WIP-ADD option to swap the source and target pointcloud when calculating cloud2cloud distance and refactoring

Author: eleniv3d

src/gh/components/DF_cloud_to_cloud_distance/code.py

@@ -21,7 +21,8 @@
 class CloudToCloudDistance(component):
     def RunScript(self,
         i_cloud_source:  typing.List[rg.PointCloud],
-        i_cloud_target: typing.List[rg.PointCloud]):
+        i_cloud_target: typing.List[rg.PointCloud],
+        i_swap: bool):
         """
             The cloud-to-cloud component computes the distance between each point in the source point cloud and its nearest neighbour in thr target point cloud.
 
@@ -38,7 +39,13 @@ def RunScript(self,
         if i_cloud_source is None or i_cloud_target is None:
             ghenv.Component.AddRuntimeMessage(RML.Warning, "Please provide both objects of type point clouds to compare")
             return None
-
+        
+        # swap
+        if i_swap is True:
+            temp = i_cloud_source
+            i_cloud_source = i_cloud_target
+            i_cloud_target = temp
+            
         # conversion
         df_cloud_source_list = [df_cvt_bindings.cvt_rhcloud_2_dfcloud(i_cl_s) for i_cl_s in i_cloud_source]
         df_cloud_target_list = [df_cvt_bindings.cvt_rhcloud_2_dfcloud(i_cl_t) for i_cl_t in i_cloud_target]
@@ -53,5 +60,6 @@ def RunScript(self,
     com = CloudToCloudDistance()
     o_distances, o_mse, o_max_deviation, o_min_deviation, o_std_deviation, o_results = com.RunScript(
         i_cloud_source,
-        i_cloud_target
+        i_cloud_target,
+        i_swap
         )

src/gh/components/DF_vizualization/code.py

@@ -36,30 +36,30 @@ def RunScript(self,
         # by default we color the target
         distances_flattened = [item for sublist in i_results.distances for item in sublist]
 
-        min_value = min(min(sublist) for sublist in i_results.distances)
-
         if i_viz_settings.lower_threshold is not None:
             min_value = i_viz_settings.lower_threshold
+        else:
+            min_value = min(min(sublist) for sublist in i_results.distances)
 
         if i_viz_settings.upper_threshold is not None:
             max_value = i_viz_settings.upper_threshold
         else:
             max_value = max(max(sublist) for sublist in i_results.distances)
 
-        o_source = [df_vizualization.color_pcd(src, dist, min_value, max_value) for src, dist in zip(o_source, i_results.distances)]
-
-        o_target = [df_cvt_bindings.cvt_dfcloud_2_rhcloud(trg) for trg in i_results.target]
+        # we always color the source
+        # check if source is a pcd
+        o_colored_geo = [df_vizualization.color_pcd(src, dist, min_value, max_value) for src, dist in zip(o_source, i_results.distances)]
 
         o_legend = df_vizualization.create_legend(min_value, max_value)
 
         o_histogram = df_vizualization.create_histogram(distances_flattened, min_value, max_value)
 
-        return o_source, o_target, o_legend, o_histogram
+        return o_source, o_colored_geo, o_legend, o_histogram
 
 
 if __name__ == "__main__":
     com = Vizualization()
-    o_source, o_target, o_legend, o_histogram  = com.RunScript(
+    o_source, o_colored_geo, o_legend, o_histogram  = com.RunScript(
         i_results,
         i_viz_settings
         )