def test_fc3dnsgs():
N.setNumericsVerbose(2)
FCP = N.FrictionContactProblem(3, M, q, mu)
SO = N.SolverOptions(N.SICONOS_FRICTION_3D_NSGS)
r = N.frictionContact3D_nsgs(FCP, reactions, velocities, SO)
assert SO.dparam[1] < 1e-10
assert not r
def test_fc3dlocalac():
N.setNumericsVerbose(2)
FCP = N.FrictionContactProblem(3, M, q, mu)
SO = N.SolverOptions(N.SICONOS_FRICTION_3D_LOCALAC)
r = N.frictionContact3D_localAlartCurnier(FCP, reactions, velocities, SO)
assert SO.dparam[1] < 1e-10
assert not r
def test_fc3dfischer():
N.setNumericsVerbose(2)
FCP = N.FrictionContactProblem(3,M,q,mu)
SO=N.SolverOptions(N.SICONOS_FRICTION_3D_LOCALFB)
r = N.frictionContact3D_localFischerBurmeister(FCP, reactions, velocities, SO)
assert SO.dparam[1] < 1e-10
assert not r
def test_mlcp_enum_large_fromfile():
SO=N.SolverOptions(mlcp,N.SICONOS_MLCP_ENUM)
N.mlcp_driver_init(mlcp, SO)
info = N.mlcp_enum(mlcp, z, w, SO)
N.mlcp_driver_reset(mlcp, SO)
print("z = ", z)
print("w = ", w)
assert (linalg.norm(z-zsol) <= ztol)
assert not info
def test_mcp_FB():
mcp=N.MCP(1,1,mcp_function,mcp_Nablafunction)
z = array([0., 0.])
w = array([0., 0.])
SO=N.SolverOptions(mcp,N.SICONOS_MCP_FB)
N.mcp_driver_init(mcp, SO)
info = N.mcp_FischerBurmeister(mcp, z, w, SO)
N.mcp_driver_reset(mcp, SO)
print("z = ", z)
print("w = ", w)
assert (linalg.norm(z-zsol) <= ztol)
assert not info
def test_lcp_pgs():
SO=N.SolverOptions(lcp,N.SICONOS_LCP_PGS)
info = N.lcp_pgs(lcp,z,w,SO)
print('pgs iter =', SO.iparam[1])
print('pgs error=', SO.dparam[1])
assert (linalg.norm(z-zsol) <= ztol)
assert not info
def test_mcp_newton_minFBLSA():
mcp = SN.MixedComplementarityProblem2(0, 2, mcp_function, mcp_Nablafunction)
z = array([0., 0.])
w = array([0., 0.])
SO = SN.SolverOptions(mcp, SN.SICONOS_MCP_NEWTON_MINFBLSA)
info = SN.mcp_newton_minFBLSA(mcp, z, w, SO)
print("z = ", z)
print("w = ", w)
assert (linalg.norm(z-zsol) <= ztol)
assert not info
SO.iparam[0] = 100
SO.iparam[3] = 2
SO.iparam[4] = 10
lambdaPM = np.empty((N, 4))
signs = np.empty((N, 2))
sol = np.empty((N, 2))
sol[0, :] = xk
z[4:6] = xk
z[6] = hh
k = 0
while t <= T:
k += 1
info = SN.mcp_newton_minFBLSA(mcp, z, w, SO)
#info = SN.mcp_newton_FBLSA(mcp, z, w, SO)
# print('iter {:} ; solver iter = {:} ; prec = {:}'.format(k, SO.iparam[1], SO.dparam[1]))
if info > 0:
mcp_function(0, 4, z, w)
sol[k, 0] = w[0] - z[1]
sol[k, 1] = w[2] - z[3]
if sol[k, 0] < -1e-7 and np.abs(z[1]) < 1e-10:
z[1] = -sol[k, 0]
z[0] = 1.0
if z[4] < -1e-7 and np.abs(z[3]) < 1e-10:
z[3] = -sol[k, 1]
z[2] = 1.0
if z[1] < -1e-7:
z[1] = 0.0
z[0] = 0.0
SO.dparam[0] = 1e-12
SO.iparam[0] = 50
SO.iparam[2] = 1
SO.iparam[3] = 0
SO.iparam[4] = 10
signs = np.empty((N, 2))
sol = np.empty((N, 2))
sol[0, :] = xk
k = 0
#SN.setNumericsVerbose(3)
while t <= T:
k += 1
info = SN.variationalInequality_box_newton_QiLSA(vi, lambda_, xkp1, SO)
#print('iter {:} ; solver iter = {:} ; prec = {:}'.format(k, SO.iparam[1], SO.dparam[1]))
#info = SN.mcp_newton_FBLSA(mcp, z, w, SO)
if info > 0:
print(lambda_)
# vi_function(2, signs[k-1, :], xkp1)
lambda_[0] = -np.sign(xkp1[0])
lambda_[1] = -np.sign(xkp1[1])
if np.abs(xk[0]) < 1e-10:
lambda_[0] = 0.01
if np.abs(xk[1]) < 1e-10:
lambda_[1] = 0.01
print('ok lambda')
print(lambda_)
info = SN.variationalInequality_box_newton_QiLSA(vi, lambda_, xkp1, SO)
# info = SN.mcp_newton_minFBLSA(mcp, z, w, SO)
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Siconos; if not, write to the Free Software # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA # # Contact: Vincent ACARY, [email protected] import Siconos.Kernel as SK import Siconos.Numerics as SN import numpy as np from scipy.linalg import expm from functions import compute_dt_matrices kmax = 10 if SN.compiled_in_debug_mode() else 100 def test_TI(): h = 1.0e-4 k = 0 err = False while k < kmax: n = np.random.randint(2, kmax) m = np.random.randint(1, n) A = np.random.random((n, n)) B = np.random.random((n, m)) errInv = 1 try: Ainv = np.linalg.inv(A) Aexp = expm(A*h) Psi = Ainv.dot((Aexp-np.eye(n)).dot(B))
[ 0. ],
[ 0. ],
[ 0. ],
[ 0. ]])
mlcp=N.MLCP(3,M,q)
def test_mlcp_enum_large():
SO=N.SolverOptions(mlcp,N.SICONOS_MLCP_ENUM)
N.mlcp_driver_init(mlcp, SO)
info = N.mlcp_enum(mlcp, z, w, SO)
N.mlcp_driver_reset(mlcp, SO)
print("z = ", z)
print("w = ", w)
assert (linalg.norm(z-zsol) <= ztol)
assert not info
mlcp =0
mlcp=N.MLCP()
N.mixedLinearComplementarity_newFromFilename(mlcp,"./data/diodeBridge_mlcp.dat")
N.mixedLinearComplementarity_display(mlcp)
def test_mlcp_enum_large_fromfile():
SO=N.SolverOptions(mlcp,N.SICONOS_MLCP_ENUM)
N.mlcp_driver_init(mlcp, SO)
info = N.mlcp_enum(mlcp, z, w, SO)
N.mlcp_driver_reset(mlcp, SO)
print("z = ", z)
print("w = ", w)
assert (linalg.norm(z-zsol) <= ztol)
assert not info
def test_lcp_enum():
SO=N.SolverOptions(lcp,N.SICONOS_LCP_ENUM)
info = N.lcp_enum(lcp, z, w, SO)
assert (linalg.norm(z-zsol) <= ztol)
assert not info
def test_lcp_lexicolemke():
SO=N.SolverOptions(lcp, N.SICONOS_LCP_LEMKE)
info = N.lcp_lexicolemke(lcp, z, w, SO)
print('lexicolemke iter =', SO.iparam[1])
assert (linalg.norm(z-zsol) <= ztol)
assert not info
