Update testing for multiple sample shapes

This commit is contained in:
Joe Knapper 2025-04-15 16:29:29 +01:00
parent 7373424fcf
commit b414697cfb
7 changed files with 61 additions and 142 deletions

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@ -253,7 +253,22 @@ def test_closest_focus_wth_large_numbers():
def test_example_smart_spiral():
_, planner = scan_test_helpers.example_smart_spiral()
expected_planner = scan_test_helpers.get_expected_result_for_example_smart_spiral()
assert planner.path_history == expected_planner.path_history
assert planner.imaged_locations == expected_planner.imaged_locations
"""Test the smart spiral scan algorithm on the sample types listed
below and defined in scan_test_helpers.load_sample_points
Will fail if the locations or path between locations visited has changed
for any of the samples listed"""
example_samples = [
"regular",
"lobed",
"core",
]
for sample_type in example_samples:
_, planner = scan_test_helpers.example_smart_spiral(sample=sample_type)
expected_planner = (
scan_test_helpers.get_expected_result_for_example_smart_spiral(
sample=sample_type
)
)
assert planner.path_history == expected_planner.path_history
assert planner.imaged_locations == expected_planner.imaged_locations

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@ -111,23 +111,19 @@ def interp_closed_path(xy_points: list[tuple[int, int]], n_points: int) -> MatPa
return MatPath(path_points, closed=True)
def example_smart_spiral() -> tuple[FakeSample, scan_planners.ScanPlanner]:
def example_smart_spiral(
sample: str = "lobed",
) -> tuple[FakeSample, scan_planners.ScanPlanner]:
"""
Run an example scan and return the sample scanned and the planner object
after scan is complete
"""
xy_sample_points = [
(-5000, -5000),
(-2000, 10000),
(1000, 2000),
(6000, 7000),
(9000, 2000),
]
xy_sample_points = load_sample_points(sample=sample)
sample = FakeSample(xy_sample_points)
img_size = (1000, 1000)
intial_position = (0, 0)
planner_settings = {"dx": 700, "dy": 700, "max_dist": 100000}
planner = scan_planners.ShortSmartSpiral(
planner_settings = {"dx": 1200, "dy": 800, "max_dist": 100000}
planner = scan_planners.SmartSpiral(
intial_position=intial_position, planner_settings=planner_settings
)
@ -166,7 +162,7 @@ def profile_and_save_plot_for_example_smart_spiral():
run_stats.print_stats("scan_planners.py")
def update_example_smart_spiral_pickle():
def update_example_smart_spiral_pickle(sample: str):
"""
Pickle the ScanPlanner for the example_smart_spiral(),
this is done so the history can be compared by testing to check
@ -174,23 +170,54 @@ def update_example_smart_spiral_pickle():
If the algorithm is purposefully changed then this will need to be
run to update the pickle for the test to pass.
Takes sample, the sample type we have generated, so we can make a
pickle for each sample type
"""
pkl_fname = os.path.join(THIS_DIR, "example_smart_spiral.pkl")
pkl_fname = os.path.join(THIS_DIR, f"example_smart_spiral_{sample}.pkl")
with open(pkl_fname, "wb") as pkl_file_obj:
_, planner = example_smart_spiral()
_, planner = example_smart_spiral(sample=sample)
pickle.dump(planner, pkl_file_obj, pickle.HIGHEST_PROTOCOL)
def get_expected_result_for_example_smart_spiral():
def get_expected_result_for_example_smart_spiral(sample: str):
"""
Return the expected ScanPlanner object for the example_smart_spiral(),
this is pickled, so that it can be committed.
"""
pkl_fname = os.path.join(THIS_DIR, "example_smart_spiral.pkl")
pkl_fname = os.path.join(THIS_DIR, f"example_smart_spiral_{sample}.pkl")
with open(pkl_fname, "rb") as pkl_file_obj:
planner = pickle.load(pkl_file_obj)
return planner
def load_sample_points(sample: str):
"""Returns the points to generate a FakeSample of sample type "sample" """
sample_options = {
"lobed": [
(-5000, -5000),
(-2000, 16000),
(1000, 2000),
(6000, 7000),
(9000, 2000),
],
"regular": [
(-5000, -5000),
(-5000, 5000),
(5000, 5000),
(5000, -5000),
],
"core": [
(-12000, 2000),
(-12000, 1000),
(0, -2000),
(10000, -2000),
(10000, -1000),
(1000, 0),
],
}
return sample_options[sample]
if __name__ == "__main__":
profile_and_save_plot_for_example_smart_spiral()