Changelog

0.5.0 (TBD)

…

0.4.0 (Feb 19th, 2021)

Summary

This release brings many improvements of which the most relevant are summarised here depending on their scope within the pipeline workflow.

Performance-wise, protopipe caught up with the EventDisplay and CTAMARS historical pipelines starting from about 500 GeV onwards. Below this threshold, even if compatible with requirements, the sensitivity diverges. The cause seems to be a low-energy effect delimited to the steps before model training.

  • All pipeline

    • upgrade to the API of ctapipe 0.9.1

    • documentation also on readthedocs and link to Zenodo

    • Continuous Integration is now performed on GitHub

    • New benchmarks have been added

    • Reference analysis and benchmarks results have been updated

  • Data training

    • calibration benchmarks need only ctapipe-stage1-process

    • write_dl1 has become data_training

    • DL1 parameters and (optionally) images are merged in a single file

    • DL1 parameters names as in ctapipe and they are in degrees (TelescopeFrame)

    • scale correction with the effective focal length

    • fixed bugs and wrong behaviors

  • Modeling and DL2 production

    • fixed bugs and wrong behaviors

    • Added missing features to get closer to CTAMARS

  • DL3

    • the performance step is now based on the pyirf library

    • performance results are stored here

Contributors

Changes from previous release

Pull-requests that contain changes belonging to multiple classes are repeated.

🚀 General features

  • Performance using Pyirf (#83) @gaia-verna & @adonini

  • Towards using Pyirf (#79) @gaia-verna & @adonini

  • Upgrade of DL2 production (#77) @HealthyPear

  • Upgrade calibration benchmarks (#59) @HealthyPear

  • Upgrade of data training (#58) @HealthyPear

🐛 Bug Fixes

  • Fix calibration benchmarking settings (#100) @HealthyPear

  • Fix plot of simulated signal and noise of 2nd pass image extraction (#99) @HealthyPear

  • Upgrade of DL2 production (#77) @HealthyPear

  • Upgrade of data training (#58) @HealthyPear

🧰 Maintenance

  • Use mamba to create virtual enviroment for the CI (#101) @HealthyPear

  • Upgrade all other notebooks and their docs version (#76) @HealthyPear

  • Upgrade calibration benchmarks (#59) @HealthyPear

  • Upgrade of data training (#58) @HealthyPear

  • Enable CI from GitHub actions (#84) @HealthyPear

  • Update documentation + general maintenance (#62) @HealthyPear

0.3.0 (Nov 9th, 2020)

Summary

  • early improvements related to the DL1 comparison against the CTAMARS pipeline

  • improvements to basic maintenance

  • a more consistent approach for full-scale analyses

  • bug fixes

Contributors

Changes from previous release

🚀 General features

🌐 GRID support

🐛 Bug Fixes

🧰 Maintenance

0.2.1 (Oct 28th, 2019)

Summary

  • Released Oct 28, 2019

  • 1 contributor

  • 1 pull requests

Description

The ctapipe-based cleaning algorithm for the biggest cluster was crashing in case of cleaned images with no surviving pixel clusters.

Contributors:

In alphabetical order by first name:

  • Michele Peresano

Pull Requests

  • (#16) Bugfix: Closes #15 (Michele Peresano)

0.2.0 (Oct 24th, 2019)

Summary

  • Released Oct 24, 2019

  • 3 contributor(s)

  • 7 pull requests

Description

protopipe 0.2 now fully supports the stable release of ctapipe 0.7.0.

The main improvements involve the calibration process (high gain selected by default), the direction reconstruction and new camera-type labels.

Code based on pywi/pywi-cta libraries, relevant for wavelet-based image cleaning, has been removed in favor of ctapipe or made completely optional where needed. Wavelet cleaning is still optional but will need those two libraries to be additionally installed. Tailcut-based cleaning is now faster.

The README has been improved with installation, basic use, and developer instructions. Dependencies are listed in protopipe_environment.yaml and have been simplified.

The auxiliary scripts merge_tables.py and merge.sh have been added to allow merging of DL1 and DL2 HDF5 tables.

The mars_cleaning_1st_pass method is now imported from _ctapipe_. Novel code using the largest cluster of survived pixels (number_of_islands and largest_island methods in the event_preparer module) has been hardcoded in _protopipe_ and will disappear with the next release of _ctapipe_.

Model estimators now load the camera types directly from the analysis .yaml configuration file.

Contributors:

In alphabetical order by first name:

  • Alice Donini

  • Michele Peresano

  • Thierry Stolarczyk

Pull Requests

This list is incomplete. Small improvements and bug fixes are not listed here.

The complete list is found here.

  • (#9) Update image cleaning and make wavelet-based algorithms independent

  • (#8) Import CTA-MARS 1st pass cleaning from ctapipe

0.1.1 (Oct 1st, 2019)

Summary

  • Released Oct 1, 2019

  • X contributor(s)

  • X pull request(s)

Description

The write_dl1 and write_dl2 tools can now save an additional file through the flag --save-images when applied to a single run. This file will contain the original and calibrated (after gain selection) photoelectron images per event. A new method save_fig has been introduced in the utils module, so that model_diagnostic can save images also in PNG format. Additional docstrings and PEP8 formatting have been added throughout the code.

Contributors:

In alphabetical order by first name:

  • …

Pull Requests

The development of protopipe on GitHub started out directly in the master branch, so there are no pull request we can list here.

0.1.0 (Sep 23th, 2019)

Summary

  • Released Sep 23, 2019

  • 6 contributor(s)

  • 1 pull request(s)

Description

First version of protopipe to be publicly release on GitHub. This version is based on ctapipe 0.6.2 (conda package stable version). Its performance has been shown in a presentation at the CTAC meeting in Lugano 2019.

Contributors:

In alphabetical order by first name:

  • David Landriu

  • Julien Lefacheur

  • Karl Kosack

  • Michele Peresano

  • Thomas Vuillaume

  • Tino Michael

Pull Requests

  • (#2) Custom arrays, example configs and aux scripts (M.Peresano)