elif mc_name == 'ENSO_proc':
list_obs = [
'20CRv2', 'AVISO', 'ERA-Interim', 'ERSSTv5', 'GODAS', 'HadISST',
'NCEP2', 'SODA3.4.2', 'Tropflux'
]
else:
list_obs = [
'20CRv2', 'AVISO', 'CMAP', 'ERA-Interim', 'ERSSTv5', 'GODAS',
'GPCPv2.3', 'HadISST', 'NCEP2', 'SODA3.4.2', 'Tropflux'
]
# ---------------------------------------------------#
# ---------------------------------------------------#
# Main
# ---------------------------------------------------#
dict_mc = defCollection(mc_name)
list_metric = sorted(dict_mc["metrics_list"].keys())
#
# list of variables needed for the given metric collection
#
list_variables = list()
for metric in list_metric:
listvar = dict_mc["metrics_list"][metric]["variables"]
for var in listvar:
if var not in list_variables:
list_variables.append(var)
list_variables = sorted(list_variables)
#
# finding file and variable name in file for each observational dataset
pass
pattern = "_".join([mip, exp, metric_collection, case_id])
# ---------------------------------------------------#
# Main
# ---------------------------------------------------#
# read json file
filename_js = OSpath__join(path_in_json, pattern + "_allModels_allRuns.json")
print('filename_js:', filename_js)
with open(filename_js) as ff:
data_json = json.load(ff)['RESULTS']['model'][model][run]
ff.close()
del ff, filename_js
# loop on metrics
metrics = sorted(defCollection(metric_collection)['metrics_list'].keys(),
key=lambda v: v.upper())
for met in metrics:
try:
print('met:', met)
# get NetCDF file name
filename_nc = OSpath__join(
path_in_nc, pattern + "_" + model + "_" + run + "_" + met + ".nc")
print("filename_nc:", filename_nc)
# get diagnostic values for the given model and observations
if metric_collection == "ENSO_tel" and "Map" in met:
dict_dia = data_json["value"][met + "Corr"]["diagnostic"]
diagnostic_values = dict((key1, None) for key1 in dict_dia.keys())
diagnostic_units = ""
else:
dict_dia = data_json["value"][met]["diagnostic"]
