[pre-commit.ci] auto fixes from pre-commit.com hooks

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graph_weather/models/graphs/ico.py

@@ -283,8 +283,8 @@ def inside_points(vAB, vAC):
         j = i + 1
         interp_multipliers = (np.arange(1, j) / j)[:, None]
         out.append(
-            np.multiply(interp_multipliers, vAC[i, None]) +
-            np.multiply(1 - interp_multipliers, vAB[i, None])
+            np.multiply(interp_multipliers, vAC[i, None])
+            + np.multiply(1 - interp_multipliers, vAB[i, None])
         )
     return np.concatenate(out)
 
@@ -298,6 +298,7 @@ def generate_icosphere_graph(resolution=1):
     edges = np.unique(np.sort(edges, axis=1), axis=0)
     return vertices, edges
 
+
 def generate_icosphere_mapping(lat_lons, resolutions=(1, 2, 4, 8, 16, 32, 64)) -> Data:
     """
     Generate mapping from lat/lon to icosphere index.
@@ -325,13 +326,18 @@ def generate_icosphere_mapping(lat_lons, resolutions=(1, 2, 4, 8, 16, 32, 64)) -
     # Check the verticies of each pair are the same up to the resolution
     for i in range(len(verticies_per_level) - 1):
         for vertex_lower_index, vertex in enumerate(verticies_per_level[i]):
-            vertex_mapping = np.argmin(np.sum(np.abs(verticies_per_level[i + 1] - vertex), axis=1), axis=0)
+            vertex_mapping = np.argmin(
+                np.sum(np.abs(verticies_per_level[i + 1] - vertex), axis=1), axis=0
+            )
             # Change all edge indicies from vertex_lower_index to vertex_mapping
             edges_per_level[i + 1][edges_per_level[i + 1] == vertex_lower_index] = vertex_mapping
-    verticies = verticies_per_level[-1] # The last layer has all the verticies of the ones above
+    verticies = verticies_per_level[-1]  # The last layer has all the verticies of the ones above
     edges = np.unique(np.sort(np.concatenate(edges_per_level), axis=1), axis=0)
     # TODO Create mapping from the lat/lon to the icosphere nodes
-    ico_graph = Data(x=torch.tensor(verticies, dtype=torch.float), edge_index=torch.tensor(edges, dtype=torch.long).t().contiguous())
+    ico_graph = Data(
+        x=torch.tensor(verticies, dtype=torch.float),
+        edge_index=torch.tensor(edges, dtype=torch.long).t().contiguous(),
+    )
     return ico_graph