{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9dbd7ed4",
   "metadata": {},
   "source": [
    "# 2D coarse graining of bedload transport"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "998d1035",
   "metadata": {},
   "source": [
    "In this example, we demonstrate how to use the `CoarseGraining` to perform coarse graining on a 2D bedload transport simulation with periodic boundaries, and plot the results.\n",
    "In order to do that, you can use the `compute_CG.ipynb` Jupyter notebook provided in the `examples/bedload_transport` directory. \n",
    "\n",
    "The files required for this example can be found in the `examples/bedload_transport` directory of the repository:\n",
    "\n",
    "- The DEM simualtion data files in the `examples/bedload_transport/DEM_data` directory\n",
    "- The configuration file `config.ini` in the `examples/bedload_transport` directory"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cab25d5",
   "metadata": {},
   "source": [
    "## Import packages"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca4dd69",
   "metadata": {},
   "source": [
    "First, ensure you have the necessary libraries installed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4d9ff8fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello from pysammos\n",
      "Loading macroscopic_fields package...\n",
      "Loading data_read package...\n",
      "Loading particle_phase package...\n",
      "Loading spatial_weights package...\n",
      "Loading neighbour_search package...\n",
      "Loading grid_generation package...\n",
      "Loading data_handle package...\n",
      "Loading data_write package...\n",
      "Loading post_averaging package...\n"
     ]
    }
   ],
   "source": [
    "from pysammos.utils.config_loader import load_config\n",
    "from pysammos.coarse_graining import CoarseGraining\n",
    "from pysammos.data_write.h5.writer import H5XarrayManager\n",
    "from pysammos.post_averaging.profiles import VerticalIntegrator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "28571097",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pyvista as pv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "525d3b7f",
   "metadata": {},
   "source": [
    "## Completing the Configuration file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b8ce0ed",
   "metadata": {},
   "source": [
    "Before running the coarse graining, ensure that the `config.ini` file is properly set up. The configuration file contains various sections, marked by headers in square brackets. \n",
    "\n",
    "The `paths` section specifies the input and output file paths."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8e835d4",
   "metadata": {},
   "source": [
    "```ini\n",
    "[paths]\n",
    "particles_path = ./VTU/DES_FB1_\n",
    "contacts_path = ./VTU/ENTIRE_DOMAIN_\n",
    "output_path = ./PysammosCG/\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51c873da",
   "metadata": {},
   "source": [
    "The `timesteps` section defines the time range and interval for the coarse graining process. `t0` is the starting timestep, `tf` is the ending timestep, and `dt` is the timestep interval. \n",
    "Note that the `t_pad` parameter is used to specify the number of zero-padding to be added to the `t0` and `tf` values when reading the DEM simulation data files. This is useful when the timestep numbers in the filenames have leading zeros."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d92cae3a",
   "metadata": {},
   "source": [
    "```ini\n",
    "[timesteps]\n",
    "t0 = 150\n",
    "tf = 152\n",
    "dt = 1 \n",
    "t_pad = 4\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8d70a38",
   "metadata": {},
   "source": [
    "\n",
    "The `smoothing_function` section defines the `type` of smoothing function to be used for coarse graining. In this case, we are using the Lucy function.\n",
    "Find the corresponding documentation in the page `kernels_module`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "819eb7cf",
   "metadata": {},
   "source": [
    "```ini\n",
    "[smoothing_function]\n",
    "type = Lucy\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9db6509a",
   "metadata": {},
   "source": [
    "The `flags` section defines the `partialignore` flag, which indicates whether to ignore particle phases during the coarse graining process. \n",
    "It will force the number phases to be one if it is set to True."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "604892d9",
   "metadata": {},
   "source": [
    "```ini\n",
    "[flags]\n",
    "partialignore = True\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a109bc9d",
   "metadata": {},
   "source": [
    "The `key_mapping` section maps the DEM simulation data fields to the expected keys used in the coarse graining process."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af01fb2f",
   "metadata": {},
   "source": [
    "```ini\n",
    "[key_mapping]\n",
    "Global_ID = Particle_ID\n",
    "Particle_Velocity = Velocity\n",
    "Particle_Diameter = Diameter\n",
    "Particle_Density = Density\n",
    "Particle_Volume = Volume\n",
    "Particle_Mass = Mass\n",
    "Particle_Radius = None\n",
    "Coordination_Number = None\n",
    "Particle_i_ID = Particle_ID_1\n",
    "Particle_j_ID = Particle_ID_2\n",
    "Force_ij = FORCE_CHAIN_FC\n",
    "Contact_ij = FORCE_CHAIN_CONTACT_POINT\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8df278d1",
   "metadata": {},
   "source": [
    "The `DEM_software` section specifies the DEM software used for the simulation. In this case, it is set to `mfix`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98c31351",
   "metadata": {},
   "source": [
    "```ini\n",
    "[DEM_software]\n",
    "software = mfix\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3fe7d338",
   "metadata": {},
   "source": [
    "The `grid_info` section specifies the grid parameters for the coarse graining process, including the grid dimensions, axes, and boundaries. \n",
    "\n",
    "- The `grid_dimension` is set to '2' for a 2D simulation.\n",
    "- The `grid_axes` are set to '`xy`', indicating that the coarse graining will be performed in the x and y directions.\n",
    "- The `automatic_grid` is set to `False`, allowing for manual specification of grid boundaries.\n",
    "- The `x_min`, `x_max`, `y_min`, and `y_max` parameters define the spatial extent of the grid.\n",
    "- The `z_transect` is set to '0.0', indicating that the coarse graining will be performed at this z-level.\n",
    "- The `x_axis_periodic` is set to '`True`', indicating that the x-axis is periodic, while the y and z axes are non-periodic.\n",
    "\n",
    "Find the corresponding documentation in the following page: `grid_generation`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08dc2c95",
   "metadata": {},
   "source": [
    "```ini\n",
    "[grid_info]\n",
    "grid_dimension = 2\n",
    "grid_axes = xy\n",
    "automatic_grid = False\n",
    "x_min = 0.00105\n",
    "x_max = 0.5\n",
    "y_min = 0.001\n",
    "y_max = 0.24\n",
    "z_min = None\n",
    "z_max = None\n",
    "x_transect = None\n",
    "y_transect = None\n",
    "z_transect = 0.0\n",
    "x_axis_periodic = True\n",
    "y_axis_periodic = False\n",
    "z_axis_periodic = False\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79b3c36b",
   "metadata": {},
   "source": [
    "The `simulation_box` section specifies the limits of the DEM simulation box, required on every periodic axis in `[grid_info]`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "237b9e0d",
   "metadata": {},
   "source": [
    "```ini\n",
    "[simulation_box]\n",
    "x_range = 0, 0.5\n",
    "y_range = None\n",
    "z_range = None\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb015fa7",
   "metadata": {},
   "source": [
    "The `fields_to_export` section specifies which coarse-grained fields to export. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b0be3cd",
   "metadata": {},
   "source": [
    "```ini\n",
    "[fields_to_export]\n",
    "volume_fraction = True\n",
    "density_particle = False\n",
    "density_mixture = True\n",
    "momentum_density = False\n",
    "velocity = True\n",
    "velocity_gradient = True\n",
    "kinetic_tensor = False\n",
    "contact_tensor = False\n",
    "total_stress_tensor = True\n",
    "pressure = True\n",
    "granular_temperature = True\n",
    "granular_temperature_slices = True\n",
    "fabric_tensor = True\n",
    "inertial_number = True\n",
    "coordination_number = False\n",
    "d43 = False\n",
    "d32 = False\n",
    "frictional_coefficient = True\n",
    "shear_rate_tensor = False\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbd96e55",
   "metadata": {},
   "source": [
    "The `output_options` section defines the output formats for the coarse-grained data, including `vkthdf` and `h5` formats.\n",
    "Additionally, `time_average` defines whether time-averaged quantities will be exported into seperate files."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb593446",
   "metadata": {},
   "source": [
    "```ini\n",
    "[output_options]\n",
    "vkthdf_output = True\n",
    "h5_output = False\n",
    "time_average = True\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b930e97",
   "metadata": {},
   "source": [
    "## Run the coarse graining"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc30620f",
   "metadata": {},
   "source": [
    "We should initialize the configuration and the coarse graining object. You can either do it through the configuration file and the `load_config` function, \n",
    "or you can directly input the parameters (that you have entered in the configuration file) into the `CoarseGraining` class arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "62499fd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output path already exists: ./PysammosCG/\n"
     ]
    }
   ],
   "source": [
    "# Load the configuration from the ini file\n",
    "cfg = load_config(\"./config.ini\")  \n",
    "\n",
    "# Initialize the CoarseGraining class with the loaded configuration\n",
    "CG = CoarseGraining(\n",
    "    particle_path=cfg[\"particle_path\"],\n",
    "    contacts_path=cfg[\"contacts_path\"],\n",
    "    output_path=cfg[\"output_path\"],\n",
    "    start_timestep=cfg[\"start_timestep\"],\n",
    "    end_timestep=cfg[\"end_timestep\"],\n",
    "    dt_time_step=cfg[\"dt_time_step\"],\n",
    "    t_pad=cfg[\"t_pad\"],\n",
    "    DEM_keymap=cfg[\"DEM_keymap\"],\n",
    "    DEM_software=cfg[\"DEM_software\"],\n",
    "    grid_info=cfg[\"grid_info\"],\n",
    "    weight_function=cfg[\"weight_function\"],\n",
    "    fields_to_export=cfg[\"fields_to_export\"],\n",
    "    time_average=cfg[\"time_average\"],\n",
    "    ignore_phases=cfg[\"ignore_phases\"],\n",
    "    h5_output=cfg[\"h5_output\"],\n",
    "    vkthdf_output=cfg[\"vkthdf_output\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2478c30",
   "metadata": {},
   "source": [
    "If you use the `load_config` to load the configuration file entries, you can input the `CoarseGraining` arguments directly: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2d3ce807",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output path already exists: ./PysammosCG/\n"
     ]
    }
   ],
   "source": [
    "cfg = load_config(\"config.ini\")  \n",
    "CG = CoarseGraining(**cfg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47623c67",
   "metadata": {},
   "source": [
    "Next, we can perform the coarse graining on the simulation data. You can either do it with a single command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8eb217ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting coarse-graining process...\n",
      "Sampling data for the first time step to obtain particle properties and bounds ... \n",
      "XML-based PolyData detected.\n",
      "... initial particle data sampled\n",
      "... particle size statistics computed\n",
      "Ignoring phases. Using mean density and d50 as phase.\n",
      "... particle phases identified\n",
      "... coarse-graining resolution set: w/d =  0.75\n",
      "Generating Grid with Customised Grid Ranges\n",
      "Customised grid bounds: x = [0.00105, 0.5], y = [0.001, 0.24], z = [None, None], x_transect = None, y_transect = None, z_transect = 0.0\n",
      "... grid generated\n",
      "Processing time step 150 (1/3)...\n",
      "Loading data ... \n",
      "  Particle data loaded\n",
      "  Repeated pairs in contact data:  1142\n",
      "  Contact data loaded and mapped\n",
      "  Coordination number not required. Skipping its calculation.\n",
      "... data loaded\n",
      "Matching particles to grid points ...\n",
      "... particles assigned to grid nodes\n",
      "Computing weights ...\n",
      "  Using Lucy kernel with cutoff 0.024164815722222066 and search sampling factor 1000\n",
      "... weights computed\n",
      "Computing Coarse Graining fields...\n",
      "  volume fraction done\n",
      "  mixture density done\n",
      "  momentum density done\n",
      "  velocity done\n",
      "  velocity gradient done\n",
      "  kinetic tensor done\n",
      "  contact tensor done\n",
      "  d43 done\n",
      "  d32 done\n",
      "  frabric tensor done\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "... fields computed\n",
      "Writing results for timestep 150...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/exports/csce/datastore/geos/users/s1857688/Coarse_Graining/pysammos/pysammos/macroscopic_fields/gridded/derived_fields.py:216: RuntimeWarning: divide by zero encountered in divide\n",
      "  out[f\"frictional_coefficient_{s_name}_P{p_name}\"] = tau / out[f\"pressure_{p_name}\"]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_0150.vtkhdf\n",
      "... results written\n",
      "\n",
      "Processing time step 151 (2/3)...\n",
      "Loading data ... \n",
      "  Particle data loaded\n",
      "  Repeated pairs in contact data:  1140\n",
      "  Contact data loaded and mapped\n",
      "  Coordination number not required. Skipping its calculation.\n",
      "... data loaded\n",
      "Matching particles to grid points ...\n",
      "... particles assigned to grid nodes\n",
      "Computing weights ...\n",
      "  Using Lucy kernel with cutoff 0.024164815722222066 and search sampling factor 1000\n",
      "... weights computed\n",
      "Computing Coarse Graining fields...\n",
      "  volume fraction done\n",
      "  mixture density done\n",
      "  momentum density done\n",
      "  velocity done\n",
      "  velocity gradient done\n",
      "  kinetic tensor done\n",
      "  contact tensor done\n",
      "  d43 done\n",
      "  d32 done\n",
      "  frabric tensor done\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "... fields computed\n",
      "Writing results for timestep 151...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_0151.vtkhdf\n",
      "... results written\n",
      "\n",
      "Processing time step 152 (3/3)...\n",
      "Loading data ... \n",
      "  Particle data loaded\n",
      "  Repeated pairs in contact data:  1165\n",
      "  Contact data loaded and mapped\n",
      "  Coordination number not required. Skipping its calculation.\n",
      "... data loaded\n",
      "Matching particles to grid points ...\n",
      "... particles assigned to grid nodes\n",
      "Computing weights ...\n",
      "  Using Lucy kernel with cutoff 0.024164815722222066 and search sampling factor 1000\n",
      "... weights computed\n",
      "Computing Coarse Graining fields...\n",
      "  volume fraction done\n",
      "  mixture density done\n",
      "  momentum density done\n",
      "  velocity done\n",
      "  velocity gradient done\n",
      "  kinetic tensor done\n",
      "  contact tensor done\n",
      "  d43 done\n",
      "  d32 done\n",
      "  frabric tensor done\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "... fields computed\n",
      "Writing results for timestep 152...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_0152.vtkhdf\n",
      "... results written\n",
      "\n",
      "Writing time averages over 3 time steps (150 to 152) ...\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "Writing results for time_averaged...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse_time_averaged.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_time_averaged.vtkhdf\n",
      "Coarse-graining process completed, summary:\n",
      ">>> Number of grid points: 903\n",
      ">>> Total preparation time: 0.01 seconds\n",
      ">>> Average time per time step: 1.63 seconds\n",
      "       >> duration per time step: [4.6882545948028564, 0.10654568672180176, 0.10777664184570312]\n",
      ">>> Number of cores used:  2\n"
     ]
    }
   ],
   "source": [
    "CG.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6cd724a",
   "metadata": {},
   "source": [
    "or running each step of the workflow separately: "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d7f9c41",
   "metadata": {},
   "source": [
    "### 1. Load the size-relevant particle data for the first time step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "84dc6ac3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sampling data for the first time step to obtain particle properties and bounds ... \n",
      "XML-based PolyData detected.\n"
     ]
    }
   ],
   "source": [
    "Bounds_t0, Diameter_t0, Density_t0, Mass_t0, GlobalID_t0 = CG.data_sampling()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "338bd569",
   "metadata": {},
   "source": [
    "### 2. Calculate the particle size range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d9410d4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">> Particle size statistics: \n",
      "       d43:  0.01651367411185649\n",
      "       dmax:  0.019993\n",
      "       d50:  0.016306963\n",
      "       d32:  0.016109877148148044\n",
      "       drms:  0.015422490500786803\n"
     ]
    }
   ],
   "source": [
    "\n",
    "CG.get_particle_size_statistics(Diameter_t0, Mass_t0)\n",
    "print(\">> Particle size statistics: \") \n",
    "print(\"       d43: \", CG.d43)\n",
    "print(\"       dmax: \", CG.dmax)\n",
    "print(\"       d50: \", CG.d50)\n",
    "print(\"       d32: \", CG.d32)\n",
    "print(\"       drms: \", CG.drms)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8853dcbd",
   "metadata": {},
   "source": [
    "### 3. Get the phases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4cdd254c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ignoring phases. Using mean density and d50 as phase.\n",
      ">> Phases: \n",
      "       Diameters:  [0.01610988]\n",
      "       Densities:  [2700.]\n"
     ]
    }
   ],
   "source": [
    "CG.get_particle_phases(Diameter_t0, Density_t0, GlobalID_t0, 8)\n",
    "print(\">> Phases: \")\n",
    "print(\"       Diameters: \", CG.phases[:,0])\n",
    "print(\"       Densities: \", CG.phases[:,1])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "965535f2",
   "metadata": {},
   "source": [
    "### 4. Calculate the CG grid spacing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f2d14442",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">> Coarse Graining resolution: \n",
      "       c: 0.024164815722222066\n",
      "       w: 0.012082407861111033\n"
     ]
    }
   ],
   "source": [
    "CG.set_resolution(CG.d32) # here you can input different number, to make w and c bigger or smaller \n",
    "print(\">> Coarse Graining resolution: \")\n",
    "print(\"       c:\", CG.c)\n",
    "print(\"       w:\", CG.w)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af76dc98",
   "metadata": {},
   "source": [
    "### 5. Generate the CG grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c18afc9a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating Grid with Customised Grid Ranges\n",
      "Customised grid bounds: x = [0.00105, 0.5], y = [0.001, 0.24], z = [None, None], x_transect = None, y_transect = None, z_transect = 0.0\n",
      ">> Grid: \n",
      "       Grid Points:  (903, 3) First Point:  [0.00105 0.001   0.     ]\n",
      "       Nodes:  [43 21  1]\n",
      "       Spacing:  [0.01187976 0.01195   ]\n"
     ]
    }
   ],
   "source": [
    "CG.generate_grid()\n",
    "print(\">> Grid: \")\n",
    "print(\"       Grid Points: \", CG.GridPoints.shape, \"First Point: \", CG.GridPoints[0])\n",
    "print(\"       Nodes: \", CG.Nodes)\n",
    "print(\"       Spacing: \", CG.Spacing)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2931fa0a",
   "metadata": {},
   "source": [
    "### 6. Calculate the CG fields"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a59d542a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " \n",
      "-------------------- Calculating Coarse Grained Fields --------------------\n",
      " \n",
      "---> Time step 0: time 0150 ................................................\n",
      "Loading data ... \n",
      "  Particle data loaded\n",
      "  Repeated pairs in contact data:  1142\n",
      "  Contact data loaded and mapped\n",
      "  Coordination number not required. Skipping its calculation.\n",
      "... data loaded\n",
      "Matching particles to grid points ...\n",
      "... particles assigned to grid nodes\n",
      "Computing weights ...\n",
      "  Using Lucy kernel with cutoff 0.024164815722222066 and search sampling factor 1000\n",
      "... weights computed\n",
      "Computing Coarse Graining fields...\n",
      "  volume fraction done\n",
      "  mixture density done\n",
      "  momentum density done\n",
      "  velocity done\n",
      "  velocity gradient done\n",
      "  kinetic tensor done\n",
      "  contact tensor done\n",
      "  d43 done\n",
      "  d32 done\n",
      "  frabric tensor done\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "... fields computed\n",
      "Writing results for timestep 150...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_0150.vtkhdf\n",
      "... results written\n",
      "... primary fields added to time average accumulator\n",
      "  File successfully updated to ./PysammosCG/CG_GranularTemperature_slices.h5\n",
      "  File successfully written to ./PysammosCG/CG_GranularTemperature_slices.h5\n",
      ">> time step 0 took 2.198777198791504 to run.\n",
      "  \n",
      "---> Time step 1: time 0151 ................................................\n",
      "Loading data ... \n",
      "  Particle data loaded\n",
      "  Repeated pairs in contact data:  1140\n",
      "  Contact data loaded and mapped\n",
      "  Coordination number not required. Skipping its calculation.\n",
      "... data loaded\n",
      "Matching particles to grid points ...\n",
      "... particles assigned to grid nodes\n",
      "Computing weights ...\n",
      "  Using Lucy kernel with cutoff 0.024164815722222066 and search sampling factor 1000\n",
      "... weights computed\n",
      "Computing Coarse Graining fields...\n",
      "  volume fraction done\n",
      "  mixture density done\n",
      "  momentum density done\n",
      "  velocity done\n",
      "  velocity gradient done\n",
      "  kinetic tensor done\n",
      "  contact tensor done\n",
      "  d43 done\n",
      "  d32 done\n",
      "  frabric tensor done\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "... fields computed\n",
      "Writing results for timestep 151...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_0151.vtkhdf\n",
      "... results written\n",
      "... primary fields added to time average accumulator\n",
      "  File successfully updated to ./PysammosCG/CG_GranularTemperature_slices.h5\n",
      "  File successfully written to ./PysammosCG/CG_GranularTemperature_slices.h5\n",
      ">> time step 1 took 0.5893969535827637 to run.\n",
      "  \n",
      "---> Time step 2: time 0152 ................................................\n",
      "Loading data ... \n",
      "  Particle data loaded\n",
      "  Repeated pairs in contact data:  1165\n",
      "  Contact data loaded and mapped\n",
      "  Coordination number not required. Skipping its calculation.\n",
      "... data loaded\n",
      "Matching particles to grid points ...\n",
      "... particles assigned to grid nodes\n",
      "Computing weights ...\n",
      "  Using Lucy kernel with cutoff 0.024164815722222066 and search sampling factor 1000\n",
      "... weights computed\n",
      "Computing Coarse Graining fields...\n",
      "  volume fraction done\n",
      "  mixture density done\n",
      "  momentum density done\n",
      "  velocity done\n",
      "  velocity gradient done\n",
      "  kinetic tensor done\n",
      "  contact tensor done\n",
      "  d43 done\n",
      "  d32 done\n",
      "  frabric tensor done\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "... fields computed\n",
      "Writing results for timestep 152...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_0152.vtkhdf\n",
      "... results written\n",
      "... primary fields added to time average accumulator\n",
      "  File successfully updated to ./PysammosCG/CG_GranularTemperature_slices.h5\n",
      "  File successfully written to ./PysammosCG/CG_GranularTemperature_slices.h5\n",
      ">> time step 2 took 0.6125955581665039 to run.\n",
      "  \n",
      "Writing time averages over 3 time steps (150 to 152) ...\n",
      "  particle density done\n",
      "  total stress done\n",
      "  pressure done\n",
      "  granular temp done\n",
      "  shear rate done\n",
      "  inertial number done\n",
      "  mu done\n",
      "Writing results for time_averaged...\n",
      "  File successfully updated to ./PysammosCG/CG_Lucy_Monodisperse_time_averaged.h5\n",
      "  Warning: VTKHDFWriter promoting 2D ImageData (nz=1) to thin 3D (nz=2) for VTK compatibility.\n",
      "  File successfully written to ./PysammosCG/CG_Lucy_Monodisperse_time_averaged.vtkhdf\n",
      "  File successfully updated to ./PysammosCG/CG_GranularTemperature_slices_time_averaged.h5\n"
     ]
    }
   ],
   "source": [
    "CG.fields_in_time()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f62526c6",
   "metadata": {},
   "source": [
    "## Plotting the Results in Python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20c8fb7e",
   "metadata": {},
   "source": [
    "After running the above code, the coarse-grained fields will be saved in the specified output directory.\n",
    "To visualize the results from the `.h5` files, you can use the provided Jupyter notebook `visualization_bedload_transport.ipynb` in the same directory."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de43741a",
   "metadata": {},
   "source": [
    "### 1. Initialize the H5XarrayManager to read the coarse-grained data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4b811f9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing key: density_mixture\n",
      "Processing key: fabric_tensor\n",
      "Processing key: frictional_coefficient_01_Pxy\n",
      "Processing key: frictional_coefficient_01_Pxyz\n",
      "Processing key: frictional_coefficient_01_Py\n",
      "Processing key: frictional_coefficient_Dxy_Pxy\n",
      "Processing key: frictional_coefficient_Dxy_Pxyz\n",
      "Processing key: frictional_coefficient_Dxy_Py\n",
      "Processing key: frictional_coefficient_Dxyz_Pxy\n",
      "Processing key: frictional_coefficient_Dxyz_Pxyz\n",
      "Processing key: frictional_coefficient_Dxyz_Py\n",
      "Processing key: granular_temperature_x\n",
      "Processing key: granular_temperature_xyz\n",
      "Processing key: granular_temperature_y\n",
      "Processing key: granular_temperature_z\n",
      "Processing key: inertial_number_Sxy_Pxy_d32\n",
      "Processing key: inertial_number_Sxy_Pxy_d43\n",
      "Processing key: inertial_number_Sxy_Pxyz_d32\n",
      "Processing key: inertial_number_Sxy_Pxyz_d43\n",
      "Processing key: inertial_number_Sxy_Py_d32\n",
      "Processing key: inertial_number_Sxy_Py_d43\n",
      "Processing key: positions\n",
      "Processing key: pressure_x\n",
      "Processing key: pressure_xy\n",
      "Processing key: pressure_xyz\n",
      "Processing key: pressure_y\n",
      "Processing key: pressure_z\n",
      "Processing key: time\n",
      "Processing key: total_stress_tensor_xy_dev\n",
      "Processing key: total_stress_tensor_xy_dev_mag\n",
      "Processing key: total_stress_tensor_xyz\n",
      "Processing key: total_stress_tensor_xyz_dev\n",
      "Processing key: total_stress_tensor_xyz_dev_mag\n",
      "Processing key: total_stress_tensor_xyz_mag\n",
      "Processing key: velocity\n",
      "Processing key: velocity_gradient\n",
      "Processing key: volume_fraction\n",
      "Processing key: density_mixture\n",
      "Processing key: fabric_tensor\n",
      "Processing key: frictional_coefficient_01_Pxy\n",
      "Processing key: frictional_coefficient_01_Pxyz\n",
      "Processing key: frictional_coefficient_01_Py\n",
      "Processing key: frictional_coefficient_Dxy_Pxy\n",
      "Processing key: frictional_coefficient_Dxy_Pxyz\n",
      "Processing key: frictional_coefficient_Dxy_Py\n",
      "Processing key: frictional_coefficient_Dxyz_Pxy\n",
      "Processing key: frictional_coefficient_Dxyz_Pxyz\n",
      "Processing key: frictional_coefficient_Dxyz_Py\n",
      "Processing key: granular_temperature_x\n",
      "Processing key: granular_temperature_xyz\n",
      "Processing key: granular_temperature_y\n",
      "Processing key: granular_temperature_z\n",
      "Processing key: inertial_number_Sxy_Pxy_d32\n",
      "Processing key: inertial_number_Sxy_Pxy_d43\n",
      "Processing key: inertial_number_Sxy_Pxyz_d32\n",
      "Processing key: inertial_number_Sxy_Pxyz_d43\n",
      "Processing key: inertial_number_Sxy_Py_d32\n",
      "Processing key: inertial_number_Sxy_Py_d43\n",
      "Processing key: positions\n",
      "Processing key: pressure_x\n",
      "Processing key: pressure_xy\n",
      "Processing key: pressure_xyz\n",
      "Processing key: pressure_y\n",
      "Processing key: pressure_z\n",
      "Processing key: time\n",
      "Processing key: total_stress_tensor_xy_dev\n",
      "Processing key: total_stress_tensor_xy_dev_mag\n",
      "Processing key: total_stress_tensor_xyz\n",
      "Processing key: total_stress_tensor_xyz_dev\n",
      "Processing key: total_stress_tensor_xyz_dev_mag\n",
      "Processing key: total_stress_tensor_xyz_mag\n",
      "Processing key: velocity\n",
      "Processing key: velocity_gradient\n",
      "Processing key: volume_fraction\n",
      "Processing key: granular_temperature_Kamrin\n",
      "Processing key: granular_temperature_LAMMPS\n",
      "Processing key: positions\n",
      "Processing key: time\n",
      "Processing key: granular_temperature_Kamrin\n",
      "Processing key: granular_temperature_LAMMPS\n",
      "Processing key: positions\n",
      "Processing key: time\n"
     ]
    }
   ],
   "source": [
    "# gridded data\n",
    "manager = H5XarrayManager(\"./PysammosCG/CG_Lucy_Monodisperse.h5\")\n",
    "bedload_CG = manager.h5_to_xarray()\n",
    "\n",
    "# time-averaged gridded data\n",
    "manager_avg = H5XarrayManager(\"./PysammosCG/CG_Lucy_Monodisperse_time_averaged.h5\")\n",
    "bedload_CG_avg = manager_avg.h5_to_xarray()\n",
    "\n",
    "# sliced granular temperature data\n",
    "manager_gt = H5XarrayManager(\"./PysammosCG/CG_GranularTemperature_slices.h5\")\n",
    "slices_gt = manager_gt.h5_to_xarray()\n",
    "\n",
    "# sliced granular temperature time averaged \n",
    "manager_gt_avg = H5XarrayManager(\"./PysammosCG/CG_GranularTemperature_slices_time_averaged.h5\")\n",
    "slices_gt_avg = manager_gt_avg.h5_to_xarray()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "450f6933",
   "metadata": {},
   "source": [
    "### 2. Plotting the mixture density field at a specific time step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "68a53dff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create figure and axis\n",
    "fig = plt.figure(figsize=(10,5))\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "# Plot DEM particle positions \n",
    "bedload_DEM = pv.read('../data_examples/bedload_transport/DEM_data/DES_FB1_0150.vtp')\n",
    "bedload_particles = bedload_DEM.points\n",
    "x_particle = bedload_particles[:, 0]; y_particle = bedload_particles[:, 1]\n",
    "ax.scatter(x_particle, y_particle, s=10, c='k', alpha=1, label='Particle Positions', zorder=3)\n",
    "\n",
    "# Plot the CG data\n",
    "x = np.asarray(bedload_CG.positions[:, 0]) \n",
    "y = np.asarray(bedload_CG.positions[:, 1])\n",
    "z = np.asarray(bedload_CG.positions[:, 2])\n",
    "var = np.asarray(bedload_CG.density_mixture.values[0, :])\n",
    "sc = ax.scatter(x, y, s=65, c=var, \n",
    "                cmap='viridis', alpha=0.6, label='CG Density', \n",
    "                zorder=1, marker='s')\n",
    "\n",
    "# Add colorbar and labels\n",
    "plt.colorbar(sc, ax=ax, label='Density')\n",
    "ax.set_xlabel('X Position')\n",
    "ax.set_ylabel('Y Position')\n",
    "ax.set_title(' Coarse-Grained Mixture Density')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09ca63f6",
   "metadata": {},
   "source": [
    "### 3. Plotting the granular temperature field at a specific time step"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e3fb51e",
   "metadata": {},
   "source": [
    "The vertical profiles of the coarse-grained fields can be plotted using the following code, which uses the subpackage `vertical_profiles`. Below we plot the profile of density_mixture of the first time step, after performing vertical intergration to obtain vertical profiles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "aa138680",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting integration along profile dimension: y\n",
      "Completed integration along profile dimension: y\n"
     ]
    },
    {
     "data": {
      "image/png": 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+5xtvvFHsj219lSeRGjBggE65SZMmCQDirbfe0jk+aNAg4ezsrL19+PBhAUB89dVXOuXu3LkjrKysxNSpU8uMNTExUTz55JPa+lQoFKJTp05i7ty5Ij09XadsSdexEELMnTtXmJmZFWsQ2LBhgwAgtm7dqj0GQFhZWekkePn5+aJRo0aifv36ZcZaVK3s2tMYN24cEhMTsWnTJgBAfn4+1qxZgy5duiAoKAgAsGXLFvTo0QPe3t7Iz8/X/tN0++3bt0/nnAMHDoRCoSh3TJGRkSgoKMAbb7xRZrmEhAS89tpr8PPzg7m5ORQKBfz9/QEAly5dKvfzP/HEE1AoFLCzs0NYWBg8PT2xbdu2YoPun332WZ3bu3fvho2NDZ577jmd45qm4127dpU7Jo3r16/j8uXL2nFLj/4++vXrh9jY2GLdL5Ud46N69OihM7jXw8MD7u7ues0q27FjB/Lz8zFy5Eid12lpaYlu3bppu1CuXLmCuLg4DBkyROfxderUQefOnUs8d2nX6G+//YbOnTvD1tZWe00tX75c7+tJ3/fKnj17YGdnh4EDB+o8vujg3Yoo/JwslJOTg127duGZZ56BtbV1sesmJycHR44c0Xl80diaN28O4L8u7vr168PJyQnvvfceli1bhosXL1Y45tdffx1AYTetxrfffovg4GB07dpV7/N069YN9erVw4oVK3Du3DkcO3as1G690nTu3BmfffYZFi1ahNdffx0vvfRShceMlqXo54m+139Zli1bhtatW8PS0lJ7Pe/atatCn48aEydOxLFjx3T+dejQoczHFH2NANC+fXts27YN77//Pvbu3Yvs7OwKx1ZRYWFhOrcbN24MAOjfv3+x4w8ePNB2723ZsgUymQwvvfSSzu/M09MTLVq0eOzvzMXFBQcOHMCxY8fw+eef4+mnn8bVq1cxbdo0BAcH6zVsZcuWLWjWrBlatmypE0Pv3r1LHKLRs2dPne82uVyOoUOH4vr16zpd9I9TKwebazz33HN48803sXLlSjz77LPYunUr4uPjMW/ePG2Z+Ph4bN68udTkqOgv18vLq0Ix3b9/HwDKHICuVqsRGhqKe/fuYcaMGQgODoaNjQ3UajWeeOKJCr0ZV61ahcaNG8Pc3BweHh4lvh5ra+tisz2SkpLg6elZbLyXu7s7zM3NkZSUVO6YNDRLUUyZMgVTpkwpsUxZb7bKiPFRLi4uxY4plUq9fj+a16oZU1OUZsyAJuaSZpd6eHggKiqq2PGSfqd//PEHhgwZgueffx7vvvsuPD09YW5ujqVLl2LFihWPjVcTsz7vlaSkpBLj9fT01Ot59BEdHQ1vb2/t8+Xn52Px4sVYvHhxmbFpFP3daQbja353Dg4O2LdvHz777DN88MEHSE5OhpeXF1555RV8+OGH5fpjysPDA0OHDsX333+P999/HxcuXMCBAwfw/fffG3QemUyGMWPG4JtvvkFOTg4aNGiALl26GBzP8OHDMWPGDOTm5mrHQ5lK0WtS3+u/NAsWLMDkyZPx2muv4ZNPPoGrqyvkcjlmzJhhlETK19dXOylHXyW977755hv4+vpi/fr1mDdvHiwtLdG7d2988cUX2j/mK1vRGcoWFhZlHs/JyYGtrS3i4+MhhCh1pnvdunX1ev62bdtq61alUuG9997DwoULMX/+/McOOo+Pj8f169f1/r4u6TNHcywpKUnviWC1OpGysrLCiy++iB9//BGxsbFYsWIF7Ozs8Pzzz2vLuLq6onnz5vjss89KPIfmw1qjojNNNIMfY2Ji4OfnV2KZ8+fP48yZMwgPD8eoUaO0x69fv16h5wYK/8p43AdESa/RxcUFR48ehRBC5/6EhATk5+fD1dW1wrFpzjFt2jQMHjy4xDINGzYs9fGVEaOxaGLZsGGDtqWxJJov/JLWOytt8HZJv781a9YgMDAQ69ev17lfM+hX35j1ea+4uLjg33//1TteQ/3777+Ii4vTtqA4OTlBLpdjxIgRpbb0BgYGGvw8wcHBWLduHYQQOHv2LMLDwzF79mxYWVnh/fffL1fsEydOxOrVq/HXX39h+/btcHR0LNfM0dGjR+Ojjz7CsmXLSv19lKWgoADDhw+Hk5MTlEolxo0bh3/++Uf75fk4SqWyxGuntD9Wil6T+l7/pVmzZg26d++OpUuX6hxPT083+FzGUtL7zsbGBrNmzcKsWbMQHx+vbZ0aMGAALl++LEGU5efq6gqZTIYDBw6UOAu4PDODFQoFPv74YyxcuBDnz5/XKwYrK6tS//gr+hlf0meO5lhJfwiXplYnUkBh996yZcvwxRdfYOvWrRg9erTOVP6wsDBs3boV9erVg5OTU7meo+hfs2UJDQ2FXC7H0qVL0bFjxxLLaN6QRS9MQ/9yNaaePXvi119/xZ9//olnnnlGe3zVqlXa+yuqYcOGCAoKwpkzZzBnzpwqGaOhSrs2evfuDXNzc9y4caPELgGNhg0bwtPTE7/++iveeecd7fHo6GgcOnSoWKJfGs3Clo9+2MfFxRWbtaeJuaRrWd/3So8ePfDrr79i06ZNOl1oa9eu1SvWsjx48ACvvfYaFAoF3n77bQCFLag9evTAqVOn0Lx5c72TAX3JZDK0aNECCxcuRHh4OE6ePFlq2cd9FrRp0wadOnXCvHnzcP78ebz66qvlWr/Nx8cH7777Li5fvqzzx5a+Pv74Yxw4cAARERGwsbFB165d8e677+Lrr7/W67UEBATg7NmzOsd2795dbJZXafS9/ksjk8mKfT6ePXsWhw8f1vkD1ZDPZlPz8PDA6NGjcebMGSxatEi7rMyjMVpZWUkcZenCwsLw+eef4+7du8WGGugjNja2xFY7TQvio59lZX0GzZkzBy4uLnr9cbRr1y7Ex8drW9EKCgqwfv161KtXz6BliWp9ItW2bVs0b94cixYtghCi2DiA2bNnIzIyEp06dcJbb72Fhg0bIicnB7du3cLWrVuxbNmyx1Z4vXr1YGVlhZ9//hmNGzeGra0tvL29S/ySCwgIwAcffIBPPvkE2dnZePHFF+Hg4ICLFy8iMTERs2bNQqNGjVCvXj28//77EELA2dkZmzdvRmRkpFHrxhAjR47Ed999h1GjRuHWrVsIDg7GwYMHMWfOHPTr1w+9evUyyvN8//336Nu3L3r37o3Ro0fDx8cHDx48wKVLl3Dy5En89ttvksdoCM06R19//TVGjRoFhUKBhg0bIiAgALNnz8b06dNx8+ZN9OnTB05OToiPj8e///6r/UvWzMwMs2bNwvjx4/Hcc89h7NixSElJwaxZs+Dl5fXYLhCNsLAw/PHHH5gwYQKee+453LlzB5988gm8vLxw7dq1YjHv3bsXmzdvhpeXF+zs7NCwYUO93ysjR47EwoULMXLkSHz22WcICgrC1q1bsWPHDoPq7tq1azhy5AjUarV2Qc7ly5cjLS0Nq1atQtOmTbVlv/76azz55JPo0qULXn/9dQQEBCA9PR3Xr1/H5s2bsXv3boOee8uWLViyZAkGDRqEunXrQgiBP/74AykpKQgJCSn1cfp8FkycOBFDhw6FTCYrcZ07fX3++eflelxkZCTmzp2LGTNmaP+4mDt3LqZMmYLu3btr/wgp7dq1s7PDiBEjMGPGDHz00Ufo1q0bLl68iG+//RYODg56xaDv9V+asLAwfPLJJ/j444/RrVs3XLlyBbNnz0ZgYKDOUhx2dnbw9/fHX3/9hZ49e8LZ2Rmurq460+lNqUOHDggLC0Pz5s3h5OSES5cuYfXq1ejYsaP2D3pNPc+bNw99+/aFXC43yR8EFdW5c2e8+uqrGDNmDI4fP46uXbvCxsYGsbGxOHjwIIKDg7XjAEvSu3dv+Pr6YsCAAWjUqBHUajVOnz6Nr776Cra2tpg4caK2rKY1eP369ahbty4sLS0RHByMSZMm4ffff0fXrl3x9ttvo3nz5lCr1YiOjkZERAQmT56sM5bN1dUVTz31FGbMmAEbGxssWbIEly9fNnwJBIOGptdQmin+TZo0KfH++/fvi7feeksEBgYKhUIhnJ2dRZs2bcT06dNFRkaGEOK/2RxffPFFief45ZdfRKNGjYRCodCZJVLS8gdCCLFq1SrRrl07YWlpKWxtbUWrVq10ZvpcvHhRhISECDs7O+Hk5CSef/55ER0dXWwGSkWXPyhq1KhRwsbGpsT7kpKSxGuvvSa8vLyEubm58Pf3F9OmTSs2Vbcis/aEEOLMmTNiyJAhwt3dXSgUCuHp6SmeeuopsWzZsjJjN0aMJSlt1t4bb7xRrGzRmTJCCDFt2jTh7e0tzMzMir3eP//8U/To0UPY29sLpVIp/P39xXPPPSd27typc44ffvhB1K9fX1hYWIgGDRqIFStWiKefflpnxt3jrtHPP/9cBAQECKVSKRo3bix+/PHHEq/P06dPi86dOwtra2sBQGf2jD7vFSGEiImJEc8++6ywtbUVdnZ24tlnnxWHDh0yaNae5p+5ublwcXERHTt2FB988IG4detWiY+LiooSY8eOFT4+PkKhUAg3NzfRqVMn8emnnxY7d9EZgZq608R2+fJl8eKLL4p69eoJKysr4eDgINq3by/Cw8N1HlfS77u0zwKN3NxcoVQqRZ8+fcqsh0fp+/593Ky9e/fuCXd3d/HUU0/pzIBVq9ViwIABwtHRUeezpLRrNzc3V0ydOlX4+fkJKysr0a1bN3H69OlSZ+2VFre+139Rubm5YsqUKcLHx0dYWlqK1q1biz///FOMGjVKZyarEELs3LlTtGrVSiiVSgGgxBmpGo97DwlR+my4kmaZvv/++6Jt27bCyclJKJVKUbduXfH222+LxMREndfy8ssvCzc3NyGTyfT6PH80FkNn7RWNs7Tfkeaz4f79+zrHV6xYITp06CBsbGyElZWVqFevnhg5cqQ4fvx4mbGuX79eDBs2TAQFBQlbW1uhUChEnTp1xIgRI3SWFBFCiFu3bonQ0FBhZ2enXbJBIyMjQ3z44YeiYcOGwsLCQrvsydtvv60zQ0/zGb1kyRJRr149oVAoRKNGjcTPP/9cZpwlkT08IRHVICkpKWjQoAEGDRqEH374QepwyACbN2/GwIED8ffff6Nfv35Sh0NUI8lkMrzxxhv49ttvK3yuWt+1R1TdxcXF4bPPPkOPHj3g4uKC27dvY+HChUhPT9dpDqeq7eLFi7h9+7Z2hXnNshFEVLUxkSKq5pRKJW7duoUJEybgwYMHsLa2xhNPPIFly5bpjBOiqm3ChAn4559/0Lp1a+0WPERU9bFrj4iIiKicavXK5kREREQVwUSKiIiIqJyYSBERERGVEweb60mtVuPevXuws7PjIFAiIqJqQgiB9PR0eHt7671IsSGYSOnp3r17pe59R0RERFXbnTt3DNr6RV9MpPRkZ2cHoPAXYW9vX+HzqVQqREREIDQ0tFw7xVP5se6lwXqXButdOqx7aRSt97S0NPj5+Wm/x42NiZSeNN159vb2RkukrK2tYW9vzzdYJWPdS4P1Lg3Wu3RY99Iord5NNSyHg82JiIiIyomJFBEREVE5MZEiIiIiKieOkSIiqgQFBQVQqVSV/rwqlQrm5ubIyclBQUFBpT9/bca6rxwKhQJyuVyy52ciRURkQkIIxMXFISUlRbLn9/T0xJ07d7gGXiVj3VceR0dHeHp6SlLPTKSIiExIk0S5u7vD2tq60j/o1Wo1MjIyYGtra5LFCKl0rHvTE0IgKysLCQkJAAAvL69Kj4GJFBGRiRQUFGiTKBcXF0liUKvVyMvLg6WlJb/MKxnrvnJYWVkBABISEuDu7l7pz8/fLBGRiWjGRFlbW0scCVHNpnmPSTEOkYkUEZGJcXwMkWlJ+R5jIkVERERUTkykiIioShs9ejQGDRokdRhVJo7aSiaT4c8//5Q6jGKYSBERUTGjR4+GTCaDTCaDQqGAh4cHQkJCsGLFCqjV6kqN5euvv0Z4eLj2dvfu3TFp0qQKn3fmzJmQyWTo06dPsfvmz58PmUyG7t27lxrH48yaNQtdunSpcJwVdf36dYwdOxZ16tSBUqmEj48PevbsiZ9//hn5+flSh1ftMZEigwkhkJyZByGE1KEQkQn16dMHsbGxuHXrFrZt24YePXpg4sSJCAsLq9QvYAcHBzg6Oprk3F5eXtizZw9iYmJ0jq9cuRJ16tSptDjKIoQod33/+++/aN26NS5duoTvvvsO58+fx5YtWzB27FgsW7YMFy5cMHK0hikoKKj0xNzYmEiRXoQQuHAvFfO2X0bXL/ag1SeRaPPpToxa8S++iriCyIvxiE/LkTpMIjIipVIJT09P+Pj4oHXr1vjggw/w119/Ydu2bTotM6mpqXj11Vfh7u4Oe3t7PPXUUzhz5oz2/pkzZ6Jly5ZYvXo1AgIC4ODggBdeeAHp6enaMhs2bEBwcDCsrKzg4uKCXr16ITMzE4Bul9ro0aOxb98+fP3119oWs6ioKNSvXx9ffvmlTvznz5+HmZkZbty4UeprdHd3R2hoKH766SftsUOHDiExMRH9+/fXKftoHPfv34enpyfmzJmjvf/o0aOwsLBAREQEwsPDMXv2bJw/fx5yuRwymQzh4eG4desWZDIZTp8+rX1cSkoKZDIZ9u7dCwDYu3cvZDIZduzYgbZt20KpVOLAgQMQQmD+/PmoW7curKys0KJFC2zYsKHU1yaEwOjRo9GgQQP8888/GDBgAIKCgtCqVSsMHz4cBw4cQPPmzbXl7969i6FDh8LJyQkuLi54+umncevWrWKv/8svv4SXlxdcXFzwxhtv6MyUy8vLw9SpU+Hj4wMbGxt06NBB+7oAIDw8HI6OjtiyZQuaNGkCpVKJ27dv49ixYwgJCYGrqyscHBzQrVs3nDx5stTXVpVwHSkq09X4dGw5cw9bzsbiZmKmzn0PMvOw7+p97Lt6X3vMw16JYB9HNPd1ePjPEc42FpUdNlGVJYRAtqrytgtRq9XIziuAeV4+bJSKCs9ueuqpp9CiRQv88ccfePnllyGEQP/+/eHs7IytW7fCwcEB33//PXr27ImrV6/C2dkZAHDjxg38+eef2LJlC5KTkzFkyBB8/vnn+OyzzxAbG4sXX3wR8+fPxzPPPIP09HRt4lDU119/jatXr6JZs2aYPXs2AMDNzQ1jx47FypUrMWXKFG3ZFStWoEuXLqhXr16Zr2ns2LGYOnUqpk+frn3c8OHDy3yMm5sbVqxYgUGDBiE0NBSNGjXCSy+9hAkTJiA0NBTZ2dk4d+4ctm7dil27dsHMzAwODg6Ij4/Xu66nTp2KL7/8EnXr1oWjoyM+/PBD/PHHH1i6dCmCgoKwf/9+vPTSS3Bzc0O3bt2KPf706dO4dOkSfvnll1LXsdJcD1lZWejRowe6dOmC/fv3w9zcHJ9++in69OmDs2fPwsKi8HN8z5492la869evY+jQoWjZsiVeeeUVAMCYMWNw69YtrFu3Dt7e3ti4cSP69OmDc+fOISgoSPtcc+fOxf/+9z+4uLjA3d0dUVFRGDVqFL755hsAwFdffYV+/frh2rVrsLOz07vOpMBEioqJSszEljP3sPnsPVyNz9AeV5qboUdDdwxo4Y0n67viVlImzsak4GxMKs7dTcXV+HTEp+UiPi0eOy/992Hh62SlTaqa+zigma8D7C0VUrw0IsllqwrQ5KMdkjz3xdm9YW1R8Y/9Ro0a4ezZswAKv1jPnTuHhIQEKJVKAMCXX36JP//8Exs2bMCrr74KoDChCw8P134pjhgxArt27dImUvn5+Rg8eDD8/f0BAMHBwSU+t4ODAywsLGBtbQ1PT0/t8TFjxuCjjz7Cv//+i/bt20OlUmHNmjX44osvHvt6wsLC8Nprr2H//v1o06YNfv31Vxw8eBArVqwo83H9+vXDK6+8guHDh6Ndu3awtLTE559/DqBwkUhbW1uYm5vD09OzXAtyzp49GyEhIQCAzMxMLFiwALt370bHjh0BAHXr1sXBgwfx/fffl5hIXb16FQDQsGFD7bGEhATUrVtXe3v+/PmYMGEC1q1bBzMzM/zvf//TJlcrV66Eo6Mj9u7di9DQUACAk5MTvv32W8jlcjRq1Aj9+/fHrl278Morr+DGjRv45ZdfEBMTA29vbwDAlClTsH37dqxcuVLbeqdSqbBkyRK0aNFCG8dTTz2lE/v3338PJycn7Nu3D2FhYQbXXWViIkUAgDsPsrDlbCy2nL2HC/fStMcVchm6NXBDWHNv9GriAVvlf5dMC2tHtPBz1N7OysvHxXtpOBOTinMPE6ybiZmISc5GTHI2tp6L05at62qDYE1y5euApt72RvmAJyLTE0Jov2xPnDiBjIyMYiu3Z2dn63SpBQQE6LQseHl5abf1aNGiBXr27Ing4GD07t0boaGheO655+Dk5KR3TF5eXujfvz9WrFiB9u3bY8uWLcjJycHzzz//2McqFAq89NJLWLlyJW7evIkGDRrodHmV5csvv0SzZs3w66+/4vjx47C0tNQ75sdp27at9ueLFy8iJydHm1hp5OXloVWrVmWe59FWSBcXF223Yvfu3ZGXlweg8Pd4/fr1Yq0/OTk5Or/Hpk2b6mwQ7OXlhXPnzgEATp48CSEEGjRooHOO3NxcnevDwsKiWP0mJCTgo48+wu7duxEfH4+CggJkZWUhOjq6zNdWFfCbqxaLTc3G32djsflsLM7cSdEel5vJ8GR9V4Q190JoU084WOnXemRtYY62Ac5oG+CsPZaWo8L5u6mFrVYxqTgTk4KY5GzcTMzEzcRM/HX6HgDATAYEudsh2NcBA1p4o1sDN6O+VqKqwkohx8XZvSvt+dRqNdLT0mFnbwcrhfzxD9DDpUuXEBgYqD2/l5eXzjgYjUcHZisUup8jMplMO8hYLpcjMjIShw4dQkREBBYvXozp06fj6NGj2ufRx8svv4wRI0Zg4cKFWLlyJYYOHar3qvJjx45Fhw4dcP78eYwdO1bv57x58ybu3bsHtVqN27dvPzYB07RMPdptWdpq3DY2NtqfNXX1999/w8fHR6ecpiWwKE1X2uXLl9GyZUsAhXVdv359AIC5+X8pgFqtRps2bfDzzz8XO4+b23+fx2X9HtVqNeRyOU6cOKGTbAGAra2t9mcrK6tiXcyjR4/G/fv3sWjRIvj7+0OpVKJjx47aRK8qYyJVyySk52DbuThsOXsPx24la4+byYAn6rogrLk3+jTzNNq4JntLBTrVc0Wneq7aYw8y83A2JgXnYlJx9m4qzsakID4tF1fi03ElPh2bTt/DsQ976Z3AEVUnMpmsUltf1Wo18i3ksLYwN8rqz7t378a5c+fw9ttvAwBat26NuLg4mJubIyAgoNznlclk6Ny5Mzp37oyPPvoI/v7+2LhxI955551iZS0sLFBQUHycWb9+/WBjY4OlS5di27Zt2L9/v97P37RpUzRt2hRnz57FsGHD9HpMXl4ehg8fjqFDh6JRo0YYN24czp07Bw8Pj1Lj1CQlsbGx2pakRweel0YzMDs6OrrEbryStGrVCo0aNcKXX36JIUOGlNm92Lp1a6xfv147YaA8WrVqhYKCAiQkJBi87MOBAwewZMkS9OvXDwBw584dJCYmliuOysZEqhZ4kJmHbedjseVMLI5GJUH9yPjN9gHOCGvhhT7NPOFuZ7wm6bI421ige0N3dG/43+aS8Wk5OBuTik+2XET0gyzsuZyAQa18yjgLEZlabm4u4uLiUFBQgPj4eGzfvh1z585FWFgYRo4cCQDo1asXOnbsiEGDBmHevHlo2LAh7t27h61bt2LQoEE63VOlOXr0KHbt2oXQ0FC4u7vj6NGjuH//Pho3blxi+YCAABw9ehS3bt2Cra0tnJ2dYWZmBrlcjtGjR2PatGmoX7++diyRvnbv3g2VSqX3EgfTp09HamoqvvnmG9ja2mLbtm0YN24ctmzZAgDw9/dHdHQ0Tp8+jTp16sDOzg5WVlZ44okn8PnnnyMgIACJiYn48MMPH/tcdnZ2mDJlCt5++22o1Wo8+eSTSEtLw6FDh2Bra4tRo0YVe4xMJsPKlSsREhKCzp07Y9q0aWjcuDFUKhX279+P+/fva1uOhg8fji+++AJPP/00Zs+eDV9fX0RHR+OPP/7Au+++C19f38fG2KBBAwwfPhwjR47EV199hVatWiExMRG7d+9GcHCwNkkqSf369bF69Wq0bdsWaWlpePfdd7WbEVd1ki5/sH//fgwYMADe3t7FVixVqVR47733EBwcDBsbG3h7e2PkyJG4d++ezjlyc3Px5ptvwtXVFTY2Nhg4cGCx9UCSk5MxYsQIODg4wMHBASNGjEBKSkolvEJpbTsXi5Er/kW7z3Zi+sbzOHyzMIlq6eeID/s3xuFpT+HX1zpiZMeASkuiSuNhb4mQJh4Y2KJwgOKOC3GPeQQRmdr27dvh5eWFgIAA9OnTB3v27ME333yDv/76S/sFLJPJsHXrVnTt2hVjx45FgwYN8MILL+DWrVvalpnHsbe3x/79+9GvXz80aNAAH374Ib766iv07du3xPJTpkyBXC5HkyZN4ObmpjOOZty4ccjLyzOoe07DxsZG7yRq7969WLRoEVavXg17e3uYmZlh9erVOHjwIJYuXQoAePbZZ9GzZ0/07NkTbm5u+OWXXwAUzgpUqVRo27YtJk6ciE8//VSv5/zkk0/w0UcfYe7cuWjcuDF69+6NzZs3l9n9+cQTT+DEiRNo2LAh3njjDTRp0gSdOnXCL7/8goULF+L1118HULjp7/79+1GnTh0MHjwYjRs3xtixY5GdnW1QC9XKlSsxcuRITJ48GQ0bNsTAgQNx9OhR+Pn5lfm4FStWIDk5Ga1atcKIESPw1ltvwd3dvczHVBUyIeGqitu2bcM///yD1q1b49lnn8XGjRu1a3SkpqbiueeewyuvvIIWLVogOTkZkyZNQn5+Po4fP649x+uvv47NmzcjPDwcLi4umDx5Mh48eKDTR9u3b1/ExMTghx9+AAC8+uqrCAgIwObNm/WONS0tDQ4ODkhNTS13s+ejVCoVtm7din79+hXrczaGW4mZ6P7lXu3tZj72CGvujf7BXvBzrro70Z+LScWAbw/CSiHHqY9CYGmkMR2PMnXdU8lqY73n5OQgKioKgYGBRh2EbAi1Wo20tDTtl31N988//6B79+6IiYnRO5EzldpW91J69L0ml8t1PmuM/f1dlKRde3379i31Lw4HBwdERkbqHFu8eDHat2+P6Oho1KlTB6mpqVi+fDlWr16NXr16AQDWrFkDPz8/7Ny5E71798alS5ewfft2HDlyBB06dAAA/Pjjj+jYsSOuXLmiMy20JrmeULhsgb+LNcLHtEegq81jHlE1NPOxh4+jFe6mZGP/1fsIber5+AcRUa2Xm5uLO3fuYMaMGRgyZIjkSRTVHtVqjFRqaipkMpm26fXEiRNQqVTa9S0AwNvbG82aNcOhQ4fQu3dvHD58GA4ODtokCihs6nRwcMChQ4dKTaRyc3ORm5urvZ2WVrgkgEqlKnWGhSE05zDGuUpyK7FwxeCGHrbwdbAw2fOYQq/GbvjpcDS2nY9FjwYuj3+AgUxd91Sy2ljvKpUKQgio1WrJtsHQdDpo4qipfv75Z7zyyito2bIlfvrppyrxWmtL3VcFarUaQgioVCptXVfWZ061SaRycnLw/vvvY9iwYdqmubi4OFhYWBRba8TDwwNxcXHaMiX1s7q7u2vLlGTu3LmYNWtWseMRERF6T6fVR9FWN2M5cMsMgBlUyXHYunWrSZ7DVOxTAcAcO87dRRdlNOQVn2hUIlPVPZWtNtW7ZjHGjIwMyadxP7odS000ePBgDB48WHtb88dvVVDT674qyMvLQ3Z2Nvbv36/dl1DzWZOVlWXS564WiZRKpcILL7wAtVqNJUuWPLb8o4vFAShxym/RMkVNmzZNZ9ptWloa/Pz8EBoaarQxUpGRkQgJCTHJeJHNP58CYu+ja5sm6NehzuMfUIUUqAXWzNuL5CwVXBt3QMe6xm2VMnXdU8lqY73n5OTgzp07sLW1lWyMlBAC6enpsLOzM8ryB6Q/1n3lycnJgZWVFbp27apdl0zzWWPqpLrKJ1IqlQpDhgxBVFQUdu/erZPEeHp6Ii8vD8nJyTqtUgkJCejUqZO2TEl7G92/f7/MPnSlUlniImcKhcKoXwLGPp9GTErhBsIBrnbV7ktLASCkiQd+PR6DXZcT0bWhacZJmaruqWy1qd4LCgq0G+tKNdhY080hZQy1Feu+8mjeZwqFQjvRTPNZY+rPmyr9m9UkUdeuXcPOnTuLbUHQpk0bKBQKna6C2NhYnD9/XptIdezYEampqfj333+1ZY4ePYrU1FRtmZpGCIGY5GwAgJ9z9ViHo6g+zQqTpx0X4qFWSzaxlKhCNB/gpu5aIKrtNO8xKf5Ik7RFKiMjA9evX9fejoqKwunTp+Hs7Axvb28899xzOHnyJLZs2YKCggLtmCZnZ2dYWFjAwcEB48aNw+TJk+Hi4gJnZ2dMmTIFwcHB2ll8jRs3Rp8+ffDKK6/g+++/B1C4/EFYWFiNnbGXkqVCRm5hH7GvU9Vd6qAsneq5wsZCjri0HJy9m4qWj+zpR1RdyOVyODo6aveUs7a2rvQuHrVajby8POTk5LBVpJKx7k1PCIGsrCwkJCTA0dERcrm80gf2S5pIHT9+HD169NDe1oxJGjVqFGbOnIlNmzYBgHaPII09e/age/fuAICFCxfC3NwcQ4YMQXZ2Nnr27Inw8HCdfX5+/vlnvPXWW9rZfQMHDsS3335rwlcmLU1rlJud0iTrMFUGS4Uc3Ru54++zsdhxIY6JFFVbnp6FrauaZKqyCSGQnZ1d4v5mZFqs+8rj6Oiofa9VNkkTqe7du6Os9UD1WSvU0tISixcvxuLFi0st4+zsjDVr1pQrxuroTnJhE6efU/Xs1tPo3dRTm0i916eR1OEQlYtMJoOXlxfc3d0lWfpBsx1I165da83YtKqCdV85Hh0XJYUqP9icDHfnwcNEqgqvYK6PHg3dYCE3w837mbiekI767nZSh0RUbnK5XJIPe7lcjvz8fFhaWvLLvJKx7msHdtrWQJoWKd9q3iJlZ6lAp/qFEwx2XCg+85KIiEhqTKRqoDsPHs7Yq6YDzR/V5+EWMdvPcxNjIiKqephI1UDaMVLVvGsPAHo18YCZDDh3NxV3U7KlDoeIiEgHE6kaRq1+ZA2pGtAi5WqrRFt/ZwBAxAW2ShERUdXCRKqGuZ+Ri7x8NcxkgJejNFtSGFto08IV6HcwkSIioiqGiVQNo5mx5+VgBYW8Zvx6ez8cJ/Vv1AM8yJR241ciIqJH1YxvWtL6b3xU9Z6x9yg/Z2s08bKHWgA7L3L2HhERVR1MpGqYmjRj71H/7b3H7j0iIqo6mEjVMDVlMc6iNN17B64navcRJCIikhoTqRqmJnbtAUADD1sEuFgjL1+NfVfuSx0OERERACZSNU5N7dqTyWTaVil27xERUVXBRKoGURWoEZv6MJGqYV17ABD6MJHaczkBufkFEkdDRETERKpGiUvNgVoAFuZmcLNVSh2O0bXyc4S7nRLpufk4dCNJ6nCIiIiYSNUkmoHmvk5WMDOTSRyN8ZmZybSLc3KVcyIiqgqYSNUg2oHmNWx81KM046QiL8ajQC0kjoaIiGo7JlI1iGagua9TzZqx96gn6rrA3tIciRl5OBmdLHU4RERUyzGRqkH+W/qg5rZIKeRm6Nn44d5759m9R0RE0mIiVYNoF+OswV17ANBbs4nxxTgIwe49IiKSDhOpGuROsmbpg5rbtQcAXRu4QWluhjsPsnExNk3qcIiIqBZjIlVD5KgKcD89F0DNb5GytjBHtwZuAIAdF7iJMRERSYeJVA0R83B8lK3SHI7WComjMT3N7D0ug0BERFJiIlVDPDpjTyareWtIFdWzsTvkZjJcjkvH7aRMqcMhIqJaiolUDVEbZuw9ytHaAk/UdQbAvfeIiEg6TKRqiNoyY+9R/21izHFSREQkDSZSNYSma6+mz9h7VGiTwkTqxO1kJKTlSBwNERHVRkykaojasD1MUZ4Olmjp5wgAiLjIVikiIqp8TKRqCG3XXi0ZI6XxX/cex0kREVHlYyJVA6Rmq5CWkw+gZu+zVxLNKueHbyQhNVslcTRERFTbMJGqATRrSLnYWMBGaS5xNJWrrpstgtxtka8W2HM5QepwiIiolmEiVQNo15CqZd16GuzeIyIiqTCRqgE0LVK1rVtPQ5NI7b1yHzmqAomjISKi2oSJVA1QG9eQelQzH3v4OFohW1WA/VfvSx0OERHVIkykaoA7ybVvDalHyWQyhD4cdM7FOYmIqDIxkaoBanuLFPBf996uy/HIL1BLHA0REdUWTKSqOSEEYrQtUrU3kWoX4AxnGwukZKnwb9QDqcMhIqJagolUNZeYkYdsVQFkMsDb0VLqcCQjN5OhV2N3AJy9R0RElYeJVDWn2RrG094SSnO5xNFI69FNjNVqIXE0RERUGzCRquY4Puo/neu7wsZCjri0HJy9myp1OEREVAswkarmNOOjfGvpjL1HWSrk6N6I3XtERFR5mEhVc2yR0sVVzomIqDIxkarmNGOkavOMvUf1aOgGC7kZbt7PxPWEdKnDISKiGo6JVDWn2WfPr5ZuD1OUnaUCneq7AODinEREZHpMpKqxArXAvRSuIVWUpntv+3l27xERkWlJmkjt378fAwYMgLe3N2QyGf7880+d+4UQmDlzJry9vWFlZYXu3bvjwoULOmVyc3Px5ptvwtXVFTY2Nhg4cCBiYmJ0yiQnJ2PEiBFwcHCAg4MDRowYgZSUFBO/OtOLS8tBvlpAIZfBw772riFVVEgTD8hkwLm7qbj7MNEkIiIyBUkTqczMTLRo0QLffvttiffPnz8fCxYswLfffotjx47B09MTISEhSE//b+zLpEmTsHHjRqxbtw4HDx5ERkYGwsLCUFBQoC0zbNgwnD59Gtu3b8f27dtx+vRpjBgxwuSvz9Q0A819HK0gN5NJHE3V4WqrRDt/ZwBABAedExGRCZlL+eR9+/ZF3759S7xPCIFFixZh+vTpGDx4MADgp59+goeHB9auXYvx48cjNTUVy5cvx+rVq9GrVy8AwJo1a+Dn54edO3eid+/euHTpErZv344jR46gQ4cOAIAff/wRHTt2xJUrV9CwYcPKebEmoJ2xx269YkKbeuDfWw+w40IcxnQOlDocIiKqoarsGKmoqCjExcUhNDRUe0ypVKJbt244dOgQAODEiRNQqVQ6Zby9vdGsWTNtmcOHD8PBwUGbRAHAE088AQcHB22Z6uqOZg0pDjQvRjNO6t+oB3iQmSdxNEREVFNJ2iJVlri4wi4ZDw8PneMeHh64ffu2toyFhQWcnJyKldE8Pi4uDu7u7sXO7+7uri1TktzcXOTm5mpvp6WlAQBUKhVUKlU5XpEuzTkqcq7oxAwAgLe90igx1SSedgo09rTDpbh07Dh/D8+19tHeZ4y6J8Ox3qXBepcO614aRevd1PVfZRMpDZlMd+yPEKLYsaKKlimp/OPOM3fuXMyaNavY8YiICFhbG68rLTIystyPPXtTDkCGxNtXsHXrZaPFVFMEKmS4BDnW7D0H67gzxe6vSN1T+bHepcF6lw7rXhqaes/KyjLp81TZRMrTs7BrJi4uDl5eXtrjCQkJ2lYqT09P5OXlITk5WadVKiEhAZ06ddKWiY8vvp7Q/fv3i7V2PWratGl45513tLfT0tLg5+eH0NBQ2NvbV+zFoTBDjoyMREhICBQKRbnOMefCPgC5COvRES39HCscU01TPz4dW789jGvp5ujasztslYWXuzHqngzHepcG6106rHtpFK13TY+SqVTZRCowMBCenp6IjIxEq1atAAB5eXnYt28f5s2bBwBo06YNFAoFIiMjMWTIEABAbGwszp8/j/nz5wMAOnbsiNTUVPz7779o3749AODo0aNITU3VJlslUSqVUCqVxY4rFAqjviHKe77c/AIkpBd2PQa62/NNWoImPk4IcLHGraQsHLqZgv7NvXTuN/bvkvTDepcG6106rHtpaOrd1HUvaSKVkZGB69eva29HRUXh9OnTcHZ2Rp06dTBp0iTMmTMHQUFBCAoKwpw5c2BtbY1hw4YBABwcHDBu3DhMnjwZLi4ucHZ2xpQpUxAcHKydxde4cWP06dMHr7zyCr7//nsAwKuvvoqwsLBqPWPvbnI2hACsFHK42FhIHU6VJJPJ0LupJ77ffxM7LsQVS6SIiIgqStJE6vjx4+jRo4f2tqYrbdSoUQgPD8fUqVORnZ2NCRMmIDk5GR06dEBERATs7Oy0j1m4cCHMzc0xZMgQZGdno2fPnggPD4dcLteW+fnnn/HWW29pZ/cNHDiw1LWrqgvNjD0/Z6vHjhmrzUIfJlJ7LicgN78ASnP54x9ERESkJ0kTqe7du0MIUer9MpkMM2fOxMyZM0stY2lpicWLF2Px4sWllnF2dsaaNWsqEmqVo11DyolrSJWllZ8j3O2USEjPxaEbSejRsPgMTiIiovKqsutIUdnuJHMxTn2YmckQ2rRwUgFXOSciImNjIlVNxTzgYpz60izOGXkxHgXq0ltAiYiIDMVEqppii5T+nqjrAntLcyRm5OFkdLLU4RARUQ3CRKqaitEMNucYqcdSyM3Qs3Fh9962c+zeIyIi46lQIpWTk2OsOMgAmbn52v3j/JzZtaePvs0Ku/e2nY+Fmt17RERkJAYnUmq1Gp988gl8fHxga2uLmzdvAgBmzJiB5cuXGz1AKk7TredorYCdJRd500fXBm6wVZojNjUHp2NSpQ6HiIhqCIMTqU8//RTh4eGYP38+LCz+WwgyODgY//vf/4waHJXszgN26xnKUiFHSJPC7r2t59m9R0RExmFwIrVq1Sr88MMPGD58uM6il82bN8fly9w4tzJo1pDijD3DhD1c2Xz7+Xiwd4+IiIzB4ETq7t27qF+/frHjarUaKpXKKEFR2Thjr3yeDHKFnaU54tNzEZUudTRERFQTGJxINW3aFAcOHCh2/LffftNuLkym9V/XHlukDKE0lyO0SeGg89NJnLBKREQVZ/AWMR9//DFGjBiBu3fvQq1W448//sCVK1ewatUqbNmyxRQxUhExD1ukfNkiZbCw5l74/WQMTifJUKAW4FB9IiKqCIP/LB8wYADWr1+PrVu3QiaT4aOPPsKlS5ewefNmhISEmCJGeoQQgvvsVUDn+q6wtzRHmkqG47e5OCcREVWMQS1S+fn5+OyzzzB27Fjs27fPVDFRGZKzVMjMKwDAweblYWFuhpAm7vj95D1sOx+PJxt4SB0SERFVYwa1SJmbm+OLL75AQUGBqeKhx9C0RrnbKWGpkD+mNJWk38PFObdf4N57RERUMQZ37fXq1Qt79+41QSikD87Yq7iOdZ1hbS6QlJmHo1FJUodDRETVmMGDzfv27Ytp06bh/PnzaNOmDWxsbHTuHzhwoNGCo+I4Y6/iFHIztHAWOJwgw99nY9GpnqvUIRERUTVlcCL1+uuvAwAWLFhQ7D6ZTMZuPxNji5RxtHQROJwAbD8fh1kDm8JczuUQiIjIcOXaa6+0f0yiTI8z9owjyEHAyVqBpMw8HLn5QOpwiIiomuKf4dXM3eTCrj1fZ3btVYRcBoQ+3Hvv73P3JI6GiIiqK4O79mbPnl3m/R999FG5g6GyqdUCMcncsNhY+jXzwPrjMdh+Pg6zn24GBbv3iIjIQAYnUhs3btS5rVKpEBUVBXNzc9SrV4+JlAklpOcir0ANuZkMXg6WUodT7bUPcIKLjQWSMvNw+EYSujZwkzokIiKqZgxOpE6dOlXsWFpaGkaPHo1nnnnGKEFRyTQDzb0dLTk42gjM5Wbo08wTPx+Nxt9nY5lIERGRwYzybWxvb4/Zs2djxowZxjgdlUIz0NzXkd16xhLW3BsAsP1CHFQFaomjISKi6sZozRopKSlITU011umoBNo1pDjQ3GjaBzrD1VaJ1GwV/rmeKHU4RERUzRjctffNN9/o3BZCIDY2FqtXr0afPn2MFhgVp11DigPNjUZuJkO/YE+sOnwbf5+NRfeG7lKHRERE1YjBidTChQt1bpuZmcHNzQ2jRo3CtGnTjBYYFaddQ4qLcRpV/2AvrDp8GzsuxOGzZ4JhYc7xZ0REpB+DE6moqChTxEF60C59wK49o2ob4Ax3OyUS0nNx8Pp9PNXIQ+qQiIiomjD4T++xY8ciPT292PHMzEyMHTvWKEFRcaoCNWJTuYaUKRR273kBALacjZU4GiIiqk4MTqR++uknZGdnFzuenZ2NVatWGSUoKu5eSjbUAlCam8HNTil1ODVO/+aFiVTkhXjk5nOrIyIi0o/eXXtpaWkQQkAIgfT0dFha/rcgZEFBAbZu3Qp3dw7UNRXNjD1fJyvIZDKJo6l52tRxgqe9JeLScnDgaiJ6NWH3HhERPZ7eiZSjoyNkMhlkMhkaNGhQ7H6ZTIZZs2YZNTj6j3bGHgeam4TZw+69Ff9E4e9zsUykiIhIL3onUnv27IEQAk899RR+//13ODs7a++zsLCAv78/vL29TRIkPTJjj+OjTKZ/88JEKvJiPHJUBbBUyKUOiYiIqji9E6lu3boBKJy15+fnBzMzThGvTHc4Y8/kWvk5wtvBEvdSc7Dv6n30buopdUhERFTFGZwN/e9//4MQotjx1NRUvPjii0YJioqL4WKcJmf2yOy9vzl7j4iI9GBwIrVq1Sp07twZN27c0B7bu3cvgoODcevWLWPGRo/4b3sYJlKmpJm9t/NSYfceERFRWQxOpM6ePYuAgAC0bNkSP/74I959912EhoZi9OjROHjwoClirPWy8wqQmJELgC1SptbSzxE+jlbIyivA3isJUodDRERVnMErmzs4OGDdunWYPn06xo8fD3Nzc2zbtg09e/Y0RXyE/7r17CzN4WCtkDiamk0mk6F/cy/8sP8mtpyNRZ9mXlKHREREVVi5RowvXrwYCxcuxIsvvoi6devirbfewpkzZ4wdGz2kWfrAl61RlaL/w3FSuy4lIDuP3XtERFQ6gxOpvn37YtasWVi1ahV+/vlnnDp1Cl27dsUTTzyB+fPnmyLGWk87PsqJM/YqQ3NfB/g5WyFbVYA97N4jIqIyGJxI5efn4+zZs3juuecAAFZWVli6dCk2bNiAhQsXGj1AemQNKQ40rxQymQz9gwvXROPsPSIiKovBiVRkZGSJC2/2798f586dM0pQpEu7qjlbpCpN2MPZe7suxyMzN1/iaIiIqKoy6qqarq6uxjwdPcSlDypfU297+LtYI0elxu7L7N4jIqKS6ZVIOTs7IzExEQDg5OQEZ2fnUv+R8XGfvcpX2L3HxTmJiKhsei1/sHDhQtjZ2QEAFi1aZMp4qIjULBXScwq7lnzZtVep+jf3wpK9N7DnSgIycvNhqzR4tRAiIqrh9PpmGDVqVIk/k+lpWqNcbS1gbcEv8srUxMsega42iErMxK5L8Xi6pY/UIRERURVTpXcezs/Px4cffojAwEBYWVmhbt26mD17NtRqtbaMEAIzZ86Et7c3rKys0L17d1y4cEHnPLm5uXjzzTfh6uoKGxsbDBw4EDExMZX9cspFM2OPa0hVPnbvERHR4+idSMnlcr3+GdO8efOwbNkyfPvtt7h06RLmz5+PL774AosXL9aWmT9/PhYsWIBvv/0Wx44dg6enJ0JCQpCenq4tM2nSJGzcuBHr1q3DwYMHkZGRgbCwMBQUVP3FFjk+SlphLQoTqb1X7yM9RyVxNEREVNXo3VckhIC/vz9GjRqFVq1amTImrcOHD+Ppp59G//79AQABAQH45ZdfcPz4cW1MixYtwvTp0zF48GAAwE8//QQPDw+sXbsW48ePR2pqKpYvX47Vq1ejV69eAIA1a9bAz88PO3fuRO/evSvltZQXF+OUVkMPO9Rzs8GN+5nYeSkez7TylTokIiKqQvROpI4ePYoVK1bg66+/RmBgIMaOHYvhw4fDycnJZME9+eSTWLZsGa5evYoGDRrgzJkzOHjwoHbAe1RUFOLi4hAaGqp9jFKpRLdu3XDo0CGMHz8eJ06cgEql0inj7e2NZs2a4dChQ6UmUrm5ucjNzdXeTktLAwCoVCqoVBVvmdCc43Hnin6QWRizg9Ioz0v6171G36Ye+HbvTWw+fQ9hzTxMGVqNZmi9k3Gw3qXDupdG0Xo3df3rnUi1a9cO7dq1w8KFC7FhwwasXLkS7733HgYMGIBx48YhJCTE6MG99957SE1NRaNGjSCXy1FQUIDPPvsML774IgAgLi4OAODhofvl5uHhgdu3b2vLWFhYFEv4PDw8tI8vydy5czFr1qxixyMiImBtbbxutsjIyDLvv3xHDkCGe1fPYWvCWaM9Lz2+7jVsswDAHPuuJmDDpq2w5pj/CtG33sm4WO/SYd1LQ1PvWVlZJn0eg78SLC0t8dJLL+Gll15CVFQUxo0bhz59+uD+/ftGX0dq/fr1WLNmDdauXYumTZvi9OnTmDRpEry9vXVmD8pkMp3HCSGKHSvqcWWmTZuGd955R3s7LS0Nfn5+CA0Nhb29fTlf0X9UKhUiIyMREhIChUJRaozvHd8FQI3BfbrBn+OkjEKfui9qw71/cP1+JuR+LdGvVfGV/enxylPvVHGsd+mw7qVRtN41PUqmUq6/rWNiYhAeHo7w8HBkZ2fj3XffNUpyUdS7776L999/Hy+88AIAIDg4GLdv38bcuXMxatQoeHp6AihsdfLy8tI+LiEhQdtK5enpiby8PCQnJ+u0SiUkJKBTp06lPrdSqYRSqSx2XKFQGPUNUdb5EtJzkKNSw0wG1HGxg8K8Sk+yrHYM+V2GtfDGop3XsP1iAoa09zdxZDWbsd9DpB/Wu3RY99LQ1Lup617vb+a8vDysX78eoaGhCAoKwsmTJ7Fo0SLcuXMHn3/+OczNjd/fkZWVBTMz3RDlcrl2+YPAwEB4enrqNJvm5eVh37592iSpTZs2UCgUOmViY2Nx/vz5MhOpqkAz0NzT3hIWTKIkpdl778C1+0jN4ngHIiIqpHf24+XlBTs7O4waNQpLliyBu7s7ACAjI0OnnDFbpgYMGIDPPvsMderUQdOmTXHq1CksWLAAY8eOBVDYpTdp0iTMmTMHQUFBCAoKwpw5c2BtbY1hw4YBABwcHDBu3DhMnjwZLi4ucHZ2xpQpUxAcHKydxVdVxTxc+sCXXXqSq+9uh0aedrgcl46Ii3F4vq2f1CEREVEVoHcilZycjOTkZHzyySf49NNPi92vGXNkzLWZFi9ejBkzZmDChAlISEiAt7c3xo8fj48++khbZurUqcjOzsaECROQnJyMDh06ICIiQrulDVC4xY25uTmGDBmC7Oxs9OzZE+Hh4UZf98rYNItx+nExziqhf7AXLsel4+9zsUykiIgIgAGJ1J49e0wZR4ns7OywaNGiMvf3k8lkmDlzJmbOnFlqGUtLSyxevFhnIc/qQLuGlDPXkKoK+jX3wleRV3HwWiKSM/PgZGMhdUhERCQxvROpbt26mTIOKoF2VXO2SFUJ9dxs0djLHpdi0xBxMQ5D29WROiQiIpIYRzBXYdwepurRDDrfwr33iIgITKSqrPwCNe6l5ABg115V0u/hJsaHbiThQWaexNEQEZHUmEhVUbGpOShQC1jIzeBhZyl1OPRQoKsNmnrbo0AtsONC6SvjExFR7cBEqorSdOv5OFnBzKzsVdqpcvV/2L33N7v3iIhqPYNX0QwPD8eQIUOMut8cFRfzcMaerxO79aqasGBvzN9+BYduJCIpIxcutsVXwKeqL79AjZuJmbh4Lw2X49KRlZePArWAWhQu56Lzsyj8Wa0WUIvCfwXqwvvUQqBAPPJzkXPYWSowvltddKrnKvVLJiITMDiRmjZtGt566y08//zzGDduXJVfHby6iuFA8yqrjos1mvs64GxMKrZfiMPwDtwypqpLy1Hhcmw6Lt5LxaXYdFyMTcOV+HTk5asr5fn3Xb2PAS28Mb1fY3g6sKueqCYxOJGKiYnB33//jfDwcPTo0QOBgYEYM2aMzt53VHF3kh+uIcWlD6qk/sFeOBuTii1nYplIPSSEwIV7aThyMwkKuRnc7JSF/2wL/7eohIEEQgjcTcnGxXtpDxOmVFyMTdOuyVaUjYUcjb3s0djLHk42FjCTAWYyGeRmMshkgFwmg5ns4c9mhT+byQCzR39+WMbM7JGfZTLIzQrXuTtw7T5+PhqNzWfuYfeleEzq1QCjOwdAIefICqKawOBESi6XY+DAgRg4cCASEhKwZs0ahIeHY8aMGejTpw/GjRuHAQMGFNsjjwyjXdWcM/aqpH7BXpi77TKORiUhIT0H7rV0QkB6jgoHryViz5UE7L1yHwnpuaWWtbaQw1omx6q7/8Ld3lInyXKzU8LdrvCYi62FXklGbn4BrsVn4FJsGi7Gpj1MntKQlpNfYnlvB0s08S5Mmpo8TJ7qOFubfAxi76aeGNq2Dmb8dR6n76Tgs62X8OvxO5j1dFN29xHVABXaadjd3R2dO3fGlStXcPXqVZw7dw6jR4+Go6MjVq5cie7duxspzNqHi3FWbX7O1mjh54gzd1Kw43wcRnQMkDqkSiGEwPWEDOy5koA9l+/j2K0HyFcL7f3WFnJ0rOsCC3Mz3E/Pxf2MXCSk5SJbVYCsvAJkQYbE6JTHPo+zjYVOkqVJugDgUlxh0nQ9IUPnuTXMzWQI8rBDYy87NPGyL0yePO0lXYk+2NcBf7zeCRtOxODz7ZdxLSEDw348yu6+CspRFSAuNQf3UrKRnKVCU297+LtYQybjBB2qPOVKpOLj47F69WqsXLkSN2/exKBBg7Blyxb06tUL2dnZ+PDDDzFq1Cjcvn3b2PHWCjmqAsSnFf5lzzFSVVdYsBfO3EnBlrOxNTqRys4rwKEbidrk6W6KbjdZXTcb9Gjojh4N3dEu0AlK8+J7WGbm5iM2ORObIveifrPWSM4uKEy0HiZbmp8TM3KRrxZ4kJmHB5l5uBKfXmZsDlaKhwmTw8PWJjvUd7ctMQapmZnJMKSdH0KbeuCriKtYc/S2trtvYq8gjOkcyO6+RxSoBRLSc3AvpTBRik3NfuTnwv+TSljLzcfRCh3ruaBTPRd0qufKJJVMzuBEasCAAdixYwcaNGiAV155BSNHjoSzs7P2fisrK0yePBkLFy40aqC1ieaLytpCDidrhcTRUGn6Bnvis62X8O+tB0hIy4G7fc35wL6dlIk9lxOw58p9HL6ZpDMo28LcDB3ruqBHQzd0b+iOAFebx57PRmkOfxdr1LMH+jbzhEJR8nWtVgukZKseSbJy/vs5PReqAoGGnnaF3XPe9vB2sKx2rQ+O1hb4ZFAzDG3nhxl/ncep6BTM2XoZvx2PqTXdfUIIJGepdJKiew8TpdiHx+LSCtfSexwrhRxejpawVZrjUmwa7qZkY8OJGGw4EQMAqOtqg471XNC5viueqOsCZ+6RSUZmcCLl7u6Offv2oWPHjqWW8fLyQlRUVIUCq82046Oc2ERdlfk6WaNVHUecik7BtvNxGNUpQOqQyi03vwDHopIftjol4GZips79Po5W6NHIDT0auqNTPVdYWZimxcfMTAZnGws421igoaedSZ6jqmjm44DfX+uEDSdj8Pm2mtndl5ajwvWEDFyPz8DV+HRcS8jAnQdZuJeajRzV42dMmpvJ4GFvCW9HS3g7WsHLwarwZwcreD3839Faof2czMrLx/FbyTh0IwmHbyTi3N1U3EzMxM3ETPx8NBoA0NjLHp3quaBzfRe0C3CGnSX/WKWKMTiR6tatG1q3bl3seF5eHtatW4eRI0dCJpPB358zmcpLO2OPA82rvLDm3jgVnYLfT8agjb8T/F2sq80H872UbOy9ch97riTgn+uJyMor0N5nbiZD2wAnPNWosMuuvrstk3oTMDOTYUhbP/Ru4omvIq9gzZHq2d2Xml2YMF17mCxdjU/H9YQMxKbmlPk4V1slvB0t4eVQmCh5O1gVJkwPkyQ3OyXkBkwGsLYwR9cGbujawE0b19GbSQ8TqyRciU/HpdjCSQnLD0ZBbiZDc18HbTdgG38nWCqqXrcwVW0GJ1JjxoxBnz594O7urnM8PT0dY8aMwciRI40WXG0V87BFypcDzau8fsGe+GTLRZyNSUXY4oMAABcbC/i7WCPA1QYBLjaFP7vYIMDVBg5WlZdkZecV4G5KNu6mZCMmOQt3k7MRk1x4+25yNuLSdL/k3OyU6NGwsNWpc5Ar7KtJQlgTOFgrMPvpZhjS1g8f/XUeJx929/16PAazBzZFp/pVo7svNUuFawm6ydLV+HTtmM6SeNgr0cCjcOxaAw87+LtYw8fRCp4OliYfy+ZgpUBoU0+ENi1cmud+ei4O3yxsrTp0Iwm3k7JwKjoFp6JT8N2eG7AwN0ObOk6FiVV9FzT3dawWiSxJy+BESghR4l+mMTExcHBwMEpQtd0dLsZZbXg5WOGjsCbYei4Wt5KykJiRi6TMPCRl5uFkCbPTnKwV8HexQUAJiZahs8rSc1SFSdKD7GIJ092UbCRmlL2pskwGtPJzLBwo3sgdTbzsuR2RxJr5OGDDw+6+edsu43pCBob97yjCmnvhw/5NKq27LyUrT5ssXYvP0CZMZS1v4eVgqU2WgtxtEeRhi/rudpX6x8PjuNkpMbCFNwa28AZQuPDx4RuFLVaHbiQiPu1honUzCV9FFq4z1j7QGX2aeeL5Nn58f1CJ9E6kWrVqBZlMBplMhp49e8Lc/L+HFhQUICoqCn369DFJkLWNZvFAP24PUy2MfTIQY58MBFCY3NxOysLtpCzcSsrErcRM7c8J6blIzlIhOSsFp++kFDuPg5UCAS7W2kTL38UGPk5WSMnKQ0yR1qSY5KxS10t6lK3SHD6OVvB1soKPk9XDn63h42SFQBcbOHAyQ5VTUnfflrOx2H05ARN7Fnb3WZiXv5VECIGULJU28dZcW5rrKyY5C+llXFveDpao72GHBg+TpaCHrU3VsQXT18kaz7e1xvNt/SCEwM3EzMKk6noiDt9MQkqWCnuu3MeeK/ex8dRdfPl8C/YUUDF6J1KDBg0CAJw+fRq9e/eGra2t9j4LCwsEBATg2WefNXqAtRFbpKovO0sFmvk4oJlP8dbZzNz8h0lWJm49/D/qYaIVl5aD1GwVzsSk4kxMqt7P52itKEySHK3g42itkzD5OVnD3sqcY5uqqZK6++Zuu4zfTpTd3SeEQGJGnjYpik7KwKGbZti4+iTupebgbnI2Mh8ZD1caH0erwkTJ3RZB7nYPW5hsq80YQEPJZDLUc7NFPTdbjHjCH2q1wKW4NOy5nIAle2/gyM0H6LPoAD4e0ATPtfHl+4q09E6kPv74YwBAQEAAhg4dCkvL6j+jpCpKz1EhJUsFgIlUTWOjNEcT78Jp+0Vl5xUg+kHWw8Tqv0Trbko2nKwt4ONkBV+dlqXCViVbZYXW1KVqQNPd9/vD2X2PdveFNPF4pCWpMHG6l1LSjDgzID5R54ibnVKntdLXyVrnGrO2qN3XlpmZDE29HdDU2wEDWnhj8q9ncPx2Mt7dcBYRF+Mxd3AwXLlhOaEcY6RGjRplijjoIU23npO1gl+StYiVhRwNPe1q/JR/Kh8zMxmeb+uH0CaeWBB5BasfdvdtORtbYnmZDPC0t4SPoxW8HSyRnXQX3do2Qx0XW/g6Fc6M4+w0/fm72GD9+I74Yf9NLIi8gsiL8Th5OxlzBgejd1PuMVvb6fVN7ezsjKtXr8LV1RVOTk5lNmk+ePDAaMHVRuzWI6LSOFgrMOvpZhjSzg+Ldl5DWrZKO+bNV9tqaQ1PB0vtOCqVSoWtW++gX1vfUhdCpceTm8nwevd66N7QDW+vP43LcekYv/oEnm3ti48HNqmWY8TIOPRKpBYuXAg7Ozvtz+wbNp0YzRpSHNBIRKVo6u2AH0e2lTqMWqmxlz3++r/OWLTzGr7fdwO/n4zBkZtJ+OL55rViVXoqTq9E6tHuvNGjR5sqFsJ/q5r7cjFOIqIqSWkux3t9GqFnI3e88+sZRD/IwrAfj2Js50BM7dOQ3aa1jMFzaE+ePIlz585pb//1118YNGgQPvjgA+Tllb1uDT1eTPJ/28MQEVHV1TbAGdsmdsGwDnUAACv+iUL/bw7gbEyKtIFRpTI4kRo/fjyuXr0KALh58yaGDh0Ka2tr/Pbbb5g6darRA6xttGtIcYwUEVGVZ6M0x5xngrFyTDu42ylx434mnllyCIt2XoWq4PH7CVL1Z3AidfXqVbRs2RIA8Ntvv6Fbt25Yu3YtwsPD8fvvvxs7vlpFCPHfYHMuxklEVG30aOiOHZO6on9zLxSoBRbtvIahP/6L+GypIyNTMziREkJArS7Msnfu3Il+/foBAPz8/JCYmFjWQ+kxHmTmaTeO9XZkIkVEVJ042Vjgu2Gt8c2LrWBvaY5zd9PwxRk5wg/fhlotpA6PTMTgRKpt27b49NNPsXr1auzbtw/9+/cHAERFRcHDw8PoAdYmdx7O2POwV3KwIhFRNTWwhTci3u6GJ+u7QCVk+GzrFby0/CjuprB5qiYyOJFatGgRTp48if/7v//D9OnTUb9+fQDAhg0b0KlTJ6MHWJtoZuxxoDkRUfXm6WCJFSNb4/nAAlgpzHDoRhL6LNyP30/EQAi2TtUkBi+d3bx5c51ZexpffPEF5HK2olQEF+MkIqo5ZDIZnvQUePXpjpj6xwWcik7B5N/OIOJiHOY8EwwXbjFTI5R7C/G8vDzExMQgOjoa0dHRSEhIQGxsydsVkH60M/Y40JyIqMYIcLHBb+M74t3eDaGQy7DjQjx6L9qPyIvxUodGRlCuWXtdunSBlZUV/P39ERgYiMDAQAQEBCAwMNAUMdYamjWkfNkiRURUo5jLzfBGj/r4843OaOhhh8SMPLyy6jh+OnRL6tCoggzu2hszZgzMzc2xZcsWeHl5cbsYI+IYKSKimq2ptwP++r/O+HzbZYQfuoXFu69haDs/TjCqxgxOpE6fPo0TJ06gUaNGpoin1ipQC+2MDj9uD0NEVGNZKuT4sH9jRFyIw73UHGw+cw/Pt/WTOiwqJ4O79po0acL1okwgPi0HqgIBczMZvByYSBER1WTmcjOM7BQAAFjxzy3O5KvGDE6k5s2bh6lTp2Lv3r1ISkpCWlqazj8qH023nrejFeRm7C4lIqrpXmjnByuFHJdi03Dk5gOpw6FyMrhrr1evXgCAnj176hwXQkAmk6GgoMA4kdUyMcns1iMiqk0crS3wbBsfrDkSjRX/RKFjPRepQ6JyMDiR2rNnjyniqPX+22OPA82JiGqL0Z0CseZINHZeikd0UhbquPA7oLoxOJHq1q2bKeKo9bRrSHHpAyKiWqO+uy26N3TD3iv3EX7oFj4a0ETqkMhA5VqQ88CBA3jppZfQqVMn3L17FwCwevVqHDx40KjB1SaaFilfLsZJRFSrjOlcuAbjr8fvID1HJXE0ZCiDE6nff/8dvXv3hpWVFU6ePInc3FwAQHp6OubMmWP0AGuLmAfcHoaIqDbqGuSK+u62yMjNx2/HY6QOhwxkcCL16aefYtmyZfjxxx+hUCi0xzt16oSTJ08aNbjaIi9fjdi0HABskSIiqm1kMhnGdA4AAIQfuoUCNZdCqE4MTqSuXLmCrl27Fjtub2+PlJQUY8RU69xLyYYQgKXCDG7cxJKIqNYZ3MoXDlYKRD/Iwq5L3IOvOjE4kfLy8sL169eLHT948CDq1q1rlKBqm//GR1lzyx0iolrIykKOYR3qAABW/BMlcTRkCIMTqfHjx2PixIk4evQoZDIZ7t27h59//hlTpkzBhAkTjB7g3bt38dJLL8HFxQXW1tZo2bIlTpw4ob1fCIGZM2fC29sbVlZW6N69Oy5cuKBzjtzcXLz55ptwdXWFjY0NBg4ciJiYqtMPrZ2xx249IqJaa2RHf8jNZDhy8wEu3EuVOhzSk8GJ1NSpUzFo0CD06NEDGRkZ6Nq1K15++WWMHz8e//d//2fU4JKTk9G5c2coFAps27YNFy9exFdffQVHR0dtmfnz52PBggX49ttvcezYMXh6eiIkJATp6enaMpMmTcLGjRuxbt06HDx4EBkZGQgLC6syi4dq15DiQHMiolrLy8EK/YK9AAAr/7klbTCkN4PXkQKAzz77DNOnT8fFixehVqvRpEkT2NraGjs2zJs3D35+fli5cqX2WEBAgPZnIQQWLVqE6dOnY/DgwQCAn376CR4eHli7di3Gjx+P1NRULF++HKtXr9auyr5mzRr4+flh586d6N27t9HjNpRmexguxklEVLuN7RyAzWfuYdPpe3ivTyO42XHcbFVXrkRKCIGsrCwEBgbCxcV0S9pv2rQJvXv3xvPPP499+/bBx8cHEyZMwCuvvAIAiIqKQlxcHEJDQ7WPUSqV6NatGw4dOoTx48fjxIkTUKlUOmW8vb3RrFkzHDp0qNREKjc3V7u0AwDtPoIqlQoqVcXX+dCcQ6VSIfpBJgDAy97CKOemsj1a91R5WO/SYL1Lpzx138zLFi39HHD6TipWH4rCm0/VM1V4NVbRejf1tW9QIhUXF4epU6di06ZN2q4ze3t7PPPMM5g7dy48PDyMGtzNmzexdOlSvPPOO/jggw/w77//4q233oJSqcTIkSMRFxcHAMWe18PDA7dv39bGbGFhAScnp2JlNI8vydy5czFr1qxixyMiImBtbbyWo8jISNyMkwOQ4fbFE9h622inpseIjIyUOoRaifUuDda7dAyt+xaWMpyGHCsOXod/1hWYl2vpbNLUe1ZWlkmfR+9EKi0tDZ06dUJGRgbGjBmDRo0aQQiBixcv4pdffsHBgwdx8uRJo3bxqdVqtG3bVrvQZ6tWrXDhwgUsXboUI0eO1JYrOtNNs4FyWR5XZtq0aXjnnXe0t9PS0uDn54fQ0FDY29uX5+XoUKlUiIyMRKduPZBx+AAA4IWwENhbKR7zSKooTd2HhITorIVGpsV6lwbrXTrlrfuQAjV2LDiAuLRc5Pu0wMBWPiaMsuYpWu+aHiVT0TuR+vrrryGXy3HhwgW4ubnp3Pfhhx+ic+fO+Oabb/DBBx8YLTgvLy80aaK771Djxo3x+++/AwA8PT0BFLY6eXl5acskJCRoW6k8PT2Rl5eH5ORknVaphIQEdOrUqdTnViqVUCqL900rFAqjfhglZOQDAOwtzeFizzFSlcnYv0vSD+tdGqx36Rha9woFMKpTIOZtv4yfDt/BkHb+XBqnHDT1burrXu8Gw7///hsffPBBsSQKANzd3TFt2jRs3rzZqMF17twZV65c0Tl29epV+Pv7AwACAwPh6emp02yal5eHffv2aZOkNm3aQKFQ6JSJjY3F+fPny0ykKktMSuGK5pyxR0REGi+294OlwgwXY9NwNOqB1OFQGfROpK5evVpm4tGpU6diSU9Fvf322zhy5AjmzJmD69evY+3atfjhhx/wxhtvACjs0ps0aRLmzJmDjRs34vz58xg9ejSsra0xbNgwAICDgwPGjRuHyZMnY9euXTh16hReeuklBAcHa2fxSSkmWbOGFBMpIiIq5GhtgcGtfQEAKw5ygc6qzKAxUo+u31SUo6Oj0fsh27Vrh40bN2LatGmYPXs2AgMDsWjRIgwfPlxbZurUqcjOzsaECROQnJyMDh06ICIiAnZ2dtoyCxcuhLm5OYYMGYLs7Gz07NkT4eHhkMvlRo23PLSJlDMX4yQiov+M6RSAtUejEXkpHtFJWajjwj+4qyK9EykhBMzMSm/AkslkEML4Gy2GhYUhLCyszOedOXMmZs6cWWoZS0tLLF68GIsXLzZ6fBX1XyLFNwgREf0nyMMOXRu4Yf/V+wg/dAsfDWjy+AdRpTMokWrQoEGpA95MkUTVBhZyM9hZmrNrj4iIihnbOQD7r97Hr8fv4O2QINhZcsJAVaN3IvXo6uJkPIuGNodCoWAiSkRExXQNckM9NxvcuJ+JDSdiMKZzoNQhURF6J1KjRo0yZRy1Hqe2EhFRUWZmMozpHIgP/zyP8EO3MLJjAORm/L6oSrheKhERURU2uLUPHKwUuJ2Uhd2XE6QOh4pgIkVERFSFWVuY48X2dQBwKYSqiIkUERFRFTeyoz/kZjIcvpmEi/dMu+UJGYaJFBERURXn7WiFvs0Kt0Vb+Q9bpaoSJlJERETVwNgnC2fs/XX6HhIzciWOhjT0mrX3zjvv6H3CBQsWlDsYIiIiKlnrOk5o6eeI03dS8PORaEzsFSR1SAQ9E6lTp07p3D5x4gQKCgrQsGFDAIX78MnlcrRp08b4ERIRERGAwlapt345hdVHbuO17nWhNJd+q7PaTq9Eas+ePdqfFyxYADs7O/z0009wcnICACQnJ2PMmDHo0qWLaaIkIiIi9G3mCU97S8Sl5WDLmVg828ZX6pBqPYPHSH311VeYO3euNokCACcnJ3z66af46quvjBocERER/UchN8OIjv4AgBX/RHFXjCrA4EQqLS0N8fHxxY4nJCQgPT3dKEERERFRyYa1rwOluRku3EvDv1EPpA6n1jM4kXrmmWcwZswYbNiwATExMYiJicGGDRswbtw4DB482BQxEhER0UNONhYY3LqwS28Fl0KQnMGJ1LJly9C/f3+89NJL8Pf3h7+/P4YPH46+fftiyZIlpoiRiIiIHjG2cwAAIOJiPKKTsqQNppYzOJGytrbGkiVLkJSUhFOnTuHkyZN48OABlixZAhsbG1PESERERI8I8rBDlyBXCAH8dPiW1OHUauVekDM2NhaxsbFo0KABbGxsOOCNiIioEmkW6Pz12B1k5OZLHE3tZXAilZSUhJ49e6JBgwbo168fYmNjAQAvv/wyJk+ebPQAiYiIqLhuQW6o62aD9Nx8bDh+R+pwai2DE6m3334bCoUC0dHRsLa21h4fOnQotm/fbtTgiIiIqGRmZjKM6VzYKrXy0C2o1ewZkoLBiVRERATmzZsHX1/dRcCCgoJw+/ZtowVGREREZXu2tQ/sLc1xOykLuy8nSB1OrWRwIpWZmanTEqWRmJgIpVJplKCIiIjo8awtzPFihzoAuBSCVAxOpLp27YpVq1Zpb8tkMqjVanzxxRfo0aOHUYMjIiKiso3sGAC5mQyHbiThUmya1OHUOnrttfeoL774At27d8fx48eRl5eHqVOn4sKFC3jw4AH++ecfU8RIREREpfBxtEKfZp74+2wsVv4ThfnPtZA6pFrF4BapJk2a4OzZs2jfvj1CQkKQmZmJwYMH49SpU6hXr54pYiQiIqIyaBbo/PP0PSRm5EobTC1jcItUdHQ0/Pz8MGvWrBLvq1OnjlECIyIiIv20ruOEFr4OOBOTirVHo/FWzyCpQ6o1DG6RCgwMxP3794sdT0pKQmBgoFGCIiIiIv3JZDLtAp2rj9xGbn6BxBHVHgYnUkIIyGSyYsczMjJgaWlplKCIiIjIMH2becHDXon76bn4+2ys1OHUGnp37b3zzjsACrPeGTNm6CyBUFBQgKNHj6Jly5ZGD5CIiIgez8LcDCM7BuCLHVew/GAUnmnlU2LDBxmX3onUqVOnABS2SJ07dw4WFhba+ywsLNCiRQtMmTLF+BESERGRXl5sXwff7LqGC/fScOFeGpr5OEgdUo2ndyK1Z88eAMCYMWPw9ddfw97e3mRBERERkeGcbSzQJcgNOy/F48C1RCZSlcDgMVIrV65kEkVERFRFdW3gCgA4cK34xDAyPoOXPwCAY8eO4bfffkN0dDTy8vJ07vvjjz+MEhgREREZrkuQGwDg+K1kZOXlw9qiXF/1pCeDW6TWrVuHzp074+LFi9i4cSNUKhUuXryI3bt3w8GBTYhERERSCnCxhq+TFfIK1Dh684HU4dR4BidSc+bMwcKFC7FlyxZYWFjg66+/xqVLlzBkyBAuxklERCQxmUymbZXaz+49kzM4kbpx4wb69+8PAFAqlcjMzIRMJsPbb7+NH374wegBEhERkWG6BmnGSSVKHEnNZ3Ai5ezsjPT0dACAj48Pzp8/DwBISUlBVlaWcaMjIiIig3Wq7wozGXA9IQP3UrKlDqdGMziR6tKlCyIjIwEAQ4YMwcSJE/HKK6/gxRdfRM+ePY0eIBERERnGwUqBln6OAICDbJUyKYOH8n/77bfIyckBAEybNg0KhQIHDx7E4MGDMWPGDKMHSERERIbrEuSGk9Ep2H/tPoa085M6nBrLoBap/Px8bN68GWZmhQ8zMzPD1KlTsWnTJixYsABOTk4mCZKIiIgMo1lP6uD1RBSohcTR1FwGJVLm5uZ4/fXXkZuba6p4iIiIyAha+DrCTmmOlCwVzt9NlTqcGsvgMVIdOnTQ7rtHREREVZO53Ayd6rsA4CrnpmTwGKkJEyZg8uTJiImJQZs2bWBjY6Nzf/PmzY0WHBEREZVflyA37LgQj/3XEvF/TwVJHU6NZHAiNXToUADAW2+9pT0mk8kghIBMJkNBQYHxoiMiIqJy69agcGHOk7eTkZGbD1slt4sxNoNrNCoqyhRxEBERkZH5OVsjwMUat5KycORGEno18ZA6pBrH4DFS/v7+Zf4zpblz50Imk2HSpEnaY0IIzJw5E97e3rCyskL37t1x4cIFncfl5ubizTffhKurK2xsbDBw4EDExMSYNFYiIqKqgNvFmJbBLVKbNm0q8bhMJoOlpSXq16+PwMDACgdW1LFjx/DDDz8UG4M1f/58LFiwAOHh4WjQoAE+/fRThISE4MqVK7CzswMATJo0CZs3b8a6devg4uKCyZMnIywsDCdOnIBcLjd6rERERFVFlyBXrD5ym9vFmIjBidSgQYO0Y6Ie9eg4qSeffBJ//vmn0daVysjIwPDhw/Hjjz/i008/1R4XQmDRokWYPn06Bg8eDAD46aef4OHhgbVr12L8+PFITU3F8uXLsXr1avTq1QsAsGbNGvj5+WHnzp3o3bu3UWIkIiKqijrWc4HcTIaoxEzceZAFP2drqUOqUQzu2ouMjES7du0QGRmJ1NRUpKamIjIyEu3bt8eWLVuwf/9+JCUlYcqUKUYL8o033kD//v21iZBGVFQU4uLiEBoaqj2mVCrRrVs3HDp0CABw4sQJqFQqnTLe3t5o1qyZtgwREVFNZWepQOs6jgC4ibEpGNwiNXHiRPzwww/o1KmT9ljPnj1haWmJV199FRcuXMCiRYswduxYowS4bt06nDx5EseOHSt2X1xcHADAw0N38JyHhwdu376tLWNhYVGsdczDw0P7+JLk5ubqLDyalpYGAFCpVFCpVOV7MY/QnMMY5yLDsO6lwXqXButdOlWp7jvVdcaxW8nYdyUez7f2kjockypa76auf4MTqRs3bsDe3r7YcXt7e9y8eRMAEBQUhMTEime9d+7cwcSJExEREQFLS8tSy8lkMp3bmi7GsjyuzNy5czFr1qxixyMiImBtbbxmUc0G0FT5WPfSYL1Lg/UunapQ9/J0ADDH/ivx2Pz3VsjL/oqsETT1npWVZdLnMTiRatOmDd59912sWrUKbm6FMwHu37+PqVOnol27dgCAa9euwdfXt8LBnThxAgkJCWjTpo32WEFBAfbv349vv/0WV65cAVDY6uTl9V+GnZCQoG2l8vT0RF5eHpKTk3VapRISEnRa1YqaNm0a3nnnHe3ttLQ0+Pn5ITQ0tMRE0lAqlQqRkZEICQmBQqGo8PlIf6x7abDepcF6l05VqvsCtcDyG3uQmp0P3+ad0MrPUdJ4TKlovWt6lEzF4ERq+fLlePrpp+Hr6ws/Pz/IZDJER0ejbt26+OuvvwAUDg6fMWNGhYPr2bMnzp07p3NszJgxaNSoEd577z3UrVsXnp6eiIyMRKtWrQAAeXl52LdvH+bNmwegMPFTKBSIjIzEkCFDAACxsbE4f/485s+fX+pzK5VKKJXKYscVCoVR3xDGPh/pj3UvDda7NFjv0qkKda8A8GR9N/x9LhaHbiajfV03SeOpDJp6N3XdG5xINWzYEJcuXcKOHTtw9epVCCHQqFEjhISEwMyscOz6oEGDjBKcnZ0dmjVrpnPMxsYGLi4u2uOTJk3CnDlzEBQUhKCgIMyZMwfW1tYYNmwYAMDBwQHjxo3D5MmT4eLiAmdnZ0yZMgXBwcHFBq8TERHVVF2CXPH3uVgcuJaISb0aSB1OjVGuteJlMhn69OmD7t27Q6lUPnY8kilNnToV2dnZmDBhApKTk9GhQwdERERo15ACgIULF8Lc3BxDhgxBdnY2evbsifDwcK4hRUREtcaTQa4AgNN3UpCarYKDFVsojcHg5Q/UajU++eQT+Pj4wNbWVrtlzIwZM7B8+XKjB1jU3r17sWjRIu1tmUyGmTNnIjY2Fjk5Odi3b1+xVixLS0ssXrwYSUlJyMrKwubNm+Hn52fyWImIiKoKXydr1HWzQYFa4PCNJKnDqTEMTqQ+/fRThIeHY/78+bCwsNAeDw4Oxv/+9z+jBkdERETG0/XhdjEHuF2M0RicSK1atQo//PADhg8frtM11rx5c1y+fNmowREREZHxdG1Q2L3HhTmNx+BE6u7du6hfv36x42q1ukosOkZEREQl6xDoAoVchugHWbidlCl1ODWCwYlU06ZNceDAgWLHf/vtN+0SBERERFT12CjN0ca/cE3F/VfZvWcMBs/a+/jjjzFixAjcvXsXarUaf/zxB65cuYJVq1Zhy5YtpoiRiIiIjKRLkBuO3HyA/dcSMaJjgNThVHsGt0gNGDAA69evx9atWyGTyfDRRx/h0qVL2Lx5M0JCQkwRIxERERmJZsD54RtJUBWoJY6m+ivXOlK9e/dG7969jR0LERERmVhTb3s421jgQWYeTt9JQbsAZ6lDqtYMbpGqW7cukpKKrz+RkpKCunXrGiUoIiIiMg0zMxmerP9w9h7HSVWYwYnUrVu3UFBQUOx4bm4u7t69a5SgiIiIyHS6PFzlfD+XQagwvbv2Nm3apP15x44dcHBw0N4uKCjArl27EBAQYNTgiIiIyPi6PBwndTYmBSlZeXC0tnjMI6g0eidSmo2IZTIZRo0apXOfQqFAQEAAvvrqK6MGR0RERMbn6WCJBh62uBqfgX+uJ6F/cy+pQ6q29E6k1OrCkf2BgYE4duwYXF1dTRYUERERmVaXIDdcjc/AgWv3mUhVgMFjpKKiophEERERVXOacVIHriVCCCFxNNVXuZY/2LVrF3bt2oWEhARtS5XGihUrjBIYERERmU6HQBdYmJvhbko2biZmop6brdQhVUsGt0jNmjULoaGh2LVrFxITE5GcnKzzj4iIiKo+Kws52j9cQ4rLIJSfwS1Sy5YtQ3h4OEaMGGGKeIiIiKiSdAlyxcHriThwLRGjOwdKHU61ZHCLVF5eHjp16mSKWIiIiKgSaZZBOHwzCXn53C6mPAxOpF5++WWsXbvWFLEQERFRJWrkaQdXWyWy8gpw4jaH55SHwV17OTk5+OGHH7Bz5040b94cCoVC5/4FCxYYLTgiIiIyHTMzGboEuWLjqbs4cO0+OtZzkTqkasfgROrs2bNo2bIlAOD8+fM698lkMqMERURERJXjv0QqEVP7SB1N9WNwIrVnzx5TxEFEREQSePLhelLn76UiKSMXLrZKiSOqXgweI0VEREQ1h7udJRp72UMI4J8bSVKHU+3o3SI1ePBgvcr98ccf5Q6GiIiIKl/XIFdcik3Dgav3MbCFt9ThVCt6J1IODg6mjIOIiIgk0iXIDd/vv6ndLoZjnvWndyK1cuVKU8ZBREREEmkb4ASluRni0nJwLSEDDTzspA6p2uAYKSIiolrOUiFHh7qFSx/s53YxBmEiRUREROj6cPbegWuJEkdSvTCRIiIiIu12MUejkpCjKpA4muqDiRQRERGhgYctPOyVyFGpuV2MAZhIEREREWQymbZVav81jpPSFxMpIiIiAlC4XQwAHLjKcVL6YiJFREREAIAn6xcmUhdj03A/PVfiaKoHJlJEREQEAHCxVaKZjz0A4OB1du/pg4kUERERaWnGSbF7Tz9MpIiIiEirq3bAeeF2MVQ2JlJERESk1drfEdYWciRm5OJyXLrU4VR5TKSIiIhIS2kuxxMPt4s5wGUQHouJFBEREenowu1i9MZEioiIiHT8t13MA2TncbuYsjCRIiIiIh313Gzg7WCJvHw1/r31QOpwqjQmUkRERKTj0e1iDlzlOKmyMJEiIiKiYro2eJhIcZxUmZhIERERUTGd67tAJgOuxKcjPi1H6nCqLCZSREREVIyjtQWa+zoCYKtUWZhIERERUYm6PlwGYT/HSZWqSidSc+fORbt27WBnZwd3d3cMGjQIV65c0SkjhMDMmTPh7e0NKysrdO/eHRcuXNApk5ubizfffBOurq6wsbHBwIEDERMTU5kvhYiIqNrRDDg/eD0RajW3iylJlU6k9u3bhzfeeANHjhxBZGQk8vPzERoaiszMTG2Z+fPnY8GCBfj2229x7NgxeHp6IiQkBOnp/y1rP2nSJGzcuBHr1q3DwYMHkZGRgbCwMBQUcG0MIiKi0rSq4wgbCzkeZObhYmya1OFUSeZSB1CW7du369xeuXIl3N3dceLECXTt2hVCCCxatAjTp0/H4MGDAQA//fQTPDw8sHbtWowfPx6pqalYvnw5Vq9ejV69egEA1qxZAz8/P+zcuRO9e/eu9NdFRERUHSjkZuhYzxU7L8Vj/7X7aObjIHVIVU6VTqSKSk1NBQA4OzsDAKKiohAXF4fQ0FBtGaVSiW7duuHQoUMYP348Tpw4AZVKpVPG29sbzZo1w6FDh0pNpHJzc5Gbm6u9nZZWmImrVCqoVKoKvxbNOYxxLjIM614arHdpsN6lU1Pq/sl6ToWJ1JUEvNLZX+pwHqtovZu6/qtNIiWEwDvvvIMnn3wSzZo1AwDExcUBADw8PHTKenh44Pbt29oyFhYWcHJyKlZG8/iSzJ07F7NmzSp2PCIiAtbW1hV6LY+KjIw02rnIMKx7abDepcF6l051r/v8bAAwx7FbD7Bx81Yo5VJHpB9NvWdlZZn0eapNIvV///d/OHv2LA4ePFjsPplMpnNbCFHsWFGPKzNt2jS888472ttpaWnw8/NDaGgo7O3tDYy+OJVKhcjISISEhEChUFT4fKQ/1r00WO/SYL1Lp6bUvRAC4bcPIiY5G04N26H7w4U6q6qi9a7pUTKVapFIvfnmm9i0aRP2798PX19f7XFPT08Aha1OXl5e2uMJCQnaVipPT0/k5eUhOTlZp1UqISEBnTp1KvU5lUollEplseMKhcKobwhjn4/0x7qXButdGqx36dSEuu/awA1rj0bjnxvJCGnqLXU4etHUu6nrvkrP2hNC4P/+7//wxx9/YPfu3QgMDNS5PzAwEJ6enjrNpnl5edi3b582SWrTpg0UCoVOmdjYWJw/f77MRIqIiIgKadaTOnCN60kVVaVbpN544w2sXbsWf/31F+zs7LRjmhwcHGBlZQWZTIZJkyZhzpw5CAoKQlBQEObMmQNra2sMGzZMW3bcuHGYPHkyXFxc4OzsjClTpiA4OFg7i4+IiIhK17GeK+RmMty4n4m7KdnwcbSSOqQqo0onUkuXLgUAdO/eXef4ypUrMXr0aADA1KlTkZ2djQkTJiA5ORkdOnRAREQE7OzstOUXLlwIc3NzDBkyBNnZ2ejZsyfCw8Mhl1eTEXNEREQScrBSoKWfI07cTsbBa/cxtF0dqUOqMqp0IiXE41dRlclkmDlzJmbOnFlqGUtLSyxevBiLFy82YnRERES1R5cgV5y4nYzIi/FMpB5RpcdIERERUdXQP9gLMhmw81ICztxJkTqcKoOJFBERET1WkIcdnmnlAwCYt/2yXr1GtQETKSIiItLLOyENYCE3w6EbSThwLVHqcKoEJlJERESkF18na4zoWLhNzLztl6FWs1WKiRQRERHp7Y0e9WGnNMeFe2nYci5W6nAkx0SKiIiI9OZsY4FXu9YFAHy54wry8tUSRyQtJlJERERkkHFdAuFqq0T0gyysOxYtdTiSYiJFREREBrG2MMfEXkEAgG92XUNmbr7EEUmHiRQREREZ7IV2fghwsUZiRh7+dyBK6nAkw0SKiIiIDKaQm2FyaEMAwA/7byApI1fiiKTBRIqIiIjKpX+wF5r52CMzrwDf7rkudTiSYCJFRERE5WJmJsP7fRoDANYcuY07D7IkjqjyMZEiIiKicnsyyBVP1neFqkBgQeRVqcOpdEykiIiIqELe69MIAPDn6bu4FJsmcTSVi4kUERERVUiwrwPCmntBCGD+9stSh1OpmEgRERFRhU0JbQhzMxn2XLmPIzeTpA6n0jCRIiIiogoLcLXBC+39AACfb7sMIWrHhsZMpIiIiMgo3uoZBCuFHKfvpGDHhXipw6kUTKSIiIjIKNztLPFyl0AAwPwdl5FfUPM3NGYiRUREREbzate6cLJW4Ob9TGw4ESN1OCbHRIqIiIiMxs5SgTd61AcALNp5DTmqAokjMi0mUkRERGRULz3hDx9HK8Sl5SD80C2pwzEpJlJERERkVJYKOd4JaQAAWLLnOlKzVBJHZDpMpIiIiMjoBrXyQUMPO6Tl5GPJvpq7oTETKSIiIjI6uZkMU/s0BACE/3MLsanZEkdkGkykiIiIyCSeauSOdgFOyM1XY1HkNanDMQkmUkRERGQSMpkM7/ct3ND4txN3cD0hXeKIjI+JFBEREZlMG39nhDTxgFoAX+y4InU4RsdEioiIiExqau+GMJMBOy7E48TtZKnDMSomUkRERGRSQR52eLa1LwBg3vaataExEykiIiIyubdDGsDC3Az/Rj3A3iv3pQ7HaJhIERERkcl5O1phdKcAAIWtUgXqmtEqxUSKiIiIKsWE7vVgZ2mOy3Hp+Ov0XanDMQomUkRERFQpHK0t8Hr3egCAryKuIje/+m9ozESKiIiIKs2YToHwsFfibko2fj4SLXU4FcZEioiIiCqNlYUcE3sWbmj87Z7rSM+p3hsaM5EiIiKiSjWkrS/qutrgQWYeftx/U+pwKoSJFBEREVUqc7kZ3u1duKHx/w5GISE9R+KIyo+JFBEREVW6Ps080cLPEVl5BVi867rU4ZQbEykiIiKqdDKZDO/1KWyV+uXfaNxKzJQ4ovJhIkVERESS6FTPFV0buCFfLfBV5FWpwykXJlJEREQkGU2r1OYz93D+bqrE0RiOiRQRERFJpqm3A55u6Q0XGwvEpla/QefmUgdAREREtduMsCawVMhhq6x+aUmtapFasmQJAgMDYWlpiTZt2uDAgQNSh0RERFTrudoqq2USBdSiRGr9+vWYNGkSpk+fjlOnTqFLly7o27cvoqOr//L0REREJI1ak0gtWLAA48aNw8svv4zGjRtj0aJF8PPzw9KlS6UOjYiIiKqp6tmOZqC8vDycOHEC77//vs7x0NBQHDp0qMTH5ObmIjc3V3s7LS0NAKBSqaBSVXxfIM05jHEuMgzrXhqsd2mw3qXDupdG0Xo3df3XikQqMTERBQUF8PDw0Dnu4eGBuLi4Eh8zd+5czJo1q9jxiIgIWFtbGy22yMhIo52LDMO6lwbrXRqsd+mw7qWhqfesrCyTPk+tSKQ0ZDKZzm0hRLFjGtOmTcM777yjvZ2WlgY/Pz+EhobC3t6+wrGoVCpERkYiJCQECoWiwucj/bHupcF6lwbrXTqse2kUrXdNj5Kp1IpEytXVFXK5vFjrU0JCQrFWKg2lUgmlUlnsuEKhMOobwtjnI/2x7qXBepcG6106rHtpaOrd1HVfKwabW1hYoE2bNsWaVyMjI9GpUyeJoiIiIqLqrla0SAHAO++8gxEjRqBt27bo2LEjfvjhB0RHR+O1116TOjQiIiKqpmpNIjV06FAkJSVh9uzZiI2NRbNmzbB161b4+/tLHRoRERFVU7UmkQKACRMmYMKECVKHQURERDVErRgjRURERGQKTKSIiIiIyomJFBEREVE51aoxUhUhhAAAoy3spVKpkJWVhbS0NK4vUslY99JgvUuD9S4d1r00ita75ntb8z1ubEyk9JSeng4A8PPzkzgSIiIiMlR6ejocHByMfl6ZMFWKVsOo1Wrcu3cPdnZ2pW4rYwjNljN37twxypYzpD/WvTRY79JgvUuHdS+NovUuhEB6ejq8vb1hZmb8EU1skdKTmZkZfH19jX5ee3t7vsEkwrqXButdGqx36bDupfFovZuiJUqDg82JiIiIyomJFBEREVE5MZGSiFKpxMcffwylUil1KLUO614arHdpsN6lw7qXRmXXOwebExEREZUTW6SIiIiIyomJFBEREVE5MZEiIiIiKicmUkRERETlxETKiJYsWYLAwEBYWlqiTZs2OHDgQJnl9+3bhzZt2sDS0hJ169bFsmXLipX5/fff0aRJEyiVSjRp0gQbN240VfjVlrHrPTw8HDKZrNi/nJwcU76MaseQeo+NjcWwYcPQsGFDmJmZYdKkSSWW4/WuH2PXPa95/RhS73/88QdCQkLg5uYGe3t7dOzYETt27ChWjtf84xm73o1+vQsyinXr1gmFQiF+/PFHcfHiRTFx4kRhY2Mjbt++XWL5mzdvCmtrazFx4kRx8eJF8eOPPwqFQiE2bNigLXPo0CEhl8vFnDlzxKVLl8ScOXOEubm5OHLkSGW9rCrPFPW+cuVKYW9vL2JjY3X+0X8MrfeoqCjx1ltviZ9++km0bNlSTJw4sVgZXu/6MUXd85p/PEPrfeLEiWLevHni33//FVevXhXTpk0TCoVCnDx5UluG1/zjmaLejX29M5Eykvbt24vXXntN51ijRo3E+++/X2L5qVOnikaNGukcGz9+vHjiiSe0t4cMGSL69OmjU6Z3797ihRdeMFLU1Z8p6n3lypXCwcHB6LHWJIbW+6O6detW4pc5r3f9mKLuec0/XkXqXaNJkyZi1qxZ2tu85h/PFPVu7OudXXtGkJeXhxMnTiA0NFTneGhoKA4dOlTiYw4fPlysfO/evXH8+HGoVKoyy5R2ztrGVPUOABkZGfD394evry/CwsJw6tQp47+Aaqo89a4PXu+PZ6q6B3jNl8UY9a5Wq5Geng5nZ2ftMV7zZTNVvQPGvd6ZSBlBYmIiCgoK4OHhoXPcw8MDcXFxJT4mLi6uxPL5+flITEwss0xp56xtTFXvjRo1Qnh4ODZt2oRffvkFlpaW6Ny5M65du2aaF1LNlKfe9cHr/fFMVfe85stmjHr/6quvkJmZiSFDhmiP8Zovm6nq3djXu3m5HkUlkslkOreFEMWOPa580eOGnrM2Mna9P/HEE3jiiSe093fu3BmtW7fG4sWL8c033xgr7GrPFNcmr3f9GLueeM3rp7z1/ssvv2DmzJn466+/4O7ubpRz1ibGrndjX+9MpIzA1dUVcrm8WIackJBQLJPW8PT0LLG8ubk5XFxcyixT2jlrG1PVe1FmZmZo164d/zp/qDz1rg9e749nqrovite8rorU+/r16zFu3Dj89ttv6NWrl859vObLZqp6L6qi1zu79ozAwsICbdq0QWRkpM7xyMhIdOrUqcTHdOzYsVj5iIgItG3bFgqFoswypZ2ztjFVvRclhMDp06fh5eVlnMCrufLUuz54vT+eqeq+KF7zuspb77/88gtGjx6NtWvXon///sXu5zVfNlPVe1EVvt6NNmy9ltNM0Vy+fLm4ePGimDRpkrCxsRG3bt0SQgjx/vvvixEjRmjLa6bhv/322+LixYti+fLlxabh//PPP0Iul4vPP/9cXLp0SXz++eecGluEKep95syZYvv27eLGjRvi1KlTYsyYMcLc3FwcPXq00l9fVWVovQshxKlTp8SpU6dEmzZtxLBhw8SpU6fEhQsXtPfzetePKeqe1/zjGVrva9euFebm5uK7777TmWKfkpKiLcNr/vFMUe/Gvt6ZSBnRd999J/z9/YWFhYVo3bq12Ldvn/a+UaNGiW7duumU37t3r2jVqpWwsLAQAQEBYunSpcXO+dtvv4mGDRsKhUIhGjVqJH7//XdTv4xqx9j1PmnSJFGnTh1hYWEh3NzcRGhoqDh06FBlvJRqxdB6B1Dsn7+/v04ZXu/6MXbd85rXjyH13q1btxLrfdSoUTrn5DX/eMaud2Nf7zIhHo60JSIiIiKDcIwUERERUTkxkSIiIiIqJyZSREREROXERIqIiIionJhIEREREZUTEykiIiKicmIiRURERFROTKSIiEohk8nw559/AgBu3boFmUyG06dPSxoTEVUtTKSIiPTg5+eH2NhYNGvWzKjnDQgIwKJFi4x6TiKqPEykiKhWU6lUepWTy+Xw9PSEubm5iSMiouqEiRQRmcSqVavg4uKC3NxcnePPPvssRo4cWerjYmJi8MILL8DZ2Rk2NjZo27Ytjh49qr1/6dKlqFevHiwsLNCwYUOsXr1a5/HR0dF4+umnYWtrC3t7ewwZMgTx8fHa+2fOnImWLVtixYoVqFu3LpRKJYQQuHbtGrp27QpLS0s0adKk2I7zRbv29u7dC5lMhl27dqFt27awtrZGp06dcOXKFe1jbty4gaeffhoeHh6wtbVFu3btsHPnTu393bt3x+3bt/H2229DJpNBJpNp7zt06BC6du0KKysr+Pn54a233kJmZqYeNU9ElYmJFBGZxPPPP4+CggJs2rRJeywxMRFbtmzBmDFjSnxMRkYGunXrhnv37mHTpk04c+YMpk6dCrVaDQDYuHEjJk6ciMmTJ+P8+fMYP348xowZgz179gAAhBAYNGgQHjx4gH379iEyMhI3btzA0KFDdZ7n+vXr+PXXX/H777/j/9u7t5Cm+ziO4+/HpSCtyKCo8BA2kBktNiJI6XCxGA2EZXVRI5HQIjpcZV5IBEJQdFiHG6VA6c6LJhQRDiFqliGVM1GDQcpkCVJGFxEF7fdcRP+nlZrMw/Pw8HnBYP/f7/v/Hf5XX37/L1ssFiOVSlFZWYnNZuPZs2c0NTVRX18/o302NDRw+fJlnj9/zqJFizh06FDafvx+P52dnfT29uLz+aioqCCRSAAQDofJz8+nsbGRsbExxsbGAOjv78fn81FZWcmrV69oa2ujq6uL48ePz/Dpi8iCyfjvjkVE/uDo0aNm165d1vXVq1dNcXGxSaVSk8Y3NzebJUuWmPfv30/aX1ZWZmpra9Pa9u3bZ/x+vzHGmEgkYmw2m0kkElb/wMCAAUxPT48xxpizZ8+a7OxsMz4+bsV0dHQYm81mRkdHrbYHDx4YwLS3txtjjBkeHjaA6e3tNcYY8/DhQwOYzs5O65779+8bwHz+/HnKZ1JaWmpu3LhhXRcVFZlQKJQWc/DgQXP48OG0tmg0arKysqYdW0QWnk6kRGTe1NbWEolESCaTALS0tFBdXZ32CutnsVgMt9vN8uXLJ+0fGhqivLw8ra28vJyhoSGrv6CggIKCAqu/tLSUZcuWWTEARUVFrFixIm3cwsJC8vPzrbYtW7bMaI8ul8v6vnr1agDGx8cB+PTpE6dPn7bWYLfbef36tXUiNZUXL17Q2tqK3W63Pj6fj1QqxfDw8IzWJSILQ1WTIjJv3G43Gzdu5Pbt2/h8Pvr7+7l3796U8bm5uX8c89ckzBhjtf38faoYgMWLF//W/6d5ppKdnf3bPT9eRdbV1dHR0cGlS5dwOBzk5uayd+9evn79Ou2YqVSKI0eOcPLkyd/6CgsLZ7QuEVkYSqREZF7V1NQQCoVIJpN4vd6006JfuVwubt26xcTExKSnUk6nk66urrRi9adPn+J0OoHvp0+JRILR0VFrnsHBQT5+/GjFTObHfW/fvmXNmjUAdHd3Z7Tfn0WjUaqrq9m9ezfwvWZqZGQkLSYnJ4dv376ltXk8HgYGBnA4HLNeg4jML73aE5F5FQwGSSaT3Lx5M60QezL79+9n1apVBAIBnjx5wps3b7hz546V1NTV1dHa2kpTUxPxeJwrV64QDoc5deoUAF6vF5fLRTAY5OXLl/T09FBVVcX27dvZtGnTlPN6vV5KSkqoqqqir6+PaDRKQ0PDrPfucDgIh8PEYjH6+vo4cOCAdVr1w9q1a3n8+DHJZJJ3794BUF9fT3d3N8eOHSMWixGPx7l79y4nTpyY9ZpEZG4pkRKRebV06VL27NmD3W4nEAhMG5uTk0MkEmHlypX4/X42bNjA+fPnsdlsAAQCAa5du8bFixdZv349zc3NtLS0sGPHDuCfXyLPy8tj27ZteL1eiouLaWtrm3berKws2tvb+fLlC5s3b6ampoZz587Neu+hUIi8vDzKysqoqKjA5/Ph8XjSYhobGxkZGWHdunVW3ZbL5eLRo0fE43G2bt2K2+3mzJkzVg2WiPx3/GUmKw4QEZlDO3fuxOl0cv369X97KSIic0qJlIjMm4mJCSKRCMFgkMHBQUpKSv7tJYmIzCkVm4vIvPF4PHz48IELFy4oiRKR/yWdSImIiIhkSMXmIiIiIhlSIiUiIiKSISVSIiIiIhlSIiUiIiKSISVSIiIiIhlSIiUiIiKSISVSIiIiIhlSIiUiIiKSISVSIiIiIhn6G2r3v3R8JILbAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Perform vertical integration\n",
    "VI = VerticalIntegrator(bedload_CG, 'y')\n",
    "vertical_ds_general = VI.integration()\n",
    "\n",
    "# plot the profile of density_mixture of the first time step\n",
    "vertical_ds_general['density_mixture'].isel(time=0).plot.line(x='y', label='Density Mixture General')\n",
    "plt.xlabel('y coordinate')\n",
    "plt.ylabel('Integrated Density Mixture')\n",
    "plt.title('Vertical Profile of Integrated Density Mixture at First Time Step')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da155aca",
   "metadata": {},
   "source": [
    "### 4. Plotting the granular temperature slices calculated with other methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "955040e8",
   "metadata": {},
   "source": [
    "Pysammos provides the granular temperature slices along specified transects using other methods. See the documentation for more details: check the page `gran_temp_slices`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "eb948ffc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot first time step vertical profile comparing Kamrin and LAMMPS\n",
    "fig, ax = plt.subplots(figsize=(8,5))\n",
    "ax.plot(slices_gt.granular_temperature_Kamrin[0,:,0], slices_gt.positions[:, 1], label='Granular Temperature Kamrin', color='blue')\n",
    "ax.plot(slices_gt.granular_temperature_LAMMPS[0,:,0], slices_gt.positions[:, 1], label='Granular Temperature LAMMPS', color='orange')\n",
    "ax.set_xlabel('Granular Temperature')\n",
    "ax.set_ylabel('Y Position')\n",
    "ax.set_title('Granular Temperature Vertical Profile at z=0, Timestep 0')\n",
    "#gridlines\n",
    "ax.grid(visible=True, which='both', linestyle='--', linewidth=0.5)\n",
    "# log scale x axis\n",
    "ax.set_xscale('log')\n",
    "ax.legend()\n",
    "plt.show()  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94de8dbc",
   "metadata": {},
   "source": [
    "### 5. Plotting time-averaged data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "190e4758",
   "metadata": {},
   "source": [
    "Pysammos also calculates time-averaged quantities, below we show how to visualise them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "49a07f61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,5))\n",
    "ax.plot(slices_gt_avg.granular_temperature_Kamrin[0,:,0], slices_gt_avg.positions[:, 1], color=\"blue\")\n",
    "ax.set_xlabel('X Position')\n",
    "ax.set_ylabel('Granular Temperature Kamrin')\n",
    "ax.set_title('Time-Averaged Granular Temperature Kamrin Profile')\n",
    "ax.grid(visible=True, which='both', linestyle='--', linewidth=0.5)\n",
    "ax.set_xscale('log')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2973b1a2",
   "metadata": {},
   "source": [
    "Note that time averaging of non-linear fields, e.g. inertial number, is constructred from the time-averaged quantities, instead of taking the time series average of the non-linear field of interest. The difference between these two calculations is shown below: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e8c85173",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate time-averaged and time series averaged inertial numbers\n",
    "I_tav = bedload_CG_avg.inertial_number_Sxy_Pxy_d32[0,:]\n",
    "I_ts_averaged = bedload_CG.inertial_number_Sxy_Pxy_d32.mean(dim='time')\n",
    "\n",
    "# plot difference between time-averaged inertial number and time series averaged inertial number\n",
    "fig, ax = plt.subplots(figsize=(8,5))\n",
    "ax.scatter(I_tav, bedload_CG_avg.positions[:, 1], label='Time-Averaged Inertial Number [correct]', color='blue')\n",
    "ax.scatter(I_ts_averaged,  bedload_CG_avg.positions[:, 1], label='Time Series Averaged Inertial Number [incorrect]', color='orange')\n",
    "ax.set_xlabel('Inertial Number')\n",
    "ax.set_ylabel('Y Position')\n",
    "ax.set_title('Comparison of Time-Averaged Inertial Number Profiles')\n",
    "#gridlines\n",
    "ax.grid(visible=True, which='both', linestyle='--', linewidth=0.5)\n",
    "# log scale x axis\n",
    "ax.set_xscale('log')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Pysammos_Env",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}