{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from shapely.geometry import (box, LineString, MultiLineString, MultiPoint,\n",
    "    Point, Polygon, MultiPolygon, shape, GeometryCollection)\n",
    "from shapely_tools import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# plot functions\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "def plot_coords(ax, ob):\n",
    "    x, y = ob.xy\n",
    "    ax.plot(x, y, '.', color='#999999', zorder=3)\n",
    "\n",
    "def plot_point(ax, ob, color='#000000'):\n",
    "    x, y = ob.xy\n",
    "    ax.plot(x, y, 'o', color=color, zorder=4, markersize=7)\n",
    "    \n",
    "def plot_bounds(ax, ob, color='#000000', marker='o'):\n",
    "    x, y = zip(*list((p.x, p.y) for p in ob.boundary))\n",
    "    ax.plot(x, y, marker, color=color, zorder=3)\n",
    "\n",
    "def plot_line(ax, ob, color='red'):\n",
    "    x, y = ob.xy\n",
    "    ax.plot(x, y, color=color, alpha=0.7, linewidth=2, solid_capstyle='round', zorder=2)\n",
    "    \n",
    "\n",
    "def baseplot(lines, title='', ax=None):\n",
    "    if ax is None:\n",
    "        fig, ax = plt.subplots(1, figsize=(5, 5))\n",
    "    for line in lines:\n",
    "        plot_line(ax, line, 'grey')\n",
    "        plot_bounds(ax, line)\n",
    "        plot_coords(ax, line)       \n",
    "\n",
    "    ax.set_title(title)\n",
    "    ax.get_xaxis().set_visible(False)\n",
    "    ax.get_yaxis().set_visible(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'NoneType' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-10-a79a220fe8bf>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNoneType\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'NoneType' is not defined"
     ]
    }
   ],
   "source": [
    "isinstance(None, )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.2, 1.2)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAASUAAAE0CAYAAABq7SVJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x43c6160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bbox = shapely.geometry.Polygon([(0, 0), (0, 1), (1, 1), (1, 0)])\n",
    "\n",
    "lines = explode_polygons(bbox)\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
    "baseplot(lines, 'line', ax=ax)\n",
    "ax.set_xlim(-0.2, 1.2)\n",
    "ax.set_ylim(-0.2, 1.2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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UACw3wUNPMEEBwHISPPQMExQALBfBQ08xQQHAchA89BwTFAAsNcFDTzJBAcBSEjz0JBMU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\nHgCg8f4fBtjuKKClgxAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x72d8e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1 = LineString([[0, 1], [1, 0]])\n",
    "lines_cap = cap_lines(l1, offset=0., length=0.2)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
    "baseplot([l1], 'line', ax=ax[0])\n",
    "ax[0].set_xlim(-0.2, 1.2)\n",
    "ax[0].set_ylim(-0.2, 1.2)\n",
    "baseplot(lines_cap, 'caps', ax=ax[1])\n",
    "ax[1].set_xlim(-0.2, 1.2)\n",
    "a = ax[1].set_ylim(-0.2, 1.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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J1EonkTYIPBW7ctzzhRdeEHqAKugkMmwCT+UuH/c8fvx4jh071vaRAJZFJ5FhEng6wLgn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\nVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x43c62e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1 = LineString([[0, 1], [1, 0]])\n",
    "l1_extended = extend_line(l1, offset=0.5, side='both')\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
    "baseplot([l1], 'line', ax=ax[0])\n",
    "ax[0].set_xlim(-0.5, 1.5)\n",
    "ax[0].set_ylim(-0.5, 1.5)\n",
    "baseplot([l1_extended], 'extended line', ax=ax[1])\n",
    "ax[1].set_xlim(-0.5, 1.5)\n",
    "a = ax[1].set_ylim(-0.5, 1.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = {'id': {'id2': 2}, 'blal': 2}\n",
    "'id2' in a['id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 0, 1, 1]\n",
      "number of lines after split: 4\n"
     ]
    },
    {
     "data": {
      "image/png": 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MLvBwZASKEvO4J7LB+gwUJYaexKACDzVvFC3WcU+0j/UZKFroR1AEE3ioecMX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\nNIiPFVoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x43a2ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1 = LineString([[0, 1], [1, 0]])\n",
    "l2 = LineString([[0, 0], [1, 1]])\n",
    "lines = [l1, l2]\n",
    "\n",
    "# find intersection points of boundaries and lines and split lines based on it\n",
    "lines_split, index = split_lines(lines, return_index=True)\n",
    "print(index)\n",
    "print(\"number of lines after split: {:d}\".format(len(lines_split)))\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
    "baseplot(lines, 'lines', ax=ax[0])\n",
    "baseplot(lines_split, 'splitted at intersection', ax=ax[1])\n",
    "ax[0].set_xlim(-0.2, 1.2)\n",
    "ax[0].set_ylim(-0.2, 1.2)\n",
    "ax[1].set_xlim(-0.2, 1.2)\n",
    "a = ax[1].set_ylim(-0.2, 1.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of lines after snap: 2\n"
     ]
    },
    {
     "data": {
      "image/png": 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CAoDPqElE0hF4EoQRFAB8Rk0ikozAkzCMoADgK2oSkWQEngRiBAUAX1GTiKQi8CQU7Z4A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\nAEDwCDwAACB4BB4AABC8/wfvSLH0kzoGSQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7c763c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1 = LineString([[0, 1], [1, 0]])\n",
    "l2 = LineString([[.2, 0], [.4, .4]])\n",
    "lines = [l1, l2]\n",
    "\n",
    "# find intersection points of boundaries and lines and split lines based on it\n",
    "lines_snap = snap_lines(lines, max_dist=0.5)\n",
    "print(\"number of lines after snap: {:d}\".format(len(lines_snap)))\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
    "baseplot(lines, 'lines', ax=ax[0])\n",
    "baseplot(lines_snap, 'extend line snap & clip', ax=ax[1])\n",
    "ax[0].set_xlim(-0.2, 1.2)\n",
    "ax[0].set_ylim(-0.2, 1.2)\n",
    "ax[1].set_xlim(-0.2, 1.2)\n",
    "a = ax[1].set_ylim(-0.2, 1.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 0, 1, 2, 2, 2]\n",
      "number of lines after split: 6\n"
     ]
    },
    {
     "data": {
      "image/png": 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NTk56XRKQUnwTeCRp5cqV2rVrlySpublZN27c8LgiAIhNWlqa6urqlJ2drb6+PjU3N3td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\nqan5Fh0dHXrnO9/p2euO130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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7e230b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l1 = LineString([[0, 1], [1, 0]])\n",
    "l2 = LineString([[.2, 0.05], [.4, .4]])\n",
    "l3 = LineString([[0,0], [1.2, 0]])\n",
    "lines = [l1, l2, l3]\n",
    "\n",
    "# find intersection points of boundaries and lines and split lines based on it\n",
    "max_dist=0.0\n",
    "lines_snap, idx_snap = snap_lines(lines, max_dist=10, tolerance=1e-3, return_index=True)\n",
    "lines_split, index = split_lines(lines_snap, tolerance=1e-3, return_index=True)\n",
    "print(index)\n",
    "print(\"number of lines after split: {:d}\".format(len(index)))\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
    "baseplot(lines, 'lines', ax=ax[0])\n",
    "baseplot(lines_split, 'extend line snap & clip; max_dist {:.2f}'.format(max_dist), ax=ax[1])\n",
    "ax[0].set_xlim(-0.2, 1.4)\n",
    "ax[0].set_ylim(-0.2, 1.2)\n",
    "ax[1].set_xlim(-0.2, 1.4)\n",
    "a = ax[1].set_ylim(-0.2, 1.2)"
   ]
  }
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