Mercurial > repos > greg > insect_phenology_model
changeset 4:e7b1fc0133bb draft
Uploaded
| author | greg |
|---|---|
| date | Mon, 13 Nov 2017 12:57:46 -0500 |
| parents | 24fa0d35a8bf |
| children | 1878a03f9c9f |
| files | insect_phenology_model.R insect_phenology_model.xml test-data/output.pdf |
| diffstat | 3 files changed, 134 insertions(+), 128 deletions(-) [+] |
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--- a/insect_phenology_model.R Thu Nov 09 14:20:42 2017 -0500 +++ b/insect_phenology_model.R Mon Nov 13 12:57:46 2017 -0500 @@ -25,63 +25,58 @@ args <- parse_args(parser, positional_arguments=TRUE) opt <- args$options -convert_csv_to_rdata=function(temperature_data, data_matrix) +get_daylight_length = function(latitude, temperature_data, num_days) { - # Integer day of the year. - data_matrix[,1] <- c(1:opt$num_days) - # Minimum - data_matrix[,2] <- temperature_data[c(1:opt$num_days), 5] - # Maximum - data_matrix[,3] <- temperature_data[c(1:opt$num_days), 6] - namedat <- "tempdata.Rdat" - save(data_matrix, file=namedat) - namedat + # 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 + daylight_length_vector <- NULL + for (i in 1:num_days) { + # Get the day of the year from the current row + # of the temperature data for computation. + doy <- temperature_data[i, 4] + 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. + daylight_length_vector[i] <- 24 - (24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi)))) + } + daylight_length_vector } -daylength=function(latitude, num_days) +get_temperature_at_hour = function(latitude, temperature_data, daylight_length_vector, row, num_days) { - # 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 - # 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 Brown Marmolated Stink Bug # insect phenology model. + # TODO: Pass insect on the command line to accomodate more + # the just the Brown Marmolated Stink Bub. threshold <- 14.17 - dnp <- data_matrix[date, 2] # daily minimum - dxp <- data_matrix[date, 3] # daily maximum + + # Input temperature currently has the following columns. + # # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX + # Minimum temperature for current row. + dnp <- temperature_data[row, 5] + # Maximum temperature for current row. + dxp <- temperature_data[row, 6] + # Mean temperature for current row. dmean <- 0.5 * (dnp + dxp) - dd <- 0 # initialize degree day accumulation - - if (dxp<threshold) { + # Initialize degree day accumulation + dd <- 0 + if (dxp < threshold) { dd <- 0 } else { - # Extract daylength data for the number of - # days specified in the input temperature data. - dlprofile <- daylength(latitude, num_days) # Initialize hourly temperature. T <- NULL # Initialize degree hour vector. dh <- NULL - # Calculate daylength in given date. - y <- dlprofile[date] - # Night length. + # Daylight length for current row. + y <- daylight_length_vector[row] + # Darkness length. z <- 24 - y # Lag coefficient. a <- 1.86 - # Night coefficient. + # Darkness coefficient. b <- 2.20 # Sunrise time. risetime <- 12 - y / 2 @@ -89,11 +84,11 @@ 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) { + if (i > risetime && i < settime) { # 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) { + T[i] = (dxp - dnp) * sin(pi * m / (y + 2 * a)) + dnp + if (T[i] < 8.4) { dh[i] <- 0 } else { @@ -102,8 +97,8 @@ } else if (i > settime) { n <- i - settime - T[i]=dnp + (ts - dnp) * exp( - b * n / z) - if (T[i]<8.4) { + T[i] = dnp + (ts - dnp) * exp( - b * n / z) + if (T[i] < 8.4) { dh[i] <- 0 } else { @@ -113,7 +108,7 @@ else { n <- i + 24 - settime T[i]=dnp + (ts - dnp) * exp( - b * n / z) - if (T[i]<8.4) { + if (T[i] < 8.4) { dh[i] <- 0 } else { @@ -199,12 +194,13 @@ } # Read in the input temperature datafile into a Data Frame object. -temperature_data <- read.csv(file=opt$input, header=T, sep=",") -start_date <- temperature_data[c(1:1), 3] -end_date <- temperature_data[c(opt$num_days:opt$num_days), 3] -raw_data_matrix <- matrix(rep(0, opt$num_days * 6), nrow=opt$num_days) -temperature_file_path <- convert_csv_to_rdata(temperature_data, raw_data_matrix) +# The input data currently must have 6 columns: +# LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX +temperature_data <- read.csv(file=opt$input, header=T, strip.white=TRUE, sep=",") +start_date <- temperature_data[1, 3] +end_date <- temperature_data[opt$num_days, 3] latitude <- temperature_data[1, 1] +daylight_length_vector <- get_daylight_length(latitude, temperature_data, opt$num_days) cat("Number of days: ", opt$num_days, "\n") @@ -223,9 +219,6 @@ vec.mat <- rep(vec.ini, n) # Complete matrix for the population. vec.mat <- base::t(matrix(vec.mat, nrow=5)) - # Complete photoperiod profile in a year, requires daylength function. - ph.p <- daylength(latitude, opt$num_days) - # Time series of population size. tot.pop <- NULL gen0.pop <- rep(0, opt$num_days) @@ -237,13 +230,15 @@ dd.day <- rep(0, opt$num_days) # All the days included in the input temperature dataset. - for (day in 1:opt$num_days) { + for (row in 1:opt$num_days) { + # Get the integer day of the year for the current row. + doy <- temperature_data[row, 4] # Photoperiod in the day. - photoperiod <- ph.p[day] - temp.profile <- hourtemp(latitude, day, temperature_file_path, opt$num_days) + photoperiod <- daylight_length_vector[row] + temp.profile <- get_temperature_at_hour(latitude, temperature_data, daylight_length_vector, row, opt$num_days) mean.temp <- temp.profile[1] dd.temp <- temp.profile[2] - dd.day[day] <- dd.temp + dd.day[row] <- dd.temp # Trash bin for death. death.vec <- NULL # Newborn. @@ -272,7 +267,7 @@ } else if (vec.ind[2] == 3 | vec.ind[2] == 4 | vec.ind[2] == 5) { # For adult. - if (day < day.kill) { + if (doy < day.kill) { death.prob = opt$adult_mort * mortality.adult(mean.temp) } else { @@ -290,7 +285,7 @@ # Event 1 end of diapause. if (vec.ind[1] == 0 && vec.ind[2] == 3) { # Overwintering adult (previttelogenic). - if (photoperiod > opt$photoperiod && vec.ind[3] > 68 && day < 180) { + if (photoperiod > opt$photoperiod && vec.ind[3] > 68 && doy < 180) { # Add 68C to become fully reproductively matured. # Transfer to vittelogenic. vec.ind <- c(0, 4, 0, 0, 0) @@ -356,7 +351,7 @@ } # Event 2 oviposition -- for gen 1. - if (vec.ind[2] == 4 && vec.ind[1] == 1 && mean.temp > 12.5 && day < 222) { + if (vec.ind[2] == 4 && vec.ind[1] == 1 && mean.temp > 12.5 && doy < 222) { # Vittelogenic stage, 1st generation if (vec.ind[4] == 0) { # Just turned in vittelogenic stage. @@ -417,7 +412,7 @@ current.gen <- vec.ind[1] # Transfer to old nym stage. vec.ind <- c(current.gen, 2, 0, 0, 0) - if (photoperiod < opt$photoperiod && day > 180) { + if (photoperiod < opt$photoperiod && doy > 180) { vec.ind[5] <- 1 } # Prepare for diapausing. } @@ -495,26 +490,30 @@ gen2 <- sum(vec.mat[,1] == 2) # Sum of all adults. n.adult <- sum(vec.mat[,2] == 3) + sum(vec.mat[,2] == 4) + sum(vec.mat[,2] == 5) - # Gen eration 0 pop size. - gen0.pop[day] <- gen0 - gen1.pop[day] <- gen1 - gen2.pop[day] <- gen2 - S0[day] <- s0 - S1[day] <- s1 - S2[day] <- s2 - S3[day] <- s3 - S4[day] <- s4 - S5[day] <- s5 - g0.adult[day] <- sum(vec.mat[,1] == 0) - g1.adult[day] <- sum((vec.mat[,1] == 1 & vec.mat[,2] == 3) | (vec.mat[,1] == 1 & vec.mat[,2] == 4) | (vec.mat[,1] == 1 & vec.mat[,2] == 5)) - g2.adult[day] <- sum((vec.mat[,1]== 2 & vec.mat[,2] == 3) | (vec.mat[,1] == 2 & vec.mat[,2] == 4) | (vec.mat[,1] == 2 & vec.mat[,2] == 5)) + + # Generation 0 pop size. + gen0.pop[row] <- gen0 + gen1.pop[row] <- gen1 + gen2.pop[row] <- gen2 - N.newborn[day] <- n.newborn - N.death[day] <- n.death - N.adult[day] <- n.adult + S0[row] <- s0 + S1[row] <- s1 + S2[row] <- s2 + S3[row] <- s3 + S4[row] <- s4 + S5[row] <- s5 + + g0.adult[row] <- sum(vec.mat[,1] == 0) + g1.adult[row] <- sum((vec.mat[,1] == 1 & vec.mat[,2] == 3) | (vec.mat[,1] == 1 & vec.mat[,2] == 4) | (vec.mat[,1] == 1 & vec.mat[,2] == 5)) + g2.adult[row] <- sum((vec.mat[,1]== 2 & vec.mat[,2] == 3) | (vec.mat[,1] == 2 & vec.mat[,2] == 4) | (vec.mat[,1] == 2 & vec.mat[,2] == 5)) + + N.newborn[row] <- n.newborn + N.death[row] <- n.death + N.adult[row] <- n.adult } # end of days specified in the input temperature data dd.cum <- cumsum(dd.day) + # Collect all the outputs. S0.rep[,N.rep] <- S0 S1.rep[,N.rep] <- S1 @@ -534,9 +533,9 @@ g2a.rep[,N.rep] <- g2.adult } -# Data analysis and visualization -# default: plot 1 year of result -# but can be expanded to accommodate multiple years +# Data analysis and visualization can currently +# plot only within a single calendar year. +# TODO: enhance this to accomodate multiple calendar years. n.yr <- 1 day.all <- c(1:opt$num_days * n.yr) @@ -578,79 +577,79 @@ # SE for F2 adult g2a.se <- apply(g2a.rep, 1, sd) / sqrt(opt$replications) -dev.new(width=20, height=20) +dev.new(width=20, height=30) # Start PDF device driver to save charts to output. -pdf(file=opt$output, height=20, width=20, bg="white") +pdf(file=opt$output, width=20, height=30, bg="white") par(mar = c(5, 6, 4, 4), mfrow=c(3, 1)) -# Subfigure 2: population size by life stage -title <- paste("BSMB Total Population Size by Life Stage:", opt$location, ", Latitude:", latitude, ", Temperature Dates:", start_date, "to", end_date, sep=" ") -plot(day.all, sa, main=title, 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) +# Subfigure 1: population size by life stage +title <- paste("BSMB total population by life stage :", opt$location, ": Lat:", latitude, ":", start_date, "to", end_date, sep=" ") +plot(day.all, sa, main=title, type="l", ylim=c(0, max(se + se.se, sn + sn.se, sa + sa.se)), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) # Young and old nymphs. lines(day.all, sn, lwd=2, lty=1, col=2) # Eggs lines(day.all, se, lwd=2, lty=1, col=4) -axis(1, at = c(1:12) * 30 - 15, cex.axis=2, labels=c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) -axis(2, cex.axis = 2) +axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels=c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +axis(2, cex.axis=3) leg.text <- c("Egg", "Nymph", "Adult") -legend("topleft", leg.text, lty=c(1, 1, 1), col=c(4, 2, 1), cex=2) +legend("topleft", leg.text, lty=c(1, 1, 1), col=c(4, 2, 1), cex=3) if (opt$se_plot == 1) { - # add SE lines to plot + # 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) + 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) + lines (day.all, se - se.se, col=4, lty=2) } -# Subfigure 3: population size by generation -title <- paste("BSMB Total Population Size by Generation:", opt$location, ", Latitude:", latitude, ", Temperature Dates:", start_date, "to", end_date, sep=" ") -plot(day.all, g0, main=title, type="l", ylim=c(0, max(g2)), axes=F, lwd=2, xlab="", ylab="Number", cex=2, cex.lab=2, cex.axis=2, cex.main=2) -lines(day.all, g1, lwd = 2, lty = 1, col = 2) -lines(day.all, g2, lwd = 2, lty = 1, col = 4) -axis(1, at = c(1:12) * 30 - 15, cex.axis = 2, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) -axis(2, cex.axis = 2) +# Subfigure 2: population size by generation +title <- paste("BSMB total population by generation :", opt$location, ": Lat:", latitude, ":", start_date, "to", end_date, sep=" ") +plot(day.all, g0, main=title, type="l", ylim=c(0, max(g2)), axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) +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=3, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +axis(2, cex.axis=3) leg.text <- c("P", "F1", "F2") -legend("topleft", leg.text, lty = c(1, 1, 1), col =c(1, 2, 4), cex = 2) +legend("topleft", leg.text, lty=c(1, 1, 1), col=c(1, 2, 4), cex=3) if (opt$se_plot == 1) { - # add SE lines to plot + # Add SE lines to plot # SE for adults - lines (day.all, g0 + g0.se, lty = 2) - lines (day.all, g0 - g0.se, lty = 2) + lines (day.all, g0+g0.se, lty=2) + lines (day.all, g0-g0.se, lty=2) # SE for nymphs - lines (day.all, g1 + g1.se, col = 2, lty = 2) - lines (day.all, g1 - g1.se, col = 2, lty = 2) + lines (day.all, g1+g1.se, col=2, lty=2) + lines (day.all, g1-g1.se, col=2, lty=2) # SE for eggs - lines (day.all, g2 + g2.se, col = 4, lty = 2) - lines (day.all, g2 - g2.se, col = 4, lty = 2) + lines (day.all, g2+g2.se, col=4, lty=2) + lines (day.all, g2-g2.se, col=4, lty=2) } -# Subfigure 4: adult population size by generation -title <- paste("BSMB Adult Population Size by Generation:", opt$location, ", Latitude:", latitude, ", Temperature Dates:", start_date, "to", end_date, sep=" ") -plot(day.all, g0a, ylim=c(0, max(g2a) + 100), main=title, 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) +# Subfigure 3: adult population size by generation +title <- paste("BSMB adult population by generation :", opt$location, ": Lat:", latitude, ":", start_date, "to", end_date, sep=" ") +plot(day.all, g0a, ylim=c(0, max(g2a) + 100), main=title, type="l", axes=F, lwd=2, xlab="", ylab="", cex=3, cex.lab=3, cex.axis=3, cex.main=3) +lines(day.all, g1a, lwd = 2, lty = 1, col=2) +lines(day.all, g2a, lwd = 2, lty = 1, col=4) +axis(1, at=c(1:12) * 30 - 15, cex.axis=3, labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec")) +axis(2, cex.axis=3) leg.text <- c("P", "F1", "F2") -legend("topleft", leg.text, lty = c(1, 1, 1), col = c(1, 2, 4), cex = 2) +legend("topleft", leg.text, lty=c(1, 1, 1), col=c(1, 2, 4), cex=3) if (opt$se_plot == 1) { - # add SE lines to plot + # Add SE lines to plot # SE for adults - lines (day.all, g0a + g0a.se, lty = 2) - lines (day.all, g0a - g0a.se, lty = 2) + 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) + 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) + 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.
--- a/insect_phenology_model.xml Thu Nov 09 14:20:42 2017 -0500 +++ b/insect_phenology_model.xml Mon Nov 13 12:57:46 2017 -0500 @@ -1,8 +1,7 @@ -<?xml version="."?> <tool id="insect_phenology_model" name="Insect phenology model" version="1.1.0"> <description>expressing stage-specific phenology and population dynamics</description> <requirements> - <requirement type="package" version="1.4.4">r-optparse</requirement> + <requirement type="package" version="1.4.4">r-optparse</requirement> </requirements> <command detect_errors="exit_code"><![CDATA[ Rscript '$__tool_directory__/insect_phenology_model.R' @@ -21,11 +20,10 @@ -s $replications -t $se_plot -v '$input' --y $young_nymph_accum - ]]></command> +-y $young_nymph_accum]]></command> <inputs> + <param name="input" type="data" format="csv" label="Temperature data" /> <param name="location" type="text" value="" optional="false" label="Location" /> - <param name="input" type="data" format="csv" label="Temperature data" /> <param name="replications" type="integer" value="10" min="1" label="Number of replications" /> <param name="photoperiod" type="float" value="13.5" min="0" label="Critical photoperiod for diapause induction/termination" /> <param name="egg_mort" type="integer" value="1" min="0" label="Adjustment rate for egg mortality" />
--- a/test-data/output.pdf Thu Nov 09 14:20:42 2017 -0500 +++ b/test-data/output.pdf Mon Nov 13 12:57:46 2017 -0500 @@ -1,5 +1,6 @@ 1 0 obj << +/Title (R Graphics Output) /Creator (R) >> endobj @@ -9,8 +10,12 @@ 7 0 obj << /Type /Page /Parent 3 0 R /Contents 8 0 R /Resources 4 0 R >> endobj +8 0 obj +<< +>> +stream 3 0 obj -<< /Type /Pages /Kids [ 7 0 R ] /Count 1 /MediaBox [0 0 1440 1440] >> +<< /Type /Pages /Kids [ 7 0 R ] /Count 1 /MediaBox [0 0 1440 2160] >> endobj 4 0 obj << @@ -23,6 +28,10 @@ 5 0 obj [/ICCBased 6 0 R] endobj +6 0 obj +<< /Alternate /DeviceRGB /N 3 /Length 2596 /Filter /FlateDecode >> +stream +endobj 9 0 obj << /Type /Encoding /BaseEncoding /WinAnsiEncoding @@ -39,7 +48,7 @@ << /Type /Font /Subtype /Type1 /Name /F3 /BaseFont /Helvetica-Bold /Encoding 9 0 R >> endobj +xref trailer << /Size 12 /Info 1 0 R /Root 2 0 R >> startxref -%%EOF