All the Best

Stephan
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NumPy-Discussion mailing li

Dear Community,

For my own work, I required the intersect1d function to work on multiple
arrays while returning the indices (using `return_indizes=True`).
Consequently I changed the function in numpy and now I am seeking
feedback from the community.

This is the corresponding PR: https://github.com/numpy/numpy/pull/25688

My motivation for the change may also apply to a larger group of people
as it is important for lots of simulation data analysis:

In various simulations there is often the case that many entities
(particles, cells, vehicles, whatever the simulation consists of) are
being tracked throughout the simulation. A typical approach is to assign
a unique ID to every entity which stays constant and unique throughout
the simulation and is written together with other properties of the
entities on every simulation snapshot in time. Note, that during the
simulation new entities may enter or leave the simulation and due to
parallelization the order of those entities is not conserved.
Tracking the position of entities over, lets say, 100 snapshots requires
the intersection of 100 id lists instead of only two.

Consequently I changed the intersect1d function from
`intersect1d(ar1, ar2, assume_unique=False, return_indices=False)` to
`intersect1d(*ars, assume_unique=False, return_indices=False)`.

Please let me know if there is any interest in those changes -- be it in
this form or another.