v3.2.0

This maintenance release accommodates the deprecation of installing a package with setup.py. It also establishes the CI pipeline again and includes testing across multiple python versions and operating systems.

What's Changed

• build: switch to pyproject.toml by @wibuhm in #21
• CI unit tests by @rpartzsch in #19
• Fix examples with py3 by @cbespin in #22
• Release: 3.2.0 by @cbespin in #24

New Contributors

• @wibuhm made their first contribution in #21
• @rpartzsch made their first contribution in #19
• @cbespin made their first contribution in #22

Full Changelog: 3.1.7...3.2.0

Maintanance release

Cache numba compiled code and suppress numpy warnings.

3.1.5

• support of clustering positions/coordinates in addition to indices
• adding parameter to enable/disable (default) charge weighted clustering
• adding a parameter to adjust the charge offset (in case where charge weighted clustering is enabled)
• code cleanup

Bugfix Release 3.1.4

• fixing JIT issues on several platforms and installation methods (pip install vs. python setup.py) when executing the clusterizer in a multiprocessing environment

Bugfix Release 3.1.3

• fixing pickling of jitted cluster functions when module is installed into site-packages folder

Bugfix Release 3.1.2

• Cleanup
• Support multiprocessing

Bugfix version

Increase Package version to 3.1.1

Bugfix and enhancements

Bug fixed:

• No crash if hit array is empty

Enhancements:

• Example how to add col/row distance calculation added
• Hit field definition simplified and checks added
• End of cluster/event functions can be jitted manually to allow for special jut arguments
• Small code clean up

Feature release with API changes

• Noisy pixel mask supported
• Disabled pixel mask supported
• Min/max hit charge can be set
• API changes (e.g. array size does not have to be specified)
• More tests / coverage
• Clean up

Minor data format change

This release changes the cluster data format! The mean column / row are not centered anymore.

Consider a cluster with on pixel at column / row = 1 / 2

Before:
cluster: mean column / mean row = 1.5 / 2.5

Now:
cluster: mean column / mean row = 1.0 / 2.0

This adresses issue #2 and solves the discrepancy that cluster seeds were not shiftet by 0.5.