5
+ − 1 #!/usr/bin/env Rscript
+ − 2
+ − 3 suppressPackageStartupMessages(library("optparse"))
+ − 4
+ − 5 option_list <- list(
6
+ − 6 make_option(c("--adult_mortality"), action="store", dest="adult_mortality", type="integer", help="Adjustment rate for adult mortality"),
+ − 7 make_option(c("--adult_accumulation"), action="store", dest="adult_accumulation", type="integer", help="Adjustment of degree-days accumulation (old nymph->adult)"),
+ − 8 make_option(c("--egg_mortality"), action="store", dest="egg_mortality", type="integer", help="Adjustment rate for egg mortality"),
38
+ − 9 make_option(c("--input_norm"), action="store", dest="input_norm", help="30 year normals temperature data for selected station"),
43
+ − 10 make_option(c("--input_ytd"), action="store", dest="input_ytd", default=NULL, help="Year-to-date temperature data for selected location"),
6
+ − 11 make_option(c("--insect"), action="store", dest="insect", help="Insect name"),
+ − 12 make_option(c("--insects_per_replication"), action="store", dest="insects_per_replication", type="integer", help="Number of insects with which to start each replication"),
10
+ − 13 make_option(c("--life_stages"), action="store", dest="life_stages", help="Selected life stages for plotting"),
+ − 14 make_option(c("--life_stages_adult"), action="store", dest="life_stages_adult", default=NULL, help="Adult life stages for plotting"),
16
+ − 15 make_option(c("--life_stages_nymph"), action="store", dest="life_stages_nymph", default=NULL, help="Nymph life stages for plotting"),
45
+ − 16 make_option(c("--location"), action="store", dest="location", default=NULL, help="Selected location"),
6
+ − 17 make_option(c("--min_clutch_size"), action="store", dest="min_clutch_size", type="integer", help="Adjustment of minimum clutch size"),
+ − 18 make_option(c("--max_clutch_size"), action="store", dest="max_clutch_size", type="integer", help="Adjustment of maximum clutch size"),
43
+ − 19 make_option(c("--num_days_ytd"), action="store", dest="num_days_ytd", default=NULL, type="integer", help="Total number of days in the year-to-date temperature dataset"),
6
+ − 20 make_option(c("--nymph_mortality"), action="store", dest="nymph_mortality", type="integer", help="Adjustment rate for nymph mortality"),
+ − 21 make_option(c("--old_nymph_accumulation"), action="store", dest="old_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (young nymph->old nymph)"),
+ − 22 make_option(c("--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"),
+ − 23 make_option(c("--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"),
10
+ − 24 make_option(c("--plot_generations_separately"), action="store", dest="plot_generations_separately", help="Plot Plot P, F1 and F2 as separate lines or pool across them"),
+ − 25 make_option(c("--plot_std_error"), action="store", dest="plot_std_error", help="Plot Standard error"),
27
+ − 26 make_option(c("--replications"), action="store", dest="replications", type="integer", help="Number of replications"),
50
+ − 27 make_option(c("--script_dir"), action="store", dest="script_dir", help="R script source directory"),
6
+ − 28 make_option(c("--young_nymph_accumulation"), action="store", dest="young_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (egg->young nymph)")
5
+ − 29 )
+ − 30
8
+ − 31 parser <- OptionParser(usage="%prog [options] file", option_list=option_list);
+ − 32 args <- parse_args(parser, positional_arguments=TRUE);
+ − 33 opt <- args$options;
5
+ − 34
49
+ − 35 add_daylight_length = function(temperature_data_frame) {
+ − 36 # Return temperature_data_frame with an added column
50
+ − 37 # of daylight length (photoperiod profile).
49
+ − 38 num_rows = dim(temperature_data_frame)[1];
8
+ − 39 latitude = temperature_data_frame$LATITUDE[1];
+ − 40 daylight_length_vector = NULL;
5
+ − 41 for (i in 1:num_rows) {
+ − 42 # Get the day of the year from the current row
+ − 43 # of the temperature data for computation.
8
+ − 44 doy = temperature_data_frame$DOY[i];
56
+ − 45 daylight_length_vector[i] = get_daylen(doy, latitude);
5
+ − 46 }
+ − 47 # Append daylight_length_vector as a new column to temperature_data_frame.
27
+ − 48 temperature_data_frame = append_vector(temperature_data_frame, daylight_length_vector, "DAYLEN");
8
+ − 49 return(temperature_data_frame);
5
+ − 50 }
+ − 51
27
+ − 52 append_vector = function(data_frame, vec, new_column_name) {
+ − 53 num_columns = dim(data_frame)[2];
+ − 54 current_column_names = colnames(data_frame);
+ − 55 # Append vector vec as a new column to data_frame.
+ − 56 data_frame[,num_columns+1] = vec;
+ − 57 # Reset the column names with the additional column for later access.
+ − 58 colnames(data_frame) = append(current_column_names, new_column_name);
+ − 59 return(data_frame);
+ − 60 }
+ − 61
49
+ − 62 from_30_year_normals = function(norm_data_frame, start_date_doy, end_date_doy, year) {
+ − 63 # The data we want is fully contained within the 30 year normals data.
+ − 64 first_norm_row = which(norm_data_frame$DOY==start_date_doy);
+ − 65 last_norm_row = which(norm_data_frame$DOY==end_date_doy);
+ − 66 # Add 1 to the number of rows to ensure that the end date is included.
+ − 67 tmp_data_frame_rows = last_norm_row - first_norm_row + 1;
+ − 68 tmp_data_frame = get_new_temperature_data_frame(nrow=tmp_data_frame_rows);
+ − 69 j = 0;
+ − 70 for (i in first_norm_row:last_norm_row) {
+ − 71 j = j + 1;
+ − 72 tmp_data_frame[j,] = get_next_normals_row(norm_data_frame, year, i);
+ − 73 }
+ − 74 return (tmp_data_frame);
+ − 75 }
+ − 76
56
+ − 77 get_daylen = function(doy, latitude, p=0.8333) {
+ − 78 # The default value for p is from Forsythe 1995.
+ − 79 theta = 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (doy - 186)));
+ − 80 phi = asin(0.39795 * cos(theta));
+ − 81 # Compute the length of daylight for the day of the year.
+ − 82 darkness_length = 24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi)));
+ − 83 daylight_length = 24 - darkness_length;
+ − 84 return (daylight_length);
+ − 85 }
+ − 86
49
+ − 87 get_new_norm_data_frame = function(is_leap_year, input_norm=NULL, nrow=0) {
+ − 88 # The input_norm data has the following 10 columns:
+ − 89 # STATIONID, LATITUDE, LONGITUDE, ELEV_M, NAME, ST, MMDD, DOY, TMIN, TMAX
+ − 90 column_names = c("STATIONID", "LATITUDE","LONGITUDE", "ELEV_M", "NAME", "ST", "MMDD", "DOY", "TMIN", "TMAX");
+ − 91 if (is.null(input_norm)) {
+ − 92 norm_data_frame = data.frame(matrix(ncol=10, nrow));
+ − 93 # Set the norm_data_frame column names for access.
+ − 94 colnames(norm_data_frame) = column_names;
+ − 95 } else {
+ − 96 norm_data_frame = read.csv(file=input_norm, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
+ − 97 # Set the norm_data_frame column names for access.
+ − 98 colnames(norm_data_frame) = column_names;
+ − 99 if (!is_leap_year) {
+ − 100 # All normals data includes Feb 29 which is row 60 in
+ − 101 # the data, so delete that row if we're not in a leap year.
+ − 102 norm_data_frame = norm_data_frame[-c(60),];
+ − 103 # Since we've removed row 60, we need to subtract 1 from
+ − 104 # each value in the DOY column of the data frame starting
+ − 105 # with the 60th row.
+ − 106 num_rows = dim(norm_data_frame)[1];
+ − 107 for (i in 60:num_rows) {
+ − 108 leap_year_doy = norm_data_frame$DOY[i];
+ − 109 non_leap_year_doy = leap_year_doy - 1;
+ − 110 norm_data_frame$DOY[i] = non_leap_year_doy;
+ − 111 }
+ − 112 }
+ − 113 }
+ − 114 return (norm_data_frame);
+ − 115 }
+ − 116
+ − 117 get_new_temperature_data_frame = function(input_ytd=NULL, nrow=0) {
+ − 118 # The input_ytd data has the following 6 columns:
+ − 119 # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX
+ − 120 if (is.null(input_ytd)) {
+ − 121 temperature_data_frame = data.frame(matrix(ncol=6, nrow));
+ − 122 } else {
+ − 123 temperature_data_frame = read.csv(file=input_ytd, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
+ − 124 }
+ − 125 colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
+ − 126 return(temperature_data_frame);
+ − 127 }
+ − 128
+ − 129 get_next_normals_row = function(norm_data_frame, year, index) {
39
+ − 130 # Return the next 30 year normals row formatted
+ − 131 # appropriately for the year-to-date data.
+ − 132 latitude = norm_data_frame[index,"LATITUDE"][1];
+ − 133 longitude = norm_data_frame[index,"LONGITUDE"][1];
+ − 134 # Format the date.
+ − 135 mmdd = norm_data_frame[index,"MMDD"][1];
+ − 136 date_str = paste(year, mmdd, sep="-");
+ − 137 doy = norm_data_frame[index,"DOY"][1];
+ − 138 tmin = norm_data_frame[index,"TMIN"][1];
+ − 139 tmax = norm_data_frame[index,"TMAX"][1];
56
+ − 140 daylen = get_daylen(doy, latitude);
+ − 141 # Calculate the average temperature based on the
+ − 142 # tmin and tmax values from the 30 year normals data.
+ − 143 temp.profile = get_temperature_at_hour(latitude, row, tmin=tmin, tmax=tmax, daylen=daylen);
+ − 144 mean_temp = temp.profile[1];
+ − 145 avg_temp = temp.profile[2];
+ − 146 return(list(latitude, longitude, date_str, doy, tmin, tmax, daylen, avg_temp));
39
+ − 147 }
+ − 148
56
+ − 149 get_temperature_at_hour = function(latitude, row, temperature_data_frame=NULL, tmin=NULL, tmax=NULL, daylen=NULL) {
8
+ − 150 # Base development threshold for Brown Marmorated Stink Bug
5
+ − 151 # insect phenology model.
8
+ − 152 threshold = 14.17;
56
+ − 153 if (is.null(temperature_data_frame)) {
+ − 154 # The values of tmin and tmax cannot be NULL.
+ − 155 curr_min_temp = tmin;
+ − 156 curr_max_temp = tmax;
+ − 157 } else {
+ − 158 # Minimum temperature for current row.
+ − 159 curr_min_temp = temperature_data_frame$TMIN[row];
+ − 160 # Maximum temperature for current row.
+ − 161 curr_max_temp = temperature_data_frame$TMAX[row];
+ − 162 }
5
+ − 163 # Mean temperature for current row.
8
+ − 164 curr_mean_temp = 0.5 * (curr_min_temp + curr_max_temp);
5
+ − 165 # Initialize degree day accumulation
8
+ − 166 averages = 0;
6
+ − 167 if (curr_max_temp < threshold) {
8
+ − 168 averages = 0;
5
+ − 169 }
+ − 170 else {
+ − 171 # Initialize hourly temperature.
8
+ − 172 T = NULL;
5
+ − 173 # Initialize degree hour vector.
8
+ − 174 dh = NULL;
56
+ − 175 if (is.null(temperature_data_frame)) {
+ − 176 # The value of daylen cannot be NULL.
+ − 177 y = daylen;
+ − 178 } else {
+ − 179 # Daylight length for current row.
+ − 180 y = temperature_data_frame$DAYLEN[row];
+ − 181 }
5
+ − 182 # Darkness length.
8
+ − 183 z = 24 - y;
5
+ − 184 # Lag coefficient.
8
+ − 185 a = 1.86;
5
+ − 186 # Darkness coefficient.
8
+ − 187 b = 2.20;
5
+ − 188 # Sunrise time.
8
+ − 189 risetime = 12 - y / 2;
5
+ − 190 # Sunset time.
8
+ − 191 settime = 12 + y / 2;
+ − 192 ts = (curr_max_temp - curr_min_temp) * sin(pi * (settime - 5) / (y + 2 * a)) + curr_min_temp;
5
+ − 193 for (i in 1:24) {
+ − 194 if (i > risetime && i < settime) {
+ − 195 # Number of hours after Tmin until sunset.
8
+ − 196 m = i - 5;
+ − 197 T[i] = (curr_max_temp - curr_min_temp) * sin(pi * m / (y + 2 * a)) + curr_min_temp;
5
+ − 198 if (T[i] < 8.4) {
8
+ − 199 dh[i] = 0;
5
+ − 200 }
+ − 201 else {
8
+ − 202 dh[i] = T[i] - 8.4;
5
+ − 203 }
+ − 204 }
6
+ − 205 else if (i > settime) {
8
+ − 206 n = i - settime;
+ − 207 T[i] = curr_min_temp + (ts - curr_min_temp) * exp( - b * n / z);
5
+ − 208 if (T[i] < 8.4) {
8
+ − 209 dh[i] = 0;
5
+ − 210 }
+ − 211 else {
8
+ − 212 dh[i] = T[i] - 8.4;
5
+ − 213 }
+ − 214 }
+ − 215 else {
8
+ − 216 n = i + 24 - settime;
+ − 217 T[i] = curr_min_temp + (ts - curr_min_temp) * exp( - b * n / z);
5
+ − 218 if (T[i] < 8.4) {
8
+ − 219 dh[i] = 0;
5
+ − 220 }
+ − 221 else {
8
+ − 222 dh[i] = T[i] - 8.4;
5
+ − 223 }
+ − 224 }
+ − 225 }
8
+ − 226 averages = sum(dh) / 24;
5
+ − 227 }
6
+ − 228 return(c(curr_mean_temp, averages))
5
+ − 229 }
+ − 230
38
+ − 231 is_leap_year = function(date_str) {
+ − 232 # Extract the year from the date_str.
+ − 233 date = format(date_str);
+ − 234 items = strsplit(date, "-")[[1]];
+ − 235 year = as.integer(items[1]);
+ − 236 if (((year %% 4 == 0) & (year %% 100 != 0)) | (year %% 400 == 0)) {
39
+ − 237 return(TRUE);
38
+ − 238 } else {
39
+ − 239 return(FALSE);
38
+ − 240 }
+ − 241 }
+ − 242
6
+ − 243 mortality.adult = function(temperature) {
+ − 244 if (temperature < 12.7) {
8
+ − 245 mortality.probability = 0.002;
6
+ − 246 }
+ − 247 else {
8
+ − 248 mortality.probability = temperature * 0.0005 + 0.02;
6
+ − 249 }
+ − 250 return(mortality.probability)
5
+ − 251 }
+ − 252
54
+ − 253 mortality.egg = function(temperature, adj=0) {
+ − 254 # If no input from adjustment, default
+ − 255 # value is 0 (data from Nielsen, 2008).
+ − 256 T.mortality = c(15, 17, 20, 25, 27, 30, 33, 35);
+ − 257 egg.mortality = c(50, 2, 1, 0, 0, 0, 5, 100);
+ − 258 # Calculates slopes and intercepts for lines.
+ − 259 slopes = NULL;
+ − 260 intercepts = NULL;
+ − 261 for (i in 1:length(T.mortality)) {
+ − 262 slopes[i] = (egg.mortality[i+1] - egg.mortality[i]) / (T.mortality[i+1] - T.mortality[i]);
+ − 263 intercepts[i] = -slopes[i] * T.mortality[i] + egg.mortality[i];
5
+ − 264 }
54
+ − 265 # Calculates mortality based on temperature.
+ − 266 mortality.probability = NULL;
+ − 267 for (j in 1:length(temperature)) {
+ − 268 mortality.probability[j] = if(temperature[j] <= T.mortality[2]) {
+ − 269 temperature[j] * slopes[1] + intercepts[1];
+ − 270 } else if (temperature[j] > T.mortality[2] && temperature[j] <= T.mortality[3]) {
+ − 271 temperature[j] * slopes[2] + intercepts[2];
+ − 272 } else if (temperature[j] > T.mortality[3] && temperature[j] <= T.mortality[4]) {
+ − 273 temperature[j] * slopes[3] + intercepts[3];
+ − 274 } else if (temperature[j] > T.mortality[4] && temperature[j] <= T.mortality[5]) {
+ − 275 temperature[j] * slopes[4] + intercepts[4];
+ − 276 } else if (temperature[j] > T.mortality[5] && temperature[j] <= T.mortality[6]) {
+ − 277 temperature[j] * slopes[5] + intercepts[5];
+ − 278 } else if (temperature[j] > T.mortality[6] && temperature[j] <= T.mortality[7]) {
+ − 279 temperature[j] * slopes[6] + intercepts[6];
+ − 280 } else if (temperature[j] > T.mortality[7]) {
+ − 281 temperature[j] * slopes[7] + intercepts[7];
+ − 282 }
+ − 283 # If mortality > 100, make it equal to 100.
+ − 284 mortality.probability[mortality.probability>100] = 100;
+ − 285 # If mortality <0, make equal to 0.
+ − 286 mortality.probability[mortality.probability<0] = 0;
5
+ − 287 }
54
+ − 288 # Make mortality adjustments based on adj parameter.
+ − 289 mortality.probability = (100 - mortality.probability) * adj + mortality.probability;
+ − 290 # if mortality > 100, make it equal to 100.
+ − 291 mortality.probability[mortality.probability>100] = 100;
+ − 292 # If mortality <0, make equal to 0.
+ − 293 mortality.probability[mortality.probability<0] = 0;
+ − 294 # Change percent to proportion.
+ − 295 mortality.probability = mortality.probability / 100;
6
+ − 296 return(mortality.probability)
5
+ − 297 }
+ − 298
+ − 299 mortality.nymph = function(temperature) {
+ − 300 if (temperature < 12.7) {
8
+ − 301 mortality.probability = 0.03;
5
+ − 302 }
+ − 303 else {
8
+ − 304 mortality.probability = temperature * 0.0008 + 0.03;
5
+ − 305 }
8
+ − 306 return(mortality.probability);
6
+ − 307 }
+ − 308
49
+ − 309 parse_input_data = function(input_ytd, input_norm, location, start_date, end_date) {
+ − 310 # The end DOY for norm data prepended to ytd data.
+ − 311 prepend_end_doy_norm = 0;
+ − 312 # The start DOY for norm data appended to ytd data.
+ − 313 append_start_doy_norm = 0;
+ − 314 if (is.null(start_date) && is.null(end_date)) {
+ − 315 # We're not dealing with a date interval.
+ − 316 date_interval = FALSE;
+ − 317 if (is.null(input_ytd)) {
+ − 318 # Base all dates on the current date since 30 year
+ − 319 # normals data does not include any dates.
+ − 320 year = format(Sys.Date(), "%Y");
+ − 321 }
43
+ − 322 } else {
49
+ − 323 date_interval = TRUE;
+ − 324 year = get_year_from_date(start_date);
+ − 325 # Get the DOY for start_date and end_date.
+ − 326 start_date_doy = as.integer(strftime(start_date, format="%j"));
+ − 327 end_date_doy = as.integer(strftime(end_date, format="%j"));
+ − 328 }
+ − 329 if (is.null(input_ytd)) {
+ − 330 # We're processing only the 30 year normals data.
+ − 331 processing_year_to_date_data = FALSE;
+ − 332 if (is.null(start_date) && is.null(end_date)) {
+ − 333 # We're processing the entire year, so we can
+ − 334 # set the start_date to Jan 1.
+ − 335 start_date = paste(year, "01", "01", sep="-");
+ − 336 }
+ − 337 } else {
+ − 338 processing_year_to_date_data = TRUE;
+ − 339 # Read the input_ytd temperature data file into a data frame.
+ − 340 temperature_data_frame = get_new_temperature_data_frame(input_ytd=input_ytd);
+ − 341 num_ytd_rows = dim(temperature_data_frame)[1];
+ − 342 if (!date_interval) {
+ − 343 start_date = temperature_data_frame$DATE[1];
+ − 344 year = get_year_from_date(start_date);
+ − 345 }
43
+ − 346 }
38
+ − 347 # See if we're in a leap year.
+ − 348 is_leap_year = is_leap_year(start_date);
+ − 349 # Read the input_norm temperature datafile into a data frame.
49
+ − 350 norm_data_frame = get_new_norm_data_frame(is_leap_year, input_norm=input_norm);
+ − 351 if (processing_year_to_date_data) {
+ − 352 if (date_interval) {
+ − 353 # We're plotting a date interval.
+ − 354 start_date_ytd_row = which(temperature_data_frame$DATE==start_date);
+ − 355 if (length(start_date_ytd_row) > 0) {
+ − 356 # The start date is contained within the input_ytd data.
+ − 357 start_date_ytd_row = start_date_ytd_row[1];
+ − 358 start_doy_ytd = as.integer(temperature_data_frame$DOY[start_date_ytd_row]);
+ − 359 } else {
+ − 360 # The start date is contained within the input_norm data.
+ − 361 start_date_ytd_row = 0;
+ − 362 start_date_norm_row = which(norm_data_frame$DOY==start_date_doy);
+ − 363 }
+ − 364 end_date_ytd_row = which(temperature_data_frame$DATE==end_date);
+ − 365 if (length(end_date_ytd_row) > 0) {
+ − 366 end_date_ytd_row = end_date_ytd_row[1];
+ − 367 # The end date is contained within the input_ytd data.
+ − 368 end_doy_ytd = as.integer(temperature_data_frame$DOY[end_date_ytd_row]);
53
+ − 369 if (end_doy_ytd > end_date_ytd_row + 1) {
+ − 370 # The input year-to-date dataset is missing 1 or more
+ − 371 # days of data.
+ − 372 days_missing = end_doy_ytd - end_date_ytd_row;
+ − 373 msg = cat("The year-to-date dataset is missing ", days_missing, " days of data.\n");
+ − 374 stop_err(msg);
+ − 375 }
49
+ − 376 } else {
+ − 377 end_date_ytd_row = 0;
+ − 378 }
+ − 379 } else {
+ − 380 # We're plotting an entire year.
+ − 381 # Get the start date and end date from temperature_data_frame.
+ − 382 start_date_ytd_row = 1;
+ − 383 # Temporarily set start_date to get the year.
+ − 384 start_date = temperature_data_frame$DATE[1];
+ − 385 end_date_ytd_row = num_ytd_rows;
+ − 386 end_date = temperature_data_frame$DATE[num_ytd_rows];
+ − 387 date_str = format(start_date);
+ − 388 # Extract the year from the start date.
+ − 389 date_str_items = strsplit(date_str, "-")[[1]];
+ − 390 # Get the year.
+ − 391 year = date_str_items[1];
+ − 392 # Properly set the start_date to be Jan 1 of the year.
+ − 393 start_date = paste(year, "01", "01", sep="-");
+ − 394 # Properly set the end_date to be Dec 31 of the year.
+ − 395 end_date = paste(year, "12", "31", sep="-");
+ − 396 # Save the first DOY to later check if start_date is Jan 1.
+ − 397 start_doy_ytd = as.integer(temperature_data_frame$DOY[1]);
+ − 398 end_doy_ytd = as.integer(temperature_data_frame$DOY[num_ytd_rows]);
53
+ − 399 if (end_doy_ytd > end_date_ytd_row + 1) {
+ − 400 # The input year-to-date dataset is missing 1 or more
+ − 401 # days of data.
+ − 402 days_missing = end_doy_ytd - end_date_ytd_row;
+ − 403 msg = cat("The year-to-date dataset is missing ", days_missing, " days of data.\n");
+ − 404 stop_err(msg);
+ − 405 }
49
+ − 406 }
+ − 407 } else {
+ − 408 # We're processing only the 30 year normals data, so create an empty
+ − 409 # data frame for containing temperature data after it is converted
+ − 410 # from the 30 year normals format to the year-to-date format.
+ − 411 temperature_data_frame = get_new_temperature_data_frame();
+ − 412 if (date_interval) {
+ − 413 # We're plotting a date interval.
+ − 414 # Extract the year, month and day from the start date.
+ − 415 start_date_str = format(start_date);
+ − 416 start_date_str_items = strsplit(start_date_str, "-")[[1]];
+ − 417 year = start_date_str_items[1];
+ − 418 start_date_month = start_date_str_items[2];
+ − 419 start_date_day = start_date_str_items[3];
+ − 420 start_date = paste(year, start_date_month, start_date_day, sep="-");
+ − 421 # Extract the month and day from the end date.
+ − 422 end_date_str = format(start_date);
+ − 423 end_date_str_items = strsplit(end_date_str, "-")[[1]];
+ − 424 end_date_month = end_date_str_items[2];
+ − 425 end_date_day = end_date_str_items[3];
+ − 426 end_date = paste(year, end_date_month, end_date_day, sep="-");
+ − 427 } else {
+ − 428 # We're plotting an entire year.
+ − 429 start_date = paste(year, "01", "01", sep="-");
+ − 430 end_date = paste(year, "12", "31", sep="-");
+ − 431 }
6
+ − 432 }
49
+ − 433 # Set the location to be the station name if the user elected not to enter it.
+ − 434 if (is.null(location) | length(location) == 0) {
45
+ − 435 location = norm_data_frame$NAME[1];
+ − 436 }
49
+ − 437 if (processing_year_to_date_data) {
+ − 438 # Merge the year-to-date data with the 30 year normals data.
+ − 439 if (date_interval) {
+ − 440 # The values of start_date_ytd_row and end_date_ytd_row were set above.
+ − 441 if (start_date_ytd_row > 0 & end_date_ytd_row > 0) {
+ − 442 # The date interval is contained within the input_ytd
+ − 443 # data, so we don't need to merge the 30 year normals data.
+ − 444 temperature_data_frame = temperature_data_frame[start_date_ytd_row:end_date_ytd_row,];
+ − 445 } else if (start_date_ytd_row == 0 & end_date_ytd_row > 0) {
+ − 446 # The date interval starts in input_norm and ends in
+ − 447 # input_ytd, so prepend appropriate rows from input_norm
+ − 448 # to appropriate rows from input_ytd.
+ − 449 first_norm_row = which(norm_data_frame$DOY==start_date_doy);
+ − 450 # Get the first DOY from temperature_data_frame.
+ − 451 first_ytd_doy = temperature_data_frame$DOY[1];
+ − 452 # End DOY of input_norm data prepended to input_ytd.
+ − 453 prepend_end_doy_norm = first_ytd_doy - 1;
+ − 454 # Get the number of rows for the restricted date interval
+ − 455 # that are contained in temperature_data_frame.
+ − 456 num_temperature_data_frame_rows = end_date_ytd_row;
+ − 457 # Get the last row needed from the 30 year normals data.
+ − 458 last_norm_row = which(norm_data_frame$DOY==prepend_end_doy_norm);
+ − 459 # Get the number of rows for the restricted date interval
+ − 460 # that are contained in norm_data_frame.
+ − 461 num_norm_data_frame_rows = last_norm_row - first_norm_row;
+ − 462 # Create a temporary data frame to contain the 30 year normals
+ − 463 # data from the start date to the date immediately prior to the
+ − 464 # first row of the input_ytd data.
+ − 465 tmp_norm_data_frame = get_new_temperature_data_frame(nrow=num_temperature_data_frame_rows+num_norm_data_frame_rows);
+ − 466 j = 1;
+ − 467 for (i in first_norm_row:last_norm_row) {
+ − 468 # Populate the temp_data_frame row with
+ − 469 # values from norm_data_frame.
+ − 470 tmp_norm_data_frame[j,] = get_next_normals_row(norm_data_frame, year, i);
+ − 471 j = j + 1;
+ − 472 }
+ − 473 # Create a second temporary data frame containing the
+ − 474 # appropriate rows from temperature_data_frame.
+ − 475 tmp_temperature_data_frame = temperature_data_frame[1:num_temperature_data_frame_rows,];
+ − 476 # Merge the 2 temporary data frames.
+ − 477 temperature_data_frame = rbind(tmp_norm_data_frame, tmp_temperature_data_frame);
+ − 478 } else if (start_date_ytd_row > 0 & end_date_ytd_row == 0) {
+ − 479 # The date interval starts in input_ytd and ends in input_norm,
+ − 480 # so append appropriate rows from input_norm to appropriate rows
+ − 481 # from input_ytd. First, get the number of rows for the restricted
+ − 482 # date interval that are contained in temperature_data_frame.
+ − 483 num_temperature_data_frame_rows = num_ytd_rows - start_date_ytd_row + 1;
+ − 484 # Get the DOY of the last row in the input_ytd data.
+ − 485 last_ytd_doy = temperature_data_frame$DOY[num_ytd_rows];
+ − 486 # Get the DOYs for the first and last rows from norm_data_frame
+ − 487 # that will be appended to temperature_data_frame.
+ − 488 append_start_doy_norm = last_ytd_doy + 1;
+ − 489 # Get the row from norm_data_frame containing first_norm_doy.
+ − 490 first_norm_row = which(norm_data_frame$DOY == append_start_doy_norm);
+ − 491 # Get the row from norm_data_frame containing end_date_doy.
+ − 492 last_norm_row = which(norm_data_frame$DOY == end_date_doy);
+ − 493 # Get the number of rows for the restricted date interval
+ − 494 # that are contained in norm_data_frame.
+ − 495 num_norm_data_frame_rows = last_norm_row - first_norm_row;
+ − 496 # Create a temporary data frame to contain the data
+ − 497 # taken from both temperature_data_frame and norm_data_frame
+ − 498 # for the date interval.
+ − 499 tmp_data_frame = get_new_temperature_data_frame(nrow=num_temperature_data_frame_rows+num_norm_data_frame_rows);
+ − 500 # Populate tmp_data_frame with the appropriate rows from temperature_data_frame.
+ − 501 j = start_date_ytd_row;
+ − 502 for (i in 1:num_temperature_data_frame_rows) {
+ − 503 tmp_data_frame[i,] = temperature_data_frame[j,];
+ − 504 j = j + 1;
+ − 505 }
+ − 506 # Apppend the appropriate rows from norm_data_frame to tmp_data_frame.
+ − 507 current_iteration = num_temperature_data_frame_rows + 1;
+ − 508 num_iterations = current_iteration + num_norm_data_frame_rows;
+ − 509 j = first_norm_row;
+ − 510 for (i in current_iteration:num_iterations) {
+ − 511 tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, j);
+ − 512 j = j + 1;
+ − 513 }
+ − 514 temperature_data_frame = tmp_data_frame[,];
+ − 515 } else if (start_date_ytd_row == 0 & end_date_ytd_row == 0) {
+ − 516 # The date interval is contained witin input_norm.
+ − 517 temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
+ − 518 }
+ − 519 } else {
+ − 520 # We're plotting an entire year.
+ − 521 if (start_doy_ytd > 1) {
+ − 522 # The input_ytd data starts after Jan 1, so prepend
+ − 523 # appropriate rows from input_norm to temperature_data_frame.
+ − 524 prepend_end_doy_norm = start_doy_ytd - 1;
+ − 525 last_norm_row = which(norm_data_frame$DOY == prepend_end_doy_norm);
+ − 526 # Create a temporary data frame to contain the input_norm data
+ − 527 # from Jan 1 to the date immediately prior to start_date.
+ − 528 tmp_data_frame = temperature_data_frame[FALSE,];
+ − 529 # Populate tmp_data_frame with appropriate rows from norm_data_frame.
+ − 530 for (i in 1:last_norm_row) {
+ − 531 tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
+ − 532 }
+ − 533 # Merge the temporary data frame with temperature_data_frame.
+ − 534 temperature_data_frame = rbind(tmp_data_frame, temperature_data_frame);
+ − 535 }
+ − 536 # Set the value of total_days.
+ − 537 total_days = get_total_days(is_leap_year);
+ − 538 if (end_doy_ytd < total_days) {
+ − 539 # Define the next row for the year-to-date data from the 30 year normals data.
+ − 540 append_start_doy_norm = end_doy_ytd + 1;
+ − 541 first_norm_row = which(norm_data_frame$DOY == append_start_doy_norm);
+ − 542 # Append the 30 year normals data to the year-to-date data.
+ − 543 for (i in first_norm_row:total_days) {
+ − 544 temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
+ − 545 }
+ − 546 }
38
+ − 547 }
43
+ − 548 } else {
49
+ − 549 # We're processing only the 30 year normals data.
+ − 550 if (date_interval) {
+ − 551 # Populate temperature_data_frame from norm_data_frame.
+ − 552 temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
+ − 553 } else {
+ − 554 total_days = get_total_days(is_leap_year);
+ − 555 for (i in 1:total_days) {
+ − 556 temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
43
+ − 557 }
+ − 558 }
38
+ − 559 }
+ − 560 # Add a column containing the daylight length for each day.
49
+ − 561 temperature_data_frame = add_daylight_length(temperature_data_frame);
+ − 562 return(list(temperature_data_frame, start_date, end_date, prepend_end_doy_norm, append_start_doy_norm, is_leap_year, location));
5
+ − 563 }
+ − 564
50
+ − 565 # Import the shared utility functions.
+ − 566 utils_path <- paste(opt$script_dir, "utils.R", sep="/");
+ − 567 source(utils_path);
49
+ − 568
+ − 569 if (is.null(opt$input_ytd)) {
+ − 570 processing_year_to_date_data = FALSE;
+ − 571 } else {
+ − 572 processing_year_to_date_data = TRUE;
+ − 573 }
10
+ − 574 # Determine if we're plotting generations separately.
+ − 575 if (opt$plot_generations_separately=="yes") {
+ − 576 plot_generations_separately = TRUE;
+ − 577 } else {
+ − 578 plot_generations_separately = FALSE;
+ − 579 }
39
+ − 580 # Parse the inputs.
49
+ − 581 data_list = parse_input_data(opt$input_ytd, opt$input_norm, opt$location, opt$start_date, opt$end_date);
39
+ − 582 temperature_data_frame = data_list[[1]];
49
+ − 583 # Information needed for plots, some of these values are
+ − 584 # being reset here since in some case they were set above.
39
+ − 585 start_date = data_list[[2]];
41
+ − 586 end_date = data_list[[3]];
49
+ − 587 prepend_end_doy_norm = data_list[[4]];
+ − 588 append_start_doy_norm = data_list[[5]];
41
+ − 589 is_leap_year = data_list[[6]];
49
+ − 590 location = data_list[[7]];
38
+ − 591
50
+ − 592 # We're plotting an entire year.
+ − 593 # Display the total number of days in the Galaxy history item blurb.
+ − 594 if (processing_year_to_date_data) {
+ − 595 cat("Number of days year-to-date: ", opt$num_days_ytd, "\n");
49
+ − 596 } else {
50
+ − 597 if (is_leap_year) {
+ − 598 num_days = 366;
+ − 599 } else {
+ − 600 num_days = 365;
49
+ − 601 }
50
+ − 602 cat("Number of days in year: ", num_days, "\n");
49
+ − 603 }
50
+ − 604
38
+ − 605 # Get the ticks date labels for plots.
50
+ − 606 ticks_and_labels = get_x_axis_ticks_and_labels(temperature_data_frame, prepend_end_doy_norm, append_start_doy_norm);
34
+ − 607 ticks = c(unlist(ticks_and_labels[1]));
+ − 608 date_labels = c(unlist(ticks_and_labels[2]));
10
+ − 609 # All latitude values are the same, so get the value for plots from the first row.
8
+ − 610 latitude = temperature_data_frame$LATITUDE[1];
38
+ − 611
20
+ − 612 # Determine the specified life stages for processing.
10
+ − 613 # Split life_stages into a list of strings for plots.
+ − 614 life_stages_str = as.character(opt$life_stages);
+ − 615 life_stages = strsplit(life_stages_str, ",")[[1]];
38
+ − 616
10
+ − 617 # Determine the data we need to generate for plotting.
+ − 618 process_eggs = FALSE;
+ − 619 process_nymphs = FALSE;
20
+ − 620 process_young_nymphs = FALSE;
+ − 621 process_old_nymphs = FALSE;
+ − 622 process_total_nymphs = FALSE;
10
+ − 623 process_adults = FALSE;
23
+ − 624 process_previttelogenic_adults = FALSE;
+ − 625 process_vittelogenic_adults = FALSE;
20
+ − 626 process_diapausing_adults = FALSE;
+ − 627 process_total_adults = FALSE;
51
+ − 628 process_total = FALSE;
10
+ − 629 for (life_stage in life_stages) {
+ − 630 if (life_stage=="Total") {
+ − 631 process_eggs = TRUE;
+ − 632 process_nymphs = TRUE;
+ − 633 process_adults = TRUE;
51
+ − 634 process_total = TRUE;
10
+ − 635 } else if (life_stage=="Egg") {
+ − 636 process_eggs = TRUE;
+ − 637 } else if (life_stage=="Nymph") {
+ − 638 process_nymphs = TRUE;
+ − 639 } else if (life_stage=="Adult") {
+ − 640 process_adults = TRUE;
+ − 641 }
+ − 642 }
20
+ − 643 if (process_nymphs) {
+ − 644 # Split life_stages_nymph into a list of strings for plots.
+ − 645 life_stages_nymph_str = as.character(opt$life_stages_nymph);
+ − 646 life_stages_nymph = strsplit(life_stages_nymph_str, ",")[[1]];
23
+ − 647 for (life_stage_nymph in life_stages_nymph) {
20
+ − 648 if (life_stage_nymph=="Young") {
+ − 649 process_young_nymphs = TRUE;
+ − 650 } else if (life_stage_nymph=="Old") {
+ − 651 process_old_nymphs = TRUE;
+ − 652 } else if (life_stage_nymph=="Total") {
+ − 653 process_total_nymphs = TRUE;
+ − 654 }
+ − 655 }
+ − 656 }
16
+ − 657 if (process_adults) {
+ − 658 # Split life_stages_adult into a list of strings for plots.
+ − 659 life_stages_adult_str = as.character(opt$life_stages_adult);
+ − 660 life_stages_adult = strsplit(life_stages_adult_str, ",")[[1]];
23
+ − 661 for (life_stage_adult in life_stages_adult) {
+ − 662 if (life_stage_adult=="Pre-vittelogenic") {
+ − 663 process_previttelogenic_adults = TRUE;
24
+ − 664 } else if (life_stage_adult=="Vittelogenic") {
23
+ − 665 process_vittelogenic_adults = TRUE;
20
+ − 666 } else if (life_stage_adult=="Diapausing") {
+ − 667 process_diapausing_adults = TRUE;
+ − 668 } else if (life_stage_adult=="Total") {
+ − 669 process_total_adults = TRUE;
+ − 670 }
+ − 671 }
16
+ − 672 }
6
+ − 673 # Initialize matrices.
49
+ − 674 total_days = dim(temperature_data_frame)[1];
10
+ − 675 if (process_eggs) {
38
+ − 676 Eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 677 }
23
+ − 678 if (process_young_nymphs | process_total_nymphs) {
38
+ − 679 YoungNymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
20
+ − 680 }
23
+ − 681 if (process_old_nymphs | process_total_nymphs) {
38
+ − 682 OldNymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 683 }
23
+ − 684 if (process_previttelogenic_adults | process_total_adults) {
38
+ − 685 Previttelogenic.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
23
+ − 686 }
+ − 687 if (process_vittelogenic_adults | process_total_adults) {
38
+ − 688 Vittelogenic.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
23
+ − 689 }
+ − 690 if (process_diapausing_adults | process_total_adults) {
38
+ − 691 Diapausing.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 692 }
38
+ − 693 newborn.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 694 adult.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 695 death.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 696 if (plot_generations_separately) {
+ − 697 # P is Parental, or overwintered adults.
38
+ − 698 P.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 699 # F1 is the first field-produced generation.
38
+ − 700 F1.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 701 # F2 is the second field-produced generation.
38
+ − 702 F2.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 703 if (process_eggs) {
38
+ − 704 P_eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 705 F1_eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 706 F2_eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 707 }
20
+ − 708 if (process_young_nymphs) {
38
+ − 709 P_young_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 710 F1_young_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 711 F2_young_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
20
+ − 712 }
+ − 713 if (process_old_nymphs) {
38
+ − 714 P_old_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 715 F1_old_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 716 F2_old_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
20
+ − 717 }
+ − 718 if (process_total_nymphs) {
38
+ − 719 P_total_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 720 F1_total_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 721 F2_total_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 722 }
23
+ − 723 if (process_previttelogenic_adults) {
38
+ − 724 P_previttelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 725 F1_previttelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 726 F2_previttelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
23
+ − 727 }
+ − 728 if (process_vittelogenic_adults) {
38
+ − 729 P_vittelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 730 F1_vittelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 731 F2_vittelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
23
+ − 732 }
+ − 733 if (process_diapausing_adults) {
38
+ − 734 P_diapausing_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 735 F1_diapausing_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 736 F2_diapausing_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
23
+ − 737 }
+ − 738 if (process_total_adults) {
38
+ − 739 P_total_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 740 F1_total_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
+ − 741 F2_total_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
10
+ − 742 }
+ − 743 }
+ − 744 # Total population.
38
+ − 745 population.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
5
+ − 746
6
+ − 747 # Process replications.
18
+ − 748 for (current_replication in 1:opt$replications) {
6
+ − 749 # Start with the user-defined number of insects per replication.
8
+ − 750 num_insects = opt$insects_per_replication;
6
+ − 751 # Generation, Stage, degree-days, T, Diapause.
8
+ − 752 vector.ini = c(0, 3, 0, 0, 0);
10
+ − 753 # Replicate to create a matrix where the columns are
+ − 754 # Generation, Stage, degree-days, T, Diapause and the
+ − 755 # rows are the initial number of insects per replication.
8
+ − 756 vector.matrix = rep(vector.ini, num_insects);
10
+ − 757 # Complete transposed matrix for the population, so now
+ − 758 # the rows are Generation, Stage, degree-days, T, Diapause
8
+ − 759 vector.matrix = base::t(matrix(vector.matrix, nrow=5));
5
+ − 760 # Time series of population size.
10
+ − 761 if (process_eggs) {
38
+ − 762 Eggs = rep(0, total_days);
10
+ − 763 }
23
+ − 764 if (process_young_nymphs | process_total_nymphs) {
38
+ − 765 YoungNymphs = rep(0, total_days);
23
+ − 766 }
+ − 767 if (process_old_nymphs | process_total_nymphs) {
38
+ − 768 OldNymphs = rep(0, total_days);
10
+ − 769 }
23
+ − 770 if (process_previttelogenic_adults | process_total_adults) {
38
+ − 771 Previttelogenic = rep(0, total_days);
23
+ − 772 }
+ − 773 if (process_vittelogenic_adults | process_total_adults) {
38
+ − 774 Vittelogenic = rep(0, total_days);
23
+ − 775 }
+ − 776 if (process_diapausing_adults | process_total_adults) {
38
+ − 777 Diapausing = rep(0, total_days);
10
+ − 778 }
38
+ − 779 N.newborn = rep(0, total_days);
+ − 780 N.adult = rep(0, total_days);
+ − 781 N.death = rep(0, total_days);
+ − 782 overwintering_adult.population = rep(0, total_days);
+ − 783 first_generation.population = rep(0, total_days);
+ − 784 second_generation.population = rep(0, total_days);
10
+ − 785 if (plot_generations_separately) {
+ − 786 # P is Parental, or overwintered adults.
+ − 787 # F1 is the first field-produced generation.
+ − 788 # F2 is the second field-produced generation.
+ − 789 if (process_eggs) {
38
+ − 790 P.egg = rep(0, total_days);
+ − 791 F1.egg = rep(0, total_days);
+ − 792 F2.egg = rep(0, total_days);
10
+ − 793 }
20
+ − 794 if (process_young_nymphs) {
38
+ − 795 P.young_nymph = rep(0, total_days);
+ − 796 F1.young_nymph = rep(0, total_days);
+ − 797 F2.young_nymph = rep(0, total_days);
20
+ − 798 }
+ − 799 if (process_old_nymphs) {
38
+ − 800 P.old_nymph = rep(0, total_days);
+ − 801 F1.old_nymph = rep(0, total_days);
+ − 802 F2.old_nymph = rep(0, total_days);
20
+ − 803 }
+ − 804 if (process_total_nymphs) {
38
+ − 805 P.total_nymph = rep(0, total_days);
+ − 806 F1.total_nymph = rep(0, total_days);
+ − 807 F2.total_nymph = rep(0, total_days);
10
+ − 808 }
23
+ − 809 if (process_previttelogenic_adults) {
38
+ − 810 P.previttelogenic_adult = rep(0, total_days);
+ − 811 F1.previttelogenic_adult = rep(0, total_days);
+ − 812 F2.previttelogenic_adult = rep(0, total_days);
23
+ − 813 }
+ − 814 if (process_vittelogenic_adults) {
38
+ − 815 P.vittelogenic_adult = rep(0, total_days);
+ − 816 F1.vittelogenic_adult = rep(0, total_days);
+ − 817 F2.vittelogenic_adult = rep(0, total_days);
23
+ − 818 }
+ − 819 if (process_diapausing_adults) {
38
+ − 820 P.diapausing_adult = rep(0, total_days);
+ − 821 F1.diapausing_adult = rep(0, total_days);
+ − 822 F2.diapausing_adult = rep(0, total_days);
23
+ − 823 }
+ − 824 if (process_total_adults) {
38
+ − 825 P.total_adult = rep(0, total_days);
+ − 826 F1.total_adult = rep(0, total_days);
+ − 827 F2.total_adult = rep(0, total_days);
10
+ − 828 }
+ − 829 }
8
+ − 830 total.population = NULL;
38
+ − 831 averages.day = rep(0, total_days);
+ − 832 # All the days included in the input_ytd temperature dataset.
+ − 833 for (row in 1:total_days) {
5
+ − 834 # Get the integer day of the year for the current row.
8
+ − 835 doy = temperature_data_frame$DOY[row];
5
+ − 836 # Photoperiod in the day.
8
+ − 837 photoperiod = temperature_data_frame$DAYLEN[row];
56
+ − 838 temp.profile = get_temperature_at_hour(latitude, row, temperature_data_frame=temperature_data_frame);
8
+ − 839 mean.temp = temp.profile[1];
+ − 840 averages.temp = temp.profile[2];
+ − 841 averages.day[row] = averages.temp;
5
+ − 842 # Trash bin for death.
8
+ − 843 death.vector = NULL;
5
+ − 844 # Newborn.
8
+ − 845 birth.vector = NULL;
5
+ − 846 # All individuals.
6
+ − 847 for (i in 1:num_insects) {
+ − 848 # Individual record.
8
+ − 849 vector.individual = vector.matrix[i,];
6
+ − 850 # Adjustment for late season mortality rate (still alive?).
5
+ − 851 if (latitude < 40.0) {
8
+ − 852 post.mortality = 1;
+ − 853 day.kill = 300;
5
+ − 854 }
+ − 855 else {
8
+ − 856 post.mortality = 2;
+ − 857 day.kill = 250;
5
+ − 858 }
6
+ − 859 if (vector.individual[2] == 0) {
5
+ − 860 # Egg.
54
+ − 861 death.probability = opt$egg_mortality * mortality.egg(mean.temp, adj=opt$egg_mortality);
5
+ − 862 }
6
+ − 863 else if (vector.individual[2] == 1 | vector.individual[2] == 2) {
18
+ − 864 # Nymph.
8
+ − 865 death.probability = opt$nymph_mortality * mortality.nymph(mean.temp);
5
+ − 866 }
6
+ − 867 else if (vector.individual[2] == 3 | vector.individual[2] == 4 | vector.individual[2] == 5) {
+ − 868 # Adult.
5
+ − 869 if (doy < day.kill) {
8
+ − 870 death.probability = opt$adult_mortality * mortality.adult(mean.temp);
5
+ − 871 }
+ − 872 else {
+ − 873 # Increase adult mortality after fall equinox.
8
+ − 874 death.probability = opt$adult_mortality * post.mortality * mortality.adult(mean.temp);
5
+ − 875 }
+ − 876 }
6
+ − 877 # Dependent on temperature and life stage?
8
+ − 878 u.d = runif(1);
6
+ − 879 if (u.d < death.probability) {
8
+ − 880 death.vector = c(death.vector, i);
6
+ − 881 }
5
+ − 882 else {
6
+ − 883 # End of diapause.
+ − 884 if (vector.individual[1] == 0 && vector.individual[2] == 3) {
27
+ − 885 # Overwintering adult (pre-vittelogenic).
6
+ − 886 if (photoperiod > opt$photoperiod && vector.individual[3] > 68 && doy < 180) {
5
+ − 887 # Add 68C to become fully reproductively matured.
+ − 888 # Transfer to vittelogenic.
8
+ − 889 vector.individual = c(0, 4, 0, 0, 0);
+ − 890 vector.matrix[i,] = vector.individual;
5
+ − 891 }
+ − 892 else {
27
+ − 893 # Add average temperature for current day.
8
+ − 894 vector.individual[3] = vector.individual[3] + averages.temp;
5
+ − 895 # Add 1 day in current stage.
8
+ − 896 vector.individual[4] = vector.individual[4] + 1;
+ − 897 vector.matrix[i,] = vector.individual;
5
+ − 898 }
+ − 899 }
6
+ − 900 if (vector.individual[1] != 0 && vector.individual[2] == 3) {
27
+ − 901 # Not overwintering adult (pre-vittelogenic).
8
+ − 902 current.gen = vector.individual[1];
6
+ − 903 if (vector.individual[3] > 68) {
5
+ − 904 # Add 68C to become fully reproductively matured.
+ − 905 # Transfer to vittelogenic.
8
+ − 906 vector.individual = c(current.gen, 4, 0, 0, 0);
+ − 907 vector.matrix[i,] = vector.individual;
5
+ − 908 }
+ − 909 else {
6
+ − 910 # Add average temperature for current day.
8
+ − 911 vector.individual[3] = vector.individual[3] + averages.temp;
5
+ − 912 # Add 1 day in current stage.
8
+ − 913 vector.individual[4] = vector.individual[4] + 1;
+ − 914 vector.matrix[i,] = vector.individual;
5
+ − 915 }
+ − 916 }
6
+ − 917 # Oviposition -- where population dynamics comes from.
+ − 918 if (vector.individual[2] == 4 && vector.individual[1] == 0 && mean.temp > 10) {
5
+ − 919 # Vittelogenic stage, overwintering generation.
6
+ − 920 if (vector.individual[4] == 0) {
5
+ − 921 # Just turned in vittelogenic stage.
8
+ − 922 num_insects.birth = round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size));
5
+ − 923 }
+ − 924 else {
+ − 925 # Daily probability of birth.
8
+ − 926 p.birth = opt$oviposition * 0.01;
+ − 927 u1 = runif(1);
5
+ − 928 if (u1 < p.birth) {
8
+ − 929 num_insects.birth = round(runif(1, 2, 8));
5
+ − 930 }
+ − 931 }
6
+ − 932 # Add average temperature for current day.
8
+ − 933 vector.individual[3] = vector.individual[3] + averages.temp;
5
+ − 934 # Add 1 day in current stage.
8
+ − 935 vector.individual[4] = vector.individual[4] + 1;
+ − 936 vector.matrix[i,] = vector.individual;
6
+ − 937 if (num_insects.birth > 0) {
5
+ − 938 # Add new birth -- might be in different generations.
8
+ − 939 new.gen = vector.individual[1] + 1;
5
+ − 940 # Egg profile.
8
+ − 941 new.individual = c(new.gen, 0, 0, 0, 0);
+ − 942 new.vector = rep(new.individual, num_insects.birth);
5
+ − 943 # Update batch of egg profile.
8
+ − 944 new.vector = t(matrix(new.vector, nrow=5));
5
+ − 945 # Group with total eggs laid in that day.
8
+ − 946 birth.vector = rbind(birth.vector, new.vector);
5
+ − 947 }
+ − 948 }
6
+ − 949 # Oviposition -- for generation 1.
+ − 950 if (vector.individual[2] == 4 && vector.individual[1] == 1 && mean.temp > 12.5 && doy < 222) {
5
+ − 951 # Vittelogenic stage, 1st generation
6
+ − 952 if (vector.individual[4] == 0) {
5
+ − 953 # Just turned in vittelogenic stage.
8
+ − 954 num_insects.birth = round(runif(1, 2+opt$min_clutch_size, 8+opt$max_clutch_size));
5
+ − 955 }
+ − 956 else {
+ − 957 # Daily probability of birth.
8
+ − 958 p.birth = opt$oviposition * 0.01;
+ − 959 u1 = runif(1);
5
+ − 960 if (u1 < p.birth) {
8
+ − 961 num_insects.birth = round(runif(1, 2, 8));
5
+ − 962 }
+ − 963 }
6
+ − 964 # Add average temperature for current day.
8
+ − 965 vector.individual[3] = vector.individual[3] + averages.temp;
5
+ − 966 # Add 1 day in current stage.
8
+ − 967 vector.individual[4] = vector.individual[4] + 1;
+ − 968 vector.matrix[i,] = vector.individual;
6
+ − 969 if (num_insects.birth > 0) {
5
+ − 970 # Add new birth -- might be in different generations.
8
+ − 971 new.gen = vector.individual[1] + 1;
5
+ − 972 # Egg profile.
8
+ − 973 new.individual = c(new.gen, 0, 0, 0, 0);
+ − 974 new.vector = rep(new.individual, num_insects.birth);
5
+ − 975 # Update batch of egg profile.
8
+ − 976 new.vector = t(matrix(new.vector, nrow=5));
5
+ − 977 # Group with total eggs laid in that day.
8
+ − 978 birth.vector = rbind(birth.vector, new.vector);
5
+ − 979 }
+ − 980 }
6
+ − 981 # Egg to young nymph.
+ − 982 if (vector.individual[2] == 0) {
+ − 983 # Add average temperature for current day.
8
+ − 984 vector.individual[3] = vector.individual[3] + averages.temp;
6
+ − 985 if (vector.individual[3] >= (68+opt$young_nymph_accumulation)) {
+ − 986 # From egg to young nymph, degree-days requirement met.
8
+ − 987 current.gen = vector.individual[1];
5
+ − 988 # Transfer to young nymph stage.
8
+ − 989 vector.individual = c(current.gen, 1, 0, 0, 0);
5
+ − 990 }
+ − 991 else {
+ − 992 # Add 1 day in current stage.
8
+ − 993 vector.individual[4] = vector.individual[4] + 1;
5
+ − 994 }
8
+ − 995 vector.matrix[i,] = vector.individual;
5
+ − 996 }
6
+ − 997 # Young nymph to old nymph.
+ − 998 if (vector.individual[2] == 1) {
+ − 999 # Add average temperature for current day.
8
+ − 1000 vector.individual[3] = vector.individual[3] + averages.temp;
6
+ − 1001 if (vector.individual[3] >= (250+opt$old_nymph_accumulation)) {
+ − 1002 # From young to old nymph, degree_days requirement met.
8
+ − 1003 current.gen = vector.individual[1];
5
+ − 1004 # Transfer to old nym stage.
8
+ − 1005 vector.individual = c(current.gen, 2, 0, 0, 0);
5
+ − 1006 if (photoperiod < opt$photoperiod && doy > 180) {
8
+ − 1007 vector.individual[5] = 1;
5
+ − 1008 } # Prepare for diapausing.
+ − 1009 }
+ − 1010 else {
+ − 1011 # Add 1 day in current stage.
8
+ − 1012 vector.individual[4] = vector.individual[4] + 1;
5
+ − 1013 }
8
+ − 1014 vector.matrix[i,] = vector.individual;
6
+ − 1015 }
27
+ − 1016 # Old nymph to adult: pre-vittelogenic or diapausing?
6
+ − 1017 if (vector.individual[2] == 2) {
+ − 1018 # Add average temperature for current day.
8
+ − 1019 vector.individual[3] = vector.individual[3] + averages.temp;
6
+ − 1020 if (vector.individual[3] >= (200+opt$adult_accumulation)) {
+ − 1021 # From old to adult, degree_days requirement met.
8
+ − 1022 current.gen = vector.individual[1];
6
+ − 1023 if (vector.individual[5] == 0) {
+ − 1024 # Previttelogenic.
8
+ − 1025 vector.individual = c(current.gen, 3, 0, 0, 0);
5
+ − 1026 }
+ − 1027 else {
+ − 1028 # Diapausing.
8
+ − 1029 vector.individual = c(current.gen, 5, 0, 0, 1);
5
+ − 1030 }
+ − 1031 }
+ − 1032 else {
+ − 1033 # Add 1 day in current stage.
8
+ − 1034 vector.individual[4] = vector.individual[4] + 1;
5
+ − 1035 }
8
+ − 1036 vector.matrix[i,] = vector.individual;
5
+ − 1037 }
6
+ − 1038 # Growing of diapausing adult (unimportant, but still necessary).
+ − 1039 if (vector.individual[2] == 5) {
8
+ − 1040 vector.individual[3] = vector.individual[3] + averages.temp;
+ − 1041 vector.individual[4] = vector.individual[4] + 1;
+ − 1042 vector.matrix[i,] = vector.individual;
5
+ − 1043 }
+ − 1044 } # Else if it is still alive.
+ − 1045 } # End of the individual bug loop.
6
+ − 1046
+ − 1047 # Number of deaths.
8
+ − 1048 num_insects.death = length(death.vector);
6
+ − 1049 if (num_insects.death > 0) {
+ − 1050 # Remove record of dead.
8
+ − 1051 vector.matrix = vector.matrix[-death.vector,];
5
+ − 1052 }
6
+ − 1053 # Number of births.
8
+ − 1054 num_insects.newborn = length(birth.vector[,1]);
+ − 1055 vector.matrix = rbind(vector.matrix, birth.vector);
5
+ − 1056 # Update population size for the next day.
8
+ − 1057 num_insects = num_insects - num_insects.death + num_insects.newborn;
5
+ − 1058
10
+ − 1059 # Aggregate results by day. Due to multiple transpose calls
+ − 1060 # on vector.matrix above, the columns of vector.matrix
+ − 1061 # are now Generation, Stage, degree-days, T, Diapause,
+ − 1062 if (process_eggs) {
+ − 1063 # For egg population size, column 2 (Stage), must be 0.
+ − 1064 Eggs[row] = sum(vector.matrix[,2]==0);
+ − 1065 }
23
+ − 1066 if (process_young_nymphs | process_total_nymphs) {
10
+ − 1067 # For young nymph population size, column 2 (Stage) must be 1.
+ − 1068 YoungNymphs[row] = sum(vector.matrix[,2]==1);
20
+ − 1069 }
23
+ − 1070 if (process_old_nymphs | process_total_nymphs) {
10
+ − 1071 # For old nymph population size, column 2 (Stage) must be 2.
+ − 1072 OldNymphs[row] = sum(vector.matrix[,2]==2);
+ − 1073 }
23
+ − 1074 if (process_previttelogenic_adults | process_total_adults) {
+ − 1075 # For pre-vittelogenic population size, column 2 (Stage) must be 3.
+ − 1076 Previttelogenic[row] = sum(vector.matrix[,2]==3);
+ − 1077 }
+ − 1078 if (process_vittelogenic_adults | process_total_adults) {
+ − 1079 # For vittelogenic population size, column 2 (Stage) must be 4.
24
+ − 1080 Vittelogenic[row] = sum(vector.matrix[,2]==4);
23
+ − 1081 }
+ − 1082 if (process_diapausing_adults | process_total_adults) {
10
+ − 1083 # For diapausing population size, column 2 (Stage) must be 5.
+ − 1084 Diapausing[row] = sum(vector.matrix[,2]==5);
+ − 1085 }
5
+ − 1086
6
+ − 1087 # Newborn population size.
8
+ − 1088 N.newborn[row] = num_insects.newborn;
6
+ − 1089 # Adult population size.
8
+ − 1090 N.adult[row] = sum(vector.matrix[,2]==3) + sum(vector.matrix[,2]==4) + sum(vector.matrix[,2]==5);
6
+ − 1091 # Dead population size.
8
+ − 1092 N.death[row] = num_insects.death;
6
+ − 1093
8
+ − 1094 total.population = c(total.population, num_insects);
6
+ − 1095
10
+ − 1096 # For overwintering adult (P) population
+ − 1097 # size, column 1 (Generation) must be 0.
8
+ − 1098 overwintering_adult.population[row] = sum(vector.matrix[,1]==0);
10
+ − 1099 # For first field generation (F1) population
+ − 1100 # size, column 1 (Generation) must be 1.
8
+ − 1101 first_generation.population[row] = sum(vector.matrix[,1]==1);
10
+ − 1102 # For second field generation (F2) population
+ − 1103 # size, column 1 (Generation) must be 2.
8
+ − 1104 second_generation.population[row] = sum(vector.matrix[,1]==2);
5
+ − 1105
10
+ − 1106 if (plot_generations_separately) {
+ − 1107 if (process_eggs) {
18
+ − 1108 # For egg life stage of generation P population size,
10
+ − 1109 # column 1 (generation) is 0 and column 2 (Stage) is 0.
+ − 1110 P.egg[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==0);
+ − 1111 # For egg life stage of generation F1 population size,
+ − 1112 # column 1 (generation) is 1 and column 2 (Stage) is 0.
+ − 1113 F1.egg[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==0);
+ − 1114 # For egg life stage of generation F2 population size,
+ − 1115 # column 1 (generation) is 2 and column 2 (Stage) is 0.
+ − 1116 F2.egg[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==0);
+ − 1117 }
20
+ − 1118 if (process_young_nymphs) {
+ − 1119 # For young nymph life stage of generation P population
+ − 1120 # size, the following combination is required:
+ − 1121 # - column 1 (Generation) is 0 and column 2 (Stage) is 1 (Young nymph)
+ − 1122 P.young_nymph[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==1);
+ − 1123 # For young nymph life stage of generation F1 population
+ − 1124 # size, the following combination is required:
+ − 1125 # - column 1 (Generation) is 1 and column 2 (Stage) is 1 (Young nymph)
+ − 1126 F1.young_nymph[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==1);
+ − 1127 # For young nymph life stage of generation F2 population
+ − 1128 # size, the following combination is required:
+ − 1129 # - column 1 (Generation) is 2 and column 2 (Stage) is 1 (Young nymph)
+ − 1130 F2.young_nymph[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==1);
+ − 1131 }
+ − 1132 if (process_old_nymphs) {
+ − 1133 # For old nymph life stage of generation P population
+ − 1134 # size, the following combination is required:
+ − 1135 # - column 1 (Generation) is 0 and column 2 (Stage) is 2 (Old nymph)
+ − 1136 P.old_nymph[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==2);
+ − 1137 # For old nymph life stage of generation F1 population
+ − 1138 # size, the following combination is required:
+ − 1139 # - column 1 (Generation) is 1 and column 2 (Stage) is 2 (Old nymph)
+ − 1140 F1.old_nymph[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==2);
+ − 1141 # For old nymph life stage of generation F2 population
+ − 1142 # size, the following combination is required:
+ − 1143 # - column 1 (Generation) is 2 and column 2 (Stage) is 2 (Old nymph)
+ − 1144 F2.old_nymph[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==2);
+ − 1145 }
+ − 1146 if (process_total_nymphs) {
+ − 1147 # For total nymph life stage of generation P population
10
+ − 1148 # size, one of the following combinations is required:
+ − 1149 # - column 1 (Generation) is 0 and column 2 (Stage) is 1 (Young nymph)
+ − 1150 # - column 1 (Generation) is 0 and column 2 (Stage) is 2 (Old nymph)
20
+ − 1151 P.total_nymph[row] = sum((vector.matrix[,1]==0 & vector.matrix[,2]==1) | (vector.matrix[,1]==0 & vector.matrix[,2]==2));
+ − 1152 # For total nymph life stage of generation F1 population
10
+ − 1153 # size, one of the following combinations is required:
+ − 1154 # - column 1 (Generation) is 1 and column 2 (Stage) is 1 (Young nymph)
+ − 1155 # - column 1 (Generation) is 1 and column 2 (Stage) is 2 (Old nymph)
20
+ − 1156 F1.total_nymph[row] = sum((vector.matrix[,1]==1 & vector.matrix[,2]==1) | (vector.matrix[,1]==1 & vector.matrix[,2]==2));
+ − 1157 # For total nymph life stage of generation F2 population
10
+ − 1158 # size, one of the following combinations is required:
+ − 1159 # - column 1 (Generation) is 2 and column 2 (Stage) is 1 (Young nymph)
+ − 1160 # - column 1 (Generation) is 2 and column 2 (Stage) is 2 (Old nymph)
20
+ − 1161 F2.total_nymph[row] = sum((vector.matrix[,1]==2 & vector.matrix[,2]==1) | (vector.matrix[,1]==2 & vector.matrix[,2]==2));
10
+ − 1162 }
23
+ − 1163 if (process_previttelogenic_adults) {
+ − 1164 # For previttelogenic adult life stage of generation P population
+ − 1165 # size, the following combination is required:
+ − 1166 # - column 1 (Generation) is 0 and column 2 (Stage) is 3 (Pre-vittelogenic)
+ − 1167 P.previttelogenic_adult[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==3);
+ − 1168 # For previttelogenic adult life stage of generation F1 population
+ − 1169 # size, the following combination is required:
+ − 1170 # - column 1 (Generation) is 1 and column 2 (Stage) is 3 (Pre-vittelogenic)
+ − 1171 F1.previttelogenic_adult[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==3);
+ − 1172 # For previttelogenic adult life stage of generation F2 population
+ − 1173 # size, the following combination is required:
+ − 1174 # - column 1 (Generation) is 2 and column 2 (Stage) is 3 (Pre-vittelogenic)
+ − 1175 F2.previttelogenic_adult[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==3);
+ − 1176 }
+ − 1177 if (process_vittelogenic_adults) {
+ − 1178 # For vittelogenic adult life stage of generation P population
+ − 1179 # size, the following combination is required:
24
+ − 1180 # - column 1 (Generation) is 0 and column 2 (Stage) is 4 (Vittelogenic)
23
+ − 1181 P.vittelogenic_adult[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==4);
+ − 1182 # For vittelogenic adult life stage of generation F1 population
+ − 1183 # size, the following combination is required:
24
+ − 1184 # - column 1 (Generation) is 1 and column 2 (Stage) is 4 (Vittelogenic)
23
+ − 1185 F1.vittelogenic_adult[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==4);
+ − 1186 # For vittelogenic adult life stage of generation F2 population
+ − 1187 # size, the following combination is required:
24
+ − 1188 # - column 1 (Generation) is 2 and column 2 (Stage) is 4 (Vittelogenic)
23
+ − 1189 F2.vittelogenic_adult[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==4);
+ − 1190 }
+ − 1191 if (process_diapausing_adults) {
+ − 1192 # For diapausing adult life stage of generation P population
+ − 1193 # size, the following combination is required:
10
+ − 1194 # - column 1 (Generation) is 0 and column 2 (Stage) is 5 (Diapausing)
23
+ − 1195 P.diapausing_adult[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==5);
+ − 1196 # For diapausing adult life stage of generation F1 population
+ − 1197 # size, the following combination is required:
+ − 1198 # - column 1 (Generation) is 1 and column 2 (Stage) is 5 (Diapausing)
+ − 1199 F1.diapausing_adult[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==5);
+ − 1200 # For diapausing adult life stage of generation F2 population
+ − 1201 # size, the following combination is required:
+ − 1202 # - column 1 (Generation) is 2 and column 2 (Stage) is 5 (Diapausing)
+ − 1203 F2.diapausing_adult[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==5);
+ − 1204 }
+ − 1205 if (process_total_adults) {
+ − 1206 # For total adult life stage of generation P population
10
+ − 1207 # size, one of the following combinations is required:
23
+ − 1208 # - column 1 (Generation) is 0 and column 2 (Stage) is 3 (Pre-vittelogenic)
24
+ − 1209 # - column 1 (Generation) is 0 and column 2 (Stage) is 4 (Vittelogenic)
23
+ − 1210 # - column 1 (Generation) is 0 and column 2 (Stage) is 5 (Diapausing)
+ − 1211 P.total_adult[row] = sum((vector.matrix[,1]==0 & vector.matrix[,2]==3) | (vector.matrix[,1]==0 & vector.matrix[,2]==4) | (vector.matrix[,1]==0 & vector.matrix[,2]==5));
+ − 1212 # For total adult life stage of generation F1 population
+ − 1213 # size, one of the following combinations is required:
+ − 1214 # - column 1 (Generation) is 1 and column 2 (Stage) is 3 (Pre-vittelogenic)
24
+ − 1215 # - column 1 (Generation) is 1 and column 2 (Stage) is 4 (Vittelogenic)
10
+ − 1216 # - column 1 (Generation) is 1 and column 2 (Stage) is 5 (Diapausing)
23
+ − 1217 F1.total_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));
+ − 1218 # For total adult life stage of generation F2 population
10
+ − 1219 # size, one of the following combinations is required:
23
+ − 1220 # - column 1 (Generation) is 2 and column 2 (Stage) is 3 (Pre-vittelogenic)
24
+ − 1221 # - column 1 (Generation) is 2 and column 2 (Stage) is 4 (Vittelogenic)
10
+ − 1222 # - column 1 (Generation) is 2 and column 2 (Stage) is 5 (Diapausing)
23
+ − 1223 F2.total_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));
10
+ − 1224 }
+ − 1225 }
38
+ − 1226 } # End of days specified in the input_ytd temperature data.
5
+ − 1227
56
+ − 1228 # Set the cumulative average temperature (this is never used).
8
+ − 1229 averages.cum = cumsum(averages.day);
5
+ − 1230
6
+ − 1231 # Define the output values.
10
+ − 1232 if (process_eggs) {
18
+ − 1233 Eggs.replications[,current_replication] = Eggs;
10
+ − 1234 }
23
+ − 1235 if (process_young_nymphs | process_total_nymphs) {
18
+ − 1236 YoungNymphs.replications[,current_replication] = YoungNymphs;
20
+ − 1237 }
23
+ − 1238 if (process_old_nymphs | process_total_nymphs) {
18
+ − 1239 OldNymphs.replications[,current_replication] = OldNymphs;
10
+ − 1240 }
23
+ − 1241 if (process_previttelogenic_adults | process_total_adults) {
+ − 1242 Previttelogenic.replications[,current_replication] = Previttelogenic;
+ − 1243 }
+ − 1244 if (process_vittelogenic_adults | process_total_adults) {
24
+ − 1245 Vittelogenic.replications[,current_replication] = Vittelogenic;
23
+ − 1246 }
+ − 1247 if (process_diapausing_adults | process_total_adults) {
18
+ − 1248 Diapausing.replications[,current_replication] = Diapausing;
10
+ − 1249 }
18
+ − 1250 newborn.replications[,current_replication] = N.newborn;
+ − 1251 adult.replications[,current_replication] = N.adult;
+ − 1252 death.replications[,current_replication] = N.death;
10
+ − 1253 if (plot_generations_separately) {
+ − 1254 # P is Parental, or overwintered adults.
18
+ − 1255 P.replications[,current_replication] = overwintering_adult.population;
10
+ − 1256 # F1 is the first field-produced generation.
18
+ − 1257 F1.replications[,current_replication] = first_generation.population;
10
+ − 1258 # F2 is the second field-produced generation.
18
+ − 1259 F2.replications[,current_replication] = second_generation.population;
10
+ − 1260 if (process_eggs) {
18
+ − 1261 P_eggs.replications[,current_replication] = P.egg;
+ − 1262 F1_eggs.replications[,current_replication] = F1.egg;
+ − 1263 F2_eggs.replications[,current_replication] = F2.egg;
10
+ − 1264 }
20
+ − 1265 if (process_young_nymphs) {
+ − 1266 P_young_nymphs.replications[,current_replication] = P.young_nymph;
+ − 1267 F1_young_nymphs.replications[,current_replication] = F1.young_nymph;
+ − 1268 F2_young_nymphs.replications[,current_replication] = F2.young_nymph;
+ − 1269 }
+ − 1270 if (process_old_nymphs) {
+ − 1271 P_old_nymphs.replications[,current_replication] = P.old_nymph;
+ − 1272 F1_old_nymphs.replications[,current_replication] = F1.old_nymph;
+ − 1273 F2_old_nymphs.replications[,current_replication] = F2.old_nymph;
+ − 1274 }
+ − 1275 if (process_total_nymphs) {
+ − 1276 P_total_nymphs.replications[,current_replication] = P.total_nymph;
+ − 1277 F1_total_nymphs.replications[,current_replication] = F1.total_nymph;
+ − 1278 F2_total_nymphs.replications[,current_replication] = F2.total_nymph;
10
+ − 1279 }
23
+ − 1280 if (process_previttelogenic_adults) {
+ − 1281 P_previttelogenic_adults.replications[,current_replication] = P.previttelogenic_adult;
+ − 1282 F1_previttelogenic_adults.replications[,current_replication] = F1.previttelogenic_adult;
+ − 1283 F2_previttelogenic_adults.replications[,current_replication] = F2.previttelogenic_adult;
+ − 1284 }
+ − 1285 if (process_vittelogenic_adults) {
+ − 1286 P_vittelogenic_adults.replications[,current_replication] = P.vittelogenic_adult;
+ − 1287 F1_vittelogenic_adults.replications[,current_replication] = F1.vittelogenic_adult;
+ − 1288 F2_vittelogenic_adults.replications[,current_replication] = F2.vittelogenic_adult;
+ − 1289 }
+ − 1290 if (process_diapausing_adults) {
+ − 1291 P_diapausing_adults.replications[,current_replication] = P.diapausing_adult;
+ − 1292 F1_diapausing_adults.replications[,current_replication] = F1.diapausing_adult;
+ − 1293 F2_diapausing_adults.replications[,current_replication] = F2.diapausing_adult;
+ − 1294 }
+ − 1295 if (process_total_adults) {
+ − 1296 P_total_adults.replications[,current_replication] = P.total_adult;
+ − 1297 F1_total_adults.replications[,current_replication] = F1.total_adult;
+ − 1298 F2_total_adults.replications[,current_replication] = F2.total_adult;
10
+ − 1299 }
+ − 1300 }
18
+ − 1301 population.replications[,current_replication] = total.population;
+ − 1302 # End processing replications.
5
+ − 1303 }
+ − 1304
56
+ − 1305 # Append the averages.day vector (i.e., degree-days)
+ − 1306 # to the various temperature_data_frames.
+ − 1307 temperature_data_frame = append_vector(temperature_data_frame, averages.day, "DEGREE.DAYS");
+ − 1308
10
+ − 1309 if (process_eggs) {
+ − 1310 # Mean value for eggs.
+ − 1311 eggs = apply(Eggs.replications, 1, mean);
27
+ − 1312 temperature_data_frame = append_vector(temperature_data_frame, eggs, "EGG");
10
+ − 1313 # Standard error for eggs.
+ − 1314 eggs.std_error = apply(Eggs.replications, 1, sd) / sqrt(opt$replications);
27
+ − 1315 temperature_data_frame = append_vector(temperature_data_frame, eggs.std_error, "EGGSE");
10
+ − 1316 }
+ − 1317 if (process_nymphs) {
+ − 1318 # Calculate nymph populations for selected life stage.
16
+ − 1319 for (life_stage_nymph in life_stages_nymph) {
28
+ − 1320 if (life_stage_nymph=="Young") {
16
+ − 1321 # Mean value for young nymphs.
+ − 1322 young_nymphs = apply(YoungNymphs.replications, 1, mean);
27
+ − 1323 temperature_data_frame = append_vector(temperature_data_frame, young_nymphs, "YOUNGNYMPH");
16
+ − 1324 # Standard error for young nymphs.
+ − 1325 young_nymphs.std_error = apply(YoungNymphs.replications / sqrt(opt$replications), 1, sd);
27
+ − 1326 temperature_data_frame = append_vector(temperature_data_frame, young_nymphs.std_error, "YOUNGNYMPHSE");
18
+ − 1327 } else if (life_stage_nymph=="Old") {
16
+ − 1328 # Mean value for old nymphs.
+ − 1329 old_nymphs = apply(OldNymphs.replications, 1, mean);
27
+ − 1330 temperature_data_frame = append_vector(temperature_data_frame, old_nymphs, "OLDNYMPH");
16
+ − 1331 # Standard error for old nymphs.
+ − 1332 old_nymphs.std_error = apply(OldNymphs.replications / sqrt(opt$replications), 1, sd);
27
+ − 1333 temperature_data_frame = append_vector(temperature_data_frame, old_nymphs.std_error, "OLDNYMPHSE");
28
+ − 1334 } else if (life_stage_nymph=="Total") {
+ − 1335 # Mean value for all nymphs.
+ − 1336 total_nymphs = apply((YoungNymphs.replications+OldNymphs.replications), 1, mean);
+ − 1337 temperature_data_frame = append_vector(temperature_data_frame, total_nymphs, "TOTALNYMPH");
+ − 1338 # Standard error for all nymphs.
+ − 1339 total_nymphs.std_error = apply((YoungNymphs.replications+OldNymphs.replications) / sqrt(opt$replications), 1, sd);
+ − 1340 temperature_data_frame = append_vector(temperature_data_frame, total_nymphs.std_error, "TOTALNYMPHSE");
16
+ − 1341 }
10
+ − 1342 }
+ − 1343 }
+ − 1344 if (process_adults) {
+ − 1345 # Calculate adult populations for selected life stage.
16
+ − 1346 for (life_stage_adult in life_stages_adult) {
28
+ − 1347 if (life_stage_adult == "Pre-vittelogenic") {
23
+ − 1348 # Mean value for previttelogenic adults.
+ − 1349 previttelogenic_adults = apply(Previttelogenic.replications, 1, mean);
50
+ − 1350 temperature_data_frame = append_vector(temperature_data_frame, previttelogenic_adults, "PRE.VITADULT");
23
+ − 1351 # Standard error for previttelogenic adults.
+ − 1352 previttelogenic_adults.std_error = apply(Previttelogenic.replications, 1, sd) / sqrt(opt$replications);
50
+ − 1353 temperature_data_frame = append_vector(temperature_data_frame, previttelogenic_adults.std_error, "PRE.VITADULTSE");
18
+ − 1354 } else if (life_stage_adult == "Vittelogenic") {
23
+ − 1355 # Mean value for vittelogenic adults.
24
+ − 1356 vittelogenic_adults = apply(Vittelogenic.replications, 1, mean);
27
+ − 1357 temperature_data_frame = append_vector(temperature_data_frame, vittelogenic_adults, "VITADULT");
23
+ − 1358 # Standard error for vittelogenic adults.
24
+ − 1359 vittelogenic_adults.std_error = apply(Vittelogenic.replications, 1, sd) / sqrt(opt$replications);
27
+ − 1360 temperature_data_frame = append_vector(temperature_data_frame, vittelogenic_adults.std_error, "VITADULTSE");
18
+ − 1361 } else if (life_stage_adult == "Diapausing") {
23
+ − 1362 # Mean value for vittelogenic adults.
16
+ − 1363 diapausing_adults = apply(Diapausing.replications, 1, mean);
27
+ − 1364 temperature_data_frame = append_vector(temperature_data_frame, diapausing_adults, "DIAPAUSINGADULT");
23
+ − 1365 # Standard error for vittelogenic adults.
16
+ − 1366 diapausing_adults.std_error = apply(Diapausing.replications, 1, sd) / sqrt(opt$replications);
27
+ − 1367 temperature_data_frame = append_vector(temperature_data_frame, diapausing_adults.std_error, "DIAPAUSINGADULTSE");
28
+ − 1368 } else if (life_stage_adult=="Total") {
+ − 1369 # Mean value for all adults.
+ − 1370 total_adults = apply((Previttelogenic.replications+Vittelogenic.replications+Diapausing.replications), 1, mean);
+ − 1371 temperature_data_frame = append_vector(temperature_data_frame, total_adults, "TOTALADULT");
+ − 1372 # Standard error for all adults.
+ − 1373 total_adults.std_error = apply((Previttelogenic.replications+Vittelogenic.replications+Diapausing.replications), 1, sd) / sqrt(opt$replications);
+ − 1374 temperature_data_frame = append_vector(temperature_data_frame, total_adults.std_error, "TOTALADULTSE");
16
+ − 1375 }
10
+ − 1376 }
+ − 1377 }
5
+ − 1378
10
+ − 1379 if (plot_generations_separately) {
56
+ − 1380 # Create copies of the temperature data for generations P, F1 and F2 if we're plotting generations separately.
+ − 1381 temperature_data_frame_P = data.frame(temperature_data_frame);
+ − 1382 temperature_data_frame_F1 = data.frame(temperature_data_frame);
+ − 1383 temperature_data_frame_F2 = data.frame(temperature_data_frame);
+ − 1384
20
+ − 1385 m_se = get_mean_and_std_error(P.replications, F1.replications, F2.replications);
+ − 1386 P = m_se[[1]];
+ − 1387 P.std_error = m_se[[2]];
+ − 1388 F1 = m_se[[3]];
+ − 1389 F1.std_error = m_se[[4]];
+ − 1390 F2 = m_se[[5]];
+ − 1391 F2.std_error = m_se[[6]];
10
+ − 1392 if (process_eggs) {
20
+ − 1393 m_se = get_mean_and_std_error(P_eggs.replications, F1_eggs.replications, F2_eggs.replications);
+ − 1394 P_eggs = m_se[[1]];
+ − 1395 P_eggs.std_error = m_se[[2]];
50
+ − 1396 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_eggs, "EGG.P");
+ − 1397 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_eggs.std_error, "EGG.P.SE");
20
+ − 1398 F1_eggs = m_se[[3]];
+ − 1399 F1_eggs.std_error = m_se[[4]];
50
+ − 1400 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_eggs, "EGG.F1");
+ − 1401 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_eggs.std_error, "EGG.F1.SE");
20
+ − 1402 F2_eggs = m_se[[5]];
+ − 1403 F2_eggs.std_error = m_se[[6]];
50
+ − 1404 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_eggs, "EGG.F2");
+ − 1405 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_eggs.std_error, "EGG.F2.SE");
20
+ − 1406 }
+ − 1407 if (process_young_nymphs) {
+ − 1408 m_se = get_mean_and_std_error(P_young_nymphs.replications, F1_young_nymphs.replications, F2_young_nymphs.replications);
+ − 1409 P_young_nymphs = m_se[[1]];
+ − 1410 P_young_nymphs.std_error = m_se[[2]];
50
+ − 1411 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_young_nymphs, "YOUNGNYMPH.P");
+ − 1412 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_young_nymphs.std_error, "YOUNGNYMPH.P.SE");
20
+ − 1413 F1_young_nymphs = m_se[[3]];
+ − 1414 F1_young_nymphs.std_error = m_se[[4]];
50
+ − 1415 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_young_nymphs, "YOUNGNYMPH.F1");
+ − 1416 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_young_nymphs.std_error, "YOUNGNYMPH.F1.SE");
20
+ − 1417 F2_young_nymphs = m_se[[5]];
+ − 1418 F2_young_nymphs.std_error = m_se[[6]];
50
+ − 1419 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_young_nymphs, "YOUNGNYMPH.F2");
+ − 1420 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_young_nymphs.std_error, "YOUNGNYMPH.F2.SE");
10
+ − 1421 }
20
+ − 1422 if (process_old_nymphs) {
+ − 1423 m_se = get_mean_and_std_error(P_old_nymphs.replications, F1_old_nymphs.replications, F2_old_nymphs.replications);
+ − 1424 P_old_nymphs = m_se[[1]];
+ − 1425 P_old_nymphs.std_error = m_se[[2]];
50
+ − 1426 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_old_nymphs, "OLDNYMPH.P");
+ − 1427 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_old_nymphs.std_error, "OLDNYMPH.P.SE");
20
+ − 1428 F1_old_nymphs = m_se[[3]];
+ − 1429 F1_old_nymphs.std_error = m_se[[4]];
50
+ − 1430 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_old_nymphs, "OLDNYMPH.F1");
+ − 1431 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_old_nymphs.std_error, "OLDNYMPH.F1.SE");
20
+ − 1432 F2_old_nymphs = m_se[[5]];
+ − 1433 F2_old_nymphs.std_error = m_se[[6]];
50
+ − 1434 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_old_nymphs, "OLDNYMPH.F2");
+ − 1435 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_old_nymphs.std_error, "OLDNYMPH.F2.SE");
20
+ − 1436 }
+ − 1437 if (process_total_nymphs) {
+ − 1438 m_se = get_mean_and_std_error(P_total_nymphs.replications, F1_total_nymphs.replications, F2_total_nymphs.replications);
+ − 1439 P_total_nymphs = m_se[[1]];
+ − 1440 P_total_nymphs.std_error = m_se[[2]];
50
+ − 1441 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_nymphs, "TOTALNYMPH.P");
+ − 1442 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_nymphs.std_error, "TOTALNYMPH.P.SE");
20
+ − 1443 F1_total_nymphs = m_se[[3]];
+ − 1444 F1_total_nymphs.std_error = m_se[[4]];
50
+ − 1445 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_nymphs, "TOTALNYMPH.F1");
+ − 1446 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_nymphs.std_error, "TOTALNYMPH.F1.SE");
20
+ − 1447 F2_total_nymphs = m_se[[5]];
+ − 1448 F2_total_nymphs.std_error = m_se[[6]];
50
+ − 1449 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_nymphs, "TOTALNYMPH.F2");
+ − 1450 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_nymphs.std_error, "TOTALNYMPH.F2.SE");
10
+ − 1451 }
23
+ − 1452 if (process_previttelogenic_adults) {
+ − 1453 m_se = get_mean_and_std_error(P_previttelogenic_adults.replications, F1_previttelogenic_adults.replications, F2_previttelogenic_adults.replications);
+ − 1454 P_previttelogenic_adults = m_se[[1]];
+ − 1455 P_previttelogenic_adults.std_error = m_se[[2]];
50
+ − 1456 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_previttelogenic_adults, "PRE.VITADULT.P");
+ − 1457 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_previttelogenic_adults.std_error, "PRE.VITADULT.P.SE");
23
+ − 1458 F1_previttelogenic_adults = m_se[[3]];
+ − 1459 F1_previttelogenic_adults.std_error = m_se[[4]];
50
+ − 1460 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_previttelogenic_adults, "PRE.VITADULT.F1");
+ − 1461 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_previttelogenic_adults.std_error, "PRE.VITADULT.F1.SE");
23
+ − 1462 F2_previttelogenic_adults = m_se[[5]];
+ − 1463 F2_previttelogenic_adults.std_error = m_se[[6]];
50
+ − 1464 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_previttelogenic_adults, "PRE.VITADULT.F2");
+ − 1465 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_previttelogenic_adults.std_error, "PRE.VITADULT.F2.SE");
23
+ − 1466 }
+ − 1467 if (process_vittelogenic_adults) {
+ − 1468 m_se = get_mean_and_std_error(P_vittelogenic_adults.replications, F1_vittelogenic_adults.replications, F2_vittelogenic_adults.replications);
+ − 1469 P_vittelogenic_adults = m_se[[1]];
+ − 1470 P_vittelogenic_adults.std_error = m_se[[2]];
50
+ − 1471 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_vittelogenic_adults, "VITADULT.P");
+ − 1472 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_vittelogenic_adults.std_error, "VITADULT.P.SE");
23
+ − 1473 F1_vittelogenic_adults = m_se[[3]];
+ − 1474 F1_vittelogenic_adults.std_error = m_se[[4]];
50
+ − 1475 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_vittelogenic_adults, "VITADULT.F1");
+ − 1476 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_vittelogenic_adults.std_error, "VITADULT.F1.SE");
23
+ − 1477 F2_vittelogenic_adults = m_se[[5]];
+ − 1478 F2_vittelogenic_adults.std_error = m_se[[6]];
50
+ − 1479 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_vittelogenic_adults, "VITADULT.F2");
+ − 1480 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_vittelogenic_adults.std_error, "VITADULT.F2.SE");
23
+ − 1481 }
+ − 1482 if (process_diapausing_adults) {
+ − 1483 m_se = get_mean_and_std_error(P_diapausing_adults.replications, F1_diapausing_adults.replications, F2_diapausing_adults.replications);
+ − 1484 P_diapausing_adults = m_se[[1]];
+ − 1485 P_diapausing_adults.std_error = m_se[[2]];
50
+ − 1486 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_diapausing_adults, "DIAPAUSINGADULT.P");
+ − 1487 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_diapausing_adults.std_error, "DIAPAUSINGADULT.P.SE");
23
+ − 1488 F1_diapausing_adults = m_se[[3]];
+ − 1489 F1_diapausing_adults.std_error = m_se[[4]];
50
+ − 1490 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_diapausing_adults, "DIAPAUSINGADULT.F1");
+ − 1491 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_diapausing_adults.std_error, "DIAPAUSINGADULT.F1.SE");
23
+ − 1492 F2_diapausing_adults = m_se[[5]];
+ − 1493 F2_diapausing_adults.std_error = m_se[[6]];
50
+ − 1494 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_diapausing_adults, "DIAPAUSINGADULT.F2");
+ − 1495 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_diapausing_adults.std_error, "DIAPAUSINGADULT.F2.SE");
23
+ − 1496 }
+ − 1497 if (process_total_adults) {
+ − 1498 m_se = get_mean_and_std_error(P_total_adults.replications, F1_total_adults.replications, F2_total_adults.replications);
+ − 1499 P_total_adults = m_se[[1]];
+ − 1500 P_total_adults.std_error = m_se[[2]];
50
+ − 1501 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_adults, "TOTALADULT.P");
+ − 1502 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_adults.std_error, "TOTALADULT.P.SE");
23
+ − 1503 F1_total_adults = m_se[[3]];
+ − 1504 F1_total_adults.std_error = m_se[[4]];
50
+ − 1505 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_adults, "TOTALADULT.F1");
+ − 1506 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_adults.std_error, "TOTALADULT.F1.SE");
23
+ − 1507 F2_total_adults = m_se[[5]];
+ − 1508 F2_total_adults.std_error = m_se[[6]];
50
+ − 1509 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_adults, "TOTALADULT.F2");
+ − 1510 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_adults.std_error, "TOTALADULT.F2.SE");
10
+ − 1511 }
51
+ − 1512 if (process_total) {
+ − 1513 temperature_data_frame_P = append_vector(temperature_data_frame_P, P, "ALL.TOTAL.P");
+ − 1514 temperature_data_frame_P = append_vector(temperature_data_frame_P, P.std_error, "ALL.TOTAL.P.SE");
+ − 1515 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1, "ALL.TOTAL.F1");
+ − 1516 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1.std_error, "ALL.TOTAL.F1.SE");
+ − 1517 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2, "ALL.TOTAL.F2");
+ − 1518 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2.std_error, "ALL.TOTAL.F2.SE");
+ − 1519 }
10
+ − 1520 }
6
+ − 1521
31
+ − 1522 # Save the analyzed data for combined generations.
34
+ − 1523 file_path = paste("output_data_dir", "04_combined_generations.csv", sep="/");
+ − 1524 write.csv(temperature_data_frame, file=file_path, row.names=F);
31
+ − 1525 if (plot_generations_separately) {
+ − 1526 # Save the analyzed data for generation P.
34
+ − 1527 file_path = paste("output_data_dir", "01_generation_P.csv", sep="/");
+ − 1528 write.csv(temperature_data_frame_P, file=file_path, row.names=F);
31
+ − 1529 # Save the analyzed data for generation F1.
34
+ − 1530 file_path = paste("output_data_dir", "02_generation_F1.csv", sep="/");
+ − 1531 write.csv(temperature_data_frame_F1, file=file_path, row.names=F);
31
+ − 1532 # Save the analyzed data for generation F2.
34
+ − 1533 file_path = paste("output_data_dir", "03_generation_F2.csv", sep="/");
+ − 1534 write.csv(temperature_data_frame_F2, file=file_path, row.names=F);
31
+ − 1535 }
5
+ − 1536
49
+ − 1537 total_days_vector = c(1:dim(temperature_data_frame)[1]);
10
+ − 1538 if (plot_generations_separately) {
15
+ − 1539 for (life_stage in life_stages) {
10
+ − 1540 if (life_stage == "Egg") {
+ − 1541 # Start PDF device driver.
+ − 1542 dev.new(width=20, height=30);
19
+ − 1543 file_path = get_file_path(life_stage, "egg_pop_by_generation.pdf")
10
+ − 1544 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1545 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
+ − 1546 # Egg population size by generation.
18
+ − 1547 maxval = max(P_eggs+F1_eggs+F2_eggs) + 100;
45
+ − 1548 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1549 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=P_eggs, group_std_error=P_eggs.std_error,
+ − 1550 group2=F1_eggs, group2_std_error=F1_eggs.std_error, group3=F2_eggs, group3_std_error=F2_eggs.std_error);
10
+ − 1551 # Turn off device driver to flush output.
+ − 1552 dev.off();
+ − 1553 } else if (life_stage == "Nymph") {
16
+ − 1554 for (life_stage_nymph in life_stages_nymph) {
+ − 1555 # Start PDF device driver.
+ − 1556 dev.new(width=20, height=30);
50
+ − 1557 file_path = get_file_path(life_stage, "nymph_pop_by_generation.pdf", sub_life_stage=life_stage_nymph)
16
+ − 1558 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1559 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
20
+ − 1560 if (life_stage_nymph=="Young") {
+ − 1561 # Young nymph population size by generation.
+ − 1562 maxval = max(P_young_nymphs+F1_young_nymphs+F2_young_nymphs) + 100;
+ − 1563 group = P_young_nymphs;
+ − 1564 group_std_error = P_young_nymphs.std_error;
+ − 1565 group2 = F1_young_nymphs;
+ − 1566 group2_std_error = F1_young_nymphs.std_error;
+ − 1567 group3 = F2_young_nymphs;
+ − 1568 group3_std_error = F2_young_nymphs.std_error;
+ − 1569 } else if (life_stage_nymph=="Old") {
+ − 1570 # Total nymph population size by generation.
+ − 1571 maxval = max(P_old_nymphs+F1_old_nymphs+F2_old_nymphs) + 100;
+ − 1572 group = P_old_nymphs;
+ − 1573 group_std_error = P_old_nymphs.std_error;
+ − 1574 group2 = F1_old_nymphs;
+ − 1575 group2_std_error = F1_old_nymphs.std_error;
+ − 1576 group3 = F2_old_nymphs;
+ − 1577 group3_std_error = F2_old_nymphs.std_error;
+ − 1578 } else if (life_stage_nymph=="Total") {
+ − 1579 # Total nymph population size by generation.
+ − 1580 maxval = max(P_total_nymphs+F1_total_nymphs+F2_total_nymphs) + 100;
+ − 1581 group = P_total_nymphs;
+ − 1582 group_std_error = P_total_nymphs.std_error;
+ − 1583 group2 = F1_total_nymphs;
+ − 1584 group2_std_error = F1_total_nymphs.std_error;
+ − 1585 group3 = F2_total_nymphs;
+ − 1586 group3_std_error = F2_total_nymphs.std_error;
+ − 1587 }
45
+ − 1588 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1589 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
50
+ − 1590 group2=group2, group2_std_error=group2_std_error, group3=group3, group3_std_error=group3_std_error, sub_life_stage=life_stage_nymph);
16
+ − 1591 # Turn off device driver to flush output.
+ − 1592 dev.off();
+ − 1593 }
10
+ − 1594 } else if (life_stage == "Adult") {
16
+ − 1595 for (life_stage_adult in life_stages_adult) {
+ − 1596 # Start PDF device driver.
+ − 1597 dev.new(width=20, height=30);
50
+ − 1598 file_path = get_file_path(life_stage, "adult_pop_by_generation.pdf", sub_life_stage=life_stage_adult)
16
+ − 1599 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1600 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
23
+ − 1601 if (life_stage_adult=="Pre-vittelogenic") {
+ − 1602 # Pre-vittelogenic adult population size by generation.
+ − 1603 maxval = max(P_previttelogenic_adults+F1_previttelogenic_adults+F2_previttelogenic_adults) + 100;
+ − 1604 group = P_previttelogenic_adults;
+ − 1605 group_std_error = P_previttelogenic_adults.std_error;
+ − 1606 group2 = F1_previttelogenic_adults;
+ − 1607 group2_std_error = F1_previttelogenic_adults.std_error;
+ − 1608 group3 = F2_previttelogenic_adults;
+ − 1609 group3_std_error = F2_previttelogenic_adults.std_error;
+ − 1610 } else if (life_stage_adult=="Vittelogenic") {
+ − 1611 # Vittelogenic adult population size by generation.
+ − 1612 maxval = max(P_vittelogenic_adults+F1_vittelogenic_adults+F2_vittelogenic_adults) + 100;
+ − 1613 group = P_vittelogenic_adults;
+ − 1614 group_std_error = P_vittelogenic_adults.std_error;
+ − 1615 group2 = F1_vittelogenic_adults;
+ − 1616 group2_std_error = F1_vittelogenic_adults.std_error;
+ − 1617 group3 = F2_vittelogenic_adults;
+ − 1618 group3_std_error = F2_vittelogenic_adults.std_error;
+ − 1619 } else if (life_stage_adult=="Diapausing") {
+ − 1620 # Diapausing adult population size by generation.
+ − 1621 maxval = max(P_diapausing_adults+F1_diapausing_adults+F2_diapausing_adults) + 100;
+ − 1622 group = P_diapausing_adults;
+ − 1623 group_std_error = P_diapausing_adults.std_error;
+ − 1624 group2 = F1_diapausing_adults;
+ − 1625 group2_std_error = F1_diapausing_adults.std_error;
+ − 1626 group3 = F2_diapausing_adults;
+ − 1627 group3_std_error = F2_diapausing_adults.std_error;
+ − 1628 } else if (life_stage_adult=="Total") {
+ − 1629 # Total adult population size by generation.
+ − 1630 maxval = max(P_total_adults+F1_total_adults+F2_total_adults) + 100;
+ − 1631 group = P_total_adults;
+ − 1632 group_std_error = P_total_adults.std_error;
+ − 1633 group2 = F1_total_adults;
+ − 1634 group2_std_error = F1_total_adults.std_error;
+ − 1635 group3 = F2_total_adults;
+ − 1636 group3_std_error = F2_total_adults.std_error;
+ − 1637 }
45
+ − 1638 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1639 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
50
+ − 1640 group2=group2, group2_std_error=group2_std_error, group3=group3, group3_std_error=group3_std_error, sub_life_stage=life_stage_adult);
16
+ − 1641 # Turn off device driver to flush output.
+ − 1642 dev.off();
+ − 1643 }
10
+ − 1644 } else if (life_stage == "Total") {
+ − 1645 # Start PDF device driver.
18
+ − 1646 # Name collection elements so that they
+ − 1647 # are displayed in logical order.
10
+ − 1648 dev.new(width=20, height=30);
19
+ − 1649 file_path = get_file_path(life_stage, "total_pop_by_generation.pdf")
10
+ − 1650 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1651 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
+ − 1652 # Total population size by generation.
18
+ − 1653 maxval = max(P+F1+F2) + 100;
45
+ − 1654 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1655 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=P, group_std_error=P.std_error,
+ − 1656 group2=F1, group2_std_error=F1.std_error, group3=F2, group3_std_error=F2.std_error);
10
+ − 1657 # Turn off device driver to flush output.
+ − 1658 dev.off();
+ − 1659 }
15
+ − 1660 }
10
+ − 1661 } else {
+ − 1662 for (life_stage in life_stages) {
+ − 1663 if (life_stage == "Egg") {
+ − 1664 # Start PDF device driver.
+ − 1665 dev.new(width=20, height=30);
19
+ − 1666 file_path = get_file_path(life_stage, "egg_pop.pdf")
10
+ − 1667 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1668 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
+ − 1669 # Egg population size.
18
+ − 1670 maxval = max(eggs+eggs.std_error) + 100;
45
+ − 1671 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1672 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=eggs, group_std_error=eggs.std_error);
10
+ − 1673 # Turn off device driver to flush output.
+ − 1674 dev.off();
+ − 1675 } else if (life_stage == "Nymph") {
16
+ − 1676 for (life_stage_nymph in life_stages_nymph) {
+ − 1677 # Start PDF device driver.
+ − 1678 dev.new(width=20, height=30);
50
+ − 1679 file_path = get_file_path(life_stage, "nymph_pop.pdf", sub_life_stage=life_stage_nymph)
16
+ − 1680 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1681 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
+ − 1682 if (life_stage_nymph=="Total") {
+ − 1683 # Total nymph population size.
+ − 1684 group = total_nymphs;
+ − 1685 group_std_error = total_nymphs.std_error;
+ − 1686 } else if (life_stage_nymph=="Young") {
+ − 1687 # Young nymph population size.
+ − 1688 group = young_nymphs;
+ − 1689 group_std_error = young_nymphs.std_error;
+ − 1690 } else if (life_stage_nymph=="Old") {
+ − 1691 # Old nymph population size.
+ − 1692 group = old_nymphs;
+ − 1693 group_std_error = old_nymphs.std_error;
+ − 1694 }
18
+ − 1695 maxval = max(group+group_std_error) + 100;
45
+ − 1696 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1697 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
50
+ − 1698 sub_life_stage=life_stage_nymph);
16
+ − 1699 # Turn off device driver to flush output.
+ − 1700 dev.off();
+ − 1701 }
10
+ − 1702 } else if (life_stage == "Adult") {
16
+ − 1703 for (life_stage_adult in life_stages_adult) {
+ − 1704 # Start PDF device driver.
+ − 1705 dev.new(width=20, height=30);
50
+ − 1706 file_path = get_file_path(life_stage, "adult_pop.pdf", sub_life_stage=life_stage_adult)
16
+ − 1707 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1708 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
+ − 1709 if (life_stage_adult=="Total") {
+ − 1710 # Total adult population size.
+ − 1711 group = total_adults;
+ − 1712 group_std_error = total_adults.std_error
+ − 1713 } else if (life_stage_adult=="Pre-vittelogenic") {
+ − 1714 # Pre-vittelogenic adult population size.
+ − 1715 group = previttelogenic_adults;
+ − 1716 group_std_error = previttelogenic_adults.std_error
+ − 1717 } else if (life_stage_adult=="Vittelogenic") {
+ − 1718 # Vittelogenic adult population size.
+ − 1719 group = vittelogenic_adults;
+ − 1720 group_std_error = vittelogenic_adults.std_error
+ − 1721 } else if (life_stage_adult=="Diapausing") {
+ − 1722 # Diapausing adult population size.
+ − 1723 group = diapausing_adults;
+ − 1724 group_std_error = diapausing_adults.std_error
+ − 1725 }
18
+ − 1726 maxval = max(group+group_std_error) + 100;
45
+ − 1727 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1728 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
50
+ − 1729 sub_life_stage=life_stage_adult);
16
+ − 1730 # Turn off device driver to flush output.
+ − 1731 dev.off();
+ − 1732 }
10
+ − 1733 } else if (life_stage == "Total") {
+ − 1734 # Start PDF device driver.
+ − 1735 dev.new(width=20, height=30);
19
+ − 1736 file_path = get_file_path(life_stage, "total_pop.pdf")
10
+ − 1737 pdf(file=file_path, width=20, height=30, bg="white");
+ − 1738 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
+ − 1739 # Total population size.
18
+ − 1740 maxval = max(eggs+eggs.std_error, total_nymphs+total_nymphs.std_error, total_adults+total_adults.std_error) + 100;
45
+ − 1741 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
38
+ − 1742 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=total_adults, group_std_error=total_adults.std_error,
+ − 1743 group2=total_nymphs, group2_std_error=total_nymphs.std_error, group3=eggs, group3_std_error=eggs.std_error);
10
+ − 1744 # Turn off device driver to flush output.
+ − 1745 dev.off();
+ − 1746 }
+ − 1747 }
+ − 1748 }
