Migration Guide

Migrating to PyARPES v3

You no longer need to provide data spreadsheets. See the documentation at Loading Data for details on the the data loading API.

Many improvements have been made to performance. For the most part, these changes are completely transparent, as in momentum conversion which is 10-50x faster than in PyARPES v2. However, PyARPES v3 uses multiprocessing for large groups of curve fits, through the parallel=True/False kwarg to arpes.fits.utilities.broadcast_model. If you do not want to use parallel curve fitting, simply pass False to this kwarg when you do your curve fitting.

A downside to parallel curve fitting is that there is a substantial memory overhead: about 200MB / core on your computer. As most high-core computers also have more memory headroom, we felt this an appropriate default behavior. Again, you can avoid the overhead with the parallelization kwarg.

For more detailed changes see the Changelog.