segfault when processing a catalog with "processed" tiles

[jmmonnet]

Hi, I want to run a normalization (and then add dtm computation) pipeline on selected tiles of a LAScatalog. When the pipeline is run on all tiles (no processed field), the pipeline runs smoothly, but when the processed fields indicates only a subset of tiles to process, the output files are created but then R crashes with a segfault error. I have lasR 0.4.2 installed today.

Here are some files for testing:
https://filesender.renater.fr/?s=download&token=6a1fdcd3-50a2-462a-861c-79a93f85afee

The code I ran:

cata <- lidR::catalog("./las")
library(lasR)
# read catalog
read = reader(cata)
# build del
tri = triangulate(filter = "-keep_class 2 9")
# normalize
trans = transform_with(tri)
# write
write2 = write_las("./norm/*.laz")
#
# run pipeline
ans1 = exec(read + tri + trans + write2)
outputfiles <- list.files("./norm/", full.names = TRUE)
print(outputfiles)
#
# remove previous output files
unlink(outputfiles)
#
# set files to process in catalog
cata$processed <- FALSE
cata$processed[2:3] <- TRUE
# read catalog
read = reader(cata)
# run pipeline
ans1 = exec(read + tri + trans + write2)

The error I get with R ran from a console:

 *** caught segfault ***
address (nil), cause 'memory not mapped'

Traceback:
 1: processor(pipeline, ncores = with$ncores, progress = with$progress,     ...)
 2: exec(read + tri + trans + write2)

[Jean-Romain]

Will check it tomorrow. Thank you for your simple and reproducible example as usual.

MRE:

library(lasR)

f = list.files("issue 22/test/las", pattern = ".las", full.names = T)[1:2]

read = reader_las(filter = "-keep_random_fraction 0.05")
tri = triangulate(filter = "-keep_class 2 9")
trans = transform_with(tri)
write2 = write_las()
ans1 = exec(read + tri + trans + write2,  on = f, noprocess = c(T, F), progress = T, noread = TRUE)
ans1

[Jean-Romain]

Fixed.

FYI reader(cata) is deprecated. It works with exec because I added a convenient workaround. The correct syntax is:

read = reader_las()
tri = triangulate(filter = "-keep_class 2 9")
trans = transform_with(tri)
write2 = write_las()
ans1 = exec(read + tri + trans + write2,  on = cata)

When reader_las() is called without argument, it can be omitted.

tri = triangulate(filter = "-keep_class 2 9")
trans = transform_with(tri)
write2 = write_las()
ans1 = exec(tri + trans + write2,  on = cata)

Also I'm now using r-universe. You can install pre-compiled versions of the package like on the CRAN

install.packages('lasR', repos = 'https://r-lidar.r-universe.dev')

[jmmonnet]

Thank you for the tips and for the fix. Fast and efficient as usual !

[Jean-Romain]

Please reinstall in an hour or two (or now with remotes::) my fix was not correct. It fixed the segfault but broke the order of the output with parallel processing. This was not caught by unit tests but it was an (un)happy accident.