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+.. algorithm::
+
+.. summary::
+
+.. alias::
+
+.. properties::
+
+Description
+-----------
+Used to crop an n-dimensional :ref:`MDHistoWorkspace <MDHistoWorkspace>` to the first non-zero signal values found in all dimensions.
+
+Cropping
+--------
+The cropping is done by supplying `IntegrateMDHistoWorkspace <http://docs.mantidproject.org/nightly/algorithms/IntegrateMDHistoWorkspace-v1.html>`__ with the minimum and maximum extents associated with the first non-zero
+signal values in the workspace.
+
+
+Usage
+-----
+
+
+**Example - CompactMD on MDHistoWorkspace**
+
+.. testcode:: CompactMDOnMDHistoWorkspace
+
+    import math
+    #create an MDEventWorkspace for Rebinning
+    mdws = CreateMDWorkspace(Dimensions=3, Extents='-10,10,-10,10,-10,10', Names='A,B,C', Units='U,U,U')
+    FakeMDEventData(InputWorkspace=mdws, PeakParams='100000,-5,-5,0,1')
+    FakeMDEventData(InputWorkspace=mdws, PeakParams='100000,0,0,0,1')
+    FakeMDEventData(InputWorkspace=mdws, PeakParams='100000,5,5,0,1')
+    #Rebin mdws to create an MDHistoWorkspace
+    binned_ws = BinMD(InputWorkspace=mdws, AxisAligned=False, BasisVector0='a,unit,1,1,0',BasisVector1='b,unit,-1,1,0',BasisVector2='c,unit,0,0,1',NormalizeBasisVectors=True,Translation=[-10,-10,0], OutputExtents=[0,math.sqrt(2*20*20),-2,2,-10,10], OutputBins=[100, 100, 1] )
+    
+    #A visualisation of the rebinned_ws can be found in the 'Input' section below.
+    
+    #run CompactMD on the rebinned workspace 
+    compact_output = CompactMD(binned_ws)
+    
+    #A visualisation of the compacted workspace can be found in the 'Output' section below.
+
+Input:
+
+.. figure:: /images/RebbinedWorkspaceNoCompactMDApplied.jpg
+   :alt: RebbinedWorkspaceNoCompactMDApplied.jpg
+   :width: 400px
+   :align: center
+
+   
+Output:
+
+.. figure:: /images/RebbinedWorkspaceWithCompactMDApplied.jpg
+   :alt: RebbinedWorkspaceWithCompactMDApplied.jpg
+   :width: 400px
+   :align: center
+
+   
+   
+.. categories::
+
+.. sourcelink::
\ No newline at end of file
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