Michael,
I have not gone through extensive testing, but it seems pretty fast and
usefull for my 1.0 las. I've loaded a 235 Mb file on a USB drive, and it
ran in ~20 seconds. SAGA, in comparison did it in 3 min 22 seconds.
Cheers,
Etienne
Le 2010-06-06 10:18, Michael Sumner a écrit :
> Hello,
>
>
>> To other issue I see here is that R is loading the whole file in memory, so
>> if you can manage small files, that might not be that easy with (standard)
>> larger ones. Don't you think ?
>>
> That was certainly true of the version of code I posted, but writing a
> more flexible version is not difficult, and actually less difficult
> than I expected. I've implemented arguments to "skip" and read "nrows"
> at a time, so there is the beginnings of a wrapper around the core
> read for building more flexibility.
>
> (I was thinking of including subsetting of various kinds which really
> makes it more complicated, and the appropriate level to handle that is
> in a wrapper to this function).
>
> I've updated the R source on my site, and here's a new example. This
> should be considered as a rough working draft, the details can be
> hidden in the final suite of functions. My chunk/rows handling is
> pretty awkward, and may have bugs for particular record numbers.
>
> Any testing you can provide would be greatly appreciated.
>
>
> # new version with "skip" and "nrows" arguments
> source("http://staff.acecrc.org.au/~mdsumner/las/readLAS.R";)
>
> f<- "lfile.las"
>
> ## get just the header
> hd<- readLAS(f, returnHeaderOnly = TRUE)
>
> numrows<- hd$`Number of point records`
> ## [1] 1922632
>
> ## read in chunks, and pass to DB or ff, or subset by sampling, etc..
> rowskip<- 0
> chunk<- 1e5
> rowsleft<- numrows
>
> system.time({
>
> ## keep track of how many rows we skip, and how many are left
> for (i in 1:ceiling(numrows / chunk)) {
> if (rowsleft< chunk) chunk<- rowsleft
> if (chunk< 1) break;
> d<- readLAS(f, skip = rowskip, nrows = chunk)
> rowskip<- rowskip + nn
> rowsleft<- numrows - nn
> }
>
> })
>
> # user system elapsed
> # 1.10 0.55 1.64
>
>
>
>
>
>
>
> On Sun, Jun 6, 2010 at 8:09 PM, Etienne Bellemare Racine
> <etienn...@gmail.com> wrote:
>
>> This is interesting, I'll try your code on my lidar files in the next few
>> days.
>>
>> 2010-06-04 22:36, Michael Sumner wrote :
>>
>>> Thanks Alex, I will eventually post this to a broader audience.
>>>
>>> I've used liblas and lastools, but the aim here is for a pure R
>>> implementation that is built directly from the LAS specification
>>> without 3rd party tools.
>>>
>>>
>> What might be of interest in using liblas is that it provides support for
>> many las versions and they plan to provide support for some versions to come
>> (conditional to funding) so having an R binding might be of interest here.
>> They are also working on the integration of a spatial index which would
>> allow easier handling of large files. I must say I don't know how hard
>> writing a wrapper for R might be for that particular tool.
>>
>> To other issue I see here is that R is loading the whole file in memory, so
>> if you can manage small files, that might not be that easy with (standard)
>> larger ones. Don't you think ? Did you give a try to the R SAGA package.
>> There is a module for loading las files but again, I don't know how it
>> manages memory. I guess that it could be possible to use some sort of ff
>> package to handle bigger files, but that's just on the top of my head.
>>
>> Etienne
>>
>>
>>> The R code already works quite well to extract x/y/z/time/intensity,
>>> it just needs some extra work to tidy up and generalize things and
>>> ensure that very big datasets can be read.
>>>
>>> Cheers, Mike.
>>>
>>>
>>> On Sat, Jun 5, 2010 at 6:07 AM, Alex Mandel<tech_...@wildintellect.com>
>>> wrote:
>>>
>>>
>>>> On 06/03/2010 07:54 PM, Michael Sumner wrote:
>>>>
>>>>
>>>>> Hello,
>>>>>
>>>>> I'm looking for interest in this functionality and eventually working
>>>>> it into a package.
>>>>>
>>>>> I don't actually use LAS data much, and only have one example file so
>>>>> I'm hoping others who do or know others who would be interested can
>>>>> help. I have previously posted this to r-spatial-devel.
>>>>>
>>>>>
>>>>>
>>>> I think there are people who would use it. You might want to have a look
>>>> at http://liblas.org/ (some of the same people that do gdal/org work)
>>>> Wrapping this library might be a good approach. There are example files
>>>> available too.
>>>>
>>>> Thanks,
>>>> Alex
>>>>
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