def generateNGramCandidatesToChange(sentence, MAX_NGRAMS):
final_Sentence = ''
token_position = 0
for w, t in sentence:
#if t not in ('NNP', 'NNPS') and token_position == 0:
#final_Sentence=final_Sentence + ' ' + w.lower() + delim + t + delim + str(token_position)
final_Sentence = final_Sentence + ' ' + w + delim + t + delim + str(
token_position)
token_position = token_position + 1
#print final_Sentence.strip()
candidates = OrderedDict()
n = [i + 1 for i in xrange(MAX_NGRAMS)]
for i in n:
#print i
nGrams = ngrams(final_Sentence.strip().split(), i)
candidates[i] = list(nGrams)
#total_candidates_to_change=sum(len(v) for v in candidates.itervalues())
#print 'Total candidates that can be changed ~~ ',total_candidates_to_change
paraphraseCandidateList = []
for i in n:
ngramlist = candidates[i]
for ngram in ngramlist:
#print ngrams
candidateObject = CandidateObject(ngram, i)
paraphraseCandidateList.append(candidateObject)
#print candidateObject.wordObjectList[0].token
# sequence=' '.join(gram.split('/')[0] for gram in ngrams)
#indices=[int(gram.split('/')[2]) for gram in ngrams]
#print sequence, indices
return paraphraseCandidateList
def nodecoords(tree, sentence, highlight):
"""
Produce coordinates of nodes on a grid.
Objective:
- Produce coordinates for a non-overlapping placement of nodes and
horizontal lines.
- Order edges so that crossing edges cross a minimal number of previous
horizontal lines (never vertical lines).
Approach:
- bottom up level order traversal (start at terminals)
- at each level, identify nodes which cannot be on the same row
- identify nodes which cannot be in the same column
- place nodes into a grid at (row, column)
- order child-parent edges with crossing edges last
Coordinates are (row, column); the origin (0, 0) is at the top left;
the root node is on row 0. Coordinates do not consider the size of a
node (which depends on font, &c), so the width of a column of the grid
should be automatically determined by the element with the greatest
width in that column. Alternatively, the integer coordinates could be
converted to coordinates in which the distances between adjacent nodes
are non-uniform.
Produces tuple (nodes, coords, edges, highlighted) where:
- nodes[id]: Tree object for the node with this integer id
- coords[id]: (n, m) coordinate where to draw node with id in the grid
- edges[id]: parent id of node with this id (ordered dictionary)
- highlighted: set of ids that should be highlighted
"""
def findcell(m, matrix, startoflevel, children):
"""
Find vacant row, column index for node ``m``.
Iterate over current rows for this level (try lowest first)
and look for cell between first and last child of this node,
add new row to level if no free row available.
"""
candidates = [a for _, a in children[m]]
minidx, maxidx = min(candidates), max(candidates)
leaves = tree[m].leaves()
center = scale * sum(leaves) // len(leaves) # center of gravity
if minidx < maxidx and not minidx < center < maxidx:
center = sum(candidates) // len(candidates)
if max(candidates) - min(candidates) > 2 * scale:
center -= center % scale # round to unscaled coordinate
if minidx < maxidx and not minidx < center < maxidx:
center += scale
if ids[m] == 0:
startoflevel = len(matrix)
for rowidx in range(startoflevel, len(matrix) + 1):
if rowidx == len(matrix): # need to add a new row
matrix.append([
vertline if a not in (corner, None) else None
for a in matrix[-1]
])
row = matrix[rowidx]
i = j = center
if len(children[m]) == 1: # place unaries directly above child
return rowidx, next(iter(children[m]))[1]
elif all(a is None or a == vertline
for a in row[min(candidates):max(candidates) + 1]):
# find free column
for n in range(scale):
i = j = center + n
while j > minidx or i < maxidx:
if i < maxidx and (matrix[rowidx][i] is None
or i in candidates):
return rowidx, i
elif j > minidx and (matrix[rowidx][j] is None
or j in candidates):
return rowidx, j
i += scale
j -= scale
raise ValueError('could not find a free cell for:\n%s\n%s'
'min=%d; max=%d' %
(tree[m], minidx, maxidx, dumpmatrix()))
def dumpmatrix():
"""Dump matrix contents for debugging purposes."""
return '\n'.join('%2d: %s' % (n, ' '.join(('%2r' % i)[:2]
for i in row))
for n, row in enumerate(matrix))
leaves = tree.leaves()
if not all(isinstance(n, int) for n in leaves):
raise ValueError('All leaves must be integer indices.')
if len(leaves) != len(set(leaves)):
raise ValueError('Indices must occur at most once.')
if not all(0 <= n < len(sentence) for n in leaves):
raise ValueError('All leaves must be in the interval 0..n '
'with n=len(sentence)\ntokens: %d indices: '
'%r\nsentence: %s' %
(len(sentence), tree.leaves(), sentence))
vertline, corner = -1, -2 # constants
tree = tree.copy(True)
for a in tree.subtrees():
a.sort(key=lambda n: min(n.leaves()) if isinstance(n, Tree) else n)
scale = 2
crossed = set()
# internal nodes and lexical nodes (no frontiers)
positions = tree.treepositions()
maxdepth = max(map(len, positions)) + 1
childcols = defaultdict(set)
matrix = [[None] * (len(sentence) * scale)]
nodes = {}
ids = dict((a, n) for n, a in enumerate(positions))
highlighted_nodes = set(n for a, n in ids.items()
if not highlight or tree[a] in highlight)
levels = dict((n, []) for n in range(maxdepth - 1))
terminals = []
for a in positions:
node = tree[a]
if isinstance(node, Tree):
levels[maxdepth - node.height()].append(a)
else:
terminals.append(a)
for n in levels:
levels[n].sort(
key=lambda n: max(tree[n].leaves()) - min(tree[n].leaves()))
terminals.sort()
positions = set(positions)
for m in terminals:
i = int(tree[m]) * scale
assert matrix[0][i] is None, (matrix[0][i], m, i)
matrix[0][i] = ids[m]
nodes[ids[m]] = sentence[tree[m]]
if nodes[ids[m]] is None:
nodes[ids[m]] = '...'
highlighted_nodes.discard(ids[m])
positions.remove(m)
childcols[m[:-1]].add((0, i))
# add other nodes centered on their children,
# if the center is already taken, back off
# to the left and right alternately, until an empty cell is found.
for n in sorted(levels, reverse=True):
nodesatdepth = levels[n]
startoflevel = len(matrix)
matrix.append([
vertline if a not in (corner, None) else None
for a in matrix[-1]
])
for m in nodesatdepth: # [::-1]:
if n < maxdepth - 1 and childcols[m]:
_, pivot = min(childcols[m], key=itemgetter(1))
if (set(a[:-1] for row in matrix[:-1]
for a in row[:pivot] if isinstance(a, tuple)) &
set(a[:-1] for row in matrix[:-1]
for a in row[pivot:] if isinstance(a, tuple))):
crossed.add(m)
rowidx, i = findcell(m, matrix, startoflevel, childcols)
positions.remove(m)
# block positions where children of this node branch out
for _, x in childcols[m]:
matrix[rowidx][x] = corner
# assert m == () or matrix[rowidx][i] in (None, corner), (
# matrix[rowidx][i], m, str(tree), ' '.join(sentence))
# node itself
matrix[rowidx][i] = ids[m]
nodes[ids[m]] = tree[m]
# add column to the set of children for its parent
if m != ():
childcols[m[:-1]].add((rowidx, i))
assert len(positions) == 0
# remove unused columns, right to left
for m in range(scale * len(sentence) - 1, -1, -1):
if not any(isinstance(row[m], (Tree, int)) for row in matrix):
for row in matrix:
del row[m]
# remove unused rows, reverse
matrix = [
row for row in reversed(matrix)
if not all(a is None or a == vertline for a in row)
]
# collect coordinates of nodes
coords = {}
for n, _ in enumerate(matrix):
for m, i in enumerate(matrix[n]):
if isinstance(i, int) and i >= 0:
coords[i] = n, m
# move crossed edges last
positions = sorted([a for level in levels.values() for a in level],
key=lambda a: a[:-1] in crossed)
# collect edges from node to node
edges = OrderedDict()
for i in reversed(positions):
for j, _ in enumerate(tree[i]):
edges[ids[i + (j, )]] = ids[i]
return nodes, coords, edges, highlighted_nodes
