Installation of PYME on 64 bit Windows, OSX, or Linux¶
PYME requires python (version 2.7) and a number of additional scientific packages. Although it is possible to install all packages individually, and then install PYME, by far the easiest way to get a system up and running is to install a pre-packaged ‘scientfic python’ distribution. Anaconda is one such distribution which is free for both academic and commercial use and includes extensive package management capabilities which allow us to easily distribute and update PYME on a variety of platforms. We currently provide compiled packages for 64 bit windows, OSX, and Linux.
This is the recommended way of installing PYME in most circumstances. If you absolutely don’t want to deal with the command line there is also a completely graphical way of doing the installation. If you are looking to actively develop PYME or want to use it to control microscope hardware, see Installation for development or instrument control.
The instructions here assume a clean anaconda install. If you already use anaconda for other work, consider installing PYME in a dedicated conda environment e.g. conda create -n PYME python=2.7 (see https://conda.io/docs/user-guide/tasks/manage-environments.html for details). The downside of this is that you will need to run source activate PYME before you can run any of the PYME programs. You might also not be able to associate files to open with dh5view or VisGUI on windows.
STEP 1: Installing Anaconda¶
Anaconda is available in both Python 2.7 and Python 3.x flavours. PYME will only work with the Python 2.7 version.
STEP 2: Installing PYME using conda¶
Anaconda comes with a built in package manager called conda which can be used to install additional packages. In addition to the main set of packages maintained by Continuim Analytics (the developers of anaconda) conda can install packages which members of the community have uploaded to binstar.org. The python-microscopy package and a number of it’s dependencies are available through the david_baddeley binstar channel. To install PYME, we first need to tell conda to use the david_baddeley channel in addition to it’s existing channels. We can simply tell conda to install the package named python-microscopy.
This is accomplished by opening a terminal window (On OSX use spotlight to launch the Terminal app, on Windows, launch the Anaconda Command Prompt from the “Anaconda” group in the start menu) and running the following two commands:
conda config --add channels david_baddeley conda install python-microscopy
This should download and install PYME, along with a number of it’s dependencies.
Troubleshooting: There appears to be a dependency conflict between the mayavi (which we use for 3D
visualization) and navigator-updater packages in recent versions of Anaconda. As navigator-updater
is installed by default, this can prevent python-microscopy from installing. If the installation above fails
with an error message about dependencies, try running
conda uninstall navigator-updater and then re-running
conda install python-microscopy.
Other dependency issues can result in an old version of PYME being installed (most likely in older anaconda installs) A good sanity check is to look at what version conda wants to install when you run conda install python-microscopy. If it’s older than a month or two (PYME uses date based versions) something is going wrong.
STEP 3: Verifying the Installation¶
From the command prompt, launch any of the following programs, which should have been installed as part of PYME.
||This is the data acquistion component, which when launched without any options will start with simulated hardware.|
||This is a viewer for point data sets. When launched without any parameters it will show a large pink triangle.|
STEP 4: Setting up bioformats importing [optional]¶
PYME (or specifically dh5view) can use bioformats to load data formats it doesn’t natively support. For this to work you need to have java (JRE should be enough, but as the JDK is needed to compile the interface modules I have only tested with that) and the following 2 python modules installed:
For OSX, I have compiled versions of these in the david_baddeley channel which you can get using
conda install. On other platforms you will have to download the JDK and build these from source (both are on github). You might also get away with
pip install ing them.