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authorPauli Virtanen <pav@iki.fi>2015-12-06 01:08:43 +0200
committerPauli Virtanen <pav@iki.fi>2015-12-06 01:09:38 +0200
commit8e9c91ca962b1cb76c392983740300691a37c3cd (patch)
tree02dd9b287ab54048080b76756fa0ad4f49317fdb /benchmarks
parenta42cb551c5da01072a9dd4b980d6a68620672a4e (diff)
downloadnumpy-8e9c91ca962b1cb76c392983740300691a37c3cd.tar.gz
BENCH: allow benchmark suite to run on Python 3
Diffstat (limited to 'benchmarks')
-rw-r--r--benchmarks/benchmarks/bench_app.py2
-rw-r--r--benchmarks/benchmarks/common.py12
2 files changed, 9 insertions, 5 deletions
diff --git a/benchmarks/benchmarks/bench_app.py b/benchmarks/benchmarks/bench_app.py
index 0e2aca64b..ccf6e4c4a 100644
--- a/benchmarks/benchmarks/bench_app.py
+++ b/benchmarks/benchmarks/bench_app.py
@@ -4,6 +4,8 @@ from .common import Benchmark
import numpy as np
+from six.moves import xrange
+
class LaplaceInplace(Benchmark):
params = ['inplace', 'normal']
diff --git a/benchmarks/benchmarks/common.py b/benchmarks/benchmarks/common.py
index c99b0afb8..e98396bed 100644
--- a/benchmarks/benchmarks/common.py
+++ b/benchmarks/benchmarks/common.py
@@ -1,3 +1,5 @@
+from __future__ import absolute_import, division, print_function
+
import numpy
import random
@@ -26,7 +28,7 @@ TYPES1 = [
# values which will be used to construct our sample data matrices
# replicate 10 times to speed up initial imports of this helper
# and generate some redundancy
-values = [random.uniform(0, 100) for x in range(nx*ny/10)]*10
+values = [random.uniform(0, 100) for x in range(nx*ny//10)]*10
squares = {t: numpy.array(values,
dtype=getattr(numpy, t)).reshape((nx, ny))
@@ -34,16 +36,16 @@ squares = {t: numpy.array(values,
# adjust complex ones to have non-degenerated imagery part -- use
# original data transposed for that
-for t, v in squares.iteritems():
+for t, v in squares.items():
if t.startswith('complex'):
v += v.T*1j
# smaller squares
-squares_ = {t: s[:nxs, :nys] for t, s in squares.iteritems()}
+squares_ = {t: s[:nxs, :nys] for t, s in squares.items()}
# vectors
-vectors = {t: s[0] for t, s in squares.iteritems()}
+vectors = {t: s[0] for t, s in squares.items()}
-indexes = range(nx)
+indexes = list(range(nx))
# so we do not have all items
indexes.pop(5)
indexes.pop(95)