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()))