Installing PyCBC

This document explains how to set up a virtual environment to install PyCBC either for development or use in a production analysis with a release. The code build will be a standard Python install which requires that the installation directory containing the Python libraries is accessible at runtime. Some executables also use weave for just-in-time compilation of code at runtime. These executables require a gcc and Python build environment on the execution machine.

If you wish to run PyCBC executables on a machine that does not have the required environment, then you must use PyInstaller to build bundled versions of the executables. Documentation on doing this is available on the page Building Bundled Executables.

Note

PyCBC uses the fork and pull model for development. If you wish to develop PyCBC, then you will need an account on GitHub. Once you have set up your account you should follow the instructions to fork a repository to fork the ligo-cbc/pycbc repository into your own account. From your own fork, you can follow the GitHub flow model to develop and maintain the code. For each new feature or bug fix, you should create a new branch to develop the feature. You can then create a pull request so that the PyCBC maintainers can review and merge your changes into the official repository.

These instructions walk you through the process of

Setting up a virtual environment for installing PyCBC

The recommended way of installing PyCBC is to use pip within a Python Virtual Environment. Virtualenv isolates PyCBC and its dependencies from the system environment and installing with pip ensures that PyCBC picks up the correct dependencies. The following instructions will create a working virtual environment into which you can install PyCBC.

Make sure that you have at least version 13.1.1 of virtualenv. To do this, you can run the command below and check the return result. Run this command and note the result:

virtualenv --version

If this returns virtualenv: command not found or the command returns a lower version than 13.1.1 (as is the case with Scientific Linux 6 systems) then follow the instructions for setting virtualenv at:

Once you have a version virtualenv installed that is at least as new as 13.1.1 you can continue with these instructions.

Unset your current PYTHONPATH so that you do not inherit any packages that may conflict with your installation. To do this, run the command:

unset PYTHONPATH

By default, virtualenv will modify your shell prompt so that it prepends the name of the virtual environment. This can be very useful to make sure that you are developing in the virtual environment, or if you have several virtual environments, so it is not recommended to disable this. However, if you do not want your prompt changed, then you can set

VIRTUAL_ENV_DISABLE_PROMPT=True

Before running the command to create the new virtual environment.

Next, you need to choose a directory name where you’d like to make your virtual environment, and then make it. In this example, we use ${HOME}/pycbc-dev but this can be changed to any path that you you have write access to, except for ${HOME}/.local as that will cause conflicts with pip.

Note

It is very important that your virtualenv version is at least 13.1.1 before continuing. Read the preceding instructions if you are not sure how to check this, or need to upgrade virtualenv.

You first set up a new virtual environment. A virtual environment is defined by a directory path that will hold the contents of the virtual environment. In this example, we chose ~/src/pycbc although you can change this to whatever you like by changing the command below. Initialize the virtual environment by running the command:

virtualenv ~/src/pycbc

You can create as many different virtual environments as you like, as long as they all have different paths.

Note

Do not run virtualenv twice with the same path as it will overwrite the existing virtual environment with a new one, destroying the environment.

To enter your virtual environment run the command (replacing the string ~/src/pycbc/ if you chose a different path)

source ~/src/pycbc/bin/activate

After running the activate script, you will now be in your virtual environment, and so you can install packages without conflicting with either the system build, or other builds that you may have sitting around. You may install other programs and libraries, such as lalsuite (Installing lalsuite for PyCBC), into this virtual environment. The activate script also sets the environment variable ${VIRTUAL_ENV} to the full path to your virtual environment.

Note

Python implements a per user site packages directory to install packages in the user’s home directory. By default this is ~/.local but the location is controlled by the PYTHONUSERBASE environment variable. If you make use of the ~/.local directory, you should add the line export PYTHONUSERBASE=${VIRTUAL_ENV}/.local to the end of your virtual environment’s activate script to prevent conflicts. Similarly, pip caches data in the directory ~/.caches/pip. To prevent conflicts with this directory, you can add the line export XDG_CACHE_HOME=${VIRTUAL_ENV}/.cache to the virtual environment activate script so that pip uses a cache that is specific to the virtual environment.

To leave this virtual environment type

deactivate

which will return you to a regular shell.

Installing lalsuite into a virtual environment

Enter the virtual environment that you wish to use for PyCBC development by sourcing the activate script, for example

source ~/src/pycbc/bin/activate

Note

CentOS 6 provides a buggy version of the HDF5 library, so you will need to install a newer version into your virtual environment. If you are using a CentOS 6 cluster, you must install HDF5. If you are using another cluster, then this step is optional.

If you are running on a Scientific Linux 6 cluster, you need to install the HDF5 library. To do this, run the commands:

mkdir -p $VIRTUAL_ENV/src
cd $VIRTUAL_ENV/src
pip install "nose>=1.0.0"
curl https://support.hdfgroup.org/ftp/HDF5/releases/hdf5-1.8/hdf5-1.8.12/src/hdf5-1.8.12.tar.gz > hdf5-1.8.12.tar.gz
tar -zxvf hdf5-1.8.12.tar.gz
cd hdf5-1.8.12
./configure --prefix=$VIRTUAL_ENV/opt/hdf5-1.8.12
make install
HDF5_DIR=$VIRTUAL_ENV/opt/hdf5-1.8.12 pip install h5py

Note

On a Scientific Linux 6 or Scientific Linux 7 system, if you do not upgrade the version of setuptools that is in your virtual environment, then the PyCBC install will fail to process the required dependencies.

Make sure your versions of pip and setuptools are up to date by running the command:

pip install --upgrade pip
pip install --upgrade setuptools

Install unittest2, python-cjson, and numpy with the command:

pip install "numpy>=1.6.4" unittest2 python-cjson Cython decorator

Once you have these packages installed, you can now install lalsuite following the instructions at:

Installing PyCBC in a virtual environment

Enter the virtual environment that you wish to use for PyCBC development by sourcing the activate script, for example

source ~/src/pycbc/bin/activate

Next install the Pegasus WMS python libraries needed to build the workflows with the command:

pip install http://download.pegasus.isi.edu/pegasus/4.7.3/pegasus-python-source-4.7.3.tar.gz

To query the new Advanced LIGO and Advanced Virgo Segment Database, you will need to install the dqsegdb tools. Install the 1.4.1 pre-release of these tools, run the command:

pip install dqsegdb

For uploading triggers to GraceDB at the end of the workflow you will need to have the gracedb client tools installed. The latest release is in pip

pip install ligo-gracedb

You now need to decide whether you want to install a release of PyCBC or an editable version of the source code from a git repository for development.

Installing a released version of PyCBC

Note

Make sure you have run the commands in the section Installing lalsuite into a virtual environment above to install unittest2 before installing PyCBC.

Releases of PyCBC are available from the PyPi PyCBC page. To install the latest release run the command

pip install PyCBC

To install an older version, use the pip version specifier.

To install a release of the code from GitHub, determine the tag of the release that you want to install from the list of PyCBC tags. This example installs the v1.1.0 release. If you want to install a different release, change the command below accordingly:

pip install git+https://github.com/ligo-cbc/pycbc@v1.1.0#egg=pycbc

Installing source from GitHub for development

Note

Make sure you have run the command in the section Installing lalsuite into a virtual environment above to install unittest2 before installing PyCBC.

To install and editable version of PyCBC you need to have forked PyCBC to your own account and know the URL of your fork. This can be obtained from the clone URL on your GitHub repository page. This example uses the URL git@github.com:your-username-here/pycbc.git which you should change to the URL of your fork of PyCBC on GitHub.

Note

There are two main authentication schemes for GitHub: SSH and HTTPS. The examples below use URLs containing git@github.com, which assumed that you are usingg SSH authentication. If you have not already enabled ssh keys on your GitHub account, you can follow the GitHub instructions for setting up ssh keys to set this up. Alternatively, you can use the HTTPS connection method, where git@github.com: is replaced with https://github.com/. See the GitHub documentation on URLs for more information. You can also read the pip git instructions for more details on how to install a branch or a specific tag.

Install the PyCBC source code from the GitHub URL using the command:

pip install -e git+git@github.com:your-username-here/pycbc.git#egg=pycbc

This will fetch the PyCBC source and will also install all the listed dependencies. The -e option to pip creates a directory called ${VIRTUAL_ENV}/src/pycbc with a git checkout which is fully editable. To prevent pip from removing this source directory run the command

rm -f ${VIRTUAL_ENV}/src/pip-delete-this-directory.txt

You can then make changes to your PyCBC source code in the directory ${VIRTUAL_ENV}/src/pycbc

You can also use the repository created by pip as your working repository, creating branches, commits, and pull requests as you need to. To keep your repository in sync with the ligo-cbc/pycbc repository, you can read the GitHub instructions that explain how to sync a fork of a repository to keep it up-to-date with the upstream repository..

Note

The version of PyCBC that is checked out will be on the master branch. To track a remote branch from your GitHub repository, run the command

git branch --set-upstream branch_name origin/branch_name

git checkout branch_name

where branch_name is the name of the branch that you want to track.

To build and install any changes that you make to the source code in your virtual environment, run the command

python setup.py install

from the PyCBC source directory in ${VIRTUAL_ENV}/src/pycbc

Note

PyCBC no longer requires an installation of the pycbc-pylal package. If you are running a workflow that needs code from this package, you will need to manually install it with pip install pycbc-pylal.

Building and Installing Documentation

To build the documentation from your virtual environment, first make sure that you have Sphinx and the required helper tools installed with

pip install "Sphinx>=1.5.0"
pip install sphinx-rtd-theme
pip install sphinxcontrib-programoutput

To generate the documentation and push it to your personal GitHub pages, first create a branch names gh-pages, if you do not already have one. Follow the GitHub branch instructions to do this.

To build and publish the documentation, run the following commands from the top-level of your PyCBC source tree, replacing github-username with your GitHub user name:

git clone git@github.com:github-username/pycbc.git _gh-pages
cd _gh-pages
git checkout gh-pages
git rm -rf *
git commit -a -m "flush documentation"
cd ..
python setup.py build_gh_pages
cd _gh-pages
git add --all
git commit -a -m "documentation update"
git push origin gh-pages

The documentation will then be visible at http://github-username.github.io/pycbc/latest/html where github-username should be replaced with your GitHub username.

Note

Be careful with the git rm -rf * command as if you run it in the wrong directory you can delete the contents of your git repository. If you do this by accident, you can use git reset to undo the commit.

For more details on building and maintaining the documentation under GitHub project pages, see

Use of Intel MKL Optimized FFT libraries

PyCBC has the ability to use optimized FFT libraries such as FFTW and MKL. If MKL is the correct library for your platform, you can add the script that sets up the MKL environment to you virtualenv activate script with the command

echo 'source /opt/intel/bin/compilervars.sh intel64' >> ${VIRTUAL_ENV}/bin/activate

changing the path to the compilervars.sh script appropriately for your cluster.

Graphics Processing Unit support with CUDA

PyCBC has the ability to accelerate its processing using CUDA. To take advantage of this, follow the instructions linked below to install the CUDA dependencies.