Mercurial > hg > nsaunier > traffic-intelligence
comparison scripts/performance-lcss.py @ 998:933670761a57
updated code to python 3 (tests pass and scripts run, but non-executed parts of code are probably still not correct)
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Sun, 27 May 2018 23:22:48 -0400 |
| parents | a850a4f92735 |
| children |
comparison
equal
deleted
inserted
replaced
| 997:4f3387a242a1 | 998:933670761a57 |
|---|---|
| 1 #! /usr/bin/env python | 1 #! /usr/bin/env python3 |
| 2 | 2 |
| 3 import timeit | 3 import timeit |
| 4 | 4 |
| 5 vectorLength = 10 | 5 vectorLength = 10 |
| 6 number = 10 | 6 number = 10 |
| 7 | 7 |
| 8 print('Default Python implementation with lambda') | 8 print('Default Python implementation with lambda') |
| 9 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) | 9 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)) |
| 10 | 10 |
| 11 print('Using scipy distance.cdist') | 11 print('Using scipy distance.cdist') |
| 12 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) | 12 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)) |
