insect_phenology_model: insect_phenology

comparison insect_phenology_model.R @ 26:3c06cab3db2c draft

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author	greg
date	Thu, 09 Nov 2017 11:30:27 -0500
parents	5354a82ed295
children	24949e72f7ec

comparison

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-:3852133fb058
+:3c06cab3db2c
 parser <- OptionParser(usage="%prog [options] file", option_list=option_list)
 args <- parse_args(parser, positional_arguments=TRUE)
 opt <- args$options
-get_temperature_file_path=function(loc, temperature_data)
+convert_csv_to_rdata=function(loc, temperature_data)
 {
-expdata <- matrix(rep(0, opt$num_days * 3), nrow=opt$num_days)
+expdata <- matrix(rep(0, opt$num_days * 6), nrow=opt$num_days)
 expdata[,1] <- c(1:opt$num_days)
 # Minimum
-expdata[,2] <- temperature_data[c(1:opt$num_days), 3]
+expdata[,2] <- temperature_data[c(1:opt$num_days), 5]
 # Maximum
-expdata[,3] <- temperature_data[c(1:opt$num_days), 2]
+expdata[,3] <- temperature_data[c(1:opt$num_days), 6]
-date <- temperature_data[1, 3]
+namedat <- "tempdata.Rdat"
-year <- substr(date, 1, 4)
-namedat <- paste(loc,  year, ".Rdat", sep="")
 save(expdata, file=namedat)
 namedat
 }
 daylength=function(latitude, num_days)
 {
-# from Forsythe 1995
+# From Forsythe 1995.
 p=0.8333
 dl <- NULL
 for (i in 1:num_days) {
 theta <- 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (i - 186)))
 phi <- asin(0.39795 * cos(theta))
 dl[i] <- 24 - 24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi)))
 }
-# return a vector of daylength for the number of
+# Return a vector of daylength for the number of
-# days specifie din the input temperature data
+# days specified in the input temperature data.
 dl
 }
 hourtemp=function(latitude, date, temperature_file_path, num_days)
 {
 load(temperature_file_path)
-# base development threshold for BMSB
+# Base development threshold for Brown Marmolated Stink Bug
+# insect phenology model.
 threshold <- 14.17
 dnp <- expdata[date, 2]  # daily minimum
 dxp <- expdata[date, 3]  # daily maximum
 dmean <- 0.5 * (dnp + dxp)
 dd <- 0  # initialize degree day accumulation
 if (dxp<threshold) {
 dd <- 0
 }
 else {
-# extract daylength data for the number of
+# Extract daylength data for the number of
-# days specified in the input temperature data
+# days specified in the input temperature data.
 dlprofile <- daylength(latitude, num_days)
-T <- NULL  # initialize hourly temperature
+# Initialize hourly temperature.
-dh <- NULL #initialize degree hour vector
+T <- NULL
-# calculate daylength in given date
+# Initialize degree hour vector.
+dh <- NULL
+# Calculate daylength in given date.
 y <- dlprofile[date]
-# night length
+# Night length.
 z <- 24 - y
-# lag coefficient
+# Lag coefficient.
 a <- 1.86
-# night coefficient
+# Night coefficient.
 b <- 2.20
-# sunrise time
+# Sunrise time.
 risetime <- 12 - y / 2
-# sunset time
+# Sunset time.
 settime <- 12 + y / 2
 ts <- (dxp - dnp) * sin(pi * (settime - 5) / (y + 2 * a)) + dnp
 for (i in 1:24) {
 if (i > risetime && i<settime) {
-# number of hours after Tmin until sunset
+# Number of hours after Tmin until sunset.
 m <- i - 5
 T[i]=(dxp - dnp) * sin(pi * m / (y + 2 * a)) + dnp
 if (T[i]<8.4) {
 dh[i] <- 0
 }
 }
 return = mort.prob
 return
 }
-cat("Replications: ", opt$replications, "\n")
-cat("Photoperiod: ", opt$photoperiod, "\n")
-cat("Oviposition rate: ", opt$oviposition, "\n")
-cat("Egg mortality rate: ", opt$egg_mort, "\n")
-cat("Nymph mortality rate: ", opt$nymph_mort, "\n")
-cat("Adult mortality rate: ", opt$adult_mort, "\n")
-cat("Min clutch size: ", opt$min_clutch_size, "\n")
-cat("Max clutch size: ", opt$max_clutch_size, "\n")
-cat("(egg->young nymph): ", opt$young_nymph_accum, "\n")
-cat("(young nymph->old nymph): ", opt$old_nymph_accum, "\n")
-cat("(old nymph->adult): ", opt$adult_accum, "\n")
 # Read in the input temperature datafile into a Data Frame object.
 temperature_data <- read.csv(file=opt$input, header=T, sep=",")
-temperature_file_path <- get_temperature_file_path(opt$location, temperature_data)
+temperature_file_path <- convert_csv_to_rdata(opt$location, temperature_data)
 latitude <- temperature_data[1, 1]
+cat("Number of days: ", opt$num_days, ", ")
+cat("Latitude: ", latitude, "\n")
+cat("Replications: ", opt$replications, ", ")
+cat("Photoperiod: ", opt$photoperiod, "\n")
+cat("Oviposition rate: ", opt$oviposition, ", ")
+cat("Egg mortality rate: ", opt$egg_mort, "\n")
+cat("Nymph mortality rate: ", opt$nymph_mort, ", ")
+cat("Adult mortality rate: ", opt$adult_mort, "\n")
+cat("Min clutch size: ", opt$min_clutch_size, ", ")
+cat("Max clutch size: ", opt$max_clutch_size, "\n")
+cat("(egg->young nymph): ", opt$young_nymph_accum, ", ")
+cat("(young nymph->old nymph): ", opt$old_nymph_accum, "\n")
+cat("(old nymph->adult): ", opt$adult_accum
 # Initialize matrix for results from all replications
 S0.rep <- S1.rep <- S2.rep <- S3.rep <- S4.rep <- S5.rep <- matrix(rep(0, opt$num_days * opt$replications), ncol = opt$replications)
 newborn.rep <- death.rep <- adult.rep <- pop.rep <- g0.rep <- g1.rep <- g2.rep <- g0a.rep <- g1a.rep <- g2a.rep <- matrix(rep(0, opt$num_days * opt$replications), ncol=opt$replications)
 # loop through replications
 for (N.rep in 1:opt$replications) {
-# during each replication
+# During each replication start with 1000 individuals.
-# start with 1000 individuals -- user definable as well?
+# TODO: user definable as well?
 n <- 1000
-# Generation, Stage, DD, T, Diapause
+# Generation, Stage, DD, T, Diapause.
 vec.ini <- c(0, 3, 0, 0, 0)
-# overwintering, previttelogenic, DD=0, T=0, no-diapause
+# Overwintering, previttelogenic, DD=0, T=0, no-diapause.
 vec.mat <- rep(vec.ini, n)
-# complete matrix for the population
+# Complete matrix for the population.
-vec.mat <- t(matrix(vec.mat, nrow=5))
+vec.mat <- base::t(matrix(vec.mat, nrow=5))
-# complete photoperiod profile in a year, requires daylength function
+# Complete photoperiod profile in a year, requires daylength function.
 ph.p <- daylength(latitude, opt$num_days)
-# time series of population size
+# Time series of population size.
 tot.pop <- NULL
-# gen.0 pop size
 gen0.pop <- rep(0, opt$num_days)
 gen1.pop <- rep(0, opt$num_days)
 gen2.pop <- rep(0, opt$num_days)
 S0 <- S1 <- S2 <- S3 <- S4 <- S5 <- rep(0, opt$num_days)
 g0.adult <- g1.adult <- g2.adult <- rep(0, opt$num_days)
 N.newborn <- N.death <- N.adult <- rep(0, opt$num_days)
 dd.day <- rep(0, opt$num_days)
-# start tick
-ptm <- proc.time()
 # All the days included in the input temperature dataset.
 for (day in 1:opt$num_days) {
-# photoperiod in the day
+# Photoperiod in the day.
 photoperiod <- ph.p[day]
 temp.profile <- hourtemp(latitude, day, temperature_file_path, opt$num_days)
 mean.temp <- temp.profile[1]
 dd.temp <- temp.profile[2]
 dd.day[day] <- dd.temp
-# trash bin for death
+# Trash bin for death.
 death.vec <- NULL
-# new born
+# Newborn.
 birth.vec <- NULL
-# all individuals
+# All individuals.
 for (i in 1:n) {
-# find individual record
+# Find individual record.
 vec.ind <- vec.mat[i,]
-# first of all, still alive?
+# First of all, still alive?
-# adjustment for late season mortality rate
+# Adjustment for late season mortality rate.
 if (latitude < 40.0) {
 post.mort <- 1
 day.kill <- 300
 }
 else {
 post.mort <- 2
 day.kill <- 250
 }
 if (vec.ind[2] == 0) {
-# egg
+# Egg.
 death.prob = opt$egg_mort * mortality.egg(mean.temp)
 }
 else if (vec.ind[2] == 1 | vec.ind[2] == 2) {
 death.prob = opt$nymph_mort * mortality.nymph(mean.temp)
 }
 else if (vec.ind[2] == 3 | vec.ind[2] == 4 | vec.ind[2] == 5) {
-# for adult
+# For adult.
 if (day < day.kill) {
 death.prob = opt$adult_mort * mortality.adult(mean.temp)
 }
 else {
-# increase adult mortality after fall equinox
+# Increase adult mortality after fall equinox.
 death.prob = opt$adult_mort * post.mort * mortality.adult(mean.temp)
 }
 }
 # (or dependent on temperature and life stage?)
 u.d <- runif(1)
 if (u.d < death.prob) {
 death.vec <- c(death.vec, i)
 }
 else {
-# aggregrate index of dead bug
+# Aggregrate index of dead bug.
-# event 1 end of diapause
+# Event 1 end of diapause.
 if (vec.ind[1] == 0 && vec.ind[2] == 3) {
-# overwintering adult (previttelogenic)
+# Overwintering adult (previttelogenic).
 if (photoperiod > opt$photoperiod && vec.ind[3] > 68 && day < 180) {
-# add 68C to become fully reproductively matured
+# Add 68C to become fully reproductively matured.
-# transfer to vittelogenic
+# Transfer to vittelogenic.
 vec.ind <- c(0, 4, 0, 0, 0)
 vec.mat[i,] <- vec.ind
 }
 else {
-# add to DD
+# Add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 vec.mat[i,] <- vec.ind
 }
 }
 if (vec.ind[1] != 0 && vec.ind[2] == 3) {
-# NOT overwintering adult (previttelogenic)
+# Not overwintering adult (previttelogenic).
 current.gen <- vec.ind[1]
 if (vec.ind[3] > 68) {
-# add 68C to become fully reproductively matured
+# Add 68C to become fully reproductively matured.
-# transfer to vittelogenic
+# Transfer to vittelogenic.
 vec.ind <- c(current.gen, 4, 0, 0, 0)
 vec.mat[i,] <- vec.ind
 }
 else {
-# add to DD
+# Add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 vec.mat[i,] <- vec.ind
 }
 }
-# event 2 oviposition -- where population dynamics comes from
+# Event 2 oviposition -- where population dynamics comes from.
 if (vec.ind[2] == 4 && vec.ind[1] == 0 && mean.temp > 10) {
-# vittelogenic stage, overwintering generation
+# Vittelogenic stage, overwintering generation.
 if (vec.ind[4] == 0) {
-# just turned in vittelogenic stage
+# Just turned in vittelogenic stage.
 n.birth=round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size))
 }
 else {
-# daily probability of birth
+# Daily probability of birth.
 p.birth = opt$oviposition * 0.01
 u1 <- runif(1)
 if (u1 < p.birth) {
 n.birth=round(runif(1, 2, 8))
 }
 }
-# add to DD
+# Add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 vec.mat[i,] <- vec.ind
 if (n.birth > 0) {
-# add new birth -- might be in different generations
+# Add new birth -- might be in different generations.
-# generation + 1
 new.gen <- vec.ind[1] + 1
-# egg profile
+# Egg profile.
 new.ind <- c(new.gen, 0, 0, 0, 0)
 new.vec <- rep(new.ind, n.birth)
-# update batch of egg profile
+# Update batch of egg profile.
 new.vec <- t(matrix(new.vec, nrow=5))
-# group with total eggs laid in that day
+# Group with total eggs laid in that day.
 birth.vec <- rbind(birth.vec, new.vec)
 }
 }
-# event 2 oviposition -- for gen 1.
+# Event 2 oviposition -- for gen 1.
 if (vec.ind[2] == 4 && vec.ind[1] == 1 && mean.temp > 12.5 && day < 222) {
-# vittelogenic stage, 1st generation
+# Vittelogenic stage, 1st generation
 if (vec.ind[4] == 0) {
-# just turned in vittelogenic stage
+# Just turned in vittelogenic stage.
 n.birth=round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size))
 }
 else {
-# daily probability of birth
+# Daily probability of birth.
 p.birth = opt$oviposition * 0.01
 u1 <- runif(1)
 if (u1 < p.birth) {
 n.birth = round(runif(1, 2, 8))
 }
 }
-# add to DD
+# Add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 vec.mat[i,] <- vec.ind
 if (n.birth > 0) {
-# add new birth -- might be in different generations
+# Add new birth -- might be in different generations.
-# generation + 1
 new.gen <- vec.ind[1] + 1
-# egg profile
+# Egg profile.
 new.ind <- c(new.gen, 0, 0, 0, 0)
 new.vec <- rep(new.ind, n.birth)
-# update batch of egg profile
+# Update batch of egg profile.
 new.vec <- t(matrix(new.vec, nrow=5))
-# group with total eggs laid in that day
+# Group with total eggs laid in that day.
 birth.vec <- rbind(birth.vec, new.vec)
 }
 }
-# event 3 development (with diapause determination)
+# Event 3 development (with diapause determination).
-# event 3.1 egg development to young nymph (vec.ind[2]=0 -> egg)
+# Event 3.1 egg development to young nymph (vec.ind[2]=0 -> egg).
 if (vec.ind[2] == 0) {
-# egg stage
+# Egg stage.
-# add to DD
+# Add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
 if (vec.ind[3] >= (68 + opt$young_nymph_accum)) {
-# from egg to young nymph, DD requirement met
+# From egg to young nymph, DD requirement met.
 current.gen <- vec.ind[1]
-# transfer to young nym stage
+# Transfer to young nymph stage.
 vec.ind <- c(current.gen, 1, 0, 0, 0)
 }
 else {
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 }
 vec.mat[i,] <- vec.ind
 }
-# event 3.2 young nymph to old nymph (vec.ind[2]=1 -> young nymph: determines diapause)
+# Event 3.2 young nymph to old nymph (vec.ind[2]=1 -> young nymph: determines diapause).
 if (vec.ind[2] == 1) {
-# young nymph stage
+# young nymph stage.
-# add to DD
+# add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
 if (vec.ind[3] >= (250 + opt$old_nymph_accum)) {
-# from young to old nymph, DD requirement met
+# From young to old nymph, dd requirement met.
 current.gen <- vec.ind[1]
-# transfer to old nym stage
+# Transfer to old nym stage.
 vec.ind <- c(current.gen, 2, 0, 0, 0)
 if (photoperiod < opt$photoperiod && day > 180) {
 vec.ind[5] <- 1
-} # prepare for diapausing
+} # Prepare for diapausing.
 }
 else {
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 }
 vec.mat[i,] <- vec.ind
 }
-# event 3.3 old nymph to adult: previttelogenic or diapausing?
+# Event 3.3 old nymph to adult: previttelogenic or diapausing?
 if (vec.ind[2] == 2) {
-# old nymph stage
+# Old nymph stage.
-# add to DD
+# add to dd.
 vec.ind[3] <- vec.ind[3] + dd.temp
 if (vec.ind[3] >= (200 + opt$adult_accum)) {
-# from old to adult, DD requirement met
+# From old to adult, dd requirement met.
 current.gen <- vec.ind[1]
 if (vec.ind[5] == 0) {
-# non-diapausing adult -- previttelogenic
+# Non-diapausing adult -- previttelogenic.
 vec.ind <- c(current.gen, 3, 0, 0, 0)
 }
 else {
-# diapausing
+# Diapausing.
 vec.ind <- c(current.gen, 5, 0, 0, 1)
 }
 }
 else {
-# add 1 day in current stage
+# Add 1 day in current stage.
 vec.ind[4] <- vec.ind[4] + 1
 }
 vec.mat[i,] <- vec.ind
 }
-# event 4 growing of diapausing adult (unimportant, but still necessary)##
+# Event 4 growing of diapausing adult (unimportant, but still necessary).
 if (vec.ind[2] == 5) {
 vec.ind[3] <- vec.ind[3] + dd.temp
 vec.ind[4] <- vec.ind[4] + 1
 vec.mat[i,] <- vec.ind
 }
-} # else if it is still alive
+} # Else if it is still alive.
-} # end of the individual bug loop
+} # End of the individual bug loop.
-# find how many died
+# Find how many died.
 n.death <- length(death.vec)
 if (n.death > 0) {
 vec.mat <- vec.mat[-death.vec, ]
 }
-# remove record of dead
+# Remove record of dead.
-# find how many new born
+# Find how many new born.
 n.newborn <- length(birth.vec[,1])
 vec.mat <- rbind(vec.mat, birth.vec)
-# update population size for the next day
+# Update population size for the next day.
 n <- n - n.death + n.newborn
-# aggregate results by day
+# Aggregate results by day.
 tot.pop <- c(tot.pop, n)
-# egg
+# Egg.
 s0 <- sum(vec.mat[,2] == 0)
-# young nymph
+# Young nymph.
 s1 <- sum(vec.mat[,2] == 1)
-# old nymph
+# Old nymph.
 s2 <- sum(vec.mat[,2] == 2)
-# previtellogenic
+# Previtellogenic.
 s3 <- sum(vec.mat[,2] == 3)
-# vitellogenic
+# Vitellogenic.
 s4 <- sum(vec.mat[,2] == 4)
-# diapausing
+# Diapausing.
 s5 <- sum(vec.mat[,2] == 5)
-# overwintering adult
+# Overwintering adult.
 gen0 <- sum(vec.mat[,1] == 0)
-# first generation
+# First generation.
 gen1 <- sum(vec.mat[,1] == 1)
-# second generation
+# Second generation.
 gen2 <- sum(vec.mat[,1] == 2)
-# sum of all adults
+# Sum of all adults.
 n.adult <- sum(vec.mat[,2] == 3) + sum(vec.mat[,2] == 4) + sum(vec.mat[,2] == 5)
-# gen.0 pop size
+# Gen eration 0 pop size.
 gen0.pop[day] <- gen0
 gen1.pop[day] <- gen1
 gen2.pop[day] <- gen2
 S0[day] <- s0
 S1[day] <- s1
 N.death[day] <- n.death
 N.adult[day] <- n.adult
 }   # end of days specified in the input temperature data
 dd.cum <- cumsum(dd.day)
-# collect all the outputs
+# Collect all the outputs.
 S0.rep[,N.rep] <- S0
 S1.rep[,N.rep] <- S1
 S2.rep[,N.rep] <- S2
 S3.rep[,N.rep] <- S3
 S4.rep[,N.rep] <- S4

Mercurial > repos > greg > insect_phenology_model

comparison insect_phenology_model.R @ 26:3c06cab3db2c draft