dists = [rcp + "-" + str(year) for year in years]
for ii in range(len(dists)):
if ii < len(values) and values[ii] is not None:
impacts.collect_in_dictionaries(
data, combine_years(values[ii]), dists[ii], region, collection, model
)
if batches == "truehist":
rcps = ["truehist"]
else:
rcps = results.rcps
# Combine across all batch-realizations that have all models
for rcp in rcps:
model_weights = weights.get_weights(rcp)
if do_yearsets:
dists = [rcp + "-" + str(years[0]) for years in yearses]
else:
dists = [rcp + "-" + str(year) for year in years]
for dist in dists:
if dist not in data:
continue
with open(os.path.join(outdir, impact + "-" + dist + ".csv"), "w") as csvfp:
writer = csv.writer(csvfp, quoting=csv.QUOTE_MINIMAL)
if output_format == "edfcsv":
writer.writerow(["region"] + map(lambda q: "q" + str(q), evalpvals))
elif output_format == "valuescsv":
print "Creating file: " + str(filestuff)
with open(configs.csv_makepath(filestuff, config), 'w') as fp:
writer = csv.writer(fp, quoting=csv.QUOTE_MINIMAL)
rownames = configs.csv_rownames(config)
if output_format == 'edfcsv':
writer.writerow(rownames +
map(lambda q: 'q' + str(int(q * 100)), evalqvals))
elif output_format == 'valuescsv':
writer.writerow(rownames +
['batch', 'gcm', 'iam', 'value', 'weight'])
for rowstuff in configs.csv_sorted(data[filestuff].keys(), config):
print "Outputing row: " + str(rowstuff)
if do_gcmweights:
model_weights = weights.get_weights(
configs.csv_organized_rcp(filestuff, rowstuff, config))
allvalues = []
allweights = []
allmontevales = []
for batch, gcm, iam in data[filestuff][rowstuff]:
value = data[filestuff][rowstuff][(batch, gcm, iam)]
if do_gcmweights:
weight = model_weights[gcm]
else:
weight = 1.
allvalues.append(value)
allweights.append(weight)
allmontevales.append([batch, gcm, iam])
for ii in range(len(dists)):
if ii < len(values) and values[ii] is not None:
impacts.collect_in_dictionaries(data,
combine_years(values[ii]),
dists[ii], region,
collection, model)
if batches == 'truehist':
rcps = ['truehist']
else:
rcps = results.rcps
# Combine across all batch-realizations that have all models
for rcp in rcps:
model_weights = weights.get_weights(rcp)
if do_yearsets:
dists = [rcp + '-' + str(years[0]) for years in yearses]
else:
dists = [rcp + '-' + str(year) for year in years]
for dist in dists:
if dist not in data:
continue
with open(os.path.join(outdir, impact + '-' + dist + '.csv'),
'w') as csvfp:
writer = csv.writer(csvfp, quoting=csv.QUOTE_MINIMAL)
if output_format == 'edfcsv':
writer.writerow(['region'] +