WIP-FIX Cloud2Cloud

Author: eleniv3d

src/gh/components/DF_cloud_to_cloud_distance/code.py

@@ -32,7 +32,6 @@ def RunScript(self,
             :return o_max_deviation: the max deviation between source and target (Hausdorff Distance)
             :return o_min_deviation: the min deviation between source and target
         """
-        print ("yes")
         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
@@ -43,16 +42,16 @@ def RunScript(self,
 
         # calculate distances
         o_distances = df_error_estimation.cloud_2_cloud_distance(df_cloud_source, df_cloud_target)
-        o_mse = df_error_estimation.compute_mse(df_cloud_source, df_cloud_target)
-        o_max_deviation = df_error_estimation.compute_max_deviation(df_cloud_source, df_cloud_target)
-        o_min_deviation = df_error_estimation.compute_min_deviation(df_cloud_source, df_cloud_target)
+        o_mse = df_error_estimation.compute_mse(o_distances)
+        o_max_deviation = df_error_estimation.compute_max_deviation(o_distances)
+        o_min_deviation = df_error_estimation.compute_min_deviation(o_distances)
 
-        return o_distances
+        return o_distances, o_mse, o_max_deviation, o_min_deviation
 
 
 if __name__ == "__main__":
-    com = CloudToCloudDistance(component)
-    o_distances = com.RunScript(
+    com = CloudToCloudDistance()
+    o_distances, o_mse, o_max_deviation, o_min_deviation = com.RunScript(
         i_cloud_source,
         i_cloud_target
         )

src/gh/components/DF_cloud_to_mesh_distance/code.py

@@ -13,39 +13,43 @@
 import diffCheck
 from diffCheck import diffcheck_bindings
 from diffCheck import df_cvt_bindings
-import diffCheck.df_util
+from diffCheck import df_error_estimation
 
-class CloudToCloudDistance(component):
+class CloudToMeshDistance(component):
     def RunScript(self,
         i_cloud_source: rg.PointCloud,
-        i_cloud_target: rg.PointCloud,
-        
-    ) -> [float]:
+        i_mesh_target: rg.PointCloud):
         """
             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.
 
             :param i_cloud_source: source point cloud
-            :param i_cloud_target: target point cloud to align to
+            :param i_mesh_target: target point cloud to align to
 
             :return o_distances : list of calculated distances for each point
+            :return o_mse: the average squared difference between corresponding points of source and target
+            :return o_max_deviation: the max deviation between source and target (Hausdorff Distance)
+            :return o_min_deviation: the min deviation between source and target
         """
-        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")
+        if i_cloud_source is None or i_mesh_target is None:
+            ghenv.Component.AddRuntimeMessage(RML.Warning, "Please provide an object of type point cloud and an object of type mesh to compare")
             return None
 
         # conversion
         df_cloud_source = df_cvt_bindings.cvt_rhcloud_2_dfcloud(i_cloud_source)
-        df_cloud_target = df_cvt_bindings.cvt_rhcloud_2_dfcloud(i_cloud_target)
+        df_mesh_target = df_cvt_bindings.cvt_rhmesh_2_dfmesh(i_mesh_target)
 
         # calculate distances
-        o_distances = cloud_2_cloud_distance(df_cloud_source, df_cloud_target)
+        o_distances = df_error_estimation.cloud_2_mesh_distance(df_cloud_source, df_mesh_target)
+        o_mse = df_error_estimation.compute_mse(o_distances)
+        o_max_deviation = df_error_estimation.compute_max_deviation(o_distances)
+        o_min_deviation = df_error_estimation.compute_min_deviation(o_distances)
 
-        return o_distances
+        return o_distances, o_mse, o_max_deviation, o_min_deviation
 
 
-# if __name__ == "__main__":
-#     com = CloudToCloudDistance(component)
-#     o_distances = com.RunScript(
-#         i_cloud_source,
-#         i_cloud_target
-#         )
+if __name__ == "__main__":
+    com = CloudToMeshDistance()
+    o_distances, o_mse, o_max_deviation, o_min_deviation = com.RunScript(
+        i_cloud_source,
+        i_mesh_target
+        )

src/gh/diffCheck/diffCheck/df_error_estimation.py

@@ -14,39 +14,44 @@ def cloud_2_cloud_distance(source, target):
 
     return distances
 
-def compute_mse(source, target):
+def cloud_2_mesh_distance(source, target):
+
+    distances = np.ones(len(source.points), dtype=float)
+
+    return distances
+
+def compute_mse(distances):
     """
         Calculate mean squared distance
     """
 
-    distances = cloud_2_cloud_distance(source, target)
     mse = np.sqrt(np.mean(distances ** 2))
 
     return mse
 
-def compute_max_deviation(source, target):
+def compute_max_deviation(distances):
     """
         Calculate max deviation of distances
     """
 
-    max_deviation = np.max(cloud_2_cloud_distance(source, target))
+    max_deviation = np.max(distances)
 
     return max_deviation
 
-def compute_min_deviation(source, target):
+def compute_min_deviation(distances):
     """
         Calculate min deviation of distances
     """
 
-    min_deviation = np.min(cloud_2_cloud_distance(source, target))
+    min_deviation = np.min(distances)
 
     return min_deviation
 
-def compute_standard_deviation(source, target):
+def compute_standard_deviation(distances):
     """
         Calculate standard deviation of distances
     """
 
-    standard_deviation = np.std(cloud_2_cloud_distance(source, target))
+    standard_deviation = np.std(distances)
 
-    return standard_deviation
+    return standard_deviation