class ExpressionTreeEmbedder:
def __init__(self):
self.exprTreeProvider = ExpressionTreeProvider()
self.trackingInfoProvider = TrackingInfoProvider()
self.treeToExprConverter = TreeToExpressionConverter()
def embed(self, context, symbol):
return self._termDocumentMatrixFromContext(context, symbol)
def _termDocumentMatrixFromContext(self, context, symbol):
x = self._termDictsFromContext(context, symbol)
if x == None: return None
(vecs, allNgrams) = x
self.nameDictMapToMatrix = NameDictMapToMatrix()
self.nameDictMapToMatrix.convertFromDicts(vecs, allNgrams)
termDocMatrix = self.nameDictMapToMatrix.termDocumentMatrix
return termDocMatrix
def _termDictsFromContext(self, context, symbol):
vecs = NameToDictMap()
allNgrams = OccurrenceCounter()
context.neighbours.append(context.origin)
for neighbour in context.neighbours:
nOcc = neighbour.nOccurrences
location = neighbour.location
expressions = self.treeToExprConverter.getExpressionsForSymbol(
location, symbol)
# expressions.append('@+$_+@')
# expressions.append('@+EXPR@+$_+@+@')
# print 'FOO %s: %s: %s' % (symbol, location, expressions)
neighbour.setExpressions(expressions)
# add null-vector for function if it does not contain expressions
if len(expressions) == 0:
vecs.add(None, location)
for expr in expressions:
# vecs.add(expr, location, 1.0/nOcc)
# vecs.add(expr, location, 1.0)
vecs.setItem(expr, location, 1.0)
allNgrams.add(expr)
context.neighbours.pop()
if len(vecs.d) == 0 or len(allNgrams.d) == 0:
return None
return (vecs, allNgrams)
def getAllConditionNodes(self):
return self.tree.conditionalNodes
class ExpressionTreeEmbedder:
def __init__(self):
self.exprTreeProvider = ExpressionTreeProvider()
self.trackingInfoProvider = TrackingInfoProvider()
self.treeToExprConverter = TreeToExpressionConverter()
def embed(self, context, symbol):
return self._termDocumentMatrixFromContext(context, symbol)
def _termDocumentMatrixFromContext(self, context, symbol):
x = self._termDictsFromContext(context, symbol)
if x == None: return None
(vecs, allNgrams)= x
self.nameDictMapToMatrix = NameDictMapToMatrix()
self.nameDictMapToMatrix.convertFromDicts(vecs, allNgrams)
termDocMatrix = self.nameDictMapToMatrix.termDocumentMatrix
return termDocMatrix
def _termDictsFromContext(self, context, symbol):
vecs = NameToDictMap()
allNgrams = OccurrenceCounter()
context.neighbours.append(context.origin)
for neighbour in context.neighbours:
nOcc = neighbour.nOccurrences
location = neighbour.location
expressions = self.treeToExprConverter.getExpressionsForSymbol(location, symbol)
# expressions.append('@+$_+@')
# expressions.append('@+EXPR@+$_+@+@')
# print 'FOO %s: %s: %s' % (symbol, location, expressions)
neighbour.setExpressions(expressions)
# add null-vector for function if it does not contain expressions
if len(expressions) == 0:
vecs.add(None, location)
for expr in expressions:
# vecs.add(expr, location, 1.0/nOcc)
# vecs.add(expr, location, 1.0)
vecs.setItem(expr, location, 1.0)
allNgrams.add(expr)
context.neighbours.pop()
if len(vecs.d) == 0 or len(allNgrams.d) == 0:
return None
return (vecs, allNgrams)
def getAllConditionNodes(self):
return self.tree.conditionalNodes
def __init__(self):
self.exprTreeProvider = ExpressionTreeProvider()
self.trackingInfoProvider = TrackingInfoProvider()
self.treeToExprConverter = TreeToExpressionConverter()
def __init__(self):
self.exprTreeProvider = ExpressionTreeProvider()
self.trackingInfoProvider = TrackingInfoProvider()
self.treeToExprConverter = TreeToExpressionConverter()