diff options
| author | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-10-24 16:54:23 +0200 |
|---|---|---|
| committer | Birte Kristina Friesel <birte.friesel@uos.de> | 2024-10-24 16:54:23 +0200 |
| commit | 06c4a5f52d9a58afac2f5a7d60bd4cc6e8b4ae58 (patch) | |
| tree | 30ca9820c7125708aea278acd156ba2868ef7aa2 /lib | |
| parent | a0933fef969c4555452fcbf70e6183eddf141956 (diff) | |
Add --add-total-observation support to non-xv quality metrics
Diffstat (limited to 'lib')
| -rw-r--r-- | lib/model.py | 22 |
1 files changed, 20 insertions, 2 deletions
diff --git a/lib/model.py b/lib/model.py index 2815830..f22173c 100644 --- a/lib/model.py +++ b/lib/model.py @@ -449,7 +449,7 @@ class AnalyticModel: return model_getter, info_getter - def assess(self, model_function, ref=None, return_raw=False): + def assess(self, model_function, ref=None, return_raw=False, with_sum=False): """ Calculate MAE, SMAPE, etc. of model_function for each by_name entry. @@ -479,12 +479,30 @@ class AnalyticModel: ) measures = regression_measures(predicted_data, elem[attribute]) detailed_results[name][attribute] = measures - if return_raw: + if return_raw or with_sum: raw_results[name]["attribute"][attribute] = { "groundTruth": elem[attribute], "modelOutput": predicted_data, } + if with_sum: + for name in ref.keys(): + attr_0 = ref[name]["attributes"][0] + gt_sum = np.zeros( + len(raw_results[name]["attribute"][attr_0]["groundTruth"]) + ) + mo_sum = np.zeros( + len(raw_results[name]["attribute"][attr_0]["modelOutput"]) + ) + for attribute in ref[name]["attributes"]: + gt_sum += np.array( + raw_results[name]["attribute"][attribute]["groundTruth"] + ) + mo_sum += np.array( + raw_results[name]["attribute"][attribute]["modelOutput"] + ) + detailed_results[name]["TOTAL"] = regression_measures(mo_sum, gt_sum) + if return_raw: return detailed_results, raw_results return detailed_results |