Building on Linux

Using interal workflow

We provide a workflow script for our CI pipeline/action runner which may be use also local for all platforms.

Prepare workspace:

    mkdir -p gimli
    git clone https://github.com/gimli-org/gimli.git
    # optionally change to the development branch
    git checkout dev

Runing workflow:

    bash gimli/.workflow.sh install

The workflow have several targets which you might try:

    bash gimli/.workflow.sh help

If something goes wrong you can try the manual compilation.

Manual compiling with a virtual environment

If you don’t want to use the conda environment we encourage the use of a virtual environment. Assuming you have a proper build toolchain and the required libraries (see Installation on Ubuntu below) installed.

First we need to create a root directory for our installation, e.g., $HOME/src/gimli and get the source code:

    mkdir -p gimli
    cd gimli
    git clone https://github.com/gimli-org/gimli.git
    # optionally change to the development branch
    git checkout dev
    # create a virtual environment for pyGIMLi, this can be at any place with any name
    # if you want easy VScode support consider gimli/.venv
    deactivate # in case there is another venv active
    python -m venv venv-build --prompt=gimli-build
    # activate the venv
    source venv-build/bin/activate
    # update pip is allways a good idea
    python -m pip install -U pip
    # install gimli as editable with its dependencies into to venv
    pip install -e ./gimli/[build]

We need to compile the C++ part of pyGIMLi, which is currently done with cmake and not with the pip internal build system. We recommend an out of source build:

    mkdir -p build
    cd build
    cmake ../gimli
    make -j 4 gimli
    make pygimli J=4
    cd ..

There is no more need to change the PATH or LD_LIBRARY_PATH. In fact, check to remove any prior changes to these environment variables from older installations. If the build was successful he copy the compiled libraries back into the source tree which is already editable known to the venv, so you can test the pygimli build with:

    python -c 'import pygimli as pg; pg.version()'
    python -c 'import pygimli as pg; print(pg.Report())'

Note, if you test like this, ensure there is no actual path with a name pygimli in your current directory or he will test this path as package instead. This is a sideeffect of the --editable install and such the test will probably fail.

As long nothing changes in the C++ part of pygimli you can just update pyGIMLi but just pulling the latest changes from git. If you end the terminal session you can reactivate the venv with:

    source venv-build/bin/activate

Example Installation on Ubuntu

Last try on Ubuntu 22.04.03 (23-11-14)

    sudo apt-get install build-essential g++ subversion git cmake \
                 python3-dev python3-matplotlib python3-numpy python3-pyqt5 \
                 python3-scipy libboost-all-dev libedit-dev \
                 libsuitesparse-dev libopenblas-openmp-dev libumfpack5 \
                 libomp-dev doxygen \
                 libcppunit-dev clang

Rest see above.

Useful cmake settings

You can rebuild and update all local generated third party software by setting the CLEAN environment variable:

CLEAN=1 cmake ../gimli

Use an alternative C++ compiler:

CC=clang CXX=clang++ cmake ../gimli

Build the library with debug and profiling flags:

cmake ../gimli -DCMAKE_BUILD_TYPE=Debug

Build the library with GCC address sanitizer check:

cmake ../gimli -DCMAKE_BUILD_TYPE=Debug -DASAN=1

Useful make commands

Show more verbose build output:

make VERBOSE=1