{
 "metadata": {
  "name": "",
  "signature": "sha256:3f28a84fd60926eecfe4af2e2afed0c1d0b7203c32431e0b6e90253ea046975f"
 },
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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "pyModis notebook"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Download data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "First we have to import pymodis library and set all the needed variables"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import os\n",
      "import glob\n",
      "from IPython.core.display import Image\n",
      "from pymodis import downmodis"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# destination foldert\n",
      "dest = \"/tmp\"\n",
      "# tiles to download\n",
      "tiles = \"h18v04,h19v04\"\n",
      "# starting day\n",
      "day = \"2014-08-14\"\n",
      "# number of day to download\n",
      "delta = 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "At this point we can initialize the downmodis object. We are going to download MODIS LST product, in the \"/tmp\" directory"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisDown = downmodis.downModis(destinationFolder=dest, tiles=tiles, today=day, delta=delta)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisDown.connect()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "At this point we start the download of files."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<div style=\"border: 1px solid red;\"><h6 style=\"color:#ff4040; margin: 0.5em;\">Warning</h6>\n",
      "<span style=\"margin: 0.5em;\">The next operation could take some minutes depending on your internet speed</span></div>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisDown.downloadsAllDay()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# create the list of files to use\n",
      "files = glob.glob(os.path.join(dest, 'MOD11A1.A2014*.hdf'))\n",
      "print files"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from topng import hdf2png\n",
      "pngfile = hdf2png(files[0])\n",
      "Image(filename=pngfile)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Parse the data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We import the needed modules and after we obtain a list with the full path to the downloaded MODIS files"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pymodis import parsemodis"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Parse single data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "At this point we can parse one file (in this case the first one), creating a parseModis object"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisParse = parsemodis.parseModis(files[0])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now you can obtain several parameters from the MODIS metadata, we query only some values to show you:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# bounding box of the tiles\n",
      "modisParse.retBoundary()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# quality statistics\n",
      "modisParse.retMeasure()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisParse.retRangeTime()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Check parseModis class documentation for more info"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "parsemodis.parseModis?"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Parse multiple data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "After the test with only a MODIS file, we are going to test the parsing for multiple files"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisMultiParse = parsemodis.parseModisMulti(files)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now you can obtain the value of boundary"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisMultiParse.valBound()\n",
      "modisMultiParse.boundary"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "or write a xml for a MODIS mosaic file"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "modisMultiParse.writexml(os.path.join(dest, 'modismultiparse.xml'))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "at the end you can read the created file and print the lines"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f = open(os.path.join(dest, 'modismultiparse.xml'))\n",
      "lines = f.readlines()\n",
      "p = [l.strip() for l in lines]\n",
      "f.close()\n",
      "print \"\\n\".join(p)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Create a mosaic file"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We are going to use the GDAL library to create the mosaic. As subset we are going to use daily and nightly temperature and it's quality layer"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pymodis.convertmodis_gdal import createMosaicGDAL\n",
      "# [daily temp, quality for daily, not used, not used, nightly temp, quality for nightly]\n",
      "subset = [1,1,0,0,1,1]\n",
      "output_pref = os.path.join(dest, 'MOD11A1.A2014226.mosaic')\n",
      "output_tif = os.path.join(dest, 'MOD11A1.A2014226.mosaic.tif')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "First we'll initialize the mosaic object"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# the first parameter is a list with the original tiles,\n",
      "# the second one is a list with the the subset to process,\n",
      "# the last is the output format, in this case GeoTiff\n",
      "mosaic = createMosaicGDAL(files, subset, 'GTiff')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "At this point we create the xml file with the information of input data, and a multilayr GeoTiff file containing the mosaic of the choosen band"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mosaic.run(output_tif)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Finally we can also create a GDAL VRT file, a XML file containing the information about input data. This is really powerfull if you want convert it in different format or projection system"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mosaic.write_vrt(output_pref)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Convert data"
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Single HDF file"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "In this first example we are going to convert an original MODIS HDF file using GDAL library"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from pymodis.convertmodis_gdal import convertModisGDAL\n",
      "output_pref = os.path.join(dest, 'MOD11A1.A2014226.h18v04')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We are going to convert a single tile, with the 'subset' already used for mosaicking, the output resolution will be 1000 meters and the projection system will be EU-LAEA"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "convertsingle = convertModisGDAL(hdfname=files[0], prefix=output_pref, subset=subset, res=1000, epsg=3035)\n",
      "convertsingle.run()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "VRT mosaic file"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We created separated VRT file, one for each choosen subset. So first we collect the name of VRT files"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "vrtfiles = glob.glob(os.path.join(dest, 'MOD11A1.A2014*.vrt'))\n",
      "print vrtfiles"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now we can convert all the VRT files in a *``for``* loop "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for f in vrtfiles:\n",
      "    base = os.path.basename(f).replace('.vrt', '_vrt')\n",
      "    output = os.path.join(dest, base)\n",
      "    convertsingle = convertModisGDAL(hdfname=f, prefix=output, subset= [1,1,1,1], res=1000, epsg=3035, vrt=True)\n",
      "    convertsingle.run_vrt_separated()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It will create 4 GeoTIFF files ready to be processed."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "vrttiffiles = glob.glob(os.path.join(dest, 'MOD11A1.A2014*_vrt.tif'))\n",
      "print vrttiffiles"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from topng import tif2png\n",
      "pngfile = tif2png(vrttiffiles[1])\n",
      "Image(filename=pngfile)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "The tutorial is finished, you can find more info at <a href=\"http://www.pymodis.org/\" targe=\"_blank\">pyModis website</a>"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}