def top_documents_widget(dataset, word):
w = Widget('Top Documents', 'words/top_documents')
docwords = word.documentword_set.filter(
document__dataset=dataset)
total = reduce(lambda x, dw: x + dw.count, docwords, 0)
docs = sorted([WordSummary(dw.document.filename, float(dw.count) / total)
for dw in docwords])
w['chart_url'] = get_chart(docs)
return w
def top_documents_widget(dataset, word):
w = Widget('Top Documents', 'words/top_documents')
docs = Document.objects.raw('''select doc.*,count(*) as count
from visualize_wordtype as type, visualize_wordtoken as token, visualize_document as doc
where type.type=%s and token.type_id=type.id and token.document_id=doc.id group by doc.id order by count desc''', [word.type])
total = float(sum([doc.count for doc in docs]))
doc_summaries = [WordSummary(doc.filename, float(doc.count) / total) for doc in docs]
w['chart_url'] = get_chart(doc_summaries)
return w
def top_topics_widget(analysis, word):
w = Widget('Top Topics', 'words/top_topics')
topicwords = word.topicword_set.filter(
topic__analysis=analysis)
total = reduce(lambda x, tw: x + tw.count, topicwords, 0)
topics = sorted([WordSummary(tw.topic.name, float(tw.count) / total)
for tw in topicwords])
topics.sort()
w['chart_url'] = get_chart(topics)
return w
def top_topics_widget(analysis, document):
w = Widget('Top Topics', 'documents/top_topics')
topicdocs = document.documenttopic_set.filter(topic__analysis=analysis)
total = 0
topics = []
for topicdoc in topicdocs:
total += topicdoc.count
for topicdoc in topicdocs:
t = WordSummary(topicdoc.topic.name, float(topicdoc.count) / total)
topics.append(t)
topics.sort()
w['chart_address'] = get_chart(topics)
return w
def top_topics_widget(session, analysis, word):
w = Widget('Top Topics', 'words/top_topics')
analysis_tokens = word.tokens.filter(topics__analysis=analysis)
total = float(analysis_tokens.count())
topicwords = analysis_tokens.values('topics').annotate(count=Count('topics')).order_by('-count')
ns = current_name_scheme(session, analysis)
topics = list()
for count_obj in topicwords:
pct = count_obj['count'] / total
topic = Topic.objects.get(id=count_obj['topics'])
name = topic_name_with_ns(topic, ns)
topics.append(WordSummary(name,pct))
# topics = [WordSummary(Topic.objects.get(id=x['topics']).name, x['count']/total) for x in topicwords]
# topicwords = word.topicword_set.filter(
# topic__analysis=analysis)
# total = reduce(lambda x, tw: x + tw.count, topicwords, 0)
# topics = sorted([WordSummary(tw.topic.name, float(tw.count) / total)
# for tw in topicwords])
# topics.sort()
w['chart_url'] = get_chart(topics)
return w
def top_words_chart_widget(words):
w = Widget('Top Words', 'attributes/top_words_chart')
w['chart_address'] = get_chart(words)
return w
def word_chart_widget(words):
w = Widget("Word Chart", 'topics/word_chart')
w['chart_address'] = get_chart(words)
return w
