[docs] more docs cleanup

meanas/fdfd/operators.py

@@ -64,11 +64,11 @@ def e_full(
         epsilon: Vectorized dielectric constant
         mu: Vectorized magnetic permeability (default 1 everywhere).
         pec: Vectorized mask specifying PEC cells. Any cells where `pec != 0` are interpreted
-          as containing a perfect electrical conductor (PEC).
+            as containing a perfect electrical conductor (PEC).
-          The PEC is applied per-field-component (i.e. `pec.size == epsilon.size`)
+            The PEC is applied per-field-component (i.e. `pec.size == epsilon.size`)
         pmc: Vectorized mask specifying PMC cells. Any cells where `pmc != 0` are interpreted
-          as containing a perfect magnetic conductor (PMC).
+            as containing a perfect magnetic conductor (PMC).
-          The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
+            The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
 
     Returns:
         Sparse matrix containing the wave operator.
@@ -148,11 +148,11 @@ def h_full(
         epsilon: Vectorized dielectric constant
         mu: Vectorized magnetic permeability (default 1 everywhere)
         pec: Vectorized mask specifying PEC cells. Any cells where `pec != 0` are interpreted
-           as containing a perfect electrical conductor (PEC).
+            as containing a perfect electrical conductor (PEC).
-           The PEC is applied per-field-component (i.e. `pec.size == epsilon.size`)
+            The PEC is applied per-field-component (i.e. `pec.size == epsilon.size`)
         pmc: Vectorized mask specifying PMC cells. Any cells where `pmc != 0` are interpreted
-           as containing a perfect magnetic conductor (PMC).
+            as containing a perfect magnetic conductor (PMC).
-           The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
+            The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
 
     Returns:
         Sparse matrix containing the wave operator.
@@ -217,11 +217,11 @@ def eh_full(
         epsilon: Vectorized dielectric constant
         mu: Vectorized magnetic permeability (default 1 everywhere)
         pec: Vectorized mask specifying PEC cells. Any cells where `pec != 0` are interpreted
-          as containing a perfect electrical conductor (PEC).
+            as containing a perfect electrical conductor (PEC).
-          The PEC is applied per-field-component (i.e. `pec.size == epsilon.size`)
+            The PEC is applied per-field-component (i.e. `pec.size == epsilon.size`)
         pmc: Vectorized mask specifying PMC cells. Any cells where `pmc != 0` are interpreted
-          as containing a perfect magnetic conductor (PMC).
+            as containing a perfect magnetic conductor (PMC).
-          The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
+            The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
 
     Returns:
         Sparse matrix containing the wave operator.
@@ -267,8 +267,8 @@ def e2h(
         dxes: Grid parameters `[dx_e, dx_h]` as described in `meanas.fdmath.types`
         mu: Vectorized magnetic permeability (default 1 everywhere)
         pmc: Vectorized mask specifying PMC cells. Any cells where `pmc != 0` are interpreted
-          as containing a perfect magnetic conductor (PMC).
+            as containing a perfect magnetic conductor (PMC).
-          The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
+            The PMC is applied per-field-component (i.e. `pmc.size == epsilon.size`)
 
     Returns:
         Sparse matrix for converting E to H.
@@ -483,4 +483,3 @@ def e_boundary_source(
 #             (numpy.roll(mask, +1, axis=2) != mask))
 
     return sparse.diags_array(jmask.astype(int)) @ full
-

meanas/fdfd/waveguide_3d.py

@@ -52,7 +52,7 @@ def solve_mode(
         axis: Propagation axis (0=x, 1=y, 2=z)
         polarity: Propagation direction (+1 for +ve, -1 for -ve)
         slices: `epsilon[tuple(slices)]` is used to select the portion of the grid to use
-                as the waveguide cross-section. `slices[axis]` must select exactly one item.
+            as the waveguide cross-section. `slices[axis]` must select exactly one item.
         epsilon: Dielectric constant
         mu: Magnetic permeability (default 1 everywhere)
 
@@ -62,7 +62,7 @@ def solve_mode(
         - `E`: full-grid electric field for the solved mode
         - `H`: full-grid magnetic field for the solved mode
         - `wavenumber`: propagation constant corrected for the discretized
-          propagation axis
+            propagation axis
         - `wavenumber_2d`: propagation constant of the reduced 2D eigenproblem
 
     Notes:

meanas/fdfd/waveguide_cyl.py

@@ -216,13 +216,13 @@ def solve_modes(
      of the bent waveguide with the specified mode number.
 
     Args:
-        mode_number: Number of the mode, 0-indexed
+        mode_numbers: Mode numbers to solve, 0-indexed.
         omega: Angular frequency of the simulation
         dxes: Grid parameters [dx_e, dx_h] as described in meanas.fdmath.types.
-              The first coordinate is assumed to be r, the second is y.
+            The first coordinate is assumed to be r, the second is y.
         epsilon: Dielectric constant
         rmin: Radius of curvature for the simulation. This should be the minimum value of
-               r within the simulation domain.
+            r within the simulation domain.
 
     Returns:
         e_xys: NDArray of vfdfield_t specifying fields. First dimension is mode number.

meanas/fdmath/operators.py

@@ -158,7 +158,7 @@ def cross(
 
     Args:
         B: List `[Bx, By, Bz]` of sparse matrices corresponding to the x, y, z
-           portions of the operator on the left side of the cross product.
+            portions of the operator on the left side of the cross product.
 
     Returns:
         Sparse matrix corresponding to (B x), where x is the cross product.

meanas/fdmath/vectorization.py

@@ -58,7 +58,7 @@ def vec(
 
     Args:
         f: A vector field, e.g. `[f_x, f_y, f_z]` where each `f_` component is a 1- to
-           3-D ndarray (`f_*` should all be the same size). Doesn't fail with `f=None`.
+            3-D ndarray (`f_*` should all be the same size). Doesn't fail with `f=None`.
 
     Returns:
         1D ndarray containing the linearized field (or `None`)
@@ -123,4 +123,3 @@ def unvec(
     if v is None:
         return None
     return v.reshape((nvdim, *shape), order='C')  # type: ignore
-

pyproject.toml

@@ -63,6 +63,7 @@ docs = [
     "mkdocs-print-site-plugin>=2.3",
     "pymdown-extensions>=10.7",
     "htmlark>=1.0",
+    "ruff>=0.6",
     ]
 examples = [
     "matplotlib>=3.10.8",