Changeset 22865

Timestamp:

06/22/18 01:03:19 (7 years ago)

Author:

bdef

Message:

BUG: random fixes in nightlies

Location:

issm/trunk-jpl/src/m

Files:

• consistency/checkfield.py (modified) (6 diffs)
• mesh/ComputeHessian.py (modified) (1 diff)
• miscellaneous/MatlabFuncs.py (modified) (1 diff)

issm/trunk-jpl/src/m/consistency/checkfield.py

@@ -9 +9 @@
 
            Used to check model consistency.,
-           Requires: 
-           'field' or 'fieldname' option. If 'fieldname' is provided, it will retrieve it from the model md. (md.(fieldname)) 
+           Requires:
+           'field' or 'fieldname' option. If 'fieldname' is provided, it will retrieve it from the model md. (md.(fieldname))
              If 'field' is provided, it will assume the argument following 'field' is a numeric array.
 
@@ -40 +40 @@
                 fieldname=options.getfieldvalue('fieldname','no fieldname')
         else:
-                fieldname=options.getfieldvalue('fieldname') 
+                fieldname=options.getfieldvalue('fieldname')
                 exec("field=md.{}".format(fieldname))
 
@@ -80 +80 @@
                                 if (not np.size(field,0)==fieldsize[0]) or (not np.size(field,1)==fieldsize[1]):
                                         md = md.checkmessage(options.getfieldvalue('message',"field '%s' size should be %d x %d" % (fieldname,fieldsize[0],fieldsize[1])))
-        
+
         #Check numel
         if options.exist('numel'):
@@ -164 +164 @@
 
                 if options.getfieldvalue('singletimeseries',0):
-                        field2 = np.reshape(field[0],np.prod(np.shape(field[0])),1)
+                        field2 = np.reshape(field[0],int(np.prod(np.shape(field[0]))),1)
 
                 if np.any(field2>upperbound):
@@ -176 +176 @@
 
                 if options.getfieldvalue('singletimeseries',0):
-                        field2 = np.reshape(field[0],np.prod(np.shape(field[0])),1)
+                        field2 = np.reshape(field[0],int(np.prod(np.shape(field[0]))),1)
 
                 if np.any(field2>=upperbound):
@@ -228 +228 @@
 
         return md
-
-

issm/trunk-jpl/src/m/mesh/ComputeHessian.py

@@ -33 +33 @@
         linesize=3*numberofelements
 
-        #get areas and nodal functions coefficients N(x,y)=alpha x + beta y + gamma 
+        #get areas and nodal functions coefficients N(x,y)=alpha x + beta y + gamma
         [alpha,beta,dum]=GetNodalFunctionsCoeff(index,x,y)
         areas=GetAreas(index,x,y)
 
         #compute weights that hold the volume of all the element holding the node i
-        weights=m.sparse(line,np.ones((linesize,1)),np.tile(areas.reshape(-1,),(3,1)),numberofnodes,1)
+        weights=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile(areas,(3,1)),numberofnodes,1)
 
         #compute field on nodes if on elements
         if np.size(field,axis=0)==numberofelements:
-                field=m.sparse(line,np.ones((linesize,1)),np.tile(areas*field,(3,1)),numberofnodes,1)/weights
+                field=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile(areas*field,(3,1)),numberofnodes,1)/weights
 
         #Compute gradient for each element
-        grad_elx=np.sum(field[index-1,0]*alpha,axis=1) 
-        grad_ely=np.sum(field[index-1,0]*beta,axis=1)
+        grad_elx=np.sum(field[index-1]*alpha,axis=1)
+        grad_ely=np.sum(field[index-1]*beta,axis=1)
 
         #Compute gradient for each node (average of the elements around)
-        gradx=m.sparse(line,np.ones((linesize,1)),np.tile((areas*grad_elx).reshape(-1,),(3,1)),numberofnodes,1)
-        grady=m.sparse(line,np.ones((linesize,1)),np.tile((areas*grad_ely).reshape(-1,),(3,1)),numberofnodes,1)
+        gradx=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*grad_elx),(3,1)),numberofnodes,1)
+        grady=m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*grad_ely),(3,1)),numberofnodes,1)
         gradx=gradx/weights
         grady=grady/weights
 
         #Compute hessian for each element
-        hessian=np.vstack((np.sum(gradx[index-1,0]*alpha,axis=1).reshape(-1,),np.sum(grady[index-1,0]*alpha,axis=1).reshape(-1,),np.sum(grady[index-1,0]*beta,axis=1).reshape(-1,))).T
+        hessian=np.vstack((np.sum(gradx[index-1,0]*alpha,axis=1),np.sum(grady[index-1,0]*alpha,axis=1),np.sum(grady[index-1,0]*beta,axis=1))).T
 
         if m.strcmpi(type,'node'):
                 #Compute Hessian on the nodes (average of the elements around)
-                hessian=np.hstack((m.sparse(line,np.ones((linesize,1)),np.tile((areas*hessian[:,0]).reshape(-1,),(3,1)),numberofnodes,1)/weights,
-                                                                                         m.sparse(line,np.ones((linesize,1)),np.tile((areas*hessian[:,1]).reshape(-1,),(3,1)),numberofnodes,1)/weights,
-                                                                                         m.sparse(line,np.ones((linesize,1)),np.tile((areas*hessian[:,2]).reshape(-1,),(3,1)),numberofnodes,1)/weights ))
+                hessian=np.hstack((m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*hessian[:,0]),(3,1)),numberofnodes,1)/weights,
+                                                                                         m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*hessian[:,1]),(3,1)),numberofnodes,1)/weights,
+                                                                                         m.sparse(line,np.ones((linesize,1),dtype=int),np.tile((areas*hessian[:,2]),(3,1)),numberofnodes,1)/weights ))
 
         return hessian
-

issm/trunk-jpl/src/m/miscellaneous/MatlabFuncs.py

@@ -105 +105 @@
 
         return y
-