Installation¶
The best to install PYME will depend on your background and whether you are already using python on your computer.
Executable installers (Windows-only)¶
Recommended if you don’t already have python on your computer and/or are unfamiliar with python. Download the latest installer from https://python-microscopy.org/downloads/. Double-click the installer and follow instructions.
Caveats: The executable installers lag the conda packages so you’re getting an older version. The installers give you a bunch of error messages which you can safely ignore.
Installing using conda¶
Download and install the python 2.7 version of Miniconda. Then, open the Anaconda prompt 1 and enter
conda config --append channels anaconda
conda config --add channels david_baddeley
conda install python-microscopy
Note
Which python version? We are currently in the process of switching the default install from python 2.7 to python 3. As of 2020/8/6 the python 3 packages are not in the above conda channel, but that should change shortly. The python2.7 version is better tested, but most of the core functionality now runs on python 3 as well.
Updating¶
Assuming that you’ve installed using either the executable or conda routes, you can update PYME by dropping into the Anaconda prompt 1 and entering:
conda update python-microscopy
Development installs¶
This assumes a basic familiarity with python and conda. We maintain a conda metapackage, pyme-depends for PYMEs dependencies, and reccomend a separate conda environment for development installs. Entering the following at the command prompt should get you a functional system, alter to suit your needs:
conda config --add channels david_baddeley
conda create -n pyme pyme-depends python=X.X
conda activate pyme
git clone https://github.com/python-microscopy/python-microscopy.git
cd python-microscopy
python setup.py develop
On OSX, use /path/to/conda/environment/python.app/Contents/MacOS/python setup.py develop instead of python setup.py develop so that the PYME programs can access the screen.
Enable bioformats data importers¶
Install a JAVA JDK or JRE. Open a command prompt in the installation conda
environment and enter
conda install javabridge
conda install python-bioformats
Caveat: This currently only works on OSX. If conda packages for javabridge and bioformats don’t work, try pip.
Verify installation¶
Locate the PYMEVisualize (VisGUI) desktop shortcut. Double-click it and confirm the program launches. If you don’t have a desktop shortcut, launch any of the following programs from an anaconda prompt, which should have been installed as part of PYME.
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This is for viewing images. The -t option initiates a test mode which displays an image of random noise. |
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This for acquiring data from a custom microscope. When launched without any options, it will start with simulated hardware. It will display a live image of random noise, streamed from a simulated camera. |
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This is for viewing point data sets. It shows a blank canvas when launched without any parameters. |
Troubleshooting¶
Executable installers¶
If prompted with Windows protected your PC, click More info and then Run anyway.
If prompted with Installation error, press OK and then Ignore.
Developer installs [OSX]¶
On OSX, the following error may appear when launching a PYME application from the command line.
This program needs access to the screen. Please run with a Framework build of python,
and only when you are logged in on the main display of your Mac.
This can be solved by the following.
cd /path/to/python-microscopy/
/path/to/mininconda/install/python.app/Contents/MacOS/python setup.py develop
Additional resources¶
Detailed developer installation docs are located at Installation for development or instrument control
A step by step walkthough of installation using anaconda along with some troubleshooting tips can be found at Installation of PYME on 64 bit Windows, OSX, or Linux
pip installation [EXPERIMENTAL]¶
You can also install PYME using pip, although we recommend this as a last resort as a conda based installation will generally give better performance and should be easier. When using pip, you might need to manually hunt down some dependencies, and for dependencies which don’t have binary wheels, you might need to spend a lot of time setting up the development evironment and finding the DLLs etc which dependencies link against. Some of our dependencies also need to be compiled using gcc (rather than MSVCC), even on windows. Because we view this as a fallback when, e.g. conda can’t come up with a resolvable set of dependencies, or when you are installing on top of a bunch of existing packages, the pip packages depend only on numpy, with the rest of the dependencies being installed separately through the use of a requirements.txt file.
pip install -r https://raw.githubusercontent.com/python-microscopy/python-microscopy/master/requirements.txt
pip install python-microscopy
If installing in a tricky evironment, you can manually edit requirements.txt before installing. You can also use the top line to setup for a development install.
Footnotes