Geographic Information Systems Asked on December 8, 2021
I have LAS files with a useless extra scalar field (named "tree") that I would like to remove.
I tried the following code to create a new LAS file, copy each field of the orginal LAS file into the new LAS file, except the unwanted field.
import laspy
LASInput = laspy.file.File('foo.las', mode = 'r')
LASOutput = laspy.file.File('bar.las', mode = "w", header = LASInput.header)
#Lets copy all the existing data from input file:
for dimension in LASInput.point_format:
print(dimension.name)
if not(dimension.name == 'tree'):
LASOutput.writer.set_dimension(dimension.name, LASInput.reader.get_dimension(dimension.name))
LASOutput.close()
LASInput.close()
But the resulting LAS file still contains the field "tree". I guess the header also has to be modified so I tried this approach, creating a new header:
import laspy
LASInput = laspy.file.File('D:\foo.las', mode = 'r')
LASOutput = laspy.file.File('D:\bar.las', mode = "w", header = laspy.header.Header(1.3))
#Lets create the extra fields
NamesOutput = [i.name for i in LASOutput.point_format]
for dimension in LASInput.point_format:
print(dimension.name)
if not(dimension.name == 'tree'):
if not(dimension.name in NamesOutput):
LASOutput.define_new_dimension(name = dimension.name, data_type = 5, description ='blabla')
#Lets copy all the existing data from the imput file
for dimension in LASInput.point_format:
print(dimension.name)
if not(dimension.name == 'tree'):
LASOutput.writer.set_dimension(dimension.name, LASInput.reader.get_dimension(dimension.name))
LASOutput.close()
LASInput.close()
print('ok')
This works, but I find it rather inelegant, and also I did not find a way to get the fromat of the fields in the input header, in my code I used data_type=5, which is likely to be incorrect. Is there not a way to duplicate the input header and then to discard the unwanted field from the header?
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