Disregard this previous post: I am going to stick with .tps files. I will
have to append all of the individuals for each group first in order to do
the between group analysis, but it's a method I know works. I hope I didn't
waste anyone's time looking into this.
Brenna
On Monday, April 4, 2016 at 5:47:59 PM UTC-4, Brenna Hays wrote:
>
> Hello All,
> For my thesis project I am looking at the shape variations of crinoid
> ossicles between species of a certain taxonomic family. I have completed my
> within-species analysis and have saved the mean configurations of each
> species for my between-species or "between-group" PCA. To test this out, I
> compiled three species (three configurations) into a .txt file then
> performed Procrustes superimposition on the matrix. All of the coding is
> working fine, but I notice when I plot the superimposed configurations, not
> all 3 are oriented together. Two of them are oriented to the left, and the
> third is oriented to the right. These orientations are exactly the same as
> how their mean configurations were saved (they didn't change after gpagen),
> so it doesn't seem they were actually correctly superimposed upon each
> other.
> For my intra-species tests I was able to directly upload the coordinates
> via a .tps file so the superimposition worked great. However, since I have
> had to save mean configurations as the representative for each of my
> species and compile them for the different between-group tests I will be
> doing, the coding has been a bit different. I compiled the mean
> configurations in Excel then exported it as a .txt file.
> Below is my code. I have also attached the superimposed image with
> joinline so you can see how one of oriented opposite of the other two. Any
> help or thoughts on this matter would be greatly appreciated!
>
> > setwd("C:/Users/B/Documents/THESIS/Statistics/Scenario1/Antedonidae
> incertae sedis")
> > AISdata <- read.table(file.choose("AIS matrix.txt"), head=TRUE)
> > species <- as.factor(AISdata[,1])
> > csize <- as.vector(AISdata[,2])
> > depth <- as.factor(AISdata[,3])
> > locale <- as.factor(AISdata[,4])
> > RR <- as.factor(AISdata[,5])
> > CDR <- as.factor(AISdata[,6])
>
> > AIS <- as.matrix(AISdata[,-(1:6)])
> >
> > is.numeric(AIS)
> [1] TRUE
>
> > AIS.shape <- arrayspecs(AIS,25,2)
> > AIS.super <- gpagen(AIS.shape)
> > names(AIS.super)
> [1] "coords" "Csize" "iter" "points.VCV"
> "points.var" "consensus"
> [7] "p" "k" "nsliders" "nsurf" "data"
> "Q"
> [13] "slide.method" "call"
>
> > AISarray <- two.d.array(AIS.shape)
> > AISarray
> [,1] [,2] [,3] [,4] [,5] [,6]
> [,7] [,8]
> [1,] -0.3023043 0.11018580 -0.09019077 0.2063007 0.10797090 0.2356602
> 0.1942508 0.1284485
> [2,] -0.3189721 0.08885828 -0.10303453 0.1979945 0.10652075 0.2377025
> 0.1694973 0.1731607
> [3,] 0.3680717 -0.05312220 0.01887333 -0.1909477 -0.08767592 -0.2014106
> -0.1486420 -0.1485168
> [,9] [,10] [,11] [,12] [,13] [,14]
> [,15] [,16]
> [1,] 0.1980599 0.03970195 0.1017983 0.05041833 0.09914963 -0.04387893
> 0.1933970 -0.08178463
> [2,] 0.1651301 0.08660780 0.1155678 0.08307038 0.11690521 -0.07633613
> 0.1716527 -0.08059491
> [3,] -0.1603194 -0.06361361 -0.1035876 -0.06069144 -0.10815490 0.04951909
> -0.1662444 0.06520166
> [,17] [,18] [,19] [,20] [,21] [,22]
> [,23] [,24]
> [1,] 0.1764013 -0.1647228 0.09535528 -0.2353786 -0.092696160 -0.1846257
> -0.2982749 -0.11114690
> [2,] 0.1716527 -0.1667319 0.11626194 -0.2417347 -0.101362815 -0.1927248
> -0.3245558 -0.07686364
> [3,] -0.1572431 0.1453066 -0.10713760 0.1982355 0.003947048 0.1968381
> 0.3625471 0.05191814
> [,25] [,26] [,27] [,28] [,29]
> [,30] [,31] [,32]
> [1,] -0.2892081 -0.01549321 -0.2661613 -0.0000096006 -0.07823776
> 0.02564890 -0.05870517 0.1191063
> [2,] -0.2791457 -0.02152225 -0.2136730 0.0004915837 -0.06976480
> 0.02706498 -0.07740526 0.1500473
> [3,] 0.3512638 0.01748087 0.3235535 0.0000778100 0.03703989
> -0.02924458 0.02404925 -0.1525469
> [,33] [,34] [,35] [,36] [,37]
> [,38] [,39] [,40]
> [1,] -0.023388670 0.12534780 0.05604006 0.07290103 0.09462322
> 0.004968850 0.04503409 -0.06598428
> [2,] -0.004267756 0.10304202 0.05518285 0.05854853 0.09531672
> 0.001285137 0.05287348 -0.05727687
> [3,] -0.024146350 -0.07941564 -0.05238288 -0.04300939 -0.08674858
> -0.003493334 -0.05213929 0.04122498
> [,41] [,42] [,43] [,44] [,45]
> [,46] [,47] [,48]
> [1,] -0.001610772 0.0066155220 -0.0301974800 -0.10920320 -0.06167416
> -0.1110030 -0.07546186 -0.01649362
> [2,] 0.012413723 -0.0002767074 -0.0009055873 -0.11089758 -0.07277358
> -0.1487385 -0.06680632 -0.03298501
> [3,] -0.013718360 -0.0004120264 -0.0261172500 0.07330989 0.01402188
> 0.1622024 0.03644913 0.02526047
> [,49] [,50]
> [1,] 0.3060308 0.0144204200
> [2,] 0.2808471 -0.0011906212
> [3,] -0.2455590 -0.0001512177
>
> > AIS.means <- rowsum(AISarray, species)/as.vector(table(species))
> > AIS.means.shape <- arrayspecs(AIS.means, 25, 2)
> > AIS.means.super <- gpagen(AIS.means.shape, Proj=TRUE, ProcD=TRUE,
> PrinAxes=TRUE, curves=NULL, surfaces=NULL)
>
> > #plot the superimposed configurations
> > AISMcoord <- AIS.means.super$coords
> > max(AISMcoord[ ,1, ]); min(AISMcoord[ ,1, ]); max(AISMcoord[ ,2, ]);
> min(AISMcoord[ ,2, ])
> [1] 0.3076018
> [1] -0.3717857
> [1] 0.2391025
> [1] -0.2434714
> > plot(AISMcoord[ ,1,1], AISMcoord[ ,2,1], asp=1, pch=21,
> bg="darkgoldenrod1", xlab="x", ylab="y", cex=1.5, xlim=c(-0.4, 0.35),
> ylim=c(-0.3, 0.3))
> > points(AISMcoord[ ,1,2], AISMcoord[ ,2,2], asp=1, pch=21,
> bg="darkorange", cex=1.5)
> > points(AISMcoord[ ,1,3], AISMcoord[ ,2,3], asp=1, pch=21, bg="orange",
> cex=1.5)
> > legend('bottomright', legend=c("Balba", "Hybse", "Polpx"),
> fill=c("darkgoldenrod1", "darkorange", "orange"), cex=1)
> > title("Superimpositions for specimens of \nAntedonidae incertae sedis",
> cex.main=1.5)
> > joinline <- c(1:3,25,10:14,NA,15:17,3:10,22:24,NA,18:21,18)
> > for (i in 1:3) {lines(AIS.shape[joinline,,i], col="grey")}
>
> Thanks,
> Brenna
>
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