Skip to content
Snippets Groups Projects
Commit 9944c256 authored by Erin Kuci's avatar Erin Kuci
Browse files

add continuation on mma parameter for constraint relaxation

parent d431fb3c
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
Ccore/onelab_optimize.py
+ 7
− 1
View file @ 9944c256
......@@ -130,7 +130,13 @@ def Optimize(Optimizer):
conveks.mma.initialize(initialPoint, lowerBound, upperBound)
# Set some options for MMA
conveks.mma.option.setNumber('General.Verbosity', 0) # def 4
if Optimizer == 1:
conveks.mma.option.setNumber('General.Verbosity', 0) # def 4
conveks.mma.option.setNumber('SubProblem.isContinuation', 1)
conveks.mma.option.setNumber('SubProblem.cInitial' , 1e2)
conveks.mma.option.setNumber('SubProblem.cFinal' , 1e5)
conveks.mma.option.setNumber('SubProblem.cMultiply' , 10)
conveks.mma.option.setNumber('SubProblem.cIteration', 50)
# Get iteration count (here it will be 1 - could be different in case of restart)
it = conveks.mma.getOuterIteration()
......
Lbracket/topo.pro
+ 5
− 4
View file @ 9944c256
......@@ -9,6 +9,7 @@ DefineConstant [
Optimizer = {0,Choices {0="Conveks - MMA",1="Conveks - GCMMA"},Name "Optimization/00Optimizer"}
Opt_maxIter = {1600, Name "Optimization/01Max iterations"}
Opt_maxChange = {0.01, Name "Optimization/02Max change"}
Opt_isInnerIter = {0, Name "Optimization/03Inner Iteration", Visible 0, Choices {0, 1}}
// Density field parameters
densityFieldInit = {0.5, Name "Optimization/3Density/0Inital value"}
......@@ -624,16 +625,16 @@ PostOperation {
Format Table, StoreInVariable $vonMises_qp_pnorm, File "", Color "LightYellow",
SendToServer StrCat[Opt_ResDir_Onelab,"pnorm of Von-Mises"] ] ;
If(Flag_PrintLevel > 2)
If(Flag_PrintLevel > 2 && !Opt_isInnerIter)
CreateDir[Opt_ResDir];
Print[ vonMises_qp, OnElementsOf Vol_Elast~{iP},
File StrCat[Opt_ResDir,"vm_qp.pos"]];
EndIf
If(Flag_PrintLevel > 4)
If(Flag_PrintLevel > 4 && !Opt_isInnerIter)
Print[ vonMises, OnElementsOf Vol_Elast~{iP},
File StrCat[Opt_ResDir,"vm.pos"]];
EndIf
If(Flag_PrintLevel > 5)
If(Flag_PrintLevel > 5 && !Opt_isInnerIter)
Print[ Young, OnElementsOf Vol_Elast~{iP},
File StrCat[Opt_ResDir, "young.pos"] ];
//Print[ Felast_pressure, OnElementsOf Sur_Force~{iP},
......@@ -762,7 +763,7 @@ Resolution {
InitSolution[LAM];
// Show the density field
If(Flag_PrintLevel > 0)
If(Flag_PrintLevel > 0 && !Opt_isInnerIter)
PostOperation[Get_DensityField];
EndIf
......
Lbracket/topo.py
+ 51
− 14
View file @ 9944c256
......@@ -131,10 +131,18 @@ conveks.initialize()
# Initialize the MMA optimizer
conveks.mma.initialize(x, lowerBound, upperBound)
# Set appropriate options for MMA
conveks.mma.option.setNumber('General.Verbosity', 0)
if Optimizer==0:conveks.mma.option.setNumber('SubProblem.move', 0.1)
# if Optimizer==0:conveks.mma.option.setNumber('SubProblem.move', 0.1)
# conveks.mma.option.setNumber('SubProblem.asymptotesRmax', 10)
# conveks.mma.option.setNumber('SubProblem.asymptotesRmin', 0.01)
# conveks.mma.option.setNumber('SubProblem.adaptSubproblem', 1)
if Optimizer != 1:
conveks.mma.option.setNumber('SubProblem.isContinuation', 1)
conveks.mma.option.setNumber('SubProblem.cInitial' , 1e2)
conveks.mma.option.setNumber('SubProblem.cFinal' , 1e5)
conveks.mma.option.setNumber('SubProblem.cMultiply' , 10)
conveks.mma.option.setNumber('SubProblem.cIteration', 50)
# Get iteration count (here it will be 1 - could be different in case of restart)
it = conveks.mma.getOuterIteration()
......@@ -154,17 +162,28 @@ c.setNumber('Optimization/Results/objective', value=objective)
c.addNumberChoice('Optimization/Results/objective', value=objective)
c.setNumber('Optimization/Results/max(|Constraints|)', value=np.max(np.abs(constraints)))
c.addNumberChoice('Optimization/Results/max(|Constraints|)', value=np.max(np.abs(constraints)))
c.setNumber('Optimization/03Inner Iteration', value=0)
show_inner = 1
# show current iteration
# print 'iter. inner iter. obj. max(constr.) L2-norm(kkt) point'
# print '%3i %3i %2.4e %2.4e %2.4e'%(it-1, innerit, objective, np.max(np.abs(constraints)), kkt_norm),
# print x[0:5]
print 'iter. inner iter. obj. max(constr.) L2-norm(kkt) point'
print '%3i %3i %2.4e %2.4e %2.4e'%(it-1, innerit, objective, np.max(np.abs(constraints)), kkt_norm),
print x[0:5]
print '%3i %3i %.6e %.6e %.6e %3i'%(it-1, innerit, objective, np.max(np.abs(constraints)), kkt_norm, 0),
print '[',
for xk in x[0:5]:
print '%.6e'%(float(xk)),
print ']'
while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'stop':
# Solve MMA
conveks.mma.updateCurrentPoint(objective,grad_objective,constraints,grad_constraints)
# and get the total number of nonlinear loops
nlloops = conveks.mma.countNonlinearIterations()
# Let us check now if the MMA approximation is conservative
# at the new point; and adapt the latter if it is not the case.
if Optimizer == 1:
......@@ -174,29 +193,42 @@ while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'st
conserv = conveks.mma.isConservativeSubProblem(obj_new, c_new)
innerit = 0
print '\t it. new-point (xn) f(xc) f(xn) max(c(xc)) max(c(xn))'
print '\t%3i'%(innerit),
print conveks.mma.getCurrentPoint()[0:5],
print ' %.4e %.4e %.4e %.4e'%(objective,obj_new,np.max(constraints), np.max(c_new))
# print '\t it. new-point (xn) f(xc) f(xn) max(c(xc)) max(c(xn))'
# print '\t%3i'%(innerit),
# print conveks.mma.getCurrentPoint()[0:5],
# print ' %.4e %.4e %.4e %.4e'%(objective,obj_new,np.max(constraints), np.max(c_new))
while innerit <= 15 and conserv==0:
# Do not show fields (density, von-Mises, ...) during inner iterations
c.setNumber('Optimization/03Inner Iteration', value=1)
innerit += 1
# adapt the subproblem to make it conservative and generate a new point
conveks.mma.updateCurrentPoint(objective,grad_objective,
objectiveAtUpdatedPoint=obj_new,constraintsAtUpdatedPoint=c_new)
# and get the total number of nonlinear loops
nlloops = conveks.mma.countNonlinearIterations()
# evaluate the objective and the constraints at the new point
# and check if the subproblem is conservative at this point
obj_new,c_new = get_objective(conveks.mma.getCurrentPoint())
conserv = conveks.mma.isConservativeSubProblem(obj_new, c_new)
# show inner iteration
print '\t%3i'%(innerit),
print conveks.mma.getCurrentPoint()[0:5],
print ' %.4e %.4e %.4e %.4e'%(objective,obj_new,np.max(constraints), np.max(c_new))
# print '\t%3i'%(innerit),
# print conveks.mma.getCurrentPoint()[0:5],
# print ' %.4e %.4e %.4e %.4e %3i'%(objective,obj_new,np.max(constraints), np.max(c_new), nlloops)
if show_inner:
print '%3i %3i '%(it, innerit),
print '%.6e %.6e %.6e %3i'%(obj_new,np.max(np.abs(c_new)), kkt_norm, nlloops),
print '[',
for xk in conveks.mma.getCurrentPoint()[0:5]:
print '%.6e'%(float(xk)),
print ']'
inneritTot += innerit
c.setNumber('Optimization/03Inner Iteration', value=0)
# get (copy of) current point
x = conveks.mma.getCurrentPoint()
......@@ -208,10 +240,15 @@ while change > maxChange and it <= maxIter and c.getString('topo/Action') != 'st
# evaluate the L2-norm of KKT
kkt_norm = conveks.mma.getKKTNorm(constraints,grad_objective,grad_constraints)
# show the current state
print '%3i %3i %2.4e %2.4e %2.4e'%(it, innerit, objective, np.max(np.abs(constraints)), kkt_norm),
print x[0:5]
# print '%3i %3i %2.4e %2.4e %2.4e %4i'%(it, innerit, objective, np.max(np.abs(constraints)), kkt_norm, nlloops),
# print x[0:5]
print '%3i %3i %.6e %.6e %.6e %3i'%(it, innerit, objective, np.max(np.abs(constraints)), kkt_norm, nlloops),
print '[',
for xk in x[0:5]:
print '%.6e'%(float(xk)),
print ']'
# get the outer iteration count here as well as the
# change between two successive points
......
Team25/shape.py
+ 7
− 0
View file @ 9944c256
......@@ -155,6 +155,13 @@ conveks.mma.initialize(initialPoint, lowerBound, upperBound)
# Set some options for MMA
conveks.mma.option.setNumber('General.Verbosity', 0*4)
if Optimizer != 1:
conveks.mma.option.setNumber('General.Verbosity', 0) # def 4
conveks.mma.option.setNumber('SubProblem.isContinuation', 1)
conveks.mma.option.setNumber('SubProblem.cInitial' , 1e2)
conveks.mma.option.setNumber('SubProblem.cFinal' , 1e5)
conveks.mma.option.setNumber('SubProblem.cMultiply' , 10)
conveks.mma.option.setNumber('SubProblem.cIteration', 50)
# Get iteration count (here it will be 1 - could be different in case of restart)
it = conveks.mma.getOuterIteration()
......
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment