Package usage

A high-level companion python package to the CTLearn package is available for easy usage of the CTLearn tools. The package is called CTLearnManager.

Low-level usage of CTLearn tools

This page provides a brief overview of how to use the CTLearn tools.

Training tool

To train a model, use the ctlearn-train-model command. The following command will display all available options for training a CTLearn model:

ctlearn-train-model --help-all

View training progress in real time with TensorBoard:

tensorboard --logdir=/path/to/my/model_dir

Prediction tools

To predict with a trained model, use the ctlearn-predict-mono-model or ctlearn-predict-stereo-model command. The following command will display all available options for predicting with a CTLearn model:

ctlearn-predict-mono-model --help-all
ctlearn-predict-stereo-model --help-all

Caution

This tool expects the input data to be produced via the ctapipe package. The output file with the predictions follows the ctapipe DL2 data format.

To predict on real observational data from the LST1 telescope, use the ctlearn-predict-LST1 command. The following command will display all available options for predicting with a CTLearn model:

ctlearn-predict-LST1 --help-all

Caution

This tool expects the input data to be produced via the cta-lstchain package. The output file with the predictions follows the ctapipe DL2 data format.