nsaunier/traffic-intelligence: python/utils.py comparison

forgotten update of histogram class

author	Nicolas Saunier <nicolas.saunier@polymtl.ca>
date	Mon, 12 Apr 2010 11:18:19 -0400
parents	48e56179c39e
children	1a2ac2d4f53a

comparison

equal deleted inserted replaced

-:388a5a25fe92
+:8cafee54466f
 return result
 class histogram:
 '''Class to represent a sample of a distribution for a continuous random variable
 with the number of observations for each interval'''
+def __init__(self, categories, counts):
+self.categories = categories
+self.counts = counts
+def mean(self):
+result = 0.
+for i,c in zip(self.categories, self.counts):
+result += c*(i[1]+i[0])/2
+return result/sum(self.counts)
+def var(self, mean = None):
+if not mean:
+m = self.mean()
+else:
+m = mean
+result = 0.
+for i,c in zip(self.categories, self.counts):
+mid = (i[1]+i[0])/2
+result += c*(mid - m)*(mid - m)
+return result/(self.nSamples()-1)
+def nSamples(self):
+return sum(self.counts)
+def referenceCounts(self, cdf):
+'''cdf is a cumulative distribution function
+returning the probability of the variable being less that x'''
+# refCumulativeCounts = [0]#[cdf(self.categories[0][0])]
+#         for inter in self.categories:
+#             refCumulativeCounts.append(cdf(inter[1]))
+refCumulativeCounts = [cdf(inter[1]) for inter in self.categories[:-1]]
+refProba = [refCumulativeCounts[0]]
+for i in xrange(1,len(refCumulativeCounts)):
+refProba.append(refCumulativeCounts[i]-refCumulativeCounts[i-1])
+refProba.append(1-refCumulativeCounts[-1])
+refCounts = [p*self.nSamples() for p in refProba]
+return refCounts, refProba
 #########################
 # maths section
 #########################

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