v0.10.2

What's Changed

• Update help description of callbacks by @rcervinoucm in #233

Full Changelog: v0.10.1...v0.10.2

v0.10.1

What's Changed

• Version script reupload by @rcervinoucm in #222
• Update release.yml to manually trigger CD workflow by @rcervinoucm in #223
• Update environment.yml with setuptools package by @rcervinoucm in #224
• Update pyproject.toml with setup tools by @rcervinoucm in #225
• CTLearn Docker container by @TjarkMiener in #231
• Add EarlyStopping option for training by @rcervinoucm in #217
• Polishing docs for v0.10.X by @TjarkMiener in #228

Full Changelog: v0.10.0...v0.10.1

v0.10.0

What's Changed

• Update build configuration, use setuptools_scm by @maxnoe in #199
• Transform back the predicted quantities into proper the space for real data by @TjarkMiener in #200
• Hot fix dependencies by @rcervinoucm in #203
• Allow extrapolation for the pointing by @TjarkMiener in #204
• Added Exceptions to Handle Non-Existent Directories by @Olmichu22 in #206
• Update run_model.py by @rcervinoucm in #209
• Adopts ctapipe components and tools & defines API for CTLearn models by @TjarkMiener in #213
• Fix LST1 tool based on lstchain data by @TjarkMiener in #214
• Bug fixes for prediction tools by @TjarkMiener in #215
• Updating metadata for 0.10.0 by @nietootein in #220

New Contributors

• @maxnoe made their first contribution in #199
• @Olmichu22 made their first contribution in #206

Full Changelog: v0.9.0...v0.10.0

v0.9.0

What's Changed

• fix numpy bug by @TjarkMiener in #190
• CI&CD fixes by @rcervinoucm in #192
• Properly perform direction task for any arbitrary tel pointing by @TjarkMiener in #194
• Cluster env file by @TjarkMiener in #191
• Support only ctapipe data format v6.0.0 by @TjarkMiener in #193
• Issue hotfix by @rcervinoucm in #198

Full Changelog: v0.8.0...v0.9.0

v0.8.0

CTLearn Release v0.8.0

Waveform processing
AI-Trigger application
LST-1 observation processing

Major Features

• AI-based trigger system #180

Minor Improvements

• Added the SST1M camera to the default config files
• Renamed the default CTLearn's model: mergedTRN to stackedTRN
• Added default models for calibrated waveforms and AITrigger
• Improving docs and README
• Upgrade to dl1dh v0.11.1, ctapipe v0.20.0 , pyirf to v0.11, TensorFlow v2.15 & python 3.10

Bug Fixes and Other Changes

Known Issues

• Particle classification is not working with Multitask Learning models yet.

v0.7.0

CTLearn Release v0.7.0

GitHub actions and featuring of the LSTSiPM camera

Major Features

• Fixed GitHub actions #162 @nietootein

Minor Improvements

• Added the LSTSiPM camera to the default config files #167
• Renamed the structure of CTLearn's core modules
• Get viewcone from difference of max and min stored in the file
• Improving docs and README
• Upgrade to dl1dh v0.10.10, ctapipe v0.19.0 , pyirf to v0.8, TensorFlow v2.9 & python 3.10

Bug Fixes and Other Changes

Known Issues

• Particle classification is not working with Multitask Learning models yet.

v0.6.1

CTLearn Release v0.6.1

Output (dl2-like) format handling and creation of an IRF builder using pyirf #142
Store keras model in onnx format #143

Major Features

• Speeding up the output writing by pseudo-chunk processing of the keras predictions
• Clean up CNNRNN model via TimeDistributed layer
• Enable learning rate reducer (including early stopper) callback
• Automatised class label handling for multiple particle types
• Set cleaning from the command line via a flag. Therefore default models with cleaned images can be removed.

Minor Improvements

• Store only the best model checkpoints for validation metric
• Improve installation process of TF by removing cpu/gpu mode
• Upgrade supplementary scripts to the new output format
• Upgrade to dl1dh v0.10.7, ctapipe v0.15.0 & python 3.9

Bug Fixes and Other Changes

Known Issues

• Particle classification is not working with Multitask Learning models yet.
• There is some version incompatibility (numpy and numba) when trying to run on Wilkes-3.

v0.6.0

CTLearn Release v0.6.0

Major upgrade to TensorFlow v2.8 #137
Sphinx docs #139

Major Features

• Upgrade the models to the Keras API in order to run with TF v2.8
• Enable usage of multiple GPUs via tf.distribute.MirroredStrategy
• Make CTLearn user-friendly by allowing several analysis options (like reconstruction tasks, directories, telescope types/ids, quality cuts) to be set from command line. Therefore minimum information about the model has to be included in the config file. Default CTLearn models can be constructed from the command line via default config files shipped by the installation.
• Balance the data for the classification task by default
• Add Sphinx docs and additional code meta data @nietootein

Minor Improvements

• ResNets can be constructed with the SingleCNN model.
• Store Only the best model checkpoints
• Model architecture & matrices can be plotted automatically
• Upgrade to dl1dh v0.10.5, ctapipe v0.12.0 & python 3.8

Bug Fixes and Other Changes

Known Issues

• Particle classification is not working with Multitask Learning models yet.
• There is some version incompatibility (numpy and numba) when trying to run on Wilkes-3.

v0.5.2

CTLearn Release v0.5.2

upgrade to dl1dh v0.10.4

Major Features

Minor Improvements

Bug Fixes and Other Changes

• Improve installation instructions

Known Issues

• apply_class_weights only supported for CTLearn <= v0.5.1 and dl1dh <= v0.10.2. Please balance your dataset by hand beforehand. For CTLearn v0.6.0 apply_class_weights will be supported again and automatized.

v0.5.1

CTLearn Release v0.5.1

ctapipe-stage1 migration

Major Features

• Support of the official CTA stage 1 files (the dl1dh data format is still supported but will be deprecated in the future)
• Upgrade to dl1dh v0.10.0 and ctapipe v0.10.5
• Added ResNet-RNN model
• New feature: Freeze the backbone in deep stereo models like the ResNet-RNN
• pypi installation for CTLearn

Minor Improvements

• Add CTA and MAGIC example files
• Improve input file handling in predict mode to process real data in standard convention

Bug Fixes and Other Changes