random % with corresponding % from real landscape about landscapetools

[wegmann]

of course, please feel free to implement the whole r.pi suit into your R package!

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On 03/26/2018 03:46 PM, Marco Sciaini wrote: Ah, very nice 👍 thanks a lot - would it be OK with you if I (if times allows it) implement it in nlmr <https://github.com/ropensci/nlmr>? and sorry for sidetracking you here :) — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#6 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AHJ6mJQVqsLEpDsYNvMzZhLb7wWzCGICks5tiPEpgaJpZM4S6reR>.

[marcosci]

Hi Martin :-)

Makes perfect sense, will have a look at that in the next days (grass is most likely a never-ending resource of inspiration for us). Thanks for the comment!

I have for a couple of weeks now an email draft in my inbox - is there a way to see your grass algorithms for the midpoint displacement somewhere (from your dissertation)? didn't find it in grass anymore.

[wegmann]

Hi Marco, I moved in the past years more and more to R hence I neglected GRASS a bit, but try to get back into it. Therefore I am not anymore up-to-date with the GRASS code status. What do you mean with "midpoint displacement"? In which command was it used? regards, Martin

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On 03/26/2018 10:17 AM, Marco Sciaini wrote: Hi Martin :-) Makes perfect sense, will have a look at that in the next days (grass is most likely a never-ending resource of inspiration for us). Thanks for the comment! I have for a couple of weeks now an email draft in my inbox - is there a way to see your grass algorithms for the midpoint displacement somewhere (from your dissertation)? didn't find it in grass anymore. — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#6 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AHJ6mOdq24WFaDhEFBCXICPENrtA-MA8ks5tiKQ3gaJpZM4S6reR>.

[marcosci]

r.nlm was I think the algorithm you mentioned in your thesis :)

[wegmann]

Hi Marco, r.nlm was renamed to r.pi.nlm, and r.pi.nlm.stats (and old trial r.pi.nlm.circ) https://grass.osgeo.org/grass74/manuals/addons/r.pi.nlm.html https://grass.osgeo.org/grass74/manuals/addons/r.pi.nlm.stats.html the code can be seen here: https://trac.osgeo.org/grass/browser/grass-addons/grass7/raster/r.pi/r.pi.nlm.stats regards, Martin

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On 03/26/2018 10:51 AM, Marco Sciaini wrote: r.nlm was I think the algorithm you mentioned in your thesis :) — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#6 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AHJ6mACFx5MM2PuYRSueyOkijMnoUG1Kks5tiKv7gaJpZM4S6reR>.

[marcosci]

Ah, very nice 👍 thanks a lot - would it be OK with you (if time allows it) if I implement it in nlmr? and sorry for sidetracking you here :)

[mattfrit]

Hi Martin,

I finally found some time to implement your idea... :)

You can now give an optional 'real' landscape to the util_classify function. The classification then overwrites the weightings with the proportions from this landscape. In case you want to mask parts of the nlm landscape you have to give the exact value for the class in the real landscape. There is an example in the help file.

I hope this covers your idea/request, if not feel free to reopen this issue or make another nice suggestion to improve our package.

Thanks and kind regards
Matthias

[wegmann]

Hi Matthias, great, thanks a lot. I will test is asap. regards, Martin

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On 05/07/2018 10:18 AM, mattfrit wrote: Hi Martin, I finally found some time to implement your idea... :) You can now give an optional 'real' landscape to the util_classify function. The classification then overwrites the weightings with the proportions from this landscape. In case you want to mask parts of the nlm landscape you have to give the exact value for the class in the real landscape. There is an example in the help file. I hope this covers your idea/request, if not feel free to reopen this issue or make another nice suggestion to improve our package. Thanks and kind regards Matthias — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#6 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AHJ6mD3QQya3nqEFEmvLnjQCKFx6ee6Sks5twANjgaJpZM4S6reR>.