Merge branch 'master' into dp/poincare

CHANGELOG.md

@@ -8,6 +8,7 @@ New Feature
 - Adds an option ``scaled_termination`` (defaults to True) to all of the desc optimizers to measure the norms for ``xtol`` and ``gtol`` in the scaled norm provided by ``x_scale`` (which defaults to using an adaptive scaling based on the Jacobian or Hessian). This should make things more robust when optimizing parameters with widely different magnitudes. The old behavior can be recovered by passing ``options={"scaled_termination": False}``.
 - ``desc.objectives.Omnigenity`` is now vectorized and able to optimize multiple surfaces at the same time. Previously it was required to use a different objective for each surface.
 - Adds a new objective ``desc.objectives.MirrorRatio`` for targeting a particular mirror ratio on each flux surface, for either an ``Equilibrium`` or ``OmnigenousField``.
+- Adds the output quantities ``wb`` and ``wp`` to ``VMECIO.save``.
 
 Bug Fixes
 

desc/vmec.py

@@ -295,7 +295,16 @@ def save(cls, eq, path, surfs=128, verbose=1, M_nyq=None, N_nyq=None):  # noqa:
         grid_full = LinearGrid(M=M_nyq, N=N_nyq, NFP=NFP, rho=r_full)
 
         data_quad = eq.compute(
-            ["R0/a", "V", "<|B|>_rms", "<beta>_vol", "<beta_pol>_vol", "<beta_tor>_vol"]
+            [
+                "R0/a",
+                "V",
+                "W_B",
+                "W_p",
+                "<|B|>_rms",
+                "<beta>_vol",
+                "<beta_pol>_vol",
+                "<beta_tor>_vol",
+            ]
         )
         data_axis = eq.compute(["G", "p", "R", "<|B|^2>", "<|B|>"], grid=grid_axis)
         data_lcfs = eq.compute(["G", "I", "R", "Z"], grid=grid_lcfs)
@@ -508,6 +517,16 @@ def save(cls, eq, path, surfs=128, verbose=1, M_nyq=None, N_nyq=None):  # noqa:
         betator.units = "None"
         betator[:] = data_quad["<beta_tor>_vol"]
 
+        wb = file.createVariable("wb", np.float64)
+        wb.long_name = "plasma magnetic energy * mu_0/(4*pi^2)"
+        wb.units = "T^2*m^3"
+        wb[:] = data_quad["W_B"] * mu_0 / (4 * np.pi**2)
+
+        wp = file.createVariable("wp", np.float64)
+        wp.long_name = "plasma thermodynamic energy * mu_0/(4*pi^2)"
+        wp.units = "T^2*m^3"
+        wp[:] = np.abs(data_quad["W_p"]) * mu_0 / (4 * np.pi**2)
+
         # scalars computed at the magnetic axis
 
         rbtor0 = file.createVariable("rbtor0", np.float64)
@@ -1344,16 +1363,8 @@ def fullfit(x):
         specw = file.createVariable("specw", np.float64, ("radius",))
         specw[:] = np.zeros((file.dimensions["radius"].size,))
 
-        # this is not the same as DESC's "W_B"
-        wb = file.createVariable("wb", np.float64)
-        wb[:] = 0.0
-
         wdot = file.createVariable("wdot", np.float64, ("time",))
         wdot[:] = np.zeros((file.dimensions["time"].size,))
-
-        # this is not the same as DESC's "W_p"
-        wp = file.createVariable("wp", np.float64)
-        wp[:] = 0.0
         """
 
         file.close()

docs/installation.rst

@@ -96,17 +96,18 @@ specific JAX GPU installation instructions, as that is the main installation dif
 
 **Note that DESC does not always test on or guarantee support of the latest version of JAX (which does not have a stable 1.0 release yet), and thus older versions of GPU-accelerated versions of JAX may need to be installed, which may in turn require lower versions of JaxLib, as well as CUDA and CuDNN.**
 
+
 Perlmutter (NERSC)
 ++++++++++++++++++++++++++++++
-These instructions were tested and confirmed to work on the Perlmutter supercomputer at NERSC on June 18, 2024.
+These instructions were tested and confirmed to work on the Perlmutter supercomputer at NERSC on December 17, 2024.
 
 Set up the correct cuda environment for jax installation
 
 .. code-block:: sh
 
-    module load cudatoolkit/12.2
+    module load cudatoolkit/12.4
     module load cudnn/8.9.3_cuda12
-    module load python
+    module load python/3.11
 
 Check that you have loaded these modules
 
@@ -118,21 +119,9 @@ Create a conda environment for DESC (`following these instructions <https://docs
 
 .. code-block:: sh
 
-    conda create -n desc-env python=3.9
+    conda create -n desc-env python=3.11
     conda activate desc-env
-    pip install --no-cache-dir "jax==0.4.23" "jaxlib[cuda12_cudnn89]==0.4.23" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
-
-For Perlmutter installation, please change the scipy version from
-
-.. code-block:: sh
-
-    scipy >= 1.7.0, < 2.0.0
-
-to
-
-.. code-block:: sh
-
-    scipy >= 1.7.0, <= 1.11.3
+    pip install --upgrade "jax[cuda12]"
 
 Clone and install DESC
 

requirements.txt

@@ -13,6 +13,6 @@ plotly >= 5.16, <= 5.24.1
 psutil <= 6.1.0
 pylatexenc >= 2.0, <= 2.10
 quadax >= 0.2.2, <= 0.2.4
-scikit-image <= 0.24.0
+scikit-image <= 0.25.0
 scipy >= 1.7.0, <= 1.14.1
 termcolor <= 2.5.0

tests/test_vmec.py

@@ -496,6 +496,10 @@ def test_vmec_save_1(VMEC_save):
     np.testing.assert_allclose(
         vmec.variables["betator"][:], desc.variables["betator"][:], rtol=1e-5
     )
+    np.testing.assert_allclose(vmec.variables["wb"][:], desc.variables["wb"][:])
+    np.testing.assert_allclose(
+        vmec.variables["wp"][:], desc.variables["wp"][:], rtol=1e-6
+    )
     np.testing.assert_allclose(
         vmec.variables["ctor"][:], desc.variables["ctor"][:], rtol=1e-5
     )