I want to create a vector, but to do that I have to use information of another vector. I guess it's necessary to use a loop, but I don't know.
I have the vector
n <- c(2, 4, 2, 4, 4, 2, 3, 4, 2, 3, 5, 10, 2, 5)
and I have to create
rbeta(N-12,i+1,N-i+1)
where i is the ith element of n.
If N is a scalar value then you can use the fact that R is vectorized to get your result with
rbeta(N - 12, n + 1, N - n + 1)
For example:
n <- c(2, 4, 2, 4, 4, 2, 3, 4, 2, 3, 5, 10, 2, 5)
N <- 20
rbeta(N - 12, n + 1, N - n + 1)
#> [1] 0.06464326 0.41683835 0.14648202 0.22730181 0.21056577 0.17171969
#> [7] 0.28686094 0.14333501
Related
I have to do the following:
I have a vector, let as say
x <- c(1, 1, 2, 3, 3, 3, 4, 4, 5, 5, 3, 2, 11, 1, 3, 3, 4, 1)
I have to subset the remainder of a vector after 1, 2, 3, 4 occurred at least once.
So the subset new vector would only include 4, 5, 5, 3, 2, 11, 1, 3, 3, 4, 1.
I need a relatively easy solution on how to do this. It might be possible to do an if and while loop with breaks, but I am kinda struggling to come up with a solution.
Is there a simple (even mathematical way) to do this in R?
Use sapply to find where each predefined number occurs first time.
x[-seq(max(sapply(1:4, function(y) which(x == y)[1])))]
# [1] 4 5 5 3 2 11 1 3 3 4 1
Data
x <- c(1, 1, 2, 3, 3, 3, 4, 4, 5, 5, 3, 2, 11, 1, 3, 3, 4, 1)
You can use run length encoding for this
x = c(1, 1, 2, 3, 3, 3, 4, 4, 5, 5, 3, 2, 11, 1, 3, 3, 4, 1)
encoded = rle(x)
# Pick the first location of 1, 2, 3, and 4
# Then find the max index location
indices = c(which(encoded$values == 1)[1],
which(encoded$values == 2)[1],
which(encoded$values == 3)[1],
which(encoded$values == 4)[1])
index = max(indices)
# Find the index of x corresponding to your split location
reqd_index = cumsum(encoded$lengths)[index-1] + 2
# Print final split value
x[reqd_index:length(x)]
The result is as follows
> x[reqd_index:length(x)]
[1] 4 5 5 3 2 11 1 3 3 4 1
I was trying some operations on the List object and wanted to see some "broadcast" behavior :
x = [-1, 1, 2, 3, 4, 5, 6, 7, 8, 9]
x = -1*x
In [46]: x
Out[46]: []
I was expecting something like x = [1, -1, -2, -3, -4, -5, -6, -7, -8, -9].
What is actually happening?
You can only this kind of multiplication with a pandas Series (or better the underlaying numpy array). If you write something like
List = n * List
with n as an integer your list gets resized by n:
x = [-1, 1, 2, 3, 4, 5, 6, 7, 8, 9]
x = 3*x
print(x)
>> [-1, 1, 2, 3, 4, 5, 6, 7, 8, 9, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9, -1, 1, 2, 3, 4, 5, 6, 7, 8, 9]
And negative numbers will remove your list entries (treated as 0 - see here).
Values of n less than 0 are treated as 0 (which yields an empty
sequence of the same type as s).
So you have to use one of these methods to multiply each list element:
NewList = [i * 5 for i in List]
for i in List:
NewList.append(i * 5)
import pandas as pd
s = pd.Series(List)
NewList = (s * 5).tolist()
You want the following:
x = [-1 * i for i in x]
I have two matrixes:
I would like to count the distance between point X and point Y without using a loop and in the way that when the matrix is expanded by additional columns the expression/function works.
For validation one could use:
sqrt((m1[,1] - m2[,1])^2 + (m1[,2] - m2[,2])^2 + (m1[,3] - m2[,3])^2 + (m1[,4] - m2[,4])^2 + (m1[,5] - m2[,5])^2)
The expression above gives the correct result for the distance between X and Y however once the matrix is expanded by additional columns the expression has also to be expanded and that is an unacceptable solution...
Would you be so kind and tell how to achieve this? Any help would be more than welcome. I'm stuck with this one for a while...
- between matrix is element-wise in R and the rowSums is useful for calculating the sum of along the row:
m1 <- matrix(
c(4, 3, 1, 6,
2, 4, 5, 7,
9, 0, 1, 2,
6, 7, 8, 9,
1, 6, 4, 3),
nrow = 4
)
m2 <- matrix(
c(2, 6, 3, 2,
9, 4, 1, 4,
1, 3, 0, 1,
4, 5, 0, 2,
7, 2, 1, 3),
nrow = 4
)
sqrt((m1[,1] - m2[,1])^2 + (m1[,2] - m2[,2])^2 + (m1[,3] - m2[,3])^2 + (m1[,4] - m2[,4])^2 + (m1[,5] - m2[,5])^2)
# [1] 12.529964 6.164414 9.695360 8.660254
sqrt(rowSums((m1 - m2) ^ 2))
# [1] 12.529964 6.164414 9.695360 8.660254
I'm working on the following df:
Num1 <- c(1, 2, 1, 3, 4, 4, 6, 2)
Num2 <- c(3, 3, 2, 1, 1, 2,4, 4)
Num3 <- c(2, 2, 3, 4, 3, 5, 5, 7)
Num4 <- c(1, 3, 3, 1, 2,3, 3, 6)
Num5 <- c(2, 1, 1, 1, 5, 3, 2, 1)
df <- data.frame(Num1, Num2, Num3, Num4, Num5)
I need to create a new matrix having the first column as df[1] - df[2], the second as df[2] - df[3] and so on.
How about this?
mapply('-', df[-length(df)], df[-1])
Or (as mentioned by #Pierre Lafortune)
df[-length(df)] - df[-1]
I have a list containing 100 lists within it, each of which has 552 numerical values. How do I sequentially extract the 1st value (and so on up to 552) from each of the 100 lists?
Example: 5 lists within a list containing the numbers 1-10
list(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), c(1, 2, 3, 4, 5, 6, 7,
8, 9, 10), c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), c(1, 2, 3, 4, 5,
6, 7, 8, 9, 10), c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
I want to extract each term sequentially i.e. 1,1,1,1,1 and then
2,2,2,2,2 and so on
This statement produces a list of vectors, taking the first element of each of your original vectors, the second element, etc., giving NA for the value of a short vector:
num <- max(unlist(lapply(x, length))) ## Length of the longest vector in x
lapply(seq(num), function(i) unlist(lapply(x, `[`, i)))
And here's a matrix approach:
matrix(unlist(x), ncol=length(x))
The rows of that matrix are your elements. This relies on each vector being the same length.