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IMP Manual  for IMP version 2.16.0
installation.md
1 Installation {#installation}
2 ============
3 
4 [TOC]
5 
6 # Binary installation {#installation_binary}
7 
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.
11 
12 We recommend you use a stable release. These are available for
13 Windows, Mac and Linux from our [download page](https://integrativemodeling.org/download.html#stable).
14 
15 Binaries are [also available for our latest nightly builds](https://integrativemodeling.org/download.html#develop). If you do decide to use a nightly build,
16 please check out the [nightly builds results page](https://integrativemodeling.org/nightly/results/)
17 to see if the code is currently stable enough for your purposes.
18 
19 # Source code installation {#installation_source}
20 
21 ## Prerequisites {#installation_prereqs}
22 
23 In order to build %IMP from source, you will need:
24 
25 - [CMake](https://cmake.org) (2.8.12 or later; 3.14 or later is recommended)
26 - [Boost](https://www.boost.org) (1.53 or later; Boost.Iostreams must be built
27  with its [zlib filter enabled](https://www.boost.org/doc/libs/1_67_0/libs/iostreams/doc/installation.html))
28 - [Eigen](https://eigen.tuxfamily.org/) (3.0 or later)
29 - [HDF5](https://support.hdfgroup.org/HDF5/) (1.8 or later; 1.10 or 1.12
30  should also work)
31 - [Python](https://www.python.org) (2.7 or later, or any version of Python 3)
32 - [SWIG](http://www.swig.org) (1.3.40 or later; 2.0.4 or later is needed
33  if you want to use Python 3)
34 
35 The following prerequisites are _optional_; without them some parts of %IMP
36 will not build, and some will not function optimally.
37 
38 - The [NumPy](https://numpy.org/) library is strongly recommended; if %IMP
39  is built with NumPy, many operations that transfer data between C++ and Python
40  become more efficient.
41 - [Doxygen](http://www.doxygen.org/) (only exactly version 1.8.6 is supported)
42  and [Graphviz](http://www.graphviz.org/): required for building
43  documentation.
44 - [Modeller](\ref modeller): needed to use the IMP.modeller module.
45 - [CGAL](\ref CGAL): enables faster geometric operations, such as
46  nonbonded lists.
47 - [Google perf tools](\ref perf): needed only for profiling %IMP code.
48 - [ANN](\ref ANN): certain data structures will be faster if it is available.
49 - [GSL](\ref GSL) (1.13 or later): needed to use the IMP.gsl module.
50 - [OpenCV](\ref OpenCV) (2.1 or later): needed to use the IMP.em2d module or the
51  [idock](@ref idock_pcsk9) and [emagefit](@ref emagefit_3sfd) command
52  line tools.
53 - [FFTW](http://www.fftw.org): needed to use the IMP.em2d or IMP.multifit
54  modules or the [multifit](@ref multifit_3sfd) command line tool.
55 - [libTAU](https://integrativemodeling.org/libTAU.html): needed to use the
56  IMP.cnmultifit module or the [cnmultifit](@ref cnmultifit_groel) command
57  line tool.
58 - [Protobuf](https://github.com/google/protobuf): needed to use the
59  IMP.npctransport module.
60 - An [MPI](@ref IMP::mpi) library is needed to use the IMP.mpi module.
61 - The [scipy](http://www.scipy.org/scipylib/download.html),
62  [scikit-learn](http://scikit-learn.org/stable/install.html),
63  and [matplotlib](http://matplotlib.org/downloads.html)
64  Python libraries are also recommended.
65 - [Chimera](https://www.cgl.ucsf.edu/chimera/download.html) or
66  [ChimeraX](https://www.rbvi.ucsf.edu/chimerax/) are recommended
67  for visualization of results.
68 
69 The following prerequisites are _bundled_, i.e. they are included with %IMP
70 itself and will be built at the same time as %IMP, unless explicitly
71 requested otherwise (see [CMake](@ref cmake_config) for more information):
72 
73 - [RMF](https://integrativemodeling.org/rmf/) (1.3 or later) for handling
74  RMF files, and the IMP.rmf module.
75 - [python-ihm](https://github.com/ihmwg/python-ihm) for handling mmCIF and
76  BinaryCIF files.
77 
78 ### Getting prerequisites on Linux {#installation_prereqs_linux}
79 All of the prerequisites should be available as pre-built packages for
80 your Linux distribution of choice. For example, on a Fedora system the
81 following should install most of the prerequisites:
82 
83  sudo dnf install boost-devel gperftools-devel CGAL-devel graphviz gsl-devel cmake hdf5-devel swig fftw-devel opencv-devel python3-numpy
84 
85 ### Getting prerequisites on a Mac {#installation_prereqs_mac}
86 
87 Mac users must first install the developer Command Line Tools, which can be
88 done from the command line by running
89 
90  sudo xcode-select --install
91 
92 These can also be obtained by installing Xcode from the App store, then trying
93 to run a command line tool (such as `clang`) which will prompt to install the
94 tools.
95 
96 Then Mac users should use one of the available collections of Unix tools,
97 such as
98 - [Homebrew](https://brew.sh) (_recommended_) Once you installed `homebrew`
99  do
100 
101  brew tap salilab/salilab
102  brew install boost gmp google-perftools cgal graphviz gsl cmake hdf5 swig fftw mpfr opencv libtau eigen
103 
104  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).
105 - [Macports](https://www.macports.org/) If you use MacPorts, you must verify `/opt/local/bin` is in your path (this may be taken care of by MacPorts automatically, and can be done manually either by modifying your shell's config file or by making an `environment.plist` file), and then do
106 
107  sudo port install boost cgal cmake fftw gmp gperftools graphviz gsl eigen hdf5 mpfr ninja opencv protobuf-cpp swig swig-python
108  (as in brew, some of these packages may be optional)
109 
110 - or [Fink](http://www.finkproject.org/) (not supported)
111 
112 ### Getting prerequisites on Windows {#installation_prereqs_windows}
113 
114 We recommend Linux or Mac for developing with %IMP, as obtaining the
115 prerequisites on Windows is much more involved. However, if you really want
116 to build on Windows, see the
117 [building from source code on Windows](@ref install_windows) page for the
118 procedure we use.
119 
120 
121 ## Download {#installation_download}
122 
123 - Download the source code tarball from [our download page](https://integrativemodeling.org/download.html#source), then extract it with something like:
124 
125  tar -xvzf ../imp-<version>.tar.gz
126 
127 - Alternatively you can use [git](https://git-scm.com/) to get the code
128  directly from our [GitHub repository](https://github.com/salilab/imp)
129  with something like:
130 
131  git clone -b main https://github.com/salilab/imp.git
132  (cd imp && git submodule update --init && ./setup_git.py)
133 
134  (the `main` branch tracks the most recent stable
135  release; alternatively you can use `develop` to get the most recent code,
136  but please check out the [nightly builds results page](https://integrativemodeling.org/nightly/results/)
137  to see if the code is currently stable enough for your purposes).
138 
139 ## Compilation {#installation_compilation}
140 
141 Make a separate directory to keep the compiled version of %IMP in (it's tidier
142 to keep this separate from the source code, and if you need to later you can
143 just delete this directory without affecting the source). Set up the build
144 with [CMake](@ref cmake_config), then finally compile it, with something
145 like:
146 
147  mkdir imp_release
148  cd imp_release
149  cmake <path to IMP source>
150  make -j8
151 
152 There are a number of ways in which %IMP can be configured.
153 See [the configuration options page](@ref cmake_config) for more details
154 and for help with CMake problems.
155 
156 ## Testing {#installation_testing}
157 Once the compilation is complete, you can optionally run the test suite.
158 Test are run using `ctest`. A good start is to run `ctest --output-on-failure`.
159 
160 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"`.
161 
162 Benchmarks are simply tests labeled as `benchmark`; examples are tests labeled as `example`.
163 
164 Note that some test failures are to be expected; compare the failures with
165 those at our own [nightly builds page](https://integrativemodeling.org/nightly/results/)
166 if you are concerned.
167 
168 ## Installation {#installation_install}
169 
170 Once everything is compiled (and optionally tested) you can install %IMP
171 by simply running `make install`. If you opted to install in a non-standard
172 location, it is up to you to set up your environment variables so that %IMP
173 can be found (you may need to set `PATH`, `PYTHONPATH`, and `LD_LIBRARY_PATH`).
174 
175 Alternatively, you can run %IMP directly from the build directory by using
176 the `setup_environment.sh` script. This sets the necessary environment
177 variables and then runs the rest of the command line with this modified
178 environment. For example, to run the `ligand_score` command line tool you
179 can either run
180 
181  ./setup_environment.sh ligand_score <arguments>
182 
183 or create a new shell with
184 
185  ./setup_environment.sh $SHELL
186 
187 and then run
188 
189  ligand_score <arguments>
190 
191 in that shell.