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- #!/bin/bash
- # Based on a script from scikit-learn
- # This script is meant to be called by the "install" step defined in
- # .travis.yml. See http://docs.travis-ci.com/ for more details.
- # The behavior of the script is controlled by environment variabled defined
- # in the .travis.yml in the top level folder of the project.
- set -e
- # Fix the compilers to workaround avoid having the Python 3.4 build
- # lookup for g++44 unexpectedly.
- export CC=gcc
- export CXX=g++
- if [[ "$DISTRIB" == "conda_min" ]]; then
- # Deactivate the travis-provided virtual environment and setup a
- # conda-based environment instead
- deactivate
- # Use the miniconda installer for faster download / install of conda
- # itself
- wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh \
- -O miniconda.sh
- chmod +x miniconda.sh && ./miniconda.sh -b -p $HOME/miniconda
- export PATH=/home/travis/miniconda/bin:$PATH
- conda config --set always_yes yes
- conda update --yes conda
- # Configure the conda environment and put it in the path using the
- # provided versions
- conda create -n testenv --yes python=$PYTHON_VERSION pip nose coverage \
- six=$SIX_VERSION numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION
- source activate testenv
- conda install libgfortran=1
- if [[ "$INSTALL_MKL" == "true" ]]; then
- # Make sure that MKL is used
- conda install --yes --no-update-dependencies mkl
- else
- # Make sure that MKL is not used
- conda remove --yes --features mkl || echo "MKL not installed"
- fi
- elif [[ "$DISTRIB" == "conda" ]]; then
- # Deactivate the travis-provided virtual environment and setup a
- # conda-based environment instead
- deactivate
- # Use the miniconda installer for faster download / install of conda
- # itself
- wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh \
- -O miniconda.sh
- chmod +x miniconda.sh && ./miniconda.sh -b -p $HOME/miniconda
- export PATH=/home/travis/miniconda/bin:$PATH
- conda config --set always_yes yes
- conda update --yes conda
- # Configure the conda environment and put it in the path using the
- # provided versions
- conda create -n testenv --yes python=$PYTHON_VERSION pip nose coverage six=$SIX_VERSION \
- numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION pandas=$PANDAS_VERSION scikit-learn
- source activate testenv
- if [[ "$INSTALL_MKL" == "true" ]]; then
- # Make sure that MKL is used
- conda install --yes --no-update-dependencies mkl
- else
- # Make sure that MKL is not used
- conda remove --yes --features mkl || echo "MKL not installed"
- fi
- if [[ "$COVERAGE" == "true" ]]; then
- pip install coveralls
- fi
- python -c "import pandas; import os; assert os.getenv('PANDAS_VERSION') == pandas.__version__"
- elif [[ "$DISTRIB" == "ubuntu" ]]; then
- deactivate
- # Create a new virtualenv using system site packages for numpy and scipy
- virtualenv --system-site-packages testenv
- source testenv/bin/activate
- pip install nose
- pip install coverage
- pip install numpy==$NUMPY_VERSION
- pip install scipy==$SCIPY_VERSION
- pip install six==$SIX_VERSION
- pip install quantities
- fi
- if [[ "$COVERAGE" == "true" ]]; then
- pip install coveralls
- fi
- # pip install neo==0.3.3
- wget https://github.com/NeuralEnsemble/python-neo/archive/master.tar.gz
- tar -xzvf master.tar.gz
- pushd python-neo-master
- python setup.py install
- popd
- pip install .
- python -c "import numpy; import os; assert os.getenv('NUMPY_VERSION') == numpy.__version__"
- python -c "import scipy; import os; assert os.getenv('SCIPY_VERSION') == scipy.__version__"
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