def mass_weightedUnion(L):
"A list of (mapping, weight) pairs -> their weightedUnion IIBucket."
if len(L) < 2:
return _trivial(L)
# Balance unions as closely as possible, smallest to largest.
merge = NBest(len(L))
for x, weight in L:
merge.add((x, weight), len(x))
while len(merge) > 1:
# Merge the two smallest so far, and add back to the queue.
(x, wx), dummy = merge.pop_smallest()
(y, wy), dummy = merge.pop_smallest()
dummy, z = weightedUnion(x, y, wx, wy)
merge.add((z, 1), len(z))
(result, weight), dummy = merge.pop_smallest()
return result
def mass_weightedUnion(l_):
"A list of (mapping, weight) pairs -> their weightedUnion IIBucket."
if len(l_) < 2:
return _trivial(l_)
# Balance unions as closely as possible, smallest to largest.
merge = NBest(len(l_))
for x, weight in l_:
merge.add((x, weight), len(x))
while len(merge) > 1:
# Merge the two smallest so far, and add back to the queue.
(x, wx), dummy = merge.pop_smallest()
(y, wy), dummy = merge.pop_smallest()
dummy, z = weightedUnion(x, y, wx, wy)
merge.add((z, 1), len(z))
(result, weight), dummy = merge.pop_smallest()
return result
def testMany(self):
import random
inputs = [(-i, i) for i in range(50)]
reversed_inputs = inputs[:]
reversed_inputs.reverse()
# Test the N-best for a variety of n (1, 6, 11, ... 50).
for n in range(1, len(inputs) + 1, 5):
expected = inputs[-n:]
expected.reverse()
random_inputs = inputs[:]
random.shuffle(random_inputs)
for source in inputs, reversed_inputs, random_inputs:
# Try feeding them one at a time.
nb = NBest(n)
for item, score in source:
nb.add(item, score)
self.assertEqual(len(nb), n)
self.assertEqual(nb.capacity(), n)
self.assertEqual(nb.getbest(), expected)
# And again in one gulp.
nb = NBest(n)
nb.addmany(source)
self.assertEqual(len(nb), n)
self.assertEqual(nb.capacity(), n)
self.assertEqual(nb.getbest(), expected)
for i in range(1, n + 1):
self.assertEqual(nb.pop_smallest(), expected[-i])
self.assertRaises(IndexError, nb.pop_smallest)
def testMany(self):
import random
inputs = [(-i, i) for i in range(50)]
reversed_inputs = inputs[:]
reversed_inputs.reverse()
# Test the N-best for a variety of n (1, 6, 11, ... 50).
for n in range(1, len(inputs)+1, 5):
expected = inputs[-n:]
expected.reverse()
random_inputs = inputs[:]
random.shuffle(random_inputs)
for source in inputs, reversed_inputs, random_inputs:
# Try feeding them one at a time.
nb = NBest(n)
for item, score in source:
nb.add(item, score)
self.assertEqual(len(nb), n)
self.assertEqual(nb.capacity(), n)
self.assertEqual(nb.getbest(), expected)
# And again in one gulp.
nb = NBest(n)
nb.addmany(source)
self.assertEqual(len(nb), n)
self.assertEqual(nb.capacity(), n)
self.assertEqual(nb.getbest(), expected)
for i in range(1, n+1):
self.assertEqual(nb.pop_smallest(), expected[-i])
self.assertRaises(IndexError, nb.pop_smallest)
