def rough_scores():
proposals = l.scored_proposals()
consensus = l.get_batch_coverage()
for x in proposals:
x['auto_group'] = ''
if x['batchgroup']:
x['consensus'] = consensus[x['batch_id']][x['id']]
else:
x['consensus'] = -1
return render_template('admin/rough_scores.html',
proposals=proposals,
groups=l.raw_list_groups())
def rough_scores():
proposals = l.scored_proposals()
consensus = l.get_batch_coverage()
for x in proposals:
x['auto_group'] = ''
if x['batchgroup']:
x['consensus'] = consensus[x['batch_id']][x['id']]
else:
x['consensus'] = -1
return render_template('admin/rough_scores.html',
proposals=proposals,
groups=l.raw_list_groups())
def sample_grouping():
min_normed_score = int(request.values.get('min_normed_score', '80'))
min_nominations = int(request.values.get('min_nominations', '5'))
group_size = int(request.values.get('group_size', '20'))
cutoff = float(request.values.get('cutoff', '0.75'))
scored_proposals = {x['id']:x for x in l.scored_proposals()}
groups = l.get_proposals_auto_grouped(topics_count=group_size,
cutoff=cutoff)
return render_template('sample_grouping.html',
group_size=group_size,
min_normed_score=min_normed_score,
min_nominations=min_nominations,
scored_proposals=scored_proposals,
groups=groups,
cutoff=cutoff)
def rough_scores():
return render_template('rough_scores.html', proposals=l.scored_proposals())
