Installation

If you’re just planning to use the code, you’ll want to perform a basic installation. If you’re planning to develop for the code, or if you want to stay on the bleeding edge, then you should perform a developer installation.

Basic Installation

There are two recommended approaches for a basic installation: conda-based, or pip-based. Using conda is much easier, and will continue to be easier for anything else you install. However, the disadvantage is that you must put your entire Python environment under conda. If you already have a highly customized Python environment, you might prefer the pip install. But otherwise, we highly recommend installing conda, either using the full Ananconda distribution or the smaller-footprint miniconda. Once conda is installed and in your path, installation is as simple as:

conda install -c conda-forge contact_map

which tells conda to get contact_map from the conda-forge channel, which manages our conda-based installation recipe.

If you would prefer to use pip, that takes a few extra steps, but will work on any Python setup (conda or not). Because of some weirdness in how pip handles packages (such as MDTraj) that have a particular types of requirements from Numpy, you should install Cython and Numpy separately, so the whole install is:

pip install cython
pip install numpy
pip install contact_map

If you already have Numpy installed, you may need to re-install it with pip install -U --force-reinstall numpy. Note that some systems may require you to preface pip install commands with sudo (depending on where Python keeps its packages).

Developer installation

If you plan to work with the source, or if you want to stay on the bleeding edge, you can install a version so that your downloaded/cloned version of this git repository is the live code your Python interpreter sees. We call that a “developer installation.”

This is a three-step process:

  1. Download or clone the repository. If you plan to contribute changes back to the repository, please fork it on GitHub and then clone your fork. Otherwise, you can download or clone the main repository. You can follow GitHub’s instructions on how to do this, and apply those steps to forking our repository at http://github.com/dwhswenson/contact_map.

  2. Install the requirements. This can be done using either pip or conda. First, change into the directory for the repository. You should see setup.py and requirements.txt (among many other things) in that directory. Using conda:

    conda install -y --file requirements.txt
    

    Or, using pip:

    pip install cython
    pip install numpy
    pip install -r requirements.txt
    

    In some cases, you may need to add -U --force-reinstall to the Numpy step.

  3. Install the package. Whether you get the requirements with pip or with conda, you can install the package (again, from the directory containing setup.py) with:

    pip install -e .
    

    The -e means that the installation is “editable” (developer version; the stuff in this directory will be the live code your Python interpreted uses) and the . tells it to find setup.py in the current directory.

Additional functionality

Installing some additional packages will immediately enable additional features in contact_map. To get all the functionality, install the packages in optional_installs.txt, either with pip install -r optional_installs.txt or conda install -y --file optional_installs.txt.

Specific extra functionality that can be enabled:

  • plotting tools (install matplotlib)
  • parallelization (install dask, distributed)

Testing your installation

However you have installed it, you should test that your installation works. To do so, first check that the new package can be imported. This can be done with

python -c "import contact_map"

If your Python interpreter can find the newly-installed package, that should exit without complaint.

For a more thorough check that everything works, you should run our test suite. This can be done by installing pytest (using either pip or conda) and then running the command:

py.test --pyargs contact_map -v

This will run the tests on the installed version of contact_map. All tests should either pass or skip.