I had a vector like this :
x= c(0.542949849, 0.242292905, 0.163459552, 0.069668097, 0.042969073, 0.035829825)
and I want to plot (x[i], x[i+1]). Using Excel I got this :
How can I get this graphic in R ? I tried this :
for(i in 1:5){
plot(x[i], x[i+1])
par(new = TRUE)
}
but it doesn't give the excepted result
Here are two solutions.
The first uses base R only.
x <- c(0.542949849, 0.242292905, 0.163459552, 0.069668097, 0.042969073, 0.035829825)
plot(range(x), range(x), type = "n")
for(i in seq_along(x)[-length(x)]){
points(x[i], x[i+1])
}
The second uses package tsDyn.
tsDyn::autopairs(x, type = "points")
Try this:
plot(embed(rev(x), 2))
or
plot(embed(x, 2)[, 2:1])
You can get what you want but you have to add a few intermediate steps.
You need to put in a qualifier to force the array to be numeric. This is the equivalent of forcing the array to be an array of float values. Otherwise all you get is integer values in your array.
You need to redefine the sub-components of x to 2 new vectors. Vector 'a' has an index of elements from 1 to 5 of the x array. It appears on the x-axis. Vector 'b' has an index of elements from 2 to 6 of the x array. It appears on the y-axis. The first elements in vectors a and b index position 1 are equivalent to x[i],x[i+1] where i is 1.
You need to bind the 2 vectors together and then plot the result.
x <- as.numeric(c(0.542949849, 0.242292905, 0.163459552, 0.069668097, 0.042969073, 0.035829825))
a <- x[1:5]
b <- x[2:6]
c <- cbind(a,b)
plot(c)
and the result graph is as follows
Related
A <- list(X = c(Z = 15))
How do I access 15 in the above example
We can try using a combination of list access syntax along with vector access syntax:
A <- list(X = c(Z = 15))
A$X["Z"]
Z
15
Above A$X refers to the element in the list named X, which happens to be a vector. Then, A$X["Z"] accesses the element in the vector named Z, which is the value 15.
Can also access it with indices:
A[[c(1, 1)]]
You can simply do:
A[[1]]
This gets the first "component" of the list.
A[[1]]
Z
15
Or if you want to go step by step, then:
A[1][[1]]
Z
15
I am using Jenks Natural Breaks via the BAMMtools package to segment my data in RStudio Version 1.0.153. The output is a vector that shows where the natural breaks occur in my data set, as such:
[1] 14999 41689 58415 79454 110184 200746
I would like to take the output above and create the ranges inferred by the breaks. Ex: 14999-41689, 41690-58415, 58416-79454, 79455-110184, 110185-200746
Are there any functions that I can use in R Studio to accomplish this? Thank you in advance!
Input data
x <- c(14999, 41689, 58415, 79454, 110184, 200746)
If you want the ranges as characters you can do
y <- x; y[1] <- y[1] - 1 # First range given in question doesn't follow the pattern. Adjusting for that
paste(head(y, -1) + 1, tail(y, -1), sep = '-')
#[1] "14999-41689" "41690-58415" "58416-79454" "79455-110184" "110185-200746"
If you want a list of the actual sets of numbers in each range you can do
seqs <- Map(seq, head(y, -1) + 1, tail(y, -1))
You can definitely create your own function that produces the exact output you're looking for, but you can use the cut function that will give you something like this:
# example vector
x = c(14999, 41689, 58415, 79454, 110184, 200746)
# use the vector and its values as breaks
ranges = cut(x, x, dig.lab = 6)
# see the levels
levels(ranges)
#[1] "(14999,41689]" "(41689,58415]" "(58415,79454]" "(79454,110184]" "(110184,200746]"
Given a list of 16 elements, where each element is a named numeric vector, I want to plot the length of the intersection of names between every 2 elements. That is; the intersection of element 1 with element 2, that of element 3 with element 4, etc.
Although I can do this in a very tedious, low-throughput manner, I'll have to repeat this sort of analysis, so I'd like a more programmatic way of doing it.
As an example, the first 5 entries of the first 2 list elements are:
topGenes[[1]][1:5]
3398 284353 219293 7450 54658
2.856363 2.654106 2.653845 2.635599 2.626518
topGenes[[2]][1:5]
1300 64581 2566 5026 146433
2.932803 2.807381 2.790484 2.739735 2.705030
Here, the first row of numbers are gene IDs & I want to know how many each pair of vectors (a treatment replicate) have in common, among, say, the top 100.
I've tried using lapply() in the following manner:
vectorOfIntersectLengths <- lapply(topGenes, function(x) lapply(topGenes, function(y) length(intersect(names(x)[1:100],names(y)[1:100]))))
This only seems to operate on the first two elements; topGenes[[1]] & topGenes[[2]].
I've also been trying to do this with a for() loop, but I'm unsure how to write this. Something along the lines of this:
lengths <- c()
for(i in 1:length(topGenes)){
lens[i] <- length(intersect(names(topGenes[[i]][1:200]),
names(topGenes[[i+1]][1:200])))
}
This returns a 'subscript out of bounds' error, which I don't really understand.
Thanks a lot for any help!
Is this what you're looking for?
# make some fake data
set.seed(123)
some_list <- lapply(1:16, function(x) {
y <- rexp(100)
names(y) <- sample.int(1000,100)
y
})
# identify all possible pairs
pairs <- t( combn(length(some_list), 2) )
# note: you could also use: pairs <- expand.grid(1:length(some_list),1:length(some_list))
# but in addition to a-to-b, you'd get b-to-a, a-to-a, and b-to-b
# get the intersection of names of a pair of elements with given indices kept for bookkeeping
get_intersection <- function(a,b) {
list(a = a, b = b,
intersection = intersect( names(some_list[[a]]), names(some_list[[b]]) )
)
}
# get intersection for each pair
intersections <- mapply(get_intersection, a = pairs[,1], b = pairs[,2], SIMPLIFY=FALSE)
# print the intersections
for(indx in 1:length(intersections)){
writeLines(paste('Intersection of', intersections[[indx]]$a, 'and',
intersections[[indx]]$b, 'contains:',
paste( sort(intersections[[indx]]$intersection), collapse=', ') ) )
}
I have a set of vectors of length n, say, for example that n=3:
vec1<-c(1,2,3)
vec2<-c(2,2,2)
And a multidimensional array of size n^n:
threeDarray<-array(0,dim=c(3,3,3))
I want to create a loop that goes through my set of vectors and adds 1 to the corresponding index in the array. After analysing the two vectors above the array should be like:
threeDarray[1,2,3]=1
threeDarray[2,2,2]=1
I'm trying to use the multidimensional array to store the number of occurrences of each vector (my vectors are patterns in a time series).
The community is right (and the noob is wrong). Multidimensional arrays are not the way to go about this.
An example of code working with lists:
freqPatterns<-function(timeSeries,dimension){
temp<-character()
for (i in 1:(length(timeSeries)-dimension+1)){
pattern<-paste(as.character(rank(timeSeries[i:(i+dimension-1)])-1),collapse=", ")
#print(pattern)
temp[[length(temp)+1]] <- pattern
}
freqTable=sort(table(temp),decreasing=T)
return(freqTable)
}
Thank you guys!
Like you found out yourself, I wouldn't use a multidimensioanl array neither.
Here is a solution using a dataframe:
n=4 # dimension
ll = lapply(vector("list", n), function(x) x=1:n) # build list of vectors (n * 1:n)
df_occurs = expand.grid(ll, KEEP.OUT.ATTRS=F) # get all combinations
df_occurs$occurences = 0
# for-loop for storing the occurences
for(v in list(vec1, vec2)) {
v_match = apply(df_occurs[,1:n], 1, function(x) all(x==v))
df_occurs$occurences[v_match] = 1
}
Maybe performance is an issue with large n. If it's possible to build a character-key out of your vector, eg.
paste(vec1, collapse="")
the lookup in the dataframe would be easier:
df_occurs = data.frame(
key = apply(expand.grid(ll, KEEP.OUT.ATTRS=F), 1, paste, collapse=""),
occurences = 0
)
for(key in list(vec1, vec2)) {
df_occurs$occurences[df_occurs$key==paste(key, collapse="")] = 1
}
I'm trying to plot from a rather complex array in R. I want to produce an image with 3 by 3 graphs, each with red and blue points on it.
I've got a structure of apply loops which works, but I'd like to change the y maximum value by each row.
I would normally do this using a counter, like i, in other languages. But the apply thing in R is completely baffling me!
par(mfrow=c(3,3),pty="s") # a 3 by 3 graphic
set.seed(1001)
x <- 1:54 # with 1 to 54 along the x axis
y <- array(rexp(20), dim=c(54,6,3,2)) # and the y axis coming
# from an array with dimensions as shown.
ymax <- c(1,0.1,0.3) # three different y maximum values I want
# on the graphic, one for each row of graphs
counter <- 1 # a counter, starting at 1,
# as I would use in a traditional loop
apply(y[,3:5,,], 2, function(i) # my first apply, which only considers
# the 3rd, 4th and 5th columns
{
yy <- ymax[counter] # using the counter to select my ylimit maximum
apply(i, 2, function (ii) # my second apply, considering the 3rd
# dimension of y
{
plot(x,ii[,1], col="blue", ylim=c(0,yy))
# plotting the 4th dimension
points(x,ii[,2], col="red")
# adding points in a different
# colour from the 4th dim.
})
})
Thank you in advance for your thoughts, they are very much appreciated!
Cheers
Kate
I think it might be easier to use loops in this case.
Also, your code does not have a line to update the counter, like counter <- counter + 1. From inside apply you will need to assign to the global environment using <<-, note the doubled smaller < sign. An example using lapply, e.g.
Single lapply usage
counter <- 0
lapply(1:3, function(x) {
counter <<- counter + 1
cat("outer", counter, "\n")
plot(1:10, main=counter)
})
Or nested usage of lapply
counter <- 0
lapply(1:3, function(x) {
counter <<- counter + 1
cat("outer", counter, "\n")
lapply(1:3, function(x) {
counter <<- counter + 1
cat("inner", counter, "\n")
plot(1:10, main=counter)
})
})
The key thing here is to use lapply on the index rather than on the array itself, so then you can use the index to subset both your y limits and the array ahead of the inner loop. This also avoids having to use the <<- construct.
Simplified your data a bit:
par(mfrow=c(3,3),pty="s") # a 3 by 3 graphic
set.seed(1001)
x <- 1:10 # with 1 to 54 along the x axis
dims <- c(10,6,3,2)
y <- array(rexp(prod(dims)), dim=c(10,6,3,2)) # and the y axis coming
ymax <- c(1,0.1,0.3)
lapply(1:3, function(counter, arr) {
apply(
arr[ ,counter + 2, , ], 2,
function(ii) {
plot(x, ii[,1], col="blue", ylim=c(0,ymax[counter]))
points(x, ii[,2], col="red")
} )
},
arr=y
)
I am not going to rewrite your code as I must say it is difficult to comprehend, but this will help: you can update a variable outside of the scope of apply by using <<- assignment, e.g. to update some external "counter"