New Format Features: LAS Versions 1.3 and 1.4ΒΆ

There is not a great deal of LAS version 1.3 and 1.4 test data around, so laspy’s implementation of these formats is neccesarily preliminary. Nevertheless, based on the test data we’ve been able to find, all the basic features should work.

The dimensions which are newly available from point formats 4-10 are accessed in the same way as those from formats 0-3. The tutorial background section has an extensive list of what laspy calls each of these dimensions, but here we’ll provide some quick examples. More examples can be found by looking at the ./test/ file included in the source.

Additionally, LAS version 1.4 provides the ability to specify an “extra bytes” variable length record (or EVLR) which can dynamically add additional dimensins. Laspy now parses such records, and provides the specified dimensions accordingly.

The names of these new dimensions are constructed by using the name field specified in the VLR record, and replacing null bytes with python empty strings, spaces with underscores, and upper case letters with lower case letters. For example, the field

“Pulse Width\X00\X00\X00\X00\X00\X00\X00\X00\X00”

would become simply: “pulse_width”

In order to maintain backwards compatability, laspy also provides access to these dimensions via laspy.file.extra_bytes, which provides raw access to the extra bytes in point records (present when data_record_length is greater than the default for a given point format).

Opening Files

Opening 1.3 and 1.4 files works exactly the same:

import numpy as np
import laspy

inFile_v13 = laspy.file.File("./laspytest/data/simple1_3.las", mode = "r")
inFile_v14 = laspy.file.File("./laspytest/data/simple1_4.las", mode = "r")

Reading Data - New Dimensions

#By checking the data_format_ids, we can see what new
# dimensions are present. Our 1.3 file has data format 4,
# and our 1.4 file has data format 7.

#Grab some dimensions as usual:
v_13 points = inFile_v13.points
x_t = inFile_v13.x_t

v_14_points = inFile_v14.points
v_14_classification = inFile_v14.classification

# Note that classification means different things depending on
# the file version. Before v1.4, classification was part of the
# classification byte. This is called classification flags in 1.4,
# and classification refers to a new whole-byte field. For a
# discussion, see tutorial:background.

Writing Data + EVLRS

EVLRS work very much the same way as traditional VLRs, though they are stored in a different part of the file.

import laspy
outFile_14 = laspy.file.File("./laspytest/data/output_14.las", mode = "w",
                header = inFile_v14.header)
new_evlr = laspy.header.EVLR(user_id = 10, record_id = 2,
                VLR_body = "Lots of data can go here.")
#outFile_14 has the same, single EVLR as inFile
old_evlrs = outFile_14.header.evlrs
outFile_14.header.evlrs = old_evlrs

Extra Bytes

The extra bytes in a point record can now be described by a particular type of VLR. From the LAS 1.4 specification, a VLR which describes new dimensions should have the following header information:

User ID: LASF_Spec

Record ID: 4

Record Length after Header: n x 192 bytes

where n is the number of new dimensions that the VLR will define. The actual dimension specification goes in the body of the VLR, and has the following structure:


Laspy coerces the no_data, max and min fields to have double precision format. If this is a problem for your application, let us know.

Extra Bytes Struct

Name Format[number] (Total Bytes)
reserved unsigned char[2] (2)
data_type unsigned char[1] (1)
options unsigned char[1] (1)
name char[32] (32)
unused char[4] (4)
no_data double[3] (24)
min double[3] (24)
max double[3] (24)
scale scale[3] (24)
offset offset[3] (24)
description char[32] (24)

Data Type Description

Value Meaning Size
0 Raw Extra Bytes Value of “options”
1 unsigned char 1 byte
2 Char 1 byte
3 unsigned short 2 bytes
4 Short 2 bytes
5 unsigned long 4 bytes
6 Long 4 bytes
7 unsigned long long 8 bytes
8 long long 8 bytes
9 Float 4 bytes
10 Double 8 bytes
11 unsigned char[2] 2 byte
12 char[2] 2 byte
13 unsigned short[2] 4 bytes
14 short[2] 4 bytes
15 unsigned long[2] 8 bytes
16 long[2] 8 bytes
17 unsigned long long[2] 16 bytes
18 long long[2] 16 bytes
19 float[2] 8 bytes
20 double[2] 16 bytes
21 unsigned char[3] 3 byte
22 char[3] 3 byte
23 unsigned short[3] 6 bytes
24 short[3] 6 bytes
25 unsigned long[3] 12 bytes
26 long[3] 12 bytes
27 unsigned long long[3] 24 bytes
28 long long[3] 24 bytes
29 float[3] 12 bytes
30 double[3] 24 bytes

Adding Extra Dimensions - The laspy way.

One can easily create new dimensions using the above data type table and a laspy file object. In fact, it is not even neccesary to use a 1.4 file in this process, however other software will likely not know to use the new 1.4 features in a previous file version. Most readers should, however, be able to treat the extra dimensions as extra bytes. Here’s the easy way to specify new dimensions:

import laspy

# Set up our input and output files.
inFile = laspy.file.File("./laspytest/data/simple.las", mode = "r")
outFile = laspy.file.File("./laspytest/data/output.las", mode = "w",
            header = inFile.header)
# Define our new dimension. Note, this must be done before giving
# the output file point records.
outFile.define_new_dimension(name = "my_special_dimension",
                        data_type = 5, description = "Test Dimension")

# Lets go ahead and copy all the existing data from inFile:
for dimension in inFile.point_format:
    dat = inFile.reader.get_dimension(
    outFile.writer.set_dimension(, dat)

# Now lets put data in our new dimension
# (though we could have done this first)

# Note that the data type 5 refers to a long integer
outFile.my_special_dimension = range(len(inFile))

Adding Extra Dimensions - The long way.

If you want to see what’s happening when you create new dimensions at a level much closer to the raw specification, laspy lets you create the requisite components manually.

import laspy
import copy

inFile = laspy.file.File("./laspytest/data/simple.las", mode = "r")

# We need to build the body of our dimension VLRs, and to do this we
# will use a class called ExtraBytesStruct. All we really need to tell
# it at this point is the name of our dimension and the data type.

extra_dimension_spec_1 = laspy.header.ExtraBytesStruct(name = "My Super Special Dimension",
                                                       data_type = 5)
extra_dimension_spec_2 = laspy.header.ExtraBytesStruct(name = "Another Special Dimension",
                                                       data_type = 5)
vlr_body = (extra_dimension_spec_1.to_byte_string() +

# Now we can create the VLR. Note the user_id and record_id choices.
# These values are how the LAS specification determines that this is an
# extra bytes record. The description is just good practice.
extra_dim_vlr = laspy.header.VLR(user_id = "LASF_Spec",
                                 record_id = 4,
                                 description = "Testing Extra Bytes.",
                                 VLR_body = vlr_body)

# Now let's put together the header for our new file. We need to increase
# data_record_length to fit our new dimensions. See the data_type table
# for details. We also need to change the file version
new_header = copy.copy(inFile.header)
new_header.data_record_length += 8
new_header.format = 1.4

# Now we can create the file and give it our VLR.
new_file = laspy.file.File("./laspytest/data/new_14_file.las", mode = "w",
                header = new_header, vlrs = [extra_dim_vlr])

# Let's copy the existing data:
for dimension in inFile.point_format:
    dim = inFile._reader.get_dimension(
    new_file._writer.set_dimension(, dim)

# We should be able to acces our new dimensions based on the
# Naming convention described above. Let's put some dummy data in them.
new_file.my_super_special_dimension = [0]*len(new_file)
new_file.another_special_dimension = [10]*len(new_file)

# If we would rather grab a raw byte representation of all the extra
# dimensions, we can use:

raw_bytes = new_file.extra_bytes

# This might be useful if we wanted to later take this data and put it
# back into an older file version which doesn't support extra dimensions.

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