-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
New Foraging model according to Gloria's calculations
- Loading branch information
Showing
1 changed file
with
241 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,241 @@ | ||
| library(data.table) | ||
| library(dplyr) | ||
| library(tidyverse) | ||
| library(lubridate) | ||
| library(ggplot2) | ||
| library(chillR) | ||
| library(geosphere) | ||
| library(suncalc) | ||
|
|
||
| options(digits=9) | ||
| options(digit=9) | ||
|
|
||
| read_binary <- function(file_path, hist, no_vars){ | ||
| ###### The modeled historical is in /data/hydro/jennylabcommon2/metdata/maca_v2_vic_binary/ | ||
| ###### modeled historical is equivalent to having 4 variables, and years 1950-2005 | ||
| ###### | ||
| ###### The observed historical is in | ||
| ###### /data/hydro/jennylabcommon2/metdata/historical/UI_historical/VIC_Binary_CONUS_to_2016 | ||
| ###### observed historical is equivalent to having 8 variables, and years 1979-2016 | ||
| ###### | ||
| if (hist) { | ||
| if (no_vars==4){ | ||
| start_year <- 1950 | ||
| end_year <- 2005 | ||
| } else { | ||
| start_year <- 1979 | ||
| end_year <- 2015 | ||
| } | ||
| } else{ | ||
| start_year <- 2006 | ||
| end_year <- 2099 | ||
| } | ||
| ymd_file <- create_ymdvalues(start_year, end_year) | ||
| data <- read_binary_addmdy(file_path, ymd_file, no_vars) | ||
| return(data) | ||
| } | ||
|
|
||
| read_binary_addmdy <- function(filename, ymd, no_vars){ | ||
| if (no_vars==4){ | ||
| return(read_binary_addmdy_4var(filename, ymd)) | ||
| } else {return(read_binary_addmdy_8var(filename, ymd))} | ||
| } | ||
|
|
||
| read_binary_addmdy_8var <- function(filename, ymd){ | ||
| Nofvariables <- 8 # number of variables or column in the forcing data file | ||
| Nrecords <- nrow(ymd) | ||
| ind <- seq(1, Nrecords * Nofvariables, Nofvariables) | ||
| fileCon <- file(filename, "rb") | ||
| temp <- readBin(fileCon, integer(), size = 2, n = Nrecords * Nofvariables, | ||
| endian = "little") | ||
| dataM <- matrix(0, Nrecords, 8) | ||
| k <- 1 | ||
| dataM[1:Nrecords, 1] <- temp[ind] / 40.00 # precip data | ||
| dataM[1:Nrecords, 2] <- temp[ind + 1] / 100.00 # Max temperature data | ||
| dataM[1:Nrecords, 3] <- temp[ind + 2] / 100.00 # Min temperature data | ||
| dataM[1:Nrecords, 4] <- temp[ind + 3] / 100.00 # Wind speed data | ||
| dataM[1:Nrecords, 5] <- temp[ind + 4] / 10000.00 # SPH | ||
| dataM[1:Nrecords, 6] <- temp[ind + 5] / 40.00 # SRAD | ||
| dataM[1:Nrecords, 7] <- temp[ind + 6] / 100.00 # Rmax | ||
| dataM[1:Nrecords, 8] <- temp[ind + 7] / 100.00 # RMin | ||
| AllData <- cbind(ymd, dataM) | ||
| # calculate daily GDD ...what? There doesn't appear to be any GDD work? | ||
| colnames(AllData) <- c("year", "month", "day", "precip", "tmax", "tmin", | ||
| "windspeed", "SPH", "SRAD", "Rmax", "Rmin") | ||
| close(fileCon) | ||
| return(AllData) | ||
| } | ||
|
|
||
| read_binary_addmdy_4var <- function(filename, ymd) { | ||
| Nofvariables <- 4 # number of variables or column in the forcing data file | ||
| Nrecords <- nrow(ymd) | ||
| ind <- seq(1, Nrecords * Nofvariables, Nofvariables) | ||
| fileCon <- file(filename, "rb") | ||
| temp <- readBin(fileCon, integer(), size = 2, n = Nrecords * Nofvariables, | ||
| endian="little") | ||
| dataM <- matrix(0, Nrecords, 4) | ||
| k <- 1 | ||
| dataM[1:Nrecords, 1] <- temp[ind] / 40.00 # precip data | ||
| dataM[1:Nrecords, 2] <- temp[ind + 1] / 100.00 # Max temperature data | ||
| dataM[1:Nrecords, 3] <- temp[ind + 2] / 100.00 # Min temperature data | ||
| dataM[1:Nrecords, 4] <- temp[ind + 3] / 100.00 # Wind speed data | ||
|
|
||
| AllData <- cbind(ymd, dataM) | ||
| # calculate daily GDD ...what? There doesn't appear to be any GDD work? | ||
| colnames(AllData) <- c("year", "month", "day", "precip", "tmax", "tmin", | ||
| "windspeed") | ||
| close(fileCon) | ||
| return(AllData) | ||
| } | ||
|
|
||
| create_ymdvalues <- function(data_start_year, data_end_year){ | ||
| Years <- seq(data_start_year, data_end_year) | ||
| nYears <- length(Years) | ||
| daycount_in_year <- 0 | ||
| moncount_in_year <- 0 | ||
| yearrep_in_year <- 0 | ||
|
|
||
| for (i in 1:nYears){ | ||
| ly <- leap_year(Years[i]) | ||
| if (ly == TRUE){ | ||
| days_in_mon <- c(31, 29, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31) | ||
| } | ||
| else{ | ||
| days_in_mon <- c(31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31) | ||
| } | ||
|
|
||
| for (j in 1:12){ | ||
| daycount_in_year <- c(daycount_in_year, seq(1, days_in_mon[j])) | ||
| moncount_in_year <- c(moncount_in_year, rep(j, days_in_mon[j])) | ||
| yearrep_in_year <- c(yearrep_in_year, rep(Years[i], days_in_mon[j])) | ||
| } | ||
| } | ||
|
|
||
| daycount_in_year <- daycount_in_year[-1] #delete the leading 0 | ||
| moncount_in_year <- moncount_in_year[-1] | ||
| yearrep_in_year <- yearrep_in_year[-1] | ||
| ymd <- cbind(yearrep_in_year, moncount_in_year, daycount_in_year) | ||
| colnames(ymd) <- c("year", "month", "day") | ||
| return(ymd) | ||
| } | ||
|
|
||
| filePathPrefix <- '' | ||
| file <- '' | ||
| location <- 'Richland' | ||
| hist <- TRUE | ||
| vars <- 8 | ||
|
|
||
| if (location == 'Omak') | ||
| file <- 'data_48.40625_-119.53125' | ||
| if (location == 'Wenatchee') | ||
| file <- 'data_47.40625_-120.34375' | ||
| if (location == 'Richland') | ||
| file <- 'data_46.28125_-119.34375' | ||
| if (location == 'WallaWalla') | ||
| file <- 'data_46.03125_-118.34375' | ||
|
|
||
| if (hist) { | ||
| filePathPrefix <- "D:/Coursework/PACCAR/VarroaPOP/Beepop/Simulations/ObservedHistoricalBinary/" | ||
| } else { | ||
| filePathPrefix <- "D:/Coursework/PACCAR/VarroaPOP/Beepop/Simulations/Rcp85Binary/" | ||
| vars <- 4 | ||
| } | ||
|
|
||
| outputfilePath <- paste0('D:/Coursework/PACCAR/VarroaPOP/Beepop/Simulations/', file, '.csv') | ||
|
|
||
| met_data <- read_binary(file_path = paste0(filePathPrefix, file), | ||
| hist = hist, no_vars=vars) | ||
|
|
||
| # I make the assumption that lat always has same number of decimal points | ||
| lat <- as.numeric(substr(x = file, start = 6, stop = 13)) | ||
| lon <- as.numeric(substr(x = file, start = 15, stop =24)) | ||
|
|
||
| # data frame required | ||
| met_data <- as.data.frame(met_data) | ||
|
|
||
| # 3b. Clean it up | ||
| # rename needed columns | ||
|
|
||
| data.table::setnames(met_data, old=c("year","month", "day", "tmax", "tmin"), | ||
| new=c("Year", "Month", "Day", "Tmax", "Tmin")) | ||
|
|
||
| met_data <- met_data %>% | ||
| select(-c(precip, windspeed)) %>% | ||
| data.frame() | ||
|
|
||
| # 3c. Get hourly interpolation | ||
| # generate hourly data | ||
| met_hourly <- stack_hourly_temps(weather = met_data, | ||
| latitude = lat) | ||
| met_hourly <- met_hourly$hourtemps | ||
|
|
||
| met_data['HRSFLYtemp'] <- 0 | ||
|
|
||
| for (row in 1:nrow(met_data)) { | ||
|
|
||
| year <- met_data[row, "Year"] | ||
| month <- met_data[row, "Month"] | ||
| day <- met_data[row, "Day"] | ||
|
|
||
| onThatDay <- filter(met_hourly, Year == year & Month == month & Day == day) | ||
|
|
||
| sunrise = as.POSIXlt(getSunlightTimes(date = as.Date(strptime(paste(onThatDay$Year[1], onThatDay$Month[1], onThatDay$Day[1], sep = '-'), "%Y-%m-%d")), lat = lat, lon = lon, tz = 'America/Los_Angeles')$sunrise) | ||
| sunset = as.POSIXlt(getSunlightTimes(date = as.Date(strptime(paste(onThatDay$Year[1], onThatDay$Month[1], onThatDay$Day[1], sep = '-'), "%Y-%m-%d")), lat = lat, lon = lon, tz = 'America/Los_Angeles')$sunset) | ||
|
|
||
| onThatDay <- filter(onThatDay, Hour >= sunrise$hour & Hour <= sunset$hour) | ||
|
|
||
| count <- sum(onThatDay$Temp > 10) | ||
| rm(onThatDay) | ||
| met_data$HRSFLYtemp[row] = count | ||
|
|
||
| } | ||
|
|
||
| met_data['HRSlight'] = daylength(lat, as.character(strptime(paste(met_data$Year, met_data$Month, met_data$Day, sep = '-'), "%Y-%m-%d"))) | ||
|
|
||
| HRSsolstice = max(met_data$HRSlight) | ||
|
|
||
| #met_data['PROPHRSFLYtemp'] <- met_data['HRSFLYtemp'] / met_data['HRSlight'] | ||
|
|
||
|
|
||
| #for (row in 1:nrow(met_data)) { | ||
|
|
||
| # if(met_data$PROPHRSFLYtemp[row] > 1) { | ||
| # met_data$PROPHRSFLYtemp[row] = 1 | ||
| # } | ||
| # | ||
| #} | ||
|
|
||
| #met_data['HRSFLY'] = met_data['PROPHRSFLYtemp'] * 24 | ||
|
|
||
| met_data['PROPFLIGHTDAY'] <- met_data['HRSFLYtemp'] / HRSsolstice | ||
|
|
||
| met_data['SUMFLIGHTDAY'] <- 0 | ||
|
|
||
| met_data$SUMFLIGHTDAY[1] = met_data$PROPFLIGHTDAY[1] | ||
|
|
||
| for (row in 2:nrow(met_data)) { | ||
|
|
||
| met_data$SUMFLIGHTDAY[row] = ifelse(met_data$PROPFLIGHTDAY[row] + met_data$SUMFLIGHTDAY[row - 1] > 14, 0, met_data$PROPFLIGHTDAY[row] + met_data$SUMFLIGHTDAY[row - 1]) | ||
|
|
||
| } | ||
|
|
||
| met_data['CURPROPFLIGHTDAY'] <- 0 | ||
|
|
||
| for (row in 1:nrow(met_data)) { | ||
|
|
||
| met_data$CURPROPFLIGHTDAY[row] = ifelse(met_data$PROPFLIGHTDAY[row] > 0, 1, met_data$CURPROPFLIGHTDAY[row]) | ||
|
|
||
| } | ||
|
|
||
| met_data['CURSUMFLIGHTDAY'] <- 0 | ||
|
|
||
| met_data$CURSUMFLIGHTDAY[1] = met_data$CURPROPFLIGHTDAY[1] | ||
|
|
||
| for (row in 2:nrow(met_data)) { | ||
|
|
||
| met_data$CURSUMFLIGHTDAY[row] = ifelse(met_data$CURPROPFLIGHTDAY[row] + met_data$CURSUMFLIGHTDAY[row - 1] > 14, 0, met_data$CURPROPFLIGHTDAY[row] + met_data$CURSUMFLIGHTDAY[row - 1]) | ||
|
|
||
| } | ||
|
|
||
| write.csv(met_data,'D:/Coursework/PACCAR/VarroaPOP/Beepop/Simulations/Richland.csv', row.names = FALSE) | ||
|
|