Accuracy Experiments-Copy1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.pyplot:Loaded backend module://ipykernel.pylab.backend_inline version unknown.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from mpl_toolkits.mplot3d import proj3d\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "from xgboost import XGBRegressor\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.gaussian_process import GaussianProcessRegressor\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import train_test_split\n",
    "from matplotlib import patches\n",
    "from sklearn import metrics\n",
    "import os\n",
    "import sys\n",
    "import itertools\n",
    "from pathlib import Path\n",
    "import pickle\n",
    "from codebase.utils import compute_boxes,compute_iou,min_dist\n",
    "from codebase.Accuracy import AccuracyRunnerApprox\n",
    "from Optimization_Methods.GlowWorm import GlowWorm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "logging.basicConfig(stream=sys.stdout, level=logging.ERROR,)\n",
    "logger = logging.getLogger(__name__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:queries-uniform-1-multi_False-aggr-XGB-RMSE=0.26-R2=0.97.pkl\n",
      "[15:58:07] WARNING: /workspace/src/objective/regression_obj.cu:152: reg:linear is now deprecated in favor of reg:squarederror.\n",
      "INFO:__main__:Starting Optimization\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-f76d73254750>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m     \u001b[0mac\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mAccuracyRunnerApprox\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdims\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mmulti\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maggr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m     \u001b[0mproposed\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mac\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_test\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     20\u001b[0m     \u001b[0miou_metric\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mavg_min_dist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mac\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_accuracy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mproposed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0;31m#     r2 =  float(a[7].split('=')[1][:4])\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/dev_projects/data_vis/Year 3/reproducibility/codebase/Accuracy.py\u001b[0m in \u001b[0;36mrun_test\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     31\u001b[0m         \u001b[0mlogger\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Starting Optimization'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     32\u001b[0m         \u001b[0mgw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGlowWorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__objective\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdimensions\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdims\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mglowworms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0miter_max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mITER_MAX\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mr0\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrad\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 33\u001b[0;31m         \u001b[0mgw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     34\u001b[0m         \u001b[0mix_sort\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margsort\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__objective\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     35\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mJ\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m!=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__objective\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mgw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/dev_projects/data_vis/Year 3/reproducibility/Optimization_Methods/GlowWorm.py\u001b[0m in \u001b[0;36moptimize\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     30\u001b[0m                 \u001b[0mstart\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     31\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mL\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 32\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mL\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_luciferin_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mL\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     33\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime_capture\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     34\u001b[0m                 \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/dev_projects/data_vis/Year 3/reproducibility/Optimization_Methods/GlowWorm.py\u001b[0m in \u001b[0;36m_luciferin_update\u001b[0;34m(self, l, x)\u001b[0m\n\u001b[1;32m     22\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     23\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_luciferin_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 24\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrho\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0ml\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgamma\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopt_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     25\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     26\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0moptimize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/dev_projects/data_vis/Year 3/reproducibility/codebase/Accuracy.py\u001b[0m in \u001b[0;36m__objective\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__objective\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m         \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mYREQ\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mC\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m//\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     14\u001b[0m         \u001b[0mres\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misnan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mres\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/sklearn/utils/metaestimators.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    116\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    117\u001b[0m         \u001b[0;31m# lambda, but not partial, allows help() to work with update_wrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 118\u001b[0;31m         \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    119\u001b[0m         \u001b[0;31m# update the docstring of the returned function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    120\u001b[0m         \u001b[0mupdate_wrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/sklearn/model_selection/_search.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(self, X)\u001b[0m\n\u001b[1;32m    489\u001b[0m         \"\"\"\n\u001b[1;32m    490\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_is_fitted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'predict'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 491\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbest_estimator_\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    492\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    493\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mif_delegate_has_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdelegate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'best_estimator_'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'estimator'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/xgboost/sklearn.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(self, data, output_margin, ntree_limit, validate_features)\u001b[0m\n\u001b[1;32m    454\u001b[0m                                           \u001b[0moutput_margin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moutput_margin\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    455\u001b[0m                                           \u001b[0mntree_limit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mntree_limit\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 456\u001b[0;31m                                           validate_features=validate_features)\n\u001b[0m\u001b[1;32m    457\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    458\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mntree_limit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/xgboost/core.py\u001b[0m in \u001b[0;36mpredict\u001b[0;34m(self, data, output_margin, ntree_limit, pred_leaf, pred_contribs, approx_contribs, pred_interactions, validate_features)\u001b[0m\n\u001b[1;32m   1290\u001b[0m                                           \u001b[0mctypes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mc_uint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mntree_limit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1291\u001b[0m                                           \u001b[0mctypes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbyref\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlength\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1292\u001b[0;31m                                           ctypes.byref(preds)))\n\u001b[0m\u001b[1;32m   1293\u001b[0m         \u001b[0mpreds\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mctypes2numpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpreds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlength\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloat32\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1294\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mpred_leaf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "result_details = []\n",
    "#Load models and run experiments\n",
    "directory = os.fsencode('models')\n",
    "for file in os.listdir(directory):\n",
    "    filename = os.fsdecode(file)\n",
    "    if not filename.startswith('queries'):\n",
    "        continue;\n",
    "    logger.debug(filename)\n",
    "    a = filename.split('-')\n",
    "    dims = int(a[2])\n",
    "    multi = a[3].split('_')[1]==\"True\"\n",
    "    aggr = a[4]\n",
    "    m = None\n",
    "    \n",
    "    with open('models/%s' % filename, 'rb') as file:  \n",
    "        m = pickle.load(file)\n",
    "        \n",
    "    ac = AccuracyRunnerApprox(dims,multi, aggr,m)\n",
    "    proposed = ac.run_test()\n",
    "    iou_metric, avg_min_dist = ac.check_accuracy(proposed)\n",
    "#     r2 =  float(a[7].split('=')[1][:4])\n",
    "#     print(a[7].split('=')[1][:4])\n",
    "    rmse =  float(a[6].split('=')[1])\n",
    "    model_name = a[5]\n",
    "    result_details.append([dims,multi,aggr,model_name, rmse, iou_metric ,avg_min_dist])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_df = pd.DataFrame(result_details, columns=['dimensions','multiple_regions','type of aggr', 'model','rmse', 'iou', 'avg_min_dist'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>dimensions</th>\n",
       "      <th>multiple_regions</th>\n",
       "      <th>type of aggr</th>\n",
       "      <th>model</th>\n",
       "      <th>rmse</th>\n",
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       "      <td>XGB</td>\n",
       "      <td>0.26</td>\n",
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       "      <td>0.383510</td>\n",
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       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
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       "      <td>XGB</td>\n",
       "      <td>43.11</td>\n",
       "      <td>0.185489</td>\n",
       "      <td>0.718886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.026275</td>\n",
       "      <td>0.970794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>116.78</td>\n",
       "      <td>0.095907</td>\n",
       "      <td>0.855572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>19.19</td>\n",
       "      <td>0.033120</td>\n",
       "      <td>1.016402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>145.02</td>\n",
       "      <td>0.517868</td>\n",
       "      <td>0.441360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.142235</td>\n",
       "      <td>0.767718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>207.81</td>\n",
       "      <td>0.204928</td>\n",
       "      <td>0.626914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>65.87</td>\n",
       "      <td>0.273085</td>\n",
       "      <td>0.544468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>68.60</td>\n",
       "      <td>0.022695</td>\n",
       "      <td>0.972875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.352710</td>\n",
       "      <td>0.602276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.611214</td>\n",
       "      <td>0.416812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.239170</td>\n",
       "      <td>0.637196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>51.92</td>\n",
       "      <td>0.487345</td>\n",
       "      <td>0.438333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.008798</td>\n",
       "      <td>0.971569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.005638</td>\n",
       "      <td>1.070985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>27.57</td>\n",
       "      <td>0.069139</td>\n",
       "      <td>0.831642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>XGB</td>\n",
       "      <td>43.75</td>\n",
       "      <td>0.010550</td>\n",
       "      <td>1.081120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.051871</td>\n",
       "      <td>0.907166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>XGB</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.130366</td>\n",
       "      <td>0.830280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    dimensions  multiple_regions type of aggr model    rmse       iou  \\\n",
       "0            1             False         aggr   XGB    0.26  0.730302   \n",
       "1            3             False      density   XGB   43.11  0.185489   \n",
       "2            4              True         aggr   XGB    0.12  0.026275   \n",
       "3            3              True      density   XGB  116.78  0.095907   \n",
       "4            5             False      density   XGB   19.19  0.033120   \n",
       "5            1              True      density   XGB  145.02  0.517868   \n",
       "6            3             False         aggr   XGB    0.09  0.142235   \n",
       "7            2              True      density   XGB  207.81  0.204928   \n",
       "8            2             False      density   XGB   65.87  0.273085   \n",
       "9            4              True      density   XGB   68.60  0.022695   \n",
       "10           2             False         aggr   XGB    0.16  0.352710   \n",
       "11           1              True         aggr   XGB    0.66  0.611214   \n",
       "12           2              True         aggr   XGB    0.31  0.239170   \n",
       "13           1             False      density   XGB   51.92  0.487345   \n",
       "14           5             False         aggr   XGB    0.15  0.008798   \n",
       "15           5              True         aggr   XGB    0.15  0.005638   \n",
       "16           4             False      density   XGB   27.57  0.069139   \n",
       "17           5              True      density   XGB   43.75  0.010550   \n",
       "18           4             False         aggr   XGB    0.14  0.051871   \n",
       "19           3              True         aggr   XGB    0.17  0.130366   \n",
       "\n",
       "    avg_min_dist  \n",
       "0       0.383510  \n",
       "1       0.718886  \n",
       "2       0.970794  \n",
       "3       0.855572  \n",
       "4       1.016402  \n",
       "5       0.441360  \n",
       "6       0.767718  \n",
       "7       0.626914  \n",
       "8       0.544468  \n",
       "9       0.972875  \n",
       "10      0.602276  \n",
       "11      0.416812  \n",
       "12      0.637196  \n",
       "13      0.438333  \n",
       "14      0.971569  \n",
       "15      1.070985  \n",
       "16      0.831642  \n",
       "17      1.081120  \n",
       "18      0.907166  \n",
       "19      0.830280  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea897eb5f8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=11.0 to DejaVu Sans ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 2.050000.\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=12.0 to DejaVu Sans ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 2.050000.\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.2 to DejaVu Sans ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 2.050000.\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(121)\n",
    "sns.pointplot(x='dimensions', y='iou', hue='model', data=eval_df, ax=ax)\n",
    "ax = fig.add_subplot(122)\n",
    "sns.pointplot(x='dimensions', y='rmse', hue='model', data=eval_df, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea89601780>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='type of aggr',y='iou',hue='multiple_regions', data=eval_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea89674da0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pointplot(x='dimensions', y='avg_min_dist', hue='model', data=eval_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Multi-modal boxes regions are : [0,0.2]^d, [0.3,0.5]^d, [0.6,0.8]^d\n",
    "#Single regions : [0.6,0.9]^d\n",
    "#Defined by Multi\n",
    "\n",
    "#Evaluation metrics are F-Score and IOU\n",
    "#IOU = Intersection Over Union, ie the overlap of the proposed region and the actual regions divided by the total covered region\n",
    "#F-Score : the defined region covers a number of points F-Score, in which true positives are the points covered by the defined region\n",
    "\n",
    "#Alternative methods are :\n",
    "#1) PRIM\n",
    "#2) Naive (exhaustive) without objective function. Get region with highest and then merge surrounding until no improvement or exceed coverage\n",
    "# 3) Naive (exhaustive) with objective. Random Walk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Using PRIM</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:prim.prim_box:mpld3 library not found, some functionality will be disabled\n"
     ]
    }
   ],
   "source": [
    "import prim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:Loading file data_density_dimensions=1_multi_True\n",
      "INFO:prim.prim_alg:12500 points remaining, containing 12500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_density_dimensions=1_multi_False\n",
      "INFO:prim.prim_alg:7500 points remaining, containing 7500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=3_multi_True\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 251 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.072636, mass: 0.520400, coverage: 0.752988, density: 0.072636 restricted_dimensions: 3\n",
      "INFO:prim.prim_alg:2398 points remaining, containing 62 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.031699, mass: 0.334400, coverage: 0.211155, density: 0.031699 restricted_dimensions: 2\n",
      "INFO:prim.prim_alg:726 points remaining, containing 9 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.013761, mass: 0.130800, coverage: 0.035857, density: 0.013761 restricted_dimensions: 2\n",
      "INFO:prim.prim_alg:72 points remaining, containing 0 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.000000, mass: 0.014400, coverage: 0.000000, density: 0.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 4\n",
      "DEBUG:__main__:Proposed [[2.28024041e-04 2.25001651e-04 9.98830418e-04 8.24625444e-01\n",
      "  8.17139906e-01 7.93878538e-01]]\n",
      "DEBUG:__main__:length of IOUs 3\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.014845\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.014955\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.014566\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=1_multi_False\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 1573 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.998624, mass: 0.290600, coverage: 0.922441, density: 0.998624 restricted_dimensions: 1\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Proposed [[0.60264266 0.29421224]]\n",
      "DEBUG:__main__:length of IOUs 1\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.980707\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=2_multi_False\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 540 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 0.075000, coverage: 0.694444, density: 1.000000 restricted_dimensions: 2\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Proposed [[0.61335742 0.61123963 0.26961433 0.28289396]]\n",
      "DEBUG:__main__:length of IOUs 1\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.847470\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=4_multi_True\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 135 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.029397, mass: 0.775600, coverage: 0.844444, density: 0.029397 restricted_dimensions: 3\n",
      "INFO:prim.prim_alg:1122 points remaining, containing 21 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.024359, mass: 0.156000, coverage: 0.140741, density: 0.024359 restricted_dimensions: 2\n",
      "INFO:prim.prim_alg:342 points remaining, containing 2 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.038462, mass: 0.010400, coverage: 0.014815, density: 0.038462 restricted_dimensions: 3\n",
      "INFO:prim.prim_alg:290 points remaining, containing 0 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.000000, mass: 0.058000, coverage: 0.000000, density: 0.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 4\n",
      "DEBUG:__main__:Loading file data_density_dimensions=2_multi_True\n",
      "INFO:prim.prim_alg:12500 points remaining, containing 12500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=5_multi_True\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 128 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.035840, mass: 0.396200, coverage: 0.554688, density: 0.035840 restricted_dimensions: 4\n",
      "INFO:prim.prim_alg:3019 points remaining, containing 57 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.026567, mass: 0.293600, coverage: 0.304688, density: 0.026567 restricted_dimensions: 2\n",
      "INFO:prim.prim_alg:1551 points remaining, containing 18 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.017544, mass: 0.205200, coverage: 0.140625, density: 0.017544 restricted_dimensions: 3\n",
      "INFO:prim.prim_alg:525 points remaining, containing 0 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.000000, mass: 0.105000, coverage: 0.000000, density: 0.000000 restricted_dimensions: 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 4\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=5_multi_False\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 136 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 4\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.034185, mass: 0.579200, coverage: 0.727941, density: 0.034185 restricted_dimensions: 4\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_density_dimensions=3_multi_True\n",
      "INFO:prim.prim_alg:12500 points remaining, containing 12500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_density_dimensions=5_multi_False\n",
      "INFO:prim.prim_alg:7500 points remaining, containing 7500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_density_dimensions=2_multi_False\n",
      "INFO:prim.prim_alg:7500 points remaining, containing 7500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=1_multi_True\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 2968 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.740061, mass: 0.784800, coverage: 0.978437, density: 0.740061 restricted_dimensions: 1\n",
      "INFO:prim.prim_alg:1076 points remaining, containing 64 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.750000, mass: 0.010400, coverage: 0.013140, density: 0.750000 restricted_dimensions: 1\n",
      "INFO:prim.prim_alg:1024 points remaining, containing 25 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.029114, mass: 0.158000, coverage: 0.007749, density: 0.029114 restricted_dimensions: 1\n",
      "INFO:prim.prim_alg:234 points remaining, containing 2 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.032787, mass: 0.012200, coverage: 0.000674, density: 0.032787 restricted_dimensions: 1\n",
      "INFO:prim.prim_alg:173 points remaining, containing 0 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.000000, mass: 0.034600, coverage: 0.000000, density: 0.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 5\n",
      "DEBUG:__main__:Proposed [[4.28919170e-04 7.92856777e-01]\n",
      " [4.28919170e-04 8.03976835e-01]\n",
      " [4.28919170e-04 9.51095798e-01]\n",
      " [9.56600001e-01 1.16447733e-02]]\n",
      "DEBUG:__main__:length of IOUs 12\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.251575\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.252252\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.248763\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=4_multi_False\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 140 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "INFO:prim.prim_alg:pasting 3\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.102450, mass: 0.089800, coverage: 0.328571, density: 0.102450 restricted_dimensions: 4\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Proposed [[6.09922310e-01 3.86595263e-01 2.17520067e-01 1.30070453e-04\n",
      "  2.88677201e-01 5.29396872e-01 6.68676820e-01 9.06586055e-01]]\n",
      "DEBUG:__main__:length of IOUs 1\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.079689\n",
      "DEBUG:__main__:Loading file data_density_dimensions=4_multi_True\n",
      "INFO:prim.prim_alg:12500 points remaining, containing 12500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=2_multi_True\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 702 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.205653, mass: 0.615600, coverage: 0.901709, density: 0.205653 restricted_dimensions: 2\n",
      "INFO:prim.prim_alg:1922 points remaining, containing 69 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.040454, mass: 0.281800, coverage: 0.081197, density: 0.040454 restricted_dimensions: 1\n",
      "INFO:prim.prim_alg:513 points remaining, containing 12 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.035503, mass: 0.067600, coverage: 0.017094, density: 0.035503 restricted_dimensions: 2\n",
      "INFO:prim.prim_alg:175 points remaining, containing 0 cases of interest\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 0.000000, mass: 0.035000, coverage: 0.000000, density: 0.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 4\n",
      "DEBUG:__main__:Proposed [[6.63815998e-05 6.62586731e-05 7.96005216e-01 7.81996640e-01]\n",
      " [1.13957580e-01 2.21615849e-02 8.02019560e-01 9.74077777e-01]]\n",
      "DEBUG:__main__:length of IOUs 6\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.064214\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.064260\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.056954\n",
      "DEBUG:__main__:Loading file data_density_dimensions=3_multi_False\n",
      "INFO:prim.prim_alg:7500 points remaining, containing 7500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_density_dimensions=5_multi_True\n",
      "INFO:prim.prim_alg:12500 points remaining, containing 12500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "INFO:prim.prim_alg:no data remaining\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_density_dimensions=4_multi_False\n",
      "INFO:prim.prim_alg:7500 points remaining, containing 7500 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 1.000000, coverage: 1.000000, density: 1.000000 restricted_dimensions: 0\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=3_multi_False\n",
      "INFO:prim.prim_alg:5000 points remaining, containing 250 cases of interest\n",
      "DEBUG:prim.prim_alg:peeling started\n",
      "DEBUG:prim.prim_alg:peeling completed\n",
      "DEBUG:prim.prim_alg:pasting started\n",
      "INFO:prim.prim_alg:pasting 0\n",
      "INFO:prim.prim_alg:pasting 1\n",
      "INFO:prim.prim_alg:pasting 2\n",
      "DEBUG:prim.prim_alg:pasting completed\n",
      "INFO:prim.prim_alg:mean: 1.000000, mass: 0.023000, coverage: 0.460000, density: 1.000000 restricted_dimensions: 3\n",
      "DEBUG:__main__:Number of boxes found by PRIM 1\n",
      "DEBUG:__main__:Proposed [[0.59805076 0.61696698 0.59861828 0.29656566 0.28326546 0.30053973]]\n",
      "DEBUG:__main__:length of IOUs 1\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.913702\n"
     ]
    }
   ],
   "source": [
    "directory = os.fsencode('input')\n",
    "prim_details = []\n",
    "for file in os.listdir(directory):\n",
    "    filename = os.fsdecode(file)\n",
    "    if not filename.endswith(\".csv\") and filename.startswith(\"data\"):\n",
    "        a =filename.split('_')\n",
    "        t = a[1]\n",
    "        dim = int(a[2].split('=')[1])\n",
    "        multi = a[-1]==\"True\"\n",
    "        #Check if query file has been generated and skip\n",
    "        logger.debug('Loading file {0}'.format(filename))\n",
    "        d = np.loadtxt('input/%s' % (filename) ,delimiter=',')\n",
    "        b_set = []\n",
    "        if t=='density':\n",
    "            p = prim.Prim(d, np.ones(d.shape[0]), threshold=0.4,\n",
    "                          threshold_type=\">\")       \n",
    "        else:\n",
    "            p = prim.Prim(d[:,:d.shape[1]-1], d[:,-1], threshold=2,mass_min=0.01,\n",
    "                          threshold_type=\">\")            \n",
    "        if multi :\n",
    "            b_set = p.find_all()\n",
    "        else:\n",
    "            b_set = [p.find_box()]\n",
    "        logger.debug(\"Number of boxes found by PRIM {0}\".format(len(b_set)))\n",
    "        \n",
    "        boxes = compute_boxes(multi,dim)\n",
    "        proposed = []\n",
    "        for box in b_set :\n",
    "            if box.limits.sort_index().values.shape[0]!=0:#Means is empty PRIM covers whole range\n",
    "                box_x = box.limits.values[:,0]\n",
    "                box_l = box.limits.values[:,1]\n",
    "                box_p = np.column_stack((box_x.reshape(1,-1), box_l.reshape(1,-1)-box_x.reshape(1,-1)))\n",
    "                if box_p.shape[1]!=2*dim:\n",
    "                    continue;\n",
    "                proposed.append(box_p.flatten())\n",
    "        if len(proposed)==0:\n",
    "            prim_details.append([dim,multi,t,'prim', np.nan ,np.nan])\n",
    "            continue;\n",
    "        proposed = np.array(proposed)\n",
    "        logger.debug('Proposed '+ np.array2string(proposed))\n",
    "        iou = compute_iou(boxes, proposed, multi, dim)\n",
    "        avg_min_dist = min_dist(boxes, proposed)\n",
    "        prim_details.append([dim,multi,t,'prim', iou ,avg_min_dist])        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_df_prim = pd.DataFrame(prim_details, columns=['dimensions','multiple_regions','type of aggr', 'model', 'iou', 'avg_min_dist'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea89311470>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(121)\n",
    "sns.pointplot(x='dimensions', y='iou', data=eval_df_prim, ax=ax)\n",
    "ax = fig.add_subplot(122)\n",
    "sns.pointplot(x='dimensions', y='avg_min_dist', data=eval_df_prim, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea89336d68>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='type of aggr',y='iou', hue='multiple_regions',data=eval_df_prim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>dimensions</th>\n",
       "      <th>multiple_regions</th>\n",
       "      <th>type of aggr</th>\n",
       "      <th>model</th>\n",
       "      <th>iou</th>\n",
       "      <th>avg_min_dist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.014789</td>\n",
       "      <td>1.060053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.980707</td>\n",
       "      <td>0.006363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.847470</td>\n",
       "      <td>0.038996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.250864</td>\n",
       "      <td>0.587804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.079689</td>\n",
       "      <td>1.052804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.061809</td>\n",
       "      <td>0.910252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>density</td>\n",
       "      <td>prim</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>aggr</td>\n",
       "      <td>prim</td>\n",
       "      <td>0.913702</td>\n",
       "      <td>0.024202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    dimensions  multiple_regions type of aggr model       iou  avg_min_dist\n",
       "0            1              True      density  prim       NaN           NaN\n",
       "1            1             False      density  prim       NaN           NaN\n",
       "2            3              True         aggr  prim  0.014789      1.060053\n",
       "3            1             False         aggr  prim  0.980707      0.006363\n",
       "4            2             False         aggr  prim  0.847470      0.038996\n",
       "5            4              True         aggr  prim       NaN           NaN\n",
       "6            2              True      density  prim       NaN           NaN\n",
       "7            5              True         aggr  prim       NaN           NaN\n",
       "8            5             False         aggr  prim       NaN           NaN\n",
       "9            3              True      density  prim       NaN           NaN\n",
       "10           5             False      density  prim       NaN           NaN\n",
       "11           2             False      density  prim       NaN           NaN\n",
       "12           1              True         aggr  prim  0.250864      0.587804\n",
       "13           4             False         aggr  prim  0.079689      1.052804\n",
       "14           4              True      density  prim       NaN           NaN\n",
       "15           2              True         aggr  prim  0.061809      0.910252\n",
       "16           3             False      density  prim       NaN           NaN\n",
       "17           5              True      density  prim       NaN           NaN\n",
       "18           4             False      density  prim       NaN           NaN\n",
       "19           3             False         aggr  prim  0.913702      0.024202"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_df_prim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Naive + Glow</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from codebase.query_generation import generate_boolean_vector,execute_query_aggr,execute_query_dens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ac.YREQ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def objective_density_naive(X):\n",
    "    mid = X.shape[1]//2\n",
    "    assert X[:,:mid].shape == (1,mid)\n",
    "    b = generate_boolean_vector(d, X[:,:mid].flatten(),X[:,mid:].flatten(), dims)\n",
    "    y = execute_query_dens(b, d)\n",
    "    res = np.log(y - 1000) - 4*np.sum(np.log(1+X[:,mid:]),axis=1)\n",
    "    res[np.isnan(res)] = -np.inf\n",
    "    return res\n",
    "def objective_aggr_naive(X):\n",
    "    mid = X.shape[1]//2\n",
    "    assert X[:,:mid].shape == (1,mid)\n",
    "    b = generate_boolean_vector(d, X[:,:mid].flatten(),X[:,mid:].flatten(), dims)\n",
    "    y = execute_query_aggr(b, d)\n",
    "    res = np.log(y - 2) - 4*np.sum(np.log(1+X[:,mid:]),axis=1)\n",
    "    res[np.isnan(res)] = -np.inf\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:Loading file data_density_dimensions=1_multi_True\n",
      "INFO:__main__:(12500, 1)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.40582964 0.38603743]\n",
      " [0.32912166 0.49348581]\n",
      " [0.26793961 0.51775264]\n",
      " [0.111372   0.36366918]\n",
      " [0.09563815 0.44627517]\n",
      " [0.00203304 0.5818865 ]\n",
      " [0.05484252 0.30367374]\n",
      " [0.16832389 0.62172149]\n",
      " [0.14424158 0.30632485]\n",
      " [0.5738617  0.19689926]\n",
      " [0.03691442 0.2356134 ]\n",
      " [0.28180321 0.67079326]\n",
      " [0.51343212 0.25416967]\n",
      " [0.33875258 0.70177823]\n",
      " [0.40989217 0.23485568]\n",
      " [0.55057673 0.47957182]\n",
      " [0.66775228 0.24522489]\n",
      " [0.63591146 0.39701684]\n",
      " [0.05023918 0.97105553]\n",
      " [0.20470273 0.84252432]\n",
      " [0.2218651  0.84707302]\n",
      " [0.36277959 0.77334942]\n",
      " [0.20245594 0.87368029]\n",
      " [0.41388583 0.79553844]\n",
      " [0.44688293 0.81878338]\n",
      " [0.57000575 0.7123953 ]\n",
      " [0.55962061 0.72781067]\n",
      " [0.41515775 0.93165187]\n",
      " [0.49965465 0.78778161]\n",
      " [0.36742326 0.0883275 ]\n",
      " [0.72369515 0.11199827]\n",
      " [0.47919287 0.98830421]\n",
      " [0.76172441 0.37738   ]\n",
      " [0.44470923 0.10808818]\n",
      " [0.55056469 0.10697319]\n",
      " [0.7514396  0.72890753]\n",
      " [0.95086873 0.57059531]\n",
      " [0.99026329 0.37046527]\n",
      " [0.89594286 0.00781294]\n",
      " [0.89866514 0.65064207]\n",
      " [0.90455704 0.04824792]\n",
      " [0.94671009 0.59071836]\n",
      " [0.93894852 0.08598306]\n",
      " [0.10809611 0.03654293]\n",
      " [0.98713299 0.37826608]\n",
      " [0.87479037 0.22018996]\n",
      " [0.04050682 0.03148729]\n",
      " [0.85338497 0.51590237]\n",
      " [0.81066334 0.72578215]\n",
      " [0.94454334 0.14131458]]\n",
      "DEBUG:__main__:length of IOUs 150\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.598418\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.450408\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.755117\n",
      "INFO:__main__:Average Minimum Distance 0.38\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=1_multi_False\n",
      "INFO:__main__:(7500, 1)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.54445124 0.38649702]\n",
      " [0.63918091 0.38714553]\n",
      " [0.56883332 0.2353264 ]\n",
      " [0.43572691 0.51730122]\n",
      " [0.58957447 0.50346228]\n",
      " [0.50435473 0.613837  ]\n",
      " [0.62238037 0.54336899]\n",
      " [0.31583558 0.73192184]\n",
      " [0.23181905 0.52965957]\n",
      " [0.27596948 0.80227647]\n",
      " [0.05718576 0.79146179]\n",
      " [0.25194265 0.44765938]\n",
      " [0.61356608 0.65100147]\n",
      " [0.19198362 0.50507617]\n",
      " [0.00680801 0.93265078]\n",
      " [0.12822157 0.57408535]\n",
      " [0.32411906 0.86738392]\n",
      " [0.06744433 0.97729317]\n",
      " [0.51207762 0.82278783]\n",
      " [0.22562485 0.99252558]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.776203\n",
      "INFO:__main__:Average Minimum Distance 0.45\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=3_multi_True\n",
      "INFO:__main__:(5000, 4)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[9.60972641e-01 3.37279015e-01 3.00889411e-01 9.43547813e-01\n",
      "  3.95692018e-02 2.73109890e-01]\n",
      " [3.07890435e-02 3.32257701e-01 2.80329551e-01 7.94125453e-02\n",
      "  4.40031941e-01 3.97235055e-01]\n",
      " [6.99566748e-01 6.59535500e-02 8.04885466e-01 5.37542667e-01\n",
      "  6.00491476e-01 1.85448504e-01]\n",
      " [1.00641712e-01 4.20640751e-01 7.64577693e-01 5.95673027e-01\n",
      "  3.97740289e-01 7.50065457e-01]\n",
      " [2.89325429e-02 1.92696752e-01 6.58314999e-01 6.44149166e-02\n",
      "  7.06342088e-01 8.08279444e-01]\n",
      " [5.55746128e-01 9.74878871e-01 9.39810350e-01 4.12204415e-01\n",
      "  1.78651171e-01 5.47881417e-01]\n",
      " [1.82629856e-01 7.70721481e-01 4.19381177e-01 5.94849981e-01\n",
      "  4.88097078e-01 2.50845136e-02]\n",
      " [9.40148802e-01 1.85107101e-01 4.99819923e-01 8.00999900e-02\n",
      "  3.76823550e-01 8.20355857e-01]\n",
      " [5.79883969e-01 8.21580966e-01 3.93789450e-01 4.85923076e-02\n",
      "  2.13176781e-01 7.58631669e-02]\n",
      " [1.54305708e-01 1.77532593e-01 5.75656239e-01 9.66647083e-01\n",
      "  6.10270733e-01 7.13628648e-01]\n",
      " [9.19023517e-01 4.76401088e-01 5.32858717e-01 7.00788308e-02\n",
      "  4.48857603e-01 3.84078643e-01]\n",
      " [3.87709594e-01 9.70586144e-02 4.98010998e-01 5.39433614e-01\n",
      "  8.77848278e-01 5.88938456e-01]\n",
      " [4.61775263e-01 3.12051903e-01 2.68159331e-01 7.94371287e-01\n",
      "  6.47547521e-02 4.24397677e-01]\n",
      " [5.50516826e-01 9.07443967e-01 5.27385586e-01 9.31771043e-01\n",
      "  7.81743160e-01 5.81077836e-01]\n",
      " [3.35288712e-01 6.56391233e-01 5.90009673e-01 4.58220571e-01\n",
      "  5.09991293e-01 7.82402858e-01]\n",
      " [6.71261135e-02 9.85177583e-01 5.50438928e-01 3.99638251e-01\n",
      "  4.90024283e-01 8.29118733e-01]\n",
      " [7.04054121e-02 9.77613379e-01 4.54204806e-01 6.37431990e-02\n",
      "  7.10261629e-01 4.36916993e-01]\n",
      " [9.35088349e-01 5.14198190e-01 6.94653863e-01 5.50691508e-01\n",
      "  1.89711734e-01 1.33061990e-01]\n",
      " [1.48649647e-01 9.03050072e-01 5.93521421e-01 1.07735051e-01\n",
      "  6.17922862e-01 2.56602012e-01]\n",
      " [7.73541343e-01 4.04851911e-01 4.28714128e-01 2.64335225e-01\n",
      "  1.61793420e-02 9.11022744e-01]\n",
      " [8.15182459e-01 7.82774101e-03 2.41059443e-01 4.43084887e-01\n",
      "  3.22450659e-01 3.65420644e-01]\n",
      " [4.63522675e-01 9.61704860e-01 8.12559151e-01 1.20570597e-03\n",
      "  1.71127568e-01 6.36864527e-01]\n",
      " [5.27409920e-01 2.33438586e-01 2.86152991e-01 4.62849119e-01\n",
      "  4.34984172e-01 9.87244346e-01]\n",
      " [9.58446162e-01 3.28081505e-01 4.47948188e-01 6.16892650e-01\n",
      "  5.24179534e-01 9.77107819e-01]\n",
      " [5.17909602e-01 2.46399687e-01 3.00017349e-01 3.17774932e-01\n",
      "  7.76429515e-02 8.05820952e-01]\n",
      " [5.75359614e-01 7.30005470e-01 5.89547842e-01 5.97540119e-01\n",
      "  2.38630635e-01 9.50462494e-01]\n",
      " [9.92817951e-01 1.52420774e-01 5.72089454e-01 1.95041507e-01\n",
      "  8.93983270e-01 9.43913639e-01]\n",
      " [6.91607911e-01 4.09457115e-02 7.73887232e-01 2.99478402e-01\n",
      "  7.59660974e-01 3.37798752e-01]\n",
      " [9.56926201e-01 9.49866669e-01 8.11802272e-01 1.58417101e-01\n",
      "  8.32668272e-01 2.16950089e-01]\n",
      " [7.17340461e-01 4.43067978e-01 8.66466544e-01 6.55018369e-01\n",
      "  5.53454259e-01 3.21229345e-01]\n",
      " [6.05949228e-02 1.14600335e-01 1.01496809e-01 3.75660408e-01\n",
      "  8.77997574e-01 2.13140357e-01]\n",
      " [3.18977211e-01 8.68391732e-01 7.86193956e-01 7.43911704e-01\n",
      "  1.42284850e-01 6.46512889e-01]\n",
      " [7.55303453e-01 8.09571848e-02 1.83454202e-01 8.16567264e-01\n",
      "  9.17238743e-01 2.20774750e-01]\n",
      " [9.10426108e-01 6.35329490e-01 2.15460941e-01 3.83659072e-01\n",
      "  2.26111407e-01 6.01809113e-01]\n",
      " [6.68649450e-01 7.52861525e-01 4.82208796e-01 9.78028453e-01\n",
      "  8.75009328e-01 3.30011759e-01]\n",
      " [2.07407248e-01 8.59730553e-01 3.54471707e-01 5.98066873e-01\n",
      "  9.14041992e-02 7.58052840e-01]\n",
      " [8.07158593e-01 1.93778760e-01 8.68823292e-01 1.83391042e-01\n",
      "  7.07041159e-01 3.73960121e-01]\n",
      " [3.00944323e-01 8.45481690e-01 5.67039460e-01 9.35861096e-01\n",
      "  2.19147586e-02 3.23602135e-01]\n",
      " [4.00814460e-01 9.25873510e-01 5.03125003e-01 6.19859740e-01\n",
      "  9.94433703e-01 2.54628509e-01]\n",
      " [1.61390737e-01 8.03115285e-01 9.66763928e-01 1.78233582e-01\n",
      "  8.23812267e-02 1.79085164e-01]\n",
      " [5.27445141e-01 6.94241186e-01 3.96536112e-01 4.84553973e-01\n",
      "  5.40688823e-01 8.14384073e-01]\n",
      " [2.43679095e-01 6.73995953e-01 6.07067433e-01 6.68839807e-01\n",
      "  3.08953149e-01 9.70766826e-01]\n",
      " [5.89422779e-01 3.63159367e-01 8.49107221e-01 1.98934074e-01\n",
      "  7.84402909e-01 1.00275315e-01]\n",
      " [4.96865422e-01 8.95831067e-01 5.79697626e-01 6.97497376e-01\n",
      "  6.95102760e-01 8.54009563e-01]\n",
      " [7.66772376e-01 9.39002469e-01 2.64925951e-01 1.45890752e-01\n",
      "  7.05491650e-01 6.80544771e-02]\n",
      " [7.86612507e-01 6.61145996e-01 8.28732488e-01 1.71667884e-01\n",
      "  4.45634488e-01 5.68668636e-01]\n",
      " [4.37032067e-01 3.38304333e-01 1.50914967e-01 8.97219232e-01\n",
      "  2.21054988e-01 4.04813513e-01]\n",
      " [9.45066450e-01 3.81986635e-01 2.48003992e-01 9.55593952e-01\n",
      "  4.93297365e-01 6.21955357e-01]\n",
      " [2.72024009e-02 1.70112401e-01 2.98665684e-02 1.85726697e-01\n",
      "  2.50726690e-02 7.28478289e-01]\n",
      " [2.28893463e-01 5.40186195e-01 4.73692810e-01 4.26080766e-02\n",
      "  4.07466610e-01 3.91477204e-01]\n",
      " [2.87536677e-02 6.21013490e-01 3.82690012e-01 9.23452801e-01\n",
      "  5.26062634e-01 2.12409973e-01]\n",
      " [8.05574771e-01 1.04035289e-01 9.70688262e-01 1.92713346e-01\n",
      "  7.34061238e-01 4.40483608e-01]\n",
      " [2.51639305e-01 6.23234310e-01 5.81949275e-01 5.52410086e-01\n",
      "  8.84936807e-01 1.82327302e-01]\n",
      " [5.00732961e-01 6.14984962e-01 6.77883356e-01 2.47399203e-01\n",
      "  8.11531005e-01 9.66299373e-01]\n",
      " [6.39382075e-01 8.50544858e-01 6.26834412e-02 6.79999004e-02\n",
      "  6.29150240e-03 1.46828089e-01]\n",
      " [9.52696743e-01 3.78330269e-01 1.93687038e-01 6.30668584e-01\n",
      "  7.08435286e-01 8.54688102e-01]\n",
      " [1.97777826e-01 3.13716058e-01 9.35010202e-01 6.92673947e-01\n",
      "  7.94574480e-01 6.28275348e-01]\n",
      " [7.34403914e-02 2.27545391e-01 8.75527115e-01 6.18932943e-02\n",
      "  5.93664580e-01 6.93457368e-01]\n",
      " [5.47440871e-01 9.54066195e-01 4.93814115e-01 7.69616050e-01\n",
      "  6.70426549e-01 4.68217547e-01]\n",
      " [8.13514581e-01 4.41102998e-01 3.22605798e-01 6.94013075e-01\n",
      "  1.69871650e-01 3.00307007e-01]\n",
      " [8.06289309e-01 4.33259595e-01 3.89579178e-01 1.13232761e-02\n",
      "  2.91853581e-01 6.22821913e-01]\n",
      " [5.94655663e-01 7.94378333e-01 2.45130923e-01 7.67334769e-01\n",
      "  3.21442260e-01 7.76027135e-01]\n",
      " [2.02807737e-01 8.63766590e-01 9.19094517e-01 7.70467218e-01\n",
      "  8.66606760e-01 5.66195975e-01]\n",
      " [9.23465759e-01 9.67788913e-02 7.66858342e-01 8.63605274e-01\n",
      "  6.08732127e-01 1.03650922e-01]\n",
      " [2.35877207e-01 1.57774641e-01 4.68130106e-01 9.56402653e-01\n",
      "  5.33020835e-02 4.89131862e-02]\n",
      " [8.83540077e-01 5.56573673e-01 1.54776742e-01 7.69781070e-01\n",
      "  6.56221179e-02 6.49955818e-02]\n",
      " [4.02749276e-01 4.85229708e-01 9.96109087e-01 8.44228015e-01\n",
      "  7.38575937e-01 1.16323301e-01]\n",
      " [6.41412940e-01 9.01987744e-01 5.94186970e-01 9.14933188e-02\n",
      "  8.27327078e-02 8.74327173e-01]\n",
      " [9.34717612e-02 3.99728640e-01 5.89117400e-01 1.39702830e-01\n",
      "  6.74726428e-02 6.67404102e-01]\n",
      " [5.25776154e-01 7.28144788e-01 7.09921076e-01 5.58493261e-01\n",
      "  3.00462182e-01 5.79263013e-01]\n",
      " [5.18814590e-01 4.23292751e-01 4.94565244e-01 7.66491765e-01\n",
      "  7.35131405e-01 3.90019316e-01]\n",
      " [1.74407937e-01 9.69912362e-01 4.58181622e-02 9.22478693e-01\n",
      "  8.50838718e-01 7.58058728e-01]\n",
      " [8.60350647e-01 8.00814186e-01 1.56802100e-01 8.57334026e-01\n",
      "  3.75650233e-01 4.21007695e-01]\n",
      " [8.74848451e-01 3.03528938e-02 1.61428717e-01 6.05228317e-01\n",
      "  8.82309603e-01 2.76151366e-01]\n",
      " [7.15184201e-01 8.52376657e-02 2.75638620e-01 1.39676373e-01\n",
      "  9.53013271e-01 6.28851032e-01]\n",
      " [2.48802439e-01 6.15221972e-01 9.35733116e-01 3.33421180e-01\n",
      "  5.35562393e-01 8.55041673e-01]\n",
      " [2.86190481e-01 1.25523709e-01 9.88857427e-02 6.27856325e-01\n",
      "  2.89234493e-01 5.92764356e-04]\n",
      " [3.11385158e-01 7.88994917e-01 4.16166239e-01 8.81358443e-01\n",
      "  2.39502672e-01 6.63978805e-01]\n",
      " [4.27839958e-01 2.19544575e-01 8.97029950e-01 6.84224830e-01\n",
      "  6.16523020e-01 5.77399668e-01]\n",
      " [7.71795427e-01 7.76059784e-01 6.89932848e-01 2.58153207e-01\n",
      "  7.44748879e-01 2.66759601e-01]\n",
      " [5.99334596e-01 3.41160257e-02 7.30286679e-01 3.47305861e-01\n",
      "  9.28566181e-01 6.45146232e-01]\n",
      " [3.88433999e-01 2.91413520e-01 5.33375699e-01 8.87166282e-01\n",
      "  5.09677138e-02 6.68233578e-01]\n",
      " [9.65708924e-01 1.02400650e-01 6.24582588e-01 4.88261992e-01\n",
      "  1.48784593e-02 7.16795161e-01]\n",
      " [5.92296703e-01 3.73291925e-02 7.00368588e-02 6.58725126e-01\n",
      "  5.05733333e-01 8.70004445e-01]\n",
      " [4.74296755e-01 5.59865680e-01 6.66370501e-01 2.85194235e-01\n",
      "  9.95259840e-01 9.13410804e-01]\n",
      " [7.17402489e-01 2.13576287e-02 1.94679149e-01 2.73468109e-01\n",
      "  2.76221060e-01 7.52864855e-01]\n",
      " [1.23922790e-01 5.68551634e-01 7.38803991e-02 8.52420240e-01\n",
      "  2.48642327e-01 7.97928706e-01]\n",
      " [4.07159252e-01 2.97596410e-01 3.68875775e-01 8.03825611e-01\n",
      "  1.64983171e-01 1.29189849e-01]\n",
      " [8.46340079e-01 2.66299323e-01 5.51983249e-01 2.05660895e-01\n",
      "  1.57531528e-01 5.95595292e-01]\n",
      " [7.22078741e-01 2.11518440e-01 7.25883799e-01 4.10771050e-01\n",
      "  9.18208123e-01 2.55615811e-01]\n",
      " [5.41643623e-02 5.11158535e-01 3.31331914e-01 1.42493087e-01\n",
      "  6.21431351e-01 5.35360906e-02]\n",
      " [5.92886589e-01 1.45902108e-01 6.36024241e-01 3.36703563e-02\n",
      "  1.76846005e-01 4.41363486e-01]\n",
      " [5.30740846e-01 3.82686344e-02 5.69965168e-02 6.18263161e-01\n",
      "  8.86574148e-01 9.19807395e-01]\n",
      " [3.07398822e-01 5.74086231e-01 9.36812345e-01 9.82642475e-01\n",
      "  3.67832388e-01 8.74675372e-01]\n",
      " [7.37527687e-02 9.15296686e-01 7.95967910e-01 5.49687093e-01\n",
      "  8.53439052e-01 9.15610272e-01]\n",
      " [3.70847433e-01 7.83819158e-01 3.48627268e-01 1.82613154e-01\n",
      "  1.23589054e-01 5.66879059e-01]\n",
      " [5.67834613e-03 4.38172094e-01 3.37425033e-01 1.08830564e-01\n",
      "  7.54308889e-01 6.17698941e-01]\n",
      " [6.02948089e-01 3.28472367e-01 4.59435936e-01 5.87819993e-01\n",
      "  9.03215732e-01 9.66223541e-01]\n",
      " [8.45390677e-01 2.12454655e-01 5.35930035e-01 5.47526438e-01\n",
      "  8.50166796e-01 7.04374736e-01]\n",
      " [5.24644438e-01 9.19298053e-01 6.41300597e-01 4.43633333e-01\n",
      "  1.19870247e-01 9.32471174e-01]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.069178\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.084114\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.063595\n",
      "INFO:__main__:Average Minimum Distance 0.83\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=1_multi_False\n",
      "INFO:__main__:(5000, 2)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.66879256 0.03216754]\n",
      " [0.77616246 0.11150339]\n",
      " [0.60406189 0.1832509 ]\n",
      " [0.61468257 0.21794838]\n",
      " [0.71910045 0.21329525]\n",
      " [0.60308023 0.33175302]\n",
      " [0.5360069  0.29965604]\n",
      " [0.50609286 0.41766539]\n",
      " [0.5875651  0.52617763]\n",
      " [0.56291537 0.55698204]\n",
      " [0.65372098 0.71850784]\n",
      " [0.68746355 0.75085409]\n",
      " [0.60962852 0.88995352]\n",
      " [0.43993343 0.58934118]\n",
      " [0.5825555  0.97283232]\n",
      " [0.78393373 0.58264407]\n",
      " [0.72628045 0.970636  ]\n",
      " [0.81090349 0.49401521]\n",
      " [0.43339486 0.93057915]\n",
      " [0.39222299 0.86312066]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.886769\n",
      "INFO:__main__:Average Minimum Distance 0.33\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=2_multi_False\n",
      "INFO:__main__:(5000, 3)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.7712188  0.66890184 0.12696595 0.07137007]\n",
      " [0.85353844 0.59821392 0.0188956  0.17331838]\n",
      " [0.48967743 0.57634135 0.37202003 0.32543156]\n",
      " [0.504822   0.67744054 0.18947306 0.24670429]\n",
      " [0.56929519 0.74218497 0.33082311 0.45819453]\n",
      " [0.73461234 0.69493503 0.02196133 0.98622801]\n",
      " [0.58856095 0.44602695 0.36781024 0.42006557]\n",
      " [0.50449693 0.61263137 0.94327748 0.22774247]\n",
      " [0.56111425 0.66327667 0.16186316 0.90801677]\n",
      " [0.73870577 0.70041138 0.1922637  0.93081809]\n",
      " [0.55945549 0.77237172 0.33979508 0.80867493]\n",
      " [0.34195859 0.62735847 0.96694243 0.19368605]\n",
      " [0.65344338 0.70595933 0.52927    0.51728122]\n",
      " [0.6026954  0.77050749 0.95115626 0.29352941]\n",
      " [0.53344065 0.97923412 0.01764851 0.56683433]\n",
      " [0.90107912 0.50528009 0.35192242 0.03053574]\n",
      " [0.33422195 0.74955079 0.7902886  0.57812461]\n",
      " [0.53969309 0.80121726 0.47750517 0.75284572]\n",
      " [0.85678381 0.47204585 0.65983748 0.26821074]\n",
      " [0.0997394  0.06539331 0.90888969 0.5501055 ]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.592264\n",
      "INFO:__main__:Average Minimum Distance 0.50\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=4_multi_True\n",
      "INFO:__main__:(5000, 5)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[3.83441956e-01 1.41636811e-01 7.32132758e-01 5.80060784e-01\n",
      "  9.45775635e-01 2.76594470e-03 3.48320850e-01 9.91930554e-01]\n",
      " [9.62418950e-01 8.76465469e-01 7.50126617e-01 8.59016600e-01\n",
      "  9.75128365e-01 4.12458475e-01 2.75186717e-02 6.05059435e-01]\n",
      " [2.84689037e-01 8.10251447e-01 6.76874586e-01 2.38243642e-01\n",
      "  6.10090591e-02 6.36296401e-01 9.87517751e-01 3.05780009e-01]\n",
      " [3.00187613e-01 5.03800164e-01 5.54542149e-01 7.77472316e-01\n",
      "  4.75813937e-01 9.99384274e-01 7.15938409e-01 4.15176040e-01]\n",
      " [3.52962469e-01 1.88255402e-01 8.96543355e-01 4.38051186e-01\n",
      "  1.13346996e-02 8.79564190e-01 6.54202407e-01 6.93950619e-01]\n",
      " [3.09091295e-01 3.20286327e-01 7.71538664e-02 8.39590291e-01\n",
      "  2.82306907e-01 6.07716573e-01 7.31063731e-01 8.42974905e-01]\n",
      " [8.89909057e-01 1.26764133e-01 9.54348925e-01 9.96876096e-01\n",
      "  3.63039409e-02 6.19676379e-01 4.68429636e-01 8.44435648e-01]\n",
      " [4.42332602e-01 6.08377834e-01 1.96119117e-01 4.99294785e-02\n",
      "  8.50683813e-01 1.11875507e-01 3.96939071e-01 9.68706908e-01]\n",
      " [3.45926688e-01 7.32926466e-01 1.27420286e-01 5.21908341e-01\n",
      "  8.96091832e-01 7.64604562e-02 6.44318389e-01 2.46774139e-01]\n",
      " [9.59857376e-01 6.48411461e-01 2.69288518e-02 2.68093272e-01\n",
      "  9.75838602e-01 7.36887864e-01 4.09568654e-01 9.05628130e-01]\n",
      " [2.02253007e-01 7.28568168e-01 9.83615353e-01 7.83417518e-01\n",
      "  8.75649414e-01 9.21987098e-01 6.43326460e-01 6.15041089e-01]\n",
      " [8.00710284e-01 4.00117825e-01 1.48293075e-02 7.65158391e-01\n",
      "  9.57091830e-01 9.65494851e-01 4.65307197e-01 9.22343272e-02]\n",
      " [6.16542465e-01 8.44703262e-01 2.00188753e-01 1.89525986e-01\n",
      "  7.88846257e-01 3.47826288e-01 5.27816623e-01 2.42246189e-01]\n",
      " [5.79618514e-01 4.21476540e-01 6.14643529e-01 6.74790462e-01\n",
      "  8.11062265e-01 6.42770092e-01 4.58485486e-01 1.83511569e-01]\n",
      " [6.35053629e-01 9.37469404e-01 6.53444589e-01 5.99751107e-01\n",
      "  2.79419490e-01 5.09624677e-01 4.48496914e-01 2.80893987e-01]\n",
      " [4.42649783e-01 2.71267678e-01 2.40201341e-01 4.89757469e-01\n",
      "  8.61883021e-01 5.17891626e-01 5.79583355e-01 3.88861643e-01]\n",
      " [7.72405514e-01 4.30180120e-02 5.97374422e-01 4.80707385e-01\n",
      "  3.50151122e-02 3.06285621e-01 5.59684165e-01 6.61913878e-01]\n",
      " [9.40483926e-01 3.71234171e-01 6.92676634e-01 9.88839378e-02\n",
      "  4.51709726e-01 7.46109288e-01 5.97260344e-01 9.56085717e-01]\n",
      " [1.02451071e-01 8.19676563e-01 1.76165197e-01 4.34466101e-01\n",
      "  4.87799200e-01 7.92036717e-01 4.70309091e-01 2.50396289e-01]\n",
      " [9.50849857e-01 8.14927072e-01 2.05197174e-01 9.56525915e-01\n",
      "  9.11307493e-01 7.39359327e-01 2.43708481e-01 1.69147063e-01]\n",
      " [7.73366145e-01 3.87939003e-01 3.10847740e-01 2.02112573e-01\n",
      "  1.76792167e-01 2.19501854e-01 4.05725810e-01 4.61899413e-01]\n",
      " [1.69459302e-01 2.78651075e-02 6.15272456e-01 6.35221448e-01\n",
      "  9.39593700e-02 1.62165587e-02 4.47041148e-01 9.18507250e-01]\n",
      " [6.23172507e-01 3.10290623e-02 4.68592530e-01 1.82316495e-01\n",
      "  7.07495850e-01 2.16871199e-01 4.94607361e-01 7.49805069e-01]\n",
      " [5.65782218e-01 3.38058062e-01 1.81200540e-01 5.91084385e-01\n",
      "  1.75324818e-01 3.48228354e-02 7.91104181e-02 1.89486489e-02]\n",
      " [6.64737056e-01 1.03923730e-01 3.47140435e-01 5.79285218e-01\n",
      "  6.77022154e-01 9.22209655e-01 8.45129803e-01 5.31905682e-01]\n",
      " [5.95494538e-01 4.88375040e-01 5.92356622e-01 2.84532774e-01\n",
      "  7.52312342e-01 1.66141965e-01 8.09449595e-01 4.93110930e-01]\n",
      " [2.35829210e-01 7.46114387e-01 7.03330261e-01 6.11385078e-01\n",
      "  4.17771535e-01 7.89322479e-01 2.69946485e-01 7.81978656e-01]\n",
      " [1.20343190e-01 3.28783122e-02 6.75384791e-01 3.03189403e-01\n",
      "  2.14724569e-01 4.67720842e-01 1.90592789e-01 1.59585880e-01]\n",
      " [2.88838570e-01 9.79852765e-01 9.92555100e-01 3.33340867e-01\n",
      "  7.54073808e-01 7.54236441e-01 3.84658362e-01 6.42388987e-03]\n",
      " [5.52649138e-01 9.84995087e-01 8.78944875e-01 1.94287593e-01\n",
      "  3.09568460e-01 7.59825287e-01 9.51509180e-01 3.06795238e-02]\n",
      " [2.37829796e-01 9.16831961e-01 6.99572963e-01 2.19878014e-01\n",
      "  2.68503490e-01 9.69321335e-01 5.73028507e-01 6.52714994e-01]\n",
      " [2.69243774e-01 3.13752469e-01 5.49560462e-01 1.97524383e-01\n",
      "  6.39517594e-01 9.96770156e-01 3.22457386e-02 6.11091003e-01]\n",
      " [8.07100155e-01 8.26228187e-01 2.38423347e-01 2.02302538e-01\n",
      "  2.52916205e-01 7.47185013e-01 9.72752374e-01 6.47747061e-01]\n",
      " [9.88722200e-01 3.69696546e-01 7.22668504e-01 4.23393880e-01\n",
      "  9.48631866e-01 8.95496227e-01 8.00887700e-01 7.72236576e-01]\n",
      " [9.67386048e-01 7.18067474e-01 7.84105450e-02 7.30581660e-01\n",
      "  3.18231128e-02 9.04432240e-01 7.95954930e-01 1.00584891e-01]\n",
      " [4.55318233e-01 4.91074527e-01 7.56632761e-01 8.09361922e-01\n",
      "  2.49745363e-03 7.09430741e-01 4.54229491e-01 4.37660123e-01]\n",
      " [2.58376214e-03 3.40504529e-01 9.33197090e-01 4.37775876e-01\n",
      "  2.71490852e-01 5.41194275e-01 6.44276776e-01 7.11993922e-01]\n",
      " [1.84880712e-01 4.22777023e-01 6.62846058e-01 5.30043312e-01\n",
      "  9.31389527e-01 1.92642598e-01 2.13603430e-01 3.26952921e-01]\n",
      " [3.08186959e-01 8.62109485e-01 3.46219417e-01 6.82158084e-02\n",
      "  6.52683675e-01 2.19896320e-01 2.55801603e-01 2.45295727e-02]\n",
      " [9.67737147e-01 1.07339977e-01 2.31982175e-01 7.81774766e-02\n",
      "  8.16447311e-01 6.56215515e-01 4.84366568e-01 8.36636875e-01]\n",
      " [7.48323760e-01 3.27983477e-01 2.99471972e-02 5.99554094e-01\n",
      "  3.54515481e-01 7.58589505e-01 5.80931578e-01 5.09667169e-01]\n",
      " [2.97404821e-01 4.91056770e-01 8.13720425e-01 6.03047988e-01\n",
      "  6.63725530e-01 3.31824298e-02 2.27430581e-01 2.60021755e-01]\n",
      " [7.21238363e-01 8.80288630e-01 4.68880106e-01 1.40204773e-01\n",
      "  5.10530077e-01 1.25167578e-01 5.99590845e-01 1.11670313e-02]\n",
      " [9.71624490e-02 6.32368167e-01 9.96618495e-01 7.28405034e-01\n",
      "  7.90483292e-01 9.53521769e-01 7.50589179e-02 2.07992959e-01]\n",
      " [1.50923679e-01 4.03747455e-02 9.31362247e-01 2.69463710e-01\n",
      "  1.19817912e-01 8.03875598e-01 4.61219389e-01 8.13932574e-01]\n",
      " [2.50650129e-02 9.41200514e-01 7.01722186e-01 3.79136428e-01\n",
      "  9.75633189e-01 3.32736438e-01 7.75100761e-01 2.02712355e-01]\n",
      " [3.94366260e-01 6.17943129e-02 1.90719682e-01 9.01577201e-01\n",
      "  8.37544723e-01 6.88762045e-01 1.61099419e-01 1.87802905e-01]\n",
      " [6.00116896e-01 1.10317605e-01 3.46842424e-01 2.69288434e-02\n",
      "  2.05317722e-01 6.32962551e-01 5.33760743e-01 6.72708167e-02]\n",
      " [4.87063953e-01 4.44581531e-01 3.65663277e-01 3.21050836e-01\n",
      "  3.76194701e-01 1.99496037e-01 4.11400710e-01 6.92046642e-01]\n",
      " [9.15864793e-01 4.74816521e-01 4.12993218e-01 8.60564603e-01\n",
      "  5.37370406e-01 2.28772231e-01 1.50556583e-02 1.52214149e-01]\n",
      " [6.52654835e-01 3.71879465e-02 4.05263495e-01 9.27494161e-01\n",
      "  2.59027180e-01 4.16976174e-01 1.73144472e-01 3.23983391e-01]\n",
      " [3.31180251e-02 2.80758953e-01 8.25836427e-01 5.99590739e-01\n",
      "  7.37442304e-01 4.80368077e-01 5.68552206e-01 1.41640960e-01]\n",
      " [5.83375543e-01 9.95128617e-01 1.66887650e-01 3.53756472e-02\n",
      "  7.66930096e-01 5.03117779e-01 3.45767170e-01 8.39071925e-02]\n",
      " [1.79093134e-01 4.98938286e-01 7.12607883e-04 4.78371753e-01\n",
      "  2.88532492e-01 7.16786334e-01 2.67496129e-01 7.47092894e-01]\n",
      " [3.01479629e-01 7.36314784e-01 1.61430540e-02 2.80716652e-02\n",
      "  5.92939706e-01 2.36208220e-01 1.02896405e-01 3.19433540e-01]\n",
      " [6.45425236e-01 8.69177461e-01 6.13212808e-03 3.47509108e-01\n",
      "  3.83849162e-01 6.57681489e-01 9.38212126e-01 4.68346810e-01]\n",
      " [3.94558314e-01 3.64507260e-02 5.38525669e-01 8.04477781e-01\n",
      "  9.07428145e-01 7.04602801e-01 7.69167345e-01 7.95606293e-01]\n",
      " [3.81310104e-01 9.29180993e-01 7.16983560e-01 6.27096287e-01\n",
      "  3.90918658e-01 1.25819595e-01 8.20949979e-01 9.60901348e-01]\n",
      " [3.03169120e-01 3.60206940e-01 7.88824852e-01 6.81592643e-01\n",
      "  8.26641521e-01 1.65668072e-01 9.03717500e-01 5.33774051e-03]\n",
      " [2.56092304e-01 3.22618151e-01 7.12365625e-02 2.89329002e-01\n",
      "  3.77286715e-01 1.69872517e-01 2.45262767e-01 8.30173970e-01]\n",
      " [3.35595070e-01 9.88803362e-01 2.10204353e-01 1.81292824e-01\n",
      "  7.56080511e-03 6.44114062e-01 1.01299735e-01 4.87140475e-01]\n",
      " [7.82052454e-01 2.17888857e-01 9.53122766e-01 9.59079528e-01\n",
      "  6.46128080e-02 9.69236754e-01 2.42518602e-01 1.89031268e-01]\n",
      " [3.85001236e-01 7.65595400e-01 6.75175217e-01 4.06238924e-01\n",
      "  2.86368743e-01 6.07987458e-01 2.66989801e-01 3.55624979e-01]\n",
      " [4.73325704e-01 2.68456335e-01 4.59185608e-01 6.25400266e-01\n",
      "  5.77571068e-01 7.27340447e-01 2.67027643e-01 5.72418078e-01]\n",
      " [5.84425427e-01 9.89764741e-01 5.03013140e-01 2.61095695e-01\n",
      "  6.78109230e-01 9.92926871e-01 3.88688689e-01 6.87894012e-01]\n",
      " [2.76474868e-01 2.52564603e-01 9.80353388e-01 1.93084823e-02\n",
      "  2.86974171e-01 2.36650685e-01 1.56442978e-01 2.27357874e-01]\n",
      " [9.92014866e-01 1.66075828e-01 7.25833139e-01 5.78932589e-01\n",
      "  7.86126374e-01 1.65097179e-01 8.82232988e-01 2.47503763e-01]\n",
      " [4.62994140e-01 3.87020847e-01 7.15453546e-01 5.62483913e-01\n",
      "  2.51942277e-01 9.70514291e-01 5.14360935e-01 4.54399275e-01]\n",
      " [5.86214789e-01 2.54305589e-01 9.01684860e-02 3.01545721e-01\n",
      "  7.35557083e-01 3.64750033e-01 1.97915573e-01 7.38937573e-01]\n",
      " [6.98358211e-01 4.45404520e-01 1.17730112e-01 6.85984455e-01\n",
      "  4.14451081e-01 8.60237362e-02 9.52514165e-01 3.93664554e-01]\n",
      " [9.31477277e-01 9.98043726e-01 2.01288462e-01 8.03996928e-01\n",
      "  9.31162318e-01 7.60859113e-01 6.91611067e-01 7.98984702e-03]\n",
      " [1.78862249e-01 8.70579334e-01 6.37544757e-01 9.21559179e-02\n",
      "  6.54333732e-03 5.78702381e-01 1.20663739e-01 5.75385708e-02]\n",
      " [8.63333408e-01 2.52644934e-01 5.41214174e-01 5.76644250e-01\n",
      "  5.59153848e-02 7.46669157e-01 2.52044970e-01 4.94374755e-01]\n",
      " [6.07637814e-01 3.56373724e-01 4.69829246e-01 1.18526981e-01\n",
      "  5.65909667e-01 9.69936545e-01 2.18258288e-01 7.41099021e-01]\n",
      " [8.08415543e-01 1.22015055e-01 1.42275287e-01 7.29609765e-01\n",
      "  4.99066761e-01 4.41214941e-01 7.59360583e-01 4.03138804e-01]\n",
      " [6.25934778e-01 4.30819717e-01 6.53196453e-01 4.88697426e-01\n",
      "  2.24183180e-01 2.76097785e-01 1.08406733e-01 4.49882794e-02]\n",
      " [6.08071332e-01 7.67775479e-01 2.45700042e-01 3.34727340e-01\n",
      "  4.62070578e-01 9.82714646e-01 6.00711822e-01 8.13670049e-01]\n",
      " [7.56622912e-01 1.63883712e-01 6.45721809e-01 6.18226738e-02\n",
      "  8.78974250e-01 8.36866702e-01 1.71723432e-01 1.47374829e-01]\n",
      " [9.26413368e-01 8.65859727e-01 9.26747179e-02 8.46399108e-01\n",
      "  9.59494530e-01 3.86273220e-02 1.00614172e-01 6.95119676e-02]\n",
      " [8.61594544e-01 8.66768730e-02 7.30177099e-01 3.36935573e-01\n",
      "  3.34253323e-01 6.93848925e-01 1.19752014e-01 3.11565020e-01]\n",
      " [8.34041675e-01 6.93759890e-01 5.75707472e-01 6.73155140e-01\n",
      "  1.92418971e-01 6.28872039e-02 9.24387142e-01 5.89267823e-01]\n",
      " [2.24419350e-01 3.99070220e-01 4.55396192e-01 8.08034850e-01\n",
      "  5.44936306e-01 8.38554251e-01 8.03734958e-01 4.93049564e-01]\n",
      " [3.30916899e-01 8.65644788e-01 9.86097621e-01 3.96335880e-01\n",
      "  9.16894639e-01 3.77634152e-01 3.91114012e-01 2.73856882e-01]\n",
      " [9.34284712e-01 7.06429140e-01 2.87679264e-01 1.94488065e-01\n",
      "  6.56092213e-01 2.67299462e-01 9.17973703e-01 5.76872867e-01]\n",
      " [5.05290065e-02 6.09468201e-01 9.52344361e-01 3.31172342e-01\n",
      "  9.03302352e-01 6.35090687e-01 5.75065201e-01 5.69114820e-01]\n",
      " [7.50958425e-01 7.21484406e-01 8.31977462e-01 6.43901021e-01\n",
      "  3.41397546e-01 7.03192774e-01 7.34555759e-01 5.00085134e-01]\n",
      " [7.41117564e-01 2.66016689e-01 3.44062658e-01 9.07665189e-01\n",
      "  6.36898580e-01 7.73993276e-01 5.55893807e-02 8.71841644e-01]\n",
      " [8.54042189e-01 3.17569945e-01 8.54499769e-01 5.15354844e-01\n",
      "  3.61653292e-01 1.38081234e-01 5.86947296e-01 1.03681368e-01]\n",
      " [4.14959598e-01 4.55537619e-02 8.53651258e-01 2.44285059e-01\n",
      "  5.28474022e-01 1.10650039e-01 2.69031558e-01 9.68502295e-01]\n",
      " [4.39618683e-01 4.07478499e-02 5.13164203e-01 4.86858792e-01\n",
      "  8.39255253e-01 8.74966150e-01 1.13059999e-01 2.24424253e-01]\n",
      " [2.65325552e-01 6.88711029e-01 2.25787125e-01 3.60182459e-01\n",
      "  1.47164587e-01 2.24680818e-01 4.31687564e-01 1.57329560e-01]\n",
      " [2.88034969e-01 4.34199883e-01 3.65404579e-01 2.71079388e-01\n",
      "  6.14261150e-01 9.42667103e-01 1.68918224e-01 6.11464511e-01]\n",
      " [7.49669358e-01 3.95245712e-01 6.45346055e-01 9.76098763e-01\n",
      "  8.64312935e-01 1.59248957e-01 4.05240921e-01 1.58858597e-01]\n",
      " [8.65644528e-01 4.70645166e-01 4.37594552e-01 1.84885438e-01\n",
      "  8.93239671e-01 8.46633808e-01 6.26825022e-01 7.16317983e-01]\n",
      " [1.94218689e-01 4.86531651e-01 4.89656501e-01 9.28492529e-01\n",
      "  4.21499316e-01 6.87597730e-01 6.61988011e-01 5.04241503e-01]\n",
      " [4.81884002e-01 2.12994674e-01 6.22345603e-01 3.58181987e-01\n",
      "  7.82298751e-01 9.26599594e-02 9.73299275e-02 3.65469379e-01]\n",
      " [3.81494542e-01 3.83240934e-01 7.60588481e-01 7.78391267e-01\n",
      "  4.24648426e-01 9.73222452e-01 5.18861731e-01 8.83664976e-01]\n",
      " [9.37108429e-01 6.19450824e-01 7.82314933e-01 2.92049986e-01\n",
      "  4.76051681e-01 4.93544937e-01 1.96628075e-01 9.99388083e-01]\n",
      " [2.49522391e-01 5.49124841e-01 9.62748738e-01 8.88132350e-01\n",
      "  2.03218903e-01 1.21743706e-01 8.83074732e-02 8.31704344e-01]\n",
      " [2.68196498e-01 4.64931624e-01 5.29016953e-02 1.93737976e-01\n",
      "  3.66209943e-01 3.10730507e-01 9.31515002e-01 9.56299993e-01]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.007712\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.032102\n",
      "INFO:__main__:Average Minimum Distance 0.97\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=2_multi_True\n",
      "INFO:__main__:(12500, 2)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[2.04868543e-01 1.67455494e-01 5.39097708e-01 3.14122616e-01]\n",
      " [6.61568233e-01 5.72175821e-01 2.63650873e-01 4.43800304e-01]\n",
      " [2.64482916e-01 2.64436249e-01 6.81815774e-01 2.74215001e-01]\n",
      " [5.25317142e-01 6.43132303e-01 2.54402958e-01 4.47170243e-01]\n",
      " [2.26750139e-01 4.27041086e-01 7.35367219e-01 4.10893711e-01]\n",
      " [3.23329067e-01 6.63570286e-01 5.14943981e-01 2.13201118e-01]\n",
      " [1.21974082e-01 3.44017397e-01 7.98013253e-01 5.01250564e-01]\n",
      " [3.32111496e-01 4.33068247e-01 4.04859661e-01 5.87706865e-01]\n",
      " [2.50179029e-01 3.22945666e-01 8.68544789e-01 4.25095292e-01]\n",
      " [5.87496331e-02 5.47853178e-03 6.56606691e-01 3.07973310e-01]\n",
      " [4.12795465e-02 8.04178687e-02 8.42057355e-01 6.26845626e-01]\n",
      " [4.46013375e-02 7.63622212e-02 8.40154682e-01 6.30603633e-01]\n",
      " [4.26325838e-01 8.47544508e-02 4.56115344e-01 8.56826857e-01]\n",
      " [6.05855342e-01 3.87327698e-01 4.31859910e-01 7.19426350e-01]\n",
      " [1.59413288e-01 5.03414525e-01 6.61454822e-01 5.49400919e-01]\n",
      " [4.87421886e-01 2.88777884e-01 3.05305065e-01 9.21661019e-01]\n",
      " [3.18132541e-01 1.34567526e-01 1.45698194e-01 9.11282084e-01]\n",
      " [3.01003532e-01 4.31943535e-01 4.08106720e-01 2.06399547e-01]\n",
      " [6.28351428e-01 2.75037926e-01 4.54983095e-01 4.53663051e-01]\n",
      " [4.00831625e-01 1.43925980e-01 6.52225542e-01 4.03452424e-01]\n",
      " [3.08743063e-01 6.02794161e-01 5.23896665e-01 8.08517669e-01]\n",
      " [2.62209416e-01 6.32134644e-01 4.31753640e-01 1.67663963e-01]\n",
      " [9.30723762e-02 3.71856039e-01 4.84431763e-01 8.02898139e-01]\n",
      " [4.75942514e-02 7.01294509e-01 9.20850728e-01 1.80140377e-01]\n",
      " [5.76875041e-01 5.49567907e-01 1.44732202e-01 8.71143227e-01]\n",
      " [6.20084937e-01 2.94119780e-01 7.22813019e-01 6.77120620e-01]\n",
      " [2.71856848e-01 4.95461261e-02 9.19364228e-01 9.74612389e-01]\n",
      " [3.71653870e-01 5.13855345e-01 9.43153893e-01 5.58485684e-01]\n",
      " [7.04986897e-01 5.06772659e-01 6.61090192e-01 3.48502677e-01]\n",
      " [1.02184814e-01 7.39776620e-01 7.87752079e-01 2.30190220e-01]\n",
      " [4.75443495e-01 6.86638259e-01 9.42123274e-01 3.43627579e-01]\n",
      " [2.06929305e-01 4.30066510e-01 6.82643617e-01 1.39248688e-01]\n",
      " [4.22137848e-01 3.15310862e-01 7.63464307e-01 2.23904927e-01]\n",
      " [4.00860202e-01 6.65151846e-01 3.76237165e-01 8.92026273e-01]\n",
      " [6.28093378e-01 5.49760038e-01 9.43716949e-01 5.69364783e-01]\n",
      " [2.06952899e-01 6.99415084e-01 8.35491297e-01 5.57284616e-01]\n",
      " [5.78126291e-01 7.16280310e-01 7.63678212e-01 1.40474073e-01]\n",
      " [2.43176416e-01 7.20653921e-01 9.94472285e-01 6.11410063e-01]\n",
      " [7.10620139e-01 5.59533837e-01 9.33406079e-01 6.65848022e-01]\n",
      " [9.02465622e-01 6.33255187e-01 7.47826689e-01 3.12498212e-02]\n",
      " [3.20862513e-01 8.65701729e-01 9.93372090e-01 7.11294631e-01]\n",
      " [1.58858542e-01 6.63098256e-01 4.55994975e-01 8.11251346e-01]\n",
      " [9.26690775e-01 2.85064724e-01 4.30087332e-01 8.71349471e-01]\n",
      " [3.55466418e-01 8.40489800e-01 5.62077606e-01 5.45480172e-01]\n",
      " [9.36138493e-01 8.19816415e-01 8.15591276e-01 6.97657549e-01]\n",
      " [4.80973499e-01 3.73034335e-01 3.77847104e-01 2.90181867e-02]\n",
      " [8.19720885e-01 7.02254240e-01 4.45533521e-01 3.61651465e-02]\n",
      " [8.23940030e-01 9.57948165e-01 2.56267104e-01 4.36298752e-01]\n",
      " [3.91702759e-02 9.53996207e-01 1.44476395e-01 2.69995312e-01]\n",
      " [8.21950982e-01 9.77388217e-01 2.78683494e-01 1.72711334e-01]\n",
      " [6.93879418e-01 9.04750616e-01 7.61258160e-01 8.18756973e-01]\n",
      " [1.31385129e-01 3.51021254e-01 2.72995497e-01 2.66820772e-02]\n",
      " [7.68477195e-01 9.34436579e-01 3.60664900e-01 6.64395316e-01]\n",
      " [7.79253790e-01 3.69686150e-01 6.77308306e-01 6.19039406e-01]\n",
      " [9.00907794e-01 2.24037708e-01 1.62093471e-01 2.18246871e-01]\n",
      " [9.26242809e-01 8.65927115e-01 3.06424976e-01 6.71543130e-01]\n",
      " [7.28266776e-01 1.27202670e-01 5.47507894e-01 4.76042639e-01]\n",
      " [1.15988221e-01 7.22831918e-01 2.48339393e-01 5.14247566e-01]\n",
      " [2.00366013e-01 7.66005479e-01 1.72771046e-01 1.24349352e-01]\n",
      " [1.40311746e-01 9.43283801e-01 5.73194388e-02 4.03932466e-01]\n",
      " [8.84204556e-01 4.35437740e-01 4.70890511e-01 9.98280553e-01]\n",
      " [1.76217597e-01 5.84394341e-01 2.11770945e-01 9.54878704e-01]\n",
      " [1.04904293e-01 9.07660522e-01 3.32477351e-02 3.83318706e-01]\n",
      " [9.14242961e-01 8.12240186e-01 2.77220649e-01 6.02901180e-01]\n",
      " [8.73485137e-01 3.59608562e-01 6.56815191e-01 8.89507704e-02]\n",
      " [3.81827143e-01 8.37282154e-01 1.69652370e-01 9.97930935e-01]\n",
      " [7.73636839e-01 4.50725236e-02 8.45742022e-01 4.09693685e-01]\n",
      " [1.23966921e-01 9.44607771e-01 8.90796538e-01 2.96701178e-01]\n",
      " [6.21413940e-01 8.25156292e-01 2.02346517e-01 3.65764904e-01]\n",
      " [4.19086183e-01 6.17314197e-01 9.08236436e-01 4.49501196e-02]\n",
      " [6.56118563e-01 7.85582429e-01 1.54367938e-01 6.20868786e-04]\n",
      " [8.78054158e-01 3.62961615e-01 1.07328389e-01 3.76788267e-01]\n",
      " [1.81264908e-01 6.62750833e-01 3.97528362e-01 4.78289958e-01]\n",
      " [6.13934819e-01 1.11581071e-01 2.77833843e-01 1.86454513e-01]\n",
      " [9.18671951e-01 6.86196260e-01 3.79896387e-01 8.85028233e-01]\n",
      " [3.72390449e-01 8.43824515e-01 2.30181039e-01 5.25156343e-01]\n",
      " [4.63244311e-01 8.83138792e-01 7.08091254e-01 1.19781669e-01]\n",
      " [9.19650567e-01 4.71274118e-02 3.26292805e-01 3.30266006e-01]\n",
      " [9.41041082e-01 7.39392709e-01 1.17225893e-01 1.01402032e-01]\n",
      " [4.08593233e-01 5.05266835e-01 1.17830903e-01 9.64510558e-01]\n",
      " [5.73825139e-01 9.56016841e-01 5.44332188e-01 5.49155035e-01]\n",
      " [8.93763246e-01 1.58999590e-01 5.65320439e-01 9.55417325e-01]\n",
      " [9.69677115e-01 2.91597932e-01 8.70397201e-01 1.34383450e-01]\n",
      " [9.72051896e-01 6.20794677e-01 7.35586712e-01 4.79442434e-01]\n",
      " [9.23598633e-01 3.31669134e-01 7.63086860e-01 8.90583403e-01]\n",
      " [1.75902362e-01 8.01336934e-01 2.50222653e-01 4.59812578e-02]\n",
      " [6.25516776e-01 9.89934829e-01 6.84209059e-01 8.02958154e-01]\n",
      " [2.55495440e-01 8.64874910e-01 6.84016927e-01 6.64933704e-02]\n",
      " [1.89336481e-01 5.24132331e-01 1.77243926e-01 6.25684356e-01]\n",
      " [9.17079248e-01 3.63051344e-01 4.36348841e-01 9.99782426e-01]\n",
      " [9.69535880e-01 9.86831402e-01 3.42739185e-01 9.35053994e-01]\n",
      " [3.12537815e-01 1.51518739e-01 8.67995391e-01 4.72484380e-03]\n",
      " [7.86012905e-01 4.97805468e-01 6.87247544e-01 1.91887745e-01]\n",
      " [4.76509089e-01 6.68968705e-01 6.26775837e-02 3.41010442e-02]\n",
      " [8.72586823e-01 5.42234569e-01 1.03304140e-01 7.79976974e-01]\n",
      " [8.35657114e-01 2.42459981e-01 5.53553052e-01 5.13420254e-01]\n",
      " [7.90512850e-01 6.59458852e-01 2.20194342e-01 8.76253255e-01]\n",
      " [8.40264973e-01 4.79322985e-01 8.81916567e-01 8.92110111e-01]\n",
      " [8.58958995e-01 7.87858335e-01 9.52559047e-01 9.97206461e-01]\n",
      " [9.37775392e-01 7.26208924e-01 9.18728573e-01 8.24803743e-01]]\n",
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.127950\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.213945\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.224516\n",
      "INFO:__main__:Average Minimum Distance 0.66\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=5_multi_True\n",
      "INFO:__main__:(5000, 6)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[1.59713877e-01 1.34977201e-01 7.32327979e-01 8.56406758e-01\n",
      "  5.49456446e-01 6.77050957e-01 2.53232446e-01 9.77660368e-02\n",
      "  3.77119306e-01 9.43859635e-02]\n",
      " [8.64448489e-01 2.63195283e-01 2.15908799e-01 4.57906427e-01\n",
      "  5.35101805e-01 8.50644137e-01 5.12127006e-01 4.30916838e-02\n",
      "  8.82188543e-01 3.12705616e-01]\n",
      " [4.24793060e-01 7.07625277e-01 2.98188653e-01 1.24088675e-01\n",
      "  8.08448468e-01 9.34026203e-02 9.78108892e-02 1.32989174e-01\n",
      "  1.67171212e-01 5.98012852e-01]\n",
      " [5.78843393e-01 5.10466234e-01 8.54033335e-01 1.19630169e-01\n",
      "  3.38647548e-01 5.07451750e-01 4.77892304e-01 6.22827294e-01\n",
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      " [3.87536872e-01 7.54086755e-01 9.88453959e-01 1.19941211e-01\n",
      "  6.91144288e-01 9.84458000e-01 2.35813040e-01 8.13456361e-01\n",
      "  1.22272514e-01 4.92518447e-01]\n",
      " [5.73296872e-01 2.29660621e-01 9.72844346e-01 6.26340674e-01\n",
      "  3.74389217e-01 5.02518661e-01 9.62954054e-01 7.42478413e-01\n",
      "  6.96870554e-01 6.38502126e-01]\n",
      " [4.71100856e-01 7.40670796e-02 7.14099202e-01 5.58347484e-02\n",
      "  8.63338172e-01 4.93674021e-01 4.95155256e-01 1.97936606e-01\n",
      "  3.66617709e-01 8.12857659e-02]\n",
      " [2.21275270e-02 6.67445646e-01 3.30658464e-02 2.67300150e-01\n",
      "  6.17841219e-01 6.58265628e-01 2.53729696e-01 4.41128209e-01\n",
      "  3.41466255e-01 5.82515718e-02]\n",
      " [5.45497082e-01 2.83981207e-01 2.72222938e-01 8.10974779e-01\n",
      "  8.85649110e-01 7.13155143e-01 1.10021546e-01 2.93478553e-01\n",
      "  2.77407131e-01 6.68366116e-01]\n",
      " [6.39039579e-01 6.54063647e-01 3.32646475e-01 3.40182843e-01\n",
      "  5.27811372e-01 9.84281120e-01 2.06328697e-01 8.55243615e-01\n",
      "  6.12617791e-02 3.19246754e-01]\n",
      " [4.08155243e-01 7.99189773e-02 9.64405470e-01 9.44957320e-01\n",
      "  4.20168288e-01 9.57891527e-02 6.65697904e-01 8.28255683e-01\n",
      "  1.49222931e-01 3.00387915e-01]\n",
      " [3.19605976e-02 1.94101236e-01 4.15500959e-02 3.63296141e-01\n",
      "  8.95080384e-01 7.12980237e-01 3.89940050e-01 1.30696049e-02\n",
      "  8.20015787e-01 8.98225749e-01]\n",
      " [7.09127275e-01 8.46147171e-01 4.71539733e-01 7.76430693e-01\n",
      "  2.36668120e-01 6.06902069e-01 4.68475788e-01 7.82376288e-01\n",
      "  5.02098456e-01 3.07574260e-01]\n",
      " [6.98125353e-01 8.07972797e-01 1.31550266e-01 6.25457465e-01\n",
      "  6.90827728e-01 4.39666938e-01 2.70701188e-01 2.21925850e-01\n",
      "  7.35956504e-01 5.46275121e-01]\n",
      " [9.29166578e-01 5.66407537e-01 1.34970593e-01 4.20364916e-01\n",
      "  7.33756458e-01 8.74469119e-01 7.69119056e-02 1.61886166e-01\n",
      "  8.33802761e-01 9.19802181e-01]\n",
      " [9.01028212e-01 8.51509904e-01 6.13293085e-01 6.51709502e-01\n",
      "  5.61839831e-01 3.84454351e-01 5.80820495e-01 2.11329739e-01\n",
      "  6.88588231e-01 4.07311419e-01]\n",
      " [7.18880451e-01 2.78628008e-01 2.16835864e-01 7.05694413e-01\n",
      "  4.91327016e-01 8.50950827e-01 7.36026647e-01 6.58036869e-01\n",
      "  3.69850132e-01 1.55910668e-01]\n",
      " [1.42353453e-01 6.22217373e-01 9.27112722e-01 7.92915269e-01\n",
      "  4.30838901e-02 4.15104191e-01 6.34542948e-01 3.01088295e-01\n",
      "  6.68334846e-01 3.75775250e-01]\n",
      " [1.57283458e-01 4.98954947e-01 4.93246595e-01 2.03660871e-03\n",
      "  2.80376180e-01 4.17566447e-01 2.84164799e-01 9.87392716e-01\n",
      "  4.57851738e-01 7.37372957e-01]\n",
      " [6.64002988e-01 6.74422676e-01 2.77238794e-01 6.85046026e-01\n",
      "  4.24925213e-01 5.11289970e-01 9.49836698e-01 5.66455600e-02\n",
      "  9.74537883e-01 8.00339240e-01]\n",
      " [5.83384342e-01 9.78512803e-01 3.07452769e-02 1.56792172e-01\n",
      "  5.12527717e-01 9.52559420e-01 6.32435269e-01 7.20319717e-01\n",
      "  7.12152109e-01 8.78241800e-01]\n",
      " [3.72474453e-01 5.95799547e-01 3.71979329e-01 6.26875519e-01\n",
      "  5.69741287e-01 5.77524832e-01 7.04141959e-02 1.10773049e-01\n",
      "  2.76663434e-01 1.10482399e-02]\n",
      " [6.76182617e-01 4.89115729e-01 7.80380966e-01 4.67817425e-01\n",
      "  9.17255092e-01 7.60767135e-01 2.25414384e-01 4.48534398e-01\n",
      "  8.25594804e-02 6.34760513e-01]\n",
      " [9.17579951e-01 1.97733602e-01 5.18891322e-01 4.36446680e-01\n",
      "  2.74097097e-01 2.92584460e-01 3.07007458e-01 3.41462309e-01\n",
      "  6.45509073e-01 7.66949859e-01]\n",
      " [5.11799324e-01 6.85823800e-02 9.15686073e-01 3.18460950e-01\n",
      "  6.96360958e-01 6.70996976e-01 7.09532076e-01 5.66169444e-01\n",
      "  4.50937486e-02 2.24135261e-01]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.027097\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.002913\n",
      "INFO:__main__:Average Minimum Distance 1.08\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=5_multi_False\n",
      "INFO:__main__:(5000, 6)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.97917198 0.94262079 0.23322357 0.56385074 0.27277642 0.22924484\n",
      "  0.41734228 0.84861659 0.20020219 0.4071633 ]\n",
      " [0.62586425 0.88224822 0.05366885 0.34517743 0.82059992 0.08811544\n",
      "  0.05863999 0.9209985  0.8581133  0.69906226]\n",
      " [0.99018562 0.98649298 0.09340659 0.64441901 0.76047233 0.50104141\n",
      "  0.42504754 0.04623303 0.30669462 0.37306904]\n",
      " [0.93882916 0.60219558 0.68029206 0.3247486  0.09545595 0.73697941\n",
      "  0.87456093 0.31403531 0.59990988 0.94283149]\n",
      " [0.66896496 0.14762825 0.50409725 0.60747109 0.34141708 0.22372667\n",
      "  0.88553332 0.16103518 0.45160826 0.08504937]\n",
      " [0.64356115 0.74063626 0.85062603 0.58389284 0.23746916 0.61010686\n",
      "  0.10203    0.23844942 0.63921913 0.32180898]\n",
      " [0.25081892 0.89353298 0.2839536  0.87691049 0.52527124 0.76754648\n",
      "  0.44504844 0.15254999 0.66077199 0.67763354]\n",
      " [0.59306019 0.13960292 0.67813855 0.61006404 0.50244513 0.00770257\n",
      "  0.98929038 0.99346175 0.77610285 0.44666753]\n",
      " [0.71162389 0.54855757 0.89349376 0.15862419 0.66139368 0.86009771\n",
      "  0.75216316 0.71115146 0.77049352 0.14178939]\n",
      " [0.95714095 0.03253718 0.40799163 0.65520438 0.71924434 0.61349133\n",
      "  0.01135561 0.71670642 0.96048846 0.61218913]\n",
      " [0.76037686 0.06270229 0.3087795  0.15408109 0.19843857 0.28656952\n",
      "  0.98634879 0.2738555  0.35112948 0.03330152]\n",
      " [0.14365777 0.81149919 0.34850976 0.10885717 0.19792331 0.18786653\n",
      "  0.78183098 0.30177786 0.97943829 0.29081989]\n",
      " [0.04728518 0.42145656 0.13978252 0.88864713 0.64990955 0.15521171\n",
      "  0.34353404 0.24704881 0.26132207 0.58677762]\n",
      " [0.5880527  0.6208651  0.87942491 0.50198708 0.69580247 0.32750373\n",
      "  0.60775236 0.11844544 0.11958124 0.05724241]\n",
      " [0.97752308 0.19817441 0.59237097 0.79857098 0.69199373 0.98534055\n",
      "  0.43361601 0.07480107 0.26806491 0.57830047]\n",
      " [0.46542215 0.5799417  0.2029374  0.01101533 0.77075644 0.66698584\n",
      "  0.60104099 0.02181155 0.67868505 0.96238289]\n",
      " [0.67686671 0.88052408 0.37510471 0.65714449 0.0672175  0.23117607\n",
      "  0.54117961 0.75405613 0.02027588 0.15025678]\n",
      " [0.04307998 0.04504169 0.25615453 0.60971296 0.63225557 0.52546116\n",
      "  0.69315822 0.13585837 0.77244502 0.6044693 ]\n",
      " [0.3775512  0.60023683 0.11549396 0.60613224 0.34979169 0.69055689\n",
      "  0.18490814 0.30887278 0.48859238 0.24700391]\n",
      " [0.217254   0.07911035 0.25115442 0.65945395 0.30753803 0.83016044\n",
      "  0.2140157  0.09952072 0.85150569 0.30035217]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.002120\n",
      "INFO:__main__:Average Minimum Distance 1.00\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=3_multi_True\n",
      "INFO:__main__:(12500, 3)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[4.20367043e-01 4.87792280e-01 4.44991748e-01 3.46183063e-01\n",
      "  5.22724408e-01 3.45473439e-01]\n",
      " [2.06816302e-01 3.05051574e-01 3.65735637e-01 8.23681187e-01\n",
      "  5.00934422e-01 4.58020733e-01]\n",
      " [3.51957113e-01 4.11804479e-01 3.99625182e-01 7.28776563e-01\n",
      "  4.27904966e-01 5.01393849e-01]\n",
      " [5.50545888e-01 3.91767076e-01 6.09139862e-01 5.10638924e-01\n",
      "  5.88087190e-01 4.81281628e-01]\n",
      " [4.08635941e-02 1.56185730e-01 2.86160399e-01 3.97303514e-01\n",
      "  4.27970313e-01 6.18930994e-01]\n",
      " [3.47325537e-01 2.05124221e-01 3.13199989e-02 1.60351781e-01\n",
      "  6.22068200e-01 7.73296363e-01]\n",
      " [3.16432787e-02 3.17106186e-01 3.59360426e-01 5.91696258e-01\n",
      "  4.78575620e-01 5.18348421e-01]\n",
      " [6.56553344e-01 5.65336610e-01 4.51175417e-01 2.89920470e-01\n",
      "  5.45280448e-01 2.85293253e-01]\n",
      " [4.86359798e-01 3.00140034e-01 5.27206434e-01 9.28478010e-01\n",
      "  6.32947465e-01 3.93627183e-01]\n",
      " [5.13127587e-01 5.09296430e-01 6.49468615e-01 7.59148014e-01\n",
      "  8.00726901e-01 1.61877601e-01]\n",
      " [4.38628970e-01 2.25467121e-01 4.09523001e-01 6.00429072e-01\n",
      "  5.83335865e-01 8.63859469e-01]\n",
      " [1.18238776e-01 3.34752241e-01 1.68688015e-01 5.58275412e-01\n",
      "  7.76007315e-01 8.15634451e-01]\n",
      " [3.37569911e-01 3.24572736e-01 3.46130546e-01 8.64663554e-01\n",
      "  7.41439855e-01 6.42898717e-01]\n",
      " [7.56849721e-02 6.27538218e-01 1.36748714e-01 8.78976786e-01\n",
      "  3.87175895e-01 8.13811951e-01]\n",
      " [7.28656791e-03 3.86331940e-01 2.43645526e-01 5.38035270e-01\n",
      "  8.09931508e-01 4.31360507e-01]\n",
      " [3.12295027e-01 4.92234380e-01 6.69621692e-01 5.64065176e-01\n",
      "  4.78090148e-01 7.87156676e-01]\n",
      " [3.02615272e-01 5.16071880e-01 3.70830956e-01 8.36823893e-01\n",
      "  1.68717376e-01 5.29298558e-01]\n",
      " [2.22153611e-01 4.53209643e-01 1.54973226e-01 8.72219329e-01\n",
      "  8.09507024e-01 5.57833310e-01]\n",
      " [5.49532712e-01 5.55907016e-01 6.40078399e-01 2.81556064e-01\n",
      "  9.19511066e-01 8.75969198e-01]\n",
      " [3.86907341e-01 8.62662194e-02 5.10531500e-02 7.73840095e-01\n",
      "  6.06131916e-01 3.64005936e-01]\n",
      " [6.76192676e-01 5.51990907e-01 3.88998866e-01 6.99123326e-01\n",
      "  7.93813250e-01 5.29409992e-01]\n",
      " [1.48528291e-01 4.17616250e-01 3.73060751e-01 4.54007741e-01\n",
      "  4.01255755e-01 9.68463294e-01]\n",
      " [7.13120172e-01 6.44896027e-01 4.12107495e-01 4.78212372e-01\n",
      "  3.19844500e-01 7.18377349e-01]\n",
      " [2.11974483e-02 7.96140204e-02 7.08878982e-01 7.85526999e-01\n",
      "  9.04601739e-01 9.61518056e-01]\n",
      " [5.80015474e-02 2.73545889e-01 7.49950683e-01 9.11646283e-01\n",
      "  6.87859636e-01 1.13024364e-01]\n",
      " [6.87850639e-01 6.31587933e-02 7.70436693e-01 5.94439510e-01\n",
      "  9.70607235e-01 4.46463259e-01]\n",
      " [7.25444422e-01 2.79981599e-01 6.43206049e-01 1.67801615e-01\n",
      "  7.44698506e-01 8.79494689e-01]\n",
      " [1.91112703e-01 8.47251025e-01 2.14630090e-01 7.04239879e-01\n",
      "  1.99086710e-01 5.78234655e-01]\n",
      " [4.38948411e-01 7.86184468e-01 7.74298155e-01 4.59052371e-01\n",
      "  3.84439000e-01 5.87304607e-01]\n",
      " [8.53483430e-01 1.41804200e-01 8.05709140e-01 9.53298746e-01\n",
      "  5.51463876e-01 1.80493725e-01]\n",
      " [5.12591924e-01 1.34636691e-01 8.07778160e-01 4.58369417e-01\n",
      "  2.10821020e-01 5.07844050e-01]\n",
      " [8.89425579e-01 9.01831106e-01 1.81670032e-01 6.91653613e-01\n",
      "  7.96388048e-02 6.57560543e-01]\n",
      " [4.95514041e-01 5.28739093e-01 6.30595100e-01 8.65360609e-02\n",
      "  2.36677555e-02 8.99731915e-01]\n",
      " [8.52747862e-01 8.16193817e-01 7.65909471e-01 1.06063047e-01\n",
      "  1.86662838e-01 5.30301263e-01]\n",
      " [1.87915474e-02 5.51505038e-02 3.16285621e-01 2.14524253e-01\n",
      "  8.30084768e-01 4.48361493e-01]\n",
      " [1.88905241e-01 7.30699411e-01 3.60267002e-01 1.97220834e-01\n",
      "  4.41158659e-01 4.66953653e-01]\n",
      " [5.63441513e-01 3.34312697e-01 6.34999969e-01 3.87843916e-01\n",
      "  1.42156552e-01 8.97921516e-01]\n",
      " [8.38022906e-01 5.49215207e-01 3.68553468e-01 2.34666822e-01\n",
      "  5.08641602e-01 4.78735491e-01]\n",
      " [7.11939571e-01 1.52823987e-01 1.21233290e-01 9.16810049e-01\n",
      "  3.42637043e-02 2.76131606e-01]\n",
      " [6.60786678e-01 2.73276915e-01 3.08543679e-01 5.25425155e-01\n",
      "  2.72172888e-01 7.33787259e-02]\n",
      " [5.98441774e-01 1.63958507e-02 9.22620259e-01 3.13679285e-01\n",
      "  4.81794252e-02 6.99952754e-01]\n",
      " [8.18263823e-01 6.59015852e-01 4.05459032e-01 9.43014196e-01\n",
      "  6.72552571e-01 5.15411251e-01]\n",
      " [2.24462022e-01 1.17559581e-01 5.41900092e-01 2.53671992e-01\n",
      "  2.60444729e-01 6.47064668e-01]\n",
      " [4.86195183e-01 2.34364370e-01 5.58038601e-02 6.99191816e-01\n",
      "  7.29691623e-02 8.83610370e-01]\n",
      " [1.02277027e-01 9.83874174e-01 9.93463806e-01 6.02601319e-01\n",
      "  4.35047916e-01 3.14048056e-02]\n",
      " [6.78301714e-01 8.95447737e-01 3.02891260e-01 4.65798745e-01\n",
      "  7.55423782e-01 8.20399119e-01]\n",
      " [3.11195166e-01 9.39288766e-02 4.83245488e-01 9.82008799e-01\n",
      "  2.70416340e-01 1.71909300e-01]\n",
      " [6.03702133e-01 3.94006959e-01 3.46015151e-01 1.74636359e-01\n",
      "  6.82526626e-01 3.29534618e-01]\n",
      " [6.87000483e-01 8.34856830e-01 5.16345112e-01 8.01799747e-01\n",
      "  9.73820249e-01 7.68838927e-01]\n",
      " [4.31358596e-01 2.38384597e-01 6.06785626e-01 1.62959955e-01\n",
      "  1.91052038e-01 4.65519100e-01]\n",
      " [9.50318645e-01 8.32581230e-01 2.86660307e-01 6.93123875e-01\n",
      "  2.68604534e-01 4.23072265e-01]\n",
      " [9.19946078e-01 8.58332234e-01 3.61549176e-01 8.61195119e-01\n",
      "  5.60189796e-02 6.12475566e-01]\n",
      " [8.26711269e-01 8.27247859e-01 2.99553153e-01 2.21735066e-01\n",
      "  2.31382125e-01 7.94371891e-01]\n",
      " [1.81161388e-02 9.04386404e-01 1.04053931e-02 7.65889557e-01\n",
      "  6.61679288e-01 8.03730716e-01]\n",
      " [3.50117762e-01 3.09833254e-01 1.28072367e-01 5.81196922e-01\n",
      "  8.23302822e-01 1.34267893e-01]\n",
      " [2.18172388e-01 7.96909048e-01 7.83629760e-01 2.66747495e-01\n",
      "  6.75086546e-01 8.20461986e-01]\n",
      " [2.60731887e-01 5.34711411e-01 2.11431438e-02 2.82062743e-01\n",
      "  9.20885704e-01 6.76775878e-01]\n",
      " [2.53609370e-01 6.71995233e-01 9.10906105e-01 8.09922045e-01\n",
      "  3.54602292e-01 5.15048413e-01]\n",
      " [9.20407683e-01 4.15689055e-01 9.36593396e-01 6.18260192e-01\n",
      "  2.12409117e-01 8.42238496e-01]\n",
      " [5.00106061e-01 6.37826161e-01 4.29656980e-01 2.97661999e-02\n",
      "  4.91833608e-01 8.99278774e-01]\n",
      " [8.38093944e-01 9.56779398e-02 5.97911804e-01 9.81700694e-01\n",
      "  7.19849135e-02 6.39053902e-02]\n",
      " [7.81262705e-01 3.89535153e-01 7.88499709e-02 4.56919179e-01\n",
      "  4.48396510e-01 7.53649906e-01]\n",
      " [4.56849526e-01 1.30315322e-01 4.81441728e-01 1.16613000e-01\n",
      "  6.05828133e-01 3.22833366e-01]\n",
      " [5.67929273e-01 5.83118240e-01 8.09275455e-01 2.19848934e-01\n",
      "  9.16936443e-01 7.35145592e-01]\n",
      " [1.76494033e-01 6.70555214e-01 5.45811822e-01 1.73694133e-01\n",
      "  7.82931188e-01 4.27592405e-01]\n",
      " [7.93739649e-01 9.63098700e-01 3.80809542e-02 6.51492022e-01\n",
      "  9.66240006e-01 4.12124722e-01]\n",
      " [8.49907509e-01 7.40634296e-02 2.54433866e-01 4.94641500e-01\n",
      "  8.54123544e-01 2.12519545e-01]\n",
      " [3.75833910e-01 4.28501481e-01 6.96208031e-02 1.37801672e-01\n",
      "  7.75469332e-01 8.73758297e-01]\n",
      " [1.93637378e-01 7.42502386e-01 8.47469825e-01 1.57797853e-01\n",
      "  2.22103747e-01 6.44193951e-01]\n",
      " [7.53893702e-01 8.25954725e-01 7.87975113e-01 7.73451353e-01\n",
      "  6.11754368e-01 9.32538382e-01]\n",
      " [1.31300010e-01 2.58643625e-03 4.07047310e-01 5.89731017e-01\n",
      "  3.09303583e-01 7.27192307e-01]\n",
      " [6.13377430e-01 1.93346585e-01 8.32321121e-01 2.51186790e-01\n",
      "  1.58422825e-01 3.62082884e-01]\n",
      " [4.90350052e-01 8.27268179e-01 4.29928221e-01 1.55322819e-01\n",
      "  7.94936259e-01 3.57067040e-01]\n",
      " [2.06954404e-01 5.41340600e-01 7.41442960e-01 2.73515536e-01\n",
      "  5.87464177e-02 5.29991085e-01]\n",
      " [9.14078454e-01 2.85816320e-01 2.68290603e-01 9.65455925e-01\n",
      "  5.35316412e-01 6.77648600e-01]\n",
      " [8.06739746e-01 4.88858704e-01 2.50323537e-01 7.36188734e-01\n",
      "  2.14962333e-01 4.04371025e-02]\n",
      " [7.69767404e-01 4.23782956e-01 9.59900925e-01 3.29183017e-01\n",
      "  8.64907941e-01 7.90741261e-01]\n",
      " [4.66130147e-01 7.95671937e-01 8.25667054e-01 4.92067325e-01\n",
      "  8.73332062e-01 2.94305073e-01]\n",
      " [4.57129021e-01 2.99562765e-01 2.13972729e-01 4.52995035e-01\n",
      "  2.00419528e-01 1.09234780e-01]\n",
      " [8.38889589e-01 3.18664471e-01 1.03045078e-02 5.85155177e-01\n",
      "  3.17163328e-01 9.74810886e-01]\n",
      " [9.66914066e-01 8.45817262e-01 2.80340873e-01 5.77370156e-01\n",
      "  3.53031403e-01 2.16602510e-01]\n",
      " [9.01200685e-01 2.91960094e-02 4.32112926e-01 6.12648522e-01\n",
      "  1.65697358e-02 7.25577916e-01]\n",
      " [4.63983858e-01 3.61119470e-02 6.31560374e-01 9.96268992e-01\n",
      "  2.58678951e-01 8.09986659e-01]\n",
      " [9.77985658e-01 7.13190677e-01 1.44966601e-01 7.01279177e-01\n",
      "  8.57412375e-01 4.96784536e-01]\n",
      " [9.80627098e-01 5.51690151e-01 2.64536242e-01 9.97889574e-01\n",
      "  5.55164001e-01 9.15496931e-01]\n",
      " [2.52547134e-01 8.74479922e-01 6.35038868e-01 5.30072066e-01\n",
      "  7.12780729e-01 4.61850615e-01]\n",
      " [9.17742948e-01 3.78779149e-02 1.03512306e-01 8.34532939e-01\n",
      "  3.94789054e-01 7.45122456e-01]\n",
      " [3.00102383e-02 9.12373246e-01 4.13743131e-01 2.36330694e-01\n",
      "  2.97594632e-01 3.13818254e-01]\n",
      " [1.35827023e-01 9.44398361e-01 5.89960578e-01 3.06022396e-01\n",
      "  1.81815208e-01 1.23271340e-01]\n",
      " [2.52445335e-01 8.80966800e-01 8.56946261e-01 9.47532373e-01\n",
      "  4.61869047e-01 3.77321358e-01]\n",
      " [8.10543818e-02 9.61017809e-01 7.19701903e-01 1.40849679e-01\n",
      "  7.56268732e-01 9.10176010e-01]\n",
      " [7.50244770e-01 5.83351617e-01 5.09263272e-01 6.91513246e-01\n",
      "  2.06656094e-01 8.77317678e-02]\n",
      " [3.56494853e-01 4.74563663e-01 5.99744571e-02 3.52564874e-01\n",
      "  1.66692279e-01 7.71121910e-01]\n",
      " [6.78603804e-01 4.55734572e-01 4.09694366e-01 3.23719469e-02\n",
      "  2.94618259e-02 9.39596612e-01]\n",
      " [9.02868054e-01 7.40571881e-01 9.11747886e-01 6.40241867e-01\n",
      "  7.23486075e-02 4.33595855e-02]\n",
      " [9.72330395e-01 1.01504810e-04 4.41507539e-01 6.39949227e-02\n",
      "  8.83656962e-01 9.51967744e-01]\n",
      " [5.74174118e-01 9.11924011e-01 7.40624831e-01 9.89281591e-01\n",
      "  2.43881810e-01 4.82930233e-01]\n",
      " [9.24297196e-01 4.86604967e-01 5.93352482e-01 4.39169226e-01\n",
      "  9.84407013e-01 2.11359722e-01]\n",
      " [8.40520330e-01 6.56050292e-01 4.74334856e-01 8.54961742e-01\n",
      "  9.41738641e-04 7.66956208e-02]\n",
      " [5.93066582e-01 7.82379317e-01 3.24642621e-01 1.24056141e-01\n",
      "  9.86809592e-01 4.23607125e-01]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.077275\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.098866\n",
      "INFO:__main__:Average Minimum Distance 0.83\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=5_multi_False\n",
      "INFO:__main__:(7500, 5)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.32699883 0.64266446 0.20887722 0.60877443 0.52831264 0.72587415\n",
      "  0.24030501 0.94291464 0.25781928 0.3752216 ]\n",
      " [0.28903765 0.2338234  0.44035042 0.30284019 0.60847554 0.88048532\n",
      "  0.59015233 0.47013047 0.52430527 0.25623165]\n",
      " [0.25522694 0.33176159 0.36582195 0.49999708 0.31103323 0.92761593\n",
      "  0.56563531 0.93049919 0.69347622 0.7324094 ]\n",
      " [0.31672745 0.43019688 0.30140718 0.51467826 0.48137203 0.81558468\n",
      "  0.95114862 0.74434238 0.85292175 0.74514567]\n",
      " [0.66704405 0.51695742 0.4956437  0.36124631 0.27326505 0.86462604\n",
      "  0.79608926 0.89494257 0.82448339 0.86889436]\n",
      " [0.7451508  0.60807551 0.3481416  0.47733467 0.52643978 0.61021171\n",
      "  0.21934003 0.96741919 0.62911655 0.76025837]\n",
      " [0.4209008  0.37344195 0.45644531 0.62465086 0.77949332 0.7115671\n",
      "  0.71994117 0.77893346 0.77097663 0.13053371]\n",
      " [0.032609   0.48471246 0.27026203 0.3239423  0.38752426 0.62649353\n",
      "  0.75259789 0.92010655 0.91491205 0.65750781]\n",
      " [0.38097003 0.67348475 0.35039694 0.86574852 0.10733897 0.62907754\n",
      "  0.35833223 0.08710692 0.4853841  0.40435238]\n",
      " [0.09085079 0.89356427 0.79122297 0.02037014 0.88212055 0.57453433\n",
      "  0.80381358 0.57301275 0.61623156 0.7105717 ]\n",
      " [0.8090041  0.84629726 0.77688263 0.36964477 0.75438353 0.17168952\n",
      "  0.29523061 0.67178781 0.99309549 0.7569366 ]\n",
      " [0.68914308 0.32033472 0.36796142 0.91411163 0.95825091 0.60570303\n",
      "  0.87593208 0.35782195 0.62649205 0.62402338]\n",
      " [0.72687246 0.29893882 0.39001581 0.42694561 0.06594959 0.2399629\n",
      "  0.06067548 0.88649008 0.97098626 0.96972208]\n",
      " [0.76598716 0.18426912 0.84357961 0.38427247 0.4319945  0.42104272\n",
      "  0.81938333 0.30598446 0.77513914 0.86294411]\n",
      " [0.71395232 0.05108145 0.14702776 0.9235728  0.79572735 0.30590698\n",
      "  0.68453043 0.79294897 0.71413212 0.87762749]\n",
      " [0.71017765 0.09914703 0.98449487 0.44125384 0.10582336 0.4185907\n",
      "  0.24004495 0.63048662 0.50096742 0.9911465 ]\n",
      " [0.9895627  0.302678   0.35080562 0.01896137 0.76797923 0.47637895\n",
      "  0.56938363 0.58619683 0.88918488 0.43967291]\n",
      " [0.16755754 0.3306307  0.07423814 0.80211453 0.82624134 0.27095382\n",
      "  0.72858867 0.96072816 0.35381668 0.65736482]\n",
      " [0.95666658 0.21993485 0.72122987 0.02012188 0.42705362 0.85128611\n",
      "  0.18255317 0.71344697 0.28163901 0.06312026]\n",
      " [0.03461069 0.00563209 0.83959218 0.18214835 0.77657772 0.61750035\n",
      "  0.11200859 0.25998406 0.67014275 0.40150892]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.100358\n",
      "INFO:__main__:Average Minimum Distance 1.11\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=2_multi_False\n",
      "INFO:__main__:(7500, 2)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.31555699 0.50875741 0.58778594 0.44730676]\n",
      " [0.59657004 0.48297545 0.51588743 0.34183222]\n",
      " [0.62457203 0.59094461 0.18784767 0.68528152]\n",
      " [0.49517698 0.58409534 0.54846703 0.68826771]\n",
      " [0.62596114 0.48627759 0.48834399 0.26612112]\n",
      " [0.39973381 0.30589637 0.45774555 0.83921871]\n",
      " [0.24408645 0.1990487  0.56791289 0.73232669]\n",
      " [0.32814319 0.19584402 0.60193042 0.55621961]\n",
      " [0.23318444 0.4141248  0.89188327 0.43941854]\n",
      " [0.35636085 0.07531152 0.64515438 0.7735253 ]\n",
      " [0.15627755 0.64567447 0.63911078 0.47624977]\n",
      " [0.09889589 0.06764415 0.78643561 0.84186832]\n",
      " [0.55940216 0.2322177  0.53940336 0.96227915]\n",
      " [0.65389411 0.44040388 0.60707963 0.68980357]\n",
      " [0.18290242 0.59129303 0.48992932 0.42219924]\n",
      " [0.54877088 0.32398421 0.71600632 0.82854813]\n",
      " [0.07758066 0.21078908 0.79218919 0.92606332]\n",
      " [0.60101129 0.67172676 0.84014339 0.49943531]\n",
      " [0.60767178 0.67321351 0.83009563 0.49173177]\n",
      " [0.02831519 0.04359359 0.96086051 0.60631857]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.347064\n",
      "INFO:__main__:Average Minimum Distance 0.64\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=1_multi_True\n",
      "INFO:__main__:(5000, 2)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.31665347 0.00989973]\n",
      " [0.62668481 0.01618597]\n",
      " [0.3048751  0.04604684]\n",
      " [0.58184389 0.10061105]\n",
      " [0.0730865  0.30829059]\n",
      " [0.57509692 0.30075184]\n",
      " [0.09721298 0.35560352]\n",
      " [0.21084439 0.24284071]\n",
      " [0.38608501 0.41598723]\n",
      " [0.21728548 0.21212641]\n",
      " [0.13076232 0.12840549]\n",
      " [0.16479039 0.34481289]\n",
      " [0.45641816 0.23548114]\n",
      " [0.06970282 0.23862874]\n",
      " [0.33084043 0.5163222 ]\n",
      " [0.23341594 0.55074123]\n",
      " [0.48482709 0.38448748]\n",
      " [0.151378   0.59341276]\n",
      " [0.02564248 0.69088277]\n",
      " [0.02384679 0.72321326]\n",
      " [0.14459687 0.67002088]\n",
      " [0.10772809 0.74715172]\n",
      " [0.07619826 0.81271384]\n",
      " [0.1306964  0.78202031]\n",
      " [0.58086985 0.45342353]\n",
      " [0.10732403 0.86841955]\n",
      " [0.30465054 0.89921101]\n",
      " [0.2856628  0.88805627]\n",
      " [0.39194176 0.73473164]\n",
      " [0.2989508  0.97673759]\n",
      " [0.32307733 0.96011007]\n",
      " [0.19385381 0.83083373]\n",
      " [0.14657268 0.98526856]\n",
      " [0.62702703 0.66699771]\n",
      " [0.42426115 0.85039325]\n",
      " [0.6235295  0.99992809]\n",
      " [0.54391431 0.95213828]\n",
      " [0.53118612 0.76848779]\n",
      " [0.99372473 0.69514319]\n",
      " [0.92371807 0.29769378]\n",
      " [0.95061201 0.95913103]\n",
      " [0.93858828 0.60182879]\n",
      " [0.20651485 0.090897  ]\n",
      " [0.93391734 0.1648135 ]\n",
      " [0.76287292 0.7076103 ]\n",
      " [0.18185041 0.13940526]\n",
      " [0.84549226 0.4966626 ]\n",
      " [0.99808167 0.43689439]\n",
      " [0.72107958 0.37676084]\n",
      " [0.96194452 0.04029839]]\n",
      "DEBUG:__main__:length of IOUs 150\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.422588\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.580025\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.665000\n",
      "INFO:__main__:Average Minimum Distance 0.41\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=4_multi_False\n",
      "INFO:__main__:(5000, 5)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.56681443 0.90775496 0.85105875 0.98823111 0.64231502 0.49210161\n",
      "  0.84772066 0.05698013]\n",
      " [0.0028903  0.52197885 0.83211707 0.59025969 0.35800008 0.70502574\n",
      "  0.15301925 0.9833616 ]\n",
      " [0.71740964 0.59918366 0.715448   0.186791   0.26459758 0.01093644\n",
      "  0.57896012 0.15986571]\n",
      " [0.42137818 0.34448318 0.72877266 0.25456187 0.18371579 0.33052803\n",
      "  0.76465203 0.94047281]\n",
      " [0.97195168 0.6216326  0.20999447 0.96050925 0.24226024 0.14054516\n",
      "  0.12810377 0.49284713]\n",
      " [0.52850799 0.91345789 0.17489751 0.01222704 0.97959565 0.01104115\n",
      "  0.21345823 0.66404852]\n",
      " [0.63945747 0.34021241 0.14529558 0.96184475 0.68803951 0.42883775\n",
      "  0.24170955 0.73673004]\n",
      " [0.81837399 0.29321317 0.99090593 0.70413483 0.02129796 0.53936547\n",
      "  0.940148   0.42487457]\n",
      " [0.98811894 0.39242551 0.6671577  0.60469051 0.32319321 0.81369401\n",
      "  0.04630065 0.0535485 ]\n",
      " [0.82269631 0.78336057 0.36972049 0.02663262 0.7947545  0.85285038\n",
      "  0.30187255 0.76844674]\n",
      " [0.19313029 0.78662862 0.62691018 0.91018905 0.93851718 0.04907891\n",
      "  0.26719766 0.75471261]\n",
      " [0.92439955 0.22177489 0.0180383  0.45098029 0.66538376 0.78746832\n",
      "  0.51399742 0.43415226]\n",
      " [0.21983894 0.5030838  0.61275991 0.78692843 0.67583747 0.40125961\n",
      "  0.52414729 0.96972072]\n",
      " [0.19522678 0.47553754 0.61860606 0.54483904 0.37008321 0.12301014\n",
      "  0.8776688  0.53919359]\n",
      " [0.81966725 0.71116908 0.36009462 0.06425094 0.67902803 0.81140442\n",
      "  0.90703411 0.03772357]\n",
      " [0.95988784 0.97318647 0.89306937 0.56242488 0.24064509 0.91707167\n",
      "  0.53332716 0.67373028]\n",
      " [0.64938585 0.92044386 0.36428595 0.40104991 0.60288579 0.22537833\n",
      "  0.92933073 0.47577653]\n",
      " [0.76880582 0.25906621 0.51911909 0.08926135 0.70052891 0.43619662\n",
      "  0.18860061 0.58405808]\n",
      " [0.086576   0.78300336 0.15990578 0.45877671 0.99581152 0.45011361\n",
      "  0.77641942 0.24750909]\n",
      " [0.53391277 0.7163105  0.50639568 0.5994379  0.54363337 0.2899813\n",
      "  0.79715186 0.50218757]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.074864\n",
      "INFO:__main__:Average Minimum Distance 0.91\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=4_multi_True\n",
      "INFO:__main__:(12500, 4)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[1.98879227e-01 5.71072514e-01 6.27323144e-01 4.49283020e-01\n",
      "  9.02554269e-01 3.14450051e-01 3.16303181e-01 8.24666400e-01]\n",
      " [3.14366914e-01 2.70631795e-01 2.40825208e-01 2.44781605e-01\n",
      "  1.23124455e-01 4.51948576e-01 9.13999054e-01 7.83621918e-01]\n",
      " [6.03838344e-01 2.08986752e-01 2.61961728e-01 6.13678180e-01\n",
      "  2.02799269e-01 7.42202834e-01 8.36916802e-01 7.92819146e-01]\n",
      " [1.76250663e-01 2.39700295e-01 1.14386743e-01 3.90715177e-01\n",
      "  9.11380865e-01 8.59137020e-01 6.71755627e-01 4.70201991e-01]\n",
      " [7.53825369e-03 8.62937748e-02 1.64235308e-01 1.44463437e-02\n",
      "  8.24399210e-01 3.89162248e-01 7.80663478e-01 8.90144244e-01]\n",
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      " [6.67441266e-01 4.26865502e-01 8.50770366e-01 8.93982367e-02\n",
      "  4.86855724e-01 3.30390257e-01 8.90391347e-01 7.08734339e-01]\n",
      " [9.39261507e-01 4.07491203e-02 7.60227375e-01 7.45611584e-01\n",
      "  6.75334998e-01 6.40529322e-01 9.15479626e-01 1.87079289e-01]\n",
      " [9.17325784e-03 8.21933080e-01 7.91407382e-01 6.62752970e-01\n",
      "  7.90417831e-01 5.03552184e-01 3.76043909e-01 3.82231351e-01]\n",
      " [8.38559415e-01 3.53949243e-01 5.15292831e-01 2.16797820e-01\n",
      "  6.42265670e-01 3.00974905e-01 6.66791020e-01 4.15357825e-01]\n",
      " [2.06201154e-01 2.65376111e-01 8.56552341e-01 2.72801149e-01\n",
      "  8.92924390e-01 8.44667993e-01 5.62026867e-01 9.24570770e-01]\n",
      " [2.27319781e-01 3.50390185e-01 5.47286107e-01 4.16614557e-01\n",
      "  7.12404557e-01 3.21895092e-01 9.71767355e-01 2.69315639e-01]\n",
      " [2.90755150e-01 4.26928324e-01 3.95004746e-01 7.21606168e-01\n",
      "  5.35221699e-01 7.98397171e-01 3.84679229e-01 1.19867065e-01]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.000647\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.029366\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.027167\n",
      "INFO:__main__:Average Minimum Distance 0.96\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=2_multi_True\n",
      "INFO:__main__:(5000, 3)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.35602772 0.38277029 0.15691839 0.12588838]\n",
      " [0.0526357  0.3136465  0.32787211 0.73139816]\n",
      " [0.58737445 0.19576893 0.88752702 0.14299735]\n",
      " [0.34827672 0.27239101 0.5851413  0.95667396]\n",
      " [0.9347325  0.78996157 0.68318621 0.04445248]\n",
      " [0.81397163 0.41092081 0.92334645 0.15691066]\n",
      " [0.24826431 0.65967602 0.79807287 0.23974362]\n",
      " [0.20471479 0.26656312 0.97729501 0.42145284]\n",
      " [0.4780136  0.43737888 0.40749797 0.10486378]\n",
      " [0.49331633 0.14650117 0.08312371 0.76785448]\n",
      " [0.55591869 0.9250315  0.998357   0.94770357]\n",
      " [0.03671598 0.21543178 0.24156429 0.42169595]\n",
      " [0.77319211 0.46084423 0.92123205 0.31987305]\n",
      " [0.09132194 0.25682413 0.3470557  0.44950288]\n",
      " [0.88037737 0.62794455 0.99043621 0.68538737]\n",
      " [0.94279411 0.32284242 0.45134892 0.69843158]\n",
      " [0.04498946 0.5355213  0.75702475 0.4503714 ]\n",
      " [0.671879   0.26702708 0.54791813 0.26513727]\n",
      " [0.93445946 0.30787594 0.52977804 0.02034404]\n",
      " [0.90499749 0.46318987 0.76273452 0.38088285]\n",
      " [0.3421115  0.72203381 0.40374834 0.04617136]\n",
      " [0.47245057 0.09331352 0.32614157 0.28654614]\n",
      " [0.73779348 0.52568078 0.17534154 0.73856374]\n",
      " [0.36011681 0.41878527 0.99861487 0.91741818]\n",
      " [0.21369491 0.07736444 0.12162888 0.12093331]\n",
      " [0.62024399 0.8622413  0.30314408 0.03974592]\n",
      " [0.05510399 0.83488643 0.57816822 0.49373417]\n",
      " [0.65240215 0.14938959 0.58839603 0.76482369]\n",
      " [0.42831559 0.846315   0.49752369 0.9361039 ]\n",
      " [0.48338639 0.09795245 0.13963081 0.38690243]\n",
      " [0.42286277 0.38212073 0.77060969 0.07894687]\n",
      " [0.20068919 0.96136453 0.75079474 0.9039319 ]\n",
      " [0.39736976 0.87664155 0.49116038 0.69676691]\n",
      " [0.70725442 0.32755938 0.31390098 0.69675356]\n",
      " [0.75583088 0.10786698 0.6450006  0.514494  ]\n",
      " [0.76642843 0.81719197 0.96714728 0.14901358]\n",
      " [0.44974223 0.52999029 0.58677473 0.67840634]\n",
      " [0.45056396 0.68407006 0.78033734 0.18588211]\n",
      " [0.86868251 0.55246977 0.06649991 0.44531501]\n",
      " [0.36724016 0.19315462 0.32608326 0.23334426]\n",
      " [0.6182978  0.11054263 0.6321326  0.90561418]\n",
      " [0.9086225  0.6709943  0.59666961 0.65443992]\n",
      " [0.09610972 0.35712007 0.0438021  0.96056   ]\n",
      " [0.41960094 0.71464252 0.02254662 0.69649043]\n",
      " [0.29302055 0.47590612 0.39109197 0.18583167]\n",
      " [0.69253265 0.09785513 0.86855627 0.26056927]\n",
      " [0.47298829 0.6054747  0.2521152  0.72764051]\n",
      " [0.21122936 0.74279213 0.37172674 0.52025228]\n",
      " [0.46116674 0.28857836 0.74060233 0.86462177]\n",
      " [0.94814767 0.97508087 0.97681113 0.51420062]\n",
      " [0.25922528 0.05309787 0.82537075 0.4683138 ]\n",
      " [0.81570157 0.49106152 0.16622174 0.22438378]\n",
      " [0.00186567 0.83295037 0.6321337  0.91400029]\n",
      " [0.97894887 0.26540367 0.65049837 0.26921621]\n",
      " [0.06087612 0.57622738 0.41499323 0.87870484]\n",
      " [0.10801797 0.41873115 0.23380454 0.64393705]\n",
      " [0.96026279 0.06516111 0.81816603 0.40414439]\n",
      " [0.28981006 0.47531062 0.50488422 0.62316895]\n",
      " [0.78751499 0.56583147 0.7775937  0.30698984]\n",
      " [0.65602095 0.73705231 0.78293674 0.12727707]\n",
      " [0.78595849 0.33466542 0.44405773 0.79652868]\n",
      " [0.68337859 0.42897737 0.75332458 0.78212679]\n",
      " [0.09715371 0.91100681 0.86558114 0.4591612 ]\n",
      " [0.08891633 0.09487684 0.3971537  0.5708625 ]\n",
      " [0.14193993 0.50895128 0.55321686 0.61188632]\n",
      " [0.14379439 0.13263212 0.73934805 0.81353058]\n",
      " [0.99289694 0.56084428 0.08697609 0.41704862]\n",
      " [0.68464331 0.42382919 0.66723149 0.36094899]\n",
      " [0.07521939 0.20906003 0.68505277 0.49784943]\n",
      " [0.49914828 0.79881481 0.02272574 0.44521579]\n",
      " [0.97175467 0.81967441 0.17490723 0.67507071]\n",
      " [0.50445489 0.64414148 0.2355883  0.49434938]\n",
      " [0.76873034 0.58012625 0.53872021 0.2153615 ]\n",
      " [0.65549215 0.28663467 0.94392531 0.15973738]\n",
      " [0.26645436 0.7252191  0.85664036 0.92413517]\n",
      " [0.31110579 0.74236491 0.98577803 0.54384028]\n",
      " [0.92876133 0.61634395 0.89348326 0.58209465]\n",
      " [0.8340557  0.03007418 0.62875911 0.38870654]\n",
      " [0.47672416 0.5079303  0.73956113 0.97864731]\n",
      " [0.91464857 0.53119198 0.81278255 0.86415596]\n",
      " [0.08393644 0.77647632 0.66423684 0.17477441]\n",
      " [0.95512384 0.88670075 0.50682283 0.60448951]\n",
      " [0.64608171 0.43091785 0.57294186 0.37426321]\n",
      " [0.42554664 0.90581493 0.28029227 0.34495535]\n",
      " [0.70937185 0.18025148 0.28434308 0.04982288]\n",
      " [0.62143284 0.91420432 0.5570416  0.73966425]\n",
      " [0.2065124  0.45699285 0.80974201 0.80264227]\n",
      " [0.41943685 0.15514431 0.26875441 0.1525458 ]\n",
      " [0.84290133 0.31743422 0.77828391 0.10977129]\n",
      " [0.46210744 0.35180053 0.80060951 0.44707898]\n",
      " [0.84645502 0.37477488 0.13990655 0.32119397]\n",
      " [0.10175938 0.27226106 0.17449664 0.70460864]\n",
      " [0.60154694 0.00632543 0.20878987 0.04127609]\n",
      " [0.44242525 0.76404948 0.23556901 0.71762873]\n",
      " [0.53210492 0.56096611 0.22513961 0.35855326]\n",
      " [0.09541091 0.86027332 0.568097   0.50864596]\n",
      " [0.89072443 0.64640748 0.55052428 0.91827795]\n",
      " [0.8052361  0.76991351 0.50736288 0.29479128]\n",
      " [0.76993161 0.2363279  0.35894085 0.92051205]\n",
      " [0.80365826 0.07197464 0.31441005 0.2963413 ]]\n",
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.045786\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.393639\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.352268\n",
      "INFO:__main__:Average Minimum Distance 0.64\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=3_multi_False\n",
      "INFO:__main__:(7500, 3)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.40614248 0.39317364 0.16046648 0.4364604  0.59107445 0.7548683 ]\n",
      " [0.33696596 0.52295999 0.66525727 0.95438016 0.51757147 0.33476678]\n",
      " [0.03462801 0.6062844  0.69688574 0.8458062  0.51134953 0.48031528]\n",
      " [0.54126451 0.76366377 0.27098599 0.62528687 0.312375   0.72831303]\n",
      " [0.27179414 0.35926023 0.0263275  0.79235595 0.6791016  0.74358288]\n",
      " [0.10119255 0.35613404 0.18549661 0.77080219 0.73372037 0.53813542]\n",
      " [0.35247549 0.6479448  0.51024978 0.76003057 0.59473484 0.80474712]\n",
      " [0.52618747 0.50797765 0.48356176 0.96779084 0.6303088  0.66579441]\n",
      " [0.52933079 0.30088601 0.62416983 0.50485229 0.88836338 0.87599877]\n",
      " [0.22674438 0.49474371 0.67338831 0.61870101 0.29135526 0.54967956]\n",
      " [0.37368354 0.58980142 0.12797678 0.50146873 0.99195719 0.69157808]\n",
      " [0.01879836 0.34137337 0.58972827 0.68746212 0.60648296 0.57741638]\n",
      " [0.13418207 0.27887404 0.74465192 0.65839999 0.80943445 0.20052173]\n",
      " [0.58385409 0.55444063 0.60857926 0.13645607 0.52145894 0.46586352]\n",
      " [0.2024755  0.21665079 0.34466462 0.90969245 0.52784618 0.92480142]\n",
      " [0.14754509 0.05011785 0.23623848 0.85625206 0.69143582 0.42622154]\n",
      " [0.73706994 0.41512888 0.6376003  0.86502298 0.50107965 0.22338504]\n",
      " [0.18508087 0.29750773 0.76542041 0.77788604 0.95170694 0.5399873 ]\n",
      " [0.51220452 0.21429916 0.73721821 0.80722045 0.6808881  0.78489943]\n",
      " [0.28718459 0.69334531 0.61089975 0.83894018 0.96312798 0.72283739]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.211930\n",
      "INFO:__main__:Average Minimum Distance 0.84\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=5_multi_True\n",
      "INFO:__main__:(12500, 5)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[4.06283742e-01 3.72643641e-01 5.25513579e-01 8.47848248e-02\n",
      "  5.75402866e-01 4.07472334e-01 5.30694072e-01 2.04691218e-01\n",
      "  7.16137038e-01 6.55314688e-01]\n",
      " [6.88583721e-01 5.79997100e-01 2.88288904e-01 3.62232388e-01\n",
      "  4.46240265e-01 8.04313662e-01 2.35097716e-01 4.72622679e-01\n",
      "  7.49432706e-01 4.78366807e-01]\n",
      " [1.84639499e-02 9.01996839e-02 3.39242827e-01 1.69667633e-01\n",
      "  6.75974472e-01 9.40192495e-01 8.11669459e-01 8.48160035e-01\n",
      "  8.29802672e-01 3.78669439e-01]\n",
      " [7.07905075e-01 4.19570470e-01 4.54298227e-01 3.07665774e-01\n",
      "  4.43987093e-01 4.97000586e-01 5.02660648e-01 8.43144963e-01\n",
      "  4.64471969e-01 5.98234451e-01]\n",
      " [6.88281331e-01 2.30683888e-01 7.00826168e-01 7.35340922e-01\n",
      "  4.77795109e-01 4.33385562e-01 5.74130280e-01 4.64766974e-01\n",
      "  3.40664473e-02 2.00753729e-01]\n",
      " [3.26943263e-01 4.98138658e-01 5.73565543e-01 4.99389919e-01\n",
      "  1.77455085e-01 7.69768000e-01 6.65229480e-01 2.04178900e-01\n",
      "  5.46697985e-01 4.40037162e-01]\n",
      " [7.55771870e-01 2.79488098e-01 9.56177869e-01 6.36909625e-01\n",
      "  3.65650647e-02 8.16291037e-01 3.68689319e-01 8.93392084e-01\n",
      "  3.62092365e-01 2.53935764e-01]\n",
      " [9.93663271e-01 3.50523159e-01 7.18604547e-01 5.44941443e-01\n",
      "  6.88072203e-02 6.22863422e-01 4.09898451e-01 7.08985373e-02\n",
      "  5.33806122e-01 2.51043081e-01]\n",
      " [2.00207375e-01 4.45436278e-01 5.50466206e-01 1.08000678e-01\n",
      "  5.36406653e-01 4.35188152e-01 7.27740095e-01 4.64487561e-01\n",
      "  7.15315502e-01 4.37307157e-01]\n",
      " [2.27453689e-01 3.91414466e-01 5.45822941e-01 7.32971864e-01\n",
      "  1.54203908e-01 6.32232464e-01 2.09090059e-01 6.35216334e-01\n",
      "  7.51537273e-01 1.00648116e-01]\n",
      " [6.48496897e-03 5.01070019e-01 9.98696072e-01 1.84738020e-01\n",
      "  3.46523153e-01 6.49270360e-01 3.77952649e-01 3.69128453e-01\n",
      "  3.50516176e-01 6.52319994e-01]\n",
      " [3.65062012e-01 1.92713175e-02 6.30718511e-01 9.49374758e-01\n",
      "  1.30868218e-01 5.30078933e-01 1.36948953e-01 9.53024679e-01\n",
      "  9.79647938e-02 7.57346557e-02]\n",
      " [6.35077092e-01 2.29452272e-01 5.63015966e-01 7.44682827e-01\n",
      "  3.32529882e-01 7.97264369e-01 2.48180727e-01 9.16606751e-01\n",
      "  9.77513087e-01 1.79552556e-01]\n",
      " [5.20468729e-01 1.72584976e-01 9.78480367e-01 5.04573890e-01\n",
      "  9.45518864e-01 3.10028753e-02 3.70351383e-01 2.11870896e-01\n",
      "  9.16766611e-01 6.19897561e-01]\n",
      " [9.28664871e-02 8.05963046e-01 2.90230583e-01 2.68288130e-01\n",
      "  6.32853557e-01 4.44854461e-01 3.54622999e-01 6.14154454e-01\n",
      "  1.68146445e-01 6.09697764e-01]\n",
      " [3.48699912e-01 3.25267512e-01 2.74727653e-01 6.06499986e-01\n",
      "  4.87831645e-01 9.44592834e-01 6.66263835e-01 3.77219249e-01\n",
      "  6.14290745e-01 9.04698389e-01]\n",
      " [5.44821476e-03 3.40047666e-01 8.91580540e-01 4.66604538e-02\n",
      "  5.64883763e-01 7.51098859e-01 2.67101180e-04 4.70643423e-01\n",
      "  3.19202093e-01 7.25146939e-01]\n",
      " [6.12731953e-01 6.40205724e-01 1.87390655e-03 7.19504790e-01\n",
      "  8.75215722e-01 5.98970772e-01 6.15840701e-01 7.11218745e-01\n",
      "  3.16706405e-01 6.68625276e-01]\n",
      " [9.97174034e-01 4.73989991e-01 4.38358072e-01 6.41726575e-01\n",
      "  1.27805039e-01 3.75463782e-01 9.04996368e-01 2.92400070e-01\n",
      "  7.99493476e-01 8.18957816e-01]\n",
      " [5.27404040e-01 3.63280249e-01 7.09548500e-02 7.16687851e-01\n",
      "  6.40692317e-01 2.79815984e-01 8.24637517e-01 8.56538034e-01\n",
      "  2.37264825e-01 2.39548815e-01]\n",
      " [1.23324723e-01 9.29029204e-01 2.42255032e-01 4.02384633e-04\n",
      "  9.89673820e-01 9.78370533e-01 3.50812057e-01 8.59379354e-01\n",
      "  5.30388403e-01 5.33081418e-01]\n",
      " [7.58469913e-01 7.28256195e-01 5.19233146e-01 5.03365895e-01\n",
      "  6.89615688e-01 3.05191108e-01 8.54898673e-01 8.44876033e-01\n",
      "  3.76387440e-01 4.68959840e-01]\n",
      " [2.53043962e-01 9.09240685e-01 1.69545017e-01 6.61284077e-01\n",
      "  2.35526214e-01 9.41320498e-01 6.77776202e-01 2.50051774e-01\n",
      "  1.01300264e-02 4.97550684e-01]\n",
      " [1.11925642e-01 3.48034067e-01 8.81669704e-01 9.01437176e-01\n",
      "  5.13128429e-01 3.67950062e-01 1.74475418e-01 6.94563333e-01\n",
      "  6.00776339e-01 9.61865758e-01]\n",
      " [6.51602521e-01 9.53613108e-01 6.89192386e-01 5.56070004e-01\n",
      "  1.83127955e-01 7.63728188e-01 8.39370922e-01 6.80168642e-01\n",
      "  3.98588034e-01 3.16316756e-01]\n",
      " [1.57692792e-01 1.04668623e-01 2.96821762e-02 6.05640529e-01\n",
      "  3.81281386e-02 6.61971831e-02 5.67872493e-01 8.26225918e-01\n",
      "  3.21093743e-01 8.47925779e-01]\n",
      " [1.82170543e-01 7.51984995e-01 8.01694672e-01 2.21151007e-01\n",
      "  4.42507857e-01 1.28891247e-01 6.24858259e-01 8.11559960e-01\n",
      "  5.41575383e-02 2.11093625e-02]\n",
      " [1.14171185e-01 8.53135526e-01 9.56656544e-01 8.89246379e-01\n",
      "  9.40784292e-01 8.49406703e-01 9.80624135e-01 3.95999448e-01\n",
      "  5.62645050e-01 9.09373803e-02]\n",
      " [2.72550065e-01 1.22250925e-01 1.46646414e-01 5.12846787e-02\n",
      "  1.58469664e-01 1.38147987e-01 5.40362245e-01 7.44667810e-01\n",
      "  3.86759175e-01 2.47098323e-01]\n",
      " [6.36519985e-01 4.10455545e-01 9.58477659e-02 3.31467149e-01\n",
      "  8.22593782e-01 2.38391818e-01 9.44266441e-01 5.29987550e-01\n",
      "  1.83991836e-01 1.08488850e-01]\n",
      " [6.19593759e-01 4.71439518e-01 9.32171855e-01 3.61510919e-01\n",
      "  9.75595969e-01 4.73898614e-01 8.31602669e-01 7.10545923e-01\n",
      "  5.67330356e-01 9.82647058e-01]\n",
      " [4.94545883e-01 1.33016297e-01 3.10694413e-01 2.20231018e-01\n",
      "  1.38787622e-01 4.68637182e-01 9.99952674e-01 1.85106811e-01\n",
      "  2.55510275e-01 7.48660931e-01]\n",
      " [7.75287288e-01 4.36407917e-01 5.77320235e-01 7.99572159e-01\n",
      "  4.01157079e-01 9.96511865e-01 6.11233166e-01 3.94885506e-01\n",
      "  2.06168267e-02 9.94825481e-01]\n",
      " [1.13167111e-01 1.01063809e-01 4.66133772e-01 1.15981001e-01\n",
      "  8.00118631e-01 2.79765856e-01 7.62444004e-01 6.46004070e-01\n",
      "  8.04020565e-01 6.65373834e-01]\n",
      " [6.36057158e-01 9.08620228e-01 2.69320016e-01 1.95821096e-01\n",
      "  1.05144464e-01 1.86747047e-01 7.33042311e-01 2.40488787e-01\n",
      "  4.67826734e-01 4.66915391e-01]\n",
      " [2.70048916e-01 9.73759831e-01 6.83406103e-01 8.73842399e-01\n",
      "  7.17633446e-01 9.86187500e-01 8.20310043e-01 6.81733544e-01\n",
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      "  7.10959210e-01 4.65645808e-01]\n",
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      "  1.81542487e-01 1.98878444e-01 5.81809588e-01 6.59157729e-01\n",
      "  2.30163167e-01 8.68234787e-01]\n",
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      "  4.13320151e-01 5.97218014e-01 8.59501149e-01 6.75301699e-01\n",
      "  6.52219435e-01 2.89529985e-01]\n",
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      "  7.57175183e-01 1.37645346e-01 9.77158389e-01 9.45679494e-01\n",
      "  2.06350035e-02 5.07851196e-01]\n",
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      "  8.44905183e-01 3.49593889e-01]\n",
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      "  6.94592680e-01 9.63107444e-01]\n",
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      "  2.52174770e-01 4.56815280e-01]\n",
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      "  9.30598235e-02 5.31574036e-01 6.66607120e-01 8.06966457e-02\n",
      "  4.79032113e-01 7.87789749e-01]\n",
      " [4.99712368e-01 7.62389516e-01 5.69000505e-01 7.82854252e-02\n",
      "  1.03953778e-01 8.92743713e-01 9.14442707e-01 2.13083864e-01\n",
      "  2.67068245e-01 2.61168554e-01]\n",
      " [3.66923815e-01 1.61292482e-01 2.76686737e-01 5.11168474e-01\n",
      "  4.91576981e-01 7.51491273e-02 8.71070338e-01 7.34716633e-01\n",
      "  7.78557742e-01 1.50004808e-02]\n",
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      "  9.11392206e-01 1.73475666e-01]\n",
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      "  6.60687326e-01 2.02652107e-02 7.66325836e-01 3.47669665e-01\n",
      "  2.95385397e-01 2.67072516e-01]\n",
      " [2.02138365e-01 7.32640584e-01 4.27957585e-01 2.87484907e-01\n",
      "  7.76691283e-02 5.93667081e-01 9.55653954e-01 7.93057721e-01\n",
      "  4.82871618e-01 2.95980814e-01]\n",
      " [6.19176332e-01 6.66118448e-01 6.41420628e-01 8.39427234e-01\n",
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      "  7.56133231e-01 5.39289588e-01]\n",
      " [9.18701414e-01 4.86266333e-01 5.48747608e-01 2.01380612e-01\n",
      "  2.99983415e-01 6.87285310e-01 3.20541569e-01 4.40234762e-01\n",
      "  6.85159967e-01 6.19149501e-01]\n",
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      "  7.88015244e-01 6.74019733e-01]\n",
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      "  1.75970748e-01 6.87369306e-02 7.02090743e-01 6.16055050e-01\n",
      "  2.98820851e-01 3.20909317e-01]\n",
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      "  6.79777247e-01 8.65041504e-01 5.79792815e-01 5.94490069e-01\n",
      "  7.06212211e-01 8.98245096e-01]\n",
      " [4.09292355e-01 8.20160570e-01 4.75710339e-01 3.99136209e-01\n",
      "  6.03393450e-01 1.26277803e-01 1.96497201e-01 3.78117121e-01\n",
      "  4.85930113e-01 5.70936773e-01]\n",
      " [9.15597133e-01 4.07754387e-01 9.33148991e-02 1.47672746e-01\n",
      "  3.07176323e-01 3.88345010e-01 8.81920864e-01 3.76373022e-01\n",
      "  5.74473006e-01 5.13342028e-01]\n",
      " [3.19336244e-01 7.40250833e-01 5.36909543e-01 2.61808176e-01\n",
      "  3.93050714e-01 9.03894122e-01 8.59382805e-01 7.54621350e-01\n",
      "  2.26647837e-01 5.50574855e-01]\n",
      " [1.83388953e-01 3.70623117e-01 2.02405568e-01 4.58731815e-01\n",
      "  6.12782470e-01 1.89976552e-01 4.11238125e-01 8.69481224e-01\n",
      "  6.63199613e-01 3.99069514e-01]\n",
      " [5.09236342e-01 1.04501594e-01 5.68770779e-01 7.37453580e-01\n",
      "  9.94292815e-01 8.15622901e-01 4.29539203e-01 8.75060610e-01\n",
      "  4.19670738e-01 8.28579964e-01]\n",
      " [4.13805306e-02 9.20962841e-01 2.59606065e-01 9.53273477e-01\n",
      "  1.04998296e-01 8.22854528e-01 8.14911448e-01 3.65539791e-01\n",
      "  2.21376586e-01 7.72103446e-02]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 300\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.011589\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.009975\n",
      "INFO:__main__:Average Minimum Distance 1.11\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_density_dimensions=4_multi_False\n",
      "INFO:__main__:(7500, 4)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.57991296 0.61960797 0.47061469 0.54013215 0.55734783 0.24658138\n",
      "  0.33141957 0.60099452]\n",
      " [0.56436875 0.33341693 0.52943246 0.44590046 0.46574807 0.59408642\n",
      "  0.51265659 0.28086688]\n",
      " [0.46095371 0.07968348 0.55242148 0.31106213 0.55017018 0.88316419\n",
      "  0.6037718  0.48778219]\n",
      " [0.5141264  0.53969559 0.51775939 0.52246697 0.5462433  0.26612743\n",
      "  0.98531328 0.83401871]\n",
      " [0.53294331 0.00721053 0.45652774 0.29033375 0.32080617 0.95282231\n",
      "  0.30820676 0.89662891]\n",
      " [0.22935185 0.54956715 0.64342316 0.38498537 0.75612793 0.84558922\n",
      "  0.75534842 0.54274325]\n",
      " [0.06795405 0.28080832 0.530422   0.0108737  0.95783519 0.55385181\n",
      "  0.76285459 0.93125849]\n",
      " [0.10175627 0.29724912 0.49751804 0.21895749 0.92720997 0.40645921\n",
      "  0.46542099 0.90648951]\n",
      " [0.50335217 0.39851381 0.63569314 0.00888066 0.63403091 0.31955227\n",
      "  0.33012343 0.94285691]\n",
      " [0.4938303  0.08873823 0.49704938 0.22889044 0.93748571 0.81234962\n",
      "  0.81857137 0.76871071]\n",
      " [0.35444364 0.29713211 0.47486388 0.71618259 0.46291027 0.98586466\n",
      "  0.74517091 0.76458903]\n",
      " [0.76514312 0.5097879  0.29869509 0.5607875  0.95424402 0.18917356\n",
      "  0.06747606 0.17051684]\n",
      " [0.63881296 0.24681755 0.88966763 0.02279672 0.59400806 0.30335436\n",
      "  0.70138531 0.73048411]\n",
      " [0.23668629 0.26309658 0.42266171 0.57873578 0.40710451 0.88775999\n",
      "  0.58130727 0.47745008]\n",
      " [0.08895425 0.68998827 0.22783286 0.39088885 0.42371423 0.16967277\n",
      "  0.49577795 0.9970478 ]\n",
      " [0.86942385 0.44579496 0.72684668 0.35906827 0.02120104 0.63637401\n",
      "  0.58370028 0.41766329]\n",
      " [0.75054618 0.96324962 0.84869689 0.08722732 0.6947236  0.69674121\n",
      "  0.99015281 0.42761787]\n",
      " [0.41877036 0.55055471 0.74132858 0.50381822 0.22720444 0.52459625\n",
      "  0.94650877 0.5600886 ]\n",
      " [0.33723788 0.50536813 0.98098502 0.5422637  0.50463028 0.67461474\n",
      "  0.22176004 0.18421228]\n",
      " [0.74371872 0.14675697 0.37243642 0.43858949 0.37833729 0.11210257\n",
      "  0.92624412 0.39662703]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.144678\n",
      "INFO:__main__:Average Minimum Distance 0.92\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:Loading file data_aggr_dimensions=3_multi_False\n",
      "INFO:__main__:(5000, 4)\n",
      "INFO:__main__:Starting Optimization\n",
      "DEBUG:__main__:Proposed [[0.5452378  0.60956834 0.64866514 0.3623173  0.85247829 0.48387941]\n",
      " [0.88281504 0.05329085 0.04135134 0.97599425 0.14263387 0.88439516]\n",
      " [0.19766151 0.5393341  0.93353453 0.55723251 0.30000089 0.67697789]\n",
      " [0.20550511 0.84432246 0.1775298  0.4885727  0.77779142 0.67175655]\n",
      " [0.74482521 0.33042891 0.22818957 0.66542326 0.43024235 0.4253713 ]\n",
      " [0.25457468 0.69212708 0.61106897 0.9138016  0.98028206 0.31168138]\n",
      " [0.56095922 0.22336098 0.0011934  0.12677824 0.79300877 0.90181565]\n",
      " [0.19304903 0.66534866 0.07241248 0.83259522 0.89009997 0.34926126]\n",
      " [0.95562813 0.88583212 0.71136221 0.35300953 0.34414665 0.97552072]\n",
      " [0.39774992 0.64567355 0.30939498 0.9163999  0.97567025 0.57673281]\n",
      " [0.0763889  0.75228914 0.90219819 0.50660348 0.50203075 0.10226439]\n",
      " [0.59656166 0.93162612 0.34265218 0.47536221 0.76158724 0.88565397]\n",
      " [0.78445441 0.2046907  0.92355328 0.55412472 0.51046597 0.19593216]\n",
      " [0.34440098 0.44109593 0.73035918 0.12855167 0.42765258 0.50733694]\n",
      " [0.53487091 0.9491906  0.68068783 0.40986197 0.73605414 0.66490612]\n",
      " [0.72674697 0.2586224  0.17907205 0.28311021 0.12958273 0.74778268]\n",
      " [0.00155225 0.52318686 0.73270639 0.41284611 0.4682857  0.04751821]\n",
      " [0.49208766 0.63733537 0.30682707 0.6268399  0.32571467 0.97676055]\n",
      " [0.74077132 0.30820758 0.5944308  0.67234755 0.83414473 0.89654663]\n",
      " [0.83812834 0.44740872 0.99925258 0.10791158 0.61605902 0.97842536]]\n",
      "DEBUG:__main__:length of IOUs 20\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.141688\n",
      "INFO:__main__:Average Minimum Distance 0.82\n",
      "INFO:__main__:Finished Run =======================================\n"
     ]
    }
   ],
   "source": [
    "directory = os.fsencode('input')\n",
    "naive_glow = []\n",
    "for file in os.listdir(directory):\n",
    "    filename = os.fsdecode(file)\n",
    "    if not filename.endswith(\".csv\") and filename.startswith(\"data\"):\n",
    "        a =filename.split('_')\n",
    "        t = a[1]\n",
    "        dims = int(a[2].split('=')[1])\n",
    "        multi = a[-1]==\"True\"\n",
    "        aggr= a[1]\n",
    "        #Check if query file has been generated and skip\n",
    "        logger.debug('Loading file {0}'.format(filename))\n",
    "        d = np.loadtxt('input/%s' % (filename) ,delimiter=',')\n",
    "        \n",
    "        d = d.reshape(-1,dims if aggr!='aggr' else dims+1)\n",
    "        logger.info(d.shape)\n",
    "        logger.info('Starting Optimization') \n",
    "        #Adapt number of glowworms and radius for dimensionality\n",
    "        g = int(50*(dims))\n",
    "        rad = (1-0.5**(1/g))**(1/dims)\n",
    "        if multi:\n",
    "            SUGGESTIONS=g #100\n",
    "        else:\n",
    "            SUGGESTIONS=g #20\n",
    "        if aggr!='aggr':\n",
    "            gw = GlowWorm(objective_density_naive, dimensions=2*dims,glowworms=g,iter_max=250,r0=rad)\n",
    "            gw.optimize()\n",
    "            ix_sort = np.argsort(np.array(list(map(lambda x: -objective_density_naive(x.reshape(1,-1)),gw.X))).reshape(g,))\n",
    "            proposed = gw.X[ix_sort,:][:SUGGESTIONS]\n",
    "            assert proposed.shape == (min(SUGGESTIONS,50*(dims)),2*dims)\n",
    "        else:\n",
    "            gw = GlowWorm(objective_aggr_naive, dimensions=2*dims,glowworms=g,iter_max=250,r0=rad)\n",
    "            gw.optimize()        \n",
    "            ix_sort = np.argsort(np.array(list(map(lambda x: -objective_aggr_naive(x.reshape(1,-1)),gw.X))).reshape(g,))\n",
    "            proposed = gw.X[ix_sort,:][:SUGGESTIONS]\n",
    "            assert proposed.shape == (min(SUGGESTIONS,50*(dims)),2*dims)\n",
    "        logger.debug('Proposed '+ np.array2string(proposed))\n",
    "        #Construct boxes or box and check IOU\n",
    "        #Multi-modal boxes regions are : [0,0.2]^d, [0.3,0.5]^d, [0.6,0.8]^d\n",
    "        #Single regions : [0.6,0.9]^d\n",
    "        boxes = compute_boxes(multi,dims)\n",
    "        iou_metric = compute_iou(boxes, proposed, multi,dims)\n",
    "        avg_min_dist = min_dist(boxes, proposed)\n",
    "        logger.info('Average Minimum Distance {:.2f}'.format(avg_min_dist))\n",
    "        logger.info('Finished Run =======================================')\n",
    "    naive_glow.append([dims,multi,aggr,'naive_glow', iou_metric ,avg_min_dist])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_df_naive_glow = pd.DataFrame(naive_glow, columns=['dimensions','multiple_regions','type of aggr', 'model', 'iou', 'avg_min_dist'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea545a36d8>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(121)\n",
    "sns.pointplot(x='dimensions', y='iou', data=eval_df_naive_glow, ax=ax)\n",
    "ax = fig.add_subplot(122)\n",
    "sns.pointplot(x='dimensions', y='avg_min_dist', data=eval_df_naive_glow, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Naive Method</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def naive_objective_density(X):\n",
    "    res = np.log(X[:,-1] - 1000) - 4*np.sum(np.log(1+X[:,X.shape[1]//2:X.shape[1]-1]))\n",
    "    res[np.isnan(res)] = -np.inf\n",
    "    return res\n",
    "def naive_objective_aggr(X):\n",
    "    res = np.log(X[:,-1] - 2) - 4*np.sum(np.log(1+X[:,X.shape[1]//2:X.shape[1]-1]))\n",
    "    res[np.isnan(res)] = -np.inf\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:queries-uniform-5-multi_True-density\n",
      "DEBUG:__main__:Proposed [[ 0.14635957  0.22110478  0.24259034  0.27470112  0.19990558  0.68107532\n",
      "   0.68107532  0.68107532  0.68107532  0.68107532]\n",
      " [ 0.14225574  0.25659157  0.29976499  0.25589146  0.20471911  0.65962711\n",
      "   0.65962711  0.65962711  0.65962711  0.65962711]\n",
      " [ 0.1321929   0.15265547  0.29099151  0.31698348  0.15939118  0.68157021\n",
      "   0.68157021  0.68157021  0.68157021  0.68157021]\n",
      " [-0.08034538 -0.10445049 -0.14900062 -0.12584046 -0.12646103  0.66600669\n",
      "   0.66600669  0.66600669  0.66600669  0.66600669]\n",
      " [ 0.2985861   0.101992    0.1853636   0.12378225  0.29591551  0.66634589\n",
      "   0.66634589  0.66634589  0.66634589  0.66634589]\n",
      " [ 0.26634186  0.21490286  0.32627021  0.2137244   0.21558102  0.62026601\n",
      "   0.62026601  0.62026601  0.62026601  0.62026601]\n",
      " [ 0.09013018  0.13989449  0.27705663  0.27847162  0.17377982  0.65746472\n",
      "   0.65746472  0.65746472  0.65746472  0.65746472]\n",
      " [ 0.18601002  0.18582052  0.13456278  0.33706248  0.28004334  0.64371041\n",
      "   0.64371041  0.64371041  0.64371041  0.64371041]\n",
      " [ 0.18389833  0.23304959  0.11546418  0.09261549  0.29475664  0.6612773\n",
      "   0.6612773   0.6612773   0.6612773   0.6612773 ]\n",
      " [ 0.33367561  0.12476273  0.35502601  0.28646148  0.14184424  0.67525479\n",
      "   0.67525479  0.67525479  0.67525479  0.67525479]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.002442\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.003026\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.003485\n",
      "INFO:__main__:Average Minimum Distance 1.06\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-3-multi_False-aggr\n",
      "DEBUG:__main__:Proposed [[ 0.55691438  0.51483979  0.58256725  0.34736853  0.34736853  0.34736853]\n",
      " [ 0.86811055  0.99244554 -0.20969883  0.48061949  0.48061949  0.48061949]\n",
      " [ 0.60752645  0.45485317  0.59930796  0.31934845  0.31934845  0.31934845]\n",
      " [ 0.56133788  0.64945439  0.58863609  0.3581327   0.3581327   0.3581327 ]\n",
      " [ 0.60422581  0.53515426  0.78956391  0.31783558  0.31783558  0.31783558]\n",
      " [ 0.56978066  0.5761537   0.47741584  0.33204423  0.33204423  0.33204423]\n",
      " [ 0.12795717  0.98027486  0.92126564  0.44223839  0.44223839  0.44223839]\n",
      " [-0.14762586  0.99103385  0.78427726  0.34066012  0.34066012  0.34066012]\n",
      " [ 0.59520988  0.65328363  0.69619906  0.35411104  0.35411104  0.35411104]\n",
      " [ 0.5418423   0.47639452  0.55670217  0.31484766  0.31484766  0.31484766]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.520755\n",
      "INFO:__main__:Average Minimum Distance 0.36\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-3-multi_True-aggr\n",
      "DEBUG:__main__:Proposed [[-0.37813595 -0.37359982 -0.13512357  0.40683649  0.40683649  0.40683649]\n",
      " [-0.50367201 -0.51408414  0.06188308  0.53007974  0.53007974  0.53007974]\n",
      " [-0.29656155 -0.23348421 -0.23237556  0.32010826  0.32010826  0.32010826]\n",
      " [-0.41044012 -0.19658533 -0.25900952  0.43082731  0.43082731  0.43082731]\n",
      " [-0.38562695  0.07715594 -0.2854697   0.39686933  0.39686933  0.39686933]\n",
      " [-0.1386972  -0.11936224 -0.2694477   0.31699603  0.31699603  0.31699603]\n",
      " [-0.25978856 -0.33857644 -0.1300317   0.39133678  0.39133678  0.39133678]\n",
      " [-0.1062398  -0.09768345 -0.27559832  0.32214725  0.32214725  0.32214725]\n",
      " [-0.23016024 -0.41182891 -0.33587416  0.44447136  0.44447136  0.44447136]\n",
      " [-0.22326311 -0.25573785 -0.13702461  0.41803562  0.41803562  0.41803562]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.084600\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.000000\n",
      "INFO:__main__:Average Minimum Distance 0.59\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-1-multi_False-density\n",
      "DEBUG:__main__:Proposed [[0.59824551 0.14825429]\n",
      " [0.64595614 0.14631621]\n",
      " [0.63804493 0.14425509]\n",
      " [0.61379349 0.14364601]\n",
      " [0.62036729 0.12872843]\n",
      " [0.61964457 0.12730273]\n",
      " [0.67963905 0.12756731]\n",
      " [0.79130894 0.13125449]\n",
      " [0.75379988 0.11859159]\n",
      " [0.77596409 0.11390694]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.487721\n",
      "INFO:__main__:Average Minimum Distance 0.19\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-5-multi_False-aggr\n",
      "DEBUG:__main__:Proposed [[ 0.74586208  0.74981811  0.75159413  0.84425204  0.83212718  0.5459864\n",
      "   0.5459864   0.5459864   0.5459864   0.5459864 ]\n",
      " [ 0.65731033  0.74704869  0.68631743  0.82703036  0.77702965  0.61486525\n",
      "   0.61486525  0.61486525  0.61486525  0.61486525]\n",
      " [ 0.83976654  0.68212376  0.73211611  0.8410999   0.84230892  0.62519852\n",
      "   0.62519852  0.62519852  0.62519852  0.62519852]\n",
      " [ 0.7799493   0.8469198   0.64648863  0.84551959  0.60004035  0.61216299\n",
      "   0.61216299  0.61216299  0.61216299  0.61216299]\n",
      " [ 0.21459032  0.98634013 -0.38335658  0.22929307 -0.35262795  0.60905298\n",
      "   0.60905298  0.60905298  0.60905298  0.60905298]\n",
      " [ 0.11068304  0.98602251 -0.09874644  0.24155756 -0.08293901  0.57686207\n",
      "   0.57686207  0.57686207  0.57686207  0.57686207]\n",
      " [-0.47841366  0.5627995   0.43737566 -0.48719678  0.59761673  0.55347363\n",
      "   0.55347363  0.55347363  0.55347363  0.55347363]\n",
      " [ 0.83549149 -0.49922442  0.76760816 -0.50423655  0.22685031  0.56699298\n",
      "   0.56699298  0.56699298  0.56699298  0.56699298]\n",
      " [ 0.79126335  0.75740857  0.77092565  0.81080418  0.64069908  0.52250928\n",
      "   0.52250928  0.52250928  0.52250928  0.52250928]\n",
      " [-0.28429079  0.92184582  0.94626432 -0.23310085  0.40050329  0.57765706\n",
      "   0.57765706  0.57765706  0.57765706  0.57765706]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.001120\n",
      "INFO:__main__:Average Minimum Distance 1.16\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-2-multi_False-aggr\n",
      "DEBUG:__main__:Proposed [[0.6682112  0.6983873  0.20016447 0.20016447]\n",
      " [0.62053148 0.60458502 0.23777416 0.23777416]\n",
      " [0.59242873 0.60261894 0.27666801 0.27666801]\n",
      " [0.59493843 0.6108892  0.26531962 0.26531962]\n",
      " [0.68201671 0.6471557  0.22428832 0.22428832]\n",
      " [0.64681428 0.58741209 0.2700963  0.2700963 ]\n",
      " [0.631633   0.57658102 0.23159636 0.23159636]\n",
      " [0.57430522 0.6010668  0.20462224 0.20462224]\n",
      " [0.73085954 0.58464156 0.18703305 0.18703305]\n",
      " [0.6478266  0.70389709 0.25545853 0.25545853]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.808412\n",
      "INFO:__main__:Average Minimum Distance 0.11\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-5-multi_False-density\n",
      "DEBUG:__main__:Proposed [[0.27930291 0.3935273  0.3289541  0.31611418 0.26228147 0.66657181\n",
      "  0.66657181 0.66657181 0.66657181 0.66657181]\n",
      " [0.24439323 0.31107238 0.39070409 0.24092184 0.36807704 0.67370352\n",
      "  0.67370352 0.67370352 0.67370352 0.67370352]\n",
      " [0.27765798 0.23437032 0.49518357 0.25351593 0.31502824 0.68088232\n",
      "  0.68088232 0.68088232 0.68088232 0.68088232]\n",
      " [0.33179166 0.36505123 0.34423435 0.37345764 0.25746158 0.65966513\n",
      "  0.65966513 0.65966513 0.65966513 0.65966513]\n",
      " [0.30392933 0.33746352 0.29095669 0.38844142 0.26601272 0.65444731\n",
      "  0.65444731 0.65444731 0.65444731 0.65444731]\n",
      " [0.41668921 0.33266994 0.3118373  0.24244307 0.34041104 0.65687788\n",
      "  0.65687788 0.65687788 0.65687788 0.65687788]\n",
      " [0.24034272 0.23641073 0.27491305 0.54430517 0.30651458 0.67855877\n",
      "  0.67855877 0.67855877 0.67855877 0.67855877]\n",
      " [0.2754978  0.33501555 0.3871478  0.4592801  0.29883977 0.67598276\n",
      "  0.67598276 0.67598276 0.67598276 0.67598276]\n",
      " [0.39672452 0.36847129 0.318496   0.31075307 0.41919733 0.65321826\n",
      "  0.65321826 0.65321826 0.65321826 0.65321826]\n",
      " [0.27413586 0.46911191 0.23914354 0.45860145 0.33997799 0.68177613\n",
      "  0.68177613 0.68177613 0.68177613 0.68177613]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.020432\n",
      "INFO:__main__:Average Minimum Distance 1.03\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-4-multi_True-density\n",
      "DEBUG:__main__:Proposed [[ 0.2672114   0.29312246  0.28893574  0.21861454  0.55719346  0.55719346\n",
      "   0.55719346  0.55719346]\n",
      " [-0.03682385  0.02661132 -0.01205364  0.00066636  0.55491652  0.55491652\n",
      "   0.55491652  0.55491652]\n",
      " [ 0.20231388  0.11158432  0.19220335  0.29556387  0.6141167   0.6141167\n",
      "   0.6141167   0.6141167 ]\n",
      " [-0.0798869  -0.11465813 -0.04041474 -0.02325076  0.57169768  0.57169768\n",
      "   0.57169768  0.57169768]\n",
      " [ 0.33995017  0.31691247  0.28731822  0.21189951  0.57485154  0.57485154\n",
      "   0.57485154  0.57485154]\n",
      " [ 0.31018023  0.2670526   0.30516774  0.33020587  0.51732759  0.51732759\n",
      "   0.51732759  0.51732759]\n",
      " [ 0.35930872  0.16827433  0.25058707  0.16565677  0.61751764  0.61751764\n",
      "   0.61751764  0.61751764]\n",
      " [ 0.26593422  0.17207555  0.37489839  0.23168351  0.61408912  0.61408912\n",
      "   0.61408912  0.61408912]\n",
      " [-0.1289001   0.02588434 -0.01509062  0.00687198  0.59090435  0.59090435\n",
      "   0.59090435  0.59090435]\n",
      " [ 0.0210241  -0.14212495 -0.02434143 -0.07366233  0.59171943  0.59171943\n",
      "   0.59171943  0.59171943]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.014978\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.017451\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.020558\n",
      "INFO:__main__:Average Minimum Distance 0.77\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-2-multi_False-density\n",
      "DEBUG:__main__:Proposed [[0.53726387 0.50913501 0.38235025 0.38235025]\n",
      " [0.59433418 0.53684991 0.35966487 0.35966487]\n",
      " [0.51977686 0.5805775  0.36662366 0.36662366]\n",
      " [0.58869621 0.59989546 0.30106554 0.30106554]\n",
      " [0.56920251 0.59109383 0.3145559  0.3145559 ]\n",
      " [0.53256627 0.63852955 0.35079516 0.35079516]\n",
      " [0.50009683 0.50874029 0.35911806 0.35911806]\n",
      " [0.60647846 0.47868328 0.35408644 0.35408644]\n",
      " [0.49692451 0.58852325 0.33656007 0.33656007]\n",
      " [0.62006562 0.65789805 0.33285266 0.33285266]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.927614\n",
      "INFO:__main__:Average Minimum Distance 0.10\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-1-multi_True-density\n",
      "DEBUG:__main__:Proposed [[0.06256774 0.14905357]\n",
      " [0.07696407 0.139028  ]\n",
      " [0.04367143 0.12565917]\n",
      " [0.02268585 0.1261903 ]\n",
      " [0.00741877 0.12590827]\n",
      " [0.60460031 0.12545544]\n",
      " [0.37765602 0.13094714]\n",
      " [0.28409642 0.13491376]\n",
      " [0.36917921 0.12424183]\n",
      " [0.35467482 0.12439464]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.649425\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.621973\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.627277\n",
      "INFO:__main__:Average Minimum Distance 0.09\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-1-multi_True-aggr\n",
      "DEBUG:__main__:Proposed [[0.33768978 0.03906357]\n",
      " [0.15483106 0.03508952]\n",
      " [0.39910126 0.03850111]\n",
      " [0.3999134  0.05612712]\n",
      " [0.33324488 0.10165116]\n",
      " [0.62744838 0.06904672]\n",
      " [0.62843153 0.06771697]\n",
      " [0.60151655 0.08078135]\n",
      " [0.32249198 0.09576304]\n",
      " [0.3411014  0.08623635]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.175448\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.508256\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.403907\n",
      "INFO:__main__:Average Minimum Distance 0.15\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-4-multi_False-density\n",
      "DEBUG:__main__:Proposed [[0.33288531 0.31452173 0.37512896 0.48265496 0.60667251 0.60667251\n",
      "  0.60667251 0.60667251]\n",
      " [0.29361298 0.30576378 0.5226364  0.38743524 0.60840573 0.60840573\n",
      "  0.60840573 0.60840573]\n",
      " [0.39356747 0.47907521 0.32785933 0.34200387 0.5750155  0.5750155\n",
      "  0.5750155  0.5750155 ]\n",
      " [0.3989995  0.56665058 0.4420375  0.31800187 0.60981794 0.60981794\n",
      "  0.60981794 0.60981794]\n",
      " [0.42380981 0.51583406 0.46341779 0.37691675 0.60304813 0.60304813\n",
      "  0.60304813 0.60304813]\n",
      " [0.44565401 0.37868305 0.3348447  0.5069492  0.59926983 0.59926983\n",
      "  0.59926983 0.59926983]\n",
      " [0.33987155 0.37136337 0.54826716 0.42859852 0.58123344 0.58123344\n",
      "  0.58123344 0.58123344]\n",
      " [0.49170599 0.29714151 0.31779651 0.31001249 0.59333309 0.59333309\n",
      "  0.59333309 0.59333309]\n",
      " [0.47811657 0.49228827 0.4031833  0.45498599 0.60171431 0.60171431\n",
      "  0.60171431 0.60171431]\n",
      " [0.54450674 0.30876515 0.35104579 0.49104122 0.61277544 0.61277544\n",
      "  0.61277544 0.61277544]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.074091\n",
      "INFO:__main__:Average Minimum Distance 0.73\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-2-multi_True-aggr\n",
      "DEBUG:__main__:Proposed [[-0.06269705 -0.18495982  0.19288403  0.19288403]\n",
      " [-0.1396879  -0.06578025  0.2578441   0.2578441 ]\n",
      " [-0.17595896 -0.16918948  0.34337756  0.34337756]\n",
      " [-0.12245063 -0.15117659  0.2907368   0.2907368 ]\n",
      " [-0.24844978 -0.11078754  0.2966484   0.2966484 ]\n",
      " [-0.01018145 -0.04509237  0.17801491  0.17801491]\n",
      " [-0.14971506 -0.08444095  0.19939479  0.19939479]\n",
      " [-0.14454637 -0.1050193   0.31315781  0.31315781]\n",
      " [-0.12723379 -0.34965578  0.37373341  0.37373341]\n",
      " [ 0.29462258  0.34713348  0.17989726  0.17989726]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.451775\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.583963\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.000000\n",
      "INFO:__main__:Average Minimum Distance 0.22\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-4-multi_True-aggr\n",
      "DEBUG:__main__:Proposed [[ 0.68969191 -0.53292017  0.21311698 -0.39524283  0.54295517  0.54295517\n",
      "   0.54295517  0.54295517]\n",
      " [-0.20843106 -0.19127064 -0.42054902  0.13776275  0.44869418  0.44869418\n",
      "   0.44869418  0.44869418]\n",
      " [ 0.97877071  0.37159146 -0.46249035 -0.51748218  0.59855834  0.59855834\n",
      "   0.59855834  0.59855834]\n",
      " [ 0.37848063  0.12706977 -0.49294364  0.97471579  0.54429782  0.54429782\n",
      "   0.54429782  0.54429782]\n",
      " [ 0.46999431  0.12136418 -0.54128285  0.98218185  0.58621609  0.58621609\n",
      "   0.58621609  0.58621609]\n",
      " [ 0.9478167   0.32258873  0.96153076 -0.43317478  0.49105781  0.49105781\n",
      "   0.49105781  0.49105781]\n",
      " [ 0.94393511  0.40398921  0.89678401 -0.52678592  0.54863601  0.54863601\n",
      "   0.54863601  0.54863601]\n",
      " [ 0.93935331 -0.23483475  0.83961825  0.88536421  0.4784788   0.4784788\n",
      "   0.4784788   0.4784788 ]\n",
      " [ 0.9456586  -0.1747586   0.80896033  0.94291471  0.57319546  0.57319546\n",
      "   0.57319546  0.57319546]\n",
      " [ 0.34241916  0.1783979  -0.33187635  0.95053282  0.42467774  0.42467774\n",
      "   0.42467774  0.42467774]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.001666\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.000000\n",
      "INFO:__main__:Average Minimum Distance 1.21\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-3-multi_False-density\n",
      "DEBUG:__main__:Proposed [[0.43661408 0.37508307 0.47698362 0.52323114 0.52323114 0.52323114]\n",
      " [0.49678903 0.51495242 0.39314386 0.527118   0.527118   0.527118  ]\n",
      " [0.44843487 0.40071209 0.54220834 0.52541844 0.52541844 0.52541844]\n",
      " [0.49627036 0.55177228 0.49398703 0.51354672 0.51354672 0.51354672]\n",
      " [0.49835879 0.39992256 0.59209624 0.50273116 0.50273116 0.50273116]\n",
      " [0.49397722 0.40398275 0.40737414 0.48875136 0.48875136 0.48875136]\n",
      " [0.52324584 0.44473845 0.52286139 0.46765219 0.46765219 0.46765219]\n",
      " [0.34177448 0.42532214 0.48629229 0.53037115 0.53037115 0.53037115]\n",
      " [0.51208142 0.57036617 0.4352297  0.46890694 0.46890694 0.46890694]\n",
      " [0.57281519 0.44197951 0.49831856 0.46316089 0.46316089 0.46316089]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.271749\n",
      "INFO:__main__:Average Minimum Distance 0.42\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-3-multi_True-density\n",
      "DEBUG:__main__:Proposed [[ 0.2725233   0.35798272  0.27072457  0.51895429  0.51895429  0.51895429]\n",
      " [ 0.3079659   0.38262421  0.290682    0.52859047  0.52859047  0.52859047]\n",
      " [ 0.20647638  0.30486558  0.35227426  0.52737717  0.52737717  0.52737717]\n",
      " [ 0.24856791  0.33404537  0.35617705  0.51331756  0.51331756  0.51331756]\n",
      " [ 0.21412433  0.3045126   0.27378098  0.48896237  0.48896237  0.48896237]\n",
      " [ 0.0119742   0.01463404  0.04349512  0.45889634  0.45889634  0.45889634]\n",
      " [ 0.35630983  0.33997832  0.38576658  0.48859008  0.48859008  0.48859008]\n",
      " [ 0.20069263  0.21199657  0.25970433  0.50709864  0.50709864  0.50709864]\n",
      " [-0.02749176  0.12467114  0.07303838  0.53108138  0.53108138  0.53108138]\n",
      " [-0.01202621  0.0668062   0.08994349  0.49206763  0.49206763  0.49206763]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.054997\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.066786\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.068589\n",
      "INFO:__main__:Average Minimum Distance 0.54\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-2-multi_True-density\n",
      "DEBUG:__main__:Proposed [[0.12748861 0.17338493 0.3747063  0.3747063 ]\n",
      " [0.44093195 0.43915643 0.35867625 0.35867625]\n",
      " [0.60201303 0.46463182 0.38644686 0.38644686]\n",
      " [0.54855196 0.43211769 0.3706453  0.3706453 ]\n",
      " [0.56194703 0.44108009 0.3661283  0.3661283 ]\n",
      " [0.57931135 0.60223975 0.37736701 0.37736701]\n",
      " [0.42926968 0.52933638 0.36350563 0.36350563]\n",
      " [0.23882199 0.28455944 0.32294539 0.32294539]\n",
      " [0.30976821 0.31458431 0.34614035 0.34614035]\n",
      " [0.50254263 0.53279305 0.31738923 0.31738923]]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.010813\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.383532\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.397078\n",
      "INFO:__main__:Average Minimum Distance 0.27\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-1-multi_False-aggr\n",
      "DEBUG:__main__:Proposed [[0.70631112 0.03899378]\n",
      " [0.81223465 0.05543381]\n",
      " [0.81538211 0.04601409]\n",
      " [0.65936403 0.09541617]\n",
      " [0.79893399 0.08231406]\n",
      " [0.71746151 0.05677274]\n",
      " [0.69620344 0.09827685]\n",
      " [0.65659085 0.10845128]\n",
      " [0.72183018 0.07200903]\n",
      " [0.64999717 0.06187349]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.361504\n",
      "INFO:__main__:Average Minimum Distance 0.26\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-5-multi_True-aggr\n",
      "DEBUG:__main__:Proposed [[ 0.27300124  0.90154413  0.69365484 -0.43923839  0.12808513  0.54089198\n",
      "   0.54089198  0.54089198  0.54089198  0.54089198]\n",
      " [-0.36273958  0.87806337  0.91490513  0.04319764 -0.24153092  0.56665419\n",
      "   0.56665419  0.56665419  0.56665419  0.56665419]\n",
      " [ 0.97268408  0.90624848  0.71484618 -0.08540314  0.1026581   0.51784498\n",
      "   0.51784498  0.51784498  0.51784498  0.51784498]\n",
      " [ 0.96842979  0.83381609  0.61404541 -0.35232365 -0.52848508  0.67258743\n",
      "   0.67258743  0.67258743  0.67258743  0.67258743]\n",
      " [-0.53605685 -0.181465    0.82762048  0.76976818  0.52865555  0.56147539\n",
      "   0.56147539  0.56147539  0.56147539  0.56147539]\n",
      " [-0.48353539  0.18361003  0.83766311  0.83561958  0.46623658  0.50052381\n",
      "   0.50052381  0.50052381  0.50052381  0.50052381]\n",
      " [-0.55728905  0.04251942  0.69981124  0.86553629  0.31812569  0.57047273\n",
      "   0.57047273  0.57047273  0.57047273  0.57047273]\n",
      " [ 0.20413125  0.23211617  0.63707289  0.22166306  0.97663874  0.52972653\n",
      "   0.52972653  0.52972653  0.52972653  0.52972653]\n",
      " [-0.38076628 -0.02655907  0.84847112  0.21553931  0.98408571  0.58808\n",
      "   0.58808     0.58808     0.58808     0.58808   ]\n",
      " [-0.30626661 -0.22619494  0.85621019  0.20450656  0.96092991  0.52307497\n",
      "   0.52307497  0.52307497  0.52307497  0.52307497]]\n",
      "DEBUG:__main__:length of IOUs 30\n",
      "INFO:__main__:Maximum IOU for box 1 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 2 is : 0.000000\n",
      "INFO:__main__:Maximum IOU for box 3 is : 0.000000\n",
      "INFO:__main__:Average Minimum Distance 1.38\n",
      "INFO:__main__:Finished Run =======================================\n",
      "DEBUG:__main__:queries-uniform-4-multi_False-aggr\n",
      "DEBUG:__main__:Proposed [[ 0.93218518 -0.0325577   0.97584813  0.01513983  0.58093859  0.58093859\n",
      "   0.58093859  0.58093859]\n",
      " [ 0.01181869  0.97886234  0.91345621  0.37083289  0.47093554  0.47093554\n",
      "   0.47093554  0.47093554]\n",
      " [ 0.29230731  0.98558926  0.8425065  -0.38023206  0.56517477  0.56517477\n",
      "   0.56517477  0.56517477]\n",
      " [ 0.25834778  0.97513635  0.81833607 -0.36338459  0.55940509  0.55940509\n",
      "   0.55940509  0.55940509]\n",
      " [ 0.18398621  0.98625718  0.54742035 -0.52904928  0.58291275  0.58291275\n",
      "   0.58291275  0.58291275]\n",
      " [ 0.31798794  0.97316176  0.79120925 -0.49798043  0.55194171  0.55194171\n",
      "   0.55194171  0.55194171]\n",
      " [ 0.42165817  0.99788125  0.40656824 -0.2556753   0.5777464   0.5777464\n",
      "   0.5777464   0.5777464 ]\n",
      " [ 0.99191637  0.09416184 -0.43011438  0.20543679  0.52765298  0.52765298\n",
      "   0.52765298  0.52765298]\n",
      " [-0.28875613  1.31767001  1.53937053  0.79257514  0.61519519  0.61519519\n",
      "   0.61519519  0.61519519]\n",
      " [ 0.75717483 -0.11560848  0.27823567 -0.24271208  0.51973922  0.51973922\n",
      "   0.51973922  0.51973922]]\n",
      "DEBUG:__main__:length of IOUs 10\n",
      "INFO:__main__:Maximum IOU of proposed boxes 0.000000\n",
      "INFO:__main__:Average Minimum Distance 1.25\n",
      "INFO:__main__:Finished Run =======================================\n"
     ]
    }
   ],
   "source": [
    "naive_details = []\n",
    "directory = os.fsencode('input/queries')\n",
    "for file in os.listdir(directory):\n",
    "    filename = os.fsdecode(file)\n",
    "    if filename.startswith('queries'):\n",
    "        a = filename.split('-')\n",
    "        dims = int(int(a[2]))\n",
    "        multi = a[3].split('_')[1]==\"True\"\n",
    "        aggr = a[4]\n",
    "        m = None\n",
    "        f = np.loadtxt('input/queries/%s' % (filename) ,delimiter=',')\n",
    "        logger.debug(filename)\n",
    "        if multi:\n",
    "            SUGGESTIONS=f.shape[0]#100\n",
    "        else:\n",
    "            SUGGESTIONS=f.shape[0]#20\n",
    "        if aggr=='aggr':\n",
    "            proposed = f[np.argsort(naive_objective_aggr(f))[::-1][:SUGGESTIONS],:f.shape[1]-1]\n",
    "        else:\n",
    "            proposed = f[np.argsort(naive_objective_density(f))[::-1][:SUGGESTIONS],:f.shape[1]-1]\n",
    "        assert proposed.shape[1]==2*dims and proposed.shape[0]==10\n",
    "            \n",
    "        logger.debug('Proposed '+ np.array2string(proposed))\n",
    "        #Construct boxes or box and check IOU\n",
    "        #Multi-modal boxes regions are : [0,0.2]^d, [0.3,0.5]^d, [0.6,0.8]^d\n",
    "        #Single regions : [0.6,0.9]^d\n",
    "        boxes = compute_boxes(multi,dims)\n",
    "        iou_metric = compute_iou(boxes, proposed, multi, dims)\n",
    "        avg_min_dist = min_dist(boxes, proposed)\n",
    "        logger.info('Average Minimum Distance {:.2f}'.format(avg_min_dist))\n",
    "        logger.info('Finished Run =======================================')\n",
    "        naive_details.append([dims,multi,aggr,'naive_obj', iou_metric ,avg_min_dist])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "eval_df_naive = pd.DataFrame(naive_details, columns=['dimensions','multiple_regions','type of aggr', 'model', 'iou', 'avg_min_dist'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea89300eb8>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(121)\n",
    "sns.pointplot(x='dimensions', y='iou', data=eval_df_naive, ax=ax)\n",
    "ax = fig.add_subplot(122)\n",
    "sns.pointplot(x='dimensions', y='avg_min_dist', data=eval_df_naive, ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea894a0358>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='type of aggr',y='iou', hue='multiple_regions',data=eval_df_naive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fea53a49780>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='dimensions',y='iou',hue='type of aggr', data=eval_df_naive)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Comparison All</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_df = pd.concat([eval_df,eval_df_naive,eval_df_prim, eval_df_naive_glow],ignore_index=True,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_df = total_df.replace(np.nan, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import datetime\n",
    "# now = datetime.datetime.now()\n",
    "# total_df.to_csv('output/synthetic_accuracy{0}.csv'.format(str(now)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# total_df = pd.read_csv('output/synthetic_accuracy2019-05-09 15:36:22.898531.csv',index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_df['model']=total_df['model'].replace({'XGB':'SuRF','naive_glow': '$f$+GlowWorm', 'naive_obj':'Naive', 'prim': 'PRIM'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_df['multiple'] = total_df['multiple_regions']\n",
    "total_df = total_df.drop(columns=['multiple_regions'])\n",
    "total_df['type of aggr']=total_df['type of aggr'].replace({'aggr':'Aggregate','density': 'Density'})\n",
    "total_df['multiple']=total_df['multiple'].replace({True:'k=3',False: 'k=1'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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></th>\n",
       "      <th>dimensions</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <th>type of aggr</th>\n",
       "      <th>multiple</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td rowspan=\"4\" valign=\"top\">$f$+GlowWorm</td>\n",
       "      <td rowspan=\"2\" valign=\"top\">Aggregate</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.886769</td>\n",
       "      <td>0.592264</td>\n",
       "      <td>[]</td>\n",
       "      <td>0.0748642</td>\n",
       "      <td>0.0021196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.555871</td>\n",
       "      <td>0.263898</td>\n",
       "      <td>0.0722956</td>\n",
       "      <td>0.0132715</td>\n",
       "      <td>0.0100036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"2\" valign=\"top\">Density</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.776203</td>\n",
       "      <td>0.347064</td>\n",
       "      <td>0.21193</td>\n",
       "      <td>0.144678</td>\n",
       "      <td>0.100358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.601315</td>\n",
       "      <td>0.188804</td>\n",
       "      <td>0.0587136</td>\n",
       "      <td>0.0190599</td>\n",
       "      <td>0.00718816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"4\" valign=\"top\">Naive</td>\n",
       "      <td rowspan=\"2\" valign=\"top\">Aggregate</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.361504</td>\n",
       "      <td>0.808412</td>\n",
       "      <td>0.520755</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00111992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.362537</td>\n",
       "      <td>0.345246</td>\n",
       "      <td>0.0281999</td>\n",
       "      <td>0.000555265</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"2\" valign=\"top\">Density</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.487721</td>\n",
       "      <td>0.927614</td>\n",
       "      <td>0.271749</td>\n",
       "      <td>0.0740912</td>\n",
       "      <td>0.0204322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.632892</td>\n",
       "      <td>0.263808</td>\n",
       "      <td>0.0634573</td>\n",
       "      <td>0.0176623</td>\n",
       "      <td>0.00298459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"4\" valign=\"top\">PRIM</td>\n",
       "      <td rowspan=\"2\" valign=\"top\">Aggregate</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.980707</td>\n",
       "      <td>0.84747</td>\n",
       "      <td>0.913702</td>\n",
       "      <td>0.0796889</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.250864</td>\n",
       "      <td>0.0618094</td>\n",
       "      <td>0.0147887</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"2\" valign=\"top\">Density</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"4\" valign=\"top\">SuRF</td>\n",
       "      <td rowspan=\"2\" valign=\"top\">Aggregate</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.730302</td>\n",
       "      <td>0.35271</td>\n",
       "      <td>0.142235</td>\n",
       "      <td>0.0518714</td>\n",
       "      <td>0.0087978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.611214</td>\n",
       "      <td>0.23917</td>\n",
       "      <td>0.130366</td>\n",
       "      <td>0.0262752</td>\n",
       "      <td>0.00563758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td rowspan=\"2\" valign=\"top\">Density</td>\n",
       "      <td>k=1</td>\n",
       "      <td>0.487345</td>\n",
       "      <td>0.273085</td>\n",
       "      <td>0.185489</td>\n",
       "      <td>0.0691393</td>\n",
       "      <td>0.03312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>k=3</td>\n",
       "      <td>0.517868</td>\n",
       "      <td>0.204928</td>\n",
       "      <td>0.0959071</td>\n",
       "      <td>0.0226951</td>\n",
       "      <td>0.0105497</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "dimensions                                 1          2          3  \\\n",
       "model        type of aggr multiple                                   \n",
       "$f$+GlowWorm Aggregate    k=1       0.886769   0.592264         []   \n",
       "                          k=3       0.555871   0.263898  0.0722956   \n",
       "             Density      k=1       0.776203   0.347064    0.21193   \n",
       "                          k=3       0.601315   0.188804  0.0587136   \n",
       "Naive        Aggregate    k=1       0.361504   0.808412   0.520755   \n",
       "                          k=3       0.362537   0.345246  0.0281999   \n",
       "             Density      k=1       0.487721   0.927614   0.271749   \n",
       "                          k=3       0.632892   0.263808  0.0634573   \n",
       "PRIM         Aggregate    k=1       0.980707    0.84747   0.913702   \n",
       "                          k=3       0.250864  0.0618094  0.0147887   \n",
       "             Density      k=1              0          0          0   \n",
       "                          k=3              0          0          0   \n",
       "SuRF         Aggregate    k=1       0.730302    0.35271   0.142235   \n",
       "                          k=3       0.611214    0.23917   0.130366   \n",
       "             Density      k=1       0.487345   0.273085   0.185489   \n",
       "                          k=3       0.517868   0.204928  0.0959071   \n",
       "\n",
       "dimensions                                    4           5  \n",
       "model        type of aggr multiple                           \n",
       "$f$+GlowWorm Aggregate    k=1         0.0748642   0.0021196  \n",
       "                          k=3         0.0132715   0.0100036  \n",
       "             Density      k=1          0.144678    0.100358  \n",
       "                          k=3         0.0190599  0.00718816  \n",
       "Naive        Aggregate    k=1                 0  0.00111992  \n",
       "                          k=3       0.000555265           0  \n",
       "             Density      k=1         0.0740912   0.0204322  \n",
       "                          k=3         0.0176623  0.00298459  \n",
       "PRIM         Aggregate    k=1         0.0796889           0  \n",
       "                          k=3                 0           0  \n",
       "             Density      k=1                 0           0  \n",
       "                          k=3                 0           0  \n",
       "SuRF         Aggregate    k=1         0.0518714   0.0087978  \n",
       "                          k=3         0.0262752  0.00563758  \n",
       "             Density      k=1         0.0691393     0.03312  \n",
       "                          k=3         0.0226951   0.0105497  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_df.pivot_table(values='iou',index=['model','type of aggr','multiple'], columns=['dimensions'], aggfunc=lambda x:x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dimensions  model       \n",
       "1           $f$+GlowWorm    0.705039\n",
       "            Naive           0.461163\n",
       "            PRIM            0.307893\n",
       "            SuRF            0.586682\n",
       "2           $f$+GlowWorm    0.348007\n",
       "            Naive           0.586270\n",
       "            PRIM            0.227320\n",
       "            SuRF            0.267473\n",
       "3           $f$+GlowWorm    0.122999\n",
       "            Naive           0.221040\n",
       "            PRIM            0.232123\n",
       "            SuRF            0.138499\n",
       "4           $f$+GlowWorm    0.062968\n",
       "            Naive           0.023077\n",
       "            PRIM            0.019922\n",
       "            SuRF            0.042495\n",
       "5           $f$+GlowWorm    0.029917\n",
       "            Naive           0.006134\n",
       "            PRIM            0.000000\n",
       "            SuRF            0.014526\n",
       "Name: iou, dtype: float64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_df.groupby(['dimensions','model'])['iou'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('seaborn-ticks')\n",
    "plt.rc('text', usetex=True)\n",
    "font_size=22\n",
    "params = {'backend': 'ps',\n",
    "          'text.latex.preamble': ['\\\\usepackage{gensymb}'],\n",
    "          'text.usetex': True,\n",
    "          'font.family': 'serif'\n",
    "}\n",
    "\n",
    "plt.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=serif:style=normal:variant=normal:weight=normal:stretch=normal:size=11.0 to DejaVu Serif ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf') with score of 0.050000.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
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      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmr10.tfm): ['kpsewhich', 'cmr10.tfm']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b'/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr10.tfm'\n",
      "DEBUG:matplotlib.dviread:opening tfm file /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr10.tfm\n",
      "DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=36, nh=16, nd=10\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmr10.vf): ['kpsewhich', 'cmr10.vf']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b''\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmmi10.tfm): ['kpsewhich', 'cmmi10.tfm']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b'/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi10.tfm'\n",
      "DEBUG:matplotlib.dviread:opening tfm file /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi10.tfm\n",
      "DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=98, nh=15, nd=9\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmmi10.vf): ['kpsewhich', 'cmmi10.vf']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b''\n",
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/c9c234ac8e2d43dd09e292509a1a8b19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/388c6ec693c26383f1e32e19cd24cfaa.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/82072bfaaf21a9431e26684dd365e4a6.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/40ccaa6a2f32628dbec97667339ee86f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ada10624a87904d7fc66a54edc980419.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/5f9a04b7b257b87773ce86e2dc349b7a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/c9c234ac8e2d43dd09e292509a1a8b19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/388c6ec693c26383f1e32e19cd24cfaa.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/82072bfaaf21a9431e26684dd365e4a6.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/40ccaa6a2f32628dbec97667339ee86f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ada10624a87904d7fc66a54edc980419.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=serif:style=normal:variant=normal:weight=normal:stretch=normal:size=12.0 to DejaVu Serif ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf') with score of 0.050000.\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce37e3bc3c278de36ceb72ea035685b1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmr12.tfm): ['kpsewhich', 'cmr12.tfm']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:find_tex_file result: b'/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr12.tfm'\n",
      "DEBUG:matplotlib.dviread:opening tfm file /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr12.tfm\n",
      "DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=34, nh=16, nd=10\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmr12.vf): ['kpsewhich', 'cmr12.vf']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b''\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/388c6ec693c26383f1e32e19cd24cfaa.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ada10624a87904d7fc66a54edc980419.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/25cbacf377c9afe186aac039edaeac40.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8468eb14319513aaeb55ff81836854c5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/241305c72687f2c183b7a4147b5bf8da.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/350173a3242bc258fce34f318fdab645.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/7170687f7d611eb7c0c196de82ba42b9.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/920f6025f4f3200916e71d56461ab129.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/dcdf70a8d142441064e2a99fb58a0530.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/543b0ef4416c487c6cf150f7ed7a2222.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4b6531b71c7fc655a750639b64ad2085.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/b4eefa8fff134dd3c80a080e3640f2c0.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmr17.tfm): ['kpsewhich', 'cmr17.tfm']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b'/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr17.tfm'\n"
     ]
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     "name": "stdout",
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     "text": [
      "DEBUG:matplotlib.dviread:opening tfm file /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmr17.tfm\n",
      "DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=36, nh=16, nd=9\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmr17.vf): ['kpsewhich', 'cmr17.vf']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b''\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmmi12.tfm): ['kpsewhich', 'cmmi12.tfm']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b'/usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi12.tfm'\n",
      "DEBUG:matplotlib.dviread:opening tfm file /usr/share/texlive/texmf-dist/fonts/tfm/public/cm/cmmi12.tfm\n",
      "DEBUG:matplotlib.dviread:lh=18, bc=0, ec=127, nw=97, nh=15, nd=9\n",
      "DEBUG:matplotlib.dviread:find_tex_file(cmmi12.vf): ['kpsewhich', 'cmmi12.vf']\n",
      "DEBUG:matplotlib.dviread:find_tex_file result: b''\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/731fea91495e45dd1eb5c0a88c127a62.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:['latex', '-interaction=nonstopmode', '--halt-on-error', '/home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.tex']\n",
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     "name": "stdout",
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     "text": [
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/731fea91495e45dd1eb5c0a88c127a62.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/731fea91495e45dd1eb5c0a88c127a62.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/731fea91495e45dd1eb5c0a88c127a62.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8be2a8820fb79ca4ba9120f8cc4c9fd3.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.backends.backend_ps:['latex', '-interaction=nonstopmode', '\"/tmp/tmprgw8g_d1/tmp.ps.tex\"']\n",
      "DEBUG:matplotlib.backends.backend_ps:b\"This is pdfTeX, Version 3.14159265-2.6-1.40.16 (TeX Live 2015/Debian) (preloaded format=latex)\\n restricted \\\\write18 enabled.\\nentering extended mode\\n(/tmp/tmprgw8g_d1/tmp.ps.tex\\nLaTeX2e <2016/02/01>\\nBabel <3.9q> and hyphenation patterns for 81 language(s) loaded.\\n(/usr/share/texlive/texmf-dist/tex/latex/base/article.cls\\nDocument Class: article 2014/09/29 v1.4h Standard LaTeX document class\\n(/usr/share/texlive/texmf-dist/tex/latex/base/size10.clo))\\n(/usr/share/texlive/texmf-dist/tex/latex/type1cm/type1cm.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/base/textcomp.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/base/ts1enc.def))\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/ucs.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/data/uni-global.def))\\n(/usr/share/texlive/texmf-dist/tex/latex/base/inputenc.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/utf8x.def))\\n(/usr/share/texlive/texmf-dist/tex/latex/was/gensymb.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/geometry/geometry.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty)\\n(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/ifpdf.sty)\\n(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/ifvtex.sty)\\n(/usr/share/texlive/texmf-dist/tex/generic/ifxetex/ifxetex.sty)\\n\\nPackage geometry Warning: Over-specification in `h'-direction.\\n    `width' (765.46695pt) is ignored.\\n\\n\\nPackage geometry Warning: Over-specification in `v'-direction.\\n    `height' (494.34747pt) is ignored.\\n\\n) (/usr/share/texlive/texmf-dist/tex/latex/psfrag/psfrag.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/graphics.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/trig.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/latexconfig/graphics.cfg)\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/dvips.def)))\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/graphicx.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/color.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/latexconfig/color.cfg)\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/dvipsnam.def))\\nNo file tmp.ps.aux.\\n(/usr/share/texlive/texmf-dist/tex/latex/base/ts1cmr.fd)\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/ucsencs.def)\\n*geometry* detected driver: dvips\\n<tmp.ps.eps>\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <18> not available\\n(Font)              size <17.28> substituted on input line 53.\\n\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <12.59995> not available\\n(Font)              size <12> substituted on input line 53.\\n\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <20> not available\\n(Font)              size <20.74> substituted on input line 53.\\n\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <13.99994> not available\\n(Font)              size <14.4> substituted on input line 53.\\n\\n[1] (./tmp.ps.aux)\\n\\nLaTeX Font Warning: Size substitutions with differences\\n(Font)              up to 0.74pt have occurred.\\n\\n )\\nOutput written on tmp.ps.dvi (1 page, 6624 bytes).\\nTranscript written on tmp.ps.log.\\n\"\n",
      "DEBUG:matplotlib.backends.backend_ps:['dvips', '-q', '-R0', '-o', 'tmp.ps.ps', 'tmp.ps.dvi']\n",
      "DEBUG:matplotlib.backends.backend_ps:b''\n",
      "DEBUG:matplotlib.backends.backend_ps:['gs', '-dBATCH', '-dNOPAUSE', '-r6000', '-sDEVICE=ps2write', '-dEPSCrop', '-sOutputFile=/tmp/tmprgw8g_d1/tmp.ps.ps', '/tmp/tmprgw8g_d1/tmp.ps']\n",
      "DEBUG:matplotlib.backends.backend_ps:b'GPL Ghostscript 9.26 (2018-11-20)\\nCopyright (C) 2018 Artifex Software, Inc.  All rights reserved.\\nThis software comes with NO WARRANTY: see the file PUBLIC for details.\\n'\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=serif:style=normal:variant=normal:weight=normal:stretch=normal:size=18.0 to DejaVu Serif ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf') with score of 0.050000.\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n"
     ]
    },
    {
     "name": "stdout",
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     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=serif:style=normal:variant=normal:weight=normal:stretch=normal:size=22.0 to DejaVu Serif ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf') with score of 0.050000.\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:['dvipng', '-bg', 'Transparent', '-D', '72', '-T', 'tight', '-o', '/home/fotis/.cache/matplotlib/tex.cache/58f66ee7bb5cc9bc17a90fa279cc1592.png', '/home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi']\n",
      "DEBUG:matplotlib.texmanager:b'This is dvipng 1.15 Copyright 2002-2015 Jan-Ake Larsson\\n[1] \\n'\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.font_manager:findfont: Matching :family=serif:style=normal:variant=normal:weight=normal:stretch=normal:size=20.0 to DejaVu Serif ('/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf') with score of 0.050000.\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8fc6d3fcf1c4c899c862f8a4f8c17961.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bc9c678d0653e56c2b4221d5516366c.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/047c85c6330895fcd9ed0533e0b2ae0d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/be8195efb43cd14370f2eb4799aa630a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6f4da468c7a6def2c08d46f75342edb5.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/4bd0d189ca32480032eca8a322a7e008.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81df03f758abccc3f3f6535f130e5d91.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8069aac72578843ea6e945188478ee38.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8c9f25c26ec5c9fddf03b5004980ef26.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/bdf7eac86a857e0b53b442750712671f.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/ce6fbca9ad6487d35381d6a3817d69dd.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/915b621e15e16bb08332cf95c10b5bda.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/08c01847e9586056d664dad849f44383.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8ad0f1a228abecdabc9c63605fb13300.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/13dfa2deb03f1caa903632fd3b172939.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/1aa199f78e38bade1510fea08033d7a2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 756x432 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g= sns.catplot(x=\"dimensions\", y=\"iou\", hue=\"model\",ci=False,markers=['v', '^','*','o', '.'] ,scale=1.5 ,col=\"type of aggr\",  row=\"multiple\"\n",
    "            ,despine=False,kind='point', data=total_df, legend=False,legend_out=False,height=3, aspect=1.75)\n",
    "lgd = g.fig.get_axes()[0].legend(loc='upper center', bbox_to_anchor=(1, 1.5),prop={'size':20},\n",
    "                                ncol=4, columnspacing=0.3, handletextpad=0.1,frameon=True,fancybox=True, shadow=True)\n",
    "g.set_titles(template=\"Type: {col_name} - Regions: {row_name}\", size=20)\n",
    "g.set_xlabels(label=\"Dimensions\", fontsize=font_size)\n",
    "g.set_ylabels(label=r'IoU', fontsize=font_size)\n",
    "g.set_xticklabels(labels=range(1,6),size=18)\n",
    "g.set_yticklabels(size=18)\n",
    "g.despine(top=False, right=False)\n",
    "# plt.savefig('output/accuracy/synthetic-four.eps',format='eps',dpi=300, bbox_extra_artists=(lgd,), bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'multiple_regions'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2896\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2897\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2898\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'multiple_regions'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-40-dfe3a749beac>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtotal_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'multiple_regions'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreplace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"k=3\"\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2978\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2979\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2980\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2981\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2982\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/data_vis/lib/python3.5/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2897\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2898\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2899\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2900\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2901\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'multiple_regions'"
     ]
    }
   ],
   "source": [
    "total_df['multiple_regions'].replace({True: \"k=3\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
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      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
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      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
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      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
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      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
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      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/76ab5df0af4597d96551cca7fd3db824.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/700be4b31277cdf0c5f18e1141363a04.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/37a8fcdc5c788079a052dd2572fb94b1.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6aa22efebbcc439fc2afa276ad3ca223.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/b89efb5e7d0e3541a3884f8e71473423.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/b89efb5e7d0e3541a3884f8e71473423.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/37a8fcdc5c788079a052dd2572fb94b1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6aa22efebbcc439fc2afa276ad3ca223.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/b89efb5e7d0e3541a3884f8e71473423.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/37a8fcdc5c788079a052dd2572fb94b1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6aa22efebbcc439fc2afa276ad3ca223.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/37a8fcdc5c788079a052dd2572fb94b1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/6aa22efebbcc439fc2afa276ad3ca223.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/b89efb5e7d0e3541a3884f8e71473423.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/b89efb5e7d0e3541a3884f8e71473423.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x='multiple',y='iou',hue='model', data=total_df)\n",
    "ax.set_xlabel('Multiple Regions', fontsize=font_size)\n",
    "ax.set_ylabel(r'IoU', fontsize=font_size)\n",
    "ax.tick_params(labelsize=18)\n",
    "plt.legend(prop={'size':16},shadow=True, frameon=True)\n",
    "plt.tight_layout()\n",
    "# plt.savefig('output/accuracy/synthetic_accuracy_multiple_regions.eps',format='eps', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n"
     ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n",
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/731fea91495e45dd1eb5c0a88c127a62.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d5b36263c33c02e057e78e6d458e5a19.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/731fea91495e45dd1eb5c0a88c127a62.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/fotis/anaconda3/envs/data_vis/lib/python3.5/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n"
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      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8a5c34cb08cc73292460ed5ebe1b30c2.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.backends.backend_ps:['latex', '-interaction=nonstopmode', '\"/tmp/tmpqn49lx82/tmp.ps.tex\"']\n",
      "DEBUG:matplotlib.backends.backend_ps:b\"This is pdfTeX, Version 3.14159265-2.6-1.40.16 (TeX Live 2015/Debian) (preloaded format=latex)\\n restricted \\\\write18 enabled.\\nentering extended mode\\n(/tmp/tmpqn49lx82/tmp.ps.tex\\nLaTeX2e <2016/02/01>\\nBabel <3.9q> and hyphenation patterns for 81 language(s) loaded.\\n(/usr/share/texlive/texmf-dist/tex/latex/base/article.cls\\nDocument Class: article 2014/09/29 v1.4h Standard LaTeX document class\\n(/usr/share/texlive/texmf-dist/tex/latex/base/size10.clo))\\n(/usr/share/texlive/texmf-dist/tex/latex/type1cm/type1cm.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/base/textcomp.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/base/ts1enc.def))\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/ucs.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/data/uni-global.def))\\n(/usr/share/texlive/texmf-dist/tex/latex/base/inputenc.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/utf8x.def))\\n(/usr/share/texlive/texmf-dist/tex/latex/was/gensymb.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/geometry/geometry.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty)\\n(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/ifpdf.sty)\\n(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/ifvtex.sty)\\n(/usr/share/texlive/texmf-dist/tex/generic/ifxetex/ifxetex.sty)\\n\\nPackage geometry Warning: Over-specification in `h'-direction.\\n    `width' (433.62pt) is ignored.\\n\\n\\nPackage geometry Warning: Over-specification in `v'-direction.\\n    `height' (289.07999pt) is ignored.\\n\\n) (/usr/share/texlive/texmf-dist/tex/latex/psfrag/psfrag.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/graphics.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/trig.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/latexconfig/graphics.cfg)\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/dvips.def)))\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/graphicx.sty)\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/color.sty\\n(/usr/share/texlive/texmf-dist/tex/latex/latexconfig/color.cfg)\\n(/usr/share/texlive/texmf-dist/tex/latex/graphics/dvipsnam.def))\\nNo file tmp.ps.aux.\\n(/usr/share/texlive/texmf-dist/tex/latex/base/ts1cmr.fd)\\n(/usr/share/texlive/texmf-dist/tex/latex/ucs/ucsencs.def)\\n*geometry* detected driver: dvips\\n<tmp.ps.eps>\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <18> not available\\n(Font)              size <17.28> substituted on input line 31.\\n\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <12.59995> not available\\n(Font)              size <12> substituted on input line 31.\\n\\n\\nLaTeX Font Warning: Font shape `TS1/cmr/m/n' in size <16> not available\\n(Font)              size <17.28> substituted on input line 31.\\n\\n[1] (./tmp.ps.aux)\\n\\nLaTeX Font Warning: Size substitutions with differences\\n(Font)              up to 1.28pt have occurred.\\n\\n )\\nOutput written on tmp.ps.dvi (1 page, 2972 bytes).\\nTranscript written on tmp.ps.log.\\n\"\n",
      "DEBUG:matplotlib.backends.backend_ps:['dvips', '-q', '-R0', '-o', 'tmp.ps.ps', 'tmp.ps.dvi']\n",
      "DEBUG:matplotlib.backends.backend_ps:b''\n",
      "DEBUG:matplotlib.backends.backend_ps:['gs', '-dBATCH', '-dNOPAUSE', '-r6000', '-sDEVICE=ps2write', '-dEPSCrop', '-sOutputFile=/tmp/tmpqn49lx82/tmp.ps.ps', '/tmp/tmpqn49lx82/tmp.ps']\n",
      "DEBUG:matplotlib.backends.backend_ps:b'GPL Ghostscript 9.26 (2018-11-20)\\nCopyright (C) 2018 Artifex Software, Inc.  All rights reserved.\\nThis software comes with NO WARRANTY: see the file PUBLIC for details.\\n'\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.axes._base:update_title_pos\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:following keys changed: ['text.latex.preamble', 'text.latex.unicode', 'text.latex.preview', 'font.family', 'font.serif', 'font.sans-serif', 'font.cursive', 'font.monospace']\n",
      "DEBUG:matplotlib.texmanager:text.latex.preamble : None       -> ['\\\\usepackage{gensymb}']\n",
      "DEBUG:matplotlib.texmanager:text.latex.unicode  : None       -> True      \n",
      "DEBUG:matplotlib.texmanager:text.latex.preview  : None       -> False     \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.texmanager:font.family         : None       -> ['serif'] \n",
      "DEBUG:matplotlib.texmanager:font.serif          : None       -> ['DejaVu Serif', 'Bitstream Vera Serif', 'Computer Modern Roman', 'New Century Schoolbook', 'Century Schoolbook L', 'Utopia', 'ITC Bookman', 'Bookman', 'Nimbus Roman No9 L', 'Times New Roman', 'Times', 'Palatino', 'Charter', 'serif']\n",
      "DEBUG:matplotlib.texmanager:font.sans-serif     : None       -> ['Arial', 'Liberation Sans', 'DejaVu Sans', 'Bitstream Vera Sans', 'sans-serif']\n",
      "DEBUG:matplotlib.texmanager:font.cursive        : None       -> ['Apple Chancery', 'Textile', 'Zapf Chancery', 'Sand', 'Script MT', 'Felipa', 'cursive']\n",
      "DEBUG:matplotlib.texmanager:font.monospace      : None       -> ['DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Computer Modern Typewriter', 'Andale Mono', 'Nimbus Mono L', 'Courier New', 'Courier', 'Fixed', 'Terminal', 'monospace']\n",
      "DEBUG:matplotlib.texmanager:RE-INIT\n",
      "old fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: serif, font: Computer Modern Roman, info: ('cmr', '')\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:sans-serif font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: sans-serif, font: sans-serif, info: ('cmss', '')\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:cursive font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: cursive, font: Zapf Chancery, info: ('pzc', '\\\\usepackage{chancery}')\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:monospace font is not compatible with usetex.\n",
      "DEBUG:matplotlib.texmanager:family: monospace, font: Computer Modern Typewriter, info: ('cmtt', '')\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/d926cbc05438a7fdb9dc6992a2cfd131.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/0caf379f2974979b9c3cd2bde8c1aa20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/02cebaaae22da448878f65c8fd64bd2a.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/56ce8e07d3d6fece11b5525b9503bdef.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/15c2d33f1ff5492eb13bd62704839d77.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/9f7c8ed9c7f098ed3c96ca9a62168ef1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/81bd9bbb932f88fc4382d7ec2fb15f2d.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/eb694ff9b716ace8d6ca7b37ca7e1e20.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/522bb5b693b91df30293792556b40d30.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/951bcf332ce574e85776831b5d42a5a1.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/31b8fb0116f3d2a0c48d8b5803c44249.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.texmanager:fontconfig: serifcmrcmsspzccmtt20497a30a03f610e773b50fa581d240e\n",
      "DEBUG:matplotlib.dviread:Dvi: /home/fotis/.cache/matplotlib/tex.cache/8292f763250662be410ef763001bd0a4.dvi\n",
      "DEBUG:matplotlib.dviread:Dvi._xxx: encountered special: papersize=5203.43999pt,5203.43999pt\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.barplot(x='type of aggr',y='iou',hue='model', data=total_df)\n",
    "ax.set_xlabel('Aggregate Type', fontsize=font_size)\n",
    "ax.set_ylabel(r'IoU', fontsize=font_size)\n",
    "ax.tick_params(labelsize=18)\n",
    "plt.legend(prop={'size':16},shadow=True, frameon=True)\n",
    "plt.tight_layout()\n",
    "# plt.savefig('output/accuracy/synthetic_accuracy_type.eps',format='eps', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}