from __future__ import division 
from pycdf import *
from numpy import *
from matplotlib import *

startY=01
endY=03
startM=01
endM=12

yvals=endY-startY+1
mvals=endM-startM+1

columns=-1

totalCloudFraction=zeros((yvals*mvals), float)

for y in range(startY,endY+1):
	for m in range(startM,endM+1):
		if(m==1):
			month='January'
		elif(m==2):
			month='February'
		elif(m==3):
			month='March'
		elif(m==4):
			month='April'
		elif(m==5):
			month='May'
		elif(m==6):
			month='June'
		elif(m==7):
			month='July'
		elif(m==8):
			month='August'
		elif(m==9):
			month='September'
		elif(m==10):
			month='October'
		elif(m==11):
			month='November'
		elif(m==12):
			month='December'

		if(y<10  and m<10):
			filename='/home/csuplinski/netcdf_data/Trend_14_y0'+str(y)+'m0'+str(m)+'_'+month+'_9090.nc'
		elif(y>9  and m<10):
			filename='/home/csuplinski/netcdf_data/Trend_14_y'+str(y)+'m0'+str(m)+'_'+month+'_9090.nc'
		elif(y<10 and  m>9):
			filename='/home/csuplinski/netcdf_data/Trend_14_y0'+str(y)+'m'+str(m)+'_'+month+'_9090.nc'
		else:
			filename='/home/csuplinski/netcdf_data/Trend_14_y'+str(y)+'m'+str(m)+'_'+month+'_9090.nc'

		
		columns=columns+1
		file=CDF(filename)
		totalLandPoints=file.var('pts_ea_land')
		totalLandPoints=totalLandPoints.get()
		totalLandPoints=totalLandPoints[0]
		print(totalLandPoints)
		cloudPoints=file.var('cldpts_ea_land')
		cloudPoints=cloudPoints.get()
		cloudPoints=cloudPoints[0]
		print(cloudPoints)
		totalCloudFraction[columns]=cloudPoints/float(totalLandPoints)


print(arange(size(totalCloudFraction))+1)
print(totalCloudFraction)
matplotlib.pyplot.plot(arange(size(totalCloudFraction))+1, totalCloudFraction)
matplotlib.pyplot.title('Total Cloud Fraction Data')
matplotlib.pyplot.xlabel('Time (in years - each year marker indicates January of that year)')
matplotlib.pyplot.ylabel('Total Cloud Fraction')
matplotlib.pyplot.xticks(12*arange(size(totalCloudFraction)/12)+1, arange(size(totalCloudFraction))+2001, rotation=17)