I found this while searching for a similar approach.
Selecting rows with same result in different columns in R
Is there a way to search within a range of columns? Playing off the example in the link, what if instead of catch[catch$tspp.name == catch$elasmo.name,], is it possible to do this?
catch[catch$tspp.name == c[23:56],] where R would search for values within columns 23 to 56 that match the tspp value?
Thanks in advance and please let me know whether it's better to post an independent question on a topic related to a previous post or to insert a follow up question within the aforementioned post.
Here's one way to do it. This finds rows of X where the first column appears in columns 2 through 9.
> set.seed(1)
> X<-matrix(sample(10,100,T),10)
> X
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 3 10 5 9 5 10 4 5 3
[2,] 4 2 3 6 7 9 3 9 8 1
[3,] 6 7 7 5 8 5 5 4 4 7
[4,] 10 4 2 2 6 3 4 4 4 9
[5,] 3 8 3 9 6 1 7 5 8 8
[6,] 9 5 4 7 8 1 3 9 3 8
[7,] 10 8 1 8 1 4 5 9 8 5
[8,] 7 10 4 2 5 6 8 4 2 5
[9,] 7 4 9 8 8 7 1 8 3 9
[10,] 1 8 4 5 7 5 9 10 2 7
> X[rowSums(X[,1]==X[,2:9])>0,]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 3 10 5 9 5 10 4 5 3
[2,] 3 8 3 9 6 1 7 5 8 8
[3,] 9 5 4 7 8 1 3 9 3 8
[4,] 7 4 9 8 8 7 1 8 3 9
Related
This is what I know in Matlab and want do same in r programming
A=[1 2 3;4 5 6; 7 8 9];
A =
1 2 3
4 5 6
7 8 9
[m,n]=size(A)
m=3
n=3
so here I have two distinct variables to which the dimension or size of 2D matrix is assigned automatically
> x<-c(1:10)
> x
[1] 1 2 3 4 5 6 7 8 9 10
> A=matrix(0,10,10)
> A=Toeplitz(x,c(x[1],rev(x[-1])))
> A
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 10 9 8 7 6 5 4 3 2
[2,] 2 1 10 9 8 7 6 5 4 3
[3,] 3 2 1 10 9 8 7 6 5 4
[4,] 4 3 2 1 10 9 8 7 6 5
[5,] 5 4 3 2 1 10 9 8 7 6
[6,] 6 5 4 3 2 1 10 9 8 7
[7,] 7 6 5 4 3 2 1 10 9 8
[8,] 8 7 6 5 4 3 2 1 10 9
[9,] 9 8 7 6 5 4 3 2 1 10
[10,] 10 9 8 7 6 5 4 3 2 1
> n=size(A)
> n
[1] 10 10
>[ m,n]=size(A)
this is not working so is there any way to assign the size of the 2Dmatrix to two distinct variable m and n in r.I am learning r programming and need help
The command
matrix(sample.int(12, 9*12, TRUE), 9, 12)
generates an integer random matrix (9 rows and 12 columns) with integer values from 1 to 12. I wonder if there is a version of this code that generates a matrix whose rows are integer random rows with value from 1 to 12 (without repetition). I was able to find a "trivial" answer to this question; with
matrix(sample.int(m, 1*12), 9, 12, byrow=TRUE)
I obtain a matrix of this kind, but the rows are all equal to each other (this is the same row repeated 9 times).
The replicate function (which repeats an operation like sample(12) a specified number of times) returns a matrix whose column major orientation can be flipped to your desired row orientation with t:
t( replicate(9, {sample(12)} ) )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
[1,] 9 11 5 3 4 6 2 8 10 12 7 1
[2,] 4 5 12 6 8 2 9 1 11 10 7 3
[3,] 9 8 10 12 2 6 3 7 4 1 11 5
[4,] 4 9 1 2 6 11 8 5 7 3 12 10
[5,] 1 2 4 5 11 6 3 8 10 9 12 7
[6,] 4 8 10 12 5 9 2 7 11 1 3 6
[7,] 5 7 8 4 1 6 10 11 2 3 12 9
[8,] 2 4 10 1 12 5 7 6 11 3 8 9
[9,] 2 7 9 11 8 1 12 10 6 5 3 4
The replicate function is used in a lot of simulation code.
I'm trying to create a 6x6 matrix with the cell values equal to the sum of the row index and he col index. I can do this using loops, but I'm wondering if there is a way to do this using vector functions.
Use the outer function with "+":
outer(1:6, 1:6, "+")
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 2 3 4 5 6 7
[2,] 3 4 5 6 7 8
[3,] 4 5 6 7 8 9
[4,] 5 6 7 8 9 10
[5,] 6 7 8 9 10 11
[6,] 7 8 9 10 11 12
Incidentally, this is basically a shortcut for the following vectorized approach:
matrix(rep(1:6, 6) + rep(1:6, each = 6), nrow = 6)
Here's another possibility:
m <- matrix(NA,6,6)
m <- col(m)+row(m)
# [,1] [,2] [,3] [,4] [,5] [,6]
#[1,] 2 3 4 5 6 7
#[2,] 3 4 5 6 7 8
#[3,] 4 5 6 7 8 9
#[4,] 5 6 7 8 9 10
#[5,] 6 7 8 9 10 11
#[6,] 7 8 9 10 11 12
Is there a function in R which switches the first element with the last one in a vector? I have a for loop which need that reordering. From:
months = seq(1:12)
[1] 1 2 3 4 5 6 7 8 9 10 11 12
I would like to have:
[1] 12 1 2 3 4 5 6 7 8 9 10 11
and then again:
[1] 11 12 1 2 3 4 5 6 7 8 9 10
...
until the 12th position.
If you need a matrix output
cbind(c(months),embed(c(months, months), 12)[-13,-12])
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
# [1,] 1 12 11 10 9 8 7 6 5 4 3 2
# [2,] 2 1 12 11 10 9 8 7 6 5 4 3
# [3,] 3 2 1 12 11 10 9 8 7 6 5 4
# [4,] 4 3 2 1 12 11 10 9 8 7 6 5
# [5,] 5 4 3 2 1 12 11 10 9 8 7 6
# [6,] 6 5 4 3 2 1 12 11 10 9 8 7
# [7,] 7 6 5 4 3 2 1 12 11 10 9 8
# [8,] 8 7 6 5 4 3 2 1 12 11 10 9
# [9,] 9 8 7 6 5 4 3 2 1 12 11 10
#[10,] 10 9 8 7 6 5 4 3 2 1 12 11
#[11,] 11 10 9 8 7 6 5 4 3 2 1 12
#[12,] 12 11 10 9 8 7 6 5 4 3 2 1
Or another approached suggested by #Marat Talipov
z <- length(months)
i <- rep(seq(z),z) + rep(seq(z),each=z) - 1
matrix(months[ifelse(i>z,i-z,i)],ncol=z)
I'm afraid that you have to come up with a home-made function, something like this one:
rotate <- function(v,i=1) {
i <- i %% length(v)
if (i==0) return(v)
v[c(seq(i+1,length(v)),seq(i))]
}
Couple of examples:
v <- seq(12)
rotate(v,1)
# [1] 2 3 4 5 6 7 8 9 10 11 12 1
rotate(v,-1)
# [1] 12 1 2 3 4 5 6 7 8 9 10 11
You can also use tail and head functions:
x = c(tail(x,n), head(x,-n))
and modify n to rotate n times
The permute package can do this for you:
ap <- allPerms(length(months),
control = how(within = Within(type = "series"),
observed = TRUE))
ap[rev(seq_len(nrow(ap))), ]
(because of the way allPerms() does its work, we need to reverse the order of the rows, which is what the last line does.)
This gives:
> ap[rev(seq_len(nrow(ap))), ]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
[1,] 1 2 3 4 5 6 7 8 9 10 11 12
[2,] 12 1 2 3 4 5 6 7 8 9 10 11
[3,] 11 12 1 2 3 4 5 6 7 8 9 10
[4,] 10 11 12 1 2 3 4 5 6 7 8 9
[5,] 9 10 11 12 1 2 3 4 5 6 7 8
[6,] 8 9 10 11 12 1 2 3 4 5 6 7
[7,] 7 8 9 10 11 12 1 2 3 4 5 6
[8,] 6 7 8 9 10 11 12 1 2 3 4 5
[9,] 5 6 7 8 9 10 11 12 1 2 3 4
[10,] 4 5 6 7 8 9 10 11 12 1 2 3
[11,] 3 4 5 6 7 8 9 10 11 12 1 2
[12,] 2 3 4 5 6 7 8 9 10 11 12 1
Technically this only works because months is the vector 1:12 and allPerms() returns a permutation matrix of the indices of the thing you want permuted. For different inputs, use ap to index into the thing you want to permute
perms <- ap
perms[] <- months[ap[rev(seq_len(nrow(ap))), ]]
perms
Is there any function in R to find most frequently occuring element in matrix??I Have a matrix containing image pixels.I want to find which image pixel occur most frequently in the image matrix.I dont want to use the for loops since it would be very time taking to iterate over all the pixels of an image.
Set up some test data.
> (image = matrix(sample(1:10, 100, replace = TRUE), nrow = 10))
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 4 4 2 7 2 2 3 8 2 5
[2,] 7 3 2 6 6 5 7 8 1 3
[3,] 7 5 7 9 4 9 4 8 2 7
[4,] 5 3 4 2 1 5 9 10 9 5
[5,] 9 10 7 2 7 4 9 1 1 9
[6,] 2 3 5 1 2 8 1 5 9 4
[7,] 5 4 10 5 9 10 1 6 1 10
[8,] 6 3 9 7 1 1 9 2 1 7
[9,] 5 9 4 8 9 9 5 10 5 4
[10,] 10 1 4 7 3 2 3 5 4 5
Do it manually.
> table(image)
image
1 2 3 4 5 6 7 8 9 10
12 12 8 12 15 4 11 5 14 7
Here we can see that the value 5 appeared most often (15 times). To get the same results programmatically:
> which.max(table(image))
5
5
Get mode (or majority value) in 1 line of code
using set.seed to generate same random matrix
> set.seed(123)
> image = matrix(sample(1:10, 100, replace = TRUE), nrow = 10)
> image
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 10 9 10 2 1 7 8 3 2
[2,] 8 5 7 10 5 5 1 7 7 7
[3,] 5 7 7 7 5 8 4 8 5 4
[4,] 9 6 10 8 4 2 3 1 8 7
[5,] 10 2 7 1 2 6 9 5 2 4
[6,] 1 9 8 5 2 3 5 3 5 2
[7,] 6 3 6 8 3 2 9 4 10 8
[8,] 9 1 6 3 5 8 9 7 9 1
[9,] 6 4 3 4 3 9 8 4 9 5
[10,] 5 10 2 3 9 4 5 2 2 6)
Mode value of matrix (if tie, its gives minimum tie value)
> names(which.max(table(image)))
[1] "5"
I do not know any function to do that directly but you can use these functions:
sort(table(as.vector(Matrix))