Hard to tell why it is not working for you.
Assuming that you have the specimens "stacked" one on top of each other,
each of them with 30 landmarks in 2D, it should work changing the
relevant parameters.
My suggestion to you would be to carefully check what these two lines
are doing
data$specimen=as.factor(unlist(lapply(seq_len(landmarks), function(x)
rep(seq_len(landmarks)[x],30))))
data$landmark=as.factor(rep(1:30,30))
As they comprise various nested calls, you might find it useful to try
on the nested part first and then run the whole call.
If checking data$specimen and data$landmark you get indeed the right
number of rows and the right names, I don't see why the reshaping
shouldn't work.
I hope this helps.
Carmelo
On 12/08/2018 22:33, Ian F wrote:
im sorry to ask so many questions. How would I reformat the script you
have provided to convert 2686 observations of 2 variables (x and y
coordinates) into wide format? when i try to alter it i end up with
millions of rows.
On Thursday, August 2, 2018 at 1:32:02 PM UTC-4, Ian F wrote:
I am trying to do an analysis of three specimens. I am using
semi-landmarks and having trouble. perhaps someone can point out mt
error? these are my results
Generalized Procrustes Analysis
with Partial Procrustes Superimposition
-4 fixed landmarks
12 semilandmarks (sliders)
2-dimensional landmarks
6 GPA iterations to converge
Minimized Bending Energy used
Consensus (mean) Configuration
X Y
[1,] 0.51447153 -0.03794928
[2,] 0.36957021 0.11431610
[3,] -0.11602250 0.19898458
[4,] -0.40489951 0.11095030
[5,] -0.43738229 -0.09965594
[6,] -0.20913543 -0.09698422
[7,] 0.04257626 -0.09131803
[8,] 0.29799009 -0.04811314
it should be three individuals with 4 landmarks and 4 sliders each.
i want to perform PCA on the procrustes coordinates. my code and
data are below. Im new to R and its probably an easy fix im just
really confused. any help is greatly appreciated.
Code: Y <- arrayspecs(coordsrformat, k=2, p= ncol(coordsrformat)/2)
slidermatrix
Y.gpa <- gpagen(Y,curves=slidermatrix)
summary(Y.gpa)
plot(Y.gpa)
Y.gpa <- gpagen(Y,curves=slidermatrix,ProcD=FALSE )
summary(Y.gpa)
plot(Y.gpa)
a<-(Y.gpa$coords)
plotTangentSpace(a)
slider matrix:
before slide after
5 6 7
7 8 1
1 2 3
3 4 5
1 8 7
7 6 5
5 4 3
3 2 1
1 2 3
3 4 5
5 6 7
7 8 1
coordsrformat:
1630 1827 1530 1549 1198
1345 908 1557 833 1840
1027 1895 1223 1907 1417 1887
2767 1081 2633 1581 2139
2047 1693 1753 1535 1159
1841 1067 2151 1009 2437 1071
2956 928 2936 1692 2112
2360 1300 1784 1304 1016
1700 888 2084 832 2480 872
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Carmelo Fruciano
Institute of Biology
Ecole Normale Superieure - Paris
CNRS
http://www.fruciano.it/research/
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