- Raise an issue here on GitHub.
- Ask a question on the GitHub discussion board
- Look at the contributions guide
- You can also contact us directly at [email protected]
Documentation is currently available online at http://grossfieldlab.github.io/loos/.
These pages include brief summaries of most of the tools available with LOOS, as well as auto-generated class and method level documentation for developers. If you want a local copy of the documentation, you can build it by running doxygen in the main LOOS directory. See the INSTALL file for more details.
Additional documentation is available on the GitHub wiki, including slides from a talk introducing LOOS and brief articles focused on how to use LOOS and how to develop with LOOS.
If you use LOOS in published work, please cite these two papers:
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Romo, T.D., Grossfield, A. "LOOS: An extensible platform for the structural analysis of simulations." 31st Annual International Conference of the IEEE EMBS (2009): 2332-2335
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Romo, T. D., Leioatts, N. and Grossfield, A., "Lightweight Object Oriented Structure Analysis: Tools for building tools to analyze molecular dynamics simulations", J. Comput. Chem. (2014): 2305-2318
Welcome to the GitHub version of LOOS. This repository was created by converting our old SVN repository. The SVN feature branches exist as refs/tags, and appear in GitHub as releases, but they should not be confused with the actual LOOS releases. Those can be found using semantic versioning (e.g. release-2.3.1, release-2.3.0, ...)
We don't release all that often, but we maintain the main branch in a correct and usable state. All development is done in other branches, and merged once we believe it's correct.
For help with installing LOOS, please see the INSTALL.md file. For more details about what has changed in LOOS, see the ChangeLog file.
The structure of this repository changed substantively for the 4.0 release. LOOS is
simultaneously a C++ library for analyzing molecular dynamics simulations, a python
wrapper for that library, and a suite of tools in C++ and python. The main directory
contains a src/ containing the code for the C++ library, Tools/ containing applications
written in C++, and Packages/, which contains several sets of tools with extra code
that don't really fit inside the library. These include Packages/Voronoi, which performs
voronoi analysis on membrane systems, Packages/Clustering, which does clustering of
macromolecules (although there are other clustering tools found elsewhere in LOOS),
Packages/Convergence, which focuses on estimating uncertainty and statistical error,
Packages/ElasticNetworks, which implements a variety of elastic network analysis,
Packages/HydrogenBonds, which does hydrogen bond analysis, Packages/PyLOOS, which contains
tools written in Python, and Packages/User, is a location for users to easily
add new C++ programs. Code for implementing the python bindings (including library
code associated with packages) is found in src/loos. Finally, the top-level share/ directory
contains several data files associated with particular tools (e.g. suite definitions for the
rna_suites tool.
Users looking for simple example programs on which they can base new code can start with Packages/User (for C++ tools) and Packages/PyLOOS (for Python tools). If you are considering writing a new tool, we suggest starting with the python. Obviously, writing python is easier, and generally speaking the performance hit for python vs. C++ isn't prohibitive. You can find resources for developing with LOOS on the GitHub wiki, particularly the Tutorials for Developers.
This release includes a number of fixes related to issues listed on github. Added support for PDBx, mmCIF, and MDTraj-HDF5 formats.
This release includes a number of fixes that address recent issues listed on github. Molecular
order parameter function was also added to AtomicGroup.
LOOS 4.0 is now officially "in production" and can be installable either via conda-forge or by building from source. The first few versions had minor issues either related to the new build system (cmake) or the conda-forge packaging. The current release is 4.0.3 and we recommend that everyone update to this as soon as possible.
If you have been using LOOS prior to 4.0, particulary with the conda build system, then the safest way to upgrade is to recreate your conda environment and install the new conda-forge package. If you chose to build from source, but had previously installed LOOS into your conda environment, then we still recommend that you delete and recreate your environment, then build and install the latest LOOS.
If you have installed a previous version of LOOS from conda-forge, then you can update to the latest with,
conda activate loos
conda update loos
This release involves a complete switch from using SCons for building LOOS to CMake. In general, you should find the build process simpler and configuration easier.
This is a pre-release version, so it should be considered experimental and not used for production. Features may change without notice.
This release has a new and improved facility for reweighting (from Louis Smith), methods for calculating logistic and hard-cutoff lateral densities in AtomicGroup, several new tools for working with clusters in the Clustering package, and dipole computation in membrane_map. Also, a new tool (ocf) for calculating a quantity related to persistence length (also from Louis Smith).
There are also a number of bugfixes:
- Incorrect bonds removed from add_molecule.py
- Fixed units for periodic box read by gmxdump2pdb.pl
- Update to handle new constraints format in gromacs 2020.3+ in gmxdump2pdb.pl
- Fixed charge units when reading Amber prmtop files
- OMG correctly handles 4- and 5-site water models
- In subsetter and merge-traj, the --regex and --scanf flags now imply --sort
There were also a few housekeeping updates. We migrated continuous integration from Travis-CI to GitHub Actions, Louis Smith contributed a much cleaner .gitignore file, and we fixed a potential build-bug where the C++ file generated by swig had different names depending on which compiler/swig version was used. We also added scikit-learn to the list of conda packages installed by conda_build.sh, and fixed a silly bug in its detection of the available compilers.
This is another major release. The biggest change is a totally reworked build system, which should make the process of installing LOOS much easier. In particular, we've greatly improved our support for installing under Conda. See INSTALL.md for detailed instructions.
We've added a new package, Clustering. At the moment, it only has one tool (a fast k-medioids tool), but several others are planned. There are also a number of improvements to other tools.
This is a major release. Most notably, from the development side we've converted from python 2.7 to python 3.x for better long-term interoperability. We've also finally dropped SourceForge as a distribution platform (the old site forwards here), and are deprecating the old mailing lists. Instead, to keep abreast of LOOS development, we suggest following the project on GitHub. Similarly, we recommend raising issues on GitHub as the best way to ask for support, although emailing us directly at [email protected] will also work.
Note: Checking out a beta release means you are checking out a version of LOOS that is under active development. This may include build issues, tools not working, and undocumented "features."
Major changes in LOOS include better DCD handling, support for multiple trajectories in some tools (and at the API level), as well as a new parser for specifying frame ranges for tools.
LOOS now has the ability to handle DCD trajectories with a 0 frame count in the header (fixdcd is no longer required for this case). The count will be estimated based on the model-size and trajectory file size.
A new subclass of Trajectory has been added called MultiTrajectory. A MultiTrajectory object may contain multiple pTraj's and treats them as one giant trajectory. Each sub-trajectory can have its own skip and stride. In addition, there is a MultiTrajOptions class for handling multiple trajectories in a tool.
The parse for specifying ranges has been upgraded to use Boost Spirit. This should make it more robust. In addition, you now no longer need to know the length of a trajectory to use a range. An empty "field" will be filled in with the appropriate value. For example, to skip the first 10 frames, then take every other frame until the end of the trajectory, use: toolname -r 10:2: model.psf trajectory.dcd
NOTE: The short options to subsetter have been changed to be consistent with the new MultiTrajOptions set of options: "-i" is used for stride and "-k" for skip. The long options have not changed.
Additional changes to LOOS include the addition of a new lipid_survival tool and a multi-rmsds tool. Proper (full) support for atom inequalities in Python has been addressed. A new reimaging mode has been added to subsetter (--reimage=zealous) that fixes some issues coming from Gromacs. The output of dibmops has been changed to have a "0" in bins with no data rather than "-1". Finally, a number of bugs have been fixed. See the ChangeLog for more details.
This release includes a number of changes to support our migration to GitHub as well as some important bug fixes and additions.
We have reorganized the LOOS source code so that the core library now resides in the "src" directory. The shared library that's built (along with the python code) is still copied to the top-level LOOS directory.
The Doxygen-based documentation is now handled a little bit differently. When cloning from GitHub, the documentation will be automatically built by SCons. This means doxygen and graphviz are now required to build LOOS. If you download a release from GitHub, then you can also download the pre-built tar file containing the documentation. If this is in the top LOOS source directory, then SCons will see it and unpack it for you. Finally, if you download a release from SourceForge, the the pre-built documentation is bundled with the release. In all cases, you can always find the docs for the current release online at http://grossfieldlab.github.io/loos/ or http://loos.sourceforge.net
Bugs fixed in this release include some important fixes to the OMG, a bug affecting aligner and membrane_map when aligning to a reference structure, making XTCWriter available to PyLOOS, and a few more minor fixes. See the INSTALL file for more details.
New tools in this release include verap, a quick vertical area profile tool, cylindrical-thickness, and inside_helices. New features include providing support for manually mapping molecule names to segids in the gmxdump2pdb tool and support for writing GRO files.
This release of LOOS is a bug-fix release. A bug was discovered in membrane_map that caused the z-axis of all coordinates to be set to 0. This affects height and vector calculations, but not density.
The build system has been changed slightly. Some compilers require multiple environment variables to work correctly. In order to handle these cases, the LOOS build will import all environment variables into SCons before building. This is not the SCons way to do things, however it makes handling these edge cases much easier. In the event that these extra environment variables cause problems, you can revert to a mostly "clean" build environment by editing the SConstruct file. Starting at line 72 with "env = Environment(...)", uncomment the first invocation and comment out the second one.
In addition, improvements were made to the documentation.
This release of LOOS comes with a number of major changes, most related to PyLOOS. A detailed description of these changes is available in the new "what's new in PyLOOS" section of the documentation, and is listed in the "Quick Links" off the main page.
NUMPY IS NOW REQUIRED FOR BUILDING PYLOOS. For Linux users, this will just be a package install. For Mac users, the system numpy will be used. See the INSTALL file for more information.
PyLOOS has been reorganized and new trajectory handling classes have been added. All Python-based components of PyLOOS are now in the loos.pyloos module. The new trajectory classes are easier to use than the old PyTraj classes (they no longer require you to explicitly wrap a loos.Trajectory object). In addition, you can combine multiple trajectories into a large "virtual" trajectory. The frames of the composite trajectory can be iteratively aligned (a la aligner) or aligned to a reference structure. See the documentation for pyloos under the Namespace tab or search for Trajectory.
Additional PyLOOS changes include bug fixes for the iterativeAlignment function. The splitting functions in AtomicGroup now return a Python list rather than an AtomicGroupVector. Coordinates can be extracted from an AtomicGroup or a Trajectory as a NumPy matrix. An SVD/PCA function has also been added to PyLOOS. All old PyLOOS functions that begin or end with Py are now deprecated and will be removed in the next release. These include PyTraj, PyAlignedTraj, and iterativeAlignmentPy. Finally, a k-means clustering program (using PyLOOS) has been added. Also, we've added a new package (Voronoi), which will help users analyze membrane/membrane protein simulations.
There are a number of significant non-PyLOOS changes as well. An "index" keyword has been added to pick atoms based on their position in a model (rather than atom id). The rmsds tool (all-to-all RMSD) has been significantly optimized and can now be run multithreaded. The default is to use only a single thread. If you built LOOS with a multithreaded math library, be aware of possible conflicts (though that shouldn't happen with rmsds). Last, but not least, a number of minor bug fixes are included. See the ChangeLog file or the change log in the documentation for more details.