{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\anton.kireyeu\\Downloads\\WinPython-64bit-3.4.4.2\\python-3.4.4.amd64\\lib\\site-packages\\calmap\\__init__.py:294: FutureWarning: how in .resample() is deprecated\n",
      "the new syntax is .resample(...).sum()\n",
      "  by_day = data.resample('D', how=how)\n"
     ]
    },
    {
     "data": {
      "image/png": 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t2jTJ71phMRW3TvXq1bFt2zZ4eXnB2dkZv/76K3788UeYmJgUuG8ltX79egwY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\nXzOhQdkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb9fd8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ygoiIiIiIiIjUiskJIiIiIiIiIlIrJieIiIiIiIiISK2YnCAiIiIiIiIitWJy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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc4a8cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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/fv2grq6OcePG4datWzh58qTCYwqVOacAWfv71q1bWLJkCbp166awPTnPUxMm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\njfmVxpvy+QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb61f400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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REWkVkxNEREREREREFYifnx8UCgXGjBmjtmzOnDlQKBTo379/icbE5AQRERER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\nwwkAAAAAAGAqDicAAAAAAICpfgCcuZeGcgzy1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb50b978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from sqlalchemy import create_engine, text\n",
    "from datetime import timedelta\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as pltt\n",
    "import calmap\n",
    "\n",
    "# setting up a visual style for PyPlot, much better than the standard\n",
    "pltt.style.use('fivethirtyeight')\n",
    "\n",
    "# Your database url as specified in configuration.yaml\n",
    "# If using default settings, it's \\\n",
    "# sqlite:///<path to config dir>/home-assistant_v2.db\n",
    "DB_URL = \"sqlite:///./home-assistant_v3.db\"\n",
    "engine = create_engine(DB_URL)\n",
    "\n",
    "\n",
    "# let's get a list of distinct entity_ids from domain 'device tracker'\n",
    "entitystmt = text(\"select distinct entity_id from states where \\\n",
    "    domain='device_tracker'\")\n",
    "entitiesquery = engine.execute(entitystmt)\n",
    "entitylist = list(entitiesquery.fetchall())\n",
    "\n",
    "\n",
    "# now let's loop through the entitylist to generate plots for each entity\n",
    "for entity in entitylist:\n",
    "\n",
    "    # sql query pulling each state for a given entity, joining in on itself \\\n",
    "    # in order to get the time of next state change\n",
    "    stmt = text(\"select distinct case when t1.state='home' then 1 else 0 end as \\\n",
    "    HomeBit, t1.last_changed, (select  last_changed from states t2 where \\\n",
    "    t2.state_id> t1.state_id and entity_id=:entity_filter order by \\\n",
    "    t2.state_id limit 1) as next_change from states t1 where \\\n",
    "    entity_id=:entity_filter\")\n",
    "\n",
    "    # bind entity parameter to query\n",
    "    stmt = stmt.bindparams(entity_filter=entity[0])\n",
    "\n",
    "    # execute the SQL statement\n",
    "    devicestatesquery = engine.execute(stmt)\n",
    "\n",
    "    # get rows from query into a pandas dataframe\n",
    "    devicestatesDF = pd.DataFrame(devicestatesquery.fetchall())\n",
    "\n",
    "    # name the dataframe rows for usability\n",
    "    devicestatesDF.columns = ['HomeBit',  'last_changed', 'next_change']\n",
    "\n",
    "    # create a dataframe with an index ranging from the min to the max\\\n",
    "    # last_changed timestamp from our query\n",
    "    dates = pd.DataFrame(index=pd.date_range(min(pd.to_datetime(\n",
    "            devicestatesDF['last_changed']).dt.date.unique()),\n",
    "            max(pd.to_datetime(devicestatesDF['last_changed']).dt.date.unique()\n",
    "                )-timedelta(days=1)))\n",
    "\n",
    "    # create a HomeTime column with a zero timedelta value\n",
    "    dates['HomeTime'] = timedelta(days=0)\n",
    "\n",
    "    # create a last_changed_date column with only the date portion of \\\n",
    "    # last_changed value\n",
    "    devicestatesDF['last_changed_date'] = pd.to_datetime(devicestatesDF\n",
    "                                    ['last_changed']).apply(lambda x: x.date())\n",
    "\n",
    "    # grab the index values of our dates dataframe\n",
    "    dateslist_DATE = pd.to_datetime(dates.index.values.tolist())\n",
    "\n",
    "    # start processing for each date\n",
    "    for date in dateslist_DATE:\n",
    "\n",
    "        # create a filtered dataframe where the last_changed_date column \\\n",
    "        # matches the date currently being processed\n",
    "        datedf = devicestatesDF.loc[devicestatesDF['last_changed_date'] ==\n",
    "                                    date.date()]\n",
    "\n",
    "        # the filtered dataframe will retain the indexes, so let's reset them\n",
    "        datedf.reset_index(inplace=True)\n",
    "\n",
    "        # initialize our \"counter\" as a 0 timedelta\n",
    "        datetimehomesum = pd.Timedelta(hours=0, unit='us')\n",
    "\n",
    "        # start processing the filtered dataframe row by row\n",
    "        for item in datedf.index:\n",
    "\n",
    "            # if this is the first row of current day\n",
    "            if item == 0:\n",
    "\n",
    "                # and the first row of this day indicates that the device \\\n",
    "                # wasn't home, it must've been home for whatever time since \\\n",
    "                # the beginning of current day\n",
    "                if datedf.ix[item]['HomeBit'] == 0:\n",
    "                    datetimehomesum += (pd.to_datetime(datedf.ix[item]\n",
    "                        ['last_changed'])-pd.to_datetime(pd.to_datetime\n",
    "                        (datedf.ix[item]['last_changed']).date()))*1\n",
    "\n",
    "                    # if there's more rows to be processed in this day, \\\n",
    "                    # calculate the home value from first timestamp to second\n",
    "                    if len(datedf.index) > 1:\n",
    "                        datetimehomesum += (pd.to_datetime(datedf.ix[item]\n",
    "                            ['next_change'])-pd.to_datetime(datedf.ix[item]\n",
    "                            ['last_changed']))*datedf.ix[item]['HomeBit']\n",
    "\n",
    "                # if the first row of this day indicates that the device was\\\n",
    "                # home, calculatee the home value for the first timestamp as \\\n",
    "                # usual\n",
    "                else:\n",
    "                    datetimehomesum += (pd.to_datetime(datedf.ix[item]\n",
    "                            ['next_change'])-pd.to_datetime(datedf.ix[item]\n",
    "                            ['last_changed']))*datedf.ix[item]['HomeBit']\n",
    "\n",
    "            # if this is the last row of this day, calculate the home value\\\n",
    "            # until beginning of next day\n",
    "            elif item == len(datedf.index)-1:\n",
    "                datetimehomesum += (pd.to_datetime(((pd.to_datetime(datedf.ix\n",
    "                    [item]['last_changed']))+(timedelta(days=1))).date()) -\n",
    "                    pd.to_datetime(datedf.ix[item]['last_changed']))\\\n",
    "                    * datedf.ix[item]['HomeBit']\n",
    "\n",
    "            # otherwise calculate the home value as usual\n",
    "            else:\n",
    "                datetimehomesum += (pd.to_datetime(datedf.ix[item]\n",
    "                    ['next_change'])-pd.to_datetime(datedf.ix[item]\n",
    "                    ['last_changed']))*datedf.ix[item]['HomeBit']\n",
    "\n",
    "        # set the value of our dates dataframe at index of current date\\\n",
    "        # to the calculated home value for this day\n",
    "        dates.loc[date] = datetimehomesum\n",
    "\n",
    "    # convert index of our dates dataframe to datetime\n",
    "    dates.index = pd.to_datetime(dates.index, box=True)\n",
    "\n",
    "    # convert each value in our dates dataframe from an hour timedelta \\\n",
    "    # to a float\n",
    "    dates = dates.apply(lambda x: x/np.timedelta64(1, 'h'))\n",
    "\n",
    "    # create a series from our dates dataframe (necessary for calmap)\n",
    "    datesseries = dates['HomeTime']\n",
    "\n",
    "    # create a calendar map\n",
    "    entityplot = calmap.calendarplot(datesseries, cmap='YlGn', fig_kws=dict(figsize=(15, 3)), \n",
    "                                linecolor='white')\n",
    "\n",
    "    # set the plot title to match our current entity name\n",
    "    entityplot[0].suptitle('Heatmap of hours spent home daily by {}'.format(entity[0]))\n",
    "    pltt.show()\n"
   ]
  }
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