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)