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IMP Manual  for IMP version 2.7.0
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 or later)
26 - [Boost](http://www.boost.org) (1.40 or later)
27 - [HDF5](https://support.hdfgroup.org/HDF5/) (1.8 or later; 1.10 should also
28  work)
29 - [Python](https://www.python.org) (2.6 or later, or any version of Python 3)
30 - [SWIG](http://www.swig.org) (1.3.40 or later; 2.0.4 or later is needed
31  if you want to use Python 3)
32 
33 The following prerequisites are _optional_; without them some parts of %IMP
34 will not build, and some will not function optimally.
35 
36 - [Doxygen](http://www.doxygen.org/) (only exactly version 1.8.6 is supported)
37  and [Graphviz](http://www.graphviz.org/): required for building
38  documentation.
39 - [Modeller](\ref modeller): needed to use the IMP.modeller module.
40 - [CGAL](\ref CGAL): enables faster geometric operations, such as
41  nonbonded lists.
42 - [Google perf tools](\ref perf): needed only for profiling %IMP code.
43 - [ANN](\ref ANN): certain data structures will be faster if it is available.
44 - [GSL](\ref GSL): needed to use the IMP.gsl module.
45 - [OpenCV](\ref OpenCV) (2.1 or later): needed to use the IMP.em2d module or the
46  [idock](@ref idock_pcsk9) and [emagefit](@ref emagefit_3sfd) command
47  line tools.
48 - [FFTW](http://www.fftw.org): needed to use the IMP.em2d or IMP.multifit
49  modules or the [multifit](@ref multifit_3sfd) command line tool.
50 - [libTAU](https://integrativemodeling.org/libTAU.html): needed to use the
51  IMP.cnmultifit module or the [cnmultifit](@ref cnmultifit_groel) command
52  line tool.
53 - An [MPI](@ref IMP::mpi) library is needed to use the IMP.mpi module.
54 - The [numpy, scipy](http://www.scipy.org/scipylib/download.html),
55  [scikit-learn](http://scikit-learn.org/stable/install.html),
56  and [matplotlib](http://matplotlib.org/downloads.html)
57  Python libraries are also recommended.
58 - [Chimera](https://www.cgl.ucsf.edu/chimera/download.html) is recommended
59  for visualization of results.
60 
61 ### Getting prerequisites on Linux {#installation_prereqs_linux}
62 All of the prerequisites should be available as pre-built packages for
63 your Linux distribution of choice. For example, on a Fedora system the
64 following should install most of the prerequisites:
65 
66  sudo dnf install boost-devel gperftools-devel CGAL-devel graphviz gsl-devel cmake doxygen hdf5-devel swig fftw-devel opencv-devel
67 
68 ### Getting prerequisites on a Mac {#installation_prereqs_mac}
69 
70 Mac users must first install Xcode (previously known as Developer Tools)
71 which is not installed by default with OS X, but is available from the App store
72 (or from the Mac OS install DVD for old versions of Mac OS). They will also
73 need the Xcode command line tools (install by going to Xcode Preferences, then
74 Downloads, then Components, and select "Command Line Tools").
75 
76 Then Mac users should use one of the available collections of Unix tools,
77 such as
78 - [Homebrew](http://brew.sh) (_recommended_) Once you installed `homebrew`
79  do
80 
81  brew tap homebrew/science
82  brew tap salilab/salilab
83  brew install boost gmp google-perftools cgal graphviz gsl cmake doxygen hdf5 swig fftw mpfr opencv libtau
84 
85  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).
86 - [Macports](http://www.macports.org/) If you use MacPorts, you must add `/opt/local/bin` to your path (either by modifying your shell's
87  config file or by making an `environment.plist` file) and then do
88 
89  sudo port install boost cmake swig-python
90 
91  to install the needed libraries and tools. When installing HDF5 with MacPorts, be sure to install `hdf5-18`
92  (version 1.8), rather than the older `hdf5` (version 1.6.9).
93 - or [Fink](http://www.finkproject.org/) (not supported)
94 
95 ### Getting prerequisites on Windows {#installation_prereqs_windows}
96 
97 We recommend Linux or Mac for developing with %IMP, as obtaining the
98 prerequisites on Windows is much more involved. However, if you really want
99 to build on Windows, see the
100 [building from source code on Windows](@ref install_windows) page for the
101 procedure we use.
102 
103 
104 ## Download {#installation_download}
105 
106 - Download the source code tarball from [our download page](https://integrativemodeling.org/download.html#source), then extract it with something like:
107 
108  tar -xvzf ../imp-<version>.tar.gz
109 
110 - Alternatively you can use [git](https://git-scm.com/) to get the code
111  directly from our [GitHub repository](https://github.com/salilab/imp)
112  with something like:
113 
114  git clone -b master https://github.com/salilab/imp.git
115  (cd imp && ./setup_git.py)
116 
117  (the `master` branch tracks the most recent stable
118  release; alternatively you can use `develop` to get the most recent code,
119  but please check out the [nightly builds results page](https://integrativemodeling.org/nightly/results/)
120  to see if the code is currently stable enough for your purposes).
121 
122 ## Compilation {#installation_compilation}
123 
124 Make a separate directory to keep the compiled version of %IMP in (it's tidier
125 to keep this separate from the source code, and if you need to later you can
126 just delete this directory without affecting the source). Set up the build
127 with [CMake](@ref cmake_config), then finally compile it, with something
128 like:
129 
130  mkdir imp_release
131  cd imp_release
132  cmake <path to IMP source>
133  make -j8
134 
135 There are a number of ways in which %IMP can be configured.
136 See [the configuration options page](@ref cmake_config) for more details.
137 
138 ## Testing {#installation_testing}
139 Once the compilation is complete, you can optionally run the test suite.
140 Test are run using `ctest`. A good start is to run `ctest --output-on-failure`.
141 
142 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"`.
143 
144 Benchmarks are simply tests labeled as `benchmark`; examples are tests labeled as `example`.
145 
146 Note that some test failures are to be expected; compare the failures with
147 those at our own [nightly builds page](https://integrativemodeling.org/nightly/results/)
148 if you are concerned.
149 
150 ## Installation {#installation_install}
151 
152 Once everything is compiled (and optionally tested) you can install %IMP
153 by simply running `make install`. If you opted to install in a non-standard
154 location, it is up to you to set up your environment variables so that %IMP
155 can be found (you may need to set `PATH`, `PYTHONPATH`, and `LD_LIBRARY_PATH`).
156 
157 Alternatively, you can run %IMP directly from the build directory by using
158 the `setup_environment.sh` script. This sets the necessary environment
159 variables and then runs the rest of the command line with this modified
160 environment. For example, to run the `ligand_score` command line tool you
161 can either run
162 
163  ./setup_environment.sh ligand_score <arguments>
164 
165 or create a new shell with
166 
167  ./setup_environment.sh $SHELL
168 
169 and then run
170 
171  ligand_score <arguments>
172 
173 in that shell.