Update
I've been trying the apply() functions but the output is stumping me. I need a data.frame or data.table. apply(smallExample, 1, SectionDev) gives the right output but in a list. I've read sapply() can output a data.frame or matrix but I can't get the entire row to feed into the function.
New Function
SectionDev <- function(x){
parameters <- data.table("Name" = c("Head", "Foot", "Pillow", "Mattress", "Sleeping", "Restless"),
"Space" = c(8, 78, 17, 17, 3, 8),
"Portion" = c(2, 4, 2, 2, 3, 3))
RG <- as.numeric(x[which(names(x) == "Gas")])
RS <- as.numeric(x[which(names(x) == "Solid")])
A <- data.frame(MG=c(1, 0, 1, 0),
MS=c(1, 0, 0, 1),
VG=c(0, 1, -1*RG, 0),
VS=c(0, 1, 0, -1*RS))
for (j in 1:nrow(parameters)) {
SectName <- as.vector(as.matrix(parameters[j, `Name`]))
Ac <- parameters[j, `Portion`]
Vt <- parameters[j, `Space`]
Pushing <- as.numeric(x[which(names(x) == SectName)])
Driving <- as.numeric(Pushing * 249.1)
Pressing <- Driving*Ac / 9.8
b <- c(Pressing, Vt, 0, 0)
MatrixConstants <- data.table("Timestamp" = as.vector(as.matrix(x[which(names(x) == "Timestamp")])),
"Section" = SectName,
RG,
RS)
MatrixSolution <- solve(A,b)
MatrixPtResult <- cbind(MatrixConstants,t(
as.data.frame(MatrixSolution)))
if (exists("MatrixTest")){
rlist <- list(MatrixTest, MatrixPtResult)
} else {
rlist <- list(MatrixPtResult)
}
MatrixTest <- rbindlist(rlist)
}
return(MatrixTest)
}
Desired Output
> MatrixOutput[1:12,]
Timestamp Portion Gas Solid MG MS VG
1: 2019-04-24 06:00:00 Head 18 234 149.2218 -67.88299 8.290098
2: 2019-04-24 06:00:00 Foot 18 234 1427.7993 -309.39116 79.322184
3: 2019-04-24 06:00:00 Pillow 18 234 318.7908 -166.28061 17.710601
4: 2019-04-24 06:00:00 Mattress 18 234 183.2262 1596.05952 10.179233
5: 2019-04-24 06:00:00 Sleeping 18 234 -316.4209 4815.47194 -17.578940
6: 2019-04-24 06:00:00 Restless 18 234 -549.3597 9013.67602 -30.519983
7: 2019-04-24 07:00:00 Head 17 239 141.7429 -80.73885 8.337819
8: 2019-04-24 07:00:00 Foot 17 239 1365.2541 -551.86634 80.309064
9: 2019-04-24 07:00:00 Pillow 17 239 303.3448 -201.67136 17.843813
10: 2019-04-24 07:00:00 Mattress 17 239 178.7719 1549.67705 10.515996
11: 2019-04-24 07:00:00 Sleeping 17 239 -277.9378 4624.47863 -16.349283
12: 2019-04-24 07:00:00 Restless 17 239 -501.7540 8966.07028 -29.514938
VS
1: -0.2900983
2: -1.3221844
3: -0.7106009
4: 6.8207672
5: 20.5789399
6: 38.5199830
7: -0.3378195
8: -2.3090642
9: -0.8438132
10: 6.4840044
11: 19.3492830
12: 37.5149384
Original
I have to solve the same matrix for each time point and location in my data. The for loop works but isn't fast at 12,000+ time points and 6 locations.
Is there a way to do this without using for? It just doesn't feel like R the way I'm doing it currently.
I did try using foreach with doParallel but it was actually slower than the for as written in TERR.
There are two nested loops. The first pulls the measurements for the time point and the second executes solve for each location.
for (i in 1:nrow(smallExample)) {
RG <- as.matrix(smallExample[i, "Gas"])
RS <- as.matrix(smallExample[i, "Solid"])
A <- data.frame(MG=c(1, 0, 1, 0),
MS=c(1, 0, 0, 1),
VG=c(0, 1, -1*RG,0),
VS=c(0, 1, 0, -1*RS))
for (j in 1:nrow(parameters)) {
SectName <- as.vector(as.matrix(parameters[j, "Name"]))
Ac <- parameters[j, "Portion"]
Vt <- parameters[j, "Space"]
Pushing <- smallExample[i, get(SectName)]
Driving <- as.matrix(Pushing*249.1)
Pressing <- Driving * as.matrix(Ac) / 9.8
b <- c(Pressing,Vt,0,0)
MatrixConstants <- data.table("Timestamp" = as.vector(as.matrix(smallExample[i, "Timestamp"])),
"Portion" = SectName,
RG,
RS)
MatrixSolution <- solve(A,b)
MatrixPtResult <- cbind(MatrixConstants,t(
as.data.frame(MatrixSolution)))
if (exists("MatrixOutput")){
rlist <- list(MatrixOutput, MatrixPtResult)
} else {
rlist <- list(MatrixPtResult)
}
MatrixOutput <- rbindlist(rlist)
cat(paste("\r",i, "Observations of ", nrow(smallExample),"\t",nrow(MatrixOutput),"Matrix results",sep = " "))
}
}
The result is an unpivoted table of times, locations, measurements, and the four parts of the solutions.
Data:
library(data.table)
smallExample <- structure(list(Gas = c(18, 17, 15, 14, 12, 11),
Solid = c(234, 239, 237, 238, 233, 239),
Timestamp = structure(c(1556085600,
1556089200,
1556092800,
1556096400,
1556100000,
1556103600),
class = c("POSIXct", "POSIXt"), tzone = "UTC"),
Head = c(1.6, 1.2, 1.1, 1.0, 0.8, 0.7),
Foot = c(11, 8, 7, 6, 5, 4),
Pillow = c(3, 2, 2, 2, 1, 1),
Mattress = c(35, 34, 31, 30, 28, 26),
Sleeping = c(59, 57, 59, 58, 59, 59),
Restless = c(111, 111, 110, 111, 112, 113)),
class = c("data.table", "data.frame"),
row.names = c(NA_integer_, -6L))
parameters <- data.table("Name" = c("Head", "Foot", "Pillow", "Mattress", "Sleeping", "Restless"),
"Space" = c(8, 78, 17, 17, 3, 8),
"Portion" = c(2, 4, 2, 2, 3, 3))
The solution was to use apply and do.call with rbind (thanks to fotNelton). Benchmarking with microbenchmark using apply came in 60% faster. Just left wishing I could get do.call(rbindlist,)) to work.
MatrixAnswer <- as.data.table(do.call(rbind, apply(MatrixSubTest, 1, SectionMasses)))