ForeTiS.postprocess.model_reuse

Module Contents

Functions

apply_final_model(results_directory_model, ...[, ...])

Apply a final model on a new dataset. It will be applied to the whole dataset.
ForeTiS.postprocess.model_reuse.apply_final_model(results_directory_model, old_data_dir, old_data, new_data_dir, new_data, save_dir=None, config_file_path=None, retrain_model=True)

Apply a final model on a new dataset. It will be applied to the whole dataset. So the main purpose of this function is, if you get new samples you want to predict on. If the final model was saved, this will be used for inference on the new dataset. Otherwise, it will be retrained on the initial dataset and then used for inference on the new dataset.

The new dataset will be filtered for the SNP ids that the model was initially trained on.

CAUTION: the SNPs of the old and the new dataset have to be the same!

Parameters:

  • results_directory_model (str) – directory that contains the model results that you want to use

  • new_data_dir (str) – directory that contains the new data

  • old_data_dir (str) – directory that contains the old data

  • save_dir (str) – directory to store the results

  • old_data (str) – the old dataset that you used

  • new_data (str) – the new dataset that you want to use

  • config_file_path (pathlib.Path) – the path to the config file you want to use

  • retrain_model (bool) – whether to retrain the model with the whole old dataset