bmsb: bmsb.R comparison

comparison bmsb.R @ 33:390ed5192839 draft

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author	greg
date	Fri, 16 Dec 2016 08:50:54 -0500
parents
children	7c40c2b303f1

comparison

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-:7418fc8f0780
+:390ed5192839
+#!/usr/bin/env Rscript
+suppressPackageStartupMessages(library("optparse"))
+option_list <- list(
+make_option(c("-a", "--adult_mort"), action="store", dest="adult_mort", type="integer", help="Adjustment rate for adult mortality"),
+make_option(c("-b", "--adult_nymph_accum"), action="store", dest="adult_nymph_accum", type="integer", help="Adjustment of DD accumulation (old nymph->adult)"),
+make_option(c("-c", "--egg_mort"), action="store", dest="egg_mort", type="integer", help="Adjustment rate for egg mortality"),
+make_option(c("-d", "--latitude"), action="store", dest="latitude", type="double", help="Latitude of selected location"),
+make_option(c("-e", "--location"), action="store", dest="location", help="Selected location"),
+make_option(c("-f", "--min_clutch_size"), action="store", dest="min_clutch_size", type="integer", help="Adjustment of minimum clutch size"),
+make_option(c("-g", "--max_clutch_size"), action="store", dest="max_clutch_size", type="integer", help="Adjustment of maximum clutch size"),
+make_option(c("-j", "--nymph_mort"), action="store", dest="nymph_mort", type="integer", help="Adjustment rate for nymph mortality"),
+make_option(c("-k", "--old_nymph_accum"), action="store", dest="old_nymph_accum", type="integer", help="Adjustment of DD accumulation (young nymph->old nymph)"),
+make_option(c("-o", "--output"), action="store", dest="output", help="Output dataset"),
+make_option(c("-p", "--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"),
+make_option(c("-q", "--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"),
+make_option(c("-s", "--replications"), action="store", dest="replications", type="integer", help="Number of replications"),
+make_option(c("-t", "--se_plot"), action="store", dest="se_plot", help="Plot SE"),
+make_option(c("-u", "--year"), action="store", dest="year", type="integer", help="Starting year"),
+make_option(c("-v", "--temperature_dataset"), action="store", dest="temperature_dataset", help="Temperature data for selected location"),
+make_option(c("-y", "--young_nymph_accum"), action="store", dest="young_nymph_accum", type="integer", help="Adjustment of DD accumulation (egg->young nymph)")
+)
+parser <- OptionParser(usage="%prog [options] file", option_list=option_list)
+args <- parse_args(parser, positional_arguments=TRUE)
+opt <- args$options
+data.input=function(loc, start.yr, temperature.dataset)
+{
+expdata <- matrix(rep(0, 365 * 3), nrow=365)
+# replace 2004 with start. yr
+yr <- start.yr
+namedat <- paste(loc,  yr, ".Rdat", sep="")
+temp.data <- read.csv(file=temperature.dataset, header=T)
+expdata[,1] <- c(1:365)
+save(expdata, file=namedat)
+namedat
+}
+daylength=function(L)
+{
+# from Forsythe 1995
+p=0.8333
+dl <- NULL
+for (i in 1:365)
+{
+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(L * pi / 180) * sin(phi)) / (cos(L * pi / 180) * cos(phi)))
+}
+dl   # return a vector of daylength in 365 days
+}
+hourtemp=function(L, date, temperature_file_path)
+{
+load(temperature_file_path)
+threshold <- 14.17  # base development threshold for BMSB
+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
+{
+dlprofile <- daylength(L)  # extract daylength data for entire year
+T <- NULL  # initialize hourly temperature
+dh <- NULL #initialize degree hour vector
+# date <- 200
+y <- dlprofile[date]  # calculate daylength in given date
+z <- 24 - y     # night length
+a <- 1.86     # lag coefficient
+b <- 2.20     # night coefficient
+#tempdata <- read.csv("tempdata.csv") #import raw data set
+# Should be outside function otherwise its redundant
+risetime <- 12 - y / 2      # sunrise time
+settime <- 12 + y / 2       # sunset time
+ts <- (dxp - dnp) * sin(pi * (settime - 5) / (y + 2 * a)) + dnp
+for (i in 1:24)
+{
+if (i > risetime && i<settime)
+{
+m <- i - 5  # number of hours after Tmin until sunset
+T[i]=(dxp - dnp) * sin(pi * m / (y + 2 * a)) + dnp
+if (T[i]<8.4)
+{
+dh[i] <- 0
+}
+else
+{
+dh[i] <- T[i] - 8.4
+}
+}
+else if (i > settime)
+{
+n <- i - settime
+T[i]=dnp + (ts - dnp) * exp( - b * n / z)
+if (T[i]<8.4)
+{
+dh[i] <- 0
+}
+else
+{
+dh[i] <- T[i] - 8.4
+}
+}
+else
+{
+n <- i + 24 - settime
+T[i]=dnp + (ts - dnp) * exp( - b * n / z)
+if (T[i]<8.4)
+{
+dh[i] <- 0
+}
+else
+{
+dh[i] <- T[i] - 8.4
+}
+}
+}
+dd <- sum(dh) / 24
+}
+return=c(dmean, dd)
+return
+}
+dev.egg = function(temperature)
+{
+dev.rate= -0.9843 * temperature + 33.438
+return = dev.rate
+return
+}
+dev.young = function(temperature)
+{
+n12 <- -0.3728 * temperature + 14.68
+n23 <- -0.6119 * temperature + 25.249
+dev.rate = mean(n12 + n23)
+return = dev.rate
+return
+}
+dev.old = function(temperature)
+{
+n34 <- -0.6119 * temperature + 17.602
+n45 <- -0.4408 * temperature + 19.036
+dev.rate = mean(n34 + n45)
+return = dev.rate
+return
+}
+dev.emerg = function(temperature)
+{
+emerg.rate <- -0.5332 * temperature + 24.147
+return=emerg.rate
+return
+}
+mortality.egg=function(temperature)
+{
+if (temperature<12.7)
+{
+mort.prob = 0.8
+}
+else
+{
+mort.prob = 0.8 - temperature / 40.0
+if (mort.prob<0)
+{
+mort.prob=0.01
+}
+}
+return=mort.prob
+return
+}
+mortality.nymph=function(temperature)
+{
+if (temperature<12.7)
+{
+mort.prob=0.03
+}
+else
+{
+mort.prob=temperature * 0.0008 + 0.03
+}
+return=mort.prob
+return
+}
+mortality.adult=function(temperature)
+{
+if (temperature<12.7)
+{
+mort.prob=0.002
+}
+else
+{
+mort.prob=temperature * 0.0005 + 0.02
+}
+return=mort.prob
+return
+}
+# Read in the input temperature datafile
+temperature_file_path <- data.input(opt$location, opt$year, opt$temperature_dataset)
+# Initialize matrix for results from all replications
+S0.rep <- S1.rep <- S2.rep <- S3.rep <- S4.rep <- S5.rep <- matrix(rep(0, 365 * 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, 365 * opt$replications), ncol=opt$replications)
+# loop through replications
+for (N.rep in 1:opt$replications)
+{
+# during each replication
+# start with 1000 individuals -- user definable as well?
+n <- 1000
+# Generation, Stage, DD, T, Diapause
+vec.ini <- c(0, 3, 0, 0, 0)
+# overwintering, previttelogenic, DD=0, T=0, no-diapause
+vec.mat <- rep(vec.ini, n)
+# complete matrix for the population
+vec.mat <- t(matrix(vec.mat, nrow=5))
+# complete photoperiod profile in a year, requires daylength function
+ph.p <- daylength(opt$latitude)
+# time series of population size
+tot.pop <- NULL
+# gen.0 pop size
+gen0.pop <- rep(0, 365)
+gen1.pop <- rep(0, 365)
+gen2.pop <- rep(0, 365)
+S0 <- S1 <- S2 <- S3 <- S4 <- S5 <- rep(0, 365)
+g0.adult <- g1.adult <- g2.adult <- rep(0, 365)
+N.newborn <- N.death <- N.adult <- rep(0, 365)
+dd.day <- rep(0, 365)
+# start tick
+ptm <- proc.time()
+# all the days
+for (day in 1:365)
+{
+# photoperiod in the day
+photoperiod <- ph.p[day]
+temp.profile <- hourtemp(opt$latitude, day, temperature_file_path)
+mean.temp <- temp.profile[1]
+dd.temp <- temp.profile[2]
+dd.day[day] <- dd.temp
+# trash bin for death
+death.vec <- NULL
+# new born
+birth.vec <- NULL
+# all individuals
+for (i in 1:n)
+{
+# find individual record
+vec.ind <- vec.mat[i,]
+# first of all, still alive?
+# adjustment for late season mortality rate
+if (opt$latitude < 40.0)
+{
+post.mort <- 1
+day.kill <- 300
+}
+else
+{
+post.mort <- 2
+day.kill <- 250
+}
+if (vec.ind[2] == 0)
+{
+# 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
+if (day < day.kill)
+{
+death.prob = opt$adult_mort * mortality.adult(mean.temp)
+}
+else
+{
+# increase adult mortality after fall equinox
+death.prob = opt$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
+# event 1 end of diapause
+if (vec.ind[1] == 0 && vec.ind[2] == 3)
+{
+# overwintering adult (previttelogenic)
+if (photoperiod > opt$photoperiod && vec.ind[3] > 68 && day < 180)
+{
+# add 68C to become fully reproductively matured
+# transfer to vittelogenic
+vec.ind <- c(0, 4, 0, 0, 0)
+vec.mat[i,] <- vec.ind
+}
+else
+{
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+# add 1 day in current stage
+vec.ind[4] <- vec.ind[4] + 1
+vec.mat[i,] <- vec.ind
+}
+}
+if (vec.ind[1] != 0 && vec.ind[2] == 3)
+{
+# NOT overwintering adult (previttelogenic)
+current.gen <- vec.ind[1]
+if (vec.ind[3] > 68)
+{
+# add 68C to become fully reproductively matured
+# transfer to vittelogenic
+vec.ind <- c(current.gen, 4, 0, 0, 0)
+vec.mat[i,] <- vec.ind
+}
+else
+{
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+# add 1 day in current stage
+vec.ind[4] <- vec.ind[4] + 1
+vec.mat[i,] <- vec.ind
+}
+}
+# event 2 oviposition -- where population dynamics comes from
+if (vec.ind[2] == 4 && vec.ind[1] == 0 && mean.temp > 10)
+{
+# vittelogenic stage, overwintering generation
+if (vec.ind[4] == 0)
+{
+# just turned in vittelogenic stage
+n.birth=round(runif(1, 2 + min.ovi.adj, 8 + max.ovi.adj))
+}
+else
+{
+# daily probability of birth
+p.birth = opt$oviposition * 0.01
+u1 <- runif(1)
+if (u1 < p.birth)
+{
+n.birth=round(runif(1, 2, 8))
+}
+}
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+# 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
+# generation + 1
+new.gen <- vec.ind[1] + 1
+# egg profile
+new.ind <- c(new.gen, 0, 0, 0, 0)
+new.vec <- rep(new.ind, n.birth)
+# update batch of egg profile
+new.vec <- t(matrix(new.vec, nrow=5))
+# group with total eggs laid in that day
+birth.vec <- rbind(birth.vec, new.vec)
+}
+}
+# 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
+if (vec.ind[4] == 0)
+{
+# just turned in vittelogenic stage
+n.birth=round(runif(1, 2 + min.ovi.adj, 8 + max.ovi.adj))
+}
+else
+{
+# daily probability of birth
+p.birth = opt$oviposition * 0.01
+u1 <- runif(1)
+if (u1 < p.birth)
+{
+n.birth = round(runif(1, 2, 8))
+}
+}
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+# add 1 day in current stage
+vec.ind[4] <- vec.ind[4] + 1
+vec.mat[i,] <- vec.ind
+if (n.birth > 0)
+{
+# add new birth -- might be in different generations
+# generation + 1
+new.gen <- vec.ind[1] + 1
+# egg profile
+new.ind <- c(new.gen, 0, 0, 0, 0)
+new.vec <- rep(new.ind, n.birth)
+# update batch of egg profile
+new.vec <- t(matrix(new.vec, nrow=5))
+# group with total eggs laid in that day
+birth.vec <- rbind(birth.vec, new.vec)
+}
+}
+# event 3 development (with diapause determination)
+# event 3.1 egg development to young nymph (vec.ind[2]=0 -> egg)
+if (vec.ind[2] == 0)
+{
+# egg stage
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+if (vec.ind[3] >= (68 + dd.adj1))
+{
+# from egg to young nymph, DD requirement met
+current.gen <- vec.ind[1]
+# transfer to young nym stage
+vec.ind <- c(current.gen, 1, 0, 0, 0)
+}
+else
+{
+# add 1 day in current stage
+vec.ind[4] <- vec.ind[4] + 1
+}
+vec.mat[i,] <- vec.ind
+}
+# event 3.2 young nymph to old nymph (vec.ind[2]=1 -> young nymph: determines diapause)
+if (vec.ind[2] == 1)
+{
+# young nymph stage
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+if (vec.ind[3] >= (250 +dd.adj2))
+{
+# from young to old nymph, DD requirement met
+current.gen <- vec.ind[1]
+# transfer to old nym stage
+vec.ind <- c(current.gen, 2, 0, 0, 0)
+if (photoperiod < opt$photoperiod && day > 180)
+{
+vec.ind[5] <- 1
+} # prepare for diapausing
+}
+else
+{
+# 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?
+if (vec.ind[2] == 2)
+{
+# old nymph stage
+# add to DD
+vec.ind[3] <- vec.ind[3] + dd.temp
+if (vec.ind[3] >= (200 + dd.adj3))
+{
+# from old to adult, DD requirement met
+current.gen <- vec.ind[1]
+if (vec.ind[5] == 0)
+{
+# non-diapausing adult -- previttelogenic
+vec.ind <- c(current.gen, 3, 0, 0, 0)
+}
+else
+{
+# diapausing
+vec.ind <- c(current.gen, 5, 0, 0, 1)
+}
+}
+else
+{
+# 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)##
+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
+} # end of the individual bug loop
+# find how many died
+n.death <- length(death.vec)
+if (n.death > 0)
+{
+vec.mat <- vec.mat[-death.vec, ]
+}
+# remove record of dead
+# 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
+n <- n - n.death + n.newborn
+# aggregate results by day
+tot.pop <- c(tot.pop, n)
+# egg
+s0 <- sum(vec.mat[,2] == 0)
+# young nymph
+s1 <- sum(vec.mat[,2] == 1)
+# old nymph
+s2 <- sum(vec.mat[,2] == 2)
+# previtellogenic
+s3 <- sum(vec.mat[,2] == 3)
+# vitellogenic
+s4 <- sum(vec.mat[,2] == 4)
+# diapausing
+s5 <- sum(vec.mat[,2] == 5)
+# overwintering adult
+gen0 <- sum(vec.mat[,1] == 0)
+# first generation
+gen1 <- sum(vec.mat[,1] == 1)
+# second generation
+gen2 <- sum(vec.mat[,1] == 2)
+# 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
+gen0.pop[day] <- gen0
+gen1.pop[day] <- gen1
+gen2.pop[day] <- gen2
+S0[day] <- s0
+S1[day] <- s1
+S2[day] <- s2
+S3[day] <- s3
+S4[day] <- s4
+S5[day] <- s5
+g0.adult[day] <- sum(vec.mat[,1] == 0)
+g1.adult[day] <- sum((vec.mat[,1] == 1 & vec.mat[,2] == 3) | (vec.mat[,1] == 1 & vec.mat[,2] == 4) | (vec.mat[,1] == 1 & vec.mat[,2] == 5))
+g2.adult[day] <- sum((vec.mat[,1]== 2 & vec.mat[,2] == 3) | (vec.mat[,1] == 2 & vec.mat[,2] == 4) | (vec.mat[,1] == 2 & vec.mat[,2] == 5))
+N.newborn[day] <- n.newborn
+N.death[day] <- n.death
+N.adult[day] <- n.adult
+#print(c(N.rep, day, n, n.adult))
+}   # end of 365 days
+dd.cum <- cumsum(dd.day)
+# 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
+S5.rep[,N.rep] <- S5
+newborn.rep[,N.rep] <- N.newborn
+death.rep[,N.rep] <- N.death
+adult.rep[,N.rep] <- N.adult
+pop.rep[,N.rep] <- tot.pop
+g0.rep[,N.rep] <- gen0.pop
+g1.rep[,N.rep] <- gen1.pop
+g2.rep[,N.rep] <- gen2.pop
+g0a.rep[,N.rep] <- g0.adult
+g1a.rep[,N.rep] <- g1.adult
+g2a.rep[,N.rep] <- g2.adult
+}
+# save(dd.day, dd.cum, S0.rep, S1.rep, S2.rep, S3.rep, S4.rep, S5.rep, newborn.rep, death.rep, adult.rep, pop.rep, g0.rep, g1.rep, g2.rep, g0a.rep, g1a.rep, g2a.rep, file=opt$output)
+# maybe do not need to export this bit, but for now just leave it as-is
+# do we need to export this Rdat file?
+# Data analysis and visualization
+# default: plot 1 year of result
+# but can be expanded to accommodate multiple years
+n.yr <- 1
+day.all <- c(1:365 * n.yr)
+# mean value for adults
+sa <- apply((S3.rep + S4.rep + S5.rep), 1, mean)
+# mean value for nymphs
+sn <- apply((S1.rep + S2.rep), 1,mean)
+# mean value for eggs
+se <- apply(S0.rep, 1, mean)
+# mean value for P
+g0 <- apply(g0.rep, 1, mean)
+# mean value for F1
+g1 <- apply(g1.rep, 1, mean)
+# mean value for F2
+g2 <- apply(g2.rep, 1, mean)
+# mean value for P adult
+g0a <- apply(g0a.rep, 1, mean)
+# mean value for F1 adult
+g1a <- apply(g1a.rep, 1, mean)
+# mean value for F2 adult
+g2a <- apply(g2a.rep, 1, mean)
+# SE for adults
+sa.se <- apply((S3.rep + S4.rep + S5.rep), 1, sd) / sqrt(opt$replications)
+# SE for nymphs
+sn.se <- apply((S1.rep + S2.rep) / sqrt(opt$replications), 1, sd)
+# SE for eggs
+se.se <- apply(S0.rep ,1 ,sd) / sqrt(opt$replications)
+# SE value for P
+g0.se <- apply(g0.rep, 1, sd) / sqrt(opt$replications)
+# SE for F1
+g1.se <- apply(g1.rep, 1, sd) / sqrt(opt$replications)
+# SE for F2
+g2.se <- apply(g2.rep, 1, sd) / sqrt(opt$replications)
+# SE for P adult
+g0a.se <- apply(g0a.rep, 1, sd) / sqrt(opt$replications)
+# SE for F1 adult
+g1a.se <- apply(g1a.rep, 1, sd) / sqrt(opt$replications)
+# SE for F2 adult
+g2a.se <- apply(g2a.rep, 1, sd) / sqrt(opt$replications)
+dev.new(width = 9, height = 9)
+# Start PDF device driver to save charts to output.
+pdf(file=opt$output, height=20, width=20, bg="white")
+par(mar = c(5, 6, 4, 4), mfrow=c(3, 1))
+# Subfigure 2: population size by life stage
+plot(day.all, sa, main = "Total Population Size by Life Stage", type = "l", ylim = c(0, max(se + se.se, sn + sn.se, sa + sa.se)), axes = F, lwd = 2, xlab = "", ylab = "Number", cex = 2, cex.lab = 2, cex.axis = 2, cex.main = 2)
+# Young and old nymphs
+lines(day.all, sn, lwd = 2, lty = 1, col = 2)
+# Eggs
+lines(day.all, se, lwd = 2, lty = 1, col = 4)
+axis(1, at = c(1:12) * 30 - 15, cex.axis = 2, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"))
+axis(2, cex.axis = 2)
+leg.text <- c("Egg", "Nymph", "Adult")
+legend("topleft", leg.text, lty = c(1, 1, 1), col = c(4, 2, 1), cex = 2)
+if (opt$se_plot == 1)
+{
+# add SE lines to plot
+# SE for adults
+lines (day.all, sa + sa.se, lty = 2)
+lines (day.all, sa - sa.se, lty = 2)
+# SE for nymphs
+lines (day.all, sn + sn.se, col = 2, lty = 2)
+lines (day.all, sn - sn.se, col = 2, lty = 2)
+# SE for eggs
+lines (day.all, se + se.se, col = 4, lty = 2)
+lines (day.all, se - se.se, col = 4, lty = 2)
+}
+# Subfigure 3: population size by generation
+plot(day.all, g0, main = "Total Population Size by Generation", type = "l", ylim = c(0, max(g2)), axes = F, lwd = 2, xlab = "", ylab = "Number", cex = 2, cex.lab = 2, cex.axis = 2, cex.main = 2)
+lines(day.all, g1, lwd = 2, lty = 1, col = 2)
+lines(day.all, g2, lwd = 2, lty = 1, col = 4)
+axis(1, at = c(1:12) * 30 - 15, cex.axis = 2, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"))
+axis(2, cex.axis = 2)
+leg.text <- c("P", "F1", "F2")
+legend("topleft", leg.text, lty = c(1, 1, 1), col =c(1, 2, 4), cex = 2)
+if (opt$se_plot == 1)
+{
+# add SE lines to plot
+# SE for adults
+lines (day.all, g0 + g0.se, lty = 2)
+lines (day.all, g0 - g0.se, lty = 2)
+# SE for nymphs
+lines (day.all, g1 + g1.se, col = 2, lty = 2)
+lines (day.all, g1 - g1.se, col = 2, lty = 2)
+# SE for eggs
+lines (day.all, g2 + g2.se, col = 4, lty = 2)
+lines (day.all, g2 - g2.se, col = 4, lty = 2)
+}
+# Subfigure 4: adult population size by generation
+plot(day.all, g0a, ylim = c(0, max(g2a) + 100), main = "Adult Population Size by Generation", type = "l", axes = F, lwd = 2, xlab = "Year", ylab = "Number", cex = 2, cex.lab = 2, cex.axis = 2, cex.main = 2)
+lines(day.all, g1a, lwd = 2, lty = 1, col = 2)
+lines(day.all, g2a, lwd = 2, lty = 1, col = 4)
+axis(1, at = c(1:12) * 30 - 15, cex.axis = 2, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"))
+axis(2, cex.axis = 2)
+leg.text <- c("P", "F1", "F2")
+legend("topleft", leg.text, lty = c(1, 1, 1), col = c(1, 2, 4), cex = 2)
+if (opt$se_plot == 1)
+{
+# add SE lines to plot
+# SE for adults
+lines (day.all, g0a + g0a.se, lty = 2)
+lines (day.all, g0a - g0a.se, lty = 2)
+# SE for nymphs
+lines (day.all, g1a + g1a.se, col = 2, lty = 2)
+lines (day.all, g1a - g1a.se, col = 2, lty = 2)
+# SE for eggs
+lines (day.all, g2a + g2a.se, col = 4, lty = 2)
+lines (day.all, g2a - g2a.se, col = 4, lty = 2)
+}
+# Turn off device driver to flush output.
+dev.off()

Mercurial > repos > greg > bmsb

comparison bmsb.R @ 33:390ed5192839 draft