Fix bug in `add_k_nn_edges` and add minor extension

[anton-bushuiev]

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What does this implement/fix? Explain your changes

This pull request fixes a bug in add_k_nn_edges. Currenly, kneighbors_graph(X=dist_mat, ...) leads to wrong results which may seem correct. According to scikit-learn docs, it does not support X to be a distance matrix.

Secondly, this PR adds filter_distmat to generalise self-loops filtering. It adds the functionality to filter inter- or intra- connections between nodes of a single or multiple chains. It may be useful to incorporate it into other functions to add edges. By running the following code you will get the visualized graphs.

for val in ['inter', 'intra']:
    edge_funcs = {
        'edge_construction_functions': [
            partial(add_k_nn_edges, k=2, long_interaction_threshold=0, exclude_edges=[val])
        ]
    }
    config = ProteinGraphConfig(**edge_funcs)
    g = construct_graph(config=config, pdb_code='10gs')
...

What testing did you do to verify the changes in this PR?

Pull Request Checklist

• [x] Added a note about the modification or contribution to the ./CHANGELOG.md file (if applicable)
• [x] Added appropriate unit test functions in the ./graphein/tests/* directories (if applicable)
• [ ] Modify documentation in the corresponding Jupyter Notebook under ./notebooks/ (if applicable)
• [x] Ran python -m py.test tests/ and make sure that all unit tests pass (for small modifications, it might be sufficient to only run the specific test file, e.g., python -m py.test tests/protein/test_graphs.py)
• [x] Checked for style issues by running black . and isort .

[a-r-j]

Thanks for this @anton-bushuiev. Good spot!

LGTM! Would you be able to add a couple tests?

[anton-bushuiev]

Yeah, I'll add them tomorrow.

[anton-bushuiev]

Hi, @a-r-j ! I've added the tests. I had to fix a new bug introduced by the distance matrix filtering (see this) 😄.

[sonarcloud[bot]]

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[codecov-commenter]

Codecov Report

Base: 40.27% // Head: 47.86% // Increases project coverage by +7.59% :tada:

Coverage data is based on head (fd1b36b) compared to base (8123f42). Patch coverage: 52.20% of modified lines in pull request are covered.

Additional details and impacted files

```diff @@ Coverage Diff @@ ## master #229 +/- ## ========================================== + Coverage 40.27% 47.86% +7.59% ========================================== Files 48 85 +37 Lines 2811 5398 +2587 ========================================== + Hits 1132 2584 +1452 - Misses 1679 2814 +1135 ``` | [Impacted Files](https://codecov.io/gh/a-r-j/graphein/pull/229?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb) | Coverage Δ | | |---|---|---| | [graphein/ml/diffusion.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vbWwvZGlmZnVzaW9uLnB5) | `0.00% <0.00%> (ø)` | | | [graphein/ppi/graph\_metadata.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcHBpL2dyYXBoX21ldGFkYXRhLnB5) | `0.00% <0.00%> (ø)` | | | [graphein/ppi/visualisation.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcHBpL3Zpc3VhbGlzYXRpb24ucHk=) | `0.00% <0.00%> (ø)` | | | [graphein/protein/analysis.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcHJvdGVpbi9hbmFseXNpcy5weQ==) | `0.00% <0.00%> (ø)` | | | [graphein/protein/features/sequence/utils.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcHJvdGVpbi9mZWF0dXJlcy9zZXF1ZW5jZS91dGlscy5weQ==) | `28.00% <0.00%> (+3.00%)` | :arrow_up: | | [graphein/protein/features/utils.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcHJvdGVpbi9mZWF0dXJlcy91dGlscy5weQ==) | `27.77% <0.00%> (ø)` | | | [graphein/rna/utils.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcm5hL3V0aWxzLnB5) | `38.46% <ø> (ø)` | | | [graphein/rna/visualisation.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vcm5hL3Zpc3VhbGlzYXRpb24ucHk=) | `28.57% <ø> (+28.57%)` | :arrow_up: | | [graphein/utils/config.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vdXRpbHMvY29uZmlnLnB5) | `100.00% <ø> (+100.00%)` | :arrow_up: | | [graphein/utils/config\_parser.py](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb#diff-Z3JhcGhlaW4vdXRpbHMvY29uZmlnX3BhcnNlci5weQ==) | `100.00% <ø> (ø)` | | | ... and [81 more](https://codecov.io/gh/a-r-j/graphein/pull/229/diff?src=pr&el=tree-more&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Arian+Jamasb) | | 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=Arian+Jamasb). 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=Arian+Jamasb)

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[a-r-j]

Thanks for the contribution @anton-bushuiev!