shapely.ops.cascaded_union

shapely.ops.cascaded_union.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from shapely.geometry import Point, LineString\n",
    "from shapely.ops import cascaded_union\n",
    "import geopandas as gpd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "%matplotlib inline\n",
    "mpl.rcParams['figure.figsize'] = 5,5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.LineString`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "line_1 = LineString((Point(1,1), Point(3,1)))\n",
    "line_2 = LineString((Point(1,1), Point(1,3)))\n",
    "line_3 = LineString((Point(1,3), Point(3,3)))\n",
    "line_4 = LineString((Point(1,3), Point(1,4)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.ops.cascaded_union`  --  `line_1` + `line_2` + `line_4`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MULTILINESTRING ((1 3, 1 4), (1 1, 3 1), (1 1, 1 3))\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.88 0.88 2.24 3.24\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,5.0)\"><g><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,3.0 1.0,4.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,1.0 3.0,1.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,1.0 1.0,3.0\" opacity=\"0.8\" /></g></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.multilinestring.MultiLineString at 0x1049e9810>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cascade_124 = cascaded_union([line_1,line_2,line_4])\n",
    "print cascade_124\n",
    "cascade_124"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.ops.cascaded_union`  --  `line_1` + `line_3` + `line_4`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MULTILINESTRING ((1 1, 3 1), (1 3, 3 3), (1 3, 1 4))\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.88 0.88 2.24 3.24\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,5.0)\"><g><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,1.0 3.0,1.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,3.0 3.0,3.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,3.0 1.0,4.0\" opacity=\"0.8\" /></g></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.multilinestring.MultiLineString at 0x104a074d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cascade_134 = cascaded_union([line_1,line_3,line_4])\n",
    "print cascade_134\n",
    "cascade_134"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.ops.cascaded_union`  --  `line_3` + `line_1` + `line_4`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MULTILINESTRING ((1 1, 3 1), (1 3, 3 3), (1 3, 1 4))\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.88 0.88 2.24 3.24\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,5.0)\"><g><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,1.0 3.0,1.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,3.0 3.0,3.0\" opacity=\"0.8\" /><polyline fill=\"none\" stroke=\"#66cc99\" stroke-width=\"0.0648\" points=\"1.0,3.0 1.0,4.0\" opacity=\"0.8\" /></g></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.multilinestring.MultiLineString at 0x104a078d0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cascade_314 = cascaded_union([line_3,line_1,line_4])\n",
    "print cascade_314\n",
    "cascade_314"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.Point`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.25 0.25 2.0 2.0\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,2.5)\"><circle cx=\"1.25\" cy=\"1.25\" r=\"0.06\" stroke=\"#555555\" stroke-width=\"0.02\" fill=\"#66cc99\" opacity=\"0.6\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.point.Point at 0x11197f850>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "point = Point(1.25, 1.25)\n",
    "point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.intepolate`  and `shapely.project`  -- `cascade_124` + `point`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1.25, 1.0)]\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.25 0.0 2.0 2.0\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,2.0)\"><circle cx=\"1.25\" cy=\"1.0\" r=\"0.06\" stroke=\"#555555\" stroke-width=\"0.02\" fill=\"#66cc99\" opacity=\"0.6\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.point.Point at 0x11197f7d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snapped_point = cascade_124.interpolate(cascade_124.project(point))\n",
    "print snapped_point.coords[:]\n",
    "snapped_point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.intepolate`  and `shapely.project`  -- `cascade_134` + `point`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1.25, 1.0)]\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.25 0.0 2.0 2.0\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,2.0)\"><circle cx=\"1.25\" cy=\"1.0\" r=\"0.06\" stroke=\"#555555\" stroke-width=\"0.02\" fill=\"#66cc99\" opacity=\"0.6\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.point.Point at 0x111885390>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snapped_point = cascade_134.interpolate(cascade_134.project(point))\n",
    "print snapped_point.coords[:]\n",
    "snapped_point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### `shapely.intepolate`  and `shapely.project`  -- `cascade_314` + `point`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1.25, 1.0)]\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"0.25 0.0 2.0 2.0\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,2.0)\"><circle cx=\"1.25\" cy=\"1.0\" r=\"0.06\" stroke=\"#555555\" stroke-width=\"0.02\" fill=\"#66cc99\" opacity=\"0.6\" /></g></svg>"
      ],
      "text/plain": [
       "<shapely.geometry.point.Point at 0x11187a450>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "snapped_point = cascade_314.interpolate(cascade_314.project(point))\n",
    "print snapped_point.coords[:]\n",
    "snapped_point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "point_gdf = gpd.GeoDataFrame([point], columns=[\"geometry\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1.25, 1.0)]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x111b5f390>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MN+79mGQ2yZbB9mbgrcDPlizbA3xwsH0l8N0anC0Zxii+xWZdNvrHmw8x35XAx5IcA44C\nO9fyP8CIXAy8H3h48JoD4NPA2cfNOc79OMx8496P24BbkmxiMfTbququJNcB81W1h8W/ML6e5BCL\nR7Sda3kA364lNZmEp5HSVDA2qYmxSU2MTWpibFITY5OaGJvU5P8BLndVJgsOd+4AAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111a8a150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdf_124 = gpd.GeoDataFrame([line_1, line_2, line_4], columns=[\"geometry\"])\n",
    "cascade_124 = gdf_124.cascaded_union\n",
    "nearest_point_124 = cascade_124.interpolate(cascade_124.project(point))\n",
    "print nearest_point_124.coords[:]\n",
    "nearest_point_124 = gpd.GeoDataFrame([nearest_point_124], columns=[\"geometry\"])\n",
    "base = gdf_124.plot()\n",
    "point_gdf.plot(ax=base)\n",
    "nearest_point_124.plot(ax=base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1.25, 1.0)]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x111aa06d0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tX332ebvtRWrs0y+SZ7CktZKGI+LZcZZ1bD+Wma/T+9F2v+1ZxfZMSXdK+rhp2WZJDxbb\nyyW9FcXZkjKq+BabSZnuH29eYr7lkh62PSrplKQVE/kfoCK3SXpA0v7iNYckPSlpwZg5O7kfy8zX\n6f04R9I62zPUCH1DRGyx/bSkWkRsVuMvjJdtH1TjiLZiIg/A27WAJN3wNBLoCcQGJCE2IAmxAUmI\nDUhCbEASYgOS/B9Cw1a/jBB3JwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111a53750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdf_134 = gpd.GeoDataFrame([line_1, line_3, line_4], columns=[\"geometry\"])\n",
    "cascade_134 = gdf_134.cascaded_union\n",
    "nearest_point_134 = cascade_134.interpolate(cascade_134.project(point))\n",
    "print nearest_point_134.coords[:]\n",
    "nearest_point_134 = gpd.GeoDataFrame([nearest_point_134], columns=[\"geometry\"])\n",
    "base = gdf_134.plot()\n",
    "point_gdf.plot(ax=base)\n",
    "nearest_point_134.plot(ax=base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1.25, 1.0)]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x111a81850>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tX332ebvtRWrs0y+SZ7CktZKGI+LZcZZ1bD+Wma/T+9F2v+1ZxfZMSXdK+rhp2WZJDxbb\nyyW9FcXZkjKq+BabSZnuH29eYr7lkh62PSrplKQVE/kfoCK3SXpA0v7iNYckPSlpwZg5O7kfy8zX\n6f04R9I62zPUCH1DRGyx/bSkWkRsVuMvjJdtH1TjiLZiIg/A27WAJN3wNBLoCcQGJCE2IAmxAUmI\nDUhCbEASYgOS/B9Cw1a/jBB3JwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111969350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gdf_314 = gpd.GeoDataFrame([line_3, line_1, line_4], columns=[\"geometry\"])\n",
    "cascade_314 = gdf_314.cascaded_union\n",
    "nearest_point_314 = cascade_314.interpolate(cascade_314.project(point))\n",
    "print nearest_point_314.coords[:]\n",
    "nearest_point_314 = gpd.GeoDataFrame([nearest_point_314], columns=[\"geometry\"])\n",
    "base = gdf_314.plot()\n",
    "point_gdf.plot(ax=base)\n",
    "nearest_point_314.plot(ax=base)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "--------------------------"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:py2]",
   "language": "python",
   "name": "conda-env-py2-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}