example_a_timeseries.ipynb

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    "# NEMPY Constraints Analysis\n",
    "\n",
    "Jupyter Notebook <br>Version: 1.1 <br>Updated: 22/03/22 <br>\n",
    "Author: Declan Heim <br>\n",
    "Contact: [Email](mailto:d.heim@unsw.edu.au)<br>\n",
    "GitHub Ref: [nempy_constraints_v1](https://github.com/dec-heim/nempy_constraints_v1)\n",
    "\n",
    "---\n",
    "\n",
    "## Introduction & Background\n",
    "\n",
    "This notebook serves as an example of how constraints can be analysed using the open-source python simulator of AEMO's dispatch process, 'nempy'. This tool was initially developed by Nick Gorman and is expanded upon in this example, with additional functionality to draw insights into the impact of specific constraint equations in historical dispatch. These changes are not yet available via the official nempy release through pip, rather it draws on a forked version of the github repo. Updates to integrate and streamline these features into the official release of nempy are in progress.\n",
    "\n",
    "The purpose of analysing constraints in this regard is to convey a deeper understanding and discussion around the impact of constraints to those units involved in the constraint. Further, this example demonstrates the outcomes that could be seen in the market by alleviating a specific constraint, both in a market price sense and the volume (MW) dispatched for each unit in the constraint. This type of analysis is possible by re-simulating the same dispatch interval and modifying the inputs that define the historically binding constraint. Such conterfactual work requires the use of a dispatch simulator, unlike higher-level observations which demonstrate the units have been constrained as opposed to what otherwise may have happened.\n",
    "\n",
    "The example provided assumes the reader has some foundational understanding of the NEM dispatch process, how constraints are defined, the types of constraints and so forth. Hence it can be seen as an intermediate example. Explainations of historical dispatch procedures in nempy are omitted given there is abundant information [covered in this example](https://nempy.readthedocs.io/en/latest/examples.html#detailed-recreation-of-historical-dispatch). To gain a thorough understanding of the work presented here, one should first understand simplier examples of NEM dispatch and have some insight as to how nempy can be used, as provided in [Nempy Documentation.](https://nempy.readthedocs.io/) Some helpful resources to assist in understanding constraints in the NEM are linked below.\n",
    "\n",
    "### Acknowledgement:\n",
    "Special thanks to Nick Gorman at UNSW for developing the nempy tool and providing continued support in expanding it's functionality for the constraints analysis here. \n",
    "\n",
    "### Specific Notebook Context:\n",
    "This specific example demonstrates a timeseries constraints analysis and follows a previous example on constraints [available here](https://github.com/dec-heim/Constraints-Analysis/blob/main/example_a.ipynb). I've omitted a fair amount of explaination here as it is covered in the earlier notebook. This example is somewhat more advanced so the reader should be well acquainted with constraints to digest the material here.\n",
    "\n",
    "---\n",
    "\n",
    "### Useful References:\n",
    "<font color=blue>**Relevant nempy material:**</font>\n",
    "- [UNSW-CEEM Nempy Github](https://github.com/UNSW-CEEM/nempy)\n",
    "- [Nempy Documentation](https://nempy.readthedocs.io/)\n",
    "\n",
    "<font color=blue>**Relevant nempy examples:**</font>\n",
    "- [Nempy: Simple Examples 1-5](https://nempy.readthedocs.io/en/latest/examples.html#)\n",
    "- [Nempy: Detailed Recreation of Historical Dispatch](https://nempy.readthedocs.io/en/latest/examples.html#detailed-recreation-of-historical-dispatch)\n",
    "\n",
    "<font color=blue>**Relevant material for understanding constraints:**</font>\n",
    "- [AEMO Constraint Implementation Guidelines (2015)](https://www.aemo.com.au/Electricity/National-Electricity-Market-NEM/Security-and-reliability/-/media/943DDD419E5942B8993CCA8EA201C37E.ashx)\n",
    "- [AEMO Constraint Naming Guidelines (2013)](https://www.aemo.com.au/-/media/Files/Electricity/NEM/Security_and_Reliability/Congestion-Information/2016/Constraint-Naming-Guidelines.pdf)\n",
    "- [Example of Marginal Value Calculations of 'X5' constraint, by Allan O'Neil (WattClarity)](https://wattclarity.com.au/articles/2020/12/casestudy-followup-x5-constraint/)\n",
    "\n",
    "<font color=blue>**Specific material for the constraint that this example draws upon:**</font>\n",
    "- [Example Analysis of Constraint Impact on PV, by Jack Simpson](https://jacksimpson.co/exploring-the-impact-of-constraints-on-a-solar-farm-in-the-national-electricity-market/)\n",
    "- [AEMO Feb 2021 Monthly Constraint Report](https://www.aemo.com.au/-/media/files/electricity/nem/security_and_reliability/congestion-information/statistics/2021/monthly-constraint-report-february-2021.pdf?la=en).\n",
    "---"
   ]
  },
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   "source": [
    "## Example 2 - Investigating the impact of NSW Line 94T in Feb 2021 (Timeseries)\n",
    "### Event Description\n",
    "This example highlights historical events of the constrained line 94T representing Molong to Orange North in NSW during February 2021. Specifically this event  was noted earlier by [J. Simpson.](https://jacksimpson.co/exploring-the-impact-of-constraints-on-a-solar-farm-in-the-national-electricity-market/) and can further be found through AEMO's [monthly reporting process.](https://www.aemo.com.au/-/media/files/electricity/nem/security_and_reliability/congestion-information/statistics/2021/monthly-constraint-report-february-2021.pdf?la=en)\n",
    "\n",
    "\n",
    "Specific details of which units are involved in the constraint is provided in the latter sections of this notebook, demonstrating how such information can be extracted from nempy. In the meantime, we can contextualise this constraint as having a signficant impact on a number of solar farms located in Central-West NSW as flagged by the earlier references. **Noting this second example looks into the timeseries across the day as opposed to a single dispatch interval.**\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section A. Model Building\n",
    "### A1. Import Python Packages\n"
   ]
  },
  {
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      "Printout of package installs omitted here\n"
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   "source": [
    "import pandas as pd\n",
    "!pip install db-sqlite3\n",
    "import sqlite3\n",
    "\n",
    "# The forked nempy market dispatch engine is loaded\n",
    "!pip install --user --upgrade git+https://github.com/dec-heim/nempy_constraints_v1.git --no-warn-script-location\n",
    "from nempy import markets, time_sequential\n",
    "from nempy.historical_inputs import loaders, mms_db, \\\n",
    "    xml_cache, units, demand, interconnectors, constraints\n",
    "\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "!pip install git+https://github.com/jmcnamara/XlsxWriter\n",
    "import xlsxwriter\n",
    "\n",
    "# Plotting packages\n",
    "!pip install plotly kaleido\n",
    "import plotly.graph_objects as go\n",
    "import plotly.express as px\n",
    "from plotly.subplots import make_subplots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### A2. Retrieve + Prepare Historical Data from AEMO\n",
    "\n",
    "The data for this example has already been extracted and prepared for nempy locally. The data was found for the **15th February 2021** as described in the previous examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "wQ_QQTrUutwI"
   },
   "outputs": [],
   "source": [
    "con = sqlite3.connect('feb_2021_mms.db')\n",
    "mms_db_manager = mms_db.DBManager(connection=con)\n",
    "xml_cache_manager = xml_cache.XMLCacheManager('feb_2021_cache')\n",
    "\n",
    "raw_inputs_loader = loaders.RawInputsLoader(\n",
    "    nemde_xml_cache_manager=xml_cache_manager,\n",
    "    market_management_system_database=mms_db_manager)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### A3. Define Dispatch Intervals\n",
    "Building on the previous constraints example, we are now interested to see the impact of a specific constraint across multiple dispatch intervals (a timeseries analysis).\n",
    "\n",
    "Here we define functions to generate a list of 5-minute dispatch intervals to later input to nempy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def perdelta(start_date, end_date, min_interval):\n",
    "    \"\"\"\n",
    "    Function accessed by create_dispatch_list. Generates List of Datetimes between 2 dates.\n",
    "    perdelta SourceCode retrieved and modified from: \n",
    "    https://stackoverflow.com/questions/10688006/generate-a-list-of-datetimes-between-an-interval\n",
    "    \"\"\"\n",
    "    start = datetime.strptime(start_date,'%Y/%m/%d %H:%M:%S')    \n",
    "    end = datetime.strptime(end_date,'%Y/%m/%d %H:%M:%S')  \n",
    "    delta = timedelta(minutes=min_interval)\n",
    "    \n",
    "    curr = start\n",
    "    while curr <= end:\n",
    "        yield curr\n",
    "        curr += delta\n",
    "\n",
    "def create_dispatch_list(start_date, end_date, min_interval=5):\n",
    "    \"\"\"\n",
    "    Generates a list of dispatch intervals between two dates.\n",
    "    Inputs: start_date, end_date >> passed as string\n",
    "    \"\"\"\n",
    "    result = []\n",
    "    for n in perdelta(start_date, end_date, min_interval):\n",
    "        result = result + [datetime.strftime(n,'%Y/%m/%d %H:%M:%S')]\n",
    "    return result"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
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       "                 di_list\n",
       "0    2021/02/15 06:00:00\n",
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       "..                   ...\n",
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       "\n",
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   "source": [
    "dispatch_intervals = create_dispatch_list('2021/02/15 06:00:00','2021/02/15 18:05:00')\n",
    "di_df = pd.DataFrame(dispatch_intervals, columns=['di_list'])\n",
    "di_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### A4. Define Market Data & Economic Dispatch Process\n",
    "A more detailed explaination of what is happening here can be found in the earlier constraints example. Defining a function allows us to iterate this procedure later. Noting a slight addition before the <code>market.dispatch()</code> is called we ensure that if a constraint name is provided, then it is removed in the economic dispatch procedure via the function <code>market.remove_generic_constraint_set()</code>.\n",
    "\n",
    "We also have created some lists to convieniently store output data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "outputs, outputs_mvs, outputs_prices, outputs_units = [],[],[],[]\n",
    "\n",
    "def economic_dispatch(interval, remove_constraint_name=None):\n",
    "    \n",
    "    raw_inputs_loader.set_interval(interval)\n",
    "    unit_inputs = units.UnitData(raw_inputs_loader)\n",
    "    interconnector_inputs = interconnectors.InterconnectorData(raw_inputs_loader)\n",
    "    constraint_inputs = constraints.ConstraintData(raw_inputs_loader)\n",
    "    demand_inputs = demand.DemandData(raw_inputs_loader)\n",
    "\n",
    "    # Define market, unit info\n",
    "    unit_info = unit_inputs.get_unit_info()\n",
    "    market = markets.SpotMarket(market_regions=['QLD1', 'NSW1', 'VIC1',\n",
    "                                                'SA1', 'TAS1'],\n",
    "                                unit_info=unit_info)\n",
    "\n",
    "    # Set volume, price bids\n",
    "    volume_bids, price_bids = unit_inputs.get_processed_bids()\n",
    "    market.set_unit_volume_bids(volume_bids)\n",
    "    market.set_unit_price_bids(price_bids)\n",
    "\n",
    "    # Set bid in capacity limits\n",
    "    unit_bid_limit = unit_inputs.get_unit_bid_availability()\n",
    "    market.set_unit_bid_capacity_constraints(unit_bid_limit)\n",
    "    cost = constraint_inputs.get_constraint_violation_prices()['unit_capacity']\n",
    "    market.make_constraints_elastic('unit_bid_capacity', violation_cost=cost)\n",
    "\n",
    "    # Set limits provided by the unconstrained intermittent generation\n",
    "    # forecasts. Primarily for wind and solar.\n",
    "    unit_uigf_limit = unit_inputs.get_unit_uigf_limits()\n",
    "    market.set_unconstrained_intermitent_generation_forecast_constraint(\n",
    "        unit_uigf_limit)\n",
    "    cost = constraint_inputs.get_constraint_violation_prices()['uigf']\n",
    "    market.make_constraints_elastic('uigf_capacity', violation_cost=cost)\n",
    "\n",
    "    # Set unit ramp rates.\n",
    "    ramp_rates = unit_inputs.get_ramp_rates_used_for_energy_dispatch()\n",
    "    market.set_unit_ramp_up_constraints(\n",
    "        ramp_rates.loc[:, ['unit', 'initial_output', 'ramp_up_rate']])\n",
    "    market.set_unit_ramp_down_constraints(\n",
    "        ramp_rates.loc[:, ['unit', 'initial_output', 'ramp_down_rate']])\n",
    "    cost = constraint_inputs.get_constraint_violation_prices()['ramp_rate']\n",
    "    market.make_constraints_elastic('ramp_up', violation_cost=cost)\n",
    "    market.make_constraints_elastic('ramp_down', violation_cost=cost)\n",
    "\n",
    "    # Set unit FCAS trapezium constraints.\n",
    "    unit_inputs.add_fcas_trapezium_constraints()\n",
    "    cost = constraint_inputs.get_constraint_violation_prices()['fcas_max_avail']\n",
    "    fcas_availability = unit_inputs.get_fcas_max_availability()\n",
    "    market.set_fcas_max_availability(fcas_availability)\n",
    "    market.make_constraints_elastic('fcas_max_availability', cost)\n",
    "    cost = constraint_inputs.get_constraint_violation_prices()['fcas_profile']\n",
    "    regulation_trapeziums = unit_inputs.get_fcas_regulation_trapeziums()\n",
    "    market.set_energy_and_regulation_capacity_constraints(regulation_trapeziums)\n",
    "    market.make_constraints_elastic('energy_and_regulation_capacity', cost)\n",
    "    scada_ramp_down_rates = unit_inputs.get_scada_ramp_down_rates_of_lower_reg_units()\n",
    "    market.set_joint_ramping_constraints_lower_reg(scada_ramp_down_rates)\n",
    "    market.make_constraints_elastic('joint_ramping_lower_reg', cost)\n",
    "    scada_ramp_up_rates = unit_inputs.get_scada_ramp_up_rates_of_raise_reg_units()\n",
    "    market.set_joint_ramping_constraints_raise_reg(scada_ramp_up_rates)\n",
    "    market.make_constraints_elastic('joint_ramping_raise_reg', cost)\n",
    "    contingency_trapeziums = unit_inputs.get_contingency_services()\n",
    "    market.set_joint_capacity_constraints(contingency_trapeziums)\n",
    "    market.make_constraints_elastic('joint_capacity', cost)\n",
    "\n",
    "    # Set interconnector definitions, limits and loss models.\n",
    "    interconnectors_definitions = \\\n",
    "        interconnector_inputs.get_interconnector_definitions()\n",
    "    loss_functions, interpolation_break_points = \\\n",
    "        interconnector_inputs.get_interconnector_loss_model()\n",
    "    market.set_interconnectors(interconnectors_definitions)\n",
    "    market.set_interconnector_losses(loss_functions,\n",
    "                                      interpolation_break_points)\n",
    "\n",
    "    # Add FCAS market constraints.\n",
    "    fcas_requirements = constraint_inputs.get_fcas_requirements()\n",
    "    market.set_fcas_requirements_constraints(fcas_requirements)\n",
    "    violation_costs = constraint_inputs.get_violation_costs()\n",
    "    market.make_constraints_elastic('fcas', violation_cost=violation_costs) \n",
    "\n",
    "    # Add generic constraints, RHS parameters\n",
    "    generic_rhs = constraint_inputs.get_rhs_and_type_excluding_regional_fcas_constraints()\n",
    "    market.set_generic_constraints(generic_rhs)\n",
    "    market.make_constraints_elastic('generic', violation_cost=violation_costs)\n",
    "    \n",
    "    # Add generic constraints, LHS coefficients DUIDs\n",
    "    unit_generic_lhs = constraint_inputs.get_unit_lhs()\n",
    "    market.link_units_to_generic_constraints(unit_generic_lhs)\n",
    "    \n",
    "    # Add generic constraints, LHS coeffients ICs\n",
    "    interconnector_generic_lhs = constraint_inputs.get_interconnector_lhs()\n",
    "    market.link_interconnectors_to_generic_constraints(\n",
    "        interconnector_generic_lhs)\n",
    "    \n",
    "    # Set the operational demand to be met by dispatch.\n",
    "    regional_demand = demand_inputs.get_operational_demand()\n",
    "    market.set_demand_constraints(regional_demand)\n",
    "    \n",
    "    # Check to remove constraint set\n",
    "    if remove_constraint_name is not None:\n",
    "        for constraint in remove_constraint_name:\n",
    "            market.remove_generic_constraint_set(constraint)\n",
    "    \n",
    "    # Run market dispatch\n",
    "    market.dispatch()\n",
    "    \n",
    "    # Retrieve & Save market data\n",
    "    result_mv = market.get_constraint_marginal_values()\n",
    "    result_mv.insert(0,'interval',interval)\n",
    "\n",
    "    result_units = market.get_unit_dispatch()\n",
    "    result_units.insert(0,'interval',interval)\n",
    "    \n",
    "    result_prices = market.get_energy_prices()\n",
    "    result_prices.insert(0,'interval',interval)\n",
    "\n",
    "    return {'marginal_values': result_mv, 'unit_dispatch': result_units, 'energy_prices': result_prices}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Section B - Running Market Dispatch across timeseries\n",
    "### B1. Initial Results\n",
    "Importantly, we are now interested in observing what is happening throughout the day across multiple dispatch intervals and the overall impact of the constraint under investigation on unit dispatch and market prices. At this stage, the first iteration across the timeseries includes all historical constraints."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dispatch Simulation Complete\n"
     ]
    }
   ],
   "source": [
    "for di in di_df['di_list']:\n",
    "    outputs = economic_dispatch(di)\n",
    "    outputs_mvs += [outputs['marginal_values']]\n",
    "    outputs_units += [outputs['unit_dispatch']]\n",
    "    outputs_prices += [outputs['energy_prices']]\n",
    "\n",
    "marginal_values = pd.concat(outputs_mvs)\n",
    "unit_dispatch = pd.concat(outputs_units)\n",
    "prices = pd.concat(outputs_prices)\n",
    "\n",
    "print(\"Dispatch Simulation Complete\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### B2. Simulated Market Prices\n",
    "Tablulating the price results we can later compare the impact of the specific constraint on market prices. The full dataframe is accesible via a downloaded excel file at the end of this notebook.\n",
    "\n",
    "**Tabulated Price Results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>interval</th>\n",
       "      <th>2021/02/15 06:00:00</th>\n",
       "      <th>2021/02/15 06:05:00</th>\n",
       "      <th>2021/02/15 06:10:00</th>\n",
       "      <th>2021/02/15 06:15:00</th>\n",
       "      <th>2021/02/15 06:20:00</th>\n",
       "      <th>2021/02/15 06:25:00</th>\n",
       "      <th>2021/02/15 06:30:00</th>\n",
       "      <th>2021/02/15 06:35:00</th>\n",
       "      <th>2021/02/15 06:40:00</th>\n",
       "      <th>2021/02/15 06:45:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2021/02/15 17:20:00</th>\n",
       "      <th>2021/02/15 17:25:00</th>\n",
       "      <th>2021/02/15 17:30:00</th>\n",
       "      <th>2021/02/15 17:35:00</th>\n",
       "      <th>2021/02/15 17:40:00</th>\n",
       "      <th>2021/02/15 17:45:00</th>\n",
       "      <th>2021/02/15 17:50:00</th>\n",
       "      <th>2021/02/15 17:55:00</th>\n",
       "      <th>2021/02/15 18:00:00</th>\n",
       "      <th>2021/02/15 18:05:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NSW1</th>\n",
       "      <td>37.128317</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.470000</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>37.262931</td>\n",
       "      <td>37.539484</td>\n",
       "      <td>37.222093</td>\n",
       "      <td>35.470000</td>\n",
       "      <td>...</td>\n",
       "      <td>36.142973</td>\n",
       "      <td>36.067103</td>\n",
       "      <td>35.617971</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.842109</td>\n",
       "      <td>36.175748</td>\n",
       "      <td>35.580000</td>\n",
       "      <td>49.220000</td>\n",
       "      <td>52.605351</td>\n",
       "      <td>38.265085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QLD1</th>\n",
       "      <td>38.900000</td>\n",
       "      <td>37.124287</td>\n",
       "      <td>36.396962</td>\n",
       "      <td>36.682978</td>\n",
       "      <td>36.444699</td>\n",
       "      <td>35.616770</td>\n",
       "      <td>37.730000</td>\n",
       "      <td>37.730000</td>\n",
       "      <td>37.730000</td>\n",
       "      <td>35.406946</td>\n",
       "      <td>...</td>\n",
       "      <td>37.386470</td>\n",
       "      <td>37.314017</td>\n",
       "      <td>37.143988</td>\n",
       "      <td>37.576261</td>\n",
       "      <td>38.258477</td>\n",
       "      <td>38.900000</td>\n",
       "      <td>38.548054</td>\n",
       "      <td>52.145162</td>\n",
       "      <td>55.730000</td>\n",
       "      <td>41.470000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SA1</th>\n",
       "      <td>32.736256</td>\n",
       "      <td>32.104579</td>\n",
       "      <td>32.019084</td>\n",
       "      <td>32.009874</td>\n",
       "      <td>32.462971</td>\n",
       "      <td>32.964412</td>\n",
       "      <td>35.382052</td>\n",
       "      <td>36.950017</td>\n",
       "      <td>37.016680</td>\n",
       "      <td>35.350532</td>\n",
       "      <td>...</td>\n",
       "      <td>38.031225</td>\n",
       "      <td>38.612664</td>\n",
       "      <td>38.191360</td>\n",
       "      <td>38.772997</td>\n",
       "      <td>38.761503</td>\n",
       "      <td>39.407664</td>\n",
       "      <td>39.505089</td>\n",
       "      <td>55.359105</td>\n",
       "      <td>58.103616</td>\n",
       "      <td>42.463455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAS1</th>\n",
       "      <td>39.881000</td>\n",
       "      <td>38.581000</td>\n",
       "      <td>38.581000</td>\n",
       "      <td>38.581000</td>\n",
       "      <td>40.205455</td>\n",
       "      <td>43.641044</td>\n",
       "      <td>53.210000</td>\n",
       "      <td>60.160000</td>\n",
       "      <td>57.960000</td>\n",
       "      <td>60.160000</td>\n",
       "      <td>...</td>\n",
       "      <td>36.964312</td>\n",
       "      <td>39.517000</td>\n",
       "      <td>39.517000</td>\n",
       "      <td>37.848780</td>\n",
       "      <td>37.268780</td>\n",
       "      <td>39.517000</td>\n",
       "      <td>40.783248</td>\n",
       "      <td>52.169272</td>\n",
       "      <td>53.692700</td>\n",
       "      <td>38.988223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIC1</th>\n",
       "      <td>32.683259</td>\n",
       "      <td>31.934547</td>\n",
       "      <td>31.967247</td>\n",
       "      <td>31.958052</td>\n",
       "      <td>32.303594</td>\n",
       "      <td>32.622727</td>\n",
       "      <td>34.606221</td>\n",
       "      <td>35.622464</td>\n",
       "      <td>35.700290</td>\n",
       "      <td>34.115011</td>\n",
       "      <td>...</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>35.004952</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>48.705042</td>\n",
       "      <td>51.129443</td>\n",
       "      <td>37.578004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 146 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "interval  2021/02/15 06:00:00  2021/02/15 06:05:00  2021/02/15 06:10:00  \\\n",
       "region                                                                    \n",
       "NSW1                37.128317            35.480000            35.480000   \n",
       "QLD1                38.900000            37.124287            36.396962   \n",
       "SA1                 32.736256            32.104579            32.019084   \n",
       "TAS1                39.881000            38.581000            38.581000   \n",
       "VIC1                32.683259            31.934547            31.967247   \n",
       "\n",
       "interval  2021/02/15 06:15:00  2021/02/15 06:20:00  2021/02/15 06:25:00  \\\n",
       "region                                                                    \n",
       "NSW1                35.470000            35.480000            35.480000   \n",
       "QLD1                36.682978            36.444699            35.616770   \n",
       "SA1                 32.009874            32.462971            32.964412   \n",
       "TAS1                38.581000            40.205455            43.641044   \n",
       "VIC1                31.958052            32.303594            32.622727   \n",
       "\n",
       "interval  2021/02/15 06:30:00  2021/02/15 06:35:00  2021/02/15 06:40:00  \\\n",
       "region                                                                    \n",
       "NSW1                37.262931            37.539484            37.222093   \n",
       "QLD1                37.730000            37.730000            37.730000   \n",
       "SA1                 35.382052            36.950017            37.016680   \n",
       "TAS1                53.210000            60.160000            57.960000   \n",
       "VIC1                34.606221            35.622464            35.700290   \n",
       "\n",
       "interval  2021/02/15 06:45:00  ...  2021/02/15 17:20:00  2021/02/15 17:25:00  \\\n",
       "region                         ...                                             \n",
       "NSW1                35.470000  ...            36.142973            36.067103   \n",
       "QLD1                35.406946  ...            37.386470            37.314017   \n",
       "SA1                 35.350532  ...            38.031225            38.612664   \n",
       "TAS1                60.160000  ...            36.964312            39.517000   \n",
       "VIC1                34.115011  ...            34.960000            34.960000   \n",
       "\n",
       "interval  2021/02/15 17:30:00  2021/02/15 17:35:00  2021/02/15 17:40:00  \\\n",
       "region                                                                    \n",
       "NSW1                35.617971            35.480000            35.842109   \n",
       "QLD1                37.143988            37.576261            38.258477   \n",
       "SA1                 38.191360            38.772997            38.761503   \n",
       "TAS1                39.517000            37.848780            37.268780   \n",
       "VIC1                34.960000            34.960000            34.960000   \n",
       "\n",
       "interval  2021/02/15 17:45:00  2021/02/15 17:50:00  2021/02/15 17:55:00  \\\n",
       "region                                                                    \n",
       "NSW1                36.175748            35.580000            49.220000   \n",
       "QLD1                38.900000            38.548054            52.145162   \n",
       "SA1                 39.407664            39.505089            55.359105   \n",
       "TAS1                39.517000            40.783248            52.169272   \n",
       "VIC1                35.004952            34.960000            48.705042   \n",
       "\n",
       "interval  2021/02/15 18:00:00  2021/02/15 18:05:00  \n",
       "region                                              \n",
       "NSW1                52.605351            38.265085  \n",
       "QLD1                55.730000            41.470000  \n",
       "SA1                 58.103616            42.463455  \n",
       "TAS1                53.692700            38.988223  \n",
       "VIC1                51.129443            37.578004  \n",
       "\n",
       "[5 rows x 146 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices_table = prices.groupby(['region','interval']).price.first().unstack()\n",
    "prices_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### B3. Binding Constraint Results\n",
    "The below produces a very useful table showing all constraints that have binded at some stage during the timeseries. Each column displays the marginal value for the specific interval, where NaN (or zero) indicates that the constraint did not bind during that interval.\n",
    "\n",
    "Not also that some constraints may have a dynamic RHS that is not necessarily fixed, however we haven't captured this level of detail here. The consequent change in marginal value that may be due to the dynamic rhs changing as opposed to the lhs arguments is not known here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>interval</th>\n",
       "      <th>2021/02/15 06:00:00</th>\n",
       "      <th>2021/02/15 06:05:00</th>\n",
       "      <th>2021/02/15 06:10:00</th>\n",
       "      <th>2021/02/15 06:15:00</th>\n",
       "      <th>2021/02/15 06:20:00</th>\n",
       "      <th>2021/02/15 06:25:00</th>\n",
       "      <th>2021/02/15 06:30:00</th>\n",
       "      <th>2021/02/15 06:35:00</th>\n",
       "      <th>2021/02/15 06:40:00</th>\n",
       "      <th>2021/02/15 06:45:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2021/02/15 17:20:00</th>\n",
       "      <th>2021/02/15 17:25:00</th>\n",
       "      <th>2021/02/15 17:30:00</th>\n",
       "      <th>2021/02/15 17:35:00</th>\n",
       "      <th>2021/02/15 17:40:00</th>\n",
       "      <th>2021/02/15 17:45:00</th>\n",
       "      <th>2021/02/15 17:50:00</th>\n",
       "      <th>2021/02/15 17:55:00</th>\n",
       "      <th>2021/02/15 18:00:00</th>\n",
       "      <th>2021/02/15 18:05:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>set</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>#MWPS1PV1_E</th>\n",
       "      <td>-1032.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1032.0</td>\n",
       "      <td>-1032.5</td>\n",
       "      <td>-1033.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>-1037.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1039.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1042.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#MWPS2PV1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1032.0</td>\n",
       "      <td>-1032.5</td>\n",
       "      <td>-1033.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1037.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.2</td>\n",
       "      <td>-1038.8</td>\n",
       "      <td>-1038.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1055.4</td>\n",
       "      <td>-1058.1</td>\n",
       "      <td>-1042.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#MWPS4PV1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1032.1</td>\n",
       "      <td>-1032.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-1038.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1039.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1055.4</td>\n",
       "      <td>-1058.1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#PPCCGT_D_E</th>\n",
       "      <td>14967.3</td>\n",
       "      <td>14967.9</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14967.5</td>\n",
       "      <td>14967.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>14962.0</td>\n",
       "      <td>14961.4</td>\n",
       "      <td>14961.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#TORRB1_D_E</th>\n",
       "      <td>14967.3</td>\n",
       "      <td>14967.9</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14967.5</td>\n",
       "      <td>14967.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#TORRB3_D_E</th>\n",
       "      <td>14967.3</td>\n",
       "      <td>14967.9</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14967.5</td>\n",
       "      <td>14967.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#WARWSF1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#YATSF1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$BARRON-1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$BLOWERNG</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>-1037.3</td>\n",
       "      <td>-1037.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>...</td>\n",
       "      <td>-1036.1</td>\n",
       "      <td>-1036.1</td>\n",
       "      <td>-1035.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.8</td>\n",
       "      <td>-1036.2</td>\n",
       "      <td>-1035.6</td>\n",
       "      <td>-1049.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$CALL_B_1</th>\n",
       "      <td>14961.1</td>\n",
       "      <td>14962.9</td>\n",
       "      <td>14963.6</td>\n",
       "      <td>14963.3</td>\n",
       "      <td>14963.6</td>\n",
       "      <td>14964.4</td>\n",
       "      <td>14962.3</td>\n",
       "      <td>14962.3</td>\n",
       "      <td>14962.3</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>12.2</td>\n",
       "      <td>12.3</td>\n",
       "      <td>12.5</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>10.7</td>\n",
       "      <td>11.1</td>\n",
       "      <td>-2.5</td>\n",
       "      <td>-6.1</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$YATSF1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F_T_AUFLS2_R6</th>\n",
       "      <td>-3.5</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-7.2</td>\n",
       "      <td>-5.1</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-3.6</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.1</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>-12.8</td>\n",
       "      <td>-8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N&gt;&gt;N-NIL_94T</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N&gt;&gt;N-NIL_94T_947</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N&gt;&gt;N-PKWL_94K_2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-51.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_N_DARLSF1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N^^N_NIL_2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N^^N_NIL_3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q&gt;NIL_COLNVSF1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q&gt;NIL_YLMR</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S&gt;NIL_MHNW1_MHNW2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V&gt;&gt;V_NIL_14</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V&gt;V_NIL_17</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V_BANSF_BBD_80</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V_T_NIL_FCSPS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26 rows × 146 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "interval           2021/02/15 06:00:00  2021/02/15 06:05:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1032.7                  0.0   \n",
       "#MWPS2PV1_E                        0.0                  0.0   \n",
       "#MWPS4PV1_E                        0.0              -1032.1   \n",
       "#PPCCGT_D_E                    14967.3              14967.9   \n",
       "#TORRB1_D_E                    14967.3              14967.9   \n",
       "#TORRB3_D_E                    14967.3              14967.9   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                          0.0                  0.0   \n",
       "$CALL_B_1                      14961.1              14962.9   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -3.5                 -8.0   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:10:00  2021/02/15 06:15:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0              -1032.0   \n",
       "#MWPS2PV1_E                        0.0              -1032.0   \n",
       "#MWPS4PV1_E                    -1032.0                  0.0   \n",
       "#PPCCGT_D_E                    14968.0              14968.0   \n",
       "#TORRB1_D_E                    14968.0              14968.0   \n",
       "#TORRB3_D_E                    14968.0              14968.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.5                  0.0   \n",
       "$CALL_B_1                      14963.6              14963.3   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.0   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:20:00  2021/02/15 06:25:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1032.5              -1033.0   \n",
       "#MWPS2PV1_E                    -1032.5              -1033.0   \n",
       "#MWPS4PV1_E                        0.0                  0.0   \n",
       "#PPCCGT_D_E                    14967.5              14967.0   \n",
       "#TORRB1_D_E                    14967.5              14967.0   \n",
       "#TORRB3_D_E                    14967.5              14967.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.5              -1035.5   \n",
       "$CALL_B_1                      14963.6              14964.4   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -3.5                 -7.2   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:30:00  2021/02/15 06:35:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1035.4              -1037.0   \n",
       "#MWPS2PV1_E                    -1035.4                  0.0   \n",
       "#MWPS4PV1_E                    -1035.4                  0.0   \n",
       "#PPCCGT_D_E                    14964.6              14963.0   \n",
       "#TORRB1_D_E                    14964.6              14963.0   \n",
       "#TORRB3_D_E                    14964.6              14963.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1037.3              -1037.5   \n",
       "$CALL_B_1                      14962.3              14962.3   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -5.1                 -3.5   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:40:00  2021/02/15 06:45:00  ...  \\\n",
       "set                                                          ...   \n",
       "#MWPS1PV1_E                        0.0              -1035.4  ...   \n",
       "#MWPS2PV1_E                    -1037.0                  0.0  ...   \n",
       "#MWPS4PV1_E                        0.0                  0.0  ...   \n",
       "#PPCCGT_D_E                    14963.0              14964.6  ...   \n",
       "#TORRB1_D_E                    14963.0              14964.6  ...   \n",
       "#TORRB3_D_E                    14963.0              14964.6  ...   \n",
       "#WARWSF1_E                         0.0                  0.0  ...   \n",
       "#YATSF1_E                          0.0                  0.0  ...   \n",
       "$BARRON-1                          0.0                  0.0  ...   \n",
       "$BLOWERNG                          0.0              -1035.5  ...   \n",
       "$CALL_B_1                      14962.3              14964.6  ...   \n",
       "$YATSF1                            0.0                  0.0  ...   \n",
       "F_T_AUFLS2_R6                     -3.6                 -3.5  ...   \n",
       "N>>N-NIL_94T                       0.0                  0.0  ...   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0  ...   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0  ...   \n",
       "NC_N_DARLSF1                       0.0                  0.0  ...   \n",
       "N^^N_NIL_2                         0.0                  0.0  ...   \n",
       "N^^N_NIL_3                         0.0                  0.0  ...   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0  ...   \n",
       "Q>NIL_YLMR                         0.0                  0.0  ...   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0  ...   \n",
       "V>>V_NIL_14                        0.0                  0.0  ...   \n",
       "V>V_NIL_17                         0.0                  0.0  ...   \n",
       "V_BANSF_BBD_80                     0.0                  0.0  ...   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0  ...   \n",
       "\n",
       "interval           2021/02/15 17:20:00  2021/02/15 17:25:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0              -1038.6   \n",
       "#MWPS2PV1_E                        0.0                  0.0   \n",
       "#MWPS4PV1_E                    -1038.0                  0.0   \n",
       "#PPCCGT_D_E                    14962.0              14961.4   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1036.1              -1036.1   \n",
       "$CALL_B_1                         12.2                 12.3   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.0   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                  -51.9                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 17:30:00  2021/02/15 17:35:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0                  0.0   \n",
       "#MWPS2PV1_E                    -1038.2              -1038.8   \n",
       "#MWPS4PV1_E                        0.0              -1038.8   \n",
       "#PPCCGT_D_E                    14961.8                  0.0   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.6                  0.0   \n",
       "$CALL_B_1                         12.5                 12.0   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.0   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 17:40:00  2021/02/15 17:45:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0                  0.0   \n",
       "#MWPS2PV1_E                    -1038.8                  0.0   \n",
       "#MWPS4PV1_E                        0.0              -1039.4   \n",
       "#PPCCGT_D_E                        0.0                  0.0   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.8              -1036.2   \n",
       "$CALL_B_1                         11.4                 10.7   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.1                 -8.0   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 17:50:00  2021/02/15 17:55:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1039.5                  0.0   \n",
       "#MWPS2PV1_E                        0.0              -1055.4   \n",
       "#MWPS4PV1_E                        0.0              -1055.4   \n",
       "#PPCCGT_D_E                        0.0                  0.0   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.6              -1049.2   \n",
       "$CALL_B_1                         11.1                 -2.5   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.5   \n",
       "N>>N-NIL_94T                       0.0                  0.0   \n",
       "N>>N-NIL_94T_947                   0.0                  0.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 18:00:00  2021/02/15 18:05:00  \n",
       "set                                                          \n",
       "#MWPS1PV1_E                        0.0              -1042.5  \n",
       "#MWPS2PV1_E                    -1058.1              -1042.5  \n",
       "#MWPS4PV1_E                    -1058.1                  0.0  \n",
       "#PPCCGT_D_E                        0.0                  0.0  \n",
       "#TORRB1_D_E                        0.0                  0.0  \n",
       "#TORRB3_D_E                        0.0                  0.0  \n",
       "#WARWSF1_E                         0.0                  0.0  \n",
       "#YATSF1_E                          0.0                  0.0  \n",
       "$BARRON-1                          0.0                  0.0  \n",
       "$BLOWERNG                          0.0              -1038.3  \n",
       "$CALL_B_1                         -6.1                  8.1  \n",
       "$YATSF1                            0.0                  0.0  \n",
       "F_T_AUFLS2_R6                    -12.8                 -8.3  \n",
       "N>>N-NIL_94T                       0.0                  0.0  \n",
       "N>>N-NIL_94T_947                   0.0                  0.0  \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0  \n",
       "NC_N_DARLSF1                       0.0                  0.0  \n",
       "N^^N_NIL_2                         0.0                  0.0  \n",
       "N^^N_NIL_3                         0.0                  0.0  \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0  \n",
       "Q>NIL_YLMR                         0.0                  0.0  \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0  \n",
       "V>>V_NIL_14                        0.0                  0.0  \n",
       "V>V_NIL_17                         0.0                  0.0  \n",
       "V_BANSF_BBD_80                     0.0                  0.0  \n",
       "V_T_NIL_FCSPS                      0.0                  0.0  \n",
       "\n",
       "[26 rows x 146 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mv_table = marginal_values.groupby(['set','interval']).marginal_value.first().unstack().fillna(0).round(1)\n",
    "mv_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Retrieve information about the 'N>>N-NIL_94T_947' constraint\n",
    "Specifically, we are interested in the impact of removing the <b>N>>N-NIL_94T_947</b> constraint, as per the previous example however now looking across the timeseries of dispatch intervals. From which we can compare the earlier analysis of this occurance in the [Example by J. Simpson](https://jacksimpson.co/exploring-the-impact-of-constraints-on-a-solar-farm-in-the-national-electricity-market/)\n",
    "\n",
    "Here we can note the change in marginal values across the timeseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>N&gt;&gt;N-NIL_94T_947</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>interval</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021/02/15 07:20:00</th>\n",
       "      <td>-52.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 07:25:00</th>\n",
       "      <td>-49.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 07:30:00</th>\n",
       "      <td>-50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 07:35:00</th>\n",
       "      <td>-48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 07:55:00</th>\n",
       "      <td>-471.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 15:35:00</th>\n",
       "      <td>-476.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 15:40:00</th>\n",
       "      <td>-498.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 15:45:00</th>\n",
       "      <td>-522.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 15:50:00</th>\n",
       "      <td>-498.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021/02/15 15:55:00</th>\n",
       "      <td>-498.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     N>>N-NIL_94T_947\n",
       "interval                             \n",
       "2021/02/15 07:20:00             -52.2\n",
       "2021/02/15 07:25:00             -49.6\n",
       "2021/02/15 07:30:00             -50.0\n",
       "2021/02/15 07:35:00             -48.0\n",
       "2021/02/15 07:55:00            -471.7\n",
       "...                               ...\n",
       "2021/02/15 15:35:00            -476.5\n",
       "2021/02/15 15:40:00            -498.6\n",
       "2021/02/15 15:45:00            -522.9\n",
       "2021/02/15 15:50:00            -498.6\n",
       "2021/02/15 15:55:00            -498.6\n",
       "\n",
       "[96 rows x 1 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "con_vals = mv_table.loc['N>>N-NIL_94T_947',:]\n",
    "con_vals_nonzero = con_vals[con_vals != 0]\n",
    "pd.DataFrame(con_vals_nonzero)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### B4. Unit Dispatch Results\n",
    "For completeness, we can also tabulate the unit dispatch results here. Specifically, we are only interested in the energy service not FCAS here. These are further saved in the downloaded results file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>interval</th>\n",
       "      <th>2021/02/15 06:00:00</th>\n",
       "      <th>2021/02/15 06:05:00</th>\n",
       "      <th>2021/02/15 06:10:00</th>\n",
       "      <th>2021/02/15 06:15:00</th>\n",
       "      <th>2021/02/15 06:20:00</th>\n",
       "      <th>2021/02/15 06:25:00</th>\n",
       "      <th>2021/02/15 06:30:00</th>\n",
       "      <th>2021/02/15 06:35:00</th>\n",
       "      <th>2021/02/15 06:40:00</th>\n",
       "      <th>2021/02/15 06:45:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2021/02/15 17:20:00</th>\n",
       "      <th>2021/02/15 17:25:00</th>\n",
       "      <th>2021/02/15 17:30:00</th>\n",
       "      <th>2021/02/15 17:35:00</th>\n",
       "      <th>2021/02/15 17:40:00</th>\n",
       "      <th>2021/02/15 17:45:00</th>\n",
       "      <th>2021/02/15 17:50:00</th>\n",
       "      <th>2021/02/15 17:55:00</th>\n",
       "      <th>2021/02/15 18:00:00</th>\n",
       "      <th>2021/02/15 18:05:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unit</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AGLHAL</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGLSOM</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANGAST1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARWF1</th>\n",
       "      <td>112.4</td>\n",
       "      <td>105.9</td>\n",
       "      <td>100.1</td>\n",
       "      <td>104.7</td>\n",
       "      <td>103.6</td>\n",
       "      <td>111.4</td>\n",
       "      <td>99.2</td>\n",
       "      <td>95.0</td>\n",
       "      <td>89.7</td>\n",
       "      <td>94.1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BALBG1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YENDWF1</th>\n",
       "      <td>61.4</td>\n",
       "      <td>65.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.6</td>\n",
       "      <td>47.3</td>\n",
       "      <td>52.8</td>\n",
       "      <td>55.6</td>\n",
       "      <td>58.3</td>\n",
       "      <td>55.5</td>\n",
       "      <td>...</td>\n",
       "      <td>18.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>17.6</td>\n",
       "      <td>19.3</td>\n",
       "      <td>17.8</td>\n",
       "      <td>17.9</td>\n",
       "      <td>17.6</td>\n",
       "      <td>18.8</td>\n",
       "      <td>18.1</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS1</th>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>...</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS2</th>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>...</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS3</th>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>...</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS4</th>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>...</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>334 rows × 146 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "interval  2021/02/15 06:00:00  2021/02/15 06:05:00  2021/02/15 06:10:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                   112.4                105.9                100.1   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  61.4                 65.8                 61.0   \n",
       "YWPS1                   380.0                380.0                380.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   390.0                390.0                390.0   \n",
       "\n",
       "interval  2021/02/15 06:15:00  2021/02/15 06:20:00  2021/02/15 06:25:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                   104.7                103.6                111.4   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  52.0                 52.6                 47.3   \n",
       "YWPS1                   380.0                380.0                380.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   390.0                390.0                390.0   \n",
       "\n",
       "interval  2021/02/15 06:30:00  2021/02/15 06:35:00  2021/02/15 06:40:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                    99.2                 95.0                 89.7   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  52.8                 55.6                 58.3   \n",
       "YWPS1                   380.0                380.0                380.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   390.0                390.0                390.0   \n",
       "\n",
       "interval  2021/02/15 06:45:00  ...  2021/02/15 17:20:00  2021/02/15 17:25:00  \\\n",
       "unit                           ...                                             \n",
       "AGLHAL                    0.0  ...                  0.0                  0.0   \n",
       "AGLSOM                    0.0  ...                  0.0                  0.0   \n",
       "ANGAST1                   0.0  ...                  0.0                  0.0   \n",
       "ARWF1                    94.1  ...                  0.0                  0.0   \n",
       "BALBG1                    0.0  ...                  0.0                  0.0   \n",
       "...                       ...  ...                  ...                  ...   \n",
       "YENDWF1                  55.5  ...                 18.6                 18.9   \n",
       "YWPS1                   380.0  ...                370.0                370.0   \n",
       "YWPS2                   350.0  ...                350.0                350.0   \n",
       "YWPS3                   375.0  ...                375.0                375.0   \n",
       "YWPS4                   390.0  ...                380.0                380.0   \n",
       "\n",
       "interval  2021/02/15 17:30:00  2021/02/15 17:35:00  2021/02/15 17:40:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                     0.0                  0.0                  0.0   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  17.6                 19.3                 17.8   \n",
       "YWPS1                   370.0                370.0                370.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   380.0                380.0                380.0   \n",
       "\n",
       "interval  2021/02/15 17:45:00  2021/02/15 17:50:00  2021/02/15 17:55:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                     0.0                  0.0                  0.0   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  17.9                 17.6                 18.8   \n",
       "YWPS1                   370.0                370.0                370.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   380.0                380.0                380.0   \n",
       "\n",
       "interval  2021/02/15 18:00:00  2021/02/15 18:05:00  \n",
       "unit                                                \n",
       "AGLHAL                    0.0                  0.0  \n",
       "AGLSOM                    0.0                  0.0  \n",
       "ANGAST1                   0.0                  0.0  \n",
       "ARWF1                     0.0                  0.0  \n",
       "BALBG1                    0.0                  0.0  \n",
       "...                       ...                  ...  \n",
       "YENDWF1                  18.1                 16.5  \n",
       "YWPS1                   370.0                375.0  \n",
       "YWPS2                   350.0                350.0  \n",
       "YWPS3                   375.0                375.0  \n",
       "YWPS4                   380.0                380.0  \n",
       "\n",
       "[334 rows x 146 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unit_dispatch = unit_dispatch[unit_dispatch['service'] == 'energy']\n",
    "\n",
    "units_table = unit_dispatch.groupby(['unit','interval']).dispatch.first().unstack().round(1)\n",
    "units_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Section C - Rerun dispatch with constraint removed\n",
    "### C1. Dispatch Simulation\n",
    "Re-runing the earlier economic dispatch loop, however with the <code>remove_constraint_name</code> variable set to **'N>>N-NIL_94T_947'** yields a new set of results. Noting the <font color=purple>**_r**</font> designation to each variable indicating the dispatch with the constriant removed.\n",
    "\n",
    "Unsuprisingly (or perhaps even suprisingly) after the **'N>>N-NIL_94T_947'** constraint is removed, the **'N>>N-NIL_94T'** constraint then binds. Given this is the same line 94T being considered which is thermally constrained, and for somewhat illustrative purposes both are removed here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dispatch Simulation Complete\n"
     ]
    }
   ],
   "source": [
    "#Clear output lists\n",
    "outputs, outputs_mvs, outputs_units, outputs_prices = [],[],[],[]\n",
    "\n",
    "for di in dispatch_intervals:\n",
    "    outputs = economic_dispatch(di,remove_constraint_name=['N>>N-NIL_94T_947','N>>N-NIL_94T'])\n",
    "    outputs_mvs += [outputs['marginal_values']]\n",
    "    outputs_units += [outputs['unit_dispatch']]\n",
    "    outputs_prices += [outputs['energy_prices']]\n",
    "\n",
    "marginal_values_r = pd.concat(outputs_mvs)\n",
    "unit_dispatch_r = pd.concat(outputs_units)\n",
    "prices_r = pd.concat(outputs_prices)\n",
    "\n",
    "print(\"Dispatch Simulation Complete\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### C2. Simulated Market Prices\n",
    "Tablulating the price results we can compare with the earlier results. The full dataframe is accesible via a downloaded excel file at the end of this notebook.\n",
    "\n",
    "**Tabulated Price Results**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>interval</th>\n",
       "      <th>2021/02/15 06:00:00</th>\n",
       "      <th>2021/02/15 06:05:00</th>\n",
       "      <th>2021/02/15 06:10:00</th>\n",
       "      <th>2021/02/15 06:15:00</th>\n",
       "      <th>2021/02/15 06:20:00</th>\n",
       "      <th>2021/02/15 06:25:00</th>\n",
       "      <th>2021/02/15 06:30:00</th>\n",
       "      <th>2021/02/15 06:35:00</th>\n",
       "      <th>2021/02/15 06:40:00</th>\n",
       "      <th>2021/02/15 06:45:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2021/02/15 17:20:00</th>\n",
       "      <th>2021/02/15 17:25:00</th>\n",
       "      <th>2021/02/15 17:30:00</th>\n",
       "      <th>2021/02/15 17:35:00</th>\n",
       "      <th>2021/02/15 17:40:00</th>\n",
       "      <th>2021/02/15 17:45:00</th>\n",
       "      <th>2021/02/15 17:50:00</th>\n",
       "      <th>2021/02/15 17:55:00</th>\n",
       "      <th>2021/02/15 18:00:00</th>\n",
       "      <th>2021/02/15 18:05:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>region</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NSW1</th>\n",
       "      <td>37.128317</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.470000</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>37.262931</td>\n",
       "      <td>37.539484</td>\n",
       "      <td>37.222093</td>\n",
       "      <td>35.470000</td>\n",
       "      <td>...</td>\n",
       "      <td>36.142973</td>\n",
       "      <td>36.067103</td>\n",
       "      <td>35.617971</td>\n",
       "      <td>35.480000</td>\n",
       "      <td>35.842109</td>\n",
       "      <td>36.175748</td>\n",
       "      <td>35.580000</td>\n",
       "      <td>49.220000</td>\n",
       "      <td>52.605351</td>\n",
       "      <td>38.265085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QLD1</th>\n",
       "      <td>38.900000</td>\n",
       "      <td>37.124287</td>\n",
       "      <td>36.396962</td>\n",
       "      <td>36.682978</td>\n",
       "      <td>36.444699</td>\n",
       "      <td>35.616770</td>\n",
       "      <td>37.730000</td>\n",
       "      <td>37.730000</td>\n",
       "      <td>37.730000</td>\n",
       "      <td>35.406946</td>\n",
       "      <td>...</td>\n",
       "      <td>37.386470</td>\n",
       "      <td>37.314017</td>\n",
       "      <td>37.143988</td>\n",
       "      <td>37.576261</td>\n",
       "      <td>38.258477</td>\n",
       "      <td>38.900000</td>\n",
       "      <td>38.548054</td>\n",
       "      <td>52.145162</td>\n",
       "      <td>55.730000</td>\n",
       "      <td>41.470000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SA1</th>\n",
       "      <td>32.736256</td>\n",
       "      <td>32.104579</td>\n",
       "      <td>32.019084</td>\n",
       "      <td>32.009874</td>\n",
       "      <td>32.462971</td>\n",
       "      <td>32.964412</td>\n",
       "      <td>35.382052</td>\n",
       "      <td>36.950017</td>\n",
       "      <td>37.016680</td>\n",
       "      <td>35.350532</td>\n",
       "      <td>...</td>\n",
       "      <td>38.031225</td>\n",
       "      <td>38.612664</td>\n",
       "      <td>38.191360</td>\n",
       "      <td>38.772997</td>\n",
       "      <td>38.761503</td>\n",
       "      <td>39.407664</td>\n",
       "      <td>39.505089</td>\n",
       "      <td>55.359105</td>\n",
       "      <td>58.103616</td>\n",
       "      <td>42.463455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAS1</th>\n",
       "      <td>39.881000</td>\n",
       "      <td>38.581000</td>\n",
       "      <td>38.581000</td>\n",
       "      <td>38.581000</td>\n",
       "      <td>40.205455</td>\n",
       "      <td>43.641044</td>\n",
       "      <td>53.210000</td>\n",
       "      <td>60.160000</td>\n",
       "      <td>57.960000</td>\n",
       "      <td>60.160000</td>\n",
       "      <td>...</td>\n",
       "      <td>36.964312</td>\n",
       "      <td>39.517000</td>\n",
       "      <td>39.517000</td>\n",
       "      <td>37.848780</td>\n",
       "      <td>37.268780</td>\n",
       "      <td>39.517000</td>\n",
       "      <td>40.783248</td>\n",
       "      <td>52.169272</td>\n",
       "      <td>53.692700</td>\n",
       "      <td>38.988223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VIC1</th>\n",
       "      <td>32.683259</td>\n",
       "      <td>31.934547</td>\n",
       "      <td>31.967247</td>\n",
       "      <td>31.958052</td>\n",
       "      <td>32.303594</td>\n",
       "      <td>32.622727</td>\n",
       "      <td>34.606221</td>\n",
       "      <td>35.622464</td>\n",
       "      <td>35.700290</td>\n",
       "      <td>34.115011</td>\n",
       "      <td>...</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>35.004952</td>\n",
       "      <td>34.960000</td>\n",
       "      <td>48.705042</td>\n",
       "      <td>51.129443</td>\n",
       "      <td>37.578004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 146 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "interval  2021/02/15 06:00:00  2021/02/15 06:05:00  2021/02/15 06:10:00  \\\n",
       "region                                                                    \n",
       "NSW1                37.128317            35.480000            35.480000   \n",
       "QLD1                38.900000            37.124287            36.396962   \n",
       "SA1                 32.736256            32.104579            32.019084   \n",
       "TAS1                39.881000            38.581000            38.581000   \n",
       "VIC1                32.683259            31.934547            31.967247   \n",
       "\n",
       "interval  2021/02/15 06:15:00  2021/02/15 06:20:00  2021/02/15 06:25:00  \\\n",
       "region                                                                    \n",
       "NSW1                35.470000            35.480000            35.480000   \n",
       "QLD1                36.682978            36.444699            35.616770   \n",
       "SA1                 32.009874            32.462971            32.964412   \n",
       "TAS1                38.581000            40.205455            43.641044   \n",
       "VIC1                31.958052            32.303594            32.622727   \n",
       "\n",
       "interval  2021/02/15 06:30:00  2021/02/15 06:35:00  2021/02/15 06:40:00  \\\n",
       "region                                                                    \n",
       "NSW1                37.262931            37.539484            37.222093   \n",
       "QLD1                37.730000            37.730000            37.730000   \n",
       "SA1                 35.382052            36.950017            37.016680   \n",
       "TAS1                53.210000            60.160000            57.960000   \n",
       "VIC1                34.606221            35.622464            35.700290   \n",
       "\n",
       "interval  2021/02/15 06:45:00  ...  2021/02/15 17:20:00  2021/02/15 17:25:00  \\\n",
       "region                         ...                                             \n",
       "NSW1                35.470000  ...            36.142973            36.067103   \n",
       "QLD1                35.406946  ...            37.386470            37.314017   \n",
       "SA1                 35.350532  ...            38.031225            38.612664   \n",
       "TAS1                60.160000  ...            36.964312            39.517000   \n",
       "VIC1                34.115011  ...            34.960000            34.960000   \n",
       "\n",
       "interval  2021/02/15 17:30:00  2021/02/15 17:35:00  2021/02/15 17:40:00  \\\n",
       "region                                                                    \n",
       "NSW1                35.617971            35.480000            35.842109   \n",
       "QLD1                37.143988            37.576261            38.258477   \n",
       "SA1                 38.191360            38.772997            38.761503   \n",
       "TAS1                39.517000            37.848780            37.268780   \n",
       "VIC1                34.960000            34.960000            34.960000   \n",
       "\n",
       "interval  2021/02/15 17:45:00  2021/02/15 17:50:00  2021/02/15 17:55:00  \\\n",
       "region                                                                    \n",
       "NSW1                36.175748            35.580000            49.220000   \n",
       "QLD1                38.900000            38.548054            52.145162   \n",
       "SA1                 39.407664            39.505089            55.359105   \n",
       "TAS1                39.517000            40.783248            52.169272   \n",
       "VIC1                35.004952            34.960000            48.705042   \n",
       "\n",
       "interval  2021/02/15 18:00:00  2021/02/15 18:05:00  \n",
       "region                                              \n",
       "NSW1                52.605351            38.265085  \n",
       "QLD1                55.730000            41.470000  \n",
       "SA1                 58.103616            42.463455  \n",
       "TAS1                53.692700            38.988223  \n",
       "VIC1                51.129443            37.578004  \n",
       "\n",
       "[5 rows x 146 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices_table_r = prices_r.groupby(['region','interval']).price.first().unstack()\n",
    "prices_table_r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### C3. Binding Constraint Results\n",
    "Similarly, producing the new marginal value results for the second iteration of economic dispatch simulation..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>interval</th>\n",
       "      <th>2021/02/15 06:00:00</th>\n",
       "      <th>2021/02/15 06:05:00</th>\n",
       "      <th>2021/02/15 06:10:00</th>\n",
       "      <th>2021/02/15 06:15:00</th>\n",
       "      <th>2021/02/15 06:20:00</th>\n",
       "      <th>2021/02/15 06:25:00</th>\n",
       "      <th>2021/02/15 06:30:00</th>\n",
       "      <th>2021/02/15 06:35:00</th>\n",
       "      <th>2021/02/15 06:40:00</th>\n",
       "      <th>2021/02/15 06:45:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2021/02/15 17:20:00</th>\n",
       "      <th>2021/02/15 17:25:00</th>\n",
       "      <th>2021/02/15 17:30:00</th>\n",
       "      <th>2021/02/15 17:35:00</th>\n",
       "      <th>2021/02/15 17:40:00</th>\n",
       "      <th>2021/02/15 17:45:00</th>\n",
       "      <th>2021/02/15 17:50:00</th>\n",
       "      <th>2021/02/15 17:55:00</th>\n",
       "      <th>2021/02/15 18:00:00</th>\n",
       "      <th>2021/02/15 18:05:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>set</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>#MWPS1PV1_E</th>\n",
       "      <td>-1032.7</td>\n",
       "      <td>-1032.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1032.0</td>\n",
       "      <td>-1032.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.6</td>\n",
       "      <td>-1038.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1039.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#MWPS2PV1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>-1037.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.4</td>\n",
       "      <td>...</td>\n",
       "      <td>-1038.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.8</td>\n",
       "      <td>-1039.4</td>\n",
       "      <td>-1039.5</td>\n",
       "      <td>-1055.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#MWPS4PV1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-1032.1</td>\n",
       "      <td>-1032.0</td>\n",
       "      <td>-1032.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1033.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1037.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1038.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1039.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1042.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#PPCCGT_D_E</th>\n",
       "      <td>14967.3</td>\n",
       "      <td>14967.9</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14967.5</td>\n",
       "      <td>14967.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>14962.0</td>\n",
       "      <td>14961.4</td>\n",
       "      <td>14961.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#TORRB1_D_E</th>\n",
       "      <td>14967.3</td>\n",
       "      <td>14967.9</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14967.5</td>\n",
       "      <td>14967.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#TORRB3_D_E</th>\n",
       "      <td>14967.3</td>\n",
       "      <td>14967.9</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14968.0</td>\n",
       "      <td>14967.5</td>\n",
       "      <td>14967.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14963.0</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#WARWSF1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#YATSF1_E</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$BARRON-1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$BLOWERNG</th>\n",
       "      <td>-1037.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>-1037.3</td>\n",
       "      <td>-1037.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>...</td>\n",
       "      <td>-1036.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.6</td>\n",
       "      <td>-1035.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1035.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1052.6</td>\n",
       "      <td>-1038.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$CALL_B_1</th>\n",
       "      <td>14961.1</td>\n",
       "      <td>14962.9</td>\n",
       "      <td>14963.6</td>\n",
       "      <td>14963.3</td>\n",
       "      <td>14963.6</td>\n",
       "      <td>14964.4</td>\n",
       "      <td>14962.3</td>\n",
       "      <td>14962.3</td>\n",
       "      <td>14962.3</td>\n",
       "      <td>14964.6</td>\n",
       "      <td>...</td>\n",
       "      <td>12.2</td>\n",
       "      <td>12.3</td>\n",
       "      <td>12.5</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.4</td>\n",
       "      <td>10.7</td>\n",
       "      <td>11.1</td>\n",
       "      <td>-2.5</td>\n",
       "      <td>-6.1</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>$YATSF1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F_T_AUFLS2_R6</th>\n",
       "      <td>-3.5</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-7.2</td>\n",
       "      <td>-5.1</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-3.6</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.1</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>-12.8</td>\n",
       "      <td>-8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N&gt;&gt;N-PKWL_94K_2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-51.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N&gt;&gt;N-PKWL_94K_3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NC_N_DARLSF1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N^^N_NIL_2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>N^^N_NIL_3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q&gt;NIL_COLNVSF1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Q&gt;NIL_YLMR</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S&gt;NIL_MHNW1_MHNW2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V&gt;&gt;V_NIL_14</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V&gt;V_NIL_17</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V_BANSF_BBD_80</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V_T_NIL_FCSPS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 146 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "interval           2021/02/15 06:00:00  2021/02/15 06:05:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1032.7              -1032.1   \n",
       "#MWPS2PV1_E                        0.0                  0.0   \n",
       "#MWPS4PV1_E                        0.0              -1032.1   \n",
       "#PPCCGT_D_E                    14967.3              14967.9   \n",
       "#TORRB1_D_E                    14967.3              14967.9   \n",
       "#TORRB3_D_E                    14967.3              14967.9   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1037.1                  0.0   \n",
       "$CALL_B_1                      14961.1              14962.9   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -3.5                 -8.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:10:00  2021/02/15 06:15:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0              -1032.0   \n",
       "#MWPS2PV1_E                        0.0                  0.0   \n",
       "#MWPS4PV1_E                    -1032.0              -1032.0   \n",
       "#PPCCGT_D_E                    14968.0              14968.0   \n",
       "#TORRB1_D_E                    14968.0              14968.0   \n",
       "#TORRB3_D_E                    14968.0              14968.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.5                  0.0   \n",
       "$CALL_B_1                      14963.6              14963.3   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:20:00  2021/02/15 06:25:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1032.5                  0.0   \n",
       "#MWPS2PV1_E                        0.0                  0.0   \n",
       "#MWPS4PV1_E                        0.0              -1033.0   \n",
       "#PPCCGT_D_E                    14967.5              14967.0   \n",
       "#TORRB1_D_E                    14967.5              14967.0   \n",
       "#TORRB3_D_E                    14967.5              14967.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                          0.0              -1035.5   \n",
       "$CALL_B_1                      14963.6              14964.4   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -3.5                 -7.2   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:30:00  2021/02/15 06:35:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0                  0.0   \n",
       "#MWPS2PV1_E                    -1035.4              -1037.0   \n",
       "#MWPS4PV1_E                        0.0                  0.0   \n",
       "#PPCCGT_D_E                    14964.6              14963.0   \n",
       "#TORRB1_D_E                    14964.6              14963.0   \n",
       "#TORRB3_D_E                    14964.6              14963.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1037.3              -1037.5   \n",
       "$CALL_B_1                      14962.3              14962.3   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -5.1                 -3.5   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 06:40:00  2021/02/15 06:45:00  ...  \\\n",
       "set                                                          ...   \n",
       "#MWPS1PV1_E                        0.0              -1035.4  ...   \n",
       "#MWPS2PV1_E                        0.0              -1035.4  ...   \n",
       "#MWPS4PV1_E                    -1037.0                  0.0  ...   \n",
       "#PPCCGT_D_E                    14963.0              14964.6  ...   \n",
       "#TORRB1_D_E                    14963.0              14964.6  ...   \n",
       "#TORRB3_D_E                    14963.0              14964.6  ...   \n",
       "#WARWSF1_E                         0.0                  0.0  ...   \n",
       "#YATSF1_E                          0.0                  0.0  ...   \n",
       "$BARRON-1                          0.0                  0.0  ...   \n",
       "$BLOWERNG                          0.0              -1035.5  ...   \n",
       "$CALL_B_1                      14962.3              14964.6  ...   \n",
       "$YATSF1                            0.0                  0.0  ...   \n",
       "F_T_AUFLS2_R6                     -3.6                 -3.5  ...   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0  ...   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0  ...   \n",
       "NC_N_DARLSF1                       0.0                  0.0  ...   \n",
       "N^^N_NIL_2                         0.0                  0.0  ...   \n",
       "N^^N_NIL_3                         0.0                  0.0  ...   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0  ...   \n",
       "Q>NIL_YLMR                         0.0                  0.0  ...   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0  ...   \n",
       "V>>V_NIL_14                        0.0                  0.0  ...   \n",
       "V>V_NIL_17                         0.0                  0.0  ...   \n",
       "V_BANSF_BBD_80                     0.0                  0.0  ...   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0  ...   \n",
       "\n",
       "interval           2021/02/15 17:20:00  2021/02/15 17:25:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                        0.0              -1038.6   \n",
       "#MWPS2PV1_E                    -1038.0                  0.0   \n",
       "#MWPS4PV1_E                        0.0              -1038.6   \n",
       "#PPCCGT_D_E                    14962.0              14961.4   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1036.1                  0.0   \n",
       "$CALL_B_1                         12.2                 12.3   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.0   \n",
       "N>>N-PKWL_94K_2                  -51.9                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 17:30:00  2021/02/15 17:35:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1038.2                  0.0   \n",
       "#MWPS2PV1_E                        0.0                  0.0   \n",
       "#MWPS4PV1_E                        0.0                  0.0   \n",
       "#PPCCGT_D_E                    14961.8                  0.0   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.6              -1035.5   \n",
       "$CALL_B_1                         12.5                 12.0   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 17:40:00  2021/02/15 17:45:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1038.8                  0.0   \n",
       "#MWPS2PV1_E                    -1038.8              -1039.4   \n",
       "#MWPS4PV1_E                    -1038.8                  0.0   \n",
       "#PPCCGT_D_E                        0.0                  0.0   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                          0.0                  0.0   \n",
       "$CALL_B_1                         11.4                 10.7   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.1                 -8.0   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 17:50:00  2021/02/15 17:55:00  \\\n",
       "set                                                           \n",
       "#MWPS1PV1_E                    -1039.5                  0.0   \n",
       "#MWPS2PV1_E                    -1039.5              -1055.4   \n",
       "#MWPS4PV1_E                    -1039.5                  0.0   \n",
       "#PPCCGT_D_E                        0.0                  0.0   \n",
       "#TORRB1_D_E                        0.0                  0.0   \n",
       "#TORRB3_D_E                        0.0                  0.0   \n",
       "#WARWSF1_E                         0.0                  0.0   \n",
       "#YATSF1_E                          0.0                  0.0   \n",
       "$BARRON-1                          0.0                  0.0   \n",
       "$BLOWERNG                      -1035.6                  0.0   \n",
       "$CALL_B_1                         11.1                 -2.5   \n",
       "$YATSF1                            0.0                  0.0   \n",
       "F_T_AUFLS2_R6                     -8.0                 -8.5   \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0   \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0   \n",
       "NC_N_DARLSF1                       0.0                  0.0   \n",
       "N^^N_NIL_2                         0.0                  0.0   \n",
       "N^^N_NIL_3                         0.0                  0.0   \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0   \n",
       "Q>NIL_YLMR                         0.0                  0.0   \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0   \n",
       "V>>V_NIL_14                        0.0                  0.0   \n",
       "V>V_NIL_17                         0.0                  0.0   \n",
       "V_BANSF_BBD_80                     0.0                  0.0   \n",
       "V_T_NIL_FCSPS                      0.0                  0.0   \n",
       "\n",
       "interval           2021/02/15 18:00:00  2021/02/15 18:05:00  \n",
       "set                                                          \n",
       "#MWPS1PV1_E                        0.0                  0.0  \n",
       "#MWPS2PV1_E                        0.0                  0.0  \n",
       "#MWPS4PV1_E                        0.0              -1042.5  \n",
       "#PPCCGT_D_E                        0.0                  0.0  \n",
       "#TORRB1_D_E                        0.0                  0.0  \n",
       "#TORRB3_D_E                        0.0                  0.0  \n",
       "#WARWSF1_E                         0.0                  0.0  \n",
       "#YATSF1_E                          0.0                  0.0  \n",
       "$BARRON-1                          0.0                  0.0  \n",
       "$BLOWERNG                      -1052.6              -1038.3  \n",
       "$CALL_B_1                         -6.1                  8.1  \n",
       "$YATSF1                            0.0                  0.0  \n",
       "F_T_AUFLS2_R6                    -12.8                 -8.3  \n",
       "N>>N-PKWL_94K_2                    0.0                  0.0  \n",
       "N>>N-PKWL_94K_3                    0.0                  0.0  \n",
       "NC_N_DARLSF1                       0.0                  0.0  \n",
       "N^^N_NIL_2                         0.0                  0.0  \n",
       "N^^N_NIL_3                         0.0                  0.0  \n",
       "Q>NIL_COLNVSF1                     0.0                  0.0  \n",
       "Q>NIL_YLMR                         0.0                  0.0  \n",
       "S>NIL_MHNW1_MHNW2                  0.0                  0.0  \n",
       "V>>V_NIL_14                        0.0                  0.0  \n",
       "V>V_NIL_17                         0.0                  0.0  \n",
       "V_BANSF_BBD_80                     0.0                  0.0  \n",
       "V_T_NIL_FCSPS                      0.0                  0.0  \n",
       "\n",
       "[25 rows x 146 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mv_table_r = marginal_values_r.groupby(['set','interval']).marginal_value.first().unstack().fillna(0).round(1)\n",
    "mv_table_r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "### C4. Unit Dispatch Results\n",
    "Again, for unit dispatch..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>interval</th>\n",
       "      <th>2021/02/15 06:00:00</th>\n",
       "      <th>2021/02/15 06:05:00</th>\n",
       "      <th>2021/02/15 06:10:00</th>\n",
       "      <th>2021/02/15 06:15:00</th>\n",
       "      <th>2021/02/15 06:20:00</th>\n",
       "      <th>2021/02/15 06:25:00</th>\n",
       "      <th>2021/02/15 06:30:00</th>\n",
       "      <th>2021/02/15 06:35:00</th>\n",
       "      <th>2021/02/15 06:40:00</th>\n",
       "      <th>2021/02/15 06:45:00</th>\n",
       "      <th>...</th>\n",
       "      <th>2021/02/15 17:20:00</th>\n",
       "      <th>2021/02/15 17:25:00</th>\n",
       "      <th>2021/02/15 17:30:00</th>\n",
       "      <th>2021/02/15 17:35:00</th>\n",
       "      <th>2021/02/15 17:40:00</th>\n",
       "      <th>2021/02/15 17:45:00</th>\n",
       "      <th>2021/02/15 17:50:00</th>\n",
       "      <th>2021/02/15 17:55:00</th>\n",
       "      <th>2021/02/15 18:00:00</th>\n",
       "      <th>2021/02/15 18:05:00</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unit</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AGLHAL</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGLSOM</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ANGAST1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARWF1</th>\n",
       "      <td>112.4</td>\n",
       "      <td>105.9</td>\n",
       "      <td>100.1</td>\n",
       "      <td>104.7</td>\n",
       "      <td>103.6</td>\n",
       "      <td>111.4</td>\n",
       "      <td>99.2</td>\n",
       "      <td>95.0</td>\n",
       "      <td>89.7</td>\n",
       "      <td>94.1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BALBG1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YENDWF1</th>\n",
       "      <td>61.4</td>\n",
       "      <td>65.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.6</td>\n",
       "      <td>47.3</td>\n",
       "      <td>52.8</td>\n",
       "      <td>55.6</td>\n",
       "      <td>58.3</td>\n",
       "      <td>55.5</td>\n",
       "      <td>...</td>\n",
       "      <td>18.6</td>\n",
       "      <td>18.9</td>\n",
       "      <td>17.6</td>\n",
       "      <td>19.3</td>\n",
       "      <td>17.8</td>\n",
       "      <td>17.9</td>\n",
       "      <td>17.6</td>\n",
       "      <td>18.8</td>\n",
       "      <td>18.1</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS1</th>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>...</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS2</th>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>...</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS3</th>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>...</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YWPS4</th>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>390.0</td>\n",
       "      <td>...</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>380.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>334 rows × 146 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "interval  2021/02/15 06:00:00  2021/02/15 06:05:00  2021/02/15 06:10:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                   112.4                105.9                100.1   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  61.4                 65.8                 61.0   \n",
       "YWPS1                   380.0                380.0                380.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   390.0                390.0                390.0   \n",
       "\n",
       "interval  2021/02/15 06:15:00  2021/02/15 06:20:00  2021/02/15 06:25:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                   104.7                103.6                111.4   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  52.0                 52.6                 47.3   \n",
       "YWPS1                   380.0                380.0                380.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   390.0                390.0                390.0   \n",
       "\n",
       "interval  2021/02/15 06:30:00  2021/02/15 06:35:00  2021/02/15 06:40:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                    99.2                 95.0                 89.7   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  52.8                 55.6                 58.3   \n",
       "YWPS1                   380.0                380.0                380.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   390.0                390.0                390.0   \n",
       "\n",
       "interval  2021/02/15 06:45:00  ...  2021/02/15 17:20:00  2021/02/15 17:25:00  \\\n",
       "unit                           ...                                             \n",
       "AGLHAL                    0.0  ...                  0.0                  0.0   \n",
       "AGLSOM                    0.0  ...                  0.0                  0.0   \n",
       "ANGAST1                   0.0  ...                  0.0                  0.0   \n",
       "ARWF1                    94.1  ...                  0.0                  0.0   \n",
       "BALBG1                    0.0  ...                  0.0                  0.0   \n",
       "...                       ...  ...                  ...                  ...   \n",
       "YENDWF1                  55.5  ...                 18.6                 18.9   \n",
       "YWPS1                   380.0  ...                370.0                370.0   \n",
       "YWPS2                   350.0  ...                350.0                350.0   \n",
       "YWPS3                   375.0  ...                375.0                375.0   \n",
       "YWPS4                   390.0  ...                380.0                380.0   \n",
       "\n",
       "interval  2021/02/15 17:30:00  2021/02/15 17:35:00  2021/02/15 17:40:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                     0.0                  0.0                  0.0   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  17.6                 19.3                 17.8   \n",
       "YWPS1                   370.0                370.0                370.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   380.0                380.0                380.0   \n",
       "\n",
       "interval  2021/02/15 17:45:00  2021/02/15 17:50:00  2021/02/15 17:55:00  \\\n",
       "unit                                                                      \n",
       "AGLHAL                    0.0                  0.0                  0.0   \n",
       "AGLSOM                    0.0                  0.0                  0.0   \n",
       "ANGAST1                   0.0                  0.0                  0.0   \n",
       "ARWF1                     0.0                  0.0                  0.0   \n",
       "BALBG1                    0.0                  0.0                  0.0   \n",
       "...                       ...                  ...                  ...   \n",
       "YENDWF1                  17.9                 17.6                 18.8   \n",
       "YWPS1                   370.0                370.0                370.0   \n",
       "YWPS2                   350.0                350.0                350.0   \n",
       "YWPS3                   375.0                375.0                375.0   \n",
       "YWPS4                   380.0                380.0                380.0   \n",
       "\n",
       "interval  2021/02/15 18:00:00  2021/02/15 18:05:00  \n",
       "unit                                                \n",
       "AGLHAL                    0.0                  0.0  \n",
       "AGLSOM                    0.0                  0.0  \n",
       "ANGAST1                   0.0                  0.0  \n",
       "ARWF1                     0.0                  0.0  \n",
       "BALBG1                    0.0                  0.0  \n",
       "...                       ...                  ...  \n",
       "YENDWF1                  18.1                 16.5  \n",
       "YWPS1                   370.0                375.0  \n",
       "YWPS2                   350.0                350.0  \n",
       "YWPS3                   375.0                375.0  \n",
       "YWPS4                   380.0                380.0  \n",
       "\n",
       "[334 rows x 146 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unit_dispatch_r = unit_dispatch_r[unit_dispatch_r['service'] == 'energy']\n",
    "\n",
    "units_table_r = unit_dispatch_r.groupby(['unit','interval']).dispatch.first().unstack().round(1)\n",
    "units_table_r"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Section D - Results & Discussion\n",
    "### D1. Price Variations\n",
    "We can merge the previous results from Section B and C to compare the difference in prices for each region across the timeseries.\n",
    "\n",
    "The first figure shows the cleared price for each interval in NSW with all constraints (blue), and with the Line 94T constraints removed.\n",
    "\n",
    "The latter figure then shows the difference in price per region due to the removal of constraints. Here all values are either zero or negative, showing a reduction in the price by removing the constraints compared to the base case with all constraints considered."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "prices_all = pd.merge(left=prices,right=prices_r,on=['interval','region'])\n",
    "prices_all.rename(columns = {'price_x':'Price before','price_y':'Price after'},inplace=True)\n",
    "prices_all['diff'] = prices_all['Price after'] - prices_all['Price before']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "timeaxis = []\n",
    "for item in prices_r['interval'].unique():\n",
    "    timeaxis += [datetime.strptime(item, \"%Y/%m/%d %H:%M:%S\").time()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "marker": {
          "size": 8,
          "symbol": "circle"
         },
         "mode": "lines+markers",
         "name": "NSW price",
         "type": "scatter",
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        "title": {
         "text": "Figure 1: NSW Pool Price - Impact of 'N>>N-NIL_94T_947' & 'N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>"
        },
        "xaxis": {
         "title": {
          "text": "Time"
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          "text": "Price ($/MWh)"
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($/MWh)\"}},\"title\":{\"text\":\"Figure 1: NSW Pool Price - Impact of 'N>>N-NIL_94T_947' & 'N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>\"}},                        {\"responsive\": true}                    ).then(function(){\n",
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   "source": [
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=timeaxis, y=prices[prices['region'] == 'NSW1']['price'], name='NSW price', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig.add_trace(go.Scatter(x=timeaxis, y=prices_r[prices_r['region'] == 'NSW1']['price'], name='NSW price [r]', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig.update_xaxes(title=\"Time\")\n",
    "fig.update_yaxes(title=\"Price ($/MWh)\")\n",
    "fig.update_layout(title=\"Figure 1: NSW Pool Price - Impact of 'N>>N-NIL_94T_947' & 'N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>\",\n",
    "                 template=\"plotly_white\")\n",
    "fig.show()"
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  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
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           "zerolinecolor": "#EBF0F8",
           "zerolinewidth": 2
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         }
        },
        "title": {
         "text": "Figure 2: All Region Change in Pool Prices due to 'N>>N-NIL_94T_947' & 'N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>"
        },
        "xaxis": {
         "title": {
          "text": "Time"
         }
        },
        "yaxis": {
         "title": {
          "text": "Price ($/MWh)"
         }
        }
       }
      },
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     },
     "metadata": {},
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   ],
   "source": [
    "fig2 = go.Figure()\n",
    "fig2.add_trace(go.Scatter(x=timeaxis, y=prices_all[prices_all['region'] == 'NSW1']['diff'], name='NSW Δ Price', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig2.add_trace(go.Scatter(x=timeaxis, y=prices_all[prices_all['region'] == 'QLD1']['diff'], name='QLD Δ Price', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig2.add_trace(go.Scatter(x=timeaxis, y=prices_all[prices_all['region'] == 'VIC1']['diff'], name='VIC Δ Price', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig2.add_trace(go.Scatter(x=timeaxis, y=prices_all[prices_all['region'] == 'SA1']['diff'], name='SA Δ Price', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig2.add_trace(go.Scatter(x=timeaxis, y=prices_all[prices_all['region'] == 'TAS1']['diff'], name='TAS Δ Price', mode='lines+markers',\n",
    "                         marker_size=8, marker_symbol='circle'))\n",
    "fig2.update_xaxes(title=\"Time\")\n",
    "fig2.update_yaxes(title=\"Price ($/MWh)\")\n",
    "fig2.update_layout(title=\"Figure 2: All Region Change in Pool Prices due to 'N>>N-NIL_94T_947' & 'N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>\",\n",
    "                  template=\"plotly_white\")\n",
    "fig2.show()"
   ]
  },
  {
   "attachments": {
    "image-4.png": {
     "image/png": 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7V1TtJ5AOBHKZQFab5jDzFdR5JNueLU/0S7rS7D/YKsr8sehU7gaWtiMMWtWRzaK87S9scijMs7grLd8tlbcWtf7t6d6WbLEKJ64ttsuJEz6TDX5h3PzPHyfj4jeiYUY4KI/SmOag56llPQU9xx10vagVrNJoS5dpDnse0G/0g8oSVj4/C3lVTrDldiN0qDr5Ex18KqY5aoufPLnTudLM+aq0T7F1VX6Gm9nz1lN5BU5sXRWvN+L82QiJw/z8bESfJBsweStnSUwzX0PeFTKo15/i22PTbZr52txexJZz8YwkbxPmlXlhCoX25H48qh1GfR82sfC/1on5tjjtpMDTc+UVsKi+KaqvSTbRkQ+HEs8QixVbsXtDrPqpHgomrhd0U1ZFD+LxA/GqMBFXQbvzE06EFzfWxLP4Yrzhx5vE4U5BOyVksylvx0/VNKu22XSZZq67oHMkxBZ0vsEhDqyS++2ofivq+6iJc0nGXf+4IvLwm+lk106lXQbt7Al7xjhszhHGKcowcxn8z02X1DCLfi5o+3hUPeF7EAABdQI5Y5r9Axv/dyomR77LHvS6GL8BljteHgiqValcrFb8hx4FVVs6TDNfR96eJp61jnpuKIiBbGzEoSjy9loxgPHkj59tjNoaq1peW1aao8oTNfEo7UpzabSVrJuIWmkOM8epmOawtGJSLtj4V079kyKXVpr9RkN+Xl20T3nlIcwE+/u7MMMRZpr577J2xaFBUXqX+xa5P5H1FHYAUdBkV7U/UB/y9u+g4cO1eLcNr1gefdQR8ZXvZPn4b/alMjmPis8/eQ57Vl7ORx5zZNMbdThT1Dgjbhywznrf8UixHR7+g6WiyhZkmqP0EHTAl2yCxTXlV2QF3TQS6YJMs//d1+Lgt6ib2WGPF0SNqekyzUH8/duLZfMZVl/JTptWXeWV8y7JSrO/fzFpmsXuibBnjMPOCwg6eM+/JZtPNfe/vSBq16Hcz4st6/4TvmXe6egro9o2vgeBXCOQU6ZZbLlMtrVMnoDLz0jL29ZUTDMLST5UhZ81kjs87hBVnhNL1hGW5JlmIXD/q6H47/KgybG3Ojs/thJzRrxNiJN45bvBcscvDtiQJ1X+wTrKmKfS8dv0THNYx1ES0yxPNsQ2RLFi2Ob8Fgmv+xLPsZVEW5k2zXz9oDMHxE2XINMc1D5lLfOka8TgHt4EhW/oLFq2ksQhL/KrWXj7vPgETUQy9UyzSvsU22j5UCT/qptcp6w9XmHm1/EEGQ45bdDznLK5FGlLapr590HPFKay0sy6OPmEBgmyDXpVjF/XXA5Rx6yJMZNeSjjoTGXnBuepyzTL8bB2Hxn/gnfgFn/E2JSqaQ47JEh1QiMz4P79jps7eT/99rsfEt4BHNV/B10v7PGfZHrg3/DHv3PCnz9zCto54U8X9ky+3J+I35TUNEeNqVGmWeZ+oG9K/gozTifrSYwTYjeOGD8yYZpL8kxzOk0z661D21bxA8Pk7dnyjdlkzxgne+WU2BXiX2EWr+yUNcnnmQQ9Ny33/+IZZlVdpDJ3Uu0XkA4EQCCRQE6ZZvmutIyBO6Xhd/XwzEjUM3Dy5Cmqk0p2urPK5JOvlewaKttNw+6Kc97+Z6GCnjsNajD+rejyCZn+VUH/pCSVCUlU2qjTs8VzxVyGZKd4ys/HRW2BFDxU05XENCebxAsmOrSVrDM0sdIcdH359GyZHf+9SuVK8ddb8SqhrNewSaHczoIm6WEaizo9m19tIm56RdWxKme/KQtrnzwp40+yVQf+Pui1J2GxhB2C5D8YSqXfCjNJQX1rKqY5KPaoPoJ/E6QNlQOuolaSo74PYy3rRU4Tddp1sj7Hf45DSSY6yfpIkZ8KN/+1S6IHVe2qpkt2kJ1/XhClqZKOqVGmOajOVNpb2HgRteMgqt+K+l5FY6Udd3WuNCe7ESXmNFHPGIeNu/IbFcLat8yL+72g56b984swxkG6iJqPqtQX0oAACCQnkDOmme8C3zfq7/FDcPxYZLMnr0ZwOrE1RpwCq7rSzL8VKwnye2bZpF/e5hzq3umySH0m6wiFCVA9jdo/KZe3p3Egcj5sdsUrTkSQQe815u/kbdvJDkTjtFHbvFLt+Dm9Te9p9ldo1MQj2XNfcrnEO4Lv6d81bpZKq61k4jNhmvnOPD9bKp5Z5ImA/5EFWVvijvviZd94z3/6D9jzv4fb/45o1rt8qqx8syyIhcp7mvl3UXWsyjmV9hnZcaSYINnJwfLEVWUSH2aS/Kz8/UHU9uygIkUZHP6NHD/XefP8RtT/xoLImw5Rpjjq+7AqkPXC487pTY4v9ox50G/D+oqgAw1TrH4vuTi74p05nye861zEJ96GkKpxLqkeSlKGKOZRZoN/H6WpZKY52ZhqwjRz3eQ3Ps5bUfWfLp7q2FSafk1cS2hKPlMhaB4Rpm2dppnLI2tbsOpacIn3Jgv+RD1jzGn880MuT98brgi8iRqmR/kZ+qCdj1E7A6J0HKVhnW0LeYFALhHIOtNcksqRBzL/3Xx5JTTK0JXk2vgNCIBAIoGSmg1wBAEQAAEQAAEQAAEQAIFMEMgJ0yzfGfafYCxMc0nfa5mJSsM1QSCbCcA0Z3Pt2RU73xBdEHt/edAnr3r086DpKA2PN2EfsaKVjusiTzcJ8I6iok1bAgun8ky/m1RQKhAAARAwTyAnTDNjFYc7sDk+tn4dj/Tmrdvi29CiniczXzW4Igi4SQCm2c16zUSpkj3/r7KVPB0xJ3t2EruZ0kHc7TyTbdXFNly36x6lAwEQsItAzphm//OJXA3iebIOl7aKP9NiV/UgGhBwjwBMs3t1ihKBAAiAAAiAAAiAgMsEcsY0u1yJKBsIgAAIgAAIgAAIgAAIgAAIgEB6CMA0p4crcgUBEAABEAABEAABEAABEAABEHCAQNaZZvl5saDnw+Rn3FSeaROvVcCzQWbUzM9nrVi1lj6dOc7MBS2/itBrsteGWV4EhAcCIAACIAACIAACIAACThPIStPM7wIOew5ZnKZ648CRZJtpZoNe0O58qlenVlaKig3et9/9QFdf3rrE8TODJctX04SRA5Xy0HFNpQtlKBFMc4bA47IgAAIgAAIgAAIgAAIgoEggK02zyqocr0jbZJpnzPqYBtz7OGXzinbbToOoWpXKNO3JIYryKn2yTFyz9FGr5wDTrM4KKUEABEAABEAABEAABEAgEwSy3jTzdt+jjjws9r+aNHnaTOpzfQfq3ukyCjPNvBLdfcBDtHDpSu/07OMa1qG58xfHzSy/E/G+UX/3vufPWc1OpoeH9KK86lWIr1W1aiWqE7vW9NfeI359VdvWZ9GwAdd5adkYj5n0kvcaK/k7/vvgERNo+46d8TrmreUcyz0jJ9Gbsz/1/l6/bi0aflcPanJiQ3ruX7Poib+/Qht/KvLy+m2LU2nU0N4JGhG/f//jL728uTxjHujr/Z5XdP/91kfe7/nvPa5tF18hZjZ84+HTL5bGOYjvufyD7nsi/iouvvEwbsStcWYiAHHjgvNi5h9//pXHceoTQ+iFV9+h2R8VxmOXGYnXZ4it9cli8b9qI+hmSdD1OcaoOqxetbLHndn271FAX329KrBOwziymed6Fu/9FuaXd0FwPfHvpr38drxeZP6DR0yMX4vrleNQuRGUiQ4C1wQBEAABEAABEAABEACBXCfghGnmZ2T5w+9fvqvftZ5pDDPN3fo/6Jk7NsMnHlcvbmzECnCr9n28vAb1+pP3/7PZzW98nLedWJg4/29ff3a4l/aSjoM8E1bwhwu8Lch8HTZDvCW7x6CHPZPFBvPkExp4r7jqN2SMZ5j4HdFHH3UEPfDoM/TDxp+95335vdL8GTagG61Z94P3b74ZIH/E70U8332/0TNsbLjve+Rpz4Sf3/I0emfO5961RRnFc+EdLj3Xy45vALCxnv3SaBJ8OM5qMWPJZpJvCox75lUa/dR0L887bu4U22J+hLfNnPPiMlepXImOPLyGtwrNades20AXtTqDHpvwkmfMxbWDTDPHEBRL2DVlBkHXL0kdBtXpnE8WhnLkberMWNykEXXBNw0WLvmv9x2XiRlMf222V8/83UefLoxzlOsGpjnXu2KUHwRAAARAAARAAARAwFYCTphmNmVsXOVnhcNMM/9dGESuFPkgsLzqVemqHkOL1ZXY5i0Mn1hdlH+7eNk3nhkSJooz4WuxyZzxzPC44Za3Z7MxllefxYV5FVaYV/795W3OiRnvC7zVbvkjjLX/UC3xWzZpfANBrIKyiWMDLMfF+clGVhhVZtTq7Hy6/k+XelxFHv4t736evPo98slp8ZVmEW8y0ywY+WMJu6bfNMv1ySvlqdShKLvQj/hvjnfStNfjq+dBHJn/ETUPpef+NphaX9nPu2nDNw0Ef7+QOE9xE0FcD9uzbe0aERcIgAAIgAAIgAAIgAAI7CfgjGn2n6RdGtPMxvCmbu3jGmEzzabJv0qqwzTzRR4ZdlOCHnkVmj+8rfut9z6JbyP2m2OxyloS0yybX3+52HjyFusZs+Z6pp7Nd9GmLRR0uJqfszDdvE35nv5dadyzr3rb5pOZ5rBYVE2z/HthmlXr0F/2VEyz2GbNNyN4tZ53DPAhacI0ix0EonKbnHhMfJs7TDO6YBAAARAAARAAARAAARDIDgI5Z5qFoWFTx89Bi+dO5e3Z/Bwwb5c9u1lj+mj+Iqpb+3DPDCUzzbxdOWh7tljdFQZbXHdAz6vi27N5a3DXgkuIV6uLNm8l/o7jbHHaSd5W7jv/+hRt3ba92Gua/FvN+RllXukM25494u6esWewWxTbui6Xi40gb8vmsvtXWsWq8u8vPNv7ns19MtN84blnxJ/xLolp5iYUdE25aQXdHOHt2ap1mMw0iy3Y/m3uguPqtevjdc4xiZsXMv/eXdvH6nQLzYs9881b58VNBTb1zZs2im+dx/bs7OgwESUIgAAIgAAIgAAIgEDuEcg508xGZ8CwJ+IHYPEWZF4lFKaOVyofGf+Cty2XP7z1l59vZrOZzDSzgQw6CKz/jQXetmrOt/cdj8QP5uLnh/0HeYnnodk0i4OmRAzyQVJCpvz7W4aOjccqb3P2H2DVsf3v4s9E+42m3zQzD/74DzoTK6v8nVhV9eflP2jt/tuu91aoS2qag64ZZZpTqcNkppnrNBlHjkP83m965d9xOr4xIl6zJZ5/FvXNK/EwzbnX+aLEIAACIAACIAACIAAC2UEgK02zzvc0Z0c1IUoQAAEQAAEQAAEQAAEQAAEQAIFMEMhK0yxA+Z9j5r+L52D53yrvac4EdFwTBEAABEAABEAABEAABEAABEAgOwhknWnODqyIEgRAAARAAARAAARAAARAAARAwAUCMM0u1CLKAAIgAAIgAAIgAAIgAAIgAAIgkBYCMM1pwYpMQQAEQAAEQAAEQAAEQAAEQAAEXCAA0+xCLaIMIAACIAACIAACIAACIAACIAACaSEA05wWrMgUBEAABEAABEAABEAABEAABEDABQIwzS7UIsoAAiAAAiAAAiAAAiAAAiAAAiCQFgIwzWnBikxBAARAAARAAARAAARAAARAAARcIADT7EItogwgAAIgAAIgAAIgAAIgAAIgAAJpIQDTnBasyBQEQAAEQAAEQAAEQAAEQAAEQMAFAjDNLtQiygACIAACIAACIAACIAACIAACIJAWAjDNacGKTEEABEAABEAABEAABEAABEAABFwgANPsQi2iDCAAAiAAAiAAAiAAAiAAAiAAAmkhANOcFqzIFARAAARAAARAAARAAARAAARAwAUCMM0u1CLKAAIgAAIgAAIgAAIgAAIgAAIgkBYCMM1pwYpMQQAEQAAEQAAEQAAEQAAEQAAEXCAA0+xCLaIMIAACIAACIAACIAACIAACIAACaSEA05wWrMgUBEAABEAABEAABEAABEAABEDABQIwzS7UIsoAAiAAAiAAAiAAAiAAAiAAAiCQFgIwzWnBiva5o+YAACAASURBVExBAARAAARAAARAAARAAARAAARcIADT7EItogwgAAIgAAIgAAIgAAIgAAIgAAJpIQDTnBasyBQEQAAEQAAEQAAEQAAEQAAEQMAFAjDNLtQiygACIAACIAACIAACIAACIAACIJAWAjDNacGKTEEABEAABEAABEAABEAABEAABFwgANPsQi2iDCAAAiAAAiAAAiAAAiAAAiAAAmkhANOcFqzIFARAAARAAARAAARAAARAAARAwAUCMM0u1CLKAAIgAAIgAAIgAAIgAAIgAAIgkBYCMM1pwYpMQQAEQAAEQAAEQAAEQAAEQAAEXCAA0+xCLaIMIAACIAACIAACIAACIAACIAACaSEA05wWrMgUBEAABEAABEAABEAABEAABEDABQIwzS7UIsoAAiAAAiAAAiAAAiAAAiAAAiCQFgIwzWnBikxBAARAAARAAARAAARAAARAAARcIADT7EItogwgAAIgAAIgAAIgAAIgAAIgAAJpIQDTnBasyBQEQAAEQAAEQAAEQAAEQAAEQMAFAjDNLtSiVIaNRb9SzbyDtZRKV1625cNwEJOaRGzjpCseaMBs/YO3Gm8bOaHNqdWdLk668rFRS4jJrJZs5a1GAalAwD4CMM321UmpInJ5wHW5bLYObrqY25YPeKt1M7rqDbzVeNvICRpQqztdnHTlY6OWEJNZLdnKW40CUoGAfQRgmu2rk1JF5PKA63LZbB3cdDG3LR/wVutmdNUbeKvxtpETNKBWd7o46crHRi0hJrNaspW3GgWkAgH7CMA021cnpYrI5QHX5bLZOrjpYm5bPuCt1s3oqjfwVuNtIydoQK3udHHSlY+NWkJMZrVkK281CkgFAvYRgGm2r05KFZHLA67LZbN1cNPF3LZ8wFutm9FVb+CtxttGTtCAWt3p4qQrHxu1hJjMaslW3moUkAoE7CMA02xfnZQqIpcHXJfLZuvgpou5bfmAt1o3o6vewFuNt42coAG1utPFSVc+NmoJMZnVkq281SggFQjYRwCm2b46KVVELg+4LpfN1sFNF3Pb8gFvtW5GV72BtxpvGzlBA2p1p4uTrnxs1BJiMqslW3mrUUAqELCPAEyzfXVSqohcHnBdLputg5su5rblA95q3YyuegNvNd42coIG1OpOFydd+dioJcRkVku28lajgFQgYB8BmGb76qRUEbk84LpcNlsHN13MbcsHvNW6GV31Bt5qvG3kBA2o1Z0uTrrysVFLiMmslmzlrUYBqUDAPgIwzfbVSakicnnAdblstg5uupjblg94q3UzuuoNvNV428gJGlCrO12cdOVjo5YQk1kt2cpbjQJSgYB9BGCa7auTUkXk8oDrctlsHdx0MbctH/BW62Z01Rt4q/G2kRM0oFZ3ujjpysdGLSEms1qylbcaBfdSbfyJaNnyvbRtO9EJx5WhenXKaCtk4/O6eHld1Ko5jRraO54v//2URg1p2pNDvL8NHjGRZsyaS9t37KSaNfKoY/vfUbWqlem+R56mu/peQ1df3tpL163/gzR3/mJ68sH+dM6ZTby/Fdw4lBYuXUmL3p1c6rg5rxWr1tKnM8eVOi+TGcA0m6Rt4FouD7gul83WwU0Xc9vyAW+1zkhXvYG3Gm8bOUEDanWni5OufGzUEmIyqyVbeatRcCvVy6/voVdn7k0o1O9aHURXtS+rpaDCNHNmstGVTfNz/5rlmWM20c2bNqIly1fTicfVo4J259MlHQclGO7mbbp7xrpLQRsa0PMqL0a/AS9N4CMen+pdf8LIgaXJxvhvYZqNI0/vBV0ecF0um62Dmy7mtuUD3mr9kK56A2813jZyggbU6k4XJ1352KglxGRWS7byVqPgTqrPv9xHYyfsDixQwf+VpQvPO6jUhRWGlleC5ZVl2eiyUZ08bWaCqRYXbtW+D1WpXJFmPDOcFixZSVf1GOqtRB95eA1vlfqDeQvoxoEjE0x0qYPOwgxgmrOw0pKF7PKA63LZbB3cdDG3LR/wVuv4dNUbeKvxtpETNKBWd7o46crHRi0hJrNaspW3GgW7U73+n720K9gHFwt8zty99OPP+wILVKkSxUyz+mpzuzbBBluY46OOPIzenP0pjbi7J7Vt3SJhdVisNLMZ7nFtu/hWbA6s35Ax3u8+fGUszXh7rrcizavMbLJ5O/a4Z16l0U9NDzTcvNV689Zt1Dy/EU1/7T2qVLEC9e9R4OUvzDbHM2bSS/TDxp+9Ldn+rd5s6P/91ke08aeihN/PmPUxDR/7j/jf27Y+i4YNuC5j4oBpzhj69FzY5QHX5bLZOrjpYm5bPuCt1v/oqjfwVuNtIydoQK3udHHSlY+NWkJMZrVkK281Cnanuum2XbQ99myy0of9sqbHlx/7a3lio+3/CNM8YnAPb6s1G+PZL40utqWan2lmY8sfXpEeN+JWyqteJcEUT39tNi1d8S3dcXMnb3WZt3tPmva694xz0PPMwgCf1exkb7v3tJff9rZ2v/7scFq99gcvDzbSR9Q81DPWbHpl0yzMfP26tej8lqfRd99vpH7dr/Bi5LJwnDd1a0+Ll33jGfc+13eg7p0uU0KvOxFMs26iGc7P5QHX5bLZOrjpYm5bPuCt1lHpqjfwVuNtIydoQK3udHHSlY+NWkJMZrVkK281Cnan0rXSHNsRTb87X99KM2+lFtuw+WAv8QyzOAiMqa5eu56GPjzFM8FsdPm5YrElm1eXecX39CbHeweKsRkXfxPbt/01E7RqLLaBc1o2zf4DyuTfiEPHpj4xhJqc2DCevVjd9l9Pfs7atEpgmk0TT/P1XB5wXS6brYObLua25QPeah2RrnoDbzXeNnKCBtTqThcnXfnYqCXEZFZLtvJWo+BOKpPPNLM5Ltq0lVpf2c8DyCu+4hln/juvKouPODxMrB7z4V/H1q/jnZAtTtJmc1u1aiXPYHe49NzArdF+0yxWs3mFWphmv9GVfyP+HWaa+boXtTojHne9OkfETh6vlRGBwDRnBHv6LurygOty2Wwd3HQxty0f8Fbrg3TVG3ir8baREzSgVne6OOnKx0YtISazWtLFe+OydbRuyWqqWqk8NbzwdLVCIFUCAROnZ8sHgInVZg5C/J3NKX/45GzeAs3PMIuVZv67WPHlf/PWajamcj7iOWl/1QZtz+Y0s54fFVvB/m/gAWKyaRYryvL27A6Xtopd/whve7Z4RjqvWlWa+9kiuuKy8xNWpE1KDabZJG0D13J5wHW5bLoGN5356MxLV93pysfGstkYE3irddouc3K5bGhz0Dc0EK6BrRs309ejJlCDr1+MJyoqfyTtufZ2OubiZmriQao4AX5P89Kv97+nudHx+t/TLJtmviifiM0Ha4m/y4dt8fe8Zfqe/l3jq8/CvIrnoTmNOMiL/82HhMkr1aJgwgBzfmzEgw4CS7bSzPn43x895oG+njHmg8D4ALFVa9Z7l2Nj/cTwW7DSjHalh4DLExyXy2bjwG1jTNCAWj+hi5OufGzUEmIyqyXwBm9oILs08MVdo6jBsunFgt5RpiqVu3cS1TyhtlqBkMppAv7t2S4XFivNjtWuy5Ncl8uGyYRaQ4QGzHICb7O8bewHoAGzGgBvs7zR5sJ5/3LlOaFffpPfmZreeYNaZSGV0wRgmp2uXrcL5/KA63LZbBy4bYwJGlDrv3Rx0pWPjVpCTGa1BN7gDQ1kjwb++8Z8qjGhT2jA31XPp5OfGqtWIKRymgBMs9PV63bhXJ7kulw2TCbU2iU0YJYTeJvlbWM/AA2Y1QB4m+WNNhfMm59n3vXnS8JXmk/oQE3v239CMz4gkCsEsD3bsZp2ecB1uWw2Dtw2xgQNqHVYujjpysdGLSEms1oCb/CGBrJLAwv+PJCO3vhhYNBbbp1Idc88Qa1ASAUCjhCAaXakIkUxXJ7kulw2TCbUGiI0YJYTeJvlbWM/AA2Y1QB4m+WNNhfOm1ebv7ulNx2+Y0VCorUX30aNu/1eraKQCgQcIgDT7FBl6uz8dealaxKgKx8by4aY1BoiNGCWE3ib5W1jPwANmNUAeJvljTYXzXvFtZ3osO0r6ZcKdajqkNE4NTsaGVI4SgCm2bGKdXnAdblsNg7cNsYEDah1WLo46crHRi0hJrNaAm/whgayUwNfd+lMh29bQfyqqSOnzVQrBFKBgIMEYJodq1SXJ7kulw2TCbWGCA2Y5QTeZnnb2A9AA2Y1AN5meaPNRfOWXz11yPMfRP8AKUDAUQIwzY5VrMsDrstls3HgtjEmaECtw9LFSVc+NmoJMZnVEniDNzSQnRqAaVarN6RynwBMs2N17PIk1+WyYTKh1hChAbOcwNssbxv7AWjArAbA2yxvtLnkvFfG3td8qPS+Zqw0q+kzKNXeH9bR7sVf0L5tm6ncyadR2QbHlzwz3y8bn9fF+8tFrZrTqKG949/y309p1JCmPTnE+9vgERNpxqy5tH3HTqpZI486tv8dVatame575Gm6q+81dPXlrb103fo/SHPnL6YnH+xP55zZxPubzvcxc14rVq2lT2eO08JAlJ8zW/Tu5MA8VdJEBQPTHEUoy753ecB1uWw2Dtw2xgQNqHVIujjpysdGLSEms1oCb/CGBrJPAzDNanUWlWrH8xNox4uTEpId3PZKqtTl5qifKn0vG0LZ6Mqm+bl/zfLMMZvo5k0b0ZLlq+nE4+pRQbvz6ZKOgxIMd/M23T1j3aWgDQ3oeZUXg9+AKwUWkmjE41O9608YObA02cR/y7HxDYMOl7aKm3x/xh/MW0APPPoMrVqzPtRYRwUD0xxFKMu+d3mS63LZMJlQa2jQgFlO4G2Wt439ADRgVgPgbZY32lxy3l+Onkb15jwWT4SVZjV9yql2zXuPtj50R+APK3W+mQ6+9MrUM/X9QhjahUtXJqwsy0aXjerk2EFusqkW2bRq34eqVK5IM54ZTguWrKSregz1VqKPPLyGt0rNhvPGgSMTTHSpg9aYAZdTNvhhWZd2tRymWWOl2ZCVywOuy2WzceC2MSZoQK2X0cVJVz42agkxmdUSeIM3NJB9Gvji/vHUoHAKTLOv6n791zO0b9dOpQrd+e4M2rvh+8C0ZSpXTck0V7ziusB8hDk+6sjD6M3Zn9KIu3tS29YtElaHxUozm+Ee17aLb8XmDPsNGeP97sNXxtKMt+d6K9JsQtlk83bncc+8SqOfmh5ouNmIbt66jZrnN6Lpr71HlSpWoP49Crz8hdnmeMZMeol+2PiztyXbb17Z0P/7rY9o409FCb+fMetjGj72H/G/t219Fg0bUJyB3zRz/sziqCNremXoc30H6t7pslJvMYdpVpJ89iRyeZLrctkwmVBrY9CAWU7gbZa3jf0ANGBWA+BtljfaXHLeC3sNorob5sA0+zAVdWkTezZ5i5pY9+0jKlNGLW1EqrzJM4mNtv8jTPOIwT28rdZsjGe/NLrYlmp+ppmNLX94m/a4EbdSXvUqCaZ4+muzaemKb+mOmzt5q8u8Mj1p2uveM85BzwsLA3xWs5O97d7TXn7b29r9+rPDafXaH7w82EgfUfNQz1iz6ZVNszDz9evWovNbnkbffb+R+nW/wouRy8Jx3tStPS1e9o1n3IUBlhkEmWZ+Zpo/x9avQ3f1u5aanNgQplmLCh3KxOUB1+Wy2Thw2xgTNKDWWenipCsfG7WEmMxqCbzBGxrIPg18dUMvql1UCNPsqzp9K81VYivNBWrCiKWKWmnmrdRiGzYf7CWeYRYHgfGFVq9dT0MfnuKZYDa6/Fyx2JLNq8u84nt6k+O9A8WEGeW/ie3b/mCDVo3FNnBOy6bZf0CZ/Btx6NjUJ4Z4xlZ8xOq2/3pB27CDTDNvVWfjXq9OrXgW2J6tLLXcSOjyJNflsmEyodY+oQGznMDbLG8b+wFowKwGwNssb7S55LxXdexAebvWU1G5Iyhv9w+09daJVOfME9QqCak8AiafaWZzXLRpK7W+sp93bV7xFadn8995VVl8xOFhYvWYD//iVVk2m+IkbTaZVatW8gx2h0vPDdwa7TeiYjWbV6iFafYbXfk34t9hppmve1GrM+Jx16tzRIIR5i/CTLN/ZRymGY0ygYDLA67LZbNx4LYxJmhArcPTxUlXPjZqCTGZ1RJ4gzc0kH0aEO9oXlv9VKqz6Uv6udtoanhxM7WCIFWcQPDp2VfETs/uo4WS/2RrsdrMmQvTzIaRP3xyNm+B5meYxUoz/12s+PK/xQqtnI94TtofcND2bE4z6/lRsRXs/wYeICabV7GiLG/P5lOw2Rzz9mzxjHRetao097NFdMVl5yesSMM0a5FQbmbi8iTX5bJhMqHWXqEBs5zA2yxvG/sBaMCsBsDbLG+0uXDePy5bR2XvuoK2H1SFfqp6LEyzmjRDU+1/T/PntG/rFirXWP97muX3MXMQfCI2H6wl/i4ftsXf85bpe/p3ja8+C/MqnofmNOIgL/43HxImr1SLggoDzPmxEQ86CCzZSjPn439/9JgH+nrGmA8C4wPE+DVR/GFj/cTwW7DSXEot4uf/I+DygOty2WwcuG2MCRpQ6+p0cdKVj41aQkxmtQTe4A0NZJcGxDua1+Xl097YYVZYaVarv1xLVdotzzp44T3NOijmYB4uT3JdLhsmE2qNFRowywm8zfK2sR+ABsxqALzN8kabC+e99PnZVOvFO2nN4S2pzK+bYZrVpJlzqWwxzQJ80Anf/J14hpv/HZYmqvLwyqkoQln2vcsDrstls3HgtjEmaECtQ9LFSVc+NmoJMZnVEniDNzSQXRoQ72j+Jr8zlV/5OUyzWvXlXCobTLMp6DDNpkgbuo7Lk1yXy4bJhFoDgQbMcgJvs7xt7AegAbMaAG+zvNHmwnkX3v0I1V/6IsE0q2kSqdwnANPsWB27POC6XDYbB24bY4IG1DosXZx05WOjlhCTWS2BN3hDA9mlAfGOZj4xe9sLE7DSrFZ9SOUwAZhmxyrX5Umuy2XDZEKtIUIDZjmBt1neNvYD0IBZDYC3Wd5oc+G8YZrVtIhUuUMAptmxunZ5wHW5bDYO3DbGBA2odVi6OOnKx0YtISazWgJv8IYGsksD4h3Nhzz/AX3Wbxgds/ZNWt3yJjq1T4FaQZAKBBwjANPsWIW6PMl1uWyYTKg1RGjALCfwNsvbxn4AGjCrAfA2yxttLpy3bJo/GfokHb/oae/55qZ33qBWSUgFAo4RgGl2rEJdHnBdLpuNA7eNMUEDah2WLk668rFRS4jJrJbAG7yhgezRgHhH88ZKx9JxU6YQTLNa3SGV2wRyzjSLo9HlahXv61qwZCXdN+rvtHDpSqpZI496XNuOrr68dVYpwOVJrstlw2RCrZlBA2Y5gbdZ3jb2A9CAWQ2At1neaHPBvIVpXpeXTyeNHwvTrCZLpHKcQM6a5i4FbeJVO6DnVd6/haHucOm59GnhUlq1Zj29/uxwqlenVtbIwOUB1+Wy2Thw2xgTNKDWFenipCsfG7WEmMxqCbzBGxrIHg18OXoa1ZvzGK1q9EfKv7cvTLNa1SGV4wRyzjS37TTIq9IZzwxPqNrVa9fTJR0H0VnNTqYJIwfSjFkf04B7Hyc218JUZ4MWXJ7kulw2TCbUWhc0YJYTeJvlbWM/AA2Y1QB4m+WNNhfM+4v7x1ODwinxZ5ixPVtNl0jlNoGcM82Nz+sSr9FKFStQwR8u8EzxB/MW0I0DR8ZNst9EZ4sMXB5wXS6bjQO3jTFBA2o9kS5OuvKxUUuIyayWwBu8oYHs0cDCXoOo7oY5tLbN7dT4ukux0qxWdUjlOIGcM82DR0ykalUre9U67eW3afuOnXRX32vo6KOOSDDN/D0b7FMaNaRpTw4hnjziAwIgAAIgAAIgAAIgAAIuE1jfvx/V2fQlren4MB15Xj6tfGSyd3r2142voYZ9u2Rd0WvmHZx1MSNg+wjknGmWq0Degn12s8ZYafbpU9cqk2354G63ekdkW93pigcaUNMAeIMTNGBWA+BtlreNY4ENGljVsQPl7VpPe+57gQ47oTZWmtVkiVSOE4Bp/t9zywXtzsczzTDNKTd3GwY3f9Aux+Ry2TB5U2t+0IBZTuAN3tBA7mlAfkczl/6zJ16lY94eTmsOb0mnjE08E0iNDlKBQPYTyCnTzM8tP/DoM3R+y9O8mhPbs6c+MYSanNgQp2fDNKfcojGZUEOmi5OufGw0qDbGBN5m9Q0NgDfaHDSQaQ38uGwdlb3rCtp+UBWqPfUNr0IWvjyP6j57C4lXUKnVElKBgFsEcso08+FePQY97L1Kij/169ai3l3bU9vWLbz/Ltq0lboPeMh7TzMfEta/RwHe06zhORBdA4CufGycmCImtY4VGjDLCbzN8raxH4AGzGoAvM3yRpsrztv/jmaYZjVNIpX7BHLKNLtfneQdWKbrwANdedmWj42DJGJSa526tATe4A0NQAM2agB9HHSZaQ0sfX421XrxzoRVZaw0q+kSqdwmANPsWP1murMNwqkrJl352DhRQkxqDREaMMsJvM3ytrEfgAbMagC8zfJGmzvAe+vGzbT8L6Op1pr3qeLeLfTjwfXo4JuHUt0zT8D2bDVZIpXjBGCaHatglwdcl8tm48BtY0zQgFqHpYuTrnxs1BJiMqsl8AZvaMBeDbBh3tina+zE7O+LBbnl1on0y7pf8EyzWvUhlcMEYJodq1yXJ7kulw2TCbWGCA2Y5QTeZnnb2A9AA2Y1AN5meaPN7ef9xf3jqUHhlED431VvSnsvuxamWU2aSOUwAZhmxyrX5QHX5bLZOHDbGBM0oNZh6eKkKx8btYSYzGoJvMEbGrBXA4uv70VHbSoMDXBNx4dhmtWqD6kcJgDT7FjlujzJdblsmEyoNURowCwn8DbL28Z+ABowqwHwNssbbW4/b5hmNd0hVW4TgGl2rP5dHnBdLpuNA7eNMUEDah2WLk668rFRS4jJrJbAG7yhAXs1kHx7dj5V7DWIavzlT1RUvhbVf3a6WkGQCgQcIwDT7FiFujzJdblsmEyoNURowCwn8DbL28Z+ABowqwHwNssbbW4/bz4I7LtbetPhO1YkVMC2MpVpb/8xVLFRfSp3Q2vvu0Oe/0CtkpAKBBwjANPsWIW6POC6XDYbB24bY4IG1DosXZx05WOjlhCTWS2BN3hDA3ZrgI3z1488RQ2Wvkj7yhCtqdmSavftRzVPqE08FsA0q9UfUrlLAKbZsbp1eZLrctkwmVBriNCAWU7gbZa3jf0ANGBWA+BtljfaXHHev1x5TrEVZZhmNV0ildsEYJodq1+XB1yXy2bjwG1jTNCAWoeli5OufGzUEmIyqyXwBm9oIDs0ANOsVk9IlXsEYJodq3OXJ7kulw2TCbWGCA2Y5QTeZnnb2A9AA2Y1AN5meaPNYaVZTXFIBQJEMM2OqcDlAdflstk4cNsYEzSg1mHp4qQrHxu1hJjMagm8wRsayA4NYKVZrZ6QKvcIwDQ7VucuT3JdLhsmE2oNERowywm8zfK2sR+ABsxqALzN8kabw0qzmuKQCgSw0uycBlwecF0um40Dt40xQQNqXZYuTrrysVFLiMmslsAbvKEB+zWw8o35dOiEPrSx0rF03JQp8YBxEJha3SGV2wSw0uxY/bo8yXW5bJhMqDVEaMAsJ/A2y9vGfgAaMKsB8DbLG20ukbcwzevy8umk8WMTTPO2P/+Jqu9aT3vue4EOi72GCh8QyDUCMM2O1bjLA67LZbNx4LYxJmhArcPSxUlXPjZqCTGZ1RJ4gzc0YL8GkpnmDbfeQrWLCunnbqOp4cXN1AqDVCDgEAGYZocqU+eApDMvXRNvXfnYWDbEpNYQoQGznMDbLG8b+wFowKwGwNssb7S5RN4wzWr6Q6rcJADT7Fi9uzzgulw2GwduG2OCBtQ6LF2cdOVjo5YQk1ktgTd4QwP2awCmWa2OkCo3CcA0O1bvLk9yXS4bJhNqDREaMMsJvM3ytrEfgAbMagC8zfJGm8NKs5rikAoEcHq2cxpwecB1uWw2Dtw2xgQNqHVZujjpysdGLSEms1oCb/CGBuzXAFaa1eoIqXKTAFaaHat3lye5LpcNkwm1hggNmOUE3mZ529gPQANmNQDeZnmjzWGlWU1xSAUCWGl2TgMuD7gul83GgdvGmKABtS5LFydd+dioJcRkVkvgDd7QgP0aWPr8bKr14p205vCWdMrY4fGAeSzA6dlq9YdU7hLASrNjdevyJNflsmEyodYQoQGznMDbLG8b+wFowKwGwNssb7S5RN5f3D+eGhROoW/yO1PTO2+AaVaTI1LlCAGYZscq2uUB1+Wy2Thw2xgTNKDWYenipCsfG7WEmMxqCbzBGxqwXwPJTPP3dwymuhvm0No2t1Pj6y5VKwxSgYBDBGCaHapMnQOSzrx0Tbx15WNj2RCTWkOEBsxyAm+zvG3sB6ABsxoAb7O80ebUV5rXjPl74Cq0Wo0hFQhkPwGY5uyvw4QSuDzgulw2GwduG2OCBtQ6LF2cdOVjo5YQk1ktgTd4QwP2ayDZSjNMs1r9IZW7BGCaHatblye5LpcNkwm1hggNmOUE3mZ529gPQANmNQDeZnmjzWGlWU1xSAUCOD3bOQ24POC6XDYbB24bY4IG1LosXZx05WOjlhCTWS2BN3hDA/ZrACvNanWEVLlJACvNjtW7y5Ncl8uGyYRaQ4QGzHICb7O8bewHoAGzGgBvs7zR5rDSrKY4pAIBrDQ7pwGXB1yXy2bjwG1jTNCAWpeli5OufGzUEmIyqyXwBm9owH4NYKVZrY6QKjcJYKXZsXp3eZLrctkwmVBriNCAWU7gbZa3jf0ANGBWA+BtljfaXCLvhb0GBb5WinWJg8DUtIlU7hKAaXasbl0ecF0um40Dt40xQQNqHZYuTrrysVFLiMmslsAbvKEB+zXw1Q29qHZRIf3cbTQ1vLhZPGCYZrW6Qyq3CcA0O1a/Lk9yXS4bJhNqDREaMMsJvM3yPclFrgAAIABJREFUtrEfgAbMagC8zfJGm0vkncw0fzf5X1RvzmO0qtEfKf/evmoVhVQg4BABmGaHKlNn568zL12TAF352Fg2xKTWEKEBs5zA2yxvG/sBaMCsBsDbLG+0OXXTvHnuQjp0Qh9al5dPJ40fq1ZRSAUCDhGAaXaoMnV2/jrz0jUJ0JWPjWVDTGoNERowywm8zfK2sR+ABsxqALzN8kabg2lWUxxSgQBOz3ZOAy4PuC6XzcaB28aYoAG1LksXJ1352KglxGRWS+AN3tCA/RpItj0bK81q9YdU7hLASrNjdevyJNflsmEyodYQoQGznMDbLG8b+wFowKwGwNssb7Q5rDSrKQ6pQAArzc5pwOUB1+Wy2Thw2xgTNKDWZenipCsfG7WEmMxqCbzBGxqwXwNYaVarI6TKTQJYaXas3l2e5LpcNkwm1BoiNGCWE3ib5W1jPwANmNUAeJvljTaHlWY1xSEVCGCl2TkNuDzgulw2GwduG2OCBtS6LF2cdOVjo5YQk1ktgTd4QwP2a+CXK8/xgjzk+Q8SguWxAM80q9UfUrlLACvNjtWty5Ncl8uGyYRaQ4QGzHICb7O8bewHoAGzGgBvs7zR5hJ5wzSr6Q+pcpMATLNj9e7ygOty2WwcuG2MCRpQ67B0cdKVj41aQkxmtQTe4A0N2K+BZKb516WrqMpD19GGysfS8ZOnqBUGqUDAIQIwzQ5Vps4BSWdeuibeuvKxsWyISa0hQgNmOYG3Wd429gPQgFkNgLdZ3mhz6ivNNfMOpjBTrVZrSAUC2U0Apjm7669Y9C4PuC6XzcaB28aYoAG1DksXJ1352KglxGRWS+AN3tCA/RpIttIM06xWf0jlLgGYZsfq1uVJrstlw2RCrSFCA2Y5gbdZ3jb2A9CAWQ2At1neaHNYaVZTHFKBAE7Pdk4DLg+4LpfNxoHbxpigAbUuSxcnXfnYqCXEZFZL4A3e0ID9GsBKs1odIVVuEsBKs2P17vIk1+WyYTKh1hChAbOcwNssbxv7AWjArAbA2yxvtDmsNKspDqlAACvNzmnA5QHX5bLZOHDbGBM0oNZl6eKkKx8btYSYzGoJvMEbGrBbAz8uW0dl77qCth9UhWpPfSMhWDEW4CAwtTpEKjcJ5OxK8+q166l9t7tp+46dtOjdyV7tFtw4lBYuXZlQ0+K7bKl+lye5LpcNkwm1FgYNmOUE3mZ529gPQANmNQDeZnmjzR3gvfKN+XTohD60Li+fTho/FqZZTYpIlUMEctY0d+v/IM2dv9irar9p7lLQJi6BAT2vyio5uDzgulw2GwduG2OCBtS6I12cdOVjo5YQk1ktgTd4QwN2awCmWa1+kCp3CeSkaZ4x62MaPGICHVHzUFq1Zn3cNLftNMhTwoxnhmetIlye5LpcNkwm1JocNGCWE3ib5W1jPwANmNUAeJvljTZ3gLeKaV531cVUae9WqvD461T5sGpqlYVUIOAIgZwzzUWbtlK7LndQx/a/o1nvf+ZtxxYrzY3P6xKv1koVK1DBHy4grDQfXGqp65oE6MrHxkESManJDBowywm8zfK2sR+ABsxqALzN8kabS800f3VDL6pdVEg/dxtNDS9uplZZSAUCjhDIOdM84vGp9O+3PqLZL42m5m26JzzTPHjERKpWtbJXtdNeftv77q6+19DVl7fOmup2ecB1uWw2Dtw2xgQNqHVFujjpysdGLSEms1oCb/CGBuzWgMpKM0yzWh0ilZsEcso0L1iykq7qMZRG3N2T2rZuQWJlOeiwL97CPeDex4mfb+bVZp484gMCIAACIAACIAACIAACrhH4/t1CqvvsLbS2+qlUa+SowOKt79+P6mz6ktZ0fJiOPC8/axDUzCv9rsmsKSwCTRuBnDLNvMo8edrMQJh+4+w3zWmrAc0Zu7wy5HLZcAderSFAA2Y5gbdZ3jb2A9CAWQ2At1neaHMHeGOlWU17SJW7BHLKNH8wbwF9NH9RvLaFgebV5LObNaYHHn2Gzm95mve92J499Ykh1OTEhlmjEJcHXJfLZuPAbWNM0IBaV6SLk658bNQSYjKrJfAGb2jAbg3ANKvVD1LlLoGcMs3+apa3Z/N7m3sMetg7TZs/9evWot5d23vbuLPp4/Ik1+WyYTKh1sqgAbOcwNssbxv7AWjArAbA2yxvtLkDvL8cPY3qzXmMVjX6I+Xf2zehIoQu8Uyzmj6Ryk0COW2aXaxSlwdcl8tm48BtY0zQgFqvpYuTrnxs1BJiMqsl8AZvaMBuDXxx/3hqUDiFvsnvTE3vvAGmWa26kCqHCMA0O1bZLk9yXS4bJhNqDREaMMsJvM3ytrEfgAbMagC8zfJGmzvAG6ZZTXtIlbsEYJodq3uXB1yXy2bjwG1jTNCAWoeli5OufGzUEmIyqyXwBm9owG4NpGKa1//xfmp0ZSu1AiEVCDhCwKhpLtq0lRYs+a+HrsmJx1Be9SqOYLSnGC5Pcl0uGyYTam0IGjDLCbzN8raxH4AGzGoAvM3yRptLbaU5mbFWqzmkAoHsJZB208wHbD31j9do9keFtPGnogRSlSpWoN+2OJX6db+C6tWplb0ULYrc5QHX5bLZOHDbGBM0oNbZ6OKkKx8btYSYzGoJvMEbGrBbAyorzTDNanWIVG4SSKtplt+LzAb52Pp1EiiuWLWWtu/Y6f2NX/s0oOdVblI2WCqXJ7kulw2TCbVGAg2Y5QTeZnnb2A9AA2Y1AN5meaPNHeAN06ymPaTKXQJpNc38SqeLWjWnC889I/TVTfzu5OmvzaY3Z39Ki96dnLs1oankLg+4LpfNxoHbxpigAbWOQhcnXfnYqCXEZFZL4A3e0IDdGoBpVqsfpMpdAmk1zWyIzzmziRLdVNIqZZijiVye5LpcNkwm1BosNGCWE3ib5W1jPwANmNUAeJvljTZ3gHfh3Y9Q/aUvJn3lFLZnq+kTqdwkkFbT7EfGzzevXvtDMZKqxtrNKtBbKpcHXJfLZuPAbWNM0IBaf6GLk658bNQSYjKrJfAGb2jAbg18dUMvql1USD93G00NL26WEKwYC2Ca1eoQqdwkYMQ0L1iyknrf8Uixg8AEUmzL1iculye5LpcNkwm1NgANmOUE3mZ529gPQANmNQDeZnmjzR3gDdOspj2kyl0CRkxzq/Z9Qg0zo4dp1idAlwdcl8tm48BtY0zQgFpfoYuTrnxs1BJiMqsl8AZvaMBuDcA0q9UPUuUuASOmmQ8Eq1kjj16Z/ADezZxmrbk8yXW5bJhMqDUMaMAsJ/A2y9vGfgAaMKsB8DbLG20OK81qikMqECAyYpp5pfnIw2vQtCeHgHmaCbg84LpcNhsHbhtjggbUOhBdnHTlY6OWEJNZLYE3eEMDdmtAZaV55Rvz6dAJfWhdXj6dNH6sWoGQCgQcIZA208ynYYvP4mXf0OinpnvvYj67WeNi6HAQmD41uTzJdblsmEyotQFowCwn8DbL28Z+ABowqwHwNssbbS61lWaYZjV9IpWbBNJmmnlLtuoHzzSrkopO5/KA63LZbBy4bYwJGojuA2ysN8SkVm82ckKbU6s7XZx05WOjlhCTWS2lyhsrzWr1g1S5SwCm2bG6d3nAdblsqQ5uyWTrMieXy2ajBsBbbYBwmZPLZUObg76hAaw0q7UCpAIBQ880A7Q5Ai5PcFwum40Dt40xQQNqfYkuTrrysVFLiMmslsAbvKEBuzWwqmMHytu1nvbc9wIddkLthGDFWIDt2Wp1iFRuEkjbSjPj6tb/QWpx2kl0dvNTqMmJDd0kaFmpXJ7kulw2TCbUGhI0YJYTeJvlbWM/AA2Y1QB4m+WNNneA9y9XnuP9xyHPf1CsEmCa1XSJVG4TSKtplp9rrlSxAuU3Pg4mOs16cnnAdblsNg7cNsYEDah1ILo46crHRi0hJrNaAm/whgbs1gBMs1r9IFXuEkiraX7uX7No3udf0dIV39KqNesTKMsmununy3K3BjSX3OVJrstlw2RCrSFAA2Y5gbdZ3jb2A9CAWQ2At1neaHMHeMM0q2kPqXKXQFpNs4y1aNNWmvPJQpr72SJauvxbWrh0ZfxrnJ6tT4AuD7gul83GgdvGmKABtb5CFydd+dioJcRkVkvgDd7QgN0agGlWqx+kyl0CxkwzI16wZCV99OlCmvX+Z/T9hp9o409FHnmYZn0CdHmS63LZMJlQawPQgFlO4G2Wt439ADRgVgPgbZY32twB3iqmmVMnS6dWe0gFAtlJIK2mWZjkj2NbtAsXLaftO3bGKdWvW4ua5zeii1qdQeec2SQ76VkYtcsDrstls3HgtjEmaECt09HFSVc+NmoJMZnVEniDNzRgtwZgmtXqB6lyl0BaTbN8ENgpjRpSo+OOprNOb0wtzziF8qpXyV3qaSy5y5Ncl8uGyYRao4AGzHICb7O8bewHoAGzGgBvs7zR5g7whmlW0x5S5S4BY6aZV5YbHXs0nRl7BRWb5np1auUu9TSW3OUB1+Wy2Thw2xgTNKDWeejipCsfG7WEmMxqCbzBGxqwWwMwzWr1g1S5SyCtpnn12vXe4V98gvZnC76OP8PMuGvWyKPTmxxPF557BrVt3SJ3a0BzyV2e5LpcNkwm1BoCNGCWE3ib5W1jPwANmNUAeJvljTa3n/fKN+bToRP60MZKx9JxU6YUqwRZl3imWU2jSOUegbSaZj8uNtEz35lHX329KuE1VDgITJ+wXB5wXS6bjQO3jTFBA2p9hS5OuvKxUUuIyayWwBu8oQF7NSBM87q8fDpp/FiYZrWqQqocI2DMNMurzv73NsM061Ody5Ncl8uGyYRaG4AGzHICb7O8bewHoAGzGgBvs7zR5vbzhmlW0x1S5TaBtJrmcc+8SkEnZzNycXo2HwyG7dn6ROjygOty2WwcuG2MCRpQ6yt0cdKVj41aQkxmtQTe4A0N2KsBmGa1ukGq3CaQVtMsn54tnmHGQWDpFZzLk1yXy4bJhFq7gAbMcgJvs7xt7AegAbMaAG+zvNHmsNKspjikAgGitJrmfkPG4LRswypzecB1uWw2Dtw2xgQNqHUoujjpysdGLSEms1oCb/CGBuzVQCorzV/d0ItqFxXSz91GU8OLm6kVCqlAwAECaTXNH8xboITonDObKKVDomgCLk9yXS4bJhPR2tbJSGdeLuvS5bJBA2hzNmoAbQ66zIQGYJrVdIdUuU0graZZ3p6dDDMOAtMnwkx0tlHR64pJVz42TpQQU5SK9n8PDZjlBN5meevUuK6605WPjWWzMSbwRpvLhAZgmtV0h1S5TcCIaebnmY88vEYo6WlPDsntWtBY+kx0tlHh64pJVz42TpQQU5SKYJrVCOnlhDanRt1lTi6XzcZ+F7zR5jKhgaXPz6ZaL95Jaw5vSaeMHV6sEuSYsD1bTaNI5R6BtJrmVu1jL0r/qcijxqdlX97mHGpz/plUr04t90haUqJMdLZRRdcVk658bJwoIaYoFek1g+AN3tAANGCjBjDOQZeZ0MAX94+nBoVT6Jv8ztT0zhtgmtVkiFQ5RiCtpplZLliykl549R2a/VEhDLQBcWWis40qlq6YdOVj40QJMUWpCKZZjZBeTmhzatRd5uRy2Wzsd8EbbS4TGoBpVtMdUuU2gbSbZhmvMNCfFi6lVWvWe1/x1u3ZL43O7VrQWPpMdLZR4euKSVc+Nk6UEFOUivSaQfAGb2gAGrBRAxjnoMtMaACmWU13SJXbBIyaZka9eu16mvPJQnr6xTfjxhkHgekTYSY626jodcWkKx8bJ0qIKUpFMM1qhPRyQptTo+4yJ5fLZmO/C95oc5nQAEyzmu6QKrcJGDHNbJRnvjOP/jXzg7hRZuxnNTuZWpx2EnXvdFlu14LG0meis40KX1dMuvKxcaKEmKJUpNcMgjd4QwPQgI0awDgHXWZCAzDNarpDqtwmkFbTPHjExIRnmStVrEC/bXEqnRkzym0vOIvyqlfJbfppKH0mOtuoYuiKSVc+Nk6UEFOUimCa1Qjp5YQ2p0bdZU4ul83Gfhe80eYyoYFUTHPh3Y9Q/aUvhh4aplaDSAUC2UcgraZZvKeZT85unt+I6tY+nIo2by1GaUDPq7KPnKURZ6KzjUKhKyZd+dg4UUJMUSrSawbBG7yhAWjARg1gnIMuM6GBVExzVFq1GkQqEMg+AkZMcxQWPNMcRUj9+0x0tlHR6YpJVz42TpQQU5SKYJrVCOnlhDanRt1lTi6XzcZ+F7zR5jKhgSgjLMcUlVatBpEKBLKPQFpN84jHpyoRwUqzEialRJnobKMC0xWTrnxsnCghpigV6TWD4A3e0AA0YKMGMM5Bl5nQwMJeg6juhjm0ts3t1Pi6S4tVAkyzmi6Rym0CaTXNRZu24rllw/rJRGcbVURdMenKx8aJEmKKUhFMsxohvZzQ5tSou8zJ5bLZ2O+CN9pcJjTw1Q29qHZRIf3cbTQ1vLgZTLOaDJEqxwik1TTzM818QnaHtq2obesWOYY2M8XNRGcbVVJdMenKx8aJEmKKUpFeMwje4A0NQAM2agDjHHSZCQ3ANKvpDqlym0BaTXOr9n1o409FHmE+Obtt67PoisvOpyYnNsxt6mksfSY626ji6IpJVz42TpQQU5SKYJrVCOnlhDanRt1lTi6XzcZ+F7zR5jKhAZhmNd0hVW4TSKtpZrQLlqykic+9Ru9//CVt37HTo82naV/e5hwqaHcBtm9r1l8mOtuoIuiKSVc+Nk6UEFOUivSaQfAGb2gAGrBRAxjnoMtMaACmWU13SJXbBNJummW8z/1rFv3n/fk0d/7i+J95+/aEkQNzuxY0lj4TnW1U+Lpi0pWPjRMlxBSlIphmNUJ6OaHNqVF3mZPLZbOx3wVvtLlMaACmWU13SJXbBIyaZoF69dr1NPOdefTsS//xtm/jlVP6RJiJzjYqel0x6crHxokSYopSkV4zCN7gDQ1AAzZqAOMcdJkJDaRimpc+P5tqvXgnrTm8JZ0ydrhahSEVCDhAICOmWebG27cz8YwzG/f23e72towL086x3Dfq77Rw6UqqWSOPelzbjq6+vHVWVXMmOtsoQLpi0pWPjRMlxBSlIphmNUJ6OaHNqVF3mZPLZbOx3wVvtLlMaCAV07zyjfl06IQ+tC4vn04aP1atwpAKBBwgkFbTPO6ZVz1E4tllfgVV9wEPeab0lEYNadyIWzP2THO3/g/Gt4kL01xw41Avtg6XnkufFi6lVWvW0+vPDqd6dWplTVVnorONgqMrJl352DhRQkxRKtJrBsEbvKEBaMBGDWCcgy4zoQGYZjXdIVVuE0iraW7baZBnPIUp7TdkDL05+9M48YtaNadRQ3sbr4EZsz6mwSMm0BE1D43HxyvPl3Qc5L0ii5+x5jQD7n2cuhS0oQE9rzIeY0kvmInONipWXTHpysfGiRJiilIRTLMaIb2c0ObUqLvMyeWy2djvgjfaXCY08MuV53jgD3n+g8AKkGPCSrOaRpHKPQJpNc38nmZeUZ725BASppS3PT/92B10zU0P0NZt2+nTmeOMUuXV7nZd7qCO7X9Hs97/zFtZZlP/wbwFdOPAkXGT7DfRRoMsxcUy0dlGhasrJl352DhRQkxRKtJrBsEbvKEBaMBGDWCcgy4zoQGYZjXdIVVuE0ibaWbDrPoxeRDYiMen0r/f+ohmvzSamrfpHn+m2W+aOXbZ9KuWJdPpMtHZRpVZV0y68rFxooSYolQE06xGSC8ntDk16i5zcrlsNva74I02lwkNwDSr6Q6pcptA2kwzY23Vvo9H9/7brqe+gx/zDKp4Rlg8U2zSMPNBX1f1GEoj7u5JbVu38Ewxf1RWmrkTwwcEQAAEQAAEQAAEQAAEXCJQ7ob9h97uHj8rsljfv1tIdZ+9hdZWP5VqjRwVmd6GBDXzDrYhDMSQ5QTSapoHj5hI0197L46ID9gaNuA677/ZUFepXJFmPGPuuHpeZZ48bWZglbGZxzPNiWh03e20LR8uJWJS67ls46QrHmjAbP2DtxpvGzmhzanVnS5OuvKxUUuIyayWUuGNlWa1ukGq3CaQVtPMzw/fM3ISfbbgazq9yfF0T/+u3mnZYiu0bKJNVANf96P5i+KXEgZaHPaF07NhmlPVISY4asR0cdKVTyqTiagSuhyTy2WDBqKUvf97aMAsJ/A2y1unxnXVna58UikbTLOa7pAqtwmk1TTbjlbens2xyq/EqlSxAvXvUYD3NGvY0qJrANCVTyoDSZSGEVMUIb0Tb/AGb2gAGnBZAy6XDWOv2babCu9UTPO2HzfTzp6X0I4yVenIkN2baiVFKhDILgJpNc28cjticI/I9xzzSdUDhj3hnbKNT+kIuDzguly2VAa3KIW4zMnlstmoAfCOam16bwpBA+CNNgcNZEIDqZhmrqGo9Gq1iFQgkF0E0mqaxenU/Nqp1r89nU4+oUECncXLvqGPP/+K5s5fTLyya/r1U9lVVWrRZqKzjYpMV0y68rFxYoqYolTkvjmxUQNoc9AlNGBWA+Btljf6XaIfl62jsnddQZvK16J6z04PrAC/LmGa1XSKVG4RSKtpFs80vzn706TULmrVPP68s1t4zZfG5QHX5bLZOHDbGBM0oNan6OKkKx8btYSYzGoJvMEbGrBTAyvfmE+HTuhD6/Ly6aTxY2Ga1aoJqXKQQFpNs+DJ5nnG23Ppq69X0dLl33p/bnTc0XTS8fWp5RmnRG7fzsF6KXGRXZ7kulw2TCbUJA8NmOUE3mZ529gPQANmNQDeZnmjzRHBNKtpDqlAwIhpBmZzBFwecF0um40Dt40xQQNqfYkuTrrysVFLiMmslsAbvKEBOzUA06xWL0gFAjDNjmnA5Umuy2XDZEKtIUIDZjmBt1neNvYD0IBZDYC3Wd5oc1hpVlMcUoEAEUyzYypwecB1uWw2Dtw2xgQNqHVYujjpysdGLSEms1oCbzd4b9tO9O3afbFH7fbFHrMr4/0vlY+uPkVXPjbq0nTZsNKcioKRNpcJwDQ7VvumO1sVfLpi0pWPjYMkYlJREhE0YJYTeJvlbWM/AA2Y1YDNvFfHzPLYp3bTjz8dYHJ0nTI04KZyVLkSOOmqO135qPYnMM1q2kUqEDBmmvkwsDmfLKRFy1bS2c0a0zlnNgH9NBAw3dmqFEFXTLryUR1ITJYNManQhmlWo6SPE9qcGnGXOblcNhv7XVt5V65wMA0auou2x1aa/R9ebWbjrPLRVT5d+UADJduevbxzZ6q5fQVtvXUi1TnzBJWqRxoQyHoCRkzzgiUrqWvfv9D2HTs9YF0K2lD3jpdR6yv70W9bnEqjhvbOepC2FAADiVpN6OKkKx8bB24bYwJv6BsagAZc1oCtZVu6pDxN+seeUPENHlgu9iaU6K3ausqnKx+McyUzzV/d0ItqFxXSz91GU8OLm6l1SkgFAllOwIhp7tb/QZo7fzHx+5j5nc1smgf0vIr474WLltOnM8dlOUZ7wsdAolYXujjpysfGgdvGmMAb+oYGoAGXNWBr2eZ8WI5enbk3VHy9upWj006Faa6Zd7BaA02SyrQGvhw9jerNeYxWNfoj5d/bNzAyf0wwzaWuZmSQhQSMmObG53WhDpeeS8MGXEf8b2GaRzw+lSZPm0mL3p2chejsDNl0Z6tCQVdMuvKx0QwiJhUl6dt2DN7gDQ1AA6Y0sPTrfTT1n3u8A7QqxZ79bXnmQdTukrKBzwHbOs5FrTQP6F2OGh0P05yNpvmL+8dTg8Ip9E1+Z2p65w0wzWpdI1LlIIGMmuaCG4fSwqUrYZo1Cs/WATcbBxKVanGZt6kJpQpnkQa81Wjp4qQrHxu1hJjMailXeX/+ZezwrAm7i8HmA7SGxLY0+z+2tjnvmeZ7Ys807yium7pHlaF7BuGZZl11pysf1TaXqmneuGwdbR52Mx3663e06pROdFyvTlSlZjW1DgWpQCCLCRgxzf7t2ac0aughY8N8VrOTacLIgVmM0K7QTXe2KqXXFZOufFQHEpNlQ0wqtLHSrEZJHye0OTXiLnNyuWwm+t2bBgUbTb52wf+VpQvPOyhBZDbz5hXzMbHTs2XjzIb5uk5llZ5nNsFbrcUmptLF3LZ8VHmnYpoXTfg3HfbmGKq4b0scYlH5I6lsnweoLg4EK4n88JssImDENPsPAhN8KlWsQC9NuDfW2dbKImR2h6qr01btbFVo6IpJVz42lg0xqShJnxkEb/CGBqCBdGuAX9E07MHiq8yCfNMmZaj39YkrtLaPc/ye5ptjNwL2xXZiH1ye6G8Pxf5PCh9d5dOVT7o1kAKaeFLTZVM1zbT+J9p9d9cEwyyC3lD5WDp+8pSSFBe/AYGsIWDENDMNfuXUtFfepqLNWz04edWqUEG7CyivepWsgZUNgZrubFWY6IpJVz42DpKISUVJMM1qlPRxQptTI+4yJ5fLlu5+d2Psfca3xV7TFPb5TezZ5us6lk342nbevNo8YsyBGwFPjYZpFhWoq+505aOqb1XTvGbM371nn8M+W2Kvn8Jqs9qYgVTZScCIaWbDDHNsRiCmO1uVUumKSVc+qgOJybIhJhXa+swgeIM3NAANmNAAPwf848/BrLv+qSy1bJE927O5FCtmL6NFk2ZQnV3LafnB+dT6tt9TzRNqq4kplkrXOK4rHxMaUIbzv4Smy6Zsmkf8jRosmx5anJ9ir586Bq+fSrW6kT6LCBgxzXzg1/cbfqJXJj8QN89spH/TrheeadYsFtOdrUr4umLSlY+NgyRiUlGSvgkXeIM3NAANmNCAf2VWUD/h2DI08ObsOQiMD/Pc+e4M2va3BxKEs/fgqlT9tgeoXOPTlQSlaxzXlY8JDSiBkRKZLpuqaf5u8j9jr6YaE1qc3fe9kNINlFS5ID0IZJqAEdPMr5niw7+mPTkkobw4PVt/9ZvubFVKoCsmXfnYOEgiJhUlwTSrUdLHCW1OjbjLnFwum6l+l59tfnLyblq/nmhf7KK/ObMMdetHBy/iAAAgAElEQVQUfNq0rbxr/PoTbep9RWCDOOjwI6nag5OoTJXoE5R1lU9XPqY0oNaT7E9lumyFdz9C9Ze+SKtb3kSn9ikIDJVjqrRrJxX16kCV920rlubbmr+hJn97MJViIi0IZB0BmOasq7LkAZvubFXw6YpJVz46ByXEpKIAfZMA8AZvaAAayEYNvPz6Hnp15l6v8pK909jWslX74GXaPuXRUPFVHfKo0mqzrvLpysfG+YDpsn11Qy+qXVRIP8e2VzcM2V4tYlozbxntfuQ2OmT3D3EtsGE+ZtjdeO2UWteMVFlMwIhpbttpEK1as546XHouXdTqDA/Xm7M/oemvvUc1a+TR7JdGZzFCu0I33dn6S7914+ZiHaeumHTlY+MgiZjU2hE0YJYTeJvlbWM/AA3o0cDUl/bQf2bvN81Br5oSV7GVd9U3nqEdL04KhVH5z3dQhfPaRsLSVT5d+aDNEaVimkUF//eN+bSraAtVaVAbh39Fqh4JXCFgxDTPmPUxDbj38UBmfa7vQN07XeYKz4yXI1MDydLnZ1PFlx+jvF3fewy+q96Uqne/2etMdcWkKx8bB0nEpNZ0oAGznMDbLG8b+wFoQI8GHnx0Ny1bwZuziS5rcxD94ZLEU7NtN815Sz+mrQ/dEQqDt2eXbXB8JCxdetKVD9pcyUxzZEUjAQg4SMCIaWZuH8xbQJOmvU5btsRe8hf7VK1aiTq0bUVtW7dwEGvmipSJgYTvONaY0KdYoXeUqUrVxr5A28tXID5EpLSfTJQtKmbEFEVo//e6OOnKBzGZrTfwVuNtIye0ObW6S8Zp96LPaNmoiXTUpi9oe2xcXHV0G2oxtFvgM8A28948oAvtWbW8GJAKrS6hyr3uVAKlq3y68kGbg2lWEi4SgUCMgDHTDNpmCGRiIPnmT+0Tnm+RS7qq7sVUZ8hAmGaF6tdVd7rywWRCodI03hAAb/CGBtzTwK557wWu0JZtcFzs8KzJxQpsc/+9+utNtGHo7XTszsJ43O9X6UC/H3O90iFgNurbxphMa6Ak27PVWipSgYBbBNJmmnlLNn94JXnE41OTUhvQ8yq3qGawNKY6W35FQYWVhVRj83KquG9LaIk3VDyGio7/LR12VjNqeKHaKynCMjNVtlSqDzGp0dLFSVc+Nk6UbIwJvM3qGxrIHG9+NdQrM/fQ0uX76LAaRKc1OYjaxbZQV65Uuph+6XIx0batgZlU6nwzHXzplQnf2dzmxOuzHvruvP0xlylDd9d6hYY/WKPUnNQoH0hlM6dUy+JPb7psMM2lrTH8PlcIpM0082um+LPo3ckk/h0GldPgU3oCG5eto3VLVlPVSuVLbVCTTd4WX98rts3swJ3m4Mj3P7sVG1XjX2+ofCxV+vOdJT40wvRAolIjiEmFErZnq1GyjxP0rVZzLnNyuWxinPt2VQUaO2F3sco+uk4ZGjIw+NVQKkZnzzdf0+aBXUNFVL75OVRl4F+97/m1VNNih4WxaedPo+PKUEH7slQvFkNJP7rqTuTz1rt7ado/99BD686Ph/T4YaOo/S3NqdHxanHqjqmkbOTf2RaTrniSzePk8sM061AR8sgFAmkzzYNHTPT4DRtwHfH7mJN9/O9vzgXwOsvIJ1b/d8j9dPSGD7QZ1LDOdtGEf1OdN/YP8vHPvtggH7vjnPDf/B/y3/73JRvn4ydPKVHxTQ8kKkEiJhVK9plB1cmESulc1oDLZYMGVNStr+3azHvoAwfR9h3BPJKddC3/Iqit7P1hXei7jfm34llgNszDHixu2ivFVrmHDCwfe8uIWl35U+lqvyIf8dos2TS/Ur03Nbm5gE47FaZZN++S1Xrir1RigmnWQRp55AKBtJnmXIBnSxkX/HkgHb3xw2LhFJU/kmqOnlTid+cFdbaFt9xL9de8kXitmGneFxsvy4hVZb+J9kX2U+xdgMeEvAswGVOVzl+1TnTlpSsfmyeUNh3iBt5qCtfFSVc+0LdavdnIyXUNFC79lR7720GhFfSbMw+i6zoGn3QdZZr5+01/7kB7N64PzF+8pmnMU7vpiwVid1Zi0qZNylDv69VWu9Ntmic+u4eWfPgd3bHh6vil3q/SnvZe2Sf0NPB0x6TessJT6tK4bfmo9ierOnaIvflkPe257wU67ITagaB0lU1HfSEPEMgUASOmWd6qnamCunpd3pJd7q4rQou3umVvOrVPyZ4ZVzbNfHXPKBP9ULkRVdj5S+jBYJz0m/zO1PTOG1KuEp2dtq68dOWjOripQHM5JpfLZqMGwFulxbm9Guu6BtJtmvnk7C1Dby4mpO318qn2Q2O9v1/fZ1eo0Pj56uFDyqsJ0ZdKV92JfPi1WXu++px6/tgvfqUVFfJpTcdHYZpjRHTzLlGll0ADv1x5jverQ54/sFvRf21dZdNRJuQBApkiYMQ0t2rfhzb+VEQfvjKW8qpXyVRZnbxu2OueRGG/OaEDNb3vwACXCoSgTvLL0VOp3pwxgdlsK1OZjpr2JvE7m2u9GP76Caw0B9eCrkFJVz4wcWqtBbzNcnKZN9qcWS0J3sm2Z3f9U1lq2SJ8JVpEnEyXK2Yvoz1PDKYjdn8bS16G3qzWmQ6+4rq40bxp0K7Q7eF1jypD9wyyY6V50NBddMj3X3im+aCatbwVdH6F1tMt/00Db1aLUVf71ZUP2hwRTLNav4NUIGDENC9YspK69v0L5Tc+jroWXFKM+jlnNkFNlJDAmnnLqOpD14X+uqSruskGkq+v7UyH71hR7Jrr/3g/NbqyFfEz1htu7hy42vxLuSPo8EenlGjLuMuDpI0Dt40xQQNqHYUuTrrysVFLiMmslmzm/eMPFWjEmOLPFJ9wbBktZpBPnS78y3i6aMvfPegPHP4ctfz9UXHTzNueP5y3N7BCftfqILoqdiBYST662q/Ih1fEj9253zSXO7kp7V78hRfW5LNepb63HKoUou6YlC4akci2mHTFo9rmYJp1qAh55AIBI6aZDwJbuHRlKE+cnl06qYWZWF75rXDvFKoZ8oxK1FXDOm42xWsG3kK1Ni/2DvvaUPFYKtvx5oTnlNnM737ktgTjvLlsDSrT7yGcnh0CXtdAqSsf1QE3Skc25oOYVGpN33ZD8FbjbSMnl/sTmTcfxvXk5N20Pvb4MT9d/Jszy1C3Tmqrp1H15jfNfOJ02ZNOixvybduJhg7fRT/+nKgTXmXmFVzV1175Vaar7jgf2nMw3RZbab50+2Q6/5cpVPGPXenXhZ/TviVfEJfn9sfPUBK5zph0nLcRVXdKhfpfomwtG0xzKrWMtLlMwIhpxiun0iuxIIO6s0wF2nDRLdS42+9LfPFkA4A4bVGsLgddxDPXb39GB/17Ah2+fQWtOuNGyh94bVriSTXTbB3cVMqpq2yYTKjQdttYuqwlG/VtY0y5pAH5QK4Bvcspv0Ypqt741OlfX5gQX2n2m2b+PRvne9g4/7S/32nVsgz9sV3JDXNUTGq92/5UrAGxGv+n8pPp9NX7TfPeDd/Tztmv07RDBtGN4y5TylKXnnTlo5uTDiNvumwwzUrSRSIQICOmGZzTT4AN6jcvz6Z9H8+iuj9/QqtrnUunjnmgVBdO1nF/X9CGKu7bQhUef50qH1Yt6XU+HTmVjvt4DK2u14ZOfeiuEsdkeiBRCRQxqVDSZyzBG7yhAWggXRrgg66Wrdh/ivVlbQ5SPtwqynj5TTObzE8qtaGnRice8MXPDAvTnKppD1KFLk6cj3iXdefKk6nJiv2mmT87XpxEb1a9lvJvv0HpJoPOmHQY1Ki6U2ttB24u6IhJFyPVssE0p1LLSJvLBNJumlevXU8z35lH1apWprYXnIWDwNKstiWzF9ORY7tTUflaVP/Z6aW6WljHvTa29bpK7DnqTbFr1FO4hq6YTA8kKvAQkwolmGY1SvZxgr7Vas5lTi6XzW8q0mmaa/7jdmr86/5XQ7LJfLNa1wTTzCvNN9924BRt20zznA/L0asz99Jt5e6imt/OoSq3PkBlqlT1TgbnE7SrDhkD0xy7uQDTrNZnIhUIZCOBtJrmD+YtoBsHjoxzqVSxAk165HZqcmLDbGSVFTHzBKfcDa29WFVWgZMVKmyytGjia1Rn5l+UV451xZRLk7fSiM1lTi6XTXVVQEUbujjpysfGsiEmFSXpu5GTDbxvipnW7THzyp9UDgGLKhuvNNd99ubYIVqFXt4f1+5ML1AXGjywHNWrE3tXY+zDzz3Lh5HZZpr/M6sc/Wf2XrprX9/YCdqFMZP8aMw0V6PNA7vST2Vr0YobX6ALzyvdKeNqityfyuW+yXTZsNKcivKQNpcJpNU0d+v/IM2dv5jq161FW7ft8F47dVazk2nCyIG5zDytZefOdsOtt1DtokJK9ryxShBhHfeXt95H9VbPpNUtb4q9A7ogMitdMZkeSCIL5vjArXNioqvudOVjY9lsjAm8VXoBTODVKOnjlC5dyu9L1mmaeQW79bw+cdO87Ig2NK7sIJKN8Vvv7qVp/9wTR2mbaZ44pay3df2Biv2owsovPNNcrvHp8dcVze46W2k7u66605VPrvW7/JrSCodWix/IujL234dO6EPr8vLppPH73xse9NHJW7W/QDoQsI1AWk0zHwBWs0YezX5ptFdu8b5mnJadPhlwx7ZmzN+pQeEUWtXoj5R/b98SXyysk/y6S+yVU9tW0NZbJ1KdM0+IzF+OKR2vwIoMICCBrgFAVz42Dtw2xgTeamrXxUlXPjZqCTGZ1VI28JZNM8frf+Y4GbFkbcVvmjfWbEp/LT+KCv6vbHx1dupLe7yV3IoHx54Tjh1Wrfp+6JLGpFb7+1Nx2YRp/ivdQOXWLadqD06isg2Op+97daaKG1bQW81H0RUDo0/Q1tWn6MrHJl3y2TTL/zKaKm38ml9MQlvrnEbH9+tWold0ivoVnL4cPZWO+HCydxYNf3bE3q9d1OF2qpBXFaY5lcaAtDlNIO2m+ZRGDWnak0M8yOLVUzDN6dMcd5Cb5y70OsENlY+l4ydPKfHFggalbT9upp09979r+5DnP1DKW44p6m6miQmATYOkXF5dkwBd+djIyeWygbdSd+L0tkxoIHMa4FdODXtwNx0We92wePVTukzzL0fm031lHkk4bEw8T92w/j5auapMygeRBZHT1V9yPrcN3r/1+qF15yeM/+sHD6KDl8yhN0+8l64ctv87E+O4rrLZ0uY2LltHu+/uGje1guHmsjXp1wrVqOb2ld6cbkezttTkpugdfuL3zOnHN+ZSrRfvDKyWtRcOpDpvPYiV5ijh4nsQiBFIu2nm55iPrV/Hg71i1VravmMnsZGWP8JUo0ZKT0AMJOIZldI81xw0KKlu5fGbwcq7d6Zstv00XBsk01U+lzm5XDZbJm/+tqvjYBsby4aY1MabXGlz4pli3pbNh3Kt+W5fwvbpKFrJOA2NmfErCrvRUbtWeNnsOOI4uqvs+Ni7oA+i6zqW9f4mVrlbnrWP5szNHtP805QJdNBrk+idQ66l/xvXPQqTtpterulywZ8H0tEb9x8Ud+DDJ7nvf+Zd/nxzQgdqel+/SNaij9vS82o6ZPcPgem/r3YKHbl5IUyzEk0kynUCaTfNKoCx8qxCSS2NGEhU3qMclWPQoPTF/eO9rd+pbLMW+Szv3Dl2t3QF/dxtNDW8uFnU5Yt979og6S+grvLpykcMuDpMk66YdOVjY9lsjAm81boplzm5XDa5zcmmmf/Oz++m8lxxMk5siMUKrVDUrbXfiR82tjH2bubbYq+b4lXupvl7ada7B1m10jzvi500blIZL97uH5znFUHsNNs17z3a+tAdtOjg31DLpx+MbDC69KQrH1v6XbHQcQBgsGEW32+JPR5XN8njcbzV+4fPv6Yf586n4xaE7zjcUvZQqrrnZ5jmSOUiAQikeaV5xONTlRgP6HmVUjokiiYgBpKSmFsVE1cSMy5iSvUAMZV4ookEp9A14OrKx5aBO13MdXHSlQ94q7Uc8AanXNGAOIiLV38rVyLv+eJU3tVcEtN8WA2i4UPK0+df7qOxE3Z7pvToo/dYa5rPq/kF/X5BPyp3clOqes8Yr3HsXvSZ99qp78ofS0c8NiV2jk3yNqNLT7rysWUsSNU0r27ZO3YQa/DceU3staB7Rt9Bebu+9ypjX+z/lQlYsebvNlQ8hg7f8V+YZrWuHqlynEBaV5pznG1Gii8GkqXPz/aeYdH9DPH3BW28Z25S2fYtYhKvqlpzeEs6ZezwlPm4NkjablBtmUzInKABtWaji5OufGzUEmIyqyXbefNrofg9xGyU+SP+/YdL9m+fjvoom+bKVYi2baW7a71C2w+q5h02Jl+7YqU99MI/yyRs3Y66dtj3utrvc//81TPyV55USGe+3TfBNPO1heFbf//7ke9q1hWTrnxs0eXi63vRUZv2v5Js/yf5SvPai2+jxt1+X6zqeYV5c68rEp+NTpLVN8f+HzVY8c/IuaJO3iXVM34HApkmANOc6RrQfH3RsZXkwC5/KP5Ocm3s7mWVh66jTeVrUb1npytHLvIRvy+K/b5+Cr8XF9LZaevKS1c+tgzcURpQrnRfQl2cdOUD3mo1Cd7glCsakI1rvToHxVd+B95cTkkEYZzE1muxPZtXaXcv/oIeP2wUrajQlB79a3ma+Oxu+mLBPu/E7PIH745vhVa9tinTfE1+IeXPLG6a13XuQJW2r6cV10ygZpc1SspLl5505WPLWMCrw1Vj86sDnjnmdPkI7aBP7Ku1hzanMnt3057839IxV7eNn7Atdhkm/Gzf/1yzL7s9VI7Wnn0j1ftoDP1QpRGdMGliaN3p5K3UoJAIBCwkANNsYaWUJiS5Y/OeId62nNZeNIj+n73vAJOi2Np+ZzYn4sKSgyyggmQxgIp6FcTAVRDworBELxnJUZAgggTJikQVRUX9MAImEPEqigQJEiXHXXbZnOer07M129NTHWamgRG7/v97rux0nz51qrq63jrnvKde7ydcYomlMaJMtGYZAzqtPHfqMuIbV3fdt2v6ctTYuRInq7VBg1njDasp1+lc59aIKMxAwdQPUbZORcMyzPywmSnLzA+JWbLMkhOIdrqR+2bZ29hyYM2Ba2unf4q9Fy5zAte+/zqGmOoVMXN5hCvn2IjF1ezEc6WVoPnz2+Zic2IjKW96xbv5SGJ5zS+ODEbi4ZN470MbytWthEABzXOW5GL/nzaMarYJ5T6bjtD7HkFk/2I25uOD+qPU+d3Y98BUtPhvKws0a1iAwHHpmyq69l+010o+dg4Zx8+x6MCxKHAEIchWKEm4HFoFZXJPu0sTeI2vhFRA1MQFyE5Jw+U1a1Dt3LcqGjhwpkxz5MVWQ8zx7Sibc9INmJ8t0QjlR45DrGBvZuY6YOR9sq6xLBCIFrBAcyCOih868YWNgHHmxL4oUZAoSaOafBeq3ou4Uz+4wnaofEFm3K0odfpXKfeFFt6U6nei1ImfXbkwdN/FuNtR7fz3Lq2SQyqj/LxlhmsHynXKmtgHMYx0ghot0Pn1WyJi11dS3WdJx5oPsF9siPvrW0lP0rGwbQ/U7XifJusmfXgOz12O0sd/RFg+u4/VwQy+80E4tqxHmbQjSIuIQ2bde9FwTE/p2WZ9AMySY+lkbNJb9r62drLsfW3tHYjrwD9lDnw56j00Pr4aEUV1bI+GNMLaUiPx6qJqhiaBFmj+eM5v6JvkzAWmRp5mKtG06UpLCTS/ujAftXJ2on/QTBRecuahpoVVQMXRYxFcr4mh54su8nfsCPCv/aQAp1g5LmrPhq1CI2aj8A6sNFJH57eUQGDugokok3NK+vepci1RULYKSh/dLO0j5N/1yPN7EcM80vR9Lt2thyaRlV6n5X0j72rU4R9dsoNbPIT8bV+jXOIu5ARHI7lGS816x/7aiZ5fev9G1z7qMntecMp5VL3kLMtJe528slVR/a/PXN26EHWrlGtcIeNAcVeZR/hky0GolPBvcAJOSrUr2PSBFLqdElIJpfLOepqGDU+BjYFtFLCobg0PNbuTE4gd7NEbcemyZxdJVStV6q+N9MbT+t2ywN/BAhZo/juMkhc60sIWkZeLxMHdXcBXul20kHr8jS220immLIZHZQH2pgY018lQno1K7g2RXlRKeNL1IZGbhADz2eEDJODtaip608fr1mULLdBscE6Z9aEMNDnUfUsn/Ulglo0se+vbml9hls0DTU4gz4GYH9cja/V8j0G6HFQBNZethC0qRncAjYLm4FsbI3vdSqkCxcKLCZI3u2D/7+h7eajwGTEzVyKoRm3d54su8GcOcHIyudyH01bi4fS3ENSuO2K69ISwtrBwr0H7Ck8NL7NKGjfJKmkQAE/6divspw+jsEptVG7fVuj1lM+lw127MSIr2befNjHKfQy7gfYslWYtFB72+2On3UOnoPrpje57D/qX1j5KCpdWXFMkgeZFlQFdhXsdz7xnwd6OyXYwW4uIv86WaMj2P4twbOMOlFk+WHVOXegwTXJUyJs/NvJp8lo3WRYIQAtYoDkAB8UflWhhO7vqE1Tb5mS2dDURQFZ+xZTX6JxYarE3KhfbMy/NdP+w0FqvZHTUIKug0+rgpeuFHxJRDo8WWyQRaMR1eEgoy1vbm/khMUuWWXLkGxNv7aK83iydzJITiH0LRJ0sexub+TeynW7kvvF3Lrj3g6oDndZ2IKomdNKdCGp2Ilbu397f4fI0K0EzMWh3PDwEtXLlJFDFjwtp1hJRI1/Rfb7oAn/GbuCoPGRlu0ttl7oA92R8jDPNElBvZC941Bb2AjCTZIpuq75mnfSQfcs/R+WN7v2k737+sPlCj7TqXkeDQEttz+KrnTzykKkj2vxdToPqXJP/5rfGQbNwZtAOyB04XwqvhYgB4yRb7pm31nOPKJMjKinqq418mrjWTZYFAtQCFmgO0IHxVS1a2M6NmYCqiT9pizDiedYBzSeqtEbDORN0VSWdkgf2cT8N9vLjSg851WU2bmt3h8fzvGWdJL0rTxxpgWbdkQs8b6yZH26zZJklh4bDLFmBJicQ+2bpZGABMHFOBqq9k7b/gqBZw1SNkX1zC1SYrF/tQe2dI4Kx/Z8yT3JReDYHzcn3JGDakW7Sc5U1nOXK2CKjUXLVBmODpbjK13WAk5cpH9o3yQnuKR/72Qm342ynhxHpyCy+zMi+QiE0n/GbUMufwEK+i0Lj5ZcQsI6dt9LDQ0x9Ex3GaxmKe1qV1/hqJyH4VAJiE/c6Qq+2KlmYA4kRNyEl/h5EVK7kxrSt52kWMXP7aiOfJq51k2WBALWABZoDdGB8Vcvwh0R40umx2jM1VNgb2S+i00iR3qTTxWFDDZRT0D5+PdfvDdzSqp7HIyzQ7G4SMz9uZskKNDmBuoEPNDuZpY9lb+Mrulk2DzQ5ATsHjp5A8JguqgN0+tb2qD/pBd0BNAqaw5/uIdU1zq3ZCGOz50pyx13ojNKFF4TPCKoej5hXV+k+X+3by3NjvRGQmQUMGp3ncQsHzV83m4unR96O4/95CqXyLxZf5yNovrB1h4eXWf5wZRg3n0uGHAQyQWaDZpF33NONLNrX+LbXoXD43Andig8qdBwbx+u0R5UR/TwcBJTSdmlQN/exK7JTpi0SJRd9JDyk8GUueTPvrGstCwS6Bf5RoPlKagYmzV6Jrb/sYWFHuYgID0Wndg9gRF9ngfhOz7+EvQf/chuzfZt9+1hdr4GnD3fSxp+lGs1uzUjotZcfPNGHTO3DfXrhW6ixe7W7Sh7h2eoEFtkIx+k7eiKydEmUb9nYLc/JCs92t7pZm+VA3OTeyH2z7G1s1fwnzQEiYjp41IGqlW2oG29DZIS+jQjwHDxC9+Whbq0QNL5N/eBTX5p+9AN5JQ8dKQQ9tw7TsRrTVa15O3Zqsr2Vo9VPkmV7sQ+CzsnzYovv2Hv/FLTse7+uqbRA8/lPvkSnlBkS63Roq0ck0Oyo3QjD052gud2Vhbg3U1zGMazt04hIUM8/1eubr0Bn0ox8nD5blHtb9BAOmv9sNw93dmkKkefTI59WAx8SQKv0/iYIyyTJOqbm+RSnorEbVaag2kG/r/OJQGzw+Ke191r0q5H9V5EUCqMuvWCpaiQchYRnLZzmityjslFByBdOA8pNLtv6TqEskmOfPcAtUoDGI7vHdLc8cy7YVxvpvjjWBZYF/kYW+EeBZhqXts+OYhuJqqhUIRbfb9uJE6cv4I2Zw9Cy+W0u0JzQqY1rCDmg/ruMKV/YhB8zooaQf0yMhA2xawptdtilDJniZtTLTHeQTkROdnYoI+uSE3YYeb70wfH8CJ5o3N3FhC08NVUlAnMSYZj1ATBLDreTrxsc+djcyDrdyH0LxDlg2dvYym+2nVAQhkWsBBJnLSYtIhhgHtAzGHVrq4PSk4zlmO6j8kW8Uc5s/17BmmBWq5dafeO1jeX3/+s+Ozo/FSQU6Y2dKBf4fcbcLG90AEB98UaO3giSrCu7TiBy8UDGnJ3hdvlvEa3xe9Mxhko/qek0c34+auxaIRFoEet0cL3GEmg+Ht4QC0u/Jj0vvDANQ1KHIjbriNvzycscPWmBISIyUT/9sRPNpVeZ7vK85innH5fYxUuu/ErSyfC3VwU484N3Yoj2OOiXdYgzPou+c8ef7YhSuXJGafHDUoLLo9z81VeBCGwy42vZVKyasCayiGXFU08CrYXDFiK8bnXd9DGyfdbldKnMlBL8kjI8fU5rDpCMo2u+QGE6kxEdg1pdHlWtiuLPXNJ7B63fLQv8XSzwjwPN8oF5dclarHp/Awb3ao8+zz4uAWpqX76jn78UqAMsX9joQ5T98w8IST0vhYJVefoxnP1qC4L/2IqC0CjYm96L4JgYqZxBZOY5pJWKR1S7Tkj/8zBsB39HUG4G8m+7B2XvboZL6z9D6PkjyCtRATGt2wpPItVswnWSykK9sRahf+1CSG46MlOmKXwAACAASURBVGNZ2Fnbx5Dx8XsIT7+AvNBoOO56RBJj+99X0jXB+Rkone8swaFscoZHkn189BhUvrKTlV4IxtnYO2Br1AL27ZucYeHsQ7Yn4j6UHjQatzUrYdqmy8wPiVmyzJJD9jZLVqDJCcS+BaJOZo1bIPYtkHVasToIh5iHWdkIOM+YGCL0OJOn96WZeW6Amd9ftjS7b1KIT58ttTkgYlfmD3i8jR3tHvEEzkbnE69tLFKYZLe4O18XVBjtLOmUdDEUC+YnY3RKb0TnsO8Nc5em/6sHJu1/znCtZqOgufDxnsjt1lJSb3jF4lKO9O8hWSNRJXm79Nu2qCfx6KrhRrshvM6ovdUeQp7+GfPycJlViaxUARi2y+lxL/WBs5QSNem7/horQXlyl/Rv+q5HtGyFnG8+c33X0fJx5B45gPKHNzHPZhoy7THI7j7VbR/hyYLtlH8q9m7ctnimh4q8b0e6PccOG45Jpa3C2aEHhWAXNn8Yjl3bUCnxZwQ5CnCmZGPUeGW6aYCQ+nxx52FJp/w181Au4wiuhDIDsVc2I7ICgtp2RtaBP932OrHPPINLm76X/kb7qPA775Xul+/Raj/fWdLR23GT7624bM5+7a0s1bnA3hMzDvX9mtDWzZYFrrMF/rGgmUK1h760CLv3HcHHy6ewU/g41GuV4BoOZej2dR4nw483a4GkB5olyx85HjlTMkso85N4iJfSC54+aYBUF3NV6Skoce+96NElKCD6phxUf+wkl2WWnECZA/+Uvln2NrbM3cjzmyyw+2AOFiy2qxqj05NBeKiV5+9aIJaE9Wde6sYNvA/V1gKDImBPzyLvNoF7X9e4hcxbvusPz0MDkkcHBxPHFJq2gaf+7dwZInm1J195hh0gOw9pg3uNxZAvHpL+e9k8/QMHo6B5a/nuuH2xEzApQTMPf6bflpSdi6eGNtOMLNB7Y8x4V8hTTuNM9aTjxt0jPVIOmvV0kP/+Fyt1VJqVOjpXsiFueXOR260U6nxx5lQ37hMCzDdNnuAGdgkgHnvvS+QdO8QO1jNYLeStSGVkYdXWeIa3q+0JfJ2XdJ9HKDk7kM8IKoXSi9YiMzjUlHlpxrjxPpolyyw53swX61rLAoFmgX8kaObgOLZMSYzq/x+0fdDJyPziqysQEx0p/ff767+T8p7HD3kOz/z7QQlkWe3aW0CrFMiV4DhELXnXpdTJSTNw05lNOHLHANTo9aTr7/b1q2D//G1siu6KTTHdMXGsg+Wzizdk176H1hMtCwSuBXhoZkR44Op4o2l27C8blq5UB7cP3u/AQ+z/lO3r7234lv2fWlO7z1f7zZhjR3KK+t2vTC70VTTeWGHHX8evjmyR1K+/A77dbHdjsS587DmM3NFDutyfvsxjByC3HXbWNyaZG0t0xyPvPiDJ1QPNDz7fEDfVvL7fqtEvOg9oJr2QiuiR7eCIiELB/E99GtvUYxdQZvp/kG1nJSTfWO8hIzs5HdEjnnD9PX8ZGxhZu7TzCEovGebBsn2saltUe9GTAf34sk8Q/8tCHK31FKqP7u+TzvKbjr/5MeK3u4N9/jsRlZZrHO/3MywBV8cClpf86tj1nyb1HwmaKSybGs9pfnVCXxdw5hPgy29/wYgpS0D5zX+nvGYzTwPNkuWPHC1PszJs60Dv/qh4ZTeSe85DzdZNXe9yzhcfIGv1fByr1AaLHaNAnprGjfOsE2EDq50/YycXH2hySDdLJ/UJQOGxK94tzo0lIqruLEJDi+RJbzpZ9tazkPP3G8LTrBIObnQOaHmaKdR8xAvmepq3/RSMbZ+fxdhLz7gGieojv+qYKpFhkZdVK5dcaz3pNTgPvL5xRLdB+CGqAyov7Y5K+Uclb/LR0EauZ8pLTwWKp5n0p/Z6nz+kXOzgWxuxPOuFxiaz4KqUjs7QdJG3mnui+W0Zw1egMqsrzJtaCDf9TqWrYutUdHuilmdb9H2ilLaCTR8yb/cuqYZ0Sv1HXNwp5AlPn9RfyDhNsqxSlj5PCetGywJ/Gwv8I0EzH50ft/+B50fOxp1Nb8Xy2SPdBs0CzYEBKrRYNZXs3Se6tEfJvAsoYB/PsrKPZ/6+36WPfXa1hhif+xpCw4AqlRyof0sw7m5uRywLJfS1Gd0EGpFvliyz5GhtBI30R7Qp8fY+5fU3ct8Cxd7yfNLS+eeQxbxC2SwHUQqLHRni8/ti1tiZJSdQ7C2a46o5zczjT7nJIhZtKad5BstpZvmnynatc5rVQsiNjt21zmle+2EQ0nbslGop80bgcHGZ11yhyf6AZh52HT1xPnJvaoJDz/dHjezdbqA5gpGBTblQ7GWldKJHhrfSBetaa6pRe6vJ4ONQs7oDo1rvNQU0n2BlqkqyMlXK7zTpoCQEkx+AE9tz9Cyn51/UROSkZ9g9UeyeKyFxqC4I3+ZyyE5iJm4Wem0viShHqu6ni9LFys+eYx3G61rKusCywN/XAv8o0EwgeeX7X+Hm+GrSiHFPMxGB3VqnBl6e/w7ub9FY+o2HZ699fSJuu7nm32aE/f1Iyjtqlix/5ewaPxc1DrnnK51sMQANBjtLhfGmdoJdePEcUgc8jezoChgf857bPUYYaa/mpiQQ7R3IOvk7lwK5b6SbWf3zRw7lMIbu/QGdrsyUmHKpXQ6qIHEClG9SGwMYe7EvzR+drsa4BYq9lbYkO0Wyk72h4/OQL6skY7c7MKxfiC579vQ5+ciT3UeAuX/vG4M9mzNzmzWX+BygQ4qSe7+SykKRhznvNyfR1YbOW/DNlkKoEZsZmZfkqZWD5uB6TZA4ZgCCj+5yA82tYnfhsT+KQTulEzUc0/u6gmaeJ28maN7Xqx8qp+7xiAgjWyoPyeVA+BjLhy7D8qHVGtUkbjTVs562lmeby6L5lNvncbfyS1KZKGqykiMiDmwugyLfKk6fYoFmXz4O1j2WBf4mFvhHgeaTZy7gv6PmSGWmqFFO82MP3SWFXyt/q14lDgO6P+URth3o42r2ZsKMPBAzdKJT5uRlS1A1ZTuO1+6ARtPcP478RDkxohbiV7vXg6Yx4x9OZQ4Z/aZGWmNkrM3om/zDHSj2DlSdLHsbmZX+ge/p/92OvpeHejwoi7HTroxfirHTnIeO3jazxs4sOaS/WbLMksN1OnUiFIuW56NENNCIkXf9sM2BcObpXzhDm5CK2I5HvZQHG9vvU73cqhVtmDTat0MOo2vALzscWLraidKrV2XcICPUdfTWTu9+XMByjZ250XLZ3srRmqski0CzvCxU9rqV0i1bum/BZxt8B83k/R80Og8DkodInmXyNBNozlo1DzlffoikhwZib5UO7CDfjpuStyJj1liXqgSaS3ftJSR9M/ru+WsnXlLswVaFeDLvHZBdqGxWeMeeRlXwuG5P35GolvQTzrQZg3o9HnX7ffeE11D94DrX307U7YCGU4ZI/xbWRJbdLTpIp59Psgi0EoIINPmD/1j/C6quUeRECytXqRed1qqJ7K2x/B03+fPMkmWWHG9tYV1vWSCQLPCPAs2BZPirpYuZC5tZssySs3f9dlRZM1TIvKmXu3SeHYCEZ1zEnNg3cTbEk6zjxZG+eWLM6pu0KTCppINZcgJRpxu5b4Fi753P9UPNnD3CJepoibvRdJln+Rcj65lZYyeSQzVlfcm3vpo6GbGJ6BrSaeVbQTh4xIHu/wlCizvsGDXJGXatt06tZSCTPKPkXabr69SyGaoxrKWrno3kodQUubPgFfNAszy3WS5bTydvbE+yXprOakufGYd6OT8hst9Y5G7+Uqq4cO65eZj9TQNDdhTpxG0zLHOIxLfBQXP2B8s9ACj/G9edQHPY0z2FpbuM9s9fO/H59BirBNkm9S1TQPOvL72B2vvehiicmvOS0G81dq/2+NaLos7IFlo1mNW4TvRBMwPIMi+zdD15nyWuPXfCPe7l9tfeXCez5ATKN8XofLWusywQ6BawQHOgj5CX+t3Ii+2fW/ajwqI+wvwkHtYlP5mWm+5IvwGITXQPh5P/boToRW2Da4Z3OFA/bmbNp0CTY9lbfWHhURmiKyjFocKKYk+QN8uT2XOAvHgr1+Rjp6w00ROsNvATrI6v0Wa2TkafK7qOgP8hBpRPnCnAT78AkbL8ZQ5eeHiy2nPIy5zEvM0UTkwe0msNmkmv+Qw0i3KufXnnXpqZj1PMLrxx2WaNG9eJGKLlIdTZH66QQHNKl2mY+t3dqFZF24Ou1jdvQHPmomnI3fKVxE5ty8qQqj1cb9DMy0316e5Ag0NvmwKaf5u9VmK0PluzDW6dMd5tKh9O6IZymUdxssVAVNu2wONbz2tCy9O1LoXXQsSAcagiIwyTC90zfCqqndwgyWwwuJPw1aH55BGeTUWXFeDYdTMDzyeqt4WjdHmUaNbEVW/arHlplhxf3jm1tcVMnfxZJ617LQtcTwtYoPl6Wv8qPNvMhc0sWWbK4SWolMybevUYD059DXF71rnKTilNr7XR0xoms/oWqB83s/oXaHIse6vP6uRuraVNu6j5w5xr9hyYNCNfYjZWNj1gKb/ebJ18XdI5KJbfX7O6DeOGOkOrOfjSSiXh+aec9IuzHhupMezPGrftl0KsfLfAJULrANJbe/M+EPjntYKJkMtbOXr9I9A85fzjUg5/iYUfSp5mCkXeXbMb3s5OcN2udSij5Wl++eLjCC1IR8mVX8EWFYO87T9IodiUPx018hVJfvqkARJQL7zrYdj/twm/RbRGRuex19XTzA9hBvVzIP6bVyVQT5740FZtfZ3q0IoYk+cfq+UiJzEW66BxHZBjD0fQlHc8GLOViuntDfi3IGnjz4hbN674dsmrLC7hRp7tGu9+7GEDs+alWXIC9Tvn8+SxbrQscJ0tYIHm6zwAZj/+Rl5sqW8pg/ogNuuoB4mIXggWD33jtZrldjdC8qI2TjeyvQPxg2vZ29iK4Y+duMdL9CR/8hn90UkJdA/+GeIG1JS6vjKxmOWbPNK7/igE5fuSB5QY87kn1AydCND+eTSP5aWGgEpzUSPvaNJlB6qwf+uFjStBp7wvchbqgaPyQHWz5X2T3lHWL3re5m2F2HugEJ1ZSb2HWtlxrUAzz3vleqsxZ3u7nlC/RjPPOdUIb9zAjp+2F7rC1c0YN67vnoO5mL/Y5qrRTAeyvEzh1qinsL7EQLfppfa9EOnEx5aXkuKHvbyig/wQ6kpCGzgy01HYfSTsK2eyUlQNcbrL/OsKmvkcojrV4XOHSaCeh5gbW4k8r+IRY5cia6H2qmL+kcykNOT2ZXHgrJGd1HKReSrWmRINUG/ZYl01OCP36XItUH/RDOH1fOycZGODJB9zYjilcTlQLvuY2z2Ztkhk95ju8i4r1yYzIs/MnN9myTJLju6AWRdYFghgC1igOYAHxxfVzFzYzJJlppzzY19ElUvbQKQbdTve5zIRD+tS1mjmF/BNyrmSDTE78jXXff4AZm83gXrjaaadzPhwm9k/q296o+/8PRDs5MhIQ9qIBBQmOgkTeQuqHo+YV1cZ64jgKjP7RnV1KfxYrXFvJ4U8L1pWXG+arpcz5vujE4Fxkk25x7zFMOKuXFbWNienWLPGt1GN62DVkGUeAivqC4HwiYxvgdqKNSxsmwFHOShVeqhJk64dg3FfC5vXoJnA/8GjDpw6XcgYm+2uwwU9GylBs9aaqidLbgPuXScvM3mX5YRc3sjRm7Dbd+Xi86VHMTSxN+yxcSix+CP8vGYHbl4/WAKuS8oWfy+4LFFkkkgnbhsjoJl7VguGz0bQrGHSs3c/Mh89WH10X5s/dpIfWkwcax5oJp1EEWNKXhK1g3DuOT5a6yk0ne5JWKi0lR7fiXzd5dfKCUUJdOdu/gJBuRnIrRCPKl07q3q3/bG3XG+z5ATKN8XX+WvdZ1kg0CxggeZAGxE/9bmRF1vq2+mFb0kEIUoSEb2yEgXHDyNtZHcE1YhH0EurMJAxmpJPyNewbD5MN7K9A/GDa9nb2ALhr51OHk5F8PhOrAQLq0/KkFhicGXEv/eBsYerXOWvTvJ3zihoVgvhJuA8g3mjM3NzfC4RowS7GhmQ0AoZ5948NePy8Goefs2BtBKsyu8nwrCZ8/KRzcC7kTVOJItCwUcMZKReQdo24vfyEGqtPGpv5sDXjDX7/U8KJNs1vs2OVxfmu3K0vZGjN2kJNH/7xm6pRjP3/H60+CAe3NyTlVqLw8vl13qIEIWgewOaeRlEW2Q0Sq7aANf3iR1M5T7d1wWav20+zy8iN3/sJD+06NGtAGHTnmd6HvHb0ywHzaFLWLh32RjJvtwjTAfbt7y5CJxJW5mLzHOUjz0wCk3++7je8ELpwRbdwO20Z977Ui71yWpt0GCWe7617oPYBf7Y2wLNRixsXWNZ4PpawALN19f+pj/drEU7UAETzzuSh1rxj2KWPQoV125UtakcWE+bk4u/TtjgKwGYBZq9m7pmzUuz5ATi/A4knX7ecgU3LyouB0PlplKnfnVda8bK37nM9FBMZiRRokbhvAtYaSY5q7PoOvLYNm6c5xNoJg+22vP1wK/ydzVPc6W8I2iXvxp1Sp2HLZIBiwefxuB1d0m3t38sCF9sKkBOrufT6L4nSmxCxKXDOFoQj1v6dkTtOyqpvrBadqobz7zkXQs0bcQZrsmeBHK18q69eX+5F5081xSeTfbmsr2Ro7dS/d+GPKSu+whPpC5EWNunEZEwGHQQcN9KZySTqEyhiMXcG9BMcuXfI3m4dk7b5wICNPPQckpneOKxfKF3WM+2ot/JTpeGD5XYxOWRYcrcY7VcZB5VdrrLHNRv19yQCnqH6i7QbIA0TOuBZs1Ls+QE0jfF0EBZF1kWCHALWKA5wAfIW/Vu5MWW+pb2816UXj4Y8nwoI+FX0iYloTWQmSERvbz+RVn8vsvmFurora3N/CCZKevvMAcIdFDTy/dUjsnfoW++zCN+j1n981fOptd/Q/PvhuBy+QaIST6KkLwM7Hn2fdz7RGWfu+evTkobzZifh8NH3dUJDwN6PhvMQJYN3DOrpjCBsRZ35/sEmkVAU4M3SFJB7YBOpGf9rK1ISHnRQ/Ufo9vj/2IGqPL6NsvcgM5XPPM2tcibRCRk8gePHOpAneqhquPOQT/1j7zB1NTIx7yZA3K5FJ4tz9H2Ro7ehH3vkxwEfbYaD6e/5apBTOMbOqE9Shd6linkRGtG1iY6UDi4OxVTLjzBEuqjUGpV8aGuHMhxzg0C7Zn3/BtBY7pIXu51d71/3TzNPIKAvydqJJx69hXZSQSauWeZR5EpPc9cDrdb/pvfGn539ThP+HzSS/PS66tZ89IsOYG6r9Czo/W7ZYFAtYAFmgN1ZHzU60ZebHnflKfG+1Z8gcobpkOL6IPMydlJicjkw0P18O1mu2bYpJEhuJHtfTU+uAQQVrybjyyWD0qNwmR7/McJcow0y95GrOR/mOB3w99Ek5OrkXz7Uwg+cxQxZ3fj59unos2IVsYUEFzl79hRjuWnzAN4/iJjanbYcewEO3hh/7/eLTYc/cshhSI/V5TPS4/X8wZTDeS6N19/TzPpSuki/J2gf085/xhjchYzmC8pMwdHwxq7WZi8y6EFGeiZMl5igPZoDLCVXLROYm5WNnktZNHgUrmh5o2MgWYCWnKWa6U8b+YAZ27mxGc81J7AednyuYYBk96EJdBc7eMJUo3mqOEvI6T5vdItxwf1R6nzu1lO81yWX9zIuV6xKIYBvYKFEReivhHwLziw0y30m+uT2q+9xBsQM3OlxKZNbN1EtJfe+lmXV3dpy83XDTTzecHfEzNBsyjNSgls+WG4/ID8zPZDiJrVA6khcYhc/K7hOcBlK7lQ+Fio7S305o4/81tLtjfviZ6OZskyS46evtbvlgUC2QIWaA7k0fFBNzMXNrNkmS2Hs2pmDF+Byqw2o5GSEmRKzgpMXpddpf6FpSttftcxNatvpJ9ZssySY7ZOSRdDXZ4o5dQ2GiYfqH270YjX/pcwErdk/oSs3pNRcOQYor9fhV8qdkPreb1dQ0dEWARiiQgrM8shRQ10eioYsSwXVtT8GTsCwK8uKD5s4fLLlQWmvxgihdMSUZQyd1gt9Jm8hRNHXbuc5kaMDIzAFm9kOyL1ov89yYi3qNZ06ZLAk48GwXbkV9y6fpjq6r8puhs2xSRIv9+Tvo55SFcXAWWtrGrm6FQpFcRtVzr/HOrnbEN4YTrOhsRjX3hL6RnEnKw1v+Ue4a+3FDCmcoeL5dofUKFk/+Ygrn/PYFStbh5oXrwyF3d8+wJq5e52y9fNWjUPOV9+iD31B2BtanuJ4K1312Dc0VR8wOctaJYf4vK60HSgm1Klngs0z2u22UUE58N2wK9vinxcY3MOIGhyH/hLBsi/KSLQLPLyKg/I5UzYFV6ebBg06+0RaOxyDp6QALmcBMxbm/uzxsmfZZYcs7/hZn3nvLWrdb1lgUCxgAWaA2UkTNLjRl5sed+UJ9KcGORMmzGo16M4D1NpUh4CR6f5l+57Di+9bJM8nQteYWQ3PrYb2d5mf3BXrA6SvFCipkUe9E/aTJg1n/yRQx7dvL5tJCBWMH0NSiSdkGrKEptv03cWScNBYI9ALJU6kjd6n0YMDBaG3fujkxqhFz2bPGGxZWzSgYycbZrrOX1uHs7JiMCJ4fqFfk4d/dGJ7DRrYR4Sk4otEBLsQF6+O6iqWc0mPY+XuaLQ34XL3Q8AyIrdOgXh3rvtSNr+i5TTqta2RrVnZZAGSIC5XZpzPKSmEx+uVi6MxnLtsE/xSNJiNy/1mZBa+Ovpebjz/ghNcMLBLRGOfb3ZeXjhTVkmUT95+HuVSjZMGuU8bFCGC8s38HSoQp76smweqB3aqNmT+C36//yA9DOvo0z/Lf9evJuX4MFcrpTnD2jOWj1fItkir3Ny6Wou0Ez51P7U2fZnfvPoBxrXrD+cc9KfOu3cXqQTT7PipF/0myjv+Fzn1ogozEDB1A9Rtk5FtwPyKgO6GgbNnODrRN0OaDhliMdUIJ0ufPSNoYg11ReT/eCPveVyzZJDMs2SZZYcLftZv1kWCHQLWKA50EfIS/3MXNjMkmW2HOWpsV6+EjchhcDR5j+kWUtkPf8SA812qe6pEXZZtWEwq2+B+nEzq38kh9tbzZZGNodm6fNPsLevXoE/fjiLqgs7Iic4CkFLPkWZnMtIHfA05GRgnNlYNJZEHkXA2QioMLK8EagbxMKX1Rr34qrVJaZSTduYV7dSnA3nzjtQtUpxGSd/55OUD8xYnqtWdeBf91KagV06UNi5p5DVTS7ABQbWu7OSQS3usEvq028UdiwPxeb9cpFcnUtE8OB/q/Z3bclR+C2yjWcItw5oJkAWVKO2h1zO3Cx6YMjt9yCrzyRDoJneX56fLT8E4xEJNAbUbzrYeKINI2HTSMngcuQeek5MRX/r/LSTnIzA8ko2vvLDG4o2eOKRINUSX8p+ykEzr6NM1/DvBQFFKv208t0CKCMG9IAOzclaubuE4dnyyKfMxS9Louj5NCd5KPT1BM3y94kf5Fxr0Kz8tsvDrMu2vtMwaNbjPSGbn5m1BNUPrvOozGFkjeLX+LuemC0nUL9z3tjUutayQCBZwALNgTQaJuhi1qIdiIst75uyLMT5Tm0QTl6xotNoNTPKGUqzX5gN7vk0Ghosknsj29vsObDw9SCcPuv0TFIoKLXk4IrS//JwWe6No7+Rt4nqgsm9R5a9jS0S/thp2+ubUe+78Uip0BDRU+ZIG9NLXVpLZGCHer2P5g9XhlZtYdJQdADiq068XqxazzmQURJH8et5biwxHnPGa35Q5qtOXPZLjNGZAJso75cfLIiAn1pfeL5u9MZ3pBxXZeN1g8ML0zCVyKU8mjhEWwvscI+q6ro57/8QWzFWdeLJwRXPI5czaKtFCcjrTSuFy73K7RgA5usBjybo/3wBIkPDVA8gtEp8KZ+1YMR2PHdiKBxV4lF6zirXz27fi0ELMZoddmhFJonmkhZo5nYPve8R5G75ykUURnLCprLyTieOYE7sm5i8+BZjL73gKl/nt9LTf3nzd7AvflE6cI4a+YrP+tCNpFNkfi5y+z4iyaGDAjVQq4wiO9GlPUrmXQClZoXVrW4YNPNc6CssF7r6mo889CedRORk3nbUV3srn2OWHG5vXw9Q5XqZqZO3drWutywQKBawQHOgjIRJepi5sJkly2w5yg+sXjkJblpHRhqudHd+qIl585tvg/HNFvVQQiNDYlbfAvXjZlb/SA7V1t2/fgc6XZmJMgXnJfOS93JtiZE4ENMShQXOsNamzFt37GQhklOKR4B7j/ypq3u1NiZm2ShQ5oCLBOyeBMR0fU7amHJSpJ0tp+L+Qa10QbMoesMfOw0cxbyzLCpE1Dj4kpco4kDLBeJYDvOMSSGQkxuR99cfnTiYJ3KoiWM9835dv8tSQLRqK1Pf5ORkaRP7o2D/LnZwZGN8Z+z/hUZheoW1SM5zknnNOne/pznI20yN3cPbiSqt0YCFpIpIwOganlurtt4VDJ+Nss3vUF0OlR5++b+1IhK0AKhynPjDuWzKs965M0QqcaXWjEYQTe/7q9ATTHLl3xY+BzkxmZH1hPR9OG2lGzM3v4+DZjrQyGfjzA82aE6Gzx0m/Y1IyMYsuV21j3o/+Dq/5TWaRw4KxuW33oD987dd7OJ6z9X6neskt60aaFZGlcnv8bZvWvsEuXdfXjva2356q5OafLPkkHyzZJklx1ubWtdbFggkC1igOZBGwwRdzFzYzJJlthxel5nMRSfO3pB3yMtV8E0X1aHswUIofWlm9S1QP25m9Y/klE4+ibSR3YVm5ozAPENWRLVDwPlfD/pWIkj0UDP7ZsZJvq9zgMAZNXkupz9929W1P2pk70bB0Plw3FJPAs2nlyyTyMB+r9YND8zq7covFdlVnocq/90fndTKR8kjFEShwRy08Xdc+W9/dBKFwC4WqAAAIABJREFUCyvtMWpSHpKSi8tN8XvU1ho5M3Rq/w4ovHReynNNmzRAKpdXMG4lTtrikXjZgfr/exkROzcIRYW17YCcLz7EX6H18fUdizQZmHU9zRqlfZTgipSRs1xTSDYRnmn1l8pJKZtq1ECRPUexMlgbv7ZLpGPeylZe/0GPpRKo5TWa5b/z7wXlOi96L8IrkjOeVqAGmnO++ACUy2wvV0EaZ/I4R/YfJ4Gc6w2alcR6VwM0H+nWDbFZR6Vv+KWvt6DG7tUeodFy4q+oJzpK5SZ5HrS37y4nEBVFpP25ZT8qLOojsXJXE3iije4NvNVJTa5Zcnz9plzN76VRW1rXWRYIRAtYoDkQR8UPnW7kxVbeN04QQiUk4taNc31I9UzHvSrkPUks3VwiDzJKQnW1PyRmjZ1Zcsz+4Ea8MRF5v/3oaUbmHUsMroz9YXcjyx6F3yJa4/asjaiVs5vVST2Ps8Hx+L8S/ZASVBHhzGsXFQk0vs27vMWrOXbXy97K8l0UEkvluwiE+KoTbfRzuzlZkwkoJOWHSqA5/ccfkD+/mAyMrps4PQ/JVzwtq5bu4KtO/Anz38jHnn3OkH1qBIQ7P1WcuyrPfebh4UqPJfc8cy+nPzopS/KIDk6495uHC5OOL81wAmll4+uQ/IDJHhuHEos/cjH/y4EdRc6kDuwIR3qamygCX+FPs7I8RXnob7f4XBM0F148hwuDEiTCJWWj52U8+V/VMFgRaJazXB88UihF86g1CpkX1WpXy0/nYJrC4c+dC5JIx9SamkdYfj0dOH033AmaRURpcobr7y81kjzbaoesyrnEbfOfkFVS+TalfB7+zfXhvytB81NDmwlLXOl96/xZv5Xh8VcDNMvzla/89rsQNMs90Hn170W1bQtwslobNJg13us1Tov75PfXP8NN383QLVupZ3N/1hO3eckOTq7nQezV/F7q2dD63bJAIFvAAs2BPDo+6GbWou3PB1eptlk6yeXwDyCdOle8shtqrJhKXTJmjpaAW2G/yQi/4wEXwZAREqqr/SG5GnbyYQq53WKmTsGDWQ4m85a5N2etXXk4adEf3C6jMO5VpSe71aeNKw80aRCEY8cL2abSLm1mvWHONbNv13qDwzfkyvElMDhxJGODD/Jt03X0h0Mou7AH0sPiUOXtj1wbU57aQOOQN+crCeh88XUhPvm8AMFBDuSz0HoaxhpVgQnDxWz0/tqbs/kO6udAg7riusFyLycdHsiZnXm+PPf+EmCLjPa9dBHXh8CZmr2591vO6n2QMcjPnJfvNuUJMA/o7WTYJjtFffK6VO6Ig2ROSkVeyRKs3jJvqcOeQ+HJvxBUM56VA6oNIu7idYa5l1Sv1i8dJGx68RO0T5vNziOKvb6Uv0qeT35wIlpLRKBZDriqVbZjEWMKFzWKEqCQeY/vBQOyUv4wC3tfMMP9d34I8WCrQrRoHurKUVfKUIt2UF5H+qe/NMCj3BS/jn8vqFzX+dqPSM9TMrTza/0FzbwkWCCAZqWnP3l8P9gO7XEryeXrt4XbafeE1yTirZMtBiJk7w/Sdzy55zzUbN3UJVoeVUbfeDlRl7frCc+Ppuc1GNzJTf1fX3oDtfe97RcJWCDumQJVJ1/njnWfZYHrbQELNF/vETD5+d5+SLQeb5asqyGHfwCz2SaeSMCON+yGRuOKa8iq9YuHIhY+9hzKdH0eenlqesNjVt8C9eNmVv9ITtCk52E7c8QDM8v26ew39Vqzl4Mq4OXy70n3i4iCCTCSp1WLlVf+cDP7dq1Bs1YJJjm7sN78Vf7+y/zPUffHV5BYtQXiZ89w8+ac6doeUdkXXGRgnGCL6uYSQCUwSnnH3uR8GtWPg08CWiNeUK8bLM9r5oBNCaCITZtChikXunHjPJ88OkqiJK255MrDZeCaDnU4qIyvaUPrB4JQltWalntbSVbo2C6u0GzOeJ2S0Fo6dOIs2C5PZWQUSq3a6GFKDpon3PS9Zlk9spn98+Us93a1UwbDzf+LeByPrB4t/VOrb6KQeCXz9fylRRECCg3VIhJEQJzfysPrmzRyoF/3UGz4thDrPnXPaw4NcWD0CyFCD7bSSHqgWV52KrxjT+EhDJfpLWhWspZTjebgek3cDk0+ZaXF7hjV6Zp7mjnBHR+jqwGa5fnKYcd3CUEz2ZbPY6qfTOHcHFh7u35r1Wre16sfKqfu8QDtRtcntTng7f1my9F7f73Rz1t7eyPbutaywN/FAhZo/ruMlEE9zVzYzJJ1NeTwDyA3i/KEWs1cPI+s8K6HUeaFF12ERr4yaJvVt0D9uJnVP5JzeuFbUgieq4mQrzpmlm6bVu5dXC5i3BblPRNwnsHAiZyFW20umNm3aw2aORAT9Y3CtEcMUQeWWkvJzyNew80n1uF8q4G4uV8nN8B0ZNgoxJ7ahoMtRyO01aOSB1HuLeRg1Gj4qsElTbqMh/zqAV05iKvGSkuJiP7k1/To5ixd5G1Thl1rzSVliDj3UKutOUl79yNoch/w0GyuGy9RxL3P/N9q9ZeT//sUbJcv6jIwE0Dqs+MxqUYzySLWbnlNbq2+iViueQg898hSPe8/mUe3dEkGgFg4v4O9uBNVwrKpr8q8c/nYcEBds7oD44aGgpcTq1oJqF7Vjh9/LpQYrmcyD7aRNYByzOvNvld6hLzcFH9m7uYvQeWgeL4x98DSQZHycE5pJz7P+tlm4KazG8A9yfL+cEBIf+M1okkOZ0/fFN0VDcf0vuagWRkefzVA874VX7jqIle5tE11DHhUGbcbJ+rydv2W50fXXzTD7ZU3WoFDb53wVqer/W0K1H2Fnh2t3y0LBKoFLNAcqCPjo15mLdqBuNjK+8ZznbiZjIJmyTszaSAcVWux8iJvQcS4y2Ue27gDcU3rICrWyVYragc270O1+tVc12QkpuHizsOo+VATr0aQcuvOXMpBw7rFG3jafEZG2Fwhx0Zlb9+Vi/osfJVvGhMPnUN2ShqqNK/jtU6X03JRp7o4FNYbYTR2r75mx7D9bRHqYImd1ISgmXJWRXDYecvbpSbgRPAtSAlxlqqi0juV8o7iWFgjlzq9uwajYgV3751IV7PeFaUcylulMkRUr9jbZlQnOZt0pbwjjIU8ylW+i0J9fQGD0vwa0hOlc88is/88VLqvqRto5mRgu8q3x8/xA3HkL4fkrX3w1gtwZKYjuURtV1keCjWuWsnmBlyUfVPOb7IVgSKqoywHPPJcZSkU+uw+lClfBvbyzjlAoeNUnif41sZSHWSq6UxnL6VLMZDGGNh53iy9++S1zbLHuK55vqcDzRuoz2/RWNK7OndJHi5cLCb4ojq2Zerd6mKopjxhsgk9j4PABvVtqHOTXfKMkvd74oAsl958ntB9KUtnw77nZw9iKu5ZtpUth6hBE5E+kZGDsVZi4YcuW8jnGwc6WgzM23c48Psbn6NzygwW3h2PiIRBLFx5kASaoycu1M2P56C5Q4sLeKh5lqsOtAS62CAM7BOMBW/mS6HWr4zIxpLJf+JPWyPVaATSXwnE5bbk4xvO5E0aFSLNN2oku1QqK9H0zW04xMLfiYWc18bWege/WJ+CFmseky4RgWb+vQiqWZt5+Fd56CaXrZzfvB/jHUNQ6vxuYWhzytMtinL0ba7nX2/QzG0sD49P7v0EbClJUmoAf++8Xdv49dxO8nxlCs1WG4O9/UeBg2rivKi41hlVYXSt5M9VY+g+9s1ulFnaj60L0S7Z/vbN1/uVNvJXji92Unumt/Y2Q3dLhmWBQLOABZoDbUT81MfMhc0sWVdDztnfjiByRrcia9kQsuQrTXBLF9LmK+O1iSg4st9l5Yt3dcfM411d5C4EHA7PXY4ah4vzBk+Va4mbXhrnJl/p6U4Mq47CoHCUzzzokn2icXfmJeipOaIEHD5afhplTv7IAGA6Tsc0QniDJkj9dQduyt2NbPYhzypXFy0vrkCVNFZ+pqgdr90BtV/o6dKJNjpfsg3gqe93MhB5BMmMNCuqekXccXg+yrOQNmoUyn6pZXdU7NIJSYx9lxoBu+82XkHqD1tZOOg55FesjTL1ayPqiwW4JdNJ2nUgsiWiuw9CfumKOMXqLFOIaSNGxCXy5NBBQ9rvu2CPZhuQ1vciokw0Tny6Fcl/ncHlU2m4J4PVyAwNlcIQWSIs8vf+5m4fNU+zglb7bHANZNpLIT632CY/RHbAxpiuyGGgiBoP16b/5nrXibdLvx1iBEUnz+ajbq0QRipmA40DMfFSn6hvEQyMk955F84hvHZtVGnVGMnHziH5l50oTE9H2QfvkQ4hyHuRdvAQIitXRliDxtj0HctVPcwIzArO4WxIPGo9eR+alDmCpG+3umwSW8cJ9uSNDjbObfwBOSmpqND6Pt0DDvKwpW7ZIpXvIg8hNQpf/zhmAOuTDRVznTpVf+Ie4XtBXjBukzj7BeS8Pg2VUottyecuf3dpfm1Z/APu+nmM9JxNMd2RHFIBfSMWMuM6Q+5tkdHYVCIBZ7LLo2I+C6NkczCrakO07VIFSUkOl70JTH258k/EX/lRmt+XYhuhVI0KSNu5yzV37U1a4JF2pRmILsQfBxzYu78Qz5RYh9tPr5bAKDV75eqwhYWj4FjxO3el+dNYc6wlamX/Lsk+HVwbz8ZvQ8ntH7rMnVe/Jd5ISkDVjJ2ud67hU00lkE/5xjQHKEf+q/XJKPx9m2ssI9h7ufdkJLKLSl/Rgc2I6m+7yQ66qS4cOdkoPHPCZZND9bvj6yM1pbxZ0ulQSEP0iH4LZU8Uk+KF3HEf8o8cgCOJIXFq7EApvNtAhD/W2aU3hfOmj+0FB3tveAuqVA0xr73rMZ/oD1qgmQDdX59skcapcdb3KJ9/AoUJ41CCjYM3oHnzil9R7esZrhJyNAf+uGMUftvpcM2BRFsFPBOyCmUvFc+v5Hu7o+YA8drIvblj2+5B7KfTpTB1Pr8I1A/+7CHksjTp+nVtOLPvLJ4vnIlyScWyN0Z3w+/VE6SIE95o/h48wuY8e8/5+kV/++aNX9Fm5wtIKtcQtRYtcrOj6HuR/kB3TDrQ1Y08kss+eDQP1SoFu9ZGLdBMssmDnb9/p+uZYW07MgK37lIOudzTXLprLzzUyrluGW2k064/3Nc40b3ydYCv6bv3OjCfHXTQOjK41sfI/nCF650LqhHPPObjXIcjRvWRX8fXlCS25gWNf9r1E2fFVsrcPXoGqh/7VDqEuRhdF3VWrpAu8XZfQWts8Dh6ngMXOk2HzW5D2EfzWN1n5/wqhB2XOkxB3Y73+dItn3RSe5C3fdNS2CxZZsnx2bjWjZYFAsACFmgOgEEwUwUzFzazZJkt5/T2QyiYN9b1sSP7XWEb+KDBL6uCDfJGUbkjvgGT23xrVHscaDxQYpj9o99IVE38yWNIzpZohFuXMYDAmhIwS39UAXvH67RHo6kvCIeYPFabxr6HtpdlmzW2Wc6yxSACTmDgFG1naYaeLLFy2WvmHMBdv05wbV4lLy4lJwqcnetj+mNrdAdJ9s2FO9Hl4osu4EX3ORDEnL3uzyMCqDmxS13eTAKkA4pyWUkOHTacGD3GDXiRrDxbGEKQW9x/9recR3oirkcP6W+caKe4swK9hbYVG3xvWEusKjPFNST0H3IThLB9NDmyc4tUIikxjI07PbNYxYrs0KFf0gvFNmE/ZdsiWO58kYdcGhQHsoOiGOgqvjEXYdKzQpDjEpZti2T3yYSzX5SHKaL5RAc1ty16RThv6I/pWxmb9YKxit89SdWU7wVtphcty5cABLUwBvyGJfZm8+aCx7NoflUZ0U8KX6b5dff2cYzNvBjUecwvQY1gmjefluyPXyPaOOWzx3a+8gqaMXZ02aRg9mW2lNlJSfx2T/o6tEtzBzXid04xLwymABwNaYSVZSYzUOs8cLkpeye6p8jeC/a3MyG18H7J0dJhCLV2qQudh0C8CfrvfA9Zk0dPeExd9ZwEnucqMWX3f9oFXuSDpRaefXnuZNj/twnvlxqFViMec4X4rn/rNOI3jkNlFqFRrDtbiyoNxqPDWiJv+NNS/fTUqV9pepqVObnO8eXs5kVvHa0nNlq/PEtDifSm+TluWh6Cks9hXFof2LKL10Gu66pSkyWvYAbTsQcbI17zXW6TTQw4V+jVEzWqO/WgOU9rFEWlnGXjaI+OQSZ7Le/M+AwdUmczz3oj/NxqHrp3cZKx6X0v/o/lGlOIuUg21cOmtXEHA63fbi7EBHh6mtNGJEhRBsrG2crloDns6Z7gdcc9bhD8gaI1FrLUCeoDj8KhUPnurKwiz52nQ8KV7OCNDhFq5exkczsejsgYsAAOpJ88xw6KLqBqwRE8fkXxztFUZgcjJRZ9qFr3W09H+X5AHp4uAs27xs9FjUOyd4wJP1G1DRrO9o49m/YMwbMHSfwnzqbBncHIyG6SkZHp9Uf+u9l7HW+erXZtIOpkRr8sGZYFrocFLNB8Pax+FZ9p1gJJKpoly0w5EXm5SBzc3Q0wc3MSQIidt1LoWeO5zGqmHx/3KUY/l4joWU4wJ2qXiz6m8g+93geYfg9ZLPaCb1ryK5p/rwDUHpt87STf/KkfIjOKeYfYJqwS8xoVN/X7aEM8ocJnEmAaf/E/buBQGDJdJHRvWAsGSKe6HiHPH/bY3IjAQtGdlyJrofYqZ24zbewoN1NeispepSbscZWQf4B5jxjxkYMBDrZQybqmHcI9J/ZNCdgoTamTLi3Jd4LIPu4bcRHw8th0CaQL73N2g0qlkUeD59mJ5psWuZ3HplvD3vL3gufX8ucJwahMmbQZ/8c8m6HIf7GHwibsIuWBjEZ/+Zg8nLoKD2fI8tqlSSCQxf5E83Ra+XclIDvlPOXcypnXRfZWyvFuTOjwbD0DQ+EFaRh3SfFeFNmEgPPc2GUonc9AHbvGrRmZJ16mJATf2gjRkxZCr5ayKLSYlwmS58USKKUcUfJ6KxvZ+1CX5Wj4jpNZ+Nd+P0geTrX12+PAy/lGuw+CzkvH9Sa9Vq7Jx86iusudU5QHK0Xayu2nI5vWdArFj0IaOl6eifo5xZ79v0Lqo1TBRdchUD5C8UWJ3iwkvqNUxszI94JkRzrS0CnZXTYd3K0tPZIdBDkPYPonD0FNVvecH4DwPGnRO09/y5++BqWyk1we/9Nd5hsGzWTH6eNP4t/nZ6JWnnsUzv463TB6LGPSY236tGTUO7wa92YWR1SdDK7Djv1yEMeiDpwj6XBjU5frK6pprdYf5d/l84nXTqZrlOvdnnlrWYkp50G1sp1sMQCVEp40xEdAhyVp7MCpGDBT59S/IfLvk9E+8evM3Ov4wrUg0jcQdfLWrtb1lgUCxQIWaA6UkTBJD7MWSFLHLFlmykna+LNUl1mtcTCi/J2T5qjdt6TMHNxf4xhu/l38keYf9RLNmqDM8sEKMdq7Nw62lc/+pT8LBbvkyXrrdp3Gx52uI9lXUh2o+eEQr3QiQq362ds8vHdaGyUOtuUPopxW2lh7e5CgtAmFK1J4OHlpOFswPYf+TvVmvbHJ2pKj8GtkG5GT3XP4FUNXP3MrEq68qG1Lg8BHy5anYu/GbYtnYn+v/sw77wlgSAEKp6/w/gbhlPWwt848ofei6uP3uUqscaGq4KToglNdZiMjPQg3r9eZXzrP54B03IXODKjIvNo699FY0gHIUOYN150DRjy4OkBreMXvoXeQQGsFtb6Xh3r1zkkXC/qrNU/oFgKWvF6w2vrFGbXlv4tA8+FfzqLc7I5qYnCAAatbDjkPNbZ03yKBNbX1O7VfexQm6oylzvhyIMlDsrlifZOGeAJ7L0/BaJyOhjZGQvJ4BpidRFOuMaD/EHAnvFt+MvotfMBVF1vNUKqyi26gyIUlsXOlfw1N7CV5fPd1XI4WHerqHoAUDJ+NklEhPoFmyp+vvLS74gDVqRS9gw2nDkEW87Bfmjxa2yY648YPc1QnksYP8vkkJ/lSgmattZGAbel5Sw2B5n3LP0fljYqoHZ3+iQ6hjPTVzL2OBZqNWNy6xrLAtbWABZqvrb2v+tPMWrRJUbNkmSnHg4FZYVE175yqp6bIQ3cq5GaE2XJQPu+46hidaT0acfc0RbAsD8u1CdMgr0ofzvKRBSRcB5/vj7hkGWAyCMbkChL4tGelo9S7ioMEnU0BgYOH05jXL13p9VM/gU+2x2Fa3Fo3+zzexo4WtS56bROyZb2eTgIeveYJENkdGhxbfEOrvEbHJJIahmxixKOo06mzJRqycP9FONy1G8plyyME3G9U27zx8kOuq3U6R+9FRMdeeHWhe81cYX9lKpzr9wbC//gfSm9dpeiRgTBo2R1ELLWk7GuYde5+bTmKXynM9ge22Z96gdX4ljcjg+nDOJFHvH7Wj57ecNmzeXiwB2hWAnLh+yyYuxpAnjNo6x36ceZlt7Xhq09hXzkTv0W0RtXx46VQ6zObdyBqsfLQr/iu87Vao+zJrQjJy8QvHdaidccqqt8BDyDvg72JxOzwlQoe81IImpXvlM4coLEk01L6gfvcUV8/KF//pvfW6QJbSTYTPixJvcyhtA6FNXbNeV76Sy9qwB/Q/DMrGXczKxmn1i4N+wC5V9JReZkiosrI+yQTSjW8o0aqP0dr+ZPvBw5274W49APSen7u8Um45bmHXLd6HsS6S81/81tDoFmYTqURnp3JUmoqvb9J77Mk/N3MvY4Fmn0aAusmywJX1QIWaL6q5r32ws1atElzs2SZKSf1570CT2+xndW8uq6apsqNN/2bA162caByKCwY2GPg6EMaOmU1iMTJA+hobDhSgsujxrsfCyfCX5OmovR+sSfRdYMB2el/Hmbhs90VG0N18MsBTLPMDSy/1L30hsZeQtp8ry3lrN3KG2ep9dfTrPWmiDbnauNELNLTWC1nCp30iB4W7ZWvoqdZKwSQe5rVcujJHlpzxwNE+ehprsVyd/smKz2mztGg50cveQ/hR/ch/5VBiiEyEuxefAuB300xCRh6iXnd5GkEBjzNv7GoAQ8QZQSQCt9nbb3pMEn4Xsh6z0PNvfWaSyJEOmnYgIfB5m3/ARmzlDnsTqWI9Trm1VUerxAxegfNGiYxYfMQX2HkhuzO9PsTGJHdTkSd3o2vm83F0yNvV/0OeIA/Lw/98irUQrn5q12M1PIOeIyBl7LPBtfCnHLLVKIGtOcAHVQJvxdFCvLDQ72IBD7n+UERzS1ify/DQvs9omeKZNMhSe70d1Hq9D6Xp3n3I/PRg+UjG2mH5ixD+Z895wK/N6PfPNjYIWvkSmW0lsgm6naKGv4yQpo7S3V522g/QGlWHhwYTBCFXTcY7CS/0/Q0hzNP8wJjnmZhCozGO6fFQ6LXVzP3OhZo1rO29btlgWtvAQs0X3ubX9UnmrVok5JmyTJbjpp37hL7kNZ+S+E5lVnbc5PHfhTkZYoAmdwzSqQi9tkDWD6bjOBJsL8goF04bKEqOZmQSEeEWlVkZ/eY7iIsOTe8PyJOKsJ8BffRhm9x2bkSoRex/w671NsjXFbUfw5GOVESmZVKkswoqofqcZpf5MEXhUByL6vRF4E2+gSc3UJBBXbKDorE2pjR2BtxjyTaw/FHw62Tckk5zcMFNvHoh0eoqODARWNjxg93iG3cM9zfaRn5BlJpK8oFp9JpbmRCKntc+XuhzGkmuaIQbT53w+tWl7w5FwZ0Q9hFhUfcSDg0k09zh4AmzTkx0BArTnN1drk3pZxmyiEmcjb30G7F+6sCrNznszoQcOU0i96LogHgB070TyJQ6p4y3o0MznPSiQ6vBDowJl8U0t+LG4Hh6EkLXIRLQm9zZBRiWM6zPKWBSxCBZvrt0kujELJPFq5cdENeSCRil37EQnfHIPSvXfj8trl4doI6aKbbdjyryI82CG5pTpx9dj6aPl4XvJ6xco4nXJaFVau9S4K/k2yKaqCw/vpZLN2CkYW5N33QTNeLPMJy2TT+niH6xU+i1AI68JGD5mXznIzewpxpNpbRI6YjpUo9lE4+KRFXEmnZ53csl0gqjbS0NctRsH6l6qUUDk+NGNLdmhAzF81HRRQVr1ltRB/RNbQfOP3qYg+CL34tXxu1+B68zWm+NKgbSuUXkRi6lPLsNK2VleYs1K3EodZ3s/c6vtpYfl8g6mRGvywZlgWuhwUs0Hw9rH4Vn2nWAkkqmiXLbDkEWrMWTnMLa6WPXcSAcbqlesiDkPfrVmQfPYT8g/sZ07Gzzqf7BsLB6gDHIdiRh+iCy/jrlmfQ+CVnTVTeeMmrAlsQTtV5ElSOJqQkY3T9/CNUvbBFYvOOnbdK8+NLpC1rh3+GxxPnIIQ9S2rkiYqtBFvSOdez8sNYmZuWnZG894hLdhSroSovXUQgKuXlMcxLVEz+UliqPFKadYTj9y0om7QHmWVqYWXV+fjrUpRLNpWn6p06DjG5xRuK7Cr1kREeh+hTOxGWfRkZZePxYe25rNxOtOu+soxPpj+rxcvZWOkHJRlYNsJRaAuRyHJcdmNhydVfecXrTQn1L3fzV8jc/RvCSpZEyO33SPVCsz9dg7wfv4a9ZBlET1uK//0VJzFDZ2axPO/qduw7UCjVbeUtmnU9L48xeOcWn5bElmVzPal4bKvjMCMOmoG4nGKQeCW4HMIYQVS4o6jeEBuntJByiMlPdN2YYS+BsKBcBOcVXcN+yYyqiMiM4rHMYzPuYuthbqHplHNXfuNst7lo1Nvxy7MvoG7OdsnbmHnrfUjdvEXzvaA5t4IRLlF5Ld76J7+Amlk7kVL2VmQy0q/cmo1Q+/nO0hjxd5cOeFLnTYPtTDHjb0HFWoh66BEUnjgqEboFxd+K3P17UMhqDPOWHxqJ/ys/Gj8XOA8yqD0TvApNT8kOt2jOl60A2+Xi/NicqDgsKzkFfzlqu+5rc1cGWu8ajoKjBxB0cwOEP/4MA5TR0vtM+lGdZtIj56ticiO6OaxNB9gYWzKV9yFBcNdPAAAgAElEQVRwaWPevPT3VyA4p/jQ62RsCywNGuViz65pO4xeqeMRll78XjhqN8LOe6fheGK0NL/qsvJlVKM6bch/GFlaLkJbPYrQ+9owHdIlnUgXKq2Wc5KVc/p+vdv7HN2uMxzprL50kd6hrdpK+uXv24mcK1cQ2bAZwh71zD0mjzNdRwdJ1Be6hngARC3p6AkEjenCSoTF4Y+uH7jIpCQm7lfGwHGweK0oKFkepcaxWs1M5sVRAyTQvOnmKeg4+X7N7wDVY26bthQPpL0HW0wMwh57BjlsXXXsLCbdKmDrV3TCAOTv+gV5v2xGNhvbqdHL0PL+khLpFlUReGlGHrKKXxtXd9plvoF7UtZKshEcBkdK8fvmuojNn6BbGqLgT1bSK7ICpsY4D1qo0cHguIvP6JPIFQlTAkL6XuRs+MiptyHZTkHygyIOmj9ut8XNY8y/RfI5QGsaf+d49M7SlpsNg2bNSIIycSj1upOJOuW/7RkhhgFuAXo3y1UBqlR3rbu+epj5eFH/gns/KJyz9McTVVqj4ZwJ0u+i0GqeguXNvkJtz5B5C/OWXzrLWNrZN6puE5eXW1U5nR+80UlLlFly6BlmyTJLjq+2te6zLBAIFrBAcyCMgok6mLmwmSXraskhLx2FJkffXNvrEhF6H24KTc34V09U3jAdJ6u1QYNZ491Gad+KL5y/lb0bDZbMdP12hgH6KMbAfYWB7upr3EtlSB8wtkH8aXuhVH82l+HkYyccGJXWF+XTWI3WB59CiTZPSBtX2kjR/1F5j+B6jaWNMa9rqUUQdbLzYyhRkIKI/45E6J33S/fxUENO3rLtl0KmhxM0tbgjCKVTD4PYmKl+cvTY2c4ayqxxbwjfSFIpk5Xv5SOR7VsH9glGw/qeYeyHuvdA+YyDONmEheE+1Uaq03xhxyFc/uMQytxWx+txUr4aornEN5dq+b+kN5VYIYBftYpT51OnHTjA6qo2uS1E+jv9Tn+LjHBeUzYsDVcS2qCQbdRTEl6V9KY6n0m72GFLWhpKsr5QnjrNQd63uKZ1pHI1zrE7Io0bjSVt2JI+WIfqJ77A2TK349Y3XvN44/c/PwSVLv/qzO0Lr4tb3nLWItVrn3Wfw8oefYyIboNcIEvyXi+jvFVWj/TlH12lhuSyejKwQ6HZHe+/gtiPXwKYl6vkonUeAExpb5pL1Deq18rniVJH6n/Gay+yWsUnETVqBvLqtXTZ+xZWF5tya7NWvMbAyIcIufMBRDzbTzoAkebpJPKAOVBy1QYk5cRI9xFApTGhceKh+pxASmQfAg4ELOndIfuTbGUj4Jj1/jLkblgngW1iqJbPAdKRanXTHHCGozhQ6kNP7yzJ1Zt/dI38fVbTieto5nrJwcmGzlskgCpvR7p1RWzmMWT/m3Er/Psx19hfWLYMYZtW4cdyXfHYoj66oPnhtJWMG+EtyEtIyeeJdFAhW4foUGZs9ly3WsfkbV66Og95+cVrCkWyDIn/GGW/XsBYrZ9mhxJtkcYiTohRX97oufSukffUVi0ec1lY9mlWT5438jY/k/YKO/TSjgxSevb5/TwiSE12ZyY7XC6b3ci9zCSDg+bQ1T8Ka9sr56Y/oJlkidi589jhZZkZS10RCTQ+yZOHs8NaeTnAoqkuV4gB7RKTF+JyWBlD+cN66xX9fmTnCcRO76J6qTISSb7uEqcIPyz25T1R2zP4IkvUgUCTQzoGok5G5ol1jWWBQLSABZoDcVT80MmsBTIQF1uz+5Y8sI8qCRPlnJZJ6KUKgHdPeA3VD67DkTsGoNkwZw4Wb2qbaNoYrng3H1mycr/yTVX+vPWIrcjcnhpNb4Mu+p17HwhEEBhRNiWo5r+L/s7De/uzOqSNG3iC5gPPdkPF3KMImcJKf9Ut9hKaNXa+gGY1c2rppGYTXzdKfzEgW5qxrquVMzmcwAjBMos920bYW+kA5sQgZ3isEkRe+E9rhOVn4M/+X+DO+0q6qX159XLYv5CHcDoQ+q92iOwz0qN7vo6bCNzKZWWtmoecLz90A/v0cM7ITARRIrCbNpLVt2WgXcQW7e2yqTfGyvQJkU78GkcVlmM5Rz01xBvdfLW58hnyg0GRt/JcJ3aoxerWKvvFw5KpVFXHFeqgmQ4ZJs/Mx7/zV6HlpdVuoFnUXzqouNL9Eeknyu+lknULXnGGK1ObvTgf+w86UKEc0LwpIxhkB3rR3yxH9rqVLtlSJMEXHyDryEGEV6osRZzwwxv52kcs0lSDmFrdeBvuqlkcERD2RBeEtnxI8tZTRICWZ1+0pgtls3npyGQ1gNkjKb98T2o8i3gpZOkTh/Ho/3rBVjUeJWevMjQN/AXNki3HHEDPo72cz2M6JQexqJjF/4dYVoeZGo1d4bB/s7JbibBXrSkdsJIHmR840f+SXUNbPSIdeJg1J+nZegfWck+zlsHM1smMHGKzdDJLDrd3IPXN0EtgXWRZIEAtYIHmAB0YX9W6kRdbs/umRiomJ/0617k18zhloIDVQy7LSMB44yDndJc5qN+uudtwiYArhcWOeomFICoAM4VHUzkdBzvRL5jxru5pvpo+pMCpI6mIGdtW0kUJurTANvdMKBlROSCwl6uAEswLSW39VwX4bEMhiDWbytEom9pzzBo7kRwj3kfR+6SlE7eJkfw9o33TGgP+W05QFPOIZSBx+AeIb15JcxkgD3o6SxsQgeZjA/qhzMU92N3mNdzXo5lLjipzbwTzNC/W9zQbXZc4KJZ7H+V2UhszvbHUOzQyqh9dJ5rf8vuVZFAi7za/xlGnAUpPXezN41WvNTqf9B5GcmzD/4OgKxfwXrO16DuShdnKmpotjYJmmn/Exj4wZzyqX94GI+RQ/JkTan4vhWMTMRYBOVofB412pqjMZ0CaIjao8TzuyH5jJU8zb74cnvmzNunNOzkRopzJXO9gRmtd4jLnNduMiSON5TSTPDpMmz/+gPO7wg5z8i+cZ2zoGfip9XK07VlXeuSXyw/i7o09kRURh4qrPSOilHqZNScl/SineeFbqLFbfMikVm3iausUSMDSbHsHUt/01i3rd8sCgWwBCzQH8uj4oNuNvNhejb5RuJZ99TQXSQiFhpXoM9iVG83rSMrrP2cmsfzavk6PiajsBb8nmZWDqsnCeqnxDaZySO/N+AhPpC5EYt02KDV8hC5oFsnmMrk380yJBqi3zH0Dr+XB45tkOcDhMpWbRQrtXvluAe5ubvdgdD2y/SxiZ3VETnAU4t51rz9t1thdK9CsZRNfN29HunVDbNZRyOcFyeLjlhhRC4UMvJa/vAd/tpuHO7s4545aozkVN86ZK6wsOXR6aH9EMwZknpeqHE+RTNH4+zpuIvt5A5rVAJgeePF2yTRymMRlKoEb/Z33s5ClVpR5XsxC7q1OvtpcNC8LXx7mRurFr3G9q+yQJu4993eVM3UT6dktby5CZm6OcF3ia9qwzCGoeMUz2kHU7+T/PsVy1y9KIH7HmTiMGBAshevzdaVOLZtb/q7aIYrIRpRiQsR4oigEHm3DS3jJdTNib63DHGUesfxwxS/QnNBaCkWfEPcpFiwochEbmExkyx9W7WCM8y+ADnNSS9VBye3r8GvZ9nhoyQuShK19puC2lI240rwDqg9X1mD3fIgRGxlQTbqEy1JyYNBhdVr7cajb8T5Doq6GToYerHGRWTqZJUdu70Dpm796WPdbFrieFrBA8/W0/lV49o282F7NvmUkpgnJqTgRyYm6HdBwinNzwUHOuZINUW7WHI8NpQjY8k2hcsg5c/HR5gNQvfeTfoHmXet2oMYHg3G+VAPcvNQdNGtt+rg3R54Xy/Xkm1wewsk3ysrNLV1/4LMdqPj2YFws0xB1Xl/k1lWzxk4kRy3UV+/10tIpY+Zo5P3GchAVHi6RTKN92zN8Kqqd3IAzbcagXo9HXaL2zHsf1bYtkHLn7dGRqLL/Yxytn4CmLxaFV6p0hLz+9610bjCVkQUnFi9Fyc1vufJS6RqtMjr0u6j2qtG+KVUURS/IZel5OUUA3uXVNTEUmushqnOs9MqLdHKB5seeQ5muz+tNOUO/+2pzpXCSg1eGIfjoLnxUdy56TrnddYl8DSNgLG/czgSaoxnhYNnyuZqgeeLlZxCTc94jzFvU2eTx/WA7tAfbH3gNHxxo6IpYWbGmQOJ66PRkEB5qZXfdysPxlV5+bw/PtMCrEXtrrZ9aEQn+gGb+zCWs2sGYJcVjpzeJyJZ5W75Ep5QZKLzrYZR88hmJiTvLxkjz5nwl3R4y9BEpNN9omoMRG+npxX+XyyK+hyuM7yKiSkUQJwSRDxptV0sno8/351ug94wbuW96fbd+tywQyBawQHMgj44Put3Ii+316JsoF1UOpCsP7+uxoeT5zidbDGRsnJ2kUeT5f8ohHZrICLPyjiJpwAqUbOgs76PV+LM5g6j82h2z1qLW9oU4XucpNJrq7vVSC3Ok+7U2hHyTyzetPIxSmY9Icn6Z/znq/vgKztdqjZunO9lPRRslH6a1phxvvMIkiAAd5TLmXklFeHxdiWRImT+rFybsS99EBzAkh88XGtOoctEo980iHCrfBs0XupPPKe327ZqDaLq+J2MjLo8KK91rgV9+6w3YP38bPC+V7tWr0ctrAvvSN6VuIrBgGmg2MRRaOb/l/eCHMUQQRR5M0aECnycFw2ejbPM7/JnaV+VdiXhjonT4836pUXh+6eOuZ/y8ZgduXj8YibGNEL94oZveRkEz5fa+/0mBi+jKSB5+8rSRsO3+CSefmIb5v97tilgZyEKzKXWFh2tzhbwJqdZa49RSUOg5Rr4rWgdzyhraSkI0IijjJIxGJgjXx1fQTGlATU84ydkKiw5zTvROQMkrR7Cz5VRJhcY/jkdaqXhUXbrKiEqGbGRIkEF7G5FlZNyMyDE6B4zIMksns+QEYt+M2NG6xrJAoFrAAs2BOjI+6nUjL7bXq2/KjZs8ZLts6zs9gK4asFXWyCV23ikXnpBGmjacRvqnBZr5b4frPYfbJ7p7vbSAZWr/Dii8dF7odbg8dzLs/9vkRthEZWao8ZqjfKr+PGEZbj64ChfvTECdoe5eUiN9MzLlRXKULN9ackS1bokgjerhymvdankglfKN9k3NuyePTAiPKkDE/KEgL1/Td9w9gMrnbnr9NzT/bgjSKjVE1dfcr5XX6CVvIYXAUuMhrCIbiXJ2jfZNKU+UL8xl8d8IjBJpkrxxACICGXycyXtW5gVl7V0js8fzGi3QzEELgSAioxLpxD2hBS8uRdn6t/qmhOIuX20umpfRG9+RdJcfntB1WusIP1whz+T5cV+hanWxp5kiHb758orbGqZnAH6Yk35/Aib92Q1VGSP6E22CsGh5PqpUsmHSKPfcXW9As9Yap/WbEXsbkc37LgfNfD6LDlzUbOUPaKZ85tEMND/LGL0bpW9EYaf+KNP+GRxb/j7KbJyPZHt56bGlCy7hcpuBuKmn81BXrxmxkZ4M/rtZssySQ3qZJSvQ5ARi34zOE+s6ywKBaAELNAfiqPihk1mLdiAutterb8pcVL6RC13C6gYHh3qAZlc5KkWpKvLSfkobzS2F0gjXyt0l5Z3Zbm6Ekqysh5H+HfxgC+LWjcPpci1Qf9EMt5myfcBU1Lm4ARceG4W6XYu9SnSRFrDUyuvkm1z5RnDm/Hyp9jHPR+RK8Oenth+Dap2Kw4+v9lwyGgKp9AjJjUcllGJmrnL9yZvcWSPjRoLlufByr5zbfMpldZ4Ht5P0SJ271a0OtnJZ+ODF7/HwnxOQc3MLxE12nwty0Jw9cAFjInaGvCbuZuXFpo9G6UJZjVb2d1Hosb/jprQht5PWeGn9djVCoS+/MQf2bz8W9p+DZsqvzpg1VrKfGsGeiNvA12Xc6HzSk09y1EDzjsnLUGvvKpxploB6Iz3TAPjYbem+BS3uzhdGwBBo3v/p79IaZtSTKl9PBmzrKnXhX/fZpTWR/ldeFovPBdHhishGfH6IIiZExHTcfkbsrbV+8ucS6ZbtNKsc0Kwloka+Ion3NgpG/s754mmmCg10AMHzzCkCwlHpVpwbPRRVcw+4TZlTobeg4vw3XYzaWvPJiI305qM39jYi60bW6Ubum5Gxta6xLBCoFrBAc6COjI963ciL7fXqmzx8ttxD90llqFJZHeZqrA6zSCetfEEaVslTy8qALGz5luQF4ps8I/3Tks09liJGbzUw4ioDw+r0llrlTghEul7e/B3si1902wiqlZ3a8ayz/FHI6PmIauKs9XwtNkpGQbPIyyzXkedtG5XnS9+U7Oe89rZ8PhX0fUIqF3VqwAe47V51Bu3vhr+JJidXg7x2VfoqPPvnkiTwTd7C7QlfuJjOKSd9wfxkjE3ugcicS6xOciuEtWmvWnPZyJxUW6rUQLNWqKxWeTQOfLj3zMcl0u020aEQv0AebcBLJclzn13h7uzdyZ/3qW5qhVF9/bG58p2L+XE9slbPx28RrdFo7gQXQNr931ES43VKl2mo0c6TeOmqgeai9YRA9svBc3HxEsuvDWUpE6xcMDFEUy1u3rzNQ9a6Xivdwoi9jcgmMjg6gJEfIPgDmvl6RaH1rUY8Jqy3rpxTaz92HspOyumF6MtHQaD50Ac/4ZaTYobsPTd1w72v9NadmkZspCuk6AKzZJklh9QyS1agyQnEvhmdJ9Z1lgUC0QIWaA7EUfFDJ7MW7UBcbK9X3+Te3cI6TVykTQ1mjdcEzaKavDy3mUIRh2cNQf7+Xa5SLUb6d4YRpxBov8JAe3UG2uWN10jOHL0UlZq4h4qqldfRA4jcYynfCIrKTpEX/UqCuO7rtZhLRjzDnNxL7fXipDjehlQaGTf+TCUbO59bRCpHhEwkK33CUJQ6v9ujXJRS70/6LMX9KW8hqF13xHTp6fYzyQnu/aD0N3mNXj52s87dL/2ml4fqTd+U+imBCpelByTUxvJq5A9f/upT2FfOhKi0mFwPEeiSvzvZL8wOSNBc6vQ+VpZskBTuLw/T12Lhp3G81OVhVqYoE9u6fI47WkUI+0YRJxX2rJPY/0XeXdF7xteT5PKNMC1obvElDCt3fybIFRFBP2h5d0Xz0giw9TUFwYjswu4jpblE6R4lV22Q+qY310U2Ur4nFFrfcExvQ6D5JVY3m+pT8/ebIiAu9euDiow3Q9TOhdbCLe/o1xf3Zx1QPtcsWWbJuRbfJ2+3dDdy37y1hXW9ZYFAsoAFmgNpNEzQ5UZebK9X37g3MJt57RJjG6LKpW0uBmQ1ndQ2/nL26ed/fwyOzHQX66zR/qnJ5n9XCxUV3acHEBOLPJZygCUqOyUvfyQCYkb7pvcKeGtvuTy+CRc+Q+Zp93aj603flLmkyn+TrIw3l0glYn6v1g0PzFL3AnHPvhoQsI/8D+zJF7Ci1psYOv0WqdvErPvnT2cx9tIzgEp0gdw+3vTNKGjWCpUlGSlFpXa455/LvRqgWXQoRM9zHTLFxqHE4o/AD1zkpbDktbwznx3+twLNx55pjzIFF1QZry+OGuAqVdVmUANV0Fxj1wqJcEotvF85J5KOnkDQmC5SBMSECp95vIrylA9v85BdUTNMqloYvYgl3egcV1t36bCQ1vH8eetdqRX8+d6uJXIAJ6+XbQQ0y2tdy0EzPzwTrXtZ9khUXLtJb9k1zRMbiAA1EHUyOid1B45dYJYss+QY0dm6xrJAoFrAAs2BOjI+6mXmwmaWrECT48tH8mSX9iiRdwHZiEQ4MpExfAUqN6+j+kFS22BxT99TDY7h7o09Ia8batRO8hzYyLLOEh1EABP835bSf6uCZgEY0dvUyT2WfCMoKju147ODqPV2TyTHxKPm8lUes9do3/SmvZocrRqtXCZtqum6wkT3fF76XV5uS6sEl0g/b/rG8915Tvre/qOkQxheB5xk2Teth/3D+fijVGvcs9SdhZw/nzbI5C2kcHg10Bw+d5gUySAvWUPewYIDOw3noXrTN6VtlIzDXJYeM7na73qHQnpzR/R70t79CJrch5HAuee0Kz2LovdE/rf01s8GJGgunXxSKjd0NqQWgiatcnkr9SIzjILmJjumo1nWRkOl2fi6y0Hc8IrfewxJo9tsGNDLSQamxVjt7eGZVn+NznEjh5XBgxmxI6utzA989NZXrfXEKGimtYDKdf3yWwGOnQDuiN6FjkdeAOWC54x/A8ksn7lc0m7h63GpbEPUXqJNOOjL91LrXTRqb7332Sw5ZvbPLJ3MkhOIfdMbV+t3ywKBbAELNAfy6Pig24282F6vviUeOofcCT0R6UiVRsQBG5J7voabWjdVBc1K8jA+lBw09661USrPJCeNMdo/UWilXu1oer4IjOjVOCadwqY+L5Xc0So7tWXFb2i4YQhSKjREjfmemzCjfdOb8mpy9IAYl0vAOX36CBQc2ls0lg5EdhuMsEc7uh5tVBa/wZu+KcPrT7DDmJLsMEZ+CCMPqaWQ7cgIT6vQwUWJ8c5aq2res8h3ZiF3y1dSuSGeE0n59PdmfCSF1IpCkpVP8qZvynuVgMFb0Cz36pLsqwGaRYdC9Cxl3rXcqxzZf5zUVXkt79TGDwYkaKYSdtxuv/b7QaqBfOpIKmLGtkVOUBTi3vPkMaC+GQXND24frHpwI3qXyd55fZ5g8zYDE+I+RZbdvS6vnEHblzzk1H7tpUMxeZSCFlu7N6BCdDDH89rp8DN3+rvgB1V8rfR2LZHrYwQ002HpqwvykMT+lzdOMEkpNZQ2EH50H/JfGSRcWoMZ/0S0gn9Cbdz0yiHqrd2+rJdaMv1Zm8xc5+SyzNLJLDnezG+98TNTJ71nWb9bFghUC1igOVBHxke9zFzYzJIVaHK8+ZBkJDLvZP+nEc7AibJd7jkPJe6sL9wsq+UMcubpKRVmIGLnBjcPp1E7iWQf+GwHKr49GJQbW27WHKFOohBTvU0d6aTcCJIdlGWnto55E7cdXY2kJh1Qa/QQD1sZ7ZvetFeTIwcwoa3aaorhm1E4GBubzebhqeXhlsrwYDWh3vZN7rESkWWVDc4FJ566MG2rMJfRSDi8nDm58vO9mBy7VI7m0axVLBd6taGQWm/7JreREmhyWXrlvETeOTnwIe+ZmRt47vmUh/QqdRDltMrfnZQq9UzVyYz+Ke1NTNjtHgmCHlEhjWHamuUoWL8S35fqinte7SbsG60BvM68KNpBDXydHjgUNbJ3SxEQR0MbuV1Wp5YNIwc5Pc2+gGa93PPoSe41qb35FujJlgBqUXQHP/DRW1//v70zgbOiuPb/GWCAWQBFBAVECWtERONGIoqKK0TJAxUXFBBFFBQQAXFDBRdABRRwCQIajOK+REDzcAnGuD5BXEAlCqKsgiwDCMPw+vRYl7o9vVTfW9NT3fPr/+f9o07f0+d8z6nqOl1Vp/wSVNF+uIjbnj432R88nJd4n8j/XXwU23TsuVRwxVW277Yu+BcVPTTGKjC4zb7112r5VHDVzVR4wolBXa7992z6AecDdMnSJUenfbp00iXHRNuUAg43gYChBJA0G+qYTNVKcmdbEbYtvHkCHfK1e+XRTbkHUMHUJ10HlJ9dP4aarJiX2vss/CkKtdxDV1C1VXtnb8O83EQ17xXHX0OHDyo9Z/OTe5+mZh9OppWHdqcDhlztqpNbMiLOmRVFsNwGOCL58jt2yq+ScxjbguLeKwbCLIMUs+t78gooZ3tRmeQxaOlqtoNA8dHj+3a96JBFj9sfOnhGWea0rucZlLuziD7rOZtOPKdRGSwfvvEjtZzWg3blFtD+T5adLWROonLygoJuVHL+IGrdvAqNn7z3OBqVRCebNudMNJ1JnFcRMjdflmfRLbePQs59125VvcXHFZ7p/7m47NFzQbHs9fdsmMsyhRy5qFeXrvvQwuc+oUOeGURr67ajlg+7L82VZzlPmeCdNKsWlBN6sU6i0J1b0jygbzU68vDSCtp+H1eCPp557T0XqwTcOAX5S2zbyL/6RhIf5uSaENuvvD11xJfoK7NJmkXMcxG3lRc/kKqAL/SU9zDLup++ZYa9z3xJq97U/PpL0t4F/PGJL/lM+iC7dfbfOmXpaicm6pRk21TiDfeAgKkEkDSb6pkM9UpyZ1sRtn15+QBquNl9Pxi7aMvYl+igpvXKeMtZ4Enc8Mxlf7WWxz5nzVwXWeu891jLgntQXu/SpXOq9rnJlv9b44GXuibNohCWXOk2KEFknUTSLP/OeeyUKEpV7dq7qLBD2dkLVduCwj4oaVap4isGsuKIGHmJvN/ZsLqSHPFBhY+Z4n3yK6TzvIV9PwweQLV+WkQLjp9IZw86usyjVZbDy8u85x87yZ6xfnVeCY3acTnV2rjMOpd6RuDgORu/pWaHf9svzLLEHlt5L7/TOLfidPJyaU5OdMzEijbnljS7JTvOtiL/ezacnPbrkiXkfH/tgLRq7F59k6xHeSbN8gqIN2r1ST327DOrpCWGmexDDtp7XvP89CrzYfrdINm8r935gbE8k2ZxEoMzfi745R57n/nbLW6gDsNP09JWdMVkGN6ZvguCfuf2d132mSbHVN6Z+Ai/AQETCCBpNsELGnXQ1Wmb2NlWhG1BSbNX0a3PJs22j6Za3upcaje6dLny5mmTqOSNZ8t4O/eYE6hg2N3KSbMoJiUnWx8OHEMt186jdWePpH3POdV1oOSc+Qs6o1nEgEi+vI6dOu2kqr5FqaKIpaCjs2ToYoaQzzCteu/QtCNiwsgRMsPGpYgN8Xt5xYCQ9dPEiZT/3nP0wYG96IxJZStoh0mauQjU4y2nUStrppkLBoWZHQxrmzO4nYmlWyw5f+Pmg/IsulXw4sP065xn07ZKuCU7Yk8rz9DzxUc5iTaRLSeZgS5ZQs7q6wdQzRWL6J9HT6Dzhh9Dn9wxjZp9PpN4pcMRN7lXZxcfLr6o8SeqdfMYOryVdZiydPEs56TrPrILynHBqVrjZ+7Ae3wAACAASURBVCq9xeSPcL+e3pveb9TH2rOfY3/Qkc9odlYvdwoP+ngmr4oJKuynylvEoPxhTl6RwEmzM77LM2lmJteM2EXbd6TTuernwfY+80VnTqQ23dsiaVaITNUYCBJlmpwo3r1BTPB3EEgSASTNSfKmZYuuTtvEzrYibPts0tNW8lt2Hxzz+al2O6p/n/v+Yee+QTEI9Ao3nvXbuG8TpQGO255EeZ9zLY991qlZ1N9m/lQSRHl2UK4wLI6d4mq3p3WsSg1uOsE2zWvJrS7feclRsYX1k4+l4Q8e1UdelFY4KMwyb+HLsLZ9/cICqv/USNbG+r8cWnvh3dSyWyk/IUusCvjI2s9YYBWeamklvPXq7o0e1eXwImnlSsW8X3T90lX2cVN+M71yjIa1zRnfzqS5ztIPqOjeG9MK4Dl/kyqutP8BVHvKc/afyzNpdtt+IC+9zikoLVYlJ0B7irbadsQhaV5z6wiqseTf9Ebr0XT+HSfTov4j6OAN/6ZfLr6TDuna0bVLkpcG775+Ah17RHrSzHvqX7j/Y+Uq7HJbUYmBoPbsFZci2Zc/8AUlrqoxrrKv3Zk0bx5wLpWsW+15tJcbfKFP0PJs/u0/3y6h2S/uThMj9pnnjp5B2w9Qe6d4vZcy7eP85Knyrsw66WIkv1OCeAb9XadOQc/C30HAVAJImk31TIZ66ezYdMkyTU7YF8k3l/ai/XcsS/PItpx8qj76caIGdV0TXWdiK5aXermVZ0ZUj60RstflN6MWMy0drGuppWMDS8fd1z1Ae37vXZRITmKCzmiWOTmXSsrHTp3YrohaT+li61FRSbNIhnPyC6nOzHmerce5NzbvkVG06+N3U0fmBJ0h7DfIVWmyKz/8mnZPHEF1itelbt9UbX+qOngsNf7tCLP86jXoxfs+oi6fDbEKJbWzCiZNpDyrgvYF/1OVjj+utBhQJkkz/06urOtWFMlpQ7Zt11ksyy1BdePmjLfyLLpV+9P5tG3qXWnVxN2WBsuJO+u847kZqf3w2XKSGeiSJeSsfGgaFb41M3Xut1eRQlkHlaT57fH/oB6/jFWqwi5ks04qqw2c1ctV49ItsRV1G7z28KvyVkmaRRE/0Q8FbX/x609En8ZnWs895zW67OKqrl3MyNHFtG49f4ArveSVJKq2BfVduuTI75SgZwb9Pck6Jdm2IL/i7yBgMgEkzSZ7JwPdktzZVqRtPONcbfEC2yM7D2hOLQZfTgX1annO7G/7eQvtvOos+35OJEWC6uVSPid4S4euSjPNLCPT/ZVycR2ezZQH/n4DuF8cZzzLRWguabfI97ipqAZKKgNUuaLztp7Xp4plieOXgmal/BgFNVeuxL5+UB/riKnVZW7lonL1JlkzQ7nV6elnq9LSRZtp9BrrzFfrEufZcuI8aniuPeP8Ud/h1GLLe7S7/1203ynee8iFPaLokqicrbL3W4ffMk6af4s3cZxWeSbNziROPkao9tS9RQDl5bnMRl7SXZF9k1fceSXN31/UnfYpXkO59z5LBU0OdP25YLChagP65sqn6IyTys40L7r7r3bBKXkpdFAbkFeuVJFWEjh/F7Tiw4u3W8G2oH5B1XduH+bk/lQUg/Orjh/Ex9nmhKxHO7ydqiouy+Ajp7gifl5N60SDS6pRo322UrXr9r53VG0L0kuXHB19itA1yTol2bagWMPfQcBkAkiaTfZOBrolubONm23y4IkHc+sG9aIau0uP/HBefLzRhhrus9Zu98uyOYHd2auDfRsn6H6c5ORj10cLyuzldD5LyHJLJsWxU6fXeZdOX3ILbW52PDW5e6yrfbp85yfH7YxWv8G4vAdRLD0XyylVimSFHbwtfeYdavBc6Rm/bteac++k/I7t6fa7qlDDXd/SoPX9qeqeYlqe24aW1DyG/lmrN4liSaLwWtDsWSpprlt6vE+PnZPpmA3PKyc62fpNPgecPwq5Fd1yY+GMt/KsVC2SZhEDXkuD5f/OOhd/uTB1XFm2nGQGumQJOSIB5SrqZ8+4rswHN694FH3M3Avn04X/UyPtNt6eseHhiXRC0Qtpe8GDXllCp6BENtOkmZ/v90HRTb8wvFU+Vop+iPuQLcNLC515rcAJ0icoaZ7+5G67TsGfjq1iz0R7VawP8kvQ38MwikpWknVKsm1B8YG/g4DJBCpV0rxpcxHddt8MWvDBZ1bxjJ3W19nq1KPrKTTsqgtsHy1e8h2NmfAEfb70O2s2pw71v/QcuvAvnUz2XxndktzZxs22FRd3t6sjF10/nRpZS29fuulVOumbskmlmKkJY9+3vaxjYLYvs2Xv3LiF9n1sEG0oaE6/mzFTOWne8ez0tIG/3wDO7RxkcUaoOOJk68m9qfFVl7u2lzC2+TU41Q8C1dr8wVWMSMb4SJpNrY6zZ/bl2SJxPnKmg1w/3UXVYq97uDDTzi696L2p71LvX24tc9vnNTrQwo5jaODl1ei/F3anurvXeO6VFJzevmYCHbHmeXqj8FLiSsWiSBAv49+vvTsjnQmccy9ypklzeVeqVtm2kCpOZc2Q8sV7VcXHFV3xzXJ1yRJy5KXWB99zT9pMpF+8+iXNL8/dTY2fvNYuOKVydJl4jmrSHLTiw4+RWBXDqxTYZ1ywza9YWRje8oe5Pdu22kmxqA/g9oGRn10eSTN/KP15I9G4B6xCYNY/3zOqdAUKkubMhmthYiDT91MYzXTpUx79SRg7cC8IJI1ApUqa2Xmde46gVs0OooYH1KO3/v0pLV+5hh4ZN5Q6HNuWelhHmXDC3L3LifTxoqX23+Y+Odaq6tkgNn5PcmcbN9ucewevuWEXnffTLXT49gXESxP5rEw+7zP32NLltWHsk2XzbzlpFuf9+smRk5hdHy+wBpXf+h495JytkpdiimOnum5+MHDGKYxtmQ5K5IRYMHXKkmeSReE18TteIr/98QeUi2Q5E4GgTuK/r39CdS0/eV0b+k6i3CMOo2rXnkN5fCSZy7Wkww3UsHsXqj0kuPDap5/m0sYnptlLaEXSfOPaC+xk+7U/TqOLh7QOUjlUTLoJEwXNePk7L4fPHdSVONkQy669FJDjlNvI5oHnlUlOApVXuMEtifOb5RSJpBAtPq7oiu+w/YBKW5GT5rqXXJbWV/j+vufpVG3nNnru1Jfp8n77pd2abdIclBQH/V314xkrLVc5d7M3jO9kvZyyhRzxgVH0J3xfph/hnDPNfMzUDGt2+Qfrf/ni/79hgxwafWM1+9+dFb7D2KYSSwpNKvAW6BSIKOt+V36CibyDCeAOEDCTQKVLmmU3jH/oaZo5ex4Nurw7nXnysXTWxSOo/VGH0mP3Dac58z+gYaMfot49zkzNRJvpwnStdHWQ5TF4y5Zf3Gz7fMAIarzu38TLblud35F4ObOobOo2OxPGPnHW749njqQdG7ZQsw8n009Nz6RDx97s+8KVEwLezxw0oBM6uRXm4YEzn/srZi/9ZpzC2Jbp4C1oSSfLdZuxFEuIueIuL7mVK++qxGwY29yKyvEz1tW0iro98Tit//wLqnbHlZ6PLTnlPFr/pz5Uf0xnX9+xTtMfr0p1Pp9rF2vio4Nm1L0zVSSI90lPm5QbaF4Y29yEOQuvVbuidOVOUBIh+7JamyPL/Xgn+Tip4i8+9dzrL2Ya2Qa5Anm2nMpzkCt8wEeP5VxwLR34t70f2PwCYO2IgVT9u4X00qH3U+/bjk27ldt+xxmllbeDPoC42RaUFLtVL1dlJMvmj4L8IcxvD38Y34mEmFeq8McfuYCc8wOjjv5k43W9KWflt/T3Q6dR7xGtaYS1f5lnlp3XgL7V6MjDc9KqzPOZ1GFsy7TfDexEHDdAp2Biuhjxk3TJ0iUn2HrcAQLmEqi0STMv1b7u9im06Itv6YXHRtOKH9fSlcPvSyXJK35ck5ZEm+vCdM10dmy6ZJkmJ6oXiViOy8tu886/nMZPLvY9IzcMJ1k223PIosdT5676yUkdO2Wdrbp7+bdE+QW0z8zXPcNbyHLb5zlvfgk998puErOXfvuAw9iW6eAtKGkWy2vFUk2hk7NIm2qRLKFnGNu4evb2yXemVWPnhDlv4E129eyfP/zAPjva6+IZ2+VNzrQTn7V121HLh6e43iqS5t1ffWofC8RVuF+uPdD6aHMFbaxSn+5sMDvSpJn3C++0VvJUHXmx0ky+XNmdZ5rL+3gnOdHy27Yg7mPo8seVMDEQ9C7RJUuWIz4W/V+TXvSHFY/TykO702G3DfFVxS9p5r203V4uTZqDPoC4JbvyXvcaXc4vo0fQnmc/Rn5Vzt0MDsNbpYK6uIf7Ge5js/kIJxfya3raH+h/3ymhfYtX0dHbS/vsn3Kb0xc1O9jV9R+8J5ec22jC2JZpvxsUz86/Q6dgYroYRTXWCbYId4BAMghUyqS5zUm9be/xvuURAy6izp2Oo3c/XJyWNPPf+b7DWjWl2daxNNyJ4QKBMAS+mziTWnzxN/qmzSW0p2sfmv/IIjuB2dO4Ge0e9WgYUWXu/X7ai9T8g8m0rFk3KrHOjG2x+g1acfwAati7m6/cnKUL05KyPS0Pp93DJgTqkrN+tZ3wUF4hFT/wMr37nxz6x9wc+3fiiJOpf3yTLrloj13JtSKuKp/+m6pMvZW8bPL6e8q2PdZiR8ukkj9fSiVdS/uI8rpWvb2Qdq5aQ9UPbEAHnnRE2mOqDjqHcra5L88u6XE1fby+GR07fyhtqH841b7T23evWv75asEa+1xmroI8e58bUgn0S20m0qCrS8rLvDS5YnZ59/X32bGnEnMiTvnePS3bUZV//M3yyyXl5pcq08dSlf+8QSU9BlDOpwso5+vPiPXd0yrdN1WenkJV5r9g21fSyWp7FwyIhGG2DxE++LDRpXTsj0/YfVLTwf4xXnznEKr5/Wf0TIsJ1G344WkqPP/gMurxWT/aVbs+5dz3VGj1qrw809Onoj3uySug3Q+8kpVs+nlNqV/7DKeSP50RWpbzB7LetL3IjgWOmZJT9/a7mfaxbspVHT/EjkWufl/S8ghq/Plz1HVL+oeyZblHWKtI7qBrry+k/f862DN2szYeAkAgxgS4fgkuEMiWQKVMmnlZNl9iT/P4W66i2rXyMdPsiCZdXztNk8NmRqGTfFbz190eoF+ffczeX+o1kxlGJ1k223PgpkW00doT2/SMowJtk/dl5h7dgQqG3+PZj7jNVq25c4E9a85X3eLVdlImZi+PbJtDA6xCVc4rjG1+nZrKLLrXzI5zJlrIKt13+6D12NJ9gjl19qWCwbeTVzGx8rJNxGWtd1+2l5Q6rz2NmtO+E2aSWGXgN1vItvF5zyNu20WjvzvZFsX7mjn+uIpyyxuHUKsWpR89MuUd9FvxdxFvJVffYX/UCIo5/p1cdItn18v7TGQ5NvgoKbd916xT0biRVGJ9QOKrSr0DrLZzt12bQFd8ixjQMcBza7u8TL/Nr+/RurNHUotLSs9W97oEE46b86f3S7tt1uiP6M+Lh9DOpkdQ/bGTVUMhxUk++i1/QHpFea/q5fJD/HjLW0nYj3KVczdFw/hOrIDgPoYvtwrqQn/xLF0zzc2bEp32sfvqgAUF3a3K6ENI1Gzg0xiq1D9QW1yGYRQUDLpk6ZJTXm0uiEN597tCvi5OuuRkwwW/BYGKJlApk2YBXcwu8z7mUdf1wp5mRzTq6iRNkxPVS1JObBed9QAd9OJIe8Caf/WNdgEw5xWGkyy72q6ttP+2ZbRtwCRq2DFc0hx0xqqcWO6YNZX27C6m4qr59F6NzlY15kvpmO3zqOvmKbS82u/pwf0fsk1y2ysbxrZMBxOp83U9zn91W7pY+9P59r5E55WTX2gXSOOBZ9ClyzY5LnlwzsuEeXnnHuv//ZqTT99d/Rz9sWMdWjDyr9R22eO08YTe1PQa/2rlfI7r7oFnUI3iIntfM8ffls7X0EG9ewSZZf9dh21ivzDPGvOsWVDMCcVEsi32hvI+Ui7wpkMn54BSLli285259p/lZcciiXeDxnEiisopQQ24SZd9spyv+w+g+hsWpZ4sPrD5qeKXND9z61v2MXO/tj6eGtzhfsycm2yhk19iLCemhbe5J+SqH8+4wrlc5dxPJxXfyXpzQs57pkUtB7ePFCxTV9J8QYPXad8v53mqyfHqXNZeHrGkwinTPjyMbF226ernTJRjqk5h/Ix7QcAkApUqaeYkecbsudS6eRPbB2KmmQuB9et5NqpnOyJT10vJNDlRvUh+/noVVb35PNqRU0hPHP8PuuTff7aqIm8NPCZIpYPY9vMW2nnVWWm3qlbyFUkM/5grvLrtKRSC2XeFr8+yZ/rSLmspcwlVoyo5u1P/+V/559IrdQbQrcOrWRXn02cxo4oBv72QzuJDrFP1kRdZM4drXJHzDKdzFizbQXeQb904re3bjapvWZuqeP3hwDHUcu082tx9JDXp4T5bKMuR9+Hy8zM5IihIb7+/i+dnmjSLvaFuyUk2esn9gEiGuLgXx4Nc5IvvEx9c3J7HM+fbrf3aOmaHy6tv+v7aAbTP6r1J8+6bZtB+7Vr44vNLml/s9yid/MsTVNKlD9Xt1VfZDc6kWZyNLQsIqk0QxEhepcAJM19++67D9E3iwxx/VOOkWZbtlTRnUyNB9sEZjT6jPdb2Gq8rdS60VKcijG1+TtQlJ8h3yoFk3ZhknZJsWxgf414QMI1ApUqaubhX/xH320dJ8cV7mv982h9T1bG5OFi/Yffax07xGc5D+/fAOc0a9oHoegHokhPli1skcVNbPEVXf3MhldQsoLpPuBfeCmtfpsffbLnhMtr936X2auT8QbdR9Q6nefZL65ctp2q8l1m+eO8vXzlll/e+UdjLWsp5RRl5YW3zUihIjnxGa05BrTQxbrMwYq+n2/NUZ4iCdArT6bvJ2nD/nVTl/bn0nzrd6Ky/XkfOo8zc5PslzWLppopeOmzbNuVOErO3/EwxYxz0fGeyr3vJqdwPBC2pFXHlpjMnULsmvRyrpFmleJeY8eUVCvVuHZu2nP+Zyx61l/qrrhoQ3NwSS6cu2SbN/CyvvjGorQTFpJ9s2Tb5w2Q2jOSk+YQWaynvU++ZZv6o5DxeS0f71fm+1ClLl20m6pRk21TaGO4BAVMJVKqk2VQn6NQryZ1tHG1bdcEZlFdSRK9YlYvP2TzZdz9nWPtWXNydau8q/QC0oaA5/W7GTPufveTsKdpiL0Xe9dGCvSFXoybl973Odbk43/Tz2/Op6tRRjhDlpNl7P6zbgDysbV5tIkiO11E2YoZIrhbOsuKQNIvkhY8MKhw3k7YO700Ndy1TOl+bOYqBt2CqkjC5JTmZ9lPO56vOdDuTZtWVFGH09JoddO67lo+acsrnWemdd//d6KRZ7IMPEwPy+c6FoyanJc2f9BxAzXYuCrVqwdk3ea0KkY918jpvPagfkJPmoI9fQbKc/pY/oIhK/E7b5NjVlTQf1esk2m/KZa7hzc/gvfVylXkTk0HopNY7hY1JP6m6ZOmSo0YAd4GAmQSQNJvpl4y10tmx6ZJlmpwoX9xiVvCnas2oYfEy35mZsJyEbLZnVZ129Pu/llZV9ZIjjnlxCy6v46Lcj0DyT5rdZIW1TXfS7LaHknXKn3Vv2iyo/FyvvedO3XTZ5ue7dT3PoNydRfTBuU/Tcc9dYKuguuRUTlrlQb5KJ6PDNrFfWDxPdaY7LV7LYcmpVxLH/92Z6Pi1HV7Gv63n9UYnzV+Mm0aNPp5pu0DuK/xioLyTZjEb6+wvgs5wVum/vY4Gc7M3bIyrHDsmr67QlTS3G3kFzZ/0Fp23bjTl7tmVMqVK3f2p9sMvljmjWYWTSh+gU45OWWH95merLlmmyTGVt2rc4T4QMI0AkmbTPJKlPro6bRM72zjaJie2zNRvli2sfZ8PGEGN1/3bjpgV1tm9h997s/3PXnKcSxblUPOs6L1qfenybPkIJP+c2TWZC2ubVzMIkiOSG+dAVSSOsp0sa79qO2nrbdeUnlktXar7mXW2Ez9ZK8eMocLP5tH/HjCQTl1dWhxJNWn+9R9P/1YdPIeqNmpCtSb+XbmXCeKtIsi59Fl1pltO9qM4E9lvSS2v0nCLE55lrjV+Jv1cXN3opHnlQ9Oo8K2ZtrtUk2axOoOPK1t86TPU9ayqpX3Nj3so97qzfOszqLRfr+TYWQHaTVZQXMqJbdCe4iBZzufLsuV+QpYjx66upHlrp7703oclNHDrCDpk8wdU/eQutPP9t6ylJNvtVSd28UCr9oT8vLC2qfhNpc373QOdggnqYqTz/aRTp2ACuAMEzCSApNlMv2Sslc6OTZcs0+RE+SJxLousM2MuOffaCmeH5STL/r5dLzriptK9xG5ynImLM8C8ljCyrDIVpu3zjN2XZ3sdJxTWtkwHb177IUUyLRc+k3Xi2VAuIJRTUGhVuz3SrtKseumyzS8ut777L+t87BtTKsnL8f2SCrcZUravYNhdnnEoy9NhW1rsSTPGQXzF0UF8XxRJs5wMue275sSZ46T4y09t1ZkjF9Hj9qyDU6b9gEpbEdX2+d7lrc6ldqMHB+G3/y4+tL3T551U0rz0mz3U4KYT7L+rfgBxs03MxjpXdPgV81NlJMd9UNIa1ndeCbGzPxHHxgUVW3Q6QpYjz/bPbDyRtm8nurvoQsrdvNpOlLmN8BFpnLyXrFtlH4Elx25Y21RiSSlwfG6CTsEEdTHye6cEa5F+h06dwj4b94OAKQSQNJviCU166OzYdMkyTU6UL5LF1mzwQWtLZ4O35dWnhk+84OnpsJxk2SsanUqHT7zNlu0lJ6OZZitp5qrAPHjjhIGr0XJiWaV+I2vA9lqaLbz0t/C2B12TsbC2ZTp42zZ9Au2c+zxVadDQnnHJPaaDvfz615f+RiUbN1Be/xFUo9M5vpzCNkVdtgXF5boLT6Pc4m32dvKN1RtS/YnTqaBeerEzOamos/QDe4+j2xU0+6aanKiwsqsZD+tt31rlwEZU6+7HlBL21Ay5ZW9p0uy//UBFF+c9su+23HC5VSDvK7tAXl6va6jGn0uXwatcUcWAii5uvlt4+1Q65PPSFQY/7H88tZ2qdkyU6DOmtH+bOp9alQ6quZq+mz6bWvz3WSrOqU402trL3TL4WDY3ney9yx+9S1VbHEo1/9LT3pP76z9fol9fnmX7oPaU5zyPfAviLWTzc2t0vZjyel7liS5IlvOHsuzqJ3e2jxB0tl05dquf0c2qGzFU2XWyPkX/93+0655raVn1djR1v4lWfYwtNGZNaf/FHyzs1QADzrX7hJyaebTHyqrl2A1rm5eSuuQ4OSlDcbkxyTol2bZsfI7fgkBFE0DSXNEe0Pz8JHe2cbKtaP0WWn7DSGq4Of2IkB/270Btp9zj6vUw9n15+QBL9t4jZFjgT7WPoEOnTda6p9lPJx6w8UwHX3yesdvZ026D5WxC3k8fZ5Vme+RdxVpSWlKS9kgxsxWGt5/OuuT4DSi/eOwf1Oj19LjZlHsAVR10FzU+tmUZ9VinvEdG0a6P33VVnSs+15npXYlXl9/k2WIhk5/NH1c4SfK63GbI+XiiwlEPal8KbS/Rv91aom+duStfNTqfT3m9r1UK1yhiQEkR6Sah0+Krh9NB699L+zn3FQffc7fnR5dt1ozm+AeLqd8nXaxl2EV0S4NXqNmOhdRj8zh7Wba4+Di9TdbRZ63O76ikHuvkyptXr1TLtQ4VL07J4Tjhtuq26sOLN68GKBp/Y2o1gBBW/STr+Lirb8qq3w2SLXQq2w+RFeulseu1ykhWTMjhZfDPjfuYLls1xE6aH7KS5ua7PqX+669LrbzgPphPQ9izdUuabWJ2XVdc6pLj18cpBZBLfIf9ndv9uuwzTY6pvHX4DDJAoCIIIGmuCOrl+ExdnbaJnW2cbFt48wQ65OvnXT0tL6V2GywFhYdzybd8P8tuPPBS1/2VpYO+kfYSvtRlLZfN7z3IM+HVxby85TgrNNv2+ey95mJUG2rU1bIPVZdtXm1u5YdfU+G97lVz1+U3oxYzHy8TMqxTzQlD033tuMtvq4C4NRvbUhXLXQLa7XxecZuoFu7WDnKPOYG297tNi98Ebz9OqsdjZcPJaacuWSxn5eQn6JBFZeODn/l9y+50xJghrt3N9Cd32/tnr/p5sF0l+7F976SLfrk7LWEWP+TEudaUZz0TcGcfV/Diw/aS4tTlc4QdJ861LdnOZNOLkV/BNq9l0qq8g2Rv6dCV/FZ3qNZJYH3yq9eg28ftss7WXmj5YG/SfPqWGfZRXyWnnEd1+w+y9tkP9GzjHLubWh2npa2oMgp6d5k4rjBRp6TzVokT3AMCJhJA0myiV7LQKcmdbZxs+/6ibrRP8VpXT/5Uu501I1y61NQ5oOSl0EGXn2xOovad9KjvQImXWhd/8ak9O8z7Mvl/vS5dzMtbTtnBo3+1Mp6J2XpGz1gMKP0+krDfisc8W2aJrD3w9qkMzgWsak91/6iTSUy6xY/rhwzpRq+K7eLIIa+YLP7rfC1+E4Nlv2PHwiQ6Km03qG3rHsBvvKYf7b9jmetjeaXCwU8+5/q3yweVVmcWSfObBRfSKUVPeaq/5tw7lWabOS6rDbKWF6cVFvSukcAPdPtw4dWf+J2n7Ve3QcV3fseOsewdQ+7zXd3BtqjsAWfbfl5bncZPLraOlvuWrlt/BfFxc/fXm0Z9NtxEbX59j747ZSQd2b9LmfOoZQfprOquq//WHd8qfou6zenQKem8VXyCe0DARAJImk30ShY6JbmzjZNtfvuHt+XkU8PZb5Txsqp9QbKrP/qq1qTCpEGA8mDZp1gZg+c9vUX/018LJ1W/qTRrN1luy2tlWRv6TqLfnXFUmniWs+/GFbRleB/Xx6oWJ8rGNr+ZOVbKq5K83+wZ/6747iepXrODVXAG3rP+8y+o2h1Xet4XdMav+GE2nJwP1yWL5ezsxBTpagAAIABJREFUdzbl77H2wXtcXkmcM2n+OO8MOnr7655yVhw/kA4fFLwH3E6ar+iULiegrboV8vLsB87v4Kmj14ciVd5+/S6f/1486RVtqzuWLsmlGX/fbdty76qT7f+9/sC36Ma1F1Dd3Wvok66P0UnHV/Fs33y/SORN6r9ZL1XeQY1XlxwTdUqybUF+xd9BwGQCSJpN9k4GuiW5s42Tbd9c2stzhifbmWa3/cwiVFh2/fvu15IMxmkwUSbRChiIc9LIyynjMKAMmmnOnTq3zNJY0Vbspc5T70yb2QuqJix3O9m0Oef5zM7uzOu8Zt9k+7fkRIffRHz7zTRHWTBNdwLOvls18pYy+5nFc9bVtJb2P+G+dHvEbbvo541EYjnwRzVPo2N2/NPzjeT24cbtZtap+siLqGT9mr1/Dmirbh9XvOJSPjbM+fxsK/v7yRYJqt/qDk6s95np/eFB9v+2rdXpjnGl+7tF0sz7ykf/VgTsu5sX0JGH5/jONMdpNU0GQx1tyXec3nMVySmbd0EmeuM3IGAiASTNJnolC510dmy6ZJkmJ4qX5NJn3qEGz7kXnvEaYKpy+u/rn1Ddxwa5RgnLrt3+MC3JYBScwoa6FyP3I7Xcl2jrPltX1W8qtrrJ4qJy667t5brc32tfqlMO8+GLi2+pFCPSkcDxHnpONNISpN8E+yWj9l7o4b3Tl/D+9judHztEfBe+Pss+37bMZSU5tcfN9N2+oIOT87m64onlbH7/c8++wm9J9T/fLqHZL+5OJc1vFF5KrX/9iJrssqqLOy6vj4Bu8c46ue/7dW+rYZdU++2H99oOoMo7SPbGfZtQ3V83+MYuH1EWdAl9Jk8rpoWL96SS5of2m2Dvb/6xVjtq81jp9h7PLRC/xW5c6jYEMfGKJZ0fz3TIUo2lIHt1yTHxHR5kO/4OAiYTQNJssncy0C3JnW3cbPts0tNU773pqeWRvCx7S/ebPPf+hbGPqynv+8YDrrLDyAkKMV2yopBTZlY1L89KElvS7q/2VhnnY7HyB9xkJ49R6BTEVzVh4mJg2yffmbZ6gRPmFoMvdy3AZIptfNwUVxPevXxvZWpOmGued5lv8s5JPv9OTrh1VwSWB5TO5IM/rHCcVGvzByUX6uJdHoNct75i/Z8uC1xOzYlz8Yxx9Mdtr9KSGsdQbdpEDXd+bam494z2H+r9iX53xy1KRcBk2+xVCM8+tvfDCLfVhgfT7mVLUrx5Zph94PaRx493GdlWAllgVc72Ons9jO/8ZAs5frGrEkxCDlcwn/5kMfV84yT7Z/zhQi4CJmT5xW4Y2/x00yWnPOJbhWnQPbrsM02OqbyD/IG/g4CpBJA0m+qZDPXS1Wmb2NnG1TaeGebLue9UNWHyCwU32XHlpBLyKraJWVWR8PCMJydvVfY/MG3WUEWWLp1U5Ki0OU6ed27cQg2OaumbqJhmG88eb/x+BdVtc2iomW72G/tPniHXZZuTt4gTTtL8jsNy82V56aQaN0E68WqFNZ9wwhvcD/E9zGLb1Lusc5QXpIvOzaXi4Y/S5tWbqXbThqHOaHaLb26rMm+Ok5J1q8q01Uz6Smc/4MUyE9+5yXbKEbGr+uFF6OeUs7HXGZSzvYj2NG5OOSu/tY/hch7v5xW7mdgWFEvZxKRKH6cqX5dtJuqUZNtU/Yv7QMBEAkiaTfRKFjolubNNsm0mvrhN1AkxoNY56OKkS46JsQSdvGPJb1+5VwE3lcjUFU+65JgYA07bnPUavJaZl2eym2TecYgBlbal86NQecZSNrbgtyBQ0QSQNFe0BzQ/P8kvtyTbZuKL20SdEANqHYYuTrrkmBhL0Mk7lvyObvIqqKUSmbriSZccE2MgKGlWObZK+EIXJ11yTORtok5J563SV+AeEDCRAJJmE72ShU5J7myTbJuJL24TdUIMqHUOujjpkmNiLEEnn6TZ5+gm1WO4ynO2Kslx6Zc0h2Wvi5MuOWhz0fbfpvJWo4C7QMA8AkiazfNJVhol+eWWZNtMfbnpYm6aHPBW62Z0+Q281Xibwgkzzer+Ku9ZXXl5tuoRaOWtU3g6e3+hq0/RJceUNiczTbJt2cQOfgsCFU0ASXNFe0Dz85Pc2SbZNhNf3CbqhBhQ6zB0cdIlx8RYgk7eseR5lJH1E+xpduemq63IcrjAV9E9I6h4iXUCgFW0vGbPAVTznIvUOgHrrvLQSfnhHjdCp2CCuhiZ2scFE8AdIGAmASTNZvolY62S3Nkm2TZTX266mJsmB7zVuhhdfgNvNd4mcSpTDMw6uim/96AylZvVLUMSp8JKtDmuvl00fqRVTXz13p/VzKPCEWMjPwoN/YCK5xDfapRwFwjElwCS5vj6zlXzJL/ckmybSYNlObB0MTdNDnirdXy6/AbearxN48SJ2y9ffUW199vHPoarSv0D1Q1xuVNXPOmSYxpvWZ/NV3dPO6dc4MzJL6TaU55VOrpNFyddckzkbaJOSeedVSeCH4NABRJA0lyB8Mvj0UnubJNsm4kvbhN1Qgyo9Rq6OOmSY2IsQadoYwm81Xnvs/IL2nr7tZ4/cDur2e1mXe1XlxzEgHoM1KtTQ+3mgLt0+U6XHC1GQQgIVBABJM0VBL68HquzY9MlyzQ5eHGrR59pvtOlD2JALQbAG5wQA9HGAPOu/el82jb1Ls8H1zy3D9U8v2+gYrp8p0sO+t1Al9k3JJ23GgXcBQLmEUDSbJ5PstIoyZ1tkm3T+aJMMqck22ZiDIC3WnecZE5Jts3UNoeZ5uB2l+S4TLJtwZ7FHSBgLgEkzeb6JiPNktzZJtk2EwdvJuqEGFDrFnRx0iXHxFiCTtHGEniH4y0fNSX/skq9BlRr/EzsabZm5JO6hDnp/a5aS8BdIGAeASTN5vkkK42S3Nkm2TYMKNXCHjEQLSfwjpa3if0AYiDaGBC87eOmrOrZxV8uTClQ9eDmlD/gJrsom8qly3e65JgY3ybqlHTeKrGLe0DARAJImk30ShY6JbmzTbJtJr64TdQJMaDWOejipEuOibEEnaKNJfDOjDdXMC9Zu8qaWS5UPmpKPElX+9UlBzGQWQyo/cr9Ll2+0yUnG1vwWxCoaAJImivaA5qfr7Nj0yXLNDl4casHnWm+06UPYkAtBsAbnBAD0cYAeEfL28R3QdJjQM3DuAsEzCOApNk8n2SlUZI72yTbZuKL20SdEANq3YMuTrrkmBhL0CnaWAJv8EYMIAbUCOAuEDCTAJJmM/2SsVZJHuQm2TYMJtRCHjEQLSfwjpa3if0AYiDaGADvaHmjzUXPW+2JuAsEzCOApNk8n2SlUZJfuEm2zcQXt4k6IQbUugddnHTJMTGWoFO0sQTe4I0YQAyoEcBdIGAmASTNZvolY62SPMhNsm0YTKiFPGIgWk7gHS1vE/sBxEC0MQDe0fJGm4uet9oTcRcImEcASbN5PslKoyS/cJNsm4kvbhN1QgyodQ+6OOmSY2IsQadoYwm8wRsxgBhQI4C7QMBMAkiazfRLxloleZCbZNswmFALecRAtJzAO1reJvYDiIFoYwC8o+WNNhc9b7Un4i4QMI8AkmbzfJKVRkl+4SbZNhNf3CbqhBhQ6x50cdIlx8RYgk7RxhJ4gzdiADGgRgB3gYCZBJA0m+mXjLVK8iA3ybZhMKEW8oiBaDmBd7S8TewHEAPRxgB4R8sbbS563mpPxF0gYB4BJM3m+SQrjZL8wk2ybSa+uE3UCTGg1j3o4qRLjomxBJ2ijSXwBm/EAGJAjQDuAgEzCSBpNtMvGWuV5EFukm3DYEIt5BED0XIC72h5m9gPIAaijQHwjpY32lz0vNWeiLtAwDwCSJrN80lWGiX5hZtk20x8cZuoE2JArXvQxUmXHBNjCTpFG0vgDd6IAcSAGgHcBQJmEkDSbKZfMtYqyYPcJNuGwYRayCMGouUE3tHyNrEfQAxEGwPgHS1vtLnoeas9EXeBgHkEkDSb55OsNEryCzfJtpn44jZRJ8SAWvegi5MuOSbGEnSKNpbAG7wRA4gBNQK4CwTMJICk2Uy/ZKxVkge5SbYNgwm1kEcMRMsJvKPlbWI/gBiINgbAO1reaHPR81Z7Iu4CAfMIIGk2zydZaZTkF26SbTPxxW2iTogBte5BFyddckyMJegUbSyBN3gjBhADagRwFwiYSQBJs5l+yVirJA9yk2wbBhNqIY8YiJYTeEfL28R+ADEQbQyAd7S80eai5632RNwFAuYRQNJsnk+gEQiAAAiAAAiAAAiAAAiAAAiAgCEEkDQb4gioAQIgAAIgAAIgAAIgAAIgAAIgYB4BJM3m+QQagQAIgAAIgAAIgAAIgAAIgAAIGEIASbMhjoAaIAACIAACIAACIAACIAACIAAC5hFA0myeT6ARCIAACIAACIAACIAACIAACICAIQSQNBviCKgBAiAAAiAAAiAAAiAAAiAAAiBgHgEkzeb5BBqBAAiAAAiAAAiAAAiAAAiAAAgYQgBJsyGOyESNTZuLaM6b79PKVetSP2984P7U+ZT2VKd2gbJI0+Sw4tBJzX2mcdKlj6kx4OYVtjlMe/PyrC45gp1JOiXZNvBW76t0xKSJvE3UCW0u2rgEbzXeuAsE4kwASXNMvbd4yXfUZ/DdtH3HzjIW5NWsTncM60udOx0XaJ1pclhh6BTsNxM56fKbibZ5NaQVP66hbn1voaH9e9CFf+kU2N7KWw7LN00nXfqYaJuJOoG3WjNMMqck24Y2F9/4VtMcd4GAuQSQNJvrG1/NOnYbREXbtlO/nmfToS0PSd375dff06OzXqWC/Dx654VJgdaZJocVhk7BfjORky6/mWibX0MaMmoyvfHOx/T0w6OobeumgW3O6wZdcli+LlmmyTHRNhN10uU3E22DTmpdDGIgWk7grcYbd4FAnAkgaY6p99qc1Jt69ziThl11QRkLxj/0NM2cPY++eHtmoHWmyWGFoVOw30zkpMtvJtrGOvW48nbP9vT50u+IV3h8PO/RwDanS46JOiXZNvBGfCMGEAPo49RiIPBFiBtAIIYEkDTH0GmsspjV69ypPf2+xcF0UMP69MNPa+mrb5bTnPnvU/16+9KcWWMDrTNNjom2QadoY8lU3vxRIOhS/VClQ474uKBDFmxT/1AF3v4EdMWSifFtok7gTcoTBCa1XRNjSadOQazxdxCIIwEkzXH0mqUz7x8deONEWr9hUxkL6tWtQ5PvGqy0VNQ0OWwMdFJb4msaJ136mBoDMe0qoDYIgAAIgAAIgAAIgECWBJA0Zwmwon/+7oeLifcxb9piVfCtVWDvb+5wbNvQapkmhw2ATmpuNI2TLn1MjQE1r+AuEAABEAABEAABEACBpBBA0hxjT86Z/wE9P+cd2rp1u21FYWEeHXfk76nHOaeEOgLHNDl+LgmzXzsKOfyMMDrxsRTX3T7F9tnRR7Sy96RzpdPZr7xlf/Tgwm6qly5ZuuRwstykUX3r/xrYR4bddt8M+mn1z7Y5wlZV23TJ0iVH6M3ynn/tnZRd/N8bHrAfde/SMdTHKl1yxIcFHTq5+Yb1zOQjnFOWLjnC3jA68R7EVs0Psk4UuKyMibeOn05Dr+yh3F/qkqVLDvc9P61eTxNuH1jGNu7X+VI5RUH0Yzpk6dRJ7l/bH3Uo3T9qgLKvnEBEP52tHF06sT5Lvl1Bj9033FaVV+rMe+sDatOyKdWulW//N5U41yVH2KVDJ5ala1yhU5ZOndz6yzBjgaB3oS5ZYeXoGg8E2Ye/g0AcCSBpjqPXLJ2femk+jZn4tzTteVk2L9c+uHEDemrqrUqDC9PksEF9h46jPj3Och0whHkB6JKjW6f3P/mShK9O73g0Lfjgs9TRYd27nOg6uHcLU7ZPhyxdcuRCYJwUcHEs+Qpjmy5ZuuSwHW5tRbbPqzCf03e65OjUyS2++GPOWRePII5Rt6RMtevUJYefl4kssefTaUdFytKl09Fn9rOS4vZ2n8EfJv7zyRep4pBcr6Igv6ZSbQtmq0uWLjkivkSfz++1tes32h8Ww3xc1C1HJJdcbDMbnZjTCccdnmpbovqy3K5UaiTokiNiQIdOusYVXn1cRY51TB1X6BgzibGOjnGF6vsB94FAnAggaY6TtyRdxYDo4bHX2TN73JE3OqAenXf2yfb5zfKLz89E0+SwrmJAyS/G/peek3b+bZikWZcc3TqJ5IqPBps07Xk7gb7zhsvtGUxOoFUqMAuddMiSE8tsdJLl8D/LSYpIzFUGgU7bspGlUycenHKBvbE390+rF8AzRCPGPGwP6FV8p0uOGOTq0MmrjxCD35sHX5LVOdS65MiDaFWdOAY4uVm+ck2ZDwCcqIRtczpk6dJJjm9n3ximr3S2uWxk6dRJTlC57+A4eviJV+yPAc52GPQql23KRo4unZynDQj9xt9yFT3+zDz7o6NKf6lLjjMGZDvD6qRrXME66JKlS46p4wpmle2YSee4Iqg94u8gEEcCSJrj6LXfEkt5ZkseEPCSQ66grTKA93rh8su6IuSwOzgJmf7Ua/bZt3zxUT49up5iLTs/2V7GrHqcli45OnVi3jwA4SWTPDN05fD7iJcL8hI9kVioDJTEy02HLF06de45gmoV5NPsR0bZA52Of2yXmjXnWHr+tX8pDQLZNl2ydMkRvL1my8PYx7x1yNGtU1BXqBKXplby5b6y8YH726tzDmvVlB4df729EieM3+QBZbayRL+rQ46IJWHLI+OG2qt0MrFNhyw5vrPVid9rHy9caieQ7EPewtL4wPqppFJ19YouOSKR1KETfzxr16Z5anm2/GExzAcPXXLYNl2ydI0r/BL5ihqjmDiu0KmTrvFA0PsEfweBOBJA0hxHr/2WVPDMFi/Nq1VoJSovv2lbwolymBcuJxUmyZHdwXtrZr/yJj35wv+mqoSLZVkqA3ghS5cclpetLObN18nHH2n7jGcJeQZMLPNTPSpMJJY6ZOnSifeLDRv9kP21u3nTRvbScZ5t3rx1W+qfVZf56pKlSw5zFkvO2Vetmh1k7WWuZ+8nXbrsB9uH4uNHUJeiS45unYL05o8hQZffGabitypyhG1Bz1ORJQ/gxYcp/hDX7OBGdjLGSbSKHOcAPhtZunQSiRbbwLZwDHK7E1cY23TJ0iVH8A6KAZV3gYkfc8RybO5P+OI+RPgrzDtclxzWQZcsXeMK8Z4zcYyS7VjA1LGOrvFAULvF30EgjgSQNMfRa5bOzuN9eBA4tH8PewklD+Zemvuu0kDQNDle7uBZ2Rmz56YGhCoDJTdZuuSw7ExkMW9ePr99x87U3vM5b75P9z0821pymKd8VBg/X5csXXJYJ05SJ894wR4Ayhcnz7cN7aO0z178TpcsXXJEcTOxAiJT+3TJ4efrlBXTrjBQbeesF7fbux6YZcdomOP5RBInr/DJVJYunZxtd86ssakVQvxR4OYhlyodPejWn2QqS6dOzhliN2dzMcWgS5ccfo4uWaLgkvjIIceic3+6n3265Ij+hAtVZquTrnGFiEv5eM2KHuuYOK7QqZPO8UBQu8TfQSBuBJA0x81jDn355cpX29a/C5WQOM02TY6XW7h4z4of1ypVFfVzrS45/IywsniQs3jJf7O2QQxydMjSqZOsl47YFLplK0uXHDGQ27R5q9XmCpWTErd45AGKDjk6dYp5l1hGfbmCera26ZKlS46wh+OobWu1892DGOiSpUtOmATSzzZdcvgZOmUF+SPOf9c1rhDMs30H6JTj5pewY4EoxiiZ6KR7PBDnGIbuICATQNIc03jg2WS+eGaZL+e/q5plmhw3WyraNuikFk26Ygm81XibyAkxoOY7XZx0yTExlqBTtLEE3uCtMwbUaOIuEIgXASTN8fJXSluxR0ssU3b+u6pZpslhvaGTmvdM46RLH8SAmv9N5IQYUPOdLk665JgYS9Ap2lgCb/DWGQNqNHEXCMSLAJLmePkrpS3v0+SLqzDz5fx3VbNMk+NmS0XbBp3UoklXLIG3Gm8TOSEG1Hyni5MuOSbGEnSKNpbAG7x1xoAaTdwFAvEigKQ5Xv5K05b3nXARqZWr1qX+Ox9h0vmU9sr7m7moSZuWTVPJt/wAHpCJpFwFkyhA1umEP1C/nmer/MTzHtNsY0V12afDNtbHRN8l2TZmrsM+nX4zLS6TbBvaXOkHWpVLV1+JNhdMG20u+rjU8R4wtT/R1eaCIxd3gED8CCBpjp/PbI3lCodOE7i65B3D+iolvGJ5382DL0ntj2Z5XDzirItH2GdjqlQnFS8APkNZHOcSpnKrbIOJtumyT5dtrI9pvkuybaa2OdPiUmdMmmYb2hzeBeI9JY6EyuZdp6u/RJuLNi51+c3E/kTney6mQ2uoDQK+BJA0xzRAOnYbREXbttszuoe2PCRlxZdff0+PznrVPr7onRcmBVrHL1x+8fMRSM7Emc9cXb1ug5IceYA798mxNOHRZ4mP5une5UQaemUP5ZlvlmOibbrs02WbeOGa5Lsk24a4jL4/QZsL7L619ZUm9idoc2hzJsYl3nNqcRnce+EOEIgfASTN8fOZrbHznE/ZDPEVXOUsYyHnp9Xr7SRXnlkOI4ePlnj+tXdsGY+MG2ofxcPXmAlP2In3iAEXKc18m2gb66TLPl1+kzmZ4rsk24a4nEdR9idoc2r9Jdoc4lLXOxxtDm1O53supkNrqA0CvgSQNMc0QMTXzs6d2tPvWxxMBzWsTz/8tJa++ma5VRTsfapfb1+aM2tsoHXyoGvIqMl20ntYq6Z09BGtaPbLb4aasQ56mMqgW55dMMU28SLRYZ8uvzlfbib4Lsm2IS6j7U/Q5kjpIwXaHOJS1zscbQ5tTud7Lmi8hL+DQBwJIGmOo9csnXlfzcAbJ9L6DZvKWFCvbh2afNdgatu6aaB1zpkKMbssfjj+lquUZojFUm7Wh5Nut2v2I6MC9eEbTLONddJlny7b3L4IV7Tvkmwb4jLa/gRtjkilv0SbQ1zqeoejzaHN6XzPKQ32cBMIxIwAkuaYOcypLi8b5n3Mm7YUUZ1aBfb+5g7HtlW2ihOtPx7VJu03XBly8ZL/UpNG9a3/a6AsS1RMVRnsqQg1yTbWV6d92drG+pjquyTbxtyztU+n30yLyyTbhjaHd4F4b5n0LkCbq5i4zPY9YHJ/ouM9pzLGwz0gEDcCSJrj5jFJX13HHpgmh02ETmqBaRonXfogBtT8byInxICa73Rx0iXHxFiCTtHGEniDt84YUKOJu0AgPgSQNMfHV2ma6jr2wDQ5bCR0Ujt30jROuvRBDKgdF2ciJ8SAmu90cdIlx8RYgk7RxhJ4g7fOGIjp0Bpqg4AvASTNMQ0QXccemCaH3QGdgo8KM5GTLr+ZaBt0UjtmBDEQLSfwjpa3if0AYiDaGABvNd4xHVpDbRBA0pzEGNB11IhpcthX0GmmUsiaxkmXPogBtWN0TOSEGFDznS5OuuSYGEvQKdpYAm/w1hkDSoMY3AQCMSOAmeaYOUyoq+uoEdPkyF/ysz1ySpdt0EntWBfwBifEQLQxAN7R8jbxXYAYiDYGwFuNd0yH1lAbBDDTnMQY0HXUiGly2FfQKfioMBM56fKbibZBJ7WjfRAD0XIC72h5m9gPIAaijQHwVuOdxHE3bAIBzDTHPAZ0HHvACEyTA53UA9M03+nSBzGAGEAMqMUA2hw4IQaijQHwVuONu0AgSQSQNMfUm3xOJF8X/qWT/b/Of1c1yzQ5brZUtG3QSS2adMUSeKvxNpETYkDNd7o46ZJjYixBp2hjCbzBW2cMqNHEXSAQLwJImuPlr5S2XACGry/enmn/r/PfVc0yTY6bLRVtG3RSiyZdsQTearxN5IQYUPOdLk665JgYS9Ap2lgCb/DWGQNqNHEXCMSLAJLmePkrpe2c+R/Y/9y5U+mZvs5/VzXLNDlutlS0bdBJLZp0xRJ4q/E2kRNiQM13ujjpkmNiLEGnaGMJvMFbZwyo0cRdIBAvAkia4+WvMtqu+HENrfhxbeq/N2lUn5o0ahDaKtPksAHQSc2NpnHSpQ9iQM3/JnJCDKj5ThcnXXJMjCXoFG0sgTd464wBNZq4CwTiQQBJczz8VEbLTZuLqN+we+nzpd+V+dthrZrSzUMupbatg6swmyaHjYFOwX4zkZMuv5loG3SKtj8Bb/BGDCAGTIwBvOfU4jKmQ2uoDQK+BJA0xzRAelx5u50wtz/qUGrdvEnKiiXfrqD3P/mSOHGe/cioQOtMk8MKQ6dgv5nISZffTLQNOkXbn4A3eCMGEAMmxgDec2pxGTj4xA0gEEMCSJpj6DRWmQvAdO9yIt0x7LIyFtw6fjo9/9q/UkXC/Ew0TY6JtkGnaGMJvNV4m8hJV39iom0m6gTeam0lyZySbBvaXHzjO6ZDa6gNAphpTmIMHH1mP6pfb18a2KcbHdb6EHsfM+9r+3zJ9zR5xgtUtG0HvfPCpEDTTZPDCkOnYL+ZyEmX30y0DTpF25+AN3gjBhADJsYA3nNqcRk4+MQNIBBDAphpjqHTWGU+n3PMxL95an/z4EtSZzj7mWiaHBNtg07RxhJ4q/E2kZOu/sRE20zUCbzV2kqSOSXZNrS5+MZ3TIfWUBsEMNOc1BjgmeXZr7xFvI9569btVFiYZ+9v7nHOyaEqaJsmh/0FndSi1jROuvRBDKj530ROiAE13+nipEuOibEEnaKNJfAGb50xoEYTd4FAfAhgpjk+viqjKVdxnPPm+7Ry1brU3xofuD91PqU91aldoGyZaXJYceik5j7TOOnSBzGg5n8TOSEG1Hyni5MuOSbGEnSKNpbAG7x1xoAaTdwFAvEhgKQ5Pr5K03Txku+oz+C7afuOnWUsyKtZ3SoQ1pc6dzou0DrT5LDC0CnYbyZy0uU3E22DTtH2J+AN3ogBxICJMYD3nFpcBg4+cQMIxJAAkuYYOo1V7thtkFXsazv163k2HdrykJQVX379PT0661WFrNjbAAAHR0lEQVQqyM9TKgRmmhwTbYNO0cYSeKvxNpGTrv7ERNtM1Am81dpKkjkl2Ta0ufjGd0yH1lAbBHwJIGmOaYDwMRO9e5xJw666oIwF4x96mmbOnqd85JRJctgY02yDTtHGEnir8TaRk662a6JtJuoE3mptJcmckmwb2lx84zumQ2uoDQJImpMYA+LrcudO7en3LQ6mgxrWpx9+WktffbOc5sx/3z6Oas6ssYGmmyZH/rJsim3QKdpYAm813iZy0tWfmGibiTqBt1pbSTKnJNuGNhff+A4cfOIGEIghAcw0x9BprDLvqxl440Rav2FTGQvq1a1Dk+8aTG1bNw20zjQ5JtoGnaKNJfBW420iJ139iYm2magTeKu1lSRzSrJtaHPxje/AwSduAIEYEkDSHEOnySq/++Fi4n3Mm7YUUZ1aBfb+5g7Htg1tlWly2ADopOZG0zjp0gcxoOZ/EzkhBtR8p4uTLjkmxhJ0ijaWwBu8dcaAGk3cBQLxIICkOR5+gpYgAAIgAAIgAAIgAAIgAAIgAAIVQABJcwVAxyNBAARAAARAAARAAARAAARAAATiQQBJczz8BC1BAARAAARAAARAAARAAARAAAQqgACS5gqAjkeCAAiAAAiAAAiAAAiAAAiAAAjEgwCS5nj4CVqCAAiAAAiAAAiAAAiAAAiAAAhUAAEkzRUAHY8EARAAARAAARAAARAAARAAARCIBwEkzfHwE7QEARAAARAAARAAARAAARAAARCoAAJImisAOh4JAiAAAiAAAiAAAiAAAiAAAiAQDwJImuPhJ2gJAiAAAiAAAiAAAiAAAiAAAiBQAQSQNFcAdDwSBEAABEAABEAABEAABEAABEAgHgSQNMfDT9ASBEAABEAABEAABEAABEAABECgAgggaa4A6HgkCIAACIAACIAACIAACIAACIBAPAggaY6Hn6AlCIAACIAACIAACIAACIAACIBABRBA0lwB0PFIEAABEAABEAABEAABEAABEACBeBBA0hwPP0FLEAABEAABEAABEAABEAABEACBCiCApLkCoOORIAACIAAC0RGYM/8DGjb6Iere5US6Y9hl0T0YTwIBEAABEAABEEgEASTNiXAjjAABEACByklg/ENP08zZ8zyN/+LtmYSkuXLGBqwGARAAARAAAV0EkDTrIgk5IAACIAACkRN46qX59NLcd+3nLlv+I23fsZMObtyAahXk2/9t9iOjItcJDwQBEAABEAABEEgWASTNyfInrAEBEACBSkugx5W30+dLv6NHxg2lDse2TXEQs9GHtWpqJ9HvfriYrhx+n71cm68589+3k+32Rx1Ko67rRbff/zi9/8mXlFezOnXu1D5tSTfPWk+e8QItX7nG/vsJxx1Otw3tQ3VqF1Ra7jAcBEAABEAABJJOAElz0j0M+0AABECgkhAImzQzFk58mx3cyE62xVWvbh0qyK9pJ8Z8Pf3wKGrbumkq2ebf9Oh6Ci35doWdXItkvJJghpkgAAIgAAIgUOkIIGmudC6HwSAAAiCQTAKZJM1iVvrW8dPp+df+RZwwvzLzLnvmuHPPEXbi3LvHmTTsqguo79BxdpJ88+BL6MK/dLIhduw2iNZv2ETvvTIFs83JDCtYBQIgAAIgAAKEpBlBAAIgAAIgkAgCmSTNXCiML+cSbv5vQp5ImsW/u8FyLglPBFAYAQIgAAIgAAIgYBNA0oxAAAEQAAEQSASBqJLm0zseTQ0PqJfGrMc5J1OTRg0SwRFGgAAIgAAIgAAIpBNA0oyIAAEQAAEQSASB8k6axfJsMfMsoG3aXISl2YmIIBgBAiAAAiAAAu4EkDQjMkAABEAABBJBoLyTZlF1m2GJ2eaPFy612eFoq0SEEIwAARAAARAAAVcCSJoRGCAAAiAAAokgUN5JM0PixPmuB2alKmtz4bCLu51K/XqenQiGMAIEQAAEQAAEQKAsASTNiAoQAAEQAAEQAAEQAAEQAAEQAAEQ8CCApBmhAQIgAAIgAAIgAAIgAAIgAAIgAAJImhEDIAACIAACIAACIAACIAACIAACIBCOAGaaw/HC3SAAAiAAAiAAAiAAAiAAAiAAApWIAJLmSuRsmAoCIAACIAACIAACIAACIAACIBCOAJLmcLxwNwiAAAiAAAiAAAiAAAiAAAiAQCUigKS5EjkbpoIACIAACIAACIAACIAACIAACIQjgKQ5HC/cDQIgAAIgAAIgAAIgAAIgAAIgUIkIIGmuRM6GqSAAAiAAAiAAAiAAAiAAAiAAAuEIIGkOxwt3gwAIgAAIgAAIgAAIgAAIgAAIVCICSJorkbNhKgiAAAiAAAiAAAiAAAiAAAiAQDgCSJrD8cLdIAACIAACIAACIAACIAACIAAClYgAkuZK5GyYCgIgAAIgAAIgAAIgAAIgAAIgEI4AkuZwvHA3CIAACIAACIAACIAACIAACIBAJSKApLkSORumggAIgAAIgAAIgAAIgAAIgAAIhCPw/5gU5B6B5qXDAAAAAElFTkSuQmCC"
    },
    "image-5.png": {
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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image-4.png](attachment:image-4.png)\n",
    "![image-5.png](attachment:image-5.png)\n",
    "\n",
    "The first figure shows small variations in NSW price before and after removing the constraints however at first glance seems somewhat immaterial.\n",
    "\n",
    "The latter figure capturing a broader impact on all regions given a change in the market. Although this line constraint is within NSW, with changes in dispatch there may be subsequent affects to other regions (a conversation for another day on analysing interconnectors)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### D2. Impact to specific units\n",
    "Based on the previous example from a single dispatch interval, it was found that the constraint had a signficant impact on Beryl Solar Farm. The mappings have been omitted here but nonetheless, we shall dive deeper into Beryl SF.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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        "plotlyServerURL": "https://plot.ly"
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        "title": {
         "text": "Figure 3: Impact on Beryl SF dispatch by 'N>>N-NIL_94T_947' & N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>"
        },
        "xaxis": {
         "title": {
          "text": "Time"
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          "text": "Unit dispatch (MW)"
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    "fig3 = go.Figure()\n",
    "fig3.add_trace(go.Scatter(x=timeaxis, y=unit_dispatch[unit_dispatch['unit'] == 'BERYLSF1']['dispatch'], name='BERYLSF1', mode='lines+markers',\n",
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    "                         marker_size=8, marker_symbol='circle',line_color='purple'))\n",
    "fig3.update_xaxes(title=\"Time\")\n",
    "fig3.update_yaxes(title=\"Unit dispatch (MW)\")\n",
    "fig3.update_layout(title=\"Figure 3: Impact on Beryl SF dispatch by 'N>>N-NIL_94T_947' & N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>\",\n",
    "                  template=\"plotly_white\")\n",
    "fig3.show()"
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    "fig4.add_trace(go.Scatter(x=timeaxis, y=unit_dispatch[unit_dispatch['unit'] == 'MANSLR1']['dispatch'], name='MANSLR1', mode='lines+markers',\n",
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    "                         marker_size=8, marker_symbol='circle',line_color='purple'))\n",
    "fig4.update_xaxes(title=\"Time\")\n",
    "fig4.update_yaxes(title=\"Unit dispatch (MW)\")\n",
    "fig4.update_layout(title=\"Figure 4: Impact on Manildra SF dispatch by 'N>>N-NIL_94T_947' & N>>N-NIL_94T' on 15/02/21<br><sup>[r] denotes constraint removed</sup>\",\n",
    "                  template=\"plotly_white\")\n",
    "fig4.write_image(\"image-4.png\")\n",
    "fig4.show()"
   ]
  },
  {
   "attachments": {
    "image-6.png": {
     "image/png": 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"
    },
    "image-7.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image-6.png](attachment:image-6.png)\n",
    "![image-7.png](attachment:image-7.png)\n",
    "\n",
    "Figure 3 and Figure 4 captures the real crux of this type of constraints analysis using nempy. The impact of the specific line constraint for Beryl Solar Farm is profound throughout the majority of the day, at least the important hours where solar is available that is! However that cannot be said for Manildra. Despite being constrained signficantly, the cause of Manildra's curtailment cannot be attributed to 'N>>N-NIL_94T_947' & 'N>>N-NIL_94T' constraints. It is plausible (very much so) that another thermal line constraint in the vincinity is also binding... but we'll save this adventure for another time!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Download Results\n",
    "\n",
    "The excel file here is also available should it be of interest to look into specific numbers. A copy can be found in the constraints repository."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "dflist = [prices_table.reset_index(), prices_table_r.reset_index(), mv_table.reset_index(), \\\n",
    "          mv_table_r.reset_index(), units_table.reset_index(), units_table_r.reset_index()]\n",
    "dfnames = ['Base-Prices','ConRemoved-Prices','Base-MVs','ConRemoved-MVs','Base-Units','ConRemoved-Units']\n",
    "\n",
    "Excelwriter = pd.ExcelWriter(\"results.xlsx\",engine=\"xlsxwriter\")\n",
    "for i, df in enumerate (dflist):\n",
    "    df.to_excel(Excelwriter, sheet_name=dfnames[i],index=False)\n",
    "Excelwriter.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## Parting Words\n",
    "\n",
    "This example of the timeseries builds on the previous explaination of using nempy for analysing constraints. It captures a tangible or visual sense of why constraints matter so much for specific units, here highlighting Beryl Solar Farm and Manildra Solar Farm as only one example of comparison. Such analysis is extremely insightful for anyone looking to gain a grasp on the uniqueness of constraints and subsequent impacts to specific generators or market outcomes at large.\n",
    "\n",
    "If there's two cents to take from this, firstly finding the root cause for a specific plant to be constrained isn't necessarily easy... and secondly, not all units will behave in the same way when a constraint is removed... irrespective of their contribution (LHS coefficients) towards that constraint. Imagine how many constraints might be applied to that unit at any one time... (yep let's save that analysis for another day!) \n",
    "\n",
    "I hope this example proved to be benefiticial in one way or another. Feel free to reach out if you have any questions!"
   ]
  }
 ],
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   "name": "nempy_constraints_analysis_example_a.ipynb",
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   "display_name": "constraintsenv",
   "language": "python",
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