| 180 | return features, labels |
| 181 | |
| 182 | def fs_patch_transform(self, fs_list): |
| 183 | num_samples = sum([ |
| 184 | sum([1 for dp in self.datasets[fs] if self.file_filter(dp)]) |
| 185 | for fs in fs_list]) |
| 186 | |
| 187 | features = {} |
| 188 | features['text'] = [None] * num_samples |
| 189 | features['frc'] = np.zeros((num_samples, 3)) |
| 190 | labels = [None] * num_samples |
| 191 | ind = 0 |
| 192 | for fs in fs_list: |
| 193 | for dp in self.datasets[fs]: |
| 194 | if self.file_filter(dp): |
| 195 | features['text'][ind] = dp[self.text_feature] |
| 196 | features['frc'][ind] = np.array([dp['num_files'], |
| 197 | dp['num_adds'], |
| 198 | dp['num_dels']]) |
| 199 | labels[ind] = self.label_func(dp, self.is_jira) |
| 200 | ind += 1 |
| 201 | return features, labels |
| 202 | |
| 203 | class ItemSelector(BaseEstimator, TransformerMixin): |
| 204 | |