1 Installation {#installation}
6 # Binary installation {#installation_binary}
8 Binary installation is strongly recommended
for new users of %IMP. It is
9 much faster than building from source code, requires a smaller download,
10 and all the necessary prerequisites are handled
for you automatically.
12 We recommend you use a stable release. These are available
for
13 Windows, Mac and Linux from our [download page](https:
15 Binaries are [also available
for our latest nightly builds](https:
16 please check out the [nightly builds results page](https:
17 to see
if the code is currently stable enough
for your purposes.
19 # Source code installation {#installation_source}
21 ## Prerequisites {#installation_prereqs}
23 In order to build %IMP from source, you will need:
25 - A C++ compiler that supports the C++11 standard, such as gcc, clang,
26 or Microsoft Visual Studio 2012 or later.
29 with its [zlib filter enabled](https:
36 The following prerequisites are _optional_; without them some parts of %IMP
37 will not build, and some will not
function optimally.
40 is built with NumPy, many operations that transfer data between C++ and Python
41 become more efficient.
45 - [Modeller](\ref modeller): needed to use the IMP.modeller module.
46 - [CGAL](\ref CGAL): enables faster geometric operations, such as
48 - [Google perf tools](\ref perf): needed only
for profiling %IMP code.
49 - [ANN](\ref ANN): certain data structures will be faster
if it is available.
50 - [GSL](\ref GSL) (1.13 or later): needed to use the IMP.gsl module.
51 - [OpenCV](\ref OpenCV) (2.1 or later): needed to use the IMP.em2d module or the
52 [idock](@ref idock_pcsk9) and [emagefit](@ref emagefit_3sfd) command
55 modules or the [multifit](@ref multifit_3sfd) command line tool.
57 IMP.cnmultifit module or the [cnmultifit](@ref cnmultifit_groel) command
60 IMP.npctransport module.
61 - An [MPI](@ref IMP::mpi) library is needed to use the IMP.mpi module.
64 and [matplotlib](http:
65 Python libraries are also recommended.
68 for visualization of results.
70 The following prerequisites are _bundled_, i.e. they are included with %IMP
71 itself and will be built at the same time as %IMP, unless explicitly
72 requested otherwise (see [CMake](@ref cmake_config)
for more information):
75 RMF files, and the IMP.rmf module.
79 ### Getting prerequisites on Linux {#installation_prereqs_linux}
80 All of the prerequisites should be available as pre-built packages
for
81 your Linux distribution of choice. For example, on a Fedora system the
82 following should install most of the prerequisites:
84 sudo dnf install boost-devel gperftools-devel CGAL-devel graphviz gsl-devel cmake hdf5-devel swig fftw-devel opencv-devel python3-numpy
86 ### Getting prerequisites on a Mac {#installation_prereqs_mac}
88 Mac users must first install the developer Command Line Tools, which can be
89 done from the command line by running
91 sudo xcode-
select --install
93 These can also be obtained by installing Xcode from the App store, then trying
94 to run a command line tool (such as `clang`) which will prompt to install the
97 Then Mac users should use one of the available collections of Unix tools,
102 brew tap salilab/salilab
103 brew install boost gmp google-perftools cgal graphviz gsl cmake hdf5 swig fftw mpfr opencv libtau eigen
105 to install everything %IMP finds useful (or that you will want
for installing various useful Python libs that %IMP finds useful). On older Macs, you may also need to `brew install git`
if you want to use git (newer Macs include git).
108 sudo port install boost cgal cmake fftw gmp gperftools graphviz gsl eigen hdf5 mpfr ninja opencv protobuf-cpp swig swig-python
109 (as in brew, some of these packages may be optional)
113 ### Getting prerequisites on Windows {#installation_prereqs_windows}
115 We recommend Linux or Mac
for developing with %IMP, as obtaining the
116 prerequisites on Windows is much more involved. However,
if you really want
117 to build on Windows, see the
118 [building from source code on Windows](@ref install_windows) page
for the
122 ## Download {#installation_download}
124 - Download the source code tarball from [our download page](https:
126 tar -xvzf ../imp-<version>.tar.gz
128 - Alternatively you can use [git](https:
129 directly from our [GitHub repository](https:
132 git clone -b
main https:
133 (cd imp && git submodule update --init && ./setup_git.py)
135 (the `main` branch tracks the most recent stable
136 release; alternatively you can use `develop` to
get the most recent code,
137 but please check out the [nightly builds results page](https:
138 to see
if the code is currently stable enough
for your purposes).
140 ## Compilation {#installation_compilation}
142 Make a separate directory to keep the compiled version of %IMP in (it
's tidier
143 to keep this separate from the source code, and if you need to later you can
144 just delete this directory without affecting the source). Set up the build
145 with [CMake](@ref cmake_config), then finally compile it, with something
150 cmake <path to IMP source>
153 There are a number of ways in which %IMP can be configured.
154 See [the configuration options page](@ref cmake_config) for more details
155 and for help with CMake problems.
157 ## Testing {#installation_testing}
158 Once the compilation is complete, you can optionally run the test suite.
159 Test are run using `ctest`. A good start is to run `ctest --output-on-failure`.
161 Tests are labeled with the module name and the type and cost of the test, so to run just the expensive tests in the `atom` module, use `ctest -L "^IMP\.atom\-test\-.*EXPENSIVE"`.
163 Benchmarks are simply tests labeled as `benchmark`; examples are tests labeled as `example`.
165 Note that some test failures are to be expected; compare the failures with
166 those at our own [nightly builds page](https://integrativemodeling.org/nightly/results/)
167 if you are concerned.
169 ## Installation {#installation_install}
171 Once everything is compiled (and optionally tested) you can install %IMP
172 by simply running `make install`. If you opted to install in a non-standard
173 location, it is up to you to set up your environment variables so that %IMP
174 can be found (you may need to set `PATH`, `PYTHONPATH`, and `LD_LIBRARY_PATH`).
176 Alternatively, you can run %IMP directly from the build directory by using
177 the `setup_environment.sh` script. This sets the necessary environment
178 variables and then runs the rest of the command line with this modified
179 environment. For example, to run the `ligand_score` command line tool you
182 ./setup_environment.sh ligand_score <arguments>
184 or create a new shell with
186 ./setup_environment.sh $SHELL
190 ligand_score <arguments>