v <- dput(x,"sampledata.txt")
dim(v)
q <- v[1:10,1:10]
f =as.matrix(dist(t(q)))
distB=NULL
for(k in 1:(nrow(f)-1)) for( m in (k+1):ncol(f)) {
if(f[k,m] <2) distB=rbind(distB,c(k,m,f[k,m]))
}
#now distB looks like this
> distB
[,1] [,2] [,3]
[1,] 1 2 1.6275568
[2,] 1 3 0.5252058
[3,] 1 4 0.7323116
[4,] 1 5 1 .9966001
[5,] 1 6 1.6664110
[6,] 1 7 1.0800540
[7,] 1 8 1.8698925
[8,] 1 10 0.5161808
[9,] 2 3 1.7325811
[10,] 2 5 0.8267843
[11,] 2 6 0.5963280
[12,] 2 7 0.8787230
#now from this output< i want to cluster all 1's, friedns of 1 and friends
of friends of 1 in one cluster. The same goes for 2,3 and so on
But when i do that using hclust, i get the following error. I think what I
need to do is convert my cureent matrix somehow into a format that would be
accepted by the hclust function but I dont know how to achieve that.
distclust <- hclust(distB,method="single")
Error in if (n < 2) stop("must have n >= 2 objects to cluster") :
argument is of length zero
P.S: Please let me know if this makes things more clear? "cuz i dont know
how looking at the original data set would help becuase the matrix under
consdieration right now is the distance matrix and how it can be altered. I
have tried as.dist, doesnt work because my matrix as i mentioned eralier is
not a square matrix.
On Fri, May 28, 2010 at 2:37 PM, Tal Galili <[email protected]> wrote:
> Hi Ayesha,
> I wish to help you, but without a simple self contained example that shows
> your issue, I will not be able to help.
> Try using the ?dput command to create some simple data, and let us see what
> you are doing.
>
> Best,
> Tal
> ----------------Contact
> Details:-------------------------------------------------------
> Contact me: [email protected] | 972-52-7275845
> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
> www.r-statistics.com (English)
>
> ----------------------------------------------------------------------------------------------
>
>
>
>
> On Fri, May 28, 2010 at 9:04 PM, Ayesha Khan <
> [email protected]> wrote:
>
>> Thanks Tal & Joris!
>> I created my distance matrix distA by using the dist() function in R
>> manipulating my output in order to get a matrix.
>> distA =as.matrix(dist(t(x2))) # x2 being my original dataset
>> as according to the documentaion on dist()
>>
>> For the default method, a "dist" object, or a matrix (of distances) or an
>> object which can be coerced to such a matrix using as.matrix()
>>
>> On Fri, May 28, 2010 at 6:34 AM, Joris Meys <[email protected]>wrote:
>>
>>> As Tal said.
>>>
>>> Next to that, I read that column1 (and column2?) are supposed to be seen
>>> as factors, not as numerical variables. Did you take that into account
>>> somehow?
>>>
>>> It's easy to reproduce the error code :
>>> > n <- NULL
>>> > if(n<2)print("This is OK")
>>> Error in if (n < 2) print("This is OK") : argument is of length zero
>>>
>>> In the hclust code, you find following line :
>>> n <- as.integer(attr(d, "Size"))
>>> where d is the distance object entered in the hclust function. Looking at
>>> the error you get, this means that the size attribute of your distance is
>>> NULL. Which tells me that distA is not a dist-object.
>>>
>>> > A <- matrix(1:4,ncol=2)
>>> > A
>>> [,1] [,2]
>>> [1,] 1 3
>>> [2,] 2 4
>>> > hclust(A,method="single")
>>>
>>> Error in if (n < 2) stop("must have n >= 2 objects to cluster") :
>>> argument is of length zero
>>>
>>> Did you actually put in a distance object? see also ?dist or ?as.dist.
>>>
>>> Cheers
>>> Joris
>>>
>>>
>>>
>>>
>>> On Fri, May 28, 2010 at 1:41 AM, Ayesha Khan <
>>> [email protected]> wrote:
>>>
>>>> i have a matrix with the following dimensions
>>>> 136 3
>>>>
>>>> and it looks something like
>>>>
>>>> [,1] [,2] [,3]
>>>> [1,] 402 675 1.802758
>>>> [2,] 402 696 1.938902
>>>> [3,] 402 699 1.994253
>>>> [4,] 402 945 1.898619
>>>> [5,] 424 470 1.812857
>>>> [6,] 424 905 1.816345
>>>> [7,] 470 905 1.871252
>>>> [8,] 504 780 1.958191
>>>> [9,] 504 848 1.997111...............
>>>>
>>>> ................................................................................
>>>> so you get the idea. I want to group similar items in one group/cluster
>>>> following the "friends of friends" approach. I tried doing
>>>>
>>>> distclust <- hclust(distA,method="single")
>>>> However, I got the following error.
>>>>
>>>> Error in if (n < 2) stop("must have n >= 2 objects to cluster") :
>>>> argument
>>>> is of length zero
>>>> which probably means there's something wrong with my input here. Is
>>>> there
>>>> another way of doing this kind of clustering without getting into all
>>>> the
>>>> looping and ifelse etc. Basically, if 402 is close to 675,696,and699
>>>> and
>>>> thus fall in cluster A then all items close to 675,696,and 699 should
>>>> also
>>>> fall into the same cluster A following a friends of friedns strategy.
>>>> Any help would be highly appreciated.
>>>>
>>>> --
>>>> Ayesha Khan
>>>>
>>>> MS Bioengineering
>>>> Dept. of Bioengineering
>>>> Rice University, TX
>>>>
>>>> [[alternative HTML version deleted]]
>>>>
>>>> ______________________________________________
>>>> [email protected] mailing list
>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>> PLEASE do read the posting guide
>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>
>>>
>>>
>>>
>>> --
>>> Joris Meys
>>> Statistical Consultant
>>>
>>> Ghent University
>>> Faculty of Bioscience Engineering
>>> Department of Applied mathematics, biometrics and process control
>>>
>>> Coupure Links 653
>>> B-9000 Gent
>>>
>>> tel : +32 9 264 59 87
>>> [email protected]
>>> -------------------------------
>>> Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php
>>>
>>
>>
>>
>> --
>> Ayesha Khan
>>
>> MS Bioengineering
>> Dept. of Bioengineering
>> Rice University, TX
>>
>
>
--
Ayesha Khan
MS Bioengineering
Dept. of Bioengineering
Rice University, TX
[[alternative HTML version deleted]]
______________________________________________
[email protected] 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.
