Like many python modules PsychoPy is built and dependent on a number of other libraries (OpenGL, numpy...). Details on how to install those are below.
The bare minimum requirements for PsychoPy are a graphics card that supports OpenGL (most graphics cards do, but on windows you should install new drivers from the graphics card the windows-supplied drivers are buggy and sometimes don’t support OpenGL at all).
Ideally OpenGL 2.0 should be supported - certain functions run much faster with where it is available and some stimuli (e.g. ElementArrayStim) even requires it.
If you’re thinking of buying a laptop for running experiments, avoid the built-in intel graphics chips (e.g. GMA 950). The drivers are crummy and performance is poor. Get something with nVidia or ATI chips instead.
If you’re new to python then you probably want to install the standalone package. This includes a copy of python and all the dependent libraries (if you do have python already installed, that won’t be touched by this installation). Once installed, you’ll now find a link to the PsychoPy application in >Start>Progams>PsychoPy2. Click that and then on the demos menu to get going.
You should make sure you have reasonably current drivers for your graphics card (download the latest from the vendor, rather than using the pre-installed windows drivers).
The standalone installer adds the PsychoPy folder to your path, so you can run the included version of python from the command line etc. If you have your own version of python installed as well then you need to check which one is run by default, and change your path according to your personal preferences.
There are different ways to install PsychoPy on a mac that will suit different users
Intel Mac users (with OS X v10.5) can simply download the standalone application bundle (the dmg file) and drag it to their Applications folder. The app bundle contains its own independent python and all the dependencies and will not interact with anything else on your system (except its own preferences).
sudo port install py25-psychopy
(thanks James Kyles for that).
For PPC macs (or for intel mac users that want their own custom python for running PsychoPy) you need to install the dependencies and PsychoPy manually. The easiest way is to use the Enthought Python Distribution. It’s free (for academic use) and the only things it misses are avbin (if you want to play movies) and pygame (for sound reproduction). You could alternatively manually install the ‘framework build’ of python and download all the dependencies below. One advantage to this is that you can then upgrade versions with:
sudo /usr/local/bin/easy_install-2.5 -N -Z -U psychopy
For Debian users, PsychoPy is in the Debian packages index so you can simply do:
sudo apt-get install psychopy
For Debian-based distributions (e.g. Ubuntu):
Add the following sources in Synaptic, in the Configuration>Repository dialog box, under “Other software”:
deb http://neuro.debian.net/debian karmic main contrib non-free deb-src http://neuro.debian.net/debian karmic main contrib non-freeThen follow the ‘Package authentification’ procedure described in http://neuro.debian.net/
Then install the psychopy package under Synaptic or through sudo apt-get install psychopy which will install all dependencies.
For non-Debian systems you need to install the dependencies below manually and then PsychoPy (with easy_install?).
Thanks to Yaroslav Halchenko for his work on the Debian package.
If you want to install each library individually rather than use the simple distributions of packages above then you can download the following. Make sure you get the correct version for your OS and your version of Python.
In addition to the required packages above, there are numerous other additional packages that are useful to PsychoPy users, e.g. for controlling hardware and performing specific tasks. These are packaged with the Standalone versions of PsychoPy but users with their own custom Python environment need to install these manually to use them. Most of these can be installed with easy_install
General packages:
- psignifit for bootsrtapping and other resampling tests
- pyserial for interfacing with the serial port
- parallel python (aka pp) for parallel processing
Specific hardware interfaces:
- pynetstation to communicate with EGI netstation. See notes on using egi (pynetstation)
- ioLabs toolbox
- labjack tolbox
For developers:
- nose and coverage for running unit tests (if this means nothing to you don’t worry)
- sphinx for documentation
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