[fix] Removal of BaseHatcher._getChildPaths

Depreciated function with the transition to pyclipr

pyslm/hatching/hatching.py

@@ -199,29 +199,6 @@ def error(cls) -> float:
         """
         return 1. / cls.PYCLIPPER_SCALEFACTOR
 
-    @staticmethod
-    def _getChildPaths(poly):
-
-        offsetPolys = []
-
-        # Create single closed polygons for each polygon
-        paths = [path.Contour for path in poly.Childs]  # Polygon holes
-        paths.append(poly.Contour)  # Path holes
-
-        # Append the first point to the end of each path to close loop
-        for path in paths:
-            path.append(path[0])
-
-        paths = BaseHatcher.scaleFromClipper(paths)
-
-        offsetPolys.append(paths)
-
-        for polyChild in poly.Childs:
-            if len(polyChild.Childs) > 0:
-                for polyChild2 in polyChild.Childs:
-                    offsetPolys += BaseHatcher._getChildPaths(polyChild2)
-
-        return offsetPolys
 
     @staticmethod
     def offsetPolygons(polygons, offset: float):
@@ -366,7 +343,6 @@ def clipContourLines(paths, contourPaths: List[np.ndarray]):
 
         return outPaths
 
-
     def generateHatching(self, paths, hatchSpacing: float, hatchAngle: Optional[float] = 90.0) -> np.ndarray:
         """
         Generates un-clipped hatches which is guaranteed to cover the entire polygon region base on the maximum extent
@@ -1005,11 +981,11 @@ class BasicIslandHatcher(Hatcher):
     (:attr:`.islandWidth`)  which covers a region.  This a common scan strategy adopted across SLM systems.
     This has the effect of limiting the max length of the scan whilst by orientating the scan vectors orthogonal
     to each other mitigating any preferential distortion or curling  in a single direction and any
-    effects to micro-structure.
+    effects to microstructure.
 
     :note:
 
-        This method is not optimal and is provided as a reference for the user to improve their own understand and
+        This method is not optimal and is provided as a reference for the user to improve their own understanding and
         develop their own island scan strategies. For optimal performance, the user should refer instead to
         :class:`IslandHatcher`
 

pyslm/hatching/islandHatcher.py

@@ -146,10 +146,10 @@ def hatch(self) -> np.ndarray:
 
 class IslandHatcher(Hatcher):
     """
-    IslandHatcher extends the standard :class:`Hatcher` but generates a set of islands of fixed size (:attr:`~.islandWidth`)
-    which covers a region.  This a common scan strategy adopted across SLM systems. This has the effect of limiting the
-    maximum length of the scan whilst by orientating the scan vectors orthogonal to each other mitigating any
-    preferential distortion or curling  in a single direction and any effects to micro-structure.
+    IslandHatcher extends the standard :class:`Hatcher` but generates a set of islands of fixed size
+    (:attr:`islandWidth`) which covers a region.  This a common scan strategy adopted across SLM systems.
+    This has the effect of limiting the maximum length of the scan vectors whilst by orientating the scan vectors
+    orthogonal to each other mitigating any     preferential distortion or curling due to residual in a single direction and any effects to the microstructure.
     """
 
     def __init__(self):