Releases: fact-project/aict-tools
Releases · fact-project/aict-tools
v0.27.1 – 2021-05-05
v0.27.0 – 2021-04-06
- Add preliminary support for the ctapipe DL1 format. Applying cuts, training and applying models is possible now. (#142) @LukasNickel @maxnoe
v0.26.0
This release drops support for python 3.7, following the same decision in our dependencies astropy and numpy
- New method for origin reconstruction: dx/dy regression (#145) @ArnePoggenpohl
- Improvements to
fact_to_dl3
(#148) @maxnoe- add zd / az predictions also for simulations
- fix tool for when just 1 process is used
- make use of
ErfaAstromInterpolator
to speed up coordinate transform
v0.25.1
v0.25.0
v0.25.0
-
Important From this version onwards, the aict-tools won't require a fixed version of scikit-learn and will try to support the most recent versions. This means you should pin the scikit-learn version when using the aict-tools yourself.
-
Fix an issue with padding in the disp plots
v0.24.2
v0.24.1
v0.24.0
v0.24.0
This is a pretty large release with lots of improvements regarding CTA integration.
- Added config options for all columns where units are needed (e.g. az_pointing_unit).
The defaults follow the conventions of the FACT-Tools analysis chain, for CTA you will need to define
these options appropriately. (e.g.delta_unit: deg
- Similarly, one can now provide either altitude or zenith distance, mutually exclusive
- If the global config options
true_energy_column
orsize_column
are set, these values are stored in the cross validation output hdf5 file, to enable energy/size dependent performance evaluation.
For now, this is only used inplot_disp_performance
, where r2 score and sign accuracy are shown versus true energy.