'1980030100-1980033118',
'1980040100-1980043018',
'1980050100-1980053118',
'1980060100-1980063018',
'1980070100-1980073118',
'1980080100-1980083118',
'1980090100-1980093018',
'1980100100-1980103118',
'1980110100-1980113018',
'1980120100-1980123118']
#get the desired resolution from JRA-55 (1.25x1.25)
f1=cdms2.open('/att/dataportal01/CREATE-IP/reanalysis/JMA/JRA-55/6hr/atmos/ta/ta_6hr_reanalysis_JRA-55_1980010100-1980013118.nc')
ta2=f1('ta',genutil.picker(plev=(100000, 97500, 95000, 92500, 90000,
87500, 85000, 82500, 80000, 77500, 75000, 70000, 65000, 60000, 55000,
50000, 45000, 40000, 35000, 30000, 25000, 20000, 15000, 10000)))
ta2=ta2(time=('1980-01-00','cob'))
outfixlev=cdms2.open('/att/dmznsd/nobackup01/projects/ESGF/glpotter/CFSR/ensemble/level_test.nc','w')
ta2.id='ta'
outfixlev.write(ta2)
outfixlev.close()
f1=cdms2.open('/att/dmznsd/nobackup01/projects/ESGF/glpotter/CFSR/ensemble/level_test.nc')
ta1=f1('ta')
outgrid=ta1.getGrid()
lat=f1.getAxis('lat')
lon=f1.getAxis('lon')
plev=f1.getAxis('plev')
#!/usr/bin/env python
# Adapted for numpy/ma/cdms2 by convertcdms.py
import cdms2 as cdms,genutil,vcs,cdtime,os,sys
import vcs.test.support
bg=vcs.test.support.bg
cdms.setAutoBounds('on')
#f=cdms.open('/pcmdi/obs/mo/ta/rnl_ncep/ta.rnl_ncep.ctl')
f=cdms.open(os.path.join(vcs.sample_data,'ta_ncep_87-6-88-4.nc'))
levels = [1000,700,800]
try:
s=f('ta',slice(0,1),genutil.picker(level=levels,match=1))
error = False
except:
print 'Ok failed getting the missing levels as expected!'
error = True
if error == False:
raise Exception,"Error it should have failed here!"
s=f('ta',slice(0,1),genutil.picker(level=levels,match=0))
if s.shape[1]!=3:
raise "Error did not return 3 levels!"
if (s.getLevel()[:]!=levels).any():
raise Exception,"Error did not retrieve the right levels!"
print "folowing plot should show all missing values, since 800 does not exisits!"
x=vcs.init()
x.plot(s[0,-1],bg=bg)
import numpy as np
import numpy.ma as ma
dataportal_data_path = '/att/dataportal01/CREATE-IP/reanalysis'
dass_data_path = '/dass/pubrepo/CREATE-IP/data/reanalysis'
data_path = dass_data_path
target_grid_dset = cdms2.open(
data_path +
'/JMA/JRA-55/6hr/atmos/ta/ta_6hr_reanalysis_JRA-55_1958010100-1958013118.nc'
)
target_grid_var = target_grid_dset['ta']
""":type : FileVariable """
dset_address = data_path + "/NASA-GMAO/GEOS-5/MERRA2/6hr/atmos/ta/ta_6hr_reanalysis_MERRA2_1980010100-1980013118.nc"
vname = "ta"
levs = (100000, 97500, 95000, 92500, 90000, 87500, 85000, 82500, 80000, 77500,
75000, 70000, 65000, 60000, 55000, 50000, 45000, 40000, 35000, 30000,
25000, 20000, 15000, 10000)
t0 = time.time()
dset = cdms2.open(dset_address)
var0 = dset[vname]
var1 = dset(vname, genutil.picker(level=levs))
""":type : AbstractVariable """
# newvar = var.regrid( target_grid_var.getGrid() )
t1 = time.time()
print "Completed test in time {0}, shape0 = {1}, shape1 = {2}".format(
str(t1 - t0), str(var0.shape), str(var1.shape))
def executeOperations(self, task, _inputs):
"""
:type task: Task
:type _inputs: dict[str,npArray]
"""
cdms2.setAutoBounds(2)
start = time.time()
mdata = task.metadata
""":type : dict[str,str] """
self.logger.info(" Execute Ensemble Task with metadata: " +
str(task.metadata))
target = str(mdata.get("target", ""))
method = str(mdata.get("method", "linear")).lower()
res = sa2f(self.getListParm(mdata, "res"))
shape = sa2i(self.getListParm(mdata, "shape"))
plevs = sa2f(self.getListParm(mdata, "plev"))
resultDir = task.metadata.get("resultDir")
target_input = _inputs.get(target, None)
if (target_input is None):
raise Exception(
"Must set the 'target' parameter in EnsembleWorkflowKernel to the id of the input that determines the output grid"
)
outgrid = target_input.getGrid()
arrays = []
for (id, _input) in _inputs.iteritems():
dset_address = _input.metadata.get("uri",
_input.metadata.get("dataPath"))
vname = _input.metadata.get("name")
dset = cdms2.open(dset_address)
var = dset(vname, genutil.picker(
plev=plevs)) if (plevs) else dset(vname)
""":type : AbstractVariable """
if (id == target):
lat = var.getLatitude()
""":type : AbstractCoordinateAxis """
lon = var.getLongitude()
""":type : AbstractCoordinateAxis """
plev = var.getLevel()
""":type : AbstractCoordinateAxis """
t = var.getTime()
""":type : AbstractCoordinateAxis """
units = var.getattribute("units")
varname = vname
arrays.append(var)
else:
arrays.append(var.regrid(outgrid))
times = t.asComponentTime()
trange = str(times[0]) + "-" + str(times[-1])
concatenate = ma.masked_array(arrays)
average = cdms2.MV2.average(concatenate, axis=0)
ave = cdms2.createVariable(average, axes=(t, plev, lat, lon))
ave.units = units
ave.id = varname
ave.long_name = 'ensemble average'
outfile = cdms2.open(
resultDir + "/" + varname + '_6hr_reanalysis_ensemble_ave_' +
trange + '.nc', 'w')
outfile.write(ave)
outfile.close()
stdv = genutil.statistics.std(concatenate, axis=0)
stdvave = cdms2.createVariable(stdv, axes=(t, plev, lat, lon))
stdvave.id = varname + '_stdv'
stdvave.long_name = 'standard deviation'
stdvave.units = units
outfile_std = cdms2.open(
resultDir + "/" + varname + '6hr_reanalysis_ensemble_std_' +
trange + '.nc', 'w')
outfile_std.write(stdvave)
outfile_std.close()
#newgrid.shape
end = time.time()
print "Completed EnsembleWorkflowKernel in " + str(
(end - start) / 60.) + " min "
select = cdms2.selectors.Selector(lon=slice(0, 3), time=('1950', cdtime.comptime(1960)))
print u(equator)(select).shape
# -> appliquez à la lecture du fichier
# Le module genutil : utilitaires generiques
# - contenu
import genutil
print dir(genutil)
# - statistics standards
print dir(genutil.statistics)
ustd = genutil.statistics.std(u, axis=0) # testez les options
ustd.info()
print N.ma.allclose(ustd, u.std(axis=0))
# - salstat
print dir(genutil.salstat)
print genutil.salstat.kurtosis(u, axis='t') # essayez d'autres fonctions
# - divers
_, uu = genutil.grower(u, u[0]) # testez d'autres slices
print uu.shape
print genutil.minmax(u, u**2)
print u[:, 0, 0](genutil.picker(time=['1960-01-03', '1965-05-03'])) # testez option match
