blas.nrm2(hTemp1[-n::] - matrix(GTemp)[-n::,:] * solSOCP['x'][1::] )
blas.nrm2(hTemp[1::] - GTemp[1::,1::] * sol1['x'] )
# now an socp
print sol1['x']
print sol2['x']
print qpOut['x']
print solSOCP['x'][1::]
## sqp
xhat, output = sqp(rosen,
rosen_der,
x0=theta,
maxiter=100,
method='trust',
disp=5, full_output=True)
xhat, output = sqp(rosen,
rosen_der,
rosen_hess,
x0=theta,
maxiter=100,
method='trust',
disp=5, full_output=True)
xhat, output = sqp(rosen,
rosen_der,
rosen_hess,
x0=theta,
jac=objFH.gradient,
hess=objFH.jtj,
bounds = numpy.array(boxBounds),
method = 'trust-ncg',
options = {'maxiter':1000},
callback=objFH.thetaCallBack)
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)
method='exact',
disp=3, full_output=True)
xhatA, outputA = trustRegion(objFH.cost, objFH.gradient, hessian='SR1',
x0=theta,
maxiter=100,
method='exact',
disp=3, full_output=True)
## sqp
xhat, output = sqp(objFH.cost,
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,
