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# Various statistics functions.
#
# Written by Konrad Hinsen <hinsen@ibs.ibs.fr>
# last revision: 1997-6-1
#
import Numeric
#
# Univariate statistics functions
#
def average(data):
data = Numeric.array(data)
return Numeric.add.reduce(data)/len(data)
def variance(data):
data = Numeric.array(data)
return Numeric.add.reduce((data-average(data))**2)/(len(data)-1)
def standardDeviation(data):
data = Numeric.array(data)
return Numeric.sqrt(variance(data))
def histogram(data, nbins, range = None):
data = Numeric.array(data, Numeric.Float)
if range is None:
min = Numeric.minimum.reduce(data)
max = Numeric.maximum.reduce(data)
else:
min, max = range
data = Numeric.repeat(data,
Numeric.logical_and(Numeric.less_equal(data, max),
Numeric.greater_equal(data,
min)))
bin_width = (max-min)/nbins
data = Numeric.floor((data - min)/bin_width).astype(Numeric.Int)
histo = Numeric.add.reduce(Numeric.equal(
Numeric.arange(nbins)[:,Numeric.NewAxis], data), -1)
histo[-1] = histo[-1] + Numeric.add.reduce(Numeric.equal(nbins, data))
bins = min + bin_width*(Numeric.arange(nbins)+0.5)
return Numeric.transpose(Numeric.array([bins, histo]))
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