def __call__(self, it, importanceratio):
assert it.repLength >= self.W
Xn = it.representative[:self.W]
weight = self.Zncalculator(Xn) * importanceratio
# If we are sampling unique W-mers rather than occurrences
# we must multiply by the number of occurrences
if self.unique:
weight *= it.numOccurrences
self.cb(arrayforXn(Xn, weight))
def __call__(self, it, importanceratio):
assert it.repLength >= self.W
Xn = it.representative[:self.W]
weight = self.Zncalculator(Xn) * importanceratio
# If we are sampling unique W-mers rather than occurrences
# we must multiply by the number of occurrences
if self.unique:
weight *= it.numOccurrences
self.cb(arrayforXn(Xn, weight))
def __call__(self, it):
# Always go further than the root
if 0 == it.repLength:
return True
# Don't go any further if we have an unknown base
if UNKNOWNBASE in parentEdgeLabelUpToW(it, self.W):
return False
if it.repLength >= self.W:
# Get the word
Xn = it.representative[:self.W]
# Calculate Zn
Zn = self.Zncalculator(Xn)
# Update sums
self.cb(arrayforXn(Xn, Zn * it.numOccurrences))
# Have gone deep enough in index, truncate traversal
return False
else:
# Keep descending
return True
def __call__(self, it):
# Always go further than the root
if 0 == it.repLength:
return True
# Don't go any further if we have an unknown base
if UNKNOWNBASE in parentEdgeLabelUpToW(it, self.W):
return False
if it.repLength >= self.W:
# Get the word
Xn = it.representative[:self.W]
# Calculate Zn
Zn = self.Zncalculator(Xn)
# Update sums
self.cb(arrayforXn(Xn, Zn * it.numOccurrences))
# Have gone deep enough in index, truncate traversal
return False
else:
# Keep descending
return True
