Calculating Intake energy with loops - r

Question

I am trying to run through an old coworkers script and I am hoping someone can help inform me of what exactly he did during this code segment. Earlier in the script we calculated the intake rate for several prey species and now it appears that we are grouping them based on unique locations. The section of code after this requires that there be 41 rows ( 1 row for each unique location in the complete dataset). I believe that the code subsets the data based on latitude and then adds an 'alpha' column. The main issue that I am having is what is this line calculating: x= x + d$Intakerate_kjday[j]*d$alpha[j]. For locations that had several prey items (profit.fall.38.4.959) is this code summing up "intakerate_kjday" and "alpha" and then multiplying them together? When the code is performed I receive the error Error in
`[<-.data.frame`(`*tmp*`, k, , value = c("2", "Bishop's Head", : replacement has 6 items, need 7
I would really appreciate any insight into what he was trying to calculate and a potential work around. Thank you.
dput(profit)
structure(list(Sample.ID = structure(c(5L, 19L, 27L, 28L, 30L,
38L, 12L, 62L, 49L, 29L, 25L, 17L, 61L, 67L, 27L, 26L, 32L, 9L,
47L, 45L, 5L, 26L, 27L, 44L, 45L, 4L, 1L, 43L, 19L, 35L), .Label = c("Barren Island Mud 1",
"BH High 1", "BH High 2", "BH Low 1", "BH Low 2", "BH Low 3",
"BHH 1 C", "BHH 2 E", "BHL 1 E", "BHL 2", "BHL 3 (B)", "BHM 1 C",
"BI High 1", "BI Low 1", "BI Low 2C", "BI Low 3", "BI Mud", "BIHI High B",
"BIL1 (low) E", "BIL1E", "BIL2 E", "BIL2E", "BW Fresh 1", "BW Fresh 2",
"BW High 1", "BW High 2", "BW High 5", "BW Low 3", "BW Money Stump",
"BW Mud 1", "BW SAV 1", "BW SAV 2", "BWH 1 D", "BWH 2", "BWH 3",
"BWH 5", "BWL 1", "BWL 2", "BWL 3", "BWM 1", "BWMS D", "EN High 2",
"EN High 4", "EN High 5", "EN Low 1", "EN Low 2", "EN Mud 2",
"ENH3 A High", "ENH4 A High", "ENH5 A High", "ENL1 Low E", "ENM1 A Mud",
"ENS1 SAV", "ENS2 SAV 2C", "ENS3 SAV 3E", "High 3C", "MWP 29 Low 1",
"MWP 30 Mud 1", "MWP 31 Low 2", "MWP 32 Mud 2", "MWP 33 Low 3",
"MWP 34 Low 4", "PWRC Fresh", "WP 27 HM-MARC", "WP 28 HM-MARC",
"WP 30 IT MARE", "WP29 LM-MARC"), class = "factor"), Season = structure(c(2L,
3L, 2L, 2L, 2L, 3L, 3L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 2L,
3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 3L, 3L), .Label = c("",
"Fall", "Spring", "Spring?"), class = "factor"), Refuge = structure(c(3L,
2L, 5L, 5L, 5L, 5L, 4L, 7L, 6L, 5L, 5L, 2L, 7L, 7L, 5L, 5L, 5L,
4L, 6L, 6L, 3L, 5L, 5L, 6L, 6L, 3L, 2L, 6L, 2L, 5L), .Label = c("",
"Barren Island", "Bishop's Head", "Bishops Head", "Blackwater",
"Eastern Neck", "Martin", "PWRC"), class = "factor"), Habitat.Type = structure(c(3L,
3L, 2L, 3L, 4L, 3L, 4L, 3L, 2L, 3L, 2L, 4L, 3L, 3L, 2L, 2L, 5L,
3L, 4L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 4L, 2L, 3L, 2L), .Label = c("Fresh",
"High", "Low", "Mud", "SAV"), class = "factor"), Longitude = c(-76.03896,
-76.26205, -76.05714, -76.06332, -76.14641, -76.23522, -76.03869,
-75.99733, -76.21661, -76.23491, -76.22003, -76.26163, -75.99354,
-76.01407, -76.05714, -76.01762, -76.10363, -76.04883, -76.21547,
-76.23986, -76.03896, -76.01762, -76.05714, -76.2181, -76.23986,
-76.04883, -76.26163, -76.21661, -76.26205, -76.0235), Latitude = c(38.22447,
38.33905, 38.40959, 38.39708, 38.41795, 38.43055, 38.23255, 37.99369,
39.03264, 38.43141, 38.41026, 38.33606, 37.98833, 38.01108, 38.40959,
38.41913, 38.40351, 38.22694, 39.04036, 39.02677, 38.22447, 38.41913,
38.40959, 39.03887, 39.02677, 38.22694, 38.33606, 39.03264, 38.33905,
38.39138), Prey = structure(c(11L, 41L, 35L, 30L, 41L, 41L, 41L,
3L, 18L, 31L, 40L, 9L, 41L, 38L, 30L, 13L, 35L, 41L, 20L, 27L,
4L, 40L, 13L, 35L, 41L, 5L, 5L, 15L, 22L, 20L), .Label = c("Hydrobia",
"Hydrobia genus", "Hydrobia sp.", "Hydrobia spp", "Melampus bidentatus",
"Ruppia (maritima or rostellata)", "Ruppia genus", "Ruppia maritima",
"Schoenoplectus pungens", "Schoenoplectus robustus", "Schoenoplectus spp",
"Schoenoplectus spp.", "Scirpus acutus", "Scirpus acutus?", "Scirpus americanus",
"Scirpus fluviatilis", "Scirpus genus", "Scirpus genus 1", "Scirpus genus 1?",
"Scirpus genus 2", "Scirpus genus 3", "Scirpus genus?", "Scirpus heterochaetus",
"Scirpus meterochaetus", "Scirpus mevadensis", "Scirpus olney?",
"Scirpus olneyi", "Scirpus paludosis", "Scirpus paludosus", "Scirpus robustus",
"Scirpus robustus?", "Scirpus species", "Scirpus subterminalis",
"Scirpus subtermiralis", "Scirpus validus", "Spartina alterniflora",
"Spartina genus", "Spartina genus?", "Spartina patens", "Spartina pectinata",
"Zannichallia palustris"), class = "factor"), Density = c(2.36e-05,
0.000101477, 0.000335244, 1.17e-05, 1.91e-06, 2.8e-06, 1.72e-05,
1.34e-05, 2.71e-05, 0.000107843, 2.16e-06, 4.46e-06, 1.22e-05,
6.61e-05, 0.000263052, 3.91e-05, 0.00034925, 3.69e-06, 8.02e-06,
2.04e-05, 2.9e-05, 2.05e-05, 0.000564046, 0.001912535, 2.04e-05,
0.001117905, 0.00255132, 9.03e-05, 4.23e-05, 0.000248282), Intakerate_kcals = c(-3.5399430250046e-07,
7.6382794280604e-14, -5.02872205332896e-06, -1.7549698484651e-07,
2.70599529637464e-17, 5.81535679492809e-17, 2.19440708445348e-15,
4.34155540862746e-08, -4.06493587341127e-07, -1.61763139817e-06,
-3.23994151550826e-08, -6.68988064422799e-08, 1.10402768540446e-15,
-9.91487886840506e-07, -3.94580269988612e-06, -5.8649138992111e-07,
-5.23882134070119e-06, 1.00998060784975e-16, -1.2029789281118e-07,
-3.05994985702607e-07, 9.3958523768985e-08, -3.07494963928282e-07,
-8.46097103856411e-06, -2.86925082960488e-05, 3.08688633134856e-15,
3.62058033172122e-06, 8.25888178764606e-06, -1.35448644277712e-06,
-6.34490870510011e-07, -3.72424640639279e-06), Intakerate_kjs = c(-1.48111216166192e-06,
3.19585611270047e-13, -2.10401730711284e-05, -7.34279384597799e-07,
1.13218843200315e-16, 2.43314528299791e-16, 9.18139924135334e-15,
1.81650678296973e-07, -1.70076916943527e-06, -6.76816976994329e-06,
-1.35559153008866e-07, -2.79904606154499e-07, 4.61925183573226e-15,
-4.14838531854068e-06, -1.65092384963235e-05, -2.45387997542992e-06,
-2.19192284894938e-05, 4.22575886324335e-16, -5.03326383521979e-07,
-1.28028302017971e-06, 3.93122463449433e-07, -1.28655892907593e-06,
-3.54007028253523e-05, -0.000120049454710668, 1.29155324103624e-14,
1.51485081079216e-05, 3.45551613995111e-05, -5.66717127657947e-06,
-2.65470980221389e-06, -1.55822469643474e-05), Intakerate_kjday = c(-0.12796809076759,
2.76121968137321e-08, -1.81787095334549, -0.0634417388292498,
9.78210805250721e-12, 2.1022375245102e-11, 7.93272894452929e-10,
0.0156946186048585, -0.146946456239208, -0.584769868123101, -0.011712310819966,
-0.0241837579717487, 3.99103358607267e-10, -0.358420491521915,
-1.42639820608235, -0.212015229877145, -1.89382134149226, 3.65105565784226e-11,
-0.043487399536299, -0.110616452943527, 0.033965780842031, -0.111158691472161,
-3.05862072411043, -10.3722728870017, 1.11590200025531e-09, 1.30883110052443,
2.98556594491776, -0.489643598296466, -0.22936692691128, -1.34630613771962
)), row.names = c(NA, -30L), class = "data.frame")
lat=unique(profit$Latitude)
## for each location I am calculating the weight for Fall only
nfall=0
latfall<-c(double())
for(i in lat){
name = paste0("profit.fall.",round(i,5))
x = subset(profit,Latitude==i & Season=="Fall")
if(nrow(x)>=1){
for(j in 1:nrow(x)){
x$alpha[j]<- 1 # used to be this x$Density[j]/sum(x$Density)
}
nfall= nfall+1
assign(name, data.frame(x))
latfall<-c(latfall,round(i,5))
print(name)
}
}
View(profit.fall.38.4.959)
profit.fall.all <- data.frame(matrix(ncol=7,nrow=nfall))
names(profit.fall.all)[1]<-'Id'
names(profit.fall.all)[2]<-'Refuge'
names(profit.fall.all)[3]<-'Season'
names(profit.fall.all)[4]<-'HType'
names(profit.fall.all)[5]<-'Lat'
names(profit.fall.all)[6]<-'Long'
names(profit.fall.all)[7]<-'IntakeEnergy'
View(profit.fall.all)
k=0
lat=latfall
for(i in lat){
df=as.name(paste0('profit.fall.',i))
d=get(as.character(df))
x=0
for(j in 1:nrow(d)){
x= x + d$Intakerate_kjday[j]*d$alpha[j]
}
k=k+1
new_row <- c(k,as.character(d$Refuge[1]),as.character(d$Season[1]),as.character(d$Habitat.Type[1]),as.numeric(d$Latitude[1]),as.numeric(d$Longtitude[1]),as.numeric(x))
#names(new_row)<-c("id","Refuge","Season","HType","Lat","Long","Intakerate_kjday")
#profit.spring.all <- rbind(profit.spring.all, new_row)
profit.fall.all[k,] <- new_row
}
View(profit.fall.all)

Answer 1

The code in question apparently computes (very inefficiently and inaccurately)
sum(d$Intakerate_kjday * d$alpha)
Your error however suggests, that a column is missing in one of the data frames.
Take a look at new_row here:
for(i in lat){
df=as.name(paste0('profit.fall.',i))
d=get(as.character(df))
x=0
for(j in 1:nrow(d)){
x= x + d$Intakerate_kjday[j]*d$alpha[j]
}
k=k+1
new_row <- c(k,as.character(d$Refuge[1]),as.character(d$Season[1]),as.character(d$Habitat.Type[1]),as.numeric(d$Latitude[1]),as.numeric(d$Longtitude[1]),as.numeric(x))
#names(new_row)<-c("id","Refuge","Season","HType","Lat","Long","Intakerate_kjday")
#profit.spring.all <- rbind(profit.spring.all, new_row)
if (length(new_row) != ncol(profit.fall.all)) {
# Catch the bad df
browser()
}
profit.fall.all[k,] <- new_row
}