diff --git a/.gitignore b/.gitignore
index f5fa96e0e..bf9806ab1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -20,4 +20,6 @@ tests/benchmarks/.benchmarks/
*.output
*.pdf
*.pyc
+*.swp
+*.swo
.pymon
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 51d9eee57..77497379f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -12,12 +12,14 @@ New Features
- Changes ``ToroidalFlux`` objective to default using a 1D loop integral of the vector potential
to compute the toroidal flux when possible, as opposed to a 2D surface integral of the magnetic field dotted with ``n_zeta``.
- Allow specification of Nyquist spectrum maximum modenumbers when using ``VMECIO.save`` to save a DESC .h5 file as a VMEC-format wout file
+- Added and tested infinite-n ideal-ballooning stability solver implemented as a part of the BallooningStability Objective. DESC can use reverse-mode AD to now optimize equilibria against infinite-n ideal ballooning modes.
- Add ``jac_chunk_size`` to ``ObjectiveFunction`` and ``_Objective`` to control the above chunk size for the ``fwd`` mode Jacobian calculation
- if ``None``, the chunk size is equal to ``dim_x``, so no chunking is done
- if an ``int``, this is the chunk size to be used.
- if ``"auto"`` for the ``ObjectiveFunction``, will use a heuristic for the maximum ``jac_chunk_size`` needed to fit the jacobian calculation on the available device memory, according to the formula: ``max_jac_chunk_size = (desc_config.get("avail_mem") / estimated_memory_usage - 0.22) / 0.85 * self.dim_x`` with ``estimated_memory_usage = 2.4e-7 * self.dim_f * self.dim_x + 1``
- the ``ObjectiveFunction`` ``jac_chunk_size`` is used if ``deriv_mode="batched"``, and the ``_Objective`` ``jac_chunk_size`` will be used if ``deriv_mode="blocked"``
+
Bug Fixes
- Fixes bugs that occur when saving asymmetric equilibria as wout files
diff --git a/desc/compute/_core.py b/desc/compute/_core.py
index 574cd062c..784e296f7 100644
--- a/desc/compute/_core.py
+++ b/desc/compute/_core.py
@@ -1547,24 +1547,6 @@ def _alpha_t(params, transforms, profiles, data, **kwargs):
return data
-@register_compute_fun(
- name="alpha_tt",
- label="\\partial_{\\theta \\theta} \\alpha",
- units="~",
- units_long="None",
- description="Field line label, second derivative wrt poloidal coordinate",
- dim=1,
- params=[],
- transforms={},
- profiles=[],
- coordinates="rtz",
- data=["theta_PEST_tt", "phi_tt", "iota"],
-)
-def _alpha_tt(params, transforms, profiles, data, **kwargs):
- data["alpha_tt"] = data["theta_PEST_tt"] - data["iota"] * data["phi_tt"]
- return data
-
-
@register_compute_fun(
name="alpha_tz",
label="\\partial_{\\theta \\zeta} \\alpha",
@@ -1601,12 +1583,30 @@ def _alpha_z(params, transforms, profiles, data, **kwargs):
return data
+@register_compute_fun(
+ name="alpha_tt",
+ label="\\partial_{\\theta \\theta} \\alpha",
+ units="~",
+ units_long="None",
+ description="Field line label, second-order derivative wrt poloidal coordinate",
+ dim=1,
+ params=[],
+ transforms={},
+ profiles=[],
+ coordinates="rtz",
+ data=["phi_tt", "iota", "theta_PEST_tt"],
+)
+def _alpha_tt(params, transforms, profiles, data, **kwargs):
+ data["alpha_tt"] = data["theta_PEST_tt"] - data["iota"] * data["phi_tt"]
+ return data
+
+
@register_compute_fun(
name="alpha_zz",
label="\\partial_{\\zeta \\zeta} \\alpha",
units="~",
units_long="None",
- description="Field line label, second derivative wrt toroidal coordinate",
+ description="Field line label, second-order derivative wrt toroidal coordinate",
dim=1,
params=[],
transforms={},
@@ -3105,8 +3105,8 @@ def _theta_PEST_r(params, transforms, profiles, data, **kwargs):
label="\\partial_{\\rho \\theta} \\vartheta",
units="rad",
units_long="radians",
- description="PEST straight field line poloidal angular coordinate, derivative wrt "
- "radial and DESC poloidal coordinate",
+ description="PEST straight field line poloidal angular coordinate,"
+ "derivative wrt poloidal and radial coordinate",
dim=1,
params=[],
transforms={},
@@ -3201,8 +3201,8 @@ def _theta_PEST_t(params, transforms, profiles, data, **kwargs):
label="\\partial_{\\theta \\theta} \\vartheta",
units="rad",
units_long="radians",
- description="PEST straight field line poloidal angular coordinate, second "
- "derivative wrt poloidal coordinate",
+ description="PEST straight field line poloidal angular coordinate,"
+ "second derivative wrt poloidal coordinate",
dim=1,
params=[],
transforms={},
@@ -3277,8 +3277,8 @@ def _theta_PEST_tzz(params, transforms, profiles, data, **kwargs):
label="\\partial_{\\zeta} \\vartheta",
units="rad",
units_long="radians",
- description="PEST straight field line poloidal angular coordinate, derivative wrt "
- "toroidal coordinate",
+ description="PEST straight field line poloidal angular coordinate,"
+ " derivative wrt toroidal coordinate",
dim=1,
params=[],
transforms={},
diff --git a/desc/compute/_metric.py b/desc/compute/_metric.py
index ed4ea4814..da4353ad0 100644
--- a/desc/compute/_metric.py
+++ b/desc/compute/_metric.py
@@ -83,7 +83,7 @@ def _sqrtg_clebsch(params, transforms, profiles, data, **kwargs):
@register_compute_fun(
name="|e_theta x e_zeta|",
- label="|\\mathbf{e}_{\\theta} \\times \\mathbf{e}_{\\zeta}|",
+ label="| \\mathbf{e}_{\\theta} \\times \\mathbf{e}_{\\zeta} |",
units="m^{2}",
units_long="square meters",
description="2D Jacobian determinant for constant rho surface",
@@ -141,7 +141,7 @@ def _e_theta_x_e_zeta_r(params, transforms, profiles, data, **kwargs):
@register_compute_fun(
name="|e_theta x e_zeta|_rr",
- label="\\partial_{\\rho\\rho} |\\mathbf{e}_{\\theta} \\times \\mathbf{e}_{\\zeta}|",
+ label="\\partial_{\\rho\\rho}|\\mathbf{e}_{\\theta}\\times\\mathbf{e}_{\\zeta}|",
units="m^{2}",
units_long="square meters",
description="2D Jacobian determinant for constant rho surface"
@@ -180,7 +180,7 @@ def _e_theta_x_e_zeta_rr(params, transforms, profiles, data, **kwargs):
@register_compute_fun(
name="|e_theta x e_zeta|_z",
- label="\\partial_{\\zeta}|e_{\\theta} \\times e_{\\zeta}|",
+ label="\\partial_{\\zeta}|\\mathbf{e}_{\\theta} \\times \\mathbf{e}_{\\zeta}|",
units="m^{2}",
units_long="square meters",
description="2D Jacobian determinant for constant rho surface,"
@@ -1443,6 +1443,44 @@ def _g_sup_rr_r(params, transforms, profiles, data, **kwargs):
return data
+@register_compute_fun(
+ name="g^rr_t",
+ label="\\partial_{\\theta} g^{\\rho \\rho}",
+ units="m^-2",
+ units_long="inverse square meters",
+ description="Radial/Radial element of contravariant metric tensor, "
+ + "first poloidal derivative",
+ dim=1,
+ params=[],
+ transforms={},
+ profiles=[],
+ coordinates="rtz",
+ data=["e^rho", "e^rho_t"],
+)
+def _g_sup_rr_t(params, transforms, profiles, data, **kwargs):
+ data["g^rr_t"] = 2 * dot(data["e^rho_t"], data["e^rho"])
+ return data
+
+
+@register_compute_fun(
+ name="g^rr_z",
+ label="\\partial_{\\zeta} g^{\\rho \\rho}",
+ units="m^-2",
+ units_long="inverse square meters",
+ description="Radial/Radial element of contravariant metric tensor, "
+ + "first toroidal derivative",
+ dim=1,
+ params=[],
+ transforms={},
+ profiles=[],
+ coordinates="rtz",
+ data=["e^rho", "e^rho_z"],
+)
+def _g_sup_rr_z(params, transforms, profiles, data, **kwargs):
+ data["g^rr_z"] = 2 * dot(data["e^rho_z"], data["e^rho"])
+ return data
+
+
@register_compute_fun(
name="g^rt_r",
label="\\partial_{\\rho} g^{\\rho \\theta}",
@@ -1544,25 +1582,6 @@ def _g_sup_zz_r(params, transforms, profiles, data, **kwargs):
return data
-@register_compute_fun(
- name="g^rr_t",
- label="\\partial_{\\theta} g^{\\rho \\rho}",
- units="m^-2",
- units_long="inverse square meters",
- description="Radial/Radial element of contravariant metric tensor, "
- + "first poloidal derivative",
- dim=1,
- params=[],
- transforms={},
- profiles=[],
- coordinates="rtz",
- data=["e^rho", "e^rho_t"],
-)
-def _g_sup_rr_t(params, transforms, profiles, data, **kwargs):
- data["g^rr_t"] = 2 * dot(data["e^rho_t"], data["e^rho"])
- return data
-
-
@register_compute_fun(
name="g^rt_t",
label="\\partial_{\\theta} g^{\\rho \\theta}",
@@ -1664,25 +1683,6 @@ def _g_sup_zz_t(params, transforms, profiles, data, **kwargs):
return data
-@register_compute_fun(
- name="g^rr_z",
- label="\\partial_{\\zeta} g^{\\rho \\rho}",
- units="m^-2",
- units_long="inverse square meters",
- description="Radial/Radial element of contravariant metric tensor, "
- + "first toroidal derivative",
- dim=1,
- params=[],
- transforms={},
- profiles=[],
- coordinates="rtz",
- data=["e^rho", "e^rho_z"],
-)
-def _g_sup_rr_z(params, transforms, profiles, data, **kwargs):
- data["g^rr_z"] = 2 * dot(data["e^rho_z"], data["e^rho"])
- return data
-
-
@register_compute_fun(
name="g^rt_z",
label="\\partial_{\\zeta} g^{\\rho \\theta}",
@@ -1900,6 +1900,42 @@ def _gradzeta(params, transforms, profiles, data, **kwargs):
return data
+@register_compute_fun(
+ name="g^aa",
+ label="g^{\\alpha \\alpha}",
+ units="m^{-2}",
+ units_long="inverse square meters",
+ description="Contravariant metric tensor grad alpha dot grad alpha",
+ dim=1,
+ params=[],
+ transforms={},
+ profiles=[],
+ coordinates="rtz",
+ data=["grad(alpha)"],
+)
+def _g_sup_aa(params, transforms, profiles, data, **kwargs):
+ data["g^aa"] = dot(data["grad(alpha)"], data["grad(alpha)"])
+ return data
+
+
+@register_compute_fun(
+ name="g^ra",
+ label="g^{\\rho \\alpha}",
+ units="m^{-2}",
+ units_long="inverse square meters",
+ description="Contravariant metric tensor grad rho dot grad alpha",
+ dim=1,
+ params=[],
+ transforms={},
+ profiles=[],
+ coordinates="rtz",
+ data=["grad(alpha)", "e^rho"],
+)
+def _g_sup_ra(params, transforms, profiles, data, **kwargs):
+ data["g^ra"] = dot(data["grad(alpha)"], data["e^rho"])
+ return data
+
+
@register_compute_fun(
name="gbdrift",
# Exact definition of the magnetic drifts taken from
@@ -1967,10 +2003,13 @@ def _cvdrift(params, transforms, profiles, data, **kwargs):
transforms={},
profiles=[],
coordinates="rtz",
- data=["|B|^2", "b", "e^rho", "grad(|B|)"],
+ data=["rho", "|B|^2", "b", "e^rho", "grad(|B|)"],
)
def _cvdrift0(params, transforms, profiles, data, **kwargs):
data["cvdrift0"] = (
- 1 / data["|B|^2"] * (dot(data["b"], cross(data["grad(|B|)"], data["e^rho"])))
+ 2
+ * data["rho"]
+ / data["|B|^2"]
+ * (dot(data["b"], cross(data["grad(|B|)"], data["e^rho"])))
)
return data
diff --git a/desc/compute/_stability.py b/desc/compute/_stability.py
index 1757fee0b..fc773674e 100644
--- a/desc/compute/_stability.py
+++ b/desc/compute/_stability.py
@@ -11,7 +11,7 @@
from scipy.constants import mu_0
-from desc.backend import jnp
+from desc.backend import jit, jnp, scan, vmap
from ..integrals.surface_integral import surface_integrals_map
from ..utils import dot
@@ -232,3 +232,399 @@ def _magnetic_well(params, transforms, profiles, data, **kwargs):
0, # coefficient of limit is V_r / V_rr, rest is finite
)
return data
+
+
+@register_compute_fun(
+ name="ideal ballooning lambda",
+ label="\\lambda_{\\mathrm{ballooning}}=\\gamma^2",
+ units="~",
+ units_long="None",
+ description="Normalized squared ideal ballooning growth rate, "
+ "requires data along a field line",
+ dim=1,
+ params=["Psi"],
+ transforms={"grid": []},
+ profiles=[],
+ coordinates="rtz",
+ data=[
+ "a",
+ "g^aa",
+ "g^ra",
+ "g^rr",
+ "cvdrift",
+ "cvdrift0",
+ "|B|",
+ "B^zeta",
+ "p_r",
+ "iota",
+ "shear",
+ "psi",
+ "psi_r",
+ "rho",
+ ],
+ source_grid_requirement={"coordinates": "raz", "is_meshgrid": True},
+ zeta0="array: points of vanishing integrated local shear to scan over. "
+ "Default 15 points linearly spaced in [-π/2,π/2]",
+)
+def _ideal_ballooning_gamma2(params, transforms, profiles, data, **kwargs):
+ """
+ Ideal-ballooning growth rate finder.
+
+ This function uses a finite-difference method
+ to calculate the maximum growth rate against the
+ infinite-n ideal ballooning mode. The equation being solved is
+
+ d/dζ(g dX/dζ) + c X = λ f X, g, f > 0
+
+ where
+
+ 𝛋 = b ⋅∇ b
+ g = a_N^3 * B_N * (b ⋅∇ζ) * (dψ_N/dρ)² * |∇α|², / B,
+ c = a_N^3 * B_N * (1/ b ⋅∇ζ) * (dψ_N/dρ)² * dp/dψ * (b × 𝛋) ⋅|∇α|/ B**2,
+ f = a_N * B_N^3 * (dψ_N/dρ)² * |∇α|² / B^3 * (1/ b ⋅∇ζ) ,
+
+ are needed along a field line to solve the ballooning equation once and
+ find
+
+ λ = a_N^2 / v_A^2 * γ²,
+
+ where
+
+ v_A = B_N /sqrt(mu_0 * n0 * M) is the Alfven speed, and
+ ψ_N = ψ/ψ_b is the normalized toroidal flux, and
+ ψ_b = 0.5*(B_N * a_N**2) is the total enclosed toroidal flux.
+
+ To obtain the parameters g, c, and f, we need a set of parameters
+ provided in the list ``data`` above. Here's a description of
+ these parameters:
+
+ - a: minor radius of the device
+ - g^aa: |grad alpha|^2, field line bending term
+ - g^ra: (grad alpha dot grad rho) integrated local shear
+ - g^rr: |grad rho|^2 flux expansion term
+ - cvdrift: geometric factor of the curvature drift
+ - cvdrift0: geometric factor of curvature drift 2
+ - |B|: magnitude of the magnetic field
+ - B^zeta: B dot grad zeta
+ - p_r: dp/drho, pressure gradient
+ - phi: coordinate describing the position in the toroidal angle
+ along a field line
+ """
+ source_grid = transforms["grid"].source_grid
+ # Vectorize in rho later
+ rho = source_grid.meshgrid_reshape(data["rho"], "arz")
+
+ psi_b = params["Psi"] / (2 * jnp.pi)
+ a_N = data["a"]
+ B_N = 2 * psi_b / a_N**2
+
+ zeta0 = kwargs.get("zeta0", jnp.linspace(-0.5 * jnp.pi, 0.5 * jnp.pi, 15))
+ N_zeta0 = len(zeta0)
+
+ # This would fail with rho vectorization
+ iota = jnp.mean(data["iota"])
+ shear = jnp.mean(data["shear"])
+ psi = jnp.mean(data["psi"])
+ sign_psi = jnp.sign(psi)
+ sign_iota = jnp.sign(iota)
+
+ N_rho = int(source_grid.num_rho)
+ N_alpha = int(source_grid.num_alpha)
+
+ # phi is the same for each alpha
+ phi = source_grid.nodes[:: N_rho * N_alpha, 2]
+ N_zeta = len(phi)
+
+ B = source_grid.meshgrid_reshape(data["|B|"], "arz")
+ B_sup_zeta = source_grid.meshgrid_reshape(data["B^zeta"], "arz")
+ gradpar = B_sup_zeta / B
+
+ # This would fail with rho vectorization
+ dpdpsi = jnp.mean(mu_0 * data["p_r"] / data["psi_r"])
+
+ g_sup_aa = source_grid.meshgrid_reshape(data["g^aa"], "arz")[None, ...]
+ g_sup_ra = source_grid.meshgrid_reshape(data["g^ra"], "arz")[None, ...]
+ g_sup_rr = source_grid.meshgrid_reshape(data["g^rr"], "arz")[None, ...]
+
+ gds2 = jnp.reshape(
+ rho**2
+ * (
+ g_sup_aa
+ - 2 * sign_iota * shear / rho * zeta0[:, None, None, None] * g_sup_ra
+ + zeta0[:, None, None, None] ** 2 * (shear / rho) ** 2 * g_sup_rr
+ ),
+ (N_alpha, N_zeta0, N_zeta),
+ )
+
+ f = a_N * B_N**3 * gds2 / B**3 * 1 / gradpar
+ g = a_N**3 * B_N * gds2 / B * gradpar
+ g_half = (g[:, :, 1:] + g[:, :, :-1]) / 2
+
+ cvdrift = source_grid.meshgrid_reshape(data["cvdrift"], "arz")[None, ...]
+ cvdrift0 = source_grid.meshgrid_reshape(data["cvdrift0"], "arz")[None, ...]
+
+ c = (
+ a_N**3
+ * B_N
+ * jnp.reshape(
+ 2
+ / B_sup_zeta[None, ...]
+ * sign_psi
+ * rho**2
+ * dpdpsi
+ * (cvdrift - shear / (2 * rho**2) * zeta0[:, None, None, None] * cvdrift0),
+ (N_alpha, N_zeta0, N_zeta),
+ )
+ )
+
+ h = phi[1] - phi[0]
+
+ i = jnp.arange(N_alpha)[:, None, None, None]
+ l = jnp.arange(N_zeta0)[None, :, None, None]
+ j = jnp.arange(N_zeta - 2)[None, None, :, None]
+ k = jnp.arange(N_zeta - 2)[None, None, None, :]
+
+ A = jnp.zeros((N_alpha, N_zeta0, N_zeta - 2, N_zeta - 2))
+ B_inv = jnp.zeros((N_alpha, N_zeta0, N_zeta - 2, N_zeta - 2))
+
+ A = A.at[i, l, j, k].set(
+ g_half[i, l, k] / h**2 * (j - k == -1)
+ + (-(g_half[i, l, j + 1] + g_half[i, l, j]) / h**2 + c[i, l, j + 1])
+ * (j - k == 0)
+ + g_half[i, l, j] / h**2 * (j - k == 1)
+ )
+
+ B_inv = B_inv.at[i, l, j, k].set(1 / jnp.sqrt(f[i, l, j + 1]) * (j - k == 0))
+
+ A_redo = B_inv @ A @ jnp.transpose(B_inv, axes=(0, 1, 3, 2))
+
+ w, _ = jnp.linalg.eigh(A_redo)
+ # max over "zeta" axis, still a function of rho, alpha, zeta0
+ gamma = jnp.real(jnp.max(w, axis=(2,)))
+
+ data["ideal ballooning lambda"] = gamma.flatten()
+
+ return data
+
+
+@register_compute_fun(
+ name="Newcomb ballooning metric",
+ label="\\mathrm{Newcomb-ballooning-metric}",
+ units="~",
+ units_long="None",
+ description="A measure of Newcomb's distance from marginal ballooning stability",
+ dim=1,
+ params=["Psi"],
+ transforms={"grid": []},
+ profiles=[],
+ coordinates="rtz",
+ data=[
+ "a",
+ "g^aa",
+ "g^ra",
+ "g^rr",
+ "cvdrift",
+ "cvdrift0",
+ "|B|",
+ "B^zeta",
+ "p_r",
+ "iota",
+ "shear",
+ "psi",
+ "psi_r",
+ "rho",
+ ],
+ source_grid_requirement={"coordinates": "raz", "is_meshgrid": True},
+ zeta0="array: points of vanishing integrated local shear to scan over. "
+ "Default 15 points linearly spaced in [-π/2,π/2]",
+)
+def _Newcomb_ball_metric(params, transforms, profiles, data, **kwargs):
+ """
+ Ideal-ballooning growth rate proxy.
+
+ This function uses a finite-difference method to integrate the
+ marginal stability ideal-ballooning equation
+
+ d/dζ(g dX/dζ) + c X = 0, g > 0
+
+ using the Newcomb's stability criterion. The geometric factors
+
+ 𝛋 = b ⋅∇ b
+ g = a_N^3 * B_N * (b ⋅∇ζ) * (dψ_N/dρ)² * |∇α|², / B,
+ c = a_N^3 * B_N * (1/ b ⋅∇ζ) * (dψ_N/dρ)² * dp/dψ * (b × 𝛋) ⋅|∇α|/ B**2,
+
+ are needed along a field line to solve the ballooning equation and
+ ψ_N = ψ/ψ_b is the normalized toroidal flux, and
+ ψ_b = 0.5*(B_N * a_N**2) is the enclosed toroidal flux by the boundary.
+
+ To obtain the parameters g, c, and f, we need a set of parameters
+ provided in the list ``data`` above. Here's a description of
+ these parameters:
+
+ - a: minor radius of the device
+ - g^aa: |grad alpha|^2, field line bending term
+ - g^ra: (grad alpha dot grad rho) integrated local shear
+ - g^rr: |grad rho|^2 flux expansion term
+ - cvdrift: geometric factor of the curvature drift
+ - cvdrift0: geometric factor of curvature drift 2
+ - |B|: magnitude of the magnetic field
+ - B^zeta: B dot grad zeta
+ - p_r: dp/drho, pressure gradient
+ - psi_r: radial gradient of the toroidal flux
+ - phi: coordinate describing the position in the toroidal angle
+ along a field line
+
+ Here's how we define the Newcomb metric:
+ If zero crossing is at -inf (root finder failed), use the Y coordinate
+ as a metric of stability else use the zero-crossing point on the X-axis
+ as the metric
+ This idea behind Newcomb's method is explained further in Appendix D of
+ [Gaur _et al._](https://doi.org/10.1017/S0022377823000107)
+ """
+ source_grid = transforms["grid"].source_grid
+ # Vectorize in rho later
+ rho = source_grid.meshgrid_reshape(data["rho"], "arz")
+
+ psi_b = params["Psi"] / (2 * jnp.pi)
+ a_N = data["a"]
+ B_N = 2 * psi_b / a_N**2
+
+ zeta0 = kwargs.get("zeta0", jnp.linspace(-0.5 * jnp.pi, 0.5 * jnp.pi, 15))
+ N_zeta0 = len(zeta0)
+
+ # This would fail with rho vectorization
+ iota = jnp.mean(data["iota"])
+ shear = jnp.mean(data["shear"])
+ psi = jnp.mean(data["psi"])
+ sign_psi = jnp.sign(psi)
+ sign_iota = jnp.sign(iota)
+
+ N_rho = int(source_grid.num_rho)
+ N_alpha = int(source_grid.num_alpha)
+
+ # phi is the same for each alpha
+ phi = source_grid.nodes[:: N_rho * N_alpha, 2]
+ N_zeta = len(phi)
+
+ B = source_grid.meshgrid_reshape(data["|B|"], "arz")
+ B_sup_zeta = source_grid.meshgrid_reshape(data["B^zeta"], "arz")
+ gradpar = B_sup_zeta / B
+
+ dpdpsi = source_grid.meshgrid_reshape(mu_0 * data["p_r"] / data["psi_r"], "arz")
+
+ g_sup_aa = source_grid.meshgrid_reshape(data["g^aa"], "arz")[None, :]
+ g_sup_ra = source_grid.meshgrid_reshape(data["g^ra"], "arz")[None, :]
+ g_sup_rr = source_grid.meshgrid_reshape(data["g^rr"], "arz")[None, :]
+
+ gds2 = jnp.reshape(
+ rho**2
+ * (
+ g_sup_aa
+ - 2 * sign_iota * shear / rho * zeta0[:, None] * g_sup_ra
+ + zeta0[:, None] ** 2 * (shear / rho) ** 2 * g_sup_rr
+ ),
+ (N_alpha, N_zeta0, N_zeta),
+ )
+
+ g = a_N**3 * B_N * gds2 / B * gradpar
+ g_half = (g[:, :, 1:] + g[:, :, :-1]) / 2
+
+ cvdrift = source_grid.meshgrid_reshape(data["cvdrift"], "arz")[None, :]
+ cvdrift0 = source_grid.meshgrid_reshape(data["cvdrift0"], "arz")[None, :]
+
+ c = (
+ a_N**3
+ * B_N
+ * jnp.reshape(
+ 2
+ / B_sup_zeta[None, :]
+ * sign_psi
+ * rho**2
+ * dpdpsi
+ * (cvdrift - shear / (2 * rho**2) * zeta0[:, None] * cvdrift0),
+ (N_alpha, N_zeta0, N_zeta),
+ )
+ )
+
+ h = phi[1] - phi[0]
+
+ # g_half on half grid points, c_full on full grid points
+ g_half = (g[:, :, 1:] + g[:, :, :-1]) / 2
+ c_full = c[:, :, :-1]
+
+ i = jnp.arange(N_alpha)[:, None, None]
+ j = jnp.arange(N_zeta0)[None, :, None]
+ k = jnp.arange(N_zeta - 1)[None, None, :]
+
+ X = jnp.zeros((N_alpha, N_zeta0, N_zeta - 1))
+ X = X.at[i, j, k].set(phi[k])
+
+ Y = jnp.zeros((N_alpha, N_zeta0))
+ eps = 5e-3 # slope of the test functio
+ Yp = eps * jnp.ones((N_alpha, N_zeta0))
+
+ @jit
+ def integrator(carry, x):
+ y, dy = carry
+ g_element, c_element = x
+ # Update the array (Y) and its derivative on scattered grids and
+ # integrate using leapfrog-like method.
+ y_new = y + h * dy / g_element
+ dy_new = dy - c_element * y_new * h
+ # y starts at 0 with positive slope. If y goes negative it's unstable,
+ # so we look for a sign change.
+ sign_change = y_new < 0.0
+ return (y_new, dy_new), (y_new, sign_change)
+
+ @jit
+ def cumulative_update_jit(y, dy, g_half, c_full):
+ _, scan_output = scan(integrator, (y, dy), (g_half, c_full))
+ Y, sign_change = scan_output
+ # argmax of boolean array returns index if first True, where y goes negative
+ first_negative_index = jnp.argmax(sign_change)
+ # return last index if there are no sign crossings
+ first_negative_index = jnp.where(
+ ~jnp.any(sign_change),
+ -1,
+ first_negative_index,
+ )
+ # slope of Y where it crosses 0
+ slope = (Y[first_negative_index] - Y[first_negative_index - 1]) / h
+ # This factor will give us the exact X point of intersection
+ lin_interp_factor = jnp.where(
+ first_negative_index != -1,
+ -Y[first_negative_index - 1] / slope,
+ 0,
+ )
+
+ return Y, first_negative_index, lin_interp_factor
+
+ # Vectorize over the first two dimensions
+ vectorized_cumulative_update = jit(vmap(vmap(cumulative_update_jit)))
+ Y, first_negative_indices, lin_interp_factors = vectorized_cumulative_update(
+ Y, Yp, g_half, c_full
+ )
+
+ # x at crossing pts, or last value of x if there were no crossings
+ X0 = jnp.zeros((N_alpha, N_zeta0))
+ i0 = jnp.arange(N_alpha)[:, None]
+ j0 = jnp.arange(N_zeta0)[None, :]
+ X0 = X0.at[i0, j0].set(
+ X[i0, j0, first_negative_indices[i0, j0]] + lin_interp_factors[i0, j0] * h
+ )
+ # where X0 < phimax, it means there was a zero crossing so its unstable. We take
+ # the distance from X0 to phimax as the distance to stability. If there was no
+ # crossing we take Y[phi=phimax]. This gives a continuous metric, though
+ # the first derivative will be discontinuous. Could maybe think of something better?
+ # RG: Peak of the metric doesn't match mean peak of the growth rate in rho
+ metric = jnp.where(
+ first_negative_indices != -1,
+ # if it crossed, then X0 < phimax, so this < 0
+ (X0 - jnp.max(phi)) / jnp.ptp(phi),
+ # if it reached the end without crossing, this is >=0
+ Y[:, :, -1],
+ )
+
+ data["Newcomb ballooning metric"] = jnp.min(metric)
+
+ return data
diff --git a/desc/equilibrium/coords.py b/desc/equilibrium/coords.py
index d46ae8474..7e50a71a6 100644
--- a/desc/equilibrium/coords.py
+++ b/desc/equilibrium/coords.py
@@ -674,10 +674,10 @@ def get_rtz_grid(
jitable=True,
**kwargs,
):
- """Return DESC grid in rtz (rho, theta, zeta) coordinates from given coordinates.
+ """Return DESC grid in (rho, theta, zeta) coordinates from given coordinates.
- Create a tensor-product grid from the given coordinates, and return the same grid
- in DESC coordinates.
+ Create a tensor-product grid from the given coordinates, and return the same
+ grid in DESC coordinates.
Parameters
----------
diff --git a/desc/equilibrium/equilibrium.py b/desc/equilibrium/equilibrium.py
index dd85b123c..f5ce69b3b 100644
--- a/desc/equilibrium/equilibrium.py
+++ b/desc/equilibrium/equilibrium.py
@@ -51,7 +51,7 @@
)
from ..compute.data_index import is_0d_vol_grid, is_1dr_rad_grid, is_1dz_tor_grid
-from .coords import is_nested, map_coordinates, to_sfl
+from .coords import get_rtz_grid, is_nested, map_coordinates, to_sfl
from .initial_guess import set_initial_guess
from .utils import parse_axis, parse_profile, parse_surface
@@ -1221,6 +1221,43 @@ def map_coordinates(
**kwargs,
)
+ def get_rtz_grid(
+ self, radial, poloidal, toroidal, coordinates, period, jitable=True, **kwargs
+ ):
+ """Return DESC grid in (rho, theta, zeta) coordinates from given coordinates.
+
+ Create a tensor-product grid from the given coordinates, and return the same
+ grid in DESC coordinates.
+
+ Parameters
+ ----------
+ radial : ndarray
+ Sorted unique radial coordinates.
+ poloidal : ndarray
+ Sorted unique poloidal coordinates.
+ toroidal : ndarray
+ Sorted unique toroidal coordinates.
+ coordinates : str
+ Input coordinates that are specified by the arguments, respectively.
+ raz : rho, alpha, zeta
+ rvp : rho, theta_PEST, phi
+ rtz : rho, theta, zeta
+ period : tuple of float
+ Assumed periodicity for each quantity in inbasis.
+ Use np.inf to denote no periodicity.
+ jitable : bool, optional
+ If false the returned grid has additional attributes.
+ Required to be false to retain nodes at magnetic axis.
+
+ Returns
+ -------
+ desc_grid : Grid
+ DESC coordinate grid for the given coordinates.
+ """
+ return get_rtz_grid(
+ self, radial, poloidal, toroidal, coordinates, period, jitable, **kwargs
+ )
+
def compute_theta_coords(
self, flux_coords, L_lmn=None, tol=1e-6, maxiter=20, full_output=False, **kwargs
):
diff --git a/desc/objectives/__init__.py b/desc/objectives/__init__.py
index 0fb9ce132..1504dbdd7 100644
--- a/desc/objectives/__init__.py
+++ b/desc/objectives/__init__.py
@@ -40,7 +40,7 @@
)
from ._power_balance import FusionPower, HeatingPowerISS04
from ._profiles import Pressure, RotationalTransform, Shear, ToroidalCurrent
-from ._stability import MagneticWell, MercierStability
+from ._stability import BallooningStability, MagneticWell, MercierStability
from .getters import (
get_equilibrium_objective,
get_fixed_axis_constraints,
diff --git a/desc/objectives/_stability.py b/desc/objectives/_stability.py
index 8229eddda..600359b40 100644
--- a/desc/objectives/_stability.py
+++ b/desc/objectives/_stability.py
@@ -2,10 +2,11 @@
import numpy as np
-from desc.compute import get_profiles, get_transforms
+from desc.backend import jnp
+from desc.compute import get_params, get_profiles, get_transforms
from desc.compute.utils import _compute as compute_fun
from desc.grid import LinearGrid
-from desc.utils import Timer, warnif
+from desc.utils import Timer, errorif, setdefault, warnif
from .normalization import compute_scaling_factors
from .objective_funs import _Objective
@@ -385,6 +386,7 @@ def compute(self, params, constants=None):
"""
if constants is None:
constants = self.constants
+
data = compute_fun(
"desc.equilibrium.equilibrium.Equilibrium",
self._data_keys,
@@ -393,3 +395,289 @@ def compute(self, params, constants=None):
profiles=constants["profiles"],
)
return constants["transforms"]["grid"].compress(data["magnetic well"])
+
+
+class BallooningStability(_Objective):
+ """A type of ideal MHD instability.
+
+ Infinite-n ideal MHD ballooning modes are of significant interest.
+ These instabilities are also related to smaller-scale kinetic instabilities.
+ With this class, we optimize MHD equilibria against the ideal ballooning mode.
+
+ Targets the following metric:
+
+ f = w₀ sum(ReLU(λ-λ₀)) + w₁ max(ReLU(λ-λ₀))
+
+ where λ is the negative squared growth rate for each field line (such that λ>0 is
+ unstable), λ₀ is a cutoff, and w₀ and w₁ are weights.
+
+ Parameters
+ ----------
+ eq : Equilibrium
+ Equilibrium that will be optimized to satisfy the Objective.
+ target : {float, ndarray}, optional
+ Target value(s) of the objective. Only used if bounds is None.
+ Must be broadcastable to Objective.dim_f. Default is ``target=0``
+ bounds : tuple of {float, ndarray}, optional
+ Lower and upper bounds on the objective. Overrides target.
+ Both bounds must be broadcastable to to Objective.dim_f. Default is ``target=0``
+ weight : {float, ndarray}, optional
+ Weighting to apply to the Objective, relative to other Objectives.
+ Must be broadcastable to to Objective.dim_f
+ normalize : bool, optional
+ Whether to compute the error in physical units or non-dimensionalize.
+ Not used since the growth rate is always normalized.
+ normalize_target : bool, optional
+ Whether target and bounds should be normalized before comparing to computed
+ values. If `normalize` is `True` and the target is in physical units,
+ this should also be set to True. Not used since the growth rate is always
+ normalized.
+ loss_function : {None, 'mean', 'min', 'max'}, optional
+ Loss function to apply to the objective values once computed. This loss function
+ is called on the raw compute value, before any shifting, scaling, or
+ normalization. Has no effect for this objective.
+ deriv_mode : {"auto", "fwd", "rev"}
+ Specify how to compute jacobian matrix, either forward mode or reverse mode AD.
+ "auto" selects forward or reverse mode based on the size of the input and output
+ of the objective. Has no effect on self.grad or self.hess which always use
+ reverse mode and forward over reverse mode respectively.
+ rho : float
+ Flux surface to optimize on. To optimize over multiple surfaces, use multiple
+ objectives each with a single rho value.
+ alpha : float, ndarray
+ Field line labels to optimize. Values should be in [0, 2pi). Default is alpha=0
+ for axisymmetric equilibria, or 8 field lines linearly spaced in [0, pi] for
+ non-axisymmetric cases.
+ nturns : int
+ Number of toroidal transits of a field line to consider. Field line
+ will run from -π*nturns to π*nturns. Default 3.
+ nzetaperturn : int
+ Number of points along the field line per toroidal transit. Total number of
+ points is ``nturns*nzetaperturn``. Default 100.
+ zeta0 : array-like
+ Points of vanishing integrated local shear to scan over.
+ Default 15 points in [-π/2,π/2]
+ lambda0 : float
+ Threshold for penalizing growth rates in metric above.
+ w0, w1 : float
+ Weights for sum and max terms in metric above.
+ name : str, optional
+ Name of the objective function.
+
+ """
+
+ _coordinates = "" # not vectorized over rho, always a scalar
+ _scalar = True
+ _units = "(dimensionless)"
+ _print_value_fmt = "Ideal ballooning lambda: "
+
+ def __init__(
+ self,
+ eq,
+ target=None,
+ bounds=None,
+ weight=1,
+ normalize=True,
+ normalize_target=True,
+ loss_function=None,
+ deriv_mode="auto",
+ rho=0.5,
+ alpha=None,
+ nturns=3,
+ nzetaperturn=200,
+ zeta0=None,
+ lambda0=0.0,
+ w0=1.0,
+ w1=10.0,
+ name="ideal ballooning lambda",
+ ):
+ if target is None and bounds is None:
+ target = 0
+
+ self._rho = rho
+ self._alpha = alpha
+ self._nturns = nturns
+ self._nzetaperturn = nzetaperturn
+ self._zeta0 = zeta0
+ self._lambda0 = lambda0
+ self._w0 = w0
+ self._w1 = w1
+
+ super().__init__(
+ things=eq,
+ target=target,
+ bounds=bounds,
+ weight=weight,
+ normalize=normalize,
+ normalize_target=normalize_target,
+ loss_function=loss_function,
+ deriv_mode=deriv_mode,
+ name=name,
+ )
+
+ errorif(
+ np.asarray(self._rho).size > 1,
+ ValueError,
+ "BallooningStability objective only works on a single surface. "
+ "To optimize multiple surfaces, use multiple instances of the objective.",
+ )
+
+ def build(self, eq=None, use_jit=True, verbose=1):
+ """Build constant arrays.
+
+ Parameters
+ ----------
+ eq : Equilibrium, optional
+ Equilibrium that will be optimized to satisfy the Objective.
+ use_jit : bool, optional
+ Whether to just-in-time compile the objective and derivatives.
+ verbose : int, optional
+ Level of output.
+
+ """
+ eq = self.things[0]
+
+ # we need a uniform grid to get correct surface averages for iota
+ iota_grid = LinearGrid(
+ rho=self._rho,
+ M=eq.M_grid,
+ N=eq.N_grid,
+ NFP=eq.NFP,
+ )
+ self._iota_keys = ["iota", "iota_r", "shear"]
+ iota_profiles = get_profiles(self._iota_keys, obj=eq, grid=iota_grid)
+ iota_transforms = get_transforms(self._iota_keys, obj=eq, grid=iota_grid)
+
+ # Separate grid to calculate the right length scale for normalization
+ len_grid = LinearGrid(rho=1.0, M=eq.M_grid, N=eq.N_grid, NFP=eq.NFP)
+ self._len_keys = ["a"]
+ len_profiles = get_profiles(self._len_keys, obj=eq, grid=len_grid)
+ len_transforms = get_transforms(self._len_keys, obj=eq, grid=len_grid)
+
+ # make a set of nodes along a single fieldline
+ zeta = jnp.linspace(
+ -jnp.pi * self._nturns,
+ jnp.pi * self._nturns,
+ self._nturns * self._nzetaperturn,
+ )
+
+ # set alpha/zeta0 grids
+ self._alpha = setdefault(
+ self._alpha,
+ (
+ jnp.linspace(0, jnp.pi, 8)
+ if eq.N != 0 and eq.sym is True
+ else (
+ jnp.linspace(0, 2 * np.pi, 16)
+ if eq.N != 0 and eq.sym is False
+ else jnp.array(0.0)
+ )
+ ),
+ )
+
+ self._zeta0 = setdefault(
+ self._zeta0, jnp.linspace(-0.5 * jnp.pi, 0.5 * jnp.pi, 15)
+ )
+ self._dim_f = 1
+ self._data_keys = ["ideal ballooning lambda"]
+
+ self._args = get_params(
+ self._iota_keys + self._len_keys + self._data_keys,
+ obj="desc.equilibrium.equilibrium.Equilibrium",
+ has_axis=False,
+ )
+
+ self._constants = {
+ "iota_transforms": iota_transforms,
+ "iota_profiles": iota_profiles,
+ "len_transforms": len_transforms,
+ "len_profiles": len_profiles,
+ "rho": self._rho,
+ "alpha": self._alpha,
+ "zeta": zeta,
+ "zeta0": self._zeta0,
+ "lambda0": self._lambda0,
+ "w0": self._w0,
+ "w1": self._w1,
+ "quad_weights": 1.0,
+ }
+ super().build(use_jit=use_jit, verbose=verbose)
+
+ def compute(self, params, constants=None):
+ """
+ Compute the ballooning stability growth rate.
+
+ Parameters
+ ----------
+ params : dict
+ Dictionary of equilibrium degrees of freedom, eg Equilibrium.params_dict
+ constants : dict
+ Dictionary of constant data, eg transforms, profiles etc. Defaults to
+ self.constants
+
+ Returns
+ -------
+ lam : ndarray
+ ideal ballooning growth rate.
+
+ """
+ eq = self.things[0]
+
+ if constants is None:
+ constants = self.constants
+ # we first compute iota on a uniform grid to get correct averaging etc.
+ iota_data = compute_fun(
+ eq,
+ self._iota_keys,
+ params=params,
+ transforms=constants["iota_transforms"],
+ profiles=constants["iota_profiles"],
+ )
+
+ len_data = compute_fun(
+ eq,
+ self._len_keys,
+ params=params,
+ transforms=constants["len_transforms"],
+ profiles=constants["len_profiles"],
+ )
+
+ # Now we compute theta_DESC for given theta_PEST
+ rho, alpha, zeta = constants["rho"], constants["alpha"], constants["zeta"]
+
+ # we prime the data dict with the correct iota values so we don't recompute them
+ # using the wrong grid
+ data = {
+ "iota": iota_data["iota"][0],
+ "iota_r": iota_data["iota_r"][0],
+ "shear": iota_data["shear"][0],
+ "a": len_data["a"],
+ }
+
+ grid = eq.get_rtz_grid(
+ rho,
+ alpha,
+ zeta,
+ coordinates="raz",
+ period=(np.inf, 2 * np.pi, np.inf),
+ params=params,
+ )
+
+ lam = compute_fun(
+ eq,
+ self._data_keys,
+ params,
+ get_transforms(self._data_keys, eq, grid, jitable=True),
+ profiles=get_profiles(self._data_keys, eq, grid),
+ data=data,
+ zeta0=constants["zeta0"],
+ )["ideal ballooning lambda"]
+
+ lambda0, w0, w1 = constants["lambda0"], constants["w0"], constants["w1"]
+
+ # Shifted ReLU operation
+ data = (lam - lambda0) * (lam >= lambda0)
+
+ results = w0 * jnp.sum(data) + w1 * jnp.max(data)
+
+ return results
diff --git a/docs/index.rst b/docs/index.rst
index 0cfbeb9bf..d0ff30cfd 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -32,6 +32,7 @@
notebooks/tutorials/nae_constraint.ipynb
notebooks/tutorials/bootstrap_current.ipynb
notebooks/tutorials/coil_stage_two_optimization.ipynb
+ notebooks/tutorials/ideal_ballooning_stability.ipynb
memory_usage
.. toctree::
diff --git a/docs/notebooks/tutorials/ideal_ballooning_stability.ipynb b/docs/notebooks/tutorials/ideal_ballooning_stability.ipynb
new file mode 100644
index 000000000..1ccb88234
--- /dev/null
+++ b/docs/notebooks/tutorials/ideal_ballooning_stability.ipynb
@@ -0,0 +1,835 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "1d92f237",
+ "metadata": {
+ "pycharm": {
+ "name": "#%% md\n"
+ }
+ },
+ "source": [
+ "# Infinite-$n$ ideal ballooning stability optimization"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "497bc74a",
+ "metadata": {
+ "pycharm": {
+ "name": "#%% md\n"
+ }
+ },
+ "source": [
+ "\n",
+ " \n",
+ "This tutorial demonstrates how to evaluate and optimize an equilibrium for infinite-$n$ ideal-ballooning stability with DESC.\n",
+ "The infinite-$n$ ideal ballooning equation is\n",
+ "\n",
+ "$$\\mathbf{B} \\cdot \\nabla \\left( \\frac{|\\nabla \\alpha|^2}{B^2} \\mathbf{B} \\cdot \\nabla X \\right) + 2 \\frac{d \\mu_0 p}{d\\psi} \\left[\\mathbf{B} \\times (\\mathbf{b} \\cdot \\nabla \\mathbf{b})\\right] \\cdot \\nabla \\alpha\\, X = \\lambda \\frac{|\\nabla \\alpha|^2}{B^2} X, \\quad \\lambda = \\gamma^2$$\n",
+ "\n",
+ "where $X$ is the ballooning eigenfunction whereas $\\gamma$ is the ballooning eigenvalue. When $\\lambda > 0$, the mode is ballooning-unstable, otherwise it is ballooning-stable. The equation is solved subject to Dirichlet boundary conditions on the eigenfunction $X$\n",
+ "\n",
+ "$$X(\\zeta = \\zeta_1) = 0, X(\\zeta = \\zeta_2) = 0$$\n",
+ "\n",
+ "where $\\zeta_1$ and $\\zeta_2$ are endpoints of the domain in ballooning space (a transformed covering space where $\\zeta_{\\mathrm{DESC}} \\in [0, 2\\pi]$ to $\\zeta \\in [-\\infty, \\infty]$). Note that the ballooning $\\zeta$ is a different coordinate than periodic $\\zeta_{\\mathrm{DESC}}$ due to their range of applicability. \n",
+ "\n",
+ "Numerically, this equation becomes a 1D EVP (eigenvalue problem) along a field line. \n",
+ "\n",
+ "$$ \\frac{d}{d\\zeta} \\left(g \\frac{dX}{d\\zeta} \\right) + c X = \\lambda f X$$\n",
+ "\n",
+ "where \n",
+ "\n",
+ "$$\n",
+ "\\begin{eqnarray}\n",
+ " \\text{g} &=& (\\mathbf{b} \\cdot \\nabla \\zeta) \\frac{|\\nabla \\alpha|^2}{B}, \\\\\n",
+ " \\text{c} &=& \\frac{1}{B^2} \\frac{d(\\mu_0 p)}{d\\psi} \\frac{2}{(\\mathbf{b} \\cdot \\nabla \\zeta)} (\\mathbf{b} \\times (\\mathbf{b} \\cdot \\nabla \\mathbf{b})) \\times \\nabla \\alpha, \\\\\n",
+ " \\text{f} &=& \\frac{1}{(\\mathbf{b} \\cdot \\nabla \\zeta)} \\frac{|\\nabla \\alpha|^2}{B^3},\n",
+ "\\end{eqnarray}\n",
+ "$$\n",
+ "\n",
+ "are functions of $\\zeta$ along a field line.\n",
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "0974e779",
+ "metadata": {
+ "pycharm": {
+ "name": "#%%\n"
+ },
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "import sys\n",
+ "import os\n",
+ "\n",
+ "sys.path.insert(0, os.path.abspath(\".\"))\n",
+ "sys.path.append(os.path.abspath(\"../../../\"))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4b44dea5",
+ "metadata": {
+ "pycharm": {
+ "name": "#%% md\n"
+ }
+ },
+ "source": [
+ "If you have access to a GPU, uncomment the following two lines. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "9a54753b",
+ "metadata": {
+ "pycharm": {
+ "name": "#%%\n"
+ },
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "# from desc import set_device\n",
+ "# set_device(\"gpu\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "ee57db1b",
+ "metadata": {
+ "pycharm": {
+ "name": "#%%\n"
+ },
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "DESC version 0.12.2+257.gdae097e3b,using JAX backend, jax version=0.4.31, jaxlib version=0.4.31, dtype=float64\n",
+ "Using device: CPU, with 19.30 GB available memory\n"
+ ]
+ }
+ ],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "\n",
+ "import desc\n",
+ "from desc.grid import Grid, LinearGrid\n",
+ "from desc.optimize import Optimizer\n",
+ "from desc.objectives import (\n",
+ " ForceBalance,\n",
+ " AspectRatio,\n",
+ " FixIota,\n",
+ " FixPressure,\n",
+ " FixPsi,\n",
+ " PrincipalCurvature,\n",
+ " BallooningStability,\n",
+ " ObjectiveFunction,\n",
+ " FixBoundaryR,\n",
+ " FixBoundaryZ,\n",
+ " GenericObjective,\n",
+ ")\n",
+ "\n",
+ "plt.rcParams[\"font.size\"] = 14"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "49d77d2f-c944-4e0a-b2b8-20c512d3a3e4",
+ "metadata": {},
+ "source": [
+ "## Evaluating ballooning stability of the initial equilibrium"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8779fd24-4503-411d-8d52-26e4048efe41",
+ "metadata": {},
+ "source": [
+ "In this section, we will show how you can take a DESC or VMEC equilibrium and evaluate its ballooning stability using DESC\n",
+ "You have to specify the normalized distance $\\rho$ and the field line label $\\alpha$ on which you want to solve the ballooning equation. \n",
+ "\n",
+ "DESC will solve the ballooning equation on multiple field lines on each flux surface and output the maximum ballooning growth rate on each flux surface. \n",
+ "\n",
+ "$$ \\lambda_{\\rho, \\mathrm{max}} = \\mathrm{max}_{\\alpha}(\\lambda_{\\rho, \\alpha}), \\quad \\forall \\quad \\alpha \\in [0, \\pi]$$\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "58b19a1d-e20d-4623-b219-01ab8c9901af",
+ "metadata": {
+ "scrolled": true,
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "# Importing the HELIOTRON DESC equilibrium\n",
+ "eq0 = desc.examples.get(\"HELIOTRON\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "21c22119-91ac-4f54-96ed-5f38992cfb80",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
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+ "