opendatacube / odc-stats

Statistician is a framework of tools for generating statistical summaries of large collections of EO data managed in an ODC instance.
Apache License 2.0
9 stars 4 forks source link

[pre-commit.ci] pre-commit autoupdate #79

Closed pre-commit-ci[bot] closed 1 year ago

pre-commit-ci[bot] commented 1 year ago

updates:

codecov[bot] commented 1 year ago

Codecov Report

Base: 75.27% // Head: 75.27% // No change to project coverage :thumbsup:

Coverage data is based on head (abce3ca) compared to base (8f564b2). Patch coverage: 50.00% of modified lines in pull request are covered.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## develop #79 +/- ## ======================================== Coverage 75.27% 75.27% ======================================== Files 33 33 Lines 3134 3134 ======================================== Hits 2359 2359 Misses 775 775 ``` | [Impacted Files](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube) | Coverage Δ | | |---|---|---| | [odc/stats/\_cli\_common.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL19jbGlfY29tbW9uLnB5) | `53.84% <ø> (ø)` | | | [odc/stats/io.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL2lvLnB5) | `32.24% <ø> (ø)` | | | [odc/stats/model.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL21vZGVsLnB5) | `85.19% <ø> (ø)` | | | [odc/stats/plugins/fc\_percentiles.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL3BsdWdpbnMvZmNfcGVyY2VudGlsZXMucHk=) | `85.71% <ø> (ø)` | | | [odc/stats/plugins/mangroves.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL3BsdWdpbnMvbWFuZ3JvdmVzLnB5) | `80.00% <ø> (ø)` | | | [odc/stats/proc.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL3Byb2MucHk=) | `25.64% <0.00%> (ø)` | | | [odc/stats/tasks.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL3Rhc2tzLnB5) | `38.14% <ø> (ø)` | | | [tests/test\_fc\_percentiles.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-dGVzdHMvdGVzdF9mY19wZXJjZW50aWxlcy5weQ==) | `100.00% <ø> (ø)` | | | [tests/test\_utils.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-dGVzdHMvdGVzdF91dGlscy5weQ==) | `99.43% <ø> (ø)` | | | [odc/stats/utils.py](https://codecov.io/gh/opendatacube/odc-stats/pull/79?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=opendatacube#diff-b2RjL3N0YXRzL3V0aWxzLnB5) | `93.87% <100.00%> (ø)` | | 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=opendatacube). 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=opendatacube)

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