pyOPALTools

pyOPALTools is a post-processing library written in Python. The main idea behind the library is to provide a common interface to all output formats generated by OPAL in order to analyse the data. In the directory pyOPALTools/opal/test/ you can find several notebooks that show the usage of the library.

Main developers:

• Matthias Frey (PSI)
• Jochem Snuverink (PSI)
• Andreas Adelmann (PSI)

Other contributors:

• Nicole Neveu (SLAC)
• Ryan Roussel (UCLA)
• Philippe Ganz (PSI)
• Renato Bellotti (PSI)

You might also check out the graph.

Direct Use

It is recommended to create a Python virtual environment where you install all necessary Python packages:

• numpy (version
  \ge
  1.13.3)
• scipy (version
  \ge
  0.19.1)
• jupyter notebook
• matplotlib (version
  \ge
  2.1.0)
• h5py (version
  \ge
  2.7.1)
• seaborn (version
  \ge
  0.8.1)
• plotly (version
  \ge
  2.5.1)
• pandas (version
  \ge
  0.21.0)
• pyaml (version
  \ge
  18.11.0)
• pickleshare (version
  \ge
  0.7.4)

In order to work properly you need to append the path of the root directory of pyOPALTools to PYTHONPATH, i.e.

export PYTHONPATH=/path/to/root/of/pyOPALTools/:$PYTHONPATH

You can check if it works by importing the library in an interactive session, e.g.

>>> import opal
>>>

Installation with setup.py

You can also use the setup.py in order to install the opal package in your Python virtual environment. For this purpose you just call

python setup.py install

in the root directory of pyOPALTools. Make sure you have the virtual environment loaded otherwise it will be installed to your default Python. This will install all dependencies and the opal package.