Skip to content

Improve statistics aggregators #2848

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
wants to merge 11 commits into
base: main
Choose a base branch
from
Draft

Improve statistics aggregators #2848

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
11 commits
Select commit Hold shift + click to select a range
0f982b5
Add option to aggregate statistics by time
mexanick Sep 29, 2025
2d5ac5e
Escape asteriscs in the docs and add changelog
mexanick Sep 30, 2025
1b03740
make docstrings r-strings to avoid issues with py<3.12
mexanick Sep 30, 2025
3c493e0
refactor to reduce cognitive complexity
mexanick Sep 30, 2025
d4651ce
Factor out basic aggregation functinoality
mexanick Sep 30, 2025
63dc69c
make add_result_column private
mexanick Oct 1, 2025
f294829
Fix StatisticsAggregator
mexanick Oct 1, 2025
a1b1415
Change name of the expected time column from "time_mono" to "time"
mexanick Oct 1, 2025
f0e17d3
Fix 1D arrays aggregation
mexanick Oct 2, 2025
a598ee7
Fix NaN handling
mexanick Oct 2, 2025
045fcb6
fix typo in `calculator` doc string
matteobalbo Oct 7, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 6 additions & 0 deletions docs/changes/2848.feature.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,6 @@
Enhanced ``StatisticsAggregator`` classes to support time-based chunking in addition to event-based chunking.

Introduced ``BaseAggregator`` as a new base class for all aggregators, allowing extensions beyond statistics aggregation.
The new ``chunking_mode`` parameter allows aggregating statistics over time intervals (seconds) rather than
fixed event counts, enabling time-series analysis. The aggregators now work with any N-dimensional event-wise data,
making them universally applicable across different data types in ctapipe.
Loading