Merge branch 'master' into dd/linking_current

.github/dependabot.yml

@@ -0,0 +1,9 @@
+# Please see the documentation for all configuration options:
+# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
+
+version: 2
+updates:
+  - package-ecosystem: "pip"
+    directory: "/" # Location of package manifests
+    schedule:
+      interval: "weekly"

.github/workflows/benchmark.yml

@@ -82,6 +82,7 @@ jobs:
           source .venv-${{ matrix.python-version }}/bin/activate
           pwd
           lscpu
+          pip list
           cd tests/benchmarks
           python -m pytest benchmark_cpu_small.py -vv \
             --benchmark-save='Latest_Commit' \
@@ -108,6 +109,7 @@ jobs:
           source .venv-${{ matrix.python-version }}/bin/activate
           pwd
           lscpu
+          pip list
           cd tests/benchmarks
           python -m pytest benchmark_cpu_small.py -vv \
             --benchmark-save='master' \

.github/workflows/jax_tests.yml

@@ -44,6 +44,7 @@ jobs:
         run: |
           pwd
           lscpu
+          pip list
           python -m pytest -m unit \
             --durations=0 \
             --mpl \

.github/workflows/mpl_tests.yml

@@ -72,4 +72,5 @@ jobs:
         run: |
           pwd
           lscpu
+          pip list
           python -m pytest tests/test_plotting.py --durations=0 --mpl --maxfail=1

.github/workflows/notebook_tests.yml

@@ -75,6 +75,7 @@ jobs:
           source .venv-${{ matrix.python-version }}/bin/activate
           pwd
           lscpu
+          pip list
           export PYTHONPATH=$(pwd)
           pytest -v --nbmake "./docs/notebooks" \
             --nbmake-timeout=2000 \

.github/workflows/regression_tests.yml

@@ -80,6 +80,7 @@ jobs:
           source .venv-${{ matrix.python-version }}/bin/activate
           pwd
           lscpu
+          pip list
           python -m pytest -v -m regression\
             --durations=0 \
             --cov-report xml:cov.xml \

.github/workflows/unit_tests.yml

@@ -86,6 +86,7 @@ jobs:
           source .venv-${{ matrix.combos.python_version }}/bin/activate
           pwd
           lscpu
+          pip list
           python -m pytest -v -m unit \
             --durations=0 \
             --cov-report xml:cov.xml \

.github/workflows/weekly_tests.yml

@@ -35,6 +35,7 @@ jobs:
         run: |
           pwd
           lscpu
+          pip list
           python -m pytest -v -m unit \
             --durations=0 \
             --splits 4 \

CHANGELOG.md

@@ -7,6 +7,10 @@ New Feature
 - Add ``desc.objectives.LinkingCurrent`` for ensuring that coils in a stage 2 or single stage optimization provide the required linking current for a given equilibrium.
 
 
+Bug Fixes
+
+- Small bug fix to use the correct normalization length ``a`` in the BallooningStability objective
+
 v0.13.0
 -------
 

desc/backend.py

@@ -73,7 +73,7 @@
     from jax.lax import cond, fori_loop, scan, switch, while_loop
     from jax.nn import softmax as softargmax
     from jax.numpy import bincount, flatnonzero, repeat, take
-    from jax.numpy.fft import irfft, rfft, rfft2
+    from jax.numpy.fft import ifft, irfft, irfft2, rfft, rfft2
     from jax.scipy.fft import dct, idct
     from jax.scipy.linalg import block_diag, cho_factor, cho_solve, qr, solve_triangular
     from jax.scipy.special import gammaln
@@ -434,7 +434,7 @@ def tangent_solve(g, y):
     jit = lambda func, *args, **kwargs: func
     execute_on_cpu = lambda func: func
     import scipy.optimize
-    from numpy.fft import irfft, rfft, rfft2  # noqa: F401
+    from numpy.fft import ifft, irfft, irfft2, rfft, rfft2  # noqa: F401
     from scipy.fft import dct, idct  # noqa: F401
     from scipy.integrate import odeint  # noqa: F401
     from scipy.linalg import (  # noqa: F401

desc/compute/__init__.py

@@ -35,6 +35,7 @@
     _field,
     _geometry,
     _metric,
+    _neoclassical,
     _omnigenity,
     _profiles,
     _stability,

desc/compute/_basis_vectors.py

@@ -3223,17 +3223,61 @@ def _e_sub_zeta_zz(params, transforms, profiles, data, **kwargs):
     transforms={},
     profiles=[],
     coordinates="rtz",
-    data=["e^rho", "e^theta", "e^zeta", "alpha_r", "alpha_t", "alpha_z"],
+    data=["grad(alpha) (periodic)", "grad(alpha) (secular)"],
 )
 def _grad_alpha(params, transforms, profiles, data, **kwargs):
-    data["grad(alpha)"] = (
-        data["alpha_r"] * data["e^rho"].T
+    data["grad(alpha)"] = data["grad(alpha) (periodic)"] + data["grad(alpha) (secular)"]
+    return data
+
+
+@register_compute_fun(
+    name="grad(alpha) (periodic)",
+    label="\\mathrm{periodic}(\\nabla \\alpha)",
+    units="m^{-1}",
+    units_long="Inverse meters",
+    description=(
+        "Gradient of field line label, which is perpendicular to the field line, "
+        "periodic component"
+    ),
+    dim=3,
+    params=[],
+    transforms={},
+    profiles=[],
+    coordinates="rtz",
+    data=["e^rho", "e^theta", "e^zeta", "alpha_r (periodic)", "alpha_t", "alpha_z"],
+)
+def _periodic_grad_alpha(params, transforms, profiles, data, **kwargs):
+    data["grad(alpha) (periodic)"] = (
+        data["alpha_r (periodic)"] * data["e^rho"].T
         + data["alpha_t"] * data["e^theta"].T
         + data["alpha_z"] * data["e^zeta"].T
     ).T
     return data
 
 
+@register_compute_fun(
+    name="grad(alpha) (secular)",
+    label="\\mathrm{secular}(\\nabla \\alpha)",
+    units="m^{-1}",
+    units_long="Inverse meters",
+    description=(
+        "Gradient of field line label, which is perpendicular to the field line, "
+        "secular component"
+    ),
+    dim=3,
+    params=[],
+    transforms={},
+    profiles=[],
+    coordinates="rtz",
+    data=["e^rho", "alpha_r (secular)"],
+)
+def _secular_grad_alpha(params, transforms, profiles, data, **kwargs):
+    data["grad(alpha) (secular)"] = (
+        data["alpha_r (secular)"][:, jnp.newaxis] * data["e^rho"]
+    )
+    return data
+
+
 @register_compute_fun(
     name="grad(psi)",
     label="\\nabla\\psi",

desc/compute/_core.py

@@ -1518,14 +1518,48 @@ def _alpha(params, transforms, profiles, data, **kwargs):
     transforms={},
     profiles=[],
     coordinates="rtz",
-    data=["theta_PEST_r", "phi", "phi_r", "iota", "iota_r"],
+    data=["alpha_r (periodic)", "alpha_r (secular)"],
 )
 def _alpha_r(params, transforms, profiles, data, **kwargs):
-    data["alpha_r"] = (
-        data["theta_PEST_r"]
-        - data["iota_r"] * data["phi"]
-        - data["iota"] * data["phi_r"]
-    )
+    data["alpha_r"] = data["alpha_r (periodic)"] + data["alpha_r (secular)"]
+    return data
+
+
+@register_compute_fun(
+    name="alpha_r (periodic)",
+    label="\\mathrm{periodic}(\\partial_\\rho \\alpha)",
+    units="~",
+    units_long="None",
+    description="Field line label, derivative wrt radial coordinate, "
+    "periodic component",
+    dim=1,
+    params=[],
+    transforms={},
+    profiles=[],
+    coordinates="rtz",
+    data=["theta_PEST_r", "iota", "phi_r"],
+)
+def _periodic_alpha_r(params, transforms, profiles, data, **kwargs):
+    data["alpha_r (periodic)"] = data["theta_PEST_r"] - data["iota"] * data["phi_r"]
+    return data
+
+
+@register_compute_fun(
+    name="alpha_r (secular)",
+    label="\\mathrm{secular}(\\partial_\\rho \\alpha)",
+    units="~",
+    units_long="None",
+    description="Field line label, derivative wrt radial coordinate, "
+    "secular component",
+    dim=1,
+    params=[],
+    transforms={},
+    profiles=[],
+    coordinates="rtz",
+    data=["iota_r", "phi"],
+)
+def _secular_alpha_r(params, transforms, profiles, data, **kwargs):
+    data["alpha_r (secular)"] = -data["iota_r"] * data["phi"]
     return data
 
 

desc/compute/_equil.py

@@ -658,12 +658,12 @@ def _F_anisotropic(params, transforms, profiles, data, **kwargs):
     transforms={"grid": []},
     profiles=[],
     coordinates="",
-    data=["|B|", "sqrt(g)"],
+    data=["|B|^2", "sqrt(g)"],
     resolution_requirement="rtz",
 )
 def _W_B(params, transforms, profiles, data, **kwargs):
     data["W_B"] = jnp.sum(
-        data["|B|"] ** 2 * data["sqrt(g)"] * transforms["grid"].weights
+        data["|B|^2"] * data["sqrt(g)"] * transforms["grid"].weights
     ) / (2 * mu_0)
     return data