Installation¶

Using QuTiP’s PPA¶

The easiest way to install QuTiP in Ubuntu (14.04 and later) is to use the QuTiP PPA

sudo add-apt-repository ppa:jrjohansson/qutip-releases
sudo apt-get update
sudo apt-get install python-qutip

A Python 3 version is also available, and can be installed using:

sudo apt-get install python3-qutip

With this method the most important dependencies are installed automatically, and when a new version of QuTiP is released it can be upgraded through the standard package management system. In addition to the required dependencies, it is also strongly recommended that you install the texlive-latex-extra package:

sudo apt-get install texlive-latex-extra

Manual installation of dependencies¶

First install the required dependencies using:

sudo apt-get install python-dev cython python-setuptools python-nose
sudo apt-get install python-numpy python-scipy python-matplotlib

Then install QuTiP from source following the instructions given above.

Alternatively (or additionally), to install a Python 3 environment, use:

sudo apt-get install python3-dev cython3 python3-setuptools python3-nose
sudo apt-get install python3-numpy python3-scipy python3-matplotlib

and then do the installation from source using python3 instead of python.

Optional, but recommended, dependencies can be installed using:

sudo apt-get install texlive-latex-extra # recommended for plotting
sudo apt-get install mayavi2             # optional, for Bloch3d only
sudo apt-get install libblas-dev         # optional, for Fortran Monte Carlo solver
sudo apt-get install liblapack-dev       # optional, for Fortran Monte Carlo solver
sudo apt-get install gfortran            # optional, for Fortran Monte Carlo solver

Setup Using Homebrew¶

The latest version of QuTiP can be quickly installed on OS X using Homebrew and the automated installation shell scripts

Python 2.7 installation script

Python 3.4 installation script

Having downloaded the script corresponding to the version of Python you want to use, the installation script can be run from the terminal using (replacing X with 2 or 3)

sh install_qutip_pyX.sh

The script will then install Homebrew and the required QuTiP dependencies before installing QuTiP itself and running the built in test suite. Any errors in the homebrew configuration will be displayed at the end. Using Python 2.7 or 3.4, the python commend-line and IPython interpreter can be run by calling python and ipython or python3 and ipython3, respectively.

If you have installed other packages in the /usr/local/ directory, or have changed the permissions of any of its sub-directories, then this script may fail to install all the necessary tools automatically.

Setup Using Macports¶

If you have not done so already, install the Apple Xcode developer tools from the Apple App Store. After installation, open Xcode and go to: Preferences -> Downloads, and install the ‘Command Line Tools’.

On the Mac OS, you can install the required libraries via MacPorts. After installation, the necessary “ports” for QuTiP may be installed via (Replace ‘34’ with ‘27’ if you want Python 2.7)

sudo port install py34-scipy
sudo port install py34-matplotlib +latex
sudo port install py34-cython
sudo port install py34-ipython +notebook+parallel
sudo port install py34-pip

Now, we want to tell OS X which Python and iPython we are going to use

sudo port select python python34
sudo port select ipython ipython34
sudo port select pip pip34

We now want to set the macports compiler to the vanilla GCC version. From the command line type

port select gcc

which will bring up a list of installed compilers, such as

Available versions for gcc:
        mp-gcc48
        none (active)

We want to set the the compiler to the gcc4x compiler, where x is the highest number available, in this case mp-gcc48 (the “mp-” does not matter). To do this type

sudo port select gcc mp-gcc48

Running port select again should give

Available versions for gcc:
       mp-gcc48 (active)
       none

To install QuTiP, run

sudo pip install qutip --install-option=--with-f90mc

Setup via SciPy Superpack¶

A third option is to install the required Python packages using the SciPy Superpack. Further information on installing the superpack can be found on the SciPy Downloads page.

Anaconda CE Distribution¶

Finally, one can also use the Anaconda CE package to install all of QuTiP.

UMFPACK Linear Solver¶

As of SciPy 0.14+, the umfpack linear solver routines for solving large-scale sparse linear systems have been replaced due to licensing restrictions. The default method for all sparse linear problems is now the SuperLU library. However, scipy still includes the ability to call the umfpack library via the scikits.umfpack module. In our experience, the umfpack solver is 2-5x faster than the SuperLU routines, which is a very noticeable performance increase when used for solving steady state solutions. We have an updated scikits.umfpack module available at http://github.com/nonhermitian/umfpack that can be installed to have SciPy find and use the umfpack library.

Optimized BLAS Libraries¶

QuTiP is designed to take advantage of some of the optimized BLAS libraries that are available for NumPy. At present, this includes the OPENBLAS and MKL libraries. If NumPy is built against these libraries, then QuTiP will take advantage of the performance gained by using these optimized tools. As these libraries are multi-threaded, you can change the number of threads used in these packages by adding:

>>> import os
>>> os.environ['OPENBLAS_NUM_THREADS'] = '4'
>>> os.environ['MKL_NUM_THREADS'] = '4'

at the top of your Python script files, or iPython notebooks, and then loading the QuTiP framework. If these commands are not present, then QuTiP automatically sets the number of threads to one.