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View Code? Open in Web Editor NEW⚠️ pylas was merged into laspy 2.0 https://github.com/laspy/laspy⚠️
License: BSD 3-Clause "New" or "Revised" License
⚠️ pylas was merged into laspy 2.0 https://github.com/laspy/laspy⚠️
License: BSD 3-Clause "New" or "Revised" License
Hi,
I'm trying to read a received LAS file with pylas and I'm getting this:
>>> import pylas
>>> f1 = pylas.open('/usr/src/data/pylas/lidar/pointcloud.las')
>>> f1.read()
Traceback (most recent call last):
File "/opt/anaconda3/lib/python3.7/site-packages/pylas-0.3.4-py3.7.egg/pylas/point/record.py", line 260, in from_stream
data = np.frombuffer(point_data_buffer, dtype=points_dtype, count=count)
ValueError: buffer is smaller than requested size
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/anaconda3/lib/python3.7/site-packages/pylas-0.3.4-py3.7.egg/pylas/lasreader.py", line 62, in read
points = self._read_points(vlrs)
File "/opt/anaconda3/lib/python3.7/site-packages/pylas-0.3.4-py3.7.egg/pylas/lasreader.py", line 115, in _read_points
self.stream, point_format, self.header.point_count
File "/opt/anaconda3/lib/python3.7/site-packages/pylas-0.3.4-py3.7.egg/pylas/point/record.py", line 269, in from_stream
points_dtype,
File "/opt/anaconda3/lib/python3.7/site-packages/pylas-0.3.4-py3.7.egg/pylas/point/record.py", line 32, in raise_not_enough_bytes_error
point_data_buffer_len / points_dtype.itemsize,
pylas.errors.PylasError: The file does not contain enough bytes to store the expected number of points
expected 230066000 bytes, read 195556100 bytes (34509900 bytes missing == 862747.5 points) and it cannot be corrected
195556100 (bytes) / 40 (point_size) = 4888902.5 (points)
I can't attach the LAS file that is bigger than 10MB but I could send a link to download it if needed.
I hope you can help.
pm
Hi! I am using pylas
for reading and writing LAS and LAZ files, it is really a great tool! Just wanted to mention that while files with both upper- and lower-case extensions (e.g. 'file.laz' and 'file.LAZ') are properly recognised as compressed files in reading, this is not the case in writing: writing to 'file.laz' would generate a compressed file, while 'file.LAZ' would not be compressed. Maybe having filename.split(".").lower()[-1] == "laz"
here?
Line 327 in 1255266
compress_points_buf
is a bytes object when using lazrs causing errors with the compress_points_buf.tobytes()
call.
Line 283 in 7b35d43
Using lazrs 0.2.5, pylas 0.4.3, Python 3.8.5
Other notes in case relevant:
.tobytes()
or replace with points_bytes = bytearray(compressed_points_buf if isinstance(compressed_points_buf, bytes) else compressed_points_buf.tobytes())
.Thanks for this module! I love the laz-perf integration and streaming support! Would it be possible to add return_number
to the point attributes?
For example lasinfo
shows:
lasinfo -i pylastests/simple.laz
...
number of first returns: 925
number of intermediate returns: 28
number of last returns: 901
number of single returns: 789
overview over number of returns of given pulse: 789 195 71 10 0 0 0
...
However, with pylas:
python -c 'import pylas; print(pylas.open("pylastests/simple.laz").points.dtype.names)'
You only get:
('X', 'Y', 'Z', 'intensity', 'bit_fields', 'raw_classification', 'scan_angle_rank', 'user_data', 'point_source_id', 'gps_time', 'red', 'green', 'blue')
I would like to suggest a new feature to be able to convert a lidar .las / .laz to a .tif file.
Hey,
I am struggling to remove the dimension once it is already on the point_format.dimensions list and in the points array.
Is there any method that I miss ? or any trick or advice that can help me?
Thanks
Hi,
First of all, I want to compliment you on this python implementation for reading LiDAR data. I think the on the fly decompression in Python is great.
I was wondering if there was a possibility for adding a seek
function to the LasReader
. This would greatly improve the usability for indexed reading, especially for large compressed LAZ datasets containing a lasindex
.
I saw in the rust package that the LasZipDecompressor actually supports seeking. https://github.com/tmontaigu/laz-rs-python/blob/master/src/lib.rs#L187. I think the same holds for your laszip python bindings.
I was actually kind of surprised that this option was missing and wondering before doing the implementation whether there is a limitation I'm overlooking?
Thijs van Winden
PS: I have a use case where I have to query nearby LiDAR points from a huge dataset, so streaming access would be really useful there.
Using a script like this:
import sys
import io
import pylas
las = pylas.read(sys.argv[1])
las.write("tmp.laz")
with io.BytesIO() as out:
las.write(out, do_compress=True)
out.seek(0)
pylas.read(out)
if sys.argv[1] is a file with extra bytes, the tmp.laz will be invalid
(lasinfo will output errors like
[...]
ERROR: 'end-of-file' after 454 of 1065 points for '.\tmp.laz'
corrupt chunk table
[...]
And pylas will fail to read the file with an error like
pylas.errors.PylasError: The file does not contain enough bytes to store the expected number of points
expected 64965 bytes, read 27703 bytes (37262 bytes missing == 610.8524590163935 points) and it cannot be corrected
27703 (bytes) / 61 (point_size) = 454.1475409836066 (points)
however if the file at sys.argv[1] does not have extra bytes everything is fine.
Right now the pylas.open
function only alows to open in read mode.
(Writing is possible but it is a method a pylas.LasBase class)
The PR #16 plan to add a Write mode to create a new file and write to it.
Can a "append" mode be added ?:
Can a read + write be added ?:
In both cases the hardest will be the compressed case (LAZ file) as well as files with EVLRs).
(Append mode seems more feasible tho)
I'm developing a tool which requires laz files and am looking to use pylas to perform conversions from las on-the-fly. The tool uses a GUI and, although pylas is quick, there's no getting around the volume of data; las files are large and can still take several (10+) seconds to convert. I would like to provide users with a process dialog during the conversion.
To convert, I'm running:
las = pylas.read(las_input)
las.write(laz_output)
It doesn't look like write
provides a way to measure progress or a return value indicating completion. Is this something you would be interested in?
It looks like LasData (ultimately) uses LasData._write_to()
for the write
call. This creates a writer which calls write_points
. (I think I linked the correct invocation). This checks a self.done
. Is that something which could be returned up the call chain to indicate success?
As for getting progress updates, I'd have to think about how that could be done (another method to avoid a performance hit?), if you're even interested in that. For now, I'm just going to check for the existence of the output file; if it exists, the process completed, right? :).
I was trying to read LAZ files from S3, using s3fs and pylas' ability to read from streams:
import pylas
import s3fs
fs = s3fs.S3FileSystem()
las = pylas.open(fs.open('s3://bucketname/example.laz', 'rb'))
However, I get the following error:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/home/ubuntu/miniconda3/envs/pylas-env/lib/python3.6/site-packages/pylas/lib.py", line 34, in open_las
return read_las_stream(source)
File "/home/ubuntu/miniconda3/envs/pylas-env/lib/python3.6/site-packages/pylas/lib.py", line 90, in read_las_stream
vlrs = vlr.VLRList.read_from(data_stream, num_to_read=header.number_of_vlr)
File "/home/ubuntu/miniconda3/envs/pylas-env/lib/python3.6/site-packages/pylas/vlr.py", line 571, in read_from
raw = RawVLR.read_from(data_stream)
File "/home/ubuntu/miniconda3/envs/pylas-env/lib/python3.6/site-packages/pylas/vlr.py", line 61, in read_from
data_stream.readinto(header)
AttributeError: 'S3File' object has no attribute 'readinto'
Looks like s3fs doesn't have an implementation of readinto
. So, is there a recommended way to read from S3? Or, should I look into getting an implementation of readinto for S3File?
Hi,
I'm trying to write the file with the same name after I apply the update_header(), but I'm getting "Permission Denied". It happens even if I close the file.
I tried to check the documentation but I can't find a way to save the file after the update_header using the same name. Am I forced to write to another file name?
I hope you can help,
pm
Handle 'Scaled Extra Byte'
Downloading any .laz
file from here: https://remotesensingdata.gov.scot/data#/map and attempting to extract it using e.g.
pylas.read("NT0763_2PPM_LAS_PHASE1.laz")
Results in:
60 vlr_data = np.frombuffer(laszip_vlr.record_data, dtype=np.uint8)
62 point_decompressed = np.zeros(point_count * point_size, np.uint8)
---> 64 lazrs.decompress_points(point_compressed, vlr_data, point_decompressed, parallel)
65 except lazrs.LazrsError as e:
66 raise LazError("lazrs error: {}".format(e)) from e
PanicException: assertion failed: mid <= self.len()
Any idea why this would be?
I'm on a Windows 10 machine. The file opens correctly in QGIS.
This might be a tough request, but it would be nice to be able to separate out the current open
function into more pythonic open
and read
functions. For example:
with pylas.open('simple.laz') as fh:
fh.read()
Having pylas.open
read into the file/handle/stream enough just to get the header, would also provide convenient/quick access to some info without reading the entire dataset.
I find that the tests (while they work fine) should be improved to be more readable / understandable
Hi,
First, thank you for this very helpful library.
Is there any way to easily write the SRS in WKT format when creating a las file with pylas.create() ?
I see there is a write_to() method from the pylas.vlrs.vlrlist module but I do not understand how it works. Maybe an example can help here.
Thanks.
import pylas
las = pylas.create()
las.write('empty.las') # Ok
las.write('empty.laz') # crash
Atm, sub fields are a bit weird to interact with.
Example:
import pylas
las = pylas.read(som_file)
las.classification[:] = 0
assert np.all(las.classification == 0) # This will fail (unless the classification was already 0s)
The current way to work arround this is to do
import pylas
las = pylas.read(som_file)
classification = las.classification
classification[:] = 0
las.classification = classification
assert np.all(las.classification == 0) # This will work
All 'sub fields' have this behaviour, (classification, key_point, number_of_returns, return_number, etc), this is because when accessing these fields we return a new array with the valuesz.
The way to fix/improve this would be to return an object that act as a view into the array that holds the values
and that view-object would take care of returning and setting the proper values using a bitmask.
I am comparing pylas[lazr] to laszip64 at converting las to laz and seeing a 30% speed bump with lazr 🎉. If I understand correctly, it should be as simple as:
las = pylas.read(las_input)
las.write(laz_output)
However, I get the following warning:
WARNING:pylas.headers.rawheader:Received return numbers up to 6, truncating to 5 for header.
I'm not sure what this means. I have tried grepping through all the sources and can't find the source.
Any insight? Is my data being truncated?
In pylas==0.4.3
for example, it was possible to concatenate fields and to apply several numpy operations to the fields of the point clouds. Unfortunately, some operations are not possible anymore in pylas==0.5.0a1
, probably because of the new SubFieldView
class. Here are some examples of operations that crash with pylas==0.5.0a1
but worked perfectly with pylas==0.4.3
:
>>> import pylas
>>> import numpy as np
>>> cloud = pylas.read("pylastests/simple.las")
>>> np.concatenate([cloud.return_number, cloud.return_number])
...
ValueError: zero-dimensional arrays cannot be concatenated
>>> cloud.return_number[0] + 1
...
TypeError: unsupported operand type(s) for +: 'SubFieldView' and 'int'
>>> field = np.zeros(len(cloud.points), dtype=np.uint8)
>>> field[:] = cloud.return_number[:]
...
TypeError: __array__() takes 1 positional argument but 2 were given
>>> ordered = np.argsort(cloud.gps_time)
>>> cloud.return_number[:] = cloud.return_number[ordered]
...
TypeError: unsupported operand type(s) for <<: 'SubFieldView' and 'int'
Current support for 1.4 files with EVLR is not very good (especially for LAZ files), some tests are currently skipped.
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