Index: ../trunk-jpl/test/NightlyRun/test420.py
===================================================================
--- ../trunk-jpl/test/NightlyRun/test420.py	(nonexistent)
+++ ../trunk-jpl/test/NightlyRun/test420.py	(revision 23257)
@@ -0,0 +1,71 @@
+#Test Name: SquareSheetShelfDakotaScaledResponse
+
+import numpy as np
+from model import *
+from socket import gethostname
+from triangle import *
+from setmask import *
+from parameterize import *
+from setflowequation import *
+from solve import *
+from partitioner import *
+
+md = triangle(model(),'../Exp/Square.exp',200000.)
+md = setmask(md,'../Exp/SquareShelf.exp','')
+md = parameterize(md,'../Par/SquareSheetShelf.py')
+md = setflowequation(md,'SSA','all')
+md.cluster = generic('name',gethostname(),'np',3)
+
+#partitioning
+md.qmu.numberofpartitions = 10
+md = partitioner(md,'package','chaco','npart',md.qmu.numberofpartitions)
+md.qmu.partition = md.qmu.partition-1
+md.qmu.isdakota = 1
+
+#Dakota options
+
+#dakota version
+version = IssmConfig('_DAKOTA_VERSION_')
+version = float(version[0])
+
+#variables
+md.qmu.variables.rho_ice = normal_uncertain.normal_uncertain('MaterialsRhoIce',md.materials.rho_ice,0.01)
+
+#responses
+md.qmu.responses.MaxVel = response_function.response_function('scaled_Thickness',[],[0.0001,0.001,0.01,0.25,0.5,0.75,0.99,0.999,0.9999])
+
+#method
+md.qmu.method = dakota_method.dakota_method('nond_l')
+
+#parameters
+md.qmu.params.direct = True
+md.qmu.params.interval_type = 'forward'
+
+if version >= 6:
+	md.qmu.params.analysis_driver = 'matlab'
+	md.qmu.params.evaluation_scheduling = 'master'
+	md.qmu.params.processors_per_evaluation = 2
+else:
+	md.qmu.params.analysis_driver = 'stressbalance'
+	md.qmu.params.evaluation_concurrency = 1
+
+#imperative! 
+md.stressbalance.reltol = 10**-5 #tighten for qmu analysese
+
+#solve
+md.verbose = verbose('000000000')	# this line is recommended
+md = solve(md,'Stressbalance','overwrite','y')
+md.qmu.results = md.results.dakota
+
+#test on thickness
+h = np.zeros((md.qmu.numberofpartitions,))
+for i in range(md.qmu.numberofpartitions):
+	h[i] = md.qmu.results.dresp_out[i].mean
+
+#project onto grid
+thickness = h[(md.qmu.partition).flatten()]
+
+#Fields and tolerances to track changes
+field_names      = ['Thickness']
+field_tolerances = [1e-10]
+field_values     = [thickness]