiL6V/mM4lgTXqlC0JlTpazwTJEQeptPBwYPJl8IGDKjFl1+2w9FR7izOz6QQEiInS4iBe2dTXtKK/Df9x3BwhyLVwLUaFKn66N8qMu2FyHecnW1ZtaoLXbuu55tv2tO9e1WtI4kcQAohIXICfTyEn0/Zjyci2Diic3rYFn5U5DwqelyrGgsfOxkJV+RPQUFhODhYU6JEctHfrFkprlx5GwcHaw2TiZxECiEhspMhEe5feqzYOQ13TxmLIENi+o5h7fio2Kn6WOFTFeyLSd8eITB2iF68+AijRgXQsGEJdu7sh4VF8v8NKYLE46QQEiKrxNyFm4GPzvI8KnrunQV93NP3BShgZ7yEZXZJqyo4eknBI0Qa7tyJZvDgX9iyJQiA3buvsHjxEYYOratxMpFTSSEkRFa4uhs2d0799vT/srCCwpUeXc56rOhx8gYLGShUiPQKCLjIgAGbCQmJMrUNHepDv341NUwlcjophITIbBGX4ZdXUhZBOkvjHF1JhU5S0VOoHFhaaZNViDwgNjaRceN2MnfuQVObq6s9S5e+TMeOFTVMJnIDKYSEyEzxUfBzJ4i9Z1z3agHVXzcWPS4VoYDcpitEZjp5MpTevTdy8uRtU5ufX1mWL++Mu3tBDZOJ3EIKISEyi1KwYwCEnTSuu1SATj+DjbOWqYTIs/799z716i0hLs44ObCNjSWzZr3A8OH1zTpHC/EkMpa4EJnl4HS48JNx2doJOm2WIkiILFSqVCFT/5/q1d04fPgNRo5sIEWQyBA5IyREZri4BQ5MerSigw5roEglTSMJkR988YUfpUo5M2ZMY2xt5SNNZJycERLied09C7/2SV5vOh3KdNAujxB5UHR0PEOHbmX58uNm7Q4O1kyY0FyKIPHM5CdHiOcRGw6bOxnn/gKo0APqj9U2kxB5zJEjN+ndeyNBQXdZvfokzZqVpGzZwlrHEnmEnBES4lkZ9LCtF4RfMK4XrQntlspgh0JkEr3ewKef7qdhw+8ICroLgMGgOHXq9lP2FCL95IyQEM9q/3i4ssO4bOdqvEPMykHTSELkFdeuRdC37yb27k2eYNjHx4M1a7pRoYLMnycyjxRCQjyLs2vg71nGZZ0ldNwAzt6aRhIir1i//jRDhmzl/v1YwHiSdezYpnz4YQusrWW0dZG5pBASIqNCj8Bvg5LXW84zDpwohHguDx7EMWLEr6xYccLU5uXlxKpVXfD19dYumMjTpBASIiOiQ+HnzpBo/EuVaoOg1puaRhIir4iL0/Pbb5dM6/7+VVmwoAMuLnYaphJ5nXSWFiK99PHGOcSirhvXPRpB6/nSOVqITOLqas+KFZ1xcrJh5crO/PBDNymCRJaTM0JCpNfut+HGfuNyQU94+SeZO0yI5xAcHI6DgxXFiiXPCfbCC2X59993KFTIVsNkIj+RM0JCpMeJRXBioXHZ0gZe3gQFPbTNJEQupZRixYrj1Ky5kNde24JSyuxxKYJEdpJCSIinub4Pfh+evP7CYvCor10eIXKx8PAYevb8iQEDNhMVFc/27RdYtuy41rFEPiaXxoR4kshrxn5BhkTjus8oqNpP20xC5FJ79lyhb99NXL8eaWobMKAW3btX0TCVyO+kEBIiLQkPYXNnePhoFNuSbaD5LE0jCZEbxcfrmTx5N7NmHSDpKpiLiy2LFr1E9+5VtQ0n8j0phIRIjVLw2+tw+6hx3bkMvLQOLOS/jBAZce5cGL17b+To0VumtpYtvVm5sgslSjhpmEwII/mtLkRqDn8G59YYl60coPNmsJNJHoXIiODgcOrUWURMjPHSspWVBdOnt2LMmMZYWMiwEyJnkM7SQvzX5R2w77EZ5F9cBa7VtMsjRC5VpowLXbtWBqBixSL89ddg3nuviRRBIkeRM0JCPC78AmzrCcpgXG80Bcp30TaTELnY/PntKVXKmQkTmmNvb6V1HCFSeK4zQrGxsZmVQwjtxUXCz50gLsK4Xq4zNJqsaSQhcovY2ERGjdrBhg2nzdqdnW2ZPr21FEEix8pwIWQwGPj4448pXrw4BQsWJDg4GIBJkybx3XffZXpAIbKFMsD2PnDvrHG9SFV4cSXo5OqxEE9z8mQo9esvYe7cg7zxxlauXYvQOpIQ6Zbh3/LTpk1j+fLlzJo1C2tra1N7tWrV+PbbbzM1nBDZ5s8PIfgX47Kti7FztLWjppGEyOkMBsW8eX9Rr94STp40DjMRE5PA4cM3NU4mRPpluBBauXIlixcvpnfv3lhaWpraa9asyblz5zI1nBDZ4vyP8NfHxmWdBXRYB4XKaptJiBzu1q0HtG+/mnfeCSAuTg9A9epuHD78Bl26VNY4nRDpl+HO0jdu3KBcuXIp2g0GAwkJCZkSSohsc+cf+LV/8nrz2eD9gnZ5hMgFNm8+x+DBvxAW9tDUNmpUQ2bMaI2trdyDI3KXDP/EVqlShX379lGqVCmz9h9//JHatWtnWjAhstzDMGPn6MRHv8wr9zFOoSGESFV0dDxjxvzGokVHTG0eHgVZvrwzbdvKWVSRO2W4EJo8eTL9+/fnxo0bGAwGNm7cSFBQECtXrmTr1q1ZkVGIzGdIhG3+EHnFuF6srnEyVZ2MbyJEWiIj4/jpp7Om9c6dK7FkSUdcXe01TCXE88lwH6FOnTrxyy+/sHPnThwcHJg8eTJnz57ll19+4YUX5JKCyCX2vgtXfzcu2xeDTpvAyk7bTELkcB4ejnz7bUfs7a1YsqQjGzf2kCJI5Ho6pZKmwMsfIiMjcXZ2JiIiAicnmecmXzq1DAJeMy5bWEGP3VC8ibaZhMiBrl2LwMHBmsKFzf9IuH07Gjc3B41Sifwqqz6/M3xGqEyZMty9ezdF+/379ylTpkymhBIiy9w6CDuHJq+3ni9FkBCpWL/+NDVqLGTIkK389+9lKYJEXpLhQujKlSvo9foU7XFxcdy4cSNTQgmRJaJuwuYuoI83rtd8E2q8rm0mIXKYyMg4Bgz4GX//H7l/P5YffzzDmjUntY4lRJZJd2fpLVu2mJYDAgJwdnY2rev1enbt2oW3t3emhhMi0yTGwpauEH3LuF6iObScq2kkIXKawMBr9O69kcuX75va/P2r0r59ee1CCZHF0l0Ide7cGQCdTkf//v3NHrOyssLb25vPP/88U8MJkSmUgp3DjJfFABxLQscfwVLmPhICIDHRwPTpf/Dxx3+g1xsvgzk6WjN/fnv69KmBTu6mFHlYugshg8E4G3fp0qX5+++/cXV1zbJQQmSqY1/B6eXG5QJ20OlnsC+qZSIhcozg4HD69NlIYOB1U1vjxl58/30XSpd20TCZENkjw+MIXb58OStyCJE1rv4Oe0Ynr/stg2Iy8KcQABcv3qNOnUU8eGDsN2dpqWPyZF/Gj29GgQIy4bDIH55pLPTo6Gj27t3L1atXiY+PN3ts5MiRmRJMiOcWcRl+6Q7qUef++mOhkr+2mYTIQcqWdaF16zL8/PM5ypRxYfXqrjRsWELrWEJkqwwXQseOHaN9+/Y8fPiQ6OhoChcuTFhYGPb29ri5uUkhJHKG+CjY3Bli7xnXS78ITaZpGkmInEan07FkSUdKlXLm449b4uhoo3UkIbJdhs99jho1io4dOxIeHo6dnR1//fUX//77Lz4+Pnz22WdZkVGIjFEKAgYaJ1QFcKkA7deAhaW2uYTQUHy8nrFjd7Jt23mzdldXe+bObSdFkMi3MlwIHT9+nDFjxmBhYYGlpSVxcXF4eXkxa9Ysxo8fnxUZhciYgzPg/I/GZWsn6LQZbAtpGkkILQUFhdGo0Xd8+ukBXnttC6GhUVpHEiLHyHAhZGVlhYWFcTc3NzeuXr0KgLOzM9euXcvcdEJk1OVf4cDERys66LAGilTSNJIQWlFKsWjRYWrXXsTRo8YxtMLDYzhwQH5XC5Ekw32Eateuzd9//0358uXx9fVl8uTJhIWFsWrVKqpVq5YVGYVIn4QY43hBSZpOhzIdtMsjhIbu3Ilm8OBf2LIlyNRWsWIR1qzpRp06HhomEyJnyfAZoRkzZuDhYfxPNH36dFxcXBg2bBh37txh0aJFmR5QiHQ78jlE/mtcLtnGeJeYEPlQQMBFatRYaFYEDRtWl6NHh0gRJMR/yOzzIm94cB2WVoTEh6CzhH4nwLWq1qmEyFaxsYmMG7eTuXMPmtpcXe1ZuvRlOnasqGEyIZ5fjpl9Pi1Hjx7lpZdeyqzDCZEx+8YaiyCAWm9KESTypdu3o1m27LhpvV27cpw8OUyKICGeIEOFUEBAAO+++y7jx48nODgYgHPnztG5c2fq1atnmoZDiGx14084u9q4bFsYGn2oaRwhtFKypDMLFnTAxsaSL79sx/btvXB3L6h1LCFytHR3lv7uu+94/fXXKVy4MOHh4Xz77bfMmTOHESNG4O/vz6lTp6hcuXJWZhUiJWWA3W8nrzf5GOwKa5dHiGx069YDHByscXJKHgPo1Ver07RpSby8nDVMJkTuke4zQvPmzePTTz8lLCyM9evXExYWxjfffMPJkydZuHChFEFCG6dXQuhh47JrNajxhrZ5hMgmmzefo0aNhYwc+WuKx6QIEiL90l0IXbp0ie7duwPQtWtXChQowOzZsylRQualERqJfwD7xyWvt5gLFs80fZ4QuUZ0dDxDh26lc+d1hIU9ZMWKE/z00xmtYwmRa6X7UyMmJgZ7e3vAOD+NjY2N6TZ6ITRxcAZEhxiXy3WBUq21zSNEFjty5Ca9em3k/Pm7prbOnSvh6+utXSghcrkM/fn87bffUrCgseNdYmIiy5cvx9XV1WwbmXRVZIv7l+DIHOOypTX4yjx3Iu/S6w189tmfTJy4m8RE400p9vZWzJvXjkGDaqPT6TROKETule5xhLy9vZ/6n02n05nuJkuv+fPnM3v2bEJCQqhZsyZfffUV9evXT3P7+/fvM2HCBDZu3Mi9e/coVaoUc+fOpX379ul6PhlHKI/Y3AUu/mxcrj8Oms3QNI4QWeXatQj69t3E3r3/mtp8fDxYs6YbFSoU0TCZENkrqz6/031G6MqVK5n2pEnWrVvH6NGjWbhwIQ0aNGDu3Ln4+fkRFBSEm5tbiu3j4+N54YUXcHNz48cff6R48eL8+++/FCpUKNOziRzs353JRZCDOzQY98TNhcitzp+/S4MG33L/fiwAOh2MHduUDz9sgbW1pcbphMgbNB1ZukGDBtSrV4+vv/4aAIPBgJeXFyNGjGDs2JTTIyxcuJDZs2dz7tw5rKysnuk55YxQLmdIhJW14O5p43q75VC1v5aJhMgyBoOiffvVBARcwsvLiVWrukh/IJFv5fiRpTMqPj6eI0eO0KZNm+QwFha0adOGwMDAVPfZsmULjRo14q233qJYsWJUq1aNGTNmoNfrsyu20NqJRclFkHs9qNJX2zxCZCELCx3LlnXijTfqcOLEUCmChMgCmt1rHBYWhl6vp1ixYmbtxYoV49y5c6nuExwczO+//07v3r3Zvn07Fy9e5M033yQhIYEpU6akuk9cXBxxcXGm9cjIyMx7ESJ7xdyFPyclr7ecBzrNankhMlViooHp0/+gWbNStGpV2tTu4eHIokUdNUwmRN6WqwZdMRgMuLm5sXjxYiwtLfHx8eHGjRvMnj07zUJo5syZTJ06NZuTiizx54cQG25crtwHPBtpGkeIzBIcHE6fPhsJDLxO8eKO/PPPMAoXttM6lhD5gmZ/Tru6umJpaUloaKhZe2hoKO7u7qnu4+HhQYUKFbC0TO4kWLlyZUJCQoiPj091n3HjxhEREWH6unbtWua9CJF9wk7BiQXG5QL20OwTbfMIkQmUUqxceYJatRYSGHgdgJCQKHbvvqxxMiHyj2cqhC5dusTEiRN59dVXuX37NgC//vorp0+fTvcxrK2t8fHxYdeuXaY2g8HArl27aNQo9b/0mzRpwsWLF80mdz1//jweHh5YW1unuo+NjQ1OTk5mXyKXUQp2jwL1qC9Yg/HgWFzbTEI8p/DwGHr2/In+/X/mwQPjH3Jlyriwf/9rdOtWReN0QuQfGS6E9u7dS/Xq1Tl48CAbN24kKioKgBMnTqR5eSoto0ePZsmSJaxYsYKzZ88ybNgwoqOjGThwIAD9+vVj3LjkW6OHDRvGvXv3ePvttzl//jzbtm1jxowZvPXWWxl9GSI3ufQLXN1pXHbyBp/RmsYR4nnt2XOFGjUWsn598h+PAwbU4vjxITRsKNMWCZGdMtxHaOzYsUybNo3Ro0fj6Ohoam/VqpXpNvj08vf3586dO0yePJmQkBBq1arFjh07TB2or169ioVFcq3m5eVFQEAAo0aNokaNGhQvXpy3336bDz74IKMvQ+QWiXGw97HCx/czsJK+EyJ3io/XM2XKbj799ABJA5cUKmTL4sUv0b17VW3DCZFPZXgcoYIFC3Ly5ElKly6No6MjJ06coEyZMly5coVKlSoRGxubVVkzhYwjlMscmgX7HhW6Xi2g++/GUeWEyIWCg8OpUWMB0dEJALRo4c3KlZ1ltngh0iHHjCNUqFAhbt26laL92LFjFC8u/TZEJooOgb8+Ni7rLIyzy0sRJHKxMmVcmDevHVZWFsya1YZdu/pJESSExjJ8aaxnz5588MEHbNiwAZ1Oh8Fg4MCBA7z77rv069cvKzKK/GrfeEgw9kGjxhvgVlPbPEJkUFjYQ+ztrbC3Tx4J/7XXauPr6025coU1TCaESJLhM0IzZsygUqVKeHl5ERUVRZUqVWjevDmNGzdm4sSJWZFR5Echf8PpZcZlG2do/JG2eYTIoICAi1SvvoD33vvNrF2n00kRJEQO8sxzjV29epVTp04RFRVF7dq1KV++fGZnyxLSRygXUAp+aAK3Hk210uIL8HlH00hCpFdsbCLjxu1k7tyDpratW1+lQ4cKGqYSIvfTfPb5JPv376dp06aULFmSkiVLZloQIUzO/ZBcBBWuBLVkeASRO5w8GUrv3hs5efK2qa1du3L4+HhqmEoI8SQZvjTWqlUrSpcuzfjx4zlz5kxWZBL5WUI0/PF+8nqLL8DSKu3thcgBDAbFvHl/Ua/eElMRZGNjyZdftmP79l64uxfUOKEQIi0ZLoRu3rzJmDFj2Lt3L9WqVaNWrVrMnj2b69evZ0U+kd8c+hSibhiXy3SA0u20zSPEU9y69YD27VfzzjsBxMUZRz+vXt2Nw4ffYMSIBujkTkchcrRn7iMEcPnyZdasWcMPP/zAuXPnaN68Ob///ntm5st00kcoB4v8F5ZVgsRYsCgA/U9DYelXIXKuoKAwmjZdRljYQ1PbqFENmTGjNba2uWpOayFyvBwzjtDjSpcuzdixY/nkk0+oXr06e/fuzaxcIj/a+76xCAKo/bYUQSLHK1euMFWqFAXAw6MgAQF9mDPHT4ogIXKRZy6EDhw4wJtvvomHhwe9evWiWrVqbNu2LTOzifzk+h9wfr1x2a4oNJqkbR4h0sHS0oJVq7rQt28N/vlnGG3bltU6khAigzL8Z8u4ceNYu3YtN2/e5IUXXmDevHl06tQJe3v7rMgn8gODHn5/O3m96Qzj2EFC5CB6vYHPPvuTZs1K0bixl6m9ZElnVq7somEyIcTzyHAh9Mcff/Dee+/Ro0cPXF1dsyKTyG9OLYU7x43LbrWh2kBN4wjxX9euRdC37yb27v2X0qULcfz4UJycbLSOJYTIBBkuhA4cOJAVOUR+FXsf9k9IXm85DywsNYsjxH+tX3+aIUO2cv++sf/alSv3+e23S7zyShWNkwkhMkO6CqEtW7bw4osvYmVlxZYtW5647csvv5wpwUQ+8dfHEHPHuFzRH0o00zaPEI9ERsYxcuSvrFhxwtTm5eXEqlVd8PX11i6YECJTpev2eQsLC0JCQnBzc8PCIu3+1TqdDr1en6kBM5vcPp+D3AuCFdXAkAgFbGFgEDjJaOVCe4GB1+jTZxPBweGmNn//qixY0AEXFzsNkwmRf2k6xYbBYEh1WYjnsme0sQgCqPu+FEFCc4mJBqZP/4OPP/4Dvd74N6KjozXz57enT58aMjiiEHlQhm+fX7lyJXFxcSna4+PjWblyZaaEEvlA8Ha4vN24XLAE1H//ydsLkQ0uXbrHzJn7TUVQ48ZenDgxlL59a0oRJEQeleFCaODAgURERKRof/DgAQMHyt0+Ih30CcazQUmazwIrB+3yCPFIxYquzJr1ApaWOqZObcHevQMoXdpF61hCiCyU4bvGlFKp/mV0/fp1nJ1l7BeRDsfnQ3iQcdmzCVTqqW0ekW+Fh8dgb2+FjU3yr8IRI+rTqlVpqlVz0zCZECK7pLsQql27NjqdDp1OR+vWrSlQIHlXvV7P5cuXaddOJsgUT/HwDgR++GhFB63mgVxyEBrYs+cKfftuomfPqsye3dbUrtPppAgSIh9JdyHUuXNnAI4fP46fnx8FCxY0PWZtbY23tzfdunXL9IAijzkwCeIeXVqtNhCK+WibR+Q78fF6pkzZzaefHkAp+OyzQNq1K0fr1mW0jiaE0EC6C6EpU6YA4O3tjb+/P7a2tlkWSuRRt4/DP4uNy9aO0HS6pnFE/hMUFEavXhs5evSWqa1lS28qVpRR8oXIrzLcR6h///5ZkUPkdUrB7neAR8NWNZwEDu5aJhL5iFKKxYuPMGpUADExxiEbrKwsmD69FWPGNMbCQi7PCpFfpasQKly4MOfPn8fV1RUXF5cn3kZ67969TAsn8pALP8H1vcblQuWg9kht84h8486daAYP/oUtW4JMbRUrFmHNmm7UqeOhYTIhRE6QrkLoiy++wNHR0bQs42mIDEmIgb3vJq+3mAMFZMJKkfWCgsJo0WIFISFRprZhw+ry2Wdtsbe30jCZECKnSFch9PjlsAEDBmRVFpFXHfkcIv81LpdqC2Ve0jaPyDfKlHHBy8uJkJAoXF3tWbr0ZTp2rKh1LCFEDpLhARWPHj3KyZMnTeubN2+mc+fOjB8/nvj4+EwNJ/KAB9fh4Ezjss4SWn4ht8uLbGNlZcnq1V3p2rUyJ08OkyJICJFChguhIUOGcP78eQCCg4Px9/fH3t6eDRs28P77Mk2C+I99YyHxoXG51ptQpIq2eUSeZTAovvzyIMeO3TJrL1++CD/91AN394Jp7CmEyM8yXAidP3+eWrVqAbBhwwZ8fX1Zs2YNy5cv56effsrsfCI3uxkIZ1cbl20LQ6MPNY0j8q5btx7Qvv1q3n57B716beThwwStIwkhcokMF0JKKdMM9Dt37qR9+/YAeHl5ERYWlrnpRO6lDLD77eT1Jh+DXWHt8og8a/Pmc9SosZCAgEsAnDsXxq+/XtA4lRAit8jwOEJ169Zl2rRptGnThr1797JgwQIALl++TLFixTI9oMilzqyCkL+Ny67VoMYb2uYReU50dDxjxvzGokVHTG0eHgVZvrwzbduW1TCZECI3yXAhNHfuXHr37s3PP//MhAkTKFeuHAA//vgjjRs3zvSAIheKf2DsG5SkxVywyPCPmhBpOnLkJr16beT8+bumts6dK7FkSUdcXe01TCaEyG10SimVGQeKjY3F0tISK6ucPTZHZGQkzs7ORERE4OTkpHWcvGnfODj0iXG5XBfotFHbPCLP0OsNzJ79J5Mm7SYx0XiJ3t7eirlz/Rg8uI6McSZEHpZVn9/P/Gf6kSNHOHv2LABVqlShTp06mRZK5GL3L8GROcZlS2vw/UzbPCJPOXcuzKwI8vHxYM2ablSoUETjZEKI3CrDhdDt27fx9/dn7969FCpUCID79+/TsmVL1q5dS9GiRTM7o8hN9r4L+kfjSfmMgUIyo7fIPFWruvHxxy0ZP34XY8c25cMPW2Btbal1LCFELpbhu8ZGjBhBVFQUp0+f5t69e9y7d49Tp04RGRnJyJEyf1S+9u9OuPizcdnBAxqM0zSOyP0ePIgznf1J8t57jTl06HVmzGgtRZAQ4rlluBDasWMH33zzDZUrVza1ValShfnz5/Prr79majiRixgSH80u/0izT8DaUbM4IvcLDLxGrVqLmDbtD7N2S0sL6tb11CiVECKvyXAhZDAYUu0QbWVlZRpfSORDJxbB3dPGZff6UKWPtnlErpWYaGDq1D00a7aM4OBwPv74D/7885rWsYQQeVSGC6FWrVrx9ttvc/PmTVPbjRs3GDVqFK1bt87UcCKXiLkLf05KXm85D3QZ/tESguDgcJo3X8aHH+5Frzfe0NqwYQk8PGR6DCFE1sjwp9XXX39NZGQk3t7elC1blrJly1K6dGkiIyP56quvsiKjyOn+/BBiw43LlfuAZ0NN44jcRynFypUnqFVrIYGB1wGwtNQxdWoL9u4dQOnSLtoGFELkWRm+a8zLy4ujR4+ya9cu0+3zlStXpk2bNpkeTuQCYafhhHF0cQrYG/sGCZEB4eExDBu2jXXrTpvaypRxYfXqrjRsWELDZEKI/CBDhdC6devYsmUL8fHxtG7dmhEjRmRVLpEbKIOxg7TSG9cbjAfH4ppGErlLUFAYL7ywimvXIk1tAwbU4ssv2+HoaKNhMiFEfpHuQmjBggW89dZblC9fHjs7OzZu3MilS5eYPXt2VuYTOdXDO/BrP7i607ju5A0+ozWNJHKfUqUKUaiQLdeuReLiYsuiRS/RvXtVrWMJIfKRdPcR+vrrr5kyZQpBQUEcP36cFStW8M0332RlNpFTXdsLq2rBlR2PGnTQ6iuwstMylciFbG0LsGZNN9q3L88//wyTIkgIke3SPdeYnZ0dZ8+exdvbGzDeRm9nZ8eVK1fw8PDIyoyZSuYaew4GPRycAYEfGi+LAdgXg/bfQynpIyaeTCnFkiVHadq0JFWqyAj0QoiM0Xyusbi4OBwcHEzrFhYWWFtbExMTk2lhRA4WHQLb+8DVXcltJVsbiyAHd+1yiVzhzp1oBg/+hS1bgqhZsxgHDw7GxuaZpzoUQohMk6HfRJMmTcLe3t60Hh8fz/Tp03F2dja1zZkzJ/PSiZzh312wvTc8DDWu6yyg0YfGztEWMsWBeLKAgIsMGLCZkJAoAE6cCGXr1vN061ZF42RCCJGBQqh58+YEBQWZtTVu3Jjg4GDTuk6ny7xkQnsGPQROhb+mAY+uoDp4QIcfwMtX02gi54uNTWTs2J3Mm3fQ1Obqas/SpS/TsWNFDZMJIUSydBdCe/bsycIYIseJugnbesH1vclt3n7w4kqwd9Mul8gVTp4MpVevjZw6ddvU5udXluXLO+PuLqNECyFyDrlIL1K6EmDsDxQTZlzXWUKTaVD/fZk6QzyRwaD46quDfPDBTuLijONL2dhYMmvWCwwfXh8LCzlrLITIWaQQEskMiXBgEhx6bHTogiWMl8JKNNUul8g1Tp4MZfTo3zAYjJdSq1d3Y82ablSrJmcRhRA5k/x5L4wir8G6FuZFUJkO0O+4FEEi3WrWdGf8eOPPy6hRDTl06HUpgoQQOZqcERIQvM04SnTsPeO6RQHjnGE+o+RSmHiihw8TsLUtYHbJa/JkX9q2LUuzZqU0TCaEEOkjn3L5mT4e9rwLm15KLoKcSoH/Pqg7Roog8URHjtykdu1FfP75n2btVlaWUgQJIXKNZ/qk27dvH3369KFRo0bcuHEDgFWrVrF///5MDSeyUMQVWNccjnye3FauM/Q9Bp4NtUolcgG93sCnn+6nYcPvOH/+LhMm/M7Ro7e0jiWEEM8kw4XQTz/9hJ+fH3Z2dhw7doy4uDgAIiIimDFjRqYHFFng0lZYVRtuPRrfxcIKWs6DlzeCrYu22USOdu1aBK1br2Ts2F0kJhqnWalRoxgFC1prnEwIIZ5NhguhadOmsXDhQpYsWYKVlZWpvUmTJhw9ejRTw4ksEHkNfnkF4u4b153LwKt/Qp2RIANiiidYv/40NWosZO/efwHjj8u4cU35889BVKhQRON0QgjxbDLcWTooKIjmzZunaHd2dub+/fuZkUlkpbOrQW88i0eZl4xzhdk4P3kfka9FRsYxcuSvrFhxwtTm5eXEqlVd8PX11i6YEEJkggwXQu7u7ly8eNE0C32S/fv3U6ZMmczKJbKCUnB2VfJ6qy+lCBJPFBQURvv2awgODje1+ftXZeHClyhUyFbDZEIIkTkyfGns9ddf5+233+bgwYPodDpu3rzJ6tWreffddxk2bFhWZBSZ5c4JuHvGuFy8KTiX1jaPyPFKlHCiQAHjrwlHR2tWruzMDz90kyJICJFnZLgQGjt2LL169aJ169ZERUXRvHlzBg8ezJAhQxgxYsQzhZg/fz7e3t7Y2trSoEEDDh06lK791q5di06no3Pnzs/0vPnOme+Tlyv30S6HyDUcHKxZs6YrLVp4c+LEUPr2rSmTKwsh8hSdUko9y47x8fFcvHiRqKgoqlSpQsGCzzaR4rp16+jXrx8LFy6kQYMGzJ07lw0bNhAUFISbW9oj0l65coWmTZtSpkwZChcuzM8//5yu54uMjMTZ2ZmIiAicnJyeKXOuZNDDYi+IvmW8S2xoCNgV1jqVyEGUUqxa9Q9NmnhRtmzhFI9JASSE0FJWfX4/84h51tbWVKlShfr16z9zEQQwZ84cXn/9dQYOHEiVKlVYuHAh9vb2LF26NM199Ho9vXv3ZurUqdIvKb2u/m4sgsA4dYYUQeIx4eEx9Oz5E/37/0zv3htJSNCbPS5FkBAir8pwZ+mWLVs+8Zfi77//nu5jxcfHc+TIEcaNG2dqs7CwoE2bNgQGBqa530cffYSbmxuDBg1i3759T3yOuLg401hHYKwo86WzcllMpG7Pniv07buJ69eN/zcOHrzB1q3n6dKlssbJhBAi62W4EKpVq5bZekJCAsePH+fUqVP0798/Q8cKCwtDr9dTrFgxs/ZixYpx7ty5VPfZv38/3333HcePH0/Xc8ycOZOpU6dmKFeekxANFzYal22cjWeERL4XH69n8uTdzJp1gKQL5C4utixe3FGKICFEvpHhQuiLL75Itf3DDz8kKirquQM9yYMHD+jbty9LlizB1dU1XfuMGzeO0aNHm9YjIyPx8vLKqog508UtkPDovanQHQrIHT/5XVBQGL16bTSbGqNlS29WruxCiRL5qO+cECLfy7TZ5/v06UP9+vX57LPP0r2Pq6srlpaWhIaGmrWHhobi7u6eYvtLly5x5coVOnbsaGozGIzD/BcoUICgoCDKli1rto+NjQ02NjYZeSl5j1wWE48opVi8+AijRgUQE5MIgJWVBdOnt2LMmMZms8gLIUR+kGmFUGBgILa2GTvTYG1tjY+PD7t27TLdAm8wGNi1axfDhw9PsX2lSpU4efKkWdvEiRN58OAB8+bNy39netLj4W24EmBcdvSCEs20zSM0dexYCEOHbjOtV6xYhDVrulGnjoeGqYQQQjsZLoS6du1qtq6U4tatWxw+fJhJkyZlOMDo0aPp378/devWpX79+sydO5fo6GgGDhwIQL9+/ShevDgzZ87E1taWatWqme1fqFAhgBTt4pFz60A9ugOocm/QPfONgiIPqFPHg9GjGzJnzl8MG1aXzz5ri7291dN3FEKIPCrDhZCzs/mUDBYWFlSsWJGPPvqItm3bZjiAv78/d+7cYfLkyYSEhFCrVi127Nhh6kB99epVLCzkw/uZyWWxfC0uLhFra0uzOz1nzGhNu3bleOGFsk/YUwgh8ocMDaio1+s5cOAA1atXx8XFJStzZZl8NaDivfOwrKJxuWgt6HdM0zgie508GUqvXhsZNqwub75ZT+s4QgjxXHLEgIqWlpa0bdtWZpnPLc6uTl6uImeD8guDQTFv3l/Uq7eEU6duM2bMb5w5c0frWEIIkSNl+NJYtWrVCA4OpnRpmbAzR1PqsctiOqj0qqZxRPa4desBAwduJiDgkqmtfHkZRVwIIdKS4c4306ZN491332Xr1q3cunWLyMhIsy+RQ9z6CyKCjcslW0NBT23ziCy3efM5atRYaFYEjRrVkEOHXqdKlaIaJhNCiJwr3WeEPvroI8aMGUP79u0BePnll806YCZNyqjX69M6hMhOj880L5fF8rTo6HjGjPmNRYuOmNo8PAqyfHln2raVDtFCCPEk6e4sbWlpya1btzh79uwTt/P19c2UYFklX3SW1sfDQk+IvQsF7Iwzzdvk0deaz50/f5eOHX/g/Pm7prbOnSuxZElHXF3tNUwmhBCZK6s+v9N9RiipXsrphY7AOIBi7KMPxrKdpAjKw4oVcyA+3ngW1t7einnz2jFoUG2ZLV4IIdIpQ32E5JdrLiGXxfINZ2dbvv++Cw0aFOfYsSEMHlxH/p8KIUQGpPvSmIWFBc7Ozk/9JXvv3r1MCZZV8vylsbgIWOgOibFg5wpDboKljBycV2zYcJqGDUvg5WU+sGlSHz0hhMirNL80BjB16tQUI0uLHObCRmMRBFCxpxRBeURkZBwjR/7KihUnaNHCm507+2JpmXxCV4ogIYR4NhkqhHr27Imbm1tWZRGZ4axcFstrAgOv0afPJoKDwwHYs+cKW7eep1OnShonE0KI3C/dfYTkL85c4MF1uLrbuFyoHLjX1zaPeC6JiQamTt1Ds2bLTEWQo6M1K1d25uWXK2qcTggh8oYM3zUmcrBzPwCP3qfKfUCK11wrODicPn02Ehh43dTWuLEX33/fhdKlc+c8f0IIkROluxAyGAxZmUNkBrOZ5ntrl0M8M6UUq1b9w/Dh23nwIB4AS0sdkyf7Mn58MwoUyPBg8EIIIZ4gw3ONiRzqzj/GLwCPhuBSTts84pkcPnyT/v1/Nq2XKePC6tVdadiwhHahhBAiD5M/L/OKx2earyydpHOrevWKM2SIDwADBtTi+PEhUgQJIUQWkjNCeYEyJBdCFgWgYg9t84h0S0jQU6CAhdnNCJ9/3pb27ctLh2ghhMgGckYoL7i2F6JuGJe924G9zDSeGwQFhdGw4XesWHHCrN3BwVqKICGEyCZSCOUFZp2k5bJYTqeUYtGiw9SuvYijR28xYsSvXLyYs0dkF0KIvEoujeV2CTFw/kfjsrUjlO2obR7xRHfuRDN48C9s2RJkaite3JGYmAQNUwkhRP4lhVBuF7wV4iONy+W7gZW9tnlEmgICLjJgwGZCQqJMbUOH+vD5537Y28tUKEIIoQUphHI7uSyW48XGJjJu3E7mzj1oanN1tWfp0pfp2FH6AgkhhJakEMrNHobB5e3G5YKe4NVC0zgipYsX79G16zpOnrxtamvXrhzLlnXC3b2ghsmEEEKAFEK52/kNYEg0LlfqBRaW2uYRKbi42HL3bgwANjaWzJ79AsOH15e5+4QQIoeQu8ZyM7ksluMVKWLP8uWdqFmzGIcPv8GIEQ2kCBJCiBxEzgjlVveD4eafxmXXalC0hrZ5BAC//BJEvXrFzS57vfBCWY4cKY2lpfzdIYQQOY38Zs6t/julhpxl0FR0dDxDh27l5ZfX8tprm1FKmT0uRZAQQuRM8ts5N1LK/LJYpV7aZREcOXKTOnUWs2jREQB+/fUiW7ee1ziVEEKI9JBCKDcKPQzhjz5ovVqAk5emcfIrvd7Ap5/up2HD7zh//i4A9vZWLFnSkZdeqqBxOiGEEOkhfYRyozPSSVpr165F0LfvJvbu/dfU5uPjwZo13ahQoYiGyYQQQmSEFEK5jT4Bzv1gXLa0MY4mLbLVunWnGDp0G/fvxwLG7lljxzblww9bYG0tQxgIIURuIoVQbnN1J8TcMS6X7Qi2hTSNk9/89dd1evb8ybTu5eXEqlVd8PX11i6UEEKIZyZ9hHIbuSymqYYNS9C3r3GoAn//qpw4MVSKICGEyMXkjFBuEv8ALm4yLtsWhtIvapsnHzAYFBYW5kMTfP11ezp0KE+PHlVlcEQhhMjl5IxQbnLxZ0g0TtdAxR5gaa1pnLwuODicpk2Xsn79abN2Jycb/P2rSREkhBB5gJwRyk1OL09elstiWUYpxapV/zB8+HYePIjn7NmtNGpUAi8vZ62jCSGEyGRyRii3uLobrv5uXHYuA56Ntc2TR4WHx9Cz50/07/8zDx7EA1C4sJ1p4lQhhBB5i5wRyg2UAf54P3m90RSZUiML7Nlzhb59N3H9eqSpbcCAWnz5ZTscHW00TCaEECKrSCGUGwStN44mDVC0JlTurW2ePCY+Xs/kybuZNesASVOEFSpky+LFL9G9e1VtwwkhhMhSUgjldIlxsH988nrzT8FCBu3LLMHB4XTvvoGjR2+Z2lq08Gblys7SJ0gIIfIB6SOU0/2zECIuG5dLtoFSbbXNk8fY2RXg6tUIAKysLJg1qw27dvWTIkgIIfIJKYRysrgICPw4eb35p9I3KJN5eDjy3XcvU6mSK3/9NZj33muSYtwgIYQQeZdcGsvJDn0KscZZzancG4rV0TZPHrBzZzC1a7tTpIi9qe3llyvy4ovlsLKSS45CCJHfyBmhnOrBdTj6hXHZ0hqaTNM2Ty4XG5vIqFE7eOGFVQwZshWV1Cv6ESmChBAif5JCKKf6cwokGmc3p9ZwcPbWNE5udvJkKPXrL2Hu3IMA/PTTWXbsuKhxKiGEEDmBFEI50Z2TyaNI2xSCBhO0TJNrGQyKefP+ol69JZw8eRsAGxtLvvyyHe3aldM4nRBCiJxA+gjlRPvGGgdRBKg/DuwKa5snF7p16wEDB24mIOCSqa16dTfWrOlGtWpuGiYTQgiRk0ghlNNc3Q2XtxuXHb2g9ght8+RCW7YEMWjQFsLCHpraRo1qyIwZrbG1lR95IYQQyeRTISf571QaTT4GKzvt8uRCBw5cpVOntaZ1d/eCrFjRmbZty2qYSgghRE4lfYRykqANj02lUUNmmH8GjRt70aVLJQA6darIyZPDpAgSQgiRJjkjlFMkxsH+ccnrzWQqjfRQSqF7bJBJnU7HkiUdefnlivTvX9PsMSGEEOK/5IxQTmE2lUZr8PbTNk8ucO1aBK1arWTr1vNm7UWK2DNgQC0pgoQQQjyVnBHKCWQqjQxbv/40Q4Zs5f79WE6fvs0//wzD3b2g1rGEEELkMnJGKCd4fCqNSr2gmI+2eXKwyMg4Bgz4GX//H7l/3zjgpK1tAW7efKBxMiGEELmRnBHS2n+n0mgqU2mkJTDwGr17b+Ty5fumNn//qixY0AEXF7m7TgghRMZJIaQ1s6k03gLn0trmyYESEw1Mm/YH06b9gV5vnCPM0dGa+fPb06dPDekLJIQQ4plJIaSlsFOPTaXhLFNppOLKlfv06vUTgYHXTW2NG3vx/fddKF3aRcNkQggh8gLpI6SlFFNpFNE2Tw5kYaHjzJk7AFha6pg6tQV79w6QIkgIIUSmkEJIK9f2QPA243LBElB7pJZpcqySJZ1ZuPAlypRxYf/+15g82ZcCBeTHVgghROaQTxQtKAPsfS95XabSMNm3718iI+PM2nr2rMbp02/SsGEJjVIJIYTIq3JEITR//ny8vb2xtbWlQYMGHDp0KM1tlyxZQrNmzXBxccHFxYU2bdo8cfsc6fGpNFyrQ5W+2ubJAeLj9YwduxNf3+WMGPFrisdlslQhhBBZQfNCaN26dYwePZopU6Zw9OhRatasiZ+fH7dv3051+z179vDqq6+ye/duAgMD8fLyom3btty4cSObkz8jfTzsH5+83lym0ggKCqNRo+/49NMDKAUrV57gt98uaR1LCCFEPqBTSiktAzRo0IB69erx9ddfA2AwGPDy8mLEiBGMHTv2qfvr9XpcXFz4+uuv6dev31O3j4yMxNnZmYiICJycnJ47f4Yd/RJ2v21cLtkKXtmZb0eRVkqxePERRo0KICYmEQArKwumT2/FmDGNsbDIn98XIYQQKWXV57em1xvi4+M5cuQI48YlTzZqYWFBmzZtCAwMTNcxHj58SEJCAoULF0718bi4OOLikvucREZGPl/o5xEbDoEfJa83n5Vvi6A7d6IZPPgXtmwJMrVVrFiENWu6UaeOh4bJhBBC5CeaXhoLCwtDr9dTrFgxs/ZixYoREhKSrmN88MEHeHp60qZNm1QfnzlzJs7OzqYvLy+v5879zHa//dhUGq/m26k0AgIuUqPGQrMiaNiwuhw9OkSKICGEENlK8z5Cz+OTTz5h7dq1bNq0CVtb21S3GTduHBEREaava9euZXPKRy5ugTOrjMs2zsazQfnQvn3/0q7dakJCogBwdbVny5aefPNNB+ztrTROJ4QQIr/R9NKYq6srlpaWhIaGmrWHhobi7u7+xH0/++wzPvnkE3bu3EmNGjXS3M7GxgYbG5tMyfvMYu7CziHJ6y3mgmP+vBW8adOStGtXjh07LtKuXTmWLesks8YLIYTQjKZnhKytrfHx8WHXrl2mNoPBwK5du2jUqFGa+82aNYuPP/6YHTt2ULdu3eyI+nx+HwnRjy71lekAVftrm0dDOp2OZcs68c037dm+vZcUQUIIITSl+aWx0aNHs2TJElasWMHZs2cZNmwY0dHRDBw4EIB+/fqZdab+9NNPmTRpEkuXLsXb25uQkBBCQkKIiorS6iU82YWNcG6NcdmmELywON90kA4JiaJDhzXs2hVs1u7uXpBhw+rJZKlCCCE0p/kodf7+/ty5c4fJkycTEhJCrVq12LFjh6kD9dWrV7GwSK7XFixYQHx8PK+88orZcaZMmcKHH36YndGf7uEd+N/Q5PVWX0FBT+3yZKMtW4IYNGgLYWEPOXEihBMnhlKkiL3WsYQQQggzmo8jlN2ydRyhX/zh/HrjctmXodPPef5sUHR0PGPG/MaiRUdMbR4eBfnll1fx8ckfRaAQQojMlyfHEcrTgjYkF0G2heGFRXm+CDpy5Ca9e28kKOiuqa1z50osWdIRV1c5GySEECLnkUIoKzy8DbveTF5v9TU4PPkuuNxMrzfw2Wd/MnHibhITDQDY21sxb147Bg2qLX2BhBBC5FhSCGU2pWDnmxATZlwv3xUq9dQ2Uxa6fj2Svn03sWfPFVObj48Ha9Z0o0KFItoFE0IIIdJB87vG8pygdXDhJ+OybRFo/U2eviQWE5PA338bJ7zV6WDcuKb8+ecgKYKEEELkClIIZaboENj1VvJ6m2/AoVja2+cB5csX4csvX8TLy4ndu/szY0ZrrK0ttY4lhBBCpIsUQplFKeOt8rH3jOsVukPFHtpmygKHDt3g4cMEs7aBA2tx5sxb+Pp6axNKCCGEeEZSCGWWY1/Dpc3GZbui0Hq+tnkyWWKigalT99C48Xe8++5vZo/pdDoKFrTWKJkQQgjx7KQQel7KAHvfh90jk9vaLAD7otplymTBweE0b76MDz/ci16vWLDgMLt3X9Y6lhBCCPHc5K6x55EQDdv7wMWfk9vqvgcVumkWKTMppVi16h+GD9/OgwfxAFha6pg82ZdmzUppnE4IIYR4flIIPauom/DzyxD6aARlnaVxCo1aw7TNlUnCw2MYNmwb69adNrWVKePC6tVdadiwhIbJhBBCiMwjhdCzuH0CNr0EUdeN69aO8NJ6KN1O21yZZO/eK/Ttu4lr1yJNbQMG1OLLL9vh6GijYTIhhBAic0khlFHB22BrT0h4NNu9Y0noug1cq2mbK5Ps3XuFli1XkDQDnYuLLYsWvUT37lW1DSaEEEJkAeksnRFHvzReDksqgtzrQ++DeaYIAmjatCTNmxv7/7Rs6c0//wyTIkgIIUSeJWeE0ivwY/hzcvJ6he7QbgVY2WmXKQtYWlqwalUXNmw4wzvvNMTCIu+Oii2EEELIGaH0SIiGg9OT1xuMh5fW5voi6M6daLp1W8+BA1fN2r28nBk9upEUQUIIIfI8OSOUHtf2gj7OuFx1ADSd/sTNc4OAgIsMGLCZkJAojh69xYkTQ3Fyko7QQggh8hc5I5QeV3YkL5d9WbscmSA2NpF33tlBu3arCQkx9nWKiorn/Pm7GicTQgghsp+cEUqPKwHGfy0KQMlW2mZ5DidPhtKr10ZOnbptamvXrhzLlnXC3b2ghsmEEEIIbUgh9DT3gyH8vHHZszHYOGub5xkYDIqvvjrIBx/sJC5OD4CNjSWzZ7/A8OH10emkL5AQQoj8SQqhp0k6GwTg7addjmd069YDBg7cTEDAJVNb9epurFnTjWrV3DRMJoQQQmhP+gg9jVkhlPtGjr53L4Y9e66Y1keNasihQ69LESSEEEIghdCT6ePh6i7jsl1RcKulaZxnUbWqG7Nnv4C7e0ECAvowZ44ftrZyIlAIIYQAKYSe7GZg8ijS3n6gy/nfrhMnQoiLSzRrGz68PmfOvEnbtmU1SiWEEELkTDn/k11Lj982n8P7B+n1Bj79dD916y5hwoTfzR7T6XS4uOTuwR+FEEKIrCCF0JOY9Q9qq12Op7h2LYLWrVcyduwuEhMNfP55IPv3X336jkIIIUQ+J51F0hIdArePGZfd6oB9zuxcvH79aYYM2cr9+7EA6HQwdmxT6tcvrnEyIYQQIueTQigtV35LXi6d8+4Wi4yMY+TIX1mx4oSpzcvLiVWruuDr661dMCGEECIXkUIoLTn4tvnAwGv06bOJ4OBwU5u/f1UWLOggfYGEEEKIDJBCKDXKAP8+OiNk7QgeDbXN85g9e67Qps1K9HoFgKOjNfPnt6dPnxoyQrQQQgiRQdJZOjWhRyEmzLhcsg1YWmmb5zFNmnjh4+MJQOPGXpw4MZS+fWtKESSEEEI8AzkjlJocfNu8lZUlq1d3Zd26U3zwQVMKFJBaVgghhHhWUgilJofMLxYeHsPw4b8yenRD01kggHLlCjNhQnPNcgmR3yilSExMRK/Xax1FiDzNysoKS0vLbH1OKYT+K/a+cURpAJeK4OytSYw9e67Qt+8mrl+P5MiRmxw9OgR7+5xziU6I/CI+Pp5bt27x8OFDraMIkefpdDpKlChBwYIFs+05pRD6r6u7QD36q0+D2+bj4/VMnrybWbMOoIz9obl9O5rTp29Tr56MDSREdjIYDFy+fBlLS0s8PT2xtraW/nhCZBGlFHfu3OH69euUL18+284MSSGUZN94CP4FokOT27L5slhQUBi9em3k6NFbpraWLb1ZubILJUo4ZWsWIYTxbJDBYMDLywt7e3ut4wiR5xUtWpQrV66QkJAghVC2Cj0Kh2aat1naQAnfbHl6pRSLFx9h1KgAYmKME6ZaWVkwfXorxoxpjIWF/AUqhJYsLOSmBCGygxZnXKUQguSpNMBYAFk7QcMJYJX1fwHeuRPN4MG/sGVLkKmtYsUirFnTjTp1PLL8+YUQQoj8TAohgLunk5e7bIVSbbLtqa9di2T79gum9WHD6vLZZ22lY7QQQgiRDeR8L0DYY4VQkarZ+tR16ngwbVpLXF3t2bKlJ99800GKICGE0FBQUBDu7u48ePBA6yh5SlhYGG5ubly/fl3rKGakEILkM0K2LuDgnqVPde5cGAkJ5mORvPtuY06ffpOOHStm6XMLIfKPAQMGoNPp0Ol0WFlZUbp0ad5//31iY2NTbLt161Z8fX1xdHTE3t6eevXqsXz58lSP+9NPP9GiRQucnZ0pWLAgNWrU4KOPPuLevXtZ/Iqyz7hx4xgxYgSOjo5aR8ky8+fPx9vbG1tbWxo0aMChQ4eeuH2LFi1MP0+Pf3Xo0MG0zeM/c0lf7dol333t6upKv379mDJlSpa9rmchhVDsfYi6YVwuUhWyqKOWwaCYN+8vatVayLRpf5g9ZmlpgZubQ5Y8rxAi/2rXrh23bt0iODiYL774gkWLFqX4EPrqq6/o1KkTTZo04eDBg/zzzz/07NmToUOH8u6775ptO2HCBPz9/alXrx6//vorp06d4vPPP+fEiROsWrUq215XfHx8lh376tWrbN26lQEDBjzXcbIy4/Nat24do0ePZsqUKRw9epSaNWvi5+fH7du309xn48aN3Lp1y/R16tQpLC0t6d69u9l2ST9zSV8//PCD2eMDBw5k9erVOatwVvlMRESEAlRERISx4foBpT7D+PXbG1nynDdvRio/v1UKPlTwobKwmKoOHryeJc8lhMg8MTEx6syZMyomJkbrKBnWv39/1alTJ7O2rl27qtq1a5vWr169qqysrNTo0aNT7P/ll18qQP31119KKaUOHjyoADV37txUny88PDzNLNeuXVM9e/ZULi4uyt7eXvn4+JiOm1rOt99+W/n6+prWfX191VtvvaXefvttVaRIEdWiRQv16quvqh49epjtFx8fr4oUKaJWrFihlFJKr9erGTNmKG9vb2Vra6tq1KihNmzYkGZOpZSaPXu2qlu3rllbWFiY6tmzp/L09FR2dnaqWrVqas2aNWbbpJZRKaVOnjyp2rVrpxwcHJSbm5vq06ePunPnjmm/X3/9VTVp0kQ5OzurwoULqw4dOqiLFy8+MePzql+/vnrrrbdM63q9Xnl6eqqZM2em+xhffPGFcnR0VFFRUaa21N7L1JQuXVp9++23qT72pP9zKT6/M4l0lr6btf2DNm8+x+DBvxAWljwq7ciR9alRo1imP5cQIpt8XxeiQ7L/eR3coc/hZ9r11KlT/Pnnn5QqVcrU9uOPP5KQkJDizA/AkCFDGD9+PD/88AMNGjRg9erVFCxYkDfffDPV4xcqVCjV9qioKHx9fSlevDhbtmzB3d2do0ePYjAYMpR/xYoVDBs2jAMHDgBw8eJFunfvTlRUlGkU4oCAAB4+fEiXLl0AmDlzJt9//z0LFy6kfPny/PHHH/Tp04eiRYvi65v68Cj79u2jbt26Zm2xsbH4+PjwwQcf4OTkxLZt2+jbty9ly5alfv36aWa8f/8+rVq1YvDgwXzxxRfExMTwwQcf0KNHD37//XcAoqOjGT16NDVq1CAqKorJkyfTpUsXjh8/nuawDTNmzGDGjBlP/H6dOXOGkiVLpmiPj4/nyJEjjBs3ztRmYWFBmzZtCAwMfOIxH/fdd9/Rs2dPHBzMr2bs2bMHNzc3XFxcaNWqFdOmTaNIkSJm29SvX599+/YxaNCgdD9fVpJCKIsKoejoeMaM+Y1Fi46Y2tzdC7JiRWfati2bac8jhNBAdEjyJfUcbOvWrRQsWJDExETi4uKwsLDg66+/Nj1+/vx5nJ2d8fBIOVSHtbU1ZcqU4fz58wBcuHCBMmXKYGWVsZs51qxZw507d/j7778pXLgwAOXKlcvwaylfvjyzZs0yrZctWxYHBwc2bdpE3759Tc/18ssv4+joSFxcHDNmzGDnzp00atQIgDJlyrB//34WLVqUZiH077//piiEihcvblYsjhgxgoCAANavX29WCP0347Rp06hdu7ZZ0bJ06VK8vLw4f/48FSpUoFu3bmbPtXTpUooWLcqZM2eoVq1aqhmHDh1Kjx49nvj98vT0TLU9LCwMvV5PsWLmf4wXK1aMc+fOPfGYSQ4dOsSpU6f47rvvzNrbtWtH165dKV26NJcuXWL8+PG8+OKLBAYGmg2O6OnpybFjx/57WM1IIfT4HWOumVMIHTlyk169NnL+/F1TW6dOFfn225dxdZXRaYXI9bL4porMet6WLVuyYMECoqOj+eKLLyhQoECKD970Uklz/mTQ8ePHqV27tqkIelY+Pj5m6wUKFKBHjx6sXr2avn37Eh0dzebNm1m7di1gPGP08OFDXnjhBbP94uPjqV27dprPExMTg62trVmbXq9nxowZrF+/nhs3bhAfH09cXFyK0cb/m/HEiRPs3r071XmzLl26RIUKFbhw4QKTJ0/m4MGDhIWFmc6UXb16Nc1CqHDhws/9/Xwe3333HdWrVzcrAgF69uxpWq5evTo1atSgbNmy7Nmzh9atW5ses7Ozy1Fz90khZLpjrDDYP//lqt9/v4yf3/ckJhp/mO3trZg714/Bg+vIHEVC5BXPeHkquzk4OJjOvixdupSaNWvy3XffmS5JVKhQgYiICG7evJniDEJ8fDyXLl2iZcuWpm33799PQkJChs4K2dnZPfFxCwuLFEVWQkJCqq/lv3r37o2vry+3b9/mf//7H3Z2dqa7lKKiogDYtm0bxYubz9NoY2OTZh5XV1fCw8PN2mbPns28efOYO3cu1atXx8HBgXfeeSdFh+j/ZoyKiqJjx458+umnKZ4n6Sxcx44dKVWqFEuWLMHT0xODwUC1atWe2Nn6eS6Nubq6YmlpSWhoqFl7aGgo7u5PL7Sjo6NZu3YtH3300VO3LVOmDK6urly8eNGsELp37x5FixZ96v7ZJX/fNRYbDtGP5vXKpDvGmjTxokoV4xvs4+PBsWNDeP11HymChBCasrCwYPz48UycOJGYmBgAunXrhpWVFZ9//nmK7RcuXEh0dDSvvvoqAL169SIqKopvvvkm1ePfv38/1fYaNWpw/PjxNO8SKlq0KLdu3TJrO378eLpeU+PGjfHy8mLdunWsXr2a7t27m4q0KlWqYGNjw9WrVylXrpzZl5eXV5rHrF27NmfOnDFrO3DgAJ06daJPnz7UrFnT7JLhk9SpU4fTp0/j7e2dIoODgwN3794lKCiIiRMn0rp1aypXrpyiCEvN0KFDOX78+BO/0ro0Zm1tjY+PD7t27TK1GQwGdu3aZbqE+CQbNmwgLi6OPn36PHXb69evc/fu3RSXXk+dOvXEs3LZLlO7XucCZr3Or+1LvmPsf0Mz7TlOnQpVEybsUnFxiZl2TCFE9strd40lJCSo4sWLq9mzZ5vavvjiC2VhYaHGjx+vzp49qy5evKg+//xzZWNjo8aMGWO2//vvv68sLS3Ve++9p/7880915coVtXPnTvXKK6+keTdZXFycqlChgmrWrJnav3+/unTpkvrxxx/Vn3/+qZRSaseOHUqn06kVK1ao8+fPq8mTJysnJ6cUd429/fbbqR5/woQJqkqVKqpAgQJq3759KR4rUqSIWr58ubp48aI6cuSI+vLLL9Xy5cvT/L5t2bJFubm5qcTE5N/fo0aNUl5eXurAgQPqzJkzavDgwcrJycns+5taxhs3bqiiRYuqV155RR06dEhdvHhR7dixQw0YMEAlJiYqvV6vihQpovr06aMuXLigdu3aperVq6cAtWnTpjQzPq+1a9cqGxsbtXz5cnXmzBn1xhtvqEKFCqmQkBDTNn379lVjx45NsW/Tpk2Vv79/ivYHDx6od999VwUGBqrLly+rnTt3qjp16qjy5cur2NhY03bR0dHKzs5O/fHHH6lm0+KusfxbCK16QallVZILoaNfPcOxYtXgwZvVqVOhWZBUCKG1vFYIKaXUzJkzVdGiRc1ue968ebNq1qyZcnBwULa2tsrHx0ctXbo01eOuW7dONW/eXDk6OioHBwdVo0YN9dFHHz3x9vkrV66obt26KScnJ2Vvb6/q1q2rDh48aHp88uTJqlixYsrZ2VmNGjVKDR8+PN2F0JkzZxSgSpUqpQwGg9ljBoNBzZ07V1WsWFFZWVmpokWLKj8/P7V37940syYkJChPT0+1Y8cOU9vdu3dVp06dVMGCBZWbm5uaOHGi6tev31MLIaWUOn/+vOrSpYsqVKiQsrOzU5UqVVLvvPOOKev//vc/VblyZWVjY6Nq1Kih9uzZk+WFkFJKffXVV6pkyZLK2tpa1a9f3zScweOvp3///mZt586dU4D67bffUhzv4cOHqm3btqpo0aLKyspKlSpVSr3++utmxZVSSq1Zs0ZVrFgxzVxaFEI6pZ6xB1wuFRkZibOzMxHTwOnx/nA9doNXi3QfJzDwGn36bCI4OJwaNYpx6NBgbGyky5UQeUlsbCyXL1+mdOnSKTrQirxr/vz5bNmyhYCAAK2j5DkNGzZk5MiR9OrVK9XHn/R/zvT5HRGBk5NTpmXK332EkpR6AYo3TdemiYkGpk7dQ7NmywgONl7LvXw5nH/+CX3KnkIIIXKDIUOG0Lx5c5lrLJOFhYXRtWtXU7+znCJ/n8IoVA76n4ICad9B8Ljg4HD69NlIYGDyhHGNG3vx/fddKF3aJatSCiGEyEYFChRgwoQJWsfIc1xdXXn//fe1jpFC/i6EdBbpKoKUUqxa9Q/Dh2/nwQPjLY2WljomT/Zl/PhmFCggJ9aEEEKI3Ch/F0LpEB4ew7Bh21i3LnngxTJlXFi9uisNG5bQMJkQQgghnpcUQk9x9mwYGzYkjykxYEAtvvyyHY6O6bucJoTI/fLZPSVCaEaL/2tyTecpGjf2YsKEZhQqZMv69a+wbFknKYKEyCeSBufLSdMBCJGXJY2o/fjcZFlNzgj9x+XL4ZQs6YylZXKNOGlSc4YM8aF48cy7XU8IkfNZWlpSqFAhbt++DYC9vb2MEi9EFjEYDNy5cwd7e3sKFMi+8kQKoUeUUixefIRRowKYMsWXDz5Ivp3eyspSiiAh8qmk+ZeSiiEhRNaxsLCgZMmS2foHhxRCwJ070Qwe/AtbtgQBMHHibtq2LUvt2h5P2VMIkdfpdDo8PDxwc3NLdTJQIUTmsba2xsIie3vt5IhCaP78+cyePZuQkBBq1qzJV199Rf369dPcfsOGDUyaNIkrV65Qvnx5Pv30U9q3b/9Mzx0QcJEBAzYTEhJlahs8uDYVK7o+0/GEEHmTpaVltvZbEEJkD807S69bt47Ro0czZcoUjh49Ss2aNfHz80vzNPSff/7Jq6++yqBBgzh27BidO3emc+fOnDp1KkPPG5tgyTs/1KFdu9WmIsjV1Z4tW3qyYMFL2NtbPfdrE0IIIUTOpvlcYw0aNKBevXp8/fXXgLGzlJeXFyNGjGDs2LEptvf39yc6OpqtW7ea2ho2bEitWrVYuHDhU58vaa6Sym6DOHvby9Terl05li3rhLt7wUx4VUIIIYTITHlyrrH4+HiOHDlCmzZtTG0WFha0adOGwMDAVPcJDAw02x7Az88vze3TcvZ2UQBsbCz58st2bN/eS4ogIYQQIp/RtI9QWFgYer2eYsWKmbUXK1aMc+fOpbpPSEhIqtuHhISkun1cXBxxcXGm9YiIiKRHqOIZwXc/jaFKlaIyuZ4QQgiRg0VGRgKZP+hijugsnZVmzpzJ1KlTU3nkC87chEaNFmR7JiGEEEI8m7t37+Ls7Jxpx9O0EHJ1dcXS0pLQ0FCz9tDQUNPYHf/l7u6eoe3HjRvH6NGjTev379+nVKlSXL16NVO/kSLjIiMj8fLy4tq1a5l6vVc8G3k/cg55L3IOeS9yjoiICEqWLEnhwoUz9biaFkLW1tb4+Piwa9cuOnfuDBg7S+/atYvhw4enuk+jRo3YtWsX77zzjqntf//7H40aNUp1exsbG2xsUk6J4ezsLD/UOYSTk5O8FzmIvB85h7wXOYe8FzlHZo8zpPmlsdGjR9O/f3/q1q1L/fr1mTt3LtHR0QwcOBCAfv36Ubx4cWbOnAnA22+/ja+vL59//jkdOnRg7dq1HD58mMWLF2v5MoQQQgiRC2leCPn7+3Pnzh0mT55MSEgItWrVYseOHaYO0VevXjWr/ho3bsyaNWuYOHEi48ePp3z58vz8889Uq1ZNq5cghBBCiFxK80IIYPjw4WleCtuzZ0+Ktu7du9O9e/dnei4bGxumTJmS6uUykb3kvchZ5P3IOeS9yDnkvcg5suq90HxARSGEEEIIrWg+xYYQQgghhFakEBJCCCFEviWFkBBCCCHyLSmEhBBCCJFv5clCaP78+Xh7e2Nra0uDBg04dOjQE7ffsGEDlSpVwtbWlurVq7N9+/ZsSpr3ZeS9WLJkCc2aNcPFxQUXFxfatGnz1PdOZExG/28kWbt2LTqdzjTwqXh+GX0v7t+/z1tvvYWHhwc2NjZUqFBBfldlkoy+F3PnzqVixYrY2dnh5eXFqFGjiI2Nzaa0edcff/xBx44d8fT0RKfT8fPPPz91nz179lCnTh1sbGwoV64cy5cvz/gTqzxm7dq1ytraWi1dulSdPn1avf7666pQoUIqNDQ01e0PHDigLC0t1axZs9SZM2fUxIkTlZWVlTp58mQ2J897Mvpe9OrVS82fP18dO3ZMnT17Vg0YMEA5Ozur69evZ3PyvCmj70eSy5cvq+LFi6tmzZqpTp06ZU/YPC6j70VcXJyqW7euat++vdq/f7+6fPmy2rNnjzp+/Hg2J897MvperF69WtnY2KjVq1ery5cvq4CAAOXh4aFGjRqVzcnznu3bt6sJEyaojRs3KkBt2rTpidsHBwcre3t7NXr0aHXmzBn11VdfKUtLS7Vjx44MPW+eK4Tq16+v3nrrLdO6Xq9Xnp6eaubMmalu36NHD9WhQweztgYNGqghQ4Zkac78IKPvxX8lJiYqR0dHtWLFiqyKmK88y/uRmJioGjdurL799lvVv39/KYQySUbfiwULFqgyZcqo+Pj47IqYb2T0vXjrrbdUq1atzNpGjx6tmjRpkqU585v0FELvv/++qlq1qlmbv7+/8vPzy9Bz5alLY/Hx8Rw5coQ2bdqY2iwsLGjTpg2BgYGp7hMYGGi2PYCfn1+a24v0eZb34r8ePnxIQkJCpk+wlx896/vx0Ucf4ebmxqBBg7IjZr7wLO/Fli1baNSoEW+99RbFihWjWrVqzJgxA71en12x86RneS8aN27MkSNHTJfPgoOD2b59O+3bt8+WzCJZZn1+54iRpTNLWFgYer3eND1HkmLFinHu3LlU9wkJCUl1+5CQkCzLmR88y3vxXx988AGenp4pftBFxj3L+7F//36+++47jh8/ng0J849neS+Cg4P5/fff6d27N9u3b+fixYu8+eabJCQkMGXKlOyInSc9y3vRq1cvwsLCaNq0KUopEhMTGTp0KOPHj8+OyOIxaX1+R0ZGEhMTg52dXbqOk6fOCIm845NPPmHt2rVs2rQJW1tbrePkOw8ePKBv374sWbIEV1dXrePkewaDATc3NxYvXoyPjw/+/v5MmDCBhQsXah0t39mzZw8zZszgm2++4ejRo2zcuJFt27bx8ccfax1NPKM8dUbI1dUVS0tLQkNDzdpDQ0Nxd3dPdR93d/cMbS/S51neiySfffYZn3zyCTt37qRGjRpZGTPfyOj7cenSJa5cuULHjh1NbQaDAYACBQoQFBRE2bJlszZ0HvUs/zc8PDywsrLC0tLS1Fa5cmVCQkKIj4/H2to6SzPnVc/yXkyaNIm+ffsyePBgAKpXr050dDRvvPEGEyZMMJskXGSttD6/nZyc0n02CPLYGSFra2t8fHzYtWuXqc1gMLBr1y4aNWqU6j6NGjUy2x7gf//7X5rbi/R5lvcCYNasWXz88cfs2LGDunXrZkfUfCGj70elSpU4efIkx48fN329/PLLtGzZkuPHj+Pl5ZWd8fOUZ/m/0aRJEy5evGgqRgHOnz+Ph4eHFEHP4Vnei4cPH6YodpIKVCVTd2arTPv8zlg/7pxv7dq1ysbGRi1fvlydOXNGvfHGG6pQoUIqJCREKaVU37591dixY03bHzhwQBUoUEB99tln6uzZs2rKlCly+3wmyeh78cknnyhra2v1448/qlu3bpm+Hjx4oNVLyFMy+n78l9w1lnky+l5cvXpVOTo6quHDh6ugoCC1detW5ebmpqZNm6bVS8gzMvpeTJkyRTk6OqoffvhBBQcHq99++02VLVtW9ejRQ6uXkGc8ePBAHTt2TB07dkwBas6cOerYsWPq33//VUopNXbsWNW3b1/T9km3z7/33nvq7Nmzav78+XL7fJKvvvpKlSxZUllbW6v69eurv/76y/SYr6+v6t+/v9n269evVxUqVFDW1taqatWqatu2bdmcOO/KyHtRqlQpBaT4mjJlSvYHz6My+n/jcVIIZa6Mvhd//vmnatCggbKxsVFlypRR06dPV4mJidmcOm/KyHuRkJCgPvzwQ1W2bFlla2urvLy81JtvvqnCw8OzP3ges3v37lQ/A5K+//3791e+vr4p9qlVq5aytrZWZcqUUcuWLcvw8+qUknN5QgghhMif8lQfISGEEEKIjJBCSAghhBD5lhRCQgghhMi3pBASQgghRL4lhZAQQggh8i0phIQQQgiRb0khJIQQQoh8SwohIYSZ5cuXU6hQIa1jPDOdTsfPP//8xG0GDBhA586dsyWPECJnk0JIiDxowIAB6HS6FF8XL17UOhrLly835bGwsKBEiRIMHDiQ27dvZ8rxb926xYsvvgjAlStX0Ol0HD9+3GybefPmsXz58kx5vrR8+OGHptdpaWmJl5cXb7zxBvfu3cvQcaRoEyJr5anZ54UQydq1a8eyZcvM2ooWLapRGnNOTk4EBQVhMBg4ceIEAwcO5ObNmwQEBDz3sdOaNfxxzs7Oz/086VG1alV27tyJXq/n7NmzvPbaa0RERLBu3bpseX4hxNPJGSEh8igbGxvc3d3NviwtLZkzZw7Vq1fHwcEBLy8v3nzzTaKiotI8zokTJ2jZsiWOjo44OTnh4+PD4cOHTY/v37+fZs2aYWdnh5eXFyNHjiQ6OvqJ2XQ6He7u7nh6evLiiy8ycuRIdu7cSUxMDAaDgY8++ogSJUpgY2NDrVq12LFjh2nf+Ph4hg8fjoeHB7a2tpQqVYqZM2eaHTvp0ljp0qUBqF27NjqdjhYtWgDmZ1kWL16Mp6en2czuAJ06deK1114zrW/evJk6depga2tLmTJlmDp1KomJiU98nQUKFMDd3Z3ixYvTpk0bunfvzv/+9z/T43q9nkGDBlG6dGns7OyoWLEi8+bNMz3+4YcfsmLFCjZv3mw6u7Rnzx4Arl27Ro8ePShUqBCFCxemU6dOXLly5Yl5hBApSSEkRD5jYWHBl19+yenTp1mxYgW///4777//fprb9+7dmxIlSvD3339z5MgRxo4di5WVFQCXLl2iXbt2dOvWjX/++Yd169axf/9+hg8fnqFMdnZ2GAwGEhMTmTdvHp9//jmfffYZ//zzD35+frz88stcuHABgC+//JItW7awfv16goKCWL16Nd7e3qke99ChQwDs3LmTW7dusXHjxhTbdO/enbt377J7925T271799ixYwe9e/cGYN++ffTr14+3336bM2fOsGjRIpYvX8706dPT/RqvXLlCQEAA1tbWpjaDwUCJEiXYsGEDZ86cYfLkyYwfP57169cD8O6779KjRw/atWvHrVu3uHXrFo0bNyYhIQE/Pz8cHR3Zt28fBw4coGDBgrRr1474+Ph0ZxJCQJ6cfV6I/K5///7K0tJSOTg4mL5eeeWVVLfdsGGDKlKkiGl92bJlytnZ2bTu6Oioli9fnuq+gwYNUm+88YZZ2759+5SFhYWKiYlJdZ//Hv/8+fOqQoUKqm7dukoppTw9PdX06dPN9qlXr5568803lVJKjRgxQrVq1UoZDIZUjw+oTZs2KaWUunz5sgLUsWPHzLbp37+/6tSpk2m9U6dO6rXXXjOtL1q0SHl6eiq9Xq+UUqp169ZqxowZZsdYtWqV8vDwSDWDUkpNmTJFWVhYKAcHB2Vra2uaSXvOnDlp7qOUUm+99Zbq1q1bmlmTnrtixYpm34O4uDhlZ2enAgICnnh8IYQ56SMkRB7VsmVLFixYYFp3cHAAjGdHZs6cyblz54iMjCQxMZHY2FgePnyIvb19iuOMHj2awYMHs2rVKtPlnbJlywLGy2b//PMPq1evNm2vlMJgMHD58mUqV66caraIiAgKFiyIwWAgNjaWpk2b8u233xIZGcnNmzdp0qSJ2fZNmjThxIkTgPGy1gsvvEDFihVp164dL730Em3btn2u71Xv3r15/fXX+eabb7CxsWH16tX07NkTCwsL0+s8cOCA2RkgvV7/xO8bQMWKFdmyZQuxsbF8//33HD9+nBEjRphtM3/+fJYuXcrVq1eJiYkhPj6eWrVqPTHviRMnuHjxIo6OjmbtsbGxXLp06Rm+A0LkX1IICZFHOTg4UK5cObO2K1eu8NJLLzFs2DCmT59O4cKF2b9/P4MGDSI+Pj7VD/QPP/yQXr16sW3bNn799VemTJnC2rVr6dKlC1FRUQwZMoSRI0em2K9kyZJpZnN0dOTo0aNYWFjg4eGBnZ0dAJGRkU99XXXq1OHy5cv8+uuv7Ny5kx49etCmTRt+/PHHp+6blo4dO6KUYtu2bdSrV499+/bxxRdfmB6Piopi6tSpdO3aNcW+tra2aR7X2tra9B588skndOjQgalTp/Lxxx8DsHbtWt59910+//xzGjVqhKOjI7Nnz+bgwYNPzBsVFYWPj49ZAZokp3SIFyK3kEJIiHzkyJEjGAwGPv/8c9PZjqT+KE9SoUIFKlSowKhRo3j11VdZtmwZXbp0oU6dOpw5cyZFwfU0FhYWqe7j5OSEp6cnBw4cwNfX19R+4MAB6tevb7adv78//v7+vPLKK7Rr14579+5RuHBhs+Ml9cfR6/VPzGNra0vXrl1ZvXo1Fy9epGLFitSpU8f0eJ06dQgKCsrw6/yviRMn0qpVK4YNG2Z6nY0bN+bNN980bfPfMzrW1tYp8tepU4d169bh5uaGk5PTc2USIr+TztJC5CPlypUjISGBr776iuDgYFatWsXChQvT3D4mJobhw4ezZ88e/v33Xw4cOMDff/9tuuT1wQcf8OeffzJ8+HCOHz/OhQsX2Lx5c4Y7Sz/uvffe49NPP2XdunUEBQUxduxYjh8/zttvvw3AnDlz+OGHHzh37hznz59nw4YNuLu7pzoIpJubG3Z2duzYsYPQ0FAiIiLSfN7evXuzbds2li5dauoknWTy5MmsXLmSqVOncvr0ac6ePcvatWuZOHFihl5bo0aNqFGjBjNmzACgfPnyHD58mICAAM6fP8+kSZP4+++/zfbx9vbmn3/+ISgoiLCwMBISEujduzeurq506tSJffv2cfnyZfbs2cPIkSO5fv16hjIJke9p3UlJCJH5Uutgm2TOnDnKw8ND2dnZKT8/P7Vy5UoFqPDwcKWUeWfmuLg41bNnT+Xl5aWsra2Vp6enGj58uFlH6EOHDqkXXnhBFSxYUDk4OKgaNWr8v107RFkgiAMoPp8giwirwSJi8QJrMlgM3kMsBm9g03OsB/AI2vYGewOLRbDZLMuziZ+L2TDvF2dYmJn0YP+1Yed3n8PSn6qqYrfbMRgMaDabZFnG8Xh87ed5zng8pt1uk6Yp8/mcsixf++FtWBpgv98zHA5pNBrMZrOv71NVFf1+nxAC5/O5dq7T6cR0OqXVapGmKZPJhDzPv95ju92SZVlt/XA4kCQJl8uFx+PBcrmk0+nQ7XZZr9dsNpt/391ut9f7hhAoigKA6/XKYrGg1+uRJAmj0YjVasX9fv96Jkl1fwC/TTFJkqTf8NeYJEmKliEkSZKiZQhJkqRoGUKSJClahpAkSYqWISRJkqJlCEmSpGgZQpIkKVqGkCRJipYhJEmSomUISZKkaBlCkiQpWk+kAb3lu7764QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.6229461595315253\n",
      "max bootstrapping aucroc:\n",
      "0.8626129967593382\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.7480144385354908(0.6788773920783266,0.8152372456565141)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = cbclaff\n",
      "Sex = girls\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = girls in final sample n = 71\n",
      "positive girls in final sample n = 18\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8694968553459119\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.5134408602150538\n",
      "max bootstrapping aucroc:\n",
      "0.9965909090909091\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8684420395303515(0.739795918367347,0.9750000000000001)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = cbclaff\n",
      "Sex = girls\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = girls in final sample n = 200\n",
      "positive girls in final sample n = 18\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.7057387057387058\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.42486486486486486\n",
      "max bootstrapping aucroc:\n",
      "0.9209009009009008\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.7110364151853009(0.5584622942765904,0.8359375)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = anxiousdep\n",
      "Sex = both\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = both in final sample n = 173\n",
      "positive both in final sample n = 68\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8487394957983194\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7368777056277056\n",
      "max bootstrapping aucroc:\n",
      "0.9498732751337651\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8486238643109874(0.7913165266106443,0.905267629566695)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = anxiousdep\n",
      "Sex = both\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = both in final sample n = 680\n",
      "positive both in final sample n = 68\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.6580521914648212\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.5374824355971897\n",
      "max bootstrapping aucroc:\n",
      "0.7678465827490073\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.6570707364945328(0.5827533502551926,0.7221370967741936)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = anxiousdep\n",
      "Sex = boys\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = boys in final sample n = 102\n",
      "positive boys in final sample n = 50\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8523076923076923\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7286549707602339\n",
      "max bootstrapping aucroc:\n",
      "0.9521153846153846\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8523583770410136(0.7767857142857143,0.9147727272727273)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = anxiousdep\n",
      "Sex = boys\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = boys in final sample n = 484\n",
      "positive boys in final sample n = 50\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.6851152073732719\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.5621136590229312\n",
      "max bootstrapping aucroc:\n",
      "0.7850632440476191\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.6836310304471943(0.604153199741435,0.7567407024793389)\n",
      "\n",
      "...END AUCROC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = anxiousdep\n",
      "Sex = girls\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = girls in final sample n = 71\n",
      "positive girls in final sample n = 18\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8317610062893082\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.5593681917211328\n",
      "max bootstrapping aucroc:\n",
      "0.9711328976034859\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8310363613403801(0.6911764705882353,0.9392156862745098)\n",
      "\n",
      "...END AUCROC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = anxiousdep\n",
      "Sex = girls\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = girls in final sample n = 187\n",
      "positive girls in final sample n = 18\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.6305062458908612\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.3625103220478943\n",
      "max bootstrapping aucroc:\n",
      "0.8600206611570248\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.6341235723730065(0.4851796407185629,0.7722431077694235)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = withdrawndep\n",
      "Sex = both\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = both in final sample n = 173\n",
      "positive both in final sample n = 68\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8840336134453781\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7922077922077921\n",
      "max bootstrapping aucroc:\n",
      "0.9537114845938376\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.883597163293737(0.8286835222319093,0.9293197278911565)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = withdrawndep\n",
      "Sex = both\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = both in final sample n = 680\n",
      "positive both in final sample n = 68\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.7689350249903883\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.6587992086038961\n",
      "max bootstrapping aucroc:\n",
      "0.8880478662053057\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.7675373066919936(0.7025931928687196,0.8246815951560705)\n",
      "\n",
      "...END AUCROC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = withdrawndep\n",
      "Sex = boys\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = boys in final sample n = 102\n",
      "positive boys in final sample n = 50\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8769230769230769\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7835964574509049\n",
      "max bootstrapping aucroc:\n",
      "0.9651520985752793\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.878010828546762(0.8109356950327301,0.9390384615384616)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = withdrawndep\n",
      "Sex = boys\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = boys in final sample n = 472\n",
      "positive boys in final sample n = 50\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.7693364928909953\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.6482175383814728\n",
      "max bootstrapping aucroc:\n",
      "0.8756635071090048\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.7674610854926145(0.7039835164835164,0.8348503236245955)\n",
      "\n",
      "...END AUCROC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = withdrawndep\n",
      "Sex = girls\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = girls in final sample n = 71\n",
      "positive girls in final sample n = 18\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8820754716981132\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.6714285714285715\n",
      "max bootstrapping aucroc:\n",
      "0.9825757575757575\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8828635136749514(0.7744318181818182,0.96684350132626)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "Measure = withdrawndep\n",
      "Sex = girls\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = girls in final sample n = 215\n",
      "positive girls in final sample n = 18\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.7272983643542018\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_52535/1571086051.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 9.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.5441736481340442\n",
      "max bootstrapping aucroc:\n",
      "0.8905809362662154\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.727713407066252(0.6010362694300518,0.8473618090452261)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "FINISH ALL\n"
     ]
    }
   ],
   "source": [
    "for measure in ['cbclaff', 'anxiousdep', 'withdrawndep']:\n",
    "    for sex in ['both', 'boys', 'girls']:\n",
    "        for hypothesis in ['1', '2a']:\n",
    "            mydata = load_all_data(path_to_consensusfile=path_to_consensusfile,\n",
    "                                   path_to_demosfile=path_to_demosfile,\n",
    "                                   path_to_cbclfile=path_to_cbclfile,\n",
    "                                   hypothesis=hypothesis,\n",
    "                                   measure=measure,\n",
    "                                   sex=sex,\n",
    "                                   do_print=False)\n",
    "            fig_file_name = 'HBN_'+measure+'_'+hypothesis+'_'+sex\n",
    "            y_true,y_measure = run_aucroc_and_plot(mydata, \n",
    "                                                    path_to_save_plots='../plotting/plot_data/', \n",
    "                                                    name_to_save=fig_file_name, \n",
    "                                                    mymeasure = measure, \n",
    "                                                    hypothesis = hypothesis,\n",
    "                                                    nboots=100, \n",
    "                                                    target_auc=0.8)\n",
    "print('\\nFINISH ALL')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "39f402dc-cb57-4091-a51d-953e39f502c2",
   "metadata": {},
   "source": [
    "# Use this code to create a csv with output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f17b5951-5aab-4780-af35-835a26efad6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_89530/3035102799.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 8.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = cbclaff\n",
      "Sex = both\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = both in final sample n = 214\n",
      "positive both in final sample n = 76\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.8604118993135011\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.7726018675721562\n",
      "max bootstrapping aucroc:\n",
      "0.944546332046332\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.8623091920444785(0.8035482258870565,0.9129480286738352)\n",
      "\n",
      "...END AUCROC\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_89530/3035102799.py:305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 8.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Measure = cbclaff\n",
      "Sex = both\n",
      "Hypothesis = 2a\n",
      "\n",
      "Sex = both in final sample n = 760\n",
      "positive both in final sample n = 76\n",
      "BEGIN AUCROC...\n",
      "\n",
      "Single AUCROC score without bootstrapping:\n",
      "0.709631809787627\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min bootstrapping aucroc:\n",
      "0.6151102941176471\n",
      "max bootstrapping aucroc:\n",
      "0.8121070559610706\n",
      "p_onesided = 0\n",
      "p_twosided = 0\n",
      "boots_mean_AUCROC =\n",
      "0.7098070324767908(0.6448714596949892,0.7720617596166645)\n",
      "\n",
      "...END AUCROC\n",
      "\n",
      "FINISH ALL\n",
      "\n",
      "FINISH DICT\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# use this code to create a csv with output\n",
    "dict_to_save = {'Dataset':[],\n",
    "                'Wave':[],\n",
    "                'Scale':[],\n",
    "                'Measure':[],\n",
    "                'gs-Reporter':[],\n",
    "                'Sex':[],\n",
    "                'Hypothesis':[],\n",
    "                'b-AUCROC':[],\n",
    "                'q_25':[],\n",
    "                'q_75':[],\n",
    "                'p1sided': [],\n",
    "                'p2sided': []}\n",
    "\n",
    "fordict_datasets = []\n",
    "fordict_waves = []\n",
    "fordict_scales = []\n",
    "fordict_measures = []\n",
    "fordict_reporters = []\n",
    "fordict_sexes = []\n",
    "fordict_hypotheses = []\n",
    "fordict_aucrocs = []\n",
    "fordict_q25 = []\n",
    "fordict_q75 = []\n",
    "fordict_p1 = []\n",
    "fordict_p2 = []\n",
    "\n",
    "Dataset = 'HBN'\n",
    "Scale = 'CBCL'\n",
    "Wave = 'baseline-matched'\n",
    "Reporter = 'clinician'\n",
    "\n",
    "for measure in ['cbclaff']: #['cbclaff', 'anxiousdep', 'withdrawndep']\n",
    "    for sex in ['both']: #['both', 'boys', 'girls']\n",
    "        for hypothesis in ['1', '2a']:\n",
    "            mydata = load_all_data(path_to_consensusfile=path_to_consensusfile,\n",
    "                                   path_to_demosfile=path_to_demosfile,\n",
    "                                   path_to_cbclfile=path_to_cbclfile,\n",
    "                                   hypothesis=hypothesis,\n",
    "                                   measure=measure,\n",
    "                                   sex=sex,\n",
    "                                   do_print=False)\n",
    "            mydata.to_csv('/Users/zeleninam2/Documents/projects/cbcl_ksads_work/revision_2023/results/my_subsample_HBN_H'+hypothesis+'.csv', sep=',', index=False, encoding='utf-8')\n",
    "\n",
    "            fig_file_name = 'HBN_'+measure+'_'+hypothesis+'_'+sex\n",
    "            y_true,y_measure, b_AUCROC, q25, q75, p1, p2 = run_aucroc_and_plot(mydata, \n",
    "                                                    path_to_save_plots='../plotting/plot_data/', \n",
    "                                                    name_to_save=fig_file_name, \n",
    "                                                    mymeasure = measure, \n",
    "                                                    hypothesis = hypothesis,\n",
    "                                                    nboots=100, \n",
    "                                                    target_auc=0.8)\n",
    "            fordict_datasets.append(Dataset)\n",
    "            fordict_waves.append(Wave)\n",
    "            fordict_scales.append(Scale)\n",
    "            fordict_measures.append(measure)\n",
    "            fordict_reporters.append(Reporter)\n",
    "            fordict_sexes.append(sex)\n",
    "            fordict_hypotheses.append(hypothesis)\n",
    "            fordict_aucrocs.append(b_AUCROC)\n",
    "            fordict_q25.append(q25)\n",
    "            fordict_q75.append(q75)\n",
    "            fordict_p1.append(p1)\n",
    "            fordict_p2.append(p2)\n",
    "\n",
    "print('\\nFINISH ALL')\n",
    "\n",
    "dict_to_save = {'Dataset':fordict_datasets,\n",
    "                'Wave':fordict_waves,\n",
    "                'Scale':fordict_scales,\n",
    "                'Measure':fordict_measures,\n",
    "                'gs-Reporter':fordict_reporters,\n",
    "                'Sex':fordict_sexes,                \n",
    "                'Hypothesis':fordict_hypotheses,\n",
    "                'b-AUCROC':fordict_aucrocs,\n",
    "                'q_25':fordict_q25,\n",
    "                'q_75':fordict_q75,\n",
    "                'p1sided': fordict_p1,\n",
    "                'p2sided': fordict_p2}\n",
    "\n",
    "print('\\nFINISH DICT\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3c9f9c1f-eba9-4fb8-8281-e158e22d85b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Dataset': ['HBN', 'HBN'],\n",
       " 'Wave': ['baseline-matched', 'baseline-matched'],\n",
       " 'Scale': ['CBCL', 'CBCL'],\n",
       " 'Measure': ['cbclaff', 'cbclaff'],\n",
       " 'gs-Reporter': ['clinician', 'clinician'],\n",
       " 'Sex': ['both', 'both'],\n",
       " 'Hypothesis': ['1', '2a'],\n",
       " 'b-AUCROC': [0.8605060516768895, 0.7115494592011461],\n",
       " 'q_25': ['0.8041873117652772', '0.6478212647567487'],\n",
       " 'q_75': ['0.9147104851330203', '0.7736684984122758'],\n",
       " 'p1sided': [0.9820179820179821, 0.002997002997002997],\n",
       " 'p2sided': [0.03596403596403597, 0.005994005994005994]}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_to_save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "55349e42-da39-45dc-ad00-5b79e26cee0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset</th>\n",
       "      <th>Wave</th>\n",
       "      <th>Scale</th>\n",
       "      <th>Measure</th>\n",
       "      <th>gs-Reporter</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Hypothesis</th>\n",
       "      <th>b-AUCROC</th>\n",
       "      <th>q_25</th>\n",
       "      <th>q_75</th>\n",
       "      <th>p1sided</th>\n",
       "      <th>p2sided</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HBN</td>\n",
       "      <td>baseline-matched</td>\n",
       "      <td>CBCL</td>\n",
       "      <td>cbclaff</td>\n",
       "      <td>clinician</td>\n",
       "      <td>both</td>\n",
       "      <td>1</td>\n",
       "      <td>0.860506</td>\n",
       "      <td>0.8041873117652772</td>\n",
       "      <td>0.9147104851330203</td>\n",
       "      <td>0.982018</td>\n",
       "      <td>0.035964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HBN</td>\n",
       "      <td>baseline-matched</td>\n",
       "      <td>CBCL</td>\n",
       "      <td>cbclaff</td>\n",
       "      <td>clinician</td>\n",
       "      <td>both</td>\n",
       "      <td>2a</td>\n",
       "      <td>0.711549</td>\n",
       "      <td>0.6478212647567487</td>\n",
       "      <td>0.7736684984122758</td>\n",
       "      <td>0.002997</td>\n",
       "      <td>0.005994</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Dataset              Wave Scale  Measure gs-Reporter   Sex Hypothesis  \\\n",
       "0     HBN  baseline-matched  CBCL  cbclaff   clinician  both          1   \n",
       "1     HBN  baseline-matched  CBCL  cbclaff   clinician  both         2a   \n",
       "\n",
       "   b-AUCROC                q_25                q_75   p1sided   p2sided  \n",
       "0  0.860506  0.8041873117652772  0.9147104851330203  0.982018  0.035964  \n",
       "1  0.711549  0.6478212647567487  0.7736684984122758  0.002997  0.005994  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_to_save = pd.DataFrame.from_dict(dict_to_save)\n",
    "df_to_save.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cec672af-b437-412d-8836-23f51b16214c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_to_save.to_csv('/Users/zeleninam2/Documents/projects/cbcl_ksads_work/revision_2023/results/HBNresults_newnew.csv', sep=',', index=False, encoding='utf-8')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cc9eb96-65d9-4650-8f58-d29b92086531",
   "metadata": {},
   "source": [
    "# for flowchart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "372f9467-f869-453b-afea-0c29708a7ae3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ALL DATA:\n",
      "(6182, 161)\n",
      "(3628, 15)\n",
      "Anonymized ID            3617\n",
      "Subject Type                1\n",
      "Visit                       1\n",
      "Days since enrollment       1\n",
      "EID                      3615\n",
      "                         ... \n",
      "DX_10_ByHx                  2\n",
      "DX_10_New                   1\n",
      "DX_10_Rem                   1\n",
      "DX_10_PRem                  1\n",
      "DX_10_Past_Doc              1\n",
      "Length: 161, dtype: int64\n",
      "\n",
      "\n",
      "Anonymized ID            3628\n",
      "Subject Type                1\n",
      "Visit                       1\n",
      "Days since enrollment       1\n",
      "EID                      3628\n",
      "START_DATE                  1\n",
      "Patient_ID               3628\n",
      "Enrollment Year             6\n",
      "Enrollment Season           4\n",
      "Sex                         2\n",
      "Age                      3312\n",
      "Study Site                  5\n",
      "Commercial Use              2\n",
      "Release Number              9\n",
      "Participant_Status          3\n",
      "dtype: int64\n",
      "\n",
      "\n",
      "Anonymized ID_x            3617\n",
      "Subject Type_x                1\n",
      "Visit_x                       1\n",
      "Days since enrollment_x       1\n",
      "EID                        3615\n",
      "                           ... \n",
      "Study Site                    5\n",
      "Commercial Use                2\n",
      "Release Number                9\n",
      "Participant_Status            3\n",
      "_merge                        1\n",
      "Length: 176, dtype: int64\n",
      "     Anonymized ID_x Subject Type_x Visit_x Days since enrollment_x  \\\n",
      "5136       A00097094        UNKNOWN      V1                       0   \n",
      "\n",
      "               EID          START_DATE_x Study Site  Year  Season  ...  \\\n",
      "5136  NDARPA265JGD  1901-01-01T07:00:00Z   HBN    1  2019  Spring  ...   \n",
      "\n",
      "        Patient_ID Enrollment Year Enrollment Season Sex        Age  \\\n",
      "5136  NDARPA265JGD            2019            Spring   0  11.368697   \n",
      "\n",
      "     Study Site Commercial Use Release Number Participant_Status _merge  \n",
      "5136          1            Yes              7            Dropout   both  \n",
      "\n",
      "[1 rows x 176 columns]\n",
      "\n",
      "\n",
      "     Anonymized ID_x Subject Type_x Visit_x Days since enrollment_x  \\\n",
      "5137       A00097094        UNKNOWN      V1                       0   \n",
      "\n",
      "               EID          START_DATE_x Study Site  Year  Season  ...  \\\n",
      "5137  NDARPA265JGD  1901-01-01T07:00:00Z   HBN    1  2019  Spring  ...   \n",
      "\n",
      "        Patient_ID Enrollment Year Enrollment Season Sex        Age  \\\n",
      "5137  NDARPA265JGD            2019            Spring   0  11.368697   \n",
      "\n",
      "     Study Site Commercial Use Release Number Participant_Status _merge  \n",
      "5137          1            Yes              7            Dropout   both  \n",
      "\n",
      "[1 rows x 176 columns]\n",
      "\n",
      "\n",
      "     Anonymized ID_x Subject Type_x Visit_x Days since enrollment_x  \\\n",
      "5138       A00098028        UNKNOWN      V1                       0   \n",
      "\n",
      "               EID          START_DATE_x Study Site  Year  Season  ...  \\\n",
      "5138  NDARTR157NPQ  1901-01-01T07:00:00Z   HBN    3  2018  Spring  ...   \n",
      "\n",
      "        Patient_ID Enrollment Year Enrollment Season Sex       Age Study Site  \\\n",
      "5138  NDARTR157NPQ            2017            Summer   1  6.925165          3   \n",
      "\n",
      "     Commercial Use Release Number Participant_Status _merge  \n",
      "5138            Yes              7           Complete   both  \n",
      "\n",
      "[1 rows x 176 columns]\n",
      "overall healthy\n",
      "healthy_9-13\n",
      "False    3469\n",
      "True      145\n",
      "Name: count, dtype: int64\n",
      "anxiety\n",
      "False    2612\n",
      "True     1002\n",
      "Name: count, dtype: int64\n",
      "ADHD\n",
      "True     1938\n",
      "False    1676\n",
      "Name: count, dtype: int64\n",
      "anxiety_or_ADHD\n",
      "True     2312\n",
      "False    1302\n",
      "Name: count, dtype: int64\n",
      "currently_depressed\n",
      "False    3352\n",
      "True      262\n",
      "Name: count, dtype: int64\n",
      "depressionYES_anxietyADHDNO\n",
      "False    3532\n",
      "True       82\n",
      "Name: count, dtype: int64\n",
      "depressionNO_anxietyADHDYES\n",
      "True     2132\n",
      "False    1482\n",
      "Name: count, dtype: int64\n",
      "\n",
      "AFTER REMOVING DUPLICATES AND MISSING DATA\n",
      "(3614, 215)\n",
      "\n",
      "RIGHT AGE\n",
      "(3614,)\n",
      "\n",
      "DEPRESSION 9 to 13 (<=13)\n",
      "depressed_9-13\n",
      "False    3537\n",
      "True       77\n",
      "Name: count, dtype: int64\n",
      "\n",
      "HEALTHY 9 to 13 (<=13)\n",
      "healthy_9-13\n",
      "False    3469\n",
      "True      145\n",
      "Name: count, dtype: int64\n",
      "\n",
      "depressionYES_anxietyADHDNO 9 to 13 (<=13)\n",
      "depressionYES_anxietyADHDNO_9-13\n",
      "False    3601\n",
      "True       13\n",
      "Name: count, dtype: int64\n",
      "\n",
      "depressionNO_anxietyADHDYES 9 to 13 (<=13)\n",
      "depressionNO_anxietyADHDYES_9-13\n",
      "False    2540\n",
      "True     1074\n",
      "Name: count, dtype: int64\n",
      "(3098, 157)\n",
      "CBCL_AD\n",
      "0     441\n",
      "1     381\n",
      "2     341\n",
      "3     318\n",
      "4     283\n",
      "5     227\n",
      "6     211\n",
      "7     183\n",
      "8     146\n",
      "9     113\n",
      "10    104\n",
      "12     78\n",
      "11     77\n",
      "13     53\n",
      "14     41\n",
      "17     20\n",
      "16     20\n",
      "15     20\n",
      "19     12\n",
      "18     11\n",
      "20      8\n",
      "22      4\n",
      "24      2\n",
      "21      2\n",
      "23      1\n",
      "25      1\n",
      "Name: count, dtype: int64\n",
      "CBCL_WD\n",
      "0     790\n",
      "1     597\n",
      "2     427\n",
      "3     315\n",
      "4     261\n",
      "5     201\n",
      "6     153\n",
      "7     103\n",
      "8      77\n",
      "9      66\n",
      "10     36\n",
      "11     29\n",
      "12     20\n",
      "13      9\n",
      "14      8\n",
      "16      5\n",
      "99      1\n",
      "Name: count, dtype: int64\n",
      "CBCL_05\n",
      "0     2315\n",
      "1      614\n",
      "2      167\n",
      "99       2\n",
      "Name: count, dtype: int64\n",
      "CBCL_14\n",
      "0     2282\n",
      "1      632\n",
      "2      181\n",
      "99       3\n",
      "Name: count, dtype: int64\n",
      "CBCL_18\n",
      "0     2956\n",
      "1      125\n",
      "2       14\n",
      "99       3\n",
      "Name: count, dtype: int64\n",
      "CBCL_24\n",
      "0     2022\n",
      "1      793\n",
      "2      279\n",
      "99       4\n",
      "Name: count, dtype: int64\n",
      "CBCL_35\n",
      "0     2185\n",
      "1      776\n",
      "2      134\n",
      "99       3\n",
      "Name: count, dtype: int64\n",
      "CBCL_52\n",
      "0     2721\n",
      "1      314\n",
      "2       59\n",
      "99       4\n",
      "Name: count, dtype: int64\n",
      "CBCL_54\n",
      "0     2392\n",
      "1      535\n",
      "2      166\n",
      "99       5\n",
      "Name: count, dtype: int64\n",
      "CBCL_76\n",
      "0     2454\n",
      "1      455\n",
      "2      187\n",
      "99       2\n",
      "Name: count, dtype: int64\n",
      "CBCL_77\n",
      "0     2733\n",
      "1      257\n",
      "2       98\n",
      "99      10\n",
      "Name: count, dtype: int64\n",
      "CBCL_91\n",
      "0     2831\n",
      "1      235\n",
      "2       22\n",
      "99      10\n",
      "Name: count, dtype: int64\n",
      "CBCL_100\n",
      "0     2156\n",
      "1      614\n",
      "2      314\n",
      "99      14\n",
      "Name: count, dtype: int64\n",
      "CBCL_102\n",
      "0     2375\n",
      "1      534\n",
      "2      179\n",
      "99      10\n",
      "Name: count, dtype: int64\n",
      "CBCL_103\n",
      "0     2159\n",
      "1      785\n",
      "2      143\n",
      "99      11\n",
      "Name: count, dtype: int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "int64\n",
      "Age\n",
      "7.048254     1\n",
      "5.851813     1\n",
      "16.921172    1\n",
      "14.486995    1\n",
      "15.987451    1\n",
      "            ..\n",
      "6.826602     1\n",
      "9.854665     1\n",
      "15.661647    1\n",
      "8.803331     1\n",
      "8.611567     1\n",
      "Name: count, Length: 61, dtype: int64\n",
      "age_9to13\n",
      "False    39\n",
      "True     22\n",
      "Name: count, dtype: int64\n",
      "(3031, 232)\n",
      "\n",
      "DEPRESSION 9 to 13 (<=13)\n",
      "depressed_9-13\n",
      "False    2955\n",
      "True       76\n",
      "Name: count, dtype: int64\n",
      "\n",
      "HEALTHY 9 to 13 (<=13)\n",
      "healthy_9-13\n",
      "False    2893\n",
      "True      138\n",
      "Name: count, dtype: int64\n",
      "\n",
      "depressionYES_anxietyADHDNO 9 to 13 (<=13)\n",
      "depressionYES_anxietyADHDNO_9-13\n",
      "False    3019\n",
      "True       12\n",
      "Name: count, dtype: int64\n",
      "\n",
      "depressionNO_anxietyADHDYES 9 to 13 (<=13)\n",
      "depressionNO_anxietyADHDYES_9-13\n",
      "False    1967\n",
      "True     1064\n",
      "Name: count, dtype: int64\n",
      "Sex\n",
      "0    125\n",
      "1     89\n",
      "Name: count, dtype: int64\n",
      "\n",
      "Measure = cbclaff\n",
      "Sex = both\n",
      "Hypothesis = 1\n",
      "\n",
      "Sex = both in final sample n = 214\n",
      "positive both in final sample n = 76\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/7l/34y2s3yx5q77_c0h8j6s32gc0000gs/T/ipykernel_80189/2112300360.py:317: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  checkage['age_9to13'] = (checkage.Age.astype(float) >= 8.0) & (checkage.Age.astype(float) <= 13.0)\n"
     ]
    }
   ],
   "source": [
    "mydata = load_all_data(path_to_consensusfile=path_to_consensusfile,\n",
    "                                   path_to_demosfile=path_to_demosfile,\n",
    "                                   path_to_cbclfile=path_to_cbclfile,\n",
    "                                   hypothesis='1',\n",
    "                                   measure='cbclaff',\n",
    "                                   sex='both',\n",
    "                                   do_print=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fcf9cbb-5b6b-4e01-befc-38167547f913",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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