Merge branch 'v.1.7.7' of https://github.com/a-r-j/graphein into v.1.7.7

Author: a-r-j

.requirements/base.in

@@ -1,4 +1,4 @@
-pandas>=2.0.0
+pandas
 biopandas>=0.5.1
 biopython
 bioservices>=1.10.0
@@ -8,7 +8,7 @@ looseversion
 matplotlib>=3.4.3
 multipledispatch
 networkx
-numpy<1.24.0
+numpy>2.0.0
 pandas
 plotly
 pydantic

graphein/protein/features/nodes/geometry.py

@@ -47,7 +47,9 @@ def add_sidechain_vector(
     if "rgroup_df" not in g.graph.keys():
         g.graph["rgroup_df"] = compute_rgroup_dataframe(g.graph["raw_pdb_df"])
 
-    sc_centroid = g.graph["rgroup_df"].groupby("node_id").mean(numeric_only=True)
+    sc_centroid = (
+        g.graph["rgroup_df"].groupby("node_id").mean(numeric_only=True)
+    )
 
     # Iterate over nodes and compute vector
     for n, d in g.nodes(data=True):

graphein/protein/tensor/io.py

@@ -267,7 +267,9 @@ def protein_to_pyg(
 
     if store_bfactor:
         # group by residue_id and average b_factor per residue
-        residue_bfactors = df.groupby("residue_id")["b_factor"].mean(numeric_only=True)
+        residue_bfactors = df.groupby("residue_id")["b_factor"].mean(
+            numeric_only=True
+        )
         out.bfactor = torch.from_numpy(residue_bfactors.values)
 
     return out