def base_snapshot_timespan(topics_id):
# find the timespan matching this one in the base snapshot (ie. with no foci_id)
snapshots_id, timespans_id, foci_id, q = filters_from_args(request.args)
base_snapshot_timespans = apicache.cached_topic_timespan_list(user_mediacloud_key(), topics_id,
snapshots_id=snapshots_id, foci_id=None)
timespan = apicache.topic_timespan(topics_id, snapshots_id, foci_id, timespans_id) # the selected timespan
for t in base_snapshot_timespans:
if apicache.is_timespans_match(timespan, t):
return t
raise ValueError("Can't find a timespan in the base snapshot matching the one specified")
def topic_focal_set_sentences_compare(topics_id, focal_sets_id):
snapshots_id, timespans_id, foci_id, q = filters_from_args(request.args)
all_focal_sets = topic_focal_sets(user_mediacloud_key(), topics_id,
snapshots_id)
# need the timespan info, to find the appropriate timespan with each focus
base_snapshot_timespans = cached_topic_timespan_list(
user_mediacloud_key(), topics_id, snapshots_id=snapshots_id)
# if they have a focus selected, we need to find the appropriate overall timespan
if foci_id is not None:
timespan = topic_timespan(topics_id, snapshots_id, foci_id,
timespans_id)
for t in base_snapshot_timespans:
if timespans_match(timespan, t):
base_timespan = t
else:
base_timespan = None
for t in base_snapshot_timespans:
if t['timespans_id'] == int(timespans_id):
base_timespan = t
logger.info('base timespan = %s', timespans_id)
if base_timespan is None:
return json_error_response("Couldn't find the timespan you specified")
# iterate through to find the one of interest
focal_set = None
for fs in all_focal_sets:
if int(fs['focal_sets_id']) == int(focal_sets_id):
focal_set = fs
if focal_set is None:
return json_error_response('Invalid Focal Set Id')
# collect the sentence counts for each foci
for focus in focal_set['foci']:
# find the matching timespan within this focus
snapshot_timespans = cached_topic_timespan_list(
user_mediacloud_key(),
topics_id,
snapshots_id=snapshots_id,
foci_id=focus['foci_id'])
timespan = None
for t in snapshot_timespans:
if timespans_match(t, base_timespan):
timespan = t
logger.info('matching in focus %s, timespan = %s',
focus['foci_id'], t['timespans_id'])
if timespan is None:
return json_error_response(
'Couldn\'t find a matching timespan in the ' + focus.name +
' focus')
data = topic_sentence_counts(user_mediacloud_key(),
topics_id,
snapshots_id=snapshots_id,
timespans_id=timespan['timespans_id'],
foci_id=focus['foci_id'])
focus['sentence_counts'] = data
return jsonify(focal_set)
def topic_focal_set_split_stories_compare(topics_id, focal_sets_id):
snapshots_id, timespans_id, foci_id, q = filters_from_args(request.args)
# need the timespan info, to find the appropriate timespan with each focus
base_snapshot_timespans = apicache.cached_topic_timespan_list(
user_mediacloud_key(), topics_id, snapshots_id=snapshots_id)
# if they have a focus selected, we need to find the appropriate overall timespan
if foci_id is not None:
timespan = apicache.topic_timespan(topics_id, snapshots_id, foci_id,
timespans_id)
for t in base_snapshot_timespans:
if apicache.is_timespans_match(timespan, t):
base_timespan = t
else:
base_timespan = None
for t in base_snapshot_timespans:
if t['timespans_id'] == int(timespans_id):
base_timespan = t
logger.info('base timespan = %s', timespans_id)
if base_timespan is None:
return json_error_response("Couldn't find the timespan you specified")
# iterate through to find the one of interest
focal_set = apicache.topic_focal_set(user_mediacloud_key(), topics_id,
snapshots_id, focal_sets_id)
if focal_set is None:
return json_error_response('Invalid Focal Set Id')
# collect the story split counts for each foci
timespans = apicache.matching_timespans_in_foci(topics_id, base_timespan,
focal_set['foci'])
for idx in range(0, len(timespans)):
data = apicache.topic_split_story_counts(
user_mediacloud_key(),
topics_id,
snapshots_id=snapshots_id,
timespans_id=timespans[idx]['timespans_id'])
focal_set['foci'][idx]['split_story_counts'] = data
return jsonify(focal_set)