dear deepayan & all...
let me explain you my full problem clearly..so that you could clearly suggest
me in right direction....
my matrix (a) looks like as below...I´ve done clusutering in this matrix
----------------------------------------------------------------
a<-matrix(c(seq(3,45,3),seq(10,6,-1)),4,5,byrow=F)
col<-c("ra","rb","rc","rd","re")
rows<-c("ca","cb","cc","cd")
dimnames(a)<-list(rows,col)
a
ra rb rc rd re
ca 3 15 27 39 9
cb 6 18 30 42 8
cc 9 21 33 45 7
cd 12 24 36 10 6
-----------------------------------------------------------
clustering based on row and columns..suppose after clustering my row & col
clustes looks like this..
row cluster 1: ra,rb
2: rc,rd
3:re
column cluster 1: ca,cb
2: cc,cd
So my clustered matrix (should) looks like
ROWS
1 2 3
I ra rb I rc rd I
re
----------------I------------------I----------------------I------------------
ca I 3 15 I 27 39 I 9
1 I I I
cb I 6 18 I 30 42 I 8
I I I
COLUMNS---------------I-----------------------------------------I-----------------
cc I 9 21 I 33 45 I 7
2 I I I
cd I 12 24 I 36 10 I 6
----------------I-----------------I-----------------------I--------------------
The above is the output matrix..It has to be plotted in graphs showing the
partitions clearly as it is shown in the above matrix...
.
what kind of approach will be useful in gettign this..?particularly in
colored graphs...
thanks a lot...
yours sincerely,
eric.
Deepayan Sarkar <[EMAIL PROTECTED]> wrote:
On 11/21/05, peter eric wrote:
>
> Really your (Mr.deepayan´s)answer is what I expected..thanks a lot...and I
> like to ask you one more thing..
> Is it possible to do boolean operations in this matrix and plot that also
> in graphs?
>
> for example
> 1. a[anja,maya] Vs a[vincent,selva]
> means things common between the rows anja&maya and columns vincent &
> selva
You mean
levelplot(a[c("anja", "maya"), c("vincent", "selva")])
? This is standard matrix indexing in R.
> 2.a[anja,maya] Vs a[peter,david]
> and so on...
>
> So in that case whether it is possible to plot in the same graph(since I´m
> doing different...more than one.. comparisions) or I´ve to plot in a
> multiple graph..
It depends on what you want to do. If the different comparisons are
based on some systematic rule then levelplot may take you further.
[Note that for this you may need to work with a data.frame instead of
a matrix. E.g.,
mat2df <- function(x) {
rx <- row(x)
cx <- col(x)
data.frame(row = rownames(x)[rx],
column = colnames(x)[cx],
z = as.vector(x))
}
b <- mat2df(a)
b is now a data frame:
> b
row column z
1 julius peter 3
2 caeser peter 6
3 anja peter 9
...
]
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