add issues to TODOs or remove

desc/basis.py

@@ -1098,13 +1098,13 @@ def evaluate(
         if not len(modes):
             return np.array([]).reshape((len(nodes), 0))
 
-        # TODO: avoid duplicate calculations when mixing derivatives
+        # TODO(#1243): avoid duplicate calculations when mixing derivatives
         r, t, z = nodes.T
         l, m, n = modes.T
         lm = modes[:, :2]
 
         if unique:
-            # TODO: can avoid this here by using grid.unique_idx etc
+            # TODO(#1243): can avoid this here by using grid.unique_idx etc
             # and adding unique_modes attributes to basis
             _, ridx, routidx = np.unique(
                 r, return_index=True, return_inverse=True, axis=0

desc/batching.py

@@ -102,7 +102,6 @@ def f_(carry, x):
     return res_append
 
 
-# TODO in_axes a la vmap?
 def _scanmap(fun, scan_fun, argnums=0):
     """A helper function to wrap f with a scan_fun."""
 

desc/coils.py

@@ -1901,8 +1901,8 @@ def save_in_makegrid_format(self, coilsFilename, NFP=None, grid=None):
             if None, will default to the coil compute functions's
             default grid
         """
-        # TODO: name each group based off of CoilSet name?
-        # TODO: have CoilGroup be automatically assigned based off of
+        # TODO(#1376): name each group based off of CoilSet name?
+        # TODO(#1376): have CoilGroup be automatically assigned based off of
         # CoilSet if current coilset is a collection of coilsets?
 
         NFP = 1 if NFP is None else NFP

desc/compute/_omnigenity.py

@@ -47,7 +47,7 @@ def fitfun(x):
     return data
 
 
-# TODO: do math to change definition of nu so that we can just use B_zeta_mn here
+# TODO (#568): do math to change definition of nu so that we can just use B_zeta_mn here
 @register_compute_fun(
     name="B_phi_mn",
     label="B_{\\phi, m, n}",

desc/compute/_profiles.py

@@ -1378,7 +1378,7 @@ def _iota_num_rrr(params, transforms, profiles, data, **kwargs):
                 - beta * data["sqrt(g)_rrr"],
                 data["sqrt(g)"],
             ),
-            # Todo: axis limit of beta_rrr
+            # TODO(#587): axis limit of beta_rrr
             #   Computed with four applications of l’Hôpital’s rule.
             #   Requires sqrt(g)_rrrr and fourth derivatives of basis vectors.
             jnp.nan,
@@ -1656,7 +1656,7 @@ def _iota_den_rrr(params, transforms, profiles, data, **kwargs):
             - gamma * data["sqrt(g)_rrr"],
             data["sqrt(g)"],
         ),
-        # Todo: axis limit
+        # TODO(#587): axis limit
         #   Computed with four applications of l’Hôpital’s rule.
         #   Requires sqrt(g)_rrrr and fourth derivatives of basis vectors.
         jnp.nan,
@@ -1713,7 +1713,7 @@ def _q(params, transforms, profiles, data, **kwargs):
     return data
 
 
-# TODO: add K(rho,theta,zeta)*grad(rho) term
+# TODO (#1381): add K(rho,theta,zeta)*grad(rho) term
 @register_compute_fun(
     name="I",
     label="I",

desc/compute/_stability.py

@@ -76,7 +76,7 @@ def _D_current(params, transforms, profiles, data, **kwargs):
                 / data["|grad(psi)|"] ** 3
                 * dot(Xi, data["B"])
             ),
-            # Todo: implement equivalent of equation 4.3 in desc coordinates
+            # TODO(#671): implement equivalent of equation 4.3 in desc coordinates
             jnp.nan,
         )
     )

desc/continuation.py

@@ -748,7 +748,6 @@ def solve_continuation(  # noqa: C901
         if len(deltas) > 0:
             if verbose > 0:
                 print("Perturbing equilibrium")
-            # TODO: pass Jx if available
             eqp = eqfam[ii - 1].copy()
             objective_i = get_equilibrium_objective(
                 eq=eqp, mode=objective, jac_chunk_size=jac_chunk_size

desc/equilibrium/coords.py

@@ -107,7 +107,7 @@ def map_coordinates(  # noqa: C901
 
     profiles = get_profiles(inbasis + basis_derivs, eq)
 
-    # TODO: make this work for permutations of in/out basis
+    # TODO (#1382): make this work for permutations of in/out basis
     if outbasis == ("rho", "theta", "zeta"):
         if inbasis == ("rho", "alpha", "zeta"):
             if "iota" in kwargs:
@@ -766,7 +766,7 @@ def get_rtz_grid(
     return desc_grid
 
 
-# TODO: deprecated, remove eventually
+# TODO(#1383): deprecated, remove eventually
 def compute_theta_coords(
     eq, flux_coords, L_lmn=None, tol=1e-6, maxiter=20, full_output=False, **kwargs
 ):

desc/equilibrium/utils.py

@@ -146,7 +146,7 @@ def parse_axis(axis, NFP=1, sym=True, surface=None):
             name="axis",
         )
     elif axis is None:  # use the center of surface
-        # TODO: make this method of surface, surface.get_axis()?
+        # TODO (#1384): make this method of surface, surface.get_axis()?
         if isinstance(surface, FourierRZToroidalSurface):
             axis = FourierRZCurve(
                 R_n=surface.R_lmn[np.where(surface.R_basis.modes[:, 1] == 0)],
@@ -160,7 +160,7 @@ def parse_axis(axis, NFP=1, sym=True, surface=None):
                 NFP=NFP,
             )
         elif isinstance(surface, ZernikeRZToroidalSection):
-            # TODO: include m=0 l!=0 modes
+            # TODO (#782): include m=0 l!=0 modes
             axis = FourierRZCurve(
                 R_n=surface.R_lmn[
                     np.where(

desc/geometry/surface.py

@@ -339,7 +339,7 @@ def from_input_file(cls, path, **kwargs):
         )
         return surf
 
-    # TODO: add k value for number of rotations per field period
+    # TODO (#1385): add k value for number of rotations per field period
     @classmethod
     def from_qp_model(
         cls,

desc/input_reader.py

@@ -386,7 +386,6 @@ def parse_inputs(self, fname=None):  # noqa: C901
             if match:
                 inputs["bdry_mode"] = words[0].lower()
                 flag = True
-                # TODO: set bdry_mode automatically based on bdry coeffs
 
             # coefficient indices
             match = re.search(r"l\s*:\s*" + num_form, command, re.IGNORECASE)

desc/integrals/bounce_utils.py

@@ -83,7 +83,7 @@ def _check_spline_shape(knots, g, dg_dz, pitch_inv=None):
         to that field line.
 
     """
-    errorif(knots.ndim != 1, msg=f"knots should be 1d; got shape {knots.shape}.")
+    errorif(knots.ndim != 1, msg=f"knots should be 1d, got shape {knots.shape}.")
     errorif(
         g.shape[-2] != (knots.size - 1),
         msg=(
@@ -390,7 +390,8 @@ def loop(z):  # over num well axis
             )
 
         result = jnp.moveaxis(
-            # TODO: Use batch_size arg of imap after increasing JAX version requirement.
+            # TODO (#1386): Use batch_size arg of imap after
+            #  increasing JAX version requirement.
             imap(loop, (jnp.moveaxis(z1, -1, 0), jnp.moveaxis(z2, -1, 0)))[1],
             source=0,
             destination=-1,

desc/integrals/interp_utils.py

@@ -82,7 +82,7 @@ def polyval_vec(*, x, c):
     )
 
 
-# TODO: Eventually do a PR to move this stuff into interpax.
+# TODO (#1388): Eventually do a PR to move this stuff into interpax.
 
 
 def _subtract_last(c, k):

desc/integrals/surface_integral.py

@@ -8,8 +8,8 @@
 from desc.grid import ConcentricGrid, LinearGrid
 from desc.utils import errorif, warnif
 
-# TODO: Make the surface integral stuff objects with a callable method instead of
-#       returning functions. Would make simpler, allow users to actually see the
+# TODO (#1389): Make the surface integral stuff objects with a callable method instead
+#       of returning functions. Would make simpler, allow users to actually see the
 #       docstrings of the methods, and less bookkeeping to default to more
 #       efficient methods on tensor product grids.
 
@@ -227,8 +227,6 @@ def surface_integrals_map(grid, surface_label="rho", expand_out=True, tol=1e-14)
     )
     spacing = jnp.prod(spacing, axis=1)
 
-    # Todo: Define mask as a sparse matrix once sparse matrices are no longer
-    #       experimental in jax.
     if has_idx:
         # The ith row of masks is True only at the indices which correspond to the
         # ith surface. The integral over the ith surface is the dot product of the

desc/magnetic_fields/_core.py

@@ -2401,7 +2401,7 @@ def __init__(
             assert len(x_lmn) == self.x_basis.num_modes
             self._x_lmn = x_lmn
 
-        # TODO: should we not allow some types of helicity?
+        # TODO (#1390): should we not allow some types of helicity?
         helicity_sign = sign(helicity[0]) * sign(helicity[1])
         warnif(
             self.helicity != (0, self.NFP * helicity_sign)

desc/magnetic_fields/_dommaschk.py

@@ -117,7 +117,7 @@ def fit_magnetic_field(  # noqa: C901
             B = field(coords)
         else:  # it must be the field evaluated at the passed-in coords
             B = field
-        # TODO: add basis argument for if passed-in field or callable
+        # TODO (#928): add basis argument for if passed-in field or callable
         # evaluates rpz or xyz basis magnetic field vector,
         # and what basis coords is
 
@@ -132,7 +132,7 @@ def fit_magnetic_field(  # noqa: C901
         # b is made, now do A
         #####################
         num_modes = 1 + (max_l) * (max_m + 1) * 4
-        # TODO: if symmetric, technically only need half the modes
+        # TODO (#928): if symmetric, technically only need half the modes
         # however, the field and functions are setup to accept equal
         # length arrays for a,b,c,d, so we will just zero out the
         # modes that don't fit symmetry, but in future
@@ -141,7 +141,7 @@ def fit_magnetic_field(  # noqa: C901
         # and the modes array can then be [m,l,x] where x is 0,1,2,3
         # and we dont need to keep track of a,b,c,d separately
 
-        # TODO: technically we can drop some modes
+        # TODO (#928): technically we can drop some modes
         # since if max_l=0, there are only ever nonzero terms for a and b
         # and if max_m=0, there are only ever nonzero terms for a and c
         # but since we are only fitting in a least squares sense,
@@ -247,7 +247,7 @@ def get_B_dom(coords, X, ms, ls):
 
         # now solve Ac=b for the coefficients c
 
-        # TODO: use min singular value to give sense of cond number?
+        # TODO (#928): use min singular value to give sense of cond number?
         c, res, _, _ = jnp.linalg.lstsq(A, rhs)
 
         if verbose > 0:
@@ -258,7 +258,7 @@ def get_B_dom(coords, X, ms, ls):
         B0 = c[0]
 
         # we zero out the terms that should be zero due to symmetry here
-        # TODO: should also just not return any zeroed-out modes, but
+        # TODO (#928): should also just not return any zeroed-out modes, but
         # the way the modes are cataloged here with the ls and ms arrays,
         # it is not straightforward to do that
         a_arr = c[1 : n + 1] * abcd_zero_due_to_sym_inds[0]

desc/objectives/linear_objectives.py

@@ -20,7 +20,7 @@
 from .objective_funs import _Objective
 
 
-# TODO: get rid of this class and inherit from FixParameters instead?
+# TODO (#1391): get rid of this class and inherit from FixParameters instead?
 class _FixedObjective(_Objective):
     _fixed = True
     _linear = True
@@ -45,8 +45,8 @@ def update_target(self, thing):
     def _parse_target_from_user(
         self, target_from_user, default_target, default_bounds, idx
     ):
-        # TODO: add logic here to deal with `target_from_user` as a pytree?
-        # TODO: does this actually need idx?
+        # TODO (#1391): add logic here to deal with `target_from_user` as a pytree?
+        # TODO (#1391: does this actually need idx?
         if target_from_user is None:
             target = default_target
             bounds = default_bounds
@@ -2513,7 +2513,6 @@ def __init__(
             normalize_target=normalize_target,
             name=name,
         )
-        # TODO: add normalization?
 
 
 class FixCurveRotation(FixParameters):
@@ -2879,7 +2878,6 @@ def __init__(
             normalize_target=normalize_target,
             name=name,
         )
-        # TODO: add normalization?
 
 
 class FixOmniMap(FixParameters):
@@ -3094,7 +3092,6 @@ def __init__(
             normalize_target=normalize_target,
             name=name,
         )
-        # TODO: add normalization?
 
 
 class FixNearAxisR(_FixedObjective):

desc/objectives/nae_utils.py

@@ -295,18 +295,17 @@ def _make_RZ_cons_order_rho(  # noqa: C901
         the O(rho) behavior of the equilibrium R coefficients to match the NAE.
     Zconstraints : tuple of Objective
         tuple of constraints of type FixSumModesZ, which enforce
-        the O(rho) behavior of the equilibrium Z coefficents to match the NAE.
+        the O(rho) behavior of the equilibrium Z coefficients to match the NAE.
     Lconstraints : tuple of Objective
         tuple of constraints of type FixSumModesLambda, which enforce
-        the O(rho) behavior of the equilibrium lambda coefficents to match the NAE.
+        the O(rho) behavior of the equilibrium lambda coefficients to match the NAE.
         Tuple is empty if fix_lambda=False.
 
     """
     if qsc is not None:
         # r is the ratio  r_NAE / rho_DESC
         r = np.sqrt(2 * abs(desc_eq.Psi / qsc.Bbar) / 2 / np.pi)
     else:
-        # TODO: is this true?
         r = 1  # using DESC equilibrium's behavior, no conversion is needed
 
     Rconstraints = ()

desc/objectives/objective_funs.py

@@ -613,7 +613,7 @@ def unpack_state(self, x, per_objective=True):
 
     def x(self, *things):
         """Return the full state vector from the Optimizable objects things."""
-        # TODO: also check resolution etc?
+        # TODO (#1392): also check resolution of the things etc?
         things = things or self.things
         errorif(
             len(things) != len(self.things),

desc/optimize/_constraint_wrappers.py

@@ -704,7 +704,7 @@ def unpack_state(self, x, per_objective=True):
 
     def x(self, *things):
         """Return the full state vector from the Optimizable objects things."""
-        # TODO: also check resolution etc?
+        # TODO (#1392): also check resolution etc?
         things = things or self.things
         assert [type(t1) is type(t2) for t1, t2 in zip(things, self.things)]
         xs = []
@@ -872,7 +872,7 @@ def grad(self, x, constants=None):
             gradient vector.
 
         """
-        # TODO: figure out projected vjp to make this better
+        # TODO (#1393): figure out projected vjp to make this better
         f = jnp.atleast_1d(self.compute_scaled_error(x, constants))
         J = self.jac_scaled_error(x, constants)
         return f.T @ J

desc/optimize/_desc_wrappers.py

@@ -87,7 +87,7 @@ def _optimize_desc_aug_lagrangian(
             ub,
             lambda x, *c: constraint.jac_scaled(x, c[1]),
         )
-        # TODO: can't pass constants dict into vjp for now
+        # TODO (#1394): can't pass constants dict into vjp for now
         constraint_wrapped.vjp = lambda v, x, *args: constraint.vjp_scaled(v, x)
     else:
         constraint_wrapped = None

desc/optimize/least_squares.py

@@ -344,7 +344,7 @@ def lsqtr(  # noqa: C901
             )
             alltr.append(trust_radius)
             alpha *= tr_old / trust_radius
-            # TODO: does this need to move to the outer loop?
+            # TODO (#1395): does this need to move to the outer loop?
             success, message = check_termination(
                 actual_reduction,
                 cost,

desc/plotting.py

@@ -3340,7 +3340,7 @@ def plot_basis(basis, return_data=False, **kwargs):
     """
     title_fontsize = kwargs.pop("title_fontsize", None)
 
-    # TODO: add all other Basis classes
+    # TODO(#1377): add all other Basis classes
     if basis.__class__.__name__ == "PowerSeries":
         grid = LinearGrid(rho=100, endpoint=True)
         r = grid.nodes[:, 0]