{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Engineering WindFarmModels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All Wind farms models take a `Site` and a `WindTurbines` object as input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install PyWake if needed\n",
    "try:\n",
    "    import py_wake\n",
    "except ModuleNotFoundError:\n",
    "    !pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import and setup site and windTurbines\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import py_wake\n",
    "from py_wake.examples.data.hornsrev1 import V80, Hornsrev1Site\n",
    "\n",
    "site = Hornsrev1Site()\n",
    "windTurbines = V80()\n",
    "wt_x, wt_y = site.initial_position.T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model overview\n",
    "![Engineering models](../_static/EngineeringModels.svg)\n",
    "\n",
    "The engineering wind farms models in PyWake are composed of one of two wind farms models in combination with a wake deficit model, a superposition model and optionally a blockage deficit and a turbulence model.\n",
    "\n",
    "- `WindFarmModel`: Defines the proceedure that detemines how wake and blockage deficits propagates in the wind farm. \n",
    "Two models are available:\n",
    "  - [PropagateDownwind](#PropagateDownwind) (fast, but blockage is neglected)\n",
    "  - [All2AllIterative](#All2AllIterative) (slower but supports blockage).\n",
    "- Wake `DeficitModel`: Calculate wake deficit from one wind turbine to downstream wind turbines or sites in the wind farm. Several common models are available: \n",
    "  - [NOJDeficit](#NOJDeficit)\n",
    "  - [FugaDeficit](#FugaDeficit)\n",
    "  - [BastankhahGaussianDeficit](#BastankhahGaussianDeficit)\n",
    "  - [NiayifarGaussianDeficit](#NiayifarGaussianDeficit)\n",
    "  - [ZongGaussianDeficit](#ZongGaussianDeficit)\n",
    "  - [IEA37SimpleBastankhahGaussianDeficit](#IEA37SimpleBastankhahGaussianDeficit)\n",
    "  - [GCLDeficit](#GCLDEficit)\n",
    "- `SuperpositionModel`: Defines how deficits from multiple sources sums up. Available models are:\n",
    "  - [LinearSum](#LinearSum): Deficits sum up linearly\n",
    "  - [SquaredSum](#SquaredSum): Deficits sum as root-sum-square\n",
    "  - [MaxSum](#MaxSum): Only the largest deficit is considered\n",
    "- Blockage `DeficitModel`: Calculate blockage deficit from one wind turbine to upstream wind turbines or sites in the wind farm. Available models are:\n",
    "  - [FugaDeficit](#FugaDeficit)\n",
    "  - [SelfSimilarityDeficit](#SelfSimilarityDeficit)\n",
    "- `RotorAvgModel`: Defines one or more points at the rotor to calculate a (weighted) rotor-average deficit from\n",
    "  - [RotorCenter](#RotorCenter): One point at the center of the rotor\n",
    "  - [GridRotorAvg](#GridRotorAvg): Custom grid in Cartesian coordinates\n",
    "  - [EqGridRotorAvg](#EqGridRotorAvg): Equidistant N x N Cartesian grid covering the rotor\n",
    "  - [GQGridRotorAvg](#GQGridRotorAvg): M x N cartesian grid using Gaussian quadrature coordinates and weights\n",
    "  - [PolarGridRotorAvg](#PolarGridRotorAvg): Custom grid in polar coordinates  \n",
    "  - [CGIRotorAVG](#CGIRotorAvg): Circular Gauss Integration\n",
    "- `DeflectionModel`: Calculate deflected downwind and crosswind distances due to yaw misalignment, shear etc. Available models are:\n",
    "  - [JimenezWakeDeflection](#JimenezWakeDeflection)\n",
    "- `TurbulenceModel`: Calculate added turbulence in the wake from one wind turbine to downstream wind turbines or sites in the wind farm. Available models are:\n",
    "  - [STF2005TurbulenceModel](#STF2005TurbulenceModel): Steen Frandsen, from IEC 2005 standard\n",
    "  - [STF2017TurbulenceModel](#STF2017TurbulenceModel): Steen Frandsen, from IEC 2017 standard\n",
    "  - [GCLTurbulence](#GCLTurbulence): Gunner Chr. Larsen\n",
    "  - [CrespoHernandez](#CrespoHernandez): A. Crespo and J. Hernández\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predefined WindFarmModels\n",
    "The deficit models comprise:\n",
    "\n",
    "| Name | WindFarmModel | Wake DeficitModel | Blockage DeficitModel | SuperpositionModel |\n",
    "| :--- | :--- | :--- | :--- | :--- | \n",
    "| NOJ | [PropagateDownwind](#PropagateDownwind) | [NOJDeficit](#NOJDeficit) | - | [SquaredSum](#SquaredSum) |\n",
    "| Fuga | [PropagateDownwind](#PropagateDownwind) | [FugaDeficit](#FugaDeficit) | - | [LinearSum](#LinearSum) |\n",
    "| FugaBlockage | [All2AllIterative](#All2AllIterative) | [FugaDeficit](#FugaDeficit) | [FugaDeficit](#FugaDeficit) | [LinearSum](#LinearSum) |\n",
    "| BastankhahGaussian | [PropagateDownwind](#PropagateDownwind) | [BastankhahGaussianDeficit](#BastankhahGaussianDeficit) | - | [SquaredSum](#SquaredSum) |\n",
    "| IEA37SimpleBastankhahGaussian | [PropagateDownwind](#PropagateDownwind) | [IEA37SimpleBastankhahGaussianDeficit](#IEA37SimpleBastankhahGaussianDeficit) | - | [SquaredSum](#SquaredSum) |\n",
    "\n",
    "- Default rotor-average model: `RotorCenter`\n",
    "- Default turbulence model: `None`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from py_wake import NOJ\n",
    "from py_wake import Fuga\n",
    "from py_wake import FugaBlockage\n",
    "from py_wake import BastankhahGaussian\n",
    "from py_wake import IEA37SimpleBastankhahGaussian\n",
    "\n",
    "# Path to Fuga look-up tables\n",
    "lut_path = os.path.dirname(py_wake.__file__)+'/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'\n",
    "\n",
    "models = {'NOJ': NOJ(site,windTurbines), \n",
    "          'Fuga': Fuga(lut_path,site,windTurbines),\n",
    "          'FugaBlockage': FugaBlockage(lut_path,site,windTurbines), \n",
    "          'BGaus': BastankhahGaussian(site,windTurbines),\n",
    "          'IEA37BGaus': IEA37SimpleBastankhahGaussian(site,windTurbines)\n",
    "         }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These models can easily be combined with other models, e.g. NOJ with linear sum superposition:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from py_wake.superposition_models import LinearSum\n",
    "models['NOJLinear'] = NOJ(site,windTurbines,superpositionModel=LinearSum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or models can be combined in custom ways, e.g. NOJDeficit for the wake, LinearSum superposition and SelfSimilarityDeficit for the blockage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from py_wake.wind_farm_models import All2AllIterative\n",
    "from py_wake.deficit_models import NOJDeficit, SelfSimilarityDeficit\n",
    "models['NOJ_ss'] = All2AllIterative(site,windTurbines,\n",
    "                                          wake_deficitModel=NOJDeficit(),\n",
    "                                          superpositionModel=LinearSum(), \n",
    "                                          blockage_deficitModel=SelfSimilarityDeficit() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NOJ: NOJ(PropagateDownwind, NOJDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
      "Fuga: Fuga(PropagateDownwind, FugaDeficit-wake, RotorCenter-rotor-average, LinearSum-superposition)\n",
      "FugaBlockage: FugaBlockage(All2AllIterative, FugaDeficit-wake, FugaDeficit-blockage, RotorCenter-rotor-average, LinearSum-superposition)\n",
      "BGaus: BastankhahGaussian(PropagateDownwind, BastankhahGaussianDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
      "IEA37BGaus: IEA37SimpleBastankhahGaussian(PropagateDownwind, IEA37SimpleBastankhahGaussianDeficit-wake, RotorCenter-rotor-average, SquaredSum-superposition)\n",
      "NOJLinear: NOJ(PropagateDownwind, NOJDeficit-wake, RotorCenter-rotor-average, LinearSum-superposition)\n",
      "NOJ_ss: All2AllIterative(EngineeringWindFarmModel, NOJDeficit-wake, SelfSimilarityDeficit-blockage, RotorCenter-rotor-average, LinearSum-superposition)\n"
     ]
    }
   ],
   "source": [
    "for name, model in models.items():\n",
    "    print (\"%s: %s\"%(name, model))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Engineering WindFarmModel base classes\n",
    "\n",
    "### PropagateDownwind\n",
    "The `PropagateDownwind` wind farm model is very fast as it only performs a minimum of deficit calculations. It iterates over all turbines in downstream order. In each iteration it calculates the effective wind speed at the current wind turbine as the free stream wind speed minus the sum up the deficit from upstream sources. Based on this effective wind speed, it calculates the deficit caused by the current turbine on all downstream destinations. Note, that this procedure neglects upstream blockage effects.\n",
    "\n",
    "```python\n",
    "\n",
    "for wt in wind turbines in downstream order:\n",
    "    ws_eff[wt] = ws[wt] - superposition(deficit[from_upstream_src,to_wt])\n",
    "    ct = windTurbines.ct(ws_eff[wt])\n",
    "    deficit[from_wt,to_downstream_dst] = wakeDeficitModel(ct, distances[from_wt,to_downstream_dst], ...)\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "122 ms ± 0 ns per loop (mean ± std. dev. of 1 run, 10 loops each)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "%%timeit -r1\n",
    "# simulate with 20 wind turbines, 360 wind directions and 23 wind speeds\n",
    "models['Fuga'](wt_x[:20],wt_y[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All2AllIterative\n",
    "The `All2AllIterative` wind farm model is slower but is capable of handling blockage effects. <br/> \n",
    "It iterates until the effective wind speed converge (i.e. less than or equal to the maximum number of turbines that affect each other in the wind farm. The converge tolerance is an input parameter).<br/> \n",
    "In each iteration it sums up the deficit from all wind turbine sources and calculates the deficit caused by the all wind turbines turbine on all wind turbines.\n",
    "\n",
    "```python\n",
    "\n",
    "while ws_eff not converged:\n",
    "    ws_eff[all] = ws[all] - superposition(deficit[from_all,to_all])\n",
    "    ct[all] = windTurbines.ct(ws_eff[all])\n",
    "    deficit[from_all,to_all] = wakeDeficitModel(ct[all], distances[from_all,to_all], ...)\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.78 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -r1\n",
    "# simulate with 20 wind turbines, 360 wind directions and 23 wind speeds\n",
    "models['FugaBlockage'](wt_x[:20],wt_y[:20])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deficit models\n",
    "The deficit models models the wake and/or blockage deficit cause by a single wind turbine. \n",
    "\n",
    "**Variable suffixes**\n",
    "\n",
    "The implementation of the deficit models is highly vectorized and therefore suffixes are used to indicate the dimension of variables. The suffixes used in this context are:\n",
    "\n",
    "- i: source wind turbines\n",
    "- j: destination wind turbines\n",
    "- k: wind speeds\n",
    "- l: wind directions\n",
    "\n",
    "This means that `deficit_ijlk[0,1,2,3]` holds the deficit caused by the first turbine on the second turbine for the third  wind direction and fourth wind speed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# methods to plot deficit map, used below to visualize and compare the deficit models\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from py_wake.deficit_models import BastankhahGaussianDeficit\n",
    "D = 80\n",
    "def _map(f, xy=None):\n",
    "    X, Y = np.meshgrid(*xy)\n",
    "    x_j, y_j = X.flatten(), Y.flatten()\n",
    "    downwind_distance_ijlk = x_j.reshape((1, -1, 1, 1))\n",
    "    crosswind_distance_ijlk = np.abs(y_j.reshape((1, -1, 1, 1)))\n",
    "    ws = 10\n",
    "    zeros_ijl = np.zeros(crosswind_distance_ijlk.shape[:3])\n",
    "    res_ijlk = f(\n",
    "        # specify arguments for all models\n",
    "        WS_ilk=np.array([[[ws]]]),  # wind speed at source turbine\n",
    "        D_src_il=np.array([[D]]),  # diameter of source turbine\n",
    "        D_dst_ijl=None,  # diameter of destination turbine\n",
    "        h_il=np.array([[67]]),  # source turbine hub height\n",
    "        dw_ijlk=downwind_distance_ijlk,  # down wind distance\n",
    "        hcw_ijlk=crosswind_distance_ijlk,  # horizontal cross wind distance\n",
    "        dh_ijl=np.array(zeros_ijl),\n",
    "        # height difference(vertical cross wind distance) between source and destination turbine\n",
    "        cw_ijlk=crosswind_distance_ijlk,  # cross wind distance (both horizontal and vertical)\n",
    "        ct_ilk=np.array([[[8 / 9]]]),  # thrust coefficient\n",
    "        WS_eff_ilk=np.array([[[ws]]]),  # effective wind speed at source turbine\n",
    "        TI_ilk=np.array([[[0.1]]]),\n",
    "        TI_eff_ilk=np.array([[[0.1]]]),\n",
    "        wake_radius_ijlk=BastankhahGaussianDeficit().wake_radius(dw_ijlk=downwind_distance_ijlk, \n",
    "                                                  D_src_il=np.array([[D]]), \n",
    "                                                  ct_ilk=np.array([[[8 / 9]]])),\n",
    "    )\n",
    "    return X / D, Y / D, res_ijlk[0, :, 0, 0].reshape(X.shape)\n",
    "\n",
    "    \n",
    "def plot_deficit_map(model):\n",
    "    xy = np.linspace(-200,500,200), np.linspace(-200,200,200)\n",
    "    X,Y,deficit = _map(model.calc_deficit, xy)\n",
    "    c = plt.contourf(X,Y,deficit, levels=100, cmap='Blues')\n",
    "    plt.colorbar(c, label=\"Deficit [m/s]\")\n",
    "    plt.plot([0,0],[-1/2,1/2],'k')\n",
    "    plt.ylabel(\"Crosswind distance [y/D]\")\n",
    "    plt.xlabel(\"downwind distance [x/D]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NOJDeficit\n",
    "\n",
    "The NOJDeficit model is implemented according to Niels Otto Jensen, \"A note on wind generator interaction.\" (1983), i.e. a top-hat wake, only valid in the far wake\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import NOJDeficit\n",
    "plot_deficit_map(NOJDeficit())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### FugaDeficit\n",
    "\n",
    "The FugaDeficit model calculates the wake deficit based on a set op look-up tables, which must be created in advance using the [Fuga GUI](https://orbit.dtu.dk/en/publications/developments-of-the-offshore-wind-turbine-wake-model-fuga)\n",
    "\n",
    "The fugaDeficit models both near wake, far wake and blockage deficit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import py_wake\n",
    "from py_wake.deficit_models import FugaDeficit\n",
    "\n",
    "# Path to Fuga look-up tables\n",
    "lut_path = os.path.dirname(py_wake.__file__)+'/tests/test_files/fuga/2MW/Z0=0.03000000Zi=00401Zeta0=0.00E+0/'\n",
    "\n",
    "plot_deficit_map(FugaDeficit(lut_path))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BastankhahGaussianDeficit\n",
    "\n",
    "The `BastankhahGaussianDeficit` model is implemented according to Bastankhah M and Porté-Agel F. \"A new analytical model for wind-turbine wakes\" J. Renew. Energy. 2014;70:116-23. The model is valid in the far wake only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HpGcBzweelBxbqHJh1ZTND4Dr2+0l7dUuHepMLy2D2xLhT4v4qAW8mUnUZs933a8kx78+joilFSfQpqHuhV1tZ9B2DuljaboEsNBhpK8pF5a28ygbgMzet8yR9JNOqirInTN6+lfxlg03TTLS8MXs0naPQ+vFVE+BfSFhuv3bzewKSfsCn6hyYZVZPS8HjgV+TVixG0bawkCCM6WYBYG9YWnHyrEyAa9bvLNPEzua5c4ie77Nruti4kg01Bnptx/t49Q0kDzHsJTMXMn+8eY5hCVaucfzru/oS1FpdN/uslmSIso+deQ5kEJnkDsNtlys0vb24wPCgrpBhXCw69K38yqoYctb4AzgK2b2ivZxM7sCeGeVPqpE/EcD9zWz3wxkpTMRDKNpLW7asSr8/Yj3sMKdXTeQJ+xVxL/ZCmUFFmIRSyzEbcFv5/y7Uz+xtLLDRZyZH9h2GEsrUX6nGC0180WzyCEAtAqmEK30U6BV6SeMKpF81nGUpajSjqOnE7Bq7VbaN6sNnKcJg+j9i3bVFFv3df1fk4s0jdM5PwIcDrxK0hJhUe2XzOzCqh1UKtkA/G4w+5xJYRbE+4alZaB+4e51/XL2fdbp5AjdcuaejSi022kxWhH99jjbigNIxCrrECAR9Wa3Y0hf18tBtFlqdTsJCMKUdaCr98tXrJWUlHWuIOsS3szl2VRU1lkUiV3aYVRxFlUcQN9pnz7VO6qQOuu6Jj2+MsMPBmZ2LnAu8BZJdwAeB7xa0gHANoIT+I+yPqoI/+XA1yR9AbgtdfP3DGy5M3KMIKS/vaVZKtrDCnZWrMOxTJoo81fYrBD9QxDf5XUNbl1u0YjDIG8j1kr0D2nBp+N9+/r2sdsSjc0K34qYN7vTPFnxb+asLsqbTdKQWMqN4EPbrKNYvW/R8UDaUeSKburyovGKKgO1TazSgHfLqs+IqprmWZk5VVG502mnUSzwEtUG/ydFkon5ZPJC0gMITwOlVBH+nyevxeTlrAHa8/iv/X1I9fQS7F5iDd2C3ZU6yqkLkb1v3h9n3nXtwd2mGbHE4kJEI4poRKsrKRupx/D8JwAjjuDW8NCT6xTSx29rljiGYFRP5wAlDiLz2VfHIbKRey8HAWmVzx2vSJxEoTBb+WB25XROhZmOIV3TW5Srz5xa/X6ec/7J5uzPA/YhpeXpvH8RVaZzvnUY45zJEGr1GNfdtKPjeC+xHkSo85xEXiqnqui3r22L+mIj5rZl0WjP8IkVBnwTR5Bu2xbTPIdw6w5LHbOVp4Rbl4udQroPgGUrcQwEEW6maiG0+0onddpppfTPouOeyfHu8Yf8VEzbQeSPQxSfG9Y5AD1zKnGF3H77/tXblZtUZ4A+5fP4v0hI+VwM5Dx7F1NlVs8dgb8F/hewvn3czB7dn43OODELJRuu//1tHceriHS/At1xbe6TQs6iroK/3nTbdh30xUaLdQsRjTgK8/njthNoJe20OtjbdgbLQfxvXe52BmmhbwvurTssJfDWUae+adWcQhyp4/+kIbGck74Zt2OA4ByKBqgbJbq23ENPGiUhf6Teu8DV5RjWQn5f0k+BGwk/7uXsHr1J2YXTgSuSQ6ea2d+XdLnezF41iC1VUj2nAP8OPJEwZ/T5hN3inSmmaUGsb7xlR7ewDyHO/Yl4/vEqog+rwr+00GJpOWKxEdNoR/uJEwBSjiAs8IpTA72NKKz0TTsDoLJDgM6B7jg1g2chFs3lfHFeiJU7qLryNNNO5+RE5G3H0GHDSj+rQtt2DF3pJrPcgeilZn5OflCnEEm5K7UhmeJaIsArU1wLGsUVcvedYj+lat/No5KKx0V8w8yeWLGvf5H0V8B/0jn+el2vC6sI/x3M7CRJR5vZ14GvS/p6RcOcCWEYy80WN9x4W4GAVxflPLEvP178R9jPfaMo1EJvNls0mzFLcSvk+uOISK0VwS5yBACxgiO4LWnHMokzgEZbxFMOYbnZ6QygOOLvdAiwg9VUUtYhtAfR246l7RSKHEIwq1uQm81m96Az3bOS2mMjWYr+4PMG6ctolETqvRwCFEfldTuEOpjiBVxLhN263sTqoI8B9+h1YRXhbyeJr5b0BMIGAHsOYKQzRlpmNJvGjTeGQKBIcPuNygFaJds2tUrKK5Zdl3dtFEXEsdhppwV27GixsBCxY0fEwkJMFK2mfCKJ23a0Vp4GWhaxtNxaSQsFYW87gtWnghVnADRanc6gkRL7tDPIE/cg7Kweb7VFPRzbwWoaKX0NkOsQ0uJW1SHklrXso+B+nhCUTVXNO94+V7b4bBCHkP6oeQ6hyuK3MbBR0tbU+y1mtiXTxoAzJRnw4ZzzAA+RdCFBZ19jZt8vueergHv1eILIpYrwv03S7YBXAx8AdgOO6fdGznhpWYjIb7rxtu5zAwp3r2uBjvx1HlYxAdtqtogXYhoLDZpNY3ExotVqEEUtms0WcRyxIxJxHK04gVayY0v7aSCOxFIi+tkB44atOgKAZhzOL3c5glQ6xlYHkNP9ZZ3BqqizerzEGQCZ6zrPhQ+V/Q/qfDuMM4jVvXdBo2AmTvm6heKZSL1WImcdQsfithqcwaCo+gKu7dmcfQ6HmNlVku4EnCXpB2Z2Tur8NmBvM7tJ0hHAZ4F7l/T3feDmKsZlqSL815vZ7wiLuB4FIOmQQW7mjI+WGa1mi1t+f8vKsV6i20vUobdj6KevXv1FOyLiOGZx/SKtVtsBxLRaRhSFqD1KxL/YCaRFd/V4WrgbcbQivM2mEcei2QqqveIIoijJhaccQSyWl1fz6ctN63IEkBX11PFW5yAy8eq36WvCdRlnkBfMZ/8rc9tkxlGiqGumV54jgHxn0GvqaZmTKOoLyh1BuLazz65VzlM4wmtmVyVfr5F0GvAg4JzU+RtS339R0ockbSyJ6JvABZLOpjPHP/x0TkKUf3CFY84U0bIgvrfdHH4f6hbs1fZ97l/Y6qN9FER/ldXoP44jWq0g9MERpL92RvgtC+mg5aZ1OIFGHLG0bKVPA2lHEEdiubU6RtBOqy5jq2MEy/kDq2lR75jC07GwKSNWqWvS4wR5xFGnWDdyIvNGsi4i3We2JlORIwC6+odi8S5bg5A+lz5elyOodTon9UznlLQzEJnZjcn3jwP+PtPmLsCvzcwkPYjgustK5Xw2efVNofBLegjwUOCOktJThnaj89fYmUJaLaPVarJ0c8GTYHNH/vGeHdewUW3Vey+sZ+nWdalbt2gsNGi1jIUFI45bpQ4gjiOWkp3I2pH90vLqzJa2mAOZc4nItP/gk49cxQmE68KX4ZxAfp9516VTScHsbicA3YKbN100WxYb8qeV5vUPxTWCisS+6HhZX+H+qQqsPZ4GpoQ7A6clu401gH81sy9JOgrAzDYDfw78b0nLwC3AM61klxoz+9igxpRF/IvALkmbXVPHb0gMdKaYlhFE+tYbUwdr3F0coLlcb39ZWk2W1+9MlIm4olZEiP5FHPd2ANDpAICOp4BwLKnpk3IAy81mSOeQivq6/gvbApS2MZUKav/dFv3XFziBIOZJk6iztMZCrI6pnF3n+nACbbGdhBPICn0VJ5A7HTVxAj0Xmw2AVM8mL2Z2OXBgzvHNqe+PB47vbZO2mNmRw7QpFP7U1M2TzexnSWcRsEs6F+VMJwYhn3trH2M/gz4F1EnahsUNtHYssZwR/gYNllmmsZD+9c0T4BYQ0Wo1VxzAcupcW8yXO0R51QF0nst/Cui6LopSUyO7HUDXwHBqVk+emGcdAFB4TfYc0JHaAjrsgHwRzlsf0HYCvdYRZPtf+d/JEe4yoS9yDpNyAFPGn0oq21NXJOOxRVTJ8b8jeRxpAucBt5P0HjM7rrqdzrhpmYUIf6lE+Ot+AqibpZthx60sRzFRFNGKWjSjYHN/4t8+1lo5t5w6F2b9ZG8eHEO7EFn7yWC5GY6358mvpn9s5TpYdQDtCqPhPt0OoP0Ekh68Tc/B7+UA0tfAeBxAlTUDZQ6gn0VkRcerOIC6iOPue0yY11Zo842yk1WEfz8zu0HSswm1IV5HcABDC7+kw4H3ER54TzSzSpsIOL0xA6wFO7qnc64pmjug1aTVatFqtUKaJ14drG5Fq2Ie6Bb/9iKwtviHtJAlKZxVMU8LfBDK6uIPrDiAkP9vdUT/bQewMgicrK6tEv1DRuRb+eIP3SLcdb6VWSeQWeWbJ7TZPqtG/3n9w2DiD/n1hvqrEDobDJPbb1NF+BckLQB/ChxvZjuSBQhDISkGPgg8FrgS+J6kz/l+vjUz7VF9LxL7W80WrajVEfVHUZSarRR1RWbpRWgr9d0TQY9XUjnpvL9l8v6siHwv8c+jLf4dx3LEfxAmLf79UIf4lzFK8ZdU25qAaaJKMuzDwE+BnYFzJO1NGOAdlgcBPzGzy81sCfg34Ck19OtQuOnT2qTi2EOzacmrVVhOIk3aMRSVhu6HduSfWwivhznpekrpwdqyvRPSlJ0bFdmpoJC/r0JdFK0Wdvqnp/Cb2fvN7G5mdoQFfkaPgYOK3I2wu1ebK5NjHUg6UtJWSVu3b/facI7jOACS/qLKsTzK5vE/x8w+kZnDn2bYHbjynp+6XHpSz2ILwMEP2OQuvyIz9XAaL1RvGmsljdOL9O5NeYt0+n3ELxsELKtyGe6/em3Z3gBFdJV4GAPZQV6oZ+pjEf2mgOpA0JWumyLeAHyqwrEuynL8Oydfdy1pMwxXAndPvd+TUJjIqZNoytba9TPmEDdW7I/iaOXVfg8hzx8lpRrSwhunjqUFvr2wq01acNPVPbNkz6WLvnWZnSrzkCXdd7/5/c7a/8XtyvYMSNtXZEeewA4j6P18zkHEfd4GdyU9HjgCuJuk96dO7QZUWlxTNo//w8nXtw5jZAnfA+4taV/gl8Azgb8c0b3mDin5J64yfj9G+rEnikO0n0znjKIIRSKO4xXBB1YEvh3tx6WOYPWatIhnhT29oreK6MfZ61Kin90lDDrFsEq0Xyb6VXcPS9uXZ0ewtZroV432i0Q/T6zLRL/o3DhEv9fT2gS4CtgKPJkww7LNjcArq3RQlup5f9E5qFYIqMf1y5JeBnyZMJ3zIz1KkDp9IABFsLC+V9PRMeyCsMUNEMU0FhdWov04DhU7Q5Qf0ViIC0W/Hen3I/ppwYfekX5W8GFV9NOCkd0aMn0Mqgl+uA/F50qvKxf8YG9xf6v91C/4effudbysr3D/6VPrujCzC4ELJZ1iZgMtny8Lv9qe5BBgP8IuXAB/QaeXGRgz+yJhbYBTM5EUIuaddun/4tpKMeQ4nX6Kui2ug4X1icA3Vl5VRb/9HlbFv1eU74Lvgp9Gyk/9TRJJ/2FmTwfOz5tab2YH9OqjLNXzseQmLyBsF7Yjeb8ZOHNQo53xECoUxLBu555tuxh27n9ZpF99nBbiBRbXr2Nx/WKO8GulSmee4AMd4j+qCH9cKZ0ysc89PwUpnX7FvuzcvEb3BRydfK26RWMXVRKuf0AY4G3v47hLcsyZYiShOKaxc/7Y/FSVX06TdhoL6zsEP7xWo/zFxUalCD8t6oPk8KtE97Mi9nlCn9cur3+YHrGvawKQ6H8QftSY2dXJtxFwtZndCiBpJ0IV0J5UEf53Eh4pzk7ePxJ4S3+mOuMmUpjxsn5Dfo6/rk1X6thwpZP1K/02Fhosrl9cifgXFqJSwe8nuh9VZD9NA7XB1vlI48zg4toqfIpQOr9NMzn2wF4X9hR+M/uopDOAP04Ovd7MfjWIlc74iCMRN2I27LqhUJynYZvFsntEcRSEf90Ci4tRl+AvLMRdA7ZtUe+Vt68rqp8moZ/kjJyi+5cdL+sr3H88UX0ZfWy9OAkaSdUDAMxsSdJi2QUrF1ZplAj96QMa50yAEPGLnTZ0/h70u7n6uDZWz7u+sdBgcd0CO+3UYGEhTiL+7ui+SOzzovpBIvpxpG48mh9O5NdKPZ2kRtlW4Jdmlpujl/RA4FzgGWb26ZLurpX0ZDP7XHLdU4BKG69P2SRvpy4iiUYjYrfdwg5W/Qh+UZ2b4uP5fRcdL7rvyrnkPo2FmF12WWRhIUqEP84V+2xU34/Qjyqa90h+siJf1/x+Ufuq6KOBywiLrbrvFxzDuwjT3HtxFHCKpOMJpmI5A4wAABmoSURBVP4CeF4VI1z4ZxQRouJddgnCnxXaPBHvxwnkt+3vaaKXg1lcbLBhwwILCzGLC1Gu2JcJ/SAiP8ko3gW+k3EK/DiQtCfwBODtQFEpnJcDn6FCnt7M/gd4sKRdAJnZjb2uaVO2gOv2PW56Xdl5Z7JECmK2xy6LXdUil3MEOrvRdV61ytzrhnYWxW0XFmLWrWuwYV1jRewXG6GEQzvqj6WOaL5I5Mui+Doj+LWaoik710tchx10rUvgJ+wENkramnq/Jakzlua9wN9SUAZH0t2ApwKPpkT4i+qoJfv5YmY966j1WsBlhEeIvYDrk+93B34O7Nurc2dyRAoiuNuG7rGerKhnBb2KE8gtPdyjn6K+8hwKBJHesK7BuoWYxUbUIfTpaL6XyJcJ/CjEfdBpk0X1cPqZNll0/7LjPfubosi9ertKzXqj4p9Lhu1mtqmwG+mJwDVmdp6kQwuavRd4nZk1VX7PDcnXgeuolS3g2hdWFmx9Llll2y4Q9JhBb+iMh0hBrPbYsLpiKlsTfjkzwJoV87zUTbbeehUhr+oAsvePo0T4G/GK2LeFvhGrp8D3I+5laZlewj4NEfugoh5sWHvCHtpWbjoNHAI8WdIRhDnLu0n6hJk9J9VmE/BviehvBI6QtGxmn830dc/k66Vm1rMSZx5VcvwPNLOj2m/M7AxJ/zDIzZzxIUQjEht3DsKfFeywccdq5c6sWC93CXzm/QicSLjPaj+NOGKnxZj1jWhF6NMiXyTweeI+TMQ+aLQ+6gVOZf2F+w8/HXItiHo0Qg8g6hncNbM3EEomk0T8r8mI/kqwnbQ5GfjPHNGH4BDeTMUSzHlUEf7tyU0+QUj9PAf4zSA3c8aHkoh/9506yzKX7eiUDcK7zuc6jzZx384Dyh1II4rYZTGIflvoF2J1CXyZuJeJ+iQFfdoj9Cp29NsutK3cNLTv84K1NNgLIOkoADPb3MdlXyJM29xZ0g0E/9ROy5uZ5c4YSlNF+J8FHAuclrw/JznmTDFS+AO/w04LHYKd3b4uK87ZSL0/8R/WecBys7NW/vpGxPoFFUT4mZx+H6KePV9VzF3Is20rNw3tB4jOJynm4e+o3j7N7GvA15LvcwXfzF5Qcv1rgddKOt3MBtqutsrK3etYLQrkrBGEiBWxy8JCR469S+i7hL9Ver7MceQN+A7jOOII1jeiJMpXl8CvTN1MiXpa0KuIeb9CvpZSK/23rdx09ZoxCvkay+mPHDN7SrIH+r3N7CtJrZ5GlWmdPYVf0n2A1wD7pNub2aMHN9kZOYJYsGFhNdXTNVsnK+Itg7ik/SBOI1WNs9+nDYB1ccS6dnmFKCoU9rSYZEW7XxGflumJ/bRbbd9X83DNgIo6TCQ+rIiPMq+fpq4c/yiQ9FfAkcDtCQO+ewKbgcN6XVsl1fOppLMTCUWAnDWACAK080KjS8BXBDbR+KzeLlungFdyGLDiNIZ1GO02scRiHK8IfJiiWizwXdF8gYCXacZaGMxcuWYI8Rs2fVKH7tYl3mssrV8nLwUeBHwXwMx+LOlOVS6sIvzLZnbCEMY5E2D/Aw7klqUmi42oe+FU3C32abFeR1TsLAqu7+UsoH+HAbAYRysCv1J7JyXoedpRJN51LgJaK5H1ah9DdxH6qTnSHoVo17nhe0iZTq1nuS0pzAaApAZhkLcnVYT/85L+hjC4e1v7oK/cnW7e9s73cN3vQ+G+rPDni37nL3fXNZngOSvSPZ1FTh/Q22EsRvGKaKUFPU8MywSyql5NavCxTj0dVRpklPo3xeI6zXxd0huBnSQ9Fvgb4PNVLqwi/M9Pvr42dcyAe/RlojNWpFQqJPnaTrGkJ3iGQ6t/dCuCnxKPvFI7WYEO12WcRw9n0TJjgcx008zNFjIllTOmhfc9hG4QYZ7WCDnNuLRy3KLcY9XqWGlPi55SXg+8GLgY+GvCNrYnVrmwyqyefYcyzZkIUSQWGp1ReJwIc15FZLNuwc86ik7dbvfVj6PIOpiMo7DVGjsrn0Or4pkf5Xffq6vNGs0lT0MUPA0iXLAp2NxjZi1JnwU+a2bX9nNtWZG2R5vZVyU9reCmp/ZppzNG2iUbmq3uP9xW9/7MgLoi8hiVO4n2jegcsK3LUUTSSrMi8e5XlyYpptMgolVZK2K71hZs1YHCL9KxwMsIf1iS1AQ+YGZ/X6WPsoj/kcBXgSflnDPAhX+KiaRk96DO42a2Evmnabby/4jynESeUFdyEsGwrlk9ZY6ibVKRYI9aTNeKANbNPApqEVO4ycsxhNo/DzSzKwAk3QM4QdIrzeyfenVQVqTt2OTrC2sy1hkjoaDZ6i/siqhm/qDbIpx1EOGaIieR/4dQu5NgVdj7EWAXrXrx/8+p43nAY81sZbctM7tc0nOAM4HBhb+NpP8hbAP2DeAcM7t0cHudcZKXHsnO1smubu3Q3tS5dJSe9xQBdDmJwqcIM6IcR5PnJLLXuwitDeouczAppOIKqhNkIS36bczsWkkLeRdkqTKrZz/CRusPB94t6X7AhWb21L5MdcaKlD/wGSUzFHrtg17mILoC8xocBBSL+qyIiDM+1tJ4ygAsDXhuhSrC3wR2JF9bwK+Ba6p07kyW8ui4XPmjWH07B6jXQYRLCpzBlPxh55WWdmYHUV6Ab0IcmFTlzCJCrf+eVBH+GwjzRN8D/LOZeUnmNUAsYQWRcrNlFVMmwzsHKHcQubqZY9uU6HwHZtPjgJz5wcxyEqX9UbUs88MIq8JeIunbhFz/fw17c2e0pDUpLbBVZinU5RyASpPtizZkh/EV5Cojzz7X/Gqs5YeiKS/ZMDBVFnCdDpye5PYfT5hK9LfATiO2zamRXr+72T/OXs6hvcJ2HM5hHLrf68llGpzPMJQ51lEzg7rZN5LWE/YyWUfQ3U+3Z06m2jwF+AdCSn0ZOMbMvjkKe6rM6vkMcH/gJ8A3CVOJvjsKY5z6kET2ebAsH123Y4D6nUM/M3ryCr6V991X87FRl16vdcc1MZS/M9sA3AY82sxuSmbefFPSGWZ2bqrNfxH2NzdJBwD/AdyvjptnqZLqeSewzcy8JPMap9cja52OAao/NUD90zSnYdpnv84nj2nV6wk+QKxJLMxYuCl5u5C8LNPmptTbnbPn66SK8O8D/AC4Mdl792DgbWa2bVRGOZNhlI4BBntqmBR5m8L0yyScTx3OpgpT/KObFBslbU2932JmW9INJMXAecC9gA+aWVfmRNJTgXcAdwKeMCpjqwj/35nZpyQ9DPgT4N3ACYS5/c4Uk50Kmbcyth/KHEOVaY2DPDXk9TEObRuHU6rDuWSZ5JPOuJzOOBGVZ25tN7NNZQ2SrMn9Je0OnCZpfzO7JNPmtOTcIwj5/scMZnk5VefxQ/A+J5jZ6ZLeMgpjnNFStqhllE4B6nEM/barg1Fq2SidyyicSi+mIb22FjCz30r6GnA4cElBm3Mk3VPSxrxVusNSZdTil5I+DDwd+KKkdRWvK0TSX0j6vqSWpFIv6YwHJUXdil7DEkulr2lFqvc1LuJII3/NAyKsOen16tmPdMck0ifZFP0xhBR6us29ksqbSDoYWARGsm6qSsT/dIJnenfiqe5K56Ysg3AJ8DTgw0P244yJUT4twPgXQk1qxW2dH3PSmZVxiv8knmBq5q7Ax5I8fwT8h5n9p6SjAMxsM/BnwPMk7QBuAZ5hdfxx5VBF+O8KfMHMbpN0KHAA8PFhbmpml8HM19OYG0btFEZBHY5m0uUa6v7zmdIfFTDJiQCqJYVlZhcBB+Uc35z6/l3Au4a+WQWqpGw+AzQl3Qs4CdgX+NeRWuXMDKNMH02aXumrtZbeWqtpLad/qkT8LTNbTnbieq+ZfUDS+b0ukvQV4C45p96UrAauhKQjgSMB7r7XXlUvc9YAvZ4UqjiHaX2iqMIw4j/pp40qjEL8x/2xpaks0jY0VYR/h6RnEVbstnfj6lnz2cxqmYaUzIXdAnDwAzZN/2+7UwtVnwiGeXKYV6cBa8Nx5OFPEvVQRfhfCBwFvN3MrpC0L/CJ0ZrlOKNnEKexlp1FmlkY4xgHU1qWeWiqFGm7VNJrgPtI2h/4oZm9c5ibJqvTPgDcEfiCpAvM7E+G6dNxxsE8O4ss8/rUMQtUKdJ2KPAx4KcEB3h3Sc83s3MGvWl7ddqg1zvOWqJfZzGrjiLLWnnqmMWFaVVSPf8IPM7Mfggg6T7AJ4EHjNIwx5lX/KmiOtM4O2otUEX4F9qiD2BmP6q6oa/jOOPBnyqcfqgi/OdJOgn4l+T9swkV5hzHWaP4U0U1hGiolnr8U0UV4T8KeCnwCkKO/xzgQ6M0ynGc6cOdxexQKvySIuA8M9ufsNm64zhOZdZ8CkqzufdA6TOMmbWACyX5klnHcUZOryqxs1j6YxJULdL2fUn/Dfy+fdDMnjwyqxzHcSoySvEX071T3KBUEf63jtwKx3EcZ2wUCn9SjfPOZvb1zPFHAL8ctWGO4zjTwCwu4CrL8b8XuDHn+M3JOcdxHKcCku4u6WxJlyW7Dx6d0+bZki5KXt+WdOCo7ClL9eyTbB7QgZltlbTPqAxyHMeZFkRtEf8y8Goz2yZpV8L6qLPM7NJUmyuAR5rZ9ZIeT6hK/Md13DxLmfCvLzm3U92GOI7jzCpmdjVwdfL9jZIuA+4GXJpq8+3UJecCe47KnrJUz/ck/VX2oKQX4yt3HceZB5J5/L1ewEZJW1OvIwu7DBmTg4Dvltz5xcAZNX6SDsoi/mOA0ySlSzRsIuz8/tRRGeQ4jrMG2W5mm3o1krQLYTvbY8zshoI2jyII/8PqNXGVQuE3s18DD02M2D85/AUz++qojHEcx5lVkuKWnwFOMbNTC9ocAJwIPN7MfjMqW6psxHI2cPaoDHAcx5leRFTDAi6FVWYnAZeZWW75m6RCwqnAc83sR0PftIQqC7gcx3Gc4TgEeC5wsaQLkmNvBPYCMLPNwP8B7gB8KFmNvFwlfTQILvyO4zgF1DWd08y+mXRX1uYlwEuGvlkFZq/QtOM4jlOKR/yO4zglzGCNNo/4Hcdx5g2P+B3HcQqQqGVWz7ThEb/jOM6c4RG/4zhOCTNYldkjfsdxnHnDhd9xHGfO8FSP4zhOCfEM5no84nccx5kzPOJ3HMcpQIA84nccx3HWOh7xO47jFCGIZjA8nsGP5DiO45ThEb/jOE4hqqUs87ThEb/jOM4YkPQRSddIuqTg/P0kfUfSbZJeM0pbXPgdx3EKaG/E0utVkZOBw0vOXwe8Anj3cFb3ZiLCL+k4ST+QdJGk0yTtPgk7HMdxxoWZnUMQ96Lz15jZ94Ado7ZlUhH/WcD+ZnYA8CPgDROyw3EcpxhBHPV+ARslbU29jpyw5aVMZHDXzM5MvT0X+PNJ2OE4jlMT20e1MfoomIYc/4uAM4pOSjqy7UW3b792jGY5juPMJiOL+CV9BbhLzqk3mdnpSZs3AcvAKUX9mNkWYAvAwQ/YZCMw1XEcJ5dZLdkwMuE3s8eUnZf0fOCJwGFm5oLuOM5MI+mTwKGE8YArgWOBBQAz2yzpLsBWYDegJekYYD8zu6FuWyaS45d0OPA64JFmdvMkbHAcx6lCXWWZzexZPc7/Ctizlpv1YFI5/uOBXYGzJF0gafOE7HAcx5k7JjWr516TuK/jOE6/zGCKfypm9TiO4zhjxIu0OY7jFCBBFM1eyO8Rv+M4zpzhEb/jOE4JMxjwe8TvOI4zb3jE7ziOU4B8IxbHcRxnFnDhdxzHmTM81eM4jlOEIJ7B0V2P+B3HceYMj/gdx3EKCGWZJ21F/XjE7ziOM2e48DuO45QQSz1fVZB0uKQfSvqJpNfnnJek9yfnL5J0cO0fJsGF33EcZ8RIioEPAo8H9gOeJWm/TLPHA/dOXkcCJ4zKHhd+x3GcEiT1fFXgQcBPzOxyM1sC/g14SqbNU4CPW+BcYHdJd6330wRc+B3HcUbP3YBfpN5fmRzrt00trKlZPedvO2/7hkX9bMDLNwLb67RnDTCPnxnm83P7Z+5m72FvcP628768YVEbKzRdL2lr6v0WM9uSep/3WJDda7xKm1pYU8JvZncc9FpJW81sU532TDvz+JlhPj+3f+bRYGaH19TVlcDdU+/3BK4aoE0teKrHcRxn9HwPuLekfSUtAs8EPpdp8zngecnsngcDvzOzq0dhzJqK+B3HcdYiZrYs6WXAl4EY+IiZfV/SUcn5zcAXgSOAnwA3Ay8clT3zJPxbejeZOebxM8N8fm7/zFOOmX2RIO7pY5tT3xvw0nHYonAvx3EcZ17wHL/jOM6cMVfCL+k4ST9IlkOfJmn3Sds0KnotD581JN1d0tmSLpP0fUlHT9qmcSEplnS+pP+ctC3jQtLukj6d/D1fJukhk7ZpLTFXwg+cBexvZgcAPwLeMGF7RkLF5eGzxjLwajP7Q+DBwEvn4DO3ORq4bNJGjJn3AV8ys/sBBzJ/n38o5kr4zexMM1tO3p5LmCc7i1RZHj5TmNnVZrYt+f5GghCMZNXjNCFpT+AJwImTtmVcSNoNeARwEoCZLZnZbydr1dpiroQ/w4uAMyZtxIgY29LvaUTSPsBBwHcna8lYeC/wt0Br0oaMkXsA1wIfTVJcJ0raedJGrSVmTvglfUXSJTmvp6TavImQGjhlcpaOlLEt/Z42JO0CfAY4xsxumLQ9o0TSE4FrzOy8SdsyZhrAwcAJZnYQ8Htg5sex6mTm5vGb2WPKzkt6PvBE4DCb3bmsY1v6PU1IWiCI/ilmduqk7RkDhwBPlnQEsB7YTdInzOw5E7Zr1FwJXGlm7Se6T+PC3xczF/GXIelw4HXAk83s5knbM0KqLA+fKRRq454EXGZm75m0PePAzN5gZnua2T6En/FX50D0MbNfAb+QdN/k0GHApRM0ac0xcxF/D44H1gFnJTW0zzWzoyZrUv0ULQ+fsFmj5hDgucDFki5Ijr0xWS3pzB4vB05JApvLGWF5g1nEV+46juPMGXOV6nEcx3Fc+B3HceYOF37HcZw5w4XfcRxnznDhdxzHmTNc+B3HceYMF/4ZRtJbJL1mgvf/dp/tD61SWljS1yRtSr7/Yll5bUnHSNrQjx11kdj5Q0lPrtD2WZLeJOkFkq5NatD8WNKXJT001e44Sb+a5M/VWfu48Dsjw8we2rvV0Pc4okdlxmOAiQh/wrPNrMqq6cOBLyXf/7uZHWRm9wbeCZwq6Q8BzOy1wOaCPhynEi78M0YSNf5Q0leA+6aO31/SualNaPaQdCdJ5yXnD5RkkvZK3v+PpA2STpb0fknflnS5pD9Pzn+oHckm/X0k+f7Fkt6WfH9T8vXQJPptb5xxSlJiob1hzA8kfRN4WsFn2knSvyW2/zuwU+rcTyVtlLSzpC9IujApyvcMSa8A/gA4W9LZSfsTJG1NNmt5a6aft0raJuliSfdLju8i6aPJsYsk/Vly/HGSvpO0/1RSHK7s59KQ9D1Jhybv3yHp7cn3Au4PbMteZ2ZnE/aWPbKsf8fpBxf+GULSAwg1Ww4iiOgDU6c/Drwu2YTmYuBYM7sGWK9Q3/zhwFbg4ZL2JlR9bNczuivwMEJxu3cmx85JroFQ8rm96cnDgG/kmHcQIfrej1BW9xBJ64F/Bp6U9HWXgo/2v4GbE9vfDjwgp83hwFVmdqCZ7U/YpOP9hOJ0jzKzRyXt3mRmm4ADgEdKOiDVx3YzOxg4AWinUv4O+J2Z/VFy/69K2gi8GXhM0n4r8KoC24FQRgN4AXCCpMcm9rYdz0HAhSVFA7cB9yvr33H6wYV/tng4cJqZ3ZyUJP4cgKTbAbub2deTdh8jbGQB8G1CnZtHAP83+fpwOsX7s2bWMrNLgTsnx75BcBL7EQpk/VrSXYGHJH1m+W8zu9LMWsAFwD4EMbvCzH6ciN4nCj7XI9rnzOwi4KKcNhcDj5H0LkkPN7PfFfT1dEnbgPOB/8WqwwJoV/Q8L7EP4DGE3cxI7n89YYev/YBvJXWBng/sXXC/FZJ6Sf8CfB54UbJJDgQnULY3RF6ZbccZmHkr0jYP9Ft86RsEod8bOJ1QvdSA9CDrbanvBWBmv5S0B0G0zgFuDzwduCnZAStLuo8mq797Ve0tbWdmP0qeeI4A3iHpTDP7+3QbSfsSIvkHmtn1kk4mlDPO2pi2Tzn3FnCWmT2rou1p/gj4LasOFOBxwJ+VXHMQvrWgUyMe8c8W5wBPTXLiuxJSKCTR7/WS2qmZ5wJfT13zHODHSTR+HUE8v1Xhft8hpG/OITiQ15Cf5iniB8C+ku6ZvC8S0nOAZwNI2p+QpulA0h8Q0kGfAN5N2KgD4EZg1+T73QibdvxO0p0JexL34kzgZan77EHYtvMQSfdKjm2QdJ9eHUl6GnAHwhPM+xU2DL8d0DCz3xRc80hCfv+fK9jqOJXwiH+GMLNtyeDnBcDP6BTh5wObFaY2rpSxNbOfJuOs5yTtvgnsmaQ0evEN4HFm9hNJPyNE/ZWF38xulXQk8AVJ25N775/T9ATCNnsXJZ/tv3Pa/BFwnKQWsIMwLgBhYPQMSVeb2aMknQ98n/B/UMW5vQ34oKRLCE8CbzWzUyW9APikpHVJuzcDPyrqJBkXeCdhA6BfSDqesGH454GvZJo/Q9LDCLORrgD+zMw84ndqw8syO86IkPQ14DVmtrWkzYnAiWZ2bh/9voWQUnv30EY6c4mnehxndFwHnKySBVxm9pI+Rf84Qmru9zXY58wpHvE7juPMGR7xO47jzBku/I7jOHOGC7/jOM6c4cLvOI4zZ7jwO47jzBn/HxtuPWTJys0QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import BastankhahGaussianDeficit\n",
    "plot_deficit_map(BastankhahGaussianDeficit())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IEA37SimpleBastankhahGaussianDeficit\n",
    "\n",
    "The `IEA37SimpleBastankhahGaussian` model is implemented according to the [IEA task 37 documentation](https://github.com/byuflowlab/iea37-wflo-casestudies/blob/master/cs1-2/iea37-wakemodel.pdf) and is equivalent to BastankhahGaussian for $beta=1/\\sqrt{8} \\sim ct=0.9637188$. The model is valid in the far wake only."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import IEA37SimpleBastankhahGaussianDeficit\n",
    "plot_deficit_map(IEA37SimpleBastankhahGaussianDeficit())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GCLDeficit\n",
    "\n",
    "    Implemented according to:\n",
    "            Larsen, G. C. (2009). A simple stationary semi-analytical wake model.\n",
    "            Risoe National Laboratory for Sustainable Energy,\n",
    "            Technical University of Denmark. Denmark.\n",
    "            Forskningscenter Risoe. Risoe-R, No. 1713(EN)\n",
    "\n",
    "    Description:\n",
    "        based on an analytical solution of the thin shear layer approximation of the NS equations.\n",
    "        The wake flow fields are assumed rotationally symmetric, and the rotor inflow fields\n",
    "        are consistently assumed uniform.\n",
    "        The effect of expansion is approximately accounted for by imposing suitable\n",
    "        empirical downstream boundary conditions on the wake expansion that depend\n",
    "        on the rotor thrust and the ambient turbulence conditions, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import GCLDeficit\n",
    "plot_deficit_map(GCLDeficit())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NiayifarGaussianDeficit\n",
    "  \n",
    "    Implemented according to:\n",
    "        Amin Niayifar and Fernando Porté-Agel\n",
    "        Analytical Modeling of Wind Farms: A New Approach for Power Prediction\n",
    "        Energies 2016, 9, 741; doi:10.3390/en9090741\n",
    "\n",
    "    Features:\n",
    "        - Wake expansion function of local turbulence intensity\n",
    "\n",
    "    Description:\n",
    "        The expansion rate 'k' varies linearly with local turbluence\n",
    "        intensity: k = a1 I + a2. The default constants are set\n",
    "        according to publications by Porte-Agel's group, which are based\n",
    "        on LES simulations. Lidar field measurements by Fuertes et al. (2018)\n",
    "        indicate that a = [0.35, 0.0] is also a valid selection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import NiayifarGaussianDeficit\n",
    "plot_deficit_map(NiayifarGaussianDeficit(a=[0.38, 4e-3]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ZongGaussianDeficit\n",
    "  \n",
    "    Implemented according to:\n",
    "        Haohua Zong and Fernando Porté-Agel\n",
    "        A momentum-conserving wake superposition method for\n",
    "        wind farm power prediction\n",
    "        J. Fluid Mech. (2020), vol. 889, A8; doi:10.1017/jfm.2020.77\n",
    "\n",
    "    Features:\n",
    "        - Wake expansion function of local turbulence intensity\n",
    "        - New wake width expression following the approach by\n",
    "          Shapiro et al. (2018)\n",
    "\n",
    "    Description:\n",
    "        Extension of the Niayifar et al. (2016) implementation with Shapirio\n",
    "        wake width expression, which uses the near-wake length estimation by\n",
    "        Vermeulen (1980)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import ZongGaussianDeficit\n",
    "plot_deficit_map(ZongGaussianDeficit(a=[0.38, 4e-3]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GCLDeficit\n",
    "\n",
    "    Implemented according to:\n",
    "            Larsen, G. C. (2009). A simple stationary semi-analytical wake model. \n",
    "            Risø National Laboratory for Sustainable Energy, \n",
    "            Technical University of Denmark. Denmark. \n",
    "            Forskningscenter Risoe. Risoe-R, No. 1713(EN)\n",
    "\n",
    "    Description:\n",
    "        based on an analytical solution of the thin shear layer approximation of the NS equations. \n",
    "        The wake flow fields are assumed rotationally symmetric, and the rotor inflow fields \n",
    "        are consistently assumed uniform.\n",
    "        The effect of expansion is approximately accounted for by imposing suitable \n",
    "        empirical downstream boundary conditions on the wake expansion that depend \n",
    "        on the rotor thrust and the ambient turbulence conditions, respectively. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import GCLDeficit\n",
    "plot_deficit_map(GCLDeficit())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SelfSimilarityDeficit\n",
    "Simple inductionmodel model, see https://onlinelibrary.wiley.com/doi/full/10.1002/we.2137"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import SelfSimilarityDeficit\n",
    "plot_deficit_map(SelfSimilarityDeficit())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare deficit models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "deficitModels = [NOJDeficit(),\n",
    "                 FugaDeficit(lut_path),\n",
    "                 BastankhahGaussianDeficit(),\n",
    "                 IEA37SimpleBastankhahGaussianDeficit(),\n",
    "                 NiayifarGaussianDeficit(),\n",
    "                 ZongGaussianDeficit(),\n",
    "                 GCLDeficit(),\n",
    "                 SelfSimilarityDeficit()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Deficit along center line**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1960d56fbb0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=((10,6)))\n",
    "for deficitModel in deficitModels:\n",
    "    X, Y, deficit = _map(deficitModel.calc_deficit, xy=(np.linspace(-200,500,300), 0))\n",
    "    plt.plot(X[0], deficit[0], label=deficitModel.__class__.__name__)\n",
    "plt.title(\"Center line deficit\")\n",
    "plt.xlabel('x/D')\n",
    "plt.ylabel('Deficit [m/s]')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Deficit profile 2D downstream**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1960f7f06a0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=((10,6)))\n",
    "for deficitModel in deficitModels:\n",
    "    X, Y, deficit = _map(deficitModel.calc_deficit, xy=(2*D, np.linspace(-200,200,300)))\n",
    "    plt.plot(Y[:,], deficit[:,0], label=deficitModel.__class__.__name__)\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Implement your own deficit models\n",
    "Deficit models must subclass `DeficitModel`and thus must implement the `calc_deficit` method and a class variable, `args4deficit` specifying the arguments required by its `calc_deficit` method\n",
    "\n",
    "```python \n",
    "class DeficitModel(ABC):\n",
    "    args4deficit = ['WS_ilk', 'dw_ijlk']\n",
    "\n",
    "    @abstractmethod\n",
    "    def calc_deficit(self):\n",
    "        \"\"\"Calculate wake deficit caused by the x'th most upstream wind turbines\n",
    "        for all wind directions(l) and wind speeds(k) on a set of points(j)\n",
    "\n",
    "        This method must be overridden by subclass\n",
    "\n",
    "        Arguments required by this method must be added to the class list\n",
    "        args4deficit\n",
    "\n",
    "        See class documentation for examples and available arguments\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        deficit_ijlk : array_like\n",
    "        \"\"\"\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deficit_models import DeficitModel\n",
    "from numpy import newaxis as na\n",
    "class MyDeficitModel(DeficitModel):\n",
    "    args4deficit = ['WS_ilk', 'dw_ijlk', 'cw_ijlk']\n",
    "\n",
    "    def calc_deficit(self, WS_ilk, dw_ijlk, cw_ijlk,**_):\n",
    "        # 10% deficit in downstream triangle\n",
    "        ws_10pct_ijlk = 0.1*WS_ilk[:,na]\n",
    "        triangle_ijlk = ((.2*dw_ijlk) >cw_ijlk)\n",
    "        return ws_10pct_ijlk *triangle_ijlk\n",
    "\n",
    "plot_deficit_map(MyDeficitModel())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Superposition models\n",
    "The super position models calculates the effective wind speed given the local wind speed and deficits (typically from multiple sources)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LinearSum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1996.81it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x1960f92cc40>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "linear_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=LinearSum())\n",
    "plt.figure(figsize=(10,4))\n",
    "linear_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SquaredSum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1999.19it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x1960f7000d0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.superposition_models import SquaredSum\n",
    "squared_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=SquaredSum())\n",
    "plt.figure(figsize=(10,4))\n",
    "squared_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MaxSum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2000.14it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x1960cb028b0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.superposition_models import MaxSum\n",
    "max_sum = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=MaxSum())\n",
    "plt.figure(figsize=(10,4))\n",
    "max_sum([0,200],[0,0],wd=270,ws=10).flow_map().plot_wake_map(levels=np.arange(1,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rotor-average models\n",
    "\n",
    "In the plots below, it is clearly seen that the wind speed varies over the rotor, and that the the rotor-average wind speed is not well-defined by the wind sped at the rotor center.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1998.72it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Wind speed [m/s]')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.superposition_models import SquaredSum\n",
    "from py_wake.flow_map import HorizontalGrid, YZGrid\n",
    "R = D/2\n",
    "wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, superpositionModel=SquaredSum())\n",
    "sim_res = wfm([0,200],[0,0],wd=270,ws=10)\n",
    "fig,(ax1,ax2) = plt.subplots(1,2, figsize=(10,4))\n",
    "ax1.set_xlabel(\"x [m]\"), ax1.set_ylabel(\"y [m]\")\n",
    "sim_res.flow_map(HorizontalGrid(extend=.1)).plot_wake_map(10, ax=ax1, plot_colorbar=False)\n",
    "sim_res.flow_map(YZGrid(x=200)).plot_wake_map(10, ax=ax2)\n",
    "ax2.plot([-100,100],[70,70],'-.')\n",
    "ax2.set_xlabel(\"y [m]\"), ax1.set_ylabel(\"z [m]\")\n",
    "\n",
    "plt.figure()\n",
    "flow_map = sim_res.flow_map(HorizontalGrid(x=[200], y=np.arange(-80, 80)))\n",
    "\n",
    "for x in [-.5,.5]:\n",
    "    plt.gca().axvline(x,color='grey')\n",
    "plt.plot(flow_map.Y[:, 0]/D, flow_map.WS_eff_xylk[:, 0, 0, 0], '-.', label='Hub-height profile')\n",
    "plt.plot([-.5,.5],[7.73,7.73],label='Rotor average: 7.73m/s')\n",
    "rc_ws = flow_map.WS_eff_xylk[80, 0, 0, 0]\n",
    "plt.plot(flow_map.Y[80, 0]/D, rc_ws,'.', ms=10, label='Rotor center: %.2fm/s'%rc_ws)\n",
    "plt.legend()\n",
    "plt.xlabel(\"y/D\")\n",
    "plt.ylabel('Wind speed [m/s]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A better estimate of the rotor-average wind speed can be obtained by a (weighted) mean of the wind speed at a number of points covering the rotor. Here is a some model examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from py_wake.rotor_avg_models import RotorCenter, GridRotorAvg, EqGridRotorAvg, GQGridRotorAvg, CGIRotorAvg, PolarGridRotorAvg,polar_gauss_quadrature\n",
    "from py_wake.flow_map import HorizontalGrid\n",
    "R=D/2\n",
    "def plot_rotor_avg_model(rotorAvgModel, name):\n",
    "    plt.figure()\n",
    "    m = rotorAvgModel\n",
    "    wfm = IEA37SimpleBastankhahGaussian(site,windTurbines,rotorAvgModel=m)\n",
    "    ws_eff = wfm([0, 200], [0, 0], wd=270, ws=10).WS_eff_ilk[1,0,0]\n",
    "    plt.title(name)\n",
    "    c = plt.scatter(m.nodes_x, m.nodes_y,c=m.nodes_weight,label=\"%.2fm/s\"%(ws_eff))\n",
    "    plt.colorbar(c,label='weight')\n",
    "    plt.gca().add_artist(plt.Circle((0,0),1,fill=False))\n",
    "    plt.axis('equal')\n",
    "    plt.xlabel(\"y/R [m]\"); plt.ylabel('z/R [m]')\n",
    "    plt.xlim([-1.5,1.5])\n",
    "    plt.ylim([-1.5,1.5])\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RotorCenter\n",
    "The `RotorCenter` model determines the rotor average wind speed from the rotor center point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 499.50it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rotor_avg_model(RotorCenter(), 'RotorCenter')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GridRotorAvg\n",
    "\n",
    "The `GridRotorAvg` defines a set of points in cartesian coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2199.43it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x =y= np.array([-.6, 0,.6])\n",
    "plot_rotor_avg_model(GridRotorAvg(x,y,nodes_weight = [0.25,.5,.25]), 'Grid_4')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EqGridRotorAvg\n",
    "\n",
    "The `EqGridRotorAvg` defines a NxN equidistant cartesian grid of points and discards points outside the rotor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1992.54it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rotor_avg_model(EqGridRotorAvg(4), 'Grid_4')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GQGridRotorAvg\n",
    "\n",
    "The `GQGridRotorAvg` defines a grid of M x N cartesian grid points using Gaussian quadrature coordinates and weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 499.77it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rotor_avg_model(GQGridRotorAvg(4,3), 'GQGrid_4,3')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### PolarGridRotorAvg\n",
    "\n",
    "The `PolarGridRotorAvg` defines a grid in polar coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1995.39it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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7zfGEaSaw+Ph4br/9drZt20b79u3p0aMHt99+O3v22LAfr1OEPI1xtIUbSxDGkcLCQqZPn855551HzZo1+fzzz5k4cSLVq1d3O7SIUr16de6//362bt1K9erV6dChAzNnzrSGbA9ThQKt4mgLN9HZrcSUy86dOxk1ahQ//fQTy5cvL9cU06Zi6taty+OPP87IkSMZOXIkr7zyCnPmzKFJkyZuh2ZOIhE7UC78UpoJmaJSw/nnn09qaiorV6605BBibdu2ZdWqVfTu3ZuUlBQrTXiQYiUIE2V27NjBqFGjOHLkiJUaXBYbG8uECRMYNGgQI0aM4P/+7//4xz/+YaUJDwnHBmgnIvNVmQpT1RNKDR9++KElB49o27YtH330Eb1796ZLly7MmDHDShMeoDhbjzocFxWyEoQ57siRI9x8881s376dFStWWGLwoNjYWCZOnEhaWhq/+c1vWLFiBXPmzAnpdOjmRArk2VxMJpLt2rWLiy++mLi4OEsOYaBt27asXLkSVaVnz55kZ2e7HVIUEwocbuHGEoRh1apVdOvWjWHDhvGvf/3Lfo2GiYSEBJ5//nmuuuoqunXrxscff+x2SFFJsZHUJkLNnTuXIUOGMGfOHMaPHx/xs6xGGhFhwoQJzJw5k7S0NObNm+d2SFEpUksQkVlxZsqUn5/P+PHjeeutt1i+fDnnnnuu2yGZ0zBw4ECWLl1KWloa69evZ9KkSVE7e26oqUpQSwcikgo8BcQAc1T1sRKP1wT+AzTG9x3+uKo+F7QAirESRBT68ccfGTBgAJs2beKTTz6x5BAh2rRpw+rVq1m3bh2DBg3ip59+cjukqOBrpA7OVBsiEgM8C/QH2gDXi0ibEof9FtikqufhW5HzCRGplCUZLUFEmUOHDnH55ZfTqFEj3nrrLc+u/2wqpk6dOrzzzjs0aNCA1NRUfvjhB7dDigISzIFyXYHtqvqlqh4DXgQGlzhGgTPFVx9cAzgA5AfzFRWxBBFFDhw4QJ8+fejcuTOzZs2yKogIFRsbyz/+8Q/atWtH3759+f77790OKaL5Gqkdj4OoJyIZxbYxJU6XDOwqdj/bv6+4Z4DWQA6wAbhLVQsr47VZgogS+/bto1evXlxyySX8/e9/t2m5I1yVKlWYNm0aF1xwAb179+bAgQNuhxTRyjHd9z5VTSm2zSpxqkAt2SVHQ/YD1gJJQEfgGRE5K+gvCksQUeH777/n8ssvJzU1lSlTplhPpSghIjz55JP07t2byy+/nEOHDrkdUkQK8kjqbKBRsfsN8ZUUihsJzFef7cAOoFIaEi1BRLgffviB1NRULrnkEh599NGoSw4L1uzmwsfep9mEt7jwsfdZsGa32yGFlIgwefJkLrjgAvr378/hw4fdDikiFVLF0ebAp0ALEWnmb3geBqSXOOZroDeAiJwNtAK+DOLLOc4SRAQ7cuQIAwYMoHPnzjz55JNRmRwmzt/A7oO5KLD7YC4T52+IyiQxdepU2rVrx6BBg8jNzXU7pIiiCnmFVRxtZZ9L84FxwCJgM/Cyqn4mIreJyG3+wx4GLhCRDcAS4Pequq8yXpsliAilqowYMYImTZrw7LPPRl1yAJiyaCu5eQUn7MvNK2DKoq0uReSeKlWqMGPGDBITExk1apRN8hdEviqm4I2kVtW3VbWlqjZX1Uf8+2ao6gz/7RxVvVxV26tqO1X9T2W9NksQEeqRRx7h66+/Zs6cOVHbIJ1zMPAv5dL2R7oqVaowd+5ctm3bxqRJk9wOJ6LYSGoTNhYsWMDMmTNZvXo1Z5xxhtvhuCapVgK7AySDpFrRO9dUQkICCxYsoFu3brRt25ZBgwa5HVLYK+rmGomi86dlBNuwYQO33HIL8+fPJzEx0e1wXDW+XysS4k4cvZoQF8P4fq1cisgbkpOTeeWVVxg1ahSbNm1yO5wIENwqJi8Jv4hNqfbt28fgwYOZOnUq559/vtvhuG5Ip2QeHdqe5FoJCJBcK4FHh7ZnSKeS446iT/fu3ZkyZQppaWk2RiIICv3rUpe1hRurYooQeXl5XHPNNVx77bUMHz7c7XA8Y0inZEsIpbjpppvYsGED1157Le+8846NrK8gXy+msudZCkdWgogQ9957L9WrV+eRRx5xOxQTRiZNmkRcXBzjx493O5SwZUuOGk9bvHgxr7/+OuvXrycmJjJ/yZjKERMTwwsvvECHDh0YOHAgvXv3djuksBSO1UdOWAkizB06dIhbbrmFOXPmULNmTbfDMWGodu3azJo1i1GjRtlI6woo52R9YcUSRJj73e9+R2pqKn379nU7FBPG+vfvT+/evbnvvvvcDiUsRWovJqtiCmOLFy9m8eLFbNiwwe1QTAR44oknaN++PVdffbVVNZWDqpAfhl/+TkTmq4oCxauWzjqrUmb6NVGmVq1aVtVUQVbFVAlEJFVEtorIdhGZEODxS0XkkIis9W//z404vciqlkxlsKqm8ovkNgjXqpiKrb3aF98c6J+KSLqqlhzauUJVB4Y8QA9bvHgx7777LuvXr3c7FBOBnnzySdq3b897771Hnz593A4nLITjl78TbpYgnKy9akrIy8tj3LhxTJ8+3aqWTKWoWbMm06ZNY9y4ceTnV8pSxxElksdBuJkgnKy9CtBDRNaJyEIRaVvayURkTNE6r999912wY/WMuXPn0rhxY/r37+92KCaCDRgwgAYNGjBv3jy3QwkLkTrVhpsJwsnaq1lAE1U9D/g7sKC0k6nqrKJ1Xv/nf/4niGF6x5EjR/jzn//MY4895nYoJsKJCI899hgPPfSQLTBUBlXIL6ziaAs3bkZc5tqrqvqDqv7ov/02ECci9UIXorc8/fTTXHjhhaSkpLgdiokC3bt35/zzz+fZZ591OxTPi9QqJjfHQRxfexXYjW/t1RuKHyAiDYC9qqoi0hVfQtsf8kg94MCBAzzxxBOsXLnS7VBMFHnkkUe45JJLGD16NLVq1XI7HE8qaoOIRK6VIByuvXo1sFFE1gFPA8M0StdKnDRpEkOHDqVly5Zuh2KiSOvWrRk0aBCTJ092OxRPUxVHW7hxdSS1v9ro7RL7ZhS7/QzwTKjj8prs7GzmzJlj3VqNKx566CE6duzIHXfcEfWLUJUmHBugnQi/VpMo9PDDD3PLLbeQnGzrGpjQa9SoESNHjuThhx92OxRPUrU2COOS/fv38/LLL7Nt2za3QzFR7L777qNVq1Y88sgj1K5d2+1wPEYoCMMeSk5E5quKIM899xxpaWnUqxe1nbeMB9SvX58BAwbwz3/+0+1QPClS2yAsQXhYYWEh06dPZ+zYsW6HYgxjx45l+vTpFBYWuh2Kp0TyXEyWIDxs0aJF1KpVi65du7odijH06NGDatWqsWTJErdD8Rb1tUM42cKNJQgPmzZtGmPHjkUk/H55mMgjIowdO5Zp06a5HYrnROpUG9ZI7VE7d+5k1apVvPTSSyG/9oI1u5myaCs5B3NJqpXA+H6tGNLJelB5gdufzQ033MDEiRPZtWsXjRo1KvsJUUCtkdqE2syZM7nxxhupVq1aSK+7YM1uJs7fwO6DuSiw+2AuE+dvYMGa3SGNw5zMC59NjRo1GD58OLNmzQrZNcOBVTGZkDl27Bhz587ltttuK/vgIJuyaCu5eQUn7MvNK2DKoq0hj8WcyCufze23387s2bM5duxYSK/rZdaLyYTM0qVLad68Oa1atQr5tXMOBp65s7T9JnS88tm0bt2apk2bsmLFipBe16t8pQNLECZE0tPTGTzYnbWTkmollGu/CR0vfTZpaWmkp6eH/LpeZd1cTUioKunp6aSlpbly/fH9WpEQF3PCvoS4GMb3C31pxpzIS59NUYKI0rkzTxKpbRDWi8lj1q1bR9WqVTn33HNduX5RjxjrxeQ9Xvps2rZti4iwceNG2rdvH/Lre4kiFEZoLyZLEB6Tnp7OoEGDXB37MKRTsiUEj/LKZyMiDBo0iPT09KhPEHDyUpiRIjLTXhhzs3rJmPJIS0vjjTfecDsM9wW5kVpEUkVkq4hsF5EJpRxzqYisFZHPRGRZUF9PMZYgPCQ7O5sdO3Zw4YUXuh2KMWXq2bMnW7du5ZtvvnE7FPepw60MIhIDPAv0B9oA14tImxLH1AKmAWmq2ha4JlgvoyRLEB7y5ptv0r9/f+Li4twOxZgyxcXFkZqayptvvul2KK4LYgmiK7BdVb9U1WPAi0DJLo03APNV9WvftfXboL6YYixBeMi7775L//793Q7DGMf69+/P4sWL3Q7DVQoUFoqjDagnIhnFtjElTpcM7Cp2P9u/r7iWQG0RWSoimSJyY2W9NksQHpKRkWEzt5qw0rVrVzIzM90Ow10KqDjbYJ+qphTbSs5ZEqiYUbJyKhboAgwA+gEPikilLFZvCcIj9u3bx6FDh2jevLnboRjjWMuWLfnuu+/4/vvv3Q7FVUEcB5ENFJ8FsSGQE+CYd1T1J1XdBywHzgvG6yjJEoRHZGZm0qlTJ6pUsY/EhI8qVarQsWNHsrKy3A7FXUFqpAY+BVqISDMRiQeGASWHrL8OXCwisSJSDegGbA7CqziJfRt5RGZmJikpKW6HYUy5denSJcqrmZw1UDtppFbVfGAcsAjfl/7LqvqZiNwmIrf5j9kMvAOsB1YDc1R1Y2W8Mhso5xEZGRlce+21bodhTLl16dLF5mUK4kg5VX0beLvEvhkl7k8BpgTvqoGdMkGISGcH58hT1Q1BiidqZWZmMmnSJLfDMKbcunTpwh//+Ee3w3CPghaG30R8TpRVgliGr07sVK++GdA0WAFFI2ugNuGsZcuWfPvtt3z//ffUrl3b7XBcEp0J4lNV7XWqA0Tk/SDGE5WysrKsgdqErZiYmOMN1b1793Y7HHd4dDImEblLVZ8qa19pTvmNVFZycHqMObUvvviCli0rpRuzMSHRsmVLvvzyS7fDcE/wejEF200B9o1w+mTHjdQi0gFfVdLx56jqfKfPN6Xbs2cPiYmJbodhTIUlJiayZ88et8NwR9FAOQ8RkevxTcnRTESK9yA4E9jv9DyOEoSIzAU6AJ8Bhf7dCliCCIKcnBwbQW3CWlJSEuvXr3c7DNd4cDGgVcAeoB7wRLH9h/F1j3XEaQmiu6q2KfswUxFWgjDhLjExkUWLFrkdhns81otJVb8CvgJ6nM55nLaKflRyylkTPJYgTLhLSkqK3iomQNTZFvK4RIaKyDYROSQiP4jIYRH5wenznZYg5uFLEt8AP+Pr06Wq2qECMZsScnJySEpKcjsMYyosMTGRnJySUwZFCfcaoJ2YDAzyj74uN6cJYi7wG2ADv7RBmCDIz89n//791K9f3+1QjKmwBg0a8O2331JYWBiF3bXFc43UxeytaHIA5wnia1WN8rH0lWPv3r3UrVuX2Fib9cSEr/j4eGrWrMl3333H2Wef7XY4oeexEoSIDPXfzBCRl4AF+Gp/AOc9UJ1+K20RkReANypyEVO6vXv30qBBA7fDMOa0JSYm8s0330RngvBevcqgYrePAJcXu++4B6rTBJGALzFU6CKmdEePHqVatWpuh2HMaUtISODo0aNuhxF6HhwHoaojg3EeRwkiWBcrSURSgaeAGHxT1j5W4nHxP34Fviw4QlUjauL5vLw8q14yESE2Npb8/Hy3w3CFGz2UnBCRpwPsPgRkqOrrZT3/lK1JAdZLrdAxpTwvBngW6A+0Aa4P0JW2P9DCv40BplfkWl6Wn59PXFyc22EYc9qiOUF4eKqNM4COwDb/1gGoA4wSkallPbmsn64TRGTfKR4X4C6g5LqqTnQFtqvqlwAi8iIwGNhU7JjBwL9UVYGPRaSWiCSqasR0uM7Pz7cShIkIUZ0gvOtXQC//QkSIyHRgMdAXX6/UU3Iy3fegMo5510GQgSQDu4rdz8a3dF5ZxyTjG0J+An9JZgxA48aNKxhS6KkHx+gbUxEiQmGh91prQ8GrVUz4vi+r46tWwn87SVULROTn0p/mc8oEUVltD36BWnVKvs1OjvHtVJ2FvySTkpLi3Y+rBPvVZSJF1FaXKp6baqOYycBaEVmK7/u0J/BXEakOvFfWk92s28gGGhW73xAoORTTyTFhLS4uzhKEiQhRXV3q0Z+kqvoPEXkbX/aw/pcAABwmSURBVJW+AH9Q1aLv0PFlPd/NIY+fAi1EpJmIxAPDgJKD8dKBG8WnO3AoktofwEoQJnJEc488r83FJCLn+v92BhLxVdV/DTRwuJQ04GIJQlXzRWQcsAhfN9e5qvqZiNzmf3wGvoW7rwC24+vmWplVXq6Ij4+Pzr7jJuL8/PPPxMfHux2GO7xXgvhffG2yTwR4TAFHC72VmSD83VFrq+o+//14fCsS3aOqrZ1GG4iqvo0vCRTfN6PYbQV+ezrX8Lr69euzd+9et8Mw5rTt3bs3OkdRg+cShKqO8f+97HTOU9Y4iGHAAWC9iCwTkcuAL/GNTxh+Ohc2PsUnOTMmXBVNOhmNCcJp9ZJL031XE5EHRGSW/34LERno9PlllSAeALqo6nZ/vdVHwDBVfa3iIZviqlatyllnncW+fftsRlcTtr799lvq1KkTtW0QHu7F9ByQCVzgv58N/B/wppMnl9VIfUxVtwP4p7jYYckh+KJ6Ln0TEaJ90SuvliCA5qo6GcgDUNVcAg8fCKisdF9fRP632P0axe+r6pPlidQEVrQaV8eOHd0OxZgKifpFrzzWBlHMMRFJwB+hiDSn2IzcZSkrQcwGzjzFfRMEiYmJUb1cowl/UV2CcK904MQfgXeARiLyPHAhvk5GjpSVID4HFqvq/gqHZ8qUlJRkVUwmrFkJwu0ASnUj8BbwCr4ORncV9Uh1oqw2iCbA/4nIChF5SES6+afgNkFkJQgT7qK6BAFIobPNBc/hm9E1DXgamCkidzl98ikThKo+pqq98A1WWwfcDGSJyAsicqOIRF+ftkrQpEkTvvjiC7fDMKbCvvzyS5o0aeJ2GKYEVX0feAR4EJgDpAC3O32+0wWDDgOv+Tf86zb0B/4F9CtfyKakzp07k5WVhapiBTQTblSVzMxMOnd2PIND5PFoFZOILME3g+tHwArgfFX91unzHc3FJCJLROSKovuquglopaqWHIIgOTkZESE7O9vtUIwpt507d5KQkBC9a6t7eKAcsB44BrTDt1hQO3+vJkecTtbXDPi9iPyx2L4UxyGaUxIRunTpQmZmptuhGFNumZmZdOnSxe0w3OXRFeVU9R5V7QlcCezH1yZx0OnznSaIg0Bv4GwReUNEapY7UnNKliBMuLIEgWcThIiME5GXgLXAEGAuvuYBR5wmCFHVfFUdC7wKfAjYvBBBlJKSQkZGhtthGFNumZmZpKREb4WC4OleTAnAk8C5qtpbVf/kb7h2xGmCKD7D6j/xDbRYXI4gTRmKShC2BKkJJ0UN1FFdgghyG4SIpIrIVhHZLiITTnHc+SJSICJXlxqa6hRV/aRoTerycpQgVHVmifuZqnpzRS5oArOGahOOvvrqK84444zobaAuEqQqJv/yCs/iqwZqA1zv7zUa6LhJ+NbTqTRurihniilqqLZqJhNOMjIyorv0UCR4bRBdge2q+qWqHgNeBAYHOO4OfNX9jrusVoQlCA/p1asXixdbzZ0JH4sXL6ZXL0eLk0W0clQx1RORjGLbmBKnSsa3PGiRbP++X64lkoyvV9IMKpklCA9JS0sjPT3d2iFMWCgsLOSNN95g0KBBbofiPucliH2qmlJsm1XiTIFGypb8QpgK/F5VC4L3AgKzBOEhLVu25MwzzyQrK8vtUIwpU0ZGBnXq1KF58+Zuh+IuDWovpmygUbH7DYGSM3mmAC+KyE7gamCaiAwJwis5iSUIjxk0aBDp6eluh2FMmdLT00lLS3M7DG8IXhvEp0ALEWkmIvHAMOCELwRVbaaqTVW1Kb5ZWseq6oLgvJATWYLwmKJqJmO8zhLEL4LVzdXfHXUcvt5Jm4GXVfUzEblNRG6r3FdxsihdQNa7evTowa5du/j6669p3LixKzEsWLObKYu2knMwl6RaCYzv14ohnZLLfqKpdF75bHbs2MHevXvp2rVryK/tSUFsNlTVt4G3S+wL2CCtqiOCd+WTWQnCY2JjYxkwYABvvPGGK9dfsGY3E+dvYPfBXBTYfTCXifM3sGDNblfiMb/w0mfzxhtvMGDAAGJiYkJ+bc9xWr0Uhn1PLEF4kJvVTFMWbSU378TOEbl5BUxZtNWVeMwvvPTZWPXSLwRPz+Z6WixBeFC/fv1YvXq1K8uQ5hzMLdd+Ezpe+Wyys7PJysqib9++Ib2ul1mCMCFTo0YNhg0bxpw5c0J+7aRagaeKL22/CR2vfDazZ8/mhhtuoHr16iG9rqdZFZMJpdtvv51Zs2aRl5cX0uuO79eKhLgT65UT4mIY369VSOMwJ/PCZ5OXl8fs2bO5/XbHq1ZGB0sQJpQ6dOhAs2bNQt5YPaRTMo8ObU9yrQQESK6VwKND21svJg/wwmezYMECWrZsSdu2bUN2Tc8L8myuXmLdXD1s7NixTJs2jaFDh4b0ukM6JVtC8Ci3P5tp06YxduxY167vWWH45e+ElSA8bOjQoWzcuJEtW7a4HYoxbNq0iS1btjBkSKXM6hDWPLxg0GmxBOFhVatWZdSoUcyYUemTNhpTpunTp3PLLbcQHx/vdiieE6lVTJYgPG7MmDH8+9//5qeffnI7FBPFDh8+zPPPP8+YMSVnpzY2UM64pkmTJlx66aVWijCumj59On369KFhw4Zuh+JNEZogrJE6DPz5z3+mV69ejB49mpo1a7odjoky33//PVOmTGHFihVuh+JJRSOpI5GVIMJA27ZtueKKK3j88cfdDsVEocmTJzNkyBDOPfdct0PxLClUR1u4sRJEmHjooYfo3Lkzv/3tb22BeBMyOTk5zJo1i3Xr1rkdineFafWRE66UIESkjoi8KyLb/H9rl3LcThHZICJrRSQj1HF6SZMmTbjpppt4+OGH3Q7FRJE//elPjBo1ytoeymC9mIJrArBEVVsAS/z3S3OZqnZU1ZTQhOZdf/jDH3jppZf44osv3A7FRIHPP/+cV199lQkTTvXf0wAR20jtVoIYDMzz354H2MgbB+rVq8fdd9/Ngw8+6HYoJgo88MAD3HvvvdSpU8ftUDzPShDBdbaq7gHw/61fynEKLBaRTBE5ZQdsERkjIhkikvHdd98FOVzvuPvuu/nggw/IyspyOxQTwT799FM+/PBD7rzzTrdDCQ8RWoKotEZqEXkPCNSaen85TnOhquaISH3gXRHZoqrLAx2oqrOAWQApKSlh+FE4U6NGDR599FFGjx7NJ598QlxcnNshmQhz7NgxRo8ezaRJk2xKbyc0PKfRcKLSShCq2kdV2wXYXgf2ikgigP/vt6WcI8f/91vgNcAWwAVuuukmGjRowKOPPup2KCYC/eUvf6Fx48b8+te/djuUsGArygVfOnCT//ZNwOslDxCR6iJyZtFt4HJgY8gi9DARYdasWfz973+37ocmqLKyspgxYwYzZ85ERNwOJ3yoOtvCjFsJ4jGgr4hsA/r67yMiSSLytv+Ys4EPRWQdsBp4S1XfcSVaD2rYsCGTJ09m5MiRIV9UyESmY8eOMXLkSJ544gmSkpLcDiesWAkiiFR1v6r2VtUW/r8H/PtzVPUK/+0vVfU8/9ZWVR9xI1YvGzFiBImJiVbVZILCqpYqKIIn67OR1GGsqKqpU6dODB48mPPOO8/tkEyYKqpaWrt2rVUtVYA1UhtPSk5OZvLkyYwYMYJjx465HY4JQ8eOHWPEiBFWtXQabMEg41k33XQTjRs35p577nE7FBNmVJU77riDX/3qV1a1VFGKNVIb7xIR/v3vf/PBBx8wc+ZMt8MxYWT69OmsXLmSefPmWdXSaYjURmprg4gQZ511Fq+//joXXXQRrVu3pmfPnm6HZDzu/fff589//jOrVq3izDPPdDuc8BaGX/5OWAkigrRo0YL//Oc/XHfddezcudPtcIyHffnll9xwww288MILnHPOOW6HE9YieaCclSAiTN++fZkwYQKDBw9m5cqV1KhRw+2QXLVgzW6mLNpKzsFckmolML5fK4Z0SnY7LFcdPnyYtLQ0HnzwQXr16uV2OOFPw3MxICesBBGB7rzzTrp06cJNN91EYWEYdp0IkgVrdjNx/gZ2H8xFgd0Hc5k4fwML1ux2OzTXFBYW8pvf/IYLLriAsWPHuh1O5IjQcRCWICKQiDB9+nT27NnDQw895HY4rpmyaCu5eQUn7MvNK2DKoq0uReS+Bx98kP379/PMM89Yo3QQWRWTCStVq1bltdde46KLLqJ27dpR2QU252BuufZHuscff5xXXnmFFStWEB8f73Y4kUOBCK1isgQRwc4++2yWLFnCJZdcQtWqVaOuSiGpVgK7AySDpFoJLkTjrmeeeYbp06ezbNky6tcvbfkVU2GRmR+siinSNW7cmCVLlvDoo48yd+5ct8MJqfH9WpEQF3PCvoS4GMb3a+VSRO6YPXs2U6ZMYcmSJba2dCUJZhWTiKSKyFYR2S4iJ633KiLDRWS9f1slIpU2x46VIKLAOeecw3vvvUfv3r0pKCjglltucTukkCjqrRTNvZhmzJjBI488wvvvv0/Tpk3dDidiBasXk4jEAM/im+U6G/hURNJVdVOxw3YAl6jq9yLSH99Cad2CEkAJliCiRKtWrfjggw/o06cPP//8M+PGjXM7pJAY0ik5qhJCcVOnTmXq1KksXbqU5s2bux1O5ApuD6WuwHZV/RJARF4EBgPHE4Sqrip2/MdApRULLUFEkRYtWrBs2TJ69+5Nbm4u48ePdzskU0kee+wx5syZw7Jly2jSpInb4UQ030A5xxminohkFLs/y79ccpFkYFex+9mcunQwCljo9OLlZQkiyjRt2pRly5bRt29fvvrqK/72t7/ZutYR5NixY9x1110sX76cZcuWkZwcnaWnkHM+3Gifqqac4vFAfY8DZh8RuQxfgrjI8dXLyRqpo1DDhg35+OOP2bFjB/369WP//v1uh2SC4LvvvuPyyy9n165dfPTRR5YcQkhUHW0OZAONit1vCOScdD2RDsAcYLCqVtp/YEsQUapmzZqkp6dz/vnn07VrVzZutOW+w9n69evp2rUrPXr04PXXX+ess85yO6ToEdwV5T4FWohIMxGJB4YB6cUPEJHGwHzgN6r6eXBeRGBWxRTFYmJimDRpEu3bt6dXr17Mnj2bwYMHux2WKaf58+dz66238vTTT3P99de7HU4UCt5cTKqaLyLjgEVADDBXVT8Tkdv8j88A/h9QF5jmHw2fX0a1VYVZgjD8+te/pmXLlgwdOpSNGzfyhz/8waZhCAOFhYX85S9/Yfbs2SxcuJCUlEr5jjBOBHExIFV9G3i7xL4ZxW6PBkYH7YKnYFVMBoCuXbuyevVq0tPTufbaazlw4IDbIZlT2L9/P9dccw0LFy5k9erVlhzcpLbkqIkCSUlJx3u+tG/fnjfeeMPtkEwACxYsoH379jRu3JgPPviAxMREt0MyEbrkqFUxmROcccYZTJ06laFDh3LzzTfz8ssv89RTT1GnTh23Q4t6+/fv584772T16tW8/PLLXHRRpfVuNOUVft/9jlgJwgTUs2dP1q1bR506daw04QFFpYb69euzbt06Sw4eI4WFjrZwYyUIU6rq1avz1FNPcdVVV1lpwiVWaggDSnkGyoUVK0GYMpUsTcydO5f8/Hy3w4po+fn5zJkzx0oNYUBwNkiuHNNxeIYlCONIUWni1VdfZd68eXTo0IHXXnsNDcN/9F6mqrz66qu0a9eO559/ngULFvC3v/2NatWquR2aOZUIbaS2BGHKpXv37ixdupQnnniCP/3pT/To0YOlS5e6HVZE+OCDD+jevTt/+ctfmDp1Ku+//z5du3Z1OyzjhCUIY3xEhP79+5OVlcUdd9zBzTffTP/+/VmzZo3boYWlrKws+vXrx+jRo7n77rvJzMwkNTXVBiuGi6I2CCdbmLEEYSqsSpUqDB8+nC1btjBgwACuuOIKrrvuOlatWmVVT2VQVVauXMm1117LgAEDGDx4MJs3b+b666+nShX7bxluIrUXk/1LNKctPj6ecePGsW3bNrp3786IESPo1KkTs2bN4scff3Q7PE/58ccfmTlzJh07duTmm2/mggsuYNu2bYwdO5b4+Hi3wzMV4rB6KQx/NFmCMEFTo0YN7rnnHrZs2cKUKVNYuHAhTZo04c4772Tz5s1uh+eqTZs2cccdd9CkSRMWL17Mk08+yZYtW7j77rupUaOG2+GZ06FYgjDGqSpVqtC3b19ee+011q5dS82aNenVqxe9evXipZdeippSxeHDh3nxxRe57LLL6NOnD3Xq1GHdunW8+uqr9O7d29oYIom1QRhTfo0aNeLhhx/mq6++4tZbb2Xu3LkkJSXRv39/pk+fTnZ2ttshBtWuXbuYNm0aqampJCcn889//pOxY8fy1Vdf8ac//YmGDStt+WDjokgdB2EjqU1IxMfHc91113Hdddfxww8/sGjRItLT03nwwQdp3LgxaWlppKWl0alTp7D6Za2qZGVlkZ6eTnp6Ort27WLAgAGMHj2al19+2RbuiRZh+OXvhCsJQkSuAR4CWgNdVTWjlONSgafwLZwxR1UfC1mQptKcddZZXHPNNVxzzTXk5+ezatUq0tPTue6668jNzeWiiy6iS5cudOnShc6dO1OrVi23Qz7u4MGDZGVlkZGRQWZmJh9++CE1atQgLS2Np59+mh49ehAba7+7oooqFIRh/ZED4kZ3RBFpja9Gbibwu0AJQkRigM+BvvjWaf0UuF5VN5V1/pSUFM3ICJhzjIepKtu2bePjjz8mMzOTzMxM1q5dS2Ji4vGE0aVLFzp06EDdunUrtaShquzfv5/169cfTwaZmZns3buXjh07Ho+le/futGjRotLiMJVLRDJPdzW2mmc00Asa3ejo2He2Tznt64WSKz91VHUzUNZ/8K7AdlX90n/si8BgoMwEYcKTiNCyZUtatmzJjTf6/sMVFBSwdevW41/Sr7/+Ohs3buTo0aMkJiaSmJhIUlLSSbdr165NbGwscXFxxMbGEhMTQ0FBAfn5+eTl5ZGfn8/333/Pnj17yMnJOeFv0ZaQkEC7du3o0qULAwcO5I9//COtWrUiJibG5XfKeI5VMYVcMrCr2P1soFtpB4vIGGAMQOPGjSs3MhMyMTExtGnThjZt2hxPGgBHjhw5/kVe/At+y5Yt5OTkcOjQIfLz80/YYmNjT9hq1ap1PKn86le/4uKLLz4h2dj8R8YRBYK0JrXXVFqCEJH3gAYBHrpfVV93cooA+0r9FFR1FjALfFVMjoI0YatatWo0b96c5s2bux2KiXoKGpltEJWWIFS1z2meIhtoVOx+QyDnNM9pjDHBpURsI7WXx0F8CrQQkWYiEg8MA9JdjskYY05mI6mDR0SuFJFsoAfwlogs8u9PEpG3AVQ1HxgHLAI2Ay+r6mduxGuMMacUoQnCrV5MrwGvBdifA1xR7P7bwNshDM0YY8opPL/8nfByLyZjjPE+BcJwKm8nLEEYY8zpshKEMcaYk0XuVBuWIIwx5nQoqI2DMMYYE5CNpDbGGBOQtUEYY4w5iar1YjLGGFMKK0EYY4w5maIFBW4HUSksQRhjzOmw6b6NMcaUKkK7uXp5NldjjPE8BbRQHW1OiEiqiGwVke0iMiHA4yIiT/sfXy8inYP9mopYgjDGmNOh/gWDnGxlEJEY4FmgP9AGuF5E2pQ4rD/Qwr+NAaYH9wX9whKEMcacJi0ocLQ50BXYrqpfquox4EVgcIljBgP/Up+PgVoikhjcV+QTkW0QmZmZP4rIVrfjKId6wD63gyincIs53OIFizkUWp3uCQ7z/aL39JV6Dg8/Q0Qyit2f5V8uuUgysKvY/WygW4lzBDomGdjjMAbHIjJBAFtVNcXtIJwSkYxwihfCL+Zwixcs5lAo8WVdIaqaGoxY/CTQJSpwTFBYFZMxxnhHNtCo2P2GQE4FjgkKSxDGGOMdnwItRKSZiMQDw4D0EsekAzf6ezN1Bw6patCrlyByq5hmlX2Ip4RbvBB+MYdbvGAxh4Kn4lXVfBEZBywCYoC5qvqZiNzmf3wGvmWYrwC2A0eAkZUVj2iEziFijDHm9FgVkzHGmIAsQRhjjAko7BOEiFwjIp+JSKGIlNq9TkR2isgGEVkbjK5tp6McMZ9yyH0oiUgdEXlXRLb5/9Yu5ThX32cvTVPglIOYLxWRQ/73dK2I/D834iwWz1wR+VZENpbyuBff47Ji9tR77BmqGtYb0BrfYJelQMopjtsJ1HM7Xqcx42ug+gI4B4gH1gFtXIx5MjDBf3sCMMlr77OT9wxf495CfH3JuwOfuPxvwUnMlwJvuhlniXh6Ap2BjaU87qn32GHMnnqPvbKFfQlCVTerajiNmnYas5Mh96E0GJjnvz0PGOJiLKXx1DQFDnntcy6Tqi4HDpziEK+9x05iNgGEfYIoBwUWi0imiIxxOxgHShtO75az1d/X2v+3finHufk+O3nPvPa+Oo2nh4isE5GFItI2NKFVmNfeY6fC6T0OibAYByEi7wENAjx0v6q+7vA0F6pqjojUB94VkS3+XxWVIggxh2w4/fELniLmcpwmpO9zCZ6apsAhJ/FkAU1U9UcRuQJYgG8mT6/y2nvsRLi9xyERFglCVfsE4Rw5/r/fishr+Ir2lfbFFYSYQzacvsipYhaRvSKSqKp7/NUF35ZyjpC+zyV4apoCh8qMR1V/KHb7bRGZJiL1VNWrk+J57T0uUxi+xyERFVVMIlJdRM4sug1cDgTszeAhTobch1I6cJP/9k3ASaUgD7zPnpqmwKEyYxaRBiIi/ttd8f2/3R/ySJ3z2ntcpjB8j0PD7Vby092AK/H9YvkZ2Ass8u9PAt723z4HX++QdcBn+Kp5PB2z//4VwOf4erm4HXNdYAmwzf+3jhff50DvGXAbcJv/tuBbkOULYAOn6PnmoZjH+d/PdcDHwAUux/tffFNL5/n/HY8Kg/e4rJg99R57ZbOpNowxxgQUFVVMxhhjys8ShDHGmIAsQRhjjAnIEoQxxpiALEEYY4wJyBKECWsi8o6IJIvIUv+MqOtE5FMR6VjK8UWzzZY6i26A5zT3z/D5Y/AiN8b7LEGYsCUiCfjGY+z27xququcB04App3jqZarqeCpyVf1CVQMmHGMimSUI42ki8rCI3FXs/iMicqf/7qX4pkwv6SMcTg7nL1H8VUQ+EpEMEeksIotE5AvxrwNsTLSyBGG87h/4p/gQkSr4pqJ43v9Yf+CdAM9JxTfZmlO7VLUHsAL4J3A1vnUM/lyxkI2JDGExWZ+JXqq6U0T2i0gn4GxgjaoWzZFzIfC7Yoc/758DKgbf4jBOFc19tAGooaqHgcMiclREaqnqwdN8GcaEJStBmHAwBxgBjATmAojIOfh++R8rdtxwoBnwAr65gJz62f+3sNjtovv2I8pELUsQJhy8hq/a6HxgkX9fwOolVc0DHgC6i0jrkEVoTASyBGE8z19K+AB4WVUL/LtTCdz+gKrmAk9wYvWTMaacbDZX43n+xuks4BpV3SYiVYGVqup4LEOxc+3EN/10uReCEZEfVbVGeZ9nTLiyEoTxNBFpA2wHlqjqNgBV/bkiycHvO2BJRQbK4Vu7w5ioYSUIY4wxAVkJwhhjTECWIIwxxgRkCcIYY0xAliCMMcYEZAnCGGNMQP8ftqXjwgw8HCAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "theta = np.linspace(-np.pi,np.pi,6, endpoint=False)\n",
    "r = 2/3\n",
    "plot_rotor_avg_model(PolarGridRotorAvg(nodes_r =r, nodes_theta=theta, nodes_weight=None), 'PolarGrid_6')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The polar grid can be combined with Gaussian Quadrature. This is similar to the implementation in FusedWake (https://gitlab.windenergy.dtu.dk/TOPFARM/FUSED-Wake/-/blob/master/fusedwake/gcl/fortran/GCL.f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1997.29it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rotor_avg_model(PolarGridRotorAvg(*polar_gauss_quadrature(4,10)), 'PolarGrid_4,10')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### CGIRotorAvg\n",
    "Circular Gauss integration with 4,7,9 or 21 points as defined in Abramowitz M and Stegun A. Handbook of Mathematical Functions. Dover: New York, 1970."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1001.03it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2003.01it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1894.87it/s]\n",
      "100%|███████████████████████████████████████████████████████████████████████████| 2/2 [00:00<?, ?it/s]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for n in [4,7,9,21]:\n",
    "    plot_rotor_avg_model(CGIRotorAvg(n), 'CGIRotorAvg_%d'%n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare rotor-average models\n",
    "In general, the compuational cost and the accuracy of the estimate increases with the number of points, but the distribution of the points also has an impact.\n",
    "\n",
    "The plot below shows the absolute error of the estimated rotor-average wind speed for the wind directions \n",
    "270$\\pm$30$^\\circ$ (i.e. wind directions with more than 1% deficit) for a number of different rotor-average models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 13.33it/s]\n",
      "100%|███████████████████████████████████████████████████████████████████████████| 2/2 [00:00<?, ?it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2001.58it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1966.39it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2000.62it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2003.49it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1999.67it/s]\n",
      "100%|███████████████████████████████████████████████████████████████████████████| 2/2 [00:00<?, ?it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2000.62it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1998.72it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1997.29it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1999.19it/s]\n",
      "100%|███████████████████████████████████████████████████████████████████████████| 2/2 [00:00<?, ?it/s]\n",
      "100%|██████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 991.09it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2018.43it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2000.14it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1001.39it/s]\n",
      "100%|█████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2007.80it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1960d5cdbe0>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid_models = [EqGridRotorAvg(i) for i in range(1,10)]\n",
    "wd_lst = np.arange(240,301)\n",
    "\n",
    "def get_ws_eff(rotorAvgModel):\n",
    "    wfm = IEA37SimpleBastankhahGaussian(site,windTurbines,rotorAvgModel=rotorAvgModel)\n",
    "    return wfm([0, 200], [0, 0], wd=wd_lst, ws=10).WS_eff_ilk[1,:,0]\n",
    "\n",
    "ws_ref = get_ws_eff(EqGridRotorAvg(200)) # Use 200x200 points (31700 inside the rotor) to determine the reference value\n",
    "\n",
    "def get_n_err(rotorAvgModel):\n",
    "    ws_mean_err = np.abs(get_ws_eff(rotorAvgModel) - ws_ref).mean()\n",
    "    return len(rotorAvgModel.nodes_x), ws_mean_err\n",
    "        \n",
    "\n",
    "plt.gca().axhline(0, color='grey',ls='--')\n",
    "plt.plot(*zip(*[get_n_err(m) for m in grid_models]), label='Grid_x')\n",
    "model_lst = [('RotorCenter', EqGridRotorAvg(1)),\n",
    "             ('Grid_4', EqGridRotorAvg(4)),             \n",
    "             ('PolarGrid_4,10', PolarGridRotorAvg(*polar_gauss_quadrature(4,10))),\n",
    "             ('GQGrid_4,3', GQGridRotorAvg(4, 3))] + \\\n",
    "            [('CGI_%d'%n, CGIRotorAvg(n)) for n in [4,7,9,21]]\n",
    "for name, model in model_lst:\n",
    "    n,err = get_n_err(model)\n",
    "    plt.plot(n,err,'.',ms=10, label=\"%s (%.4f)\"%(name,err))\n",
    "plt.xlabel('Number of rotor-average points')\n",
    "plt.ylabel('Mean abs error (270$\\pm30^\\circ$) [m/s]')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deflection models\n",
    "The deflection models calculate the deflection of the wake due to yaw-misalignment, sheared inflow etc.\n",
    "The deflection models take as input the downwind and crosswind distances between the source wind turbines and the destination wind turbines/sites and calculate a new set of deflected downwind and crosswind distances."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### JimenezWakeDeflection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `JimenezWakeDeflection` model is implemented according to Jiménez, Á., Crespo, A. and Migoya, E. (2010), Application of a LES technique to characterize the wake deflection of a wind turbine in yaw. Wind Energ., 13: 559-572. doi:10.1002/we.380"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x231ecf3ae50>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake import IEA37SimpleBastankhahGaussian\n",
    "from py_wake.deflection_models import JimenezWakeDeflection\n",
    "from py_wake.examples.data.iea37._iea37 import IEA37Site, IEA37_WindTurbines\n",
    "\n",
    "site = IEA37Site(16)\n",
    "x, y = [0, 600, 1200], [0, 0, 0]  # site.initial_position[:2].T\n",
    "windTurbines = IEA37_WindTurbines()\n",
    "iea_deflection = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=JimenezWakeDeflection())\n",
    "\n",
    "yaw_ilk = np.reshape([-30,30,0],(3,1,1))\n",
    "\n",
    "plt.figure(figsize=(14,3))\n",
    "iea_deflection(x, y, yaw_ilk=yaw_ilk, wd=270, ws=10).flow_map().plot_wake_map()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Implement your own deflection models\n",
    "\n",
    "Deficit models must subclass `DeficitModel` and thus must implement the `calc_deflection` method and a class variable, `args4deflection` specifying the arguments required by its calc_deflection method\n",
    "\n",
    "```python\n",
    "\n",
    "class DeflectionModel(ABC):\n",
    "    args4deflection = [\"ct_ilk\"]\n",
    "\n",
    "    @abstractmethod\n",
    "    def calc_deflection(self, dw_ijl, hcw_ijl, **kwargs):\n",
    "        \"\"\"Calculate deflection\n",
    "\n",
    "        This method must be overridden by subclass\n",
    "\n",
    "        Arguments required by this method must be added to the class list\n",
    "        args4deflection\n",
    "\n",
    "        See documentation of EngineeringWindFarmModel for a list of available input arguments\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        dw_ijlk : array_like\n",
    "            downwind distance from source wind turbine(i) to destination wind turbine/site (j)\n",
    "            for all wind direction (l) and wind speed (k)\n",
    "        hcw_ijlk : array_like\n",
    "            horizontal crosswind distance from source wind turbine(i) to destination wind turbine/site (j)\n",
    "            for all wind direction (l) and wind speed (k)\n",
    "        \"\"\"\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x24a30799550>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.deflection_models import DeflectionModel\n",
    "from numpy import newaxis as na\n",
    "class MyDeflectionModel(DeflectionModel):\n",
    "    args4deficit = ['dw_ijlk', 'cw_ijlk']\n",
    "\n",
    "    def calc_deflection(self, dw_ijl, hcw_ijl, **_):\n",
    "        dw_ijlk = dw_ijl[..., na] # add extra wind speed dimension\n",
    "        hcw_ijlk =hcw_ijl[..., na] + .1*dw_ijlk # deflect 1/10 of the downstream distance\n",
    "        return dw_ijlk, hcw_ijlk\n",
    "\n",
    "iea_my_deflection = IEA37SimpleBastankhahGaussian(site, windTurbines, deflectionModel=MyDeflectionModel())\n",
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "iea_my_deflection(x, y, wd=270, ws=10).flow_map().plot_wake_map()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Turbulence models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# methods to plot turbulence map, used below to visualize and compare the deficit models\n",
    "   \n",
    "def plot_turb_map(turbulenceModel):\n",
    "    xy = np.linspace(-200,500,200), np.linspace(-200,200,200)\n",
    "    X,Y,deficit = _map(turbulenceModel.calc_added_turbulence, xy)\n",
    "    c = plt.contourf(X,Y,deficit, levels=100, cmap='Blues')\n",
    "    plt.colorbar(c, label=\"Turbulence intensity [-]\")\n",
    "    plt.plot([0,0],[-1/2,1/2],'k')\n",
    "    plt.ylabel(\"Crosswind distance [y/D]\")\n",
    "    plt.xlabel(\"downwind distance [x/D]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### STF2005TurbulenceModel\n",
    "\n",
    "Steen Frandsen model implemented according to IEC61400-1, 2005"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.turbulence_models import STF2005TurbulenceModel\n",
    "plot_turb_map(STF2005TurbulenceModel())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### STF2017TurbulenceModel\n",
    "\n",
    "Steen Frandsen model implemented according to IEC61400-1, 2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.turbulence_models import STF2017TurbulenceModel\n",
    "plot_turb_map(STF2005TurbulenceModel())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GCLTurbulence\n",
    "\n",
    "Gunner Chr. Larsen model implemented according to \n",
    "    \n",
    "    Pierik, J. T. G., Dekker, J. W. M., Braam, H., Bulder, B. H., Winkelaar, D., Larsen, G. C., Morfiadakis, E., Chaviaropoulos, P., Derrick, A., & Molly, J. P. (1999). European wind turbine standards II (EWTS-II). In E. L. Petersen, P. Hjuler Jensen, K. Rave, P. Helm, & H. Ehmann (Eds.), Wind energy for the next millennium. Proceedings (pp. 568-571). James and James Science Publishers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.turbulence_models import GCLTurbulence\n",
    "plot_turb_map(GCLTurbulence())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### CrespoHernandez\n",
    "\n",
    "    Implemented according to:\n",
    "    A. Crespo and J. Hernández\n",
    "    Turbulence characteristics in wind-turbine wakes\n",
    "    J. of Wind Eng. and Industrial Aero. 61 (1996) 71-85"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from py_wake.turbulence_models import CrespoHernandez\n",
    "plot_turb_map(CrespoHernandez())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare Turbulence models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "turbulenceModels = [STF2005TurbulenceModel(),\n",
    "                 STF2017TurbulenceModel(),\n",
    "                 GCLTurbulence(),\n",
    "                 CrespoHernandez()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**turbulence intensity along center line**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24a30ff09a0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=((10,6)))\n",
    "for turbulenceModel in turbulenceModels:\n",
    "    X, Y, ti = _map(turbulenceModel.calc_added_turbulence, xy=(np.linspace(-200,500,300), 0))\n",
    "    plt.plot(X[0], ti[0], label=turbulenceModel.__class__.__name__)\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Deficit profile 2D downstream**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24a31665ca0>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=((10,6)))\n",
    "for turbulenceModel in turbulenceModels:\n",
    "    X, Y, ti = _map(turbulenceModel.calc_added_turbulence, xy=(2*D, np.linspace(-200,200,300)))\n",
    "    plt.plot(Y[:,], ti[:,0], label=turbulenceModel.__class__.__name__)\n",
    "\n",
    "plt.legend()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "373.333px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}