def _send_output(self) -> None:
"""
Create corpus with scores and output it
"""
if self.corpus is None:
self.Outputs.corpus.send(None)
self.Outputs.selected_documents.send(None)
return
scores, labels = self._gather_scores()
if labels:
d = self.corpus.domain
domain = Domain(
d.attributes,
d.class_var,
metas=d.metas + tuple(
ContinuousVariable(get_unique_names(d, l))
for l in labels),
)
out_corpus = Corpus(
domain,
self.corpus.X,
self.corpus.Y,
np.hstack([self.corpus.metas, scores]),
)
Corpus.retain_preprocessing(self.corpus, out_corpus)
else:
out_corpus = self.corpus
self.Outputs.corpus.send(
create_annotated_table(out_corpus, self.selected_rows))
self.Outputs.selected_documents.send(
out_corpus[self.selected_rows] if self.selected_rows else None)
def _send_output(self, scores: np.ndarray, labels: List[str]) -> None:
"""
Create corpus with scores and output it
"""
if labels:
d = self.corpus.domain
domain = Domain(
d.attributes,
d.class_var,
metas=d.metas + tuple(ContinuousVariable(l) for l in labels),
)
corpus = Corpus(
domain,
self.corpus.X,
self.corpus.Y,
np.hstack([self.corpus.metas, scores]),
)
Corpus.retain_preprocessing(self.corpus, corpus)
self.Outputs.corpus.send(corpus)
elif self.corpus is not None:
self.Outputs.corpus.send(self.corpus)
else:
self.Outputs.corpus.send(None)
