get_test_metric

behavenet.fitting.eval.get_test_metric(hparams, model_version, metric='r2', dtype='test', multioutput='variance_weighted', sess_idx=0)[source]

Calculate a single R2 value across all test batches for a decoder.

Parameters:

  • hparams (dict) – needs to contain enough information to specify an autoencoder

  • model_version (int or str) – version from test tube experiment defined in hparams or the string ‘best’

  • metric (str, optional) – ‘r2’ | ‘fc’ | ‘mse’

  • dtype (str) – type of trials to use for computing metric ‘train’ | ‘val’ | ‘test’

  • multioutput (str) – defines how to aggregate multiple r2 scores; see r2_score documentation in sklearn ‘raw_values’ | ‘uniform_average’ | ‘variance_weighted’

  • sess_idx (int, optional) – session index into data generator

Returns:

  • hparams (dict): hparams of model used to calculate metrics

  • metric (int)

Return type:

tuple