def setUp(self):
self.A = array([[ 1, 0, -1], [ 0, 1, 0], [ 1, 0, 1]])
self.B = array([[1e12,0],[0,1e-8]])
self.dummyOptions = helper.dummyOptions()
self.dummyOptions.verbose=0;
self.abs_tol=1e-15;
self.rel_tol=1e-15;
def setUp(self):
self.options = helper.dummyOptions()
self.options.verbose = 2
#self.values = helper.dummyValues()
self.abs_tol=1e-14
self.rel_tol=1e-14
pass
def setUp(self):
set_check_condition(0)
self.x = array([[0.5, 1.0, 0.5]]).T
self.lb = array([])
self.ub = array([])
self.values = helper.dummyValues()
self.options = helper.dummyOptions()
self.info = dummyInfo()
self.abs_tol=1e-8;
self.rel_tol=1e-8;
def setUp(self):
self.options = helper.dummyOptions()
self.info = dummyInfo()
self.x = array(
[[0.500000000000000, 1.000000000000000, 0.500000000000000]]).T
self.lm = array([[0, 0, 0, -0.333333332763891, -0.000000000249999]]).T
#print "lm", self.lm
self.lb = array([[-0.500000000000000, 0, -np.Inf]]).T
self.ub = array([[np.Inf, np.Inf, np.Inf]]).T
def setUp(self):
self.M = array(np.eye(3))
self.y = array([[-0.009783923878659, -0.0, 0.0]]).T
self.s = array([[-0.503054026564966, -1.0, -0.184478531874161]]).T
self.first = 1
self.info = dummyInfo()
self.options = helper.dummyOptions()
# set hessian approximation to bfgs
self.options.hess_approx = 130
self.values = helper.dummyValues()
def setUp(self):
self.info = dummyInfo()
self.old_delta = 1
self.norms = 0
self.pc = 0
self.itype = None
self.options = helper.dummyOptions()
self.nb = 2
self.mi = 0
self.values = helper.dummyValues()
self.constrained_pbl = 2
self.merit = 5.105551275463990
def setUp(self):
self.X = array([[0, 1, 0], [0, 0, 1]])
self.fX = array([1, 100, 101])
self.y = array([[2, 4]]).T
self.ciX = copy(self.X)
self.ceX = copy(self.X)
self.info = dummyInfo()
self.options = helper.dummyOptions()
self.values = helper.dummyValues()
self.abs_tol = 1e-15
self.rel_tol = 1e-15
def test_sqpdfo_check_convex3(self):
"""
With a non symmetric matrix non convex
"""
C = array([[1,2,3],[4,5,6],[7,8,9]])
res = sqpdfo_check_convex_(C, helper.dummyOptions())
self.assertFalse(compare_array(C, res, self.abs_tol, self.rel_tol))
self.assertTrue(compare_array(res, res.T, self.abs_tol, self.rel_tol))
correctres=array([[0.000000000925233, 0.000000001000001, 1.88302358e+01]])
self.assertTrue(compare_array(correctres, np.sort(eig_(res)), 1e-8, 1e-8))
def setUp(self):
self.simul = sqpdfo_evalfgh_
self.x = array([[-0.003054026564966, 0, 0.315521468125839]]).T
self.null_step = 0
self.constrained_pbl = 2
self.lm = array(
[[0, -0.999999999499998, 0, -0.000000000375002,
0.000000000083334]]).T
self.M = array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
self.n = 3
self.me = 2
self.mi = 0
self.s = array(
[[-0.503054026564966, -1.000000000000000, -0.184478531874161]]).T
self.gx = array([[-0.009783923878659, 1.000000000000000, 0]]).T
self.gci = array([])
self.gce = array(
[[1.000000000000000, 0.999999999999999, 1.000000000000000],
[1.000000000000000, 1.999999999999999, 3.000000000000000]])
self.info = dummyInfo()
self.options = helper.dummyOptions()
self.values = helper.dummyValues()
self.fcmodel = array([[
0.099563123926544, -0.013550429460611, 1.384968815034240, 0,
6.144976749236061
],
[
0.312467441560872, 1.384968815034241,
1.384968815034240, 1.384968815034241,
0.000000000000006
],
[
-0.056489622187450, 1.384968815034241,
2.769937630068480, 4.154906445102721,
0.000000000000014
]])
self.Y = array([[
-0.003054026564966, -0.500000000000000, 0.500000000000000,
0.500000000000000, 0.500000000000000
], [0, 1.000000000000000, 0, 1.000000000000000, 1.000000000000000],
[
0.315521468125839, 0.500000000000000,
0.500000000000000, -0.500000000000000,
0.500000000000000
]])
self.fY = array([
0.099563123926544, 1.500000000000000, 0.500000000000000,
1.500000000000000, 1.500000000000000
])
self.ciY = array([])
self.ceY = array([[
0.312467441560872, 1.000000000000000, 1.000000000000000,
1.000000000000000, 2.000000000000000
],
[
-0.056489622187450, 2.000000000000000,
1.000000000000000, 0, 3.000000000000000
]])
self.sigma = 1
self.scale = array([[
1.000000000000000, 0.722037918214987, 0.722037918214987,
0.722037918214987, 0.521338755340232
]]).T
self.shift_Y = 1
self.QZ = array([[1.000000000000000, 0, 0, 0, 0],
[
0, -0.437717028004984, -0.826365739060244,
0.329535025867438, -0.130115853870500
],
[
0, 0.880814115424577, -0.315023389192614,
0.329471408091712, -0.127966204837389
],
[
0, 0.162491294867564, -0.418566952172131,
-0.884320607054428, -0.127966204837389
],
[
0, 0.078529462977709, -0.206595343893201,
-0.028849989870035, 0.974843149132506
]])
self.RZ = array([[
1.000000000000000, 1.000000000000000, 1.000000000000000,
1.000000000000000, 1.000000000000000
],
[
0, 0.819739267991799, -0.132165180682231,
0.386491133279071, 0.503816009553305
],
[
0, 0, -0.369537503265736, -0.294775124607443,
-0.596996335387400
], [0, 0, 0, 0.876403859762092, 0.237890849609900],
[0, 0, 0, 0, -0.092396452142661]])
self.whichmodel = 0
self.ind_Y = array([4, 1, 2, 3, 0])
self.i_xbest = 4
self.m = 4
self.abs_tol = 1e-14
self.rel_tol = 1e-14
def setUp(self):
self.options = helper.dummyOptions()
self.values = helper.dummyValues()
pass
def setUp(self):
set_threshold(1.000000000000000e-08)
set_test_prob(3)
set_fileoutput(1)
set_simul_not_initialized(1)
set_check_condition(0)
self.func = sqpdfo_evalfgh_
self.n = 3
self.nb = 2
self.mi = 0
self.me = 2
self.lm = array([[0.0], [0.0], [0.0], [-0.333333332763891],
[-0.000000000249999]])
self.nitold = 0
self.nit = 0
self.i_xbest = 0
self.lb = array([[-0.500000000000000], [0.0], [-np.Inf]])
self.ub = array([[np.Inf], [np.Inf], [np.Inf]])
self.m = 3
self.X = array([[
0.500000000000000, -0.500000000000000, 0.500000000000000,
0.500000000000000
], [1.000000000000000, 1.000000000000000, 0.0, 1.000000000000000],
[
0.500000000000000, 0.500000000000000,
0.500000000000000, -0.500000000000000
]])
self.fX = array([
1.500000000000000, 1.500000000000000, 0.500000000000000,
1.500000000000000
])
self.ciX = array([])
self.ceX = array([[2.0, 1.0, 1.0, 1.0], [3.0, 2.0, 1.0, 0.0]])
self.ind_Y = array([0, 1, 2, 3])
self.QZ = array([[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]])
self.RZ = array([[1.0, 1.0, 1.0, 1.0], [0.0, -1.0, 0.0, 0.0],
[0.0, 0.0, -1.0, 0.0], [0.0, 0.0, 0.0, -1.0]])
self.delta = 1
self.cur_degree = 4
self.neval = 0
self.maxeval = 600
self.maxit = 600
self.fcmodel = array([[1.500000000000000, 0.0, 1.000000000000000, 0.0],
[
2.000000000000000, 1.000000000000000,
1.000000000000000, 1.000000000000000
],
[
3.000000000000000, 1.000000000000000,
2.000000000000000, 3.000000000000000
]])
self.gx = array([[0.0], [1.0], [0.0]])
self.normgx = 1.0
self.show_errg = 0
self.pquad = 10
self.pdiag = 7
self.plin = 4
self.stallfact = 2.220446049250313e-15
self.eps_rho = 1.000000000000000e-14
self.Deltamax = 100000.0
self.rep_degree = 4
self.epsilon = 1.000000000000000e-05
self.verbose = 2
self.eta1 = 1.000000000000000e-04
self.eta2 = 0.900000000000000
self.gamma1 = 0.010000000000000
self.gamma2 = 0.500000000000000
self.gamma3 = 2.0
self.interpol_TR = 1
self.factor_CV = 100
self.Lambda_XN = 1.000000000000000e-10
self.Lambda_CP = 1.200000000000000
self.factor_FPU = 1.0
self.factor_FPR = 10.0
self.Lambda_FP = 1.000000000000000e-10
self.criterion_S = 'distance'
self.criterion_FP = 'distance'
self.criterion_CP = 'standard'
self.mu = 0.0
self.theta = 1.0
self.eps_TR = 1.000000000000000e-04
self.eps_L = 1.000000000000000e-03
self.lSolver = 1
self.stratLam = 1
self.eps_current = 1.000000000000000e-05
self.vstatus = array([[0], [0], [0]])
self.xstatus = array([[1], [1], [1], [1]])
self.sstatus = array([[1], [1], [1], [1]])
self.dstatus = array([[0], [0], [0], [0]])
self.ndummyY = 0
self.sspace_save = array([])
self.xspace_save = array([])
self.xfix = array([[0], [0], [0]])
self.fxmax = 1.000000000000000e+25
self.poised_model = 1
self.M = array([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]])
self.kappa_ill = 1.000000000000000e+15
self.kappa_th = 2000
self.eps_bnd = 1.000000000000000e-06
self.poised = 1
self.Y_radius = 1
self.c = helper.dummyUnionStruct()
self.c.free = 0
self.c.fixed = 1
self.c.alwaysfixed = 2
self.c.in_ = 1
self.c.out = 0
self.c.unused = 0
self.c.inY = 1
self.c.dummy = 1
self.c.nodummy = 0
self.level = 'toplevel'
self.whichmodel = 0
self.hardcons = 0
self.noisy = 0
self.scaleX = 0
self.scalefacX = array([1, 1, 1])
self.CNTsin = 0
self.shrink_Delta = 1
self.scale = array([[1], [1], [1], [1]])
self.shift_Y = 1
self.info = dummyInfo()
self.options = helper.dummyOptions()
self.values = helper.dummyValues()
self.abs_tol = 1e-5
self.rel_tol = 1e-5
