explanation of a for loop

[tim1]

Hi, I have some problems in understanding a for loop, maybe someone is able to help me.

This is the loop i have:

T_e <- Ta
  for (i in 1:99999) {
    v_e <- 0.6108 * exp(17.27 * T_e/(T_e + 237.3))
    T_enew <- Ta - 1 / gamma * (1 - R_ng / (lambda * Epenman.Daily)) * (v_e - vabar)
    T_e <- T_enew}

As an example this are the first five values of my data set:

Ta=c( 15.85000, 17.95000,  19.40000, 17.20000, 15.75000)
gamma = 0.06599192
 R_ng=c( 3.40699658 , 7.14502764, 4.30308424, 7.38261795, 6.40369739)
lambda=2.45
Epenman.Daily=c( 1.76016607, 2.95703213, 3.29923681, 3.01600420, 2.72208139
vabar=c( 1.2448065, 1.3487874, 1.3361953, 1.2641520, 1.2194822)

and this is the solution for T_e:
T_e:
14.54253001
17.80607304
15.99105488
17.19057572
15.42830198

My question is know, how exactly did you come to this values of T_e?
If i calculated it step by step I come to different solutions for T_e.
Maybe someone can show me, what of the data I have to put in the different equations to come to the solutions of the for loop.
Thank you very much.

[Flm]

This isn't a for loop.
You asked for "i", but in your code there isn't an i.

I give you an example which makes no sense, but can help you understand the mechanism:

library(tidyverse)

Ta = c(15.85000, 17.95000,  19.40000, 17.20000, 15.75000)
gamma = 0.06599192


for(i in Ta){
  
  x <- i*gamma
  print(x)
  
}

The output is

[1] 1.045972
[1] 1.184555
[1] 1.280243
[1] 1.135061
[1] 1.039373

Because every value in Ta is multiplied and printed

[tim1]

Ok thanks. But as it is no for loop, do you still know how the values of T_e are caluculated? How did the program come to the solutions with the code and the data I put in? When I calculate each value of T_e, I come to different outputs.

[jms]

Even tough you don't use the i, the code in your loop still runs 9999 times.

At the end of the loop, you assign your result (T_enew) to T_e. Since T_e is used in the first line of the loop to calculate v_e, each new iteration of the loop uses an updated value of T_e to compute v_eand thus T_enew.
Here a simple example to ilustrate this principle:

a <- 12
for(i in 1:5){
  b <- a/2 # Do some operations based on a 
  a <- b   # assign the results of the previous line back to a
  print(a) # Just to ilustrate what happens to a in each iteration
}
#> [1] 6
#> [1] 3
#> [1] 1.5
#> [1] 0.75
#> [1] 0.375
a 
#> [1] 0.375

I think that might explain why you get a different value of T_e if you simply paste the individual values in your formula.