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Spelling corrections and docstring improvements

Browse source 
Co-authored by Joe Knapper <jaknapper@hotmail.com>
This commit is contained in:
Julian Stirling 2025-04-14 15:46:27 +00:00
parent bd411db5ea
commit 06632f195e
5 changed files with 33 additions and 29 deletions
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6
tests/test_scan_planners.py
View file

@ -39,7 +39,7 @@ def test_v_basic_smart_spiral():
planner = scan_planners.SmartSpiral(
intial_position=intial_position, planner_settings=planner_settings
)
# Create a planner it shouldn't start complete
# Create a planner. It shouldn't be complete.
assert not planner.scan_complete
# When we start it should want to stay in the inital pos and have
# no z_estimate
@ -47,7 +47,7 @@ def test_v_basic_smart_spiral():
assert xy_pos == intial_position
assert z_pos is None
# Try to make imaged with only xy_position
# Try to mark location as imaged with only xy_position
with pytest.raises(ValueError):
planner.mark_location_visited(xy_pos, imaged=False, focused=False)
# scan still not complete
@ -100,7 +100,7 @@ def test_smart_spiral_first_few_pos():
This test is VERY long, not really a "unit". It checks step-by-step
that data is added correctly for the first few postions in a scan.
This should catch basic caseses of if the algorithm is updated.
This should catch basic cases of if the algorithm is updated.
"""
intial_position = (100, 50)
planner_settings = {"dx": 50, "dy": 50, "max_dist": 10000}

6
tests/utilities/scan_test_helpers.py
View file

@ -31,7 +31,7 @@ class FakeSample:
Return whether an image at a given location with a given image size
is on the sample
This doesn't check the entire image feild as this is designed to be used
This doesn't check the entire image field as this is designed to be used
where the fake sample is much larger than the image and has smooth edges
It just checks the 4 corners
"""
@ -48,7 +48,7 @@ class FakeSample:
@property
def patch(self) -> PathPatch:
"""
The sample as a matplotlib patch fro plotting
The sample as a matplotlib patch for plotting
"""
patch = PathPatch(self._sample_perimeter)
patch.set(color=(1.0, 0.8, 1.0, 1.0))
@ -86,7 +86,7 @@ def visualise_scan(sample: FakeSample, planner: scan_planners.ScanPlanner) -> Fi
def interp_closed_path(xy_points: list[tuple[int, int]], n_points: int) -> MatPath:
"""
Given a lists of xy_points interpolate an n_point closed curve. This can be used
to creat an arbitrary sample shape plan a scan.
to create an arbitrary sample shape plan a scan.
Modified from:
https://stackoverflow.com/questions/33962717/interpolating-a-closed-curve-using-scipy