💬 Update type hints

src/arpes/plotting/bz.py

@@ -33,8 +33,6 @@
     from matplotlib.typing import ColorType
     from numpy.typing import ArrayLike, NDArray
 
-    from arpes._typing import DataType
-
 __all__ = (
     "annotate_special_paths",
     "bz2d_plot",

src/arpes/plotting/dispersion.py

@@ -49,7 +49,7 @@ def plot_dispersion(
     out: str | Path = "",
 ) -> Axes | Path:
     """Plots an ARPES cut with bands over it."""
-    ax = spectrum.plot()
+    ax = spectrum.S.plot()
 
     for band in bands:
         plt.scatter(band.center.values, band.coords[band.dims[0]].values)
@@ -70,7 +70,7 @@ class CutDispersionPlotParam(TypedDict, total=False):
 def cut_dispersion_plot(  # noqa: PLR0913
     data: xr.DataArray,
     e_floor: float | None = None,
-    ax: Axes | None = None,
+    ax: Axes3D | None = None,
     *,
     include_symmetry_points: bool = True,
     out: str | Path = "",

src/arpes/plotting/spatial.py

@@ -40,7 +40,7 @@
 
 
 @save_plot_provenance
-def plot_spatial_reference(
+def plot_spatial_reference(  # noqa: PLR0913
     reference_map: xr.DataArray,
     data_list: list[DataType],
     offset_list: list[dict[str, Any] | None] | None = None,
@@ -246,7 +246,7 @@ def reference_scan_spatial(
     if offset > 0:
         offset = 0
 
-    if rng > 3:
+    if rng > 3:  # noqa: PLR2004
         mul = rng / 5.0
 
     for i in range(5):
@@ -265,7 +265,7 @@ def reference_scan_spatial(
 
     # idea here is to collect points by those that are close together, then
     # only plot one annotation
-    condensed = []
+    condensed: list[tuple[float, float, list[int]]] = []
     cutoff = 3  # 3 percent
     for index, _ in referenced.iterrows():
         ff = load_data(index)