topfarm_type_example.ipynb

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  "metadata": {
    "colab": {
      "name": "Untitled5.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNDP9hSUGkaIX2qyXHbTHbK",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mifm/examples/blob/master/topfarm_type_example.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wkRAPCcjNtGr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/TopFarm2.git"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uE3R9HlKNxM8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 919
        },
        "outputId": "976c51ca-1d53-4a4e-f270-b89aa80dd6e7"
      },
      "source": [
        "\"\"\"Example: optimizing a layout with constraints\n",
        "\n",
        "This example uses a dummy cost function to optimize turbine types. \n",
        "\"\"\"\n",
        "import numpy as np\n",
        "import os\n",
        "from topfarm.cost_models.dummy import DummyCost\n",
        "from topfarm._topfarm import TopFarmProblem\n",
        "from openmdao.drivers.doe_generators import FullFactorialGenerator\n",
        "from topfarm.plotting import TurbineTypePlotComponent, NoPlot\n",
        "\n",
        "\n",
        "# ------------------------ INPUTS ------------------------\n",
        "\n",
        "# define the conditions for the wind farm\n",
        "positions = np.array([[0, 0], [6, 6]])  # initial turbine pos\n",
        "optimal_types = np.array([[2], [6]])  # optimal layout\n",
        "\n",
        "# ===============================================================================\n",
        "# Setup the problem and plotting\n",
        "# ===============================================================================\n",
        "\n",
        "try:\n",
        "    import matplotlib.pyplot as plt\n",
        "    plt.gcf()\n",
        "    plot_comp = TurbineTypePlotComponent(\n",
        "        turbine_type_names=[\"Turbine %d\" % i for i in range(10)],\n",
        "        plot_initial=False,\n",
        "        delay=0.1, legendloc=0)\n",
        "    plot = True\n",
        "except RuntimeError:\n",
        "    plot_comp = NoPlot()\n",
        "    plot = False\n",
        "\n",
        "# create the wind farm\n",
        "tf = TopFarmProblem(\n",
        "    design_vars={'type': ([0, 0], 0, 9)},\n",
        "    cost_comp=DummyCost(optimal_types, ['type']),\n",
        "    plot_comp=plot_comp,\n",
        "    driver=FullFactorialGenerator(10))\n",
        "\n",
        "# ===============================================================================\n",
        "# #  Run the optimization\n",
        "# ===============================================================================\n",
        "state = {'x': positions[:, 0], 'y': positions[:, 1]}\n",
        "cost, state, recorder = tf.optimize(state)\n",
        "\n",
        "# ===============================================================================\n",
        "# plot and prin the the final, optimal types\n",
        "# ===============================================================================\n",
        "print(state['type'])\n",
        "tf.evaluate(state)\n",
        "\n",
        "\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING: The following inputs are not connected:\n",
            "   penalty: ['cost_comp.penalty']\n",
            "   x: ['plot_comp.x']\n",
            "   y: ['plot_comp.y']\n",
            "\n",
            "WARNING: The following inputs are not connected:\n",
            "   penalty: ['cost_comp.penalty']\n",
            "   x: ['plot_comp.x']\n",
            "   y: ['plot_comp.y']\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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tGzt27FCiaQd3Z8eOHXTr1i3VoYhIEiXtro+8vDwqKiqoqqpK1iEzUrdu3cjL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\niVpEJOSUqEVEQk6JWkQk5JSoRURC7v8DwjPTvyhhSCsAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING: The following inputs are not connected:\n",
            "   penalty: ['cost_comp.penalty']\n",
            "   x: ['plot_comp.x']\n",
            "   y: ['plot_comp.y']\n",
            "\n",
            "[2. 6.]\n",
            "WARNING: The following inputs are not connected:\n",
            "   penalty: ['cost_comp.penalty']\n",
            "   x: ['plot_comp.x']\n",
            "   y: ['plot_comp.y']\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0.0, {'type': array([2., 6.])})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Z3n333cQ7IyJZK7Qj6uXLl7NgwYLAkjSEq8wpROapIfIfxrRp0ygtLT3IHolI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\n5P4/VGqDUDz4B0cAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wjYRDAhcOzME",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}