On 6/2/2011 6:07 PM, Keir Rice wrote:
Hi All,
The following function was showing up in my profiles as a large bottle neck:
# Slow version
def RMSBand(self, histogram):
"""Calculates the root-mean-squared value for the given colour stream
histogram."""
intermediateResult = map(lambda (i, h): h*(i**2), zip(histogram,
range(255)))
totalSum = sum(intermediateResult)
# calculate rms
return math.sqrt(totalSum / self.Area())
So after a bit of trial and error I came up with the following function which
is a lot faster:
# Fast version
def RMSBand(self, histogram):
"""Calculates the root-mean-squared value for the given colour stream
histogram."""
totalSum = 0
for i, h in enumerate(histogram):
totalSum += h*(i**2)
# calculate rms
return math.sqrt(totalSum / self.Area())
My question is why is the second method so much faster?
Is it the removal of the extra function calls?
Yes. Map is only 'fast' when one already has a function and is going to
call it repeatedly regardless of the other code. When one has an
expression, wrapping it as a function to use map is surely slower. Have
you tried
return math.sqrt(sum([h*i*i for i,h in enumerate(histogram)])
/ self.Area())
or same without [] brackets?
i*i should be faster than i**2 in any version.
Is it skipping the creation of a list?
A bit.
See Tim's response.
--
Terry Jan Reedy
--
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