## Example script that downloads data from Google Earth Engine using the python API

## MODIS MOD09GA data is processed to extract the MOD09 cloud flag and calculate monthly cloud frequency

## import some libraries

import ee

from ee import mapclient

import ee.mapclient 

import datetime

import wget

import os

from subprocess import call

#import logging

#logging.basicConfig()

## set working directory (where files will be downloaded)

os.chdir('/mnt/data2/projects/cloud/mod09')

MY_SERVICE_ACCOUNT = '511722844190@developer.gserviceaccount.com'  # replace with your service account

MY_PRIVATE_KEY_FILE = '/home/adamw/EarthEngine-privatekey.p12'       # replace with you private key file path

#MY_SERVICE_ACCOUNT = '205878743334-4mrtqgu0n5rnsv1vanrvv6atqk6vu8am@developer.gserviceaccount.com'

#MY_PRIVATE_KEY_FILE = '/home/adamw/EarthEngine_Jeremy-privatekey.p12'

ee.Initialize(ee.ServiceAccountCredentials(MY_SERVICE_ACCOUNT, MY_PRIVATE_KEY_FILE))

## set map center to speed up viewing

#ee.mapclient.centerMap(-121.767, 46.852, 11)

#///////////////////////////////////

#// Function to extract cloud flags

def getmod09(img): return(img.select(['state_1km']).expression("((b(0)/1024)%2)>0.5")); 

# added the >0.5 because some values are coming out >1.  Need to look into this further as they should be bounded 0-1...

#// Date ranges

yearstart=2000

yearstop=2012

monthstart=1

monthstop=12

#////////////////////////////////////////////////////

# Loop through months and get monthly % missing data

## set a year-month if you don't want to run the loop (for testing)

#year=2001

#month=2

#r=1

## define the regions to be processed

regions=['[[-180, -60], [-180, 0], [0, 0], [0, -60]]',  # SW

         '[[-180, 0], [-180, 90], [0, 90], [0, 0]]',    # NW

         '[[0, 0], [0, 90], [180, 90], [180, 0]]',      # NE

         '[[0, 0], [0, -60], [180, -60], [180, 0]]']    # SE

## name the regions (these names will be used in the file names

## must be same length as regions list above

rnames=['SW','NW','NE','SE']

## Loop over regions, years, months to generate monthly timeseries

for r in range(0,len(regions)):                                    # loop over regions

  for year in range(yearstart,yearstop+1):              # loop over years

    for month in range(monthstart,monthstop+1):         # loop over months

      print('Processing '+rnames[r]+"_"+str(year)+'_'+str(month))

      # output filename

      filename='mod09_'+rnames[r]+"_"+str(year)+"_"+str(month)

      unzippedfilename='mod09_'+rnames[r]+"_"+str(year)+"_"+str(month)+".MOD09_"+str(year)+"_"+str(month)+".tif"

      # Check if file already exists and continue if so...

      if(os.path.exists(unzippedfilename)):

        print("File exists:"+filename)

        continue

      # MOD09 internal cloud flag for this year-month

      # to filter by a date range:  filterDate(datetime.datetime(yearstart,monthstart,1),datetime.datetime(yearstop,monthstop,31))

      mod09 = ee.ImageCollection("MOD09GA").filter(ee.Filter.calendarRange(year,year,"year")).filter(ee.Filter.calendarRange(month,month,"month")).map(getmod09);

#      myd09 = ee.ImageCollection("MYD09GA").filter(ee.Filter.calendarRange(year,year,"year")).filter(ee.Filter.calendarRange(month,month,"month")).map(getmod09);

      # calculate mean cloudiness (%), rename band, multiply by 100, and convert to integer

      mod09a=mod09.mean().select([0], ['MOD09_'+str(year)+'_'+str(month)]).multiply(ee.Image(100)).byte();

#      myd09a=myd09.mean().select([0], ['MYD09_'+str(year)+'_'+str(month)]).multiply(ee.Image(100)).byte();

```

# Next few lines for testing only

# print info to confirm there is data

mod09a.getInfo()

myd09a.getInfo()

# add to plot to confirm it's working

ee.mapclient.addToMap(mod09a, {'range': '0,100'}, 'MOD09')

ee.mapclient.addToMap(myd09a, {'range': '0,100'}, 'MOD09')

```

      # build the URL and name the object (so that when it's unzipped we know what it is!)

      path =mod09a.getDownloadUrl({

          'name': filename,  # name the file (otherwise it will be a uninterpretable hash)

          'scale': 1000,                              # resolution in meters

          'crs': 'EPSG:4326',                         # MODIS sinusoidal

          'region': regions[r]                        # region defined above

          });

      # Sometimes EE will serve a corrupt zipped file with no error

      # to check this, use a while loop that keeps going till there is an unzippable file.  

      # This has the potential for an infinite loop...

      while(not(os.path.exists(filename+".zip"))):

        # download with wget

        print("Downloading "+filename) 

        wget.download(path)

        # try to unzip it

        print("Unzipping "+filename)

        zipstatus=call("unzip "+filename+".zip",shell=True)

         # if file doesn't exists or it didn't unzip, remove it and try again      

        if(zipstatus==9):

          print("ERROR: "+filename+" unzip-able")

          os.remove(filename)

print 'Finished'