Michael Friendly
2011-Mar-22 15:27 UTC
[R] how to convert a data.frame to a list of dist objects for individual differences MDS?
I have a 45 x 16 data frame consisting of dissimilarities among 10
colors, giving in each
column the 45 = 10*9/2 pairwise judgments for one of 16 subjects. The
rownames
identify each pair of colors, e.g, "AC" =
("A","C"), and the pairs are
ordered by columns
in the lower triangle of each distance matrix.
> helm.raw <-
read.table("http://euclid.psych.yorku.ca/datavis/Private/mdshelm.dat",
header=TRUE, row.names=1)
> head(helm.raw)
N1 N2 N3 N4 N5 N6a N6b N7 N8 N9 N10 CD1 CD2a
CD2b CD3 CD4
AC 6.8 5.9 7.1 7.5 6.6 5.2 5.8 6.2 7.5 6.0 9.2 11.5 9.3 9.0
10.4 9.9
AE 12.5 11.1 10.2 10.3 10.5 9.4 10.5 10.8 9.1 9.4 10.8 13.1 10.7 10.0
12.4 13.2
AG 13.8 18.8 11.1 10.7 10.2 11.4 13.4 9.9 10.2 9.5 9.7 12.6 10.7 10.4
12.8 12.3
AI 14.2 17.3 12.5 11.6 9.6 13.3 14.0 11.1 12.1 9.5 10.1 10.6 11.9 10.0
13.7 11.1
AK 12.5 16.6 11.8 10.6 10.8 12.0 13.2 10.3 12.5 9.8 10.3 10.6 11.0 9.3
11.8 8.7
AM 11.0 16.5 9.9 9.7 9.7 12.3 11.7 8.8 9.7 8.7 9.7 10.8 9.8 8.6
4.3 5.6
> row.names(helm.raw)
[1] "AC" "AE" "AG" "AI" "AK"
"AM" "AO" "AQ" "AS" "CE"
"CG" "CI" "CK"
"CM" "CO" "CQ" "CS" "EG"
"EI" "EK"
[21] "EM" "EO" "EQ" "ES" "GI"
"GK" "GM" "GO" "GQ" "GS"
"IK" "IM" "IO"
"IQ" "IS" "KM" "KO" "KQ"
"KS" "MO"
[41] "MQ" "MS" "OQ" "OS" "QS"
>
To analyse this (with individual differences MDS, e.g., smacofDiff()), I
need to:
(a) convert this to a list of objects of class "dist", one for each
column of helm.raw
(b) rename the 1-letter codes to color name abbreviations as row/col
labels for each distance matrix,
according to:
'A'='RPur'
'C'='Red'
'E'='Yel'
'G'='Gy1'
'I'='Gy2'
'K'='Green'
'M'='Blue'
'O'='BlP'
'Q'='Pur1'
'S'='Pur2'
I've done this in SAS, but I don't know how to do it in R because
neither dist() nor
as.dist() seem to be able to work with data in this format. I could try
brute-force,
but maybe there is an easier way. Can someone help?
As a distance matrix, the column helm.raw$CD1 for subject CD1 should
appear something like
shown below (without the Obs column, where stim is the rowname)
--------------------------------- Subject=CD1
----------------------------------
Obs stim RPur Red Yel Gy1 Gy2 Green Blue BlP Pur1 Pur2
1 RPur . . . . . . . . . .
2 Red 11.5 . . . . . . . . .
3 Yel 13.1 6.0 . . . . . . . .
4 Gy1 12.6 7.9 6.2 . . . . . . .
5 Gy2 10.6 8.4 8.4 5.2 . . . . . .
6 Green 10.6 9.4 9.9 6.5 4.1 . . . . .
7 Blue 10.8 10.2 10.3 8.8 7.0 6.4 . . . .
8 BlP 7.3 11.3 12.7 11.2 10.4 9.9 4.2 . . .
9 Pur1 5.4 11.5 12.9 11.7 10.8 9.4 8.4 4.5 . .
10 Pur2 5.0 11.5 10.7 10.2 10.6 10.1 8.1 6.4 3 .
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
Phil Spector
2011-Mar-22 16:47 UTC
[R] how to convert a data.frame to a list of dist objects for individual differences MDS?
Michael -
I think this does what you want:
helm.raw <-
read.table("http://euclid.psych.yorku.ca/datavis/Private/mdshelm.dat",header=TRUE,
row.names=1)
trans =
c('A'='RPur','C'='Red','E'='Yel','G'='Gy1','I'='Gy2','K'='Green','M'='Blue','O'='BlP','Q'='Pur1','S'='Pur2')
cnames = do.call(rbind,strsplit(rownames(helm.raw), ""))
cnames = apply(cnames,2,function(x)trans[x])
uu = unique(as.vector(cnames))
onecol = function(col){
themat = matrix(NA,10,10)
dimnames(themat) = list(uu,uu)
themat[cnames] = col
as.dist(t(themat))
}
result = lapply(as.data.frame(helm.raw),onecol)
> result$CD1
RPur Red Yel Gy1 Gy2 Green Blue BlP Pur1
Red 11.5
Yel 13.1 6.0
Gy1 12.6 7.9 6.2
Gy2 10.6 8.4 8.4 5.2
Green 10.6 9.4 9.9 6.5 4.1
Blue 10.8 10.2 10.3 8.8 7.0 6.4
BlP 7.3 11.3 12.7 11.2 10.4 9.9 4.2
Pur1 5.4 11.5 12.9 11.7 10.8 9.4 8.4 4.5
Pur2 5.0 11.5 10.7 10.2 10.6 10.1 8.1 6.4 3.0
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spector at stat.berkeley.edu
On Tue, 22 Mar 2011, Michael Friendly wrote:
> I have a 45 x 16 data frame consisting of dissimilarities among 10 colors,
> giving in each
> column the 45 = 10*9/2 pairwise judgments for one of 16 subjects. The
> rownames
> identify each pair of colors, e.g, "AC" =
("A","C"), and the pairs are
> ordered by columns
> in the lower triangle of each distance matrix.
>
>> helm.raw <-
>
read.table("http://euclid.psych.yorku.ca/datavis/Private/mdshelm.dat",
> header=TRUE, row.names=1)
>> head(helm.raw)
> N1 N2 N3 N4 N5 N6a N6b N7 N8 N9 N10 CD1 CD2a CD2b CD3
> CD4
> AC 6.8 5.9 7.1 7.5 6.6 5.2 5.8 6.2 7.5 6.0 9.2 11.5 9.3 9.0
10.4
> 9.9
> AE 12.5 11.1 10.2 10.3 10.5 9.4 10.5 10.8 9.1 9.4 10.8 13.1 10.7 10.0
12.4
> 13.2
> AG 13.8 18.8 11.1 10.7 10.2 11.4 13.4 9.9 10.2 9.5 9.7 12.6 10.7 10.4
12.8
> 12.3
> AI 14.2 17.3 12.5 11.6 9.6 13.3 14.0 11.1 12.1 9.5 10.1 10.6 11.9 10.0
13.7
> 11.1
> AK 12.5 16.6 11.8 10.6 10.8 12.0 13.2 10.3 12.5 9.8 10.3 10.6 11.0 9.3
11.8
> 8.7
> AM 11.0 16.5 9.9 9.7 9.7 12.3 11.7 8.8 9.7 8.7 9.7 10.8 9.8 8.6
4.3
> 5.6
>> row.names(helm.raw)
> [1] "AC" "AE" "AG" "AI"
"AK" "AM" "AO" "AQ" "AS"
"CE" "CG" "CI" "CK" "CM"
> "CO" "CQ" "CS" "EG" "EI"
"EK"
> [21] "EM" "EO" "EQ" "ES"
"GI" "GK" "GM" "GO" "GQ"
"GS" "IK" "IM" "IO" "IQ"
> "IS" "KM" "KO" "KQ" "KS"
"MO"
> [41] "MQ" "MS" "OQ" "OS"
"QS"
>>
>
> To analyse this (with individual differences MDS, e.g., smacofDiff()), I
need
> to:
>
> (a) convert this to a list of objects of class "dist", one for
each column of
> helm.raw
> (b) rename the 1-letter codes to color name abbreviations as row/col labels
> for each distance matrix,
> according to:
> 'A'='RPur'
> 'C'='Red'
> 'E'='Yel'
> 'G'='Gy1'
> 'I'='Gy2'
> 'K'='Green'
> 'M'='Blue'
> 'O'='BlP'
> 'Q'='Pur1'
> 'S'='Pur2'
>
> I've done this in SAS, but I don't know how to do it in R because
neither
> dist() nor
> as.dist() seem to be able to work with data in this format. I could try
> brute-force,
> but maybe there is an easier way. Can someone help?
>
> As a distance matrix, the column helm.raw$CD1 for subject CD1 should appear
> something like
> shown below (without the Obs column, where stim is the rowname)
>
> --------------------------------- Subject=CD1
> ----------------------------------
>
> Obs stim RPur Red Yel Gy1 Gy2 Green Blue BlP Pur1 Pur2
>
> 1 RPur . . . . . . . . . .
> 2 Red 11.5 . . . . . . . . .
> 3 Yel 13.1 6.0 . . . . . . . .
> 4 Gy1 12.6 7.9 6.2 . . . . . . .
> 5 Gy2 10.6 8.4 8.4 5.2 . . . . . .
> 6 Green 10.6 9.4 9.9 6.5 4.1 . . . . .
> 7 Blue 10.8 10.2 10.3 8.8 7.0 6.4 . . . .
> 8 BlP 7.3 11.3 12.7 11.2 10.4 9.9 4.2 . . .
> 9 Pur1 5.4 11.5 12.9 11.7 10.8 9.4 8.4 4.5 . .
> 10 Pur2 5.0 11.5 10.7 10.2 10.6 10.1 8.1 6.4 3 .
>
>
> --
> Michael Friendly Email: friendly AT yorku DOT ca
> Professor, Psychology Dept.
> York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
> 4700 Keele Street Web: http://www.datavis.ca
> Toronto, ONT M3J 1P3 CANADA
>
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