I'm fairly new to R and I have not been working with functions in R before.
I want to write a program/algorithm (using R) that calculates the square root of a given positive number.
Would anyone mind take the time to give me an example of how this can be achieved?
Thanks a lot in advance!
UPDATE
posNum_to_squaRtNum <- function(posNum) {
if (posNum <= 0)
print("Due to mathmatical principles you have to input a positive number")
else
squaRtNum <- sqrt(posNum)
return(squaRtNum)
}
When I insert a negative number in the function, the output is my print PLUS the error: "Error in posNum_to_squaRtNum(-1) : object 'squaRtNum' not found." It should not go on to the else statement, if the if statement is fulfilled right?
You should wrap your if conditions in brackets:
posNum_to_squaRtNum <- function(posNum) {
if (posNum <= 0) {
print("Due to mathmatical principles you have to input a positive number")
} else {
squaRtNum <- sqrt(posNum)
return(squaRtNum)
}
}
Related
Greetings I am getting an error of
Error in if (nrow(pair) == 0) { :argument is of length zero
I have checked the other answers but do not seem to work on a variable like mine. Please check code below, please assist if you can.
pair<-NULL
if(exists("p.doa.ym")) pair <- rbind(pair, p.doa.ym[,1:2])
if(exists("p.doa.yd")) pair <- rbind(pair, p.doa.yd[,1:2])
if(nrow(pair) == 0) {
print("THERE ARE NO MATCHES FOR TODAY. STOP HERE")
quit()
}
Since you set pair=NULL and then it might happen that pair stays null if those two if statements are not true, you either need to check if pair is null first, or you could set pair to an empty data frame, or something else.
One option:
if (!is.null(pair)) {
if (nrow(pair)==0) {
# your code
}
}
Another option:
pair=data.frame()
# your code
I am attempting to combine a series of loops/functions into one all-encompassing function to then be able to see the result for different input values. While the steps work properly when standalone (and when given just one input), I am having trouble getting the overall function to work. The answer I am getting back is a vector of 1s, which is incorrect.
The goal is to count the number of occurrences of consecutive zeroes in the randomly generated results, and then to see how the probability of consecutive zeroes occurring changes as I change the initial percentage input provided.
Does anyone have a tip for what I'm doing wrong? I have stared at this at several separate points now but cannot figure out where I'm going wrong. Thanks for your help.
### Example
pctgs_seq=seq(0.8,1,.01)
occurs=20
iterations=10
iterate_pctgs=function(x) {
probs=rep(0,length(pctgs_seq))
for (i in 1:length(pctgs_seq)) {
all_sims=lapply(1:iterations, function (x) ifelse(runif(occurs) <= i, 1, 0))
totals=sapply(all_sims,sum)
consec_zeroes=function (x) {
g=0
for (i in 1:(length(x)-1))
{ g= g+ifelse(x[i]+x[i+1]==0,1,0) }
return (g) }
consec_zeroes_sim=sapply(all_sims,consec_zeroes)
no_consec_prob=sum(consec_zeroes_sim==0)/length(consec_zeroes_sim)
probs[i]=no_consec_prob }
return (probs)
}
answer=iterate_pctgs(pctgs_seq)
I am trying to implement following algorithm in R:
Iterate(Cell: top)
While (top != null)
Print top.Value
top = top.Next
End While
End Iterate
Basically, given a list, the algorithm should break as soon as it hits 'null' even when the list is not over.
myls<-list('africa','america south','asia','antarctica','australasia',NULL,'europe','america north')
I had to add a for loop for using is.null() function, but following code is disaster and I need your help to fix it.
Cell <- function(top) {
#This algorithm examines every cell in the linked list, so if the list contains N cells,
#it has run time O(N).
for (i in 1:length(top)){
while(is.null(top[[i]]) !=TRUE){
print(top)
top = next(top)
}
}
}
You may run this function using:
Cell(myls)
You were close but there is no need to use for(...) in this
construction.
Cell <- function(top){
i = 1
while(i <= length(top) && !is.null(top[[i]])){
print(top[[i]])
i = i + 1
}
}
As you see I've added one extra condition to the while loop: i <= length(top) this is to make sure you don't go beyond the length of the
list in case there no null items.
However you can use a for loop with this construction:
Cell <- function(top){
for(i in 1:length(top)){
if(is.null(top[[i]])) break
print(top[[i]])
}
}
Alternatively you can use this code without a for/while construction:
myls[1:(which(sapply(myls, is.null))[1]-1)]
Check this out: It runs one by one for all the values in myls and prints them but If it encounters NULL value it breaks.
for (val in myls) {
if (is.null(val)){
break
}
print(val)
}
Let me know in case of any query.
HI i just started learning R and finding this problem to be really interesting where I just run a code directly without wrapping in a function it works but when I place it inside a function it doesn't work, What can be possible reason?
fill_column<-function(colName){
count <- 0
for(i in fg_data$particulars) {
count <- count +1
if(grepl(colName, i) && fg_data$value[count] > 0.0){
fg_data[,colName][count] <- as.numeric(fg_data$value[count])
} else {
fg_data[,colName][count] <- 'NA'
}
}
}
fill_column('volume')
Where I am creating new column named volume it this string exists in particulars column.
I have added a comment where solution given by another question does not work for me, Please look at my comment below.
Finally I got it working but reading another answer on SO, here is the solution:
fill_column <- function(colName){
count <- 0
for(i in fg_data$particulars) {
count <- count +1
if(grepl(colName, i) && fg_data$value[count] > 0.0){
fg_data[,colName][count] <- as.numeric(fg_data$value[count])
} else {
fg_data[,colName][count] <- 'NA'
}
}
return(fg_data)
}
fg_data = fill_column('volume')
Now reason, Usually in any language when we modify global object inside any function it reflects on global object immediately but in R we have to return the modified object from function and then assign it again to global object to see our changes. or another way for doing this is to assign local object from within the function to global context using envir=.GlobalEnv.
Sorry for trivial question, but I`m not a programmer. Do I transformed the following tasks in the form of R function OK?
I have recurrence equations, e.g.(p1_par,...,p4_par-parameters to find):
z1[i+1]= z1[i]+p1_par*p2_par
z12[i+1]= z12[i]+(p1_par*z1[i]-p3_par*z1z2[i]-p4_par)*p2_par
z1z2[i+1]=z1z2[i]+(-p3_par*z12[i]-p4_par*z1z2[i])*p2_par
i=1,...,5
with the initial conditions for i=0:
z1_0=1.23
z12_0=1
z1z2_0=0
and t=6, y=c(0.1,0.06,0.08,0.04,0.05,0.01)
I want to find parameters based on min value of function e.g. like this:
(-2*p1_par*z1[i]-z12[i]+y[i+1]^2+2*p3_par*z1z2[i]+2*p4_par*z1z3[i])^2
I try to build the function in R like:
function1=function(p1_par,p2_par,p3_par,p4_par,y,t){
ep=1
summa=0
result=rep(1,t)
for(i in 1:t){
z1_0=1.23
z12_0=1
z1z2_0=0
z1[1]=z1_0+p1_par*p2_par
z12[1]=z12_0+(p1_par*z1_0-*p3_par*z1z2_0-*p4_par)*p2_par
z1z2[1]=z1z2_0+(-p3_par*z12_0-p4_par*z1z2_0)*p2_par
z1[i+1]= z1[i]+p1_par*p2_par
z12[i+1]= z12[i]+p1_par*z1[i]-p3_par*z1z2[i]-p4_par)*p2_par
z1z2[i+1]=z1z2[i]+(-p3_par*z12[i]-p4_par*z1z2[i])*p2_par
if(i==1) {
result[ep]=(-2*p1_par*z1_0-z12_0+y[i+1]^2+2*p3_par*z1z2_0+2*p4_par*z1z3_0)^2
} else {
result[ep]=(-2*p1_par*z1[i]-z12[i]+y[i+1]^2+2*p3_par*z1z2[i]+2*p4_par*z1z3[i])^2
}
summa<<-summa+result[ep]
ep=ep+1
}
return(result)
}
Do I transformed task of the R function correct? Results from other softwares (like Math) differs. Thanks in advance for help.
PPS