use absolute path for res_opt

Team25/shape.py

@@ -139,7 +139,7 @@ while it <= maxIter and c.getString('shape/Action') != 'stop':
     # generate the velocity field of each design variable
     getVelocityField(x)
 
-    # compute objective function and constraints 
+    # compute objective function and constraints
     c.runSubClient('myGetDP', mygetdp + '-solve GetPerformances')
 
     # as well as their sensitivity with respect to design variables at `x'
@@ -151,11 +151,11 @@ while it <= maxIter and c.getString('shape/Action') != 'stop':
 
     # get the value of the objective function and of the constraints
     # as well as their sensitivity with respect to design variables at `x'
-    objective = np.sum(readSimpleTable('res_opt/w.txt'))
+    objective = np.sum(readSimpleTable(c.getPath('res_opt/w.txt')))
     constraints = np.array([np.sum(xFromMMA)/100.0-1.0])
-    grad_objective = np.asarray([np.sum(readSimpleTable('res_opt/Grad_w_wrt_dv_'+str(dv)+'.txt'))\
+    grad_objective = np.asarray([np.sum(readSimpleTable(c.getPath('res_opt/Grad_w_wrt_dv_'+str(dv)+'.txt')))\
         for dv in xrange(numVariables)])
-    grad_constraints = np.ones(numVariables)/100.0	     
+    grad_constraints = np.ones(numVariables)/100.0
 
     if it == 1: fscale = 1.0 / objective
     objective *= fscale