def test2(self):
inputFile = "tests/1.xml"
inputFile = th.collapseToTmp(inputFile)
print "Unary-collapsed tree at %s" % inputFile
self.maxDiff = None
penn = shared.ma_util.readPenn("tests/1-binarization-yv.ptb").next()
tiger = project.readTiger(inputFile).next()
res = project.getMappingFromNodeIDToSentiment(tiger, penn)
expected = yaml.load(open("tests/1.newcollapse.expected.yml"))
self.assertEqual(self._mapToString(res), self._mapToString(expected))
def main(inputFile, annotations, alignment, targetFile, output,
stripTargetIDPrefix, applyParentSentiment, projectRootSentiment,
alignTypes):
"""
Projects sentiment labels from a source tree to a target tree
using an alignment between source and target nodes.
@param inputFile {basestring} Filename of source treebank in TigerXML
format
@param annotations {basestring} Filename of treebank with sentiment labels
in Penn Treebank format
@param alignment {basestring} Filename of mapping between source and
target nodes in Stockholm Treealigner format
@param targetFile {basestring} Filename of target treebank in TigerXML
format
@param output {basestring} Filename for resulting output file
@param stripTargetIDPrefix {boolean} Whether to strip alphabetic prefixes
from node IDs in target tree
@param applyParentSentiment {boolean} Whether to infer sentiment labels
for unaligned nodes from ancestor nodes
@param projectRootSentiment {boolean} Whether to perform implicit alignment
between source and target root nodes if unaligned
@param alignTypes {list} Which link types to include: good, fuzzy or both
"""
mapping = {}
logger.info("Loading alignment.")
alignment = readAlignment(alignment, alignTypes)
logger.info("Done loading alignment.")
logger.info("Alignment source was: %s", alignment["source"])
logger.info("Alignment target was: %s", alignment["target"])
alignment = alignment["alignment"]
logger.info("Collapsing unary nodes for source file")
# Now get some node statistic from source/input side
# This means we have to load the file again in tigerHelper
inputHelper = TigerHelper(inputFile)
print ("Target has %s nodes (T, NT) before unary-collapsing nodes"
% inputHelper.count)
del inputHelper
# Now overwrite inputFile variable!
inputFile = th.collapseToTmp(inputFile, alignment.keys())
logger.info("Wrote unary-collapsed source tigerXML to %s", inputFile)
logger.info("Extracting mapping from source ID to sentiment value.")
for (tigerSentence, pennSentence) in itertools.izip_longest(
readTiger(inputFile), ma_util.readPenn(annotations),
fillvalue="LIST_LENGTH_NOT_EQUAL"):
mapping.update(
getMappingFromNodeIDToSentiment(tigerSentence, pennSentence))
logger.info("Done extracting mapping.")
fh = open(targetFile, "r")
target = etree.parse(fh)
fh.close()
tigerHelper = TigerHelper(target, stripTargetIDPrefix)
print "Target has %s nodes (T, NT)" % tigerHelper.count
logger.info("Applying mapping to target.")
applyMappingToTarget(
mapping, alignment, tigerHelper, stripTargetIDPrefix)
print ("Source nodes with sentiment, not in alignment: %s"
% countSourceNotInAlignment)
print ("Nodes with sentiment and alignment, but not found "
+ "in target tree: %s" % countTargetNotFound)
print ("Sentiment label projected using alignment for %s nodes"
% countMappingApplied)
logger.info("Done applying mapping.")
logger.info("Unary-collapsing nodes in target tree.")
tigerHelper.collapseUnary()
logger.info("Done collapsing unary nodes.")
print ("After collapsing unary nodes, Target has %s nodes (T, NT)"
% tigerHelper.count)
logger.info("Fixing up remaining nodes")
# Need to map root sentiment before looking up parent sentiment
# so we can use the new information
if projectRootSentiment:
logger.info("Projecting root sentiment for unaligned root nodes.")
mapRootSentiment(ma_util.readPenn(annotations), tigerHelper)
logger.info("Done projecting root sentiment.")
if applyParentSentiment:
logger.info("Using parent lookup for nodes with"
+ "unknown sentiment values.")
(modTree, count) = tigerHelper.applyParentSentimentValue()
print "Applied parent sentiment value for %s nodes" % count
else:
logger.info("Using default for nodes with unknown sentiment values.")
(modTree, count) = tigerHelper.applyDefaultSentimentValue()
print "Applied default sentiment value for %s nodes" % count
logger.info("Done fixing up remaining nodes.")
logger.info("Saving to disk...")
tigerHelper.tree.write(output)
logger.info("Done!")
