Stephane DRAY
2004-Jul-20 14:44 UTC
[R] a bug with LAPACK ? non orthogonal vectors obtained with eigen of a symmetric matrix
Hello,
I have obtained strange results using eigen on a symmetric matrix:
# this function perform a double centering of a matrix
(xij-rowmean(i)-colmean(j)+meantot)
dbcenter=function(mat){
rmean=apply(mat,1,mean)
cmean=apply(mat,2,mean)
newmat=sweep(mat,1,rmean,"-")
newmat=sweep(newmat,2,cmean,"-")
newmat=newmat+mean(mat)
newmat}
# i use spdep package to create a spatial contiguity matrix
library(spdep)
x=dbcenter(nb2mat(cell2nb(3,3),style="B"))
#compute eigenvalues of a 9 by 9 matrix
res=eigen(x)
# some eigenvalues are equal to 0
eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, 0),
TRUE))
# I remove the corresponding eigenvectors
res0=res$vec[,-which(eq0)]
# then I compute the Froebenius norm with the identity matrix
sum((diag(1,ncol(res0))-crossprod(res0))^2)
[1] 1.515139e-30
# The results are correct,
# then I do it again with a biggest matrix(100 by 100)
x=dbcenter(nb2mat(cell2nb(10,10),style="B"))
res=eigen(x)
eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, 0),
TRUE))
res0=res$vec[,-which(eq0)]
sum((diag(1,ncol(res0))-crossprod(res0))^2)
[1] 3.986387
I have try the same with res=eigen(x,EISPACK=T):
x=dbcenter(nb2mat(cell2nb(10,10),style="B"))
res=eigen(x,EISPACK=T)
eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, 0),
TRUE))
res0=res$vec[,-which(eq0)]
sum((diag(1,ncol(res0))-crossprod(res0))^2)
[1] 1.315542e-27
So I wonder I there is a bug in the LAPACK algorithm or if there are some
things that I have not understood. Note that my matrix has some pairs of
equal eigenvalues.
Thanks in advance.
St??phane DRAY
--------------------------------------------------------------------------------------------------
D??partement des Sciences Biologiques
Universit?? de Montr??al, C.P. 6128, succursale centre-ville
Montr??al, Qu??bec H3C 3J7, Canada
Tel : (514) 343-6111 poste 1233 Fax : (514) 343-2293
E-mail : stephane.dray at umontreal.ca
--------------------------------------------------------------------------------------------------
Web http://www.steph280.freesurf.fr/
Stephane DRAY
2004-Jul-20 16:57 UTC
[R] a bug with LAPACK ? non orthogonal vectors obtained with eigen of a symmetric matrix
I have continue my experiments in changing the size of my matrix :
(3^2 by 3^2, 4^2 by 4^2... 20^2 by 20^2)
EISPACK is always correct but LINPACK provide very strange results:
> for(i in 3:20){
+ x=dbcenter(nb2mat(cell2nb(i,i),style="B"))
+ res=eigen(x,EIS=T)
+ eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
0), TRUE))
+ res0=res$vec[,-which(eq0)]
+ print(sum((diag(1,ncol(res0))-crossprod(res0))^2))
+ }
[1] 7.939371e-30
[1] 2.268788e-29
[1] 9.237286e-29
[1] 1.806393e-28
[1] 3.24619e-28
[1] 5.239195e-28
[1] 9.78079e-28
[1] 1.315542e-27
[1] 1.838600e-27
[1] 3.114150e-27
[1] 5.499297e-27
[1] 5.471782e-27
[1] 1.075098e-26
[1] 1.534822e-26
[1] 1.771326e-26
[1] 2.342404e-26
[1] 3.462522e-26
[1] 4.310143e-26
> for(i in 3:20){
+ x=dbcenter(nb2mat(cell2nb(i,i),style="B"))
+ res=eigen(x)
+ eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
0), TRUE))
+ res0=res$vec[,-which(eq0)]
+ print(sum((diag(1,ncol(res0))-crossprod(res0))^2))
+ }
[1] 1.515139e-30
[1] 1.054286e-27
[1] 9.553017e-29
[1] 2.263455e-28
[1] 5.641993e-27
[1] 4.442088e-26
[1] 3.996714
[1] 3.986387
[1] 3.996545
[1] 7.396718
[1] NaN
[1] 7.980621
[1] 7.996769
[1] 3.984399
[1] NaN
[1] NaN
[1] NaN
[1] NaN
> R.Version()
$platform
[1] "i386-pc-mingw32"
$arch
[1] "i386"
$os
[1] "mingw32"
$system
[1] "i386, mingw32"
$status
[1] ""
$major
[1] "1"
$minor
[1] "9.1"
$year
[1] "2004"
$month
[1] "06"
$day
[1] "21"
$language
[1] "R"
At 10:44 20/07/2004, Stephane DRAY wrote:>Hello,
>I have obtained strange results using eigen on a symmetric matrix:
>
># this function perform a double centering of a matrix
>(xij-rowmean(i)-colmean(j)+meantot)
>dbcenter=function(mat){
>rmean=apply(mat,1,mean)
>cmean=apply(mat,2,mean)
>newmat=sweep(mat,1,rmean,"-")
>newmat=sweep(newmat,2,cmean,"-")
>newmat=newmat+mean(mat)
>newmat}
>
># i use spdep package to create a spatial contiguity matrix
>library(spdep)
>x=dbcenter(nb2mat(cell2nb(3,3),style="B"))
>
>#compute eigenvalues of a 9 by 9 matrix
>res=eigen(x)
>
># some eigenvalues are equal to 0
>eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
>0), TRUE))
>
># I remove the corresponding eigenvectors
>res0=res$vec[,-which(eq0)]
>
># then I compute the Froebenius norm with the identity matrix
>sum((diag(1,ncol(res0))-crossprod(res0))^2)
>
>[1] 1.515139e-30
>
># The results are correct,
># then I do it again with a biggest matrix(100 by 100)
>
>x=dbcenter(nb2mat(cell2nb(10,10),style="B"))
>res=eigen(x)
>eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
>0), TRUE))
>res0=res$vec[,-which(eq0)]
>sum((diag(1,ncol(res0))-crossprod(res0))^2)
>
>[1] 3.986387
>
>
>I have try the same with res=eigen(x,EISPACK=T):
>
> x=dbcenter(nb2mat(cell2nb(10,10),style="B"))
>res=eigen(x,EISPACK=T)
>eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
>0), TRUE))
>res0=res$vec[,-which(eq0)]
>sum((diag(1,ncol(res0))-crossprod(res0))^2)
>[1] 1.315542e-27
>
>
>So I wonder I there is a bug in the LAPACK algorithm or if there are some
>things that I have not understood. Note that my matrix has some pairs of
>equal eigenvalues.
>
>Thanks in advance.
>
>St??phane DRAY
>--------------------------------------------------------------------------------------------------
>
>D??partement des Sciences Biologiques
>Universit?? de Montr??al, C.P. 6128, succursale centre-ville
>Montr??al, Qu??bec H3C 3J7, Canada
>
>Tel : (514) 343-6111 poste 1233 Fax : (514) 343-2293
>E-mail : stephane.dray at umontreal.ca
>--------------------------------------------------------------------------------------------------
>
>Web
http://www.steph280.freesurf.fr/
>
>______________________________________________
>R-help at stat.math.ethz.ch mailing list
>https://www.stat.math.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
St??phane DRAY
--------------------------------------------------------------------------------------------------
D??partement des Sciences Biologiques
Universit?? de Montr??al, C.P. 6128, succursale centre-ville
Montr??al, Qu??bec H3C 3J7, Canada
Tel : (514) 343-6111 poste 1233 Fax : (514) 343-2293
E-mail : stephane.dray at umontreal.ca
--------------------------------------------------------------------------------------------------
Web http://www.steph280.freesurf.fr/
Stephane DRAY
2004-Jul-28 14:57 UTC
[R] a bug with LAPACK ? non orthogonal vectors obtained with eigen of a symmetric matrix
Hello,
I have send send this message one week ago but I have receive no answer.
Perhaps, some of RListers were in holidays and do not read my message. I
try again..
My problem is that I obtained non orthonormal eigenvectors with some
matrices with LAPACK while EISPACK seems to provide "good" results. Is
there some restrictions with the use of LAPACK ? Is it a bug ? I did not
find the answer. Here is my experiment:
I have obtained strange results using eigen on a symmetric matrix:
# this function perform a double centering of a matrix
(xij-rowmean(i)-colmean(j)+meantot)
dbcenter=function(mat){
rmean=apply(mat,1,mean)
cmean=apply(mat,2,mean)
newmat=sweep(mat,1,rmean,"-")
newmat=sweep(newmat,2,cmean,"-")
newmat=newmat+mean(mat)
newmat}
# i use spdep package to create a spatial contiguity matrix
library(spdep)
x=dbcenter(nb2mat(cell2nb(3,3),style="B"))
#compute eigenvalues of a 9 by 9 matrix
res=eigen(x)
# some eigenvalues are equal to 0
eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, 0),
TRUE))
# I remove the corresponding eigenvectors
res0=res$vec[,-which(eq0)]
# then I compute the Froebenius norm with the identity matrix
sum((diag(1,ncol(res0))-crossprod(res0))^2)
[1] 1.515139e-30
# The results are correct,
# then I do it again with a biggest matrix(100 by 100)
x=dbcenter(nb2mat(cell2nb(10,10),style="B"))
res=eigen(x)
eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, 0),
TRUE))
res0=res$vec[,-which(eq0)]
sum((diag(1,ncol(res0))-crossprod(res0))^2)
[1] 3.986387
I have try the same with res=eigen(x,EISPACK=T):
x=dbcenter(nb2mat(cell2nb(10,10),style="B"))
res=eigen(x,EISPACK=T)
eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, 0),
TRUE))
res0=res$vec[,-which(eq0)]
sum((diag(1,ncol(res0))-crossprod(res0))^2)
[1] 1.315542e-27
So I wonder I there is a bug in the LAPACK algorithm or if there are some
things that I have not understood. Note that my matrix has some pairs of
equal eigenvalues.
Thanks in advance.
++++++++++++++++++++++++++++++++++++
I have continue my experiments in changing the size of my matrix :
(3^2 by 3^2, 4^2 by 4^2... 20^2 by 20^2)
EISPACK is always correct but LINPACK provide very strange results:
> for(i in 3:20){
+ x=dbcenter(nb2mat(cell2nb(i,i),style="B"))
+ res=eigen(x,EIS=T)
+ eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
0), TRUE))
+ res0=res$vec[,-which(eq0)]
+ print(sum((diag(1,ncol(res0))-crossprod(res0))^2))
+ }
[1] 7.939371e-30
[1] 2.268788e-29
[1] 9.237286e-29
[1] 1.806393e-28
[1] 3.24619e-28
[1] 5.239195e-28
[1] 9.78079e-28
[1] 1.315542e-27
[1] 1.838600e-27
[1] 3.114150e-27
[1] 5.499297e-27
[1] 5.471782e-27
[1] 1.075098e-26
[1] 1.534822e-26
[1] 1.771326e-26
[1] 2.342404e-26
[1] 3.462522e-26
[1] 4.310143e-26
> for(i in 3:20){
+ x=dbcenter(nb2mat(cell2nb(i,i),style="B"))
+ res=eigen(x)
+ eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x,
0), TRUE))
+ res0=res$vec[,-which(eq0)]
+ print(sum((diag(1,ncol(res0))-crossprod(res0))^2))
+ }
[1] 1.515139e-30
[1] 1.054286e-27
[1] 9.553017e-29
[1] 2.263455e-28
[1] 5.641993e-27
[1] 4.442088e-26
[1] 3.996714
[1] 3.986387
[1] 3.996545
[1] 7.396718
[1] NaN
[1] 7.980621
[1] 7.996769
[1] 3.984399
[1] NaN
[1] NaN
[1] NaN
[1] NaN
Note that I have do the same with random number and never find this kind of
problems
> R.Version()
$platform
[1] "i386-pc-mingw32"
$arch
[1] "i386"
$os
[1] "mingw32"
$system
[1] "i386, mingw32"
$status
[1] ""
$major
[1] "1"
$minor
[1] "9.1"
$year
[1] "2004"
$month
[1] "06"
$day
[1] "21"
$language
[1] "R"
St??phane DRAY
--------------------------------------------------------------------------------------------------
D??partement des Sciences Biologiques
Universit?? de Montr??al, C.P. 6128, succursale centre-ville
Montr??al, Qu??bec H3C 3J7, Canada
Tel : (514) 343-6111 poste 1233 Fax : (514) 343-2293
E-mail : stephane.dray at umontreal.ca
--------------------------------------------------------------------------------------------------
Web http://www.steph280.freesurf.fr/
Roger D. Peng
2004-Jul-28 15:25 UTC
[R] a bug with LAPACK ? non orthogonal vectors obtained with eigen of a symmetric matrix
This is interesting. I can reproduce your results but cannot come up with an explanation. However, using svd(LINPACK = FALSE) seems to work every time. Might you consider trying that instead? -roger Stephane DRAY wrote:> Hello, > I have send send this message one week ago but I have receive no answer. > Perhaps, some of RListers were in holidays and do not read my message. I > try again.. > My problem is that I obtained non orthonormal eigenvectors with some > matrices with LAPACK while EISPACK seems to provide "good" results. Is > there some restrictions with the use of LAPACK ? Is it a bug ? I did not > find the answer. Here is my experiment: > > I have obtained strange results using eigen on a symmetric matrix: > > # this function perform a double centering of a matrix > (xij-rowmean(i)-colmean(j)+meantot) > dbcenter=function(mat){ > rmean=apply(mat,1,mean) > cmean=apply(mat,2,mean) > newmat=sweep(mat,1,rmean,"-") > newmat=sweep(newmat,2,cmean,"-") > newmat=newmat+mean(mat) > newmat} > > # i use spdep package to create a spatial contiguity matrix > library(spdep) > x=dbcenter(nb2mat(cell2nb(3,3),style="B")) > > #compute eigenvalues of a 9 by 9 matrix > res=eigen(x) > > # some eigenvalues are equal to 0 > eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, > 0), TRUE)) > > # I remove the corresponding eigenvectors > res0=res$vec[,-which(eq0)] > > # then I compute the Froebenius norm with the identity matrix > sum((diag(1,ncol(res0))-crossprod(res0))^2) > > [1] 1.515139e-30 > > # The results are correct, > # then I do it again with a biggest matrix(100 by 100) > > x=dbcenter(nb2mat(cell2nb(10,10),style="B")) > res=eigen(x) > eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, > 0), TRUE)) > res0=res$vec[,-which(eq0)] > sum((diag(1,ncol(res0))-crossprod(res0))^2) > > [1] 3.986387 > > > I have try the same with res=eigen(x,EISPACK=T): > > x=dbcenter(nb2mat(cell2nb(10,10),style="B")) > res=eigen(x,EISPACK=T) > eq0 <- apply(as.matrix(res$values),1,function(x) identical(all.equal(x, > 0), TRUE)) > res0=res$vec[,-which(eq0)] > sum((diag(1,ncol(res0))-crossprod(res0))^2) > [1] 1.315542e-27 > > > So I wonder I there is a bug in the LAPACK algorithm or if there are > some things that I have not understood. Note that my matrix has some > pairs of equal eigenvalues. > > Thanks in advance. > ++++++++++++++++++++++++++++++++++++ > > I have continue my experiments in changing the size of my matrix : > (3^2 by 3^2, 4^2 by 4^2... 20^2 by 20^2) > > EISPACK is always correct but LINPACK provide very strange results: > > > > for(i in 3:20){ > + x=dbcenter(nb2mat(cell2nb(i,i),style="B")) > + res=eigen(x,EIS=T) > + eq0 <- apply(as.matrix(res$values),1,function(x) > identical(all.equal(x, 0), TRUE)) > + res0=res$vec[,-which(eq0)] > + print(sum((diag(1,ncol(res0))-crossprod(res0))^2)) > + } > [1] 7.939371e-30 > [1] 2.268788e-29 > [1] 9.237286e-29 > [1] 1.806393e-28 > [1] 3.24619e-28 > [1] 5.239195e-28 > [1] 9.78079e-28 > [1] 1.315542e-27 > [1] 1.838600e-27 > [1] 3.114150e-27 > [1] 5.499297e-27 > [1] 5.471782e-27 > [1] 1.075098e-26 > [1] 1.534822e-26 > [1] 1.771326e-26 > [1] 2.342404e-26 > [1] 3.462522e-26 > [1] 4.310143e-26 > > for(i in 3:20){ > + x=dbcenter(nb2mat(cell2nb(i,i),style="B")) > + res=eigen(x) > + eq0 <- apply(as.matrix(res$values),1,function(x) > identical(all.equal(x, 0), TRUE)) > + res0=res$vec[,-which(eq0)] > + print(sum((diag(1,ncol(res0))-crossprod(res0))^2)) > + } > [1] 1.515139e-30 > [1] 1.054286e-27 > [1] 9.553017e-29 > [1] 2.263455e-28 > [1] 5.641993e-27 > [1] 4.442088e-26 > [1] 3.996714 > [1] 3.986387 > [1] 3.996545 > [1] 7.396718 > [1] NaN > [1] 7.980621 > [1] 7.996769 > [1] 3.984399 > [1] NaN > [1] NaN > [1] NaN > [1] NaN > > Note that I have do the same with random number and never find this kind > of problems > > > > R.Version() > $platform > [1] "i386-pc-mingw32" > > $arch > [1] "i386" > > $os > [1] "mingw32" > > $system > [1] "i386, mingw32" > > $status > [1] "" > > $major > [1] "1" > > $minor > [1] "9.1" > > $year > [1] "2004" > > $month > [1] "06" > > $day > [1] "21" > > $language > [1] "R" > > St??phane DRAY > -------------------------------------------------------------------------------------------------- > > D??partement des Sciences Biologiques > Universit?? de Montr??al, C.P. 6128, succursale centre-ville > Montr??al, Qu??bec H3C 3J7, Canada > > Tel : (514) 343-6111 poste 1233 Fax : (514) 343-2293 > E-mail : stephane.dray at umontreal.ca > -------------------------------------------------------------------------------------------------- > > Web > http://www.steph280.freesurf.fr/ > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html >