{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# aPMV (Adaptive Predicted Mean Vote) Setpoints Demonstration\n",
    "\n",
    "This notebook demonstrates how to use the `apmv_setpoints` module from the `accim` package to integrate Adaptive Predicted Mean Vote (aPMV) setpoints into an EnergyPlus model. The entire workflow, including model modification and simulation, is managed using Python.\n",
    "\n",
    "## Prerequisites\n",
    "\n",
    "Before running this notebook, ensure the following files are in the same directory:\n",
    "- `aPMV_testing_v01_no_script.idf`: The base EnergyPlus model.\n",
    "- `Seville.epw`: The weather file for the simulation.\n",
    "\n",
    "## Workflow Overview\n",
    "\n",
    "The demonstration is divided into three main parts:\n",
    "1.  **Baseline Simulation:** We first run the model with standard PMV setpoints (equivalent to aPMV with an adaptive coefficient, λ, of 0). This establishes a reference case.\n",
    "2.  **Adaptive Simulation:** We then apply zone-specific `λ` coefficients to enable aPMV-based control and compare the results.\n",
    "3.  **Cleanup:** Finally, we remove the simulation output directories."
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Initial Setup and Model Loading\n",
    "\n",
    "First, we import the necessary libraries, including `pandas` and `seaborn` for data handling and visualization, and modules from `besos` and `accim` for EnergyPlus interaction.\n",
    "\n",
    "The code below then loads the IDF file into a `besos` building object. For this demonstration, we modify the occupancy schedules to ensure the zones are always occupied, which makes the comfort control logic continuously active and easier to visualize. Finally, we identify the occupied thermal zones that will be controlled."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:09:52.434238Z",
     "start_time": "2025-11-23T16:09:52.417465Z"
    }
   },
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from besos import eppy_funcs as ef\n",
    "from besos import eplus_funcs as ep\n",
    "import accim.sim.apmv_setpoints as apmv\n",
    "import os\n",
    "\n",
    "# Visualization setup\n",
    "plt.rcParams['figure.figsize'] = [15, 6]\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Define file paths\n",
    "idfname = \"aPMV_testing_v01_no_script.idf\"\n",
    "epwfile = \"Seville.epw\"\n",
    "\n",
    "print(f\"IDF File: {idfname}\")\n",
    "print(f\"EPW File: {epwfile}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IDF File: aPMV_testing_v01_no_script.idf\n",
      "EPW File: Seville.epw\n"
     ]
    }
   ],
   "execution_count": 64
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:09:52.981680Z",
     "start_time": "2025-11-23T16:09:52.495059Z"
    }
   },
   "source": [
    "# Load the building model using BESOS\n",
    "building = ef.get_building(idfname)\n",
    "\n",
    "# Ensure zones are always occupied for the demonstration\n",
    "apmv.set_zones_always_occupied(building=building)\n",
    "\n",
    "# Identify occupied zones\n",
    "zones = [i.Zone_or_ZoneList_Name for i in building.idfobjects['people']]\n",
    "print(\"Building loaded successfully.\")\n",
    "print(f\"Occupied zones found: {zones}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "On Schedule already was in the model\n",
      "Building loaded successfully.\n",
      "Occupied zones found: ['Block1:Zone2', 'Block1:Zone1']\n"
     ]
    }
   ],
   "execution_count": 65
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:09:53.012480Z",
     "start_time": "2025-11-23T16:09:53.004902Z"
    }
   },
   "source": [
    "# Helper function to find columns dynamically (used in both parts)\n",
    "def get_columns(df, zone_name_part):\n",
    "    # Find aPMV value column\n",
    "    apmv_col = [i for i in df.columns if 'EMS:aPMV' in i and zone_name_part in i and 'Setpoint' not in i][0]\n",
    "    # Find cooling setpoint column (no tolerance)\n",
    "    cool_sp_col = [i for i in df.columns if 'EMS:aPMV Cooling Setpoint No Tolerance' in i and zone_name_part in i][0]\n",
    "    # Find heating setpoint column (no tolerance)\n",
    "    heat_sp_col = [i for i in df.columns if 'EMS:aPMV Heating Setpoint No Tolerance' in i and zone_name_part in i][0]\n",
    "    \n",
    "    return apmv_col, cool_sp_col, heat_sp_col"
   ],
   "outputs": [],
   "execution_count": 66
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 1: Baseline Scenario (Standard PMV)\n",
    "\n",
    "First, we will run a baseline simulation using standard Fanger PMV control. This is achieved by setting the adaptive coefficients (λ) to **0**.\n",
    "\n",
    "According to the aPMV equation:\n",
    "$$ aPMV = \\frac{PMV}{1 + \\lambda \\times PMV} $$\n",
    "\n",
    "If λ = 0, then **aPMV = PMV**. This allows us to simulate standard PMV control with fixed setpoints at ±0.5, which will serve as our reference case."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:09:53.511574Z",
     "start_time": "2025-11-23T16:09:53.024638Z"
    }
   },
   "source": [
    "# Create a copy of the building for the baseline simulation\n",
    "building_pmv = ef.get_building(idfname)\n",
    "apmv.set_zones_always_occupied(building=building_pmv)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "On Schedule already was in the model\n"
     ]
    }
   ],
   "execution_count": 67
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next step will be calling the `apply_apmv_setpoints` function, therefore, the documentation should be read before, or at least, the available parameters should be checked:\n",
    "\n",
    "*   **`building`**: The `besos.IDF_class` building object to be modified.\n",
    "*   **`outputs_freq`**: List of frequencies for simulation outputs (e.g., `['hourly']`).\n",
    "*   **`other_PMV_related_outputs`**: If `True`, adds detailed PMV calculation outputs for analysis.\n",
    "*   **`adap_coeff_cooling`**: Adaptive coefficient (λ) for the cooling season (default: `0.293`).\n",
    "*   **`adap_coeff_heating`**: Adaptive coefficient (λ) for the heating season (default: `-0.293`).\n",
    "*   **`pmv_cooling_sp`**: Upper base PMV limit for cooling (default: `0.5`).\n",
    "*   **`pmv_heating_sp`**: Lower base PMV limit for heating (default: `-0.5`).\n",
    "*   **`tolerance_cooling_sp_cooling_season`**: Negative offset for the cooling setpoint during the cooling season (default: `-0.1`).\n",
    "*   **`tolerance_cooling_sp_heating_season`**: Negative offset for the cooling setpoint during the heating season (default: `-0.1`).\n",
    "*   **`tolerance_heating_sp_cooling_season`**: Positive offset for the heating setpoint during the cooling season (default: `0.1`).\n",
    "*   **`tolerance_heating_sp_heating_season`**: Positive offset for the heating setpoint during the heating season (default: `0.1`).\n",
    "*   **`cooling_season_start`**: Global start of the cooling season (day of year or \"dd/mm\") (default: `120`).\n",
    "*   **`cooling_season_end`**: Global end of the cooling season (day of year or \"dd/mm\") (default: `210`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The full documentation can be read below:"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:09:53.543186Z",
     "start_time": "2025-11-23T16:09:53.529619Z"
    }
   },
   "source": [
    "apmv.apply_apmv_setpoints?"
   ],
   "outputs": [],
   "execution_count": 68
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Applying PMV Setpoints (λ = 0)\n",
    "\n",
    "Now, we call the core function of the module: `apply_apmv_setpoints`. By setting `adap_coeff_cooling` and `adap_coeff_heating` to `0`, we are instructing `accim` to implement standard PMV control. The function modifies the `building_pmv` object in-memory by adding all the necessary EnergyPlus objects (Schedules, EMS Sensors, Actuators, Programs, and Output Variables) required for the control logic.\n",
    "\n",
    "The `verboseMode=True` argument prints a log of every object being added to the IDF model."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:09:54.010966Z",
     "start_time": "2025-11-23T16:09:53.611282Z"
    }
   },
   "source": [
    "# Apply setpoints with coefficients set to 0\n",
    "building_with_pmv = apmv.apply_apmv_setpoints(\n",
    "    building=building_pmv,\n",
    "    adap_coeff_cooling=0,\n",
    "    adap_coeff_heating=0,\n",
    "    pmv_cooling_sp=0.5,\n",
    "    pmv_heating_sp=-0.5,\n",
    "    cooling_season_start='01/04',  # April 1st\n",
    "    cooling_season_end='01/10',    # October 1st\n",
    "    verboseMode=True,\n",
    "    tolerance_cooling_sp_cooling_season=-0.15,\n",
    "    tolerance_cooling_sp_heating_season=-0.15\n",
    ")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PMV_H_SP_Block1_Zone2 Schedule has been added\n",
      "PMV_H_SP_Block1_Zone1 Schedule has been added\n",
      "PMV_C_SP_Block1_Zone2 Schedule has been added\n",
      "PMV_C_SP_Block1_Zone1 Schedule has been added\n",
      "Added - PMV_Block1_Zone2 Sensor\n",
      "Added - People_Occupant_Count_Block1_Zone2 Sensor\n",
      "Added - PMV_Block1_Zone1 Sensor\n",
      "Added - People_Occupant_Count_Block1_Zone1 Sensor\n",
      "Added - PMV_H_SP_act_Block1_Zone2 Actuator\n",
      "Added - PMV_H_SP_act_Block1_Zone1 Actuator\n",
      "Added - PMV_C_SP_act_Block1_Zone2 Actuator\n",
      "Added - PMV_C_SP_act_Block1_Zone1 Actuator\n",
      "Added - CoolingSeason GlobalVariable object\n",
      "Added - CoolSeasonEnd GlobalVariable object\n",
      "Added - CoolSeasonStart GlobalVariable object\n",
      "Added - tolerance_cooling_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_cooling_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_cooling_season_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_heating_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_heating_season_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_heating_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_heating_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_heating_sp_cooling_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_heating_sp_cooling_season_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_heating_sp_heating_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_heating_sp_heating_season_Block1_Zone1 GlobalVariable object\n",
      "Added - adap_coeff_Block1_Zone2 GlobalVariable object\n",
      "Added - adap_coeff_Block1_Zone1 GlobalVariable object\n",
      "Added - adap_coeff_heating_Block1_Zone2 GlobalVariable object\n",
      "Added - adap_coeff_heating_Block1_Zone1 GlobalVariable object\n",
      "Added - adap_coeff_cooling_Block1_Zone2 GlobalVariable object\n",
      "Added - adap_coeff_cooling_Block1_Zone1 GlobalVariable object\n",
      "Added - pmv_heating_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - pmv_heating_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - pmv_cooling_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - pmv_cooling_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_Block1_Zone1 GlobalVariable object\n",
      "Added - comfhour_Block1_Zone2 GlobalVariable object\n",
      "Added - comfhour_Block1_Zone1 GlobalVariable object\n",
      "Added - discomfhour_Block1_Zone2 GlobalVariable object\n",
      "Added - discomfhour_Block1_Zone1 GlobalVariable object\n",
      "Added - discomfhour_heat_Block1_Zone2 GlobalVariable object\n",
      "Added - discomfhour_heat_Block1_Zone1 GlobalVariable object\n",
      "Added - discomfhour_cold_Block1_Zone2 GlobalVariable object\n",
      "Added - discomfhour_cold_Block1_Zone1 GlobalVariable object\n",
      "Added - occupied_hour_Block1_Zone2 GlobalVariable object\n",
      "Added - occupied_hour_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_H_SP_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_H_SP_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_C_SP_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_C_SP_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_H_SP_noTol_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_H_SP_noTol_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_C_SP_noTol_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_C_SP_noTol_Block1_Zone1 GlobalVariable object\n",
      "Added - set_cooling_season_input_data Program\n",
      "Added - set_cooling_season Program\n",
      "Added - set_zone_input_data_Block1_Zone2 Program\n",
      "Added - apply_aPMV_Block1_Zone2 Program\n",
      "Added - set_zone_input_data_Block1_Zone1 Program\n",
      "Added - apply_aPMV_Block1_Zone1 Program\n",
      "Added - monitor_aPMV_Block1_Zone2 Program\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone2 Program\n",
      "Added - monitor_aPMV_Block1_Zone1 Program\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone1 Program\n",
      "Added - set_cooling_season_input_data Program Calling Manager\n",
      "Added - set_cooling_season Program Calling Manager\n",
      "Added - set_zone_input_data_Block1_Zone2 Program Calling Manager\n",
      "Added - apply_aPMV_Block1_Zone2 Program Calling Manager\n",
      "Added - set_zone_input_data_Block1_Zone1 Program Calling Manager\n",
      "Added - apply_aPMV_Block1_Zone1 Program Calling Manager\n",
      "Added - monitor_aPMV_Block1_Zone2 Program Calling Manager\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone2 Program Calling Manager\n",
      "Added - monitor_aPMV_Block1_Zone1 Program Calling Manager\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone1 Program Calling Manager\n",
      "Added - Adaptive Coefficient_Block1_Zone2 Output Variable\n",
      "Added - Adaptive Coefficient_Block1_Zone1 Output Variable\n",
      "Added - aPMV_Block1_Zone2 Output Variable\n",
      "Added - aPMV_Block1_Zone1 Output Variable\n",
      "Added - aPMV Heating Setpoint_Block1_Zone2 Output Variable\n",
      "Added - aPMV Heating Setpoint_Block1_Zone1 Output Variable\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone2 Output Variable\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone1 Output Variable\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone2 Output Variable\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone1 Output Variable\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone2 Output Variable\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone1 Output Variable\n",
      "Added - Comfortable Hours_Block1_Zone2 Output Variable\n",
      "Added - Comfortable Hours_Block1_Zone1 Output Variable\n",
      "Added - Discomfortable Hot Hours_Block1_Zone2 Output Variable\n",
      "Added - Discomfortable Hot Hours_Block1_Zone1 Output Variable\n",
      "Added - Discomfortable Cold Hours_Block1_Zone2 Output Variable\n",
      "Added - Discomfortable Cold Hours_Block1_Zone1 Output Variable\n",
      "Added - Discomfortable Total Hours_Block1_Zone2 Output Variable\n",
      "Added - Discomfortable Total Hours_Block1_Zone1 Output Variable\n",
      "Added - Occupied hours_Block1_Zone2 Output Variable\n",
      "Added - Occupied hours_Block1_Zone1 Output Variable\n",
      "Added - Adaptive Coefficient_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Adaptive Coefficient_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Comfortable Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Comfortable Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Hot Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Hot Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Cold Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Cold Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Total Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Total Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Occupied hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Occupied hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Operative Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Clothing Surface Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Clothing Value Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Control Fanger High Setpoint PMV Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Control Fanger Low Setpoint PMV Reporting Frequency Hourly Output:Variable data\n",
      "Not added - Zone Thermal Comfort Fanger Model PMV Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Fanger Model PPD Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Mean Radiant Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Air Relative Humidity Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Mean Air Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Cooling Coil Total Cooling Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - Heating Coil Heating Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - Facility Total HVAC Electric Demand Power Reporting Frequency Hourly Output:Variable data\n",
      "Added - Facility Total HVAC Electricity Demand Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Surface Venting Window or Door Opening Factor Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Infiltration Air Change Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Infiltration Volume Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Ventilation Air Change Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Ventilation Volume Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_H_SP_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_H_SP_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_C_SP_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_C_SP_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Default Air Velocity for Comfort Calculations Reporting Frequency Hourly Output:Variable data\n",
      "Not added - OutputControl:Files object - Output CSV, MTR and ESO fields set to Yes\n"
     ]
    }
   ],
   "execution_count": 69
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Running the Baseline Simulation\n",
    "\n",
    "With the IDF file now modified by `accim`, we use BESOS's `run_building` function to execute the EnergyPlus simulation. The results will be saved in the `sim_results_pmv` directory."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:16.758535Z",
     "start_time": "2025-11-23T16:09:54.044803Z"
    }
   },
   "source": [
    "# Run simulation\n",
    "output_dir_base = 'sim_results_pmv'\n",
    "print(f\"Running baseline simulation in: {output_dir_base}...\")\n",
    "\n",
    "ep.run_building(\n",
    "    building=building_with_pmv,\n",
    "    out_dir=output_dir_base,\n",
    "    epw=epwfile\n",
    ")\n",
    "print(\"Baseline simulation finished.\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running baseline simulation in: sim_results_pmv...\n",
      "Running EnergyPlus with stdout output suppressed...\n",
      "Baseline simulation finished.\n"
     ]
    }
   ],
   "execution_count": 70
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Visualizing the Baseline Results\n",
    "\n",
    "We load the simulation results from the output CSV file and plot the PMV for Zone 1. As expected, the plot shows the zone's PMV value fluctuating between the fixed heating and cooling setpoints of -0.5 and +0.5, respectively. This confirms our baseline is working correctly."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:17.397634Z",
     "start_time": "2025-11-23T16:10:16.827305Z"
    }
   },
   "source": [
    "# Load Baseline results\n",
    "results_path_base = os.path.join(output_dir_base, 'eplusout.csv')\n",
    "df_base = pd.read_csv(results_path_base)\n",
    "df_base['Hour'] = df_base.index\n",
    "\n",
    "# Get columns for Zone 1\n",
    "z1_apmv_b, z1_cool_b, z1_heat_b = get_columns(df_base, 'Block1_Zone1')\n",
    "\n",
    "# Visualize Baseline\n",
    "plt.figure()\n",
    "sns.lineplot(data=df_base, x='Hour', y=z1_apmv_b, color='gray', linewidth=0.5, label='PMV (Lambda=0)')\n",
    "sns.lineplot(data=df_base, x='Hour', y=z1_cool_b, color='blue', linestyle='--', label='Cooling SP (0.5)')\n",
    "sns.lineplot(data=df_base, x='Hour', y=z1_heat_b, color='red', linestyle='--', label='Heating SP (-0.5)')\n",
    "\n",
    "plt.title('Zone 1: Baseline (Standard Fanger)')\n",
    "plt.ylabel('PMV / aPMV')\n",
    "plt.xlabel('Hours of the Year')\n",
    "plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12), frameon=True)\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 71
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2: Adaptive Scenario (aPMV)\n",
    "\n",
    "Now, we will apply true aPMV logic by defining distinct adaptive coefficients (λ) for each zone. This demonstrates the tool's ability to handle multi-zone buildings with different occupant adaptation profiles. For this example:\n",
    "\n",
    "*   **Block1:Zone1:** Will be assigned a **high adaptation** profile (Cooling λ = 0.3, Heating λ = 0.1).\n",
    "*   **Block1:Zone2:** Will be assigned a **low adaptation** profile (Cooling λ = 0.2, Heating λ = 0.05)."
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Defining Zone-Specific Adaptive Coefficients\n",
    "\n",
    "A key feature of the `apmv_setpoints` module is its ability to accept dictionaries for most parameters. This allows us to assign unique values to each thermal zone. Here, we create separate dictionaries for the heating and cooling adaptive coefficients."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:17.443008Z",
     "start_time": "2025-11-23T16:10:17.424992Z"
    }
   },
   "source": [
    "# Define dictionaries for specific coefficients per zone\n",
    "adap_coeff_cooling = {}\n",
    "adap_coeff_heating = {}\n",
    "\n",
    "for zone in zones:\n",
    "    if 'zone1' in zone.lower():\n",
    "        adap_coeff_cooling.update({zone: 0.3})\n",
    "        adap_coeff_heating.update({zone: 0.1})\n",
    "        print(f\"Configuring {zone}: Cooling Coeff=0.3, Heating Coeff=0.1\")\n",
    "\n",
    "    if 'zone2' in zone.lower():\n",
    "        adap_coeff_cooling.update({zone: 0.2})\n",
    "        adap_coeff_heating.update({zone: 0.05})\n",
    "        print(f\"Configuring {zone}: Cooling Coeff=0.2, Heating Coeff=0.05\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Configuring Block1:Zone2: Cooling Coeff=0.2, Heating Coeff=0.05\n",
      "Configuring Block1:Zone1: Cooling Coeff=0.3, Heating Coeff=0.1\n"
     ]
    }
   ],
   "execution_count": 72
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:17.489012Z",
     "start_time": "2025-11-23T16:10:17.475920Z"
    }
   },
   "source": [
    "adap_coeff_cooling"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Block1:Zone2': 0.2, 'Block1:Zone1': 0.3}"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 73
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:17.535491Z",
     "start_time": "2025-11-23T16:10:17.515890Z"
    }
   },
   "source": [
    "adap_coeff_heating"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Block1:Zone2': 0.05, 'Block1:Zone1': 0.1}"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 74
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:17.582778Z",
     "start_time": "2025-11-23T16:10:17.560156Z"
    }
   },
   "source": [
    "# Generate DataFrame to inspect arguments before applying (Optional)\n",
    "df_args = apmv.generate_df_from_args(\n",
    "    building=building,\n",
    "    adap_coeff_cooling=adap_coeff_cooling,\n",
    "    adap_coeff_heating=adap_coeff_heating,\n",
    "    pmv_cooling_sp=0.5,\n",
    "    pmv_heating_sp=-0.5,\n",
    ")\n",
    "display(df_args)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "              adap_coeff_cooling  adap_coeff_heating  pmv_cooling_sp  \\\n",
       "Block1:Zone2                 0.2                0.05             0.5   \n",
       "Block1:Zone1                 0.3                0.10             0.5   \n",
       "\n",
       "              pmv_heating_sp  tolerance_cooling_sp_cooling_season  \\\n",
       "Block1:Zone2            -0.5                                 -0.1   \n",
       "Block1:Zone1            -0.5                                 -0.1   \n",
       "\n",
       "              tolerance_cooling_sp_heating_season  \\\n",
       "Block1:Zone2                                 -0.1   \n",
       "Block1:Zone1                                 -0.1   \n",
       "\n",
       "              tolerance_heating_sp_cooling_season  \\\n",
       "Block1:Zone2                                  0.1   \n",
       "Block1:Zone1                                  0.1   \n",
       "\n",
       "              tolerance_heating_sp_heating_season underscore_zonename  \n",
       "Block1:Zone2                                  0.1        Block1_Zone2  \n",
       "Block1:Zone1                                  0.1        Block1_Zone1  "
      ],
      "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>adap_coeff_cooling</th>\n",
       "      <th>adap_coeff_heating</th>\n",
       "      <th>pmv_cooling_sp</th>\n",
       "      <th>pmv_heating_sp</th>\n",
       "      <th>tolerance_cooling_sp_cooling_season</th>\n",
       "      <th>tolerance_cooling_sp_heating_season</th>\n",
       "      <th>tolerance_heating_sp_cooling_season</th>\n",
       "      <th>tolerance_heating_sp_heating_season</th>\n",
       "      <th>underscore_zonename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Block1:Zone2</th>\n",
       "      <td>0.2</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Block1_Zone2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Block1:Zone1</th>\n",
       "      <td>0.3</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Block1_Zone1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 75
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Applying aPMV Setpoints with Custom Coefficients\n",
    "\n",
    "We call the `apply_apmv_setpoints` function again, but this time on the **original `building` object**. We pass the dictionaries we just created for the adaptive coefficients. `accim` will now generate a unique set of EMS objects for each zone, each with its own specific `λ` values."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:18.346211Z",
     "start_time": "2025-11-23T16:10:17.758711Z"
    }
   },
   "source": [
    "# Apply multi-zone configuration to the model\n",
    "building_with_apmv = apmv.apply_apmv_setpoints(\n",
    "    building=building,\n",
    "    adap_coeff_cooling=adap_coeff_cooling,\n",
    "    adap_coeff_heating=adap_coeff_heating,\n",
    "    pmv_cooling_sp=0.5,\n",
    "    pmv_heating_sp=-0.5,\n",
    "    cooling_season_start='01/04',\n",
    "    cooling_season_end='01/10',\n",
    "    verboseMode=True\n",
    ")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PMV_H_SP_Block1_Zone2 Schedule has been added\n",
      "PMV_H_SP_Block1_Zone1 Schedule has been added\n",
      "PMV_C_SP_Block1_Zone2 Schedule has been added\n",
      "PMV_C_SP_Block1_Zone1 Schedule has been added\n",
      "Added - PMV_Block1_Zone2 Sensor\n",
      "Added - People_Occupant_Count_Block1_Zone2 Sensor\n",
      "Added - PMV_Block1_Zone1 Sensor\n",
      "Added - People_Occupant_Count_Block1_Zone1 Sensor\n",
      "Added - PMV_H_SP_act_Block1_Zone2 Actuator\n",
      "Added - PMV_H_SP_act_Block1_Zone1 Actuator\n",
      "Added - PMV_C_SP_act_Block1_Zone2 Actuator\n",
      "Added - PMV_C_SP_act_Block1_Zone1 Actuator\n",
      "Added - CoolingSeason GlobalVariable object\n",
      "Added - CoolSeasonEnd GlobalVariable object\n",
      "Added - CoolSeasonStart GlobalVariable object\n",
      "Added - tolerance_cooling_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_cooling_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_cooling_season_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_heating_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_cooling_sp_heating_season_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_heating_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_heating_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_heating_sp_cooling_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_heating_sp_cooling_season_Block1_Zone1 GlobalVariable object\n",
      "Added - tolerance_heating_sp_heating_season_Block1_Zone2 GlobalVariable object\n",
      "Added - tolerance_heating_sp_heating_season_Block1_Zone1 GlobalVariable object\n",
      "Added - adap_coeff_Block1_Zone2 GlobalVariable object\n",
      "Added - adap_coeff_Block1_Zone1 GlobalVariable object\n",
      "Added - adap_coeff_heating_Block1_Zone2 GlobalVariable object\n",
      "Added - adap_coeff_heating_Block1_Zone1 GlobalVariable object\n",
      "Added - adap_coeff_cooling_Block1_Zone2 GlobalVariable object\n",
      "Added - adap_coeff_cooling_Block1_Zone1 GlobalVariable object\n",
      "Added - pmv_heating_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - pmv_heating_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - pmv_cooling_sp_Block1_Zone2 GlobalVariable object\n",
      "Added - pmv_cooling_sp_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_Block1_Zone1 GlobalVariable object\n",
      "Added - comfhour_Block1_Zone2 GlobalVariable object\n",
      "Added - comfhour_Block1_Zone1 GlobalVariable object\n",
      "Added - discomfhour_Block1_Zone2 GlobalVariable object\n",
      "Added - discomfhour_Block1_Zone1 GlobalVariable object\n",
      "Added - discomfhour_heat_Block1_Zone2 GlobalVariable object\n",
      "Added - discomfhour_heat_Block1_Zone1 GlobalVariable object\n",
      "Added - discomfhour_cold_Block1_Zone2 GlobalVariable object\n",
      "Added - discomfhour_cold_Block1_Zone1 GlobalVariable object\n",
      "Added - occupied_hour_Block1_Zone2 GlobalVariable object\n",
      "Added - occupied_hour_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_H_SP_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_H_SP_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_C_SP_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_C_SP_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_H_SP_noTol_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_H_SP_noTol_Block1_Zone1 GlobalVariable object\n",
      "Added - aPMV_C_SP_noTol_Block1_Zone2 GlobalVariable object\n",
      "Added - aPMV_C_SP_noTol_Block1_Zone1 GlobalVariable object\n",
      "Added - set_cooling_season_input_data Program\n",
      "Added - set_cooling_season Program\n",
      "Added - set_zone_input_data_Block1_Zone2 Program\n",
      "Added - apply_aPMV_Block1_Zone2 Program\n",
      "Added - set_zone_input_data_Block1_Zone1 Program\n",
      "Added - apply_aPMV_Block1_Zone1 Program\n",
      "Added - monitor_aPMV_Block1_Zone2 Program\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone2 Program\n",
      "Added - monitor_aPMV_Block1_Zone1 Program\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone1 Program\n",
      "Added - set_cooling_season_input_data Program Calling Manager\n",
      "Added - set_cooling_season Program Calling Manager\n",
      "Added - set_zone_input_data_Block1_Zone2 Program Calling Manager\n",
      "Added - apply_aPMV_Block1_Zone2 Program Calling Manager\n",
      "Added - set_zone_input_data_Block1_Zone1 Program Calling Manager\n",
      "Added - apply_aPMV_Block1_Zone1 Program Calling Manager\n",
      "Added - monitor_aPMV_Block1_Zone2 Program Calling Manager\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone2 Program Calling Manager\n",
      "Added - monitor_aPMV_Block1_Zone1 Program Calling Manager\n",
      "Added - count_aPMV_comfort_hours_Block1_Zone1 Program Calling Manager\n",
      "Added - Adaptive Coefficient_Block1_Zone2 Output Variable\n",
      "Added - Adaptive Coefficient_Block1_Zone1 Output Variable\n",
      "Added - aPMV_Block1_Zone2 Output Variable\n",
      "Added - aPMV_Block1_Zone1 Output Variable\n",
      "Added - aPMV Heating Setpoint_Block1_Zone2 Output Variable\n",
      "Added - aPMV Heating Setpoint_Block1_Zone1 Output Variable\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone2 Output Variable\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone1 Output Variable\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone2 Output Variable\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone1 Output Variable\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone2 Output Variable\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone1 Output Variable\n",
      "Added - Comfortable Hours_Block1_Zone2 Output Variable\n",
      "Added - Comfortable Hours_Block1_Zone1 Output Variable\n",
      "Added - Discomfortable Hot Hours_Block1_Zone2 Output Variable\n",
      "Added - Discomfortable Hot Hours_Block1_Zone1 Output Variable\n",
      "Added - Discomfortable Cold Hours_Block1_Zone2 Output Variable\n",
      "Added - Discomfortable Cold Hours_Block1_Zone1 Output Variable\n",
      "Added - Discomfortable Total Hours_Block1_Zone2 Output Variable\n",
      "Added - Discomfortable Total Hours_Block1_Zone1 Output Variable\n",
      "Added - Occupied hours_Block1_Zone2 Output Variable\n",
      "Added - Occupied hours_Block1_Zone1 Output Variable\n",
      "Added - Adaptive Coefficient_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Adaptive Coefficient_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Heating Setpoint No Tolerance_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - aPMV Cooling Setpoint No Tolerance_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Comfortable Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Comfortable Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Hot Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Hot Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Cold Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Cold Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Total Hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Discomfortable Total Hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Occupied hours_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Occupied hours_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Operative Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Clothing Surface Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Clothing Value Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Control Fanger High Setpoint PMV Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Control Fanger Low Setpoint PMV Reporting Frequency Hourly Output:Variable data\n",
      "Not added - Zone Thermal Comfort Fanger Model PMV Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Fanger Model PPD Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Thermal Comfort Mean Radiant Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Air Relative Humidity Reporting Frequency Hourly Output:Variable data\n",
      "Added - Zone Mean Air Temperature Reporting Frequency Hourly Output:Variable data\n",
      "Added - Cooling Coil Total Cooling Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - Heating Coil Heating Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - Facility Total HVAC Electric Demand Power Reporting Frequency Hourly Output:Variable data\n",
      "Added - Facility Total HVAC Electricity Demand Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Surface Venting Window or Door Opening Factor Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Infiltration Air Change Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Infiltration Volume Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Ventilation Air Change Rate Reporting Frequency Hourly Output:Variable data\n",
      "Added - AFN Zone Ventilation Volume Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_H_SP_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_H_SP_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_C_SP_Block1_Zone2 Reporting Frequency Hourly Output:Variable data\n",
      "Added - PMV_C_SP_Block1_Zone1 Reporting Frequency Hourly Output:Variable data\n",
      "Added - Default Air Velocity for Comfort Calculations Reporting Frequency Hourly Output:Variable data\n",
      "Not added - OutputControl:Files object - Output CSV, MTR and ESO fields set to Yes\n"
     ]
    }
   ],
   "execution_count": 76
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To validate the implementation, we extract the Energy Management System (EMS) program generated by the `accim` library. The code below retrieves the `EnergyManagementSystem:Program` object responsible for calculating the aPMV setpoints for **Zone 1**.\n",
    "\n",
    "This ERL (EnergyPlus Runtime Language) code dynamically calculates the required operative temperature to meet the aPMV target based on real-time environmental variables."
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Validating the EMS Implementation\n",
    "\n",
    "The `accim` library works by writing EnergyPlus Runtime Language (ERL) code into `EnergyManagementSystem:Program` objects within the IDF file. To validate that our zone-specific logic has been correctly implemented, we can extract and inspect the generated code.\n",
    "\n",
    "The cell below retrieves the `apply_aPMV` program for **Zone 1**. Note how the program name and all internal variables are customized with the zone name (`_Block1_Zone1`), confirming the zone-specific implementation. This is the ERL code that will dynamically calculate the aPMV setpoints during the simulation."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:18.393388Z",
     "start_time": "2025-11-23T16:10:18.379527Z"
    }
   },
   "source": [
    "# Retrieve all EMS Programs\n",
    "ems_programs = building_with_apmv.idfobjects['EnergyManagementSystem:Program']\n",
    "\n",
    "# Filter for the application program specific to Zone 1\n",
    "target_zone_program = [p for p in ems_programs if 'apply_aPMV' in p.Name and 'Zone1' in p.Name]\n",
    "target_zone_program"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\n",
       " ENERGYMANAGEMENTSYSTEM:PROGRAM,\n",
       "     apply_aPMV_Block1_Zone1,    !- Name\n",
       "     if CoolingSeason == 1,    !- Program Line 1\n",
       "     set adap_coeff_Block1_Zone1 = adap_coeff_cooling_Block1_Zone1,    !- Program Line 2\n",
       "     set tolerance_cooling_sp_Block1_Zone1 = tolerance_cooling_sp_cooling_season_Block1_Zone1,    !- Program Line 3\n",
       "     set tolerance_heating_sp_Block1_Zone1 = tolerance_heating_sp_cooling_season_Block1_Zone1,    !- Program Line 4\n",
       "     elseif CoolingSeason == 0,    !- Program Line 5\n",
       "     set adap_coeff_Block1_Zone1 = adap_coeff_heating_Block1_Zone1,    !- Program Line 6\n",
       "     set tolerance_cooling_sp_Block1_Zone1 = tolerance_cooling_sp_heating_season_Block1_Zone1,    !- Program Line 7\n",
       "     set tolerance_heating_sp_Block1_Zone1 = tolerance_heating_sp_heating_season_Block1_Zone1,    !- Program Line 8\n",
       "     endif,                    !- Program Line 9\n",
       "     set aPMV_H_SP_noTol_Block1_Zone1 = pmv_heating_sp_Block1_Zone1/(1+adap_coeff_Block1_Zone1*pmv_heating_sp_Block1_Zone1),    !- Program Line 10\n",
       "     set aPMV_C_SP_noTol_Block1_Zone1 = pmv_cooling_sp_Block1_Zone1/(1+adap_coeff_Block1_Zone1*pmv_cooling_sp_Block1_Zone1),    !- Program Line 11\n",
       "     set aPMV_H_SP_Block1_Zone1 = aPMV_H_SP_noTol_Block1_Zone1+tolerance_heating_sp_Block1_Zone1,    !- Program Line 12\n",
       "     set aPMV_C_SP_Block1_Zone1 = aPMV_C_SP_noTol_Block1_Zone1+tolerance_cooling_sp_Block1_Zone1,    !- Program Line 13\n",
       "     if People_Occupant_Count_Block1_Zone1 > 0,    !- Program Line 14\n",
       "     if aPMV_H_SP_Block1_Zone1 < 0,    !- Program Line 15\n",
       "     set PMV_H_SP_act_Block1_Zone1 = aPMV_H_SP_Block1_Zone1,    !- Program Line 16\n",
       "     else,                     !- Program Line 17\n",
       "     set PMV_H_SP_act_Block1_Zone1 = 0,    !- Program Line 18\n",
       "     endif,                    !- Program Line 19\n",
       "     if aPMV_C_SP_Block1_Zone1 > 0,    !- Program Line 20\n",
       "     set PMV_C_SP_act_Block1_Zone1 = aPMV_C_SP_Block1_Zone1,    !- Program Line 21\n",
       "     else,                     !- Program Line 22\n",
       "     set PMV_C_SP_act_Block1_Zone1 = 0,    !- Program Line 23\n",
       "     endif,                    !- Program Line 24\n",
       "     else,                     !- Program Line 25\n",
       "     set PMV_H_SP_act_Block1_Zone1 = -100,    !- Program Line 26\n",
       "     set PMV_C_SP_act_Block1_Zone1 = 100,    !- Program Line 27\n",
       "     endif;                    !- Program Line 28]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 77
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Running the Adaptive Simulation\n",
    "\n",
    "Finally, we run the simulation for the `building_with_apmv` object. This model now contains the multi-zone adaptive control logic. The results will be saved in a separate directory, `sim_results_apmv`, for comparison."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:49.778685Z",
     "start_time": "2025-11-23T16:10:18.420586Z"
    }
   },
   "source": [
    "# Run adaptive simulation\n",
    "output_dir_apmv = 'sim_results_apmv'\n",
    "print(f\"Running adaptive simulation in: {output_dir_apmv}...\")\n",
    "\n",
    "ep.run_building(\n",
    "    building=building_with_apmv,\n",
    "    out_dir=output_dir_apmv,\n",
    "    epw=epwfile\n",
    ")\n",
    "print(\"Adaptive simulation finished.\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running adaptive simulation in: sim_results_apmv...\n",
      "Running EnergyPlus with stdout output suppressed...\n",
      "Adaptive simulation finished.\n"
     ]
    }
   ],
   "execution_count": 78
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the Adaptive Results\n",
    "\n",
    "Now we load and visualize the results from the adaptive simulation to observe the impact of the non-zero `λ` coefficients."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:49.980880Z",
     "start_time": "2025-11-23T16:10:49.847477Z"
    }
   },
   "source": [
    "# Load adaptive results CSV\n",
    "results_path = os.path.join(output_dir_apmv, 'eplusout.csv')\n",
    "df_apmv = pd.read_csv(results_path)\n",
    "df_apmv['Hour'] = df_apmv.index\n",
    "\n",
    "print(f\"Adaptive results loaded. Dimensions: {df_apmv.shape}\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adaptive results loaded. Dimensions: (8760, 54)\n"
     ]
    }
   ],
   "execution_count": 79
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "First, we plot the results for Zone 1."
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:50.448599Z",
     "start_time": "2025-11-23T16:10:49.996845Z"
    }
   },
   "source": [
    "# Get columns for Zone 1\n",
    "z1_apmv, z1_cool, z1_heat = get_columns(df_apmv, 'Block1_Zone1')\n",
    "\n",
    "plt.figure()\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z1_apmv, color='green', linewidth=0.5, label='Zone 1 aPMV')\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z1_cool, color='blue', linewidth=1.5, linestyle='--', label='Cooling SP (Coeff=0.3)')\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z1_heat, color='red', linewidth=1.5, linestyle='--', label='Heating SP (Coeff=0.1)')\n",
    "\n",
    "plt.title('Zone 1: High Adaptation')\n",
    "plt.ylabel('aPMV')\n",
    "plt.xlabel('Hours of the Year')\n",
    "plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12), frameon=True)\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 80
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:50.916189Z",
     "start_time": "2025-11-23T16:10:50.482475Z"
    }
   },
   "source": [
    "# Get columns for Zone 2\n",
    "z2_apmv, z2_cool, z2_heat = get_columns(df_apmv, 'Block1_Zone2')\n",
    "\n",
    "plt.figure()\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z2_apmv, color='purple', linewidth=0.5, label='Zone 2 aPMV')\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z2_cool, color='cyan', linewidth=1.5, linestyle='--', label='Cooling SP (Coeff=0.2)')\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z2_heat, color='orange', linewidth=1.5, linestyle='--', label='Heating SP (Coeff=0.05)')\n",
    "\n",
    "plt.title('Zone 2: Low Adaptation')\n",
    "plt.ylabel('aPMV')\n",
    "plt.xlabel('Hours of the Year')\n",
    "plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12), frameon=True)\n",
    "\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 81
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:51.337191Z",
     "start_time": "2025-11-23T16:10:50.949524Z"
    }
   },
   "source": [
    "# Compare cooling setpoints to see the impact of the lambda coefficient\n",
    "plt.figure()\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z1_cool, color='blue', label='Zone 1 Cooling SP (λ=0.3)')\n",
    "sns.lineplot(data=df_apmv, x='Hour', y=z2_cool, color='cyan', linestyle=':', linewidth=2, label='Zone 2 Cooling SP (λ=0.2)')\n",
    "\n",
    "plt.title('Comparison of Dynamic Setpoints between Zones')\n",
    "plt.ylabel('aPMV Setpoint')\n",
    "plt.xlabel('Hours of the Year')\n",
    "plt.legend()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 82
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleanup\n",
    "\n",
    "This final section removes the generated simulation directories to keep the workspace clean. **Warning:** This will permanently delete the simulation results."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-11-23T16:10:51.415386Z",
     "start_time": "2025-11-23T16:10:51.387288Z"
    }
   },
   "source": [
    "import shutil\n",
    "\n",
    "# List of output directories defined previously\n",
    "output_dirs = ['sim_results_pmv', 'sim_results_apmv']\n",
    "\n",
    "print(\"Starting cleanup...\")\n",
    "\n",
    "for folder in output_dirs:\n",
    "    if os.path.exists(folder):\n",
    "        try:\n",
    "            shutil.rmtree(folder)\n",
    "            print(f\"✅ Deleted directory: {folder}\")\n",
    "        except Exception as e:\n",
    "            print(f\"❌ Error deleting {folder}: {e}\")\n",
    "    else:\n",
    "        print(f\"⚠️ Directory not found (already deleted or not created): {folder}\")\n",
    "\n",
    "print(\"Cleanup finished.\")"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting cleanup...\n",
      "✅ Deleted directory: sim_results_pmv\n",
      "✅ Deleted directory: sim_results_apmv\n",
      "Cleanup finished.\n"
     ]
    }
   ],
   "execution_count": 83
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
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 },
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