def test_dBdX_by_dcoilcoeff_reverse_taylortest(self):
np.random.seed(1)
coil = get_coil()
bs = BiotSavart([coil], [1e4])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
points += 0.001 * (np.random.rand(*points.shape) - 0.5)
bs.set_points(points)
coil_dofs = np.asarray(coil.get_dofs())
B = bs.B()
dBdX = bs.dB_by_dX()
J0 = np.sum(dBdX**2)
dJ = bs.B_and_dB_vjp(B, dBdX)
h = 1e-2 * np.random.rand(len(coil_dofs)).reshape(coil_dofs.shape)
dJ_dh = 2 * np.sum(dJ[1][0] * h)
err = 1e6
for i in range(5, 10):
eps = 0.5**i
coil.set_dofs(coil_dofs + eps * h)
bs.clear_cached_properties()
dBdXh = bs.dB_by_dX()
Jh = np.sum(dBdXh**2)
deriv_est = (Jh - J0) / eps
err_new = np.linalg.norm(deriv_est - dJ_dh)
assert err_new < 0.55 * err
err = err_new
def test_residual(self):
"""
This test loads a SurfaceXYZFourier that interpolates the xyz coordinates
of a surface in the NCSX configuration that was computed on a previous
branch of pyplasmaopt. Here, we verify that the Boozer residual at these
interpolation points is small.
"""
s = get_exact_surface()
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
bs_tf = BiotSavart(stellarator.coils, stellarator.currents)
weight = 1.
tf = ToroidalFlux(s, bs_tf)
# these data are obtained from `boozer` branch of pyplamsaopt
tf_target = 0.41431152
iota = -0.44856192
boozer_surface = BoozerSurface(bs, s, tf, tf_target)
x = np.concatenate((s.get_dofs(), [iota]))
r0 = boozer_surface.boozer_penalty_constraints(
x,
derivatives=0,
constraint_weight=weight,
optimize_G=False,
scalarize=False)
# the residual should be close to zero for all entries apart from the y
# and z coordinate at phi=0 and theta=0 (and the corresponding rotations)
ignores_idxs = np.zeros_like(r0)
ignores_idxs[[1, 2, 693, 694, 695, 1386, 1387, 1388, -2, -1]] = 1
assert np.max(np.abs(r0[ignores_idxs < 0.5])) < 1e-8
assert np.max(np.abs(r0[-2:])) < 1e-6
def stdBonAxis(self):
bs = BiotSavart(self.coils, self.currents)
bs.set_points(self.axis.gamma())
Bfield = bs.B()
devBstrength = [
sqrt(dot(Bfieldi, Bfieldi)) - self.stel.B0 for Bfieldi in Bfield
]
return std(devBstrength)
def subtest_biotsavart_gradient_symmetric_and_divergence_free(self, idx):
coil = get_coil()
bs = BiotSavart([coil], [1e4])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
points += 0.001 * (np.random.rand(*points.shape) - 0.5)
bs.set_points(points)
dB = bs.dB_by_dX()
assert abs(dB[idx][0, 0] + dB[idx][1, 1] + dB[idx][2, 2]) < 1e-14
assert np.allclose(dB[idx], dB[idx].T)
def subtest_biotsavart_dAdX_taylortest(self, idx):
coil = get_coil()
bs = BiotSavart([coil], [1e4])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
points += 0.001 * (np.random.rand(*points.shape) - 0.5)
bs.set_points(points)
A0 = bs.A()[idx]
dA = bs.dA_by_dX()[idx]
for direction in [
np.asarray((1., 0, 0)),
np.asarray((0, 1., 0)),
np.asarray((0, 0, 1.))
]:
deriv = dA.T.dot(direction)
err = 1e6
for i in range(5, 10):
eps = 0.5**i
bs.set_points(points + eps * direction)
Aeps = bs.A()[idx]
deriv_est = (Aeps - A0) / (eps)
new_err = np.linalg.norm(deriv - deriv_est)
assert new_err < 0.55 * err
err = new_err
def subtest_d2B_by_dXdX_is_symmetric(self, idx):
coil = get_coil()
bs = BiotSavart([coil], [1e4])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
points += 0.001 * (np.random.rand(*points.shape) - 0.5)
bs.set_points(points)
d2B_by_dXdX = bs.d2B_by_dXdX()
for i in range(3):
assert np.allclose(d2B_by_dXdX[idx, :, :, i],
d2B_by_dXdX[idx, :, :, i].T)
def subtest_boozer_penalty_constraints_gradient(self,
surfacetype,
stellsym,
optimize_G=False):
np.random.seed(1)
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
bs_tf = BiotSavart(stellarator.coils, stellarator.currents)
s = get_surface(surfacetype, stellsym)
s.fit_to_curve(ma, 0.1)
weight = 11.1232
tf = ToroidalFlux(s, bs_tf)
tf_target = 0.1
boozer_surface = BoozerSurface(bs, s, tf, tf_target)
iota = -0.3
x = np.concatenate((s.get_dofs(), [iota]))
if optimize_G:
x = np.concatenate((x, [
2. * np.pi * np.sum(np.abs(bs.coil_currents)) *
(4 * np.pi * 10**(-7) / (2 * np.pi))
]))
f0, J0 = boozer_surface.boozer_penalty_constraints(
x, derivatives=1, constraint_weight=weight, optimize_G=optimize_G)
h = np.random.uniform(size=x.shape) - 0.5
Jex = J0 @ h
err_old = 1e9
epsilons = np.power(2., -np.asarray(range(7, 20)))
print(
"################################################################################"
)
for eps in epsilons:
f1 = boozer_surface.boozer_penalty_constraints(
x + eps * h,
derivatives=0,
constraint_weight=weight,
optimize_G=optimize_G)
Jfd = (f1 - f0) / eps
err = np.linalg.norm(Jfd - Jex) / np.linalg.norm(Jex)
print(err / err_old, f0, f1)
assert err < err_old * 0.55
err_old = err
print(
"################################################################################"
)
def subtest_boozer_constrained_jacobian(self,
surfacetype,
stellsym,
optimize_G=False):
np.random.seed(1)
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
bs_tf = BiotSavart(stellarator.coils, stellarator.currents)
s = get_surface(surfacetype, stellsym)
s.fit_to_curve(ma, 0.1)
tf = ToroidalFlux(s, bs_tf)
tf_target = 0.1
boozer_surface = BoozerSurface(bs, s, tf, tf_target)
iota = -0.3
lm = [0., 0.]
x = np.concatenate((s.get_dofs(), [iota]))
if optimize_G:
x = np.concatenate((x, [
2. * np.pi * np.sum(np.abs(bs.coil_currents)) *
(4 * np.pi * 10**(-7) / (2 * np.pi))
]))
xl = np.concatenate((x, lm))
res0, dres0 = boozer_surface.boozer_exact_constraints(
xl, derivatives=1, optimize_G=optimize_G)
h = np.random.uniform(size=xl.shape) - 0.5
dres_exact = dres0 @ h
err_old = 1e9
epsilons = np.power(2., -np.asarray(range(7, 20)))
print(
"################################################################################"
)
for eps in epsilons:
res1 = boozer_surface.boozer_exact_constraints(
xl + eps * h, derivatives=0, optimize_G=optimize_G)
dres_fd = (res1 - res0) / eps
err = np.linalg.norm(dres_fd - dres_exact)
print(err / err_old)
assert err < err_old * 0.55
err_old = err
print(
"################################################################################"
)
def pyoculusPoincare(stel,
qvfilename,
Rbegin=1.55,
Rend=1.62,
nPpts=50,
nPtrj=5):
from axisOptFuncs import importCoils, getFourierCurve
from pyoculus.solvers import PoincarePlot
import matplotlib.pyplot as plt
_, current = importCoils("coils." + qvfilename)
outputFile = qvfilename + "_coil_coeffs.dat"
coils, currents = getFourierCurve(outputFile, current)
bs = BiotSavart(coils, currents)
sbsp = SimsgeoBiotSavart(bs, R0=sum(stel.rc), Z0=0, Nfp=stel.nfp)
params = dict()
Rbegin = 1.01 * sum(stel.rc)
params["Rbegin"] = Rbegin
params["Rend"] = Rend
params["nPpts"] = nPpts
params["nPtrj"] = nPtrj
p = PoincarePlot(sbsp, params)
poincare_output = p.compute()
p.plot(s=1)
plt.savefig("poincarePyoculus_" + qvfilename + '.pdf',
bbox_inches='tight',
pad_inches=0)
iota = p.compute_iota()
p.plot_iota()
plt.savefig("iotaPyoculus_" + qvfilename + '.pdf',
bbox_inches='tight',
pad_inches=0)
plt.show()
def test_interpolated_field_convergence_rate(self):
R0test = 1.5
B0test = 0.8
B0 = ToroidalField(R0test, B0test)
coils, currents, _ = get_ncsx_data(Nt_coils=5, Nt_ma=10, ppp=5)
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
old_err_1 = 1e6
old_err_2 = 1e6
btotal = bs + B0
for n in [4, 8, 16]:
rmin = 1.3
rmax = 1.7
rsteps = n
phimin = 0
phimax = 2 * np.pi
phisteps = n * 32
zmin = -0.1
zmax = 0.1
zsteps = n
bsh = InterpolatedField(btotal, 2, [rmin, rmax, rsteps],
[phimin, phimax, phisteps],
[zmin, zmax, zsteps], True)
err_1 = np.mean(bsh.estimate_error_B(1000))
err_2 = np.mean(bsh.estimate_error_GradAbsB(1000))
print(err_1, err_2)
assert err_1 < 0.6**3 * old_err_1
assert err_2 < 0.6**3 * old_err_2
old_err_1 = err_1
old_err_2 = err_2
def subtest_boozer_penalty_constraints_hessian(self,
surfacetype,
stellsym,
optimize_G=False):
np.random.seed(1)
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
bs_tf = BiotSavart(stellarator.coils, stellarator.currents)
s = get_surface(surfacetype, stellsym)
s.fit_to_curve(ma, 0.1)
tf = ToroidalFlux(s, bs_tf)
tf_target = 0.1
boozer_surface = BoozerSurface(bs, s, tf, tf_target)
iota = -0.3
x = np.concatenate((s.get_dofs(), [iota]))
if optimize_G:
x = np.concatenate((x, [
2. * np.pi * np.sum(np.abs(bs.coil_currents)) *
(4 * np.pi * 10**(-7) / (2 * np.pi))
]))
f0, J0, H0 = boozer_surface.boozer_penalty_constraints(
x, derivatives=2, optimize_G=optimize_G)
h1 = np.random.uniform(size=x.shape) - 0.5
h2 = np.random.uniform(size=x.shape) - 0.5
d2f = h1 @ H0 @ h2
err_old = 1e9
epsilons = np.power(2., -np.asarray(range(10, 20)))
print(
"################################################################################"
)
for eps in epsilons:
fp, Jp = boozer_surface.boozer_penalty_constraints(
x + eps * h1, derivatives=1, optimize_G=optimize_G)
d2f_fd = (Jp @ h2 - J0 @ h2) / eps
err = np.abs(d2f_fd - d2f) / np.abs(d2f)
print(err / err_old)
assert err < err_old * 0.55
err_old = err
def test_biotsavart_both_interfaces_give_same_result(self):
coils = [get_coil()]
currents = [1e4]
points = np.asarray(
10 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
B1 = BiotSavart(coils, currents).set_points(points).B()
from simsoptpp import biot_savart_B
B2 = biot_savart_B(points, [c.gamma() for c in coils],
[c.gammadash() for c in coils], currents)
assert np.linalg.norm(B1) > 1e-5
assert np.allclose(B1, B2)
def test_get_set_points_cyl_cart(self):
coils, currents, _ = get_ncsx_data(Nt_coils=5, Nt_ma=10, ppp=5)
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
points_xyz = np.asarray([[0.5, 0.6, 0.7]])
points_rphiz = np.zeros_like(points_xyz)
points_rphiz[:, 0] = np.linalg.norm(points_xyz[:, 0:2], axis=1)
points_rphiz[:, 1] = np.mod(
np.arctan2(points_xyz[:, 1], points_xyz[:, 0]), 2 * np.pi)
points_rphiz[:, 2] = points_xyz[:, 2]
bs.set_points_cyl(points_rphiz)
# import IPython; IPython.embed()
# import sys; sys.exit()
assert np.allclose(bs.get_points_cyl(), points_rphiz)
assert np.allclose(bs.get_points_cart(), points_xyz)
bs.set_points_cart(points_xyz)
assert np.allclose(bs.get_points_cyl(), points_rphiz)
assert np.allclose(bs.get_points_cart(), points_xyz)
def CoilsBonAxis(axis, qvfilename, NFP):
from axisOptFuncs import importCoils, getFourierCurve, plot_stellarator
from simsopt.geo.biotsavart import BiotSavart
from numpy import sqrt, dot
import matplotlib.pyplot as plt
_, current = importCoils("coils." + qvfilename)
outputFile = qvfilename + "_coil_coeffs.dat"
coils, currents = getFourierCurve(outputFile, current)
print("Look at resulting coils")
plot_stellarator("coils_FOURIER_", qvfilename, coils, NFP, axis,
"quasisymmetry_out." + qvfilename + ".nc")
print("Plot on-axis B from these coils")
bs = BiotSavart(coils, currents)
bs.set_points(axis.gamma())
Bfield = bs.B()
Bstrength = [sqrt(dot(Bfieldi, Bfieldi)) for Bfieldi in Bfield]
plt.figure()
plt.plot(Bstrength)
plt.xlabel('phi')
plt.ylabel('B')
plt.savefig("Bonaxis" + qvfilename + '.pdf',
bbox_inches='tight',
pad_inches=0)
def residue(self, guess=1.6, pp=3, qq=8, sbegin=1.58, send=1.62):
bs = BiotSavart(self.coils, self.currents)
sbsp = SimsgeoBiotSavart(bs, R0=sum(self.stel.rc), Z0=0, Nfp=self.nfp)
fp = FixedPoint(sbsp, {"Z": 0.0})
output = fp.compute(guess=guess,
pp=pp,
qq=qq,
sbegin=sbegin,
send=send)
try:
residue = output.GreenesResidue
except:
residue = 0
return residue
def test_biotsavart_exponential_convergence(self):
coil = get_coil()
from time import time
# points = np.asarray(17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04 ]])
points = np.asarray(
10 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
tic = time()
btrue = BiotSavart([get_coil(1000)], [1e4]).set_points(points).B()
# print(btrue)
bcoarse = BiotSavart([get_coil(10)], [1e4]).set_points(points).B()
bfine = BiotSavart([get_coil(20)], [1e4]).set_points(points).B()
assert np.linalg.norm(btrue -
bfine) < 1e-4 * np.linalg.norm(bcoarse - bfine)
# print(time()-tic)
tic = time()
dbtrue = BiotSavart([get_coil(1000)],
[1e4]).set_points(points).dB_by_dX()
# print(dbtrue)
dbcoarse = BiotSavart([get_coil(10)],
[1e4]).set_points(points).dB_by_dX()
dbfine = BiotSavart([get_coil(20)],
[1e4]).set_points(points).dB_by_dX()
assert np.linalg.norm(btrue -
bfine) < 1e-4 * np.linalg.norm(bcoarse - bfine)
# print(time()-tic)
tic = time()
dbtrue = BiotSavart([get_coil(1000)],
[1e4]).set_points(points).d2B_by_dXdX()
# print("dbtrue", dbtrue)
dbcoarse = BiotSavart([get_coil(10)],
[1e4]).set_points(points).d2B_by_dXdX()
dbfine = BiotSavart([get_coil(20)],
[1e4]).set_points(points).d2B_by_dXdX()
assert np.linalg.norm(btrue -
bfine) < 1e-4 * np.linalg.norm(bcoarse - bfine)
def subtest_toroidal_flux1(self, surfacetype, stellsym):
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
bs_tf = BiotSavart(stellarator.coils, stellarator.currents)
s = get_surface(surfacetype, stellsym)
tf = ToroidalFlux(s, bs_tf)
coeffs = s.get_dofs()
def f(dofs):
s.set_dofs(dofs)
return tf.J()
def df(dofs):
s.set_dofs(dofs)
return tf.dJ_by_dsurfacecoefficients()
taylor_test1(f, df, coeffs)
def test_helicalcoil_Bfield(self):
point = [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]]
field = [[-0.00101961, 0.20767292, -0.00224908]]
derivative = [[[0.47545098, 0.01847397, 1.10223595],
[0.01847426, -2.66700072, 0.01849548],
[1.10237535, 0.01847085, 2.19154973]]]
coils = [CurveHelical(100, 2, 5, 2, 1., 0.3) for i in range(2)]
coils[0].set_dofs(np.concatenate(([0, 0], [0, 0])))
coils[1].set_dofs(np.concatenate(([np.pi / 2, 0], [0, 0])))
currents = [-3.07e5, 3.07e5]
Bhelical = BiotSavart(coils, currents)
Bhelical.set_points(point)
assert np.allclose(Bhelical.B(), field)
assert np.allclose(Bhelical.dB_by_dX(), derivative)
def test_biotsavart_B_is_curlA(self):
coil = get_coil()
bs = BiotSavart([coil], [1e4])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
bs.set_points(points)
B, dA_by_dX = bs.B(), bs.dA_by_dX()
curlA1 = dA_by_dX[:, 1, 2] - dA_by_dX[:, 2, 1]
curlA2 = dA_by_dX[:, 2, 0] - dA_by_dX[:, 0, 2]
curlA3 = dA_by_dX[:, 0, 1] - dA_by_dX[:, 1, 0]
curlA = np.concatenate(
(curlA1[:, None], curlA2[:, None], curlA3[:, None]), axis=1)
err = np.max(np.abs(curlA - B))
assert err < 1e-14
def getResidue(stel,
axis,
qvfilename,
guess=1.6,
pp=3,
qq=8,
sbegin=1.58,
send=1.62):
from axisOptFuncs import importCoils, getFourierCurve
from pyoculus.solvers import FixedPoint
_, current = importCoils("coils." + qvfilename)
outputFile = qvfilename + "_coil_coeffs.dat"
coils, currents = getFourierCurve(outputFile, current)
bs = BiotSavart(coils, currents)
sbsp = SimsgeoBiotSavart(bs, R0=sum(stel.rc), Z0=0, Nfp=stel.nfp)
fp = FixedPoint(sbsp, {"Z": 0.0})
#sbegin=1.01*sum(stel.rc)
output = fp.compute(guess=guess, pp=pp, qq=qq, sbegin=sbegin, send=send)
residue = output.GreenesResidue
print(residue)
def test_toroidal_flux_is_constant(self):
"""
this test ensures that the toroidal flux does not change, regardless
of the cross section (varphi = constant) across which it is computed
"""
s = get_exact_surface()
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
bs_tf = BiotSavart(stellarator.coils, stellarator.currents)
gamma = s.gamma()
num_phi = gamma.shape[0]
tf_list = np.zeros((num_phi, ))
for idx in range(num_phi):
tf = ToroidalFlux(s, bs_tf, idx=idx)
tf_list[idx] = tf.J()
mean_tf = np.mean(tf_list)
max_err = np.max(np.abs(mean_tf - tf_list)) / mean_tf
assert max_err < 1e-2
def test_interpolated_field_close(self):
R0test = 1.5
B0test = 0.8
B0 = ToroidalField(R0test, B0test)
coils, currents, _ = get_ncsx_data(Nt_coils=5, Nt_ma=10, ppp=5)
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
btotal = bs + B0
n = 10
rmin = 1.5
rmax = 1.7
rsteps = n
phimin = 0
phimax = 2 * np.pi
phisteps = n * 32
zmin = -0.1
zmax = 0.1
zsteps = n
bsh = InterpolatedField(btotal, 4, [rmin, rmax, rsteps],
[phimin, phimax, phisteps],
[zmin, zmax, zsteps], True)
N = 10
points = np.random.uniform(size=(N, 3))
points[:, 0] = points[:, 0] * (rmax - rmin) + rmin
points[:, 1] = points[:, 1] * (phimax - phimin) + phimin
points[:, 2] = points[:, 2] * (zmax - zmin) + zmin
bsh.set_points_cyl(points)
btotal.set_points_cyl(points)
B = btotal.B()
Bh = bsh.B()
dB = btotal.GradAbsB()
dBh = bsh.GradAbsB()
print("btotal.B()", B)
print("bsh.B()", Bh)
print("btotal.GradAbsB(()", dB)
print("bsh.GradAbsB()", dBh)
assert np.allclose(B, Bh, rtol=1e-3)
assert np.allclose(dB, dBh, rtol=1e-3)
def test_sum_Bfields(self):
pointVar = 1e-1
npoints = 20
points = np.asarray(
npoints * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
points += pointVar * (np.random.rand(*points.shape) - 0.5)
# Set up helical field
coils = [CurveHelical(101, 2, 5, 2, 1., 0.3) for i in range(2)]
coils[0].set_dofs(np.concatenate(([np.pi / 2, 0], [0, 0])))
coils[1].set_dofs(np.concatenate(([0, 0], [0, 0])))
currents = [-2.1e5, 2.1e5]
Bhelical = BiotSavart(coils, currents)
# Set up toroidal fields
Btoroidal1 = ToroidalField(1., 1.)
Btoroidal2 = ToroidalField(1.2, 0.1)
# Set up sum of the three in two different ways
Btotal1 = MagneticFieldSum([Bhelical, Btoroidal1, Btoroidal2])
Btotal2 = Bhelical + Btoroidal1 + Btoroidal2
Btotal3 = Btoroidal1 + Btoroidal2
# Evaluate at a given point
Bhelical.set_points(points)
Btoroidal1.set_points(points)
Btoroidal2.set_points(points)
Btotal1.set_points(points)
Btotal2.set_points(points)
Btotal3.set_points(points)
# Verify
assert np.allclose(Btotal1.B(), Btotal2.B())
assert np.allclose(Bhelical.B() + Btoroidal1.B() + Btoroidal2.B(),
Btotal1.B())
assert np.allclose(Btotal1.dB_by_dX(), Btotal2.dB_by_dX())
assert np.allclose(
Bhelical.dB_by_dX() + Btoroidal1.dB_by_dX() +
Btoroidal2.dB_by_dX(), Btotal1.dB_by_dX())
assert np.allclose(Btoroidal1.d2B_by_dXdX() + Btoroidal2.d2B_by_dXdX(),
Btotal3.d2B_by_dXdX())
assert np.allclose(Btoroidal1.A() + Btoroidal2.A(), Btotal3.A())
assert np.allclose(Btoroidal1.dA_by_dX() + Btoroidal2.dA_by_dX(),
Btotal3.dA_by_dX())
assert np.allclose(Btoroidal1.d2A_by_dXdX() + Btoroidal2.d2A_by_dXdX(),
Btotal3.d2A_by_dXdX())
def BonAxis(self):
bs = BiotSavart(self.coils, self.currents)
bs.set_points(self.axis.gamma())
Bfield = bs.B()
Bstrength = [sqrt(dot(Bfieldi, Bfieldi)) for Bfieldi in Bfield]
return Bstrength
def test_circularcoil_Bfield(self):
current = 1.2e7
radius = 1.12345
center = [0.12345, 0.6789, 1.23456]
pointVar = 1e-1
npoints = 1
## verify the field at the center of a coil in the xy plane
Bfield = CircularCoil(I=current, r0=radius)
points = np.array([[1e-10, 0, 0.]])
Bfield.set_points(points)
assert np.allclose(Bfield.B(),
[[0, 0, current / 1e7 * 2 * np.pi / radius]])
# Verify that divergence is zero
dB1_by_dX = Bfield.dB_by_dX()
assert np.allclose(
dB1_by_dX[:, 0, 0] + dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints)))
# Verify that, as a vacuum field, grad B=grad grad phi so that grad_i B_j = grad_j B_i
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(dB1_by_dX, transpGradB1)
### compare to biosavart(circular_coil)
## at these points
points = np.asarray(
npoints * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
points += pointVar * (np.random.rand(*points.shape) - 0.5)
## verify with a x^2+z^2=radius^2 circular coil
normal = [np.pi / 2, 0]
coils = [CurveXYZFourier(300, 1)]
coils[0].set_dofs(
[center[0], radius, 0., center[1], 0., 0., center[2], 0., radius])
Bcircular = BiotSavart(coils, [current])
Bfield = CircularCoil(I=current,
r0=radius,
normal=normal,
center=center)
Bfield.set_points(points)
Bcircular.set_points(points)
dB1_by_dX = Bfield.dB_by_dX()
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(Bfield.B(), Bcircular.B())
assert np.allclose(Bfield.dB_by_dX(), Bcircular.dB_by_dX())
assert np.allclose(
dB1_by_dX[:, 0, 0] + dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints)))
assert np.allclose(dB1_by_dX, transpGradB1)
# use normal = [0, 1, 0]
normal = [0, 1, 0]
coils = [CurveXYZFourier(300, 1)]
coils[0].set_dofs(
[center[0], radius, 0., center[1], 0., 0., center[2], 0., radius])
Bcircular = BiotSavart(coils, [current])
Bfield = CircularCoil(I=current,
r0=radius,
normal=normal,
center=center)
Bfield.set_points(points)
Bcircular.set_points(points)
dB1_by_dX = Bfield.dB_by_dX()
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(Bfield.B(), Bcircular.B())
assert np.allclose(Bfield.dB_by_dX(), Bcircular.dB_by_dX())
assert np.allclose(
dB1_by_dX[:, 0, 0] + dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints)))
assert np.allclose(dB1_by_dX, transpGradB1)
## verify with a y^2+z^2=radius^2 circular coil
normal = [np.pi / 2, np.pi / 2]
coils = [CurveXYZFourier(300, 1)]
coils[0].set_dofs(
[center[0], 0, 0., center[1], radius, 0., center[2], 0., radius])
Bcircular = BiotSavart(coils, [current])
Bfield = CircularCoil(I=current,
r0=radius,
normal=normal,
center=center)
Bfield.set_points(points)
Bcircular.set_points(points)
dB1_by_dX = Bfield.dB_by_dX()
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(Bfield.B(), Bcircular.B())
assert np.allclose(Bfield.dB_by_dX(), Bcircular.dB_by_dX())
assert np.allclose(dB1_by_dX[:, 0, 0] +
dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints))) # divergence
assert np.allclose(dB1_by_dX, transpGradB1) # symmetry of the gradient
Bfield.set_points([[0.1, 0.2, 0.3]])
Afield = Bfield.A()
assert np.allclose(Afield, [[0, 5.15786, -2.643056]])
# use normal=[1,0,0]
normal = [1, 0, 0]
coils = [CurveXYZFourier(300, 1)]
coils[0].set_dofs(
[center[0], 0, 0., center[1], radius, 0., center[2], 0., radius])
Bcircular = BiotSavart(coils, [current])
Bfield = CircularCoil(I=current,
r0=radius,
normal=normal,
center=center)
Bfield.set_points(points)
Bcircular.set_points(points)
dB1_by_dX = Bfield.dB_by_dX()
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(Bfield.B(), Bcircular.B())
assert np.allclose(Bfield.dB_by_dX(), Bcircular.dB_by_dX())
assert np.allclose(dB1_by_dX[:, 0, 0] +
dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints))) # divergence
assert np.allclose(dB1_by_dX, transpGradB1) # symmetry of the gradient
## verify with a x^2+y^2=radius^2 circular coil
center = [0, 0, 0]
normal = [0, 0]
coils = [CurveXYZFourier(300, 1)]
coils[0].set_dofs(
[center[0], 0, radius, center[1], radius, 0., center[2], 0., 0.])
Bcircular = BiotSavart(coils, [current])
coils2 = [CurveRZFourier(300, 1, 1, True)]
coils2[0].set_dofs([radius, 0, 0])
Bcircular2 = BiotSavart(coils, [current])
Bfield = CircularCoil(I=current,
r0=radius,
normal=normal,
center=center)
Bfield.set_points(points)
Bcircular.set_points(points)
Bcircular2.set_points(points)
dB1_by_dX = Bfield.dB_by_dX()
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(Bfield.B(), Bcircular.B())
assert np.allclose(Bfield.B(), Bcircular2.B())
assert np.allclose(Bfield.dB_by_dX(), Bcircular.dB_by_dX())
assert np.allclose(Bfield.dB_by_dX(), Bcircular2.dB_by_dX())
assert np.allclose(dB1_by_dX[:, 0, 0] +
dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints))) # divergence
assert np.allclose(dB1_by_dX, transpGradB1) # symmetry of the gradient
# use normal = [0, 0, 1]
center = [0, 0, 0]
normal = [0, 0, 1]
coils = [CurveXYZFourier(300, 1)]
coils[0].set_dofs(
[center[0], 0, radius, center[1], radius, 0., center[2], 0., 0.])
Bcircular = BiotSavart(coils, [current])
coils2 = [CurveRZFourier(300, 1, 1, True)]
coils2[0].set_dofs([radius, 0, 0])
Bcircular2 = BiotSavart(coils, [current])
Bfield = CircularCoil(I=current,
r0=radius,
normal=normal,
center=center)
Bfield.set_points(points)
Bcircular.set_points(points)
Bcircular2.set_points(points)
dB1_by_dX = Bfield.dB_by_dX()
transpGradB1 = [dBdx.T for dBdx in dB1_by_dX]
assert np.allclose(Bfield.B(), Bcircular.B())
assert np.allclose(Bfield.B(), Bcircular2.B())
assert np.allclose(Bfield.dB_by_dX(), Bcircular.dB_by_dX())
assert np.allclose(Bfield.dB_by_dX(), Bcircular2.dB_by_dX())
assert np.allclose(dB1_by_dX[:, 0, 0] +
dB1_by_dX[:, 1, 1] + dB1_by_dX[:, 2, 2],
np.zeros((npoints))) # divergence
assert np.allclose(dB1_by_dX, transpGradB1) # symmetry of the gradient
def subtest_boozer_surface_optimisation_convergence(
self, surfacetype, stellsym, optimize_G, second_stage):
coils, currents, ma = get_ncsx_data()
if stellsym:
stellarator = CoilCollection(coils, currents, 3, True)
else:
# Create a stellarator that still has rotational symmetry but
# doesn't have stellarator symmetry. We do this by first applying
# stellarator symmetry, then breaking this slightly, and then
# applying rotational symmetry
from simsopt.geo.curve import RotatedCurve
coils_flipped = [RotatedCurve(c, 0, True) for c in coils]
currents_flipped = [-cur for cur in currents]
for c in coils_flipped:
c.rotmat += 0.001 * np.random.uniform(
low=-1., high=1., size=c.rotmat.shape)
c.rotmatT = c.rotmat.T
stellarator = CoilCollection(coils + coils_flipped,
currents + currents_flipped, 3, False)
bs = BiotSavart(stellarator.coils, stellarator.currents)
s = get_surface(surfacetype, stellsym)
s.fit_to_curve(ma, 0.1)
iota = -0.3
ar = Area(s)
ar_target = ar.J()
boozer_surface = BoozerSurface(bs, s, ar, ar_target)
if optimize_G:
G = 2. * np.pi * np.sum(np.abs(
bs.coil_currents)) * (4 * np.pi * 10**(-7) / (2 * np.pi))
else:
G = None
# compute surface first using LBFGS exact and an area constraint
res = boozer_surface.minimize_boozer_penalty_constraints_LBFGS(
tol=1e-9, maxiter=500, constraint_weight=100., iota=iota, G=G)
print('Squared residual after LBFGS', res['fun'])
if second_stage == 'ls':
res = boozer_surface.minimize_boozer_penalty_constraints_ls(
tol=1e-9,
maxiter=100,
constraint_weight=100.,
iota=res['iota'],
G=res['G'])
elif second_stage == 'newton':
res = boozer_surface.minimize_boozer_penalty_constraints_newton(
tol=1e-9,
maxiter=10,
constraint_weight=100.,
iota=res['iota'],
G=res['G'],
stab=1e-4)
elif second_stage == 'newton_exact':
res = boozer_surface.minimize_boozer_exact_constraints_newton(
tol=1e-9, maxiter=10, iota=res['iota'], G=res['G'])
print('Residual after second stage', np.linalg.norm(res['residual']))
assert res['success']
# For the stellsym case we have z(0, 0) = y(0, 0) = 0. For the not
# stellsym case, we enforce z(0, 0) = 0, but expect y(0, 0) \neq 0
gammazero = s.gamma()[0, 0, :]
assert np.abs(gammazero[2]) < 1e-10
if stellsym:
assert np.abs(gammazero[1]) < 1e-10
else:
assert np.abs(gammazero[1]) > 1e-6
if surfacetype == 'SurfaceXYZTensorFourier':
assert np.linalg.norm(res['residual']) < 1e-9
if second_stage == 'newton_exact' or surfacetype == 'SurfaceXYZTensorFourier':
assert np.abs(ar_target - ar.J()) < 1e-9
def test_to_vtk(self):
coils, currents, _ = get_ncsx_data(Nt_coils=5, Nt_ma=10, ppp=5)
stellarator = CoilCollection(coils, currents, 3, True)
bs = BiotSavart(stellarator.coils, stellarator.currents)
bs.to_vtk('/tmp/bfield')
def subtest_biotsavart_d2A_by_dXdX_taylortest(self, idx):
coil = get_coil()
bs = BiotSavart([coil], [1e4])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
bs.set_points(points)
dA_by_dX, d2A_by_dXdX = bs.dA_by_dX(), bs.d2A_by_dXdX()
for d1 in range(3):
for d2 in range(3):
second_deriv = d2A_by_dXdX[idx, d1, d2]
err = 1e6
for i in range(5, 10):
eps = 0.5**i
ed2 = np.zeros((1, 3))
ed2[0, d2] = 1.
bs.set_points(points + eps * ed2)
dA_dXp = bs.dA_by_dX()[idx, d1]
bs.set_points(points - eps * ed2)
dA_dXm = bs.dA_by_dX()[idx, d1]
second_deriv_est = (dA_dXp - dA_dXm) / (2. * eps)
new_err = np.linalg.norm(second_deriv - second_deriv_est)
print("new_err", new_err)
assert new_err < 0.30 * err
err = new_err
"""
This example demonstrate how to compute surfaces in Boozer coordinates for a
magnetic field induced by coils.
We start with an initial guess that is just a tube around the magnetic axis,
then we reduce the Boozer residual with BFGS first, then drive it to machine
zero with a Levenberg-Marquardt algorithm. All of this is done while keeping
the surface area constant. We then switch the label to the Toroidal Flux, and
aim for a Boozer surface with three times larger flux.
"""
coils, currents, ma = get_ncsx_data()
stellarator = CoilCollection(coils, currents, 3, True)
coils = stellarator.coils
currents = stellarator.currents
bs = BiotSavart(coils, currents)
bs_tf = BiotSavart(coils, currents)
G0 = 2. * np.pi * np.sum(np.abs(bs.coil_currents)) * (4 * np.pi * 10**(-7) / (2 * np.pi))
mpol = 5 # try increasing this to 8 or 10 for smoother surfaces
ntor = 5 # try increasing this to 8 or 10 for smoother surfaces
stellsym = True
nfp = 3
phis = np.linspace(0, 1/nfp, 2*ntor+1, endpoint=False)
thetas = np.linspace(0, 1, 2*mpol+1, endpoint=False)
s = SurfaceXYZTensorFourier(
mpol=mpol, ntor=ntor, stellsym=stellsym, nfp=nfp, quadpoints_phi=phis, quadpoints_theta=thetas)
s.fit_to_curve(ma, 0.10, flip_theta=True)
iota = -0.4
def test_biotsavart_coil_current_taylortest(self):
coil0 = get_coil()
current0 = 1e4
coil1 = get_coil(perturb=True)
current1 = 1e3
bs = BiotSavart([coil0, coil1], [current0, current1])
points = np.asarray(
17 * [[-1.41513202e-03, 8.99999382e-01, -3.14473221e-04]])
bs.set_points(points)
B = bs.B()
J = bs.dB_by_dX()
H = bs.d2B_by_dXdX()
dB = bs.dB_by_dcoilcurrents()
dJ = bs.d2B_by_dXdcoilcurrents()
dH = bs.d3B_by_dXdXdcoilcurrents()
h = 1.
bs.currents_optim[0].set_dofs(1e4 + h)
bs.invalidate_cache()
Bp = bs.B()
Jp = bs.dB_by_dX()
Hp = bs.d2B_by_dXdX()
bs.currents_optim[0].set_dofs(1e4 - h)
bs.invalidate_cache()
Bm = bs.B()
Jm = bs.dB_by_dX()
Hm = bs.d2B_by_dXdX()
dB_approx = (Bp - Bm) / (2 * h)
dJ_approx = (Jp - Jm) / (2 * h)
dH_approx = (Hp - Hm) / (2 * h)
assert np.linalg.norm(dB[0] - dB_approx) < 1e-15
assert np.linalg.norm(dJ[0] - dJ_approx) < 1e-15
assert np.linalg.norm(dH[0] - dH_approx) < 1e-13
