G2PSR_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Genome-to-Phenome Sparse Regression (G2PSR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"..\")\n",
    "\n",
    "from bayes_G2PSR import G2PSR\n",
    "from gpu import DEVICE\n",
    "import torch as pt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "import copy\n",
    "from plotnine import *\n",
    "\n",
    "# Evaluation metric for synthetic data\n",
    "from sklearn.metrics import precision_recall_curve\n",
    "from sklearn.metrics import auc\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.metrics import average_precision_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load and format synthetic data for G2PSR\n",
    "\n",
    "Synthetic data generated with `synthetic_data.py` file found in [`utils`](https://gitlab.inria.fr/mlorenzi/pathways-bnn/-/tree/master/utils)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Set up data directory\n",
    "data_directory = \"/user/mdeprez/home/Documents/BNN/benchmark_results/local_synthetic_dataset/200s_30g_15t_3tg_100tt_0.20n_0rep/\"\n",
    "\n",
    "dir_name = data_directory.split(\"/\")\n",
    "info =  dir_name[-2].split(\"_\")\n",
    "truey = [1]*int(info[3][:-2]) + [0]*(int(info[1][:-1]) - int(info[3][:-2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(554, 200)\n",
      "(554, 30)\n",
      "(554, 15)\n",
      "(200, 15)\n"
     ]
    }
   ],
   "source": [
    "# Load data\n",
    "X_csv=pd.read_csv(data_directory+'gen_matrix.csv', sep=';',header=None)\n",
    "X_Gsnp =pd.read_csv(data_directory+'gen_snp.csv', sep=';',header=None)\n",
    "W_csv = pd.read_csv(data_directory+'w_snp_target.csv', sep=';',header=None)\n",
    "Y = pd.read_csv(data_directory+'target_noise.csv', sep=';',header=None).transpose()\n",
    "\n",
    "# Data shape\n",
    "print(X_csv.shape)         # (SNPs, samples)\n",
    "print(X_Gsnp.shape)        # (SNPs, genes)         \n",
    "print(W_csv.shape)         # (SNPs, phenotypes) Used to generate genome-to-phenome relationship in synthetic data\n",
    "print(Y.shape)             # (samples, phenotypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file `gen_snp.csv` contains the information associating SNPs to their respective genes.  \n",
    "It is a matrix filled with 0 or 1 values with SNPs in row and Genes in columns, the value 1 associated the SNPs to the specific genes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "     0    1    2    3    4\n",
       "0  1.0  0.0  0.0  0.0  0.0\n",
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     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_Gsnp.iloc[0:5, 0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30\n",
      "torch.Size([200, 2])\n",
      "torch.Size([200, 15])\n"
     ]
    }
   ],
   "source": [
    "# Format data\n",
    "## Genetic data is a list of tensor each element correspond to a gene and its associated SNPs.\n",
    "X_group = X_Gsnp.iloc[:,:int(info[1][:-1])].to_numpy()\n",
    "X_group = X_group[[i == 1 for i in np.sum(X_group, axis = 1)],:]\n",
    "X_tensor = []\n",
    "for i in range(0,X_group.shape[1]):\n",
    "    snpGene = X_group[:,i] == 1    \n",
    "    Xi = pt.tensor(X_csv.loc[snpGene.tolist(),:].to_numpy().transpose(), device=DEVICE, dtype=float)\n",
    "    X_tensor.append(Xi)\n",
    "\n",
    "Y_tensor = pt.tensor(Y.to_numpy(), device=DEVICE, dtype=float)\n",
    "\n",
    "# Data shape\n",
    "print(len(X_tensor))\n",
    "print(X_tensor[0].shape) # First gene has 2 SNPs\n",
    "print(Y_tensor.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### Launch G2PSR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Average difference with target: tensor(-0.0106, dtype=torch.float64, grad_fn=<MeanBackward0>)\n",
      "probability that the gene is not relevant: \n",
      "tensor([[0.0046],\n",
      "        [0.0026],\n",
      "        [0.0206],\n",
      "        [0.4534],\n",
      "        [0.3753],\n",
      "        [0.9262],\n",
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      "        [0.2967],\n",
      "        [0.7542],\n",
      "        [0.3755],\n",
      "        [0.4874]], grad_fn=<MulBackward0>)\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "g2psr=G2PSR(X_tensor, Y_tensor)\n",
    "result = g2psr.optimize(X_tensor, Y_tensor, epochmax=20000, step=1000, verbose = True)\n",
    "end_time = time.time()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### G2PSR synthetic scenario results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-199-a029f96d5d75>:16: RuntimeWarning: invalid value encountered in true_divide\n"
     ]
    }
   ],
   "source": [
    "# Get perfomance metrics\n",
    "truey = [1]*int(info[3][:-2]) + [0]*(int(info[1][:-1]) - int(info[3][:-2]))\n",
    "compil_time = end_time - start_time\n",
    "\n",
    "# Performance during optimization process\n",
    "avg_auprc = []\n",
    "auc_auprc = []\n",
    "fscore = []\n",
    "\n",
    "for i in range(0, len(result[\"plist\"])):\n",
    "    testy = copy.deepcopy(result[\"plist\"][i])\n",
    "    testy = [1-j for j in testy]\n",
    "    precision, recall, thresholds = precision_recall_curve(truey,  testy)\n",
    "    avg_auprc.append(average_precision_score(truey, testy))\n",
    "    auc_auprc.append(auc(recall, precision))\n",
    "    f1 = (2 * precision * recall) / (precision + recall)\n",
    "    ix = np.argmax(f1)\n",
    "    fscore.append(f1[ix])\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "### G2PSR optimization analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> LOSS parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss = []\n",
    "epoch = []\n",
    "for i in range(0, len(result['Losslist'])):\n",
    "    loss.append(float(result['Losslist'][i]))\n",
    "    epoch.append(i*1000)\n",
    "\n",
    "loss_df = pd.DataFrame(data = {'Loss':loss, 'Epoch':epoch})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8785368247065)>"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ggplot(loss_df, aes(x='Epoch', y='Loss'))\n",
    " + geom_line()\n",
    " + scale_y_log10()\n",
    " + theme_bw()\n",
    " + geom_vline(xintercept = 17000, color = \"red\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Reconstruction error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "ynoise = pd.DataFrame(data = result['ynoise'])\n",
    "ynoise.columns = [\"P\" + str(i) for i in ynoise.columns.tolist()]\n",
    "ynoise[\"Epoch\"] = epoch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Epoch</th>\n",
       "      <th>Phenotype</th>\n",
       "      <th>Sigma</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>P0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000</td>\n",
       "      <td>P0</td>\n",
       "      <td>0.890807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000</td>\n",
       "      <td>P0</td>\n",
       "      <td>0.976064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3000</td>\n",
       "      <td>P0</td>\n",
       "      <td>1.010311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4000</td>\n",
       "      <td>P0</td>\n",
       "      <td>1.026832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>15000</td>\n",
       "      <td>P14</td>\n",
       "      <td>0.901007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>16000</td>\n",
       "      <td>P14</td>\n",
       "      <td>0.806893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>17000</td>\n",
       "      <td>P14</td>\n",
       "      <td>0.655439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>298</th>\n",
       "      <td>18000</td>\n",
       "      <td>P14</td>\n",
       "      <td>0.428303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>299</th>\n",
       "      <td>19000</td>\n",
       "      <td>P14</td>\n",
       "      <td>0.124544</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>300 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Epoch Phenotype     Sigma\n",
       "0        0        P0  0.500000\n",
       "1     1000        P0  0.890807\n",
       "2     2000        P0  0.976064\n",
       "3     3000        P0  1.010311\n",
       "4     4000        P0  1.026832\n",
       "..     ...       ...       ...\n",
       "295  15000       P14  0.901007\n",
       "296  16000       P14  0.806893\n",
       "297  17000       P14  0.655439\n",
       "298  18000       P14  0.428303\n",
       "299  19000       P14  0.124544\n",
       "\n",
       "[300 rows x 3 columns]"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ynoise_df = pd.melt(ynoise, id_vars = \"Epoch\", value_vars = ynoise.columns.tolist()[:-1], value_name='Sigma', var_name = \"Phenotype\")\n",
    "ynoise_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8785355203744)>"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ggplot(ynoise_df, aes(x='Epoch', y='Sigma', color = \"Phenotype\"))\n",
    " + geom_line()\n",
    " + theme_bw()\n",
    " + geom_vline(xintercept = 17000, color = \"red\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Alpha parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha = pd.DataFrame(data = np.array(result['plist'])[0:21, 0:30, 0])\n",
    "alpha.columns = [\"G\" + str(i) for i in alpha.columns.tolist()]\n",
    "alpha[\"Epoch\"] = epoch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Epoch</th>\n",
       "      <th>Gene</th>\n",
       "      <th>Alpha</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>G0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000</td>\n",
       "      <td>G0</td>\n",
       "      <td>0.500231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000</td>\n",
       "      <td>G0</td>\n",
       "      <td>0.498193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3000</td>\n",
       "      <td>G0</td>\n",
       "      <td>0.498571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4000</td>\n",
       "      <td>G0</td>\n",
       "      <td>0.498495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>625</th>\n",
       "      <td>16000</td>\n",
       "      <td>G29</td>\n",
       "      <td>0.504961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>626</th>\n",
       "      <td>17000</td>\n",
       "      <td>G29</td>\n",
       "      <td>0.530400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>18000</td>\n",
       "      <td>G29</td>\n",
       "      <td>0.558510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>628</th>\n",
       "      <td>19000</td>\n",
       "      <td>G29</td>\n",
       "      <td>0.581898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>629</th>\n",
       "      <td>20000</td>\n",
       "      <td>G29</td>\n",
       "      <td>0.487376</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>630 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Epoch Gene     Alpha\n",
       "0        0   G0  0.500000\n",
       "1     1000   G0  0.500231\n",
       "2     2000   G0  0.498193\n",
       "3     3000   G0  0.498571\n",
       "4     4000   G0  0.498495\n",
       "..     ...  ...       ...\n",
       "625  16000  G29  0.504961\n",
       "626  17000  G29  0.530400\n",
       "627  18000  G29  0.558510\n",
       "628  19000  G29  0.581898\n",
       "629  20000  G29  0.487376\n",
       "\n",
       "[630 rows x 3 columns]"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alpha_df = pd.melt(alpha, id_vars = \"Epoch\", value_vars = alpha.columns.tolist()[:-1], value_name='Alpha', var_name = \"Gene\")\n",
    "alpha_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8785360623496)>"
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ggplot(alpha_df, aes(x='Epoch', y='Alpha', color = \"Gene\"))\n",
    " + geom_line() \n",
    " + scale_color_grey()\n",
    " + theme_bw()\n",
    " + geom_vline(xintercept = 17000, color = \"red\")\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> G2PSR performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_df = pd.DataFrame(data = {'AUPRC':avg_auprc, 'AUC':auc_auprc, 'Fscore':fscore, 'Epoch':epoch})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/user/mdeprez/home/miniconda3/envs/vae_env/lib/python3.8/site-packages/plotnine/guides/guides.py:197: PlotnineWarning: Cannot generate legend for the 'color' aesthetic. Make sure you have mapped a variable to it\n"
     ]
    },
    {
     "data": {
      "image/png": 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Lkxr4uWLXHn5duHrYmAkKy8NOfHy8hg4dqvz8fD300EM6evSoNm7cqMcee6ze92zcuFHDhg2r85kpO3fuVM+ePdWhQwcVFRVpyZIlGjx4cJ33p6amBg5/JScnBy5VD9eO5HQ6o2cnbQTTNAPbZtedVLJv/yR6GO3s2j+Px6NrrrmmVs+iqofn6nQ6nYHH9bFrD8/Hyh5aHnYk6f7779ecOXM0ceJEJSYmKicnR/369ZPX69W0adM0d+7cswlZZy9J3Llzp/74xz/WGeeTTz7Riy++qIqKCiUnJ2vIkCHKyclp6c0BADSDx+PhsnOEVESEnaSkJM2YMaPO8rS0NC1fvrzWspSUFK1evfq840yaNEmTJk0KS40AgPCrrKxUUVERl50jpKJkThAA0BocOnRIkpjZQUgRdgAAEcPtdqtNmzbKyMiwuhTYCGEHABAxPB6PunXrFj0nIyMq8NUEAIgYNTcUBEKJsAMAiBhciYVwIOwAACIGMzsIB8IOACBiMLODcCDsAAAigmEY8ng8zOwg5Ag7AICIcPToUVVVVTGzg5Aj7AAAIoLH45GkwIdCA6FC2AEARAS3262MjAzFx8dbXQpshrADAIgInK+DcCHsAAAigtvt5nwdhAVhBwAQEZjZQbgQdgAAEYGZHYQLYQcAEBGY2UG4EHYAAJY7ffq0jh8/zswOwoKwAwCwXM09dpjZQTgQdgAAlnO73Wrbtq06dOhgdSmwIcIOAMByNefrOBwOq0uBDRF2AACW40oshBNhBwBgOa7EQjgRdgAAlmNmB+FE2AEAWI6ZHYQTYQcAYKnq6moVFhYys4OwIewAACx1+PBhGYbBzA7ChrADALCU2+2W0+lUly5drC4FNkXYAQBYyuPxqEuXLnK5XFaXApsi7AAALMWVWAg3wg4AwFJciYVwI+wAACzFzA7CjbADALAUMzsIN8IOAMAypmkys4OwI+wAACzz1Vdfqby8nJkdhBVhBwBgGbfbLUmEHYQVYQcAYBmPx6OUlBS1a9fO6lJgY4QdAIBlOF8HLYGwAwCwDFdioSUQdgAAlmFmBy2BsAMAsAwzO2gJfOqapKSkJLlcLpmmGdJxTdMMjBvqsSNBzTbZcdsk+/dPoofRzg79c7vd6t69e73bEJU9NE05dK4vDdRshx42JFw9bMwHxxJ2JA0YMEApKSny+XwhHzslJUWGYcgwjJCPHSn8fr/VJYRNa+ifRA+jXbT2r6KiQsXFxerSpcsFv/9GXQ99PsVKZ7cpyJ8r0drDYIWjhykpKUGvS9iRtHv3bvXt21dpaWkhHdcwDB07dkwdO3aU02m/I4amacrv9ysmJkYOh8PqckLO7v2T6GG0i/b+HTlyRJLUq1even9Lj8oentsWl8sVeFyfaO9hMMLVQ6/XG/S6hB1JpaWl8vl8If9CczgcgXHt+kUsybbb11r6J9HDaBet23fw4EHFxcUpIyOj3vqjsofn6nQ4HIHHDb8liravkcLVw8YcjQkqYlVWVuqZZ57R1q1b611n69ateuaZZ1RRURH0Pw4AaL3cbre6desWPTM2iFpBfYW9+uqreuWVVzRw4MB61xk4cKDmz5+vl156KWTFAQDsy+PxcNk5WkTQYWfatGlq27Ztveu0bdtW06dP1+uvvx6y4gAA9lVzJRYQbkGFnb1792rQoEENrnfVVVdp7969zS4KAGB/zOygpQR9oDRqLvkDAEQFZnbQUoIKO3369NH27dsbXG/r1q3q3bt3s4sCANibYRg6ePAgMztoEUGFnbFjx2rWrFnas2dPvevs2bNHf/rTnzRu3LiQFQcAsKeioiJVV1czs4MWEdR9dh599FG9+eabuvbaa/XAAw/o5ptvVrdu3eRwOOTxeLR+/XrNmzdPF198sR599NFw1wwAiHIej0eS1K1bN4srQWsQVNhJTEzUpk2b9OCDD2rWrFl6/vnna73ucDg0duxYzZ07VwkJCWEpFABgH263W5mZmYqLi7O6FLQCQd9BuUOHDnr99dd18OBBbd26VYWFhTJNU127dtWwYcPUtWvXcNYJALARrsRCS2r0x0V069ZNOTk59b5++vRptWvXrllFAQDsjSux0JJCdo/u4uJi/frXv+aLFwDQIGZ20JKCDjsffPCBHnjgAf3whz/Uww8/rC+//FKSdPToUU2bNk09evTQ73//e91yyy1hKxYAYA/M7KAlBXUYa/369Ro9erRM01RaWpreffddLVu2THl5eZowYYKOHz+uu+++W48//rguueSScNcMAIhyzOygJQU1s/O///u/GjhwoAoLC1VUVKSvvvpKN910k2699VYlJibqww8/VF5eHkEHANCgU6dO6cSJE8zsoMUEFXb+85//6H/+53+UmZkpSUpKStKzzz4rn8+nZ599Vt/5znfCWiQAwD5q7rHDzA5aSlBh59ixY+rcuXOtZTXP+/TpE/qqAAC25Xa7lZSUpPbt21tdClqJoE9Qdjgc510eExMTsmIAAPZXc75OfT9XgFAL+j47N9xwg5zOutnouuuuq7Xc4XDo5MmToakOAGA7XImFlhZU2HnyySfDXQcAoJXgSiy0NMIOAKBFud1u7smGFhX0YazKykqtW7dOBQUF6tKli0aOHKm0tLRw1gYAsCFmdtDSggo7Ho9HI0eO1P79+2WapiQpJSVFq1ev1vXXXx/WAgEA9lFdXa3Dhw9zzg5aVFBXY/3617/WiRMntGTJEn366af661//qszMTP3kJz8Jd30AABspLCyUYRjM7KBFBTWzs23bNv3ud79Tbm6uJOmyyy5TZmamrrnmGpWUlCg1NTWsRQIA7MHtdismJkadOnWyuhS0IkHN7Bw6dEh9+/attezKK6+UaZoqLCwMS2EAAPvxeDzq2rWrXK6gTxkFmi2osGOaZp0vzJp76xiGEfqqAAC2xD12YIWgo/XPf/7zWrf2rjlR+ZFHHtFFF10UWO5wOLRmzZoQlggAsAuuxIIVggo7119/vRwOh06fPl1r+bBhwySpznIAAM7H7XbrqquusroMtDJBhZ333nsvzGUAAFoDj8ejMWPGWF0GWpmgPwgUAIDmME2Tc3ZgiaBmdl577bV6X4uNjVV6erquvvpqJScnh6wwAIC9HDt2TBUVFZyzgxYXVNiZOHFig+skJCToF7/4hZ5++unm1gQAsCG32y1JzOygxQUVdrxeb72v+f1+HTlyRG+99ZZmzpypjIwMPfjggyErEABgDx6PRx07dlTbtm2tLgWtTFBhp2PHjhd8PT09Xf369VNZWZnmzZtH2AEA1MH5OrBKSE9QHjlypD7//PNQDgkAsAnusQOrhDTsVFRUKDY2NpRDAgBsgpkdWCWkYScvL08DBw4M5ZAAAJtwu93M7MASQZ2zs2rVqnpf8/v9Kioq0po1a7Rlyxb97W9/C1lxAAD78Hg8zOzAEkGFnTvvvPOCrzudTl199dV65513NHLkyEYXUVpaqrlz52rXrl1KSEhQdna2Ro0aVWe9o0eP6r777lN8fHxg2fDhw2udEL127VqtWLFCFRUVGjhwoKZPn67ExMRG1wQACJ3y8nJ5vV5mdmCJoMJOQUFB/QO4XOrYsWMggHzxxRe6+OKLG1XEyy+/LL/fr0WLFunIkSN64okn1LVrV1155ZXnXX/p0qVq06ZNneW7d+/W66+/rt/+9rfKzMzUrFmz9PLLL+vRRx9tVD0AgNA6ePCgJO6xA2sEdc5OVlZWvX+6dOmiU6dO6U9/+pMGDRqkSy+9tFEFVFZWaseOHcrNzVViYqJ69+6tESNGaMOGDY3emE2bNmnkyJHq1auXEhMTlZOTo+3bt+vMmTONHgsAEDput1txcXFKT0+3uhS0Qk0+Qbm0tFSvvfaavv/976tLly565JFHJEmzZ89u1DiFhYWSaqf9Xr16Be60eT7333+/Jk6cqD/84Q+1bnjodrvVs2fPwPOsrCwZhqHDhw83qiYAQGjVnK/jcDisLgWtUFCHsWr4fD6tW7dO+fn5Wrt2rSorK9WlSxcZhqE333yzSZ9kW1lZqYSEhFrL2rZtq4qKijrrJicn649//KN69eqlsrIyLV68WDNnztTzzz+vmJgYVVZW1rozp8PhUGJiYp2xSkpKVFJSIuns3aGrqqokSYZhNLr+C6kZL9TjRgrTNGUYhgzDsOU3MLv3T6KH0S6a+nfgwAF179690b2Iyh4ahpw6V3MDdUdTD5sqEnoYVNjZunWr8vPztWLFCh0/flypqamaNGmScnJydNlll6lDhw5KS0trUgHx8fF1wkhZWVmdACSd/fytPn36SDobfB544AGNGzdOR44cUdeuXRUfH6/y8vJa7ykvL68z1sqVKzV//vzA82HDhkmSioqKmrQNDSkuLg7LuGgZ9C/60UPr7du3T2lpaU3+PhtNPYzxepWhs79M+89zfmlrZWUPgwo7w4cPl8Ph0MiRI/Wzn/1M3/ve9xQTEyNJOnnyZLMK6NKli6SzJ69169ZN0tkTohtzxr5pmpLOHrYqKCgIhBe32y2n06nOnTvXWn/MmDGBdbxer9avXy9JyszMbNa2fJNhGCouLlZ6erqczpDe0igimKYpn88nl8tly99I7N4/iR5Gu2jqn9fr1Q033NDo77NR2cNzRwvS0tKkBrY3mnrYVOHqYWOCc1Bhp3///vrXv/6l9957T06nU8XFxbr99tvVrl27JhdZIz4+XkOHDlV+fr4eeughHT16VBs3btRjjz1WZ919+/YpMTFRXbp0UXl5uRYvXqxOnToFwsyIESP0/PPPa9iwYcrIyFB+fr6++93vKi4urtY4qampSk1NlXR2hqjmyq5w7UhOpzN6dtJGME0zsG123Ukl+/ZPoofRLpr6V/NREU3tQ1T18FydTqcz8Lg+0dTD5rKyh0H9q7t27dLevXv1q1/9Sl988YUmTpyojIwMZWdna82aNc1u0P333y9Jmjhxop5++mnl5OSoX79+8nq9ys7ODpyEXFRUpN/+9rcaN26cHnzwQZWWlurxxx8PzDINGDBA48aN09NPP62JEycqJiYmMDYAwBp+v18HDx7kHjuwTNAnKF966aV65pln9Mwzz+iDDz5Qfn6+3nzzTa1YsUIOh0MvvviiJOn6669vdBFJSUmaMWNGneVpaWlavnx54PmwYcMCh5/qc8stt+iWW25pdA0AgPAoKiqSz+cj7MAyTZpPuvbaazV79mwdPnxY69atU05Ojt59913dcMMN6tWrV6hrBABEMbfbLYfDoa5du1pdClqpRl16/k1Op1M/+MEP9IMf/EAVFRVas2aNli1bFqraAAA24PF41KlTp/Pe+R5oCSE7UyghIUF33XWX3n777VANCQCwAbfbzcdEwFJRcmo7ACBa1VyJBViFsAMACCtmdmA1wg4AIKyY2YHVCDsAgLBiZgdWI+wAAMLm5MmTOnXqFDM7sBRhBwAQNm63W5KY2YGlCDsAgLDxeDxKTk5W+/btrS4FrRhhBwAQNpyvg0hA2AEAhA1XYiESEHYAAGHDzA4iAWEHABA2zOwgEhB2AABhw8wOIgFhBwAQFlVVVTpy5AgzO7AcYQcAEBaHDh2SaZrM7MByhB0AQFh4PB65XC516tTJ6lLQyhF2AABh4Xa71bVrV8XExFhdClo5wg4AICy4EguRgrADAAgLrsRCpCDsAADCgpkdRArCDgAgLJjZQaQg7AAAQs40TWZ2EDEIOwCAkPN6vaqsrGRmBxGBsAMACDmPxyNJhB1EBMIOACDk3G63UlNTlZiYaHUpAGEHABB6nK+DSELYAQCEHFdiIZIQdgAAIcfMDiIJYQcAEHLM7CCSEHYAACHHzA4iCWEHABBSZWVlKikpYWYHEYOwAwAIqYMHD0oSMzuIGIQdAEBIud1uJSQkKDU11epSAEmEHQBAiHk8HnXv3l0Oh8PqUgBJhB0AQIhxJRYiDWEHABBSXImFSEPYAQCEFDM7iDSEHQBASDGzg0hD2AEAhIzf79ehQ4eY2UFEcVldQCRISkqSy+WSaZohHdc0zcC4oR47EtRskx23TbJ//yR6GO0isX+HDx+Wz+dT9+7dQ1JXVPbQNOXQub40UHMk9jDUwtVDlyv4CEPYkTRgwAClpKTI5/OFfOyUlK1aP34AABxaSURBVBQZhiHDMEI+dqTw+/1WlxA2raF/Ej2MdpHUv/3798vhcCgjIyNk31Ojroc+n2Kls9sf5P9BJPUwHMLRw5SUlKDXJexI2r17t/r27au0tLSQjmsYho4dO6aOHTvK6bTfEUPTNOX3+xUTE2PL+2nYvX8SPYx2kdi/wsJCde7cWYmJiSEZLyp7eG7GweVyBR7XJxJ7GGrh6qHX6w16XcKOpNLSUvl8vpB/oTkcjsC4dv0ilmTb7Wst/ZPoYbSLpO0L9Q0Fo7KH5+p0OByBxw2/JYq2r5HC1cPGzBxGSUwGAEQDrsRCJCLsAABCxu12E3YQcQg7AICQqTmMBUQSwg4AICRM02RmBxGJsAMACImTJ0/q9OnTzOwg4hB2AAAh4Xa7JYmZHUQcwg4AICQ8Ho8uuugiJScnW10KUAthBwAQEpyvg0hF2AEAhARXYiFSEXYAACHBzA4iFWEHABASzOwgUhF2AAAhwcwOIhVhBwDQbGfOnNGRI0eY2UFEIuwAAJrt0KFDkrjHDiITYQcA0Gwej0exsbHKzMy0uhSgDsIOAKDZ3G63unXrJqeTHyuIPHxVAgCajSuxEMkIOwCAZuNKLEQywg4AoNncbjczO4hYhB0AQLN5PB5mdhCxCDsAgGYxDINzdhDRCDsAgGbxer06c+YMMzuIWIQdAECzuN1uSVK3bt0srgQ4P8IOAKBZ9uzZo06dOikhIcHqUoDzIuwAAJplyZIlGjt2rNVlAPUi7AAAmuy///2vtm7dqsmTJ1tdClAvwg4AoMleffVVXX311bryyiutLgWoF2EHANAk1dXVWrx4MbM6iHiEHQBAk7zzzjs6ffq07r77bqtLAS6IsAMAaJKFCxcqOztbycnJVpcCXJDL6gIAANGnsLBQ69at05YtW6wuBWgQMzsAgEZbsmSJ+vTpo6FDh1pdCtAgwg4AoFEMw9DChQs1efJkORwOq8sBGkTYAQA0ynvvvSePx6N77rnH6lKAoBB2AACNsnDhQt16663KyMiwuhQgKJygDAAI2vHjx7Vy5UqtWrXK6lKAoDGzAwAIWn5+vlJTU/X973/f6lKAoBF2AABBMU1TCxYs0KRJkxQTE2N1OUDQIuIwVmlpqebOnatdu3YpISFB2dnZGjVqVJ31PvroI61cuVJut1sul0tXXnmlpkyZopSUFEnSxo0bNXv2bLVp0ybwngcffFDDhw9vqU0BANvatWuXPv74Y61evdrqUoBGiYiw8/LLL8vv92vRokU6cuSInnjiCXXt2rXOB8uVl5drzJgx6tu3r0zT1EsvvaQXX3xRTz31VGCdiy++WM8991wLbwEA2N+CBQt04403qmfPnlaXAjSK5YexKisrtWPHDuXm5ioxMVG9e/fWiBEjtGHDhjrrDhs2TFdffbXi4+OVkJCg0aNHa+/evRZUDQCtS3l5uZYtW8aHfiIqWR52CgsLJUndu3cPLOvVq5fcbneD792zZ0+t90nSgQMHlJubq6lTp2rx4sU6c+ZMaAsGgFZoxYoVcrlcuu2226wuBWg0yw9jVVZWKiEhodaytm3bqqKi4oLv++9//6s333xTjz/+eGDZFVdcoTlz5ig9PV2HDx/WCy+8oMWLF+v++++v9d6SkhKVlJRIkrxer6qqqiSdvStoKNWMF+pxI4VpmjIMQ4Zh2PIuqnbvn0QPo11L9m/BggXKyclRmzZtWvT/Myp7aBhy6lzNDdRt931QioweWh524uPj6wSbsrKyOgHo6woKCjRz5kxNnz5dl19+eWB5ZmZm4HHXrl11zz336LnnnqsTdlauXKn58+cHng8bNkySVFRU1KxtqU9xcXFYxkXLoH/Rjx42z5dffqlt27bpiSeeCNv3yYZEUw9jvF5l6Owv0/6vXTDT2lnZQ8vDTpcuXSRJBw8eVLdu3SSdDTNZWVnnXd/tduvJJ5/Uj3/84wY/gM7pdMo0zTrLx4wZEwg4Xq9X69evl1Q7LIWCYRgqLi5Wenq6nE7LjxiGnGma8vl8crlctvyNxO79k+hhtGup/r3wwgu65pprNGLEiLD9G/WJyh6eO1qQlpYmNfBzxe77oBS+HjYmeFseduLj4zV06FDl5+froYce0tGjR7Vx40Y99thjddb1eDx6/PHHdc8995z3cvKdO3eqZ8+e6tChg4qKirRkyRINHjy4znqpqalKTU2VJCUnJwcuVQ/XjuR0OqNnJ20E0zQD22bXnVSyb/8kehjtWqJ/1dXVWrJkiZ555hlL/w+jqofn6nQ6nYHH9Wkt+6BkbQ8tDzuSdP/992vOnDmaOHGiEhMTlZOTo379+snr9WratGmaO3eu0tLStHr1ap08eVKvvPKKXnnllcD7ly9fLkn65JNP9OKLL6qiokLJyckaMmSIcnJyrNosAIh677zzjkpLS3XXXXdZXQrQZBERdpKSkjRjxow6y9PS0gJBRpIefvhhPfzww/WOM2nSJE2aNCksNQJAa7RgwQJlZ2crOTnZ6lKAJouIsAMAiDyFhYVav369tm7danUpQLNEyQFQAEBLW7x4sS655BINGTLE6lKAZiHsAADqMAxDr776qiZPnmz7E2dhf4QdAEAd7733njwej+655x6rSwGajbADAKhjwYIFuvXWW5Wenm51KUCzcYIyAKCWr776SqtWrdLq1autLgUICWZ2AAC15OfnKy0tTTfddJPVpQAhQdgBAASYpqkFCxZo0qRJiomJsbocICQ4jAUACNi5c6f+/e9/a82aNVaXAoQMMzsAgIAFCxboxhtvVI8ePawuBQgZwg4AQJJUVlamv/zlL5o8ebLVpQAhRdgBAEiSVqxYIZfLpdtuu83qUoCQIuwAACRJCxcu1IQJExQXF2d1KUBIEXYAANq3b5+2bdvGISzYEmEHAKCFCxdq0KBB6tu3r9WlACFH2AGAVq66ulpLlixhVge2RdgBgFZu7dq1Kisr01133WV1KUBYEHYAoJVbuHChsrOz1a5dO6tLAcKCOygDQCtWWFio9evXa9u2bVaXAoQNMzsA0IotXrxYl156qQYPHmx1KUDYEHYAoJUyDEMLFy7U5MmT5XA4rC4HCBvCDgC0Ups3b9ahQ4c0YcIEq0sBwoqwAwCt1MKFC3XrrbcqPT3d6lKAsOIEZQBohb766iutWrVKb731ltWlAGHHzA4AtEL5+flKT0/X9773PatLAcKOsAMArYxpmpo/f74mTZqkmJgYq8sBwo7DWADQyvzzn//Unj179Pbbb1tdCtAimNkBgFZm4cKFuvHGG9WjRw+rSwFaBGEHAFqRsrIyLVu2TFOmTLG6FKDFEHYAoBVZsWKF2rRpox/96EdWlwK0GMIOALQiCxYs0IQJExQXF2d1KUCLIewAQCuxb98+bd++XZMnT7a6FKBFEXYAoBWorq7Wn//8Zw0aNEjf/va3rS4HaFFceg4ANlBdXa1Dhw7pwIED5/1z6NAhGYah/Px8q0sFWhxhBwCiQH1hpqCgQG63OxBmXC6Xunfvrh49eqhHjx6BS8x79Oihnj17qmvXrlZvCtDiCDsAooJpmvL5fKqqqtKZM2eC+ruiokLHjh1T+/bt5XRGz1H70tJSud3u887MfD3MZGVlacSIEerVq5d69uypHj16qHPnztwVGfgGwg4QQoZhqLq6WtXV1aqqqlJVVVXg8TeXGYZhdbkyTVN+v18xMTFyOBwNru/3+2uFiVD++XpQqS+8mKbZYI0xMTFq06aN4uLi1KZNGzmdzqgKOpKUkJAQmI353ve+F3jco0cPderUKRBmagKgy+UKqn9Aa0XYiTJer1czZszQW2+9JYfDIafTqZiYmMA39PM9b+w6jfmmaZqmrb/JVlRUyOl0njesnG+Zz+ezuuSwcjgcatOmTa0w0Zg/cXFxuuiii+osj42NVVxcXGDMYP6u77Wvz2oYhqGioiJlZmZGXeABEDqEnSjh9/v18ssv6ze/+Y169OihuXPnKiEhQYZhyO/3yzCMwJ9vPg9mnZrnfr8/6JpM05RhGI0OSNHCNE2VlZUpJSUl8IM0Nja21t/BLvvma7GxsRFxqKEpMwN27DUAeyPsRIH3339f06ZN0/79+zVz5kz95Cc/kctlfevsPoXeWmYFHA5H4A8A2JF9v4PbgNfr1eTJkzV06FD169dP+/bt0/Tp0yMi6AAAEC34qSkpKSlJLpcrqJMfG8M0zcC4jRm75pDV//t//089evTQtm3bNGTIkMCYkaKmlkiqKZSa2r9oQg+jm937J0VpD01TDp3rSwM108Oma8wv/oQdSQMGDFBKSkpYTi5NSUkJnBcTjA8++EAPPfSQCgoK9PTTT2vq1KlyuVwRfeJrY87ziTaN7V+0oofRzc79k6Kwhz6fYqWz37eD/N5ND5s2ZrAIO5J2796tvn37Ki0tLaTjGoahY8eOqWPHjg2e81FzldXixYt17733av369crIyAhpPaHW2MuWo01j+het6GF0s3v/pCjt4bkZB5fLFXhcH3rYdF6vN+h1CTs6ewMvn88X8i80h8MRGLe+sb9+lVVWVpa2bdumoUOHhrSOcLPrya3B9M8u7LqNraWHdt6+qOzhuTodDkfgccNviaLta6Rw9bAxRzwIOxb64IMPNG3aNH355ZcRdZUVAAB2EiVzgvZSc5XVkCFDdOWVV3KVFQAAYUTYaUF+v18vvfSSLrnkEu3cuVPbtm3TokWLIv7cHAAAohlTCS2EQ1YAAFiDmZ0wO3bsmKZMmcIhKwAALMJP3DBas2aNJk2aFLgxYLRdZQUAgB0wsxNGWVlZ+uUvf6kPP/yQoAMAgEWY2Qmj/v37KzMzk0NWAABYiJkdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABga4QdAABgay6rC4gUJSUlYRu7qKgobGNbyeVyKSUlRV6vVz6fz+pywsau/ZPoYbRrLf2ToquHMUePKkPS0aNH5Xdd+McsPWy6xvzcbvVhJzExUbGxsVq1alXIx66srJTb7VZWVpbi4+NDPj7Ci/5FP3oY/aK2h08+Kb3zjtVVRIRw9jA2NlaJiYkNrucwTdMM6b8chU6cOKHy8vKQj/vll1/q0Ucf1axZs9S7d++Qj4/won/Rjx5GP3oY/cLZw8TERLVv377B9Vr9zI4ktW/fPqj/rMY6deqUJCktLU2dO3cO+fgIL/oX/ehh9KOH0S8SesgJygAAwNZinnrqqaesLsLOEhISdNVVVwV1TBGRh/5FP3oY/ehh9LO6h5yzAwAAbI3DWAAAwNYIOwAAwNa4GitMSktLNXfuXO3atUsJCQnKzs7WqFGjrC6r1XrhhRe0detWub52g6+5c+cqLS1NkuT1ejV79mzt3btXKSkpmjhxooYMGRJYd8eOHVq8eLFOnDihyy67TA8//LA6duwoSaqurtYrr7yi7du3KyYmRjfffLNycnJadgNtaO3atdq0aZMOHDigwYMH65e//GXgNbfbrdmzZ+vAgQPKzMzUAw88oCuuuKLWe1esWKGKigoNHDhQ06dPD5wr0NC+uWfPHs2bN09FRUXq0aOHHnroIXXv3r3lNtxGLtTDKVOm6MSJE3I6z/7OnZaWprlz5wZeb6gPS5cu1fr162UYhq677jpNnTo1sH83tD8jONXV1Zo3b54+/vhjnT59WqmpqRo7dqyGDx8uKcr2QxNh8dxzz5m/+93vzLKyMvOLL74wx48fb3788cdWl9VqzZo1y1y8eHG9rz/22GPmvHnzzMrKSnPXrl1mdna2eejQIdM0TfPgwYNmdna2uXv3brOystL885//bM6YMSPw3ry8PPMXv/iFefLkSbOoqMi87777zHfffTfs22R3O3bsMN9//33zz3/+s/n73/8+sLy6utqcMmWKuWLFCrOqqsrctGmTeffdd5unT582TdM0d+3aZebk5JhffvmlWVZWZs6cOdN8/vnnA++/0L558uRJ86677jI3b95sVlVVmcuXLzfvu+8+0+fztezG20R9PTRN05w8ebL5z3/+87zva6gPf//738377rvPLCoqMk+cOGH+/Oc/N/Pz8wPvv9D+jOBVVFSYS5cuNY8cOWL6/X7z008/NceNG2fu3bs36vZDDmOFQWVlpXbs2KHc3FwlJiaqd+/eGjFihDZs2GB1aTiPw4cP6/PPP1dOTo7i4uI0YMAA9e/fX5s3b5Ykbd68Wd/5znfUv39/xcXFKScnR//5z3905MgRSdKGDRs0btw4JScnKyMjQ7feeiu9DoEhQ4bo2muvVXJycq3l//73v3XmzBndfvvtio2N1Q033KCMjAz94x//kCRt2rRJI0eOVK9evZSYmKicnBxt375dZ86caXDffP/999W5c2cNHz5csbGxuuOOO1RRUaE9e/a0+PbbQX09bEhDfdiwYYNuu+02ZWRk6KKLLlJ2dnaghw3tzwhefHy8cnJylJmZKafTqcsvv1yXXXaZ9u7dG3X7IWEnDAoLCyWp1pRbr1695Ha7rSoJkv7+979r/Pjxeuihh/Tuu+8GlrvdbqWlpSkpKSmwrGfPnvJ4PIHXe/bsGXitXbt2SktLk9vtVmlpqb766qtar/fs2ZNeh5HH41FWVlbg8Id04X5lZWXJMAwdPny4wX3T4/HUem9MTIyysrLoZ5i88MILys3N1a9//Wt99tlngeUN9cHj8ahHjx6B13v27KmSkhKVlZU1uD+j6SorK/XFF18oKysr6vZDztkJg8rKSiUkJNRa1rZtW1VUVFhUEUaPHq0f//jHatu2rT777DM9++yzatu2rYYMGaLKykq1bdu21vpJSUmBflVWVta5N0RNP2vW+frr9Dq8Kioq6vSrbdu2gY98+WY/HQ6HEhMTVVFRIdM0L7hvVlRU1Poh+c3XETo/+9nPAh8dsHHjRj399NOaPXu20tPTG+zDN3tc87iioqLB/RlNY5qmXnzxRfXp00cDBgzQf//736jaD5nZCYP4+Pg6TSkrK6vTXLSc3r17Kzk5WTExMerbt69++MMfaseOHZLO9uubn4329X5d6PWadb7+enl5Ob0Oo4SEhDr9+Pr/+fn6VfN6Q/tmQ2MjdC6//HLFxcUpLi5Oo0aNUq9evbRz505Jje9xzeOaHl9of0bjmaapl156SceOHdNjjz0mh8MRdfshYScMunTpIkk6ePBgYFlBQYGysrKsKgnf4HA4ZJ67n2ZWVpaKi4tVVlYWeL2goCAwxZqVlaUDBw4EXistLVVJSYmysrKUlJSkDh061Hp9//799DqMunfvLrfbLcMwAsu+2a+CgoLAa263W06nU507d25w3+zevXutXhqGoQMHDtDPFuB0OgP7ZEN96N69e60eFxQUKDU1VW3btm1wf0bjmKapefPmaf/+/XrqqacCn1oebfshYScM4uPjNXToUOXn56u8vFwFBQXauHGjRo4caXVprdb27dtVXl4uwzD02Wef6Z133tG1114rSercubMuvvhiLVu2TGfOnNHHH3+s3bt364YbbpAkDR8+XDt37tTHH3+sM2fOKD8/X5deeqk6deokSRo5cqTeeOMNnTp1SkePHtXbb7+tG2+80bJttQu/36+qqioZhiHDMFRVVSWfz6e+ffsqNjZWb731lqqrq7VlyxYVFRVp8ODBkqQRI0Zo48aNKigoUHl5ufLz8/Xd735XcXFxDe6bgwcPVmFhobZs2aLq6mqtXr1aCQkJ+va3v23lf0XUqq+HXq9Xn376qaqrq1VdXa2///3v+vzzzzVgwABJDfdh5MiRevvtt1VcXKxTp07pjTfeCOxzDe3PaJyXX35Z+/bt09NPP13rcH207Yd8XESYlJaWas6cOdq1a5cSExO5z47FZsyYEfgtJDU1VbfccotuvvnmwOter1d/+tOfAvflmDRpUq37cmzfvl1LlizR8ePHdfnll5/3Pjvbtm0L3GcnNze3xbfRbpYtW6bXX3+91rIRI0bokUce0YEDBzRnzhwdOHBAGRkZeuCBB2p9I6y5v0d5ebkGDhyon/70p7Xu73GhffPf//635s2bp6NHj3KfnWaqr4d33HGH/vjHP+rIkSNyuVzq1q2bcnNz1bdv38B6F+qDaZrKz8/X+vXr5ff7df3119e5z86F9mcEp7i4WFOmTFFsbKxiYmICy++8805lZ2dH1X5I2AEAALbGYSwAAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0ALeKpp56Sw+E475+ZM2e2eD2LFy+Ww+FQSUlJi//bAFqWy+oCALQeCQkJ2rRpU53l3bp1s6AaAK0FYQdAi3E6nYFPmweAlsJhLAARw+Fw6Nlnn9Vjjz2mtLQ0tWvXThMnTtTp06drrefxeDR27Fi1b99eiYmJGjFihP75z3/WGe+1117TgAEDFB8fr9TUVI0aNUput7vOWDfffLPatm2rPn366LXXXgvrNgJoeYQdAC3K5/PV+WOaZuD12bNna+/evVqyZImeffZZrVy5Uvfdd1/g9dOnT2vYsGH66KOPNHfuXP3lL3/RmTNnNHz4cP3nP/8JrPeHP/xB9957rwYOHKhVq1Zp4cKF6tOnj7xeb616cnNzddNNN+mtt95Sv379NHHiRH322Wfh/48A0HJMAGgBTz75pCnpvH82b95smqZpSjJ79uxp+ny+wPsWLFhgOhwOc+/evaZpmuaLL75oOhwOc8+ePYF1Tp8+bXbo0MG89957TdM0zRMnTpiJiYnm1KlT661n0aJFpiRz7ty5gWWnTp0y4+PjzWeeeSaEWw7AapyzA6DFJCQkaOvWrXWWX3rppYHHo0ePVkxMTOD5HXfcoSlTpujDDz/Ut771LW3btk1XXHGFrrjiisA6SUlJGj16tLZt2yZJev/991VeXq7Jkyc3WNNNN90UeNyuXTt169ZNhw4datL2AYhMhB0ALcbpdOqqq6664Drp6em1nqekpCg2NlZHjhyRJB0/flyZmZl13peZmamvvvpKknTs2DFJUufOnRusqX379rWet2nTRpWVlQ2+D0D04JwdABGluLi41vPjx4+rurpanTp1kiR16NBBR48erfO+oqIidejQQZLUsWNHSdLhw4fDXC2AaEDYARBR/vrXv8rv9weer1q1Sg6HQ1dffbUk6bvf/a727NlT6yTisrIyrV27Vtddd50kafDgwUpMTNSiRYtatngAEYnDWABajGEY+uCDD+osT0tLU+/evSVJZ86c0W233aYHH3xQBQUF+tWvfqU777xTl112mSRp0qRJmjVrlm655RbNnDlTSUlJ+v3vf6+KigrNmDFDknTRRRfpySef1K9+9Sv5/X7ddtttMgxDmzdv1t13393goTQA9kLYAdBiKioqNHjw4DrL7733Xi1evFiS9NOf/lRer1e5ubmqqqrS7bffrjlz5gTWbdeunbZs2aKf//zneuCBB1RdXa1Bgwbpvffe07e+9a3AejX36pk1a5aWLFmidu3aafDgwXXOCQJgfw7T/NoNLgDAQg6HQ3/4wx/0i1/8wupSANgI5+wAAABbI+wAAABb45wdABGDo+oAwoGZHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGv/H5k3aoR2ZE6hAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8785354551315)>"
      ]
     },
     "execution_count": 204,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ggplot(avg_df, aes(x='Epoch', y='AUPRC'))\n",
    " + geom_line() \n",
    " + scale_color_grey()\n",
    " + theme_bw()\n",
    " + geom_vline(xintercept = 17000, color = \"red\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21, 30)"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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