|
| Operating System | LOOS Support | PyLOOS Support | Notes |
|---|---|---|---|
| Fedora 18 | yes | yes | Deprecated |
| Fedora 19 | yes | yes | Deprecated |
| Fedora 20 | yes | yes | Deprecated |
| Fedora 21 | yes | yes | Deprecated |
| Fedora 22 | yes | yes | Deprecated |
| Fedora 23 | yes | yes | Deprecated |
| Fedora 24 | yes | yes | Deprecated |
| Fedora 25 | yes | yes | Deprecated |
| Fedora 26 | yes | yes | Deprecated |
| Fedora 27 | yes | yes | Deprecated |
| Fedora 28 | yes | yes | |
| Fedora 29 | yes | yes | |
| Ubuntu 12.04 LTS | yes | yes | Deprecated |
| Ubuntu 14.04 LTS | yes | yes | Deprecated |
| Ubuntu 15.04 | yes | yes | Deprecated |
| Ubuntu 15.10 | yes | yes | Deprecated |
| Ubuntu 16.04 LTS | yes | yes | Deprecated |
| Ubuntu 18.04 | yes | yes | |
| Debian 7.8 | yes | yes | Deprecated |
| Debian 8.1 | yes | yes | Deprecated |
| Debian 9.8 | yes | yes | |
| Centos 7 | yes | yes | |
| OpenSUSE 12 | yes | yes | Deprecated |
| OpenSUSE 13 | yes | yes | Deprecated |
| OpenSUSE 15 | yes | yes | |
| MacOS X | yes | yes | See OS notes |
- Deprecated: We used to support this configuration, but no longer test it. It may still work.
- Unsupported: We have built LOOS in the past using this configuration, but do not regularly test it and provide no direct support for using it.
As of LOOS 3.0, we also support building inside a Conda environment. This is the preferred way to build on MacOS, and on any Linux environment that is not supported.
LOOST requires BOOST 1.36 or higher, SCons, and Atlas/LAPACK or other BLAS. Please refer to the OS-specific instructions below for more details. For general advice about configuring LOOS and building in unusual environments, see the "General Notes" section at the end of this file.
If you are building on a system where the default python is 2.7, you will need to copy custom.py-proto to custom.py, and uncomment the line setting PYTHON_INC (verifying that it's the correct location for your system).
LOOS can then be built using the following command:
scons
Or installed (to /opt as a default): sudo scons install
To install in a user-specified location:
scons PREFIX=/path/to/install install
To use LOOS, your environment must be first setup: (bash) source /path/to/loos/setup.sh (tcsh) source /path/to/loos/setup.csh
| Target | Description |
|---|---|
| core | LOOS Library and PyLOOS |
| tools | LOOS Library, Tools, and PyLOOS |
| all | LOOS Library, Tools, PyLOOS, and documentation (if necessary), and all Packages (default) |
| install | Install library, tools, PyLOOS, documentation, and all Packages |
| Name | Description |
|---|---|
| ENM | Elastic Network Models |
| HBonds | Hydrogen Bonds Analysis |
| Conv | Convergence Analysis |
| Density | Density/3D Histogram Tools |
| User | User-created tools |
| Python | PyLOOS scripts |
The Python interface to LOOS will be included in the build if you have a recent SWIG (version 2.0 or better) in your standard path as well as NumPy installed. Not all operating systems and versions are supported. If you need to disable the automatic building of PyLOOS, use the pyloos flag to scons:
scons pyloos=0
To build only the core LOOS libraries and PyLOOS, use the following command:
scons core
Note that the Optimal Membrane Generator requires PyLOOS. If you do not have SWIG installed or disable PyLOOS support, then the OMG will not be installed.
LOOS now supports a subset of the Amber NetCDF convention 1.0-B. Only coordinates are retrieved and are converted into the default LOOS data type (i.e. doubles). Periodic boxes are assumed to be orthogonal and the angles are currently ignored.
If the netcdf libraries are installed, these will be automatically detected by SCons and included in the build. When opening an amber trajectory file, LOOS will determine if it is a NetCDF file or an ASCII MDCRD file and act appropriately.
If the netcdf libraries and headers are installed in a non-standard location, set the NETCDF variable in your custom.py file to point to the installation. The specific include and library directories can be set using the NETCDF_INCLUDE and NETCDF_LIBPATH variables respectively, and the libraries linked against can be specified using the NETCDF_LIBS variable.
LOOS requires Boost version 1.36 or more recent. To explicitly specify an install location, set the BOOST variable in your custom.py file or on the command line:
scons BOOST=/usr/local/boost_1_54_0
In some cases, you may need to override either the include directory or the library directory. The BOOST_INCLUDE and BOOST_LIBPATH variables will specify the corresponding directories for the LOOS build. You may also explicitly specify which libraries to link against with the BOOST_LIBS variable. See custom.py-proto for examples.
If you have a full install of ATLAS including threaded versions of the BLAS and LAPACK, you can link against these to take advantage of multiple cores in LOOS. Copy the custom.py-proto to custom.py and uncomment/change the appropriate lines.
The MacOS version by default uses the vecLib framework which is already multithreaded.
You have 2 options for accessing LOOS documention.
-
consult the online documentation at http://grossfieldlab.github.io/loos/
This is fine if you're not developing new methods for the core library, and if you don't mind needing network access. -
build a new copy of the documentation. To do so, you will need to install doxygen and graphviz (available in most package managers). Then, run
doxygenfrom the top-level LOOS directory, and look for the results by accessing
Docs/html/index.html
======
Assuming you already have a working install of Anaconda or miniconda (if not, you'll need to get one from https://www.anaconda.com/distribution/), you'll need to say
conda create -n loos python=3 swig scons numpy scipy boost openblas libnetcdf

Then, run the newly installed scons to build LOOS
$CONDA_PREFIX/bin/scons
It is possible that the build can fail with errors saying there are missing references to some of the boost libraries (e.g. program_options); this generally occurs when scons gets confused by the presence of more than one BOOST install on the system. If this occurs, clean out the build and rebuild specifying the location of BOOST
$CONDA_PREFIX/bin/scons -c
$CONDA_PREFIX/bin/scons -c config
$CONDA_PREFIX/bin/scons BOOST=/path/to/boost/installed/by/conda
Alternatively, you can also copy custom.py-proto to custom.py, and uncomment then edit the lines describing BOOST's location (particularly BOOST_LIB).
We have also seen some macs where it may be necessary to separately install boost to get the build to work. After installing it (eg in /opt/boost_1_62_0), you can then set BOOST='/opt/boost_1_62_0' either on the command line or in custom.py.
To build the documentation, you will also require doxygen and graphviz,
conda install doxygen graphviz
doxygen
LOOS has been tested on Fedora (64-bit). We assume you already have the basic compiler tools installed (i.e. g++). You will need to install scons, boost, and atlas:
sudo dnf install gcc-c++ scons boost-devel atlas-devel netcdf-devel python3-devel swig python3-numpy python3-scipy
Copy custom.py-proto to custom.py, and uncomment the line setting PYTHON_INC (verifying that it's the correct location for your system).
LOOS/PyLOOS only supports Python 3, so you must specify which version of numpy and scipy to use for Fedora 24 and later. For earlier Fedoras, which don't have python3 packages for numpy and scipy, you can either install them manually or use conda.
To build the documentation, you will also require doxygen and graphviz,
sudo dnf install doxygen graphviz
doxygen
You'll need the epel repository in order to get python3 versions of numpy and scipy:
yum install https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm
Then install the packages
sudo yum install gcc-c++ scons boost-devel atlas-devel netcdf-devel python36 python36-devel swig python36-numpy python36-scipy
Copy custom.py-proto to custom.py, and uncomment the line setting PYTHON_INC (the comments will say which value is correct for CentOS).
To build the documentation, also install: sudo yum install doxygen graphviz doxygen
sudo apt-get install g++ scons libboost-all-dev libatlas-base-dev libnetcdf-dev swig python3-dev python3-numpy python3-scipy
Copy custom.py-proto to custom.py, and uncomment the line setting PYTHON_INC (verifying that it's the correct location for your system).
To build the documentation:
sudo apt-get install doxygen graphviz
doxygen
As of OpenSUSE 13, there is a pre-build ATLAS package available. However, it does not include all of the LAPACK functions LOOS requires. At this time, we recommend only installing lapack and blas. If you install ATLAS, it will be ignored by the LOOS build.
Using zypper (or your favorite package manager), install the following:
sudo zypper install gcc-c++ scons boost-devel lapack-devel blas-devel swig netcdf-devel python-numpy python3-numpy-devel python3-scipy libboost_filesystem1_66_0-devel libboost_program_options1_66_0 libboost_program_options1_66_0-devel libboost_regex1_66_0 libboost_regex1_66_0-dev libboost_system1_66_0-devel libboost_thread1_66_0-devel
You should get the blas as a dependency for lapack. You may also have lapack3 installed by default, however we've found that lapack must also be installed in order to build LOOS.
To build the documentation:
sudo zypper install doxygen graphviz
doxygen
The package-manager installed scons is too old. Download and install SCons 2.0 or better.
There is a problem with using PyLOOS with the new System Integrity Protection (SIP) enabled (see https://support.apple.com/en-us/HT204899 for more information about SIP). We are aware of this and working on a decent solution. Until then, there are four options for building and using PyLOOS under El Capitan.
See the conda install instructions above.
The first way is to download and install your own local Python and use this to run SCons and PyLOOS. Here again, you have two options: build and install SCons using that Python, or use the local Python to invoke the existing SCons. The latter can be done with the following command line:
/path/to/my/own/python `which scons`
Simply putting the new Python in your PATH will not work because SCons "sanitizes" the PATH before running. You will also need to be sure to invoke your PyLOOS scripts with your new local Python.
Although we have not tested this method, it is a common solution recommended to dealing with unsafe library errors. Two articles about managing SIP status are:
This is in essence a variant of "install your own python". If you say virtualenv loos-python it will create a local copy of your python-of-choice in your directory space, so you can install packages as needed. Activate that virtual environment using the activate.csh or activate.sh script in the distribution directory, then use that to install SCons and LOOS. You'll then need to make sure you're in that virtualenv whenever you want to run PyLOOS scripts.
MacOS 10.9 requires LOOS 2.1 or more recent. We have also discovered an incompatibility with Boost installed via Fink in MacOS 10.9. You will need to manually download and build a recent version of Boost and NOT use the Fink version.
There is an issue with using Swig and a recent version of MacOS 10.9 that affects how STL containers are wrapped. We have disabled the wrapping of iterator methods for MacOS 10.9 only in order to build PyLOOS. This means functions such as begin() and erase() will be unavailable in PyLOOS for the vectors used in LOOS.
First, make sure you have the Developer's Tools (i.e. XCode) installed. XCode is available for free through the Mac App store. Next, you will need to install SCons (http://scons.org) and Boost (http://boost.org) by visiting their websites, downloading the software, and following their installation instructions. Alternatively, use fink to install these packages.
Download and install the latest hdf5 and netcdf libraries. If necessary, set the NETCDF_INCLUDE and NETCDF_LIBPATH variables in your custom.py file to point to where netcdf is installed.
You will need to download and install a recent version of SWIG first. If you have installed Boost in a non-standard location, you will need to make sure that the boost libraries are in your DYLD_LIBRARY_PATH environment variable.
The default build will use the system Python and Numpy. Any non-standard locations for python modules can be specified using the PYTHON_PATH option to scons: scons PYTHON_PATH=$HOME/local/lib/python2.7
Several packages (notably Voronoi) and a few tools (e.g. cluster-structures.py) depend on scipy. For recent version of MacOS, both Scipy should already be installed. If not, you can always download it from www.scipy.org.
We have seen several instances where LOOS would not build due to multiple versions of BOOST being installed. The configuration part of the build seems to mix components from the different versions installed. If your build exits due to errors, verify that you are in fact using only the BOOST install and libraries you intend by examining config.log (or consider removing the excess versions)
For Windows 10, your best bet is to use one of the linux subsystems that are installable from Microsoft (e.g. Ubuntu or Debian), then follow the instructions for that linux distribution. We have anecodotal evidence that this works, but it isn't a supported environment.
LOOS has been tested with Manjaro 0.8.10.
Make sure scons, boost, lapack, python, and swig are installed. Also
install NetCDF, if you want NetCDF support. LOOS and PyLOOS should build.
LOOS has been tested with Slackware 14.1. You will need to install, by whatever means you prefer, lapack, blas, and scons. LOOS and PyLOOS should then build.
You can override the paths SCons will use for both libraries and include files by setting the appropriate variables in a "custom.py" file. For example, to control where the Boost include files are located, set the BOOST_INCLUDE variable.
You can also control what libraries are linked against by setting the
appropriate _LIBS variable in your custom.py file. For example, if
your Boost libraries have a naming convention that the LOOS SConstruct
cannot figure out, you can explicitly set the libraries using the
BOOST_LIBS variable. These variables take a space-separated list of
library names. It is important to have all required libraries
included in this list. So for Boost, this would include the regex,
program_options, thread, and system libraries.
If you're using a compiler in a non-standard location (e.g. you have your own build of the latest and greatest gcc), SCons may not be using it even though your $PATH is set correctly. You can force which compiler is used to build LOOS by setting the CXX variable in your "custom.py" file.
Note: Settings in the custom.py file can be overridden using the command-line and the shell environment.
Sometimes compilers will 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.
SCons supports building LOOS in parallel. If you have 4 cores, for example, use "scons -j4" to use all 4 cores.
We no longer supply pre-built documentation. You can either use the docs on the GitHub page, or you can build them yourself. You'll need to have doxygen and graphviz installed. From the main LOOS directory, run
doxygen
which will create a new directory Docs. If you open Docs/html/index.html, you'll see an updated version of the docs from the GitHub page (including any new functions or methods you might have written).