use absolute path for res_opt

Team25/shape.py

@@ -151,9 +151,9 @@ 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