I am sorry I did not provide enough information.
I am not using img later, but data that is data.frame.
I wrote that img is a "image" just to explain what kind of data is coming
from, but the object I am using is data and it is a data.frame (checked many
times).
I am not using as.dist, but dist in order to calculate the distance matrix
among the data I have. Then the whole code I am using is:
data <- <- as(img, "data.frame")[1:1] #(where img is an image 256x256 px)
kl <- kmeans(data, 5)
library(fpc)
ddata <- dist(data)
dcent <- dist(kl$centers)
cluster.stats(ddata, kl$cluster)
cluster.stats(dcent, kl$cluster)
In both cases I got the same error:
Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript)
logical subscript too long
Below the structure of the different objects is detailed below:
data is "'data.frame': 262144 obs. of 1 variable"
kl$centers is "num [1:5, 1]"
kl$cluster is "Named int [1:262144]"
I hope it is more informative. I am sorry but I did not find any explanation
for the error message I am getting.
Thank you very much in advance
Laura
2008/6/14 Christian Hennig <[EMAIL PROTECTED]>:
> The given information is not enough to tell you what's going on. as.dist
> doesn't appear in the given code and it's not clear to me what kind of
> object img is ("a small image" doesn't tell me what R makes of it).
> Also, try to read the help pages first and find out whether img is of the
> format that is required by the functions. And check (using str for example)
> whether "data" is what you expect it to be.
>
> Christian
>
>
> On Sat, 14 Jun 2008, Laura Poggio wrote:
>
> Thank you very much for your answer.
>> I tried to run the function on my data and now I am getting this message
>> of
>> error
>> Error in as.dist(dmat[clustering == i, clustering == i]) : (subscript)
>> logical subscript too long
>>
>> Below the code I am using (version2.7.0 of R with all packages updated):
>>
>> data <- <- as(img, "data.frame")[1:1] #(where img is a small image 256
>> px
>> x 256 px)
>> kl <- kmeans(data, 5)
>> library(fpc)
>> cluster.stats(data, kl$cluster)
>>
>> Thank you for any hints on the reasons and meaning of the error!
>>
>> Laura
>>
>>
>>
>>
>>
>> 2008/6/13 Christian Hennig <[EMAIL PROTECTED]>:
>>
>> Dear Laura,
>>>
>>> Dear list,
>>>
>>>> I just tried to use the function cluster.stat in the package fpc.
>>>> I just have a couple of questions about the syntax:
>>>>
>>>> cluster.stats(d,clustering,alt.clustering=NULL,
>>>> silhouette=TRUE,G2=FALSE,G3=FALSE)
>>>>
>>>> 1) the distance object (d) is an object obtained by the function dist()
>>>> on
>>>> my own original matrix?
>>>>
>>>>
>>> d is allowed to be an object of class dist or a dissimilarity matrix.
>>> The answer to your question depends on what your "original matrix" is. If
>>> it is something on which you can compute a distance by dist(), you're
>>> right,
>>> at least if dist() delivers the distance you are interested in.
>>>
>>> 2) clustering is the clusters vector as result of one of the many
>>>
>>>> clustering
>>>> methods?
>>>>
>>>>
>>> The help page tells you what clustering can be. So it could be the
>>> clustering/partition vector of a clustering method or it could be
>>> something
>>> else. Note that cluster.stats doesn't depend on any particular clustering
>>> method. It computes the statistics regardless of where the clustering
>>> vector
>>> comes from.
>>>
>>> Best regards,
>>> Christian
>>>
>>>
>>> Thank you very much in advance and sorry for such basic question, but I
>>>> did
>>>> not manage to clarify my mind.
>>>>
>>>> Laura
>>>>
>>>> [[alternative HTML version deleted]]
>>>>
>>>> ______________________________________________
>>>> R-help@r-project.org mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide
>>>> http://www.R-project.org/posting-guide.html
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>>
>>>> *** --- ***
>>> Christian Hennig
>>> University College London, Department of Statistical Science
>>> Gower St., London WC1E 6BT, phone +44 207 679 1698
>>> [EMAIL PROTECTED],
>>> www.homepages.ucl.ac.uk/~ucakche<http://www.homepages.ucl.ac.uk/%7Eucakche>
>>> <http://www.homepages.ucl.ac.uk/%7Eucakche>
>>>
>>>
>>
> *** --- ***
> Christian Hennig
> University College London, Department of Statistical Science
> Gower St., London WC1E 6BT, phone +44 207 679 1698
> [EMAIL PROTECTED],
> www.homepages.ucl.ac.uk/~ucakche<http://www.homepages.ucl.ac.uk/%7Eucakche>
>
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