Extends LasIO with LASzip integration.
Uses the LASzip shared library to read compressed las files (*.laz) into the uncompressed format that LasIO reads natively.
julia> using LazIO
# Open file and iterate over points
julia> ds = LazIO.open("test/libLAS_1.2.laz")
LazIO Dataset of test/libLAS_1.2.laz with 497536 points of version 0.
# Each point is correctly scaled and has its return_number and classification widened
julia> p = ds[1]
LazIO.Point0(1.44013394e6, 375000.23, 846.66, 0x00fa, 0x00, 0x00, 0x00, false, 2, false, false, false, 0x00, 0x001d)
# This results in accessible attributes, such as edge_of_flightline and withheld
julia> fieldnames(typeof(p))
(:x, :y, :z, :intensity, :return_number, :number_of_returns, :scan_direction, :edge_of_flight_line, :classification, :synthetic, :key_point, :withheld, :user_data, :point_source_id)
# LazIO implements the GeoInterface
julia> using GeoInterface
julia> GeoInterface.coordinates(p)
3-element Vector{Float64}:
1.44013394e6
375000.23
846.66
julia> GeoInterface.extent(ds)
Extent(X = (1.44e6, 1.44499996e6), Y = (375000.03, 379999.99), Z = (832.1800000000001, 972.6700000000001))
# Or one can use the Tables interface
julia> using DataFrames
julia> DataFrame(ds)
497536×14 DataFrame
Row │ x y z intensity return_number number ⋯
│ Float64 Float64 Float64 UInt16 UInt8 UInt8 ⋯
────────┼───────────────────────────────────────────────────────────────────────
1 │ 1.44013e6 3.75e5 846.66 250 0 ⋯
2 │ 1.44012e6 3.75e5 846.55 245 0
3 │ 1.44011e6 3.75001e5 846.44 239 0
4 │ 1.4401e6 375001.0 846.32 251 0
5 │ 1.44009e6 3.75001e5 846.21 229 0 ⋯
6 │ 1.44009e6 3.75002e5 846.1 249 0
7 │ 1.44008e6 3.75002e5 846.0 189 0
8 │ 1.44007e6 3.75002e5 845.9 250 0
Plotting is done via either the Plots, or Makie ecosystem. The latter is recommended for large datasets.
julia> # using Plots
julia> using GLMakie
julia> plot(ds)