update algo MNx and test

RELEASE_NOTES.md

@@ -1,3 +1,7 @@
+### 0.3.0
+
+Update algorithm of [mark_points_to_use_for_digital_models_with_new_dimension](pdal_ign_macro/mark_points_to_use_for_digital_models_with_new_dimension.py), 
+
 ### 0.2.1
 
 Fix (and test) arguments parsing in [mark_points_to_use_for_digital_models_with_new_dimension](pdal_ign_macro/mark_points_to_use_for_digital_models_with_new_dimension.py)

pdal_ign_macro/version.py

@@ -1,4 +1,4 @@
-__version__ = "0.2.1"
+__version__ = "0.3.0"
 
 
 if __name__ == "__main__":

test/pdal_ign_macro/test_mark_points_to_use_for_digital_models_with_new_dimension.py

@@ -4,6 +4,11 @@
 import numpy as np
 import pdal
 
+import pytest
+
+from pdaltools.las_remove_dimensions import remove_dimensions_from_las
+
+
 from pdal_ign_macro.mark_points_to_use_for_digital_models_with_new_dimension import (
     main,
     mark_points_to_use_for_digital_models_with_new_dimension,
@@ -131,3 +136,62 @@ def test_parse_args():
     parsed_args_keys = args.__dict__.keys()
     main_parameters = inspect.signature(main).parameters.keys()
     assert parsed_args_keys == main_parameters
+
+
+@pytest.mark.parametrize(
+    "crop",
+    [
+        "crop_1.laz",
+        "crop_2.laz",
+        "crop_3.laz",
+    ],
+)
+def test_algo_mark_points_for_dm_with_reference(crop):
+    ini_las = "test/data/mnx/input/" + crop
+    dsm_dimension = "dsm_marker"
+    dtm_dimension = "dtm_marker"
+    with tempfile.NamedTemporaryFile(suffix="_after.las") as las_output:
+        main(
+            ini_las,
+            las_output.name,
+            dsm_dimension,
+            dtm_dimension,
+            "",
+            "",
+            keep_temporary_dims=False,
+            skip_buffer=True,
+        )
+        pipeline = pdal.Pipeline()
+        pipeline.execute()
+
+        def sort_points(points):
+            sorted_index = np.lexsort((points["Y"], points["X"], points["Z"], points["GpsTime"]))
+            np.set_printoptions(precision=30)
+            sorted_points = points[sorted_index]
+            return sorted_points
+
+        pipeline_calc = pdal.Pipeline() | pdal.Reader.las(filename=las_output.name)
+        pipeline_calc.execute()
+        arr_result = pipeline_calc.arrays[0]
+
+        # read reference :
+        ref_las = "test/data/mnx/reference/" + crop
+
+        pipeline_ref = pdal.Pipeline() | pdal.Reader.las(filename=ref_las)
+        pipeline_ref.execute()
+        arr_reference = pipeline_ref.arrays[0]
+
+        assert len(arr_result) == len(arr_reference)
+
+        arr_result = sort_points(arr_result)
+        arr_reference = sort_points(arr_reference)
+
+        arr_result_dimensions = list(arr_result.dtype.fields.keys())
+        arr_ref_dimensions = list(arr_reference.dtype.fields.keys())
+
+        assert arr_result_dimensions == arr_ref_dimensions
+
+        for dim in arr_result_dimensions:
+            diff_mask = np.where(arr_result[dim] == arr_reference[dim], 0, 1)
+            nb_pts_incorrect = np.count_nonzero(diff_mask)
+            assert nb_pts_incorrect == 0