SOPT is an open-source C++
package available under the license below. It performs Sparse OPTimisation using state-of-the-art convex optimisation algorithms. It solves a variety of sparse regularisation problems, including the Sparsity Averaging Reweighted Analysis (SARA) algorithm.
SOPT also has several MPI wrappers that can be adapted for computational distirbution of various linear operators and convex optimisation algorithms. Wavelet Operators with SOPT also support multi-threading through OpenMP.
SOPT is written in C++
primarily but also contains partial and prototyped Matlab implementations of various algorithms.
SOPT is largely provided to support the PURIFY package, a companion open-source code to perform radio interferometric imaging, also written by the authors of SOPT. For further background please see the reference section.
This documentation outlines the necessary and optional dependencies upon which SOPT should be built, before describing installation and testing details and Matlab support. Contributors, references and license information then follows.
SOPT is mostly written in C++17
. Pre-requisites and dependencies are listed in following and minimal versions required are tested against Travis CI
meaning that they come natively with OSX and the Ubuntu Trusty release. These are also the default ones fetched by CMake
.
C++
minimal dependencies:
- CMake v3.9.2 A free software that allows cross-platform compilation.
- GCC v7.3.0 GNU compiler for
C++
. - OpenMP v4.8.4 (Trusty) - Optional - Speeds up some of the operations.
- Cppflow v2.0.0 - Optional - A warpper for the Tensorflow C API allowing us to read Tensorflow models into SOPT. Needed if you are using a learned prior.
- Eigen3 v3.4.0 (Trusty) Modern
C++
linear algebra. Downloaded automatically if absent. - Catch2 v3.4.0 - Optional - A
C++
unit-testing framework only needed for testing. Downloaded automatically if absent. - google/benchmark - Optional - A
C++
micro-benchmarking framework only needed for benchmarks. Downloaded automatically if absent. - tiff v4.5.1 (Trusty) Tag Image File Format library - only installed if needed.
Conan is a C++ package manager that helps deal with most of the C++ dependencies as well as the SOPT installation:
-
If you are using a learned prior you must install the Tensorflow C API and
cppflow
package:-
Install TensorFlow C API
-
Clone the UCL fork of cppflow and create a conan package using
git clone git@github.com:UCL/cppflow.git conan create ./cppflow/
Note that conan requires you to specify the host (h) and the build (b) profiles on the command line (
-pr:b=default -pr:h=default
or simply-pr:a=default
), unless you have defined them in your conan profile. You can set up a default profile for your system usingconan profile detect
(only needs to be done once).
-
-
Once the mandatory dependencies are present,
git clone
from the GitHub repository:git clone https://github.com/astro-informatics/sopt.git
-
Then, the program can be built using conan:
cd /path/to/code mkdir build cd build conan install .. -of . --build missing conan build .. -of .
Things to note:
-
To install in directory
INSTALL_FOLDER
, add the following options to the conan build command:conan build .. -of INSTALL_FOLDER
-
CMake build options should be passed as options to
conan install
using the-o
flag with a valueon
oroff
. Possible options are:- tests (default on)
- benchmarks (default off)
- examples (default on)
- openmp (default off)
- dompi (default off)
- docs (default off)
- coverage (default off)
- cppflow (default off)
For example, to build with both MPI and OpenMP on you would use
conan install .. -of . --build missing -o openmp=on -o dompi=on
conan build .. -of .
If the dependencies are already available on your system, you can also install SOPT manually like so
cd /path/to/code
mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX=${PWD}/../local
make -j
make -j install
On MacOS, you can also install most of the dependencies with Homebrew e.g.
brew install libtensorflow eigen tiff catch2
Note that the ONNXruntime interface is currently only supported when compiling with Clang on MacOS, but not with g++
You can set commonly used options, choices of compilers etc. in a
conan profile.
You can list profiles available on your system using conan profile list
and
select the profile you want to use with conan install
with
conan install .. -pr my_profile
.
CMake build options can also be added to the profile under [options]
.
Here is an example of a conan profile for building with a homebrew installed gcc 11 on MacOS.
[settings]
os=Macos
os_build=Macos
arch=x86_64
arch_build=x86_64
compiler=gcc
compiler.version=11
compiler.libcxx=libstdc++11
build_type=Release
[options]
[build_requires]
To check everything went all right, run the test suite:
cd /path/to/code/build
ctest .
A separate Matlab implementation is provided with SOPT.
This implementation includes some (but not all) of the optimisation algorithms implemented in the C++
code, including the SARA algorithm.
The Matlab implementation is contained in the matlab directory.
This is a stand-alone implementation and does not call any of the C++
code.
In future, Matlab interfaces to the C++
code may also be included in SOPT.
See matlab/README.txt
for an overview of the Matlab implementation.
The stand-alone Matlab implementation is also self-documenting;
corresponding documentation can be found in matlab/doc
.
We thank Gilles Puy for contributing to this Matlab implementation.
Check the [contributors](@ref sopt_contributors) page (github).
If you use SOPT for work that results in publication, please reference the webpage and our related academic papers:
- L. Pratley et al. (to be published)
- A. Onose, R. E. Carrillo, A. Repetti, J. D. McEwen, J.-P. Thiran, J.-C. Pesquet, and Y. Wiaux. "Scalable splitting algorithms for big-data interferometric imaging in the SKA era" Mon. Not. Roy. Astron. Soc. 462(4):4314-4335 (2016) arXiv:1601.04026
- R. E. Carrillo, J. D. McEwen, D. Van De Ville, J.-P. Thiran, and Y. Wiaux. "Sparsity averaging for compressive imaging" IEEE Signal Processing Letters 20(6):591-594 (2013) arXiv:1208.2330
- R. E. Carrillo, J. D. McEwen and Y. Wiaux. "Sparsity Averaging Reweighted Analysis (SARA): a novel algorithm for radio-interferometric imaging" Mon. Not. Roy. Astron. Soc. 426(2):1223-1234 (2012) arXiv:1205.3123
SOPT: Sparse OPTimisation package Copyright (C) 2013-2024
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details (LICENSE.txt).
You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
For any questions or comments, feel free to contact Jason McEwen, or add an issue to the issue tracker.
The code is given for educational purpose. For the Matlab
version of the code see the folder matlab.