Revert to node numbering based on list of solvent-exposed residues - …

…more efficient

README.rst

@@ -74,7 +74,7 @@ In addition, users can save graph as a PDB file, with nodes represented by the C
 
 .. code:: python
 
-  >>> SERD.g2pdb(graph, atomic, 'graph.pdb')
+  >>> SERD.g2pdb(graph, atomic, residues, 'graph.pdb')
 
 If users prefer, instead of running **SERD.detect** function, users can apply the detection of solvent-exposed residues in a step-by-step fashion. Below, we briefly describe this procedure.
 
@@ -476,7 +476,7 @@ Create a graph from a list of solvent-exposed residues.
 
   Cutoff for beta-carbon is based on CAPRI round 28. For more details, refer to https://www.ebi.ac.uk/msd-srv/capri/round28/round28.html.
 
-**SERD.g2pdb(graph, atomic, fn='graph.pdb')**
+**SERD.g2pdb(graph, atomic, residues, fn='graph.pdb')**
 
   Save a graph to a PDB-formatted file. Each node are represented by the
   CA atom of the residue and edges are represented by CONECT record.
@@ -487,6 +487,8 @@ Create a graph from a list of solvent-exposed residues.
     * **atomic** (*numpy.ndarray*) – A numpy array with atomic data (residue number, chain, residue name, atom name, xyz coordinates
       and radius) for each atom.
 
+    * **residues** – A list of solvent-exposed residues.
+
     * **fn** (`Union <https://docs.python.org/3/library/typing.html#typing.Union>`_\[`str <https://docs.python.org/3/library/stdtypes.html#str>`_, `pathlib.Path <https://docs.python.org/3/library/pathlib.html#pathlib.Path>`_], *optional*) – A path to a PDB file, by default “graph.pdb”.
 
 *******

SERD/__init__.py

@@ -824,24 +824,22 @@ def r2g(
     if selection != "all":
         atomic = _get_atom_selection(atomic, selection=selection)
 
+    # Keep solvent exposed residues
+    # https://stackoverflow.com/questions/51352527/check-for-identical-rows-in-different-numpy-arrays
+    atomic = atomic[(atomic[:, 0:3][:, None] == residues).all(-1).any(-1)]
+
     # Calculate distance
     distance = _calculate_distance(atomic[:, 4:7])
 
     if selection == "all":
         distance = _all_atoms_to_residues(atomic, distance)
-        atomic = _get_atom_selection(atomic, selection=selection)
 
     # Calculate adjacency matrix
     if intraresidual:
         adjacency = (distance < cutoff).astype(int)
     else:
         adjacency = numpy.logical_and(distance > 0.0, distance < cutoff).astype(int)
 
-    # Keep solvent exposed residues
-    # https://stackoverflow.com/questions/51352527/check-for-identical-rows-in-different-numpy-arrays
-    adjacency[:, ~(atomic[:, 0:3][:, None] == residues).all(-1).any(-1)] = 0
-    adjacency[~(atomic[:, 0:3][:, None] == residues).all(-1).any(-1), :] = 0
-
     # Create networkx.Graph
     G = networkx.Graph()
     G.add_edges_from(numpy.argwhere(adjacency))
@@ -852,6 +850,7 @@ def r2g(
 def g2pdb(
     graph: networkx.classes.graph.Graph,
     atomic: numpy.ndarray,
+    residues: List[List[str]],
     fn: Union[str, pathlib.Path] = "graph.pdb",
 ):
     """Save a graph to a PDB-formatted file. Each node are represented by the
@@ -864,11 +863,14 @@ def g2pdb(
     atomic : numpy.ndarray
         A numpy array with atomic data (residue number, chain, residue name, atom name, xyz coordinates
         and radius) for each atom.
+    residues : List[List[str]]
+        A list of solvent-exposed residues.
     fn : Union[str, pathlib.Path], optional
         A path to a PDB file, by default "graph.pdb".
     """
     # Get atom information of solvent-exposed residues
     atomic = _get_atom_selection(atomic, selection="CA")
+    atomic = atomic[(atomic[:, 0:3][:, None] == residues).all(-1).any(-1)]
 
     # Write nodes to pdb
     with open(fn, "w") as f: