sissa-data-science / DADApy

Distance-based Analysis of DAta-manifolds in python
https://dadapy.readthedocs.io/
Apache License 2.0
103 stars 18 forks source link

I3D #83

Closed imacocco closed 1 year ago

imacocco commented 1 year ago

Proposed changes

Adding discrete routines to main branch (and documentation)

codecov-commenter commented 1 year ago

Codecov Report

Patch coverage: 81.33% and project coverage change: -0.28 :warning:

Comparison is base (4a06bb8) 82.14% compared to head (1fdfb51) 81.87%.

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Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #83 +/- ## ========================================== - Coverage 82.14% 81.87% -0.28% ========================================== Files 10 14 +4 Lines 1585 2372 +787 ========================================== + Hits 1302 1942 +640 - Misses 283 430 +147 ``` | [Impacted Files](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None) | Coverage Δ | | |---|---|---| | [dadapy/\_utils/id\_estimation.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L191dGlscy9pZF9lc3RpbWF0aW9uLnB5) | `67.94% <67.94%> (ø)` | | | [dadapy/base.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L2Jhc2UucHk=) | `85.85% <75.00%> (ø)` | | | [dadapy/id\_discrete.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L2lkX2Rpc2NyZXRlLnB5) | `79.80% <79.80%> (ø)` | | | [dadapy/\_utils/discrete\_functions.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L191dGlscy9kaXNjcmV0ZV9mdW5jdGlvbnMucHk=) | `90.76% <90.76%> (ø)` | | | [dadapy/\_\_init\_\_.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L19faW5pdF9fLnB5) | `100.00% <100.00%> (ø)` | | | [dadapy/\_utils/\_\_init\_\_.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L191dGlscy9fX2luaXRfXy5weQ==) | `100.00% <100.00%> (ø)` | | | [dadapy/\_utils/utils.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L191dGlscy91dGlscy5weQ==) | `66.08% <100.00%> (ø)` | | | [dadapy/id\_estimation.py](https://app.codecov.io/gh/sissa-data-science/DADApy/pull/83?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=None#diff-ZGFkYXB5L2lkX2VzdGltYXRpb24ucHk=) | `84.92% <100.00%> (ø)` | |

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