def _log_eval_average(self, result_dct_list, configs):
bresult = BenchmarkResult(result_dct_list, configs)
df = bresult.get_data_frame()
for eval_group in bresult.get_evaluation_groups():
if eval_group not in df.columns:
df[eval_group] = np.nan
df.fillna(-1, inplace=True)
grouped = df.apply(pd.to_numeric, errors='ignore').groupby(bresult.get_evaluation_groups()).mean()
self.logger.info("\n------------------- Current Evaluation Results ---------------------- \n Num. Results:{}\n {} \n \
---------------------------------------------------------------------".format(len(result_dct_list),
grouped.to_string()))
def _log_eval_average(self, result_dct_list, configs):
bresult = BenchmarkResult(result_dct_list, configs)
df = bresult.get_data_frame()
grouped = df.apply(pd.to_numeric, errors='ignore').groupby(bresult.get_evaluation_groups()).mean()[
self._evaluation_criteria()]
self.logger.info("\n------------------- Current Evaluation Results ---------------------- \n Num. Results:{}\n {} \n \
---------------------------------------------------------------------".format(len(result_dct_list),
grouped.to_string()))
