diff --git a/docs/source/algorithms/LineProfile-v1.rst b/docs/source/algorithms/LineProfile-v1.rst
index 963da14b0f8ec83551dd86e80e650d7f3072f672..7e6b73a9aca1ad2ccff13147ba3c6b6b319feb92 100644
--- a/docs/source/algorithms/LineProfile-v1.rst
+++ b/docs/source/algorithms/LineProfile-v1.rst
@@ -144,17 +144,17 @@ Output:
     sumCutWS = LineProfile(wsInTheta, centre, width, Mode='Sum')
 
     # When no NaNs are present both modes give the same result.
-    iElastic = sumCutWS.blocksize() / 2
+    iElastic = sumCutWS.blocksize() // 2
     y = sumCutWS.readY(0)[iElastic]
     e = sumCutWS.readE(0)[iElastic]
-    print('Sum profile at elastic peak: {} +/- {}'.format(y, e))
+    print('Sum profile at elastic peak: {:.8f} +/- {:.10f}'.format(y, e))
 
     # The weighting is apparent when the profile crosses some
     # special values.
-    iEdge = sumCutWS.blocksize() / 6
+    iEdge = sumCutWS.blocksize() // 6
     y = sumCutWS.readY(0)[iEdge]
     e = sumCutWS.readE(0)[iEdge]
-    print('Sum profile near NaNs: {} +/- {}'.format(y, e))
+    print('Sum profile near NaNs: {:.11f} +/- {:.11f}'.format(y, e))
 
 .. testoutput:: SumMode