def test_distance(self):
c = CurveRZFourier(100, 1, 1, False)
dofs = c.get_dofs()
dofs[0] = 1.
c.set_dofs(dofs)
s = SurfaceRZFourier(mpol=1, ntor=1)
s.fit_to_curve(c, 0.2, flip_theta=True)
xyz = np.asarray([[0, 0, 0], [1., 0, 0], [2., 0., 0]])
d = signed_distance_from_surface(xyz, s)
assert np.allclose(d, [-0.8, 0.2, -0.8])
s.fit_to_curve(c, 0.2, flip_theta=False)
d = signed_distance_from_surface(xyz, s)
assert np.allclose(d, [-0.8, 0.2, -0.8])
def test_guidingcenterphihits(self):
bsh = self.bsh
ma = self.ma
nparticles = 2
m = PROTON_MASS
q = ELEMENTARY_CHARGE
Ekin = 9000 * ONE_EV
nphis = 10
phis = np.linspace(0, 2 * np.pi, nphis, endpoint=False)
mpol = 5
ntor = 5
nfp = 3
s = SurfaceRZFourier(mpol=mpol,
ntor=ntor,
stellsym=True,
nfp=nfp,
quadpoints_phi=np.linspace(0,
1,
nfp * 2 * ntor + 1,
endpoint=False),
quadpoints_theta=np.linspace(0,
1,
2 * mpol + 1,
endpoint=False))
s.fit_to_curve(ma, 0.10, flip_theta=False)
sc = SurfaceClassifier(s, h=0.1, p=2)
if with_evtk:
sc.to_vtk('/tmp/classifier')
# check that the axis is classified as inside the domain
assert sc.evaluate(ma.gamma()[:1, :]) > 0
assert sc.evaluate(2 * ma.gamma()[:1, :]) < 0
np.random.seed(1)
gc_tys, gc_phi_hits = trace_particles_starting_on_curve(
ma,
bsh,
nparticles,
tmax=1e-4,
seed=1,
mass=m,
charge=q,
Ekin=Ekin,
umin=-0.1,
umax=+0.1,
phis=phis,
mode='gc_vac',
stopping_criteria=[LevelsetStoppingCriterion(sc)])
if with_evtk:
particles_to_vtk(gc_tys, '/tmp/particles_gc')
for i in range(nparticles):
assert validate_phi_hits(gc_phi_hits[i], bsh, nphis)
def test_tracing_on_surface_runs(self):
bsh = self.bsh
ma = self.ma
nparticles = 1
m = PROTON_MASS
q = ELEMENTARY_CHARGE
tmax = 1e-3
Ekin = 9000 * ONE_EV
np.random.seed(1)
ntor = 1
mpol = 1
stellsym = True
nfp = 3
phis = np.linspace(0, 1, 50, endpoint=False)
thetas = np.linspace(0, 1, 50, endpoint=False)
s = SurfaceRZFourier(mpol=mpol,
ntor=ntor,
stellsym=stellsym,
nfp=nfp,
quadpoints_phi=phis,
quadpoints_theta=thetas)
s.fit_to_curve(ma, 0.03, flip_theta=False)
gc_tys, gc_phi_hits = trace_particles_starting_on_surface(
s,
bsh,
nparticles,
tmax=tmax,
seed=1,
mass=m,
charge=q,
Ekin=Ekin,
umin=-0.80,
umax=-0.70,
phis=[],
mode='gc_vac',
tol=1e-11,
stopping_criteria=[IterationStoppingCriterion(10)])
assert len(gc_tys[0]) == 11
def test_stopping_criteria(self):
bsh = self.bsh
ma = self.ma
nparticles = 1
m = PROTON_MASS
q = ELEMENTARY_CHARGE
tmax = 1e-3
Ekin = 9000 * ONE_EV
np.random.seed(1)
gc_tys, gc_phi_hits = trace_particles_starting_on_curve(
ma,
bsh,
nparticles,
tmax=tmax,
seed=1,
mass=m,
charge=q,
Ekin=Ekin,
umin=-0.80,
umax=-0.70,
phis=[],
mode='gc_vac',
tol=1e-11,
stopping_criteria=[IterationStoppingCriterion(10)])
assert len(gc_tys[0]) == 11
# consider a particle with mostly perpendicular velocity so that it get's lost
ntor = 1
mpol = 1
stellsym = True
nfp = 3
phis = np.linspace(0, 1, 50, endpoint=False)
thetas = np.linspace(0, 1, 50, endpoint=False)
s = SurfaceRZFourier(mpol=mpol,
ntor=ntor,
stellsym=stellsym,
nfp=nfp,
quadpoints_phi=phis,
quadpoints_theta=thetas)
s.fit_to_curve(ma, 0.03, flip_theta=False)
sc = SurfaceClassifier(s, h=0.1, p=2)
gc_tys, gc_phi_hits = trace_particles_starting_on_curve(
ma,
bsh,
nparticles,
tmax=tmax,
seed=1,
mass=m,
charge=q,
Ekin=Ekin,
umin=-0.01,
umax=+0.01,
phis=[],
mode='gc_vac',
tol=1e-11,
stopping_criteria=[LevelsetStoppingCriterion(sc)])
if with_evtk:
particles_to_vtk(gc_tys, '/tmp/particles_gc')
assert gc_phi_hits[0][-1][1] == -1
assert np.all(sc.evaluate(gc_tys[0][:, 1:4]) > 0)
mpol = 5
ntor = 5
stellsym = True
nfp = 3
constraint_weight = 1e0
phis = np.linspace(0, 1 / nfp, 25, endpoint=False)
thetas = np.linspace(0, 1, 25, endpoint=False)
s = SurfaceRZFourier(mpol=mpol,
ntor=ntor,
stellsym=stellsym,
nfp=nfp,
quadpoints_phi=phis,
quadpoints_theta=thetas)
s.fit_to_curve(ma, 0.2, flip_theta=True)
# First optimize at fixed volume
qfm = QfmResidual(s, bs)
qfm.J()
vol = Volume(s)
vol_target = vol.J()
qfm_surface = QfmSurface(bs, s, vol, vol_target)
res = qfm_surface.minimize_qfm_penalty_constraints_LBFGS(
tol=1e-12, maxiter=1000, constraint_weight=constraint_weight)
print(
f"||vol constraint||={0.5*(s.volume()-vol_target)**2:.8e}, ||residual||={np.linalg.norm(qfm.J()):.8e}"
