Mercurial > repos > greg > insect_phenology_model
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author | greg |
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date | Tue, 13 Feb 2018 13:53:37 -0500 |
parents | fe3f86012394 |
children | 61bc6bd8807d |
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#!/usr/bin/env Rscript suppressPackageStartupMessages(library("optparse")) option_list <- list( make_option(c("--adult_mortality"), action="store", dest="adult_mortality", type="integer", help="Adjustment rate for adult mortality"), make_option(c("--adult_accumulation"), action="store", dest="adult_accumulation", type="integer", help="Adjustment of degree-days accumulation (old nymph->adult)"), make_option(c("--egg_mortality"), action="store", dest="egg_mortality", type="integer", help="Adjustment rate for egg mortality"), make_option(c("--input"), action="store", dest="input", help="Temperature data for selected location"), make_option(c("--insect"), action="store", dest="insect", help="Insect name"), make_option(c("--insects_per_replication"), action="store", dest="insects_per_replication", type="integer", help="Number of insects with which to start each replication"), make_option(c("--location"), action="store", dest="location", help="Selected location"), make_option(c("--min_clutch_size"), action="store", dest="min_clutch_size", type="integer", help="Adjustment of minimum clutch size"), make_option(c("--max_clutch_size"), action="store", dest="max_clutch_size", type="integer", help="Adjustment of maximum clutch size"), make_option(c("--nymph_mortality"), action="store", dest="nymph_mortality", type="integer", help="Adjustment rate for nymph mortality"), make_option(c("--old_nymph_accumulation"), action="store", dest="old_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (young nymph->old nymph)"), make_option(c("--num_days"), action="store", dest="num_days", type="integer", help="Total number of days in the temperature dataset"), make_option(c("--output"), action="store", dest="output", help="Output dataset"), make_option(c("--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"), make_option(c("--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"), make_option(c("--replications"), action="store", dest="replications", type="integer", help="Number of replications"), make_option(c("--std_error_plot"), action="store", dest="std_error_plot", help="Plot Standard error"), make_option(c("--young_nymph_accumulation"), action="store", dest="young_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (egg->young nymph)") ) parser <- OptionParser(usage="%prog [options] file", option_list=option_list); args <- parse_args(parser, positional_arguments=TRUE); opt <- args$options; add_daylight_length = function(temperature_data_frame, num_columns, num_rows) { # Return a vector of daylight length (photoperido profile) for # the number of days specified in the input temperature data # (from Forsythe 1995). p = 0.8333; latitude = temperature_data_frame$LATITUDE[1]; daylight_length_vector = NULL; for (i in 1:num_rows) { # Get the day of the year from the current row # of the temperature data for computation. doy = temperature_data_frame$DOY[i]; theta = 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (doy - 186))); phi = asin(0.39795 * cos(theta)); # Compute the length of daylight for the day of the year. darkness_length = 24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi))); daylight_length_vector[i] = 24 - darkness_length; } # Append daylight_length_vector as a new column to temperature_data_frame. temperature_data_frame[, num_columns+1] = daylight_length_vector; return(temperature_data_frame); } dev.egg = function(temperature) { dev.rate = -0.9843 * temperature + 33.438; return(dev.rate); } dev.emerg = function(temperature) { emerg.rate = -0.5332 * temperature + 24.147; return(emerg.rate); } dev.old = function(temperature) { n34 = -0.6119 * temperature + 17.602; n45 = -0.4408 * temperature + 19.036; dev.rate = mean(n34 + n45); return(dev.rate); } dev.young = function(temperature) { n12 = -0.3728 * temperature + 14.68; n23 = -0.6119 * temperature + 25.249; dev.rate = mean(n12 + n23); return(dev.rate); } get_date_labels = function(temperature_data_frame, num_rows) { # Keep track of the years to see if spanning years. month_labels = list(); current_month_label = NULL; for (i in 1:num_rows) { # Get the year and month from the date which # has the format YYYY-MM-DD. date = format(temperature_data_frame$DATE[i]); items = strsplit(date, "-")[[1]]; month = items[2]; month_label = month.abb[as.integer(month)]; if (!identical(current_month_label, month_label)) { month_labels[length(month_labels)+1] = month_label; current_month_label = month_label; } } return(c(unlist(month_labels))); } get_temperature_at_hour = function(latitude, temperature_data_frame, row, num_days) { # Base development threshold for Brown Marmorated Stink Bug # insect phenology model. threshold = 14.17; # Minimum temperature for current row. curr_min_temp = temperature_data_frame$TMIN[row]; # Maximum temperature for current row. curr_max_temp = temperature_data_frame$TMAX[row]; # Mean temperature for current row. curr_mean_temp = 0.5 * (curr_min_temp + curr_max_temp); # Initialize degree day accumulation averages = 0; if (curr_max_temp < threshold) { averages = 0; } else { # Initialize hourly temperature. T = NULL; # Initialize degree hour vector. dh = NULL; # Daylight length for current row. y = temperature_data_frame$DAYLEN[row]; # Darkness length. z = 24 - y; # Lag coefficient. a = 1.86; # Darkness coefficient. b = 2.20; # Sunrise time. risetime = 12 - y / 2; # Sunset time. settime = 12 + y / 2; ts = (curr_max_temp - curr_min_temp) * sin(pi * (settime - 5) / (y + 2 * a)) + curr_min_temp; for (i in 1:24) { if (i > risetime && i < settime) { # Number of hours after Tmin until sunset. m = i - 5; T[i] = (curr_max_temp - curr_min_temp) * sin(pi * m / (y + 2 * a)) + curr_min_temp; if (T[i] < 8.4) { dh[i] = 0; } else { dh[i] = T[i] - 8.4; } } else if (i > settime) { n = i - settime; T[i] = curr_min_temp + (ts - curr_min_temp) * 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] = curr_min_temp + (ts - curr_min_temp) * exp( - b * n / z); if (T[i] < 8.4) { dh[i] = 0; } else { dh[i] = T[i] - 8.4; } } } averages = sum(dh) / 24; } return(c(curr_mean_temp, averages)) } mortality.adult = function(temperature) { if (temperature < 12.7) { mortality.probability = 0.002; } else { mortality.probability = temperature * 0.0005 + 0.02; } return(mortality.probability) } mortality.egg = function(temperature) { if (temperature < 12.7) { mortality.probability = 0.8; } else { mortality.probability = 0.8 - temperature / 40.0; if (mortality.probability < 0) { mortality.probability = 0.01; } } return(mortality.probability) } mortality.nymph = function(temperature) { if (temperature < 12.7) { mortality.probability = 0.03; } else { mortality.probability = temperature * 0.0008 + 0.03; } return(mortality.probability); } parse_input_data = function(input_file, num_rows) { # Read in the input temperature datafile into a data frame. temperature_data_frame = read.csv(file=input_file, header=T, strip.white=TRUE, sep=","); num_columns = dim(temperature_data_frame)[2]; if (num_columns == 6) { # The input data has the following 6 columns: # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX # Set the column names for access when adding daylight length.. colnames(temperature_data_frame) = c("LATITUDE","LONGITUDE", "DATE", "DOY", "TMIN", "TMAX"); # Add a column containing the daylight length for each day. temperature_data_frame = add_daylight_length(temperature_data_frame, num_columns, num_rows); # Reset the column names with the additional column for later access. colnames(temperature_data_frame) = c("LATITUDE","LONGITUDE", "DATE", "DOY", "TMIN", "TMAX", "DAYLEN"); } return(temperature_data_frame); } render_chart = function(chart_type, insect, location, latitude, start_date, end_date, days, maxval, plot_std_error, group1, group2, group3, group1_std_error, group2_std_error, group3_std_error, date_labels) { if (chart_type == "pop_size_by_life_stage") { title = paste(insect, ": Total pop. by life stage :", location, ": Lat:", latitude, ":", start_date, "-", end_date, sep=" "); legend_text = c("Egg", "Nymph", "Adult"); columns = c(4, 2, 1); } else if (chart_type == "pop_size_by_generation") { title = paste(insect, ": Total pop. by generation :", location, ": Lat:", latitude, ":", start_date, "-", end_date, sep=" "); legend_text = c("P", "F1", "F2"); columns = c(1, 2, 4); } else if (chart_type == "adult_pop_size_by_generation") { title = paste(insect, ": Adult pop. by generation :", location, ": Lat:", latitude, ":", start_date, "-", end_date, sep=" "); legend_text = c("P", "F1", "F2"); columns = c(1, 2, 4); } plot(days, group1, main=title, type="l", ylim=c(0, maxval), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3); legend("topleft", legend_text, lty=c(1, 1, 1), col=columns, cex=3); lines(days, group2, lwd=2, lty=1, col=2); lines(days, group3, lwd=2, lty=1, col=4); axis(1, at=c(1:length(date_labels)) * 30 - 15, cex.axis=3, labels=date_labels); axis(2, cex.axis=3); if (plot_std_error==1) { # Standard error for group1. lines(days, group1+group1_std_error, lty=2); lines(days, group1-group1_std_error, lty=2); # Standard error for group2. lines(days, group2+group2_std_error, col=2, lty=2); lines(days, group2-group2_std_error, col=2, lty=2); # Standard error for group3. lines(days, group3+group3_std_error, col=4, lty=2); lines(days, group3-group3_std_error, col=4, lty=2); } } temperature_data_frame = parse_input_data(opt$input, opt$num_days); # All latitude values are the same, so get the value from the first row. latitude = temperature_data_frame$LATITUDE[1]; num_columns = dim(temperature_data_frame)[2]; date_labels = get_date_labels(temperature_data_frame, opt$num_days); # Initialize matrices. Eggs.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); YoungNymphs.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); OldNymphs.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); Previtellogenic.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); Vitellogenic.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); Diapausing.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); newborn.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); adult.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); death.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); P.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); P_adults.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); F1.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); F1_adults.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); F2.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); F2_adults.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); population.replications = matrix(rep(0, opt$num_days*opt$replications), ncol=opt$replications); # Process replications. for (N.replications in 1:opt$replications) { # Start with the user-defined number of insects per replication. num_insects = opt$insects_per_replication; # Generation, Stage, degree-days, T, Diapause. vector.ini = c(0, 3, 0, 0, 0); # Overwintering, previttelogenic, degree-days=0, T=0, no-diapause. vector.matrix = rep(vector.ini, num_insects); # Complete matrix for the population. vector.matrix = base::t(matrix(vector.matrix, nrow=5)); # Time series of population size. Eggs = rep(0, opt$num_days); YoungNymphs = rep(0, opt$num_days); OldNymphs = rep(0, opt$num_days); Previtellogenic = rep(0, opt$num_days); Vitellogenic = rep(0, opt$num_days); Diapausing = rep(0, opt$num_days); N.newborn = rep(0, opt$num_days); N.adult = rep(0, opt$num_days); N.death = rep(0, opt$num_days); overwintering_adult.population = rep(0, opt$num_days); first_generation.population = rep(0, opt$num_days); second_generation.population = rep(0, opt$num_days); P.adult = rep(0, opt$num_days); F1.adult = rep(0, opt$num_days); F2.adult = rep(0, opt$num_days); total.population = NULL; averages.day = rep(0, opt$num_days); # All the days included in the input temperature dataset. for (row in 1:opt$num_days) { # Get the integer day of the year for the current row. doy = temperature_data_frame$DOY[row]; # Photoperiod in the day. photoperiod = temperature_data_frame$DAYLEN[row]; temp.profile = get_temperature_at_hour(latitude, temperature_data_frame, row, opt$num_days); mean.temp = temp.profile[1]; averages.temp = temp.profile[2]; averages.day[row] = averages.temp; # Trash bin for death. death.vector = NULL; # Newborn. birth.vector = NULL; # All individuals. for (i in 1:num_insects) { # Individual record. vector.individual = vector.matrix[i,]; # Adjustment for late season mortality rate (still alive?). if (latitude < 40.0) { post.mortality = 1; day.kill = 300; } else { post.mortality = 2; day.kill = 250; } if (vector.individual[2] == 0) { # Egg. death.probability = opt$egg_mortality * mortality.egg(mean.temp); } else if (vector.individual[2] == 1 | vector.individual[2] == 2) { death.probability = opt$nymph_mortality * mortality.nymph(mean.temp); } else if (vector.individual[2] == 3 | vector.individual[2] == 4 | vector.individual[2] == 5) { # Adult. if (doy < day.kill) { death.probability = opt$adult_mortality * mortality.adult(mean.temp); } else { # Increase adult mortality after fall equinox. death.probability = opt$adult_mortality * post.mortality * mortality.adult(mean.temp); } } # Dependent on temperature and life stage? u.d = runif(1); if (u.d < death.probability) { death.vector = c(death.vector, i); } else { # End of diapause. if (vector.individual[1] == 0 && vector.individual[2] == 3) { # Overwintering adult (previttelogenic). if (photoperiod > opt$photoperiod && vector.individual[3] > 68 && doy < 180) { # Add 68C to become fully reproductively matured. # Transfer to vittelogenic. vector.individual = c(0, 4, 0, 0, 0); vector.matrix[i,] = vector.individual; } else { # Add to # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; vector.matrix[i,] = vector.individual; } } if (vector.individual[1] != 0 && vector.individual[2] == 3) { # Not overwintering adult (previttelogenic). current.gen = vector.individual[1]; if (vector.individual[3] > 68) { # Add 68C to become fully reproductively matured. # Transfer to vittelogenic. vector.individual = c(current.gen, 4, 0, 0, 0); vector.matrix[i,] = vector.individual; } else { # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; vector.matrix[i,] = vector.individual; } } # Oviposition -- where population dynamics comes from. if (vector.individual[2] == 4 && vector.individual[1] == 0 && mean.temp > 10) { # Vittelogenic stage, overwintering generation. if (vector.individual[4] == 0) { # Just turned in vittelogenic stage. num_insects.birth = round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size)); } else { # Daily probability of birth. p.birth = opt$oviposition * 0.01; u1 = runif(1); if (u1 < p.birth) { num_insects.birth = round(runif(1, 2, 8)); } } # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; vector.matrix[i,] = vector.individual; if (num_insects.birth > 0) { # Add new birth -- might be in different generations. new.gen = vector.individual[1] + 1; # Egg profile. new.individual = c(new.gen, 0, 0, 0, 0); new.vector = rep(new.individual, num_insects.birth); # Update batch of egg profile. new.vector = t(matrix(new.vector, nrow=5)); # Group with total eggs laid in that day. birth.vector = rbind(birth.vector, new.vector); } } # Oviposition -- for generation 1. if (vector.individual[2] == 4 && vector.individual[1] == 1 && mean.temp > 12.5 && doy < 222) { # Vittelogenic stage, 1st generation if (vector.individual[4] == 0) { # Just turned in vittelogenic stage. num_insects.birth = round(runif(1, 2+opt$min_clutch_size, 8+opt$max_clutch_size)); } else { # Daily probability of birth. p.birth = opt$oviposition * 0.01; u1 = runif(1); if (u1 < p.birth) { num_insects.birth = round(runif(1, 2, 8)); } } # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; vector.matrix[i,] = vector.individual; if (num_insects.birth > 0) { # Add new birth -- might be in different generations. new.gen = vector.individual[1] + 1; # Egg profile. new.individual = c(new.gen, 0, 0, 0, 0); new.vector = rep(new.individual, num_insects.birth); # Update batch of egg profile. new.vector = t(matrix(new.vector, nrow=5)); # Group with total eggs laid in that day. birth.vector = rbind(birth.vector, new.vector); } } # Egg to young nymph. if (vector.individual[2] == 0) { # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; if (vector.individual[3] >= (68+opt$young_nymph_accumulation)) { # From egg to young nymph, degree-days requirement met. current.gen = vector.individual[1]; # Transfer to young nymph stage. vector.individual = c(current.gen, 1, 0, 0, 0); } else { # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; } vector.matrix[i,] = vector.individual; } # Young nymph to old nymph. if (vector.individual[2] == 1) { # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; if (vector.individual[3] >= (250+opt$old_nymph_accumulation)) { # From young to old nymph, degree_days requirement met. current.gen = vector.individual[1]; # Transfer to old nym stage. vector.individual = c(current.gen, 2, 0, 0, 0); if (photoperiod < opt$photoperiod && doy > 180) { vector.individual[5] = 1; } # Prepare for diapausing. } else { # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; } vector.matrix[i,] = vector.individual; } # Old nymph to adult: previttelogenic or diapausing? if (vector.individual[2] == 2) { # Add average temperature for current day. vector.individual[3] = vector.individual[3] + averages.temp; if (vector.individual[3] >= (200+opt$adult_accumulation)) { # From old to adult, degree_days requirement met. current.gen = vector.individual[1]; if (vector.individual[5] == 0) { # Previttelogenic. vector.individual = c(current.gen, 3, 0, 0, 0); } else { # Diapausing. vector.individual = c(current.gen, 5, 0, 0, 1); } } else { # Add 1 day in current stage. vector.individual[4] = vector.individual[4] + 1; } vector.matrix[i,] = vector.individual; } # Growing of diapausing adult (unimportant, but still necessary). if (vector.individual[2] == 5) { vector.individual[3] = vector.individual[3] + averages.temp; vector.individual[4] = vector.individual[4] + 1; vector.matrix[i,] = vector.individual; } } # Else if it is still alive. } # End of the individual bug loop. # Number of deaths. num_insects.death = length(death.vector); if (num_insects.death > 0) { # Remove record of dead. vector.matrix = vector.matrix[-death.vector,]; } # Number of births. num_insects.newborn = length(birth.vector[,1]); vector.matrix = rbind(vector.matrix, birth.vector); # Update population size for the next day. num_insects = num_insects - num_insects.death + num_insects.newborn; # Aggregate results by day. # Egg population size. Eggs[row] = sum(vector.matrix[,2]==0); # Young nymph population size. YoungNymphs[row] = sum(vector.matrix[,2]==1); # Old nymph population size. OldNymphs[row] = sum(vector.matrix[,2]==2); # Previtellogenic population size. Previtellogenic[row] = sum(vector.matrix[,2]==3); # Vitellogenic population size. Vitellogenic[row] = sum(vector.matrix[,2]==4); # Diapausing population size. Diapausing[row] = sum(vector.matrix[,2]==5); # Newborn population size. N.newborn[row] = num_insects.newborn; # Adult population size. N.adult[row] = sum(vector.matrix[,2]==3) + sum(vector.matrix[,2]==4) + sum(vector.matrix[,2]==5); # Dead population size. N.death[row] = num_insects.death; total.population = c(total.population, num_insects); # Overwintering adult population size. overwintering_adult.population[row] = sum(vector.matrix[,1]==0); # First generation population size. first_generation.population[row] = sum(vector.matrix[,1]==1); # Second generation population size. second_generation.population[row] = sum(vector.matrix[,1]==2); # P adult population size. P.adult[row] = sum(vector.matrix[,1]==0); # F1 adult population size. F1.adult[row] = sum((vector.matrix[,1]==1 & vector.matrix[,2]==3) | (vector.matrix[,1]==1 & vector.matrix[,2]==4) | (vector.matrix[,1]==1 & vector.matrix[,2]==5)); # F2 adult population size F2.adult[row] = sum((vector.matrix[,1]==2 & vector.matrix[,2]==3) | (vector.matrix[,1]==2 & vector.matrix[,2]==4) | (vector.matrix[,1]==2 & vector.matrix[,2]==5)); } # End of days specified in the input temperature data. averages.cum = cumsum(averages.day); # Define the output values. Eggs.replications[,N.replications] = Eggs; YoungNymphs.replications[,N.replications] = YoungNymphs; OldNymphs.replications[,N.replications] = OldNymphs; Previtellogenic.replications[,N.replications] = Previtellogenic; Vitellogenic.replications[,N.replications] = Vitellogenic; Diapausing.replications[,N.replications] = Diapausing; newborn.replications[,N.replications] = N.newborn; adult.replications[,N.replications] = N.adult; death.replications[,N.replications] = N.death; P.replications[,N.replications] = overwintering_adult.population; P_adults.replications[,N.replications] = P.adult; F1.replications[,N.replications] = first_generation.population; F1_adults.replications[,N.replications] = F1.adult; F2.replications[,N.replications] = second_generation.population; F2_adults.replications[,N.replications] = F2.adult; population.replications[,N.replications] = total.population; } # Mean value for eggs. eggs = apply(Eggs.replications, 1, mean); # Standard error for eggs. eggs.std_error = apply(Eggs.replications, 1, sd) / sqrt(opt$replications); # Mean value for nymphs. nymphs = apply((YoungNymphs.replications+OldNymphs.replications), 1, mean); # Standard error for nymphs. nymphs.std_error = apply((YoungNymphs.replications+OldNymphs.replications) / sqrt(opt$replications), 1, sd); # Mean value for adults. adults = apply((Previtellogenic.replications+Vitellogenic.replications+Diapausing.replications), 1, mean); # Standard error for adults. adults.std_error = apply((Previtellogenic.replications+Vitellogenic.replications+Diapausing.replications), 1, sd) / sqrt(opt$replications); # Mean value for P. P = apply(P.replications, 1, mean); # Standard error for P. P.std_error = apply(P.replications, 1, sd) / sqrt(opt$replications); # Mean value for P adults. P_adults = apply(P_adults.replications, 1, mean); # Standard error for P_adult. P_adults.std_error = apply(P_adults.replications, 1, sd) / sqrt(opt$replications); # Mean value for F1. F1 = apply(F1.replications, 1, mean); # Standard error for F1. F1.std_error = apply(F1.replications, 1, sd) / sqrt(opt$replications); # Mean value for F1 adults. F1_adults = apply(F1_adults.replications, 1, mean); # Standard error for F1 adult. F1_adults.std_error = apply(F1_adults.replications, 1, sd) / sqrt(opt$replications); # Mean value for F2. F2 = apply(F2.replications, 1, mean); # Standard error for F2. F2.std_error = apply(F2.replications, 1, sd) / sqrt(opt$replications); # Mean value for F2 adults. F2_adults = apply(F2_adults.replications, 1, mean); # Standard error for F2 adult. F2_adults.std_error = apply(F2_adults.replications, 1, sd) / sqrt(opt$replications); # Display the total number of days in the Galaxy history item blurb. cat("Number of days: ", opt$num_days, "\n"); dev.new(width=20, height=30); # Start PDF device driver to save charts to output. pdf(file=opt$output, width=20, height=30, bg="white"); par(mar=c(5, 6, 4, 4), mfrow=c(3, 1)); # Data analysis and visualization plots only within a single calendar year. days = c(1:opt$num_days); start_date = temperature_data_frame$DATE[1]; end_date = temperature_data_frame$DATE[opt$num_days]; # Subfigure 1: population size by life stage. maxval = max(eggs+eggs.std_error, nymphs+nymphs.std_error, adults+adults.std_error); render_chart("pop_size_by_life_stage", opt$insect, opt$location, latitude, start_date, end_date, days, maxval, opt$std_error_plot, adults, nymphs, eggs, adults.std_error, nymphs.std_error, eggs.std_error, date_labels); # Subfigure 2: population size by generation. maxval = max(F2); render_chart("pop_size_by_generation", opt$insect, opt$location, latitude, start_date, end_date, days, maxval, opt$std_error_plot, P, F1, F2, P.std_error, F1.std_error, F2.std_error, date_labels); # Subfigure 3: adult population size by generation. maxval = max(F2_adults) + 100; render_chart("adult_pop_size_by_generation", opt$insect, opt$location, latitude, start_date, end_date, days, maxval, opt$std_error_plot, P_adults, F1_adults, F2_adults, P_adults.std_error, F1_adults.std_error, F2_adults.std_error, date_labels); # Turn off device driver to flush output. dev.off();