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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "# Geospatial Data in Python: Database, Desktop, and the Web\n",
      "## Tutorial (Part 3)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {
      "slideshow": {
       "slide_type": "subslide"
      }
     },
     "source": [
      "## Convert vector data formats (Shapefile -> GeoJSON)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import fiona\n",
      "from fiona.crs import to_string\n",
      "import os\n",
      "\n",
      "boro_file = os.path.join(\"..\", \"data\", \"nybb\", \"nybb.shp\")\n",
      "out_file =  os.path.join(\"..\", \"data\", \"nybb\", \"nybb.geojson\")\n",
      "\n",
      "# Register format drivers with a context manager\n",
      "with fiona.drivers():\n",
      "    # Open the shapefile (can also open directly from zip files with vfs!)\n",
      "    with fiona.open(boro_file) as source:\n",
      "        print(\"Feature Count: %s\" % len(source))\n",
      "        print(\"Input Driver: %s\" % source.driver)\n",
      "        \n",
      "        meta = source.meta\n",
      "        meta.update(driver=\"GeoJSON\")\n",
      "        \n",
      "        if os.path.exists(out_file):\n",
      "            os.remove(out_file)\n",
      "        with fiona.open(out_file, 'w', **meta) as sink:\n",
      "            print(\"Output Driver: %s\" % sink.driver)\n",
      "            for rec in source:\n",
      "                sink.write(rec)\n",
      "# Did it work?\n",
      "print(\"File Exists: %s\" % os.path.exists(out_file))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {
      "slideshow": {
       "slide_type": "subslide"
      }
     },
     "source": [
      "## Read geospatial raster data\n",
      "\n",
      "Note: You can download the GeoTIFF of Manhattan used in this example [from here](https://www.dropbox.com/s/mba7obrfh2b2ucb/manhattan.tif). Make sure you put it in your `data` folder."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import rasterio\n",
      "from fiona.crs import to_string\n",
      "import os\n",
      "import numpy as np\n",
      "\n",
      "image_file = os.path.join('..', 'data', 'manhattan.tif')\n",
      "\n",
      "# Register format drivers with a context manager\n",
      "with rasterio.drivers():\n",
      "    with rasterio.open(image_file, 'r') as source:\n",
      "        print(source.count, source.shape)\n",
      "        print(source.driver)\n",
      "        print(to_string(source.crs))\n",
      "        \n",
      "        # Get data from each band (newer versions of rasterio use source.read())\n",
      "        r, g, b = map(source.read_band, (1, 2, 3))\n",
      "        data = np.dstack((r, g, b))  # Each band is just an ndarray!\n",
      "        print(type(data))\n",
      "        \n",
      "        # Get the bounds of the raster (for plotting later)\n",
      "        bounds = source.bounds[::2] + source.bounds[1::2]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An alternative way (outside of `with` context manager as above):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "source = rasterio.open(image_file, 'r')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {
      "slideshow": {
       "slide_type": "subslide"
      }
     },
     "source": [
      "## Simple plot of geospatial raster"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "%matplotlib inline\n",
      "fig = plt.figure(figsize=(8, 8))\n",
      "ax = plt.imshow(data, extent=bounds)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "### Time to work on Notebook:\n",
      "\n",
      "[`Working with Rasters in Python`](../exercises/Working with Rasters in Python.ipynb)"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}