New upstream version 1.0.0-beta.19+dfsg

language: python

python:

  - "2.7"

  - "3.5"

  - "3.6"

  - 2.7

  - 3.4

  - 3.5

  - 3.6

  # also includes 3.7 (see below)

env:

  - NUMPY_VERSION=""  WITH_COVERAGE=1 # environment to test with the latest version of NumPy

  - NUMPY_VERSION=""  # environment to test with the latest version of NumPy

  - NUMPY_VERSION="<1.13"

matrix:

  # support for python 3.7 is rather awkward via Travis CI

  # https://github.com/travis-ci/travis-ci/issues/9815

  include:

    - python: 3.7

      dist: xenial

      sudo: true

      env: NUMPY_VERSION=""

    - python: 3.7

      dist: xenial

      sudo: true

      env: NUMPY_VERSION="<1.13"

  exclude:

      # for older python versions only test the latest versions of NumPy

      - python: 2.7

        env: NUMPY_VERSION="<1.13"

      - python: 3.4

        env: NUMPY_VERSION="<1.13"

      - python: 3.5

        env: NUMPY_VERSION="<1.13"

before_install:

  - phantomjs --version

  - wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh

  - chmod +x miniconda.sh

  - wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh && chmod +x miniconda.sh

  - ./miniconda.sh -b

  - export PATH=/home/travis/miniconda2/bin:$PATH

  # Update conda itself

  - conda update --yes conda

install:

  - conda create --yes -n env_name python=$TRAVIS_PYTHON_VERSION pip numpy${NUMPY_VERSION} 'scipy>=0.17.0' matplotlib pandas nose flake8 pep8 jupyter

  - source activate env_name

  - pip install https://github.com/google/closure-linter/archive/master.zip

  - pip install 'sphinx<1.6' sphinx-bootstrap-theme coverage coveralls

  # install lockfile before to prevent a failure in travis

  - pip install 'lockfile>=0.10.2'

  - conda create --yes -n travis python=$TRAVIS_PYTHON_VERSION pip numpy${NUMPY_VERSION} 'scipy>=0.17.0' matplotlib pandas flake8 pep8 jupyter coverage cython

  - source activate travis

  - conda install -c conda-forge phantomjs --yes

  # scikit-learn has to be pinned down due to a bug: https://github.com/scikit-learn/scikit-learn/issues/12671

  - pip install https://github.com/google/closure-linter/archive/master.zip 'sphinx<1.6' sphinx-bootstrap-theme coveralls 'scikit-learn==0.19.2' --no-binary scikit-learn

  - pip install -e '.[all]' --verbose

  - npm install -g jsdoc

script:

  - flake8 emperor/*.py tests/*.py scripts/*.py setup.py

  # we can only run gjslint in a python 2.7.x environment

  - if [[ $TRAVIS_PYTHON_VERSION == 2.7 ]]; then gjslint --custom_jsdoc_tags 'module,function,constructs,alias,default' 'emperor/support_files/js/*.js' 'tests/javascript_tests/*.js'; fi

  # execute the full test suite

  - python tests/all_tests.py

  # we just check coverage in the latest version of NumPy

  - if [ ${WITH_COVERAGE} ]; then nosetests emperor --with-coverage --cover-package=emperor --cover-inclusive tests; fi

  - coverage run tests/all_tests.py; coverage report

  - make -C doc html

after_success:

  - coveralls

## Usage

You can start using Emperor through [QIIME2](https://qiime2.org)'s [interfaces](https://docs.qiime2.org/2.0.6/interfaces/) (the command line interface or the graphical user interface), or alternatively using the Python interface (compatible with the Jupyter notebook, see [this example](http://nbviewer.jupyter.org/github/biocore/emperor/blob/new-api/examples/keyboard.ipynb)). For more detalis, refer to our [online documentation](http://emperor.microbio.me/uno/).

You can start using Emperor through [QIIME2](https://qiime2.org)'s [interfaces](https://docs.qiime2.org/2018.8/interfaces/) (the command line interface or the graphical user interface), or alternatively using the Python interface (compatible with the Jupyter notebook, see [this example](http://nbviewer.jupyter.org/github/biocore/emperor/blob/new-api/examples/keyboard.ipynb)). For more detalis, refer to our [online documentation](http://emperor.microbio.me/uno/).

## Publications

- [EMPeror: a tool for visualizing high-throughput microbial community data](https://www.ncbi.nlm.nih.gov/pubmed/24280061). GigaScience, 2013.

- [Bringing the Dynamic Microbiome to Life with Animations](https://www.ncbi.nlm.nih.gov/pubmed/28081445). Cell Host & Microbe, 2016.