cctbx-base

Computational Crystallography Toolbox

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Computational Crystallography Toolbox

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Table of Contents

Introduction

The Computational Crystallography Toolbox (cctbx) is being developed as the open source component of the Phenix project. The goal of the Phenix project is to advance automation of macromolecular structure determination. Phenix depends on the cctbx, but not vice versa. This hierarchical approach enforces a clean design as a reusable library. The cctbx is therefore also useful for small-molecule crystallography and even general scientific applications.

The cctbx also provides some of the key component of the Olex 2 software. Olex 2 is dedicated to the workflow of small molecule crystallographic studies. It features a powerful and flexible refinement engine, olex2.refine, which is developed as part of the cctbx, in the smtbx top-module.

To maximize reusability and, maybe even more importantly, to give individual developers a notion of privacy, the cctbx is organized as a set of smaller modules. This is very much like a village (the cctbx project) with individual houses (modules) for each family (groups of developers, of any size including one).

The cctbx code base is available without restrictions and free of charge to all interested developers, both academic and commercial. The entire community is invited to actively participate in the development of the code base. A sophisticated technical infrastructure that enables community based software development is provided by GitHub. This service is also free of charge and open to the entire world.

The cctbx is designed with an open and flexible architecture to promote extendability and easy incorporation into other software environments. The package is organized as a set of ISO C++ classes with Python bindings. This organization combines the computational efficiency of a strongly typed compiled language with the convenience and flexibility of a dynamically typed scripting language in a strikingly uniform and very maintainable way.

Use of the Python interfaces is highly recommended, but optional. The cctbx can also be used purely as a C++ class library.

Installation

The easiest way to install cctbx is through the Conda package manager. You can get a full environment from Anaconda or just the conda package manager with the Miniconda installer.

There are two packages available, cctbx and cctbx-base. The cctbx package is cctbx-base with some additional packages (wxpython, pyside2, ipython).

With the conda command available, a new cctbx-base environment named my_env can be created with

conda create -n my_env -c conda-forge cctbx-base

To choose a specific version of Python, add the python package with the specific version

conda create -n my_env -c conda-forge cctbx-base python=3.8

Then the environment can be activated with

conda activate my_env

To install cctbx-base into the currently active environment, use

conda install -c conda-forge cctbx-base

The python package with a specific version can be added to change the version of python that is already installed in the active environment.

Building a development version

  1. Download https://raw.githubusercontent.com/cctbx/cctbx_project/master/libtbx/auto_build/bootstrap.py in the directory where the cctbx and its dependencies shall be installed
  2. Run python bootstrap.py (you may want to run it with the --help option first to discover the available options).
  • For better compatibility with newer operating systems, conda packages can be used for dependencies. Add the --use-conda flag and the command becomes python bootstrap.py --use-conda. This will run the miniconda installer if conda cannot be found. The environment with the dependencies will be located in the conda_base directory. See the description of the --use-conda flag from the --help output for more details.

The installation will take a long while but the script will verbosely describe what it does.

Contributing to the cctbx

For a more detailed description on how to contribute to the cctbx please visit our contribution guide.

Nightly builds

Build Status Conda Version Conda Platforms

A nightly build of the conda packages are available on the cctbx-nightly channel. To use these packages, prepend -c cctbx-nightly as a channel to the commands above. For example, the command to create a new my_env environment would become


conda create -n my_env -c cctbx-nightly -c conda-forge cctbx-base

This will use the cctbx-base package from the cctbx-nightly channel, but pull the remaining dependencies from conda-forge.

Nightly builds are only updated if there are additional commits from the previous build.

Nightly checks of current release and nightly builds (except for Apple Silicon)

A subset of tests is run on the current cctbx-base packages every night (10 pm Pacific) to test compatibility with the latest packages from conda-forge. Additional source files for fable and antlr3 are needed for the tests.

Variantconda-forgecctbx-nightly
linux_64_numpy1.18python3.6.____cpython variant variant
linux_64_numpy1.18python3.7.____cpython variant variant
linux_64_numpy1.18python3.8.____cpython variant variant
linux_64_numpy1.19python3.9.____cpython variant variant
osx_64_numpy1.18python3.6.____cpython variant variant
osx_64_numpy1.18python3.7.____cpython variant variant
osx_64_numpy1.18python3.8.____cpython variant variant
osx_64_numpy1.19python3.9.____cpython variant variant
osx_arm64_python3.8.____cpython variant variant
osx_arm64_python3.9.____cpython variant variant
win_64_numpy1.18python3.6.____cpython variant variant
win_64_numpy1.18python3.7.____cpython variant variant
win_64_numpy1.18python3.8.____cpython variant variant
win_64_numpy1.19python3.9.____cpython variant variant

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