diff --git a/python_tools/void_python_tools/voidUtil/catalogUtil.py b/python_tools/void_python_tools/voidUtil/catalogUtil.py
index 40b2d7d..4bba836 100644
--- a/python_tools/void_python_tools/voidUtil/catalogUtil.py
+++ b/python_tools/void_python_tools/voidUtil/catalogUtil.py
@@ -344,7 +344,8 @@ def loadVoidCatalog(sampleDir, dataPortion="central", loadParticles=True,
                                eigenVecs = np.zeros((3,3)),
                                ))
 
-  print "Read %d voids" % len(catalog.voids)
+  catalog.numVoids = len(catalog.voids)
+  print "Read %d voids" % catalog.numVoids
 
   print "Loading barycenters..."
   iLine = 0
@@ -461,7 +462,7 @@ def getArray(objectList, attr):
       attrArr[:,idim] = np.fromiter((np.atleast_1d(getattr(v, attr))[idim] \
                                     for v in objectList), float )
   
-    if ndim == 1: attrArr = attArr[:,0]
+    if ndim == 1: attrArr = attrArr[:,0]
 
     return attrArr
   else:
diff --git a/python_tools/void_python_tools/voidUtil/profileUtil.py b/python_tools/void_python_tools/voidUtil/profileUtil.py
index 47775a9..0ba4928 100644
--- a/python_tools/void_python_tools/voidUtil/profileUtil.py
+++ b/python_tools/void_python_tools/voidUtil/profileUtil.py
@@ -190,21 +190,19 @@ def getHSWProfile(density, radius):
     },
   ]
 
-  if not np.any(density == samples[:]['name']):
-    print "Sample", density," not found! Use one of ", samples[:]['name']
-    return -1
+  mySample = next((item for item in samples if item['name'] == density), None)
+  if mySample == None:
+    print "Sample", density," not found! Use one of ", [item['name'] for item in samples]
+    return 
 
   # interpolate the radii
-  for sample in samples:
-    if not density == sample['name']: continue
- 
-    rsFunc = interp1d( sample['rv'], sample['rs'], kind='cubic' )
-    dcFunc = interp1d( sample['rv'], sample['dc'], kind='cubic' )
+  rsFunc = interp1d( mySample['rv'], mySample['rs'], kind='cubic' )
+  dcFunc = interp1d( mySample['rv'], mySample['dc'], kind='cubic' )
     
-    rs = rsFunc(radius)
-    dc = dcFunc(radius)  
+  rs = rsFunc(radius)
+  dc = dcFunc(radius)
 
   # return best-fits
   rVals = np.linspace(0.0, 3*radius, 100) / radius
-  return (rs,dc), rVals, HSWProfile(rVals,rs,dc)
+  return (rs,dc), rVals*radius, HSWProfile(rVals,rs,dc)