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kwgoodmankwgoodman
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upgrade to numpy 1.12.1
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‎.travis.yml

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@@ -8,31 +8,31 @@ matrix:
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# test installing bottleneck tarball before installing numpy;
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# start this test first because it takes the longest
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- os: linux
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env: TEST_DEPS="numpy==1.11.3 nose" PYTHON_VERSION="2.7" PYTHON_ARCH="64" TEST_RUN="sdist"
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env: TEST_DEPS="numpy==1.12.1 nose" PYTHON_VERSION="2.7" PYTHON_ARCH="64" TEST_RUN="sdist"
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# flake8
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- os: linux
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env: TEST_DEPS="flake8" PYTHON_VERSION="2.7" PYTHON_ARCH="64" TEST_RUN="style"
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# python 3.4
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- os: linux
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env: TEST_DEPS="numpy==1.11.3 nose" PYTHON_VERSION="3.4" PYTHON_ARCH="64" TEST_RUN="sdist"
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env: TEST_DEPS="numpy==1.12.1 nose" PYTHON_VERSION="3.4" PYTHON_ARCH="64" TEST_RUN="sdist"
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# python 3.5
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- os: linux
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env: TEST_DEPS="numpy==1.11.3 nose" PYTHON_VERSION="3.5" PYTHON_ARCH="64"
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env: TEST_DEPS="numpy==1.12.1 nose" PYTHON_VERSION="3.5" PYTHON_ARCH="64"
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# python 2.7
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- os: osx
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env: TEST_DEPS="numpy==1.11.3 nose" PYTHON_VERSION="2.7" PYTHON_ARCH="64" TEST_RUN="sdist"
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env: TEST_DEPS="numpy==1.12.1 nose" PYTHON_VERSION="2.7" PYTHON_ARCH="64" TEST_RUN="sdist"
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# python 3.4
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- os: osx
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env: TEST_DEPS="numpy==1.11.3 nose" PYTHON_VERSION="3.4" PYTHON_ARCH="64"
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env: TEST_DEPS="numpy==1.12.1 nose" PYTHON_VERSION="3.4" PYTHON_ARCH="64"
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# python 3.5
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- os: osx
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env: TEST_DEPS="numpy==1.11.3 nose" PYTHON_VERSION="3.5" PYTHON_ARCH="64"
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env: TEST_DEPS="numpy==1.12.1 nose" PYTHON_VERSION="3.5" PYTHON_ARCH="64"
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before_install:
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- uname -a

‎README.rst

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@@ -31,42 +31,42 @@ Bottleneck comes with a benchmark suite::
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>>> bn.bench()
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Bottleneck performance benchmark
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Bottleneck 1.3.0.dev0; Numpy 1.11.3
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Bottleneck 1.3.0.dev0; Numpy 1.12.1
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Speed is NumPy time divided by Bottleneck time
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NaN means approx one-fifth NaNs; float64 used
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no NaN no NaN NaN no NaN NaN
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(100,) (1000,1000)(1000,1000)(1000,1000)(1000,1000)
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axis=0 axis=0 axis=0 axis=1 axis=1
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nansum 62.3 1.6 2.0 2.3 2.5
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nanmean 230.7 2.4 2.4 3.5 2.9
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nanstd 260.2 2.1 2.2 2.7 2.6
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nanvar 250.5 2.1 2.3 2.8 2.6
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nanmin 43.3 0.7 1.9 0.8 2.6
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nanmax 45.9 0.7 2.1 1.0 3.3
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median 108.6 1.3 6.2 1.1 6.2
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nanmedian 108.8 5.7 6.6 5.5 6.6
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ss 27.2 1.2 1.2 1.6 1.6
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nanargmin 80.8 3.1 5.4 2.3 6.0
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nanargmax 95.0 3.2 5.4 2.3 6.0
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anynan 18.1 0.3 34.5 0.5 29.6
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allnan 39.7 146.3 126.9 117.0 96.3
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rankdata 56.1 2.5 2.5 2.8 2.9
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nanrankdata 60.8 2.7 2.7 3.1 3.0
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partition 4.1 1.2 1.6 1.0 1.4
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argpartition 3.0 1.1 1.4 1.1 1.6
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replace 12.3 1.4 1.4 1.4 1.4
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push 3363.6 7.6 9.1 20.2 15.7
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move_sum 5046.7 67.5 147.9 192.9 211.7
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move_mean 12277.3 111.8 180.0 252.9 261.6
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move_std 10677.3 97.0 196.6 145.1 258.0
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move_var 13537.3 123.7 235.5 214.7 324.8
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move_min 2474.2 20.0 36.9 23.5 41.9
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move_max 2416.5 20.2 37.1 23.7 42.3
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move_argmin 3876.9 38.9 72.4 39.6 80.7
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move_argmax 3910.2 40.3 73.9 41.2 81.0
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move_median 2087.3 148.2 161.9 148.4 160.7
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move_rank 1312.5 1.8 2.1 2.3 2.7
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nansum 67.3 0.3 0.7 2.5 2.4
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nanmean 194.8 1.9 2.1 3.4 3.1
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nanstd 241.5 1.6 2.1 2.7 2.6
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nanvar 229.7 1.7 2.1 2.7 2.5
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nanmin 34.1 0.7 1.1 0.8 2.6
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nanmax 45.6 0.7 2.7 1.0 3.7
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median 111.0 1.3 5.6 1.0 4.8
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nanmedian 108.8 5.9 6.7 5.6 6.7
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ss 16.3 1.1 1.2 1.6 1.6
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nanargmin 89.2 2.9 5.1 2.2 5.6
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nanargmax 107.4 3.0 5.4 2.2 5.8
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anynan 19.4 0.3 35.0 0.5 29.9
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allnan 39.9 146.6 128.3 115.8 75.6
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rankdata 55.0 2.6 2.3 2.9 2.8
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nanrankdata 59.8 2.8 2.2 3.2 2.5
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partition 4.4 1.2 1.6 1.0 1.4
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argpartition 3.5 1.1 1.4 1.1 1.6
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replace 17.7 1.4 1.4 1.3 1.4
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push 3440.0 7.8 9.5 20.0 15.5
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move_sum 4743.0 75.7 156.1 195.4 211.1
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move_mean 8760.9 116.2 167.4 252.1 258.8
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move_std 8979.9 96.1 196.3 144.0 256.3
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move_var 11216.8 127.3 243.9 225.9 321.4
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move_min 2245.3 20.6 36.7 23.2 42.1
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move_max 2223.7 20.5 37.2 24.1 42.4
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move_argmin 3664.0 48.2 73.3 40.2 83.9
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move_argmax 3916.9 42.0 75.4 41.5 81.2
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move_median 2023.3 166.8 173.7 153.8 154.3
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move_rank 1208.5 1.9 1.9 2.5 2.8
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You can also run a detailed benchmark for a single function using, for
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example, the command::
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Requirements:
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======================== ====================================================
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Bottleneck Python 2.7, 3.4, 3.5; NumPy 1.11.3
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Bottleneck Python 2.7, 3.4, 3.5; NumPy 1.12.1
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Compile gcc, clang, MinGW or MSVC
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Unit tests nose
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======================== ====================================================

‎appveyor.yml

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@@ -3,7 +3,7 @@ shallow_clone: true # download the zip instead of the whole history
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environment:
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global:
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DEPS: "numpy=1.11.3 nose"
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DEPS: "numpy=1.12.1 nose"
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CONDA_VENV: "testy"
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# SDK v7.0 MSVC Express 2008's SetEnv.cmd script will fail if the
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# /E:ON and /V:ON options are not enabled in the batch script

‎tox.ini

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# Tox (http://tox.testrun.org/) configuration
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[tox]
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envlist = py27_np1113, py35_np1113
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envlist = py27_np1121, py35_np1121
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[testenv]
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changedir={envdir}
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commands={envpython} {toxinidir}/tools/test-installed-bottleneck.py {posargs:}
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[testenv:py27_np1113]
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[testenv:py27_np1121]
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basepython = python2.7
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deps =
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nose
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numpy==1.11.3
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numpy==1.12.1
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[testenv:py35_np1113]
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[testenv:py35_np1121]
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basepython = python3.5
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deps =
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nose
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numpy==1.11.3
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numpy==1.12.1
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# Not run by default. Use 'tox -e py27_npmaster' to call it
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[testenv:py27_npmaster]

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