rosen_der, x0=theta, lb=lb, ub=ub, G=None, h=None, A=A, b=b, method='trust', disp=3, full_output=True) ## interior point interface xhat, output = ip(rosen, rosen_der, x0=theta, lb=None, ub=None, G=None, h=None, A=None, b=None, maxiter=50, method='pdc', disp=5, full_output=True) xhat, output = ip(rosen, rosen_der, x0=theta, lb=lb, ub=ub, G=None, h=None, A=None, b=None, maxiter=500, method='pdc', disp=5, full_output=True)
from pygotools.convex import sqp, ip boxBoundsArray = numpy.array(boxBounds) lb = numpy.array([0.0,0.0,0.0]) ub = numpy.array([5.0,5.0,5.0]) xhat,qpOut = sqp(objFH.cost, objFH.gradient, hessian=objFH.jtj, x0=[0.5,0.5,0.5], lb=lb, ub=ub,disp=3,full_output=True) xhat,qpOut = sqp(objFH.cost, objFH.gradient, hessian=None, x0=[0.5,0.5,0.5], lb=lb, ub=ub,disp=3,full_output=True) xhat,output = ip(objFH.cost, objFH.gradient, hessian=objFH.jtj, x0=[0.5,0.5,0.5], lb=lb, ub=ub, method='bar', disp=3, full_output=True) xhat,output = ip(objFH.cost, objFH.gradient, hessian=None, x0=[0.5,0.5,0.5], lb=lb, ub=ub,disp=3,full_output=True) xhat,output = ipD(objFH.cost, objFH.gradient, hessian=objFH.jtj, x0=[0.5,0.5,0.5], lb=lb, ub=ub,disp=3,full_output=True) xhat,output = ipD(objFH.cost, objFH.gradient, hessian=None, x0=[0.5,0.5,0.5], lb=lb, ub=ub,disp=3,full_output=True) from pygotools.optutils.consMani import addLBUBToInequality G,h = addLBUBToInequality(lb,ub) G = matrix(G) h = matrix(h) z = qpOut['z']
objFH.gradient, x0=theta, disp=4, full_output=True) xhat, output = sqp(objFH.cost, objFH.gradient, x0=theta, lb=lb, ub=ub, disp=4, full_output=True) ## interior point interface xhat, output = ip(objFH.cost, objFH.gradient, x0=theta, lb=None, ub=None, G=None, h=None, A=None, b=None, method='bar', disp=3, full_output=True) xhat, output = ip(objFH.cost, objFH.gradient, x0=theta, lb=lb, ub=ub, G=None, h=None, A=None, b=None, maxiter=200, method='bar', disp=3, full_output=True)