def Regrid2deg(d):
"""
Regrid to 2deg (180lon*90lat) horizontal resolution
Input
- d: cdms variable
Output
- drg: cdms variable with 2deg horizontal resolution
"""
# Regridding
tgrid = cdms.createUniformGrid(-89, 90, 2.0, 0, 180, 2.0, order='yx')
orig_grid = d.getGrid()
regridFunc = Regridder(orig_grid, tgrid)
drg = MV.zeros((d.shape[0], tgrid.shape[0], tgrid.shape[1]), MV.float)
for it in range(d.shape[0]):
drg[it] = regridFunc(d[it])
# Dimension information
time = d.getAxis(0)
lat = tgrid.getAxis(0)
lon = tgrid.getAxis(1)
drg.setAxisList((time, lat, lon))
# Missing value (In case, missing value is changed after regridding)
drg[drg >= d.missing_value] = d.missing_value
mask = np.array(drg == d.missing_value)
drg.mask = mask
print('Complete regridding from', d.shape, 'to', drg.shape)
return drg
def regrid (self, togrid, missing=None, order=None, mask=None):
"""return self regridded to the new grid. Keyword arguments
are as for regrid.Regridder."""
from regrid2 import Regridder
if togrid is None:
return self
else:
fromgrid = self.getGrid()
regridf = Regridder(fromgrid, togrid)
result = regridf(self, missing=missing, order=order, mask=mask)
return result
print 'Test 8: Regridding ...',
## lat = cdms2.createGaussianAxis(32)
## lon = cdms2.createUniformLongitudeAxis(0.0,64,360.0/64.)
## outgrid = cdms2.createRectGrid(lat,lon,'yx','gaussian')
outgrid = cdms2.createGaussianGrid(32)
f = cdms2.openDataset(os.path.join(get_sample_data_dir(), 'readonly.nc'))
u = f.variables['u']
ingrid = u.getGrid()
try:
sh = ingrid.shape
except:
markError('Grid shape')
regridf = Regridder(ingrid, outgrid)
newu = regridf(u)
if (abs(newu[0, 0, -1] - 488.4763488) > 1.e-3):
markError('regrid', newu[0, 0, -1])
newu = u.regrid(outgrid)
if (abs(newu[0, 0, -1] - 488.4763488) > 1.e-3):
markError('regrid', newu[0, 0, -1])
# Regrid TV
tv = u.subSlice(0)
newtv = regridf(tv)
if (abs(newtv[0, 0, -1] - 488.4763488) > 1.e-3):
markError('regrid tv', newtv[0, 0, -1])
newtv = tv.regrid(outgrid)
if (abs(newtv[0, 0, -1] - 488.4763488) > 1.e-3):
ver = 'v20200421'
dir = '/p/user_pub/PCMDIobs/PCMDIobs2_clims/atmos/' + var + '/' + data + '/'
nc = var + '_mon_' + data + '_BE_gn_' + period + '.' + ver + '.AC.nc'
f = cdms.open(dir + nc)
d = f[var]
ogrid = d.getGrid()
print(ogrid)
# Target grid data
dir = '/p/user_pub/PCMDIobs/PCMDIobs2_clims/atmos/pr/GPCP-2-3/'
nc = 'pr_mon_GPCP-2-3_BE_gn_197901-201907.v20200421.AC.nc'
ft = cdms.open(dir + nc)
dt = ft['pr']
tgrid = dt.getGrid()
print(tgrid)
# Regridding
regridFunc = Regridder(ogrid, tgrid)
dr = regridFunc(d)
# Write data
out = cdms.open(
var + '_mon_' + data + '_BE_gn_' + period + '.' + ver +
'.AC_regrid.144x72.nc', 'w')
out.write(dr)
out.close()
# In[2]:
get_ipython().system('jupyter nbconvert --to script regridding.ipynb')
data2 = f2('tas', time=('1991-1-1', '1993-12-1'))
print data1.shape
# (48, 160, 320)
print data2.shape
# (48, 73, 144)
grid1 = data1.getGrid()
print grid1
print 'original ERA40 data shape: ', data1.shape
# original ERA40 data shape: (48, 160, 320)
grid2 = data2.getGrid()
print grid2
regridfunc = Regridder(grid1, grid2)
data1 = regridfunc(data1)
print 'new ERA40 data shape: ', data1.shape
cdutil.setTimeBoundsMonthly(data1)
cdutil.setTimeBoundsMonthly(data2)
start_time = cdtime.comptime(1991, 1, 1)
end_time = cdtime.comptime(1993, 12, 1)
ac1 = cdutil.ANNUALCYCLE.climatology(data1(time=(start_time, end_time, 'cob')))
ac2 = cdutil.ANNUALCYCLE.climatology(data2(time=(start_time, end_time, 'cob')))
print ac1
data1 = cdutil.ANNUALCYCLE.departures(data1, ref=ac1)
data2 = cdutil.ANNUALCYCLE.departures(data2, ref=ac2)
sst = b('sst')
b.close()
print sst.shape
x.clear()
x.plot(sst)
y = vcs.init()
y.setcolormap('default')
y.plot(tas)
# get grid for regridding
grid2 = sst.getGrid()
# setup a regridding function (as: fromgrid, togrid)
regridfunc = Regridder(grid2, grid1)
# create new data with 'togrid' (5-deg) resolution by passing
# the data with 'fromgrid' resolution into the funstion above
sst_new = regridfunc(sst)
tas_new = regridfunc(tas)
x.clear()
x.plot(sst_new)
y.setcolormap('default')
y.plot(tas_new)
# extract a land/sea mask and regrid it to our desired 5 degree grid
# (these data are percent land coverage [0-100])
file4 = os.path.join(sys.prefix, 'sample_data/geo.1deg.ctl')
c = cdms2.open(file4)
def _oisst_daily(daily_sst_dir, daily_sst_filename, targ_grid_res):
#---------------------------------------------------------------------
"""
See file header.
"""
print('targ_grid_res: ', targ_grid_res)
time_span_tag = daily_sst_filename.split('.')[2]
time_units = 'days since ' + time_span_tag.split('-')[0] + '-1-1 00:00:00'
year_start = int(time_span_tag.split('-')[0])
daily_ice_filename = daily_sst_filename.replace('sst', 'icec')
# Create target grid.
# For a ONEXONE target grid resolution with arguments:
# (-90., 181, 1., 0., 360, 1.)
# A grid will be created with:
# latitude starting at -90 & going north 181 points,
# with an increment of 1 degree;
# longitude starting at 0E & going east 360 points,
# with an increment of 1 degree.
# The out_filename will reflect the designated resolution.
#---------------------------------------------------------
args = TARG_GRID_RES_DICT[targ_grid_res]['args']
targ_grid = cdms2.createUniformGrid(args[0], args[1], args[2], args[3],
args[4], args[5])
label = TARG_GRID_RES_DICT[targ_grid_res]['label']
out_filename = 'sst_daily_cdcunits' + label + time_span_tag + '.nc'
fdaily_sst = cdms2.open(daily_sst_dir + '/' + daily_sst_filename)
fdaily_ice = cdms2.open(daily_sst_dir + '/' + daily_ice_filename)
input_grid = fdaily_sst.variables['sst'].getGrid()
rg_in2targ = Regridder(input_grid, targ_grid)
# Create file and variables for output.
#--------------------------------------
#fout = NetCDF.NetCDFFile(out_filename, 'w')
fout = Cdunif.CdunifFile(out_filename, 'w')
lons = targ_grid.getLongitude()[:]
lats = targ_grid.getLatitude()[:]
fout.createDimension('lon', len(lons))
fout.createDimension('lat', len(lats))
fout.createDimension('time', None)
sst_cpl = fout.createVariable('sst', 'f', ('time', 'lat', 'lon'))
sst_cpl.long_name = 'sea surface temperature'
sst_cpl.units = 'degrees_C'
ifrac = fout.createVariable('ifrac', 'f', ('time', 'lat', 'lon'))
ifrac.long_name = 'ice fraction'
ifrac.units = 'fraction'
lat = fout.createVariable('lat', 'd', ('lat', ))
lat.long_name = 'latitude of grid cell center'
lat.units = 'degrees_north'
lon = fout.createVariable('lon', 'd', ('lon', ))
lon.long_name = 'longitude of grid cell center'
lon.units = 'degrees_east'
time = fout.createVariable('time', 'd', ('time', ))
time.long_name = 'time'
time.units = time_units
time.calendar = 'noleap'
date = fout.createVariable('date', 'i', ('time', ))
date.long_name = 'calendar date (YYYYMMDD)'
datesec = fout.createVariable('datesec', 'i', ('time', ))
datesec.long_name = 'seconds elapsed on calendar date'
datesec.units = 'seconds'
# Coordinate data.
#-----------------
lat[:] = lats
lat.long_name = 'latitude'
lat.units = 'degrees_north'
lon[:] = lons
lon.long_name = 'longitude'
lon.units = 'degrees_east'
sst_w = fdaily_sst.variables['sst']
ntimes = sst_w.shape[0]
intime = sst_w.getTime()
intime_units = intime.units
intimes = intime[:]
# Time loop.
#-----------
time_idx_out = -1
for time_idx in range(ntimes - 1):
# Data is centered on time in file.
#----------------------------------
mid_intime = intimes[time_idx]
rtime = cdtime.reltime(mid_intime, intime_units)
ctime = rtime.tocomp()
new_reltime = ctime.torel(time_units, cdtime.NoLeapCalendar)
new_ctime = new_reltime.tocomp()
year = ctime.year
if year < year_start:
#=======
continue
#=======
month = ctime.month
day = ctime.day
hour = ctime.hour
minute = ctime.minute
second = ctime.second
# Change time units.
#-------------------
print ('time_idx_out, ctime, new_ctime: ', \
time_idx_out, ctime, new_ctime)
time[time_idx_out] = new_reltime.value
print('time[time_idx_out]: ', time[time_idx_out])
date[time_idx_out] = (year * 10000) + (month * 100) + day
datesec[time_idx_out] = (hour * 60 * 60) + (minute * 60) + second
data = fdaily_sst('sst',
time=slice(time_idx, (time_idx + 1)),
raw=1,
squeeze=1)
data_f = fill_msg(data, nscan=200)
data_f = n.array(data_f, n.float32)
print ('data_f min,max,mean: ', \
data_f.min(), data_f.max(), data_f.mean() )
data_f = rg_in2targ(data_f).filled()
out_sst = data_f
print ('out_sst min,max,mean: ', \
out_sst.min(), out_sst.max(), out_sst.mean() )
data = fdaily_ice('icec',
time=slice(time_idx, (time_idx + 1)),
raw=1,
squeeze=1)
data_f = data * 1.0
print ('data_f min,max,mean: ', \
data_f.min(), data_f.max(), data_f.mean() )
# Set ice to zero where missing - over land.
#-------------------------------------------
data_f = rg_in2targ(data_f).filled(0.0)
out_ice = data_f
print ('out_ice min,max,mean: ', \
out_ice.min(), out_ice.max(), out_ice.mean() )
sst_cpl[time_idx_out, :, :] = out_sst
ifrac[time_idx_out, :, :] = out_ice
time_idx_out = time_idx_out + 1
fout.sync()
fout.close()
return
var = newfile.split('/')[7]
rep = '/'
newdir = rep.join(newdir_tmp)
#print(newdir)
try:
os.mkdir(newdir + '/' + target)
except:
print('cant make dir ' + newdir + '/' + target)
try:
os.mkdir(newdir + '/' + target + '/' + ver_out + '/')
except:
pass
fc = cdms2.open(l)
d = fc(var)
orig_grid = d.getGrid()
regridFunc = Regridder(orig_grid, tgrid)
dn = regridFunc(d)
dn.id = var
g = cdms2.open(newfile, 'w+')
g.write(dn)
g.close()
#print(newdir)
print('done with ', newfile)