Preserve UserData dimension

opendm/dem/ground_rectification/extra_dimensions/userdata_dimension.py

@@ -0,0 +1,25 @@
+import numpy as np
+from .dimension import Dimension
+
+class UserDataDimension(Dimension):
+    """A dimension that stores the user data of a point cloud."""
+
+    def __init__(self):
+        super(UserDataDimension, self).__init__()
+
+    def assign_default(self, point_cloud):
+        default = np.full(point_cloud.len(), 0, dtype=np.uint8)
+        super(UserDataDimension, self)._set_values(point_cloud, default)
+
+    def assign(self, *point_clouds, **kwargs):
+
+        # Simply copy the value of the UserData dimension from the original point cloud
+        # to the new point cloud
+        for point_cloud in point_clouds:
+            super(UserDataDimension, self)._set_values(point_cloud, point_cloud.user_data)
+
+    def get_name(self):
+        return 'UserData'
+
+    def get_las_type(self):
+        return 'uint8'

opendm/dem/ground_rectification/io/las_io.py

@@ -1,4 +1,5 @@
 import time
+from opendm.dem.ground_rectification.extra_dimensions.userdata_dimension import UserDataDimension
 import pdal
 import numpy as np
 from opendm import log
@@ -22,6 +23,7 @@ def read_cloud(point_cloud_path):
     blue = arrays["Blue"]
 
     cloud = PointCloud.with_dimensions(x, y, z, classification, red, green, blue)
+    cloud.add_dimension(UserDataDimension(), arrays["UserData"])
 
     return pipeline.metadata["metadata"]["readers.las"], cloud
 
@@ -63,6 +65,7 @@ def write_cloud(metadata, point_cloud, output_point_cloud_path):
     arrays['Red'] = red.astype(np.uint8).ravel()
     arrays['Green'] = green.astype(np.uint8).ravel()
     arrays['Blue'] = blue.astype(np.uint8).ravel()
+    arrays['UserData'] = point_cloud.extra_dimensions["UserData"].ravel()
 
     writer_pipeline = {
         "pipeline": [