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Revert "script now changes path type based on os" #21

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Revert "script now changes path type based on os" #21

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63 changes: 27 additions & 36 deletions cmip6-BC_InputData_meanTS.R
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Original file line number Diff line number Diff line change
Expand Up @@ -14,22 +14,13 @@ library(colorRamps)
library(rgeos)
library(rgdal)

# Configure path based on os type

path_sep <- "/"

if(.Platform$OS.type != "unix") {
path_sep <- "\\"
}



monthdays <- c(31, 28.25, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31)
monthcodes <- c("01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12")
seasons <- c("wt", "sp", "sm", "at")
seasonmonth.mat <- matrix(monthcodes[c(12, 1:11)],4, byrow=T)

dem.pts <- read.csv(paste("outputs", "dem_cmip6eval.csv", sep=path_sep))
dem.pts <- read.csv("./outputs/dem_cmip6eval.csv")
ecoprovs <- c("BC", sort(as.character(unique(dem.pts$id2))))
ecoprov.names <- c("British Columbia", "Boreal Plains", "Central Interior", "Coast and Mountains", "Georgia Depression", "Northern Boreal Mountains", "Sub-Boreal Interior", "Southern Interior Mountains", "Southern Interior", "Taiga Plains")
# elements <- c("Tave", "Tmax", "Tmin", "PPT", "NFFD")
Expand Down Expand Up @@ -63,7 +54,7 @@ compute_seasonal <- function(cvar_name, cvar_monthly_df, func, sep="") {

dd_0 <- function(tm) {

optimized_params <- read.csv(file = paste("optimizedParameterTables","param_DD_S1.csv", sep=path_sep), sep=',', header = TRUE)
optimized_params <- read.csv(file = "./optimizedParameterTables/param_DD_S1.csv", sep=',', header = TRUE)

#optimized_params <- dd_param[dd_param$Month == m,]
#dd_param <- dd_param_above_5[dd_param_above_5$Region == "All"]
Expand All @@ -89,7 +80,7 @@ dd_0 <- function(tm) {

dd5 <- function(tm) {

optimized_params <- read.csv(file = paste("optimizedParameterTables", "param_DD_S2.csv", sep=path_sep), sep=',', header = TRUE)
optimized_params <- read.csv(file = "./optimizedParameterTables/param_DD_S2.csv", sep=',', header = TRUE)
optimized_params <- optimized_params[optimized_params$Region == "All",]

k <- optimized_params$k
Expand All @@ -112,8 +103,8 @@ dd5 <- function(tm) {

dd_18 <- function(tm) {

optimized_params <- read.csv(file = paste("optimizedParameterTables", "param_DD_S3.csv", sep=path_sep), sep=',', header = TRUE)

optimized_params <- read.csv(file = "./optimizedParameterTables/param_DD_S3.csv", sep=',', header = TRUE)
k <- optimized_params$k
a <- optimized_params$a
b <- optimized_params$b
Expand All @@ -132,7 +123,7 @@ dd_18 <- function(tm) {

dd18 <- function(tm) {

optimized_params <- read.csv(file = paste("optimizedParameterTables", "param_DD_S4.csv", sep=path_sep), sep=',', header = TRUE)
optimized_params <- read.csv(file = "./optimizedParameterTables/param_DD_S4.csv", sep=',', header = TRUE)
optimized_params <- optimized_params[optimized_params$Region == "All",]


Expand All @@ -152,8 +143,8 @@ dd18 <- function(tm) {

# NFFD
compute_nffd <- function(t_min) {
nffd_param <- read.csv(file = paste("optimizedParameterTables", "param_NFFD.csv", sep=path_sep), sep=',', header = TRUE)
nffd_param <- read.csv(file = "./optimizedParameterTables/param_NFFD.csv", sep=',', header = TRUE)

a <- nffd_param$a
b <- nffd_param$b
t0 <- nffd_param$T0
Expand Down Expand Up @@ -207,8 +198,8 @@ ffp <-function(effp,bffp) {
# tm: min temperature for that month
pas <- function(t_min_monthly, ppt_monthly) {

pas_param <- read.csv(file = paste("optimizedParameterTables", "param_PAS.csv", sep=path_sep), sep=',', header = TRUE)
pas_param <- read.csv(file = "./optimizedParameterTables/param_PAS.csv", sep=',', header = TRUE)

b <- pas_param$b
t0 <- pas_param$T0

Expand Down Expand Up @@ -270,7 +261,7 @@ rh <- function(t_min_monthly, t_max_monthly) {
# ==========================================
#step 2d: create mean observational time series for province/ecoregion

obs.ts <- read.csv(paste("outputs","obs.ts.csv", sep=path_sep))
obs.ts <- read.csv("./outputs/obs.ts.csv")

## station observations
ecoprov=ecoprovs[2]
Expand Down Expand Up @@ -395,13 +386,13 @@ for(ecoprov in ecoprovs){
##########################
ts <- aggregate(gridded_data, by=list(gridded_data$Year), FUN = mean, na.rm=T)[,-1]

write.csv(ts,paste(paste("gridded_output", "ts.obs.mean.", sep=path_sep), ecoprov, ".csv", sep=""), row.names=FALSE)
write.csv(ts,paste("./gridded_output/ts.obs.mean.", ecoprov, ".csv", sep=""), row.names=FALSE)
print(ecoprov)
}


## ERA5
era5.ts <- read.csv(paste("outputs","era5.ts.csv", sep=path_sep))
era5.ts <- read.csv("./outputs/era5.ts.csv")

ecoprov=ecoprovs[2]
for(ecoprov in ecoprovs){
Expand Down Expand Up @@ -524,7 +515,7 @@ for(ecoprov in ecoprovs){
# Aggregate all years together
##########################
ts <- aggregate(gridded_data, by=list(gridded_data$Year), FUN = mean, na.rm=T)[,-1]
write.csv(ts,paste(paste("gridded_output","ts.era5.mean.", sep=path_sep), ecoprov, ".csv", sep=""), row.names=FALSE)
write.csv(ts,paste("./gridded_output/ts.era5.mean.", ecoprov, ".csv", sep=""), row.names=FALSE)
print(ecoprov)
}

Expand All @@ -535,7 +526,7 @@ for(ecoprov in ecoprovs){
# step 3: GCM Files
# ==========================================

files <- list.files("outputs", pattern=paste("^ts.*", sep="."))
files <- list.files("outputs/", pattern=paste("^ts.*", sep="."))
gcms <- unique(sapply(strsplit(files, "[.]"), "[", 2))
gcms <- gcms[-grep("obs|era", gcms)]

Expand All @@ -547,7 +538,7 @@ for(i in 1:length(gcms)){
# ==========================================
# step 3b: calculate average time series across BC/ecoprovince for each gcm and scenario

files <- list.files("outputs")
files <- list.files("outputs/")
files <- files[grep(paste("ts", gcm, sep="."), files)] #these ts (time series) files have one record for each grid cell for each year.
run.list <- sapply(strsplit(files, "[.]"), "[", 3)
scenario.list <- sapply(strsplit(run.list, "_"), "[", 1)
Expand All @@ -560,7 +551,7 @@ for(i in 1:length(gcms)){
ripfs <- unique(ripf.list[which(scenario.list==scenario)])
ripf <- ripfs
for(ripf in ripfs){
data.full <- read.csv(paste(paste("outputs","ts.", sep=path_sep), gcm, ".", scenario, "_", ripf, ".csv", sep=""))
data.full <- read.csv(paste("./outputs/ts.", gcm, ".", scenario, "_", ripf, ".csv", sep=""))
ecoprov <- ecoprovs[1]
for(ecoprov in ecoprovs){
if(ecoprov=="BC") s <- 1:dim(data.full)[1] else {
Expand Down Expand Up @@ -703,7 +694,7 @@ for(i in 1:length(gcms)){
}
names(ensemble) <- ripfs
ensemble <- data.frame(Year=x, ensemble)
write.csv(ensemble, paste(paste("gridded_output","ensemble", sep=path_sep), gcm, ecoprov, variable, scenario, "csv", sep="."), row.names=FALSE)
write.csv(ensemble,paste("./gridded_output/ensemble", gcm, ecoprov, variable, scenario, "csv", sep="."), row.names=FALSE)
# print(variable)
}
# print(ecoprov)
Expand All @@ -720,9 +711,9 @@ for(i in 1:length(gcms)){
# min, max, and mean for each model and for whole ensemble
# ==========================================

variables <-names(read.csv(paste("gridded_output", "ts.era5.mean.SIM.csv", sep=path_sep)))[-1] # changed to file with all variables
variables <-names(read.csv("./gridded_output/ts.era5.mean.SIM.csv"))[-1]

files <- list.files(paste("gridded_output", path_sep, sep="") , pattern=paste("^ensemble.*", sep="."))
files <- list.files("./gridded_output/", pattern=paste("^ensemble.*", sep="."))
gcms.all <- unique(sapply(strsplit(files, "[.]"), "[", 2))
scenarios <- unique(sapply(strsplit(files, "[.]"), "[", 5))
funs <- c("min", "max", "mean")
Expand All @@ -736,21 +727,21 @@ for(fun in funs){
variable <- variables[1]
for(variable in variables){

files <- list.files(paste("gridded_output", path_sep, sep=""), pattern=paste("^ensemble.*", ecoprov, variable, scenario,"*", sep="."))
files <- list.files("./gridded_output/", pattern=paste("^ensemble.*", ecoprov, variable, scenario,"*", sep="."))
gcms <- unique(sapply(strsplit(files, "[.]"), "[", 2))
gcm <- gcms[1]
data <- read.csv(paste(paste("gridded_output", "ensemble", sep=path_sep), gcm, ecoprov, variable, scenario, "csv", sep="."))
data <- read.csv(paste("./gridded_output/ensemble", gcm, ecoprov, variable, scenario, "csv", sep=".")) ##
temp <- data.frame(data[,1], matrix(NA, dim(data)[1],length(gcms.all)))
names(temp) <- c("Year", gcms.all)
for(gcm in gcms){
data <- read.csv(paste(paste("gridded_output", "ensemble", sep=path_sep), gcm, ecoprov, variable, scenario, "csv", sep=".")) ##
data <- read.csv(paste("./gridded_output/ensemble", gcm, ecoprov, variable, scenario, "csv", sep="."))
stat <- if(dim(data)[2]==2) data[,2] else round(apply(data[,-1], 1, fun),1)
temp[match(data$Year, temp$Year),which(names(temp)==gcm)] <- stat
print(gcm)
}
temp <- cbind(temp, round(apply(temp[,-1], 1, fun, na.rm=T),1))
names(temp) <- c("Year", gcms.all, "ensemble")
write.csv(temp,paste(paste(paste("gridded_output","ens", sep=path_sep), fun, sep=""), ecoprov, variable, scenario, "csv", sep="."), row.names=FALSE)
write.csv(temp,paste(paste("./gridded_output/ens", fun, sep=""), ecoprov, variable, scenario, "csv", sep="."), row.names=FALSE)
print(variable)
}
print(ecoprov)
Expand All @@ -761,7 +752,7 @@ for(fun in funs){
}

## rbind the scenarios together and write out.
files <- list.files(paste("gridded_output", path_sep, sep=""), pattern=paste("^ensemble.*", sep="."))
files <- list.files("./gridded_output/", pattern=paste("^ensemble.*", sep="."))
scenarios <- unique(sapply(strsplit(files, "[.]"), "[", 5))
variables <- unique(sapply(strsplit(files, "[.]"), "[", 4))
ecoprovs <- unique(sapply(strsplit(files, "[.]"), "[", 3))
Expand All @@ -770,11 +761,11 @@ for(fun in funs){
for(ecoprov in ecoprovs){
for(variable in variables){
for(scenario in scenarios){
temp <- read.csv(paste(paste(paste("gridded_output","ens", sep=path_sep), fun, sep=""), ecoprov, variable, scenario, "csv", sep="."))
temp <- read.csv(paste(paste("./gridded_output/ens", fun, sep=""), ecoprov, variable, scenario, "csv", sep="."))
data <- if(scenario==scenarios[1]) data.frame(scenario=rep(scenario, dim(temp)[1]), temp) else rbind(data, data.frame(scenario=rep(scenario, dim(temp)[1]), temp))
# print(scenario)
}
write.csv(data,paste(paste(paste("gridded_output", "ens", sep=path_sep), fun, sep=""), ecoprov, variable, "csv", sep="."), row.names=FALSE)
write.csv(data,paste(paste("./gridded_output/ens", fun, sep=""), ecoprov, variable, "csv", sep="."), row.names=FALSE)
# print(variable)
}
print(ecoprov)
Expand Down