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Objects for scan locations allowing more sophisitcated tracking.

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This commit updates the scan planners to allow more sophisticated
tracking of past positions. Currently it still checks that
the algorithm is unchanged from past behaviour.
This commit is contained in:
Julian Stirling 2025-10-19 19:55:36 +01:00
parent 3d3ca9ebcf
commit 39a04df5be
3 changed files with 191 additions and 79 deletions
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31
tests/test_scan_planners.py
View file

@ -254,17 +254,27 @@ def test_closest_focus_with_large_numbers():
planner = scan_planners.SmartSpiral(
initial_position=initial_position, planner_settings=planner_settings
)
# Directly overwrite the private focussed locations list for test
# Directly overwrite the private path history locations list for test
# For two points 1m points away it should choose the last as they are equal
planner._focused_locations = [(1000000, 0, 0), (0, 1000000, 0)]
planner._path_history = [
scan_planners.VisitedScanLocation((1000000, 0, 0), imaged=True, focused=True),
scan_planners.VisitedScanLocation((0, 1000000, 0), imaged=True, focused=True),
]
assert planner.closest_focus_site((0, 0)) == (0, 1000000, 0)
# Try similar
planner._focused_locations = [(1234567, 0, 0), (-1234567, 0, 0)]
planner._path_history = [
scan_planners.VisitedScanLocation((1234567, 0, 0), imaged=True, focused=True),
scan_planners.VisitedScanLocation((-1234567, 0, 0), imaged=True, focused=True),
]
assert planner.closest_focus_site((0, 0)) == (-1234567, 0, 0)
# Make the first point 1 step closer
planner._focused_locations = [(1234566, 0, 0), (-1234567, 0, 0)]
planner._path_history = [
scan_planners.VisitedScanLocation((1234566, 0, 0), imaged=True, focused=True),
scan_planners.VisitedScanLocation((-1234567, 0, 0), imaged=True, focused=True),
]
assert planner.closest_focus_site((0, 0)) == (1234566, 0, 0)
@ -292,5 +302,14 @@ def test_example_smart_spiral():
expected_planner = (
scan_test_helpers.get_expected_result_for_example_smart_spiral(sample_name)
)
assert planner.path_history == expected_planner.path_history
assert planner.imaged_locations == expected_planner.imaged_locations
# Use hasattr to check if the saved test data is the old object where imaged
# locations were saved directly as a list of tuples rather than being generated
# from a history of VisitedScanLocation objects.
# This "if" section of this if-else block can be deleted once we are confident
# of the new format and the pickles are updated
if hasattr(expected_planner, "_imaged_locations"):
assert planner.path_history == expected_planner._path_history
assert planner.imaged_locations == expected_planner._imaged_locations
else:
assert planner.path_history == expected_planner.path_history
assert planner.imaged_locations == expected_planner.imaged_locations

6
tests/utilities/scan_test_helpers.py
View file

@ -60,8 +60,8 @@ def visualise_scan(sample: FakeSample, planner: scan_planners.ScanPlanner) -> Fi
"""For a given sample and scanner object return a matplotlib figure of the scan."""
fig, ax = plt.subplots(figsize=(8, 8))
ax.add_artist(sample.patch)
xh, yh = zip(*planner._path_history, strict=True)
xi, yi, _ = zip(*planner._imaged_locations, strict=True)
xh, yh = zip(*planner.path_history, strict=True)
xi, yi, _zi = zip(*planner.imaged_locations, strict=True)
# convert history to numpy array so can calculate quiver arrows
xh = np.array(xh)
@ -99,7 +99,7 @@ def interp_closed_path(xy_points: list[tuple[int, int]], n_points: int) -> MatPa
# fit splines to x=f(u) and y=g(u), treating both as periodic. also note that s=0
# is needed in order to force the spline fit to pass through all the input points.
spline_data, _ = interpolate.splprep([x, y], s=0, per=True)
spline_data, *_extra = interpolate.splprep([x, y], s=0, per=True)
# evaluate the spline
xi, yi = interpolate.splev(np.linspace(0, 1, n_points), spline_data)