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Switch to neighbour cutoff based on dx and dy

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This commit is contained in:
jaknapper 2025-08-19 14:07:30 +01:00
parent 422e63ea90
commit 501fe3f9d2
1 changed files with 7 additions and 4 deletions
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11
src/openflexure_microscope_server/scan_planners.py
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@ -370,8 +370,7 @@ class SmartSpiral(ScanPlanner):
Lowest position is best, as starting too high causes smart stacking to Lowest position is best, as starting too high causes smart stacking to
autofocus and restart. Starting too low just requires extra movements in +z. autofocus and restart. Starting too low just requires extra movements in +z.
Nearby is defined as within NEIGHBOUR_CUTOFF times the distance to the closest Nearby is defined as within 1.1 times the larger of the x and y scan offsets.
neighbour.
Returns None if there if no focused locations are present Returns None if there if no focused locations are present
""" """
@ -386,9 +385,13 @@ 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)
# Get indices of all focused sites within NEIGHBOUR_CUTOFF the minimum distance. # 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.
# 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 <= NEIGHBOUR_CUTOFF * np.min(dists))[0] indices = np.where(dists <= distance_cutoff)[0]
# Turning into an array allows slicing based on a list # Turning into an array allows slicing based on a list
focused_locations_array = np.array(self._focused_locations) focused_locations_array = np.array(self._focused_locations)