Formatting, add cores arg

alan-turing-institute · Sep 11, 2023 · 1501cc0 · 1501cc0
1 parent d59ee7b
commit 1501cc0
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diff --git a/scripts/data_prep/SPC_loadWorkspace_run_1.R b/scripts/data_prep/SPC_loadWorkspace_run_1.R
@@ -1,8 +1,3 @@
-# One-time loading
-#install.packages("stringr")
-#install.packages("tidyverse")
-#install.packages("rgdal")
-
 library(parallel)
 library(stringr)
 library(tidyverse)
@@ -15,46 +10,45 @@ cores <- detectCores()
 source("SPC_functions_run_1.R")
 
 # Lookup
-lu <- read.csv(paste(folderInOT,"lookUp-GB.csv", sep = ""))
+lu <- read.csv(paste(folderInOT, "lookUp-GB.csv", sep = ""))
 
 # Income related data // Only necessary for England
 # ageRescaleFFT <- read.csv(paste(folderInOT,"ageRescaleFFT.csv", sep = ""))
 # ageRescaleFPT <- read.csv(paste(folderInOT,"ageRescaleFPT.csv", sep = ""))
 # ageRescaleMFT <- read.csv(paste(folderInOT,"ageRescaleMFT.csv", sep = ""))
 # ageRescaleMPT <- read.csv(paste(folderInOT,"ageRescaleMPT.csv", sep = ""))
-coefFFT <- read.csv(paste(folderInOT,"coefFFT.csv", sep = ""))
-coefFPT <- read.csv(paste(folderInOT,"coefFPT.csv", sep = ""))
-coefMFT <- read.csv(paste(folderInOT,"coefMFT.csv", sep = ""))
-coefMPT <- read.csv(paste(folderInOT,"coefMPT.csv", sep = ""))
-meanHoursMFT <- read.csv(paste(folderInOT,"meanHoursMFT.csv", sep = ""))
-meanHoursMPT <- read.csv(paste(folderInOT,"meanHoursMPT.csv", sep = ""))
-meanHoursFFT <- read.csv(paste(folderInOT,"meanHoursFFT.csv", sep = ""))
-meanHoursFPT <- read.csv(paste(folderInOT,"meanHoursFPT.csv", sep = ""))
-distribHours <- read.csv(paste(folderInOT,"distribHours.csv", sep = ""))
+coefFFT <- read.csv(paste(folderInOT, "coefFFT.csv", sep = ""))
+coefFPT <- read.csv(paste(folderInOT, "coefFPT.csv", sep = ""))
+coefMFT <- read.csv(paste(folderInOT, "coefMFT.csv", sep = ""))
+coefMPT <- read.csv(paste(folderInOT, "coefMPT.csv", sep = ""))
+meanHoursMFT <- read.csv(paste(folderInOT, "meanHoursMFT.csv", sep = ""))
+meanHoursMPT <- read.csv(paste(folderInOT, "meanHoursMPT.csv", sep = ""))
+meanHoursFFT <- read.csv(paste(folderInOT, "meanHoursFFT.csv", sep = ""))
+meanHoursFPT <- read.csv(paste(folderInOT, "meanHoursFPT.csv", sep = ""))
+distribHours <- read.csv(paste(folderInOT, "distribHours.csv", sep = ""))
 distribHoursMFT <- distribHours$MFT
 distribHoursMPT <- distribHours$MPT
 distribHoursFFT <- distribHours$FFT
 distribHoursFPT <- distribHours$FPT
 
 # Health related data
-HST <- read.table(paste(folderInOT,"HSComplete.csv",sep = ""), sep=",", header=TRUE)
-BMIdiff <- read.table(paste(folderInOT,"BMIdiff.csv",sep = ""), sep=",", header=TRUE)
-dMean <- read.table(paste(folderInOT,"BMIdMean.csv",sep = ""), sep=",", header=TRUE)
-varData <- c(37.25736,42.28994,37.73406,42.16856,48.20913,44.52134,39.19527,55.90769)
+HST <- read.table(paste(folderInOT, "HSComplete.csv", sep = ""), sep = ",", header = TRUE)
+BMIdiff <- read.table(paste(folderInOT, "BMIdiff.csv", sep = ""), sep = ",", header = TRUE)
+dMean <- read.table(paste(folderInOT, "BMIdMean.csv", sep = ""), sep = ",", header = TRUE)
+varData <- c(37.25736, 42.28994, 37.73406, 42.16856, 48.20913, 44.52134, 39.19527, 55.90769)
 
 # NSSEC8
-nssecNames<- c("F_16to24","F_25to34","F_35to49","F_50to64","F_65to74",
-               "M_16to24","M_25to34","M_35to49","M_50to64","M_65to74")
-for(i in nssecNames){
-  assign(paste("NSSEC",i,sep = ""), read.csv(paste(folderInOT,"NSSEC8_EW_",i,"_CLEAN.csv",sep = "")))
+nssecNames <- c(
+  "F_16to24", "F_25to34", "F_35to49", "F_50to64", "F_65to74",
+  "M_16to24", "M_25to34", "M_35to49", "M_50to64", "M_65to74"
+)
+for (i in nssecNames) {
+  assign(paste("NSSEC", i, sep = ""), read.csv(paste(folderInOT, "NSSEC8_EW_", i, "_CLEAN.csv", sep = "")))
 }
-NSSECS <- read.csv(paste(folderInOT,"NSSECS_CLEAN.csv", sep = ""))
+NSSECS <- read.csv(paste(folderInOT, "NSSECS_CLEAN.csv", sep = ""))
 
 # TUS
-indivTUS <- read.table(paste(folderInOT,"indivTUS.csv",sep = ""), sep=",", header=TRUE)
-
-#OA coordinates
-OACoords <- read.csv(paste(folderInOT,"OACentroids.csv",sep = ""))
-
-
+indivTUS <- read.table(paste(folderInOT, "indivTUS.csv", sep = ""), sep = ",", header = TRUE)
 
+# OA coordinates
+OACoords <- read.csv(paste(folderInOT, "OACentroids.csv", sep = ""))
diff --git a/scripts/data_prep/SPC_pipelineLAD_run_1.R b/scripts/data_prep/SPC_pipelineLAD_run_1.R
@@ -108,7 +108,7 @@ print("adding income data")
 
 region <- unique(lu$RGN20NM[lu$LAD20CD == lad])
 if (countryR == "England") {
-  merge <- addToData(merge, region, coefFFT, coefFPT, coefMFT, coefMPT)
+  merge <- addToData(merge, region, coefFFT, coefFPT, coefMFT, coefMPT, cores)
 } else {
   merge$incomeH <- NA
   merge$incomeY <- NA