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Single line summaries of docstrings

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This commit is contained in:
Julian Stirling 2025-07-10 01:58:14 +01:00
parent 35d47fe3ed
commit 4dc41bb008
20 changed files with 153 additions and 115 deletions
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46
tests/utilities/scan_test_helpers.py
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@ -14,23 +14,23 @@ THIS_DIR = os.path.dirname(os.path.realpath(__file__))
class FakeSample:
"""A fake sample to test scan algorithms. The sample is able to return
whether a given position is sample, no image associated with the sample
"""A fake sample to test scan algorithms.
The sample is able to return whether a given position is sample, there is no image
associated with the sample
"""
def __init__(self, xy_points: list[tuple[int, int]]):
"""Create the sample from a spline interpolation around
the given points.
"""
"""Create the sample from a spline interpolation around the given points."""
self._sample_perimeter = interp_closed_path(xy_points, 500)
def is_sample(self, pos: tuple[int, int], im_size: tuple[int, int]) -> bool:
"""Return whether an image at a given location with a given image size
is on the sample
"""Return True if an image at a given location is on the sample.
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
The image size is specified to check if it overlaps the sample. It 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.
"""
img_corners = [
(pos[0] + im_size[0], pos[1] + im_size[1]),
@ -77,8 +77,9 @@ 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 create an arbitrary sample shape plan a scan.
"""Interpolate an n_point closed curve from a lists of xy_points.
This can be used to create an arbitrary sample shape for testing a scan planner.
Modified from:
https://stackoverflow.com/questions/33962717/interpolating-a-closed-curve-using-scipy
@ -105,8 +106,9 @@ def interp_closed_path(xy_points: list[tuple[int, int]], n_points: int) -> MatPa
def example_smart_spiral(
sample_name: str = "lobed",
) -> tuple[FakeSample, scan_planners.ScanPlanner]:
"""Run an example scan and return the sample scanned and the planner object
after scan is complete
"""Run an example scan.
:returns: The sample scanned and the planner object after scan is complete.
"""
xy_sample_points = load_sample_points(sample_name)
sample = FakeSample(xy_sample_points)
@ -126,11 +128,11 @@ def example_smart_spiral(
def profile_and_save_plot_for_example_smart_spiral():
"""Run the example scan and save a plot and the profile data
Also print the cumulative stats
"""Run the example scan and save a plot and the profile data.
Also print the cumulative stats.
This runs if you run this file directly
This runs if you run this file directly.
"""
import pstats
import cProfile
@ -152,8 +154,9 @@ def profile_and_save_plot_for_example_smart_spiral():
def update_example_smart_spiral_pickle(sample_name: str):
"""Pickle the ScanPlanner for the example_smart_spiral(),
this is done so the history can be compared by testing to check
"""Pickle the ScanPlanner for the example_smart_spiral().
This is done so the history can be compared by testing to check
the algorithm is unchanged.
If the algorithm is purposefully changed then this will need to be
@ -171,8 +174,9 @@ def update_example_smart_spiral_pickle(sample_name: str):
def get_expected_result_for_example_smart_spiral(
sample_name: str,
) -> scan_planners.ScanPlanner:
"""Return the expected ScanPlanner object for the example_smart_spiral(),
this is pickled, so that it can be committed.
"""Return the expected ScanPlanner object for the example_smart_spiral().
This is loaded from a pickle so that the object can be committed to the repo.
"""
pkl_fname = os.path.join(THIS_DIR, f"example_smart_spiral_{sample_name}.pkl")
with open(pkl_fname, "rb") as pkl_file_obj: