Basic Manipulation¶
Opening & Reading¶
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))
Opening¶
pylas can also pylas.open()
files reading just the header and vlrs but not the points, this is useful
if you are interested in metadata that are contained in the header and do not need to read the points.
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)
Chunked reading¶
Sometimes files are big, too big to be read entirely and fit into your RAM.
The object returned by the pylas.open()
function, LasReader
can also be used to read points chunk by chunk by using LasReader.chunk_iterator()
, 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)
Writing¶
To be able to write a las file you will need a LasData
.
You obtain this type of object by using one of the function described in the section above
use its method LasData.write()
to write to a file or a stream.
Chunked Writing¶
Similar to 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])
Creating¶
Creating a new Las from scratch is simple.
Use pylas.create()
.
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()
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, <PointFormat(3, 0 bytes of extra dims)>)>
>>> 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 LasHeader
.
Accessing Points Records¶
To access point records using the dimension name, you have 2 options:
- regular attribute access using the las.dimension_name syntax
- 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.header.vlrs
[<ExtraBytesVlr(extra bytes structs: 5)>]
To retrieve a particular vlr from the list there are 2 ways: VLRList.get()
and
VLRList.get_by_id()