========================= Installation instructions ========================= Kwant can be installed either using prepared packages (Debian and Ubuntu variants of GNU/Linux, Mac OS X, and Windows), or it can be built and installed from source. In general, installation from packages is advisable, especially for novice users. Expert users may find it helpful to build Kwant from source, as this will also allow them to customize Kwant to use certain optimized versions of libraries. ************************ Installing from packages ************************ Ubuntu (and derivatives) ======================== Execute the following commands:: sudo apt-add-repository ppa:kwant-project/ppa sudo apt-get update sudo apt-get install python-kwant python-kwant-doc This should provide Kwant for all versions of Ubuntu >= 12.04. The HTML documentation will be installed locally in the directory ``/usr/share/doc/python-kwant-doc``. Debian (and derivatives) ======================== The easiest way to install Kwant on a Debian system is using the pre-built packages we provide. Our packages are known to work with Debian "wheezy" and Debian "jessie", but they may also work on many other recent Debian-derived sytems as well. (For example, the following works with recent Ubuntu versions.) The lines prefixed with ``sudo`` have to be run as root. 1. Add the following lines to ``/etc/apt/sources.list``:: deb http://downloads.kwant-project.org/debian/ stable main deb-src http://downloads.kwant-project.org/debian/ stable main 2. (Optional) Add the OpenPGP key used to sign the repositories by executing:: sudo apt-key adv --keyserver pgp.mit.edu --recv-key C3F147F5980F3535 3. Update the package data, and install Kwant:: sudo apt-get update sudo apt-get install python-kwant python-kwant-doc The ``python-kwant-doc`` package is optional and installs the HTML documentation of Kwant in the directory ``/usr/share/doc/python-kwant-doc``. Should the last command (``apt-get install``) fail due to unresolved dependencies, you can try to build and install your own packages, which is surprisingly easy:: cd /tmp sudo apt-get build-dep tinyarray apt-get source --compile tinyarray sudo dpkg -i python-tinyarray_*.deb sudo apt-get build-dep kwant apt-get source --compile kwant sudo dpkg -i python-kwant_*.deb python-kwant-doc_*.deb This method should work for virtually all Debian-derived systems, even on exotic architectures. Windows ======= There are multiple distributions of scientific Python software for Windows that provide the prerequisites for Kwant. We recommend to use the packages kindly provided by Christoph Gohlke. To install Kwant on Windows 1. Determine whether you have a 32-bit or 64-bit Windows installation by following these `instructions <http://support.microsoft.com/kb/827218>`_. 2. Download and install Python 2.7 for the appropriate architecture (32-bit or 64-bit) from the official `Python download site <http://www.python.org/download/>`_. 3. Download and install ``scipy-stack``, ``tinyarray``, and ``kwant`` for Python 2.7 from `Christoph Gohlke's page <http://www.lfd.uci.edu/~gohlke/pythonlibs/>`_. Once again you should choose the architecture that is appropriate for your system. ("win32" means 32-bit, "amd64" means 64-bit -- even if you have a processor from Intel.) If the download from Gohlke's site is slow, try to download from `our mirror <http://downloads.kwant-project.org/gohlke-mirror/>`_. You may see a warning that says "The publisher could not be verified. Do you want to run this software?". Select "Run". Mac OS X ======== There is a number of different package managers for bringing software from the Unix/Linux world to Mac OS X. Since the community is quite split, we provide Kwant and its dependencies both via the `homebrew <http://brew.sh>`_ and the `MacPorts <http://www.macports.org>`_ systems. Mac OS X: homebrew ================== homebrew is a recent addition to the package managers on Mac OS X. It is lightweight, tries to be as minimalistic as possible and give the user freedom than Macports. We recommend this option if you have no preferences. 1. Open a terminal and install homebrew as described on the `homebrew homepage <http://brew.sh>`_ (instructions are towards the end of the page) 2. Run :: brew doctor and follow its directions. It will ask for a few prerequisites to be installed, in particular * the Xcode developer tools (compiler suite for Mac OS X) from `<http://developer.apple.com/downloads>`_. You will need an Apple ID to download. Note that if you have one already from using the App store on the Mac/Ipad/Iphone/... you can use that one. Downloading the command line tools (not the full Xcode suite) is sufficient. If you have the full Xcode suite installed, you might need to download the command line tools manually if you have version 4 or higher. In this case go to `Xcode->Preferences`, click on `Download`, go to `Components`, select `Command Line Tools` and click on `Install`. * although `brew doctor` might not complain about it right away, while we're at it, you should also install the X11 server from the `XQuartz project <http://xquartz.macosforge.org>`_ if you have Mac OS X 10.8 or higher. 3. Add permanently ``/usr/local/bin`` before ``/usr/bin/`` in the ``$PATH$`` environment variable of your shell, for example by adding :: export PATH=/usr/local/bin:$PATH at the end of your ``.bash_profile`` or ``.profile``. Then close the terminal and reopen it again. 4. Install a few prerequisites :: brew install gfortran python 5. Add additional repositories :: brew tap homebrew/science brew tap samueljohn/python brew tap michaelwimmer/kwant 6. Install Kwant and its prerequisites :: pip install nose brew install numpy scipy matplotlib brew install kwant Notes: - If something does not work as expected, use ``brew doctor`` for instructions (it will find conflicts and things like that). - As mentioned, homebrew allows for quite some freedom. In particular, if you are an expert, you don't need necessarily to install numpy/scipy/matplotlib from homebrew, but can use your own installation. The only prerequisite is that they are importable from python. (the Kwant installation will in any case complain if they are not) - In principle, you need not install the homebrew python, but could use Apple's already installed python. Homebrew's python is more up-to-date, though. Mac OS X: MacPorts ================== MacPorts is a full-fledged package manager that recreates a whole Linux-like environment on your Mac. In order to install Kwant using MacPorts, you have to 1. Install a recent version of MacPorts, as explained in the `installation instructions of MacPorts <http://www.macports.org/install.php>`_. In particular, as explained there, you will have to install also a few prerequisites, namely * the Xcode developer tools (compiler suite for Mac OS X) from `<http://developer.apple.com/downloads>`_. You will need an Apple ID to download. Note that if you have one already from using the App store on the Mac/Ipad/Iphone/... you can use that one. You will also need the command line tools: Within Xcode 4, you have to download them by going to `Xcode->Preferences`, click on `Download`, go to `Components`, select `Command Line Tools` and click on `Install`. Alternatively, you can also directly download the command line tools from the Apple developer website. * if you have Mac OS X 10.8 or higher, the X11 server from the `XQuartz project <http://xquartz.macosforge.org>`_. 2. After the installation, open a terminal and execute :: echo http://downloads.kwant-project.org/macports/ports.tar |\ sudo tee -a /opt/local/etc/macports/sources.conf >/dev/null (this adds the Kwant MacPorts download link `<http://downloads.kwant-project.org/macports/ports.tar>`_ at the end of the ``sources.conf`` file.) 3. Execute :: sudo port selfupdate 4. Now, install Kwant and its prerequisites :: sudo port install py27-kwant 5. Finally, we choose python 2.7 to be the default python :: sudo port select --set python python27 After that, you will need to close and reopen the terminal to have all changes in effect. Notes: * If you have problems with macports because your institution's firewall blocks macports (more precisely, the `rsync` port), resulting in errors from ``sudo port selfupdate``, follow `these instructions <https://trac.macports.org/wiki/howto/PortTreeTarball>`_. * Of course, if you already have macports installed, you can skip step 1 and continue with step 2. *********************************** Building and installing from source *********************************** Prerequisites ============= Building Kwant requires * `Python <http://python.org>`_ 2.6 or 2.7 (Python 3 is not supported yet), * `SciPy <http://scipy.org>`_ 0.9 or newer, * `LAPACK <http://netlib.org/lapack/>`_ and `BLAS <http://netlib.org/blas/>`_, (For best performance we recommend the free `OpenBLAS <http://xianyi.github.com/OpenBLAS/>`_ or the nonfree `MKL <http://software.intel.com/en-us/intel-mkl>`_.) * `Tinyarray <http://git.kwant-project.org/tinyarray/about/>`_, a NumPy-like Python package optimized for very small arrays, * An environment which allows to compile Python extensions written in C and C++. The following software is highly recommended though not strictly required: * `matplotlib <http://matplotlib.sourceforge.net/>`_ 1.1 or newer, for Kwant's plotting module and the tutorial, * `MUMPS <http://graal.ens-lyon.fr/MUMPS/>`_, a sparse linear algebra library that will in many cases speed up Kwant several times and reduce the memory footprint. (Kwant uses only the sequential, single core version of MUMPS. The advantages due to MUMPS as used by Kwant are thus independent of the number of CPU cores of the machine on which Kwant runs.) * The `nose <http://nose.readthedocs.org/>`_ testing framework for running the tests included with Kwant. In addition, to build a copy of Kwant that has been checked-out directly from `its Git repository <http://git.kwant-project.org/kwant>`_, you will also need `Cython <http://cython.org/>`_ 0.22 or newer. You do not need Cython to build Kwant that has been unpacked from a source .tar.gz-file. Generic instructions ==================== Kwant can be built and installed following the `usual Python conventions <http://docs.python.org/install/index.html>`_ by running the following commands in the root directory of the Kwant distribution. :: python setup.py build python setup.py install Depending on your system, you might have to run the second command with administrator privileges (e.g. prefixing it with ``sudo``). After installation, tests can be run with:: python -c 'import kwant; kwant.test()' The tutorial examples can be found in the directory ``tutorial`` inside the root directory of the Kwant source distribution. Unix-like systems (GNU/Linux) ============================= Kwant should run on all recent Unix-like systems. The following instructions have been verified to work on Debian 7 (Wheezy) or newer, and on Ubuntu 12.04 or newer. For other distributions step 1 will likely have to be adapted. If Ubuntu-style ``sudo`` is not available, the respective command must be run as root. 1. Install the required packages. On Debian-based systems like Ubuntu this can be done by running the command :: sudo apt-get install python-dev python-scipy python-matplotlib python-nose g++ gfortran libopenblas-dev liblapack-dev libmumps-scotch-dev 2. Unpack Tinyarray, enter its directory. To build and install, run :: python setup.py build sudo python setup.py install 3. Inside the Kwant source distribution's root directory run :: python setup.py build sudo python setup.py install By default the package will be installed under ``/usr/local``. You can change this using the ``--prefix`` option, e.g.:: sudo python setup.py install --prefix=/opt If you would like to install Kwant into your home directory only you can use :: python setup.py install --home=~ This does not require root privileges. If you install Kwant in this way be sure to tell python where to find it. This can be done by setting the ``PYTHONPATH`` environment variable:: export PYTHONPATH=$HOME/lib/python You can make this setting permanent by adding this line to the file ``.bashrc`` (or equivalent) in your home directory. Mac OS X: MacPorts ================== The required dependencies of Kwant are best installed with one of the packaging systems. Here we only consider the case of `MacPorts <http://www.macports.org>`_ in detail. Some remarks for homebrew are given below. 1. In order to set up MacPorts or homebrew, follow steps 1 - 3 of the respective instructions of `MacPorts`_ 2. Install the required dependencies:: sudo port install gcc47 python27 py27-numpy py27-scipy py27-matplotlib mumps_seq sudo port select --set python python27 3. Unpack Tinyarray, enter its directory, build and install:: python setup.py build sudo python setup.py install 5. Unpack Kwant, go to the Kwant directory, and edit ``build.conf`` to read:: [lapack] extra_link_args = -Wl,-framework -Wl,Accelerate [mumps] include_dirs = /opt/local/include library_dirs = /opt/local/lib libraries = zmumps_seq mumps_common_seq pord_seq esmumps scotch scotcherr mpiseq gfortran 6. Then, build and install Kwant. :: CC=gcc-mp-4.7 LDSHARED='gcc-mp-4.7 -shared -undefined dynamic_lookup' python setup.py build sudo python setup.py install You might note that installing Kwant on Mac OS X is somewhat more involved than installing on Linux. Part of the reason is that we need to mix Fortran and C code in Kwant: While C code is usually compiled using Apple compilers, Fortran code must be compiled with the Gnu Fortran compiler (there is no Apple Fortran compiler). For this reason we force the Gnu compiler suite with the environment variables ``CC`` and ``LDSHARED`` as shown above. Mac OS X: homebrew ================== It is also possible to build Kwant using homebrew. The dependencies can be installed as :: brew install gcc python brew tap homebrew/science brew tap homebrew/python brew tap michaelwimmer/kwant pip install nose six brew install numpy scipy matplotlib Note that during the installation you will be told which paths to add when you want to compile/link against scotch/metis/mumps; you need to add these to the build.conf file. Also, when linking against mumps, one needs also to link against metis (in addition to the libraries needed for MacPorts). Windows ======= Our efforts to compile Kwant on Windows using only free software (MinGW) were only moderately successful. At the end of a very complicated process we obtained packages that worked, albeit unreliably. As the only recommended way to compile Python extensions on Windows is using Visual C++, it may well be that there exists no easy solution. It is possible to compile Kwant on Windows using non-free compilers, however we (the authors of Kwant) have no experience with this. The existing Windows binary installers of Kwant and Tinyarray were kindly prepared by Christoph Gohlke. Build configuration =================== The setup script of Kwant has to know how to link against LAPACK & BLAS, and, optionally, MUMPS. By default it will assume that LAPACK and BLAS can be found under their usual names. MUMPS will be not linked against by default, except on Debian-based systems when the package ``libmumps-scotch-dev`` is installed. All these settings can be configured by creating/editing the file ``build.conf`` in the root directory of the Kwant distribution. This configuration file consists of sections, one for each dependency, led by a [dependency-name] header and followed by name = value entries. Possible names are keyword arguments for ``distutils.core.Extension`` (For a complete list, see its `documentation <http://docs.python.org/2/distutils/apiref.html#distutils.core.Extension>`_). The corresponding values are whitespace-separated lists of strings. The two currently possible sections are [lapack] and [mumps]. The former configures the linking against LAPACK _AND_ BLAS, the latter against MUMPS (without LAPACK and BLAS). Example ``build.conf`` for linking Kwant against a self-compiled MUMPS, `SCOTCH <http://www.labri.fr/perso/pelegrin/scotch/>`_ and `METIS <http://glaros.dtc.umn.edu/gkhome/metis/metis/overview>`_:: [mumps] libraries = zmumps mumps_common pord metis esmumps scotch scotcherr mpiseq gfortran Example ``build.conf`` for linking Kwant with Intel MKL.:: [lapack] libraries = mkl_intel_lp64 mkl_sequential mkl_core mkl_def library_dirs = /opt/intel/mkl/lib/intel64 extra_link_args = -Wl,-rpath=/opt/intel/mkl/lib/intel64 The detailed syntax of ``build.conf`` is explained in the `documentation of Python's configparser module <http://docs.python.org/3/library/configparser.html#supported-ini-file-structure>`_. Building the documentation ========================== To build the documentation, the `Sphinx documentation generator <http://sphinx.pocoo.org/>`_ is required with ``numpydoc`` extension (version 0.5 or newer). If PDF documentation is to be built, the tools from the `libRSVG <http://live.gnome.org/LibRsvg>`_ (Debian/Ubuntu package ``librsvg2-bin``) are needed to convert SVG drawings into the PDF format. As a prerequisite for building the documentation, Kwant must have been built successfully using ``./setup.py build`` as described above (or Kwant must be already installed in Python's search path). HTML documentation is built by entering the ``doc`` subdirectory of the Kwant package and executing ``make html``. PDF documentation is generated by executing ``make latex`` followed by ``make all-pdf`` in ``doc/build/latex``. Because of some quirks of how Sphinx works, it might be necessary to execute ``make clean`` between building HTML and PDF documentation. If this is not done, Sphinx may mistakenly use PNG files for PDF output or other problems may appear.