diff --git a/Landuse_classification.ipynb b/Landuse_classification.ipynb
deleted file mode 100644
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--- a/Landuse_classification.ipynb
+++ /dev/null
@@ -1,4765 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# TODO list\n",
- "\n",
- "- Add the following metrics:\n",
- " 1. Density of built floor area (sum of built pixels' height / area of block)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "
\n",
- " Table of contents \n",
- "
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- ""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 109,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "application/javascript": [
- "$.getScript('https://kmahelona.github.io/ipython_notebook_goodies/ipython_notebook_toc.js')"
- ],
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "%%javascript\n",
- "$.getScript('https://kmahelona.github.io/ipython_notebook_goodies/ipython_notebook_toc.js')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- " Define working environment
\n",
- "\n",
- "The following cells are used to :\n",
- "- Set the environment variables for Python and GRASS GIS and R statistical computing \n",
- "- Define the [\"GRASSDATA\" folder](https://grass.osgeo.org/grass73/manuals/helptext.html), the name of \"location\" and \"mapset\" where you will to work."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Import libraries**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "## Import libraries needed for setting parameters of operating system \n",
- "import os\n",
- "import sys"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**Set 'Python' and 'GRASS GIS' environment variables**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Here, we set [the environment variables allowing to use of GRASS GIS](https://grass.osgeo.org/grass64/manuals/variables.html) inside this Jupyter notebook. Please change the directory path according to your own system configuration. Here after are the environment variables defined on a Linux Mint system."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "### Define GRASS GIS environment variables for LINUX UBUNTU Mint 18.1 (Serena)\n",
- "# Check is environmental variables exists and create them (empty) if not exists.\n",
- "if not 'PYTHONPATH' in os.environ:\n",
- " os.environ['PYTHONPATH']=''\n",
- "if not 'LD_LIBRARY_PATH' in os.environ:\n",
- " os.environ['LD_LIBRARY_PATH']=''\n",
- "# Set environmental variables\n",
- "os.environ['GISBASE'] = '/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu'\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'bin')\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'script')\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'lib')\n",
- "#os.environ['PATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'etc','python')\n",
- "os.environ['PYTHONPATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'etc','python')\n",
- "os.environ['PYTHONPATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'etc','python','grass')\n",
- "os.environ['PYTHONPATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'etc','python','grass','script')\n",
- "os.environ['PYTHONLIB'] = '/usr/lib/python2.7'\n",
- "os.environ['LD_LIBRARY_PATH'] += os.pathsep + os.path.join(os.environ['GISBASE'],'lib')\n",
- "os.environ['GIS_LOCK'] = '$$'\n",
- "os.environ['GISRC'] = os.path.join(os.environ['HOME'],'.grass7','rc')\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'],'.grass7','addons')\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'],'.grass7','addons','bin')\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'],'.grass7','addons')\n",
- "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'],'.grass7','addons','scripts')\n",
- "\n",
- "## Define GRASS-Python environment\n",
- "sys.path.append(os.path.join(os.environ['GISBASE'],'etc','python'))"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "**Import GRASS Python packages**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "## Import libraries needed to launch GRASS GIS in the jupyter notebook\n",
- "import grass.script.setup as gsetup\n",
- "\n",
- "## Import libraries needed to call GRASS using Python\n",
- "import grass.script as gscript\n",
- "from grass.script import core as grass"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "**Display current environment variables of your computer**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "MDMSESSION = mate \t\n",
- "MANDATORY_PATH = /usr/share/gconf/mate.mandatory.path \t\n",
- "MATE_DESKTOP_SESSION_ID = this-is-deprecated \t\n",
- "LESSOPEN = | /usr/bin/lesspipe %s \t\n",
- "MDM_LANG = fr_BE.UTF-8 \t\n",
- "LOGNAME = tais \t\n",
- "USER = tais \t\n",
- "HOME = /home/tais \t\n",
- "XDG_VTNR = 9 \t\n",
- "PATH = /usr/local/bin:/home/tais/BIN:/home/tais/bin:/home/tais/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/bin:/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/script:/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/lib:/home/tais/.grass7/addons:/home/tais/.grass7/addons/bin:/home/tais/.grass7/addons:/home/tais/.grass7/addons/scripts \t\n",
- "CLICOLOR = 1 \t\n",
- "DISPLAY = :0.0 \t\n",
- "SSH_AGENT_PID = 5974 \t\n",
- "LANG = fr_BE.UTF-8 \t\n",
- "TERM = xterm-color \t\n",
- "SHELL = /bin/bash \t\n",
- "GIS_LOCK = $$ \t\n",
- "XAUTHORITY = /home/tais/.Xauthority \t\n",
- "SESSION_MANAGER = local/tais-HP-Z620-Workstation:@/tmp/.ICE-unix/5837,unix/tais-HP-Z620-Workstation:/tmp/.ICE-unix/5837 \t\n",
- "SHLVL = 1 \t\n",
- "QT_LINUX_ACCESSIBILITY_ALWAYS_ON = 1 \t\n",
- "INSIDE_CAJA_PYTHON = \t\n",
- "QT_ACCESSIBILITY = 1 \t\n",
- "LD_LIBRARY_PATH = :/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/lib \t\n",
- "COMPIZ_CONFIG_PROFILE = mate \t\n",
- "WINDOWPATH = 9 \t\n",
- "GTK_OVERLAY_SCROLLING = 0 \t\n",
- "PYTHONPATH = :/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/etc/python:/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/etc/python/grass:/home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu/etc/python/grass/script \t\n",
- "GISBASE = /home/tais/SRC/GRASS/grass_trunk/dist.x86_64-pc-linux-gnu \t\n",
- "CLUTTER_BACKEND = x11 \t\n",
- "USERNAME = tais \t\n",
- "XDG_SESSION_DESKTOP = mate \t\n",
- "GDM_XSERVER_LOCATION = local \t\n",
- "XDG_RUNTIME_DIR = /run/user/1000 \t\n",
- "JPY_PARENT_PID = 7955 \t\n",
- "QT_STYLE_OVERRIDE = gtk \t\n",
- "SSH_AUTH_SOCK = /run/user/1000/keyring/ssh \t\n",
- "VTE_VERSION = 4205 \t\n",
- "GDMSESSION = mate \t\n",
- "GISRC = /home/tais/.grass7/rc \t\n",
- "GIT_PAGER = cat \t\n",
- "XDG_CONFIG_DIRS = /etc/xdg/xdg-mate:/etc/xdg \t\n",
- "XDG_CURRENT_DESKTOP = MATE \t\n",
- "XDG_SESSION_ID = c21 \t\n",
- "DBUS_SESSION_BUS_ADDRESS = unix:abstract=/tmp/dbus-oiw1S789SI,guid=e626cdc47bce079de737e4fe5a3fcda7 \t\n",
- "_ = /usr/local/bin/jupyter \t\n",
- "XDG_SESSION_COOKIE = 8441891e86e24d76b9616edf516d5734-1514130855.90561-444848216 \t\n",
- "DESKTOP_SESSION = mate \t\n",
- "WINDOWID = 56623110 \t\n",
- "LESSCLOSE = /usr/bin/lesspipe %s %s \t\n",
- "DEFAULTS_PATH = /usr/share/gconf/mate.default.path \t\n",
- "MPLBACKEND = module://ipykernel.pylab.backend_inline \t\n",
- "MDM_XSERVER_LOCATION = local \t\n",
- "GTK_MODULES = gail:atk-bridge \t\n",
- "XDG_DATA_DIRS = /usr/share/mate:/usr/local/share/:/usr/share/:/usr/share/mdm/ \t\n",
- "PWD = /media/tais/data/Dropbox/ULB/MAUPP/Traitements/Landscape_metrics/r.li/Landuse_mapping \t\n",
- "COLORTERM = mate-terminal \t\n",
- "PYTHONLIB = /usr/lib/python2.7 \t\n",
- "LS_COLORS = rs=0:di=01;34:ln=01;36:mh=00:pi=40;33:so=01;35:do=01;35:bd=40;33;01:cd=40;33;01:or=40;31;01:mi=00:su=37;41:sg=30;43:ca=30;41:tw=30;42:ow=34;42:st=37;44:ex=01;32:*.tar=01;31:*.tgz=01;31:*.arc=01;31:*.arj=01;31:*.taz=01;31:*.lha=01;31:*.lz4=01;31:*.lzh=01;31:*.lzma=01;31:*.tlz=01;31:*.txz=01;31:*.tzo=01;31:*.t7z=01;31:*.zip=01;31:*.z=01;31:*.Z=01;31:*.dz=01;31:*.gz=01;31:*.lrz=01;31:*.lz=01;31:*.lzo=01;31:*.xz=01;31:*.bz2=01;31:*.bz=01;31:*.tbz=01;31:*.tbz2=01;31:*.tz=01;31:*.deb=01;31:*.rpm=01;31:*.jar=01;31:*.war=01;31:*.ear=01;31:*.sar=01;31:*.rar=01;31:*.alz=01;31:*.ace=01;31:*.zoo=01;31:*.cpio=01;31:*.7z=01;31:*.rz=01;31:*.cab=01;31:*.jpg=01;35:*.jpeg=01;35:*.gif=01;35:*.bmp=01;35:*.pbm=01;35:*.pgm=01;35:*.ppm=01;35:*.tga=01;35:*.xbm=01;35:*.xpm=01;35:*.tif=01;35:*.tiff=01;35:*.png=01;35:*.svg=01;35:*.svgz=01;35:*.mng=01;35:*.pcx=01;35:*.mov=01;35:*.mpg=01;35:*.mpeg=01;35:*.m2v=01;35:*.mkv=01;35:*.webm=01;35:*.ogm=01;35:*.mp4=01;35:*.m4v=01;35:*.mp4v=01;35:*.vob=01;35:*.qt=01;35:*.nuv=01;35:*.wmv=01;35:*.asf=01;35:*.rm=01;35:*.rmvb=01;35:*.flc=01;35:*.avi=01;35:*.fli=01;35:*.flv=01;35:*.gl=01;35:*.dl=01;35:*.xcf=01;35:*.xwd=01;35:*.yuv=01;35:*.cgm=01;35:*.emf=01;35:*.ogv=01;35:*.ogx=01;35:*.aac=00;36:*.au=00;36:*.flac=00;36:*.m4a=00;36:*.mid=00;36:*.midi=00;36:*.mka=00;36:*.mp3=00;36:*.mpc=00;36:*.ogg=00;36:*.ra=00;36:*.wav=00;36:*.oga=00;36:*.opus=00;36:*.spx=00;36:*.xspf=00;36: \t\n",
- "PAGER = cat \t\n",
- "XDG_SEAT = seat0 \t\n"
- ]
- }
- ],
- "source": [
- "## Display the current defined environment variables\n",
- "for key in os.environ.keys():\n",
- " print \"%s = %s \\t\" % (key,os.environ[key])"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- " Define functions
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "This section of the notebook is dedicated to defining functions which will then be called later in the script. If you want to create your own functions, define them here."
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function for computing processing time"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The \"print_processing_time\" is used to calculate and display the processing time for various stages of the processing chain. At the beginning of each major step, the current time is stored in a new variable, using [time.time() function](https://docs.python.org/2/library/time.html). At the end of the stage in question, the \"print_processing_time\" function is called and takes as argument the name of this new variable containing the recorded time at the beginning of the stage, and an output message."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "## Import library for managing time in python\n",
- "import time \n",
- "\n",
- "## Function \"print_processing_time()\" compute processing time and printing it.\n",
- "# The argument \"begintime\" wait for a variable containing the begintime (result of time.time()) of the process for which to compute processing time.\n",
- "# The argument \"printmessage\" wait for a string format with information about the process. \n",
- "def print_processing_time(begintime, printmessage): \n",
- " endtime=time.time() \n",
- " processtime=endtime-begintime\n",
- " remainingtime=processtime\n",
- "\n",
- " days=int((remainingtime)/86400)\n",
- " remainingtime-=(days*86400)\n",
- " hours=int((remainingtime)/3600)\n",
- " remainingtime-=(hours*3600)\n",
- " minutes=int((remainingtime)/60)\n",
- " remainingtime-=(minutes*60)\n",
- " seconds=round((remainingtime)%60,1)\n",
- "\n",
- " if processtime<60:\n",
- " finalprintmessage=str(printmessage)+str(seconds)+\" seconds\"\n",
- " elif processtime<3600:\n",
- " finalprintmessage=str(printmessage)+str(minutes)+\" minutes and \"+str(seconds)+\" seconds\"\n",
- " elif processtime<86400:\n",
- " finalprintmessage=str(printmessage)+str(hours)+\" hours and \"+str(minutes)+\" minutes and \"+str(seconds)+\" seconds\"\n",
- " elif processtime>=86400:\n",
- " finalprintmessage=str(printmessage)+str(days)+\" days, \"+str(hours)+\" hours and \"+str(minutes)+\" minutes and \"+str(seconds)+\" seconds\"\n",
- " \n",
- " return finalprintmessage"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function for creation of configuration file for r.li (landscape units provided as polygons) (multiprocessed)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "##### Function that create the r.li configuration file for a list of landcover raster.\n",
- "### It enable to create in one function as many configuration file as the number of raster provided in 'listoflandcoverraster'.\n",
- "### It could be use only in case study with a several landcover raster and only one landscape unit layer.\n",
- "### So, the landscape unit layer if fixed and there are the landcover raster which change. \n",
- "# 'listoflandcoverraster' wait for a list with the name (string) of landcover rasters.\n",
- "# 'landscape_polygons' wait for the name (string) of the vector layer containing the polygons to be used as landscape units.\n",
- "# 'masklayerhardcopy' wait for a boolean value (True/False) depending if the user want to create hard copy of the landscape units mask layers or not.\n",
- "# 'returnlistpath' wait for a boolean value (True/False) according to the fact that a list containing the path to the configuration files is desired.\n",
- "# 'ncores' wait for a integer corresponding to the number of desired cores to be used for parallelization.\n",
- "\n",
- "# Import libraries for multiprocessing \n",
- "import multiprocessing\n",
- "from multiprocessing import Pool\n",
- "from functools import partial \n",
- "\n",
- "# Function that copy the landscape unit raster masks on a new layer with name corresponding to the current 'landcover_raster'\n",
- "def copy_landscapeunitmasks(current_landcover_raster,base_landcover_raster,landscape_polygons,landscapeunit_bbox,cat):\n",
- " ### Copy the landscape units mask for the current 'cat'\n",
- " # Define the name of the current \"current_landscapeunit_rast\" layer\n",
- " current_landscapeunit_rast=current_landcover_raster.split(\"@\")[0]+\"_\"+landscape_polygons.split(\"@\")[0]+\"_\"+str(cat) \n",
- " base_landscapeunit_rast=base_landcover_raster.split(\"@\")[0]+\"_\"+landscape_polygons.split(\"@\")[0]+\"_\"+str(cat) \n",
- " # Copy the the landscape unit created for the first landcover map in order to match the name of the current landcover map\n",
- " gscript.run_command('g.copy', overwrite=True, quiet=True, raster=(base_landscapeunit_rast,current_landscapeunit_rast))\n",
- " # Add the line to the text variable\n",
- " text=\"MASKEDOVERLAYAREA \"+current_landscapeunit_rast+\"|\"+landscapeunit_bbox[cat]\n",
- " return text\n",
- "\n",
- "# Function that create the r.li configuration file for the base landcover raster and then for all the binary rasters\n",
- "def create_rli_configfile(listoflandcoverraster,landscape_polygons,\n",
- " masklayerhardcopy=False,returnlistpath=True,ncores=2):\n",
- " # Check if 'listoflandcoverraster' is not empty\n",
- " if len(listoflandcoverraster)==0:\n",
- " sys.exit(\"The list of landcover raster is empty and should contain at least one raster name\")\n",
- " # Check if rasters provided in 'listoflandcoverraster' exists to avoid error in mutliprocessing \n",
- " for cur_rast in listoflandcoverraster:\n",
- " try:\n",
- " mpset=cur_rast.split(\"@\")[1]\n",
- " except:\n",
- " mpset=\"\"\n",
- " if cur_rast.split(\"@\")[0] not in [x[0] for x in gscript.list_pairs(type='raster',mapset=mpset)]:\n",
- " sys.exit('Raster <%s> not found' %cur_rast)\n",
- " # Check if rasters provided in 'listoflandcoverraster' have the same extend and spatial resolution \n",
- " raster={}\n",
- " for x, rast in enumerate(raster_list):\n",
- " raster[x]=gscript.raster_info(rast)\n",
- " key_list=raster.keys()\n",
- " for x in key_list[1:]:\n",
- " for info in ('north','south','east','west','ewres','nsres'):\n",
- " if not raster[0][info]==raster[x][info]:\n",
- " sys.exit(\"Some raster provided in the list have different spatial resolution or extend, please check\") \n",
- " # Get the version of GRASS GIS \n",
- " version=grass.version()['version'].split('.')[0]\n",
- " # Define the folder to save the r.li configuration files\n",
- " if sys.platform==\"win32\":\n",
- " rli_dir=os.path.join(os.environ['APPDATA'],\"GRASS\"+version,\"r.li\")\n",
- " else: \n",
- " rli_dir=os.path.join(os.environ['HOME'],\".grass\"+version,\"r.li\")\n",
- " if not os.path.exists(rli_dir):\n",
- " os.makedirs(rli_dir)\n",
- " ## Create an ordered list with the 'cat' value of landscape units to be processed.\n",
- " list_cat=[int(x) for x in gscript.parse_command('v.db.select', quiet=True, \n",
- " map=landscape_polygons, column='cat', flags='c')]\n",
- " list_cat.sort()\n",
- " # Declare a empty dictionnary which will contains the north, south, east, west values for each landscape unit\n",
- " landscapeunit_bbox={}\n",
- " # Declare a empty list which will contain the path of the configation files created\n",
- " listpath=[]\n",
- " # Declare a empty string variable which will contains the core part of the r.li configuration file\n",
- " maskedoverlayarea_1=\"\"\n",
- " # Duplicate 'listoflandcoverraster' in a new variable called 'tmp_list'\n",
- " tmp_list=list(listoflandcoverraster)\n",
- " # Set the current landcover raster as the first of the list\n",
- " base_landcover_raster=tmp_list.pop(0) #The pop function return the first item of the list and delete it from the list at the same time\n",
- " # Loop trough the landscape units\n",
- " for cat in list_cat:\n",
- " # Extract the current landscape unit polygon as temporary vector\n",
- " tmp_vect=\"tmp_\"+base_landcover_raster.split(\"@\")[0]+\"_\"+landscape_polygons.split(\"@\")[0]+\"_\"+str(cat)\n",
- " gscript.run_command('v.extract', overwrite=True, quiet=True, \n",
- " input=landscape_polygons, cats=cat, output=tmp_vect)\n",
- " # Set region to match the extent of the current landscape polygon, with resolution and alignement matching the landcover raster\n",
- " gscript.run_command('g.region', vector=tmp_vect, align=base_landcover_raster)\n",
- " # Rasterize the landscape unit polygon\n",
- " landscapeunit_rast=tmp_vect[4:]\n",
- " gscript.run_command('v.to.rast', overwrite=True, quiet=True, input=tmp_vect, output=landscapeunit_rast, use='cat', memory='3000')\n",
- " # Remove temporary vector\n",
- " gscript.run_command('g.remove', quiet=True, flags=\"f\", type='vector', name=tmp_vect)\n",
- " # Set the region to match the raster landscape unit extent and save the region info in a dictionary\n",
- " region_info=gscript.parse_command('g.region', raster=landscapeunit_rast, flags='g')\n",
- " n=str(round(float(region_info['n']),5)) #the config file need 5 decimal for north and south\n",
- " s=str(round(float(region_info['s']),5))\n",
- " e=str(round(float(region_info['e']),6)) #the config file need 6 decimal for east and west\n",
- " w=str(round(float(region_info['w']),6))\n",
- " # Save the coordinates of the bbox in the dictionary (n,s,e,w)\n",
- " landscapeunit_bbox[cat]=n+\"|\"+s+\"|\"+e+\"|\"+w\n",
- " # Add the line to the maskedoverlayarea_1 variable\n",
- " maskedoverlayarea_1+=\"MASKEDOVERLAYAREA \"+landscapeunit_rast+\"|\"+landscapeunit_bbox[cat]+\"\\n\"\n",
- "\n",
- " # Compile the content of the r.li configuration file\n",
- " config_file_content=\"SAMPLINGFRAME 0|0|1|1\\n\"\n",
- " config_file_content+=maskedoverlayarea_1\n",
- " config_file_content+=\"RASTERMAP \"+base_landcover_raster+\"\\n\"\n",
- " config_file_content+=\"VECTORMAP \"+landscape_polygons+\"\\n\"\n",
- "\n",
- " # Create a new file and save the content\n",
- " configfilename=base_landcover_raster.split(\"@\")[0]+\"_\"+landscape_polygons.split(\"@\")[0]\n",
- " path=os.path.join(rli_dir,configfilename)\n",
- " listpath.append(path)\n",
- " f=open(path, 'w')\n",
- " f.write(config_file_content)\n",
- " f.close()\n",
- " \n",
- " # Continue creation of r.li configuration file and landscape unit raster the rest of the landcover raster provided\n",
- " while len(tmp_list)>0:\n",
- " # Initialize 'maskedoverlayarea_2' variable as an empty string\n",
- " maskedoverlayarea_2=\"\"\n",
- " # Set the current landcover raster as the first of the list\n",
- " current_landcover_raster=tmp_list.pop(0) #The pop function return the first item of the list and delete it from the list at the same time\n",
- " if masklayerhardcopy: # If the user asked for hard copy of the landscape units mask layers\n",
- " # Copy all the landscape units masks for the current landcover raster\n",
- " p=Pool(ncores) #Create a pool of processes and launch them using 'map' function\n",
- " func=partial(copy_landscapeunitmasks,current_landcover_raster,base_landcover_raster,landscape_polygons,landscapeunit_bbox) # Set fixed argument of the function\n",
- " maskedoverlayarea_2=p.map(func,list_cat) # Launch the processes for as many items in the list and get the ordered results using map function\n",
- " p.close()\n",
- " p.join()\n",
- " # Compile the content of the r.li configuration file\n",
- " config_file_content=\"SAMPLINGFRAME 0|0|1|1\\n\"\n",
- " config_file_content+=\"\\n\".join(maskedoverlayarea_2)+\"\\n\"\n",
- " config_file_content+=\"RASTERMAP \"+current_landcover_raster+\"\\n\"\n",
- " config_file_content+=\"VECTORMAP \"+landscape_polygons+\"\\n\"\n",
- " else: # If the user not asked for hard copy\n",
- " # Compile the content of the r.li configuration file\n",
- " config_file_content=\"SAMPLINGFRAME 0|0|1|1\\n\"\n",
- " config_file_content+=maskedoverlayarea_1 # If user do not asked for hard copy, the mask layers are the same than for the first configuration file\n",
- " config_file_content+=\"RASTERMAP \"+current_landcover_raster+\"\\n\" # But the name of the RASTERMAP should be the one of the current landcover raster\n",
- " config_file_content+=\"VECTORMAP \"+landscape_polygons+\"\\n\"\n",
- " # Create a new file and save the content\n",
- " configfilename=current_landcover_raster.split(\"@\")[0]+\"_\"+landscape_polygons.split(\"@\")[0]\n",
- " path=os.path.join(rli_dir,configfilename)\n",
- " listpath.append(path)\n",
- " f=open(path, 'w')\n",
- " f.write(config_file_content)\n",
- " f.close()\n",
- " \n",
- " # Return a list of path of configuration files creates if option actived\n",
- " if returnlistpath:\n",
- " return list_cat,listpath\n",
- " else:\n",
- " return list_cat"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function for creation of binary raster from a categorical raster (multiprocessed)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "###### Function creating a binary raster for each category of a base raster. \n",
- "### The function run within the current region. If a category do not exists in the current region, no binary map will be produce\n",
- "# 'categorical_raster' wait for the name of the base raster to be used. It is the one from which one binary raster will be produced for each category value\n",
- "# 'prefix' wait for a string corresponding to the prefix of the name of the binary raster which will be produced\n",
- "# 'setnull' wait for a boolean value (True, False) according to the fact that the output binary should be 1/0 or 1/null\n",
- "# 'returnlistraster' wait for a boolean value (True, False) regarding to the fact that a list containing the name of binary raster is desired as return of the function\n",
- "# 'category_list' wait for a list of interger corresponding to specific category of the base raster to be used \n",
- "# 'ncores' wait for a integer corresponding to the number of desired cores to be used for parallelization\n",
- "\n",
- "# Import libraries for multiprocessing \n",
- "import multiprocessing\n",
- "from multiprocessing import Pool\n",
- "from functools import partial \n",
- "\n",
- "def create_binary_raster(categorical_raster,prefix=\"binary\",setnull=False,returnlistraster=True,category_list=None,ncores=2):\n",
- " # Check if raster exists to avoid error in mutliprocessing \n",
- " try:\n",
- " mpset=categorical_raster.split(\"@\")[1]\n",
- " except:\n",
- " mpset=\"\"\n",
- " if categorical_raster not in gscript.list_strings(type='raster',mapset=mpset):\n",
- " sys.exit('Raster <%s> not found' %categorical_raster)\n",
- " # Check for number of cores doesnt exceed available\n",
- " nbcpu=multiprocessing.cpu_count()\n",
- " if ncores>=nbcpu:\n",
- " ncores=nbcpu-1\n",
- " returnlist=[] #Declare empty list for return\n",
- " #gscript.run_command('g.region', raster=categorical_raster, quiet=True) #Set the region\n",
- " null='null()' if setnull else '0' #Set the value for r.mapcalc\n",
- " minclass=1 if setnull else 2 #Set the value to check if the binary raster is empty\n",
- " if category_list == None: #If no category_list provided\n",
- " category_list=[cl for cl in gscript.parse_command('r.category',map=categorical_raster,quiet=True)]\n",
- " for i,x in enumerate(category_list): #Make sure the format is UTF8 and not Unicode\n",
- " category_list[i]=x.encode('UTF8')\n",
- " category_list.sort(key=float) #Sort the raster categories in ascending.\n",
- " p=Pool(ncores) #Create a pool of processes and launch them using 'map' function\n",
- " func=partial(get_binary,categorical_raster,prefix,null,minclass) # Set the two fixed argument of the function\n",
- " returnlist=p.map(func,category_list) # Launch the processes for as many items in the 'functions_name' list and get the ordered results using map function\n",
- " p.close()\n",
- " p.join()\n",
- " if returnlistraster:\n",
- " return returnlist\n",
- "\n",
- "#### Function that extract binary raster for a specified class (called in 'create_binary_raster' function)\n",
- "def get_binary(categorical_raster,prefix,null,minclass,cl):\n",
- " binary_class=prefix+\"_\"+cl\n",
- " gscript.run_command('r.mapcalc', expression=binary_class+'=if('+categorical_raster+'=='+str(cl)+',1,'+null+')',overwrite=True, quiet=True)\n",
- " if len(gscript.parse_command('r.category',map=binary_class,quiet=True))>=minclass: #Check if created binary is not empty\n",
- " return binary_class\n",
- " else:\n",
- " gscript.run_command('g.remove', quiet=True, flags=\"f\", type='raster', name=binary_class)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function for computation of spatial metrics at landscape level (multiprocessed)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "##### Function that compute different landscape metrics (spatial metrics) at landscape level. \n",
- "### The metric computed are \"dominance\",\"pielou\",\"renyi\",\"richness\",\"shannon\",\"simpson\".\n",
- "### It is important to set the computation region before runing this script so that it match the extent of the 'raster' layer.\n",
- "# 'configfile' wait for the path (string) to the configuration file corresponding to the 'raster' layer.\n",
- "# 'raster' wait for the name (string) of the landcover map on which landscape metrics will be computed.\n",
- "# 'returnlistresult' wait for a boolean value (True/False) according to the fact that a list containing the path to the result files is desired.\n",
- "# 'ncores' wait for a integer corresponding to the number of desired cores to be used for parallelization.\n",
- "\n",
- "# Import libraries for multiprocessing \n",
- "import multiprocessing\n",
- "from multiprocessing import Pool\n",
- "from functools import partial \n",
- "\n",
- "def compute_landscapelevel_metrics(configfile, raster, spatial_metric):\n",
- " filename=raster.split(\"@\")[0]+\"_%s\" %spatial_metric\n",
- " outputfile=os.path.join(os.path.split(configfile)[0],\"output\",filename)\n",
- " if spatial_metric=='renyi': # The alpha parameter was set to 2 as in https://en.wikipedia.org/wiki/R%C3%A9nyi_entropy\n",
- " gscript.run_command('r.li.%s' %spatial_metric, overwrite=True,\n",
- " input=raster,config=configfile,alpha='2', output=filename)\n",
- " else:\n",
- " gscript.run_command('r.li.%s' %spatial_metric, overwrite=True,\n",
- " input=raster,config=configfile, output=filename)\n",
- " return outputfile\n",
- " \n",
- "def get_landscapelevel_metrics(configfile, raster, returnlistresult=True, ncores=2):\n",
- " # Check if raster exists to avoid error in mutliprocessing \n",
- " try:\n",
- " mpset=raster.split(\"@\")[1]\n",
- " except:\n",
- " mpset=\"\"\n",
- " if raster not in gscript.list_strings(type='raster',mapset=mpset):\n",
- " sys.exit('Raster <%s> not found' %raster)\n",
- " # Check if configfile exists to avoid error in mutliprocessing \n",
- " if not os.path.exists(configfile):\n",
- " sys.exit('Configuration file <%s> not found' %configfile)\n",
- " # List of metrics to be computed\n",
- " spatial_metric_list=[\"dominance\",\"pielou\",\"renyi\",\"richness\",\"shannon\",\"simpson\"]\n",
- " # Check for number of cores doesnt exceed available\n",
- " nbcpu=multiprocessing.cpu_count()\n",
- " if ncores>=nbcpu:\n",
- " ncores=nbcpu-1\n",
- " if ncores>len(spatial_metric_list):\n",
- " ncores=len(spatial_metric_list) #Adapt number of cores to number of metrics to compute\n",
- " #Declare empty list for return\n",
- " returnlist=[] \n",
- " # Create a new pool\n",
- " p=Pool(ncores)\n",
- " # Set the two fixed argument of the 'compute_landscapelevel_metrics' function\n",
- " func=partial(compute_landscapelevel_metrics,configfile, raster)\n",
- " # Launch the processes for as many items in the 'functions_name' list and get the ordered results using map function\n",
- " returnlist=p.map(func,spatial_metric_list)\n",
- " p.close()\n",
- " p.join()\n",
- " # Return list of paths to result files\n",
- " if returnlistresult:\n",
- " return returnlist"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function for computation of spatial metrics at class level (multiprocessed)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "##### Function that compute different landscape metrics (spatial metrics) at class level. \n",
- "### The metric computed are \"patch number (patchnum)\",\"patch density (patchdensity)\",\"mean patch size(mps)\",\n",
- "### \"coefficient of variation of patch area (padcv)\",\"range of patch area size (padrange)\",\n",
- "### \"standard deviation of patch area (padsd)\", \"shape index (shape)\", \"edge density (edgedensity)\".\n",
- "### It is important to set the computation region before runing this script so that it match the extent of the 'raster' layer.\n",
- "# 'configfile' wait for the path (string) to the configuration file corresponding to the 'raster' layer.\n",
- "# 'raster' wait for the name (string) of the landcover map on which landscape metrics will be computed.\n",
- "# 'returnlistresult' wait for a boolean value (True/False) according to the fact that a list containing the path to the result files is desired.\n",
- "# 'ncores' wait for a integer corresponding to the number of desired cores to be used for parallelization.\n",
- "\n",
- "# Import libraries for multiprocessing \n",
- "import multiprocessing\n",
- "from multiprocessing import Pool\n",
- "from functools import partial \n",
- "\n",
- "def compute_classlevel_metrics(configfile, raster, spatial_metric):\n",
- " filename=raster.split(\"@\")[0]+\"_%s\" %spatial_metric\n",
- " gscript.run_command('r.li.%s' %spatial_metric, overwrite=True,\n",
- " input=raster,config=configfile,output=filename)\n",
- " outputfile=os.path.join(os.path.split(configfile)[0],\"output\",filename)\n",
- " return outputfile\n",
- " \n",
- "def get_classlevel_metrics(configfile, raster, returnlistresult=True, ncores=2):\n",
- " # Check if raster exists to avoid error in mutliprocessing \n",
- " try:\n",
- " mpset=raster.split(\"@\")[1]\n",
- " except:\n",
- " mpset=\"\"\n",
- " if raster not in [x.split(\"@\")[0] for x in gscript.list_strings(type='raster',mapset=mpset)]:\n",
- " sys.exit('Raster <%s> not found' %raster)\n",
- " # Check if configfile exists to avoid error in mutliprocessing \n",
- " if not os.path.exists(configfile):\n",
- " sys.exit('Configuration file <%s> not found' %configfile)\n",
- " # List of metrics to be computed\n",
- " spatial_metric_list=[\"patchnum\",\"patchdensity\",\"mps\",\"padcv\",\"padrange\",\"padsd\",\"shape\",\"edgedensity\"]\n",
- " # Check for number of cores doesnt exceed available\n",
- " nbcpu=multiprocessing.cpu_count()\n",
- " if ncores>=nbcpu:\n",
- " ncores=nbcpu-1\n",
- " if ncores>len(spatial_metric_list):\n",
- " ncores=len(spatial_metric_list) #Adapt number of cores to number of metrics to compute\n",
- " # Declare empty list for return\n",
- " returnlist=[] \n",
- " # Create a new pool\n",
- " p=Pool(ncores)\n",
- " # Set the two fixed argument of the 'compute_classlevel_metrics' function\n",
- " func=partial(compute_classlevel_metrics,configfile, raster)\n",
- " # Launch the processes for as many items in the 'functions_name' list and get the ordered results using map function\n",
- " returnlist=p.map(func,spatial_metric_list)\n",
- " p.close()\n",
- " p.join()\n",
- " # Return list of paths to result files\n",
- " if returnlistresult:\n",
- " return returnlist"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function for computation of each land cover class proportion in landscape units"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 47,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "### Function that compute the proportion of each class of landcover\n",
- "import itertools\n",
- "import multiprocessing\n",
- "from functools import partial\n",
- "import sys, csv\n",
- "import grass.script as gscript\n",
- "\n",
- "def random_string(N):\n",
- " import random, string\n",
- " prefix=random.choice(string.ascii_uppercase + string.ascii_lowercase)\n",
- " suffix=''.join(random.choice(string.ascii_uppercase + string.ascii_lowercase + string.digits) for _ in range(N))\n",
- " return prefix+suffix\n",
- "\n",
- "def compute_prop_landcover(outputfolder,landscape_units_raster,binary_class_raster):\n",
- " # Save the current class in a new variable \n",
- " current_class=binary_class_raster.split(\"@\")[0].split(\"_\")[-1]\n",
- " # Initialize a temp files\n",
- " temp_file=os.path.join(outputfolder,random_string(10))\n",
- " tmp_copy='%s_%s'%(random_string(4),current_class)\n",
- " # Make copy of the raster and fill the null values with zero\n",
- " gscript.run_command('g.copy', overwrite=True, raster='%s,%s'%(binary_class_raster,tmp_copy))\n",
- " gscript.run_command('r.null', map=tmp_copy, null='0')\n",
- " # Compute area of landscape unit and total pixels of the current binary class raster\n",
- " gscript.run_command('i.segment.stats', flags=\"r\", quiet=True, overwrite=True, \n",
- " map=landscape_units_raster, area_measures='area', \n",
- " rasters=tmp_copy, raster_statistics='sum', \n",
- " csvfile=temp_file, separator='pipe')\n",
- " gscript.run_command('g.remove', flags='f', type='raster', name=tmp_copy)\n",
- " # Create outputfile and compute proportion of class\n",
- " outfile=os.path.join(outputfolder, \"prop_%s\"%current_class)\n",
- " writer=csv.writer(open(outfile,'w'), delimiter=\"|\")\n",
- " reader=csv.reader(open(temp_file,'r'), delimiter=\"|\")\n",
- " header=reader.next()\n",
- " crash_report=[]\n",
- " content=[]\n",
- " content.append([header[0],\"prop_%s\"%current_class]) #Create new header with first original column and current class related name for proportion\n",
- " for row in reader:\n",
- " try:\n",
- " prop=100*float(row[2])/float(row[1])\n",
- " content.append([row[0],\"{0:.5f}\".format(prop)])\n",
- " except ZeroDivisionError:\n",
- " crash_report.append(row[0])\n",
- " continue\n",
- " writer.writerows(content)\n",
- " os.remove(temp_file)\n",
- " # Print notification of ZeroDivisionError if it happened\n",
- " if len(crash_report)>0:\n",
- " print \"An 'ZeroDivisionError' has been registered for the following <%s>\"%header[0]+\"\\n\".join(crash_report)\n",
- " # Return the result file\n",
- " return outfile\n",
- " \n",
- "def get_classproportions(outputfolder,landscape_units_raster,binary_class_raster_list,\n",
- " returnlistresult=True,ncores=2):\n",
- " # Check if raster exists to avoid error in mutliprocessing \n",
- " try:\n",
- " mpset=landscape_units_raster.split(\"@\")[1]\n",
- " except:\n",
- " mpset=\"\"\n",
- " if landscape_units_raster not in [x.split(\"@\")[0] for x in gscript.list_strings(type='raster',mapset=mpset)]:\n",
- " sys.exit('Raster <%s> not found' %landscape_units_raster)\n",
- " # Check for number of cores doesnt exceed available\n",
- " nbcpu=multiprocessing.cpu_count()\n",
- " if ncores>=nbcpu:\n",
- " ncores=nbcpu-1\n",
- " if ncores>len(binary_class_raster_list):\n",
- " ncores=len(binary_class_raster_list) #Adapt number of cores to number of metrics to compute\n",
- " # Declare empty list for return\n",
- " returnlist=[] \n",
- " # Create a new pool\n",
- " p=Pool(ncores)\n",
- " # Set the two fixed argument of the 'compute_prop_landcover' function\n",
- " func=partial(compute_prop_landcover,outputfolder,landscape_units_raster)\n",
- " # Launch the processes for as many items in the 'functions_name' list and get the ordered results using map function\n",
- " returnlist=p.map(func,binary_class_raster_list)\n",
- " p.close()\n",
- " p.join()\n",
- " # Return list of paths to result files\n",
- " if returnlistresult:\n",
- " return returnlist"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Function that enable for join of multiple different .csv files"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 66,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "def atoi(text):\n",
- " '''\n",
- " Function that return integer if text is digit - Used in 'natural_keys' function\n",
- " '''\n",
- " return int(text) if text.isdigit() else text\n",
- "\n",
- "def natural_keys(text): # Trick was found here: https://stackoverflow.com/questions/5967500/how-to-correctly-sort-a-string-with-a-number-inside\n",
- " '''\n",
- " Return key to be used for sorting string containing numerical values - Used in 'leftjoin_2csv' function\n",
- " '''\n",
- " import re #Import needed library\n",
- " return [ atoi(c) for c in re.split('(\\d+)', text) ] #Split the string\n",
- "\n",
- "def join_2csv(file1,file2,separator=\";\",join='inner',fillempty='NULL'):\n",
- " '''\n",
- " Function that join two csv files according to the first column (primary key).\n",
- " 'file1' and 'file2' wait for complete path (strings) to the corresponding files. Please not that 'file1' is assume to be the left-one in the join\n",
- "\t'separator' wait for the character to be considered as .csv delimiter (string)\n",
- "\t'join' parameter wait either for 'left' or 'inner' according to type of join\n",
- "\t'fillempty' wait for the string to be use to fill the blank when no occurance is found for the join operation\n",
- " '''\n",
- " import tempfile,csv,os\n",
- " header_list=[]\n",
- " file1_values_dict={}\n",
- " file2_values_dict={}\n",
- " reader1=csv.reader(open(file1), delimiter=separator) #Csv reader for file 1\n",
- " reader2=csv.reader(open(file2), delimiter=separator) #Csv reader for file 2\n",
- " # Make a list of headers\n",
- " header_list1=[ x for x in reader1.next()]\n",
- " header_list2=[ x for x in reader2.next()[1:]]\n",
- " # Make a list of unique IDs from the first and second table according to type of join\n",
- " if join=='inner':\n",
- " id_list=[ row[0] for row in reader1]\n",
- " [id_list.append(row[0]) for row in reader2]\n",
- " id_list=list(set(id_list))\n",
- " id_list.sort(key=natural_keys)\n",
- " if join=='left':\n",
- " id_list=[ row[0] for row in reader1]\n",
- " id_list=list(set(id_list))\n",
- " id_list.sort(key=natural_keys)\n",
- " # Build dictionnary for values of file 1\n",
- " reader1=csv.reader(open(file1), delimiter=separator)\n",
- " reader1.next()\n",
- " values_dict1={rows[0]:rows[1:] for rows in reader1}\n",
- " # Build dictionnary for values of file 2\n",
- " reader2=csv.reader(open(file2), delimiter=separator)\n",
- " reader2.next()\n",
- " values_dict2={rows[0]:rows[1:] for rows in reader2}\n",
- " # Built new content\n",
- " new_content=[]\n",
- " new_header=header_list1+header_list2\n",
- " new_content.append(new_header)\n",
- " for key in id_list:\n",
- " new_row=[key]\n",
- " try:\n",
- " [new_row.append(value) for value in values_dict1[key]]\n",
- " except:\n",
- " [new_row.append('%s'%fillempty) for x in header_list1[1:]]\n",
- " try:\n",
- " [new_row.append(value) for value in values_dict2[key]]\n",
- " except:\n",
- " [new_row.append('%s'%fillempty) for x in header_list2]\n",
- " new_content.append(new_row)\n",
- " #Return the result\n",
- " outfile=os.path.join(tempfile.gettempdir(),\"temp\")\n",
- " writer=csv.writer(open(outfile,\"w\"), delimiter=separator)\n",
- " writer.writerows(new_content) #Write multiples rows in the file\n",
- " return outfile\n",
- "\n",
- "def join_multiplecsv(fileList,outfile,separator=\";\",join='inner', fillempty='NULL', overwrite=False):\n",
- " '''\n",
- " Function that apply join on multiple csv files\n",
- " '''\n",
- " import os, sys, shutil\n",
- " # Stop execution if outputfile exitst and can not be overwriten\n",
- " if os.path.isfile(outfile) and overwrite==False:\n",
- " print \"File '%s' aleady exists and overwrite option is not enabled.\"%outfile\n",
- " else:\n",
- " if os.path.isfile(outfile) and overwrite==True: # If outputfile exitst and can be overwriten\n",
- " #os.remove(outfile)\n",
- " print \"File '%s' will be overwrited.\"%outfile\n",
- " nbfile=len(fileList)\n",
- " if nbfile<=1: #Check if there are at least 2 files in the list\n",
- " sys.exit(\"This function require at least two .csv files to be jointed together.\")\n",
- " # Copy the list of file in a queue list\n",
- " queue_list=list(fileList)\n",
- " # Left join on the two first files\n",
- " file1=queue_list.pop(0)\n",
- " file2=queue_list.pop(0)\n",
- " tmp_file=join_2csv(file1,file2,separator=separator,join=join, fillempty=fillempty)\n",
- " # Left join on the rest of the files in the list\n",
- " while len(queue_list)>0:\n",
- " file2=queue_list.pop(0)\n",
- " tmp_file=join_2csv(tmp_file,file2,separator=separator,join=join, fillempty=fillempty)\n",
- " #Copy the temporary file to the desired output path\n",
- " shutil.copy2(tmp_file,outfile)\n",
- " # Print what happend\n",
- " print \"%s individual .csv files were joint together.\"%nbfile\n",
- "\n",
- "def create_csvt(csv_file,separator=\";\",first_col_type=\"Integer\",rest_type=\"Real\"):\n",
- " '''\n",
- " Function that create a .csvt file with the same type of all columns except first one\n",
- " '''\n",
- " import csv\n",
- " writer=csv.writer(open(csv_file+\"t\",\"w\"),delimiter=separator)\n",
- " reader=csv.reader(open(csv_file,\"r\"),delimiter=separator)\n",
- " header=reader.next()\n",
- " typecolumn=[]\n",
- " typecolumn.append(first_col_type)\n",
- " for columns in header[1:]:\n",
- " typecolumn.append(rest_type)\n",
- " writer.writerow(typecolumn)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- " User inputs
"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "## Define a empty dictionnary for saving user inputs\n",
- "user={}"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "## Enter the path to GRASSDATA folder\n",
- "user[\"gisdb\"] = \"/home/tais/Documents/GRASSDATA_Spie2017subset_Ouaga\"\n",
- "\n",
- "## Enter the name of the location (existing or for a new one)\n",
- "user[\"location\"] = \"SPIE_subset\"\n",
- "\n",
- "## Enter the EPSG code for this location \n",
- "user[\"locationepsg\"] = \"32630\"\n",
- "\n",
- "## Enter the name of the mapset to use for segmentation\n",
- "user[\"mapsetname\"] = \"test_rli\""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "# Compute landscape metrics (spatial metrics) from the land cover map, using r.li"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "**Launch GRASS GIS working session**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 12,
- "metadata": {
- "scrolled": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "You are now working in mapset 'test_rli'\n"
- ]
- }
- ],
- "source": [
- "## Set the name of the mapset in which to work\n",
- "mapsetname=user[\"mapsetname\"]\n",
- "\n",
- "## Launch GRASS GIS working session in the mapset\n",
- "if os.path.exists(os.path.join(user[\"gisdb\"],user[\"location\"],mapsetname)):\n",
- " gsetup.init(os.environ['GISBASE'], user[\"gisdb\"], user[\"location\"], mapsetname)\n",
- " print \"You are now working in mapset '\"+mapsetname+\"'\" \n",
- "else: \n",
- " print \"'\"+mapsetname+\"' mapset doesn't exists in \"+user[\"gisdb\"]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "**Set the path to the r.li folder for configuration file and for results**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "GRASS GIS add-on's r.li configuration files will be saved under .\n",
- "GRASS GIS add-on's r.li outputs will be saved under .\n"
- ]
- }
- ],
- "source": [
- "# Define path of the outputfile (in r.li folder)\n",
- "version=grass.version()['version'].split('.')[0] # Get the version of GRASS GIS \n",
- "if sys.platform==\"win32\":\n",
- " rli_config_dir=os.path.join(os.environ['APPDATA'],\"GRASS\"+version,\"r.li\")\n",
- " rli_output_dir=os.path.join(os.environ['APPDATA'],\"GRASS\"+version,\"r.li\",\"output\")\n",
- "else: \n",
- " rli_config_dir=os.path.join(os.environ['HOME'],\".grass\"+version,\"r.li\")\n",
- " rli_output_dir=os.path.join(os.environ['HOME'],\".grass\"+version,\"r.li\",\"output\")\n",
- "if not os.path.exists(rli_config_dir):\n",
- " os.makedirs(rli_config_dir)\n",
- "if not os.path.exists(rli_output_dir):\n",
- " os.makedirs(rli_output_dir)\n",
- "# Print\n",
- "print \"GRASS GIS add-on's r.li configuration files will be saved under <%s>.\"%(rli_config_dir,)\n",
- "print \"GRASS GIS add-on's r.li outputs will be saved under <%s>.\"%(rli_output_dir,)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Define the name of the base landcover map and landscape units polygons"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set the name of the 'base' landcover map\n",
- "baselandcoverraster=\"classif@test_rli\"\n",
- "# Set the name of the vector polygon layer containing the landscape units\n",
- "landscape_polygons=\"streetblocks\""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Import shapefile containing street blocks polygons"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set the path to the shapefile containing streetblocks polygons\n",
- "pathtoshp=\"/media/tais/data/Dropbox/ULB/MAUPP/Landuse_mapping/Test_spatial_metrics_computation/Data/streetblocks_subset.shp\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0"
- ]
- },
- "execution_count": 17,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Import shapefile\n",
- "gscript.run_command('v.in.ogr', quiet=True, overwrite=True, input=pathtoshp, output=landscape_polygons)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Create binary rasters from the base landcover map"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Extraction of binary rasters achieved in 4.4 seconds'"
- ]
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "\n",
- "# Create as many binary raster layer as categorical values existing in the base landcover map\n",
- "gscript.run_command('g.region', raster=baselandcoverraster, quiet=True) #Set the region\n",
- "pref=baselandcoverraster.split(\"@\")[0]+\"_cl\" #Set the prefix\n",
- "\n",
- "raster_list=[] # Initialize a empty list for results\n",
- "raster_list=create_binary_raster(baselandcoverraster,\n",
- " prefix=pref,setnull=True,returnlistraster=True,\n",
- " category_list=None,ncores=15) #Extract binary raster \n",
- "\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Extraction of binary rasters achieved in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "metadata": {
- "scrolled": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "['classif@test_rli',\n",
- " 'classif_cl_11',\n",
- " 'classif_cl_13',\n",
- " 'classif_cl_14',\n",
- " 'classif_cl_20',\n",
- " 'classif_cl_30',\n",
- " 'classif_cl_31',\n",
- " 'classif_cl_41',\n",
- " 'classif_cl_51']"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Insert the name of the base landcover map at first position in the list\n",
- "raster_list.insert(0,baselandcoverraster)\n",
- "# Display the raster to be used for landscape analysis\n",
- "raster_list"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Create r.li configuration file for a list of landcover rasters"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Creation of r.li configuration files achieved in 3 minutes and 33.1 seconds'"
- ]
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Run creation of r.li configuration file and associated raster layers\n",
- "list_cats,list_configfile=create_rli_configfile(raster_list,landscape_polygons,masklayerhardcopy=False,returnlistpath=True,ncores=20)\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Creation of r.li configuration files achieved in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "metadata": {
- "scrolled": false
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[u'/home/tais/.grass7/r.li/classif_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_11_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_13_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_14_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_20_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_30_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_31_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_41_streetblocks',\n",
- " u'/home/tais/.grass7/r.li/classif_cl_51_streetblocks']"
- ]
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Display the path to the configuration files created\n",
- "list_configfile"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Compute spatial metrics at landscape level"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Initialize an empty list which will contains the resultfiles \n",
- "resultfiles=[]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Computation of spatial metric achieved in 41.3 seconds'"
- ]
- },
- "execution_count": 23,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Get the path to the configuration file for the base landcover raster\n",
- "currentconfigfile=list_configfile[0]\n",
- "# Get the name of the base landcover raster\n",
- "currentraster=raster_list[0]\n",
- "# Set the region to match the extent of the base raster\n",
- "gscript.run_command('g.region', raster=currentraster, quiet=True)\n",
- "# Launch the processes for as many items in the 'functions_name' list and get the ordered results using map function\n",
- "resultfiles.append(get_landscapelevel_metrics(currentconfigfile, currentraster, returnlistresult=True, ncores=15))\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Computation of spatial metric achieved in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[[u'/home/tais/.grass7/r.li/output/classif_dominance',\n",
- " u'/home/tais/.grass7/r.li/output/classif_pielou',\n",
- " u'/home/tais/.grass7/r.li/output/classif_renyi',\n",
- " u'/home/tais/.grass7/r.li/output/classif_richness',\n",
- " u'/home/tais/.grass7/r.li/output/classif_shannon',\n",
- " u'/home/tais/.grass7/r.li/output/classif_simpson']]"
- ]
- },
- "execution_count": 24,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "resultfiles"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Compute spatial metrics at class level"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 25,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Computation of spatial metric achieved in 6 minutes and 1.1 seconds'"
- ]
- },
- "execution_count": 25,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Get a list with paths to the configuration file for class level metrics\n",
- "classlevelconfigfiles=list_configfile[1:]\n",
- "# Get a list with name of binary landcover raster for class level metrics\n",
- "classlevelrasters=raster_list[1:]\n",
- "\n",
- "for x,currentraster in enumerate(classlevelrasters[:]):\n",
- " # Get the path to the configuration file for the base landcover raster\n",
- " currentconfigfile=classlevelconfigfiles[x]\n",
- " # Set the region to match the extent of the base raster\n",
- " gscript.run_command('g.region', raster=currentraster, quiet=True)\n",
- " # Launch the processes for as many items in the 'functions_name' list and get the ordered results using map function\n",
- " resultfiles.append(get_classlevel_metrics(currentconfigfile, currentraster, returnlistresult=True, ncores=10))\n",
- "\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Computation of spatial metric achieved in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[[u'/home/tais/.grass7/r.li/output/classif_dominance',\n",
- " u'/home/tais/.grass7/r.li/output/classif_pielou',\n",
- " u'/home/tais/.grass7/r.li/output/classif_renyi',\n",
- " u'/home/tais/.grass7/r.li/output/classif_richness',\n",
- " u'/home/tais/.grass7/r.li/output/classif_shannon',\n",
- " u'/home/tais/.grass7/r.li/output/classif_simpson'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_11_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_13_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_14_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_20_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_30_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_31_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_41_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_edgedensity'],\n",
- " [u'/home/tais/.grass7/r.li/output/classif_cl_51_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_edgedensity']]"
- ]
- },
- "execution_count": 26,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "resultfiles"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Change the results files from r.li to get the correct 'cat' value for each landscape unit"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 28,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Flat the 'resultfiles' list which contains several lists\n",
- "resultfiles=[item for sublist in resultfiles for item in sublist]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 29,
- "metadata": {},
- "outputs": [],
- "source": [
- "import csv, shutil\n",
- "from itertools import izip\n",
- "\n",
- "for f in resultfiles:\n",
- " f_in=open(f)\n",
- " f_tmp=open(f+'_tmp',\"w\")\n",
- " f_in_reader=csv.reader(f_in,delimiter='|')\n",
- " f_tmp_writer=csv.writer(f_tmp,delimiter='|')\n",
- " f_tmp_writer.writerow(['cat',\"_\".join(os.path.split(f)[-1].split(\"_\")[1:])])\n",
- " for i,row in enumerate(f_in_reader):\n",
- " newrow=[]\n",
- " try:\n",
- " newrow.append(list_cats[i])\n",
- " newrow.append(row[1])\n",
- " f_tmp_writer.writerow(newrow)\n",
- " except:\n",
- " continue\n",
- " f_in.close()\n",
- " f_tmp.close()\n",
- " os.remove(f)\n",
- " shutil.copy2(f+'_tmp',f)\n",
- " os.remove(f+'_tmp')"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "# Compute some special metrics"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "### Creating a raster layer of landscape units"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Creating a raster layer of landscape units with resolution corresponding to the one of land cover raster"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0"
- ]
- },
- "execution_count": 30,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Create a raster corresponding to the landscape units (for computing statistics using i.segment.stats)\n",
- "gscript.run_command('g.region', raster=baselandcoverraster, quiet=True) #Set the region\n",
- "raster_landscapeunits=\"temp_%s\"%landscape_polygons.split(\"@\")[0]\n",
- "gscript.run_command('v.to.rast', overwrite=True, input=landscape_polygons, output=raster_landscapeunits, use='cat') "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "### Shape statistics for the landscape units"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 31,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set the path to the file for i.segment.stats results for landscape units shape metrics\n",
- "landscape_units_shape_metrics=os.path.join(rli_output_dir,\"landscape_units_shape_metrics\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 32,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Metrics computed in 1.0 seconds'"
- ]
- },
- "execution_count": 32,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Run i.segment.stats\n",
- "gscript.run_command('i.segment.stats', overwrite=True, map=raster_landscapeunits,\n",
- " area_measures='area,perimeter,compact_circle,compact_square,fd',\n",
- " csvfile=landscape_units_shape_metrics,\n",
- " processes='1')\n",
- "\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Metrics computed in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 33,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "resultfiles.append(landscape_units_shape_metrics)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "### Mean and standard deviation of SAR textures, NDVI, NDWI"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 34,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set the name of the nDSM layer\n",
- "ndsm=\"ndsm\"\n",
- "# Set the name of the NDVI layer\n",
- "ndvi=\"ndvi\"\n",
- "# Set the name of the NDWI layer\n",
- "ndwi=\"ndwi\"\n",
- "# Set the prefix of SAR textures layer\n",
- "SAR_prefix=\"SAR_w\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 35,
- "metadata": {
- "scrolled": false
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Layer to be used :\n",
- "\n",
- "ndvi\n",
- "ndwi\n",
- "SAR_w11.1@PERMANENT\n",
- "SAR_w11.2@PERMANENT\n",
- "SAR_w11.3@PERMANENT\n",
- "SAR_w11.4@PERMANENT\n",
- "SAR_w11.5@PERMANENT\n",
- "SAR_w11.6@PERMANENT\n",
- "SAR_w11.7@PERMANENT\n",
- "SAR_w7.1@PERMANENT\n",
- "SAR_w7.2@PERMANENT\n",
- "SAR_w7.3@PERMANENT\n",
- "SAR_w7.4@PERMANENT\n",
- "SAR_w7.5@PERMANENT\n",
- "SAR_w7.6@PERMANENT\n",
- "SAR_w7.7@PERMANENT\n"
- ]
- }
- ],
- "source": [
- "# Set up a list with name of raster layer to be used\n",
- "ancillarylayers=[]\n",
- "ancillarylayers.append(ndvi)\n",
- "ancillarylayers.append(ndwi)\n",
- "[ancillarylayers.append(x) for x in gscript.list_strings(\"rast\", pattern=SAR_prefix, flag='r')] #Append SAR textures\n",
- "print \"Layer to be used :\\n\\n\"+'\\n'.join(ancillarylayers)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 36,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set the path to the file for i.segment.stats results for metrics_ndvi_ndwi_sar\n",
- "metrics_ndvi_ndwi_sar=os.path.join(rli_output_dir,\"metrics_ndvi_ndwi_sar\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Metrics computed in 11.2 seconds'"
- ]
- },
- "execution_count": 37,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "###### Compute shape metrics as well as mean and stddev of ancillary layers for each landscape unit\n",
- "## Set number of cores to be used\n",
- "ncores=len(ancillarylayers) \n",
- "nbcpu=multiprocessing.cpu_count()\n",
- "if ncores>=nbcpu:\n",
- " ncores=nbcpu-1\n",
- " if ncores>len(ancillarylayers):\n",
- " ncores=len(ancillarylayers) #Adapt number of cores to number of metrics to compute\n",
- "# Run i.segment.stats\n",
- "gscript.run_command('i.segment.stats', overwrite=True, map=raster_landscapeunits,\n",
- " raster_statistics='stddev,median',\n",
- " rasters=','.join(ancillarylayers),\n",
- " csvfile=metrics_ndvi_ndwi_sar,\n",
- " processes=ncores,\n",
- " flags='s')\n",
- "\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Metrics computed in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 38,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "resultfiles.append(metrics_ndvi_ndwi_sar)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 39,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[u'/home/tais/.grass7/r.li/output/classif_dominance',\n",
- " u'/home/tais/.grass7/r.li/output/classif_pielou',\n",
- " u'/home/tais/.grass7/r.li/output/classif_renyi',\n",
- " u'/home/tais/.grass7/r.li/output/classif_richness',\n",
- " u'/home/tais/.grass7/r.li/output/classif_shannon',\n",
- " u'/home/tais/.grass7/r.li/output/classif_simpson',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/landscape_units_shape_metrics',\n",
- " u'/home/tais/.grass7/r.li/output/metrics_ndvi_ndwi_sar']"
- ]
- },
- "execution_count": 39,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "resultfiles"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "### Mean and standard deviation of building's height"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "**Create raster with nDSM value of 'buildings' pixels**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 40,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set pixel value of 'buildings' on the 'baselandcoverraster'\n",
- "buildpixel=11\n",
- "# Set the name of the new layer containing height of buildings\n",
- "buildings_height='buildings_height'\n",
- "# Set the path to the file for i.segment.stats results for metrics_ndvi_ndwi_sar\n",
- "metrics_buildings_height=os.path.join(rli_output_dir,\"metrics_buildings_height\")\n",
- "# Create temp fil which will contain intermediate results\n",
- "TMP_sumheights=grass.tempfile()+'_sumheights.csv'\n",
- "TMP_nbrbuildpixels=grass.tempfile()+'_nbrbuildpixels.csv'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 41,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'Creation of layer in 5.9 seconds'"
- ]
- },
- "execution_count": 41,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Create a raster layer with height of pixels classified as 'buildings'\n",
- "gscript.run_command('g.region', raster=baselandcoverraster, quiet=True) #Set the region\n",
- "formula=\"%s=if(%s==%s, %s, 0)\"%(buildings_height,baselandcoverraster,buildpixel,ndsm)\n",
- "gscript.mapcalc(formula, overwrite=True)\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Creation of layer in \")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "**Compute the metric**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 42,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'i.segment.stats run in 10.4 seconds'"
- ]
- },
- "execution_count": 42,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Compute sum of build pixels's height using i.segment.stats \n",
- "gscript.run_command('i.segment.stats', overwrite=True, map=raster_landscapeunits,\n",
- " raster_statistics='sum', flags='s', rasters='buildings_height',\n",
- " csvfile=TMP_sumheights,processes=ncores)\n",
- "# Compute number of built pixels using i.segment.stats\n",
- "binary_builtup_raster=\"%s_cl_%s\"%(baselandcoverraster.split(\"@\")[0],buildpixel)\n",
- "gscript.run_command('g.copy', overwrite=True, raster='%s,tmp'%binary_builtup_raster)\n",
- "gscript.run_command('r.null', map='tmp', null=0)\n",
- "gscript.run_command('i.segment.stats', overwrite=True, map=raster_landscapeunits,\n",
- " raster_statistics='sum', flags='s', rasters='tmp',\n",
- " csvfile=TMP_nbrbuildpixels,processes=ncores)\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"i.segment.stats run in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 43,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "\"Mean build pixels's height computed in 0.0 seconds\""
- ]
- },
- "execution_count": 43,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Save time for computing processin time\n",
- "begintime=time.time()\n",
- "# Improt library to be able to iterate on two files in the same loop\n",
- "from itertools import izip\n",
- "# Declare empty dictionnary\n",
- "tmp_dic={}\n",
- "for i, (line_from_file_1, line_from_file_2) in enumerate(izip(open(TMP_sumheights), open(TMP_nbrbuildpixels))):\n",
- " if i==0:\n",
- " continue\n",
- " f1_items=line_from_file_1.split(\"\\n\")[0].split(\"|\")\n",
- " f2_items=line_from_file_2.split(\"\\n\")[0].split(\"|\")\n",
- " key=f1_items[0]\n",
- " sumheight=f1_items[1]\n",
- " nbpixel=f2_items[1]\n",
- " try:\n",
- " mean_height=float(sumheight)/float(nbpixel)\n",
- " except ZeroDivisionError:\n",
- " mean_height=0\n",
- " tmp_dic[key]=mean_height\n",
- "# Get the name of the first colum\n",
- "with open(TMP_sumheights) as f:\n",
- " column_a=f.next().split(\"\\n\")[0].split(\"|\")[0]\n",
- "# Built the content of the file\n",
- "content=[]\n",
- "content.append((column_a,'mean_build_height'))\n",
- "for key in tmp_dic.keys():\n",
- " content.append((key,tmp_dic[key]))\n",
- "# Create a new file\n",
- "fout=open(metrics_buildings_height,\"w\")\n",
- "writer=csv.writer(fout, delimiter='|')\n",
- "writer.writerows(content)\n",
- "fout.close()\n",
- "# Compute and print processing time\n",
- "print_processing_time(begintime,\"Mean build pixels's height computed in \")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 44,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Remove temporary layers\n",
- "gscript.run_command('g.remove', flags='ef', type='raster', name='tmp')\n",
- "# Remove temporary files\n",
- "os.remove(TMP_sumheights)\n",
- "os.remove(TMP_nbrbuildpixels)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 45,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "resultfiles.append(metrics_buildings_height)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 63,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[u'/home/tais/.grass7/r.li/output/classif_dominance',\n",
- " u'/home/tais/.grass7/r.li/output/classif_pielou',\n",
- " u'/home/tais/.grass7/r.li/output/classif_renyi',\n",
- " u'/home/tais/.grass7/r.li/output/classif_richness',\n",
- " u'/home/tais/.grass7/r.li/output/classif_shannon',\n",
- " u'/home/tais/.grass7/r.li/output/classif_simpson',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/landscape_units_shape_metrics',\n",
- " u'/home/tais/.grass7/r.li/output/metrics_ndvi_ndwi_sar',\n",
- " u'/home/tais/.grass7/r.li/output/metrics_buildings_height']"
- ]
- },
- "execution_count": 63,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "resultfiles"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "### Proportion of each of individual classes in the landcover map"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 48,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Set a tuple with name of land cover class binary raster to be processed \n",
- "listofbinary=tuple(raster_list[1:])\n",
- "# Compute proportion of each land cover class in landscape units\n",
- "proportion_results=get_classproportions(rli_output_dir,raster_landscapeunits,listofbinary,returnlistresult=True,ncores=10)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 64,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[None, None, None, None, None, None, None, None]"
- ]
- },
- "execution_count": 64,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "[resultfiles.append(x) for x in proportion_results]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 65,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[u'/home/tais/.grass7/r.li/output/classif_dominance',\n",
- " u'/home/tais/.grass7/r.li/output/classif_pielou',\n",
- " u'/home/tais/.grass7/r.li/output/classif_renyi',\n",
- " u'/home/tais/.grass7/r.li/output/classif_richness',\n",
- " u'/home/tais/.grass7/r.li/output/classif_shannon',\n",
- " u'/home/tais/.grass7/r.li/output/classif_simpson',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_11_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_13_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_14_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_20_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_30_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_31_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_41_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchnum',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_patchdensity',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_mps',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padcv',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padrange',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_padsd',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_shape',\n",
- " u'/home/tais/.grass7/r.li/output/classif_cl_51_edgedensity',\n",
- " u'/home/tais/.grass7/r.li/output/landscape_units_shape_metrics',\n",
- " u'/home/tais/.grass7/r.li/output/metrics_ndvi_ndwi_sar',\n",
- " u'/home/tais/.grass7/r.li/output/metrics_buildings_height',\n",
- " u'/home/tais/.grass7/r.li/output/prop_11',\n",
- " u'/home/tais/.grass7/r.li/output/prop_13',\n",
- " u'/home/tais/.grass7/r.li/output/prop_14',\n",
- " u'/home/tais/.grass7/r.li/output/prop_20',\n",
- " u'/home/tais/.grass7/r.li/output/prop_30',\n",
- " u'/home/tais/.grass7/r.li/output/prop_31',\n",
- " u'/home/tais/.grass7/r.li/output/prop_41',\n",
- " u'/home/tais/.grass7/r.li/output/prop_51']"
- ]
- },
- "execution_count": 65,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "resultfiles"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "# File management (join, cleaning, etc)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Combine all .csv files together"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 67,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Define the path for the .csv with final results\n",
- "outfile=os.path.join(rli_output_dir,\"land_use_metrics.csv\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 68,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "81 individual .csv files were joint together.\n"
- ]
- }
- ],
- "source": [
- "# Join (inner join) all result files together in a new .csv file\n",
- "join_multiplecsv(resultfiles,outfile,separator=\"|\",join='inner',fillempty='NULL',overwrite=True)\n",
- "# Create .csvt file\n",
- "create_csvt(outfile,separator=\"|\",first_col_type=\"Integer\",rest_type=\"Real\")"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Make a copy of the .csv file with results, where 'null' values are empty cells "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**For .csvt**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 69,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Define path to the .csv files\n",
- "afile=outfile+'t'\n",
- "pathtofile,extension=os.path.splitext(afile)\n",
- "bfile=pathtofile+\"_blanknull\"+extension\n",
- "# Make copy of the file\n",
- "shutil.copy2(afile,bfile)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**For .csv**"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 70,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "# Define path to the .csv files\n",
- "afile=outfile\n",
- "pathtofile,extension=os.path.splitext(afile)\n",
- "outfile_withoutnull=pathtofile+\"_blanknull\"+extension"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 71,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import csv\n",
- "# Create a copy by removing the 'NULL' values\n",
- "reader=csv.reader(open(afile,'r'),delimiter=\"|\")\n",
- "writer=csv.writer(open(outfile_withoutnull,'w'),delimiter=\"|\")\n",
- "for row in reader:\n",
- " newline=[]\n",
- " [newline.append(x) if x != \"NULL\" else newline.append(\"\") for x in row]\n",
- " writer.writerow(newline)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Check if all the lines have the same number of items"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 72,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "#### Function that check if rows of a .csv file have the same number of items than number of column in the first line (header)\n",
- "### If rows's lenght are identical, the function return 0. If not, it return a list containing the index number of row(s) that failed\n",
- "### The index is starting with value 1 for the first line of data (the header row is indexed 0)\n",
- "# 'csvfile' wait for the complete path (string) to the csvfile to be checked\n",
- "# 'separator' wait for the character used as separator in the .csv file (string)\n",
- "# 'allowemptycell' wait for a boolean value (True, False) depending if a empty cell should not be considered as a problem in the file\n",
- "\n",
- "def check_lenght_row(csvfile,separator,allowemptycell=True):\n",
- " listofunequalrow=[]\n",
- " afile=open(csvfile,'r')\n",
- " header=afile.next() # Save header row and go to the next one\n",
- " nb_item_control=len(header.split(separator))\n",
- " for x,row in enumerate(afile,1): # Start counting at \"1\" because header is already skipped\n",
- " row_items=row.split(separator)\n",
- " if len(row_items) != nb_item_control: # Check it number of items is identical than the number of items in the header\n",
- " listofunequalrow.append(x)\n",
- " if not allowemptycell:\n",
- " if \"\" in row_items:\n",
- " listofunequalrow.append(x)\n",
- " listofunequalrow=list(set(listofunequalrow)) # Recreate a list with uniques values from the original list\n",
- " if len(listofunequalrow)>0:\n",
- " return listofunequalrow # Return a list of indexes for line whose length is not equal to the header\n",
- " else:\n",
- " return 0"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 73,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "The csv looks good.\n"
- ]
- }
- ],
- "source": [
- "# Check number of row in the .csv file\n",
- "fout=check_lenght_row(outfile_withoutnull,\";\",allowemptycell=True)\n",
- "if fout>0:\n",
- " print \"Rows in csv do not have the same lenght. Please check the following row(s) index(es).\"\n",
- " print \"/n\".join(fout)\n",
- "else:\n",
- " print \"The csv looks good.\""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "collapsed": true
- },
- "source": [
- "## Replace current delimiter by ';'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 74,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import csv\n",
- "reader=csv.reader(open(outfile,'r'),delimiter=\"|\")\n",
- "newfile=[]\n",
- "for row in reader:\n",
- " newline=[]\n",
- " [newline.append(x) for x in row]\n",
- " newfile.append(newline)\n",
- "writer=csv.writer(open(outfile,'w'),delimiter=\";\")\n",
- "writer.writerows(newfile)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 75,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import csv\n",
- "reader=csv.reader(open(outfile+'t','r'),delimiter=\"|\")\n",
- "newfile=[]\n",
- "for row in reader:\n",
- " newline=[]\n",
- " [newline.append(x) for x in row]\n",
- " newfile.append(newline)\n",
- "writer=csv.writer(open(outfile+'t','w'),delimiter=\";\")\n",
- "writer.writerows(newfile)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 76,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import csv\n",
- "reader=csv.reader(open(outfile_withoutnull,'r'),delimiter=\"|\")\n",
- "newfile=[]\n",
- "for row in reader:\n",
- " newline=[]\n",
- " [newline.append(x) for x in row]\n",
- " newfile.append(newline)\n",
- "writer=csv.writer(open(outfile_withoutnull,'w'),delimiter=\";\")\n",
- "writer.writerows(newfile)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 77,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": [
- "import csv\n",
- "reader=csv.reader(open(outfile_withoutnull+'t','r'),delimiter=\"|\")\n",
- "newfile=[]\n",
- "for row in reader:\n",
- " newline=[]\n",
- " [newline.append(x) for x in row]\n",
- " newfile.append(newline)\n",
- "writer=csv.writer(open(outfile_withoutnull+'t','w'),delimiter=\";\")\n",
- "writer.writerows(newfile)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Visual check of the table (display the .csv using pandas)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 78,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
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586 rows × 117 columns
\n",
- "