Demo for Rotation Equivariance.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Show Rotation Equivariance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "M1 = 1\n",
    "M2 = 1\n",
    "M3 = 1\n",
    "Ntheta = 8\n",
    "\n",
    "Nrot = 16"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Layer 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finish generation fb bases, bases is:\n",
      "[[[ 0.   -0.   -0.   -0.    0.  ]\n",
      "  [ 0.06 -0.12 -0.06  0.11  0.14]\n",
      "  [ 0.12 -0.25  0.    0.32 -0.  ]\n",
      "  [ 0.06 -0.12  0.06  0.11 -0.14]\n",
      "  [ 0.   -0.    0.   -0.   -0.  ]]\n",
      "\n",
      " [[ 0.06 -0.06 -0.12 -0.11  0.14]\n",
      "  [ 0.26 -0.32 -0.32 -0.    0.46]\n",
      "  [ 0.34 -0.45  0.    0.35 -0.  ]\n",
      "  [ 0.26 -0.32  0.32 -0.   -0.46]\n",
      "  [ 0.06 -0.06  0.12 -0.11 -0.14]]\n",
      "\n",
      " [[ 0.12  0.   -0.25 -0.32 -0.  ]\n",
      "  [ 0.34  0.   -0.45 -0.35 -0.  ]\n",
      "  [ 0.44  0.    0.    0.    0.  ]\n",
      "  [ 0.34  0.    0.45 -0.35  0.  ]\n",
      "  [ 0.12  0.    0.25 -0.32  0.  ]]\n",
      "\n",
      " [[ 0.06  0.06 -0.12 -0.11 -0.14]\n",
      "  [ 0.26  0.32 -0.32  0.   -0.46]\n",
      "  [ 0.34  0.45  0.    0.35  0.  ]\n",
      "  [ 0.26  0.32  0.32  0.    0.46]\n",
      "  [ 0.06  0.06  0.12 -0.11  0.14]]\n",
      "\n",
      " [[ 0.    0.   -0.    0.   -0.  ]\n",
      "  [ 0.06  0.12 -0.06  0.11 -0.14]\n",
      "  [ 0.12  0.25  0.    0.32  0.  ]\n",
      "  [ 0.06  0.12  0.06  0.11  0.14]\n",
      "  [ 0.    0.    0.    0.    0.  ]]]\n",
      "finish generation fourier bases, bases is:\n",
      "[[ 1.      1.      1.      1.      1.      1.      1.      1.    ]\n",
      " [ 1.4142  1.      0.     -1.     -1.4142 -1.     -0.      1.    ]\n",
      " [ 0.      1.      1.4142  1.      0.     -1.     -1.4142 -1.    ]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/zichen/Projects/RotDCF-Pytorch/Rot_DCF.py:40: UserWarning: nn.init.normal is now deprecated in favor of nn.init.normal_.\n",
      "  init.normal(self.joint_coeff, mean=0, std=stdv)\n"
     ]
    }
   ],
   "source": [
    "from Rot_DCF import Rot_DCF_Init\n",
    "\n",
    "rot_dcf_init = Rot_DCF_Init(M2, M1, 5, Ntheta, 5, 3, bias=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### show rotate kernels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "## with shape [Ntheta*chn_out, chn_in, k_s, k_s]\n",
    "kernel = rot_dcf_init.rototion_weight()\n",
    "kernel = kernel.view(Ntheta, M2, M1, 5, 5)\n",
    "kernel = kernel[:, 0, 0, ...]\n",
    "plt.figure(figsize=(10,5))\n",
    "for i in range(Ntheta):\n",
    "    plt.subplot(1,Ntheta,i+1)\n",
    "    plt.imshow(kernel[i].detach().numpy())\n",
    "    plt.axis('off')\n",
    "plt.savefig('./rotate_filter.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### show rotation equivariance in output feature maps of first layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2880x2160 with 144 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## test outputs of rotated images\n",
    "## prepare data\n",
    "import numpy as np\n",
    "import torch\n",
    "import PIL\n",
    "\n",
    "import torchvision.transforms as transforms\n",
    "\n",
    "idx_img = 3\n",
    "## change the dir here to the actual data path\n",
    "data_path = '/home/zichen/Projects/data/MNIST/processed/training.pt'\n",
    "per_rot_ang = 360/Nrot\n",
    "\n",
    "## load data\n",
    "data = torch.load(data_path)\n",
    "images, labels = data\n",
    "\n",
    "img_ori = images[idx_img]\n",
    "img_ori_show = transforms.functional.to_pil_image(img_ori)\n",
    "\n",
    "\n",
    "## create rotation images of angles [0, 22.5, ..., 337.5]\n",
    "img_rot_show_list = []\n",
    "img_rot_list = []\n",
    "\n",
    "ang = 0\n",
    "while ang < 360:\n",
    "    img_rot_show = transforms.functional.rotate(img_ori_show, ang, resample=PIL.Image.BICUBIC)\n",
    "    img_rot = transforms.functional.to_tensor(img_rot_show)\n",
    "    img_rot_show_list.append(img_rot_show)\n",
    "    img_rot_list.append(img_rot)\n",
    "    ang += per_rot_ang\n",
    "\n",
    "feat_map_1_list = []\n",
    "for img_rot in img_rot_list:\n",
    "    feat_map_1_list.append(rot_dcf_init(img_rot.unsqueeze(0).float()).view(Ntheta*M2, 28, 28).detach().numpy())\n",
    "\n",
    "plt.figure(figsize=(40, 30))\n",
    "\n",
    "## plt original image\n",
    "for i in range(len(img_rot_show_list)):\n",
    "    plt.subplot(Ntheta+1, Nrot, i+1)\n",
    "    plt.imshow(img_rot_show_list[i], cmap='gray')\n",
    "    plt.axis('off')\n",
    "    if i == 0:\n",
    "        plt.title('original image', fontsize=15)\n",
    "\n",
    "# plt feat with specific \\lambda(idx_feature_map) and \\alpha(idx_rotation_group)\n",
    "for alpha in range(Ntheta):\n",
    "    for idx in range(len(feat_map_1_list)):\n",
    "        plt.subplot(Ntheta+1, Nrot, (alpha+1)*Nrot+idx+1)\n",
    "        ## fetch the features for a rot image\n",
    "        feat = feat_map_1_list[idx]\n",
    "        feat = feat.reshape([Ntheta, M2, 28, 28])\n",
    "        plt.imshow(feat[alpha, 0], cmap='gray')\n",
    "        plt.axis('off')\n",
    "        if idx == 0:\n",
    "            plt.title('alpha={}'.format(alpha+1), fontsize=15)\n",
    "plt.savefig('./layer1_rotequi.png', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Layer 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "M1 = 1\n",
    "M2 = 1\n",
    "M3 = 1\n",
    "Ntheta = 8\n",
    "\n",
    "Nrot = 16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finish generation fb bases, bases is:\n",
      "[[[ 0.   -0.   -0.   -0.    0.  ]\n",
      "  [ 0.06 -0.12 -0.06  0.11  0.14]\n",
      "  [ 0.12 -0.25  0.    0.32 -0.  ]\n",
      "  [ 0.06 -0.12  0.06  0.11 -0.14]\n",
      "  [ 0.   -0.    0.   -0.   -0.  ]]\n",
      "\n",
      " [[ 0.06 -0.06 -0.12 -0.11  0.14]\n",
      "  [ 0.26 -0.32 -0.32 -0.    0.46]\n",
      "  [ 0.34 -0.45  0.    0.35 -0.  ]\n",
      "  [ 0.26 -0.32  0.32 -0.   -0.46]\n",
      "  [ 0.06 -0.06  0.12 -0.11 -0.14]]\n",
      "\n",
      " [[ 0.12  0.   -0.25 -0.32 -0.  ]\n",
      "  [ 0.34  0.   -0.45 -0.35 -0.  ]\n",
      "  [ 0.44  0.    0.    0.    0.  ]\n",
      "  [ 0.34  0.    0.45 -0.35  0.  ]\n",
      "  [ 0.12  0.    0.25 -0.32  0.  ]]\n",
      "\n",
      " [[ 0.06  0.06 -0.12 -0.11 -0.14]\n",
      "  [ 0.26  0.32 -0.32  0.   -0.46]\n",
      "  [ 0.34  0.45  0.    0.35  0.  ]\n",
      "  [ 0.26  0.32  0.32  0.    0.46]\n",
      "  [ 0.06  0.06  0.12 -0.11  0.14]]\n",
      "\n",
      " [[ 0.    0.   -0.    0.   -0.  ]\n",
      "  [ 0.06  0.12 -0.06  0.11 -0.14]\n",
      "  [ 0.12  0.25  0.    0.32  0.  ]\n",
      "  [ 0.06  0.12  0.06  0.11  0.14]\n",
      "  [ 0.    0.    0.    0.    0.  ]]]\n",
      "finish generation fourier bases, bases is:\n",
      "[[ 1.      1.      1.      1.      1.      1.      1.      1.    ]\n",
      " [ 1.4142  1.      0.     -1.     -1.4142 -1.     -0.      1.    ]\n",
      " [ 0.      1.      1.4142  1.      0.     -1.     -1.4142 -1.    ]]\n"
     ]
    }
   ],
   "source": [
    "from Rot_DCF import Rot_DCF, Rot_DCF_Init\n",
    "\n",
    "rot_dcf = Rot_DCF(M3, M2, 5, Ntheta, 5, 3, bias=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### show rotate kernels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 64 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "## with shape [Ntheta*chn_out, Ntheta*chn_in, k_s, k_s]\n",
    "kernel = rot_dcf.rotation_weight()\n",
    "kernel = kernel.view(Ntheta, M3, Ntheta, M2, 5, 5)\n",
    "kernel = kernel[:, 0, :, 0, ...]\n",
    "\n",
    "plt.figure(figsize=(8, 8))\n",
    "cnt = 1\n",
    "for i in range(Ntheta):\n",
    "    for j in range(Ntheta):\n",
    "        plt.subplot(Ntheta,Ntheta,cnt)\n",
    "        # every row is rotated filters operated on input alpha channels\n",
    "        plt.imshow(kernel[j, i].detach().numpy())\n",
    "        \n",
    "        plt.axis('off')\n",
    "        cnt += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### show rotation equivariance in output feature maps of first layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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++uspZpu5ceNGUQbPTjgWca/NNsbfR9jnO8H7zLk1ouyfPBvl2Mu9NX8fUZ6Xsv7YzmpnAFw7dLL+1IvXyX23L0qStHaa5uams7XaPornLU17xNrabaU8CZQkSZIkSZIkSZIkSVJX8sEYSZIkSZIkSZIkSZIkdSUfjJEkSZIkSZIkSZIkSVJX2vyyL+Blacp5ypzWBw8eLMpgnuvp6ekU9/X1pfjNN99M8dGjR4symfd4dnY2xcybW8vNZZ7NZqz/zZvLrsAc9Dt27Egx88tfvnw5xSdOnCjKZJ7k8fHxFNdy7z7L/Larh/2G9cucd7V801evXk3xD37wgxRPTU2lmG2sv7+/KNM6Xx1N+aU5vrOuIiKGhoZSzP7M/s581RFlO2PMvOh6Mdivenp6iteMjIykeHBwMMUzMzMp5hpgcXGxKJNtgHEnec/5M8eI9YN14XpM6lzT2pzzckTEgwcPUrywsJBizqm1sX7btm0pbsqLrJXh3MU174EDB4r3HDp0KMWch+/cudP2M/bu3VuUyf03P+PevXspvn79elEGP/fp06fFa5TV1io7d+5MMdddXGffvn07xe+9915R5p/8yZ+kmOssnvHwM5y3V0/TvWUbqfWrubm5FJ86dSrF3/rWt1J87NixFI+NjRVlHjlypO11aGVY3zxL4TjKuo0ozzo5Hp85cybFN2/eLMrgmSzHAI5DXFcwrl2XSpyPeZ8jynn/8OHDKb57926KuS7k2UtE2Y54nl6rT+LYw3WhY8Tq4H2urcc5rrAvct3PuqzVHduq+wBJkupzJudIntHxbI3zMPfzERHz8/Mp5lzO7+Nq38/VvtfvhDO+JEmSJEmSJEmSJEmSupIPxkiSJEmSJEmSJEmSJKkr+WCMJEmSJEmSJEmSJEmSutLKEjB1AeabZs5y5jsdGBgoymD+0qmpqRQzby5zWO/evbsok5+zuLiYYvNdvhjMk8b2EBGxY8eOFDNvGnMcv/POOylmjvOIiP3796eYee15Xax/5lmLMBf6StTu2cOHD1PMnMaM2b8jIm7cuJHikydPpnhycjLFbA/Mg167VnMavxjMc8j6X1hYSHFPT09RBnMjso2wDI4hEWUeRNYvx3xed41jQjPe197e3uI1IyMjKea6gDnrl5aWUtzf31+U2ZQXm2U8evSoKINthjHzZDtmvBi8j53c16b65u9razzXfeoWbMuMuRbfuXNnimvzMPdenJc5pnK/F1GOofa5F4NzEefMsbGxFL/++utFGXv27Ekx50Tmo2b9c8yNiBgeHm57HdzfM44o13sqcY5kvvGI8mxk3759KeaYMDs7m+IrV64UZU5MTKSY48j09HTbMrkfiCjbnevsF4P3sZM1EccV7ou497p582aKZ2ZmijJHR0fblqmVYX0+ePAgxRy/OZ9HlGP62bNnU/xnf/ZnKb569Wp7NIbiAAAgAElEQVRRBs9b2K727t2bYu4JuY6IqM8tr7qmM4zaeSt/xnmC675du3Y1XsetW7dSzDmBbYRjRET9nO9ZHIe0MmwjrP/a+QzHZ44j7K/3799PcW3/znbG62B9u0+QJHWjprVcRMT27dtTzPM1fg9y7969FHOvVvsZ9wy8Dl5DxMq/93BGlyRJkiRJkiRJkiRJUlfywRhJkiRJkiRJkiRJkiR1JR+MkSRJkiRJkiRJkiRJUlfa3PyS7sC8kMx5xfzizHFdyzd97ty5FP/gBz9IMfOZMk96Lc8qP3dxcTHFjx8/Lt6j58f8ZMwrGhHR19eXYrYh5ii/ePFiimt5kplLnfXLPMrMaW4+4xejljucfZx58FhXtTKY0445bpnHnvmLa/n7mnLcOiasDOuP9Xvjxo0U13JN8zUffPBBipnjemBgoCiDYz5zKbPPs011Uv/M8a6yr9bmY84LO3fubFtGU1z72eTkZIrff//9FLONRZRj09atW1PMMWPz5rzUW2nuzVcN7xPvY63NEPsrY/bvWpn8XOKc0Em72yhtgNfpWPbyNLWZTvIRc2xqijlnsq1HRMzMzKSY62ZeF8fxiDJHse2sWa09cPziveZ659ChQynmHimiHCO5T+I6a25uLsVc20WU8yo/l+M025Q600nfGxkZSfGuXbtSfPfu3RRzr11bI/Fz2b9Zn9zP1/Z3fI9jxOpoWndFlPNE01qMdVer36br0Mqwn7AuuLfm+B1RntlybcGYc0RExP3791PMM9m9e/emmGeA3HdFlOdGnbSrVw3rv3aezvrivpj9m+tAjgcR5b6Y9U21sxSuPZrOW5wTVqaprnbv3l28h/2ZdVXrr8+q1SXLZFvlXMTrrv2stg+SpI2uk/M5/qxpjVRbdzuGrg3eZ667+P1URHl20vSdFs9ruM6OKM8AuN7jmQH39xHlXM74x7GlSZIkSZIkSZIkSZIkqSv5YIwkSZIkSZIkSZIkSZK6kg/GSJIkSZIkSZIkSZIkqSv5YIwkSZIkSZIkSZIkSZK60uaXfQGrodVqFT/btm1bivft25figwcPpnj79u0p/uCDD4oyT58+neILFy6keG5uLsVLS0spfvLkSVHm/v37U9zT05Pip0+fpnh5ebkoQyW2iddey8+EsX1EROzYsaPte+7cuZPiu3fvpri3t7coc2RkJMWDg4Mp3rw5d8mHDx+m2PpePY8fP07xvXv3UvzgwYMU1+p3dHQ0xaxf1ic/c+vWrUWZbHe2kReD4+/i4mKKJycnUzw/P1+UwTH+9u3bKZ6dnU3xo0ePijIGBgZSzLln586dxXuexXklomxXZBsp70FtPuYYwDbAMf/+/fsp3r17d1Em5wDO+X19fSnmGiAi4tq1a20/l/i3cgyJKOfI2jrqVcP71N/fn+Jdu3YV7+Ea7ebNmylmG2K727RpU1Emx3h+BtXK4DzC19Te87ya1llUG4ea3tPJGphl2Jab1e5RUxtpGjNq6xmuq7mO4nua5r9aGXv27Ekx++nRo0cby5yZmWl8zauG9Vubm4aGhlLMvTbrhvMdx7qIcsy8ceNGiqemplLM+ZDzdES5p+ffxrGf68OI5nH4VdTURvbu3Vu858CBAynesmVLii9evJji73//+21/H1HWH9sdxzLu52us79XB+ZpzQCdrIvbx2r7oWbU18PPOb1oZ9iPus2pjLc9SeGY7PT2d4tqZ7fXr11M8MTGR4jfeeCPFw8PDKa7Nd7xWx4jmvXWtb/K8hf2Z93lhYSHFtb7JtSbXgU3rxohybOIZD9su/1bPWjrDuuA5yaFDh4r3sI1w3cDz2E7a4a1bt1LMtSXbYW29ynGC8xmv03llddTuK/vjRhmvm85FpOfVSf9oOtPjmrl2js7vzjiG8jNr50b8jtb+sDJN9cm5i99PcR1eew2/w+IYy2uolcn1AL9L4TlCbS6/cuVKimtzdY0tS5IkSZIkSZIkSZIkSV3JB2MkSZIkSZIkSZIkSZLUlXwwRpIkSZIkSZIkSZIkSV2pTLLbBWr5iJlbdGxsLMXMi8580+fPny/KvHz5coqZ15y5upjLq5b3fG5uLsW8bnNTvhisC+aviyhznDF33uzsbIpZn8xvGxGxb9++FPf396e4lvdaL14t7y/z4DFnHWPmuIso8+AyT+7777+fYuazreXAY9tsGgPMaVzXdF+YB5M5rDvJT7hz584Ucx7hHBFRtgHOG8zXyM+o/V1Nea9V3rda3XCMZxu5du1aipnDvjZGfPazn03x0aNHU/yJT3wixVybREScO3cuxZcuXUrx/Px8itl2a22Z4wrXUYxfhbUHx97h4eEUHzhwoHgP2xXvK/tz032OKNcWHJvYdh89elSUwTGA19mUe7uTMYTrF8Yss5YnmD/jezi2PX78uCiDY2htfbeRsG54j2p9sWld0JRrOKJcAzfleWaZtVzRnL+4Tmb/YP7iGvYPjm9cdx8+fLgog2M729mrqGmfxPsaUa6BOWZyTGC7ZP7xiIipqakUc76bmJhIMec/xhERV69eTTH/Vu69a/3DtXaJ8xf77/j4ePGePXv2pJh7Le6bTp8+nWKem0SU4wpzlNf258+yblcP5wmukTh/19ZEXPNwDuAaiJ/JdUVEOW9wbVF7j54f+xbvc23u5fqTYwbHlVr/5l774sWLKX7rrbdS3Mn5XG1eULaSvfbMzEyKuQbgXru2px0cHEzxkSNHUtxJm+H81bQv4jqytm9ybilxbdnX15di7hsiynmB+xXO+azL2lqTa0muPa5cuZJittuIcvziXNS0P3VM6QzndLaHTu5j05zfSV+tnbf8pDjXrMX5m+1uY2k602k646mtq5s+g2t1xrXzOI6HTeeXHPsjyv34Rj/TWwu1MYLjStOcyXV2bY3EdtW0JmIbqa2rOUc2nUV28v1cpxwFJUmSJEmSJEmSJEmS1JV8MEaSJEmSJEmSJEmSJEldyQdjJEmSJEmSJEmSJEmS1JXKxE4bEPNb1XJgjY6OpnhkZCTFzIl17ty5FB8/frwo89q1a22vg3nSeF2162ReLXP+rQ7eV973iIitW7em+M6dOylmnnvmwK3lTWPOYn4G2yFjc9OuHuYOZt5D5qOt5WdkPj6OASzjxo0bKWbuxVqZa5Fr9FXEvra0tNT4nqb8jCxzenq6KIO5tDlujI2NpXj79u0pruVWZE5Ptm3bzMryns/NzaX4woULKT579myKOb5HRExOTqb4s5/9bIqZ5571H1HmW+V65vLlyylmXmy2uYjy72cOT8Zsp924VuHfyL7HnOURZZ1zjDh27FiKBwcHU1xbi9y+fTvFHEdu3bqV4vn5+aKMpjGBebI5V9XGQ5bBfMNsE005j2tl8Lp5L2r5vXlPa/1wrfBvrq0LqSnPOdcAnfx9Tfmoa2Vwj8L2z7bKMnbu3FmUybrhGon1z8+ojdPXr19PMedd9o/a+Me2/CJzFm8UTfmnh4eHU3zw4MGijP3796eY9cn6Y/9lf48o5+GrV6+mmHtx1m+tTP6tfA3beq1/uI4q7wHXCdy/sH1ElPd2YmIixVxnsT3U6mZoaCjFHMs4hjblSdeLw3vN+mMbqq0TOEdy/GaZ7M+1Mjnmc2zy/GV1sO5qa02Oz+y/3Hvv3bu3KINjFc/suDfjWp3zYUTZztiGbDPlPait2e/evZviprNQ3neOB7UyuU7ke7ivjijHDa5neKbLdlpry44rpabz19qanXtUtgnWFfcj3HtElGvcI0eOpJhrzfPnzxdlvPfeeynmtTftLXjdEZ771vA+sT5rZykPHjxIce3MvR2204iyPzetHWvjH8ttWiPx97VzBb6maZxpOiNYiW48F3xendzHpvtUq7umNsP+wbiTsyhiO2Qfq/UPXjvHbd6f2nfjtZ+96njfOjnT4xzIdTNj3vfa2MYxlVj/LKM2t3Oe5d/Gc4Ta2pztrNY2axyxJEmSJEmSJEmSJEmS1JV8MEaSJEmSJEmSJEmSJEldyQdjJEmSJEmSJEmSJEmS1JWeP8HYOvC8Oa0jIsbGxlLMvGjMZ3X8+PEUnzt3rijzzp07KWYuLsbMX8pcXxFlTjDzSq4O3lfmkY0o8/FNT0+n+PLlyymem5tL8ejoaFEm65w5AZlXtdOcaPrJMQ8e88AyX10tTyzbEfs8P2N2djbFbEMREYODgylmm3FMWJmmfKrMg1jLo9iUx575ipl/OqJsAxxnmMOa810tNyn/tqZcpK9iG+I9quUo5xzP+8g2wd8zZ31EmdP4ypUrKb506VKKv/CFLxRlMO/1Jz/5yRSPj4+nmDmv33333aJM5l9v+tua1ioRZQ7bppyo603TnFDrz3wN7yPHiKGhoRQzd2pE2V85F/E6atfF6+Ba4+7duynmXDQ/P1+UyT7D6+S94GfW2gzLmJqaantdtTzJAwMDKV7L/MS8fua+reW1J447vM8ss5ZLvalvsf/W7hHnHq5n+Ldwfcv3R5R1w/vF+uX8yHEqIuL9999PMce7TsZl/m21+WAja8pZH1HWF9eeHKtYlxHlvWZb5tjEMYL1HVHOiR988EGKJyYmUry0tJTiWv5pXjtf0zR36UMcw9mGuA+utZnbt2+n+NSpUyk+c+ZMitmGmBc9ojwH4n6e63vGnPu1MrV+w5+xr7GuaucgXAOxz3OfxL1YbR7mdfFzbROrg/e5drbC+mZ/5RjAPVJEOcfPzMyk+NatWylmfdfWSGxnHJt4nar356a+xX0T52v2/4iyzXCPw7h2Dsx5ZN++fSnmOMKxrPa3cm3puFLuT3kOVjsb5V6AZysc81l3IyMjRZkcN/ga1ndtj8PXcL3KPS2vm/vkiHK9znZWOwfsdtyfcK1ZW/fzHIN7Z95H/r7WV5vOytjfWd8R5Vj06NGjFDetT/n6mqY9bdM6rPa5jHn/auczG72tNp1jrqRvch/F99Tql+2M9cW2y7h2BsBr52t4xsP9XK3NcH/HOZX9h+u0iPIec+32KuA9aKrv2tzEe9t0DsI2VpubWH8cE7g243nNyZMnizL5HQXHrqNHj7aNI1Z+7ruxRydJkiRJkiRJkiRJkiTpx/DBGEmSJEmSJEmSJEmSJHUlH4yRJEmSJEmSJEmSJElSV/LBGEmSJEmSJEmSJEmSJHWlzS/7AlZi06ZNKR4eHk7xwYMHi/cMDg6m+Pbt2yk+ffp0is+dO5fi+fn5xuvYtm1bint6etrGfH1ExGuv5WeVWq1W8Ro9P95X3vsdO3YU72H9sg1MT0+n+OHDhylmfdc+9+nTp23j5eXlogytDt7rR48epXhxcTHFDx48KMro7+9P8YEDB1K8c+fOFN+9ezfFs7OzRZksg22Z7fTJkycptg11puk+PX78uPjZ/fv3U9w0J/T19RVl3LlzJ8VsZ3NzcylmG9qyZUtRJscejisr0e3tqHaPOKbzHnDe2L9/f4p7e3uLMjmPnD9/PsWcV65du1aU8bnPfS7FX/ziF1PMNdCuXbtSzPVQRMSFCxdSPDk5mWKumTh21fpH05qH6xuObT/uZ2uFcwD7aq1u+JqrV6+2/Yxjx46l+I033ihew/rifeSYwDVx7TVNaxH+HYw7ce/evbZxbX3LPnfx4sUU19bNtHv37hTX2uZqYZvft29fikdGRor3sJ3NzMykmHM6+zPrNiJi8+a8vdu6dWvb9wwMDBRl8Gecv1gm/47aGmlhYSHFnN+49zp79myKOU5FRLz33nspZp/bvn17ijlvR5RjJt+z0bD++ffUxgj2G9Y3y2RfjSjrnPea8x/r/8qVK0WZ3J9zzmSZ7B+cl2s/49/6Mued9ap2T7gG4vjG8a/WZt59990Uf/vb304xxwCOM2y3EWUb4LjMv6Xb17frSdMelr/nuiEi4saNGym+efNmijlndrJvYrtibBtZG7X1GtvA0tJSioeGhlI8NjZWlLFnz54Uc/3O+NatWymurQnYdj2zXRn2Ld5Hxlx71vYFHPO5TmD98uyldl2c79gmeB21cYZthp/xKo4zXDdyXVjbS5w5cybF3DvwPVzjjY+PF2V+6lOfSvEnP/nJFDetGyMi3nzzzRRzDcQ1LtezU1NTRZn8W7iOYn/gWr0b17NNY37tOxieyXFOYMx9EvtuRLnW4FjF+Yz7+4hyLOJ8x7Gpk/MZntE1ndk1jUu162A7bNp3RjSvxV+m2rXwvjSdrTCulcl727QGrp1P8zo4FvH7KNZFrW44f/E1PBPiPqtmYmKi7e/Zf9ivI8rxrzYfbGRN652Ist+wLnjfat9r19Yjz2L/ZjtkXUWUa3F+j9k039XO9DhGcv/GsYt7tdq1djrOrJ/RSJIkSZIkSZIkSZIkSXqBfDBGkiRJkiRJkiRJkiRJXckHYyRJkiRJkiRJkiRJktSVNje/5OVjXijm1WKeyFpuWebrunTpUoqZ45q5Zmv5q5h7rSnPXCd558xPuzp4r5l7jW0qosz5x/y0CwsLKWbdMSdaRJkjjnkGmRPtVcw1+7I01cX9+/fb/j6izLd46NChFDNfKdsU8+pGlLn02IY4rpgXfXXUcnwyzyXHAObrHBwcLMpg/bANMC8sc8kyJ25ExO7du1PMvJHMCcm2XftbX0VN94H1y7pgjteIss/fvHkzxcw1/Kd/+qdFGdevX08x83H+zM/8TIqPHDmS4o9//ONFmRyrpqenU8w8oGfPnm37+ohyjGS749jGnLkRZU7ophypLxLHUvY95oGOKNeOx48fTzHvE8eE0dHRokyuJdiumMP8wIEDRRnMjc7X8Dq4/qmtTXldnJtYv4xrON415dauraM5D7PM1cS15cjISIoPHz5cvIftrOm+ssxO1q+8T+xrtX7FMlh/k5OTKb548WKKuc+KKNs/x7Jz586lmPmJa+PM7du3U8y/7eDBg21/H7Hx9l5N9cl843v37k0x21BEuafl/Md1Qm1tyeviGMn6PH36dIqZfzoi4urVq23L5HjIsY5xRNlneP82WntYDU3r2YiyXbGvsU1xfoyIeOedd1LMNsG9NsvkOBVR1mcn5y9aG2xXrBvORbV1FscRziNce7LM2lqE61P30i9Hbd/FuuGYwDUfz1oiyn0x9+8TExMp5lg1NDRUlMm27LzxYjT1NfZvjiERZZvgOprtbHZ2tiiDewfutfm5XP/Xrotjkee+5VjL+87+H9F8Jsv3cO/I/UtEuWc5efJkio8dO5biN998syiDr+Fam3tttlPugSLK+Y7nhA8fPkxx0/dTERt/7OJ6lP27tqflexhzr1Ab85vwzIr3tXY+w7bM93BM4LkIzw0jyrGK4xvXVVwT1c5NuBfj+SX/jlq7W0/jG/cOrLuIci/NNsMyavuRps/lmQ/nkVqZ7OMcV7jHZZm1/RyxPtlGOMbW2iH3c6dOnUoxx+3ad/js22z/Gw37N+uXdRtRrmn5fQPbaW085zzRNIfyumr3/fLlyyl+7733Uvz++++nmONQ7Tr5fQTPGXjmXbtfK93jezIgSZIkSZIkSZIkSZKkruSDMZIkSZIkSZIkSZIkSepKPhgjSZIkSZIkSZIkSZKkrlQmWl+HmFuMuaWY05r5xiMibty4kWLmkWT+RubWq+UqZE4rxsxVV8trr9XBnGW898zFxlx8NcxpzNx6rH/mf4soc4nW2pXWB+bBZA5cxhFlnx8fH08x85cy520tpydz/vEzOD6yXdbydatZJ3lQmW+TOcs57tTmpqZ54vbt2ymen59vLJPjGdsI8xM35ZmM2Pj5iFcDc1gyZ2stvy5fwzmAdcX6j4i4du1aiv/4j/84xcwt/KlPfSrFb7/9dlEm11FcZzFPNmNeU+06uM6amppKcS3nLe/hWs6Z7AfMyVzD8ZdjBNcRzMnLHM41HJs4htTGBObKZv1xvcJ8xFwzRZR5X/kZTWNbbQxhDlu2mYmJibZlRpRtdy019WfGEWUbZ/3y3rPuamWyrTKvL9sd55WIcp5gf2Vu4XPnzqWYdRdRjmdcA/H3zIlcywHO+Y71f/jw4RTX1ubraS3etH+JKPcbbCPMN86/mTnNI8rxjuuZ2pq3qQzOC8ePH0/xd7/73RTXxj/+/aOjoyk+cuRIirnuru3vOhmLXnW8R9y/RpT3mnMCxyHmH4+IOH/+fIq5HmVbZduvrbN47SvNN64Xj3nrWZ8ci2trYM5F3Dtz/OP4yGuIKNdq7p1fjtrem3MR19FcJ9TGfI5NHPO5X+H6p7YvZjtyHlkdbBOsi1rdcF3MPQ3nM+49aj+7fv162+saGxtLcSd7Ws53ryKOtezPtfodHh5OMe8rxwzuNbgniijHlVOnTqWY3x2dPn26KOPTn/50ir/4xS+m+NixYyl+8803U8y5K6Jsq9xrcazqZC7j2MV4vX9nxfrlnrbWryYnJ1PMv5lzAO9BJ3NA0/q0thblvpb7taaYe9yIsg/xbIq/Z5up9Y933303xWfOnEkx12G1/Tr/fl7HamJdcW/Bs5WIcpzhHM/7xs+ozQGci1if7O+1NsM+zbbKmPe5k3U1z9vYf1gGv2uPKPd8Fy5cSDH7x1tvvVWUwfbNPrbeNZ3p8My21g65fuU9YHtgu4wo2xGvi2c8nFdYdxERJ06cSPHFixdTzDUU1+ZcM0WUZzx8D/tUbT+3Up4USJIkSZIkSZIkSZIkqSv5YIwkSZIkSZIkSZIkSZK6kg/GSJIkSZIkSZIkSZIkqSutuwSCtZyGzLXGnNa7d+9OcS2v4OXLl1PMHFjMo8X8VfyM2nUxZxxz65mL9uVhzmrWVS1fHXNJMvcoc7ExB1otR1wneQO1PjB3MPMz3rt3r7EM5sk7cuRIipm/kfk5I8q8oBwjmZ+R40wtz6BWB+8120wt3ypznHLcYRnM1zg9PV2UyTbCz2Dubc5FtTy6HKteZE7HblWb49lfh4aGUsy5qLb2YC5ljhvf+973Usz1Ty1P6Oc///kUM8/rvn372sa18fDq1asp/va3v51izqG8NxFlft9aruzVwjmA11vDvtWUc57r1Vrf42uYK50x1yoREdevX0/x2bNnU8w1Ev/2Wt1wzcM8uRzvOskLy7+Vea75t/b19RVlMIc78zevJrYRXu/NmzeL93BMb8pzzvtcm+OvXbuWYvZ55oLmZ9Z+xnFnfn4+xcw3XduLsc7ZRrg2379/f4o57kSUuZc5ZrCdso9GNOdeXkus78HBweI1Bw4caPsalsG/p1Y3bEccix48eJBitoeIcsxnTvrjx4+nmO2wlo+de372b66z2YZq+yz33yXeJ/ZN3ueIsm44j3DcYb75iHINyzI4xnONxPEwolzzcv6y/tdG7T6zj7O/8vfcA0eU8yrbDOcErqNrcwDHN66BtDZq953rKu43+HuetUWUYxXXCVy/8DNqew/Os03rCNvUi9HJ3oxrHM4BnN+4Towo10Tca09NTaWYcxHHoYhy7OG188yH67C13AOvFdYn49pekesCzvm8T2wPtX1h016a3xWdPHmyKIN7PK5xv/CFL6T44x//eIpr3x3wb+W1X7lyJcXc709OThZlcnxju+Q6a719X8G6YV/lPYiIOHPmTIpZ3xwjms5jI8o5gPeRaxPGEeW4wXMjxjw3ZFwrk+sstinurTk/RpR9ivMb11C1c6NOzkRWC6+H68LXX3+9eA/XErx+jit8fW1/wutgm2Ff49okotw38TyG/YPjEM+FI8pxhOdIPBPi3147V+B18byLbbd23sF7ut6/f2C/4BjBtQbPudjfI8r+y77G8a92Lsi9FNsV2xTbw+nTp4syucfn57KPHT58OMWdzHe1Z0NWy/qa5SRJkiRJkiRJkiRJkqQXxAdjJEmSJEmSJEmSJEmS1JV8MEaSJEmSJEmSJEmSJEldae2SNnWolveX+aeYe4u52j744IOijBMnTqSYea6ZN5T5G2t5Qpk3rimnu9ZOU3435s6s5bVnfj7mQWTePH4G88FFlG2VuWXNP7x+NOUwZp7JiDL/KMcI5vBke6jlkWQOY5bBtt4UR9jOXpSm+8gckMzvGFG2gaY8sGwPjCPKHLYc75jfku321q1bRZm8duaRZE7U9ZaPeL1gf2zKP8y6iyhzaTPvNdvE+++/n2LmjY2IOH/+fIo/97nPpfinf/qnU/yxj30sxbX87FyrvfXWWylmW6+t/9iOate+WlYyTnItwfGa94k5rBlHlHl7mRucv6/llm3KY8/+zfUP1zsRZd5y3q+mfNS1uYnXzjGUuYUPHDhQlMF5t9auVgvrgjl72Vcjyhy9zFvPdQHbWK2++bnMt849Tw37Hscm3lfmEq7lF+d8xvzS7B98fS1fN8cRXif/jvW2N+P19Pb2ppj5pyMifuqnfirFvE9N/Zf9KqIcEzjOTExMpPjMmTNFGWfPnk3x1atXU8xxppPc2nzN8PBwitkfXHt0hu2O/ZX9eXx8vCiD/ZFrD7aRixcvFmVwLOJ1cL3Dts44ohybbBMvR+2+s25Yf5zja3vtxcXFtmXyDG/Xrl1tPyOiXK+4T14/uC7mOotzF+s/IuL1119P8cGDB1PcNGfyMyPKtsu5iNdlm1odtfvK+uJruE7kXi2i3H9zXc11FNfqtbmpab3K+ZBjHfdyEd3frmprdp65N+GYz3V2RLm2ZF2w7vi9QER5fvbOO++kmGukK1eupPjzn/98UeaxY8dSzPMX7oO5p/zhD39YlMn1POc/Wm9nyVwXML58+XLxntOnT6eY+2L+jfz7antttiv2507K4Hu4D+b6pZM18ODgYIq512abOXLkSIpr32Gx7fI8g9ddK4P3o3ZOsFqa1omjo6ON7+G+mLjmrdX3zMxMijlm8PeXLl0qyuB33bOzsynm+oVlci6rvYfzG/82zo/cq0WU+3f2F7bL2nkHy11P+7lO5ib2X+6lee5RO/dnXbAdcp3AOKKsc849PK/h69nGIsozgKb65Bxb+1tfZv2un5YlSbA3Me0AACAASURBVJIkSZIkSZIkSZIkvUA+GCNJkiRJkiRJkiRJkqSu5IMxkiRJkiRJkiRJkiRJ6ko+GCNJkiRJkiRJkiRJkqSutPllX8CmTZtS3N/fX7zmwIEDKR4eHk7x/Px8is+dO1eUceLEiRRfuXIlxVu3bk3xtm3b2v4+ImLLli0pbrVaxWv0crAuWFfbt29PMdthRMTt27dTfO3atRTfunUrxWwzT548Kcq8f/9+29c8ffo0xcvLy0UZWhu8948ePUrx4uJi8Z579+6luGl86+npSTHHsoiIGzdupHh8fDzFvb29KWZbf/jwYVGm7Wp18L6yf7N9RJRzC9sE65dj28LCQlEmx67R0dEUj4yMpJjtkm0uIuLy5cspvnPnTorZ7hhHOEfWNN2TzZvLZdrOnTtTzHvNcYfzytTUVFHm9PR0irlGOnv2bIo/9rGPpfjgwYNFmX19fSnmmMl5eHBwsCiDfYjXud689lp+3ryTteSzamMz78Hjx49TzPplXCuD8xnXJnfv3k1xbW7ieMYy+Hted63t1679WTt27Egxx7KIiF27dqW4NhatFt4DrhNrcwD71ve+970UT0xMpJj9m/0oohw32K7YN2t9jz8bGBho+7mcu2r3vWl+Y3/h31pbq7MdbbR5hmMG79HQ0FDxnj179qSY943rvqWlpRSznUZEzM7Opph76ePHj7f9fUS5LmD9Hj16NMVjY2Mp3r17d1Fm035to9X3y9K0L+a4ybqptUPW9+nTp1N88uTJFN+8ebMog2MTx3iOO/w944j6OKG1V6sHjgmsP7aH2pqPYxXnO44j3OPU1tVav9gmOL9xPqutszme8Wz51KlTKZ6bm0vxgwcPijL37t2bYrZtrvea1rdamU7OtFh/rCuuiSPKOZFrkevXr6eY+yR+RkS5vuP4x30S982e361MJ2M+10RN3w3V2gzXRFx7cw3E87qrV68WZX72s59tGx86dCjFPJ/hNdRwbOrkLJk/W8vxjX8TP7v2HQz7HuuPbYRx7e/j/o0xz1p4thJR3ke2idr3Dc+q/a3E+uTfzrmM96qT6zh8+HCK2Q4jyvPL2l50tbBuOhkT2M64Hp2ZmUkx54TaPfvggw9SzD7PMngeGxExOTmZYrahprGrdj7DcwW2AdZd0xlRrQzuCXidtTGVZbAeX6batXBO59rz2LFjKeZ9rY0RHBNY/9wT8ewxovwe+8KFCylm22bd8PmLiPJcgK/hvWCfW091GeG/GCNJkiRJkiRJkiRJkqQu5YMxkiRJkiRJkiRJkiRJ6ko+GCNJkiRJkiRJkiRJkqSu9NKT7DLnWS2/+L59+1LM/GTMzcYc1xERly9fTjFzjTL/cC33GjHXoDmt1w/mUmdOs07ql3kBFxYWUsw8sMwlW8sDyxyAzAtp/uH1g/XXlPc3omwjzJXI/I2M+f6IMq8g83EyBzLbYS0vNnOemrN4bbANRTTnbGX+xU7GLuanZK7JppyQtXy1LIOv4RjLMTiiHN9sdyvDe8v8qxxXWDe13MHMe8111cTERIq/+c1vppi5ZiPKdsXPZT7a119/vSiDbbWWe3U9Y13V+kUTri07GQOIfY0x+zPniE7yize9h+NfJ7lleb+a8mRHlDltV3K/VqppnVCbj3l97Dcsk+2Ba4BaGdu3b28bd3IfmW+Y1836rLX1pnzstJL+stE0/Y21dQPXiuy/HL+ZO5r5qCPKfNM//OEPU/zee++luJYbfmRkJMUc00dHR1PMOYBtLOLVaANrgfeRec3Hx8dTfPDgwRTXxtFz586lmG3m/fffT3Ft/ubYw3GHv+fYVTt7sc28HLzvtbrhOpD1yTnyxo0bRRkcv7jG5bjCfXGtfbgfWb9YN1xrcp3F30eU57w8W+bcMz8/n+JO9h6d7IO1Npr6M9tI7fyVcyTX1VyHcR89NTVVlMn5ranNPO+aOaJ5v6e6pu8OuBapnaXwe6ylpaUU8yxtZmYmxSdPnizKZDuanJxM8Re+8IUU89yEf0dExIEDB1LMdsk9Bdt2RMTc3FyK1/I7DO6L2Mb590REHD16NMX79+9P8Uq+KyK2IZ6D1PZNfE3TfeTYde/eveI1nK/YDjm/Ma6dVfD7CF4nv2vl6yMijhw5kmKuzVYT2zTvUW2tyf75zjvvpPj69ettP6M2B3BfxDGB9VtbzxDXvDwH5rjE10eUdcHv6Blz/Kv1l6Zzoab5rvaal6lpjogox99Dhw6lmOckHBNq/YZtk2fy/H2t3fE1bLvszzwT4HgZUa6J2EY6Wa+sJxvraiVJkiRJkiRJkiRJkqQO+WCMJEmSJEmSJEmSJEmSupIPxkiSJEmSJEmSJEmSJKkrlYmxVhnzDTN/J/NuRZS5uphL9syZMyk+ceJEUQZzxO3atSvFzDXLPJK1vGnMM8b8huspJ9qrrimHXS3/KnM+Mscfy2BbZhuKKHMYM4ejeWDXL+aNrOX0ZI5O5jjlOMP8fcwbG1G2O7ZLtkOOVRstv183YX+u5Y1lbsnnzXHcSW7ZCxcutL0O5uqt5cwcGxtrG7N/zM7OFmUwb2YneVP1/DjPMAdoLacv2xVzj3JsYq7S8+fPF2WyftkfmPP2M5/5TFHGJz/5yRRznn0VrWRt2fQers05j9TaTFMe+9XIN875rDa/vcw5j/eAY2utHtgPPv3pT6eYYzz/vu3btxdlsp8w7y/ru3bP+Jqm3NBaGfYT7gump6eL93C+5XjMPOgXL15MMdcItZ9xPct5pbZfP3z4cIoPHDiQYrbLpvzjWpnafeSYzhzzrKu9e/emuJb3nOuEa9eupfjOnTuN18X1ZlPcNC7p5WFd1M7OuNbkuMJxZ2Jioijj1q1bKWYbYZmchxlHlGOq1g+uq7i34LlwbV/MNrFnz54U9/T0pJjjHce6iHIfzOv0/GX9aFqbLy0tFe9hm+Hc09/fn+KFhYXGMrmXZhvhXovfV9TGKbZ3fq5nyy8G64r7qtrPuD9j/XKOrJ0D82ff+c53Usw5kms7tuOIcr23f//+FPNvZduOqK8J10pTm66dWfAMvmm87uS7oqb1Z9N5a63cppjzX+0slWfLHBO4z+TruXaPKNs2xx2uw/h9Re1zamvE1cLrmZubSzHXERER7733Xoq/8Y1vpPjq1aspblp7RpR9ifeNey/OARHlOppzEeOmM6GI5nOhpjOgV2Evxr+xNrayvlifrIupqakU8zub2s9u3rzZtoza2MwzHs5Ng4ODKT548GCKeVYZUf79G33Nu7GvXpIkSZIkSZIkSZIkSfoxfDBGkiRJkiRJkiRJkiRJXckHYyRJkiRJkiRJkiRJktSVNje/5MVi/jLm2RoeHi7ewxxYzKXO/G/nz58vymBeOeaWZa5F5m7jdde8CrnVulUnOVuZb5F5A5mfmPn9IsqclyzDNrR+McdnLXcwc6NzPOO4wnyntTySbJvMG8jPpFq+P7Yz8w+vjdp9Zv0y7ys15S+OKNsI8xMzFyXn1PHx8aJM5prknMm8sbWctxxDa6/RT479m/lrd+zYUbyHeX65NmOOVLYp5riOKNtVUx70Wk5j/mwt8xG/yl7F3MFroXYf2R+5lmSOcpZRm+O5Z2mqP+v35eG6gGsA5kGv/ezUqVMp/qM/+qO2v6/hnH7kyJEUj42NpZjr14hyDcs9z0bPP72RcUzgOFNbSz6rlrN8ZmYmxTxr4dhWy8fOvTKvyzazcbCu2P8jIgYGBlLMPc21a9dSfPPmzaKMxcXFFHOvzTUvx9RO9mLui9cv1hX3EtyPRpRzE9sM2yrbIePa53IM5XjH8ZFrO62dpnVXRMTdu3dTzPmMYxnPdK9fv16UefXq1RQvLCyk+OjRoyk+duxYijk/RpRjJM94Ohn/9GJwL8V1F8cIrqNr9Xvr1q0U81zkxIkTKWabqq2h3n777RSz7Y6MjKS41j/Wczuq7Wmbzo/WYq3JtcmLUJtH+DPWb9PveV4XUZ4Nc57lHDo0NFSUUVsTrhW2Ye5pat8FXrlyJcWXL19OMc8++TePjo4WZbJvDQ4Opnj37t0prn2fyHGC7YrjDtt2rX94DvT8as8HNPVxrivYxmrnNRcuXGhbRtN31BFlO+IamDHXN7Xxs9v2593110iSJEmSJEmSJEmSJEkf8cEYSZIkSZIkSZIkSZIkdSUfjJEkSZIkSZIkSZIkSVJXevGJ7howFxdzzTF/Z83s7GyKmd+NuRgjIvr6+trGTXmwa3kU13NuRbXH3IqPHj0qXsOf8T1Nufhq+d2acjxq/WJ/r7UZ5nWdn59vWybz9zEHdkSZN3Bubi7FzFW5Z8+eFNdyHTKvJvOE2i5fntq48aymfMW1n924cSPFzJH67rvvpvjAgQNFmZ/5zGdS/OlPfzrFnMtr+Wlr+Vu1+jhX1cYEtiuugZiblHl0Oe5ERMzMzKR4aWkpxVx31XLxsi2bA1cbWa39su8xbtpr2Cc2tqa1ZW0d+fDhwxRz38vfUy3P+759+1J89OjRFHNdsHPnzqIMzi22zfWLa03uC7iGO336dFHGxYsX276H83dtj8N9ENsm1yK2qfWDdcF887Wc9D09PW3fw3XigwcPijKa1o67d+9O8bZt21LMPW+EZ3obCc8oON/V2gzbIvcs3NNwn7y4uFiUyfmOYxnfw/HRs5aXh/29dj7BcYL1zXFo7969KeacGhFx/vz5FF+6dCnFnO/efvvtFHOdVrtOrgdr/UGro2ke4XzH9U5tzuR3VmxXHEeuXLmS4uvXrxdl3rx5M8VsI5/61KfaXmftc9cT3uf1YjWuq5Mya+d+7dS+j+X6nW2dZxe1z+S1rmU9sb1yfq61Z/ZHrjX5N3MOOHz4cFHm8PBwirlP4hxQGxOa9kHuk9ZGrc1wncfvYDhfv/POOyk+ceJEUSa/+6u1iWdxzoiI2L9/f4rZVjnGs22/CtbnrCFJkiRJkiRJkiRJkiT9hHwwRpIkSZIkSZIkSZIkSV3JB2MkSZIkSZIkSZIkSZLUlXwwRpIkSZIkSZIkSZIkSV1p82p/QKvVahvTo0ePip/Nzs6m+PLlyymemppK8aZNm4oyhoaGUjwwMJDi117Lzwg9ffq07XVqY3ny5EmK79+/3zaOKNsR20x/f3+Kt27d2ngdbFfLy8uN79H6wLp6/Phx8Zq7d++meG5uLsW9vb0p3rZtW9vfR0TMzMyk+M6dOynu6elJ8ZEjR1Jca9sffPBBiqenp1Ps+Ld2msYAtjPWzebN5TS+a9euFHPsunjxYtv4+9//flHmmTNnUnzp0qUUv/nmmymujYf8Wxz/1g+uzdiumuLt27cXZY6MjKSYbZdzLMeyiIgtW7a0vU6p29nmXy3cr9TWY5xLOed/5jOfSfH4+HiKa2vN0dHRFO/bty/FO3bsSDH3zRG21fWM7Yr7lStXrqSYe43vfOc7RZnf/e53U7y4uJhirgHYTiPKeZ/7IttUd+E53+3bt1PMPS/bbUQ5Vr3xxhspHhsbSzHHuwcPHnR2sVqXuHdkm+I4VHsNz/D27t3b9vcclyLKdsU5ku+pzZlaH2rnEVxnLS0tpZj128mZHtvmhQsXUsyzk2PHjjWWybbt2crGwfUNzzxqP6uNRc9aWFhIcW08fPjwYYonJydTzHPh3bt3F2U4nm0cz1tXtdfXvl99kZ+52jgucm1ZGzcHBwdT/PGPfzzFr7/+eor7+vpSXNvzPO+6wD3Q+tG09oyIuHXrVop5hnPjxo0Uf/Ob30zxO++8U5TJOYDf9XH9Wmt3w8PDKea5/Xrrry+Dd0CSJEmSJEmSJEmSJEldyQdjJEmSJEmSJEmSJEmS1JV8MEaSJEmSJEmSJEmSJEldafNqfwBzcTHPFvN1Mu9WRMTVq1dTfPLkyRRPTU2leGBgoCiDOTqZf5i5u5h7sZbj3Zxv6xfbHetzfn4+xcxpHVHmX2d979y5M8XM3bZnz56iTOZ8Y7viZ2r9qo0J9+7dSzHzDLIdMs95rf6vX7/e9j1vv/1228+o5Qzkz9i2GZuveO003Wu2u1r9Mm8kc0/u378/xZxDb968WZQ5MTGR4pGRkRRz3q3lI37e/LRavzZvzsvHWt329PS0LaOTNZTrLEmvstqagPM+59+PfexjKWYebI7fEWXec+6Lm9aJWj9qbYZtgPsN/p7rwFOnThVlHj9+PMWPHz9ue12jo6MdXas2BtYdY7apiPK8he3w3XffTTH3JxHl+MU9D/dJ3BfX2qntcONoOuPj2UtExOTkZIoXFhZSzPls69atKa6d+dy/f79tzHZmG9tYWOccz/gdBtXWWcQzPp5Pc23HNhZRrt3YH7RxdLKu5tjE7x/efPPNFPf19RVlPHnyJMU8J2w6v4lwPHvV1M6bu0mt7/X29qaYZ9/Es9Da2ah75+5R2+PcuXMnxfxu8NKlS23ja9euFWX29/en+MiRIynmHMA4olwndHt/XgnviCRJkiRJkiRJkiRJkrqSD8ZIkiRJkiRJkiRJkiSpK/lgjCRJkiRJkiRJkiRJkrpSc/LLF4z5Vpnj9fLly8V7bt++nWLmub569WqKmUMrojl3LPOAmhd2Y2N9PXjwIMXMcc1cmxFlW5yenk4xc7hu2bKlbRxR5nNjzHbK2Ha4ftTqoml8Y5tZXFxMcS1fMfNiX7lyJcUcu5h/+MCBA0WZ7A9s/7az9aOpLmpjFzE3JfMPcz5km4sox7PR0dEUMx9xLYeq7ap71erbPLqS9OI17WkZc+7tZGx2/O4ubAPcK3BfwLzotT0t85izzezevTvFfX19RRncw9juNq6nT5+mmHvciIibN2+mmO3w3XffTfEHH3xQlMG9MvfFg4ODbePaXsT9ycbFs5W5ubniNTyfuXTpUoq5752amkrxhQsXijJ5Hs0xk9fVyX5d6xfrj+NQJ2PIjh07Urxp06YUsx2yjXHOjYgYGxtrW6Zj28axkrri914jIyMp5vxX+xyWwT2E6zK9ivg9HfsF2U+6G8fN2pquaV3A93BOHx8fL8rcvn17ioeGhlLM73lqz0KwLavkHZIkSZIkSZIkSZIkSVJX8sEYSZIkSZIkSZIkSZIkdSUfjJEkSZIkSZIkSZIkSVJX2tz8kherKf9wLVfXzMxMimdnZ9vGtfyMzFG8b9++FHeSf1gbB+uvKf9wLQ/2tWvXUsx22JR/+OTJk0WZvA4y//DG1pR/mDmuGff29hZl9vT0pJj5h0+cOJFi5iFkzuuIiF27dqXYvIMbx0rmJrYhzn/MeX306NGiDOZNZT5LtjvzrEqStPqa5lvnY3HtyP0Hf79ly5YUv/7660WZzHO+efPmtr/n3qP2Odq4eMZXO/O4detWiu/evZvi+fn5FHMfXXsPzwH5GdwDbd26tShTG0fTWLawsFC8h+1oeno6xTwHZBk8R46IOHXqVIp5ltLX11e8RxsX292jR49SzPGPcUR5/vKJT3wixRy7du/eneLaeR3PHj3Te7Wwvjnfbdu2rXiPewbp+dkv9KzadzJNe2t+X/Lmm2+mmHN+RLlP3rNnT9syXQOsjHdNkiRJkiRJkiRJkiRJXckHYyRJkiRJkiRJkiRJktSVfDBGkiRJkiRJkiRJkiRJXckHYyRJkiRJkiRJkiRJktSVNq/1Bz5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\n",
      "text/plain": [
       "<Figure size 2880x2160 with 144 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## test outputs of rotated images\n",
    "## prepare data\n",
    "import numpy as np\n",
    "import torch\n",
    "import PIL\n",
    "\n",
    "import torchvision.transforms as transforms\n",
    "\n",
    "\n",
    "feat_map_2_list = []\n",
    "for img_rot in img_rot_list:\n",
    "    feat_map_2_list.append(rot_dcf(rot_dcf_init(img_rot.unsqueeze(0).float())).\\\n",
    "                               view(Ntheta*M3, 28, 28).detach().numpy())\n",
    "\n",
    "plt.figure(figsize=(40, 30))\n",
    "\n",
    "## plt original image\n",
    "for i in range(len(img_rot_show_list)):\n",
    "    plt.subplot(Ntheta+1, Nrot, i+1)\n",
    "    plt.imshow(img_rot_show_list[i], cmap='gray')\n",
    "    plt.axis('off')\n",
    "    if i == 0:\n",
    "        plt.title('original image', fontsize=15)\n",
    "\n",
    "# plt feat with specific \\lambda(idx_feature_map) and \\alpha(idx_rotation_group)\n",
    "for alpha in range(Ntheta):\n",
    "    for idx in range(len(feat_map_2_list)):\n",
    "        plt.subplot(Ntheta+1, Nrot, (alpha+1)*Nrot+idx+1)\n",
    "        ## fetch the features for a rot image\n",
    "        feat = feat_map_2_list[idx]\n",
    "        feat = feat.reshape([Ntheta, M3, 28, 28])\n",
    "        plt.imshow(feat[alpha, 0], cmap='gray')\n",
    "        plt.axis('off')\n",
    "        if idx == 0:\n",
    "            plt.title('alpha={}'.format(alpha+1), fontsize=15)"
   ]
  }
 ],
 "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}