ub,
iteration=50,
numBox=1000,
targetMin=0,
scaleOutput=False,
full_output=True)
index = directUtil.findLowestObjIndex(rectListOptim)
rectListOptim[index].getFx()
rectListOptim[index].getLocation()
pyOptimUtil.direct.plotDirectBox(rectListOptim, lb, ub, scaleOutput=False)
# class object
directObj = directAlg.direct(optimTestFun.rosen, lb, ub)
rectListOptim, output = directObj.divide(50, numBox=10000, full_output=True)
potentialIndex = directUtil.identifyPotentialOptimalObjectPareto(rectListOptim)
pyOptimUtil.direct.directUtil.plotParetoFrontRect(rectListOptim,
potentialIndex)
pyOptimUtil.direct.plotDirectBox(rectListOptim, lb, ub, scaleOutput=False)
# in terms of inequalities
A, b = polyOperation.addBoxToInequalityLBUB(lb, ub)
directObj = directAlg.direct(optimTestFun.gp, lb, ub, A, b)
polyListOptim, output = directObj.divide(10, numBox=2000, full_output=True)
potentialIndex = polyOperation.identifyPotentialOptimalPolygonPareto(
polyListOptim)
pyOptimUtil.direct.plotDirectPolygon(newPolyList, potentialIndex)
x, sol, G, h = polyOperation.findAnalyticCenter(A, b, full_output=True)
import pyOptimUtil.direct
rectListOptim, output = directAlg.directOptim(
optimTestFun.rosen, lb, ub, iteration=50, numBox=1000, targetMin=0, scaleOutput=False, full_output=True
)
pyOptimUtil.direct.plotDirectBox(rectListOptim, lb, ub, scaleOutput=False)
# class object
directObj = directAlg.direct(optimTestFun.rosen, lb, ub)
rectListOptim = directObj.divide(10)
directObj = directAlg.direct(optimTestFun.rosen, lb, ub, A, b)
polyListOptim = directObj.divide(5)
potentialIndex = polyOperation.identifyPotentialOptimalPolygonPareto(polyListOptim)
pyOptimUtil.direct.plotDirectPolygon(polyListOptim, potentialIndex)
polyListOptim = directObj.divide(1)
potentialIndex = polyOperation.identifyPotentialOptimalPolygonPareto(polyListOptim)
pyOptimUtil.direct.plotDirectPolygon(polyListOptim, potentialIndex)
import pyOptimUtil.direct
rectListOptim, output = directAlg.directOptim(optimTestFun.rosen,
lb,
ub,
iteration=50,
numBox=1000,
targetMin=0,
scaleOutput=False,
full_output=True)
pyOptimUtil.direct.plotDirectBox(rectListOptim, lb, ub, scaleOutput=False)
# class object
directObj = directAlg.direct(optimTestFun.rosen, lb, ub)
rectListOptim = directObj.divide(10)
directObj = directAlg.direct(optimTestFun.rosen, lb, ub, A, b)
polyListOptim = directObj.divide(5)
potentialIndex = polyOperation.identifyPotentialOptimalPolygonPareto(
polyListOptim)
pyOptimUtil.direct.plotDirectPolygon(polyListOptim, potentialIndex)
polyListOptim = directObj.divide(1)
potentialIndex = polyOperation.identifyPotentialOptimalPolygonPareto(
polyListOptim)
pyOptimUtil.direct.plotDirectPolygon(polyListOptim, potentialIndex)
rectListOptim,output = directAlg.directOptim(optimTestFun.rosen,lb,ub,
iteration=50,
numBox=1000,
targetMin=0,
scaleOutput=False,
full_output=True)
index = directUtil.findLowestObjIndex(rectListOptim)
rectListOptim[index].getFx()
rectListOptim[index].getLocation()
pyOptimUtil.direct.plotDirectBox(rectListOptim,lb,ub,scaleOutput=False)
# class object
directObj = directAlg.direct(optimTestFun.rosen,lb,ub)
rectListOptim,output = directObj.divide(50,numBox=10000,full_output=True)
potentialIndex = directUtil.identifyPotentialOptimalObjectPareto(rectListOptim)
pyOptimUtil.direct.directUtil.plotParetoFrontRect(rectListOptim,potentialIndex)
pyOptimUtil.direct.plotDirectBox(rectListOptim,lb,ub,scaleOutput=False)
# in terms of inequalities
A,b = polyOperation.addBoxToInequalityLBUB(lb,ub)
directObj = directAlg.direct(optimTestFun.gp,lb,ub,A,b)
polyListOptim,output = directObj.divide(10,numBox=2000,full_output=True)
potentialIndex = polyOperation.identifyPotentialOptimalPolygonPareto(polyListOptim)
