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annotate scripts/performance-lcss.py @ 962:64259b9885bf

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verbose option to print classification information (more to add)
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 06 Nov 2017 21:25:41 -0500
parents a850a4f92735
children 933670761a57
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730
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
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1 #! /usr/bin/env python
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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2
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
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3 import timeit
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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4
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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5 vectorLength = 10
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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6 number = 10
a850a4f92735 added performance script comparing lcss using cdist with default
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7
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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8 print('Default Python implementation with lambda')
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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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)
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
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10
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
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11 print('Using scipy distance.cdist')
a850a4f92735 added performance script comparing lcss using cdist with default
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
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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)