WIP-ADD helper functions for error_estimation

Author: mariklad

src/gh/diffCheck/diffCheck/df_error_estimation.py

@@ -0,0 +1,57 @@
+#! python3
+"""
+    This module contains the utility functions to convert the data between the
+    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
+
+def cloud_2_cloud_distance(source, target):
+
+    # Convert pts to np array and calculate distances
+    distances = np.linalg.norm(np.asarray(source.points) - np.asarray(target.points), axis=1)
+
+    return distances
+
+def compute_mse(source, target):
+    """
+        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):
+    """
+        Calculate max deviation of distances
+    """
+     
+    max_deviation = np.max(cloud_2_cloud_distance(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))
+
+    return min_deviation
+
+
+def compute_standard_deviation(source, target):
+    """
+        Calculate standard deviation of distances
+    """
+     
+    std_deviation = np.std(cloud_2_cloud_distance(source, target))
+
+    return standard_deviation