Basic Manipulation

Opening & Reading

Reading is done using pylas.read() function. This function will read everything in the file (Header, vlrs, point records, …) and return an object that you can use to access to the data.

import pylas

las = pylas.read('somefile.las')
print(np.unique(las.classification))

pylas can also pylas.open() files reading just the header and vlrs but not the points, this is useful if you need metada informations that are contained in the header.

import s3fs
import pylas

fs = s3fs.S3FileSystem()
with fs.open('my-bucket/some_file.las', 'rb') as f:
     if f.header.point_count < 100_000_000:
         las = pylas.read(f)

Sometimes files are big, too big to be read entirely and fit into your RAM. The object returned by the pylas.open() function, pylas.lasreader.LasReader can also be used to read points chunk by chunk, which will allow you to do some processing on large files (splitting, filtering, etc)

import pylas

with pylas.open("some_big_file.laz") as f:
    for points in f.chunk_iterator(1_000_000):
        do_something_with(points)

Converting

pylas also offers the ability to convert a file between the different version and point format available (as long as they are compatible).

To convert, use the pylas.convert()

Creating

Creating a new Las from scratch is simple. Use pylas.create().

Writing

To be able to write a las file you will need a pylas.lasdatas.base.LasBase (or one if its subclasses). You obtain this type of object by using one of the function above, use its method pylas.lasdatas.base.LasBase.write() to write to a file or a stream.

Similar to pylas.lasreader.LasReader there exists a way to write a file chunk by chunk.

import pylas

with pylas.open("some_big_file.laz") as f:
    with pylas.open("grounds.laz", mode="w", header=f.header) as writer:
        for points in f.chunk_iterator(1_234_567):
            writer.write_points(points[points.classification == 2]

Accessing the file header

You can access the header of a las file you read or opened by retrieving the ‘header’ attribute:

>>> import pylas
>>> las = pylas.read('pylastests/simple.las')
>>> las.header
<LasHeader(1.2)>
>>> las.header.point_count
1065
>>> with pylas.open('pylastests/simple.las') as f:
...     f.header.point_count
1065

you can see the accessible fields in pylas.headers.rawheader.RawHeader1_1 and its sub-classes.

Accessing Points Records

To access point records using the dimension name, you have 2 options:

  1. regular attribute access using the las.dimension_name syntax
  2. dict-like attribute access las[dimension_name].
>>> import numpy as np
>>> las = pylas.read('pylastests/simple.las')
>>> np.all(las.user_data == las['user_data'])
True

Point Format

The dimensions available in a file are dictated by the point format id. The tables in the introduction section contains the list of dimensions for each of the point format. To get the point format of a file you have to access it through the las object:

>>> point_format = las.point_format
>>> point_format
<PointFormat(3, 0 bytes of extra dims)>
>>> point_format.id
3

If you don’t want to remember the dimensions for each point format, you can access the list of available dimensions in the file you read just like that:

>>> list(point_format.dimension_names)
['X', 'Y', 'Z', 'intensity', 'return_number', 'number_of_returns', 'scan_direction_flag', 'edge_of_flight_line', 'classification', 'synthetic', 'key_point', 'withheld', 'scan_angle_rank', 'user_data', 'point_source_id', 'gps_time', 'red', 'green', 'blue']

This gives you all the dimension names, including extra dimensions if any. If you wish to get only the extra dimension names the point format can give them to you:

>>> list(point_format.standard_dimension_names)
['X', 'Y', 'Z', 'intensity', 'return_number', 'number_of_returns', 'scan_direction_flag', 'edge_of_flight_line', 'classification', 'synthetic', 'key_point', 'withheld', 'scan_angle_rank', 'user_data', 'point_source_id', 'gps_time', 'red', 'green', 'blue']
>>> list(point_format.extra_dimension_names)
[]
>>> las = pylas.read('pylastests/extrabytes.las')
>>> list(las.point_format.extra_dimension_names)
['Colors', 'Reserved', 'Flags', 'Intensity', 'Time']

You can also have more information:

>>> point_format[3].name
'intensity'
>>> point_format[3].num_bits
16
>>> point_format[3].kind
<DimensionKind.UnsignedInteger: 1>
>>> point_format[3].max
65535

Manipulating VLRs

To access the VLRs stored in a file, simply access the vlr member of the las object.

>>> las = pylas.read('pylastests/extrabytes.las')
>>> las.vlrs
[<ExtraBytesVlr(extra bytes structs: 5)>]
>>> with pylas.open('pylastests/extrabytes.las') as f:
...     f.vlrs
[<ExtraBytesVlr(extra bytes structs: 5)>]

To retrieve a particular vlr from the list there are 2 ways: pylas.vlrs.vlrlist.VLRList.get() and pylas.vlrs.vlrlist.VLRList.get_by_id()