from pyremap import LatLonGridDescriptor, Remapper
from mpas_analysis.shared.constants import constants
inputFileName = '/media/xylar/extra_data/analysis/output/GMPAS-QU240/' \
'remap_obs/clim/obs/mld_1.0x1.0degree.nc'
obsDescriptor = LatLonGridDescriptor.read(fileName=inputFileName,
latVarName='lat',
lonVarName='lon')
comparisonLatRes = 4.
comparisonLonRes = 4.
nLat = int((constants.latmax - constants.latmin) / comparisonLatRes) + 1
nLon = int((constants.lonmax - constants.lonmin) / comparisonLonRes) + 1
lat = numpy.linspace(constants.latmin, constants.latmax, nLat)
lon = numpy.linspace(constants.lonmin, constants.lonmax, nLon)
comparisonDescriptor = LatLonGridDescriptor.create(lat, lon, units='degrees')
remapper = Remapper(obsDescriptor,
comparisonDescriptor,
mappingFileName='map.nc')
remapper.build_mapping_file()
remapper.remap_file(inputFileName,
'mld_4.0x4.0degree.nc', ['mld', 'month', 'year'],
renormalize=0.05)
# modify the size and resolution of the Antarctic grid as desired
outDescriptor = get_polar_descriptor(Lx=6000.,
Ly=5000.,
dx=10.,
dy=10.,
projection='antarctic')
outGridName = outDescriptor.meshName
mappingFileName = 'map_{}_to_{}_bilinear.nc'.format(inGridName, outGridName)
remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
# conservative remapping with 4 MPI tasks (using mpirun)
remapper.build_mapping_file(method='bilinear', mpiTasks=4)
# select the SST at the initial time as an example data set
srcFileName = 'temp_{}.nc'.format(inGridName)
ds = xarray.open_dataset(inGridFileName)
dsOut = xarray.Dataset()
dsOut['temperature'] = ds['temperature'].isel(nVertLevels=0, Time=0)
dsOut.to_netcdf(srcFileName)
# do remapping with ncremap
outFileName = 'temp_{}_file.nc'.format(outGridName)
remapper.remap_file(srcFileName, outFileName)
# do remapping again, this time with python remapping
outFileName = 'temp_{}_array.nc'.format(outGridName)
dsOut = remapper.remap(dsOut)
dsOut.to_netcdf(outFileName)
