Mercurial > hg > nsaunier > traffic-intelligence

comparison trafficintelligence/utils.py @ 1267:ad60e5adf084

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cleaned interaction categorization and added stationary category
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Wed, 29 May 2024 09:52:42 -0400
parents 77fbd0e2ba7d
children bae8de98406f
comparison
equal deleted inserted replaced
1266:ebb18043616e 1267:ad60e5adf084
136 k = round(norm.ppf(0.5+percentConfidence/200., 0, 1), 2) 136 k = round(norm.ppf(0.5+percentConfidence/200., 0, 1), 2)
137 else: # use Student 137 else: # use Student
138 k = round(t.ppf(0.5+percentConfidence/200., nSamples-1), 2) 138 k = round(t.ppf(0.5+percentConfidence/200., nSamples-1), 2)
139 e = k*stdev/sqrt(nSamples) 139 e = k*stdev/sqrt(nSamples)
140 if printLatex: 140 if printLatex:
141 print('${0} \pm {1}\\frac{{{2}}}{{\sqrt{{{3}}}}}$'.format(mean, k, stdev, nSamples)) 141 print('${0} \\pm {1}\\frac{{{2}}}{{\\sqrt{{{3}}}}}$'.format(mean, k, stdev, nSamples))
142 return mean-e, mean+e 142 return mean-e, mean+e
143 143
144 def computeChi2(expected, observed): 144 def computeChi2(expected, observed):
145 '''Returns the Chi2 statistics''' 145 '''Returns the Chi2 statistics'''
146 return sum([((e-o)*(e-o))/float(e) for e, o in zip(expected, observed)]) 146 return sum([((e-o)*(e-o))/float(e) for e, o in zip(expected, observed)])