# -*- Mode: python -*-
### ===========================================================================
###
### Compute runoff weights.
### For LMDZ only. Not suitable for DYNAMICO
###
### ===========================================================================
##
##  Warning, to install, configure, run, use any of Olivier Marti's
##  software or to read the associated documentation you'll need at least
##  one (1) brain in a reasonably working order. Lack of this implement
##  will void any warranties (either express or implied).
##  O. Marti assumes no responsability for errors, omissions,
##  data loss, or any other consequences caused directly or indirectly by
##  the usage of his software by incorrectly or partially configured
##  personal.
##
# SVN information
__Author__   = "$Author$"
__Date__     = "$Date$"
__Revision__ = "$Revision$"
__Id__       = "$Id$"
__HeadURL__  = "$HeadURL$"
__SVN_Date__ = "$SVN_Date: $"
##

## Modules
import netCDF4
import numpy as np
import nemo
from scipy import ndimage
import sys, os, platform, argparse, textwrap, time

## Userful constants
zero    = np.dtype('float64').type(0.0)
zone    = np.dtype('float64').type(1.0)
epsfrac = np.dtype('float64').type(1.0E-10)
pi      = np.pi
rad     = pi/np.dtype('float64').type(180.0)  # Conversion from degrees to radian
ra      = np.dtype('float64').type(6371229.0) # Earth radius

## Functions
def geodist (plon1, plat1, plon2, plat2) :
      """Distance between two points (on sphere)"""
      zs = np.sin (rad*plat1) * np.sin (rad*plat2) +  np.cos (rad*plat1) * np.cos (rad*plat2) * np.cos(rad*(plon2-plon1))
      zs = np.maximum (-zone, np.minimum (zone, zs))
      geodist =  np.arccos (zs)
      return geodist

### ===== Reading command line parameters ==================================================
# Creating a parser
parser = argparse.ArgumentParser (
    description = """Compute calving weights""",
    epilog='-------- End of the help message --------')

# Adding arguments
parser.add_argument ('--oce'          , help='oce model name', type=str, default='eORCA1.2', choices=['ORCA2.3', 'eORCA1.2', 'eORCA025'] )
parser.add_argument ('--atm'          , help='atm model name', type=str, default='LMD9695'    )
parser.add_argument ('--atmCoastWidth', help='width of the coastal band in atmosphere (in grid points)', type=int, default=1 )
parser.add_argument ('--oceCoastWidth', help='width of the coastal band in ocean (in grid points)'     , type=int, default=2 )
parser.add_argument ('--atmQuantity'  , help='Quantity if atm provides quantities (m/s), Surfacic if atm provided flux (m/s/m2)'  , type=str, default='Quantity', choices=['Quantity', 'Surfacic'] )
parser.add_argument ('--oceQuantity'  , help='Quantity if oce requires quantities (ks/s), Surfacic if oce requires flux (m/s/m2)' , type=str, default='Surfacic', choices=['Quantity', 'Surfacic'] )
parser.add_argument ('--searchRadius' , help='max distance to connect a land point to an ocean point (in km)', type=float, default=600.0 )
parser.add_argument ('--grids' , help='grids file name', default='grids.nc' )
parser.add_argument ('--areas' , help='masks file name', default='areas.nc' )
parser.add_argument ('--masks' , help='areas file name', default='masks.nc' )
parser.add_argument ('--o2a'   , help='o2a file name'  , default='o2a.nc' )
parser.add_argument ('--output', help='output rmp file name', default='rmp_tlmd_to_torc_runoff_64bit.nc' )
parser.add_argument ('--fmt'   , help='NetCDF file format, using nco syntax', default='64bit', choices=['classic', 'netcdf3', '64bit', '64bit_data', '64bit_data', 'netcdf4', 'netcdf4_classsic'] )

# Parse command line
myargs = parser.parse_args()

#
grids = myargs.grids
areas = myargs.areas
masks = myargs.masks
o2a   = myargs.o2a

# Model Names
atm_Name = myargs.atm
oce_Name = myargs.oce
# Width of the coastal band (land points) in the atmopshere
atmCoastWidth = myargs.atmCoastWidth
# Width of the coastal band (ocean points) in the ocean 
oceCoastWidth = myargs.oceCoastWidth
searchRadius  = myargs.searchRadius * 1000.0 # From km to meters
# Netcdf format
if myargs.fmt == 'classic'         : FmtNetcdf = 'CLASSIC'
if myargs.fmt == 'netcdf3'         : FmtNetcdf = 'CLASSIC'
if myargs.fmt == '64bit'           : FmtNetcdf = 'NETCDF3_64BIT_OFFSET'
if myargs.fmt == '64bit_data'      : FmtNetcdf = 'NETCDF3_64BIT_DATA'
if myargs.fmt == '64bit_offset'    : FmtNetcdf = 'NETCDF3_64BIT_OFFSET'
if myargs.fmt == 'netcdf4'         : FmtNetcdf = 'NETCDF4'
if myargs.fmt == 'netcdf4_classic' : FmtNetcdf = 'NETCDF4_CLASSIC'

#
if atm_Name.find('LMD') >= 0 : atm_n = 'lmd' ; atmDomainType = 'rectilinear'
if atm_Name.find('ICO') >= 0 : atm_n = 'ico' ; atmDomainType = 'unstructured'

print ('atmQuantity : ' + str (myargs.atmQuantity) )
print ('oceQuantity : ' + str (myargs.oceQuantity) )
    
### Read coordinates of all models
###

diaFile    = netCDF4.Dataset ( o2a   )
gridFile   = netCDF4.Dataset ( grids )
areaFile   = netCDF4.Dataset ( areas )
maskFile   = netCDF4.Dataset ( masks )

o2aFrac             = diaFile ['OceFrac'][:].squeeze()
o2aFrac = np.where ( np.abs(o2aFrac) < 1E10, o2aFrac, 0.0)

(atm_nvertex, atm_jpj, atm_jpi) = gridFile['t'+atm_n+'.clo'][:].shape
atm_grid_size = atm_jpj*atm_jpi
atm_grid_rank = len(gridFile['t'+atm_n+'.lat'][:].shape)

atm_grid_center_lat = gridFile['t'+atm_n+'.lat'][:].ravel()
atm_grid_center_lon = gridFile['t'+atm_n+'.lon'][:].ravel()
atm_grid_corner_lat = np.reshape ( gridFile['t'+atm_n+'.cla'][:], (atm_nvertex, atm_grid_size) )
atm_grid_corner_lon = np.reshape ( gridFile['t'+atm_n+'.clo'][:], (atm_nvertex, atm_grid_size) )
atm_grid_area       = areaFile['t'+atm_n+'.srf'][:].ravel()
atm_grid_imask      = 1-maskFile['t'+atm_n+'.msk'][:].squeeze().ravel()
atm_grid_dims       = gridFile['t'+atm_n+'.lat'][:].shape

atm_perio = 0
atm_grid_pmask = atm_grid_imask
atm_address = np.arange(atm_jpj*atm_jpi)


(oce_nvertex, oce_jpj, oce_jpi) = gridFile['torc.cla'][:].shape ; jpon=oce_jpj*oce_jpj
oce_grid_size = oce_jpj*oce_jpi
oce_grid_rank = len(gridFile['torc.lat'][:].shape)

oce_grid_center_lat = gridFile['torc.lat'][:].ravel()
oce_grid_center_lon = gridFile['torc.lon'][:].ravel()
oce_grid_corner_lat = np.reshape( gridFile['torc.cla'][:], (oce_nvertex, oce_grid_size) )
oce_grid_corner_lon = np.reshape( gridFile['torc.clo'][:], (oce_nvertex, oce_grid_size) )
oce_grid_area       = areaFile['torc.srf'][:].ravel()
oce_grid_imask      = 1-maskFile['torc.msk'][:].ravel()
oce_grid_dims       = gridFile['torc.lat'][:].shape
if oce_jpi ==  182 : oce_perio = 4 # ORCA 2
if oce_jpi ==  362 : oce_perio = 6 # ORCA 1
if oce_jpi == 1442 : oce_perio = 6 # ORCA 025
oce_grid_pmask = nemo.lbc_mask (np.reshape(oce_grid_imask, (oce_jpj,oce_jpi)), 'T', oce_perio).ravel()
oce_address = np.arange(oce_jpj*oce_jpi)

## Fill closed sea with image processing library
oce_grid_imask2D = np.reshape(oce_grid_pmask,(oce_jpj,oce_jpi))
oce_grid_imask2D = nemo.lbc_mask ( 1-ndimage.binary_fill_holes (1-nemo.lbc(oce_grid_imask2D, nperio=oce_perio, cd_type='T')), nperio=oce_perio, cd_type='T' )
oce_grid_imask = oce_grid_imask2D.ravel()
## 
print ("Determination d'une bande cotiere ocean")

oceLand2D  = np.reshape ( np.where (oce_grid_pmask[:] < 0.5, True, False), (oce_jpj, oce_jpi) )
oceOcean2D = np.reshape ( np.where (oce_grid_pmask[:] > 0.5, True, False), (oce_jpj, oce_jpi) )

NNocean = 1+2*oceCoastWidth
oceOceanFiltered2D = ndimage.uniform_filter(oceOcean2D.astype(float), size=NNocean)
oceCoast2D = np.where (oceOceanFiltered2D<(1.0-0.5/(NNocean**2)),True,False) & oceOcean2D
oceCoast2D = nemo.lbc_mask (np.reshape(oceCoast2D,(oce_jpj,oce_jpi)), oce_perio, 'T').ravel()

oceOceanFiltered = oceOceanFiltered2D.ravel()
oceLand  = oceLand2D.ravel()
oceOcean = oceOcean2D.ravel()
oceCoast = oceCoast2D.ravel()

print ('Number of points in oceLand  : ' + str(oceLand.sum()) )
print ('Number of points in oceOcean : ' + str(oceOcean.sum()) )
print ('Number of points in oceCoast : ' + str(oceCoast.sum()) )

# Arrays with coastal points only
oceCoast_grid_center_lon = oce_grid_center_lon[oceCoast]
oceCoast_grid_center_lat = oce_grid_center_lat[oceCoast]
oceCoast_grid_area       = oce_grid_area      [oceCoast]
oceCoast_grid_imask      = oce_grid_imask     [oceCoast]
oceCoast_grid_pmask      = oce_grid_pmask     [oceCoast]
oceCoast_address         = oce_address        [oceCoast]

print ("Determination d'une bande cotiere atmosphere " )
atmLand      = np.where (o2aFrac[:] < epsfrac       , True, False)
atmLandFrac  = np.where (o2aFrac[:] < zone-epsfrac  , True, False)
atmFrac      = np.where (o2aFrac[:] > epsfrac       , True, False) & np.where (o2aFrac[:] < (zone-epsfrac), True, False)
atmOcean     = np.where (o2aFrac[:] < (zone-epsfrac), True, False)
atmOceanFrac = np.where (o2aFrac[:] > epsfrac       , True, False)

## La suite marche avec LMDZ seulement !!
if atmDomainType == 'rectilinear' :
    NNatm = 1+2*atmCoastWidth
    atmLand2D = np.reshape ( atmLand, ( atm_jpj, atm_jpi) )

    atmLandFiltered2D = ndimage.uniform_filter(atmLand2D.astype(float), size=NNatm)
    atmCoast2D = np.where (atmLandFiltered2D<(1.0-0.5/(NNatm**2)),True,False) & atmLandFrac
    
    atmLandFiltered = atmLandFiltered2D.ravel()
    atmCoast = atmCoast2D.ravel()

    print ('Number of points in atmLand  : ' + str(atmLand.sum())  )
    print ('Number of points in atmOcean : ' + str(atmOcean.sum()) )
    print ('Number of points in atmCoast : ' + str(atmCoast.sum()) )

else :
    atmCoast = atmFrac
    
    
# Arrays with coastal points only
atmCoast_grid_center_lon = atm_grid_center_lon[atmCoast]
atmCoast_grid_center_lat = atm_grid_center_lat[atmCoast]
atmCoast_grid_area       = atm_grid_area      [atmCoast]
atmCoast_grid_imask      = atm_grid_imask     [atmCoast]
atmCoast_grid_pmask      = atm_grid_pmask     [atmCoast]
atmCoast_address         = atm_address        [atmCoast]

# Initialisations before the loop
remap_matrix = np.empty ( shape=(0), dtype=np.float64 )
atm_address  = np.empty ( shape=(0), dtype=np.int32   )
oce_address  = np.empty ( shape=(0), dtype=np.int32   )

## Loop on atmosphere coastal points
for ja in np.arange(len(atmCoast_grid_pmask)) :
    z_dist = geodist ( atmCoast_grid_center_lon[ja], atmCoast_grid_center_lat[ja], oceCoast_grid_center_lon, oceCoast_grid_center_lat)
    z_mask = np.where ( z_dist*ra < searchRadius, True, False)
    num_links = np.int(z_mask.sum())
    if num_links == 0 : continue
    z_area = oceCoast_grid_area[z_mask].sum()
    poids = np.ones ((num_links),dtype=np.float64) / z_area
    if myargs.atmQuantity == 'Surfacic' : poids = poids * atm_grid_area[ja]
    if myargs.oceQuantity == 'Quantity' : poids = poids * oceCoast_grid_area[z_mask]
    if  ja % (len(atmCoast_grid_pmask)//50) == 0 : # Control print
        print ( 'ja:{:8d}, num_links:{:8d},  z_area:{:8.4e},  atm area:{:8.4e},  weights sum:{:8.4e}  '.format(ja, num_links, z_area, atm_grid_area[ja], poids.sum() ) )
    #
    matrix_local = poids
    atm_address_local = np.ones(num_links, dtype=np.int32 ) * atmCoast_address[ja]
    # Address on destination grid
    oce_address_local = oceCoast_address[z_mask]
    # Append to global tabs
    remap_matrix = np.append ( remap_matrix, matrix_local      )
    atm_address  = np.append ( atm_address , atm_address_local )
    oce_address  = np.append ( oce_address , oce_address_local )

print ('End of loop')

num_links = remap_matrix.shape[0]

### Output file
runoff = myargs.output
f_runoff = netCDF4.Dataset ( runoff, 'w', format=FmtNetcdf )
print ('Output file: ' + runoff )

f_runoff.Conventions     = "CF-1.6"
f_runoff.source          = "IPSL Earth system model"
f_runoff.group           = "ICMC IPSL Climate Modelling Center"
f_runoff.Institution     = "IPSL https.//www.ipsl.fr"
f_runoff.Ocean           = oce_Name + " https://www.nemo-ocean.eu"
f_runoff.Atmosphere      = atm_Name + " http://lmdz.lmd.jussieu.fr"
f_runoff.associatedFiles = grids + " " + areas + " " + masks
f_runoff.directory       = os.getcwd ()
f_runoff.description     = "Generated with cotes_etal.py"
f_runoff.title           = runoff
f_runoff.Program         = "Generated by " + sys.argv[0] + " with flags " + str(sys.argv[1:])
f_runoff.atmCoastWidth   = str(atmCoastWidth) + " grid points"
f_runoff.oceCoastWidth   = str(oceCoastWidth) + " grid points"
f_runoff.searchRadius    = str(searchRadius/1000.) + " km"
f_runoff.gridsFile       = grids
f_runoff.areasFile       = areas
f_runoff.masksFile       = masks
f_runoff.o2aFile         = o2a
f_runoff.timeStamp       = time.asctime()
f_runoff.uuid            = areaFile.uuid
f_runoff.HOSTNAME        = platform.node()
#f_runoff.LOGNAME         = os.getlogin()
f_runoff.Python          = "Python version " +  platform.python_version()
f_runoff.OS              = platform.system()
f_runoff.release         = platform.release()
f_runoff.hardware        = platform.machine()
f_runoff.conventions     = "SCRIP"
f_runoff.source_grid     = "curvilinear"
f_runoff.dest_grid       = "curvilinear"
f_runoff.Model           = "IPSL CM6"
f_runoff.SVN_Author      = "$Author$"
f_runoff.SVN_Date        = "$Date$"
f_runoff.SVN_Revision    = "$Revision$"
f_runoff.SVN_Id          = "$Id$"
f_runoff.SVN_HeadURL     = "$HeadURL$"

d_num_links = f_runoff.createDimension ('num_links'       , num_links )
d_num_wgts  = f_runoff.createDimension ('num_wgts'        ,         1 )

d_atm_grid_size    = f_runoff.createDimension ('src_grid_size'   , atm_grid_size )
d_atm_grid_corners = f_runoff.createDimension ('src_grid_corners', atm_grid_corner_lon.shape[0]  )
d_atm_grid_rank    = f_runoff.createDimension ('src_grid_rank'   , atm_grid_rank  )

d_oce_grid_size    = f_runoff.createDimension ('dst_grid_size'   , oce_grid_size )
d_oce_grid_corners = f_runoff.createDimension ('dst_grid_corners', oce_grid_corner_lon.shape[0] )
d_oce_grid_rank    = f_runoff.createDimension ('dst_grid_rank'   , oce_grid_rank  )

v_remap_matrix = f_runoff.createVariable ( 'remap_matrix', 'f8', ('num_links', 'num_wgts') )

v_atm_address  = f_runoff.createVariable ( 'src_address' , 'i4', ('num_links',) )
v_oce_address  = f_runoff.createVariable ( 'dst_address' , 'i4', ('num_links',) )

v_remap_matrix[:] = remap_matrix
v_atm_address [:] = atm_address + 1 # OASIS uses Fortran style indexing
v_oce_address [:] = oce_address + 1

v_atm_grid_dims       = f_runoff.createVariable ( 'src_grid_dims'      , 'i4', ('src_grid_rank',) )
v_atm_grid_center_lon = f_runoff.createVariable ( 'src_grid_center_lon', 'i4', ('src_grid_size',) )
v_atm_grid_center_lat = f_runoff.createVariable ( 'src_grid_center_lat', 'i4', ('src_grid_size',) )
v_atm_grid_center_lon.units='degrees_east'  ; v_atm_grid_center_lon.long_name='Longitude' ; v_atm_grid_center_lon.long_name='longitude' ; v_atm_grid_center_lon.bounds="src_grid_corner_lon"
v_atm_grid_center_lat.units='degrees_north' ; v_atm_grid_center_lat.long_name='Latitude'  ; v_atm_grid_center_lat.long_name='latitude ' ; v_atm_grid_center_lat.bounds="src_grid_corner_lat"
v_atm_grid_corner_lon = f_runoff.createVariable ( 'src_grid_corner_lon', 'f8', ('src_grid_size', 'src_grid_corners')  )
v_atm_grid_corner_lat = f_runoff.createVariable ( 'src_grid_corner_lat', 'f8', ('src_grid_size', 'src_grid_corners')  )
v_atm_grid_corner_lon.units="degrees_east"
v_atm_grid_corner_lat.units="degrees_north"
v_atm_grid_area       = f_runoff.createVariable ( 'src_grid_area'      , 'f8', ('src_grid_size',)  )
v_atm_grid_area.long_name="Grid area" ; v_atm_grid_area.standard_name="cell_area" ; v_atm_grid_area.units="m2"
v_atm_grid_imask      = f_runoff.createVariable ( 'src_grid_imask'     , 'i4', ('src_grid_size',)  )
v_atm_grid_imask.long_name="Land-sea mask" ; v_atm_grid_imask.units="Land:1, Ocean:0"
v_atm_grid_pmask      = f_runoff.createVariable ( 'src_grid_pmask'     , 'i4', ('src_grid_size',)  )
v_atm_grid_pmask.long_name="Land-sea mask (periodicity removed)" ; v_atm_grid_pmask.units="Land:1, Ocean:0"

v_atm_grid_dims      [:] = atm_grid_dims
v_atm_grid_center_lon[:] = atm_grid_center_lon[:]
v_atm_grid_center_lat[:] = atm_grid_center_lat[:]
v_atm_grid_corner_lon[:] = atm_grid_corner_lon
v_atm_grid_corner_lat[:] = atm_grid_corner_lat
v_atm_grid_area      [:] = atm_grid_area[:]
v_atm_grid_imask     [:] = atm_grid_imask[:]
v_atm_grid_pmask     [:] = atm_grid_pmask[:]

# --

v_oce_grid_dims       = f_runoff.createVariable ( 'dst_grid_dims'      , 'i4', ('dst_grid_rank',) )
v_oce_grid_center_lon = f_runoff.createVariable ( 'dst_grid_center_lon', 'i4', ('dst_grid_size',) )
v_oce_grid_center_lat = f_runoff.createVariable ( 'dst_grid_center_lat', 'i4', ('dst_grid_size',) )
v_oce_grid_center_lon.units='degrees_east'  ; v_oce_grid_center_lon.long_name='Longitude' ; v_oce_grid_center_lon.long_name='longitude' ; v_oce_grid_center_lon.bounds="dst_grid_corner_lon"
v_oce_grid_center_lat.units='degrees_north' ; v_oce_grid_center_lat.long_name='Latitude'  ; v_oce_grid_center_lat.long_name='latitude'  ; v_oce_grid_center_lat.bounds="dst_grid_corner_lat"
v_oce_grid_corner_lon = f_runoff.createVariable ( 'dst_grid_corner_lon', 'f8', ('dst_grid_size', 'dst_grid_corners')  )
v_oce_grid_corner_lat = f_runoff.createVariable ( 'dst_grid_corner_lat', 'f8', ('dst_grid_size', 'dst_grid_corners')  )
v_oce_grid_corner_lon.units="degrees_east"
v_oce_grid_corner_lat.units="degrees_north"
v_oce_grid_area       = f_runoff.createVariable ( 'dst_grid_area'  , 'f8', ('dst_grid_size',) )
v_oce_grid_area.long_name="Grid area" ; v_oce_grid_area.standard_name="cell_area" ; v_oce_grid_area.units="m2"
v_oce_grid_imask      = f_runoff.createVariable ( 'dst_grid_imask'     , 'i4', ('dst_grid_size',)  )
v_oce_grid_imask.long_name="Land-sea mask" ; v_oce_grid_imask.units="Land:1, Ocean:0"
v_oce_grid_pmask      = f_runoff.createVariable ( 'dst_grid_pmask'     , 'i4', ('dst_grid_size',)  )
v_oce_grid_pmask.long_name="Land-sea mask (periodicity removed)" ; v_oce_grid_pmask.units="Land:1, Ocean:0"

v_oce_grid_dims      [:] = oce_grid_dims
v_oce_grid_center_lon[:] = oce_grid_center_lon[:]
v_oce_grid_center_lat[:] = oce_grid_center_lat[:]
v_oce_grid_corner_lon[:] = oce_grid_corner_lon
v_oce_grid_corner_lat[:] = oce_grid_corner_lon
v_oce_grid_area      [:] = oce_grid_area[:]
v_oce_grid_imask     [:] = oce_grid_imask[:]
v_oce_grid_pmask     [:] = oce_grid_pmask[:]

v_atm_lon_addressed   = f_runoff.createVariable ( 'src_lon_addressed'  , 'f8', ('num_links',) )
v_atm_lat_addressed   = f_runoff.createVariable ( 'src_lat_addressed'  , 'f8', ('num_links',) )
v_atm_area_addressed  = f_runoff.createVariable ( 'src_area_addressed' , 'f8', ('num_links',) )
v_atm_imask_addressed = f_runoff.createVariable ( 'src_imask_addressed', 'i4', ('num_links',) )
v_atm_pmask_addressed = f_runoff.createVariable ( 'src_pmask_addressed', 'i4', ('num_links',) )

v_oce_lon_addressed   = f_runoff.createVariable ( 'dst_lon_addressed'  , 'f8', ('num_links',) )
v_oce_lat_addressed   = f_runoff.createVariable ( 'dst_lat_addressed'  , 'f8', ('num_links',) )
v_oce_area_addressed  = f_runoff.createVariable ( 'dst_area_addressed' , 'f8', ('num_links',) )
v_oce_imask_addressed = f_runoff.createVariable ( 'dst_imask_addressed', 'i4', ('num_links',) )
v_oce_pmask_addressed = f_runoff.createVariable ( 'dst_pmask_addressed', 'i4', ('num_links',) )

v_atm_lon_addressed.long_name="Longitude" ; v_atm_lon_addressed.standard_name="longitude" ; v_atm_lon_addressed.units="degrees_east"
v_atm_lat_addressed.long_name="Latitude"  ; v_atm_lat_addressed.standard_name="latitude"  ; v_atm_lat_addressed.units="degrees_north"
v_atm_lon_addressed  [:] = atm_grid_center_lon[atm_address]
v_atm_lat_addressed  [:] = atm_grid_center_lat[atm_address]
v_atm_area_addressed [:] = atm_grid_area[atm_address]
v_atm_imask_addressed[:] = 1-atm_grid_imask[atm_address]
v_atm_pmask_addressed[:] = 1-atm_grid_pmask[atm_address]

v_oce_lon_addressed.long_name="Longitude" ; v_oce_lon_addressed.standard_name="longitude" ; v_oce_lon_addressed.units="degrees_east"
v_oce_lat_addressed.long_name="Latitude"  ; v_oce_lat_addressed.standard_name="latitude"  ; v_oce_lat_addressed.units="degrees_north"
v_oce_lon_addressed  [:] = oce_grid_center_lon[oce_address]
v_oce_lat_addressed  [:] = oce_grid_center_lat[oce_address]#.ravel()
v_oce_area_addressed [:] = oce_grid_area[oce_address]
v_oce_imask_addressed[:] = 1-oce_grid_imask[oce_address]
v_oce_pmask_addressed[:] = 1-oce_grid_pmask[oce_address]

if atmDomainType == 'rectilinear' :
    v_atmLand         = f_runoff.createVariable ( 'atmLand'        , 'i4', ('src_grid_size',) )
    v_atmLandFiltered = f_runoff.createVariable ( 'atmLandFiltered', 'f4', ('src_grid_size',) )
    v_atmLandFrac     = f_runoff.createVariable ( 'atmLandFrac'    , 'i4', ('src_grid_size',) )
    v_atmFrac         = f_runoff.createVariable ( 'atmFrac'        , 'i4', ('src_grid_size',) )
    v_atmOcean        = f_runoff.createVariable ( 'atmOcean'       , 'i4', ('src_grid_size',) )
    v_atmOceanFrac    = f_runoff.createVariable ( 'atmOceanFrac'   , 'i4', ('src_grid_size',) )
    
    v_atmLand[:]         = atmLand
    v_atmLandFrac[:]     = atmLandFrac
    v_atmLandFiltered[:] = atmLandFiltered
    v_atmFrac[:]         = atmFrac
    v_atmOcean[:]        = atmOcean
    v_atmOceanFrac[:]    = atmOceanFrac

v_atmCoast         = f_runoff.createVariable ( 'atmCoast'       , 'i4', ('src_grid_size',) ) 
v_atmCoast[:]      = atmCoast

v_oceLand          = f_runoff.createVariable ( 'oceLand'         , 'i4', ('dst_grid_size',) )
v_oceOcean         = f_runoff.createVariable ( 'oceOcean'        , 'i4', ('dst_grid_size',) )
v_oceOceanFiltered = f_runoff.createVariable ( 'oceOceanFiltered', 'f4', ('dst_grid_size',) )
v_oceCoast         = f_runoff.createVariable ( 'oceCoast'        , 'i4', ('dst_grid_size',) )

v_oceLand[:]      = oceLand
v_oceOcean[:]     = oceOcean
v_oceOceanFiltered[:]     = oceOceanFiltered
v_oceCoast[:]     = oceCoast

f_runoff.sync ()

## 
f_runoff.close()

print ('The end')

## ======================================================================================