| |
|
|
| import numpy as np |
| from omegaconf import OmegaConf |
|
|
| from utils.io import write_json |
|
|
|
|
| def compute_recall(errors): |
| num_elements = len(errors) |
| sort_idx = np.argsort(errors) |
| errors = np.array(errors.copy())[sort_idx] |
| recall = (np.arange(num_elements) + 1) / num_elements |
| recall = np.r_[0, recall] |
| errors = np.r_[0, errors] |
| return errors, recall |
|
|
|
|
| def compute_auc(errors, recall, thresholds): |
| aucs = [] |
| for t in thresholds: |
| last_index = np.searchsorted(errors, t, side="right") |
| r = np.r_[recall[:last_index], recall[last_index - 1]] |
| e = np.r_[errors[:last_index], t] |
| auc = np.trapz(r, x=e) / t |
| aucs.append(auc * 100) |
| return aucs |
|
|
|
|
| def write_dump(output_dir, experiment, cfg, results, metrics): |
| dump = { |
| "experiment": experiment, |
| "cfg": OmegaConf.to_container(cfg), |
| "results": results, |
| "errors": {}, |
| } |
| for k, m in metrics.items(): |
| if hasattr(m, "get_errors"): |
| dump["errors"][k] = m.get_errors().numpy() |
| write_json(output_dir / "log.json", dump) |
|
|
