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cleaning and polishing
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@oloapinivad
oloapinivad committed Dec 23, 2024
1 parent c887b3f commit b838ec0
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Showing 3 changed files with 63 additions and 63 deletions.
61 changes: 42 additions & 19 deletions ecmean/global_mean.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,9 +83,11 @@ def __init__(self, exp, year1, year2, config='config.yml', loglevel='WARNING', n

self.loglevel = loglevel
self.loggy = setup_logger(level=self.loglevel)
self.diag = Diagnostic(exp, year1, year2, config, funcname=self.__class__.__name__,
numproc=numproc, ensemble=ensemble, interface=interface, modelname=model,
addnan=addnan, silent=silent, trend=trend, line=line, outputdir=outputdir,
self.diag = Diagnostic(exp, year1, year2, config,
funcname=self.__class__.__name__,
numproc=numproc, ensemble=ensemble, interface=interface,
modelname=model, addnan=addnan, silent=silent,
trend=trend, line=line, outputdir=outputdir,
xdataset=xdataset)
self.face = None
self.ref = None
Expand Down Expand Up @@ -129,8 +131,13 @@ def run(self):
processes = []

for varlist in weight_split(self.diag.var_all, self.diag.numproc):
core = Process(target=self.gm_worker, args=(self.util_dictionary, self.ref, self.face, self.diag,
self.varmean, self.vartrend, varlist))
core = Process(target=self.gm_worker, args=(self.util_dictionary,
self.ref,
self.face,
self.diag,
self.varmean,
self.vartrend,
varlist))
core.start()
processes.append(core)

Expand All @@ -145,38 +152,52 @@ def store(self, yamlfile=None):
# reorder the data to be stored
for var in self.diag.var_all:
gamma = self.ref[var]

# if dictionary we have more info season, mean and standard deviation
if isinstance(gamma['obs'], dict):
tabval = gamma['obs']['ALL']['Global']
outval = str(tabval['mean']) + '\u00B1' + str(tabval['std'])
else:
outval = gamma['obs']

if 'year1' in gamma.keys():
years = str(gamma['year1']) + '-' + str(gamma['year2'])
else:
raise ValueError('Year1 and Year2 are not defined in the reference file')
years = f"{gamma['year1']}-{gamma['year2']}"

# prepare output sequence using list expansion if trend is requested
out_sequence = [
var,
gamma['longname'],
gamma['units'],
self.varmean[var]['ALL']['Global'],
*([self.vartrend[var]['ALL']['Global']] if self.diag.ftrend else []),
outval,
gamma.get('dataset', ''),
years
]

out_sequence = [var, gamma['longname'], gamma['units'], self.varmean[var]['ALL']['Global']]
if self.diag.ftrend:
out_sequence = out_sequence + [self.vartrend[var]['ALL']['Global']]
out_sequence = out_sequence + [outval, gamma.get('dataset', ''), years]
global_table.append(out_sequence)

head = ['Variable', 'Longname', 'Units', self.diag.modelname]
if self.diag.ftrend:
head = head + ['Trend']
head = head + ['Obs.', 'Dataset', 'Years']
# create header using list expansion if trend is requested
head = [
'Variable',
'Longname',
'Units',
self.diag.modelname,
*(['Trend'] if self.diag.ftrend else []),
'Obs.',
'Dataset',
'Years'
]

# save table
tablefile = self.diag.filenames('txt')
self.loggy.info('TXT file is: %s', tablefile)
with open(tablefile, 'w', encoding='utf-8') as out:
out.write(tabulate(global_table, headers=head, stralign='center', tablefmt='orgtbl'))

# reaorder
# reorder
self.varmean = {var: self.varmean[var] for var in self.diag.var_all}

# save yaml fil
# save yaml file
if yamlfile is None:
yamlfile = self.diag.filenames('yml')

Expand Down Expand Up @@ -251,6 +272,8 @@ def gm_worker(util, ref, face, diag, varmean, vartrend, varlist):

xfield = xfield.sel(time=xfield.time.dt.year.isin(diag.years_joined))
check_time_axis(xfield.time, diag.years_joined)

# compute here since the operation are built on this
cfield = formula_wrapper(var, face, xfield).compute()

for season in diag.seasons:
Expand Down
43 changes: 12 additions & 31 deletions ecmean/libs/masks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,6 +80,8 @@ def mask_field(xfield, mask_type, dom, mask):
out = xfield.where(mask.data < 0.5)
else:
raise ValueError("ERROR: mask_field -> Mask undefined, this cannot be handled!")
else:
raise ValueError("ERROR: mask_field -> Domain undefined, this cannot be handled!")

return out

Expand Down Expand Up @@ -121,37 +123,16 @@ def select_region(xfield, region):

if region == 'Global':
return xfield

if region == 'North Midlat':
lat_min, lat_max = 30.0, 90.0
elif region == 'South Midlat':
lat_min, lat_max = -90.0, -30.0
elif region == 'Tropical':
lat_min, lat_max = -30.0, 30.0
else:
if region == 'North Midlat':
lat_min, lat_max = 30.0, 90.0
elif region == 'South Midlat':
lat_min, lat_max = -90.0, -30.0
elif region == 'Tropical':
lat_min, lat_max = -30.0, 30.0
else:
raise KeyError(region + "region not supported!!!")

# new version more flexible than the slice one
return xfield.where((xfield.lat >= lat_min) & (xfield.lat <= lat_max))

raise KeyError(region + "region not supported!!!")

# def select_region_old(xfield, region):
# """Trivial function to convert region definition to xarray
# sliced array to compute the PIs or global means on selected regions"""

# # fixed for the order of latitudes
# #xfield = xfield.sortby('lat')


# if region == 'Global':
# slicearray = xfield
# elif region == 'North Midlat':
# slicearray = xfield.sel(lat=slice(30, 90))
# elif region == 'South Midlat':
# slicearray = xfield.sel(lat=slice(-90, -30))
# elif region == 'Tropical':
# slicearray = xfield.sel(lat=slice(-30, 30))
# else:
# sys.exit(region + "region not supported!!!")
# new version more flexible than the slice one
return xfield.where((xfield.lat >= lat_min) & (xfield.lat <= lat_max))

# return slicearray
22 changes: 9 additions & 13 deletions ecmean/libs/plotting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -220,13 +220,9 @@ def prepare_clim_dictionaries_pi(data, clim, shortnames):
del filt_piclim[k][f]

# set longname, reorganize the dictionaries
data2plot = {}
cmip6 = {}
data2plot = {clim[var]['longname']: data[var] for var in shortnames}
cmip6 = {clim[var]['longname']: filt_piclim[var] for var in shortnames}
longnames = [clim[var]['longname'] for var in shortnames]
for var in shortnames:
longname = clim[var]['longname']
data2plot[longname] = data[var]
cmip6[longname] = filt_piclim[var]

return data2plot, cmip6, longnames

Expand Down Expand Up @@ -254,6 +250,7 @@ def prepare_clim_dictionaries_gm(data, clim, shortnames, seasons, regions):
obsstd = {}
for var in shortnames:
gamma = clim[var]
obs = gamma['obs']

# extract from yaml table for obs mean and standard deviation
mmm = init_mydict(seasons, regions)
Expand All @@ -262,19 +259,18 @@ def prepare_clim_dictionaries_gm(data, clim, shortnames, seasons, regions):
if isinstance(gamma['obs'], dict):
for season in seasons:
for region in regions:
mmm[season][region] = gamma['obs'][season][region]['mean']
sss[season][region] = gamma['obs'][season][region]['std']
mmm[season][region] = obs[season][region]['mean']
sss[season][region] = obs[season][region]['std']
# if only global observation is available
else:
mmm['ALL']['Global'] = gamma['obs']

# Assign to obsmean and obsstd using longname as the key
obsmean[gamma['longname']] = mmm
obsstd[gamma['longname']] = sss

# set longname, get units
data2plot = {}
units_list = []
for var in shortnames:
data2plot[clim[var]['longname']] = data[var]
units_list.append(clim[var]['units'])
data2plot = {clim[var]['longname']: data[var] for var in shortnames}
units_list = [clim[var]['units'] for var in shortnames]

return obsmean, obsstd, data2plot, units_list

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