optlab -> conveks

Lbracket/topo.py

@@ -3,7 +3,7 @@
 #
 
 import numpy as np
-import optlab
+import conveks
 import onelab
 
 c = onelab.client(__file__)
@@ -110,20 +110,20 @@ lowerBound = 0.001*np.ones(numVariables)
 upperBound = np.ones(numVariables)
 
 # Initialize the MMA optimizer
-optlab.mma.initialize(x, lowerBound, upperBound)
+conveks.mma.initialize(x, lowerBound, upperBound)
 
 # Set appropriate options for MMA
-optlab.mma.option.setNumber('General.Verbosity', 4)
-optlab.mma.option.setNumber('General.SaveHistory', 0)
-optlab.mma.option.setNumber('SubProblem.isRobustMoveLimit', 1)
-optlab.mma.option.setNumber('SubProblem.isRobustAsymptotes', 1)
-optlab.mma.option.setNumber('SubProblem.type', 0)
-optlab.mma.option.setNumber('SubProblem.addConvexity', 1)
-optlab.mma.option.setNumber('SubProblem.asymptotesRmax', 100.0)
-optlab.mma.option.setNumber('SubProblem.asymptotesRmin', 0.001)
+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)
 
 # Get iteration count (here it will be 1 - could be different in case of restart)
-it = optlab.mma.getOuterIteration()
+it = conveks.mma.getOuterIteration()
 change = 1.0
 
 while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'stop':
@@ -134,7 +134,7 @@ while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'st
                 attributes={'Highlight':'LightYellow'})
 
     # get (copy of) current point
-    x = np.array(optlab.mma.getCurrentPoint())
+    x = np.array(conveks.mma.getCurrentPoint())
 
     if filtering:
         setElementTable('Optimization/Results/filterInput', elements, x)
@@ -183,10 +183,10 @@ 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
-    optlab.mma.setMoveLimits(lowerBound, upperBound, 0.1)
-    optlab.mma.updateCurrentPoint(constraints, grad_objective, grad_constraints)
-    change = optlab.mma.getDesignChange()
-    it = optlab.mma.getOuterIteration()
+    conveks.mma.setMoveLimits(lowerBound, upperBound, 0.1)
+    conveks.mma.updateCurrentPoint(constraints, grad_objective, grad_constraints)
+    change = conveks.mma.getDesignChange()
+    it = conveks.mma.getOuterIteration()
 
 # This should be called at the end
-optlab.mma.finalize()
+conveks.mma.finalize()

Team25/shape.py

@@ -3,7 +3,7 @@
 #
 
 import numpy as np
-import optlab
+import conveks
 import onelab
 
 c = onelab.client(__file__)
@@ -102,20 +102,20 @@ for label, var in x.iteritems():
   upperBound[label] = var[3]
 
 # Initialize the MMA optimizer
-optlab.mma.initialize(initialPoint, lowerBound, upperBound)
+conveks.mma.initialize(initialPoint, lowerBound, upperBound)
 
 # Set some options for MMA
-optlab.mma.option.setNumber('General.Verbosity', 4)
-optlab.mma.option.setNumber('General.SaveHistory', 0)
-optlab.mma.option.setNumber('SubProblem.isRobustMoveLimit', 1)
-optlab.mma.option.setNumber('SubProblem.isRobustAsymptotes', 1)
-optlab.mma.option.setNumber('SubProblem.type', 0)
-optlab.mma.option.setNumber('SubProblem.addConvexity', 0)
-optlab.mma.option.setNumber('SubProblem.asymptotesRmax', 100.0)
-optlab.mma.option.setNumber('SubProblem.asymptotesRmin', 0.001)
+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', 0)
+conveks.mma.option.setNumber('SubProblem.asymptotesRmax', 100.0)
+conveks.mma.option.setNumber('SubProblem.asymptotesRmin', 0.001)
 
 # Get iteration count (here it will be 1 - could be different in case of restart)
-it = optlab.mma.getOuterIteration()
+it = conveks.mma.getOuterIteration()
 change = 1.0
 
 while it <= maxIter and c.getString('shape/Action') != 'stop':
@@ -124,7 +124,7 @@ while it <= maxIter and c.getString('shape/Action') != 'stop':
                 attributes={'Highlight':'LightYellow'})
 
     # get (copy of) current point
-    xFromMMA = np.array(optlab.mma.getCurrentPoint())
+    xFromMMA = np.array(conveks.mma.getCurrentPoint())
 
     # send the current point to GetDP model
     for label, var in x.iteritems():
@@ -171,10 +171,10 @@ while it <= maxIter and c.getString('shape/Action') != 'stop':
     c.sendInfo('Optimization: it. {}, obj. {}, constr. {}'.format(it,objective,constraints[0]))
 
     # call MMA and update the current point
-    optlab.mma.setMoveLimits(lowerBound, upperBound, 1.0e-4)
-    optlab.mma.updateCurrentPoint(constraints,grad_objective,grad_constraints)
-    change = optlab.mma.getDesignChange()
-    it = optlab.mma.getOuterIteration()
+    conveks.mma.setMoveLimits(lowerBound, upperBound, 1.0e-4)
+    conveks.mma.updateCurrentPoint(constraints,grad_objective,grad_constraints)
+    change = conveks.mma.getDesignChange()
+    it = conveks.mma.getOuterIteration()
 
 # This should be called at the end
-optlab.mma.finalize()
+conveks.mma.finalize()