refs #9509. Single threaded CCL works faster.

Small adjustment to the code to use single threaded CCL. Results in a 4-5 times speed up. This is because we have n * small images being processed rather than one large one. The overhead of the parallel execution completely dominates the speed up acheived from the asynchronous thread execution in this case.

The next step will be to make the algorithm parallel with respect to the individual peaks in the peak list. This should result in a further speedup.

Code/Mantid/Framework/Crystal/src/IntegratePeaksHybrid.cpp

@@ -174,6 +174,8 @@ namespace Mantid
       PeakClusterProjection projection(mdWS);
       auto outImageResults = boost::make_shared<WorkspaceGroup>();
 
+      Progress progress(this, 0, 1, peakWS->getNumberPeaks());
+
       //PARALLEL_FOR1(peakWS)
       for (int i = 0; i < peakWS->getNumberPeaks(); ++i)
       {
@@ -215,9 +217,11 @@ namespace Mantid
 
         HardThresholdBackground backgroundStrategy(threshold, normalization);
         // CCL. Multi-processor version.
-        ConnectedComponentLabeling analysis;
+        const size_t startId = 1;
+        const size_t nThreads = 1;
+        ConnectedComponentLabeling analysis(startId, nThreads);
 
-        Progress progress(this, 0, 1, 1); // HACK Fix!
+        Progress dummyProgress;
         // Perform CCL.
         ClusterTuple clusters = analysis.executeAndFetchClusters(localImage, &backgroundStrategy, progress);
         // Extract the clusters
@@ -248,8 +252,9 @@ namespace Mantid
           peak.setIntensity(integratedValues.get<0>());
           peak.setSigmaIntensity(integratedValues.get<1>());
 
-          progress.report();
+
         }
+        progress.report();
         //PARALLEL_END_INTERUPT_REGION
       }
       //PARALLEL_CHECK_INTERUPT_REGION