def test_jacobian():
from test_ginzburg_landau import GinzburgLandau
a = 10.0
n = 10
points, cells = meshzoo.rectangle(-a / 2, a / 2, -a / 2, a / 2, n, n)
mesh = meshplex.MeshTri(points, cells)
gl = GinzburgLandau(mesh)
glr = GinzburgLandauReal(mesh)
n = points.shape[0]
numpy.random.seed(123)
for _ in range(10):
psi = numpy.random.rand(n) + 1j * numpy.random.rand(n)
mu = numpy.random.rand(1)[0]
jac0 = gl.jacobian(psi, mu)
jac1 = glr.jacobian(to_real(psi), mu)
for _ in range(10):
phi = numpy.random.rand(n) + 1j * numpy.random.rand(n)
out0 = (jac0 * phi) * mesh.control_volumes
out1 = to_complex(jac1 * to_real(phi))
assert numpy.all(numpy.abs(out0 - out1) < 1.0e-12)
def test_jacobian():
from test_ginzburg_landau import GinzburgLandau
a = 10.0
n = 10
points, cells = meshzoo.rectangle_tri((-a / 2, -a / 2), (a / 2, a / 2), n)
# add column with zeros for magnetic potential
points = np.column_stack([points, np.zeros(points.shape[0])])
mesh = meshplex.MeshTri(points, cells)
gl = GinzburgLandau(mesh)
glr = GinzburgLandauReal(mesh)
n = points.shape[0]
np.random.seed(123)
for _ in range(10):
psi = np.random.rand(n) + 1j * np.random.rand(n)
mu = np.random.rand(1)[0]
jac0 = gl.jacobian(psi, mu)
jac1 = glr.jacobian(to_real(psi), mu)
for _ in range(10):
phi = np.random.rand(n) + 1j * np.random.rand(n)
out0 = (jac0 * phi) * mesh.control_volumes
out1 = to_complex(jac1 * to_real(phi))
assert np.all(np.abs(out0 - out1) < 1.0e-12)
def test_df_dlmbda():
from test_ginzburg_landau import GinzburgLandau
a = 10.0
n = 10
points, cells = meshzoo.rectangle_tri(np.linspace(-a / 2, a / 2, n),
np.linspace(-a / 2, a / 2, n))
# add column with zeros for magnetic potential
points = np.column_stack([points, np.zeros(points.shape[0])])
mesh = meshplex.Mesh(points, cells)
gl = GinzburgLandau(mesh)
glr = GinzburgLandauReal(mesh)
n = points.shape[0]
np.random.seed(123)
for _ in range(10):
psi = np.random.rand(n) + 1j * np.random.rand(n)
mu = np.random.rand(1)[0]
out = gl.df_dlmbda(psi, mu) * mesh.control_volumes
out2 = glr.df_dlmbda(to_real(psi), mu)
assert np.all(np.abs(out - to_complex(out2)) < 1.0e-12)
def test_df_dlmbda():
from test_ginzburg_landau import GinzburgLandau
a = 10.0
n = 10
points, cells = meshzoo.rectangle(-a / 2, a / 2, -a / 2, a / 2, n, n)
mesh = meshplex.MeshTri(points, cells)
gl = GinzburgLandau(mesh)
glr = GinzburgLandauReal(mesh)
n = points.shape[0]
numpy.random.seed(123)
for _ in range(10):
psi = numpy.random.rand(n) + 1j * numpy.random.rand(n)
mu = numpy.random.rand(1)[0]
out = gl.df_dlmbda(psi, mu) * mesh.control_volumes
out2 = glr.df_dlmbda(to_real(psi), mu)
assert numpy.all(numpy.abs(out - to_complex(out2)) < 1.0e-12)