INSTALL.rst

Installation instructions

Kwant can be installed either using prepared packages (Debian, Ubuntu, and Arch variants of GNU/Linux, Mac OS X, Microsoft 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

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 pool.sks-keyservers.net --recv-key C3F147F5980F3535

   The fingerprint of the key is 5229 9057 FAD7 9965 3C4F 088A C3F1 47F5 980F 3535.

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.

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.

Arch Linux

Arch install scripts for Kwant are kindly provided by Jörg Behrmann (formerly by Max Schlemmer). To install, follow the Arch User Repository installation instructions. Note that for checking the validity of the package you need to add the key used for signing to your user's keyring via:

gpg --keyserver pool.sks-keyservers.net --recv-key C3F147F5980F3535

The fingerprint of the key is 5229 9057 FAD7 9965 3C4F 088A C3F1 47F5 980F 3535.

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 and the MacPorts 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 (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 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. 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.

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.
• Of course, if you already have macports installed, you can skip step 1 and continue with step 2.

Microsoft 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.

2. Download and install Python 2.7 for the appropriate architecture (32-bit or 64-bit) from the official Python download site.

3. Open a command prompt, as described in "How do I get a command prompt" at the Microsoft Windows website.

4. In the command prompt window, execute:

   C:\Python27\python.exe C:\Python27\Tools\Scripts\win_add2path.py

   (Instead of typing this command, you can also just copy it from here and paste it into the command prompt window). If you did not use the default location to install Python in step 2, then replace C:\Python27 by the actual location where Python is installed.

5. Reboot your computer.

6. Download the necessary packages (with the ending .whl) for your operating system (32 or 64 bit) and Python version (e.g. cp27 for Python 2.7) from the website of Christoph Gohlke. For Kwant, we recommend to download at least NumPy, SciPy, Matplotlib, Nose, Tinyarray, and Kwant itself.

7. Now open a command prompt with administrator rights, as described in "How do I run a command with elevated permissions" at the Microsoft Windows website.

   In this new command prompt window, execute

   pip install <filename>

   for each of the downloaded files (replacing <filename> with it).

   Now you are done, you can import kwant from within Python scripts.

(Note that many other userful scientific packages are available in Gohlke’s repository. For example, you might want to install IPython and its various dependencies so that you can use the IPython notebook.)

Building and installing from source

Prerequisites

Building Kwant requires

• Python 2.6 or 2.7 (Python 3 is not supported yet),
• SciPy 0.9 or newer,
• LAPACK and BLAS, (For best performance we recommend the free OpenBLAS or the nonfree MKL.)
• Tinyarray, 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 1.1 or newer, for Kwant's plotting module and the tutorial,
• 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 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, you will also need Cython 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 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 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). 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 and METIS:

[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.

Building the documentation