On 17/05/2011 14:00, Mathieu Rajerison wrote: > Many thanks for the code! > > What are the units of R in marktable? I didn't find the information in the > documentation. > The same units of x and y coordinates in your ppp object.
Cheers, Marcelino > 2011/5/17 Marcelino de la Cruz<[email protected]> > > >> On 16/05/2011 10:27, Matevž PavliÄ? wrote: >> >> >>> Hi all, >>> >>> I read (just now) about the Simpson idex. This would probably be a good >>> thing to try in my case. Do you have any ideas of how to create a diversity >>> map using Simpson index? >>> >>> >>> >> library(vegan) >> simpson<- diversity(lansing.tab, "simpson") >> lansing.simpson<- setmarks(lansing,simpson) >> lansing.simpson.s<-smooth.ppp(lansing.simpson) >> plot(lansing.simpson.s) >> >> >> . I have just a few more questions about the code : >> >>> The line below as I understand sets a table for each point with the type >>> of points that are in the near in the radius R=350 units? >>> mol.tab<- marktable(mol.ppp,R=350) >>> >>> >>> >> Yes. >> To resolve questions like this about the arguments of the functions, please >> read the help pages, e.g. >> help(marktable) >> >> >> And this line creates a surface(map) of diversity ? >> >>> lansing.div.s<-smooth.ppp(lansing.div) >>> >>> >> Yes again. >> help(smooth.ppp); help(density.ppp) >> >> >> >>> I think this map that is created with smooth.ppp is to rough giving to >>> little detail on the diversity. Would it be possible to use kriging to >>> create diversity map? >>> >>> >>> >> It depends on what do you think is "too rough". You may control >> the"roughnes" of the map changing the "dimyx" argument (that controls the >> final grid of the smoothed surface). You may be also interested in setting >> the argument "sigma" (that controls the bandwith of the smoothing kernel). >> Although it is possible to krige the results, I think that in this case is >> preferable to trust the smoothed surface. >> >> Cheers, >> Marcelino >> >> >> >> >> Thanks for the help, >> >>> m >>> >>> -----Original Message----- >>> From: [email protected] [mailto:[email protected]] >>> Sent: Monday, May 16, 2011 9:59 AM >>> To: Matevž PavliÄ? >>> Cc: [email protected] >>> Subject: RE: [R-sig-Geo] density /diversity of points >>> >>> Con fecha 15/5/2011, "Matevž Pavlič"<[email protected]> >>> escribió: >>> >>> >>> >>> >>>> Hi Marcelino, >>>> >>>> Was out of the office for a while... >>>> Thanks for the help. I think this could work...but can you tell me what >>>> this line does? >>>> >>>> diversity<- apply(mol.tab,1,function(x) sum(x>0)) >>>> >>>> >>>> >>> mol.tab is a table with the number of occurrences of each type (columns) >>> in the neighborhood of each point (rows). This line computes for each >>> row (i.e. for each point) the number of types whose value is ">0" >>> (i.e. types that are present in the neighborhood). This is a very simple >>> definition of diversity (i.e. "richness"). From that table you could >>> also compute Shannon or Simpson diversity indices, if you would prefer >>> that. >>> >>> >>> Marcelino >>> >>> >>> >>> >>>> i cant figure out how diversity is calculated here? >>>> >>>> Thanks again for the help, >>>> >>>> matevz >>>> >>>> -----Original Message----- >>>> From: Marcelino de la Cruz [mailto:[email protected]] >>>> Sent: Thursday, May 12, 2011 2:03 PM >>>> To: MatevÃ...¾ PavliÃ" Cc: [email protected] >>>> Subject: Re: [R-sig-Geo] density /diversity of points >>>> >>>> On 12/05/2011 13:12, MatevÃ...¾ PavliÃ" wrote: >>>> >>>> >>>> >>>>> Hi all, >>>>> >>>>> >>>>> >>>>> I have a point data set (SHP) with coordinates and a attribute (i.e. >>>>> type of point). >>>>> >>>>> These points are scattered around a fairly big area. What i would like >>>>> to do is to find a sub-area where density of points sombined with the >>>>> diversity of type is the biggest. >>>>> >>>>> Does anyone have any idea iff this is somehowe possible to do in R? >>>>> Any idea would be greatly aprpeciated, >>>>> >>>>> >>>>> >>>>> >>>>> >>>> To your first question: >>>> >>>> library(fortunes) >>>> fortune("Yoda") >>>> >>>> ;-) >>>> >>>> More seriously, you could transform your shp data in a ppp object with >>>> spatstat. See the vignette in spatstat. Then you can use some functions >>>> there, for example (with the data set lansing): >>>> >>>> library(spatstat) >>>> data(lansing) >>>> plot(lansing) >>>> # get an estimate of point density >>>> lansing.den<- density.ppp(lansing) >>>> plot(lansing.den) >>>> >>>> # get an estimate of point diversity (here, for the shake of brevity, at >>>> the points themselves) >>>> lansing.tab<- marktable(lansing,R=0.05) >>>> diversity<- apply(lansing.tab,1,function(x) sum(x>0)) lansing.div<- >>>> setmarks(lansing,diversity) lansing.div.s<-smooth.ppp(lansing.div) >>>> >>>> plot(lansing.div.s) >>>> >>>> # select areas with arbitrary high values of density and diversity plot( >>>> eval.im(lansing.div.s>4.5& (lansing.den/max(lansing.den))>0.9)) >>>> >>>> >>>> HTH. Cheers, >>>> >>>> Marcelino >>>> >>>> >>>> >>>> -- >>>> _________________________________ >>>> >>>> Marcelino de la Cruz Rot >>>> Departamento de Biologia Vegetal >>>> E.U.T.I. Agricola >>>> Universidad Politecnica de Madrid >>>> 28040 Madrid >>>> Tel: 34913365654 >>>> _________________________________ >>>> >>>> >>>> >>>> >>> >> -- >> _________________________________ Marcelino de la Cruz Rot Departamento de >> Biologia Vegetal E.U.T.I. Agricola Universidad Politecnica de Madrid 28040 >> Madrid Tel: 34913365654 _________________________________ >> >> >> _______________________________________________ >> R-sig-Geo mailing list >> [email protected] >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >> >> > [[alternative HTML version deleted]] > > > > > _______________________________________________ > R-sig-Geo mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > -- _________________________________ Marcelino de la Cruz Rot Departamento de Biologia Vegetal E.U.T.I. Agricola Universidad Politecnica de Madrid 28040 Madrid Tel: 34913365654 _________________________________ [[alternative HTML version deleted]]
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