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'] +