Update VMECIO to specify Nyquist spectrum and fix issues with asymmetric wouts

CHANGELOG.md

@@ -4,6 +4,14 @@ Changelog
 New Features
 
 - Add ``use_signed_distance`` flag to ``PlasmaVesselDistance`` which will use a signed distance as the target, which is positive when the plasma is inside of the vessel surface and negative if the plasma is outside of the vessel surface, to allow optimizer to distinguish if the equilbrium surface exits the vessel surface and guard against it by targeting a positive signed distance.
+- Allow specification of Nyquist spectrum maximum modenumbers when using ``VMECIO.save`` to save a DESC .h5 file as a VMEC-format wout file
+
+Bug Fixes
+
+- Fixes bugs that occur when saving asymmetric equilibria as wout files
+- Fixes bug that occurs when using ``VMECIO.plot_vmec_comparison`` to compare to an asymmetric wout file
+
+
 
 v0.12.1
 -------

desc/vmec.py

@@ -25,7 +25,7 @@
 from desc.objectives.utils import factorize_linear_constraints
 from desc.profiles import PowerSeriesProfile, SplineProfile
 from desc.transform import Transform
-from desc.utils import Timer
+from desc.utils import Timer, warnif
 from desc.vmec_utils import (
     fourier_to_zernike,
     ptolemy_identity_fwd,
@@ -158,7 +158,7 @@
         zax_cs = file.variables["zaxis_cs"][:].filled()
         try:
             rax_cs = file.variables["raxis_cs"][:].filled()
-            rax_cc = file.variables["zaxis_cc"][:].filled()
+            zax_cc = file.variables["zaxis_cc"][:].filled()
         except KeyError:
             rax_cs = np.zeros_like(rax_cc)
             zax_cc = np.zeros_like(zax_cs)
@@ -208,7 +208,9 @@
         return eq
 
     @classmethod
-    def save(cls, eq, path, surfs=128, verbose=1):  # noqa: C901 - FIXME - simplify
+    def save(  # noqa: C901 - FIXME - simplify
+        cls, eq, path, surfs=128, verbose=1, M_nyq=None, N_nyq=None
+    ):
         """Save an Equilibrium as a netCDF file in the VMEC format.
 
         Parameters
@@ -224,6 +226,10 @@
             * 0: no output
             * 1: status of quantities computed
             * 2: as above plus timing information
+        M_nyq, N_nyq: int
+            The max poloidal and toroidal modenumber to use in the
+            Nyquist spectrum that the derived quantities are Fourier
+            fit with. Defaults to M+4 and N+2.
 
         Returns
         -------
@@ -242,8 +248,14 @@
         NFP = eq.NFP
         M = eq.M
         N = eq.N
-        M_nyq = M + 4
-        N_nyq = N + 2 if N > 0 else 0
+        M_nyq = M + 4 if M_nyq is None else M_nyq
+        warnif(
+            N_nyq is not None and int(N) == 0,
+            UserWarning,
+            "Passed in N_nyq but equilibrium is axisymmetric, setting N_nyq to zero",
+        )
+        N_nyq = N + 2 if N_nyq is None else N_nyq
+        N_nyq = 0 if int(N) == 0 else N_nyq
 
         # VMEC radial coordinate: s = rho^2 = Psi / Psi(LCFS)
         s_full = np.linspace(0, 1, surfs)
@@ -807,6 +819,14 @@
             lmnc.long_name = "cos(m*t-n*p) component of lambda, on half mesh"
             lmnc.units = "rad"
         l1 = np.ones_like(eq.L_lmn)
+        # should negate lambda coefs bc theta_DESC + lambda = theta_PEST,
+        # since we are reversing the theta direction (and the theta_PEST direction),
+        # so -theta_PEST = -theta_DESC - lambda, so the negative of lambda is what
+        # should be saved, so that would be negating all of eq.L_lmn
+        # BUT since we are also reversing the poloidal angle direction, which
+        # would negate only the coeffs of L_lmn corresponding to m<0
+        # (sin theta modes in DESC), the effective result is to only
+        # negate the cos(theta) (m>0) lambda modes
         l1[eq.L_basis.modes[:, 1] >= 0] *= -1
         m, n, x_mn = zernike_to_fourier(l1 * eq.L_lmn, basis=eq.L_basis, rho=r_half)
         xm, xn, s, c = ptolemy_identity_rev(m, n, x_mn)
@@ -823,7 +843,7 @@
 
         sin_basis = DoubleFourierSeries(M=M_nyq, N=N_nyq, NFP=NFP, sym="sin")
         cos_basis = DoubleFourierSeries(M=M_nyq, N=N_nyq, NFP=NFP, sym="cos")
-        full_basis = DoubleFourierSeries(M=M_nyq, N=N_nyq, NFP=NFP, sym=None)
+        full_basis = DoubleFourierSeries(M=M_nyq, N=N_nyq, NFP=NFP, sym=False)
         if eq.sym:
             sin_transform = Transform(
                 grid=grid_lcfs, basis=sin_basis, build=False, build_pinv=True
@@ -932,7 +952,7 @@
             if eq.sym:
                 x_mn[i, :] = cosfit(data[i, :])
             else:
-                x_mn[i, :] = full_transform.fit(data[i, :])
+                x_mn[i, :] = fullfit(data[i, :])
         xm, xn, s, c = ptolemy_identity_rev(m, n, x_mn)
         bmnc[0, :] = 0
         bmnc[1:, :] = c
@@ -975,7 +995,7 @@
             if eq.sym:
                 x_mn[i, :] = cosfit(data[i, :])
             else:
-                x_mn[i, :] = full_transform.fit(data[i, :])
+                x_mn[i, :] = fullfit(data[i, :])
         xm, xn, s, c = ptolemy_identity_rev(m, n, x_mn)
         bsupumnc[0, :] = 0
         bsupumnc[1:, :] = -c  # negative sign for negative Jacobian
@@ -1018,7 +1038,7 @@
             if eq.sym:
                 x_mn[i, :] = cosfit(data[i, :])
             else:
-                x_mn[i, :] = full_transform.fit(data[i, :])
+                x_mn[i, :] = fullfit(data[i, :])
         xm, xn, s, c = ptolemy_identity_rev(m, n, x_mn)
         bsupvmnc[0, :] = 0
         bsupvmnc[1:, :] = c
@@ -1641,13 +1661,15 @@
             return C + S
 
     @classmethod
-    def compute_theta_coords(cls, lmns, xm, xn, s, theta_star, zeta, si=None):
+    def compute_theta_coords(
+        cls, lmns, xm, xn, s, theta_star, zeta, si=None, lmnc=None
+    ):
         """Find theta such that theta + lambda(theta) == theta_star.
 
         Parameters
         ----------
         lmns : array-like
-            fourier coefficients for lambda
+            sin(mt-nz) Fourier coefficients for lambda
         xm : array-like
             poloidal mode numbers
         xn : array-like
@@ -1662,6 +1684,8 @@
         si : ndarray
             values of radial coordinates where lmns are defined. Defaults to linearly
             spaced on half grid between (0,1)
+        lmnc : array-like, optional
+            cos(mt-nz) Fourier coefficients for lambda
 
         Returns
         -------
@@ -1672,19 +1696,30 @@
         if si is None:
             si = np.linspace(0, 1, lmns.shape[0])
             si[1:] = si[0:-1] + 0.5 / (lmns.shape[0] - 1)
-        lmbda_mn = interpolate.CubicSpline(si, lmns)
+        lmbda_mns = interpolate.CubicSpline(si, lmns)
+        if lmnc is None:
+            lmbda_mnc = lambda s: 0
+        else:
+            lmbda_mnc = interpolate.CubicSpline(si, lmnc)
 
         # Note: theta* (also known as vartheta) is the poloidal straight field line
         # angle in PEST-like flux coordinates
 
         def root_fun(theta):
             lmbda = np.sum(
-                lmbda_mn(s)
+                lmbda_mns(s)
                 * np.sin(
                     xm[np.newaxis] * theta[:, np.newaxis]
                     - xn[np.newaxis] * zeta[:, np.newaxis]
                 ),
                 axis=-1,
+            ) + np.sum(
+                lmbda_mnc(s)
+                * np.cos(
+                    xm[np.newaxis] * theta[:, np.newaxis]
+                    - xn[np.newaxis] * zeta[:, np.newaxis]
+                ),
+                axis=-1,
             )
             theta_star_k = theta + lmbda  # theta* = theta + lambda
             err = theta_star - theta_star_k  # FIXME: mod by 2pi
@@ -1782,36 +1817,80 @@
         t_nodes = t_grid.nodes
         t_nodes[:, 0] = t_nodes[:, 0] ** 2
 
+        sym = "lmnc" not in vmec_data.keys()
+
         v_nodes = cls.compute_theta_coords(
             vmec_data["lmns"],
             vmec_data["xm"],
             vmec_data["xn"],
             t_nodes[:, 0],
             t_nodes[:, 1],
             t_nodes[:, 2],
+            lmnc=vmec_data["lmnc"] if not sym else None,
         )
 
         t_nodes[:, 1] = v_nodes
+        if sym:
+            Rr_vmec, Zr_vmec = cls.vmec_interpolate(
+                vmec_data["rmnc"],
+                vmec_data["zmns"],
+                vmec_data["xm"],
+                vmec_data["xn"],
+                theta=r_nodes[:, 1],
+                phi=r_nodes[:, 2],
+                s=r_nodes[:, 0],
+            )
 
-        Rr_vmec, Zr_vmec = cls.vmec_interpolate(
-            vmec_data["rmnc"],
-            vmec_data["zmns"],
-            vmec_data["xm"],
-            vmec_data["xn"],
-            theta=r_nodes[:, 1],
-            phi=r_nodes[:, 2],
-            s=r_nodes[:, 0],
-        )
-
-        Rv_vmec, Zv_vmec = cls.vmec_interpolate(
-            vmec_data["rmnc"],
-            vmec_data["zmns"],
-            vmec_data["xm"],
-            vmec_data["xn"],
-            theta=t_nodes[:, 1],
-            phi=t_nodes[:, 2],
-            s=t_nodes[:, 0],
-        )
+            Rv_vmec, Zv_vmec = cls.vmec_interpolate(
+                vmec_data["rmnc"],
+                vmec_data["zmns"],
+                vmec_data["xm"],
+                vmec_data["xn"],
+                theta=t_nodes[:, 1],
+                phi=t_nodes[:, 2],
+                s=t_nodes[:, 0],
+            )
+        else:
+            Rr_vmec = cls.vmec_interpolate(
+                vmec_data["rmnc"],
+                vmec_data["rmns"],
+                vmec_data["xm"],
+                vmec_data["xn"],
+                theta=r_nodes[:, 1],
+                phi=r_nodes[:, 2],
+                s=r_nodes[:, 0],
+                sym=False,
+            )
+            Zr_vmec = cls.vmec_interpolate(
+                vmec_data["zmnc"],
+                vmec_data["zmns"],
+                vmec_data["xm"],
+                vmec_data["xn"],
+                theta=r_nodes[:, 1],
+                phi=r_nodes[:, 2],
+                s=r_nodes[:, 0],
+                sym=False,
+            )
+            Rv_vmec = cls.vmec_interpolate(
+                vmec_data["rmnc"],
+                vmec_data["rmns"],
+                vmec_data["xm"],
+                vmec_data["xn"],
+                theta=t_nodes[:, 1],
+                phi=t_nodes[:, 2],
+                s=t_nodes[:, 0],
+                sym=False,
+            )
+            Zv_vmec = cls.vmec_interpolate(
+                vmec_data["zmnc"],
+                vmec_data["zmns"],
+                vmec_data["xm"],
+                vmec_data["xn"],
+                theta=t_nodes[:, 1],
+                phi=t_nodes[:, 2],
+                s=t_nodes[:, 0],
+                sym=False,
+            )
 
         coords = {
             "Rr_desc": Rr_desc,

tests/conftest.py

@@ -335,3 +335,22 @@ def VMEC_save(SOLOVEV, tmpdir_factory):
     )
     desc = Dataset(str(SOLOVEV["desc_nc_path"]), mode="r")
     return vmec, desc
+
+
+@pytest.fixture(scope="session")
+def VMEC_save_asym(tmpdir_factory):
+    """Save an asymmetric equilibrium in VMEC netcdf format for comparison."""
+    tmpdir = tmpdir_factory.mktemp("asym_wout")
+    filename = tmpdir.join("wout_HELIO_asym_desc.nc")
+    vmec = Dataset("./tests/inputs/wout_HELIOTRON_asym_NTHETA50_NZETA100.nc", mode="r")
+    eq = Equilibrium.load("./tests/inputs/HELIO_asym.h5")
+    VMECIO.save(
+        eq,
+        filename,
+        surfs=vmec.variables["ns"][:],
+        verbose=0,
+        M_nyq=round(np.max(vmec.variables["xm_nyq"][:])),
+        N_nyq=round(np.max(vmec.variables["xn_nyq"][:]) / eq.NFP),
+    )
+    desc = Dataset(filename, mode="r")
+    return vmec, desc, eq