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[MRG+1] Update version dependencies to numpy 1.8.2, scipy 1.13.3 (sci…
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jnothman authored May 23, 2017
1 parent bbf4348 commit db25f57
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Showing 7 changed files with 18 additions and 13 deletions.
7 changes: 4 additions & 3 deletions .travis.yml
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Expand Up @@ -15,6 +15,7 @@ addons:
- python-scipy
- libatlas3gf-base
- libatlas-dev
dist: trusty
env:
global:
# Directory where tests are run from
Expand All @@ -23,17 +24,17 @@ env:
- OPENBLAS_NUM_THREADS=4
matrix:
# This environment tests that scikit-learn can be built against
# versions of numpy, scipy with ATLAS that comes with Ubuntu Precise 12.04
# versions of numpy, scipy with ATLAS that comes with Ubuntu Trusty 14.04
- DISTRIB="ubuntu" PYTHON_VERSION="2.7" CYTHON_VERSION="0.23.4"
COVERAGE=true
# This environment tests the oldest supported anaconda env
- DISTRIB="conda" PYTHON_VERSION="2.7" INSTALL_MKL="false"
NUMPY_VERSION="1.6.2" SCIPY_VERSION="0.11.0" CYTHON_VERSION="0.23"
NUMPY_VERSION="1.8.1" SCIPY_VERSION="0.13.3" CYTHON_VERSION="0.23"
COVERAGE=true
# This environment tests the newest supported anaconda env
# It also runs tests requiring Pandas.
- DISTRIB="conda" PYTHON_VERSION="3.6" INSTALL_MKL="true"
NUMPY_VERSION="1.11.2" SCIPY_VERSION="0.18.1" PANDAS_VERSION="0.19.1"
NUMPY_VERSION="1.11.2" SCIPY_VERSION="0.18.1" PANDAS_VERSION="0.19.2"
CYTHON_VERSION="0.25.2" COVERAGE=true
# This environment use pytest to run the tests. It uses the newest
# supported anaconda env. It also runs tests requiring Pandas.
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4 changes: 2 additions & 2 deletions README.rst
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Expand Up @@ -50,8 +50,8 @@ Dependencies
scikit-learn requires:

- Python (>= 2.7 or >= 3.3)
- NumPy (>= 1.6.1)
- SciPy (>= 0.9)
- NumPy (>= 1.8.1)
- SciPy (>= 0.13.3)

For running the examples Matplotlib >= 1.1.1 is required.

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4 changes: 4 additions & 0 deletions build_tools/travis/install.sh
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Expand Up @@ -45,7 +45,11 @@ if [[ "$DISTRIB" == "conda" ]]; then
${PANDAS_VERSION+pandas=$PANDAS_VERSION}

else
# libgfortran=1 needs to be specified explicitly. This is a work-around for
# https://github.com/ContinuumIO/anaconda-issues/issues/445
# with numpy=1.8.1, python=2.7
conda create -n testenv --yes python=$PYTHON_VERSION pip nose pytest \
libgfortran=1 \
numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
nomkl cython=$CYTHON_VERSION \
${PANDAS_VERSION+pandas=$PANDAS_VERSION}
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4 changes: 2 additions & 2 deletions doc/conf.py
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Expand Up @@ -239,8 +239,8 @@
'reference_url': {
'sklearn': None,
'matplotlib': 'http://matplotlib.org',
'numpy': 'http://docs.scipy.org/doc/numpy-1.6.0',
'scipy': 'http://docs.scipy.org/doc/scipy-0.11.0/reference'},
'numpy': 'http://docs.scipy.org/doc/numpy-1.8.1',
'scipy': 'http://docs.scipy.org/doc/scipy-0.13.3/reference'},
'expected_failing_examples': [
'../examples/applications/plot_stock_market.py']
}
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4 changes: 2 additions & 2 deletions doc/developers/advanced_installation.rst
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Expand Up @@ -36,8 +36,8 @@ Installing an official release
Scikit-learn requires:

- Python (>= 2.7 or >= 3.3),
- NumPy (>= 1.6.1),
- SciPy (>= 0.9).
- NumPy (>= 1.8.1),
- SciPy (>= 0.13.3).


Mac OSX
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4 changes: 2 additions & 2 deletions doc/install.rst
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Expand Up @@ -16,8 +16,8 @@ Installing the latest release
Scikit-learn requires:

- Python (>= 2.7 or >= 3.3),
- NumPy (>= 1.6.1),
- SciPy (>= 0.9).
- NumPy (>= 1.8.1),
- SciPy (>= 0.13.3).

If you already have a working installation of numpy and scipy,
the easiest way to install scikit-learn is using ``pip`` ::
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4 changes: 2 additions & 2 deletions setup.py
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Expand Up @@ -40,8 +40,8 @@

VERSION = sklearn.__version__

SCIPY_MIN_VERSION = '0.9'
NUMPY_MIN_VERSION = '1.6.1'
SCIPY_MIN_VERSION = '0.13.3'
NUMPY_MIN_VERSION = '1.8.1'


# Optional setuptools features
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