startinpy

A library for modelling and processing 2.5D terrains using a (2D) Delaunay triangulation. The triangulation is computed in 2D, but the z-elevation of the vertices is kept.

The underlying code is written in Rust (so it’s rather fast) and robust arithmetic is used (so it shouldn’t crash).

startinpy uses the startin Rust library and adds several utilities and functions, for instance NumPy support for input/output, export to several formats, and easy-of-use.

startinpy allows you to:

1. insert points incrementally

2. delete vertices (useful for simplification, interpolation, and other operations)

3. interpolate with several methods: TIN, natural neighbours, IDW, Laplace, etc

4. use other useful terrain Python libraries that are also NumPy-based, eg laspy, rasterio, and meshio

5. output the TIN to several formats: OBJ, PLY, GeoJSON, and CityJSON

6. store extra attributes for the vertices (eg the ones from LAS/LAZ)

import laspy
import numpy as np
import startinpy

las = laspy.read("../data/small.laz")
pts = np.vstack((las.x, las.y, las.z)).transpose()

dt = startinpy.DT()
dt.insert(pts)

# -- remove vertex #4
try:
    dt.remove(4)
except Exception as e:
    print(e)

print("# vertices:", dt.number_of_vertices())
print("# triangles:", dt.number_of_triangles())

# -- print the vertices forming the convex hull, in CCW-order
print("CH: ", dt.convex_hull())

# -- fetch all the incident triangles (CCW-ordered) to the vertex #235
vi = 235
one_random_pt = dt.points[vi]
print("one random point:", one_random_pt)
print(dt.incident_triangles_to_vertex(vi))

# -- interpolate at a location with the linear in TIN method
zhat = dt.interpolate({"method": "TIN"}, [[85718.5, 447211.6]])
print("result: ", zhat[0])

Table of content

• Installation
  • pip
  • If you want to compile it yourself
  • Development (to debug the code)
• API
  • DT
    • DT.adjacent_triangles_to_triangle()
    • DT.adjacent_vertices_to_vertex()
    • DT.area2d_triangle()
    • DT.area3d_triangle()
    • DT.attributes
    • DT.closest_point()
    • DT.collect_garbage()
    • DT.convex_hull()
    • DT.duplicates_handling
    • DT.get_attributes_schema()
    • DT.get_bbox()
    • DT.get_point()
    • DT.get_vertex_attributes()
    • DT.has_garbage()
    • DT.incident_triangles_to_vertex()
    • DT.insert()
    • DT.insert_one_pt()
    • DT.interpolate()
    • DT.is_finite()
    • DT.is_inside_convex_hull()
    • DT.is_triangle()
    • DT.is_vertex_convex_hull()
    • DT.is_vertex_removed()
    • DT.jump_and_walk
    • DT.locate()
    • DT.normal_triangle()
    • DT.normal_vertex()
    • DT.number_of_triangles()
    • DT.number_of_vertices()
    • DT.points
    • DT.remove()
    • DT.set_attributes_schema()
    • DT.set_vertex_attributes()
    • DT.snap_tolerance
    • DT.triangles
    • DT.update_vertex_z_value()
    • DT.vertical_exaggeration()
    • DT.volume_triangle()
    • DT.write_cityjson()
    • DT.write_geojson()
    • DT.write_obj()
    • DT.write_ply()
• How startinpy works
  • Original code written in Rust
  • Insertion + deletion are possible
  • The data structure
  • Infinite vertex and triangles
  • Parameters to setup that will influence the DT
    • Snap tolerance
    • Point location: latest triangle or first “jump”?
    • How xy-duplicates are handled
  • Some examples of the data structure and infinity
• GitHub
• Examples
  • Reading a LAZ file
  • Exporting the DT to GeoJSON
  • Exporting the DT to several mesh formats with meshio
  • Reading a GeoTIFF file with rasterio
  • 3D visualisation with Polyscope
  • Plotting the DT with matplotlib
  • Gridding the dataset with spatial interpolation
  • Creating a DSM
• Extra attributes
  • Attaching extra attributes
  • Retrieving the extra attributes
  • One full Python example
• Comparison to alternatives
• Issues? Bugs? Questions?

Indices and tables

• Index