Ulm-IQO /
qudi
| Total Complexity | 87 |
| Total Lines | 896 |
| Duplicated Lines | 2.01 % |
| Changes | 1 | ||
| Bugs | 1 | Features | 0 |
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like ConfocalLogic often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | # -*- coding: utf-8 -*- |
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| 243 | class ConfocalLogic(GenericLogic): |
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| 244 | """ |
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| 245 | This is the Logic class for confocal scanning. |
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| 246 | """ |
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| 247 | _modclass = 'confocallogic' |
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| 248 | _modtype = 'logic' |
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| 249 | |||
| 250 | # declare connectors |
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| 251 | _in = { |
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| 252 | 'confocalscanner1': 'ConfocalScannerInterface', |
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| 253 | 'savelogic': 'SaveLogic' |
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| 254 | } |
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| 255 | _out = {'scannerlogic': 'ConfocalLogic'} |
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| 256 | |||
| 257 | # signals |
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| 258 | signal_start_scanning = QtCore.Signal() |
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| 259 | signal_continue_scanning = QtCore.Signal() |
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| 260 | signal_scan_lines_next = QtCore.Signal() |
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| 261 | signal_xy_image_updated = QtCore.Signal() |
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| 262 | signal_depth_image_updated = QtCore.Signal() |
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| 263 | signal_change_position = QtCore.Signal(str) |
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| 264 | |||
| 265 | sigImageXYInitialized = QtCore.Signal() |
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| 266 | sigImageDepthInitialized = QtCore.Signal() |
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| 267 | |||
| 268 | signal_history_event = QtCore.Signal() |
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| 269 | |||
| 270 | def __init__(self, config, **kwargs): |
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| 271 | super().__init__(config=config, **kwargs) |
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| 272 | |||
| 273 | self.log.info('The following configuration was found.') |
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| 274 | |||
| 275 | # checking for the right configuration |
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| 276 | for key in config.keys(): |
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| 277 | self.log.info('{0}: {1}'.format(key, config[key])) |
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| 278 | |||
| 279 | #locking for thread safety |
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| 280 | self.threadlock = Mutex() |
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| 281 | |||
| 282 | # counter for scan_image |
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| 283 | self._scan_counter = 0 |
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| 284 | self._zscan = False |
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| 285 | self.stopRequested = False |
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| 286 | self.depth_scan_dir_is_xz = True |
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| 287 | self.permanent_scan = False |
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| 288 | |||
| 289 | def on_activate(self, e): |
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| 290 | """ Initialisation performed during activation of the module. |
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| 291 | |||
| 292 | @param e: error code |
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| 293 | """ |
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| 294 | self._scanning_device = self.get_in_connector('confocalscanner1') |
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| 295 | # print("Scanning device is", self._scanning_device) |
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| 296 | |||
| 297 | self._save_logic = self.get_in_connector('savelogic') |
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| 298 | |||
| 299 | #default values for clock frequency and slowness |
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| 300 | #slowness: steps during retrace line |
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| 301 | if 'clock_frequency' in self._statusVariables: |
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| 302 | self._clock_frequency = self._statusVariables['clock_frequency'] |
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| 303 | else: |
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| 304 | self._clock_frequency = 500 |
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| 305 | if 'return_slowness' in self._statusVariables: |
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| 306 | self.return_slowness = self._statusVariables['return_slowness'] |
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| 307 | else: |
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| 308 | self.return_slowness = 50 |
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| 309 | |||
| 310 | # Reads in the maximal scanning range. The unit of that scan range is micrometer! |
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| 311 | self.x_range = self._scanning_device.get_position_range()[0] |
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| 312 | self.y_range = self._scanning_device.get_position_range()[1] |
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| 313 | self.z_range = self._scanning_device.get_position_range()[2] |
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| 314 | |||
| 315 | # restore here ... |
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| 316 | self.history = [] |
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| 317 | if 'max_history_length' in self._statusVariables: |
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| 318 | self.max_history_length = self._statusVariables ['max_history_length'] |
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| 319 | for i in reversed(range(1, self.max_history_length)): |
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| 320 | try: |
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| 321 | new_history_item = ConfocalHistoryEntry(self) |
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| 322 | new_history_item.deserialize(self._statusVariables['history_{0}'.format(i)]) |
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| 323 | self.history.append(new_history_item) |
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| 324 | except KeyError: |
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| 325 | pass |
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| 326 | except OldConfigFileError: |
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| 327 | self.log.warning('Old style config file detected. ' |
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| 328 | 'History {0} ignored.'.format(i)) |
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| 329 | except: |
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| 330 | self.log.warning( |
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| 331 | 'Restoring history {0} failed.'.format(i)) |
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| 332 | else: |
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| 333 | self.max_history_length = 10 |
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| 334 | try: |
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| 335 | new_state = ConfocalHistoryEntry(self) |
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| 336 | new_state.deserialize(self._statusVariables['history_0']) |
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| 337 | new_state.restore(self) |
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| 338 | except: |
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| 339 | new_state = ConfocalHistoryEntry(self) |
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| 340 | new_state.restore(self) |
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| 341 | finally: |
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| 342 | self.history.append(new_state) |
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| 343 | |||
| 344 | self.history_index = len(self.history) - 1 |
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| 345 | |||
| 346 | # Sets connections between signals and functions |
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| 347 | self.signal_scan_lines_next.connect(self._scan_line, QtCore.Qt.QueuedConnection) |
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| 348 | self.signal_start_scanning.connect(self.start_scanner, QtCore.Qt.QueuedConnection) |
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| 349 | self.signal_continue_scanning.connect(self.continue_scanner, QtCore.Qt.QueuedConnection) |
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| 350 | |||
| 351 | self._change_position('activation') |
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| 352 | |||
| 353 | def on_deactivate(self, e): |
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| 354 | """ Reverse steps of activation |
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| 355 | |||
| 356 | @param e: error code |
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| 357 | |||
| 358 | @return int: error code (0:OK, -1:error) |
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| 359 | """ |
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| 360 | self._statusVariables['clock_frequency'] = self._clock_frequency |
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| 361 | self._statusVariables['return_slowness'] = self.return_slowness |
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| 362 | self._statusVariables['max_history_length'] = self.max_history_length |
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| 363 | closing_state = ConfocalHistoryEntry(self) |
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| 364 | closing_state.snapshot(self) |
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| 365 | self.history.append(closing_state) |
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| 366 | histindex = 0 |
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| 367 | for state in reversed(self.history): |
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| 368 | self._statusVariables['history_{0}'.format(histindex)] = state.serialize() |
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| 369 | histindex += 1 |
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| 370 | return 0 |
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| 371 | |||
| 372 | def switch_hardware(self, to_on=False): |
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| 373 | """ Switches the Hardware off or on. |
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| 374 | |||
| 375 | @param to_on: True switches on, False switched off |
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| 376 | |||
| 377 | @return int: error code (0:OK, -1:error) |
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| 378 | """ |
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| 379 | if to_on: |
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| 380 | return self._scanning_device.activation() |
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| 381 | else: |
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| 382 | return self._scanning_device.reset_hardware() |
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| 383 | |||
| 384 | def set_clock_frequency(self, clock_frequency): |
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| 385 | """Sets the frequency of the clock |
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| 386 | |||
| 387 | @param int clock_frequency: desired frequency of the clock |
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| 388 | |||
| 389 | @return int: error code (0:OK, -1:error) |
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| 390 | """ |
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| 391 | self._clock_frequency = int(clock_frequency) |
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| 392 | #checks if scanner is still running |
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| 393 | if self.getState() == 'locked': |
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| 394 | return -1 |
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| 395 | else: |
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| 396 | return 0 |
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| 397 | |||
| 398 | def start_scanning(self, zscan = False): |
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| 399 | """Starts scanning |
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| 400 | |||
| 401 | @param bool zscan: zscan if true, xyscan if false |
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| 402 | |||
| 403 | @return int: error code (0:OK, -1:error) |
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| 404 | """ |
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| 405 | # TODO: this is dirty, but it works for now |
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| 406 | # while self.getState() == 'locked': |
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| 407 | # time.sleep(0.01) |
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| 408 | self._scan_counter = 0 |
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| 409 | self._zscan = zscan |
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| 410 | if self._zscan: |
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| 411 | self._zscan_continuable = True |
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| 412 | else: |
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| 413 | self._xyscan_continuable = True |
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| 414 | |||
| 415 | self.signal_start_scanning.emit() |
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| 416 | return 0 |
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| 417 | |||
| 418 | |||
| 419 | def continue_scanning(self,zscan): |
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| 420 | """Continue scanning |
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| 421 | |||
| 422 | @return int: error code (0:OK, -1:error) |
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| 423 | """ |
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| 424 | self._zscan = zscan |
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| 425 | if zscan: |
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| 426 | self._scan_counter = self._depth_line_pos |
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| 427 | else: |
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| 428 | self._scan_counter = self._xy_line_pos |
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| 429 | self.signal_continue_scanning.emit() |
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| 430 | return 0 |
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| 431 | |||
| 432 | |||
| 433 | def stop_scanning(self): |
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| 434 | """Stops the scan |
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| 435 | |||
| 436 | @return int: error code (0:OK, -1:error) |
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| 437 | """ |
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| 438 | with self.threadlock: |
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| 439 | if self.getState() == 'locked': |
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| 440 | self.stopRequested = True |
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| 441 | return 0 |
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| 442 | |||
| 443 | def initialize_image(self): |
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| 444 | """Initalization of the image. |
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| 445 | |||
| 446 | @return int: error code (0:OK, -1:error) |
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| 447 | """ |
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| 448 | # x1: x-start-value, x2: x-end-value |
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| 449 | x1, x2 = self.image_x_range[0], self.image_x_range[1] |
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| 450 | # y1: x-start-value, y2: x-end-value |
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| 451 | y1, y2 = self.image_y_range[0], self.image_y_range[1] |
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| 452 | # z1: x-start-value, z2: x-end-value |
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| 453 | z1, z2 = self.image_z_range[0], self.image_z_range[1] |
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| 454 | |||
| 455 | # Checks if the x-start and x-end value are ok |
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| 456 | if x2 < x1: |
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| 457 | self.log.error( |
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| 458 | 'x1 must be smaller than x2, but they are ' |
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| 459 | '({0:.3f},{1:.3f}).'.format(x1, x2)) |
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| 460 | return -1 |
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| 461 | |||
| 462 | if self._zscan: |
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| 463 | # creates an array of evenly spaced numbers over the interval |
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| 464 | # x1, x2 and the spacing is equal to xy_resolution |
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| 465 | self._X = np.linspace(x1, x2, self.xy_resolution) |
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| 466 | # Checks if the z-start and z-end value are ok |
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| 467 | if z2 < z1: |
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| 468 | self.log.error( |
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| 469 | 'z1 must be smaller than z2, but they are ' |
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| 470 | '({0:.3f},{1:.3f}).'.format(z1, z2)) |
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| 471 | return -1 |
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| 472 | # creates an array of evenly spaced numbers over the interval |
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| 473 | # z1, z2 and the spacing is equal to z_resolution |
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| 474 | self._Z = np.linspace(z1, z2, max(self.z_resolution, 2)) |
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| 475 | else: |
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| 476 | # Checks if the y-start and y-end value are ok |
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| 477 | if y2 < y1: |
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| 478 | self.log.error( |
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| 479 | 'y1 must be smaller than y2, but they are ' |
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| 480 | '({0:.3f},{1:.3f}).'.format(y1, y2)) |
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| 481 | return -1 |
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| 482 | |||
| 483 | # prevents distorion of the image |
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| 484 | if (x2 - x1) >= (y2 - y1): |
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| 485 | self._X = np.linspace(x1, x2, max(self.xy_resolution, 2)) |
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| 486 | self._Y = np.linspace(y1, y2, max(int(self.xy_resolution*(y2-y1)/(x2-x1)), 2)) |
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| 487 | else: |
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| 488 | self._Y = np.linspace(y1, y2, max(self.xy_resolution, 2)) |
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| 489 | self._X = np.linspace(x1, x2, max(int(self.xy_resolution*(x2-x1)/(y2-y1)), 2)) |
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| 490 | |||
| 491 | self._XL = self._X |
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| 492 | self._YL = self._Y |
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| 493 | self._AL = np.zeros(self._XL.shape) |
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| 494 | |||
| 495 | # Arrays for retrace line |
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| 496 | self._return_XL = np.linspace(self._XL[-1], self._XL[0], self.return_slowness) |
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| 497 | self._return_AL = np.zeros(self._return_XL.shape) |
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| 498 | |||
| 499 | if self._zscan: |
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| 500 | if self.depth_scan_dir_is_xz: |
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| 501 | self._image_vert_axis = self._Z |
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| 502 | # creates an image where each pixel will be [x,y,z,counts] |
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| 503 | self.depth_image = np.zeros((len(self._image_vert_axis), len(self._X), 4)) |
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| 504 | self.depth_image[:, : ,0] = np.full((len(self._image_vert_axis), len(self._X)), self._XL) |
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| 505 | self.depth_image[:, :, 1] = self._current_y * np.ones((len(self._image_vert_axis), len(self._X))) |
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| 506 | z_value_matrix = np.full((len(self._X), len(self._image_vert_axis)), self._Z) |
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| 507 | self.depth_image[:, :, 2] = z_value_matrix.transpose() |
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| 508 | else: # depth scan is yz instead of xz |
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| 509 | self._image_vert_axis = self._Z |
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| 510 | # creats an image where each pixel will be [x,y,z,counts] |
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| 511 | self.depth_image = np.zeros((len(self._image_vert_axis), len(self._Y), 4)) |
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| 512 | self.depth_image[:, :, 0] = self._current_x * np.ones((len(self._image_vert_axis), len(self._Y))) |
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| 513 | self.depth_image[:, :, 1] = np.full((len(self._image_vert_axis), len(self._Y)), self._YL) |
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| 514 | z_value_matrix = np.full((len(self._Y), len(self._image_vert_axis)), self._Z) |
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| 515 | self.depth_image[:, :, 2] = z_value_matrix.transpose() |
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| 516 | # now we are scanning along the y-axis, so we need a new return line along Y: |
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| 517 | self._return_YL = np.linspace(self._YL[-1], self._YL[0], self.return_slowness) |
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| 518 | self._return_AL = np.zeros(self._return_YL.shape) |
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| 519 | self.sigImageDepthInitialized.emit() |
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| 520 | else: |
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| 521 | self._image_vert_axis = self._Y |
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| 522 | # creats an image where each pixel will be [x,y,z,counts] |
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| 523 | self.xy_image = np.zeros((len(self._image_vert_axis), len(self._X), 4)) |
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| 524 | self.xy_image[:, :, 0] = np.full((len(self._image_vert_axis), len(self._X)), self._XL) |
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| 525 | y_value_matrix = np.full((len(self._X), len(self._image_vert_axis)), self._Y) |
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| 526 | self.xy_image[:, :, 1] = y_value_matrix.transpose() |
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| 527 | self.xy_image[:, :, 2] = self._current_z * np.ones((len(self._image_vert_axis), len(self._X))) |
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| 528 | self.sigImageXYInitialized.emit() |
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| 529 | return 0 |
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| 530 | |||
| 531 | def start_scanner(self): |
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| 532 | """Setting up the scanner device and starts the scanning procedure |
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| 533 | |||
| 534 | @return int: error code (0:OK, -1:error) |
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| 535 | """ |
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| 536 | self.lock() |
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| 537 | self._scanning_device.lock() |
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| 538 | if self.initialize_image() < 0: |
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| 539 | self._scanning_device.unlock() |
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| 540 | self.unlock() |
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| 541 | return -1 |
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| 542 | |||
| 543 | returnvalue = self._scanning_device.set_up_scanner_clock(clock_frequency=self._clock_frequency) |
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| 544 | if returnvalue < 0: |
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| 545 | self._scanning_device.unlock() |
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| 546 | self.unlock() |
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| 547 | self.set_position('scanner') |
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| 548 | return |
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| 549 | |||
| 550 | returnvalue = self._scanning_device.set_up_scanner() |
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| 551 | if returnvalue < 0: |
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| 552 | self._scanning_device.unlock() |
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| 553 | self.unlock() |
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| 554 | self.set_position('scanner') |
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| 555 | return |
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| 556 | |||
| 557 | self.signal_scan_lines_next.emit() |
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| 558 | return 0 |
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| 559 | |||
| 560 | def continue_scanner(self): |
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| 561 | """Continue the scanning procedure |
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| 562 | |||
| 563 | @return int: error code (0:OK, -1:error) |
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| 564 | """ |
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| 565 | self.lock() |
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| 566 | self._scanning_device.lock() |
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| 567 | self._scanning_device.set_up_scanner_clock(clock_frequency=self._clock_frequency) |
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| 568 | self._scanning_device.set_up_scanner() |
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| 569 | self.signal_scan_lines_next.emit() |
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| 570 | return 0 |
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| 571 | |||
| 572 | def kill_scanner(self): |
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| 573 | """Closing the scanner device. |
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| 574 | |||
| 575 | @return int: error code (0:OK, -1:error) |
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| 576 | """ |
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| 577 | try: |
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| 578 | self._scanning_device.close_scanner() |
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| 579 | self._scanning_device.close_scanner_clock() |
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| 580 | except Exception as e: |
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| 581 | self.log.exception('Could not even close the scanner, giving up.') |
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| 582 | raise e |
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| 583 | try: |
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| 584 | self._scanning_device.unlock() |
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| 585 | except Exception as e: |
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| 586 | self.log.exception('Could not unlock scanning device.') |
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| 587 | |||
| 588 | return 0 |
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| 589 | |||
| 590 | def set_position(self, tag, x=None, y=None, z=None, a=None): |
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| 591 | """Forwarding the desired new position from the GUI to the scanning device. |
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| 592 | |||
| 593 | @param string tag: TODO |
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| 594 | |||
| 595 | @param float x: if defined, changes to postion in x-direction (microns) |
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| 596 | @param float y: if defined, changes to postion in y-direction (microns) |
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| 597 | @param float z: if defined, changes to postion in z-direction (microns) |
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| 598 | @param float a: if defined, changes to postion in a-direction (microns) |
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| 599 | |||
| 600 | @return int: error code (0:OK, -1:error) |
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| 601 | """ |
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| 602 | # print(tag, x, y, z) |
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| 603 | # Changes the respective value |
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| 604 | if x is not None: |
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| 605 | self._current_x = x |
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| 606 | if y is not None: |
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| 607 | self._current_y = y |
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| 608 | if z is not None: |
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| 609 | self._current_z = z |
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| 610 | |||
| 611 | # Checks if the scanner is still running |
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| 612 | if self.getState() == 'locked' or self._scanning_device.getState() == 'locked': |
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| 613 | return -1 |
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| 614 | else: |
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| 615 | self._change_position(tag) |
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| 616 | self.signal_change_position.emit(tag) |
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| 617 | return 0 |
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| 618 | |||
| 619 | |||
| 620 | def _change_position(self, tag): |
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| 621 | """ Threaded method to change the hardware position. |
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| 622 | |||
| 623 | @return int: error code (0:OK, -1:error) |
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| 624 | """ |
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| 625 | # if tag == 'optimizer' or tag == 'scanner' or tag == 'activation': |
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| 626 | self._scanning_device.scanner_set_position( |
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| 627 | x=self._current_x, |
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| 628 | y=self._current_y, |
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| 629 | z=self._current_z, |
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| 630 | a=self._current_a |
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| 631 | ) |
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| 632 | return 0 |
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| 633 | |||
| 634 | |||
| 635 | def get_position(self): |
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| 636 | """Forwarding the desired new position from the GUI to the scanning device. |
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| 637 | |||
| 638 | @return list: with three entries x, y and z denoting the current |
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| 639 | position in microns |
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| 640 | """ |
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| 641 | #FIXME: change that to SI units! |
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| 642 | return self._scanning_device.get_scanner_position()[:3] |
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| 643 | |||
| 644 | |||
| 645 | def _scan_line(self): |
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| 646 | """scanning an image in either depth or xy |
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| 647 | |||
| 648 | """ |
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| 649 | # TODO: change z_values, if z is changed during scan! |
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| 650 | # stops scanning |
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| 651 | if self.stopRequested: |
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| 652 | with self.threadlock: |
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| 653 | self.kill_scanner() |
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| 654 | self.stopRequested = False |
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| 655 | self.unlock() |
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| 656 | self.signal_xy_image_updated.emit() |
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| 657 | self.signal_depth_image_updated.emit() |
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| 658 | self.set_position('scanner') |
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| 659 | if self._zscan: |
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| 660 | self._depth_line_pos = self._scan_counter |
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| 661 | else: |
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| 662 | self._xy_line_pos = self._scan_counter |
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| 663 | # add new history entry |
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| 664 | new_history = ConfocalHistoryEntry(self) |
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| 665 | new_history.snapshot(self) |
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| 666 | self.history.append(new_history) |
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| 667 | if len(self.history) > self.max_history_length: |
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| 668 | self.history.pop(0) |
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| 669 | self.history_index = len(self.history) - 1 |
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| 670 | return |
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| 671 | |||
| 672 | if self._zscan: |
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| 673 | if self.TiltCorrection: |
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| 674 | image = copy(self.depth_image) |
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| 675 | image[:, :, 2] += self._calc_dz(x=image[:, :, 0], y=image[:, :, 1]) |
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| 676 | else: |
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| 677 | image = self.depth_image |
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| 678 | else: |
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| 679 | if self.TiltCorrection: |
||
| 680 | image = copy(self.xy_image) |
||
| 681 | image[:, :, 2] += self._calc_dz(x=image[:, :, 0], y=image[:, :, 1]) |
||
| 682 | else: |
||
| 683 | image = self.xy_image |
||
| 684 | |||
| 685 | try: |
||
| 686 | if self._scan_counter == 0: |
||
| 687 | # defines trace of positions for single line scan |
||
| 688 | start_line = np.vstack(( |
||
| 689 | np.linspace(self._current_x, image[self._scan_counter, 0, 0], self.return_slowness), |
||
| 690 | np.linspace(self._current_y, image[self._scan_counter, 0, 1], self.return_slowness), |
||
| 691 | np.linspace(self._current_z, image[self._scan_counter, 0, 2], self.return_slowness), |
||
| 692 | np.linspace(self._current_a, 0, self.return_slowness) |
||
| 693 | )) |
||
| 694 | # scan of a single line |
||
| 695 | start_line_counts = self._scanning_device.scan_line(start_line) |
||
| 696 | # defines trace of positions for a single line scan |
||
| 697 | line = np.vstack((image[self._scan_counter, :, 0], |
||
| 698 | image[self._scan_counter, :, 1], |
||
| 699 | image[self._scan_counter, :, 2], |
||
| 700 | image[self._scan_counter, :, 3])) |
||
| 701 | # scan of a single line |
||
| 702 | line_counts = self._scanning_device.scan_line(line) |
||
| 703 | # defines trace of positions for a single return line scan |
||
| 704 | if self.depth_scan_dir_is_xz: |
||
| 705 | return_line = np.vstack(( |
||
| 706 | self._return_XL, |
||
| 707 | image[self._scan_counter, 0, 1] * np.ones(self._return_XL.shape), |
||
| 708 | image[self._scan_counter, 0, 2] * np.ones(self._return_XL.shape), |
||
| 709 | self._return_AL |
||
| 710 | )) |
||
| 711 | else: |
||
| 712 | return_line = np.vstack(( |
||
| 713 | image[self._scan_counter, 0, 1] * np.ones(self._return_YL.shape), |
||
| 714 | self._return_YL, |
||
| 715 | image[self._scan_counter, 0, 2] * np.ones(self._return_YL.shape), |
||
| 716 | self._return_AL |
||
| 717 | )) |
||
| 718 | |||
| 719 | # scan of a single return-line |
||
| 720 | # This is just needed in order to return the scanner to the start of next line |
||
| 721 | return_line_counts = self._scanning_device.scan_line(return_line) |
||
| 722 | |||
| 723 | # updating images |
||
| 724 | if self._zscan: |
||
| 725 | if self.depth_scan_dir_is_xz: |
||
| 726 | self.depth_image[self._scan_counter, :, 3] = line_counts |
||
| 727 | else: |
||
| 728 | self.depth_image[self._scan_counter, :, 3] = line_counts |
||
| 729 | self.signal_depth_image_updated.emit() |
||
| 730 | else: |
||
| 731 | self.xy_image[self._scan_counter, :, 3] = line_counts |
||
| 732 | self.signal_xy_image_updated.emit() |
||
| 733 | |||
| 734 | # call this again from event loop |
||
| 735 | self._scan_counter += 1 |
||
| 736 | # stop scanning when last line scan was performed and makes scan not continuable |
||
| 737 | |||
| 738 | if self._scan_counter >= np.size(self._image_vert_axis): |
||
| 739 | if not self.permanent_scan: |
||
| 740 | self.stop_scanning() |
||
| 741 | if self._zscan: |
||
| 742 | self._zscan_continuable = False |
||
| 743 | else: |
||
| 744 | self._xyscan_continuable = False |
||
| 745 | else: |
||
| 746 | self._scan_counter = 0 |
||
| 747 | |||
| 748 | self.signal_scan_lines_next.emit() |
||
| 749 | |||
| 750 | except Exception as e: |
||
| 751 | self.log.critical('The scan went wrong, killing the scanner.') |
||
| 752 | self.stop_scanning() |
||
| 753 | self.signal_scan_lines_next.emit() |
||
| 754 | raise e |
||
| 755 | |||
| 756 | |||
| 757 | def save_xy_data(self, colorscale_range=None, percentile_range=None): |
||
| 758 | """ Save the current confocal xy data to file. |
||
| 759 | |||
| 760 | Two files are created. The first is the imagedata, which has a text-matrix of count values |
||
| 761 | corresponding to the pixel matrix of the image. Only count-values are saved here. |
||
| 762 | |||
| 763 | The second file saves the full raw data with x, y, z, and counts at every pixel. |
||
| 764 | |||
| 765 | A figure is also saved. |
||
| 766 | |||
| 767 | @param: list colorscale_range (optional) The range [min, max] of the display colour scale (for the figure) |
||
| 768 | |||
| 769 | @param: list percentile_range (optional) The percentile range [min, max] of the color scale |
||
| 770 | """ |
||
| 771 | save_time = datetime.now() |
||
| 772 | |||
| 773 | filepath = self._save_logic.get_path_for_module(module_name='Confocal') |
||
| 774 | |||
| 775 | # Prepare the metadata parameters (common to both saved files): |
||
| 776 | parameters = OrderedDict() |
||
| 777 | |||
| 778 | parameters['X image min (micrometer)'] = self.image_x_range[0] |
||
| 779 | parameters['X image max (micrometer)'] = self.image_x_range[1] |
||
| 780 | parameters['X image range (micrometer)'] = self.image_x_range[1] - self.image_x_range[0] |
||
| 781 | |||
| 782 | parameters['Y image min'] = self.image_y_range[0] |
||
| 783 | parameters['Y image max'] = self.image_y_range[1] |
||
| 784 | parameters['Y image range'] = self.image_y_range[1] - self.image_y_range[0] |
||
| 785 | |||
| 786 | parameters['XY resolution (samples per range)'] = self.xy_resolution |
||
| 787 | parameters['XY Image at z position (micrometer)'] = self._current_z |
||
| 788 | |||
| 789 | parameters['Clock frequency of scanner (Hz)'] = self._clock_frequency |
||
| 790 | parameters['Return Slowness (Steps during retrace line)'] = self.return_slowness |
||
| 791 | |||
| 792 | # data for the text-array "image": |
||
| 793 | image_data = OrderedDict() |
||
| 794 | image_data['Confocal pure XY scan image data without axis.\n' |
||
| 795 | '# The upper left entry represents the signal at the upper ' |
||
| 796 | 'left pixel position.\n' |
||
| 797 | '# A pixel-line in the image corresponds to a row ' |
||
| 798 | 'of entries where the Signal is in counts/s:'] = self.xy_image[:,:,3] |
||
| 799 | |||
| 800 | # Prepare a figure to be saved |
||
| 801 | figure_data = self.xy_image[:,:,3] |
||
| 802 | image_extent = [self.image_x_range[0], |
||
| 803 | self.image_x_range[1], |
||
| 804 | self.image_y_range[0], |
||
| 805 | self.image_y_range[1] |
||
| 806 | ] |
||
| 807 | axes = ['X', 'Y'] |
||
| 808 | crosshair_pos = [self.get_position()[0], self.get_position()[1]] |
||
| 809 | |||
| 810 | fig = self.draw_figure(data=figure_data, |
||
| 811 | image_extent=image_extent, |
||
| 812 | scan_axis=axes, |
||
| 813 | cbar_range=colorscale_range, |
||
| 814 | percentile_range=percentile_range, |
||
| 815 | crosshair_pos=crosshair_pos |
||
| 816 | ) |
||
| 817 | |||
| 818 | # Save the image data and figure |
||
| 819 | filelabel = 'confocal_xy_image' |
||
| 820 | self._save_logic.save_data(image_data, |
||
| 821 | filepath, |
||
| 822 | parameters=parameters, |
||
| 823 | filelabel=filelabel, |
||
| 824 | as_text=True, |
||
| 825 | timestamp=save_time, |
||
| 826 | plotfig=fig |
||
| 827 | ) |
||
| 828 | #, as_xml=False, precision=None, delimiter=None) |
||
| 829 | plt.close(fig) |
||
| 830 | |||
| 831 | # prepare the full raw data in an OrderedDict: |
||
| 832 | data = OrderedDict() |
||
| 833 | x_data = [] |
||
| 834 | y_data = [] |
||
| 835 | z_data = [] |
||
| 836 | counts_data = [] |
||
| 837 | |||
| 838 | for row in self.xy_image: |
||
| 839 | for entry in row: |
||
| 840 | x_data.append(entry[0]) |
||
| 841 | y_data.append(entry[1]) |
||
| 842 | z_data.append(entry[2]) |
||
| 843 | counts_data.append(entry[3]) |
||
| 844 | |||
| 845 | data['x values (micron)'] = x_data |
||
| 846 | data['y values (micron)'] = y_data |
||
| 847 | data['z values (micron)'] = z_data |
||
| 848 | data['count values (c/s)'] = counts_data |
||
| 849 | |||
| 850 | # Save the raw data to file |
||
| 851 | filelabel = 'confocal_xy_data' |
||
| 852 | self._save_logic.save_data(data, |
||
| 853 | filepath, |
||
| 854 | parameters=parameters, |
||
| 855 | filelabel=filelabel, |
||
| 856 | as_text=True, |
||
| 857 | timestamp=save_time |
||
| 858 | ) |
||
| 859 | #, as_xml=False, precision=None, delimiter=None) |
||
| 860 | |||
| 861 | self.log.debug('Confocal Image saved to:\n{0}'.format(filepath)) |
||
| 862 | |||
| 863 | def save_depth_data(self, colorscale_range=None, percentile_range=None): |
||
| 864 | """ Save the current confocal depth data to file. |
||
| 865 | |||
| 866 | Two files are created. The first is the imagedata, which has a text-matrix of count values |
||
| 867 | corresponding to the pixel matrix of the image. Only count-values are saved here. |
||
| 868 | |||
| 869 | The second file saves the full raw data with x, y, z, and counts at every pixel. |
||
| 870 | """ |
||
| 871 | save_time = datetime.now() |
||
| 872 | |||
| 873 | filepath = self._save_logic.get_path_for_module(module_name='Confocal') |
||
| 874 | |||
| 875 | # Prepare the metadata parameters (common to both saved files): |
||
| 876 | parameters = OrderedDict() |
||
| 877 | |||
| 878 | # TODO: This needs to check whether the scan was XZ or YZ direction |
||
| 879 | parameters['X image min (micrometer)'] = self.image_x_range[0] |
||
| 880 | parameters['X image max (micrometer)'] = self.image_x_range[1] |
||
| 881 | parameters['X image range (micrometer)'] = self.image_x_range[1] - self.image_x_range[0] |
||
| 882 | |||
| 883 | parameters['Z image min'] = self.image_z_range[0] |
||
| 884 | parameters['Z image max'] = self.image_z_range[1] |
||
| 885 | parameters['Z image range'] = self.image_z_range[1] - self.image_z_range[0] |
||
| 886 | |||
| 887 | parameters['XY resolution (samples per range)'] = self.xy_resolution |
||
| 888 | parameters['Z resolution (samples per range)'] = self.z_resolution |
||
| 889 | parameters['Depth Image at y position (micrometer)'] = self._current_y |
||
| 890 | |||
| 891 | parameters['Clock frequency of scanner (Hz)'] = self._clock_frequency |
||
| 892 | parameters['Return Slowness (Steps during retrace line)'] = self.return_slowness |
||
| 893 | |||
| 894 | # data for the text-array "image": |
||
| 895 | image_data = OrderedDict() |
||
| 896 | image_data['Confocal pure depth scan image data without axis.\n' |
||
| 897 | '# The upper left entry represents the signal at the upper ' |
||
| 898 | 'left pixel position.\n' |
||
| 899 | '# A pixel-line in the image corresponds to a row in ' |
||
| 900 | 'of entries where the Signal is in counts/s:'] = self.depth_image[:,:,3] |
||
| 901 | |||
| 902 | # Prepare a figure to be saved |
||
| 903 | figure_data = self.depth_image[:,:,3] |
||
| 904 | |||
| 905 | if self.depth_scan_dir_is_xz: |
||
| 906 | horizontal_range = [self.image_x_range[0], self.image_x_range[1]] |
||
| 907 | axes = ['X', 'Z'] |
||
| 908 | crosshair_pos = [self.get_position()[0], self.get_position()[2]] |
||
| 909 | else: |
||
| 910 | horizontal_range = [self.image_y_range[0], self.image_y_range[1]] |
||
| 911 | axes = ['Y', 'Z'] |
||
| 912 | crosshair_pos = [self.get_position()[1], self.get_position()[2]] |
||
| 913 | |||
| 914 | image_extent = [horizontal_range[0], |
||
| 915 | horizontal_range[1], |
||
| 916 | self.image_z_range[0], |
||
| 917 | self.image_z_range[1] |
||
| 918 | ] |
||
| 919 | |||
| 920 | fig = self.draw_figure(data=figure_data, |
||
| 921 | image_extent=image_extent, |
||
| 922 | scan_axis=axes, |
||
| 923 | cbar_range=colorscale_range, |
||
| 924 | percentile_range=percentile_range, |
||
| 925 | crosshair_pos=crosshair_pos |
||
| 926 | ) |
||
| 927 | |||
| 928 | # Save the image data and figure |
||
| 929 | filelabel = 'confocal_xy_image' |
||
| 930 | self._save_logic.save_data(image_data, |
||
| 931 | filepath, |
||
| 932 | parameters=parameters, |
||
| 933 | filelabel=filelabel, |
||
| 934 | as_text=True, |
||
| 935 | timestamp=save_time, |
||
| 936 | plotfig=fig |
||
| 937 | ) |
||
| 938 | #, as_xml=False, precision=None, delimiter=None) |
||
| 939 | plt.close(fig) |
||
| 940 | |||
| 941 | # prepare the full raw data in an OrderedDict: |
||
| 942 | data = OrderedDict() |
||
| 943 | x_data = [] |
||
| 944 | y_data = [] |
||
| 945 | z_data = [] |
||
| 946 | counts_data = [] |
||
| 947 | |||
| 948 | for row in self.depth_image: |
||
| 949 | for entry in row: |
||
| 950 | x_data.append(entry[0]) |
||
| 951 | y_data.append(entry[1]) |
||
| 952 | z_data.append(entry[2]) |
||
| 953 | counts_data.append(entry[3]) |
||
| 954 | |||
| 955 | data['x values (micros)'] = x_data |
||
| 956 | data['y values (micros)'] = y_data |
||
| 957 | data['z values (micros)'] = z_data |
||
| 958 | data['count values (micros)'] = counts_data |
||
| 959 | |||
| 960 | # Save the raw data to file |
||
| 961 | filelabel = 'confocal_depth_data' |
||
| 962 | self._save_logic.save_data(data, |
||
| 963 | filepath, |
||
| 964 | parameters=parameters, |
||
| 965 | filelabel=filelabel, |
||
| 966 | as_text=True, |
||
| 967 | timestamp=save_time |
||
| 968 | ) |
||
| 969 | #, as_xml=False, precision=None, delimiter=None) |
||
| 970 | |||
| 971 | self.log.debug('Confocal Image saved to:\n{0}'.format(filepath)) |
||
| 972 | |||
| 973 | def draw_figure(self, data, image_extent, scan_axis=None, cbar_range=None, percentile_range=None, crosshair_pos=None): |
||
| 974 | """ Create a 2-D color map figure of the scan image. |
||
| 975 | |||
| 976 | @param: array data: The NxM array of count values from a scan with NxM pixels. |
||
| 977 | |||
| 978 | @param: list image_extent: The scan range in the form [hor_min, hor_max, ver_min, ver_max] |
||
| 979 | |||
| 980 | @param: list axes: Names of the horizontal and vertical axes in the image |
||
| 981 | |||
| 982 | @param: list cbar_range: (optional) [color_scale_min, color_scale_max]. If not supplied then a default of |
||
| 983 | data_min to data_max will be used. |
||
| 984 | |||
| 985 | @param: list percentile_range: (optional) Percentile range of the chosen cbar_range. |
||
| 986 | |||
| 987 | @param: list crosshair_pos: (optional) crosshair position as [hor, vert] in the chosen image axes. |
||
| 988 | |||
| 989 | @return: fig fig: a matplotlib figure object to be saved to file. |
||
| 990 | """ |
||
| 991 | if scan_axis is None: |
||
| 992 | scan_axis = ['X', 'Y'] |
||
| 993 | |||
| 994 | # If no colorbar range was given, take full range of data |
||
| 995 | if cbar_range is None: |
||
| 996 | cbar_range = [np.min(data), np.max(data)] |
||
| 997 | |||
| 998 | # Scale color values using SI prefix |
||
| 999 | prefix = ['', 'k', 'M', 'G'] |
||
| 1000 | prefix_count = 0 |
||
| 1001 | image_data = data |
||
| 1002 | draw_cb_range = np.array(cbar_range) |
||
| 1003 | |||
| 1004 | while draw_cb_range[1] > 1000: |
||
| 1005 | image_data = image_data/1000 |
||
| 1006 | draw_cb_range = draw_cb_range/1000 |
||
| 1007 | prefix_count = prefix_count + 1 |
||
| 1008 | |||
| 1009 | c_prefix = prefix[prefix_count] |
||
| 1010 | |||
| 1011 | # Use qudi style |
||
| 1012 | plt.style.use(self._save_logic.mpl_qd_style) |
||
| 1013 | |||
| 1014 | # Create figure |
||
| 1015 | fig, ax = plt.subplots() |
||
| 1016 | |||
| 1017 | # Create image plot |
||
| 1018 | cfimage = ax.imshow(image_data, |
||
| 1019 | cmap=plt.get_cmap('inferno'), # reference the right place in qd |
||
| 1020 | origin="lower", |
||
| 1021 | vmin=draw_cb_range[0], |
||
| 1022 | vmax=draw_cb_range[1], |
||
| 1023 | interpolation='none', |
||
| 1024 | extent=image_extent |
||
| 1025 | ) |
||
| 1026 | |||
| 1027 | ax.set_aspect(1) |
||
| 1028 | ax.set_xlabel(scan_axis[0] + ' position (um)') |
||
| 1029 | ax.set_ylabel(scan_axis[1] + ' position (um)') |
||
| 1030 | ax.spines['bottom'].set_position(('outward', 10)) |
||
| 1031 | ax.spines['left'].set_position(('outward', 10)) |
||
| 1032 | ax.spines['top'].set_visible(False) |
||
| 1033 | ax.spines['right'].set_visible(False) |
||
| 1034 | ax.get_xaxis().tick_bottom() |
||
| 1035 | ax.get_yaxis().tick_left() |
||
| 1036 | |||
| 1037 | # draw the crosshair position if defined |
||
| 1038 | if crosshair_pos is not None: |
||
| 1039 | trans_xmark = mpl.transforms.blended_transform_factory( |
||
| 1040 | ax.transData, |
||
| 1041 | ax.transAxes) |
||
| 1042 | |||
| 1043 | trans_ymark = mpl.transforms.blended_transform_factory( |
||
| 1044 | ax.transAxes, |
||
| 1045 | ax.transData) |
||
| 1046 | |||
| 1047 | ax.annotate('', xy=(crosshair_pos[0], 0), xytext=(crosshair_pos[0], -0.01), xycoords=trans_xmark, |
||
| 1048 | arrowprops=dict(facecolor='#17becf', shrink=0.05), |
||
| 1049 | ) |
||
| 1050 | |||
| 1051 | ax.annotate('', xy=(0, crosshair_pos[1]), xytext=(-0.01, crosshair_pos[1]), xycoords=trans_ymark, |
||
| 1052 | arrowprops=dict(facecolor='#17becf', shrink=0.05), |
||
| 1053 | ) |
||
| 1054 | |||
| 1055 | # Draw the colorbar |
||
| 1056 | cbar = plt.colorbar(cfimage, shrink=0.8)#, fraction=0.046, pad=0.08, shrink=0.75) |
||
| 1057 | cbar.set_label('Fluorescence (' + c_prefix + 'c/s)') |
||
| 1058 | |||
| 1059 | # remove ticks from colorbar for cleaner image |
||
| 1060 | cbar.ax.tick_params(which=u'both', length=0) |
||
| 1061 | |||
| 1062 | # If we have percentile information, draw that to the figure |
||
| 1063 | if percentile_range is not None: |
||
| 1064 | cbar.ax.annotate(str(percentile_range[0]), |
||
| 1065 | xy=(-0.3, 0.0), |
||
| 1066 | xycoords='axes fraction', |
||
| 1067 | horizontalalignment='right', |
||
| 1068 | verticalalignment='center', |
||
| 1069 | rotation=90 |
||
| 1070 | ) |
||
| 1071 | cbar.ax.annotate(str(percentile_range[1]), |
||
| 1072 | xy=(-0.3, 1.0), |
||
| 1073 | xycoords='axes fraction', |
||
| 1074 | horizontalalignment='right', |
||
| 1075 | verticalalignment='center', |
||
| 1076 | rotation=90 |
||
| 1077 | ) |
||
| 1078 | cbar.ax.annotate('(percentile)', |
||
| 1079 | xy=(-0.3, 0.5), |
||
| 1080 | xycoords='axes fraction', |
||
| 1081 | horizontalalignment='right', |
||
| 1082 | verticalalignment='center', |
||
| 1083 | rotation=90 |
||
| 1084 | ) |
||
| 1085 | |||
| 1086 | return fig |
||
| 1087 | |||
| 1088 | ##################################### Tilit correction ######################################## |
||
| 1089 | |||
| 1090 | def set_tilt_point1(self): |
||
| 1091 | """ Gets the first reference point for tilt correction.""" |
||
| 1092 | self.point1 = np.array(self._scanning_device.get_scanner_position()[:3]) |
||
| 1093 | |||
| 1094 | def set_tilt_point2(self): |
||
| 1095 | """ Gets the second reference point for tilt correction.""" |
||
| 1096 | self.point2 = np.array(self._scanning_device.get_scanner_position()[:3]) |
||
| 1097 | |||
| 1098 | def set_tilt_point3(self): |
||
| 1099 | """Gets the third reference point for tilt correction.""" |
||
| 1100 | self.point3 = np.array(self._scanning_device.get_scanner_position()[:3]) |
||
| 1101 | |||
| 1102 | def calc_tilt_correction(self): |
||
| 1103 | """Calculates the values for the tilt correction.""" |
||
| 1104 | a = self.point2 - self.point1 |
||
| 1105 | b = self.point3 - self.point1 |
||
| 1106 | n = np.cross(a,b) |
||
| 1107 | self._scanning_device.tilt_variable_ax = n[0] / n[2] |
||
| 1108 | self._scanning_device.tilt_variable_ay = n[1] / n[2] |
||
| 1109 | |||
| 1110 | def activate_tiltcorrection(self): |
||
| 1111 | self._scanning_device.tiltcorrection = True |
||
| 1112 | self._scanning_device.tilt_reference_x = self._scanning_device.get_scanner_position()[0] |
||
| 1113 | self._scanning_device.tilt_reference_y = self._scanning_device.get_scanner_position()[1] |
||
| 1114 | |||
| 1115 | def deactivate_tiltcorrection(self): |
||
| 1116 | self._scanning_device.tiltcorrection = False |
||
| 1117 | self._scanning_device.tilt_reference_x = self._scanning_device.get_scanner_position()[0] |
||
| 1118 | self._scanning_device.tilt_reference_y = self._scanning_device.get_scanner_position()[1] |
||
| 1119 | |||
| 1120 | View Code Duplication | def history_forward(self): |
|
|
Duplication
introduced
by
|
|||
| 1121 | if self.history_index < len(self.history) - 1: |
||
| 1122 | self.history_index += 1 |
||
| 1123 | self.history[self.history_index].restore(self) |
||
| 1124 | self.signal_xy_image_updated.emit() |
||
| 1125 | self.signal_depth_image_updated.emit() |
||
| 1126 | self._change_position('history') |
||
| 1127 | self.signal_change_position.emit('history') |
||
| 1128 | self.signal_history_event.emit() |
||
| 1129 | |||
| 1130 | View Code Duplication | def history_back(self): |
|
| 1131 | if self.history_index > 0: |
||
| 1132 | self.history_index -= 1 |
||
| 1133 | self.history[self.history_index].restore(self) |
||
| 1134 | self.signal_xy_image_updated.emit() |
||
| 1135 | self.signal_depth_image_updated.emit() |
||
| 1136 | self._change_position('history') |
||
| 1137 | self.signal_change_position.emit('history') |
||
| 1138 | self.signal_history_event.emit() |
||
| 1139 |
Loading history...