How should I deal with floating numbers that numbers that can get so small that the become zero
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by Tristan Havelick
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Published on 2010-06-08T17:48:44Z
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2010/06/08
17:52 UTC
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floating-point
|numerical-methods
So I just fixed an interesting bug in the following code, but I'm not sure the approach I took it the best:
p = 1
probabilities = [ ... ] # a (possibly) long list of numbers between 0 and 1
for wp in probabilities:
if (wp > 0):
p *= wp
# Take the natural log, this crashes when 'probabilites' is long enough that p ends up
# being zero
try:
result = math.log(p)
Because the result doesn't need to be exact, I solved this by simply keeping the smallest non-zero value, and using that if p ever becomes 0.
p = 1
probabilities = [ ... ] # a long list of numbers between 0 and 1
for wp in probabilities:
if (wp > 0):
old_p = p
p *= wp
if p == 0:
# we've gotten so small, its just 0, so go back to the smallest
# non-zero we had
p = old_p
break
# Take the natural log, this crashes when 'probabilites' is long enough that p ends up
# being zero
try:
result = math.log(p)
This works, but it seems a bit kludgy to me. I don't do a ton of this kind of numerical programming, and I'm not sure if this is the kind of fix people use, or if there is something better I can go for.
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