Building and installing basics

Building IMP from source is straightforward if the prerequisites are already installed. We recommend you get IMP from git by git clone git://github.com/salilab/imp.git To build, create a directory to build IMP in (it is good practice not to build in the source directory and do)

cmake ../imp -DCMAKE_BUILD_TYPE=Release
make -j 4

See Building IMP with CMake for more information.

Prerequisites

In order to obtain and compile IMP, you will need:

cmake (2.8 or later)
Boost (1.40 or later)
HDF5 (1.8 or later)
Developers will also need a git client to access the repository

If you wish to build the Python interfaces, you will also need:

Python (2.4 or later)
SWIG (1.3.40 or later)

Getting prerequisites on a Mac

Mac users must first install Xcode (previously known as Developer Tools) which is not installed by default with OS X, but is available from the App store (or from the Mac OS install DVD for old versions of Mac OS).

Then Mac users should use one of the available collections of Unix tools, either

Homebrew: (recommended) Once you installed homebrew do brew install boost gmp google-perftools cgal graphviz gsl cmake doxygen hdf5 swig eigen fftw mpfr to install everything IMP finds useful (or that you will want for installing various useful python libs that IMP finds useful).
MacPorts: If you use MacPorts, you must add /opt/local/bin to your path (either by modifying your shell's config file or by making an environment.plist file-see the FAQ) and then do
sudo port install boost cmake swig-python

to install the needed libraries and tools. When installing HDF5 with MacPorts, be sure to install hdf5-18 (version 1.8), rather than the older hdf5 (version 1.6.9).
or Fink

Note: Mac OS X 10.5 and 10.6 include a 'swig' binary, but it is too old to use with IMP. You need to make sure that the newer version of swig is found first in your PATH.

Getting prerequisites on Windows

We recommend Linux or Mac for developing with IMP, as obtaining the prerequisites on Windows is much more involved. However, we do test IMP on Windows, built with the Microsoft Visual Studio compilers (we use Visual Studio Express 2010 SP1). One complication is that different packages are compiled with different versions of Visual Studio, and mixing the different runtimes (msvc*.dll) can cause odd behavior; therefore, we recommend building most of the dependencies from source code using the same version of Visual Studio that you're going to use to build IMP. The basic procedure is as follows:

Install Microsoft Visual Studio Express (it is free, but registration with Microsoft is required).
Get and install cmake.
Get Python 2 (not Python 3) (make sure you get the 32-bit version if you're going to build IMP for 32-bit Windows).
Download the Boost source code (we extracted it into C:\Program Files\boost_1_53_0), then
- Open a Visual Studio Command Prompt, and cd into the directory where Boost was extracted
- Run bootstrap.bat
- Run "bjam link=shared runtime-link=shared"
Get and install SWIG for Windows
Get and install the zlib binary package.
- We found that the zconf.h header included with zlib erroneously includes unistd.h, which doesn't exist on Windows, so we commented out that line.
Get the HDF5 source code
- Edit the H5pubconf.h file in the windows\src subdirectory to disable szip (or first install szip if you want to include szip support). Copy this file into the top-level src directory.
- Open the h5libsettings project (in windows\misc\typegen\h5libsettings) in Visual Studio, and build it in Release configuration. (Note that if you don't have the x64 SDK installed, you'll first need to edit the project file in a text editor and remove any mention of the x64 platform, since otherwise the upgrade of this solution to 2010 format will fail.)
- Build the 'h5tinit' project (in windows\misc\typegen\h5tinit) in Release configuration.
- Build the 'hdf5dll' project (in windows\proj\hdf5dll) in Release configuration.
  - In order for Visual Studio to find zlib, we first opened the project settings, and under C/C++, Additional Include Directories, added C:\Program Files\GnuWin32\include, and under Linker, Additional Dependencies, added C:\Program Files\GnuWin32\lib\zlib.lib.
- Copy proj\hdf5dll\Release\hdf5dll.lib to hdf5.lib to help cmake find it.
(Optional) Build CGAL from source code.
(Optional) Get and install Eigen.
(Optional) Download the FFTW DLLs and follow the instructions at that website to make .lib import libraries needed for Visual Studio.
- Copy libfftw3-3.lib to fftw3.lib to help cmake find it
(Optional) Get the GSL source code and build it:
- Open the libgsl project file in the src\gsl\1.8\gsl-1.8\VC8 subdirectory
- Build in Release-DLL configuration
- Copy the generated libgsl.dll and libgslcblas.dll to a suitable location (we used C:\Program Files\gsl-1.8\lib)
- Copy the corresponding .lib files, libgsl_dll.lib and libgslcblas_dll.lib (we recommend removing the dll suffix and the lib prefix when you do this so that cmake has an easier time finding them, i.e. call them gsl.lib and gslcblas.lib).
(Optional) Get numpy and scipy to match your Python version.
(Optional) Get and install libTAU

Copy libTAU.lib to TAU.lib to help cmake find it.
(Optional) Get the OpenCV source code and build it by following the instructions at that website.

Copy each opencv*.lib to a similar file without the version extension (e.g. copy opencv_ml244.lib to opencv_ml.lib) to help cmake find it
Set PATH, INCLUDE, and/or LIB environment variables so that the compiler can find all of the dependencies. (We wrote a little batch file.)
Set up IMP by running something similar to
cmake <imp_source_directory> -DCMAKE_BUILD_TYPE=Release -DCMAKE_CXX_FLAGS="/DBOOST_ALL_DYN_LINK /EHsc /D_HDF5USEDLL_ /DWIN32 /DGSL_DLL" -G "NMake Makefiles"
Then use simply 'nmake' (instead of 'make', as on Linux or Mac) to build IMP. (cmake can also generate Visual Studio project files, but we recommend nmake.)
To use IMP or run tests, first run the setup_environment.bat file to set up the environment so all the programs and Python modules can be found. (This batch file needs to be run only once, not for each test.)

Getting prerequisites on Linux

All of the prerequisites should be available as pre-built packages for your Linux distribution of choice.

Optional prerequisites

IMP can make use of a variety of external tools to provide more or better functionality.

Doxygen and Dot

Building the documentation requires Doxygen and graphviz. It is available as part of most Unix tool sets (HomeBrew, all Linux distributions etc.).

MODELLER

If you want to use IMP with MODELLER, you should use version 9v7 or later. If you installed the MODELLER Linux RPM or Mac package, it should be detected automatically. Make sure that MODELLER is found in your PYTHONPATH.

CGAL

A wide variety of geometric computations will be faster, better or more reliable if CGAL is installed. CGAL is available as part of most Linux distributions and can be built from source on Mac OS or Linux. It is free for academic use, but commercial use requires a license. See IMP::cgal for more information.

Google Perf Tools

The google perf tools can be used for cpu and memory profiling of IMP. They can be controlled from the command line in many IMP executables.

ANN

ANN is a library implementing fast nearest neighbor searches. Certain data structures will be faster if it is installed. While compilation of the library from source is quite straight forward, it is not avaible as a package for common platforms. In addition, ANN must be built as a shared library rather than a static library. See the FAQ.

GSL

The IMP.gsl module requires GSL. It is available as a prebuilt package on all supported platforms. Note that GSL is distributed under the GPL and so cannot be used in C++ applications with certain other dependencies such as CGAL.

Where to go next

You are now ready to use IMP within Python and C++.

Everyone should read the Introduction and developers should then move on to the Developer guide.

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