From 9dda28d2ff8c67d0efb30333cafa35995ed18521 Mon Sep 17 00:00:00 2001
From: Oleg Zendel <13455948+Zendelo@users.noreply.github.com>
Date: Tue, 27 Feb 2024 22:16:40 +1100
Subject: [PATCH] Analyses with qpptk@tirex in progress

work in progress
---
 code/qpp_notebook.ipynb | 2519 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 2519 insertions(+)
 create mode 100644 code/qpp_notebook.ipynb

diff --git a/code/qpp_notebook.ipynb b/code/qpp_notebook.ipynb
new file mode 100644
index 0000000..463e54c
--- /dev/null
+++ b/code/qpp_notebook.ipynb
@@ -0,0 +1,2519 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:19.496959Z",
+     "start_time": "2024-02-27T09:44:19.493171Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "PxFxlda_EpHQ",
+    "outputId": "b5f63c83-af04-4c91-e7ee-b4dc49d1dcdc"
+   },
+   "outputs": [],
+   "source": [
+    "# !pip3 install tira ir_datasets python-terrier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:20.666891Z",
+     "start_time": "2024-02-27T09:44:19.498572Z"
+    },
+    "id": "SX4juBzqChpJ"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "PyTerrier 0.10.0 has loaded Terrier 5.7 (built by craigm on 2022-11-10 18:30) and terrier-helper 0.0.7\n",
+      "\n",
+      "No etc/terrier.properties, using terrier.default.properties for bootstrap configuration.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import pyterrier as pt\n",
+    "from tira.rest_api_client import Client\n",
+    "from tira.third_party_integrations import ensure_pyterrier_is_loaded\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "ensure_pyterrier_is_loaded()\n",
+    "tira = Client()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-O5UUtTZHxPG"
+   },
+   "source": [
+    "# First, Example for a single dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:21.273458Z",
+     "start_time": "2024-02-27T09:44:21.242597Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 206
+    },
+    "id": "hEdqVc5iGGWK",
+    "outputId": "e967d78c-a3fe-48b2-8092-0172675d5a3b"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>qid</th>\n",
+       "      <th>query</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3990512</td>\n",
+       "      <td>how can we get concentration onsomething</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>714612</td>\n",
+       "      <td>why doesn t the water fall off earth if it s r...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2528767</td>\n",
+       "      <td>how do i determine the charge of the iron ion ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>821387</td>\n",
+       "      <td>i have mice how do i get rid of them humanely</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1880028</td>\n",
+       "      <td>what does see leaflet mean on ept pregnancy test</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       qid                                              query\n",
+       "0  3990512           how can we get concentration onsomething\n",
+       "1   714612  why doesn t the water fall off earth if it s r...\n",
+       "2  2528767  how do i determine the charge of the iron ion ...\n",
+       "3   821387      i have mice how do i get rid of them humanely\n",
+       "4  1880028   what does see leaflet mean on ept pregnancy test"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset = 'antique-test-20230107-training'\n",
+    "pt_dataset = pt.get_dataset(f\"irds:ir-benchmarks/{dataset}\")\n",
+    "\n",
+    "pt_dataset.get_topics('query').head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:26.021398Z",
+     "start_time": "2024-02-27T09:44:21.274610Z"
+    },
+    "id": "MQ6m5dptGi3C"
+   },
+   "outputs": [],
+   "source": [
+    "bm25 = tira.pt.from_submission('ir-benchmarks/tira-ir-starter/BM25 Re-Rank (tira-ir-starter-pyterrier)', dataset)\n",
+    "qpp_predictions = tira.pt.transform_queries('ir-benchmarks/qpptk/all-predictors', dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:26.068925Z",
+     "start_time": "2024-02-27T09:44:26.023712Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 377
+    },
+    "id": "I6F83a5NHlNv",
+    "outputId": "7bf7dc2b-ce46-403d-b1c4-35c2e6585c7a"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>qid</th>\n",
+       "      <th>query</th>\n",
+       "      <th>max-idf</th>\n",
+       "      <th>avg-idf</th>\n",
+       "      <th>scq</th>\n",
+       "      <th>max-scq</th>\n",
+       "      <th>avg-scq</th>\n",
+       "      <th>var</th>\n",
+       "      <th>max-var</th>\n",
+       "      <th>avg-var</th>\n",
+       "      <th>...</th>\n",
+       "      <th>smv+50</th>\n",
+       "      <th>clarity+50+100</th>\n",
+       "      <th>wig+100</th>\n",
+       "      <th>nqc+100</th>\n",
+       "      <th>smv+100</th>\n",
+       "      <th>clarity+100+100</th>\n",
+       "      <th>wig+1000</th>\n",
+       "      <th>nqc+1000</th>\n",
+       "      <th>smv+1000</th>\n",
+       "      <th>clarity+1000+100</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3990512</td>\n",
+       "      <td>how can we get concentration onsomething</td>\n",
+       "      <td>11.116584</td>\n",
+       "      <td>7.046932</td>\n",
+       "      <td>154.548142</td>\n",
+       "      <td>48.116900</td>\n",
+       "      <td>38.637036</td>\n",
+       "      <td>11.621307</td>\n",
+       "      <td>6.724458</td>\n",
+       "      <td>1.936884</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.030120</td>\n",
+       "      <td>3.795747</td>\n",
+       "      <td>1.823258</td>\n",
+       "      <td>0.039069</td>\n",
+       "      <td>0.035748</td>\n",
+       "      <td>3.731287</td>\n",
+       "      <td>0.972405</td>\n",
+       "      <td>0.019728</td>\n",
+       "      <td>0.010170</td>\n",
+       "      <td>3.389977</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>714612</td>\n",
+       "      <td>why doesn t the water fall off earth if it s r...</td>\n",
+       "      <td>12.215196</td>\n",
+       "      <td>7.627986</td>\n",
+       "      <td>380.326020</td>\n",
+       "      <td>47.708207</td>\n",
+       "      <td>38.032602</td>\n",
+       "      <td>15.536635</td>\n",
+       "      <td>5.230969</td>\n",
+       "      <td>1.294720</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.004710</td>\n",
+       "      <td>4.267368</td>\n",
+       "      <td>1.538839</td>\n",
+       "      <td>0.011142</td>\n",
+       "      <td>0.008922</td>\n",
+       "      <td>4.106367</td>\n",
+       "      <td>0.695940</td>\n",
+       "      <td>0.009800</td>\n",
+       "      <td>0.006195</td>\n",
+       "      <td>3.815700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2528767</td>\n",
+       "      <td>how do i determine the charge of the iron ion ...</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.712145</td>\n",
+       "      <td>442.767537</td>\n",
+       "      <td>52.221022</td>\n",
+       "      <td>40.251594</td>\n",
+       "      <td>20.639520</td>\n",
+       "      <td>3.725044</td>\n",
+       "      <td>1.876320</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.016734</td>\n",
+       "      <td>4.314736</td>\n",
+       "      <td>2.091532</td>\n",
+       "      <td>0.017572</td>\n",
+       "      <td>0.015034</td>\n",
+       "      <td>4.305586</td>\n",
+       "      <td>0.928886</td>\n",
+       "      <td>0.012062</td>\n",
+       "      <td>0.007967</td>\n",
+       "      <td>4.294343</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>821387</td>\n",
+       "      <td>i have mice how do i get rid of them humanely</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.890641</td>\n",
+       "      <td>340.263514</td>\n",
+       "      <td>50.394187</td>\n",
+       "      <td>37.807057</td>\n",
+       "      <td>11.381356</td>\n",
+       "      <td>2.897810</td>\n",
+       "      <td>1.138136</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.021428</td>\n",
+       "      <td>3.532815</td>\n",
+       "      <td>2.210218</td>\n",
+       "      <td>0.021395</td>\n",
+       "      <td>0.017602</td>\n",
+       "      <td>3.516496</td>\n",
+       "      <td>0.805009</td>\n",
+       "      <td>0.015333</td>\n",
+       "      <td>0.010520</td>\n",
+       "      <td>3.508216</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1880028</td>\n",
+       "      <td>what does see leaflet mean on ept pregnancy test</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>6.848213</td>\n",
+       "      <td>339.046657</td>\n",
+       "      <td>49.747516</td>\n",
+       "      <td>37.671851</td>\n",
+       "      <td>11.333447</td>\n",
+       "      <td>3.290287</td>\n",
+       "      <td>1.259272</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.011415</td>\n",
+       "      <td>4.770863</td>\n",
+       "      <td>1.538375</td>\n",
+       "      <td>0.016755</td>\n",
+       "      <td>0.011784</td>\n",
+       "      <td>4.750485</td>\n",
+       "      <td>0.881017</td>\n",
+       "      <td>0.009732</td>\n",
+       "      <td>0.005666</td>\n",
+       "      <td>4.640350</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 34 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       qid                                              query    max-idf  \\\n",
+       "0  3990512           how can we get concentration onsomething  11.116584   \n",
+       "1   714612  why doesn t the water fall off earth if it s r...  12.215196   \n",
+       "2  2528767  how do i determine the charge of the iron ion ...  12.908343   \n",
+       "3   821387      i have mice how do i get rid of them humanely  12.908343   \n",
+       "4  1880028   what does see leaflet mean on ept pregnancy test  12.908343   \n",
+       "\n",
+       "    avg-idf         scq    max-scq    avg-scq        var   max-var   avg-var  \\\n",
+       "0  7.046932  154.548142  48.116900  38.637036  11.621307  6.724458  1.936884   \n",
+       "1  7.627986  380.326020  47.708207  38.032602  15.536635  5.230969  1.294720   \n",
+       "2  8.712145  442.767537  52.221022  40.251594  20.639520  3.725044  1.876320   \n",
+       "3  8.890641  340.263514  50.394187  37.807057  11.381356  2.897810  1.138136   \n",
+       "4  6.848213  339.046657  49.747516  37.671851  11.333447  3.290287  1.259272   \n",
+       "\n",
+       "   ...    smv+50  clarity+50+100   wig+100   nqc+100   smv+100  \\\n",
+       "0  ...  0.030120        3.795747  1.823258  0.039069  0.035748   \n",
+       "1  ...  0.004710        4.267368  1.538839  0.011142  0.008922   \n",
+       "2  ...  0.016734        4.314736  2.091532  0.017572  0.015034   \n",
+       "3  ...  0.021428        3.532815  2.210218  0.021395  0.017602   \n",
+       "4  ...  0.011415        4.770863  1.538375  0.016755  0.011784   \n",
+       "\n",
+       "   clarity+100+100  wig+1000  nqc+1000  smv+1000  clarity+1000+100  \n",
+       "0         3.731287  0.972405  0.019728  0.010170          3.389977  \n",
+       "1         4.106367  0.695940  0.009800  0.006195          3.815700  \n",
+       "2         4.305586  0.928886  0.012062  0.007967          4.294343  \n",
+       "3         3.516496  0.805009  0.015333  0.010520          3.508216  \n",
+       "4         4.750485  0.881017  0.009732  0.005666          4.640350  \n",
+       "\n",
+       "[5 rows x 34 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qpp_predictions(pt_dataset.get_topics('query').head())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:26.628811Z",
+     "start_time": "2024-02-27T09:44:26.070498Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 424
+    },
+    "id": "MSlPf_B5H1vT",
+    "outputId": "5b91b276-3690-4149-83d7-3e4f74e76a06"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>qid</th>\n",
+       "      <th>measure</th>\n",
+       "      <th>value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>70</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>100653</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.428160</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1015624</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.580570</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1017690</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.754357</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>116</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1035857</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.652168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>103830</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.530858</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>851124</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.545156</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>896725</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.360260</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>104</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>922849</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.498273</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>178</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>949154</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.664721</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>142</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>953489</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.195793</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>200 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     name      qid      measure     value\n",
+       "70   BM25   100653  ndcg_cut.10  0.428160\n",
+       "85   BM25  1015624  ndcg_cut.10  0.580570\n",
+       "43   BM25  1017690  ndcg_cut.10  0.754357\n",
+       "116  BM25  1035857  ndcg_cut.10  0.652168\n",
+       "122  BM25   103830  ndcg_cut.10  0.530858\n",
+       "..    ...      ...          ...       ...\n",
+       "19   BM25   851124  ndcg_cut.10  0.545156\n",
+       "95   BM25   896725  ndcg_cut.10  0.360260\n",
+       "104  BM25   922849  ndcg_cut.10  0.498273\n",
+       "178  BM25   949154  ndcg_cut.10  0.664721\n",
+       "142  BM25   953489  ndcg_cut.10  0.195793\n",
+       "\n",
+       "[200 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_eval = pt.Experiment([bm25], pt_dataset.get_topics('query'), pt_dataset.get_qrels(), names=['BM25'],\n",
+    "                        eval_metrics=['ndcg_cut.10'], perquery=True)\n",
+    "df_eval"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:44:26.680325Z",
+     "start_time": "2024-02-27T09:44:26.630771Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 461
+    },
+    "id": "5iDu8XkXJJhR",
+    "outputId": "1288cef2-3f77-444c-943f-8256cb144968"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>qid</th>\n",
+       "      <th>measure</th>\n",
+       "      <th>value</th>\n",
+       "      <th>max-idf</th>\n",
+       "      <th>avg-idf</th>\n",
+       "      <th>scq</th>\n",
+       "      <th>max-scq</th>\n",
+       "      <th>avg-scq</th>\n",
+       "      <th>var</th>\n",
+       "      <th>...</th>\n",
+       "      <th>smv+50</th>\n",
+       "      <th>clarity+50+100</th>\n",
+       "      <th>wig+100</th>\n",
+       "      <th>nqc+100</th>\n",
+       "      <th>smv+100</th>\n",
+       "      <th>clarity+100+100</th>\n",
+       "      <th>wig+1000</th>\n",
+       "      <th>nqc+1000</th>\n",
+       "      <th>smv+1000</th>\n",
+       "      <th>clarity+1000+100</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>70</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>100653</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.428160</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>9.051803</td>\n",
+       "      <td>598.373506</td>\n",
+       "      <td>50.637838</td>\n",
+       "      <td>37.398344</td>\n",
+       "      <td>23.617904</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014273</td>\n",
+       "      <td>3.544082</td>\n",
+       "      <td>1.951133</td>\n",
+       "      <td>0.016508</td>\n",
+       "      <td>0.009057</td>\n",
+       "      <td>3.544058</td>\n",
+       "      <td>0.745923</td>\n",
+       "      <td>0.009943</td>\n",
+       "      <td>0.006240</td>\n",
+       "      <td>3.544040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>85</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1015624</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.580570</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.369403</td>\n",
+       "      <td>280.338094</td>\n",
+       "      <td>50.578374</td>\n",
+       "      <td>40.048299</td>\n",
+       "      <td>9.523332</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.011114</td>\n",
+       "      <td>3.999061</td>\n",
+       "      <td>1.929926</td>\n",
+       "      <td>0.018038</td>\n",
+       "      <td>0.013737</td>\n",
+       "      <td>3.935562</td>\n",
+       "      <td>1.029481</td>\n",
+       "      <td>0.012135</td>\n",
+       "      <td>0.007093</td>\n",
+       "      <td>3.716341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1017690</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.754357</td>\n",
+       "      <td>12.215196</td>\n",
+       "      <td>7.912693</td>\n",
+       "      <td>283.592656</td>\n",
+       "      <td>49.248037</td>\n",
+       "      <td>40.513237</td>\n",
+       "      <td>8.418207</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.013975</td>\n",
+       "      <td>3.511534</td>\n",
+       "      <td>1.571078</td>\n",
+       "      <td>0.018584</td>\n",
+       "      <td>0.015681</td>\n",
+       "      <td>3.456468</td>\n",
+       "      <td>0.938830</td>\n",
+       "      <td>0.009677</td>\n",
+       "      <td>0.004896</td>\n",
+       "      <td>3.187760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>116</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1035857</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.652168</td>\n",
+       "      <td>10.135754</td>\n",
+       "      <td>7.745829</td>\n",
+       "      <td>367.762077</td>\n",
+       "      <td>50.625796</td>\n",
+       "      <td>45.970260</td>\n",
+       "      <td>15.929586</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.004655</td>\n",
+       "      <td>3.839171</td>\n",
+       "      <td>1.919674</td>\n",
+       "      <td>0.006738</td>\n",
+       "      <td>0.004749</td>\n",
+       "      <td>3.618240</td>\n",
+       "      <td>1.054783</td>\n",
+       "      <td>0.012100</td>\n",
+       "      <td>0.009408</td>\n",
+       "      <td>3.312848</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>103830</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.530858</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>7.721879</td>\n",
+       "      <td>277.966310</td>\n",
+       "      <td>50.531838</td>\n",
+       "      <td>39.709473</td>\n",
+       "      <td>11.214659</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005703</td>\n",
+       "      <td>3.557757</td>\n",
+       "      <td>1.829664</td>\n",
+       "      <td>0.015672</td>\n",
+       "      <td>0.013502</td>\n",
+       "      <td>3.459321</td>\n",
+       "      <td>0.914128</td>\n",
+       "      <td>0.012781</td>\n",
+       "      <td>0.007959</td>\n",
+       "      <td>3.326919</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>851124</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.545156</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>9.099939</td>\n",
+       "      <td>306.580831</td>\n",
+       "      <td>49.457465</td>\n",
+       "      <td>34.064537</td>\n",
+       "      <td>8.378009</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.007420</td>\n",
+       "      <td>4.803370</td>\n",
+       "      <td>1.619716</td>\n",
+       "      <td>0.010545</td>\n",
+       "      <td>0.007952</td>\n",
+       "      <td>4.641726</td>\n",
+       "      <td>0.926463</td>\n",
+       "      <td>0.007980</td>\n",
+       "      <td>0.004847</td>\n",
+       "      <td>4.121996</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>896725</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.360260</td>\n",
+       "      <td>10.962433</td>\n",
+       "      <td>7.438826</td>\n",
+       "      <td>467.079609</td>\n",
+       "      <td>48.917291</td>\n",
+       "      <td>42.461783</td>\n",
+       "      <td>12.903404</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.004789</td>\n",
+       "      <td>3.113233</td>\n",
+       "      <td>1.477184</td>\n",
+       "      <td>0.008821</td>\n",
+       "      <td>0.007782</td>\n",
+       "      <td>3.153661</td>\n",
+       "      <td>0.824822</td>\n",
+       "      <td>0.007862</td>\n",
+       "      <td>0.005510</td>\n",
+       "      <td>2.968856</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>104</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>922849</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.498273</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>7.112997</td>\n",
+       "      <td>274.841073</td>\n",
+       "      <td>46.525209</td>\n",
+       "      <td>34.355134</td>\n",
+       "      <td>6.537749</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.005467</td>\n",
+       "      <td>3.781467</td>\n",
+       "      <td>1.575306</td>\n",
+       "      <td>0.021174</td>\n",
+       "      <td>0.019889</td>\n",
+       "      <td>3.714051</td>\n",
+       "      <td>0.716917</td>\n",
+       "      <td>0.012303</td>\n",
+       "      <td>0.006179</td>\n",
+       "      <td>3.498253</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>178</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>949154</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.664721</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.687071</td>\n",
+       "      <td>248.388020</td>\n",
+       "      <td>48.224169</td>\n",
+       "      <td>31.048502</td>\n",
+       "      <td>12.579528</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.017332</td>\n",
+       "      <td>3.884780</td>\n",
+       "      <td>1.356908</td>\n",
+       "      <td>0.018738</td>\n",
+       "      <td>0.015678</td>\n",
+       "      <td>3.836012</td>\n",
+       "      <td>0.721010</td>\n",
+       "      <td>0.011075</td>\n",
+       "      <td>0.006777</td>\n",
+       "      <td>3.563908</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>142</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>953489</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.195793</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.647971</td>\n",
+       "      <td>529.897082</td>\n",
+       "      <td>47.823053</td>\n",
+       "      <td>35.326472</td>\n",
+       "      <td>20.710882</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.012084</td>\n",
+       "      <td>3.654480</td>\n",
+       "      <td>1.778057</td>\n",
+       "      <td>0.012714</td>\n",
+       "      <td>0.010522</td>\n",
+       "      <td>3.645432</td>\n",
+       "      <td>0.669576</td>\n",
+       "      <td>0.009267</td>\n",
+       "      <td>0.005655</td>\n",
+       "      <td>3.632626</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>200 rows × 36 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     name      qid      measure     value    max-idf   avg-idf         scq  \\\n",
+       "70   BM25   100653  ndcg_cut.10  0.428160  12.908343  9.051803  598.373506   \n",
+       "85   BM25  1015624  ndcg_cut.10  0.580570  12.908343  8.369403  280.338094   \n",
+       "43   BM25  1017690  ndcg_cut.10  0.754357  12.215196  7.912693  283.592656   \n",
+       "116  BM25  1035857  ndcg_cut.10  0.652168  10.135754  7.745829  367.762077   \n",
+       "122  BM25   103830  ndcg_cut.10  0.530858  12.908343  7.721879  277.966310   \n",
+       "..    ...      ...          ...       ...        ...       ...         ...   \n",
+       "19   BM25   851124  ndcg_cut.10  0.545156  12.908343  9.099939  306.580831   \n",
+       "95   BM25   896725  ndcg_cut.10  0.360260  10.962433  7.438826  467.079609   \n",
+       "104  BM25   922849  ndcg_cut.10  0.498273  12.908343  7.112997  274.841073   \n",
+       "178  BM25   949154  ndcg_cut.10  0.664721  12.908343  8.687071  248.388020   \n",
+       "142  BM25   953489  ndcg_cut.10  0.195793  12.908343  8.647971  529.897082   \n",
+       "\n",
+       "       max-scq    avg-scq        var  ...    smv+50  clarity+50+100   wig+100  \\\n",
+       "70   50.637838  37.398344  23.617904  ...  0.014273        3.544082  1.951133   \n",
+       "85   50.578374  40.048299   9.523332  ...  0.011114        3.999061  1.929926   \n",
+       "43   49.248037  40.513237   8.418207  ...  0.013975        3.511534  1.571078   \n",
+       "116  50.625796  45.970260  15.929586  ...  0.004655        3.839171  1.919674   \n",
+       "122  50.531838  39.709473  11.214659  ...  0.005703        3.557757  1.829664   \n",
+       "..         ...        ...        ...  ...       ...             ...       ...   \n",
+       "19   49.457465  34.064537   8.378009  ...  0.007420        4.803370  1.619716   \n",
+       "95   48.917291  42.461783  12.903404  ...  0.004789        3.113233  1.477184   \n",
+       "104  46.525209  34.355134   6.537749  ...  0.005467        3.781467  1.575306   \n",
+       "178  48.224169  31.048502  12.579528  ...  0.017332        3.884780  1.356908   \n",
+       "142  47.823053  35.326472  20.710882  ...  0.012084        3.654480  1.778057   \n",
+       "\n",
+       "      nqc+100   smv+100  clarity+100+100  wig+1000  nqc+1000  smv+1000  \\\n",
+       "70   0.016508  0.009057         3.544058  0.745923  0.009943  0.006240   \n",
+       "85   0.018038  0.013737         3.935562  1.029481  0.012135  0.007093   \n",
+       "43   0.018584  0.015681         3.456468  0.938830  0.009677  0.004896   \n",
+       "116  0.006738  0.004749         3.618240  1.054783  0.012100  0.009408   \n",
+       "122  0.015672  0.013502         3.459321  0.914128  0.012781  0.007959   \n",
+       "..        ...       ...              ...       ...       ...       ...   \n",
+       "19   0.010545  0.007952         4.641726  0.926463  0.007980  0.004847   \n",
+       "95   0.008821  0.007782         3.153661  0.824822  0.007862  0.005510   \n",
+       "104  0.021174  0.019889         3.714051  0.716917  0.012303  0.006179   \n",
+       "178  0.018738  0.015678         3.836012  0.721010  0.011075  0.006777   \n",
+       "142  0.012714  0.010522         3.645432  0.669576  0.009267  0.005655   \n",
+       "\n",
+       "     clarity+1000+100  \n",
+       "70           3.544040  \n",
+       "85           3.716341  \n",
+       "43           3.187760  \n",
+       "116          3.312848  \n",
+       "122          3.326919  \n",
+       "..                ...  \n",
+       "19           4.121996  \n",
+       "95           2.968856  \n",
+       "104          3.498253  \n",
+       "178          3.563908  \n",
+       "142          3.632626  \n",
+       "\n",
+       "[200 rows x 36 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# now with all qpp predictions\n",
+    "qpp_predictions(df_eval)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Gtq7M4GvJRwi"
+   },
+   "source": [
+    "Here we now can do some evaluations, e.g., measureing correlations or similar."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "KkTNdTzvJQS4"
+   },
+   "source": [
+    "# Now, prepare this evaluation slightly bigger, on multiple datasets\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:45:40.444234Z",
+     "start_time": "2024-02-27T09:44:26.683458Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "it34eGzzJffr",
+    "outputId": "39734b7d-60df-4f36-dad9-cc9da8b573c4"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 17%|█████████████████████████████▋                                                                                                                                             | 4/23 [00:10<00:53,  2.81s/it]/home/sh3/S3806763/miniconda3/envs/tira-qpp/lib/python3.10/site-packages/pyterrier/pipelines.py:129: UserWarning: 73 topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.\n",
+      "  warn(f'{backfill_count} topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.')\n",
+      " 22%|█████████████████████████████████████▏                                                                                                                                     | 5/23 [00:13<00:54,  3.03s/it]/home/sh3/S3806763/miniconda3/envs/tira-qpp/lib/python3.10/site-packages/pyterrier/pipelines.py:129: UserWarning: 1 topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.\n",
+      "  warn(f'{backfill_count} topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.')\n",
+      " 57%|████████████████████████████████████████████████████████████████████████████████████████████████                                                                          | 13/23 [00:42<00:33,  3.37s/it]/home/sh3/S3806763/miniconda3/envs/tira-qpp/lib/python3.10/site-packages/pyterrier/pipelines.py:129: UserWarning: 1 topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.\n",
+      "  warn(f'{backfill_count} topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.')\n",
+      " 65%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                           | 15/23 [00:49<00:25,  3.23s/it]/home/sh3/S3806763/miniconda3/envs/tira-qpp/lib/python3.10/site-packages/pyterrier/pipelines.py:129: UserWarning: 1 topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.\n",
+      "  warn(f'{backfill_count} topic(s) not found in qrels. Scores for these topics are given as NaN and should not contribute to averages.')\n",
+      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 23/23 [01:13<00:00,  3.21s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "datasets = [\n",
+    "    'antique-test-20230107-training', 'argsme-touche-2021-task-1-20230209-training',\n",
+    "    'argsme-touche-2020-task-1-20230209-training',\n",
+    "    'cord19-fulltext-trec-covid-20230107-training', 'cranfield-20230107-training',\n",
+    "    'disks45-nocr-trec-robust-2004-20230209-training',\n",
+    "    'disks45-nocr-trec7-20230209-training', 'disks45-nocr-trec8-20230209-training',\n",
+    "    'gov-trec-web-2002-20230209-training',\n",
+    "    'gov-trec-web-2003-20230209-training', 'gov-trec-web-2004-20230209-training', 'gov2-trec-tb-2006-20230209-training',\n",
+    "    'gov2-trec-tb-2005-20230209-training', 'gov2-trec-tb-2004-20230209-training',\n",
+    "    'medline-2004-trec-genomics-2004-20230107-training',\n",
+    "    'medline-2004-trec-genomics-2005-20230107-training', 'medline-2017-trec-pm-2017-20230211-training',\n",
+    "    'medline-2017-trec-pm-2018-20230211-training', 'msmarco-passage-trec-dl-2019-judged-20230107-training',\n",
+    "    'msmarco-passage-trec-dl-2020-judged-20230107-training',\n",
+    "    'nfcorpus-test-20230107-training', 'vaswani-20230107-training',\n",
+    "    'wapo-v2-trec-core-2018-20230107-training'\n",
+    "]\n",
+    "df_eval = []\n",
+    "\n",
+    "for dataset in tqdm(datasets):\n",
+    "    pt_dataset = pt.get_dataset(f\"irds:ir-benchmarks/{dataset}\")\n",
+    "    bm25 = tira.pt.from_submission('ir-benchmarks/tira-ir-starter/BM25 Re-Rank (tira-ir-starter-pyterrier)', dataset)\n",
+    "    df = pt.Experiment([bm25], pt_dataset.get_topics('query'), pt_dataset.get_qrels(), names=['BM25'],\n",
+    "                       eval_metrics=['ndcg_cut.10', 'map'], perquery=True)\n",
+    "\n",
+    "    qpp_predictions = tira.pt.transform_queries('ir-benchmarks/qpptk/all-predictors', dataset)\n",
+    "    df['dataset'] = dataset\n",
+    "    df_eval += [qpp_predictions(df)]\n",
+    "df_eval = pd.concat(df_eval)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:45:40.473898Z",
+     "start_time": "2024-02-27T09:45:40.446329Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "2iEy57VaEtMI",
+    "outputId": "08f3713e-f4ce-417d-f8ad-814a3a10e940"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>qid</th>\n",
+       "      <th>measure</th>\n",
+       "      <th>value</th>\n",
+       "      <th>dataset</th>\n",
+       "      <th>max-idf</th>\n",
+       "      <th>avg-idf</th>\n",
+       "      <th>scq</th>\n",
+       "      <th>max-scq</th>\n",
+       "      <th>avg-scq</th>\n",
+       "      <th>...</th>\n",
+       "      <th>smv+50</th>\n",
+       "      <th>clarity+50+100</th>\n",
+       "      <th>wig+100</th>\n",
+       "      <th>nqc+100</th>\n",
+       "      <th>smv+100</th>\n",
+       "      <th>clarity+100+100</th>\n",
+       "      <th>wig+1000</th>\n",
+       "      <th>nqc+1000</th>\n",
+       "      <th>smv+1000</th>\n",
+       "      <th>clarity+1000+100</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>140</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>100653</td>\n",
+       "      <td>map</td>\n",
+       "      <td>0.571908</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>9.051803</td>\n",
+       "      <td>598.373506</td>\n",
+       "      <td>50.637838</td>\n",
+       "      <td>37.398344</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014273</td>\n",
+       "      <td>3.544082</td>\n",
+       "      <td>1.951133</td>\n",
+       "      <td>0.016508</td>\n",
+       "      <td>0.009057</td>\n",
+       "      <td>3.544058</td>\n",
+       "      <td>0.745923</td>\n",
+       "      <td>0.009943</td>\n",
+       "      <td>0.006240</td>\n",
+       "      <td>3.544040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>141</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>100653</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.428160</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>9.051803</td>\n",
+       "      <td>598.373506</td>\n",
+       "      <td>50.637838</td>\n",
+       "      <td>37.398344</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.014273</td>\n",
+       "      <td>3.544082</td>\n",
+       "      <td>1.951133</td>\n",
+       "      <td>0.016508</td>\n",
+       "      <td>0.009057</td>\n",
+       "      <td>3.544058</td>\n",
+       "      <td>0.745923</td>\n",
+       "      <td>0.009943</td>\n",
+       "      <td>0.006240</td>\n",
+       "      <td>3.544040</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>170</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1015624</td>\n",
+       "      <td>map</td>\n",
+       "      <td>0.667378</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.369403</td>\n",
+       "      <td>280.338094</td>\n",
+       "      <td>50.578374</td>\n",
+       "      <td>40.048299</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.011114</td>\n",
+       "      <td>3.999061</td>\n",
+       "      <td>1.929926</td>\n",
+       "      <td>0.018038</td>\n",
+       "      <td>0.013737</td>\n",
+       "      <td>3.935562</td>\n",
+       "      <td>1.029481</td>\n",
+       "      <td>0.012135</td>\n",
+       "      <td>0.007093</td>\n",
+       "      <td>3.716341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>171</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1015624</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.580570</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>12.908343</td>\n",
+       "      <td>8.369403</td>\n",
+       "      <td>280.338094</td>\n",
+       "      <td>50.578374</td>\n",
+       "      <td>40.048299</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.011114</td>\n",
+       "      <td>3.999061</td>\n",
+       "      <td>1.929926</td>\n",
+       "      <td>0.018038</td>\n",
+       "      <td>0.013737</td>\n",
+       "      <td>3.935562</td>\n",
+       "      <td>1.029481</td>\n",
+       "      <td>0.012135</td>\n",
+       "      <td>0.007093</td>\n",
+       "      <td>3.716341</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>86</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>1017690</td>\n",
+       "      <td>map</td>\n",
+       "      <td>0.606246</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>12.215196</td>\n",
+       "      <td>7.912693</td>\n",
+       "      <td>283.592656</td>\n",
+       "      <td>49.248037</td>\n",
+       "      <td>40.513237</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.013975</td>\n",
+       "      <td>3.511534</td>\n",
+       "      <td>1.571078</td>\n",
+       "      <td>0.018584</td>\n",
+       "      <td>0.015681</td>\n",
+       "      <td>3.456468</td>\n",
+       "      <td>0.938830</td>\n",
+       "      <td>0.009677</td>\n",
+       "      <td>0.004896</td>\n",
+       "      <td>3.187760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>823</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.779171</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>9.253328</td>\n",
+       "      <td>6.472552</td>\n",
+       "      <td>133.850744</td>\n",
+       "      <td>53.319835</td>\n",
+       "      <td>44.616915</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.018770</td>\n",
+       "      <td>6.755578</td>\n",
+       "      <td>4.113982</td>\n",
+       "      <td>0.024965</td>\n",
+       "      <td>0.018158</td>\n",
+       "      <td>6.492418</td>\n",
+       "      <td>1.785332</td>\n",
+       "      <td>0.057001</td>\n",
+       "      <td>0.048890</td>\n",
+       "      <td>6.120643</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>96</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>824</td>\n",
+       "      <td>map</td>\n",
+       "      <td>0.314803</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>6.043616</td>\n",
+       "      <td>2.944800</td>\n",
+       "      <td>132.174833</td>\n",
+       "      <td>54.350762</td>\n",
+       "      <td>33.043708</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.035296</td>\n",
+       "      <td>5.879690</td>\n",
+       "      <td>4.295972</td>\n",
+       "      <td>0.046101</td>\n",
+       "      <td>0.036535</td>\n",
+       "      <td>5.865900</td>\n",
+       "      <td>2.664010</td>\n",
+       "      <td>0.045072</td>\n",
+       "      <td>0.033262</td>\n",
+       "      <td>5.825797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>97</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>824</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.691973</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>6.043616</td>\n",
+       "      <td>2.944800</td>\n",
+       "      <td>132.174833</td>\n",
+       "      <td>54.350762</td>\n",
+       "      <td>33.043708</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.035296</td>\n",
+       "      <td>5.879690</td>\n",
+       "      <td>4.295972</td>\n",
+       "      <td>0.046101</td>\n",
+       "      <td>0.036535</td>\n",
+       "      <td>5.865900</td>\n",
+       "      <td>2.664010</td>\n",
+       "      <td>0.045072</td>\n",
+       "      <td>0.033262</td>\n",
+       "      <td>5.825797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>98</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>825</td>\n",
+       "      <td>map</td>\n",
+       "      <td>0.302538</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>7.867033</td>\n",
+       "      <td>5.313623</td>\n",
+       "      <td>182.362550</td>\n",
+       "      <td>58.058460</td>\n",
+       "      <td>45.590637</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020023</td>\n",
+       "      <td>6.314339</td>\n",
+       "      <td>3.748762</td>\n",
+       "      <td>0.027191</td>\n",
+       "      <td>0.021909</td>\n",
+       "      <td>6.201889</td>\n",
+       "      <td>2.259479</td>\n",
+       "      <td>0.032763</td>\n",
+       "      <td>0.025157</td>\n",
+       "      <td>5.856790</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>825</td>\n",
+       "      <td>ndcg_cut.10</td>\n",
+       "      <td>0.634952</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>7.867033</td>\n",
+       "      <td>5.313623</td>\n",
+       "      <td>182.362550</td>\n",
+       "      <td>58.058460</td>\n",
+       "      <td>45.590637</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020023</td>\n",
+       "      <td>6.314339</td>\n",
+       "      <td>3.748762</td>\n",
+       "      <td>0.027191</td>\n",
+       "      <td>0.021909</td>\n",
+       "      <td>6.201889</td>\n",
+       "      <td>2.259479</td>\n",
+       "      <td>0.032763</td>\n",
+       "      <td>0.025157</td>\n",
+       "      <td>5.856790</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4288 rows × 37 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     name      qid      measure     value  \\\n",
+       "140  BM25   100653          map  0.571908   \n",
+       "141  BM25   100653  ndcg_cut.10  0.428160   \n",
+       "170  BM25  1015624          map  0.667378   \n",
+       "171  BM25  1015624  ndcg_cut.10  0.580570   \n",
+       "86   BM25  1017690          map  0.606246   \n",
+       "..    ...      ...          ...       ...   \n",
+       "95   BM25      823  ndcg_cut.10  0.779171   \n",
+       "96   BM25      824          map  0.314803   \n",
+       "97   BM25      824  ndcg_cut.10  0.691973   \n",
+       "98   BM25      825          map  0.302538   \n",
+       "99   BM25      825  ndcg_cut.10  0.634952   \n",
+       "\n",
+       "                                      dataset    max-idf   avg-idf  \\\n",
+       "140            antique-test-20230107-training  12.908343  9.051803   \n",
+       "141            antique-test-20230107-training  12.908343  9.051803   \n",
+       "170            antique-test-20230107-training  12.908343  8.369403   \n",
+       "171            antique-test-20230107-training  12.908343  8.369403   \n",
+       "86             antique-test-20230107-training  12.215196  7.912693   \n",
+       "..                                        ...        ...       ...   \n",
+       "95   wapo-v2-trec-core-2018-20230107-training   9.253328  6.472552   \n",
+       "96   wapo-v2-trec-core-2018-20230107-training   6.043616  2.944800   \n",
+       "97   wapo-v2-trec-core-2018-20230107-training   6.043616  2.944800   \n",
+       "98   wapo-v2-trec-core-2018-20230107-training   7.867033  5.313623   \n",
+       "99   wapo-v2-trec-core-2018-20230107-training   7.867033  5.313623   \n",
+       "\n",
+       "            scq    max-scq    avg-scq  ...    smv+50  clarity+50+100  \\\n",
+       "140  598.373506  50.637838  37.398344  ...  0.014273        3.544082   \n",
+       "141  598.373506  50.637838  37.398344  ...  0.014273        3.544082   \n",
+       "170  280.338094  50.578374  40.048299  ...  0.011114        3.999061   \n",
+       "171  280.338094  50.578374  40.048299  ...  0.011114        3.999061   \n",
+       "86   283.592656  49.248037  40.513237  ...  0.013975        3.511534   \n",
+       "..          ...        ...        ...  ...       ...             ...   \n",
+       "95   133.850744  53.319835  44.616915  ...  0.018770        6.755578   \n",
+       "96   132.174833  54.350762  33.043708  ...  0.035296        5.879690   \n",
+       "97   132.174833  54.350762  33.043708  ...  0.035296        5.879690   \n",
+       "98   182.362550  58.058460  45.590637  ...  0.020023        6.314339   \n",
+       "99   182.362550  58.058460  45.590637  ...  0.020023        6.314339   \n",
+       "\n",
+       "      wig+100   nqc+100   smv+100  clarity+100+100  wig+1000  nqc+1000  \\\n",
+       "140  1.951133  0.016508  0.009057         3.544058  0.745923  0.009943   \n",
+       "141  1.951133  0.016508  0.009057         3.544058  0.745923  0.009943   \n",
+       "170  1.929926  0.018038  0.013737         3.935562  1.029481  0.012135   \n",
+       "171  1.929926  0.018038  0.013737         3.935562  1.029481  0.012135   \n",
+       "86   1.571078  0.018584  0.015681         3.456468  0.938830  0.009677   \n",
+       "..        ...       ...       ...              ...       ...       ...   \n",
+       "95   4.113982  0.024965  0.018158         6.492418  1.785332  0.057001   \n",
+       "96   4.295972  0.046101  0.036535         5.865900  2.664010  0.045072   \n",
+       "97   4.295972  0.046101  0.036535         5.865900  2.664010  0.045072   \n",
+       "98   3.748762  0.027191  0.021909         6.201889  2.259479  0.032763   \n",
+       "99   3.748762  0.027191  0.021909         6.201889  2.259479  0.032763   \n",
+       "\n",
+       "     smv+1000  clarity+1000+100  \n",
+       "140  0.006240          3.544040  \n",
+       "141  0.006240          3.544040  \n",
+       "170  0.007093          3.716341  \n",
+       "171  0.007093          3.716341  \n",
+       "86   0.004896          3.187760  \n",
+       "..        ...               ...  \n",
+       "95   0.048890          6.120643  \n",
+       "96   0.033262          5.825797  \n",
+       "97   0.033262          5.825797  \n",
+       "98   0.025157          5.856790  \n",
+       "99   0.025157          5.856790  \n",
+       "\n",
+       "[4288 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_eval"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:45:40.501808Z",
+     "start_time": "2024-02-27T09:45:40.475513Z"
+    },
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+     "height": 424
+    },
+    "id": "kaHsxq5PmMei",
+    "outputId": "80bb46e5-1115-4764-9902-dba47c05924a"
+   },
+   "outputs": [
+    {
+     "data": {
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+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>dataset</th>\n",
+       "      <th>qid</th>\n",
+       "      <th>ndcg@10</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>141</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>100653</td>\n",
+       "      <td>0.428160</td>\n",
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+       "    <tr>\n",
+       "      <th>171</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
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+       "    <tr>\n",
+       "      <th>87</th>\n",
+       "      <td>BM25</td>\n",
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+       "      <td>1017690</td>\n",
+       "      <td>0.754357</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>233</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>1035857</td>\n",
+       "      <td>0.652168</td>\n",
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+       "    <tr>\n",
+       "      <th>245</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>103830</td>\n",
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+       "    <tr>\n",
+       "      <th>...</th>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>821</td>\n",
+       "      <td>0.447272</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>93</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>822</td>\n",
+       "      <td>0.521296</td>\n",
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+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>823</td>\n",
+       "      <td>0.779171</td>\n",
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+       "    <tr>\n",
+       "      <th>97</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>824</td>\n",
+       "      <td>0.691973</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>BM25</td>\n",
+       "      <td>wapo-v2-trec-core-2018-20230107-training</td>\n",
+       "      <td>825</td>\n",
+       "      <td>0.634952</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2144 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     name                                   dataset      qid   ndcg@10\n",
+       "141  BM25            antique-test-20230107-training   100653  0.428160\n",
+       "171  BM25            antique-test-20230107-training  1015624  0.580570\n",
+       "87   BM25            antique-test-20230107-training  1017690  0.754357\n",
+       "233  BM25            antique-test-20230107-training  1035857  0.652168\n",
+       "245  BM25            antique-test-20230107-training   103830  0.530858\n",
+       "..    ...                                       ...      ...       ...\n",
+       "91   BM25  wapo-v2-trec-core-2018-20230107-training      821  0.447272\n",
+       "93   BM25  wapo-v2-trec-core-2018-20230107-training      822  0.521296\n",
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+       "99   BM25  wapo-v2-trec-core-2018-20230107-training      825  0.634952\n",
+       "\n",
+       "[2144 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ap_df = df_eval.loc[df_eval['measure'] == 'map', ['name', 'dataset', 'qid', 'value']].rename({'value': 'map'}, axis=1)\n",
+    "ndcg_10_df = df_eval.loc[df_eval['measure'] == 'ndcg_cut.10', ['name', 'dataset', 'qid', 'value']].rename(\n",
+    "    {'value': 'ndcg@10'}, axis=1)\n",
+    "ndcg_10_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:45:40.505660Z",
+     "start_time": "2024-02-27T09:45:40.503241Z"
+    },
+    "id": "a2FNhMMWn3sp"
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:45:40.541559Z",
+     "start_time": "2024-02-27T09:45:40.507058Z"
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+    "id": "1eVIWHT6kbqU",
+    "outputId": "c4f5abb4-8b89-41bd-9193-17aee9c3bcc1"
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+    {
+     "data": {
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+       "      <th></th>\n",
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+       "      <td>3.266062</td>\n",
+       "      <td>0.002495</td>\n",
+       "      <td>0.002357</td>\n",
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+       "      <td>0.011908</td>\n",
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+       "      <td>0.007093</td>\n",
+       "      <td>3.716341</td>\n",
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+       "      <td>3.266062</td>\n",
+       "      <td>0.002495</td>\n",
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+       "      <td>0.013737</td>\n",
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+       "      <td>1.029481</td>\n",
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+       "      <td>0.007093</td>\n",
+       "      <td>3.716341</td>\n",
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+       "      <td>0.011821</td>\n",
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+       "      <td>3.511534</td>\n",
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+       "      <td>0.018584</td>\n",
+       "      <td>0.015681</td>\n",
+       "      <td>3.456468</td>\n",
+       "      <td>0.938830</td>\n",
+       "      <td>0.009677</td>\n",
+       "      <td>0.004896</td>\n",
+       "      <td>3.187760</td>\n",
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+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>5.529098</td>\n",
+       "      <td>0.013639</td>\n",
+       "      <td>0.010667</td>\n",
+       "      <td>8.384763</td>\n",
+       "      <td>5.237965</td>\n",
+       "      <td>0.017567</td>\n",
+       "      <td>0.014289</td>\n",
+       "      <td>7.664940</td>\n",
+       "      <td>4.947712</td>\n",
+       "      <td>0.019486</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.018770</td>\n",
+       "      <td>6.755578</td>\n",
+       "      <td>4.113982</td>\n",
+       "      <td>0.024965</td>\n",
+       "      <td>0.018158</td>\n",
+       "      <td>6.492418</td>\n",
+       "      <td>1.785332</td>\n",
+       "      <td>0.057001</td>\n",
+       "      <td>0.048890</td>\n",
+       "      <td>6.120643</td>\n",
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+       "    <tr>\n",
+       "      <th>96</th>\n",
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+       "      <td>6.011216</td>\n",
+       "      <td>5.565914</td>\n",
+       "      <td>0.025530</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.035296</td>\n",
+       "      <td>5.879690</td>\n",
+       "      <td>4.295972</td>\n",
+       "      <td>0.046101</td>\n",
+       "      <td>0.036535</td>\n",
+       "      <td>5.865900</td>\n",
+       "      <td>2.664010</td>\n",
+       "      <td>0.045072</td>\n",
+       "      <td>0.033262</td>\n",
+       "      <td>5.825797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>97</th>\n",
+       "      <td>6.094802</td>\n",
+       "      <td>0.014414</td>\n",
+       "      <td>0.012791</td>\n",
+       "      <td>5.968235</td>\n",
+       "      <td>5.895828</td>\n",
+       "      <td>0.016362</td>\n",
+       "      <td>0.013797</td>\n",
+       "      <td>6.011216</td>\n",
+       "      <td>5.565914</td>\n",
+       "      <td>0.025530</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.035296</td>\n",
+       "      <td>5.879690</td>\n",
+       "      <td>4.295972</td>\n",
+       "      <td>0.046101</td>\n",
+       "      <td>0.036535</td>\n",
+       "      <td>5.865900</td>\n",
+       "      <td>2.664010</td>\n",
+       "      <td>0.045072</td>\n",
+       "      <td>0.033262</td>\n",
+       "      <td>5.825797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>98</th>\n",
+       "      <td>5.064507</td>\n",
+       "      <td>0.003857</td>\n",
+       "      <td>0.003020</td>\n",
+       "      <td>7.272382</td>\n",
+       "      <td>4.962457</td>\n",
+       "      <td>0.006068</td>\n",
+       "      <td>0.005158</td>\n",
+       "      <td>6.847458</td>\n",
+       "      <td>4.699434</td>\n",
+       "      <td>0.015013</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020023</td>\n",
+       "      <td>6.314339</td>\n",
+       "      <td>3.748762</td>\n",
+       "      <td>0.027191</td>\n",
+       "      <td>0.021909</td>\n",
+       "      <td>6.201889</td>\n",
+       "      <td>2.259479</td>\n",
+       "      <td>0.032763</td>\n",
+       "      <td>0.025157</td>\n",
+       "      <td>5.856790</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>5.064507</td>\n",
+       "      <td>0.003857</td>\n",
+       "      <td>0.003020</td>\n",
+       "      <td>7.272382</td>\n",
+       "      <td>4.962457</td>\n",
+       "      <td>0.006068</td>\n",
+       "      <td>0.005158</td>\n",
+       "      <td>6.847458</td>\n",
+       "      <td>4.699434</td>\n",
+       "      <td>0.015013</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.020023</td>\n",
+       "      <td>6.314339</td>\n",
+       "      <td>3.748762</td>\n",
+       "      <td>0.027191</td>\n",
+       "      <td>0.021909</td>\n",
+       "      <td>6.201889</td>\n",
+       "      <td>2.259479</td>\n",
+       "      <td>0.032763</td>\n",
+       "      <td>0.025157</td>\n",
+       "      <td>5.856790</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4288 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        wig+5     nqc+5     smv+5  clarity+5+100    wig+10    nqc+10  \\\n",
+       "140  5.114781  0.000341  0.000256       3.856976  4.320086  0.021442   \n",
+       "141  5.114781  0.000341  0.000256       3.856976  4.320086  0.021442   \n",
+       "170  3.266062  0.002495  0.002357       4.257047  3.025123  0.009375   \n",
+       "171  3.266062  0.002495  0.002357       4.257047  3.025123  0.009375   \n",
+       "86   2.891790  0.009229  0.008948       4.269795  2.691789  0.009796   \n",
+       "..        ...       ...       ...            ...       ...       ...   \n",
+       "95   5.529098  0.013639  0.010667       8.384763  5.237965  0.017567   \n",
+       "96   6.094802  0.014414  0.012791       5.968235  5.895828  0.016362   \n",
+       "97   6.094802  0.014414  0.012791       5.968235  5.895828  0.016362   \n",
+       "98   5.064507  0.003857  0.003020       7.272382  4.962457  0.006068   \n",
+       "99   5.064507  0.003857  0.003020       7.272382  4.962457  0.006068   \n",
+       "\n",
+       "       smv+10  clarity+10+100    wig+20    nqc+20  ...    smv+50  \\\n",
+       "140  0.019348        3.544212  3.190317  0.025751  ...  0.014273   \n",
+       "141  0.019348        3.544212  3.190317  0.025751  ...  0.014273   \n",
+       "170  0.008483        4.113981  2.743009  0.011908  ...  0.011114   \n",
+       "171  0.008483        4.113981  2.743009  0.011908  ...  0.011114   \n",
+       "86   0.008685        3.880512  2.422779  0.011821  ...  0.013975   \n",
+       "..        ...             ...       ...       ...  ...       ...   \n",
+       "95   0.014289        7.664940  4.947712  0.019486  ...  0.018770   \n",
+       "96   0.013797        6.011216  5.565914  0.025530  ...  0.035296   \n",
+       "97   0.013797        6.011216  5.565914  0.025530  ...  0.035296   \n",
+       "98   0.005158        6.847458  4.699434  0.015013  ...  0.020023   \n",
+       "99   0.005158        6.847458  4.699434  0.015013  ...  0.020023   \n",
+       "\n",
+       "     clarity+50+100   wig+100   nqc+100   smv+100  clarity+100+100  wig+1000  \\\n",
+       "140        3.544082  1.951133  0.016508  0.009057         3.544058  0.745923   \n",
+       "141        3.544082  1.951133  0.016508  0.009057         3.544058  0.745923   \n",
+       "170        3.999061  1.929926  0.018038  0.013737         3.935562  1.029481   \n",
+       "171        3.999061  1.929926  0.018038  0.013737         3.935562  1.029481   \n",
+       "86         3.511534  1.571078  0.018584  0.015681         3.456468  0.938830   \n",
+       "..              ...       ...       ...       ...              ...       ...   \n",
+       "95         6.755578  4.113982  0.024965  0.018158         6.492418  1.785332   \n",
+       "96         5.879690  4.295972  0.046101  0.036535         5.865900  2.664010   \n",
+       "97         5.879690  4.295972  0.046101  0.036535         5.865900  2.664010   \n",
+       "98         6.314339  3.748762  0.027191  0.021909         6.201889  2.259479   \n",
+       "99         6.314339  3.748762  0.027191  0.021909         6.201889  2.259479   \n",
+       "\n",
+       "     nqc+1000  smv+1000  clarity+1000+100  \n",
+       "140  0.009943  0.006240          3.544040  \n",
+       "141  0.009943  0.006240          3.544040  \n",
+       "170  0.012135  0.007093          3.716341  \n",
+       "171  0.012135  0.007093          3.716341  \n",
+       "86   0.009677  0.004896          3.187760  \n",
+       "..        ...       ...               ...  \n",
+       "95   0.057001  0.048890          6.120643  \n",
+       "96   0.045072  0.033262          5.825797  \n",
+       "97   0.045072  0.033262          5.825797  \n",
+       "98   0.032763  0.025157          5.856790  \n",
+       "99   0.032763  0.025157          5.856790  \n",
+       "\n",
+       "[4288 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pre_ret_predictors = df_eval.columns[5:13]\n",
+    "post_ret_predictors = df_eval.columns[13:].str.split('+').str[0].unique()\n",
+    "post_ret_predictors\n",
+    "\n",
+    "pre_qpp_df = df_eval.iloc[:, 5:13]\n",
+    "post_qpp_df = df_eval.iloc[:, 13:]\n",
+    "post_qpp_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T11:08:27.690453Z",
+     "start_time": "2024-02-27T11:08:27.673798Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 721
+    },
+    "id": "rrGwcml4npj8",
+    "outputId": "fc29895b-22e4-4f4a-9147-0d16e6e8e3bf"
+   },
+   "outputs": [],
+   "source": [
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from scipy.stats import rankdata\n",
+    "import numpy.typing as npt\n",
+    "\n",
+    "PlotNames = {'scq': 'SCQ', 'avg-scq': 'AvgSCQ', 'max-scq': 'MaxSCQ', 'var': 'SumVAR', 'avg-var': 'AvgVAR',\n",
+    "             'max-var': 'MaxVAR', 'max-idf': 'MaxIDF', 'avg-idf': 'AvgIDF', 'clarity': 'Clarity', 'smv': 'SMV',\n",
+    "             'nqc': 'NQC', 'wig': 'WIG', 'qf': 'QF', 'uef-clarity': 'UEF(Clarity)', 'uef-smv': 'UEF(SMV)',\n",
+    "             'uef-nqc': 'UEF(NQC)', 'uef-wig': 'UEF(WIG)', 'uef-qf': 'UEF(QF)', 'sd': 'SD', 'mean': 'Mean',\n",
+    "             'entropy': 'Entropy', 'kl': 'KL', 'skew': 'Skew', 'kurtosis': 'Kurtosis', 'ap@1000': 'AP',\n",
+    "             'ndcg@10': 'nDCG@10', 'title': 'Title Queries', 'vars': 'Query Variants', 'lovins': r'\\texttt{lovins}',\n",
+    "             'porter': r'\\texttt{porter}', 'nostem': r'\\texttt{nostem}', 'indri': r'\\texttt{indri}',\n",
+    "             'nostop': r'\\texttt{nostop}', 'lingpipe': r'\\texttt{lingpipe}', 'atire': r'\\texttt{atire}',\n",
+    "             'zettair': r'\\texttt{zettair}'}\n",
+    "\n",
+    "plt.rcParams.update(plt.rcParamsDefault)\n",
+    "paper_fmt = {\n",
+    "    \"font.family\": [\"Linux Libertine O\"],\n",
+    "    \"font.serif\": [\"Linux Libertine O\"],\n",
+    "    \"font.sans-serif\": \"Linux Biolinum\",\n",
+    "    'font.size': 12,\n",
+    "    'pdf.fonttype': 42,\n",
+    "    #     'figure.facecolor': (0.98, 0.98, 0.98),\n",
+    "    #     'figure.facecolor':'#212121',\n",
+    "    #     'text.color': '#23373b',\n",
+    "    #     'axes.labelcolor': 'white',\n",
+    "    #     'xtick.color': 'white',\n",
+    "    #     'ytick.color': 'white',\n",
+    "    #     'axes.titlecolor':'white',\n",
+    "    'figure.dpi': 300,\n",
+    "    'savefig.dpi': 300,\n",
+    "    'figure.figsize': (8, 2),\n",
+    "    'legend.borderaxespad': 0.5,\n",
+    "    'legend.fontsize': 'small',\n",
+    "    'legend.title_fontsize': 'small',\n",
+    "    #     'legend.facecolor':'white',\n",
+    "    #     \"axes.labelpad\": 20.0\n",
+    "    \"axes.labelpad\": 5.0,\n",
+    "    #     'axes.titlesize':'medium',\n",
+    "    #     'axes.labelsize':'medium'\n",
+    "}\n",
+    "plt.rcParams.update(paper_fmt)\n",
+    "\n",
+    "\n",
+    "def calc_sare(x: npt.ArrayLike, y: npt.ArrayLike) -> npt.NDArray[np.float64]:\n",
+    "    \"\"\"\n",
+    "    Calculate the scaled Absolute Rank Error (sARE) between two arrays.\n",
+    "    \"\"\"\n",
+    "    assert len(x) == len(y), f'Lengths of a and b must be equal: {len(x)} != {len(y)}'\n",
+    "    return abs(rankdata(x, method='average') - rankdata(y, method='average')) / len(x)\n",
+    "\n",
+    "\n",
+    "def calc_smare(x: npt.ArrayLike, y: npt.ArrayLike) -> float:\n",
+    "    \"\"\"\n",
+    "    Calculate the scaled Mean Absolute Rank Error (sMARE) between two arrays.\n",
+    "    \"\"\"\n",
+    "    return calc_sare(x, y).mean()\n",
+    "\n",
+    "\n",
+    "def calc_correlations(df, corr_method='pearson'):\n",
+    "    if corr_method == 'smare':\n",
+    "        corr_func = calc_smare\n",
+    "    else:\n",
+    "        corr_func = corr_method\n",
+    "    _df = df.groupby(['measure', 'dataset']).corr(method=corr_func, numeric_only=True).drop(columns='value')\n",
+    "    _df = _df.loc[_df.index.get_level_values(2) == 'value'].droplevel(2).stack().reset_index().rename(\n",
+    "        columns={'level_2': 'qpp+params', 0: corr_method})\n",
+    "    return _df.assign(QPP=_df['qpp+params'].str.split('+').str[0])\n",
+    "\n",
+    "\n",
+    "def plot_pre_qpp_boxplot(corr_df, qpp_methods, measure):\n",
+    "    pre_order = corr_df.loc[corr_df['QPP'].isin(qpp_methods)].groupby('QPP')[measure].mean().index\n",
+    "    ax = sns.boxplot(data=corr_df.set_index('QPP').loc[pre_order].rename(PlotNames), x='QPP', y=measure, hue='measure')\n",
+    "    # annotate the boxplot outliers (fliers)\n",
+    "    for i, artist in enumerate(ax.artists):\n",
+    "        x = []\n",
+    "        y = []\n",
+    "        for j in range(i * 6, i * 6 + 6):\n",
+    "            line = ax.lines[j]\n",
+    "            x.extend(line.get_xdata())\n",
+    "            y.extend(line.get_ydata())\n",
+    "        y = [y[i] for i in range(len(y)) if i % 6 == 0]\n",
+    "        x = [x[i] for i in range(len(x)) if i % 6 == 0]\n",
+    "        for i in range(len(x)):\n",
+    "            ax.text(x[i], y[i], f'{y[i]:.2f}', ha='center', va='bottom', fontsize=8, color='black')\n",
+    "    plt.xticks(rotation=45)\n",
+    "\n",
+    "    plt.title('Pre-Retrieval Predictors')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T11:04:25.957032Z",
+     "start_time": "2024-02-27T11:04:10.819596Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>measure</th>\n",
+       "      <th>dataset</th>\n",
+       "      <th>qpp+params</th>\n",
+       "      <th>smare</th>\n",
+       "      <th>QPP</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>map</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>max-idf</td>\n",
+       "      <td>0.309125</td>\n",
+       "      <td>max-idf</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>map</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>avg-idf</td>\n",
+       "      <td>0.316800</td>\n",
+       "      <td>avg-idf</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>map</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>scq</td>\n",
+       "      <td>0.327675</td>\n",
+       "      <td>scq</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>map</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>max-scq</td>\n",
+       "      <td>0.266175</td>\n",
+       "      <td>max-scq</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>map</td>\n",
+       "      <td>antique-test-20230107-training</td>\n",
+       "      <td>avg-scq</td>\n",
+       "      <td>0.300750</td>\n",
+       "      <td>avg-scq</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  measure                         dataset qpp+params     smare      QPP\n",
+       "0     map  antique-test-20230107-training    max-idf  0.309125  max-idf\n",
+       "1     map  antique-test-20230107-training    avg-idf  0.316800  avg-idf\n",
+       "2     map  antique-test-20230107-training        scq  0.327675      scq\n",
+       "3     map  antique-test-20230107-training    max-scq  0.266175  max-scq\n",
+       "4     map  antique-test-20230107-training    avg-scq  0.300750  avg-scq"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pearson_df = calc_correlations(df_eval, 'pearson')\n",
+    "kendall_df = calc_correlations(df_eval, 'kendall')\n",
+    "smare_df = calc_correlations(df_eval, 'smare')\n",
+    "smare_df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T11:09:17.256906Z",
+     "start_time": "2024-02-27T11:09:15.511670Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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DDz+U+Pm7UmZmpsPc9u/fX6I4ERERdjEeffTRUuf1xx9/GLfeeqtTx9HX19d47733jOzs7ELjOTpnnP2xWCzG+++/b4uVkpJiTJw40ejfv78RFBRkuLm52e2zadMmW/9Dhw4Z//nPfxzGvv76642cnBxb3x07dhjTp083nn32WeO2224zGjVq5JL3TE5OjvHpp586fA86+rnuuuuMX3/91WGs1NRUo3r16k4fvwYNGhj5+fkOY+3Zs8epGLfcckuhzy09Pd34+OOPjcDAQKditW3b1vjzzz9LfAwNwzCaNGliitWkSZNSxSmNsWPH2j2XgQMHljjO2rVr7eLUqVPHyMjIMPU7duyY8eabbxr3339/oZ9pJ06csPXfvn27ERIS4rDfPffcU+g5cKG///7buO+++5x6HatXr2689NJLRmpqaomPwfnnN2zYMKNatWql/mwYN25cofH3799vzJ4924iIiDDuvPNOIzAw0LBYLKb9v/jiixLnnZ+fb3z77bdGy5YtncrRy8vLGDhwoHHw4EG7WAcOHCj1c5dkNG7c2Dhz5kyxOaenpxvjxo0r9N9XRz89evQwdu/e7dQx+fvvv41x48YZd999t8PPTB8fHyMvL8/W/5dffrF7L5//GTlyZJFjrVmzxrj55ptLdJzatGnj1PMAAAAAXIHCBgAAAABwAVcUNmRnZxv169c3xXB3dzf27dtn13fw4MFFXmxo166dre+7775bZN+bbrqpyLxSU1ONPn362Pq7ubkZffr0MZYtW2b8888/xs6dO42FCxcaN9xwg13st99+u0THwJVcUdhw7Ngxw9fX17R/7dq1jX///bfE+eTn5xtvvfWW6QJghw4djNmzZxtxcXFGfHy88fPPPxsPPvigXc533323kZWV5TBuenq6cerUKdvPTTfdZLf/hY9f+FPwgu+RI0eKvZD1/fff2/oWV+iycuVKW+ynn3662Nglfc+cOHHCuOWWW2z7e3p6GgMHDjSio6ON+Ph4Y9u2bcbs2bPtLpS6ubkZX3/9tcOYycnJxsqVK43evXsXmmeXLl2MtWvXGmlpaUXmd+bMGWPDhg1Gz5497S7Ivv7668aff/5ZaNFKTEyMqaDhP//5j/HJJ58Yf/31l3Ho0CEjNjbW+OKLL4xWrVqZYtesWbNUxQ2XQmHDmDFj7OK89tprdv1+++23Ys/FLVu2GIZhGHFxcUZAQECRfffs2VNkXl988YXh6elp6x8UFGR8/PHHxtatW40DBw4Yq1atMoYOHWpXSNSxY0cjKSmpRMfghx9+MH1mXXnllcZbb71lbNy40Thy5Iixd+9eY8WKFcbQoUNNORX8Kaqw4Z133in2+JW0sCE5Odm46667TDF69+5tLF682Ni7d68RFxdnLFiwwLjtttvsxgoICDC2bdtmipefn2/6rFu8eLHdfmPGjHH4uZiQkOBUscr69euNhg0b2uI1bNjQePvtt43ffvvNOHjwoBEbG2t8++23xv33329XZOLp6Wm89dZbxY7z9ddfF3usz58ja9asMby8vArtV61aNSM9Pd3hOB9++KGp75VXXmn873//M/766y/bOTpw4EC7wq/69es79wIDAAAALkBhAwAAAAC4gCsKGz7//HO7GKNGjXLY988//zTeffddo1+/foaHh4fdfq1btzYMwzC+/PLLYi+K3HzzzYXmdPLkSdOdyoGBgUZcXJzDvnl5ecaLL75oF/+rr74q0XFwlbIWNqSlpRlhYWF2F6NKM6tAbm6u8fDDD9vi+Pj4GN9++22h/ZcuXWq4u7ubxn7iiSecGqtLly52z9lZ2dnZxvTp040XXnjBaN26tcPjN3fuXCMjI8No06ZNsedWVFSULfbatWuNYcOGGR06dCi0f0mO7Z49e0x3MN9www3G4cOHHfbNysoyHnnkEdNYFovFWLt2bZFjODqfJRU640Nh/v77b9u+VqvV2LFjR5H9Y2JijJo1a9r2+e9//1voBdAzZ84Y7dq1M+XXpEmTQgthCnOxFzYkJibaFSE1adLE4V33SUlJxtSpU43nnnvOaNCggcPXeMOGDcaJEyeMevXqFXue7927t9C8LjyH3N3djY8++qjQ13Lz5s2m112S0b17d6cushuGYURGRpr27d+/v5GSklJo/7///rvQ2RGKKmzYsmWLMXLkyCJnnilJYcORI0eMa665xravt7e3sXjxYod98/LyjIEDB9qN16pVKyM3N7fQMdasWVOi51icn376yTRLwx133FHkDBt//fWXw2MdERFR5Ot75MgRY/LkycYzzzxj1KlTx+GxPn78uLFz506jRo0aRZ6n7u7udsVs55/Lhf2aNWtmnDx50mE+W7duNa644gpTXwAAAKCiUNgAAAAAAC5Q1sKGHTt22F2UCw0NNc6ePVvsvps2bbIbu3HjxkZ8fLxhtVoNScYLL7xgJCQkGK+//rpd388++8xh3KysLNPd8HXq1DEOHDhQZC55eXlG+/btTfGvuOIKIzk52elj4SplKWzYuHGjcf3115v2q1+/vrF69epS5VLwTvIlS5YUu8/IkSMdXmwtTlkKGy6Ul5dn3HnnnXaxZs6cafz3v/+1XTjeunWrsXXrVrtCiMDAQIcX0QzDML799luHr42z75nTp0+bZioIDAws9s72jIwMu4vU11xzTZEXQ8+ePevwYuSsWbOcyvO8Cy+qzpw5s8i+2dnZRosWLUzjFbwbvaA//vjDLsfJkyeXKMeLubAhJyfHuP322037e3p6Gn/88Uex+549e9buM0uSsWrVKtv5f+211xr79u0zfvnlF7tz6Kabbir0wvTHH39s6jtlypRi8/nggw/scpk3b16x+xW8s//ee+81LQVTmKNHjzpczsjZi/4bN260K8KSnC9sSE9Pt/us/e6774rcp7BlJqKjowvdx5WFDdu2bTPNdhEcHOxUIdG///7rcJmI//3vf06Nm5yc7LDQ5u+//zauu+46Q5Jx2223GUePHjW+//57uyKZ/v3728XMz8+3W2aluH+fVq9ebesbFBTkVO4AAACAK1DYAAAAAAAuUNrChvz8fOP777+3m+r85ptvNq3xXpwbb7zRbvzzywQ8+eSTpr6ffPKJUa9ePcPb29v4v//7P9P63BcaOnRoqS5UTZs2zS6Xzz//3Onn4irOFDakpaUZ+/fvNzZv3mz8+OOPxttvv20q5jj/c8899xinTp0qVR7z588v1QXbXbt22eUxYMCAYvdzVWGDYRjGsmXLCj2vatasaVon/vjx40Z4eLjh5uZmtGvXrtCZPc5r27Ztqd8zvXr1KvF+huH4AnpRF0MNw/7itHTu7uySeOqppwxJRsuWLYsspDAMw/j+++/txtu8eXOxYxS8OFzcEjMFXayFDQcPHjS6du1q2tfX19dYvny50+M7eo3PF5c0aNDA9Fm8e/duo2PHjobFYjG6dOlS6Cwhv//+u+mCf5cuXZyaeSElJcWuUOCWW24pcp8///zTdKG9Xr16Rc7UUNDbb79dpov+d999d6kLGwrOpHL//fc7tV/jxo3txiysSM8wXFfYkJmZaQQHB5vilKTgLSYmxrQckXRuhgpHS0454mi5lfPnart27UzFZL/99pvRpk0bw83Nzbj33nsdFn/t37/fLl5CQkKxeYSHhxvSuaIfAAAAoKK4CQAAAABQLvbs2aNjx47p7NmzysvLk2EYyszM1L///qt169Zp4sSJuvbaa3XvvfcqISFBkmSxWDRkyBCtWrVKV1xxhdNjXXXVVXZt+/bt03XXXadJkyaZ2p966ikdOXJEZ86c0RtvvCE3N/v/GsbFxenTTz+1bTdu3FgPP/ywU7ncfPPNdm3ff/+9U/tWhGbNmslischisahmzZpq1qyZOnTooDvvvFMvvviifvvtN0nnXou7775bUVFR+v777xUQEFDisbKysjRmzBhT24svvujUvq1bt1adOnVMbYsXL5ZhGCXOo7QKO68kaebMmWrdurWtvV69elq5cqXS09O1detWtWnTpsjYjRs3LlVOK1as0PLly23bnTp1UpcuXZzatzTn5sCBA+Xr62tq+/nnn3Xy5EmnxkxPT9e8efMkSWPGjJG7u3uR/ffs2WPX9vfffxc7zn/+8x/T9qZNm5SSkuJUjlXRqVOn9M8//ygtLU25ubnKz89XTk6OTp8+rbi4OH355Zd64IEH1Lx5c61Zs8a2X5s2bbRhwwb17NnT6bEcnef//POP3N3dtWDBAtNncevWrbVx40ZlZGRo7dq1atiwod2+hmHo2WefVV5enq3tpZdeksViKTYXq9Wqdu3amdp+++03nTp1ymF/wzA0atQoZWdn29qGDx8uq9Va7FjntWjRwum+jpT2vbxp0yZ99dVXprZx48Y5tW/Hjh3t2q6//vpS5VESH3/8seLi4mzbV199tW699Van97/22mvt/i3NzMxURESEU/sXdq76+vrq22+/lbe3t6395ptvVlxcnNLT07Vo0SLVqlXLbt9///3Xru383yNFue+++yRJXl5eTuUNAAAAuEK1yk4AAAAAAC5VTz31VIn69+nTRxMmTFBwcHCJx/Lz83PY/umnnzq88ODu7l7kBdYXXnhB+fn5tu17771XHh4eTuVSr149u7b4+Hin9q1K6tWrp6+++sruonZJfPTRRzp06JBtu127dqZigKJYLBbVq1dPp0+ftrWlpaXp1KlTJSp6KYvCzqu77rpLffv2dfiYsxe6ateuXeJ88vPzNXbsWFPbAw884NQFY6l052aNGjU0aNAgTZ482daWm5urr776Ss8//3yxY86dO1fJycny9/fXgAEDiu3ftm1bu5y7du1a7H4FPzfy8vK0Z88e3XDDDcXuWxUtX77cVMBSnFatWunVV1/VQw89VGzxSEGFnefDhg3TTTfd5PCxos7z7777Tps3b7Zt165dW2FhYU7n4+g83b9/v+rWrWvX/sMPP9iKsc576KGHnB5Lkvz9/UvUv6DSvJelc//OXKht27ZO//v33HPPKTo6WklJSbJarXrzzTd13XXXlSoPZ+Xk5OjDDz80td1xxx1Of/6cN3r0aH399demtsWLF+vYsWOqX79+kfsWdq6OGzeu0AKVos5VR4U5v/32W7H/Tt1zzz3as2dPhRSTAAAAAOdR2AAAAAAA5aRPnz5KSEjQtm3blJycbGuvXr26AgICFBAQoOuuu049evRQWFiYw4tWznI060Lfvn1LdVHzxIkTdhcUr7/+eqfu4pSkv/76y67t8OHDMgyjxBeAysPGjRtVq1YtpaSk6OjRo1q/fr2+++47uwvcx48f17hx4/TBBx+UeqwvvvjCtB0aGur0cTx9+rQSExPt2g8fPlxhhQ2OzitJeuedd8otdlH++usvbd++3dTWvn17p46pYRjaunWrXfvhw4eL3ffpp582FTZI52aseO6554o8pw3D0NSpUyVJTz75pOlu6sLcdttt+uabb7R+/Xo1adJEjz32mFMXnh1dXHZ0/lwsgoOD1apVK/3xxx86fvy4cnNzJZ0r+KlTp44CAgIUGBio7t27Kzw8XMHBwaX+fHF0Lnp5eenVV18tVTxH7/ukpCSn9k1LS9PRo0ft2g8fPqwOHTrYtX/22Wem7bp166pZs2YlyFZl/lwuzXs5Pj5ea9euNbWVpPgjNDRUx44d07///qurrrpK1atXL3EOJbV8+XIdOXLE1OZo5ojitG3bVs2bN7fNfiOdK0T66quv7Aq3CnJ0rBs0aKBnnnmmxHlIUv369eXl5aWsrCxb29ixY/Wf//xHLVu2LHS/evXq6f333y/VmAAAAEBpUdgAAAAAAOVk+PDhtimq8/PzlZ6eLkmqWbNmhVzgv+2220q139KlS+2WO3j00UfLlEtaWprOnDljd/F1/fr16tmzZ4mnzPfy8tKKFSucXoLgQldeeaWaNm0qSbrxxhvVu3dvvfbaa3r22Wf1ySefmPpOnjxZgwYNspsa3hn//POPdu7caWr79NNPTUt8lMahQ4cq9S7Zhg0b6pprrqmUsZcsWWLX5sxsBkW5cEaNwgQFBalbt25avXq1rW3nzp3avHlzkRc2N23apC1btsjd3V3Dhg1zKh+LxaJ+/fqpX79+TvU/z9Fd2c4W0VRF119/vWbNmiXpXIHI2bNnlZWVJavVWuIZGUrjhhtuKNXyM2lpaVq1apWp7aeffipT4Zrk+DxNT0+3G6tt27ZVooCsOEuXLrVra9++fYlieHl52T7LK0LBYy05XhqiOBaLRb169dKUKVNM7evWrSu2sMGRrl27lrqww83NTbfffrsWL15sa0tMTFSXLl30zjvvaMCAAaUqXAEAAADKA3+ZAgAAAEAFcHNzk9VqldVqrbCLTqWdgn7FihUuzuTcxbYaNWrYtb///vslLmqQpKysLNM652Xl5eWljz76yK5QIj8/X0OHDjUty+Gs8jiOdevWLfIu2opQmUsblMcxLWypgYKGDh1q1zZjxowi9zk/W8P999/vcMr3sjp+/LgWLlyoESNGOCycyMnJcfmYlcFiscjLy0u1atWqkKIGqfTn+dq1a3X27FmX5uLr66s2bdrYta9Zs8ZuLEfLWFRFK1eutGtr3LhxJWTivIIzTEilX8YjJCTErm3Dhg12RYXOKOtn8sSJE+Xp6WlqO378uAYOHKiQkBB98MEHOnHiRJnGAAAAAFyBwgYAAAAAuEQVthZ3cQ4cOGDXlpWVJcMwSv2zbds2uwsnkvTLL7+UKkdJ6tmzZ6n3dcTd3V2ffPKJPDw8TO0bNmzQzJkzSxzP0XFcsWJFmY7jyZMnnV6DvryU9rxyhYLHtF69emU6noZh6KeffnJq7Hvuucfu7ux58+bZZmIp6NSpU5o/f74kaeTIkSV/sg5kZWVpyZIleuyxx9SiRQvVr19fDzzwgKZMmeLwfEPpufLz85NPPinTOZqcnKwePXrYxd2/f79dm6+vb6nyrmiOZqCoyrkbhqG9e/fatZe2sMFRoUpSUpIyMjJKHKusn8ktWrTQ559/7nDWh507d+q5555TgwYN9OCDD2rTpk1lGgsAAAAoCwobAAAAAAAmx48ft2tLTU0tl7E6d+5cqv2ee+45BQYGujgb6eqrr3Y4FfjYsWNLPK1/RR7Hy0F2drYSExNNbRV5PD08PPTkk0/ajf/dd9857D9z5kxlZ2frxhtvVGhoaKnHNQxDy5cv1yOPPKIrrrhCvXv31qxZs7Rv3z5dffXVeuaZZ7Ro0SItWrSo1GPAdSryff/vv//atfn4+JTLWK7mKPeKmo2jNDIyMpSVlWXXXq1a6Vb5rV+/vsP2gp9xFeWRRx7Rr7/+qiZNmjh8PC8vTwsWLFBoaKg6d+6sXbt2VXCGAAAAAIUNAAAAAIACTp48add26tSpchnr+++/L9UdzO+//3655CNJL730kpo3b25qO336tF544YUSxanI43g5cHTs0tPTlZmZWWE5DBkyxO7iq6PZPPLy8vTJJ59IOjdbQ2mXn4mLi9Ott96qO+64Q19//bVSU1PVqlUr/e9//9ORI0e0a9cuffTRR7r33ntVu3btUo0B16rI972jsUpzx39lOHPmjFNtVUVhuR07dqxU8axWq8P2ilqqypEbb7xRf//9tz777DO1aNGi0H6//fabbrjhBn3xxRelWjoDAAAAKC0KGwAAAAAAJl5eXnZtO3furIRMKoe3t7emTp1q1z5jxgz9/vvvTse53I+jqzk6nlLFHtMGDRqod+/eprZffvlF//zzj6ltxYoVOnDggOrVq6e+ffuWeJycnByNHj1a7du317p16yRJdevW1U8//aTdu3fr2WefVYMGDUr9PFB+KvJ972is5OTkchnL1Rwtn1CVC78KW+7hyJEjpYpXWGHDFVdcUap4rlK9enUNGTJEu3fv1sKFC9WpUyeH/TIyMvT444/r66+/ruAMAQAAcDmjsAEAAAAAYOLozu+//vqrEjKpPD169NBDDz1k1z5s2DDl5uY6FYPj6Fq1atVy2F7Rx3To0KF2bV988YVp+3xhzLBhw+Tp6Vmi+NnZ2brvvvv0/vvvKy8vT5IUGBioDRs26Pbbb6/UO7pRvMLe9+VxZ7ujsQ4dOuTyccqDv7+/XVtV/nysUaOGvL297doPHz5cqnjZ2dl2bXXq1FH16tVLFc/V3N3ddf/992v9+vXasGGD7rzzTof9hg8fXupjAAAAAJQUhQ0AAAAAAJOCyzBI0pIlSyohk8r1wQcf2N2lGxsbqylTpji1v6PjuHHjRodry6N47u7uatq0qV17RZ+b3bp1U6tWrUxts2fPthUhxMfH66effpKnp6eeeuqpEscfN26cli5damqbMWOGw/MJVY+j1+n48eP6888/XT6Wo1k7tm7dqvz8fJeP5WotW7a0ayvJjDgVzWKx6MYbb7Rr/+OPP0oV7/Tp03Ztt9xyS6lilbfQ0FD98MMPmjNnjl2BWXJyst58883KSQwAAACXHQobAAAAAAAmoaGhdm07d+6s0nfTlod69erp7bfftmt/9dVXdfTo0WL3d3QcDcPQnDlzXJJfSVwMFzqd4eiYRkVF6fjx4xWWg8Vi0bBhw0xtR48e1YoVKyRJ06ZNk2EYevjhh0s8rfzRo0c1ceJEU9tNN92kW2+9tUw5o+I4Okcl6csvv3T5WB07drRrS0tL05YtW8ocuzxmmLjQf/7zH7u23377TQcPHizXcS9U0s/FsLAwu7affvqpVMfK0b8ht912W4njlMWZM2d0/fXX67HHHiu2r8ViUf/+/fXNN9/YPRYVFVUe6QEAAAB2KGwAAAAAABdwdGGjIi8mOxq/tBemunfv7rB93LhxpYpXWQp7/ufvrHfGk08+qQ4dOpja0tLS9Oyzzxa7b6dOnRxOXR4ZGam0tDSnc3AFR9OeO8OV55UrYjs6N3Nycir8juGBAwfavbZTpkzRqVOn9Mknn0iSRowYUeK4CxYssDs/y3IXd05OjtN9Cx778r6wXdxYF+vnZ6tWrdSwYUO79unTp7t8yv7g4GBZrVa7dkcXn4uSmppq15aenu70/qU5fuHh4Q73mTZtmtPjllVJPxf79+9vtxTMkSNHFB0dXeKxC85O4enpqXvuuafY/Vx5rlarVk0xMTGaNWuWU8V6ktSzZ0917drV1ObsvgAAAEBZUdgAAAAAAGVkGIZSUlLs2h1NNV1eMjIynGpzRteuXdWiRQu79mXLlmnWrFkljmcYRoVeJD3P0WsinbtL1Vnu7u769NNP5e7ubmpfuHChfvrppyL39fX1Vf/+/e3aT548qf/+97+lOialvdibmZlZqv1ceV45EycrK6vIfR588EH5+vratU+bNq1UFxdLezxr1aqlhx9+2NT2888/KygoSGlpaerSpYvat29f4rh79+61a2vcuLFT+zp6LsnJyU6PXfD1KO05UxqX0uenxWJxuATJ2bNnNWjQIOXm5pY4ZmHnabVq1dSvXz+79pkzZyoxMdHp+OvWrbNrK8mSOaV5L1977bW66aab7No/+OAD/f33306PLZ0rzHjuuef0zz//lGi/kp7jLVq0UJ8+fezaC86y4oyC/3489dRTDpcWKciV52qNGjXk5nbuq+EffvjB6f1CQkJM2wEBAaUaHwAAACgpChsAAAAAoIwyMjIcXsQ5duxYheXg6GJ9SS7gX8jNzU2jR492+NjTTz9dojXFs7Ky9MADD6ht27YlugPYFRISEhy2l+SCnyS1b99eo0aNsmt/+umnHd7pfKFRo0apWrVqdu2zZ8/Wxx9/7HQOhmHovffe0xVXXFHsNPM1a9a0azt06JDTY13IledVQY4uuhdWjHJezZo17ZaBkM5d+H3ooYe0f/9+p8dPSkrSrbfeqrCwsFIVOAwdOtSu7fy5NXLkyBLHk87dtV2QsxeYN23aZNfm7GtlGIbd61GSooiycvRevVg/PyVpyJAh8vPzs2tfvXq1XnjhhRIVNX3zzTeqW7euli1b5vBxR0UUZ86cUURERLGx8/PzNWX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+      "text/plain": [
+       "<Figure size 2400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2400x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_pre_qpp_boxplot(pearson_df, pre_ret_predictors, 'pearson')\n",
+    "plot_pre_qpp_boxplot(kendall_df, pre_ret_predictors, 'kendall')\n",
+    "plot_pre_qpp_boxplot(smare_df, pre_ret_predictors, 'smare')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T09:45:48.926411Z",
+     "start_time": "2024-02-27T09:45:40.611200Z"
+    },
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x7fad7b427af0>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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aAHV72UeT2ZwvDv1mq6VjRojj8dyNxyi0AABypXPR8er9+TptOZbCzUL/aVohKJMiAgAAAG4Pa7QA2V1gcaly++TtZi+p7hOZHw+Q24WGSw/MkgqWlSQlGWYttjbUK4l9nTaLiU/yRHQAUrDpyAV98Os+zfjnkM5Fx3s6HCBHe/uHHakWWcyy6YWAP/TaiZfs6w6u/EhK4u8SAAAAWRcjWoCc4N6PpcW+0s4fJFuSVKCU1OZdqWh1T0cG5E5h90iV2koX/tXDM3dp7enkI85aVS7sgcAAuPLGvK36au1Rx+MxP+7Rp4/WUbNKIansBcAdsQlJ+mnHKZd9IQG+qlOqoF6Jek8Vz/wkHf+v4+ga6cBvUo95ksmUecECAAAAacSIFiAn8AuU7vtMenWf9PxG6YUtUpWOno4KyN1MJqlQWQ3o0lD5fJ3va6hWPFA9G5fxTFwAnCzffdqpyCJJcYlWvfLdFiVaXa8bAcB9STZDSTYXU95KCs7nq0/utNiLLDc6sFw6+EfGBgcAAAC4iREtQE6St5D9B0CWcPJSnM5GxWviAzW16+Rlnbx8RbVLFVTHGkXl62XxdHgATm3TiX+Wq4zJX/8aRZ26zkbFa+PhC2pQLvkaEYu3ntB3648p6kqimlUKUa8mZRWYxzuzogaytfx+3mpQtpDWHDqfrO+uqqHSsRUp73x0rVS+ZQZGBwAAALiHQgsAABlg5OKdmrHyX1n/u2u3RolATe1ZV4UD/DwcGQDFR0nfPiYdWK4ekh72MWmBrYleS3xaVllU37RLj3r9oqo/TZAqNJUaPisFhEqSJvy8R5OW73ccauORi/px+ynNf7aJ8vhQQAXSYljncD0ydY0iYxIcbdVLBOqpO8pK/+5PecfA4in32WzS/l+l8wekItWkMk3TMWIAAAAgdRRaAABIZws2Hde0vw85tW05dklvzN2m6Y/X81BUABx+GWKfhug/ZpOhrpa/dcGWT3uMkhrtPU1mkyGdlnR6vbTte+mp3xRpKqhP/jyY7HC7T0Vp/qbjerhBqUx8ErjRrpOXNem3fVp/+IKKBvrp8cZl1LV2CU+HBRcqF8mv5a+00ILNx3XsQqyqlyigthFF5G0xSxXvlgqVk87f8LeWL1QK7+L6gNFnpFldpNPbr7WVbSY99LXk459xTwQAAAD4D4UWAABuR0KMFHVKyl9M8s4jSZq78ZjLTX/fc0YXYhJU0N8nMyMEcD3DkLZ847Krt/ePshmS+ca1ti8fk1Z/rG2lnlNCkut1WzYcvkChxYP2n4lW909WKTo+SZJ96reXv92i8zEJevKOch6ODq4E5vV2vV6ZxUt6dL60qP9/a7IYUqlGUoeJKRdNfhrsXGSRpEN/Sn9NkO58K13jBgAAAFyh0AIAgDsMQ1o+UlrzqZQQJfkFSo1fkJq9qrgEq8tdbIZ9ke2CmRwqgOsYNikpLsXuZEWWq46sVpGIV1Pcr2gg0wJ60vS/Dyo6Pklm2WRIMmSWJP3vjwN6rFEZ+XiZPRsgbk3BMtJjC6TY85LNKuULSXlbm03a+YPrvh3zKbQAAAAgU/CNA8jiYuKT9PvuM1p76Lxs/631ACALWDlJ+mucvcgiSVcuSctHSOtnqGXlwi53qVI0v4oVyJOJQQJIxmyRKtx16/sFFNG/kbEpdp++HKcTF1Mu4CBjnT52SB95f6A9vj212/dxve89WUG6pMiYBJ2JuuLp8OCuvIVSL7JcZbgeaZZiOwAAAJDOKLQAWdj3G46pwbu/qdfn63T/p6vUavwf2n3qsqfDAiBJa6em2P544zKqWbKAU3M+Xy+NvDc84+MCcHN3j5T8XRdEU1S4qn7cejTF7u82HFenj/7RcYotmS8pQe9FvaEOljXyNlnla0pSF8s/muUzWvn9zArO5+vpCJGRzGapSkeXXWdLtsnkYAAAAJBbUWgBsqh9p6M04PstjrnGJenfyFj1+WIDI1uArCDqZIrt/r5e+vbpRvrgwZp6rFFpDWgbpuWvNFed0oUyN0YAroVUkp5bK7UdLQUUcb2N6YaPyX+M0iuHn1V+xaR42HPR8Zqy4kA6Boo02bVQIYnHkzVXNR/WkCqn5edt8UBQyFRt3tFJrxJOTRttFdRpa2OdjYr3UFAAAADITVijBcii5m48Llf1lCPnY7X23/NqWC4o84MCcE2pRtK/f7lul+TjZVbnmsXVuWbxTA4MQJrkKSg17CsVryN90VlKvG5asDyFpJAq0pF/nHYpGb9X/bwWaFTSIykedv3hCxkVMVJy/lCKXd3KcJE9N9gTG6D20e/qLvMGlTWd0k6jtFbYqsuQWd+uP6p+LSt4OkQAAADkcBRagCwq5rqRLDeKvpJy3/WWbD2p7zYcVdSVJDWvFKLHm5RRfj/v9AoRyN1avSV90UlKum7uf58AqcXrnosJwK0rWV96+k9p7RQp8oAUGi7VfVL6sJbLze/Lu1mjLqdcaCmS3y+jIkVKilRLsctUpHomBgJPOXo+Vkny0jJbA5d9AAAAQEaj0AJkUS0rh2jW6sPJ2vP6WNSg3M2nH5rw8x5NWr7f8XjD4Qv6cfspzXu2MVNoZBdndkkrP5RObZUKlZcaPSeVrOfpqHBVqQbSU79La/4nndsnFa4qNXxWCuauWSDbuHLJXlwpUFpqN/Zau80qmb0kqzXZLt4+vhrUrrJ+3H5KG49cTNb/WOMyGRcvXKt4t1S8rnR8vXN7uRZS6UYeCQmZq2qx/LKYTbK6GA5erUSgByICAABAbkOhBciiWoYVVofqRbV467V1IEwm6a0OVRVwk1Ep52MS9MmfB5O17zx5WfM3HddD9Uule7xIZye3SjPukRKi7Y9PbZN2L5Ye/kaq0NqzseGa0KpSpw89HQWAW2UY0vIR0ur/2acMM3tLtXrYiy0Wb8lskcK7SFu/TrbrlAt19NHS3SqQ11t3Vw3Vir1nFZ9kU+EAX716d5iaVwrxwBPK5cxm6dH50l/jpZ0//Pfv11W642VPR4ZMUqxAHj1Uv6Rmrz7i1F4+xF9dajGFJwAAADIehRYgizKZTJr0YC3dW7O4lu85I38fi7rWLqEqRfPfdN+txy4qIcnmsm/D4QsUWrKDP8dcK7JcZUuSlo+k0AIAt2v9dPtF+atsidKGGVLeIOnOt+xtbd6Vzu2VTmx0bPaLtY6mWDtIki7GJmrjkYta/cadirqSpGIF/ORlMWfms8D1/PJLdw2z/9xEQpJNn/1zSIu2nJDVZuieiKLq06yc8vgw4jc7G94pQmGhAfp+wzFFxyepZVhh9W1RXnl9+MoLAACAjMenTiALM5tNal01VK2rht7SfkUD86TYx9zx2cSxDa7bT2z6b0obLgYBgNvWf+66fcOMa4UW/yCpz+/Sob+09M9/9PFuf203yjltfi46XluOXVSLsMIZGy9uTdwFaf0M6egaKX8xqe4TTuu4PDtng37ddUaSobbmdSq3YrU2rvdV445PyFS1s30IMTzv7F5p27f2tdAq3SOVaZLq5mazSWazSZevJOnI+Vit+/e8mhwPVkv+PrOH+Ghp6zfS6R1SUAWp5kNSnoKejgoAACDNKLQAOVBYkQA1KFtIaw6dd2rP423RA/VKeigq3JLA4lLUieTtAUUpsgDA7Yo9l0L7eclms09FdVXZO7R+e5C2G4dc7pJoTb4mBDLerpOXdeJinKoVD1Th628iiYmUpreWzl83herGWdIDs6Swe7TpyIX/iizSu17T9LDX7/Ztrkj6boVUu6fUaVLmPRG4tmGmtLi/ZPw3Qnvlh1Ld3lKHCSnuMnPlv3p74Q7H4y3HLunJmes1u3cDNSoflMEB47ZcPmmfMvfCde+z/3wgPb6Ete8AAEC2wfwGQA71vx511Da8iCxm+12ZlULzafrjdVWyUF4PR4Y0adjXdXuDZzI3DgDIicrckUJ7U+ciy3/ahLseWRrg66UmFbiAm5kuxibooSmrdc8Hf6n3zPVqPHq53lmy89oGqz92LrJI9qnhfhokGYa2Hb8kSapq+vdakeV6G2fa10WD58Sel5YNvFZkuWr9dOnwKpe7GIahT1YcSNZutRma+lfydQuRxfwxyrnIIknRp6Rf3/ZMPACQkyXGSb8MkcZWlN4pJn33uHTe9Q1FAG4NI1qAHKqQv48+ebSOLsYmKCbBquIFUp5ODFlQRDf71Cd/jpOiTtqnTmjQV2ryoqcjA4Dsr8Xr0oHlziNbfPJJrV2v79GgXJAeb1xGn6/819HmbTFpdLfqrP+Qyd5csF2rDkY6HifZDE3965DCiuTXfXVKSIf+dL3j+YPSxSMqWdB+w0lj8w7X20nSwT+cphpDJju0QkqKc923Z6lUulGy5tgEq05euuJylwNno122IwvZ97Pr9r0/ZW4cAJAbfP2w/XPwVTvmS0dWS8+ulvIU8FhYQE7AN0MghyuQ10cFGMSSPdV7UqrTS4o5K+UpJHn5eDoiAMgZgspLz/wtrZsqndpuXw+gXm97ewqGdgpX19rF9duuM8rrY1GnmsVSXRMN6S86Pkk/bj/lsu/7DUfthRb/YNc7m70lv0A1qxSoMkF5df5CQMon2j5XqvGwfZ0eZD6vVP6uvF335fWxqGShPDp6PnmBJiw0lX9rZA3eKXxZ8eFLDACkqyOrnYssV0WdlLZ8LTVkBg3gdjB1GABkZWaLFFCEIktOY7NKh1dK//4jWZM8HQ2QO+UvKt05RHrkW6ntu6kWWa6qXqKAXrqrkp5uXp4iiwdcSbQqyeZ6TZyYeKv9f+o87nrniK5SngK6usz9j7b6Om/kc73tiU3SN4/cVqy4DeVbSv4uFrA3maVq97vcxWQy6flWFZO1+1jM6tvi5n/b8LCaD7lur5FCOwDAPeump9x3fEPmxQHkUBRaAADITIdXShOr2xd9/bydNDFCOrjC01EBQJYXnM9X1YoHuuxrGRZi/59KbaS2oyW//7YzmaUqnaT24yVJ/xw4p38jYxUrP/VKGKDzRgqjHY6sshdckPm8fKUHZjsXW7zzSh0npbow+v11S+qjh2upRskCKpjXW3dUDNaXTzVQrVIFMyFo3JYm/aVq3SVHKVRSxTb2YjgAIP3ER6Xc5+f6MxaAtGPqMADIYPFJVhmG5Odt8XQo8LT4KOmrB6Url661RZ2Uvn5EemmbfS0eAECKhnYKV8/P1io6/tpowMpFAtS7ablrGzXsK9XuKZ3dbR8Vmr+Yo+v05XjH/28xKmiptZ56eLmYQkOSLh2XitVK9+eANCjVQHpph329nKQ4qWzzm88bf/6gOuQ9pA6PVrWPWEP2YfGWuk2TWrwhnd5hn84xtKqnowKAnKdkPWnvMtd9dXtnbixADuRWoeXcuXN67733tGrVKp0/f16G4TyEf9euXekSHABkZ2ej4jV88U79uP2krDZDLcIKa0iHqioT7O/p0OApuxY7F1muSoiSdv6Q8pQ3AABJUp3SBfXry8317fqjOnExTjVLFtC9tYonv5nBJ69UvLbL/U0m6erXl022SuohF4UWk4Uii6d5+UiV7r75dgmx0vw+9hwrQzJ72de4u2eMZGYCh2wlqHyapnEEALipdk9p1f+k2LPO7VU6S6FVPBMTkIO4VWh5/fXXdfLkST377LMqXNjF/LkAkMsZhqGen63VzpOXHW3Ld5/R7pOX9dsrLZTHh9EtOd2pS1d0+vIVVQoNuPbv7arIclVqfQAAhyKBfnrhzuTrcaRF2WB/PdKglGavPiJJWmRrpF62HxVh/td5wwZPS4HFbzNSZIpf35Z2Lbr22JYkrZsqBVe0/zsCAAA7/2DpiR+l5SOk/b/Zpwur1UNq9qqnIwNyBLcKLRs2bNCXX36pKlWodgKAK//sj3Qqslx14tIVLd56Qt3rlvRAVMgMMfFJeu37Lfpx+ynZDCnAz0v9W1dS76ZlpQqtZZ9/3MVizhVaZ3aoAJArjegcoTqlC2rBphOKT7JqU6VZCrMtkff+nyUff6nmw/YfZH2GIW3+ynXfplkUWgAAuFFwBen+mZ6OAsiR3Cq0FC1aNNl0YQCAa46cj02x72gqfcj+3vphu5ZuO+V4HHUlSSMW71SZoLy6s0oFqfHz0spJzjs1eEYKDc/kSAEgdzKZTOpSq4S61CpxXWt1qdUbHosJaXfoXIwm/bZPaw5GKjSfRfMSoq9fQv0aRooCAHIrm006vU3y8pNCwjwdDZBruFVoGTRokMaPH69hw4apRIkSN98BAHKZasUDU+yLSKUP2VvUlUQt3nLSZd+Xa47oziqh0t0jpAp3SjvmS4ZNqnqv/TEAAEjViYtx6va/lTofk2B/fEn6x7uqmlp2JN+YkaIAgNzo4B/Swueli/ZpUlW0htRtun1KTQAZyq1Cy0svvaS4uDjddddd8vPzk7e3t1P/2rVr0yU4AMiuqpUI1N1VQ/XzztNO7TVLFrBfbEeOFHUlSQlWm8u+c/9dFJIklWth/0GuE5dglZ+3WSaTy/uvAaSD+CSrjkTGKiTAVwXy+ng6HKSjz1f+6yiyXPVu0iP6yvyOAk0x1xoLlJKavZbJ0QEA4GFRp6SvHpISr5tF4+QWaU536fkNkpm1YoGM5PaIFgBA6j56uLam/31IP2w+riSbobbhRfRMi/KymLnAmlMVDfRT2WB/HToXk6yvSfkgD0SErGLBpuP64Ld9OnQuRkXy++mpZuXs6/YASFdfrPpXE3/dp/MxCfKxmNWlVnEN6xwuP+9ULixcOi6t/lg6tk4KLCHV7yOVaph5QSPNdp5Ivv7dTqOM7oofoyVNDyok4bhUtLpU8xEpT4HMDxAAAE/a+o1zkeWqC4fsI12YSQHIUG4VWrp06ZLecQBAjuPjZVbfFuXVt0V5T4eCTGIymfRm+yp6ZvYGJVqvrWVWOigvF9VzsoQY6exuKaColL9Ysu6fd5xS/282Ox6funxFIxbvlJfZpJ6Ny2RenEAO9+vO0xryw7UppBKsNn2z/qh8vc0a3jnC9U4Xj0pTW0kxZ+yPj66xT+143wwp/N6MDxq3pHRQXv29P3n7Ja8g+dz5gJTHO3knAAC5Rcw59/puZv+v0uav7EWcinfZb2jw8nX/eEAO5VahRZKsVqt+/fVXHThwQJJUsWJFtWrVShYLw9CATHFsvXRmlxRSWSpZz9PRAPjPnVVCtfC5ppqz5rBOXryi2qUL6pEGpZi+Jqda+ZG04j0p/rJkMktVOkmdJ0u++RybTPvrkMtdp/x5kEILkI6+WH3YZft3649pULsqrke1rPzwWpHlKsMm/TpUqtpZYpq/LOXxxmX0/YZjik9ynqbzwXolFUiRBQCQ25VtLq2clLzdZJHKNHXvmCvGSr+PvPZ4z1JpxwKpxzzJ4vZlZSBHcusv4vDhw+rTp49Onz6tsmXtd+hOmTJFRYoU0ZQpU1SqVKl0DRLAdRJipK8ftg/7vKpsM+nBr5wu7AHwnCpF82vkvdU8HQYy2u4l0s+Drz02bNLOBZKPv3Tvx47mw+eTTyUnSccvxinJapOXxZzBgQK5w9moeJftcYlWRV1Jcl1oObLK9cEuHJKiT0sBRdIxQtyuiqEBmtW7gcb8uFvrD19Qwbze6tGwtF68kwV+AQBQhTulsHb2Ysj1mvaXAovf+vGiz0p/jknefmiFtHsxo3+BG7hVaBk5cqRKliypb775RgUKFJAkXbhwQa+99ppGjhypKVOmpGeMTubMmaPp06fr7Nmzqly5st566y1Vr17d5bbffvutFixYoH379kmSwsPD9fLLL6e4PZAt/P6uc5FFkg79Kf3+jtR2VPLt9/4srZ9uv1hQuonU+HkuGgBAelg/w3X7tu+ke96TfAMkSRHFAnX68plkm1UuEkCRBUhH9csU1K6TydfwKB/ir5CAFKa3yF9MOrU1ebu3v+QXmM4RIj3UL1tI3/dtTKEaAIAbmUzS/bPs30d2L5a8/KTqD0iV7rb3R5+Rtn4rxZyVyt4hlb8z9dG7R1dL1gTXff/+RaEFuIFbn0zXrVun1157zVFkkaSCBQvq1Vdf1bp169IrtmSWLl2qUaNGqV+/fpo/f74qV66s3r17KzIy0uX2a9asUfv27fXFF1/o66+/VtGiRfXEE0/o9OnTGRYjkOG2fZf29nXTpC+7S3t/lE5sklZ9JE29055cAQC3JzaFeY6tCVJ8lOPhc60qyMfL+SOX2SS9dFeljIwOyHWeaVFeofmdCypeZpPeuKdKyjvVe8p1e+1HJe886RgdUnV0nTSvj/R5B+m34Wn6rEqRBQAAFyxeUs2HpAfnSPdNv1ZkOfSXNKmWfUT+PxOl2d2krx6SrEkpH8s/xL0+IJdy69Opj4+PYmKST4MRExMjb++Mmxt3xowZuv/++9WtWzdVqFBBw4YNk5+fn+bOnety+/Hjx+uRRx5RlSpVVL58eY0cOVI2m02rVqUwRQCQHaR0N8GN7Unx9tEvN7p8TFo7Nf3jAoDcpmwz1+3Blex3yf+nVqmC+u7pRmoTHqqShfLojorBmvlEfbUJZ3QhkJ6KBubRouea6tkW5dW4fJDuq1NC859totZVQ1PeqWJrqdNHUkBR+2MvP6nek9JdIzInaEg75kuf3S1t/cZ+d+xf46UpLaWoU56ODACAnMEwpIXPSQnRzu17l0lbv055v5INpMLhydu9/KQaD6VvjEAO4NbUYS1atNCQIUP0zjvvOKbh2rJli4YOHapWrVqla4BXJSQkaMeOHXr66acdbWazWY0bN9amTZvSdIy4uDglJSUpMPDWpwGwWq23vA+QEUyV7pF5y5fJ2m1h7WRc/3t6dq8ssa5HexlH18jG7zSA22SxuFjv4BZk+9za4FmZd/4g04V/HU2GxUe21iOkG55bRLEAffxwLae2bP/8gSwoyN9br9zlvF7HTf/WajwsVbtfunRMyhvkmPbvxr9jZADDJvMvb8tkOC9ur8vHZFv5kYzWwzwTlwfl+twKAEh/p3fKct13lusZuxbLVj2VoskDc2Re8LRMR9fYtw8sKVu7cVL+Etnqs9Lt5lcgLdwqtLz55psaOHCgHnjgAXl52Q9htVrVqlUrDR48+CZ7u+fChQuyWq0KCgpyag8KCtLBgwfTdIxx48apcOHCaty48S2ff9u2bbe8D5ARvAp3VZj/X/KLOepou+JfQnsLd1Hi5s2ONkv8JdUwWWQykie+yCQ/Hb5uWwBwR506dW5r/5yQWy31Jyrk8GL5X9ihhDyFdbZ0R12JCZF4jwWyqYueDiBX8Y49reoXD7vsi931q/YEd8nkiDyP3AoASG++0UcVkULfhahYHbrZd5eao+RT8bgsSVcUl7+sFG3Odt93bje/AmnhVqElf/78+t///qfDhw/rwIEDkqTy5curdOnS6RpcepoyZYqWLl2qL774Qr6+KSyGmYpq1apR/UTWUXetbDt/kM7ulkLC5F21s8K9/JJtZpy6X6atXzm3mSwqePcAFSxWM5OCBQDXckxurX9tCrGgVDYDANwgPkrGH74yWeOTdfmHllPNmjUzP6ZsLsfkVgBAOqopY3ctmU4mnxGooC4psHo1yXyz3FEzQyIDchK3Ci1XlS5dWqVLl5bVatXevXt16dIlt6blSouCBQvKYrEkW/g+MjJSwcHBqe47ffp0TZkyRTNmzFDlypXdOr/FYuEDK7IOS16pVhrmw+z4vuTlY5/zOumKVKicTHeNkKVk3YyPEQBugtwKALlc3gJSjQekjV8k6zLVf5Ic4QZyKwDApfbjpGmtJRlOzaaTm2XZ/7NUpYNn4gJyELM7O73zzjv67rvvJNmnDOvRo4e6dOmiFi1aaM2aNeka4FU+Pj4KDw93Wsj+6sL2tWrVSnG/qVOn6uOPP9a0adNUrVq1DIktK1pzMFKPz1irxqN+06PT12jl/nOeDgme4J1H6jRJGnBQenmX9PxGkicAAACyjnvGSDUfkcze9sf+haWOk6TyGbP2JwAAuVL0Gd1YZHE4sDxTQwFyKrdGtPz000/q1KmTJOn333/X0aNHtWzZMv3www96//339fXXX6drkFf16tVLAwcOVEREhKpXr66ZM2cqLi5OXbt2lSQNGDBAoaGheuWVVyTZpwubNGmSxo8fr+LFi+vs2bOSpLx588rf3z9DYswKVu4/p8c+W6skm/0N9MSlK1p5IFLTe9ZVi7DCHo4OHuHjb/8BAAAAshLvPNK9H0t3j5RizkkFy9hHZAMAgPSTp0AqfQUzLQwgJ3Or0HLhwgWFhIRIklasWKF77rlHZcuWVbdu3fTFF8mHfaeXdu3a6fz585o0aZLOnj2rKlWqaNq0aY6pw06ePCmz+dogna+//lqJiYl64YUXnI7z3HPP6fnnn8+wOD1t0vJ9jiLLVVaboUm/7UtzoWXrsYv6Zedp+XqZ1bFGMZUO4iI9AAAr9p7VjH8O6eTFK6pZsoCeaVFeZYPJkQBw2/IWsv8AAID0V6qRFFxJOrfXud3sLdV82DMxATmMW4WW4OBg7d+/XyEhIfrrr780dOhQSdKVK1cyfD7YHj16qEePHi77Zs2a5fR4+fLcOfRtx4nLLtu3p9B+o1FLd+nTPw86Hr//6z6N7lpN3euWTJf4AADIjuZtPKZXvtsi4797GfacjtKPO07ph35NVCbYXzIM6cQm+5pYxetyRzYAAACArMFkkh76Wvqup3Rqm73NP0RqP14KKu/Z2IAcwq1CS9euXdW/f3+FhITIZDKpcePGkqQtW7aoXLly6Rogbl2ZIH9tO34pWXt+Py/N33RM90QUlZ+364LY5qMXnYoskn00zFs/bNfdVYsoMK93hsQMAEBWZrMZGv/zXkeR5apLcYn69M+DGtXELH33+LU7xPxD7GsMVG6X6bECAABke5EH7BeGC3GNKUtJiJV2L5ZiI6WyzaXQqp6OCLciqLz0zN/2QktCjFSsNjeHAenIrULL888/r0qVKunkyZNq27atfHzsf5QWi0VPPfVUugaIW9enWTk9/9WmZO3nohP00jdbNObHPZrzZAOVC8mXbJufd5xyecwriTb9ue+sOtYolu7xAkCO4xjZEC+VqCtZKFJnd+di4nX8YpzLvq1HIqUjz0sXj1xrjDlrL7w8v0EqwIhQAACANDm1XVrQVzq11f64SHXp3v9JRSI8Gxek4xulOd2l2HPX2uo+IXV433MxwT1Fqnk6AiBHMt98E2eJiYnq2bOnwsLC9Pjjj6tIkSKOvi5duqh169bpGiBuXccaxTSuew2VCcrrsv/kpSt664ftLvt8vFL+lUitD0Aa7FwoTW8jja8sffWw/YMqcp7TO6TJ9aWpLaUZbaUJVaU9yzwdFW5TYB5vBfi6vj/lLr9dzkWWq6zx0tZvMjgyAACAHCIhVprV5VqRRbL//+yuUqLrG16QieY/7VxkkaT1n0m7FnkmHgDIYm75yrm3t7f27NmTEbEgHd1Xp4T+eK2lqpcIdNm/8kCkLsUmJmsvGujncnt/H4uaVwpJ1xiBXGXTbOnbR6Wjq6Wok9KeJdKMdtLJLZ6ODOnJmiR9+YDzAoMxZ6Rve0qXjnkuLtw2Xy+LHmlYOlm7ySTdU8F17pQkxV3IwKgAAABykF2L7J+dbxR9mov5nnZqe/JF1K/aMT9zYwGALMqtIQqdOnXS999/n96xIAPYbpxM/nqm5E1zNxx3uWlofr8U13UBcBOGIf3xXvL2pDjpnw8yPx5knIO/S5eOJm9nZEOO8FqbMD3borwC/OwjW8oE5dWHD9VSWMP2kjmF6eEq3JmJEQIAAGRj0afd60MmSOXakmHLvDAAIAtza40Wq9Wqr776SitXrlRERITy5Mnj1P/GG2+kS3BwX2R0vAbO3artxy+77G9WMUSBeZJfFNp1yvX2x1KYlx5AGly5KF1yMa2QZF+EDjnHlUsp98VdzLQwkDEsZpMGtK2s/q0rKTo+SQXzestk+u+uhVaDpV+HOu8Q3kUq1zLT4wQAAMiWSjdJua9M08yLA8mFRkiFykvnDyTvq3pvpocDAFmRW4WWvXv3qmrVqpKkQ4cOOfU5LjjAo/p9uVGrD5532VcmKK9G3ut6IblyIfm05ejF5O3B/ukZHpC7+OaX/EPsi2PfqFD5zI8HGadMU/vIBlvyqRlVvlXmx4MM4eNlViEvH+fGpi9JJRtKW7+WEq9IYfdIVTrZ5xYDAADAzZWoI1XrLm37zrm9+gNSsVqeiQl2JpPU5VPpy+7OU+PW6iFV7ey5uAAgC3Gr0DJr1qz0jgPpaP+ZqBSLLHdXDdXHj9SWl8X1rHF9m5fXM7M3JG9vwcVgwG1mi9ToOenXt53bTRap8XOeiQkZI6CI1PIN6bfhzu3hXaRyLTwSEjJR6Ub2HwAAALinyxT7DUo7f7A/rnqvvdACzytZT+q/TdqxQIqNlMo1pwAGANdxq9CCrO3M5fgU+/L6WFIsspyLjtfk3/c7teXz9dKwTuHqXLN4usYI5DpN+0sWb2nVZOnycalINanlmwyBz4nueMU+smHbt/aRDZXbSZU7MrIBAAAAuBmzWar5sP0HWY9vgFT7UU9HAQBZktuFlm3btmnZsmU6efKkEhOdp0j56KOPbjswuC+8eKDyeFsUl2hN1le/bFCK+729cIe2HXdeXyA6PkkXYhPSPUYgV2rUz/5js9pHuSDnKtPE/gMAAAAAAIAcz/XQhptYsmSJHnroIR08eFC//PKLkpKStG/fPq1evVoBAQHpHSNuUWAeb71wZ8Vk7eHF8qtLLdcjU64kWvXT9lMu+xZuOZGu8QG5HkUWAAAAAAAAIMdwa0TLJ598ojfeeEOPPPKIatWqpcGDB6tEiRIaMmSIQkJC0jtGuKFvi/KqXCRA36w7qktxiWoeFqIeDUsrj4/rC7xWmyGrYbjsi0+0ZWSoAAAAAAAAyK5iz0tXLkoFyzJlMoBcy61Cy9GjR9W8eXNJko+Pj2JjY2UymfT444+rZ8+eeuGFF9I1SLinZeXCalm5cMobHF0nXTwsFa0p/+AKalI+WH/vP5dss7vDQzMwSgAAAAAAAGQ7Vy5Ji/pLO3+QDKtUsIzUZpR9nUoAyGXcmjosf/78iomJkSQVLlxY+/btkyRdvnxZcXFx6RcdMkbseWn63dL01tLc3tJHdaX5fTW0Q2WFBPg6bVqjRKD6NCvnoUABAAAAAACQJc17Wtoxz15kkaQL/0rfPiad3uHRsADAE9wa0VKvXj2tXLlSYWFhatu2rd555x2tXr1aK1euVKNGjdI7RqS3ZQOlo2uuazCkLV+qwslN+rvO3Vrq11574gJVo0Sg7qoaKi+LW/U4AABynCuJVvlYzDKbmRIBAAAAudjFI9LeH5O32xKl9TOk9uMyPyYA8CC3Ci1vvfWW4uPjJUl9+/aVt7e3Nm7cqLvvvlt9+/ZN1wCRzpLipZ0LXPed2SXfM7vUxW+m1GupFFo0U0MDACCrWn0wUqOX7dbmoxeV389LDzUopVfvDpM3NyMAAAAgN4o6Jcn1Wr+KOpmpoQBAVuBWoaVAgQKO/zebzerTp096xYOMZkuSrAmpb3PlorT8HemhL//bxyaZuZAEAMid9p2OUs/P1io+ySZJunwlSZ+uOKioK0l6t0s1+918O3+QbFapSkcpqLyHIwYAAAAyWGi45Jtfir+cvK9Uw8yPBwA8zO2r50eOHNH777+vl19+WZGRkZKkFStWONZrQRbl4y+VbXbz7Q7+Lv06THqvrDS8kDSzk3RiU8bHBwBAFjNz1b+OIsv1vl9/TDGrPpM+qCn9/Kb069vSh3WklR9lfpAAAABAZvLxl1oOSt4eXEmq/VjmxwMAHuZWoWXt2rXq2LGjtm7dqp9//lmxsbGSpD179ujDDz9M1wCRAdq+J+UNTn0bk0n6e4IUd16SIR1aYS+2XDySKSECAJBVHI6Mddme33pBeX4ZeG3xT0mSYS+6RB7InOAAAAAAT2nYV3rke6lyB6lUY6nFG9ITP0l+gZ6ODAAynVuFlvHjx6t///6aMWOGvL29He0NGzbU5s2b0ys2ZJTQqtLz66W6T9qHebqSGJe8Lf6ytG56xsYGAEAWE1Hc9RfF9r6bZba5mo7TkHYtytigAAAAgKyg4l3Sg3OkJ5ZJLV6X8hbydEQA4BFuFVr27t2r1q1bJ2svVKiQLly4cNtBIRMc3yhtmJF8Lk2zl1Sls2QknyJFkhS5P+NjAwAgC+nZqIyC8/kka28WFpryTmZLBkYEAAAAAACyErcKLQEBATp79myy9l27dik0NJWLDsg6/hx3w1Qn/ylcVeo4UbL4ut6vSLUMDQsAgKymSKCf5vVtovvrllDJQnlUq1QBje9eQ3fe20vyypN8B5NFqnpvpscJAAAAAAA8w8udndq3b69x48bpgw8+kMlkks1m04YNG/Tee+/p3nvvTecQkSFO73DdfnaPfZhn/aekVTcs5utfWKr7RMbHBgBAFlMqKK/G3FcjeUeX/0nz+0pJ/025afGR2k+QCpTM3AABAAAAAIDHuFVoeemllzR8+HC1aNFCVqtV7du3V1JSkjp27Ki+ffumd4zICEHlpRMbk7cHV7T/12aVZJJk2B97+0tdPpHyFc6sCAEAyPrCu0hlm0t7ltpzZ9g95EoAAIAbRR6Q1n8mXfhXKl5bqtOLtTwAADmKyTAMw92dT548qb179yo2NlZVq1ZV6dKl0zO2LMFqtWrz5s2qWbOmLJYcNN/6zoXSt48mb+86TfL2k77pkbyvaE3p6RUZHhoAIGfLsbkVAAAPIbciSzu8Uprd7f/s3Xd8Tvf///FnphUziZhFaYIMiVkRlLao1aJaVaNEzbYUtdvaq6hSrVkUpUqpWv3SfqgRWnvUqC1mJFYGWef3R3656pIhLkmuhMf9dnNrr/dZr5xcOe9zXc9z3keKifyvLf9zUuBvUr5i1qsLAIB0ZNEdLZL0008/aeHChTp37pwkqXTp0urYsaNat26dXrUhI1VsLr35XcKzWq4fk1zcpdr9JJ/W0vIOyS9z5YB045TkUi5TSwUAAAAAANnUb0PMQxZJun1B2j5VajzRKiUBAJDeLAp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fH+PVV181Nm/ebFbHiRMnjMDAQMPX19eoWbOm0b9/fyM0NPSx9sHBgwcNd3d349KlS4ZhpO24l9ZjcGxsrPH2228by5cvT9NnrXr16pn93hOPXYnn+cuXLzfq1atneHh4GIaR+vso0e+//260bNnS8PLyMqpXr2707Nkz1RrScnx61O8/8WedO3euUatWLaN69erG8OHDjejoaNM8t27dMj755BOjatWqho+PjxEYGGicPXvWND3x+PvHH38YDRo0MHx8fIwPP/zQiIyMNH7++WejXr16RtWqVY1Ro0YZsbGxZvvwwffR7du3jU8//dSoWbOm4eXlZTRp0sT4448/DMMwjODgYKNbt25G1apVjUqVKhmNGzc2tmzZkur+edjj9nfx8fFGrVq1jLlz55qm37lzx/Dy8jLWrl1rttyWLVuMRo0aGf/++6/Fn78e97Nuch51nmgYhrFw4UKjTp06pteP+x1Acn3g4+yrRNHR0caLL75ofP311ynWmtox1t3d3ViyZInRrVs3o1KlSsa0adOM2NhYY/DgwUa9evUMb29vo0GDBsaCBQvM1mnJucCDP3Nif/Pbb78Z7dq1M3x8fIxmzZoZ+/btM1vmxx9/NOrUqWP4+PgYPXv2NL777juz7wSyio1HrhilB601Sg3871/pQWuN345cybBtPtynGEbS44Fh/LffR44caXTo0MFsWseOHY3mzZubXg8cONCoXr26ERUVZWpbunSp4evra8TFxaX/D5GNcUcLUjVx4kT9/fff+uabbzRv3jz99ddfOnr0qNk8sbGx6t27t9asWaMZM2bo0qVLGjRokCSpaNGimj59uiRp48aN2r59u+kKgKioKHXq1EkrV67UggULZGNjo169epmuhF+0aJH++OMPTZ06VRs3btQXX3yh4sWLm7bbu3dvhYaGas6cOfr555/l6empjh076tatW2rcuLE6d+6sF154wZTmN27cONmfcc2aNfLz80v13549e1LcR3PmzNGvv/6qcePG6YcfflB4eHiSWz0nTpxousJh1apVKlWqlLp06aJbt27J1tZWTZo00dq1a82W+fXXX1W5cmWzn/lB4eHhcnJySpJUJ/Lz89OQIUPk5ORk2gedO3c2Tf/uu+9Uvnx5rV69Wj179tSFCxf0/vvvq0GDBlqzZo2+/PJL7d27V6NGjTItM2DAAK1bt07Dhg3Thg0bNHLkSOXJk8ei7c+bN0/ly5fXqlWr1LVrV40ZM0Y7duxIcT8n5+7du8qfP7/p9YEDB1S1alWzqyECAgJ09uxZ3b592zRPzZo1zdYTEBCgAwcOmLX99ddfqlmzpho2bKjPP/9cN2/efKzaEusrUKCAWX1p2fbD65Bk9nM+KDIyUj///LNKlCihIkWKmLbj7u5uuh00cTvh4eE6dSrpGKGSFB8fr4iICFO90dHROnr0qPz9/U3z2Nrayt/fX/v37zfNY2NjY7a/c+TIIVtbW+3duzfZ7aR2TJASHtrm4OCgpUuXasSIEZISrrYYOnSo1q5dq/Hjx2vXrl364osvUtxnUsKV07///rtmzpypWbNm6e+//051GANJmj9/vry8vLR69Wq1bdtWw4cPNw3bFh4erh49esjd3V2rVq1S7969H1kDkBL6VvrWZ61vjY+P15YtW1S6dGkFBgaqZs2aat26tUVDwlhS38OioqIUGxubYt8aHR2tH3/8UXnz5jUNvbB//37ly5fP7KpQf39/2drapjokx+OeCyRenf3gnT62trZydHRMsW+VpJ9++kmStGDBAm3fvt10jJASHl569uxZzZ8/X7NmzZKU+jEmJffu3dN3332niRMnavHixbpy5YomTJiQ6jKrVq1S7ty5tXz5cn3yySeaMWOG6T0ZFxenXr16KVeuXPrpp580cuRIs7uVkH7odx7d70jSrl27dP36dS1evFiDBg3S9OnT1a1bN+XPn1/Lly9XmzZt9Pnnn+vq1YSHGMfExCgwMFB58uTRkiVLtHTpUuXOnVtdunQx/S1/9913WrVqlcaOHasffvhBt2/f1qZNmx73V6ivv/5ar732mtasWaM6deqof//+unXrliTpzp076tixoypWrKgVK1Zo7ty5Cg0NVZ8+fR5rG+Hh4bKxsTFdjZ6W415aj8EzZsyQs7OzWrdunaZaVqxYIUkaN26ctm/fbnotJZzn//bbb/r666+1evVqSam/jyRpy5Yt+uCDD1S3bl2tXr1aCxculI+PT4rbT8vxKS2/fynhrsoLFy5o4cKFpnOWVatWmaYPGjRIR44c0bfffqsff/xRhmGoa9euZleT37t3T4sWLdKXX36puXPnavfu3frggw+0detWzZ49WxMnTtSyZctSHE45Pj5e77//vvbt26cvvvhC69evV79+/WRrm/CV4MiRIxUdHa3Fixfr119/Vf/+/ZU7d+40/Kb+87j9XXBwsEJCQsw+b+bNm1eVKlUyfd6UEobT/PTTTzVx4kTlzJnzsWpKZMln3eQ86jzx2rVr2rRpk6pVq2Zqs+Q7gIeldV896I8//tCtW7fUqlWrFNf7qGPs119/rVdffVW//vqrWrVqleaHpj8stXOBlHz55ZcKDAzU6tWrVbp0afXr1880FPrevXv1+eefq0OHDlq9erX8/f01c+bMVNdnLQ09i2hmuyqqVLKAcjvaqVLJAprVrooaeBaxdmkmpUqV0pEjR7Rt2zadPXtWU6dO1eHDh5PMFx0draFDh+rUqVPaunWrpk+frnbt2pmOI0iQ/NEBkBQREaEVK1boiy++MHUM48ePV926dc3me/PNN03/X7JkSQ0dOlRvvvmmIiIilCdPHtOHWGdnZ7NbCBs2bGi2nrFjx6pmzZo6deqU3N3ddeXKFZUqVUpVqlSRjY2N2Qn5nj17dOjQIQUFBZlO6gYOHKjNmzfrt99+09tvv63cuXPLzs5Orq6uqf6c9evXV6VKlVKdx83NLcVpixcvVteuXfXqq69KSnh+xp9//mmaHhkZqWXLlmncuHGmfTdq1Cjt2LFDK1asUJcuXdS8eXPNnz9fly9fVrFixRQfH69169YluXU7UVhYmL755ptUx1x1dHRU3rx5ZWNjk+w+ePHFF82+nBk6dKiaNWum9957T1LCEBpDhw5V+/btNXz4cF2+fFkbNmzQ/PnzTR18yZIlLd5+5cqV1bVrV0lSmTJltG/fPi1YsEC1atVKcZ0POn/+vBYvXqyBAwea2m7cuKESJUqYzZcYNty4cUP58+fXjRs3zAIIKeG9+eBzRWrXrq1XX31VJUqU0MWLFzVlyhS9//77+vHHH2VnZ5em+vbt26cNGzaYvtBIrOHhbbu4uCg8PFz37t1LcuIYHx+vsWPHqnLlymbjaUoJY2hOmjRJkZGRKlOmjObPn2/6W0hpO5IUEhKSbL3z5s1TZGSkXnvtNUkJ483GxcUlGZLL2dnZFD74+voqV65c+uKLL9S3b18ZhqHJkycrLi4uxe3Y2dmleEyQEt53AwYMMGtLfE9KUokSJdSnTx99/vnnGj58eLLbkBJugR03bpxpeLDmzZsrKChIH3/8cYrL1KlTR++++64k6f3339eCBQu0e/duPf/88/r1118lSaNHj1aOHDlUrlw5Xb9+XcOGDUtxfUBy6Fv/Q9/67PStoaGhioyM1Jw5c9SnTx/1799f27Zt0wcffKDvv/9e1atXz9D6HjZp0iQVLlzY7AsLSfrf//6nvn37KioqSq6urvruu+9UqFAh07oS/z+Rvb298ufPn2Kft379eh0+fFgjR440qze1ffX888+rWLFimjx5skaOHKlcuXJpwYIFunr1aorbkWSqrUCBAkneG7lz59bo0aPNvgh91DEmOTExMRoxYoSee+45SdK7776rb775JsWapITxvD/44ANJCe//xYsXKygoSLVq1dKOHTt08eJFLVq0yFTzxx9/rE6dOqW6Tjwe+p3/pNbvSAl/P8OGDZOtra2ef/55zZ07V/fu3VP37t0lSd26ddOcOXO0d+9eNWnSROvXr1d8fLzGjBljGoZl3Lhxqlatmv766y8FBARo4cKF6tq1qxo0aCBJGjFihLZv355qHclp0aKFmjZtKknq27evFi1apEOHDqlOnTpavHixKlasqL59+5rmHzt2rOrWrauzZ8+qTJkyj1z//fv3NWnSJDVp0sR0/pyW415ajsF79uzRihUrTKFIWiRuN1++fEl+9zExMZo4caJpnrS8j2bOnKnGjRvro48+Mq2nfPnyKW4/LcentPz+pYQL5j777DPZ2dmpbNmyqlu3roKCgvTWW2/p3Llz+uOPP7R06VJVrlxZUkIf9dJLL2nz5s2mz2YxMTEaPny46fjbsGFDrVmzRjt27FCePHlUrlw51ahRQ7t27Uo2jNy5c6cOHTqk9evXm94PD55vXL58WQ0bNjRdXJDauUhyLOnvEt9DyX3eTJzHMAwNGjRIbdq0kbe3t4KDgx+rrkSWfNZ9WGrniX379tXvv/+ue/fuqV69ehozZoxp2uN+B5CctOyrh61YsUIBAQGmizGTkzNnzlSPsU2bNk0S1Dz4N1SyZEkdOHBAGzduTDEEl1I/F0hJ586d9dJLL5m22aRJE50/f15ly5bV4sWLVadOHdNzdMuUKaP9+/dry5YtKa7Pmhp6FlHDLBSsPKxNmzY6duyYPv74Y9nY2KhJkyZq27at2WcvSapZs6ZKlSqld999V9HR0WratKk+/PBDK1WddRG0IEUXL15UTEyM2QlrgQIFkpyoHTlyRF9//bWOHz+u27dvyzAMSdKVK1dUrly5FNd/7tw5TZs2TQcPHtTNmzfNlnN3d1eLFi3UuXNnNWrUSLVr19ZLL71kOlk5ceKEIiMjVaNGDbN13rt3TxcuXHisn9PJycniZzXcvXtXN27cMLsaxs7OTp6enqaruC5cuKCYmBjTiZMkOTg4yMfHx/QA8woVKqhs2bJau3atunbtqr/++kthYWFq1KhRkm2Gh4erW7duKlu2rKmzkqQmTZqYHlZVpUoVzZ07N9Xavby8zF4fP35cJ06cMH2hLCWc2MTHxys4OFgnTpyQnZ2d2dUZD3rc7fv6+iZ5nfjw+MQx0hM9fJXGtWvX1KVLFzVq1EhvvfVWqtuxRJMmTUz/n/gAuVdeecV0l0uXLl1MV5UWK1ZM69atM1v+5MmT6tmzp3r16mV6z1pixIgR+vfff/XDDz8kmda8eXPVqlVLISEhmjdvnvr06aOlS5emOtZ9Sn799VfNmDFD33zzzWM966RQoUL66quvNHz4cC1atMh0Bbmnp6fpw8aj9tXDPD09k7Tt3LlTs2bN0pkzZxQeHq64uDjdv39fUVFRKY47XLx4cbO/68KFC5vG203Jgw+Ms7GxkYuLi2mZs2fPysPDw2z/psdYt3j20Lc+Gn3rf56WvjXx9/byyy+bQqcKFSpo3759WrZsmapXr55p9c2ePVvr16/X999/n6TPrFGjhlavXq2bN29q+fLl6tOnj3766afHfg6YlHBl/JAhQzR69Gi98MILaV7OwcFB06dP19ChQ1W9enXZ2dmpZs2aqlOnjunv+VH76mHu7u5Jxj635BiTK1cu05d80uP3rVLCOOwP9q1FihQx+3IntSvMYRn6nbQrV66c2ZW5Li4uZn+/iQ8UTnwPHz9+XBcuXDDri6SE0OLChQu6e/euQkJCzPa9vb29vLy8TPsprR78W8qdO7ecnJxMz5A6fvy4du/eLT8/vyTLXbhwQYcPHzZ79sOcOXPMnpMSExOj3r17yzAM0x3l6SU8PFwDBgzQqFGjkoQ2iRLvQE+0bt06FStWLMV1FitWzGxdaXkfHTt2LMW7aZLbflqOT4/6/ScqV66c2cV6rq6upueUnD59Wvb29mbvkYIFC6pMmTKm8xkp6fHXxcVFxYsXNwvGXVxczJ4r9qBjx46pSJEiKYZuHTp00PDhw7V9+3b5+/urQYMGpiDqUecilvZ3abFo0SJFRESoW7duKc7z4Pu+WbNmZmGPZPln3QeldJ6YaPDgwerVq5fOnTunKVOmaNy4caleFJjRrl69qu3bt2vq1Klm7Y/aVw97+LxWSrjgc+XKlbp8+bLu37+vmJiYVENLKfVzgbQsk/h3GBYWprJly+rs2bN65ZVXzOb38fHJskFLZlu0aFGStj/++CNJ24kTJ0z/P27cOI0bN85ser9+/ZIs89FHH5mFbUiKoAVPJDIyUoGBgQoICNCkSZNUsGBBXblyRYGBgY98cFL37t1VvHhxjR49WoULF1Z8fLyaNm1qWs7T01O///67/vzzT+3cuVN9+vSRv7+/pk2bpoiICLm6uiZ7AMmb9/EeKrVmzZpUHzomJT0ZzQjNmjXTr7/+qq5du2rt2rUKCAhQwYIFzeYJDw9Xly5dlCdPHs2YMUMODg6mabNnzzbdSpmWqyIe/oI6MjJSbdq0Ufv27ZPMW7RoUZ0/fz7V9T3u9lPTu3dv09UJD7t27Zo6dOggPz8/s6FXpISTy4ev6Eh8nXgVSXLzhIaGJrnK5EElS5ZUwYIFdf78edWsWVNjxozRvXv3JCV9yNipU6f03nvv6e2331bPnj3TVJ+Tk1OSfTZy5Eht2bJFixcvTvYqlLx58ypv3rwqXbq0KlWqpOrVq2vTpk1q2rSpXFxckgxjkrjdh69USRyu5quvvjK7srdgwYKys7NLcgL08L4KCAjQ5s2bFRYWJnt7e+XLl0+1atUyXdGS2r5KzsPvy+DgYHXr1k3vvPOOPv74Y+XPn1979+7V0KFDFRMTk2LQkty2HvWBNrkHxj3uh2AgPdC3ph/61v9Ys28tWLCg7O3tVbZsWbN5ypYtawrjM7K+RPPmzdPs2bM1f/78ZL8UyJ07t0qVKqVSpUrJ19dXDRo00IoVK9StW7dkv8CKjY3V7du3k/Stf/31l3r06KHBgwfrjTfeeGS9D/etXl5e+uWXX3T37l3FxMSoUKFCat26tekLj9T2VXKSe19acoyxpJ+kb80e6HcSPOrhwYltieFxZGSkPD09NWnSpCTrSilUsNSDfVNyddSrV0/9+/dPspyrq6vi4+PNvsh/8M6emJgY9enTR5cvX9bChQvNwqq0HPcedQy+ePGiLl26ZHY3aWLdFStW1MaNG9WmTRvTnQaSHvnA84ePaWl5H6XWhz7u9hOl9fefHsfBx31vPuxR5xCtW7dWQECAtmzZoh07dmj27NkaOHCg2rdvn+q5yJP0d4nvodDQULN9Hhoaauqjd+3apQMHDiS5wK1Vq1Zq1qyZJkyYYHan1MNh65N+1pVSP09M5OrqKldXV5UtW1b58+fXu+++q549e6pw4cKP9R1AStKyrx60cuVKFShQQPXr1zdrT21fJefh4eMSH5o+cOBA+fn5KU+ePJo3b54OHjyY6nos+Rt4cD8nXsSZ0vsbyEoIWpCikiVLysHBQQcPHjRdUXL79m2dO3fOdOXlmTNndOvWLfXv319FixaVlHA11IMSD5BxcXGmtps3b+rs2bMaPXq06WQ3uTFznZyc1LhxYzVu3FgNGzY0jb3u6empGzduyM7OLsmtyg9uNy0H4ie5zTxv3rxycXHR4cOHTfskLi5O//zzj6nDe+655+Tg4KB9+/aZbpWPiYnR4cOH1bFjR9O6mjZtqqlTp+rIkSP67bffklxNFB4ersDAQDk6Ourbb79NchVmcuPNOzg4mO331FSsWFGnTp1SqVKlkp3u7u6u+Ph4/f3330mG2rBk+w93xgcPHjR9AePs7Jzs1SaJX7R4enpq3LhxScaC9PX11dSpUxUTE2N63+3cuVNlypQxDXfg6+urXbt2mQ1HtXPnziRXAT/o6tWrunXrlukEJ6X3w7///quOHTvqjTfeSHaIKl9f3yS3Xz68bcMwNGrUKG3atEmLFi1K823bhmGYxgL29fXVzJkzFRoaatqPO3fulJOTk9kViWvXrtWQIUM0ZcoU0225iRwdHeXp6amgoCDT1SLx8fEKCgpSu3btkmw/8cNEUFCQQkNDTSd1ye2r5I4JKTl69KjplvHE3/eGDRseuVx6K1OmjNasWaPo6GjTVcHJjVsKPAp963/oW5+dvtXR0VHe3t46e/as2brPnTtn+hkzsj4p4QvWmTNnat68eWm+IzE+Pt7Ut/r5+enOnTs6cuSIKfDYtWuX4uPjza5y3r17t7p3767+/fsnO7zI45yHJH5BeO7cOR05ckS9e/eWlPy+epy+NS3HmMxQpkwZXb161WxYFfrW9Ee/859HDR32uDw9PbVhwwY5Ozun+KWlq6urDh48aNrXsbGxOnr0qCpWrJiudfz2228qXrx4ihc2JVdfYshy/vx5ff/990kuREjLce9Rx+CcOXOa3YEnSVOnTlVERISGDh2qIkWKyNHR0ezZHonS2t+m5X3k7u6uoKCgZJ9XUaBAgSTbT8vxKS2//0cpW7asYmNjdfDgQdOdMYl/V6ndSfa4PDw8dPXq1VSHkitatKjeeecdvfPOO5o8ebKWL1+u9u3bp/hcuyft70qUKCFXV1cFBQWpQoUKkhLOyw4ePKh33nlHkjRs2DCzZw1dv35dgYGB+vLLL01/7ymdY6XHZ91HnScmJzFAePCz+aO+A3iUtOyrB7f/888/64033kgSCiW3r9J6jJUShkf38/MzDbct6bHvPkwPZcqUSdJHcf6ArIIn1iBFefLkUatWrfTFF18oKChIJ0+e1KBBg0xpspRw266Dg4MWLVqkixcv6vfff08yVnPx4sVlY2OjLVu2KCwsTBEREcqfP78KFCigH3/8UefPn1dQUJDGjx9vttz8+fO1du1anT59WmfPntXGjRvl6uqqfPnyyd/fX76+vurVq5e2b9+u4OBg7du3T19++aXpAFu8eHEFBwfr2LFjCgsLM3sg3YOcnJxMVy+m9C+1Kw3atWunWbNmafPmzTpz5ozGjBmj27dvm/ZT7ty59c4772jixIn6888/derUKX366ae6d++e2VjIJUqUkJ+fn4YOHaq4uDizqw/Cw8PVuXNnRUZGasyYMQoPD1dISIhCQkJSPfksXry4IiMjFRQUpLCwMEVFRaU47/vvv6/9+/dr5MiROnbsmM6dO6fNmzebbictUaKEWrRooSFDhmjz5s26ePGidu/eneqDz1Lb/r59+zRnzhydPXtWS5Ys0caNG9WhQ4cU13Xt2jW1b99eRYsW1cCBAxUWFmbaB4maNWsmBwcHDR06VP/++69paJAHx9Lt0KGDtm3bpu+++06nT5/W9OnTdeTIEdMJVUREhCZMmKADBw4oODhYQUFB6tmzp0qVKqXatWunWN/JkyfVoUMH1apVS506dTLV9uBVYG3atNHFixc1ceJEnT59WkuWLNGGDRvMTj5HjBihNWvWaPLkycqTJ49pPYl3hVy8eFGzZs3SkSNHdPnyZe3bt08fffSRcubMaRprOyAgQOXKldOAAQN0/Phxbdu2TVOnTtW7775rCgl+/fVXDRw4UAMHDlSlSpVM27l7966plk6dOmn58uVatWqVTp8+reHDhysqKkotW7Y0zbNy5UodOHBAFy5c0C+//KI+ffrovffe0/PPP5/ivkrumJCSUqVKKSYmxnSMWb16tZYtW5bi/BmlWbNmMgxDn376qU6fPm16D0kyOyYCj0LfSt/6LPatkhQYGKgNGzZo+fLlpmet/O9//0vyBUFG1Dd79mx99dVXGjt2rIoXL25aR2L/ExkZqSlTpujAgQO6dOmSjhw5osGDB+vatWumoebKli2r2rVr69NPP9WhQ4e0d+9ejRo1Sk2aNDF9ebtr1y5169ZN7du3V4MGDUzbSXwYc1r31YYNG7R7925dvHhRmzdvVufOnfXKK6+kOhyps7OzcubMqW3btunGjRtm/fnD0nKMyQy1atVSyZIlNXDgQB0/flx79+5NMswJnhz9Ttr6HUs0a9ZMBQsWVI8ePbRnzx7TMXz06NG6evWqpIS/+Tlz5mjz5s06ffq0RowYoTt37qR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+      "text/plain": [
+       "<Figure size 1635x4000 with 23 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.catplot(data=pearson_df.loc[pearson_df['Post-QPP'].isin(post_ret_predictors)].sort_values(['measure', 'dataset']),\n",
+    "            x='PostQPP', y='pearson', hue='measure', col='dataset', col_wrap=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-02-27T10:16:41.154732Z",
+     "start_time": "2024-02-27T10:16:40.743619Z"
+    },
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "Y-x0RV71usDt",
+    "outputId": "c4e03ee9-6841-4849-84bc-25170c947a77"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "# pre_order"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 424
+    },
+    "id": "YUM25mWkz3hl",
+    "outputId": "46deacd4-7f5f-4fc1-91c6-b671deb06064"
+   },
+   "outputs": [],
+   "source": [
+    "pearson_df.sort_values(['measure', 'r'], ascending=[True, False])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "pF2gzEholC_R"
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.model_selection import RepeatedKFold\n",
+    "\n",
+    "corr_method = 'pearson'\n",
+    "n_splits = 2\n",
+    "results_per_dataset = {}\n",
+    "for dataset, _df in df_eval.groupby('dataset'):\n",
+    "# print(dataset)\n",
+    "# split df into two sets\n",
+    "train_df, test_df = train_test_split(_df, shuffle=False, random_state=1609, test_size=0.5)\n",
+    "rkf = RepeatedKFold(n_splits=n_splits, n_repeats=2, random_state=1609)\n",
+    "# correlate with the effectivnness metric\n",
+    "# p_corrs = train_df.iloc[:, 5:].corrwith(train_df['value'])\n",
+    "_res_pre_fold = []\n",
+    "_res_vector = []\n",
+    "for i, (train_index, test_index) in enumerate(rkf.split(_df)):\n",
+    "    p_corrs = _df.iloc[train_index].iloc[:, 5:].corrwith(_df.iloc[train_index]['value'], method=corr_method)\n",
+    "_pre = _df.iloc[test_index][pre_ret_predictors].corrwith(_df.iloc[test_index]['value'], method=corr_method)\n",
+    "for pred in post_ret_predictors:\n",
+    "    train_best = p_corrs.loc[p_corrs.index.str.startswith(pred)].idxmax()\n",
+    "if i % 2 == 0:\n",
+    "    _\n",
+    "_df.iloc[test_index][train_best].corr(_df.iloc[test_index]['value'], method=corr_method)\n",
+    "\n",
+    "# _res_pre_fold.append(_df.iloc[test_index][pre_ret_predictors.tolist() + train_best].corrwith(_df.iloc[test_index]['value']))\n",
+    "# if i%2 == 1:\n",
+    "#     _res_vector.append(pd.concat(_res_pre_fold, axis=1).mean(1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "z8n5f-Y4ibT5",
+    "outputId": "05ca8a7f-8719-4504-82fa-c9875022b9cc"
+   },
+   "outputs": [],
+   "source": [
+    "rkf.split(_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "yVIv7VVBNAuM",
+    "outputId": "04aa7e4f-1ba5-4b6f-ec38-6addd7ee452a"
+   },
+   "outputs": [],
+   "source": [
+    "from collections import defaultdict\n",
+    "\n",
+    "_post_pred_res = defaultdict(list)\n",
+    "for i, (train_index, test_index) in enumerate(rkf.split(_df)):\n",
+    "    p_corrs = _df.iloc[train_index].iloc[:, 5:].corrwith(_df.iloc[train_index]['value'], method=corr_method)\n",
+    "_pre = _df.iloc[test_index][pre_ret_predictors].corrwith(_df.iloc[test_index]['value'], method=corr_method)\n",
+    "for pred in post_ret_predictors:\n",
+    "    train_best = p_corrs.loc[p_corrs.index.str.startswith(pred)].idxmax()\n",
+    "_t_corr = _df.iloc[test_index][train_best].corr(_df.iloc[test_index]['value'], method=corr_method)\n",
+    "_post_pred_res[pred] += [_t_corr]\n",
+    "_post_pred_res"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "WN7TQPx9xIOH",
+    "outputId": "1e799ee1-e595-47c6-8614-d0c95d982b3e"
+   },
+   "outputs": [],
+   "source": [
+    "_df.iloc[:, 5:].corrwith(_df['value']).sort_values()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "r9dPAXm6EfEa",
+    "outputId": "d7fc3876-905d-4604-da5f-7b3a1d9839a4"
+   },
+   "outputs": [],
+   "source": [
+    "_res_pre_fold"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "LOjg_sBGvimc",
+    "outputId": "32becefc-b361-4af0-92f0-b5e2c7eaa477"
+   },
+   "outputs": [],
+   "source": [
+    "train_best = []\n",
+    "p_corrs = train_df.iloc[:, 5:].corrwith(train_df['value'])\n",
+    "for pred in post_ret_predictors:\n",
+    "    train_best.append(p_corrs.loc[p_corrs.index.str.startswith(pred)].idxmax())\n",
+    "p_corrs[pre_ret_predictors.tolist() + train_best]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "AEcNWKIdzYev",
+    "outputId": "86389c74-fcbc-4fe6-b43e-63348ac96826"
+   },
+   "outputs": [],
+   "source": [
+    "test_df[pre_ret_predictors.tolist() + train_best].corrwith(test_df['value'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "YjDgaCok51j1"
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}