3. Tri-Model Managers

Once your models are trained for each task, the main component that will be used for analysis and data reconstruction (DL1 to DL2) will be the TriModelManager. As its name suggests, it is a manager that contains the three models: energy, direction, and type.

The creation of a TriModelManager is similar to the creation of a CTLearnModelManager. The main difference is that you need to pass the three models to the TriModelManager constructor.

MODEL_INDEX_FILE = "/path/to/your/ctlearn_models_index.h5"
energy_model = load_model_from_index("energy_model_nickname", MODEL_INDEX_FILE)
direction_model = load_model_from_index("direction_model_nickname", MODEL_INDEX_FILE)
type_model = load_model_from_index("type_model_nickname", MODEL_INDEX_FILE)
Tri_Model = CTLearnTriModelManager(direction_model=direction_model, energy_model=energy_model, type_model=type_model)

One can plot the loss function evolution for the tree models:

Stereo_Tri_Model.plot_loss()