[R] finding the minimum positive value of some data
useRs, I am looking to find the minimum positive value of some data I have. Currently, I am able to find the minimum of data after I apply some other functions to it: x [1] 1 0 1 2 3 3 4 5 5 5 6 7 8 8 9 9 10 10 sort(x) [1] 0 1 1 2 3 3 4 5 5 5 6 7 8 8 9 9 10 10 diff(sort(x)) [1] 1 0 1 1 0 1 1 0 0 1 1 1 0 1 0 1 0 min(diff(sort(x))) [1] 0 The minimum is given as zero, which is clearly true, but I am interested in only the positive minimum, which is 1. Can I find this by using only 1 line of code, like I have above? Thanks! dxc13 -- View this message in context: http://www.nabble.com/finding-the-minimum-positive-value-of-some-data-tf4417250.html#a12599319 Sent from the R help mailing list archive at Nabble.com. __ R-help@stat.math.ethz.ch 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.
[R] using temporary arrays in R
useR's, Is there a way to create a temporary array (or matrix) in R to hold values, then drop or delete that temporary array from memory once I do not need it anymore? I am working with multidimensional arrays/matrices and I frequently perform multiple operations on the same matrix and rename it to be another object. I want to be able to delete the older versions of the array/matrix to free up space. Thank you. -- View this message in context: http://www.nabble.com/using-temporary-arrays-in-R-tf4372367.html#a12462219 Sent from the R help mailing list archive at Nabble.com. __ R-help@stat.math.ethz.ch 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.
[R] memory.size help
I keep getting the 'memory.size' error message when I run a program I have
been writing. It always it cannot allocate a vector of a certain size. I
believe the error comes in the code fragement below where I have multiple
arrays that could be taking up space. Does anyone know a good way around
this?
w1 - outer(xk$xk1, data[,x1], function(y,z) abs(z-y))
w2 - outer(xk$xk2, data[,x2], function(y,z) abs(z-y))
w1[w1 d1] - NA
w2[w2 d2] - NA
i1 - ifelse(!is.na(w1),yvals[col(w1)],NA)
i2 - ifelse(!is.na(w2),yvals[col(w2)],NA)
zk - numeric(nrow(xk)) #DEFININING AN EMPTY VECTOR TO HOLD ZK VALUES
for(x in 1:nrow(xk)) {
k - intersect(i1[x,], i2[x,])
zk[x] - mean(unlist(k), na.rm = TRUE)
}
xk$zk - zk
data - na.omit(xk)
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Re: [R] memory.size help
I have 512 MB RAM with a 1.5 GHz processor. The dataset I am working with
increases with size with every iteration of the function that I am writing.
R can handle the input data which is about 10,000 records, and a single
iteration with 19,500 observations. After this, I get the memory.size()
error message.
I have only written 1 other R function so I am not too familiar with
optimizing code. Do you have any suggestions?
Andris Jankevics wrote:
You havn't said anithing about your OS and version. But basicly I means,
that
you don't have enoigh RAM or swap memory aviable on your system. How large
dataset you have?
1. You can optimise your code. :)
or
2. You can just add more RAM to your system, or you can add more swap
space on
your HDD. Work with data in swap will be really slow.
In linux OS you can add additional swap space, by these commmands:
2 GB file:
dd if=/dev/zero of=/swapfile1 bs=1024 count=2097152
mkswap /swapfile1
swapon /swapfile1
On Friday 31 August 2007 15:27:58 dxc13 wrote:
w1 - outer(xk$xk1, data[,x1], function(y,z) abs(z-y))
w2 - outer(xk$xk2, data[,x2], function(y,z) abs(z-y))
w1[w1 d1] - NA
w2[w2 d2] - NA
i1 - ifelse(!is.na(w1),yvals[col(w1)],NA)
i2 - ifelse(!is.na(w2),yvals[col(w2)],NA)
zk - numeric(nrow(xk)) #DEFININING AN EMPTY VECTOR TO HOLD ZK
VALUES
for(x in 1:nrow(xk)) {
k - intersect(i1[x,], i2[x,])
zk[x] - mean(unlist(k), na.rm = TRUE)
}
xk$zk - zk
data - na.omit(xk)
--
Andris Jankevics
Assistant
Department of Medicinal Chemistry
Latvian Institute of Organic Synthesis
Aizkraukles 21, LV-1006, Riga, Latvia
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[R] a faster and shorter way to perform calculations?
This is a continuation from a previous posting of mine: The following algorithm below is what I want to accomplish: Z(xk) = Average(Yi, i belongs to Ik), where Ik contains all i such that for each j, |Xi,j - xkj│≤ 2. Here, j = 1, 2 and i corresponds to the elements in each X and/or xk data x1 x2 y 11 2 22 6 33 12 Now, consider a second data frame or matrix (xk): xk1 xk2 0.50.5 1.00.5 1.50.5 2.00.5 0.51 1.01 1.51 2.01 0.51.5 1.01.5 1.51.5 2.01.5 0.52 1.02 1.52 2.02 In the end, there should be matrix or data frame with 3 columns, xk1, xk2, and z (the result of the algorithm). Having any NA's as an answer is just fine. Here is my code to get this to get this to work, it is lengthy and I am looking for a way to cut it down and get the same results. w1 - outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 - outer(xk$xk2, data[,x2], function(y,z) abs(z-y)) w1[w1 d1] - NA w2[w2 d2] - NA i1 - ifelse(!is.na(w1),col(w1),NA) i2 - ifelse(!is.na(w2),col(w2),NA) #NOW COMPARE i1 AND i2 BY ROWS...IF THEY HAVE A VALID NUMBER IN #THE SAME POSITION (RxC) THEN EXTRACT THE Z-VALUE CORRESPONDING #TO THE COLUMN NUMBER all - cbind(i1,i2) Ik - lapply(as.data.frame(t(all)), function(x) data$y[unique(x[duplicated(x)])]) zk - unlist(lapply(Ik, mean, na.rm = TRUE)) z - cbind(zk) #FINAL DATA FRAME WILL CONSIST OF xk (XK1 and XK2), ZK xk$z - z df - as.data.frame(sapply(xk,rbind)) I hope my question makes sense and someone can help find a way to reduce the amount of code here. I have attached a text file with better numbers to try this with. Thank you, dxc13 http://www.nabble.com/file/p12387673/test.txt test.txt -- View this message in context: http://www.nabble.com/a-faster-and-shorter-way-to-perform-calculations--tf4347973.html#a12387673 Sent from the R help mailing list archive at Nabble.com. __ R-help@stat.math.ethz.ch 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.
[R] alternate methods to perform a calculation
Consider a data frame (x) with 2 variables, x1 and x2, having equal values.
It looks like:
x1 x2
11
22
33
Now, consider a second data frame (xk):
xk1 xk2
0.50.5
1.00.5
1.50.5
2.00.5
0.51
1.01
1.51
2.01
0.51.5
1.01.5
1.51.5
2.01.5
0.52
1.02
1.52
2.02
I have written code to calculate some differences between these two data
sets; the main idea is to subtract off each element of xk1 from each value
of x1, and similarly for xk2 and x2. This is what I have:
w1 - array(NA,dim=c(nrow(xk),length(x$x1)))
w2 - array(NA,dim=c(nrow(xk),length(x$x2)))
for (j in 1:nrow(xk)) {
w1[j,] - abs(x$x1-xk$xk1[j])
w2[j,] - abs(x$x2-xk$xk2[j])
}
Is there a way to do the above calculation without use of a FOR loop?
Thank you
Derek
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[R] extracting duplicated elements
Can anyone help me solve this problem...thanks! Consider a data frame, namely v, as such: v X1 X2 X3 X4 X5 X1 X2 X3 X4 X5 x1 1 2 -1 -1 -1 1 2 -1 -1 -1 y1 1 2 -1 -1 -1 1 2 3 -1 -1 What I would like to do is to create an array or data frame with only the elements that appear in the data frame more than once and are = 0. I try this... v[v=0] [1] 1 1 2 2 1 1 2 2 3 which returns all = 0 elements, but they are not in their respective rows from the original data frame. I have tried using the duplicated() function and can't seem to get it to work correctly. Essentially, the outcome I am trying to get is a df or array looking like: step 1...achieve this out of original df [1] 1 2 1 2 [2] 1 2 1 2 3 (the blank element in row 1, position 5 can be just be NA) step 2...take the above and get this...only the duplicated elements [1] 1 2 [2] 1 2 -- View this message in context: http://www.nabble.com/extracting-duplicated-elements-tf4318034.html#a12295213 Sent from the R help mailing list archive at Nabble.com. __ R-help@stat.math.ethz.ch 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.
