lazpy

LAS and LAZ point clouds, read and written: a port of LASzip to C, with a Python front end.

Features

Every LAZ point format (0–10) and every LASzip item version, reading and writing
LAS 1.0–1.4, variable length records, extra bytes, LAS 1.4 compatibility mode
numpy array reading and writing (pip install lazpy[numpy])
Rectangle and circle queries, accelerated by LASzip .lax spatial indexes, which lazpy also builds
Coordinate reference systems as pyproj objects (pip install lazpy[crs])
Malformed input raises lazpy.LazError; reader.warnings collects non-fatal defects
A lazpy CLI that summarises a file

Installing

pip install lazpy

Reading

from lazpy import Reader

with Reader("cloud.laz") as reader:
    print(reader.num_points, reader.point_format)

    for point in reader:
        print(point.X, point.Y, point.Z, point.classification)

    reader.seek(1_000_000)          # random access
    point = reader.read()
    x, y, z = reader.scale(point)   # georeferenced floats

As numpy arrays:

with Reader("cloud.laz") as reader:
    xyz = reader.xyz()                        # (N, 3) float64, scaled
    a = reader.arrays(start=0)                # {name: array}, every field
    ground = a["Z"][a["classification"] == 2]

xyz() and arrays() take start= and count= for reading in blocks.

Spatial queries

with Reader("cloud.laz") as reader:
    for point in reader.points_within(rect=(x0, y0, x1, y1)):
        ...
    xyz = reader.xyz_within(circle=(x, y, 30.0))

With a LASzip spatial index — a .lax sidecar, or embedded by lasindex -append — a query decodes only the chunks that can hold matching points; without one it is a filtered full scan. To build an index:

reader.write_spatial_index(cell_size=10.0)    # writes cloud.lax

Writing

from lazpy import Reader, Writer

# thin a survey down to its ground returns, still compressed
with Reader("cloud.laz") as reader, \
     Writer("ground.laz", point_format=reader.point_format,
            scales=reader.scales, offsets=reader.offsets) as writer:
    for point in reader:
        if point.classification == 2:
            writer.write(point)

write_arrays() takes the dict arrays() returns; together they convert a file in blocks:

with Reader("in.laz") as reader, Writer("out.laz", reader.point_format,
                                        scales=reader.scales,
                                        offsets=reader.offsets) as writer:
    while reader.index < reader.num_points:
        writer.write_arrays(reader.arrays(count=1_000_000))

The writer handles the header, the LASzip VLR and the chunk table. Keyword arguments cover the rest: vlrs= and evlrs= for records, crs= for a coordinate reference system, chunk_size=, version_minor=, laz_version=, and compatibility=True for LAS 1.4 compatibility mode. A .las file name writes plain LAS.

writer.unscale() converts georeferenced floats to the integers points store, and auto_offsets(mins, maxs, scales) picks offsets a survey fits inside.

Coordinate reference systems

reader.crs is the CRS the file declares, as a pyproj CRS — None if it declares nothing usable — and Writer takes the same object back through crs=. lazpy reports the declaration as it stands; it does not validate or correct it.

What is supported

Point data format	Items	LAZ versions
0–5	POINT10, GPSTIME11, RGB12, WAVEPACKET13, BYTE	uncompressed, v1, v2
6–10	POINT14, RGB14, RGBNIR14, WAVEPACKET14, BYTE14	uncompressed, v3, v4

Also: pointwise- and layered-chunked containers, fixed, adaptive and missing chunk tables, selective decompression, spatial indexes, LAS 1.4 compatibility mode in both directions, and both host byte orders.

Development

pip install -e . pytest
pytest
flake8

The tests check lazpy's output byte-for-byte against reference data produced by laszip itself; tools/ holds the harness that generated it.

License

Apache License 2.0 — see LICENSE. Everything in src/ is a port of LASzip, itself Apache 2.0 and copyright rapidlasso GmbH; NOTICE carries the attribution.

References

LAS 1.2 specification
LAS 1.4 specification
LASzip — the reference implementation lazpy is ported from, by Martin Isenburg / rapidlasso.

Development Status
- 4 - Beta
Intended Audience
- Science/Research
Programming Language
- C
- Python :: 3
Topic
- Scientific/Engineering :: GIS

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BLAKE2b-256	`2d927733c4a5a52ebb4f9bec988a9df26a1be6958ed9fe44505a7553e71c3e57`

Algorithm	Hash digest
SHA256	`59f3817d725f8e30578278521a230ec4929e083ab6f3828f62fbae8cd20c10e0`
MD5	`3536dcaec7d953a26ec464707c2f466e`
BLAKE2b-256	`b485ec90cc214e968994847459c1f37e7d7e93147d18aeb9eff8bc5cff2305db`

Algorithm	Hash digest
SHA256	`7960b67d70490aa94b163bf935de10c9ff41f009a391b4b0b38bc0e857d0aa58`
MD5	`60f164b16430a20b37907fc38c6f40ff`
BLAKE2b-256	`f288c2e53cbb197115084d28fadf3c2334c8cf92c773c021ea8149f9595a55df`

lazpy 0.9

lazpy

Features

Installing

Reading

Spatial queries

Writing

Coordinate reference systems

What is supported

Development

License

References

Project links

Key dates

1 maintainer

Credits

GitHub Statistics

License expression

Requires

Provides Extra

Tags

Classifiers

Download files

Source Distribution

Built Distributions

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Algorithm	Hash digest
SHA256	`a027daac9064d6eef1c378308d17f816622720376214f3254904cbbf14635c7e`
MD5	`163d645dadb2412d42180d8728858495`
BLAKE2b-256	`ac3386160e065cf658b9d950a78e34a896fb391b47c14e51ed0b7ae5bd93b7e5`

Algorithm	Hash digest
SHA256	`3a3f6426a95769e34163e6a95824d935bfd59512123252cb2cc6733a6c74ff4c`
MD5	`2148f00c49ac0235b6a9fdf39d1c0c2f`
BLAKE2b-256	`924dbde50a3594dfe8758855557a01c5210dd8d360dce7b77962d8ce124a3d2d`

Algorithm	Hash digest
SHA256	`da3eb4916e0384a068128ef77504b68fecd589e510573d900731bf89f27be6bf`
MD5	`d29ad141bb06d11b9a7d91b6eb22ceef`
BLAKE2b-256	`8180c89216eef6ed26a75035a6b2bb6684cd55f27cac43dc72721bceea4cc2fd`

Algorithm	Hash digest
SHA256	`7e31293e84fbcd9c5f65b1f18809a75c1c1ac496ba36d577ac4781e2d53de5ab`
MD5	`b17319ccdad36e9e2f1a04065a54dc90`
BLAKE2b-256	`70c7ad4d7fecfc75e191d9e682deb28ff9853ebf091b13f1ed3a15747fd3cdbd`

Algorithm	Hash digest
SHA256	`ba72b40b96e1d18b25a6337579e735e99ccc0cfc9a2946620d52879339ced6eb`
MD5	`c30643bcde84bba8e6db817363faf37c`
BLAKE2b-256	`38b613a6738335a47dc5d72e59530f87adc30148e76c74403cd5f924f30ef798`

Algorithm	Hash digest
SHA256	`ae70620493ca53d2464057e0ec838109f1c19cc5d045d6341060a7c2f5031e86`
MD5	`6ae23ffc5c7f7fc946df1bd67f257cdb`
BLAKE2b-256	`92e29a0d677ecd79a35fde17f01744b8671001f5985baa052a58e9677234b5a5`

Algorithm	Hash digest
SHA256	`27ff7c94b82cd90c68c91838672383664aa6dcbb64696fa7d93db169ca95a676`
MD5	`07fdf34d85faf04a9ad7453eac1bccc7`
BLAKE2b-256	`2ebcb7afd028fc716d639b529eb7fe1e299511950f006e702ad10c1adb031282`

Algorithm	Hash digest
SHA256	`a606ecea5b5c35841701d89bec4457ba03283d3ffbac31489dc6d5c316640c50`
MD5	`d6d9df5ac97a58a0003f34d15a5e9aaf`
BLAKE2b-256	`5ef3c933cca9bb9ad46000d2b40cc54f0c402501a282e486a752046a20ccf983`

Algorithm	Hash digest
SHA256	`ad1c7c7029fee48165972034d33e917e5207bf40890b37b09dc611cae2509295`
MD5	`35ef345416d5024734cf36217b5afd59`
BLAKE2b-256	`c7e73c58ee5196fb6de30904dd2bf836bf39abe477386f2e5171751c00b73643`

Algorithm	Hash digest
SHA256	`611abfbb1dcf5ca14f1cbac36d596a80e418a59b986eaca297a8fd0632dd6354`
MD5	`785f0c436bad0f489c127ebb86b600d3`
BLAKE2b-256	`314e2f904d0eb2338bc6b81923fb926f8b6ae700ed72765bca220551d64fbc22`