Change predictions_to_csv API to cover multi scaffolds

Contrib/FreeWilson/README.md

@@ -70,7 +70,7 @@ Here are some examples (see using Molecular Filters below)
 >>> preds = FWBuild(decomp, 
 ...                 pred_filter=lambda x: x > 8, 
 ...                 mw_filter=lambda mw: 100<mw<550)
->>> predictions_to_csv(sys.stdout, preds)
+>>> predictions_to_csv(sys.stdout, decomp, preds)
 
 ```
 

Contrib/FreeWilson/freewilson.py

@@ -80,7 +80,7 @@ Here are some examples (see using Molecular Filters below)
 >>> preds = FWBuild(decomp, 
 ...                 pred_filter=lambda x: x > 8, 
 ...                 mw_filter=lambda mw: 100<mw<550)
->>> predictions_to_csv(sys.stdout, preds)
+>>> predictions_to_csv(sys.stdout, decomp, preds)
 
 ```
 
@@ -267,7 +267,7 @@ def FWDecompose(scaffolds, mols, scores, decomp_params=default_decomp_params) ->
     For an easy way to report predictions see 
 
        >>> import sys
-       >>> predictions_to_csv(sys.stdout, FWBuild(fw))
+       >>> predictions_to_csv(sys.stdout, fw, FWBuild(fw))
 
    
     See FWBuild docs to see how to filter predictions, molecular weight or molecular properties.
@@ -489,19 +489,19 @@ def _rgroup_sort(r):
     if r[0] == "R": return ("R", int(r[1:]))
     return (r, None)
 
-def predictions_to_csv(outstream, predictions):
+def predictions_to_csv(outstream, decomposition: FreeWilsonDecomposition, predictions):
     """Output predictions in csv format to the output stream
 
        :param outstream: output stream to write results
-       :param fw: freewillson decomposition
+       :param decomposition: freewillson decomposition
        :param predictions: list of Predictions to output
     """
     writer = None
     for pred in predictions:
         if not writer:
             rgroups = set()
-            for sidechain in pred.rgroups:
-                rgroups.add(sidechain.rgroup)
+            for rgroup in decomposition.rgroups:
+                rgroups.add(rgroup)
             rgroups = sorted(rgroups, key=_rgroup_sort)
 
             lookup = {}
@@ -515,7 +515,7 @@ def predictions_to_csv(outstream, predictions):
             rg[lookup[s.rgroup]] = s.smiles
         row = [pred.smiles, repr(pred.prediction)] + rg
         writer.writerow(row)
-            
+
 def test_freewilson():
     # some simple tests
     from rdkit import Chem

Contrib/FreeWilson/test/test_freewilson.py

@@ -0,0 +1,63 @@
+import freewilson as fw
+from rdkit import rdBase, Chem
+import csv, os, io
+import logging
+PATH = os.path.join(os.path.dirname(fw.__file__), 'data')
+assert os.path.exists(PATH), PATH
+
+def test_chembl():
+    logging.getLogger().setLevel(logging.INFO)
+    smilesfile = os.path.join(PATH, "CHEMBL2321810.smi")
+    scaffoldfile = os.path.join(PATH, "CHEMBL2321810_scaffold.mol")
+    csvfile = os.path.join(PATH, "CHEMBL2321810_act.csv")
+    assert os.path.exists(smilesfile)
+    mols = []
+    for line in open(smilesfile):
+        smiles, name = line.strip().split()
+        m = Chem.MolFromSmiles(smiles)
+        m.SetProp("_Name", name)
+        mols.append(m)
+
+    scaffold = Chem.MolFromMolBlock(open(scaffoldfile).read())
+    data = {k:float(v) for k,v in list(csv.reader(open(csvfile)))[1:]}
+
+    scores = [data[m.GetProp("_Name")] for m in mols]
+    assert mols and len(mols) == len(scores)
+
+    blocker = rdBase.BlockLogs()
+    free = fw.FWDecompose(scaffold, mols, scores)
+    # let's make sure the r squared is decent
+    assert free.r2 > 0.8
+
+    # assert we get something
+    preds = list(fw.FWBuild(free))
+    assert len(preds)
+
+    # check to see that the prediction filters work
+    preds2 = list(fw.FWBuild(free, pred_filter=lambda x: x > 8))
+    assert len(preds2)
+    assert len([p for p in preds if p.prediction > 8]) == len(list(preds2))
+    
+
+    # check to see that the R groups are output in order, i.e. R10 after R3
+    s = io.StringIO()
+    fw.predictions_to_csv(s, free, preds2)
+    assert s.getvalue()
+
+    s2 = io.StringIO(s.getvalue())
+    for i,row in enumerate(csv.reader(s2)):
+        if i == 0:
+            assert row == ['smiles','prediction','Core_smiles','R1_smiles','R3_smiles','R10_smiles']
+    assert i>0
+
+
+def test_multicore():
+    # test that we can add rgroups for later cores and not throw an exception
+    scaffolds = [Chem.MolFromSmiles("c1ccccc1[*].NC=O"), Chem.MolFromSmiles("C1CCCCC1")]
+    mols = [Chem.MolFromSmiles(x) for x in ['c1ccccc1CC2CNC2C(=O)N', 'Cc1ccccc1CC2CNC2C(=O)N', 'Cc1ccccc1CC2CNCC(=O)NC2', 'C3c1ccccc1CC2CNC2C(=O)N3', 'C1CCCCC1F', 'ClC1CCCCC1F']]    
+    decomp=fw.FWDecompose(scaffolds, mols, [1,2,3,4,5,6])
+    s = io.StringIO()
+    fw.predictions_to_csv(s, decomp, fw.FWBuild(decomp))
+
+
+