casact / chainladder-python

Actuarial reserving in Python
https://chainladder-python.readthedocs.io/en/latest/
Mozilla Public License 2.0
192 stars 71 forks source link

adding 4D support for drop_above/below #375

Closed henrydingliu closed 2 years ago

henrydingliu commented 2 years ago

plus some further debugging of drop_hi/lo

codecov-commenter commented 2 years ago

Codecov Report

Base: 83.22% // Head: 83.35% // Increases project coverage by +0.13% :tada:

Coverage data is based on head (214d0af) compared to base (1aa6a72). Patch coverage: 100.00% of modified lines in pull request are covered.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #375 +/- ## ========================================== + Coverage 83.22% 83.35% +0.13% ========================================== Files 49 49 Lines 4238 4254 +16 Branches 710 708 -2 ========================================== + Hits 3527 3546 +19 + Misses 509 507 -2 + Partials 202 201 -1 ``` | Flag | Coverage Δ | | |---|---|---| | unittests | `83.35% <100.00%> (+0.13%)` | :arrow_up: | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#carryforward-flags-in-the-pull-request-comment) to find out more. | [Impacted Files](https://codecov.io/gh/casact/chainladder-python/pull/375?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None) | Coverage Δ | | |---|---|---| | [chainladder/development/base.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvZGV2ZWxvcG1lbnQvYmFzZS5weQ==) | `91.72% <100.00%> (+1.79%)` | :arrow_up: | | [chainladder/core/triangle.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvY29yZS90cmlhbmdsZS5weQ==) | `89.13% <0.00%> (ø)` | | | [chainladder/methods/benktander.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvbWV0aG9kcy9iZW5rdGFuZGVyLnB5) | `96.66% <0.00%> (ø)` | | | [chainladder/utils/utility\_functions.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvdXRpbHMvdXRpbGl0eV9mdW5jdGlvbnMucHk=) | `82.55% <0.00%> (ø)` | | | [chainladder/core/base.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvY29yZS9iYXNlLnB5) | `80.99% <0.00%> (+0.23%)` | :arrow_up: | | [chainladder/core/slice.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvY29yZS9zbGljZS5weQ==) | `87.85% <0.00%> (+0.40%)` | :arrow_up: | | [chainladder/methods/capecod.py](https://codecov.io/gh/casact/chainladder-python/pull/375/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-Y2hhaW5sYWRkZXIvbWV0aG9kcy9jYXBlY29kLnB5) | `81.39% <0.00%> (+1.64%)` | :arrow_up: | 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=None). 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=None)

:umbrella: View full report at Codecov.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.

jbogaardt commented 2 years ago

Thank you @henrydingliu!