Mercurial > hg > nsaunier > traffic-intelligence
view scripts/performance-lcss.py @ 1136:30171d4fd3df Tertuis-Ou-draogo/movingpy-issue-22-from-etienne-beauchamp-1584900380975
moving.py [Issue #22 from Etienne Beauchamp In annotationTool Correction]
| author | Tertuis Ouédraogo <tertuis95@gmail.com> |
|---|---|
| date | Sun, 22 Mar 2020 18:06:22 +0000 |
| parents | 933670761a57 |
| children |
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#! /usr/bin/env python3 import timeit vectorLength = 10 number = 10 print('Default Python implementation with lambda') print(timeit.timeit('lcss.compute(random_sample(({},2)), random_sample(({}, 2)))'.format(vectorLength, vectorLength*2), setup = 'from utils import LCSS; from numpy.random import random_sample; lcss = LCSS(similarityFunc = lambda x,y: (abs(x[0]-y[0]) <= 0.1) and (abs(x[1]-y[1]) <= 0.1));', number = number)) print('Using scipy distance.cdist') print(timeit.timeit('lcss.compute(random_sample(({},2)), random_sample(({}, 2)))'.format(vectorLength, vectorLength*2), setup = 'from utils import LCSS; from numpy.random import random_sample; lcss = LCSS(metric = "cityblock", epsilon = 0.1);', number = number))
