notebooks/tanuki.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPvxXPWxvX7OO9QbtvwFYFA",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kishiyamat/la-kentei-yaminabe/blob/main/notebooks/tanuki.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# タヌキと法の裁き\n",
        "\n",
        "タヌキはムジナと弁別しづらいのか調査する。\n",
        "ただし、弁別のしづらさは相対的なものとするので、\n",
        "キツネとタヌキの弁別のしづらさから考察する。"
      ],
      "metadata": {
        "id": "RyYDyAbJdjGe"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## データのダウンロード\n",
        "\n",
        "一時的に作成している環境にダウンロードするだけなので、\n",
        "実行しても環境は汚染されません。"
      ],
      "metadata": {
        "id": "zq5uzv0Lvaqq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "from zipfile import ZipFile\n",
        "\n",
        "# 1. Google Driveからファイルをダウンロードする関数\n",
        "def download_from_google_drive(file_id, filename):\n",
        "    download_url = f\"https://drive.google.com/uc?id={file_id}\"\n",
        "    response = requests.get(download_url, stream=True)\n",
        "    response.raise_for_status()\n",
        "    with open(filename, \"wb\") as f:\n",
        "        for chunk in response.iter_content(chunk_size=8192):\n",
        "            f.write(chunk)\n",
        "\n",
        "# 2. Zipファイルをダウンロード\n",
        "zip_filename = \"tanuki.zip\"\n",
        "file_id = \"1X8Jd4UDlglztXAfMJqaQysdYzClb_L__\"\n",
        "download_from_google_drive(file_id, zip_filename)\n",
        "\n",
        "# 3. Zipファイルを解凍\n",
        "with ZipFile(zip_filename, 'r') as zip_ref:\n",
        "    zip_ref.extractall(\"tanuki\")\n"
      ],
      "metadata": {
        "id": "aCZbzUoFvDb8"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import matplotlib.pyplot as plt\n",
        "from PIL import Image\n",
        "from sklearn.cluster import KMeans\n",
        "from plotnine import *\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "import glob\n",
        "from pathlib import Path\n",
        "\n",
        "# ファイルのリストを取得(FIXME: zipにする)\n",
        "image_path_list = glob.glob('/content/tanuki/images/*.png')\n",
        "\n",
        "# ディレクトリ内の画像ファイルを読み込む\n",
        "images = []\n",
        "labels = []\n",
        "res = 32\n",
        "for file in image_path_list:\n",
        "    assert file.endswith('.png')\n",
        "    img = Image.open(file).convert('L')  # グレースケールで読み込む\n",
        "    img = img.resize((res, res))  # すべての画像を同じサイズにリサイズ\n",
        "    images.append(np.array(img).flatten())  # 1次元配列に変換\n",
        "    labels.append(Path(file).stem.split(\"_\")[0])  # ラベルを取得"
      ],
      "metadata": {
        "id": "impEw43GTINd"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "idxs = 20, 40, 50,\n",
        "imgs = np.hstack([images[idx].reshape((res,res)) for idx in idxs])\n",
        "plt.imshow(imgs, cmap='gray')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 245
        },
        "id": "HvX0kCroWmXZ",
        "outputId": "7c123ced-2ae4-44ec-ed79-2897186ff77d"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7cf7934f3b50>"
            ]
          },
          "metadata": {},
          "execution_count": 3
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## クラスタリング"
      ],
      "metadata": {
        "id": "VbOc7sHCI4my"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(images)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DF5EkoGfJzUa",
        "outputId": "8b5d20e7-9a32-45d4-b8bd-be1ef177714f"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "144"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "labels[:6]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KVRxeleoKcA5",
        "outputId": "2209bbd2-1783-407e-b0be-26ea4033d8e0"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['ANG', 'ANG', 'ANG', 'TNK', 'ANG', 'ANG']"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def shape(lab):\n",
        "    if lab==\"KTN\":\n",
        "        return \"   |v|      \"\n",
        "    if lab==\"TNK\":\n",
        "        return \"|o|            \"\n",
        "    if lab==\"ANG\":\n",
        "        return \"|x|\""
      ],
      "metadata": {
        "id": "_XUVSMfLNFtZ"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from scipy.cluster.hierarchy import linkage, dendrogram\n",
        "\n",
        "# 階層的クラスタリング（ユークリッド距離を使用）\n",
        "Z = linkage(np.array(images), method='ward', metric='euclidean')\n",
        "\n",
        "label_shapes = list(map(shape, labels))\n",
        "# デンドログラムの作成\n",
        "plt.figure(figsize=(3, 3))\n",
        "dendrogram(Z, labels=label_shapes)\n",
        "plt.title(\"Hierarchical Clustering Dendrogram\")\n",
        "plt.xlabel('Data Points')\n",
        "plt.ylabel('Distance')\n",
        "# plt.show()\n",
        "\n",
        "plt.savefig('dendrogram.png', dpi=600, bbox_inches='tight')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "8z_-vC-YLHnq",
        "outputId": "1b80b605-51fe-4f7d-cdbe-f14b02e21243"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 300x300 with 1 Axes>"
            ],
            "image/png": 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S4Obmhl27dgn625csWYLU1FT06NEDEyZMQEhICAoLC3HmzBn8/vvvBo/DtbOzw4IFC/DGG29gwIABeOmll5CZmYn169dr7WMWy2Pp0qWIi4tDv3798Morr/DD5QICAjBt2jQ+7aJFizB8+HD06tULcXFxePDgAb744gt06tRJ72PV3Me7SfQev1EPcMPlTp06JTq/X79+tQ6XY4yxhw8fslmzZrGgoCBmb2/PWrRowZ599ln26aefssrKSsbYP0NmxIZkKZVKtmjRIubv78/kcjnr2rUr2717t8bwL115MMbY+fPn2fPPP8/c3d2Zg4MDa9++PZs9ezY/nxsuV1BQILodMjMzddbz/v37bMqUKax169bM3t6e+fr6sjFjxvBDpvStB2P6DZfjPHjwgCUkJLDOnTszJycn5uDgwDp16sRmzZrF7ty5w6cTW09BQQGLiYlhTk5OzMPDg73xxhvs/PnzgmFk9+7dY/Hx8Sw4OJg5OzszNzc31qNHD7Zt2zZBXnl5eSw6Opo1bdpUYwiXqceAtuFyzs7OGmm5/ahez1dffZU1bdqUubm5sbFjx7KjR48yAOyHH37QuX254Wfcn52dHWvZsiXr27cvW7hwocYwMU5+fj6Lj49nfn5+zM7Ojnl7e7OBAweydevWaeStPhRPrL6MMbZ27VoWGBjI5HI5CwsLY4cPH2b9+vUTHS6nbXjf1q1bWdeuXZlcLmfNmjVjsbGx7NatWxrpfvjhBxYcHMzkcjnr1KkTS0pKYjExMSw4OFijnJb43GqrR21xSYyMMTN9NyaEWNRPP/2E559/HkeOHEGvXr2sXZx6oUuXLmjZsiWSk5OtXRSDUB8zIRJUVlYmeF9TU4PPP/8crq6u6Natm5VKJV1VVVUaff8HDx5EWlpavXzEKPUxEyJBb775JsrKyhAeHo6Kigrs3LkTx44dw6JFi+p0WFl9kZubi8jISLz22mto1aoVLl26hMTERHh7e2vc0FMfUFcGIRK0ZcsWLF++HNeuXUN5eTmCgoIwefJkTJkyxdpFk6Ti4mJMnDgRR48eRUFBAZydnTFw4EAsWbIE7dq1s3bxDEaBmRBCJIb6mAkhRGIoMBNCiMTQxT8zUSqVuH37Npo2bar3DQCEkLrDGMPDhw/RqlUrSfzMmi4UmM3k9u3bRj2YhxBSt3JycuDr62vtYuhEgdlMuEco5uTkaH3UJiHEehQKBfz8/OrkmeCmosBsJlz3haurKwVmQiSsPnQ1SrujhRBCGiEKzIQQIjEUmAkhRGIoMBNCiMRQYCaEEImhwEwIIRJDw+WIKMYYyqo0f32aEABwtLOtF8PO6isKzEQDYwwvJh7H6ZsPrF0UIlFh/h7YPimcgrOFUFcG0VBWVUNBmej0180H9I3KgqjFTHT666NIONnbWrsYRCJKK2sQtuB3axejwaPATHRysreFkz0dJoTUJerKIIQQiaHATAghEmPVwHz48GEMGzYMrVq1gkwmw08//SSYzxhDQkICfHx84OjoiMjISFy9elWQprCwELGxsXB1dYW7uzvGjx+PkpISQZpz586hT58+cHBwgJ+fH5YtW6ZRlu3btyM4OBgODg7o3Lkz9u7da/b6EkKIPqwamB89eoTQ0FCsWbNGdP6yZcuwevVqJCYm4sSJE3B2dkZUVBTKy8v5NLGxscjIyEBycjJ2796Nw4cPY+LEifx8hUKBQYMGwd/fH6dPn8Ynn3yCOXPmYN26dXyaY8eO4ZVXXsH48ePx999/Y8SIERgxYgTOnz9vucoTQog2TCIAsF27dvHvlUol8/b2Zp988gk/raioiMnlcvb9998zxhi7cOECA8BOnTrFp9m3bx+TyWQsNzeXMcbY2rVrmYeHB6uoqODTzJw5k7Vv355/P2rUKBYdHS0oT48ePdgbb7yhd/mLi4sZAFZcXKz3MlL1qKKK+c/czfxn7maPKqqsXRwiIfX52KhPn1HJ9jFnZmYiLy8PkZGR/DQ3Nzf06NEDx48fBwAcP34c7u7uCAsL49NERkbCxsYGJ06c4NP07dsX9vb2fJqoqChcvnwZDx484NOorodLw61HTEVFBRQKheCPEELMQbKBOS8vDwDg5eUlmO7l5cXPy8vLg6enp2B+kyZN0KxZM0EasTxU16EtDTdfzOLFi+Hm5sb/0e/9EULMRbKBWepmzZqF4uJi/i8nJ8faRSKENBCSDcze3t4AgPz8fMH0/Px8fp63tzfu3r0rmF9dXY3CwkJBGrE8VNehLQ03X4xcLud/349+548QYk6SDcyBgYHw9vZGSkoKP02hUODEiRMIDw8HAISHh6OoqAinT5/m0xw4cABKpRI9evTg0xw+fBhVVVV8muTkZLRv3x4eHh58GtX1cGm49RBCSF2yamAuKSnB2bNncfbsWQCPL/idPXsW2dnZkMlkmDp1KhYsWICkpCSkp6dj9OjRaNWqFUaMGAEA6NChAwYPHowJEybg5MmTOHr0KKZMmYKXX34ZrVq1AgC8+uqrsLe3x/jx45GRkYGtW7di1apVmD59Ol+Ot99+G/v378fy5ctx6dIlzJkzB3/99RemTJlS15uEEEKsO1wuNTWVAdD4GzNmDGPs8ZC52bNnMy8vLyaXy9nAgQPZ5cuXBXncv3+fvfLKK8zFxYW5urqyuLg49vDhQ0GatLQ01rt3byaXy1nr1q3ZkiVLNMqybds29uSTTzJ7e3vWsWNHtmfPHoPqUp+G4tSmPg+JIpZVn4+N+vQZlTHGmBXPCw2GQqGAm5sbiouL631/c2llNUISfgUAXJgXRQ8xIrz6fGzUp8+oZPuYCSGksaLATAghEkOBmRBCJIYCMyGESAwFZkIIkRgKzIQQIjEUmAkhRGIoMBNCiMRQYCaEEImhwEwIIRJDgZkQQiSGAjMhhEgMBWZCCJEYCsyEECIxFJgJIURiKDATQojEUGAmhBCJocBMCCESQ4GZEEIkhgIzIYRIDAVmQgiRGArMhBAiMRSYCSFEYigwE0KIxFBgJoQQiaHATAghEkOBmRBCJIYCMyGESAwFZkIIkRgKzIQQIjEUmAkhRGIkHZhramowe/ZsBAYGwtHREe3atcP8+fPBGOPTMMaQkJAAHx8fODo6IjIyElevXhXkU1hYiNjYWLi6usLd3R3jx49HSUmJIM25c+fQp08fODg4wM/PD8uWLauTOhJCiDpJB+alS5fiyy+/xBdffIGLFy9i6dKlWLZsGT7//HM+zbJly7B69WokJibixIkTcHZ2RlRUFMrLy/k0sbGxyMjIQHJyMnbv3o3Dhw9j4sSJ/HyFQoFBgwbB398fp0+fxieffII5c+Zg3bp1dVpfQggBADAJi46OZuPGjRNMe+GFF1hsbCxjjDGlUsm8vb3ZJ598ws8vKipicrmcff/994wxxi5cuMAAsFOnTvFp9u3bx2QyGcvNzWWMMbZ27Vrm4eHBKioq+DQzZ85k7du317usxcXFDAArLi42vKIS86iiivnP3M38Z+5mjyqqrF0cIiH1+dioT59RSbeYn332WaSkpODKlSsAgLS0NBw5cgRDhgwBAGRmZiIvLw+RkZH8Mm5ubujRoweOHz8OADh+/Djc3d0RFhbGp4mMjISNjQ1OnDjBp+nbty/s7e35NFFRUbh8+TIePHggWraKigooFArBHyGEmEMTaxdAl/fffx8KhQLBwcGwtbVFTU0NFi5ciNjYWABAXl4eAMDLy0uwnJeXFz8vLy8Pnp6egvlNmjRBs2bNBGkCAwM18uDmeXh4aJRt8eLFmDt3rhlqSQghQpJuMW/btg2bN2/Gli1bcObMGWzcuBGffvopNm7caO2iYdasWSguLub/cnJyrF0kQkgDIekW87vvvov3338fL7/8MgCgc+fOuHnzJhYvXowxY8bA29sbAJCfnw8fHx9+ufz8fHTp0gUA4O3tjbt37wryra6uRmFhIb+8t7c38vPzBWm491wadXK5HHK53PRKEkKIGkm3mEtLS2FjIyyira0tlEolACAwMBDe3t5ISUnh5ysUCpw4cQLh4eEAgPDwcBQVFeH06dN8mgMHDkCpVKJHjx58msOHD6OqqopPk5ycjPbt24t2YxBCiCVJOjAPGzYMCxcuxJ49e5CVlYVdu3ZhxYoVeP755wEAMpkMU6dOxYIFC5CUlIT09HSMHj0arVq1wogRIwAAHTp0wODBgzFhwgScPHkSR48exZQpU/Dyyy+jVatWAIBXX30V9vb2GD9+PDIyMrB161asWrUK06dPt1bVCSGNmbWHheiiUCjY22+/zdq0acMcHBxY27Zt2YcffigY1qZUKtns2bOZl5cXk8vlbODAgezy5cuCfO7fv89eeeUV5uLiwlxdXVlcXBx7+PChIE1aWhrr3bs3k8vlrHXr1mzJkiUGlbU+DcWpTX0eEkUsqz4fG/XpMypjTOU2OmI0hUIBNzc3FBcXw9XV1drFMUlpZTVCEn4FAFyYFwUne0lfiiB1qD4fG/XpMyrprgxCCGmMKDATQojE1J/vIYQQozDGUFZVY5a8SiurRV+bytHOFjKZzGz51XcUmAlpwBhjeDHxOE7fFH+0gCnCFqTUnkjfvPw9sH1SOAXn/6GuDEIasLKqGosEZXP76+YDs7XqGwJqMRPSSPz1USSc7G2tXQyB0soahC343drFkBwKzIQ0Ek72tvVqeFtjRl0ZhBAiMRSYCSFEYigwE0KIxFBgJoQQiaHATAghEkOBmRBCJIYCMyGESAwFZkIIkRgKzIQQIjEUmAkhRGIoMBNCiMRQYCaEEIkxOTCXl5eboxyEEEL+x6jArFQqMX/+fLRu3RouLi64ceMGAGD27Nn45ptvzFpAQghpbIwKzAsWLMCGDRuwbNky2Nvb89M7deqEr7/+2myFI4SQxsiowPzdd99h3bp1iI2Nha3tPw/eDg0NxaVLl8xWOEIIaYyMCsy5ubkICgrSmK5UKlFVVWVyoQghpDEzKjCHhITgjz/+0Jj+448/omvXriYXihBCGjOjfmcmISEBY8aMQW5uLpRKJXbu3InLly/ju+++w+7du81dRkIIaVSMajEPHz4cv/zyC37//Xc4OzsjISEBFy9exC+//IJ//etf5i4jIYQ0Kkb/MmOfPn2QnJxszrIQQgiBkS3mU6dO4cSJExrTT5w4gb/++svkQhFCSGNmVIs5Pj4e7733Hnr06CGYnpubi6VLl4oGbaIDY0BVqbVL8Y/KGpXXpQBstSa1CjsnQCazdikIsRijAvOFCxfQrVs3jeldu3bFhQsXTC5Uo8IY8G0UkCOhkxmTA1j/+PUnQYCswqrF0eDXExi3n4IzabCM6sqQy+XIz8/XmH7nzh00aWJ0t7Wo3NxcvPbaa2jevDkcHR3RuXNnQXcJYwwJCQnw8fGBo6MjIiMjcfXqVUEehYWFiI2NhaurK9zd3TF+/HiUlJQI0pw7dw59+vSBg4MD/Pz8sGzZMrPWQ6uqUmkFZQBOsgpkObyKLIdX4SS1oAwAOX9K6xsGIWZmVBQdNGgQZs2ahZ9//hlubm4AgKKiInzwwQdmHZXx4MED9OrVC/3798e+ffvQsmVLXL16FR4eHnyaZcuWYfXq1di4cSMCAwMxe/ZsREVF4cKFC3BwcAAAxMbG4s6dO0hOTkZVVRXi4uIwceJEbNmyBQCgUCgwaNAgREZGIjExEenp6Rg3bhzc3d0xceJEs9WnVjOuAfZOdbe++qayFPhU88YmQhocZoRbt26xtm3bMjc3NxYREcEiIiKYu7s7a9++PcvOzjYmS1EzZ85kvXv31jpfqVQyb29v9sknn/DTioqKmFwuZ99//z1jjLELFy4wAOzUqVN8mn379jGZTMZyc3MZY4ytXbuWeXh4sIqKCsG627dvr3dZi4uLGQBWXFys9zKMMcYqShj72PXxX0WJYcs2NrStDPaooor5z9zN/GfuZo8qqqxdHA11WT6jP6NWYFRXRuvWrXHu3DksW7YMISEh6N69O1atWoX09HT4+fmZ7aSRlJSEsLAwjBw5Ep6enujatSu++uorfn5mZiby8vIQGRnJT3Nzc0OPHj1w/PhxAMDx48fh7u6OsLAwPk1kZCRsbGz4i5THjx9H3759BQ9kioqKwuXLl/HgwQPRslVUVEChUAj+CCHEHIzuEHZ2drb41/wbN27gyy+/xPTp0/HBBx/g1KlTeOutt2Bvb48xY8YgLy8PAODl5SVYzsvLi5+Xl5cHT09PwfwmTZqgWbNmgjSBgYEaeXDzVLtOOIsXL8bcuXPNU1FCCFFhdGC+evUqUlNTcffuXSiVSsG8hIQEkwsGPH4oUlhYGBYtWgTg8aiP8+fPIzExEWPGjDHLOow1a9YsTJ8+nX+vUCjM+m2BENJ4GRWYv/rqK0yePBktWrSAt7c3ZCrDlmQymdkCs4+PD0JCQgTTOnTogB07dgAAvL29AQD5+fnw8fHh0+Tn56NLly58mrt37wryqK6uRmFhIb+8t7e3xigT7j2XRp1cLodcLjeyZvWUtcdbV5aKv65rNI6aWJhRgXnBggVYuHAhZs6cae7yCPTq1QuXL18WTLty5Qr8/f0BAIGBgfD29kZKSgofiBUKBU6cOIHJkycDAMLDw1FUVITTp0+je/fuAIADBw5AqVTyN8iEh4fjww8/RFVVFezs7AAAycnJaN++vWg3RqMktfHW1hydQeOoiYUZdfHvwYMHGDlypLnLomHatGn4888/sWjRIly7dg1btmzBunXrEB8fD+Bx63zq1KlYsGABkpKSkJ6ejtGjR6NVq1YYMWIEgMct7MGDB2PChAk4efIkjh49iilTpuDll19Gq1atAACvvvoq7O3tMX78eGRkZGDr1q1YtWqVoKui0ZPgeGuroXHUxMKMajGPHDkSv/32GyZNmmTu8gg8/fTT2LVrF2bNmoV58+YhMDAQK1euRGxsLJ/mvffew6NHjzBx4kQUFRWhd+/e2L9/Pz+GGQA2b96MKVOmYODAgbCxsUFMTAxWr17Nz3dzc8Nvv/2G+Ph4dO/eHS1atEBCQkLdjmGuTxrreGsaR03qiFGBOSgoCLNnz8aff/6Jzp0781//OW+99ZZZCgcAQ4cOxdChQ7XOl8lkmDdvHubNm6c1TbNmzfibSbR56qmnRB/+T0TYOwH2ztYuBSENllGBed26dXBxccGhQ4dw6NAhwTyZTGbWwEyIxRh6MdPUi4900ZDoyajAnJmZae5yEFK3TL2YaUyXBl00JHoy6uIfIfWeNS5m0kVDoiejbzC5desWkpKSkJ2djcrKSsG8FStWmFwwQuqMpS9m0kVDYiCjAnNKSgqee+45tG3bFpcuXUKnTp2QlZUFxpjoc5oJkTS6mEkkxqiujFmzZmHGjBlIT0+Hg4MDduzYgZycHPTr169OxjcTQkhDZlRgvnjxIkaPHg3g8QOBysrK4OLignnz5mHp0qVmLSAhhDQ2RgVmZ2dnvl/Zx8cH169f5+fdu3fPPCUjhJBGyqg+5p49e+LIkSPo0KED/u///g/vvPMO0tPTsXPnTvTs2dPcZSSEkEbFqMC8YsUK/jfz5s6di5KSEmzduhVPPPEEjcgghBATGRWY27Zty792dnZGYmKi2QpECCGNnVF9zG3btsX9+/c1phcVFQmCNiGEEMMZFZizsrJQU1OjMb2iogK5ubkmF4oQQhozg7oykpKS+Ne//vor3Nzc+Pc1NTVISUlBQECA2QpHCCGNkUGBmXv4vEwm0/jNPTs7OwQEBGD58uVmKxwhhDRGBgVm7kdXAwMDcerUKbRo0cIihSKEkMbMbI/9LCoqgru7u6nlIYSQRs+oi39Lly7F1q1b+fcjR45Es2bN0Lp1a6SlpZmtcIQQ0hgZFZgTExPh5+cH4PGvSf/+++/Yv38/hgwZgnfffdesBSSEkMbGqK6MvLw8PjDv3r0bo0aNwqBBgxAQEIAePXqYtYCEENLYGNVi9vDwQE5ODgBg//79iIyMBAAwxkTHNxNCCNGfUS3mF154Aa+++iqeeOIJ3L9/H0OGDAEA/P333wgKol9qIIQQUxgVmD/77DMEBAQgJycHy5Ytg4uLCwDgzp07+M9//mPWAhJCSGNjVGC2s7PDjBkzNKZPmzbN5AKROsKYYT8MWlkq/lpfdk7069CE6EnvwJyUlIQhQ4bAzs5OcGu2mOeee87kghELYgz4Nsr4X4k25odF/XoC4/ZTcCZED3oH5hEjRiAvLw+enp78rdliZDIZXQCUuqpS44OysXL+fLxe+tFTQmqld2DmbsdWf03quRnXHv9KtKVUlhrXwiakETO4j1mpVGLDhg3YuXMnsrKyIJPJ0LZtW8TExOD111+HjL6q1i/2TtSKJURiDArMjDE899xz2Lt3L0JDQ9G5c2cwxnDx4kWMHTsWO3fuxE8//WShohJCpIwxBlZWZtAyysp/uj2VpWVQVtsatLzM0bFBNgYNCswbNmzA4cOHkZKSgv79+wvmHThwACNGjMB3332H0aNHm7WQhBBpY4zh5quxKPv7b4OWK7e1B4YtAgBc7dUbDjWVBi3v2K0b/DdvanDB2aDA/P333+ODDz7QCMoAMGDAALz//vvYvHkzBWaOPkPSDB2GRsPOiASxsjKDgzIAONRUYt9PmkNv9VV25gxYWRlkTha8TmIFBgXmc+fOYdmyZVrnDxkyBKtXrza5UA2CMUPS9LlIRsPOiMQ9cfQIbBwdLboOZVkZrvbqbdF1WJNBz8ooLCyEl5eX1vleXl548OCByYXSZsmSJZDJZJg6dSo/rby8HPHx8WjevDlcXFwQExOD/Px8wXLZ2dmIjo6Gk5MTPD098e6776K6ulqQ5uDBg+jWrRvkcjmCgoKwYcMG0wprqSFp3LAzQiTKxtERNk5Olv2zcOC3NoNazDU1NWjSRPsitra2GgHPXE6dOoX/9//+H5566inB9GnTpmHPnj3Yvn073NzcMGXKFLzwwgs4evQoX+bo6Gh4e3vj2LFjuHPnDkaPHg07OzssWvS4byszMxPR0dGYNGkSNm/ejJSUFPz73/+Gj48PoqKiTC+8OYak0bAzQhoNg0dljB07FnK5XHR+RUWFWQqlrqSkBLGxsfjqq6+wYMECfnpxcTG++eYbbNmyBQMGDAAArF+/Hh06dMCff/6Jnj174rfffsOFCxfw+++/w8vLC126dMH8+fMxc+ZMzJkzB/b29khMTERgYCD/e4UdOnTAkSNH8Nlnn2kNzBUVFYL6KhQK7RWgIWmEEAMY1JUxZswYeHp6ws3NTfTP09PTIhf+4uPjER0dzT9elHP69GlUVVUJpgcHB6NNmzY4fvw4AOD48ePo3LmzoAsmKioKCoUCGRkZfBr1vKOiovg8xCxevFhQd+751KSRYwyofKT2p3aBV30+Y9YrL5Ekg1rM69evt1Q5tPrhhx9w5swZnDp1SmNeXl4e7O3tNX5r0MvLC3l5eXwa9X5x7n1taRQKBcrKyuAo0p81a9YsTJ8+nX+vUCgoODd2+lzwFeuOogu6RI1RT5erKzk5OXj77beRnJwMBwcHaxdHQC6Xa+3SIY2UsRd86TkiRI2kA/Pp06dx9+5ddOvWjZ9WU1ODw4cP44svvsCvv/6KyspKjV/ozs/Ph7e3NwDA29sbJ0+eFOTLjdpQTaM+kiM/Px+urq6irWVCaqXPBV+6oEu0MOqnperKwIEDkZ6ejrNnz/J/YWFhiI2N5V/b2dkhJSWFX+by5cvIzs5GeHg4ACA8PBzp6em4e/cunyY5ORmurq4ICQnh06jmwaXh8iDEYNwFX51/DeumCEtjjEFZWvr4T+XWb2VZGT+dNZD+ekm3mJs2bYpOnToJpjk7O6N58+b89PHjx2P69Olo1qwZXF1d8eabbyI8PBw9e/YEAAwaNAghISF4/fXXsWzZMuTl5eGjjz5CfHw83xUxadIkfPHFF3jvvfcwbtw4HDhwANu2bcOePXvqtsL1ib4P2qc7G4kZ6LrlW/VGk4Zyi7akA7M+PvvsM9jY2CAmJgYVFRWIiorC2rVr+fm2trbYvXs3Jk+ejPDwcDg7O2PMmDGYN28enyYwMBB79uzBtGnTsGrVKvj6+uLrr782zxjmhsjYB+1b685GsZNIbScMOkFIir63fDeUW7TrXWA+ePCg4L2DgwPWrFmDNWvWaF3G398fe/fu1ZlvREQE/jbiXv9GyZIP2jf3hTAaKdHgiN3y3dBu0a53gblB09U9oE+XgDVaeeZ60L6lLoTRSIkGh7vluyGjwCwVhnQPaAtg1mjl1ae7Gq05UoK6U4gBKDBLhTm6B6iVp5u1TiLUnUIMRIFZigztHqDxsNJG3SnEQBSYpag+dQ8Qw9CNJ0QPFJgJqUv19KRb2+/5qd/woUtD/Z0+c6LAbG7808VELuw05os5td2QYsiNKI15O1qBob/nV9uwtYZyE4glUWA2t/8+D9w7LZzGfS1trBdzDL0hpbav8Y11O1qJsb/np01DuQnEkigwm1vuX4BcS8BorBdzzH1DSmPdjhJgyu/5NbSbQCyJArOlqF7kkcrFHK47QVu3QV10EZhyQ4pUtmMj1hhu7pACCsyWIrWLPNq6E1QDXV10EUhtu5B6jbsoqe3iY3290EiBubHQpzuBughIPaLtomRDeNocBebGSL07gboIrE911Io1u5rMTHWYnblbtfpclKyvFxopMDdG1J0gLbpGrdR1V5MZ1eUzlNUvStb3C40UmOurBtrCElAf+6xrrHN9rqu+o1as0NXEGBNt6erTyq3LZyg3tIuSFJgtSdsoCFODSANtYQnUNvZZvevF1LrqGrFSl0FfbNSKlbqaxFq8XCvU0FZuY3iGsjlRYLYUXaMgTA0i5mhh1dbiFgtGdRm8DB37bEprsrYRK3V5gjOxm4kxhrLqf1q4pVU1Kq/LAJmtIL1jE+0tX10tXkNbuQ2tRWtpFJgtpapMe2Ax51dSY1pY+rS41YORNYOXrrHPuurKmH4nkdpOAvVktApjDKP3jcbZgrP/TFPaAZgPAIjY1g8ymyrBMl09u2Lj4I21tny5Fi+1cusGBea6wAUWS3wlNaaFpeukwVEPRtYMXsbUUexEos9JhNtXjAGl94FVTz2ebo4uKAsrqy4TBGUAkNlUoWmH97Uu8/fdv1FWXQYnO92tWWrx1i0KzHVByqMgjBk6J8W7GtXpOpHoOonYOz0OwGJBvR712R8cdRCOTTRvnWaMobymHGXVZRiycwgA8F0furo1SN2iwNzYGXPSkPKJRoyh31i0BfV60qUBPA6y6q1gsa4OAIjYFgFA/24NqRMbSSIz8vke1mJj7QKQBoh/9Cn3p9bPK5j36HF6S+JOJMY8o2PGtcd/plCtX2Wp5eurhVhXhyquW6M+40aSqPaDX+3VGzdjXwOz0nY3BrWYpUDfi1T1gaHD3IC66SJQ38b6fkhN/QVwxoDvhv/z3tAuEbFjwwzHhWpXR1l1Gd9qru+0jSQpO3MG7rU8wF9KKDBbm7EXqaTKmEd8WrqLQGwbfzcC+Hey5bdtVenjR8GqUq2vrsCr7dgww3Eh1tXR0Dxx9AiA2h/cL0UUmK3N2ItU9YGuYW51OepBbBRK7inzblt9WuRvpwGrQoVpdAXeBtDXbU3GPjdaCqiPWUpmXAM+uG3ePk2xAKGtz9PYr/va8H27an92TsCmF/4JysDjgPTt4Mfr1Kcc2n7Cq7bl304zrU5iuACr2k3z3QjNctupBdLaAq8qc/R1m0jsopqytLRe9d3WF9RilhJzjHZQ79PkvrKr2jLqn9dcCy1uH7B+sOFf99VPAvq0eHUFpMpHj4O2rnLoutnFtwcgg3Delpf+ea0eHM1BrD5ci1xfXNDVNmpER183d7ef6oU7Q4bAqQbWsuoy0WUYY8g20+3ZpHbUYraU2lqqlmplqPdpigWIO2oXR3L+fNytoCu4iLWyxU4ChtZLvSWoq9uBT6Oj++fWCc15d84YViZ1hoyqMLZFbu9k1IVGbghcjy09BBfwIrZFoMeWHhizf4zOFi1jDBOSJwiWE1uGlZfXenu2IWVWlpaKtr6pBf4YBWZLUW2lAeYJYlw+Yl/fjaEtiKhPFxtZ8O3gx61b9ZOAoWXTFZD0CXK6un/M0W2hre7a6mWJFrkOpg6BK6suQ/q9dIOWeeLoEbQ/c5q/uGYIbjjb5W7dNYa0Xe7WHZe7da93Q9ssgboyLEW9laZPS7Y2plylFzvQtQURsb5Q0ZEFIh/e70W6SYwdQaBPkOO6fwypnzpd3TGVtYyq0MxMuKydo/g8fbt9VNOrbm+R+po6BG7fC/v4uwF1MeX27Ib8cHtzohZzXTDXTQWGXCxSpd7q+2eGMI0+amuF3hbpJjH0BGQorfUzYtnvRgBK5T/vVb/5/OdP4XJiVNN/GvQ4P7F5hn5j+m54rRcXuSFwTnZOordj18aYZUzBtby5P2Na4A2VpAPz4sWL8fTTT6Np06bw9PTEiBEjcPnyZUGa8vJyxMfHo3nz5nBxcUFMTAzy8/MFabKzsxEdHQ0nJyd4enri3XffRXV1tSDNwYMH0a1bN8jlcgQFBWHDhg3mq4j6B9QcDLlKX1Wm2eoDhIFi84v65aVvK9QSox846n2+6l0qhhD7JlNd/s971W8+a3v+81pbYL2t9k0p95T4vNxT4t84tFGvnzHfuOqQ+ggOsa4JruXN/9Xj4W3mJunAfOjQIcTHx+PPP/9EcnIyqqqqMGjQIDx69IhPM23aNPzyyy/Yvn07Dh06hNu3b+OFF17g59fU1CA6OhqVlZU4duwYNm7ciA0bNiAhIYFPk5mZiejoaPTv3x9nz57F1KlT8e9//xu//vqr+Sqj+gHVRd8+ZCMvFgmoBoo8cwdSla/pRn9bEGnRi/X5mvukp4/aAqOlTkyWPOGZidht0dnjxpvUb6y6rCH5GLuctUk6MO/fvx9jx45Fx44dERoaig0bNiA7OxunT58GABQXF+Obb77BihUrMGDAAHTv3h3r16/HsWPH8Oefj792/vbbb7hw4QI2bdqELl26YMiQIZg/fz7WrFmDyspKAEBiYiICAwOxfPlydOjQAVOmTMGLL76Izz77zPRKGPJBEhsPW9vFJqlSHaNs7IVOsa/+Yv3d+p70zEFsf5rSv60tH60XF51qTwPNgKT+AH1LBimxfuTytDSDRm4I8mMM2XHj+Pf6Bnn15XLipxi1fmuQdGBWV1xcDABo1qwZAOD06dOoqqpCZGQknyY4OBht2rTB8ePHAQDHjx9H586d4eXlxaeJioqCQqFARkYGn0Y1Dy4Nl4eYiooKKBQKwZ8oQz6g2p6TzI3vVWXum0GEmZs3X2O/dmt89VfLw1KtR111Vt+fpvZvc5RK/Ubt6NFPrT4EbkLyBIzeN1pwMXDi7xPrpAXZ7vfk2hPVgpWVofzcOf69vkGelZcLlqtIT9eRWlrqTWBWKpWYOnUqevXqhU6dOgEA8vLyYG9vD3d3d0FaLy8v5OXl8WlUgzI3n5unK41CoUCZlgNg8eLFcHNz4//8/PxMrqNAq27C9+ofQj0uBvEM/QDq+vBXGXAysPTXbksNTVMf6qiLWAteX6ojWDY+JzJqR+TYUz9ZiQxrUx8Cl34vXWNI3bmCcyY9SU6fPmRA/9uixe4qrE9dD+ZWbwJzfHw8zp8/jx9++MHaRQEAzJo1C8XFxfxfTk6OeVcgdhFJ9YNqyMUgQwKN+rrV16vaRVFbvnZqD+CvLx80U29I0ZfqCJY6Wue+F/aZnIe5+5AbyqM6zaleBOYpU6Zg9+7dSE1Nha+vLz/d29sblZWVKCoqEqTPz8+Ht7c3n0Z9lAb3vrY0rq6ucNRyxpfL5XB1dRX8WURtrU59WqWW+tDXlq/60DGxvnKLdsk0fIZe3DLHkDixuwD16V7Q1srW9ahOXXnW1wt7+pB0YGaMYcqUKdi1axcOHDiAwMBAwfzu3bvDzs4OKSkp/LTLly8jOzsb4eHhAIDw8HCkp6fj7t27fJrk5GS4uroiJCSET6OaB5eGy8OiajugVL+ui15k0u9ikFnp20Wh3uoX6ytX75IxtHVvsDq4LV59PRZcw4TUN/n3+vQbmzuYGdKHnD1ufK2t7CeOHtFrPLOxFwTrC0kH5vj4eGzatAlbtmxB06ZNkZeXh7y8PL7f183NDePHj8f06dORmpqK06dPIy4uDuHh4ejZ8/GY00GDBiEkJASvv/460tLS8Ouvv+Kjjz5CfHw85HI5AGDSpEm4ceMG3nvvPVy6dAlr167Ftm3bMG3aNMtWUP2CT20HlmqfJMeUmxaMZUrfrvoNHOpdMpb+Sm/y9tIzsFv8BAOUyWRIv5/Bv9en33jKgX9GJqgHcl1BW1t/sszBQZBGV3AsT0vTeK/eIrZxdNSrX1pp5AXB+kLSgfnLL79EcXExIiIi4OPjw/9t3bqVT/PZZ59h6NChiImJQd++feHt7Y2dO3fy821tbbF7927Y2toiPDwcr732GkaPHo158+bxaQIDA7Fnzx4kJycjNDQUy5cvx9dff42oqCjLVlD9gk9tt+iq31UHaPYHV1rgpgNzBvvcU8B3wzSn+4QaUQ4jymXKTR6A/oFd/dtCHSmr1h0cM9QCeXnNPzfT6Ara1yP/xb/OmTSZf31L5bW+/cK6Wtn6XlRULYOhy9YHkn5Whj4b1sHBAWvWrMGaNWu0pvH398fevXt15hMREYG/a7mH3+ws0Tq0REvNHHmqPiRe7ARzR4/uke9GAKN/MqBcFvhg1sWJkGNEYInYFoGnWj5Ve0J+Ff+sQz1ol6neAami4vx5/nW5ymvgf/3C5f8sp+2OP22y48YJWsLZ48ajzbff6CyDalrVVrlY8K4vJN1ibhjq+KxtiWCvkacRdTLH0Db1Fm5trdI66E6w6DqMzPtcwbnaE/3PmwferD3R/+hq6Wqbd0tLy1bsNQBBUAb+10VRLn6CUKfeVSIWvOsLCsyWZsiHq7589aqLgKeNIduoLroTLNknbmDexgyFO39f/+BlyJhkjnqLGhAGa20X7Uy5McUcN7VYGwVmSzMkOIhd3KvrFrc+rNR/CkDLNiKA+Z8OZ0gfrbY+aDGqwVpbi9iUBxo1hIchUWCWErG+V2u2TqVIbBsRi3gz1bhnSxjahSB2AjBlWF99vujHocAsddZsnZJG7fw9wwKssV0IYi1s1e4OQy/iifVr1zcUmAlpIKzdUjS2C0Gsha3a3WFoC1ysX7u+ocBMSAOhOg7ZEqwd+BsTCsykjkj0Q92Ago3qOGRLaAhdBPUFBWZSN6R6EVOq5ZKghtBFUF9QYCZ1Q6oXMevqEZ+EGIACMyGESAwFZkIIkRgKzIQQIjEUmAkhZkHD6cyHAjMhxCxoOJ35UGAmhJgFDaczHwrMhBAiMRSYCSFEYigwE0KIxFBgJoQQiaHATAghEkOBmRBCJIYCMyGESAwFZkIIkRgKzIQQIjEUmAkhRGIoMBNCiMRQYCaEEImhwEwIIRJDgZkQQiSGAjMhhEgMBWY1a9asQUBAABwcHNCjRw+cPHnS2kUihDQyFJhVbN26FdOnT8fHH3+MM2fOIDQ0FFFRUbh79661i0YIaUQoMKtYsWIFJkyYgLi4OISEhCAxMRFOTk749ttvrV00Qkgj0sTaBZCKyspKnD59GrNmzeKn2djYIDIyEsePH9dIX1FRgYqKCv59cXExAEBRQT9ISepGKYCashqL5V9TyVBSY7n861qJ8nFd6sOPxlJg/p979+6hpqYGXl5eguleXl64dOmSRvrFixdj7ty5GtP9PiuxWBkJ0aSwaO7PWDR363j48CHc3NysXQydKDAbadasWZg+fTr/XqlUorCwEM2bN4dMJrNiyQghYhhjePjwIVq1amXtotSKAvP/tGjRAra2tsjPzxdMz8/Ph7e3t0Z6uVwOuVwumObu7m7JIhJCTCT1ljKHLv79j729Pbp3746UlBR+mlKpREpKCsLDw61YMkJIY0MtZhXTp0/HmDFjEBYWhmeeeQYrV67Eo0ePEBcXZ+2iEUIaEQrMKl566SUUFBQgISEBeXl56NKlC/bv369xQZAQQixJxurD2BFCCGlEqI+ZEEIkhgIzIYRIDAVmQgiRGArMhBAiMRSYCSFEYigwE0KIxNA4ZguIi4uDTCbDH3/8wU9Tv9VbdWx07969IZPJtD5elMtPfWTjkSNH0KdPH8F6VPNUna9t/X369NFrvUeOHNHIH4DOchtDW131WU9cXBxfTq6+ZWVlqKmpga2trSCt6jTutdg0jqOjI4B/tptMJkOvXr0E6ysrK4OjoyPKysr4ZbhpXFm4abrWqbqc+vJiZdG1D41hyD5QP9ZVjzOufLUd30QTjWO2kIqKCsjlcv7xoK6urigoKEDLli0F0xQKBVxdXfXOD4BgGbH1aJuvUCjQsmVLKBSPn0hm6Hq58quXwdy01VXfZYHHzzIpKCjgn2nC1V3bNAA658vlcsG2FdsuqttYdRlt83WtU6FQoKKiQnC8qM8H9NuHxjBkH6gfg9xrQ45vooYRi3jxxRdZRkYG69+/PxsyZAg7duwY8/Pz05j28ssvG5Sf+jJi69E239vbm23evJlFRkYatV6u/IaU2xja6qrvsoMGDWKbN29mnp6ebMiQIYK6a5tW23z1bSu2XbQto22+rnVGRkZqHC/G7kNjGLIP1I9BY45vIkQtZgtRKBTo2bMn3yLy8fHBjh078OyzzwqmJScnw8am9q5+Lj/1ZcTWo21+Xl4ebt26hZ49exq1Xq78hpTbGNrqqu+yTz/9NG7duoWwsDC+tcrVXdu02uarb1ux7aJtGW3zda2zZ8+eGseLsfvQ0vtA/Rg05vgmQrTFLGTChAn46quvUFFRgaCgIIwbNw7du3fXmDZp0iSD8lNfRmw92uaXlJRgxowZYIwZtV6u/IaU2xja6qrvsr6+vpgxYwYuXbqEoKAgQd21Tattvvq2Fdsu2pbRNl/XOhljGseLsfvQGIbsA/Vj0JjjmwhRi9kC5s6di+LiYvz9998oLy9HeXk5ioqK8OjRIzg7O6O6uhotWrSAu7s7ioqK8PzzzwMAEhISdObn7u4OxhiysrIQGBiI1NRUdO3aVbAe1TxV51+7dg0VFRVwdnZGeXk5vL294eHhgYiICL3Wm5qairt378LLywuMMQQEBCAwMFBnuU3Zdup11Wc9c+fOxf79+yGTyXDnzh08evQIZWVlqKqqgq2tLezt7VFZWQkbGxvBtEePHsHOzg5KpRI2NjYa8ysrK+Hq6goHBwe4u7vD3d0dFRUVGDx4ML9dSktLUVhYCLlcjqqqKn6Z8vJy2NnZwdnZWTBf1zo9PT1x7949ODo6oqqqCi4uLqiurkZpaSmqq6vh6emp9z609D5QP9azsrLQpEkTVFdXIzg4WK/jm2iiwGwBN2/eBADcunWLn5aXlydIo/rwfV9fXwCAv7+/zvzU3bp1C76+voL1qOapOl/b+n19ffVar/o6uDLrKrcxtNVVn/XcvHmTLydX34KCAty/fx/NmzcXpFWdxr0Wm8bhLnqq7zfV9al+jeeWUb1gqjpf1zrVuwRUlxcri659aAxD9oH6sa56nKmWT2xZoh0FZkIIkRjqYyaEEImhwEwIIRJDgZkQQiSGAjMhhEgMPSuD6KT+vAzudX5+Pry9vTVGe3C4dKrPegAMe76D+jMbuNd1/dwF1WdwqDP3cyr0KQv3bAqx559w+4XbRwA0nt3h5OQk2DfcfA63v9T3oVg+np6eAB5vB+4YUX1+C/cMEXWGPKtEn2eZqE6z9LNE6gKNyiCEEImhFjOp1UsvvYQnn3wSsbGx+PjjjzVe//XXXwgLC+P/q8/Lzs5G37598fbbbyM4ONjodRu6rDm99NJLOH/+vNH1MHdZdG1bsflZWVk69w03v7Z9KJaP+r5RXT+Xp9h6VKeZOl99mrX3kakoMJNabd26FdevX8emTZuQn5+PRYsWCV43adIEe/fuxf/93/9h7969aNKkiWBeYWEh7O3tMXjwYAQEBODgwYNGrTs1NdWgZc2JK8fq1auNqoclyqJt24rNv3jxIgoLC7XuG25+bftQLB/1faO6fu64EFuP6jQvLy+T5qtPs/Y+MhV1ZZBaZWRkYNOmTcjKykJQUBCqq6sFr9PS0gT9gM2aNRPMKy4uxoMHD+Ds7Ixx48Zh8uTJRq27b9++Bi1rThkZGfjss89w7Ngxo+ph7rJs2rRJ67YVm29jY4PWrVtr3Tfc/Nr2oVg+6vtGdf3ccSG2HtVpbm5uJs1Xn2btfWSyunmIHanP5s2bxzIzM7W+Vv+vPm/atGn8dFPWbU2m1sPcZdG1bcXm17Zv9N2H2o4FbevXtR7VaabON8exJiXUYiY6HT58mB8JkZaWxr++du0a2rVrh+vXr/PTuP8A+Ne3bt1C69at+elBQUEAgNDQUPTt21fvdaurbVlzOnz4MM6ePQsAGmXRpx7mLgtjDOfOncPVq1cFZQoKCuL3i0wm4+ffvn0bjDH4+voiNzcXrVq1Euwbbj63D7lnW6jvQ7F8nnjiCX47AEBaWhqeeuopnDt3DowxXL9+nX+OhuoxUlBQgBYtWghe37t3T2OaPvPV8+TKb8ixJjXUx0x0yszM5F+fO3eOf3316lWUlpbiypUrWoe0sf8N2bp37x4/r7S0FDKZDG5ubrV+WFTXrUomk9XpBy0zMxPp6emi5dCnHuYuC/B4X1y5ckVQltLSUly9ehVlZWVgjPHz8/LyIJPJcO/ePX5/qO4bbj633+7fvy+6D8XyKSsrg0wm43+lJD09Ha6urvyxcuXKFY38GWNQKBTIz8/nX+fl5WlM03e+ep737t0z+FiTGmoxE0KIxNCdf4QQIjEUmAkhRGIoMBNCiMRQYCaEEImhURkmyM7OBgDk5uYCEP9ZHU7r1q010nIPAeJ+MggACgsL0axZM/6/+s8LqePyUP+vXo7WrVsjNzeX/6/600vq6+ao/oQRV/42bdrw9VbH5a+N+nYqKCgQXSdXX/U6qf90k2qZ1X9uqXXr1mjTpo3WsphCW/0B3duHm29K3rqW4bavKn32mz7lMqV8dS07O1t0WwCWPS7MiQKzCdavXw8A/G2fWVlZ/LyAgABB2oiICI20AQEByMrKQlFREZ+uvLwcDg4O/H/ux1Xd3d1Fy8Dlof5fvRwRERE4ePAg/59LI7ZuDrfOgIAAREREQCaTISEhga+3Oi5/ddxwJvXtVFRUJLpOrr7qdeKmi5VZtawA0L9/f4v9+Ke2+te2fbj5puStaxmx24/12W/6lMuU8tW19evXa70V25LHhTnRcDkzyMjIEJ3esWNHjTTcNLFlrl27xg+KV33NLVfbevQph3o69fVoW7cY9TrVNp2bp+86VfPRt8zaymoJuuqpz3xT8ta1DMcS5TJnHpameqxJuZxiKDCbaOrUqWjevDn27t0rGOweHR2NgoICrF69mk8DPP76bmNjo7FMVlYWQkJCcOHCBQDgX/v7+yM6Oho7duxATEyM1vWI5aleDvXyqq7T399foxzculWXV683Vyf1/NWnc/NOnDgBJyenWtfJ1ReAoO66yvzo0SM888wzGmW1BF311Ge+KXnrWobb/4buN0OYIw9LUz3W6vK4MBfqyjCRra0tZs+ejaKiIsHDvGfPno333ntPkAYA3nvvPdTU1GgsU11djZSUFDz99NMAwL/u27cvZs+ejaSkJJ3rEctTvRzq5VVdZ9++fTXKwa1bdXn1fLg61Tadm/fss89i+fLlta6Tqy8AQd11lVmsnJaiq576zDclb13LcPvf0P1m6fLVNdVjTapl1IUCs4mqq6sxd+5cHD16VNBSnTdvHv/LDVwamUyGsrIy2NjYaCyTk5OD/v37IycnBwD414cOHcK8efNQWVmpcz1ieaqXQ728qus8dOiQRjm4dYv9AoV6nWqbzs07ceKEXuvk6iuTyQR111Xm0tJSPPPMM5bYzXrXX9/5puStaxlu/xu63yxdvrqmeqzV5XFhLtSVYQbUx0x9zMbMNyVvXctwqI+Z+pgbJa7VkJqaCplMJnjoTmBgIIB/ntDFjVZQTRsYGIjMzEyTRmVweaj/Vy9HREQEUlNT0b9/f6Smpho0KiMwMJAvf0JCAl9vdVz+YrhRGarbqbZRGep10mdUhmp9LXX1XVv9Ad3bh5tvSt66luGOLVX67Dd9ymVK+era3Llz+WNNnSWPC3OiwGyCmzdvAgD/WENd45i5RxGqphUbx3z//n00b96c/2+uccy+vr64desW/19sHDO3To7q2GCu/P7+/ny91XH5a6O+nQoKCkTXacg4ZtXtpF5ff39/rWUxhbb6A7q3DzfflLx1LcNtX1X67Dd9ymVK+erazZs3RbcFYNnjwpwoMBNCiMTQLdmEECIxFJgJIURiKDATQojEUGAmhBCJocBMiIXMmTMHXbp0sXYxSD1EgZlY3dixYyGTySCTyWBnZwcvLy/861//wrfffgulUmlQXhs2bNA65ttQ3JPZZDIZHBwcEBISgrVr1+q9/IwZM5CSkmLQOgMCArBy5UoDS0oaGgrMRBIGDx6MO3fuICsrC/v27UP//v3x9ttvY+jQoaiurrZauSZMmIA7d+7gwoULGDVqFOLj4/H999/rtayLi4tgjDYh+qLATCRBLpfzD+Tv1q0bPvjgA/z888/Yt28fNmzYwKdbsWIFOnfuDGdnZ/j5+eE///kPSkpKADx+HnFcXByKi4v5lu6cOXMAAP/9738RFhaGpk2bwtvbG6+++iru3r1ba7mcnJzg7e2Ntm3bYs6cOXjiiSeQlJQE4PED2YcPHw4XFxe4urpi1KhRyM/P55dV78oYO3YsRowYgU8//RQ+Pj5o3rw54uPjUVVVBeBxC/3mzZuYNm0aX37g8Q0Tw4YNg4eHB5ydndGxY0fs3bvXlM1NJI4CM5GsAQMGIDQ0FDt37uSn2djYYPXq1cjIyMDGjRtx4MAB/ulhzz77LFauXAlXV1fcuXMHd+7cwYwZMwAAVVVVmD9/PtLS0vDTTz8hKysLY8eONbhMjo6OqKyshFKpxPDhw1FYWIhDhw4hOTkZN27cwEsvvaRz+dTUVFy/fh2pqanYuHEjNmzYwJ94du7cCV9fX8ybN48vPwDEx8ejoqIChw8fRnp6OpYuXQoXFxeDy07qD3q6HJG04OBgnDt3jn8/depU/nVAQAAWLFiASZMmYe3atbC3t4ebmxtkMpnGLfHjxo3jX7dt2xarV6/G008/jZKSEr2CXE1NDb7//nucO3cOEydOREpKCtLT05GZmQk/Pz8AwHfffYeOHTvi1KlT/ONb1Xl4eOCLL76Ara0tgoODER0djZSUFEyYMAHNmjWDra0t36rnZGdnIyYmBp07d+bLTxo2ajETSeMeAsX5/fffMXDgQLRu3RpNmzbF66+/jvv376O0tFRnPqdPn8awYcPQpk0bNG3aFP369QOg+zfsAGDt2rVwcXGBo6MjJkyYgGnTpmHy5Mm4ePEi/Pz8+KAMPP5xA3d3d1y8eFFrfh07doStrS3/3sfHp9YulbfeegsLFixAr1698PHHHwtOVKRhosBMJO3ixYv8E+OysrIwdOhQPPXUU9ixYwdOnz6NNWvWAAAqKyu15vHo0SNERUXB1dUVmzdvxqlTp7Br165alwOA2NhYnD17FpmZmXj06BFWrFgBGxvjPzZ2dnaC9zKZrNaRJ//+979x48YNvP7660hPT0dYWBg+//xzo8tApI8CM5GsAwcOID09nf+JqdOnT0OpVGL58uXo2bMnnnzySdy+fVuwjL29PWpqagTTLl26hPv372PJkiXo06cPgoOD9brwBwBubm4ICgpC69atBQG5Q4cOyMnJ4X/YAAAuXLiAoqIihISEGFtl0fIDgJ+fHyZNmoSdO3finXfewVdffWX0Ooj0UWAmklBRUYG8vDzk5ubizJkzWLRoEYYPH46hQ4di9OjRAICgoCBUVVXh888/x40bN/Df//4XiYmJgnwCAgJQUlKClJQU3Lt3D6WlpWjTpg3s7e355ZKSkjB//nyTyhsZGYnOnTsjNjYWZ86cwcmTJzF69Gj069cPYWFhRucbEBCAw4cPIzc3F/fu3QPwuF/9119/RWZmJs6cOYPU1FR06NDBpPITaaPATCRh//798PHxQUBAAAYPHozU1FSsXr0aP//8M98nGxoaihUrVmDp0qXo1KkTNm/ejMWLFwvyefbZZzFp0iS89NJLaNmyJZYtW4aWLVtiw4YN2L59O0JCQrBkyRJ8+umnJpVXJpPh559/hoeHB/r27YvIyEi0bdsWW7duNSnfefPmISsrC+3ateOfMV1TU4P4+Hh06NABgwcPxpNPPmnQjS6k/qHnMRNCiMRQi5kQQiSGAjMhhEgMBWZCCJEYCsyEECIxFJgJIURiKDATQojEUGAmhBCJocBMCCESQ4GZEEIkhgIzIYRIDAVmQgiRmP8PkQIWRzUHXeMAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.spatial.distance import pdist, squareform\n",
        "# ユークリッド距離を計算\n",
        "distances = pdist(np.array(images), 'euclidean')\n",
        "distance_matrix = squareform(distances)\n",
        "\n",
        "# 距離の分布をヒストグラムで表示\n",
        "plt.hist(distances, bins=30, edgecolor=\"k\")\n",
        "plt.title(\"Distribution of Euclidean Distances\")\n",
        "plt.xlabel(\"Distance\")\n",
        "plt.ylabel(\"Number of Pairs\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "rFdFxHDXw8zy",
        "outputId": "f6b2b2de-d412-42be-bfb0-9ed3d08227ec"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "注意したいのは顔の画像が区別できないから種は画像から区別がつかないという結論にはならない。今回はかなり見た目を潰してしまっている。というのも、ピクセルごとの比較だから、黒い模様が丸い形とか耳の形が三角で、というような特徴は捉えていない。だとしても、キツネvs.タヌキの分かりやすさに対するタヌキvs.ムジナの分かりづらさは、デンドログラムでなかなか綺麗に分かれない結果からも支持できるのではないだろうか。"
      ],
      "metadata": {
        "id": "AVnqjXhj-_aE"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Appendix: NMF"
      ],
      "metadata": {
        "id": "mi000WeDI2uR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.decomposition import NMF\n",
        "\n",
        "# 真のラベル\n",
        "# numpy配列に変換\n",
        "images = np.array(images)\n",
        "\n",
        "# NMFを用いてデータを2次元に削減（可視化のため）\n",
        "nmf = NMF(n_components=2, init='random', random_state=0)\n",
        "reduced_data = nmf.fit_transform(images)\n",
        "\n",
        "# 結果をプロット\n",
        "df = pd.DataFrame(reduced_data, columns=['DIM_1', 'DIM_2'])\n",
        "df['label'] = labels"
      ],
      "metadata": {
        "id": "FLkM0AoNWW2K"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "comp1 = [\"TNK\", \"KTN\"]\n",
        "comp2 = [\"TNK\", \"ANG\"]\n",
        "df_1 = df.query(\"label in @comp1\")\n",
        "df_1.loc[:, \"compare\"] = \"TNK--KTN\"\n",
        "df_2 = df.query(\"label in @comp2\")\n",
        "df_2.loc[:, \"compare\"] = \"TNK--ANG\"\n",
        "df_comp = pd.concat([df_1, df_2])\n",
        "df_comp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "EHt8ZBw1kUvm",
        "outputId": "35ce28d2-174b-4286-fddf-104e9f5f4af4"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-10-27e6947753fd>:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "<ipython-input-10-27e6947753fd>:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         DIM_1      DIM_2 label   compare\n",
              "3     8.552060   6.683829   TNK  TNK--KTN\n",
              "6    10.752122   3.964179   TNK  TNK--KTN\n",
              "8     8.927225   2.147261   TNK  TNK--KTN\n",
              "9     7.929422   8.358726   TNK  TNK--KTN\n",
              "12    9.974892  11.171580   KTN  TNK--KTN\n",
              "..         ...        ...   ...       ...\n",
              "138  10.078871   3.618544   TNK  TNK--ANG\n",
              "139  11.865459   6.590702   ANG  TNK--ANG\n",
              "140  14.618469   4.660094   ANG  TNK--ANG\n",
              "141   8.349488   6.491250   TNK  TNK--ANG\n",
              "143  10.002105   4.714797   TNK  TNK--ANG\n",
              "\n",
              "[192 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-19d4022c-5de6-4776-ab68-6cc455bd47c7\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DIM_1</th>\n",
              "      <th>DIM_2</th>\n",
              "      <th>label</th>\n",
              "      <th>compare</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8.552060</td>\n",
              "      <td>6.683829</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--KTN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>10.752122</td>\n",
              "      <td>3.964179</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--KTN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>8.927225</td>\n",
              "      <td>2.147261</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--KTN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>7.929422</td>\n",
              "      <td>8.358726</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--KTN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>9.974892</td>\n",
              "      <td>11.171580</td>\n",
              "      <td>KTN</td>\n",
              "      <td>TNK--KTN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>10.078871</td>\n",
              "      <td>3.618544</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--ANG</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>139</th>\n",
              "      <td>11.865459</td>\n",
              "      <td>6.590702</td>\n",
              "      <td>ANG</td>\n",
              "      <td>TNK--ANG</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>140</th>\n",
              "      <td>14.618469</td>\n",
              "      <td>4.660094</td>\n",
              "      <td>ANG</td>\n",
              "      <td>TNK--ANG</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>8.349488</td>\n",
              "      <td>6.491250</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--ANG</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>143</th>\n",
              "      <td>10.002105</td>\n",
              "      <td>4.714797</td>\n",
              "      <td>TNK</td>\n",
              "      <td>TNK--ANG</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>192 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-19d4022c-5de6-4776-ab68-6cc455bd47c7')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-19d4022c-5de6-4776-ab68-6cc455bd47c7 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-19d4022c-5de6-4776-ab68-6cc455bd47c7');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-303ee90b-8148-4428-baa0-0526e9ea1746\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-303ee90b-8148-4428-baa0-0526e9ea1746')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-303ee90b-8148-4428-baa0-0526e9ea1746 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "p = (\n",
        "    ggplot(df_comp, aes(x='DIM_1', y='DIM_2', shape='label'))\n",
        "    + facet_wrap(\"~compare\", nrow=1)\n",
        "    + geom_point(fill='white', color='black', size=3)# , alpha=0.1)\n",
        "    + scale_shape_manual(values=['o', '^', 'x'])\n",
        "    + labs(title=\"NMF result\", x=\"DIM_1\", y=\"DIM_2\", shape=\"Marker\")\n",
        "    + theme_bw()  # Set the theme to black and white\n",
        "    + theme(\n",
        "        figure_size=(2.5, 2.5),  # in inch\n",
        "        text=element_text(size=12),  # set the font size for the entire plot\n",
        "        axis_title=element_text(size=14),  # set the font size for axis titles\n",
        "        axis_text=element_text(size=10),  # set the font size for axis labels\n",
        "        legend_title=element_text(size=12),  # set the font size for legend title\n",
        "        legend_text=element_text(size=10),  # set the font size for legend labels\n",
        "        legend_key=element_rect(size=10),  # set the size of legend keys\n",
        "        )\n",
        ")\n",
        "print(p)\n",
        "ggsave(p, filename = 'ch02_tnk48.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        },
        "id": "6vVfFs8qrQUM",
        "outputId": "62426ede-43b9-440a-dd88-676374dc146a"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 250x250 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "image/png": {
              "width": 250,
              "height": 250
            }
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/plotnine/ggplot.py:587: PlotnineWarning: Saving 2.5 x 2.5 in image.\n",
            "/usr/local/lib/python3.10/dist-packages/plotnine/ggplot.py:588: PlotnineWarning: Filename: ch02_tnk48.png\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "H = nmf.components_\n",
        "img_y = []\n",
        "for y in range(15, 2, -4):\n",
        "    # 上から作る: yは大きい方から\n",
        "    img_x = []\n",
        "    for x in range(2, 15, 4):\n",
        "        # 左から作る: xは小さい方から\n",
        "        img_xy = ([x, y] @ H)\n",
        "        img_xy = (img_xy - img_xy.min()) / (img_xy.max() - img_xy.min())\n",
        "        img_xy = img_xy.reshape((res,res))\n",
        "        img_x.append(img_xy)\n",
        "    img_x = np.hstack(img_x)\n",
        "    img_y.append(img_x)\n",
        "img = np.vstack(img_y)"
      ],
      "metadata": {
        "id": "4sNTlQRSJgcP"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.imshow(img, cmap='gray')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "id": "TfE7J3F0MIig",
        "outputId": "9a3b9a99-823c-4380-9c9a-13127d33dfe6"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7cf758a46380>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "image/png": {
              "width": 640,
              "height": 480
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "注意したいのは顔の画像からは区別がつかないという結論にはならない。今回はかなり見た目を潰してしまっている。というのも、ピクセルごとの比較だから、黒い模様が丸い形とか耳の形が三角で、というような特徴は捉えていない。しかも背景の部分も比較しているから、単純にキツネの背景が白がちでタヌキやムジナは黒がちだった、という解釈も十分ありえるだろう。だとしても、キツネvs.タヌキの分かりやすさに対するタヌキvs.ムジナの分かりづらさは、デンドログラムでなかなか綺麗に分かれない結果からも支持できるのではないだろうか。"
      ],
      "metadata": {
        "id": "mukZFqZd-6k9"
      }
    }
  ]
}