IoTID20_MCC_plot.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0k5B9cN6TqmE"
   },
   "source": [
    "## Imports and settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "3ZxRq5lcTqmF",
    "outputId": "c6208193-349b-4e89-a311-31430240017e"
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import time\n",
    "import sys\n",
    "import os\n",
    "\n",
    "%matplotlib inline\n",
    "matplotlib.rcParams['font.size'] = 8\n",
    "matplotlib.rcParams['figure.figsize'] = (5, 4)\n",
    "matplotlib.rcParams['figure.facecolor'] = '#00000000'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2/WAeeMFaH4F+Cvi0c64C+Bjw/B3W/TWgM3KBiKQCfwG8yTm3E7gM/JcHU+rG5dSpU36X4Cva9YN5oF0/mAdesGYBKiJ5QB3whdCil4BiESlfYd1q4E3AR5e99WPAcedcW+j1J4Hn7rDPRBFJX3oAafenwjAMwzCCxK3hvoqBfufcAoBzzolID1ACdCytJCLxwGeAdwKBZdsoAS5GvO4GtohI3NJ2l/Eh4CPLFzY1NZGSkkJtbS1nz55lZmaGtLQ0tm/fHu6Ztm3bNhYXF+nt7QVg//79dHR0MDk5SUpKChUVFRw/fhyAoqIiYmNjuXgxWFpNTQ3d3d1MTEyQlJREdXU1x44dA6CwsJCkpCS6uroA2LNnD319fYyNjZGQkMD+/ftpaGgAgrMlpKam0tERtKeqqorBwUFGR0eJi4vj4MGDNDQ04JwjNzeXrKws2tvbAdi1axejo6MMDw8TExPDoUOHaGpqIhAIkJiYyMTEBGfPngVg586dTExMMDg4CMCRI0dobm5mfn6erKwsCgsLaW1tBYLDf01PT9Pf3w9AXV0dp0+fZnZ2loyMDEpKSsK/bEtLS1lYWKCvrw+A2tpa2tramJ6eJjU1lbKyMk6cOBH8jy0pAaCnpweAffv20dnZyeTkJMnJyVRWVoYnAC4qKiIuLo7u7m4A9u7dS09PD+Pj4yQlJbFnzx6ampoA2LJlC8nJyXR2Bk9mVFdXk5CQQH19PfHx8dTW1lJfXw9Afn4+6enpnD9/Puz30NAQV65cITY2lrq6OhobG1lcXCQ3N5fs7GzOnTsHQEVFBVevXmV4eBgR4fDhwxw7doyFhQWys7PJz88P+11eXs7k5GT4RvbDhw/T0tLC3NwcmZmZFBUVcfr0aQB27NjB7Owsly9fBuDgwYO0trYyOztLeno6paWlN7XZQCAQ9vvAgQO0t7czNTVFamoq5eXltLS0AJCens7AwMBNbfbChQtcu3aNTZs2UVVVFfZ769atJCQkcOHChbDfvb29jI2NkZiYSE1NDY2NjeE2m5KSEvZ79+7dDAwMMDo6eovfeXl5ZGRkhP2urKxkZGSEkZGRcJtd8jsnJ4ecnBza2trCbXZ8fJyhoaFb2mx2djYFBQXhwdLLysqYmpoK+33o0CEWFxepr68nMzOT4uLicJvdvn07c3NzXLp0KdxmN+p3RG5uLl1dXSt+R2zevJm8vDwV3xH3w5rdByoiB4EvOud2RSxrAD7onPtOxLLfB8acc/9dREqBFudcZui9XwcqnHPvCb1OBq4BiSsFqIgkAokRi9KAPu33gfb19VFUVOR3Gb6hXT+YB9r1g3mw3u4D7SV0tAjBTkIEjyh7lq33JPDLItINfBdIF5FuEckNrbstYt1SIo5ql+Ocu+6cm1h6EAxb9Sz9utaKdv1gHmjXD+aBF6xZgDrnhoBm4G2hRc8Afc65jmXrPe6c2+acKwUeAyacc6XOuWHgW0CtiFSGVv9F4MU1EWAYhmEYEazpUH4isotgz9vNwATwdufcKRH5LPAN59w3lq1fSsQp3NCyp4CPE7x+exr4Wefc+Cr3b0P5AfPz88THx/tdhm9o1w/mgXb9YB6st1O4OOfOOecedc5VOOfqnHOnQsvftTw8Q8u7I8MztOwbzrlK51y5c+5Nqw1P4wZLHQO0ol0/mAfa9YN54AU2EpFCZmZm/C7BV7TrB/NAu34wD7zAAlQhaWm6b4fVrh/MA+36wTzwAgtQhWzfvt3vEnxFu34wD7TrB/PACyxAFaJ9GiPt+sE80K4fzAMvsAA1DMMwjCiwAFXItm3b7r7SBka7fjAPtOsH88ALLEAVsri46HcJvqJdP5gH2vWDeeAFFqAKWRr8Wiva9YN5oF0/mAdesJazsRiGYRhKWAwEuPjds1zrv0raliy2PVZFTGys32V5ypoO5ec3NpRfkOvXr5OYmHj3FTco2vWDeaBdPzxYD8589SjffP/nmLh0JbwsfetmXv+Jd7D76UceyD7vlXU3lJ/xcLA0d6BWtOsH80C7fnhwHpz56lFefPYPbwpPgInLV3jx2T/kzFePPpD9+oEFqEImJyf9LsFXtOsH80C7fngwHiwGAnzz/Z+DlU5shpZ989c/x2Ig4Pm+/cACVCEpKSl+l+Ar2vWDeaBdP3jvwfzMder/7Fu3HHnehIOJvitc/O7GGMjeOhEppKKiwu8SfEW7fjAPtOuH+/dgvHeE3qPn6Dl6jt4fnKO/5QKLC6s7srzWf/W+9v2wYAGqkOPHj3PkyBG/y/AN7frBPNCuH+7Ng4W5eQZOdNPzg3P0hUJzou/WI82krBRmr07ddXtpW7Luud6HEQtQwzAM4yYmh8bpDR1Z9hw9x+VjnSzMzt20TkxsDPk1pZQ8uoviR4KP9KJs/sfOX2Ti8pWVr4NKsDfutseq1kbIA8YCVCFFRUV+l+Ar2vWDeaBdP9zwYDEQYOh0Lz1H2+g92k7v0XOMdg7csv6m7NRwUJY8uoutdeUkpCTdst7rP/EOXnz2D0G4OUQl9P4fvWPD3A9qAaqQ2A3SeKNFu34wDzTrn7k6SW99O23/3Mw/neqjr+E8c5OzN60jIuRWFVH8aDAsi4/sYnNFISJy1+3vfvoRnn3xAyvfB/pHD899oF5gAaqQixcvUlBQ4HcZvqFdP5gHWvQvLi5ypf1ysLPPD87Re/Qcw2f7blkvMW0TRUcqKD5SQfGjuyg6XMGmzOh76e5++hEqnzq04UcisgA1DMPYIFyfnOFSY0e4d2zf0XZmrt56v2d2eQGbyjdT+8bHKD5SQV51sefhFhMby/Yn93i6zYcNG8pPITMzM2zatMnvMnxDu34wDzaCfuccY91D4SPL3qPnGDh5EbdslpW4pAS2Hiqn5JGlzj4VpORmbAgP7gcvhvKzI1CFdHd3U1W1MXrBRYN2/WAerEf987NzXG7uCveO7T16jsnBsVvWyyjJofhI6Nrlo7soqCklNv7Wr/r16MHDhgWoQiYmovqxtWHQrh/Mg/Wgf+LSFXqPtod7x/Y3dxGYX7hpndj4OLYc2E5xqKNP8SO7yCjavLrtrwMPHnYsQBWSlHRr13NNaNa/NMXUcH0HF2ZTNmTHjtXwsLWBwPwCAye7w0eWPUfPMd4zcst6qfmZ4Y4+xY9WUnhgO/GboptR5WHzYD1i10AVsrCwQFyc3t9OWvWvhymm1gq/28DUyMTNAxU0dTA/c/NABRITQ/7ebaHbSIKhmbU9f1W3kqwGvz3wGy+ugVqAKqS+vl71MGYa9S9NMXXL6DCh7+JnX/yAqhC9lzZwvxNDLwYCDJ/pC48Z23v0HFc6+m9Zb1NWKkVHdlL8SGV4oILEtAfXyUfj30Ek1onIMIy7ctcppiQ4xVTlU4dUns69E9Ectc+MTdHX0B4e1aevvp3r12ZuWS+3MjhQQfEjFZQ8UsnmXYXExNgEWesJC1CFFBYW+l2Cr2jTf/4fjq9qiqnPP/UHZG3LIzYhjtjEeOJC/8YmxBGXGE9cYjyxiXHEJcTfWGdp2dJ6CfGh5XHEJkS8lxhPbNzDE86raQO3O2pfmhj62Rc/QNWbjnDlfD+9R9tCt5O0M3yml+Vn9hJSkth6eGfwVpJHd1F0eCfJ2WleSrpntP0dPAgsQBWivfPARtU/P3OdkbZLDLb2MHi6h6EzPQy19jLee2tnlJXo/KcTD7Q+iYkJhfHN4RsbfyNkl4L45tCOv/G5hFuXhV+HtxO3bJ0bPwaWti/XF5mfuU5sYvyKR32rmRj67372j4lPTmRm9NaBCrJ25Efcd7mLvD0lD9UPCNi4fwdriQWoQrq6usjNzfW7DN9Y7/oDCwFGz/cz2NrDUOgx2NrLaOfALTfR3wsH3/U6MrZuZuH6PIG5eQJzCyxcXyBwfT60bOHmf++4LPi5yCMxt7jIwuzcLbN6+E1MbMwtR9OL8wEmLo/e8XMLs/MszM4TlxhPYV05xUcqwjOTpOZnrk3x98F6/zt4GLAANYyHlMXFRcZ7RkIB2cPQ6eC/I+cuEZhbWPEzm7JTyd+zjbzq4tC/JeTs2sqf1f36XaeYeuOf/Lyn10CdcywuBCLCdVnIzs2HgzYygJcCeWnZTZ+djwj06wsEQttYmFv6bPBzN7az8g+Bm3wOLLI4fZ356ev3rPE1H/lJHv/A08QlxHtlm7GOsABVyJ49G3t8yrvxsOl3zjE5OBY+klw6qhw603vLLBlLJKQkkVddTF51CXnVJeSHnqfmZ654m4MfU0yJCLHxwVO0K0175RfOOa6NTZAYl3BraIfCuLe+nb9//+fuuq3Sx3av2/B82P4O1iMWoArp6+tj165dfpfhG37qnxmbYuhMMCQHT19kKBSY01eurbh+bEIcObu23jiqDAVmRknOPfXY1DTF1N0QEfqHBti1a9dtbxMprN3B9/7o6xt6Ymjt3wNeYAGqkLGxMb9L8JW10D83fZ2Rtr5wZ56lI8uJvpV7w0pMDNllBeEjyeBRZQnZ5QUrjmMaDZFTTB3/biMHHjukdiSiu7WBmNjYDT8xtPbvAS+wAFVIQkKC3yX4ipf6A/MLXDnff+M6ZSgoRzsHbrmVYYmM4pzQ0eSNo8qcyq1RD8l2LyxNMTWWPs/2A3pP4a2mDWz0o3bt3wNeYCMRKcQ559lwYOuRaPQvLi4y1j3EUGvvTb1fR85dvmWA7yWSc9LJ33PzNcq83cUkZUQ/UbFXWBtYvf77HYnoYUV7G7CRiIyoaGhoUD2E1530O+eYHBi75RaR4TO9zE3dpkNPalIwJPeUhK9R5lWXkJqX8SBl3BfWBlavf6NODK29DXjBqgNURH4IyHfOfWXZ8meAfufc970uzjBuhxdHBTNXJyOC8saR5Uo3xgPEJcaTU1m07DplMRkluap/yRuGVu7lCPR3gPeusPw48CngdV4UZDx4CgoK/C7hvrjX8UnnpmYZbusLH01ebDrHK12fZeLSyjfKS0wMm8sLwvdRLl2nzCoreOhGk4mW9d4G7hft+sE88IJ7CdAM51zn8oXOuS4RyfOwJuMBk5qa6ncJUXO38Ul/9ONvJ60g88aR5ZlernYN3rZDT+a23PC1yaXTrzmVW4lP2tgdLNZzG/AC7frBPPCCewnQrDu89+Dm3DE8p6Ojg82bVzdr/cPEasYn/dYH/nLFz6bmZ4YHHpjatMAjb3w1uVVFJKUnP7iCH2LWaxvwCu36wTzwgnsJ0H4ROeKcq49cKCKHgUFvyzKMW7n43bN3nlUkRO7uYra9qvKm068puTc69NTX11N8pOJBlmoYhgLuJUD/K/BVEfld4Gho2aPAfwbevpoNiMhO4K+AHGAc+DnnXOuydR4F/iz0Mh74LvArzrnrIvJq4O+BcxEfedQ5d+tke8ZtqapaX6OnTA6Ocfpvv8cP/uT/rmr9Jz/4DDXPPn7b99eb/geBdg+06wfzwAtWHaDOuW+LyM8Avw18IrS4CXi7c+6fVrmZTwGfds49LyJvAZ4HDi1b5wRwyDk3LyIxwEvALwL/I/T+Oefc/tXWbdzK4ODgQ38f7NzULGe/3sCJF16m69snWAysfpaRtC13utqwPvQ/aLR7oF0/mAdecE/3gTrnvg18O5odhToa1QE/Elr0EvCnIlLunOuI2Md0xMcSCF5f1TPawxowOnrnaZr8IrAQoPPbJzj5wiuc/Xr9TbNjbD20k5pnH+O7//1rXBu4el/jkz6s+tcS7R5o1w/mgRfcy32g7wDinHOfXrb83cCcc+75u2yimOD9ogsAzjknIj1ACdARuaKIlAJfB8qA/wt8MuLtMhFpBgLAXzrnIt9bXnMiEDk+mr9TwD8kxMU9PONnOOe41NTByRde5tSXv8fU0Hj4veyyAmqee4J9zz3O5p2FAGQU5dz3+KQPk36/0O6Bdv1gHnjBvTj4buDfr7D8SwSPSp/3oiAA51w3sE9EUoEvAG8GXgSagSLn3LiIFAHfFJER59yXb7OpDwEfWb6wqamJlJQUamtrOXv2LDMzM6SlpbF9+3ZOnjwJwLZt21hcXKS3txeA/fv309HRweTkJCkpKVRUVHD8+HEAioqKiI2N5eLFiwDU1NTQ3d3NxMQESUlJVFdXc+zYMQAKCwtJSkqiq6sLCE4p1NfXx9jYGAkJCezfv5+GhgYgeJ9WamoqHR3B3xdVVVUMDg4yOjpKXFwcBw8epKGhAeccubm5ZGVl0d7eDsCuXbsYHR1leHiYmJgYDh06RFNTE4FAgM2bNzMxMcHZs2cB2LlzJxMTEwwOBvuCHTlyhObmZubn58nKyqKwsJDW1uCl6rKyMqanp+nv7wegrq6O06dPMzs7S0ZGBiUlJZw6dQqA0tJSFhYW6OvrA6C2tpa2tjamp6dxo9e5drSX5s//C1N9V8P/NwmZyWx5bSWv/k8/zkwWTE1NcXn2CunzuTQ3N0Oh8LpPvpPv/9eXmOofC38uOT+Dyl96DfM7NhEIBGhqagJgy5YtJCcn09kZvAOrurqatLQ06uvriY+Pp7a2lvr6YL+4/Px80tPTOX/+fNjvoaEhrly5QmxsLHV1dTQ2NrK4uEhubi7Z2dmcOxe8HF9RUcHVq1cZHh5GRDh8+DDHjh1jYWGB7Oxs8vPzw36Xl5czOTnJwMAAAIcPH6alpYW5uTkyMzMpKiri9OnTAOzYsYPZ2VkuX74MwMGDB2ltbWV2dpb09HRKS0tvarOBQCDs94EDB2hvb2dqaorU1FTKy8tpaWkBoLi4mIGBgZva7IULF7h27RqbNm2iqqoq6DewdetWEhISuHDhAgB79+6lt7eXsbExEhMTqampobGxMdxmU1JSwn7v3r2bgYEBRkdHb/E7Ly+PjIyMsN+VlZWMjIwwMjISbrNLfufk5JCTk0NbW1u4zY6PjzM0NHRLm83OzqagoIAzZ86E2+zU1FTY70OHDhEbG0t9fT2ZmZkUFxeH2+z27duZm5vj0qVL4Ta7kb8jurq6bvsdkZeX5+t3RGpqKmVlZZw4cQKAkpISAHp6egDYt28fnZ2dTE5OkpycTGVlZbjNFhUVERcXR3d3d7jN9vT0MD4+TlJSEnv27Al/R9wPqx4LV0QanXPLr1cuvddyt+uSoVO4HUC2c25BgkO39AOPRZ7CXeFzzwI/5Zx74wrvfQgodM798m0+u9IRaJ/2sXAbGho4fPjwmu93anic03/7PU588WX6Gs6Hl8dvSqDyqcPse+sTlP3wvlXNPnI/IxH5pf9hQrsH2vWDebDWY+Fm3+G9u54adc4NhU69vo3g0eozQN/y8BSRcuBiqBNRAvA0cDL03hZg0Dm3KCJpwBuAv7jDPq8D4QtpNtxakLWcQGBu+jpt3wh2Bur8x5ZwZyCJiaHsh2uoefZxqn78yG3nZbwd9zM+qaYJFG6Hdg+06wfzwAvuJUCbReQdzrmbpmkXkZ8lOJzfangP8LyIfBiYIHT7i4h8FviGc+4bwGuBXxGRQKi+fwZ+L/T5Z4BfEJGF0Ht/C6x857xxW3Jzcx/o9gMLAS78yylOfPFlzn6t/qZB2AsPlrHvrU+w5yd+iLSCO/eWfVA8aP3rAe0eaNcP5oEX3Msp3DLgFeBl4Aehxa8CniB4GvaWYf4eNmw6syBXr14lK8vb8HLOcbm5k5MvvMKpL32XycGx8HtZ2/NCnYGeIGfXVk/3Gw0PQv96Q7sH2vWDebCmp3Cdc50icgD4TwRvRXHAMeB9zrmBaHZu+EN7e7tn0xiNdg1w8oVXOPnCy4y0Xw4vT96cxp6f+CFq3voExUcqHqrT517qX69o90C7fjAPvOBebmP5RMTL9tC/acBvigjOufd7Wpnx0DI1MkHr332fEy+8TO8PbgwKFZeUQOUbD7HvrU9Q/iP7V9UZyDAMY71yL99wvwo0At8CVj8sjPHQsWvXrnv+zNz0dc79nyZOfPHf6PjHFhYXAkCwM9CO1+4NdgZ605F1MTh7NPo3Gto90K4fzAMvuJcA/XfAO4C3Al8GPrcernsatzI6OkpmZuZd11sMBLjwr6c58cWXOfPVo8xN3ugMtOXADva99Qn2/sfH7jp03sPGavVvZLR7oF0/mAdecC/XQP8F+JdQR5zngL8RkRngg8tnaDEeboaHh9mxY8eK7znn6G+5EBwZ6Evf5Vr/jUEOMkvzqHn2cfY99wS5VUVrVa7n3Em/FrR7oF0/mAdecM8XqZxzEyLydYL3hf4KUAlYgK4jYmJibll2tXuIky++wskvvsxwW194+absVPa85VXUvPVJSh7d9VB1BoqWlfRrQ7sH2vWDeeAF93IbSyzwFPBOYBvweeDzzrn+B1eet9htLDczfeUarS99nxMvvELP986Gl8clJbDrPxxk31ufpPzf7ycuId7HKg3DMLxnrUciugT0EBy44HuhZbkikgvgnDsZTQHG2jI/c52//5MvM3n0Euf/4TiB+QUgOErT9tfsoea5J9j9piMkZaT4XOmDo6mpibq6Or/L8BXtHmjXD+aBF9xLgM4CucBvErwHNPJcngPsZPpDymIgQPfLZ8Kdga5P3JgxrmDfdmqee5yan3yM9K2bfaxy7QgEAn6X4DvaPdCuH8wDL7iXTkSlD7AOw2Occwyc6Obkiy9z8sXvcu3yjbn/UrZkUvvTr2Xfc4+TV13iY5X+sHmzjh8Kd0K7B9r1g3ngBXan+wZj7OIQJ1/8LidfeJmhM73h5UmZKaHOQE+QtaeQDMXd1/Py8vwuwXe0e6BdP5gHXmABugGYuToZ7gx08ZUz4eVxifFUvP4g+976BDt/tJa4xGBnoPr6etVDeJ09e1a1fjAPtOsH88ALLEDXKfOzc7R/8xgnX3iF9r8/RmDuRmeg0ierqXnucXY//SibMjduZyDDMAw/sQB9CFjt5NCLi4tcfCXUGegrP2B2/EZnoPy924IjA/3k42QU3fnaxs6dOz3XsJ7Qrh/MA+36wTzwAgtQnznz1aN88/2fY+LSlfCy9K2bef0n3sHupx8BYPDURU588WVOfukVJvoi1ivaHB4ZKH/vtlXvc2JiguzsO82PvrHRrh/MA+36wTzwAgtQHznz1aO8+OwfBm8CimDi8hVefPYPqXnuSQZPXmDwdE/4vaSMZKqfCXYG2vZYVVSjiQwODlJaWnqf1a9ftOsH80C7fjAPvMAC1CcWAwG++f7P3RKeQHjZyS/+GwCxCXFU/FioM9CP1RKflLB2hRqGYRgrsuqh/DYCD9NQfhf+7TR/+bqP3HW9V/3aG3nyg29hU1bqGlRlGIahAy+G8rPRhH0icpaTO1F4oMzz8GxubvZ0e+sN7frBPNCuH8wDL7AA9YnVzqH5IObanJ+f93yb6wnt+sE80K4fzAMvsAD1iW2PVQXHnr3d7GAS7GW77bEqz/edlbW+JsD2Gu36wTzQrh/MAy+wAPWJmNhYXv+JdwRfLA/R0OvX/9E7Vrwf9H4pLCz0fJvrCe36wTzQrh/MAy+wAPWR3U8/wrMvfoD0wpsHPkjfuplnX/xA+D5Qr2ltbX0g210vaNcP5oF2/WAeeIHdxuIzu59+hMqnDq1qJCLDMAzj4cEC9CEgJjaW7U/uWbP9lZWVrdm+Hka06wfzQLt+MA+8wE7hKmR6evruK21gtOsH80C7fjAPvMACVCH9/f1+l+Ar2vWDeaBdP5gHXmABahiGYRhRYEP5KSQQCBCruJOSdv1gHmjXD+aBDeVnRMXp06f9LsFXtOsH80C7fjAPvMACVCGzs7N+l+Ar2vWDeaBdP5gHXmABqpDQaQu1aNcP5oF2/WAeeIEFqEJKSkr8LsFXtOsH80C7fjAPvMACVCGnTp3yuwRf0a4fzAPt+sE88AILUMMwDMOIAgtQhZSWlvpdgq9o1w/mgXb9YB54gQWoQhYWFvwuwVe06wfzQLt+MA+8wAJUIX19fX6X4Cva9YN5oF0/mAdeYAFqGIZhGFFgQ/kpZH5+nvj4eL/L8A3t+sE80K4fzAMbys+Iira2Nr9L8BXt+sE80K4fzAMvsABViPZ5ALXrB/NAu34wD7xgTQNURHaKyPdFpF1EGkWkeoV1HhWRltCjVUQ+JSKJEe+/U0TOi0iniHxGRPSeg4iS1NRUv0vwFe36wTzQrh/MAy9Y6yPQTwGfds5VAB8Dnl9hnRPAIefcfmAvkAf8IoCIbAd+D3gcKAfygXc/8Ko3GGVlZX6X4Cva9YN5oF0/mAdesGYBKiJ5QB3whdCil4BiESmPXM85N+2cmw+9TAA2AUs9nd4CfMM5N+CCvZ/+HHjugRe/wThx4oTfJfiKdv1gHmjXD+aBF6zlEWgx0O+cWwAIBWAPcMuIxiJSKiIngBFgHPhk6K0S4GLEqt0rfT5iO4kikr70ANK8EGIYhmEYcX4XsBLOuW5gn4ikEjxifTPwYhSb+hDwkeULm5qaSElJoba2lrNnzzIzM0NaWhrbt2/n5MmTAGzbto3FxUV6e3sB2L9/Px0dHUxOTpKSkkJFRQXHjx8HoKioiNjYWC5eDGZ7TU0N3d3dTExMkJSURHV1NceOHQOgsLCQpKQkurq6ANizZw99fX2MjY2RkJDA/v37aWhoAKCgoIDU1FQ6OjoAqKqqYnBwkNHRUeLi4jh48CANDQ0458jNzSUrK4v29nYAdu3axejoKMPDw8TExHDo0CGampoIBALEx8czMTHB2bNnAdi5cycTExMMDg4CcOTIEZqbm5mfnycrK4vCwkJaW1uB4Gmf6elp+vv7Aairq+P06dPMzs6SkZFBSUlJeJDq0tJSFhYWwjds19bW0tbWxvT0NKmpqZSVlYV/BS/NDNHT0wPAvn376OzsZHJykuTkZCorK2lubg77HRcXR3d3NwB79+6lp6eH8fFxkpKS2LNnD01NTQBs2bKF5ORkOjs7AaiuriYuLo76+nri4+Opra2lvr4egPz8fNLT0zl//nzY76GhIa5cuUJsbCx1dXU0NjayuLhIbm4u2dnZnDt3DoCKigquXr3K8PAwIsLhw4c5duwYCwsLZGdnk5+fH/a7vLycyclJBgYGADh8+DAtLS3Mzc2RmZlJUVFReLLjHTt2MDs7y+XLlwE4ePAgra2tzM7Okp6eTmlp6U1tNhAIhP0+cOAA7e3tTE1NkZqaSnl5OS0tLUDw+tfAwMBNbfbChQtcu3aNTZs2UVVVFfZ769atJCQkcOHChbDfvb29jI2NkZiYSE1NDY2NjeE2m5KSEvZ79+7dDAwMMDo6eovfeXl5ZGRkhP2urKxkZGSEkZGRcJtd8jsnJ4ecnJxwz9GdO3cyPj7O0NDQLW02OzubgoICzpw5E26zU1NTYb8PHTpEIBCgvr6ezMxMiouLw212+/btzM3NcenSpXCb3ajfEZs3b6arq2vF74jNmzeTl5en4jvifliz+0BDp3A7gGzn3IKICNAPPOac67jD554Ffso590YR+QBQ5px7b+i91wMfds49dpvPJgKJEYvSgD7t94H29/ezZcsWv8vwDe36wTzQrh/Mg3V1H6hzbghoBt4WWvQM0Lc8PEWkfKlnrYgkAE8DJ0NvvwQ8JSIFoQB+L3c4MnXOXXfOTSw9gGueilqnLP2C04p2/WAeaNcP5oEXrHUv3PcA7xGRduCDwNsBROSzIvJUaJ3XAsdD10CPA4MEe97inOsieEr2ewSPZocJ9uw1DMMwjDXFhvJTyOzsLElJSX6X4Rva9YN5oF0/mAfr6hSu8fCw1MFDK9r1g3mgXT+YB15gAaqQyclJv0vwFe36wTzQrh/MAy+wAFVIcnKy3yX4inb9YB5o1w/mgRfYNVCFaJ/GSLt+MA+06wfzwK6BGlGxdLOxVrTrB/NAu34wD7zAAtQwDMMwosACVCFFRUV+l+Ar2vWDeaBdP5gHXmABqpC4uIdyCOQ1Q7t+MA+06wfzwAssQBWyNMCyVrTrB/NAu34wD7zAAtQwDMMwosBuY1HI9PS06nvAtOsH80C7fjAP7DYWIyq0z8KgXT+YB9r1g3ngBRagChkfH/e7BF/Rrh/MA+36wTzwAgtQhWiegQFMP5gH2vWDeeAFdg1UIYFAgNjYWL/L8A3t+sE80K4fzAO7BmpERVNTk98l+Ip2/WAeaNcP5oEXWIAahmEYRhRYgCpky5YtfpfgK9r1g3mgXT+YB15gAaoQzfd+gekH80C7fjAPvMACVCGdnZ1+l+Ar2vWDeaBdP5gHXmABahiGYRhRYLexKGRycpLU1FS/y/AN7frBPNCuH8wDu43FiIrLly/7XYKvaNcP5oF2/WAeeIEFqEKuXr3qdwm+ol0/mAfa9YN54AUWoAqJj4/3uwRf0a4fzAPt+sE88AK7BmoYhmGow66BGlFRX1/vdwm+ol0/mAfa9YN54AUWoIZhGIYRBRagCsnPz/e7BF/Rrh/MA+36wTzwAgtQhWi//qtdP5gH2vWDeeAFFqAKOX/+vN8l+Ip2/WAeaNcP5oEXWIAahmEYRhRYgCqkqqrK7xJ8Rbt+MA+06wfzwAssQBUyNDTkdwm+ol0/mAfa9YN54AUWoAq5cuWK3yX4inb9YB5o1w/mgRdYgCokNjbW7xJ8Rbt+MA+06wfzwAtsKD/DMAxDHTaUnxEVjY2NfpfgK9r1g3mgXT+YB15gAaqQxcVFv0vwFe36wTzQrh/MAy+wAFVIbm6u3yX4inb9YB5o1w/mgRdYgCokOzvb7xJ8Rbt+MA+06wfzwAssQBVy7tw5v0vwFe36wTzQrh/MAy+wADUMwzCMKFjTABWRnSLyfRFpF5FGEaleYZ3XikiDiJwRkVYR+biIxITeKxWRgIi0RDzK1lLDRqCiosLvEnxFu34wD7TrB/PAC9b6CPRTwKedcxXAx4DnV1jnKvCsc243cBB4FfAzEe9fc87tj3h0PuiiNxpXr171uwRf0a4fzAPt+sE88II1C1ARyQPqgC+EFr0EFItIeeR6zrnjzrmu0PNZoAUojXKfiSKSvvQA0qIsf0MxPDzsdwm+ol0/mAfa9YN54AVxa7ivYqDfObcA4JxzItIDlAAdK31ARAqAtwBviFicIiKNQCzwNeAPnHOB2+zzQ8BHli9samoiJSWF2tpazp49y8zMDGlpaWzfvp2TJ08CsG3bNhYXF+nt7QVg//79dHR0MDk5SUpKChUVFRw/fhyAoqIiYmNjuXjxIgA1NTV0d3czMTFBUlIS1dXVHDt2DIDCwkKSkpLo6uoCYM+ePfT19TE2NkZCQgL79++noaEBgIKCAlJTU+noCNpTVVXF4OAgo6OjxMXFcfDgQRoaGnDOkZubS1ZWFu3t7QDs2rWL0dFRhoeHiYmJ4dChQzQ1NREIBJiammJiYoKzZ88CsHPnTiYmJhgcHATgyJEjNDc3Mz8/T1ZWFoWFhbS2tgJQVlbG9PQ0/f39ANTV1XH69GlmZ2fJyMigpKSEU6dOAVBaWsrCwgJ9fX0A1NbW0tbWxvT0NKmpqZSVlXHixAkASkpKAOjp6QFg3759dHZ2Mjk5SXJyMpWVlTQ3N4f9jouLo7u7G4C9e/fS09PD+Pg4SUlJ7Nmzh6amJgC2bNlCcnIynZ3BExXV1dVMTU1RX19PfHw8tbW11NfXA5Cfn096enp4nsSqqiqGhoa4cuUKsbGx1NXV0djYyOLiIrm5uWRnZ4c7YlRUVHD16lWGh4cREQ4fPsyxY8dYWFggOzub/Pz8sN/l5eVMTk4yMDAAwOHDh2lpaWFubo7MzEyKioo4ffo0ADt27GB2dpbLly8DcPDgQVpbW5mdnSU9PZ3S0tKb2mwgEAj7feDAAdrb25mamiI1NZXy8nJaWloAmJ2dZWBg4KY2e+HCBa5du8amTZuoqqoK+71161YSEhK4cOFC2O/e3l7GxsZITEykpqYmfFN+QUEBKSkpYb93797NwMAAo6Ojt/idl5dHRkZG2O/KykpGRkYYGRkJt9klv3NycsjJyaGtrS3cZsfHx8MDoke22ezsbAoKCjhz5ky4zU5NTYX9PnToEBMTE9TX15OZmUlxcXG4zW7fvp25uTkuXboUbrMb9TtiYWGBrq6uFb8jNm/eTF5enorviPthzYbyE5GDwBedc7siljUAH3TOfWeF9dOBfwZecM59IrQskeCwS0Mikg18Cfgn59zHb7PPRCAxYlEa0GdD+RmGYehmvQ3l1wtsEZE4ABERgkefPctXFJE04FvA15fCE8A5d905NxR6Pgp8Dnj8djsMrT+x9ACueSlovbL0S1cr2vWDeaBdP5gHXrBmARoKvmbgbaFFzwB9zrmbTt+KSCrB8PyWc+73l72XJyLxoeeJwJuB4w+69o3GwsKC3yX4inb9YB5o1w/mgResdS/c9wDvEZF24IPA2wFE5LMi8lRonfcBh4E3R9yq8luh9x4DjovICYJhPAD8wZoq2ABoH4FEu34wD7TrB/PAC2w6M4VMTEyYfsX6wTzQrh/Mg/V2DdR4SFjqWacV7frBPNCuH8wDL7AANQzDMIwosABVSHl5+d1X2sBo1w/mgXb9YB54gQWoQiYnJ/0uwVe06wfzQLt+MA+8wAJUIUsjsmhFu34wD7TrB/PACyxADcMwDCMK7DYWhTjnCA4EpRPt+sE80K4fzAO7jcWIiqUBxbWiXT+YB9r1g3ngBRagCpmbm/O7BF/Rrh/MA+36wTzwAgtQhWRmZvpdgq9o1w/mgXb9YB54gQWoQoqKivwuwVe06wfzQLt+MA+8wAJUIUuTNWtFu34wD7TrB/PACyxADcMwDCMKLEAVsmPHDr9L8BXt+sE80K4fzAMvsABVyOzsrN8l+Ip2/WAeaNcP5oEXWIAq5PLly36X4Cva9YN5oF0/mAdeYAFqGIZhGFFgQ/kpZGFhgbi4OL/L8A3t+sE80K4fzAMbys+IitbWVr9L8BXt+sE80K4fzAMvsABViPbOA9r1g3mgXT+YB15gAaoQzaevwfSDeaBdP5gHXmABqpDS0lK/S/AV7frBPNCuH8wDL7AAVcjJkyf9LsFXtOsH80C7fjAPvMAC1DAMwzCiwAJUIdu2bfO7BF/Rrh/MA+36wTzwAgtQhQQCAb9L8BXt+sE80K4fzAMvsABVSF9fn98l+Ip2/WAeaNcP5oEXWIAahmEYRhTYUH4KmZubIyEhwe8yfEO7fjAPtOsH88CG8jOior293e8SfEW7fjAPtOsH88ALLEAVMjU15XcJvqJdP5gH2vWDeeAFFqAKSU1N9bsEX9GuH8wD7frBPPACuwaqkOvXr5OYmOh3Gb6hXT+YB9r1g3lg10CNqGhpafG7BF/Rrh/MA+36wTzwAgtQwzAMw4gCC1CFFBcX+12Cr2jXD+aBdv1gHniBBahCYmJ0/7dr1w/mgXb9YB54gTmokIsXL/pdgq9o1w/mgXb9YB54gQWoYRiGYUSB3caikJmZGTZt2uR3Gb6hXT+YB9r1g3lgt7EYUXHhwgW/S/AV7frBPNCuH8wDL7AAVci1a9f8LsFXtOsH80C7fjAPvGBNA1REdorI90WkXUQaRaR6hXVeKyINInJGRFpF5OMiEhPx/htEpE1EzovIV0KnZY17QPNpGzD9YB5o1w/mgRes6TVQEfkO8NfOuedF5C3A/+ecO7RsnQPAuHOuS0SSgG8Dnw19JhXoBJ50zrWJyJ8CM865D6xy/3YNFJifnyc+Pt7vMnxDu34wD7TrB/NgXV0DFZE8oA74QmjRS0CxiJRHruecO+6c6wo9nwVagNLQ2z8GHHfOtYVefxJ47sFWvvFobm72uwRf0a4fzAPt+sE88IK4NdxXMdDvnFsAcM45EekBSoCOlT4gIgXAW4A3hBaVAJE3L3UDW0Qkbmm7yz6fCESOlpwGwV8empmamlLtgXb9YB5o1w/mgRfa1zJA74nQ6db/H/i4c64pys18CPjI8oU2hJVhGIYRIhuIKk3XMkB7iThaFBEheETZs3xFEUkDvgV83Tn3iYi3eoDXRbwuJeKodgX+GxD5+TSgDygCtHZB0+6Bdv1gHmjXD+YB3PBgNNoNrFmAOueGRKQZeBvwPPAM0Oecu+n0baij0LeAbznnfn/ZZr4F/G8RqQxdB/1F4MU77PM6cD1i20tPr0V70Xi9o90D7frBPNCuH8wDuMmDqFnr+0DfA7xHRNqBDwJvBxCRz4rIU6F13gccBt4sIi2hx28BOOeuAe8CviYiHQR/Pf3eGmswDMMwDJ1D+XEf3ZbXO9o90K4fzAPt+sE8AG880DYS0XXgd4k4rasQ7R5o1w/mgXb9YB6ABx6oOgI1DMMwDK/QdgRqGIZhGJ5gAWoYhmEYUWABahiGYRhRoCZAVzMTzEZHRLpF5FzE7UE/6XdNDxIR+V8hzU5E9kcsV9MW7uCBirYgIkki8rXQ//UJEfmnpfG3RSRPRL4VmtnptIg84Xe9D4K7ePCvInIhoh38mt/1PghE5B9F5GRI4yuhSUvu/7vAOafiAXwH+LnQ87cAjX7X5IMH3cB+v+tYQ71PELxX+CbdmtrCHTxQ0RaAJOD13Ogw+UvAv4aefw74ndDzQwRHpYn3u+Y19uBfgTf5XeMaeJAZ8fxp4ETo+X19F6g4Al3tTDDGxsI597Jzri9ymba2sJIHmnDOzTrnvulC35DAUW7M7vQfgT8PrdcIXAaeXPMiHzB38UAFzrmxiJcZgPPiu0BFgLLCTDAEx9Ut8bUqf/hrETklIn8hIrl+F+MD1hZuoLEtvA/4uohsJni0ORDxXjc62sH7gK9HvP5oqB18SUR2+FXUg0ZE/lpEegmOXvfTePBdoCVAjSBPOOdqgFpgBPgrn+sx/ENdWxCRDwPlBGdpUskKHvy0c64SqAFeAf6PX7U9aJxzP+OcKwb+M/AxL7apJUDDM8EA3GkmmI2Mc64n9O888MfA474W5A/WFtDXFkTkN4A3Az/mnJt2zl0BFkJzDi9RygZuB8s9AHDO9Yb+dc65PwV2hI7ONyzOub8CXkPwmvd9fReoCFDn3BCwNBMM3GYmmI2MiKSISGbEoueA4z6V4xvWFvS1BRF5P0GNr1t2LexvgfeG1jkEbAX+bc0LXANW8kBE4kQkP2KdZ4DB0I+LDYOIZIpIYcTrNwFXgPv+LlAzlJ+I7CI4jdpmgpOnvt05d8rXotaQ0LWNl4BYQIAu4H3OuW4/63qQiMingP8AFBD8g7nmnCvX1BZW8gD4EZS0BREpInjWoYsb815ed84dCYXH54HtwBzwS865f/Gn0gfH7TwAXkvwB0MisEjwVP77nXMn/KjzQSEi2wj+WNpEUOcw8BvOuZb7/S5QE6CGYRiG4SUqTuEahmEYhtdYgBqGYRhGFFiAGoZhGEYUWIAahmEYRhRYgBqGYRhGFFiAGoZhGEYUWIAaxn0QmhZs/z1+5leXjYAT7b5fLSI/eof3nxeRX73f/XiJiNSJyJf8rsMwvMAC1DDWnl8lOLDB/fJq4LYBupYsDYd2N5xzTc65DTn3qKEPC1DDeACIyPtDE/S2hP59NLT8t4FC4Euh9/aLSLyIfFREGkLLviwiWaH1nxeRT4nIP4cm/f2KiCSEjnrfC/xU6DO/fZd6/p2I/EBEjotIq4i8M7S8UEQGRSQ5Yt0visgvhJ4fEpHviEhT6LM/EVpeKiJjIvIxEWkmOMdk5P42hWb3OCPBSZz/MbT81SLSEnr+LrkxkXOLiARE5MnQez8tIvUi0iwiL4vIvvv+TzEMr/F7olN72GM9P7jNxNRAbsTzR4C2230G+DDwXyJe/xfgf4eePw/UA8kEh977HvBc6L3fAf74DrU9D/xq6HkWEBt6ng1cBIpCr/8GeHfoeT7BMUJTgUyCY+RuCb2XQ3Cg7a0EB153wM/cZt9PA/8Q8To79O+rgZYV1v8t4B+AOOCHgG8CiaH3Hgda/f6/toc9lj9WddrFMIx75oCI/BbBMTYXgF0issk5N7PCum8CMkKDeQMkEAzZJb7qQrNniEgDUBZFPZuBvxCRilA9m4E9BGek+J/AZ4BPAz8PvOCcmxSR1wM7gL8PTlQRZhfBcVXnuTEZ8XJOAFUi8kmC461+83aFichPExzI+0nn3IKI/DiwD6iP2G/2HfwzDF+wADUMjxGRBOArwGucc40ikg6MExy0e6UAEOCXnXP/eJtNzkY8DxDd3+2fEwyxZ5xzLnTaNQnAOdcgItMi8hrg3cAPR9TV6px71S0Fi5QC0865xZV25pzrEpHdBAcs/2Hg4yt1thKR1wK/TXB+0qWBzgX4K+fch6PQaRhrhl0DNQzvSSJ4FLk0r+AvL3t/AsiIeP014NeWrkOKSLKIVK9iP8u3cyeygIuh8HyC4BFeJP8T+GvgrHOuPbTs+8B2EVkKVELXbBPutrPQDCDOOfcN4DcIhmLxsnX2Ap8D3uSc64946xvA20SkJLRejIjUrVKnYawZFqCGcf/8g4j0LT2AdIKz3jeIyDGCU2VF8r+Azyx1IgI+BjQSPGV5EjgK7F/Ffr8K7F9NJyLgg8BHQx143kHwumokf0fwuuefLi1wzl0lOBXah0Mdgc4AH2V13xt7ge+JyAmC11E/75w7uWyd9wMpwN9EdCSqc869Avwm8NXQ51uBZ1exT8NYU2w6M8MwCB3hfRGovN1pWcMwbsaugRqGckTkswQn2X6XhadhrB47AjUMwzCMKLBroIZhGIYRBRaghmEYhhEFFqCGYRiGEQUWoIZhGIYRBRaghmEYhhEFFqCGYRiGEQUWoIZhGIYRBRaghmEYhhEFFqCGYRiGEQX/DxYjxvpsjpheAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [3, 9, 15, 21, 27]\n",
    "y = [0.327, 0.354, 0.367, 0.365, 0.382]\n",
    "\n",
    "plt.plot(x,y, marker = 'o', color='#7d0552')\n",
    "plt.grid(linestyle = '--', linewidth = 0.5)\n",
    "plt.ylabel('MCC')\n",
    "plt.xlabel('Latent layer size')\n",
    "plt.xlim(0, 30)\n",
    "plt.ylim(0.2, 0.5)\n",
    "plt.savefig(\"latent_size_mcc_iotid20.png\", dpi=150)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "accelerator": "TPU",
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.12"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}