Live View Raster Aim#
This demo illustrates how do design a custom scan that interleaves an aiming scan (two perpendicular segments) periodically throughout a raster scan.
Helper classess are used to generate the segments for each scan with different Flags
so that they can be separated in subsequent processing.
See Interleave Different Scans for a more detailed expalanation of the scan generation.
Building an Interleaved Scan#
pattern = []
idx = numpy.linspace(0, len(raster_segments), 10, dtype=int)
for (i, (a, b)) in enumerate(zip(idx[:-1], idx[1:])):
if i > 0:
markers = raster_segments[a].markers
markers.insert(0, VolumeBoundary(0, 0, False))
markers.insert(0, ScanBoundary(0, 0))
pattern += raster_segments[a:b]
pattern += aiming_segments
ffsc = FreeformScanConfig()
ffsc.pattern = pattern
ffsc.loop = True
Separating Segments by Flags#
fc = FormatPlannerConfig()
fc.adapt_shape = False
fc.mask = rsc.flags
fc.segments_per_volume = rsc.bscans_per_volume
fc.records_per_segment = rsc.ascans_per_bscan
raster_format = FormatPlanner(get_logger('format-raster', cfg.log_level))
raster_format.initialize(fc)
self._raster_format = raster_format
fc.mask = asc.flags
fc.segments_per_volume = asc.bscans_per_volume
fc.records_per_segment = asc.ascans_per_bscan
aiming_format = FormatPlanner(get_logger('format-aiming', cfg.log_level))
aiming_format.initialize(fc)
self._aiming_format = aiming_format
# format executors
cfec = StackFormatExecutorConfig()
cfec.sample_slice = SimpleSlice(self._process.config.samples_per_ascan // 2)
samples_to_save = cfec.sample_slice.count()
sfe = StackFormatExecutor()
sfe.initialize(cfec)
raster_tensor_endpoint = StackDeviceTensorEndpoint(sfe, (rsc.bscans_per_volume, rsc.ascans_per_bscan, samples_to_save), get_logger('endpoint-raster', cfg.log_level))
self._raster_tensor_endpoint = raster_tensor_endpoint
aiming_tensor_endpoint = StackDeviceTensorEndpoint(sfe, (asc.bscans_per_volume, asc.ascans_per_bscan, samples_to_save), get_logger('endpoint-aiming', cfg.log_level))
self._aiming_tensor_endpoint = aiming_tensor_endpoint