def describe(self, fh=sys.stdout):
# Prepare string representation of stats
stats = self.descriptive_stats()
s = ''
s += 'METADATA:\n'
for key, value in self.metadata.iteritems():
s += ' {} = {}\n'.format(key, value)
s += '\n'
s += 'NUMBER OF BUILDINGS: {:d}\n\n'.format(len(self.buildings))
s += 'NUMBER OF APPLIANCES PER BUILDING:\n'
s += summary_stats_string(stats['n_appliances'])
s += '\n'
s += 'PROPORTION OF ENERGY SUBMETERED PER BUILDLING:\n'
s += summary_stats_string(stats['energy_submetered'])
s += '\n'
s += 'DROPOUT RATE PER CHANNEL, INCLUDING LARGE GAPS:\n'
s += summary_stats_string(stats['dropout_rate'])
s += '\n'
s += 'DROPOUT RATE PER CHANNEL, IGNORING LARGE GAPS:\n'
s += summary_stats_string(stats['dropout_rate_ignoring_gaps'])
s += 'MAINS UPTIME PER BUILDING (DAYS):\n'
s += summary_stats_string(stats['uptime'])
s += '\n'
s += 'PROPORTION OF TIME SLICES WHERE > 70% ENERGY IS SUBMETERED:\n'
s += summary_stats_string(stats['prop_timeslices'])
s += '\n'
fh.write(s)
# dataset.buildings[2].utility.electric.appliances = (
# dataset.buildings[2].utility.electric.remove_channels_from_appliances(
# ['modem_router']))
print('Calculating stats for', ds_name)
ds_stats = dataset.descriptive_stats()
for col_short, col_long in COLUMNS.iteritems():
if col_short in ['energy_submetered', 'proportion_up',
'dropout_rate_ignoring_gaps', 'prop_timeslices']:
fmt = '{:>.0%}'
else:
fmt = '{:>.0f}'
s = ""
if len(dataset.buildings) > 1:
s += summary_stats_string(ds_stats[col_short], sep=""", """,
stat_strings=['min', 'median', 'max'],
minimal=True, fmt=fmt).replace('%', '')
else:
s += fmt.format((ds_stats[col_short][0]))
stats_df[col_long][ds_name] = s
if OUTPUT_LATEX:
print("------------LATEX BEGINS-----------------")
latex = stats_df.to_latex()
latex = latex.replace(' ', '')
n_columns = len(COLUMNS) + 1
latex = latex.replace('l' * n_columns, 'c' * n_columns)
for str_to_replace in ['midrule', 'toprule', 'bottomrule']:
latex = latex.replace(str_to_replace, 'hline')
print(latex)
print("------------LATEX ENDS-------------------")