Lint

.flake8

@@ -0,0 +1,13 @@
+[flake8]
+max_line_length = 99
+show_source = True
+format = pylint
+extend-ignore = E203,E501
+exclude =
+    .git
+    __pycache__
+    logs/*
+    .vscode/*
+    build/*
+    install/*
+    src/*

.pre-commit-config.yaml

@@ -1,11 +1,10 @@
 repos:
   - repo: https://github.com/ambv/black
-    rev: 23.12.0
+    rev: 24.4.2
     hooks:
       - id: black
-        language_version: python3.11
   - repo: https://github.com/pycqa/flake8
-    rev: 6.1.0
+    rev: 7.0.0
     hooks:
     -   id: flake8
   - repo: https://github.com/pycqa/isort

macro/ex_filtering_points.py

@@ -1,15 +1,20 @@
 import argparse
+
 import pdal
+
 import macro
 
 """
 This tool shows how to use functions of macro in a pdal pipeline
 """
 
+
 def parse_args():
     parser = argparse.ArgumentParser("Tool to apply pdal pipelines for DSM and DTM calculation")
     parser.add_argument("--input", "-i", type=str, required=True, help="Input las file")
-    parser.add_argument("--output_las", "-o", type=str, required=True, help="Output cloud las file")
+    parser.add_argument(
+        "--output_las", "-o", type=str, required=True, help="Output cloud las file"
+    )
     parser.add_argument("--output_dsm", "-s", type=str, required=True, help="Output dsm tiff file")
     parser.add_argument("--output_dtm", "-t", type=str, required=True, help="Output dtm tiff file")
     return parser.parse_args()
@@ -20,75 +25,188 @@ def parse_args():
 
     pipeline = pdal.Reader.las(args.input)
 
-    ## 1 - recherche des points max de végétation (4,5) sur une grille régulière, avec prise en compte des points sol (2) et basse
-    ##     vegetation (3) proche de la végétation : on les affecte en 100
+    # 1 - recherche des points max de végétation (4,5) sur une grille régulière, avec prise en compte des points sol (2) et basse
+    #     vegetation (3) proche de la végétation : on les affecte en 100
 
     # bouche trou : assigne les points sol en 102 à l'intérieur de la veget (4,5)
-    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==2", condition_ref=macro.build_condition("Classification", [4,5]), condition_out="Classification=102")
-    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==102", condition_ref="Classification==2", condition_out="Classification=2")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1,
+        False,
+        condition_src="Classification==2",
+        condition_ref=macro.build_condition("Classification", [4, 5]),
+        condition_out="Classification=102",
+    )
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1,
+        False,
+        condition_src="Classification==102",
+        condition_ref="Classification==2",
+        condition_out="Classification=2",
+    )
 
     # selection des points de veget basse proche de la veget haute : assigne 103
-    pipeline = macro.add_radius_assign(pipeline, 1, False, condition_src="Classification==3", condition_ref="Classification==5", condition_out="Classification=103")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1,
+        False,
+        condition_src="Classification==3",
+        condition_ref="Classification==5",
+        condition_out="Classification=103",
+    )
 
     # max des points de veget (et surement veget - 102,103) sur une grille régulière : assigne 100
-    pipeline |= pdal.Filter.gridDecimation(resolution=0.75, value="Classification=100", output_type="max", where=macro.build_condition("Classification", [4,5,102,103]))
+    pipeline |= pdal.Filter.gridDecimation(
+        resolution=0.75,
+        value="Classification=100",
+        output_type="max",
+        where=macro.build_condition("Classification", [4, 5, 102, 103]),
+    )
 
     # remise à zero des codes 102 et 103
     pipeline |= pdal.Filter.assign(value="Classification=2", where="Classification==102")
     pipeline |= pdal.Filter.assign(value="Classification=3", where="Classification==103")
 
-    ## 2 - sélection des points pour DTM et DSM
+    # 2 - sélection des points pour DTM et DSM
 
     # selection de points sol (max) sur une grille régulière
-    pipeline |= pdal.Filter.gridDecimation(resolution=0.5, value="Classification=102", output_type="max", where="Classification==2")
+    pipeline |= pdal.Filter.gridDecimation(
+        resolution=0.5, value="Classification=102", output_type="max", where="Classification==2"
+    )
 
     # selection de points DSM (max) sur une grille régulière
-    pipeline |= pdal.Filter.gridDecimation(resolution=0.5, value="Classification=200", output_type="max", where=macro.build_condition("Classification", [2,3,4,5,6,9,17,64,100]))
+    pipeline |= pdal.Filter.gridDecimation(
+        resolution=0.5,
+        value="Classification=200",
+        output_type="max",
+        where=macro.build_condition("Classification", [2, 3, 4, 5, 6, 9, 17, 64, 100]),
+    )
 
     # assigne des points sol sélectionnés (102) en 100 : les points proches de la végaétation, des ponts, de l'eau et 64
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==102",
-                                       condition_ref=macro.build_condition("Classification", [4,5,6,9,17,64,100]), condition_out="Classification=100")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==102",
+        condition_ref=macro.build_condition("Classification", [4, 5, 6, 9, 17, 64, 100]),
+        condition_out="Classification=100",
+    )
 
     # remise à zero du code 102
     pipeline |= pdal.Filter.assign(value="Classification=2", where="Classification==102")
 
-    ## 3 - gestion des ponts
-
-
+    # 3 - gestion des ponts
 
     # bouche trou : on élimine les points sol (2) au milieu du pont en les mettant à 102
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==2", condition_ref="Classification==17", condition_out="Classification=102")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==102",
-                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=2")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==2",
+        condition_ref="Classification==17",
+        condition_out="Classification=102",
+    )
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==102",
+        condition_ref=macro.build_condition("Classification", [2, 3, 4, 5]),
+        condition_out="Classification=2",
+    )
 
     # bouche trou : on élimine les points basse végétation (3) au milieu du pont en les mettant à 103
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==3", condition_ref="Classification==17", condition_out="Classification=103")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==103",
-                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=3")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==3",
+        condition_ref="Classification==17",
+        condition_out="Classification=103",
+    )
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==103",
+        condition_ref=macro.build_condition("Classification", [2, 3, 4, 5]),
+        condition_out="Classification=3",
+    )
 
     # bouche trou : on élimine les points moyenne végétation (4) au milieu du pont en les mettant à 104
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==4", condition_ref="Classification==17", condition_out="Classification=104")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==104",
-                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=4")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==4",
+        condition_ref="Classification==17",
+        condition_out="Classification=104",
+    )
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==104",
+        condition_ref=macro.build_condition("Classification", [2, 3, 4, 5]),
+        condition_out="Classification=4",
+    )
 
     # bouche trou : on élimine les points haute végétation (5) au milieu du pont en les mettant à 105
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==5", condition_ref="Classification==17", condition_out="Classification=105")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==105",
-                                       condition_ref=macro.build_condition("Classification", [2,3,4,5]), condition_out="Classification=5")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==5",
+        condition_ref="Classification==17",
+        condition_out="Classification=105",
+    )
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==105",
+        condition_ref=macro.build_condition("Classification", [2, 3, 4, 5]),
+        condition_out="Classification=5",
+    )
 
     # bouche trou : on élimine les points eau (9) au milieu du pont en les mettant à 109
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==9", condition_ref="Classification==17", condition_out="Classification=109")
-    pipeline = macro.add_radius_assign(pipeline, 1.5, False, condition_src="Classification==109",
-                                       condition_ref="Classification==9", condition_out="Classification=9")
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==9",
+        condition_ref="Classification==17",
+        condition_out="Classification=109",
+    )
+    pipeline = macro.add_radius_assign(
+        pipeline,
+        1.5,
+        False,
+        condition_src="Classification==109",
+        condition_ref="Classification==9",
+        condition_out="Classification=9",
+    )
 
     # step 15 et supression des points ??
 
     # 4 - export du nuage
-    pipeline |= pdal.Writer.las(extra_dims="all",forward="all",filename=args.output_las)
+    pipeline |= pdal.Writer.las(extra_dims="all", forward="all", filename=args.output_las)
 
     # export des DSM/DTM
-    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dtm, where=macro.build_condition("Classification", [2,66]))
-    pipeline |= pdal.Writer.gdal(gdaldriver="GTiff", output_type="max", resolution=2.0, filename=args.output_dsm, where=macro.build_condition("Classification", [2,3,4,5,17,64]))
+    pipeline |= pdal.Writer.gdal(
+        gdaldriver="GTiff",
+        output_type="max",
+        resolution=2.0,
+        filename=args.output_dtm,
+        where=macro.build_condition("Classification", [2, 66]),
+    )
+    pipeline |= pdal.Writer.gdal(
+        gdaldriver="GTiff",
+        output_type="max",
+        resolution=2.0,
+        filename=args.output_dsm,
+        where=macro.build_condition("Classification", [2, 3, 4, 5, 17, 64]),
+    )
 
     pipeline.execute()
-