Merge branch 'master' into code_quality

docs/environment.yaml

@@ -8,3 +8,4 @@ dependencies:
      - pandas
      - scikit-learn
      - beautifulsoup4
+     - networkx

docs/source/Informatics.rst

@@ -17,4 +17,4 @@ Molecular Revised Autocorrelations
 Revised Autocorrelations for MOFs
 ---------------------------------
 
-Documentation for MOFs is coming soon!
+Documentation for RACs coming soon!

molSimplify/Classes/ligand.py

@@ -261,7 +261,7 @@ def percent_buried_vol(self, radius=3.5, gridspec=0.1,
         return percent_buried
 
 
-def ligand_breakdown(mol, flag_loose=False, BondedOct=False, silent=True):
+def ligand_breakdown(mol, flag_loose=False, BondedOct=False, silent=True, transition_metals_only=True):
     """Extract axial and equatorial components of a octahedral complex.
 
     Parameters
@@ -287,7 +287,7 @@ def ligand_breakdown(mol, flag_loose=False, BondedOct=False, silent=True):
     """
     # this function takes an octahedral
     # complex and returns ligands
-    metal_index = mol.findMetal()[0]
+    metal_index = mol.findMetal(transition_metals_only=transition_metals_only)[0]
     bondedatoms = mol.getBondedAtomsSmart(metal_index, oct=True)
     # print('!!!!!boundatoms', bondedatoms)
     # print('from get oct' + str(bondedatoms))

molSimplify/Classes/mol3D.py

@@ -698,9 +698,13 @@ def convert2OBMol2(self, force_clean=False, ignoreX=False):
             #####
             obConversion.SetOutFormat('mol2')
             ss = obConversion.WriteString(OBMol)
-            # Update atom types from OBMol
-            lines = ss.split('ATOM\n')[1].split(
-                '@<TRIPOS>BOND')[0].split('\n')[:-1]
+            # Update atom types from OBMol.
+            if "UNITY_ATOM_ATTR" in ss: # If this section is present, it will be before the @<TRIPOS>BOND section.
+                lines = ss.split('ATOM\n')[1].split(
+                    '@<TRIPOS>UNITY_ATOM_ATTR')[0].split('\n')[:-1]
+            else:
+                lines = ss.split('ATOM\n')[1].split(
+                    '@<TRIPOS>BOND')[0].split('\n')[:-1]  
             for i, line in enumerate(lines):
                 if '.' in line.split()[5]:
                     self.atoms[i].name = line.split()[5].split('.')[1]
@@ -1273,6 +1277,41 @@ def apply_ffopt(self, constraints=False, ff='uff'):
         self.convert2mol3D()
         return en
 
+    def apply_ffopt_list_constraints(self, list_constraints=False, ff='uff'):
+        """
+        Apply forcefield optimization to a given mol3D class.
+        Differs from apply_ffopt in that one can specify constrained atoms as a list.
+
+        Parameters
+        ----------
+            list_constraints : list of int, optional
+                List of atom indices to employ cartesian constraints before ffopt.
+            ff : str, optional
+                Force field to be used in openbabel. Default is UFF.
+
+        Returns
+        -------
+            energy : float
+                Energy of the ffopt in kJ/mol.
+
+        """
+        forcefield = openbabel.OBForceField.FindForceField(ff)
+        constr = openbabel.OBFFConstraints()
+        if list_constraints:
+            for catom in list_constraints:
+                # Openbabel uses a 1 index instead of a 0 index.
+                constr.AddAtomConstraint(catom+1)
+        self.convert2OBMol()
+        forcefield.Setup(self.OBMol, constr)
+        if self.OBMol.NumHvyAtoms() > 10:
+            forcefield.ConjugateGradients(200)
+        else:
+            forcefield.ConjugateGradients(50)
+        forcefield.GetCoordinates(self.OBMol)
+        en = forcefield.Energy()
+        self.convert2mol3D()
+        return en
+
     def findcloseMetal(self, atom0):
         """
         Find the nearest metal to a given atom3D class.
@@ -4978,7 +5017,7 @@ def read_smiles(self, smiles, ff="mmff94", steps=2500):
 
     def get_smiles(self, canonicalize=False, use_mol2=False) -> str:
         """
-        Read a smiles string and convert it to a mol3D class instance.
+        Returns the SMILES string representing the mol3D object.
 
         Parameters
         ----------