Trying to understand how the value of "traded" is 34
available <- c(10,4,7,10,12)
desired <- c(12,5,2,6,14)
traded <- sum(mapply(function(x,y) min(x,y), available, desired))
Correct value for traded is 34. Just not sure why this is the case. I thought the value would be 6 as the minimum values from each vector (4 and 2) summed together =6
This is answered in the comments, but I wanted to add this breakdown since it helps me to visualize each step.
mapply(function(x,y) min(x,y)): Maps min(x,y) to each item in vectors x and y , so the function is doing this:
min(10,12)
min(4,5)
min(7,2)
min(10,6)
min(12,14)
and outputs = (10, 4, 2, 6, 12)
sum(mapply(...)): Which "sees" the output above and computes 10+4+2+6+12 = 34
Related
This is my first post here and I couldn't find the answer I was looking for.
I'm currently taking edX course on Probability in Data Science, but I got stuck on section 1.
The task asks you to simulate a series of 6 games with random, independent outcomes of either a loss (0) or win(1), and then use the sum function to determine whether a simulated series contained at least 4 wins.
Here's what I did:
l <- list(0:1)
n <- 6
games <- expand.grid(rep(l, n))
games <- paste (games$Var1, games$Var2, games$Var3, games$Var4, games$Var5, games$Var6)
sample (game, 1, replace = TRUE)
but I can't seem to use the sum function to sum the result of '''sample''' and check if there's a series of at least 4 games. I've been trying to use
sum(sample (game, 1, replace = TRUE))
but can't seem to get anywhere with it.
Any light would be greatly appreciated!
Thanks a lot!
This is what one simulated series look like
sample(c(0, 1), 6, replace = TRUE)
To count number of wins (i.e 1) you could use sum like
sum(sample(c(0, 1), 6, replace = TRUE)) >= 4
Now you could generate such series n times with replicate.
n <- 1000
replicate(n, sum(sample(c(0, 1), 6, replace = TRUE)) >= 4)
If you have to use games to calculate you can use rowSums to count number of 1's
sum(rowSums(games) >= 4)
#[1] 22
The fibonacci series is obtained by adding together the prior two integers in the series, the Series include 1, 1, 2 , 3, 5 , 8. I used the following code to have series till 50.
y <- 50
}
fibvals <- numeric(y)
fibvals[1] <- 1
fibvals[2] <- 1
for (i in 3:y) {
fibvals[i] <- fibvals[i-1]+fibvals[i-2]
}
Now i want to add the numbers at even position, i.e 1, 3, 8 till 50th number? please help?
Try using seq to select the even vector indices from 2 to 50, like this:
sum(fibvals[seq(2, 50, by = 2)])
Also: there are R libraries to make working with series easier. You could use the numbers package for example, to get the first 50 Fibonacci numbers:
fibvals <- sapply(1:50, numbers::fibonacci)
I have a vector c(5, 10, 15) and would like to use something like the seq function to created a new vector: 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15. This is how I would do it now, but it seems ineloquent at best. In the final (functional) form, I would need to increment by any given number, not necessarily units of 1.
original_vec <- c(5, 10, 15)
new_vec <- unique(c(seq(original_vec[1],original_vec[2],1),seq(original_vec[2],original_vec[3],1)))
> new_vec
[1] 5 6 7 8 9 10 11 12 13 14 15
Is there a way (I'm sure there is!) to use an apply or similar function to apply a sequence across multiple items in a vector, also without repeating the number in the middle (in the case above, 10 would be repeated, if not for the unique function call.
Edit: Some other possible scenarios might include changing c(1,5,7,10,12) to 1,1.5,2,2.5 ... 10, 10.5, 11, 11.5, 12, or c(1,7,4) where the price increases and then decreases by an interval.
The answer may be totally obvious and I just can't quite figure it out. I have looked at manuals and conducted searched for the answer already. Thank you!
While this isn't the answer to my original question, after discussing with my colleague, we don't have cases where seq(min(original_vec), max(original_vec), by=0.5), wouldn't work, so that's the simplest answer.
However, a more generalized answer might be:
interval = 1
seq(original_vec[1], original_vec[length(original_vec)], by = interval)
Edit: Just thought I'd go ahead and include the finished product, which includes the seq value in a larger context and work for increasing values AND for cases where values change direction. The use case is the linear interpolation of utilities, given original prices and utilities.
orig_price <- c(2,4,6)
orig_utils <- c(2,1,-3)
utility.expansion = function(x, y, by=1){
#x = original price, y = original utilities
require(zoo)
new_price <- seq(x[1],x[length(x)],by)
temp_ind <- new_price %in% x
new_utils <- rep(NA,length(new_price))
new_utils[temp_ind] <- y
new_utils <- na.approx(new_utils)
return(list("new price"=new_price,"new utilities"=new_utils))
}
I am working with long strings of repeating 1's and 0's representing the presence of a phenomenon as a function of depth. If this phenomenon is flagged for over 1m, it is deemed significant enough to use for further analyses, if not it could be due to experimental error.
I ultimately need to get a total thickness displaying this phenomenon at each location (if over 1m).
In a dummy data set the input and expected output would look like this:
#Depth from 0m to 10m with 0.5m readings
depth <- seq(0, 10, 0.5)
#Phenomenon found = 1, not = 0
phenomflag <- c(1,0,1,1,1,1,0,0,1,0,1,0,1,0,1,1,1,1,1,0)
What I would like as an output is a vector with: 4, 5 (which gets converted back to 2m and 2.5m)
I have attempted to solve this problem using
y <- rle(phenomflag)
z <- y$length[y$values ==1]
but once I have my count, I have no idea how to:
a) Isolate 1 maximum number from each group of consecutive repeats.
b) Restrict to consecutive strings longer than (x) - this might be easier after a.
Thanks in advance.
count posted a good solution in the comments section.
y <- y <- rle(repeating series of 1's and 0's)
x <- cbind(y$lengths,y$values) ; x[which(x[,1]>=3 & x[,2]==1)]
This results in just the values that repeat more than a threshold of 2, and just the maximum.
I'm new to R and I would be very grateful for an answer to my question:
I've got a vector: c(9, 11, 2, 6, 10) and the number 4 (or a vector c(4))
I want to generate a vector with the absolute difference between the first and the second one, which should look like this: c(5, 7, 2, 2, 6)
How do I do this? I can't get it to work with diff(), even after reading through the help (?diff()).
Any help is appreciated :)
x <- c(9, 11, 2, 6, 10)
abs(x - 4)
#[1] 5 7 2 2 6
abs finds the absolute value of a vector. '4' will be recycled when subtracted from x. If you have multiple values to be subtracted, they will also be recycled with a warning unless they are the same length as x.
You ran into problems with diff because it isn't designed for scalar subtraction (what you are attempting). It is better suited to finding the difference within a vector.