{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "26228cf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import netCDF4 as nc\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import datetime as dt\n",
    "from datetime import datetime, timedelta\n",
    "from scipy.ndimage import gaussian_filter1d\n",
    "\n",
    "from matplotlib.backends.backend_pdf import PdfPages\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "59f32ba2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants\n",
    "C_p = 1005  # Specific heat capacity of dry air at constant pressure (J/kg/K)\n",
    "g = 9.81    # Gravitational acceleration (m/s^2)\n",
    "Ttrip = 273.16  # Triple point temperature in Kelvin\n",
    "Rd=287.04\n",
    "Rv=461.5\n",
    "epsilon=(Rv/Rd)-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "cc9642b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert time from seconds since 1.1.2001, 00:00:00 to datetime\n",
    "def convert_time(base_time, time_array):\n",
    "    return [base_time + timedelta(seconds=int(t)) for t in time_array]\n",
    "# Function to calculate saturation vapor pressure (es) from temperature (T)\n",
    "def calculate_saturation_vapor_pressure(T):\n",
    "    es = 610.78 * np.exp(17.2694 * (T - Ttrip) / (T - 35.86))\n",
    "    return es\n",
    "# Function to calculate specific humidity (qv) from vapor pressure (ev) and atmospheric pressure (p)\n",
    "def calculate_specific_humidity(ev, p):\n",
    "    return ev * 1000 / (p*100 + (((Rv / Rd) - 1) * (p*100 - ev)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "35d684cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\n# Function to calculate pressure at different heights using numerical integration\\ndef calculate_pressure_at_heights(df):\\n    calculated_pressures = []  # To store pressure values for all times and altitudes\\n    \\n    # Group the dataframe by Time\\n    for time, group in df.groupby('Time'):\\n        group = group.sort_values('Altitude').reset_index(drop=True)  # Sort by altitude\\n        \\n        # Start with surface pressure at the first (lowest) altitude\\n        P0 = group['Surface Pressure'].iloc[0] #* 100  # Convert hPa to Pa\\n        pressures = [P0]\\n        \\n        # Perform numerical integration for each altitude step\\n        for i in range(1, len(group)):\\n            z1 = group['Altitude'].iloc[i-1]\\n            z2 = group['Altitude'].iloc[i]\\n            T1 = group['Temperature'].iloc[i-1]\\n            \\n            # Calculate pressure difference using trapezoidal rule\\n            delta_z = z2 - z1\\n            P_prev = pressures[-1]\\n            delta_P = -g * P_prev * delta_z / (Rd * T1)\\n            P_next = P_prev + delta_P\\n            pressures.append(P_next)\\n        \\n        # Store the calculated pressures for this group\\n        calculated_pressures.extend(pressures)\\n    \\n    return calculated_pressures\\n\""
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "# Function to calculate pressure at different heights using numerical integration\n",
    "def calculate_pressure_at_heights(df):\n",
    "    calculated_pressures = []  # To store pressure values for all times and altitudes\n",
    "    \n",
    "    # Group the dataframe by Time\n",
    "    for time, group in df.groupby('Time'):\n",
    "        group = group.sort_values('Altitude').reset_index(drop=True)  # Sort by altitude\n",
    "        \n",
    "        # Start with surface pressure at the first (lowest) altitude\n",
    "        P0 = group['Surface Pressure'].iloc[0] #* 100  # Convert hPa to Pa\n",
    "        pressures = [P0]\n",
    "        \n",
    "        # Perform numerical integration for each altitude step\n",
    "        for i in range(1, len(group)):\n",
    "            z1 = group['Altitude'].iloc[i-1]\n",
    "            z2 = group['Altitude'].iloc[i]\n",
    "            T1 = group['Temperature'].iloc[i-1]\n",
    "            \n",
    "            # Calculate pressure difference using trapezoidal rule\n",
    "            delta_z = z2 - z1\n",
    "            P_prev = pressures[-1]\n",
    "            delta_P = -g * P_prev * delta_z / (Rd * T1)\n",
    "            P_next = P_prev + delta_P\n",
    "            pressures.append(P_next)\n",
    "        \n",
    "        # Store the calculated pressures for this group\n",
    "        calculated_pressures.extend(pressures)\n",
    "    \n",
    "    return calculated_pressures\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6ffd87ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_pressure_at_heights(df):\n",
    "    calculated_pressures = []  # To store pressure values for all times and altitudes\n",
    "    \n",
    "    # Group the dataframe by Time\n",
    "    for time, group in df.groupby('Time'):\n",
    "        group = group.sort_values('Altitude').reset_index(drop=True)  # Sort by altitude\n",
    "        \n",
    "        # Start with surface pressure at the first (lowest) altitude\n",
    "        P0 = group['Surface Pressure'].iloc[0]  # Initial surface pressure (hPa)\n",
    "        pressures = [P0]  # First pressure is the surface pressure\n",
    "\n",
    "        # Perform second-order (Trapezoidal Rule) integration for each altitude step\n",
    "        for i in range(1, len(group)):\n",
    "            z1 = group['Altitude'].iloc[i - 1]\n",
    "            z2 = group['Altitude'].iloc[i]\n",
    "            T1 = group['Temperature'].iloc[i - 1]\n",
    "            T2 = group['Temperature'].iloc[i]\n",
    "            P1 = pressures[-1]  # Previous pressure value\n",
    "            \n",
    "            delta_z = z2 - z1  # Altitude difference\n",
    "            \n",
    "            # First order estimate of P2 based on P1\n",
    "            P2_guess = P1 * np.exp(-g * delta_z / (Rd * T1))\n",
    "            \n",
    "            # Trapezoidal rule correction for P2\n",
    "            delta_P = 0.5 * (-(g * P1 / (Rd * T1)) + -(g * P2_guess / (Rd * T2))) * delta_z\n",
    "            P2 = P1 + delta_P\n",
    "            pressures.append(P2)\n",
    "        \n",
    "        # Store the calculated pressures for this group\n",
    "        calculated_pressures.extend(pressures)\n",
    "    \n",
    "    return calculated_pressures\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4d52b161",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate theta_v using the provided formula\n",
    "def calculate_theta_v(row):\n",
    "    T = row['Temperature']  # Temperature at the current altitude\n",
    "    qv = row['Specific Humidity (qv)']  # Specific humidity\n",
    "    z=row['Altitude']\n",
    "    # Calculate theta_v\n",
    "    theta_v = (T+g*(z/C_p)) * (1 + (epsilon * qv/1000))\n",
    "    return theta_v\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c5c63dd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# Function to calculate potential temperature (theta) based on current pressure level and surface pressure\n",
    "def calculate_potential_temperature(T, P_i, P_0):\n",
    "    \"\"\"\n",
    "    Calculate potential temperature (theta) given temperature T (K) and pressures at level P_i (hPa) and surface pressure P_0 (hPa).\n",
    "    \"\"\"\n",
    "    return T * (P_0 / P_i) ** (Rd / C_p)\n",
    "\n",
    "# Alternative method to calculate theta_v using potential temperature across altitude steps\n",
    "def calculate_theta_v_alternative_by_altitude(df):\n",
    "    \"\"\"\n",
    "    Calculate virtual potential temperature (theta_v) for each time and altitude step.\n",
    "    This function iterates over each altitude for each time step and uses the surface pressure.\n",
    "    \"\"\"\n",
    "    df = df.sort_values('Altitude').reset_index(drop=True)  # Ensure data is sorted by altitude\n",
    "    \n",
    "    theta_v_alternative = []  # Store results\n",
    "    \n",
    "    theta_list   = []\n",
    "    # Loop over rows in the DataFrame (i.e., for each altitude level)\n",
    "    for i in range(len(df)):\n",
    "        T = df.loc[i, 'Temperature'] #+ 273.15  # Convert temperature from Celsius to Kelvin\n",
    "        P_i = df.loc[i, 'Calculated Pressure']# / 100  # Pressure at current altitude in hPa\n",
    "        qv = df.loc[i, 'Specific Humidity (qv)']  # Specific humidity (kg/kg)\n",
    "        \n",
    "        if i == 0:  # At the surface (lowest altitude)\n",
    "            P_0 = P_i  # Surface pressure at the first level\n",
    "            theta = T  # For the first altitude, theta is simply T\n",
    "        else:\n",
    "            P_0 = df.loc[0, 'Calculated Pressure']# / 100  # Surface pressure (remains constant)\n",
    "            # Calculate potential temperature using surface pressure\n",
    "            theta = calculate_potential_temperature(T, P_i, P_0)\n",
    "        \n",
    "        # Calculate theta_v for this level\n",
    "        theta_v_alt = theta * (1 + (epsilon * qv / 1000))\n",
    "        theta_list.append(theta)\n",
    "        # Append the calculated theta_v to the list\n",
    "        theta_v_alternative.append(theta_v_alt)\n",
    "    \n",
    "    return theta_list, theta_v_alternative\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "da0d78ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Define the folder path\n",
    "folder_path = 'C:\\\\Users\\\\magda\\\\Master_Thesis\\\\Microwave_radiometer\\\\2024-05\\\\2024-05-12'\n",
    "\n",
    "# Get a list of all .NC files in the folder\n",
    "nc_files = [f for f in os.listdir(folder_path) if f.endswith('.NC')]\n",
    "\n",
    "# Dictionary to store the datasets\n",
    "datasets = {}\n",
    "\n",
    "# Loop through each file and open it\n",
    "for file_name in nc_files:\n",
    "    file_path = os.path.join(folder_path, file_name)\n",
    "    dataset = nc.Dataset(file_path, mode='r')\n",
    "    datasets[file_name] = dataset\n",
    "\n",
    "### MET FILE PROCESSING ###\n",
    "met_file = next((file_name for file_name in datasets.keys() if file_name.upper().endswith('.MET.NC')), None)\n",
    "surf_p_values = None\n",
    "surf_t_values = None\n",
    "time_met = None\n",
    "\n",
    "if met_file in datasets:\n",
    "    met_dataset = datasets[met_file]\n",
    "\n",
    "    try:\n",
    "        # Extract Surf_P, Surf_T, and time\n",
    "        if 'Surf_P' in met_dataset.variables:\n",
    "            surf_p_values = met_dataset.variables['Surf_P'][:]\n",
    "\n",
    "        if 'Surf_T' in met_dataset.variables:\n",
    "            surf_t_values = met_dataset.variables['Surf_T'][:]\n",
    "\n",
    "        if 'time' in met_dataset.variables:\n",
    "            times = met_dataset.variables['time'][:]\n",
    "            base_time = datetime(2001, 1, 1, 0, 0, 0)\n",
    "            time_met = convert_time(base_time, times)\n",
    "    \n",
    "    except Exception as e:\n",
    "        print(f\"Error accessing data in {met_file}: {e}\")\n",
    "\n",
    "# Create DataFrame for MET data\n",
    "df_met = pd.DataFrame({\n",
    "    'Time': time_met,\n",
    "    'Surface Temperature': surf_t_values,\n",
    "    'Surface Pressure': surf_p_values\n",
    "}) if time_met is not None else pd.DataFrame()\n",
    "\n",
    "### TPC FILE PROCESSING ###\n",
    "tpc_file = next((file_name for file_name in datasets.keys() if file_name.upper().endswith('.TPC.NC')), None)\n",
    "time_tpc = None\n",
    "altitude_tpc = None\n",
    "t_profs = None\n",
    "es_profiles = None\n",
    "\n",
    "if tpc_file:\n",
    "    tpc_dataset = datasets[tpc_file]\n",
    "\n",
    "    try:\n",
    "        # Extract time, altitude, and temperature profiles\n",
    "        time_tpc = tpc_dataset.variables['time'][:]\n",
    "        altitude_tpc = tpc_dataset.variables['altitude'][:]\n",
    "        t_profs = tpc_dataset.variables['T_prof'][:]\n",
    "\n",
    "        # Calculate saturation vapor pressure profiles\n",
    "        es_profiles = np.array([calculate_saturation_vapor_pressure(T) for T in t_profs])\n",
    "    \n",
    "    except Exception as e:\n",
    "        print(f\"Error accessing data in {tpc_file}: {e}\")\n",
    "\n",
    "# Create DataFrame for TPC data\n",
    "if time_tpc is not None:\n",
    "    times_tpc = convert_time(base_time, time_tpc)\n",
    "    \n",
    "    # Flattening the data for creating DataFrame\n",
    "    data = []\n",
    "    for i, t in enumerate(times_tpc):\n",
    "        for alt, temp, es in zip(altitude_tpc, t_profs[i, :], es_profiles[i, :]):\n",
    "            data.append([t, alt, temp, es])\n",
    "    \n",
    "    df_tpc = pd.DataFrame(data, columns=['Time', 'Altitude', 'Temperature', 'Saturation Vapor Pressure'])\n",
    "else:\n",
    "    df_tpc = pd.DataFrame()\n",
    "\n",
    "### HPC FILE PROCESSING ###\n",
    "hpc_file = next((file_name for file_name in datasets.keys() if file_name.upper().endswith('.HPC.NC')), None)\n",
    "time_hpc = None\n",
    "altitude_hpc = None\n",
    "rh_profiles = None\n",
    "\n",
    "if hpc_file:\n",
    "    hpc_dataset = datasets[hpc_file]\n",
    "\n",
    "    try:\n",
    "        # Extract time, altitude, and relative humidity profiles\n",
    "        time_hpc = hpc_dataset.variables['time'][:]\n",
    "        altitude_hpc = hpc_dataset.variables['altitude'][:]\n",
    "        rh_profiles = hpc_dataset.variables['RH_prof'][:]\n",
    "    \n",
    "    except Exception as e:\n",
    "        print(f\"Error accessing data in {hpc_file}: {e}\")\n",
    "\n",
    "# Create DataFrame for HPC data\n",
    "if time_hpc is not None:\n",
    "    times_hpc = convert_time(base_time, time_hpc)\n",
    "\n",
    "    # Flattening the data for creating DataFrame\n",
    "    data = []\n",
    "    for i, t in enumerate(times_hpc):\n",
    "        for alt, rh in zip(altitude_hpc, rh_profiles[i, :]):\n",
    "            data.append([t, alt, rh])\n",
    "    \n",
    "    df_hpc = pd.DataFrame(data, columns=['Time', 'Altitude', 'Relative Humidity'])\n",
    "else:\n",
    "    df_hpc = pd.DataFrame()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9997f77d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Time  Surface Temperature  Surface Pressure  Altitude  \\\n",
      "0 2024-05-12 00:03:54           287.859985       1020.900024         0   \n",
      "1 2024-05-12 00:03:54           287.859985       1020.900024        10   \n",
      "2 2024-05-12 00:03:54           287.859985       1020.900024        25   \n",
      "3 2024-05-12 00:03:54           287.859985       1020.900024        50   \n",
      "4 2024-05-12 00:03:54           287.859985       1020.900024        75   \n",
      "\n",
      "   Relative Humidity  Temperature  Saturation Vapor Pressure  \n",
      "0          75.947235   288.277252                1718.143677  \n",
      "1          73.894501   288.242737                1714.333374  \n",
      "2          70.982712   288.176941                1707.090088  \n",
      "3          66.992439   288.063812                1694.698242  \n",
      "4          63.840687   288.030151                1691.026733  \n"
     ]
    }
   ],
   "source": [
    "### MERGE DATAFRAMES ###\n",
    "\n",
    "# Merge TPC and HPC data on 'Time' and 'Altitude'\n",
    "df_combined = pd.merge(df_hpc, df_tpc, on=['Time', 'Altitude'], how='inner')\n",
    "\n",
    "# Merge with MET data on 'Time'\n",
    "df_combined_pressure = pd.merge(df_met, df_combined, on='Time', how='inner')\n",
    "\n",
    "# Display the first few rows of the final combined DataFrame\n",
    "print(df_combined_pressure.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b10a2dac",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      Time  Surface Temperature  Surface Pressure  Altitude  \\\n",
      "0      2024-05-12 00:03:54           287.859985       1020.900024         0   \n",
      "1      2024-05-12 00:03:54           287.859985       1020.900024        10   \n",
      "2      2024-05-12 00:03:54           287.859985       1020.900024        25   \n",
      "3      2024-05-12 00:03:54           287.859985       1020.900024        50   \n",
      "4      2024-05-12 00:03:54           287.859985       1020.900024        75   \n",
      "...                    ...                  ...               ...       ...   \n",
      "108340 2024-05-12 23:59:18           290.760010       1011.200012      9000   \n",
      "108341 2024-05-12 23:59:18           290.760010       1011.200012      9300   \n",
      "108342 2024-05-12 23:59:18           290.760010       1011.200012      9600   \n",
      "108343 2024-05-12 23:59:18           290.760010       1011.200012      9800   \n",
      "108344 2024-05-12 23:59:18           290.760010       1011.200012     10000   \n",
      "\n",
      "        Relative Humidity  Temperature  Saturation Vapor Pressure  \n",
      "0               75.947235   288.277252                1718.143677  \n",
      "1               73.894501   288.242737                1714.333374  \n",
      "2               70.982712   288.176941                1707.090088  \n",
      "3               66.992439   288.063812                1694.698242  \n",
      "4               63.840687   288.030151                1691.026733  \n",
      "...                   ...          ...                        ...  \n",
      "108340          53.742638   230.424057                  13.756579  \n",
      "108341          51.621475   227.954407                  10.493198  \n",
      "108342          49.886677   225.485916                   7.948759  \n",
      "108343          48.567566   223.879822                   6.608850  \n",
      "108344          47.364021   222.303619                   5.496700  \n",
      "\n",
      "[108345 rows x 7 columns]\n"
     ]
    }
   ],
   "source": [
    "print(df_combined_pressure)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5a7add40",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      Time  Surface Temperature  Surface Pressure  Altitude  \\\n",
      "0      2024-05-12 00:03:54           287.859985       1020.900024         0   \n",
      "1      2024-05-12 00:03:54           287.859985       1020.900024        10   \n",
      "2      2024-05-12 00:03:54           287.859985       1020.900024        25   \n",
      "3      2024-05-12 00:03:54           287.859985       1020.900024        50   \n",
      "4      2024-05-12 00:03:54           287.859985       1020.900024        75   \n",
      "...                    ...                  ...               ...       ...   \n",
      "108340 2024-05-12 23:59:18           290.760010       1011.200012      9000   \n",
      "108341 2024-05-12 23:59:18           290.760010       1011.200012      9300   \n",
      "108342 2024-05-12 23:59:18           290.760010       1011.200012      9600   \n",
      "108343 2024-05-12 23:59:18           290.760010       1011.200012      9800   \n",
      "108344 2024-05-12 23:59:18           290.760010       1011.200012     10000   \n",
      "\n",
      "        Relative Humidity  Temperature  Saturation Vapor Pressure  \\\n",
      "0               75.947235   288.277252                1718.143677   \n",
      "1               73.894501   288.242737                1714.333374   \n",
      "2               70.982712   288.176941                1707.090088   \n",
      "3               66.992439   288.063812                1694.698242   \n",
      "4               63.840687   288.030151                1691.026733   \n",
      "...                   ...          ...                        ...   \n",
      "108340          53.742638   230.424057                  13.756579   \n",
      "108341          51.621475   227.954407                  10.493198   \n",
      "108342          49.886677   225.485916                   7.948759   \n",
      "108343          48.567566   223.879822                   6.608850   \n",
      "108344          47.364021   222.303619                   5.496700   \n",
      "\n",
      "        Calculated Pressure  \n",
      "0               1020.900024  \n",
      "1               1019.690351  \n",
      "2               1017.878213  \n",
      "3               1014.864201  \n",
      "4               1011.858349  \n",
      "...                     ...  \n",
      "108340           313.207155  \n",
      "108341           299.501772  \n",
      "108342           286.256534  \n",
      "108343           277.678427  \n",
      "108344           269.298927  \n",
      "\n",
      "[108345 rows x 8 columns]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Apply the pressure calculation for each time and altitude\n",
    "df_combined_pressure['Calculated Pressure'] = calculate_pressure_at_heights(df_combined_pressure)\n",
    "\n",
    "# Display the updated DataFrame with calculated pressures\n",
    "print(df_combined_pressure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2c2f2e9c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      Time  Surface Temperature  Surface Pressure  Altitude  \\\n",
      "0      2024-05-12 00:03:54           287.859985       1020.900024         0   \n",
      "1      2024-05-12 00:03:54           287.859985       1020.900024        10   \n",
      "2      2024-05-12 00:03:54           287.859985       1020.900024        25   \n",
      "3      2024-05-12 00:03:54           287.859985       1020.900024        50   \n",
      "4      2024-05-12 00:03:54           287.859985       1020.900024        75   \n",
      "...                    ...                  ...               ...       ...   \n",
      "108340 2024-05-12 23:59:18           290.760010       1011.200012      9000   \n",
      "108341 2024-05-12 23:59:18           290.760010       1011.200012      9300   \n",
      "108342 2024-05-12 23:59:18           290.760010       1011.200012      9600   \n",
      "108343 2024-05-12 23:59:18           290.760010       1011.200012      9800   \n",
      "108344 2024-05-12 23:59:18           290.760010       1011.200012     10000   \n",
      "\n",
      "        Relative Humidity  Temperature  Saturation Vapor Pressure  \\\n",
      "0               75.947235   288.277252                1718.143677   \n",
      "1               73.894501   288.242737                1714.333374   \n",
      "2               70.982712   288.176941                1707.090088   \n",
      "3               66.992439   288.063812                1694.698242   \n",
      "4               63.840687   288.030151                1691.026733   \n",
      "...                   ...          ...                        ...   \n",
      "108340          53.742638   230.424057                  13.756579   \n",
      "108341          51.621475   227.954407                  10.493198   \n",
      "108342          49.886677   225.485916                   7.948759   \n",
      "108343          48.567566   223.879822                   6.608850   \n",
      "108344          47.364021   222.303619                   5.496700   \n",
      "\n",
      "        Calculated Pressure           ev  Specific Humidity (qv)  \n",
      "0               1020.900024  1304.882690                7.988450  \n",
      "1               1019.690351  1266.798096                7.763440  \n",
      "2               1017.878213  1211.738770                7.437770  \n",
      "3               1014.864201  1135.319702                6.987494  \n",
      "4               1011.858349  1079.562988                6.662759  \n",
      "...                     ...          ...                     ...  \n",
      "108340           313.207155     7.393149                0.146827  \n",
      "108341           299.501772     5.416744                0.112497  \n",
      "108342           286.256534     3.965372                0.086163  \n",
      "108343           277.678427     3.209758                0.071898  \n",
      "108344           269.298927     2.603458                0.060132  \n",
      "\n",
      "[108345 rows x 10 columns]\n"
     ]
    }
   ],
   "source": [
    "# Calculate vapor pressure and add it as a new column\n",
    "df_combined_pressure['ev'] = df_combined_pressure['Relative Humidity'] * df_combined_pressure['Saturation Vapor Pressure'] / 100\n",
    "# Apply the specific humidity calculation\n",
    "df_combined_pressure['Specific Humidity (qv)'] = df_combined_pressure.apply(\n",
    "    lambda row: calculate_specific_humidity(row['ev'], row['Calculated Pressure']), axis=1\n",
    ")\n",
    "print(df_combined_pressure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1b65c68a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      Time  Surface Temperature  Surface Pressure  Altitude  \\\n",
      "0      2024-05-12 00:03:54           287.859985       1020.900024         0   \n",
      "1      2024-05-12 00:03:54           287.859985       1020.900024        10   \n",
      "2      2024-05-12 00:03:54           287.859985       1020.900024        25   \n",
      "3      2024-05-12 00:03:54           287.859985       1020.900024        50   \n",
      "4      2024-05-12 00:03:54           287.859985       1020.900024        75   \n",
      "...                    ...                  ...               ...       ...   \n",
      "108340 2024-05-12 23:59:18           290.760010       1011.200012      9000   \n",
      "108341 2024-05-12 23:59:18           290.760010       1011.200012      9300   \n",
      "108342 2024-05-12 23:59:18           290.760010       1011.200012      9600   \n",
      "108343 2024-05-12 23:59:18           290.760010       1011.200012      9800   \n",
      "108344 2024-05-12 23:59:18           290.760010       1011.200012     10000   \n",
      "\n",
      "        Relative Humidity  Temperature  Saturation Vapor Pressure  \\\n",
      "0               75.947235   288.277252                1718.143677   \n",
      "1               73.894501   288.242737                1714.333374   \n",
      "2               70.982712   288.176941                1707.090088   \n",
      "3               66.992439   288.063812                1694.698242   \n",
      "4               63.840687   288.030151                1691.026733   \n",
      "...                   ...          ...                        ...   \n",
      "108340          53.742638   230.424057                  13.756579   \n",
      "108341          51.621475   227.954407                  10.493198   \n",
      "108342          49.886677   225.485916                   7.948759   \n",
      "108343          48.567566   223.879822                   6.608850   \n",
      "108344          47.364021   222.303619                   5.496700   \n",
      "\n",
      "        Calculated Pressure           ev  Specific Humidity (qv)     Theta_v  \n",
      "0               1020.900024  1304.882690                7.988450  289.676924  \n",
      "1               1019.690351  1266.798096                7.763440  289.700894  \n",
      "2               1017.878213  1211.738770                7.437770  289.724807  \n",
      "3               1014.864201  1135.319702                6.987494  289.777331  \n",
      "4               1011.858349  1079.562988                6.662759  289.931600  \n",
      "...                     ...          ...                     ...         ...  \n",
      "108340           313.207155     7.393149                0.146827  318.303206  \n",
      "108341           299.501772     5.416744                0.112497  318.755304  \n",
      "108342           286.256534     3.965372                0.086163  319.210095  \n",
      "108343           277.678427     3.209758                0.071898  319.553487  \n",
      "108344           269.298927     2.603458                0.060132  319.927252  \n",
      "\n",
      "[108345 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "# Apply the calculation to the DataFrame\n",
    "df_combined_pressure['Theta_v'] = df_combined_pressure.apply(calculate_theta_v, axis=1)\n",
    "print(df_combined_pressure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "06cbe02a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Time  Altitude       Theta     Theta_v Theta_v_Alternative\n",
      "0 2024-05-12 00:03:54         0  288.277252  289.676924          289.676924\n",
      "1 2024-05-12 00:03:54        10  288.340359  289.700894          289.700905\n",
      "2 2024-05-12 00:03:54        25  288.421029  289.724807          289.724866\n",
      "3 2024-05-12 00:03:54        50  288.552097  289.777331          289.777557\n",
      "4 2024-05-12 00:03:54        75  288.762912  289.931600          289.932274\n"
     ]
    }
   ],
   "source": [
    "# Apply the altitude-based theta_v calculation for each time step\n",
    "#df_combined_pressure['Theta_v_Alternative'] = df_combined_pressure.groupby('Time').apply(calculate_theta_v_alternative_by_altitude).explode().values\n",
    "# 1) Run groupby.apply once, producing a Series of (theta_list, theta_v_list) tuples\n",
    "grouped = df_combined_pressure.groupby(\"Time\") \\\n",
    "            .apply(calculate_theta_v_alternative_by_altitude)\n",
    "\n",
    "# 2) Extract the “theta_list” (first element of each tuple), explode, and align\n",
    "theta_series = (\n",
    "    grouped\n",
    "      .apply(lambda tup: tup[0])  # take the first element → [θ0, θ1, …]\n",
    "      .explode()                  # flatten into a single long Series\n",
    "      .reset_index(drop=True)     # drop the Time index so it lines up with df_combined_pressure\n",
    ")\n",
    "\n",
    "# 3) Extract the “theta_v_alternative” (second element), explode, and align\n",
    "theta_v_series = (\n",
    "    grouped\n",
    "      .apply(lambda tup: tup[1])  # take the second element → [θᵥ0, θᵥ1, …]\n",
    "      .explode()\n",
    "      .reset_index(drop=True)\n",
    ")\n",
    "\n",
    "# 4) Assign these back as two new columns\n",
    "df_combined_pressure[\"Theta\"] = theta_series.values\n",
    "df_combined_pressure[\"Theta_v_Alternative\"]   = theta_v_series.values\n",
    "\n",
    "# Now each row in df_combined_pressure has both the θ and θᵥ that correspond\n",
    "# to its altitude (grouped by Time).\n",
    "\n",
    "# Display the updated DataFrame with the alternative theta_v column\n",
    "print(df_combined_pressure[['Time', 'Altitude', 'Theta','Theta_v', 'Theta_v_Alternative']].head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "66bf7c9e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"\\n# Select data for a single time step (e.g., the first unique time in the dataset)\\nselected_time = df_combined_pressure['Time'].unique()[600]  # Get the first unique time\\n\\n# Filter the DataFrame for the selected time\\ndf_single_time = df_combined_pressure[df_combined_pressure['Time'] == selected_time]\\n\\n# Create a figure and axis\\nfig, ax1 = plt.subplots(figsize=(10, 6))\\n\\n# Plot Specific Humidity\\nax1.set_xlabel('Specific Humidity (g/kg)', color='blue')\\nax1.set_ylabel('Altitude (m)', color='blue')\\nax1.plot(df_single_time['Specific Humidity (qv)'], df_single_time['Altitude'], label='Specific Humidity (qv)', color='blue')\\nax1.tick_params(axis='y', labelcolor='blue')\\n\\n# Create a second y-axis for Theta_v\\nax2 = ax1.twinx()\\nax2.set_ylabel('Theta_v (K)', color='red')\\nax2.plot(df_single_time['Theta_v'], df_single_time['Altitude'], label='Theta_v', color='red')\\nax2.tick_params(axis='y', labelcolor='red')\\n\\n# Set the title and grid\\nplt.title(f'Vertical Profile of Specific Humidity and Theta_v\\nTime: {selected_time}')\\nax1.grid(True)\\n\\nplt.show()\\n\""
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "# Select data for a single time step (e.g., the first unique time in the dataset)\n",
    "selected_time = df_combined_pressure['Time'].unique()[600]  # Get the first unique time\n",
    "\n",
    "# Filter the DataFrame for the selected time\n",
    "df_single_time = df_combined_pressure[df_combined_pressure['Time'] == selected_time]\n",
    "\n",
    "# Create a figure and axis\n",
    "fig, ax1 = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "# Plot Specific Humidity\n",
    "ax1.set_xlabel('Specific Humidity (g/kg)', color='blue')\n",
    "ax1.set_ylabel('Altitude (m)', color='blue')\n",
    "ax1.plot(df_single_time['Specific Humidity (qv)'], df_single_time['Altitude'], label='Specific Humidity (qv)', color='blue')\n",
    "ax1.tick_params(axis='y', labelcolor='blue')\n",
    "\n",
    "# Create a second y-axis for Theta_v\n",
    "ax2 = ax1.twinx()\n",
    "ax2.set_ylabel('Theta_v (K)', color='red')\n",
    "ax2.plot(df_single_time['Theta_v'], df_single_time['Altitude'], label='Theta_v', color='red')\n",
    "ax2.tick_params(axis='y', labelcolor='red')\n",
    "\n",
    "# Set the title and grid\n",
    "plt.title(f'Vertical Profile of Specific Humidity and Theta_v\\nTime: {selected_time}')\n",
    "ax1.grid(True)\n",
    "\n",
    "plt.show()\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d0bd75ec",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select data for a single time step (e.g., the first unique time in the dataset)\n",
    "selected_time = df_combined_pressure['Time'].unique()[800]  # Get the first unique time\n",
    "\n",
    "# Filter the DataFrame for the selected time\n",
    "df_single_time = df_combined_pressure[df_combined_pressure['Time'] == selected_time]\n",
    "\n",
    "# Create a figure and axis\n",
    "fig, ax1 = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "# Plot Specific Humidity\n",
    "ax1.set_xlabel('Specific Humidity (g/kg)', color='blue')\n",
    "ax1.set_ylabel('Altitude (m)', color='blue')\n",
    "ax1.plot(df_single_time['Specific Humidity (qv)'], df_single_time['Altitude'], label='Specific Humidity (qv)', color='blue')\n",
    "ax1.tick_params(axis='y', labelcolor='blue')\n",
    "\n",
    "# Create a second y-axis for Theta_v\n",
    "ax2 = ax1.twinx()\n",
    "ax2.set_ylabel('Theta_v (K)', color='red')\n",
    "\n",
    "# Plot Theta_v (original) in red\n",
    "ax2.plot(df_single_time['Theta_v'], df_single_time['Altitude'], label='Theta_v', color='red')\n",
    "\n",
    "# Plot Theta_v_Alternative (new method) in green\n",
    "ax2.plot(df_single_time['Theta_v_Alternative'], df_single_time['Altitude'], label='Theta_v_Alternative', color='green', linestyle='--')\n",
    "\n",
    "# Set y-axis ticks for Theta_v\n",
    "ax2.tick_params(axis='y', labelcolor='red')\n",
    "\n",
    "# Add legend for both Theta_v and Theta_v_Alternative\n",
    "ax2.legend(loc='upper left')\n",
    "\n",
    "# Set the title and grid\n",
    "plt.title(f'Vertical Profile of Specific Humidity and Theta_v\\nTime: {selected_time}')\n",
    "ax1.grid(True)\n",
    "\n",
    "# Show plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fc341c22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select data for a single time step (e.g., the first unique time in the dataset)\n",
    "selected_time = df_combined_pressure['Time'].unique()[600]  # Get the selected time\n",
    "\n",
    "# Filter the DataFrame for the selected time\n",
    "df_single_time = df_combined_pressure[df_combined_pressure['Time'] == selected_time]\n",
    "\n",
    "# Create a figure and axis\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "# Plot Theta_v (original) in red\n",
    "ax.plot(df_single_time['Temperature'], df_single_time['Altitude'], label='Temperature (K)', color='blue')\n",
    "\n",
    "# Plot Theta_v (original) in red\n",
    "ax.plot(df_single_time['Theta_v'], df_single_time['Altitude'], label='Theta_v (Original)', color='red')\n",
    "\n",
    "# Plot Theta_v_Alternative (new method) in green\n",
    "ax.plot(df_single_time['Theta_v_Alternative'], df_single_time['Altitude'], label='Theta_v (Alternative)', color='green', linestyle='--')\n",
    "\n",
    "# Set axis labels\n",
    "ax.set_xlabel('Theta_v (K)', color='black')\n",
    "ax.set_ylabel('Altitude (m)', color='black')\n",
    "\n",
    "# Add a legend to distinguish the two curves\n",
    "ax.legend(loc='upper left')\n",
    "\n",
    "# Set the title and grid\n",
    "plt.title(f'Vertical Profile of Theta_v (Original and Alternative)\\nTime: {selected_time}')\n",
    "ax.grid(True)\n",
    "plt.ylim(0,450)\n",
    "# Show plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "56987b4d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Time                                Surface Temperature  \\\n",
      "0 2024-05-12 00:03:54  [287.8599853515625, 287.8599853515625, 287.859...   \n",
      "1 2024-05-12 00:05:10  [287.8599853515625, 287.8599853515625, 287.859...   \n",
      "2 2024-05-12 00:06:12  [287.760009765625, 287.760009765625, 287.76000...   \n",
      "3 2024-05-12 00:07:13  [287.8599853515625, 287.8599853515625, 287.859...   \n",
      "4 2024-05-12 00:08:15  [287.8599853515625, 287.8599853515625, 287.859...   \n",
      "\n",
      "                                    Surface Pressure  \\\n",
      "0  [1020.9000244140625, 1020.9000244140625, 1020....   \n",
      "1  [1020.9000244140625, 1020.9000244140625, 1020....   \n",
      "2  [1020.9000244140625, 1020.9000244140625, 1020....   \n",
      "3  [1020.9000244140625, 1020.9000244140625, 1020....   \n",
      "4  [1020.9000244140625, 1020.9000244140625, 1020....   \n",
      "\n",
      "                                            Altitude  \\\n",
      "0  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "1  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "2  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "3  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "4  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "\n",
      "                                   Relative Humidity  \\\n",
      "0  [75.94723510742188, 73.89450073242188, 70.9827...   \n",
      "1  [75.9693832397461, 73.91952514648438, 71.01219...   \n",
      "2  [75.889892578125, 73.83600616455078, 70.928436...   \n",
      "3  [75.91857147216797, 73.86779022216797, 70.9642...   \n",
      "4  [75.96250915527344, 73.91497039794922, 71.0142...   \n",
      "\n",
      "                                         Temperature  \\\n",
      "0  [288.2772521972656, 288.24273681640625, 288.17...   \n",
      "1  [288.2772521972656, 288.24273681640625, 288.17...   \n",
      "2  [288.2772521972656, 288.24273681640625, 288.17...   \n",
      "3  [288.2772521972656, 288.24273681640625, 288.17...   \n",
      "4  [288.2772521972656, 288.24273681640625, 288.17...   \n",
      "\n",
      "                           Saturation Vapor Pressure  \\\n",
      "0  [1718.1436767578125, 1714.3333740234375, 1707....   \n",
      "1  [1718.1436767578125, 1714.3333740234375, 1707....   \n",
      "2  [1718.1436767578125, 1714.3333740234375, 1707....   \n",
      "3  [1718.1436767578125, 1714.3333740234375, 1707....   \n",
      "4  [1718.1436767578125, 1714.3333740234375, 1707....   \n",
      "\n",
      "                                 Calculated Pressure  \\\n",
      "0  [1020.9000244140625, 1019.6903512340347, 1017....   \n",
      "1  [1020.9000244140625, 1019.6903512340347, 1017....   \n",
      "2  [1020.9000244140625, 1019.6903512340347, 1017....   \n",
      "3  [1020.9000244140625, 1019.6903512340347, 1017....   \n",
      "4  [1020.9000244140625, 1019.6903512340347, 1017....   \n",
      "\n",
      "                                                  ev  \\\n",
      "0  [1304.8826904296875, 1266.798095703125, 1211.7...   \n",
      "1  [1305.26318359375, 1267.22705078125, 1212.2420...   \n",
      "2  [1303.8974609375, 1265.7952880859375, 1210.812...   \n",
      "3  [1304.39013671875, 1266.3402099609375, 1211.42...   \n",
      "4  [1305.14501953125, 1267.14892578125, 1212.2778...   \n",
      "\n",
      "                              Specific Humidity (qv)  \\\n",
      "0  [7.988449587460842, 7.7634404220181485, 7.4377...   \n",
      "1  [7.990790267378829, 7.7660816369664705, 7.4408...   \n",
      "2  [7.9823887816805055, 7.757265844588505, 7.4320...   \n",
      "3  [7.9854195544841735, 7.760621080941051, 7.4358...   \n",
      "4  [7.990063356768556, 7.765600595482164, 7.44109...   \n",
      "\n",
      "                                             Theta_v  \\\n",
      "0  [289.67692434117635, 289.70089432078026, 289.7...   \n",
      "1  [289.67733445636117, 289.7013571945948, 289.72...   \n",
      "2  [289.6758624153386, 289.6998122239939, 289.723...   \n",
      "3  [289.6763934430707, 289.70040023030134, 289.72...   \n",
      "4  [289.67720709290705, 289.70127289191163, 289.7...   \n",
      "\n",
      "                                               Theta  \\\n",
      "0  [288.27725, 288.3403594523984, 288.42102929820...   \n",
      "1  [288.27725, 288.3403594523984, 288.42102929820...   \n",
      "2  [288.27725, 288.3403594523984, 288.42102929820...   \n",
      "3  [288.27725, 288.3403594523984, 288.42102929820...   \n",
      "4  [288.27725, 288.3403594523984, 288.42102929820...   \n",
      "\n",
      "                                 Theta_v_Alternative  \n",
      "0  [289.67692434117635, 289.7009050669419, 289.72...  \n",
      "1  [289.67733445636117, 289.7013679407736, 289.72...  \n",
      "2  [289.6758624153386, 289.69982297011546, 289.72...  \n",
      "3  [289.6763934430707, 289.70041097644474, 289.72...  \n",
      "4  [289.67720709290705, 289.7012836380874, 289.72...  \n"
     ]
    }
   ],
   "source": [
    "# Ensure the 'Time' column is a datetime type\n",
    "df_combined_pressure['Time'] = pd.to_datetime(df_combined_pressure['Time'])\n",
    "\n",
    "# Group by 'Time' and aggregate all other columns into lists\n",
    "df_aggregated = df_combined_pressure.groupby('Time').agg(lambda x: list(x)).reset_index()\n",
    "\n",
    "# Display the first few rows of the aggregated DataFrame\n",
    "print(df_aggregated.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "35786699",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Time', 'Surface Temperature', 'Surface Pressure', 'Altitude',\n",
      "       'Relative Humidity', 'Temperature', 'Saturation Vapor Pressure',\n",
      "       'Calculated Pressure', 'ev', 'Specific Humidity (qv)', 'Theta_v',\n",
      "       'Theta', 'Theta_v_Alternative'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df_aggregated.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "85660919",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 Time                                           Altitude  \\\n",
      "0 2024-05-12 00:00:00  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "1 2024-05-12 00:10:00  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "2 2024-05-12 00:20:00  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "3 2024-05-12 00:30:00  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "4 2024-05-12 00:40:00  [0, 10, 25, 50, 75, 100, 130, 160, 190, 220, 2...   \n",
      "\n",
      "                                 Surface Temperature  \\\n",
      "0  [287.82666015625, 287.82666015625, 287.8266601...   \n",
      "1  [287.7850036621094, 287.7850036621094, 287.785...   \n",
      "2  [287.8377685546875, 287.8377685546875, 287.837...   \n",
      "3  [287.817138671875, 287.817138671875, 287.81713...   \n",
      "4  [287.760009765625, 287.760009765625, 287.76000...   \n",
      "\n",
      "                                    Surface Pressure  \\\n",
      "0  [1020.8833516438802, 1020.8833516438802, 1020....   \n",
      "1  [1020.7999877929688, 1020.7999877929688, 1020....   \n",
      "2  [1020.7999877929688, 1020.7999877929688, 1020....   \n",
      "3  [1020.7285766601562, 1020.7285766601562, 1020....   \n",
      "4  [1020.6249847412109, 1020.6249847412109, 1020....   \n",
      "\n",
      "                                   Relative Humidity  \\\n",
      "0  [75.89658991495769, 73.84461212158203, 70.9375...   \n",
      "1  [75.67946910858154, 73.6211576461792, 70.70123...   \n",
      "2  [75.60673692491319, 73.54789479573567, 70.6258...   \n",
      "3  [75.53295353480748, 73.4705581665039, 70.54012...   \n",
      "4  [75.91616344451904, 73.85508346557617, 70.9266...   \n",
      "\n",
      "                                         Temperature  \\\n",
      "0  [288.2772521972656, 288.24273681640625, 288.17...   \n",
      "1  [288.37294006347656, 288.30745697021484, 288.1...   \n",
      "2  [288.6600036621094, 288.5016174316406, 288.267...   \n",
      "3  [288.6154479980469, 288.4264351981027, 288.149...   \n",
      "4  [288.5768013000488, 288.3759574890137, 288.082...   \n",
      "\n",
      "                           Saturation Vapor Pressure  \\\n",
      "0  [1718.1436767578125, 1714.3333740234375, 1707....   \n",
      "1  [1728.8328857421875, 1721.5238952636719, 1709....   \n",
      "2  [1760.9005126953125, 1743.095458984375, 1717.0...   \n",
      "3  [1755.8781912667412, 1734.7063511439733, 1704....   \n",
      "4  [1751.5370178222656, 1729.0910339355469, 1696....   \n",
      "\n",
      "                                 Calculated Pressure  \\\n",
      "0  [1020.8833516438802, 1019.6736982195606, 1017....   \n",
      "1  [1020.7999877929688, 1019.5907690928705, 1017....   \n",
      "2  [1020.7999877929688, 1019.5917769299119, 1017....   \n",
      "3  [1020.7285766601562, 1019.5201997235853, 1017....   \n",
      "4  [1020.6249847412109, 1019.4165438641592, 1017....   \n",
      "\n",
      "                                                  ev  \\\n",
      "0  [1304.0124918619792, 1265.9428100585938, 1210....   \n",
      "1  [1308.3775939941406, 1267.4102935791016, 1208....   \n",
      "2  [1331.3593885633682, 1282.010009765625, 1212.7...   \n",
      "3  [1326.2694266183037, 1274.5033307756696, 1202....   \n",
      "4  [1329.6912231445312, 1277.013198852539, 1203.4...   \n",
      "\n",
      "                              Specific Humidity (qv)  \\\n",
      "0  [7.9832271373492505, 7.75830118920399, 7.43313...   \n",
      "1  [8.01074314529748, 7.767974346619334, 7.419783...   \n",
      "2  [8.152144961387018, 7.8578735746444925, 7.4444...   \n",
      "3  [8.121394764102426, 7.81219449733853, 7.379317...   \n",
      "4  [8.143283753852451, 7.828453399164527, 7.38838...   \n",
      "\n",
      "                                               Theta  \\\n",
      "0  [288.2772521972656, 288.3403594523984, 288.421...   \n",
      "1  [288.37294006347656, 288.4050743667076, 288.44...   \n",
      "2  [288.6600036621094, 288.5992191096352, 288.511...   \n",
      "3  [288.6154479980469, 288.52403169512706, 288.39...   \n",
      "4  [288.5768013000488, 288.47355198339045, 288.32...   \n",
      "\n",
      "                                             Theta_v  \\\n",
      "0  [289.6760093053031, 289.6999936684885, 289.723...   \n",
      "1  [289.7769932345668, 289.7667187174541, 289.744...   \n",
      "2  [290.09025365164536, 289.9775607752136, 289.81...   \n",
      "3  [290.04008350864507, 289.8940100711119, 289.68...   \n",
      "4  [290.0050853078217, 289.84614281262554, 289.62...   \n",
      "\n",
      "                                 Theta_v_Alternative  \n",
      "0  [289.6760093053031, 289.7000044146168, 289.724...  \n",
      "1  [289.7769932345668, 289.76672419907607, 289.74...  \n",
      "2  [290.09025365164536, 289.97755046389756, 289.8...  \n",
      "3  [290.04008350864507, 289.89399455457726, 289.6...  \n",
      "4  [290.0050853078217, 289.84612528369377, 289.62...  \n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Function to compute the mean profile for arrays\n",
    "def compute_mean_profile(profiles):\n",
    "    if len(profiles) == 0:\n",
    "        return []\n",
    "    profiles_array = np.array(profiles)  # Directly convert to a numpy array\n",
    "    return np.mean(profiles_array, axis=0)\n",
    "\n",
    "# Resample and average function\n",
    "def resample_and_average(df, interval='10T'):\n",
    "    resampled = df.resample(interval).agg({\n",
    "        'Altitude': 'first',  # Assuming altitude doesn't change frequently\n",
    "        'Surface Temperature': lambda x: compute_mean_profile(list(x)),\n",
    "        'Surface Pressure': lambda x: compute_mean_profile(list(x)),\n",
    "        'Relative Humidity': lambda x: compute_mean_profile(list(x)),\n",
    "        'Temperature': lambda x: compute_mean_profile(list(x)),\n",
    "        'Saturation Vapor Pressure': lambda x: compute_mean_profile(list(x)),\n",
    "        'Calculated Pressure': lambda x: compute_mean_profile(list(x)),\n",
    "        'ev': lambda x: compute_mean_profile(list(x)),\n",
    "        'Specific Humidity (qv)': lambda x: compute_mean_profile(list(x)),\n",
    "        'Theta': lambda x: compute_mean_profile(list(x)),\n",
    "        'Theta_v': lambda x: compute_mean_profile(list(x)),\n",
    "        'Theta_v_Alternative': lambda x: compute_mean_profile(list(x)),\n",
    "    })\n",
    "    return resampled\n",
    "\n",
    "# Make sure your DataFrame is indexed by 'Time'\n",
    "df_aggregated.set_index('Time', inplace=True)\n",
    "\n",
    "# Apply the resampling function\n",
    "df_10min_avg = resample_and_average(df_aggregated)\n",
    "\n",
    "# Reset index if you want 'Time' back as a column\n",
    "df_10min_avg.reset_index(inplace=True)\n",
    "\n",
    "# Display the first few rows of the averaged DataFrame\n",
    "print(df_10min_avg.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3b782282",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved DataFrame to: C:\\Users\\magda\\Master_Thesis\\Microwave_radiometer\\2024-05\\2024-05-12\\MWR_vertical_dataset_10min.parquet\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# 1. Build the output‐path inside the same folder\n",
    "parquet_path = os.path.join(folder_path, \"MWR_vertical_dataset_10min.parquet\")\n",
    "\n",
    "# 2. Save `df` to Parquet\n",
    "df_10min_avg.to_parquet(parquet_path, engine=\"pyarrow\", index=False)\n",
    "\n",
    "print(f\"Saved DataFrame to: {parquet_path}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "99f97267",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Select the 10th entry in the averaged DataFrame\n",
    "example_data = df_10min_avg.iloc[60]  # Indexing starts at 0, so 9 is the 10th entry\n",
    "\n",
    "# Create subplots in one row\n",
    "fig, axs = plt.subplots(1, 4, figsize=(20, 5), sharey=True)\n",
    "\n",
    "# Plot Temperature\n",
    "axs[0].plot(example_data['Temperature'], example_data['Altitude'], label='Temperature (K)', color='red')\n",
    "axs[0].plot(example_data['Theta'], example_data['Altitude'], label='Theta (K)', color='green')\n",
    "\n",
    "axs[0].set_title('Temperature (K)', fontsize=14)\n",
    "axs[0].legend()   # ← add legend here\n",
    "\n",
    "axs[0].grid()\n",
    "\n",
    "# Plot Theta_v\n",
    "axs[1].plot(example_data['Theta_v'], example_data['Altitude'], label='Theta_v (K)', color='orange')\n",
    "axs[1].set_title('Theta_v (K)', fontsize=14)\n",
    "axs[1].grid()\n",
    "\n",
    "# Plot Relative Humidity (RH)\n",
    "axs[2].plot(example_data['Relative Humidity'], example_data['Altitude'], label='Relative Humidity (%)', color='blue')\n",
    "axs[2].set_title('Relative Humidity (%)', fontsize=14)\n",
    "axs[2].grid()\n",
    "\n",
    "# Plot Specific Humidity (qv)\n",
    "axs[3].plot(example_data['Specific Humidity (qv)'], example_data['Altitude'], label='Specific Humidity (g/kg)', color='green')\n",
    "axs[3].set_title('Specific Humidity (g/kg)', fontsize=14)\n",
    "axs[3].set_xlabel('Value')\n",
    "axs[3].grid()\n",
    "\n",
    "# Set shared y-axis limits\n",
    "axs[0].set_ylim(0,2000)  # Reverse y-axis for altitude\n",
    "axs[0].set_ylabel('Altitude (m)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.suptitle(f'Profile at Time: {example_data[\"Time\"]}', fontsize=16, y=1.02)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7c341dee",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select the 10th entry in the averaged DataFrame\n",
    "example_data = df_10min_avg.iloc[99]  # Indexing starts at 0, so 9 is the 10th entry\n",
    "\n",
    "# Create a single plot for Specific Humidity\n",
    "fig, ax = plt.subplots(figsize=(8, 6))  # Larger figure for presentation\n",
    "\n",
    "# Plot Specific Humidity (qv)\n",
    "ax.plot(example_data['Specific Humidity (qv)'], example_data['Altitude'], label='Specific Humidity (g/kg)', color='green')\n",
    "\n",
    "# Set the title and labels with larger font sizes\n",
    "ax.set_title('Specific Humidity (g/kg)', fontsize=18)\n",
    "ax.set_xlabel('Specific Humidity (g/kg)', fontsize=16)\n",
    "ax.set_ylabel('Altitude (m)', fontsize=16)\n",
    "\n",
    "# Increase tick label font size\n",
    "ax.tick_params(axis='both', which='major', labelsize=14)\n",
    "\n",
    "# Add a grid for better visibility\n",
    "ax.grid()\n",
    "\n",
    "# Add some space between the plot and the title\n",
    "plt.tight_layout()\n",
    "\n",
    "# Display the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "70e4a142",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NDc3yulesWEFKSgqOjo4ZfmbHjx+Pg4MDOp3O1DFBfoiKiuLvv/+mdevW3LhxA4BRo0ah1Wrzpb6UUvz6668AvP322xl2xNC9e3fc3Ny4d+8ehw8fTrfMq6++SqlSpdJMr127tul59uPHj2c7xtxq1KgRpUqVIi4ujqNHj+b79gEWLVpEfHw8jRo14vnnn0+3jK2tLf379wcw1fvjHB0d0/3eu7m58eyzzwJQvnx5BgwYkKZMpUqVTJ0BZFYPI0aMSLceq1evTu/evQFYsmSJ2Tzj93fQoEGULVs23fWWK1fO1M4no/2rWbMmXbp0yTC2JykIdW2k1Wp577330p1nyb+jwnqk2xohHjF06FCmTZtGXFwcS5cuNRuDYv369dy8edNUzmjv3r3o9XoAWrdunaXtREREpNuve7NmzXIT/hMZT/jbtm2Lo6NjtpbV6/UsWbKEJUuWcPToUe7evUtiYmKack/qPSuntm/fnmFjZzs7O2bOnJluQ0InJycaNGiQ7nL//POPqaFzmzZtMtx227Zt+f333zl+/Dg6nS7XXag+ycOHD00nOR9//DFTpkzJsGxkZCRg+Exl1aFDhwBo3Lgxbm5u6Zbx9PSkUaNG7N6921Q+r2TWiP2ll17io48+AvKnvk6fPm06pkOGDEGrzfjam/HCQ0REBE2bNk0zP71pRj4+Ply+fNm0LUtLTk7m119/5Y8//uDkyZNERkamO7hnXn1fn2TXrl0AnDx5Em9v7wzLJSQkABl/vmvUqJHhgIvG39hGjRpl+BkrXbo0YWFhPHjwIMMYMvtdb926Nb/99luaz5px//73v/8xf/78DJePjo4GMt6/rPxNKOh1bVS5cuV0kzOw7N9RYT2SVAjxiIoVK9KyZUtCQ0P59ddfzZIK49XLatWqERgYaJpuvJoKZPnKyaNdcj4qox9cSzH2Ce/n55et5eLj4+ncubPZ1XB7e3uKFy9u+iMaGRmJTqcz9YxlaY8OfqfRaHBycsLHx4fAwECGDx9OQEBAusuVKFEiwxPDO3fumF5ndDURMI0/kZKSQmRkZJ7/Ibt165bpD2xWTzoz+kylx7jfme0z/Lvfjx6nvPDo8XRwcMDLy4v69eszcOBAsx6b8qO+Hv0+3717N0vLZHTsM7rDBJjugORFL0x37tyhTZs2pjFUwHBF38vLCxsbG+DfQeny6vv6JMbjnJCQYEocMpObY5zbesjss2ac9+hnTafTmXqtio6ONiUOmcnp34TCUNdGme2LJf+OCuuRpEKIxwwbNozQ0FD27NnDuXPnqFq1Kvfu3eOvv/4yzX9UamoqYLgintsfOeMfgbyW3e5Np06dSmhoKE5OTkybNo2ePXvi6+trtp7nnnuOXbt25bqL04wEBgaaulHMDksf05x2DZsdxs8UwL59+zK94p0bWd2XvN7nvBwALbuxP3rsb926VSivhI4ZM4YTJ05QokQJvvjiCzp27JjmboCvry/Xrl3Ls+/rkxiP84gRI/jxxx+tEkNW5eYztGTJEvr27ZvjbT/p96sw1LVRZvtiyb+jwnqkTYUQj+nVqxceHh7AvyNnL1iwAJ1Oh62tLYMGDTIrb/wBT0hIICwsLF9jza4yZcoAmI1pkRXG54UnTJjA6NGjKV++fJo/tIVxZNxHr5xl9miAcZ6trS2enp55HtejJ7KPXoG0FON+X716NdNyxv0uWbKkxWPIifyor0dPyPLi2Oc1nU5nejb9+++/5+WXX05zkpmamprh+A/5xRhTYTjGmX3WjONU2Nramu6kOjo64u7uDuTt/uVXXRvv5qT3uKtRVu7GZKYw/R0VGZOkQojHODo6mhr1zZ8/n9TUVFNyYRwk7FGBgYGmE+zHG+tZmvExnpxecTI+trV58+ZM/0A8znjyWb9+/XTnh4eHF8o/BA0aNDAd04wGwQLYsmULAHXr1s3z9hRgaM9Qo0YNIG8+U40aNQIMbSsyOhmIiooya3tREOS2vh59DC6j71CtWrVM7Uzy+vucnqzEmJlH2zpl9H3dtWtXtr7/ecHYVmDfvn3Zag9kDZl1gmCcV6dOHbPPmnH/li1bZnqU0dJyW9dZ/awZE/PMLkKkN5hjduTn31GRdySpECIdxkecbt68ySeffGK62vT4o09guHrarVs3AL744gvOnz+f6bpz0zDTeLITFRWVo+WHDBmCjY0N9+/fZ+LEiVleznjV7dixY+nOz6y3joLMw8OD9u3bA4a6S++2+7Fjx1ixYgWAqSea/PDqq68ChpPnJ/2Rze5nqlevXtja2pKYmMj06dPTLTNt2jSSkpKws7OjV69e2Vp/XsltfT3aKD2j75Ctra2pI4Z58+aZGtxmxNINrbMS45OWN56cpfd9TUlJMTV8t6ZBgwbh5OREamoqr7/+utkjQ4/T6/U5/s2zhJ9++indq/3nzp0z9Yz2+CNOxu/v+fPn+eKLLzJdf1xcHMnJydmOK7d1ndXPWt26dQFDu4f0RrS+c+cOs2fPzmrY6crPv6Mi70hSIUQ6GjRoQL169QD45JNPAMOjQx07dky3/FdffUWJEiWIiYmhefPm/Prrr2ZXgO/du8cff/xBz549c3ViWqtWLQDWrVtnuu2eHZUrV+bdd98FYMaMGQwfPpwLFy6Y5t+9e5elS5fSo0cPs+U6dOgAwKeffsoff/xBSkoKAJcvX2bAgAH8/vvv+fJYUF6YOnUqdnZ2hIWF0b59e1MCqdfrWbduHZ06dSIlJYVKlSrx2muv5VtcI0aMMLWlGDRoEOPHjze7UhgfH8+2bdt44403qFSpUrbWXbZsWUaNGgXA559/zsSJE00nFVFRUXz88cemE6GxY8eaHpsrCHJTXwEBAdjb2wOGLj8zujr78ccfU6lSJVJSUujQoQMzZ840a7QdHR3Nhg0bGDx4MM8995xF98/Dw8PU+Hfu3Lmm71pWubq6mq6Sjx07lq1bt5qulJ88eZJOnTpx6NChDHtMyi/e3t58/vnnAKxdu5a2bduye/duU3KhlOLs2bPMnDmTWrVqmdq0WYNOp6Nt27YcPHjQFNuWLVto3749SUlJ+Pr6MmLECLNlunXrZvodff/99xk5cqTZiXJycjL79+/nvffew8/PL0edIeS2rrP6WQsMDDR17jFkyBAOHTqEUgq9Xs+2bdto2bKlRe7G5NffUZGHrDA2hhCFwnfffWcasAdQ77//fqbl//nnH9MovGAYqdjT09M0iqjxX5s2bcyWy85AYufPn1eOjo4KUFqtVpUuXVr5+fkpPz8/dfXqVVO5zAabS0lJUa+//rpZTK6ursrZ2dn03t3d3WyZ8PBwVbp0adN8W1tb5e7ubno/bdq0TAeBy+sRtdNjHPzOz8/viWWXLFliGsQKUG5ubqbjDChfX191+vTpTOOz9OB3ShkGCDOOKvxobB4eHkqj0ZjVR3YlJSWpPn36mNah1WqVp6enaSBBQPXv318lJyenWTa/RtTOSG7qa9iwYaZyzs7Oqnz58srPz0+9/fbbZuUuXbqk6tata3bsPTw8lJubm9m0ypUrp9mGcV5mg8dl9rn55JNPTOtwcHBQvr6+ys/Pz2yk+8w+O4cOHTIb+M3BwUEVK1bM9FmZP39+pt/JrMSfVZmNqK2UUjNmzFA2Njambdrb26sSJUqYRk03/nt88LqsDMg2ePDgTLetVMb18OhnfMmSJabj9/hvpYeHhzp48GC6646Li1P9+vUz2w8XF5c03zMgzQB5WR3oNLd1nZXPmlJKbdiwwaxOnJ2dTd+5KlWqqMWLF2f4ecxKXRnl9O+oKBjkToUQGRg4cKDZWA6Pjk2Rnvr163P69Gm+//572rRpg5eXFw8fPkSv11OlShUGDBjAkiVLTA3rcqJKlSqEhobStWtXSpYsyf3794mIiCAiIiLLVzRtbGz4/vvv2bVrFwMHDqR8+fLodDrs7e2pWbMmw4YNMz0+YuTn58ehQ4cYNmwYPj4+gKHtSefOndm4cWOGg8sVFn379uXUqVO89tprVKpUiaSkJGxtbalXrx6TJ0/m5MmTVK9ePd/j8vLyYsuWLaxevZrevXvj6+tLUlISCQkJlC1blo4dO/L9999nu+E9GLoEXrp0KStWrKBjx46UKFGChw8fUqJECTp27Mgff/zBb7/9li9tSLIrN/X1ww8/MGnSJNNdvytXrhAREZHm8ZYKFSpw6NAh5s+fT+fOnSlTpozpMZUKFSrQo0cPfv31V/bu3Wvx/fvwww/55ptvaNSoEXZ2dly7do2IiIgsd4bQsGFDDhw4QJ8+ffDy8kKv11OsWDH69OnDnj170nQ2YU3vvvsuZ8+eZcyYMdSpUwdHR0eioqJwdXWlcePGjBs3jj179qQ7eF1+adq0KYcOHSI4OBh3d3dSUlIoW7Ysr7zyCidOnDC1UXqcs7MzixcvJjQ0lEGDBlGxYkX0ej2xsbGUKlWK1q1bM2PGDC5cuPDE7p0zktu6zupnrX379uzcuZPOnTvj6elJamoqvr6+vP/++xw+fDjTsUayIz/+joq8o1HKyn2MCSGEEEIUIOHh4aZRzy9fvoy/v791AxKiEJA7FUIIIYQQQohckaRCCCGEEEIIkSuSVAghhBBCCCFyRZIKIYQQQgghRK5IQ20hhBBCCCFErsidCiGEEEIIIUSu2Fo7AJF9er2eGzduUKxYMTQajbXDEUIIIYQQhZRSiocPH+Lj44NWm/P7DZJUFEI3btzA19fX2mEIIYQQQogi4urVq5QrVy7Hy0tSUQgVK1YMMFS+m5ubabpOp2PTpk20a9euQI6CK/4ldVW4SH0VHlJXhYvUV+EhdVW4ZKe+YmJi8PX1NZ1f5pQkFYWQ8ZEnNze3NEmFs7Mzbm5u8oUv4KSuChepr8JD6qpwkfoqPKSuCpec1FduH6mXhtpCCCGEEEKIXJGkQgghhBBCCJErklQIIYQQQgghckWSCiGEEEIIIUSuSFIhhBBCCCGEyBVJKoQQQgghhBC5Il3KPkV0Oh2pqanWDkNgqAtbW1sSExOlTgoBqS/Ls7GxkW4phRCiCJGk4ikQExPDvXv3SEpKsnYo4v8ppfD29ubq1au57hda5D2pr7zh4OCAl5eX2Xg7QgghCidJKoq4mJgYrl+/jqurK15eXtjZ2clJUQGg1+uJjY3F1dUVrVaeQizopL4sSymFTqcjOjqa69evA0hiIYQQhZwkFUXcvXv3cHV1pVy5cpJMFCB6vZ7k5GQcHR3lJLUQkPqyPCcnJ4oVK8a1a9e4d++eJBVCCFHIyV/HIkyn05GUlIS7u7skFEKIAkej0eDu7k5SUhI6nc7a4QghhMgFSSqKMGODUmkMKYQoqIy/T9IAXgghCjdJKp4CcpdCCFFQye+TEEIUDYUiqVi4cCGvvfYajRo1wsHBAY1GQ0hISIblY2JiGDt2LH5+fjg4OODn58fYsWOJiYnJcJnffvuNJk2a4OLigqenJ506deLQoUMZlr9w4QJ9+vShZMmSODk5UadOHb7//nv0en265ZOSkpgyZQoBAQE4OjpSpkwZhg8fzq1bt7J8HIQQQgghhCiICkVSMX78eP73v/8RERFBmTJlMi0bFxdHUFAQX3/9NVWrVmXMmDHUqFGDr7/+mqCgIOLi4tIsM23aNAYOHMjt27cZMWIEffr0Yffu3TRr1oxt27alKX/69GkaN27MqlWraN++PW+99RYAb775JiNGjEhTXq/X061bNyZOnEjx4sUZPXo0zZs3Z+7cuTRt2lQSCyGEEEIIUagViqRizpw5hIeHc/fu3XRP2h81Y8YMjh49yrhx49i0aROff/4569evZ8KECRw9epQZM2aYlb9w4QITJ04kICCA48eP89VXX/Hzzz+zZ88ebG1tGT58OCkpKWbLjBw5kujoaFatWsXChQuZPn06hw8f5vnnn2f27NmEhoaalZ83bx4bN26kX79+7N27l88//5xly5YxZ84crly5wnvvvWeZAyVyZdu2bWg0GiZNmmTtUAq0N954g5IlSxIbG5ur9bRs2ZKmTZuilLJQZEIIIYSwlkKRVLRp0wY/P78nllNKMWfOHFxdXZkwYYLZvA8++ABPT09++eUXs5OYuXPnkpKSwkcffYS7u7tpes2aNQkODubixYts3brVNP38+fPs2LGDVq1a0alTJ9N0Ozs7pk6dCsDs2bPNtm18//nnn5s9P/zyyy9TvXp1li5dysOHD7NyKEQWaTSabP3Lz7hatmyZb9uztPPnz/Pzzz8zbtw4XF1dTdNDQkLQaDR8/vnnaZZJSkqiZ8+eaDQaOnbsSHx8PAATJ07kwIEDLFmyJN/iF0IIIUTeKFLjVFy4cIEbN27Qvn17XFxczOY5OjrSokULVq9eTVhYGFWqVAEwPd7Url27NOtr3749P/30E9u3bzfNz6x8kyZN8PDwYPv27aZpiYmJ7N+/n6pVq6abGLVr145vvvmGffv20bZt2xztt0hr4sSJaaZNnjwZd3d3Ro8enf8BFRGTJ0/GwcGBkSNHZql8bGws3bt35++//6Zv374sWLDA1NtPq1ataNiwIRMmTKBfv37SYFcIIQoCpQc0IL/JIpuKXFIBmBKGxxmnX7hwwey1q6sr3t7emZbPyjY0Gg2VK1fm0KFDxMfH4+zszMWLF9Hr9VmKKaOkIikpiaSkJNN7Y4NznU5n1re78fWj/yul0Ov1GTYgL6oev1MFhhNiDw+PdOc9eoyMxywvGe+W5ce2LOXevXusWLGC3r174+zsbBZ3escuMjKSzp07s3//fl599VV++OEHtFqt2XIDBw5k7NixbN68mTZt2uTvDmVDYayvwkKv15tG2Laxscn1+h7/HRQFm9RXwaM9/iGapHukNvgObBxM06Wu8t69M/fwqu5lkXVlp74sVadFKqmIjo4GMHuM6VHGEVuN5YyvS5Uqla3yWd2Gs7NzjmJ63GeffcbkyZPTTN+0aRPOzs5ppm/evBkAW1tbvL29iY2NJTk5OcP1P030en2GvYAZH8tJSkpi586dTJkyhQMHDqDRaGjRogXTpk2jfPnyaZaLiIjgq6++YuvWrdy9exdPT09at27N+++/byq/a9cuunTpAsD27duxtf33q/fDDz8wYMAAoqOjmTt3Lps3b+bSpUvcv3+fEiVKEBQUxHvvvUeFChWyvb9vvPEGixYtYu3atQQGBqaZ/+WXXzJ16lR+/PFH+vXrl+m6QkJCSEpKolOnTmmOYWJioun/mJgYbt68Sc+ePTl79iyjR49m4sSJ6bbB6NChA2PHjmX27Nk0adIk2/uX3+QxRctLTk4mISGBHTt2pGm/lhvG30FROEh9FQw+KbtonPQlAPtvluOObaM0ZaSu8s6NBTdwquCEZ3NPi60zK/VlPP/JrSKVVBRVH3zwAWPHjjW9j4mJwdfXl3bt2pmSEjBkmps3b6Zt27bY2dmRmJjI1atXcXV1xdHR0RqhFzhardbsmD3KmKCdOHGC7777jqCgIF599VWOHj3K2rVrOXv2LMePHzc7lvv376djx47ExcXRuXNnKleuTHh4OMuWLePvv/9m9+7dVKxYkRo1ajBhwgSmTJmCn58fwcHBJCcnY29vzzPPPIObmxunT5/ms88+o2XLlvTo0QMXFxfOnj3L8uXL2bx5M4cOHcpS26JHvfzyyyxatIhVq1bRoUOHNPP/+OMPXFxcGDBggFkbifTs3r0bgNatW6c5hsZj4ujoyN27d3nhhRe4fPkyM2bM4O23385wnW5ubpQvX57du3dnWC8FgVKKhw8fUqxYMXlMy8ISExNxcnKiRYsWFvmdevx3UBRsUl8FSNRRbLf+AEBq1bE0qmN+V1/qKu+pDorTy05Ts1PNXK8rO/WV2ZAL2VGkkgrj3YCMrvobD9qjdw3c3d2zXT4r2zCeIOUkpsc5ODjg4OCQZrqdnV26HxTj9NTUVDQaDVqtFq32sTb5SkGqZTLTPGXjbPHnOtMci8emr1u3jiVLltC3b1/TvODgYBYsWMCaNWtMV/R1Oh0DBgxAr9dz6NAh6tatayq/a9cuWrZsyZgxY/jzzz+pWLEikydPZsqUKfj7+zNp0iRiYmJwc3MzbbdmzZrcvHmT4sWLm8UVGhpKmzZtmDZtWppOAJ6kdevW+Pr6snz5cr7//nvs7e1N8w4fPsyZM2d46aWXsnRCv3fvXsqWLZvuo4LGfTh16hTfffcdd+7cYc6cOQwbNuyJ623YsCErV64kIiIiR3dj8oPxkSfj90lYjlarRaPRZPh7llOWXp/IW1JfVpZ4F/a8CKkJUKY9NvVnYKNN/3FEqSvLib8Xz/ZPttN2eltsHQ2n5PVeqmfRbWSlvixVn0UqqUivDcSj0msPUaVKFfbu3cutW7fSnCxlVD6jbSilCAsLw8fHx9RQvFKlSmi12mzFlC9S4+H3zK9MFwh9YsHW5cnlLKhFixZmCQXA0KFDWbBgAQcPHjQlFX/99Rfh4eF88sknZgkFQPPmzenWrRurVq0yJQ9PklFi2apVK2rWrMmWLVuyvS8ajYYBAwYwffp01q5dS48ePUzzFi5cCMBLL730xPUkJydz9+5dGjRokGm5RYsWAfD+++9nKaEAKF26NADXrl0rsEmFEEIUWXod7OoDcRHgWhmaLYYMEgphOffO3uO3F37jwaUHpCal0vmnztYOKdeK1CW3KlWq4OPjw+7du9MMcpeYmMiOHTvw8fGhcuXKpulBQUGAoX3C4zZu3GhWBjB1B5pe+QMHDhAVFWVW3tHRkSZNmnDu3DkiIiLSLLNp0yYcHBxo2rRpNvZU5KX0TpzLlSsHQFRUlGnavn37ADh79iyTJk1K8+/WrVvo9XrOnz+f5W1v27aN7t27U6ZMGezs7Exd3p44cYIbN27kaH8GDRoE/JtEAKSmprJ48WK8vb2z1ED6/v37AHh6Zv6cZ8uWLbGzs2PWrFnpfkfSY7wzc+/evSyVF0IIYUH/vAN3toGtK7RYBfaWe55fpO/S35eY88wcHlx6gEcFD5qOKhrngEXqToVGo2H48OFMmTKFKVOmMH36dNO8zz77jAcPHvDmm2+mGSvC2Fi1W7dupqvFp06dYv78+VSqVInWrVubygcEBNCiRQtCQ0NZt26daawKnU7H+PHjAXjllVfM4nr11VfZt28f77//Pr/99ptp+3PnzuXMmTMEBwfn//PkNs6GuwAFnU3ahuh5Lb07BsaG1ampqaZpkZGRwL9X5zOS3iju6Vm2bBl9+/bF1dWV9u3b4+/vj7OzMxqNhpCQkHST0qyoWbMm9evXZ+3atURFReHh4cHmzZu5ffs2Y8eOzVKPO05OTgAkJCRkWq59+/aMGTOGF1980XSnpn379pkuY1xnep0OCCGEyEMX58L5bw2vAxeCR+6f5ReZOzz7MOv+sw59ih7fQF/6ruqLS8n8fSIjrxSKpGLOnDns2rULMDSiNU4zjhnRvXt3unfvDsC4ceNYs2YNM2bM4MiRIzRs2JBjx46xfv166tWrx7hx48zWHRAQwKRJkxg/fjx16tShd+/exMXFsXjxYnQ6HbNnzzbrqQfgxx9/JDAwkB49etCnTx98fHzYsGEDx48fZ/jw4bRq1cqsfHBwMEuXLmXJkiVcvnyZli1bcunSJVasWIGvr69Z8pNvNJp8f6yoqDEmgn/++SedO+f+tuWkSZNwdHTk8OHDaR6Hy+0AcYMGDWLs2LEsX76c4cOHm+5aGO9iPImHhwd2dnamRCozXbt2ZcWKFfTq1Ytu3bqxcuVKOnbsmGF54zpLliyZpViEEEJYwL39cHCE4XXtSVCum1XDKeqUXrHl/S3s+WIPALUH1KbrL11NbSmKgkLx+NOuXbuYN28e8+bN459//gEMPdEYpx09etRU1sXFhW3btjFmzBjOnj3LV199xcmTJxkzZgzbtm1LMygewEcffcTChQspVaoUP/74I0uWLCEwMJDdu3enSRAAatSowYEDB+jatSvr16/nm2++ITU1lW+//Zaff/45TXkbGxtWr17N5MmTuX//Pl9//TU7duxgyJAh7N+/P92Gr6LgMz6ytnfv3iwvo9Vqze52POrixYtUr149TUJx48YNLl68mPNAgf79+2NjY8PChQuJi4tj1apV1KxZk3r16mV5HbVq1SI8PDxL/Vl37tyZlStXAtCjRw/Wrl2bYdlz585hZ2dHtWrVshyLEEKIXEi4CTt7gj4ZynWHWh9bO6IiL+Z6DP/MMZzDBk0KosfCHkUqoYBCcqciJCSEkJCQLJd3d3dn5syZzJw5M8vLDBw4kIEDB2a5fEBAAMuWLctyeQcHByZMmJDuwGuicOrWrRvly5dn5syZtG/fnhYtWpjN1+l07N+/n+bNm5umFS9enGvXrqW7Pj8/P8LCwrh9+7ap8XJiYiIjR47Mdf/9xrYTmzZt4ptvviEuLi7LdymMgoKCOHLkCCdOnHhig22ATp06sXr1arp3707Pnj1ZsWJFmjs6Op2OI0eO0KhRI3n8SQgh8oNeBzt7QcINcK8Bz84HTaG4xlyoufu603dlX2KuxVBnYB1rh5Mn5FMkRA45ODiwfPlyXFxcCAoKok2bNowePZrRo0fTs2dPfHx8GD58uNkyrVu3Jjw8nBdffJEvv/yS6dOnmx7pe/PNN4mJiaF+/fq89dZb/Oc//6F27dqcOnUqTe9SOTFo0CCUUkyaNAmtVputJBowPWKYnV6o2rdvz5o1a7CxsaFXr16sWbPGbP6OHTtISkoyrVsIIUQeOz4R7u0FOw9osRrsilk7oiIr9lYs1w9eN733D/IvsgkFSFIhRK40btyYY8eOMWrUKK5cucJPP/3E3LlzOXv2LN27d+e///2vWflvvvmGPn36sGPHDj777DM+/PBDDh8+DMDrr7/OTz/9RPHixZk9ezYrV64kKCiIPXv24OHhketYe/TogaurKzqdjqCgIFOPVlkVFBREtWrVzHqRyoq2bdvy559/YmNjQ+/evVm1apVp3sKFC7G3t+fll1/O1jqFEELkwO1tcPpzw+umc6BY5UyLi5yLuRZDSFAIC9os4MahnPXeWNgUisefhLAEpVSm81u2bJlhGX9//wznlS1bllmzZjFr1qwnxuDt7c3SpUvR6/VpBr/TaDS89tprvPbaa2mWM3ZKkBvOzs48fPgwV+sYM2YMr732Gvv37zfrBnnIkCEMGTIkw+Wef/554uPNB1uMiopixYoVDBw4UBppCyFEXkuKhL2DAAUVh0L5XtaOqMiKCo9iXut5RF2Owt3PHafiTtYOKV/InQohRJYNGzaM6tWrM3ny5Fyv6+uvvyY1NZVPPvnEApEJIYTIkFJw4DWIvwbFqkDDb6wdUZEVGRbJ3BZzibochWclT4ZsH4Jnxadj7A9JKoQQWWZjY8PcuXNp2rQpsbG5G+fE09OT+fPnU7ZsWQtFJ4QQIl2X5sLV5aCxhcBFYOdq7YiKpHtn7zG3xVxirsbgVc2LIduH4OHnYe2w8o08/iREIXP06FGzdgkZ8ff3z/SRpJxq2rSpRUaAHz16dO6DEUIIkbmYC3D4LcPrOp9AicbWjaeIigyLJCQohLg7cZSqVYpBWwbhWvrpSt4kqRCikDl69GiWHj8KCgrKk6RCCCFEIZGaDHsGQEoclGoJ1d+1dkRFlpuvG971vYm7E8egTYNw9nr6ukmXpEKIQuZJjaKFEEIIAE5MhMhDYO8JgQtAa2PtiIosWwdb+q7sS2pSKo4ejtYOxyqkTYUQQgghRFFzZwecnm543WQ2OGevG3HxZNf2XWPr+K2m3iHtnOye2oQC5E6FEEIIIUTRoouFvUMwdB/7snQfmwdu/nOThR0WkhSdhEcFDxoMa2DtkKxO7lQIIYQQQhQlR9+HuMvg7AsNZ1k7miLnzqk7LGi3gKToJMo3L0+tfrWsHVKBIEmFEEIIIURRcWsrXPjB8PqZX8HOzbrxFDH3z99n/vPzSbifgE9jHwasHYC9i721wyoQJKkQQgghhCgKdA9h/1DD68ojwLuNdeMpYqLCo5j//HzibsdRuk5pXtrwEg5uDtYOq8CQpEIIIYQQoig48i7ERYCLP9SfYe1oipSUxBTmt5lPzDXDwHaDNg/CqbiTtcMqUCSpEEIIIYQo7G5ugrCfDa+f+RXsilk3niLG1tGWFh+3oERACYL/DsallIu1QypwpPcnIYQQQojCLDka9g83vA54A0q3sm48RVS9wfWo1a8Wtg5y+pweuVMhhBBCCFGYHXkb4q+Ca0Wo97m1oykyEqMSWTloJbG3Yk3TJKHImCQVQvy/bdu2odFomDRpkrVDKbL8/f3x9/e3dhhWUxA/Y3q9nrp169KpU6dcrScqKgoPDw/GjRtnociEEFlyYz1c/AXQwDMhYCuP5VhCcmwyizot4vjC4/ze+3fTAHciY5JUiCJJo9Fk619+xtWyZct8215+CQ4ORqPR4O3tTUpKSraWnTRpEhqNhm3btuVNcPmssNVxSEgIx48fT5PoDBkyBI1Gw759+9Isc/XqVapVq4ZGo2HChAkAeHh4MGrUKL799lvCw8PzIXIhBMkP/n3sqeooKPWcdeMpInQJOhZ3Xcy1vddw9HCk0/ed8vVcobCSeziiSJo4cWKaaZMnT8bd3Z3Ro0fnf0BFWExMDCtWrECj0XD79m3Wrl1Lt27drB1WgdSkSRPOnDmDl5eXtUMBIDU1lcmTJxMUFESTJk2ytMz58+dp27YtV69eZdasWYwaNco0b9SoUXz++ed8+umnzJkzJ6/CFkIYHR4DCTegWBWoO9Xa0RQJKUkp/N7zd8JDw7EvZs9LG1/Cu563tcMqFCSpEEVSeo+XTJ48GQ8PjwL16ElRsHjxYuLj43nnnXf46quv+OWXXySpyICzszPVqlWzdhgm69at48qVK6a7DU9y5MgROnTowP379wkJCSE4ONhsfvHixenYsSOLFy/mq6++wt3dPS/CFkIAXPsTLs/j38eenK0dUaGXqktlRf8VhG0Iw9bJlgFrB1C2SVlrh1VoyONPQqTjn3/+oX379hQrVgx3d3d69OiR4SMdly9fZvjw4ZQvXx4HBwfKlCnDkCFDiIiIMJUxPksPsH37dmxsbPD09MTGxoaQkBAAoqOjmT59OkFBQfj4+GBvb4+Pjw/BwcFcvHgxR/sxdOhQNBoNO3fuTHf+1KlT0Wg0LFiwIEfrB/jll1+wt7fngw8+oFmzZqxbt46bN29madmWLVsyefJkAFq1amV6HO3xdhd37txhzJgxVK5cGQcHB7y8vOjVqxcnT55Ms05ju42oqCjeeustfH19sbW1JSQkhPDwcDQaDUOGDOHSpUv07t0bT09PXFxcaNOmDceOHUuzvtDQUIYNG0bjxo1xc3PD1dWVRo0a8b///c+s3ON1/OjjdcY6Tq9NRaVKlShWrBjx8fHpHqO2bdui1Wq5cuWK2fTVq1fz/PPP4+npiaOjI7Vq1eLLL78kNTU102P+qJCQEDQaDb169Xpi2Z07d9KqVSuio6NZsWJFmoTCqE+fPsTHx/P7779nOQ4hRDYlRcKBVw2vq78NJQOtG08RseW9LZxdeRYbBxv6r+mP33N+1g6pUJE7FUI85tChQ3zxxRe0bNmS1157jSNHjrBq1SpOnDjByZMncXR0NJXdv38/7du3Jy4uji5dulC5cmXCw8NZtGgR69evZ+/evVSsWBF/f38mTpzI5MmT8fPzY/DgwSQlJeHg4EC9evUAOHPmDBMmTKBVq1b06NEDFxcXzp49y2+//cbatWv5559/8PPL3g/coEGDmDt3LgsXLuS559I+a7to0SJcXFzo0aNHjo7ViRMnOHjwID169KB48eIEBweza9cu5s2bx/vvv//E5YcMGQIYTsIHDx5sSiY8PDxMZS5evEjLli25fv067dq1o3v37ty5c4cVK1awceNG/v77b5o2bWq23qSkJFq3bs3Dhw/p0qUL9vb2lC5d2jQ/PDycpk2bUqNGDYYOHcrFixdZvXo1rVq14syZM2Zlp0+fTlhYGA0aNKBnz55ER0ezYcMGXnvtNc6dO8dXX30FkKaOjfsGmOo4PS+99BJTpkxh9erV9O/f32zezZs32bp1Ky1atKB8+fKm6R9++CGfffYZ5cqVo1evXri5ubFjxw7effdd9u/fz7Jly5547JVSbNu2jWrVqpkd7/SsW7eO3r17Y2try/r162nVKuPuKp999lkAtm7dyiuvvPLEOIQQOXDoTUi8BW7VoPYUa0dTZDwz+hkubrxIm+ltqNimorXDKXyUKHSio6MVoKKjo82mJycnq1WrVqnk5GSllFIJCQnq9OnTKiEhIcN1JcUmZfhPl6DLctnk+OQcl02OS063nKUBys/PL8P5oaGhClCAWrJkidm8QYMGKUAtXrz437iTk5W/v78qVqyYOnr0qFn5nTt3KhsbG9W5c+c0MQQFBanU1FT14MEDlZqaapoXFRWl7t+/nyaurVu3Kq1Wq4YPH56d3VVKKaXX65Wvr6/y9PRUSUnmx/TQoUMKUC+99FK212s0atQoBag//vhDKWXYB0dHR1WlSpV0y/v5+aWpg4kTJypAhYaGprtMYGCgsrW1VZs2bTKbfu7cOVWsWDFVu3btNNsAVLt27VR8fLzZvMuXL5vq+PPPPzebN378eAWozz77zGz6pUuX0tSXTqdTbdu2VTY2NioiIsKsvLGO02P8jE2cONE07cKFCwpQnTp1SlP+yy+/VICaM2eOadqmTZsUoDp27Kji4uJM0/V6vRoxYoQC1PLly9Pd/qNOnTqlADVw4MB05w8ePFgBatSoUcrOzk55eXmpgwcPPnG9SilVvHhxVb58+SyVzcrvVHY8/jsoCjaprxy4skKpRSj1m1apu/vybbNPS12l6lKfXKgQyE59ZXRemV1yp+Ip95nrZxnOq9KpCgPWDjC9/7LUl+jidemW9QvyY8i2Iab33/h/Q/y99B/n8GnkwysH/72C+UONH4iOiE5TbqJK29g6P7Ro0YK+ffuaTRs6dCgLFizg4MGD9OvXD4C//vqL8PBwPvnkE+rWrWtWvnnz5nTr1o1Vq1YRExODm5vbE7eb0fPnrVq1ombNmmzZsiXb+6LRaBgwYADTp09n7dq1ZnckFi5cCBiulOdEcnIyCxcuxNPTkxdeeAEw7EO3bt1YunQpO3bsoEWLFjlat9GRI0fYs2cPw4YNo23btmbzAgICeOWVV5g5cyYnT56kVq1aZvO/+OILnJyc0l1vhQoVePfdd82mDRs2jE8//ZSDBw+mKavX682m2draMmLECDZv3kxoaCiDBw/O6S5SuXJlmjZtyqZNm7h79y4lS5Y0zVu4cCGOjo707t3bNO37778H4Oeff8bZ+d9nqDUaDZ9//jk///wzixcvfuIjTdeuXQMwuyuTnm+++cYUS6NGjbK0T6VKleLChQsopaTHFCEsKfEuHBhheF39PfBqmnl58UShE0IpXac0NXrXAEBrKy0DckqSCiEe06BBgzTTypUrBxj64jcydrV59uzZdBt/37p1C71ez/nz57N8MrZt2zZmzZrF/v37uXfvnln3rPb29tnYi38NGjSI6dOns3DhQlNSkZqayuLFi/H29qZNmzY5Wu+qVau4f/8+I0aMMIstODiYpUuX8uuvv+Y6qTAe41u3bqV7jM+ePWv6/9GkwtHRkdq1a2e43rp166LVmv/hSK+OAR4+fMgXX3zBH3/8QXh4OHFxcWbzb9y4keX9ycigQYPYv38/S5Ys4c033wTg1KlTHD16lBdffNEs4dy3bx8uLi788ssv6a7LycnJdFwyc//+fQA8PT0zLde2bVs2b97MyJEjCQ0NzdIjeMWLFyc1NZWoqKgnrl8IkUVKwcGRkHQXPGpDbetceCtKdkzdwY5PdqCx0fD6mdcpUaWEtUMq1CSpeMp9EPtBhvO0NuYnXe/ceSfDshqt+dXIUeGjMiiZtuzrp18vUIPKpHfHwNbW8FV5tBFsZGQkYGiXkJnHT0IzsmzZMvr27Yurqyvt27fH398fZ2dnU0PfRxt+Z0fNmjWpX78+a9euNQ1QtnnzZm7fvs3YsWOxsbHJ0Xp//fVXwHBC/Kj27dvj7e3NsmXL+Pbbb7N0lyYjxmO8du1a1q5dm2G5x49xqVKlMr1CntU6Tk5OpmXLlvzzzz/UqVOHl156CS8vL2xtbQkPD2fevHkkJSVla5/S069fP8aMGcOiRYtMSYWx8fzjxzcyMpKUlBRTA/f0ZOUzZ7yLk5CQkGm5KVOm0KBBA6ZPn07Lli0JDQ194gCGxnU+eidFCJFLEUvg6grQ2MIz88DGwdoRFWr7Zu0jdHwoAG2mt5GEwgIkqXjK2btk/ep3XpW1c7bLctmCxHiy/Oeff9K5c+dcr2/SpEk4Ojpy+PBhqlSpYjZvyZIluVr3oEGDGDt2LMuXL2f48OGmR58eP2HNqqtXr7J582YAmjVrlmG5JUuW8Oqrr+ZoG/DvMf7uu+944403srycpR65Wb16Nf/88w/Dhg3jyy+/xM3NzXSHY8mSJcybN88i2ylRogQdO3ZkzZo1hIWFUalSJX777Te8vLzo0KGDWVk3Nzc0Gg337t3L1TaNj1kZE7fMfP7559jY2DBt2jRTYlGhQoUMy0dGRlKsWDEcHOSkRwiLSLgJh143vK41HorXt248hdzh2YfZOGYjAEGTggh8W3rPsgR5cEyIHDL2OLR3794sL6PVajPs8vPixYtUr149TUJx48aNHHcpa9S/f39sbGxYuHAhcXFxrFq1ipo1a2baK1Fm5s6di16vp3nz5gwbNizNP2OyktEjOo8y3ilJ77jk5BhbkvG4d+nSJc28jLrpzayOM2Ns27Jw4UK2b9/O1atX6du3L3Z25kl306ZNuX//PhcuXMj2Nh5Vs2ZNtFptltczdepUPv74YyIiImjZsiWXLl1Kt1x8fDzXrl3L9PEzIUQ2KAX7XzWMnu3ZAGp+aO2ICrXji47z12t/ARD4biBBE4KsHFHRIXcqhMihbt26Ub58eWbOnEn79u3TtB/Q6XTs37+f5s2bm6YVL17c1ED2cX5+foSFhXH79m1T49nExERGjhxp1rYiJ4xtJzZt2sQ333xDXFxcju9SKKWYO3cuGo2G+fPnZ3jF+uTJkxw4cCDdRtSPKl68OEC6x6VJkyY0bdqUxYsX07Vr1zQN6PV6PTt37iQoKG/+KBjbD+zevdtsG9u3b2f27NnpLpNZHWemS5cuuLu7s2jRIq5evQqkfyfprbfeYv369QwdOpRVq1ZRooT5Lftbt27x4MEDqlevnun2PDw8qFOnDocOHcpyg+opU6ZgY2PDpEmTTHcsKlWqZFbm0KFDpKam5lmdCPHUuTwPbvwFWnt4dh5oC+fd/YLgxqEbrBq8ChQ0GtmINtPbSGcSFiRJhRA55ODgwPLly+nYsSNBQUE8//zzppPnK1eusHPnTkqUKGHWaLZ169b8/vvvvPjii1SvXh0XFxc6d+5M7dq1efPNN3nzzTepX78+vXv3JiUlhc2bN6OUom7duukOzJYdgwYNYuPGjUyaNAmtVsvAgQNztJ6///6b8PBwWrVqlekjMC+//DJHjhzhl19+4euvv86wnHHQu48++oizZ8/i7u6Ou7s7I0eOBAwjdrdq1Yp+/foxa9YsGjZsiKOjI1euXGHv3r3cvXuXxMTEHO3Lk3Tp0gV/f3+++OILjh49Sr169Th//jx//fUX3bt3Z8WKFWmWMdZx7969qV+/PjY2NrzwwgtPvHLv6OjIiy++yJw5c4iIiKBKlSppxt8A6NChAx9//DGffPIJlStXpkOHDvj5+XH//n3CwsLYuXMnn3766ROTCoDu3bszadIkDh48SJMmTbJ0TCZOnIhWq2XChAmmxKJy5cqm+cbH4rp3756l9QkhMhF3FQ7/fxvF2pPBI+MLNOLJyjQoQ6MRjUiOTabT950kobC0XHVIK6zCkuNUPE3I4jgVj44hYGQc32Dw4MFp5l27dk2NGjVKValSRTk4OCg3NzdVvXp1NXz4cPX333+blb1586bq06eP8vLyUlqtVgFq7ty5SinDOAM//fSTqlmzpnJ0dFTe3t5q2LBh6vbt2yooKEjl9usaFxenXF1dFaBatWqV4/X069dPAWrBggWZlrt3756yt7dXXl5epjEy0hunQimlQkJCVO3atZWDg0O69RQZGanGjx+vatWqpZycnJSrq6uqUqWKGjBggGmMDKOMtqFU5vWoVPpjTFy6dEn17NlTeXl5KWdnZ9W4cWO1ZMmSDD8vmdVxZp8xpZTavn27aRyNyZMnp1vGaPPmzapLly6qZMmSys7OTnl7e6tnn31WffLJJ+rKlSuZLmt07do1ZWNjo958880084zjVOzduzfdZadOnaoAVbZsWXX+/HnT9IoVK6p69eplaftKyTgVTzupr0zo9Ur93c4wJsWGpkql6p68TB4qKnWl1+tVakrRGIsiM9YYp0KjVAHqdkdkSUxMDO7u7kRHR5v1rKPT6Vi3bh2dOnXCzs6OxMRELl++TIUKFcxGgRbWp9frTeNXPN61qSh4inJ9DRgwgE2bNhEREYGLi0uu1rV161aef/555s2bR3BwcJaWsfTv1OO/g6Jgk/rKxIWf4eAIsHGEjkfBrapVwymsdXVt/zUO/3SYzj93xsY+Z70dFkbZqa+Mziuzq2j9dRRCCJEtU6dOJTY2lh9++CHX65oyZQr16tXL8YCKQoj/F3sZjrxteF13mtUTisLq1rFbLOqwiKMhR9kxdYe1wynypE2FEEI8xSpUqMC8efNy3UVtVFQULVu2pEuXLkXubo4Q+UrpYd9QSImDks9B1YzHfRIZu3f2HgvaLiAxKhHfQF+avZtx9+fCMiSpEKKQOXr0KKtWrXpiOX9/f4YMGZLl9aY3YnV6Ro8ejYeHR5bXKwq+x3vVygkPD48sf4aEEJk49w3c2QY2zvDMXNBIkp5d9y/cZ17recTfjadMgzIMWDsAe9esj58lckaSCiEKmaNHj2Y6mrJRUFBQtpKKrKwTYMiQIZJUCCFEXog6CUc/MLxu8BUUq5R5eZHGg8sPmN96PrE3YylVqxQvbXwJRw9pV5ofJKkQopAZMmRItpKFrJI+G4QQwopSk2DPS6BPAp8XoPJr1o6o0NGn6lncZTEx12LwquZF8N/BOHs5Wzusp4bcUxNCCCGEsLbjEyDqGDh4QdM5IGMoZJvWRkunHzpRpkEZgrcG41Iqdz3aieyROxVCCCGEENZ0ezuc+cLwuslscPK2bjyFmH+QP68cfAWNVpKy/CZ3Kp4C8liLEKKgkt8n8dRLjoa9wYCCikPBt7u1IypU4u7GMa/1PG6fuG2aJgmFdUhSUYTZ2BgGedHpdFaORAgh0mf8fTL+Xgnx1Dn8FsRfAZcK0HCWtaMpVBIiE1jQdgHhoeGsfGklSi8XKaxJkooizM7ODgcHB6Kjo+VqoBCiwFFKER0djYODQ6EaoVcIi7myHC7PN3QbG7gA7IpZO6JCIzEqkQXtFnD72G1cSrvQ+/fecofCyqRNRRHn5eXF9evXuXbtGu7u7tjZ2aGRxl9Wp9frSU5OJjExUQYKKwSkvixLKYVOpyM6OprY2FjKli1r7ZCEyH/xN+DA//fwVON9KCmDs2VVUkwSizou4ubhmzh7ORP8dzBeVb2sHdZTT5KKIs7NzQ2Ae/fucf36dStHI4yUUiQkJODk5CRJXiEg9ZU3HBwcKFu2rOl3SoinhlKw72VIjgTPBlBrorUjKjSSY5P57YXfuLbvGk7FnRi0ZRClapaydlgCSSqeCm5ubri5uaHT6UhNTbV2OALDc+Q7duygRYsW8thHISD1ZXk2NjZyLMXT6/wPcGsT2DhC4EKwkdGesyp0QihXdl3Bwd2BQZsH4V1XesoqKCSpeIrY2dnJH/ECwsbGhpSUFBwdHaVOCgGpLyGExUSfgaPvGl7XmwHu1a0bTyHTcnJLIi9E8tz45yjToIy1wxGPkKRCCCGEECI/pCYbRs1OTQTvdhDwurUjKhSUXpkaYTsUc6D/n/2tHJFIj7Q4FEIIIYTIDycmwIN/wN4Tnplr6PVJZColKYUl3Zawc9pOa4cinkA+zUIIIYQQee3GBjg93fC6yWxw9rFuPIWALkHHkm5LOP/XeXZ8soMHlx5YOySRCXn8SQghhBAiL8XfgL2DDK+r/AfK97JuPIVAclwyS7ou4fLWy9g529H/z/54VvS0dlgiE5JUCCGEEELkFX0q7BkASffAsx40+MraERV4SQ+TWNx5MRE7IrB3tWfAugH4Pedn7bDEE0hSIYQQQgiRV05+Ane2g60rNFtq6EZWZMg4sN3VPVdxcHNg4IaB+D7ra+2wRBZIUiGEEEIIkRdubYWTUwyvm/wMbgHWjacQCNsQxtU9V3H0cOSlTS9RtnFZa4ckskiSCiGEEEIIS0u4DXsGAgoqDQP/AdaOqFCo2acm8ffjKfdMOcrUl3EoChNJKoQQQgghLEnpDQ2zE2+Bew1o+K21IyrQ4u7GobXR4lTcCYDGIxtbOSKRE9KlrBBCCCGEJZ2eDrc2g40TNPsdbJ2tHVGBFXsrlnkt57Gg3QISoxKtHY7IBUkqhBBCCCEs5c4uOP6x4XWjH8CjpnXjKcBirscQ0jKEu6fvEnszlvh78dYOSeSCPP4khBBCCGEJSfdhT39QqeD/ElQcYu2ICqzoK9HMaz2PBxcf4F7eneCtwRSvVNzaYYlckKRCCCGEECK3lIK9QyD+GhQLgMb/BY3G2lEVSFHhUcxrNY+o8Cg8/D0YHDoYD38Pa4clckmSCiGEEEKI3Dr7Ndz4C7QO0Px3sCtm7YgKpMiLkcxrNY+YqzF4VvJkcOhg3H3drR2WsABJKoQQQgghcuPePjj6nuF1w1ngWdeq4RRoCvQpekpULcHgrYMp5iPJV1EhSYUQQgghRE4l3IadvUGlQPkXofJr1o6oQCteuThDtg3Bwc0BV29Xa4cjLEiSCiGEEEKInNCnwO5+kHAd3KpB01+kHUU6wreHkxSTRNUuVQEoEVDCyhGJvCBdygohhBBC5MSxD+DONrB1hedWSjuKdJxfe55FHRax7MVlXD9w3drhiDwkSYUQQgghRHZdWQZnvjS8fiYE3KtZNZyC6OSSkyztvpSUxBQqta1EqdqlrB2SyEPy+JMQQgghRHZEn4F9LxteVx8H5XtZN54C6PD/DvPXiL9AQe0BtekW0g0bOxtrhyXykCQVQgghhBBZpYuBnT0gJQ5Kt4K6U60dUYGz+4vdbBm3BYCGIxrywg8voNFKW5OiTpIKIYQQQoisUMpwhyLmHDiXg2ZLQCunUo86u/qsKaFo9n4znp/2PBppvP5UkG+CEEIIIURWnPkCrv4BWntovhwcpY3A4wI6B1CrXy1K1y1N8/ebWzsckY8kqRBCCCGEeJJbWw29PQE0/Ba8mlo3ngIkVZcKgI2dDVobLT1/6yl3J55C0vuTEEIIIURm4q7C7r6g9FBxCFR+1doRFRgpiSks672M1S+vRukVgCQUTylJKoQQQgghMpKaBLt6Q9I98KwPjf4rA9z9v6SHSSzqtIhza85xZsUZbp+4be2QhBUVyaRCKcUff/xBq1atKFOmDM7OzlStWpXXXnuNS5cupSkfExPD2LFj8fPzw8HBAT8/P8aOHUtMTEyG2/jtt99o0qQJLi4ueHp60qlTJw4dOpRh+QsXLtCnTx9KliyJk5MTderU4fvvv0ev11tkn4UQQgiRBw6PgvsHwN4TnlsBtk7WjqhAiL8fz4I2CwgPDcfe1Z6B6wfiXdfb2mEJKyqSScU777xDr169OHfuHN27d+fNN9+kQoUKzJ49m3r16nHy5ElT2bi4OIKCgvj666+pWrUqY8aMoUaNGnz99dcEBQURFxeXZv3Tpk1j4MCB3L59mxEjRtCnTx92795Ns2bN2LZtW5ryp0+fpnHjxqxatYr27dvz1ltvAfDmm28yYsSIPDsOQgghhMiFi79A2M+ABgIXg2sFa0dUIERfjSYkKITrB67jVNyJ4K3B+Lf0t3ZYwsqKXEPtW7duMWvWLPz9/Tl27Bhubm6mebNmzWLMmDHMnDmTX3/9FYAZM2Zw9OhRxo0bx/Tp001lJ06cyJQpU5gxYwaTJ082Tb9w4QITJ04kICCAAwcO4O7uDsBbb71FkyZNGD58OGfPnsXW9t9DO3LkSKKjo1m7di2dOnUC4NNPP6Vjx47Mnj2b/v3706pVqzw9LkIIIYTIhpub4MD/X/irPRl82ls3ngLixqEbLO+5nNhbsbiWcWXQ5kGUqim9YIkieKciPDwcvV5Ps2bNzBIKgBdeeAGAO3fuAIbHpObMmYOrqysTJkwwK/vBBx/g6enJL7/8glLKNH3u3LmkpKTw0UcfmRIKgJo1axIcHMzFixfZunWrafr58+fZsWMHrVq1MiUUAHZ2dkydahgwZ/bs2RbaeyGEEELk2oNjsLM3qBTwGwC1PrJ2RAVGalIqCZEJlKpdimF7h0lCIUyKXFJRpUoV7O3t2b17Nw8fPjSbt27dOgBat24NGO463Lhxg2bNmuHi4mJW1tHRkRYtWnD9+nXCwsJM042PN7Vr1y7Nttu3N1zF2L59e5bKN2nSBA8PD7PyQgghhLCiuKuwrROkPIRSLeGZX0FT5E6Xcsy3mS8D1g1g6O6hePh5WDscUYAUucefSpQowdSpU3n33XepXr06Xbt2pVixYpw4cYItW7bw6quv8uabbwKGpAIMiUh6jNMvXLhg9trV1RVv77SNkR4tY5TZNjQaDZUrV+bQoUPEx8fj7Oyc090WQgghRG4lRxsSioQb4F4DWqwEGwdrR2VVqcmpbBi9gXrD6pmmVXy+ovUCEgVWkUsqwNBQ28fHh9dee40ff/zRND0wMJCXXnoJOzs7AKKjowHMHmN6lPHxKWM54+tSpdK/1ZdR+axuI6OkIikpiaSkJNN7Y69UOp0OnU5nmm58/eg0UTBJXRUuUl+Fh9RV4VKg6kufjM3OnmijT6Icy5DSfA1oXKAgxGYl8ffjWdFnBVd3XuXChgv4zfArGHUlnig73y1L1WmRTCo+/fRTpkyZwqRJkwgODsbT05OjR48yduxYWrVqxe+//07Pnj2tHWaWffbZZ2aNxY02bdqUbiKyefPm/AhLWIDUVeEi9VV4SF0VLlavL6VokPwNvinbSMGRnbxLzLaTwMknLlpUJV5P5NKnl0i+mYzWWUuJ4BJo7bTWryuRLVmpr/j4eItsq8glFVu3buXjjz9mzJgxfPjhh6bpzZo146+//qJixYqMGTOGnj17mu4ePHpn4VHGOwKP3mVwd3fPdvmsbOPxRuWP+uCDDxg7dqzZMr6+vrRr185sOZ1Ox+bNm2nbtq3pbowomKSuChepr8JD6qpwKSj1pT05EZsz21AaG2i+nObeadtBPk3Ct4Xzx0d/kByVjLu/O31W9sEjwKNA1JXImux8tzIbly07ilxSsXbtWoB0u2gtWbIktWvXZu/evdy7dy/dNhCPSq89RJUqVdi7dy+3bt1K064io/IZbUMpRVhYGD4+Pmkaij/KwcEBB4e0z3Ta2dml+0HJaLooeKSuChepr8JD6qpwsWp9hc2GM58BoGnyP2x9X7BOHAXEP3P+Ye3ItehT9JR7thz9VvXDpZSL6REZ+W4VLlmpL0vVZ5HrziA5ORmAu3fvpjvfON3BwYEqVarg4+PD7t270wxyl5iYyI4dO/Dx8aFy5cqm6UFBQYDh0aPHbdy40awMQMuWLTMsf+DAAaKioszKCyGEECKf3FgPB0caXteaAJWGWjceK1N6xanfT6FP0VOrfy0Gbx2MS6mML3oK8agil1Q0a9YMgJkzZ6Z55GjevHmEhYXRsGFDihUrhkajYfjw4cTGxjJlyhSzsp999hkPHjxg+PDhaDQa0/SXX34ZW1tbpk6darb+U6dOMX/+fCpVqmTqshYgICCAFi1aEBoaaurSFgy3pcaPHw/AK6+8YrkDIIQQQogni/wHdr0IKhUqDIbak6wdkdVptBpe/P1FOnzbgZ6LemLrWOQeaBF5qMh9Wl588UV+/vlntm3bRpUqVejatSuenp4cO3aMzZs34+DgwKxZs0zlx40bx5o1a5gxYwZHjhyhYcOGHDt2jPXr11OvXj3GjRtntv6AgAAmTZrE+PHjqVOnDr179yYuLo7Fixej0+mYPXu22WjaAD/++COBgYH06NGDPn364OPjw4YNGzh+/DjDhw+X0bSFEEKI/BQXAdtegJQ48G4DTf4Hj1xAfJrEXIvhxOITBL4TiEajwdHDkaZvNrV2WKIQKnJJhY2NDRs2bOCbb75h6dKlLF68mOTkZEqXLs2AAQP44IMPqFWrlqm8i4sL27ZtY/LkySxfvpxt27bh7e3NmDFjmDhxYrptHT766CP8/f2ZNWsWP/74I/b29gQGBjJlyhQaN26cpnyNGjU4cOAAH330EevXryc2NpbKlSvz7bff8vrrr+fp8RBCCCHEI5IfQGhHSLwFHnXguRVgY2/tqKzixuEbLOm6hIc3HmLvak/jkWnPYYTIqiKXVIChvcS4cePS3GXIiLu7OzNnzmTmzJlZ3sbAgQMZOHBglssHBASwbNmyLJcXQgghhIWlJMCOHhBzBpzKQsu1YJdx74tF2allp1g9ZDW6eB0la5akSsf0BwIWIquKZFIhhBBCCGFGFwPbu8Kd7YZEotV6cC5n7ajyXXJsMutHrefor0cBqNS+Er2X9sbR3dG6gYlCT5IKIYQQQhRtifdgW0eIPAS2xSDoL/Cobe2o8t31g9dZ0X8FDy4+AA00e68ZrT9pjda2yPXbI6xAkgohhBBCFF3x1yG0HUSfBgcvaLUBije0dlRWkZKQwoNLD3DzdaPHgh74B/lbOyRRhEhSIYQQQoii6eFF2NoG4sINbShabwH3ataOKl/pEnTYORkGN/Nr4Ufvpb2p1LYSjh7yuJOwLLnfJYQQQoiiJ+oEbG5uSChcK0PbXU9VQqGU4sivR/imwjfcP3/fNL3mizUloRB5QpIKIYQQQhQt9/bDlqB/u41tuxNc/a0dVb6JvxfP771+Z82wNcTdjmP/d/utHZJ4CsjjT0IIIYQoOm79DTu6GQa283rW0G2svae1o8o3FzddZNWQVcTejEVrp6X1p6159u1nrR2WeApIUiGEEEKIouHqKtjdF/TJ4N0WWqwE27SD2BZFugQdW97fwoFvDwDgVd2Lnot6UqZ+GStHJp4WklQIIYQQovC7NB/2DwWVCr49IfA3sHGwdlT55vD/DpsSisZvNKbt9LbYOdtZOSrxNJGkQgghhBCF27nv4PBbhtcVX4Ym/wPt03WK0/g/jbn892UajWwko2MLq5CG2kIIIYQonJSCE1P+TSiqjoamc56KhCL6ajTr3lhHanIqADZ2NvRf018SCmE1Rf9bJ4QQQoiiRyn4520497Xhfe3JUOtj0GisG1c+OLn0JGtHrCUxKhFHD0daf9ra2iEJIUmFEEIIIQoZfSoceBUu/Wp43/AbqPqWdWPKB0kxSax7Yx3HFxwHoGyTstQdXNfKUQlhIEmFEEIIIQoPpYf9w+DyPNDYQNNfoWKwtaPKc/fO3mNJ9yXcP3cfjVbDcx89R4uPW2BjZ2Pt0IQAJKkQQgghRGGhFBx669+Eovnvhp6eirhLWy7xe6/fSYpJwq2cG72X9sY30NfaYQlhRpIKIYQQQhQOxz6CCz8AGnhm3lORUAC4l3cHwK+FHy8uexGXUk/H2BuicJGkQgghhBAF36nP4PRnhteNf4QKA60bTx7Tp+rR2hg66SwRUIIhO4ZQskZJedxJFFjSpawQQgghCrbzP8CxDw2v638BVV6zbjx5LDIskv81+B+X/r5kmuZd11sSClGgSVIhhBBCiILr0jw49Ibhda2Pofo71o0nj4VtCGN249ncPn6bjWM2ovTK2iEJkSXy+JMQQgghCqYrK2D/UMPrqqMNY1EUUUopdk/fzd8f/g0Kyj1bjj4r+qDRFv1xN0TRIEmFEEIIIQqeGxtgT39DF7KVhkGDmUV2YLvkuGTWDF3Dqd9PAdDglQZ0/K4jtg5ymiYKD/m0CiGEEKJgubMDdvYEvQ7K94HGPxfZhCIxOpGQFiHcPn4brZ2Wjt91pNFrjawdlhDZJkmFEEIIIQqO+4dgW2dITQCfF+DZBaAtug2UHdwc8K7nTeztWPos70P55uWtHZIQOSJJhRBCCCEKhqiTENoeUh5C6VbQfBnY2Fs7KotTSpGalIqtoy0ajYYXfnqBhMgE3Mq6WTs0IXJMen8SQgghhPU9DIOtbSE5Eko0hRarwdbJ2lFZnC5ex8pBK1n24jJTz052TnaSUIhCT+5UCCGEEMK64q/CtjaQeAs86kDLdWBXzNpRWVxURBRLeyzl1pFbaGw0XD9wnXLPlLN2WEJYhCQVQgghhLAaG5WA7Y4XIC4CilWBVpvAobi1w7K4u2fuMq/VPOJux+Hs5cyLy16UhEIUKZJUCCGEEMI6lKJu8s9oUs6Ckw+03gJOpa0dlcVFhkUy//n5xN2Oo3Sd0vRb0w8PPw9rhyWERUlSIYQQQgir0ITPxzdlGwotmmZLwKXo9XwUFR7FvNbziL0ZS6napQjeGoxzCWdrhyWExUlDbSGEEELkv+jT2Bx5CwB9rYlQ6jkrB5Q3oq9Ek3A/Aa9qXgzaPEgSClFkyZ0KIYQQQuSvlHjY1QdNagJ3tHXxrPYeRXUkCr8WfgzaMggPPw9cS7taOxwh8ozcqRBCCCFE/jr8FkSfQjl684/jGNAUrdORuDtx3D191/Te91lfivkUvd6shHhU0foWCyGEEKJgu7wILv4CaEhtOo8kjYe1I7KohMgEFrRdQEhQCLeO3rJ2OELkG0kqhBBCCJE/Ys7DwdcMr2tNQJVqZd14LCwxOpEF7RZw+/httLZa7JztrB2SEPlGkgohhBBC5L3URNjVB1LioFRLqPWxtSOyqKSHSSzquIibh2/i7OVM8N/BlAgoYe2whMg3klQIIYQQIu/9MxaijoFDSQhcBNqi0zRbF69jcefFXNt7DUdPRwZtGUTJGiWtHZYQ+UqSCiGEEELkrYjf4cKPhtfPLgBnH+vGY0EpiSks6baEiB0ROLg5MGjTILzrels7LCHynSQVQgghhMg7Dy/CgVcMr2t8AD7trRuPhaUmp6JL0GHnYsfADQPxaVR0EiYhskPGqRBCCCFE3khNgt19QRcDJZtBnSnWjsjiHNwceGnDS9w7e08SCvFUkzsVQgghhMgb/7wNkYfBvjgELgZt0biWmZKUwpmVZ0zv7V3tJaEQTz1JKoQQQghheee+gws/GF4/Ow9cfK0bj4UkxSTxW6ff+L3n7+yYusPa4QhRYBSNSwZCCCGEKDiurYF/Rhte1/scyna2ajiW8vDmQ37r9Bu3jt7C3tWesk3KWjskIQoMSSqEEEIIYTmRh2F3f1B6qPQKVB9n7Ygs4v75+yxsv5Co8ChcSrkwcP1AyjQoY+2whCgwJKkQQgghhGXERcC2zpAaD2XaQ+MfQKOxdlS5dm3/NRZ3Xkz8vXiKVy7OwA0DKV6puLXDEqJAkaRCCCGEELmXHAXbXoDEW+BRB5r/Dlo7a0eVa3F34ljQZgHJscn4NPJhwNoBuJRysXZYQhQ4klQIIYQQIndSk2Fnb4g+BU4+0HIt2LlZOyqLcCnlQuuprbmw7gJ9lvfB3tXe2iEJUSBJUiGEEEKInFMKDo6A23+DrashoXAuZ+2ockUpRfLDZBzcHABo+lZTGr/eGK2NdJopREbk2yGEEEKInDs1FS7NBY2N4ZEnz3rWjihX9Kl61r+1nl8CfyHhQYJpuiQUQmROviFCCCGEyJnLi+D4x4bXjX4An47WjSeXUhJTWNFvBQe/P8jdU3e5tOWStUMSotCQx5+EEEIIkX23t8P+oYbX1d+FKq9ZN55cSoxKZEn3JURsj0Brp6XH/B7UfLGmtcMSotCQpEIIIYQQ2RN9Fnb2AH0y+PY2DHBXiMVcj2FRx0XcOXEH+2L29FvVjwqtK1g7LCEKFUkqhBBCCJF1iXdgWydIfgBez8Kz80FTeJ+mvnfuHgvbLST6SjSu3q4MXD8Q73re1g5LiEJHkgohhBBCZE1KHGzvBnGXwbUitFgNtk7WjipXjF3EFq9SnJc2voRnBU8rRyRE4SRJhRBCCCGeLCUetneB+/vAvji0XA+OJa0dVa65lXVj0OZBOHo64lJSBrUTIqcK7/1KIYQQQuSPlATY3hVuh4JtMcNYFG4B1o4qR1ISU1g9bDVHQ46appUIKCEJhRC5JHcqhBBCCJGxlATY0e3fwe1abQCvZ6wdVY5EX43m916/c+PgDU4tOUWVF6pIMiGEhUhSIYQQQoj0pSbCju5wazPYuhgSipKB1o4qR8K3h7PsxWXE343HqbgTvZb0koRCCAuSpEIIIYQQaaUmwo4ecGuTIaFouR5KNrN2VNmmlGL/t/vZ9PYmVKrCu543ff7oIw2yhbAwSSqEEEIIYS41CXb2gpsbwMYZgtZCqeesHVW2KaVYPWQ1x+YfA6D2wNp0+V8X7JztrByZEEWPJBVCCCGE+JcxobixDmycDI2ySwdZO6oc0Wg0eFTwQGOjod1X7Wj6VlM0Go21wxKiSLJYUhEfH09CQgLFixeXL6wQQghRGKUmw64X4cZasHGEoL+gdEtrR5Vt+hQ9WltDB5dBE4Ko1r2aDGgnRB7LUVIRExPDmjVr2LFjB7t27SIiIoLExETAcFWgePHiNGjQgOeee4527drRuHFjiwYthBBCCAtLTYbdfeD6n/+fUPwJ3q2tHVW2KKXY8+Ueziw/w+Btg7FzskOj1UhCIUQ+yFZSceDAAX744QdWrFhBQkICSqk0ZZRS3Lt3j02bNrF582YmTJhArVq1GD58OMOGDcPZ2dliwQshhBDCAvQ62N0Prq0GrQO0WAPebawdVbYkxyWzZugaTv1+CoCTi09Sf2h9K0clxNMjS0nF+fPn+eCDD1i1ahVKKby8vOjRowdNmjShcePGlClThuLFi+Pk5ERkZCSRkZGcPn2aAwcOsHv3bvbs2cPo0aOZNm0akyZN4pVXXkGrlXH3hBBCCKvT62B3f7i28v8TitVQpq21o8qWyIuRLO2xlDsn7qC11dLh2w7Ue7metcMS4qmSpaSiZs2aAPTt25fBgwfTpk0bbGxs0i1bqlQpSpUqRbVq1ejZsycA169fZ/Hixfz444/85z//4f79+3z44YcW2gUhhBBC5IheB7sHwNUVoLWHFivBp721o8qWsA1hrOi/gsSoRFxKu9BneR/KNy9v7bCEeOpkKakIDg7mww8/pFKlSjnaSNmyZXnnnXcYM2YMixYtkobcQgghhLXpU2DPS3B1uSGheG4l+HS0dlTZcjTkKKuHrgYF5Z4px4vLX8StrJu1wxLiqZSlpOKXX36xyMZsbGwIDg62yLqEEEIIkUMp8YY2FNf/BK0dPLcCynaydlTZ5t/KH6fiTtToXYMO33TA1kF6yhfCWuTbJ4QQQjxNku7D9i5wb6+hl6dmv0PZztaOKsvunLpDqZqlAPDw82DkiZEUK1PMylEJIaS1tBBCCPG0iLsCm58zJBT2ntB6C5TrYu2osiQlMYX1b63nx1o/cv6v86bpklAIUTDk+k5FdHQ027Zt49KlS8TGxqbbzSwYxq/4+OOPc7s5IYQQQuRE1EkI7QAJ18G5HLTcAB41rR1Vltw5dYcV/Vdw58QdAG4cvkFA5wArRyWEeFSukorJkyczffp0kpKSANJNKDQaDUopSSqEEEIIa7mzA7Z3A10UuNcwJBQuvtaO6omUUhz68RCb3t5ESmIKLqVc6BbSjSodq1g7NCHEY3KcVHzxxRdMnjwZgGeeeYb69etTsmRJ6dlJCCGEKEiurjSMQ6FPgpLNDAPbORS3dlRPFH8vnjXD1nBuzTkAKneoTLeQbriWdrVyZEKI9OQ4qfj555/RaDQsWrSIfv36WTImIYQQQljChZ/g0Oug9FC2KzRbArZO1o4qS67susK5NeewsbehzYw2NH2zKRqtXLgUoqDKcUPt69ev4+/vX6ATipUrV9K2bVtKlCiBk5MTFSpUoH///ly9etWsXExMDGPHjsXPzw8HBwf8/PwYO3YsMTExGa77t99+o0mTJri4uODp6UmnTp04dOhQhuUvXLhAnz59KFmyJE5OTtSpU4fvv/8evV5vsf0VQgghAFAKjk+EgyMNCUXlVw3dxhaShAKgWvdqtPqkFcMPDOeZUc9IQiFEAZfjpKJcuXK4uRXMAWaUUrz22mv07NmTy5cv069fP0aNGsVzzz3Hnj17iIiIMJWNi4sjKCiIr7/+mqpVqzJmzBhq1KjB119/TVBQEHFxcWnWP23aNAYOHMjt27cZMWIEffr0Yffu3TRr1oxt27alKX/69GkaN27MqlWraN++PW+99RYAb775JiNGjMiz4yCEEOIppE+BgyPg5BTD+1oTofFPoC3YvcjfP3+fRR0X8fDmQ9O0FuNb4F3X24pRCSGyKse/MP369WP69OlERETg5+dnyZhy7bvvvuN///sfr7/+Ot988w02NjZm81NSUkyvZ8yYwdGjRxk3bhzTp083TZ84cSJTpkxhxowZprYjYLjjMHHiRAICAjhw4ADu7u4AvPXWWzRp0oThw4dz9uxZbG3/PbQjR44kOjqatWvX0qmTYXChTz/9lI4dOzJ79mz69+9Pq1at8uRYCCGEeIqkJMCe/nBtNWi00OgHqFKwL14ppTg27xibRm9CF6dj4+iN9F7a29phCSGyKcd3Kj766CMaNGhAt27dOH78uCVjypWEhAQmT55MxYoVmTVrVpqEAjCd8CulmDNnDq6urkyYMMGszAcffICnpye//PKLWa9Wc+fOJSUlhY8++siUUADUrFmT4OBgLl68yNatW03Tz58/z44dO2jVqpUpoQCws7Nj6tSpAMyePdsyOy+EEOLplRQJoW0NCYXWAZovL/AJRWJUIhFfRrD2lbXo4nT4t/Kn3cx21g5LCJEDOb5T4ejoyPbt2+nbty8NGjSgfv36VKpUCWdn53TLazQafvnllxwHmlWbN28mMjKSIUOGkJqaypo1azh//jweHh60adOGypUrm8peuHCBGzdu0L59e1xcXMzW4+joSIsWLVi9ejVhYWFUqWLovs74eFO7dml/9Nq3b89PP/3E9u3bTfMzK9+kSRM8PDzYvn27JXZdCCHE0yruKmzrANGnwc4DgtZAqeesHVWmruy6woqBK4i5EoPWVkurT1oR+G4gWhsZl1eIwijHSUVqaiqvv/46f/31F3q9nsOHD3P48OEMy+dXUmFsLG1ra0vdunU5d+6caZ5Wq2XMmDF8+eWXgCGpAEwJw+OM0y9cuGD22tXVFW/vtM94PlrGKLNtaDQaKleuzKFDh4iPj88wIRNCCCEyFH0aQttD/DVwKgutNoBHLWtHlalza86xtMdSlF5h723PgBUD8AssWI9SCyGyJ8dJxaeffsqvv/6Kvb09vXr1ol69egVinIo7dwyjbX711Vc0aNCAAwcOUL16dY4cOcKrr77KV199RaVKlUztHACzx5geZWyIbixnfF2qVKlslc/qNjJKKpKSkkwDDAKmXql0Oh06nc403fj60WmiYJK6KlykvgqPp62uNLf/xmZvfzS6KFSxqqS0WAvO5aGA73+558rhWdGTMk3KoO2ipWS9kk9NnRVWT9t3q7DLTn1Zqk5znFSEhISg1WrZvHkzzz1XcG6xGrtotbe3Z9WqVfj4+ADw3HPPsXz5curUqcNXX33FyJEjrRlmtnz22WdmjcWNNm3alG4isnnz5vwIS1iA1FXhIvVVeDwNdVVBt45ayXPQoOe+thr7Uz9Et+0kcNLaoaWhUhUPdjzAM8jT1DWszyQfbF0NpyFPQ30VFVJXhUtW6is+Pt4i28pxUnH79m0CAgIKVEIB/94RaNSokSmhMKpZsyYVK1YkLCyMqKgoU9lH7yw8ynhH4NG7DO7u7tkun5VtZNY97wcffMDYsWPNlvH19aVdu3Zmy+l0OjZv3kzbtm2xs7PLcH3C+qSuChepr8LjqagrvQ7t0bHYXPyf4a3fS7g1/JG2Ng5WDix998/d56/hf3F9/3UCygfQ5M0mpnlPRX0VEVJXhUt26iuzcdmyI8dJhb+/P1ptwWtMVbVqVQA8PDzSnW+cnpCQkG4biEel1x6iSpUq7N27l1u3bqVpV5FR+Yy2oZQiLCwMHx+fNA3FH+Xg4ICDQ9o/FnZ2dul+UDKaLgoeqavCReqr8CiydZUUCbtehNtbAQ3U+xxt9XfRWvnR4/ToU/Xsm7WP0PGhpCSm4ODmgGtJV/m7VchJXRUuWakvS9VnjrOCwYMHc+bMGU6cOGGRQCzFON7DmTNn0szT6XSEhYXh4uJCyZIlqVKlCj4+PuzevTvNIHeJiYns2LEDHx8fsx6jgoKCAMOjR4/buHGjWRmAli1bZlj+wIEDREVFmZUXQggh0hV9BjY2MSQUtq7QYhXUGAcFMKG4f/4+IS1C2PzOZlISU6jUrhIjT46k7qC61g5NCJFHcpxUvPvuu/Ts2ZPOnTvz559/WjKmXKlUqRLt2rUjLCyMOXPmmM37/PPPiYqKokePHtja2qLRaBg+fDixsbFMmTLFrOxnn33GgwcPGD58uFnj85dffhlbW1umTp1q9kjTqVOnmD9/PpUqVaJ169am6QEBAbRo0YLQ0FDWrVtnmq7T6Rg/fjwAr7zyikWPgRBCiCLmxgbY9AzEXgQXf2i3B8p1tXZU6Trx2wl+qvsTV/dcxb6YPV1md2HghoG4+6bfYYkQomjI8eNPbdq0AeDWrVt0796d4sWLP3Gcir///junm8uW//73vwQGBvLKK6+watUqqlWrxpEjR9i6dSt+fn588cUXprLjxo1jzZo1zJgxgyNHjtCwYUOOHTvG+vXrqVevHuPGjTNbd0BAAJMmTWL8+PHUqVOH3r17ExcXx+LFi9HpdMyePdtsNG2AH3/8kcDAQHr06EGfPn3w8fFhw4YNHD9+nOHDh8to2kIIIdKnFJz7Fo6MBaWHks3huT/AsaS1I8uQV3Uv9Cl6KrapSNdfuuJeXpIJIZ4GOU4qjIO6Gd2/f5/79+9nWD4/u5qtVKkShw4dYsKECWzYsIFNmzbh7e3N66+/zoQJE8y6hHVxcWHbtm1MnjyZ5cuXs23bNry9vRkzZgwTJ05Mt63DRx99hL+/P7NmzeLHH3/E3t6ewMBApkyZQuPGjdOUr1GjBgcOHOCjjz5i/fr1xMbGUrlyZb799ltef/31PD0WQgghCqnUZDj0Olz8/7vuFV+Gxj9CAWuQrfSKG4duULZJWQDK1C/DsH3DKNOgjNW7mRdC5J8cJxWhoaGWjMPifH19mTt3bpbKuru7M3PmTGbOnJnl9Q8cOJCBAwdmuXxAQADLli3LcnkhhBBPscR7sKsX3NkBGi3U+wKqjSlw7SciL0ayZugaru65yisHX8G7nqEDE5+GPk9YUghR1OQ4qZDGxUIIIUQeiDwCO3tAXATYFoNmS6BsJ2tHZUafqmf/N/vZOn4rKQkp2LnYERkWaUoqhBBPnxwnFUIIIYSwsMuL4MBwSE0E10rQYjV41LR2VGbunLzDmmFruH7gOgD+rfzp+ktXPCt4WjkyIYQ1SVIhhBBCWJs+BY68C+dmGd6X6QjNFoF9wTpR3zV9F6Efh6LX6XFwc6Dtl21pMLyBtJ0QQmStS9lOnTqxf//+XG8sLi6Ozz//nP/+97+5XpcQQghRJCTeha1t/00oan4EQX8WuIQCwNbRFr1OT9WuVfnP6f/Q8JWGklAIIYAs3qnYuXMngYGBtGrVisGDB9O9e3eKFSuW5Y0cOXKERYsWERISwoMHD/jyyy9zHLAQQghRZEQehh09IP6qYUC7Z+eBb09rR2WSHJdMzNUYvKp5AdDkjSZ4VfWiUvtKkkwIIcxkKam4dOkSkyZNYs6cOYSGhuLg4EDz5s1p0qQJDRs2pEyZMhQvXhwHBweioqKIjIzkzJkzHDp0iF27dnHx4kWUUlSvXp1ff/2Vrl0L5oA9QgghRL65NB8OvAr6JChWxTBCtnsNa0dlcmnLJf585U+0tlpGHB+BnZMdWhstlTtUtnZoQogCKEtJRcmSJfnhhx945513+Omnn5g3bx5btmxhy5YtmV6pUEqh0Who3bo1r776Kr169UKrzfEg3kIIIUThp9fBP2/D+e8M7306Q+BCsC8Yg8QlPEhg0zubOPrrUQDcy7sTdTmKkjUK7oB7Qgjry1ZD7QoVKjB9+nSmTp1KaGgoO3bsYM+ePURERHDv3j0SExMpXrw4pUqVol69ejRv3py2bdvi5+eXV/ELIYQQhUfCbdjdxzD+BECtiVB7gmEsigLgzB9nWPf6OmJvxYIGGr/emOenPY9DsYI14J4QouDJUe9Ptra2tG3blrZt21o6HiGEEKJoun8QdvaE+GuG8ScCF0K5gvE4cHJcMqsGr+LMijMAeFXzosucLpRvVt7KkQkhCgvpUlYIIYTIa1eWw95BhvEn3KrBcyvBvZq1ozKxc7ZDF69Da6ul2XvNaDG+BbaOcooghMg6+cUQQggh8opScPozOPaR4b3PC9DsN7Bzs25cQFJMEmjAoZgDGo2Grr90Je52nIyKLYTIkYLxEKcQQghR1KQmwb6X/00oqo42jJBdABKKiB0R/FT3Jza8tcE0rViZYpJQCCFyTO5UCCGEEJaWeM/QfuLuTtDYQKPvocoIa0dFSlIKoRNC2fPFHlAQvj2chAcJOHk6WTs0IUQhJ0mFEEIIYUkx52DbCxB70XBXovkyKNPO2lFx+/htVg5aye3jtwGoP6w+7b9uLz07CSEsQpIKIYQQwlJubYWdvUAXBS4VoOVfVh/QTp+qZ+/MvYSODyU1ORXnks50md2Fat0KTkNxIUThJ0mFEEIIYQlhc+DgSFAp4BVoGCHb0foDxiVGJbL3q72kJqdStWtVuszugkspF2uHJYQoYiSpEEIIIXJDnwrH3oczXxre+w2AZ34BG0erhaSUQqPRAOBcwpluc7sRezOWei/XM00XQghLkqRCCCGEyCndQ8P4E9dWG97XngS1JoAVT9xjb8eydsRaavSpQe3+tQGo0rGK1eIRQjwdcp1U3L59mzlz5rB9+3auX79OYmIiFy9eNM1ftWoVd+7cITg4GEdH6121EUIIISzqYRjs6A7Rp0DrAM/MBf/+VgtHKcXJJSdZ/8Z6EiITuLr3KtW6V8POyc5qMQkhnh65SipWrVrFkCFDePjwIUopgDS3VU+fPs3HH39MyZIl6dGjR242J4QQQhQMNzfBrr6GBtlOZeC5P8DrGauFE3s7lrUj13J25VkAvOt50y2kmyQUQoh8k+PB744ePUrfvn2Jj49n7NixbN++nYYNG6Yp179/f5RSrFixIleBCiGEEFanlKHtxLaOhoSixDPQ/pDVEgqlFCcWn+C/Nf7L2ZVn0dpqaTm5JcMPDMe7rgxkJ4TIPzm+UzFt2jRSUlKYM2cOL7/8MkC6jzdVqFCB0qVLc/z48ZxHKYQQQlhbSjzsfwUifjO8rzgUGv8XbKw3zsOdk3f4Y8AfwL93JySZEEJYQ46Tih07dlCiRAlTQpEZX19fwsLCcropIYQQwrrirhjaTzw4AhpbaDgLqvzHqg2yAUrXLs0zY57B0cOR5h80x8bOxqrxCCGeXjlOKh48eEDt2rWzVFYpRVJSUk43JYQQQljP7e2w60VIugsOXtB8OZQOskoosbdi2Th2I60/bY1nRU8A2s9sb5VYhBDiUTlOKkqWLElERMQTy6WmpnL+/Hl8fHxyuikhhBAi/ykFF/4Lh0cbBrTzrG8Y0M6lvBVCUZz47QTr31xP4oNEEu4n8NLGl/I9DiGEyEiOG2o3b96cyMhIVq9enWm5kJAQHj58SOvWrXO6KSGEECJ/pSbB/uFw6A1DQuHXH9ruskpC8fDmQ5b2WMrKl1aS+CAR7/retP2ibb7HIYQQmcnxnYq3336bZcuW8eqrr2Jra8sLL7yQpsz8+fMZNWoUtra2jBo1KleBCiGEEPki/hrsfBHu7wONFupNh2pv53v7CaUUxxccZ8PoDSQ+SERrpyVoQhDN3msmbSeEEAVOjpOKxo0b8+WXX/LOO+/QtWtXSpUqRWJiIgAtWrTgzJkzREZGAvD9999To0YNy0QshBBC5JVbW2F3P0P7CTsPaLYEfKzTZuHY/GOsHmJ4GqBMgzJ0C+lG6dqlrRKLEEI8SY4ffwIYM2YMa9eupV69ety+fZvo6GiUUuzatYv79+9Ts2ZN/vrrL0aOHGmpeIUQQgjLU3o49TmEtjUkFJ71oMMhqyUUALX61aJMwzI8/9nzDNs3TBIKIUSBlqsRtQE6dOhAhw4duHLlCidOnCA6OhpXV1dq1KhB5cqVLRGjEEIIkXeSo2DvYLi+xvC+4svQ6AewdcrXMO6cusPemXvp/FNnbOxssHWwZfj+4WhtcnX9Twgh8kWukwqj8uXLU758/jdgE0IIIXLswXHY2RNiL4LWHhp9D5WG52v7iZSkFHZO28muz3ah1+nxqupFs3HNACShEEIUGhZLKoQQQohC5dJ8ODgCUhPAxc8w/kSJRvkawtW9V/lz+J/cPX0XgKpdq1J7YNbGgBJCiIIkS0nF/PnzLbKx4OBgi6xHCCGEyLHUJDg8CsJ+Nrwv0wECF4JDiXwLITk2mb8//JsD3x8ABS6lXOj4XUdqvFgDjZVH6RZCiJzIUlIxZMiQXP3IKaXQaDSSVAghhLCuuAjY2RsiDwEaqD0Jao03dB2bj/585U9OLjkJQL0h9Wj7ZVucSzjnawxCCGFJWUoqgoOD000qkpKSWLFiBTqdjrJlyxIQEEDp0qW5c+cO586d4/r169jb29OzZ08cHBwsHrwQQgiRZTc2wp4BkBwJ9sUhcBH4dLBKKEETg7h19BYdvu1ApbaVrBKDEEJYUpaSipCQkDTT4uLiCAoKolSpUnz33Xd069bNLPFQSrF69WpGjRrFhQsX2L59u8WCFkIIIbJMnwInp8DJTwEFxRvBc8sN7SjygVKKY/OPER0RTdCEIAC8qnnxn1P/QaOVR52EEEVDjhtqT5w4kaNHj3LkyBFq107bqEyj0dC9e3cqVqxI/fr1mTRpEjNmzMhVsEIIIUS2xF013J24u8vwvvKr0PAbsHHMl83fOXWHdf9ZR8SOCNBAlReq4NPQB0ASCiFEkZLjh0hXrFhB9erV000oHlWnTh1q1qzJ8uXLc7opIYQQIvuuroL1dQ0JhW0xCFwMTX7Ol4RCF69jywdb+Lnez0TsiMDO2Y42n7ehdB0ZwE4IUTTl+E7FrVu3CAgIyFJZjUbDzZs3c7opIYQQIsu0KhntkdEQ9l/DhOKNodliKJY/bRfO/XmO9W+uJzoiGjB0E9vh2w54+Hnky/aFEMIacpxUlClThlOnTnH27FmqVauWYbmzZ89y8uRJ/Pzy59lVIYQQT7GYs7RIHIdNWLjhffV3oM5UsLHPl80nRiWyKngViVGJuJd3p8O3HajWLeO/kUIIUVTk+PGnvn37otfreeGFF9i4cWO6ZTZt2kTnzp0B6NevX043JYQQQmROKbgUgu2WZ3DXh6McSkLLdVD/izxPKPSpetNrRw9H2n7RlsBxgfzn9H8koRBCPDVyfKfi448/ZuvWrRw8eJBOnTrh5+dHtWrVKFmyJHfv3uXcuXOEh4ejlKJRo0aMHz/eknELIYQQBrqHcHAkhC9CA9zV1saj7V/YuZXP801f2X2FtSPW0npaa6p2qQpAg+EN8ny7QghR0OQ4qXB2diY0NJTx48fzv//9j/DwcMLDw9OUeeWVV/j0009xdpZBfYQQQlhY5GHY1Q9iw0BjQ2rNiey5VJNOTmXydLPx9+LZ/N5mjv56FIAdU3YQ0DlARsMWQjy1cpxUgCFpmDlzJlOmTGHnzp2cP3+e2NhYXF1dCQgIoHnz5hQrVsxSsQohhBAGSsG5WXD0PdDrwLk8NFuM3qMxXF6Xd5vVK46GHGXzuM0k3E8AoP7w+rT5vI0kFEKIp1qukgojV1dXOnbsSMeOHS2xOiGEECJjiXdg7xC4ud7w3rcnNJ0D9p6g0+XZZu+cvMNfI/7i6u6rAJSqXYrOP3XGN9A3z7YphBCFhUWSCiGEECJf3NgA+wYbEgsbR6j/FVQZCflwlyD6SjRXd1/FzsWOlpNb0vStptjY2eT5doUQojDIcVKxY8eObC/TokWLnG5OCCHE0yw1CY6+b3jkCcC9lmHsCY9aebZJpRQPLj2geKXiAFTpVIW2X7alVt9auJVzy7PtCiFEYZTjpKJly5bZen5Uo9GQkpKS080JIYR4WkWfgd39IeqY4X3Am1BvOtg65dkm7529x7rX13Hj8A3eOPsGrt6uAAS+HZhn2xRCiMIsx0lFixYtMkwq4uLiuHjxIg8ePMDe3p5nn302xwEKIYR4SikFYf+Df8ZAagI4eMEzc6Fs5zzbZHJcMjs+3cHer/ai1+mxdbTl2v5rMt6EEEI8QY6Tim3btj2xzIoVKxg1ahQ+Pj4sWrQop5sSQgjxtEm6D/tfgWsrDe+928Kz8yCPuopVSnFu9Tk2jNpA9JVoAAI6B9Dh2w54VvDMk20KIURRkqcNtXv16kX58uVp2rQpjRs3ZvTo0Xm5OSGEEEXB7VDYMwgSroPWDup+BtXGgEabJ5tTesXSHks5t+YcAO5+7nT8tiNVu1bNk+0JIURRlDe/0I9o3LgxAQEBzJ49O683JYQQojDT6+DoB/D384aEwq0qtNsH1d/Os4QCQKPV4FHBA62dluYfNuf1069LQiGEENmUL13K2tvbExYWlh+bEkIIURg9DIPdAyDyoOF9pVeg4ddg65InmwvbGIZ7eXdKVi8JQKsprWg0ohFe1bzyZHtCCFHU5XlSERYWxtmzZylRokReb0oIIURhoxRc/AX+GQ0pcYYB7JrMhvK98mRzUeFRbByzkbOrzuIX5Mfg0MFoNBoc3BxwcHPIk20KIcTTIMdJxZUrVzKcp5Ti7t27HDx4kBkzZpCamkqXLl1yuikhhBBFUeJdOPAKXFtteF8qCJ5dAC6WH6Fal6Bjzxd72PXZLlISU9DYaCjToAx6nR4bexnATgghcivHSYW/v3+WxqlQSlGzZk2mTZuW000JIYQoaq6vhf3DIPG2oTF2nalQbSxoLXuCr5Ti3JpzbBy9kajwKAD8W/nT8buOlKpZyqLbEkKIp1mOk4ry5ctnmFRoNBpcXFyoWLEiHTt25OWXX8bBQW4rCyHEU08XC0feNow/AeBeEwIXgWfdPNncmT/OsKz3MgCKlS1Gu6/aUbNPzWwN3iqEEOLJcpxUhIeHWzAMIYQQRd7dvbB3EMReBDSGbmLrTgUbxzzbZLVu1SjTsAyV2lXiuQ+fw97VPs+2JYQQT7N86f1JCCHEUyw1GU5OgdOfgdKDs69hILvSrSy6GaUUp5acImxGGCnPp2BnZ4fWVsvwfcPR2uZ5D+pCCPFUy/GvbOvWrbM8mN2YMWN4/vnnc7opIYQQhVX0adj0LJyaakgo/AdBp+MWTyhuH7/NvJbzWB28mtiTsRyZc8Q0TxIKIYTIezm+U7Ft2zZSUlKyVPbo0aPs2LEjp5sSQghR2Cg9nPsOjr4H+iSwLw5NfobyvS26mYQHCYROCOXQfw+h9ApbJ1u8enpRf1h9i25HCCFE5vLl8afk5GRsbKTLPiGEeCrEXYV9L8Ptvw3vy3SAZ34FpzIW24RSin/m/MPWD7cSfy8egBov1qDVZ63YfXI3to7ydK8QQuSnPP/VTUhI4Pz58zL4nRBCFHVKQfhCOPQm6KLBxgkafAWVR0Ae9LZ0duVZ4u/FU7JGSTp+15EKrSug0+ngpMU3JYQQ4gmynFSsXr2a1atXm027cOECQ4cOzXCZhIQEDh48SGRkJL17W/aWtxBCiAIk8S4ceA2urTS8L9EUnp0PbgEW28TDmw+xsbfBuYQzGo2GDrM6cL7teZq80QQbO7kbLoQQ1pTlpOLo0aOEhISY3ms0Gm7fvm02LSNVqlSRwe+EEKKouroKDrwKSXdBYwu1J0GN90BrmZvhqcmp7PtmHzum7KDWgFp0+bkLACUCSvBswLMW2YYQQojcyfIvfvfu3fH39wcMz7IOHTqUgIAAPvjgg3TLazQanJycqFixIg0aNJCBhoQQoqhJjobDo+DyPMN791qGuxPFLddIOmxDGBtGbeD++fsA3Dlxh9TkVGzs5c6EEEIUJFlOKurWrUvduv+OeDpp0iTq1q3L4MGD8yQwIYQQBditrbBvCMRfBTRQ/V2oMwVsHCyy+siLkWwcs5Hzf54HwKW0C22mt6HuoLpotHKRSgghChoZUVsIIUTWpcTD0ffh/HeG964V4Zl5UKq5xTZx7s9zLOu9jNTkVLS2WpqOakqLj1vg6J53I28LIYTIHelzTwghRNbc2wd7B8NDw90DKo+A+l+AnatFN+Mb6Iu9qz1lGpahwzcdKFm9pEXXL4QQwvKylFTMnz8fAHd3d7p162Y2LTuCg4OzvYwQQggrS02Ck1Pg9OeGQe2cfKDpL+DTwSKrv3X0Fid+O0Gb6W3QaDQ4l3DmtSOv4ebrJu3xhBCikMhSUjFkyBA0Gg1Vq1Y1JRXGadkhSYUQQhQyD47B3mCIOm547z8QGn4LDsVzver4+/GEfhzK4Z8Po/QK30BfqnWvBoB7efdcr18IIUT+yVJSERwcjEajoUyZMmmmCSHE/7V353FV1fkfx18XuCyCLIqKKO7gmppr7uKCy9ikaWqjqZWWTdOi9TNNEzX3Sq2cNlucdLRtKlvcUyS13MXc0dx3U0D2C/f8/rgDIwEKcuECvp+Ph4843/M953wun77Kh3O+5yulkDUNDs6B/VPBagE3f2j5HlTrb4dTW9n1wS42TNpA8vVkABoOakjlZvZbcVtERIpWnoqKnNaiyMv6FCIiUgLFHoZfh8Mf223bVftCq/fBvWKBT31y00lWP7uaS/suAVDxnor0ersXNTrVKPC5RUTEcTRRW0REbAwrHHkLoiZAejKYfaDF21BjKNjhzrQ13cqPo3/k6uGruPu5E/pqKC2ebIGTi5MdghcREUe647/Ju3TpwvPPP5+nvmPGjKFr1653eqkCmzt3LiaTCZPJxK+//ppjn7i4OMaOHUv16tVxc3OjevXqjB07lri4uFzPu2zZMlq1aoWnpyd+fn707t2bnTt35to/OjqagQMHUqFCBTw8PGjcuDELFy7EarUW+DOKiBRI/An4qQvsHmMrKALC4C/7oeYjBSoo0pLTSLekA+Dk7ESPBT1oPro5zxx9hlZPt1JBISJSStzx3+YRERHs3r07T3337t1LRETEnV6qQA4dOsTkyZPx9PTMtU9CQgKdOnVi/vz51K1blzFjxtCgQQPmz59Pp06dSEhIyHbMzJkzGTJkCJcuXWL06NEMHDiQLVu20K5duxw/68GDB2nZsiXffvstPXr04NlnnwXgmWeeYfTo0Xb7vCIi+WJYIfpdWHkPXN4ELp62uROhq6FM1Ts/rWFw8D8H+Wf9f7LtrW2Z7XV61KHPu30o41/GHtGLiEgxUSS/IkpNTcXZ2bkoLpVFeno6w4cPp0mTJvTr1y/XfnPnzmXv3r2MGzeOtWvXMnv2bFatWsXkyZPZu3cvc+fOzdI/Ojqa8PBwQkJC2LdvH2+88Qbvv/8+W7duxcXFhZEjR5KWlpblmKeeeorY2Fi+/fZbli5dypw5c9i1axddu3Zl0aJFbNy4sVC+ByIiuYo/ARu6wY6/Q1oCVOgAvaIg+MkC3Z24tO8Sn3b5lC8HfEnMyRj2fLQHa7ruyIqIlGaFXlQkJSVx9OhRypcvX9iXymbOnDlERUXx8ccf51rUGIbBhx9+iJeXF5MnT86yb8KECfj5+fHRRx9hGEZm+yeffEJaWhoTJ07Ex+d/rz1s2LAhw4YN4/jx42zYsCGz/ejRo0RGRhIaGkrv3r0z281mMzNmzABg0aJFdvnMIiK3ZVjh6Du2uxOXNoJzGdtrYrtFQNnad3zahCsJ/PDUD7x/7/ucjDiJi7sLHV/pyKgdo3By1mNOIiKlWZ4naq9YsYIVK1ZkaYuOjuaxxx7L9ZikpCR27NjBtWvXGDBgwJ1HeQf279/P1KlTmTRpEg0bNsy1X3R0NOfPn6dHjx7ZHpFyd3enY8eOrFixgmPHjhEcHAyQ+XhTWFhYtvP16NGD9957j02bNmXuv1X/Vq1a4evry6ZNm+7kY4qI5E/8Cdj2uK2YAKjYEVp/XKBiAuDwisOsGLGC5Jj/viJ2YEO6ze2Gb3XfAgYsIiIlQZ6Lir1792Z5jazJZOLSpUt5erVscHAwM2fOvJP47khaWhojRoygfv36jB8//pZ9o6OjATILhj/LaI+Ojs7ytZeXFwEBAbfsn5drmEwm6tSpw86dO0lMTKRMmezPGaekpJCSkpK5nTF53GKxYLFYMtszvr65TYon5apkKRX5Mqw4HX8fp30vY0pPwHAug/WeGVjrPAUmJyjgZ/Ou4U3KjRQqNalE93ndqdahGlD037NSkau7iPJVcihXJUt+8mWvnOa5qOjbty81atQAbI8MPfbYY4SEhDBhwoQc+5tMJjw8PKhVqxbNmjUr0oXyZs6cSVRUFNu2bcNsNt+yb2xsLECWx5hu5u3tnaVfxtcVK+b8vvbc+uf1GjkVFbNmzWLq1KnZ2teuXZtj/3Xr1uV4HSl+lKuSpaTmq4z1Ik1TFlLBuh+Aq04N2eP6DxKjK0P06js6Z/K5ZOL3x+Pfwz+zrc6MOpQJLsP+G/vZv3K/XWK/UyU1V3cr5avkUK5KlrzkKzEx0S7XynNR0aRJE5o0aZK5PWXKFJo0acLw4cPtEoi9REVFMX36dF588UWaNWvm6HDsYsKECYwdOzZzOy4ujqCgIMLCwjILErBVmuvWraN79+63LabEsZSrkqXE5suw4nT8PZz2TcRk/e/dicaz8Kn9JJ1NdzbHITkmmc0zN7Nv4T4Mq0HPx3tSsfF/f8nS+9bHFoUSm6u7lPJVcihXJUt+8nWr5RPy444Xvzt58qRdArC34cOHU7t2baZMmZKn/hl3D26+s3CzjG/0zXcZfHx88t0/L9e4uUC4mZubG25ubtnazWZzjv+j5NYuxY9yVbKUqHzdOA7bHoPLkbbtip0w3fcxzl61uJN38VnTrez5eA8bJm4g8Yrtt1rBfwnGw9ejWH5PSlSuRPkqQZSrkiUv+bJXPkvditpRUVGAbZJ1Ttq0aQPAN998Q9++fXOcA3GznOZDBAcH88svv3Dx4sVs8ypy65/bNQzD4NixYwQGBt5yLQ0RkTwxrHDk7f+uip1kW3ei6RwI/u/ciTtwKvIUq59bzcW9FwHwr+dPj/k9qNOzjj0jFxGREixPRcWnn35ql4sNGzbMLue5lccffzzH9sjISKKjo/nrX/9KhQoVMueHBAcHExgYyJYtW0hISMjyg31ycjKRkZEEBgZSp87//vHs1KkTv/zyC2vXrs32mdasWZPZJ0Pnzp0B2xyIP08c3759OzExMfTq1euOP7OICABxR213J65ssW1X6gKtPwSvmnd8ytT4VD7r+xnJ15Nx93Wn05ROtPx7S5zNRb/2kIiIFF95KipGjBhhl4nWRVFUfPjhhzm2jxgxgujoaCZMmMB9992X2W4ymRg5ciTTpk1j2rRpzJkzJ3PfrFmzuH79Os8880yWz//oo4/y+uuvM2PGDB544IHMx5sOHDjAp59+Su3atenSpUtm/5CQEDp27MjGjRtZuXJl5loVFouFSZMmATBq1Cj7fRNE5O5iTYcjC2DfJEhPBhcvuPd1qPPEHS1iZ0my4OLugslkwtXLldBXQ7ly4Aqh00K1EraIiOQoT0XFsGHDivTtTUVt3LhxfPfdd8ydO5c9e/bQvHlzoqKiWLVqFU2bNmXcuHFZ+oeEhDBlyhQmTZpE48aNGTBgAAkJCSxfvhyLxcKiRYtwccn6rX333Xdp27Yt/fr1Y+DAgQQGBrJ69Wr27dvHyJEjCQ0NLcqPLCKlRexh+PVR+ONX23ZAd2i9CDyr5/tUhmHw27LfWP/Sev7y7l+oe39dAFo93cqeEYuISCmUp6IiL2tRlGSenp5EREQwdepUvvrqKyIiIggICGDMmDGEh4fnONdh4sSJ1KhRgwULFvDuu+/i6upK27ZtmTZtGi1btszWv0GDBmzfvp2JEyeyatUq4uPjqVOnDm+99RZPP/10UXxMESlNrGlweB7smwzWFDB7w71vQO3H7+juxLkd51j93GrO/nIWgO1vb88sKkRERG6n1E3Uzs3ixYtvWRz5+Pgwb9485s2bl+dzDhkyhCFDhuS5f0hICF9++WWe+4uI5CjmN/j1cbi2w7ZduSe0+gA8g/J9qrhzcWx4eQNRn9pecmH2NNNhYgfajGljz4hFRKSUK/Si4ty5c/z73/9m6dKl7Nu3r7AvJyJSeqWnwP7pcHA2GGlg9oHmC6Dm8Du6O7Hrg12sGbMGS6JtNdXGjzSm2+xulA0sa+fARUSktCuUoiI+Pp7//Oc/LFmyhIiICAzDKIzLiIjcPa5shW0jIe6QbbtqX2jxTygTeMenLFulLJZEC0Ftg+gxvwdVWlWxT6wiInLXsVtRYbVaWbt2LUuWLGHFihUkJSVlFhP33nsvQ4cOtdelRETuHpZ4iHoZji4EDHCvBC0WQlD/fN+dOL35NHFn42g0uBEAwb2DGfbTMGqE1ijVL+MQEZHCV+CiYs+ePSxZsoTly5dz+fLlzELCzc2NsWPHMnToUOrXr1/gQEVE7jrnV8P2JyHxtG271gjbZGy3cvk6zfUT11n/0noOfnkQNx83anWrRRn/MphMJmp2ufM1LERERDLcUVFx9uxZ/v3vf7NkyRIOHbLdijcMAz8/Px566CE++OAD/Pz8mDFjhl2DFRG5K6T8AbvGwMkltm3PGraJ2JW75+80cSn8PPNnfp3/K+mp6ZicTDQc1BB0U0JEROwsz0VFfHw8X331FUuWLGHTpk0YhoFhGHh4eNCnTx+GDBlCr169MJvNfPDBB4UZs4hI6WQYcPoL2PkMpFwBTFD3OWgyHVyyv9o6N9Y0K3s+3sPGVzaScDkBgFrdahH2RhiVGlcqpOBFRORulueiolKlSiQnJ2MYBs7OznTt2pUhQ4bw4IMP4uXlVZgxioiUfgmnYcff4fyPtm2fhtD6Q/C/L9+nunb8Gj/+/UeMdIPyIeUJeyOM4L8Ea96EiIgUmjwXFUlJSZhMJvz8/Fi4cCGDBw/WP1AiIgVlTbdNwt43EdISwMkMDV6Ghi+Ds2ueTxN/MR6vANsvePzr+tNuXDs8K3nS8u8tcTY7F1b0IiIiADjltWPDhg0xDIPr168zdOhQgoKCeOGFF9i1a1dhxiciUnpd3wfr2sLu520FRYV20CsKGk/Jc0ERfzGe75/4nvnV5nN5/+XM9q4zu3Lfc/epoBARkSKR56Lit99+Y8+ePYwZM4aAgADOnz/PggULaNWqFXXr1mXatGkcO3asMGMVESkd0pJg7wRY3Rz+2A5mb2j5HnSLBJ+8vS3Pkmghcnokbwe/ze5Fu7FarBz94WghBy4iIpKzPBcVAE2aNOGNN97gzJkzrF69msGDB+Ph4UF0dDRTp06lbt26tGzZsrBiFREp+S7+BCvv+d+q2EH94S+HIPhJMN3+r2TDahC1JIqFdRey8ZWNpManUqVVFR79+VHaj29fBB9AREQkuzt6payTkxNhYWGEhYWRkJCQ+VaoiIiIzMehLl++TNeuXXnkkUfo378/ZcuWtWvgIiIlSsofsOdF+H2xbdujCrT8J1R9IM+nMAyDpT2X8vu63wHwqeZD19ldaTSoESYnzXETERHHydedipx4enoyfPhw1q9fz+nTp5k9ezaNGjXCarWyceNGHn/8cQICAnj44YftEa+ISMliGHBiKfxQ/78FhQmCn4Y+B/NVUACYTCbq9KqDa1lXus7qytOHn+aeh+9RQSEiIg5X4KLiZoGBgYwbN459+/axe/dunn/+eSpVqkRSUhJffPGFPS8lIlL8xR2BDV3hl0ds6074NITuW6DlQts8ituIvxjPD0/9wJHvj2S2tXq6Fc8ee5b249tj9jAXZvQiIiJ5dkePP+VF06ZNadq0Ka+//jpr165l6dKlhXUpEZHiJT0ZDsyyzZuwpoKzOzSaDPVeyNNbnVLjU9n6xla2vrYVS4KFUxGnCO4djJOzE86uznhWzPtCeCIiIkWh0IqKDE5OTvTs2ZOePXsW9qVERBzvwlrbInbxx23blXvZ7kx41brtodY0K7s/2k1EeAQJl2wrYVdpVYXur3XHydmuN5ZFRETsqtCLChGRu0LSBdg1Bk5/btv2CITmb0HQg5CHhUJPbDjByqdXcvXwVQD8avvRdVZXGgxooIVGRUSk2FNRISJSENZ0OPYeRL0Mljjba2FDnoXGU/M0byKDJcnC1cNX8SjvQafwTrR4sgXOrlq4TkRESgYVFSIid+raLtg+Gq7ttG2Xawmt3oNyzW5/6PFrXD10lZA+IQAE9w7mL+/9hUaDG+Hu416YUYuIiNidigoRkfxKjYV9r0D0P8Gw2u5INJkFdZ4Ep1vfXUi8mkjk9Eh2vLMDV09Xnj3+LB7lPDCZTLR4skURfQARERH7UlEhIpJXhgGnvoDdz9vmUABU/xs0ewM8Am55qCXJwra3trF51mZSYlMAqNK6Cik3UvAo51HIgYuIiBQuFRUiInngaT2H88994NI6W0PZYGj5DgR0u+Vx1nQrUZ9GEREeQdyZOAAqNalE99e6U7t77cIOW0REpEioqBARuZW0BJx+m0aXpHk4JaWBkys0fBkavGRbf+I2rv9+ne9HfY+RbuAd5E2X6V1oPLSxVsEWEZFSRUWFiEhODAPOfA27x+CceAYAa0BPnFq+DWXr3PLQa8euUa5OOQDKB5enzQtt8KzgScunW2oVbBERKZVUVIiI/FncUdj5DFxcC4BRpjrb0/9Gs/ZTcHLNfUXsy/sv89PLPxH9YzSj942mYsOKAHSf071IwhYREXEUFRUiIhnSEmD/DDj8OlgttkedGrxEWvALXFwbkesidrGnY4kIj2Dvv/aCASZnE6d/Pp1ZVIiIiJR2KipERAwDzq6AXc9B4mlbW+Ve0OIt26NOFkuOhyVdT+LnmT+z/e3tpKekA9BgQANCp4fiX9e/qKIXERFxOBUVInJ3i//d9qjT+ZW2bc/q0GwBVH0g1zsTYHur06KWi7h+/DoANTrXoNucblRpVaUIghYRESleVFSIyN0pPRkOzoUDM8GaAk5mqP9/0HAiuJTJ8RBruhXDxcBkMuHk7ESLp1oQtTiKbnO6UadXHUy3KEJERERKMxUVInL3Ob8adv4D4o/btit1hRYLwadejt0NwyBuVxwfTfqIrjO7Uvf+ugC0frY19z1/H07OTkUVuYiISLGkokJE7h43jsHuF+Dcd7Ztj0BoNg+qDcz1UafTm0+z/uX1nPnZ9lrZLbO3ZBYVzmbnIglbRESkuFNRISKlnyXO9lanI/Ntb3UyuUDdZ+GeKWAum+MhF3ZfYMOkDRxbdQwAk9lEy6db0vmVzkUXt4iISAmhokJESi/DCr//C6ImQPIlW1vlHtBsPvjUz/Wwnyb+xOaZmwFwcnGi8YjGpLZOpdvwbpjNWrxORETkz1RUiEjpdGUr7HoWru2ybZcNthUTgb1v+VYngKA2QWCCxkMa02lKJ8pWK8vKlSuLIGgREZGSSUWFiJQuiedgzzg4tcy2bfaGRpMh5Blwzr4a9o3zN9j06ibK1SlH2xfaAhD8l2D+ceQflA8uD4All3UqRERExEZFhYiUDukpcHg+HJhuWxkbE9R+HBpPB49K2bonXU9iy9wtbHtzG2lJabj7udNidAtcPV0xmUyZBYWIiIjcnooKESn5zq2E3c/DjWjbtn8baPE2lGuerasl0cK2t7exZfYWkmOSAQhqG0TXWV1x9cx+J0NERERuT0WFiJRcN47Brufh/I+2bfcAuHcu1Bia47yJ42uP8+2Ib4m/EA9AxUYV6TKzCyF9QrRwnYiISAGoqBCRkictwfaK2MNvgDXV9orYes9Do1dscyhy4R3kTcKlBHxr+BL6aiiNHm6khetERETsQEWFiJQchgFnvoLdYyHxrK2tcg9otiDH1bB//+l3zu88T/uX2gNQoX4Fhq4ZSrUO1XBx019/IiIi9qJ/VUWkZIg9DDv/AZd+sm171oDmC6DKX7M96nRx70XWv7Se42uPY3IyUff+ulRoUAGAWt1qFW3cIiIidwEVFSJSvFniYf+r/1sN28kNGoyHBi+Bi0eWrjEnY9j4ykb2/XsfGOBkdqLFUy3wrOjpoOBFRETuDioqRKR4Mgw4/aXtUaekc7a2Kvfb7k54Zb3bkByTzKZpm9jxzx2kp6YD0GhwI0Knh1KudrkiDlxEROTuo6JCRIqfmAO21bAvbbBte9WC5m9ClT45djcMg72L95Kemk7NLjXpNqcbgS0CizBgERGRu5uKChEpPlJj4LcpcHQhGOng7A4NJkCDcbav/yvdks6RFUeo378+JpMJDz8Pei/sjUd5D2qH1dbrYUVERIqYigoRcTzDCr9/AnsnQMoVW1vQg3Dv6+BV86ZuBge+PMDGSRu5duwag78bTN376wJwz9/ucUTkIiIigooKEXG0q9tg5zNwbYdt27u+7VGnyt2zdDu+7jg/jf+JC7svAFCmQhksiZaijlZERERyoKJCRBwj6RJEjYffF9u2zd5wzxQI+Qc4mTO7ndtxjp8m/MSJn04A4OrlStv/a8t9Y+7Draxb0cctIiIi2aioEJGiZbXA0X/Cb+FgibO11RoBTWaBR0CWroZh8N1j33F5/2WcXZ1p8fcWdHi5A54V9IpYERGR4kRFhYgUnYsbbG91ij1g2y7XAlq8Df73ZXaJvxiPm48bZg8zJpOJrrO6cvDLg3Se2hnfGr4OCVtERERuTUWFiBS+hNOw50XbuhMAbv62OxO1HwOTEwApcSlseW0Lv877lc5TO9P2xbYAhPQJIaRPiIMCFxERkbxQUSEihSc9GQ69AQdmQHqSrYAI/js0ngaufgCkpaSx892dRE6PJOmPJABORpzMLCpERESk+FNRISKF49wPsOt5iD9u267Qwfaok18TwPZ62N+W/caGSRuIPRULgH89f7rO6krdB+o6KGgRERG5EyoqRMS+4qJh9/NwfqVt2yPQtt5E9cFw06J0a15Yw7YF2wAoG1iWzlM703REU5xcnIo+ZhERESkQFRUiYh+WeNtjTofngTXV9lrYemOh4SQwewFgTbfi5GwrGpqPas6+T/fR9v/a0vrZ1pjLmG91dhERESnGVFSISMEYBpz63DYRO+mcra1yL2i+ALxtE6z/OPoHGyZuwN3Pnfs/uB+ACg0qMObsGMweKiZERERKOhUVInLnYvbDzn/A5U22ba9a0GwBVOkDJhPxF+OJmBrB7kW7MdINnMxOhL4ailcl250LFRQiIiKlg4oKEcm/1Fj4bQocfRuMdHD2gIYvQ/0Xwdmd1PhUtr6xla2vbcWSYAFsr4btMrNLZkEhIiIipYeKChHJO8OAk/+GPf8HyRdtbUH9odk88KwGwJlfzvB5v89JuJQAQJXWVej+Wneqd6juqKhFRESkkKmoEJG8ub4Pdj0DlyNt22VDbK+IrRyWpZt/XX/SU9Lxq+1Ht9ndqN+/Pqab3vokIiIipY+KChG5tdTrsG8yRL8DhhWcy0CjV6DeGHB248zWMxz48gA95vXAZDLhUc6DYRuGUbFhRZxdnR0dvYiIiBQBFRUikjPDCsc/hqgJkHLV1lbtIduaE57VuHr4Kj+9/C2HvzkMQK2utQjpY3vbU+V7KzsqahEREXEAFRUikt3V7ba3Ol3bYdv2aQDN34aALty4cIOIsd+z56M9GOkGJicTTR9rSuVmKiRERETuVioqROR/ki7Z7kz8/olt2+wN90yBkH9gSYGfJ23g1/m/Ykm0vdGp7gN16TqrKxXqV3BczCIiIuJwKipEBKwWOLrQ9ppYS5ytreZwaDobPAIAcDZbOfT1ISyJFqq2qUr3ud2p1r6a42IWERGRYkNFhcjd7sI62PUcxB2ybZdrAS3exijXmgNfHqDeA/64uLvg5OJEr7d7kRKXQr2+9fRGJxEREcmkokLkbhV/Ana/AGe/sW27VYCmszBqjuD42hOsH/8+l6IuETYvjDZj2gC2ydgiIiIif6aiQuRuY4mHg7Ph0OtgTQGTM4T8A+6Zwtnd8fw0ciknI04C4ObjptfCioiIyG2pqBC5WxhW22rYe8dD0nlbW6Uu0PxNLp+ryIaBqzmy4ggAzq7OtHqmFe0ntKdM+TIODFpERERKAhUVIneDq7/a5k38sd227VXLtt5E1b5gMrFhxGccWXEEk5OJJsOb0HlKZ3yq+Tg0ZBERESk5VFSIlGaJ52x3Jk4utW27eEHDiSSUfwKc3fD872TrLtO7YHIy0WV6Fyo00OthRUREJH+cHB2AiBSC5Muw+0X4Pvi/BYUJaj1K7L27Wf1hU96s/R4bJm3I7F6xUUUGfT1IBYWIiIjcEd2pEClNkq/C4dfhyNuQnmhrq9COK16vsvX9OPYt/QxrmhWAy/suk25Jx9msidgiIiJSMKXuTsW5c+dYsGABYWFhVKtWDVdXVwICAujfvz/btm3L8Zi4uDjGjh1L9erVcXNzo3r16owdO5a4uLhcr7Ns2TJatWqFp6cnfn5+9O7dm507d+baPzo6moEDB1KhQgU8PDxo3LgxCxcuxGq1Fvgzi5ByDaImwnc14eAcW0FRriXn/b7k83ef4Z12kexdvBdrmpUaoTUYumYoj219TAWFiIiI2EWpu1Px9ttvM2fOHGrXrk337t2pWLEi0dHRfPvtt3z77bcsX76cgQMHZvZPSEigU6dO7N27l+7du/Pwww8TFRXF/Pnz2bhxI5s3b8bT0zPLNWbOnMnEiROpVq0ao0ePJj4+ns8++4x27dqxZs0aOnfunKX/wYMHadu2LYmJiQwcOJAqVaqwatUqnnnmGfbt28cHH3xQFN8aKY1SY+DwfNuftBu2Nr9m0HgqBP6FI+ERHP4mEoB6fevR7qV2VL2vquPiFRERkVKp1BUVrVq1IjIykg4dOmRp//nnn+natStPPfUUDzzwAG5ubgDMnTuXvXv3Mm7cOObMmZPZPzw8nGnTpjF37lymTp2a2R4dHU14eDghISFs374dHx/bG3KeffZZWrVqxciRIzl8+DAuLv/71j711FPExsby448/0rt3bwCmT59Or169WLRoEQ8//DChoaGF9j2RUig1Fo68CYfngSUWAGvZJhw6N4ay1TpTrUp1AFo904ob52/Q5oU2VKiv+RIiIiJSOErd408PPvhgtoICoEOHDoSGhnLt2jV+++03AAzD4MMPP8TLy4vJkydn6T9hwgT8/Pz46KOPMAwjs/2TTz4hLS2NiRMnZhYUAA0bNmTYsGEcP36cDRv+NwH26NGjREZGEhoamllQAJjNZmbMmAHAokWL7PPhpfSz3IADM22POf0WDpZY0so0ZvfZRfzzhcf56qmTbJi0MbO7ZwVP/vrhX1VQiIiISKEqdUXFrZjNZoDMuwjR0dGcP3+edu3aZXvEyd3dnY4dO3Lu3DmOHTuW2R4REQFAWFhYtvP36NEDgE2bNuWpf6tWrfD19c3SXyRHlnjbXInvatrmTqReJ8XlHrYeeIc3/z6M7186x7Xoa7j7uVO9U3Ws6ZqrIyIiIkWn1D3+lJvTp0+zfv16AgICuOeeewBbUQEQHByc4zEZ7dHR0Vm+9vLyIiAg4Jb9M9zqGiaTiTp16rBz504SExMpUybnlYtTUlJISUnJ3M6YQG6xWLBYLJntGV/f3CbFU55zlZaI0/H3cTryOqaUKwAYXsHs2PccG9+4QXLMZQDKVilL6+db0/Txprh6uZJuTSfdml6on+FuorFVcihXJYvyVXIoVyVLfvJlr5zeFUWFxWLhkUceISUlhblz5+LsbHvjTWys7Vn0mx9jupm3t3eWfhlfV6xYMV/983qN3IqKWbNmZZnXkWHt2rU5HrNu3boczyPFT265cjESqGFZS+20FZiNGABuEMBR10Gcs3bkj2uxJMdcxS3QjYoPVsSvkx9XzVdZH7m+CKO/+2hslRzKVcmifJUcylXJkpd8JSYm2uVapb6osFqtPPbYY0RGRjJq1CgeeeQRR4eUbxMmTGDs2LGZ23FxcQQFBREWFpZZlICteFq3bh3du3fPfNRLiqdcc5V4BqfohTj9/iGmtBtYrSYOH+zItohe1H6gDa3HtqUxYO1h5Vi7Y9T5Sx2cnO+qpxgdQmOr5FCuShblq+RQrkqW/OTrVkso5EepLioMw2DUqFEsXbqUoUOH8t5772XZn3H34OY7CzfL+CbffJfBx8cn3/3zco2bi4M/c3Nzy3xb1c3MZnOO/6Pk1i7FT2aurkfBodfh1GdgpJEU78HuX/uxc10zYs6mAynEXdlHu3EdMZlMYIaG/Rs6Ovy7jsZWyaFclSzKV8mhXJUsecmXvfJZaosKq9XKyJEj+eSTT3j44YdZvHgxTk5Zf6Ob0xyIm+U0HyI4OJhffvmFixcvZptXkVv/3K5hGAbHjh0jMDAw20RxuQsYBqZL6+HoAri4FoBLpyuxLbIvv22sQlqyFUjHo5wHzUY1o8VTLWwFhYiIiEgxUyqfm7i5oBg0aBBLlizJnEdxs+DgYAIDA9myZQsJCQlZ9iUnJxMZGUlgYCB16tTJbO/UqRNgm8/wZ2vWrMnSB8hcCC+n/tu3bycmJiZLf7kLpKdiOrWUTsljcYnsbSsoTE5QbRCbt7/KnlWVSUu2EtA0gL9+9FfGnB1Dt9nd8K3u6+jIRURERHJU6ooKq9XK448/zieffMJDDz3E0qVLcywowPb2pZEjRxIfH8+0adOy7Js1axbXr19n5MiRWX47/Oijj+Li4sKMGTOyPNJ04MABPv30U2rXrk2XLl0y20NCQujYsSMbN25k5cqVme0Wi4VJkyYBMGrUKLt8dinmUq7BgdnwXU1ctj+G09WrbPy6O1fMz8P9x6D9Z7T6v540eKgBj/78KE/sfoJ7H7sXs4duM4uIiEjxVuoef5o2bRqLFy/Gy8uLkJAQpk+fnq1P3759adq0KQDjxo3ju+++Y+7cuezZs4fmzZsTFRXFqlWraNq0KePGjctybEhICFOmTGHSpEk0btyYAQMGkJCQwPLly7FYLCxatCjLatoA7777Lm3btqVfv34MHDiQwMBAVq9ezb59+xg5cqRW0y7tbhyDwwvg908w0hI5dagG2zc8wuFttTCsJpICWtL7oZoABLUJIqhNkGPjFREREcmnUldUnDx5EoD4+PjMFav/rEaNGplFhaenJxEREUydOpWvvvqKiIgIAgICGDNmDOHh4TnOdZg4cSI1atRgwYIFvPvuu7i6utK2bVumTZtGy5Yts/Vv0KAB27dvZ+LEiaxatYr4+Hjq1KnDW2+9xdNPP223zy7FiGHAlc1weB6cXUFKoitRmxuzc2MHrpz+36T8oPZB1OpWy4GBioiIiBRcqSsqFi9ezOLFi/N1jI+PD/PmzWPevHl5PmbIkCEMGTIkz/1DQkL48ssv8xWXlEBWC5z+Eg7Ph2s7AVt98X74GK6fdwfA7Gmm0ZBGJDZIpP/f++stGiIiIlLilbqiQsQhUq7Bsffh6ELSb1ziyO4Q6rd2x1R7GKa6Y2iw/yxHvj1Ci7+3oMmwJjiXcc4yx0ZERESkJFNRIVIQsYfhyJtw4l/EXHRl18bm7IkYSkJsGYas6EOdVs0B6Bxeh64zu2ZO+rdYLI6MWkRERMSuVFSI5JdhhQtr4cibWM+t4fi+Ouxc35foqBAMq61oKBtYluSk/y1Y6OKuoSYiIiKll37SEcmrtAQ48SkceQviDhMf48VHU54l5opfZpeaXWrS4u8tqPvXujibc36VsYiIiEhpo6JC5HYSTsHRf2JELyLmvAm/itfBpSyerR7HtWIN3NOSaTqiKc2fbI5/XX9HRysiIiJS5FRUiOQk45WwR94k+chKoiIbs/OnIcRd9+GFzRVxvedRTGZvHvrPVXyq+WiBOhEREbmrqagQuVl6Cpz6DI68yfldl9ixvgX7fxlLWqqtaDB7mrmQ0JfqZttaE7ozISIiIqKiQsQm6SJEvwvH3uP8QRd++LgPF04EZu6u2KgiLZ5qQeOhjXHzdrvFiURERETuPioq5O72x0448iZpx7/CxTkZgDIV63HhZCDOrk40eKghLZ5qQVDboMzXwYqIiIhIVioq5O5jTYOz35D+25scWh3Dzp9a4u7Rl8GzTkPd5/ANepABfkeo0bkGnhU8HR2tiIiISLGnokLuHinX4PgiYjb/i10rK7Mnog0JsV4AOLs6kdj8I8qULwNAw4caOjJSERERkRJFRYWUfjEH4OhbnF61gS0rWhK99yEMwwkAr4AyNHuiBc1HNc8sKEREREQkf1RUSOlkWOH8KjiyAC6uB+DSqRYc3VMXgJpdqtPi7620SJ2IiIiIHaiokNIlLQF+/xfnvl/KjhWVqFH/Kk07O0HVvjSe9DTX/Sw0e0KL1ImIiIjYk4oKKR0Sz2LZt5ADS35mx+qGnP+9BwAXL95Dk9e/xlS2Jm5A2BuODVNERESkNFJRISXbtd3EbHyTnf+6wO6N95IUHwaAsxkaDqxPy2faglcVBwcpIiIiUrqpqJCSx7DCuR/h8Dy4HMHK1/5G9N52APhUMdPi6fbcO7K5XgcrIiIiUkRUVEjJkZZE6oHF7PvgB0Lqbca7fByYnGk5pAxp3v60GtuVkD4hODk7OTpSERERkbuKigop/lL+IDbyn+x4Zye71jUgOaEVsf0Mur7SCEKeIdgziOAXHR2kiIiIyN1LRYUUW8aN3zn75dtsW3SRg9tDMKzNAfALcsKv5yS4t62DIxQRERERUFEhxdG1PRgH5rDkKXdOHKgJ+AJQo40H943rQ/D99fSIk4iIiEgxoqJCigfDIPXEBlxPvQYX1mACylfuzemj1blnQGXue6kvlZoEODpKEREREcmBigpxLMNKzK9fse21lexeFcgj4w9QNcQJqg2m09vP0rlcIzwr6i1OIiIiIsWZigpxDGsaF1f9iy1zt3BgcxCGtSYA+w//jaovPAletfBycIgiIiIikjcqKqRIGWkpnFz+IVvm7eP43kCgOgC1WltpM6EPtf/aAkwmxwYpIiIiIvmiokKKRnoyHPsQY/9rrBj7ILFXAzE5WWnY04V2UwYT0DLY0RGKiIiIyB1SUSGFympJ4cii96lb6XWcUs7gBHQYsI9LcV1pM2U4fsFVHB2iiIiIiBSQigopFIbVyuFFH7NxxgGunPGl72g/mvQwoMEEmg96DJzdHR2iiIiIiNiJigqxu4ubt7L66S85tc8X8MXdMxlLwBC4/1kVEyIiIiKlkIoKsRtLQhLrR81hx2cGhuGLi9lCmxEutJ3xAu4V/B0dnoiIiIgUEhUVYh9JF/i6xwwOb6kAmGgYeo1uC0fi2+AeR0cmIiIiIoVMRYUUXMwB2NCNDr1MXDjyMH1eb0Cd4eGOjkpEREREioiKCimQxN93U2ZvL0i+TGDTRjxzaCTO/vUdHZaIiIiIFCEnRwcgJdfRr3/hrXu+4nSUO/g1g26bVFCIiIiI3IVUVMgdubjzJF8NWUlKohu/7eoIXdaBWzlHhyUiIiIiDqCiQvItOTaZL/p+hCXZhZr3nKHnkikqKERERETuYioqJN9+HL6I6+dc8K1wnYc+fxBnv9qODklEREREHEhFheTL0e9+Y/+Ka5icrPSfa8ajfm9HhyQiIiIiDqa3P0meWdOsrH76awDa/HU/VYcucXBEIiIiIlIcqKiQPEu+nkSVWicwUnzpNK0PuJRxdEgiIiIiUgyoqJA8K+N6mv5P/gsDN0z1rjo6HBEREREpJjSnQvIu4RQAJt96YPZycDAiIiIiUlzoToXkXVo8yQnupDn5oJJCRERERDLoToXk2ab3Yc6TL7FlqRekpzo6HBEREREpJlRUSJ75N64Hhonffm5Ayn69+UlEREREbFRUSJ7V61efctVMJMR5ETnlR0iNcXRIIiIiIlIMqKiQPHN2dab7/L4AbP22CYdmPwOG1bFBiYiIiIjDqaiQfKn3YGNaj64JwNczqnN0/rNgTXNwVCIiIiLiSCoqJN/C3h5KcBdP0lLNfDnBl/hvHwJLvKPDEhEREREHUVEh+ebk4sSg1WNoOqgc949ajVfyt7CqCVyOdHRoIiIiIuIAKirkjjibnXngs2doHP42lKkG8b9z4s3h7J70f1iTrjs6PBEREREpQioqpGAqtIG//EZq5Sf4btEDfD/Di0UNX+HU8nc0iVtERETkLqGiQgrO7I1Lh3dp9fS9uHmmcvFEBRb/7QpftH+Kq1t+dHR0IiIiIlLIVFSIXTi5ONEmfDjPHP8/Wgw2YzJZObQ1kHc6bueHvz7NjcM7HR2iiIiIiBQSFRViV56VfPnL8pcZvfNv1O2YgmF1Ytf3Fbny6WDYNhISzzk6RBERERGxMxUVUigqNqvL4E0zeXR1N9oMvkKtRsfh+EfwfTBnl75CWvw1R4coIiIiInaiokIKVbUe7QhbvhC6bwH/tiRcN7FkVDoLa80gas7rWFOTHR2iiIiIiBSQigopGhXaQvfNXKv0Pm5l0om94s234xN4r84E9r3xJtYUFRciIiIiJZWKCik6JhNB/YbyzKlwuv2fF+6eKVw548s3L8awsPpEds+cR3pyoqOjFBEREZF8UlEhRc7sVYZ2c1/guVMv0uV5N8p4J3H9kjc/To7hxqct4NgisKY5OkwRERERySMVFeIw7uXL0WH+eJ478zJhL5WhXb8ofL0OwfYnYFUTLm/4xtEhioiIiEgeqKgQh3P19qbN7P+jy/LPoNl8cCvPhb3XebdbFJ+1H0vs0SOODlFEREREbkFFhRQfLh5Q73m4P5rziY/g5GTlyBYf3mnyKTumLsCwWh0doYiIiIjkQEWFFD+ufjSfMYcnf+5BUIPrpCa7snJKLMvbvUjCmbOOjk5ERERE/kRFhRRbFdu049Go1+kxwRVncxrRv/qwuN18Es5pVW4RERGR4kRFhRRrJhcX7ps5gSc2dsO7fDxXz3iz7rEZjg5LRERERG7i4ugARPKiYrtOPLLShT++fIKQJofg6nDwb+3osEREREQE3amQEsS/VTvqdi2DycmAmN8cHY6IiIiI/JeKCikRrBYLEaMncnHPGVtDQDfHBiQiIiIimfT4kxR7Z1etZM3YtZw97EdUhcH8/Uc/zF41HB2WiIiIiPyXigopti7/spVNE7/i4EYfwA+zWyqhLzfA3PIJR4cmIiIiIjdRUSHFzpVtvxIx/gsORvgAPmAyaNongS7zR1O2dm1HhyciIiIif6KiQoqPpAuwL5w/vviZgxGDAajfKZaOr/YjoEMHBwcnIiIiIrnRRO0itGPHDnr37o2fnx+enp60atWKZcuWOTqs4iE1Fn5sBMcXUbfZYToOu8hTW7oyMGKeCgoRERGRYk53KopIREQEPXr0wNXVlcGDB+Pj48PXX3/NkCFDOHnyJC+//LKjQ3Qoy8WDpF1L4tLZmgQMep3QIQ86OiQRERERySMVFUUgLS2NkSNHYjKZiIyM5N577wUgPDycNm3aEB4ezkMPPURwcLCDI3Wcy9GpfPjkSwC4z9tBSPsteFZ0x6uSJ56VffEOqkDNbnXBvRK4+YOTs4MjFhEREZEMKiqKwIYNGzh+/DiPPvpoZkEBULZsWV555RUGDx7MJ598wsyZMx0YpWNV6dqJh/91kfWTt3PllDf71rj/d48FuIJP+Wief2ugrcnkxPJ5w4j9wxev8gZe/i54lHelTHkPPMp74hXgTb37q4NbOXAthyWtLC7e5TA56Wk/ERERkcKgoqIIREREABAWFpZtX0bbpk2bijKkYilk2CDq/K0/0Us+5+qBU8RfTCDhSgoJV9MoU/YGuFWAlKtgWLl8yoeYK75cOnHzGazADXwrnKae16jM1sWvjOLCycp4eKXgUdaCR1krHj7g4euEd2UzXce4g6sPmL05ucuZ9HQP3Hy9cfPzxa2cH65+5XD19cPJbC7qb4mIiIhIiaCioghER0cD5Ph4k5+fH/7+/pl97nZOLi7UfXQIdXPrYE2DlCsMrnaUG6cuEH/uKvEXYkn8I5HkmFSSYtIoUzYJfO+BlGuQeo2kBA8MqxOJcR4kxnlkOZ1vhet07T4nc3vdK6M4/3uVHC/t4x/H8x98BmZvcCnLmo8ac+18Wdw8nTB7OuPq6YKrlyuuXq64+7rTfEhFqDEETCY7fXdEREREiicVFUUgNjYWAB8fnxz3e3t7c/bs2VyPT0lJISUlJXM7Li4OAIvFgsViyWzP+PrmtlLJxZ9yrf0p1zr3Ljd/B0aG3SD58iWSLl8m5co1kq7GkHQ1juRr8bg4eZJe6wlMaXFgiaNcDSfSjRhSEp1JSXQhJdEVa7pt/obJlA5J521/gNO7m3L+d98cr+7uGUezOhNIqzoo5/jullyVEspXyaFclSzKV8mhXJUs+cmXvXJqMgzDsMuZJFdhYWGsW7eO6Oho6tSpk21/7dq1OXv2bJbC4WZTpkxh6tSp2dqXLVtGmTJl7B6v/I9hGJhSUzAlJuCcmoSnfwouJOJiJHNtt4XUP9KwJqdjTUrHmpxOepJBejKYzRY6PHGAHe7jHf0RRERERHKVmJjI3/72N2JjY/H29r7j86ioKAIPPfQQX331FTt37qR58+bZ9leoUAGTycTly5dzPD6nOxVBQUFcvXo1S/ItFgvr1q2je/fumPX8f7GmXJUsylfJoVyVLMpXyaFclSz5yVdcXBz+/v4FLir0+FMRyJhLER0dna2ouH79OlevXqVt27a5Hu/m5oabm1u2drPZnOP/KLm1S/GjXJUsylfJoVyVLMpXyaFclSx5yZe98ql3bBaBTp06AbB27dps+zLaMvqIiIiIiJQ0KiqKQNeuXalVqxbLli1j7969me03btzg1VdfxcXFhREjRjgsPhERERGRgtDjT0XAxcWFDz/8kB49etChQwcefvhhvL29+frrrzlx4gTTp08nJCTE0WGKiIiIiNwRFRVFJDQ0lM2bNxMeHs4XX3xBamoqDRs25NVXX2XIkCGODk9ERERE5I6pqChCrVq1YtWqVY4OQ0RERETErjSnQkRERERECkRFhYiIiIiIFIiKChERERERKRAVFSIiIiIiUiAqKkREREREpEBUVIiIiIiISIGoqBARERERkQJRUSEiIiIiIgWiokJERERERApERYWIiIiIiBSIigoRERERESkQFRUiIiIiIlIgKipERERERKRAXBwdgOSfYRgAxMXFZWm3WCwkJiYSFxeH2Wx2RGiSR8pVyaJ8lRzKVcmifJUcylXJkp98Zfw8mfHz5Z1SUVEC3bhxA4CgoCAHRyIiIiIipcGNGzfw8fG54+NNRkHLEilyVquV8+fPU7ZsWUwmU2Z7XFwcQUFBnDlzBm9vbwdGKLejXJUsylfJoVyVLMpXyaFclSz5yZdhGNy4cYPAwECcnO58ZoTuVJRATk5OVK1aNdf93t7eGvAlhHJVsihfJYdyVbIoXyWHclWy5DVfBblDkUETtUVEREREpEBUVIiIiIiISIGoqChF3NzcCA8Px83NzdGhyG0oVyWL8lVyKFcli/JVcihXJYsj8qWJ2iIiIiIiUiC6UyEiIiIiIgWiokJERERERApERYWIiIiIiBSIiopi5Ny5cyxYsICwsDCqVauGq6srAQEB9O/fn23btuV4zLZt23jggQfw9/fHzc2NkJAQJk+eTFJSUra+J0+exGQy5frns88+K+yPWGrExMTw7LPP0qZNGwICAnBzc6NKlSp06dKF//znPzkudR8XF8fYsWOpXr06bm5uVK9enbFjxxIXF5frdZYtW0arVq3w9PTEz8+P3r17s3PnzsL8aKVSYedLY8t+8purvXv38vLLL9OjRw8qVKiAyWSic+fOt72OxpZ9FHa+NLbsJz+5slgs/Oc//2HEiBHUr18fT09PypYtS+vWrXnnnXdIT0/P9ToaW/ZR2PkqjLGlidrFyPjx45kzZw61a9emU6dOVKxYkejoaL799lsMw2D58uUMHDgws//XX3/NoEGDcHZ2pn///gQEBLBlyxa2bdtGu3bt+Omnn7LM+j958iQ1a9akSZMm9O3bN9v1BwwYQKNGjYrio5Z4x44do2nTptx3333UqVOHcuXKcfnyZb7//nsuX77MqFGj+OCDDzL7JyQk0L59e/bu3Uv37t1p1qwZUVFRrF69mqZNm7J582Y8PT2zXGPmzJlMnDiRatWqMWDAAOLj4/nss89ITk5mzZo1efrBSWwKO18aW/aT31xNmTKFqVOn4urqSkhICPv376dTp05ERETkeg2NLfsp7HxpbNlPfnJ1+PBh6tevT9myZenSpQt169YlNjaW77//nvPnz3P//fezYsUKTCZTlmtobNlPYeerUMaWIcXGf/7zHyMyMjJbe2RkpGE2m41y5coZycnJhmEYRmJiouHv72+YzWZj586dmX2tVqvx9NNPG4Axa9asLOc5ceKEARjDhw8v1M9xN0hLSzMsFku29ri4OKNBgwYGYOzfvz+zffLkyQZgjBs3Lkv/jPbJkydnaT969Kjh4uJihISEGDExMZnt+/fvN8qUKWPUrl07x+tLzgo7Xxpb9pPfXO3fv9/YtWuXkZqaaly4cMEAjE6dOuV6fo0t+yrsfGls2U9+cnX27FnjnXfeMRISErL0jY+PN1q0aGEAxhdffJFln8aWfRV2vgpjbOnxp2LkwQcfpEOHDtnaO3ToQGhoKNeuXeO3334DYMuWLVy9epW+ffvSvHnzzL4mk4np06cD8N577+X4WIcUnLOzMy4uLtnay5YtS48ePQDbbxkADMPgww8/xMvLi8mTJ2fpP2HCBPz8/Pjoo4+y5OqTTz4hLS2NiRMn4uPjk9nesGFDhg0bxvHjx9mwYUNhfLRSqbDzJfaTn1yBbUw0a9YMs9mcp/NrbNlXYedL7Cc/uapSpQpPPfUUZcqUydLX09OTsWPHArBp06Ys+zS27Kuw81UYVFSUEBl/AWf8D3bp0iUAatasma2vr68vfn5+nDp1it9//z3b/vPnz/Puu+8ya9Ys/vWvf3H27NlCjPzukpyczIYNGzCZTDRo0ACA6Ohozp8/T7t27bI94uTu7k7Hjh05d+5cln94Mx4FCAsLy3aNjL9MiuIviNLOXvnKoLFVeHLK1Z3Q2Coa9spXBo2twpPfXP3555EMGltFw175ymDPsZXzFaRYOX36NOvXrycgIIB77rkHgAoVKgBw4sSJbP1jY2O5fv06AEePHqV27dpZ9q9bt45169Zlbru4uPDss8/y2muv4eSkOjM/YmJiWLBgAVarlcuXL7Ny5UrOnDlDeHg4wcHBgO2HVCBz+89u7nfz115eXgQEBNyyv+RPYeUrg8aW/eQlV3dCY6twFFa+Mmhs2U9Bc/Xxxx8D2YsHja3CUVj5ymDXsWW3B6mkUKSmphodO3Y0AOPTTz/NbL9x44bh7e1tmM1mY/fu3VmOeeaZZwzAAIxly5Zltl+6dMkIDw839u7da8TFxRmXL182vvvuO6N+/foGYIwfP77IPldpkfFMYsYfs9lsvPbaa4bVas3s8+9//9sAjIkTJ+Z4jmnTpmXLldlsNqpUqZJj/9OnTxuAERYWZt8PcxcorHxpbNlfXnL1Z3l5Rl9jq3AUVr40tuzvTnKV4f333zcAo0uXLtn2aWwVjsLKV2GMLRUVxVh6eroxdOhQAzBGjRqVbf+HH35oAIabm5sxZMgQ44UXXjDatGljuLq6GvXq1TMA4/PPP7/tdS5cuGCUL1/ecHV1Na5du1YYH6XUS0tLM06cOGHMmjXLcHV1Nfr165c5wUpFRfFj73zlRmOr4G6Vqz9TUeF49s5XbjS2Ci4/uTIMw/jhhx8Ms9lsVK9e3Th//ny2/Rpbhcve+cpNQcaW7hkWU4ZhMGrUKJYuXcrQoUN57733svV5/PHHWblyJW3atGHFihW88847uLi48NNPP1GnTh3gf49J3UpAQAC9e/cmNTWVHTt22P2z3A2cnZ2pUaMG48ePZ/r06XzzzTcsWrQIIHPCWmxsbI7HZqx7cPPENh8fn3z1l/yxd75yo7FVcLfK1Z3Q2Cpc9s5XbjS2Ci4/uVqzZg39+/enUqVKbNiwgcqVK2fro7FVuOydr9wUZGypqCiGrFYrjz/+OB9//DEPP/wwixcvzvW5tl69erFx40Zu3LhBYmIikZGRtG/fnv379+Pk5ESzZs3ydE1/f38AEhMT7fY57lYZzy1mTFq73bOkOT3DHxwcTHx8PBcvXsxTf7lz9sjXrWhs2c+fc3UnNLaKjj3ydSsaW/Zzq1ytXr2avn374u/vz8aNG6lVq1aO59DYKjr2yNet3OnYUlFRzFitVkaOHMknn3zCoEGDWLJkCc7Ozvk6x5YtWzh58iQ9e/bM828Ftm/fDkCNGjXyG7L8yfnz54H/vWkhODiYwMBAtmzZQkJCQpa+ycnJREZGEhgYmHl3CaBTp04ArF27Ntv516xZk6WPFIw98nUrGlv28+dc3QmNraJjj3zdisaW/eSWq4wfUP38/Ni4ceMt/97T2Co69sjXrdzx2MrXw1JSqNLT040RI0YYgPHQQw/ddpGY2NjYbG3nzp0z6tWrZ7i4uBi7du3Ksm/btm1GampqtmPeeOMNAzAaNGiQp4k/Yhh79uzJsrhPhj/++MNo2rSpARhLlizJbM/vYmpHjhzRIkJ2VNj50tiyn/zm6mZ5eUZfY8u+CjtfGlv2k99crVq1ynBzczMCAgKMw4cP3/b8Glv2Vdj5KoyxZTIMreBUXEyZMoWpU6fi5eXFc889l+Nvd/r27UvTpk0BmD59OkuXLqV9+/ZUrFiRM2fOsGLFChITE/noo48YPnx4lmM7d+7M4cOH6dSpE0FBQSQlJfHLL7+wZ88e/Pz8WL9+fZ4fl7rbPf/883z44YeEhoZSvXp1PD09OXXqFD/++CPx8fH079+fL774IvOxtYSEBNq3b8/evXvp3r07zZs3JyoqilWrVtG0aVM2b96cbU2EGTNmMGnSJKpVq8aAAQNISEhg+fLlJCUlsWbNGkJDQx3x0Uukws6Xxpb95DdXhw8fZvbs2QAkJSXxxRdfUKlSJXr27AnYbuO//vrrWa6hsWU/hZ0vjS37yU+uDh8+TNOmTUlJSWHw4MHUrVs32/lq1KjBiBEjsrRpbNlPYeerUMZWvkoQKVTDhw/P8tqwnP588sknmf1/+ukno1u3bkbFihUNs9lsBAQEGIMGDcr2itkMixYtMnr27GlUrVrVcHd3N9zd3Y26desazz33nHHmzJki+pSlw88//2yMGDHCqFevnuHt7W24uLgYFStWNHr27GksW7Ysx+o+JibGGDNmjBEUFGSYzWYjKCjIGDNmTI6/iciwdOlSo0WLFoaHh4fh4+Nj9OzZ09i+fXthfrRSqbDzpbFlP/nN1caNG2/5d2b16tVzvI7Gln0Udr40tuwnP7m6XZ64xR0mjS37KOx8FcbY0p0KEREREREpEE3UFhERERGRAlFRISIiIiIiBaKiQkRERERECkRFhYiIiIiIFIiKChERERERKRAVFSIiIiIiUiAqKkREREREpEBUVIiIiIiISIGoqBARERERkQJRUSEiIrmKiIjAZDLRuXNnR4dSKuzfvx9nZ2dGjx5tt3N26dIFX19f/vjjD7udU0Qkv1RUiIiUciaTKd9/HFVEREREMGXKFCIiIhxy/cL20ksv4ezszIQJE7K0ZxRvJpMp12PXrl2Lh4cHJpOJf/zjHxiGAcArr7xCbGws06dPL9TYRURuxcXRAYiISOFq165dtrbY2Fj279+f6/577rmn0OPKSUREBFOnTgUodXdHfv75Z1auXMmIESOoXr16vo5dvXo1/fr1Izk5meeee44FCxZk7gsNDeW+++7jnXfeYcyYMVSrVs3OkYuI3J6KChGRUm7z5s3Z2iIiIggNDc11v9jfwoULARg+fHi+jlu5ciUPPvggKSkpjB07ljfeeCNbn+HDh/Prr7+yaNEiXn31VbvEKyKSH3r8SUREpJBduXKFb7/9lsDAQDp27Jjn43744Qf69etHSkoK48aNy7GgABgwYAAuLi4sXryY9PR0e4UtIpJnKipERCRPrFYrb775Jo0aNcLd3Z1KlSrx+OOPc+XKlVyPuXbtGhMnTqRRo0Z4enpStmxZ7rvvPhYtWoTVas3S12QyZT76NHXq1CxzPEaMGJHZ7/fff2fOnDl07tyZoKAg3NzcqFChAj179uTHH38s0GdcuHAhJpOJPn363PIzubq6Yjab8zw5+ptvviE1NZVevXrh5JS3f3q/++47+vfvT2pqKi+//DJz5szJta+/vz+tW7fm7NmzbNmyJU/nFxGxJxUVIiKSJ4888gjPP/88qamp1KlTh2vXrvHxxx8TGhpKSkpKtv4HDhygcePGzJw5k+joaGrUqEGlSpXYvn07TzzxBIMGDcqcbAy2uR1BQUEABAUF0a5du8w/ISEhmf1mzpzJ+PHj2bVrF2XKlKFx48aYzWbWrFlDnz59bvnD9+0MGjQIFxcX1q5dy7Vr13Ls89VXX2GxWAgLC6N8+fJ5Om9kZCQArVq1ylP/b7/9lgEDBpCamsorr7zCjBkzbntMxrkzriUiUqQMERG562zcuNEAjNv9M5DRz2w2G4GBgca2bdsy9x05csSoWrWqARjvvvtuluPi4+ON2rVrG4Dx7LPPGrGxsZn7Dhw4YDRs2NAAjIULF2Y5Ljw83ACM8PDwXGNauXKl8euvvxpWqzVLe2RkpFG5cmXD2dnZOHbs2O2+Bbnq0aOHARjvv/9+jvs7d+5sAMbSpUvzfM6aNWsagLFz584c99+cj6+++sowm80GYEybNi3P11i2bJkBGD169MjzMSIi9qI7FSIiclsWi4W33347y2/aQ0JCGDduHACrVq3K0v/jjz/m+PHj9OvXjzfffBNvb+/MfQ0aNGDZsmWYTCbmzZuX71h69epF69ats71+tUOHDrz66qukp6fz+eef5/u8Gf72t78BsHz58mz7zp8/T2RkJGXKlOGBBx7I0/kMw+DMmTMAVK5c+bb9Bw8ejMViYcaMGbzyyit5jjvj3KdOncrzMSIi9qK3P4mIyG35+fnx4IMPZmtv2bIlYJvncLOvv/4agJEjR+Z4vsaNG1OjRg1+//13zp49S9WqVfMVz5UrV1i2bBnbtm3j8uXLJCcnA7ZX5QJERUXl63w369evH6NHjyYyMpLz588TGBiYue/zzz/HarVy//334+XllafzxcTEkJaWBkC5cuXyHEdGIZJXGee+1RwXEZHCoqJCRERuq3bt2jm2V6xYEYD4+Pgs7b/99hsAkydPZubMmTkee/XqVQDOnTuXr6Ji7dq1DBw4MLOAyElu8yHyomzZsvTp04cvv/ySzz//nDFjxmTuy7h78fDDD+f5fBkFD4Crq+tt+y9evJhhw4bx3nvv4eXlxWuvvZan63h4eACQlJSU59hEROxFjz+JiMhteXp65tie8SYj46YJ1/C/Owa7du1iy5YtOf65ceMGkL8fgmNiYhg8eDCxsbEMGzaMX3/9levXr5Oeno5hGKxbtw6wPa5VEDk9AnX8+HF27NiBr68vvXr1yvO5br47catCKMOQIUN49913AXj99deZNm1anq6TUUj5+/vnOTYREXtRUSEiInaX8WhQdHQ0hmHc8k9+Vs5etWoV169fp02bNixevJjWrVvj6+ubWdzk95Gh3PTq1QtfX1927NjBsWPHgP8VGP3798/THYcMbm5umXNK8noH5YknnshckyI8PJz58+ff9piMc1eoUCHPsYmI2IuKChERsbsGDRoAsH///nwd9+fJ13928uRJANq0aZNj34LMpbiZm5tb5hySjGIi478ZdzHyo2nTpgAcOnQoz8eMHTuWKVOmZH69aNGiW/Y/ePAgAM2aNct3fCIiBaWiQkRE7C7jB/K33nor26NRt3K7eQEZ+y9dupRt3x9//MFHH32U31BzdfMjUFFRURw8eJDKlSvn685Khvbt2wOwc+fOfB0XHh7Oiy++CMDo0aNZtmxZrn23b98O2N6CJSJS1FRUiIiI3T355JPUqlWLjRs3MmTIEC5cuJBlf3x8PF988QVjx47N0l6rVi0Atm7dmvnGpJtl/MD8xRdfsH79+sz2Cxcu0L9//xyPuVOhoaFUrlyZQ4cOMX78eMC2OF5eV8S+WVhYGACbN2/O97GvvfYao0ePxmq1Mnz4cFasWJGtj2EYbN26FWdnZ7p27Zrva4iIFJSKChERsTsvLy9+/PFHatasyfLly6latSoNGjTgvvvuo27duvj6+jJo0CC2bt2a5biwsDD8/PzYvHkz1apVo3379nTu3JnZs2cD0Lx5cwYMGIDFYqF79+4EBwdz7733Uq1aNXbv3p3Zzx6cnJwYNGgQAKtXrwby99anm3Xs2JE6deoQERGR412W23nnnXcYOnQoaWlpDBo0KHNCeoatW7dy9uxZevTokeUVuCIiRUVFhYiIFIp69eoRFRXF7NmzadmyJefOnWPv3r2kpqbSqVMnXn/9dT777LMsx3h7e7N27Vp69epFSkoKv/zyC5s2beLw4cOZff7973/zyiuvUKNGDU6dOsXFixcZMGAAO3bsoEmTJnb9DDfPn6hdu3aWxf/yw2QyMWrUqDtemM9kMrF48WIefPBBUlJS6Nu3b5a7HhnzPUaNGnVH8YmIFJTJyM/DriIiInJH4uLiqF27NuXKlePQoUN39BhVTmJiYqhRowbVqlVj7969djuviEh+6G8eERGRIuDt7c2kSZM4evRotjs0BfHmm28SGxvL7NmzVVCIiMNoRW0REZEi8tRTTxEXF4fVarXbOf38/Jg3bx69e/e22zlFRPJLjz+JiEip9fHHH/Pxxx/nuf+dvJ1JRER0p0JEREqx06dPs2XLFkeHISJS6ulOhYiIiIiIFIhmdImIiIiISIGoqBARERERkQJRUSEiIiIiIgWiokJERERERApERYWIiIiIiBSIigoRERERESkQFRUiIiIiIlIgKipERERERKRAVFSIiIiIiEiB/D8xxcaTRNq7fwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select the 10th entry in the averaged DataFrame\n",
    "example_data = df_10min_avg.iloc[99]  # Indexing starts at 0, so 79 is the specific entry\n",
    "\n",
    "# Create a single plot for Theta_v and Theta_v_Alternative\n",
    "fig, ax = plt.subplots(figsize=(8, 6))  # Larger figure for presentation\n",
    "\n",
    "# Plot Theta_v\n",
    "ax.plot(example_data['Theta_v'], example_data['Altitude'], label='Theta_v (K)', color='orange')\n",
    "\n",
    "# Plot Theta_v_Alternative\n",
    "ax.plot(example_data['Theta_v_Alternative'], example_data['Altitude'], label='Theta_v_Alternative (K)', color='purple', linestyle='--')\n",
    "\n",
    "# Set the title and labels with larger font sizes\n",
    "ax.set_title('Vertical Profile of Potential Temperature', fontsize=18)\n",
    "ax.set_xlabel('Theta_v (K)', fontsize=16)\n",
    "ax.set_ylabel('Altitude (m)', fontsize=16)\n",
    "\n",
    "# Increase tick label font size\n",
    "ax.tick_params(axis='both', which='major', labelsize=14)\n",
    "\n",
    "# Add a grid for better visibility\n",
    "ax.grid()\n",
    "\n",
    "# Add legend with larger font size for better presentation visibility\n",
    "ax.legend(fontsize=14)\n",
    "\n",
    "# Add some space between the plot and the title\n",
    "plt.tight_layout()\n",
    "\n",
    "# Display the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9663a6ce",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Select the 10th entry in the averaged DataFrame\n",
    "example_data = df_10min_avg.iloc[76]  # Indexing starts at 0, so 9 is the 10th entry\n",
    "\n",
    "# Create subplots in one row\n",
    "fig, axs = plt.subplots(1, 4, figsize=(20, 5), sharey=True)\n",
    "\n",
    "# Scatter plot for Temperature\n",
    "axs[0].scatter(example_data['Temperature'], example_data['Altitude'], color='red')\n",
    "axs[0].set_title('Temperature (K)', fontsize=14)\n",
    "axs[0].set_xlabel('Value')\n",
    "axs[0].grid()\n",
    "\n",
    "# Scatter plot for Theta_v\n",
    "axs[1].scatter(example_data['Theta_v'], example_data['Altitude'], color='orange')\n",
    "axs[1].set_title('Theta_v (K)', fontsize=14)\n",
    "axs[1].set_xlabel('Value')\n",
    "axs[1].grid()\n",
    "\n",
    "# Scatter plot for Relative Humidity (RH)\n",
    "axs[2].scatter(example_data['Relative Humidity'], example_data['Altitude'], color='blue')\n",
    "axs[2].set_title('Relative Humidity (%)', fontsize=14)\n",
    "axs[2].set_xlabel('Value')\n",
    "axs[2].grid()\n",
    "\n",
    "# Scatter plot for Specific Humidity (qv)\n",
    "axs[3].scatter(example_data['Specific Humidity (qv)'], example_data['Altitude'], color='green')\n",
    "axs[3].set_title('Specific Humidity (g/kg)', fontsize=14)\n",
    "axs[3].set_xlabel('Value')\n",
    "axs[3].grid()\n",
    "\n",
    "# Add a horizontal line at 2 km\n",
    "for ax in axs:\n",
    "    ax.axhline(y=2000, color='red', linestyle='--')\n",
    "    ax.set_ylim(0, 3000)  # Reverse y-axis for altitude\n",
    "    ax.set_ylabel('Altitude (m)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.suptitle(f'Profile at Time: {example_data[\"Time\"]}', fontsize=16, y=1.02)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "9c1e2d08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select the 10th entry in the averaged DataFrame\n",
    "example_data = df_10min_avg.iloc[36]  # Indexing starts at 0, so 38 is the selected entry\n",
    "\n",
    "# Create a figure for Temperature and Theta_v\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Scatter plot for Temperature\n",
    "plt.scatter(example_data['Temperature'], example_data['Altitude'], color='red', label='Temperature (K)', alpha=0.7)\n",
    "\n",
    "# Scatter plot for Theta_v\n",
    "plt.scatter(example_data['Theta_v'], example_data['Altitude'], color='orange', label='Theta_v (K)', alpha=0.7)\n",
    "\n",
    "# Add a horizontal line at 2 km\n",
    "plt.axhline(y=2000, color='red', linestyle='--', label='2 km Threshold')\n",
    "\n",
    "# Set labels and title\n",
    "plt.title(f'Temperature and Theta_v Profile at Time: {example_data[\"Time\"]}', fontsize=16)\n",
    "plt.xlabel('Value (K)', fontsize=14)\n",
    "plt.ylabel('Altitude (m)', fontsize=14)\n",
    "\n",
    "# Add a legend\n",
    "plt.legend()\n",
    "#plt.ylim(0,1500)\n",
    "# Set grid\n",
    "plt.grid()\n",
    "\n",
    "# Show the plot\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86bc6571",
   "metadata": {},
   "source": [
    "### BLH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6d527a7e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  Time     BLH\n",
      "0  2024-05-12 00:03:42  1320.0\n",
      "1  2024-05-12 00:18:43     0.0\n",
      "2  2024-05-12 00:33:42     0.0\n",
      "3  2024-05-12 00:48:44   880.0\n",
      "4  2024-05-12 01:03:45   880.0\n",
      "..                 ...     ...\n",
      "91 2024-05-12 22:48:51     0.0\n",
      "92 2024-05-12 23:03:51     0.0\n",
      "93 2024-05-12 23:18:50     0.0\n",
      "94 2024-05-12 23:33:51     0.0\n",
      "95 2024-05-12 23:48:51     0.0\n",
      "\n",
      "[96 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "# Load the Boundary Layer Height (BLH) data\n",
    "blh_file = next((file_name for file_name in datasets.keys() if file_name.upper().endswith('.BLH.NC')), None)\n",
    "time_blh = None\n",
    "blh_values = None\n",
    "\n",
    "if blh_file in datasets:\n",
    "    blh_dataset = datasets[blh_file]\n",
    "\n",
    "    try:\n",
    "        # Extract time and BLH\n",
    "        if 'time' in blh_dataset.variables:\n",
    "            time_var = blh_dataset.variables['time'][:]\n",
    "            time_blh = [datetime(2001, 1, 1) + timedelta(seconds=int(t)) for t in time_var]\n",
    "\n",
    "        if 'BLH' in blh_dataset.variables:\n",
    "            blh_values = blh_dataset.variables['BLH'][:]\n",
    "\n",
    "    except Exception as e:\n",
    "        print(f\"Error accessing data in {blh_file}: {e}\")\n",
    "\n",
    "# Create DataFrame for BLH data\n",
    "df_blh = pd.DataFrame({\n",
    "    'Time': time_blh,\n",
    "    'BLH': blh_values\n",
    "}) if time_blh is not None and blh_values is not None else pd.DataFrame()\n",
    "\n",
    "# Close the datasets\n",
    "for dataset in datasets.values():\n",
    "    dataset.close()\n",
    "    \n",
    "print(df_blh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ef5e142f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Check if the DataFrame is not empty\n",
    "if not df_blh.empty:\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    plt.plot(df_blh['Time'], df_blh['BLH'], marker='o', linestyle='-', color='b')\n",
    "    plt.title('Boundary Layer Height Over Time')\n",
    "    plt.xlabel('Time')\n",
    "    plt.ylabel('Boundary Layer Height (m)')\n",
    "    plt.xticks(rotation=45)\n",
    "    plt.grid()\n",
    "    plt.tight_layout()  # Adjust layout to prevent clipping of tick-labels\n",
    "    plt.show()\n",
    "else:\n",
    "    print(\"No data to plot.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "87537086",
   "metadata": {},
   "outputs": [],
   "source": [
    "def estimate_zi_from_theta_v(theta_v, z):\n",
    "    \"\"\"Estimate CBL height from theta_v profile using gradient method.\"\"\"\n",
    "    dthetav_dz = np.gradient(theta_v, z)\n",
    "    dthetav_dz_smooth = gaussian_filter1d(dthetav_dz, sigma=1)  # Optional smoothing\n",
    "    zi_index = np.argmax(dthetav_dz_smooth)\n",
    "    return z[zi_index] if zi_index < len(z) else np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cafa7697",
   "metadata": {},
   "outputs": [],
   "source": [
    "zi_list = []\n",
    "zi_times = []\n",
    "\n",
    "for idx, row in df_10min_avg.iterrows():\n",
    "    z = row['Altitude']                # height array\n",
    "    theta_v = row['Theta_v_Alternative']    # already-computed profile\n",
    "\n",
    "    zi = estimate_zi_from_theta_v(theta_v, z)\n",
    "    zi_list.append(zi)\n",
    "    zi_times.append(row['Time'])\n",
    "\n",
    "zi_df = pd.DataFrame({'Time': zi_times, 'zi': zi_list})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "d825eb77",
   "metadata": {},
   "outputs": [],
   "source": [
    "def estimate_zi_parcel_method(theta_v_profile, z_profile, theta_v_surface):\n",
    "    \"\"\"\n",
    "    Estimate boundary layer height (zi) using parcel method.\n",
    "    Finds first height where environmental theta_v > surface theta_v.\n",
    "    \n",
    "    Parameters:\n",
    "        theta_v_profile: array-like of virtual potential temperature with height\n",
    "        z_profile: array-like of corresponding height levels (same length)\n",
    "        theta_v_surface: surface virtual potential temperature (scalar)\n",
    "        \n",
    "    Returns:\n",
    "        Estimated boundary layer height (zi)\n",
    "    \"\"\"\n",
    "    for i, theta_env in enumerate(theta_v_profile):\n",
    "        if theta_env > theta_v_surface:\n",
    "            return z_profile[i]\n",
    "    return np.nan  # If no crossing is found"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9744fb4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "zi_parcel_list = []\n",
    "zi_parcel_times = []\n",
    "\n",
    "for idx, row in df_10min_avg.iterrows():\n",
    "    z = row['Altitude']                # height levels\n",
    "    theta_v = row['Theta_v_Alternative']  # profile (list or array)\n",
    "    \n",
    "    theta_v_surface = theta_v[0]  # assume surface is first level\n",
    "    zi = estimate_zi_parcel_method(theta_v, z, theta_v_surface)\n",
    "    \n",
    "    zi_parcel_list.append(zi)\n",
    "    zi_parcel_times.append(row['Time'])\n",
    "\n",
    "zi_parcel_df = pd.DataFrame({'Time': zi_parcel_times, 'zi_parcel': zi_parcel_list})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "97a36ec4",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(10, 5))\n",
    "plt.plot(zi_df['Time'], zi_df['zi'], label='CBL Height $z_i$', color='blue')\n",
    "plt.xlabel('Time (UTC)')\n",
    "plt.ylabel('Height (m)')\n",
    "plt.title('Estimated CBL Height on April 20, 2024')\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7fca03f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 5))\n",
    "\n",
    "# Plot gradient method\n",
    "plt.plot(zi_df['Time'], zi_df['zi'], label='CBL Height $z_i$ (Gradient Method)', color='blue')\n",
    "\n",
    "# Plot parcel method (make sure zi_parcel_df is created as shown earlier)\n",
    "plt.plot(zi_parcel_df['Time'], zi_parcel_df['zi_parcel'], \n",
    "         label='CBL Height $z_i$ (Parcel Method)', color='orange', linestyle='--')\n",
    "\n",
    "plt.xlabel('Time (UTC)')\n",
    "plt.ylabel('Height (m)')\n",
    "plt.title('Estimated CBL Height on May 23, 2024')\n",
    "plt.grid(True, linestyle='--', alpha=0.7)\n",
    "plt.legend()\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7553fab7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   Time   zi\n",
      "0   2024-05-12 00:00:00  250\n",
      "1   2024-05-12 00:10:00  220\n",
      "2   2024-05-12 00:20:00  190\n",
      "3   2024-05-12 00:30:00  190\n",
      "4   2024-05-12 00:40:00  190\n",
      "..                  ...  ...\n",
      "139 2024-05-12 23:10:00  220\n",
      "140 2024-05-12 23:20:00  190\n",
      "141 2024-05-12 23:30:00  220\n",
      "142 2024-05-12 23:40:00  220\n",
      "143 2024-05-12 23:50:00  220\n",
      "\n",
      "[144 rows x 2 columns]\n"
     ]
    }
   ],
   "source": [
    "print(zi_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "6c479720",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CBL height saved to: C:\\Users\\magda\\Master_Thesis\\Microwave_radiometer\\2024-05\\2024-05-12\\cbl_height_2024-05-12.csv\n"
     ]
    }
   ],
   "source": [
    "# Add parcel method CBL height to the DataFrame\n",
    "zi_df['zi_parcel'] = zi_parcel_df['zi_parcel']\n",
    "\n",
    "\n",
    "output_file = os.path.join(folder_path, 'cbl_height_2024-05-12.csv')\n",
    "\n",
    "# Save the DataFrame\n",
    "zi_df.to_csv(output_file, index=False)\n",
    "print(f\"CBL height saved to: {output_file}\")"
   ]
  }
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