def test_spot_detection_with_reference_image_exact_match(
data_stack: ImageStack,
spot_detector: FindSpotsAlgorithm,
max_intensity: float,
):
"""This testing method uses a reference image to identify spot locations then builds traces
using the exact_match strategy. This represents a workflow common in a multiplexed assays.
Each method should detect 2 total spots in the max projected reference image then group them
into 2 distinct spot traces across the ImageStack. """
reference_image = data_stack.reduce((Axes.ROUND, Axes.CH),
func=FunctionSource.np("max"))
spots = spot_detector.run(image_stack=data_stack,
reference_image=reference_image)
intensity_table = trace_builders.build_spot_traces_exact_match(spots)
assert intensity_table.sizes[
Features.AXIS] == 2, "wrong number of spots traces detected"
expected = [max_intensity * 2, max_intensity * 2]
assert np.allclose(intensity_table.sum((Axes.ROUND, Axes.CH)).values, expected), \
"wrong spot intensities detected"
# verify this execution strategy produces an empty intensitytable when called with a blank image
reference_image = EMPTY_IMAGESTACK.reduce((Axes.ROUND, Axes.CH),
func=FunctionSource.np("max"))
spots = spot_detector.run(image_stack=EMPTY_IMAGESTACK,
reference_image=reference_image)
empty_intensity_table = trace_builders.build_spot_traces_exact_match(spots)
assert empty_intensity_table.sizes[Features.AXIS] == 0
def test_spot_finding_reference_image_sequential(
data_stack: ImageStack,
spot_detector: FindSpotsAlgorithm,
max_intensity: float,
):
"""
This testing method uses a reference image to identify spot locations then builds traces
using the sequential strategy. It finds 2 spots in the max projected image, then measures the
two spots on each tile totally 2*num_chs*num_rounds spots. When building spot traces it treats
each spot as it's own trace totally 8 traces. This workflow doesn't really make sense but
we're testing it anyway.
"""
reference_image = data_stack.reduce((Axes.ROUND, Axes.CH), func="max", module=FunctionSource.np)
spots = spot_detector.run(image_stack=data_stack, reference_image=reference_image)
intensity_table = trace_builders.build_traces_sequential(spots)
expected_num_traces = (2 * data_stack.num_chs * data_stack.num_rounds)
assert intensity_table.sizes[Features.AXIS] == expected_num_traces, "wrong number of " \
"spots traces detected"
reference_image = EMPTY_IMAGESTACK.reduce((Axes.ROUND, Axes.CH), func="max",
module=FunctionSource.np)
spots = spot_detector.run(image_stack=EMPTY_IMAGESTACK, reference_image=reference_image)
empty_intensity_table = trace_builders.build_traces_sequential(spots)
assert empty_intensity_table.sizes[Features.AXIS] == 0
def test_spot_detection_with_reference_image(
data_stack: ImageStack,
spot_detector: FindSpotsAlgorithm,
):
"""This testing method uses a reference image to identify spot locations. Each method should
find 2 spots in the reference image then measure the intensity of those locations in each
r/ch pair. The final spot results should represent 2 spots for each r/ch totalling
2*num_rounds*num_ch spots """
reference_image = data_stack.reduce((Axes.ROUND, Axes.CH),
func=FunctionSource.np("max"))
spots_results = spot_detector.run(image_stack=data_stack,
reference_image=reference_image)
assert spots_results.count_total_spots() == (2 * data_stack.num_chs * data_stack.num_rounds), \
"wrong number of spots detected"
