Avoid numpy.delete() — use column indexing for better performance and readability

[SaFE-APIOpt]

Slicer/Stl2Slices.py

Line 319 in 842808f

normals2D=numpy.delete(normals,1,1)

In the line:
normals2D = numpy.delete(normals, 1, 1)
numpy.delete() creates a copy of the array and performs internal data shifting, which introduces unnecessary overhead. Since the goal here is simply to exclude the second column, a more efficient and readable alternative is to use column indexing directly:
normals2D = normals[:, [0, 2]]
This approach avoids extra memory allocation and improves clarity, especially in performance-critical operations.