Interpolation - Edge modes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interpolation: Edge modes\n",
    "### Dr. Tirthajyoti Sarkar, Fremont, CA 94536\n",
    "\n",
    "This example illustrates the different edge modes available during interpolation in routines such as `skimage.transform.rescale()` and `skimage.transform.resize()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from skimage.util import pad"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "img = np.zeros((16, 16))\n",
    "img[:8, :8] += 1\n",
    "img[:4, :4] += 1\n",
    "img[:2, :2] += 1\n",
    "img[:1, :1] += 2\n",
    "img[8, 8] = 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "modes = ['constant', 'edge', 'wrap', 'reflect', 'symmetric']\n",
    "fig, axes = plt.subplots(nrows=2, ncols=3,figsize=(10,6))\n",
    "ax = axes.flatten()\n",
    "\n",
    "for n, mode in enumerate(modes):\n",
    "    img_padded = pad(img, pad_width=img.shape[0], mode=mode)\n",
    "    ax[n].imshow(img_padded, cmap=plt.cm.gray, interpolation='nearest')\n",
    "    ax[n].plot([15.5, 15.5, 31.5, 31.5, 15.5],\n",
    "               [15.5, 31.5, 31.5, 15.5, 15.5], 'y--', linewidth=0.5)\n",
    "    ax[n].set_title(mode)\n",
    "\n",
    "for a in ax:\n",
    "    a.set_axis_off()\n",
    "    a.set_aspect('equal')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.6.2"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}