(self, scaler_index)
| 289 | return self.scaler_items[self.scaler_name_index - 1] |
| 290 | |
| 291 | def set_scaler_index(self, scaler_index): |
| 292 | self.scaler_name_index = scaler_index |
| 293 | |
| 294 | if self.scaler_name_index == 0: |
| 295 | self.scaler_data = None |
| 296 | else: |
| 297 | try: |
| 298 | scaler_name = self.scaler_items[self.scaler_name_index - 1] |
| 299 | except IndexError: |
| 300 | scaler_name = None |
| 301 | if scaler_name: |
| 302 | self.scaler_data = self.scaler_norm_dict[scaler_name] |
| 303 | logger.info( |
| 304 | "Use scaler data to normalize, " |
| 305 | "and the shape of scaler data is {}, " |
| 306 | "with (low, high) as ({}, {})".format( |
| 307 | self.scaler_data.shape, np.min(self.scaler_data), np.max(self.scaler_data) |
| 308 | ) |
| 309 | ) |
| 310 | self.set_low_high_value() # reset low high values based on normalization |
| 311 | self.show_image() |
| 312 | |
| 313 | # TODO: document the following functions |
| 314 | def update_quant_calibration_gui(self): |
no test coverage detected