--- a/scripts/performance-lcss.py	Fri Jun 01 10:43:23 2018 -0400
+++ b/scripts/performance-lcss.py	Fri Jun 01 10:47:49 2018 -0400
@@ -1,4 +1,4 @@
-#! /usr/bin/env python
+#! /usr/bin/env python3
 
 import timeit
 
@@ -6,7 +6,7 @@
 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(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)
+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))