some cleaning

Lbracket/topo.py

@@ -3,8 +3,8 @@
 #
 
 import numpy as np
-import conveks
 import onelab
+import conveks
 
 c = onelab.client(__file__)
 
@@ -92,13 +92,7 @@ conveks.mma.initialize(x, lowerBound, upperBound)
 
 # Set appropriate options for MMA
 conveks.mma.option.setNumber('General.Verbosity', 4)
-conveks.mma.option.setNumber('General.SaveHistory', 0)
-conveks.mma.option.setNumber('SubProblem.isRobustMoveLimit', 1)
-conveks.mma.option.setNumber('SubProblem.isRobustAsymptotes', 1)
-conveks.mma.option.setNumber('SubProblem.type', 0)
-conveks.mma.option.setNumber('SubProblem.addConvexity', 1)
-conveks.mma.option.setNumber('SubProblem.asymptotesRmax', 100.0)
-conveks.mma.option.setNumber('SubProblem.asymptotesRmin', 0.001)
+conveks.mma.option.setNumber('SubProblem.move', 0.1)
 
 # Get iteration count (here it will be 1 - could be different in case of restart)
 it = conveks.mma.getOuterIteration()
@@ -112,7 +106,7 @@ while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'st
                 attributes={'Highlight':'LightYellow'})
 
     # get (copy of) current point
-    x = np.array(conveks.mma.getCurrentPoint())
+    x = conveks.mma.getCurrentPoint()
 
     if filtering:
         setElementTable('Optimization/Results/filterInput', elements, x)
@@ -160,7 +154,7 @@ while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'st
     c.sendInfo('Optimization: it. {}, obj. {}, constr. {}, change {}'.format(it,objective,constraints[0], change))
 
     # call MMA and update the current point
-    conveks.mma.setMoveLimits(lowerBound, upperBound, 0.1)
+    #conveks.mma.setMoveLimits(lowerBound, upperBound, 0.1)
     conveks.mma.updateCurrentPoint(constraints, grad_objective, grad_constraints)
     change = conveks.mma.getDesignChange()
     it = conveks.mma.getOuterIteration()