delaunay plotter unitt est

Jammy2211 · Nov 14, 2024 · 7dd9b07 · 7dd9b07
1 parent 852e093
commit 7dd9b07
Show file tree

Hide file tree

Showing 4 changed files with 49 additions and 30 deletions.
diff --git a/autoarray/config/visualize/mat_wrap_2d.yaml b/autoarray/config/visualize/mat_wrap_2d.yaml
@@ -146,15 +146,15 @@ VectorYXQuiver:      # wrapper for `plt.quiver()`: customize (y,x) vectors appea
     linewidth: 5
     pivot: middle
     units: xy
-DelaunayDrawer:       # wrapper for `plt.fill()`: customize the appearance of Voronoi mesh's.
+DelaunayDrawer:       # wrapper for `plt.fill()`: customize the appearance of Delaunay mesh's.
   figure:
     alpha: 0.7
     edgecolor: k
     linewidth: 0.0
   subplot:
     alpha: 0.7
     edgecolor: k
-    linewidth: 0.0
+    linewidth: 0.0  
 VoronoiDrawer:       # wrapper for `plt.fill()`: customize the appearance of Voronoi mesh's.
   figure:
     alpha: 0.7

diff --git a/autoarray/plot/mat_plot/two_d.py b/autoarray/plot/mat_plot/two_d.py
@@ -48,7 +48,7 @@ def __init__(
         vector_yx_quiver: Optional[w2d.VectorYXQuiver] = None,
         patch_overlay: Optional[w2d.PatchOverlay] = None,
         interpolated_reconstruction: Optional[w2d.InterpolatedReconstruction] = None,
-        delaunay_drawer : Optional[w2d.DelaunayDrawer] = None,
+        delaunay_drawer: Optional[w2d.DelaunayDrawer] = None,
         voronoi_drawer: Optional[w2d.VoronoiDrawer] = None,
         origin_scatter: Optional[w2d.OriginScatter] = None,
         mask_scatter: Optional[w2d.MaskScatter] = None,
@@ -662,21 +662,21 @@ def _plot_delaunay_mapper(
         interpolation_array = None
 
         if interpolate_to_uniform:
-
-            interpolation_array = self.interpolated_reconstruction.imshow_reconstruction(
-                mapper=mapper,
-                pixel_values=pixel_values,
-                units=self.units,
-                cmap=self.cmap,
-                colorbar=self.colorbar,
-                colorbar_tickparams=self.colorbar_tickparams,
-                aspect=aspect_inv,
-                ax=ax,
-                use_log10=self.use_log10,
+            interpolation_array = (
+                self.interpolated_reconstruction.imshow_reconstruction(
+                    mapper=mapper,
+                    pixel_values=pixel_values,
+                    units=self.units,
+                    cmap=self.cmap,
+                    colorbar=self.colorbar,
+                    colorbar_tickparams=self.colorbar_tickparams,
+                    aspect=aspect_inv,
+                    ax=ax,
+                    use_log10=self.use_log10,
+                )
             )
 
         else:
-
             self.delaunay_drawer.draw_delaunay_pixels(
                 mapper=mapper,
                 pixel_values=pixel_values,

diff --git a/autoarray/plot/wrap/two_d/delaunay_drawer.py b/autoarray/plot/wrap/two_d/delaunay_drawer.py
@@ -9,10 +9,7 @@
 from autoarray.plot.wrap import base as wb
 
 
-def facecolors_from(
-        values,
-        simplices
-):
+def facecolors_from(values, simplices):
     facecolors = np.zeros(shape=simplices.shape[0])
     for i in range(simplices.shape[0]):
         facecolors[i] = np.sum(1.0 / 3.0 * values[simplices[i, :]])
@@ -65,17 +62,19 @@ def draw_delaunay_pixels(
             If `True`, the colorbar is plotted using a log10 scale.
         """
 
+        if pixel_values is None:
+            raise ValueError(
+                "pixel_values input to DelaunayPlotter are None and thus cannot be plotted."
+            )
+
         if ax is None:
             ax = plt.gca()
 
         source_pixelization_grid = mapper.mapper_grids.source_plane_mesh_grid
 
         simplices = mapper.delaunay.simplices
 
-        facecolors = facecolors_from(
-            values=pixel_values,
-            simplices=simplices
-        )
+        facecolors = facecolors_from(values=pixel_values, simplices=simplices)
 
         norm = cmap.norm_from(array=pixel_values, use_log10=use_log10)
 
@@ -89,15 +88,9 @@ def draw_delaunay_pixels(
         color_values = np.where(pixel_values > vmax, vmax, pixel_values)
         color_values = np.where(pixel_values < vmin, vmin, color_values)
 
-        if vmax != vmin:
-            color_array = (color_values - vmin) / (vmax - vmin)
-        else:
-            color_array = np.ones(color_values.shape[0])
-
         cmap = plt.get_cmap(cmap.cmap)
 
         if colorbar is not None:
-
             cb = colorbar.set_with_color_values(
                 units=units,
                 norm=norm,
@@ -120,4 +113,4 @@ def draw_delaunay_pixels(
             vmin=vmin,
             vmax=vmax,
             **self.config_dict
-        )
+        )
diff --git a/test_autoarray/plot/wrap/two_d/test_delaunay_drawer.py b/test_autoarray/plot/wrap/two_d/test_delaunay_drawer.py
@@ -0,0 +1,26 @@
+import autoarray.plot as aplt
+
+import numpy as np
+
+
+def test__draws_delaunay_pixels_for_sensible_input(delaunay_mapper_9_3x3):
+    delaunay_drawer = aplt.DelaunayDrawer(linewidth=0.5, edgecolor="r", alpha=1.0)
+
+    delaunay_drawer.draw_delaunay_pixels(
+        mapper=delaunay_mapper_9_3x3,
+        pixel_values=np.ones(9),
+        units=aplt.Units(),
+        cmap=aplt.Cmap(),
+        colorbar=None,
+    )
+
+    values = np.ones(9)
+    values[0] = 0.0
+
+    delaunay_drawer.draw_delaunay_pixels(
+        mapper=delaunay_mapper_9_3x3,
+        pixel_values=values,
+        units=aplt.Units(),
+        cmap=aplt.Cmap(),
+        colorbar=aplt.Colorbar(fraction=0.1, pad=0.05),
+    )