class OnlinePMI:
def __init__(self, d, depth, width):
self.d = d
self.sketch = Sketch(depth, width)
self.S = set()
self.V = defaultdict(list)
def pmi(self, x, y):
c = self.sketch.estimate
log2 = lambda x: math.log(x,2)
try:
return log2( c((x,y)) / (c(x) * c(y)) )
except ValueError:
return 0.0
def update(self, B):
for z,y in B:
self.S.add((z,y))
self.sketch.update(z)
self.sketch.update(y)
self.sketch.update((z,y))
# recompute vectors V(x) using current contexts in
# priority queue and {y|S(<z,y>)=1}
xs = set([x for x,y in self.S])
for x in xs:
ys = set.union( set([y for x_,y in self.S if x_ == x]),
set([y for pmi,y in self.V[x]]) )
for y in ys:
if len(self.V[x]) < self.d:
heappush(self.V[x], (self.pmi(x,y), y))
else:
heappushpop(self.V[x], (self.pmi(x,y), y))
class OnlinePMI:
def __init__(self, d, depth, width):
self.d = d
self.sketch = Sketch(depth, width)
self.S = set()
self.V = defaultdict(list)
def pmi(self, x, y):
c = self.sketch.estimate
log2 = lambda x: math.log(x, 2)
try:
return log2(c((x, y)) / (c(x) * c(y)))
except ValueError:
return 0.0
def update(self, B):
for z, y in B:
self.S.add((z, y))
self.sketch.update(z)
self.sketch.update(y)
self.sketch.update((z, y))
# recompute vectors V(x) using current contexts in
# priority queue and {y|S(<z,y>)=1}
xs = set([x for x, y in self.S])
for x in xs:
ys = set.union(set([y for x_, y in self.S if x_ == x]),
set([y for pmi, y in self.V[x]]))
for y in ys:
if len(self.V[x]) < self.d:
heappush(self.V[x], (self.pmi(x, y), y))
else:
heappushpop(self.V[x], (self.pmi(x, y), y))
def __init__(self, d, depth, width):
self.d = d
self.sketch = Sketch(depth, width)
self.S = set()
self.V = defaultdict(list)
def __init__(self, d, depth, width):
self.d = d
self.sketch = Sketch(depth, width)
self.S = set()
self.V = defaultdict(list)
