Errors with treeMap() when not using map.hough()

[jdonager]

Hello again! In the development version, I am unable to use either of the eigen methods within treeMap().

So with code: las <- readLAS(lazs[i]) map <- treeMap(las, method = map.eigen.knn())

I receive this error: point cloud apparently not normalized Calculating knn fastPointMetrics Error in knn(las %>% las2xyz, k = n + 1) : Requesting more points (101) than available in cloud (19)

**The las is indeed normalized, I continue to receive that warning.

With this code: las <- readLAS(lazs[i]) map <- treeMap(las, method = map.eigen.voxel()) point cloud apparently not normalized Calculating voxel fastPointMetrics Error in knn(nxy[, -1], k = 2) : Cloud has no points In addition: Warning messages: 1: In max(Z) : no non-missing arguments to max; returning -Inf 2: In min(Z) : no non-missing arguments to min; returning Inf

** The las object certainly has points: las <- readLAS(lazs[i]) las class : LAS (v1.3 format 3) memory : 7.8 Mb extent : 431791.4, 431816.7, 3899186, 3899208 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=12 +datum=WGS84 +units=m +no_defs area : 391.0242 m² points : 75.2 thousand points density : 192.31 points/m²

With the map.hough() method, it works fine, albeit with the same warning about normalization: las <- readLAS(lazs[i]) map <- treeMap(las, map.hough()) point cloud apparently not normalized map class : LAS (v1.2 format 0) memory : 2.4 Mb extent : 431791.2, 431810.7, 3899194, 3899207 (xmin, xmax, ymin, ymax) coord. ref. : NA area : 52.53136 units² points : 45 thousand points density : 857.05 points/units²

I have confirmed that this is consistent with several TLS point clouds. I can share the point cloud if needed. Thanks again for your work, Jonathon

[tiagodc]

If you can share one of those point clouds it will be very helpful. Thanks.

[tiagodc]

My hunch is that the error is in the treeMap.merge method used internally. Try to run treeMap(las, method = map.eigen.knn(), merge=0) and see if it works, meanwhile I'll check this bug. Thanks for reporting again!

[jdonager]

https://drive.google.com/file/d/1FmYp2Fz-TvYosZJsgwvQFkmgE_Xxi_ZN/view?usp=sharing https://drive.google.com/file/d/1YrC1fDbAwfJ3UOzQ9g2kvd7p9v3F5cnU/view?usp=sharing Two laz files of the same area, which both produced the same error for me.

[jdonager]

when I try treeMap() with merge=0 I am still getting the same errors.

[tiagodc]

Fixed.

Turns out your point clouds were not very dense and those methods apply a few heavy thinnings in the point density. Those thinnings were based on either fixed parameters or user inputs. Those parameters were originally set considering that TLS point clouds are usually very dense (thousands of points / m²), and I haven't considered their application on less dense clouds, like UAV scans.

I reconsidered those assumptions and altered the code to "guess" those parameters based on the point cloud density itself, so they're now more automatic but still require close attention from the user to try out and set the best parameters for each use case.

Please keep reporting :)

[jdonager]

Hi, I just reinstalled, but am getting the exact same errors as before.

[jdonager]

The point clouds were subsampled previous to running the analyses.

[jdonager]

I have also changed parameters within the method call, but still get the same error.

[tiagodc]

strange... I even added extra error handlers. What OS are you working on? Can you confirm that your TreeLS version is v2.0.2?

[jdonager]

I am on Linux Ubuntu 20.04, and yes, the version installed is 2.0.2

[tiagodc]

Can you share the exact code snippet and which dataset?

[tiagodc]

Can you share the exact code snippet and which dataset?

[jdonager]

Ah, my mistake! It looks like when I installed the new version, I must have failed to call the new library. Restarting R fixed the problem and it is working now as you indicated. My apologies!