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4.) refactoring allen smFish with new spot finding #1593
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Codecov Report
@@ Coverage Diff @@
## master #1593 +/- ##
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- Coverage 88.18% 86.22% -1.97%
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Files 152 155 +3
Lines 5241 5516 +275
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+ Hits 4622 4756 +134
- Misses 619 760 +141
Continue to review full report at Codecov.
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@@ -123,6 +125,11 @@ def processing_pipeline( | |||
print("Loading images...") | |||
images = enumerate(experiment[fov_name].get_images(FieldOfView.PRIMARY_IMAGES)) | |||
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decoder = starfish.spots.DecodeSpots.PerRoundMaxChannel( |
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following the other components of this pipeline, this should be above (search for "define")
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I wanted to put it above but there's no access to the experiment.codebook at that point
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Ahh, I see.
spot_attributes = tlmpf.run(primary_image) | ||
all_intensities.append(spot_attributes) | ||
spots = tlmpf.run(primary_image) | ||
decoded_intensities = decoder.run(spots) |
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should add print("Decoding spots...")
@@ -66,5 +103,6 @@ def build_traces_nearest_neighbors(spot_results: SpotFindingResults, anchor_roun | |||
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trace_builders: Mapping[TraceBuildingStrategies, Callable] = { | |||
TraceBuildingStrategies.EXACT_MATCH: build_spot_traces_exact_match, | |||
TraceBuildingStrategies.NEAREST_NEIGHBOR: build_traces_nearest_neighbors | |||
TraceBuildingStrategies.NEAREST_NEIGHBOR: build_traces_nearest_neighbors, | |||
TraceBuildingStrategies.SEQUENTIAL: build_traces_sequential |
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TraceBuildingStrategies.SEQUENTIAL: build_traces_sequential | |
TraceBuildingStrategies.SEQUENTIAL: build_traces_sequential, |
Parameters | ||
---------- | ||
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spot_diameter : odd integer or tuple of odd integers. |
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- params are not actually typed to match what is in the description.
- the params' types in the documentation does not follow the standard style we use (which is whatever is the typing in the actual function declaration).
- the styling for defaults does not match the styling for defaults in earlier PRs.
- some defaults are missing.
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@pytest.mark.skip('issues with checksums prevent this data from working properly') | ||
@pytest.mark.skip('This test runs but takes forever') |
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hahahahaha
For what it's worth, there are a few allen smfish FOVs that have relatively few spots and run relatively quickly (2-3 minutes?)
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Do you know which ones?
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fov_004 has very few spots.
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@@ -123,6 +125,11 @@ def processing_pipeline( | |||
print("Loading images...") | |||
images = enumerate(experiment[fov_name].get_images(FieldOfView.PRIMARY_IMAGES)) | |||
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decoder = starfish.spots.DecodeSpots.PerRoundMaxChannel( |
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Ahh, I see.
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@pytest.mark.skip('issues with checksums prevent this data from working properly') | ||
@pytest.mark.skip('This test runs but takes forever') |
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fov_004 has very few spots.
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* refactoring localMaxPeakFinder * adding MetricDecoder to DecodeSpots (#1596)
This PR:
depends on: #1592 #1518 #1517