user = os.path.expanduser("~")

tempOut = robj.r("rm(list=ls())")

tempOut = robj.r("i <- %i"%(i+1))

tempOut = robj.r("b <- %i"%(i*(1000)+(b+1) ))

tempOut = robj.r("source('CMLE_unstable_support.r')")

regrMat = np.array((robj.r("do.call(cbind, regr)")))

regr = OrderedDict([('SA',np.ones((regrMat.shape[0],0))),('VA',regrMat[:,0:1]),('CB',np.ones((regrMat.shape[0],0))),('barWA',regrMat[:,1:2]),('barWB',regrMat[:,2:4]),('bara',regrMat[:,4:5]),('VB',regrMat[:,5:6])])

Y = np.array((robj.r("Y")))

x0 = np.array((robj.r("unname(x0)")))

xL = np.array((robj.r("unname(xL)")))

tPL = np.array((robj.r("unname(out.2step$time )")))

def fll(x):

return LL_jo(x, Y, regr)

def heq(x):

return const_cmle(x, Y, regr)

np.random.seed(b)

while np.isinf(fll(adouble(x0)).val):

x0 = np.random.uniform(size=len(x0))

ccd = os.getcwd()

if not os.path.exists(user + '/Documents/adolc%i_%i'%(i, b)):

os.makedirs(user + '/Documents/adolc%i_%i'%(i, b))

os.chdir(user + '/Documents/adolc%i_%i'%(i, b))

adolc.trace_on(1)

ax = adolc.adouble(np.zeros(len(x0)))

adolc.independent(ax)

ay = fll(ax)

adolc.dependent(ay)

adolc.trace_off()

# trace constraint function

adolc.trace_on(2)

ax = adolc.adouble(x0)

adolc.independent(ax)

ay = heq(ax)

adolc.dependent(ay)

adolc.trace_off()

npar = len(x0)

def adFun(x):

return adolc.function(1, x)

def grFun(x):

return adolc.gradient(1, x)

def const_adolc(x):

return adolc.function(2,x)

def jac_adolc(x):

return adolc.jacobian(2,x)

def lagrangian(x, lagrange, obj_factor):

return obj_factor*fll(x) + np.dot(lagrange, heq(x))

#Jacobian

#### initalize it

class jac_c_adolc:

def __init__(self, x):

options = None

result = adolc.colpack.sparse_jac_no_repeat(2,x,options)

self.nnz = result[0]

self.rind = np.asarray(result[1],dtype=int)

self.cind = np.asarray(result[2],dtype=int)

self.values = np.asarray(result[3],dtype=float)

def __call__(self, x, flag, user_data=None):

if flag:

return (self.rind, self.cind)

else:

result = adolc.colpack.sparse_jac_repeat(2, x, self.nnz, self.rind,

self.cind, self.values)

return result[3]

##### create the function

Jac_c_adolc = jac_c_adolc(x0)

###Hessian

# trace lagrangian function

adolc.trace_on(3)

ax = adolc.adouble(x0)

adolc.independent(ax)

ay = lagrangian(ax, xL, np.array([1.0]))

adolc.dependent(ay)

adolc.trace_off()

M = Y.shape[1]

nreal = npar-M

given = {'rind': np.concatenate((np.kron(np.arange(nreal), np.ones(npar,dtype='int')), np.arange(nreal, npar))),

'cind': np.concatenate((np.tile(np.arange(npar), nreal), np.arange(nreal, npar)))}

mask = np.where(given['rind'] <= given['cind'])

given['rind'] = given['rind'][mask]

given['cind'] = given['cind'][mask]

def hessLag_adolc(x, lagrange, obj_factor, flag, user_data=None):

if flag:

result = (given['rind'], given['cind'])

else:

result = np.ravel(adolc.hessian(3, x)[given['rind'],given['cind']], order="C")

return result

H2 = hessLag_adolc(x0, xL, 1.0, False)

H2a = hessLag_adolc(x0, xL, 1.0, True)

nnzh = len(given['rind'])

##Optimization

#PRELIMS: other things to pass to IPOPT

nvar = len(x0) #number of variables in the problem

x_L = np.array([-np.inf]*nvar, dtype=float) #box contraints on variables (none)

x_U = np.array([np.inf]*nvar, dtype=float)

#PRELIMS:define the (in)equality constraints

ncon = heq(ax).shape[0] #number of constraints

g_L = np.array([0]*ncon, dtype=float) #constraints are to equal 0

g_U = np.array([0]*ncon, dtype=float) #constraints are to equal 0

#PRELIMS: define the number of nonzeros in the jacobian

val = Jac_c_adolc(x0, False)

nnzj = len(val)

# create the nonlinear programming model

nlp2 = pyipopt.create(

nvar,

x_L,

x_U,

ncon,

g_L,

g_U,

nnzj,

nnzh,

adFun,

grFun,

const_adolc,

Jac_c_adolc,

hessLag_adolc

)

nlp2.num_option('expect_infeasible_problem_ctol', 1e-15)

nlp2.int_option('max_iter', 100)

nlp2.num_option('dual_inf_tol', 1e-3)

nlp2.num_option('constr_viol_tol', 1e-3)

nlp2.num_option('tol', 1e-6)

nlp2.int_option('print_level', 0)

t1 = time()

out = nlp2.solve(x0)

t1 = time()-t1

t1 = t1 + tPL

# free the model

nlp2.close()

os.chdir(ccd)

shutil.rmtree(user + '/Documents/adolc%i_%i'%(i, b))

output = np.concatenate((out[0][:6], t1, np.array([out[5]])))