src.superphot_plus.model.lightgbm

Module Contents

Classes

SuperphotLightGBM

The LightGBM model.
class SuperphotLightGBM(config: superphot_plus.config.SuperphotConfig, target_label=None)[source]

The LightGBM model.

Parameters:

config (SuperphotConfig) – The MLP architecture configuration.

train_and_validate(train_data, rng_seed=None, **kwargs)[source]

Runs LightGBM training and validation.

Parameters:

  • train_data (TrainData) – The training dataset.

  • rng_seed (int, optional) – Random state that is seeded. if none, use machine entropy.

Returns:

A tuple containing arrays of metrics for each epoch (training accuracies and losses, validation accuracies and losses).

Return type:

tuple

evaluate(test_data, overwrite_save=False)[source]

Runs model over a group of test samples.

Parameters:

  • test_data (TestData) – The data to evaluate the model. Consists of test features, test classes, test names and a list of grouped indices, respectively.

  • probs_csv_path (str, optional) – Where to store the probability results.

Returns:

A tuple containing the labels, names, predicted labels and maximum probabilities.

Return type:

tuple

classify_from_fit_params(fit_params)[source]

Classify one or multiple light curves solely from the fit parameters used in the classifier. Excludes t0 and, for redshift-exclusive classifier, A. Includes chi-squared value.

Parameters:

fit_params (np.ndarray) – Set of model fit parameters.

Returns:

Probability of each light curve being each SN type. Sums to 1 along each row.

Return type:

np.ndarray

save(config_prefix, suffix='')[source]

Save the classifier as file.

Parameters:

models_dir (str) – Directory to write to

classmethod load(filename, config_filename=None)[source]

Load a classifier that was saved to disk

Parameters:

path (str) – Path where the classifier was saved

Returns:

Loaded classifier

Return type:

~Classifier