Welcome to pyEvalData#

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This is a Python module to read and evaluate experimental data. It can handle raw data from different sources such as spec, hdf5, NeXus files which are common data formats at synchrotrons, FELs, as well as in a growing number of laboratories. The evaluation provides common functionalities such as binning, error calculation, and advanced data manipulation via algebraic expressions as well as pre- and post-data-filters. Furthermore, advanced wrapper functions allow for plotting and fitting sequences of one or multiple scans in dependence of an external parameter.

A minimal code example would look like this:

import pyEvalData as ped
# define your data source
spec = ped.io.Spec(file_name='data.spec')
# initialize the evaluation
ev = ped.Evaluation(spec)
# define the x- and y-data
ev.xcol = 'motor1'
ev.clist = ['ct1', 'ct2', 'ct1/ct2']
# create a plot for scans 1-3
ev.plot_scans([1, 2, 3])

Please follow the user guide and examples for your first steps with pyEvalData.


  • reading of several pre-defined raw data formats

    • spec

    • hdf5

    • NeXus

    • user-defined text files

    • camera images (Dectris Pilatus, Princeton MTE, Greateyes, …)

    • composite sources

  • easy implementation of new raw-data formats using an interface class

  • common methods for plotting and fitting of experimental data, including:

    • data binning

    • error calculation

    • data manipulation via algebraic expressions

    • common data pre- and post-filters


You can either install directly from pypi.org using the command

$ pip install pyEvalData

or if you want to work on the latest develop release you can clone pyEvalData from the main git repository:

$ git clone https://github.com/dschick/pyEvalData.git pyEvalData

To work in editable mode (source is only linked but not copied to the python site-packages), just do:

$ pip install -e ./pyEvalData

Or to do a normal install with

$ pip install ./pyEvalData

Optionally, you can also let pip install directly from the repository:

$ pip install git+https://github.com/dschick/pyEvalData.git

You can have the following optional installations to enable unit tests, as well as building the documentation:

$ pip install pyEvalData[testing]
$ pip install pyEvalData[documentation]

Contribute & Support#

If you are having issues please let us know via the issue tracker.

You can contribute to the project via pull-requests following the GitHub flow concept.


The project is licensed under the MIT license.

Indices and tables#