settylab / Mellon

Non-parametric density inference for single-cell analysis.
https://mellon.readthedocs.io
GNU General Public License v3.0
62 stars 2 forks source link

Merge Dev to v1.2.0 #2

Closed katosh closed 1 year ago

codecov[bot] commented 1 year ago

Codecov Report

Patch coverage: 86.79% and project coverage change: -1.23 :warning:

Comparison is base (4e50f49) 92.90% compared to head (1b922e3) 91.68%.

:exclamation: Current head 1b922e3 differs from pull request most recent head c823e3b. Consider uploading reports for the commit c823e3b to get more accurate results

Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #2 +/- ## ========================================== - Coverage 92.90% 91.68% -1.23% ========================================== Files 16 16 Lines 1086 1419 +333 ========================================== + Hits 1009 1301 +292 - Misses 77 118 +41 ``` | [Impacted Files](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab) | Coverage Δ | | |---|---|---| | [mellon/base\_cov.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL2Jhc2VfY292LnB5) | `91.83% <ø> (+1.83%)` | :arrow_up: | | [mellon/conditional.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL2NvbmRpdGlvbmFsLnB5) | `77.55% <36.84%> (-10.11%)` | :arrow_down: | | [mellon/decomposition.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL2RlY29tcG9zaXRpb24ucHk=) | `83.78% <60.00%> (-6.70%)` | :arrow_down: | | [mellon/parameters.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL3BhcmFtZXRlcnMucHk=) | `89.87% <77.77%> (-6.43%)` | :arrow_down: | | [mellon/model.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL21vZGVsLnB5) | `87.32% <88.23%> (+1.96%)` | :arrow_up: | | [mellon/util.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL3V0aWwucHk=) | `90.47% <90.47%> (-0.23%)` | :arrow_down: | | [mellon/inference.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL2luZmVyZW5jZS5weQ==) | `96.49% <97.29%> (+0.33%)` | :arrow_up: | | [mellon/\_\_init\_\_.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-bWVsbG9uL19faW5pdF9fLnB5) | `100.00% <100.00%> (ø)` | | | [tests/inference.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-dGVzdHMvaW5mZXJlbmNlLnB5) | `100.00% <100.00%> (ø)` | | | [tests/model.py](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab#diff-dGVzdHMvbW9kZWwucHk=) | `100.00% <100.00%> (ø)` | | | ... and [1 more](https://codecov.io/gh/settylab/Mellon/pull/2?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab) | | Help us with your feedback. Take ten seconds to tell us [how you rate us](https://about.codecov.io/nps?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab). Have a feature suggestion? [Share it here.](https://app.codecov.io/gh/feedback/?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=settylab)

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