PlotDivtrees.ipynb

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   "source": [
    "import os\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "from utils.coords import feet2m\n",
    "from utils.divtree_reader import readDivideTree\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "del mpl.font_manager.weight_dict['roman']\n",
    "mpl.font_manager._rebuild()\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams[\"font.size\"] = 20\n",
    "plt.rcParams[\"font.weight\"] = 'normal'\n",
    "mpl.rcParams['image.cmap'] = 'gray'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "filesPath = 'data/dems'\n",
    "\n",
    "imgOff = 50\n",
    "edgeColor = (0.75,0,0,1)\n",
    "\n",
    "for f in os.listdir(filesPath):\n",
    "    \n",
    "    if not f.endswith('.txt'):\n",
    "        continue\n",
    "    \n",
    "    fpath = os.path.join(filesPath, f)\n",
    "        \n",
    "    # read divide tree\n",
    "    peakCoords, peakElevs, saddleCoords, saddleElevs, saddlePeaks, _ = readDivideTree(fpath, returnDEMCoords=True)\n",
    "    numPeaks = peakElevs.size\n",
    "    numSaddles = saddlePeaks.shape[0]\n",
    "    \n",
    "    # read image (16 bit PNG, heights in feet)\n",
    "    img = cv2.imread(fpath.replace('.txt', '.png'), -cv2.IMREAD_ANYDEPTH)\n",
    "    \n",
    "    print(f, '%.2f'%feet2m(img.max()), '%.2f'%feet2m(img.min()))\n",
    "    \n",
    "    # normalize image\n",
    "    img = (img - img.min())/(img.max() - img.min())\n",
    "    \n",
    "    fig = plt.figure(figsize=(8, 8*img.shape[0]/img.shape[1]))\n",
    "    ax = fig.add_subplot(111)    \n",
    "\n",
    "    # plot image\n",
    "    ax.imshow(img[...], interpolation='bicubic', zorder=0, cmap='gray')\n",
    "\n",
    "    # plot peaks\n",
    "    ax.scatter(peakCoords[:,0], img.shape[0] - peakCoords[:,1], marker='^', zorder=3,\n",
    "               s=20*peakElevs/peakElevs.max(), c='white', edgecolors=(1,0.75,0,1), linewidths=1)\n",
    "    \n",
    "    # plot saddles\n",
    "    ax.scatter(saddleCoords[:,0], img.shape[0] - saddleCoords[:,1], marker='o', \n",
    "               c='white', edgecolors=(146/255, 208/255, 80/255, 1), s=6, zorder=2)\n",
    "\n",
    "    # plot ridges\n",
    "    for i in range(saddleCoords.shape[0]):\n",
    "        if saddlePeaks[i,0] < 0 or saddlePeaks[i,1] < 0:\n",
    "            continue\n",
    "            \n",
    "        p1 = peakCoords[saddlePeaks[i,0]]\n",
    "        p2 = peakCoords[saddlePeaks[i,1]]\n",
    "        ps = saddleCoords[i]\n",
    "        \n",
    "        ax.plot([p1[0], ps[0]], [img.shape[0] - p1[1], img.shape[0] - ps[1]], color=edgeColor, linewidth=1, zorder=1)\n",
    "        ax.plot([p2[0], ps[0]], [img.shape[0] - p2[1], img.shape[0] - ps[1]], color=edgeColor, linewidth=1, zorder=1)\n",
    "\n",
    "    # place a text box in upper left in axes coords\n",
    "    #ax.text(0.016, 0.016, f.split('.')[0].replace('-', ' '), transform=ax.transAxes, fontsize=24,\n",
    "    #        verticalalignment='bottom', horizontalalignment='left',\n",
    "    #        bbox=dict(boxstyle='square', facecolor='white', alpha=1))\n",
    "\n",
    "    plt.xlim(peakCoords[:,0].min() + imgOff, peakCoords[:,0].max() - imgOff)\n",
    "    plt.ylim(peakCoords[:,1].max() - imgOff, peakCoords[:,1].min() + imgOff)\n",
    "\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "    \n",
    "    fig.savefig('divtree_%s.pdf' % f.split('.')[0], dpi=300, bbox_inches='tight', pad_inches=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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