if is_in:
current_true_positives.append((span_start, span_end))
# Predict
# TODO: Read archives for every group, var name: stations (code for archive path get from model integration)
# TODO: Then read archives, trim archives
# TODO: Write function which takes time span and arrays of current_true_positives time spans and returns
# array of timespans to which i should cut the base timespan.
progress_bar = ProgressBar()
progress_bar.set_length(60)
progress_bar.set_empty_character('.')
progress_bar.set_progress_character('=')
progress_bar.set_current_progress_char('>')
progress_bar.set_prefix_expression(
'Station {station} out of {n_stations} [')
progress_bar.set_postfix_expression('] - Batch: {start} - {end}')
progress_bar.set_prefix_arg('n_stations', len(stations))
progress_bar.set_max(stations=len(stations),
streams=1.,
traces=1.,
batches=1.,
inter=1.)
for i_station, archive_list in enumerate(stations):
progress_bar.set_progress(i_station, level='stations')
