OpenStudio_to_EnergyPlusAPI.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style='font-size: 200%; font-weight: bold; color: #45AED6;'>Python: using OpenStudio Bindings, EnergyPlus API, and matplotlib</span>\n",
    "\n",
    "<p style=\"font-size: 130%; font-weight: bold; font-family: 'Roboto', sans-serif;\">Written By Julien Marrec of <a href=\"https://effibem.com\"><span style=\"color: #45AED6;\">EffiBEM</span></a>, circa 2021-01-05</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Purpose\n",
    "\n",
    "This notebook aims to demonstrate the use of:\n",
    "\n",
    "* **The OpenStudio Python Bindings**.\n",
    "    * This is used to efficiently create and customize a model to be simulated\n",
    "\n",
    "    * **Note**: Until a version > 3.1.0 (eg 3.1.1 or 3.2.0) is out on [**pypi**](https://pypi.org/project/openstudio/), I recommend using the [**testpypi**](https://test.pypi.org/project/openstudio/) version where I made usability adjustments. You can do `pip install -i https://test.pypi.org/simple/ openstudio` for that one.\n",
    "    \n",
    "    \n",
    "* **The EnergyPlus Python API**, and how to use callbacks to retrieve data\n",
    "\n",
    "* **Updating a live matplotlib plot during E+ simulation** via the EnergyPlus Python API callback.\n",
    "\n",
    "\n",
    "Several options and examples are shown below. **I strongly recommend you encapsulate your data inside a class** (see section 3.4) instead of relying on python `global` data, but it does bring a sligthly higher complexity level so for simple stuff you can ommit that and use 3.1 to 3.3 instead (which are also used as an entry point to demonstrate the API)\n",
    "\n",
    "----\n",
    "\n",
    "**Resources:**\n",
    "\n",
    "* OpenStudio SDK documentation: https://openstudio-sdk-documentation.s3.amazonaws.com/index.html\n",
    "* EnergyPlus Python API documentation: https://energyplus.readthedocs.io/en/latest/api.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/interactive_plot.gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Top level imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "# or nbagg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import shutil\n",
    "import sys\n",
    "import datetime\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clean up artifacts (optional)\n",
    "if os.path.exists('test.idf'):\n",
    "    os.remove('test.idf')\n",
    "    \n",
    "if os.path.exists('out/'):\n",
    "    shutil.rmtree('out/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Use OpenStudio to create a Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import openstudio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pip package used initially: openstudio                        3.1.1a15\n",
      "OpenStudio Long Version:    3.1.1-alpha+70eedb538e\n"
     ]
    }
   ],
   "source": [
    "# For reproducibility, here are the versions I used to create and run this notebook\n",
    "_s = !pip list\n",
    "print(f\"Pip package used initially: {[x for x in _s if 'openstudio' in x][0]}\")\n",
    "print(f\"OpenStudio Long Version:    {openstudio.openStudioLongVersion()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create an example model\n",
    "\n",
    "This is an openstudio built in example model, which is a shoebox with 4 spaces inside a single thermal zone.\n",
    "\n",
    "If you are curious to see what the model contains, refer to the source code here in [Model.cpp#L1333](https://github.com/NREL/OpenStudio/blob/f4ba8ce3dbce2338589fb8a28979cd30d8ed0fe9/src/model/Model.cpp#L1333) (or use the [OpenStudioApplication](https://github.com/openstudiocoalition/OpenStudioApplication) to browse it)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = openstudio.model.exampleModel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set output variables\n",
    "\n",
    "We remove all existing ones (the `exampleModel()` creates a few), and add a few we care about"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(<openstudio.openstudioutilitiesidf.IdfObject; proxy of <Swig Object of type 'openstudio::IdfObject *' at 0x7f546fa042d0> >,),\n",
       " (<openstudio.openstudioutilitiesidf.IdfObject; proxy of <Swig Object of type 'openstudio::IdfObject *' at 0x7f546fa048d0> >,),\n",
       " (<openstudio.openstudioutilitiesidf.IdfObject; proxy of <Swig Object of type 'openstudio::IdfObject *' at 0x7f546fa049c0> >,),\n",
       " (<openstudio.openstudioutilitiesidf.IdfObject; proxy of <Swig Object of type 'openstudio::IdfObject *' at 0x7f546fa04a20> >,)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x.remove() for x in m.getOutputVariables()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o = openstudio.model.OutputVariable(\"Site Outdoor Air Drybulb Temperature\", m)\n",
    "o.setKeyValue(\"Environment\")\n",
    "o.setReportingFrequency(\"Timestep\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "for var in [\"Zone Mean Air Temperature\",\n",
    "            \"Zone Thermostat Heating Setpoint Temperature\",\n",
    "            \"Zone Thermostat Cooling Setpoint Temperature\"]:\n",
    "    o = openstudio.model.OutputVariable(var, m)\n",
    "    #o.setKeyValue(openstudio.model.getThermalZones(m)[0].nameString())\n",
    "    o.setReportingFrequency(\"Timestep\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:Output:Variable,\n",
      "  {c0e5b2e1-5f55-41e0-b1dd-62309d077303}, !- Handle\n",
      "  Output Variable 4,                      !- Name\n",
      "  ,                                       !- Key Value\n",
      "  Zone Thermostat Cooling Setpoint Temperature, !- Variable Name\n",
      "  Timestep;                               !- Reporting Frequency\n",
      "\n",
      "\n",
      "OS:Output:Variable,\n",
      "  {40eb80e2-4fdc-40e4-9aa2-e080c4cdeeaa}, !- Handle\n",
      "  Output Variable 3,                      !- Name\n",
      "  ,                                       !- Key Value\n",
      "  Zone Thermostat Heating Setpoint Temperature, !- Variable Name\n",
      "  Timestep;                               !- Reporting Frequency\n",
      "\n",
      "\n",
      "OS:Output:Variable,\n",
      "  {f227c373-46ac-4125-8d52-9af913a954dd}, !- Handle\n",
      "  Output Variable 2,                      !- Name\n",
      "  ,                                       !- Key Value\n",
      "  Zone Mean Air Temperature,              !- Variable Name\n",
      "  Timestep;                               !- Reporting Frequency\n",
      "\n",
      "\n",
      "OS:Output:Variable,\n",
      "  {fe7ce65f-c35c-451b-8383-f68bd5f9ce43}, !- Handle\n",
      "  Output Variable 1,                      !- Name\n",
      "  Environment,                            !- Key Value\n",
      "  Site Outdoor Air Drybulb Temperature,   !- Variable Name\n",
      "  Timestep;                               !- Reporting Frequency\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[None, None, None, None]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[print(x) for x in m.getOutputVariables()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set timestep to 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:Timestep,\n",
      "  {9b9872c1-27db-4cb3-87fc-43b2628b7943}, !- Handle\n",
      "  6;                                      !- Number of Timesteps per Hour\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "timestep = m.getTimestep()\n",
    "print(timestep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:Timestep,\n",
      "  {9b9872c1-27db-4cb3-87fc-43b2628b7943}, !- Handle\n",
      "  4;                                      !- Number of Timesteps per Hour\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "timestep.setNumberOfTimestepsPerHour(4)\n",
    "print(timestep)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check the heating thermostat schedule\n",
    "\n",
    "This is unused after, serves as a demo of how the OS SDK API works"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Object of type 'OS:Schedule:Ruleset' and named 'Medium Office Heating Setpoint Schedule'\n"
     ]
    }
   ],
   "source": [
    "z = m.getThermalZones()[0]\n",
    "t = z.thermostatSetpointDualSetpoint().get()\n",
    "heating_sch = t.heatingSetpointTemperatureSchedule().get()\n",
    "o = heating_sch.to_ScheduleRuleset()\n",
    "if o.is_initialized():\n",
    "    heating_sch = o.get()\n",
    "    print(heating_sch.briefDescription())\n",
    "else:\n",
    "    print(heating_sch.briefDescription())\n",
    "#heating_sch = openstudio.model.toScheduleRuleset(heating_sch).get()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:Schedule:Day,\n",
      "  {bc2f9235-9880-4bb8-8364-2d5e79cbe2fa}, !- Handle\n",
      "  Medium Office Heating Setpoint All Other Days Schedule, !- Name\n",
      "  {9dd62a41-f89d-4834-99b3-4e496043b5a5}, !- Schedule Type Limits Name\n",
      "  ,                                       !- Interpolate to Timestep\n",
      "  24,                                     !- Hour 1\n",
      "  0,                                      !- Minute 1\n",
      "  15.6;                                   !- Value Until Time 1\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(heating_sch.defaultDaySchedule())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:Schedule:Rule,\n",
      "  {0dad2926-1f3e-4f11-a51c-99e972bba3cf}, !- Handle\n",
      "  Medium Office Heating Setpoint Schedule Saturday Rule, !- Name\n",
      "  {ffb27c65-5e7b-4433-8907-e8543c3fa8e7}, !- Schedule Ruleset Name\n",
      "  0,                                      !- Rule Order\n",
      "  {3ad7abfd-2daa-4d10-acc3-c8a3f05adb99}, !- Day Schedule Name\n",
      "  ,                                       !- Apply Sunday\n",
      "  ,                                       !- Apply Monday\n",
      "  ,                                       !- Apply Tuesday\n",
      "  ,                                       !- Apply Wednesday\n",
      "  ,                                       !- Apply Thursday\n",
      "  ,                                       !- Apply Friday\n",
      "  Yes;                                    !- Apply Saturday\n",
      "\n",
      "\n",
      "OS:Schedule:Rule,\n",
      "  {f231912d-410d-4609-8eb5-90d092af77d5}, !- Handle\n",
      "  Medium Office Heating Setpoint Schedule Weekdays Rule, !- Name\n",
      "  {ffb27c65-5e7b-4433-8907-e8543c3fa8e7}, !- Schedule Ruleset Name\n",
      "  1,                                      !- Rule Order\n",
      "  {16532f91-d407-4a04-a2d0-c8225a7914b9}, !- Day Schedule Name\n",
      "  ,                                       !- Apply Sunday\n",
      "  Yes,                                    !- Apply Monday\n",
      "  Yes,                                    !- Apply Tuesday\n",
      "  Yes,                                    !- Apply Wednesday\n",
      "  Yes,                                    !- Apply Thursday\n",
      "  Yes;                                    !- Apply Friday\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[None, None]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[print(x) for x in heating_sch.scheduleRules()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Restrict to one month of simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:RunPeriod,\n",
      "  {ee1c1160-0e81-4a60-ac03-1c67489fa907}, !- Handle\n",
      "  Run Period 1,                           !- Name\n",
      "  1,                                      !- Begin Month\n",
      "  1,                                      !- Begin Day of Month\n",
      "  12,                                     !- End Month\n",
      "  31,                                     !- End Day of Month\n",
      "  No,                                     !- Use Weather File Holidays and Special Days\n",
      "  No,                                     !- Use Weather File Daylight Saving Period\n",
      "  No,                                     !- Apply Weekend Holiday Rule\n",
      "  Yes,                                    !- Use Weather File Rain Indicators\n",
      "  Yes,                                    !- Use Weather File Snow Indicators\n",
      "  1;                                      !- Number of Times Runperiod to be Repeated\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "r = m.getRunPeriod()\n",
    "print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r.setEndMonth(1)\n",
    "r.setEndDayOfMonth(31)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OS:RunPeriod,\n",
      "  {ee1c1160-0e81-4a60-ac03-1c67489fa907}, !- Handle\n",
      "  Run Period 1,                           !- Name\n",
      "  1,                                      !- Begin Month\n",
      "  1,                                      !- Begin Day of Month\n",
      "  2,                                      !- End Month\n",
      "  28,                                     !- End Day of Month\n",
      "  No,                                     !- Use Weather File Holidays and Special Days\n",
      "  No,                                     !- Use Weather File Daylight Saving Period\n",
      "  No,                                     !- Apply Weekend Holiday Rule\n",
      "  Yes,                                    !- Use Weather File Rain Indicators\n",
      "  Yes,                                    !- Use Weather File Snow Indicators\n",
      "  1;                                      !- Number of Times Runperiod to be Repeated\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Forward translate to IDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ft = openstudio.energyplus.ForwardTranslator()\n",
    "w = ft.translateModel(m)\n",
    "w.save(openstudio.path('test.idf'), True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RunPeriod,\r\n",
      "  Run Period 1,                           !- Name\r\n",
      "  1,                                      !- Begin Month\r\n",
      "  1,                                      !- Begin Day of Month\r\n",
      "  2009,                                   !- Begin Year\r\n",
      "  1,                                      !- End Month\r\n",
      "  31,                                     !- End Day of Month\r\n",
      "  2009,                                   !- End Year\r\n",
      "  Thursday,                               !- Day of Week for Start Day\r\n",
      "  No,                                     !- Use Weather File Holidays and Special Days\r\n",
      "  No,                                     !- Use Weather File Daylight Saving Period\r\n",
      "  No,                                     !- Apply Weekend Holiday Rule\r\n",
      "  Yes,                                    !- Use Weather File Rain Indicators\r\n",
      "  Yes;                                    !- Use Weather File Snow Indicators\r\n"
     ]
    }
   ],
   "source": [
    "!grep -A13 RunPeriod test.idf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run EnergyPlus in API mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# insert the repo build tree or install path into the search Path, then import the EnergyPlus API\n",
    "sys.path.insert(0, '/usr/local/EnergyPlus-9-4-0/')\n",
    "from pyenergyplus.api import EnergyPlusAPI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyenergyplus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.2'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pyenergyplus.api.EnergyPlusAPI.api_version()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Plot\n",
    "\n",
    "We expect the outdoor air temp to be more extreme than indoor air temperature, so we can get the bounds from the EPW, here I manually found it to be fine if I set it at -25°C to 40°C, but I could have parsed the EPW instead"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.86 s, sys: 75.9 ms, total: 1.94 s\n",
      "Wall time: 1.97 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "x = []\n",
    "y_outdoor = []\n",
    "y_zone = []\n",
    "y_htg = []\n",
    "y_clg = []\n",
    "\n",
    "years = []\n",
    "months = []\n",
    "days = []\n",
    "hours = []\n",
    "minutes = []\n",
    "current_times = []\n",
    "actual_date_times = []\n",
    "actual_times = []\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 4), num='Real time plot')\n",
    "h1, = ax.plot(x, y_outdoor, label=\"Outdoor Air Temp\")\n",
    "h2, = ax.plot(x, y_zone, label=\"Zone Temperature\")\n",
    "h_htg, = ax.plot(x, y_htg, label='Zone Heating Tstat', linestyle='--', color='r', linewidth=0.5)\n",
    "h_clg, = ax.plot(x, y_clg, label='Zone Cooling Tstat', linestyle='--', color='blue', linewidth=0.5)\n",
    "\n",
    "ax.set_title('Temperatures')\n",
    "ax.set_xlabel('Zone time step index')\n",
    "ax.set_ylabel('Temperature [C]')\n",
    "ax.legend(loc='lower right')\n",
    "ax.set_ylim(-25, 40)\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "# plt.show(False)\n",
    "#plt.draw()\n",
    "    \n",
    "\n",
    "filename_to_run = 'test.idf'\n",
    "zone_name = openstudio.model.getThermalZones(m)[0].nameString()\n",
    "got_handles = False\n",
    "oa_temp_handle = -1\n",
    "zone_temp_handle = -1\n",
    "zone_htg_tstat_handle = -1\n",
    "zone_clg_tstat_handle = -1\n",
    "count = 0\n",
    "plot_update_interval = 250  # time steps\n",
    "\n",
    "def update_line():\n",
    "    \n",
    "    \n",
    "    #hl.set_data(x, y_outdoor)\n",
    "    #h2.set_data(x, y_zone)\n",
    "    \n",
    "    h1.set_xdata(x)\n",
    "    h1.set_ydata(y_outdoor)\n",
    "    h2.set_xdata(x)\n",
    "    h2.set_ydata(y_zone)\n",
    "    h_htg.set_xdata(x)\n",
    "    h_htg.set_ydata(y_htg)\n",
    "    h_clg.set_xdata(x)\n",
    "    h_clg.set_ydata(y_clg)\n",
    "    \n",
    "    ax.set_xlim(x[0], x[-1])\n",
    "    #ax.set_ylim(min(y_outdoor + y_zone), max(y_outdoor + y_zone))\n",
    "    #ax.autoscale_view()\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "\n",
    "\n",
    "def callback_function(state_argument):\n",
    "    global count, got_handles, oa_temp_handle, zone_temp_handle, zone_htg_tstat_handle, zone_clg_tstat_handle\n",
    "    if not got_handles:\n",
    "        if not api.exchange.api_data_fully_ready(state_argument):\n",
    "            return\n",
    "        oa_temp_handle = api.exchange.get_variable_handle(state_argument, u\"SITE OUTDOOR AIR DRYBULB TEMPERATURE\", u\"ENVIRONMENT\")\n",
    "        zone_temp_handle = api.exchange.get_variable_handle(state_argument, \"Zone Mean Air Temperature\", zone_name)\n",
    "        zone_htg_tstat_handle = api.exchange.get_variable_handle(state_argument, \"Zone Thermostat Heating Setpoint Temperature\", zone_name)\n",
    "        zone_clg_tstat_handle = api.exchange.get_variable_handle(state_argument, \"Zone Thermostat Cooling Setpoint Temperature\", zone_name)\n",
    "\n",
    "        if -1 in [oa_temp_handle, zone_temp_handle, zone_htg_tstat_handle, zone_clg_tstat_handle]:\n",
    "            \n",
    "            print(\"***Invalid handles, check spelling and sensor/actuator availability\")\n",
    "            sys.exit(1)\n",
    "        got_handles = True\n",
    "    if api.exchange.warmup_flag(state_argument):\n",
    "        return\n",
    "    count += 1\n",
    "    #x.append(count)\n",
    "    oa_temp = api.exchange.get_variable_value(state_argument, oa_temp_handle)\n",
    "    y_outdoor.append(oa_temp)\n",
    "    zone_temp = api.exchange.get_variable_value(state_argument, zone_temp_handle)\n",
    "    y_zone.append(zone_temp)\n",
    "    \n",
    "    zone_htg_tstat = api.exchange.get_variable_value(state_argument, zone_htg_tstat_handle)\n",
    "    y_htg.append(zone_htg_tstat)\n",
    "    \n",
    "    zone_clg_tstat = api.exchange.get_variable_value(state_argument, zone_clg_tstat_handle)\n",
    "    y_clg.append(zone_clg_tstat)\n",
    "    \n",
    "    \n",
    "    year = api.exchange.year(state)\n",
    "    month = api.exchange.month(state)\n",
    "    day = api.exchange.day_of_month(state)\n",
    "    hour = api.exchange.hour(state)\n",
    "    minute = api.exchange.minutes(state)\n",
    "    current_time = api.exchange.current_time(state)\n",
    "    actual_date_time = api.exchange.actual_date_time(state)\n",
    "    actual_time = api.exchange.actual_time(state)\n",
    "                    \n",
    "    # Year is bogus, seems to be reading the weather file year instead...         \n",
    "    # So harcode it to 2009\n",
    "    year = 2009\n",
    "    years.append(year)\n",
    "    months.append(month)\n",
    "    days.append(day)\n",
    "    hours.append(hour)\n",
    "    minutes.append(minute)\n",
    "    \n",
    "    current_times.append(current_time)\n",
    "    actual_date_times.append(actual_date_time)\n",
    "    actual_times.append(actual_time)\n",
    "    \n",
    "    timedelta = datetime.timedelta()\n",
    "    if hour >= 24.0:\n",
    "        hour = 23.0\n",
    "        timedelta += datetime.timedelta(hours=1)\n",
    "    if minute >= 60.0:\n",
    "        minute = 59\n",
    "        timedelta += datetime.timedelta(minutes=1)\n",
    "    \n",
    "    dt = datetime.datetime(year=year, month=month, day=day, hour=hour, minute=minute)\n",
    "    dt += timedelta\n",
    "    x.append(dt)\n",
    "    \n",
    "    if count % plot_update_interval == 0:\n",
    "        update_line()\n",
    "\n",
    "api = EnergyPlusAPI()\n",
    "state = api.state_manager.new_state()\n",
    "\n",
    "api.runtime.callback_begin_zone_timestep_after_init_heat_balance(state, callback_function)\n",
    "api.runtime.run_energyplus(state,\n",
    "    [\n",
    "        '-w', '/usr/local/EnergyPlus-9-4-0/WeatherData/USA_CO_Golden-NREL.724666_TMY3.epw',\n",
    "        '-d', 'out',\n",
    "        filename_to_run\n",
    "    ]\n",
    ")\n",
    "\n",
    "# If you need to call run_energyplus again, then reset the state first\n",
    "api.state_manager.reset_state(state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot with two graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2.04 s, sys: 95.8 ms, total: 2.13 s\n",
      "Wall time: 2.13 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "x = []\n",
    "y_outdoor = []\n",
    "y_zone = []\n",
    "y_htg = []\n",
    "y_clg = []\n",
    "y_overshoot = []\n",
    "\n",
    "years = []\n",
    "months = []\n",
    "days = []\n",
    "hours = []\n",
    "minutes = []\n",
    "current_times = []\n",
    "actual_date_times = []\n",
    "actual_times = []\n",
    "\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True, figsize=(8, 6),\n",
    "                               gridspec_kw={'height_ratios': [2, 1]},\n",
    "                               num='Two graphs')\n",
    "h1, = ax0.plot(x, y_outdoor, label=\"Outdoor Air Temp\")\n",
    "h2, = ax0.plot(x, y_zone, label=\"Zone Temperature\")\n",
    "h_overshoot, = ax1.plot(x, y_overshoot, label=\"Overshoot\")\n",
    "\n",
    "ax0.set_ylabel('Temperature [C]')\n",
    "ax0.legend(loc='lower right')\n",
    "ax0.set_ylim(-25, 40)\n",
    "\n",
    "ax1.set_title('Overshoot/undershoot compared to thermostat setpoint [C]')\n",
    "ax1.set_xlabel('Zone time step index')\n",
    "ax1.set_ylabel('Temperature difference [C]')\n",
    "ax1.legend(loc='lower right')\n",
    "ax1.set_ylim(-1.1, 1.1)\n",
    "# plt.show(False)\n",
    "#plt.draw()\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "\n",
    "filename_to_run = 'test.idf'\n",
    "zone_name = openstudio.model.getThermalZones(m)[0].nameString()\n",
    "got_handles = False\n",
    "oa_temp_handle = -1\n",
    "zone_temp_handle = -1\n",
    "zone_htg_tstat_handle = -1\n",
    "zone_clg_tstat_handle = -1\n",
    "count = 0\n",
    "plot_update_interval = 250  # time steps\n",
    "\n",
    "def update_line():\n",
    "    \n",
    "    \n",
    "    #hl.set_data(x, y_outdoor)\n",
    "    #h2.set_data(x, y_zone)\n",
    "    \n",
    "    h1.set_xdata(x)\n",
    "    h1.set_ydata(y_outdoor)\n",
    "    h2.set_xdata(x)\n",
    "    h2.set_ydata(y_zone)\n",
    "    \n",
    "    y_overshoot = []\n",
    "    for i, zone_temp in enumerate(y_zone):\n",
    "        if zone_temp < y_htg[i]:\n",
    "            y_overshoot.append(zone_temp - y_htg[i])\n",
    "        elif zone_temp > y_clg[i]:\n",
    "            y_overshoot.append(zone_temp - y_clg[i])\n",
    "        else:\n",
    "            y_overshoot.append(0.0)\n",
    "    \n",
    "    h_overshoot.set_xdata(x)\n",
    "    h_overshoot.set_ydata(y_overshoot)\n",
    "\n",
    "    \n",
    "    ax0.set_xlim(x[0], x[-1])\n",
    "    ax1.set_ylim(min(y_overshoot), max(y_overshoot))\n",
    "    #ax.autoscale_view()\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "\n",
    "\n",
    "def callback_function(state_argument):\n",
    "    global count, got_handles, oa_temp_handle, zone_temp_handle, zone_htg_tstat_handle, zone_clg_tstat_handle\n",
    "    if not got_handles:\n",
    "        if not api.exchange.api_data_fully_ready(state_argument):\n",
    "            return\n",
    "        oa_temp_handle = api.exchange.get_variable_handle(state_argument, u\"SITE OUTDOOR AIR DRYBULB TEMPERATURE\", u\"ENVIRONMENT\")\n",
    "        zone_temp_handle = api.exchange.get_variable_handle(state_argument, \"Zone Mean Air Temperature\", zone_name)\n",
    "        zone_htg_tstat_handle = api.exchange.get_variable_handle(state_argument, \"Zone Thermostat Heating Setpoint Temperature\", zone_name)\n",
    "        zone_clg_tstat_handle = api.exchange.get_variable_handle(state_argument, \"Zone Thermostat Cooling Setpoint Temperature\", zone_name)\n",
    "\n",
    "        if -1 in [oa_temp_handle, zone_temp_handle, zone_htg_tstat_handle, zone_clg_tstat_handle]:\n",
    "            \n",
    "            print(\"***Invalid handles, check spelling and sensor/actuator availability\")\n",
    "            sys.exit(1)\n",
    "        got_handles = True\n",
    "    if api.exchange.warmup_flag(state_argument):\n",
    "        return\n",
    "    count += 1\n",
    "    #x.append(count)\n",
    "    oa_temp = api.exchange.get_variable_value(state_argument, oa_temp_handle)\n",
    "    y_outdoor.append(oa_temp)\n",
    "    zone_temp = api.exchange.get_variable_value(state_argument, zone_temp_handle)\n",
    "    y_zone.append(zone_temp)\n",
    "    \n",
    "    zone_htg_tstat = api.exchange.get_variable_value(state_argument, zone_htg_tstat_handle)\n",
    "    y_htg.append(zone_htg_tstat)\n",
    "    \n",
    "    zone_clg_tstat = api.exchange.get_variable_value(state_argument, zone_clg_tstat_handle)\n",
    "    y_clg.append(zone_clg_tstat)\n",
    "    \n",
    "    \n",
    "    year = api.exchange.year(state)\n",
    "    month = api.exchange.month(state)\n",
    "    day = api.exchange.day_of_month(state)\n",
    "    hour = api.exchange.hour(state)\n",
    "    minute = api.exchange.minutes(state)\n",
    "    current_time = api.exchange.current_time(state)\n",
    "    actual_date_time = api.exchange.actual_date_time(state)\n",
    "    actual_time = api.exchange.actual_time(state)\n",
    "                    \n",
    "    # Year is bogus, seems to be reading the weather file year instead...         \n",
    "    # So harcode it to 2009\n",
    "    year = 2009\n",
    "    years.append(year)\n",
    "    months.append(month)\n",
    "    days.append(day)\n",
    "    hours.append(hour)\n",
    "    minutes.append(minute)\n",
    "    \n",
    "    current_times.append(current_time)\n",
    "    actual_date_times.append(actual_date_time)\n",
    "    actual_times.append(actual_time)\n",
    "    \n",
    "    timedelta = datetime.timedelta()\n",
    "    if hour >= 24.0:\n",
    "        hour = 23.0\n",
    "        timedelta += datetime.timedelta(hours=1)\n",
    "    if minute >= 60.0:\n",
    "        minute = 59\n",
    "        timedelta += datetime.timedelta(minutes=1)\n",
    "    \n",
    "    dt = datetime.datetime(year=year, month=month, day=day, hour=hour, minute=minute)\n",
    "    dt += timedelta\n",
    "    x.append(dt)\n",
    "    \n",
    "    if count % plot_update_interval == 0:\n",
    "        update_line()\n",
    "\n",
    "api = EnergyPlusAPI()\n",
    "state = api.state_manager.new_state()\n",
    "\n",
    "api.runtime.callback_begin_zone_timestep_after_init_heat_balance(state, callback_function)\n",
    "api.runtime.run_energyplus(state,\n",
    "    [\n",
    "        '-w', '/usr/local/EnergyPlus-9-4-0/WeatherData/USA_CO_Golden-NREL.724666_TMY3.epw',\n",
    "        '-d', 'out',\n",
    "        filename_to_run\n",
    "    ]\n",
    ")\n",
    "\n",
    "# If you need to call run_energyplus again, then reset the state first\n",
    "api.state_manager.reset_state(state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## With pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.96 s, sys: 80.8 ms, total: 2.04 s\n",
      "Wall time: 2.03 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "x = []\n",
    "y_outdoor = []\n",
    "y_zone = []\n",
    "y_htg = []\n",
    "y_clg = []\n",
    "y_overshoot = []\n",
    "years = []\n",
    "months = []\n",
    "days = []\n",
    "hours = []\n",
    "minutes = []\n",
    "current_times = []\n",
    "actual_date_times = []\n",
    "actual_times = []\n",
    "\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True, figsize=(8, 6),\n",
    "                               gridspec_kw={'height_ratios': [2, 1]},\n",
    "                               num='Two graphs')\n",
    "h1, = ax0.plot(x, y_outdoor, label=\"Outdoor Air Temp\")\n",
    "h2, = ax0.plot(x, y_zone, label=\"Zone Temperature\")\n",
    "h_overshoot, = ax1.plot(x, y_overshoot, label=\"Overshoot\")\n",
    "\n",
    "ax0.set_ylabel('Temperature [C]')\n",
    "ax0.legend(loc='lower right')\n",
    "ax0.set_ylim(-25, 40)\n",
    "\n",
    "ax1.set_title('Overshoot/undershoot compared to thermostat setpoint [C]')\n",
    "ax1.set_xlabel('Zone time step index')\n",
    "ax1.set_ylabel('Temperature difference [C]')\n",
    "ax1.legend(loc='lower right')\n",
    "ax1.set_ylim(-1.1, 1.1)\n",
    "# plt.show(False)\n",
    "#plt.draw()\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "\n",
    "filename_to_run = 'test.idf'\n",
    "zone_name = openstudio.model.getThermalZones(m)[0].nameString()\n",
    "got_handles = False\n",
    "oa_temp_handle = -1\n",
    "zone_temp_handle = -1\n",
    "zone_htg_tstat_handle = -1\n",
    "zone_clg_tstat_handle = -1\n",
    "count = 0\n",
    "plot_update_interval = 250  # time steps\n",
    "df = None\n",
    "\n",
    "def update_line():\n",
    "    \n",
    "    \n",
    "    #hl.set_data(x, y_outdoor)\n",
    "    #h2.set_data(x, y_zone)\n",
    "    \n",
    "    h1.set_xdata(df.index)\n",
    "    h1.set_ydata(df['OA Temp'])\n",
    "    h2.set_xdata(df.index)\n",
    "    h2.set_ydata(df['Zone Temp'])\n",
    "    \n",
    "    \n",
    "    y_overshoot = []\n",
    "    for i, zone_temp in enumerate(y_zone):\n",
    "        if zone_temp < y_htg[i]:\n",
    "            y_overshoot.append(zone_temp - y_htg[i])\n",
    "        elif zone_temp > y_clg[i]:\n",
    "            y_overshoot.append(zone_temp - y_clg[i])\n",
    "        else:\n",
    "            y_overshoot.append(0.0)\n",
    "    \n",
    "    h_overshoot.set_xdata(df.index)\n",
    "    h_overshoot.set_ydata(y_overshoot)\n",
    "\n",
    "    \n",
    "    ax0.set_xlim(x[0], x[-1])\n",
    "    ax1.set_ylim(min(y_overshoot), max(y_overshoot))\n",
    "    #ax.autoscale_view()\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "\n",
    "\n",
    "def callback_function(state_argument):\n",
    "    \n",
    "    if not hasattr(callback_function, \"counter\"):\n",
    "        callback_function.counter = 0\n",
    "        callback_function.index = []\n",
    "    \n",
    "    \n",
    "    global count, got_handles, oa_temp_handle, zone_temp_handle, zone_htg_tstat_handle, zone_clg_tstat_handle, df\n",
    "    if not got_handles:\n",
    "        if not api.exchange.api_data_fully_ready(state_argument):\n",
    "            return\n",
    "        oa_temp_handle = api.exchange.get_variable_handle(state_argument, u\"SITE OUTDOOR AIR DRYBULB TEMPERATURE\", u\"ENVIRONMENT\")\n",
    "        zone_temp_handle = api.exchange.get_variable_handle(state_argument, \"Zone Mean Air Temperature\", zone_name)\n",
    "        zone_htg_tstat_handle = api.exchange.get_variable_handle(state_argument, \"Zone Thermostat Heating Setpoint Temperature\", zone_name)\n",
    "        zone_clg_tstat_handle = api.exchange.get_variable_handle(state_argument, \"Zone Thermostat Cooling Setpoint Temperature\", zone_name)\n",
    "\n",
    "        df = pd.DataFrame({'OA Temp': [], 'Zone Temp': [], 'Htg Tstat': [], 'Clg Tstat': []})\n",
    "        \n",
    "        if -1 in [oa_temp_handle, zone_temp_handle, zone_htg_tstat_handle, zone_clg_tstat_handle]:\n",
    "            \n",
    "            print(\"***Invalid handles, check spelling and sensor/actuator availability\")\n",
    "            sys.exit(1)\n",
    "        got_handles = True\n",
    "    \n",
    "    if api.exchange.warmup_flag(state_argument):\n",
    "        return\n",
    "    \n",
    "    \n",
    "    count += 1\n",
    "    callback_function.counter += 1\n",
    "    \n",
    "    #x.append(count)\n",
    "    oa_temp = api.exchange.get_variable_value(state_argument, oa_temp_handle)\n",
    "    y_outdoor.append(oa_temp)\n",
    "    zone_temp = api.exchange.get_variable_value(state_argument, zone_temp_handle)\n",
    "    y_zone.append(zone_temp)\n",
    "    \n",
    "    zone_htg_tstat = api.exchange.get_variable_value(state_argument, zone_htg_tstat_handle)\n",
    "    y_htg.append(zone_htg_tstat)\n",
    "    \n",
    "    zone_clg_tstat = api.exchange.get_variable_value(state_argument, zone_clg_tstat_handle)\n",
    "    y_clg.append(zone_clg_tstat)\n",
    "    \n",
    "    \n",
    "    year = api.exchange.year(state)\n",
    "    month = api.exchange.month(state)\n",
    "    day = api.exchange.day_of_month(state)\n",
    "    hour = api.exchange.hour(state)\n",
    "    minute = api.exchange.minutes(state)\n",
    "    current_time = api.exchange.current_time(state)\n",
    "    actual_date_time = api.exchange.actual_date_time(state)\n",
    "    actual_time = api.exchange.actual_time(state)\n",
    "                    \n",
    "    # Year is bogus, seems to be reading the weather file year instead...         \n",
    "    # So harcode it to 2009\n",
    "    year = 2009\n",
    "    years.append(year)\n",
    "    months.append(month)\n",
    "    days.append(day)\n",
    "    hours.append(hour)\n",
    "    minutes.append(minute)\n",
    "    \n",
    "    current_times.append(current_time)\n",
    "    actual_date_times.append(actual_date_time)\n",
    "    actual_times.append(actual_time)\n",
    "    \n",
    "    timedelta = datetime.timedelta()\n",
    "    if hour >= 24.0:\n",
    "        hour = 23.0\n",
    "        timedelta += datetime.timedelta(hours=1)\n",
    "    if minute >= 60.0:\n",
    "        minute = 59\n",
    "        timedelta += datetime.timedelta(minutes=1)\n",
    "    \n",
    "    dt = datetime.datetime(year=year, month=month, day=day, hour=hour, minute=minute)\n",
    "    dt += timedelta\n",
    "    x.append(dt)\n",
    "    \n",
    "    # More explicit, but really slow\n",
    "    # CPU times: user 8.78 s, sys: 128 ms, total: 8.9 s\n",
    "    # Wall time: 8.9 s\n",
    "    # df.loc[dt] = {'OA Temp': oa_temp, 'Zone Temp': zone_temp, 'Htg Tstat': zone_htg_tstat, 'Clg Tstat': zone_clg_tstat}\n",
    "    \n",
    "    # CPU times: user 6.66 s, sys: 128 ms, total: 6.79 s\n",
    "    # Wall time: 6.77 s\n",
    "    # df.loc[dt] = [oa_temp, zone_temp, zone_htg_tstat, zone_clg_tstat]\n",
    "    \n",
    "    # CPU times: user 6.56 s, sys: 100 ms, total: 6.66 s\n",
    "    # Wall time: 6.65 s\n",
    "    # s = pd.Series({'OA Temp': oa_temp, 'Zone Temp': zone_temp, 'Htg Tstat': zone_htg_tstat, 'Clg Tstat': zone_clg_tstat}, name=dt)\n",
    "    # df = df.append(s)\n",
    "\n",
    "    if count % plot_update_interval == 0:\n",
    "        # df = pd.concat([df, pd.DataFrame()])\n",
    "        # CPU times: user 2.09 s, sys: 84.2 ms, total: 2.18 s\n",
    "        # Wall time: 2.17 s\n",
    "#         df = pd.concat([df, pd.DataFrame({'OA Temp': y_outdoor[-plot_update_interval:],\n",
    "#                                           'Zone Temp': y_zone[-plot_update_interval:],\n",
    "#                                           'Htg Tstat': y_htg[-plot_update_interval:],\n",
    "#                                           'Clg Tstat': y_clg[-plot_update_interval:]},\n",
    "#                                          index=x[-plot_update_interval:])])\n",
    "        # CPU times: user 2.1 s, sys: 56.4 ms, total: 2.15 s\n",
    "        # Wall time: 2.14 s\n",
    "        df = pd.DataFrame({'OA Temp': y_outdoor, 'Zone Temp': y_zone, 'Htg Tstat': y_htg, 'Clg Tstat': y_clg}, index=x)\n",
    "        \n",
    "        update_line()\n",
    "\n",
    "api = EnergyPlusAPI()\n",
    "state = api.state_manager.new_state()\n",
    "\n",
    "api.runtime.callback_begin_zone_timestep_after_init_heat_balance(state, callback_function)\n",
    "api.runtime.run_energyplus(state,\n",
    "    [\n",
    "        '-w', '/usr/local/EnergyPlus-9-4-0/WeatherData/USA_CO_Golden-NREL.724666_TMY3.epw',\n",
    "        '-d', 'out',\n",
    "        filename_to_run\n",
    "    ]\n",
    ")\n",
    "\n",
    "# If you need to call run_energyplus again, then reset the state first\n",
    "api.state_manager.reset_state(state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use a class instead of globals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TwoGraphs:\n",
    "    def __init__(self, filename_to_run, zone_name):\n",
    "        \n",
    "        self.filename_to_run = filename_to_run\n",
    "        self.zone_name = zone_name\n",
    "        \n",
    "        # Storing stuff\n",
    "        self.got_handles = False\n",
    "        self.oa_temp_handle = -1\n",
    "        self.zone_temp_handle = -1\n",
    "        self.zone_htg_tstat_handle = -1\n",
    "        self.zone_clg_tstat_handle = -1\n",
    "        self.count = 0\n",
    "        self.plot_update_interval = 250  # time steps\n",
    "        \n",
    "        self.x = []\n",
    "        self.y_outdoor = []\n",
    "        self.y_zone = []\n",
    "        self.y_htg = []\n",
    "        self.y_clg = []\n",
    "        self.y_overshoot = []\n",
    "        self.years = []\n",
    "        self.months = []\n",
    "        self.days = []\n",
    "        self.hours = []\n",
    "        self.minutes = []\n",
    "        self.current_times = []\n",
    "        self.actual_date_times = []\n",
    "        self.actual_times = []\n",
    "        self.df = pd.DataFrame({'OA Temp': [], 'Zone Temp': [], 'Htg Tstat': [], 'Clg Tstat': []})\n",
    "\n",
    "\n",
    "    def init_plot(self):\n",
    "\n",
    "        fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True, figsize=(8, 6),\n",
    "                                       gridspec_kw={'height_ratios': [2, 1]},\n",
    "                                       num='Two graphs')\n",
    "        h1, = ax0.plot([], [], label=\"Outdoor Air Temp\")\n",
    "        h2, = ax0.plot([], [], label=\"Zone Temperature\")\n",
    "        h_overshoot, = ax1.plot([], [], label=\"Overshoot\")\n",
    "\n",
    "        ax0.set_ylabel('Temperature [C]')\n",
    "        ax0.legend(loc='lower right')\n",
    "        ax0.set_ylim(-25, 40)\n",
    "\n",
    "        ax1.set_title('Overshoot/undershoot compared to thermostat setpoint [C]')\n",
    "        ax1.set_xlabel('Zone time step index')\n",
    "        ax1.set_ylabel('Temperature difference [C]')\n",
    "        ax1.legend(loc='lower right')\n",
    "        ax1.set_ylim(-1.1, 1.1)\n",
    "        # plt.show(False)\n",
    "        #plt.draw()\n",
    "        fig.autofmt_xdate()\n",
    "        \n",
    "        # Store attributes\n",
    "        self.fig = fig\n",
    "        self.ax0 = ax0\n",
    "        self.ax1 = ax1\n",
    "        self.h1 = h1\n",
    "        self.h2 = h2\n",
    "        self.h_overshoot = h_overshoot\n",
    "\n",
    "        fig.show()\n",
    "        fig.canvas.draw()\n",
    "\n",
    "    def update_line(self):\n",
    "\n",
    "\n",
    "        #hl.set_data(x, y_outdoor)\n",
    "        #h2.set_data(x, y_zone)\n",
    "\n",
    "        self.h1.set_xdata(self.df.index)\n",
    "        self.h1.set_ydata(self.df['OA Temp'])\n",
    "        self.h2.set_xdata(self.df.index)\n",
    "        self.h2.set_ydata(self.df['Zone Temp'])\n",
    "\n",
    "\n",
    "        y_overshoot = []\n",
    "        for i, zone_temp in enumerate(self.y_zone):\n",
    "            if zone_temp < self.y_htg[i]:\n",
    "                y_overshoot.append(zone_temp - self.y_htg[i])\n",
    "            elif zone_temp > self.y_clg[i]:\n",
    "                y_overshoot.append(zone_temp - self.y_clg[i])\n",
    "            else:\n",
    "                y_overshoot.append(0.0)\n",
    "\n",
    "        self.h_overshoot.set_xdata(self.df.index)\n",
    "        self.h_overshoot.set_ydata(y_overshoot)\n",
    "\n",
    "\n",
    "        self.ax0.set_xlim(self.x[0], self.x[-1])\n",
    "        #self.ax1.set_ylim(min(y_overshoot), max(y_overshoot))\n",
    "        #ax.autoscale_view()\n",
    "        self.fig.canvas.draw()\n",
    "    \n",
    "\n",
    "    def callback_function(self, state_argument):\n",
    "\n",
    "\n",
    "        if not self.got_handles:\n",
    "            if not api.exchange.api_data_fully_ready(state_argument):\n",
    "                return\n",
    "            self.oa_temp_handle = (\n",
    "                api.exchange.get_variable_handle(state_argument, u\"SITE OUTDOOR AIR DRYBULB TEMPERATURE\", u\"ENVIRONMENT\")\n",
    "            )\n",
    "            self.zone_temp_handle = (\n",
    "                api.exchange.get_variable_handle(state_argument, \n",
    "                                                 \"Zone Mean Air Temperature\",\n",
    "                                                 self.zone_name)\n",
    "            )\n",
    "            self.zone_htg_tstat_handle = (\n",
    "                api.exchange.get_variable_handle(state_argument,\n",
    "                                                 \"Zone Thermostat Heating Setpoint Temperature\",\n",
    "                                                 self.zone_name)\n",
    "            )\n",
    "            self.zone_clg_tstat_handle = (\n",
    "                api.exchange.get_variable_handle(state_argument,\n",
    "                                                 \"Zone Thermostat Cooling Setpoint Temperature\",\n",
    "                                                 self.zone_name)\n",
    "            )\n",
    "\n",
    "            if -1 in [self.oa_temp_handle, self.zone_temp_handle,\n",
    "                      self.zone_htg_tstat_handle, self.zone_clg_tstat_handle]:\n",
    "\n",
    "                print(\"***Invalid handles, check spelling and sensor/actuator availability\")\n",
    "                sys.exit(1)\n",
    "            self.got_handles = True\n",
    "            self.init_plot()\n",
    "\n",
    "        # Skip warmup\n",
    "        if api.exchange.warmup_flag(state_argument):\n",
    "            return\n",
    "\n",
    "\n",
    "        self.count += 1\n",
    "\n",
    "        oa_temp = api.exchange.get_variable_value(state_argument,\n",
    "                                                  self.oa_temp_handle)\n",
    "        self.y_outdoor.append(oa_temp)\n",
    "        zone_temp = api.exchange.get_variable_value(state_argument,\n",
    "                                                    self.zone_temp_handle)\n",
    "        self.y_zone.append(zone_temp)\n",
    "\n",
    "        zone_htg_tstat = api.exchange.get_variable_value(state_argument, \n",
    "                                                         self.zone_htg_tstat_handle)\n",
    "        self.y_htg.append(zone_htg_tstat)\n",
    "\n",
    "        zone_clg_tstat = api.exchange.get_variable_value(state_argument,\n",
    "                                                         self.zone_clg_tstat_handle)\n",
    "        self.y_clg.append(zone_clg_tstat)\n",
    "\n",
    "\n",
    "        year = api.exchange.year(state)\n",
    "        month = api.exchange.month(state)\n",
    "        day = api.exchange.day_of_month(state)\n",
    "        hour = api.exchange.hour(state)\n",
    "        minute = api.exchange.minutes(state)\n",
    "        current_time = api.exchange.current_time(state)\n",
    "        actual_date_time = api.exchange.actual_date_time(state)\n",
    "        actual_time = api.exchange.actual_time(state)\n",
    "\n",
    "        # Year is bogus, seems to be reading the weather file year instead...         \n",
    "        # So harcode it to 2009\n",
    "        year = 2009\n",
    "        self.years.append(year)\n",
    "        self.months.append(month)\n",
    "        self.days.append(day)\n",
    "        self.hours.append(hour)\n",
    "        self.minutes.append(minute)\n",
    "\n",
    "        self.current_times.append(current_time)\n",
    "        self.actual_date_times.append(actual_date_time)\n",
    "        self.actual_times.append(actual_time)\n",
    "\n",
    "        timedelta = datetime.timedelta()\n",
    "        if hour >= 24.0:\n",
    "            hour = 23.0\n",
    "            timedelta += datetime.timedelta(hours=1)\n",
    "        if minute >= 60.0:\n",
    "            minute = 59\n",
    "            timedelta += datetime.timedelta(minutes=1)\n",
    "\n",
    "        dt = datetime.datetime(year=year, month=month, day=day, hour=hour, minute=minute)\n",
    "        dt += timedelta\n",
    "        self.x.append(dt)\n",
    "\n",
    "\n",
    "        if self.count % self.plot_update_interval == 0:\n",
    "\n",
    "            self.df = pd.DataFrame({'OA Temp': self.y_outdoor,\n",
    "                                    'Zone Temp': self.y_zone,\n",
    "                                    'Htg Tstat': self.y_htg,\n",
    "                                    'Clg Tstat': self.y_clg},\n",
    "                                   index=self.x)\n",
    "\n",
    "            self.update_line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.88 s, sys: 99.2 ms, total: 3.98 s\n",
      "Wall time: 3.99 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "api = EnergyPlusAPI()\n",
    "state = api.state_manager.new_state()\n",
    "\n",
    "\n",
    "filename_to_run = 'test.idf'\n",
    "g = TwoGraphs(filename_to_run=filename_to_run,\n",
    "              zone_name=openstudio.model.getThermalZones(m)[0].nameString())\n",
    "\n",
    "api.runtime.callback_begin_zone_timestep_after_init_heat_balance(state, g.callback_function)\n",
    "api.runtime.run_energyplus(state,\n",
    "    [\n",
    "        '-w', '/usr/local/EnergyPlus-9-4-0/WeatherData/USA_CO_Golden-NREL.724666_TMY3.epw',\n",
    "        '-d', 'out',\n",
    "        filename_to_run\n",
    "    ]\n",
    ")\n",
    "\n",
    "# If you need to call run_energyplus again, then reset the state first\n",
    "api.state_manager.reset_state(state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Post process example\n",
    "\n",
    "And now I'm free to do whatever with the TwoGraphs instance that I used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Resampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f54a5129a00>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True,\n",
    "                       gridspec_kw={'height_ratios': [1, 4]},\n",
    "                       figsize=(16, 9), num='Post process')\n",
    "\n",
    "g.df['OA Temp'].resample('1H').mean().plot(ax=ax0, c='orange')\n",
    "ax0.set_title('Outdoor temp')\n",
    "g.df[['Zone Temp']].resample('1H').mean().plot(ax=ax1)\n",
    "ax1.set_title('Hourly resampling')\n",
    "ax1.axhline(g.df['Htg Tstat'].max(), linestyle='--', label='Max Htg Setpoint Temp', c='r', alpha=0.3)\n",
    "ax1.axhline(g.df['Clg Tstat'].max(), linestyle='--', label='Max Clg Setpoint Temp', c='b', alpha=0.3)\n",
    "ax1.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Truncation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f54a2301640>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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S0A5ylsOOWa6TiDQKGoGWYKmAFpGIpr2gRZoYfzF8PALm3+A6SWTrchL4EmCDunGLNITCQm/ZmE/VkdRAPyIiEtFUQIs0MdumQWk2dDjadZLIFtccOh0Pm17XWmiRBqAtrCRYKqBFJKJVFNDaC1qkidjwKsS3hA5HuU4S+bqdA4VbIXOG6yQiUa+wUNO3JTgqoEUkolV8GqwRaJEmwF8E6e9C19MhJt51msjXeQoM/D0kd3GdRCTqaQRagqUu3CIS0eLiwBgV0CJNwpZPoCwXup3tOkl0iGsGI//hOoVI1PP7oaREI9ASHI1Ai0hEM8abxq0CWqQJ6HQcHPIOtD/CdZLoEfDD1mmwe6nrJCJRSx24pTZUQItIxFMBLdJExCRCl1PApwlyQQsUwzenwqqHXScRiVoVBbSmcEswVECLSMRTAS3SBGz7HH78M5Tlu04SXWKTofNJsOlNCJS5TiMSlQoLvWuNQEswVECLSMRLSFAXbpFGb80TsOpRb29jqZ3u50DxDsiY7jqJSFSqKKA1Ai3BUAEtIhEvIcFr7iEijVRZPmz+ALqdqenbddHxOIhtBhtec51EJCoVFXlNS2NiXCeRaKACWkQiXkICBAJQWuo6iYiExOYPwV+g7tt1FZvkrR3f8R1Y6zqNSNQpKtL0bQmePuYVkYiXUD6js+ITYhFpZDa+CokdoO1k10mi1+iHIC7N27pARGqlsFDTtyV4GoEWkYhX8UdNjcREGiFrwRcPPS4An+ZP1llCK/37idSRRqCjgzHmaWNMhjFmyV73tTLGTDPGrC6/bhnqHCqgRSTiVYxAq4AWaYSMgYkvw6j7XCeJfutfgY+Gg19NI0SCFQh47y80Ah0VngGO2+++W4AvrLV9gS/Kb4eUCmgRiXgqoEUaseIs1wkaj7hU2L0Ytk1znUQkalTs8qER6Mhnrf0G2Lnf3acAz5Z//SxwaqhzqIAWkYgXFwc+nwpoaSJyVsLq/4ANuE4SeiXZ8HZnWP4v10kahw5HQ1wL2PCq6yQiUUNbWEW99tbareVfbwPah/qEaiImIlEhIUEFtDQBuxbCtEnetk5JnbzOyo3Z5vcgUAxtDnKdpHGIiYeup8GmN8FfBDGqCERqohHoiBJrjJm71+2p1tqpwb7YWmuNMSHfikAj0CISFRISfv4jJ9JopQ2Fvr+C5G6w/H7XaUJvw6ve99pmguskjUe3c6A0B7Z+6jqJSFTQCHREKbPWjtnrEkzxvN0Y0xGg/DojtBFVQItIlNAItDRauxbD54dD4Xavi/LIe2HA9ZD5LeyY4zpd6JTsgm2fQbeztPVSQ+pwBPS+ApK7uE4iEhWKiiA21rtIVHoPuKj864uAd0N9QhXQIhIVVEBLo2MtrP4vfDoOcldCwaafH+t9OaT2g8J0d/lCLf1dCJRC93NcJ2lcfHEwfiq0Gu06iUhUKCzU9O1oYYx5GZgF9DfGpBtjLgPuAY42xqwGjiq/HVL6rEVEokJCApSUeDWHBqsk6pVkw5wrYOPr0PFYOOg5SGz38+NxqTBlReP+Ye90Ikz4H7Qa4zpJ42MtZC8FDLQY7DqNSEQrKtL07WhhrT2vioeODGcOjUCLSFRITPTeE5Zoe1NpDBb9ATa9BSP+AYd9tG/xXMEYCJTBrkXhzxcOiW2h18WN+0MCV6wfvjgClvzFdRKRiFdUpBFoqR0V0CISFbQXtEQ9a711vwDD/gpHz4BBvwdTzZ/iBTd5XblLdoclYths+RhWP+59QCANzxcLXc+Aze97Hd1FpFKBgEagpfZUQItIVFABLVGtaAd8fRJ8dZy37jehVXCdp3teBGV5sCboXTyiw4p/wfL7wMS4TtJ4dT8b/AWw5SPXSUQiVsV7Co1AS22ogBaRqKACWqJWxrfw8QjYNg16/AJMLdqPtBoJ7Y+AlQ+Bv5GsXyjKhO1fegWepm+HTttDILG9t1WYiFRKW1hJXaiAFpGoUFFAay9oiRoBPyz5K3xxGMQkwTGzoP+1tS8aB9wIhZth42shiRl2m94CG4BuZ7tO0rj5YqDrmbD9q8bz4YtIA6t4T6ERaKkNFdAiEhViYyEmRiPQEkUCRbD+Reh2Lhw/H1qNqttxOh0HzQd6hWdjsPFVaN4fWgxznaTxG3o7nLIeYuJdJxGJSBqBlrrQNlYiEjW0F7REhe1fQ+sxEJsCR38H8S3rN1XZ+ODwTyGpU8NldCVQCv5ib/RZ07dDr7Lu7iKyR1GR9wF9XJzrJBJNNAItIlEjMVEFtESwQBksuhW+OByW3uPdl9CqYQrFlK7elNxon4rri4NjvoOhd7pO0nRs+xI+OxhKc1wnEYk4hYUafZbaUwEtIlFDI9ASsfI3eWudl94NvS+FwX9o+HNsnw7vdIbdSxv+2OFSVuBdV7d1lzSsmETYMQvS33OdRCTiaA9oqQv9BRORqKECWiLS9ulel+1di+Dgl2D8kxCb3PDnSRvi7em74l8Nf+xwKNgCb7aB9S+7TtK0tJkAyV0aTxM6kQakEWipCxXQIhI1EhKgpAQCAddJRPaS0g1aDofj5kOP80J3nsQ20OtiWP8CFG4L3XlCZdMb4C+EliNdJ2lajM9bc771EyjZ7TqNSMSw1vtQXgW01JYKaBGJGhVbWZVE+TJQaQRy18LCP3rvwJr1giO/hOZ9Q3/e/r/1GnGtejT052poG1/zOm+nDXCdpOnpdrb3c5P+ruskIhGjuNj7Fa4p3FJbKqBFJGpUFNCaxi1OrX8FPh4Jq/8D+T+F99zN+0KXk2H1Y1BWGN5z10f+Jsj8Tns/u9J6HPT4BSR1dJ1EJGJUbGGlAlpqS9tYiUjUqCigi4ogLc1tFmmCygph/vWwZiq0OQgmvgwp3cOfY9hfoDQXYqPoXd+mN7xrFdBuGAMHP+86hUhEKSryrjWFW2orZAW0MaYr8BzQHrDAVGvtg3s9fiNwH9DWWrsjVDlEpPGo+COnEWhx4puTYdvnMOhmr4j1Odo4tMVQN+etj84ngS8hPNPcpWqF26BkJ6QNcp1ExDmNQEtdhXIEugy40Vo73xiTCswzxkyz1i4rL66PATaG8Pwi0shoCreEnbWA9RoxDboFBtwEnY51nQpKsmHhzV5h2vlE12lqltrHu4hbnx8KKT3giE9dJxFxrrAQYmIgztFnoRK9QlZAW2u3AlvLv841xiwHOgPLgAeA3wPqZiEiQfP5vD90OTmwa5frNNLoleWSvPRXBJL7UdT3dkg40rs/En72Aik03/wJgayl5CVHdgEdm/EhxpZR2u5kbyqxNKiyQIDSsgAl/gDFZQFK/QHKAhZrLQFrsXifAwWspUvKFDpte5A5P66jLLY11tp9jrXfzWp5R67m8Vocq+pzgD9gKQsEKPNbSgMBysq/v4rvM8Zn6JCaSKe0ZNqlJhIXo/Y+EpzcXE3flroJyxpoY0wPYCTwvTHmFGCztXaR0R9SEamlpCTYssW7iIRKc/9CRheeTbxdy8r4u1i93XWi/cXSM3A9Q3b9liVff8/umPGuA1Vpcv6dAMxIOcVtkChhraWgrJSdxYXs2nMp8m6XFLK7uIiSgJ/SgJ+yQKCGMnZfgxJ78FE/P+98/AAv7zwuZN+DKwZIi0+kVWISrRK8S+uEZEa26UhSrIYZ5UDt2rlOINHI7P/pY4OfwJhmwNfA34BPgK+AY6y12caY9cCYytZAG2OuBK4EiI+PH12sOZsigjflKjfXdQpptKwlKf0xmq2+kUBca3KGvERpy0Ndp6qUKcul9YyulLQ6hpxhr7mOUylfwTrazOxNbt97Kex+k+s4EW1VRjZPf7+GmT9lUlTm3+exhBgf7Zsn0SE1iXapiSTHxRIf4yMu1uddx/hI2Ot2jDH4fAaDwRjwGYPBKzBP2DKZgthOzOj4undws88VhuAHN2oaB2mIYZIYn49YnyE25ufrOJ8h1ucjNsZQ6rdsyy1kW04hW7ML2FrxdU4hGblF+K2lf7vmPHrmBJonqoiWfaWl/bw8TNwzxhRYa1Nc56hJSAtoY0wc8AHwqbX2X8aYocAXQEH5U7oAW4Bx1tptVR0nJSXF5ufnhyyniIgIADkr4cMh0PEYmPAMJLZ1nah6C26GFffBSWugWU/XaQ609B5Y9Ac4Zb2bjuVRYHH6bh76Yg2fL99OamIsp47oTM82KXRqkUTnFkl0apFIq5R4GmzW3qLbYNk9cEYGxLdsmGNGqDJ/gK9WZvLrF+czsFNzXrhsHKkqokUiVpMvoI33m/5ZYKe19voqnrOeKkag96YCWkREwiZrLrQa5TUOi3QF6bDkrzDkT5DcxXWaA308CnzxcOxs10kizrwNu3j4y9VMX5lJWlIcl03qyUUH9yAtKcQFXuF2sKWR+fMSIp8t3cY1L85nRNcWPHvpOFIStIurSCRSAW3MJOBb4EcgUH73H621H+31nPWogBYREdcyZkDeOuh5oRpdNZSSbPh4OPS/Dgb81nWaiDHnp5089MVqZqzZQauUeC6f3JMLJ3TXyGiIfbh4K9e+PJ/xPVvz9MVjSYqPcR1JRPbT5AvohqQCWkREQqY0zyv0AE5YArFRuClo5kwozoQuEdaoy1oIlEJMvOskzu0uKOHalxfw7eodtGmWwFWH9OKCCd1IjncwGrprESz6E4yfCkkdw39+R95ZsJnfvraQSX3a8MQvx5AYpyJaJJJESwGtOSwiItK0LbwZ8n6Co76OzuIZYPHtkLMcOh4fOcVqwA++mMjJ49DO/BIuePJ71mbk8acTB3LB+O5uR0B9cbDlA9j4BvS/1l2OMDt1ZGdKygL8/s3F/N9L83nsgtHEx0bBUg0RiSj6rSEiIk3Xti9g9WPeNON2k12nqbuBN0HhFtj4qusknuzl8HYH2Pal6yTO7cgr5vwnZrMuM48nLhrD5ZN7uZ8+nDYI0obAxsjs3h5KZ4/tyl9OHcLnyzO47pUFlPkDNb9IRGQvKqBFRKRp8hfB7EshtR8Mv9t1mvrpeCykDYbl93vTpl3b+BoUZ0HzAa6TOJWRW8R5U2ezPiufpy8ey6H9Iqire/dzIHMGFGx2nSTsLpzQndumDOLjJdu44bVF+AMR8P+MiEQNFdAiItI0xSTCmIfgoOeid+p2BWNgwA2wexFs/8J1Gq+AbjcZkju5TuLMtuwizn18Npt3F/K/i8cxsU8b15H21e0s73rj625zOHLZpJ7cfNwA3lu0hZvfXExARbSIBElroEVEpOnxF0NMQuQ13aqPHhfAin9B4Ta3OXYvgexlMOZRtzkc2rK7kPOemM2O3GKevXQcY3u0ch3pQM37Q7dzID4Cs4XJrw7rTUlZgAc+X0V8rI+/nTqk4fbbFpFGSwW0iIg0LSW74OPRMOQ26H2J6zQNJyYBTvjR/TZcG1/z9tDueobbHI5s2lnA+U/OZnd+Kc9dNp7R3Vu6jlS1Sa+4TuDcb47sQ3GZn8emryU+xscdJw1SES0i1VIBLSIiTcvc66BgI7Qc5jpJwzMGbAB2L4aWI9xk6HQixLWApPZuzu/QxqwCzntiNrlFpTx/+XhGdG3hOlLNygqhcDOk9nGdxAljDL87tj/FZQGemvETCbE+bjl+gIpoEamSCmgREWk60t+F9c/DkNuh1WjXaULjxzth2T/glA2Q1CH8528z3rs0Met35HPeE7MpKPHz0hUTGNI5zXWk4Hx1rNdQ77g5rpM4Y4zhTycOpKQswOPfrCM5PpbrjurrOpaIRCg1ERMRkaahaAfMudIbmR18q+s0odPzlxAohVWPhP/cWz6GHU2vEFu/I59zp86mqNTPS1eMj57iGaDzFNj5g7cXehNmjOHPJw/m9JGd+fcXq1iyOdt1JBGJUCqgRUSkadj+JZTmwoRnISbedZrQSe3jNUdb/R8oyw/fea2FudfC4j+F75wRYEOWN/JcXOaNPA/uFEXFM0C3s73rJrgn9P58PsMdJw+mdUo8t727RJ25RaRSKqBFRKRp6H42nPxT41z7vL+BN0HJTlj3TPjOuWsB5K39uSBrAjZmFXBe+cjzi5dPYGDH5q4j1V6zHtB6HGxQAQ2QlhTHLccPZMHG3bwxL911HBGJQCqgRUSkcSvcDtu+9L5uKo2t2hwMrcfDprfDd84Nr4KJha6nhe+cDm3MKuDcqbMoKPXzwuXjGdQpCovnCt3Ohl3zIW+d6yQR4fSRnRnTvSX3fLKC7IJS13FEJMKogBYRkcbLWvjhavj6RCjKcJ0mfIyByW/C4Z+E53zWelOAOxwFCa3Dc06HNu30um3nl/h54bLx0Tdte389L4Tj5kJKT9dJIoLPZ7jrlCHsLijh/mkrXccRkQijAlpERBqv9S9C+jsw7C+Q2M51mvBK7gy+WPAXh/5c+RugOAu6nxP6czm2aWcB506dTV5xGS9eHmUNw6qS2M7rSq+tm/YY1Kk5F07ozguzN7B0ixqKicjPVECLiEjjVLDZa2rVdiL0/63rNG7smAPvdoMds0N7nmY94IwM6H5uaM/jWPqun/d5bjTFc4W89fD95ZCzynWSiHHDMf1pmRzP7e8uVUMxEdlDBbSIiDQ+1npbVgWKYfz/wBfjOpEbaYPAXwLL7w/dOaz1LjGJ3qWR2ry7kPOemE1OYSkvXh5F+zwHyxcHa5/21rIL4DUUu/n4AczbsIu3Fmx2HUdEIoQKaBERaZw6nQij/w3N+7pO4k5cM+h7FaS/Fbp9fnfMhg8Hw67FoTl+BNi8u5Bzp84iu6CUFy4fz9Aujax4Bm/Kf9tJsFEF9N7OHNWFkd1acM/Hy8kuVEMxEVEBLSIijZEx0O8a6HOl6yTu9bsWTAys+Hdojr/xNW/7qpTuoTm+Y1t2F3Le1NnsLijl+cvGM6xLC9eRQqf7OZC9FHYvdZ0kYvh8hr+cMoSs/BIemKbp7SKiAlpERBoTG4Bvz4L1r7hOEjmSO0P382DdU1DSwM2QbAA2vg6djof4xjcquzXbm7a9K7+EFy4bz/CuLVxHCq2uZ4Dxef9NZY8hndO4YHw3npu1nuVbc1zHEWmyjDG/NcYsNcYsMca8bIxxsm5IBbSIiDQeq/8Lm96AUnXN3cfgW+HQDyGugfcqzpwJhZu9fYQbma3ZhZw7dTY780p4/vImUDwDJHXw/lvGJrlOEnFuOqY/aUlx3P7uEqxVQzGRcDPGdAZ+A4yx1g4BYgAnnStVQIuISOOQuxYW/A46HKOp2/tr3g/aH9rw2xRtfNVrHNb5pIY9rmPbsos4b+pssvJKeO6ycYxoCsVzhYkvw6CbXaeIOC2S47n5uAH8sH4X7yxUQzERR2KBJGNMLJAMbHERQgW0iIhEPxuA2Zd4+x6Pf1L72VamrADm/qZhp7d3OAaG/hniUhvumI5tyy7ivCdms6O8eB7ZraXrSOFnA1CQ7jpFxDl7TFeGd23B3R+tIKdIDcVEwslauxm4D9gIbAWyrbWfuciiAlpERKLf1k8h81sY/SCkdHWdJjLFJMH2r2DZ3d62Uw2hy0kw6PcNc6wIsD3HK54zcop49tJxjGqKxTPAzAvg88Mb7uekkfAaig0mM7eYZ75b7zqOSGMUa4yZu9dlz3QyY0xL4BSgJ9AJSDHG/MJFSBXQIiIS/TodD0fPgJ4XuU4SuYyBATfA7h9h2+f1P97Wz0K3NZYDGTnetO2MnCKeu2wco7s30eIZoP0RkLcGdi10nSTiDOvSgiMHtON/3/1EQUmZ6zgijU2ZtXbMXpepez12FPCTtTbTWlsKvAUc7CKkCmgREYleAT9kr/C+bjtRU7dr0uN8SOwAK+6v33ECZTDrQlh4S8Pkciwjp4hzn5jN9vKR59HdW7mO5FbX072tz7QndKWuObw3uwpKeXnOJtdRRJqSjcAEY0yyMcYARwLLXQRRAS0iItFrxX3w8TDIdvI3NPrEJED/a70p77t/rPtxMr6Gogxv3+Aoty27iHOnzmZbdhHPXDqOMT2aePEMkNAaOhwFG17TNO5KjO7eivE9W/HEN+soLvO7jiPSJFhrvwfeAOYDP+LVsVOrfVGIqIAWEZHotHsJLL4dOp8MzQe4ThM9+lwNva+A2GZ1P8bG1yA2BToe33C5HPC2qprF9pwinrt0HGNVPP+s2zmQ/xPsnOs6SUS65vA+bMsp4p0F6sgtEi7W2justQOstUOstRdaa4td5DDRsJddSkqKzc/Pdx1DREQiRaAUPp0ABRvhxKWQ2M51oqYjUApvd/Q6cE98yXWaOtuyu5DznvC2qvKmbTfhNc+VKdnt7fPd4SiIiXedJuJYa5ny8AwKSvx8fsOhxPi0fESkvowxBdbaFNc5aqIRaBERiT5L/w675sPY/6p4rqusH7wpurW1a6FXXEXx9O30XQWcM3UWO/NKeL6pNwyrSnwL6HyCiucqGGP49eF9+GlHPh8v2eo6joiEkQpoERGJPrYMevwCup3hOkn0WnYP/HA1lNVyhlfrsXDaNuh4XGhyhdimnQWc8/hssgtKeeHy8U1zn+dgFWfBoj/BzgWuk0SkYwd3oFebFB77ai3RMKNTRBqGCmgREYk+w+6Cg55znSK6DbgRSnbB2v/V/rWJbbyGZFFmY1YB506dTV5xGS9ePoHhXVu4jhTZTCwsvxd+et51kogU4zNcfWhvlm3NYfqqTNdxRCRMVECLiEj0WPEgbPvC+1pbVtVP24Oh9QRY+YC3HVgwtnwCXxwB+dG3fc/6HfmcM3UW+SVlvHj5eIZ2SXMdKfLFp3kzDTa+BjbgOk1EOnVkZzqmJfK3D5ezLjPPdRwRCQMV0CIiEh2yfoAFN8L6F1wnaTwG3gh562Dzu8E9f8MrsHM+JLYPba4G9tOOfM6dOpuiUj8vXT6BIZ1VPAet29lQuBl2zHKdJCLFx/r4xxnDyMwt5sSHZvDS9xs1nVukkVMBLSIikc9fBLMugqSOMOrfrtM0Hl1Og5ajoHhHzc/1F0P6O9D1tKhqLLV8aw5nPz6LUn+Al6+cwKBOzV1Hii5dTgZfAmx41XWSiHVIv7Z8ev0hjO7ekj++/SNXPDeXHXlOdtcRkTBQAS0iIpFv8W2QsxzGP+VNK5WG4YuB4+ZCnytrfu7Wz6A02xuRjBI/rN/J2Y/PItZneOXKCQzooOK51uJSoduZYIOc5t9EdUhL5LlLx3HblEF8s3oHx/37G75csd11LBEJAe0DLSIikW3XQvh4lFfkjfuv6zSNk7WwawG0GlX1c2ZeCFs+9DpwR8EI9BfLt3PNi/Pp3DKJ5y8bT+cWSa4jRS9r1XOgFlZsy+H6VxayYlsuv5jQjVtPGERSfIzrWCIRT/tAi4iINIQWw2D8EzDyXtdJGq8V98MnYyB3bdXPaTsJBt0cFcXzm/PSufL5efTvkMrrVx2k4rm+Kornkl1uc0SJAR2a8+7/TeTKQ3rxwuyNnPjwt/yYnu06log0EI1Ai4hI5CrN9aaQSmgVbIH3ekCfq2DMw67T1MuT367jrx8uZ2Kf1jx+4RiaJcS6jtQ4LLgZfnoWTt3sTf2XoMxcs4MbXlvEjrxifnt0P64+tDcxPo3mi1RGI9AiIiL1sf0reLc77PjedZLGL7kTdD8f1j4NxTsPfDzjGyiJ7BE0ay3/+GQFf/1wOScM7cDTF49V8dyQWo+Bou2Q+Y3rJFHl4D5t+PT6QzhuSAfu/XQl5zw+i007C1zHEpF6UAEtIiKRpzQXZl8K8a2hxRDXaZqGgTeCvwDWPL7v/WUFMP0EWHizm1xBKPMH+MNbP/Kf6Ws5f3w3Hj5vFAmxGiVtUJ1OhJhkdeOug7TkOB4+byQPnDOcldtyOf7Bb3lzXrq2uxKJUiqgRUQk8iy4CfI3wEHPQGzEz+ZqHFoMhQ7HeFtV7f3GfstHUJYfsd23i0r9/N9LC3jlh01ce0Qf/nbqEE2RDYXYZOh8Emx6EwJlrtNEHWMMp43swsfXT2ZQp+bc+Poi/u+lBewuKHEdTURqSQW0iIhEli2fwpqp3oho24mu0zQtBz0DR8/Yt+PyxtcgsR20O8RZrKrsyCvm/Cdm88nSbdw+ZRA3HtMfo27RodP9HG/P8O1fuU4Stbq0TOblKyZw83ED+GzZNo799zd8uzrTdSwRqQUV0CIiElm2fw7NB8Kwv7hO0vQkdQRfHPhLvFHosnzY/AF0PQN8kbWeePX2XE599DuWbc3hPxeM4tJJPV1Havw6HQ/jn/TWQ0udxfgMvzqsN29fM5HUxDgufGoOd72/jKJS7bUtEg3UhVtERCJPSTbEp7lO0TTtXgJfHQsT/geBUvh6Chw5Hdof6jrZHt+syuTXL84nMT6GJ385huFdW7iOJFInRaV+/v7Rcp6dtYEBHVJ55PxR9GnXzHUsESeipQu3CmgREYkM26dDQmtvLa644y+G93pC2hA44jPIXgGpfSNm66IXZm/gjveW0rddM566eKz2eA63sgKvW3vrMdBmgus0jcZXKzO48bVFFJX6+eupQzh9VBfXkUTCLloKaE3hFhER94qz4LvzvM7bUfDBbqMWkwD9roVt02DXYkgbEBHFsz9guev9ZfzpnSUc2q8tb/zqYBXPLpgYWPynA7u1S70c3r8dH/1mMkM6p3HDa4v43euLKCzRlG6RSKQRaBERce+7C7xmVcf9AC1HuE4jxTvhzdbe12fugvgWTuPkFZdx3csL+GJFBpdO7MmtJw5Up22XZl3sdWsfeod3u/cVENcMMmdB1uwDn9/3Gu+DmYxvYOe8Ax/vf73XuG7b57D7x30fM7HQ/1rv6y0fQ86KfR+PSYa+V3lfp78Leev2fTyuBfS+xPt64+tQkL7v4wntoOcF3tfrX/L2ut5bUmfoXt6Bft0zULJr38dTekLXUw/8nuqozB/gwS9W88hXa+jTthmPXjCKfu1TG+z4IpEsWkagVUCLiIhbO+fBJ2NgyO0w7M+u00iFeTfAlg9gygow7iasbdldyGXPzmXV9lzuPHkwF07o7iyLlNs+Hb44Aih/D3lqOiR3hh//DD/eeeDzz8qGuOaw4Hew/L4DHz8v4BXQc64+cGQ7JhnOKX8P+N0FsOGlfR9PbA+nb/O+/vpk2Pz+vo836wMnr/a+/vxwyJi+7+MtR8Lx872vPxkLO+fu+3i7Q+Cor72vPxgAOSv3fbzTCXDYh97XNtBg/6/MWL2D619dSF5xKXedMoSzRndRh3lp9FRANyAV0CIijdh353udnk/dpMZhkaTi/YHDN+1zftrJNS/Op7jUzyMXjOLQfm2dZZH9lBV4TeYA4lK9wtFf5K2h319cc+/nqKwQApXse1zT4xW/F/Y+ZwVjvNeD1zV+/z2qjc/LB1CaB9Zfy8djvNF1gNJcr0jemy/W+39l+gnQ9XQYcP2B+esoI7eI619ZyMy1WZw+sjN/OXUIKQmR1Q1fpCGpgG5AKqBFRBopa70RKxMLQ29znUYihLWW52dv4K73l9GtVTJTfzmaPu00jVUi2LTJULAJTlrToFu++QOWR75cw4NfrKJHmxQeOW8Ugzo1b7Dji0QSFdANSAW0iIhI01BU6ufWt5fw5vx0jhrYjn+dM4LmiXGuY4lUb9M78O1pMPHVn9dMN6BZa7O47pUF7C4s5bYTB/KLCd01pVsaHRXQDUgFtIhII1SS7TUV6nyi0zW2Ejk27y7k6ufn8ePmbH57VD+uPaIPPjULk2gQ8HtrpBNawTGzQ7L0ISuvmBtfX8T0lZkcO7g9/zxjOGnJ+nBJGo9oKaD1jkVERNxY+yR8czLsXuw6iUSAmWt3cNLDM1i/I58nfzmG647qq+JZoocvBgb8FrLmQOZ3ITlF62YJPH3RWP504kC+XJHBCQ99y7wNO0NyLhGpmkagRUQk/AKl8F5vaNYbjvrKdRpxyFrLUzN+4u8fr6BnmxSmXjiaXm2buY4lUntlBbD2aeh10c+NyUJk0abdXPvyAjbvLuSGo/tx9aG9tbWbRL1oGYFWAS0iIuG3/mWYeT4c+j50nuI6jThSVOrn5jcX8+7CLRw3uAP3nT2cZuoyLBKUnKJS/vjWj3yweCsT+7TmgXNG0C410XUskTpTAd2AVECLiDQi1nr7Pvvz4cRlWv/cRGXmFnPFc3NZlL6bm47pzzWH9VZTJGkc1j0HhVtg8C0hP5W1ltfmbuKO95bSLCGW+84azmH924X8vCKhEC0FtN61iIhIeBVtg5IsGHCDiucmavX2XE577DtWbsvlv78Yza8P76PiWRqPjK9hyV1QtCPkpzLGcM7Ybrz/f5NonZLAxf/7gb9+sIziMn/NLxaROtEItIiIhF+gDLDgUwfZpmbG6h386sV5JMbF8NRFYxjWpYXrSCINa/dS+GgIDL0rrPvbF5X6ufuj5Tw3awODOzXnofNG0lv9BCSKRMsItApoEREJn+KdEJsCMQmuk4gDr8zZyJ/eWUKfds146uKxdG6R5DqSSGh8dQLsmgenbICY8K5LnrZsO79/YxFFpQHuOGkQ54ztqhkeEhWipYDW3DkREQmfhbd4e6UGSl0nkTAKBCz/+GQFt7z1Iwf3acPrVx+k4lkat4E3QVEGrH8x7Kc+elB7Prn+EEZ1b8Etb/3Ir1+aT3aBfueKNBQV0CIiEh5FGfDTc9DxGE3dbkKKSv1c+/IC/jN9LReM78bTF40hNVH//aWRa3849PwlJHZ0c/rmiTx/6XhuOX4Any3dzvEPfsOcn7RntEhD0BRuEREJj8V3eI11TlwOaQNcp5Ew2JFXzOXPep22bz1hIJdN6qmppCJhtmjTbq57ZQEbdxZw7RF9uf6ovvr/UCKSpnCLiIhUKCuE1Y9B55NUPDcRW3YXcuZ/ZrJiWw7//cVoLp/cS2/apekp2QU/veA0wvCuLfjgN5M5dWRnHvxiNU98u85pHpFoF7IC2hjT1RjzlTFmmTFmqTHmuvL77zXGrDDGLDbGvG2MaRGqDCIiEiHS34XiHTDgRtdJJAw27Szg7MdnkZVXwouXT+DYwR1cRxJxY82TMOtC2LXQaYxmCbHcf9ZwThzakXs+XsGM1aHfYksk0hljOhhjTjbGnGSMCfoPVcimcBtjOgIdrbXzjTGpwDzgVKAL8KW1tswY8w8Aa+3N1R1LU7hFRKKctbBjNrSZABqFbNTWZeZx/hPfU1Tm5/lLxzO0S5rrSCLulOyGd7pCl1PgYLcj0QD5xWWc9th3ZOYW897/TaJrq2TXkUT2COcUbmPM5cDtwJeAAQ4F7rLWPl3Ta0M2Am2t3WqtnV/+dS6wHOhsrf3MWltW/rTZeAW1iIg0VtZ6RXPbg1Q8N3Irt+Vy9uOzKfUHePmKCSqeReJbQO/LYcOrUJDuOg0pCbE8fuEYygKWq1+YR1Gp33UkEVd+B4y01l5srb0IGA1UO6hbISxroI0xPYCRwPf7PXQp8HE4MoiIiCNfnwRL/+46hYTYks3ZnDt1Fj4Dr141gYEdm7uOJBIZ+l8HBGDlQ66TANCzTQoPnjuCZVtz+OPbPxINDYVFQiALyN3rdm75fTUKeQFtjGkGvAlcb63N2ev+W4EyoNIN8owxVxpj5hpj5paVlVX2FBERiXRZc2HLh+BLcJ1EQmjBxl2c98RskuNjee2qg+jTLtV1JJHI0awHdD0L8je6TrLHEQPac/2R/Xhr/maem7XBdRwRF9YA3xtj7jTG3IE3M3qVMeYGY8wN1b0wqDXQxpjTgUmABWZYa98OJpUxJg74APjUWvuvve6/GLgKONJaW1DTcbQGWkQkSn13Hmz5CE7dBHEakWyM5vy0k0v+N4c2qQm8ePl4urTUmkqRAwRKwRdZ+58HApYrn5/H9JUZvHTFBMb1bOU6kjRxwayBLm9A/SQwBK82vdRaO6sO57qjusettX+u8rU1FdDGmMeAPsDL5XedA6y11v66htcZ4Flgp7X2+r3uPw74F3CotTaz2pOXUwEtIhKF8jfCe71gwG9h5L2u00gIzFi9gyuem0unFom8ePkEOqQluo4kEtnyN0JSJ/DFuk4CQE5RKac+8h05RaV8cO1k/T8sTgVZQD8LfGutfdIYEw8kW2t3hyVgRYYgCugVwEBb/kRjjA9Yaq0dWMPrJgHfAj8CgfK7/wg8BCTw8xzz2dbaq6s7lgpoEZEoNP9Gb83fyesgpavrNNKA1mXmMfWbdbw5P53ebZvx/GXjaZuqafoi1cqaC59NgINegB7nuk6zx+rtuZz66Hf0bZ/Kq1dNICE2xnUkaaJqKqCNMWnAQqCXrefifWPMGOBWoDuw5xMta+2wGl8bRAH9AfBra+2G8tvdgUestSfVJ3RtqIAWEYlCu3+EzJnQ9yrXSaSB/JiezX++XsPHS7YRH+Pj7DFdueHofrRMiXcdTSTy2QB8MADi0uDYORG1K8EnS7Zy9QvzOW9cN/5++lDXcaSJCqKAHgFMBZYBw/G2Sb7OWlvrQtEYsxKvE/feg71U1LzVvjaIAvprYCwwp/yuscBcILv8JCfXNnBtqYAWERFxw1rLrLVZ/OfrtXy7egepibH88qDuXHxwT406i9TW6v/CD7+Co76Gdoe4TrOPf36ygsemr+Xvpw/lvHHdXMeRhpTxjbelZPtDXSepljGmBK+grTDVWjt1r8fH4DX7mmit/d4Y8yCQY629rQ7nmmGtnVSnnEEU0NX+S1trv67LiWujsgK6tLSU9PR0ioqKQn36Ji0xMZEuXboQFxdZjS9EJIIFSmHe9dDv15A2yHUaqaNAwPLZsu385+u1LNq0m7apCVw2qScXjO9GaqL+JojUSVkBvNsN2kyEQ991nWYf/oDlkmd+YPbaLF69agIju7V0HUkaypdHQ2kuHDvbdZJqBTEC3QFv+W+P8tuTgVustSfW4VxHAucBXwDFFfdba9+q6bU1djCoKJCNMc3Zd374ztoGbUjp6emkpqbSo0cPTARNgWlMrLVkZWWRnp5Oz549XccRkWix4TVY/Rh0OkEFdBTKKSrl9bnpPD9rPeuzCujeOpm7TxvK6aM6kxintZEi9RKbDH1/DcvugcLtkNTedaI9YnyGh84dwUmPzOBXL8zn/WsnaZZJY5G/EVoOd52i3qy124wxm4wx/a21K4Ej8aZz18UlwAAgjp+ncFugxgI6mBHoK4G7gKLygxsvv+1Vx7C1VtkI9PLlyxkwYICK5xCz1rJixQoGDqy2Z5yIiMda+GQ0+IvgxCVgfK4TSZBWbc/l2ZnreXvBZgpK/Izp3pKLDu7B8UM6EBuj/44iDaZ4J/gLILmL6ySVWrYlh9P/8x3DOrfgxSvGE6f//6ObtfBaMvT7v4jfESPILtwj8LaxigfWAZdYa3fV4VwrrbX965IzmB76vwOGWGt31OUEoaTiOfT0bywitZIxHXYtgHFPqHiOAmX+AJ8vz+C5WeuZuTaL+FgfpwzvxEUH92BI5zTX8UQap4RWQPmeyzYQcb8rB3Vqzj/OGMZ1ryzkbx8u586TB7uOJPVRlOF9qJ3c3XWSBmGtXQiMaYBDzTTGDLLW1noEO5gCei1QUPtMIiLS5Cy/DxLbQc9fuE4iVQgELMu25vDVigxe+WETm3cX0iktkd8f159zx3ajlTpqi4SevwS+PhHaToaht7tOc4BTRnRmcXo2T834ifE9W3H80I6uI0ldFWz0rlPUGG4/E4CFxpif8NZAV8yyrnEbq2AK6D/gVejfs+8C69/UMWyj0axZM/Ly8vbcfuaZZ5g7dy6PPPII77zzDv369WPQoODW//34449ceOGFAGzcuJG0tDTS0tJo06YNn3/++T7PDfbYtc0gIlIvNgBpg6H9kRCT6DqNlLPWsnFnATPW7GDmmixmrt3BroJSACb0asVtUwZy1MD2mqYtEk4x8eCLh9WPwqDfR+TvzD8cP4BvV2fy4BerOW5IB81KjFZpQ+C4edAsbKtvo8VxdX1hMAX048CX7LdHllTvnXfeYcqUKUEXr0OHDmXhwoUAXHzxxUyZMoUzzzyzXseubQYRkXoxPhj5T9cpmrRAwLKroISM3GJWZ+Qxc80OZqzZQfquQgA6piVy5MD2TOrThoN7t6Zd88h70y7SZAy8Cb44An56Afpc7jrNAWJjfFw+uRe/f2MxM9dmMbFPG9eRpC5ik6DVKNcpIo61doMxZhLQ11r7P2NMW6BZMK8NpoCOs9beUK+ETczMmTN57733+Prrr/nrX//Km2++yc6dO7nsssvw+XwcffTRfPzxxyxZsqTGY91yyy289957xMbGcswxx3D66acfcOwvv/ySqVOnUlJSQp8+fXj++edZuHDhAc/r3bt3GL57EWmSijJg53zoeCxolCKkrLV8vjyDpVuyycgtJiOnmMzcIjJyi8nMLaYs8HNz0NTEWA7u3ZqrDunFwX3a0KtNikaRRCJFu8Og5UhYcT/0vjTi1kIDnDKiE//8ZCVPfrtOBXS02vwhlOzS0qr9GGPuwFtL3R/4H1437heAiTW9NpgC+uPyTtzvs+8UbqfbWO1j6VLIzm7YY6alweDqmyYUFhYyYsSIPbd37tzJySefzMEHH8zJJ5+8zyjyKaecwhNPPMFBBx3ELbfcElSErKws3n77bVasWIExht27d9OiRYsDjt2iRQuuuOIKAP70pz/x1FNPce211x7wPBGRkFn1KCz5C5y0GlL1YV2o7Mgr5g9v/ci0ZdsBaJ0ST9vUBNo1T6Rv+1Tv69QE2qUm0rVVEoM6NtfUbJFIZQwMuBFm/QK2fAyda72VbcglxMZw4YTuPPD5KtZk5NKnXarrSFJba6ZC3joV0Ac6DRgJzAew1m4xxgT1Ax5MAX1e+fUf9rrPAk1+In1SUtKeadfw8xro/e3evZvc3FwOOuggAM4//3w++OCDGo+flpZGYmIil112GVOmTGHKlCmVPm/JkiX86U9/Yvfu3eTl5XHsscfW7RsSEamLsgJvHV/nk1Q8h9Dny7Zzy1uLySks49YTBnLRwT2Ij1VxLBLVup8NJTuh7STXSar0iwndeHT6Gp6asZ6/nz7UdRyprfwNkNI4OnA3sBJrrTXGWABjTLXbZ+2txgLaWtuzPsnCooaR4mgVGxvLnDlz+OKLL3jjjTd45JFH+PLLLw943sUXX8w777zD8OHDeeaZZ5g+fXr4w4pI0/XTc1CcBQNvdJ2kUcovLuOvHy7j5TmbGNAhlRcuH8+ADs1dxxKRhuCLg/7Xuk5RrdbNEjhjVGfemp/O747tr0790aZgI7StcVZyk2GMudta+0fgNWPM40ALY8wVwKXAE8Eco8aPro0xycaYPxljppbf7muMqXwoVPZITU0lNzcX8KZYp6am8v333wPwyiuvBHWMvLw8srOzOeGEE3jggQdYtGjRAccGyM3NpWPHjpSWlvLiiy9WmkFEJCRsAFb8C1qN9bZjkQY1b8NOjn/wW175YRNXH9qbd/9voopnkcZo4+uw+A7XKap06cSeFJcFeHH2BtdRpDZKc731z9rCam/HAVhr7wPeAN7EWwd9u7X24WAOEMzcr/8BJcDB5bc3A3+tddQm5txzz+Xee+9l5MiRrF27lqeeeoorrriCESNGkJ+fT1paWo3HyM3NZcqUKQwbNoxJkybxr3/9q9Jj/+Uvf2H8+PFMnDiRAQMGVJlBRKTB5f3kTeEeeKOahzWgkrIA9366grP+O4uAtbx65UHccvwAEmJjXEcTkVDInAVL/wb5m1wnqVTf9qkc2q8tz87aQHGZ33UcCVZ++QceyZrCvZcYY0xLY0wrYB7wd+BuYF75fTUy1trqn2DMXGvtGGPMAmvtyPL7Fllrh9czfNBSUlJsfn7+PvctX76cgQMHhitCveXl5dGsmdcZ/Z577mHr1q08+OCDjlMFJ9r+rUUkzPwlXvdYXzBtNaQmK7flcuPrC1myOYezRnfh9pMGkZoY5zqWiIRS/gZ4rzf0vx5G3ec6TaW+XZ3JhU/N4d4zh3HWmK6u40gwrIXiHRCTBHFB7dDklDGmwFob9FrkOp6jGG9A2OD19drzEGCttTX2+Qrm3U6JMSap4gTGmN7s1Y1bgvPhhx/y97//nbKyMrp3784zzzzjOpKISP0UZUJ8C4jReriGUFzm59Ev1/DY9LU0T4rjv78YzXFDOriOJSLhkNIdup0Fa5+AobdDXOQt1ZjUpw3926fy1IyfOHN0F22JFw2MgcS2rlNEmmUVg8J1VWUBbYz5zFp7DHAn8AnQ1RjzIt7eWBfX56RN0TnnnMM555zjOoaISMOZ+3+QvRROWByR+5dGk7nrd3Lzm4tZm5nPaSM7c9uUQWrUI9LUDLgRNrwCa56EgTe4TnMAYwyXTerJ799czMy1WU1+X+jS0lLS09MpKipyHaVqZQUQKIX4mpeOhlNiYiJdunQhLi46Z1dVNwLdFsBa+5kxZh4wAW9o+zpr7Y5whBMRkQiVtx42veG94VPxXGe5RaX885OVPD97A51bJPHMJWM5rH8717FExIXWY6DPVdAscjfAOXlEJ/756Qqe/HZdky+g09PTSU1NpUePHpE7Gp+3DsryoUXkLMW01pKVlUV6ejo9ezr5Wa/3GtrqCug0Y8zpldx/iDEGa+1b9T25iIhEqZUPAj7o/xvXSaLWF8u386d3lrAtp4hLJvbgpmP6k5KgdeQiTdq4/7pOUK3EuBgunNCDBz5fxZqMXPq0S3UdyZmioqLILp7B61Hii6zZTMYYWrduTWZmppPzW2ufqe8xqi2ggSl4o84HnBtQAS0i0hSV7Ia1T0L3cyG5i+s0UWdHXjF/fn8Z7y/aQv/2qTx2wShGdmvpOpaIRIqSbEh/G3peFJG7G1wwoRuPTl/D09+t5+7ThrqO41REF88AgeKIXE8f8f9uNaiugN5grb00bElERCQ6bHwNyvK8raskaMVlfp6duZ6Hv1xDcWmAG47ux9WH9iY+VlPgRWQvG1+FOVdBSk9of6jrNAdo0yyB00d25s156dx0TH/1a4hUNuCtf46wEehIYIyJAX5jrX2gLq+v7q92dH80EAbbtm3j3HPPpXfv3owePZoTTjiBVatWsX79eoYMGRL0cU477TRGjBhBnz59SEtLY8SIEYwYMYKZM2fu87z169fz0ksv1Xi8YJ8nIlInva+AY2ZByxGuk0QFay0fLt7KUf/6mrs/WsHo7i356LpJ/ObIviqeReRAPS6EhDaw4n7XSap06aSeFJcFeHH2BtdRmrT09HROOeUU+vbtS+/evbnuuusoKSnxHgyUgTGces4VTJgwodLX/+9//9tTd8THxzN06FBGjBjBLbfcEsbvIvystX7gvLq+vrq/3BfW9aBNgbWW0047jcMOO4y1a9cyb948/v73v7N9+/ZaH+vtt99m4cKFPPnkk0yePJmFCxeycOFCDj744H2epwJaRJyz1ptS2KbyP8ayr/kbd3Hmf2fx65fmkxIfy/OXjeOZS8Y16XWDIlKD2CToew1sfh+yV7hOU6l+7VM5tF9bnpu9geIyv+s4TZK1ltNPP51TTz2V1atXs2rVKvLy8rj11lu9J8TEs9v0Yt7CH8nOzmbdunUHHOOSSy7ZU3d06tSJr776ioULF3LPPfeE+btx4jtjzCPGmMnGmFEVl2BeWGUBba1d0nD5Gp+vvvqKuLg4rr766j33DR8+nMmTJ+/zvIKCAs4++2wGDRrEaaedxvjx45k7d26Nx//666/3fCI0cuRIcnNzueWWW/j2228ZMWIEDzzwAOvXr2fy5MmMGjWKUaNG7Rmx3v95IiINwlr44nBYUe8Glo3epp0F/N9L8zn9sZls3FnAP84Yyoe/mczkvtqPU0SC0O/X4EuAlZH7Pu6yST3JzC3m/UVbXUdpkr788ksSExO55JJLAIiJieGBBx7g6aefpqCgAIC33n6bk046iXPPPZdXXnkl6GPfe++9jB07lmHDhnHHHXcA3gDdgAEDuPjii+nXrx8XXHABn3/+ORMnTqRv377MmTMHgDvvvJMLL7yQgw46iL59+/LEE0808HfeYEYAg4G7gPvLL/cF88JG0e5z6VLIzm7YY6alweDBVT++ZMkSRo8eXeNxHnvsMVq2bMmyZctYsmQJI0aMCOr89913H48++igTJ04kLy+PxMRE7rnnHu677z4++OADwCvOp02bRmJiIqtXr+a8885j7ty5BzxPRKRBbP8SMr6GnpqgVJWd+SU8/vVa/vfdenw++M2RfbnqkF7qri0itZPYDnr+Ego2/zzzJ8JM7tuGfu2b8fjXa5kyrCOJcTGuI7n1+WEH3tftbOh3jbcf8/QTDny818XepWgHzDhz38eOml7t6ZYuXXpALdK8eXO6devGmjVrGNa/My+/8DS333k37Tt04IwzzuCPf/xjjd/GZ599xurVq5kzZw7WWk4++WS++eabPcd9/fXXefrppxk7diwvvfQSM2bM4L333uPuu+/mnXfeAWDx4sXMnj2b/Px8Ro4cyYknnkinTp1qPHc4WWsPr+trq118ZYyJMca8WNeDNwmluTD7Mtj4ZqUPz5gxg3PPPReAIUOGMGzYsKAOO3HiRG644QYeeughdu/eTWzsgW++SktLueKKKxg6dChnnXUWy5Ytq/v3ISJSk+X3e2/qelzgOknE2bSzgDvfW8rB93zB1G/XcdLwTnx102HccHQ/Fc8iUjdjH4XDPojI4hm8Tsq/O3YAqzPyuO6VBfgD1nUk2cv2zetYvWYdkyZPpl+/fsTFxbFkSc0TjD/77DM+++wzRo4cyahRo1ixYgWrV68GoGfPngwdOhSfz8fgwYM58sgjMcYwdOhQ1q9fv+cYp5xyCklJSbRp04bDDz98z+h0JDHGpBlj/mWMmVt+ud8YkxbMa6v9q26t9Rtjuhtj4q21JQ0Tt+FVN1IcunMO5o033oDYFNg2DYoyoNsZDXb8W265hRNPPJGPPvqIiRMn8umnnx7wnAceeID27duzaNEiAoEAiYmJDXZ+EZF97F4KWz+GoXdBjH7XVFi2JYfHv1nLB4u34jNwyojOXHVIL/q21xpnEaknX5x3XbAZ4lt5a6MjzNGD2nPblEH85YNl3PneUu46ZXDUb1FUZ9WNGMcmV/94YpsaR5z3N2jQIK8W2UtOTg4bN26kT58+PPXo39mVnUvPnj33PPbyyy/zt7/9rdrjWmv5wx/+wFVXXbXP/evXrychIWHPbZ/Pt+e2z+ejrKxsz2P7/wxE6M/E08AS4Ozy2xcC/wNOr+mFwbT/XIe3yPo2Y8wNFZc6R20kjjjiCIqLi5n6xJPe9Ixtn7J0wQy+/fbbfZ43ceJEXnvtNQCWLVvGjz/+GNTx165dy9ChQ7n55psZO3YsK1asIDU1ldzc3D3Pyc7OpmPHjvh8Pp5//nn8fq+Jw/7PExGptxX/gpgk6Psr10mcs9Yyc+0Ofvn0HE546Fs+X7adSyf24JvfH859Zw1X8SwiDSdnJbzbA9Y/7zpJlS6b1JOrDunF87M38OhXa1zHaTKOPPJICgoKeO655wDw+/3ceOONXHzxxSQnJ/Py6+/zyZtPs379etavX8+8efOCWgd97LHH8vTTT5OXlwfA5s2bycjIqFW2d999l6KiIrKyspg+fTpjx46t/TcYer2ttXdYa9eVX/4M9ArmhcEU0GuBD8qfm7rXpUkzxvD222/z+eefc9r1L0OglM+e/jUdOnTY53nXXHMNmZmZDBo0iD/96U8MHjyYtLSaZwf8+9//3jPlOy4ujuOPP55hw4YRExPD8OHDeeCBB7jmmmt49tlnGT58OCtWrCAlJQXggOeJiNRbv2tg7GPep+RNUH5xGfM37uKF2Rs49dHvOP+J71m2JZvfHdufmbccya0nDqJjWuSNDolIlEvtBy2Hex9i2oDrNFW6+bgBnDayM/d9torX5m5yHadJqKhFXn/9dfr27Uu/fv1ITEzk7rvvZv1PP7Fh0xYmHDR+z/N79uxJWloa33//fbXHPeaYYzj//PM56KCDGDp0KGeeeWatB+aGDRvG4YcfzoQJE7jtttsibv1zuUJjzKSKG8aYiUBhMC801ga3XsEY0wzAWptXl4T1kZKSYvPz8/e5b/ny5QwcODDcUSpnLbzXC5oPgMM/3uchv99PaWkpiYmJrF27lqOOOoqVK1cSHx89m5pH1L+1iEgIBQKWjTsLWLEth+Vbc1mxLYcV23LZkFWw5zndWydz5SG9OGNUFzXNEZHQW/8yzDwfDnkPupzkOk2VSsoCXPbsD8xcm8Wh/drSIjmOFknxtEiOo2VyHGnJ8bRIiqNFchwpCbHE+XzExhhifYbYGB8xPkNcjPGufT6Midipv0CEvz8OlEHOckjsAInh3f3hzjvvpFmzZtx0003VPq+yfz9jTIG1NiWU+fY61wjgWSANMMBO4CJr7eKaXltjZxNjzBDgeaBV+e0dwC+ttUvrkblxMcab1li47YBOiQUFBRx++OGUlpZireWxxx6LquJZJOLMnw/bttXppfNyLI9vgu92g3qdBCfRFHFzh6d4JutUNpR0dh0n5MoslJb/bBigZxIMToEzusOAFBiYAp0TC/BlLYVp+jMoImFgU8C0he9uhdTI/dAuHvhPW8tt2bAqPYOVpZBdBnkNsE20D+93sjHl1+X3719f719u11R+n9Enlb9eekj9A0YaXyy0GOo6RUSz1i4Ehhtjmpffzgn2tcG0Bp0K3GCt/QrAGHMY8ARwcG2DNmqDfl/p3ampqUHt+ywiQdq1C5KToV27oJ4esJYv0wt5fOlufsgoJi3ex6m9U0iJDWYFi4wyX3JczMeUpp3IJoJqThnVfAZ6NY9jQMt4+raII0k/JyISCTIuhi3/go6xkNDFdZoqNQMe6LPvfaUBy+7iANnFfnaXBNhdHCCvNECZtfgD3uN+W34dsN4HmQGLtVDxWXfAWizsuW/vx6pS0yTbhVtyeHV1LjcVlNAiWYNbDeXOO+90HSEo5R237wAOKb/9NXCXtbbGzZGDKaBTKopnAGvtdGNMWIbWo44NQPYyaDHEdRKRxquszCueBw2q9mklZQHeXbiZqd+sY3VGHp1bJHHHSYM4e0xXbSsUrIAfPrwU4sdx4THXROxWKiIijV7f26D4GmjWw3WSWosD2pZfIsmSabOY8sVO3l+8lQsndK/TMay1kTnNvHgHFO+E1D5gIu+D4GCXEIdYnbtwB/Mucp0x5ja8adwAv8DrzC37W/p3+PEOOG1r2NcbiDQZZWVQyb7oFfwBy1Mz1vHUjJ/YnlPMwI7NefDcEZwwtCNxMZH3RySibX4fclfDxFdVPIuIuBSX6l3AG7CJwKIo2gxuk8iAZoa35qfXqYBOTEwkKyuL1q1bR14RXVYAZfkR+XNirSUrKysStt/tba3dew/iPxtjFgbzwmAK6EuBPwNvld/+tvw+2V/nKbD4T7DpLeh7Vc3PF5HasRYCAYipeg3Y+4u2cPdHKzi4d2vuPXM4k/u2ibw/bNFixf2Q0h261vhhrIiIhJoNwNenQPP+MOo+12minomP5/R2cPe63azLzKNX22a1en2XLl1IT08nMzMzRAnroSgDbBlsX+46SaUSExPp0sX5UoRCY8wka+0MqF0X7hoLaGvtLuA3xphU72b4u3BHjRbDvO0GNr6mAlokFMrKvOtqRqDXZ3kd+5+9dJxGnOsjUAqtRkPPC71mJCIi4pbxeaPQa6bCkNsgvvH3pQip2FhOaeXnnp98vL1gMzce079WL4+Li6Nnz54hCldPH50HyV1g1Aeuk0SyXwHPlq+FrujCfXEwL6zx3aUxZqgxZgHeHPGlxph55Z25m7S3336bESNG7HPxxcSwpnQ0ZEyHwu0Ner6//e1ve84TExOz5+uHHnqoQc8jEtH85a08qxmBzsgtpnVKvIrn+vLFweh/Q58rXScREZEKA2+EslxY+6TrJNEvNpb2CTCpT2vemr+ZQGPaniN/gzeDTKpkrV1orR0ODAOGWmtHWmsXBfPaYIYVHufALtxTaeJduE877TROO+20PbenTp3Kiy++SK/DboFPXob0t7ytrRrIrbfeyq233gpAs2bNWLhwYYMdWyRqVBTQ1YxAZ+QU0a6583U10S1/I+SthXaHae2ziEgkaTXa+9288t/Q/zfeh51SN+XvJc4Y2oHr3lrKnPU7mdCrteNQDcBfAq1GQssRrpNEJGPMDVXcD4C19l81HSOYIZoDunAD6sK9l1WrVnHXXXfx/PPP42s1DHv4NG55YjVDhgxh6NChvPrqqwBMnz6dww47jDPPPJMBAwZwwQUX7OlCN2/ePA499FBGjx7Nsccey9atW2s8r9/v53e/+x1jx45l2LBhPP7443vOc+ihh3LKKafQq1cvbrnlFl588UXGjRvH0KFDWbt2LQAXX3wxV199NWPGjKFfv3588IGmeUiEq5jCXc0I9PacYtqlJoQpUCO1/H748hgoqtt+2yIiEkIDb4SCdNj4uusk0a28gD6mb0tS4mN4a36640ANJCYejvwS+lzhOkmkSi2/jMGbxt25/HI1MCqYAzSKLtx/fn8py7YEvfd1UAZ1as4dJw2u8XmlpaWcf/753H///XTr1g2At2ZmM2/BjyxatIgdO3YwduxYDjnE26R9wYIFLF26lE6dOjFx4kS+++47xo8fz7XXXsu7775L27ZtefXVV7n11lt5+umnqz33U089RVpaGj/88APFxcVMnDiRY445BoBFixaxfPlyWrVqRa9evbj88suZM2cODz74IA8//DD//ve/AVi/fj1z5sxh7dq1HH744axZsyYSuuKJVC6INdAZuUUM7JgapkCNUMkuWPcUdD8Pkjq6TiMiIvvrdAKMfhg6Huc6SXSL80bvkwhwwtCOfPTjNv588hCS4qv+kD4qqEt7tay1fwYwxnwDjLLW5pbfvhP4MJhjqAt3Pd12220MHjyYc845Z899M2d8w70XJhCz6TXa9ziPQw89lB9++IHmzZszbty4PV3nRowYwfr162nRogVLlizh6KOPBryR5Y4da37j+tlnn7F48WLeeOMNALKzs1m9ejXx8fGMHTt2zzF69+69p7AeOnQoX321Z0IBZ599Nj6fj759+9KrVy9WrFjBiBEjGuTfRqTB1bAG2h+wZOYW0y5VHwLV2Zqp3tYXA290nURERCpjfND//1yniH4VH8aXlXH6qC68Pi+dz5Zt45QRnd3mqq9vTwcMHPK26ySRrj1QstftkvL7ahR0F+665QqPYEaKQ2H69Om8+eabzJ8/f5/7A/jo5lsEq3dDj/P2eSwh4eeppTExMZSVlWGtZfDgwcyaNatW57fW8vDDD3PssccekGvv8/h8vj23fT4fZRWjeHDA9j7a7kciWg0j0Fn5xQQstG+uKdx14i+BlQ9B+yOh5XDXaUREpDrp70HmDBj5T9dJotNeBfT4nh3o3CKJt+Zvju4C2lrvZ6Lzya6TRIPngDnGmIpPGk4Fng3mhVWO7xtj3jfGvFfVpf6Zo9uuXbu45JJLeO6550hN3Xe66OTJk3lvYSJkfkfWpkV88803jBs3rspj9e/fn8zMzD0FdGlpKUuXLq0xw7HHHst//vMfSktLAW8tdn5+fq2+j9dff51AIMDatWtZt24d/fvXroW/SFjVUEBn5BQDqIlYXeWuAuuHgTe5TiIiIjXZtQCW3wvZkbnXb8Qrn8JNWRk+n+G0kZ35dnUmGTlFbnPVR+5qKM6CNk2613NQrLV/Ay4BdpVfLrHW3h3Ma6ubIH8fcD/wE96m0k+UX/KAtfUJ3Bj897//JSMjg1/96lf7bGX16quvctppp7E98VAAnrrjOP75z3/SoUOHKo8VHx/PG2+8wc0338zw4cMZMWIEM2fOrDHD5ZdfzqBBgxg1ahRDhgzhqquu2md0ORjdunVj3LhxHH/88fz3v//V+meJbDVM4c7I9f7oqYlYHbUYAqesh47H1vhUERFxrO81EJMIKx5wnSQ6VXwYXz4QddqozgQsvLtwi8NQ9bSjvH5oc5DbHFHAGPO8tXa+tfbB8ssCY8zzNb8STEUX6GoOPtdaO6am+0IpJSXF7j+yunz5cgYOHBiuCHXz8SjwJcCxtZuaHS4XX3wxU6ZM4cwzz6z2eVHxby1Nw+rVsGIFnHgi+A78/O/lORv5w1s/MvOWI+jUIslBwChWuB0SWoMvmNYYIiISEeZcDeuegVM3QmI712mii7XwwQfQvz/06wfAqY9+R1Gpn0+uP8RxuDqacxVseBXO3BmVjcSMMQXW2rDs9mSMmW+tHbXX7RjgR2vtoJpeG9Q2VsaYXnsdvCfaxio4PS+ClK4QKHWdRKRx8Pu9fYkrKZ7h5yncbZppBLrWZl8M0yZ7byhERCQ6DPgtBIph1WOuk0QfY7wZbXvN3jxjVGdWbMtt8N19wqb9ETDolqgsnsPFGPMHY0wuMMwYk2OMyS2/nQG8G8wxghlq+C0w3RizDjBAd+CquoZuUgZcB1znOkWVnnnmGdcRRGqnrKzaLay25xbROiWe+Fj94aiV3Utg6ycw7K/eGwoREYkOzftD/+u9a6m92Nh9Cugpwzpx1wfLeGt+OoM61TgQGXm6n1Pzc5o4a+3fgb8bY/5urf1DXY4RTBfuT4wxfYEB5XetsNYW1+VkDc1aGx1do/M3eSPRUaimKf4iYeX3V7n+GbwR6LZa/1x7K/4FMUnQ92rXSUREpLZGaw10ne1XQLdMieeIAe14Z+EWbjl+ALExUfSBfOFWCJRAcrdG/WF4+VTrucBma+2UehzqY2PMAXP1rbXf1PTCYH8qRgODgeHAOcaYX9YuX8NLTEwkKysr8gu8tf+Dd7tB3jrXSWrNWktWVpYai0nkqGEEOiO3iPbqwF07hdtg/YvQ6xJvDbSIiESf0jxY+xTYgOsk0SUubk8TsQqnj+rCjrxivl2zw1GoOlr9OLzXC8ryXCcJteuAhmg9/7u9LrcB7wN3BvPCGkegy7uR9QYWAuUtcLF4e2c506VLF9LT08nMzHQZo0axJV3pC2TMfZSs9pe7jlNriYmJdOnSxXUMEU9ZWbUj0NtziujfPrXKx6US61/w+jQM+K3rJCIiUldbPoTvL4eCLZBWPmk0pSe0Lu/5u/H1A1+T2g9aDodAGaS/feDjzQdBi8FQVghbPjjw8RbDvKnjpbneMqAKJgY6HANxzer/fYXafiPQAIf3b0eL5Djemr+Zw/tHUWO2HbMgbQjENd73QcaYLsCJwN+AG+pzLGvtSfsduyvw72BeG8wa6DHAIBthQ71xcXH07NnTdYwgDIRt42lX+BXtBt7vOoxIdPP7qxyB9gcsO/JKNAJdWwNugLaHQGof10lERKSuup4BzXrBj7f/fF/vK34uoGecfeBrBtwALe8Hf1Hljw+5wyugS3dX/vjIe70CunDrgY8P/xsM/mOdv52wiY2FgoJ97oqP9XHy8E68+sMmcopKaZ4Y5yhcLQT8kDUbup/vOkl9xRpj5u51e6q1dupet/8N/B4IxacE6UBQ2w4FU0AvAToAW+uTqEnrfg7MvwFyVkPzvq7TiESvsjKoYklBVn4x/oClfXOtga4V44M241ynEBGR+vDFwnHzoGDzz/fFt/z56xOWHPiaimU7MUmVP57Ytvx5bap4vL13ndJ938e/ORV2zqtVfGcqGYEGbxr3c7M28PGPWzlnbDcHwWopZxmU5jSG/Z/Lqtoq2RgzBciw1s4zxhxW3xMZYx7Gm1UN3rLmEcD8YF4bTAHdBlhmjJkD7GkeZq09uXYxm7CuZ3oF9MbXYMitrtOIRK9qmohVbGHVNlUj0EH76XnImgOjHtD+zyIi0S6+hXepTIvBVb/OF1PD43HVPx6TsO/jR34JSR2qSxo5KlkDDTC8Sxq92qbw5vzN0VFA75jlXbc92G2O0JoInGyMOQFIBJobY16w1v6ijsfbe6S7DHjZWvtdMC8M5h3TnXVJJHtJ6QqHvANtJ7tOIhLdqmkilpFbBKAR6NpY/yLkb1DxLCIiDSeadp6pYgTaGMMZo7pw76cr2bSzgK6tkh2Eq4XOJ8PEFtCst+skIVO+5dQfAMpHoG+qR/EM8CpQsX5tjbW2KNgX1tiF21r7dWWXuiZtsrqcAgmtXKcQiW5BjEC30xro4PiLIOMb6HC06yQiItKYFG6FuddC1g+uk9QsNhas9d5f7OfUkZ0BeHvB5gMeizhJHaD72Y16+6qGYoyJNcb8E2/N87N4jbE3GWP+aYwJasF7lQW0MSbXGJNTySXXGJPTMN9CE2ItrHoM1jltXi4S3aoZgd5eMYW7mUagg5I5E/yFKqBFRKRh+eJh1SOw/SvXSWpW8Z6iklHozi2SOKhXa96anx7Z2+YW74SVj3gd2JsIa+30euwBfS/QCuhprR1trR2Ft+NUC+C+YA5QZQFtrU211jav5JJqrW1ex8BNlzGw8VVY/g/XSUSiUyDgfRBV1Qh0bhGtUuKJjw12e/smbts0MLHQ/jDXSUREpDFJaA3J3WDXAtdJahZXPuBYSQENcPqozqzPKmD+xt3hy1Rbmd/BvGshb63rJNFiCnCFtTa34g5rbQ7wK+CEYA6gd5rh1O1syF4Gu5e6TiISfSr+uFUzAt0uVaPPQYtJ9JaWNOL9IkVExJFWI6OjgK54T1FJIzGA44d2JCkuhrfmp4cxVC3tmOV9IN6q0ubVciBb2fbM1lo/P3flrpYK6HDqeoa3ZczGV10nEYk+FeuTqiigM3OLtP65NobeAZPfcJ1CREQao5ajIGcVlOa5TlK9aqZwAzRLiOW4IR14f9EWissOXCcdEXbMhJYjITbJdZJoscwY88v97zTG/AJYEcwBVECHU1IHaHeot51VJK+lEIlEFX/cqpjCvT2nmPYagQ5OWaF+B4mISOi0HAnJnaFgk+sk1athCjd407hzisr4cnlGmELVQqDU244y+vd/DqdfA782xkw3xtxffvka+A3eNO4aqYAOt+7nQkI7KM12nUQkulQzhdsfsGTmFdNOW1gFZ95v4OORKqJFRCQ0Ok+BUzdB2kDXSapXwwg0wMG929AiOY4vV0RgAZ2z0ttVo3Hv/9ygrLWbrbXjgbuA9eWXu6y146y1QbVc1+af4db7CuhzpesUItGnYgp3JSPQO/NL8Acs7TWFu2bWwtbPoPUYbXchIiKhES1/X2pYAw0Q4zMc3Ls1367egbUWE0nfW4shcOYu8AW1+5LsxVr7JfBlXV6rEehwq/ifrmS3Rn9EaqOaEejtOUUAtEtVAV2j3NVQsFHbV4mISGgtvRu+OdV1iuoFMQINMLlvW7blFLE2MwLXdMenQWyy6xRNSsgKaGNMV2PMV8aYZcaYpcaY68rvb2WMmWaMWV1+3TJUGSLWlk/grXbR0Z1QJFJU00QsM9fbA1pTuIOwbZp3rQJaRERCqTQHtnwE/hLXSarm83mXGgroSX3aAPDt6h3hSBW8mRfCRjUEDbdQjkCXATdaawcBE/AWaw8CbgG+sNb2Bb4ov920tB7rjT5vfM11EpHoUU0TsYoRaE3hDsK2aZDSE1J7u04iIiKNWctRXpOr7AjfvjU2tsYCumurZHq0TmZGJBXQBZth/QuR36itEQpZAW2t3WqtnV/+dS6wHOgMnAI8W/60Z4FTQ5UhYiW0hg5HwQZ14xYJWjUj0BnlI9Btm2kEuka9LoNhd7lOISIijV3Lkd71rvluc9QkLq7aNdAVJvVtw+x1WZSUBcIQKgg7ZnnXbdRALNzCsgbaGNMDGAl8D7S31m4tf2gb0D4cGSJO93Mg/yfYOdd1EpHoUMMIdKuUeOJj1dahRl1Ogp6/cJ1CREQau9TeEJsKOyN8yWIQI9AAk/q0Jb/Ez4KNu8IQKgg7ZoEv4ecPKiRsQv5u0xjTDHgTuN5am7P3Y9ZaC1Q6BGuMudIYM9cYM7csiB/qqNPlFK9jnqZxiwSnrMxbp1RJ98uM3GLaaQ/ommXOhF2LXacQEZGmwPigx3mQ0t11kuoFWUAf1Ls1MT7DjDURMo07c6a3o0ZMvOskTU5IC2hjTBxe8fyitfat8ru3G2M6lj/eEah0UzVr7VRr7Rhr7ZjYSqZsRr34ljDhOehzteskItHB7690+jZARk4R7bT+uWYLfgffX+46hYiINBXjHodBv3OdonqxsUFN4U5LimN4l7TIaCRmLcS3gPZHuU7SJIWyC7cBngKWW2v/tddD7wEXlX99EfBuqDJEvB7nqpGPSLDKyqosoLfnaAS6RiXZkPU9dFT3bRERCSMb8JqJRaogR6ABJvVty+L03WQXOP5+jIHDP4Zhd7rN0USFcgR6InAhcIQxZmH55QTgHuBoY8xq4Kjy201X+ruw7jnXKUQin99f6frnQMCSmVdMe21hVb2M6WD92r5KRETCJ28dvJ4GG193naRqcXFBF9CT+7YhYGHmWsej0GpC7FTI5kZba2cABy5W9BwZqvNGnbVPw855XlMfowZIIlWqYgQ6K78Ef8BqC6uabP0MYlOgzUGuk4iISFOR3NUbfd45H3qc7zpN5WoxAj2iawuaJcTy7ZodHD+0Y4iDVeO7c71/10Peqvm50uBUsbnW/Rwo3Ow1AhCRqlWxBjoj19sDWlO4a5AxHdodCjH6dxIRkTDxxUGLobArgjtxx8ZCIOBdahAX42NCr1Zu94O2FjK+8T4UFydUQLvW+SSISVQ3bpGalJVVOoU7I8fbA1pNxGpwzGwY86jrFCIi0tS0GuUV0JE67TguzrsOehp3WzbuLGBjVkEIQ1Ujfz0UbYO22v/ZFRXQrsWlQqcTYNMbEPC7TiMSuaoqoDUCHZy4VGjWw3UKERFpalqOhJJdkL/BdZLKVcxuC6ITN8Ckvm0A+HZNZqgSVW/HLO9aS7KcUQEdCbqdDTHJUJjuOolI5KpiCvf28hHotiqgq/bjXbBKo88iIuJAu8NgyO2Ru4So4r1FkCPQvdqk0CktkW9XOZrGnTnTm76dNsTN+SV0TcSkFrqe6RXRpqqeayJSVROxjNwiWibHkRB74Oi04G0fsuoh6DTFdRIREWmK0gbAsD+7TlG1WhbQxhgm9W3DJ0u24Q9YYnxhfv/ediIktgWfyjhXNAIdCXwxXvHsL9E0bpHKWFvlNlbbc4rVgbs6uxZAcZa2rxIREXdKsmH3j65TVK6Wa6DB2w86p6iMxem7Q5OpOj3Og6F3hP+8socK6Eixcx683cHrlCsi+/KXf7BU6Qh0saZvV2frNO+6w1Fuc4iISNM19//gq+Ncp6hcLUegASb1aYMxhL8bd1EGFG4N7znlACqgI0XzgRAoUTdukcpUFNCVduEu0gh0dbZNgxbDIKm96yQiItJUtRoFhVugcLvrJAeqZRMxgFYp8Qzu1Jxv14S5gF77JLzdCUp2h/e8sg8V0JEiNtnb0mrTm97G6CLys4pPhfcbgQ4ELJm5xerAXRVrIbYZdD7ZdRIREWnKWo7yriNxP+g6jEADTOrTlvkbdpFXXLvX1UvmTG/QLb5F+M4pB1ABHUm6neOtVdz+leskIpGliincOwtKKAtYjUBXxRg49F0Y/hfXSUREpClrOcK73jXfaYxKxZT3IqplAT25bxvKApbv12WFKNh+rPW2sNL2Vc6pgI4knY6D2FTY8KrrJCKRpeKP2n5TuLfneHtAt2+uEehK+UtcJxAREYH4NGjWG3ZG4Ag0eB/Q12IKN8Do7i1JiPXxbbjWQeeugpKd0Pbg8JxPqqT+55EkJhHGPALN+7tOIhJZqhiBzsit2ANaI9CV+nSst93F2MdcJxERkaZu7GOQ2M51isrFxdV6BDoxLoZxPVsxI1zroDNnetcagXZOI9CRptcvoc141ylEIksVI9AZGoGuWuFW2L0YUrq7TiIiIgIdj/l5KnekiY2tdQENcEjftqzJyGNrdmEIQu2n47Fw0HPQfEDozyXVUgEdiXbMhp9ecJ1CJHJU0UQsI6diBFoF9AG2fe5da/9nERGJBKV5sP4VyF3jOsmB6lhAT+rbBiA807iTO0HPC8GofHNN/wUi0er/evvl+YtdJxGJDFVsY7U9t4iWyXEkxB64vVWTt3UaJLSJ3E/7RUSkaSnLh5nnweYPXCc5UB3WQAMM6JBKm2YJod8PujQH1kzVHtARQgV0JOp+DpRmw9bPXCcRiQzVjEC30/rnA1kL2z+HDkfpk2oREYkMSe0hqSPsjMBO3HVYAw1gjGFSn9Z8t2YHgYANQbBymbNgzlWQvSx055Cg6Z1VJGp/JMS3hI2vuU4iEhmq6sKdW0w7rX8+kC2DwbdC78tdJxEREflZy5GRuxd0HQpogEl925KVX8LybTkNHGovO2Z6H4i3Hhe6c0jQVEBHoph46Ho6pL8L/iLXaUTc8/sPGH0GyMwp0gh0ZXxx0O/X0OFI10lERER+1nIU5CyHsjA03aqNehTQk8OxDnrHTEgbCnGpoTuHBE0FdKTqdjb4YiF7ueskIu6VlR1QQAcClozcYnXgrszWaVCwxXUKERGRfbUaCdYPu390nWRfcXHeh/WBQK1f2r55Iv3aNwvdOuiAH3Z8r/2fI4gK6EjV/kg4bZv3i0akqfP7D5i+vbOghLKApZ06cO/LXwzfnALL/u46iYiIyL46HAOnbIDWY10n2VfFh/QVTUtr6ciB7Zm1LoufduQ3YKhyuaugLBfaqICOFCqgI5UvxpvKbS3Y2n8aJtKolJVVsge016W+fXNN4d7HjpngL9T2VSIiEnnimkFKNzDGdZJ9VRTQdejEDXDJxB7ExRge/mJ1A4YqlzYQzsiCLqc2/LGlTlRAR7K89fB+X9j0tuskIm5VsgZ6e67XH6CdCuh9bZ0GJgbaH+Y6iYiIyIE2vQWL73CdYl8V7zHquA66XWoivzyoB+8s3MyajLwGDFYuoZX34YNEBBXQkSy5izdlY+OrrpOIuFXJGujM8hFoTeHez7Zp0GYCxDV3nURERORAmTNh2T8gULfR3pCoZwENcNUhvUiMi+Ghhh6F/v4K2Phmwx5T6kUFdCTzxULXM70N58tCsKZCJFpUsgZ6e07FCLQK6D1KdsPOeZq+LSIikavVKAgUQ84K10l+FhfnXddxCjdA62YJXHRwD95fvIVV23MbJldRBqx9EvLWNszxpEGogI503c721jNu/tB1EhF3KhmBzsgtpkVyHAmxMVW8qAmKb+E1Z+lzleskIiIilWtZ3iB3ZwTtB90AI9AAV07uRXJcDA9+3kCj0Dtme9dqIBZRVEBHuraTILGDpnFL01ZJAb09p4j22gP6QCldIamD6xQiIiKVS+0HMcmwa77rJD9roAK6ZUo8l07qyYc/bmX51pz659oxE0wstBpd/2M1AsaYrsaYr4wxy4wxS40x17nIoQI60vliYMTfoecvXScRcaeSKdwZucWavr03a2HOVbD1M9dJREREquaL8aZxl+xyneRnDVRAA1w+qRepCbH8+/NV9T4WmTO9f6vYpPofq3EoA2601g4CJgC/NsYMCneI2JqfIs71uth1AhF3AgHvsv8U7pwierdt4yhUBMpdA2umQssRrpOIiIhU78jpXiEdKeq5jdXe0pLjuGxyT/79+WqWbM5mSOe0uh3IWohJgraavl3BWrsV2Fr+da4xZjnQGVgWzhwagY4WuWthw2uuU4iEn9/vXe81Ah0IWDLzNAK9j23TvGs1EBMRkUgXScVzhbi4BhmBBrh0Uk+aJ9ZzFNoYOOJTGHFPg2SKErHGmLl7Xa6s6onGmB7ASOD7sKUrpwI6Wqx6BGZdCKUNsJ5CJJpU/DHbawR6V0EJpX5Le21h9bNt0yClBzTr7TqJiIhI9Qq3wpdHezvNRIrY2AYroJsnxnHlIb34fHkGizbtrttBrG2QLFGmzFo7Zq/L1MqeZIxpBrwJXG+tDXtxpAI6WnQ/BwIlkP6u6yQi4VXJCPT28j2g2zdXEzEAAmWw/Utv9NkY12lERESqF98Ktk+HzO9cJ/lZAxbQABdP7EmL5DgeqOso9OyL4dszGixPY2GMicMrnl+01r7lIoMK6GjRejwkd9M0bml6KhmBzsjVHtD7KNzqjTx3PMZ1EhERkZrFJEDaYNgVYVtZNWAB3SwhlqsO6c30lZnMXLOj9gfY/pXXgVv2MMYY4ClgubX2X65yqICOFsZAt7Ng26eR1bVQJNQqRqD3LqDLR6DbaRsrT0pXOH4+dDvTdRIREZHgtBoFO+dHzlTluLgGaSK2t0sm9qBrqyTueG8ppf5A8C8sSIeCTdr/+UATgQuBI4wxC8svJ4Q7hAroaNL9HO+XTNYPrpOIhE/Fp8F7TeGuGIFuqzXQnkDDfWIuIiISFi1HQnEmFG5xncTTwCPQAIlxMdx24iBWZ+Tx3KwNwb9wxyzvWh2492GtnWGtNdbaYdbaEeWXj8KdQwV0NGk1Bs7I0DRNaVoqmcK9PaeYFslxJMZFYBfPcCvNgTfbwNr/uU4iIiISvNbjof2RkdMgNwQFNMDRg9pzSL+2/HvaKjJzi4N7UeYsiEmEFsMbPI/UnwroaGIMxLf0vo6U6S4ioVZJE7GM3CLaafTZs306lGZDsx6uk4iIiASvzTg48nNIG+g6iSdEBbQxhjtOGkRRmZ9/frIiuBe1Gg39fwsx8Q2eR+pPBXS0KdkF0ybDuqddJxEJjypGoNWBu9y2aRCTrHVSIiISnSJlGVLFPtAhGKTq3bYZl07syevz0lmwMYheRj0vgBF3N3gOaRgqoKNNXAso3AYbXnGdRCQ8KhmBzswt1vrnCls/g3aHeh1NRUREosmC38EH/V2n8FR8UB+CUWiAa4/sS7vUBO58bymBQDVFenEWFGWGJIM0DBXQ0cYY6H62t+er/ueSpqCsDHw+7wIEApaM3CKNQAPkb4TcVdDxaNdJREREai+hLeSt84pG10JcQDdLiOUPJwxgUXo2r8/bVPUT1z4Nb7WDojpsfSVhoQI6GnU7G2wANjnZO1wkvPz+fUafdxWUUOq3WgMN4IuHIXdApymuk4iIiNReq1HedSTsBx3iAhrg1BGdGdO9Jf/8ZCXZhVVsmbVjJjTrA4ltQpZD6kcFdDRqMQya94eNr7pOIhJ6ZWX77gFd3sFSI9BAUgcYdic07+s6iYiISO21HOld74yAAjouzrtu4L2g92aM4c6TB7OzoIQHpq068AnWeltYtTkoZBmk/lRARyNjYNAt0O0s10lEQq+sbJ8R6O053h7Q7Zs38RFoG4Atn0BZvuskIiIidZPQGpK7NZkRaIAhndM4f1w3np+9gZXbcvd9cOc8KNoOHY4IaQapHxXQ0arXxdD3V65TiISe31/pCHS71CY+Ar1rAUw/Hja97TqJiIhI3Q34LXQ8znWKsBXQADcd05/UxFjueG8Jdu+u3xtfBxMLnU8OeQapOxXQ0ax4J6S/7zqFSGjtP4W7fAS6yXfh3jrNu+5wlNscIiIi9THgeuj1S9cpwlpAt0yJ56Zj+jN73U4+/HHrzw/0/w1Meg0SWoU8g9SdCuhotuoR+OYUKNjiOolI6OzXRCwjt5i0pDgS42KqeVETsG0atBjqrYMWERGJVtZ6u0q47sQdxgIa4Lxx3RjcqTl/+3A5BSXl50zuDF1PC8v5pe5UQEezbmcDFja94TqJSOjsNwK9PadI65/LCiBzBnTQ9lUiIhLlCjfDu91hwytuc1S81whhE7G9xfgMfz55MFuzi3jsq7Ww7jn46fmwnFvqRwV0NEsb4HXk3via6yQioVPJCHSTX/+c+R0ESqDDMa6TiIiI1E9SZ0hoAzvnu81hjFdEh2kEGmBMj1acNrIzU79ZS+niu1RARwkV0NGu29nem+n8ajZkF4lm+41AZ+YWa/1zhyPhuHnQ7hDXSUREROrHGGg5CnY5LqAh7AU0wB+OH8DQ5J+IK1irHXaihAroaNf9HO96+5duc4iEyn7bWGXlldA6Jd5hoAhgfNBqFMQmuU4iIiJSf61GQfZS8Be7zeGggG7XPJFbhy2jzPqYUTQxrOeWulEBHe1S+8ApG6DXRa6TiDQ8v9+7Lh+BLigpo7DUT+tmTXgEunA7zLkasle4TiIiItIwWo6EQKlXRLsUFxe2NdB7WMtIPmdRyQhu+ySD4jJ/eM8vtaYCujFI6eY6gUho7FdAZ+WVANC6WRMegd42DdY8Dv5810lEREQaRrtD4eCXIKWH2xwORqAp2YWJTSa177n8tCOfp2esD+/5pdZUQDcG/hL49ixY+bDrJCINq+KPWPkU7qz88gK6KU/h3jYNElp7n9aLiIg0Bkntocd57vc/dlFAJ7SC4xfQb+JNHD2oPQ9/uZpt2UXhzSC1ElvzUyTixcRD/npYuxpajfHuS+oIzXpAwA9Zcw58TXIXSOnqFd875x34eEp3SO4EZYWwa+GBjzfr5f2yK82D3T/u99qu3vFF6qvij1j5CPTOfG9tVJOdwm2tV0C3P9JbBy0iItJYZC+DnBXQ9XR3GWJjwzuF21rwF3k9TYzh9imDOPJfX3P3R8t56Dx9UB6pVEA3Fj3Oh/k3wLSDvdsDboRR94G/4Of79jbkDhh2JxTvqPzxkffBwBuhYGPlj497HPpc6f2i2//x+Fbeuuy4ZvX+tqSJq5jCXT4CvSOviY9AZy+Dwq3a/1lERBqf1Y/D2ifhrFPAF1Pz80MhLi68I9DZy+DTcTD5Teh0HF1bJXP1ob156IvVXDC+G+N7tQ5fFgmaCujGou+vocVwrwEDeKPPADFJcNgnBz4/tbd3ndCq8seb9/euk7tU/njaoPLj9N338YJNsPUTKM1WAS31t98IdJNfA1242dsvs6MKaBERaWRajYJVBZC7GtIGuMlQMYXbWm97rVDb9Ab4C6HliD13/erQ3rw5L5073lvKB9dOIjZGM84ijQroxiImHjocceD9vljodGw1r0us/vHYlOofj0878PE+l1efVSRYBzQRKyYpLobk+Cb6q6vjMXDqpvD8URcREQmnit4eu+a7LaDBe/8RG4b3Ghtfh3aTIanDnruS4mP404kD+dWL83lpzkZ+eVCP0OeQWtFHGhIa2Ssga67rFBLt9msitjO/pOmOPttA+D4RFxERCbe0geBLgF0L3GWoKJrDMY07e7m3bVfXMw946LghHZjUpw33fbqSrDzHe2PLAVRAS8OzFr45GeZe6zqJRLv9RqB35Jc03fXPGd/CO11gp8M3FiIiIqHii4MWQ2HnfHcZwllAb3zDu+56xgEPGWO48+RBFJT4ue+zlaHPIrWiAloanjHQ/zrImg2ZM12nkWi2/zZWecVNtwP3ts+gaLvXAV9ERKQxOvhFr6GWK3Fx3nU4OnF3PR3GPubtelOJPu1SufjgHrzywyYWp+8OfR4JmgpoCY1eF0N8S1h+n+skEs0qm8LdVEegt06D1uO9vgMiIiKNUfN+EN/C3fnDOQLdYjD0/VW1T7nuqL60Tkng9neXEgjY0GeSoKiAltCITYG+10D6O5C7xnUaiVZ+v1c8G4O1lqy8Elo1xTXQxTth51xtXyUiIo1bSTYsvhMyZ7k5f7gK6M0fwpZKdrnZT2piHH84fgALN+3mzfnpoc0kQVMBLaHT7/8gLk3NxKTuysr2/DHLLS6jxB+gTUoTnMK9/UvAavsqERFp3HzxsPSvsOUjN+cPVwG9+E+w5K6gnnrayM6M6taCf3yygpyiMEwtlxqpgJbQSeoAp22BHue6TiLRqmIEGtjZlPeAbtYb+v0GWo9znURERCR0YpOg+QB3nbjDsQY6dw3sWgjdzgrq6T6f4a5ThpCVX8K/p60OXS4JWsgKaGPM08aYDGPMkr3uG2GMmW2MWWiMmWuM0bvBxi42yevKXbjVdRKJRnuNQGfle9s4tGqKa6BbjYQxD3odSkVERBqzlqPcFdDhGIGupvt2VYZ0TuO8cd14dtZ6Vm7LDVEwCVYoR6CfAY7b775/An+21o4Abi+/LY3d/Bvh41Hg1z52Ukt+/89bWJWPQLdpal24izJh5zxvH2gREZHGrtVIKNwChdvDf25jvJlvoSygN73hNQVN6Varl/3umP40S4jlzveWYq0airkUsgLaWvsNsHP/u4Hm5V+nAVtCdX6JIJ1PgKJtsP4l10kk2pSV7dOBG5rgFO5Nb8AnYyB3reskIiIioddypNeMNm+dm/PHxoaugC7J9mZldjuz1i9tmRLPTcf0Y9a6LD76cVsIwkmwwr0G+nrgXmPMJuA+4A9hPr+40P5IaDEMVtzvTecWCdZeBXRWXhOdwr11GqR0h9Q+rpOIiIiEXtvJcGY2tD3IzfljY0O3Bjo+DU7d5DXarYPzx3dnUMfm/PXDZRSUhGGrLalUuAvoXwG/tdZ2BX4LPFXVE40xV5avk55bFo692CR0jIEBN0L2Utj6qes0Ek32m8KdmhBLQmyM41BhFCjzOnB3ONr7/0hERKSx88V4F1fi4kI3Am0tGB/EJNbp5TE+w59PGczW7CIe+0oz01wJdwF9EfBW+devA1U2EbPWTrXWjrHWjomtWNAv0av7uZDUCdY+4TqJRJO9mojtzC9petO3s36A0mzt/ywiIk3Lmqnwzeluzh2qKdx56+GdLrDt83odZmyPVpw6ohNTv1nHhqz8hskmtRLuAnoLcGj510cA6sXeVMTEw2EfwkHPu04i0WSvbayy8oub3vTtbdMAAx2OdJ1EREQkfIoyIf1tb81wuIWqgN70ptccrVmveh/qDycMJDbG8JcPljdAMKmtUG5j9TIwC+hvjEk3xlwGXAHcb4xZBNwNXBmq80sEajkCYpO1DlqCY+0+U7iz8kpo3dQ6cA+8CY7+FhJau04iIiISPq1Gede7Fob/3KFaA73xDW+LrgYooNs3T+TaI/ry+fLtTF+Z0QDhpDZC2YX7PGttR2ttnLW2i7X2KWvtDGvtaGvtcGvteGvtvFCdXyJUxgz4aAgUbHadRCKd3+9d79kHuoQ2TW0Kd2wytJ3oOoWIiEh4tRzpXbvYDzoUa6DzN0HW7Dp1367KpZN60LNNCne9v4ySMm11GU7hnsLdKC1O3+06QvRI7gw5K2DVw66TSKSr+OMVE0MgYNmZX9K0pnBnzIDFt7uZviYiIuJSUgdI6uimgA7FFO5Nb3rX3c5qsEMmxMZw+0mDWLcjn6e/+6nBjis1UwFdT9+uzuTkR77jkS+1nDsozXpC1zNg9eNQmus6jUSyvUagswtL8QcsrVOa0BTuja/B8vvq3KlTREQkqnU+CRLbhf+8sbE/LyNrKK3Hw5DbGnxLysP7t+Ooge14+IvVbM8patBjS9VUQNfTwb3bcPrIztz32Soe/WqN6zjRYcCNULob1j7tOolEsr1GoLPySwCaVhfubZ9Bu0Mhpgl9aCAiIlJh3OMw8t7wn7di95+GHIVuexAMu6vhjreX26YMojRguefjFSE5vhxIBXQ9xfgM9541nNNHdubeT1eqiA5Gm/Heus6V//b2uRWpzF4j0Fl5xQBNZwQ6fxPkrNT2VSIiIjbM63vj4rzrhiqgM2fCztBNRe/eOoUrJ/fi7QWbmbt+Z8jOEwmMMccZY1YaY9YYY25xlUMFdAOoKKJPUxEdvGF/g5H3AcZ1EolUTXkEets077qjCmgREWmiinbAO11hzRPhPW/FCHRDdeJeeDPM+mXDHKsK1xzem45pidz+7lL8gca5240xJgZ4FDgeGAScZ4wZ5CKLCugGEuMz3KciOnjtD4VuZ4AvxnUSCRdra9d9vaKAjo1tegV08Q5I7QtpQ1wnERERcSOhNZTlw6754T1vQ07hLtgCmd81aPOwyiTHx/LHEwaybGsOL8/ZGNJzOTQOWGOtXWetLQFeAU5xEUQFdAOqKKJPHdFJRXQwSnPhxz/Djtmuk0g4rPsfvNMFfrgG/EE0uqhkCnfL5CZSQA/6PUxZCUYzNEREpIkyBlqOCOn050o15BTuTW8BNuQFNMCUYR2Z0KsV9322kl3lAw+NTGdg016308vvCzsV0A0sxme4/+wRe4rox6ariK6SiYGVD8Gyf7hOIqHk94pfelwAbSfD6v/Ap+Mhu4ZmF3tP4c4roUVyHHExTeBXli2feqXiWUREmrqWo2D3Ygg00HTqYDTkCPSmNyBtMKQNrP+xamCM4c6TB5NbVMb901aG/HwhEmuMmbvX5UrXgSrTBN6Nhl9FEX3KiE788xMV0VWKTYa+v4L0dyFH24A1OjbgbcP00VAo2e11kz76Gzj0QyjcDJ+OgY1vVP36vaZw78wvoXVT2QN6+b3w0QgoK3SdRERExK2WIyFQDDlh7DDdUGugS3Nh53zoemb9MwVpQIfmXDihOy99v5FlW3LCdt4GVGatHbPXZepej20Guu51u0v5fWGnAjpEYnyG+88avqeIfuTL1VjbOBf110u//2/vzuOjqq8+jn9OMkmABAgJi+zIDrLLpgiCWlmsa2u1Wuu+1l3xaR/bah+1te4LrlVrqVtd6i6ubKKiIogCIoogKnvCGkKSmfyeP+5EAwTIMjP3Tub7fr3ymmSWe09yMsu5v989vwshLcPryC31x/Z1MP3nMG8i5Pbb8ba2E2D8fG9NxIatd7+NSMQbhU1LY/3WktTpwL3qTXARCDX0OxIRERF/tTgAuv0O0hP4nhirEeiMxnDcKuh5aZ1DqonLDutOg4x0/vX+8oTuNwE+BrqZ2b5mlgmcCLzkRyAqoOMolJ7GrdHGYre8uYQ/vbiAcCTBrfiDruE+0Ok33vmxJQV+RyOxsGYGTBkAa6bCkHvhoGcgM3fH+zRqC4e87S1nBrD4Dtjw2Y73iUR+fBMrKCpNjQZi4WJYN0vLV4mIiADkdIYhk6Bx18TtMy3N+4rFFO5Q9q6fgeKsaaMMjujbmlc+W8m20vqzXKxzLgxcCLwBfAE87Zxb6EcsKqDjrKKIPu/gLjw2ewXn/vuTevXPHBM9L4d9DoOyTX5HInXlHCy4DkI5MHa2N0V/d+fyVlxfusmbtvzGUPjqgZ/OAQ6HId3r0l6YKgX0une9qWqtD/c7EhERkWAoD8PWbxK7z1CoblO4t6+FKft7gwo+OH5we4pKI0z5fLUv+48X59xrzrnuzrkuzrkb/IpDBXQCpKUZvx/fk+uO6cO0L9dy4oOzWbelxO+wgiN3Pzj4Je8ooySn4lVQvMYrikc8AeM+8TpnVkdmUxg/D1oeDB+fB7OO99Z+DIchFCIcKWfDtlLyUmEK9+q3IC0TWo7yOxIREZFg+ORSmDLQ662SKBkZdRuB/u55b/mtzGaxi6kGhnRqRqf8RjzzyXd7v7PUmAroBDpleEcePGUwX63ZyrH3vsfXa7f6HVKwbFkK6973OwqpqZVvwGv94aNoo8QGLSEjp2bbaNASxkyBAX+HH16CN4dBeDukp7NhWxnOQfNUGIFufiDs979egz0RERHxDsiXbYatyxK3z1CobgX0imegcTfI7Ru7mGrAzPjl/u2Y/U0hKwq2+RJDfaYCOsEO692Kp84ZzvayCL+4730+Xl7od0jB8d4J8NHZP03hlWArL4NPfw/Tx3nnsg+4sW7bszRv/eOxH0O/GyBiXgG92esimRJNxNofC32v8TsKERGR4Mgb6F1umJu4fdalgN6+DtZO99Z+9nFJyuMGtcMMnp37vW8x1FcqoH3Qv30u/z1/BPnZmZz80Ie88tlKv0MKhh6XwqZFsOp1vyORvdn2A7x9sLeGd9dz4fAPY7fGYbP+0OlE742r+B3azx7GwEaLyavvy1htWQpFK/yOQkREJFia9gELeUtCJUpdzoH+/gVvNY0Ox8c0pJpqk9uQg7o257lPvqe8XINTsaQC2icd8hvx3PkH0q9tUy58Yh4PzlyqZa46ngAN23prB0uwpTeE8FYY8RQMvT8+Sy5FIpDVGldeyrNdrqL7mpu8Ue/6asF1iT/HS0REJOjSsyC3D2yYl7h91mUEOrsjdD4DcvvHNqZaOH5we37YWMwH32ilm1hSAe2jZtmZPHbWMI7o25q/vraYS//zKUUlKdyhOy0DelzsLX+04VO/o5GdRUq8gxuRUsjKg/Gfegc94iUchiZDeX6fV3lhw2jyl98Ebx4Am76I3z794pzXQGyfQ72p7CIiIvKTftdB7/9J3P7q0kSs9eEw/GFfp29XOLx3K5o0CPHMHDUTiyV9UvNZg4x07v71QK74WXdenr+SoybNYsmaLX6H5Z+u50BWPhR+4nckUtnmr7zidd5EWDXFuy7ehV4kAunprC5uwMQfLqd8xDNQtNyb5l/fbP4Cildq/WcREZGqtP05tBqTuP3VdgR60yLvNLeAaJCRzlED2jBlwWo2FdfjWXwJpgI6ANLSjIsO7cZjZw5jU3GYoybN4tlPUvSE/8xcOPo76HKm35FIheVPwOuDoOhbGPUStDs6MfuNLmO1fmspedmZpHX8JRy5FDr8wrv9h9egdENiYom3VW95lyqgRUREdhUp9d4rN3+VmP2FQlBe7n3VxNwrvB4xATot8/j921MSLlfPpRhSAR0gB3ZtzmuXHMSA9rlc+cx8rnp2PsWlEb/DSryK82mLV/kbh8Dn18H7J3tLSIz/FNodmZj9lpd7bz7p6RQWlfzUgTuzqXdZUgjv/co7Z3j97MTEFE+r34KcrpDTye9IREREgqe8BKaNhW+fTMz+QiHvsiaj0KUbYPXb0P4XgZi+XaFfu6Z0b5XDM3NSdHAuDlRAB0zLxg147MxhXHRIV56e8z3H3vseS9el4HrRn10Lr/SCshSezh4E7Y+FPn+CQ6dBdvvE7bfiDSsUoiA6Ar2DrDw45B3A4K2R3rnZydx8a9g/4MDH/I5CREQkmDIae+sqJ6qRWEaGd1mTTtzfvwguDB1+GZ+YasnMOGloB1o2zmJ7WQoOzMWBCugACqWnccXhPXj09CGs2bydo+6excvzU2zaRZsJULYJlj7sdySpxTnvb/7xBd7PuX2g3/9BWiixcUSiL/Dp6RQUlZKfU8USVs2Hwfh50O4Y79zsGUdBeZK+MTRs7f0+IiIiUrW8QYkroGszAr3iWa8Dd97g+MRUB6eN2JcHfzuYBhnpfodSL6iADrDRPVry6sUj6dm6CRc9OY+rn/88dY4cNR8KLQ6CL++A8hTuTJ5IZZu96dofngWbl0Bku3+x7DACXULznKyq75eZCwc9DUPuhfwhkJaEbwzLn4Cv7vc7ChERkWBrNtDrx1KSgCWZalpAh4ui07d/Gajp2xIfKqADrk1uQ546ZzjnjurM4x+u4KhJs/hydYpMa+55hfdC+d1zfkdS/xXOhSmDYMV/oN/1MOYNSG/gXzzREehSS2Pz9vCuU7grM4Nu50Pfa7yf10yHz/+SPKPRX94Jy/7tdxQiIiLB1mygd5mIpU5rOoU7lA1HfQM9L49fTBIYKqCTQEZ6Gn+Y0IvJZwylsKiMIyfNYvIHy3EB6vAXF22P9M53+foffkdSv4WLYfp4b8T50OnQ52r/R3KjR3wLS7z/8SqncO/OD6/A59fCjCOD36W7dAMUzlH3bRERkb1pcSCMmwstRsZ/X7WZwt2ojfcl9Z4K6CQyqnsLXr90JAd0zufPLy7k7MmfsKGo1O+w4ictHUY+B6Ne8DuS+qlss3fOc6ghHPSs12W7ZQLelKoj+oZVUOo1BvuxC3d1DLwZhtwHa96G14fAxs/jEWFsrJ7qNT9rrQJaRERkj0LZkDcQ0mtwUL3W+6pBAV04F94eA1u+jm9MEhgqoJNM85ws/nnaEP54RC9mLFnLuDtn8v7S9X6HFT+5fSEjJ1Dr6dUL6z6AV/vCkru9n1uOhAbN/Y2psugU7oJi77JGI9Bm0O08OHQGRLbBG8Nh44J4RFl3q9+CUGPIH+p3JCIiIsG3ZhosuD7++6lJAf3FrVD4CWS1iG9MEhgqoJNQWppx1sjOPH/BCLIzQ5z80Ifc/MZiyiJJvIzPnhTMgdf6eo2tpG5cOSz6O7w90uus3fxAvyOqWsUI9PZoAb2nc6B3p8UB3lSvXldC096xjC52Sgpgn8MgLcPvSERERIJv7Uz47M9QFuclXtPTvQPyeyugi1Z4/WO6ng2ZTeMbkwSGCugk1qdtU16+6CCO378d90xbyq8e+IDl64v8Div2GrX3psUsvt3vSJLb9rUwfQJ8+nto/wuvuMwP3lILwE8j0BUF9O66cO9Nw32g31/A0ryGdO8eD9vXxSrKuhv5DBz0jN9RiIiIJIdmgwAHGz+L/75Cob03EfvyLu+yxyXxj0cCI8GLu0qsZWeFuOmX/RnZrQVXP/85E+56l6uP6MVJQztg9aWNfsNWsO8psOxR6HddsKYaJ5ONC2DtuzDkfuh6TrCXWagYgd5WRka60aRBDF6qNsyHH16Ggo9g+D+hUTvvfKpGbb3btywFt1Pn7ozG3hrN4B3EcTvN8sho6v1/QtUzJDJzoUFL73G7nBtl0Lir/w3bREREkkVetBN34VyvqVg8ZWTseQS6dBN8/SB0+BVkd4hvLBIoKqDriSP7t2Fwp2ZMfOYzrn5+AW8vWsPff9GPlk18XIoolnpeDksfgq/ug75/8jua5FIe9qZr73MIHL0cGiTBOTqRCKSlUVBUSl52ZmwOBrU7Cg5/D2YeB1MP9a5rcwSMfsX7/u2RULxqx8d0PBFGPOl9P2UQhHdaQq7L2TDsQe/7V3rsus8el8H+t0F4W9W3dz4dhj9S+99JREQklTRs651rvGFe/PcVCu25gE4LebPcWo2JfywSKCqg65HWTRsy+YyhTP5gOX+bspixd8zkhmP7MqFva79Dq7umvaDNBPhqEvSe6O8axckkvA3eGAY9LvbOz0mG4hm8N6xQiMKi0pp14N6bvP1h/DyveZeLQMNKy00MvgcixTveP7vjT98PewjcTm+kOV1++v7Ax3fdX5Oe3mV6VtW35/avWfwiIiKpzMxbD3rbivjva28FdCgbel4W/zgkcCwZ1hLOzs52RUX18NzeOPp67VYu+8+nfP7DJo4d2JZrj9qPpg2TvFHR+o9g61LocLx31E/2bs4lsOQuOHRqch0hnTcPCgo45suGNG4Q4t9nDvM7IhEREQmCcLG3BGe8ffghlJTAqFG73rbydW/W2r6n6DNpDJnZNudctt9x7I2aiNVTXVvm8N8LDuSSQ7vx0vyVjL9jJu9/neTLXTUfCp1+rReq6loz3Sueu1+UXMUzeFO4QyEKikpq14FbRERE6qdEFM+w+3OgnYP5V8MXf/ealErKUdbrsYz0NC77WXeeO/9AGmSkc9JDH3LNiwsoKqnGmnZBFS6GhX+F1e/4HUmwlW2B2adDTlcY8De/o6m5iincW0tr34FbRERE6p+yzTDrRPjuv/Hdz+6mcK+dARvmev15VECnJGU9BQxon8urF4/ktAM7MXn2txx++0xmLgnQUj41kRbyGoktvMHvSIJtzVQo/gEOeNQ7RyfZRCIUuzSKSiPkaQRaREREKoRyYOVrsHpqnPezm2WsvrjVa2TW6ZT47l8CSwV0imiYmc61R+3HM+ceQFZGGr995COufGY+G7eV+h1azaRlQPeLYc00bwkDqVq7o+Gob6DFCL8jqZ1wmIKI9/LUPEcFtIiIiERZGjTr740Cx1NGBpSXe18VNi2Gla9AtwsSN5VcAkcFdIoZ3CmP1y4eyQWju/D8vB847LaZvL5g1d4fGCRdz4FQY1h8m9+RBE/pRu/gAnjrHCerSITC6KypmHbhFhERkeTXbBBsmA/lkfjtIxTtuVN5GnfZRsgfDt0viN9+JfBUQKegBhnpXDWuJy/+bgQtG2dx3mNzOf+xT1i7ZbvfoVVPZlPochZ8+xQUfed3NMEy9zKYenjy/13CYQrKvLWf8zQCLSIiIpXlDYTINtjyVfz2UVUB3Xw4jP0AGrSM334l8FRAp7A+bZvy4oUjmDi2B+8sXsvPbpvJM3O+IxmWNqPnJdB6LIS1vNmPfngFvnkUev8PZLf3O5q6CYdZX+b9HzbXCLSIiIhUlre/tx502ab47WPnAnrde95MP0l5KqBTXEZ6Gr8b05XXLh5J15Y5THz2M379j9l8vXar36HtWXZHGP0qNO3pdyTBUFIAH54NuX2hz5/8jqZunPOmcEdPz8/XCLSIiIhUltsXxs+F5sPit4/KBXS4GGYe433WkpSnAloAb93oZ849gBuO7cOilZsZf+dMbn3zS7aXxfHcklgo+hbWzPA7Cv/NuQhK1sMBkyE9yUdso806CkodWaE0GmWm+xyQiIiIBFI8Z01mZHiXZWWwbLL3Oav7hfHbnyQNFdDyo7Q04+RhHXnnitEc0bc1d0/9mrF3BHzJq9mnwwe/hfIkXtu6rpyD5gdC/xug2QC/o6m76FSp9dsjNM/Jwsx8DkhEREQCZ9HN8FKX+BXRFSPQZSXw5e3etPGWo+KzL0kqKqBlFy0aZ3HHiQN5/KxhpJnx20c+4sIn5rJ2cwCbjPW4FLatgBXP+h2Jf8ygx4XQ+yq/I4mNaAFdWFKu6dsiIiJStYzGULTM+xwYDxUF9MqnYPOX0Pv33mcuSXkqoGW3RnRtzpRLRnLZYd15c9EaDr11BpM/WE6kPEBNxtr+HBp3h8W3xncaTxA5552Ls/wJvyOJrYh32kBBcYS8bBXQIiIiUoVmA73LwjitB11RQG/6BFqMgPa/iM9+JOmogJY9apCRziWHdeONS0fRv30uf35xIcfc8x5zV2zwOzSPpUHPy6FwDqx71+9oEuvbp2DpQ7AtyZes2ll0BLqgOKw1oEVERKRquX29z4Eb5sVn+xUFdPu/wJg3NPosP1IBLdWyb/Ns/n3mUO769UDWbtnOcfe+z1XPzqdga4nfocG+v4WGbWDDp35HkjjFq2DO7yB/OPS80u9oYisSwTkoKC6juaZwi4iISFVCjaBJLyiMUwFdtALS1noH9kPZ8dmHJKWQ3wFI8jAzjurfhkN6tuTud77i4VnLeH3Baq44vAcnD+tAKN2n4zGhhnDUUkhv4M/+E805+PAciBTDAY9CWj3rUh0OUxSBkrDTFG4RERHZvc5nxG/bcy+HzW9C6Rvx24ckJY1AS43lZIX4w4RevH7pKPq1y+WalxZy5KT3mLO80L+gKornbSv9iyFR1s6Ela9A/79Ckx5+RxN7kQgFZd63+Tmawi0iIiK70ety7yvW1syA756DnF9CeUbsty9JTQW01FrXljn8+8yh3HvyIDZtK+WX93/A5U9/ytotPnXr/uJWeLkLbA/wslux0OpgOHQq9LjE70jiIxymILoqmbpwi4iIyB6VbYHSjbHbXnkE5l4GjdpD05N+7M0iUkEFtNSJmTGhb2vevuJgLhjdhZfnr+SQW2bw4MyllIbLExtMmwkQ2Q5f3ZvY/SaKc7Dla+/7VmO8xhn1UThMQan3bb6mcIuIiMjulG2BZ3Nj+9lv2WSvMdmAv0NmDpSVxW7bUi/U00/gkmiNMkNcNa4nb152MMP2zeOvry1m7B0zeeeLNbhELS/VtBe0OQKWTIJwcWL2mUhL/wGv9o7fcg1BoSncIiIiUh0ZjSG7U2wbiRX/AC1HQccTISNDI9CyCxXQElP7Ns/m4dOG8OjpQzCDM/81h1P/+TFfr92SmAB6XQkl62H5vxOzv0TZuhzmXgEtRkGzAX5HE1/hMAXlXmM0jUCLiIjIHjUbGNulrPr8EQ6Z6i1bFQqpgE4SZnazmS02s8/M7Hkzy43XvlRAS1yM7tGSNy4dxR+P6MW8FRsYd8e7/N/Li9hUHOdpMC0PhmaD4OuH4rufRHLlMPt0wGD4I/V36naFcJiCsJGdmU6DjHrWYVxERERiK28QbF0KpZvqtp2ib73mYfDTCiehkKZwJ4+3gD7OuX7AEuAP8dpRPf8kLn7KSE/jrJGdmXblaI4f3J5/vr+MMbdM5/EPvyVSHqdp3WZw4GNwyFvx2b4fltwDa6fD/rdDdge/o4m/SISCMtP0bREREdm7ZgO9yw2f1m078ybC9AlQUvDTdRkZEIl4fWgk0JxzbzrnKqYLzAbaxWtfKqAl7prnZPG34/ry8oUH0bVFDlc/v4Aj7nqX975eH58dNu0FmU1h2/dQMCc++0ik0kJoe2R81zoMkkiEwjJ14BYREZFqyB8KgydB4y6138bad2HFM9D7KsjK/+n6UMi71DTuZHMGMCVeG1cBLQnTp21T/nPucO45aRBbS8Kc/NCHnPWvj/lm3db47HDeRHjrQFh8R3IfOex7DYx6wRtdTwXhMOvLnM5/FhERkb3Lyofuv4NGtRxwdOXRZavaQa+JO96mAjrRQmY2p9LXOZVvNLO3zWxBFV9HV7rP1UAYeDxuQcZrwyJVMTOO6NeaQ3u15JH3lnHvtKUcfvtMfntAJy45tBtNG8VwsfrB90B4m/eiuGaad/5w5aOKQbf0YcjeF/Y5pP6f91xZdBmrftmawi0iIiLVsO172LgA2oyr+WOX/RsKP4EDHoNQox1vUwGdaGHn3ODd3eicO2xPDzaz04CfA4e6OC4DlEKfyiVIGmSkc8HortHzo9vx6PvLOPiWaTz63jLKIjFaPzorzxu53f9OWDUFpgzwXlyTwaZF8PHvYMndfkeScC4cprCkXFO4RUREpHq+uh9m/Lx2y5i6cmg9Djr9etfbMqIDO2okFnhmNg64CjjKObctnvtSAS2+atE4i78d149XLx7Jfm2acO3Lixh3x0ymLo7R+tFm0ONi+Nn70KR3cjThKg/DB6dBRg4Mud/vaBJu8/YwYQd5msItIiIi1ZE3CFwENtVioKTL6TD6tapn+2kEOplMAhoDb5nZp2YWtw/RKqAlEHq1bsJjZw7jod8Oxjk449E5/ObhD1m4so5LElTIHwyHvAEZTSCyHeZcBMVrYrPtWFv0dyj8GIbcBw1b+R1Nwq0v9t6kmqsLt4iIiFRHRSfuwrnVf0zRt7D0n94I9O76zKiAThrOua7OufbOuQHRr/PitS8V0BIYZsZhvVvx+qWjuPbI3ixauZmf3z2LK56ez6pNtZiSszsFc2DpQzClP6x+O3bbjYXNS2DBX6DDCdDheL+j8UXhdm8Kv6Zwi4iISLVkd4KMXNgwr/qPmX81zLkAilfu/j4qoKUKcSugzewRM1trZgt2uv4iM1tsZgvN7KZ47V+SV2YojdNG7Mv0iWM4Z1RnXv5sJWNumc4tb3zJ1pIYvIC1PAjGfgyZeTD1cJj/R2/adBA07gr73w1D7vE7En+Ul1NQ6hXQmsItIiIi1WIGeQOrX0BvXQbfPgndL9xz924V0FKFeI5APwrs0ArPzMYARwP9nXP7AbfEcf+S5Jo2zOAP43vxzuUHM3a/fZg07WtG3zyNxz/8lnBdG43l9oFxH0Pn02HhDTDnwtgEXRfhYu/8m27nJle38FiKRFhf6n2rKdwiIiJSbfvfCSOeqt59v7wTSIMel+z5fhUFtJqISSVxK6CdczOBwp2uPh+40TlXEr3P2njtX+qP9nmNuPPEgbz4uxF0bp7D1c8vYNyd7/LWojo2Ggtlw/CHvWULel7mXedi1AG8pgrmwIsdYe0sf/YfFJEIhdGDvM0aaQRaREREqim3L+Tsu/f7lW70lgrteOLe144284pojUBLJYk+B7o7MNLMPjSzGWY2JMH7lyTWv30u/zl3OA+esj/l5Y6zJ8/hhAdmM2/FhrpteN+ToUkPcA7ePxnmXgGR0tgEXR2R7TD7VEjLgNz9ErffIAqHKSgzmmSlkxlSiwYRERGppsh2+PIuWPfenu+37Tuv0O51RfW2qwJadpLoT6ghIA8YDkwEnjaruu2dmZ1jZnPMbE5Y/7QSZWYcvt8+vHHZKK4/pg/frC/i2Hvf5/zHPuGbdVvrtnEXgawWsPg2eOsg2PpNbILem8+v9dZ9HvYwZDZLzD6DKhxmfSk0bxTyOxIRERFJJpYBn/4BVjyz5/vl9oXx86HZgOptNxTSFG7ZQaIL6O+B/zrPR0A50LyqOzrnHnTODXbODQ6F9GFadpSRnsZvhndkxsTRXHpYN2YsWcfht8/kTy8sYN2WktptNC0Eg++Ckc/Blq9gysC9vwjX1frZ8MXN0OUsaDNu7/ev76JTuPM1fVtERERqIi0dcvvtuZHYpkVQtnn3y1ZVJSNDI9Cyg0QX0C8AYwDMrDuQCaxPcAxSj2Rnhbj0sO7MmDiGXw/twBMfrWD0zdO44+0lFNW2Y3f742D8PGjSGz46zztXJl5+eAUatoNBt8ZvH8kkHKagDPKyM/yORERERJJN3iDY8GnVPW2cg/dOgqlja7ZNTeGWncRzGasngQ+AHmb2vZmdCTwCdI4ubfUUcKqrUxcoEU+Lxllcd0wf3rpsFKO6t+COt7/i4JunM/mD5ZSGa9EYLKcT/GwmHDYDMnO9F+Kty2McNdD/ehg/FzKaxH7bySgSoaAM8tWBW0RERGqq2UBvhLmq0/DWTIWN86HrWTXbpgpo2Uk8u3D/2jnX2jmX4Zxr55x72DlX6pz7jXOuj3NukHNuarz2L6mpc4sc7vvN/vz3ggPp0iKbP7+4kMNum8GLn/5AeXkNj9WkZXjLXYG33MGr+8E3/4pNoOs/go3RJdJTdcmqKkRKy9hQpiWsREREpBbyBgIGm5fsetsXt0CDVtDp5JptU+dAy07U5lbqpUEdmvHUOcN59PQhZGeFuOSpTzni7llM+3Jt7Za+6nAC5A+B2afBB6dCWR0alpVthfdOhFm/8m/ZrIDaWFRCOUZe4wZ+hyIiIiLJJrc/HL8Z2k7Y8fqNC2HV69D9Qkiv4WcMnQMtO1EBLfWWmTG6R0tevegg7jxxAEUlYU7/58ec8OBsPvm2hktfNWoDh7wDfa6BZf+GNwbDhs9qF9inV0HRchj6AJiegpUVFHnLh+WrgBYREZGaSgtBRs6u1698FdIbQbfza77NiincOutUovTpXeq9tDTj6AFtefvyg7nu6P34Zl0Rv7jvfc6ePIcvV2+pwYbSod+1cOg7EN4GZZtqHszqt+Gr+6DHpdByZM0fX8+t31pRQGsKt4iIiNTCiudg1gk7Fry9r4Ijl9TutLmK1YAikdjEJ0lPBbSkjMxQGqcc0IkZE0dz5eHdmb20gHF3zuTy/3zKioJt1d9QqzFw5Fc/FcDLn6xep+6yzTD7TGjSA/rfUKvfob4rLPbOMcrPVgEtIiIitVC8ElY8DcWrvJ8j273LRm1rt72KAlrTuCVKBbSknOysEBce0o2ZV43hnJGdefXzVRx623T+9MIC1m7eXr2NpEcLvKIVMPtUb83o9R/t+TFpWdDpJBj+Lwg1rNsvUU8VFEUL6BytAy0iIiK10Gygd7lhLoSL4MV94ctJtd+eCmjZiQpoSVnNsjP5w4RezLxqDL8a3J4nP1rBqJunceOUxWzcVlq9jWR3gMNmAg7eGgFf3Lr7tQfTs2DA36D5sJj+HvVJQXEYA5o1UgEtIiIitdCsP2BQOM9bPWX7amg2oPbby8jwLtWJW6JUQEvKa9WkATcc25d3rjiY8X1a88DMpYy8aRqTpn5FwdaSvW+g+XAYPw/aHgnzrox216503k3pBnjrIFj3fvx+iXqiYHuEZplGepr5HYqIiIgko4zG0LgbFM6BxbdD/jBoMaL229MItOwk5HcAIkHRMT+b208YwLkHd+bWN5dwS/SrddMG9G7dhN5tmrBfmyb0bt2U9nkNMatU5GU2g5HPwZJ7ID0TKt8252Io+KjmyyakoILiCPlZKp5FRESkDlqNhmWPQWQbDPjrjp/LakoFtOxEBXRdlZfrCVXP9MxrwD9O7MeClZv5YFkhC1dtYdHqLUxfso5IuTey3DgrRK99cujaIpsmDTJolJke/ZpAdmY6Ded/T8eiV2ix5U3yCp5nXfuJFBZ1Ir24EDMj3bxR1jSDNDPMoOKlvaIwr3itN6xar/v1oexcsz1Cfla632GIiIhIMhv6AGxe7PWqaXds3bZVUUBv3w6l1TzFL6gydYpcLKiArqtNm2DWLL+jkDjoE/2isfe1vTN8uQ0WFcGiojIWFW5gyg8bKIpAqdu1fL2+7Uv8Jn8KC4s7c8xrB1LmPkjwb5CcjuygDtwiIiJSR8P/BdtWeGtD10XFOdALFnhfySozE8aO9TuKesFcEiwKnp2d7YqKivwOo2olJbBypd9RiM/KIo5t4XKKw+UUlZVTXFZOUWmEBkWz2JjejWJrQcRBuXOUO4g4t8PPFU9DBzjcDqdQV+cpGvxncfWNHtCRju2b+x2GiIiIiGf1aigu9juKuklPhw4d/I5ij8xsm3Mu2+849kYFtIiIiIiIiPgqWQpodeEWERERERERqQYV0CIiIiIiIiLVoAJaREREREREpBpUQIuIiIiIiIhUgwpoERERERERkWpQAS0iIiIiIiJSDSqgRURERERERKpBBbSIiIiIiIhINaiAFhEREREREakGFdAiIiIiIiIi1aACWkRERERERKQaVECLiIiIiIiIVIMKaBEREREREZFqUAEtIiIiIiIiUg0qoEVERERERESqQQW0iIiIiIiISDWogBYRERERERGpBhXQIiIiIiIiItVgzjm/Y9grMysHiv2OYy9CQNjvIGQHyknwKCfBpLwEj3ISTMpL8CgnwaS8BE8y5KShcy7wA7xJUUAnAzOb45wb7Hcc8hPlJHiUk2BSXoJHOQkm5SV4lJNgUl6CRzmJncBX+CIiIiIiIiJBoAJaREREREREpBpUQMfOg34HILtQToJHOQkm5SV4lJNgUl6CRzkJJuUleJSTGNE50CIiIiIiIiLVoBFoEYkbMzO/YxARERERiRUV0NVkZs38jkF2ZGb5fscguzKzHmZ2NIDTFJdA0OtX8Oj1K5jMrKuZDfU7DtmRmbUzs6Z+xyE/MbOQ3zHIrvR+nxgqoPfCzBqZ2T3A62Z2kZkNjF6vv51PzCzHzG4FXjKzP5jZcL9jEu/N1MwmAf8F8s0s0++YUp2ZZZvZ7cB/zewsvX75L/r6dTvwqpldb2Zj/I5JdnhfeRZo7Hc84ol+BrsVeAP4l5mdEr1es5t8En2uPACcZWYN/Y5HPKpXEkt/1L27HMgHTgUaAA8AOOfK/QwqVZnZ/sDL0R/PB5oAv/IvIqlkMNDKObefc+4R51yp3wEJf8N73ToPKAXuBb1++cXMugHPAxHgDGAd8L++BiWYWVvgNaCfc26Ac+4dv2OSH/0JaOGc2w+YDJwNmt3kl+jo5m3AOGAQ0MffiKQS1SsJpAK6CmbWIHoZAjKBJ5xzi51zNwProqMHOqqTQJWOcq4GLnTOXeGc+wwvP3P9iyy1VTxXopoBBdHrx5nZ0Wa2X/RnPVcSpNLrVz7QBfiDc+5LvJkBbczs/6K3KyeJVwQ86Jy70jm3CK9oW2Vm7XyOK9UV4+ViKoCZDTezA8xsn+jPeq4kWHRGUwOgIfBC9OpWeKNrraP3UV4SpNKMshJgEtAP2AaM1Oko/lG94h/9QSsxs+5m9jhwt5kNds6FgRzggEp3Ow84xcza6ahO/FXKyV1mNhgocM4tNLNcM7sTb/T5cDO718xa+Rtt6tj5uWJm6XizAbaa2fnANXhHp98xsz7OuXJNuYuvnXIyxDlXEL3p6uhlO+At4Fwza6PXr/iL9gO4qeJn59xKYEqluzQCejrnvk94cCmsirwUAtOBrmb2FXAzcBpesdZOr1+JUTkvzrmwc247sAGYYGYfABOBPOAjM+urvMSfmXUzs0eAW81sGFDqnPvMObcJ78BGf2CAjyGmJNUr/tMyVlHREc7X8D7cFON9+J8FvAIsBro559ZH73sHsMk5d40/0aaGKnLSH1jsnLslejTtYOfctOgRuBuBBs658/yLODVUkZeBwEfAE3jPmQXA75xzG8zsL8BQ59x4v+JNBVXkZH9gBvAq8BzwbfS6s4HjgC+cc//wJ9rUYGZHADcBvYD/dc7daGah6AedivuMAc5wzp3iV5yppqq8RK9vAJwE5DrnbotedwfQ0Tl3rE/hpow95CUDaAncAZzunNsafV8Z7pwb61e8qSB6MPwi4B68GWbdgYedczMq3ef66Lf360BgYqheCQaNQP+kC1DknLvJOXc38BBwLN70ofvYcfHxJcD3oEYWcbZzTh4FDjKz0c65cufcNIDoUep5wA/+hZpSds7Lw8ARwD54H3J6AM2j970HKDWzRn4EmkJ2zsk/8ArlNs65kcBdwEHOuVlAFrAM9PoVZ2uAk/E+dP6PmeU458Jmllbp794bWAhgZieZWXefYk0lO+elMfz4PvJ0RfEc9QLwfXSGjcRXlXkBwnjvJ+vxpgwD3A+EzSw74VGmljXAJc65e/D6aWThzQCo3IH7caAF0MfMLjazfr5EmlpUrwRAShfQlc8JcM4tADqZ2ajoVZ8B7wBX4U2BzDOza8zsV8BZeEd91MgixvaSk/l456idutNjBgDnAEsTFGbKqeZz5XLn3CN4BzN+Y2an4513+7FzbtvO25S6qUZO3gYujd7+kXOuwLzleXrhTYvU61eM7ZSTOXgzZr4GXsf70A/ezK+Kv/tBQAszex6veChLZLypYi95uS96n3Tn3NZKjxkC3AAsdM5FEhxySqhOXqLPlYXAKOAiMzsOeArvfaUo8VHXbzudK/syMN3MMqPPgTV4swGomEnjnPsCCOHl5FS8ZpUSY5WLX9UrwZByBbSZtTGzP8NPnekqvWA8gFeI4ZzbAkzDO+KWH71+Gd4/463OuccSHHq9VcOczMQb0exuZvlm9hjeaNtdzrknEh99/VXDvEwHMsxr7vK/wPvAGGCSc+56JCZqmJMZQEn0vMKGZvZ74F94U/A+SXz09VNVOamkJHp5LvDz6LnpkejjsoD9gNHAk865I5xzyxIUdr1Xh7w0MbO/4z2f7nLO3Y/ETE3zEr1fGLgAr8/GxcC9zrlrExNx/be7nDjnyqJfFUXxfnhThCseZ2Y2Fq8j9wXOuf2dc4uRmIjm5QEza+qcc9G/t+qVgEipAtrMLsU7SpNrZjkV11d6wZgCNDSzihHO7/Aa74Scc0ucc5Odc4c75x5PZNz1WS1z0hHYHG2S9JRzbohz7j8JDLveq8NzxTnn1jrn3nDO/dY591Qi467P6vBc2eScKwZecc710utX7OwuJxWiH3rSnXObgVvxzvHEzMY550qAP0c/dD6dyLjruzrmZTPwrHNukN5XYqsueQHed85d55wbrbzEzt5yEr1PWvTg+HZgVrSQG4ZXQ7znnGurAYzYMrM/4i15eCqVlmpVvRIcob3fpX4w76T7AcBY59yKnW4z5/navMXh7zOzz4GueG3hM3fZoNRZHXKShbfGHc65VxIcdr2n50rw1PG5kgU/TvuSGNlTTnZSDuCcuy46rW4L8IiZveOceyH+kaaWOublYTOb6pz7OAGhppQ65uUfeFOJw5qGGjvVzYnzup03xSugTwCuBJ4B5lY+7UHqzsza4x08qvhbHwY0qnifr7ifPoP5r94X0Dv90w0A1pvZQGACsMA592LF7dH7vmlmt+AtYTECuHgvL/ZSQzHKyfLER16/6bkSPDHKybc+hF5vVScnle8fHVVrjteE53O8dezfS2TMqUB5CSblJXhqmpOo0XiNqsLApc65mYmINQUVAr93zn0D3tJuQLPo8yLN7TjFXp/BfFQvl7Eyb1H364AbnXMroucMNMc7arYRGIu3tMsZwGTgMefc2sr/nNFpRGocEiPKSTApL8GjnARPbXNS6fEhYJgKgdhSXoJJeQmeOryvWLR46w6Mds49WPUepDaqyEvF3zvdORcxs77Ak3iraGys9LgfD4Lo/d4f9W4E2sx6A3fiHS3LAs6MTj8pwOtweghwh3PueTObh9e17lnYpXmC/hljRDkJJuUleJST4KlLTio4rwmSioEYUl6CSXkJnjq+r7jo5RK8JZEkRnaTl4q/d8V7eBnwEV4/k40Vj600g0Dv9z6pj03ENgF/AZrirRk8En78B/svsBXoFr3uXbx105r5E2rKUE6CSXkJHuUkeJSTYFJegkl5CR7lJJiqzMtO1gB9K36wHZcZEx/V1ync2c65IjO7ApjgnDu00m3HAkfjLSzeB4gAZznnNvgTbWpQToJJeQke5SR4lJNgUl6CSXkJHuUkmPaSl4pp3JOBAufcZf5FKjurlwV0ZWb2Cd6agQ9Xuq493otFqc7nSDzlJJiUl+BRToJHOQkm5SWYlJfgUU6CaTd5SQdOBr53zk31LTjZRVIW0GZ2FbDSOffYTifSV26iE3LOhc3sSOAaYChwDDDbObfSr9jrK+UkmJSX4FFOgkc5CSblJZiUl+BRToIpFnmp/DgJjqSaS29mjc1r2T4RuMHMmlb6Z7RK/4zdndeEAufcy3hrBm/BW5BcJ9vHkHISTMpL8CgnwaOcBJPyEkzKS/AoJ8EUy7yoeA6mpCigzVvSAGAbMM051wKYCfwpentF2/d2ZvYk8Dcza2lmDc3scqARcJJz7mjn3Bpffol6RjkJJuUleJST4FFOgkl5CSblJXiUk2BSXlJHoKdwR/8RbwQygFedt2h4xUn1HYHpwM+dcwuj9/8l0Nk5d1OlbfR1zn3uQ/j1knISTMpL8CgnwaOcBJPyEkzKS/AoJ8GkvKSewBbQZmbAPUATYApwGvAC8JBzriR6nxuBHs65Y6t4fKhiWoTEhnISTMpL8CgnwaOcBJPyEkzKS/AoJ8GkvKSmIBfQTYDXgbHOuS1mNhaYAHzsnHssep9MYA5wLrAZaOWcm1oxRcKv2Osr5SSYlJfgUU6CRzkJJuUlmJSX4FFOgkl5SU2BPQfaObcZWI53JAfgPWAecKCZ7RO9TykwOXrbc4BFr9c/YxwoJ8GkvASPchI8ykkwKS/BpLwEj3ISTMpLagpsAR31PDDAzFo757YCnwHbgdYAZjYaOBv4m3Oup3PuHb8CTSHKSTApL8GjnASPchJMykswKS/Bo5wEk/KSYoJeQM8C1hM9quOcm4u3Plqj6O3fASOdc1f7El1qUk6CSXkJHuUkeJSTYFJegkl5CR7lJJiUlxQT2vtd/OOcW2VmLwI3mtnXwMd4R3Qq1kZb6md8qUg5CSblJXiUk+BRToJJeQkm5SV4lJNgUl5ST2CbiFVmZuOB44EDgUnOuUk+h5TylJNgUl6CRzkJHuUkmJSXYFJegkc5CSblJXUkRQENYGYZeOfbq9V7QCgnwaS8BI9yEjzKSTApL8GkvASPchJMyktqSJoCWkRERERERMRPQW8iJiIiIiIiIhIIKqBFREREREREqkEFtIiIiIiIiEg1qIAWERERERERqQYV0CIiIiIiIiLVoAJaREREREREpBpUQIuIiIiIiIhUgwpoERERERERkWr4f9p7EKehBTaSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 9), num='Post process')\n",
    "\n",
    "start='2009-01-16 00:00'\n",
    "end='2009-01-17 00:00'\n",
    "\n",
    "g.df[['Htg Tstat']].truncate(before=start, after=end).plot(ax=ax, c='r', alpha=0.3)\n",
    "g.df[['Clg Tstat']].truncate(before=start, after=end).plot(ax=ax, c='b', alpha=0.3)\n",
    "g.df[['Zone Temp']].truncate(before=start, after=end).plot(ax=ax)\n",
    "ax.set_ylabel('Indoor Temp')\n",
    "axbis = ax.twinx()\n",
    "g.df['OA Temp'].truncate(before=start, after=end).plot(ax=axbis, c='orange', linestyle='--')\n",
    "axbis.set_ylabel('Outdoor Temp')\n",
    "\n",
    "ax.legend(loc='best')\n",
    "axbis.legend(loc='right')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "370.6px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}