reconstruction¶
Reconstruction-specific Model class(es).
- class graphnet.models.task.reconstruction.AzimuthReconstructionWithKappa(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs azimuthal angle and associated kappa (1/var).
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['azimuth']¶
- default_prediction_labels = ['azimuth_pred', 'azimuth_kappa']¶
- nb_inputs = 2¶
- class graphnet.models.task.reconstruction.AzimuthReconstruction(*args, **kwargs)[source]¶
Bases:
AzimuthReconstructionWithKappa
Reconstructs azimuthal angle.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['azimuth']¶
- default_prediction_labels = ['azimuth_pred']¶
- nb_inputs = 2¶
- class graphnet.models.task.reconstruction.DirectionReconstructionWithKappa(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs direction with kappa from the 3D-vMF distribution.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['direction']¶
- default_prediction_labels = ['dir_x_pred', 'dir_y_pred', 'dir_z_pred', 'direction_kappa']¶
- nb_inputs = 3¶
- class graphnet.models.task.reconstruction.ZenithReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs zenith angle.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['zenith']¶
- default_prediction_labels = ['zenith_pred']¶
- nb_inputs = 1¶
- class graphnet.models.task.reconstruction.ZenithReconstructionWithKappa(*args, **kwargs)[source]¶
Bases:
ZenithReconstruction
Reconstructs zenith angle and associated kappa (1/var).
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['zenith']¶
- default_prediction_labels = ['zenith_pred', 'zenith_kappa']¶
- nb_inputs = 2¶
- class graphnet.models.task.reconstruction.EnergyReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs energy using stable method.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['energy']¶
- default_prediction_labels = ['energy_pred']¶
- nb_inputs = 1¶
- class graphnet.models.task.reconstruction.EnergyReconstructionWithPower(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs energy.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['energy']¶
- default_prediction_labels = ['energy_pred']¶
- nb_inputs = 1¶
- class graphnet.models.task.reconstruction.EnergyTCReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs track and cascade energies using stable method.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['energy_track', 'energy_cascade']¶
- default_prediction_labels = ['energy_track_pred', 'energy_cascade_pred']¶
- nb_inputs = 2¶
- class graphnet.models.task.reconstruction.EnergyReconstructionWithUncertainty(*args, **kwargs)[source]¶
Bases:
EnergyReconstruction
Reconstructs energy and associated uncertainty (log(var)).
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['energy']¶
- default_prediction_labels = ['energy_pred', 'energy_sigma']¶
- nb_inputs = 2¶
- class graphnet.models.task.reconstruction.VertexReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs vertex position and time.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['vertex']¶
- default_prediction_labels = ['position_x_pred', 'position_y_pred', 'position_z_pred', 'interaction_time_pred']¶
- nb_inputs = 4¶
- class graphnet.models.task.reconstruction.PositionReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs vertex position.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['position']¶
- default_prediction_labels = ['position_x_pred', 'position_y_pred', 'position_z_pred']¶
- nb_inputs = 3¶
- class graphnet.models.task.reconstruction.TimeReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs time.
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['interaction_time']¶
- default_prediction_labels = ['interaction_time_pred']¶
- nb_inputs = 1¶
- class graphnet.models.task.reconstruction.InelasticityReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs interaction inelasticity.
That is, 1-(track energy / hadronic energy).
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['inelasticity']¶
- default_prediction_labels = ['inelasticity_pred']¶
- nb_inputs = 1¶
- class graphnet.models.task.reconstruction.VisibleInelasticityReconstruction(*args, **kwargs)[source]¶
Bases:
StandardLearnedTask
Reconstructs interaction visible inelasticity.
That is, 1-(visible track energy / visible hadronic energy).
Construct StandardLearnedTask.
- Parameters:
hidden_size (
int
) – The number of columns in the output of the last latent layer of Model using this Task. Available through Model.nb_outputsargs (Any)
kwargs (Any)
- Return type:
object
- default_target_labels = ['visible_inelasticity']¶
- default_prediction_labels = ['visible_inelasticity_pred']¶
- nb_inputs = 1¶