Index: /issm/trunk-jpl/src/m/interp/averaging.m
===================================================================
--- /issm/trunk-jpl/src/m/interp/averaging.m	(revision 16054)
+++ /issm/trunk-jpl/src/m/interp/averaging.m	(revision 16055)
@@ -20,5 +20,5 @@
 
 if ((nargin~=4) & (nargin~=3)),
-	error('averaging error message');
+	error('averaging error message: wrong number of arguments');
 end
 if (length(data)~=md.mesh.numberofelements & length(data)~=md.mesh.numberofvertices),
Index: /issm/trunk-jpl/src/m/interp/averaging.py
===================================================================
--- /issm/trunk-jpl/src/m/interp/averaging.py	(revision 16055)
+++ /issm/trunk-jpl/src/m/interp/averaging.py	(revision 16055)
@@ -0,0 +1,89 @@
+import numpy as npy
+from GetAreas import GetAreas
+from scipy.sparse import csc_matrix
+
+def averaging(md,data,iterations,layer=0):
+	'''
+	AVERAGING - smooths the input over the mesh
+	
+	   This routine takes a list over the elements or the nodes in input
+	   and return a list over the nodes.
+	   For each iterations it computes the average over each element (average 
+	   of the vertices values) and then computes the average over each node
+	   by taking the average of the element around a node weighted by the
+	   elements volume
+	   For 3d mesh, a last argument can be added to specify the layer to be averaged on.
+	
+	   Usage:
+	      smoothdata=averaging(md,data,iterations)
+	      smoothdata=averaging(md,data,iterations,layer)
+	
+	   Examples:
+	      velsmoothed=averaging(md,md.initialization.vel,4)
+	      pressure=averaging(md,md.initialization.pressure,0)
+	      temperature=averaging(md,md.initialization.temperature,1,1)
+	'''
+
+	if (len(data)!=md.mesh.numberofelements & len(data)!=md.mesh.numberofvertices):
+		raise StandardError('averaging error message: data not supported yet')
+	if md.mesh.dimension==3 and layer!=0:
+		if layer<=0 or layer>md.mesh.numberoflayers:
+			raise ValueError('layer should be between 1 and md.mesh.numberoflayers')
+	else:
+		layer=0
+	
+	#initialization
+	if layer==0:
+		weights=npy.zeros(md.mesh.numberofvertices,)
+		data=data.flatten(1)
+	else:
+		weights=npy.zeros(md.mesh.numberofvertices2d,)
+		data=data[(layer-1)*md.mesh.numberofvertices2d+1:layer*md.mesh.numberofvertices2d,:]
+	
+	#load some variables (it is much faster if the variabes are loaded from md once for all)
+	if layer==0:
+		index=md.mesh.elements
+		numberofnodes=md.mesh.numberofvertices
+		numberofelements=md.mesh.numberofelements
+	else:
+		index=md.mesh.elements2d
+		numberofnodes=md.mesh.numberofvertices2d
+		numberofelements=md.mesh.numberofelements2d
+	
+	#build some variables
+	if md.mesh.dimension==3 and layer==0:
+		rep=6
+		areas=GetAreas(index,md.mesh.x,md.mesh.y,md.mesh.z)
+	elif md.mesh.dimension==2:
+		rep=3
+		areas=GetAreas(index,md.mesh.x,md.mesh.y)
+	else:
+		rep=3
+		areas=GetAreas(index,md.mesh.x2d,md.mesh.y2d)
+
+	index=index-1 # since python indexes starting from zero
+	line=index.flatten(1)
+	areas=npy.vstack(areas).reshape(-1,)
+	summation=1./rep*npy.ones(rep,)
+	linesize=rep*numberofelements
+	
+	#update weights that holds the volume of all the element holding the node i
+	weights=csc_matrix( (npy.tile(areas,(rep,1)).reshape(-1,),(line,npy.zeros(linesize,))), shape=(numberofnodes,1))
+	
+	#initialization
+	if len(data)==numberofelements:
+		average_node=csc_matrix( (npy.tile(areas*data,(rep,1)).reshape(-1,),(line,npy.zeros(linesize,))), shape=(numberofnodes,1))
+		average_node=average_node/weights
+	else:
+		average_node=data
+	
+	#loop over iteration
+	for i in npy.arange(1,iterations+1):
+		average_el=npy.asarray(npy.dot(average_node.todense()[index].reshape(numberofelements,rep),npy.vstack(summation))).reshape(-1,)
+		average_node=csc_matrix( (npy.tile(areas*average_el.reshape(-1),(rep,1)).reshape(-1,),(line,npy.zeros(linesize,))), shape=(numberofnodes,1))
+		average_node=average_node/weights
+	
+	#return output as a full matrix (C code do not like sparse matrices)
+	average=npy.asarray(average_node.todense()).reshape(-1,)
+
+	return average