filter search => assign

CMakeLists.txt

@@ -12,5 +12,5 @@ set(CMAKE_DEBUG_POSTFIX d)
 
 ## add plugin
 add_subdirectory(src/filter_grid_decimation)
-add_subdirectory(src/filter_radius_search)
+add_subdirectory(src/filter_radius_assign)
 

doc/grid_radius_search.md → doc/grid_radius_assign.md

@@ -1,9 +1,9 @@
-# filter grid decimation
+# filter radius assign
 
 Purpose
 ---------------------------------------------------------------------------------------------------------
 
-The **radius search filter** add a new attribut where the value depends on their neighbors in a given radius: For each point in the domain src_domain_, if it has any neighbor with a distance lower than radius_ that belongs to the domain reference_domain_, it is updated.
+The **radius assign filter** add a new attribut where the value depends on their neighbors in a given radius: For each point in the domain src_domain_, if it has any neighbor with a distance lower than radius_ that belongs to the domain reference_domain_, it is updated.
 
 
 Example
@@ -16,7 +16,7 @@ This pipeline updates the Keypoint dimension of all points with classification 1
   [
      "file-input.las",
       {
-          "type" : "filters.radiussearch",
+          "type" : "filters.radius_assign",
           "src_domain" : "Classification[1:2]",
           "reference_domain" : "Classification[6:6]",
           "radius" : 1,

macro/ex_filtering_points.py

@@ -19,36 +19,36 @@ def parse_args():
     pipeline = pdal.Reader.las(args.input)
 
     # step 1 a 9
-    pipeline = macro.add_radius_search(pipeline, 1, False, "Classification==2", macro.build_condition("Classification", [4,5]), "Classification=102")
-    pipeline = macro.add_radius_search(pipeline, 1, False, "Classification==102", "Classification==2", "Classification=2")
-    pipeline = macro.add_radius_search(pipeline, 1, False, "Classification==3", "Classification==5", "Classification=103")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, "Classification==2", macro.build_condition("Classification", [4,5]), "Classification=102")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, "Classification==102", "Classification==2", "Classification=2")
+    pipeline = macro.add_radius_assign(pipeline, 1, False, "Classification==3", "Classification==5", "Classification=103")
     pipeline = macro.add_grid_decimation(pipeline, 0.75, "max", macro.build_condition("Classification", [4,5,102,103]), "Classification=100")
     pipeline |= pdal.Filter.assign(value="Classification=2", where="Classification==102")
     pipeline |= pdal.Filter.assign(value="Classification=3", where="Classification==103")
     pipeline = macro.add_grid_decimation(pipeline, 0.5, "max", "Classification==2", "Classification=102")
     pipeline = macro.add_grid_decimation(pipeline, 0.5, "max", macro.build_condition("Classification", [2,3,4,5,6,9,17,64,100]), "Classification=200")
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==102", macro.build_condition("Classification", [4,5,6,9,17,64,100]), "Classification=100")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==102", macro.build_condition("Classification", [4,5,6,9,17,64,100]), "Classification=100")
     pipeline |= pdal.Filter.assign(value="Classification=2", where="Classification==102")
 
     # step 10
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==2", "Classification==17", "Classification=102")
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==102", macro.build_condition("Classification", [2,3,4,5]), "Classification=2")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==2", "Classification==17", "Classification=102")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==102", macro.build_condition("Classification", [2,3,4,5]), "Classification=2")
 
     # step 11
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==3", "Classification==17", "Classification=103")
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==103", macro.build_condition("Classification", [2,3,4,5]), "Classification=3")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==3", "Classification==17", "Classification=103")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==103", macro.build_condition("Classification", [2,3,4,5]), "Classification=3")
 
     # step 12
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==4", "Classification==17", "Classification=104")
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==104", macro.build_condition("Classification", [2,3,4,5]), "Classification=4")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==4", "Classification==17", "Classification=104")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==104", macro.build_condition("Classification", [2,3,4,5]), "Classification=4")
 
     # step 13
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==5", "Classification==17", "Classification=105")
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==105", macro.build_condition("Classification", [2,3,4,5]), "Classification=5")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==5", "Classification==17", "Classification=105")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==105", macro.build_condition("Classification", [2,3,4,5]), "Classification=5")
 
     # step 14
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==9", "Classification==17", "Classification=109")
-    pipeline = macro.add_radius_search(pipeline, 1.5, False, "Classification==109", "Classification==9", "Classification=9")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==9", "Classification==17", "Classification=109")
+    pipeline = macro.add_radius_assign(pipeline, 1.5, False, "Classification==109", "Classification==9", "Classification=9")
 
     pipeline |= pdal.Writer.las(extra_dims="all",minor_version=4,dataformat_id=6,filename=args.output)
     pipeline.execute()

macro/macro.py

@@ -6,7 +6,7 @@
 """
 
 
-def add_radius_search(pipeline, radius, search_3d, condition_src, condition_ref, condition_out ):
+def add_radius_assign(pipeline, radius, search_3d, condition_src, condition_ref, condition_out ):
     """
     search points from "condition_src" closed from "condition_ref", and reassign them to "condition_out"
     This combination is equivalent to the CloseBy macro of TerraScan
@@ -18,7 +18,7 @@ def add_radius_search(pipeline, radius, search_3d, condition_src, condition_ref,
     pipeline |= pdal.Filter.assign(value=["SRS_DOMAIN = 0", f"SRS_DOMAIN = 1 WHERE {condition_src}",
                                           "REF_DOMAIN = 0", f"REF_DOMAIN = 1 WHERE {condition_ref}",
                                           "radius_search = 0"])
-    pipeline |= pdal.Filter.radius_search(radius=radius, src_domain="SRS_DOMAIN",reference_domain="REF_DOMAIN",
+    pipeline |= pdal.Filter.radius_assign(radius=radius, src_domain="SRS_DOMAIN",reference_domain="REF_DOMAIN",
                                           output_name_attribute="radius_search", search_3d=search_3d)
     pipeline |= pdal.Filter.assign(value=condition_out,where="radius_search==1")
     return pipeline

src/filter_radius_assign/CMakeLists.txt

@@ -0,0 +1,16 @@
+
+file( GLOB_RECURSE GD_SRCS 
+	${CMAKE_SOURCE_DIR}/src/filter_radius_assign/*.hpp
+	${CMAKE_SOURCE_DIR}/src/filter_radius_assign/*.cpp)
+
+PDAL_CREATE_PLUGIN(
+    TYPE filter
+    NAME radius_assign
+    VERSION 1.0
+    SOURCES ${GD_SRCS}
+)
+
+install(TARGETS
+	pdal_plugin_filter_radius_assign
+)
+

src/filter_radius_search/radius_searchFilter.cpp → src/filter_radius_assign/radius_assignFilter.cpp

@@ -1,4 +1,4 @@
-#include "radius_searchFilter.hpp"
+#include "radius_assignFilter.hpp"
 
 #include <pdal/PipelineManager.hpp>
 #include <pdal/StageFactory.hpp>
@@ -13,7 +13,7 @@ namespace pdal
 {
 
 static PluginInfo const s_info = PluginInfo(
-    "filters.radius_search",
+    "filters.radius_assign",
     "Re-assign some point attributes based KNN voting",
     "" );
 

test/test_radius_search.py → test/test_radius_assign.py

@@ -20,7 +20,7 @@ def distance3d(pt1, pt2):
 
 def run_filter(arrays_las, distance_radius, search_3d, distance_cylinder=0. ):
 
-    filter = "filters.radius_search"
+    filter = "filters.radius_assign"
     utils.pdal_has_plugin(filter)
 
     with tempfile.NamedTemporaryFile(suffix="_las_tmp.las") as las:
@@ -99,7 +99,7 @@ def build_random_points_around_one_point(test_function):
     return arrays_las, nb_points_take
 
 
-def test_radius_search_3d():
+def test_radius_assign_3d():
 
     distance_radius = 1
 
@@ -114,7 +114,7 @@ def func_test(pt_ini, pt):
     assert nb_pts_radius_3d == nb_points_take_3d
 
 
-def test_radius_search_2d():
+def test_radius_assign_2d():
 
     distance_radius = 1
 
@@ -129,7 +129,7 @@ def func_test(pt_ini, pt):
     assert nb_pts_radius_2d == nb_points_take_2d
 
 
-def test_radius_search_2d_cylinder():
+def test_radius_assign_2d_cylinder():
 
     distance_radius = 1
     distance_cylinder = 0.25