💬 Update type hints

src/arpes/deep_learning/transforms.py

@@ -15,15 +15,44 @@ class Identity:
     """Represents a reversible identity transform."""
 
     def encodes(self, x: Incomplete) -> Incomplete:
+        """[TODO:summary].
+
+        Args:
+            x: [TODO:description]
+
+        Returns:
+            [TODO:description]
+        """
         return x
 
     def __call__(self, x: Incomplete) -> Incomplete:
+        """[TODO:summary].
+
+        Args:
+            x: [TODO:description]
+
+        Returns:
+            [TODO:description]
+        """
         return x
 
     def decodes(self, x: Incomplete) -> Incomplete:
+        """[TODO:summary].
+
+        Args:
+            x: [TODO:description]
+
+        Returns:
+            [TODO:description]
+        """
         return x
 
     def __repr__(self) -> str:
+        """[TODO:summary].
+
+        Returns:
+            [TODO:description]
+        """
         return "Identity()"
 
 
@@ -54,9 +83,9 @@ def __post_init__(self) -> None:
         for t in self.transforms:
             if isinstance(t, tuple | list):
                 xt, yt = t
-                t = [xt or _identity, yt or _identity]
-
-            safe_transforms.append(t)
+                safe_transforms.append([xt or _identity, yt or _identity])
+            else:
+                safe_transforms.append(t)
 
         self.original_transforms = self.transforms
         self.transforms = safe_transforms

src/arpes/plotting/spin.py

@@ -163,11 +163,9 @@ def spin_polarized_spectrum(  # noqa: PLR0913
         counts = spin_dr
         pol = to_intensity_polarization(counts)
 
-    ax_left = ax[0]
-    ax_right = ax[1]
+    ax_left, ax_right = ax[0], ax[1]
 
-    up = counts.down.data
-    down = counts.up.data
+    down, up = counts.down.data, counts.up.data
 
     energies = spin_dr.coords["eV"].values
     min_e, max_e = np.min(energies), np.max(energies)
@@ -194,8 +192,7 @@ def spin_polarized_spectrum(  # noqa: PLR0913
     ax_left.set_xlabel(r"\textbf{Kinetic energy} (eV)")
     ax_left.set_xlim(min_e, max_e)
 
-    max_up = np.max(up)
-    max_down = np.max(down)
+    max_up, max_down = np.max(up), np.max(down)
     ax_left.set_ylim(0, max(max_down, max_up) * 1.2)
 
     # Plot the polarization and associated statistical error bars
@@ -296,7 +293,7 @@ def hue_brightness_plot(
     assert isinstance(ax, Axes)
     assert isinstance(fig, Figure)
     x, y = data.coords[data.intensity.dims[0]].values, data.coords[data.intensity.dims[1]].values
-    extent = [y[0], y[-1], x[0], x[-1]]
+    extent = (y[0], y[-1], x[0], x[-1])
     ax.imshow(
         polarization_intensity_to_color(data, **kwargs),
         extent=extent,

src/arpes/utilities/qt/app.py

@@ -143,7 +143,7 @@ def set_colormap(self, colormap: Colormap | str) -> None:
             if isinstance(view, DataArrayImageView):
                 view.setColorMap(cmap)
 
-    def generate_marginal_for(
+    def generate_marginal_for(  # noqa: PLR0913
         self,
         dimensions: tuple[int, ...],
         column: int,