Index: /issm/trunk-jpl/src/m/classes/stochasticforcing.py
===================================================================
--- /issm/trunk-jpl/src/m/classes/stochasticforcing.py	(revision 26668)
+++ /issm/trunk-jpl/src/m/classes/stochasticforcing.py	(revision 26669)
@@ -108,5 +108,5 @@
         if (checkdefaults):
             md = checkfield(md, 'fieldname', 'stochasticforcing.defaultdimension', 'numel', 1, 'NaN', 1, 'Inf', 1, '>', 0)
-            md = checkfield(md, 'fieldname', 'stochasticforcing.default_id', 'Inf', 1, '>=', 0, '<=', self.defaultdimension, 'size', [md.mesh.numberofelements, 1])
+            md = checkfield(md, 'fieldname', 'stochasticforcing.default_id', 'Inf', 1, '>=', 0, '<=', self.defaultdimension, 'size', [md.mesh.numberofelements])
         return md
     # }}}
Index: /issm/trunk-jpl/test/NightlyRun/test543.py
===================================================================
--- /issm/trunk-jpl/test/NightlyRun/test543.py	(revision 26668)
+++ /issm/trunk-jpl/test/NightlyRun/test543.py	(revision 26669)
@@ -27,5 +27,5 @@
         if md.mesh.elements[ii][vertex] - 1 in iid1:  # one vertex in basin 1; NOTE: offset because of 1-based vertex indexing
             idb_tf[ii] = 1
-    if idbasin[ii] == 0:  # no vertex was found in basin 1
+    if idb_tf[ii] == 0:  # no vertex was found in basin 1
         for vertex in range(3):
             idb_tf[ii] = 2
@@ -37,5 +37,5 @@
         if md.mesh.elements[ii][vertex] - 1 in iid1:  # one vertex in basin 1; NOTE: offset because of 1-based vertex indexing
             idb_df[ii] = 1
-    if idbasin[ii] == 0:  # no vertex was found in basin 1
+    if idb_df[ii] == 0:  # no vertex was found in basin 1
         for vertex in range(3):
             idb_df[ii] = 2
@@ -69,11 +69,9 @@
 covclv[0,0]      = 1/10*covclv[0,0]
 covflmlt         = 0.05*np.identity(nb_flmlt)
-#covglob          = np.zeros([6,6])
-#covglob[0:2,0:2] = covtf
-#covglob[2:4,2:4] = covclv
-#covglob[4:6,4:6] = covflmlt
+covglob          = np.zeros([6,6])
+covglob[0:2,0:2] = covtf
+covglob[2:4,2:4] = covclv
+covglob[4:6,4:6] = covflmlt
 
-#Hard-coding covariance matrix because python is complaining
-covglob = np.array([[1e-4,0.,0.,0.,0.,0.],[0.,1e-4,0.,0.,0.,0.],[0.,0.,1e-2,0.,0.,0.],[0.,0.,0.,1e-1,0.,0.],[0.,0.,0.,0.,0.05,0.],[0.,0.,0.,0.,0.,0.05]])
 testchol = np.linalg.cholesky(covglob)
 print(testchol)
@@ -82,8 +80,8 @@
 md.stochasticforcing.isstochasticforcing = 1
 md.stochasticforcing.fields = ['FrontalForcingsRignotAutoregression','DefaultCalving','FloatingMeltRate']
-md.stochasticforcing.defauldimension = 2
-md.stochasticforcing.default_id      = idb_df
-md.stochasticforcing.covariance      = covglob # global covariance among- and between-fields
-md.stochasticforcing.randomflag      = 0 # determines true/false randomness
+md.stochasticforcing.defaultdimension = 2
+md.stochasticforcing.default_id       = idb_df-1 #NOTE: offset because of 1-based vertex indexing
+md.stochasticforcing.covariance       = covglob # global covariance among- and between-fields
+md.stochasticforcing.randomflag       = 0 # determines true/false randomness
 
 md.transient.ismovingfront   = 1