How to create multiple loops inside a function in r - r

Question

I want to obtain new values for each step and use them inside an equation for further steps. Normally, I can perform loop but for this problem, I need to use past values, too. For instance, I have flow data like this:
q<-c(10, 15.83333, 21.66667)
I created a loop manually:
z1<-190 #initial elevation
s1<-24011 #initial storage
in1<-q[1] #initial inflow
out1<-1.86*sqrt((z1-110)*19.62) #outflow
z2<- z1+0.3*((in1-out1)/s1) #elevation at second step
in2<-q[2] #second inflow
out2<-1.86*sqrt((z2-110)*19.62) #outflow at z2 elevation
ds2<-0.3*((in1+in2)/2-(out1+out2)/2) #change in storage
s2<-s1+ds2 #net storage value
z3<-z2+0.3*((in2-out2)/s2) #elevation at third step
in3<-q[3]
out3<-1.86*sqrt((z3-110)*19.62)
ds3<-0.3*((in2+in3)/2-(out2+out3)/2)
s3<-s2+ds3
.
.
.
z4<-z3+0.3*((in3-out3)/s3)
Briefly, I am calculating z value using previous values of in,out,s. What I need to find is z values considering q values.
Expected result is:
z q outflows storages
[1,] 190.0000 10.00000 73.68981 24011.00
[2,] 189.9992 15.83333 73.68944 23992.77
[3,] 189.9985 21.66667 73.68911 23976.29

Answer 1

I'll extend my comment here.
You can overwrite the variables. Following your implementation you could for instance create a temporal variable for your out2:
q = c(10, 15.83333, 21.66667)
#Results storage array
results = array(numeric(),c(length(q),4))
colnames(results) = c("z", "q", "outflows", "storages")
z = 190
s = 24011
infl = q[1]
out = 1.86*sqrt((z-110)*19.62)
#Save init values
results[1,1] = z
results[,2] = q
results[1,3] = out
results[1,4] = s
for (n in 2:length(q)) {
z = z+0.3*((infl-out)/s)
out_tmp = 1.86*sqrt((z-110)*19.62)
ds = 0.3*((infl+q[n])/2-(out+out_tmp)/2)
s = s+ds
infl = q[n]
out = out_tmp
results[n,1] = z
results[n,3] = out
results[n,4] = s
}
View(results)
If you want to avoid to create the temporal variable, you can try something like this:
q = c(10, 15.83333, 21.66667)
results = array(numeric(),c(length(q),4))
colnames(results) = c("z", "q", "outflows", "storages")
z = 190
s = 24011
infl = q[1]
out = 1.86*sqrt((z-110)*19.62)
#Save init values
results[1,1] = z
results[,2] = q
results[1,3] = out
results[1,4] = s
for (n in 2:length(q)) {
z = z+0.3*((infl-out)/s)
out = 1.86*sqrt((z-110)*19.62)
ds = 0.3*((infl+q[n])/2-(results[n-1,3]+out)/2)
s = s+ds
infl = q[n]
results[n,1] = z
results[n,3] = out
results[n,4] = s
}
View(results)

Answer 2

Init values and create a result table
Add the current state values to the table
Simulate new state using old or new states
Set the new state to all variables
library(tidyverse)
data <- tibble(step = numeric(), out = numeric(), y = numeric(), z = numeric())
# Initialization
z <- 190
y <- 1
out <- NA
for (step in seq(5)) {
# save current state
data <- data %>% add_row(step = step, out = out, z = z, y = y)
# use old state of z
new_out <- z / 2
# use old state of y
new_z <- y + 1
# use new state of out
new_y <- new_out
# Lastly, update all new variables
out <- new_out
y <- new_y
z <- new_z
}
data
#> # A tibble: 5 x 4
#> step out y z
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1 NA 1 190
#> 2 2 95 95 2
#> 3 3 1 1 96
#> 4 4 48 48 2
#> 5 5 1 1 49
Created on 2021-11-10 by the reprex package (v2.0.1)