Exemplo n.º 1
0
    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-------------------")