def test_remap(directory, sourcefiles):
ctt.loadtestfiles(directory, sourcefiles)
filepattern = "*.nc"
ens = cd.mkensemble(filepattern)
ens = cd.remap(ens, remap="r1x180")
data = ctt.sha(ens)
return data
def test_remap(directory, sourcefiles):
ctt.loadtestfiles(directory, sourcefiles)
filepattern = '*.nc'
ens = cd.mkensemble(filepattern)
ens = cd.remap(ens, remap='r1x180')
data = ctt.sha(ens)
return data
def test_ensembleenvelope(directory, sourcefiles, var, sd, ed, cwd):
""" Tests ensemble_envelope_timeseries
Parameters
----------
directory : string
the directory to link the files to
sourcefiles : list
a list of the locations of the files to link
var : string
the variable plotted
sd : int
start date for time slice
ed : int
end date for time slice
cwd : string
directory of the test modules
"""
ctt.loadtestfiles(directory, sourcefiles)
filepattern = '*.nc'
ens = cd.mkensemble(filepattern)
ens = cd.time_slice(ens, sd, ed)
ens = cd.remap(ens, 'r360x180', delete=True)
ens = cd.my_operator(ens, my_cdo_str='cdo -fldmean -yearmean {infile} {outfile}', output_prefix='processed_', delete=True)
cd.ens_stats(ens, var)
cd.ensemble_envelope_timeseries(ens, 'ENS-MEAN_processed_remap_ts_Amon_CanESM2_historical_R-MEAN_195001-200012.nc', 'ENS-STD_processed_remap_ts_Amon_CanESM2_historical_STD_195001-200012.nc', var, pdf='ensenv')
plotcompare(directory, cwd, 'ensenv')
os.system('rm ensenv.pdf')
def cmip_average(files, var):
""" Creates and stores a netCDF file with the average data
across all the models provided.
Returns the name of the created file.
"""
ens = cd.mkensemble('', filenames=files)
out = 'netcdf/' + var + '_' + 'cmip5.nc'
# skip if the new file was already made
if not os.path.isfile(out):
ens = cd.remap(ens, output_prefix='netcdf/forens-')
ensemble_means, _ = cd.ens_stats(ens, var, output_prefix='netcdf/')
os.rename(ensemble_means[0], out)
return out
def preprocess_models(datapath='./'):
# where we are starting from
cwd = os.getcwd()
# move to where the data is
os.chdir(datapath)
# time-merge, remap and zonal mean the model data
variables = ['uas', 'psl', 'tauu']
for var in variables:
# time-merge the data across the historical and rcp45 experiments
filepattern = var + '_Amon*.nc'
ens = cd.mkensemble(filepattern)
# remap to a 1x1 grid
ens_remap = cd.remap(ens,remap='r360x180', delete=True)
# Compute zonal means
ens_zonmean = cd.zonmean(ens_remap, delete=False)
# move back
os.chdir(cwd)
def test_ensembleenvelope(directory, sourcefiles, var, sd, ed, cwd):
""" Tests ensemble_envelope_timeseries
Parameters
----------
directory : string
the directory to link the files to
sourcefiles : list
a list of the locations of the files to link
var : string
the variable plotted
sd : int
start date for time slice
ed : int
end date for time slice
cwd : string
directory of the test modules
"""
ctt.loadtestfiles(directory, sourcefiles)
filepattern = '*.nc'
ens = cd.mkensemble(filepattern)
ens = cd.time_slice(ens, sd, ed)
ens = cd.remap(ens, 'r360x180', delete=True)
ens = cd.my_operator(
ens,
my_cdo_str='cdo -fldmean -yearmean {infile} {outfile}',
output_prefix='processed_',
delete=True)
cd.ens_stats(ens, var)
cd.ensemble_envelope_timeseries(
ens,
'ENS-MEAN_processed_remap_ts_Amon_CanESM2_historical_R-MEAN_195001-200012.nc',
'ENS-STD_processed_remap_ts_Amon_CanESM2_historical_STD_195001-200012.nc',
var,
pdf='ensenv')
plotcompare(directory, cwd, 'ensenv')
os.system('rm ensenv.pdf')
