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1 year ago Codecov Report
Attention: 5 lines in your changes are missing coverage. Please review.
Comparison is base (
6b1a6c3) 89.72% compared to head (5fb1eb5) 90.04%.
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```diff @@ Coverage Diff @@ ## master #88 +/- ## ========================================== + Coverage 89.72% 90.04% +0.31% ========================================== Files 151 154 +3 Lines 5012 5111 +99 ========================================== + Hits 4497 4602 +105 + Misses 515 509 -6 ``` | [Files](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation) | Coverage Δ | | |---|---|---| | [...onstrained\_convex\_minimization/gradient\_descent.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvZXhhbXBsZXMvdW5jb25zdHJhaW5lZF9jb252ZXhfbWluaW1pemF0aW9uL2dyYWRpZW50X2Rlc2NlbnQucHk=) | `79.16% <100.00%> (ø)` | | | [PEPit/functions/\_\_init\_\_.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvZnVuY3Rpb25zL19faW5pdF9fLnB5) | `100.00% <100.00%> (ø)` | | | [PEPit/functions/smooth\_convex\_function.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvZnVuY3Rpb25zL3Ntb290aF9jb252ZXhfZnVuY3Rpb24ucHk=) | `85.71% <ø> (ø)` | | | [PEPit/operators/\_\_init\_\_.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvb3BlcmF0b3JzL19faW5pdF9fLnB5) | `100.00% <100.00%> (ø)` | | | [PEPit/operators/cocoercive.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvb3BlcmF0b3JzL2NvY29lcmNpdmUucHk=) | `93.33% <100.00%> (ø)` | | | [PEPit/operators/lipschitz.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvb3BlcmF0b3JzL2xpcHNjaGl0ei5weQ==) | `93.33% <100.00%> (ø)` | | | [PEPit/operators/lipschitz\_strongly\_monotone.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvb3BlcmF0b3JzL2xpcHNjaGl0el9zdHJvbmdseV9tb25vdG9uZS5weQ==) | `94.11% <100.00%> (ø)` | | | [PEPit/operators/monotone.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvb3BlcmF0b3JzL21vbm90b25lLnB5) | `100.00% <100.00%> (ø)` | | | [PEPit/operators/strongly\_monotone.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvb3BlcmF0b3JzL3N0cm9uZ2x5X21vbm90b25lLnB5) | `100.00% <100.00%> (ø)` | | | [PEPit/primitive\_steps/epsilon\_subgradient\_step.py](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation#diff-UEVQaXQvcHJpbWl0aXZlX3N0ZXBzL2Vwc2lsb25fc3ViZ3JhZGllbnRfc3RlcC5weQ==) | `100.00% <ø> (ø)` | | | ... and [9 more](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation) | | ... and [1 file with indirect coverage changes](https://app.codecov.io/gh/PerformanceEstimation/PEPit/pull/88/indirect-changes?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=PerformanceEstimation):umbrella: View full report in Codecov by Sentry.
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It adds the operator classes "cocoercive strongly monotone" and "negatively comonotone".
It also fixes some minor typos here and there.
About the negative comonotonicity. It has been added for readability but is exactly the same as strong monotonicity with a negative parameter. Is it really useful?