Re: mean ans std dev of an array?
- From: Frederic Rentsch <anthra.norell@xxxxxxxxxx>
- Date: Wed, 25 Oct 2006 13:28:36 +0200
SpreadTooThin wrote:
import arrayI quickly fish this out of my functions toolbox. There's got to be faster functions in scipy, though.
a = array.array('f', [1,2,3])
print a.mean()
print a.std_dev()
Is there a way to calculate the mean and standard deviation on array
data?
Do I need to import it into a Numeric Array to do this?
Frederic
(Disclaimer: If you build an air liner or a ocean liner with this and the wings fall off at thirty thousand feet or it turns upside down in the middle of an ocean, respectively of course, I expect a bunch of contingency lawers lining up at my door wanting to sue you on my behalf.)
def standard_deviation (values):
"""
Takes a sequence and returns mean, variance and standard deviation.
Non-values (None) are skipped
"""
import math
mean = _sum_values_squared = _sum_values = 0.0
l = len (values)
i = 0
item_count = 0
while i < l:
value = values [i]
if value != None:
_sum_values += value
_sum_values_squared += value * value
item_count += 1
i += 1
if item_count < 2: # having skipped all Nones
return None, None, None
mean = _sum_values / item_count
variance = (_sum_values_squared - item_count * mean * mean) / (item_count - 1)
if variance < 0.0: variance = 0.0 # Rounding errors can cause minute negative values which would crash the sqrt
standard_deviation = math.sqrt (variance)
return mean, variance, standard_deviation
.
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