WIP-ADD cloud to cloud distance component

Author: mariklad

src/gh/components/DF_cloud_to_cloud_distance/code.py

@@ -13,6 +13,8 @@
 import diffCheck
 from diffCheck import diffcheck_bindings
 from diffCheck import df_cvt_bindings
+from diffCheck import df_error_estimation
+
 import diffCheck.df_util
 
 class CloudToMeshDistance(component):
@@ -28,6 +30,9 @@ def RunScript(self,
             :param i_cloud_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")
@@ -38,9 +43,12 @@ def RunScript(self,
         df_cloud_target = df_cvt_bindings.cvt_rhcloud_2_dfcloud(i_cloud_target)
 
         # calculate distances
-        o_distances = cloud_2_mesh_distance(df_cloud_source, df_cloud_target)
+        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)
 
-        return o_distances
+        return o_distances, o_mse, o_max_deviation, o_min_deviation
 
 
 if __name__ == "__main__":

src/gh/diffCheck/diffCheck/df_error_estimation.py

@@ -4,8 +4,6 @@
     Rhino, the basic diffCheck data structures and the diffCheck bindings.
 """
 
-import Rhino
-import Rhino.Geometry as rg
 import numpy as np
 from diffCheck import diffcheck_bindings
 
@@ -35,23 +33,20 @@ def compute_max_deviation(source, target):
 
     return max_deviation
 
-
-
 def compute_min_deviation(source, target):
     """
         Calculate min deviation of distances
     """
 
-    max_deviation = np.min(cloud_2_cloud_distance(source, target))
+    min_deviation = np.min(cloud_2_cloud_distance(source, target))
 
     return min_deviation
 
-
 def compute_standard_deviation(source, target):
     """
         Calculate standard deviation of distances
     """
 
-    std_deviation = np.std(cloud_2_cloud_distance(source, target))
+    standard_deviation = np.std(cloud_2_cloud_distance(source, target))
 
     return standard_deviation