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hotfix greater than/less than operations in pdb_manager (#408)
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* hotfix greater than/less than operations in pdb_manager

* bump changelog

* md formatting

* pin numpy <2

* increase test tolerance

* relax test tolerance

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: Arian Jamasb <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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3 people authored Sep 18, 2024
1 parent 2ebd211 commit 17b9d0b
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Showing 4 changed files with 18 additions and 11 deletions.
2 changes: 1 addition & 1 deletion .requirements/base.in
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ looseversion
matplotlib>=3.4.3
multipledispatch
networkx
numpy
numpy<2
pandas
plotly
pydantic
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1 change: 1 addition & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@

#### Bugfixes

* Hotfix greater than/less than operations in PDBManager oligmer selection to include equality. [#408](https://github.com/a-r-j/graphein/pull/408).
* Fixes progress bar for `download_pdb_multiprocessing`. [#394](https://github.com/a-r-j/graphein/pull/394)
* Add support for DSSP >4. Backwards compatibility is still supported. [#355](https://github.com/a-r-j/graphein/pull/355). Fixes [#353](https://github.com/a-r-j/graphein/issues/353).
* Fixes bug where RSA features are missing from nodes with insertion codes. [#355](https://github.com/a-r-j/graphein/pull/355). Fixes [#354](https://github.com/a-r-j/graphein/issues/353).
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20 changes: 12 additions & 8 deletions graphein/ml/datasets/pdb_data.py
Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,6 @@ def __init__(
).name

self.list_columns = ["ligands"]
self.labels = labels

# Data
self.download_metadata()
Expand Down Expand Up @@ -166,10 +165,9 @@ def download_metadata(self):
self._download_entry_metadata()
self._download_exp_type()
self._download_pdb_availability()
if self.labels:
self._download_pdb_chain_cath_uniprot_map()
self._download_cath_id_cath_code_map()
self._download_pdb_chain_ec_number_map()
self._download_pdb_chain_cath_uniprot_map()
self._download_cath_id_cath_code_map()
self._download_pdb_chain_ec_number_map()

def get_unavailable_pdb_files(
self, splits: Optional[List[str]] = None
Expand Down Expand Up @@ -645,12 +643,15 @@ def _parse_cath_code(self) -> Dict[str, str]:
with gzip.open(
self.root_dir / self.cath_id_cath_code_filename, "rt"
) as f:
print(f)
for line in f:
print(line)
try:
cath_id, cath_version, cath_code, cath_segment = (
line.strip().split()
)
cath_mapping[cath_id] = cath_code
print(cath_id, cath_code)
except ValueError:
continue
return cath_mapping
Expand Down Expand Up @@ -1085,7 +1086,10 @@ def oligomeric(
update: bool = False,
) -> pd.DataFrame:
"""Select molecules with a given oligmeric length.
I.e. ``df.n_chains ==/</> oligomer``
I.e. ``df.n_chains ==/ =< / >= oligomer``
N.b. the `comparison` arguments for `"greater"` and `"less"` are
`>=` and `=<` respectively.
:param length: Oligomeric length of molecule, defaults to ``1``.
:type length: int
Expand All @@ -1106,9 +1110,9 @@ def oligomeric(
if comparison == "equal":
df = splits_df.loc[splits_df.n_chains == oligomer]
elif comparison == "less":
df = splits_df.loc[splits_df.n_chains < oligomer]
df = splits_df.loc[splits_df.n_chains <= oligomer]
elif comparison == "greater":
df = splits_df.loc[splits_df.n_chains > oligomer]
df = splits_df.loc[splits_df.n_chains >= oligomer]
else:
raise ValueError(
"Comparison must be one of 'equal', 'less', or 'greater'."
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6 changes: 4 additions & 2 deletions tests/protein/tensor/test_angles.py
Original file line number Diff line number Diff line change
Expand Up @@ -86,7 +86,7 @@ def test_torsion_to_rad():

delta = ((delta + 2 * np.pi) / np.pi) % 2
np.testing.assert_allclose(
delta, torch.zeros_like(delta), atol=1e-4, rtol=1e-4
delta, torch.zeros_like(delta), atol=1e-3, rtol=1e-3
)


Expand Down Expand Up @@ -126,7 +126,9 @@ def test_dihedrals_to_rad():
delta[delta.nonzero()] = torch.abs(delta[torch.nonzero(delta)] - 2 * np.pi)

delta = ((delta + 2 * np.pi) / np.pi) % 2
np.testing.assert_allclose(delta, torch.zeros_like(delta), atol=1e-5)
np.testing.assert_allclose(
delta, torch.zeros_like(delta), atol=1e-4, rtol=1e-4
)


@pytest.mark.skipif(not TORCH_AVAIL, reason="PyTorch not available")
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