rahix/openflexure-microscope-server
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Added neighbour ratio to spiral scan init

Browse source
This commit is contained in:
jaknapper 2025-09-05 10:55:03 +01:00
parent 85e10189be
commit ce5a22eb64
1 changed files with 18 additions and 17 deletions
Download patch file Download diff file Expand all files Collapse all files

35
src/openflexure_microscope_server/scan_planners.py
View file

@ -19,13 +19,6 @@ XYPosList: TypeAlias = list[XYPos]
XYZPosList: TypeAlias = list[XYZPos] XYZPosList: TypeAlias = list[XYZPos]
# how many times the minimum distance between images to include as a "nearby" image
# default 1.6 includes images offset in x or y, but not diagonally.
# This wis based of a 4:3 aspect ratio. So x moves are 1.33 times larger than y
# testing revealed that asymmetric CSM led to anything below 1.5 being insufficient
NEIGHBOUR_CUTOFF = 1.6
def enforce_xy_tuple(value: XYPos) -> XYPos: def enforce_xy_tuple(value: XYPos) -> XYPos:
"""Check input is a tuple and is of length 2. """Check input is a tuple and is of length 2.
@ -243,18 +236,30 @@ class SmartSpiral(ScanPlanner):
Each time and image is taken the four neighbouring images are added Each time and image is taken the four neighbouring images are added
to the list of positions to image (unless they are already listed or to the list of positions to image (unless they are already listed or
tried). However, if a location is not imaged due no sample being detected tried). However, if a location is not imaged due no sample being detected,
then neibouring positions are not imaged. then neighbouring positions are not imaged.
The next image taken is the closes to the centre (considering the largest The next image taken is the fewest scan sites (moves in dx and dy) from the current
of vertical or horizontal distance), ties are broken by the distance from site, with ties broken by minimising the moves away from the start of the scan.
the current position. Final tiebreak is the distance to each site, in motor steps rather than multiple of
dx and dy.
""" """
_max_dist: int = 0 _max_dist: int = 0
_dx: int = 0 _dx: int = 0
_dy: int = 0 _dy: int = 0
def __init__(
self, initial_position: XYPos, planner_settings: Optional[dict] = None
):
"""Set up the lists inherited from ScanPlanner, plus a distance cutoff.
Use the supplied _dx and _dy to set a distance cutoff for an image to be
considered neighbouring another
"""
super().__init__(initial_position, planner_settings)
self._distance_cutoff = max([self._dx, self._dy]) * 1.1
def _parse(self, planner_settings: Optional[dict] = None) -> None: def _parse(self, planner_settings: Optional[dict] = None) -> None:
"""Parse SmartSpiral Settings dictionary. """Parse SmartSpiral Settings dictionary.
@ -388,13 +393,9 @@ class SmartSpiral(ScanPlanner):
# Note linalg.norm always uses float64 # Note linalg.norm always uses float64
dists = np.linalg.norm((path_pos - current_pos), axis=1) dists = np.linalg.norm((path_pos - current_pos), axis=1)
# distance_cutoff is the larger of the x and y offsets, times 1.1 to ensure
# that rounding at any point doesn't cause problems
distance_cutoff = max([self._dx, self._dy]) * 1.1
# Get indices of all focused sites within distance_cutoff. # Get indices of all focused sites within distance_cutoff.
# Note np.where always returns a tuple of arrays, hence the trailing [0] # Note np.where always returns a tuple of arrays, hence the trailing [0]
indices = np.where(dists <= distance_cutoff)[0] indices = np.where(dists <= self._distance_cutoff)[0]
# Handle the case that no focused positions are within this range, and # Handle the case that no focused positions are within this range, and
# instead use the nearest focused position. This will always return a # instead use the nearest focused position. This will always return a