Examples¶
Filtering¶
This example shows how you can extract points from a file and write them into a new one. We use the classification field to filter points, but this can work with the other fields.
import pylas
las = pylas.read('pylastests/simple.las')
new_file = pylas.create(point_format=las.header.point_format_id, file_version=las.header.version)
new_file.points = las.points[las.classification == 1]
new_file.write('extracted_points.las')
Creating from scratch¶
This example shows how you can create a new LAS file from scratch.
import pylas
import numpy as np
las = pylas.create()
array = np.linspace(0.0, 15.0, 10000)
las.x = array
las.y = array
las.z = array
las.write('diagonal.las')
Using chunked reading & writing¶
This example shows how to use the ‘chunked’ reading and writing feature to split potentially large LAS/LAZ file into multiple smaller file.
import argparse
import sys
from pathlib import Path
from typing import List
from typing import Optional
import numpy as np
import pylas
def recursive_split(x_min, y_min, x_max, y_max, max_x_size, max_y_size):
x_size = x_max - x_min
y_size = y_max - y_min
if x_size > max_x_size:
left = recursive_split(x_min, y_min, x_min + (x_size // 2), y_max, max_x_size, max_y_size)
right = recursive_split(x_min + (x_size // 2), y_min, x_max, y_max, max_x_size, max_y_size)
return left + right
elif y_size > max_y_size:
up = recursive_split(x_min, y_min, x_max, y_min + (y_size // 2), max_x_size, max_y_size)
down = recursive_split(x_min, y_min + (y_size // 2), x_max, y_max, max_x_size, max_y_size)
return up + down
else:
return [(x_min, y_min, x_max, y_max)]
def tuple_size(string):
try:
return tuple(map(float, string.split("x")))
except:
raise ValueError("Size must be in the form of numberxnumber eg: 50.0x65.14")
def main():
parser = argparse.ArgumentParser("LAS recursive splitter", description="Splits a las file bounds recursively")
parser.add_argument("input_file")
parser.add_argument("output_dir")
parser.add_argument("size", type=tuple_size, help="eg: 50x64.17")
parser.add_argument("--points-per-iter", default=10**6, type=int)
args = parser.parse_args()
with pylas.open(sys.argv[1]) as file:
sub_bounds = recursive_split(
file.header.x_min,
file.header.y_min,
file.header.x_max,
file.header.y_max,
args.size[0],
args.size[1]
)
writers: List[Optional[pylas.LasWriter]] = [None] * len(sub_bounds)
try:
count = 0
for points in file.chunk_iterator(args.points_per_iter):
print(f"{count / file.header.point_count * 100}%")
# For performance we need to use copy
# so that the underlying arrays are contiguous
x, y = points.x.copy(), points.y.copy()
point_piped = 0
for i, (x_min, y_min, x_max, y_max) in enumerate(sub_bounds):
mask = (x >= x_min) & (x <= x_max) & (y >= y_min) & (y <= y_max)
if np.any(mask):
if writers[i] is None:
output_path = Path(sys.argv[2]) / f"output_{i}.laz"
writers[i] = pylas.open(output_path,
mode='w',
header=file.header)
sub_points = points[mask]
writers[i].write_points(sub_points)
point_piped += np.sum(mask)
if point_piped == len(points):
break
count += len(points)
print(f"{count / file.header.point_count * 100}%")
finally:
for writer in writers:
if writer is not None:
writer.close()
if __name__ == '__main__':
main()