def merge_sentences(input_dict):
"""
Merges the input sentences in XML according to the specified method.
"""
method = input_dict['method']
merged_sen, id_to_sent = set(), {}
ids_list = []
for i, sentsXML in enumerate(input_dict['sentences']):
sents = nlp.parse_def_sentences(sentsXML)
ids = set(map(lambda x: x['id'], sents))
ids_list.append(ids)
# Save the map from id to sentence
for sent in sents:
id_to_sent[sent['id']] = sent
if i == 0 and method != 'intersection_two':
merged_sen = ids
if method == 'union':
merged_sen = merged_sen | ids
elif method == 'intersection':
merged_sen = merged_sen & ids
elif method == 'intersection_two':
# Skip the current set of sentences
# and intersect it with the others.
for ids_alt in ids_list[:i] + ids_list[i+1:]:
# As long as (at least) two sets agree with a sentence it
# will be in the resulting set.
merged_sen = merged_sen | (ids_alt & ids)
return {'merged_sentences': nlp.sentences_to_xml([id_to_sent[sid] for sid in merged_sen])}
def merge_sentences(input_dict):
"""
Merges the input sentences in XML according to the specified method.
"""
method = input_dict['method']
merged_sen, id_to_sent = set(), {}
ids_list = []
for i, sentsXML in enumerate(input_dict['sentences']):
sents = nlp.parse_def_sentences(sentsXML)
ids = set(map(lambda x: x['id'], sents))
ids_list.append(ids)
# Save the map from id to sentence
for sent in sents:
id_to_sent[sent['id']] = sent
if i == 0 and method != 'intersection_two':
merged_sen = ids
if method == 'union':
merged_sen = merged_sen | ids
elif method == 'intersection':
merged_sen = merged_sen & ids
elif method == 'intersection_two':
# Skip the current set of sentences
# and intersect it with the others.
for ids_alt in ids_list[:i] + ids_list[i + 1:]:
# As long as (at least) two sets agree with a sentence it
# will be in the resulting set.
merged_sen = merged_sen | (ids_alt & ids)
return {
'merged_sentences':
nlp.sentences_to_xml([id_to_sent[sid] for sid in merged_sen])
}
def definition_sentences_viewer(request, input_dict, output_dict, widget):
"""
Parses the input XML and displays the definition sentences given as input.
@author: Anze Vavpetic, 2012
"""
sentences = nlp.parse_def_sentences(input_dict['candidates'])
return render(request, 'visualizations/def_sentences.html',{'widget' : widget, 'sentences' : sentences})