def ownAZannot(export_annots=False):
"""
Annotates each sentence using own classifier
"""
from minerva.az.az_cfc_classification import AZannotator
annot=AZannotator("trained_az_classifier.pickle")
papers=cp.Corpus.listPapers(max_results=sys.maxint)
writer=AZPrimeWriter()
writer.save_pos_tags=True
## papers=papers[:1]
progress=ProgressIndicator(True, len(papers),False)
print("Producing annotations for SciDocs...")
for guid in papers:
doc=cp.Corpus.loadSciDoc(guid)
annot.annotateDoc(doc)
if export_annots:
output_filename=os.path.join(cp.Corpus.paths.output, doc.metadata["guid"]+".annot.txt")
output_file=open(output_filename,"w")
for sentence in doc.allsentences:
output_file.write(sentence.get("az","")+"\n")
output_file.close()
else:
cp.Corpus.saveSciDoc(doc)
progress.showProgressReport("Annotating -- %s" % guid)
def testLabels():
"""
"""
guid="f7921eed-89bc-4f38-a794-7c9a5878a7ee"
writer=AZPrimeWriter()
writer.save_pos_tags=True
doc=cp.Corpus.loadSciDoc(guid)
writer.write(doc, os.path.join(cp.Corpus.paths.output, doc.metadata["guid"]+".pos.xml"))
def exportSciXML():
"""
Exports all scidocs with the selected collection_id to AZPrime XML in the output dir of the corpus
"""
papers=cp.Corpus.listPapers(max_results=sys.maxint)
writer=AZPrimeWriter()
writer.save_pos_tags=True
## papers=papers[3894:]
progress=ProgressIndicator(True, len(papers),False)
print("Exporting SciXML files")
for guid in papers:
doc=cp.Corpus.loadSciDoc(guid)
if len(doc.allsentences) < 1:
continue
writer.write(doc, os.path.join(cp.Corpus.paths.output, doc.metadata["guid"]+".pos.xml"))
cp.Corpus.saveSciDoc(doc)
progress.showProgressReport("Exporting -- %s" % guid)
