sr_v0.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 510,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from pylab import rcParams\n",
    "\n",
    "import plotly.graph_objects as go\n",
    "import plotly.express as px\n",
    "import numpy as np\n",
    "import os\n",
    "import sys\n",
    "from pathlib import Path\n",
    "import sranodec as anom\n",
    "from sklearn.utils import shuffle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 654,
   "metadata": {},
   "outputs": [],
   "source": [
    "# less than period\n",
    "amp_window_size=100\n",
    "# (maybe) as same as period\n",
    "series_window_size=24\n",
    "# a number enough larger than period\n",
    "score_window_size=100\n",
    "percentile = 95\n",
    "range_ini = 20\n",
    "range_end = 95"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 655,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = pd.read_csv('data/NAB/data/realAWSCloudwatch/ec2_cpu_utilization_53ea38.csv', parse_dates=['timestamp'])\n",
    "df = pd.read_csv('data/NAB/data/realAWSCloudwatch/ec2_cpu_utilization_825cc2.csv', parse_dates=['timestamp'])\n",
    "\n",
    "#df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 656,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_path = Path.cwd()/'data/NAB/data/realAWSCloudwatch/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 657,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_input_dir = os.listdir(input_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 658,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ec2_cpu_utilization_825cc2.csv', 'ec2_cpu_utilization_53ea38.csv', 'ec2_cpu_utilization_c6585a.csv', 'ec2_cpu_utilization_24ae8d.csv', 'ec2_cpu_utilization_77c1ca.csv', 'rds_cpu_utilization_cc0c53.csv', 'ec2_cpu_utilization_fe7f93.csv', 'ec2_cpu_utilization_ac20cd.csv', 'rds_cpu_utilization_e47b3b.csv', 'ec2_cpu_utilization_5f5533.csv']"
      ]
     },
     "execution_count": 658,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_input_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 659,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ec2_cpu_utilization_825cc shape:  (4032, 3)\n",
      "ec2_cpu_utilization_53ea3 shape:  (4032, 3)\n",
      "ec2_cpu_utilization_c6585 shape:  (4032, 3)\n",
      "ec2_cpu_utilization_24ae8 shape:  (4032, 3)\n",
      "ec2_cpu_utilization_77c1c shape:  (4032, 3)\n",
      "rds_cpu_utilization_cc0c5 shape:  (4032, 3)\n",
      "ec2_cpu_utilization_fe7f9 shape:  (4032, 3)\n",
      "ec2_cpu_utilization_ac20c shape:  (4032, 3)\n",
      "rds_cpu_utilization_e47b3 shape:  (4032, 3)\n",
      "ec2_cpu_utilization_5f553 shape:  (4032, 3)\n"
     ]
    }
   ],
   "source": [
    "input_signal = []\n",
    "for i in list_input_dir:\n",
    "    aux = pd.read_csv(input_path/i, parse_dates=['timestamp'])\n",
    "    ########################### simulate inputation ###########################\n",
    "    aux_signal = pd.DataFrame()\n",
    "    aux_signal['datetime'] = aux.timestamp\n",
    "    aux_signal['cpu'] = aux.value\n",
    "    aux_signal['mem'] = aux.value * np.ravel(np.random.rand(1, 4032))\n",
    "    print(i[:-5], \"shape: \", aux_signal.shape)\n",
    "    ############################################################################\n",
    "    input_signal.append(aux_signal)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 660,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 660,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "input_signal[0].mem.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 661,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jfialho/.local/lib/python3.7/site-packages/sranodec/util.py:31: RuntimeWarning:\n",
      "\n",
      "invalid value encountered in double_scalars\n",
      "\n"
     ]
    }
   ],
   "source": [
    "score_cpu = []\n",
    "score_mem = []\n",
    "\n",
    "index_changes_cpu = []\n",
    "index_changes_mem = []\n",
    "\n",
    "anomaly_cadidates_cpu = []\n",
    "anomaly_cadidates_mem = []\n",
    "\n",
    "spec = anom.Silency(amp_window_size, series_window_size, score_window_size)\n",
    "\n",
    "for i in range(len(input_signal)):\n",
    "    #score_aux = pd.DataFrame()\n",
    "    #score_aux[\"cpu\"] = spec.generate_anomaly_score(input_signal[i].cpu.values)\n",
    "    #score_aux[\"mem\"] = spec.generate_anomaly_score(input_signal[i].mem.values)\n",
    "    \n",
    "    #index_changes_aux = pd.DataFrame()\n",
    "    #index_changes_aux[\"cpu\"] = np.where(score_aux[\"cpu\"].values > np.percentile(score_aux[\"cpu\"].values, 90))[0]\n",
    "    #index_changes_aux[\"mem\"] = np.where(score_aux[\"mem\"].values > np.percentile(score_aux[\"mem\"].values, 90))[0]\n",
    "    \n",
    "    #score.append(score_aux)\n",
    "    #index_changes.append(index_changes_aux)\n",
    "    \n",
    "    score_aux_cpu = spec.generate_anomaly_score(input_signal[i].cpu.values)\n",
    "    score_aux_mem = spec.generate_anomaly_score(input_signal[i].mem.values)\n",
    "    \n",
    "    index_changes_aux_cpu = np.where(score_aux_cpu > np.percentile(score_aux_cpu, percentile))[0]\n",
    "    index_changes_aux_mem = np.where(score_aux_mem > np.percentile(score_aux_mem, percentile))[0]\n",
    "    \n",
    "    aux_anomaly_cadidates_cpu = pd.DataFrame(index=index_changes_aux_cpu)\n",
    "    aux_anomaly_cadidates_mem = pd.DataFrame(index=index_changes_aux_mem)\n",
    "    \n",
    "    #aux_anomaly_cadidates_cpu['cpu'] = input_signal[i].loc[index_changes_aux_cpu,'cpu']\n",
    "    #aux_anomaly_cadidates_mem['mem'] = input_signal[i].loc[index_changes_aux_mem,'mem']\n",
    "\n",
    "    aux_anomaly_cadidates_cpu['cpu'] = input_signal[i].loc[index_changes_aux_cpu,'cpu']\n",
    "    aux_anomaly_cadidates_mem['mem'] = input_signal[i].loc[index_changes_aux_mem,'mem']\n",
    "    \n",
    "    score_cpu.append(score_aux_cpu)\n",
    "    index_changes_cpu.append(index_changes_aux_cpu)\n",
    "    \n",
    "    score_mem.append(score_aux_mem)\n",
    "    index_changes_mem.append(index_changes_aux_mem)\n",
    "    \n",
    "    anomaly_cadidates_cpu.append(aux_anomaly_cadidates_cpu)\n",
    "    anomaly_cadidates_mem.append(aux_anomaly_cadidates_mem)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 662,
   "metadata": {},
   "outputs": [],
   "source": [
    "final = pd.DataFrame(index=index_changes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 663,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jfialho/.local/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning:\n",
      "\n",
      "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",
      "\n"
     ]
    },
    {
     "ename": "IndexError",
     "evalue": "too many indices for array: array is 1-dimensional, but 10 were indexed",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-663-7d33ab195bc5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfinal\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cpu'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest_signal\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindex_changes\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m: too many indices for array: array is 1-dimensional, but 10 were indexed"
     ]
    }
   ],
   "source": [
    "final['cpu'] = test_signal[index_changes]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 664,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'cpu'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/.local/lib/python3.7/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   3080\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3081\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[0mcasted_key\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   3082\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\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: 'cpu'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-664-2ffc97b43b24>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mfinal2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfinal\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mfinal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'cpu'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbetween\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m90\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[0m\u001b[1;32m      2\u001b[0m \u001b[0;31m#final2 = final[~((final.cpu > 20) & (final.cpu < 90))]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m    887\u001b[0m                     \u001b[0;31m# AttributeError for IntervalTree get_value\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    888\u001b[0m                     \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_value\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtakeable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_takeable\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 889\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\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    890\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    891\u001b[0m             \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m   1058\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTuple\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   1059\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0msuppress\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mIndexingError\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-> 1060\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\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   1061\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1062\u001b[0m         \u001b[0;31m# no multi-index, so validate all of the indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_lowerdim\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m    789\u001b[0m         \u001b[0;31m# we may have a nested tuples indexer here\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    790\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_nested_tuple_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\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--> 791\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_nested_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\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    792\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    793\u001b[0m         \u001b[0;31m# we maybe be using a tuple to represent multiple dimensions here\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_nested_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m    863\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    864\u001b[0m             \u001b[0mcurrent_ndim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 865\u001b[0;31m             \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\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    866\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[1;32m    867\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1122\u001b[0m         \u001b[0;31m# fall thru to straight lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1123\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1124\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\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   1125\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1126\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_slice_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mslice_obj\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mslice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\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~/.local/lib/python3.7/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_label\u001b[0;34m(self, label, axis)\u001b[0m\n\u001b[1;32m   1071\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\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   1072\u001b[0m         \u001b[0;31m# GH#5667 this will fail if the label is not present in the axis.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1073\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\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   1074\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1075\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_handle_lowerdim_multi_index_axis0\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mTuple\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~/.local/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mxs\u001b[0;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[1;32m   3722\u001b[0m         \u001b[0;32mif\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3723\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mdrop_level\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3724\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\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   3725\u001b[0m             \u001b[0mindex\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3726\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3022\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3023\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[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3024\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[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3025\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3026\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[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.7/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   3081\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[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3082\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3083\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3084\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3085\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtolerance\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'cpu'"
     ]
    }
   ],
   "source": [
    "final2 = final[~final.loc[:, 'cpu'].between(20, 90)]\n",
    "#final2 = final[~((final.cpu > 20) & (final.cpu < 90))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 665,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x72 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x72 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for j in range(2):\n",
    "    fig, axs = plt.subplots(1, 5, figsize=(12, 1), sharey=True)\n",
    "    for i in range(5):\n",
    "        axs[i].hist(anomaly_cadidates_cpu[int(j*i)],bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 666,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsgAAABVCAYAAABUzBLCAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAH8klEQVR4nO3dzatcZx0H8O/PVjdasDUxlFq4CqGQlUrQgm5ElNYu0oWILmoWlWwsKLgJ+g905UIQoWBJBFEElQa60BoEcaH0Rqp9s7aVFlvSpkVQd1p4XMykHm7ueJ/cOy9n5n4+MNw5Z17O85z55uQ3z5yXaq0FAACYeMeqGwAAAGOiQAYAgAEFMgAADCiQAQBgQIEMAAADNy5zYUeOHGlbW1vLXCQLcunSpTdba0cX8d5ysllkhR5yQi9ZocdBc7LUAnlrayvb29vLXCQLUlUvL+q95WSzyAo95IReskKPg+bELhYAADCgQCZbZx/N1tlHV90MRk5O6CUr9JATeq0iKwpkAAAYUCADAMCAAhkAAAYUyAAAMKBABgCAgZUXyI5ipZes0ENO6CUr9JCTw2nlBTIAAIyJAhkAAAYUyAAAMKBABgCAAQUyAAAM7FkgV9XtVfXrqnqmqp6uqq9N599SVY9V1fPTvzcvvrkAALBYPSPIbyX5RmvtRJI7k3y1qk4kOZvkYmvteJKL02kAAFhrexbIrbXLrbU/TO//K8mzSW5LcirJ+enTzie5d0FtBACApbmufZCraivJR5L8Psmx1trl6UOvJTk24zVnqmq7qrbfeOONg7SVDSYn9JIVesgJvWSF3XQXyFX1niQ/TfL11to/h4+11lqSttvrWmsPtdZOttZOHj169ECNZXPJCb1khR5yQi9ZYTddBXJVvTOT4viHrbWfTWe/XlW3Th+/NcmVxTSRZXE5TXrICb1khR5yQq9lZqXnLBaV5PtJnm2tfXvw0IUkp6f3Tyd5ZP7NAwCA5bqx4zmfSHJfkier6onpvG8meTDJT6rq/iQvJ/nCQloIAABLtGeB3Fr7bZKa8fCn59sclmnWzxRX57/04D3LbA4jJSf0khV67JWTRFaYWOU2xZX0AABgoGcXi6Uy0kAvWaGHnNBLVuhhpPtwMIIMAAADCmQAABhQIAMAwIACGQAABhTIAAAwMLqzWFzlaGJ6yQo9HHlOL9sUesnK5jKCDAAAA6MZQZ51tRTYSVboISf0khV6yMnhMpoCmeW4nn/gfjo63HqzYtcFrjcrcnI4+f+HXmPYptjFAgAABhTIAAAwoEAGAIABBTIAAAwokAEAYECBDAAAAwpkAAAYcB7kQ8IJzuklK/SQE3rJCj3GlhMjyAAAMGAEecON7RsZ4yUr9JATeskKPcaaEyPIAAAwoEAGAIABBfKG2Tr76Gh/rmBcZIUeckIvWaHHuuREgQwAAAOjP0hv+C3jpQfvWWFLGLurWZET9iIr9JATesnK5jGCDAAAA6MfQd7Nzm9qm/bNbT/92bk/zzrs37Nos3IynLfurjcru+VCVg7PNiXZf1bkxDZlr9fMmj6MbFP+/2t2mx6bA40gV9VdVfVcVb1QVWfn1SgAAFiVfY8gV9UNSb6b5DNJXknyeFVdaK09M6/G7bRu3z6WwTq4lpxcyzrYnaxcyzq4lpxcyzrYnaxca13XwUFGkD+W5IXW2l9ba/9O8uMkp+bTLAAAWI1qre3vhVWfT3JXa+0r0+n7kny8tfbAjuedSXJmOnlHkud2vNWRJG/uqxHjt8l9u6O1dtO83qwjJ8lmr89N7tuys7LJ63KT+2abMl+b3DfblPnZ5L4dKCcLL5A73me7tXZyX40YOX1b/2Uui76t7/KWSd/Wf5nLom/ru7xl0rfZDrKLxatJbh9Mf2A6DwAA1tZBCuTHkxyvqg9W1buSfDHJhfk0CwAAVmPfZ7Forb1VVQ8k+UWSG5I83Fp7eh9v9dB+27AG9G39l7ks+ra+y1smfVv/ZS6Lvq3v8pZJ32bY9z7IAACwiVxqGgAABhTIAAAwsLICeRMvU11VL1XVk1X1RFVtT+fdUlWPVdXz0783r7qdParq4aq6UlVPDebt2pea+M70s/xTVX10zm3ZqKzIyWJyMl2GrIzUmLIiJ+M1ppxMlyErI7XorKykQK7/Xab67iQnknypqk6soi0L8KnW2ocH5947m+Ria+14kovT6XVwLsldO+bN6svdSY5Pb2eSfG9ejdjgrMjJHHOSyMoaOJcRZEVORu9cRpCTRFbWwLksMCurGkE+TJepPpXk/PT++ST3rq4p/Vprv0ny9x2zZ/XlVJIftInfJXlvVd06p6YclqzIycHJyoiNKCtyMmIjykkiK6O26KysqkC+LcnfBtOvTOetu5bkl1V1qSaXrkySY621y9P7ryU5tpqmzcWsvizy89zErMjJxLw/S1lZP7Yp8yEnE7Ype5OViT0/y32fB5ldfbK19mpVvT/JY1X15+GDrbVWVRtxXr1N6ssKyAm9ZIUeckIvWem0qhHkjbxMdWvt1enfK0l+nsnPM69fHcaf/r2yuhYe2Ky+LPLz3LisyMnb5v1Zysr6sU2ZAzl5m23KHmTlbXt+lqsqkDfuMtVV9e6quunq/SSfTfJUJv06PX3a6SSPrKaFczGrLxeSfHl6lOidSf4x+InjoDYqK3KysJwksrKObFMOSE5sU3rJynVmpbW2kluSzyX5S5IXk3xrVe2YY38+lOSP09vTV/uU5H2ZHEn5fJJfJbll1W3t7M+PklxO8p9M9tW5f1ZfklQmR/q+mOTJJCdlRU6WnRNZGfdtTFmRk/HexpQTWRn3bdFZcalpAAAYcCU9AAAYUCADAMCAAhkAAAYUyAAAMKBABgCAAQUyAAAMKJABAGDgvz1v1Pu9UQpFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x72 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x72 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for j in range(2):\n",
    "    fig, axs = plt.subplots(1, 5, figsize=(12, 1), sharey=True)\n",
    "    for i in range(5):\n",
    "        axs[i].hist(anomaly_cadidates_mem[int(j*i)],bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 667,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "aux=0\n",
    "for j in range(5):\n",
    "    fig, axs = plt.subplots(1, 2, figsize=(17, 5), sharey=True)\n",
    "    for i in range(2):\n",
    "        axs[i].scatter(anomaly_cadidates_cpu[aux][~anomaly_cadidates_cpu[aux].loc[:, 'cpu'].between(range_ini, range_end)].index.tolist(),\n",
    "                    anomaly_cadidates_cpu[aux][~anomaly_cadidates_cpu[aux].loc[:, 'cpu'].between(range_ini, range_end)].values,\n",
    "                    label='anomaly',s=5,c='red',zorder=10\n",
    "                   )\n",
    "        axs[i].plot(input_signal[aux].index.tolist(),\n",
    "                    input_signal[aux].cpu, label='observation',alpha=0.5,zorder=1\n",
    "                   )\n",
    "\n",
    "        aux+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 668,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1224x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "aux=0\n",
    "for j in range(5):\n",
    "    fig, axs = plt.subplots(1, 2, figsize=(17, 5), sharey=True)\n",
    "    for i in range(2):\n",
    "        axs[i].scatter(anomaly_cadidates_mem[aux][~anomaly_cadidates_mem[aux].loc[:, 'mem'].between(range_ini, range_end)].index.tolist(),\n",
    "                    anomaly_cadidates_mem[aux][~anomaly_cadidates_mem[aux].loc[:, 'mem'].between(range_ini, range_end)].values,\n",
    "                    label='anomaly',s=5,c='red',zorder=10\n",
    "                   )\n",
    "        axs[i].plot(input_signal[aux].index.tolist(),\n",
    "                    input_signal[aux].mem, label='observation',alpha=0.5,zorder=1\n",
    "                   )\n",
    "\n",
    "        aux+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 503,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
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                       {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('76c887a9-8fed-4c4e-b5ae-781504b87d25');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = go.Figure()\n",
    "\n",
    "fig.add_trace(go.Scatter(\n",
    "    y=test_signal,\n",
    "    name='observation',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Scatter(\n",
    "    x = final2.index.tolist(),\n",
    "    y=np.array(final2.cpu),\n",
    "    name='anomaly',\n",
    "    mode='markers'\n",
    "))\n",
    "\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "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>cpu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1.998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1.990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3974</th>\n",
       "      <td>1.996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3980</th>\n",
       "      <td>1.994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4016</th>\n",
       "      <td>1.992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4022</th>\n",
       "      <td>1.966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4028</th>\n",
       "      <td>1.972</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>404 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        cpu\n",
       "2     1.960\n",
       "8     2.026\n",
       "20    1.998\n",
       "32    1.990\n",
       "38    2.000\n",
       "...     ...\n",
       "3974  1.996\n",
       "3980  1.994\n",
       "4016  1.992\n",
       "4022  1.966\n",
       "4028  1.972\n",
       "\n",
       "[404 rows x 1 columns]"
      ]
     },
     "execution_count": 326,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 635,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n",
      "6\n",
      "7\n",
      "8\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "aux=0\n",
    "for j in range(5):\n",
    "    for i in range(2):\n",
    "        print(aux)\n",
    "        aux+=1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": []
  }
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