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melt_pond_processing_weekly.py~
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melt_pond_processing_weekly.py~
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#! /usr/bin/env python
# run melt_pond_processing_weekly.py
# python melt_pond_processing_weekly.py
from pylab import *
from scipy import *
from osgeo.gdalconst import *
from osgeo import gdal
from gmt_tools import *
from sattools import *
import sys,pipes,struct,os,glob,fnmatch,pickle
#from mpl_toolkits.basemap import NetCDFFile #laeuft so auf so snow
from netCDF4 import Dataset as NetCDFFile # for local runs
from scipy.interpolate import *
from scipy.ndimage import *
import time
from ffnet import ffnet,mlgraph
import networkx
from scipy.interpolate import *
import scipy.io as io
import scipy.optimize as opti
from mpl_toolkits.basemap import Basemap
import scipy.ndimage as nd
#READ FIRST:
#before you start, you need to go through the following steps:
# 1. download MODIS weekly *.hdf files in a specific directory
# 2. cp the files 'execute_reproj_via_shell.sh' and 'modis_hdf2tif_polster_wgs84.sh' in the same directory and adjust pathes in the 'execute_reproj_via_shell.sh' file
# 3. apply 'execute_reproj_via_shell.sh' with the comand sh execute_reproj_via_shell.sh
# 4. Change Directories in this program
#run on snow
####DEFINE FOLDERS####
#satellite data folder
#folder='/scratch/clisap/seaice/MODIS/2012_weekly/'
#workfolder=folder+'processed/'
#tmpfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/tmp/'
#Productfolder
#prodfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/2012_weekly/'
####run local
####DEFINE FOLDERS####
#satellite data folder
folder='/home/u241127/data/modis/weekly/'
workfolder=folder+'processed/'
tmpfolder='/home/u241127/tmp/'
NNfolder='/home/u241127/data/NN/'
#Productfolder
prodfolder='/home/u241127/MELT_PONDS/PRODUCTS/2011_weekly/'
year='2011'
####FUNCTIONS#####
def read_dataset(folder):
files=glob.glob(folder+'/*.tif')
dataset={}
for fn in files:
band=fn[-26:-13]
dataset[band] = gdal.Open(fn)
return dataset
def read_MOD(dataset):
print('read bands 3412...')
B={}
B={'3':array(dataset['_sur_refl_b01'].ReadAsArray(),dtype=float32),\
'4':array(dataset['_sur_refl_b02'].ReadAsArray(),dtype=float32),\
'1':array(dataset['_sur_refl_b03'].ReadAsArray(),dtype=float32),\
'2':array(dataset['_sur_refl_b04'].ReadAsArray(),dtype=float32)}
band=B.keys
#scaling of reflectances
for i in band():
print('scale band '+i)
B[i]=B[i]*0.0001
B[i][B[i]==-28672]=NaN
B[i][B[i]>=1.0]=nan
B[i][B[i]<=0.0]=nan
bands={}
for i in band():
bands[i]=B[i]
return bands
def read_MOD_FLAG(dataset):
print('read flags...')
B={}
B={'L':array(dataset['fl_state_500m'].ReadAsArray())}
band=B.keys
bands={}
for i in band():
bands[i]=B[i]
return bands
def find_cut_area_coord(MY,MX,lon_y,lat_x,f):
"""find the best fitting position of a coordinate pair in an image
MY: longitude image array
MX: latitude image
lon_0, lat_0: coordinates of desired position
f: +- amount of pixel around the centercoordinate"""
for index, item in enumerate(MX):
if item > lat_x and item < lat_x+1:
ix=index
ix_value=item
#print(index,item)
for index, item in enumerate(MY):
if item > lon_y and item < lon_y+1:
iy=index
iy_value=item
#print(index,item)
X0=ix-f
X2=ix+f
Y0=iy-f
Y2=iy+f
return X0,X2,Y0,Y2
def JulDay2Date(year,n):
import datetime
d = datetime.date(year, 1, 1) + datetime.timedelta(n - 1)
month=d.month
day=d.day
return month, day
########START
#######read_MODIS2grd
metalist = glob.glob(folder+'A20*/')
print metalist
cmd('rm -r '+folder+'*v03')
for fn in metalist:
foldername1=fn[-16:]
folderyear=foldername1[1:5]
folderday=foldername1[5:8]
foldertile=foldername1[9:15]
foldername2=folder+'processed/'+folderyear+'_'+folderday+'_'+foldertile
if not os.path.exists(foldername2):
print('grd doesnot exist - start processing of '+fn)
year=fn[-15:-11]
julday=fn[-11:-8]
tile=fn[-7:-1]
directory=year+'_'+julday+'_'+tile+'/'
dataset = read_dataset(fn)
MOD=read_MOD(dataset)
B1,B2,B3,B4=MOD['1'],MOD['2'],MOD['3'],MOD['4']
B1[isnan(B1)==True]=0
B2[isnan(B2)==True]=0
B3[isnan(B3)==True]=0
B4[isnan(B4)==True]=0
FL=read_MOD_FLAG(dataset)
bflag=FL['L']
cloud_mask=[]
land_mask=[]
print('convert cloud and land flags....')
for n in bflag.flatten():
flag=binary_repr(n,width=16)
#cloudmask #flags von hinten zaehlen!!!!-->little endian
if flag[15]=='0' and flag[14]=='0' and flag[13]=='0':
f=0 #clear
else:
f=1 #cloudy if flag[0]=='1':
cloud_mask.append(f) #1->clear, 0->cloudy
#landmask
if flag[12]=='0' and flag[11]=='0' and flag[10]=='1' or flag[12]=='0' and flag[11]=='1' and flag[10]=='0' or flag[12]=='1' and flag[11]=='0' and flag[10]=='1' or flag[12]=='1' and flag[11]=='0' and flag[10]=='0':
l=1 #land
else:
l=0 #sea
land_mask.append(l) #1->sea, 0->land
clouds=array(cloud_mask).reshape(bflag.shape)
land=array(land_mask).reshape(bflag.shape)
maske=clouds+land
maske[maske==2]=1
maske=abs(maske-1)
#dtype muss float32 sein!!!!!!!!!:
m=array(maske,dtype=float32)
###masking
B1=B1*m
B2=B2*m
B3=B3*m
B4=B4*m
#all zeros to nans:
B1[B1==0.]=nan
B2[B2==0.]=nan
B3[B3==0.]=nan
B4[B4==0.]=nan
#Koordinaten und Pixelgroesse zum spaeteren gridden werden gelesen
print 'get coordinates'
geotransform=dataset['_sur_refl_b01'].GetGeoTransform()
[X, Y]= meshgrid(arange(B1.shape[1],dtype=float32), arange(B1.shape[0],dtype=float32))
X_polar = (geotransform[0]+geotransform[1]*X+geotransform[2]*Y)/1000#[:,::-1]
Y_polar = (geotransform[3]+geotransform[4]*X+geotransform[5]*Y)/1000#[:,::-1]
print '...done'
#creating filnames and dirs:
#folder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/MOD09/MOD09GA/'
os.system('mkdir -p '+folder+'processed/'+directory)
workfile=folder+'processed/'+directory+year+'_'+julday+'_'+tile
plotfile=workfile
out_file1=workfile+'_1.nc'
out_file2=workfile+'_2.nc'
out_file3=workfile+'_3.nc'
out_file4=workfile+'_4.nc'
tmpfile=workfile+'.gz'
mapfile=plotfile+'.ps'
ctabfile=plotfile+'.ctab'
print(' ')
print('_____GRIDDING MOD______')
G1={}
cs1=0.5#geotransform[1]/1000 #0.5 #500m
x0,y0,x2,y2=X_polar.max(),Y_polar.max(),X_polar.min(),Y_polar.min()
grid_par_neu(1,x0,y0,x2,y2,cs1,G1)
G1=makecpt(ctabfile,'gray',0.0,0.9,0.2,G1)
#check if grdfiles exist - if not process them
grdfiles=glob.glob(workfile+'*.nc')
filelist1=[out_file1,out_file2,out_file3,out_file4]
print(filelist1)
for i in range(len(filelist1)):
if not os.path.exists(filelist1[i]):
print('nc gibts noch nicht')
near_neighbor(X_polar,Y_polar,B1,out_file1,G1)
near_neighbor(X_polar,Y_polar,B2,out_file2,G1)
near_neighbor(X_polar,Y_polar,B3,out_file3,G1)
near_neighbor(X_polar,Y_polar,B4,out_file4,G1)
#prepare headline:
titlestr='MOD09 - surface refl: '+year+' '+julday+' tile: '+tile
pos_x,pos_y=str(x2), str(y0+50)
cmd('GMT gmtset ELLIPSOID WGS-84 OBLIQUE_ANOTATION 1 PAPER_MEDIA A4+ PAGE_ORIENTATION portrait PSIMAGE_FORMAT hex PLOT_DEGREE_FORMAT ddd:mm:ss COLOR_NAN 255/255/255')
cmd('GMT grdimage '+out_file1+' '+opts(G1,['Rx','Jx','Bx','C'])+' -Y3.5 -K -V> '+mapfile)
cmd('GMT pscoast '+opts(G1,['Rll','Bll','coast'])+' -O -V -K>> '+mapfile)
cmd('GMT echo '+pos_x+' '+pos_y+' 18 0 0 0 "'+titlestr+'" | pstext '+opts(G1,['Rx','Jx','N'])+' -V -O >> '+mapfile)
#cmd('gv '+mapfile+'&')
else:
print(fn+'was already processed - skip processing')
####clean memory
#del X,Y,X_polar,Y_polar,dataset,MOD,B1,B2,B3,B4,FL,bflag,cloud_mask,land_mask,clouds,land,maske,m
#print('Schleife zuende')
for fn in metalist:
foldername1=fn[-16:]
folderyear=foldername1[1:5]
folderday=foldername1[5:8]
foldertile=foldername1[9:15]
foldername=folder+'processed/'+folderyear+'_'+folderday+'_'+foldertile
year=fn[-15:-11]
julday=fn[-11:-8]
tile=fn[-7:-1]
#####MOSAIC
print('MOSAIKE WERDEN GEBAUT')
metalist_m=glob.glob(workfolder+year+'*/')
print(metalist_m)
daylist=[]
for day in metalist_m:
d=day[-11:-8]
daylist.append(d)
days=list(sorted(set(daylist)))
#####
#####
#days=['147', '148', '149', '150', '151', '152', '153', '154', '155', '156', '157', '158']
#days=['249']
print(days)
#############
#BLENDFILE
###############
#for fn in metalist_m:
#if not os.path.exists(foldername):
#print('grd doesnot exist - start processing of '+fn)
for b in range(4):
band=b+1
print('working on band '+str(band))
for d in days:
os.system('mkdir '+workfolder+year+'_'+str(d)+'_mosaic/')
workfolder_mosaic=workfolder+year+'_'+str(d)+'_mosaic/'
workfile=workfolder_mosaic+year+'_'+str(d)+'_mosaic'
blendfile=workfile+str(band)+'.job'
blendoutfile=workfile+str(band)+'.nc'
ctabfile=workfile+str(band)+'.ctab'
mapfile=workfile+str(band)+'.ps'
piclist = glob.glob(workfolder+year+'_'+str(d)+'*/*'+str(band)+'.nc')
print(piclist)
mosaic = file(blendfile,'w')
for fn in piclist:
print('now working on '+fn)
file1=fn
#read Netcdfs and extract Bands
mb1=NetCDFFile(file1)
print('read nc')
MX=array(mb1.variables['x'][:])
MY=array(mb1.variables['y'][:])
xmin = min(MX)
xmax = max(MX)
ymin = min(MY)
ymax = max(MY)
mosaic.write(fn+' -R'+str(xmin)+'/'+str(xmax)+'/'+str(ymin)+'/'+str(ymax)+' 1'+'\n')
mosaic.close()
#print('######')
print(file(blendfile).read())
#print('######')
G={}
cs=0.5 #500m
region='Arc'
grid_par_reg(region,cs,G)
G=makecpt(ctabfile,'gray',0.0,0.9,0.2,G)
cmd('GMT gmtset OBLIQUE_ANOTATION 1 PAPER_MEDIA A4+ PAGE_ORIENTATION portrait PLOT_DEGREE_FORMAT ddd:mm:ss COLOR_NAN 255/255/255')
cmd('GMT grdblend '+blendfile+' -G'+blendoutfile+' '+opts(G,['Rx','I'])+' -V > '+mapfile)
cmd('GMT grdimage '+blendoutfile+' '+opts(G,['Rx','Jx','Bx','C'])+' -P -K -V>> '+mapfile)
cmd('GMT psscale -D8c/-0.5c/12c/0.4ch -C'+ctabfile+' -O -B0.1 -V -K >> '+mapfile)
cmd('GMT pscoast '+opts(G,['Rll','Bll','coast'])+' -G128/128/128 -O -V -K >> '+mapfile)
cmd('GMT echo -2000 6500 18 0 0 0 "Overview B'+str(band)+' Day '+str(d)+'" | pstext '+opts(G,['Rx','Jx','N'])+' -V -O >> '+mapfile)
#cmd('gv '+mapfile+'&')
#aufraeumen
cmd('mkdir '+workfolder+'tiles')
cmd('mv '+workfolder+' 20*_h* '+workfolder+'tiles')
"""
####Neural Net apply
print('NEURONALES NETZ WIRD AKTIVIERT')
############
##METALIST##
############
metalist_n = glob.glob(workfolder+'*_mosaic/')
print(metalist_n)
for folder in metalist_n:
print folder
jahr=folder[-16:-12]
julday=folder[-11:-8]
date=jahr+'_'+julday
workfile=folder+date+'_mosaic'
print('work on '+workfile)
if not os.path.exists(prodfolder+date+'/'+date+'_ow.data'):
print date+' does not exist'
file1,file2,file4=workfile+'1.nc',workfile+'2.nc',workfile+'4.nc'
#read Netcdfs and extract Bands
mb1,mb2,mb4=NetCDFFile(file1),NetCDFFile(file2),NetCDFFile(file4)
print('read nc')
#MX=array(mb1.variables['x'][:])
#MY=array(mb1.variables['y'][:])
MB1=array(mb1.variables['z'][:,:])
MB2=array(mb2.variables['z'][:,:])
MB4=array(mb4.variables['z'][:,:])
titlestr='MODIS mosaic- '+date
MB1[MB1==0.]=NaN
MB2[MB2==0.]=NaN
MB4[MB4==0.]=NaN
BAND1=MB1.flatten()
BAND2=MB2.flatten()
BAND4=MB4.flatten()
R=array([BAND1,BAND2,BAND4])
print('...done')
print 'loading NN'
#net=pickle.load(open(tmpfolder+'neural_net_TD.data','r'))
#net=pickle.load(open(tmpfolder+'neural_net_TDneu3_only_nomp.data','r'))
net=pickle.load(open(tmpfolder+'neural_net_TDneu.data','r'))
net=pickle.load(open(NNfolder+'net5neu.data','r'))
#net=pickle.load(open(tmpfolder+'neural_net_my_sib_can_fram_MP_valuesTSCHUDI','r')) #ergebnisse schlecht
###net=pickle.load(open(tmpfolder+'neural_net_my_sib_can_fram','r')) #GUTE RESULTS
#zeitnahme start
start = time.clock()
print('...done')
print 'Applying NN'
Z_neural=net(R.transpose()).transpose()
#zeitnahme ende
stend = time.clock()
print('dauer: '+str(stend-start))
mp=Z_neural[0].reshape((MB1.shape))
snow=Z_neural[1].reshape((MB1.shape))
ow=Z_neural[2].reshape((MB1.shape))
print('...done')
print('pickle data')
cmd('mkdir '+prodfolder+date)
pickle.dump(mp,open(prodfolder+date+'/'+date+'_mp.data','w'))
print('mp pickled')
pickle.dump(snow,open(prodfolder+date+'/'+date+'_snow.data','w'))
print('snow pickled')
pickle.dump(ow,open(prodfolder+date+'/'+date+'_ow.data','w'))
print('ow pickeld......done')
########regrid
#prodfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/2012_June_daily/'
#prodfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/KARA/'
#prodfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/GREENLAND/'
############
print('REGRID')
metalist = glob.glob(prodfolder+'20*/*mp.data')
print(metalist)
for dataset in metalist:
print dataset
#####select date:
date=dataset[-16:-8]#'2008_169'
year=int(date[0:4])
n=int(date[5:])
print date, n, year
month, day = JulDay2Date(year,n)
month=str(month)
day=str(day)
year=str(year)
DATE=day+'.'+month+'.'+year
print DATE
####---snow1:
workfolder=prodfolder+date+'/'
tmpfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/tmp/'
#plotfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/daily/plots/'
plotfolder=folder+'plots/'
jahr=date[0:4]
julday=date[5:8]
titlestr='MODIS MP - '+DATE+'('+str(n)+')'
#check this:!!!
if not os.path.exists(workfolder+date+'_mp_125.nc' or workfolder+date+'_mp_25.nc' or workfolder+date+'_mp_05.nc'):
print('need to load all objects')
print('load mp object')
mp=pickle.load(open(workfolder+date+'_mp.data','r'))
print('load ice object')
sn=pickle.load(open(workfolder+date+'_snow.data','r'))
print('load ow object')
ow=pickle.load(open(workfolder+date+'_ow.data','r'))
print('...done')
print('mpset ('+workfolder+date+'_mp_*.nc) doesnot exist - start processing of '+dataset)
mp=array(mp,dtype=float32)
print('mp shape:'+str(mp.shape))
cs_sm=0.5
region='Arc'
XYs=XYgrid(region,cs_sm)
X=array(XYs[0],dtype=float32)
Y=array(XYs[1],dtype=float32)
i=isfinite(mp)
mpi=mp[i]
owi=ow[i]
sni=sn[i]
Xi=X[i]
Yi=Y[i]
FILENAMEmp=workfolder+date+'_mp.xyz'
if not os.path.exists(workfolder+date+'_mp.xyz'):
print('write table (xyz-file)')
write_table(FILENAMEmp,Xi,Yi,mpi)
FILENAMEow=workfolder+date+'_ow.xyz'
if not os.path.exists(workfolder+date+'_ow.xyz'):
print('write table (xyz-file)')
write_table(FILENAMEow,Xi,Yi,owi)
FILENAMEsn=workfolder+date+'_sn.xyz'
if not os.path.exists(workfolder+date+'_sn.xyz'):
print('write table (xyz-file)')
write_table(FILENAMEsn,Xi,Yi,sni)
ctabfilemp=folder+'mp.ctab' # makecpt -Cjet -D -Z -T0.0/0.4/0.1 > mp.ctab
ctabfilestdev=folder+'stdev.ctab'
pos_x,pos_y=str(-3850), str(6350)
if not os.path.exists(workfolder+date+'_mp_05.nc'):
print 'start processind 0.5 km grid'
#create 0.5 grid
#plotfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/daily/plots/'
plotfolder=folder+'plots/'
outfile_mp_05=workfolder+date+'_mp_05.nc'
mapfile05=plotfolder+date+'_mp_05.ps'
G={}
cs_sm=0.5
region='Arc'
grid_par_reg(region,cs_sm,G)
titlestr05=titlestr+' mp 0.5 km grid'
xyz2grd(Xi,Yi,mpi,outfile_mp_05,G)
#check plot
#scale to 12.5 km
titlestr125=titlestr+' 12.5 km'
if not os.path.exists(workfolder+date+'_mp_125.nc'):
print 'start processing 12.5 km mp grid'
G={}
cs=12.5
region='Arc'
grid_par_reg(region,cs,G)
titlestr125=titlestr+' mp 12.5 km grid'
titlestr125SD=titlestr+' SD 12.5 km grid'
titlestr125W=titlestr+' Weight 12.5 km grid'
outfile=workfolder+date+'_mp_125.xyz'
MEANoutfile_mp125=workfolder+date+'_mp_125.nc'
os.system('GMT blockmean '+FILENAMEmp+opts(G,['Rx','I'])+' -Wo -Eslh -V > '+outfile)
os.system('GMT xyz2grd '+outfile+opts(G,['Rx','I'])+' -V -G'+MEANoutfile_mp125)
MEANfile=workfolder+date+'_mp_125MEAN.xyz'
SDfile=workfolder+date+'_mp_125SD.xyz'
SDoutfile_mp125=workfolder+date+'_mp_125SD.nc'
MEANmapfile=plotfolder+date+'_mp_125.ps'
SDmapfile=plotfolder+date+'_mp_125SD.ps'
WEIGHTfile=workfolder+date+'_mp_125WEIGHT.xyz'
WEIGHToutfile_mp125=workfolder+date+'_mp_125WEIGHT.nc'
WEIGHTmapfile=plotfolder+date+'_mp_125WEIGHT.ps'
ctabfile25weight=folder+'25weight.ctab'
cmd('GMT gmtconvert '+outfile+' -F0,1,3 -V > '+SDfile)
cmd('GMT xyz2grd '+SDfile+opts(G,['Rx','I'])+' -V -G'+SDoutfile_mp125)
cmd('GMT gmtconvert '+outfile+' -F0,1,6 -V > '+WEIGHTfile)
cmd('GMT xyz2grd '+WEIGHTfile+opts(G,['Rx','I'])+' -V -G'+WEIGHToutfile_mp125)
#################ow concentration####################
if not os.path.exists(workfolder+date+'_ow_05.nc'):
print 'start processind 0.5 km grid'
#create 0.5 grid
#plotfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/daily/plots/'
plotfolder=folder+'plots/'
outfile_ow_05=workfolder+date+'_ow_05.nc'
mapfile05=plotfolder+date+'_ow_05.ps'
G={}
cs_sm=0.5
region='Arc'
grid_par_reg(region,cs_sm,G)
titlestr05=titlestr+' ow 0.5 km grid'
xyz2grd(Xi,Yi,owi,outfile_ow_05,G)
#check plot
if not os.path.exists(workfolder+date+'_ow_125.nc'):
print 'start processing 12.5 km ow grid'
#scale to 12.5 km
outfile=workfolder+date+'_ow_125k.xyz'
outfile_ow125=workfolder+date+'_ow_125.nc'
mapfile=plotfolder+date+'_ow_125.ps'
cs=12.5
G={}
grid_par_reg(region,cs,G)
titlestr125=titlestr+' 12.5 km'
cmd('GMT gmtset OBLIQUE_ANOTATION 1 PAPER_MEDIA A4+ PAGE_ORIENTATION portrait PLOT_DEGREE_FORMAT ddd:mm:ss -V')
cmd('GMT gmtset COLOR_NAN 200')
os.system('GMT blockmean '+FILENAMEow+opts(G,['Rx','I'])+' -Eslh -V > '+outfile)
os.system('GMT xyz2grd '+outfile+opts(G,['Rx','I'])+' -V -G'+outfile_ow125)
#################sn concentration####################
if not os.path.exists(workfolder+date+'_sn_05.nc'):
print 'start processind 0.5 km grid'
#create 0.5 grid
#plotfolder='/scratch/clisap/seaice/OWN_PRODUCTS/MELT_PONDS/PRODUCTS/daily/plots/'
plotfolder=folder+'plots/'
outfile_sn_05=workfolder+date+'_sn_05.nc'
mapfile05=plotfolder+date+'_sn_05.ps'
G={}
cs_sm=0.5
region='Arc'
grid_par_reg(region,cs_sm,G)
titlestr05=titlestr+' ow 0.5 km grid'
xyz2grd(Xi,Yi,sni,outfile_sn_05,G)
#check plot
if not os.path.exists(workfolder+date+'_sn_125.nc'):
print 'start processing 12.5 km sn grid'
#scale to 12.5 km
outfile=workfolder+date+'_sn_125k.xyz'
outfile_ow125=workfolder+date+'_sn_125.nc'
mapfile=plotfolder+date+'_sn_125.ps'
cs=12.5
G={}
grid_par_reg(region,cs,G)
titlestr125=titlestr+' 12.5 km'
cmd('GMT gmtset OBLIQUE_ANOTATION 1 PAPER_MEDIA A4+ PAGE_ORIENTATION portrait PLOT_DEGREE_FORMAT ddd:mm:ss -V')
cmd('GMT gmtset COLOR_NAN 200')
os.system('GMT blockmean '+FILENAMEsn+opts(G,['Rx','I'])+' -Eslh -V > '+outfile)
os.system('GMT xyz2grd '+outfile+opts(G,['Rx','I'])+' -V -G'+outfile_ow125)
#############ICE CONCENTRATION###################
##### ice=1-ow
##run ice_konz_regrid.py
##python ice_konz_regrid.py
##check here:
#if not os.path.exists(workfolder+date+'_ice_05.nc'):
#print('ice concentration set doesnot exist - start processing of '+dataset)
#ice=1-array(ow,dtype=float32) # ice=1-ow
#print('ice shape:'+str(ice.shape))
#region='Arc'
#cs_sm=0.5
#XYs=XYgrid(region,cs_sm)
#X=array(XYs[0],dtype=float32)
#Y=array(XYs[1],dtype=float32)
#i=isfinite(ice)
#icei=ice[i]
#Xi=X[i]
#Yi=Y[i]
#pos_x,pos_y=str(-3850), str(6350)
#ctabfileice=folder+'ice.ctab'
#titlestr='MODIS ICE CONCENTRATION - '+DATE+'('+str(n)+')'
#FILENAME=workfolder+date+'_ice.xyz'
#write_table(FILENAME,Xi,Yi,icei)
#if not os.path.exists(workfolder+date+'_ice_25.nc'):
#print 'start processing 25 km ice grid'
##scale to 25 km
#outfile=workfolder+date+'_ice_25k.xyz'
#outfile_ice25=workfolder+date+'_ice_25.nc'
#mapfile=plotfolder+date+'_ice_25.ps'
#cs=25
#G={}
#grid_par_reg(region,cs,G)
##prepare headline:
#titlestr25=titlestr+' 25 km'
#cmd('gmtset OBLIQUE_ANOTATION 1 PAPER_MEDIA A4+ PAGE_ORIENTATION portrait PLOT_DEGREE_FORMAT ddd:mm:ss -V')
#cmd('gmtset COLOR_NAN 200')
#os.system('blockmean '+FILENAME+opts(G,['Rx','I'])+' -Eslh -V > '+outfile)
#os.system('xyz2grd '+outfile+opts(G,['Rx','I'])+' -V -G'+outfile_ice25)
#if not os.path.exists(workfolder+date+'_ice_125.nc'):
#print 'start processing 12.5 km ice grid'
##scale to 12.5 km
#outfile=workfolder+date+'_ice_125k.xyz'
#outfile_ice125=workfolder+date+'_ice_125.nc'
#mapfile=plotfolder+date+'_ice_125.ps'
#cs=12.5
#G={}
#grid_par_reg(region,cs,G)
#titlestr125=titlestr+' 12.5 km'
#cmd('gmtset OBLIQUE_ANOTATION 1 PAPER_MEDIA A4+ PAGE_ORIENTATION portrait PLOT_DEGREE_FORMAT ddd:mm:ss -V')
#cmd('gmtset COLOR_NAN 200')
#os.system('blockmean '+FILENAME+opts(G,['Rx','I'])+' -Eslh -V > '+outfile)
#os.system('xyz2grd '+outfile+opts(G,['Rx','I'])+' -V -G'+outfile_ice125)