Dockerfile

FROM python:3

WORKDIR /
RUN apt-get update && apt-get install -y \
        wget \
        vim \
        git \
        pkg-config \
        build-essential \
        cmake \
        liblapack-dev \
        libblas-dev \
        libboost-math-dev \
        libboost-program-options-dev \
        libboost-test-dev \
        libboost-serialization-dev \
        libarmadillo-dev \
        && rm -rf /var/lib/apt/lists/*

RUN pip install --no-cache-dir \
        numpy scipy scikit-learn pandas \
        Cython setuptools \
        pypandoc \
        pytest pytest-cov codecov nose

# Pot requires Cython to install correctly
RUN pip install --no-cache-dir pot

# OLD CONFIGURATION ##################################
# Install mlpack from source since need newer version than on apt-get repositories
# Installs to /usr/local/include/mlpack, /usr/local/lib/, /usr/local/bin/
# 1ee8268 is most recent commit hash as of 3/19/2018 since templates are only 
#  in master rather than released version
#RUN git clone https://github.com/mlpack/mlpack.git \
#        && cd mlpack \
#        && git checkout 1ee8268 \
#        && mkdir build \
#        && cd build \
#        && cmake -Wno-dev ../ \
#        && make \
#        && make install \
#        && make clean \
#        && cd ../../ \
#        && rm -rf mlpack

# Save linker library path
#ENV LD_LIBRARY_PATH /usr/local/lib/:\$LD_LIBRARY_PATH

# Install anaconda
#ENV ANACONDA_DIR /anaconda
#RUN wget https://repo.continuum.io/archive/Anaconda3-5.1.0-Linux-x86_64.sh \
#        && /bin/bash Anaconda3-5.1.0-Linux-x86_64.sh -b -p $ANACONDA_DIR \
#        && rm Anaconda3-5.1.0-Linux-x86_64.sh
#ENV PATH $ANACONDA_DIR/bin:$PATH

# Install anaconda packages
#RUN conda update -y -n base conda \
#        && conda install -y scikit-learn numpy scipy seaborn matplotlib plotly cython \
#        && conda install -y -c conda-forge pot \
#        && yes | pip install anytree

# Install python 2 kernel environment and required packages for theano/MAF
#SHELL ["/bin/bash", "-c"]
#RUN conda create -y -n python2 python=2 ipykernel \
#        && source activate python2 \
#        && python -m ipykernel install --user \
#        && conda install -y pygpu theano \
#        && conda install -y plotly cython h5py \
#        && source deactivate # Go back to original python 3 environment

# Don't know if this is needed but keeping just in case
#ENV MKL_THREADING_LAYER GNU
# OLD CONFIGURATION ##################################


# From http://singularity.lbl.gov/docs-docker#best-practices
# Must reload linker configuration cache otherwise cannot find shared library when
#  importing into singularity via singularity pull docker://...
RUN ldconfig