admin/4.0-release-prep-and-benchmark-upgrades #244
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added 11 commits
May 29, 2021 21:17
evamaxfield
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documentation
Codecov Report
@@ Coverage Diff @@
## main #244 +/- ##
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Coverage 95.43% 95.43%
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Files 32 32
Lines 2190 2190
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Hits 2090 2090
Misses 100 100 Continue to review full report at Codecov.
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AetherUnbound
approved these changes
May 30, 2021
benchmarks/benchmark_chunk_sizes.py
Outdated
| # has on the duration of various reads. | ||
| # We would expect that processing speed can be optimized based off of the | ||
| # dimensions of the file and what the user is trying to do with said file. | ||
| # i.e. If the user wants to nrmalize each channel and make a max projection |
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Suggested change
| # i.e. If the user wants to nrmalize each channel and make a max projection | |
| # i.e. If the user wants to normalize each channel and make a max projection |
| projs.compute() | ||
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| def setup(self, img_path, chunk_dims): | ||
| random.seed(42) |
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Description
Makes GitHub igore Jupyter Notebook from lang detection because.... this repo isn't jupyter, a single file is...
More importantly, it cleans up and expands benchmarking. A whole new suite for benchmarking how
chunk_dimsaffects both IO and processing performance. And adds aLibCompareSuitefor comparing aicsimageio against other "just-in-time" image reading libs.In many cases I reduced the number of files benchmarked because our benchmarks currently take ~36 minutes to run... generally just because it is running ALOT of TIFF-like image benchmarks. We don't need to run every file.
Pull request recommendations:
Resolves #242
Related: dask/dask-image#181
Related: dask/dask-image#229
Thanks for contributing!