ml4eft.core.classifier.EventDataset#

class ml4eft.core.classifier.EventDataset(df, xsec, path, n_dat, features, hypothesis=0)[source]#

Bases: torch.utils.data.dataset.Dataset

Event loader

__init__(df, xsec, path, n_dat, features, hypothesis=0)[source]#

EventDataset constructor

Parameters

  • df (pandas.DataFrame) – Event DataFrame

  • xsec (float) – inclusive cross-section

  • path (str) – Path to dataset

  • n_dat (int) – Number of data points

  • features (array_like) – List of features to train on

  • hypothesis (int) – 0 for EFT and 1 for SM

Methods

__init__(df, xsec, path, n_dat, features[, ...])

EventDataset constructor

event_loader(path)

Set the weights of the evevnts, labels and convert the events to torch.Tensor,
event_loader(path)[source]#

Set the weights of the evevnts, labels and convert the events to torch.Tensor,

Parameters

path (str) – Path to dataset